Annual Meeting Announcement, 1113

2024 Annual Meeting
Seismological Society of America
Technical Sessions
29 April–3 May • Anchorage, Alaska
The SSA 2024 Annual Meeting will convene at the Dena’ina
Civic and Convention Center and feature more than 1069
technical oral and poster presentations as well as plenary sessions, workshops, special interest groups and field trips.
The following schedule of events and abstracts are valid
until 23 February, 2024 and subject to change.

Where We are Gathered
The Seismological Society of America and the conference
organizers welcome you to the 2024 Annual Meeting in
Anchorage, Alaska.
We are gathered in a place that is defined by the environment surrounding us—the Chugach Mountains to the eastand Cook Inlet to the west. This resource-rich area has sustained the Dena’ina Athabascan people for the past millennia.
Across Alaska, colonization from Russia and then America
devastated Alaska Native populations through disease, lossof land and forced integration. Today, the work of reconciling this complex past includes components that are economic,
environmental, legal and cultural.
The Dena’ina Center itself is a small but meaningful
effort in cultural representation. The meeting rooms carry
Athabascan names for essential land and ocean features in thisregion—features that should resonate with all Earth scientists.
And the art that fills the center provides both traditional andmodern perspectives on Alaska’s indigenous cultures. Other
excellent learning resources include the Alaska Native Heritage
Center (a 20-minute drive) and the Anchorage Museum (aten-minute walk).
A sense of place runs deep in all of Alaska. We encourage
you to use this meeting to learn and appreciate its land andpeople.

Annual Meeting Co-Chairs
The Society is grateful to SSA 2024 Co-Chairs Carl Tape andMichael West of University of Alaska Fairbanks for leading thecreation of this dynamic week of science.
Contact
info@seismosoc.org
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Technical Program
Plenary Sessions
Keynote Address: Learning from Earthquakes—
Observations from the Field and the Design
Office Following the 2023 Türkiye-Syria
Earthquake Sequence
Tuesday, 30 April, 6-7 pm
Ayşe Hortaçsu, Applied Technology Council
With an official death toll of 60,000, an estimated economic loss of over $100 billion, and the immediate loss of
housing for 3 million residents, the 6 February earthquakes
directly affected the lives of millions of people in Eastern
Türkiye and Northern Syria. Following such a major event,while mourning the lives lost and supporting first responders, it is critical for engineers and scientists to conduct focused
efforts to learn from the disaster, as no analytical model or test
facility can replicate a real earthquake and its effects on built
infrastructure. The Earthquake Engineering Research Institute(EERI) established the Learning From Earthquakes (LFE) program in 1973 with a mission to accelerate and increase learning from earthquake-induced disasters that affect the natural,
built, social and political environments worldwide. Hortaçsu
was deployed to Türkiye one week following the earthquakes
as part of the EERI LFE team, and she will summarize her
field observations and findings reported by additional teams
reported over the past year. The presentation will also include
a summary of rebuilding efforts and ongoing initiatives toward
improving the way earthquake science and engineering aretaught and implemented in Türkiye, and potential implications for the U.S. practice.
Challenges in Geohazards Research in Alaska
Wednesday, 1 May, 6-7 pm
Elena Suleimani, University of Alaska Fairbanks/Alaska
Earthquake Center; Rob Witter, U.S. Geological Survey;
Jessica Larsen, University of Alaska Fairbanks; Dennis Staley,
U.S. Geological Survey
The Pacific-North American plate boundary in Alaska
produces a range of geohazards resulting from earthquakes,
volcanoes, landslides and tsunamis. The regional scale of geohazards in Alaska, their cascading effects and remoteness ofSeismological Research Letters

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the fieldwork, which is required to investigate them, present
many challenges. A panel will share perspectives on thesechallenges and discuss new frontiers and opportunities tocharacterize, monitor, detect and prepare for the myriad geohazards in Alaska.

Annual Business and Awards Luncheon
Thursday, 2 May, Noon-2 pm
SSA President Heather DeShon (2024–25) will preside over
the awards ceremony and provide an update on the Society.
SSA President Ruth Harris (2023–24) will deliver her presidential address.
The 2024 honorees:• Norman A. Abrahamson, Harry Fielding Reid Medal• Doyeon Kim, Charles F. Richter Early-Career Award• Harley M. Benz, Frank Press Public Service Award• Douglas Scott Dreger, Distinguished Service to SSA
Award
Joyner Lecture: Why Seismic Hazard ModelingHas Become a Risky Business
Thursday, 2 May, 6-7 pm
Helen Crowley, Global Earthquake Model (GEM) Foundation
Crowley’s Joyner Lecture will look at the role that probabilistic seismic hazard models have historically played indefining actions for seismic design, will review the criticismsthat have been placed on these models—especially, but not
only, after damaging earthquakes—and will present numerous
examples that underline the need for risk assessment to be an
integral part of this process going forward.

Special Interest Groups
SSA 2024 offers five special interest group meetings (SIGs).
• The Cascadia Region Earthquake Science Center(CRESCENT)• Center of Earth Geohazards• On the Quantification and Treatment of Site Response
Modeling Errors• SZ4D: Status, Progress, Upcoming Activities• What’s Working in Earthquake Public Education? A SIG
to Exchange Ideas for Interactive Learning

Workshops
SSA offers workshops for members to help advance their skills.

Data Mining on the Cloud 101
Tuesday 30 April, 10 am–4 pm
Instructors: Marine Denolle, Yiyu Ni, Qibin Shi, Akash Kharita,
Zoe Krauss and Kuan-Fu Feng of University of Washington;
and Kaiwen Wang, Theresa Sawi, and Felix Waldhauser ofLamont-Doherty Earth Observatory, Columbia University
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This workshop will introduce participants to cloud computing, from concept and best practices to practice, for two
main approaches of data mining in seismology: correlation
seismology and machine learning.

Seismic Instrumentation
Tuesday 30 April, 10 am–4 pm
Instructors: Horst Rademacher, Berkeley Seismology Lab(retired); Kasey Aderhold, EarthScope Consortium; Marianne
Karplus, University of Texas, El Paso; John Merchant, Sandia
Laboratories, Albuquerque; Adam Ringler, AlbuquerqueSeismology Lab, U.S. Geological Survey
This workshop will discuss seismic instrumentation by
explaining different scales and periods of Earth’s vibrations
and the large selection of instrumentation necessary to cover
all aspects of Earth’s vibrations. Explore the history of thedevelopment of inertial seismometers and what is typicallyused today. Learn how different kinds of inertial seismometers
work and watch a detailed demonstration of a commercial
broadband seismometer.
Publishing: How to Review and How to Be
Reviewed
Tuesday 30 April, 12:30 pm–4:30 pm
Instructors: Allison Bent, editor-in-chief of SeismologicalResearch Letters (SRL); John Ebel, Boston College and founding editor-in-chief of SRL; Brent Grocholski, editor at Science
Publishing is a key aspect of any academic career.
Participants will learn how to review a scientific paper andhow to respond effectively to reviews of your own work fromthree experienced editors. Discussion will also focus on promoting peer-reviewed research to the broader community.
This interactive session will combine group discussion withlectures.

Field Seminars
Prince William Sound Field Seminar
Monday, 29 April, 7 am–6:30 pm
Trip Leaders: Peter Haeussler and Lauren Schaefer of the
U.S. Geological Survey; and Summer Ohlendorf, National
Oceanic and Atmospheric Administration; Carolyn Parcheta,
University of Alaska Fairbanks
This 5.5-hour field seminar cruise on the waters of Prince
William Sound departs from Whittier and will include presentations from experts in tectonics, geology, cryo-seismology,
tsunamis, landslides and current instrumentation and research
efforts in the region. Participants will receive a field guide of
the seminar’s highlights, including historic earthquakes likethe 1964 Great Alaska Earthquake, glacier seismology andlocal and regional seismic and infrasound networks.

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Alaska Geophysics in the Field
Tuesday 30 April, 8 am–4:30 pm
Trip Leaders: Julie Elliott, Michigan State; Natalia Ruppert,
AEC; James Gridley, National Tsunami Warning Center
Where do seismic and GPS data come from? During visits
to an active continuous GPS station in Palmer, adjacent to the
National Tsunami Warning Center, and an active multi-instrument seismic station in Glacier View, experts will explain the
key components of each station, as well as the instruments andcomponents that are unique to Alaska. Participants will learn
what it takes to get ground deformation and ground motion
from the field to their computers.

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SSA Meetings Code of Conduct
SSA is committed to fostering the exchange of scientific ideas
by providing a safe, productive and welcoming environment
for all SSA-sponsored meeting participants, including attendees, staff, volunteers and vendors. All participants at SSA meetings are expected to be considerate and collaborative, communicating openly with respect for others and critiquing ideas
rather than individuals. Behavior that is acceptable to one person may not be acceptable to another, so use discretion to be
sure that respect is communicated. For a detailed descriptionof the ethics and code of conduct policies, please visit the SSA
website: seismosoc.org/meetings/code-of-conduct.

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Technical Sessions, 1116

Technical Sessions
The 2023 USGS National Seismic Hazard
Model and Beyond
The USGS National Seismic Hazard Models (NSHMs) are a
bridge between best-available earthquake science and public
policy. The National Seismic Hazard Model Project (NSHMP)
recently published a 50-state update that provided updates tothe conterminous U.S., Alaska and Hawaii NSHMs. The USGS
plans to update the Puerto Rico and U.S. Virgin Islands (PRVI)NSHM by the end of 2025 and the Guam and Northern
Mariana Islands and American Samoa and Neighboring South
Pacific Islands NSHMs by the end of 2026. For this session wewill present the 2023 NSHMs for Alaska and the conterminous U.S. and progress on the update of the 2025 PRVI NSHM
and invite contributions on topics that will influence future
seismic hazard models, with an emphasis on Alaska. Topics
include, but are not limited to: seismicity catalogs, declustering and smoothed seismicity models, geologic and geodetic
deformation models, multi-fault ruptures, improved representation and quantification of epistemic uncertainty, newground motion models (GMMs) including non-ergodic models, incorporation of physics-based (3D simulation) GMMs,
basin effects, site response, directivity and time dependence.
We also invite contributions on the use of NSHMs for scenario
development, risk assessment for both buildings and infrastructure and other applications of risk mitigation including
those within the insurance industry. We are also interested incontributions that highlight potential impacts of hazard modeling uncertainties on downstream applications.
Conveners: Jason M. Altekruse, U.S. Geological Survey(jaltekruse@usgs.gov); Julie A. Herrick, U.S. Geological Survey(jherrick@usgs.gov); Mark D. Petersen, U.S. Geological Survey(mpetersen@usgs.gov); Peter M. Powers, U.S. Geological
Survey (pmpowers@usgs.gov); Emel Seyhan, Moody’s
RMS (Emel.Seyhan@rms.com); Allison M. Shumway, U.S.
Geological Survey (ashumway@usgs.gov)

The 2024 Magnitude 7.5 Earthquake
and the Associated Earthquake Swarm
Beneath the Noto Peninsula, Central
Japan
On New Year’s Day 2024, a Mw 7.5 (Japanese Metrological
Agency-JMA magnitude MJMA 7.6) occurred beneath theNoto Peninsula in Central Japan. The mainshock ruptured
along a NE-SW trending thrust fault bilaterally for about 150
km. It was preceded by magnitude 5.5 and 4.6 foreshocks
about four and two minutes before, and was followed by 238
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M3.5 and larger aftershocks by 6 January 2024. Shaking fromthe mainshock reached the highest JMA intensity of 7 and produced significant damage and casualties in the Noto Peninsulaand surrounding regions. A unique feature of this sequence isthat it was preceded by an intense earthquake swarm, whichstarted beneath the Noto Peninsula in November 2020 close to
the epicenter of the M7.5 mainshock. The swarm was accompanied by up to 7 cm of uplift over the first two years. The largest event in the swarm sequence prior to the M7.5 mainshock
was a M6.2 earthquake on 5 May 2023. Recent studies haveshown that the swarm activity migrated from larger depths
to shallower depths through a complex fault network, likely
driven by upward movement of crustal fluids.
In this late-breaking session, we invite contributions fromall disciplines that are relevant to this sequence. These include,
but are not limited to: seismological and geodetic studies
on the M7.5 mainshock rupture properties, the relationshipbetween the mainshock and the ongoing earthquake swarm,
subsurface imaging in the source region beneath the Noto
Peninsula, potential remote triggering in Japan and elsewherearound the world, temporal changes in site response and subsurface medium properties tsunami generation, earthquake
and tsunami early warning, and potential impact to the building structures. We also welcome submissions on disaster-mitigation strategies based on this earthquake, as well as otherinterdisciplinary contributions.
Conveners: Dara Goldberg, U.S. Geological Survey(degoldberg@usgs.gov); Sarah Minson, U.S. Geological Survey(sminson@usgs.gov); Takuya Nishimura, Kyoto University(nishimura.takuya.4s@kyoto-u.ac.jp); Zhigang Peng, Georgia
Institute of Technology (zpeng@gatech.edu); Dun Wang,
Chinese University of Geosciences (wangdun@cug.edu.cn);
Suguru Yabe, Geological Survey of Japan (s.yabe@aist.go.jp)

3D Wavefield Simulations: From
Seismic Imaging to Ground Motion
Modeling
Advances in numerical methods and continued evolution ofcomputer hardware and high-performance computing infrastructures have made it routine to simulate full 3D seismic wave
propagation at local, regional and global scales. This capability and the growing efficiency in accomplishing it result in a
broad range of applications, from ground motion simulationand scenario earthquakes incorporating 3D models, physicsbased fault rupture dynamics simulations, to simulation-based
seismic imaging methods such as full-waveform inversion. By
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applications have considerably expanded our understandingof seismic hazard, earthquake physics and regional and global
tectonics. This session invites any seismic contributions thatleverage the capabilities of full-wave simulations, including
applications related to earthquake ground motion modeling,
kinematic and dynamic rupture simulations, ambient noiseand seismic imaging at all scales as well as other novel applications.
Conveners: Ebru Bozdag, Colorado School of Mines(bozdag@mines.edu); Bryant Chow, University of Alaska
Fairbanks (bhchow@alaska.edu); Andreas Fichtner, ETH
Zürich (andreas.fichtner@erdw.ethz.ch); Qinya Liu, Universityof Toronto (liuqy@physics.utoronto.ca); Erin W. Moriarty,
U.S. Geological Survey (emoriarty@usgs.gov); Artie Rodgers,
Lawrence Livermore National Laboratory, (rodgers7@llnl.
gov)

Advancements in Forensic Seismology
and Explosion Monitoring
Geophysical techniques are vital to enhance the detection andcharacterization of anthropogenic activity. This session calls
for abstracts showcasing the latest in geophysical forensic
analysis used in global security and monitoring. Topics may
encompass observation, modeling and characterization ofground-coupled events such as explosions, mining, collapse
and bolides. We also seek to highlight the advancements insource, propagation and signal analysis relating to controlled
source experiments. We encourage submissions that integrate
multi-modal observations and innovative instrumentationsuch as distributed acoustic sensing, remote sensing, infrasound and large-N arrays. The aim of this session is to encourage collaboration and discussion among institutional experts
to drive innovations in forensic seismology and explosion
monitoring.
Conveners: Richard A. Alfaro-Diaz, Los Alamos National
Laboratory (rad@lanl.gov); Louisa Barama, Lawrence
Livermore National Laboratory (barama1@llnl.gov); Jorge A.
Garcia, Sandia National Laboratories (jgarc26@sandia.gov);
Carl Tape, University of Alaska Fairbanks (ctape@alaska.
edu); Cleat Zeiler, Nevada National Security Site, (ZeilerCP@
nv.doe.gov)

Advances in Operational and Research
Analysis of Earthquake Swarms
Earthquake swarms are clusters of earthquakes that are localized in space and time but without a distinctive mainshockor characteristic temporal decay of aftershock event rates.
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tions. Spatiotemporal variations in earthquake rates during
swarms tend to depart from traditional mainshock-aftershock
sequences resulting in unpredictable swarm durations andspatial extents.
The purpose of this session is to provide a broad overview
of work related to earthquake swarms. Potential topics include
but are not limited to: operational practices for capturing andforecasting swarms, methods for swarm analysis, geologic
and tectonic interpretations and hazard analysis of swarms.
Submission of studies at various time and geographic scales
and those using both traditional and novel analysis methods
are encouraged. This session aims to foster collaboration andthe sharing of techniques and data sets to advance the community’s capabilities to study and understand these phenomena.
Conveners: Kyren R. Bogolub, Nevada Seismological
Laboratory, University of Nevada, Reno (kbogolub@unr.edu);
Jeffery L. Fox, Ohio Geological Survey (jeffrey.fox@dnr.ohio.
gov); Andrea L. Llenos, U.S. Geological Survey (allenos@usgs.
gov); William H. Savran, Nevada Seismological Laboratory,
University of Nevada, Reno (wsavran@unr.edu); Daniel T.
Trugman, Nevada Seismological Laboratory, University of
Nevada, Reno (dtrugman@unr.edu); Elizabeth A. Vanacore,
University of Puerto Rico Mayagüez, Puerto Rico Seismic
Network (elizabeth.vanacore@upr.edu)

Advancing Seismology withDistributed Fiber Optic Sensing
Distributed fiber optic sensing (DFOS) has emerged as atransformative technology in seismology, offering unparalleled sensing density and cost-effectiveness compared to classical seismic acquisitions, especially in challenging-to-accessareas. DFOS enables a wide range of seismic studies, including
earthquake detection and location, source focal mechanismand fault rupture process inversions, geo-hazard early warning, microseismic monitoring, subsurface imaging, near-surface and reservoir characterization, urban and environmental monitoring and nondestructive testing. The unused landand subsea telecommunication fiber optic cables, commonly
known as ‘dark fibers,’ have progressively contributed to significant new findings in the Earth sciences.
Moreover, novel sensing techniques and improved instruments are extending the range, enhancing sensitivity anddiminishing the noise floor of DFOS, enabling the observationof physical phenomena with an unprecedented resolution.
DFOS also makes it possible to integrate multi-physics measurements, such as strain/strain rate (e.g., distributed acoustic
sensing or DAS), temperature, electric and magnetic fields, in
combination with other point-based sensors, to better constrain subsurface structures and processes and quantify their
spatial and temporal variations. Both traditional and novel
big-data technologies, including high-performance computing, cloud storage and computing, as well as machine learning,
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are now successfully employed to effectively manage, process
and exploit the vast amounts of data collected by DFOS.
This session aims to explore the latest developments in
DFOS technologies, applications and challenges in the integration of DFOS into seismological research. We welcome
experts, researchers and practitioners from various disciplines
to share, network and exchange innovative ideas to leverage
DFOS and advance its applications in seismology and Earthsciences.
Conveners: Ettore Biondi, California Institute ofTechnology (ebiondi@caltech.edu); Daniel Bowden, ETH
Zürich (daniel.bowden@erdw.ethz.ch); Derrick Chambers,
Colorado School of Mines (derrickchambers@mines.edu);
Julia Correa, Lawrence Berkeley National Laboratory (juliacorrea@lbl.gov); Manuel Mendoza, University of Colorado,
Boulder(Manuel.Mendoza@colorado.edu);
Krystyna
Smolinski, ETH Zürich (krystyna.smolinski@erdw.ethz.
ch); Veronica Rodriguez Tribaldos, GFZ Potsdam (verort@
gfz-potsdam.de); Shihao Yuan, Colorado School of Mines(syuan@mines.edu)

Mapping the distribution of seismic anisotropy (radial andazimuthal) provides fascinating insights into dynamic processes of Earth (for example, lithospheric deformation, asthenospheric flow pattern, plate boundary dynamics, core-mantle
boundary processes and ice dynamics). However, given thecomplexity of possible anisotropic structures and symmetries, and the different strengths and weaknesses of various
measurement techniques, resolving anisotropy in the Earthremains challenging. The growing volume of seismic data andnovel analysis methods allow us to characterize anisotropic
properties on different scales and attempt to reconcile seismic
observables with experimental results and geodynamic models. The aim of this session is to bring together scientists working on different aspects of seismic anisotropy to provide stateof-the-art insights from both an observational and a modelingpoint of view.
Conveners: Frederik Link, Yale University (frederik.link@
yale.edu); Eric Loeberich, Yale University (eric.loeberich@yale.edu); Walid B. Mansour, Washington University in St.
Louis (walid@wustl.edu)

rapid expansion of data collected by broadband seismometers,
nodal instruments, and distributed acoustic sensing (DAS) has
led to the emergence of a unique interdisciplinary field at theintersection of glaciology and seismology. Observations fromseismic and microseismic signals offer valuable constraints fordeducing structures and processes within Earth’s cryosphere.
As a result, our understanding of the complex interconnections within Earth systems and climate dynamics is further
enriched. Seismic techniques used in recent studies have provided in-situ quantitative insights to illuminate the dynamics
of various cryospheric systems and environments including
glacial flow, retreat, iceberg calving, ice shelves, basal and episodic slip, hydrology and sea ice migration. Active and passive seismic methods allow for analysis and imaging of Earth’s
structure in polar and mountainous regions, including glaciers, ice sheets, sea ice and permafrost. Furthermore, seismic
methods prove useful for monitoring Earth’s cryosphere andrelated phenomena, in a changing world. This session aims toassemble diverse experts to present the latest cryoseismology
research and foster collaborations in this emergent field. We
welcome a wide range of contributions, encompassing studies that focus on monitoring and analyzing seismicity of tectonic or cryogenic origin, natural hazards, and near-surface
processes and structures. We also encourage investigations
into tectonic-scale structures and dynamics. Furthermore, we
invite submissions that explore the advancement of innovative
seismic methods, aiming to enhance monitoring and understanding of Earth’s cryosphere. In addition to showcasing
excellent science, this inaugural cryoseismology session will
help advance SSA’s mission of fostering scientific connections
and collaborations within an inherently interdisciplinary field.
Conveners: Rick Aster, Colorado State University (rick.
aster@colostate.edu); John Cassidy, Natural Resources
Canada, Geological Survey of Canada (john.cassidy@nrcanrncan.gc.ca); Jan Dettmer, University of Calgary (jan.dettmer@ucalgary.ca); Jeremy M. Gosselin, University of Calgary(jeremy.gosselin@ucalgary.ca); Celeste Labedz, University ofCalgary (celeste.labedz@ucalgary.ca); John-Morgan Manos,
University of Washington (jmanos@uw.edu); Elisa McGhee,
Colorado State University (elisa.mcghee@colostate.edu);
Stephanie Olinger, Harvard University, (stepholinger@fas.
harvard.edu); Rachel Willis, Colorado School of Mines, (rwillis1@mines.edu)

Applications and Discoveries in
Cryoseismology Across Spatial andTemporal Scales

Assessing Seismic Hazard for Critical
Facilities and Infrastructure—Insights
and Challenges

Polar and mountainous regions are evolving rapidly inresponse to climate change, carrying significant implications
for Earth’s cryosphere. These changes impact natural hazards, alter the availability of natural resources, and influence
global trade dynamics and additional economic factors. The

Critical facilities such as nuclear plants, industrial facilities,
dams, tailings dams and waste disposal sites need to remain
safe under potential shaking even from large, rare seismic
events. Similarly, seismic shaking presents hazards to distributed systems serving power, water, transportation and waste

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disposal. Hazards are usually assessed through specialized
frameworks including PSHA and PFDHA. Challenges in seismic hazard assessment for major structures provide a springboard for research and innovation in the engineering andseismological communities, and lead to cutting-edge solutions
and advances. Large national and international projects aimed
at critical sites often shape the state-of-the-art, but notable
contributions have also come from smaller teams from academia, government and civilian practice. New approaches andinnovations are bringing advances in topics such as source,site and ground motion characterization, quantification andrefinement of uncertainties.
In this session, we would like to bring together the seismological and engineering communities to discuss advancesin any aspect of seismology and engineering seismology where
innovation has been driven by the needs of seismic safety andhazard assessment for critical facilities or infrastructure. We
welcome contributions from academia and practice, regulating
and operating parties, research-led consulting firms, energy
and other sectors. We look forward to discussing challenges,
insights and best practices from past and current endeavors,
with a view to new directions in data, models and methods
and potential applications.
Conveners: Céline Beauval, ISTerre, Université Grenoble
Alpes(celine.beauval@univ-grenoble-alpes.fr);
Glenn
Biasi, U.S. Geological Survey (gbiasi@usgs.gov); Olga-Joan
Ktenidou, National Observatory of Athen (olga.ktenidou@
noa.gr); Andreas Skarlatoudis, AECOM (andreas.skarlatoudis@aecom.com)

Characteristics and Mechanics of Fault
Zone Rupture Processes, from Micro to
Macro Scales
Fault zones are governed by diverse mechanical processes that
hold the key to advancing our understanding of fault rupture
behaviors and the related seismic hazards. This session seeks
to delve into the interplay of intrinsic fault zone properties,stress regimes and kinematics patterns that dictate rupture
mechanics of earthquakes and slow-slip events. Through thelens of advanced multi-geophysical observations from stressaccumulation and release to the initiation, propagation andtermination of fault ruptures, we are gaining deeper insights
into the mechanical processes governing fault zones. However,weaving these insights into a comprehensive understanding
remains a challenge. This session invites contributions that
focus on the mechanics of fault zone rupture behaviors, frommicro to macro scales. We encourage interdisciplinary submissions that synthesize observational, experimental, theoretical and computational insights on the mechanics that control
rupture dynamics in the fault zones.
Conveners: Xiaowei Chen, Texas A&M University (xiaowei.chen@tamu.edu); Yifang Cheng, University of California,
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Berkeley (chengyif@berkeley.edu); Zhe Jia, University ofCalifornia, San Diego (z5jia@ucsd.edu); Junle Jiang, Universityof Oklahoma (jiang@ou.edu)

ESC-SSA Joint Session: Climate Change
and Environmental Seismology
Climate change and associated environmental impacts will
be some of the most pressing global-scale challenges of thecoming century. Many of their effects can be observed andevaluated with seismology. With decades of analog seismograms predating the satellite era, an increasing density of seismic networks around the globe and advances in data analysis
methods, our science can make significant contributions tounderstanding climate change and its environmental impacts.
This session seeks abstracts showcasing the application of seismology to advancing the observation, modeling and decisionmaking associated with climate change and other environmental hazards, including how seismology can support thereal-time management of natural hazards caused or exacerbated by extreme climate conditions. We welcome seismic andseismoacoustic studies from all domains impacted by climatechange. Presentations are also encouraged on the effects of climate change on the practice of seismology, from challenges
posed to network operations, to effects on seismic data, toadditional data streams needed to improve climate and environmental monitoring capabilities.
This session is jointly organized by the European
Seismological Commission and SSA.
Conveners: Robert E. Anthony, U.S. Geological Survey(reanthony@usgs.gov); Allison Bent, Natural Resources
Canada (allison.bent@nrcan-rncan.gc.ca); Michael Dietze,
Georg-August-University(mdietze@gfz-potsdam.de);Shujuan Mao, Stanford University (sjmao@stanford.edu);
Robert Mellors, University of California, San Diego (rmellors@ucsd.edu); Siobhan Niklasson, New Mexico Institute of
Mining and Technology (siobhan.niklasson@student.nmt.
edu)

Cordilleran Strike-Slip Faults as
Seismogenic and Seismological
Features
The North American Cordillera extends from southern
Mexico to northern Alaska and includes several active fault
systems. Strike-slip faults are a major feature in the neotectonic
framework of the North American Cordillera and, in many
places, coincide with profound geophysical boundaries in thelithosphere. Syntheses of regional geological and geophysicaldatasets reveal that the crustal-scale architecture of the faults
is tied to their geologic evolution, but a number of questions
remain regarding the long-term evolution of these structures,
leading to the present-day crustal structure and seismogenic
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behavior. This session seeks to highlight present research relating the long-term geological evolution of Cordilleran strikeslip faults as it relates to the neotectonic, seismological andgeophysical signature of the faults.
Conveners: Richard Lease, U.S. Geological Survey(rlease@usgs.gov); Sean Regan, University of Alaska Fairbanks(sregan5@alaska.edu); Sarah Roeske, University of California,
Davis (smroeske@ucdavis.edu); Trevor S. Waldien, South
Dakota School of Mines and Technology (trevor.waldien@
sdsmt.edu)

Creating Actionable Earthquake
Information Products
The earthquake science and engineering community can provide leading-edge earthquake impact information to improve
mitigation, response and recovery through accessible andactionable communication of earthquake hazard, loss and risk.
This session explores and encourages contributions concerning earthquake information tools and their development cycle:
science, system and product objectives and design; iterating
through end-user engagement and product redesign; and public and professional user information campaigns necessary for
their rollout.
We invite presentations highlighting research and applications of earthquake information, particularly those thatconsider and engage with users to improve earthquake information tools. Example topics include but are not limited to:presenting near-real-time shaking and impact estimates; alerting and follow-up EEW-related information related to earthquake early warnings; tools for communicating hazards andrisk, engineering design and mitigation tools; earthquake
information apps; and product evaluation and user engagement efforts.
Conveners: Tiegan Hobbs, Geological Survey of Canada(thobbs@eoas.ubc.ca); Sabine Loos, University of Michigan(sloos@umich.edu); Marísa A. Macías, U.S. Geological Survey(mmacias@usgs.gov); Jessie K. Saunders, California Instituteof Technology (jsaunder@caltech.edu); David Wald, U.S.
Geological Survey (wald@usgs.gov)

Cryptic Faults: Advances in
Characterizing Low Strain Rate andEnvironmentally Obscured Faults
Identifying and characterizing active faults can now be performed almost routinely in places with high strain rates andclear geomorphology. In high strain rate domains, seismicity typically aligns along active fault planes, and slip rates aredetectable with GNSS networks. Furthermore, standard methodologies in tectonic geomorphology have developed andmatured in arid environments with minimal vegetation, suchas in the deserts of the Western United States or Asia.
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However, these conditions are not met in all seismically
active regions. In low strain rate domains, faults may not produce pronounced geomorphic expressions, and if there are
significant ruptures, exceptionally long recurrence intervals
contribute to challenges in identifying them. This problem is
especially acute in recently glaciated regions where the very
young landscapes may not preserve a complete earthquake
record. Furthermore, thick vegetation common to many of
the same regions (e.g., Western Canada, Alaska), can makeremote sensing and field observations of the bare earth difficult. Microseismicity, even when rigorously relocated, often
does not align along fault planes, and GNSS networks do nothave the necessary precision to measure strain accumulation across faults. Consequently, there is often disagreement
between different disciplines about whether there is enoughevidence to consider a fault “active” and hazardous. In thissession, we solicit abstracts on inconspicuous active faults,
and those which are difficult to observe and assess. We hopeto hear from a wide variety of practitioners using innovativetechniques in paleoseismology, field geology, marine geology,
observational seismology, geodesy, remote sensing and modeling to find and characterize these challenging, cryptic faults.
Conveners: Theron Finley, University of Victoria (tfinley@uvic.ca); Tiegan Hobbs, Geological Survey of Canada(tiegan.hobbs@NRCan-RNCan.gc.ca); Barrett Salisbury,
Alaska Division of Geological & Geophysical Surveys (barrett.
salisbury@alaska.gov); Lydia Staisch, U.S. Geological Survey(lstaisch@usgs.gov)

Detecting, Characterizing andMonitoring Mass Movements
In light of evolving climate patterns and land-use changes,
coupled with improved monitoring capabilities, we are witnessing a notable increase in detections of mass movements,
such as landslides, debris and snow avalanches, lahars andglacial events. These events can pose significant hazards, andthere is a pressing need to better understand, characterize andmitigate them. While these sources are not routinely monitored in real-time like earthquakes, recent advancements inseismoacoustic data and ground-based, airborne and satellite
imagery offer opportunities for rapid early warning and postevent detection and analysis. These improved data sources
and techniques can also help search for reliable precursors tocatastrophic failure and can be used to characterize existing
unstable slope instabilities.
This session aims to explore innovative methods toimprove our comprehension of these non-earthquake seismic
sources and enhance our ability to characterize and monitor
them and mitigate associated hazards. We invite presentations
that investigate various types of mass movements by leveraging seismoacoustic, geodetic and remote sensing techniquesalong with the application of machine learning. Topics ofwww.srl-online.org•

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interest encompass but are not limited to: source detection,
location, characterization, modeling and classification, precursory signal analysis, monitoring and hazard mitigation.
Conveners: Kate Allstadt, U.S. Geological Survey (kallstadt@usgs.gov); Clément Hibert, University of Strasbourg(hibert@unistra.fr); Ezgi Karasozen, University of Alaska
Fairbanks/Alaska Earthquake Center (ekarasozen@alaska.
edu); Liam Toney, U.S. Geological Survey( ltoney@usgs.gov)

Earth’s Structure from the Crust to theCoreThis session will cover all aspects of “structural seismology”
and highlight new contributions to research of core and mantle dynamics, the role of the mantle transition zone in mantle
convection, volcanism in different settings around the world,
the structure of subducting slabs, deep lithospheric deformation and processes, and lithosphere-asthenosphere interactions and their feedbacks into geohazards. We encourage
submissions that introduce new or new combinations of seismological data types, advances in global and regional-scale
seismic tomography, 3D waveform modeling, array- based
approaches and the analysis of correlation wavefields.
Conveners: Keith Koper, University of Utah (kkoper@
gmail.com); Jeroen Ritsema, University of Michigan (jritsema@umich.edu); Vera Schulte-Pelkum, University ofColorado (vera.schulte-pelkum@colorado.edu)

End-to-End Advancements inEarthquake Early Warning Systems
The field of Earthquake Early Warning (EEW) has expanded
and evolved significantly since the first public system cameonline in Mexico in 1991. Public EEW systems can now befound in many countries around the globe. These systems
make use of cutting-edge scientific, technological and social
science advancements to deliver alerts as rapidly, accurately
and with as much positive impact as possible.
EEW systems comprise various elements that must work
together synchronously and seamlessly to deliver useful alerts.
These components include world-class seismic and geodetic
networks, rapid telecommunications, algorithms that arecapable of quickly and correctly detecting earthquakes andtechnical recipients that are capable of turning alert messages produced by the system into useful warning products.
To maximize effectiveness of EEW systems, people must also
be educated about how to take safe response actions, such as
Drop, Cover and Hold On. To establish the necessary cultureof awareness and preparedness, EEW organizations must workwith others, including public safety organizations, to ensure
a broad, consistent and authoritative EEW education andoutreach effort. Such initiatives should include engagementwith critical infrastructure operators, and take special care toVolume 95•

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address vulnerable populations, such as low-income, special
needs, new immigrants, indigenous and elderly.
This session welcomes abstracts related to all aspects ofinnovating, optimizing and maintaining EEW systems including traditional and novel sensor developments, advancements
in communications, methodology and algorithmic development, system assessment and abstracts related to education,outreach and engagement for EEW.
Conveners: Ronni Grapenthin, University of Alaska
Fairbanks (rgrapenthin@alaska.edu); Angie I. Lux, Berkeley
Seismology Laboratory (angie.lux@berkeley.edu); Mouse
Reusch, University of Washington (topo@uw.edu); Brian
Terbush, Washington State Emergency Management
Division (Brian.Terbush@mil.wa.gov); Fabia Terra, Berkeley
Seismology Laboratory (terra@berkeley.edu)

From Earthquake Recordings to
Empirical Ground-Motion Modeling
The engineering seismology community has made a major
effort in recent years to develop advanced ground motion
models (GMMs). These developments have been facilitatedby the availability of very rich earthquake databases madepossible by the expansion of seismological networks aroundthe world and open data policies. However, uncertainties in
GMMs remain significant and reducing the epistemic uncertainties is currently one of the main challenges in seismic hazard assessment. In empirical GMMs it is often assumed thatthe earthquakes are recorded at the free surface of the Earth,that the sensor installation conditions and the seasonal effects
can be neglected, and that all instruments provide recordings
with reliable amplitudes. In practice, many seismic stations arelocated at depth (e.g., in borehole, in tunnels) or in an urban
environment, errors in the metadata can occur, and detailedsite characterization and site-effect assessment are performed
only on a limited subset of stations.
With this background, this session welcomes contributions highlighting any effects (from station installation conditions to complex site-effects) that could affect the recorded
ground motion, with consequent implications for GMMs,
especially at high frequency. Topics of interest include dataprocessing and data quality control, instrument coupling,soil-structure interaction, depth effect (down-going waves),seasonal variations, topography effect, site-effects, site characterization, regional and local attenuation and small-scale
heterogeneity and scattering. Studies comparing several techniques at the same site and those integrating a variety of datasets are also encouraged. Studies on improving current practices in earthquake databases and GMMs development, or on
the enhanced understanding of the high-frequency content ofseismic records are particularly welcome.
Conveners: Carlo Cauzzi, ORFEUS, Swiss Seismological
Service, ETH Zürich, (carlo.cauzzi@sed.ethz.ch); Fabrice
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Hollender, CEA Cadarache (fabrice.hollender@cea.fr);
Vincent Perron, CEA Cadarache (vincent.perron@cea.fr);
Zafeiria Roumelioti, University of Patras (zroumelioti@upatras.gr); Paola Traversa, Electricite de France, (paola.traversa@
edf.fr)From Faults to Fjords: Earthquake
Evidence in Terrestrial and Subaqueous
Environments
Strong ground motion and surface deformation caused by slip
on plate boundary, intraslab and crustal faults perturb surficial
processes and leave geologic evidence in terrestrial and subaqueous environments. This two-part session explores paleoseismic approaches that use geologic evidence to reconstruct
records of past earthquakes. Part one will address earthquake
evidence in terrestrial settings. This evidence may be produced by coastal, fluvial and colluvial processes that together
shape the ultimate sedimentary and geomorphic response totectonic surface deformation. Presentations also may focus on
ground failure and landslides triggered by earthquake shaking. Part two will feature subaqueous lake bottom and seafloor
imprints and processes triggered by earthquakes. These earthquake-triggered responses are governed by the properties ofthe passing seismic waves (frequency, amplitude, duration)and the geomechanics of the substrate (grain size, composition, shear strength). Presentations may focus on the array of
subaqueous sedimentary responses to strong ground motion,
including different styles of mass failure, surficial sedimentremobilization, soft sediment deformation and/or seismic
strengthening.
We invite presentations from Alaska and beyond thathighlight paleoseismic records from all depositional environments, laboratory analyses, modeling studies, or syntheses
and comparisons of global records. We particularly encourage presentations of: 1) Novel techniques using geophysicalsurvey tools, sediment sampling analyses and remote sensing
techniques to quantify tectonic deformation; 2) Studies withhigh geochronological precision, beyond the limitations oftypical radiometric dating; 3) Studies that compare paleoseismic records from adjoining subaqueous and terrestrial environments, pointing out the promises and pitfalls of different
approaches; and 4) Experiments that simulate the array ofsurficial processes that form geologic evidence of earthquakes.
Conveners: Danny Brothers, U.S. Geological Survey(dbrothers@usgs.gov); Tina Dura, Virginia Polytechnic
Institute and State University, tinadura@vt.edu); Jenna Hill,
U.S. Geological Survey (jhill@usgs.gov); Kristin Morell,
University of California, Santa Barbara (kmorell@ucsb.edu);
Belle Philibosian, U.S. Geological Survey (bphilibosian@usgs.
gov); Derek Sawyer, Ohio State University (sawyer.144@osu.
edu); Drake Singleton, U.S. Geological Survey (dsingleton@
usgs.gov); Katleen Wils, University of Innsbruck (katleen.
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bgcengineering.ca)

From Geodynamics to Earthquake
Rupture, Models That Cross Time- andLength-ScalesThis session brings together researchers in geodynamic modeling and earthquake rupture modeling to exchange ideas in
the areas of algorithms, software tools, benchmarks and, ofcourse, scientific results.
The timescales of interest in global geodynamics range
from the overturn time of the mantle to the timescale of measurable change of plate motions. This latter timescale becomesincreasingly shorter as our capacity to measure deformations
reaches sub-millimeter accuracy (driven by the need to understand pressing issues in global climate change, for example).
Geodynamic timescales now overlap those associated withsurface relaxation times of large earthquakes. Coming fromthe other direction, models of earthquake rupture run overthe seismic cycle and capture the long-term evolution of thesurface deformation and capture the accumulated offset alongindividual faults.
As we approach the computing power and model capacity
to attempt to unify long-term geodynamic models with shorttimescale seismic rupture models, we propose this session to
ask: What stands in our way? What algorithm developments
are needed? Are there mathematical or physical scale-crossing
problems that need to be overcome? Can the geodynamics andearthquake modeling community talk to each other?
Conveners: Matthew Knepley, University at Buffalo (knepley@gmail.com); Louis Moresi, Australian National University(louis.moresi@anu.edu.au)

How Well Can We Predict Broadband
Site-Specific Ground Motion and Its
Spatial Variability So Far?
Over the past few decades, a large number of studies havefocused on the impacts of the shallow geological subsurface
structure (within the uppermost one to two km) on the intensity and frequency content of ground motions recorded at thesurface. One of the most significant developments in the fieldis the growing evidence that simplified 1D ground responsemodels have only limited ability to accurately match recorded
ground motions. For this reason, very detailed and computationally expensive methods for analysing the ground response
are gaining more interest as of late.
In this session, we invite presentations on site characterization and ground motion modeling covering amplification and attenuation in a wide range of frequencies from < 1
Hz (interesting from an engineering perspective) to > 10 Hz
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(of special interest for the characterization of attenuation).
Numerical or empirical studies on the frequency-dependent
effects of spatial variability on attenuation and amplification,
an often overlooked issue, are specifically welcome. Similarly,
contributions about multidimensional ground response analyses are encouraged. Further topics of interest include the useof Artificial Intelligence (AI) to enhance and/or reduce thecomputational load of very detailed ground response analyses
and site characterization as well as other geophysical surveys
using active and passive seismic sources. We also invite contributions on the spatial correlation of earthquake intensity
measures as well as correlation models for different intensity
measures and regions based on empirical data and simulations. This session aims to provide researchers and engineers
with an opportunity to discuss different modeling approaches
and their required computational effort, and to compare thenumerical results against real, observed ground motions overa broadband frequency range.
Conveners: Morteza Bastami, International Institute ofEarthquake Engineering and Seismology (m.bastmi@iiees.
ac.ir); Mohamad M. Hallal, University of California, Berkeley(mhallal@berkeley.edu); Chunyang Ji, North Carolina
State University (cji3@ncsu.edu); Andrés Olivar-Castaño,
University of Potsdam (andres.olivar-castano@uni-potsdam.
de); Marco Pilz, GFZ Potsdam (pilz@gfz-potsdam.de)Illuminating Complex, Multiplet
Earthquake Sequences at
Kahramanmaras (Türkiye), Herat(Afghanistan) and Beyond
Multiplet earthquakes (doublets, triplets, etc.) pose distinct
challenges compared to standard mainshock-aftershock
sequences, including recurring strong ground motions thatcan destroy already-damaged buildings and stretch emergency services. The overlapping seismic or surface deformation signals can also complicate the scientific interpretation and response. However, multiplet sequences also havegreat potential for illuminating earthquake processes such as
stress triggering, fault interactions, and rupture nucleation,
propagation and arrest. Notable recent examples include the
6 February 2023 Kahramanmaras, Türkiye Mw 7.8 and 7.6
doublet, the October 2023 Herat, Afghanistan Mw 6.3 quadruplet, the 1 July 2022 Mw 6.0 Hormozgan, Iran doublet,the 14 November 2021 Mw 6.2 and 6.3 Fin, Iran doublet,the 2020 Mw 7.8 and 7.6 Shumagin, Alaska doublet, and the2019 Minandao, Philippines Mw 6.4–6.8 quadruplet, which
together offer a wealth of new data to explore. We solicit workon these and other multiplet sequences that involve seismic
analyses, remote sensing, geodesy, field observations, numerical modeling or combinations of these approaches. We solicit
studies that address the progression of fault slip through time(the kinematics) and/or help explain this sequence of events
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www.srl-online.org(the dynamics). We also seek contributions that offer insights
into why some fault systems may be more prone to multiplets
than others, or perhaps even offer suggestions for how thesesequences might be better incorporated into seismic hazard
analyses. Through in-depth discussions, we aim to emphasize the significance of enhancing international collaboration, implementing monitoring technologies and establishing disaster preparedness strategies to mitigate the impact of
future seismic events.
Conveners: Aybige Akinci, National Institute of Geophysics
and Volcanology (aybige.akinci@ingv.it); Pınar Büyükakpınar,GFZ Potsdam (pinar@gfz-potsdam.de); Gareth Funning,
University of California, Riverside (gareth@ucr.edu); AliceAgnes Gabriel, University of California, San Diego (algabriel@
ucsd.edu); Mohammadreza Jamalreyhani, SUSTech, China(jamalreyhani@sustech.edu.cn); Edwin Nissen, University ofVictoria (enissen@uvic.ca)

Induced Earthquakes: Source
Characteristics, Mechanisms, Stress
Field Modeling and Hazards
Induced earthquakes triggered by oil and gas production,enhanced geothermal systems, fluid injection for mining
and carbon capture have raised significant concerns. The
spatial and temporal evolution of induced seismicity is intricately connected to multiple factors, including the poroelastic response of the site, fluid budget, duration of operations
and halts, dimension and hydromechanical properties of thesubstratum and fault-slip modes under undrained/drained
conditions. These factors vary between nonproducing unconventional reservoirs and porous conventional reservoirs. The
spatiotemporal progression of induced earthquakes appears
closely tied to pre-existing tectonic structures, the orientationof faults, the diffusion of pore pressures, stress redistribution
over time and poroelastic stress transfer. Multidisciplinary
approaches can help to unravel underlying mechanisms,
thereby providing insights into the development of multifaceted mitigation strategies.
We invite submissions of case studies that offer insight
into the underlying physics of induced earthquakes and the
dynamic evolution of stress on host faults. We encourageinterdisciplinary studies showcasing source properties of
induced earthquakes, 3D imaging of faults, numerical simulations, stress field modeling, InSAR modeling, ground motion
prediction models tailored for induced earthquakes, and integrated hydrologic and geo-mechanical modeling linked to
production/injection operational data. We welcome contributions that delve into innovative datasets such as deep learning,
distributed acoustic sensing and large-N arrays. We also seek
computational, laboratory and in-situ experiments to unravelhydromechanical processes governing triggering mechanisms
over time.
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Conveners: Asiye Aziz Zanjani, Southern Methodist
University (aazizzanjani@smu.edu); Farzaneh Aziz Zanjani,
University of Miami (fzanjani@earth.miami.edu); Nadine
Igonin, University of Texas at Dallas (Nadine.Igonin@utdallas.edu)

Integrative Assessment of SoilStructure Interaction and Local Site
Effects in Seismic Hazard Analysis
In seismically active regions, the execution of reliable site
response analyses stands out as a cost-efficient measure during
the design phase. The dynamic interactions between structuralcomponents and underlying soil layers, known as soil- structure interaction (SSI), impact the overall seismic performanceand safety of the structures. The incorporation of SSI is vital
during the design of critical infrastructures such as railroad
and tunneling systems and power plants.
In this session, we invite researchers and practitioners tocontribute to a cohesive understanding of SSI and local site
effects, two essential components of the seismic hazard analysis (SHA). This session seeks to foster cutting-edge methodologies and innovative approaches in areas including but notlimited to: site response analysis (e.g., nonlinear 2D/3D site
effects), kinematic and inertial effects of SSI (e.g., numerical and physical modeling), vertical SSI, role of physicsbased simulations in improving our understanding of SRA
and SSI, complexities of SSI in urban settings and structureswith deeply embedded foundations and large footprints (e.g.,
nuclear power plants).
Conveners: Swasti Saxena, Pacific Northwest National
Laboratory (swasti.saxena@pnnl.gov); Mohammad Yazdi,
Mott
MacDonald(mohammad.yazdi@mottmac.com);
Peiman Zogh, University of Nevada, Reno (pzogh@unr.edu)

Learning Across Geological,
Geophysical and Model-Derived
Observations to Constrain Earthquake
Behavior
Earthquakes are dynamic events, but leave permanent markers of rock deformation and displacement. Geologic field studies identify these permanent markers, often used to determine
the magnitude of slip in past earthquakes and combined withdating techniques to determine long-term rates over multiple
earthquake cycles. Geophysical methods track ongoing platemotions and earthquake-cycle deformation captured by satellites using techniques involving GPS and InSAR. Analog andnumerical models capture long-term geologic deformation
and/or short-term dynamic behavior associated with earthquakes. However, in order to best advance both seismic hazard
mitigation and earthquake science, the methods and resultsfrom these different lines of inquiry should be integrated and1124|

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Modeling can fill gaps in observational data, target future
field sites and help determine the processes responsible forobserved deformation features. Likewise, observational datais critical to characterizing earthquake behavior and provides
necessary constraints on modeling input and output. This session aims to bring together scientists from these different linesof study to facilitate mutual understanding and collaboration.
We encourage submissions that are methods- and/or resultsbased studies across structural geology, paleoseismology,
Quaternary geology, geodesy and modeling of fault behavior
and earthquake dynamics.
Conveners: Kimberly Blisniuk, San José State University(kimberly.blisniuk@sjsu.edu); Roland Burgmann, Universityof California, Berkeley (burgmann@berkeley.edu); Elizabeth
Madden, San José State University (elizabeth.madden@sjsu.
edu)

Leveraging Cutting-Edge
Cyberinfrastructure for Large Scale
Data Analysis and Education
The rapid growth of geophysical data, sensing technologies,
and computing power has opened new frontiers in seismological research and education. To harness the potential of theseresources, seismologists need to adopt advanced cyberinfrastructure and modern numerical methods for data collection,transformation, analysis, storage, and distribution at scale.
This session will showcase how cloud computing services,
open software frameworks, and high-performance computing (HPC) can enable open, reproducible, and transformative
science in seismology. We will also explore how these technologies can support seismology education and training forthe next-generation workforce. We invite contributions fromresearchers, data producers, and data providers who have experience in using or developing cutting-edge cyberinfrastructure
for large-scale seismological problems such as dynamic rupture modeling, full waveform simulations and inversions, data
mining using large seismic networks and distributed acoustic
sensing. We also welcome contributions from educators who
have implemented pedagogical approaches to teach seismology using modern cyberinfrastructure. Additionally, we
encourage contributions from community efforts that aim tofacilitate the adoption of these technologies, such as SCOPED,MTMOD, CRESCENT, SCEC, ChEESE, GeoInquire andQuakeworx.
Conveners: Alice-Agnes Gabriel, University of California,
San Diego (algabriel@ucsd.edu); Henry Berglund, EarthScope
Consortium (henry.berglund@earthscope.org); Marine A.
Denolle, University of Washington (mdenolle@uw.edu); Timwww.srl-online.org•

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Dittmann, EarthScope Consortium (tim.dittmann@earthscope.org); Zoe Krauss, University of Washington (zkrauss@uw.edu); Eileen Martin, Colorado School of Mines (eileenrmartin@mines.edu); Amanda Thomas, University of Oregon(amthomas@uoregon.edu); Chad Trabant, EarthScope
Consortium (chad.trabant@earthscope.org); Ian Wang,
University of Texas at Austin (iwang@tacc.utexas.edu)

Machine Learning for Full Waveform
Inversion: From Hybrid to End-to-End
Approaches
Machine learning (ML) is quickly changing the landscape of
how we approach seismic inverse problems, including fullwaveform inversion (FWI) where the seismic waveforms are
directly used to solve for properties such as seismic velocities,
migrated images, source locations and moment tensors. ML
can potentially overcome some of the outstanding challenges
associated with conventional FWI techniques by increasing
computational efficiency, automating to reduce human laborand expertise requirements, mitigating cycle skipping, parameterization and convergence issues, implementing uncertainty
quantification through deep learning-based approaches, andreducing the need for a suitable starting model. The wide
breadth of ML methods and emerging scientific ML, deeplearning architectures and optimization algorithms that are
rapidly expanding warrant a review of current application ofthese technologies in the seismic inverse domain.
We encourage submissions ranging from ML methods
and tools that assist conventional physics-based FWI to full
end-to-end deep learning FWI methods that estimate variety of inverted properties. All ML approaches are welcome,including but not limited to: deep neural networks, generative
methods, decision trees, unsupervised dimensionality reduction and clustering, physics-informed ML, and application ofvarious learning algorithms including supervised, self-supervised and unsupervised learning.
Conveners: Jennifer L. Harding, Sandia National
Laboratories (jlhardi@sandia.gov); Mrinal K. Sen, Universityof Texas at Austin (mrinal@utexas.edu); Hongkyu Yoon,
Sandia National Laboratories (hyoon@sandia.gov)

Marine Seismoacoustics
The depths of oceans, rivers and other water bodies, and theprocesses occurring within them, continue to be exploredthrough the use of seismic and acoustic observations. Here
we invite contributions from the full spectrum of submarine research fields, including geophysical and geodynamical
imaging and/or modeling, earthquake/tsunami early warning,interactions at the seafloor interface, water/ice interface, climate induced changes, particularly in polar regions, tracking

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of marine life and the latest advances in underwater sensors
and other related technologies.
Conveners: Kasey Aderhold, EarthScope Consortium(kasey.aderhold@earthscope.org);
Helen
Janiszewski,
University of Hawai‘i at Mānoa (hajanisz@hawaii.edu);
Siobhan Niklasson, Los Alamos National Laboratory (sniklasson@lanl.gov); Charlotte Rowe, Los Alamos National
Laboratory (char@lanl.gov).

Multidisciplinary Approaches for
Volcanic Eruption Forecasting
Detecting volcanic unrest and forecasting volcanic eruptions,
how they will evolve and when they will finish is one of themain challenges in volcanology. The interaction of volcanic
systems with their environment during an eruptive process
affects many different physical and chemical parameters.
Many of these parameters, called observables, are monitoredin volcanic systems in near-real time, being the base of alertlevel strategies and forecasting protocols. Exploring theseobservables involves complex data processing, time series
analysis and the development of numerical models of volcanic processes, with the goal of improving our understandingof the interaction between subsurface processes and volcanic
activity.
Inferring conceptual and numerical models of how volcanoes work requires a multidisciplinary analysis integrating
data and methodologies from different disciplines, including geology, seismology, remote sensing and geodesy; aswell as physics or chemistry, signal processing and statistical
approaches. At present, several promising results have been
derived from this joint analysis, improving our knowledge ofvolcanic unrest and magma ascent, which helps eruption forecasting and decision-making.
This session aims to encourage the multidisciplinary community working in volcanology to submit their most recent
results on unrest detection and eruption forecasting. We welcome (but are not limited to) contributions from volcano statistics, event trees analysis, data assimilation techniques, theuse of artificial intelligence and machine learning to study
volcanic signals, analysis of time series in volcanology, studyof the evolution of new seismic parameters/features, development of innovative analytical methods and probabilistic volcanic hazard assessment. We invite researchers to share theirvaluable work in this session, contributing to the collective
knowledge and progress in the field of volcanic forecasting.
Conveners: Alberto Ardid, University of Canterbury(alberto.ardid@canterbury.ac.nz); Francesca Bianco, Istituto
Nazionale di Geofisica e Vulcanologia (francesca.bianco@
ingv.it); Társilo Girona, Alaska Volcano Observatory,
University of Alaska Fairbanks (tarsilo.girona@alaska.edu);
Janire Prudencio, Universidad de Granada (janire@ugr.es)

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Network Seismology: Recent
Developments, Challenges and Lessons
LearnedSeismic monitoring is not only an essential component ofearthquake response but also forms the backbone of a substantial amount of research into seismic hazards, the earthquake
process and seismotectonics. To ensure networks best serve
the public, media, government and academic communities,
it is important to continue to develop monitoring networks’abilities to accurately and rapidly catalog earthquakes. Due tothe operational environment of seismic monitoring, seismic
networks encounter many unique challenges not seen by the
research community. In this session, we highlight the uniqueobservations and challenges of monitoring agencies and lookto developments that may improve networks’ ability to fulfill
their missions. Seismic operation centers play a crucial role incollecting seismic data, and generating earthquake products
including catalogs, warnings and maps of ground shaking. The
purpose of the session is to foster collaboration between network operators, inform the wider seismological community of
the interesting and challenging problems within network seismology and look to the future on how to improve monitoring
capabilities. This session is not only an opportunity for monitoring agencies to highlight new developments in their capabilities, but we also encourage submissions describing new
instrumentation, methods and techniques that would benefit
network operations for detecting, locating and characterizing
earthquakes, particularly in a near real-time environment.
Conveners: Blaine Bockholt, Idaho National Laboratory(blaine.bockholt@inl.gov); Renate Hartog, University ofWashington (jhartog@uw.edu); Kristine L. Pankow, Universityof Utah (pankowseis2@gmail.com); Adam Ringler, U.S.
Geological Survey (aringler@usgs.gov); Dmitry Storchak,International Seismological Centre (dmitry@isc.ac.uk)

New Insights into the Development,
Testing and Communication ofSeismicity Forecasts
The increasing availability and quality of geophysical datasets,
including high-resolution earthquake catalogs, fault information and interseismic strain data, has enabled the creation of
statistical and physics-based seismicity models, some of which
underpin probabilistic seismic hazard analyses. New machinelearning (ML) techniques have also improved data acquisition
and analysis for seismicity modeling. Forecasts produced bysuch models can be tested and compared prospectively, e.g.,
within the framework of the Collaboratory for the Study ofEarthquake Predictability, paving the way for potentiallymore informative earthquake forecasts. In turn, forecast models are being operationalized by public and private agencies
to provide a range of audiences with reliable information on
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Seismological Research Lettersthe occurrence of earthquakes. This poses communication
challenges that require solutions from the social sciences. We
welcome contributions that help us elucidate the main advantages and limitations of current seismicity models, identify themost informative forecasting methods, improve our understanding of the earthquake generation process, and facilitate
the communication and visualization of earthquake forecasts.
Submissions may include models based on ML-derived earthquake catalogs, new hypotheses explaining what controls
earthquake potential, quantitative analyses evaluating the predictive skills of seismicity forecasts, or studies on the effective
communication of earthquake forecast information.
Conveners: Jose Bayona, University of Bristol (jose.bayona@bristol.ac.uk); Kelian Dascher-Cousineau, University ofCalifornia, Berkeley (kdascher@berkeley.edu); Leila Mizrahi,
Swiss Seismological Service (leila.mizrahi@sed.ethz.ch);
William Savran, University of Nevada, Reno (wsavran@unr.
edu); Max Schneider, U.S. Geological Survey (mschneider@usgs.gov)

Numerical Modeling in Seismology:
Developments and Applications
We equally invite both contributions to numerical-modelingmethods/algorithms and applications in any dimension if
appropriate. Progress in seismology is unthinkable without
continuous developments of theory and numerical-modelingmethods. This is well seen in very recent important advancesin the discontinuous Galerkin, finite-difference and spectralelement methods as well as in emergence of the new powerful
distributional finite-difference method.
Recent developments include faithful rheological andgeometrical complexity of the Earth’s interior, earthquakes
and other important seismological phenomena, time-space
discretization, optimizations of computational algorithms andcomputer codes, optional balance between accuracy and efficiency. Remarkable progress in the finite-difference modelingin seismic exploration poses a useful challenge for numericalmodeling in earthquake seismology. New observations anddata from local dense networks make it possible for numerical modeling to considerably contribute to our understandingof rupture dynamics, seismic wave propagation, earthquake
ground motion including non-linear behavior, seismic noiseand earthquake hazard. We especially welcome applications tocompelling observational issues in seismology.
Conveners: Alice-Agnes Gabriel, University of California,
San Diego (algabriel@ucsd.edu); Martin Galis, Comenius
University Bratislava (martin.galis@uniba.sk); Jozef Kristek,
Comenius University Bratislava (kristek@fmph.uniba.sk);
Peter Moczo, Comenius University Bratislava (moczo@fmph.
uniba.sk); Arben Pitarka, Lawrence Livermore National
Laboratory (pitarka1@llnl.gov); Wei Zhang, Southern

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University of Science and Technology (zhangwei@sustech.
edu.cn)The OSIRIS-REx Sample Return Capsule
Reentry: Geophysical Observations
The 24 September 2023 reentry of the NASA’s OSIRIS-REx
Sample Return Capsule (SRC) was only the fifth reentry
from interplanetary space since the end of the Apollo era. It
provided a unique opportunity to geophysically observe an“artificial meteor” with known dimensions, speed and mass.
A diverse set of institutions utilized nodal seismic arrays,
ground and airborne acoustic sensors, distributed acoustic
sensing, GPS sounding and ionosphere Doppler sounding torecord the object’s passage through the atmosphere. Resultsfrom these studies have implications for the remote detection
and characterization of meteoroids and high-speed artificial
objects (e.g., reentry, orbital debris) on Earth and may informmission concepts for planetary exploration (e.g., Venus, Mars,
Titan, Jupiter). We invite contributions that emphasize geophysical observations of the OSIRIS-REx SRC reentry, anddiscuss their broad scientific implications for remote sensing
on Earth and beyond.
Conveners: Chris Carr, Los Alamos National Laboratory(cgcarr@lanl.gov); Brian Elbing, Oklahoma State University(elbing@okstate.edu); Charles Langston, University ofMemphis (clangstn@memphis.edu); Richard Lewis, The
Defense Threat Reduction Agency (richard.d.lewis1.civ@mail.
mil); Yasuhiro Nishikawa, Kochi University of Technology(nishikawa.yasuhiro@kochi-tech.ac.jp); Elizabeth A. Silber,
Sandia National Laboratory (esilbe@sandia.gov)

Physics-Based Ground Motion
Modeling
Physics-based wave propagation simulations have the potential to quantify the contribution to ground motion estimatesfrom individual features included in the modeling, such as
basin edge effects, topographic scattering, nonlinear soil
effects, small-scale heterogeneities, source effects and general 3D path effects. Such quantification is useful for understanding wave propagation as well as which features must be
included to reproduce observed seismic records. This session
welcomes submissions on physics-based numerical modeling of wave propagation, including studies focused on the
dynamic or kinematic rupture models as well as development
and validation of community seismic velocity models, andquantification of contributions from these model features on
simulated ground motions.
Conveners: Evan Hirakawa, U.S. Geological Survey (ehirakawa@usgs.gov); Kim B. Olsen, San Diego State University(kbolsen@mail.sdsu.edu);
WilliamStephenson,
U.S.
Geological Survey (wstephens@usgs.gov)
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Planetary Seismology
This session highlights contributions to seismology focusedon planets other than Earth.
Conveners: Isabella Seppi, University of Alaska Fairbanks(irseppi@alaska.edu); Yuan Tian, University of Alaska
Fairbanks (ytian4@alaska.edu)

Regional-Scale Hazard and Risk
Assessments
Efforts toward improving the resilience of urban environments to seismic hazards and associated geohazards are challenged by spatially variable ground motions and permanent
ground deformations (e.g., due to co-seismic landslides orsoil liquefaction). Regional-scale probabilistic seismic hazard
and risk analyses are often used to evaluate large, distributed
infrastructure systems such as pipelines and transportation
networks in densely populated cities. While relevant work in
the last decade has contributed toward multi-scale probabilistic modeling of regional ground shaking and deformation,
important advances to support regional risk and loss assessments, financial loss considerations, and earthquake response
tools remain missing. For instance, accurately characterizing
the spatial variability of ground motions and their associatedeffects is important to capture the seismic risk of exposed
communities in earthquake-prone areas, which is increasing
with urbanization and highly interdependent and aging infrastructure systems.
Even though there are common aspects between site-specific and regional seismic hazard and risk analyses, the characterization of ground motions, geologic conditions, and losses
present different challenges to the data collection and modeling efforts. For instance, subduction zones, from the deep
inslab environments through the megathrust and shallow
crustal faults, present significant challenges when it comes tobridging the gap between earthquake science and application.
Thus, this session invites contributions on 1) simulations andanalyses of spatiotemporal variations of ground motion anddeformation at regional scales, 2) tools developed for earthquake scenarios that capture the spatial correlation of groundmotions, 3) advances in earthquake early-warning systems
and rapid post-earthquake assessments, 4) methods based on
the integration of site-specific data and geospatial analytics,5) regional-scale approaches to estimate the occurrence anduncertainty of ground failure, 6) regional scale portfolio asset
risk analyses and methodologies, 7) regional scale exposureand vulnerability assessments, and 8) specific applications ofearthquake science for hazard and loss modeling.
Conveners: Ashly Cabas, North Carolina State University(amcabasm@ncsu.edu); John Cassidy, Geological Survey ofCanada (john.cassidy@nrcan-rncan.gc.ca); Rodrigo Costa,
University of Waterloo (rodrigo.costa@uwaterloo.ca); Cassie
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Gann-Phillips, North Carolina State University (cvgann@ncsu.edu); Mike Greenfield, Greenfield Geotechnical (mike@greenfieldgeotechnical.com); Tiegan E. Hobbs, Geological
Survey of Canada (thobbs@eoas.ubc.ca); James Kaklamanos,
Merrimack College (kaklamanosj@merrimack.edu); Albert
Kottke, Pacific Gas and Electric Company (albert.kottke@
pge.com); Sabine Loos, University of Michigan (sloos@umich.edu); Cristina Lorenzo-Velazquez, North Carolina
State University (clorenz@ncsu.edu; Andrew Makdisi, U.S.
Geological Survey (amakdisi@usgs.gov); Hong-Kie Thio,
AECOM (hong.kie.thio@aecom.com); Eric Thompson, U.S.
Geological Survey (emthompson@usgs.gov); David Wald,
U.S. Geological Survey (wald@usgs.gov); Erin Wirth, U.S.
Geological Survey (emoriarty@usgs.gov)

Research Advances in “High-Impact”“Under-Studied” Earthquakes andTheir Impacts on Communities
Many regions of the world are at risk of earthquakes with significant human and economic impacts due to regional seismic hazard and lack of earthquake preparedness (termed“high-impact”). The cause of the earthquakes might be poorly
understood due to a lack of resources, a low probability ofoccurrence, a lack of interested seismologists, their remotelocations, and/or a lack of awareness of the hazard (termed“under-studied”). The 2023 M6.8 Morocco earthquake serves
as a striking example, where high mountains exist with little
seismicity a few hundred kilometers from a plate boundary,
and which caused shaking-related fatalities and injuries plus
large economic losses. This session focuses on “high-impact,”“under-studied” (HIUS) earthquakes, and we welcome
abstracts across all areas of solid-earth science, earthquake
geology and engineering, and social science that study or
address HIUS earthquakes. We invite presentations highlighting research from any discipline with the potential to respondto the needs of vulnerable populations that have been historically underserved by current earthquake science, engineeringand public policy. Example topics include: 1) communitydriven or community-based research results; 2) discoveries
advancing our understanding of seismic hazards in areas oflow probability but high impact earthquakes (including intraplate and induced earthquakes); 3) strategies for implementing practical, research-inspired solutions for communities; 4)
research engaging low-resourced communities or historicallymarginalized populations; 5) existing efforts to coordinate
research and projects for broader community benefits; and 6)
integration of social science with seismology. We encourage
presenters to highlight strategies and efforts to improve inclusivity, diversity, equity and accessibility in seismology andearthquake science in these regions.
Conveners: Susan Bilek, New Mexico Institute of Mining
and Technology (susan.bilek@nmt.edu); Marianne Karplus,
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University of Texas at El Paso (mkarplus@utep.edu); Zhigang
Peng, Georgia Institute of Technology (zpeng@gatech.edu);
Elizabeth Vanacore, University of Puerto Rico (elizabeth.
vanacore@upr.edu); Aaron A. Velasco, University of Texas at
El Paso (aavelasco@utep.edu)

Seismic Cycle-Driven Sea-Level Change
Over Decades to Centuries:
Observations and Projections
As global sea levels rise, coastal communities worldwide will
be forced to adapt or retreat. Projections of relative sea-levelchange across decades or centuries will become essential planning tools to mitigate the vulnerability of these communities.
In seismically active regions, changes in land elevation
associated with the earthquake cycle —including interseismic,
coseismic and postseismic deformation, as well as slow-slip
events — can either mitigate or exacerbate climate-driven sealevel rise over similar timescales. To ensure accurate projections of relative sea-level change, it is therefore necessary toevaluate the influence of tectonic vertical land movements(VLM) in the relevant analyses.
Estimating and incorporating tectonic VLM into projections of relative sea-level rise requires two key components: 1)
Collecting and analyzing geologic and geodetic observations
to constrain present and past contributions of VLM to relative
sea-level change throughout all phases of the seismic cycle;
and 2) Modeling to project observed tectonic VLM decades
and centuries into the future.
We welcome contributions that link VLM resulting fromthe seismic cycle to relative sea-level changes, through data
analysis, modeling or a combination of both.
Furthermore, vertical deformation is not always primarily
associated with tectonic signals, as nontectonic processes suchas sediment loading and glacial isostasy adjustment can also
have significant influences on VLM of the lithosphere. Studies
that help identify and account for such nontectonic processes
to improve VLM projections, and thus relative sea- level projections, are also welcomed.
Conveners: Kate J. Clark, GNS Science (k.clark@gns.
cri.nz); Andrew Howell, University of Canterbury (andrew.
howell@canterbury.ac.nz); Jeonghyeop Kim, University ofWashington (jey.kim@uw.edu);

Seismic Monitoring, Modeling andManagement Needed for Geothermal
Energy and Geologic Carbon Storage
Emerging subsurface operations (e.g., geothermal energy orcarbon storage) are potential pathways to greener or more sustainable energy solutions and will play crucial roles in achieving the net-zero emission goal by 2050. However, concerns
around induced earthquakes and the longevity and developwww.srl-online.org•

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ment of needed reservoirs are a serious impediment to widespread adoption of these emerging energy resources. Thus,
tools to identify and de-risk induced seismicity concerns andbetter characterize the reservoirs will be necessary to reachclimate goals. In this session, we invite contributions fromresearch on novel seismic and non-seismic technologies andapplications of novel and advanced seismic techniques to better understand and manage the transition to greener energy
solutions. We welcome submissions of abstracts on computational, artificial intelligence/machine learning, laboratory
experimental and field-scale studies.
We strongly encourage contributions from EGS/geothermal or carbon storage projects. Additionally, we are alsointerested in lessons learned from induced seismicity causedby other anthropogenic operations (e.g., disposal, production,
hydraulic fracturing). Examples can include field test sites that
focus on geophysical technologies, such as real-time monitoring and characterization of induced seismicity, distributed
acoustic sensing, large-N array, active surface seismic, verticalseismic profiling, seismic imaging of faults and fracture zones,
laboratory experiments and novel instrumentation. We also
welcome submission of abstracts like laboratory studies that
focus on the role that fluids play in fault reactivation, modelling studies at all scales, seismicity forecasting models, hazard/
risk analysis, good-practice guidelines and mitigation strategies that would help in reducing commercial costs or enhancing the safety of future projects.
Conveners: Erkan Ay, Shell (Erkan.Ay@shell.com); Kai
Gao, Los Alamos National Laboratory (kaigao@lanl.gov);
Chet Hopp, Lawrence Berkeley National Laboratory (chopp@
lbl.gov; Lianjie Huang, Los Alamos National Laboratory (ljh@lanl.gov); Federica Lanza, ETH Zürich (federica.lanza@sed.
ethz.ch); Nori Nakata, Lawrence Berkeley National Laboratory(nnakata@lbl.gov); Annemarie Muntendam-Bos, Delft
University of Technology (A.G.Muntendam-Bos@tudelft.nl);
Kris Pankow, University of Utah (pankowseis2@gmail.com);
Ryan Schultz, ETH Zürich (ryan.schultz@sed.ethz.ch); Nana
Yoshimitsu, Kyoto University (yoshimitsu.nana.6i@kyoto-u.
ac.jp); Yingcai Zheng, University of Houston (yzheng24@central.uh.edu)

Seismoacoustic, Geodetic and Other
Geophysical Investigations of Active
Volcanoes
Seismology has long been the primary means through whichto study and monitor the movement of magma and other fluids
in active volcanic systems. However, despite decades of seismic monitoring at volcanoes, answers to important questions
about the ascent of magma, the circulation of fluids within

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volcanic systems, and how these phenomena are reflected
in geophysical signals, remain elusive. In recent decades,
improvements in instrumentation and processing techniques
have led to the widespread use of additional geophysical tools
capable of tracking fluid movement, including infrasound,high-rate GPS, InSAR and gravity. These tools, often used inconcert with seismological techniques, have brought forthmany new insights that were previously unknown. We seek
submissions that showcase the breadth of interdisciplinarygeophysical monitoring and study of active volcanoes using
any of the methods described above or other interdisciplinary approaches. We encourage contributions that emphasize
advances in numerical modeling or machine learning, feature
new instrumentation or analytical methods and/or provide
novel insights into the physical processes controlling fluid
movement or other volcanic signals.
Conveners: Josh Crozier, U.S. Geological Survey (jcrozier@usgs.gov);Ricardo Garza-Giron, Colorado State
University (rgarzagi@ucsc.edu); Margaret Glasgow, U.S.
Geological Survey (mglasgow@usgs.gov); Alicia HotovecEllis, U.S. Geological Survey (ahotovec-ellis@usgs.gov); John
J. J. Lyons, U.S. Geological Survey (jlyons@usgs.gov); Diana
Roman, Carnegie Science (droman@carnegiescience.edu)

Seismology in the Oceans: Pacific
Hemisphere and Beyond
The ocean realm provides a clear, relatively pristine view
into many of the fundamental tectonic and geodynamical
processes that form our planet, including rifting, volcanismand hydrothermal processes at mid-ocean ridges; the origin
and nature of mid-plate and hot-spot volcanism, transformfault earthquake dynamics, hydration of oceanic lithosphereand the nature of multi-scale convection and its relationshipto plate evolution, to name a few. The Pacific basin provides
a natural laboratory for studying these processes, and it has
been the focus of a number of experiments exploiting recent
advances in marine-seismic instrumentation, including thoseaffiliated with the multinational grassroots collaboration
PacificArray. We invite contributions from scientists using
active- and passive-source marine-seismic datasets to investigate fundamental Earth-science processes in the Pacific andother ocean basins.
Conveners: James Gaherty, Northern Arizona University(james.gaherty@nau.edu); Jianhua Gong, Indiana University(gongjian@iu.edu); HyeJeong Kim, University of Utah(hyejeong.kim@utah.edu); YoungHee Kim, Seoul National
University (younghkim@snu.ac.kr); Joshua Russell, Syracuse
University (jbrussel@syr.edu); Lindsay Worthington,
University of New Mexico (lworthington@unm.edu)

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Six Decades of Tsunami Science: From
the Source of the 1964 Tsunami toModern Community Preparedness
Tsunami science has evolved significantly in the 60 years sincethe 1964 Great Alaska Earthquake. There have been important
advances in tsunami source characterization, propagation andrunup modeling, tsunami warning and forecasting and probabilistic tsunami hazard assessment. After the recent tsunami
disasters of 2004 and 2011, tsunami science has encompassed
new fields of research that include studies of survivability,
resilience, loss estimates and recovery potential of coastal
communities. Translating tsunami hazards into potential risk
estimates, educating the public, counteracting disaster amnesia and preserving the memories of tsunamis for future generations are all important tasks that the tsunami community
will be working on for decades.
We welcome both focused and multidisciplinary contributions to this session covering any of the following: analytical and numerical modeling of different tsunami generation
mechanisms, including submarine and subaerial landslides,
volcanic eruptions and air-pressure disturbances; mapping
tsunami inundation and evacuation zones; paleotsunami
studies; regional and local studies that deal with hazard, risk,
vulnerabilities and exposure; tools and procedures for more
efficient forecast and warning; studies of community preparedness and human behavior; and best practices in public
education and outreach.
Conveners: Dmitry Nicolsky, University of Alaska
Fairbanks (djnicolsky@alaska.edu); Anthony Picasso, Alaska
Division of Homeland Security & Emergency Management(anthony.picasso@alaska.gov); Barrett Salisbury, Alaska
Division of Geological & Geophysical Surveys (barrett.salisbury@alaska.gov); Elena Suleimani, University of Alaska
Fairbanks (ensuleimani@alaska.edu)

Special Applications in Seismology
This session presents a range of applications that record
unique data or analyze data that contribute in novel ways. This
includes studies on noise reduction, improved earthquake
detection and characterization, low frequency and triggered
earthquakes and applications in urban areas.
Conveners: Carl Tape, University of Alaska Fairbanks(ctape@alaska.edu); Michael West, University of Alaska
Fairbanks (mewest@alaska.edu)

Structure and Behavior of the AlaskaAleutian Subduction Zone
The Alaska-Aleutian subduction zone is one of the most seismically and volcanically active plate boundaries in the world.
Over the past decade, it has ruptured in several large inter1130|

Seismological Research Lettersplate and intraplate earthquakes and produced notable volcanic eruptions and non-eruptive activity. It exhibits profoundalong-strike variations in geodynamics, lithospheric configuration, locking, rupture history of the megathrust and otherfault systems, slow-slip events and magmatic processes. The
Alaska-Aleutian subduction zone is thus an excellent place
to address fundamental questions regarding subduction zone
processes and associated earthquake and volcanic activity. The
availability of new geophysical datasets on land and off shore
and the occurrence of a series of recent, well-characterized
large earthquakes in the Alaska-Aleutian subduction zone
have enabled a plethora of new results and insights into subduction processes. We invite a wide spectrum of contributions
that focus on the Alaska-Aleutian subduction zone, including
investigations using newly available geophysical imaging andmonitoring datasets, paleoseismology and geological studies
and numerical and experimental studies.
Conveners: Grace Barcheck, Cornell University (grace.
barcheck@cornell.edu); Julie Elliott, Michigan State University(ellio372@msu.edu); Ronni Grapenthin, University of Alaska(rgrapenthin@alaska.edu); Donna Shillington, Northern
Arizona University (donna.shillington@nau.edu); Xiaotao
Yang, Purdue University (xtyang@purdue.edu)

Structure, Seismicity and Dynamics of
the Queen Charlotte-Fairweather Fault
SystemThe Queen Charlotte - Fairweather Fault System (QC-FW)
is a transform plate boundary that spans >1000 kilometers of
the western edge of North America between the Cascadia andAlaska convergent margins. In the last 100 years, the QC-FW
has hosted several major earthquakes, including the 1949
magnitude (M 8.1) Queen Charlotte earthquake, the 1958
(M 7.9) on the Fairweather Fault, and the 2012 Haida-Gwaii(M 7.8) and 2013 Craig (M 7.5) earthquakes. The tectonics of
the QC-FW are variable along its length, including obliqueconvergence in the south at Haida Gwaii, comparably simple
shear offshore Southeast Alaska, and oblique collision with
the Yakutat microplate in the north. The QC-FW is similar inlength and in slip rate (~4-5 cm/yr) to the San Andreas fault
system. However, the remote location of the QC-FW, largely
offshore hugging the North American continental shelf andslope, leaves major gaps in our understanding of its structure, seismicity and dynamics. We welcome abstracts that
explore the QC-FW system, including but not limited to: its
natural hazards, earthquakes, subsurface properties, structure
and tectonics. We encourage a large range of methods andseek perspectives that compare the QC-FW with other plateboundary systems.
Conveners: Collin Brandl, University of New Mexico(cbrandl@unm.edu); Andrew Gase, Western Washington
University (gasea@wwu.edu); Emily Roland, Westernwww.srl-online.org•

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Washington University (rolande2@wwu.edu); Lindsay
Worthington, University of New Mexico (lworthington@unm.
edu)

Tectonics and Seismicity of Stable
Continental Interiors
Earthquakes in stable continental interiors far from active plateboundaries, such as in central and eastern North America,
northern Europe, western and southern Africa, Australia andparts of Asia, are perhaps the least understood. Nevertheless,advances in intraplate seismicity are being achieved through avariety of approaches. Examples include local- and nationalscale seismic monitoring efforts that increase completeness ofearthquake catalogs, detection algorithms that identify eversmaller earthquakes from existing data, imaging of subsurface faults using relocated seismicity, seismic tomography andother geophysical methods, studies that constrain historicalslip on such faults, quantification of geodetic, geomorphologic
and elevation changes and through improved measurementsof local stresses. In parallel with these efforts, ongoing groundmotion studies continue to improve our understanding ofsource, path and site response characteristics unique to intraplate regions.
This session seeks diverse contributions related to intraplate earthquake hazards with goals of improving earthquake
catalogs, identifying and characterizing active faults and/or deformation in stable continental interiors, deciphering
long-term earthquake histories, statistical analyses of seismicity, assessing potential ground motion impacts, constraining
models of kinematics and geodynamic properties and understanding the mechanisms that cause enigmatic intraplate
earthquakes. Contributions regarding recent intraplate earthquake sequences are especially welcome.
Conveners: Oliver Boyd, U.S. Geological Survey (olboyd@
usgs.gov); Jessica Thompson Jobe, U.S. Geological Survey(jjobe@usgs.gov); William Levandowski, TetraTech (will.
levandowski@tetratech.com); Zhigang Peng, Georgia Instituteof Technology (zpeng@gatech.edu); Anjana K. Shah, U.S.
Geological Survey (ashah@usgs.gov)

Towards Advancing Earthquake
Forecasting and Nowcasting: Recent
Progress Using AI-Enhanced Methods
New technologies like advanced machine learning (ML) of big
data (BD) and artificial intelligence (AI), together with signalprocessing tools that emerged in the past decade, have broughta wave of intensified studies of earthquake forecasting andnowcasting. In addition, fast-expanding datasets due to theinstallation of dense-sensing networks, diversified observations (e.g., acoustic, elastic, satellite observations), injectioninduced seismicity from around the world and high-resolution
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ML-based catalogs provide more resources and constraints forstudying the earthquake nucleation mechanism. These methods also allow the exploration of physical earthquake precursors and call for advanced computing architectures and data
management plans in their effective usage. These new methods
and datasets open the door to multidisciplinary collaboration
in a seamless way. In this session, we welcome contributions
from a wide spectrum of advances in the field of earthquake
forecasting and nowcasting, including but not limited to: newdata-driven or physics-based ways for forecasting/nowcasting
earthquakes; machine learning and AI-enhanced methods toboost accuracy, verification and reliability; earthquake forecasting/nowcasting from laboratory to field; breakthrough realcase studies; cross-disciplinary studies of earthquake forecasting/nowcasting; and new sensing and processing technologies
for capturing the precursor signals.
Conveners: Yangkang Chen, University of Texas at Austin(yangkang.chen@beg.utexas.edu); Katsumi Hattori, Chiba
University (khattori@faculty.chiba-u.jp); Lisa G. Ludwig,
University of California, Irvine (lgrant@uci.edu); Dimitar
Ouzounov, Chapman University (ouzounov@chapman.edu);
John Rundle, University of California, Davis (john.b.rundle@
gmail.com)

Translating Seismic Imaging into
Geodynamic Understanding
Seismic imaging provides valuable information about the subsurface of the Earth. Travel times and waveforms from naturaland controlled sources can be used to construct 2D and 3D
velocity, attenuation and anisotropy models of the Earth’s interior from the core to the crust. These seismically determined
quantities are subsequently interpreted into physical properties and integrated into geodynamic models to explore a wide
range of dynamical processes to understand Earth’s past, present and future evolution.
This session seeks to increase the exchange between seismic and geodynamic model communities to better understand data and model uses and limitations. Contributions that
explore applications of seismic imaging results in computational models that increase our understanding of Earth dynamics, model uncertainty and data resolution, and software tools
used to construct model data are welcome. This includes but
is not limited to: dynamics of the deep Earth including coremantle interaction, mantle convection and mantle plumes;
dynamics of the lithosphere including subduction zones, rifting and glacial isostatic adjustment; and dynamics of the crust
including fault, geothermal and volcanic systems.
Conveners: Ebru Bozdag, Colorado School of Mines(bozdag@mines.edu); Rebecca Fildes, University ofCalifornia, Davis (rfildes@ucdavis.edu); Menno Fraters,
University of Florida (menno.fraters@ufl.edu); Lorraine J.
Hwang, University of California, Davis (ljhwang@ucdavis.
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edu); Andrew Lloyd, Lamont-Doherty Earth Observatory,
Columbia University (andrewl@ldeo.columbia.edu); Brandon
VanderBeek, Università di Padova (brandonpaul.vanderbeek@unipd.it)

Understanding and Quantifying the
Variability in Earthquake Source
Parameter Measurements
Earthquake source parameters such as stress drop, magnitude
and moment tensors are fundamental terms used to describe
earthquakes. They are also key ingredients in earthquake
ground motion modeling, rupture simulation, source physics
analysis and statistical seismology. For this reason, the estimation of these parameters is often the first step in any analysis of earthquakes, but due to variability in site characterization, network capability and resources different procedures
and methods are often used in their estimation. These issues
and uncertainties depend on length scale, and therefore varyacross magnitudes. For example, high frequency (>10 Hz)
shallow site effects will strongly affect smaller earthquakes(M<3), while larger events are more strongly affected by issues
at lower frequencies. This variability in method and inconsistencies across magnitude scales can yield artifacts which mask

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physical trends, leading to contrasting interpretations of earthquake scaling relationships and earthquake dynamic rupture
processes. For example, catalog magnitude estimation varies
regionally and by event size and network capability, producing
artifacts that can influence important statistics like magnitude
exceedance probabilities. Source parameters quantifying stressand energy release are fundamental to understanding fault
strength and dynamic rupture propagation but can vary byorders of magnitude among studies. Estimating these parameters accurately, or at least uniformly, is needed to understandearthquake mechanics and ground motion hazard.
We seek all interested researchers to compare and validate
source parameter estimates for any magnitude. We encourage
studies that aim to quantify the uncertainties of these measurements, comparative studies of multiple methods and thosethat focus on reliable interpretation of results.
Conveners: Rachel E. Abercrombie, Boston University (rea@bu.edu); Shanna Chu, U.S. Geological Survey (schu@usgs.gov);
Sydney Gable, University of Michigan (gablesyd@umich.edu);
Gene Ichinose, Lawrence Livermore National Laboratory (ichinose1@llnl.gov); Colin N. Pennington, Lawrence Livermore
National Laboratory (pennington6@llnl.gov)

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Technical Sessions, 1133

Overview of Technical Program
Monday 29 April

Tuesday 30 April

Wednesday 1 May

Thursday 2 May

Friday 3 May

7:00 am–6:30 pm

8:00 am–4:30 pm

7:00 am–5:00 pm

7:00 am–5:00 pm

7:00 am–5:00 pm

Prince William Sound
Field Seminar

Alaska Geophysics in
the Field

Registration
Lobby

Registration
Lobby

Registration
Lobby

10:00 am–4:00 pm

8:00–9:15 am

7:15–8:00 am

8:00–9:15 am

Data Mining on the
Cloud 101 Workshop
Tikahtnu Ballroom C,
Third Level

Technical Sessions

GR Briefing
Exhibit Hall

Technical Sessions

10:00 am–4:00 pm

10:30–11:45 am

9:15–10:30 am

Poster BreakExhibit Hall

Technical Sessions
Seismic
11:45 am–2:00 pm
Instrumentation
Lunch BreakWorkshop
Tikahtnu Ballroom E/F, Noon–1:00 pm
Newcomer’s Welcome
Third Level
Lunch*
12:30–4:30 pm
Exhibit Hall
Publishing: How to
Review and How to Be 2:00–3:15 pm
Technical Sessions
Reviewed Workshop
Kahtnu 1, Second Level 3:15–4:30 pm
Poster Break
3:00–7:30 pm
Exhibit Hall
Registration
4:30–5:45 pm

Lobby

Technical Sessions

4:30–6:00 pm

9:15–10:30 am

Technical Sessions

Poster BreakExhibit Hall

9:15–10:30 am

10:30–11:45 am

Poster BreakExhibit Hall

Technical Sessions

8:00–9:15 am

11:45 am–2:00 pm

10:30–11:45 am

Lunch BreakTechnical Sessions

2:00–3:15 pm

Noon–2:00 pm

Technical Sessions

Annual Business andAwards Luncheon
Exhibit Hall

3:15–4:30 pm

2:00–3:15 pm

4:30–5:45 pm

Technical Sessions

Technical Sessions

Poster BreakExhibit Hall

3:15–4:30 pm

Poster BreakExhibit Hall
4:30–5:45 pm

Technical Sessions
Opening Reception andPlenary
6:00–7:00 pm
Exhibits
Tikahtnu
Ballroom
A/B,
Joyner Lecture
Exhibit Hall
Third
Level
Tikahtnu Ballroom
6:00–7:00 pm
7:00–8:00 pm
A/B, Third Level
Plenary
Student/Early-Career
7:00–8:00 pm
Tikahtnu Ballroom A/B,
Reception*
Joyner Reception
Third Level
Exhibit Hall
Tikahtnu Ballroom
Foyer, Third Level
6:00–7:00 pm* Invite only

Volume 95•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1133

Wednesday, 1 May
Oral Sessions
Time

K’enakatnu 6/
Kahtnu 1
Kahtnu 2
Tikahtnu Ballroom
Boardroom
A/B
From Faults to
How Well Can We
Induced Earthquakes: The 2023 USGS
Fjords: Earthquake Predict Broadband
Source CharacterNational Seismic
Evidence in Terres- Site-Specific Ground istics, Mechanisms,
Hazard Model andtrial and Subaqueous Motion and Its Spa- Stress Field Modeling Beyond
Environments
tial Variability So Far? and Hazards

8:00–
9:15 am

9:15–
10:30 am
10:30–
11:45 amTikahtnu Ballroom C
Creating Actionable
Earthquake Information Products

Poster Break
From Faults to
How Well Can We
Induced Earthquakes: The 2023 USGS
Fjords: Earthquake Predict Broadband
Source CharacterNational Seismic
Evidence in Terres- Site-Specific Ground istics, Mechanisms,
Hazard Model andtrial and Subaqueous Motion and Its Spa- Stress Field Modeling Beyond
Environments
tial Variability So Far? and Hazards

11:45 am–Lunch Break
2:00 pm
How Well Can We
Induced Earthquakes: The 2023 USGS
2:00–3:15 pm From Faults toFjords: Earthquake Predict Broadband
Source CharacterNational Seismic
Evidence in Terres- Site-Specific Ground istics, Mechanisms,
Hazard Model andtrial and Subaqueous Motion and Its Spa- Stress Field Modeling Beyond
Environments
tial Variability So Far? and Hazards
3:15–4:30 pm
Poster BreakPlanetary Seismology The OSIRIS-REx
4:30–5:45 pm From Faults toFjords: Earthquake
Sample Return
Evidence in TerresCapsule Re-entry:
trial and Subaqueous
Geophysical ObserEnvironments
vations
6:00–7:00 pm
Plenary: Challenges in Geohazards Research in Alaska
7:00–8:00 pm
Student/Early-Career Reception

Creating Actionable
Earthquake Information Products

Network Seismology: Recent Developments, Challenges
and Lessons Learned

Network Seismology: Recent Developments, Challenges
and Lessons Learned

Poster Sessions• The 2023 USGS National Seismic Hazard Model and Beyond• Creating Actionable Earthquake Information Products• Cryptic Faults: Advances in Characterizing Low Strain Rate and Environmentally Obscured Faults• From Faults to Fjords: Earthquake Evidence in Terrestrial and Subaqueous Environments• How Well Can We Predict Broadband Site-Specific Ground Motion and Its Spatial Variability So Far?
• Induced Earthquakes: Source Characteristics, Mechanisms, Stress Field Modeling and Hazards• Learning Across Geological, Geophysical & Model-Derived Observations to Constrain Earthquake Behavior• Marine Seismoacoustics• Network Seismology: Recent Developments, Challenges and Lessons Learned• Numerical Modeling in Seismology: Developments and Applications• The OSIRIS-REx Sample Return Capsule Re-entry: Geophysical Observations• Special Applications in Seismology• Structure, Seismicity and Dynamics of the Queen Charlotte-Fairweather Fault System• Towards Advancing Earthquake Forecasting and Nowcasting: Recent Progress Using AI-Enhanced Methods• Translating Seismic Imaging into Geodynamic Understanding

1134

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Seismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

8:00–
9:15 amEarth’s Structure from the
Crust to the Core

Cryptic Faults: Advancesin Characterizing Low
Strain Rate and Environmentally Obscured Faults

Numerical Modeling inSeismology: Developments and Applications

Learning Across Geological, Geophysical & ModelDerived Observations toConstrain Earthquake
Behavior

9:15–
10:30 am
10:30–
11:45 amPoster BreakEarth’s Structure from the
Crust to the Core

Cryptic Faults: Advancesin Characterizing Low
Strain Rate and Environmentally Obscured Faults

Numerical Modeling inSeismology: Developments and Applications

11:45 am–Lunch Break
2:00 pm
2:00–3:15 pm Earth’s Structure from the Towards Advancing Earth- Numerical Modeling in
Crust to the Core
quake Forecasting andSeismology: DevelopNowcasting: Recent Prog- ments and Applications
ress Using AI-Enhanced
Methods
3:15–4:30 pm
Poster BreakSpecial Applications inTranslating Seismic Imag4:30–5:45 pm Marine Seismoacoustics
Seismology
ing into Geodynamic
Understanding

6:00–7:00 pm
7:00–8:00 pm

Volume 95•

Learning Across Geological, Geophysical & ModelDerived Observations toConstrain Earthquake
Behavior

Learning Across Geological, Geophysical & ModelDerived Observations toConstrain Earthquake
Behavior
Structure, Seismicity andDynamics of the Queen
Charlotte-Fairweather
Fault System

Plenary: Challenges in Geohazards Research in Alaska
Student/Early-Career Reception

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1135

Thursday, 2 May
Oral Sessions
Time

K’enakatnu 6/Boardroom

8:00–
9:15 am

3D Wavefield Simulations: Illuminating Complex,
Detecting, Characterizing
From Seismic Imaging to Multiplet Earthquake
and Monitoring Mass
Ground Motion Modelling Sequences at KahramanMovements
maras (Turkiye), Herat(Afghanistan), and Beyond

9:15–
10:30 am
10:30–
11:45 amNoon–
2:00 pm
2:00–
3:15 pm

3:15–
4:30 pm
4:30–
5:45 pm

6:00–
7:00 pm
7:00–
8:00 pm

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B
Seismic Monitoring, Modelling and Management
Needed for Geothermal
Energy and Geologic Carbon Storage

Poster Break
3D Wavefield Simulations: Illuminating Complex,
Detecting, Characterizing
From Seismic Imaging to Multiplet Earthquake
and Monitoring Mass
Ground Motion Modelling Sequences at KahramanMovements
maras (Turkiye), Herat(Afghanistan), and Beyond

Seismic Monitoring, Modelling and Management
Needed for Geothermal
Energy and Geologic Carbon Storage

Annual Business and Awards Luncheon
3D Wavefield Simulations: Six Decades of Tsunami
From Seismic Imaging to Science: From the Source
Ground Motion Modelling of the 1964 Tsunami toModern Community Preparedness

Detecting, Characterizing
and Monitoring Mass
Movements

Seismic Monitoring, Modelling and Management
Needed for Geothermal
Energy and Geologic Carbon Storage

Poster BreakApplications and Discov- Special Applications ineries in Cryoseismology
Seismology
Across Spatial and Temporal Scales

New Insights into theDevelopment, Testing
and Communication ofSeismicity Forecasts

Joyner Lecture: Why Seismic Hazard Modeling Has Become a Risky Business
Joyner Reception

Poster Sessions• 3D Wavefield Simulations: From Seismic Imaging to Ground Motion Modelling• Advancements in Forensic Seismology and Explosion Monitoring• Applications and Discoveries in Cryoseismology Across Spatial and Temporal Scales• Characteristics and Mechanics of Fault Zone Rupture Processes, from Micro to Macro Scales• Cordilleran Strike-Slip Faults as Seismogenic and Seismological Features• Detecting, Characterizing and Monitoring Mass Movements• Earth’s Structure from the Crust to the Core
• From Earthquake Recordings to Empirical Ground-Motion Modelling• Illuminating Complex, Multiplet Earthquake Sequences at Kahramanmaras (Turkiye), Herat (Afghanistan), and Beyond• Leveraging Cutting-Edge Cyberinfrastructure for Large Scale Data Analysis and Education• Multidisciplinary Approaches for Volcanic Eruption Forecasting• New Insights into the Development, Testing and Communication of Seismicity Forecasts• Seismic Monitoring, Modelling and Management Needed for Geothermal Energy and Geologic Carbon Storage• Seismology in the Oceans: Pacific Hemisphere and Beyond• Six Decades of Tsunami Science: From the Source of the 1964 Tsunami to Modern Community Preparedness
1136|

Seismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C Tikahtnu Ballroom
E/F
Characteristics and Advancements in
Mechanics of Fault
Forensic SeismolZone Rupture Proogy and Explosion
cesses, from Micro to Monitoring
Macro Scales

8:00–
9:15 am

9:15–
10:30 am
10:30–
11:45 am

Tubughnenq’ 4

Tubughnenq’ 5

Seismology in the
Oceans: Pacific
Hemisphere andBeyondFrom Earthquake
Recordings to
Empirical GroundMotion Modelling

Network Seismology: Recent Developments, Challenges
and Lessons Learned

From Earthquake
Recordings to
Empirical GroundMotion Modelling

Network Seismology: Recent Developments, Challenges
and Lessons Learned

Poster BreakCharacteristics and Advancements in
Mechanics of Fault
Forensic SeismolZone Rupture Proogy and Explosion
cesses, from Micro to Monitoring
Macro Scales

Noon–
2:00 pm
2:00–
3:15 pm

Seismology in the
Oceans: Pacific
Hemisphere andBeyondAnnual Business and Awards Luncheon
Regional-Scale Hazard, Risk and Loss
Assessments

3:15–
4:30 pm
4:30–
5:45 pm

Advancements in
Forensic Seismology and Explosion
Monitoring

Multidisciplinary
Approaches for
Volcanic Eruption
Forecasting

From Earthquake
Recordings to
Empirical GroundMotion Modelling

Network Seismology: Recent Developments, Challenges
and Lessons Learned

Leveraging CuttingEdge Cyberinfrastructure for Large
Scale Data Analysis
and Education

Cordilleran StrikeSlip Faults as Seismogenic and Seismological Features

Poster BreakRegional-Scale Hazard, Risk and Loss
Assessments

6:00–
7:00 pm
7:00–
8:00 pm

Volume 95

Tubughnenq’ 3

Advancements in
Forensic Seismology and Explosion
Monitoring

Multidisciplinary
Approaches for
Volcanic Eruption
Forecasting

Joyner Lecture: Why Seismic Hazard Modeling Has Become a Risky Business
Joyner Reception•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1137

Friday, 3 May
Oral Sessions
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

8:00–
9:15 amAdvancing Seismology
with Distributed Fiber
Optic Sensing

Physics-Based Ground
Motion Modeling

Seismoacoustic, Geodetic
and Other GeophysicalInvestigations of Active
Volcanoes

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone

9:15–
10:30 am
10:30–
11:45 am

11:45 am–
2:00 pm
2:00–
3:15 pm

3:15–
4:30 pm
4:30–
5:45 pm

Poster BreakAdvancing Seismology
with Distributed Fiber
Optic Sensing

Physics-Based Ground
Motion Modeling

Seismoacoustic, Geodetic
and Other GeophysicalInvestigations of Active
Volcanoes

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone

Lunch BreakAdvancing Seismology
with Distributed Fiber
Optic Sensing

Assessing Seismic Hazard
for Critical Facilities andInfrastructure—Insights
and Challenges

Seismoacoustic, Geodetic
and Other GeophysicalInvestigations of Active
Volcanoes

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone

Poster Break
From Geodynamics toAssessing Seismic Hazard
Earthquake Rupture, Mod- for Critical Facilities andels That Cross Time- and Infrastructure—Insights
Length-Scales
and Challenges

Machine Learning for Full Structure and Behavior
Waveform Inversion: From of the Alaska-AleutianHybrid to End-to-End
Subduction Zone
Approaches

Poster Sessions• The 2024 Magnitude 7.5 Earthquake and the Associated Earthquake Swarm Beneath the Noto Peninsula, Central Japan• Advances in Operational and Research Analysis of Earthquake Swarms• Advancing Seismology with Distributed Fiber Optic Sensing• Anisotropy Across Scales• Assessing Seismic Hazard for Critical Facilities and Infrastructure—Insights and Challenges• End-to-End Advancements in Earthquake Early Warning Systems• ESC-SSA Joint Session: Climate Change and Environmental Seismology• From Geodynamics to Earthquake Rupture, Models That Cross Time- and Length-Scales• Integrative Assessment of Soil-Structure Interaction and Local Site Effects in Seismic Hazard Analysis

1138

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Seismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C Tikahtnu Ballroom
E/F
The 2024 Magnitude End-to-End
7.5 Earthquake
Advancements inand the AssociatedEarthquake Early
Earthquake Swarm Warning Systems
Beneath theNoto Peninsula,
Central Japan(See Supplemental
Material)

8:00–
9:15 am

9:15–
10:30 am
10:30–
11:45 am

Tubughnenq’ 4

Understanding and Anisotropy AcrossQuantifying the Vari- Scales
ability in Earthquake
Source Parameter
Measurements

Tubughnenq’ 5
Tectonics andSeismicity of Stable
Continental Interiors

Poster BreakThe 2024 Magnitude
7.5 Earthquake
and the AssociatedEarthquake Swarm
Beneath theNoto Peninsula,
Central Japan(See Supplemental
Material)

11:45 am–
2:00 pm
2:00–
3:15 pm

End-to-End
Advancements inEarthquake Early
Warning Systems

Understanding and Anisotropy AcrossQuantifying the Vari- Scales
ability in Earthquake
Source Parameter
Measurements

Tectonics andSeismicity of Stable
Continental Interiors

Lunch BreakESC-SSA Joint Ses- End-to-End
sion: Climate Change Advancements inand Environmental Earthquake Early
Seismology
Warning Systems

3:15–
4:30 pm
4:30–
5:45 pm

•
•
•
•
•
•
•
•
•

Tubughnenq’ 3

Understanding and Advances in OperaQuantifying the Vari- tional and Researchability in Earthquake Analysis of EarthSource Parameter
quake Swarms
Measurements

Tectonics andSeismicity of Stable
Continental Interiors

Poster BreakESC-SSA Joint Ses- End-to-End
sion: Climate Change Advancements inand Environmental Earthquake Early
Seismology
Warning Systems

Advances in Operational and Research
Analysis of Earthquake Swarms

Tectonics andSeismicity of Stable
Continental Interiors

Machine Learning for Full Waveform Inversion: From Hybrid to End-to-End Approaches
Physics-Based Ground Motion Modeling
Regional-Scale Hazard, Risk and Loss Assessments
Research Advances in “High-Impact”, “Under-Studied” Earthquakes and Their Impacts on Communities
Seismic Cycle-Driven Sea-Level Change Over Decades to Centuries: Observations and Projections
Seismoacoustic, Geodetic and Other Geophysical Investigations of Active Volcanoes
Structure and Behavior of the Alaska-Aleutian Subduction Zone
Tectonics and Seismicity of Stable Continental Interiors
Understanding and Quantifying the Variability in Earthquake Source Parameter Measurements

Volume 95•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1139

Wednesday, 1 May 2024—Oral Sessions
Presenting author is indicated in bold.
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

From Faults to Fjords:
Earthquake Evidence inTerrestrial and Subaqueous
Environments (see page1296).

How Well Can We Predict
Broadband Site-Specific
Ground Motion and Its
Spatial Variability So Far?
(see page 1311).

Induced Earthquakes:
Source Characteristics,
Mechanisms, Stress Field
Modeling and Hazards (seepage 1322).

The 2023 USGS National
Seismic Hazard Model and
Beyond (see page 1194).

8:00 am

Effect of Marine Reservoir
Variations on the Temporal
Correlation of Earthquake
Evidence on the Central
and Southern Hikurangi
Subduction Zone. Clark,
K. J., Pizer, C., Howarth, J.,
Litchfield, N., Howell, A.

Student: Site Response
Invited: Structural Controls
Characteristics from Ambient on Induced Earthquake
Noise Data Recorded on
Sequence’s Growth and Slip
Degrading Warm Permafrost Behavior. Pennington, C. N.,
in Bethel, Alaska. Goozen, A., Chen, X.
Zhao, Y., Dutta, U., Yang, Z.

8:15 amInvited: An 8000-Year
Improving the Performance
Holocene Earthquake Record of the SSRh Site-Response
From the Northern Cascadia Assessment Techniques on a
Forearc: Evidence for Multiple Dense Array in the Koutavos
Sources at Lake Crescent,Basin (Greece). Perron, V.,
Washington. Leithold, E. L., Rischette, P., Theodoulidis,
Wegmann, K., Colip, G. D.
N., Roumelioti, Z., Hollender,F., et al.

Seismic Hazard Analysis for
Hydraulic-Fracture Triggered
Earthquakes in Oklahoma.
Walter, J., Ogwari, P. O.,
Thiel, A., Woelfel, I., Mace,
B., et al.

The 2023 U.S. 50-State
National Seismic Hazard
Model: Overview and
Implications. Petersen, M. D.,
Project Team, N.

8:30 amVariations in Mass Transport
Deposits That Record Strong
Ground Motion Events in
Western Prince WilliamSound, Alaska. Singleton, D.
M., Brothers, D. S., Haeussler,
P. J., Witter, R. C., Hill, J. C.,
et al.

Undocumented Cases
of Induced Seismicity in
Oklahoma and Texas.
Grigoratos, I., Savvaidis, A.

The 2023 Alaska National
Seismic Hazard Model.
Powers, P. M., Altekruse, J.
M., Development Team, N.

1140

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Seismological Research Letters

A Simple Way of Estimating
Site Effect With Respect to a
Distant Rock-Reference Site:
Application of the Standard
Spectra Ratio Technique
Based on Coda Waves.
Grendas, I., Hollender, F.,
Perron, V., Theodoulidis, N.,
Buscetti, M., et al.

www.srl-online.org•

Volume 95

Recommendations on Best
Available Science for theUnited States National
Seismic Hazard Model.
Anderson, J. G., Atkinson, G.
M., Baker, J. W., Campbell, K.
W., DeShon, H. R., et al.

•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4Creating Actionable
Earthquake
Information Products(see page 1251).

Earth’s Structure fromthe Crust to the Core(see page 1268).

Cryptic Faults:
Advances in
Characterizing Low
Strain Rate andEnvironmentally
Obscured Faults (seepage 1256).

Numerical Modeling Learning Acrossin Seismology:
Geological,
Developments andGeophysical & ModelApplications (see page Derived Observations
1369).
to Constrain
Earthquake Behavior(see page 1331).

8:00 amInvited: Student:
Student: A HighImproving Rapid
Resolution Body Wave
Earthquake
Tomography SuperCharacterization
Virtual Interferometry
for Tsunami Earlyof the Rio Grande Rift.
Warning for Aotearoa
Barman, D., Pulliam, J.
New Zealand and theSouthwest Pacific.
Lacoua, L. Z., Fry, B.,
Gorman, A., Liao, Y. M.,
Foundotos, L., et al.

Invited: Student:
An Ongoing Search
for Active Faults in
Major Seismic Zonesof Québec, Eastern
Canada. Gourdeau,A., Wang, K., Laly, M.,
Prush, V. B., Rowe, C.,et al.

Student: Reflection
and Transmissionof Inhomogeneous
Plane Waves in
Thermoporoelastic
Media with Twotemperature Equationsof Heat Conduction.
Hou, W., Fu, L.,
Carcione, J.

8:15 amSite-Specific,
Extended Shakemaps
for Earthquake
Engineering
Applications.
Thompson, E. M.,
Hearne, M., Worden,
C. B., Quitoriano, V.,
Cunningham, A. E.,
et al.

Invited: The Poisson’s
Raio Surrounding the
Subduction Megathrust.
Mann, M., Abers, G. A.,
Fulton, P. M.

Timescales of Surface
Faulting Preservationin Stable Continental
Regions From
Landscape Evolution
Modeling and the
Geomorphic andHistorical Record.
Thompson Jobe, J. A.,
Reitman, N.

Student: Dynamic
Partitioning of Oblique
Rupture Simulation
Convergence Duringof Caldera Collapse
Simultaneous Rupture
Earthquakes: Effects
of a Megathrustof Wave Radiation,and Splay Fault:
Magma Viscosity, and Observations From the
Evidence of Complex Western Nepal Fault
Nucleation at Kīlauea System. Bemis, S.,
2018. Wang, T. A.,
Curtiss, E. R., Murphy,
Dunham, E. M., Krenz, M. A., Taylor, M. H.,
L., Abrahams, L. S.,
Styron, R., et al.
Segall, P.

8:30 amInvited: Geonet’s
Shaking Layer Tool:
Understanding andIncorporating User
Needs into Shaking
Layers for Aotearoa,
New Zealand.
Charlton, D.,
Houltham, J., Horspool,N., Goded, T., Kaiser,A., et al.

Improving the Salt Lake
Basin Velocity Model
Using Multi-Year Nodal
Geophone Arrays. Kim,
H., Lin, F., Pechmann,
J. C., McKean, A. P.,
Hardwick, C. L., et al.

The 2018 Kaktovik,
Alaska Earthquakes
and Their Context:
Insights From
Seismotectonics,
Insar Geodesy,and Static Stress
Changes. Rollins, C.,
Freymueller, J. T., Xue,
X., Holtkamp, S. G.,
Logan, T. A., et al.

What Is the Principal
Accuracy Limit of a
Seismic Wavefields
Simulated by a FiniteDifference Method?.
Valovcan, J., Moczo, P.,
Kristek, J., Kristekova,
M., Galis, M.

Volume 95•

Number 2B•

April 2024•

www.srl-online.org

Tubughnenq’ 5Strain Accommodation
Along the Northeast
Altyn Tagh Fault
System and thePotential for a Future
Large-Magnitude,
Multi-Fault Rupture.
Yang, H., Yang, X.,
Cunningham, D.,
Huang, X.

Student: Architectureof an Active
Tsunamigenic Splay
Fault: Outcrop to
Micro-Scale Structureof the Patton Bay Fault,
Montague Island,
Alaska. Fintel, A.,
Tobin, H., Haeussler, P.

Seismological Research Letters

|

1141

Wednesday, 1 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

From Faults to Fjords:
Earthquake Evidence (continued)

How Well Can We Predict
Broadband Site-Specific
Ground (continued)

Induced Earthquakes:
Source Characteristics,
Mechanisms (continued)

The 2023 USGS National
Seismic Hazard Model and
Beyond (continued)

8:45 amStudent: Long Lacustrine
Sedimentary Records inSouth-Central Chile Evaluate
the Spatiotemporal Variabilityof Megathrust Earthquakes.
Niederstätter, M., Moreno,
V., Wils, K., Van Daele, M.,
Konzett, J., et al.

CD-VAE-GMG: Conditional
Dynamic Variational
Autoencoder for Earthquake
Ground Motion Generation.
Ren, P., Naiman, I., Lacour,M., Nakata, R., Nakata, N.,et al.

Regional Moment Tensors
for Texas. Herrmann, R. B.,
Benz, H. M.

Another Look at TimeDependent Hazard andits Implications to Seismic
Design in Southeastern
Alaska. Wong, I.,
Lewandowski, N., Thomas, P.

9:00 am

Quantitative Calibration of
the Lacustrine Seismograph
Using Sedimentary Imprints
of Recent Megathrust
Earthquakes in South-Central
Chile. Wils, K., Montalva, G.,
Moernaut, J., Van Daele, M.,
De Batist, M.

Euro-Mediterranean HardRock Reference Ground
Motion Model by Git-Based
Site Response Deconvolution.
Shible, H., Hollender, F.,
Traversa, P., Baumont, D.,
Ameri, G., et al.

Cross-Examining Methods
for Determining Source
Mechanisms for Induced
Earthquakes in the Permian
Basin. Aziz Zanjani, F.,
Savvaidis, A., Huang, G. D.,
Domino, J., Chen, Y.

USGS 2025 Puerto Ricoand the U.S. Virgin Islands
National Seismic Hazard
Model Update. Shumway, A.
M., Aagaard, B. T., Altekruse,
J. M., Briggs, R. W., Field, E.
H., et al.

9:15–10:30 am

10:30 am

1142|

Poster Break
From Faults to Fjords:
Earthquake Evidence inTerrestrial and Subaqueous
Environments (see page1296).

How Well Can We Predict
Broadband Site-Specific
Ground Motion and Its
Spatial Variability So Far?
(see page 1311).

Induced Earthquakes:
Source Characteristics,
Mechanisms, Stress Field
Modeling and Hazards (seepage 1322).

Seismic Imaging BeneathIceberg Lake, Alaska:
Sediment Characteristics
and Fundamental Site
Response Parameters Beneatha Drained Lake With an
Alaskan-Aleutian Subduction
Zone Paleoseismic Record.
Liberty, L. M., Haeussler, P.
J., Otheim, L. T., Singleton, D.
M., Wesson, R. L., et al.

Observed Strong Motions
and Site Effects During theJan. 1, 2024 Noto-Hanto
Earthquake in Japan and Its
Reproduction Based on a
Priori Information. Kawase,
H., Ito, E., Sun, J.

Spatiotemporal Evolution of
Next Steps for USGS
Induced Earthquakes in the
Earthquake Rupture Forecast
Southern Delaware Basin,
Developments. Field, E. H.
Reeves-Pecos, West Texas.
Aziz Zanjani, A., DeShon, H.
R., Savvaidis, A.

Seismological Research Letterswww.srl-online.org•

Volume 95

The 2023 USGS National
Seismic Hazard Model and
Beyond (see page 1194).

•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5Creating Actionable
Earthquake (continued)

Earth’s Structure fromthe Crust to the Core
(continued)

Cryptic Faults: (continued)

Numerical Modelingin (continued)

Learning AcrossGeological, (continued)

8:45 am

Improved Rapid
Source and Shaking
Characterization Using
Large Seismic Array
Observations. Wang,
D., Chen, W., Wald, D.

Seismic Structure of
Northern Alaska From
Ambient Noise Adjoint
Tomography. Chow, B.,
Tape, C.

Deciphering LowRate Faulting on theLandscape Above
the Marsh Creek
Anticline in Arctic
Alaska. Bender,
A. M., Craddock,W., Connors, C. D.,
Gooley, J., Lease, R. O.

Modeling the Seismic Invited: Paleoseismic
Noise Horizontal-toInvestigations ofVertical Spectral Ratio Quaternary Activein Laterally IrregularFaults in the Forearc
Configurations Using and Backarc of
the Diffuse Field
the Central Pacific
Assumption. Sanchez- Northwest, U.S.A.
Sesma, F. J., Weaver,Streig, A. R., Dunning,
R. L., Baena-Rivera, M. A., Bennett, S. E.,
E., Pardo-Dañino, J. C., Madin, I., Wells, R. E.,
Arciniega-Ceballos, A. et al.

9:00 am

A Growing Catalogueof Short-Period
Earthquake Rupture
Histories From MultiArray Back-Projection.
Vera Sanhueza, F.,
Tilmann, F., Saul, J.

Using Local andRegional Travel Time
Data From the ISC to
Estimate Lithospheric
Velocity Structure.
Pasyanos, M. E.

Student: Utilising
UAV Lidar toInvestigate Potential
Late Quaternary
Surface Ruptures
Along the San Juan
Fault on Vancouver
Island, BC. Salomon,
G. W., Finley, T.,
Nissen, E.

The Ongoing
Development ofDistributional
Finite-difference
Modeling in Global
Seismology. Lyu, C.,
Masson, Y., Awan, M.,
Romanowicz, B.

9:15–10:30 am

10:30 amVolume 95•

Coseismic Temperature
Proxies and their
Applications to
Understanding
Earthquake Ruptureand Seismic Hazard.
Coffey, G. L., Savage,
H. M., Polissar, P. J.,
Cox, S. E., Hemming,
S. R., et al.

Poster BreakCreating Actionable
Earthquake
Information Products(see page 1251).

Earth’s Structure fromthe Crust to the Core(see page 1268).

Cryptic Faults:
Advances in
Characterizing Low
Strain Rate andEnvironmentally
Obscured Faults (seepage 1256).

Visual Communicationof Aftershock Forecasts
Driven by User Needs.
Schneider, M., Wein,
A. M., van der Elst, N.,
McBride, S. K., Becker,J., et al.

Intraplate Volcanism
in Northeast China
Controlled by
the Underlying
Heterogeneous
Lithospheric Structures.
Chen, Q., Fan, X., Ai, Y.

Invited: Late
Numerical Simulation
Pleistocene andof Strong GroundProtohistoric
Motion for the Mw 6.0
Earthquakes on
Jishishan Earthquake
Forelimb Thrustsof 18 December 2023
Within the Seattle Fault in Gansu Province,
Zone: Implications for China. Zang, N.,
Independent Hanging Zhang, W., Chen, X.
Wall Deformation
Rates. Angster, S.,
Sherrod, B. L., Staisch,L., Pearl, J. K., Johns,
W.

Number 2B•

April 2024•

www.srl-online.org

Numerical Modeling Learning Acrossin Seismology:
Geological,
Developments andGeophysical & ModelApplications (see page Derived Observations
1369).
to Constrain
Earthquake Behavior(see page 1331).
Inter-Seismic Slipin Caldera Collapse
Earthquake Cycles.
Crozier, J. A.,
Anderson, K. R.,
Segall, P.

Seismological Research Letters

|

1143

Wednesday, 1 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

From Faults to Fjords:
Earthquake Evidence (continued)

How Well Can We Predict
Induced Earthquakes:
Broadband Site-SpecificSource Characteristics,
Ground Motion (continued) Mechanisms, (continued)

The 2023 USGS National
Seismic Hazard Model and
Beyond (continued)

10:45 am

The Subaerially Exposed
Iceberg Lake Sediments: A~1000 Yr Long Paleoseismic
Record From the Eastern
Edge of the Alaska
Subduction Zone. Van Daele,
M., Vercruysse, P., Witter, R.
C., Loso, M., Singleton, D.,et al.

Exploring the Spatial
Correlation of Ground
Motions During the 2019
Ridgecrest Earthquake
Sequence. Cochran, E. S.,
Parker, G. A., Minson, S. E.,
Baltay, A. S.

Seismicity Triggering in the
North Delaware Basin, West
Texas, USA. Savvaidis, A.,
Lomax, A., Huang, G., Chen,
Y., Alvarez, N., et al.

Earthquake Geology
Contributions Across the
U.S. Geological Survey 2023
50-State National Seismic
Hazard Model. Hatem, A. E.,
Briggs, R., Thompson Jobe, J.
A., Gold, R., Collett, C., et al.

11:00 am

The Great Salt Lake as a
Recorder of Sublacustrine
Surface Rupture and Strong
Shaking in the Wasatch Front
Region, Utah. DuRoss, C. B.,
Brothers, D. S., Thompson
Jobe, J. A., Briggs, R. W.,
Singleton, D. M., et al.

Student: Use of Weak
Motion Data to Constrain
Site-Specific Ground Motion
Estimates. Anbazhagan,
B., Rodriguez-Marek, A.,
Vantassel, J., Kottke, A.

Invited: Potential Poroelastic
Triggering of the 2020 M 5.0
Mentone Earthquake in the
Delaware Basin, Texas, by
Shallow Injection Wells. Lui,
S., Tan, X.

Continued Work on a
Geodetic Strain Rate and Slip
Deficit Rate Model for New
Zealand. Rollins, C., Wallace,
L. M., Johnson, K. M.,
Maurer, J., Hamling, I., et al.

11:15 amSediment Shear Strength
Development Within
Terminal Basins of theJapan Trench and Lower
Slope: Insights Into
Seismic Strengthening andEarthquake Paleoseismology
From R/V Sonne Expedition
SO251 (Eager-Japan) and
IODP Expedition 386.
Sawyer, D. E., Strasser, M.

Ergodic and Non-Ergodic
Ground-Motion Models for
Small Magnitude Earthquakes
in the San Francisco Region.
Lacour, M., Abrahamson, N.
A., Nakata, R., Nakata, N.,
Ren, P.

Using Converted Phases toCorrelation of Epistemic
Investigate Induced Seismicity Uncertainties in Seismic
in the Midland Basin, Texas. Hazard Models: An NSHM23
DeShon, H. R., Rosenblit, J., Case Study for Western U.S.
Huang, G., Savvaidis, A.
Faults. Milner, K. R.

11:30 amStudent: Beyond the Waves:
Integrating Rock Physical
Properties for Deeper Seismic
Understanding. Castillo, R.,
Sawyer, D. E., Srasser, M.,
Keep, M.

Comparison of the Spatial
Correlation of Non-Ergodic
Terms in GMMs Utilizing
Empirical and Simulation
Data From Diverse Regions.
Sung, C., Abrahamson, N. A.

Student: Fault Reactivation
During Induced Seismicity
Sequences in Southern
Kansas. Ries, R., Beroza, G.,
Ellsworth, W.

11:45 am–
2:00 pm

1144|

Seismological Research Letters

Kahtnu 2

Tikahtnu Ballroom A/B

Enhancing DecisionMaking Stability in Model
Updates Through Explicit
Consideration of Epistemic
Uncertainty in Seismic
Hazard and Risk Assessments.
Lee, Y.

Lunch Breakwww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3Creating Actionable
Earthquake (continued)

Earth’s Structure fromthe Crust to the Core
(continued)

Cryptic Faults:
Numerical Modeling
Advances (continued) in Seismology (continued)

Learning AcrossGeological, (continued)

10:45 amTomorrow’s Cities:
An Interdisciplinary
Decision Support
Environment for
Risk Sensitive Urban
Planning and Design.
Galasso, C. and theTomorrow’s Cities
Programme Working
Group

Seismic Evidence for a
Melt-Rich LithosphereAsthenosphere
Boundary Along theBase of Young Slab at
Cascadia. Wang, X.,
Chen, L., Wang, K.,
Chen, Q., Zhan, Z., et al.

Recurrence of
Large Upper-Plate
Earthquakes in the
Salish Lowland,
Washington State,USA. Sherrod, B. L.,
Styron, R.

A Detailed Analysis ofBody Waves Simulatedin HomogenizedMedia. Cupillard, P.,
Mulder, W., Anquez,P., Mazuyer, A., Zakari,M., et al.

Invited: The Influenceof Preexisting Geologic
Structures on Coseismic
Surface Deformation
During the 2019 M7.1
Ridgecrest, California,
Earthquake. Nevitt, J.
M., Brooks, B., Baden,
C., Hardebeck, J.,
Aagaard, B. T., et al.

11:00 am

Exploring the
Ethical Tensions andCommunication
Challenges of Publicly
Available Global
Aftershock Forecasting
From Science
Agencies. McBride,
S. K., Michael, A.
J., Schneider, M.,
Hardebeck, J., Wein, A.
M., et al.

Student: Mantle
Upwelling, Continental
Sutures, and LAB
Structure Identified
From a Suite of Seismic
Data Types in the
Eastern United States.
Brunsvik, B. R., Eilon,
Z., Lynner, C.

Towards Improved
Understanding ofRegional Tectonics
and Faulting at
the Mendocino
Triple Junction
from Geomorphic
Investigation. DeLong,
S. B., Vermeer, J.,
Patton, J. R., Sion, B.,
Hammer, M., et al.

Efficient Lossy
Compression of
Simulated 4d Seismic
Wavefields. Zhang, W.,
Wang, W., Tang, Y.,
Lei, T.

Student: Bayesian
Dynamic Source
Inversion of the 2004
Parkfield Earthquake:
Insights From Linked
3D Dynamic Ruptureand Afterslip ModelingConstrained by Gps
and Strong Motions.
Schliwa, N., Gabriel,
A. A., Premus, J.,
Gallovič, F.

11:15 amStudent: Development Student: Crustalof Rapid Earthquake
Structure of Eritrea
Damage Estimationfrom Receiver Function
System to Expedite
Analysis. Gauntlett, M.
Rescue Efforts in theZ., Stephenson, S. N.,
Post-Disaster Phase.
Kendall, J., Ogden, C.,
Patchett, M., Hobbs,
Hammond, J. O. S., et al.
T. E.

Geophysical Validation Student: Effects ofof Tidally Calibrated
Dip Angle on Rupture
Strains From the Novel Propagation Along
Alto Tiberina Near
Branch Fault Systems.
Fault Observatory
Marschall, E., Douilly,
Strainmeter ArrayR.
(TABOO-NFO-STAR).
Hanagan, C. E.,
Mandler, E., Bennett,
R. A., Chiaraluce, L.,
Gottlieb, M., et al.

Multi-Cycle Evolutionof Seismicity and
Fault Zone for a Fault
Network. Mia, M.,
Abdelmeguid, M.,
Elbanna, A. E.

11:30 am

Improving the Usability Surface-Wave Diffraction The Pargueraof Near-Real-Time
Stripes: Measurement,
Fault: Quaternary
Earthquake Information Observables,
Reactivation of a Fault
for Equity-Focused
Explanation, Modelingin Southwest Puerto
Decision-Making
and Inversion. Kolínský, Rico. Thompson Jobe,
Through Earthquake
P., Belinić Topić, T.,
J. A., Briggs, R., Ortega
Scenario Exercises.
Vecsey, L., Working
Diaz, V., Hughes, K.,
Macías, M. A., Loos, S., Group, t.
López-Venegas, A.,
Reddy, E., Wald, D. J.,
et al.
Knodel, E. J., et al.

11:45 am–
2:00 pm

Volume 95

Tubughnenq’ 4

Insight From 3D
Deterministic Ground
Motion Simulations inCentral Italy. Akinci,
A., Pitarka, A., De
Gori, P., Artale Harris,
P., Buttinelli, M.

Tubughnenq’ 5

Bayesian Inferenceof RheologicalParameters From
Observations Before
and After the Tohoku
Earthquake. Marsman,C., Vossepoel, F.,
D’Acquisto, M., vanDinther, Y., Govers, R.

Lunch Break•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1145

Wednesday, 1 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

From Faults to Fjords:
Earthquake Evidence inTerrestrial and Subaqueous
Environments (see page1296).

How Well Can We Predict
Broadband Site-Specific
Ground Motion and Its
Spatial Variability So Far?
(see page 1311).

Induced Earthquakes:
Source Characteristics,
Mechanisms, Stress Field
Modeling and Hazards (seepage 1322).

The 2023 USGS National
Seismic Hazard Model and
Beyond (see page 1194).

2:00 pm

Repeated Coseismic Upliftof Coastal Lagoons Above
the Patton Bay Splay Fault
System, Montague Island,
Alaska, USA. DePaolis,J., Dura, T., Witter, R. C.,
Haeussler, P. J., Bender, A.,et al.

Toward an Alternative
Approach for Using VS
Profiles in Estimating Seismic
Site Response. Pretell, R.,
Katuwal, S.

Detailed Analysis of
Microseismic Activity
Associated with Shutdowns of
the San Emidio Geothermal
Plant, Nevada. Thurber, C.
H., Guo, H., Cunningham,
E., Roecker, S. W., Hampton,J., et al.

Subduction Ground Motion
Models for Cascadia in the2023 USGS National Seismic
Hazard Model. Rezaeian, S.,
Powers, P. M., Altekruse, J.,
Ahdi, S. K., Petersen, M. D.,
et al.

2:15 pm

Re-Examination of the 1958
Resonance vs Shape of
Huslia Earthquake Sequence Sedimentary Basins.
and Regional Tectonics of the Castellaro, S., Musinu, G.
Northwestern Koyukuk Basin,
Alaska in Light of Post-1974
Seismicity, Mapped Faults andGeophysical Data. Doser, D.
I., Baker, M. R., Haeussler,
P. J.

Source Characteristics ofMicroseismicity Occurring
During Operational
Shut-in Periods at the Coso
Geothermal Field, California.
Holmgren, J. M., Kaven, J.,
Oye, V.

Ground-Motion
Characterization of Puerto
Rico and the U.S. Virgin
Islands for the 2025 Updateof the USGS National Seismic
Hazard Model. Aagaard, B.
T., Smith, J. A., Moschetti, M.
P., Stephenson, W. J., Ahdi,
S. K.

2:30 pm

Confirmation of Late
Quaternary Surface Faulting
and Preliminary Slip Rates
for the Iditarod-Nixon Fork
Fault and the Boss Creek andHolitna Sections of the Denali
Fault in West-Central Alaska.
Zellman, M., Duckworth, W.,
Koehler, R. D., Zaleski, M. P.,
Ostenaa, D. A., et al.

Student: Double-Pair
Double-Difference Relocation
for Dense Network Improves
Depth Precision of Induced
Seismicity, Leading to a
Detailed 3D Fault Geometry
Model. Biegel, K., Dettmer, J.,
Igonin, N., Eaton, D.

Student: Development of
Ground Motion Models
in Central and Eastern
United States for Use in
the Coastal Plain Using
Sediment Thickness. Akhani,M., Davatgari Tafreshi, M.,
Pezeshk, S.

1146

|

Seismological Research Letters

Impact of Shallow Subsurface
Stratigraphic Architecture
on Shear-Wave Velocity
Prediction: Examples From
the Po Plain and Other
Coastal Lowlands of Italy.
Amorosi, A., Di Martino, A.

www.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tubughnenq’ 3

Tubughnenq’ 4

Network Seismology: Earth’s Structure from
Recent Developments, the Crust to the Core
Challenges and(see page 1268).
Lessons Learned (seepage 1353).

Towards Advancing
Earthquake
Forecasting andNowcasting: Recent
Progress Using
AI-Enhanced
Methods (see page1443).

Numerical Modeling Learning Acrossin Seismology:
Geological,
Developments andGeophysical & ModelApplications (see page Derived Observations
1369).
to Constrain
Earthquake Behavior(see page 1331).

2:00 pm

ISC: CollaboratingWith Seismic Networks
Worldwide. Storchak,D., Harris, J., Di
Giacomo, D., Garth, T.,
Gallacher, R., et al.

Student: The
Continental Collision
and Rifting in East
North America Margin
Revealed by Full
Waveform Tomography.
Lei, T., Wang, K., He, B.,
Du, N., Liu, T., et al.

Towards Deep-Learned Student: The 2022
Picking at the USGS
Mw 6.6 Menyuan
National Earthquake
Earthquake, Qinghai,
Information Center.
China: An EarlyWells, D., Yeck, W.,
terminated Runaway
Cole, H., Patton, J.,
Rupture Revealed by
Shelly, D., et al.
the Dynamic Rupture
Simulations. Xu, D., Li,
Z., Zhang, Z., Yu, H.,
Chen, X.

Surveying Active Fault
Zones in California
Using Quakes-I
Wide-Swath Airborne
Stereoimagery. Zinke,
R., Donnellan, A.,
Applegate, R., Padgett,C.

2:15 pm

The International
Monitoring System
Sustainment: A
Technical Strategy.
Pérez-Campos, X., Sid
Ahmed, Y., Kramer, A.,
Zampolli, M., Woods,
V. T., et al.

Student: P-Wave
Attenuation Structureand Melting Processesof the Tonga-Lau Mantle
Wedge. Zhang, Y., Wei,
S., Byrnes, J. S., Tian, D.,
Wang, F., et al.

Evaluating theApplication of
Machine Learning
in Seismic Site
Classification: A
Case Study of Vs30
Development in Po
Plain, Italy. Mitra, D.,
Sethi, S.

Using a Dynamic
Earthquake Simulator
to Explore ThreeDimensional
Multicycle Dynamics
of Stepover Faults.
Duan, B.

Improvements toFault Displacement
Models: Examples
From the 2023 M7.8
Pazarcık, Türkiye
Earthquake. Mason,
H. B., Lavrentiadis, G.,
Asimaki, D., Hatem, A.
E., DuRoss, C. B., et al.

2:30 pm

The Chilean Seismic
Network: An Update.
Barrientos, S. E.,
Bravo, F., Koch, P.,
Baez, J. C., Rivet, D.,et al.

Invited: Illuminating
Earth’s Inner Core FineScale Heterogeneity
With Small Aperture
Arrays. Wu, S., Pang, G.,
Koper, K.

An AI-Assisted RealTime Earthquake
Forecasting Case Studyin China. Chen, Y.,
Saad, O., Chen, Y.,
Savvaidis, A., Fomel,
S., et al.

Entropy Approach to
the 2021 Alaska 8.2
Earthquake. Vogel,
E. V., Saravia, G.,
Pasten, D., Posadas, A.,
Aguilera, M.

Characterizing Surface
Fault Displacement
Uncertainty and Its
Effects on Probabilistic
Fault Displacement
Hazard. Example
From the 2023
M7.8 Pazarcık,
Türkiye Earthquake.
Lavrentiadis, G.,
Mason, H. B., Asimaki,D., Hatem, A. E.,
DuRoss, C. B., et al.

Volume 95

Tikahtnu Ballroom C•

Number 2B•

Tikahtnu Ballroom E/F

April 2024•

www.srl-online.org

Tubughnenq’ 5

Seismological Research Letters

|

1147

Wednesday, 1 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

From Faults to Fjords:
Earthquake Evidence (continued)

How Well Can We Predict
Broadband Site-Specific
Ground… (continued)

Induced Earthquakes:
Source Characteristics…
(continued)

The 2023 USGS National
Seismic Hazard Model and
Beyond (continued)

2:45 pm

Invited: A New Generationof High-Precision Dating
Techniques for CoseismicallyKilled or Damaged Trees.
Black, B.

Near-Surface Attenuation
Estimated With Coda Waves:
Insights From Numerical
Simulations and Empirical
Observations. Ji, C., Cabas,
A., Pilz, M., Kottke, A.

Multi-Sensor Microseismic
Monitoring of the Quest CCS
site, Alberta, Canada. Langet,N., Goertz-Allmann, B. P.,
Baird, A., Iranpour, K., Kühn,
D. K., et al.

New Ground-Motion
Model With Long-Period
Non-Ergodic Path Effects
From the Cybershake
Simulations in the Southern
California Region. Sung, C.,
Abrahamson, N. A., Lacour,M., Meng, X.

3:00 pm

Precisely Dating Seismically
Triggered Debris Avalanches
in the Northern California
Coast Range. Pearl, J. K.,
Kelsey, H., Angster, S.,
Caldwell, D., Pryor, I., et al.

Site-Specific Response Spectra Advanced InSAR Analysis
Estimation at Designatedof Groningen’s Subsurface
Seismic Stations of the Puerto Deformation: Enhancing
Rico Strong Motion Program Understanding of Reservoir
Seismic Network. HuertaRheology and Induced
López, C. I., Suarez-Colche, Seismicity Modeling. Li, Y.,
L. E., Martínez-Cruzado, J. A. Acosta, M., Sirorattanakul, K.,
Bourne, S., Avouac, J.

An Updated Version of the
New Empirical SourceScaling Laws for Crustal
Earthquakes Incorporating
Fault Dip and SeismogenicThickness Effects. Huang, J.,
Abrahamson, N. A., Sung, C.,
Chao, S.

3:15– 4:30 pm
Time

Poster BreakK’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom C

From Faults to Fjords:
Earthquake Evidence inTerrestrial and Subaqueous
Environments (see page1296).

Planetary Seismology (seepage 1381).

The OSIRIS-REx Sample
Return Capsule Re-entry:
Geophysical Observations(see page 1374).

Network Seismology: Recent
Developments, Challenges
and Lessons Learned (seepage 1353).

4:30 pm

Student: Diatom-Based
Coseismic Subsidence
Estimates Spanning a ~4,500
Year History of Cascadia
Subduction Zone Ruptures
Along the Southcentral Coastof Oregon. Bruce, D., Dura,
T., Witter, R., Kelsey, H.,
Hemphill-Haley, E.

Near Surface Excitation of theMartian Ground as Measured
by Insight. Pou, L., Panning,
M. P., Kedar, S., Stahler, S. C.,
Dahmen, N. J., et al.

First-Ever Detection of a
Re-Entry Capsule With
Distributed Acoustic Sensing(DAS): Initial Results andData Comparison With
Co-Located Seismic andInfrasound Sensors. Carr,C., Donahue, C., Viens, L.,
Beardslee, L., McGhee, E.,
et al.

Invited: Why Non-Seismic
Sensors Are Actually Valuable
to Network Seismology:
Examples From Alaska.
West, M. E., Ruppert, N.,
Grapenthin, R., Mohler, M.

4:45 pm

Constraints on Cascadia
Subduction Zone
Paleoearthquakes fromTerrestrial Shaking Proxies
and Coseismic Land-level
Change. Grant, A., Wirth,E., Dunham, A., LaHusen, S.,
Maurer, B., et al.

Evaluation of Lunar
Seismicity Parameters
Based on Analysis of
Newly Discovered Shallow
Moonquakes in the Apollo
Seismic Data. Onodera, K.

Array Data From the
University of Memphis
Seismo-Acoustic CouplingExperiment Fielded at the
Eureka County Airport,
Nevada. Langston, C. A.,
Bazargan, S., Horton, S.,
Mitra, I., Islam, S.

Seismic Network Station
Infrastructure as the Basisfor Multi-Disciplinary
Geophysical Stations. Perlin,
M.

1148

|

Seismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Network Seismology:(continued)

Earth’s Structure fromthe Crust to the Core
(continued)

Towards Advancing
Earthquake (continued)

Numerical Modeling(continued)

Learning AcrossGeological, (continued)

2:45 pm

Geophysical and Sea
Level Monitoring in
Puerto Rico. Huerfano,V. A.

Student: Waveform
Changes Due to Moving
Scatterers - Application
to the Inner Core. Wang,
R., Vidale, J.

Now-Casting With
Real-Time StrongMotion Response
Spectra. Franke, M.,
Lindquist, K., Vernon,
F.

Student: On the
Dynamic of Peierls
Creep at Subduction
Zones: Implication
for IntermediateDepth Lower Plane
Earthquakes. Zhang,R., Yang, J., Zhao, L.

Relating LargeVolume Landslides
and Potentially
Active Faults Using
Geotechnical Analyses
in the Pocuro Fault
System, Central Andes(32°-33°s). Sepúlveda,
S. A., UrrejolaSanhueza, J. T., Pinto,
L., Moreiras, S. M.

3:00 pm

Retrospective of
the USGS National
Earthquake
Information Center
Strategic Plan, 201923: How We Did andFuture Directions.
Earle, P., Hayes, G.,
Yeck, W., Goldberg, D.,
Wald, D., et al.

2020-2030. A Golden
Decade for VeryBroad Band Planetary
Seismology and Seismic
Imaging of Marsand Moon Interiors.
Lognonné, P. H.,
Panning, M. P., Banerdt,
W. B., Ceylan, S.,
Clinton, J., et al.

Abnormal LowMagnitude Seismicity
Preceding the M6.4–
M7.1 2019 Ridgecrest(California) Sequenceand the M7.1 2018
Anchorage (Alaska)
Earthquake. Girona,T., Drymoni, K.

Student:
Measuring Gaps
Quadrangular
Between Geodetic,
Adaptive Mesh
Geologic, and Seismic
for Elastic Wave
Moment Rates AcrossSimulation in Smooth the Western U.S.: How
Anisotropic Media.
to Determine a Budget
Rapenne, M.,
for Earthquake Rates?.
Caumon, G., Cupillard, Hatem, A. E., Briggs,
P., Gouache, C.
R., Pollitz, F., Reitman,N., Tan, M.

3:15– 4:30 pm
Time

Poster BreakTubughnenq’ 4

Tubughnenq’ 5

Marine Seismoacoustics (see Special Applications inpage 1344).
Seismology (see page 1420).

Translating Seismic
Imaging into Geodynamic
Understanding (see page1445).

Structure, Seismicity andDynamics of the Queen
Charlotte-Fairweather Fault
System (see page 1432).

4:30 pm

Student: Rupture Behaviorof Large Strike-Slip
Earthquakes at Equatorial
Atlantic Oceanic Transform
Faults: Constraints From
Hydroacoustic Data. Sampaio
de Melo, G., Grevemeyer, I.,
Metz, D., Lange, D., Kopp, H.

Student: Is Dynamically
Triggered Seismicity
Comparable to Background
Seismicity?. DeSalvio, N. D.,
Fan, W., Barbour, A. J.

Invited: Integration ofGeophysical Constraints
in Global Mantle Flow
Models for Insights Into
Plate Tectonics. Saxena, A.,
Dannberg, J., Gassmoeller, R.,
Fraters, M.

Aftershock Regions of Mw >6.7 Earthquakes on the Queen
Charlotte–Fairweather Plate
Boundary, 1929 to 2013.
Tape, C., Lomax, A.

4:45 pm

Student: Waveform
Modeling of Hydroacoustic
Teleseismic Earthquake
Records from Autonomous
Mermaid Floats.
Pipatprathanporn, S.,
Simons, F. J., Simon, J. D.

Ligabue—Large Induced
Ground Amplitudes by Urban
Excitations, as Recorded
by a 7c-Station. Braun, T.,
Famiani, D., Govoni, A., Keil,S., Wassermann, J.

Student: Immersive Insights:
Visualization of Earth’s
Interior in VR and Dome
Theaters. Hoyle, A. M.,
Orsvuran, R., Ghosh, A., Yu,
K., Peter, D., et al.

Kinematics of the
Fairweather-Queen Charlotte
Transform System andDeformation Across the
Broad Pacific-North America
Plate Boundary Zone. Elliott,
J.

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Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom C

From Faults to Fjords (continued)

Planetary Seismology (continued).

The OSIRIS-REx Sample
Return Capsule Re-entry(continued)

Network Seismology (continued)

5:00 pm

Student: A Cycle of Memory A Novel Statistical TechniqueCreation, Erasure, and Solidto Distinguish Lunar Impacts
to Fluid-Like State Transitions From Shallow Moonquakes.
Encoded Within Granular
Turner, A. R., Gulick, S. P. S.,
Assemblages Sheared byTrugman, D. T., Civilini, F.,
Faults. Dasent, J., Kilburn,
Onodera, K.
R., Wright, V., Scharer, K.,
Manga, M.

Infrasound From the OsirisRex Src Re-Entry Observed
Near the Nevada-Utah
Border. Elbing, B. R., Wilson,
T. C., Spillman, K., Fox, D.,
KC, R. J., et al.

Small Aperture Seismic
Arrays for Offshore Out-ofNetwork Events. Perry, H.,
Crane, S., Eisermann, A. S.,
Ziv, A., McCormack, D. A.,
et al.

5:15 pm

Lost and Found: Evidence of
the Penultimate Earthquakeon the Hebgen and Red
Canyon Faults, Montana.
Hecker, S., Stenner, H. D.,
Schwartz, D. P., Costa, C. H.,
Hamilton, J. C.

Invited: Direction-Finding
Observation of Vlf Radio
Emission Upon the Reentryof Osiris-Rex Sample Return
Cuspule on 24 September
2023. Watanabe, T.,
Kobayashi, M., Katoh, Y.

Student: Determining the
Feasibility of DAS for Urban
Earthquake Monitoring in
Athens, Greece. Smolinski,
K. T., Bowden, D. C., Lentas,
K., Melis, N. S., Simos, C.,et al.

5:30 pm

Unveiling Seismic Hazards:
Paleoseismic Insights From
the La Venta Fault in the
Forearc Mountains, Mexico.
Ramírez-Herrera, M.,
Gaidzik, K., Dominguez, L.
A., Coca, O., Vargas E., V. H.

Invited: Airborne Acoustic
Observations of the OSIRISREx Reentry. Bowman, D. C.,
Krishnamoorthy, S., Silber, E.
A., Popenhagen, S. K., Garces,
M. A.

Towards the Inclusion ofDistributed Acoustic Sensing
in Earthquake Monitoringand Early Warning
Operations. Biondi, E.,
Saunders, J. K., Tepp, G., Yu,
E. C., Bhadha, R., et al.

6:00–7:00 pm

A Reference Marsquake
Catalogue. Clinton, J.,
Ceylan, S., Dahmen, N. J.,
Staehler, S., Horleston, A.,et al.

Plenary: Challenges in Geohazards Research in Alaska

Poster Sessions
Network Seismology: Recent Developments, Challenges
and Lessons Learned (see page 1358).
1. Student: Picking Regional Earthquake Waveforms With
Neural Networks. Aguilar, A. L., Beroza, G. C.
2. Student: Moment Magnitude Estimation Using Machine
Learning Algorithms for Western United States. Alidadi,N., Pezeshk, S.
3. Student: National Strong Motion Project’s Advancements
in Station Health and Integration to the Earthquake Early
Warning System in the San Francisco Bay Area. Amador,
V. S., Schleicher, L. S., Carrasco Rodriguez, V., Childs, D.
M., Luna, E., et al.
4. Building an Operational Low-Cost Seismic Network in
Ukraine. Amashukeli, T., Malatesta, L., Farfuliak, L.,
Haniiev, O., Kuplovskyi, B., et al.
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5. Automated and Efficient Installation of AQMS. Antolik,
L., Friberg, P.
6. Enhancing Data Resiliency With Dual-Feed Telemetry.
Bhadha, R., Black, M. L., Hoggro, C., Hirata, T., Husker,
A. L., et al.
7. Next Generation In-Vault Power Distribution to Increase
Network Reliability and Remote Ops Capability. Blom,
L., Helmericks, J., Dalton, S.
8. Evaluation of Station Performance of the Idaho National
Laboratory Seismic Monitoring Network Using Network
Detection Thresholds. Bockholt, B., Sandru, J.
9. Field Evaluation of Seismic Sensors for Monitoring
Earthquakes, Tsunamis, Volcanoes, and Geodesy. Bodin,
P., Venkateswara, K., Wilcock, W., Tobin, H., Paros, J.
10. Performance of Raspberry Shake vs. Kentucky Seismic
and Strong-Motion Network Instruments. Schmidt, J. P.,
Carpenter, S., Wang, Z., Kalinski, M.
11. Access to Seismic Waveform Data, Services and Productsin the Euro-Mediterranean Region and Beyond: Status andwww.srl-online.org•

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Tubughnenq’ 3

Tubughnenq’ 4

Marine Seismoacoustics(continued)

Special Applications (continued).

Translating Seismic Imaging Structure, Seismicity…
(continued)(continued)

5:00 pm

Invited: Student: Decoding
the Submarine Ambient
Noise Field with Distributed
Acoustic Sensing. Fang,
J., Williams, E. F., Yang, Y.,
Biondi, E., Zhan, Z.

Student: #Utequake: An
Outreach Project Combining
Real-Time Large Crowd
Seismology and Football.
Rabade, S., Farrell, J., Hale, J.
M., Blycker, W., Morton, E.,
et al.

Student: Investigating
the Seismic Signature of
Galápagos Mantle Flow
Models. Autumn, K. R.,
Hooft, E. E. E., Ito, G.,
Faccenda, M., VanderBeek, B.
P., et al.

The Making of a Future
Accreted Terrane: Plate
Tectonics of the Queen
Charlotte Fault System andthe Development of the
Queen Charlotte Terrace
Adjacent to Haida Gwaii.
Furlong, K. P., Rohr, K. M.
M., Riedel, M.

5:15 pm

Ocean Bottom Turbulence
Evolution Observed by
Arrayed Obs, Dpg, and a
Temperature String. Chi, W.,
Yang, C., van Haren, H.

Enhancing Classification
Reliability With Anomaly
Detection for Operational
Monitoring of Continuous
Seismic Data. van Dinther,C., Malfante, M., ChiassonPoirier, L., Gaillard, P., Cano,Y.

First Steps Towards Imaging
the Antarctic’s 3D Viscosity
Structure Using GPS
Observations. Lloyd, A.,
Hollyday, A. E., Powell, E.,
Mitrovica, J. X., Gomez, N.,et al.

Student: Slope Evolution
and the Accommodation of
Oblique Convergence From
the Central to the Northern
Queen Charlotte Fault.
Adedeji, O., Worthington, L.
L., Brandl, C. C., Walton, M.
A. L., Roland, E., et al.

5:30 pm

Student: Searching for
Low-Amplitude Shallow
Tectonic Tremor in Cascadia
Using Buried Ocean Bottom
Seismometers. Krauss, Z.,
Wilcock, W., Creager, K.

Towards the Automatic
Relocation of IntermediateDepth Earthquakes Using
Adaptive Teleseismic Arrays.
Craig, T. J., Blackwell, A.,
Rost, S.

Instantaneous 3D
Tomography-Based
Convection and Melt
Generation Beneath the
Rungwe Volcanic Province,
East Africa. Njinju, E. A.,
Stamps, D., Atekwana, E. A.,
Rooney, T., Rajaonarison,
T. A.

A Spectral Perspective
on Fault Geometry andStrike-Slip Rupture at PlateBoundary Scales Along
the Queen Charlotte Fault.
Miller, N., Brothers, D. S.

6:00–7:00 pm

Plenary: Challenges in Geohazards Research in Alaska

Outlook of Orfeus Coordinated Programs. Cauzzi, C.,
Clinton, J., Crawford, W., Custódio, S., D’Amico, S., et al.
12. From Dense Seismic Monitoring to Mass-Movement
Hazards and Their Impacts: Demonstrating an
Operational Workflow and Associated Data Services.
Cauzzi, C., Böse, M., Clinton, J., Danciu, L., Kästli, P., etal.
13. Evolution of Volcano Hazards Monitoring of the Cascades
Chain in Washington and Oregon: Cascades Volcano
Observatory. Darold, A. P.
14. Seismic Network Modernization and Expansion in
Ukraine. Farfuliak, L., Amashukeli, T., Aderhold, K.,
Chiang, A., Mackey, K., et al.
15. Hydrothermal Monitoring Site in Norris Geyser Basin,
Yellowstone National Park, Wyoming, United States ofAmerica. Forbes, N. M., Farrell, J., Hale, J. M., Trow, A. J.,
Alexander, J., et al.
16. Improving Earthquake Monitoring Capabilities in Ohio
With Low-Cost Robust Posthole Vaults. Fox, J. L.
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17. Near Real-Time Earthquake Catalog for the Endeavour
Segment of the Juan De Fuca Ridge: Integrating
Community Code Into Ocean Networks Canada’s
Ocean 3.0 Data Portal. Heesemann, M., Hutchinson, J.,
Ferguson, E., Biffard, B., Krauss, Z., et al.
18. AdriaArray—a Passive Seismic Experiment to Study the
Geodynamics and Geohazards in Central Mediterranean.
Kolínský, P., Meier, T., Seismology Group, t.
19. Northern California Earthquake Data Now Available in
AWS Cloud. Marty, J., Zuzlewski, S., Taira, T., Thompson,S., Allen, R.
20. Assessment of Data Quality for the Alaska Geophysical
Network. McFarlin, H., Ruppert, N., Murphy, N.,
Holtkamp, S., Heslop, J.
21. A Review of Recent IDA Sensor Performance. Mellors, R.
J., Ebeling, C. W., Davis, P., Berger, J.
22. High Frequency Ground Motion and Electrical
Calibrations of Seismometers Used at IMS Stations.
Merchant, B. J., Bloomquist, D. K., Slad, G. W.
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Wednesday, 1 May (continued)
23. Student: Machine Learning Earthquake Catalog
Performance for Characteristic Alaska Settings. Noel, S.
K., West, M. E., Ruppert, N. A.
24. Monitoring Induced Microseismicity (M>-1) With the
Local Network at the Utah Frontier Observatory for
Research in Geothermal Energy (FORGE). Pankow, K.
L., Whidden, K., Rutledge, J., Petersen, G., Niemz, P., et al.
25. Seismic Data Compression and Telemetry Bandwidth
Considerations for EEW. Perlin, M.
26. Sensor Corrections for Multi-Component Monitoring ofSeismic Translation and Rotation. Rossi, Y., Guattari, F.,
Bernauer, F., Lin, C.
27. Comparative Analysis of Seismic Instrument Installations:Surface Vaulted Pier Mount, Direct Burial, and Bore Hole,
Considering Noise Models. Sandru, J.
28. Applying Machine Learning Salves to Network BuildOut “Growing Pains” at the Pacific Northwest Seismic
Network. Stevens, N. T., Hartog, R., Ni, Y., Hutko, A.,
Denolle, M., et al.
29. System Monitoring, Telemetry Quality Control, andPlanning Tools for Scsn. Stubailo, I., Bhadha, R., Watkins,
M., Husker, A. L., Yu, E. C., et al.
30. Quick Look at the Reoccupation and Installation ofSeismic Stations at the NNSS. Turley, R., Scalise, M.,
Zeiler, C. P., Gochenour, J., White, R., et al.
31. A Decade of the Seattle Liquefaction Array. Williams, E.
F., Denolle, M., Bodin, P., Steidl, J. H.
32. Improving Automatic Post-Processing at the Southern
California Seismic Network With Machine Learning
Algorithms. Tepp, G., Yu, E. C., Zhu, W., Jaski, E.,
Newman, Z., et al.
33. Güralp SMART Sensors - A Comparison of Next
Generation Mid-Band Seismometers and Traditional
Sensor Technologies. Lindsey, J. C., Watkiss, N., Hill, P.,
O’Neill, J.
Marine Seismoacoustics (see page 1345).
34. Pushing Boundaries With Ocean Bottom Seismometers(Obs) With a Pool-Ready System: Güralp Aquarius.
Lindsey, J. C., Watkiss, N., Hill, P., Nedimović, M., Cairns,
G.
35. Student: Probing Further the Cascadia Initiative Data to
Detect New Offshore Events. Bito, H., Denolle, M. A., Ni,
Y., Shi, Q., Krauss, Z.
36. Noise on Ocean Bottom Seismometers: Observations andNew Directions. Janiszewski, H. A., Russell, J., Hoots, C.,
Maso, E.
37. Student: Changing Ambient Noise Patterns in the
Beaufort Sea. Niklasson, S., Rowe, C., Bilek, S.
38. RBRquartz³ APT: Innovative Instrumentation for
Enhanced Marine Seismic Monitoring on Ocean Networks

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Canada’s NEPTUNE Cabled Observatory. Schlesinger,
A., Heesemann, M., Sun, T., Davis, E., Dexter, J., et al.
39. Observations From the Seafloor: Ultra-Low-Frequency
Ambient Ocean-Bottom Nodal Seismology From theGulf of Mexico. Shragge, J. C., Girard, A. J.
40. High-Resolution Acoustic Seabed Quantification with
an Autonomous Underwater Vehicle. Sonnemann, T.,
Dettmer, J., Holland, C. W., Dosso, S. E.
41. Implementation Plan for the Cascadia Offshore Subduction
Zone Observatory. Wilcock, W. S. D., Harrington, M. J.,
Schmidt, D. A., Kelley, D. S., Tobin, H. J., et al.
42. CHIRP Acoustic Reflection Imaging: Toward Improved
Signal Processing in Extant Glacial Lakes. Woller, K. L.,
McGlue, M. M., Thigpen, J. R., Yeager, K. M., Woolery, E. W.
From Faults to Fjords: Earthquake Evidence in Terrestrial
and Subaqueous Environments (see page 1301).
43. Lacustrine Paleoseismic Evidence From Two Large
Lakes in Cascadia: Preliminary Comparisons of PostGlacial Sediment Records From Ozette and Whatcom
Lakes, Washington. Brothers, D. S., Hill, J., Singleton, D.,
Derosier, B., Sherrod, B. L., et al.
44. Earthquake–triggered
Submarine
Landslides
inKachemak Bay, Alaska: New Constrains on Distribution
and Timing Based on Marine Geophysical and GeologicalData. Brothers, D. S., Haeussler, P., Hill, J., Watt, J.,
Snyder, G., et al.
45. Possible Quaternary Faulting on the Picuris-Pecos Fault
on the Eastern Margin of the Española Basin, New
Mexico. Cline, M. L., Thompson Jobe, J. A., Reitman, N.,
Briggs, R., Ellett, N.
46. Lacustrine Paleoseismic Investigation in the South
Washington Cascade Range: Geophysical andSedimentological Observations From Keechelus, Kachess,
and Cle Elum Lakes. Derosier, B., Singleton, D., Brothers,
D. S., Sherrod, B. L., Hill, J., et al.
47. Comprehensive High-Resolution Geophysical Mappingand Sediment Coring in Lake Chelan, Wa: A Deep, Steep
Lacustrine Environment Dominated by Mass Transport
Processes. Derosier, B., Brothers, D. S., Sherrod, B. L.,
Singleton, D., Dartnell, P., et al.
48. Introducing the Science Goals for the Cascadia Region
Earthquake Science Center (Crescent) Cascadia
Paleoseismology Working Group (Cpal). Dura, T.,
Hawkes, A., Witter, R., Staisch, L., Kelsey, H., et al.
49. Detection Thresholds for Large to Great Subduction
Earthquakes in South-Central Alaskan Marshes.
Engelhart, S. E., Woodroffe, S. A., Wood, K. L., Shennan,
I., Witter, R. C.
50. Student: Geotechnical Properties of Quaternary Marine
Sediments of the Eel River Plateau, Southern Cascadia

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Margin. Fitzgerald, B. L., Sawyer, D. E., Hill, J. C.,
Brothers, D. S., Singleton, D.
51. A Refined Chronology of Tsunami Deposition at
Discovery Bay, Washington State. Garrison-Laney, C.,
Padgett, J. S., Pilarczyk, J. E., Giang, A.
52. Reconnaissance Implies a Potentially Complete Record of
Holocene Earthquakes in Esther Lake Above the AlaskaAleutian Megathrust. Haeussler, P. J., Witter, R. C.,
Singleton, D. M., Marcuson, R. K., Brothers, D. S., et al.
53. Cataloging the Date of Last Event (DOLE) Across theWestern U.S. Hatem, A. E., Briggs, R., Tan, M.
54. Tectonic Oversteepening, Sediment Accretion, andLower Slope Failure in the Cascadia Subduction Zone—A
Recipe for Abyssal Seismoturbidites and Insights Into
Earthquake History. Hill, J. C., Brothers, D. S., Watt, J. T.,
Paull, C. K., Caress, D., et al.
55. Marine Seismoturbidites in the Cascadia Subduction
Zone: Filling the Gaps and Refining the Offshore Recordsof Earthquake Shaking. Hill, J. C., Watt, J. T., Paull, C. K.,
Caress, D., Brothers, D. S., et al.
56. Urban Paleoseismology of the Taylorsville Fault - New
Data and Challenges from one of the Last Remaining
Trench Sites on the West Valley Fault Zone, Utah.
Hiscock, A. I., Kleber, E. J., McDonald, G. N., Hylland,
M. D., McLean, J. H., et al.
57. Middle to Late Pleistocene Faulting on the Puye Fault
Zone, Española Basin, New Mexico. Thompson Jobe, J.
A., Cline, M. L., Reitman, N., Briggs, R., Sion, B., et al.
58. Chirp Correlation and Acoustic Characterization of
Lacustrine Turbidite Deposits in Lake Ozette, Wa
Using Ct-Derived Density, Synthetic Seismograms, andAdvanced Chirp Processing. Kluesner, J., Brothers, D. S.,
Snyder, G., La Selle, S., Singleton, D., et al.
59. How Do Large Lakes in the Seattle Area Respond to
Different Sources of Seismic Shaking? Revisiting Lake
Washington and Lake Sammamish With New HighResolution Data. Kluesner, J., Hill, J., Brothers, D. S.,
Sherrod, B. L., Conrad, J., et al.
60. Variations of the 1959 m7.3 Hebgen Lake Earthquake
Record in Four Proximal Lacustrine Systems, West
Yellowstone Region, USA. Nicovich, S. R., DuRoss, C. B.,
Thompson Jobe, J. A., Briggs, R., Hatem, A. E., et al.
61. Evidence of Past Earthquakes Preserved in Coast Redwood
Trees Along the Northern San Andreas Fault. Carroll, A.,
Philibosian, B., Sillett, S., Antoine, M., Kozaci, O., et al.
62. Ground Surface Rupture Complexity on the Northern
Alpine Fault, Aotearoa New Zealand. La Greca, J.,
Quigley, M., Langridge, R., Morgenstern, R., Kulesza, O.
63. Using Modern Fires to Estimate Charcoal Age Inheritanceat Paleoseismic Sites in California. Scharer, K., McPhillips,
D., Leidelmeijer, J., Kirby, M.
64. Refined Timing and Estimates of Coseismic Subsidence
at the Southern Cascadia Subduction Zone: Combining
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Modern Dendrochronology, Age Modeling, and Relative
Sea-level Reconstruction Techniques in the Eel River
Valley, CA. La Selle, S., Padgett, J. S., Black, B. A., Kelsey,
H. M., Witter, R. C., et al.
65. Off the Beaten Path: Preliminary Results ofReconnaissance Paleoseismic Surveys in Remote Alaskan
Lakes. Singleton, D. M., Haeussler, P. J., Brothers, D. S.,
Witter, R. C., Kaufman, D., et al.
66. A Comparative Study of Earthquake Ground-Shaking Site
Effects From Lacustrine Sediments in a Subduction Zone
Setting Using Active and Passive Seismic Methods. Wils,
K., Liberty, L., Montalva, G., Haeussler, P., Van Daele, M.
67. Temporal Clues Point to an Along-Strike Cascadia
Megathrust Rupture Sequence Between 680–950 Years Ago.
Witter, R., Staisch, L., Nelson, A., Kelsey, H., Padgett, J.
The OSIRIS-REx Sample Return Capsule Re-entry:
Geophysical Observations (see page 1376).
68. Infrasound Analysis of the OSIRIS-REx Reentry at
the NVIAR Array. Clarke, J., Arrowsmith, S., Park, J.,
Anderson, D.
69. Observation of Osiris-Rex via Shock Wave: Temporary
Observation Network Utilizing Portable InfrasoundSensors and Comparative Analysis With Hayabusa andHayabusa2. Nishikawa, Y., Yamamoto, M., Hasumi, Y.
70. Leveraging Infrasound Detections of Sample Return
Space Missions Towards Characterization of Meteors: A
Review. Silber, E. A., Bowman, D., Albert, S. A.
71. The Utility of Infrasound Towards Detection andCharacterization of Bolides. Silber, E. A.
72. Infrasound Detection of the OSIRIS-REx Re-Entry:
Signal Characteristics. Silber, E. A., Bowman, D. C.
73. The OSIRIS-REx Sample Return Capsule Re-Entry: Initial
Results From a Historic Geophysical Recording Campaign
Against an ‘Artificial Meteor’. Silber, E. A., Bowman, D.
C., Krishnamoorthy, S., Carr, C., Haaser, R. A., et al.
74. The First Detection of an ‘Artificial Meteor’ by a Large N
Acoustic Array. Silber, E. A., Bowman, D. C., Eisenberg,
D. P.
Creating Actionable Earthquake Information Products(see page 1254).
75. Post-Earthquake Liquefaction Mapping by SemiSupervised Machine Learning Using Partially Labeled
Imagery. Asadi, A., Baise, L. G., Sanon, C., Koch, M.,
Chatterjee, S., et al.
76. Investigating Different Methodologies for a Sar Coherence
Change Detection Product. Burgi, P. M.
77. New Earthquake Tsunami Preparedness Magazine forNorthern California. Dengler, L., Ozaki, V., Uyeki, A.

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Wednesday, 1 May (continued)
78. Integration of Seismic Monitoring and Involvementof Civil Protection Volunteers for an Effective PostEarthquake Response. Camassi, R., Faenza, L., Ercolani,E., Brunelli, M., Pondrelli, S., et al.
79. Applying ShakeCast to Monitor Earthquake Hazards for
Pipeline Infrastructure. Hille, M., Zellman, M., Modney,T., Widmann, B., Duckworth, W., et al.
80. Student: Making the Crowdsourced “Did You Feel It?”
System More Accessible: A Global Analysis. Knodel, E. J.,
Loos, S., Quitoriano, V., Wald, D.
81. Global Structural Health Monitoring via MyShake: An
Economical and Accessible Smartphone-Based Approach.
Kumar, U., Marcou, S., Patel, S., Allen, R.
82. ShakeCast: Pivoting USGS Products to Respond to User
Needs. Lin, K., Cheeck, L., Smith, K. K., Thompson, E.
M., Wald, D.
83. Guidelines on Using (Uncertain) Macroseismic Data in
ShakeMap. Quitoriano, V., Wald, D. J., Worden, C. B.,
Thompson, E. M.
84. Creating Earthquake Early Warning Post-Alert
Information Products: Harnessing Existing Earthquake
Information Tools to Depict Alerting Efficacy. Saunders,J. K., Wald, D. J.
85. A Framework for Implementing a New Intensity Metricfor USGS’s Shakemap: Cumulative Absolute Velocity(CAV). Smith, K., Thompson, E. M., Worden, C. B.,
Wald, D.
Cryptic Faults: Advances in Characterizing Low Strain
Rate and Environmentally Obscured Faults (see page1259).
86. Seismic Imaging and Structure of the West Napa Fault
Near Calistoga, California. Chan, J. H., Catchings, R. D.,
Goldman, M. R., Philibosian, B. E., Sickler, R. R., et al.
87. Geologic and Geomorphic Evidence for Possible
Reactivation Along the Dry Creek Fault Zone andHoadley Fault, Cryptic Faults in the Northern Sacramento
Valley and Surrounding Areas. von Dassow, W., Klinger,
R., Besana-Ostman, G., Reedy, T.
88. Constraints on Late-Quaternary Fault Displacement andTectonic Hazards in the Sacramento–San Joaquin Delta,
Northern California, From Shallow Sediment Cores Across thePittsburg–Kirby Hills Fault System. Trexler, C., Vermeer, J.,
Hammer, M., Doyle, M., Williams, T.

89. Characterization of Slip Rates Across the Buffalo Valley,
Buena Vista Valley, and Southern Shoshone Faults,
Central Nevada. Koehler, R. D., Stirling, M. W.
90. Late Pleistocene Kinematics of the Great Southern Puerto
Rico Fault Zone, Puerto Rico. Lynch, E. M., Thompson
Jobe, J. A., Briggs, R., Ortega Diaz, V. G.
91. Student: A Comprehensive Search for Evidence of
Active Faulting in the Southern Coast Mountains of
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British Columbia, Canada: Progress and Preliminary
Results. Mendoza, R., Hobbs, T. E., Salomon, G., Finley,T., Nissen, E., et al.
92. Student: Investigating Holocene-Active Faulting in theStrait of Georgia, British Columbia Through Archived
Seismic Reflection Data. Podhorodeski, A., Douglas, K.,
Hobbs, T., Leonard, L., Schaeffer, A.
93. Steps Toward Linking the Kaltag and Tintina Faults inInterior Alaska. Salisbury, B.
94. Student: A Detailed Earthquake Catalog for Interior
Alaska Fault Zones. Sims, N. E., Tape, C.
95. Spatial Patterns of Tectonic Deformation at the
Mendocino Triple Junction Inferred From River Terracesand Landscape Morphology. Vermeer, J., DeLong, S.,
Hammer, M., Patton, J. R., Trexler, C., et al.
Induced Earthquakes: Source Characteristics,
Mechanisms, Stress Field Modeling and Hazards (see page1326).
96. The Critical State of Stress Preceding the Prague m5.7
Earthquake. Alfaro-Diaz, R. A., Chen, T., Carmichael, J. D.
97. A 3-Dimensional P-Wave Tomography Model of thePecos, Texas Region of the Delaware Basin. Faith, J. L.,
Karplus, M. S., Doser, D. I., Savvaidis, A.
98. Student: Pore Pressure Effect on Coulomb Stress
Change and Triggering of Earthquakes in Raton Basin,
Colorado—New Mexico Region. Fuentes, F. A., Mendoza,
M. M., Brown, M. R. M., Ge, S., Sheehan, A. F.
99. The Minimal Effect of Solid-Earth Tides on Earthquake
Rate in Oklahoma and Kansas. Glasgow, M. E.,
Rubinstein, J. L., Hardebeck, J.
100. Student: Hindcasting the 1993 - 2023 Wirdum
Induced Earthquake Sequence. van der Heiden, V.,
Ulrich, T., Buijze, L., van Isselt, M., van de Wiel, L., et al.
101. Quake-Dfn, A Software for Simulating Sequences ofInduced Earthquakes in a Discrete Fault Network. Im, K.,
Avouac, J.
102. Crustal Rheological Layering Revealed in Multiscale
Signals of Natural and Anthropogenic Processes at
Pawnee, Oklahoma. Jiang, J., Bodunde, S., Walter, J.,
Carpenter, B., Viteri Lopez, J.
104. Fluid-Induced Aseismic Slip May Explain the NonSelf-Similar Source Scaling of the Induced Earthquake
Sequence Near the Dallas-Fort Worth Airport, Texas. Lui,
S., Jeong, S., Tan, X.
105. DC or Non-DC? Exploring Uncertainties andResolution Limitations for Source Mechanism Studies
in a Complex EGS Environment. Niemz, P., Rutledge, J.,
Petersen, G., Finger, C., Pankow, K. L.
106. Wastewater Disposal and Hydraulic Fracturing
Interaction Propagating Seismicity in Oklahoma. Ogwari,
P. O., Walter, J. I., Allen, B., Thiel, A., Woelfel, I., et al.
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107. Student: Centroid Full Moment Tensor Analysis
Reveals Geological and Injection Related Constraints ofInduced Seismicity at the Experimental Otaniemi EGS
Site, Helsinki Region, Finland. Rintamäki, A. E., Hillers,G., Heimann, S., Dahm, T., Korja, A.
108. Inferring Maximum Magnitudes From the Ordered
Sequence of Large Earthquakes. Schultz, R.
109. Constraining the Non-Double-Couple Components
of Local Events Recorded by Dense Nodal Array. Yang, L.,
Wang, R.
110. Student: Unraveling the Subsurface Mosaic:
Implications of Tectonic Structures and Fault Orientations
on Induced Seismicity. Wangari, V. N. N.
111. On Delayed Triggering of Earthquakes by
Anthropogenic Activities. Yang, H., Zi, J., Yang, Y.
112. Student: Source Mechanisms Inversion of Induced“Seismicity” During Laboratory Hydraulic Fracturing.
Yuan, H., Gu, C., Zhong, Y., Wu, P., Chen, Z., et al.
113. How Induced Earthquakes Response to Pre-Existing
Fractures and Hydraulic Fracturing Operations? a Case
Study in South China. Li, D., Zhang, M., Zheng, J., Peng,
S.
Numerical Modeling in Seismology: Developments andApplications (see page 1373).
114. Student: Utilizing Metaheuristic Algorithms for
Ground Motion Selection and Scaling in Structural Time
History Analysis. Akhani, M., Alidadi, N., Pezeshk, S.
115. Building Geologically Realistic Initial Conditions
for Geodynamic and Seismological Models With the
Geodynamic World Builder. Fraters, M., Billen, M. I.,
Saxena, A., Gassmoeller, R., Li, H.
116. Passive Source Detection Technology Based on
Short-Period Dense Seismic Array. Gamez, R., Zou, L.,
Shen, J., Zhou, B.
117. Student: Effects of Bimaterial Interface on Rupture
Along Strike-Slip Branch Faults. Marschall, E., Douilly,
R., Kame, N.
118. New Constraints on the Seismic Crustal Structureof the Southern Apennines (Italy): Numerical Modelingof P- and S- Body Waves for Moderate Earthquakes at
Regional Scale. Scarponi, M., Di Luccio, F., Piromallo, C.,
Sun, D.
How Well Can We Predict Broadband Site-Specific Ground
Motion and Its Spatial Variability So Far? (see page 1314).
120. Application of Conditional Dynamic Variational
Autoencoder for Simulating Ground Motions in the
Geysers Geothermal Field. Bi, Z., Ren, P., Nakata, R.,
Nakata, N.

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121. Lateral Variation in Coda Wave Attenuation in
Sikkim Himalaya. Singh, C., Dutta, A.
122. Inversion of Earthquake-HVSR in the Anchorage
Basin, Alaska, for Delineation of Shallow Sedimentary
Structures. Dutta, U., Thornley, J., Yang, Z., Zhao, Y.,
Stephenson, W.
123. Measuring Shallow Seismic Attenuation in the PacificNorthwest of the United States Using Ambient Noise
Seismology. Feng, K., Denolle, M., Ni, Y.
124. Relating Peak and Cumulative Ground Motions for
Earthquakes in the San Francisco Bay Area. Hirakawa, E.
T., Parker, G. A., Baltay, A. S.
125. A Comparative Study Between the ResonanceFrequency by Hvsr Analysis and Bedrock Depth inWestern Busan, Korea. Kang, S., Kim, K., Lee, S.
126. Student: Preliminary Site Characterization for
Earthquake Hazard Assessment Using Ambient Vibration
Techniques in Haines Junction, Yukon. Leishman, T.,
Gosselin, J. M., Dettmer, J., Cassidy, J., Kang, T.
127. Influence of Buried Geometries on Ground Response
Analysis: The Case of the Pescara Paleovalley System. Di
Martino, A., Sgattoni, G., Purri, F., Amorosi, A.
128. Influence of Seasonal Frozen Soil on High-Frequency
Attenuation (κ0). Haendel, A., Pilz, M., Cotton, F.
129. Combining Simulated and Empirical Nonergodic
Ground Motion Models for Southern California. Smith,J., Engler, D. T., Moschetti, M. P., Parker, G. A., Thompson,
E. M., et al.
130. Student: Shear Wave Velocity Structure Beneatha Dense Seismic Array in the Presence of Local Noise
Sources Using Matched Field Processing. Soni, Y.,
Pulliam, J.
131. Constraining Shear-Wave Velocity Profiles in
Anchorage, Alaska, Through Inversion of Microtremor
Horizontal-to-Vertical Spectral Ratios. Stephenson, W.
J., Dutta, U., Lindberg, N. S., Leeds, A., Goozen, A., et al.
132. Student: Seismic Site Characterization of Sikkim
Himalaya Using HVSR. Uthaman, M., Singh, C., Singh,
A., Bose, S.
The 2023 USGS National Seismic Hazard Model and
Beyond (see page 1197).
133. The 2023 Alaska National Seismic Hazard Model:
Hazard Implications. Altekruse, J. M., Powers, P. M.
134. Implementing Rupture Directivity Effects Into PSHA.
Bayless, J., Abrahamson, N. A.
135. Conterminous U.S. Site Parameter Maps for Ground
Motion Models. Boyd, O. S., Smith, J. A., Moschetti, M. P.
136. Recurrence Model for Puerto Rico Subduction Zone
Interface and Muertos Thrust Belt Earthquakes. Briggs,
R., ten Brink, U., Thompson Jobe, J. A., Hatem, A. E.,
Pratt, T., et al.
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Wednesday, 1 May (continued)
137. Seismic Hazard, Lithosphere Hydration, and DoubleVerging Structure of the Puerto Rico Subduction Zone: A
Seismic Reflection and Refraction Perspective. Canales,J., Han, S., ten Brink, U., Vanacore, E., Harmon, N., et al.
138. Deploying the USGS National Seismic Hazard
Models. Clayton, B., Powers, P.
139. USGS Earthquake Hazard Toolbox. Girot, D. L.,
Powers, P. M., Clayton, B. S.
140. The 2023 Alaska National Seismic Hazard Model:
Inputs and Implications. Herrick, J. A., Rukstales, K. S.,
Altekruse, J. M., Powers, P. M., Team, N.
141. Student: A New Seismic Reflection Study forSouthwestern Puerto Rico Fault Characterization.
Justiniano, C., Vanacore, E., Pratt, T., Lopez Venegas, A.
142. Gridded Seismicity Models for the 2025 USGS
National Seismic Hazard Model for Puerto Rico and the
U.S. Virgin Islands. Llenos, A. L., Michael, A. J., Shumway,
A. M., Haynie, K. L.
143. A Seismological Method for Estimating the LongPeriod Transition Period Tl in the Seismic Building Code.
Pezeshk, S., Assadollahi, C.
144. Why Seismic Hazard Models Appear to Overpredict
Historical Shaking Observations: An Intensely Simple
Answer. Salditch, L., Stein, S., Gallahue, M., Neely, J.,
Abrahamson, N. A.
145. Hybrid Empirical Ground-Motion Models for the
Island of Hawaii Based on an Updated Strong Ground
Motion Database. Davatgari Tafreshi, M., Pezeshk, S.,
Haji-Soltani, A.
146. Empirical Models for Fourier Amplitude Spectrumof Ground-Motion Calibrated on Data From the IranianPlateau. Davatgari Tafreshi, M., Pezeshk, S., Singh Bora,S.
147. Methods to Evaluate and Improve the Modeling of
Rupture Directivity in Assessment of Seismic Hazard.
Withers, K., Kelly, B., Bayless, J., Moschetti, M.
148. A Fault-Based Crustal Deformation Model With
Buried Dislocation Sources for Slip-Rate Inversion of the
Alaska Faults. Zeng, Y.
Towards Advancing Earthquake Forecasting andNowcasting: Recent Progress Using AI-Enhanced Methods(see page 1444).
149. Short-Term Earthquake Forecast Using Precursor
Phenomena. Hattori, K.
150. Deep Learning for Higher-Order Aftershock
Forecasting in Near-Real-Time. Mizrahi, L., Jozinović, D.
151. Student: Study of the b-Value Change Preceding
the 2024 Noto Peninsula Earthquake M7.6, Japan. Li, W.,
Yoshino, C., Hattori, K.

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Seismological Research Letters152. The January 1, 2024, Noto Hanto, Japan, Mw 7.6
Earthquake as a Plausible ‘Dragon King’ Event. Liu, Y.,
Zhang, Y., Wu, Z.
153. Student: Building an Enhanced Earthquake
Catalogue for Aotearoa New Zealand: Applying an
Automated Workflow With Cutting-Edge Machine
Learning Methods to Mine New Zealand’s Seismic Data.
Williams, C., Chamberlain, C. J., Townend, J.
Structure, Seismicity and Dynamics of the Queen
Charlotte-Fairweather Fault System [Poster Session] (seepage 1434).
154. Student: Transpression Along the Southern Queen
Charlotte Fault: Underthrusting and Strain Partitioning of
the Queen Charlotte Terrace. Brandl, C. C., Worthington,
L. L., Roland, E. C., Walton, M. A. L., Nedimovic, M. R., etal.
155. Local Earthquake Monitoring of the Central Queen
Charlotte Fault With an Ocean-Bottom Seismic Array.
Gase, A. C., Roland, E., Worthington, L. L., Walton, M.
A. L., Bostock, M., et al.
156. Student: Morphologic Expression of Shallow
Volcanics and Ice Sheet Extent Along the Queen Charlotte
Fault, Se Alaska and British Columbia. Kennedy, K.,
Roland, E., Clark, D., Worthington, L. L., Baichtal, J., et al.
157. Student: Crustal Velocity Structure of the 2013 m7.5
Craig Earthquake Source Region With Joint Ocean-Bottom
Seismometer and Streamer Tomography. Martin, E. C.,
Gase, A., Roland, E., Garza, L., Worthington, L. L., et al.
158. Crustal Structure Crossing the Queen Charlotte
Fault and Trough in the Region of the Haida Gwaii 2012
m7.9 Thrust Earthquake Using P-Wave Tomography.
Roland, E., Worthington, L. L., Gase, A., Walton, M. A.
L., Nedimovic, M.
159. Crustal Architecture Across the Queen Charlotte
Fault Zone North of Haida Gwaii, British Columbia From
2d Tomography. Walton, M. A. L., Worthington, L. L.,
Roland, E., Gase, A., Garza, L., et al.
160. New Constraints on Crustal Structure and Fault
Zone Architecture in the m7.8 2012 Haida Gwaii
Earthquake Source Region, Offshore British Columbia.
Worthington, L. L., Brandl, C. C., Roland, E., Walton, M.
A. L., Nedimovic, M., et al.
Translating Seismic Imaging into Geodynamic
Understanding (see page 1447).
161. Guiding Deep Earthquake Investigation with Subduction
Modeling: Is Thermal Shear Instability Viable in the Deep
Slab?. Fildes, R. A., Billen, M. I., Thielmann, M.
162. Seismic Imaging of the Mendocino Triple Junction:
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Wednesday, 1 May (continued)
Boundary Transition. Furlong, K. P., McKenzie, K. A.,
Herman, M. W., Benz, H. M., Villaseñor, A.
163. Image of Crust and Upper Mantle of Ne India Basedon Surface Wave Tomography. Mukhopadhyay, S.,
Kumar, N., Kumar, A., Chanu, M. N.
164. Student: Transdimensional Mt. Etna Volcano
P-Wave Anisotropic Seismic Imaging. Del Piccolo, G., Lo
Bue, R., VanderBeek, B. P., Faccenda, M., Cocina, O., et al.
165. Ecoman 2.0: An Open-Source Software for Exploring
the Consequences of Mechanical Anisotropy in the
Mantle. Faccenda, M., VanderBeek, B. P., de Montserrat,
A., Yang, J.
Special Applications in Seismology (see page 1422).
166. Sub-Daily Gnss Denoising Using Graph Neural
Network. Bachelot, L., Thomas, A. M., Melgar, D., Searcy,
J.
167. Analysis of Characteristic Repeating Earthquakes in
the Tehuantepec Triple Junction, Mexico. Dominguez, L.
A., Taira, T.
168. Nodal Seismometer Recordings of Aftershocks ofthe 11 May 2023 Mw 5.5 Lake Almanor Earthquake.
Goldman, M. R., Catchings, R. D., Sickler, R. R., Chan, J.
H., Criley, C. J.
169. Student: Machine Learning as a Tool to Builda Comprehensive Seismic Catalog for the Island of
Hispaniola. Muñoz, L. F., Walter, J., Pulliam, J., Leonel, J.,
Polanco Rivera, E.
170. Assessment of Atmospheric-Driven Ground Noises
for Dragonfly’s Seismic Observation on Titan. Onodera,
K., Kawamura, T., Nishida, K., Shiraishi, H., Tanaka, S., etal.
171. Ground Deformation Caused by Atmospheric
Gravity Waves on Mars: An Independent Assessmentof Martian Crustal Rigidity. Onodera, K., Nishida, K.,
Widmer-Schnidrig, R., Kawamura, T., Spiga, A., et al.
172. Student: Efficient Cataloging of Low-Frequency
Earthquakes With Deep-Learning Model and Template
Matching. Papin, L., Thomas, A. M., Lin, J., Hawthorne, J.
Learning Across Geological, Geophysical & Model-Derived
Observations to Constrain Earthquake Behavior (see page1335).
173. Student: Rupture Geometry and Static Stress
Changes of the 2022 Mw 7.0 and Mw 6.4 Earthquakes inAbra, Philippines. Catugas, S. A., Aurelio, M. A., Dianala,
J. B.

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174. Student: Investigating Early Earthquake Rupture
Characteristics With Borehole Strainmeters. Dybing, S.
N., Melgar, D., Barbour, A. J., Canitano, A., Goldberg, D. E.
175. Student: Hybrid Model: A Tool for Combining
Fault and Area Sources in Seismic Hazard Assessment.
Gamboa-Canté, C., Rivas-Medina, A., Ornelas-Agrela,A., Benito, B.
176. A New View on Interseismic Locking of the
Hikurangi Megathrust Along the North Island of New
Zealand. Govers, R., Bijlsma, E., Vos, S.
177. Geological Constraints on the Seismic Activity of the
Mid-section of the Minjiang Fault in the Eastern Marginof the Tibet Plateau. Han, Z., Guo, P., Zhou, C., Niu, P., Li,J.
178. Seismic Structure, Lithospheric Deformation andSeismicity of the Indian Plate in Sikkim Himalaya. Singh,
A., Uthaman, M., Jana, N.
179. Earthquake Rate Modelling Tools to Explore
Uncertainties in Fault Source Parameters The Case of theAlboran Sea. Perea, H., Gómez-Novell, O., Jiménez, M.,
García, M., Lozano, L., et al.
180. Mapping Finite-Fault Slip in 3D From Spatial
Correlation Between Seismicity and Point-Source
Coulomb Stress Change. Lomax, A.
181. Student: Microseismicity and Fault Structure in the
Daliangshan Subblock Within the Southeastern Tibetan
Plateau. Ma, J., Xiao, Z., Li, L., Ai, Y.
182. Student: Mapping Outerrise Normal (and other)Dip-slip Fault Parameters using Semi-automated and
Newly Developed Python Toolbox. Nielson, Q., Losasso,E., Newman, A.
183. Student: Diatom Evidence of Tsunami Inundation
Extent Following the Great Ca. 1700 Ce Earthquake(s)at the Salmon River Estuary, Oregon, USA. Priddy, M.,
Dura, T., Hawkes, A., Kelsey, H., La Selle, S., et al.
184. Moment Tensor Analysis for Earthquakes in Armenia.
Sahakyan, E., Babayan, G., Sargsyan, L., Gevorgyan, M.,
Nabelek, J.
185. Preliminary Constraints on Quaternary Fault Activity
in the Malawi Rift from New High-resolution Bathymetry
and Seismic Data. Shillington, D. J., Scholz, C. A.,
Chindandali, P. R. N., Wood, D., Greenlee, J. M., et al.
186. Student: Constraining Earthquake Nucleation using
Response of Seismicity to Transient Slow-slip Event andHydrological Surface Load. Sirorattanakul, K., Avouac, J.
187. Student: Towards Systematic Kinematic Source
Models of Historically Large Earthquakes. SolaresColón, M. M., Melgar, D., Bato, M. G.
189. Study on the Latest Activity and the Maximum
Potential Earthquake in the Middle Section of the
Minjiang Fault. Zhou, C., Han, Z., Guo, P., Niu, P.

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Thursday, 2 May 2024—Oral Sessions
Presenting author is indicated in bold.
K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

3D Wavefield Simulations:
From Seismic Imaging to
Ground Motion Modelling(see page 1201).

Illuminating Complex,
Multiplet Earthquake
Sequences at
Kahramanmaras (Turkiye),
Herat (Afghanistan), andBeyond (see page 1318).

Detecting, Characterizing
and Monitoring Mass
Movements (see page 1262).

Seismic Monitoring,
Modelling and Management
Needed for Geothermal
Energy and Geologic
Carbon Storage (see page1393).

8:00 amInvited: High Frequency(2+ Hz), 3D Wavefield
Simulations of Large
Earthquakes on the Southern
Whidbey Island Fault,
Washington State. Stone, I.,
Wirth, E., Grant, A., Frankel,
A.

The October 2023 Herat,
Afghanistan Earthquake
Quadruplet - Aftershock
Locations and Moment
Tensors. Braunmiller, J.,
Ghods, A.

Infrasound Array Analysisof Rapid Mass Movements inMountain Regions. Johnson,
J., Marchetti, E.

DOE’s Best Practices
for Addressing Induced
Seismicity Associated With
Enhanced Geothermal
Systems. Majer, E.,
Robertson-Tait, A., Nelson, J.,
Savy, J., Wong, I.

8:15 am

3D Kinematic Models of
Ground Motions of Cascadia
Megathrust Earthquakes:
Preliminary Results andComparison to Paleoseismic
Subsidence Data. Dunham,
A., Wirth, E., Kim, J.,
Schmidt, D., Grant, A., et al.

Student: Long-Term
The Mount Rainier Lahar
Seismicity of the East
Detection System: Risk
Anatolian Fault System
Mitigation for an Unlikely,
and Its Relationship With
but Potentially Catastrophic,the 2023 Mw 7.8 & 7.6
Event. Moran, S. C., Thelen,
Kahramanmaraş (Se Türkiye) W. A., Iezzi, A. M., Kramer, R.
Earthquake Doublet. Zhou,
L., Pauk, B., et al.
Y., Ding, H., Ghosh, A., Ge, Z.

Geophysical Monitoring of
Anthropic Underground
Operations in Italy: An
Operative Center for Risk
Mitigation. Saccorotti, G.,
Anderlini, L., Anselmi, M.,
Braun, T., Caciagli, M., et al.

8:30 amBroadband Ground Motion
Simulations for a Türkiye-like
Earthquake “Doublet” on
the Hayward and Calaveras
Faults. Graves, R., WangConnelly, J., Thompson, E.,
Quitoriano, V., Wald, D., et al.

Student: The
Kahramanmaras (Turkey)
Earthquake Multiplet
Sequence Revealed by Deep
Learning Computer Vision.
Tan, F., Nissen, E., Kao, H.

An Open-Source Tool for
Operational Forecasting ofInduced Seismicity (Orion).
Kroll, K., Sherman, C. S.,
Geffers, G., Wang, C., He, D.
J., et al.

Time

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Characterization of a Debris
Flow at Mount Rainier via
Seismoacoustics and a Novel
Usage of a Laser Rangefinder.
Iezzi, A., Thelen, W. A.,
Bryant, E., Gabrielson, C.,
Moran, S. C., et al.

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April 2024

Tikahtnu Ballroom C Tikahtnu Ballroom E/F Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Characteristics
and Mechanics ofFault Zone Rupture
Processes, from Microto Macro Scales (seepage 1244).

Advancements in
Forensic Seismology
and Explosion
Monitoring (see page1208).

Seismology in the
Oceans: Pacific
Hemisphere andBeyond (see page1410).

From Earthquake
Recordings to
Empirical GroundMotion Modelling(see page 1292).

Network Seismology:
Recent Developments,
Challenges andLessons Learned (seepage 1353).

8:00 amTemporally-Varying
Creep Behavior on
the East Anatolian
Fault and the Endof the 2023 Pazarçik
Rupture. Funning,
G. J., Hofstetter, C.,Özarpacı, S.

Invited: Seismology in
Support of Negotiation,
Implementation, andVerification of Nuclear
Test Ban Treaties andScience Diplomacy:
Where It Started and
DOS R&D Challenges.
Jih, R.

Structure of the
Cascadia Margin
Offshore Northern
Oregon (44.5-46deg
N) From Casie21-OBS
Wide-Angle Seismic
Profiles. Canales, J.,
Jian, H., Mann, M.,
Miller, N., Carbotte,S., et al.

From Satellites to Soil
Response: Analyzing
Body Wave locity
Variations at Shallow
Depths in Sync
With Satellite Soil
Moisture. Kyriou,
A., Roumelioti, Z.,
Hollender, F.

Making Phase-Picking
Neural Networks
More Consistent andInterpretable. Park,Y., Delbridge, B. G.,
Shelly, D. R.

8:15 amStudent: ModelingThree-dimensional
Rupture Propagation
Nonlinear Calculations
Into Creeping Faults by of Explosions at the
Thermal Pressurization. Novaya Zemlya Nuclear
Stephenson, O., Vescu, Test Site. Stevens, J. L.,
V., Lapusta, N.
O’Brien, M. S.

Student: A Newly
Identified MassTransport Deposit in
the Guaymas Basin,
Gulf of California:
Implications for
Regional Tectonics
and Continental Slope
Stability. Piña, A.,
Stock, J., Lizarralde, D.,
Berndt, C., GonzálezFernández, A., et al.

Invited: Seeking
for Dependencies ofthe High-Frequency“Kappa” Parameter ofEarthquake Spectrum
on Weather/climate
Conditions. Grendas,
I., Roumelioti, Z.,
Hollender, F.

Evaluation of Deep
Learning Phase
Picking Models.
Parikh, N., Myren,
S., Rael, R., Flynn, G.,
Casleton, E.

8:30 amAcross-Slab
Propagation and Low
Stress Drops of Deep
Earthquakes in the
Kuril Subduction Zone.
Turner, A. R., Ferreira,A. M. G., Brantut, N.,
Faccenda, M., Kendall,E., et al.

Discriminating Collapses Implications of MultiFrom Explosions andLayer High-Vp/Vs
Earthquakes. Walter,
Seafloor Sediments
W. R., Pasyanos, M. E.,
Characterized Using
Ichinose, G., Price, A.,
Passive Ocean Bottom
Pennington, C., et al.
Seismic Data: Toward
Improving Crustal
and Mantle Structure
Analysis. Kim, H.,
Kawakatsu, H.,
Akuhara, T., Takeuchi,N.

Beyond Site Response:On the Importance ofInstallation Depth on
the Quality of Seismic
Recordings - Exampleof Measurements
Carried Out at EposFrance Seismological
Network Stations.
Hollender, F.,
Iacobucci-Jund, H.,
Douste-Bacqué, I.,
Rischette, P., Buscetti,M., et al.

A Comparisonof Machine
Learning Methodsof Association.
Pennington, C. N.,
McBrearty, I., Kong,
Q., Walter, W. R.

Time

Volume 95•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1159

Thursday, 2 May (continued)
K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

3D Wavefield Simulations:(continued)

Illuminating Complex,
Multiplet Earthquake (continued)

Detecting, Characterizing
Seismic Monitoring,and Monitoring (continued) Modelling (continued)

8:45 am

Toward High-Frequency
Three-Dimensional Green’s
Function Databases. Modrak,
R. T., Kintner, J. A., Nelson,
P., Gao, K., Zhou, R., et al.

Surface Expression of theInvited: Student:
Narlı and East Anatolian Fault Identification of Lahar
Rupture Intersection in the
Signals: A Supervised
2023 M7.8 Pazarcık, Türkiye Learning Model Applied to
Earthquake. DuRoss, C. B.,
Monitoring Data of Volcan
Reitman, N. G., Hatem, A.
De Fuego, Guatemala. Bejar,E., Mason, H., Lavrentiadis,G., Waite, G. P., EscobarG., et al.
Wolf, R., Johnson, J. B., Bosa,
A., et al.

9:00 amStudent: Iterative Global
3D Centroid Moment Tensor
Inversions Using Stored
Global Green Functions
From Glad-M25. Sawade, L.,
Ekström, G., Ding, L., Peter,
D., Liu, Q., et al.

Seismic Analysis of the 2023
Earthquake Sequence inSoutheast Türkiye: Insights
From Mainshocks andAftershocks. Büyükakpınar,P., Petersen, G., Vera
Sanhueza, F., Metz, M., Cesca,S., et al.

Time

9:15–10:30 am

10:30 am

1160|

Tikahtnu Ballroom A/B

Forecasting the Next Largest
Earthquake During EGS
Stimulations. Grigoratos, I.,
Kwiatek, G., Wiemer, S.

Lahar Early Warning at
Invited: Stress-Based
Volcano Santiaguito: A
Forecasting of Seismicity
Classical and a Deep Learning Induced by Geothermal
Approach. Jozinović, D.,
Operations and CO2 Storage.
Massin, F., Roca, A., Clinton, Avouac, J.
J.

Poster Break
3D Wavefield Simulations:
From Seismic Imaging to
Ground Motion Modelling(see page 1201).

Illuminating Complex,
Multiplet Earthquake
Sequences at
Kahramanmaras (Turkiye),
Herat (Afghanistan), andBeyond (see page 1318).

Detecting, Characterizing
and Monitoring Mass
Movements (see page 1262).

Seismic Monitoring,
Modelling and Management
Needed for Geothermal
Energy and Geologic
Carbon Storage (see page1393).

SPECFEM++: A Modular andPortable Spectral-element
Framework for Seismic Wave
Propagation. Kakodkar, R.
R., Tromp, J.

High-Resolution Fault
Imaging From Fault Zone
Guided Waves Recorded
by Dense Arrays in the
Aftershock Zone of the 2023
Kahramanmaras Earthquake
Sequence in Southern
Türkiye. Peng, Z., Mach, P. V.,
Ding, C., Yalvac, O., Sevim,F., et al.

Student: Towards Buildinga Machine Learning Based
Automatic Detection System
for Surface Events in the
Pacific Northwest. Kharita,A.

Student: Factors Controlling
Rate and Magnitudes ofInduced Seismicity. Kim, T.,
Avouac, J.

Seismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Tikahtnu Ballroom C Tikahtnu Ballroom E/F Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Characteristics andMechanics of Fault
Zone (continued)

Advancements in
Forensic Seismology(continued)

Seismology in the
Oceans: (continued)

From Earthquake
Recordings (continued)

Network Seismology:(continued)

8:45 amInvited: Fault
Zone Material
Heterogeneities May
Trigger Repeating
Earthquakes in Kanto,
Japan. Huang, Y., Ide,
S., Kato, A., Yoshida,K., Jiang, C.

Source Characterizationand Uncertainty
Quantification of theNorth Korean Nuclear
Tests 2006-2017.
Alfaro-Diaz, R. A.,
Kintner, J. A., Phillips,
S., Delbridge, B.,
Carmichael, J. D.

Estimating the
Extent of Lowtemperature Ductile
Deformation in the
Lithosphere Using
Seismic Anisotropy
Measurements Aroundthe Alpine Fault.
Mark, H. F.

Student:
Student: A
Perturbations ofComprehensive
Free-Field Seismic
Earthquake Focal
Recordings Caused
Mechanism Catalog
by Soil-Structure
for Nevada ObtainedInteraction, From the Through Deep
Effects of Buildings to Learning Algorithms.
the Impact of Coupling Chatterjee, A., Srikar,
Slabs: Preliminary
G., Pennington, C.
Results From Empirical N., Walter, W. R.,
Studies Carried Out
Trugman, D. T.
in Greece. Rischette,
P., Hollender, F.,
Theodoulidis, N.,
Roumelioti, Z., Perron,V., et al.

9:00 am

The Alto Tiberina Near
Fault Observatory: A
State of Art Monitoring
Infrastructure forStudying Earthquakes
Faults and Preparatory
Phases. Chiaraluce, L.

Regional
Characterizationof Natural andAnthropogenic Seismic
Events for Monitoring
Efforts With Machine
Learning. Barama, L.,
Kong, Q.

Crustal andUppermost Mantle
Structure North of the
Gloria Fault Inferred
From OBS-Recorded
Surface Waves. Pinzon,J., Custódio, S.,
Silveira, G., Krüger, F.,João, M., et al.

Invited: Seismic
Station Installations
and Their Impact on
Recorded Signals andDerived Quantities.
Castellaro, S., Musinu,G., Alessandrini, G.

Student: Deep
Learning Enhanced
Earthquake Catalog forNorthern California.
McBrearty, I. W.,
Beroza, G. C.

Time

9:15–10:30 am

10:30 amVolume 95•

Poster BreakCharacteristics
and Mechanics ofFault Zone Rupture
Processes, from Microto Macro Scales (seepage 1244).

Advancements in
Forensic Seismology
and Explosion
Monitoring (see page1208).

Seismology in the
Oceans: Pacific
Hemisphere andBeyond (see page1410).

From Earthquake
Recordings to
Empirical GroundMotion Modelling(see page 1292).

Network Seismology:
Recent Developments,
Challenges andLessons Learned (seepage 1353).

Dynamic Rupture
Simulations on the
Alpine Fault, New
Zealand: Investigating
the Role of Fault
Geometry on Rupture
Size and Behavior OverMultiple Earthquake
Cycles. Lozos, J.,
Warren-Smith, E.,
Townend, J.

Source-Type
Discrimination Using
Phase and Amplitude
Metrics Derived From
Nonlinear Alignment
Methods. Ramos, M.
D., Tibi, R., Emry, E. L.,
Young, C. J.

Overthickened
Lithosphere Beneaththe Blanco Transform
Faults. Bao, X., Dai,A., Yang, Y., Hu, J.,
Zhang, W.

Three Relational
Databases in Supportof Model Development
for Earthquake Hazard
Products. Hearne,
M. G., Cunningham,
A. E., Knodel, E.
J., Ambruz, N. B.,
Aagaard, B. T., et al.

An Agent Based Modelto Quantify Gains in
Network Processing.
Carmichael, J. D.

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1161

Thursday, 2 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

3D Wavefield Simulations(continued)

Illuminating Complex,
Multiplet Earthquake (continued)

Detecting, Characterizing
and Monitoring Mass
Movements (continued)

Seismic Monitoring,
Modelling and Management(continued)

10:45 amStudent: Forward
Strong Ground Motion
Simulation of Air and Ground Characterization for theVibration Induced by Series
6 February 2023 Mw 7.8of Wind Turbines Using the
Pazarcık Earthquake inSpectral-Element Method.
Kahramanmaraş, Türkiye.
Fitzgerald, J., Wiboonwipa,
Tang, Y., Şeşetyan, K., Mai,
N., Gharti, H., Braun, A.
M.

Source Characterization of
How to Tame an Earthquake
Surface Events in the Pacific(Analogue). Schultz, R.
Northwest. Denolle, M. A.,
Skene, F., Smoczyk, N., Ni, Y.,
Kharita, A., et al.

11:00 amMultiscale Rupture Modeling:
Bridging Laboratory Acoustic
Emissions and Earthquake
Ground Motions. Gu, C.,
Meng, C.

Conjugate Strike-Slip
Faulting in the Truckee Basinof California, NorthernWalker Lane. Pierce, I. K.
D., Koehler, R., Owen, L.,
Wesnousky, S., Figueiredo, P.
M., et al.

Dissecting Seismic Signals to
Estimate Landslide Volume.
Collins, E., Allstadt, K. E.,
Toney, L. D.

Picoseismic Response of
Hectometer-Scale Fracture
Systems to Stimulation
With Cm-Scale Resolution
Under the Swiss Alps, inthe Bedretto Underground
Laboratory. Obermann, A.,
Rosskopf, M., Durand, V.,
Plenkers, K., Bröker, K., et al.

11:15 am

Local Geological Changes
and Simplicial Remeshing for
Wave Propagation. Cupillard,P., Caumon, G., Anquez, P.,
Legentil, C., Glinsky, N., et al.

How Often Do Subduction
Interfaces and Overriding
Upper-Plate Faults Rupturein the Same Earthquake (OrClose Enough in Time to Be
the Same Situation)?. Rollins,
C., Penney, C. E., Howell, A.,
Fry, B., Nicol, A.

Radial Backprojection
Imaging of Recent Mass
Movements in Alaska. Haney,
M. M., Toney, L., Karasozen,
E.

Student: Characterization of
Fracture Activation During
EGS Stimulation Using
Waveform Cross-Correlation:
An Example Application at
Utah Forge. Asirifi, R.

11:30 am

3D Multiresolution Velocity
Model Fusion With
Probability Graphical Models.
Zhou, Z., Gerstoft, P., Olsen,
K. B.

2021 and 2022 North Coast
California Earthquake
Sequences Light Up Gorda
Plate Faults Beneath theNorth American Plate.
Hellweg, M., Dreger, D. S.,
Lomax, A., McPherson, R. C.,
Dengler, L. A.

Enhancing Real-TimeLandslide Detection for
Improved Tsunamigenic
Landslides in Alaska.
Karasozen, E., West, M. E.

Circulation Experiments at
Utah Forge: Post-Shut-in
Fracture Growth Revealedby Limited Near-Surface
Monitoring. Niemz, P.,
McLennan, J., Pankow, K. L.,
Rutledge, J., England, K.

noon–
2:00 pm
1162|

Annual Business and Awards Luncheon

Seismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C Tikahtnu Ballroom E/F Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Characteristics andMechanics of Fault
Zone (continued)

Seismology in the
Oceans (continued)

From Earthquake
Recordings (continued)

Network Seismology(continued)

Advancements in
Forensic Seismology(continued)

10:45 amDeformation
Seismic Observations
Partitioning, Directivity and Aftershock Analysis
Effects, and Stress-Drop from a Fully Coupledof Seismicity Along the Chemical Explosion
Main Marmara Fault
in Layered Tuff.
Offshore Istanbul/
Sprinkle, D., St. Clair, J.,
Türkiye in the Light
Chojnicki, K., Knox, H.,of an Overdue M7+
Strickland, C., et al.
Earthquake. Bohnhoff,
M., Cheng, X.,
Martinez-Garzon, P.,
Becker, D., Kwiatek, G.,
et al.

The Anelastic
Fingerprint of
Small-Scale
Convection: GrainSize Reduction in
Pacific Asthenosphere
Revealed by Regional
Shear Attenuation.
Russell, J. B., Dalton,
C., Havlin, C.,
Holtzman, B., Eilon,
Z., et al.

A Magnitude
Invariant Workflow
for AutomatedEnd-to-End Ground
Motion Processing.
Lavrentiadis, G., Shi,
Y., Aday, K., Asimaki,D.

Seismology as aService: Portable
Product Generation
at the Southern
California Seismic
Network Using
Service-Oriented
Architecture andCloud Computing. Yu,
E. C., Tepp, G., Tam,R., Bhaskaran, A.,
Chen, S., et al.

11:00 amInvited: Insight Into
Depth Variations in
Effective Stress andFault Strength From
Geodynamic-Seismic
Cycle and Earthquake
Dynamic Rupture
Modeling. Madden,
E. H., Gabriel, A. A.,
Ulrich, T., van Dinther,Y., van Zelst, I.

Seismic Source
Parameters andScaling Relations for
Microseismic LowerYield Military Explosive
Events. Milburn, T. W.

An Ocean-Bottom
View of Mantle
Convection Beneaththe Pacific Basin.
Gaherty, J., Eilon, Z.,
Russell, J., Phillips, J.,
Hariharan, A., et al.

Student: Epistemic
Uncertainty Associatedto Parametric and
Non-Parametric Git
Results Related toInitial Parametrization
and Target Region
Dataset: Applicationon the Epos-France
Database. Buscetti, M.,
Traversa, P., Hollender,F., Perron, V.

NEIC Developments:
Updates on the U.S.
Geological Survey
National Earthquake
Information
Center’s Earthquake
Monitoring Systems.
Patton, J., Guy, M.,
Earle, P., Yeck, W.,
Cole, H.

11:15 amDeep Slip Occurs Prior
to Surface Creep Eventson the San Andreas
Fault. Gittins, D. B.,
Hawthorne, J. C.

Discriminating S-Wave
Polarization Anglesof Explosive andEarthquake Sources.
Nelson, P., Creasy, N.

Deep Learning for
Deep Earthquakes in
Oceans: Insights From
Obs Observations of
the Tonga Subduction
Zone. Wei, S. S., Xi, Z.,
Zhu, W., Beroza, G. C.,
Jie, Y., et al.

Ground Motion
Models Uncertainties
and Variability: The
Impact of Seismic
Station Installation
Conditions andEarthquake Catalog
Quality. Traversa, P.,
Buscetti, M., Arroucau,
P., Kotha, S. R.,
Hollender, F., et al.

gCent: Geodetic
Centroid Products
for Earthquake
Monitoring. Barnhart,W.

11:30 amSimulating the
Simulations of Local
Earthquakes andFormation andWave Propagation Effects Slab Morphology in
Evolution of Complex
on the Performance ofSouthern Mariana andFracture Patterns
P/s Source Discriminant. Yap Subduction Zones.
Arising From Shallow
Pitarka, A., Walter, W.
Yang, H., Zhu, G.
Strike-Slip Faulting
R., Pyle, M.
With Finite and Discrete
Element Analyses.
Baden, C. W., Nevitt, J.
M., Garcia, F. E.

Earthquake Ground
Motion Insights
From the USGS Lake
Almanor, California,
Aftershock Nodal
Array Deployment.
Parker, G. A., Baltay,
A. S., Hirakawa, E.
T., Catchings, R. D.,
Goldman, M. R., et al.

Overcoming
Challenges in NearField Seismic Velocity
Estimation: Insightsfrom continuos GPS
and Strong Motion
Data. Riquelme, S.,
Crempien, J., Koch, P.

noon–
2:00 pm
Volume 95

Annual Business and Awards Luncheon•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1163

Thursday, 2 May (continued)
K’enakatnu 6/Boardroom

Kahtnu 1

3D Wavefield Simulations:
From Seismic Imaging to
Ground Motion Modelling(see page 1201).

Six Decades of Tsunami
Detecting, Characterizing
Science: From the Source of and Monitoring Massthe 1964 Tsunami to Modern Movements (see page 1262).
Community Preparedness(see page 1415).

Seismic Monitoring,
Modelling and Management
Needed for Geothermal
Energy and Geologic
Carbon Storage (see page1393).

2:00 pm

Multi-Scale Seismic Imagingof Fault-Zone Structures inSouthern California With
Full-Waveform Inversions ofRegional and Dense Array
Data. Li, G., Ben-Zion, Y.

Invited: The 2021 Antarctic(South Sandwich) Tsunami
as Recorded in the North
Pacific. Rabinovich, A. B.,
Tsukanova, E., Thomson, R.
E.

Seismic Collapse Mechanismsof Large (M~4) Rock and
Ice Avalanches in Southeast
Alaska. Alvizuri, C., Rupper,N., Karasozen, E.

Geophysical Monitoring for
Feeding Decision Support
Tools: The Crucial Role ofUncertainty for a Sound
Management of Induced
Seismicity. Garcia, A., Zaheer,
A., Faenza, L., Danesi, S.,
Braun, T., et al.

2:15 pm

Invited: Student: Global
Source-Encoded Waveform
Inversion: Preliminary
Results. Cui, C., Bachmann,E., Tromp, J.

Invited: Re-evaluating
Global Threat of Tsunamis
Generated by Air-pressure
Waves from Volcano
Explosions. Titov, V.

The Seismic Puzzles ofthe 2022 Chaos Canyon
Landslide in Rocky Mountain
National Park. Allstadt, K.,
Coe, J., Collins, E., Rengers,F., Mangeney, A., et al.

B-Positive for Induced
Seismicity Catalogs
With Time-Varying
Incompleteness? ProceedWith Caution. MuntendamBos, A. G.

2:30 pm

Student: LLNLGlobeFWI
Analysing Alpine Fault
Earthquakes: First Iterations
Using a Semi-Automatic
FWI Framework Applied to
the Globe With Spiral as theStarting Model. Vazquez, L.,
Morency, C., Simmons, N. A.

Multi-Scale GeophysicalNew Insights on the Åknes
Characterization and Tsunami Rockslide (Norway) Using
Modeling of Active Listric
Borehole Microseismic Data.
Normal Faults Offshore Grays Langet, N., Oye, V., Grøvan
Harbor, Wa. Watt, J., Geist,
Aspaas, A., Lacroix, P.,
E., La Selle, S., Hill, J.
Renard, F.

Heimdall: A Graph-Based
Seismic Detector and Locatorfor Microseismicity. Bagagli,M., Grigoli, F., Bacciu, D.

2:45 pm

Homogenized Full Waveform
Inversion : Application to
Earth Model for Long Period
Seismic Waves. Colvez, M.,
Burgos, G., Capdeville, Y.,
Guillot, L.

Real-Time Prediction of
Tsunami Amplitude Using
Gaussian Process Regression.
Nichols, T.

Student: Characterizing
Subsurface Structures for
Geologic Carbon Storage at
Iron Mountain in Utah. Li,
D., Huang, L., Gao, K., Chen,
B., Zheng, Y., et al.

Time

1164

|

Seismological Research Letters

Kahtnu 2

Tikahtnu Ballroom A/B

How Do Slow-moving
Landslides Maintain Steady
Motion?. Xu, Y., Bürgmann,R., Bilham, R.

www.srl-online.org•

Volume 95•

Number 2B•

April 2024

Tikahtnu Ballroom C Tikahtnu Ballroom E/F Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Regional-Scale
Hazard, Risk and Loss
Assessments (see page1382).

Advancements in
Forensic Seismology
and Explosion
Monitoring (see page1208).

Multidisciplinary
Approaches for
Volcanic Eruption
Forecasting (see page1348).

From Earthquake
Recordings to
Empirical GroundMotion Modelling(see page 1292).

Network Seismology:
Recent Developments,
Challenges andLessons Learned (seepage 1353).

2:00 pm

Development ofa Physics-Guided
Non-Ergodic Ground
Motion Model for
the Groningen,
Netherlands Region.
Lavrentiadis, G., Oral,E., Aday, K., Asimaki,D.

Moment Tensor
Inversion and Its
Uncertainty from Green’s
Functions with Different
Algorithms. Zhou, R.,
Saikia, C. K., RomanNieves, J., VanDeMark,T. F.

Invited: Student:
Fracture Insights andPredicting Failures:
Acoustic Emission
Study in Peteroa
Volcano’s Basalt Rock.
Vesga-Ramírez, A.,
Zitto, M. E., Filipussi,
D., Camilión, E.,
Piotrkowski, R., et al.

Ground Motion and
Entropy. Clements, T.,
Cochran, E., Baltay, A.
S., Minson, S., Yoon, C.

Student: Precision
and Accuracy ofEarthquake Locators:
Insights From a
Synthetic 2019
Ridgecrest Sequence
Experiment. Yu, Y.,
Ellsworth, W. L.,
Beroza, G. C.

2:15 pm

Developing a Datacentric Workflow for
Seismic Source Model
Construction andTesting. Styron, R. H.,
Pagani, M., Johnson, K.
E., Bayliss, K.

Physics Experiment 1:
Chemical Explosive, Gas
Tracer, Electromagnetic,
and Atmospheric
Experiments for
Improved Monitoringof Nuclear-Explosive
Testing. Myers, S., Foxe,
M., Dzenitis, B., Knox,
H., Cari Seifert, C., et al.

Small Earthquakes
Matter for Triggering
Volcanic Unrest.
Gomberg, J., Prejean,S., Taveras, O., Bodin,
P., Pacheco, J., et al.

Comparisons of Recent Improving ShearPrediction Models of
Arrival Time Estimates
Ground-Motion andfor Real-Time
Seismic Duration for
Association and
Mexican Interplate and Location Algorithms.
Intraslab Earthquakes Baker, B., Armstrong,
Including the Vertical A. D., Pankow, K. L.
Component and V/H
Ratios. García-Soto,
A., Jaimes, M.

2:30 pm

Invited: Developing
Software to Assess the
Seismic Risk of Natural
Gas Infrastructure:
OpenSRA. Zheng, B.,
Largent, M., WatsonLamprey, J., Bray, J.,
Abrahamson, N. A.,
et al.

Seismo-Acoustic Signals
From an Accidental
Chemical Explosion inSouth Korea. Park, J.,
Arrowsmith, S., Che, I.,
Hayward, C., Stump, B.

Toward Unbiased
Volcano-Seismic
Monitoring:
Leveraging Weakly
Supervised Learning
for Comprehensive
Insights. Titos, M.,
Benítez, M., Carthy, J.,
Ibáñez, J.

Using Proxies
Obtained From
Horizontal-to-Vertical
Spectral Ratio toReduce the Epistemic
Uncertainty in Ground
Motion Models. Yazdi,
M., Anderson, J. G.,
Motamed, R.

Comparing ThreeDimensional Seismic
Velocity Models for
Location Accuracy.
Begnaud, M., Conley,A., Davenport, K.,
Porritt, R., Ballard, S.,et al.

2:45 pm

Invited: Addressing
Challenges inRegional Seismic
Risk Assessments in
British Columbia: M9
Cascadia Subduction
Zone Earthquakes,
Deep Sedimentary
Basin Amplification
and Non-Ductile
Reinforced Concrete
Shear Wall Buildings.
Molina Hutt, C.,
Kakoty, P.

Estimating Crustal
Velocity Structure in
Alaska From Acousticto-Seismic Coupling
From the 2022 Hunga
Eruption, Tonga.
Macpherson, K. A.,
Fee, D., Coffey, J. R.,
Awender, S., Chow, B.,
et al.

Volcanic Eruption
Forecasts ThroughSeismic Data
Assimilation: The
2023 Paroxysms of
Shishaldin Volcano,
Alaska. Girona, T.,
Haney, M. M., Fee, D.,Power, J.

Are Ground
Motions Different
for Aftershocks
or Earthquakes
Doublets?. Baltay,
A. S., Parker, G. A.,
Abrahamson, N. A.,
Hanks, T. C.

Regionalization of ML
and Its Relation to
Mw. Herrmann, R. B.,
Benz, H. M.

TimeVolume 95•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1165

Thursday, 2 May (continued)
Time

3:00 pm

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

3D Wavefield Simulations(continued)

Six Decades of Tsunami
Science (continued)

Detecting, Characterizing
Seismic Monitoring,and Monitoring (continued) Modelling and Management(continued)

Adjoint-State Traveltime
Tomography (tomoatt.com).
Tong, P., Chen, J., Nagaso, M.,
Hao, S., Xu, M.

A Behavioral Theory
Big Tsunamis in Little Lakes.
Framework for Tsunami
Higman, B., Karasozen, E.,
Preparedness. Grant Ludwig, Geertsema, M., Schwartz, S.
L.

3:15– 4:30 pm

Tikahtnu Ballroom A/B

3D Fault Detection on a
Seismic Migration Imageat the Lightning Dock
Geothermal Area. Huang, L.,
Wu, B., Gao, K., Li, D., Zheng,Y., et al.

Poster BreakK’enakatnu 6/Boardroom

Kahtnu 2

Tikahtnu Ballroom C

Applications and Discoveries Special Applications inin Cryoseismology AcrossSeismology (see page 1420).
Spatial and Temporal Scales(see page 1235).

New Insights into theDevelopment, Testing
and Communication ofSeismicity Forecasts (seepage 1367).

Regional-Scale Hazard, Risk
and Loss Assessments (seepage 1382).

4:30 pm

Student: Integrated
Geophysical and Temperature
Sensing Techniques Towards
Scalable Monitoring ofPermafrost Variability in
Utqiaġvik, AK. Tourei, A.,
Ji, X., Martin, E. R., Xiao, M.,
Rocha dos Santos, G. F., et al.

Student: Receiver Functionsin the Los Angeles Basin.
Villa, V., Clayton, R.,
Gkogkas, K., Lin, F.

Invited: Testing Rateand-State Predictions of
Aftershock Decay. Page, M.,van der Elst, N., Felzer, K.

Probabilistic Approach forSite Response Analysis andSeismic Microzonation.
Ansal, A.

4:45 pm

Student: Observations Froman Active Seismic Distributed
Acoustic Sensing Survey,
Combatant Col, British
Columbia. Manos, J. M.,
Lipovsky, B., Gräff, D.

Resolving the Structure of the Time-Dependent Earthquake
Los Angeles Basin ThroughForecasts With Pre-Existing
High-Resolution Seismic
Populations of Faults:
Tomography. Biondi, E., Li, J., Application to the Groningen
Clayton, R., Zhan, Z.
Gas Field, the Netherland.
Dahm, T., Hainzl, S.

Student: Analysis of
Shakemap Residuals for
Spatially Variable Site
Terms. Cunningham, A. E.,
Knodel, E. J., Hearne, M. G.,
Thompson, E. M., Worden, C.
B., et al.

5:00 pm

Plucking Base Notes: Seismic
Character of a Potential
Glacial Quarrying Event
at Saskatchewan Glacier,Canadian Rocky Mountains.
Stevens, N. T., Hansen, D. D.,
Zoet, L. K., Alley, R. B.

Student: Upper-Plate
Seismicity and Focal
Mechanism for Studying theStress State in the Mendocino
Triple Junction. Islam, M.,
Gong, J.

Regionalized Earthquake
Source Models of Subduction
Interface Earthquakes.
Skarlatoudis, A., Thio, H.
K., Somerville, P., Ahdi, S. K.,
Condon, S.

Time

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Kahtnu 1

What Drives the Variability
in Earthquake Sequence
Productivity in California and
Nevada?. Trugman, D. T.,
Ben-Zion, Y.

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Volume 95•

Number 2B•

April 2024

Time

3:00 pm

Tikahtnu Ballroom C Tikahtnu Ballroom E/F Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Regional-Scale
Advancements inHazard, Risk and Loss Forensic Seismology(continued)(continued)

Multidisciplinary
Approaches for (continued)

From Earthquake
Recordings to (continued)

Network Seismology:
Recent (continued)

Using Comparative
Subductology toConstrain Future
Subduction Zone
Earthquake Losses.
Wald, D. J., Hayes, G.,
Haynie, K. L., Jaiswal,
K. S., Marano, K.

Source Mechanism
Why Did the Pulseand Catalog Statistics Like Ground-Motion
for the Last Decade
Differ Three Times inof Seismicity at the
Pgv and Tp Within
Campi Flegrei Volcanic a 3 Km Wide NearComplex, Italy.
Fault Region of the
Saccorotti, G., Bianco, 2023 Mw 7.8 Turkiye
F., Chiarabba, C.,
Earthquake?. Huang,
Piccinin i, D.
J., Sung, C., Kuo, C.,
Lin, C.

Noisy Stations
Make Earthquake
Magnitudes Larger.
Ringler, A., Ambruz,
N. B., Earle, P.,
Kragness, D., Shelly,D., et al.

Detection of Seismic andAcoustic Signals With
Serial Network Data
Fusion: Demonstration
Against Atmospheric
Explosions. Carmichael,J. D., Alfaro Diaz, R.,
Light, T., Blom, P.,
Gammans, C., et al.

3:15– 4:30 pm
Time

Poster BreakTikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Advancements in Forensic
Seismology and Explosion
Monitoring (see page 1208).

Multidisciplinary
Approaches for Volcanic
Eruption Forecasting (seepage 1348).

Leveraging Cutting-Edge
Cyber­infra­structure forLarge Scale Data Analysis
and Education (see page1339).

Cordilleran Strike-Slip
Faults as Seismogenic andSeismological Features (seepage 1249).

Invited: Advancing USGS
Scientific Modeling ThroughCloud Computing. Haynie,
K. L., Hunsinger, H.,
Martinez, E., Brito Silveria, L.,
Cassidy, K., et al.

Student: Is the Rocky
Mountain—Tintina Trench
Tectonically Active?. Finley,T., Nissen, E., Cassidy, J.,
Leonard, L., Sethanant, I.,et al.

4:30 pm

Surface-to-Space Acoustic
Resonance in the Earth’s
Propagation Model Validation Crust as a Generation
Using Chemical Explosion
Mechanism of Very-LongSources: The DARPA
Period Volcanic Tremor. Xia,
AtmoSense AIRWaveS
Y., Feng, X., Chen, X.
Project. Nayak, M., Snively, J.
B., Sabatini, R., Bowman, D.
C., Egan, S.

4:45 pm

Solid/atmosphere Moment
Partitioning in Hypervelocity
Impacts on Mars From
Seis Recorded Seismic andAcoustic Signals and High
Resolution Crater Imaging.
Lognonné, P. H., Bill, C.,
Collins, G. S., Daubar, I. J.,
Kim, D., et al.

Volcanic Eruption Forecasting Student: Parallel Processing
Using Shannon Entropy: 2021 of Large Seismic Data Sets
Tajogaite Eruption (Spain).
With Mspass. Wang, C.,
Rey-Devesa, P., Carthy, J.,
Wang, Y., Pavlis, G. L.,
Titos, M., Benítez, C., D’Auria, Mohapatra, S., Ma, J.
L., Prudencio, J. et al.

Evolution of Subsidiary
Faults Associated With the
Migration of the Mount
Mckinley Restraining
Bend, Denali Fault, Alaska.
Bemis, S. P., Benowitz, J. A.,
Goehring, B. M., Priddy, M.
S., Terhune, P. J.

5:00 pm

End-to-End Numerical
Simulation of Explosion
Cavity Creation, Cavity
Circulation Processes,
Subsurface Gas Transport,
and Prompt AtmosphericReleases. Ezzedine, S. M.,
Velsko, C., Vorobiev, O.

Automated Identification
and Characterization of
Very Long-Period Seismic
Events for Applications
in Monitoring Volcanic
Activities. Gammaldi, S.,
Delle Donne, D., Cantiello,P., Bobbio, A., De Cesare, W.,
et al.

Residual Yakutat Microplate
Velocity Drives Rapid Thrust
Faulting North of the Central
Denali Fault. Bender, A. M.,
Lease, R. O., Rittenour, T.

Volume 95•

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www.srl-online.org

Enabling Large Data Analysis
on the Earthscope Data
Repositories. Trabant, C.,
Dittmann, T., Bravo, T. K.,
Weekly, R. T., Johnson, S.,et al.

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Thursday, 2 May (continued)
K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom C

Applications andDiscoveries (continued)

Special Applications in
Seismology (continued)

New Insights into theDevelopment, Testing (continued)

Advancements in Forensic
Seismology (continued)

5:15 pm

Ross Ice Shelf Lamb Wave
Propagation and Permanent
Displacement Induced
by Whillans Ice Stream
Slip Events. Wiens, D. A.,
Aster, R. C., Nyblade, A. A.,
Bromirski, P. D., Gerstoft, P.,
et al.

Student: Complex
Deformation of the Northern
Deep Tonga Slab. Williams,
A., Wiens, D. A., Bergman,
E. A.

Invited: Student:
Modernizing Earthquake
Forecasts Testing andExperimentation:
CSEP Open-Software
Contributions. Iturrieta, P.,
Maechling, P. J., Savran, W.
H., Bayona, J., Silva, F., et al.

Student: Region-SpecificGeospatial Liquefaction
Model for Alaska by BayesianModel Updating of the Global
Liquefaction Model. Shirzadi,
H., Asadi, A., Baise, L. G.,
Moaveni, B.

5:30 pm

Seismology at South Pole,
Antarctica: History and
Future Opportunities.
Anthony, R. E., DuVernois,
M., Aster, R. C., Bainbridge,
G., Braun, J., et al.

Using Machine Learning
Algorithms to Explore theSeismoacoustic Wavefield at
an Industrial Facility. Chai,
C., Marcillo, O., Maceira, M.,
Park, J., Arrowsmith, S., et al.

Operational Earthquake
Forecasting in Japan: A Studyof Municipal Government
Planning for an Earthquake
Advisory or Warning in the
Nankai Region. Goltz, J. D.,
Yamori, K., Nakayachi, K.,
Shiroshita, H., Sugiyama, T.,et al.

A Regional EarthquakeTriggered Landslide
Susceptibility Map of
the Cook Inlet Region,
Southcentral Alaska. Ellison,
S. M., Allstadt, K. E.,
Thompson, E. M., Martinez,
S. N.

Time

6:00–8:00 pm

Joyner Lecture and Reception

Poster Sessions
Earth’s Structure from the Crust to the Core [Poster
Session] (see page 1271).
1. Cenozoic Uplift and Volcanism of Hangai Dome, Central
Mongolia Triggered by Lower Mantle Upwellings. Bao,
X., Wu, Y.
2. Single-Station Teleseismic Data Analysis and Structure
Imaging on Both Earth and Mars. Chen, L., Wang, X.,
Wang, X., Yang, R.
3. Student: Full-Waveform Inversion of the Upper Mantle
Beneath the Arabia-Eurasia Collision Zone. Clennett, E.
J., Liu, C., Grand, S. P., Becker, T. W.
4. Student: Finite Difference Approach to Seismic
Wavefield Modeling Across the Hawaii-Emperor Ridge.
Fujimoto, M., Dunn, R.
5. Student: Global Shear-Wave Amplitude Observations
using Full Waveform Modeling. Ghosh, A., Bozdag, E.,
Ritsema, J.
6. Building a Community Velocity Model for the Cascadia
Region and Beyond. Hooft, E., Delph, J. R., Grant, A.,
Sahakian, V. J., Share, P., et al.

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7. Student: Complex Upper Mantle Flow Beneath theSouthern Korean Peninsula Constrained by Shear Wave
Splitting and Numerical Mantle Convection Simulation.
Jo, K., Song, J., Kim, S.
8. Advancing the Resolution of Mid-Mantle Structures: FullWaveform Box Tomography of the Yellowstone Mantle
Plume. Kumar, U., Lyu, C., Munch, F., Romanowicz, B.
9. Student: Imaging the Deformation Belt of Western
Hispaniola Using Multi-Component Ambient Noise
Cross-Correlations. Lee, H., Rabade, S., Lin, F., Douilly,R.
10. Student: The Crust was Strengthened or Weakened
After Mantle Plume: Evidence from Tarim Basin. Li, W.,
Wang, X., Liang, X., Zuo, S., Shilin, L., et al.
11. Using Multiple Voronoi Partitions to Conduct ArrayBased Ambient Noise Surface Wave Imaging. Li, Z.,
Dong, S., Shi, C., Chen, X.
12. Challenges and Triumphs Seismic Surveying in a Historic
Underground Metals Mine. McBride, J., Lambeck, L.,
Rey, K. A., Nelson, S. T., Keach, II, R.
13. Searching for Blind Faults Beneath Metropolitan Los
Angeles: Preliminary Results From the 2023 San Fernando
Valley Array. Persaud, P., Juarez-Zuniga, A., Clayton, R.

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Number 2B•

April 2024

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Advancements in Forensic
Seismology (continued)

Multidisciplinary
Approaches for Volcanic(continued)

Leveraging Cutting-Edge(continued).

Cordilleran Strike-Slip
Faults as (continued)

5:15 pm

Joint Inversion of Body andSurface Waves at the RockValley Direct Comparison(Nevada) Study Site.
Syracuse, E. M., Rowe, C., Li,
D., Ranasinghe, N.

Volcanic Eruption Forecasts
Through Seismic Pattern
Recognition: The 2023
Paroxysms of Shishaldin
Volcano, Alaska. Girona, T.,
Burgos, V.

Student: Exploring the
Impact of Lossy Compression
on Passive Seismic Event
Detection and Arrival Time
Precision. Issah, A. S.,
Martin, E. R.

Seismic Imaging of theEastern Alaska Range Crustal
Structure. Miller, M. S.,
Zhang, P., Pickle, R., Waldien,
T. S., Roeske, S.

5:30 pm

Joint Inversion Using
Waveform, First-motion
Polarities and InSAR
Deformation for the 2007
Crandall Canyon Mine
Collapse, Utah. Chi-Durán,R., Dreger, D. S., Rodgers, A.,
Lindsay, D.

Enhancing Eruption
Forecasting at Axial
Seamount With Real-Time,
Machine Learning-Based
Seismic Monitoring. Wang,
K., Waldhauser, F., Schaff, D.,
Tolstoy, M., Wilcock, W., et al.

Invited: Towards End-toEnd Earthquake Monitoring
Using a Multitask Deep
Learning Model. Zhu, W.

Invited: Student: The
Crustal Magmatic Structure
Beneath the Denali Volcanic
Gap in Central Alaska Acrossthe Denali Fault. Rabade, S.,
Lin, F., Tape, C., Ward, K. M.,
Allam, A.

Time

6:00–8:00 pm

Joyner Lecture and Reception

14. Student: Receiver Function Inversion at Erebus Volcano,
Antarctica, With Multi-Station Weighting. Reisinger, R.,
Chaput, J., Aster, R. C., Grapenthin, R.
15. Shallow Imaging of the Valles of Caldera, Northern
New Mexico: Preliminary Results From Ambient Noise
Tomography. Rodriguez, E. E., Donahue, C., Roberts, P.
M., Maier, N.
16. Student: Lithospheric Modification in Northeastern
Alaska Interpreted From Full-Wave Ambient Noise
Tomography. Sassard, V., Yang, X., Ridgway, K. D., Flesch,
L. M.
17. High-Resolution Moho Depth Mapping Beneath the
Italian Peninsula and Carpatho-Pannonian Region Using
P-Wave Coda Autocorrelation. Thapa, H. R., Vlahovic,
G.
18. Shallow Seismic Structure of the Canary Islands Using
Local Earthquakes Recorded on an Amphibious Seismic
Network. Villasenor, A., Díaz-Suárez, E. A., del Fresno,C., Domínguez-Cerdeña, I., Dannowski, A., et al.
19. Student: Slab Morphology and Mantle Wedge Processes
in the Tonga Subduction Zone Revealed by Body-wave
Double-difference Tomography. Wang, F., Wei, S., Wiens,
D. A., Adams, A.

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20. Direct Inversion of Ambient Noise Multi-Modal Surface
Wave Dispersions for 3D Velocity Structures. Zhang, G.,
Yu, C., Chen, X.
21. S-Wave Seismic Data Interpretation for Channel Sand
Reservoir at Sanhu Area, West China. Zhang, R.
22. Multi-Scale, Finite-Frequency Body Wave Tomography
With Relative Kernels. Ben Mansour, W., Wiens, D.,
Maupin, V.
Seismology in the Oceans: Pacific Hemisphere and Beyond[Poster Session] (see page 1413).
23. Upper Mantle Velocity Structure Beneath the Galapagos
Archipelagos From the Analysis of Pn Wave Recorded
by Broadband Seismic Instruments and Mermaids. Ben
Mansour, W., Nolet, G.
24. Seismic Structure of the Young Oceanic Cocos Plate
From the Ridge to the Trench Axis Offshore the Mexico
Subduction Zone. Bécel, A., Hagemeier, D., Acquisto, T.,
Cruz-Atienza, V. M., Boston, B., et al.
25. Student: Adjoint Waveform Tomography of the
Cascadia Subduction Zone Using CASIE21 ControlledSource Data. Brunsvik, B. R., Miller, N., Eilon, Z., Jian,
H., Canales, J.

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Thursday, 2 May (continued)
26. Student: Seismicity of the Atlantis Massif Oceanic Core
Complex: 2005-2006 OBS Data Revisit. Dewaelsche, P.,
Gong, J.
27. Student: P-Wave Anisotropic Velocity Model of the
Galápagos Plume. Hufstetler, R. S., Hooft, E. E. E.,
Toomey, D. R., VanderBeek, B. P.
28. Shear Wave Velocity Structure of the Upper Mantle
Beneath the Oldest Pacific Seafloor Revealed by FiniteFrequency Traveltime Tomography. Kim, Y., Kang, H.,
Hung, S., Lin, P., Isse, T., et al.
29. A New 3D Reference Velocity Model for Offshore
Cascadia Based on CASIE21 Data. Miller, N., Canales, J.,
Carbotte, S., Han, S., Boston, B.
30. Student: Seismicity Observation in the Oldest PacificPlate Using Pacific Array (Oldest-1) Data. Park, J., Kim,
Y., Isse, T., Kim, K., Shiobara, H., et al.
31. The Upflow Experiment: Data Report for 49 Ocean
Bottom Seismometer Deployment in the Azores-MadeiraCanaries Region, Atlantic Ocean. Tsekhmistrenko, M.,
Ferreira, A., Miranda, M., Tilmann, F., Harris, K., et al.
32. Using Deep Learning Algorithms to Study Seismicity
Changes Preceding and Following the 2021 Central
Hikurangi Slow Slip Event, New Zealand. Kwong, S.,
Savage, M. K., Warren-Smith, E., Jacobs, K., Wallace, L.,et al.
Leveraging Cutting-Edge Cyberinfrastructure for Large
Scale Data Analysis and Education [Poster Session] (seepage 1340).
33. SCOPED Update: A Cloud and HPC Software Platform
for Computational Seismology. Denolle, M. A., Tape, C.,
Wang, Y., Bozdag, E., Waldhauser, F., et al.
34. Updates to the U.S. Geological Survey’s ProductDistribution Layer and Impacts on Comcat and Realtime
Systems. Hunsinger, H., Martinez, E., Brown, J., Cloutet,
Z., Haynie, K., et al.
35. Alaska Earthquake Center’s Workforce Development
Program Takes Shape. Nadin, E. S., Low, G., West, M. E.,
Mohler, M., Parcheta, C.
36. Cloud-Based Gnss Processing Pipeline for the Shakealert
Earthquake Early Warning System. Ronan, T., Hamilton,
A., Sievers, C., Dittmann, T., Berglund, H., et al.
37. Student: Deep Implicit Time Series Modeling for
Earthquake Phase Picking on Edge Devices. Tsai, A.,
Chuang, L., Peng, Z., El Ghaoui, L.
38. Using Learning Analytics to Evaluate the Instructional
Design and Student Performance in a Large-Enrollment
Scientific Computing Workshop. Haberli, G., Brudzinski,
M. R., Hubenthal, M.

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New Insights into the Development, Testing andCommunication of Seismicity Forecasts [Poster Session](see page 1368).
39. The Pattern of Earthquake Magnitude Clustering Basedon Interevent Distance and Time. Gossett, D., Brudzinski,
M. R., Xiong, Q., Hampton, J.
40. ETAS-positive: An Epidemic-Type Aftershock Model
That Is Insensitive to Catalog Incompleteness. van derElst, N.
41. Correlations of Deep Low-Frequency and Crustal
Earthquake Activity in Parkfield, Ca, and Implications
for Their Joint Use in Forecasting Frameworks. Farge, G.,
Dascher-Cousineau, K., Brodsky, E.
42. Stress Shadows: Insights into Physical Models of
Aftershock Triggering. Hardebeck, J., Harris, R. A.
43. The Generalized Long-Term Fault Memory Model
and Applications to Paleoseismic Records. Neely, J. S.,
Salditch, L., Spencer, B. D., Stein, S.
44. Prototyping Aftershock Forecast Maps and Products
Based on User Needs. Schneider, M., Artigas, B.
45. Observations of the Aftershock Sequences ofIntermediate-Depth Earthquakes Beneath Japan. Warren,
L. M., Igarashi, T., Kato, A.
Multidisciplinary Approaches for Volcanic Eruption
Forecasting [Poster Session] (see page 1350).
46. Information Theory in the Context of Volcano Seismic
Singals for Forecasting Purposes. Benítez, M., ReyDevesa, P., Prudencio, J., Marcelino, M., Ibáñez, J.
47. Student: Unraveling Dynamical Influences on Volcanic
Structures Through Seismic Signatures. Brenot, L.,
Caudron, C., Girona, T., Lecocq, T., Yates, A., et al.
48. Simulating Ground Deformation From Magma Migration
Utilizing a Dipole Source. Cannavo’, F.
49. Surface-Wave Relocation and Characterization of theOctober 2023 Izu Islands, Japan Earthquake Swarm.
Deane, C. A., Earle, P., Pesicek, J. D., Prejean, S. G., Shelly,
D. R., et al.
50. The Relationship Between a 2022-2023 Magmatic
Intrusion at Aniakchak Caldera and the 2021 m8.2 Chignik
Earthquake, Alaska. Grapenthin, R., Parameswaran, R.,
Angarita, M., Shreve, T., Cheng, Y., et al.
51. Student: Characterization of the Onset of the 2021 Great
Sitkin Dome-Building Eruption Through the TransDimensional Bayesian Inversion of LP Seismicity. Kim,
K., Girona, T., Anderson, K.
52. How Is Differential Shannon Entropy Related to Volcanic
Processes?. Rey-Devesa, P., Girona, T., Prudencio, J.,
Ibáñez, J., Benitez, C.

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53. Student: Systematic Investigation and Comparison of
the 2018 and 2020 Kīlauea Volcano Eruptions Based on
Ambient Seismic Noise Analysis. Vinarski, E., Lin, G.
54. Real-Time Seismic Estimation of Vei: Improving Reduced
Displacement & Introducing the Mvo Energy Magnitude
Scale. Thompson, G., McNutt, S. R., Rodriguez Cardozo,
F. R.
Detecting, Characterizing and Monitoring Mass
Movements [Poster Session] (see page 1265).
55. The MVO Rockfall Location System 24 Years On:
Reimplementation, and Re-Analysis of Pyroclastic Flow
Trajectories. Thompson, G.
56. Using Infrasound to Detect Snow Avalanches and Inform
Forecasts in Alaska. Albert, S. A., Fleigle, M. J., Schaible,
L. P.
57. Deep Transfer Learning Framework for Regional
Landslide Mapping Using Post-Event Imagery. Asadi, A.,
Baise, L. G., Chatterjee, S., Koch, M., Moaveni, B.
58. Student: Quantifying Seismic Properties of a River
Channel at Mount Rainier for Use in Debris-FlowMonitoring and Analysis. Conner, A. E., Thomas, A. M.,
Allstadt, K. E., Collins, E., Thelen, W. A.
59. Student: Investigating Seismic Signals From the Barry
Arm Landslide. Davy, G. K., Karasozen, E., West, M. E.,
Lyons, J.
60. Seismology Versus Infrasound: Which Monitoring
Technique Is Better for Detecting Advancing Lahars?.
Roca, A., Pineda, A., Johnson, J., Mock, J., Bejar, G., et al.
61. Student: Repeated Seismicity Conditions Paraglacial
Valleys for Slope Failure in Prince William Sound, Alaska.
McCreary, M. E., Moore, J., Jensen, E., Gischig, V.
62. Student: Optimizing Landslide Detection and Validation
Through Sentinel-1 Radar Imagery: Case Studies of
Hokkaido and Hiroshima in Japan. Thapa, M., Jiang, J.,
Regmi, N.
63. Student: Landslide Susceptibility Assessment Using
Earthquake Ground Motion for Different Return Periodsin Rasuwa District, Central Nepal. Thapa, M., Pradhan,
A. M. S., Chamlagain, D., Jiang, J., Regmi, N.
64. [Un]supervised Clustering of [Non-]Earthquake Signals
Commonly Recorded on Regional Seismic Networks.
Toney, L., Allstadt, K., Collins, E., Yeck, W.
65. Seismically-Derived Ground Tilt From Rainfall-Triggered
Lahars at Volcán De Fuego, Guatemala. Waite, G. P.,
Bejar, G., Johnson, J. B., Escobar-Wolf, R., Roca, A., et al.
66. The September 16, 2023 Greenland Event: Mysterious
Days-Long Monochromatic Very Long-Period Signal
Triggered by a Landslide. Carrillo-Ponce, A., Petersen, G.,
Cesca, S., Heimann, S., Walter, T., Dahm, T., et al.

Volume 95•

Number 2B•

April 2024•

www.srl-online.org

Illuminating Complex, Multiplet Earthquake Sequencesat Kahramanmaras (Turkiye), Herat (Afghanistan), andBeyond [Poster Session] (see page 1320).
67. Coulomb Stress Variation and Frictional Properties
Control Postseismic Fault Slip and Late Aftershocks ofthe 2022 Zagros Earthquake Sequences: Deductions
From Bayesian Inference and Insar Observations. Zhao,
X., Dahm, T., Vasyara-Bathke, H., Xu, C.
68. Rupture History and Elastic Interaction of the 2022
Multiple Earthquakes in the Zagros Mountains, Iran.
Metz, M., Asayesh, B., Aref, M., Jamalreyhani, M.,
Büyükakpınar, P., et al.
69. Nodal Seismometer Array Recordings of Aftershocks of
the 6 February 2023 Mw 7.8 and Mw 7.6 Kahramanmaraş,Turkiye Earthquake Sequence. Catchings, R. D., Celebi,
M. K., Goldman, M. R., Chan, J. H., Sickler, R. R., et al.
70. Student: High-Resolution Three-Month Aftershock
Catalog using Nodal Stations of the 2023 Kahramanmaraş
Earthquake Sequence in Southeastern Türkiye. Mach, P.
V., Peng, Z., Sandvol, E., Ergin, M., Zor, E., et al.
71. Investigating the Türkiye-Syria and Afghanistan 2023
Seismic Sequences. Svigkas, N., Atzori, S., Striano, P.,
Bonano, M., Vavlas, N., et al.
72. Measuring Afterslip From the February 2023 Mw 7.8
Pazarcık Earthquake Using Optical Images and Radar
Data. Tan, M., Reitman, N., Burgi, P. M., Briggs, R.
73. Student: Decoding the Rupture Kinematics of the2023 Mw 7.8 and Mw 7.5 Kahramanmaraş Earthquake
Doublet: Insights From Comprehensive Seismic andGeodetic Analysis. Xu, L., Mohanna, S., Meng, L., Ji, C.,
Ampuero, J., et al.
Characteristics and Mechanics of Fault Zone Rupture
Processes, from Micro to Macro Scales [Poster Session](see page 1246).
74. Constraining 3D Fault Geometry With a Data-Driven
Approach at the San Andreas—Calaveras Fault Junction.
Alongi, T., Elliott, A., Skoumal, R., Hatem, A. E., Harris,
R. A., et al.
75. Unveiling Shallow Earthquake Ruptures in the Ryukyu
Area: A Comprehensive Study Through Bp Imaging andRegional Cmt Catalog. Jian, P., Tseng, T., Hsu, Y., Yang,
H., Tang, C.
76. Probing Transient Rheology and Spatial Heterogeneityof Faults Using Repeating Earthquakes and Deformation
Data. Jiang, J., Taira, T.
77. Illuminating the Jericho Fault from A New Local Seismic
Network. Klinger, A. G., Kurzon, I.
78. Student: Fault Network Geometry’s Control on
Earthquake Rupture Behavior. Lee, J., Tsai, V. C., Hirth,G., Trugman, D. T., Chatterjee, A.
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Thursday, 2 May (continued)
79. Student: Posterior Exploration of Bayesian Kinematic
Finite-Fault Earthquake Source Models. Viteri Lopez, J.,
Jiang, J.
80. Student: Comparing Fault Zones that Host Induced andTectonic Earthquakes in Oklahoma and California. Neo,J., Huang, Y., Gable, S.
81. Student: Systematic Measurements of Rupture
Directivity for Small-to-Moderate Earthquakes in
California. Patton, A., Trugman, D. T.
82. Student: Lithospheric Structure of the Hispaniola andPuerto Rico/Virgin Islands Microplates Using Teleseismicand Local Data. Rosero Rueda, S., Pulliam, J., Huerfano,V., Polanco Rivera, E., Leonel, J.
83. Student: Investigation of Earthquake Nucleation
Processes: A Case Study of the 2019 Ridgecrest Earthquake
Sequence. Wang, Y., Lin, G., Fan, W.
84. New Zealand’s South Westland Alpine Fault: What’s
Down There and How Does It Make Earthquakes Stop?.
Warren-Smith, E., Townend, J., Lozos, J., Chamberlain,
C. J., Eberhart-Phillips, D.
85. Spatio-Temporal Slip Distributions of Deep Short-Term
Slow Slip Events in the Nankai Subduction Zone Using
Gnss, Tilt, and Strain Data. Yabe, S., Ochi, T., Matsumoto,N., Matsuzawa, T.
Cordilleran Strike-Slip Faults as Seismogenic andSeismological Features [Poster Session] (see page 1250).
86. Student: Refining the Nature of Distributed and Localized
Slip-Partitioning of the Totschunda-Fairweather to
Denali Corridor Using Earthquake Relocations and Focal
Mechanisms. Biegel, K., Gosselin, J. M., Dettmer, J.,
Colpron, M., Enkelmann, E., et al.
87. Revisiting the Enigmatic Magnitude-7 Denali Fault
Earthquake of July 7, 1912. Tape, C., Lomax, A.
Seismic Monitoring, Modelling and Management Needed
for Geothermal Energy and Geologic Carbon Storage[Poster Session] (see page 1397).
88. Student: Applying Dynamic Fracture Propagation and
Activation Models to Microseismicity Generation in a
Geothermal Development Project at Blue Mountain,
Nevada. Awe, E.
89. End-to-End High-Quality Geophysics Workflow toAnalyze Das-Acquired Induced Seismicity. Calvez, J. L.,
Mizuno, T., Ay, E.
90. Application of State of Stress Analysis Tool (SoSAT) to
Estimate Risk of Induced Seismicity From CO2 Injections.
Saxena, S., Haagenson, R. J., Wang, W., Appriou, D.,
Burghardt, J. A.
91. Toward Improving the Assessment of Induced
Earthquakes in the Rome Trough of West Virginia.
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Carpenter, S., Schmidt, J. P., Hickman, J. B., Sparks, T. N.,
Greb, S., et al.
92. OhioNET: Reducing Risk from Induced Seismicity
Using Real-Time Seismic Monitoring for Regulation and
Mitigation in Ohio. Dade, S. L.
93. Automated Earthquake Detection and Location Applied
to Local-Scale Seismic Monitoring. Dzubay, A., Leifer, J.,
Stachnik, J., Friberg, P.
94. Student: Using Deep Learning for High-Resolution
Fault Analysis and Stress Characterization at the Forge
Site, Utah. Mohammadi Ghanatghestani, A., Chen, X.,
Asirifi, R.
95. Student: A Comparison of Machine Learning and ArrayBeamforming Methods in Detecting Microearthquakes
Near Cushing, Oklahoma, Using a Dense Nodal Array.
Chen, X., Cheng, Y., Hoefer, B. A.
96. Innovative Use of Broadband Sensors for Carbon
Capture Utilization and Storage (“CCUS”) Monitoring
Applications. Lindsey, J. C., Watkiss, N., Hill, P., O’Neill,J.
97. The Utah Frontier Observatory for Research in
Geothermal Energy: A Field Laboratory for Enhanced
Geothermal System (EGS) Development. Moore, J. N.,
McLennan, J., Pankow, K. L., Podgorney, R., Rutledge, J.,et al.
98. Microseismicity
Observation
andStructure
Characterization at Cape Modern, Utah. Nakata, N., Wu,
S., Hopp, C., Robertson, M., Jung, Y., et al.
99. Weak Soils, Active Faults, and the Inheritance ofGroningen Induced Seismicity: How to Proceed With
Safe Use of the Subsurface for the Energy Transition in
the Netherlands?. van der Wal, J. L. N., Muntendam-Bos,
A. G., Schouten, M. W.
100. Application of Static Stress Drops and Similarity ofSeismic Events Induced by Underground Fluid Injectionin Characterization of Seismogenic Zones on the Exampleof The Geysers Geothermal Field. Staszek, M., Rudziński,Ł., Wiszniowski, J.
101. Mapping of the Seismic B-Value Before and After
Mine Collapse Main Shocks, Rudna Mine, SW Poland.
Sobiesiak, M. M., Staszek, M., Leptokaropoulos, K.,
Rudzinski, L.
102. Focal Mechanisms of Microseismicity at the Decatur,
Illinois, CCS Site Inverted From Multiple Borehole
Seismic Arrays. Woo, J., Ting, C.
103. Microseismicity Moment Tensor Estimation Using
Surface and Downhole Geophone Arrays at Utah FORGE.
Wu, S., Nakata, N.
104. Shear-wave Splitting Observed in the Geysers
Geothermal Field to Monitor the Spatiotemporal Crustal
Conditions. Yoshimitsu, N.
105. A Cost-Effective GCS Monitoring Approach Using
Localized Seismic Waves. Zheng, Y., Sun, M., Huang, L.
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106. A Risk-Based Adaptive Monitoring Planning Tool
Based on Elastic-Wave Sensitivities for Cost-Effective
Seismic Monitoring for Geologic Carbon Storage. Tian,Y., Yang, X., Huang, L., Gao, K., Vasylkivska, V., et al.
3D Wavefield Simulations: From Seismic Imaging to
Ground Motion Modelling [Poster Session] (see page1204).
107. A Detailed Analysis of Seismic Waves Amplificationfor Basins Using 3D Seismic Simulations. Tian, Y., Tape,
C.
108. Student: Estimating Ground Motion Intensities
Using Simulation-Based Estimates of Local Crustal
Seismic Response. Agrawal, H., McCloskey, J.
109. Student: Effects of the Distribution of Ambient
Noise Sources in Subsurface Models Inverted From Noise
Correlations. Valero Cano, E., Fichtner, A., Peter, D., Mai,
P. M.
110. Southern Italy: An Intricate Litosphere. Casarotti,E., Magnoni, F., Ciaccio, M., Di Stefano, R.
111. Student: Synthetic Inversions for Anisotropic
Structures using Wavefield Simulations and Adjoint
Methods. Gupta, A., Chow, B., Tape, C.
112. Student: Analysing Alpine Fault Earthquakes
Through Ambient Seismic Noise. Juarez Garfias, I.,
Townend, J., Chamberlain, C., Holden, C.
113. Selection of a Starting Model for Adjoint Tomographyof the Pacific Northwest. Kehoe, H. L., Bozdag, E., Boyd,
O. S., Wirth, E., Stephenson, W. J., et al.
114. Rupture
Dynamics
andGroundMotions
Characteristics of the 2023 Türkiye Mw 7.8 and Mw
7.6 Earthquake Doublet. Li, B., Palgunadi, K., Wu, B.,
Suhendi, C., Zhou, Y., et al.
115. Student: Lithospheric Structures of the Central
Cascadia Subduction Zone Resolved by Full-waveform
Inversion of Ambient Noise and Receiver Functions. Du,
N., Liu, Q.
116. Ambient Noise Attenuation and Differential Adjoint
Tomography Applied to the Hongkou Linear Array
Across the Longmenshan Fault Behind the 2008 M 7.9
Sichuan Earthquake. Liu, X., Li, H., Beroza, G. C., Yang,
L., Zhao, G.
117. Student: Validating Tomographic Models of Alaska
Using 3D Wavefield Simulations. McPherson, A., Tape,C., Onyango, E., Chow, B., Peter, D.
118. High-Resolution Surface Wave Tomography of the
Hayward Fault in the Berkeley Region Using Ambient
Noise Recorded by a Dense Nodal Array. Miao, W., Qiu,
H., Qin, L.
119. Computational Challenges of Large-Scale Numerical
Simulations and Full-Waveform Inversion Workflows.
Orsvuran, R., Nagaso, M., Wang, I., Peter, D., Bozdag, E.
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120. Student: Homogenization of Sedimentary Basins
for the Simulation of Lithological Site Effects. Rapenne,
M., Cupillard, P., Gouache, C.
121. Student: Rapid 3D Green’s Functions Using
Reduced-Order Models of Physics-Based Seismic Wave
Propagation Simulations. Rekoske, J. M., May, D. A.,
Gabriel, A. A.
122. Comparison of Fundamental Fault Green’s Functions(GFs) Computed Using Frequency-Wavenumber and
Finite-Difference (SW4) Techniques for 1D Velocity
Models. Saikia, C. K., Zhou, R., Modrak, R. T.
123. A Sparse Fault Parametrization for Large-scale
Ruptures Based on Moment Tensor Interpolation.
Thurin, J.
Advancements in Forensic Seismology and Explosion
Monitoring [Poster Session] (see page 1213).
124. Moment
TensorEstimation
andUncertainty
Quantification (MTUQ). Thurin, J., Modrak, R.,
McPherson, A., Rodríguez-Cardozo, F., Braunmiller, J., etal.
125. Observations on Explosion-Triggered Seismic Events
via Fiber Optic Sensing at Small Scales. Beskardes, G. D.,
Young, B., Stanciu, C., Baker, M. G.
126. Leveraging Infrasound Signals for Integration of
Ground- and Space-Based Nuclear Explosion Monitoring
Capabilities. Blom, P. S., Bishop, J., Gammans, C.,
Carmichael, J. D., Delbridge, B., et al.
127. Influence of Local 3-D Structure at Degelen Test
Site on Short-Period Teleseismic P-Wave via Reciprocal
Hybrid Modeling. Burgos, G., Guillot, L.
128. Far-Field DAS Recordings of a Chemical Explosion.
St Clair, J. T., Chojnicki, K., Sprinkle, P., Ely, J.
129. Capturing the Spatial Variation of Seismic
Observations in SW4 Simulations of the Dry Alluvium
Geology Experiment Series at the Nevada National
Security Site. Saxena, S., St Clair, J., Sprinkle, P., Chojnicki,
K., Knox, H., et al.
130. Time-Variable
MomentTensorInversionofSeismic and Seismoacoustic Data at the Source Physics
Experiment Phase II: Dry Alluvium Geology. Darrh, A.,
Berg, E. M., Preston, L. A., Poppeliers, C.
131. Exploring Paired Neural Networks to Rapidly
Characterize Aftershock Events. Emry, E. L., Donohoe,
B., Tibi, R., Young, C. J., Ramos, M., et al.
132. A New Tool to Integrate Instrument Responses
From Seismological Databases Into Python Workflows.
Gammans, C., MacCarthy, J. K.
133. Ambient
Seismic
Noise
Tomographyof
Heterogeneous Geological Formations. Gochenour, J. A.,
Zeiler, C. P., Bilek, S., Luhmann, A. J.

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Thursday, 2 May (continued)
134. Using Deep Learning Models to Characterize
Subsurface Physical Parameters at Modeled Underground
Chemical Explosion Sources. Harding, J. L., Preston, L.
A., Eliassi, M., Gauvain, S. J.
135. Comparing Observed and Modelled Station Terms
from the Source Physics Experiments Phase 2 (DryAlluvium Geology) Explosions. Heyburn, R., Green, D.
136. Comparisons Between Geophone Array and DASArray Detections. Ichinose, G. A.
137. Explosion Source Analysis and Discrimination FromRegional Distance Seismic Observations. Kintner, J. A.,
Pippin, J., Alfaro-Diaz, R., Delbridge, B., Ammon, C. J.
138. Inferring the Focal Depths of Small Earthquakes
in Southern California Using Physics-Based Waveform
Features. Koper, K. D., Burlacu, R., Murray, R., Baker, B.,
Tibi, R., et al.
139. Providing Data for Nuclear Explosion Monitoring—
WFNE Repository. Oancea, V., Kung, Y., Murphy, J. R.,
Piraino, P. E.
140. Investigating Shallow Subsurface Structure Near
Legacy Nuclear Test Sites Using Single Station HVSR.
Miller, D. J., Berg, E. M., Preston, L. A., Abbott, R. E.
141. Detecting Subsurface Mining Activity using CrossCorrelation and Local Surface Arrays. Miller, D. J., Berg,
E. M., Marcillo, O., Chai, C., Cunningham, E., et al.
142. Investigation of Full Moment Tensor Solutions
for Earthquakes and Announced Nuclear Tests at the
Punggye-Ri Test Site, DPRK. Ogden, C. S., Selby, N.,
Heyburn, R., Nippress, S.
143. Relative
SourceTime
Function
Estimation,
Applications to the Source Physics Experiments. Pippin,
J. E., Kintner, J. A., Ammon, C. J.
144. Transportability of a Convolutional Neural Network
Seismic Denoising Model. Quinones, L. A., Tibi, R.
145. Gravity Mapping to Validate the Rock Valley
Geological Framework Model. Ranasinghe, N. R., Rowe,C., Stanbury, C.
146. Observations of Epicentral Infrasound From Shallow
Low-Magnitude Earthquakes in the Permian Basin, West
Texas. Schaible, L., Dannemann Dugick, F., Bowman, D.
C., Savvaidis, A., McCabe, C.
147. Student: Seismic Soundscape of the Parks Highway
Corridor, Central Alaska. Seppi, I., Tape, C., West, M.
148. Seismic
Data
Denoising
Using
Multi-Scale
Mathematical Morphological Filtering. Tibi, R.
149. Evaluation of Multiple-Event Location Methods
Using Ground-Truth and Synthetic Data. Tibuleac, I. M.,
Antolik, M. S., VanDeMark, T. F., Brumbaugh, D.
150. Moment Tensor Inversions for Rapid Seismic Source
Detection and Characterization of the North Korean
Nuclear Tests. Guilhem Trilla, A.

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Seismological Research Letters151. Modeling the Ground Motions From Chemical
Explosions in Proximity of a Fault. Vorobiev, O. Y.,
Ezzedine, S. M.
152. Signal Arrival Databases for Ground Truth
Infrasound Events. Dannemann Dugick, F., Wynn, N. R.
From Earthquake Recordings to Empirical GroundMotion Modelling [Poster Session] (see page 1292).
154. Frequency-Dependent
Transfer
Functionsfor
Hydroseisms in Devils Hole. Bonner, J. L., Symons, N.,
Russell, C.
155. High Frequency Seismic Waves of Normal and Leaky
Modes Excited by Heavy Trains. Feng, X., Li, Z., Chen, X.
156. Progress on the Characterization of Epos-France
Accelerometric (Rap) and Broad-Band (Rlpb) Network
Station: Focus on Implemented Methodologies.
Hollender, F., Burlot, R., Rischette, P., Douste-Bacqué, I.,
Wathelet, M., et al.
157. Student: Separation of Intrinsic and Scattering
Seismic Wave Attenuation in the Crust of Central andSouth-Central Alaska. Mahanama, A., Cramer, C. H.,
Gabrielli, S., Akinci, A.
158. Student: How Can Shaking Observations From
the MyShake Smartphone Platform Inform Free-Field
Ground Motion Residual Estimates?. Marcou, S., Allen,
R. M.
159. Student: Estimating Hazard From Crustal Sources:
An Empirical Observation Approach. MartínezJaramillo, D., Zúñiga Dávila-Madrid, F., Kotha, S.
160. Student: Multi-Resolution Basin Terms for Ground
Motion Models in Central and Eastern North America.
Meyer, E. H., Dioslaki, A., Nie, S., Zhan, W., Kaklamanos,J., et al.
161. Student: The Effect of Short Wavelength Topography
on Seismic Recordings: Results of Experiments Conducted
on Kefalonia Island in Greece. Rischette, P., Hollender, F.,
Theodoulidis, N., Roumelioti, Z., Perron, V., et al.
162. Student: Geospatial Variable Based Site Terms for
Nonergodic Ground Motion Models. Roberts, M. E.,
Gaskins Baise, L., Kaklamanos, J., Zhan, W., Nie, S.
163. NGA-Subduction Region-Specific Ground Motion
Models Using Machine Learning Algorithms. Sedaghati,
F., Pezeshk, S.
164. Ground Motion Models Using Machine Learning
Techniques Based on the NGA-West2 Data. Sedaghati,
F., Pezeshk, S.
165. Student: Developing a Hybrid Ground-Motion
Modeling Framework for the Himalayan Region of India.
Sharma, S.
166. Domain Confusion in Dispersions Picking Basedon Neural Network and the Learning Features From
Dispersion Spectrograms. Song, W., Chen, X.
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167. Monitoring Temporal Velocity Variations of Shallow
Subsurface and Engineering Structures Using 6c SingleStation Measurement. Yuan, S., Martin, E., Bernauer, F.
Six Decades of Tsunami Science: From the Source ofthe 1964 Tsunami to Modern Community Preparedness[Poster Session] (see page 1416).
168. Depth Variation in Megathrust Rupture Leads toMature Tsunami Gap in Metropolitan Chile. Carvajal,
M., Cisternas, M., Wang, K., Moreno, M., Wesson, R. L.,
et al.
169. Student: Constraining Offshore Coupling in the1946 Tsunami Earthquake Rupture Area. Chavarria
Esquivel, N., Newman, A.
170. Efficient Forward Modelling of Tsunamis Using theSpectral-Element Method. Gharti, H., Fitzgerald, J.
171. Adding Tsunami Observations and Modeling to the
USGS Finite Fault Modeling Procedure. Goldberg, D. E.,
Koch, P., Melgar, D., Hunsinger, H., Haynie, K.
172. The What, When and Whys of Alert Progression
During Tsunamigenic Events: A Simple Generative
Approach to Forecasting Decision Points and Developing
Heuristics. Heath, B., Ohlendorf, S., Kim, Y., Gridley, J.
173. Estimating Tsunami Vulnerability along Western
Coast of India. Jha, K.
174. Precise Point Positioning of Ships to Detect Tsunamis.
Manaster, A. E., Sheehan, A. F., Goldberg, D. E., Roth, E.
H., Barnhart, K. R.
175. Testing Crustal Fault Tsunami Sources in the Salish
Sea: Comparing Modeled Inundation With the Geologic
Record at Discovery Bay, WA. Wei, Y., Garrison-Laney,
C., Moore, C., Pells, C.
176. KOERI Activities in Tsunami Early Warning and
Risk Mitigation System in the Eastern Mediterranean and
Its Connected Seas. Ozener, H., Cambaz, M., Turhan, F.,Güneş, Y., Deniz Hisarlı, P., et al.
177. Estimation of the Tsunami Hazard for the Bering and
Chukchi Seas Based on Numerical Modeling of TransOceanic and Local Tsunamis. Medvedeva, A. E., Fine, I.
E., Medvedev, I., Kulikov, E., Rabinovich, A. B., et al.
178. Real Time Tsunami Run-Up Estimation From RealTime Finite Fault Models. Riquelme, S., Fuentes, M.

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179. Student: Measuring and Forecasting the Background
Open Ocean Tsunami Spectrum. Santellanes, S. R.,
Melgar, D.
180. The Role of Climate-Change Sea Level Rise
Exacerbating California’s Tsunami Hazards. Sepulveda,
I., Mosqueda, A.
181. In Search of the Missing Tsunami: Is There a Tsunami
Threat to Anchorage?. Suleimani, E., Salisbury, J. B.,
Nicolsky, D., Picasso, A.
Applications and Discoveries in Cryoseismology Across
Spatial and Temporal Scales [Poster Session] (see page1237).
182. Student: Machine Learning for Icequake Detection
and Location Across the Eastern Shear Margin of Thwaites
Glacier, West Antarctica. Gonzalez, L. F.
183. Probabilistic Multiphysics Inference for Permafrost
Characterization and Earthquake Site Hazards
Assessment. Gosselin, J. M., Dettmer, J., Shahsavari, P.
184. Student: Bayesian Surface Wave Dispersion Data
Inversion of Glaciated Environments. Lanteri, A.,
Gebraad, L., Zunino, A., Keating, S., Klaasen, S., et al.
185. Unsupervised Detection and Characterization of
Glaciogenic Noise Sources in Greenland During Winter.
Maier, N.
186. Student: Microseismicity Catalog of Icequakes
Induced by Ocean Swell at the Ross Ice Shelf Ice-Front.
McGhee, E., Aster, R. C.
187. Distributed Acoustic Sensing Reveals What’s in Store(Glacier). Olinger, S., Lipovsky, B., Denolle, M., Booth, A.
188. Array-based Characterization of Seismicity from a
Glacial Lake Outburst Flood. Sawi, T., Holtzman, B. K.,
Beaucé, E., Walter, F., Seydoux, L.
189. Student: Controlled-Source Seismic Imaging of
Mcmurdo Ice Shelf Near Williams Airfield. Seldon, Y.,
Karplus, M. S.
190. Student: Unsupervised Clustering of Cryoseismic
Events Recorded by Distributed Acoustic Sensing at
Rhonegletscher, Switzerland. Willis, R., Grimm, J.,
Stanek, F., Edme, P., Fichtner, A., et al.

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Friday, 3 May 2024—Oral Sessions
Presenting author is indicated in bold.
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

Advancing Seismology withDistributed Fiber Optic
Sensing (see page 1224).

Physics-Based Ground
Motion Modeling (see page1377).

Seismoacoustic, Geodetic
and Other GeophysicalInvestigations of Active
Volcanoes (see page 1402).

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone (see page1424).

8:00 am

High-Resolution Analysis
of Earthquake Sources and
Subsurface Structures Using
Downhole Optical Fiber
Crossing Active Fault. Ma, K.,
Liao, J., Hsiao, L.

Evaluation of Seismic
Community Velocity
Models With Simulations of
Small Earthquakes. Pinilla
Ramos, C., Ben-Zion,
Y., Abrahamson, N. A.,
Maechling, P. J., Callaghan,S., et al.

Student: Using Deep
Long-Period Earthquakes toConstrain Magmatic Volatile
Transport at Mauna Kea.
Scholz, K. J., Thomas, A. M.,
Townsend, M. R.

Invited: Forty-Five Yearsof the Shumagin Gap: What
Recent Earthquakes Tell Us
About This Seismic Gap.
Herman, M. W., Furlong, K.
P., Benz, H. M.

8:15 amStudent: Dascore: A Python
Library for Distributed
Acoustic Sensing. Chambers,
D. J. A., Martin, E. R., Jin, G.,
Tourei, A., Girard, A., et al.

Waveguide or Not? Expected
Ground Motions in the
Greater Los Angeles Area
From the ShakeOut scenario.
Yeh, T., Olsen, K. B.

Probing Magma Storage andTransport Beneath Pāhala,
Hawai‘i. Janiszewski, H. A.,
Bennington, N., Wight, J.,
Glasgow, M.

Student: Putting the Pieces
Together: A Kinematic
Coseismic Model of theMw 7.2 Alaska Earthquake.
DeGrande, J., Crowell, B.

8:30 amStudent: Characterizing
South Pole Firn StructureWith Fiber Optic Sensing.
Yang, Y., Zhan, Z., ReidMcLaughlin, A., Biondi, E.,
Karrenbach, M., et al.

Effect of Soil Nonlinearity
on Physics-Based Ground
Motion Simulations. Zhang,W.

Seismic Velocity Changes at
Mauna Loa Derived From
Seismicity Prior to andDuring Its 2022 Eruption.
Hotovec-Ellis, A. J.

Student: A Joint Coseismic
and Early Postseismic Studyof the 29 July 2021, Mw 8.2
Chignik Earthquake. Zhuo,
Z., Freymueller, J. T., Xiao, Z.,
Elliott, J., Grapenthin, R.

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April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

End-to-End
The 2024
Advancements in
Magnitude 7.5
Earthquake Early
Earthquake andWarning Systems (seethe AssociatedEarthquake Swarm page 1276).
Beneath theNoto Peninsula,
Central Japan(See Supplemental
Material)

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

Understanding
and Quantifying
the Variability
in Earthquake
Source Parameter
Measurements (seepage 1448).

Anisotropy AcrossTectonics andScales (see page 1232). Seismicity of Stable
Continental Interiors(see page 1436).

8:00 am

Exploring Five Yearsof Social Science and
Education Research
for Shakealert, theEarthquake Early
Warning System for
the West Coast of theUnited States. McBride,
S. K., de Groot, R. M.,
Sumy, D. F.

Estimating Seismic
Attenuation, Site
Corrections andGeometrical Spreading
From Large Seismic
Catalogues Using
Linearized Spectral
Ratios and Regression
Regularization Paths.
Lapins, S.

A Seismic View of theStress Field. Delorey,
A. A.

Seismicity andSeismotectonics of theBasque-Cantabrian
Zone and Adjacent
Areas of the PyreneanCantabrian Mountain
Belt: New Data
From the Siscan and
Misterios Seismic
Networks (2014-2020).
Olivar-Castaño, A.,
Díaz-González, A.,
Pulgar, J. A., Pedreira,D., González-Cortina,J., et al.

8:15 amStudent: The
Extraction of Source
Development of a Real- Parameters for French
Time Urban Earthquake Seismicity Based on
Early Warninga Radiative Transfer
System for AssetApproach: ImportanceLevel Protection forfor Attenuation and Site
Increased Community Corrections. Heller, G.,
Restoration. Martí, A. Sèbe, O., Margerin, L.,
T. J., Daiss, I., Martí,
Traversa, P., Mayor, J.,
J. R., Ventura, C. E.,
et al.
Andjelic, D., et al.

Student: Seismic
Anisotropy and StressField Variations Alongthe Dead Sea Fault
Zone in Northern
Israel. Ben-Dor, G.

The Earthquake Swarms
of Eastern Maine and
Nearby New Brunswick
Since 2006. Ebel, J. E.

8:30 amWhat It Takes to
Implement Earthquake
Early Warning in theReal World. Steele, W.
P., Lotto, G.

Student: Imaging
Los Angeles Basin via
Directional Dependent
Rayleigh Wave
Ellipticity Using Data
From the Lab2022
Nodal Array. Gkogkas,
K., Lin, F., Clayton, R.,
Villa, V., Ford, H., et al.

Student:
Seismotectonic Studiesof the Nubia Fault
System, Southwest
Aswan Area, Egypt.
Elsayed Mohamed, M.
M., Abdallah Hamimi,Z., Mohamed Moussa,
H.

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A Joint Inversion
Method for Computing
Earthquake Stress
Drop With Spectra andSpectral Ratios. Guo,
H., Thurber, C. H.

www.srl-online.org

Seismological Research Letters

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1177

Friday, 3 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

Advancing Seismology withDistributed Fiber Optic(continued)

Physics-Based Ground
Motion Modeling (continued).

Seismoacoustic, Geodetic
and Other Geophysical(continued)

Structure and Behaviorof the Alaska-Aleutian
Subduction (continued)

8:45 amAssessing Distributed
Acoustic Sensing (DAS)for Moonquake Detection.
Husker, A., Zhai, Q., Zhan,
Z., Biondi, E., Yin, J., et al.

Student: 3D 0-10 Hz
Physics-based Simulationsof the 2020 Magna, Utah
Earthquake Sequence. Xu, K.,
Olsen, K. B.

Student: A Catalog of
Estimating Slip Models andAutomated Focal Mechanisms Ground Motion for the 1964
for Microearthquakes at
Mw 9.2 Alaska Earthquake.
Axial Seamount Based on
Thurin, J., Thio, H. K., Tape,
Waveform Cross-Correlation. C.
Zhang, M., Wilcock, W.,
Waldhauser, F., Wang, K.,
Schaff, D., et al.

9:00 amInvited: Rupture Imaging ofFirn Quakes with Distributed
Acoustic Sensing. Li, J.,
Yang, Y., Biondi, E., ReidMcLaughlin, A., Aster, R. C.,
et al.

Spe Rock-Valley-DirectComparison Chemical
Explosions Near-Field 3-D
Ground Motion Simulations
and Predictions. Ezzedine, S.
M., Vorobiev, O.

Student: The Influence ofMultiple Scattered Waveson the Spectral Stability ofVolcanic Tremors. Bracale,
M., Campillo, M., Shapiro, N.,
Brossier, R., Melnik, O.

Advancing Seismology withDistributed Fiber Optic
Sensing (see page 1224).

Physics-Based Ground
Motion Modeling (see page1377).

Seismoacoustic, Geodetic
and Other GeophysicalInvestigations of Active
Volcanoes (see page 1402).

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone (see page1424).

SUBMERSE Project Paves
the Way for Continuous
Fiber-optic Monitoring in
the Oceans with Submarine
Telecommunications Cables.
Tilmann, F., Atherton, C.,
Kvatadze, R., Asero, C.,
Evangelidis, C., et al.

Student: Modeling
Local Infrasound Monitoring
Topography and Fault
of Lava Eruptions at
Geometry Effects on
Nyiragongo Volcano (d.r.
Earthquake Ruptures andCongo) Using Urban and
Ground Motions Along
Near-Source Stations.
Double Compressional Bends. Barrière, J., Oth, A., d’Oreye,Madera, N., Lozos, J.
N., Subira, J., Smittarello, D.,et al.

Upper Plate Stress in the
Alaskan Continental Crust:
Spooky Interactions at
a Variety of Distances.
Levandowski, W., Coulter, C.

9:15–10:30 am

10:30 am

1178|

Earthquake Location
Improvements for the
Aleutian-Alaska Subduction
Zone by Using Waveform
Cross-Correlation Data. Lin,
G.

Poster BreakSeismological Research Letterswww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

The 2024
Magnitude 7.5(continued)

End-to-End
Advancements in(continued)

Understanding andQuantifying the (continued)

Anisotropy AcrossScales (continued)

Tectonics andSeismicity of Stable(continued)

8:45 am

From Shakealert toPost-Earthquake
Assessment—
Improving Situation
Awareness of Building
Managers andOccupants. Parrott, B.,
Franke, M., Skolnik, D.

Student: Earthquake
Source Parameter
Analysis Using
Peak Narrow Band
Displacement
Amplitudes. Knudson,
T., Ellsworth, W. L.,
Beroza, G. C., Shaw,
B. E.

Invited: Anisotropy
Student: Focal
in Flowing Firn andMechanism Analysis
Ice: Insights fromof the 2019 Mw 4.9
Ambient Noise andWang Nuea Earthquake
Active Source Studies in and Its Implication
Antarctica. Chaput, J., for Seismotectonics.
Aster, R. C., Karplus, M. Chansom, C.,
S., Nakata, N.
Jitmahantakul, S.,
Shengji, W.

9:00 am

The Ojai California
Earthquake of August20, 2023: Earthquake
Early Warning
Performance and Alert
Recipient Responsein the m5.1 Event.
Goltz, J. D., Wald, D. J.,
McBride, S. K., Reddy,E., Quitoriano, V., et al.

Three Years of theInternational SCEC/USGS Community
Stress Drop Validation
Study: What Have We
Achieved and Where
Next. Abercrombie, R.
E., Baltay, A. S., Chu, S.,
Taira, T.

Broadband Rayleighand Love Wave Phase
Velocity Maps Based on
Double-Beamformingof Ambient Noise
Cross-Correlations.
Yang, Y., Zhao, K.,
Luo, Y.

9:15–10:30 am

Poster BreakEnd-to-End
The 2024
Advancements in
Magnitude 7.5
Earthquake Early
Earthquake andWarning Systems -IV
the AssociatedEarthquake Swarm (see page 1276).

Beneath theNoto Peninsula,
Central Japan(See Supplemental
Material)
10:30 amVolume 95

High-Rate Real-Time
Gnss Installation andData Acquisition at
the Alaska Earthquake
Center. Paris, G.,
Holtkamp, S., Khan, S.,
Underwood, L., Farrell,A., et al.

•

Middle Crustal
Earthquakes andNeotectonics in theWestern East Sea (Seaof Japan). Hong, T.,
Park, S., Lee, J., Lee, J.,
Kim, B.

Number 2B•

April 2024•

Understanding
and Quantifying
the Variability
in Earthquake
Source Parameter
Measurements (seepage 1448).

Anisotropy AcrossTectonics andScales (see page 1232). Seismicity of Stable
Continental Interiors(see page 1436).

Invited: Student:
Understanding theContribution of Site
Effects to Variability
in Microearthquake
Source Parameter
Measurements Usinga Large, Dense Arrayin Oklahoma. Chang,
H., Abercrombie, R.
E., Nakata, N., Qiu, H.,
Zhang, Z., et al.

Student: Flow in
the Mantle Beneath
Eritrea and Yemen:
Evidence From Seismic
Anisotropy. Gauntlett,
M. Z., Kendall, J.,
Hudson, T., Hammond,
J. O. S., Goitom, B.,
et al.

www.srl-online.org

Seismicity and
Structure of SW
Australia via the SWAN
and Western Australia
Seismic Networks.
Pickle, R., Zhang, P.,
Mousavi, S., Yuan, H.,
Murdie, R., et al.

Seismological Research Letters

|

1179

Friday, 3 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

Advancing Seismology withDistributed Fiber Optic(continued)

Physics-Based Ground
Motion Modeling (continued).

Seismoacoustic, Geodetic
and Other Geophysical(continued)

Structure and Behaviorof the Alaska-Aleutian
Subduction (continued)

10:45 am

Monitoring Soil MoistureWith Distributed Acoustic
Sensing in the Agricultural
Setting. Shi, Q., Collins, J.,
Denolle, M., Feng, K., Jeffery,S., et al.

Student: The Effects ofSurface Topography andBasin Layering on the
Earthquake Ground Motion
Intensities in IntermontaneBasin Settings. Agrawal, H.,
Naylor, M.

Here Comes the Boom!
Student: A Chicken andTracking Audible Acoustics
Egg Dilemma: Forearc Strain
Across Aotearoa New Zealand Field and Seismic Behavior
From the 2022 Eruption ofin the Andreanof Segment.
Hunga Volcano. Lamb, O.,
Cortés Rivas, V., Shillington,
Clive, M., Lawson, R., Potter, D. J., Lizarralde, D., Mark, H.,
S., Kilgour, G., et al.
Boston, B.

11:00 amSpatio-Temporal Fidelity of
DAS Arrays to Compression
Seismic Signals: Impacts on
Real-Time Source Estimates.
Salaree, A., Miao, Y., Spica,
Z., Nishida, K., Yamada, T.,et al.

Analysis of AnomalouslyInternal Gravity Waves
Large High-Frequency
During the 2023 Eruption of
Amplification in Chugiak,
Shishaldin Volcano, Alaska.
Ak, From the 2018 Anchorage Haney, M. M., Fee, D., Lyons,
Earthquake and Aftershocks. J. J.
Yeh, T., Olsen, K. B., Steidl, J.
H., Haeussler, P. J.

Student: Structural andCompositional Controls on
Megathrust Slip Behavior
Inferred From a 3D, CrustalScale, P-Wave Velocity Modelof the Alaska Subduction
Zone Spanning the Incoming
and Overriding Plates.
Acquisto, T. M., Bécel, A.,
Canales, J., Beauce, E.

11:15 amStudent: Understanding
the Rupture Process of theMw 7.6 2022 Michoacán
Earthquake With Distributed
Acoustic Sensing. Miao, Y.,
Huang, Y., Neo, J., Spica, Z.

Findings from a Decade of
Ground Motion Simulation
Validation Research and a
Path Forward. Rezaeian,S., Stewart, J. P., Luco, N.,
Goulet, C.

Seismic and InfrasoundSignals from the 2023
Shishaldin Volcano, Alaska
Eruption. Fee, D., Haney, M.
M., Tan, D.

A Late Miocene to Pliocene
Increase in Soft-Sediment
Deformation in Cook Inlet
Nonmarine Forearc Basin
Strata—potential Evidence
for Larger Magnitude
Earthquakes Associated With
Increased Sedimentation in
the Alaska Trench. Wartes,
M. A., LePain, D. L., Stanley,
R. G., Helmold, K. P., Gillis,
R. J.

11:30 amInvited: Distributed
Environmental Sensing Using
Trans-Oceanic Subsea Cables.
Mazur, M., Fontaine, N. K.,
Keheller, M., Kamalov, V., Ryf,
R., et al.

Correlated Noise in Source
Time Functions: A Method
to Generate Realistic HighFrequency Earthquake
Sources. Castro-Cruz, D.,
Aquib, T. T., Vyas, J. J., Mai,
P. P. M.

A Seismic Sequence
Capturing Magmatic Fluid
Ascent and Phreatomagmatic
Eruptions at Semisopochnoi
Volcano, Alaska. Lyons, J. J.,
Tan, D., Hotovec-Ellis, A.,
Lopez, T., Grapenthin, R.,
et al.

Student: Variations in the
Alaska-Aleutian Subduction
Megathrust Properties Along
Strike Using Several Seismic
Imaging Techniques. Daly, K.
A., Abers, G. A., Mann, M. E.,
Pang, G., Kim, D.

11:45 am–
2:00 pm

1180|

Seismological Research Letters

Lunch Breakwww.srl-online.org•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

The 2024
Magnitude 7.5(continued)

End-to-End
Advancements in(continued)

Understanding andQuantifying the (continued)

Anisotropy AcrossScales (continued)

Tectonics andSeismicity of Stable(continued)

10:45 am

The Potential
Demystifying
Contribution of RealEarthquake Stress Drop
Time Distributed Slip
Discrepancies Using
Models to Subduction
Synthetic Source Time
Zone Earthquake Early Functions. Neely, J. S.,
Warning in the Context Park, S., Baltay, A. S.
of Ground Motion
Thresholds and Alerting
Strategy. Murray, J. R.

Invited: Modeling
Layered Anisotropy in
the Alaska-Aleutians
Subduction Zone.
Birkey, A., Lynner, C.

Recurrent Large
Intraplate Earthquakes
on the Jindabyne
Thrust, Southeast
Highlands, Australia.
Griffin, J. D., Clark, D.
J., Kemp, J., Stirling, M.
W., King, T., et al.

11:00 amStudent: Toward
Earthquake Early
Warning in Alaska.
Fozkos, A., West,
M., Ruppert, N.,
Grapenthin, R.,
Parcheta, C., et al.

Variable HighFrequency Radiation
From Complex
Laboratory Ruptures
Due to a Normal Stress
Bump. Cebry, S. B. L.,
McLaskey, G. C.

Depth-Dependent
Seismic Azimuthal
Anisotropy Beneath the
Aleutian Subduction
Zone and the Juan De
Fuca-Gorda Plates. Liu,
C., Becker, T., Wu, M.,
Sheehan, A., Ritzwoller,
M.

Seismic Evidenceof Crustal
Modifications Below
the North American
Midcontinent. Yang, X.,
Stevens Goddard, A.,
Liu, L., Ridgway, K. D.,
Schmitt, D. R., et al.

11:15 amApplication of the
Support Vector
Machine Classifier inEarthquake Magnitude
Estimation. Zaicenco,
A. G., Weir-Jones, I.

Invited: Source
Parameter Scaling
Relations for Shallow
Crustal Earthquakewith a Simple
Heterogeneous Source
Model. Shimmoto, S.

Exploring Mantle
Dynamics of the
Cascadia Subduction
System ThroughAnisotropic
Tomography With
Transdimensional
Inference Methods.
VanderBeek, B. P., Del
Piccolo, G., Faccenda,
M.

Student: Crustal
Thickness and Radial
Anisotropy Below
the North American
Midcontinent. Li, H.,
Yang, X., Herr, B., Liu,
L., Stevens Goddard,A., et al.

11:30 amStudent: Enhancing
Offshore Earthquake
Early Warning witha Submarine DAS
Array in Monterey Bay,
California. Gou, Y.,
Allen, R. M., Zhu, W.,
Chen, L., Taira, T., et al.

Reducing theUncertainty of StressDrops. Kurzon, I.,
Lyakhovsky, V., Sagy, A.

Segregated Melts Below
the 660 in the Central
Pacific: Implications
on Water Transportin Mantle Upwellings.
Deng, K., Song, T.

Lithospheric Layeringand Seismic Activity of
the British Isles. Levin,V., Lebedev, S.

11:45 am–
2:00 pm

Volume 95

Lunch Break•

Number 2B•

April 2024•

www.srl-online.org

Seismological Research Letters

|

1181

Friday, 3 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Advancing Seismology withDistributed Fiber Optic
Sensing (see page 1224).

Assessing Seismic Hazard
Seismoacoustic, Geodetic
for Critical Facilities andand Other GeophysicalInfrastructure—Insights and Investigations of Active
Challenges (see page 1239). Volcanoes (see page 1402).

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone (see page1424).

2:00 pm

Enhancing Seismic
Monitoring in Cook Inlet,
Alaska: Integration ofDistributed Acoustic Sensing
with the Existing Seismic
Network for Advanced
Earthquake Denoising,
Detection and Location.
Shi, Q., Ni, Y., Denolle, M.,
Williams, E. F.

Invited: Challenges in
Site-Specific Seismic Hazard
Analyses for Mine Tailings
Storage Facilities in SouthAmerica. Wong, I., Gray, B.,
Givler, R., Wu, Q., Darragh,
R. B., et al.

Invited: Student:
Investigation of Tremor andExplosion Sequences fromthe 2021-2022 Eruption of
Pavlof Volcano, Alaska using
Deep Learning. Tan, D., Fee,D., Girona, T., Haney, M. M.,
Witsil, A., et al.

Implications of Yakutat
Oceanic Plateau Buoyancy
Versus Variable Interface
Coupling on Deformation
in South-Central Alaska.
Haynie, K. L., Jadamec, M. A.

2:15 pm

On DAS Recorded Strain
Amplitude. Forbriger, T.,
Karamzadeh, N., Azzola,J., Widmer-Schnidrig, R.,
Gaucher, E., Rietbrock, A.
et al.

Landfill Design Ground
Motion at the Paducah
Gaseous Diffusion Plant(Central United States).
Wang, Z., Carpenter, N.

Unique Seismic andEruption Precursors to the1996 Magmatic Eruptionsof Popocatépetl: Coupledand Fluidized Bed Events.
McCausland, W., Caballero
Jimenez, G. V., Guevara Ortiz,E., Trujillo Castrillón, N.,
Valdés González, C. M., et al.

Controls on Bending-RelatedFaulting Offshore of the
Alaska Peninsula. Clarke, J.,
Shillington, D. J., Regalla, C.,
Gaherty, J., Estep, J., et al.

2:30 pm

Evaluation of Passive Source
DAS Methods on the Source
Physics Experiment (SPE)
Phase II. Porritt, R., Stanciu,
A. C., Abbott, R. E., Luckie,
T. W.

Characterizing Uncertainty
in the Canadian National
Seismic Hazard Model. Kolaj,
M., Adams, J.

Constraining Links Between
Seismicity and Eruptive
Processes for the December
2018 Flank Eruption at Mt
Etna. Eyles, J., Frank, W. B.,
Poli, P.

Student: Outer-Rise
Earthquakes and Their
Contribution to Tsunami
Hazards Across the Alaska
Subduction Zone. Matulka,P., Wiens, D., Li, Z., Abers, G.,
Ruppert, N., et al.

2:45 pm

Student: Lossy Compression
and Reconstruction ofDistributed Acoustic Sensing
Data Using Deep Learning.
Ni, Y., Denolle, M. A.,
Lipovsky, B., Shi, Q., Pan, S.,et al.

Importance of Site-Specific
Ground Motion Data for
Critical Facilities. Hassani,
B., Yan, L.

Tracking Seismicity in an
Underfunded Institution:
The Case of La Soufrière St
Vincent Volcanic Eruption
2020–2021. ContrerasArratia, R.

High-Resolution RayleighWave Tomography
Constraints on Hydrationin the Incoming Plate Along
the Alaska Subduction Zone.
Yakubu, T., Gaherty, J.,
Shillington, D.

1182

|

Seismological Research Letters

Kahtnu 2

www.srl-online.org

Tikahtnu Ballroom A/B•

Volume 95•

Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

ESC-SSA Joint
Session: Climate
Change andEnvironmental
Seismology (see page1284).

End-to-End
Advancements inEarthquake Early
Warning Systems (seepage 1276).

Understanding
and Quantifying
the Variability
in Earthquake
Source Parameter
Measurements (seepage 1448).

Advances in
Operational andResearch Analysis ofEarthquake Swarms(see page 1220).

Tectonics andSeismicity of Stable
Continental Interiors(see page 1436).

2:00 pm

Multi-Decadal
Analysis of the Global
Microseism in Climate
Context. Aster, R. C.

Student: Improvementin Magnitude Estimation
Performance with a
Combined PGD-PGV
Scaling Law for the
G-Fast Earthquake
Early Warning Module.
DeGrande, J., Crowell,
B.

Constraining Source
Parameters of Seismic
Events Generated
by Circular Gouge
Patches on 4-meterlong Laboratory Fault.
Okubo, K., Yamashita,F., Fukuyama, E.

Student: Seismic
Clusters as Markersof Crustal Stability.
Zaccagnino, D.,
Telesca, L., Doglioni,
C.

Complex andContrasting Temporal
Patterns of Large
Intraplate andInterplate Earthquakes.
Liu, M., Chen, Y., Jin,
X., Luo, G.

2:15 pm

Student: Seismic
Imprints of a
Hurricane Landfall:
Deciphering the
Atmosphere-Generated
Signals From LargeEddy Simulation of
Turbulence. Ji, Q.,
Dunham, E. M., Dey, I.

Finite-Fault Rupture
Constraining the
Detector (FinDer)
Rupture Extent offor Earthquake Early
Mw 6--7 Intraslab
Warning and Rapid
Earthquakes Using
Impact Estimates: Recent Geodetic Data: The
Developments using
110 Km Deep 2020
Large International
Calama Earthquake,
Earthquakes. Böse, M.,
Northern Chile. Craig,
Andrews, J., Saunders, J., T. J., Liu, F., Ebmeier,
Massin, F., Ceylan, S., et al. S., Elliott, J.

Investigating Slow
Slip Transients andEarthquake Swarms on
the Blanco Transform
Fault With Obs Data
Mining. Journeau, C.,
Thomas, A. M., Hirao,
B., Toomey, D. R.,
Hooft, E. E. E., et al.

Use of Seismometers in
Studies of Precariously
Balanced Rocks(PBRs) in the Eastern
U.S. Pratt, T. L.,
McPhillips, D., Stirling,M., Figueiredo, P.,
Lindberg, N. S.

2:30 pm

How Fast, How Deep,and How Much? —Rapid Assessmentof Groundwater
Recharge From 2023
California Storms
With Seismic Sensing.
Mao, S., Beroza, G. C.,
Ellsworth, W. L.

Generalized Neural
Networks for Universal
Real-Time Earthquake
Early Warning. Zhang,
X., Zhang, M.

Uncertainty Estimates Distant Seismic
Identifying Probablefor Moment Tensors
Monitoring of a
Fault Planes in Stable
and Quantities Derived Volcanic Earthquake
Continental Regions
From Them From
Swarm Near the Manu‘a of Canada for Use inComparison of Global Islands, American
Hazard Assessment.
Catalogs. Rösler, B.,
Samoa, with DeepBent, A. L.
Stein, S., Spencer, B.
learning and TemplateD., Ringler, A., Vackář, matching EventJ.
Detection. Yoon, C.,
Skoumal, R. J., Michael,
A. J., Downs, D. T.,
Deligne, N. I., et al.

2:45 pm

Monitoring
Groundwater
Dynamics at Lyon
Water Catchment
Using Seismic
Attenuation Variations
From Train Signals.
Pinzon Rincon, L.,
Nziengui Bâ, D.,
Mordret, A., Brenguier,F., Coutant, O.

Student: Investigating
Seismic Site
Amplification for
Improved Earthquake
Early Warning in
Canada. Pietroniro,E., Perry, H., Crane, S.,
Audet, P.

Regional Moment
Tensor Estimation
With 3D Velocity
Models—Application
and Assessment to
the 2017 Hojedk,
Iran Sequence.
Rodriguez Cardozo,
F. R., Braunmiller, J.,
Ghods, A., Sawade, L.,
Orsvuran, R., et al.

Volume 95•

Number 2B•

April 2024•

www.srl-online.org

Improving Template
Matching Detections
Using a Convolutional
Neural Network.
Jozinović, D., Toledo,T., Simon, V., Kraft, T.

Invited: A Machine
Learning Re-Analysis
of Seismic Archives
in the Northeastern
U.S.: Implications for
the Nature of Active
Faults and Faulting.
Beauce, E., Wang, K.,
Waldhauser, F., Schaff,D., Kim, W.

Seismological Research Letters

|

1183

Friday, 3 May (continued)
Time

3:00 pm

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

Advancing Seismology withDistributed Fiber Optic(continued)

Assessing Seismic Hazard
for Critical Facilities (continued)

Seismoacoustic, Geodetic
and Other Geophysical(continued)

Structure and Behaviorof the Alaska-Aleutian
Subduction (continued)

Exploring Urban Distributed
Acoustic Sensing Datasets
With Scattering Networks.
Viens, L., Seydoux, L.,
Delbridge, B. G.

Student: Site-Response
Assessment Using EmpiricalTechniques for Nuclear Sites
in South-Eastern France:
Comparisons With Ssr
and Numerical Simulation
Estimates. Buscetti, M.,
Traversa, P., Hollender, F.,
Perron, V., Moczo, P., et al.

Invited: Understanding
Volcanic Tremors Based on
Seismic Network Analysis.
Shapiro, N. M., Journeau,C., Soubestre, J., Barajas, A.,
Seydoux, L., et al.

Student: Slab Dehydration
Linked to Great Earthquake
Rupture Barriers Along the
Alaska Peninsula. Moser, L.,
Canales, J., Bécel, A.

3:15– 4:30 pm
Time

Poster BreakK’enakatnu 6/Boardroom

Kahtnu 1

From Geodynamics toEarthquake Rupture, Models
That Cross Time- andLength-Scales (see page1308).

Assessing Seismic Hazard
Machine Learning for Full
for Critical Facilities andWaveform Inversion: From
Infrastructure—Insights and Hybrid to End-to-End
Challenges (see page 1239). Approaches (see page 1342).

Structure and Behaviorof the Alaska-Aleutian
Subduction Zone (see page1424).

4:30 pm

Invited: Linking
Geodynamic-Seismic Cycling
Models With Earthquake
Dynamic Rupture Models:
5 Choices to Consider.
Madden, E. H., van Dinther,Y., Gabriel, A. A., Ulrich, T.,
van Zelst, I.

Invited: Issues in the
Selection of Design Values
for Surface Fault Rupture
for Critical Facilities
Using Probabilistic Fault
Displacement Hazard
Analysis. Abrahamson, N. A.

Invited: Advancing Seismic
Full Waveform Inversion: A
Hybrid Approach of Machine
Learning and Physical Models
for Improved Generalizability
and Efficiency. Lin, Y.

Seismic Structure of Arc
Crust in the Andreanof
Segment of the Aleutian Arc
from Wide-angle Refraction
Data. Mark, H. F., Lizarralde,D., Shillington, D., Cortés
Rivas, V.

4:45 pm

Using a Multi-Cycle,
Physics-Based Earthquake
Simulator to Explore Rupture
Connectivity for Seismic
Hazard: The Aotearoa New
Zealand Example. Howell,A., Penney, C., McLennan,
T., Seebeck, H., Williams, C.
A., et al.

Exposure of Australia’s
Infrastructure to Ground
Surface Rupture Hazard.
Quigley, M., Werner, T.,
Yang, H.

Student: Ambient Noise Full
Waveform Inversion With
Neural Operators. Zou, C.,
Azizzadenesheli, K., Ross, Z.
E., Clayton, R.

Student: Along-strike
Variations in Sub-arc Melting
Beneath the Alaska Peninsula
Revealed by Body Wave
Attenuation. Zhang, Z., Wei,
S. S.

5:00 pm

Invited: Bridging the Gap
Between Millions of Yearsand Milliseconds in ViscoElasto-Plastic Subduction
Earthquake Sequence Models.
Koelzer, A. J., de Vos, M.,
Gerya, T., van Dinther, Y.

Studies of Fragile Geologic
Features in Central New
England, USA, andNortheastern New Zealand.
Stirling, M. W., Pratt, T. L.

Application of TCN, UMAP,
and XGBoost to Pg and Lg
Wave Amplitude to Identify
Mining vs. Non Mining andDeep vs. Shallow Events.
Goddard, K., Saikia, C. K.,
Stanley, J., Patrick, T., Zhou,
R., et al.

Student: A Possible SlabWindow Along the Alaska
Subduction Zone Imaged by
Full Wave Ambient Noise
Tomography. Sassard, V.,
Yang, X., Liu, L., Elliott, J.

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Tikahtnu Ballroom A/B•

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Number 2B•

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Time

3:00 pm

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 3

Tubughnenq’ 4

Tubughnenq’ 5

ESC-SSA Joint
Session: Climate
Change (continued)

End-to-End
Advancements (continued)

Understanding andQuantifying (continued)

Advances in
Operational (continued)

Tectonics andSeismicity (continued)

Merits of Installing
Environmental Sensors
at Seismic Stations.
Tanimoto, T.

Predicting Ground
Motion Waveforms
for Earthquake Early
Warning Using
Convolutional Long
Expressive Memory
Models. Lyu, D., Nakata,R., Erichson, B. N.,
Nakata, N., Ren, P., et al.

Quantifying the Effectof 3D Wavespeed
Models on Moment
Tensors Using
Synthetic Data in the
Middle East. Doody,
C., Chiang, A.,
Simmons, N., Rodgers,
A.

Invited: Student:
Automated Detection
and Characterizationof Swarms andMainshock-Aftershock
Sequences in Southern
Mexico. VenturaValentin, W. A.,
Brudzinski, M. R.,
Bennett, A., Khalkhali,M., Coker, S.

Active Seismicity
Around a Cretaceous
Magmatic Intrusion in
Monchique, SW Iberia.
Neres, M., Cunha, G.,
Custódio, S., Soares,
A., Vales, D., et al.

3:15– 4:30 pm
Time

Poster BreakTikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 4

Tubughnenq’ 5

ESC-SSA Joint Session:
Climate Change andEnvironmental Seismology(see page 1284).

End-to-End Advancements
in Earthquake Early
Warning Systems (see page1276).

Advances in Operational
and Research Analysis ofEarthquake Swarms -II (seepage 1220).

Tectonics and Seismicity of
Stable Continental Interiors(see page 1436).

4:30 pm

Invited: Leveraging
Distributed Fiber Optic
Sensing for Year-RoundObservation of Sea Ice andSubmarine Permafrost:
Successes and Lessons
Learned From the Beaufort
Sea, Alaska. Baker, M. G.,
Stanciu, C., Abbott, R. E.,
Frederick, J. M.

Engineering Earthquake Early Seismological Study of theInvited: Amplification andWarning. Galasso, C.
West Bohemia/Vogtland
Attenuation: Putting the
Swarm Region With
Puzzle Together for Ground
Waveform and Catalog
Motions in the Atlantic andData. Olivar-Castaño, A.,
Gulf Coastal Plains. Cabas,
Büyükakpinar, P., Ohrnberger, A., Gann-Phillips, C., Ji, C.
M., Dahm, T., Doubravová,J., et al.

4:45 pm

Student: Storms, Sea Ice,and Microseismic Noise in
Alaska. John, S., West, M.

Student: Toward Earthquake Systematic Measurements
Early Warning in Nevada.
of Parameters During
Kinkel, D., Trugman, D.
Earthquake Swarms.
McNutt, S. R., Thompson,G., Braunmiller, J., Rodriguez
Cardozo, F., Holtkamp, S.

The 1886 Charleston, South
Carolina, Earthquake: Source
Properties and Ground
Motions. Hough, S. E.,
Bilham, R.

5:00 pm

Correlation of Environmental
Factors With Seismic Records
on the Alaska Geophysical
Network. Heslop, J., Murphy,N., West, M., Parcheta, C.,
Ruppert, N., et al.

Evaluation of the Ocean
Networks Canada Earthquake
Early Warning System:
Magnitude Estimation andSite Condition. Babaie
Mahani, A.

Reactivated Paleozoic andMesozoic Basement Faults
in the Charleston, South
Carolina, Seismic Zone. Shah,A. K., Pratt, T. L.

Volume 95•

Number 2B•

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Invited: Earthquake Swarms
as a Window to Characterize
Transient Processes. Chen,
X., Jiang, J., Sagae, K., Uchide,
T.

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Friday, 3 May (continued)
Time

K’enakatnu 6/Boardroom

Kahtnu 1

Kahtnu 2

Tikahtnu Ballroom A/B

From Geodynamics toAssessing Seismic Hazard
Earthquake Rupture, Models for Critical Facilities (con(continued)
tinued)Machine Learning for Full
Waveform Inversion: From
Hybrid (continued)

Structure and Behaviorof the Alaska-Aleutian
Subduction (continued)

5:15 pm

Student: Fully Dynamic
Earthquake Cycle Modelingto Explore Interactions
Between Large Earthquakes
and Slow Slip Events on
Heterogeneous Faults. Tang,Z., Duan, B., Meng, Q.

Fault-Displacement Models
for Aggregate, Principal, andDistributed Displacements.
Lavrentiadis, G.,
Abrahamson, N. A.

Scaling Up Large Fourier
Neural Operator Training
in 3D Seismic Waveform
Modeling. Kong, Q., Matzel,
E., Zou, C., Choi, Y., Ross, Z.,
et al.

The Structure of the Alaskan
Mantle: A Full Waveform
Inversion Approach. Frost,
D. A., Romanowicz, B.,
Adourian, S.

5:30 pm

Student: Insights Into
Fault Interactions inCentral New Zealand Using
Paleoearthquake Records
and Earthquake Simulators.
Humphrey, J. A., Howell,A., Penney, C., Nicol, A.,
Litchfield, N., et al.

Looking for kappa in the
US and the UK Using Noise
Modeling. Ktenidou, O. J.,
Pikoulis, E. V., Darragh, R. B.,
Silva, W. J., Aldama-Bustos,G.

Invited: Physics-Informed
Deep Generative Models to
Quantify Uncertainties in the
Geophysical Full-Waveform
Inversion. Elmeliegy, A.
M., Dhara, A., Sen, M. K.,
Harding, J. L., Yoon, H.

Upper Mantle Velocity
Structure and Anisotropyof the Alaskan Subduction
Zone from Surface Wave
Tomography. Adams, A.,
Ramirez, C., Wen, J., Leclerc,
P.

Poster Sessions
The 2024 Magnitude 7.5 Earthquake and the AssociatedEarthquake Swarm Beneath the Noto Peninsula, Central
Japan (See Supplemental Material)
Advancing Seismology with Distributed Fiber Optic
Sensing (see page 1228).
1. Matched-Filter Earthquake Detection Applied to CityScale DAS Fibre-Optic Systems in Aotearoa New Zealand:
What More Can We Detect?. Chamberlain, C. J., McNab,
A., Lindsey, N., Townend, J., can Wijk, K.
2. Student: Using AIS Data to Determine the Location of
Ocean Bottom Fiber Optic Cables. Collares, M. P., Spica,
Z., Viens, L.
3. Near-Source T-Wave Observations in the North Atlantic
Using Distributed Acoustic Sensing. Schlaphorst, D.,
Loureiro, A., Matias, L., Custódio, S., Corela, C., et al.
4. Student: Geolocalization and Preliminary Surface
Signals of Cascadia DAS Array, Port Angeles, Washington.
Dingo, H., Sheehan, A. F., Mendoza, M. M., Martin, E. R.
5. Fiber Optic Wellbore Installation for Distributed Acoustic
Sensing at Los Alamos National Laboratory. Donahue,
C., Maier, N., Roberts, P.

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6. Student: Use of Distributed Acoustic Sensing as a Tool
for Monitoring Geohazards at Mt. Rainier. Gaete Elgueta,
V. A., Lipovsky, B., Denolle, M., Thelen, W., Kharita, A.
7. Student: Signal Detection With Neural Networks in
Dark Fiber Seismic Data. Hoyle, A. M., Smolinski, K.,
Bozdag, E., Wu Fung, S., Fichtner, A., et al.
8. Student: Modelling Wavefield Complexity for Submarine
DAS Data From Santorini (Greece). Igel, J., Klaasen, S.,
Noe, S., Nomikou, P., Karantzalos, K., et al.
9. Earthquake Detection of the MiDAS Seismic Monitoring
System Containing Downhole Optic-Fiber Distributed
Acoustic Sensing and Borehole Seismometers. Lin, Y.,
Chan, J.
10. Student: HD-TMA: A New Fast Template Matching
Algorithm Implementation for Linear DAS Array Data.
Lv, H., Zeng, X., Song, Z.
11. 2-D Shear-Wave Velocity Profile of Shallow Sediments
Using Ocean Bottom Distributed Acoustic Sensing andAmbient Noise Probabilistic Inversion. Ben Mansour,W., Spica, Z., Viens, L., Liu, M.
12. Towards a Metadata Standard for Distributed Acoustic
Sensing (DAS) Data Collection. Mellors, R. J., Hui Lai,
V., Hodgkinson, K. M., Porritt, R.
13. Exploring the Potential for Joint Monitoring of Tectonic
Tremor Using Dark Fiber and Seismometers. Mendoza,
M. M., Martin, E. R., Issah, A. S., Jin, G., Gaete Elgueta, V.
A., et al.
14. A Metadata and Time-Series DAS Workflow Using Cloud
Computing. Ramos, M. D., Hodgkinson, K. M., Tibi, R.
www.srl-online.org•

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Number 2B•

April 2024

Time

Tikahtnu Ballroom C

Tikahtnu Ballroom E/F

Tubughnenq’ 4

Tubughnenq’ 5

ESC-SSA Joint Session:
End-to-End Advancements
Climate Change (continued) in Earthquake (continued)

Advances in Operational
and Research Analysis ofEarthquake (continued)

Tectonics and Seismicity of
Stable Continental Interiors(continued)

5:15 pm

Invited: An Extraordinary
Student: Impact Assessment
Tsunamigenic Rockslide Into of Eew Systems in Central
a Greenland Fjord Rang theAmerica. Orihuela, B.,
Earth for 9 Days. Svennevig,
Clinton, J., Papadopoulos, A.,
K., Hicks, S. P., Forbriger, T.,
Danciu, L., Böse, M., et al.
Lecocq, T., Widmer-Schnidrig,R., Mordret A. et al.

Deep Learning Analysis
of Transient Signals
Preceding the 2023 Mw 7.8
Kahramanmaraş Earthquake
in Türkiye. Zali, Z., Martinez
Garzon, P., Kwiatek, G.,
Bohnhoff, M., Beroza, G.

Evidence of Quaternary
Deformation in the Ste.
Genevieve Fault Zone,
Southeastern Missouri:
Preliminary Results. Counts,
R. C., Vaughn, J., Nelson, W.,
Devera, J. A., Curry, B.

5:30 pm

Insights for Adjacent
Sciences—Connecting
Science, Art and Deep
Knowledge for Climate
Adaptation and Mitigation.
Strickert, G. E. H., Bradford,
L. E. A., Helgason, W.

Enhanced Seismicity at a
Geothermal Spot in Southern
Tibet Following 2004 Mw
9.1 Sumatra and 2005 Mw
8.6 Nias Earthquakes and
Its Implication for Rifting
Process. Liang, X.

Microgal-Precision Gravity
Imaging Within an Active
Intraplate Fault: The 2020
m5.1 Sparta, Nc Epicentral
Zone. Levandowski, W.

Performance of Operational
Earthquake Early Warning
Across Central America.
Massin, F., Clinton, J., Bose,
M., Burgoa, B., Marroquin,G., et al.

15. Exploring Source and Structure Sensitivity Kernels of
DAS Ambient Noise Correlations. Pinzon Rincon, L.,
Mordret, A., Brenguier, F., Gradon, C., Lavoué, A., et al.
16. Distributed Fiber-Optic Magnetic Sensing for Subsurface
Imaging and Monitoring. Yuan, S., Snyder, T., Martin, E.,
Homa, D., Dejneka, Z., et al.
End-to-End Advancements in Earthquake Early Warning
Systems (see page 1281).
17. Improving Seismic Networks for the Earthquake Early
Warning Mission. Biasi, G., Stubailo, I., Alvarez, M.
18. Picket Fence: An Earthquake Alert System for the Ligo
Detectors. Bonilla, E. L., Aguilar, I., Lantz, B.
19. Examination of Usage Rates for the Multi-Hazards San
Diego County Emergency App to Improve Earthquake
Early Warning. Brudzinski, M. R., Sumy, D., Gomez, K.,
Jordan, P., Robles, M., et al.
20. Implementation of a Machine Learning Classifier in the
Real-Time EPIC Earthquake Early Warning Algorithm.
Lux, A. I., Henson, I., Meier, M., Allen, R. M.
21. Engage With Your Regional Museums, Parks, andLibraries for Community Resilience. Preciado Mendez, R.
G., Benne, M., de Groot, R., Herrán, C., Crayne, J.
22. Recent Earthquake Early Warning Research andDevelopments at the Southern California Seismic
Network. Saunders, J. K., Biondi, E., Boese, M., Bunn, J.,
Cochran, E., et al.

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23. Preliminary Multilingual Survey Results on San Diego
County’s Sd Emergency Multi-Hazards App to Improve
Equity in Disaster Risk Reduction. Sumy, D., Brudzinski,
M. R., Gomez, K., Briceno, Y., Jordan, P., et al.
24. Magnitude Station Corrections to Improve Initial
Magnitude Estimates for ShakeAlert. Terra, F., Lombard,
P. N., Williamson, A., Uhrhammer, R., Taira, T., et al.
25. Low-Latency Digitization, Communication and Alertingfor Earthquake Early Warning Systems: Güralp Minimus.
Lindsey, J. C., Watkiss, N. R., Hill, P., O’Neill, J.
ESC-SSA Joint Session: Climate Change andEnvironmental Seismology (see page 1286).
26. Successful Deployment of an 21km SMART Cable With
Force-Feedback Seismometer and Accelerometers in the
Mediterranean Sea. Lindsey, J. C., O’Neill, J., Nicholson,
B., Watkiss, N., Marinaro, G., et al.
27. Using Deep Learning to Detect Vehicle Related Signals
From Seismic Records. Chai, C., Marcillo, O., Maceira,M., Kerekes, R.
28. Monitoring Groundwater Using Ambient Seismic Noise.
D’Amico, S., Galone, L., Panzera, F., Colica, E., Fucks, E.,
et al.
29. Influence of the Hurricane Otis on the Mexican Seismic
Network. Dominguez, L. A., Quintanar, A., Cruz-Atieza,
V. M., Gómez-Ramos, O., Plata-Martinez, R., et al.
30. Glacier Seismology Application. Germenis, N. G.

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Friday, 3 May (continued)
31. Student: Estimation of the Source Region of Secondary
Microseism Generated by Pacific Typhoons Using
CTBTO Seismic Arrays. Kim, Y., Sheen, D.
32. Global Observation of an Up to 9 Day Long, Recurring,
Monochromatic Seismic Source Near 10.9 mHz
Associated With Tsunamigenic Landslides in a Northeast
Greenland Fjord. Widmer-Schnidrig, R., Mordret, A.,
Svennevig, K., Hicks, S. P., Forbriger, T., et al.
33. Exploration of Decadal Crustal Velocity Changes
Associated With Tidal-Induced Strain Using Seismic
Noise. Wu, S., Nakata, N.
34. Student: Resolving Temporal Variations in Subsurface
Velocity and Attenuation Structure Across the Taklimakan
Desert Using Road Traffic Seismic Signals. Zhao, L.,
Meng, H., Liang, X.
Tectonics and Seismicity of Stable Continental Interiors(see page 1440).
35. Student: Inferring Crustal Stress Distribution Within
the Middleton Place/summerville Seismic Zone, South
Carolina. Adeboboye, O. E., Peng, Z., Jaume, S.
36. Student: Developing Ground Motion Model Using
Nonparametric Machine Learning Techniques for
Induced Earthquakes in Central and Eastern North
America (Cena). Alidadi, N., Pezeshk, S.
37. Seismic Networks Important in Lower Seismic Hazard
Environments like Australia. Borleis, E.
38. Neotectonic Mapping of the Charleston Seismic Zone,
South Carolina. Thompson Jobe, J. A., Briggs, R., Collett,C., Shah, A. K., Pratt, T.
39. Student: Determination of Focal Depth of Offshore
Earthquakes Around the Korean Peninsula Using Depth
Phase. Lee, H., Sheen, D.
40. Student: Africa’s Lithospheric Architecture With MultiMode Body Wave Imaging. Legre, J. B., Olugboji, T. M.
41. Crustal Structure and Mantle Deformation Across theCentral African Plateau, Zambia: Evidence from Receiver
Functions and Shear-Wave Splitting Analysis. Kounoudis,
R., Ogden, C. S., Chifwepa, C., Fishwick, S., Kendall, M.,
et al.
42. Student: Stochastic Inversions of Source, Path, andSite Parameters for West Texas Earthquakes. Pandel, B.,
Rathje, E. M., Savvaidis, A., Kottke, A. R.
43. The 2020 Sparta, North Carolina, Earthquake: Insights
From Double-Difference Earthquake Relocations,Regional Moment Tensor Inversion and Coulomb StaticStress Transfer. Parija, M., Chapman, M. C., Pollyea, R.
44. Neotectonic Controls on the Meadow Bank Scarp, Wabash
Valley Seismic Zone USA. Woolery, E. W., Stephenson,
W. J., Woller, K. L., Leeds, A. L., Lindberg, N. S., et al.
45. Source Characterization of the 2020 Mw 5.1 Sparta, North
Carolina, Earthquake Sequence. Wu, Q., Chapman, M.
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Anisotropy Across Scales (see page 1234).
46. Student: Analysis of Anisotropic Characteristics inthe Valley of Mexico. Chacón, F., Quintanar-Robles, L.,
Rodríguez-Rasilla, I.
47. S Wave Velocity and Azimuthal Anisotropy From
Ambient Noise Data in the Sanjiang Lateral Collision
Zone of SE Tibetan Plateau. Tian, J., Gao, Y., Li, Y.
48. Student: Exploration of Anisotropy from Crystal to
Whole-Earth Scales. Gupta, A., Tape, C.
49. 3D Shear Wave Velocity and Azimuthal Anisotropy Modelfor the Crust and Upper Mantle in Alaska Extracted by
the Joint Inversion of Wave Gradiometry Method andAmbient Noise Tomography Method. Liang, C., Liu, Z.,
Cao, F.
50. Imaging Lower Crustal Flow Using Harmonic
Decomposition of Receiver Functions Beneath a Dense
Seismic Profile in Eastern Massachusetts. Link, F., Luo,
Y., Long, M. D., Kuiper, Y. D.
51. Shear Wave Splitting Characteristics of Aligned Partial
Melt Configurations in a Subduction Zone Back-Arc
Setting. Loeberich, E., Wolf, J., Long, M. D.
52. A Reformulation of the Browaeys and Chevrot
Decomposition of Elastic Maps. Tape, W., Tape, C.
53. Student: Refining Splitting Intensity Measurementsof Shear Wave Splitting for Multi-Layer Anisotropy.
Valencia, N., Kumar, U., Soergel, D., Romanowicz, B.
Understanding and Quantifying the Variability in
Earthquake Source Parameter Measurements (see page1452).
54. Student: Using a 1-D Radially Symmetric Coda Envelope
Model for Robust Source Scaling in Iraq’s TectonicallyDiverse Zones. Al-Kaabi, M., Mayeda, K., Roman-Nieves,J., Chiang, A., Mahdi, H., et al.
55. A Comparison of the Stress Drop Estimates Derived
From Different Techniques in Pollino, Italy. Calderoni,G., Abercrombie, R. E.
56. Student: Sensitivity Analysis of Seismic Hazard
Parameters for the Understanding of Its Uncertainties:
A Study Case for Central America. Gamboa-Canté, C.,
Arroyo-Solórzano, M., Rivas-Medina, A., Benito, B.
57. Adjoint Earthquake Source Inversion Method Using
P-Wave Spectra and Focal Mechanism Solutions. Cheng,Y., Dreger, D. S., Allen, R. M.
58. Bayesian Inference for the Seismic Moment Tensor Using
Regional Waveforms and a Data-Derived Distribution of
Velocity Models. Chiang, A., Ford, S. R., Pasyanos, M.
59. Characterizing Directivity in Small (M3-5) Aftershocksof the Ridgecrest Sequence. Chu, S., Baltay, A. S.,
Abercrombie, R.

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60. DAS Derived Source Characterization of Ridgecrest
Aftershocks Using Coda Spectral Ratios. Delbridge, B.
G., Viens, L., Zhan, Z., Chen, X.
61. Student: Understanding Sources of Variability andUncertainty in the Relative Magnitude Method. Gable,
S., Huang, Y.
62. Student: Development of Empirical Scaling Relationships
Between Spectral Displacement Amplitudes Measured in
the Time Domain and Earthquake Magnitudes in South
Korea. Hong, Y., Kim, B., Sheen, D.
63. Moment-Rate Spectra, Source Scaling and Spectral FallOff in the Korean Peninsula Using the Coda Calibration
Tool (2.0<Mw<5.5): Application to Natural and ManMade Sources. Mayeda, K., Roman-Nieves, J., Son, M.
64. Student: Evaluating Scaling Relationships From InsarDerived Earthquake Source Parameters. Rivera, K. M.,
Funning, G. J.
65. Student: Rupture Directivity of Small Earthquakes inSouthern Korean Peninsula. Seo, M., Han, S., Kim, W.,
Kim, Y.
66. On the Variability Discrepancy Between PGA andSpectral Stress Drop: Insight From Double-CornerFrequency Spectra. Shimmoto, S., Miyake, H.
67. New Version of the Earthquake Mechanism of
Mediterranean Area (EMMA) Database With a WebGis Interface. Vannucci, G., Tarabusi, G., Taccone, R.,
Biondini, E., Lolli, B., et al.
Seismoacoustic, Geodetic and Other GeophysicalInvestigations of Active Volcanoes (see page 1405).
68. Student: Surface Deformation at the Socorro Magma
Body: A Natural Laboratory for Probing Mush andMagma in the Mid-Crust. Block, G. A., Roy, M., Graves,E., Grapenthin, R.
69. Automated Detection of Volcanic Seismicity Using
Network Covariance and Image Processing. Maher, S.,
Dawson, P., Hotovec-Ellis, A., Thelen, W., Matoza, R.
70. Long-Period Earthquakes in the Yellowstone Volcanic
System: When, Where, Why?. Farrell, J., Hale, M., Baker,
B.
71. Student: Mining for Hidden Seismicity at Mount St.
Helens. Hirao, B. W., Thomas, A. M., Shelly, D. R., Thelen,W.
72. Ground-Tilt Caused by Atmospheric Lamb Waves Fromthe 2022 Tonga Eruption Recorded at Fiji and Pinon Flat
Observatory. Ichinose, G. A., Mellors, R. J.
73. Soundquakes: Seismo-Infrasonic and Seismo-InfraSeismic Phases During a Swarm of Earthquakes at Kilauea
Volcano on September 30th, 2021. Johnson, J., Jolly, A.,
Anderson, J. F.

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74. Student: Laboratory Experiments on Gas-Driven
Volcanic Tremor and Long Period Seismicity. Kim, K.,
Spina, L., Taddeucci, J., Pennacchia, F., Cornelio, C., et al.
75. Monitoring Unrest at a Supervolcano: Insights From the2022-23 Unrest Episode at Taupō Volcano, Aotearoa New
Zealand. Lamb, O., Hreinsdóttir, S., Power, W., Bannister,S., Ristau, J., et al.
76. Student: Imaging the Magma Plumbing System Below
Okmok Volcano Using Full-Wave Ambient Noise
Tomography. Lizik, Y., Maurer, J., Yang, X., Kupres, C. A.
77. Student: Crustal Structure of the Laguna Del Maule
Volcanic Field Using Receiver Functions. Nolt-Caraway,
S., Portner, D.
78. Seismological Models and Seismicity Patterns in the Kivu
Rift and Virunga Volcanic Province (D.R. Congo). Subira,J., Barrière, J., Caudron, C., Oth, A., d’Oreye, N., et al.
79. Student: Seismicity Classification From Eruptions:
Analysis of Hawaiian and Aleutian Island Volcanoes.
Rinty, S., Goebel, T. H.
80. Analysis of the Seismicity Recorded Before the May
22, 2021 Eruption of Nyiragongo Volcano, Democratic
Republic of the Congo. Sadiki, A., Kyambikwa, A.,
Namogo, D., Diomi, L., Munguiko, O., et al.
81. Seismic Source Scaling of Volcano-Seismic Events:
Tracking Magma Plumbing System Overpressure
and Volume Through Macroscopic Seismic Source
Parameters. Niu, J., Song, T.
82. Eruption Dynamics of the 2022 Mauna Loa Eruption
Revealed Through Tremor. Thelen, W., Iezzi, A. M.,
Chang, J. C., Dotray, P.
83. Using Remote Hydroacoustic Recordings to Track
Volcanic Unrest Near the Ta‘ū Islands, American Samoa.
Wech, A., Haney, M. M., Chang, J. C., Jolly, A., Yoon, C.
84. Student: Inversion of Multiple Concurrent Resonant
Oscillations at Kīlauea Volcano During Very-LongPeriod Seismic Events Informs Magma System Properties.
Wilde, K. L., Karlstrom, L., Crozier, J. A., Lynn, K. J.
85. Seismic Velocity Changes Across Multiple Eruption
Cycles at Shishaldin Volcano in the Eastern Aleutian Arc.
Yang, X., Freymueller, J. T., Kupres, C. A., Denolle, M. A.,
Haney, M. M.
86. Seismicity,
Ambient
Noise
Tomography,
andAnthropogenic Noise via the Auckland-Hauraki Node
Array in New Zealand. Zhang, P., Pickle, R., Miller, M. S.
Physics-Based Ground Motion Modeling (see page 1380).
87. A Parametric Analysis on the Behaviors of Seismic Waves
Interacting With Geologic Metamaterials. Beskardes, G.
D., Preston, L.
88. Student: Updated Regional Seismic Velocity Modelfor the US Atlantic and Gulf Coastal Plains Based on
Measured Shear Wave Velocity, Sediment Thickness,
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Friday, 3 May (continued)
Varying Geologic Structure With Depth, and Lateral
Variations. Gann-Phillips, C., Cabas, A.
89. Physics-based Numerical Modeling of Site-specific
Amplification in Ground Motions: A Case Study of
Wellington Basin. Li, D., Thingbaijam, K., Hill, M.,
Howell, A., Bora, S., et al.
90. Constraining Large Magnitude Event Source and Path
Effects Using Ground Motion Simulations. Meng, X.,
Graves, R., Goulet, C.
91. Student: The Case of the Missing Frequencies: Reductionof Artificial Spectral Deficiency in Semistochastic
Broadband Simulation. Nye, T., Dybing, S., Melgar, D.,
Sahakian, V. J.
92. Student: 3D Ground Motion Simulations of the 1755
Lisbon Earthquake. Patel, A., Olsen, K., Yeh, T., Custódio, S.
93. Student: Extended Finite-Fault Ground Motion
Modeling Framework: Sensitivity Analysis of Number of
Sub-Faults. Singh, O.
From Geodynamics to Earthquake Rupture, Models That
Cross Time- and Length-Scales (see page 1309).
94. Bridging Spatial and Temporal Scales in Modeling
Coseismic and Interseismic Crustal Deformation with
PyLith. Aagaard, B. T., Knepley, M. G., Williams, C. A.
95. Student: Spatiotemporal Evolution of Postseismic
Stress and Aftershocks Following the 2010 Mw 8.8 Maule
Earthquake. Bodunde, S. S., Jiang, J.
96. Geodynamic Modeling of Flat Slab Subduction Driving
Microplate Tectonics in Alaska. Jadamec, M. A., Haynie,
K. L., Knepley, M. G.
97. Fast and Slow Earthquakes in Alaska: Insights From ThreeDimensional Thermal Structure and Slab Dehydration. Ji,
Y., Qu, R., Zhu, W.
98. Student: Modeling the Proposed Deep Slab-Deformation
Processes Behind Potential Precursory Signals Preceding
Large Subduction Zone Earthquakes. Lemus, I. C.,
Baden, C. W., Chanard, K., Wang, L., Bürgmann, R.
99. Geodynamic Models Connecting the Seismic Timescale
to the Tectonic Timescale. Moresi, L., Yang, H., Giordani,J., Knight, B.
Machine Learning for Full Waveform Inversion: From
Hybrid to End-to-End Approaches (see page 1343).
100. Physics-Guided Neural Network for Full Waveform
Inversion With Structural Enhancement. Bi, Z., Nakata, N.
101. Student:
Physics-Guided
Unsupervised
Deep
Learning Approach for the Inversion of Receiver
Functions in Dipping and Anisotropic Media. Dalai, B.,
Kumar, P., Sen, M. K.
102. Towards a Practical Physics-Informed Neural
Network Method for End-to-End Full Waveform
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Inversion. Harding, J. L., Lizama, D., Yoon, H., Gauvain,
S. J., Preston, L. A., et al.
103. Student: An Autoencoder-Based Prior for Bayesian
Full Waveform Inversion. Hu, S., Sen, M. K., Zhao, Z.,
Elmeliegy, A. M.
Structure and Behavior of the Alaska-Aleutian Subduction
Zone (see page 1428).
104. Student: A Re-Evaulation of Slip During the 2021
M8.2 Chignik, Alaska Earthquake. Bennett, A. J. M.,
Elliott, J., Grapenthin, R., Freymueller, J. T.
105. Take the Cook Inlet DAS Earthquake Challenge!.
Bodin, P., Williams, E. F., Shi, Q., Ni, Y., Lipovsky, B., et al.
106. Student: Searching for Microseismic Precursors
to the July 2020 Mw 7.8 Simeonof, Alaska Earthquake
in a Machine-Learning Enhanced Catalog. FriedmanAlvarez, C., Barcheck, G., Nolan, S., Abers, G. A.
107. Introducing the Alaska Broadband Accessory
Deployment for Geophysical Research (BADGER): A
New Seismic Dataset for Investigating Slow Slip and
Subduction Zone Structure. Golos, E., Aleid, M. H., Lord,N., Sobol, P., Denolle, M., et al.
108. Mapping the Alaskan Lithosphere Based Upon Joint
Full-Waveform Inversion of Ambient Noise and Local
Earthquake Data. Liu, T., Wang, K., Tape, C., He, B., Yang,Y., et al.
109. Insights Into Inherited Crustal Features and Southern
Alaska Tectonic History From Sp Receiver Functions andSeismicity. Mann, M., Fischer, K. M., Benowitz, J. A.,
Wech, A.
110. Student: Examining the Distribution of Earthquakes
Within the Alaska-Aleutian Subduction Zone Using
Events Detected by the Alaska Amphibious Community
Seismic Experiment. Nolan, S., Abers, G., Barcheck, G.,Friedman-Alvarez, C., Roecker, S. W.
111. Student: Searching for Tectonic Tremor Alongthe Lower Cook Inlet Portion of the Alaska-Aleutian
Subduction Zone. Ochoa, E., Golos, E. M.
112. Student: Probabilistic Teleseismic Tomographyof the Alaskan Mantle With Corrections for Distant
Structure. Okkonen, N., Burdick, S.
113. Building a 3D Seismic Velocity Model for the Gulf of
Alaska. Onyango, E. A., Tape, C., Mcpherson, A.
114. Student: Investigating Temporal Velocity Changes
and Plate Interface Structure in the Southern Mw 9.2 1964
Great Alaska Earthquake Rupture Area: A Comparative
Study of Ambient Noise and Earthquake Observations
Using a Dense Node Array. Osasona, J. O., Worthington,
L. L., Schmandt, B., Barcheck, G., Abers, G., et al.
115. Upper Plate Structure in the Alaska Subduction Zone
Across the 2020 and 2021 Ruptures From 2D Wide-Angle

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Seismic Data. Burstein, J., Shillington, D., Bécel, A.,
Nedimović, M. R.
116. Student: Comparison of Crustal Magmatic Storageat Aleutian Volcanoes, Gareloi and Kanaga, using
Teleseismic Receiver Function Analysis. Wandasan, C.,
Janiszewski, H., Wynn, I. V.., Power, J. A., Haney, M. M.
117. Cook Inlet DAS (CI-DAS): A Year-Long Experiment
Studying Structure, Seismicity, Ocean Waves, andAcoustics Offshore Southern Alaska. Williams, E. F.,
Abadi, S., Aderhold, K., Bodin, P., Denolle, M., et al.
118. Invited: Student: Investigation of Magmatic
Systems Through Novel Seismic Receiver Function
Analysis at Alaska-Aleutian Arc Volcanoes. Wynn, I. V.,
Janiszewski, H. A., Power, J. A., Haney, M. M., Roman, D.
119. Student: Testing Machine Learning Phase Pickers
to Develop a High-Resolution Earthquake Catalog Witha 398-Instrument Nodal Array on Kodiak Island, Alaska.
Zhu, H., Ayling, S., Worthington, L. L., Barcheck, G.
Advances in Operational and Research Analysis ofEarthquake Swarms (see page 1222).
120. Student: Feature-based Magnitude Estimates for
Small, Nearby Earthquakes in the Yellowstone Volcanic
Region. Armstrong, A. D., Baker, B., Koper, K.
121. Student: Analysis of Yellowstone Earthquake
Swarms After Relocating Using Nonlinloc-Ssst and a 3D
Velocity Model. Czech, T. L., Farrell, J.
122. It’s Swarmy Outside: Defining Swarms for the
Purpose of Forecasting. Llenos, A. L., Michael, A. J.,
McBride, S. K., Page, M. T., van der Elst, N., et al.
123. Event-Event Waveform Correlation and Multi-Event
Multi-Channel Deconvolution Applied to TemporalSpatial Patterns of Micro Earthquake Sequences (Swarms).
McLaughlin, K. L., Jaume, S. C.
124. Heterogeneous Seismic Swarm Activity in Central
Utah: Triggering Mechanisms and Their Complex
Interactions. Petersen, G., Whidden, K., Pankow, K. L.
125. What Has Unimak Island in Alaska Witnessed in theLast ~30 Years?—a Seismic Recap. Parameswaran, R. M.,
Grapenthin, R.
126. Correlations and Change Points Identification in
Crustal Anisotropy, b-Value and Vp/vs, Time Series
During Seismic Swarm Occurrences in the Alto Tiberina
Fault Zone (Italy). Zaccarelli, L., Taroni, M., Baccheschi, P.
Assessing Seismic Hazard for Critical Facilities andInfrastructure—Insights and Challenges (see page 1241).
127. Implementation of Interconnected Fault Systems in
PSHA: Testing Existing Algorithms in Different Tectonic
Context. El Kadri, S., Beauval, C., Brax, M., Klinger, Y.

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128. Magnitude Dependency of Spectral Decay Parameter(Kappa) at Rock Stations from Event Dataset that is
Restricted Only from Events that are Originated around
Eastern Anatolian Fault (EAF). Biro, Y.
129. Monitoring and No-Money-Toring of Oil and Gas
Production in Southern Italy. Braun, T., Danesi, S.
130. Student: Insights From Distinct Element Method
Models on Fault Scarp Morphology in Thrust and Reverse
Fault Earthquakes. Chiama, K., Bednarz, W., Moss, R.,
Shaw, J. H.
131. Overcoming Factors That Limit the Predictive Powerof Probabilistic Fault Displacement Hazard Models.
Elliott, A., Hammer, M., Vermeer, J., DeLong, S., Kottke,A., et al.
132. Time-Domain Seismic Response Retrieval from
Ambient Noise Recorded by the Existing Seismometer ofDams Based on Interferometric Processing. Kuroda, S.
133. Comparison of Methods to Produce Virtual Ruptures
for Background Seismicity. Yust, M., Largent, M.,
Williams, T., Watson-Lamprey, J., Montaldo-Falero, V., etal.
134. Student: The Role of Epistemic Uncertainty
Estimations in Seismic Safety Decision Making andRelation to Levels of Input Model Simplification. Liou, I.
Y., Abrahamson, N. A.
135. Using 3D Seismic Simulations to Determine
Structural Designs That Best Preserve Structural Integrityof Buildings in an Earthquake. Ronnett, M.
Integrative Assessment of Soil-Structure Interaction andLocal Site Effects in Seismic Hazard Analysis (see page1330).
136. Student: Assessment and Results From New
Bayesian SPAC Analysis for 1D Velocity Profiles
Compared to Traditional MASW in Puerto Rico. Toro
Acosta, C., Vanacore, E., Pachhai, S., Stephenson, W. J.
137. Seismic Response in Pyramids of the Chichén Itzá
Area, México. Cardenas-Soto, M., Escobedo-Zenil, D.,
Cifuentes-Nava, G., Sánchez-González, J., MartínezGonzález, J., et al.
138. Site Response Analysis and Its Significance atNonlinear Sites. Lee, J., Bayudanto, A., Yazdi, M., Rong,
W., Walker, M.
139. Student: Ambient Vibration Testing of Canada’s
Tallest Wood Frame Building. Leishman, T., Ventura, C.
E., Motamedi, M., Cassidy, J. F., Dosso, S. E.
140. Wind Turbines as a Metamaterial-Like Urban Layer:
An Experimental Investigation Using a Dense Seismic
Array and Complementary Sensing Technologies. Pilz,
M., Roux, P., Mohammed, S. A., Garcia, R. F., Steinmann,R., et al.

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Friday, 3 May (continued)
141. Site-City Interaction in the Valley of Mexico: 3D
Simulations and Observations. Ramirez-Guzman, L.,
Carrillo Lucia, M. A., Contreras, M. G., Bañuelos, D.
142. Seismic Response of Nenana Sedimentary Basin,
Central Alaska. Smith, K., Tape, C., Tsai, V. C.
143. State of the Art in Seismic Metamaterials. Stephane,
B.
Research Advances in “High-Impact”, “Under-Studied”
Earthquakes and Their Impacts on Communities (see page1390).
144. Impact of November 2023 Earthquake in Western
Nepal. Dhakal, H.
145. Student:
Examiningthe1953
Kefalonian
Earthquakes, From a Social Perspective. Galanos, N.,
Kouskouna, V., Sakellariou, N., Galanos, G. S.
146. Seismic Hazard and Risk in Lae City, Papua New
Guinea (PNG). Griffin, J. D., Cummins, P. R., Clark, D. J.,
Edwards, M., Espi, J., et al.
147. The“Earthquake
Suitcase”—A
ResearchInspired Educational Tool for Earthquake Vulnerable
Communities. Kouskouna, V., Sakkas, G., Sakellariou,N., Galanos, N., Ridge, H.
148. Student: High-Impact Earthquakes on Hidden,
Secondary Faults Within the Sparsely Instrumented
Golden Triangle Region of Laos, Thailand, and Myanmar.
Sethanant, I., Nissen, E., Bergman, E., Oliva, S., PousseBeltran, L., et al.
149. The Center for Collective Impact in Earthquake
Science (C-CIES). Velasco, A. A., Weidner, J., Karplus,
M. S., Bilek, S., Bolton Valencius, C., et al.
Seismic Cycle-Driven Sea-Level Change Over Decades toCenturies: Observations and Projections (see page 1259).
150. Validation of Probabilistic Coseismic Coastal
Deformation Models using Geologic and Geomorphic
Evidence. Clark, K. J., Howell, A., Delano, J., Litchfield,
N.
151. Student: How Will Earthquakes Change Sea Level?
a Probabilistic Coast-Seismic Hazard Model. Delano, J.,
Howell, A., Clark, K., Rollins, C., Stahl, T., et al.
152. Toward
Resilient
CoastalCommunities:
A
Probabilistic Assessment of Co- and Inter-Seismic
Vertical Land Motion. Kim, J., Schmidt, D., Pearson, A.
153. Decade-to-Century Scale Vertical Earthquake-Cycle
Deformation at Subduction Zones: Implications for
Cascadia and Nankai. Li, S., Chen, L.
154. AssimilationofVerticalLand
Movement
Observations and Models to Support Sea Level Rise
Planning Along the Shorelines of the Cascadia Subduction
Zone. Miller, I. M., Schmidt, D., Pearson, A., Kim, J.
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Seismological Research Letters155. Complex Earthquake Deformation Drives Relative
Sea-Level Change Where Oblique Contraction Focuses
Rock Uplift West of the Fairweather Fault, Southeast
Alaska. Witter, R., Kelsey, H., Lease, R., Bender, A.,
Scharer, K., et al.
Regional-Scale Hazard, Risk and Loss Assessments (seepage 1385).
156. Empirical Response of Subduction-Zone Ground
Motions in the Cook Inlet Basin of Alaska. Ahdi, S. K.,
Parker, G. A., Skarlatoudis, A.
157. Student: Physics-based Seismic Hazard Assessment
Using Multi-cycle Earthquake Simulations: Influenceof Segment Connectivity and Strength Distribution.
Aspiotis, T., Zielke, O., Mai, M. P.
158. Seismic Hazard Assessments for the Jackson Purchase
Region (Upper Mississippi Embayment) Using Reelfoot
Fault Scenarios and Site-Specific Vs Profiles. Carpenter,
S., Wang, Z.
159. A Remarkable Absence of Liquefaction: DataDriven Lessons From the 2014 South Napa Earthquake.
Greenfield, M. W.
160. Offshore Seismic Hazards in Southern Cascadia.
McPherson, R. C., Patton, J. R., Dreger, D. S., Dengler, L.
A., Hellweg, M., et al.
161. Modelled Impacts of Rupture on the Newly
Discovered XEOLXELEK-Elk Lake Fault, BC, Canada.
Hobbs, T. E., Patchett, M., Silva, V., Rao, A., Kim, J.
162. A Future Scenario Earthquake and Ground Motion
Hazards for Kathmandu, Nepal. Koketsu, K., Miyake, H.,
Okumura, K., Suzuki, H.
163. Unraveling Seismic Complexity: Repeating Rupture
Patterns and Varied Seismogenic Environments in the
Mexico Subduction Zone. Liu, C., He, P., Lay, T., Xiong, X.
164. Student: Influence of Site Effects’ Spatial Variability
on Spatially Variable Ground Motion Intensity Measures.
Lorenzo-Velazquez, C., Cabas, A.
165. Towards Probabilistic Tsunami Risk Estimates Using
Stochastic Earthquake Sources. Melgar, D., Eguchi, R.,
Koshimura, S., Crowell, B., Lee, Y., et al.
166. Seismic Geohazards in Italy: Seismic Geohazards
in Italy: An Integrated Geotechnical Earthquake Hazard
Assessment Map. Mitra, D., Nath, R. R., Sethi, S., Adarshi,N.
167. An Empirical Bayesian Kriging Approach for Site
Period Mapping of Santiago Basin, Chile. Mitra, D.
168. Understanding Regional Site-Amplification Effects
in the San Francisco Bay Region, California ThroughGround-Motion Analysis and Modeling of Regional
Seismic Velocity Structure. Moschetti, M. P., Aagaard, B.
T., Boyd, O. S.

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169. Development of a Seismically Induced Landslide
Susceptibility Scale for Greece for Addressing Data
Imbalance. Nath, R. R., Mitra, D.
170. National Seismic Hazard Assessment for Azerbaijan
Using New Seismic Data and Ground Motion Simulations.
Onur, T., Gok, R., Yetirmishli, G., Herrera, C., Godoladze,T., et al.
171. Data-Driven Performance Evaluation of Ground
Motion Models Applicable for Active Crustal Region in
Italy. Paramasivam, B., Kim, S., Seyhan, E.
172. Dependence of Seismic Hazard Assessment on the
Observation Time Interval: Insights From Physics-Based
Simulated Seismicity in Southeastern Spain. Pascual-

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Sánchez, E., Álvarez-Gómez, J. A., García-Mayordomo,J., Herrero-Barbero, P.
174. Student:
Improving
Geospatial
Liquefaction
Prediction Models by Optimizing Non-Liquefaction Points
Sampling: A Case Study of the 2023 Kahramanmaras,
Turkey Earthquake Sequence. Shirzadi, H., Baise, L. G.,
Moaveni, B.
175. Student: Correlating Resonance Frequency From
Hvsr With Vs30 Along the Wasatch Fault, Northern Utah,
USA. Smith, K., McBride, J., Harris, R., Worthen, B.
176. Student: Epistemic Uncertainty and Aleatoric
Variability within Probabilistic Liquefaction Analysis.
Thum, T., Rodriguez-Marek, A., Stafford, P. J., Green, R. A.

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• Abstracts, 1194

Abstracts of the Annual Meeting
The 2023 USGS National Seismic Hazard Model and
BeyondOral Session • Wednesday 1 May • 8:00 am PacificConveners: Jason M. Altekruse, U.S. Geological Survey(jaltekruse@usgs.gov); Julie A. Herrick, U.S. Geological
Survey (jherrick@usgs.gov); Mark D. Petersen, U.S.
Geological Survey (mpetersen@usgs.gov); Peter M. Powers,
U.S. Geological Survey (pmpowers@usgs.gov); Emel
Seyhan, Moody’s RMS (Emel.Seyhan@rms.com); Allison M.
Shumway, U.S. Geological Survey (ashumway@usgs.gov)
Recommendations on Best Available Science for the UnitedStates National Seismic Hazard Model
ANDERSON, J. G., University of Nevada, Reno, Nevada, USA, jga.
seismo@gmail.com; ATKINSON, G. M., Western University, London,
Canada, gatkins6@uwo.ca; BAKER, J. W., Stanford University, California,
USA, bakerjw@stanford.edu; CAMPBELL, K. W., Kenneth W Campbell
Consulting LLC, Oregon, USA, ken.w.campbell@comcast.net; DESHON,
H. R., Southern Methodist University, Texas, USA, hdeshon@mail.smu.
edu; JORDAN, T. H., University of Southern California, California, USA,tjordan@usc.edu; KELSON, K. I., U.S. Army Corps of Engineers, California,
USA, Keith.I.Kelson@usace.army.mil; SHOME, N., Moodys RMS, California,
USA, nilesh.shome@gmail.com; STEWART, J. P., University of California, Los
Angeles, California, USA, jstewart@seas.ucla.edu
The 50 state update to the 2023 United States National Seismic Hazard
Model (NSHM) is the latest in a sequence published by the U. S. Geological
Survey (USGS). The 2023 NSHM is intended for use in building codes andsimilar applications at return periods of 475 years (corresponding to exceedance probabilities of 10% in 50 years) or longer. In reviewing the model, theNSHM Program Steering Committee, consisting of the authors of this paper,
considered the characteristics of “best available science” that are applicableto the NSHM. Best available science must perform better than the previous
NSHM, and there should be no available alternatives that could improve themodels. The following are suggested characteristics of “best available science”:
A) Clear objectives B) Rigorous conceptual model C) Timely, relevant andinclusive D) Verified and reproducible E) Validated intermediate and final
models F) Replicable within uncertainties G) Peer reviewed H) Permanent
documentation
This presentation focuses on the justification for, and intent of, the above
criteria for best available science. As of December, 2023, considering these andadditional criteria, and subject to further steps to verify and document themodel for Alaska, the NSHM Steering Committee concluded that the 2023
National Seismic Hazard Model is suitable for use in building codes and similar applications at return periods of 475 years (i.e corresponding to exceedance probabilities of 10% in 50 years) or longer.
The 2023 U.S. 50-State National Seismic Hazard Model:
Overview and Implications
PETERSEN, M. D., U.S. Geological Survey, Colorado, USA, mpetersen@
usgs.gov; PROJECT TEAM, N., U.S. Geological Survey, Colorado, USA,mpetersen@usgs.gov
The U.S. National Seismic Hazard Model (NSHM) was updated in 2023 for all
50 states using new science on seismicity, fault ruptures, ground motions, andprobabilistic techniques to produce a standard of practice for public policy
and other engineering applications (defined for return periods greater than
~475 or less than ~10,000 years). Changes in 2023 time-independent seismic hazard (both increases and decreases compared to previous NSHMs) aresubstantial because the new model considers more data and updated earthquake rupture forecasts and ground motion components. In developing the2023 model, we tried to apply best available or applicable science based on
advice of co-authors, more than 50 reviewers, and hundreds of hazard scientists and end users, who attended public workshops and provided technicalinputs. The hazard assessment incorporates new catalogs, declustering algorithms, gridded seismicity models, magnitude-scaling equations, fault-based

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structural and deformation models, multi-fault earthquake rupture forecast
models, semi-empirical and simulation-based ground motion models, andsite amplification models conditioned on VS30 soil and deeper sedimentarybasin structures. Seismic hazard calculations yield hazard curves at hundredsof thousands of sites, ground motion maps, uniform hazard response spectra,
and disaggregations developed for pseudo-spectral accelerations at 21 oscillator periods and two peak parameters, Modified Mercalli Intensity, and 8 siteclasses required by building codes and other public policy applications. Tests
show the new model is consistent with past ShakeMap intensity observations.
Sensitivity and uncertainty assessments ensure resulting ground motions
are compatible with known hazard information and highlight the range andcauses of variability in ground motions. We produce several impact products
including building seismic design criteria, intensity maps, planning scenarios,and engineering risk assessments showing the potential physical and social
impacts. These applications provide a basis for assessing, planning, and mitigating the effects of future earthquakes.
The 2023 Alaska National Seismic Hazard Model
POWERS, P. M., U.S. Geological Survey, Colorado, USA, pmpowers@usgs.
gov; ALTEKRUSE, J. M., U.S. Geological Survey, Colorado, USA, jaltekruse@
usgs.gov; DEVELOPMENT TEAM, N., U.S. Geological Survey, Colorado,
USA, nshmp-support@usgs.gov
The U.S. Geological Survey (USGS) has developed a major revision to the
Alaska portion of the 2023 National Seismic Hazard Model (NSHM). Thisupdate incorporates new data and models that have been gathered and published since the last update of the Alaska NSHM in 2007. The 2023 Alaska
NSHM includes updates to both earthquake rupture forecast (ERF) andground motion model (GMM) components. The ERF includes updates tothe crustal fault inventory and considers both geologic and geodetic deformation models. The large-magnitude subduction interface model uses an
updated segmentation and structural model (based on the Slab2 geometryof the Alaska-Aleutian arc) and includes geologic, geodetic, and earthquake
catalog-derived earthquake rates. A new catalog that includes earthquakes
from 2007 to 2020 was compiled to inform the rate model for the both thecrustal and subduction gridded seismicity components. The gridded seismicity rate model considers multiple declustering and smoothing methods, andsubduction interface (small magnitude) and intraslab sources are modeled at
depths derived from Slab2. For the GMM component, the model uses the new
NGA-Subduction GMMs. For interface ruptures, the global NGA-Subduction
GMMs are used along with bias corrected versions of the models; the corrections are based on recent Alaska earthquakes to better represent groundmotions in south-central Alaska. For intraslab ruptures, the Alaska regionalized versions of the NGA-Subduction GMMs are used, and the NGA-West2
GMMs are used with crustal sources. The updated model implies significant
increases in hazard across south-central Alaska that are due to updated subduction interface rupture rates, the adoption of new GMMs, and improved
representations of ruptures in the ERF that are consistent with recent NSHMs
for the conterminous U.S. In particular, the newer GMMs considered include
higher aleatory variability (sigma), which maps into increased probabilistic
ground motions. Here we present implementation details of the 2023 Alaska
NSHM and comparisons to the prior NSHM from 2007.
Another Look at Time-Dependent Hazard and its
Implications to Seismic Design in Southeastern Alaska
WONG, I., Lettis Consultants International, California, USA, wong@lettisci.
com; LEWANDOWSKI, N., Lettis Consultants International, California, USA,lewandowski@lettisci.com; THOMAS, P., Lettis Consultants International,
California, USA, thomas@lettisci.com
Seismic design in the U.S. is based on the USGS National Seismic Hazard Maps
(NSHM) which assume time-independent (TI) hazard. For regions where thedata are robust enough, time-dependent (TD) hazard estimates should be
included because of the economic consequences of overly conservative seismic design ground motions (Wong and Thomas, 2020). Southeastern Alaska
is a region which can benefit from TD hazard estimates because of the recent
occurrence of the 1964 M 9.2 Great Alaska earthquake. Based on Shennan etal. (2014) who identified and dated six “1964”-like earthquakes, we computed
an average recurrence interval of 594 ± 162 years. A mean COV value of 0.27
was also estimated, which is a relatively low value indicating rather periodic

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behavior. Given the short time since 1964, the Brownian Passage Time model
predicts very low equivalent Poisson rates for a 50-year period. Incorporatingthese rates into a PSHA, TD hazard in Anchorage at a building-code return
period of 2,475 years is up to 48% lower than the TI hazard. In contrast to
the 2023 NSHM, TD analysis indicates the 1964 rupture is not significant
to the probabilistic seismic hazard in southeastern Alaska, with the WadatiBenioff zone being the controlling seismic source. The current seismic design
ground motions for Anchorage are based on the 2007 NSHM and are deterministically capped. The significantly increased hazard in the 2023 NSHM forsoutheastern Alaska will be challenging for the engineering community withregards to seismic design. Considering TD hazard is one approach to reduce
the seismic hazard estimates in southeastern Alaska.
USGS 2025 Puerto Rico and the U.S. Virgin Islands National
Seismic Hazard Model Update
SHUMWAY, A. M., U.S. Geological Survey, Colorado, USA, ashumway@
usgs.gov; AAGAARD, B. T., U.S. Geological Survey, Colorado, USA,baagaard@usgs.gov; ALTEKRUSE, J. M., U.S. Geological Survey, Colorado,
USA, jaltekruse@usgs.gov; BRIGGS, R. W., U.S. Geological Survey, Colorado,
USA, rbriggs@usgs.gov; FIELD, E. H., U.S. Geological Survey, Colorado,
USA, field@usgs.gov; HAYNIE, K. L., U.S. Geological Survey, Colorado, USA,khaynie@usgs.gov; HATEM, A. E., U.S. Geological Survey, Colorado, USA,ahatem@usgs.gov; HERRICK, J. A., U.S. Geological Survey, Colorado, USA,jherrick@usgs.gov; HUÉRFANO, V., University of Puerto Rico at Mayagüez,
Puerto Rico, USA, victor@prsnmail.uprm.edu; JAISWAL, K. S., U.S.
Geological Survey, Colorado, USA, kjaiswal@usgs.gov; LLENOS, A. L., U.S.
Geological Survey, Colorado, USA, allenos@usgs.gov; LÓPEZ-VENEGAS, A.
M., University of Puerto Rico at Mayagüez, Puerto Rico, USA, alberto.lopez3@
upr.edu; MARTÍNEZ-CRUZADO, J., University of Puerto Rico at Mayagüez,
Mayagüez, United Kingdom, jose.martinez44@upr.edu; MICHAEL, A. J.,
U.S. Geological Survey, California, USA, ajmichael@usgs.gov; MOSCHETTI,
M. P., U.S. Geological Survey, Colorado, USA, mmoschetti@usgs.gov;
MUELLER, C. S., U.S. Geological Survey, Colorado, USA, cmueller@usgs.gov;
PETERSEN, M. D., U.S. Geological Survey, Colorado, USA, mpetersen@usgs.
gov; POWERS, P. M., U.S. Geological Survey, Colorado, USA, pmpowers@
usgs.gov; PRATT, T. L., U.S. Geological Survey, Virginia, USA, tpratt@usgs.
gov; REZAEIAN, S., U.S. Geological Survey, Colorado, USA, srezaeian@usgs.
gov; SMITH, J. A., U.S. Geological Survey, Colorado, USA, jamesasmith@usgs.gov; THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA,jjobe@usgs.gov; VANACORE, E., University of Puerto Rico at Mayagüez,
Puerto Rico, USA, elizabeth.vanacore@upr.edu; ZENG, Y., U.S. Geological
Survey, Colorado, USA, zeng@usgs.gov
The U.S. Geological Survey is currently developing the next update of the
National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin
Islands (PRVI), with a planned release by the end of calendar year 2025. The
last update to the PRVI NSHM was in 2003, so this update will include over 20
years of updated science and engineering data, models, and methods. Updates
being considered include (1) an updated seismicity catalog based on improved
Puerto Rico Seismic Network data, (2) new declustering (space-and-time andnearest-neighbor), smoothing (fixed and adaptive), and seismicity rate models, (3) new magnitude scaling relationships, (4) updated geologic and geodetic
deformation models, (5) improved fault source models and a more complete
representation of epistemic uncertainties, (6) improved modeling of subduction zone geometries, and (7) updated ground motion models (GMMs) for
both crustal (NGA-West2 and other available Puerto Rico-specific models)and subduction (NGA-Subduction) sources, with particular attention paid towhether the site terms of the selected GMMs are appropriate for use in PRVI.
These updates follow similar efforts performed in the recent 2023 50-state
NSHM. Uncertainty and engineering impact studies will also be performed
for this update. NSHMs are community- and consensus-based models, withthe goal to incorporate the latest data, models, and methods currently available. Public workshops throughout the update process will allow the scientificcommunity to evaluate the input models and draft model, providing valuable
feedback as the model is developed and finalized.
Next Steps for USGS Earthquake Rupture Forecast
Developments
FIELD, E. H., U.S. Geological Survey, Colorado, USA, field@usgs.gov
An earthquake rupture forecast (ERF), also known as a seismic source characterization, is one of the two main modeling components used in seismic
hazard analysis (the other being a ground-motion model). This presentation provides an overview of recent, ongoing, and future ERF developments
at the United States Geological Survey (USGS). Two overarching goals, bothVolume 95•

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a manifestation of the paucity of data at large magnitudes, are a better representation of epistemic uncertainties and a greater utilization of physicsbased approaches. Recent accomplishments include a broader representationof multi-fault ruptures, including a wider range of epistemic uncertainties
associated with the degree of fault segmentation. Ongoing efforts include theaddition of time-dependencies, both in terms of elastic-rebound effects andspatiotemporal clustering (e.g., aftershocks), with the eventual goal of deploying an operational earthquake forecasting capability. Fundamental remaining
challenges include spanning a complete range of geodedic-constrained deformation models (fault slip rates and off-fault deformations) and representing sampling errors associated with off-fault gridded seismicity components(currently inferred from a single sample of historical earthquakes). Anotherchallenge is adequate representation of epistemic uncertainty in the face of
unknown correlation structures, which can be particularly impactful in portfolio risk analyses. We also aim to simplify models and operationalize implementations wherever we can, and to deploy a more continuously developed
research model. Finally, we also plan to add model valuation to our verification and validation protocols because a less scientifically correct model might
actually be more useful with respect to some hazard and risk metrics.
Earthquake Geology Contributions Across the U.S.
Geological Survey 2023 50-State National Seismic Hazard
Model
HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@usgs.gov;
BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.gov;
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; GOLD, R., U.S. Geological Survey, Colorado, USA, rgold@usgs.
gov; COLLETT, C., Oregon Department of Forestry, Oregon, USA, camille.
collett@odf.oregon.gov; BENDER, A., M., U.S. Geological Survey, Alaska,
USA, abender@usgs.gov; HAEUSSLER, P., U.S. Geological Survey, Alaska,
USA, pheuslr@usgs.gov; MCPHILLIPS, D., U.S. Geological Survey, California,
USA, dmcphillips@usgs.gov; DUROSS, C., U.S. Geological Survey, Colorado,
USA, cduross@usgs.gov; ANGSTER, S., U.S. Geological Survey, Washington,
USA, sangster@usgs.gov; REITMAN, N., U.S. Geological Survey, Colorado,
USA, nreitman@usgs.gov; SCHARER, K., U.S. Geological Survey, California,
USA, kscharer@usgs.gov; DELONG, S., U.S. Geological Survey, California,
USA, sdelong@usgs.gov; KNUDSEN, K., U.S. Geological Survey, California,
USA, kknudsen@usgs.gov; HECKER, S., U.S. Geological Survey, California,
USA, shecker@usgs.gov; WITTER, R., U.S. Geological Survey, Alaska, USA,rwitter@usgs.gov; ELLIOTT, A., U.S. Geological Survey, California, USA,ajelliott@usgs.gov; PHILIBOSIAN, B., U.S. Geological Survey, California,
USA, bphilibosian@usgs.gov; SHERROD, B. L., U.S. Geological Survey,
Washington, USA, bsherrod@usgs.gov; TREXLER, C., U.S. Geological
Survey, California, USA, ctrexler@usgs.gov; NICOVICH, S., U.S. Geological
Survey, Colorado, USA, snicovich@usgs.gov
The earthquake geology community made significant contributions to
the U.S. Geological Survey 2023 50-State National Seismic Hazard Model(NSHM). Since 2019, we worked with this community through workshops
and state geological surveys to provide the most inclusive and realistic depiction of earthquake geologic datasets used in an NSHM release. Fault section
databases were reviewed, revised, and significantly augmented across the conterminous U.S. and Alaska, increasing the number of fault sections included
nationwide from ~650 to ~1,100. Across the conterminous U.S., geologic slip
rates were cataloged for >450 study locations; activity rates were included withfault section data in Alaska. Slip rate datasets in the western U.S. were used toconstrain four unique geodetic deformation models, providing a broad rangeof possible fault deformation rates. A new geologic deformation model provided preferred slip rates and distribution for faults without field-based slip
rates across the western U.S. Over 60 paleoseismic datasets were cataloged andreinterpreted in California, along the Wasatch fault in Utah, and in the central and eastern U.S. Paleoseismic recurrence information was used as a constraint on the inversion-derived rupture rates. Following the western U.S. fault
system solution inversion, we reviewed preliminary results for tectonic andgeologic consistency. The review identified priority areas of potential future
research, including defining uncertainties of fault geometry in three dimensions; defining plausibility filters on dipping faults; placing bounds on maximum rupture length; better characterization of per-event displacements andslip distributions along rupture extents; defining paleoseismic rupture lengths
as inversion constraints; reconsidering the repeating large magnitude earthquake assumption in the central and eastern U.S.; and parameterizing connectivity between subduction interface and upper plate faults near Cascadia
and Alaska–Aleutian trenches. This submission seeks to encourage discussionof these and next avenues of earthquake geology research.

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Continued Work on a Geodetic Strain Rate and Slip Deficit
Rate Model for New Zealand
ROLLINS, C., GNS Science, Kelburn, New Zealand, c.rollins@gns.cri.nz;
WALLACE, L. M., Helmholtz Centre for Ocean Research, Kiel, Germany,
lwallace@utexas.edu; JOHNSON, K. M., Indiana University, Indiana, USA,kajjohns@indiana.edu; MAURER, J., University of Missouri Science andTechnology, Missouri, USA, maurer.jeremy@gmail.com; HAMLING, I.,
GNS Science, Lower Hutt, New Zealand, i.hamling@gns.cri.nz; WILLIAMS,
C. A., GNS Science, Lower Hutt, New Zealand, c.williams@gns.cri.nz;
GERSTENBERGER, M. C., GNS Science, Lower Hutt, New Zealand,m.gerstenberger@gns.cri.nz; VAN DISSEN, R. J., GNS Science, Lower Hutt,
New Zealand, r.vandissen@gns.cri.nz
Data-based fault slip rates are key inputs into national seismic hazard models:
they are one of several “budgets” that help constrain the likelihoods of large
earthquakes at each location. In regions featuring subduction zones, such as
Aotearoa New Zealand, there are (in one sense) three kinds of faults to worry
about: upper-plate faults, subduction interfaces, and intraslab/outer-rise faults.
Slip rates in the first two regimes can be constrained by data. The 2022 revision of the New Zealand National Seismic Hazard Model (NZ NSHM 2022)
included two alternate models for upper-plate fault slip rates, one based on
geologic data and one based on geodetic data. The geodesy-based model itself
included four alternative strain rate models and made use of a novel method
to invert surface strain rates directly for slip deficit rates in a way that obviates the need to connect all of the faults as block boundaries. The NZ NSHM
2022 also included two geodesy-based models of coupling on the HikurangiKermadec subduction zone (respectively featuring full locking and no locking
at the offshore subduction trench). We are now working on improving thismodel by adding new data in slow-deforming regions (Auckland/Northland
and Southland/Otago), vertical deformation rates, InSAR data (where possible), and improvements to methods (e.g. accounting for uncertainty in fault
geometry, and the trade-offs between subduction and upper-plate coupling interms of their effect on the velocity field).
Correlation of Epistemic Uncertainties in Seismic Hazard
Models: An NSHM23 Case Study for Western U.S. Faults
MILNER, K. R., Southern California Earthquake Center, California, USA,
kmilner@usc.edu
Uncertainties in probabilistic seismic hazard analysis are typically represented
using epistemic logic trees where each branching level represents a modelingchoice or alternative dataset used. Ideally, each branch of the logic tree represents a plausible realization of reality. In practice, certain branches may not bereasonable when applied uniformly and systemwide, even if they are reasonable for individual faults or in particular sub-regions of a model.
One such example is fault connectivity. In the 2023 U.S. National Seismic
Hazard Model (NSHM23), connectivity of western U.S. faults was modeledwith 5 segmentation branches ranging from fully segmented to fully unsegmented. Those end-member branches are unlikely to be correct at a regional
scale, even if they are the most correct for some faults. Fault-specific b-values
are another example; NSHM23 includes end-member models of b=0 and b=1
that are applied uniformly to all faults on their respective branches. We present an alternative model where we randomly sample from the b-value andsegmentation branches for individual faults; that model decreases epistemic
uncertainties in hazard calculations, indicating that NSHM23 might overstate
uncertainties. Additionally, rates of large (M>8) ruptures are lower for the
randomly sampled alternative model.
Deformation model slip rates are another important uncertainty. Ideally,
deformation modelers would provide many samples of realistic deformation
models that map out the solution space of viable models while maintaining
kinematic consistency. Lacking that, NSHM23 chose to over-fit slip rates.
We present an alternative model where deformation model realizations are
randomly sampled from their uncertainties using a reasonable covariancestructure. We find that using these randomly sampled deformation models
increases epistemic uncertainties relative to NSHM23.
We will describe both of these alternative uncertainty models and theirimpact on standard hazard metrics (individually and together) relative to the
published NSHM23 model.
Enhancing Decision-Making Stability in Model Updates
Through Explicit Consideration of Epistemic Uncertainty inSeismic Hazard and Risk Assessments
LEE, Y., ImageCat, California, USA, yajielee@yahoo.com

ard and risk, derived from the epistemic uncertainty distribution, serves as apivotal basis for various design, hazard and risk mitigation, and risk financing
applications. While the fundamental natural processes remain unchanged, thescientific models representing them continuously evolve, leading to fluctuations, akin to a “see-saw” effect, in estimated mean hazard and risk with eachcycle of model updates. This effect, at times substantial, can wield significant
influence over critical financial decisions and public policies, presenting practical and political challenges.
The current NSHM retains a considerable level of epistemic uncertainty.
A growing consensus underscores the importance of transparently communicating epistemic uncertainty in the NSHM to inform user expectations.
However, there is a notable absence of clarity and guidance on effectively
incorporating this uncertainty into decision-making, particularly duringmodel updates.
This study aims to bridge this gap by exploring two alternative methods
that explicitly consider epistemic uncertainty within the NSHM for decision
making. The goal is to alleviate the potential “see-saw” effect in mean hazard
and risk estimates resulting from model updates and enhance decision-making stability amid the ongoing evolution of scientific models.
Subduction Ground Motion Models for Cascadia in the2023 USGS National Seismic Hazard Model
REZAEIAN, S., U.S. Geological Survey, Colorado, USA, srezaeian@usgs.gov;
POWERS, P. M., U.S. Geological Survey, Colorado, USA, pmpowers@usgs.
gov; ALTEKRUSE, J. M., U.S. Geological Survey, Colorado, USA, jaltekruse@
usgs.gov; AHDI, S. K., AECOM, California, USA, sean.ahdi@aecom.com;
PETERSEN, M. D., U.S. Geological Survey, Colorado, USA, mpetersen@usgs.
gov; SHUMWAY, A., U.S. Geological Survey, Colorado, USA, ashumway@
usgs.gov; FRANKEL, A., U.S. Geological Survey, Washington, USA, afrankel@
usgs.gov; WIRTH, E., U.S. Geological Survey, Washington, USA, ewirth@usgs.gov; SMITH, J., U.S. Geological Survey, Colorado, USA, jamesasmith@usgs.gov; MOSCHETTI, M., U.S. Geological Survey, Colorado, USA,mmoschetti@usgs.gov; WITHERS, K., U.S. Geological Survey, Colorado,
USA, kwithers@usgs.gov; HERRICK, J. A., U.S. Geological Survey, Colorado,
USA, jherrick@usgs.gov
The U.S. Geological Survey National Seismic Hazard Models (NSHMs) areused to calculate earthquake ground-shaking intensities for design and retrofit
of structures in the United States. The most recent 2014 and 2018 versionsof the NSHM for the conterminous U.S. included major updates to groundmotion models (GMMs) for active and stable crustal tectonic settings; however, the subduction zone GMMs were largely unchanged. With recent development of the Next Generation Attenuation Subduction (NGA-Sub) GMMs,
as well as recent progress in utilization of “M9” Cascadia earthquake simulations, we now have access to improved models of ground shaking in U.S.
subduction zones and the Seattle Basin. The new NGA-Sub GMMs support“multi-period response spectra” calculations by providing median and variability models that can be used for periods up to 10 s and for eight site classes.
They provide global models as well as regional terms specific to Cascadia andterms that account for deep sedimentary basin effects. This study focuses on
updates to subduction GMMs for the Cascadia portion of the 2023 NSHM
and compares them to the GMMs of previous NSHMs. Individual subduction
GMMs, their weighted combinations, and their impact on hazard relative tothe 2018 NSHM are discussed. Logic trees are described that include three ofthe new NGA-Sub GMMs and retain two older models to represent epistemic
uncertainty in both the median and standard deviation of ground-shaking
intensities at all periods of interest. Epistemic uncertainty is further represented by a three-point logic tree for a given NGA-Sub median model. Finally,in the Seattle region, basin amplification factors are adjusted at long periods
based on state-of-the-art M9 Cascadia earthquake simulations. Overall, theGMM changes increase the mean hazard values at shorter periods and shortsource-to-site distances, but decrease them otherwise, relative to the 2018
NSHM. On deep sedimentary basins, the new models cause hazard decreases
for longer periods in the Puget Lowland but increases for shorter periods
within the Seattle Basin relative to 2018 NSHM.
Ground-Motion Characterization of Puerto Rico and the
U.S. Virgin Islands for the 2025 Update of the USGS
National Seismic Hazard ModelAAGAARD, B. T., U.S. Geological Survey, Colorado, USA, baagaard@usgs.
gov; SMITH, J. A., U.S. Geological Survey, Colorado, USA, jamesasmith@usgs.gov; MOSCHETTI, M. P., U.S. Geological Survey, Colorado, USA,mmoschetti@usgs.gov; STEPHENSON, W. J., U.S. Geological Survey,

Significant efforts have been dedicated to characterizing the epistemic uncertainty within the National Seismic Hazard Model (NSHM). The “mean” haz-

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Colorado, USA, wstephens@usgs.gov; AHDI, S. K., AECOM, California,
USA, sahdi@g.ucla.edu
We assess ground-motion models (GMMs) developed for shallow crustal
faulting or subduction zones for application in Puerto Rico and the U.S.
Virgin Islands as part of the 2025 update of the U.S. Geological Survey (USGS)
National Seismic Hazard Model. We present preliminary analysis of GMM
performance, including for site response, using linear mixed-effects regression. For our analysis we used the USGS software gmprocess to compile adataset with over 8000 ground-motion records since 2006 from 888 earthquakes with magnitudes ranging from 4.0 to 6.5 and depths reaching up to 200
km; more than half of the ground motions were recorded since January 2020.
We use the USGS SeismoTectonic Regime Earthquake Calculator (STREC)
and the USGS Slab-2 subduction zone geometry model to associate groundmotions with either subduction zone or shallow crustal earthquakes. We
compute within-event residuals using linear mixed-effects regressions relative
to Next Generation Attenuation West2 (NGA-West2) and East (NGA-East)
GMMs for shallow crustal earthquakes and NGA Subduction (NGA-Sub)
GMMs for subduction zone earthquakes. We consider both measured andproxy values for the time-averaged shear wave speed in the top 30 m (Vs30)
when computing site terms for the GMMs. For each GMM, we examine trends
with predictive variables, such as earthquake magnitude and rupture distance,
and the overall bias values. Future work will likely leverage Sammon mapping
to provide a more quantitative basis for assigning weights to the epistemic
uncertainty logic tree for GMMs.
Development of Ground Motion Models in Central andEastern United States for Use in the Coastal Plain Using
Sediment Thickness
AKHANI, M., University of Memphis, Tennessee, USA, mkhnsnjn@memphis.
edu; DAVATGARI TAFRESHI, M., University of Memphis, Tennessee, USA,
mdvtgrtf@memphis.edu; PEZESHK, S., University of Memphis, Tennessee,
USA, spezeshk@memphis.edu
This study focuses on developing ground-motion models, specifically Pezeshk
et al. (2018), initially derived for areas outside the Coastal Plain, to enhancetheir applicability within Coastal Plain regions. The adjustment factors developed are intricately linked to sedimental thickness and rupture distancewithin the Coastal Plain. Utilizing recently established sediment thickness
contour maps by Boyd et al. (2023), our approach incorporates an integrated
dataset that combines the NGA-East original dataset (Goulet et al., 2014), datafrom Chapman and Guo (2021) and a newly compiled and verified dataset byThompson et al. (2023). Residuals are computed by contrasting the logarithms
of observed data against those predicted by Pezeshk et al. (2018) groundmotion models while considering the site amplification model of Stewart etal. (2020) and employing three datasets. Through a mixed-effects regression,
we conduct residual analyses to partition total residuals into components
attributed to between-events and within-event residuals. We tailor an equation correlating within-event residuals and sediment depth and rupture distance. The outcomes reveal that, for stations within the Coastal Plain region,
the proposed correction significantly eliminates residual trends (with respect
to VS30, sediment depth, and rupture distance) across most periods. Thesefindings have practical implications for seismic hazard and risk analyses atsites within the Coastal Plain, emphasizing the importance of incorporating
sediment thickness considerations for more accurate predictions
New Ground-Motion Model With Long-Period Non-Ergodic
Path Effects From the Cybershake Simulations in theSouthern California Region
SUNG, C., University of California, Berkeley, California, USA, karensung@berkeley.edu; ABRAHAMSON, N. A., University of California, Berkeley,
USA, abrahamson@berkeley.edu; LACOUR, M., University of California,
Berkeley, California, USA, maxlacour@berkeley.edu; MENG, X., Statewide
California Earthquake Center, California, USA, xiaofenm@usc.edu
Sung et al. (2023) developed a methodology to integrate the 3-D path effects
in CyberShake simulations (Graves et al., 2011) into the Abrahamson et al.
(2014) (ASK14) ground-motion model (GMM), creating a non-ergodic
GMM that captured site-specific path effects caused by the 3-D crustal modelusing the varying coefficient model (VCM), but the example application onlyused a subset of 600 scenarios from the v15.4 CyberShake simulations andonly modeled the 3-second response spectral values. In this study, we utilized
a much larger dataset from the v15.4 CyberShake simulations, which includes
565,000 events and 117 million seismograms at 336 stations for spectral periods of 2, 3, 4, 5, 7.5, and 10 seconds. Additionally, we applied a new form of
the spatial correlation (Lacour et al., 2024) that considers the azimuths dif-Volume 95•

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ferences between ray paths that better reflects the spatial correlation in the
CyberShake data. For most ray paths, the larger data set shows a strong correlation between the path effects for moderate and large earthquakes withthe same closest point to a site (correlation coefficient of 0.7 to 0.85), indicating that the path effects of large-magnitude earthquakes can be approximated by using the path effects of smaller earthquakes. The modified ASK14
GMM with CyberShake site and path effects at periods of 2-10 s, and it has
reduced aleatory variability. Compared to an ergodic GMM representation of
the CyberShake data, for the period range of 2-10 s, the total standard deviation is reduced from 0.565 to 0.636 for the ergodic GMM to 0.435 to 0. 544
for the non-ergodic GMM. An additional advantage of using the larger data
set is that it reduces the potential for overfitting as compared to the previous
subset. We present examples of hazards calculation for T = 3 s and T = 5 s forthe ergodic and non-ergodic GMMs and for the hazard computed using the
CyberShake data directly. The resulting modified ASK14 GMM can effectively
capture the path effects observed in the CyberShake simulations, including
both the median and the aleatory standard deviation.
An Updated Version of the New Empirical Source-Scaling
Laws for Crustal Earthquakes Incorporating Fault Dip andSeismogenic-Thickness Effects
HUANG, J., National Center for Research on Earthquake Engineering, Taipei,
Taiwan, jyhuang@narlabs.org.tw; ABRAHAMSON, N. A., University ofCalifornia, Berkeley, , USA, abrahamson@berkeley.edu; SUNG, C., Universityof California, Berkeley, , USA, karensung@berkeley.edu; CHAO, S., National
Center for Research on Earthquake Engineering, Taipei, Taiwan, shchao@narlabs.org.tw
New global source-scaling relations for the aspect ratio and rupture area for
crustal earthquakes, including the width-limited effect and a possible free-surface effect, are derived using a global data set of finite-fault rupture models. In
contrast to the commonly used scaling relations between moment magnitude(M), fault length (L), width (W), and area, we built self-consistent scaling relations by relating M to the aspect ratio (L/W) and to the fault area to model thechange in the aspect ratio once the rupture width reaches the down-dip width
limit of the fault. The width-limited effect for large-magnitude earthquakes
depends on the fault dip and a regional term for the seismogenic thickness.
The magnitude scaling of the aspect ratio includes a break in the magnitudescaling that is dip-angle-dependent. This dip-angle-dependent magnitudescaling in the magnitude-area relation is thereby modeled by a trilinear relation incorporating a dip-related transition range. The effect of the free surface
was observed using a normalized depth term and parameterizing the sourceby the depth of the top of the fault rupture; it is more apparent in the area scaling relation. The scaling differences are related to the fault geometry, not therake angle, as commonly assumed. Finally, the corresponding L and W scaling
relations obtained by converting the area and aspect-ratio models to L and W
models showed good agreement with the previous regional scaling laws on
average but provided better fault-specific application due to the inclusion of
fault-specific dip angles and seismogenic thicknesses.

The 2023 USGS National Seismic Hazard Model and
Beyond [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Jason M. Altekruse, U.S. Geological Survey(jaltekruse@usgs.gov); Julie A. Herrick, U.S. Geological
Survey (jherrick@usgs.gov); Mark D. Petersen, U.S.
Geological Survey (mpetersen@usgs.gov); Peter M. Powers,
U.S. Geological Survey (pmpowers@usgs.gov); Emel
Seyhan, Moody’s RMS (Emel.Seyhan@rms.com); Allison M.
Shumway, U.S. Geological Survey (ashumway@usgs.gov)
poster 133
The 2023 Alaska National Seismic Hazard Model: Hazard
Implications
ALTEKRUSE, J. M., U.S. Geological Survey, Colorado, USA, jaltekruse@usgs.
gov; POWERS, P. M., U.S. Geological Survey, Colorado, USA, pmpowers@
usgs.gov
The 2023 U.S. Geological Survey (USGS) National Seismic Hazard Model(NSHM) for the State of Alaska incorporates more than fifteen years ofSeismological Research Letters

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new data in updates to the earthquake rupture forecast (ERF) and groundmotion model (GMM) components of the model. These changes result inlarge increases in predicted ground motions compared to the previous model
published in 2007. The ERF incorporates an expanded crustal fault inventory,
updated geologic and geodetic rate models, and several new source zones in
key areas (e.g., Cook Inlet and the Coast Shear Zone). Crustal and subduction gridded seismicity models, based on an updated earthquake catalog that
includes events through 2020, incorporate multiple catalog declustering andspatial smoothing methods. The Alaska-Aleutian arc geometry from Slab 2
is used to model depths for intraslab and small-magnitude (<M7) interface
sources as well as the large-magnitude subduction interface geometry. The
large-magnitude interface model also uses updated megathrust segmentation
models and multiple earthquake rate models. The 2023 NSHM for Alaska uses
the NGA-West 2 GMMs for crustal sources, NGA-Subduction global models
for subduction interface sources, and NGA-Subduction Alaska regional models for subduction intraslab sources. Details of the updates to the ERF and
GMM components have been presented elsewhere; here we focus on how key
model updates lead to significant increases of more than a factor of two, insome areas, in earthquake hazard across south-central Alaska. For example,
the updated interface rupture rates and the adoption of NGA-Subduction
GMMs both lead to higher hazard across much of the Alaska-Aleutian arc.
We show stepwise ratio and difference maps that illustrate the relative contributions to changes in hazard arising from each update to the ERF and GMM
model components.
poster 134
Implementing Rupture Directivity Effects Into PSHABAYLESS, J., AECOM, California, USA, jeff.bayless@aecom.com;
ABRAHAMSON, N. A., University of California, Berkeley, California, USA,abrahamson@berkeley.edu
The effects of rupture directivity on near-fault ground motions are known tobe significant and should be included to accurately estimate the hazard, especially for long-period ground motions (Abrahamson, 2000). However, theseeffects are not explicitly accounted for in typical ground motions models, andtherefore not in typical probabilistic seismic hazard analyses (PSHAs) because
substantial confusion exists in practice about which directivity models to use
and how to apply them to the median and aleatory variability of GMMs, especially to complex multi-segment rupture models (Donahue et al., 2019). In
the response spectral approach, which we adopt, rupture directivity effects
are considered by including adjustment factors to the elastic acceleration
response spectrum at 5% damping. This approach lends itself readily to inclusion into PSHA (Rodriguez-Marek and Cofer, 2009).
This work describes an update to our 2020 rupture directivity model(Bayless et al., 2020), including formalized instructions for adjustments tothe median and aleatory variability of the ground motion model to which itis applied. Additionally, we provide guidance on implementation, including
deterministic and probabilistic applications, and methods for modeling hypocenter locations and multi-segment ruptures. The result is a comprehensivemodel suitable for use in future PSHAs, including those performed as partof the USGS National Seismic Hazard Model. The model applies to strikeslip earthquakes only. A future update will address directivity effects for otherstyles of faulting.
poster 135
Conterminous U.S. Site Parameter Maps for Ground
Motion Models
BOYD, O. S., U.S. Geological Survey, Colorado, USA, olboyd@usgs.gov;
SMITH, J. A., U.S. Geological Survey, Colorado, USA, jamesasmith@usgs.gov;
MOSCHETTI, M. P., U.S. Geological Survey, Colorado, USA, mmoschetti@
usgs.gov
The amplitude of earthquake ground motions depends on parameters related
to the source (e.g., magnitude and stress drop), path (e.g., geometric spreadingand path attenuation), and site. The site component has typically been characterized in terms of VS30, the time-averaged shear-wave velocity to 30-meters
depth and in some cases, Z1.0 or Z2.5, the depths to a shear-wave velocity of 1.0
and 2.5 km/s, respectively. Other parameters have been proposed including
1) a site’s fundamental period at which there is a peak in site amplification,2) k0, which represents the site’s scattering and anelastic attenuation, and 3)
sediment thickness, the last of which is being modeled in the Atlantic and Gulf
Coastal Plains for the 2023 update of the U.S. National Seismic Hazard Model.
Application of these parameters and the concomitant improvement in hazard assessments is limited to where these models are available. Whereas there
are global and regional models for VS30, models of Z1.0, Z2.5, and sediment

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thickness are spatially restricted. With the completion of the USGS National
Crustal Model for Seismic Hazard Studies (NCM), conterminous U.S. modelsof VS30, Z1.0, Z2.5, and sediment thickness are available, in addition to otherpotentially explanatory site parameters. In this study, we derive conterminous
U.S. site-parameter maps from the NCM that can be used in ground motion
model development and application. Site parameters considered include VS30,
Z1.0, Z2.5, ZX derived from time-averaged velocity profiles, sediment thickness,sediment travel time, fundamental period, and k0. In this preliminary study,
we compare these maps to existing measurements and models and present
correlations between site parameters and ground motion residuals in thewestern U.S.
poster 136
Recurrence Model for Puerto Rico Subduction Zone
Interface and Muertos Thrust Belt Earthquakes
BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.gov; TENBRINK, U., U.S. Geological Survey, Massachusetts, USA, utenbrink@usgs.
gov; THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@
usgs.gov; PRATT, T., U.S. Geological Survey, Virginia, USA, tpratt@usgs.gov;
HAYNIE, K., U.S. Geological Survey, Colorado, USA, khaynie@usgs.gov;
HERRICK, J. A., U.S. Geological Survey, Colorado, USA, jherrick@usgs.gov
In preparation for the 2025 update to the Puerto Rico and U.S. Virgin Islands
portion of the USGS National Seismic Hazard Model, we compiled geologic,
geodetic, geophysical, and seismologic observations to characterize earthquake recurrence along the Puerto Rico subduction zone (PRSZ) and the
Muertos thrust belt. Limited historical seismicity suggests the PRSZ is active
and capable of hosting Mw 8+ ruptures. Previously reported geologic observations document precolonial (pre-1492 C.E.) inundation of Anegada, consistent with either a subduction interface event or an outer rise event. Because
geologic observations to constrain subduction interface rupture recurrence
are scant, we estimate recurrence from geodetically determined coupling andconvergence rates. Eight subduction interface fault sections are defined on thebasis of structural and geometric discontinuities and coupling is generalizedalong uniform patches, ranging from 10 to 20%. Recurrence is inferred frommoment accumulation rates with magnitudes derived from scaling relations.
This approach yields preliminary recurrence intervals of 2900-5800 years forMw 8.6-8.8 ruptures along the PRSZ for a set of prescribed interface events. A
key question is whether highly oblique convergence along the PRSZ is partitioned into only trench-normal interface rupture, or if nearly trench-parallel
rupture occurs on the dipping interface (e.g., Sagami Trough-style). Historicalseismicity on the subduction interface is consistent with highly oblique rupture on the interface and we retain that possibility in the model. Based onseismicity, geodesy, and limited geophysical data, we model three sections
along the Muertos thrust belt as 50% coupled with their down-dip extents
near the southern coast of Puerto Rico. Using a methodology similar to the
PRSZ yields earthquakes of Mw 7.8-8.5 with recurrence intervals of 770-9200
years on the Muertos thrust belt. Outstanding issues include constraining
recurrence of outer rise events, testing the recurrence model against limited
geologic and seismologic data, and incorporation of considerable epistemic
uncertainty into the model.
poster 137
Seismic Hazard, Lithosphere Hydration, and DoubleVerging Structure of the Puerto Rico Subduction Zone: A
Seismic Reflection and Refraction Perspective
CANALES, J., Woods Hole Oceanographic Institution, Massachusetts, USA,jpcanales@whoi.edu; HAN, S., University of Texas at Austin, Texas, USA,
han@ig.utexas.edu; TEN BRINK, U., U.S. Geological Survey, Massachusetts,
USA, utenbrink@usgs.gov; VANACORE, E., University of Puerto Rico at
Mayagüez, Puerto Rico, USA, elizabeth.vanacore@upr.edu; HARMON,
N., Woods Hole Oceanographic Institution, Massachusetts, USA, nicholas.
harmon@whoi.edu; JIAN, H., Woods Hole Oceanographic Institution,
Massachusetts, USA, hjian@whoi.edu; BABENDREIER, C., University ofTexas at Austin, Texas, USA, babendreiercharles@utexas.edu; MOSER, L.,
Woods Hole Oceanographic Institution, Massachusetts, USA, lmoser@
whoi.edu; BALDWIN, W., U.S. Geological Survey, Massachusetts, USA,wbaldwin@usgs.gov; FOSTER, D., U.S. Geological Survey, Massachusetts,
USA, dfoster@usgs.gov; HELLER, S., U.S. Geological Survey, Colorado, USA,sheller@usgs.gov; GRANJA-BRUÑA, J., Universidad Complutense, Madrid,
Spain, jlgranja@ucm.es; SOKOLKOVA, E., GEOMAR Helmholtz Centre of
Ocean Research, Kiel, Germany, esokolkova@geomar.de; MANN, M., Brown
University, Rhode Island, USA, michael.mann@whoi.edu; GREVEMEYER,

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I., GEOMAR Helmholtz Centre of Ocean Research, Kiel, Germany,igrevemeyer@geomar.de
The Puerto Rico Trench (PRT) is an oblique subduction zone where Atlantic
lithosphere subducts under the Caribbean plate. The PRT poses major earthquake and tsunami hazards in the Caribbean and the US East Coast. In Fall
2023 we conducted the NSF-supported PRISTINA experiment (Puerto Rico
Subduction Tectonics Seismic Investigation), a controlled-source seismic
survey across the PRT, its outer rise, and across the island of Puerto Ricousing the RV Langseth(cruises MGL2315 and MGL2316). PRISTINA consists of: (1) 2140 km of 2D ultra-long-offset (13.65 km) multichannel seismic reflection data along 8 primary profiles trending parallel to, and perpendicular to the main axis of the PRT; (2) an amphibious island-crossing
430-km-long N-S wide-angle profile sampling the incoming plate, PRT,
Puerto Rico, Muertos thrust belt and Caribbean plate instrumented with49 short-period, 3-component nodal land stations and with short-period,
3-component geophone+hydrophone ocean bottom seismometers (OBS)
successfully deployed at 46 stations: 34 stations using OBS from the US OBSInstrument Center (OBSIC) and 12 stations with ultra-deep OBS (up to 8000m) from GEOMAR; (3) a 220-km-long NE-SW wide-angle profile crossing
the PRT north of the British Virgin Islands instrumented with 17 OBSIC and
7 ultra-deep OBS; (4) Four wide-angle fan profiles over the incoming plate;(5) Underway multibeam bathymetry, gravity and magnetics. In addition, a
deployment of 6 temporary broadband in conjunction with permanent PRSN
stations through central PR is currently collecting data. These datasets will be
used to address the following scientific questions: the shallow geometry of the
subducting slab and its lateral continuity along the PRT; the degree and spatial
extent of hydration of the Atlantic lithosphere entering the PRT; the nature ofan oceanic bivergent thrust system. In this presentation we will inform theinterested community about PRISTINA objectives, datasets and expected
derived models, which we anticipate will provide new critical constraints to
inform the 2025 Puerto Rico and U.S. Virgin Islands USGS National Seismic
Hazard Model.
poster 138
Deploying the USGS National Seismic Hazard Models
CLAYTON, B., U.S. Geological Survey, Colorado, USA, bclayton@usgs.gov;
POWERS, P., U.S. Geological Survey, Colorado, USA, pmpowers@usgs.gov
We describe how the U.S. Geological Survey (USGS) develops and deploys the
National Seismic Hazard Models (NSHMs) and related products to end users.
The USGS NSHMS are developed using Java and use JSON, GeoJSON, andCSV files to describe model elements. The base codes and model files are used
to perform time-consuming large scale (grid of multiple points) hazard calculations as well as on-demand calculations for end users via web service andweb application wrappers. In the past, we deployed multiple models to a single
on-premises server but quickly faced computing limitations as the numberof models grew. To address this, we now deploy each NSHM to independent Amazon Web Services (AWS) servers that are matched to the computerequirements of each model. Each server provides identical web service accessto the model it hosts, and the services for the NSHMs are brought together ina unified interface for end-users via the USGS Earthquake Hazard Toolbox(https://earthquake.usgs.gov/nshmp/). Behind the scenes, we use GitLab continuous integration and continuous delivery pipelines for automated deployments and use the AWS Cloud Development Kit (CDK) to write infrastructure as code using TypeScript to generate CloudFormation templates. The
NSHM web service deployments use the Amazon Elastic Compute Cloud,and the USGS Earthquake Hazard Toolbox is deployed via the Amazon
Elastic Container Service. This infrastructure allows us to automate deployments to development, staging, and production environments that include
pulling version-controlled resources from multiple repositories and running
quality assurance tests. This presentation describes NSHM infrastructure, theresources available to end users, and the process of moving a new NSHM fromdevelopment through to publication and deployment. We also highlight theefficiencies gained through moving to the cloud and describe the benefits ofusing the CDK for NSHM deployments.
poster 139
USGS Earthquake Hazard Toolbox
GIROT, D. L., U.S. Geological Survey, Colorado, USA, dgirot@usgs.gov;
POWERS, P. M., U.S. Geological Survey, Colorado, USA, pmpowers@usgs.
gov; CLAYTON, B., U.S. Geological Survey, Colorado, USA, bclayton@usgs.
gov
The U.S. Geological Survey (USGS) earthquake hazards website provides
web services and applications that give users access to the National Seismic

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Hazard Models (NSHMs) for the United States and its territories. The USGS
Earthquake Hazard Toolbox (https://earthquake.usgs.gov/nshmp) web application is the main entry point for end-users to calculate hazard and to query
data for various USGS NSHMs. The tool currently supports the 2018 and 2023
conterminous U.S. NSHMs, the 2021 NSHM for the State of Hawaii, and the2023 NSHM for the State of Alaska with additional older NSHMs to be added
soon. One advantage of recent improvements to the USGS hazard modelingcodebase is that models under development can be deployed to the tool forearlier end-user evaluation and adoption. In addition to providing web applications for hazard calculation and disaggregation, the NSHM hazard tool also
provides model analysis applications. Applications for working with groundmotion models include the response spectrum plotter and ground motion
versus distance or magnitude plotters. Applications for working with source
models, or earthquake rupture forecasts, include a magnitude-frequency distribution plotter and a source data mapping application. Each application isbacked by web services that permit the underlying calculations and data to
be easily accessed via third-party applications (e.g., MATLAB, Python, R).
Moreover, each application provides export options to save any plot data in
tabular form and plots as static images. Here we provide an overview of thevarious USGS Earthquake Hazard Toolbox applications, as well as examples of
how to leverage the suite of underlying web services.
poster 140
The 2023 Alaska National Seismic Hazard Model: Inputs
and Implications
HERRICK, J. A., U.S. Geological Survey, Colorado, USA, jherrick@usgs.gov;
RUKSTALES, K. S., U.S. Geological Survey, Colorado, USA, rukstales@usgs.
gov; ALTEKRUSE, J. M., U.S. Geological Survey, Colorado, USA, jaltekruse@
usgs.gov; POWERS, P. M., U.S. Geological Survey, Colorado, USA,pmpowers@usgs.gov; TEAM, N., U.S. Geological Survey, , USA, nshmpsupport@usgs.gov
The National Seismic Hazard Model (NSHM) Project of the U.S. Geological
Survey is tasked with modeling the seismic hazard from potentially damaging
earthquakes for the 50 U.S. states and its territories. The last comprehensive
assessment for Alaska was published in 2007, and a significant update wasreleased in late 2023. The 2023 Alaska NSHM considers two main input components: an earthquake rupture forecast (ERF) and ground motion model.
The 2023 ERF includes over 80 new faults and a refined treatment of the
subduction zone, an updated earthquake catalog and new declustering andsmoothing algorithms for background seismicity, new geodetic deformation
models, and improved modeling of subduction zone interface and intraslab
geometries using the SLAB2 model. Relative to the previous model of seismic
hazard for Alaska, the new model results (ERF and ground motion) in an
overall increase in hazard across the state. We present the ERF model components in a geospatial format and provide assessments of where damaging
shaking is likely to occur. The extent of damaging shaking is represented interms of Modified Mercalli Intensity (MMI), a measure of earthquake effects
that describes the strength of earthquake shaking inferred from intensity
observations. Test sites (Anchorage, Fairbanks, Juneau, Nome, Prudhoe Bay,and Seward) were reviewed to identify sources of change in hazard, and we
describe and represent those locations with their contributing factors in thispresentation. Relative change from the 2007 model is presented to highlight
where the hazard (or damaging shaking) has increased or decreased.
poster 141
A New Seismic Reflection Study for Southwestern Puerto
Rico Fault Characterization
JUSTINIANO, C., University of Puerto Rico at Mayagüez, Puerto Rico,
USA, chris.justiniano@upr.edu; VANACORE, E., University of Puerto Rico
at Mayagüez, Puerto Rico, USA, elizabeth.vanacore@upr.edu; PRATT, T., U.S.
Geological Survey, Virginia, USA, tpratt@usgs.gov; LOPEZ VENEGAS, A.,
University of Puerto Rico at Mayagüez, Puerto Rico, USA, alberto.lopez3@
upr.eduSouthwestern Puerto Rico (SWPR) seismic activity received significant attention after the 2020 earthquake sequence. All previous research suggest thatseismicity propagated in the onshore area where it was found the presence
and interaction of left-lateral strike slip and normal faults. The sequence suggests a diffuse zone of active offshore faulting at the western side driven bycoupling at the northern boundary of the Caribbean plate. Most of the previous work in the area was conducted through offshore seismic reflection surveys, leaving behind significant gaps to understand onshore faults. Strike, dip,
and depth of fault planes are critical for comprehensively characterizing fault
structures along Puerto Rico’s tectonic boundaries for future hazard assessments. How can these enhanced descriptions of onshore faults help assess the

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overall tectonic extent of Puerto Rico-Virgin Islands block which may include
a boundary in SWPR associated with observed seismic activity? We present a geophysical approach to produce a new onshore fault characterization
qualitatively and quantitatively in Lajas Valley, SWPR, including the Punta
Montalva Fault. An initial phase of data acquisition has been completed using
a 2D-channel seismic system supplemented with nodal recorders. Seismic
data processing and data analysis are being carried out using the Seismic Unix
processing system. Preliminary results show excellent imaging of several faults
beneath the Lajas Valley, indicating potential for understanding the tectonics
of this important area.
poster 142
Gridded Seismicity Models for the 2025 USGS National
Seismic Hazard Model for Puerto Rico and the U.S. Virgin
Islands
LLENOS, A. L., U.S. Geological Survey, Colorado, USA, allenos@usgs.gov;
MICHAEL, A. J., U.S. Geological Survey, California, USA, ajmichael@usgs.
gov; SHUMWAY, A. M., U.S. Geological Survey, Colorado, USA, ashumway@
usgs.gov; HAYNIE, K. L., U.S. Geological Survey, Colorado, USA, khaynie@
usgs.gov
Gridded (or background) seismicity models are a critical component of probabilistic seismic hazard assessments, accounting for off-fault and smaller magnitude earthquakes. They are typically developed by declustering and spatiallysmoothing an earthquake catalog to estimate a long-term seismicity rate thatcan be used to forecast future earthquakes. Here, we present new gridded seismicity models for use in the 2025 National Seismic Hazard Model (NSHM)
for Puerto Rico and the U.S. Virgin Islands (PRVI). The previous PRVI NSHM
was released in 2003, and so our new models incorporate updates to bothdata and methodology. We utilize an updated earthquake catalog based on
improved Puerto Rico Seismic Network data with newly characterized completeness epochs. The catalog is divided into crustal, subduction interface,
and intraslab seismicity using new methods and an updated subduction zone
geometry. We consider three declustering methods: Gardner and Knopoff(BSSA, 1974; also used in the 2003 model), Reasenberg (JGR, 1985) and thenearest-neighbor method of Zaliapin and Ben-Zion (JGR, 2020). To spatiallysmooth the catalogs, we employ two-dimensional Gaussian kernels of either
fixed or adaptive (variable) bandwidth (Frankel, SRL, 1995; Helmstetter et al.,SRL, 2007; Moschetti, BSSA, 2015). The spatial probability density functions
that result from declustering and smoothing are later combined with a rate
model developed using the new methodology applied to the 2023 U.S. NSHM
50-state update (Petersen et al., Earthquake Spectra, 2023), which improves
representation of epistemic uncertainty relative to the 2003 model. We present preliminary PRVI gridded seismicity models and examine how they are
impacted by the ongoing and extraordinarily active Southwest Puerto Ricosequence.
poster 143
A Seismological Method for Estimating the Long-Period
Transition Period Tl in the Seismic Building CodePEZESHK, S., University of Memphis, Tennessee, USA, spezeshk@
memphis.edu; ASSADOLLAHI, C., University of Memphis, Tennessee, USA,
cmmore11@memphis.edu
The design response spectrum in the ASCE 7 Standard has undergone numerous changes in recent years. Despite these updates, one crucial parameter, thelong-period transition period parameter (TL), has remained unchanged since
its inception in FEMA 450-1/2003. TL represents the corner period signifying
the shift from constant velocity to constant displacement segments within thedesign response spectrum. This parameter holds particular significance forstructures with longer periods, like high-rise buildings and bridges. Presently,
the estimation of TL utilized in engineering design standards is primarily basedon a correlation between modal magnitude (Mw) and TL, overlooking factors
such as stress drop (Δσ) or crustal velocity in the source region (β). This study
seeks to integrate both Δσ and β into the TL estimation process. Modal magnitude data is derived from disaggregation data from the 2018 National Seismic
Hazard Model (NSHM) for the contiguous United States (CONUS) and the2021 NSHM for Hawaii (HI). β values are obtained from existing literature.
To calculate Δσ for events in the Central and Eastern United States (CEUS),
ground motion models are inverted. For events in the Western United States(WUS) and HI, published information is utilized to determine Δσ. The TL isthen determined using the definition of the corner period. The outcomes of

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this study indicate a generally more conservative or longer estimation of TL
compared to the current approach employed in engineering design standards.
poster 144
Why Seismic Hazard Models Appear to Overpredict
Historical Shaking Observations: An Intensely Simple
AnswerSALDITCH, L., Guy Carpenter & Co LLC, Colorado, USA, leah.salditch@gmail.com; STEIN, S., Northwestern University, Illinois, USA, s-stein@northwestern.edu; GALLAHUE, M., Gallagher Re Inc., Minnesota, USA,
mgallahue13@gmail.com; NEELY, J., University of Chicago, Illinois, USA,jamesneely2022@u.northwestern.edu; ABRAHAMSON, N. A., University ofCalifornia, Berkeley, California, USA, abrahamson@berkeley.edu
To understand how well seismic hazard maps predict actual shaking, we use
performance metrics to compare them via hindcasting. Our hindcasting
approach uses seismic intensities derived from documented shaking effects,
which provide the only source of information for shaking caused by historical earthquakes, and often the most abundant information for instrumentally
recorded events. Using intensities allows longer observation periods for map
performance evaluation, but has limitations in uncertainty and spatial coverage. Comparison of modern hazard maps and historical intensities also
requires conversion between forecasted metrics such as peak ground acceleration (PGA) and intensity. Recent maps for California, Japan, Italy, Nepal,
and France appear to consistently overpredict historically observed intensities. However, numerical simulations show that observed shaking is equally
likely to be above or below predictions. The consistency of results from independently developed models and datasets in different countries and tectonic
settings suggests a possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy
is due to a subtle issue: the Ground Motion Intensity Conversion Equations(GMICE) equations used to compare the maps with historically observed
intensities. Gallahue and Abrahamson (2023) showed that currently used
GMICEs introduce a bias when used to convert hazard maps, overestimating
the PGA-equivalent intensity value by as much as 1 intensity unit for above
average ground motions that often control seismic hazard. Improved GMICE
will be important for seismic hazard performance evaluation and groundmotion modelling efforts. For mitigating earthquake risk, it is encouraging
that much of the apparent overprediction of earthquake hazards results fromthe conversion equations rather than a systematic effect in the hazard modeling approach. Thus although any given hazard map may overpredict or underpredict shaking due to chance or parameter choice, we find no evidence forunderlying systematic problems with hazard mapping.
poster 145
Hybrid Empirical Ground-Motion Models for the Island of
Hawaii Based on an Updated Strong Ground Motion
Database
DAVATGARI TAFRESHI, M., University of Memphis, Tennessee, USA,
mdvtgrtf@memphis.edu; PEZESHK, S., University of Memphis, Tennessee,
USA, spezeshk@memphis.edu; HAJI-SOLTANI, A., CNA Insurance, Illinois,
USA, Alireza.haji-Soltani@cna.com
Due to different anelastic attenuation characteristics, the volcanic origin ofsome events, and the distribution of event depths, ground motion modelingon the island of Hawaii is challenging. The island of Hawaii has experienced
several significant earthquakes, contributing to a growing database of strong
ground motion observations. The development of Ground Motion Models(GMMs) for the island of Hawaii has been limited to only a few. In this study,
we have proposed two separate GMMs using the Hybrid Empirical Method(HEM), one for shallow earthquakes (hypocentral depth ≤ 20 km) and one
for deep earthquakes (hypocentral depth > 20 km) on the Island of Hawaii.
Considering Western North America (WNA) and the island of Hawaii as thehost and target regions, we utilized the stochastic point source model ratio in
the host and target regions as adjustment factors. The adjustment factors havebeen applied to transform the GMMs from the host region to the target region.
The models have been developed by the Ground Motion Intensity Measures(GMIMs) resulting from the HEM and nonlinear least-squares regression. We
further calibrate the models using the observed database to adjust any bias
between the GMIM estimates from the HEM and the Hawaii observations.
The GMMs have been developed to predict PGA and 5%-damped PSA at periods T = 0.01–10 s for moment magnitudes (M) in the range of 3 to 7.5 and for
Joyner-Boore distances in the Rjb ≤ 200 km range.

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poster 146
Empirical Models for Fourier Amplitude Spectrum of
Ground-Motion Calibrated on Data From the IranianPlateau
DAVATGARI TAFRESHI, M., University of Memphis, Tennessee, USA,
mdvtgrtf@memphis.edu; PEZESHK, S., University of Memphis, Tennessee,
USA, spezeshk@memphis.edu; SINGH BORA, S., GNS Science, Lower Hutt,
New Zealand, s.bora@gns.cri.nz
Ground motion models (GMMs) are commonly employed in engineering seismology to predict ground motion intensities. Most GMMs typically
predict the response spectral ordinates, such as spectral acceleration, fora single-degree-of-freedom oscillator due to their widespread use in engineering design. The functional forms of the GMMs for response spectra areconstructed based on principles derived from the Fourier spectral concept.
Presuming the applicability of Fourier spectral concepts in the response
spectral domain might lead to physically inexplicable outcomes. This study
employed a mixed-effects regression technique to introduce four models forpredicting the Fourier amplitude spectrum. These models explore the influence of incorporating random-effect event and station terms and variations in
employing the mixed-effects regression technique in either one or two steps,
using either a truncated dataset or the entire dataset (nontruncated dataset).
The models are developed based on data from Iranian strong motion. All datasets comprise 2581 three-component strong ground motion records derived
from 424 events with magnitudes ranging from 4.0 to 7.4. These records spanfrom 1976 to 2020 and involve 706 stations.
In contrast, the truncated dataset has fewer records, events, and stations,specifically 2071, 408, and 636. We employed simple functional forms for fourmodels, incorporating a restricted set of predictors, which include moment
magnitude (Mw), Joyner-Boore distance (Rjb), and time-averaged shear-wave
velocity in the top 30 m (VS30). The style-of-faulting term was omitted fromthe final functional forms based on statistical analyses.
poster 147
Methods to Evaluate and Improve the Modeling of
Rupture Directivity in Assessment of Seismic Hazard
WITHERS, K., U.S. Geological Survey, Colorado, USA, kwithers@usgs.gov;
KELLY, B., University of Florida, Florida, USA, bpkelly@usgs.gov; BAYLESS,
J., AECOM, California, USA, jeff.bayless@aecom.com; MOSCHETTI, M.,
U.S. Geological Survey, Colorado, USA, mmoschetti@usgs.gov
In recent years, there have been advancements that model near-source effectsof earthquake rupture on strong ground shaking, leading to an improved
characterization of ground motions. Moving forward, modern techniques canbe used to incorporate source characteristics and near-fault ground motion
behavior that contribute to the azimuthally varying effects that result in rupture directivity. One example is the application of machine learning methods
to support more automated integration of new predictor variables in model
development and to allow more evaluation opportunities to assess residuals.
Here, we utilize several techniques to take advantage of the plethora of synthetic data and its ability to supplement trends observed in data. We showcase
two examples of how models can be developed using artificial neural networks(ANNs). We evaluate the performance of the ANN with existing methods,
comparing misfit and evaluate how to improve upon these methods in the
future.
One ANN approach uses a set of simulations with synthetic groundmotions from the Southern California Earthquake Center (SCEC) CyberShakestudy to develop a ground motion model adapted to incorporate seismic directivity information using an ANN. This large database (TBs) enables us to train
the model to better capture magnitude, period, and distance variations andhow they relate to amplification from hypocenters located along finite-faults
during training. In some cases, there is reduced misfit from better representing source features that aren’t included in base ground motion models thatneglect hypocenter location (e.g., azimuthal variation, source-to-site terms).
Another ANN method uses a shallow-layered neural network model to better fit a hypocenter-independent model. This method adjusts the median andaleatory variability to account for the averaged impact of various hypocenter
distributions to fit the underlying directivity adjustment model. This method
serves as a template to apply to other directivity models, improving computational efficiency and more readily enabling integration in hazard codes.

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poster 148
A Fault-Based Crustal Deformation Model With Buried
Dislocation Sources for Slip-Rate Inversion of the Alaska
Faults
ZENG, Y., U.S. Geological Survey, Colorado, USA, zeng@usgs.gov
I apply a fault-based crustal deformation model with buried dislocation
sources to estimate on-fault slip rates and off-fault moment rate distribution
in Alaska for the long-term National Seismic Hazard Model (NSHM). Thismodel uses the method of Zeng and Shen (2017) to invert for slip-rate andstrain-rate parameters based on inputs from Global Positioning System (GPS)velocities and geologic slip-rate constraints. A time-dependent postseismic
deformation correction is applied to the data to account for the viscoelastic
responses from the 1964 Great Alaska earthquake. I modify the Alaska subduction model from the block model of Elliott and Freymueller (2020) using
the USGS Slab2.0 model (Hayes et al., 2018). Faults in Alaska are obtained
from the 2023 NSHM Alaska geologic fault model (Powers et al., 2023). The
model slip rates are determined using a least-squares inversion. The resulting
on-fault model slip rates are compared with the geologic slip rates in Alaska,
and the off-fault moment rate is compared with the regional seismicity rate.

3D Wavefield Simulations: From Seismic Imaging to
Ground Motion Modelling
Oral Session • Thursday 2 May • 8:00 am PacificConveners: Ebru Bozdag, Colorado School of Mines(bozdag@mines.edu); Rebecca Fildes, University ofCalifornia, Davis (rfildes@ucdavis.edu); Menno Fraters,
University of Florida (menno.fraters@ufl.edu); Lorraine J.
Hwang, University of California, Davis (ljhwang@ucdavis.
edu); Andrew Lloyd, Lamont-Doherty Earth Observatory,
Columbia University, (andrewl@ldeo.columbia.edu);
Brandon VanderBeek, Università di Padova (brandonpaul.
vanderbeek@unipd.it)
High Frequency (2+ Hz), 3D Wavefield Simulations of Large
Earthquakes on the Southern Whidbey Island Fault,
Washington StateSTONE, I., U.S. Geological Survey, Washington, USA, istoneuw@gmail.com;
WIRTH, E., U.S. Geological Survey, Washington, USA, emoriarty@usgs.gov;
GRANT, A., U.S. Geological Survey, Washington, USA, agrant@usgs.gov;
FRANKEL, A., U.S. Geological Survey, Washington, USA, afrankel@usgs.gov
We directly simulate large magnitude crustal earthquakes (Mw7.0-7.5) on thesouthern Whidbey Island fault in Washington State to better constrain thepossible extent and distribution of strong shaking in the Puget Sound region.
Simulations employ a 3-D seismic velocity model and kinematic, finite-fault
sources, and are run using a spectral element method code (SPECFEM3D) on
a mesh with a 30m-sampled topographic surface. We also implement targeted
updates to the seismic velocity model at shallow depths to improve accuracy ofhigh-frequency shaking (i.e., modeled up to ~2.5 Hz). These include adding a
region-specific, shallow (~100m-thick) soil velocity model and surface topography. Model quality is assessed by comparing results to empirical groundmotion models (NGA-West2) and records from the 2001 Mw6.8 Nisqually
earthquake. We test the sensitivity of ground motion estimates to a variety
of source parameters, including hypocenter location, fault dip direction, andsource location. We find that all Mw7.0 scenarios produce strong shaking in
the city of Everett, Washington, and produce peak shaking greater >10 cm/s inthe cities of Seattle, Bellevue, and Tacoma. For larger magnitude events, strong
shaking can extend as far north as Victoria, British Columbia, and as far south
as Olympia, Washington. In addition, the sedimentary structure of the nearby
Everett Basin encourages the generation of high-amplitude, intermediate- andlong-period surface waves. We also observe a strong dependence of longperiod amplification in the Everett, Seattle, and Tacoma Basins on rupture
directivity and source location. The inclusion of a shallow soil velocity model
impacts site effects at periods of 1-2 s, with the greatest impact observed atsites with VS30 < 400 m/s. The results indicate that the potential strong shaking from large southern Whidbey Island fault earthquakes will be greatest in
the central Puget Sound region, though the exact distribution and intensityof shaking will be highly dependent on local geology and earthquake source
parameters, like hypocenter location and dip direction.

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3D Kinematic Models of Ground Motions of Cascadia
Megathrust Earthquakes: Preliminary Results andComparison to Paleoseismic Subsidence Data
DUNHAM, A., U.S. Geological Survey, Washington, USA, adunham@uw.edu; WIRTH, E., U.S. Geological Survey, Washington, USA, ewirth@usgs.
gov; KIM, J., University of Washington, Washington, USA, jeykim@uw.edu;
SCHMIDT, D., University of Washington, Washington, USA, dasc@uw.edu;
GRANT, A., U.S. Geological Survey, Washington, USA, agrant@usgs.gov;
FRANKEL, A., U.S. Geological Survey, Washington, USA, afrankel@usgs.gov;
STONE, I., U.S. Geological Survey, Washington, USA, istone@usgs.gov

nario ShakeMaps. Additionally, we save ground acceleration time histories atother sites corresponding to locations of mid- and high-rise buildings for later
use in structural response analysis. Comparison of the simulated motions
with empirical ground-motion models (GMMs) are generally favorable; however, noticeable differences exist due to rupture directivity and basin response
effects. Furthermore, simulated motions along the creeping fault sections are
generally smaller than GMM predictions. The second phase of this work is
ongoing and involves analyzing potential impacts on the built environment
using the simulated ground motions.

The Cascadia Subduction Zone (CSZ) is anomalously quiet, with a dearth ofmoderate-to-large magnitude seismicity in the instrumented record. However,
paleoseismic evidence indicates that the CSZ ruptures in large (~M8-9) megathrust earthquakes, with the last great event occurring in 1700. To quantify theseismic hazard due to great CSZ earthquakes, we employ numerical methods
to simulate ground motions of many M8.7-9.2 megathrust earthquake scenarios. Here, we present preliminary results from the next generation of 3D
broadband (up to 10 Hz) ground motion simulations for the CSZ, building
off the work of Frankel et al. (2018) and Wirth et al. (2018). These broadband ground motions are generated using a hybrid approach, where low frequency (<1 Hz) waveforms are simulated in a 3D seismic velocity model using
SPECFEM3D and are combined with high frequency (1-10 Hz) waveforms
modeled stochastically. We build these scenarios using a logic tree approach,varying the event magnitude, the down-dip and up-dip limits of slip, including rupture onto secondary splay faults, and the slip distributions, which arevaried both randomly and based on interseismic geodetic locking. Ultimately,
these ground motions may be coupled with simulations of tsunami inundation to achieve a time-dependent understanding of seismic and tsunami hazard in coastal communities. These simulations will also be used to quantify
the impacts to infrastructure and cascading hazards, such as landslides, liquefaction, and land-level change, with a focus on coastal communities in the
Pacific Northwest. In addition, we highlight a subset of earthquake scenarios
to evaluate how different rupture properties, as well as methods for calculating static displacements (i.e., 3-D simulations vs. a 1-D Okada model), impact
estimates of coastal vertical land-level change and their comparison to paleoseismic estimates from past earthquakes. We show that the method used to
calculate vertical displacements influences the distribution of coseismic upliftand subsidence, and therefore has implications for comparisons to paleoseismic data from previous Cascadia earthquakes.

Toward High-Frequency Three-Dimensional Green’s
Function Databases
MODRAK, R. T., Los Alamos National Laboratory, New Mexico, USA,rmodrak@lanl.gov; KINTNER, J. A., Los Alamos National Laboratory,
New Mexico, USA, jkintner@lanl.gov; NELSON, P., Los Alamos National
Laboratory, New Mexico, USA, pln@lanl.gov; GAO, K., Los Alamos
National Laboratory, New Mexico, USA, kaigao@lanl.gov; ZHOU, R., Air
Force Technical Applications Center, Florida, USA, rongmao.zhou@us.af.
mil; SAIKIA, C. K., Air Force Technical Applications Center, Florida, USA,chandan.saikia@us.af.mil

Broadband Ground Motion Simulations for a Türkiye-like
Earthquake “Doublet” on the Hayward and Calaveras
FaultsGRAVES, R., U.S. Geological Survey, California, USA, rwgraves@usgs.gov;
WANG-CONNELLY, J., California Office of Emergency Services, California,
USA, Jia.Wang-Connelly@CalOES.ca.gov; THOMPSON, E. M., U.S.
Geological Survey, Colorado, USA, emthompson@usgs.gov; QUITORIANO,
V., U.S. Geological Survey, Colorado, USA, vinceq@contractor.usgs.gov;
WALD, D., U.S. Geological Survey, Colorado, USA, wald@usgs.gov; MILNER,
K., University of Southern California, California, USA, kmilner@usc.edu;
GUNAY, S., University of California, Berkeley, California, USA, selimgunay@
berkeley.edu
The occurrence and impact of the February 2023 earthquake doublet in
Türkiye, where an Mw 7.8 event was followed roughly 9 hours later by an Mw
7.5 event on an adjacent fault, begs the question: What would be the impact
of such a sequence in California? Here, we consider a comparable doublet
scenario on the Hayward and Calaveras faults in the San Francisco Bay region.
The first phase of this work involves characterizing the fault ruptures and simulating the ground motions. We base the fault locations and orientations on
the 2023 USGS National Seismic Hazard Model. Both faults have creeping
zones, so we use a simple scheme in our kinematic rupture generator to taper
the coseismic slip in the upper 10 km based on the ratio of long-term creep
rate to long-term fault slip rate along each section. The resulting magnitudes
are Mw 7.15 for the 95-km Hayward rupture and Mw 7.16 for the 100-km
Calaveras rupture. We compute broadband motions using a combination ofdeterministic and stochastic approaches for the lower- and higher-frequency
components, respectively. Our deterministic calculations use the USGS 3D
San Francisco Bay region velocity model (v21.1) with a minimum shear velocity of 400 m/s, and our stochastic simulations use a 1D reference model with
Vs30-based site-specific adjustments using period-dependent factors. We
saved waveforms on a 1.2 km by 1.2 km grid of points, and we extracted PGA,
PGV, and spectral accelerations at periods of 0.3, 1.0, and 3.0 s to produce sce-

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An effort is underway at national laboratories and universities to compute new
3D Green’s functions. To inform choices for production Green’s function simulations, we present ~1 Hz comparisons between elastic solvers and preliminary 3D moment tensor inversions for 6 historical underground explosions.
Among the results of the comparisons, we show that, even with extremely
conservative meshing, differences of practical significance can persist between
finite-difference and finite-element synthetics. More subtly, source-dependent
amplitude errors related to finer meshing requirements for shear relative tocompressional waves can give rise to systematic biases, motivating detailed
convergence checks.
Guided by the above, we computed finite-element Green’s functions andcorresponding moment tensors for the historical explosions. Our results showthat meaningful patterns can persist in moment tensor uncertainty surfaces
even when best-fitting moment tensor solutions become unreliable. For lowmagnitude or sparsely-recorded seismic events, 3D Earth models may provide
new source constraints different from the usual Rayleigh-wave radiation pattern constraints that tend to dominate 1D inversions, with implications for
improved source-type estimation in particular.
Iterative Global 3D Centroid Moment Tensor Inversions
Using Stored Global Green Functions From Glad-M25
SAWADE, L., Princeton University, New Jersey, USA, lsawade@princeton.
com; EKSTRÖM, G., Columbia University, New York, USA, ekstrom@ldeo.columbia.edu; DING, L., University of Toronto, Toronto, Canada,
liangding86@gmail.com; PETER, D., King Abdullah University of Science& Technology, Thuwal, Saudi Arabia, daniel.peter@kaust.edu.sa; LIU, Q.,
University of Toronto, Toronto, Canada, qinya.liu@utoronto.ca; NETTLES,
M., Columbia University, New York, USA, nettles@ldeo.columbia.edu;
TROMP, J., Princeton University, New Jersey, USA, jtromp@princeton.edu
Though the synthetic seismograms used for Global CMT inversion are basedon modern 3D Earth models, their accuracy is limited by the validity of thepath-average approximation for mode summation and surface-wave ray
theory. Inaccurate computation of ground motion amplitude and polarization, and other effects that are not modeled, may bias inverted earthquake
parameters. Synthetic seismograms of higher accuracy will improve the determination of seismic sources in the CMT analysis, and reduce concerns about
this source of uncertainty. However, traditional forward computation of 3D
synthetic seismograms for iterative source inversion remains computationally prohibitive. The calculation of a strain-tensor database has recently been
implemented for the spectral-element solver SPECFEM3D (Ding et al., 2020),
based on theory from previous work for regional inversion of seismogramsfor earthquake parameters (Zhao et al., 2006). The main barriers to a global
database of Green functions have been storage capacity, I/O, and computation
speed. We show that subselecting necessary elements can efficiently overcome
these issues when storing reciprocal wavefields for 183 stations of the Global
Seismographic Network. Here, we apply this framework of Green Function
storage to the set of GCMT solutions used for the CMT3D catalog Sawade etal. (2021) and compare GCMT, CMT3D, and CMT3D+ solutions, the latterof which are iteratively inverted for moment tensor and centroid location andtime until converged.

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SPECFEM++: A Modular and Portable Spectral-element
Framework for Seismic Wave Propagation
KAKODKAR, R. R., Princeton University, New Jersey, USA, rohit_
kakodkar@princeton.edu; TROMP, J., Princeton University, New Jersey, USA,jtromp@princeton.edu
SPECFEM represents a suite of computational tools based on the spectral
element method used to simulate wave propagation through heterogeneous
media. Over the years, SPECFEM has been developed as a set of 3 Fortranpackages (SPECFEM2D, SPECFEM3D, and SPECFEM3D_GLOBE) with partial support for GPUs (NVIDIA and AMD). The central premise of SPECFEM
has always been achieving highly optimized performance on traditional andmodern architectures by implementing domain- and dimension-specificalgorithmic optimization. However, this approach has also resulted in acodebase with a high technical overhead, heavy use of conditional branches,architecture-specific implementations, code duplication, and isolated feature
implementations.
In this talk, I will present our recent efforts to unify the suite of
SPECFEM packages under a single modular framework, SPECFEM++, while
maintaining the performance characteristics of the original packages. The
key feature of SPECFEM++ is a formulation that separates the physics fromthe parallelism of the spectral element method. We describe this parallelism
using the Kokkos programming model and the physics using C++-templated
spectral element types. The flexibility of C++ templates and the performanceportability of Kokkos programming model has let us design a modular package that is highly versatile and performant.
Forward Simulation of Air and Ground Vibration Induced
by Series of Wind Turbines Using the Spectral-Element
MethodFITZGERALD, J., Queen’s University, Kingston, Canada, 17jcf1@queensu.
ca; WIBOONWIPA, N., Queen’s University, Kingston, Canada, 21nw23@
queensu.ca; GHARTI, H., Queen’s University, Kingston, Canada, homnath.
gharti@queensu.ca; BRAUN, A., Queen’s University, Kingston, Canada,
braun@queensu.ca
Amidst the ongoing energy transition, wind power, harnessed via turbines,
has been identified as a viable renewable energy source capable of generating clean, sustainable power. As wind turbines harness the wind’s energy to
produce electricity, they introduce sub-aerial and subsurface vibrations thatcan be observed in seismic and acoustic recordings. Elastic and acoustic wave
propagation from turbine sources was simulated using the spectral-element
method implemented in SPECFEM3D across a spectrum of frequencies ranging from 1 to 10 Hz across a diverse set of subsurface conditions. Numericalresults were compared with observations from turbine installations in Wolfe
Island, Ontario for validation. Comprehensive synthetic modelling of these
coupled wavefields allows us to characterize the noise introduced by thesepower-generating structures and to assess their impact on nearby people andinfrastructure. Further, the wavefield characterization allows for the investigation of turbines as a seismic source that can lead to monitoring solutions forstructural foundation and installation integrity.
Multiscale Rupture Modeling: Bridging Laboratory
Acoustic Emissions and Earthquake Ground Motions
GU, C., Tsinghua University, Beijing, China, guchch@mit.edu; MENG, C.,
Massachusetts Institute of Technology, Massachusetts, USA, cmeng@mit.edu
Rupture phenomena occur at multiple scales, ranging from laboratory failure
experiments to real-world earthquakes. This study introduces a novel hybrid
approach combining quasi-static and dynamic rupture modeling to explore
the initiation and propagation of fracture events. This method is applied tothree distinct scenarios: a laboratory stick-slip experiment, a hydraulic fracture
experiment, and the 2022 M6.7 Luding earthquake in Sichuan Province, China.
The models for each scenario are validated using real waveform observations from laboratory Piezoelectric Transducer (PZT) sensors and an array ofdense field strong motion stations. The results from these applications demonstrate the robustness and versatility of the hybrid rupture modeling technique. The study provides insights into the intricate mechanisms of fracture
initiation and growth at different scales, highlighting the correlation between
micro-scale laboratory acoustic emissions and macro-scale earthquake
ground motions. Furthermore, our findings reveal the critical role of various
physical parameters in rupture dynamics, such as stress concentration, material heterogeneity, and fault geometry. These insights have significant implications for understanding earthquake mechanics and improving seismic hazard
assessment.

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Local Geological Changes and Simplicial Remeshing for
Wave Propagation
CUPILLARD, P., Université de Lorraine, Nancy, France, paul.cupillard@univ-lorraine.fr; CAUMON, G., Université de Lorraine, Nancy, France,
guillaume.caumon@univ-lorraine.fr; ANQUEZ, P., Geode-solutions, Pau,
France, pierre.anquez@geode-solutions.com; LEGENTIL, C., TotalEnergies,
Pau, France, capucine.legentil@gmail.com; GLINSKY, N., CEREMA, Sophia
Antipolis, France, Nathalie.Glinsky@cerema.fr; PELLERIN, J., TotalEnergies,
Pau, France, jeanne.pellerin@totalenergies.com; FROEHLY, A., INRIA, Pau,
France, algiane.froehly@inria.fr
Realistic geological models of the subsurface often hold thin layers, tangential
contacts, and horizons shifted by faults. Such features are difficult to handle inseismic wave propagation simulation because they lead to gigantic computation costs when using explicit time-schemes. As a consequence, studying theimpact of geological structural uncertainties on wave propagation remains outof reach in most cases. In this work, we propose two strategies to modify ageological model locally and provide a good-quality simplicial mesh of it. The
first strategy aims at better balancing accuracy and efficiency of wave propagation simulations by expanding or contracting the problematic aforementioned
geological features. Relying on an exclusion zone associated with each horizon
and fault, our approach locally modifies the geometry and the connectivity ofgeological layers in an automatic way. When applied to ground motion modelling in the lower Var valley basin (France), this approach allows to decrease
the computation cost of a discontinuous Galerkin simulation by a factor of 55
while keeping an excellent accuracy. The second strategy we propose aims at
inserting a new geological interface in a given model while avoiding to remesh
this latter completely. To do so, we rely on a level-set function to describe theinterface to be inserted and on the Mmg software to remesh the vicinity of theinterface, with a special care of its intersections with previous discontinuities.
Using this approach, we study the impact of the depth of a gas-water contact on a seismic wavefield. This illustrates how our method might open thepath to the inversion of waveforms for the estimation of geological structuralparameters.
3D Multiresolution Velocity Model Fusion With Probability
Graphical Models
ZHOU, Z., University of California, San Diego, California, USA, zhz039@
ucsd.edu; GERSTOFT, P., University of California, San Diego, California,
USA, pgerstoft@ucsd.edu; OLSEN, K. B., San Diego State University,
California, USA, kbolsen@sdsu.edu
The variability in spatial resolution of seismic velocity models obtained via
tomographic methodologies is attributed to many factors, including inversion
strategies, ray path coverage, and data integrity. Integration of such models,with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground motion simulations. Toward
this goal, we introduce the Probability Graphical Model (PGM), combining
velocity models with heterogeneous resolutions and non-uniform data point
distributions. The PGM integrates data relations across varying-resolution
subdomains, enhancing detail within low-resolution domains by utilizing information and a priori knowledge from high-resolution subdomains
through a maximum likelihood problem. Assessment of efficacy, utilizing
both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault zone model from Ridgecrest, CA—demonstrates noteworthy
improvements in accuracy. Specifically, we find reductions of 30% and 44% incomputed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods,
the PGM’s adaptive weight selection facilitates preserving and learning details
from complex, non-uniform high-resolution models and applies the enhancements to the low-resolution background domain.
Multi-Scale Seismic Imaging of Fault-Zone Structures inSouthern California With Full-Waveform Inversions ofRegional and Dense Array Data
LI, G., Statewide California Earthquake Center & University of Southern
California, California, USA, guoleonlee@gmail.com; BEN-ZION, Y.,
Statewide California Earthquake Center & University of Southern California,
California, USA, benzion@usc.edu
We discuss several methodologies for constructing multi-scale seismic velocity models for crustal fault zones at seismogenic depths with full-waveform
inversion of earthquake and ambient noise data recorded by regional anddense sensor configurations. We first discuss applications for the area aroundthe rupture zone of the 2019 Ridgecrest earthquake sequence in California,
leveraging data from the regional network and dense 2D and 1D deployments

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with station spacings of ~5 km and ~100 m, respectively. To build self-consistent multi-scale models, we begin with pre-existing regional velocity model
earthquake locations, and refine these results through iterative inversions ofwaveforms recorded by regional and 2D array stations. The improved results
provide a structural context of small-scale fault zone models with resolutions
up to the tens of meters using high-quality aftershock waveforms captured
by dense linear arrays with frequencies up to 10 Hz. As a second focus area,
we develop multi-scale imaging for the southern San Andreas fault using
data recorded by a dense deployment near the Thousand Palms Oasis in the
Coachella Valley at a time with very few local earthquakes. To utilize regional
and teleseismic earthquake waveforms, we use double-difference kernels
with the FK-injection SPECFEM3D solver to image the fault-zone structures
beneath the dense array. The multi-scale results on fault zone and crustal
structures contribute significantly to improved understanding of earthquake
processes and seismic hazard assessments. The developed methodologies arebroadly applicable to research on fault zones worldwide.
Global Source-Encoded Waveform Inversion: Preliminary
Results
CUI, C., Princeton University, New Jersey, USA, ccui@princeton.edu;
BACHMANN, E., Princeton University, New Jersey, USA, etienneb@
princeton.edu; TROMP, J., Princeton University, New Jersey, USA, jtromp@
princeton.edu
We present the latest update on applying source encoding on a global scale.
Our source-encoding technique enables us to compute Fréchet derivatives forall events with only a few forward and adjoint simulations and shows promising results for a hemispherical-scale study. In this study, we introduce four
improvements. First, we start with the GLAD-M35 model, which is our latest global adjoint tomography model and provides a low-rank approximationof the full Hessian. This enables us to properly scale partial velocity Hessian
terms as the preconditioner and determine the smoothing length based on the
resolution length estimation. Second, we expand the dataset to a total of 9,382
events with corrected source mechanisms from 3D numerical simulations.
The dataset is selected using a combination of FLEXWIN and new frequencydomain criteria, which restrict the difference between source-encoding andinversions using the full-frequency band. Third, by re-running forward simulations for all events every 10 iterations, we introduce a ‘windowing’ techniquethat removes unwanted parts of the time-domain observed data even when we
only have a few data points in the frequency domain. Finally, we adopt new
optimizers that better fit the varying nature of the source-encoded objectivefunction. The optimizers we are testing include ADAM, stochastic conjugate
gradient, and stochastic BFGS.
LLNLGlobeFWI: First Iterations Using a Semi-Automatic FWI
Framework Applied to the Globe With Spiral as theStarting Model
VAZQUEZ, L., University of Southern California, California, USA,luisalbe@usc.edu; MORENCY, C., Lawrence Livermore National Laboratory,
California, USA, morency1@llnl.gov; SIMMONS, N. A., Lawrence Livermore
National Laboratory, California, USA, simmons27@llnl.gov
Building on the global anisotropic travel time tomography model, SPiRaL(Simmons et al., 2021), we present the first global full waveform inversion (FWI) updates to SPiRaL using an initial set of 103 events distributed
throughout the globe at a period band from 40 s to 200 s. We employed
LLNLGlobeFWI which is a python-based framework for semi-automatedglobal full waveform inversion using the adjoint method. LLNLGlobeFWI
was developed at Lawrence Livermore National Laboratory (LLNL) andused SeisFlows (Modrak et al., 2018) as a starting point for the development.
LLNLGlobeFWI was executed on LLNL’s Quartz supercomputer and 90-minute seismograms were computed for the events to capture seismic phases at
global distances. Seismograms were windowed with Pyflex, multitaper misfits and associated adjoint sources were computing using Pyadjoint, and the
L-BFGS method was used for the optimization within the custom semi-automated workflow. Accurate prediction of waveforms and onset arrival times
at all distances with a single global model is the overall goal of this project.
Here, we present the first full waveform inversions aimed at reaching that goal
starting with the SPiRaL model and an initial set of global events. Future work
will include the incorporation of a larger data set, period band reduction, andbenchmarking with SPiRaL to ensure the onset times are improving as well.
This work was performed under the auspices of the U.S. Department ofEnergy by Lawrence
Livermore National Laboratory under Contract DE-AC52-07NA27344.

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Seismological Research Letters

Homogenized Full Waveform Inversion : Application to
Earth Model for Long Period Seismic Waves
COLVEZ, M., CEA DAM DIF, Arpajon, France, martin.colvez@ens-cachan.
fr; BURGOS, G., CEA DAM DIF, Arpajon, France, gael.burgos@cea.fr;
CAPDEVILLE, Y., Centre National de la Recherche Scientifique, Nantes,
France, yann.capdeville@univ-nantes.fr; GUILLOT, L., CEA DAM DIF,
Arpajon, France, laurent.guillot@cea.fr
In order to understand the structure and dynamics of the Earth, seismic
tomographic models are a precious tool. However the building of such models
may be biased by such an interpretative goal. Switching paradigms, we canrelax the interpretation aim to focus on building data-predictive models only,
designed to perform source properties inversion for instance.
To proceed to the construction of such an Earth model, we applied amodified version of the classical Full Waveform Inversion (FWI), considering a full anisotropic setting of mechanical properties (21 elastic parametersand density), and a Gauss-Newton algorithm. Numerical simulations are performed using a spectral-element solver (SEM3D) in order to solve for bothforward and adjoint wavefields, that give access to sensitivity kernels. Then,considering that the best model obtained by FWI is at best an effective modelof the true one (as proposed by Capdeville & Métivier, 2018), a filtering step
(whose operator comes from homogenization theory applied to nonperiodic
media) provides a spatial regularization for the inverted model. With thisin mind, a test-case is performed on a starting simplified Earth model withlargely buried mantle heterogeneities. The resulting inverted, homogenizedmodel, is very close to the homogenized starting model, as expected. The
inverted model can therefore be considered as a good data-predictive model.
Adjoint-State Traveltime Tomography (tomoatt.com)
TONG, P., Nanyang Technological University, Singapore, Singapore,
tongping@ntu.edu.sg; CHEN, J., Nanyang Technological University,
Singapore, Singapore, jing.chen@ntu.edu.sg; NAGASO, M., Nanyang
Technological University, Singapore, Singapore, masaru.nagaso@ntu.edu.sg;
HAO, S., Nanyang Technological University, Singapore, Singapore, masaru.
nagaso@ntu.edu.sg; XU, M., Nanyang Technological University, Singapore,
Singapore, mijian.xu@ntu.edu.sg
Adjoint-state traveltime tomography is an efficient approach for determining
subsurface seismic structures (Vp, Vs, anisotropy) and earthquake locations
using body wave traveltime data. One remarkable feature of this approachis its independence from ray tracing. TomoATT is the software package that
implements adjoint-state traveltime inversions. The package’s first version,
designed for non-commercial use in scientific community, is now ready forrelease. TomoATT grants users the flexibility to choose the specific type(s)of traveltime data they wish to employ. Whether it be absolute arrival times,
common-source differential arrival times, or common-receiver differential
arrival times, users can utilize them simultaneously or separately to infervelocity structures and/or earthquake locations. TomoATT stands out for its
multilevel hybrid parallelization technique, which incorporates source parallelization, subdomain parallelization, hyperplane stepping parallel fast sweeping, and Single Instruction, Multiple Data (SIMD) optimization for multiple CPU architectures (AVX2, AVX-512 and ARM-SVE). This innovative
approach significantly enhances computational efficiency and empowers the
package to tackle super large-scale problems effectively. TomoATT is a userfriendly software package. Users only need to input traveltime data in a predefined format, and the software will execute with minimal user interference.
The usage of the software package, TomoATT, can be found at www.tomoatt.
com. Notably, adjoint-state traveltime tomography has also been extended toinvert surface wave traveltime data for seismic velocity and anisotropy.

3D Wavefield Simulations: From Seismic Imaging to
Ground Motion Modelling [Poster Session]
Poster Session • Thursday 2 May
Conveners: Ebru Bozdag, Colorado School of Mines(bozdag@mines.edu); Rebecca Fildes, University ofCalifornia, Davis (rfildes@ucdavis.edu); Menno Fraters,
University of Florida (menno.fraters@ufl.edu); Lorraine J.
Hwang, University of California, Davis (ljhwang@ucdavis.
edu); Andrew Lloyd, Lamont-Doherty Earth Observatory,

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Columbia University, (andrewl@ldeo.columbia.edu);
Brandon VanderBeek, Università di Padova (brandonpaul.
vanderbeek@unipd.it)
poster 107
A Detailed Analysis of Seismic Waves Amplification forBasins Using 3D Seismic Simulations
TIAN, Y., Lawrence Livermore National Laboratory, California, USA, tian7@
llnl.gov; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu
Sedimentary basins trap seismic waves, leading to amplification and longduration shaking. This seismic response of a sedimentary basin can be relevant
both for understanding active tectonics and for assessing seismic hazards relevant to society. Using 3D seismic wavefield simulations with different models, we can explore how the basin depth and the basin’s geometrical boundary
affect the seismic waves, amplitudes, and radiation patterns. Nenana basinin central Alaska is a promising region for studying basin wave propagation
because its basement surface has been estimated from detailed active-source
imaging and because there were about 15 broadband seismic stations in theregion, enabling comparisons between simulation results (synthetics) andobservations (data). We have created four Nenana basin region models: 1) the
Berg et al. (2020) 3D tomographic model, 2) the Berg model with an embedded basin model, 3) a simplified model of an elliptical basin embedded in
the Berg model, 4) a model with upper 8km from 1D velocity profile fromBrocher2008 and bottom from the Berg model. By comparing and analyzing
the seismic simulation results in both time and frequency domains from thesemodels, together with the real data collected in this region, we can investigate
the detailed mechanism of basin amplification for a variety of different seismic
sources, basin geometries, and frequencies.
Acknowledgments
This work was performed under the auspices of the U.S. Departmentof Energy by Lawrence Livermore National Laboratory under Contract
DE-AC52-07NA27344. This manuscript was reviewed and released
LLNL-ABS-859040
poster 108
Estimating Ground Motion Intensities Using SimulationBased Estimates of Local Crustal Seismic Response
AGRAWAL, H., University of Edinburgh, Edinburgh, United Kingdom,
himanshu.agrawal@ed.ac.uk; MCCLOSKEY, J., University of Edinburgh,
Edinburgh, United Kingdom, john.mccloskey@ed.ac.uk
It is estimated that 2 billion people will move to cities in the next 30 years,
many of which possess high seismic risk, underscoring the importance of
reliable hazard assessments. Current ground motion models for these assessments typically rely on an extensive catalogue of events to derive empirical
Ground Motion Prediction Equations (GMPEs), which are often unavailable
in developing countries. Considering the challenge, we choose an alternative
method utilizing physics-based (PB) ground motion simulations and develop
a simplified decomposition of ground motion estimation by considering
regional attenuation (Δ) and local site amplification (A), thereby exploring
how much of the observed variability can be explained solely by wave propagation effects. We deterministically evaluate these parameters in a virtualcity named Tomorrowville, located in a 3D layered crustal velocity model
containing sedimentary basins, using randomly oriented extended sources.
Using these physics-based empirical parameters (Δ and A), we evaluate theintensities, particularly Peak Ground Accelerations (PGA), of hypothetical
future earthquakes. The results suggest that the estimation of PGA using thedeterministic decomposition exhibits a robust spatial correlation with the
PGA obtained from simulations within Tomorrowville. This method exposes
an order of magnitude spatial variability in PGA within Tomorrowville, primarily associated with the near-surface geology and largely independent of
the seismic source. In conclusion, advances in PB simulations and improved
crustal structure determination offer the potential to overcome the limitationsof earthquake data availability to some extent, enabling prompt evaluation ofground motion intensities.
poster 109
Effects of the Distribution of Ambient Noise Sources in
Subsurface Models Inverted From Noise Correlations
VALERO CANO, E., King Abdullah University of Science and Technology,
Jeddah, Saudi Arabia, eduardo.valerocano@kaust.edu.sa; FICHTNER, A.,ETH Zürich, Zürich, Switzerland, andreas.fichtner@erdw.ethz.ch; PETER, D.,

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King Abdullah University of Science and Technology, Thuwal, Saudi Arabia,
daniel.b.peter@gmail.com; MAI, P. M., King Abdullah University of Scienceand Technology, Thuwal, Saudi Arabia, martin.mai@kaust.edu.sa
Cross-correlations of seismic ambient noise are often used to image subsurface structure. Although it is possible to account for the distribution of noise
sources and treat noise correlations as self-consistent observations, most studies currently assume that noise sources are uniformly distributed and interpret
noise correlations as empirical Green’s functions. However, this assumption
is not always correct, as noise sources are often localized and unevenly distributed. In this work, we investigate how the treatment of the noise source
distribution changes subsurface models obtained from noise correlations. Our
main focus is to study how inverted models change if a realistic heterogeneous
noise source distribution is either incorrectly assumed to be uniform or properly taken into account. Furthermore, we explore the consequences of ignoring distant noise sources in a regional tomography, which may be necessary
to avoid excessive computational requirements. To reach these objectives, we
conduct a series of 2-D synthetic inversions for local subsurface structure,and thereby imitate a local-scale experiment exploiting ocean noise. The synthetic dataset consists of noise correlations computed with a large-scale noise
source distribution and a laterally heterogeneous Earth structure model. We
invert this dataset using three approaches, each dealing with the noise source
distribution differently. Additionally, we repeat the experiments using a second synthetic dataset generated with a different noise source distribution toinvestigate how the estimated subsurface varies artificially due to the Green’s
function approximation. Our results demonstrate that the Green’s function
approximation introduces errors in the inverted models with a magnitude
that depends on the distribution of noise sources. Since the location of noise
sources changes over time, this suggests that model errors are also timedependent. In contrast, source-related errors are avoided if the noise source
distribution is accounted for. However, all noise sources, including thoselocated away from the area of interest, must be properly considered.
poster 110
Southern Italy: An Intricate Litosphere
CASAROTTI, E., Istituto Nazionale di Geofisica e Vulcanologia - INGV,
roma, Italy, emanuele.casarotti@ingv.it; MAGNONI, F., Istituto Nazionale
di Geofisica e Vulcanologia - INGV, Roma, Italy, federica.magnoni@ingv.it;
CIACCIO, M., Istituto Nazionale di Geofisica e Vulcanologia - INGV, roma,
Italy, mariagrazia.ciaccio@ingv.it; DI STEFANO, R., Istituto Nazionale diGeofisica e Vulcanologia - INGV, Roma, Italy, raffaele.distefano@ingv.it
High-resolution adjoint tomography stands out as a valuable method for comprehending the complexities of the Earth’s lithosphere. This paper offers an
overview of the seismic images resulting from IMAGINE_IT adjoint tomography in the study of the lithosphere beneath Southern Italy and the Adriatic
region.
The Adria plate plays a crucial role in the geodynamics of the Central
Mediterranean, serving as the foreland of non-coeval mountain ranges. Its
margins are subjected to subduction systems beneath the Alps to the north,the Apennines to the west, and the Dinarides to the east. The intricate behavior of this system, combined with geographical data heterogeneity, has led to a
fragmented understanding of the Adria plate. The lithospheric structure, specifically Vp and Vs profiles, remains poorly understood due to limited seismic
stations, compromised earthquake location quality, and a lack of coverage bytraditional seismic tomography methods. These uncertainties complicate theassessment of seismic hazards along the Adriatic coasts, including tsunami
hazard evaluation. We present a preliminary analysis incorporating sevenyears of supplementary data beyond IMAGINE_IT original timeframe (limited to data until 2015). Noteworthy contributions come from the deployment
of dense regional arrays of broadband seismic stations, such as AlpArray andthe ongoing AdriaArray initiative.
Furthermore, the focus extends to southern Italy, covering the L’Aquila
region up to the Calabrian Arc. The analysis of images produced by highresolution adjoint tomography IMAGINE_IT reveals details of the lithospheric architecture, including crustal thickness variations, seismic velocity
anomalies, and clear support of a significant interruption of delamination/
subduction-related features.
poster 111
Synthetic Inversions for Anisotropic Structures using
Wavefield Simulations and Adjoint Methods
GUPTA, A., University of Alaska Fairbanks, Alaska, USA, agupta7@alaska.
edu; CHOW, B., University of Alaska Fairbanks, Alaska, USA, bhchow@

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alaska.edu; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu
Laboratory measurements confirm the presence of complex (low-symmetry)elasticity in a wide range of materials. The presence of anisotropy in the uppermost mantle is well established. In subduction settings, anisotropy is complex, with different elements—the subducting plate, the mantle wedge, andthe crust—potentially having different forms of anisotropy. Seismic imaging
problems generally offer non-unique solutions, due to extreme heterogeneity
and sparse coverage of stations and source. The addition of parameters due tothe consideration of anisotropy makes the problem even more challenging.
Here, in preparation for real seismic imaging problems, we perform a series ofsynthetic tomographic inversions, whereby a synthetic target model is used togenerate synthetic data for a given source-station geometry. An initial model,
different from the target model, is used to generate initial synthetic seismograms. Through formal minimization between initial and target seismograms,
we iteratively perturb and improve the initial model toward the target model.
We consider different target model blocks, each having a predefined typeof homogenous anisotropy, and we test their recovery with a source-stationgeometry designed to have good, yet realistic, coverage of the medium. We
test the limits of recovery of these synthetic anisotropy models by changing:1) the size of the anomaly, 2) the degree of symmetry of the anomaly, 3) thestrength of anisotropy (angular distance from isotropy), 4) the density of station coverage, and 5) the portion of waveforms to use in the inversion. Our
study prepares us for realistic synthetic inversions for complex anisotropic
structures, which will guide efforts for performing adjoint tomography in the
Alaska subduction zone.
poster 112
Analysing Alpine Fault Earthquakes Through Ambient
Seismic NoiseJUAREZ GARFIAS, I., Victoria University of Wellington, Wellington, New
Zealand, ilmadelcarmen.juarezgarfias@vuw.ac.nz; TOWNEND, J., Victoria
University of Wellington, Wellington, New Zealand, john.townend@vuw.
ac.nz; CHAMBERLAIN, C. J., Victoria University of Wellington, Wellington,
New Zealand, calum.chamberlain@vuw.ac.nz; HOLDEN, C., SeismoCity,
Wellington, New Zealand, caroline.francoisholden@gmail.com
The Alpine Fault is the primary seismic hazard in Southern New Zealand,
rupturing in M7-8 earthquakes roughly every ~300 years, with the last eventin 1717 AD. Yet, empirical data on ground shaking does not exist due to theabsence of recorded Alpine Fault earthquakes. Numerical models that simulate shaking from possible Alpine Fault earthquakes provide key information to assist in hazard mitigation but current state-of-the-art models are too
computationally expensive, limiting their ability to compute a comprehensive
range of potential earthquake source scenarios.
Our approach sidesteps these limitations by estimating ground shaking
using ambient seismic noise for modelling wave propagation. Ambient noise,
often seeming random and incoherent in seismograms, can reveal coherent
energy travelling between two seismic stations through cross-correlation,
deconvolution, and coherency analyses. We apply the Virtual Earthquake
method, which uses ambient seismic noise to compute empirical Green’s functions between station pairs. These empirical Green’s functions are modified
from a surface point-force source to a double-couple source at depth. Thismethod allows us to investigate ground shaking from many rupture scenarios
comprising a broad suite of possible Alpine Fault earthquakes.
We use ambient noise records of both permanent networks and thenovel SALSA (Southern Alps Long Skinny Array), a network of broadband
seismometers strategically deployed every ~10 km along the Alpine Fault,
which facilitates a comprehensive investigation of diverse rupture scenarios.
This study showcases the potential of using ambient seismic noise to unravel
seismic behaviour, offering a valuable tool for predicting and mitigating seismic hazards.
poster 113
Selection of a Starting Model for Adjoint Tomography of
the Pacific Northwest
KEHOE, H. L., U.S. Geological Survey, Colorado, USA, hkehoe@usgs.gov;
BOZDAG, E., Colorado School of Mines, Colorado, USA, bozdag@mines.

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edu; BOYD, O. S., U.S. Geological Survey, Colorado, USA, olboyd@usgs.gov;
WIRTH, E., U.S. Geological Survey, Washington, USA, ewirth@usgs.gov;
STEPHENSON, W. J., U.S. Geological Survey, Colorado, USA, wstephens@
usgs.gov; MOSCHETTI, M. P., U.S. Geological Survey, Colorado, USA,mmoschetti@usgs.gov
High-resolution seismic tomography models are invaluable in characterizing
subsurface geologic structures, quantifying seismic hazards, and understanding broader tectonic processes. Theoretical and computational advances over
several decades have enabled full-waveform inversion techniques that extract
more information from recorded seismograms than classical methods. In parallel, numerical methods have facilitated the rapid calculation of the forward
and adjoint (time-reversed) wavefields in earthquake seismology, their interaction allowing the construction of the gradient of a chosen misfit function
and the iterative improvement of the velocity model. It is well known thatstarting models play a crucial role in the success of full-waveform inversions.
Here, the Stephenson et al. (2017) Cascadia seismic velocity model is systematically tested as a candidate starting model for future adjoint tomography of
the Pacific Northwest. We use SPECFEM3D Cartesian (Komatitsch & Tromp,
1999) to calculate synthetic seismograms using the candidate starting modeland a catalog of over 500 M4.0+ regional earthquakes recorded from 2012–
2023. We assess starting model quality by comparing travel time anomalies
between the synthetic and observed waveforms. We explore modifications tothe starting model based on physical a priori constraints and make comparisons with a one-dimensional Earth model (ak135; Kennett et al., 1995). We
focus on crustal and uppermost mantle structure which spans depth ranges(0–60 km) that are important to accurately estimate ground motions and seismic hazards, but may be poorly resolved in existing velocity models. Whilesimilar analyses with alternative candidate starting models remain necessary,
this work will ultimately enable the development of future Pacific Northwest
adjoint tomography models.
poster 114
Rupture Dynamics and Ground Motions Characteristics ofthe 2023 Türkiye Mw 7.8 and Mw 7.6 Earthquake Doublet
LI, B., King Abdullah University of Science and Technology, Thuwal, Saudi
Arabia, bo.li.3@kaust.edu.sa; PALGUNADI, K., King Abdullah University of
Science and Technology, Thuwal, Saudi Arabia, kadek.palgunadi@kaust.edu.
sa; WU, B., University of Southern California, California, USA, baoningw@
usc.edu; SUHENDI, C., King Abdullah University of Science and Technology,
Thuwal, Saudi Arabia, cahli.suhendi@kaust.edu.sa; ZHOU, Y., Universityof California, Riverside, California, USA, yzhou279@ucr.edu; GHOSH, A.,
University of California, Riverside, , USA, aghosh.earth@gmail.com; MAI, P.,
King Abdullah University of Science and Technology, Thuwal, Saudi Arabia,
martin.mai@kaust.edu.sa
Earthquake doublets have been observed globally in various tectonic regimes.
Their occurrence disagrees with general aftershock evolution laws and thus
challenges common approaches for seismic hazard assessment. A better
understanding of the rupture evolution and interaction of faults involved inearthquake doublets is thus needed to improve earthquake forecasting andseismic hazard analysis. On February 6, 2023, the destructive earthquake doublet with magnitude 7.8 and 7.6 successively rocked south-central Türkiye andnorthwestern Syria. Here, we use data-constrained dynamic rupture modeling to investigate the rupture process and ground motions of the earthquake
doublet. We find that the complex 3D fault geometry and the regional stressregime generates a distinct pre-stress loading on the multi-segment fault network and leads to complex rupture dynamics, including rupture branching
and arresting, forward and backward rupture triggering, transitions between
subshear and supershear. Our dynamic models well reproduce InSAR, GPS,
local strong motion and teleseismic data. The synthetic ground motions show
heterogeneous distribution with strong directivity amplification by subshear
ruptures. Supershear rupture elevates the ground motion intensity off the fault,
but mitigates the directivity amplification. Our synthetic ground motions
illustrate the same distance decay pattern with the observations. In summary,our work highlights the importance of fault geometry and pre-stress loading
in determining the complexity in rupture dynamics, and indicates that physics-based modeling can complement the ground motion models for assessing
the seismic hazard.

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poster 115
Lithospheric Structures of the Central Cascadia Subduction
Zone Resolved by Full-waveform Inversion of Ambient
Noise and Receiver Functions
DU, N., University of Toronto, Toronto, Canada, nanqiao.du@mail.utoronto.
ca; LIU, Q., University of Toronto, Toronto, Canada, liuqy@physics.utoronto.
ca
Lithospheric Structures of the Central Cascadia Subduction Zone Resolved by
Full-waveform Inversion of Ambient Noise and Receiver Functions Nanqiao
Du1, Bin He2,3, Ting Lei1, Tianshi Liu1, Qinya Liu1,2 1 Department of Earth
Science, University of Toronto, Toronto, Canada 2 Department of Physics,
University of Toronto, Toronto, Canada 3 Department of Geosciences, theUniversity of Texas at Dallas, Richardson, TX, USA
The Cascadia subduction zone is one of the relatively young and warm
endmember subduction systems, mainly due to the subduction of the Juan
De Fuca plate underneath the North American Plate. Studies have shown thecomplex fluid migration processes in the crust and mantle while the tremor
activity could also be partly attributed to fluid migration in this region. In thisstudy, we aim to obtain high-resolution velocity structures of the crust andupper-mantle of this region based on full-waveform inversion. Particularly,
high frequency P receiver functions (P-RF) are sensitive to sharp discontinuities and velocity variations beneath dense seismic arrays, and ambient noisedata can be used to constrain fine-scale crustal structures. By using hybrid
spectral element method (FK-SEM), we jointly invert could combine the P-RF
waveforms and ambient noise cross-correlation data of the CASC93 array(Trehu et al., 1994) to obtain a detailed shear-wave velocity structure of thecentral Cascadia subduction Zone. Our model shows strong variations in thecrust and upper-mantle in the central Cascadia subduction zone, and may
further improve our understanding of the subduction and fluid migration
processes geodynamics in this region.
Reference
Trehu, A., Asudeh, I., Brocher, T. M., Luetgert, J. H., Mooney, W. D.,
Nabelek, J., & Nakamura, Y. (1994). Crustal architecture of the Cascadia
forearc. Science, 266(5183), 237-243.
poster 116
Ambient Noise Attenuation and Differential Adjoint
Tomography Applied to the Hongkou Linear Array Acrossthe Longmenshan Fault Behind the 2008 M 7.9 Sichuan
Earthquake
LIU, X., University of Hong Kong, Hong Kong, China, liuxine@hku.hk; LI,
H., China University of Geosciences Beijing, Beijing, China, lih@cugb.edu.
cn; BEROZA, G. C., Stanford University, California, USA, beroza@stanford.
edu; YANG, L., Chinese Academy of Sciences, Beijing, China, yanglei2@
mail.iggcas.ac.cn; ZHAO, G., University of Hong Kong, Hong Kong, China,
gzhao@hku.hk
The Longmenshan Fault is responsible for the 2008 M 7.9 Sichuan earthquake.
In this study, we investigate the structure of the thrust fault zone using amplitude and phase information derived from ambient seismic noise. We analyze
seismic noise data collected by a dense linear array of 51 3-C sensors acrossthe Longmenshan Fault Zone at Hongkou Town, which is approximately 28
km northeast of the epicenter of 2008 Sichuan earthquake and within 100 km
from the center of Chengdu, a metropolitan city with 16 million population.
We extract amplitude decay information from the noise interferometry functions across the linear array by finding different combinations of station triplets (Liu et al. 2021), which cancel the effects of noise sources and unknown
attenuation structure between the far-field noise sources and the linear array.
In addition, we perform phase velocity tomography and convert the phasevelocity map to S wave velocity in the top 5 km depth using Monte Carlo
Markov Chain (MCMC). The results delineate the thrust-fold fault structurenear Hongkou and suggest that the WFSD-1 drilling hole did not reach themain fault plane at Hongkou, which is situated further southeast and is associated with an asymmetric fault damage zone at ~1 km depth in the footwallof the Pengguan thrust fault. Our results agree with previous observations
from seismic reflection profiles, InSAR data and WFSD drilling holes along
the same line. Finally, we utilize ambient noise differential adjoint tomography (Liu et al. 2023) to improve velocity structure inversion, and the updated
results will be presented at the meeting.
poster 117
Validating Tomographic Models of Alaska Using 3D
Wavefield Simulations
MCPHERSON, A., University of Alaska Fairbanks, Alaska, USA,
ammcpherson@alaska.edu; TAPE, C., University of Alaska Fairbanks,

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Alaska, USA, ctape@alaska.edu; ONYANGO, E., University of Alaska
Fairbanks, Alaska, USA, eaonyango@alaska.edu; CHOW, B., University of
Alaska Fairbanks, Alaska, USA, bhchow@alaska.edu; PETER, D., ., Zurich,
Switzerland, daniel.b.peter@gmail.com
The EarthScope Transportable Array of seismic stations in Alaska and western
Canada peaked in 2017 and has provided excellent data coverage in Alaska
and western Canada, inspiring a wave of interest in the seismic structure of
Alaska. Seismologists have utilized ambient noise waveforms as well as bodywaves, surface waves, and arrival time data from local earthquakes to produce
several tomographic models that characterize the elastic structure (Vp, Vs) of
the region, and several of these models have been archived at the EarthScope
IRIS EMC for others to utilize. We have chosen five of these models of Alaska
to compare and contrast their utility for wavefield simulations and for generating Green’s functions for moment tensor inversions. We present synthetic
waveforms made in the software package SPECFEM3D_Globe in comparison
with recorded waveforms for a selected earthquake in Alaska. We then use thePython-based package MTUQ to perform moment tensor inversions using
Green’s functions generated in each of the five models. This testing will allow
us 1) to investigate the effects of 3D structure on moment tensor inversions
and 2) to carefully choose the best starting model for a future adjoint tomography study in Alaska.
poster 118
High-Resolution Surface Wave Tomography of the Hayward
Fault in the Berkeley Region Using Ambient Noise
Recorded by a Dense Nodal Array
MIAO, W., China Earthquake Administration, Beijing, China, miaowp@
cea-igp.ac.cn; QIU, H., China University of Geosciences, Wuhan, China,
qiuhongrui@cug.edu.cn; QIN, L., China University of Geosciences, Wuhan,
China, qinlei@cug.edu.cn
The ~70-km-long Hayward Fault (HF), capable of generating earthquakes
exceeding magnitude 6, poses a critical threat to major cities in California,
such as the San Francisco Bay area and Berkeley. Prior research revealed fault
zone head waves near the HF, indicating a bi-material interface with distinct
crustal blocks (slower P wave velocity on the eastern side). Clarifying if theentire HF is a continuous bi-material interface and obtaining a high-resolution crustal structure image surrounding the fault can greatly improve groundmotion predictions in nearby urban areas.
To better understand the Berkeley section of the HF, Taira et al. (2022)
deployed a 2-D dense nodal array across the campus of the UC Berkeley(UCB) and Lawrance Berkeley National Laboratory (LBNL). The dense
deployment consists of 182 three-component nodal sensors with an average
station spacing of ~100m and recorded continuously for about one month.
Preliminary analyses of the nodal array recordings indicate the potential forreconstructing clear surface waves from the ambient noise data. In this study,
we first reconstruct surface waves from ambient noise cross-correlation ofeach station pair. Then, Rayleigh wave group and phase velocity maps at different frequencies are constructed by inverting the picked travel times. Finally,
we obtain a high-resolution shear wave velocity model for structures acrossthe HF beneath the campus of UCB and LBNL in the top 15 km, by jointly
inverting the Rayleigh wave group and phase velocities. The resolved fault
zone image can improve our understanding of the HF in the Berkeley region.
poster 119
Computational Challenges of Large-Scale Numerical
Simulations and Full-Waveform Inversion Workflows
ORSVURAN, R., Colorado School of Mines, Colorado, USA, rorsvuran@mines.edu; NAGASO, M., Colorado School of Mines, Colorado, USA,masaru.nagaso@mines.edu; WANG, I., University of Texas at Austin, Texas,
USA, iwang@tacc.utexas.edu; PETER, D., King Abdullah University of
Science and Technology, Thuwal, Saudi Arabia, daniel.b.peter@gmail.com;
BOZDAG, E., Colorado School of Mines, , USA, bozdag@mines.edu
Parallel to the advances in HPC, computational requirements for seismic
imaging techniques have increased in order to obtain a higher spatial/temporal resolution in a numerical full-waveform modeling, and to utilize larger
databases of seismic events and multi-parameter inversions to improve theresolution of tomographic images, and our understanding of Earth’s interior
and dynamics. FWI workflows are well-defined involving numerical wave
simulations to compute synthetic seismograms and data sensitivities to model
parameters, pre-processing, and post-processing stages. However, different
scales and problems may need different treatment of data, parameterization of
the inverse problem, and model updates, potentially complicating the workflow. Moreover, improving the resolution of tomographic images, specifically

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large-scale inversions such as global-scale FWI, require dense computations
and high-volume and high-frequency I/O. Thus maximizing the benefits ofever increasing available seismic data and computational resources, whileharmoniously combining large and heterogeneous data in large-scale seismic
inversion workflows, is crucial to obtain a high resolution and accurate tomographic images which is still a scientifically and technically challenging topic.
In this research, we focus on continental and global FWI workflows on
CPU and GPU architectures, specifically to address storage and I/O bottlenecks in large-scale numerical simulations with the SPECFEM3D packages(i.e., large seismic and computational data, specifically attenuation snapshotsin adjoint simulations, etc.) towards exascale computing. We will present
our results and current efforts on data compression and asynchronous I/O
to reduce the required storage size and I/O bandwidth. The research is supported by the NSF funded SCOPED project and simulations and the tests are
performed on Texas Advanced Computing Center’s Frontera system.
poster 120
Homogenization of Sedimentary Basins for the Simulationof Lithological Site Effects
RAPENNE, M., Université de Lorraine, Nancy, France, marius.rapenne@
univ-lorraine.fr; CUPILLARD, P., Université de Lorraine, Nancy, France, paul.
cupillard@univ-lorraine.fr; GOUACHE, C., Caisse Centrale de Réassurance,
Paris, France, cgouache@ccr.fr
With the constant increase of computational power, the numerical modellingof lithological site effects can now handle 3D, geologically complex settings.
However, a computational overburden is reached when, e.g., uncertainties haveto be quantified. A possible pathway towards decreasing the cost of seismic
wave simulations in complex media is the non-periodic homogenization. Thismethod is known to provide accurate effective media for wave propagation. In
this work, we apply it to 2D sedimentary basins and explore its efficiency andaccuracy in terms of amplification simulation. Two homogenization strategies
are investigated: the Backus’ one, which considers the geological medium as a
juxtaposition of 1D profiles, and the more general 2D homogenization, which
involves the resolution of a partial differential equation. Using various velocity contrasts and geometries, we emphasize cases which require the generalhomogenization for an accurate modelling of amplification effects.
poster 121
Rapid 3D Green’s Functions Using Reduced-Order Modelsof Physics-Based Seismic Wave Propagation Simulations
REKOSKE, J. M., University of California, San Diego, California, USA,jrekoske@ucsd.edu; MAY, D. A., University of California, San Diego,
California, USA, dmay@ucsd.edu; GABRIEL, A. A., University of California,
San Diego, California, USA, algabriel@ucsd.edu
Elastodynamic Green’s functions are essential in seismology, and form aconnection between direct observations of seismic waves and earthquake
sources. They are key to enabling various seismological tasks, including
physics-based ground motion prediction and kinematic or dynamic source
inversions. In regions with comparably well-constrained 3D models of the
Earth’s elastic structure, such as Southern California, approximate 3D Green’s
functions can be computed using physics-based numerical simulations ofseismic wave propagation. However, these simulations are computationallyexpensive, which presents a challenge for real-time ground motion prediction (e.g., ShakeMap and ShakeAlert), physics-based probabilistic seismic
hazard assessment (PSHA, e.g., CyberShake), and uncertainty quantification
in source inversions. Here, we address this challenge by using a reduced-ordermodel (ROM) which enables rapid computation of approximate Green’s functions by using the proper orthogonal decomposition combined with radialbasis function interpolation. We train the ROM using three-component seismograms for six elementary moment tensors, computed with SeisSol, selecting 500 source locations to calculate 1.0 Hz elastodynamic Green’s functions
for approximately 10,000 sites in Southern California. Using leave-one-out
cross-validation, we assess the accuracy of our Green’s functions for the SCEC
CVM-S4.26-M01 velocity model in both the time domain and frequency
domain. We show that the ROM can accurately and rapidly reproduce simulated seismograms for generalized moment tensor sources in our 3D region,
as well as kinematic sources by using a finite fault model of the 1987 Mw 5.9
Whittier Narrows earthquake as an example. In these demonstrators, the accuracy is quantified using the mean absolute error of the velocity waveforms and

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the Fourier amplitude spectra. We envision that our rapid Green’s functions
would be useful for physics-based PSHA, improving the uncertainty quantification in earthquake source inversions, and constructing rapid ShakeMovies
with high spatial resolution.
poster 122
Comparison of Fundamental Fault Green’s Functions (GFs)
Computed Using Frequency-Wavenumber and FiniteDifference (SW4) Techniques for 1D Velocity Models
SAIKIA, C. K., Air Force Technical Applications Center, Florida, USA,chandanksaikia@gmail.com; ZHOU, R., Air Force Technical Applications
Center, Florida, USA, rongmao.zhou@us.af.mil; MODRAK, R. T., Los Alamos
National Laboratory, New Mexico, USA, rmodrak@lanl.gov
It has been noted that use of the green’s functions (GFs) computed using thethree-dimensional (3D) codes such as SW4 and SPECFEM3D produce morereliable moment-tensor solutions compared to those when the GFs of the onedimensional (1D) models are used. However, none of the studies explored if
the GFs computed by the 3D and 1D are similar when they are computedfor the same 1D velocity models. In this study, we have used the Dirac andGaussian source time function in SW4 to compute regional seismograms up
to 6Hz for one 1D model. We used three 1D codes, namely the Filon_AS-03,
FK_PROG, and zengSAIKIA to compute high-frequency seismograms, ensuring that the wavenumber domain discretization is small enough to reduce thespatial aliasing in the synthetics. The 1D codes uses the delta function as thesource time function. To establish the source time equivalence, fo (the frequency parameter) needed to be set quite high (say about 20Hz) especiallywhen the Gaussian source function is implemented. In this study, we will illustrate the equivalence high-frequency SW4 seismograms with those computed
using the 1D code for the fundamental faults except for those computed forthe 45o dipping dip-slip (DD) fault. For seismograms to be similar in amplitude for this fault, the corresponding moment-tensor elements have to be 2
time larger than those that are required by the 1D codes. This also involves
the Mxy component, but the contribution from this component is many order
lower than other moment-tensor elements, especially for the surface receivers.
poster 123
A Sparse Fault Parametrization for Large-scale Ruptures
Based on Moment Tensor Interpolation
THURIN, J., University of Alaska Fairbanks, Massachusetts, USA, jthurin@
alaska.edu
Modeling and characterizing earthquake sources can be challenging when
they fall outside the point-source approximation. Typical finite fault models
assume that the rupture surface can be represented as a discretized planar fault
or a combination of planes, segmented into discrete patches. This assumption requires committing to a specific fault plane geometry and discretization
before performing inversion. To address this limitation, we propose a sparse
yet robust fault representation that leverages the geometrical properties ofthe moment tensor, based on tensor interpolants and procedural surfaces.
This approach enables the representation of slip surfaces with a few key point
sources rather than an entire discrete surface and dynamically adjusts thediscretization density for numerical modeling. We show that spherical linear
interpolation is a natural interpolant function for moment tensors and showcase a preliminary application: the interpolant function is used to redistributepoint sources from a pre-existing sparse rupture model to obtain a denser
fault discretization, which we then use as a smooth source for waveform modeling, demonstrating interest for both the forward and inverse problem.

Advancements in Forensic Seismology and Explosion
Monitoring
Oral Session • Thursday 2 May • 8:00 am PacificConveners: Richard A. Alfaro-Diaz, Los Alamos National
Laboratory (rad@lanl.gov); Louisa Barama, Lawrence
Livermore National Laboratory (barama1@llnl.gov); Jorge A.
Garcia, Sandia National Laboratories (jgarc26@sandia.gov);

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Carl Tape, University of Alaska Fairbanks (ctape@alaska.
edu); Cleat Zeiler, Nevada National Security Site (ZeilerCP@
nv.doe.gov)
Seismology in Support of Negotiation, Implementation,
and Verification of Nuclear Test Ban Treaties and Science
Diplomacy: Where It Started and DOS R&D Challenges
JIH, R., U.S. Government, Washington, USA, jihrs@state.gov
In the late 1950s, scientists, diplomats, and policy makers recognized that
improved seismological knowledge and capabilities were crucial for the detection and identification of underground nuclear explosions. The Eisenhower
Administration initiated a comprehensive research and development programin seismology, known as Project Vela Uniform, based on the recommendations of the Berkner Panel Report filed by top national experts in seismology.
From the Vela program’s inception, DoD entities led by DARPA, developed
the technical basis for all U.S. test ban treaty negotiations. In 1994, DoD transferred the programmatic and funding responsibility for Applied Seismological
R&D to DOE, with the understanding that DOE would establish an applied
nuclear explosion monitoring (NEM) program at national laboratories, while
continuing to support academia and industrial communities through openand-full competitions.[1] In parallel to these major DoD and DOE efforts,
there was a small, yet operations-centric program at the former Arms Control
and Disarmament Agency and then later at the Department of State, focusing
on prompt transition of products to operations, for advancing national andinternational arms control verification goals, as well as for assessing compliance with nuclear test ban treaties and commitments. The seismic portion of
DOS “verification research” reached peak in 2018-2021. Central to this seismic research program was region-specific geophysical calibration research,which was highlighted as a national priority in a 2019 OSTP policy report. In
this talk, I describe how U.S. seismic research activities have evolved over the
decades, how the DOS-funded projects augmented major nuclear monitoring R&D and operational efforts through international cooperative activities,
often called “science diplomacy”, and how DOS is seeking a sustainable solution to move forward in this fiscally challenging environment and time.
[1] John Keliher (Director, Nonproliferation and National Security,DOE) memo to John Deutch (Deputy Secretary of Defense), April 22, 1994.
Three-dimensional Nonlinear Calculations of Explosions at
the Novaya Zemlya Nuclear Test Site
STEVENS, J. L., Leidos, California, USA, jeffry.l.stevens@leidos.com;
O’BRIEN, M. S., Leidos, California, USA, michael.s.obrien@leidos.com
We performed a series of three-dimensional nonlinear finite element calculations to model explosions at the former Soviet Novaya Zemlya nuclear testsite. We organized all the available data from Novaya Zemlya explosions,
including depth, topography and yield information. Many of these events are
multiple simultaneous explosions. We performed calculations for six multiple
events at the Northern Novaya Zemlya test site and five events at the Southern
Novaya Zemlya test site. The Northern Novaya Zemlya test site has steep
topography, so we performed equivalent calculations in a flat topography forcomparison. The Southern Novaya Zemlya test site is nearly flat, so topography is not an issue, however these events are strongly affected by tectonic
release, and are in an area of compression. We performed calculations withand without compressive tectonic stresses. From each of the calculations, we
generated surface waves, full waveform regional seismograms and far-fieldbody waves. We collected all the available seismic data from the calculated
events and remeasured all of the surface wave magnitudes. We find that without tectonic stresses, the calculated surface waves are larger than the observed
surface waves, but when compressive prestress is included the calculated surface waves are close to the observed values. Multiple simultaneous explosions
also generate Love waves and non-isotropic Rayleigh waves. Multiple explosions may cause more surface wave variability than topography. Down goingP-waves are almost unaffected by either topography or tectonic release. The
reflected pP phase is distorted by topography which can reduce interferencewith the initial P-wave. Multiple explosions cause small but distinct variability
in the P-waves at higher frequencies.
Discriminating Collapses From Explosions and Earthquakes
WALTER, W. R., Lawrence Livermore National Laboratory, California,
USA, walter5@llnl.gov; PASYANOS, M. E., Lawrence Livermore National
Laboratory, California, USA, pasyanos1@llnl.gov; ICHINOSE, G., Lawrence
Livermore National Laboratory, California, USA, ichinose1@llnl.gov; PRICE,
A., Lawrence Livermore National Laboratory, California, USA, price54@

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llnl.gov; PENNINGTON, C., Lawrence Livermore National Laboratory,
California, USA, pennington6@llnl.gov; RODD, R., Lawrence Livermore
National Laboratory, California, USA, rodd2@llnl.gov
The sudden collapse of an underground cavity produces seismo-acoustic signals that may potentially identify these events and discriminate them from
explosions and earthquakes. In moment tensor space these collapses are modeled as gravity driven closing cracks (e.g. Bowers and Walter, 2002; Chiang etal., 2018, Pasyanos et al., 2023). Using body waves, they may show less highfrequency energy than nearby earthquakes and explosions (e.g., Walter et al.,2018). The creation of cavities with the potential for collapse can follow frommining activities or underground nuclear explosions, making understanding
their source an important part of geophysical nuclear test monitoring. The
conditions leading to a possible cavity collapse vary with geology and depth.
During the historic period (prior to 1993) of nuclear testing at the former
Nevada Test Site (now the Nevada National Security Site), collapses following explosions were common as documented in Springer et al. (2002). The
collapse following the September 2017 North Korean announced nuclear testis the best documented case at other nuclear testing locations (e.g. Wang etal., 2018).
To better understand and identify collapses as a unique source type weare examining a set of several dozen collapses following nuclear tests fromthe 1970’s and 1980’s in southern Nevada. We are comparing these collapse
events with recent chemical explosions that were part of the Source Physics
Experiments (SPE - e.g., Snelson et al., 2013), which have helped provide
insight into how explosions generate shear waves (e.g., Pyle and Walter, 2022).
We want to understand how much of the relative lack of high frequency energy
observed in the historic Nevada collapse ATRISCO and the 2017 North
Korean collapse studied in Walter et al. (2018) is due the shallow nature of thecollapse source occurring in lower velocity materials, and how much may be
due to the gravity driven collapse mechanism itself. As part of this work, we
also plan to compare the nuclear explosion cavity collapses with those frommining areas at different depths and geologies, in various parts of the world.
Source Characterization and Uncertainty Quantification of
the North Korean Nuclear Tests 2006-2017
ALFARO-DIAZ, R. A., Los Alamos National Laboratory, New Mexico, USA,
rad@lanl.gov; KINTNER, J. A., Los Alamos National Laboratory, New Mexico,USA, jkintner@lanl.gov; PHILLIPS, S., Los Alamos National Laboratory,
New Mexico, USA, wsp@lanl.gov; DELBRIDGE, B., Los Alamos National
Laboratory, New Mexico, USA, delbridge@lanl.gov; CARMICHAEL, J. D.,
Los Alamos National Laboratory, New Mexico, USA, joshuac@lanl.gov
We introduce a novel and transportable technique to determine yield anddepth of burial from seismic source spectra of underground nuclear explosions. We demonstrate the application of the technique on the six declared
North Korean nuclear tests. This approach derives source spectra in absolute units for regional phase (Pg) amplitudes by correcting observations for
spreading, attenuation, and site amplification. This approach stands out as aninnovative use of broad-area propagation models, making it transportable andacross various geologic settings. The method is applicable in situations withmultiple or limited station observations where depth of burial is unknown.
We present new independent estimates of absolute yield and depth of burial
consistent with prior assessments, underscoring the potential of this method
in enhancing nuclear explosion monitoring capabilities and transportability
Regional Characterization of Natural and Anthropogenic
Seismic Events for Monitoring Efforts With Machine
Learning
BARAMA, L., Lawrence Livermore National Laboratory, California, USA,
barama1@llnl.gov; KONG, Q., Lawrence Livermore National Laboratory,
California, USA, kong11@llnl.gov
Seismic monitoring and event characterization provides useful information
about seismic events to assist in earthquake emergency response and for international monitoring efforts of explosions and nuisance events. In this presentation, we expand on the efforts of Barama et al. (2023) and Kong (2022) for
explosion discrimination at regional distances using data from both digitaland historical (formerly-analog) seismograms, including the full waveforms,
initial seismic phase arrivals, their derivative products like radiated earthquake
energy, coda wave envelopes, and phase-ratios. Using both seismograms andphysics-based features we trained regional seismic source classifiers, testing
approaches of a Convolutional Neural Network (CNN), Random Forest (RF),and Deep Neural Net (DNN) for both per-event (network) and per-station
predictions. We anticipate that machine-learning models we developed canSeismological Research Letters

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be robust tools for both regional characterization and gaining insight on what
drives the models’ prediction determinations.
Source-Type Discrimination Using Phase and Amplitude
Metrics Derived From Nonlinear Alignment Methods
RAMOS, M. D., Sandia National Laboratories, New Mexico, USA, mdramos@
sandia.gov; TIBI, R., Sandia National Laboratories, New Mexico, USA, rtibi@
sandia.gov; EMRY, E. L., Sandia National Laboratories, New Mexico, USA,elemry@sandia.gov; YOUNG, C. J., Sandia National Laboratories, New
Mexico, USA, cjyoung@sandia.gov
Seismic monitoring agencies rely on metrics to distinguish event class (i.e.,source type discrimination) to inform earthquake hazard or treaty compliance,
depending on stakeholder interest. Conventional discriminant approaches arerooted in fundamental, physics-based differences in the source properties, but
waveform path complexity can effectively erase higher frequency signal characteristics. In this study, we explore a combination of new methods for seismic
signal discrimination, dynamic time warping (DTW) and the elastic shapeanalysis of curves (ESA). DTW focuses on phase differences whereas ESA
separates both phase and amplitude signal variations using a novel transformation applied to functional data. We demonstrate the ability to distinguishunderground point-sources using synthetic waveforms calculated for a realistic Earth model and various source mechanisms. We then apply these tools
to recorded events in the Korean Peninsula, which include declared nuclear
explosions, a collapse event, and naturally occurring earthquakes. We compare DTW, ESA, and P-to-Lg amplitude ratio analysis (Tibi, 2021) to demonstrate the limitations and effectiveness of novel signal space metrics for source
discrimination.
Seismic Observations and Aftershock Analysis from a Fully
Coupled Chemical Explosion in Layered TuffSPRINKLE, D., Pacific Northwest National Laboratory, Washington,
USA, parker.sprinkle@pnnl.gov; ST. CLAIR, J., Pacific Northwest National
Laboratory, Washington, USA, james.stclair@pnnl.gov; CHOJNICKI, K.,
Pacific Northwest National Laboratory, Washington, USA, kirsten.chojnicki@
pnnl.gov; KNOX, H., Pacific Northwest National Laboratory, Washington,
USA, hunter.knox@pnnl.gov; STRICKLAND, C., Pacific Northwest National
Laboratory, Washington, USA, christopher.strickland@pnnl.gov; FELDMAN,
J., Pacific Northwest National Laboratory, Washington, USA, josh.feldman@
pnnl.gov; BOWMAN, D., Sandia National Laboratories, New Mexico,USA, dbowma@sandia.gov; BAL, A., Sandia National Laboratories, New
Mexico, USA, akbal@sandia.gov; ROBEY, E., Sandia National Laboratories,
New Mexico, USA, rerobey@sandia.gov; YOUNG, B., Sandia National
Laboratories, New Mexico, USA, byoung@sandia.gov; TURLEY, R., Nevada
National Security Sites, Nevada, USA, turleyrs@nv.doe.gov; WHITE, R.,
Nevada National Security Sites, Nevada, USA, whiterl@nv.doe.gov
On October 18, 2023, as part of the Low-Yield Nuclear Monitoring Program(LYNM), a multi-organization research team executed a fully coupled underground chemical explosion in Aqueduct Mesa on the Nevada National
Security Site (NNSS). Experiment objectives were to investigate both prompt
and non-prompt source and signal propagation signatures of underground
explosions. To this end, measurements were recorded using a variety of geophysical sensors including geophones, accelerometers, seismometers, anddistributed acoustic sensing (DAS), among several other sensing modalities.
Signatures of elastic deformation were recorded across spatial scales from 10sof meters out to greater than 100 kilometers.
Here, we focus on the data collected within the tunnel complex where
the experiment was conducted and at surface ground zero (i.e., the mesa surface) restricting our analysis to radial distances of ~ 1.5 kilometers. Our worktargets explosion source signature and the numerous aftershocks recorded by
the multi-modal sensing network. Regarding the explosion source signature,
we compare in-tunnel and surface recordings on both geophones and accelerometers, as well as comparison of co-located measurements across the different modalities (i.e., DAS and accelerometers). We compare our measurements
to pre-experiment predictions of ground motion and strain rate. Additionally,
we report on aftershock magnitudes, Omori decay rate, frequency content,
and productivity to compare with pre-experiment predictions and aftershock
sequences from previous underground explosions and natural earthquakes.

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Seismic Source Parameters and Scaling Relations for
Microseismic Lower-Yield Military Explosive EventsMILBURN, T. W., US Army Corps of Engineers, Mississippi, USA,troy.w.milburn@usace.army.mil
The ability to determine and assign a magnitude to a small microseismic
lower-yield military explosive event can be advantageous in characterizing its
source. This process involves the determination of its seismic moment which
can be accomplished by modeling the ground motion’s spectrum. However,the question remains as to whether the models available for earthquake simulation apply to much smaller ground motions from sources other than earthquakes. In this study, Brune source models are fitted to actual small groundmotions from military explosive events using the Stochastic Method Modeland the source parameters are determined for these events. The seismic waves
generated by these lower-yield military explosions were recorded by a local
network of seismometers/geophones for twenty-one events collected at two
different distances. In addition to acquiring the source parameters for theseground motions, an investigation into their scalability and compliance with
self-similarity laws for earthquake source relations is also investigated.
Discriminating S-Wave Polarization Angles of Explosiveand Earthquake Sources
NELSON, P., Los Alamos National Laboratory, New Mexico, USA, pln@
lanl.gov; CREASY, N., Los Alamos National Laboratory, New Mexico, USA,
nmcreasy@lanl.gov
Distinguishing whether a recorded seismic event is an earthquake or explosion is a core problem in explosion monitoring. In a 1D flat layer model,
earthquakes produce a predictable S-wavefield based off their radiation pattern while an explosion source will not produce a direct S-wavefield. However,observations from nuclear tests have shown they can produce significant S
wave energy on both the radial and transverse components. In this study,
we perform 2D and 3D numerical experiments using SPECFEM (2D and
GLOBE) to better constrain the conditions in which an S-wavefield generated from an explosion might differ from one sourced from an earthquake.
We demonstrate that anomalies in rigidity and anisotropic parameters near
the source can cause an explosion to produce a large S-wave field. The key
to producing an S-wavefield is that the wavelength of heterogeneities mustbe smaller than the wavelength of the wavefield and extremely close to thesource. The S-wave radiation pattern is highly sensitive to the source’s proximity to the anomalies and moving the source sightly can produce a significantly
different pattern. We do not observe the same high sensitivity near source
structure has on far-field S-wave radiation pattern for earthquake sources. P-S
ratios of explosive source change as a function of frequency and near source
anomality size while earthquakes P-S ratios remain constant. Lastly, we compare our synthetic observations to S-wave polarization measurements that we
made on nuclear tests conducted at the Nevada National Security Site andnearby earthquakes. S-wave polarization angles depend on the ratio of energy
the incoming wave has on the radial and transverse components. Our initial
results show that we can makestable measurements of the S-wave polarization angles for earthquakes as a function of frequency. We have also measured
explosion S-wave polarization angles, but the measurements are not so common nor as robust. This method might prove useful for discriminating eventsof interest which have clear S-waves. LA-UR-24-20147
Simulations of Local Wave Propagation Effects on the
Performance of P/s Source Discriminant
PITARKA, A., Lawrence Livermore National Laboratory, California, USA,pitarka1@llnl.gov; WALTER, W. R., Lawrence Livermore National Laboratory,
California, USA, walter5@llnl.gov; PYLE, M., Lawrence Livermore National
Laboratory, California, USA, pyle4@llnl.gov
Analysis of seismic records of local earthquakes and a series of undergroundchemical explosions conducted during the Source Physics Experiment (SPE)at the Nevada National Security Site have shown that at local distances (<200km) the effectiveness of the single-station P/S ratio source discriminant isreduced, especially when seismic recordings from a sparse network of stations
is used.
We used high performance computing to simulate high-frequency(0-10Hz) waveforms of the recorded SPE-5 underground chemical explosion
and one local earthquake for a network of seismic stations in the Yucca Flat,
and a series of simulations of collocated isotropic and double-couple explosion sources in the Rock valley, to investigate the effects of source radiation
and wave scattering effects on the simulated waveforms and P/S source discriminant at local distances. The wave propagation scattering was simulatedwww.srl-online.org•

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by using the Yucca Flat Geological Framework Model (GFM) with correlated
small-scale stochastic perturbations.
The inclusion of correlated depth-dependent stochastic velocity perturbations in the GFM, improved the quality of simulated source radiation andlocal waveforms, which resulted in better reproduction of the observed spatial
variations of the P/S discriminant. We found that the shallow wave scattering deforms the radiation pattern and amplitude of source generated P and S
waves, thus reducing the efficiency of the P/S discriminant. Our simulations
suggest that a good azimuthal stations coverage and the network averaging can
improve the overall performance of the P/S discriminant at local distances.
Moment Tensor Inversion and Its Uncertainty from Green’s
Functions with Different Algorithms
ZHOU, R., Air Force Technical Applications Center, Florida, USA, rongmao.
zhou@us.af.mil; SAIKIA, C. K., Air Force Technical Applications Center,
Florida, USA, chandan.saikia@us.af.mil; ROMAN-NIEVES, J., Air Force
Technical Applications Center, Florida, USA, jorge.roman-nieves.1@us.af.mil;
VANDEMARK, T. F., Air Force Technical Applications Center, Florida, USA,thomas.vandemark.1@us.af.mil
Moment tensor inversion (MTI) has been routinely used by the seismology
community to study the characteristics and the identification of source types
for earthquakes and explosions. MTI has been further used to quantify uncertainty surfaces associated with each event type obtained by the moment tensor
decomposition. In this study we are investigating uncertainties resulted due tothe use of Green’s Functions (GFs) computed by the frequency wavenumber
integration and finite difference techniques for the same velocity model. Our
focus here is to investigate the isotropic moments, especially for the explosions at the Nevada Test Site. To this end, we are investigating effects of the
GFs computed allowing the velocity models to have random fluctuations in
the geophysical parameters. We are focusing on the estimating the uncertainties in each source type of the decomposed mechanism that is mainly due tothe uncertainties in velocity models using a Monte Carlo approach. We arealso attempting to compare the MTI solutions with those determined by usinga grid-search technique for the double-couple (DC) mechanism. For explosion sources, we perform a linear-inversion for the seismic moments of theDC, isotropic and compensated linear vector dipole (CLVD) sources for eachpossible DC mechanism to minimize the misfit between the synthetic andobserved waveforms.
Physics Experiment 1: Chemical Explosive, Gas Tracer,
Electromagnetic, and Atmospheric Experiments for
Improved Monitoring of Nuclear-Explosive Testing
MYERS, S., Lawrence Livermore National Laboratory, California, USA,myers30@llnl.gov; FOXE, M., Pacific Northwest National Laboratory,
Washington, USA, michael.foxe@pnnl.gov; DZENITIS, B., Lawrence
Livermore National Laboratory, California, USA, dzenitis1@llnl.gov; KNOX,
H., Pacific Northwest National Laboratory, Washington, USA, Hunter.
Knox@pnnl.gov; CARI SEIFERT, C., Pacific Northwest National Laboratory,
Washington, USA, carolyn.seifert@pnnl.gov; FAST, J., Pacific Northwest
National Laboratory, Washington, USA, james.fast@pnnl.gov; MACLEOD,
G., Los Alamos National Laboratory, New Mexico, USA, macleod@lanl.
gov; ALGER, E., Lawrence Livermore National Laboratory, California,
USA, alger5@llnl.gov; BROOME, S., Sandia National Laboratories, New
Mexico, USA, stbroom@sandia.gov; STRICKLAND, C., Pacific Northwest
National Laboratory, Washington, USA, Christopher.Strickland@pnnl.
gov; BOWMAN, D. C., Sandia National Laboratories, Washington, USA,
dbowma@sandia.gov; FRITZ, B., Pacific Northwest National Laboratory,
Washington, USA, Bradley.Fritz@pnnl.gov; BOUKHALFA, H., Los Alamos
National Laboratory, New Mexico, USA, hakim@lanl.gov; WHARTON, S.,
Lawrence Livermore National Laboratory, California, USA, wharton4@llnl.
gov; WHITE, R., Nevada National Security Site, Nevada, USA, whiterl@
nv.doe.gov; TURLEY, R., Nevada National Security Site, Nevada, USA,
TurleyRS@nv.doe.gov; LAINTZ, K., Los Alamos National Laboratory, New
Mexico, USA, laintz@lanl.gov; TAFOYA, A., Los Alamos National Laboratory,
New Mexico, USA, tafoya_a@lanl.gov; BODMER, M., Sandia National
Laboratories, New Mexico, USA, mabodme@sandia.gov; JOHNSON, C.,
Pacific Northwest National Laboratory, Washington, USA, christine.johnson@
pnnl.gov; TAGUBA, C., Pacific Northwest National Laboratory, Washington,
USA, chad.taguba@pnnl.gov; EZZEDINE, S. M., Lawrence Livermore
National Laboratory, California, USA, ezzedine1@llnl.gov; DEKIN, W.,
Lawrence Livermore National Laboratory, California, USA, dekin1@llnl.gov;
LIPKOWITZ, P., Nevada National Security Site, Nevada, USA, lipkowpj@
nv.doe.gov; FALLINER, J., Sandia National Laboratories, New Mexico, USA,jlfalli@sandia.gov; MILLER, X., Nevada National Security Site, New Mexico,USA, MillerXD@nv.doe.gov; BROWN, B., Nevada National Security Site,

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Nevada, USA, BrownBS@nv.doe.gov; GAYLORD, J., Lawrence Livermore
National Laboratory, California, USA, gaylord2@llnl.gov; WOOD, L., PacificNorthwest National Laboratory, Washington, USA, Lynn.Wood@pnnl.gov
The challenge of monitoring low-yield nuclear explosions is being met by the
National Nuclear Security Administration (NNSA) and the national laboratories through improved understanding and utilization of multi-physics signals generated by explosions and other sources. These research efforts develop
full-physics simulation capability, new sensing methods, and advanced data
analysis. All these efforts are based on and validated by experimental data.
Legacy data, including historic nuclear detonations, provide critical information, but data gaps persist. The Physics Experiment 1 (PE1) fills data gaps witha series of non-nuclear experiments at and near the Nevada National Security
Site (NNSS) Aqueduct Mesa P-tunnel. Taken as whole, PE1 experiments generate seismic, acoustic, electromagnetic, and tracer gas signals similar to thosegenerated by nuclear detonations in varying underground emplacement andatmospheric conditions.
On October 18, 2023, PE1 Experiment A (PE1 A) commenced with
detonation of 16.3 tons (TNT equivalent) of chemical explosive in P-Tunnel.
In addition to shock-related signals, the detonation released gas tracers andchemical-explosive byproducts into the cavity formed by the explosion. Nearsource instrumentation in the grout confinement plug, nearby boreholes, andP-tunnel recorded the explosive shock, electro-magnetic waves, temperature,pressure, and real-time migration of gases from the explosion cavity. Seismic,
acoustic, and electromagnetic waves were also recorded by instrumentation
atop and around Aqueduct Mesa, at select sites within NNSS, and by regional
seismic networks. Clear signals were recorded by all sensor modalities, andseismic signals were recorded to at least 250 km. Gas tracers were detectedin boreholes and in P-tunnel within an hour after the explosive detonationand concentrations were monitored for several weeks. This presentation
will describe the PE1 experiment series, with emphasis on Experiment A.
Scientific objectives, field layout, execution, and plans for data dissemination
will be presented.
Seismo-Acoustic Signals From an Accidental Chemical
Explosion in South Korea
PARK, J., Southern Methodist University, Texas, USA, junghyunp@smu.
edu; ARROWSMITH, S., Southern Methodist University, Texas, USA,sarrowsmith@smu.edu; CHE, I., Korea Institute of Geoscience and Mineral
Resources, Daejeon, South Korea, che10@kigam.re.kr; HAYWARD, C.,
Southern Methodist University, Texas, USA, hayward@smu.edu; STUMP, B.,
Southern Methodist University, Texas, USA, stump@smu.edu
Seismo-acoustic analysis can be used to identify, detect, and locate sourcesthat generate waves in the atmosphere and solid Earth and provide a basis forthe characterization of distant phenomena, particularly explosions. On March
4, 2020, an accidental explosion occurred at a chemical plant in the southwestern city of Seosan in South Korea. The explosion generated both seismic andinfrasound signals, recorded by various sensors to distances as great as 300
km across the Korean Peninsula. Data included signals at six seismo-acoustic
arrays operated cooperatively by Southern Methodist University and Korea
Institute of Geoscience and Mineral Resources (KIGAM). Additional datafrom KSRS seismic array data from the Comprehensive Nuclear-Test-Ban
Treaty Organization and all available dense seismic network data were utilized. Nine infrasound sensors co-located at KSRS seismic arrays, three temporary infrasound arrays, and four infrasound stations operated by KIGAM
were also included in the analysis. Seismic, infrasound, and air-to-groundcoupled acoustic arrivals from the explosion are identified for this event basedon array processing and analyst review. A small number of secondary detections were identified that are consistent with the source location and may be
indicative of infrasound generated by the fire that followed the explosion by
a few minutes. Network back-projection using both seismic and infrasoundwaveforms is consistent with the ground truth location of the explosion.
Observed infrasound arrival times are well matched by ray tracing predictions using the Ground-to-Space atmospheric specification, with troposphericarrivals at the multiple arrays to the east of the source and no arrivals at thearray to the west. Lastly, the infrasound amplitudes from the explosion areused to estimate the source energy. The hybrid utilization of seismic and infrasound observations in the analysis enhances the confidence of source characterization for explosion monitoring.
Estimating Crustal Velocity Structure in Alaska From
Acoustic-to-Seismic Coupling From the 2022 Hunga
Eruption, Tonga
MACPHERSON, K. A., University of Alaska Fairbanks, Alaska, USA,kamacpherson@alaska.edu; FEE, D., University of Alaska Fairbanks, Alaska,

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USA, dfee1@alaska.edu; COFFEY, J. R., University of Alaska Fairbanks,
Alaska, USA, jrcoffey@alaska.edu; AWENDER, S., University of Alaska
Fairbanks, , USA, sawender@alaska.edu; CHOW, B., University of Alaska
Fairbanks, Alaska, USA, bhchow@alaska.edu; DELAMERE, S., University of
Alaska Fairbanks, Alaska, USA, swdelamere@alaska.edu; HANEY, M. M., U.S.
Geological Survey, Alaska, USA, mhaney@usgs.gov
The 2022 climactic eruption of the Hunga volcano in the Kingdom of Tonga
generated broadband acoustic waves that were clearly observed over 10,000
kilometers away at numerous pressure sensors in Alaska. The University of
Alaska Fairbanks and the Alaska Volcano Observatory operate over 150 stations in the state that are equipped with a single infrasound sensor, a colocated broadband seismometer, and a colocated barometer. The arrival ofhigh-amplitude acoustic energy from the eruption at a regional network ofcolocated sensors provides a unique opportunity to examine acoustic-toseismic coupling and to use these observations to estimate shallow elastic
parameters in the Alaska region. We compute coherence between pressureand vertical seismic channels between 0.01 Hz and 2 Hz for all available colocated sites in Alaska and observe network-wide peaks and troughs in coherence. Notable troughs occur at around 0.2 Hz, and to a lesser extent, at 0.075
Hz. We interpret these troughs as interference imposed by the secondary andprimary microseismic peaks on the relatively low-amplitude seismic signal
from Tonga coupling. We compute coupling coefficients from seismic overacoustic amplitude ratios in passbands with high coherence, allowing us torelate acoustic-seismic coupling to bulk elastic parameters at different maximum crustal depths. We compare our results to existing shear-wave velocity estimates in Alaska, and observe good agreement, particularly for a depthof approximately two kilometers. Mean shear-wave velocity estimates fromthese derived elastic parameters provide an empirical dataset for investigating
seismic site effects, station-specific velocity corrections, and augmenting Vs30
estimates for ground-motion modeling.
This work was supported by the Nuclear Arms Control Technology(NACT) Program at Defense Threat Reduction Agency (DTRA). Cleared for
Release.
Detection of Seismic and Acoustic Signals With Serial
Network Data Fusion: Demonstration Against Atmospheric
Explosions
CARMICHAEL, J. D., Los Alamos National Laboratory, New Mexico, USA,joshuac@lanl.gov; ALFARO DIAZ, R., Los Alamos National Laboratory, New
Mexico, USA, rad@lanl.gov; LIGHT, T., Los Alamos National Laboratory,
New Mexico, USA, tlavezzi@lanl.gov; BLOM, P. S., Los Alamos National
Laboratory, New Mexico, USA, pblom@lanl.gov; GAMMANS, C., Los Alamos
National Laboratory, New Mexico, USA, cgammans@lanl.gov; DELBRIDGE,
B. G., Los Alamos National Laboratory, New Mexico, USA, delbridge@lanl.
gov; CARR, C., Los Alamos National Laboratory, New Mexico, USA, cgcarr@lanl.gov; BEGNAUD, M., Los Alamos National Laboratory, New Mexico,USA, mbegnaud@lanl.gov
Explosion monitoring conventionally operates in siloes: seismic, infrasonic,
and other ground or space based sensors process individual modalities toperform functions like detection. Such siloed detection excludes evidencecollected by other modalities that may be leveraged to achieve greater detection rates, lower nuisance alarms, and lower thresholds. Work conducted at
Los Alamos National Laboratory seeks to increase detection performance byremoving these siloes to facilitate data fusion.
We thereby present a proto-type system to fuse multiple explosionsourced (“target” sourced) modalities into a serial architecture that sharesdetector output and makes collective (system-wide) decisions regarding
source identity. The system shares this data by coupling the thresholds of its
constituent detectors. Decisions made by one detector then inform a downstream detector, which processes a second modality. This downstream detector then adjusts its threshold according to the decision made by the upstream
detector. Our system selects the coupling strength between these thresholds
to achieve a maximum system-wide true positive rate and maintain an acceptable, system-wide false positive rate. The resulting system-wide detector
achieves a superior performance relative to that of the best, constituent detector. We present these performance characteristics on a real data recorded froman explosion sourced on the US East Coast.
Our system thereby exploits the theory of distributed detection(Viswanathan et al., 1988), which has been exploited in multiple sensor networks. It remains under-leveraged in explosion monitoring. If successfully
demonstrated in explosion monitoring scenarios, we argue that such systems
can provide a non-incremental gain to monitoring capability that mimics the
teamwork that of humans at the analyst-review stage of processing.

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Surface-to-Space Acoustic Propagation Model Validation
Using Chemical Explosion Sources: The DARPA AtmoSense
AIRWaveS Project
NAYAK, M., Defense Advanced Research Projects Agency, Virginia, USA,michael.nayak@darpa.mil; SNIVELY, J. B., Embry-Riddle Aeronautical
University, Florida, USA, snivelyj@erau.edu; SABATINI, R., Embry-Riddle
Aeronautical University, Florida, USA, sabatinr@erau.edu; BOWMAN, D.
C., Sandia National Laboratories, New Mexico, USA, dbowma@sandia.gov;
EGAN, S., Energetic Materials Research and Testing Center, New Mexico,USA, sasha.egan@emrtc.nmt.edu
Surface explosions of sufficient size create acoustic waves capable of propagating hundreds to thousands of kilometers. These waves can be detected
and characterized by ground and balloon borne microbarometers, pulsed
Doppler radar soundings of the lower ionosphere and, in exceptional cases,
ionospheric total electron content (TEC) derived from GNSS signals. While
this capability has been demonstrated for higher yield explosions, the threshold of detectability for smaller events is still uncertain. This ambiguity motivates targeted field campaigns against events of known yield. The combinationof well-understood sources with a sensing network of large horizontal andvertical aperture permits robust assessment of acoustic propagation models
and constraint on the spatial distribution of wave fields. Here we describe
an acoustic signal recording campaign planned for Spring 2024, leveraging
multiple sensing modalities, aimed at a set of surface chemical explosions incentral New Mexico as part of Phase II of the DARPA AtmoSense program.
The observations will be compared to model simulations, supporting theirvalidation extending from sources, to acoustic propagation, and ultimately
to alternate remote sensing modalities including measurements of the lower
ionosphere. The objective is to validate whole-atmosphere (surface-to-space)acoustic propagation modeling capabilities, including estimates of uncertainty
and syntheses of multiple sensor observables. We also welcome other participants to the next active-source campaign, currently planned for Fall 2024, on
a minimal interference basis. SNL is managed and operated by NTESS under
DOE NNSA contract DE-NA0003525.
Solid/atmosphere Moment Partitioning in Hypervelocity
Impacts on Mars From Seis Recorded Seismic and Acoustic
Signals and High Resolution Crater Imaging.
LOGNONNÉ, P. H., Université Paris Cité, Paris, France, lognonne@ipgp.
fr; BILL, C., Imperial College, London, United Kingdom, c.bill23@imperial.
ac.uk; COLLINS, G. S., Imperial College, London, United Kingdom,g.collins@imperial.ac.uk; DAUBAR, I. J., Brown University, Rhode Island,
USA, ingrid_daubar@brown.edu; KIM, D., Imperial College, London, United
Kingdom, doyeon.kim@imperial.ac.uk; FERNANDO, B., Johns Hopkins
University, Maryland, USA, bfernan9@jh.edu; FROMENT, M., Université
Paris Cité, Paris, France, mfroment@ipgp.fr; GARCIA, R., Institut Supérieurede l’Aéronautique et de l’Espace, Toulouse, France, raphael.garcia@isaesupaero.fr; KAWAMURA, T., Université Paris Cité, Paris, France, kawamura@
ipgp.fr; LARMAT, C., Los Alamos National Laboratory, New Mexico, USA,
carene@lanl.gov; PANNING, M. P., Jet Propulsion Laboratory, California
Institute of Technology, California, USA, mark.p.panning@jpl.nasa.gov;
POSIOLEVA, L., Malin Space Science Systems, California, USA, posiolov@
msss.com; MILJKOVIC, K., University of Curtin, Curtin, Australia, katarina.
miljkovic@curtin.edu.au; ROUGIER, E., Los Alamos National Laboratory,
New Mexico, USA, erougier@lanl.gov; XU, Z., Université Paris Cité, Paris,
France, zongboxu@ipgp.fr; LEI, Z., Los Alamos National Laboratory, New
Mexico, USA, zlei@lanl.gov
The SEIS VBB sensor detected 10 confirmed impacts on Mars, documented byboth the seismic signal and the high-resolution imaging of the formed crater.
For about half of them, a chirp in the seismic signal was also detected, which
was generated by the ground shaking generated by infrasounds generated by
the impact. At several detected impact sites, high resolution images show the
imprint of the blast with a notable occurrence on Sol 1094, dated 12/24/2021,
marking the largest impact detected by the InSight mission.
The seismic source is constrained by the amplitude of seismic bodywaves, or surface waves for S1094b, and the imaged crater diameter. The
acoustic source is constrained by the amplitude of indirect infrasounds andthe imaged diameter of the blast zone. This allows two different estimations ofthese two sources: the first is the one acting on the ground, therefore associated with the seismic source while the second is acting just above the surface
therefore associated with the acoustic source, each being expressed by seismic or acoustic moment, respectively. Comparing the seismic and acoustic
moments for those confirmed impacts will provide the first estimation of theenergy partitioning between ground and air for high velocity impacts on Mars,
characterized by speeds and energies furthermore never recorded on Earth.

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We present here preliminary results of this analysis made with different
seismic and hydrocode modeling and discuss the impact of seismic scattering, lateral variations, subsurface structure and atmospheric attenuation in
our estimations of the seismic and acoustic moments and associated energy/
moment partitioning.
End-to-End Numerical Simulation of Explosion Cavity
Creation, Cavity Circulation Processes, Subsurface Gas
Transport, and Prompt Atmospheric Releases
EZZEDINE, S. M., Lawrence Livermore National Laboratory, California,
USA, ezzedine1@llnl.gov; VELSKO, C., Lawrence Livermore National
Laboratory, California, USA, Velsko1@llnl.gov; VOROBIEV, O., Lawrence
Livermore National Laboratory, California, USA, vorobiev1@llnl.gov
A numerical study of conjugate flow, heat and mass transfer by natural convection of noble gases within an underground cavity partially filled with molten rock is presented. The molten rock is initially considered at rest at an initial temperature and concentration. The molten rock is viscous and possesses
strength that is temperature, and crystal fraction dependent. Under natural
conditions, convection cells are developed within the molten rock leading tocirculation, mixing and degassing of the initially trapped gases. Furthermore,
the molten rock as well the degassing enhances the conjugate convection
flow in the air gap within the cavity. We illustrate the onset of the different
regimes and their combined effect of flow, heat and mass transport of different gas species, the fraction of molten rock and their impact on the noble
gas fractionation. We also present a sensitivity analysis of the effect of theouter cavity boundary condition on the heat loss and cooling to the adjacentrock formation and its eventual release to the atmosphere. We demonstrate
several scenarios of underground prompt releases to the atmosphere using
a first-ever fully coupled prompt subsurface-to-atmospheric transport without ad-hoc boundary conditions between physics-based domains, or handshakes between different numerical codes. We are exploring physics informed
ML schemes for developing surface responses of the end-to-end simulation
framework to anthropogenic explosions.
This work performed under the auspices of the U.S. Departmentof Energy by Lawrence Livermore National Laboratory under Contract
DE-AC52-07NA27344.
Joint Inversion of Body and Surface Waves at the RockValley Direct Comparison (Nevada) Study Site
SYRACUSE, E. M., Los Alamos National Laboratory, New Mexico, USA,syracuse@lanl.gov; ROWE, C., Los Alamos National Laboratory, New
Mexico, USA, char@lanl.gov; LI, D., Los Alamos National Laboratory, New
Mexico, USA, davidzli@lanl.gov; RANASINGHE, N., Los Alamos National
Laboratory, New Mexico, USA, ranasinghe@lanl.gov
The Rock Valley Direct Comparison project (RVDC - Phase III of the Source
Physics Experiment) is centered on conducting a large chemical explosion that is co-located with the source region of the unusually shallow 1993
Rock Valley earthquake series in southern Nevada. The goal is to improvethe understanding of similarities and differences among signals produced by
explosions in comparison to shallow natural events, by minimizing locationand path variables.
As part of this experiment, we are developing a Vp, Vs, and density
model for the RVDC site and surrounding region, through the joint inversion of seismic body wave arrivals, ambient-noise-based Rayleigh wave dispersion measurements, and gravity anomalies. This model will serve multiple
purposes. It will be used to constrain material properties in the RVDC source
region. It will aid in the analysis of both legacy observations from the 1993
series and the upcoming chemical explosion. Seismicity between 1993 andthe present will be relocated in the model, which will be used to identify fault
locations and orientations, building knowledge of the tectonics of the studysite and of the broader Nevada National Security Site (NNSS).
Joint Inversion Using Waveform, First-motion Polarities
and InSAR Deformation for the 2007 Crandall Canyon Mine
Collapse, Utah
CHI-DURÁN, R., University of California, Berkeley, California, USA,
rodrigo.chi@berkeley.edu; DREGER, D. S., University of California, Berkeley,
California, USA, ddreger@berkeley.edu; RODGERS, A., Lawrence Livermore
National Laboratory, California, USA, rodgers7@llnl.gov; LINDSAY, D.,
University of California, Berkeley, California, USA, danielle.lindsay@berkeley.
edual., 2008). Ford et al. (2008) modeled regional waveforms for the full moment
tensor finding the event consisted of a primary vertical collapsing crack and asecondary near-vertical shear at the western edge of the collapse. Significant
deformation after the event was also measured using Interferometric
Synthetic Aperture Radar (InSAR) (e.g., Lu and Wecks, 2010; Planttner etal., 2010). Recently, joint source-type inversions have been used to analyze
underground North Korean nuclear explosions, combining regional waveform data, first-motion polarity, and InSAR deformation (Chi-Durán et al.,2021). This technique is effective at improving source type estimates, independently constraining location (and depth), and reducing uncertainties inscalar moment. Our joint inversion for the Crandall Canyon Mine Collapse
identified the event as principally a closing crack, with a waveform variance
fit of 60%, first-moment polarity fit of 45% and a line-of-sight deformation
fit of 90%. Our joint inversion results are consistent with previous studies ofthis event, providing better constraints of the source-type, moment tensor andscalar moment. These results together with those for the 4th and 6th DPRK
explosions (e.g. Chi-Durán et al., 2021, 2024) show the ability to distinguish
explosions and collapses, which in the past have been problematic for traditional discrimination methods (e.g. Walter et al., 2018).

Advancements in Forensic Seismology and Explosion
Monitoring [Poster Session]
Poster Session • Thursday 2 May
Conveners: Richard A. Alfaro-Diaz, Los Alamos National
Laboratory (rad@lanl.gov); Louisa Barama, Lawrence
Livermore National Laboratory (barama1@llnl.gov); Jorge A.
Garcia, Sandia National Laboratories (jgarc26@sandia.gov);
Carl Tape, University of Alaska Fairbanks (ctape@alaska.
edu); Cleat Zeiler, Nevada National Security Site (ZeilerCP@
nv.doe.gov)
poster 124
Moment Tensor Estimation and Uncertainty Quantification(MTUQ)THURIN, J., University of Alaska Fairbanks, Massachusetts, USA, jthurin@
alaska.edu; MODRAK, R., Los Alamos National Laboratory, New Mexico,USA, rmodrak@lanl.gov; MCPHERSON, A., University of Alaska Fairbanks,
Alaska, USA, ammcpherson@alaska.edu; RODRÍGUEZ-CARDOZO, F.,
University of South Florida, Florida, USA, felixr1@usf.edu; BRAUNMILLER,
J., University of South Florida, Florida, USA, jbraunmiller@usf.edu; DING,
L., University of Toronto, Toronto, Canada, liangding86@gmail.com; LIU, Q.,
University of Toronto, Toronto, Canada, liuqy@physics.utoronto.ca; TAPE, C.,
University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu
Accurately estimating seismic source parameters is crucial to understanding awide range of geophysical phenomena, from natural seismic events to anthropogenic activities. Seismic moment tensors, together with point forces, canrepresent a variety of source mechanisms and be estimated using seismic data.
Here, we present the latest developments in our open-source Moment Tensor
and Uncertainty Quantification (MTUQ) code, tailored for point source characterization, with an emphasis on uncertainty estimation and visualization.
We showcase the code’s capabilities by revisiting the DPRK nuclear test of
September 2017 to evaluate the influence of various data sources on the misfit space, both using a conventional grid-search approach and leveraging thefast Covariance Matrix Adaptation Evolution Strategy (CMA-ES) method. We
also demonstrate point-force inversion capabilities on a recent rock and ice
avalanche on the Barry Glacier. MTUQ takes advantage of high-performancecomputing architectures, accommodates a wide range of Green’s function
databases (both 1D and 3D and receiver side Strain Green’s Function), andoffers various optimization strategies that are adapted to different computational resource scenarios, from single-core CMA-ES optimization to largescale grid searches with up to 1,000,000,000 grid points. We underscore theimportance of accurate seismic source parameter estimation and the significant role MTUQ can play as a versatile and reliable tool in this essential aspectof seismology. New users can engage with active users and developers via
workshop resources and research projects.

On August 6, 2007, a major underground collapse at the Crandall Canyon coalmine in Utah caused a 3.9 local magnitude (ML) earthquake (Pechmann etVolume 95•

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poster 125
Observations on Explosion-Triggered Seismic Events via
Fiber Optic Sensing at Small Scales
BESKARDES, G. D., Sandia National Laboratories, New Mexico, USA,gdbeska@sandia.gov; YOUNG, B., Sandia National Laboratories, New Mexico,USA, byoung@sandia.gov; STANCIU, C., Sandia National Laboratories,
New Mexico, USA, astanci@sandia.gov; BAKER, M. G., Sandia National
Laboratories, New Mexico, USA, mgbaker@sandia.gov
We present an aftershock analysis on seismic events recorded by distributed
acoustic sensing (DAS) fiber following a series of chemical explosive experiments at the Blue Canyon Dome (BCD) on the grounds of the Energetic
Materials and Testing Center (EMRTC) located approximately 6 km west ofSocorro, NM. These experiments were a series of eight identical small (~4.5
MJ) chemical explosive sources detonated in a borehole at different depths (<~55 m) and emplacement conditions, ranging from virgin rock to areas of varied a priori subsurface damage. We additionally performed each experimentboth with and without filling the borehole with water. Here, we investigate
both the presence of aftershocks induced by explosive sources on the DAS
fiber data and characteristic differences in the aftershock sequences resulting
from different emplacement conditions. Both the number of aftershocks andtheir distributions in time and space may provide information regarding how
chemical explosive sources’ thermochemical energies are spent and converted
to seismic waves.
DAS provides much higher spatial sampling density than traditional
sensing methods, capturing seismic wavefields with considerably greater coverage and enabling detection of smaller events at close-in distances throughtrace-to-trace correlation. We visually detect aftershocks on the fiber waveforms for each chemical explosive source. Our apparent seismic velocity estimations find seismic velocities consistent with the rock velocities in the study
area suggesting that the detected events are real aftershocks. Moreover, theexplosion-triggered aftershocks follow Omori’s decay law for wet explosive
sources but results are less clear for dry sources. Observations of aftershocks
from the experiments at BCD demonstrate the utility of DAS to contribute toour understanding of explosion-induced aftershocks.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 126
Leveraging Infrasound Signals for Integration of Groundand Space-Based Nuclear Explosion Monitoring
Capabilities
BLOM, P. S., Los Alamos National Laboratory, New Mexico, USA, pblom@lanl.gov; BISHOP, J., Los Alamos National Laboratory, New Mexico, USA,jwbishop@lanl.gov; GAMMANS, C., Los Alamos National Laboratory,
New Mexico, USA, cgammans@lanl.gov; CARMICHAEL, J. D., Los Alamos
National Laboratory, New Mexico, USA, joshuac@lanl.gov; DELBRIDGE,
B., Los Alamos National Laboratory, New Mexico, USA, delbridge@lanl.gov;
NELSON, P., Los Alamos National Laboratory, New Mexico, USA, pln@lanl.
gov; BEGNAUD, M., Los Alamos National Laboratory, New Mexico, USA,mbegnaud@lanl.gov
Nuclear detonation detection is typically conducted via analysis of a combination of phenomenologies including seismic, infrasonic, hydroacoustic, airsampling, and satellite-based observations (e.g., light, gamma ray, x-ray, neutron). The ground-based components of such monitoring systems are idealfor detecting and characterizing below-ground and near-surface explosions
while space-borne sensors can reliably detect and characterize nuclear explosions in the atmosphere. Recent research at Los Alamos National Laboratory
has focused on developing and improving physical and statistical frameworks
to better integrate and communicate information between these individual
phenomenologies for near-surface and atmospheric nuclear explosions.
Specifically, infrasound source models for supersonic sources in the atmosphere have been developed and evaluated to distinguish infrasonic signaturesfrom such sources compared with point source explosion sources. Ray-based
weakly non-linear waveform analysis has been utilized to construct infrasonic detection statistics and investigate coupling of infrasonic energy in theimmediate footprint of the airburst to the seismic surface wave field. Theseand other aspects of this ongoing effort to integrate ground- and space-based
nuclear explosion monitoring capabilities will be presented.

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Seismological Research Lettersposter 127
Influence of Local 3-D Structure at Degelen Test Site on
Short-Period Teleseismic P-Wave via Reciprocal Hybrid
Modeling
BURGOS, G., CEA, DAM, DIF, Arpajon, France, gael.burgos@cea.fr;
GUILLOT, L., CEA, DAM, DIF, Arpajon, France, laurent.guillot@cea.fr
The large historical Blacknest Kazakhstan dataset, including undergroundnuclear tests conducted at the Degelen test site, provides a valuable resourcefor exploring how structural effects in the immediate vicinity of the source arecarried over at teleseismic distances.
It shows significant differences in the recorded waveforms across four
arrays (EKA, GBA, WRA, YKA), up to 2 Hz frequency. The rugged topography of the Degelen mountain range and its heterogenous crust should serve
as a marker for source parameters identification (location, depth, magnitude),through the scattering of the incident P-wave at the free surface.
We investigated these source properties using a hybrid modeling methodology to simulate the the teleseismic wavefield between the Degelen region
and the 4 arrays. It is based on a reciprocal coupling of the DSM solver, forthe 1-D Earth background wavefield, and the SEM solver, for the 3-D complex Degelen area. This coupling approach ensure the generation of full Greentensor waveforms throughout the Degelen area and accurate up to 2 Hz
frequency.
poster 128
Far-Field DAS Recordings of a Chemical Explosion
ST CLAIR, J. T., Pacific Northwest National Laboratory, Washington,
USA, james.stclair@pnnl.gov; CHOJNICKI, K., Pacific Northwest National
Laboratory, Washington, USA, kirsten.chojnicki@pnnl.gov; SPRINKLE, P.,
Pacific Northwest National Laboratory, Washington, USA, parker.sprinkle@
pnnl.gov; ELY, J., Pacific Northwest National Laboratory, Washington, USA,james.ely@pnnl.gov
On October 18, 2023 an underground chemical explosion was detonated at
the P Tunnel of the Nevada National Security Site (NNSS). The experimentused a broad suite of sensors to detect the motion the of chemical explosion. Part of the ground motion network included a past DAS fiber deployment
located approximately 14 km southeast of P Tunnel. Helically wound fiberwith a 60-degree wrapping angle was installed two vertical boreholes (E80and SW80) at the Dry Alluvium Geology (DAG) site during Phase II of the
Source Physics Experiment in 2018. During the 2023 experiment, a Silixa
Carina interrogator was used to record DAS measurements in the 385m deep
E80 hole. Data were sampled at 1kHz with a 2-meter gauge length and 1 meterchannel spacing. Starting at approximately 3.1 seconds after the explosion wasdetonated several upcoming wave phases are observed followed by a trainof surface waves. This observation is consistent with predictions made prior
to the experiment. This is the first time that DAS has been used to monitor
chemical explosion experiments at a distance greater than a few 100 meters.
We present a comparison of the predicted strain-rates and travel-times to themeasured data.
poster 129
Capturing the Spatial Variation of Seismic Observations in
SW4 Simulations of the Dry Alluvium Geology Experiment
Series at the Nevada National Security Site
SAXENA, S., Pacific Northwest National Laboratory, Washington,
USA, swasti9226@gmail.com; ST CLAIR, J., Pacific Northwest National
Laboratory, Washington, USA, james.stclair@pnnl.gov; SPRINKLE, P., PacificNorthwest National Laboratory, Washington, USA, parker.sprinkle@pnnl.
gov; CHOJNICKI, K., Pacific Northwest National Laboratory, Washington,
USA, kirsten.chojnicki@pnnl.gov; KNOX, H., Pacific Northwest National
Laboratory, Washington, USA, hunter.knox@pnnl.gov; SCHROM, B., PacificNorthwest National Laboratory, Washington, USA, brian.schrom@pnnl.gov
Improving predictive capabilities of seismic sources at varied distance andenergy length scales is crucial to understanding whether or how the nearfield geologic complexities influence seismic wavefield propagation. This presentation aims to illustrate simulation of ground motions induced in the Dry
Alluvium Geology (DAG) experiment (Mission Support and Test Services,
LLC, 2021) series in Yucca Flat to explore the effects of a diverse lithological composition and topographic features on the spatial variability of groundmotion from chemical explosions. Numerous investigations in the past have
utilized dense seismic arrays to explore the spatial variability of earthquake
ground motion (SVEGM), highlighted by variations in amplitude and phaseamong recordings from the same earthquake at diverse locations within a specific region. One of the most significant large-scale experiments to identify

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the behavior of SVEGM was carried out on natural seismic sources in Lotung,Taiwan (Abrahamson, 1992). A similar large-scale study on anthropogenic
seismic sources was carried out for events in the well characterized geology of
Yucca Flat at the Nevada National Security Site during the DAG experiment.
Simulation of the observed ground motions at DAG will be carried out in
SW4, a finite difference numerical code developed for seismic wave propagation by Lawrence Livermore National Laboratory. Finally, the accuracy of thephysics-based chemical explosion model will be presented by comparing thesimulated ground motions with the recordings from the DAG site. The ultimate goal of a precise model is to identify gaps in the instrumentation scheme
for future explosion experiments.
poster 130
Time-Variable Moment Tensor Inversion of Seismic andSeismoacoustic Data at the Source Physics Experiment
Phase II: Dry Alluvium Geology
DARRH, A., Sandia National Laboratories, New Mexico, USA, adarrh@
sandia.gov; BERG, E. M., Sandia National Laboratories, New Mexico, USA,eliberg@sandia.gov; PRESTON, L. A., Sandia National Laboratories, New
Mexico, USA, lpresto@sandia.gov; POPPELIERS, C., Leidos, Florida, USA,christian.poppeliers.ctr@us.af.mil
Seismic source inversions that assume each component of the moment tensor has the same underlying source time function (STF) are often unable toaccurately categorize the complexity of a source as it evolves in time. However,a full-waveform, time-variable moment tensor inversion, where each component of the moment tensor is independently allowed to vary in time, allows
for a better understanding of the dynamics of a source. One such example
of a complex source that is difficult to accurately represent with a conventional moment tensor would be an explosion, followed by slip on near-source
joints. When a single STF is assumed for all components, this may instead
be approximated as solely an explosion source or a double couple source,
oversimplifying the source mechanisms involved. If instead a time-variable
moment tensor inversion was used, these two mechanisms can be differentiated in time and space. In this study, we apply a time-variable moment tensor
inversion to seismic and seismoacoustic data recorded as part of the Source
Physics Experiment Phase II: Dry Alluvium Geology (DAG). We develop a
joint inversion to invert the seismic and infrasound waveform data from theDAG-4 experiment for the six independent, time-variable components of the(subsurface seismic) moment tensor, as well as a vertical force function, a termthat approximates the surface spall source. We plot the source mechanism as afunction of time on the fundamental lune to better interpret how the DAG-4
source changes with time. Additionally, we compare the seismic and seismoacoustic moment tensor results, estimating the sensitivity of both the seismicand seismoacoustic inversion formulations to the moment tensor and verticalforce function results to gain a better understanding of how the addition of
infrasound data in a joint inversion framework can affect our interpretation ofa source. SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 131
Exploring Paired Neural Networks to Rapidly Characterize
Aftershock Events
EMRY, E. L., Sandia National Laboratories, New Mexico, USA, elemry@sandia.gov; DONOHOE, B., Sandia National Laboratories, New Mexico,USA, bdonoho@sandia.gov; TIBI, R., Sandia National Laboratories, New
Mexico, USA, rtibi@sandia.gov; YOUNG, C. J., Sandia National Laboratories,
New Mexico, USA, cjyoung@sandia.gov; RAMOS, M., Sandia National
Laboratories, New Mexico, USA, mdramos@sandia.gov; CONLEY, A., Sandia
National Laboratories, New Mexico, USA, acconle@sandia.gov
Mainshocks and their aftershock sequences occur unexpectedly and increase
the burden of seismic analysts. Cross-correlation methods show promise fordetecting aftershocks but require careful curation of template libraries, which
is challenging for in-progress sequences. Also, cross-correlation methods are
more computationally intensive, in comparison to use of pre-trained, deeplearning models. We explore the effectiveness of using a paired neural network (PNN) to identify similar earthquakes, such as aftershocks. The PNNs
were trained to recognize similar earthquake pairs from a global dataset ofreal earthquakes augmented with different levels of background noise. We
test the PNNs with a suite of closely-controlled test datasets, including a subset of high-quality aftershock templates with their cross-correlation matches(Emry et al., 2023), a dataset of highly similar event pairs from China (Schaff
and Richards, 2021), and a dataset of synthetic waveforms created with a 1-dVolume 95•

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velocity model. This approach allows us to discern where the existing PNN
models succeed and where they struggle, with the goal to understand whether
PNN models may be trained differently to better generalize to in-progress
aftershock sequences. This Ground-based Nuclear Detonation Detection(GNDD) research was funded by the U.S. Department of Energy. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.
poster 132
A New Tool to Integrate Instrument Responses From
Seismological Databases Into Python Workflows
GAMMANS, C., Los Alamos National Laboratory, New Mexico, USA,
cgammans@lanl.gov; MACCARTHY, J. K., Los Alamos National Laboratory,
New Mexico, USA, jkmacc@lanl.gov
Instrument response files referenced and stored in CSS3.0, KBCore, and similarly structured databases follow a file format that predates the release of the
CSS3.0 database schema in 1990, and these response files are often referred
to as pazfir files. Pazfir files have changed slightly since 1990, with the mostrecent definition having been released in 2002 by the International Data
Centre (IDC), and they are primarily used within the explosion monitoring
community. However, the wider seismological community uses the RESP and
StationXML formats released by the FDSN, and open-source tools, such as
ObsPy, support these FDSN formats but not pazfir files, making them difficult
to incorporate into modern workflows. A pazfir file reader has been developed to ingest response information available from the appropriate databasetables, read in the file with some basic QC, and output an ObsPy Response
object. The Response object can then be attached to waveforms extracted fromthe database, allowing researchers to use ObsPy’s response removal functions either to return a waveform in units of ground motion or pressure or toincorporate it into a StationXML file. This pazfir reader will allow researchers to fully retrieve and incorporate data and metadata from these databases
into Python workflows or file formats usable by community-supported tools
through its inclusion in Pisces (https://github.com/LANL-Seismoacoustics/
pisces) an open-source python package available on GitHub from Los Alamos
National Laboratory that was developed to facilitate the integration of datafrom CSS3.0 and KBCore databases into Python-based geophysical analysis
workflows.
poster 133
Ambient Seismic Noise Tomography of Heterogeneous
Geological Formations
GOCHENOUR, J. A., Nevada National Security Sites, Nevada, USA,gochenja@nv.doe.gov; ZEILER, C. P., Nevada National Security Sites, Nevada,USA, ZeilerCP@nv.doe.gov; BILEK, S., New Mexico Tech, New Mexico, USA,susan.bilek@nmt.edu; LUHMANN, A. J., Wheaton College, Illinois, USA,
andrew.luhmann@wheaton.edu
Ambient seismic noise tomography is a unique tool suitable for characterizing
the velocity structure of various geologically complex regions. To demonstrate
this capability, we analyzed 30 days of vertical component short period seismic data from the karstic Santa Fe River Sink-Rise system in north-central
Florida. We applied power spectral density estimates and frequency-wavenumber analysis to characterize noise source biases in the tomography. We
then extracted Rayleigh wave group velocity dispersion measurements fromempirical Green’s functions estimated through phase cross-correlation andphase-weighted stacking. Finally, we inverted the dispersion measurements
at various periods, yielding a model of the aquifer’s seismic velocity structure. Our results reveal layering with varying group velocities aligning with apriori hydrostratigraphic knowledge. Notable findings include the base of theaquifer and dolostone semiconfining units characterized by elevated velocities
relative to the overall mean velocity. Furthermore, we identified low-velocity
upper layers likely expressing zones of extensive karstification. We demonstrate that ambient seismic noise tomography is a robust tool applicable forthe characterization and validation of the near-surface structure, including
physical properties, identification of unknown features, and the location andcontinuity of units. Additionally, we are applying the capabilities of ambient noise tomography and signal analysis to the Nevada National Security
Sites. Through this endeavor, we aim to enhance our knowledge of the site’s
subsurface velocity structure, contributing to a broader understanding ofgeological contexts with implications for various applications. This work
was done by Mission Support and Test Services, LLC, under Contract No.
DENA0003624 with the U.S. Department of Energy and the National Nuclear
Security Administration Office of Defense Nuclear Nonproliferation. DOE/
NV/03624--1843.

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poster 134
Using Deep Learning Models to Characterize Subsurface
Physical Parameters at Modeled Underground Chemical
Explosion Sources
HARDING, J. L., Sandia National Laboratories, New Mexico, USA, jlhardi@
sandia.gov; PRESTON, L. A., Sandia National Laboratories, New Mexico,USA, lpresto@sandia.gov; ELIASSI, M., Sandia National Laboratories,
New Mexico, USA, meliass@sandia.gov; GAUVAIN, S. J., Sandia National
Laboratories, New Mexico, USA, sjgauva@sandia.gov
The characterization of underground explosion sources is important for constraining seismic source features, such as yield and seismic moment. There islittle understanding, however, of how subsurface characteristics at the source,
such as emplacement or ground material (e.g., basalt, tuff, salt), affect theobserved far-field seismic waveforms (FFSWs) we record and analyze or the
methods through which we extract source features, such as source time function inversion. Additionally, it is not well studied how nonlinear phenomena
near the source are affected by varying subsurface characteristics, and in turn,
how these nonlinearities influence our often-linear source models. We present
work that explores how subsurface characteristics at the source affect FFSWs
by leveraging a nonlinear shock physics code coupled to a linear wave propagation code. Our methodology allows us to parametrically explore subsurface
characteristics and generate many synthetic seismic data sets at the local scale(distances < ~700 m). We vary source depth, chemical explosion size, andreceiver locations in addition to the physical properties at the source and somenonlinear modeling parameters.
We use our synthetic labeled data to train multiple deep neural networks(DNNs) to predict different subsurface characteristics that have been found tohave the greatest effect on the FFSWs, including source emplacement, groundmaterial, yield strength, and fracture pressure, and we explore different DNN
architectures to optimize results. We then leverage our trained DNNs to perform a sensitivity analysis that quantifies how the subsurface characteristics
affect the FFSWs. Once developed further, these DNN models can be used tobetter characterize explosion yield or moment by considering predicted nearsource characteristics.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 135
Comparing Observed and Modelled Station Terms from theSource Physics Experiments Phase 2 (Dry Alluvium
Geology) Explosions
HEYBURN, R., AWE Blacknest, Brimpton Common, United Kingdom,
ross@blacknest.gov.uk; GREEN, D., AWE Blacknest, Brimpton Common,
United Kingdom, dgreen@blacknest.gov.uk
Since 2011, a series of chemical explosions with a range of different depths
and explosive yields have been detonated at two sites on the Nevada National
Security Site (NNSS) to help further understanding of the seismic waves generated by underground explosions. In this study, P-wave amplitudes recorded
from explosions in the second phase of the Source Physics Experiments (SPE)
explosions at stations ranging from 2 km to around 36 km distance have been
analysed and compared with model predictions. The model seismograms werecomputed using a visco-elastic wave propagation code and a high resolution
3D Earth model of the NNSS. For comparison model seismograms are scaled
using two explosion source models, the Mueller-Murphy model and Denny
and Johnson model. In order to assess how effective the 3D Earth model was
at modelling path effects between the location of the explosions and the stations, a two-step inversion was carried out to estimate station and distanceterms for the stations used in this study for both the observed data and model
data scaled using both source models. Although there are some differences
between the observed and modelled station terms, in general there is reasonable agreement and one of the main features in the observed data, negative
station terms for stations at around 10 km distance from the location of thestations, is replicated in the model data. Distance terms which predict the falloff of amplitude with distance were also estimated for the observed and model
data and are found to be in good agreement.
poster 136
Comparisons Between Geophone Array and DAS Array
Detections
ICHINOSE, G., Lawrence Livermore National Laboratory, California, USA,ichinose1@llnl.gov
We applied an array-based detector on 14-days of continuously recorded
Distributed Acoustic Sensing (DAS) and co-located nodal geophone array

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Seismological Research Lettersdata. These data were repurposed from the 2016 PoroTomo experiment at
Brady’s Hot Springs, Nevada (e.g., Feigl et al., 2019). Since DAS is essentiallya single component seismometer, we used a time-domain delay and sum
technique modified to beamform only channels along linear portions of thefiber-optic cable with the highest coherency to measure the energy distribution in slowness space. The energies for each linear portion are then summed
together to produce a final slowness image. We applied a moving window
array detector on the geophone array using an optimal 1-3 Hz bandpass filter.
The optimal DAS bandpass filter was 0.5-2 Hz. DAS was poor at estimating
P- and S-wave BAZ and slowness compared to geophone array; however, wepredicted using synthetics that the DAS array selected has cable broadsidesensitivities. Future experiments using different fiber-optic cable geometries
should provide better BAZ estimates. A persistent night-time local noise
source toward the southwest was also observed by both geophone array and
DAS. We correlated the duration of the noise signals to pumping schedules at
the geothermal plant. Overall, the DAS and geophone array detection performance was similar over regional and teleseismic distances with the exceptionthat DAS has many more false detections. Prepared by LLNL under Contract
DE-AC52-07NA27344. LLNL-ABS-858924.
poster 137
Explosion Source Analysis and Discrimination FromRegional Distance Seismic Observations
KINTNER, J. A., Los Alamos National Laboratory, New Mexico, USA,jonas.kintner@gmail.com; PIPPIN, J., Los Alamos National Laboratory, New
Mexico, USA, jpippin@lanl.gov; ALFARO-DIAZ, R. A., Los Alamos National
Laboratory, New Mexico, USA, rad@lanl.gov; DELBRIDGE, B., Los Alamos
National Laboratory, New Mexico, USA, delbridge@lanl.gov; AMMON, C. J.,
Pennsylvania State University, Pennsylvania, USA, cja12@psu.edu
This study utilizes regional seismic observations to investigate earthquakes
and announced explosions in the Democratic People’s Republic of Korea(DPRK). We compute the coda spectral ratios and Relative Source Time
Functions (RSTFs) at common stations to isolate source information fromadditional path and site effects within the measurements. The resulting frequency-dependent amplitude ratios reflect source differences between thetwo seismic events, which can then be fitted with parametric models thatmap observations to seismic source parameters. In the case of the RSTFs, theresults also provide a time-domain representation of the source-time function. This work allows us to identify spectral differences between explosions
and nearby earthquakes. The measurements also agree with estimated earthquake and explosion source models for seismic events occurring at or near the
DPRK test site. We analyze parameter trade-offs in these models and quantify the bias associated with source parameter estimation. The coda spectral
ratios between explosions and earthquakes reveal that the explosive sources
exhibit lower S-wave corner frequencies and S-wave spectral amplitudes (athigh frequencies). These results show that a comparing spectra between different source types via spectral ratios provides valuable insights for seismic
discrimination and source characterization efforts.
poster 138
Inferring the Focal Depths of Small Earthquakes inSouthern California Using Physics-Based Waveform
Features
KOPER, K. D., University of Utah, Utah, USA, kkoper@gmail.com;
BURLACU, R., University of Uath, Utah, USA, burlacu@seis.utah.edu;
MURRAY, R., University of Utah, Utah, USA, rileymurray1324@gmail.com;
BAKER, B., University of Utah, Utah, USA, u6024448@gcloud.utah.edu; TIBI,R., Sandia National Laboratories, Utah, USA, rtibi@sandia.gov; MUEEN, A.,
University of New Mexico, Utah, USA, mueen@unm.edu
Determining the depths of small crustal earthquakes is challenging inmany regions of the world because most seismic networks are too sparse toresolve trade-offs between depth and origin time with conventional arrival
time methods. Precise and accurate depth estimation is important because
it can help seismologists discriminate between earthquakes and explosions,which is relevant to monitoring nuclear test ban treaties and producing earthquake catalogs that are uncontaminated by mining blasts. Here we examine
the depth sensitivity of several physics-based waveform features for ~8,000
earthquakes in southern California that have well-resolved depths fromarrival time inversion. We focus on small earthquakes (2 < ML < 4) recorded
at local distances (< 150 km), where depth estimation is especially challenging. We find that differential magnitudes (Mw/ML – MC) are positively correlated with focal depth, implying that coda wave excitation decreases withfocal depth. We analyze a simple proxy for apparent stress drop, log10(M0)+ 3log10(fc), and find that source spectra are preferentially enriched in highwww.srl-online.org•

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frequencies, or “blue-shifted”, as focal depth increases. We also find that two
spectral amplitude ratios, Rg,0.5-2 Hz/Sg,0.5-8 Hz and Pg/Sg at 3–8 Hz, decrease
as focal depth increases. Using multilinear regression with these features aspredictor variables, we develop models that can explain 11–59% of the variance in depths within 10 sub-regions and 25% of the depth variance acrosssouthern California as a whole. We suggest that incorporating these features
into a machine learning workflow could help constrain focal depths in regionsthat are poorly instrumented and lack large databases of well-located events.
The waveform features we evaluate in this study have previously been used assource discriminants and our results imply that their effectiveness in discrimination is partially because explosions generally occur at shallower depths thanearthquakes.
poster 139
Providing Data for Nuclear Explosion Monitoring—WFNE
Repository
OANCEA, V., Leidos, Virginia, USA, oanceavi@gmail.com; KUNG, Y.,
Leidos, Virginia, USA, yu-long.kung@leidos.com; MURPHY, J. R., Leidos,
Virginia, USA, john.r.murphy@leidos.com; PIRAINO, P. E., Leidos, Virginia,
USA, paul.e.piraino@leidos.com
Usage of a high-quality data set is a key element for any geophysical analysis.
The Waveforms From Nuclear Explosion (WFNE) is a comprehensive repository providing access to a large volume of information of potential interest to
the nuclear explosion monitoring community. It was developed and is maintained by Leidos under sponsorship of the Defense Threat Reduction Agency(DTRA). WFNE provides convenient access to source parametric data (origin, bulletin and other geophysical parameters) on all the 2,157 atmospheric,underground and underwater nuclear explosions detonated in the world
between 1945 and 2017, and to their associated waveforms and station/
instrument information, as collected from many sources. Distance domain
for waveforms ranges from local to teleseismic (0.8-179 degrees). Detailed
presentations of the test sites and detonations in each test site are provided as“Event Summaries”, including main results of studies and references.
WFNE is built as a trusted data set, starting from the previous datarepository “Nuclear Explosion Database (NEDB)” that was accessed in thepast by numerous users in the U.S. and international nuclear explosion monitoring community. Added information consists in a large volume of seismic,hydroacoustic and infrasound data collected from a variety of data sources,
including the results of recent efforts on rescue of pre-digital seismic data via
digitization. All data are collected from open sources; they are checked forcompleteness and quality and converted into a consistent format before being
merged into WFNE, offering easy access to a correct and well-organized dataset, ready to be used as input for research studies. Over 100,000 waveforms
ranging from digitized analog recordings for the oldest explosions to recent
International Monitoring System (IMS) data are included in WFNE. Data
continues to be collected from newly identified sources. Using web-based
access, users can search, visualize, and download data of interest for their own
research. Access request is available at: https://www.wfne.info/ .
poster 140
Investigating Shallow Subsurface Structure Near Legacy
Nuclear Test Sites Using Single Station HVSRMILLER, D. J., Sandia National Laboratories, New Mexico, USA, dmille4@
sandia.gov; BERG, E. M., Sandia National Laboratories, New Mexico,USA, eliberg@sandia.gov; PRESTON, L. A., Sandia National Laboratories,
New Mexico, USA, lpresto@sandia.gov; ABBOTT, R. E., Sandia National
Laboratories, New Mexico, USA, reabbot@sandia.gov
We investigate shallow subsurface structure near two legacy nuclear tests on
the Nevada National Security Site. In the first analysis, we use open-source
continuous seismic data collected from a single line of a temporary array
deployed for the Source Physics Experiment Phase I. For the second analysis,
we use continuous data collected as part of the active-source FREY experiment to investigate the HADDOCK legacy nuclear test. Shallow subsurface
structure is important for understanding seismic site response and detecting
subsurface anomalies. In this investigation, we focus on the use of ambient
noise-derived horizontal-to-vertical spectral ratios (HVSR) to highlight frequency-dependent site effects, shallow velocity profiles, and total H/V spectral
power. HVSR has several advantages, including repeatability, the need for only
short periods of data collection, and application to single-station, high frequency measurements, which are particularly sensitive to the shallowest layers. In this comparison, we test the ability of single-station HVSR to measurechanges in subsurface structure along a profile, and within an array, near twosites with potential structural features. We examine the correlation between a
new method using the integrated spectral power of H/V and traditional reso-

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nance and forward modeling-based approaches for H/V ratios. Using theseresults, we compare the feasibility of these methods for understanding shallow
structure using temporary seismic deployments at sites with potential shallow
heterogeneities.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 141
Detecting Subsurface Mining Activity using CrossCorrelation and Local Surface Arrays
MILLER, D. J., Sandia National Laboratories, New Mexico, USA, dmille4@
sandia.gov; BERG, E. M., Sandia National Laboratories, New Mexico, USA,eliberg@sandia.gov; MARCILLO, O., Oak Ridge National Laboratory,
Tennessee, USA, marcillooe@ornl.gov; CHAI, C., Oak Ridge National
Laboratory, Tennessee, USA, chaic@ornl.gov; CUNNINGHAM, E., Oak Ridge
National Laboratory, Tennessee, USA, cunninghamee@ornl.gov; MACEIRA,
M., Oak Ridge National Laboratory, Tennessee, USA, maceiram@ornl.gov;
AMMON, C. J., Pennsylvania State University, Pennsylvania, USA, cja12@
psu.edu; BOIE, K., Graymont Inc., Pennsylvania, USA, kboie@graymont.
com; MILLER, J. A., Graymont Inc., Pennsylvania, USA, jmiller@graymont.
com; QUICK, S., Graymont Inc., Pennsylvania, USA, squick@graymont.com
Detecting subsurface human and industrial activity from surface seismic
observations remains a challenging task. Using data from two mines, theRedmond Salt Mine in central Utah and the Pleasant Gap Limestone Minein central Pennsylvania, we test the extent to which we can identify, locate,and distinguish different human-generated seismic signals over different
mining subsurface structures and local geologies. The Redmond Mine wasinstrumented with a local surface array of 15 nodal seismometers over one
month in 2018. The Pleasant Gap Mine was instrumented with over 50 surface nodal seismometers over two month-long periods, one in the spring andanother in the fall of 2023. Because many anthropogenic signals are persistent,
rather than impulsive, we employ cross-correlation methods to characterize
and track these persistent signals over time. To locate the cross-correlation
signals, we implemented both array-based backprojection and single-station
polarization methods. However, we also observe impulsive signals related toblasting which we locate with traditional seismic methods. In general, we findthat anthropogenic signals at these mines are often periodic, distinct in frequency, characterized by their relative time of occurrence, and whether thesource location is stable. Between the two operations, we compare the effectsof site geology and structure, local noise levels, the density of observations,and proximity to presumed sources on the ability to understand these anthropogenic signals.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 142
Investigation of Full Moment Tensor Solutions for
Earthquakes and Announced Nuclear Tests at the
Punggye-Ri Test Site, DPRKOGDEN, C. S., AWE Blacknest, Reading, United Kingdom, cogden@
blacknest.gov.uk; SELBY, N., AWE Blacknest, Reading, United Kingdom,
neil@blacknest.gov.uk; HEYBURN, R., AWE Blacknest, Reading, United
Kingdom, ross@blacknest.gov.uk; NIPPRESS, S., AWE Blacknest, Reading,United Kingdom, stuart@blacknest.gov.uk
Event Screening is the rejection of the hypothesis that a seismoacoustic event
is generated by a single explosion source. There are several methods used toscreen events, including the ratio of body-wave to surface-wave amplitudes, theratio of high frequency P-wave to S-wave energy, and source depth. However,these methods may not screen all relevant events and so forensic seismologists have looked for additional approaches. The full moment tensor solution(MTS) resolves the six independent components of the source moment tensor,
and therefore fully characterises the source mechanism, including determining the proportion of deviatoric and isotropic energy released by a source.
However, complications arise from sources at shallow depths where themoment tensor inversion becomes underdetermined. Furthermore, explosions can generate deviatoric energy, complicating the MTS. Here, we use
the mttime inversion scheme (e.g., Chiang et al., 2021), utilising data from
IRIS, the International Data Centre (IDC) and recently published additional
datasets, to calculate MTSs for: six announced DPRK nuclear tests, the collapse event after DPRK6, and nearby earthquakes in the IDC Reviewed Event
Bulletin (REB). After tuning of station-specific time-shifts and velocity models, all six announced nuclear explosions have large positive isotropic components, with significant deviatoric components in their final MTSs, whereas
the collapse event has a large negative isotropic component. In contrast, theSeismological Research Letters

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earthquake MTSs have larger deviatoric components in comparison to isotropic. However, in all cases the compensated linear vector dipole component(volume expansion along a plane) is substantial, and solutions are not always
stable; small adjustments in the time shifts, velocity model and station distribution can produce highly variable seismic source interpretations. Thus, caremust be taken in determining the cause of a seismic source.
UK Ministry of Defence © Crown owned copyright 2024/AWE
poster 143
Relative Source Time Function Estimation, Applications to
the Source Physics Experiments
PIPPIN, J. E., Los Alamos National Laboratory, New Mexico, USA, jpippin@
lanl.gov; KINTNER, J. A., Los Alamos National Laboratory, New Mexico,USA, jkintner@lanl.gov; AMMON, C. J., Penn State University, Pennsylvania,
USA, cja12@psu.edu
The Source Physics Experiment (SPE) are a series of chemical explosion
experiments at the Nevada National Security Site (NNSS). SPE Phase-I (20112016) provided a wealth of dense, local- to regional-distance observations
suitable for characterizing shallow chemical explosions located within thesame borehole. SPE Phase-II (2018-2019) was emplaced in alluvium with adense array network in both linear profiles, borehole emplaced accelerometers
and a grid of geophones. We investigate the time-dependent source processesof each chemical explosion using relative source time function (RSTF) estimation. We characterize SPE Phase-I using data from five linear seismometer
profiles located between 100 and 2000 meters from the shot location. For SPE
Phase-II, we experiment with using surface and near-source borehole instrumentation within 100 meters to compute RSTF’s, this is due to complexitiesof the source medium and propagation. We attempt to reconstruct the relative
source time functions (RSTF) to improve the resolution of time-dependentsource processes utilizing the lower yield events in the series as the greenfunctions. The RSTF estimates do provide exceptional resolution to each
explosion’s time-history for SPE Phase-I. Preliminary modeling efforts suggest
these measurements may be useful for precise characterization of explosion
processes and spallation. Using the relative source time functions allow us toexpand our understanding of the SPE Phase-I and Phase-II explosion series.
Application of these techniques contributes to our understanding of source
physics and facilitates future efforts to additional seismic source experiments
and phenomenology.
poster 144
Transportability of a Convolutional Neural Network
Seismic Denoising ModelQUINONES, L. A., Sandia National Laboratories, New Mexico, USA,laquino@sandia.gov; TIBI, R., Sandia National Laboratories, New Mexico,USA, rtibi@sandia.gov
Machine learning algorithms typically follow the paradigm of training amodel on compiled datasets with characteristics of the type of data that themodel is designed to then evaluate. This has often led to model performance
problems when taking a previously trained model and attempting to utilize it
to evaluate a new dataset which differs in characteristics when compared tothe training dataset. This problem of model transportability is pronounced in
the field of seismology, as we typically train our machine learning models on
data specific to certain regions, networks, or time periods, which then experience significant performance drops when those models are utilized in otherregions. Here, we assess the transportability of our previously constructed
Multi-level Wavelet-based Convolutional Neural Network (MWCNN) seismic
denoising model and investigate whether techniques such as transfer learning may provide solutions to said transportability problems. The MWCNN
model was originally trained on earthquake and explosion data from the Utah
seismic region and will now be used to analyze data from the Nevada seismic network. To assess the degree to which transportability is an issue for
the MWCNN model we will first evaluate the denoising performance of the
Utah-trained model using data associated with the 2020 Monte Cristo Range,
Nevada, earthquake sequence. Then, we will compare the denoising capabilities of the Utah-trained MWCNN denoising model with that of a denoisingmodel trained exclusively on Nevada earthquake and explosion data to measure whether a performance gap exists and what its magnitude is. Lastly, ourgoal is to assess whether transfer learning techniques may provide an avenue
towards accounting for transportability issues by examining the denoising
performance of a model with weights initially assigned using Utah-based datathat is then further trained on data from the Nevada region.

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Gravity Mapping to Validate the Rock Valley Geological
Framework Model
RANASINGHE, N. R., Los Alamos National Laboratory, New Mexico, USA,ranasinghe@lanl.gov; ROWE, C., Los Alamos National Laboratory, New
Mexico, USA, char@lanl.gov; STANBURY, C., University of Washington,
Washington, USA, cstanbur@uw.edu
As part of the ongoing Source Physics Experiment, its third phase, known as
the Rock Valley Direct Comparison (RVDC) effort is underway. This experiment seeks to compare the signatures recorded from a large chemical explosion emplaced very near to an historic earthquake, whose signatures were
well recorded with nearby instrumentation. As part of this effort, a detailed
Geologic Framework Model (GFM) was developed that included projectionsof the many known faults throughout Rock Valley. Efforts to improve seismic
event locations include the use of the GFM and updates to seismic velocity, as
well as a re-evaluation of the attitude and location at depth of relevant faults.
We have acquired several lines of relative gravity data using a LaCoste &Romberg portable gravimeter to improve the observation density over previous data available from the U.S. Geological Survey. Our aim is to validate or
update the GFM and its fault projections as appropriate through these dense
data, and to provide a Bouguer Gravity map to be used in future joint gravity/seismic inversion to further update the model and improve locations forpreviously recorded earthquakes. We present our observations, data reductions, modeling methods and comparison with the existing GFM. The gravity
modeling is undertaken using open-source Python-based SimPEG software(Cockett et al., 2015).
References:
Cockett, Rowan, Seogi Kang, Lindsey J. Heagy, Adam Pidlisecky, andDouglas W. Oldenburg. “SimPEG: An Open Source Framework for Simulation
and Gradient Based Parameter Estimation in Geophysical Applications”
Computers & Geosciences, September 2015. doi:10.1016/j.cageo.2015.09.015
poster 146
Observations of Epicentral Infrasound From Shallow
Low-Magnitude Earthquakes in the Permian Basin, West
Texas
SCHAIBLE, L., Sandia National Laboratories, New Mexico, USA, dpschai@sandia.gov; DANNEMANN DUGICK, F., Sandia National Laboratories,
New Mexico, USA, fkdanne@sandia.gov; BOWMAN, D. C., Sandia National
Laboratories, New Mexico, USA, dbowma@sandia.gov; SAVVAIDIS, A.,
University of Texas at Austin, Texas, USA, alexandros.savvaidis@beg.utexas.
edu; MCCABE, C., University of Texas at Austin, Texas, USA, cooper.
mccabe@beg.utexas.edu
Seismic waves emanating from earthquakes and underground explosions candisturb the Earth/atmosphere interface and generate acoustic waves that may
propagate to local and even global distances. Epicentral infrasound (EIS) is
generated directly above an event while local infrasound (LIS) is generated
at or near a receiver. Both have been observed at distances of hundreds tothousands of km following explosions and moderate to large earthquakes (ML3.55 and greater). Proximal (<50 km) observations, however, are especially
important for characterizing low-energy events. LIS has been observed foran earthquake as small as Mw 1.87. While laterally propagating EIS has been
observed within 10 km of buried chemical explosions, to our knowledge there
are currently no observations of EIS at such distances following earthquakesof any magnitude. The Pecos Infrasound Network observational campaign,
during which infrasound was recorded on three arrays during a period of highseismic activity in the Permian Basin of West Texas, was designed to remedy
this lack of observations. From January to June 2023, nearly 1000 earthquakes(1.2 ≤ ML ≤ 4.2) occurred within 50 km of the network, all at depths <11 km.
We analyzed 191 ML ≥ 2.5 events and identify coherent infrasound signals following 45 earthquakes. We highlight exemplary infrasound signals following
three events. All three earthquakes generated LIS at or near the receivers. Twoof the three (both ML 2.9) also generated laterally-propagating EIS detected on
an array about 3 km away, which is confirmed with array processing methods
and comparison with seismic observations. To our knowledge, these are thefirst observations of laterally-propagating EIS at proximal ranges following anearthquake of any magnitude.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.

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poster 147
Seismic Soundscape of the Parks Highway Corridor, Central
AlaskaSEPPI, I., University of Alaska Fairbanks, Alaska, USA, irseppi@alaska.edu;
TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu;
WEST, M., University of Alaska Fairbanks, Alaska, USA, mewest@alaska.edu
In February of 2019, 306 three-component nodal seismometers were
deployed every 1 km along the Parks Highway in Alaska, from Nenana to
Trapper Creek, for a period of 35 days. These nodes recorded a wide range ofsignals, including from local, regional, and teleseismic earthquakes, mining
blasts, helicopters, planes, trains, and automobiles. Our overarching goal is tocharacterize the “seismic soundscape” for this region, represented by a large
set of waveforms, identified by time windows and frequency windows, thatare labeled by event type. Motivated by the findings of Meng and Ben-Zion(2018), we are particularly interested in characterizing the spectral signaturesof various aircrafts and engine types, which is made possible by a groundtruth data set of all commercial flight paths within the time period of interest. Alaska offers an exceptional opportunity for the ground-based detection
and characterization of aircrafts, because there are a wide range of different
aircrafts in use in Alaska (about 100 different types for our region and time
period) and because background noise levels (e.g., low car traffic, continental
interior) are relatively low. Spectrograms of ground motion from passing aircrafts reveal characteristics that are unique to specific types of planes, such asplane-specific harmonics and doppler shifts. In characterizing the spectral signatures of various source types we hope to create a unique database of labeled
waveforms to use as training data sets for future machine learning studies.
We are currently working to establish detection thresholds and characterize
spectral signatures of all signals. Our analysis is augmented by permanentseismic and infrasound stations, providing means for extrapolation outside of
the 35-day time period of interest.
poster 148
Seismic Data Denoising Using Multi-Scale Mathematical
Morphological Filtering
TIBI, R., Sandia National Laboratories, New Mexico, USA, rtibi@sandia.gov
Recorded seismic data are generally contaminated by noise from different
sources, which masks the signals of interest. In the seismology community,
frequency filtering is the standard method for noise suppression. However,frequency filtering is inadequate when the signal of interest and noise sharethe same frequency band. We implemented a new data denoising techniquebased on the mathematical morphology theorem. The method uses morphological opening and closing operations with respect to predefined structuring elements of varying scales, and decomposes an input noisy waveform into
several time series with differing characteristics. Using weighted stacking thedenoised waveform is constructed from the time series. The reconstruction
factors used to perform the weighted stacking are chosen carefully based on
the assessment of which scales are likely to enhance the signal of interest andwhich ones are likely to amplify the noise. We will discuss the implementationof the approach and its initial application to process high-frequency local andnear-regional data.
poster 149
Evaluation of Multiple-Event Location Methods Using
Ground-Truth and Synthetic Data
TIBULEAC, I. M., Air Force Technical Applications Center, Florida, USA,
ileana.tibuleac@us.af.mil; ANTOLIK, M. S., Leidos Inc., Florida, USA,
Michael.S.Antolik@leidos.com; VANDEMARK, T. F., Air Force TechnicalApplication Center, Florida, USA, thomas.vandemark.1@us.af.mil;
BRUMBAUGH, D., Leidos Inc., Florida, USA, DOUGLAS.BRUMBAUGH@
leidos.com
We investigate the accuracy and effectiveness of several commonly used multiple event relocation techniques to recover accurate hypocenter and uncertainty information using sparse datasets involving mostly regional-distancephase readings from ground truth (GT0 or GT1) real event clusters andsynthetic sources. The compared techniques include Progressive Multiple
Event Location (PMEL, Pavlis and Booker, 1983), MLOC (Hypocentroidal
Decomposition algorithms provided by Global Seismological Services, basedon Jordan and Swerdrup,1981), HypoDD (Waldhauser et al., 2000), and
GrowClust (Trugman and Shearer, 2017). These techniques employ different methods to account for structural heterogeneity along the ray paths fromsources to receivers or locally within the cluster source region. We compare
the results to traditional single event location using the best available 3-D
structural information in the study regions. We evaluate the methods in terms

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of mislocation with respect to GT locations and the size and accuracy of thederived uncertainty regions. It is expected that multiple-event, cluster relocation techniques will resolve relative epicenter position better than single-event
location; however, questions remain about their effectiveness in recovering
absolute hypocenter positions, or accurate estimates of location parameter
uncertainties (e.g., Lin and Shearer, 2005). In a nuclear explosion monitoring
context, the validity of the uncertainty assessments is often more important
than the accuracy of the estimated hypocenters. Initial results indicate thatlocation uncertainty estimates obtained from relative location techniques
can be unrealistically small in many cases. We comment on possible causes
embedded within the relocation codes that explain the obtained results.
poster 150
Moment Tensor Inversions for Rapid Seismic Source
Detection and Characterization of the North Korean
Nuclear Tests
GUILHEM TRILLA, A., CEA Centre - DAM France, Magny les Hameaux,France, aurelie.trilla@cea.fr
The rapid detection and source characterization of any type of seismic events
including earthquakes and nuclear explosions are two important missionsof many monitoring seismological laboratories. Here, we extend the use of atechnique already considered for earthquake monitoring in tectonically active
regions to identify non-double-couple shallow events. This approach allows
the rapid screening of such events. It can then be implemented in near realtime procedures and it can become the core of an easy-to-use interactive tool
for seismic analysts. This rapid detector of seismic events provides the full
information of the sources (origin time, location, magnitude, mechanism, andsource decomposition) from full moment tensor inversions calculated on agrid of virtual sources distributed over a region of interest with a limited setof stations. Its overall performances on all past Democratic People’s Republicof Korea (DPRK) nuclear tests and regional earthquakes are presented. This
work also allows to confirm the nature of the first DPRK explosion in 2006
despite the low signal to noise ratio observed in the seismic data, as well as
the characterization of the collapse in the Mantap mountain after the 2017
nuclear test. These rapid source parameters (location, magnitude, mechanism) are comparable to those derived from high-frequency data and more
complete set of regional and teleseismic stations. Thanks to this designed tool
rapid (i.e., within a few minutes) and complete event screening is possible andit opens numerous options for earthquake and explosion monitoring as well
as for tsunami warning.
poster 151
Modeling the Ground Motions From Chemical Explosions
in Proximity of a Fault
VOROBIEV, O. Y., Lawrence Livermore National Laboratory, California,
USA, vorobiev1@llnl.gov; EZZEDINE, S. M., Lawrence Livermore National
Laboratory, California, USA, ezzedine1@llnl.gov
The Source Physics Experiment (SPE) is being conducted at Nevada National
Security Site (NNSS) to study the ground motion generated by undergroundchemical explosion sources in various geologies. Of particular interest is theunderstanding of mechanisms of shear wave generation observed during
underground explosions, which may look like natural seismicity in the far
field. SPE-III will be conducted in proximity to a fault. We have conductednumerical modeling of the ground motion from explosions at various depths
to investigate a role the fault may play in the predicted ground motion. Various
in-situ stress conditions were assumed at the fault as well as the fluid pressure
which may affect the friction on the fault. A new constitutive model for porous
saturated rock has been used which accounts for fluid pressure build up in a
dynamic loading unloading cycle.
poster 152
Signal Arrival Databases for Ground Truth Infrasound
EventsDANNEMANN DUGICK, F., Sandia National Laboratories, New Mexico,USA, fkdanne@sandia.gov; WYNN, N. R., Sandia National Laboratories,
New Mexico, USA, nwynn@sandia.gov
Seismo-acoustic waveform model development serves to improve both precision and accuracy in event characterization estimates through the application of more robust travel time models for infrasound signal propagation.
Development requires the ability to validate models with real data against
meaningful metrics. Comparisons across a suite of ground truth (GT) events
provides the ability to evaluate model performance across a broad spectrum
in both space and time. Current infrasound GT data is limited for several

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reasons, including but not limited to, a lack of acoustic signals from naturally
occurring events and a lack of broad global network coverage. Data is particularly limited for regional networks where sensors are located between 100-600
km from a source of interest. Numerous boutique experiments have historically been conducted by researchers with varying degrees of openly available
data; however, none of these datasets exist in a singular place. Here, we present
a curated dataset of 119 GT infrasound events suitable for algorithm evaluation. Our database identifies signal arrivals and characteristics for each of theGT events, capturing all available regional signal arrivals in an open-source
repository.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.

Advances in Operational and Research Analysis ofEarthquake Swarms
Oral Session • Friday 3 May • 2:00 pm PacificConveners: Kyren R. Bogolub, Nevada Seismological
Laboratory, University of Nevada, Reno (kbogolub@unr.edu);
Jeffery L. Fox, Ohio Geological Survey (jeffrey.fox@dnr.ohio.
gov); Andrea L. Llenos, U.S. Geological Survey (allenos@
usgs.gov); William H. Savran, Nevada Seismological
Laboratory, University of Nevada, Reno (wsavran@unr.
edu); Daniel T. Trugman, Nevada Seismological Laboratory,
University of Nevada, Reno (dtrugman@unr.edu); Elizabeth
A. Vanacore, University of Puerto Rico Mayagüez, Puerto
Rico Seismic Network (elizabeth.vanacore@upr.edu)
Seismic Clusters as Markers of Crustal Stability
ZACCAGNINO, D., Sapienza Universita di Roma, Roma, Italy, davide.
zaccagnino@uniroma1.it; TELESCA, L., CNR-IMAA, Tito Scalo, Italy,
luciano.telesca@imaa.cnr.it; DOGLIONI, C., National Institute of Geophysics
and Volcanology, Rome, Italy, carlo.doglioni@ingv.it
Seismic activity is the mirror of local instability in the brittle crust. Each seismic event occurs because of stress accumulation at weak interfaces withincrustal volumes and static and dynamic perturbations, so that earthquakes
tend to be clustered in space and time. So, on one hand, seismicity triviallyprovides information about the state of stability of the fault patch where it takes
place, on the other side, it is rather difficult to assess whether the occurrence ofseismic events may be somewhat connected to the large-scale state of stabilityof a fault. Are foreshocks “fore-shocks” or simply markers of local instability
without prognostic value? Is there difference between foreshocks and swarms?
We analyse several parameters describing seismic clusters until the mainshocks in relocated seismic catalogues in relationship with the magnitude of
the incoming mainshock in the range Mw 2.5–7.3 in Southern California and
Italy (e.g., the involved area, duration, the p-value of the Omori-Utsu law, theb-value, the seismic rate, number of events, entropy, inter-event times distribution). We find differences in the distributions of some features; foreshocks
tend to spread over larger areas, they are featured by larger and more energetic
clusters with also higher variance of magnitudes and relative entropy. Others
are not distinguishable. Moreover, foreshocks and swarms are found to sharethe same scaling behaviors. Theoretical modelling suggests that the combined
effect of long-range correlations and fault memory makes the system sensitive
to both mechanical details, structural properties of the fault system and its history. Therefore, it produces different future evolutions because of tiny changes
in internal parameters or in past occurrences. We believe that foreshocks canbe hardly distinguished from swarms using the structural and statistical properties of clusters. In this sense, foreshocks are likely of limited usefulness for
short-term earthquake forecasting if considered alone, but they could be useful for the identification of regions featured by correlated seismic activity, aplausible marker of crustal instability.
Investigating Slow Slip Transients and Earthquake Swarms
on the Blanco Transform Fault With Obs Data Mining
JOURNEAU, C., University of Oregon, Oregon, USA, cyrilj@uoregon.edu;
THOMAS, A. M., University of Oregon, Oregon, USA, amthomas@uoregon.
edu; HIRAO, B., University of Oregon, Oregon, USA, bhirao@uoregon.edu;
TOOMEY, D. R., University of Oregon, Oregon, USA, drt@uoregon.edu;

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Seismological Research Letters

HOOFT, E. E. E., University of Oregon, Oregon, USA, emilie@uoregon.edu;
ABERCROMBIE, R. E., Boston University, Massachusetts, USA, rea@bu.edu
Oceanic transform faults (OTFs) constitute one type of plate boundary
accommodating deformation through quasi-periodic earthquakes, aseismic
creep and seismic swarms. Recent studies suggest that earthquake swarms are
driven by episodic slow slip, both of which can sometimes precede moderate-large earthquakes at OTFs. Here, we analyze data from an OBS network(X9 code, 55 stations deployed for 1 year in 2012-2013, Nabelek et al 2012)surrounding the Blanco Transform Fault (BTF) located offshore Oregon. We
re-visit this dataset using two advanced data mining approaches. We thus
conduct a comprehensive analysis of the BTF seismic wavefield, aiming toinvestigate slow slip phenomena and its role in generating earthquake swarms.
First, we apply a machine-learning (ML) workflow to detect microseismicity. We use the PickBlue CNN phase picker and GaMMA associator.
After a quality assessment, about 40,000 earthquakes are retained, representing 4.5 times more than a previous seismic catalog for the same dataset. Our
ML seismic catalog delineates the fault’s along-strike segmentation, revealing
distinct seismogenic behaviors: sections emitting nearly continuous microseismicity, aseismic areas, and portions characterized by seismic swarms, andmainshock - aftershock sequences. Second, we measure the seismic wavefield spatial coherence across the OBS network, by computing the covariancematrix spectral width, using CovSeisNet. An interesting finding includes very
low-frequency earthquakes (VLFE) detection in the 10-30 s period range.
To better understand the spatio-temporal relations between slow earthquakes, foreshock swarms, and mainshock earthquakes, we are relocating
seismic swarms and VLFE sources. Finally, we aim to extend the new insights
gleaned using the year with OBS data on the fault, to improve and groundtruth methods using only the permanent in-land stations near the coast. This
would improve quality and reliability of multi-year analysis of BTF swarms
when only in-land stations exist, aiding in the elucidation of their driving
mechanisms, potentially involving slow slip transients.
Distant Seismic Monitoring of a Volcanic Earthquake
Swarm Near the Manu’a Islands, American Samoa, with
Deep-learning and Template-matching Event Detection
YOON, C., U.S. Geological Survey, California, USA, cyoon@usgs.gov;
SKOUMAL, R. J., U.S. Geological Survey, California, USA, rskoumal@usgs.
gov; MICHAEL, A. J., U.S. Geological Survey, California, USA, ajmichael@usgs.gov; DOWNS, D. T., U.S. Geological Survey, Hawaii, USA, ddowns@
usgs.gov; DELIGNE, N. I., U.S. Geological Survey, Hawaii, USA, ndeligne@
usgs.gov; HANEY, M. M., U.S. Geological Survey, Alaska, USA, mhaney@
usgs.gov; WECH, A., U.S. Geological Survey, Alaska, USA, awech@usgs.gov;
LUTU-MCMOORE, E., National Oceanic and Atmospheric Administration,
American Samoa, USA, elinor.lutu-mcmoore@noaa.gov; LANGKILDE, M.,
National Oceanic and Atmospheric Administration, American Samoa, USA,
marcus.langkilde@noaa.gov
From July to October 2022, an earthquake swarm occurred near the Manu’aIslands in eastern American Samoa. The swarm started in late July, with peak
activity in August, before decreasing in late September and has fortunately
been quiet since. Earthquake information was limited to felt shaking reports
from local residents sent to the National Weather Service Pago Pago office,because of a lack of seismometers in the region when the swarm started.
Residents were concerned about the unusual frequent shaking, making it
essential to understand the source of these earthquakes in rapid responsemode.
We show how modern seismological methods provided initial information and situational awareness of the evolving Ta‘ū volcano earthquake
swarm, with limited available data. Using continuous seismic data from one
Global Seismographic Network station located ~250 km west of Ta‘ū volcano,
we applied the EQTransformer deep-learning model (Mousavi et al., 2020) toautomatically pick P and S phase arrivals for earthquakes between 2022-07-01
and 2022-08-12, when seismic activity began and intensified. We used S-Ptimes from events matching felt reports to identify additional likely Ta‘ū volcano swarm events, while excluding events from unrelated sources such as the
Tonga Trench. Waveforms from these events were used in template-matching
to detect additional events. Starting 2022-08-13, when continuous Raspberry
Shake seismometer data from Ta‘ū Island became available, short (<3 second)
S-P times output by EQTransformer constrained the swarm location to thenorthern submarine realm of Ta‘ū volcano. The Raspberry Shake data wasessential in determining Ta‘ū volcano as the correct source of the swarm, ruling out the previously assumed Vailulu‘u seamount as a potential source. On
2022-08-20, the USGS Hawaiian Volcano Observatory commenced operational response seismic monitoring in American Samoa, estimating magnitudes of 2 to 4 for most subsequent earthquakes. Methods such as deep-learn-www.srl-online.org•

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ing and template-matching can improve monitoring and forecasts of swarms
and aftershock sequences far from seismic stations.
Improving Template Matching Detections Using a
Convolutional Neural Network
JOZINOVIĆ, D., ETH Zurich, Zurich, Switzerland, dario.jozinovic@sed.
ethz.ch; TOLEDO, T., ETH Zurich, Zurich, Switzerland, tania.toledo@sed.
ethz.ch; SIMON, V., ETH Zurich, Zurich, Switzerland, verena.simon@sed.
ethz.ch; KRAFT, T., ETH Zurich, Zurich, Switzerland, tkraft@ethz.ch
The use of template matching to detect previously missed small earthquakes
is widespread in seismology, due to its power in searching for similar signals. The newly detected earthquakes improve understanding of the geology,
seismo-tectonics and seismogenesis of the area explored. The usefulness oftemplate matching has sparked the development of many software tools (e.g.
QuakeMatch; Toledo et al., 2024) that allow seismologists to easily apply themto their area of interest.
Like every detection technique, the performance of template matchingshows a tradeoff between sensitivity and false detection rate that is dependent on the choice of the detection threshold. The value of the correlation
coefficient between two earthquake signals is highly dependent on several
properties such as the distance of the earthquake from the station, the noiselevel at the station, the magnitude of the earthquake, the focal mechanism of
the earthquake, etc, making the selection of a specific correlation coefficientthreshold hard. To detect a larger number of earthquakes, researchers often
use a lower correlation coefficient detection threshold and manually inspect
the detected events to classify them as true events (Toledo et al., 2024). This is
a tedious task, especially when using a large number of templates. To reduce
the human workload, which can be especially important during evolving
earthquake sequences, we employ a Convolutional Neural Network (CNN)
to discriminate between earthquakes and noise using the template matchingdetections as input. We use the data from several microearthquake naturaland induced Swiss sequences (Simon et al., 2024, in prep.), to train and test
the developed CNN model. Our CNN model uses single-station 3-component waveforms of any length and outputs an earthquake detection score.
We demonstrate that the developed CNN can be used to significantly reduce
the human workload with high accuracy, allowing the use of low correlation
coefficient value thresholds for template matching detections. Furthermore,
we show the implementation of the method inside the QuakeMatch software(Toledo et al., 2024).
Automated Detection and Characterization of Swarms andMainshock-Aftershock Sequences in Southern Mexico
VENTURA-VALENTIN, W. A., Miami University, Ohio, USA, venturwa@
miamioh.edu; BRUDZINSKI, M. R., Miami University, Ohio, USA,brudzimr@miamioh.edu; BENNETT, A., Miami University, Ohio, USA,bennet91@miamioh.edu; KHALKHALI, M., Miami University, Ohio, USA,khalkhm@miamioh.edu; COKER, S., Miami University, Ohio, USA, scoker1@
wildcat.fvsu.edu
Earthquakes in Mexico are frequent and dangerous. Over the last decade,there have been a dozen major earthquakes including two larger than M7.5.
The Mexican subduction zone is considered a natural laboratory for studying slip processes due to the relatively short trench-to-coast distance whichbrings broad portions of the seismogenic megathrust inland. Using an automated detection algorithm that identifies clusters of events using the nearest
neighbor distances in the space-time-energy domain (Zaliapin and Ben-Zion,
2013), we sought to characterize ~700 sequences detected from 2012 to 2020.
Traditional methods are time-consuming and biased due to the number of
events and human perception, so we developed an automated strategy to evaluate sequences on a spectrum of swarm to mainshock-aftershock (MS-AS).
The automated algorithm uses quantitative forms of these attributes: 1) magnitude difference between the largest event and next largest events, 2) percentage of the sequence after the largest event, 3) slope of seismicity rate over time,4) ratio of magnitude range to the number of events and, 5) rate of maximum
magnitude decay over time. The automated method yields similar results tomanual characterization and is effective at identifying average properties
when there are discrepancies among manual ratings for complex sequences.
We found more swarms than aftershock sequences despite the prominence oflarge megathrust MS-AS sequences over the past decade. Temporally, someswarm sequences show an interesting pattern where the seismicity shuts onor off depending on nearby megathrust activity. Spatially, swarms help definea vertically dipping fault in the upper plate indicating a strike-slip sliver fault
may be closer to the coast than previously thought. We anticipate standardizing the characterization process will provide opportunities for more in-depth
studies of seismic sequence types and their causes.

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Seismological Study of the West Bohemia/Vogtland Swarm
Region With Waveform and Catalog Data
OLIVAR-CASTAÑO, A., University of Potsdam, Potsdam, Germany, andres.
olivar-castano@uni-potsdam.de; BÜYÜKAKPINAR, P., GFZ Potsdam,
Potsdam, Germany, pinar@gfz-potsdam.de; OHRNBERGER, M., Universityof Potsdam, Potsdam, Germany, Matthias.Ohrnberger@geo.uni-potsdam.
de; DAHM, T., GFZ Potsdam, Potsdam, Germany, dahm@gfz-potsdam.de;
DOUBRAVOVÁ, J., Czech Academy of Sciences, Prague, Czechia (Czech
Republic), doubravka@ig.cas.cz; FISCHER, T., Charles University, Prague,
Czechia (Czech Republic), fischer@natur.cuni.cz; WENDT, S., University ofLeipzig, Leipzig, Germany, obssw@hpwork30.collm.uni-leipzig.de
The Vogtland region is situated in the western part of the Bohemian Massif
and extends over an area of 3500 km2 across four state borders. It is intersected by the medium-sized Tertiary Eger Graben, Variscan terrain boundaries, and a small sedimentary basin. The area is a type locality for the studyof mantle-derived, diffuse degassing of CO2 and the persistent occurrenceof mid-crustal earthquake swarms. Quaternary maar volcanoes and crustal
magmatic underplating indicate extended magmatic processes. Despite intensive research, the cause of the earthquake swarms has not been elucidated, andquestions remain as to how shallow magmatic fluids penetrate, whether theapparent Moho upwelling and underplating zone correlates with an upwellingof the brittle ductile transition between 15-10 km depth. Another open question is why since 1985 the highest swarm energy release with Ml<4.5 occurs
in a cluster below Novy Kostel, and why for about 15 years the swarm has
been migrating with each new cluster in a well-defined fault zone to the northand south, reaching shallower levels in recent years. To date, the Novy Kostel
swarm extends over 35 km in length and 12 to 8 km in depth. The sources
cover strike-slip, normal and thrust mechanism.
We follow three approaches to explore the swarm region: (1) improvethe existing dense seismic network by installing high-frequency 3D arrays as
antennas to detect and locate the smallest events. So far, two swarm episodes
have been recorded by this installation; (2) unify the existing seismic catalogues from different surveys using a common velocity model and modern
relative locations; (3) use of machine learning phase detection, migrationand stacking techniques with the dense network data for the preiod 2018 to2024 to reduce the completeness magnitude and study the anatomy of swarms
in the initial activity phases. This comprehensive approach will answer thequestion of whether the distribution of the deepest micro-earthquakes follow
the upwelling brittle ductile transition over the region of CO2 degassing andswarms.
Systematic Measurements of Parameters During
Earthquake Swarms
MCNUTT, S. R., University of South Florida, Florida, USA, smcnutt@usf.edu;
THOMPSON, G., University of South Florida, Florida, USA, thompsong@usf.edu; BRAUNMILLER, J., University of South Florida, Florida, USA,jbraunmiller@usf.edu; RODRIGUEZ CARDOZO, F., University of South
Florida, Florida, USA, felixr1@usf.edu; HOLTKAMP, S., University of Alaska
Fairbanks, Alaska, USA, stephen.holtkamp@gmail.com
The identification of processes causing earthquake swarms are long-standing
problems in seismology. We are engaged in an ongoing comprehensive andsystematic approach that examines a variety of parameters. Here we summarize recent results which have not been previously published. We investigated the difference in magnitude M between the largest and second largest
events, which we call M1-M2. Large samples (67-174 swarms) of swarms in
tectonic and volcanic areas (teleseismic data) each had similar distributionsand variances and the same means of 0.16 M units. No swarms were foundwith M1-M2 equal to 0.7, which suggests a break in scaling. M1-M2 is systematically larger as M1 get larger, which suggests variability of conditions in thesource regions. Swarm durations are longest for swarms on megathrusts, andshortest at volcanoes, although distributions overlap. The largest event occurs
late in volcanic swarms, suggesting a growing source size. This trend is notobserved for mid-ocean ridge swarms. A plot of number of events in swarms
versus number of swarms shows two branches (sub-parallel trends), suggesting two dominant processes. An updated study of volcanic swarms that follow
the Generic Volcanic Earthquake Swarm Model (GVESM) using local data
show that the peak rate occurs near the onset of low-frequency events. Thissuggests that the peak rate is the culmination of development of a system ofcracks, which then facilitate fluid (water, gas, or magma) movement. Overall,
the suite of observations and measurements suggests that there are several
mechanisms or processes involved in earthquake swarms.

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Earthquake Swarms as a Window to Characterize Transient
Processes
CHEN, X., Texas A&M University, Texas, USA, xiaowei.chen@tamu.edu;
JIANG, J., University of Oklahoma, Oklahoma, USA, Junle.Jiang-1@ou.edu;
SAGAE, K., AIST, Tsukuba, Japan, k.sagae@aist.go.jp; UCHIDE, T., AIST,
Tsukuba, Japan, t.uchide@aist.go.jp
Earthquake swarms are broadly defined as earthquake sequences without adistinct mainshock. Many different parameters have been proposed to characterize earthquake swarms and distinguish them from mainshock-aftershock
sequences. However, there is no universal definition of swarms. In this study,
we compile previously identified earthquake swarms in different tectonic
regions, including tectonic strike-slip faults, volcanic and geothermal regions,and fluid-induced swarms in the intraplate region. We obtain a comprehensive set of physical and statistical parameters to characterize the swarm evolution in space and time and compare swarms from different tectonic regions.
For two swarms driven by different external processes, we further characterizeshort-duration bursts within the swarm.
Preliminary analysis found no systematic difference in effective stressdrop from different regions with values ranging up to 3 orders of magnitude.
The range of effective stress drop is similar to static stress drop for individual earthquakes, suggesting the average stress release is nearly constant. The
skewness of moment release history is mostly small, however, several prolificswarms from the Salton Trough have very high skewness, suggesting moreconcentrated moment release during the early stage of the swarm - a behavior
that is more similar to foreshock-mainshock-aftershock sequences.
A systematic difference in the scale exponent between migration velocity and swarm duration separates swarms into different groups of different
dominant triggering processes from pressure-diffusion dominant to shearstress-transfer dominant regimes. An effective diffusivity is obtained based on
the product of velocity squared and duration. Relatively narrow ranges of diffusivity are found for each group, with the Salton Trough being systematicallyhigher and bridging the gap between crustal swarms and slow-slip events. We
hypothesize that such observation suggests characteristic diffusion processes
in different tectonic regions, and swarm parameters reflect characteristic transient processes in different environments.
Deep Learning Analysis of Transient Signals Preceding the2023 Mw 7.8 Kahramanmaraş Earthquake in Türkiye
ZALI, Z., GFZ Potsdam, Potsdam, Germany, zahraazalii@gmail.com;
MARTINEZ GARZON, P., GFZ Potsdam, Potsdam, Germany, patricia@gfzpotsdam.de; KWIATEK, G., GFZ Potsdam, Potsdam, Germany, kwiatek@
gfz-potsdam.de; BOHNHOFF, M., GFZ Potsdam, Potsdam, Germany,bohnhoff@gfz-potsdam.de; BEROZA, G. C., Stanford University, California,
USA, beroza@stanford.edu
Laboratory studies indicate that faults undergo damage and stress evolution
before rupture, potentially leaving discernible signatures in seismic data.
Before the 2023 MW 7.8 Kahramanmaraş earthquake in Türkiye, an extended
period of ~ 8 months displaying seismicity around the epicenter and the entire
rupture suggested an extended preparation phase (Kwiatek et al., 2023; Picozzi& Iaccarino, 2023). This study analyzes low-frequency (< 5 Hz) recordings
from regional broadband seismic stations near the future epicenter of thisearthquake. Using a deep neural network, we extract key features from thecontinuous seismic waveforms and their spectral characteristics and employ
an unsupervised clustering analysis to identify distinct classes in the continuous waveform recordings. Our analysis reveals two main changes in the spectral characteristics about 8 and 6 months before the mainshock, respectively,
coinciding with the onset of elevated seismic rates and changes in b-values. Of
particular interest is the emergence of numerous (N=3724) temporal episodes
lasting about 12~30 minutes containing enhanced radiated energy in the frequency band 1-5 Hz, starting 6 months before the mainshock. These episodes
are observed solely at five seismic stations within 46 km epicentral distancefrom the future mainshock epicenter, all located on the east side of the East
Anatolian Fault Zone. The episodes are likely of tectonic origin, as their occurrence is not correlated with time of day, weather changes, construction processes, telemetry-related events, or instrument-related factors. Each episodecomprises numerous small transient pulses resembling extremely small earthquakes. The pulses have a similar moveout to that from a local earthquake
near the main rupture epicenter. We present the statistical analysis of observed
episodes as well as their source properties and investigate their physical origin.

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Seismological Research Letters

Enhanced Seismicity at a Geothermal Spot in Southern
Tibet Following 2004 Mw 9.1 Sumatra and 2005 Mw 8.6
Nias Earthquakes and Its Implication for Rifting Process
LIANG, X., Chinese Academy of Sciences, Beijing, China, liangxf@mail.
iggcas.ac.cn
There are several north-south trending rifts in southern Tibet, indicating theextensional stress perpendicular to the convergence direction between the
Indian and Eurasia plates. However, the rifting geodynamic process is under
debate. Strong geothermal and seismic activities are observed all over southern Tibet. In particular, there is a geothermal spot west of Pumqu-Xianza Riftin the Lhasa Terrane, where there are nearly continuous seismic activity withmagnitude 3-5 based on the global and regional catalogues. With such highseismicity rates, it is expected to observe dynamic triggering around the geothermal spot. Here we conduct a systematic search for dynamically triggered
microearthquakes in southern Tibet following the 2004 December 26 Mw 9.1
Sumatra and 2005 March 28 Mw 8.6 Nias earthquakes. We find clear increaseof high-frequency signals during the surface waves of the Sumatra mainshock,a clear hallmark for instantaneous dynamic triggering. To better quantify seismicity rate changes, we apply a Network Waveform Matched Filter Technique(NWMFT) to continuous seismic data recorded by the Hi-CLIMB 2D arrayto obtain more complete earthquake catalogues in southern Tibet. Using 213
hand-picked events as templates, we detect ~36 times more events 90 days
before and after both mainshocks. The detected catalogs show that local
seismicity in the geothermal spot west of Pumqu-Xianza Rift was enhanced
after the Sumatra earthquake, but no significant change after the Nias earthquake. The enhanced seismicity lasted about 20 days following the Sumatra
mainshock. The difference in triggering response following these two distant earthquakes could be related with the fact that the Sumatra mainshock
excited long-duration surface waves with cumulative energy density 15 times
more than that of the Nias mainshock or due to potential recharge time since
relative short time interval between these two mainshocks. We will examine
spatio-temporal evolutions of seismicity to better constrain the physical processes of dynamic triggering at geothermal regions and its implication for rifting process in southern Tibet.

Advances in Operational and Research Analysis ofEarthquake Swarms [Poster Session]
Poster Session • Friday 3 May
Conveners: Kyren R. Bogolub, Nevada Seismological
Laboratory, University of Nevada, Reno (kbogolub@unr.edu);
Jeffery L. Fox, Ohio Geological Survey (jeffrey.fox@dnr.ohio.
gov); Andrea L. Llenos, U.S. Geological Survey (allenos@
usgs.gov); William H. Savran, Nevada Seismological
Laboratory, University of Nevada, Reno (wsavran@unr.
edu); Daniel T. Trugman, Nevada Seismological Laboratory,
University of Nevada, Reno (dtrugman@unr.edu); Elizabeth
A. Vanacore, University of Puerto Rico Mayagüez, Puerto
Rico Seismic Network (elizabeth.vanacore@upr.edu)
poster 120
Feature-based Magnitude Estimates for Small, Nearby
Earthquakes in the Yellowstone Volcanic Region
ARMSTRONG, A. D., University of Utah, Utah, USA, alysha.armstrong@utah.edu; BAKER, B., ben.baker@utah.edu University of Utah, Salt Lake City,
Utah, USA; KOPER, K., keith.koper@utah.edu University of Utah, Salt Lake
City, Utah, USA.
Conventional methods of magnitude estimation for small, locally recorded
events either rely on measurements of the maximum peak-to-peak amplitude
to compute a local magnitude (ML) or measurements of waveform decay tocompute a coda duration magnitude. While at least one of these methods isgenerally able to produce an event magnitude in an automated framework,small events occurring as part of an earthquake swarm often pose a challenge.
These events can occur rapidly and close by, causing overlapped event waveforms that make it challenging to accurately estimate the required magnitude
parameters. This is particularly evident in Yellowstone, where ~50% of all seismicity occurs as part of a swarm. Additionally, only a subset of seismometers
used to process events in the Yellowstone region have the station corrections

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needed to compute ML. This further limits the ability to produce ML values forvery small events (< ~1.5). The need for another approach to estimate magnitude is magnified for large, deep-learning enhanced catalogs.
We introduce a machine learning method that uses features derived
from short-duration waveforms capturing individual phase arrivals and event
source parameters to predict the catalog network ML. We train one support
vector machine (SVM) for each station-phase pair, resulting in 34 models
using P features and 17 using S features. Producing a model for each station
allows the SVMs to efficiently learn individual station corrections. We ensemble predictions from multiple models into a network-averaged magnitude. For
each phase, we initially examine 48-potential features and narrow the final
number used in each model to ~9 by applying feature selection techniques.
Using these features, initial results produce an R2 value of ~0.9 on the test
sets when averaging the model predictions. This method will improve ourability to produce ML values for Yellowstone swarm events and lower the ML
magnitude of completeness. While not directly transferrable, this approach
may be beneficial to other seismic network operators who routinely processearthquake swarms.
poster 121
Analysis of Yellowstone Earthquake Swarms After
Relocating Using Nonlinloc-Ssst and a 3D Velocity ModelCZECH, T. L., University of Utah, Utah, USA, tessa.czech@utah.edu;
FARRELL, J., University of Utah, Utah, USA, jamie.farrell@utah.edu
The Yellowstone region is the most seismically active area in the U.S.
Intermountain West with an average of ~1,500–2,500 earthquakes per year.
About half of Yellowstone seismicity occurs as part of earthquake swarms
which have been attributed to processes such as hydrothermal fluid migration, magma injection or creep along faults. High-precision earthquake locations can be used to understand the structures where swarms occur and theunderlying causes of the swarm seismicity. NonLinLoc (NLL) is a nonlinear
high-precision earthquake location method that has been shown to produce
higher-quality absolute locations than conventional methods. We have applieda more advanced version of NLL, NonLinLoc—Source Specific Station Terms
with Coherence (NLL-SSST-coherence) to ~40 years of Yellowstone seismic
data recorded from 1984 to 2024 to obtain high-precision absolute earthquake
locations. The NLL source specific station terms are created iteratively using
a 3D velocity model and waveform coherence is used to reduce arrival timeerrors. We will compare the absolute locations from NLL-SSST-coherencewith 1D routine locations produced by the University of Utah SeismographStations and with 3D relocations using standard NLL. Initial results indicatethat the NLL-SSST-coherence locations show an improvement over both the
1D routine and standard NLL locations, and some earthquake locations converge to linear features which could indicate fault structures. These findings
suggest that using a more advanced location method for swarm events could
be an important step in understanding the structures and dynamics of earthquake swarms. It also suggests that including the use of NLL-SSST-coherence
in routine location analysis could improve the “realtime” interpretation of
Yellowstone swarm activity.
poster 122
It’s Swarmy Outside: Defining Swarms for the Purpose of
Forecasting
LLENOS, A. L., U.S. Geological Survey, Colorado, USA, allenos@usgs.gov;
MICHAEL, A. J., U.S. Geological Survey, California, USA, ajmichael@usgs.
gov; MCBRIDE, S. K., U.S. Geological Survey, California, USA, skmcbride@usgs.gov; PAGE, M. T., U.S. Geological Survey, California, USA, mpage@usgs.gov; VAN DER ELST, N., U.S. Geological Survey, California, USA,nvanderelst@usgs.gov; SCHNEIDER, M., U.S. Geological Survey, California,
USA, mschneider@usgs.gov
Compared to more common mainshock-aftershock sequences, earthquake
swarms are difficult to define and are therefore often defined by what theylack in relation to aftershock sequences (e.g., a clear mainshock, Bath’s Law,
Omori-like temporal rate decay). However, such definitions can be difficult
to quantify, particularly in more complex sequences of elevated earthquake
rate. They also do little to describe what a swarm actually is, particularly forthe general public who may never hear the term until they are in the midstof one and receiving earthquake advisories that could cause confusion or
alarm. Definitions that focus on seismogenic processes due to fluid migration, slow slip, or volcanic processes may be more informative, but it is difficult to identify these processes early in a swarm’s evolution. Because the U.S.
Geological Survey (USGS) releases earthquake advisories and forecasts during some swarms, such as the 2016, 2020, and 2021 swarms near the Salton

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Sea in California (e.g., McBride et al., SRL, 2020), we propose a definition thathelps us make better forecasts and reduces confusion.
Here we define a swarm simply as a sequence of earthquakes wherechanges in earthquake rates are driven by processes beyond typical mainshock-aftershock triggering. This definition allows a swarm to be describedwith a time-varying background rate term in the Epidemic-Type Aftershock
Sequence model (Ogata, JASA, 1988), which is already used to produce aftershock forecasts in many regions. A swarm forecast can therefore be computedby adding a temporally varying background rate to the approach used for anaftershock forecast. Currently, the USGS forecasting method estimates thisrate from the swarm so far observed and a swarm duration model (Llenos andvan der Elst, BSSA, 2019). This procedure is applied using expert judgement
when the inclusion of the extra rate improves the model. In general, we argue
that the best definition of a swarm is one that helps us best forecast the futureand is simple enough for people outside of our scientific sphere to understand.
poster 123
Event-Event Waveform Correlation and Multi-Event
Multi-Channel Deconvolution Applied to Temporal-Spatial
Patterns of Micro Earthquake Sequences (Swarms)
MCLAUGHLIN, K. L., Leidos, Virginia, USA, mclaughlin0kl@me.com;
JAUME, S., College of Charleston, South Carolina, USA, JaumeS@cofc.edu
Event-event multi-channel waveform correlation and multi-event multi-channel deconvolution is applied to two recent sequences of micro-earthquakes
in South Carolina (Elgin and Monticello Reservoir). Clustering of events
based on event-event multi-channel waveform correlation is used to identify
separate spatial clusters of co-located events independent of prior localization procedures. That is, event-event waveform correlations identify repeatedruptures on individual localized asperities. The inferred hypocentral distances
between the events on the same asperity may be smaller than the individual
event location uncertainties. Small events with poor SNR with uncertain locations may be identified as belonging to localized spatial clusters. The clusteredwaveforms may then be used as matched-filter templates to further detecteven smaller events related to the asperity. A statistical procedure is proposedto evaluate the probability of false event detection is presented. The resulting sequential pattern of event time series on the individual asperities then
may be studied with more detail. A nearest neighbor temporal-spatial analysis
is applied to characterize the sequences within and between asperities. Oncedecomposed into individual asperities, the event sequences on each asperity
begin to resemble a fore-shock, main-shock after-shock sequences. A multievent multi-channel deconvolution procedure of Der et al (1988) is applied toindividual clusters to study more detailed temporal rupture variations on theindividual asperities and reveal complex source functions.
Der, Z. A., R. H. Shumway, and A. C. (1988). Frequency Domain
Coherent Processing of Regional Seismic Signals at Small Arrays, Bull. Seism.
Soc. Am., 78, 326-338.
poster 124
Heterogeneous Seismic Swarm Activity in Central Utah:
Triggering Mechanisms and Their Complex Interactions
PETERSEN, G., GFZ Potsdam, Potsdam, Germany, gesap@gfz-potsdam.de;
WHIDDEN, K., University of Utah, Utah, USA, katherine.whidden@utah.
edu; PANKOW, K. L., University of Utah, Utah, USA, kris.pankow@utah.edu
The complex geo-tectonic transition zone between the Basin and Range province and the Colorado Plateau results in a remarkable diversity of temporaland spatial characteristics of seismic swarms in central Utah. E-W extension, high heat flow, past volcanic activity, and hydrothermal processes form
an exciting background to study forty years of seismic swarm activity basedon the regional catalog of the University of Utah Seismograph Stations (e.g.,
duration, moment release over time, spatial variations). Alternating phasesof very high and low activity are observed, as well as comparably continuous
moment release, repeated activation of the same source areas as well as large
swarms in previously seismically inactive areas. Subsequent in-depth analyses of exemplary, most recent swarm sequences, including event detections,relocations, MT inversions, waveform-based clustering, and repeater analysis,
provide unique insights into the diverse faulting processes. We observe thefollowing examples of diverse swarm activation processes: (1) swarm activity
on a normal fault related to the regional Basin and Range extension but also(2) the activation of a local fault deviating from the recent regional tectonic
regime. (3) The complex triggering of swarm activity by a mainshock and (4)years-long repeated activation of another swarm area. Combining the observations of the exemplary sequences and the catalog characteristics of the 40
years of swarm activity, we aim to expand the overall discussion on swarm
activity and its relation to geothermal and tectonic processes.

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poster 125
What Has Unimak Island in Alaska Witnessed in the Last
~30 Years?—a Seismic RecapPARAMESWARAN, R. M., University of Alaska Fairbanks, Alaska, USA,
rmparameswaran@alaska.edu; GRAPENTHIN, R., University of Alaska
Fairbanks, Alaska, USA, rgrapenthin@alaska.edu
Seismic swarms on volcanoes along a subduction arc could be reflective of amultitude of geophysical processes. These processes can broadly be volcanic,
tectonic, or cryospheric in origin, or a combination of these. Unimak Islandthat exhibits subduction arc volcanism is located in the central part of the
Alaska-Aleutian subduction zone where the Pacific plate subducts beneath theNorth-American plate, normal to the trench-line with low coupling between
the plates. The island hosts several volcanoes such as Roundtop, Isanotski,
Shishaldin, Fisher, and Westdahl. Of these, Westdahl, Fisher, and Shishaldin,
are considered active due to historic volcanism, volcano seismicity, and deformation cycles. In this study, Unimak Island is divided into smaller regions
based on the locations of the three active volcanoes and their seismic activity
from 1990-2023, including the recent 2023 unrest at Shishaldin. The seismicity in these regions is categorized into multiple time windows depending on
the length of activity and quiescence. The seismicity in each spatio-temporalunit is used to (1) characterize individual swarm clusters, (2) identify correlations with specific periods of volcanic unrest defined by different observations(eruptions, deformation etc.), and (3) identify signatures of possible interactions between the three volcanoes. The study uses relocated seismicity (Klein,2002) from the Alaska Volcano Observatory (AVO) seismic catalog (available
through USGS), and eruption history and geodetic observations curated by
AVO.
poster 126
Correlations and Change Points Identification in Crustal
Anisotropy, b-Value and Vp/vs, Time Series During Seismic
Swarm Occurrences in the Alto Tiberina Fault Zone (Italy)
ZACCARELLI, L., Istituto Nazionale di Geofisica e Vulcanologia, sezione
di Bologna, Bologna, Italy, lucia.zaccarelli@ingv.it; TARONI, M., Istituto
Nazionale di Geofisica e Vulcanologia, sezione di Roma1, Roma, Italy,
matteo.taroni@ingv.it; BACCHESCHI, P., Istituto Nazionale di Geofisica e
Vulcanologia, ONT, Roma, Italy, paola.baccheschi@ingv.it
We computed different seismological parameters from the analysis of the
waveforms recorded during the seismic swarms activity occurred along theAlto Tiberina Fault (ATF) and surrounding regions (Northern Apennines,
Italy) in the period 2010-2015: crustal anisotropy (in terms of time delay
between the two S-waves generated by the shear wave splitting), b-value of the
Gutenberg-Richter law, and vp/vs ratio. We obtained three time series of thecorresponding measures for each station of the Italian Seismic Network operating in the study area. However only three of them show enough points along
the entire 6-year period to obtain robust time series. Due to the sparse presence of values in the time series we thus apply a weighted likelihood approach
to homogenize them, and finally we looked for both correlations and change
points in their temporal trends. The times corresponding to aforementioned
variations in one or more parameters/stations are then tested to highlight thestatistical significance of their occurrence. We merge all observations for getting a more constrained interpretation of the ATF seismicity evolution. The
statistical approach presented in this study for comparing seismological timeseries could more generally find application in comparing other types of timeseries, and is especially suitable for those derived from unevenly sampledmeasurements.

Advancing Seismology with Distributed Fiber Optic
Sensing
Oral Session • Friday 3 May • 8:00 am PacificConveners: Ettore Biondi, California Institute of Technology(ebiondi@caltech.edu); Daniel Bowden, ETH Zürich (daniel.
bowden@erdw.ethz.ch); Derrick Chambers, Colorado Schoolof Mines (derrickchambers@mines.edu); Julia Correa,
Lawrence Berkeley National Laboratory (juliacorrea@lbl.
gov); Manuel Mendoza, University of Colorado, Boulder(Manuel.Mendoza@colorado.edu); Krystyna Smolinski,
ETH Zürich (krystyna.smolinski@erdw.ethz.ch); Veronica
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Seismological Research Letters

Rodriguez Tribaldos, GFZ Potsdam (verort@gfz-potsdam.
de); Shihao Yuan, Colorado School of Mines (syuan@mines.
edu)
High-Resolution Analysis of Earthquake Sources and
Subsurface Structures Using Downhole Optical Fiber
Crossing Active Fault
MA, K., Academia Sinica, Taipei, Taiwan, fong@earth.sinica.edu.tw; LIAO, J.,
National Central University, Taoyuan, Taiwan, jolan@e-dream.tw; HSIAO, L.,
National Central University, Taoyuan, Taiwan, 097038lulu@gmail.com
Distributed Acoustic Sensing (DAS) systems have proven effective in quantifying changes in frequency, amplitude, phase, and location of dynamic
perturbations along the fiber, especially when installed with assured wellcoupling. Placing an optical fiber at the depth crossing an active fault holds
potential for unraveling fault zone architecture. With the calibration of theco-site borehole-seismometers, we substantiate the reliability of DAS recordings. And, with this approach, coupled with high-resolution recordings inhigh seismicity region, constitutes our endeavor to uncover seismic insights,
enhancing our comprehension of source and site heterogeneity in earthquakes
across local to regional scales. Our exploration includes analyzing earthquake
nucleation, source time functions, features in attenuation, and the generationof high frequencies within sub-surfaces. We employed source deconvolution,utilizing aftershocks as Empirical Green’s functions up to 10Hz, to decipher
slip heterogeneity within regional fault systems. On the advantage of the highspatial resolution DAS data, we directly apply the Q-operator to the timeseries at every channel to map the Q-structure crossing the fault zone and subsurface to avoid the influence from coda while apply seismic spectra analysis.
The detailed mapping in attenuation could improve the uncertainties in earthquake source parameters estimations, namely the corner frequency and stressdrop. As the feature of the attenuation in the fault zone might mainly related
to fractured damage zone and thus the possible correlation to porosity andpermeability, which led to the structure for the fluid flow in the fault zone, thatis crucial for the understanding of the earthquake rupture dynamics, and its
triggering. We demonstrated the application of meter scale spatial resolution
and high sampling rate of in-situ downhole optical fiber could be beneficial tomap the physical architecture of a waek zone, and good capability to decipher
the slip and stress heterogeneity of regional fault system.
Dascore: A Python Library for Distributed Acoustic Sensing
CHAMBERS, D. J. A., Colorado School of Mines, Colorado, USA,
derrickchambers@mines.edu; MARTIN, E. R., Colorado School of Mines,
Colorado, USA, eileenrmartin@mines.edu; JIN, G., Colorado School of Mines,
Colorado, USA, gjin@mines.edu; TOUREI, A., Colorado School of Mines,
Colorado, USA, tourei@mines.edu; GIRARD, A., Colorado School of Mines,
Colorado, USA, agirard@mines.edu; LELLOUCH, A., Tel Aviv University,
Tel Aviv, Israel, ariellel@tauex.tau.ac.il; YUAN, S., Colorado School of Mines,
Colorado, USA, syuan@mines.edu; MENDOZA, M., University of Colorado
Boulder, Colorado, USA, manuel.mendoza@colorado.edu
In the past decade, distributed acoustic sensing (DAS) has found many monitoring applications in disparate areas such as hydrocarbon exploration andextraction; glaciology; hydrology; urban geophysics; induced, regional, andglobal seismology; and several more. Many of these DAS applications have
proven transformative to geoscience research. However, the lack of mature
open-source software for working with DAS data has resulted in redundantefforts to implement data input/output (IO) and processing routines among
various research groups. To help more new users quickly begin working withDAS data, we developed DASCore, an open-source Python library for analyzing, managing, and visualizing DAS data. DASCore provides IO support
for various DAS file formats and file system archives, common processing
routines, and static visualizations. It implements an intuitive object-oriented
interface, has an extensive automated test suite, and is comprehensively
documented. DASCore is a foundational package for the broader DAS Data
Analysis Ecosystem (DASDAE) and as such its main goal is to accelerate thedevelopment of other DAS applications.
Characterizing South Pole Firn Structure With Fiber Optic
Sensing
YANG, Y., California Institute of Technology, California, USA, yanyang@caltech.edu; ZHAN, Z., California Institute of Technology, California,
USA, zwzhan@caltech.edu; REID-MCLAUGHLIN, A., California Instituteof Technology, California, USA, areidmcl@caltech.edu; BIONDI, E.,
California Institute of Technology, California, USA, ebiondi@caltech.edu;

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KARRENBACH, M., Seismics Unusual, California, USA, martinkarrenbach@gmail.com; WIENS, D. A., Washington University in St. Louis, Missouri,
USA, doug@wustl.edu; ASTER, R. C., Colorado State University, Colorado,
USA, Rick.Aster@colostate.edu
The firn layer covers approximately 99% of Antarctica’s ice sheets and critically protects glacial ice from the external environment. Its accurate physicaland geophysical characterization is thus crucial for understanding ice sheet
evolution, including issues critical to glacial mass balance and the effects ofclimate change. Our study utilizes Distributed Acoustic Sensing (DAS) technology to transform an 8-km fiber-optic cable between the Amundsen-Scott
South Pole Station and the QSPA Global Seismographic Network station
into a dense, low-maintenance, and continuously interrogated seismic array.
With its 1 m spatial and 1000 Hz temporal resolution, this array successfully
resolves a significant number of seismic wave propagation modes, providing
detailed insights into both P and S wave velocities with depth. Comparing ourdata with the South Pole Ice Core, we have formulated a more precise, East
Antarctica-specific empirical relation, significantly enhancing firn density
estimations in the region. In addition to isotropic structures, we employ colocated geophones to also resolve the firn’s anisotropic structure. Moreover,continuous year-round DAS monitoring enables the investigation of temporal
firn variations. Our results underscore the transformative potential of DAS
technology in glaciology and firn analysis, providing new insights into ice
sheet seismology.
Assessing Distributed Acoustic Sensing (DAS) for
Moonquake Detection
HUSKER, A., California Institute of Technology, California, USA, ahusker@
caltech.edu; ZHAI, Q., California Institute of Technology, , USA, qzhai@
caltech.edu; ZHAN, Z., California Institute of Technology, , USA, zwzhan@
caltech.edu; BIONDI, E., California Institute of Technology, California, USA,ebiondi@caltech.edu; YIN, J., California Institute of Technology, , USA,yinjiuxun@icloud.com; CIVILINI, F., NASA Goddard, , USA, francesco.
civilini@nasa.gov; PEREIRA DA COSTA, L., NASA JPL, , USA, luis.d.pereira.
da.costa@jpl.nasa.gov
We present how DAS could greatly enhance geophysical networks on theMoon. Moonquakes can provide valuable insights into the lunar interior andits geophysical processes. However, extreme scattering of the lunar seismic
wave makes seismic phase identification and source characterization difficult
on individual seismic stations. DAS, on the other hand, can detect the fullwaveform even in especially high scattering environments to pick up scatteredphases that were previously unidentified by standard low-density seismic
networks. We explore the potential of DAS to detect moonquakes if installedon the lunar surface by answering two questions: How could DAS advance
Moon seismology? Can DAS detect moonquakes? To answer, we first generate
synthetic DAS recordings to show that DAS is especially suited to measuring moon quakes in highly scattered environments with low seismic velocity
on the Moon’s near surface. Then, we compare the real Apollo seismometerrecordings to the minimum resolution of DAS on the Earth in the very lownoise environment of Antarctica. We find that all thermal moonquakes previously recorded by the Apollo geophones can be detected by current DAS.
Current DAS sensitivity will also allow for 60% of the meteoroid impacts andmoonquakes that were recorded hemisphere-wide on all the Apollo seismometers to be detected. Our results show that this detection percentage should
increase to over 90% with achievable and expected improvements in DAS
equipment. Overall, we show that current DAS technology would be able
to detect on average about 15 moonquakes per day, with large fluctuations
depending on recording during lunar sunrise/sunset and the moon’s distancefrom perigee/apogee. Utilizing DAS for lunar seismology promises a transformative advance in analyzing wave propagation on the moon, paving the way
for significant insights into the Moon’s internal structure.
Rupture Imaging of Firn Quakes with Distributed Acoustic
Sensing
LI, J., California Institute of Technology, California, USA, jxli@caltech.edu;
YANG, Y., California Institute of Technology, California, USA, yanyang@caltech.edu; BIONDI, E., California Institute of Technology, California,
USA, ebiondi@caltech.edu; REID-MCLAUGHLIN, A., California Instituteof Technology, California, USA, areidmcl@caltech.edu; ASTER, R. C.,
Colorado State University, Colorado, USA, rick.aster@colostate.edu;
WIENS, D., Washington University in St. Louis, Missouri, USA, doug@
wustl.edu; KARRENBACH, M., Seismic Unusual, LLC, California, USA,

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martinkarrenbach@gmail.com; ZHAN, Z., California Institute of Technology,
California, USA, zwzhan@caltech.edu
A firn quake is an unusual seismic event resembling an earthquake but occuring in the snowfields and often accompanied by an audible “whumpf ” sound.
This intriguing phenomenon is explained to be caused by the collapse of a
weak snow layer. However, historic reports and quantitative measurementsof firn quakes are limited. Here, we report the most distinct firn quakes everrecorded, with their seismic signals clearly captured by a distributed acoustic
sensing (DAS) array near the South Pole. The DAS array, deployed in January2023, extends about ~8 kilometers from the South Pole station to the QSPA
seismograph site and consists of ~8,000 channels. The firn quakes, induced
during seismic surveys, were both felt directly during the fieldwork and recognized on the DAS records. The seismic records of firn quakes show distinct
surface waves with multiple Rayleigh modes generated by the propagating
source, with rupture durations varying from a few seconds to about 15 seconds. To investigate the kinematic features of firn quakes, we develop a novel
back-projection rupture imaging method, utilizing Rayleigh waves together
with an iterative mode striping technique. Our method yields an accurate
estimation of rupture speed, depth, and magnitude, which provides criticalinsights into the physical mechanism of firn quakes.
SUBMERSE Project Paves the Way for Continuous Fiberoptic Monitoring in the Oceans with Submarine
Telecommunications Cables
TILMANN, F., GFZ Potsdam, Potsdam, Germany, tilmann@gfz-potsdam.de;
ATHERTON, C., GÉANT, Amsterdam, Netherlands, chris.atherton@geant.
org; KVATADZE, R., GRENA, Tbilisi, Georgia, ramaz@grena.de; ASERO,
C., EFIScentre, Brussels, Belgium, asero@efiscentre.eu; EVANGELIDIS,
C., NOA, Athens, Greece, cevan@noa.org; CHARALAMPAKIS, M., NOA,
Athens, Greece, cmarinos@noa.gr; LANDRØ, M., NTNU, Trondheim,
Norway, martin.landro@ntnu.no; RONDENAY, S., University of Bergen,
Bergen, Norway, Rondenay@uib.no; OTTEMÖLLER, L., University ofBergen, Bergen, Norway, lars.ottemoller@uib.no; CORELA, C., University of
Lisbon, Lisbon, Portugal, ccorela@fc.ul.pt; MATIAS, L., University of Lisbon,
Lisbon, Portugal, lmatias@fc.ul.pt; CUSTÓDIO, S., University of Lisbon,
Lisbon, Portugal, sicustodio@fc.ul.pt; STROLLO, A., GFZ Potsdam, Potsdam,
Germany, strollo@gfz-potsdam.de; XIAO, H., GFZ Potsdam, Potsdam,
Germany, han.xiao@gfz-potsdam.de; KOUMANTAROS, K., GRNET,
Athens, Greece, kkoum@admin.grnet.gr; BOZORGEBRAHIMI, K., SIKT,
Trondheim, Norway, kurosh.bozorgebrahimi@sikt.no; PINTO, A., FCCN,
Lisbon, Portugal, Ana.Pinto@fccn.pt; VOHNOUT, R., CESNET, Budweis,
Czechia (Czech Republic), rudolf.vohnout@cesnet.cz; TEIXEIRA, M.,
Redclara, São Paulo, Brazil, marco.teixeira@redclara.net; TURZA, K., PSNC,
Poznan, Poland, kturza@man.poznan.pl; MORTEN, J., ASN, Trondheim,
Norway, jan_petter.morten@asn.com; MIHAI, H., DEIC, Aarhus, Denmark,hannah.mihai@deic.dk
In the last few years, a number of technologies to use fiber optic cables as sensing devices have been established, among them Distributed Acoustic Sensing(DAS) and State-of-Polarisation (SoP). The potential of these technologies formonitoring a range of Earth System parameters in submarine cables has been
demonstrated through several pilot experiments, but full integration with
telecommunication infrastructure has not yet been achieved. The SUBMERSE(SUBMarinE cables for ReSearch and Exploration) project links Research and
Education Networks (RENs), universities, research institutes and industry
to establish multi-method monitoring along submarine optical telecommunication cables at several key oceanic cable routes branching off from Sines
in Portugal, Madeira, Svalbard and in the Ionian Sea (cable linking Preveza,
Greece to Crotone, Italy), and in addition the Transatlantic cable between
Fortaleza and Sines. Those pilot sites should serve as a blueprint for establishing continuous monitoring services along many more cables.
The project comprises technical developments for integrating DAS and
SoP measurements, for establishing differential SoP measurements between
repeaters and for operating DAS in a co-existence mode, i.e., in fibers also carrying telecommunications traffic. Furthermore, a range of geoscientific andmarine biology use cases are included, which seek to establish code/services
for monitoring earthquakes and tsunamis, tracking whales, measuring the sea
state and other Earth System variables.
The data collected by SUBMERSE will be distributed according to FAIR
principles through established community-specific distribution channels such
as EIDA for seismological data, with exceptions for security-sensitive time
periods, and spatial or frequency ranges.
The first data from test sites are now being delivered and will be presented in this presentation. Furthermore, an outlook on the seismologicalreal-time and archive products will be provided.

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Monitoring Soil Moisture With Distributed Acoustic
Sensing in the Agricultural Setting
SHI, Q., University of Washington, Washington, USA, qibins@uw.edu;
COLLINS, J., Harper Adams University, Newport, United Kingdom,jcollins@live.harper.ac.uk; DENOLLE, M., University of Washington,
Washington, USA, mdenolle@uw.edu; FENG, K., University of Washington,
Washington, USA, kffeng@uw.edu; JEFFERY, S., Harper Adams University,
Newport, United Kingdom, sjeffery@harper-adams.ac.uk; NISSEN-MEYER,
T., University of Exeter, Exeter, United Kingdom, tarjenm@gmail.com;
WILLIAMS, E. F., University of Washington, Washington, USA, efwillia@
uw.eduDistributed Acoustic Sensing (DAS) emerges as a non-intrusive and highresolution method for monitoring crucial agricultural soil properties. The
deployment of fiber optic cables in the soil ensures minimal disturbance tothe soil environment, enabling the comprehensive monitoring of soil healthparameters, including moisture, density (compaction), temperature, andorganic content through high-resolution ambient seismic signals. Each ofthese properties involves dynamic processes from multiple perspectives, posing challenges for extraction from a single observation type. In this study, we
conducted a two-day DAS observation spanning approximately 150 meters
in a farmland setting with diverse agricultural treatments. Employing ambient noise interferometry, we derived seismic velocity variations in both space
and time, revealing a notable correlation between relative seismic velocity
and soil moisture. A spectral analysis confirmed that ambient noise power
spectral density serves as reliable proxies of precipitation intensity for shallow
farmland soil. In addition to DAS, we co-located a Distributed Temperature
Sensing (DTS) observation system to record the high-resolution temperatureof the near-surface soil, influenced by soil moisture and air temperature diffusion. By combining the precipitation and surface temperature data with independently measured soil temperature, we developed a model representing thephysical system of rainfall elastic load, diffusion in the soil, and evaporation.
Our findings indicate that rainfall leads to an abrupt increase in soil moistureand a sudden drop in seismic velocity, followed by gradual recovery during
the downward diffusion process (drainage). Notably, the substantial rise inseismic velocity, up to 60% at some plots depending on the tilling treatment,is best explained by thermoelasticity. We explore how the degree of tilling
affects drainage and soil temperature. DAS exhibits substantial potential for
real-time precision agriculture monitoring, offering opportunities to enhanceresource management, sustainability, and crop productivity in the face of achanging climate.
Spatio-Temporal Fidelity of DAS Arrays to Compression
Seismic Signals: Impacts on Real-Time Source Estimates
SALAREE, A., University of Michigan, Michigan, USA, salaree@umich.
edu; MIAO, Y., University of Michigan, Michigan, USA, yaolinm@umich.
edu; SPICA, Z., University of Michigan, Michigan, USA, zspica@umich.edu;
NISHIDA, K., Earthquake Research Institute, University of Tokyo, Tokyo,
Japan, knishida@eri.u-tokyo.ac.jp; YAMADA, T., Earthquake ResearchInstitute, University of Tokyo, Tokyo, Japan, yamada@eri.u-tokyo.ac.jp;
SHINOHARA, M., Earthquake Research Institute, University of Tokyo,
Tokyo, Japan, mshino@eri.u-tokyo.ac.jp
DAS recordings of $P$ waves have traditionally been associated with the shear
component of oblique arrivals resulting in axial phase shift along the cables.
However, careful examination of the records created by 478 local events inJapan reveals modal perturbations along the cable resulting from normal incidence of both P and S waves. We model this phenomenon as large scale oscillations (typically over a few kilometers) of the cable under localized forces
with the cable axial and torsional tensions as restoring agents. Based on ourmodel, spatial and temporal frequencies of the oscillations are determinedby cable properties, almost regardless of earthquake magnitude. This is while
modal amplitudes are significantly affected by the velocity structure of the
deployment site, as well as earthquake radiation pattern on second order. The
modal property of these waves has significant implications in both detection
and magnitude estimation of earthquakes and as such needs to be consideredin hazard assessment and early warning in active subduction zones.
Understanding the Rupture Process of the Mw 7.6 2022
Michoacán Earthquake With Distributed Acoustic Sensing
MIAO, Y., University of Michigan, Michigan, USA, yaolinm@umich.edu;
HUANG, Y., University of Michigan, Michigan, USA, yiheh@umich.edu;

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NEO, J., University of Michigan, Michigan, USA, neoj@umich.edu; SPICA,
Z., University of Michigan, Michigan, USA, zspica@umich.edu
Mexico City, the most populated city in the Americas, undergoes significant
seismic hazards. Yet, the city is sparsely instrumented compared to otherpopulated and seismically active regions. Therefore, we installed a DAS interrogator in Mexico City in the summer of 2022 to collect one year of data forobservational studies in the region. On Sep. 19, 2022, a Mw 7.6 earthquake
occurred in Michoacán, approximately 450 km away from the city. The DAS
system provides us with a high-quality, ultra-dense, and unique dataset thatcan be used to study the rupture process of the earthquake, which is essential
to refine our understanding of regional fault systems and potential seismic
hazards.
We apply a recently developed higher-frequency back-projection
method to obtain a novel 3-D earthquake rupturing image and test the limit
of DAS for earthquake source characterization. We integrate DAS recordings
with data from regional and global seismic stations to investigate the rupture
process of the Michoacán earthquake at different spatial scales at a frequency
range of 0.2-1 Hz. With preliminary analysis, we successfully identify andlocate two subevents in a 3D rupturing space, and we further validate the outcomes with conventional seismometers. These results demonstrate the great
potential of enhancing rupture imaging by integrating DAS arrays in earthquake source studies.
Distributed Environmental Sensing Using Trans-Oceanic
Subsea Cables
MAZUR, M., Nokia Bell Labs, New Jersey, USA, mikael.mazur@nokia-belllabs.com; FONTAINE, N. K., Nokia Bell Labs, , USA, nicolas.fontaine@nokiabell-labs.com; KEHELLER, M., University of Colorado Boulder, Colorado,
USA, megan.kelleher@colorado.edu; KAMALOV, V., Valey Kamalov LLC,
Florida, USA, vkamalov@gmail.com; RYF, R., Nokia Bell Labs, New Jersey,
USA, roland.ryf@nokia-bell-labs.com; DALLACHIESA, L., Nokia BellLabs, New Jersey, USA, lauren.dallachiesa@nokia-bell-labs.com; CHEN,
H., Nokia Bell Labs, New Jersey, USA, haoshuo.chen@nokia-bell-labs.com;
NEILSON, D. T., Nokia Bell Labs, New Jersey, USA, david.neilson@nokiabell-labs.com; QUINLAN, F., National Institute of Standards and Technology,
Colorado, USA, franklyn.quinlan@nist.gov; BIONDI, E., California Instituteof Technology, California, USA, ebiondi@caltech.edu
We present a distributed fiber optic sensing (DFOS) prototype capable of measurements beyond the first repeater of subsea cables. The cable spans approximately 6,400 km and includes more than 80 optical repeaters. Our system iscapable of distributed measurements of both phase and polarization of thebackscattered signal, including the Rayleigh backscattering from the silica
fiber and point reflections from fiber Bragg gratings (FBGs) present within
the optical repeaters. Each point along the cable is measured in real-time, withzero dead time and covering a frequency range from mHz to kHz. This measurement spans all degrees of freedom supported by the fiber and therefore
completely characterizes its linear response over the measurement bandwidth.
During a 1 month measurement period, all world-wide earthquakes
with >6 magnitude were detected. Here we present a detailed analysis of themeasured signatures from two earthquakes and ocean swells. The first event isa 6.3 magnitude earthquake with an epicenter in California, while the second
event is a 7.1 magnitude event located in Indonesia. The recorded signaturesfrom our about 80 points along the ocean floor are compared with data fromthe two available seismic stations in the North Atlantic ocean. Our measurement results show good quantitative agreement with the waveforms recordedby the land-based seismic stations. In addition, we show real-time tracking of
the seismic waves as they propagate along the cable and use this to determine
their relative speed. This technology is a major step towards 3D beamforming and imaging using multiple subsea cables. We also show measured cable
movements from the mid-Atlantic ridge, whose origin to date is not fully
understood.
Finally, this sensing prototype does not disrupt telecom traffic and uses
commercial off-the-shelf components, thereby providing a scalble path torealize distributed fiber optic sensing over the entire subsea network.
Enhancing Seismic Monitoring in Cook Inlet, Alaska:
Integration of Distributed Acoustic Sensing with the
Existing Seismic Network for Advanced Earthquake
Denoising, Detection and Location
SHI, Q., University of Washington, Washington, USA, qibins@uw.edu; NI,
Y., University of Washington, Washington, USA, niyiyu@uw.edu; DENOLLE,
M., University of Washington, Washington, USA, mdenolle@uw.edu;

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WILLIAMS, E. F., University of Washington, Washington, USA, efwillia@
uw.eduOffshore Distributed Acoustic Sensing (DAS) has emerged as a powerful technology for seismic monitoring, complementing the existing seismic networks
in coastal regions. However, the offshore DAS data often combine signalsthat are new to the eyes of seismologists, including new types of instrumental noise, fiber coupling issues, ocean waves, and microseism that overprint
earthquake signals. The overlap of these signals hinders accurate detection
and location of earthquakes. In this study, we propose an advanced architecture for earthquake monitoring in Cook Inlet, Alaska, by integrating theoffshore DAS with the Alaskan regional seismic network. The proposed architecture incorporates machine-learning-based denoising, phase picking, andevent relocation, leveraging an ensemble approach with DAS and broadband
observations. A denoising neural network, employing self-supervised learning, is trained on randomly masked real DAS recordings for 2000 earthquakes.
The trained denoiser effectively removes DAS signals lacking spatial-temporal
coherence. Subsequently, the denoised DAS data enables the detection oflower-magnitude earthquakes and provides significantly more phase picks
than the original noisy data, particularly for the smallest events. We then apply
the trained denoiser to the M0.6+ earthquakes in the Cook Inlet region. The
ensemble-learning approach is applied to pick P and S arrival times on both
the denoised DAS and broadband recordings. In the final step, we relocate
the detected earthquakes using their P and S phase picks of the integrated
DAS and broadband seismic network. We quantify the improvement of adding DAS to a regional network by quantifying uncertainties earthquake source
parameters This comprehensive approach results in more efficient and robust
earthquake detection and location compared to traditional seismic networks
in the offshore region. The proposed architecture holds significant promise forearthquake early warning and hazard mitigation, demonstrating the potential
for enhanced seismic monitoring networks in offshore environments.
On DAS Recorded Strain Amplitude
FORBRIGER, T., Karlsruhe Institute of Technology, Karsruhe, Germany,
thomas.forbriger@kit.edu; KARAMZADEH, N., University of Munster,
Munster, Germany, nasim.karamzadeh@uni-muenster.de; AZZOLA, J.,
Karlsruhe Institute of Technology, Karsruhe, Germany, jerome.azzola@
kit.edu; WIDMER-SCHNIDRIG, R., University of Stuttgart, Stuttgart,
Germany, widmer@gis.uni-stuttgart.de; GAUCHER, E., Karlsruhe
Institute of Technology, Karlsruhe, Germany, emmanuel.gaucher@kit.edu;
RIETBROCK, A., Karlsruhe Institute of Technology, Karlsruhe, Germany,
rietbrock@kit.edu
Distributed Acoustic Sensing (DAS) has become popular for recording seismic waves in recent years. The ability to record waveforms with useful phase
information has been demonstrated in numerous studies. Validation of thesensitivity factor with respect to strain is commonly done by application offiber stretching-devices in laboratory environment. The lack of in-situ calibration with respect to actual rock strain leaves room for unknown amplitude loss caused by imperfect coupling of the cable jacket to the rock andthe loss through several layers of coating of the fiber in the cable. We use
DAS-recordings together with recordings of the colocated invar-wire strainmeter array at BFO and an STS-2 broad-band seismometer to investigate thecoupling of DAS fibers in situ. Two types of optical fiber cables are installedin parallel. One is a conventional telecommunication cable, where fibers areembedded in a gel-type substance to avoid damage potentially caused bystraining the cable jacket. The other is a dedicated tight-buffered DAS cable.
We compare recordings from a section where the cables are simply unreeledwith recordings from a section, where sandbags are densely put on the. We use
signals from the Mw 7.7 and 7.6 East Anatolian Fault earthquakes on February
6th 2023. A comparison of signals from all three instruments is possible in
the frequency-band between 50 mHz and 0.2 Hz. At lower frequencies the
DAS signal-to-noise ratio is insufficient. At higher frequencies the invar-wirestrainmeters show a parasitic response to vertical ground motion. We find thatthe DAS fibers do not pick up the full amplitude of rock-strain. Amplitude loss
depends on the type of cable. The tight-buffered and the telecommunication
cable pick up about 1/2 and 1/4 of the amplitude, respectively. Surprisingly
the application of sandbags has little effect. Both sections show similar discrepancy in amplitude. The signal loss apparently is not due to the imperfectcoupling of the cable jacket to the rock, but due to reduced internal couplingof the fiber to the cable.
Evaluation of Passive Source DAS Methods on the Source
Physics Experiment (SPE) Phase IIPORRITT, R., Sandia National Laboratories, New Mexico, USA, rwporritt@
gmail.com; STANCIU, A. C., Sandia National Laboratories, New Mexico,

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USA, astanci@sandia.gov; ABBOTT, R. E., Sandia National Laboratories,
New Mexico, USA, reabbot@sandia.gov; LUCKIE, T. W., Sandia National
Laboratories, New Mexico, USA, twlucki@sandia.gov
Distributed Acoustic Sensing (DAS) is an emerging technology capable ofrecording the acoustic wavefield at unprecedented spatial resolution. However,this new tool requires significant refinements before it becomes operational
for explosion monitoring objectives. Recent studies have shown significant
development of array processing with DAS data. In this contribution we
explore three such array processing methods including DAS strain-rate data
versus geophone measured ground motion, beamforming for event parameters, and machine learning based denoising. We first validate the methods
on published results and then apply to high SNR data from the Source Physics
Experiment Phase II. We further investigate these methods as a function of
DAS array design and SNR through the use of synthetic signals and noise.
The Source Physics Experiment (SPE) would not have been possible without the support of many people from several organizations. The authors wish
to express their gratitude to the National Nuclear Security Administration,
Defense Nuclear Nonproliferation Research and Development (DNN R&D),
and the SPE working group, a multi-institutional and interdisciplinary groupof scientists and engineers.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525
Lossy Compression and Reconstruction of Distributed
Acoustic Sensing Data Using Deep Learning
NI, Y., University of Washington, Washington, USA, niyiyu@uw.edu;
DENOLLE, M. A., University of Washington, Washington, USA, mdenolle@
uw.edu; LIPOVSKY, B., University of Washington, Washington, USA, bpl7@
uw.edu; SHI, Q., University of Washington, Washington, USA, qibins@
uw.edu; PAN, S., University of Washington, Washington, USA, shawnpan@
uw.edu; KUTZ, J., University of Washington, Washington, USA, nathankutz@
googlemail.com
Distributed Acoustic Sensing (DAS) is a new seismic observation method.
DAS dramatically expands the ability of dense seismic observation and has
been used for ocean observation, sub-surface imaging, volcano monitoring,and earthquake characterization. While the high rate of data benefit researchanalysis, they are problematic for data transmission and storage and limit thereal-time or large-scale application of DAS. Data compression algorithms canaccelerate the transmission by transforming the raw data into smaller size ,however, at the cost of more computing time and/or data distortion. Current
state-of-the-art data compression techniques for DAS involve either a low
compression rate (40%) for a lossless compression (Dong et al., 2022) or lossy
compressions (Issah and Martin, 2023) that retain the low rank representationof the data.
In this study, we compress and reconstruct an ocean bottom fiberoptic sensing dataset using Deep Learning, particularly Implicit Neural
Representation and Shallow Recurrent Decoder. The dataset recorded on two
seafloor telecommunication cables in Alaska’s Lower Cook Inlet samples ~16k
channels at 250 Hz. On the 2.5 Hz decimated dataset, we reach a 8x (12.5%)
and 10x (10%) compression ratio while retaining a maximum mean squareerror of 0.03 and 0.05, respectively. In the reconstruction, ocean surface gravity waves that are dominantly observed in the raw data are effectively reconstructed by both methods and can be further used for physical oceanography.
We test the methods on earthquake waveforms and demonstrate feasibility of
the compression for seismological use cases. At last, we evaluate these methods by comparing their accuracy, adaptivity, computing expense and generalizability on the near real-time data transmission using our edge computing
experiment in Alaska Cook Inlet.
Exploring Urban Distributed Acoustic Sensing Datasets
With Scattering Networks
VIENS, L., Los Alamos National Laboratory, New Mexico, USA, lviens@lanl.gov; SEYDOUX, L., Université Paris Cité, Paris, France, seydoux@ipgp.
fr; DELBRIDGE, B. G., Los Alamos National Laboratory, New Mexico, USA,delbridge@lanl.gov
Distributed Acoustic Sensing (DAS) probes fiber-optic cables with repeatedlaser pulses to measure the Earth deformation along the cable. The extended
spatio-temporal nature of DAS time series provides a vast amount of information about the seismic wavefield and the related processes occurring at
the Earth’s surface and interior. Urban DAS datasets have been shown tocontain various types of natural (e.g., earthquakes) and anthropogenic (e.g.,
carry blasts, car traffic) signals, but new signals and/or hidden patterns arestill likely to be discovered. We mine continuous DAS data in urban areas in

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an unsupervised manner using a deep scattering network — a convolutional
neural network with convolutional filters restricted to wavelets. Deep scattering networks allow us to directly build an accurate representation of each DAS
dataset from which we extract the most relevant information with independent component analysis (ICA) and Uniform Manifold Approximation and
Projection (UMAP) algorithms. The ICA representation of the data is thenclustered with dendrograms together with UMAP to provide a 2D representation of the data. We use external measurements, such as earthquake catalogs
and weather stations to understand the output of the clusters and the UMAP
representations. This study shows the potential of unsupervised methods toinvestigate the extent of the nature of signals contained in terabytes of data
recorded by DAS.

Advancing Seismology with Distributed Fiber Optic
Sensing [Poster Session]
Poster Session • Friday 3 May
Conveners: Ettore Biondi, California Institute of Technology(ebiondi@caltech.edu); Daniel Bowden, ETH Zürich (daniel.
bowden@erdw.ethz.ch); Derrick Chambers, Colorado Schoolof Mines (derrickchambers@mines.edu); Julia Correa,
Lawrence Berkeley National Laboratory (juliacorrea@lbl.
gov); Manuel Mendoza, University of Colorado, Boulder(Manuel.Mendoza@colorado.edu); Krystyna Smolinski,
ETH Zürich (krystyna.smolinski@erdw.ethz.ch); Veronica
Rodriguez Tribaldos, GFZ Potsdam (verort@gfz-potsdam.
de); Shihao Yuan, Colorado School of Mines (syuan@mines.
edu)
poster 1
Matched-Filter Earthquake Detection Applied to City-ScaleDAS Fibre-Optic Systems in Aotearoa New Zealand: What
More Can We Detect?
CHAMBERLAIN, C. J., Victoria University of Wellington, Lower Hutt, New
Zealand, calum.chamberlain@vuw.ac.nz; MCNAB, A., FiberSense, California,
USA, andy.mcnab@fibersense.com; LINDSEY, N., FiberSense, California,
USA, nate.lindsey@fibersense.com; TOWNEND, J., Victoria Universityof Wellington, Wellington, New Zealand, john.townend@vuw.ac.nz; VAN
WIJK, K., University of Auckland, Auckland, New Zealand, k.vanwijk@
auckland.ac.nz
Matched-filters have been successfully applied to detect earthquakes recorded
using Distributed Acoustic Sensing (DAS) systems in multiple settings including to detect geothermal seismicity and aftershocks. This previous work has
demonstrated that matched-filters applied to DAS systems can be used todetect additional seismicity missed by standard cataloguing methods applied
to standard sensor networks. Similarly, matched-filters and recently developed machine-learning enhanced workflows have been shown to provide
enhanced detection performance on seismic recordings made using standard
seismometers. Thus far, little work has been done to ameliorate these methods
and datasets to provide optimal earthquake detection datasets and workflows.
In this work we test the sensitivity of matched-filters applied to two cityscale DAS arrays in Aotearoa New Zealand to reliably detect small aftershocks
from a M 5.9 earthquake above the Hikurangi subduction zone. We also compare the sensitivity of the DAS arrays to multiple standard and state-of-the art
earthquake detection methods applied to standard seismometer data. Using
this case study, we provide a logical comparison between advanced methods
applied to high-quality data and relatively simple matched-filter methods
using high-fold data from DAS arrays to evaluate the relative benefits of eachapproach. We also explore a combined approach using DAS data alongside
traditional seismic data to attempt to achieve an optimal detection solution.
poster 2
Using AIS Data to Determine the Location of Ocean Bottom
Fiber Optic Cables
COLLARES, M. P., University of Michigan, Michigan, USA, collares@umich.
edu; SPICA, Z., University of Michigan, Michigan, USA, zspica@umich.edu;

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VIENS, L., Los Alamos National Laboratory, New Mexico, USA, lviens@lanl.
gov
Undersea fiber-optic cables form the backbone of global telecommunication
networks, facilitating rapid data transmission across continents. However, thecorrect location of telecom subsea cables is generally inaccurate, if not completely unknown, or even sometimes undisclosed for safety reasons, as fiber
optic cables represent a crucial geopolitical asset. Unlike on land, where tap
tests with precise GPS data can be performed, subsea cables are not easily
and inexpensively accessible. This limits their potential for proper seismic andenvironmental monitoring of near-coastal regions using Distributed Acoustic
Sensing (DAS).
This study presents an approach to enhance the geolocation of undersea
fiber-optic cables using Automatic Identification System (AIS) data from ships
and large vessels transiting above subsea cables. We use a 4-month dataset
from a cable located offshore Florence, OR. The first 50 km of the cable wereprobed with a Febus A1R interrogator unit using a 20 m channel spacing,a 100 Hz sampling rate, and a 40 m gauge length. During this experiment,
we identified 186 vessels of different types and sizes, many crossing the cablemultiple times. We precisely determine the location of some channels using
the noise generated by ships and correlate it with AIS data. This study allows
us to provide additional constraints on the location of fiber-optic cables and
DAS channels.
poster 3
Near-Source T-Wave Observations in the North Atlantic
Using Distributed Acoustic Sensing
SCHLAPHORST, D., University of Lisbon, Lisbon, Portugal, dschlaphorst@
fc.ul.pt; LOUREIRO, A., Regional Agency for the Development ofResearch, Technology and Innovation, Funchal, Portugal, afonsoloureiro@afonsoloureiro.net; MATIAS, L., University of Lisbon, Lisbon, Portugal,
lmmatias@fc.ul.pt; CUSTÓDIO, S., University of Lisbon, Setubal, Portugal,susana@fc.ul.pt; CORELA, C., University of Lisbon, Lisbon, Portugal,
ccorela@ciencias.ulisboa.pt; CALDEIRA, R., Regional Agency for theDevelopment of Research, Technology and Innovation, Funchal, Portugal,
rui.caldeira@oom.arditi.pt
T phases are acoustic waves that propagate in the low velocity zone of theoceanic sound channel that acts as a waveguide, the SOFAR channel. They
are generated by earthquakes through the conversion of seismic energy at thesolid-liquid interface, but the exact processes involved are still under debate.
Due to their low attenuation and slow propagation velocity, these arrivals are especially useful for the detection and characterisation of small earthquakes in marine basins, as they can improve the location of the event while
their waveforms can yield information on source rupture.
In October 2023, a Distributed Acoustic Sensing (DAS) interrogator
was installed on the GeoLab dark fibre in the Atlantic, starting at the Praia
Formosa CLS, in Madeira Island, Portugal. The instrumentation of this cableis part of a project by ARDITI and the Oceanic Observatory of Madeira where
oceanographic data recorded by buoys and autonomous vessels are combinedwith DAS data to obtain a global view of the underwater environment ofMadeira Island in all its physical, chemical and biological aspects, including
the characterisation of regional seismicity. This initiative is also linked to the
SUBMERSE project, as the Madeira cable is a pilot site to establish continuous
DAS monitoring along many more submarine fibre-optic cables.
On October 27th, a near-source (<40 km) M2.9 earthquake wasrecorded by the DAS interrogator along the entire cable. The epicentre of theearthquake was east of the Desertas Islands, southeast of Madeira. Besides
the P and S phases, very clear T phases are also visible. The recorded T waves
have strain values larger than those of P and S waves. However, multiple T
phases are identifiable, suggesting different points of conversion or even possible reflections.
This work was funded by the Portuguese Fundação para aCiência e a Tecnologia (FCT) I.P./MCTES through national funds(PIDDAC) – UIDB/50019/2020 (DOI: 10.54499/UIDB/50019/2020),
UIDP/50019/2020 (DOI: 10.54499/UIDP/50019/2020) and LA/P/0068/2020(DOI: 10.54499/LA/P/0068/2020), and by ERC project SUBMERSE,HORIZON- INFRA-2022-TECH-01-101095055.
poster 4
Geolocalization and Preliminary Surface Signals of
Cascadia DAS Array, Port Angeles, Washington
DINGO, H., University of Colorado Boulder, Colorado, USA, hadi3153@
colorado.edu; SHEEHAN, A. F., University of Colorado Boulder, Colorado,
USA, anne.sheehan@colorado.edu; MENDOZA, M. M., University ofColorado Boulder, Colorado, USA, manuel.mendoza@colorado.edu;

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MARTIN, E. R., Colorado School of Mines, Colorado, USA, eileenrmartin@
mines.edu
In April 2023 our team conducted a Distributed Acoustic Sensing (DAS)
experiment using dark (unlit) fiber from a 4.5 km telecommunication cablein Port Angeles, Washington, situated above the Cascadia Subduction zone.
Despite the infrequency of megathrust earthquakes on this margin over the
past centuries, it is an area of concern due to the high seismic hazard present.
Our project focuses on leveraging onshore DAS for seismicity monitoring andgaining insights into the shallow subsurface of Port Angeles. This presentation
outlines the geolocalization methods employed for channel mapping along thearray, including performing and processing a tap test to map out the channel
locations of the array, which is essential information for future research withthis data. Additionally, preliminary findings regarding the ambient seismic
noise field recorded by the high-resolution DAS array will be discussed. The
continuous sampling along the fiber allows for both high spatial and temporal
resolution, making it valuable for monitoring the subsurface along the array.
The array has picked up a myriad of cultural and noise signals, including traffic from a nearby highway and bike/foot traffic along an adjacent path. Thesepassive seismic signals will be used for ambient noise tomography to deduce
information about properties and structures of sediments below the array, but
the appropriate use of ambient noise first requires careful characterizationof the noise prior to interferometry and tomography. We will examine thecharacteristics of these ambient/cultural seismic signals including their spatial and temporal distribution and the variations in their frequency content.
This analysis sets the groundwork for utilizing ambient noise tomography toestimate shallow shear wave velocities in the subsurface, crucial for assessing
ground motion hazard in the Port Angeles area.
poster 5
Fiber Optic Wellbore Installation for Distributed Acoustic
Sensing at Los Alamos National Laboratory
DONAHUE, C., Los Alamos National Laboratory, New Mexico, USA, cmd@
lanl.gov; MAIER, N., Los Alamos National Laboratory, New Mexico, USA,nmaier@lanl.gov; ROBERTS, P., Los Alamos National Laboratory, New
Mexico, USA, proberts@lanl.gov
Optical Fiber Distributed Acoustic Sensing can be used in wellbores for anumber of applications including to monitor production, monitor wellbore
integrity, and for vertical seismic profiling. The optical fiber is robust in harshenvironments, allows for a dense network of sensors, and is compact. At
Los Alamos National Laboratories (LANL) and the surrounding area, there
are wellbores previously installed for geothermal research and groundwater
monitoring. While these wellbores provide easy access for research related toseismic monitoring and wellbore integrity monitoring using optical fiber, coupling of the fiber to the wellbore casing presents a challenge since the opticalfiber is installed well after installation of the wellbore itself. Here we present efforts to couple, collect, and analyze wellbore optical data recorded on at
LANL and the surrounding area.
poster 6
Use of Distributed Acoustic Sensing as a Tool for
Monitoring Geohazards at Mt. Rainier
GAETE ELGUETA, V. A., University of Washington, Washington, USA,velgueta@uw.edu; LIPOVSKY, B., University of Washigton, Washington, USA,
bpl7@uw.edu; DENOLLE, M., University of Washington, Washington, USA,mdenolle@uw.edu; THELEN, W., U.S. Geological Survey, Washington, USA,wthelen@usgs.gov; KHARITA, A., University of Washington, Washington,
USA, ak287@uw.edu
Distributed Acoustic Sensing (DAS) is a new and expanding technology used
to monitor seismic events with optical fiber cables as a distributed array of
one-dimensional strain sensors. In this work, we investigate the potential ofusing a dark fiber, an optical fiber deployed for telecommunications purposes,
to monitor seismic activity in and around Mt. Rainier, a glaciated, active
stratovolcano in the Cascades Volcanic Arc, USA, and is monitored by the
Cascades Volcano Observatory (CVO) and the Pacific Northwest Seismic
Network (PNSN). Mt. Rainier hosts a broad spectrum of geohazards such as
earthquakes, debris flows, landslides, and various cryospheric hazards such as
icequakes or avalanches that present a risk to nearby urban areas.
In this study, we use DAS recording on a 48 km long cable, with morethan ~ 4,000 channels, buried under the road between Ashford, Washingtonand Henry M. Jackson Memorial Visitor Center on the flank of Mount Rainier.
We apply template matching to the DAS data, using events in the PNSN
earthquake and surface-event catalog to search for events not detected by thepermanent monitoring network. We use the USGS catalog to select a big mag-

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nitude event and then search for it on DAS data; after that, we process thatevent as a template to do the continuous search on the data. In addition to theactivity at the volcano, our dark fiber experiment recorded a tectonic earthquake swarm in August 2023, located in the Western Rainier Seismic Zone.
This more complete earthquake catalog will be used to perform double-difference relocation and tomography to improve our understanding of fault structures within the Western Rainier Seismic Zone. We also perform preliminary
analysis to detect and identify other event types, including surface events, volcano tectonic earthquakes, and other volcanic events. Our study presents thegroundwork for the use of DAS to monitor volcanoes in near real time.
poster 7
Signal Detection With Neural Networks in Dark Fiber
Seismic Data
HOYLE, A. M., Colorado School of Mines, Colorado, USA, austin_hoyle@mines.edu; SMOLINSKI, K., ETH Zurich, Zurich, Switzerland, krystyna.
smolinski@erdw.ethz.ch; BOZDAG, E., Colorado School of Mines, Colorado,
USA, bozdag@mines.edu; WU FUNG, S., Colorado School of Mines,
Colorado, USA, swufung@mines.edu; FICHTNER, A., ETH Zurich, Zurich,
Switzerland, andreas.fichtner@erdw.ethz.ch; BOWDEN, D., ETH Zurich,
Zurich, Switzerland, daniel.bowden@erdw.ethz.ch; KONCA, O., Bogazici
University, Istanbul, Turkey, ozgun.konca@boun.edu.tr; ERGINTAV, S.,
Bogazici University, Istanbul, Turkey, semih.ergintav@boun.edu.tr; KALKANERTAN, E., Istanbul Metropolitan Municipality, Istanbul, Turkey, esra.ertan@
ibb.gov.tr; YAVUS, E., Istanbul Metropolitan Municipality, Istanbul, Turkey,
evrim.yavuz@ibb.gov.tr; UNLU, M., Istanbul Metropolitan Municipality,
Istanbul, Turkey, muhammet.unlu@ibb.gov.tr; DURAN, K., Istanbul
Metropolitan Municipality, Istanbul, Turkey, kemal.duran@ibb.gov.tr
Distributed Acoustic Sensing (DAS) provides continuous and high-resolution
spatial monitoring capabilities along the entire length of the optical fibers
where the ground deformation caused by seismic activity is measured instrain or strain rate. Telecom cables, known as dark fibers, offer a spatiallydense and cost-effective alternative for seismic data collection in urban areas.
We demonstrated recording seismic signals with a telecom cable provided
by the Istanbul Metropolitan Municipality along the Sea of Marmara on the
Anatolian side of Istanbul from February to mid-March in 2023. The collected
data involves various seismic signals, such as teleseismic and local earthquakes, including the East Anatolian earthquakes in February 2023 and theiraftershocks, controlled explosions, traffic, and other cultural noise.
This research aims to demonstrate the detection of local seismic activity in and around Istanbul using DAS data. Monitoring local seismicity isessential to better understand the tectonics and seismic activity in a region.
However, it is challenging to detect or discriminate small earthquakes where
the higher spatial resolution of DAS may be advantageous. To this end, we
first visually inspect all earthquakes (local and teleseismic) and compare ourobservations to data recorded by nearby strong-motion seismometers. Our
goal is to generate a training set to detect local events with natural networks,
specifically those that are difficult to observe by visual inspection. Since wehave a limited data set from Istanbul, which makes the training challenging,
we explore generating additional data from nearby strong-motion seismometers to be included in the training set by converting them to DAS units. To
test the robustness of our tools, we will also demonstrate them with a larger
data set collected in Athens by the ETH Zurich group. We will present ourobservations in DAS data compared to those recorded by classical seismometers in Istanbul and the initial results of our seismic event detection withneural networks for DAS.
poster 8
Modelling Wavefield Complexity for Submarine DAS Data
From Santorini (Greece)
IGEL, J., ETH Zürich, Zürich, Switzerland, jonas.igel@erdw.ethz.ch;
KLAASEN, S., ETH Zürich, Zurich, Switzerland, sara.klaasen@erdw.ethz.
ch; NOE, S., ETH Zürich, Zurich, Switzerland, sebastian.noe@erdw.ethz.
ch; NOMIKOU, P., National and Kapodistrian University of Athens, Athens,
Greece, evinom@geol.uoa.gr; KARANTZALOS, K., National Technical
University of Athens, Athens, Greece, karank@central.ntua.gr; FICHTNER,
A., ETH Zürich, Zurich, Switzerland, andreas.fichtner@erdw.ethz.ch
Distributed Acoustic Sensing (DAS) with existing telecommunication cables
has contributed significantly to the seismological exploration of difficult-toaccess regions such as the ocean bottom. In contrast to the relative simplicity
of deployment of a DAS interrogator on dark fibres, the data can be challenging to analyse and interpret, particularly in geophysically complex areas, as the
wavefield becomes much more complex. In our study focused on the region
around Santorini in the Aegean Sea, we interrogated a 45 km long dark fibre

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extending from Santorini along the ocean bottom to the neighbouring islandof Ios from mid-October to mid-December 2021. This region is of great geophysical interest because of its historical and recent seismic and volcanic activity, especially along the Kolumbo volcanic chain. Alongside the anthropogenic
noise on Santorini, we directly observe the time-variable primary and secondary microseisms along the submarine section of the cable, the latter inducing
slow-moving Scholte waves. Throughout the experiment, we recorded 1021
seismic events with varying strengths and locations.
To better understand the complex wavefield in the region, we takeadvantage of the latest developments in DAS wave propagation modellingusing the spectral-element solver Salvus. We run simulations with varying
levels of complexity, from a simple layered model to the inclusion of topography, bathymetry, and a heterogeneous velocity model. Furthermore, the fullycomplex model allows us to perform backpropagation with the aim of locating
seismic events near the Kolumbo volcanic chain. The simulations with varying
complexity and backpropagations for four different earthquakes highlight thecomplicated wavefield in the region and the challenges of recovering a source
location, even when all complexities are taken into account.
poster 9
Earthquake Detection of the MiDAS Seismic Monitoring
System Containing Downhole Optic-Fiber Distributed
Acoustic Sensing and Borehole Seismometers
LIN, Y., National Central University, Taoyuan, Taiwan, yylinm22@gmail.com;
CHAN, J., National Central University, Taoyuan, Taiwan, draaschan@gmail.
com
Milun fault Drilling and All-inclusive Sensing (MiDAS) project initiated after
the destructive 2018 M6.4 Hualien, Taiwan, earthquake. The project successfully drilled through the Milun fault, which was one of the main rupture faults
in the Hualien earthquake, in Hole A (700 m deep) on the hanging wall. In
addition to this primary hole, a 500-m-deep hole (Hole B) was done on the
footwall 700 m away from Hole A. After drilling, the MiDAS group deployed
a 7.5-km-length optic-fiber cable perpendicular to the Milun fault, passing
through Hole A (from top to bottom), the main fault zone on the surface,and Hole B (from top to bottom) orderly. The downhole triaxial seismometer
arrays were installed in both holes. In this study, we search earthquakes fromthe continuous seismic records by two methods; one is manually picking andanother is by the deep-neural-network-based seismic arrival-time picking
method, PhaseNet. The study period is from March to May, 2023. We group
earthquakes into 5 classifications by the S-P arrival time differences (ts-tp).
Class S, A, B, and C demonstrate events with ts-tp ranges < 1s, > 1s & < 2s,> 2s & < 6s, and > 6s, respectively. Class D collects events with unclear P- or
S-wave identification. Compared both detected results of human made andfrom PhaseNet, we recognize that those from PhaseNet have high accuracy(80 ~ 98%) in local events (Class A-C). However, the accuracy drops to 22%
for Class S, which includes ultra-close events on the fault. It is possibly due tolack of ultra-close event templates in the PhaseNet model training. Next step,
we will improve the PhaseNet model and develop a labor-saving procedure inearthquake detection for the MiDAS seismic monitoring system.
poster 10
HD-TMA: A New Fast Template Matching Algorithm
Implementation for Linear DAS Array Data
LV, H., Innovation Academy for Precision Measurement Science andTechnology, Wuhan, China, lh17@mail.ustc.edu.cn; ZENG, X., Innovation
Academy for Precision Measurement Science and Technology, Wuhan,
China, zengxf@whigg.ac.cn; SONG, Z., Innovation Academy for Precision
Measurement Science and Technology, Wuhan, China, songzh@apm.ac.cn
Distributed Acoustic Sensing (DAS) technology, combined with existing telecom fiber-optic cable, has shown great potential in earthquake monitoring.
The template matching algorithm (TMA) shows good detection capabilities
but depends on heavy computational costs and diverse template events. We
developed a program named HD-TMA, which accelerates computation by 40
times on the CPU platform and 2 times on the GPU platform. For linear DAS
array data, we introduced a fast arrival-picking algorithm based on the Houghtransform to pick time windows of template waveforms. The HD-TMA algorithm was successfully applied to the 2022 Menyuan Ms6.9 earthquake’s aftershock sequence recorded by a DAS array and several optimization strategies
were discussed based on this dataset. 1) Using SNR in choosing the location
and aperture of the subarray and the time window of the template waveforms.
2) Considering the decrease in template events’ marginal utility, we proposed applying a neural network to build a template event library, followed
by HD-TMA scanning. Such strategies can effectively reduce computationalcosts and improve detection

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2-D Shear-Wave Velocity Profile of Shallow Sediments
Using Ocean Bottom Distributed Acoustic Sensing andAmbient Noise Probabilistic Inversion
BEN MANSOUR, W., Washington University in St. Louis, Missouri, USA,walid.benmansour@seismo.wustl.edu; SPICA, Z., University of Michigan,
Michigan, USA, zspica@umich.edu; VIENS, L., Los Alamos National
Laboratory, New Mexico, USA, lviens@lanl.gov; LIU, M., University ofMichigan, Michigan, USA, meichenl@umich.edu
Ambient noise tomography is a well-established technique that estimates
the physical properties (i.e., thickness and shear-wave velocity) of the crustand upper mantle through the inversion of surface-wave dispersion curves.
Imaging the shallow crust and sediment layers can be difficult, especiallyoffshore, due to the limited number of ocean bottom seismometers. A moreaccurate sediment mapping on the continental shelf can help identify potential risks like underwater landslides that could damage telecommunication cables or trigger tsunamis. The recent development of the Distributed
Acoustic Sensing (DAS) technology presents an opportunity to achieve
higher-resolution imaging of the offshore sub-surface using dense station
spacing distributed along a fiber-optic cable. We probed 50 km of a telecommunication fiber deployed offshore Cordova, Southern Alaska, and recorded
continuous data for four months in 2022. The sediment cover on the continental shelf is likely to have a significant portion of glacial sediments originatingfrom the Copper River, which is situated a few miles to the south. Although
no large earthquake (Mw>7.0) has occurred in the region since the 1964 M9.2
Prince William earthquake, the area remains seismically active and susceptible to underwater landslides. We use the data collected from May 04 to May
15, 2022, to compute cross-correlation functions between station pairs along
the fiber. From a frequency-time analysis, we estimate surface-wave phasevelocity between groups of station pairs and invert to produce a 2-D shear
wave velocity profile. In this work, we propose to use a Bayesian Monte Carlo
inversion framework to build our final velocity profile. The inverted shallow
velocity profile provides new constraints on the nature of the sediments in thisseismically active region. We will discuss the implications in terms of sediment transport and mixing but also the potential of underwater landslides
associated with these sediments.
poster 12
Towards a Metadata Standard for Distributed Acoustic
Sensing (DAS) Data Collection
MELLORS, R. J., University of California, San Diego, California, USA,rmellors@ucsd.edu; HUI LAI, V., Australian National University, Australian
Capital Territory, Australia, voonhui.lai@anu.edu.au; HODGKINSON, K.
M., Sandia National Laboratories, New Mexico, USA, kmhodgk@sandia.gov;
PORRITT, R., Sandia National Laboratories, New Mexico, USA, rwporri@sandia.gov
With increasing use of Distributed Acoustic Sensing (DAS) technology, there
is a need to implement a metadata standard specifically for DAS to facilitate
the integration of DAS measurements across experiments and increase reusability. We propose a transfer metadata standard which may be adapted forstorage. The schema describes the five key components of a DAS experiment:(1) interrogator, (2) data acquisition, (3) channels, (4) cable, and (5) fiber. The
proposed metadata schema is hierarchical based, with a parent ‘overview’
metadata block describing the experiment, and child branches describing the
instrumentation (i.e., interrogator and acquisition parameters) and the fiber
sensor (i.e., cable installation and fiber properties). The metadata schema isdesigned to be independent of the time-series data so that corrections andupdates can be applied to the metadata, without having to manipulate large
volumes of time-series data. Unique identifiers are used as pointers that map
different components within the metadata schema; they also provide a natural basis to the naming convention (i.e., source identifier) of the time-series
data, where the time series data is uniquely defined by the metadata standard.
Where possible, the identifiers are consistent in naming conventions with
ProDML. We use GitHub to implement version control for the metadata standard, to enable community collaboration and facilitate sustainable development of the metadata standard. Examples are shown for common deployment
scenarios. The path forward including technical issues and strategic path will
be discussed.
poster 13
Exploring the Potential for Joint Monitoring of Tectonic
Tremor Using Dark Fiber and Seismometers
MENDOZA, M. M., University of Colorado Boulder, Colorado, USA,
manuel.mendoza@colorado.edu; MARTIN, E. R., Colorado School of Mines,

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Colorado, USA, eileenrmartin@mines.edu; ISSAH, A. S., Colorado School ofMines, Colorado, USA, aissah@mines.edu; JIN, G., Colorado School of Mines,
Colorado, USA, gjin@mines.edu; GAETE ELGUETA, V. A., University ofWashington, Washington, USA, velgueta@uw.edu; LIPOVSKY, B., Universityof Washington, Washington, USA, bpl7@uw.edu; BODIN, P., University ofWashington, Washington, USA, bodin@uw.edu; MALONE, S. D., Universityof Washington, Washington, USA, smalone@uw.edu; CREAGER, K. C.,
University of Washington, Washington, USA, kcc@uw.edu; SHEEHAN, A. F.,
University of Colorado Boulder, Washington, USA, anne.sheehan@colorado.
edu
Tectonic tremor has been found among various plate boundary settings using
observations from permanent seismic networks and/or temporary dense array
deployments. Studying the behavior of tremor is important for understanding
the physics behind a wide spectrum of fault slip behaviors, and for constraining the spatial extent and state of stress of a plate boundary’s seismogenic
zone. Experiments in recent years have demonstrated that dark (unlit) fiberfrom telecommunication cables can be used for distributed acoustic sensing(DAS) to enhance our ability to monitor regular earthquakes. This new toolis especially valuable where seismometers are sparse, absent, or challenging todeploy and maintain long term. Fortunately, telecommunication fiber is spatially extensive across the Earth, especially onshore in (and between) urban
environments that often reside near major active faults.
Here we extend the application of onshore DAS to the study of slow
earthquakes as represented by non-volcanic tremor, to explore its potential
for joint monitoring with seismometers. In April 2023 we conducted a smallaperture (4.5 km) DAS array experiment using dark fiber during an episodic
tremor and slip event in Northern Cascadia (Port Angeles, WA). Using the
PNSN tremor catalog for reference, we find that the array detected tremor
signals generated down-dip of the seismogenic zone (>35 km depth), andvalidate these observations with the timing and shape of similar signals fromnearby seismometers. Next, to evaluate the efficacy of DAS for tremor location, we perform a comparative analysis of epicenter estimates derived fromtraditional methods using seismometer only data and from seismometer plus
DAS data. Given the large number of sampling points when using just one
cable of fiber, the hope is that DAS has the ability to leverage seismometerswith additional spatial resolution and constraints during heightened tremor
activity. At a broader scope, we aim to demonstrate how these two instruments may be used harmoniously for enhanced monitoring of regular andslow earthquakes, and general seismological investigations.
poster 14
A Metadata and Time-Series DAS Workflow Using Cloud
Computing
RAMOS, M. D., Sandia National Laboratories, New Mexico, USA, mdramos@
sandia.gov; HODGKINSON, K. M., Sandia National Laboratories, New
Mexico, USA, kmhodgk@sandia.gov; TIBI, R., Sandia National Laboratories,
New Mexico, USA, rtibi@sandia.gov
The high spatial and temporal resolution that DAS provides has the potential to transform how geophysical network monitoring is performed. DAS
provides strain measurements at a spatial resolution of meters along cables
that can be tens of kilometers in length at kilohertz sample rates, surpassing
the resolution provided by setups of traditional seismic instrumentation. The
sensitivity of DAS in the 10-1 to 100 Hz bandwidth combined with its operational capability on land and on the seafloor means that it not only provides amechanism to track the change in frequency and amplitude of seismic signals
over distance, but it can supplement recordings from conventional observatory-quality sensors in regions such as the ocean floor where station density
is extremely sparse. However, two issues impede the systematic study of DAS
to quantify its benefit: (1) the vast volumes of data generated by the system
makes it difficult to telemeter and, once at a datacenter, analyze efficiently
and (2) the lack of consistently compiled metadata inhibits the comparison ofcorrelated signals across geographically separated fibers. Both issues need tobe addressed to provide calibrated and quality-controlled DAS data sets suitable for downstream ingestion into event detection techniques such as template matching and machine learning algorithms. We show our progress withrespect to the second research question (i.e., metadata standardization, Lai etal., 2023) across the 32 data sets collected for the 2023 Global DAS project andshow how this enables comparison of DAS data across networks. We build
off pioneering DAS time-series data workflows (Ni et al., 2023) and discuss
how cloud computing technologies can be leveraged for DAS data storage andseismic event monitoring.

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poster 15
Exploring Source and Structure Sensitivity Kernels of DAS
Ambient Noise Correlations
PINZON RINCON, L., Université Grenoble Alpes, GRENOBLE, France,
laurapinzonrincon@yahoo.es; MORDRET, A., Université Grenoble Alpes,
Grenoble, France, aurelien.mordret@gmail.com; BRENGUIER, F., Université
Grenoble Alpes, GRENOBLE, France, florent.brenguier@univ-grenoblealpes.fr; GRADON, C., Sisprobe, GRENOBLE, France, chloe.gradon@sisprobe.com; LAVOUÉ, A., Sisprobe, GRENOBLE, France, anais.lavoue@sisprobe.com; BEAUPRETRE, S., Sisprobe, GRENOBLE, France, sophie.
beaupretre@sisprobe.com
Distributed Acoustic Sensing (DAS) technology has transformed seismic
monitoring and imaging by converting standard optical fiber cables into dense
arrays of virtual seismic sensors, offering continuous, well-distributed, andhigh-resolution seismic records. This study investigates the sensitivity of DAS
ambient noise cross-correlation for several fiber configurations and compares
them with standard seismometer ambient noise cross-correlations.
DAS directional response is sensitive to the angle of incidence of seismic energy with respect to the orientation of the fiber. Consequently, the DAS
ambient noise cross-correlation spatial sensitivity is influenced by factors suchas the geometry of the fiber-optic cable and the location of seismic sourcesof noise. To improve our understanding of DAS passive seismic interferometry responses to noise source distributions and cable setups, we model theirsource and structure sensitivity kernels using full waveform modeling and an
adjoint approach. This exploration sheds light on the challenges and potential biases associated with employing DAS in passive seismic interferometry,
underscoring the importance of understanding DAS responses to diverse
noise sources.
By studying these aspects, we can effectively optimize DAS-based experimental setups and bolster the reliability of passive seismic imaging applications. This work lays the foundation for the full waveform inversion of ambient noise cross-correlation of DAS data.
poster 16
Distributed Fiber-Optic Magnetic Sensing for Subsurface
Imaging and Monitoring
YUAN, S., Colorado School of Mines, Colorado, USA, syuan@mines.
edu; SNYDER, T., Colorado School of Mines, Colorado, USA, tsnyder1@mines.edu; MARTIN, E., Colorado School of Mines, Colorado, USA,eileenrmartin@mines.edu; HOMA, D., Virginia Tech, Virginia, USA, dan24@
vt.edu; DEJNEKA, Z., Virginia Tech, Virginia, USA, dejnekazb7@vt.edu;
PICKRELL, G., Virginia Tech, Virginia, USA, pickrell@vt.edu; WANG, A.,
Sentek Instrument, Virginia, USA, awang@sentekinstrument.com; THEIS, L.,
Sentek Instrument, Virginia, USA, ltheis@sentekinstrument.com
Distributed fiber-optic sensing (DFOS) technology offers a cost-effective, versatile solution for geophysical applications, with advantages such as extended
sensing range, high spatial resolution, durability, and flexibility. While electromagnetic (EM) sensing holds promise for improving fluid saturation mapping to complement seismic imaging and monitoring, distributed EM sensing
systems are still in early development stages. This study introduces an optical-fiber-based distributed magnetic sensing (DMS) system, simultaneously
recording acoustic and magnetic wavefields. The DMS system uses a standard
distributed acoustic sensing (DAS) interrogator, probing a specialized singlemode fiber optic cable embedded with magnetostrictive wires. These wires,
responding to EM fields, induce strain in the fiber core in addition to mechanical strains detected by standard single mode fiber. By measuring backscattered light, the strain-induced phase variation between two sensing fiber segments is detected. In validation experiments, prototype DMS fibers, with andwithout fiber Bragg gratings (FBGs), exhibited expected spectral responses tocontrolled EM and acoustic sources, consistent with theoretical predictions.
The DMS system achieved sub-millitesla (mT) magnetic field intensity resolution over a bandwidth of 10-2000 Hz. Cross-well EM time-lapse simulationand inversion of CO2 injection demonstrated the proposed DMS system’s
potential sensitivity, highlighting its potential to augment seismic monitoring in realistic scenarios. Preliminary results showcase valuable insights into
this multi-physics optic sensing system, indicating its potential for monitoring
subsurface fluid changes. These findings set the stage for further research anddevelopment of an integrated DAS and DMS system, enabling more comprehensive and cost-effective geophysical applications.

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Anisotropy Across Scales
Oral Session • Friday 3 May • 8:00 am PacificConveners: Frederik Link, Yale University (frederik.link@
yale.edu); Eric Loeberich, Yale University (eric.loeberich@yale.edu); Walid B. Mansour, Washington University in St.
Louis (walid@wustl.edu)
A Seismic View of the Stress Field
DELOREY, A. A., Los Alamos National Laboratory, New Mexico, USA, seis@
mailfence.com
The stress field in the Earth’s crust, often represented as the orientation of the
maximum horizontal compressive stress (SHmax), is an important parameter
for a wide variety of investigations in solid-earth geophysics. The orientations
and magnitudes of the principal stresses determine faulting types and theorientation of new fractures, are related to anisotropy in elasticity and permeability, and can affect wave propagation. Our understanding of the stressfield in the Earth’s crust is built mostly upon earthquake source characteristics, borehole-based measurements, and modeling. Observations are sparseand unevenly distributed, and the level of heterogeneity is not well known.
Compliant features in rocks, such as grain boundaries and small fracturesare very sensitive to the stress field and changes in the stress field. Due to an
asymmetry in the way that rocks relax during extension and compression,
we observe stress-induced anisotropy in the behavior of compliant featuresin rocks due to the horizontally anisotropic stress field in the Earth. Thus, we
can infer the orientation of the horizontal principal stresses using differential
travel time measurements of differential Green Functions taken at different
azimuths. We applied this method to Rock Valley at the Nevada National
Security Site for building geophysical models associated with discriminating
underground explosions from earthquakes.
Seismic Anisotropy and Stress-Field Variations Along theDead Sea Fault Zone in Northern Israel
BEN-DOR, G., Ben-Gurion University of the Negev, Tel-Aviv, Israel,
guybend@post.bgu.ac.il
Geological observations based mainly on stress (strain)-indicating meso-scale
markers suggest that the local maximum horizontal compressive stress (SHmax)
direction along the Dead Sea Fault (DSF) system in northern Israel changes
considerably over short distances from a ~N-S, fault-parallel orientation in
the south to an ~E-W, fault-perpendicular orientation in the north. However,
the association of the meso-scale markers to the present-day stress field is notwell constrained as many of them could have formed at any stage during the
DSF evolution. In this study, we use a large dataset of Shear-Wave Splitting(SWS) measurements, taken from local DSF-related earthquakes, to characterize the azimuthal seismic anisotropy of the upper-crust at this critical turning point of the DSF system, near the Lebanese Restraining Bend. The SWS
directions commonly align parallel to the inferred local SHmax as revealed by
the meso-scale markers, supporting their association with the current stressfield. In several stations, SWS fast directions indicate azimuthal anisotropy
at high angles to the trace of the master fault, indicating that stress-induced
anisotropy represents a more plausible mechanism for SWS than structurecontrolled anisotropy. The SWS measurements suggest that a northward
counterclockwise rotation of the crustal SHmax is present along this segmentof the DSF, supporting previous notation on the transition from divergent toconvergent strike-slip faulting in this area.
Imaging Los Angeles Basin via Directional Dependent
Rayleigh Wave Ellipticity Using Data From the Lab2022
Nodal ArrayGKOGKAS, K., University of Utah, Utah, USA, kos.gkogkas@utah.edu; LIN,
F., University of Utah, , USA, fanchi.lin@utah.edu; CLAYTON, R., California
Institute of Technology, , USA, clay@gps.caltech.edu; VILLA, V., California
Institute of Technology, , USA, vvilla@caltech.edu; FORD, H., University ofCalifornia, Riverside, , USA, heather.ford@ucr.edu; ALLAM, A., University of
Utah, , USA, amir.allam@utah.edu
We deployed a temporary nodal array in the Los Angeles basin, comprising~300 nodal geophone seismometers, composed of two dense lines (interstation spacing of ~0.6 km) and a 2D distributed/shotgun array (spacing of~2 km). We compute multi-component ambient-noise cross-correlations
between all stations available in the area, including both regional broadband
and nodal stations. We observe clear fundamental mode Rayleigh and Love

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Seismological Research Letterswaves in the period band of 1-10s, where higher mode Rayleigh waves are also
observed for periods shorter than ~4s. We use array processing techniques
to measure both surface wave phase velocity and Rayleigh wave ellipticity, or
H/V (Horizontal-to-Vertical) amplitude ratios. The measured Rayleigh wave
ellipticity clearly depicts the basin’s lateral boundaries. Moreover, at each station, we examine the azimuthal dependency of the ellipticity measurements.
We show that strong Rayleigh wave H/V azimuthal anisotropy is evident
within the basin, which is potentially related to the stress-induced crack alignment. We compare our findings with the SCEC Community Velocity Model(CVM) and regional stress field model and discuss how the models can be further improved. As an accurate basin model is important to earthquake groundmotion prediction, our newly acquired results demonstrate the utility of dense
nodal arrays for shallow imaging in a densely populated urban setting for seismic hazard assessment.
Anisotropy in Flowing Firn and Ice: Insights from Ambient
Noise and Active Source Studies in Antarctica
CHAPUT, J., University of Texas at El Paso, Texas, USA, jchaput82@gmail.
com; ASTER, R. C., Colorado State University, Colorado, USA, Rick.Aster@colostate.edu; KARPLUS, M. S., University of Texas at El Paso, Texas, USA,mkarplus@utep.edu; NAKATA, N., Massachusetts Institute of Technology,
Massachusetts, USA, nnakata@mit.edu
Antarctic firn, which covers 99% of the Antarctic ice sheet, promotes a variety
of exotic seismic behaviors owing to its porosity, extreme shallow velocity anddensity gradients, and highly dynamic and evolving nature. Ambient noise
excitation of firn through wind forcing creates patterns of spectral amplifications that are sensitive to both static shallow structure and surface environmental forcing effects. Spectral peaks demonstrate pervasive offsets acrossseismic components, pointing to a sensitivity to azimuthal anisotropy as well.
Here, we show that spectral peak offsets can be interpreted in the context offlowing ice and snow and can be systematically used to determine frequencydependent anisotropy. We show example results from Ross Ice Shelf seismicarrays and preliminary nodal networks from the TIME project, validated bydirect comparison to active source experiments. Flowing firn and ice demonstrate multiple kinds of anisotropy that vary with depth, with brittle fractureaccommodation of stress dominating in solid ice and plastic foam-like extension in shallow firn. We also present preliminary results from recent large-N
nodal arrays deployed in the TIME project during the 2022 and 2023 fieldseasons.
Broadband Rayleigh and Love Wave Phase Velocity Maps
Based on Double-Beamforming of Ambient Noise CrossCorrelations
YANG, Y., Southern University of Science and Technology, Shenzhen, China,
yangyj@sustech.edu.cn; ZHAO, K., China University of Geosciences, Wuhan,
China, kaifeng.zhao@cug.edu.cn; LUO, Y., China University of Geosciences,
Wuhan, China, luoyinhe@cug.edu.cn
Ambient noise tomography has become a popular method in the past two
decades to image the crust and uppermost mantle structure. To date, broadband Rayleigh wave signals can be obtained from ambient noise, which can beutilized to study the earth’s interior structure from the surface down to ~200300 km depths. However, it is hard to extract intermediate- and long-period(>50 s) Love wave signals from ambient noise using conventional data processing techniques for ambient noise. Array-based data processing techniques
can enhance weak signals. In this study, we adopt an algorithm of the doublebeamforming method to extract broadband Love wave signals from ambient noise. We validate the accuracy of the dispersion curves measured fromour method by comparing them to those measured from the conventional
method. Then, we use a finite frequency ambient noise tomography method
to construct broadband Love wave phase velocity maps across the contiguousUSA. These phase velocity maps are consistent with those obtained from conventional methods at short periods (<40 s). Finally, we analyze the resolutionof our double-beamforming method based on checkerboard tests and findthat the resolution of phase velocity maps based on our method is close to theaperture of the subarrays used in our double-beamforming method.
Flow in the Mantle Beneath Eritrea and Yemen: Evidence
From Seismic Anisotropy
GAUNTLETT, M. Z., University of Oxford, Oxford, United Kingdom,
miriam.gauntlett@linacre.ox.ac.uk; KENDALL, J., University of Oxford,
Oxford, United Kingdom, mike.kendall@earth.ox.ac.uk; HUDSON, T.,
University of Oxford, Oxford, United Kingdom, thomas.hudson@earth.
ox.ac.uk; HAMMOND, J. O. S., University of London, London, United
Kingdom, james.hammond@bbk.ac.uk; GOITOM, B., University of Bristol,www.srl-online.org•

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Bristol, United Kingdom, berhegoitom14@gmail.com; OGUBAZGHI, G.,
Eritrea Institute of Technology, Himbrti, Mai Nefhi, Eritrea, ogubazghi_
ghebrebrhan@yahoo.com

nant fast directions in the asthenosphere appear to be influenced by mantle
flow, which is partially reflected in the absolute plate motion directions.

To investigate the role of magmatism and mantle flow in continental breakup,
we analyse mantle anisotropy beneath Eritrea and Yemen, regions on eitherside of the Red Sea Rift ;near the Afar Triple Junction. We use teleseismic data
recorded on temporary regional arrays to calculate SKS shear-wave splitting
parameters at six seismic stations in Eritrea and 71 seismic stations in Yemen.
Our results show moderately high delay times (1.18 -- 1.85 s) and fast polarisation directions oriented NE-SW to NNE-SSW in Eritrea. We observe little
backazimuthal variation in the splitting parameters, providing confidence that
there is a single layer of anisotropy beneath the stations. This single layer ofanisotropy is attributed to asthenospheric flow oriented NE-SW, channelledfrom the Main Ethiopian Rift through Afar to the Red Sea. We interpret thisflow as originating from the superplume beneath Africa. Our results support
the hypothesis that the latter stages of continental breakup in Eritrea involve
magma-assisted rifting.

Exploring Mantle Dynamics of the Cascadia Subduction
System Through Anisotropic Tomography With
Transdimensional Inference Methods
VANDERBEEK, B. P., Università degli Studi di Padova, Padova, Italy,
brandon.p.vanderbeek@gmail.com; DEL PICCOLO, G., Universitàdegli Studi di Padova, Padova, Italy, gianmarco.delpiccolo@phd.unipd.it;
FACCENDA, M., Università degli Studi di Padova, Padova, Italy, manuele.
faccenda@unipd.it

Modeling Layered Anisotropy in the Alaska-Aleutians
Subduction Zone
BIRKEY, A., University of Delaware, Delaware, USA, abirkey@udel.edu;
LYNNER, C., University of Delaware, Delaware, USA, clynner@udel.edu
A major limitation of shear wave splitting is its path-integrated nature. The
most commonly used core-refracted teleseismic phases traverse thousands ofkilometers from the core-mantle boundary to the receiver, complicating interpretation of the signal. Contributions from multiple layers of anisotropy canbe determined using forward modeling. Yet these forward models often do
not consider more than two layers of anisotropy, the effects of dipping layers,or the statistical robustness of the results.
We present multilayer shear wave splitting modeling along the AlaskaAleutians Subduction Zone (AASZ). With an updated splitting catalog, we areable to identify six regions with sufficient density of splits to forward model.
We model these splits with two- and three-layer cases, including with tectonically derived middle dipping layers. Based on our modeling and previous anisotropic studies using shear wave splitting and tomography, we ultimately choose a three layer model with a dipping middle layer with the axisof anisotropy oriented parallel to paleospreading. At five of the six regions,
we identify a suite of models that is statistically better than a single-layer case.
These models oftentimes differ from the “best-fitting” model, implying that
only considering the model with the lowest misfit will provide an inaccurate
representation of layered anisotropy. We also argue that the inclusion of tectonically-derived fabrics in these models is an important step, especially inregions such as subduction zones where these fabrics are well constrained.
Depth-Dependent Seismic Azimuthal Anisotropy Beneath
the Aleutian Subduction Zone and the Juan De Fuca-Gorda
Plates
LIU, C., University of Texas at Austin, Texas, USA, chuanming.liu@jsg.
utexas.edu; BECKER, T. W., University of Texas at Austin, Texas, USA, twb@
ig.utexas.edu; WU, M., University of Colorado Boulder, , USA, mewu4448@
colorado.edu; SHEEHAN, A., University of Colorado Boulder, , USA, anne.
sheehan@colorado.edu; RITZWOLLER, M., University of Colorado Boulder,, USA, michael.ritzwoller@colorado.edu
Benefiting from the deployment of ocean-bottom seismometer arrays in
the Aleutian subduction zone (Alaska Amphibious Community Seismic
Experiment (AACSE)) and the Juan de Fuca-Gorda plates (Cascadia Initiative(CI)), researchers have constructed high-resolution surface wave dispersion
databases (e.g., Zhang, et al., 2021; Liu et al., 2022). Based on the Rayleighwave phase speed azimuthal anisotropy databases from these two regions, weconstruct depth-dependent azimuthal anisotropy models for both the crustand uppermost mantle beneath the Aleutian subduction zone and the Juande Fuca-Gorda plates.
These models of depth-dependent seismic anisotropy reveal distinct tectonic features of the subduction zone forearc and the young oceanic plate. In
the forearc region of the Aleutian subduction zone, we observe a correlation
between the along-strike variation in fast directions above the slab and thespatial changes in the orientation of local faults. Deeper within the subductedslab, we observe a trench-perpendicular pattern of anisotropy fast directions,suggesting the existence of fossil anisotropy. In contrast, on the Juan de FucaGorda plates, we find that paleo-spreading directions may account for the
anisotropy fast directions in most of the study region. Additionally, the domi-

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The Cascadia subduction system is an ideal location to investigate the natureof mantle flow and associated driving forces at a convergent margin owing
to the dense network of on- and off-shore seismic instrumentation. While
numerous shear wave splitting and tomography studies have been performed
with these data, they have produced conflicting views of mantle dynamics collectively referred to as the Cascadia Paradox. On the overriding plate,splitting observations are consistent with large-scale 3D toroidal flow while
off-shore splitting patterns are more easily explained by 2D plate-driven flow.
Either geometry is difficult to reconcile with seismic tomographic models thatimage a fragmented Juan de Fuca slab descending beneath the Western USA.
However, these observations offer only an incomplete image of Cascadia mantle structure. Shear wave splitting provides a depth integrated view of anisotropic fabrics making inferences regarding the 3D nature of mantle deformation difficult. Prior high-resolution body wave tomography typically neglects
anisotropic effects which can in turn yield significant isotropic imaging artefacts that complicate model interpretation. To overcome these limitations, weinvert P-wave delay times for a 3D hexagonally anisotropic model with arbitrarily oriented symmetry axes using the reversible jump Markov chain Monte
Carlo algorithm. This stochastic imaging approach is particularly well-suited
to the highly non-linear and under-determined nature of the anisotropic seismic tomography problem. The resulting ensemble of solutions allows us torigorously assess model parameter uncertainties and trade-off between isotropic and anisotropic heterogeneity. We investigate whether the fragmented
nature of the subducted Juan de Fuca slab is a well-resolved feature and towhat extent its geometry trades off with anisotropic parameters. In light of our
new 3D anisotropic model, we re-evaluate the Cascadia Paradox and attempt
to reconcile disparate views of Western USA mantle dynamics.
Segregated Melts Below the 660 in the Central Pacific:
Implications on Water Transport in Mantle Upwellings
DENG, K., Chengdu University of Technology, Chengdu, China, dengkai17@
cdut.edu.cn; SONG, T., University College London, London, United
Kingdom, alex.song@ucl.ac.uk
Global water cycle has been of great interest to the community in the past
several decades, and the majority of seismic observations, along with experimental studies, appears to support the transport of water down to the deep
Earth through mantle downwelling near subducting slabs. In contrast, there
is limited seismic observation in facilitating the argument for or against thetransport of water from the deep Earth back to the upper mantle. As a consequence, the key mechanism(s) or/and mineral(s) responsible for potential
water transport during mantle upwelling remain enigmatic.
In the context of receiver function technique, here we present a novel
observation of P660sP and PS660P phases, which involve P-to-S conversion
at the 660 and arrive as postcursors of surface reflected PP waves. Specifically,
we present robust detection of PP postcursors, P660sP and PS660P, in teleseismic receiver function stacks that sample the 660 beneath the central Pacificnear Hawaii. Interestingly, their amplitude systematics against the epicentral
distance are inconsistent with the predictions from isotropic media. Since
the receiver function stacks in different distance ranges effectively sample thesame proximity and such unique amplitude systematics is unlikely caused byheterogeneous sampling and lateral variation of the structure.
We search for an effective VTI (vertically transversely isotropic, orradially anisotropic) layer either below or above the 660-km discontinuity
through a Markov Chain Monte Carlo method and validate the model against
other observations of P660s, SS precursors, and ScS multiples in neighbouring regions. We find that the properties of such anisotropic layer can only bereconciled with a tilted segregated melt layer beneath the 660, presumably
due to strong shear deformation induced by the mantle upwellings against the660. We propose that such deep melts are likely hydrous melts induced by thebreakdown of hydrous aluminous poststishovite, carried by hot mantle plume,
into the less-soluble stishovite in the uppermost lower mantle.

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Anisotropy Across Scales [Poster Session]
Poster Session • Friday 3 May
Conveners: Frederik Link, Yale University (frederik.link@
yale.edu); Eric Loeberich, Yale University (eric.loeberich@yale.edu); Walid B. Mansour, Washington University in St.
Louis (walid@wustl.edu)
poster 46
Analysis of Anisotropic Characteristics in the Valley of
MexicoCHACÓN, F., Universidad Nacional Autónoma de México, Mexico City,
Mexico, fcochaconsalem@hotmail.com; QUINTANAR-ROBLES, L.,
Universidad Nacional Autónoma de México, Mexico City, Mexico, luisq@
igeofisica.unam.mx; RODRÍGUEZ-RASILLA, I., Universidad Nacional
Autónoma de México, Mexico City, Mexico, ivan@sismologico.unam.mx
We obtained preliminary results of an anisotropic seismic study based on the
Shear Wave Splitting parameters from microearthquakes that occurred in andaround the Valley of Mexico (VM), recorded by the Valley of Mexico Seismic
Network from June 1996 until July 2023. These analyses focused on determining the effects of both local and regional tectonic stresses and deformation
regimes from the behavior of common anisotropic alignments (e.g., faults,
fractures, or cracks). In most cases, fast polarizations follow the orientationof already known local fault systems with preferential orientations of NE-SW,
NNE-SSW, and E-W, along with other NW-SE fast polarizations that could
show particular cases of unknown alignments in certain areas. Temporal variations of anisotropy could show deformations in the upper crust for specificregions due to changes in the tectonic environment and possible variations ofpore-fluid pressure. Observations of splitting delays presented range mainly
between 0.015 s to 0.07 s in most stations, with some individual values overpassing these values with important values of percentage of anisotropy, which
can be considered systems bordering on critical fracturing systems. The areas
with high values of anisotropy percentage (> 4.0%) allow for the characterization of the main fracture routes in the Valle of Mexico, which could be
evidence of routes of internal deformation and important zones of groundmotions.
poster 47
S Wave Velocity and Azimuthal Anisotropy From Ambient
Noise Data in the Sanjiang Lateral Collision Zone of SE
Tibetan Plateau
TIAN, J., China Earthquake Administration, Beijing, China, tjh031055@163.
com; GAO, Y., China Earthquake Administration, Beijing, China,
qzgyseis@163.com; LI, Y., China Earthquake Administration, Beijing, China,liyseis@mail.ustc.edu.cn
The Sanjiang lateral collision zone in the SE margin of the Tibetan plateau is a
crucial area for the study of the collision between the Paleotethys orogenic belt
and the oblique subduction of the Neotethys. In this study, we used data fromthree temporary seismic arrays and regional permanent stations to obtainshear wave velocity and azimuthal anisotropy for depths of 3 km to 50 km.
Our results suggest that geometry of the low velocity zone along the LijiangXiaojinhe fault (LXF), the fast velocity directions (FD) parallel to the LXF,
and the nearly E-W oriented FDs in the Panzhihua region with high-velocity
may indicate that the high-velocity blocks obstruct the southeastward migration of the Tibetan Plateau materials. The FDs at the northwestern end of the
Red River fault (RRF) exhibit obvious segmented characteristics. This anisotropic pattern may reflect both the decoupling deformation of the upper andlower crust in the north and the coupling deformation in the south, as well as
the strong influence of the RRF on anisotropy. The clockwise rotation of thecrustal anisotropy in the western part of the study area may suggest that the
deformation is related to the complicated geological tectonic and extensional
cracks. The microcracks associated with regional compression may be responsible for the N-S trending crustal anisotropy in the east. In addition, the complex anisotropy in the LXF and RRF also highlights the important role of thesefaults in shaping crustal deformation [supported by NSFC Projects 42330311& 41730212, National Key R&D Project of China 2017YFC1500304].

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Seismological Research Lettersposter 48
Exploration of Anisotropy from Crystal to Whole-Earth
ScalesGUPTA, A., University of Alaska Fairbanks, Alaska, USA, agupta7@alaska.
edu; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.
edu
Evidence of seismic anisotropy is widespread within the Earth, including individual crystals, laboratory rock samples, borehole data, active-source seismic
data, and global seismic data. The anisotropy of a material describes how wave
speeds vary as a function of direction, and it is characterized by density and a
21-parameter symmetric 6 x 6 matrix that maps strain to stress. The space of
21-parameter elastic maps is vast and poses challenges for understanding andfor practical applications based on laboratory or field data. Most seismologists assume a high-symmetry (low-parameter) version of Earth, either in theform of isotropy (2 parameters), vertical transverse isotropy (radial anisotropy: 5 parameters), or horizontal transverse isotropy (azimuthal anisotropy:
6 parameters). We offer a general approach to explore the space of elastic maps
by starting with any given elastic map T having any type of symmetry, represented by Sigma: trivial, monoclinic, orthorhombic, tetragonal, transverse
isotropic, isotropic, cubic, and trigonal. Using a combined minimization andprojection procedure, we calculate the closest-Sigma maps to T, which resultsin 8 maps that can be visualized by a lattice of spheres representing the maps.
The pathway from T to its closest-isotropic map can be obtained either by
discretizing the direct path or by traversing a sequence of lattice nodes, such astrivial to monoclinic to orthorhombic to tetragonal to transverse isotropic toisotropic. We apply this approach to 21-parameter elastic maps derived fromlaboratory measurements of minerals, including dependencies on pressure
and temperature. We also re-examine a global model of the D” region represented by 21-parameter elastic maps derived from geochemistry and rheology principles. The two primary advantages of this approach are 1) to provide
visualization of elastic maps along specific pathways and 2) to offer distinct
options for reducing the complexity of a given elastic map by obtaining a mapthat is closer to isotropic.
poster 49
3D Shear Wave Velocity and Azimuthal Anisotropy Modelfor the Crust and Upper Mantle in Alaska Extracted by the
Joint Inversion of Wave Gradiometry Method and Ambient
Noise Tomography Method
LIANG, C., Chengdu University of Technology, Chengdu, China, liangct@
cdut.edu.cn; LIU, Z., Chengdu University of Technology, Chengdu, China,
1763326490@qq.com; CAO, F., Chengdu University of Technology, Chengdu,
China, 610391805@qq.com
The Wave Gradiometry Method(WGM) has emerged as a powerful multipurpose tool to extract strain and rotation tensor, identify phases, and mostimportantly to image the earth structure. The WGM measures the spatial gradients of the wavefield within a subarray to extract 4 major attributes: phasevelocity, wave directionality, geometrical spreading and radiation pattern.
These attributes can be further used to extract 3D shear wave velocity and 3D
azimuthal anisotropy. The WGM method is combined with the ambient noise
Tomography (ANT) to the USARRAY in Alaska to obtain a 3D shear wave
velocity structure and azimuthal anisotropic model. Our results reveal complex anisotropic patterns related to subduction structures. The fast directionsin the Aleutian fore-arc region show a depth-dependant pattern associatedwith overriding lithospheric plate, fore-arc mantle wedge, subducting plate,and sub-slab mantle in the fore-arc region, respectively.We also notice that
there are different fast directions in the Pacific Plate and the Yakutat Plate,
implying different sources of anisotropy for each. An annular anisotropic pattern is present behind the arc at the northeastern edge of the subducting plate,which could be induced by the toroidal asthenospheric flow at the plate margin. Furthermore, our results provide a new evidence for the existence of the
subducting plate beneath the Wrangell Volcanic Field.
References:
Cao F H, Liang C T. 2022, 3D velocity and anisotropy of the southeastern Tibetan plateau extracted by joint inversion of wave gradiometry, ambient noise, and receiver function, Tectonophysics, https://doi.org/10.1016/j.
tecto.2022.229690
Liang, C., Liu, Z., Hua, Q., Wang, L., Jiang, N., & Wu, J. (2020). The 3D
seismic azimuthal anisotropies and velocities in the eastern Tibetan Plateau
extracted by an azimuth-dependent dispersion curve inversion method.
Tectonics, 39, e2019TC005747. https://doi.org/10.1029/2019TC005747
Langston, C. A. (2007). Wave gradiometry in two dimensions. Bulletinof the Seismological Society of America, 97(2), 401–416. https://doi.
org/10.1785/0120060138

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poster 50
Imaging Lower Crustal Flow Using Harmonic
Decomposition of Receiver Functions Beneath a Dense
Seismic Profile in Eastern Massachusetts
LINK, F., Yale University, Connecticut, USA, frederik.link@yale.edu; LUO,
Y., Yale University, Connecticut, USA, yantao.luo@yale.edu; LONG, M. D.,
Yale University, Connecticut, USA, maureen.long@yale.edu; KUIPER, Y. D.,
Colorado School of Mines, Colorado, USA, ykuiper@mines.edu
Ganderia and the Southeastern New England Avalon terrane are both terranes that rifted from Gondwana and accreted to North America in the early
to mid-Paleozoic. Accretion of the Avalon terrane was accompanied by plutonism, deformation, and metamorphism including partial melting within
the Nashoba terrane, the trailing edge of Ganderia, and may be interpreted
as indicators for mid- to lower-crustal channel flow. Channel flow describes
the flow of weak, partially molten material between more competent crust
as a result of pressure gradients in the mid- to lower crustal levels. Suchflow should typically result in seismic anisotropy due to the crystallographic
preferred orientations of minerals and shape preferred orientations at various scales. Here, we present a new method designed to analyze the crustal
anisotropic structure beneath the Nashoba terrane and provide insight into
its capabilities in a first application to permanent stations in the area and currently collected data.
To investigate the hypothesis of crustal flow during the orogenic history of Southeastern New England, we deployed a dense profile of 6 broadband seismic stations crossing the Nashoba terrane. We analyze the harmonic
variation of amplitudes in teleseismic P-Receiver Functions (RFs) to identify
interfaces of isotropic and anisotropic contrasts within the crust. In the caseof particularly prominent anisotropic features that have significantly larger
amplitudes than other signals, it is feasible to derive quantitative constraints
on the strength and orientation of the anisotropy. However, with growing
complexity, a classical forward modelling or grid search approach becomes
unfeasible.
These difficulties can be mitigated by applying Bayesian inversion,
which infers values of model parameters from a probabilistic perspective. We
use a Bayesian framework to invert for the anisotropic model that best fits
the observed constant and harmonic terms. Applying a Bayesian inversion to
the harmonically decomposed RFs has the potential to infer the anisotropic
seismic model more faithfully, without attempting to fit unrelated signals andartifacts.
poster 51
Shear Wave Splitting Characteristics of Aligned Partial
Melt Configurations in a Subduction Zone Back-Arc Setting
LOEBERICH, E., Yale University, Connecticut, USA, eric.loeberich@yale.
edu; WOLF, J., Yale University, Connecticut, USA, jonathan.wolf@yale.edu;
LONG, M. D., Yale University, Connecticut, USA, maureen.long@yale.edu
Patterns of XKS shear-wave splitting (SWS), which depict the spatial distribution of fast orientation, ϕ, and delay time, δt, are commonly interpreted interms of upper mantle deformation that causes lattice-preferred orientation(LPO) of anisotropic minerals such as olivine. However, shape-preferred orientation (SPO) of elastically distinct materials may influence SWS observations as well. Building on previous work (e.g., Hammond and Kendall, 2016),
we have carried out global wavefield simulations using AxiSEM3D to understand the effects of vertically aligned melt discs (an endmember geometry)on anisotropy observations. We confirm earlier findings that the amount ofsplitting depends on aspect ratio, melt fraction, and thickness of the inclusion, and indicate the potential of this configuration to crucially influence thestrength of observed SWS measurements in a setting where partial melt ispresent. We explore whether melt SPO along with LPO of olivine might beable to explain the enigmatic occurrence of exceptionally high δt in the HighLava Plains in the Cascadia subduction zone backarc. Here, we expand ourmodeling efforts to examine splitting due to the presence of dike-like partial
melt inclusions, investigating spatial changes in the backazimuthal variationof SWS parameters. We carry out more advanced LPO/SPO models that e.g.,
invoke dehydration-related olivine fabric transitions in the matrix surrounding the partial melt, which we plan to integrate into generic subduction zone
anisotropy models, including those whose geometry captures that of the
Cascadia subduction zone.

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poster 52
A Reformulation of the Browaeys and Chevrot
Decomposition of Elastic Maps
TAPE, W., University of Alaska Fairbanks, Alaska, USA, wtape@alaska.edu;
TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu
An elastic map T associates stress with strain in some material. A symmetryof T is a rotation of the material that leaves T unchanged, and the symmetrygroup of T consists of all such rotations. The symmetry class of T describes
the symmetry group but without the orientation information. With an eye
toward geophysical applications, Browaeys and Chevrot (2004) developed atheory which, for any elastic map T and for each of six symmetry classes Σ,
computes the “Σ-percentage” of T. The theory also finds a “hexagonal approximation” — an approximation to T whose symmetry class is at least transverse
isotropic. We reexamine their theory and recommend that the Σ-percentages
be abandoned. We also recommend that the hexagonal approximations to T
be replaced with the closest transverse isotropic maps to T.
poster 53
Refining Splitting Intensity Measurements of Shear Wave
Splitting for Multi-Layer Anisotropy
VALENCIA, N., University of California, Berkeley, California, USA,nicolasv03@berkeley.edu; KUMAR, U., University of California, Berkeley,
California, USA, utpalkumar@berkeley.edu; SOERGEL, D., Universityof California, Berkeley, California, USA, d.soergel@berkeley.edu;
ROMANOWICZ, B., University of California, Berkeley, California, USA,barbarar@berkeley.edu
The presence of seismic anisotropy within the Earth’s upper mantle is wellknown and observed. Methods for measuring azimuthal anisotropy throughshear wave splitting (Silver & Chan 1991, Vinnik et al. 1989) are proven tobe effective, assuming a single layer of anisotropy with horizontal symmetry.
However, these methods become less reliable when applied to regions of the
Earth with more than one anisotropic layer. Results from these methods in thesouthwest Pacific imply non-orthogonal polarization directions, indicative ofmulti-layer anisotropy. The mentioned methodologies can produce multilayer anisotropy measurements, but the resolution is highly dependent on
azimuthal coverage and seismic data quality. Splitting Intensity (SI) is a robust
method to measure azimuthal anisotropy from lower-quality data (Chevrot
2000), but it is mainly applied to single layer anisotropy.
Based on previously published theoretical expressions (Romanowicz &Yuan 2011), SI can be calculated from multiple layers of anisotropy. The focusof this study is to develop a robust measurement process for shear wave splitting in complex anisotropic media, incorporating the multi-layer expressionof SI to solve for station-average anisotropic measurements. A double gridsearch method is applied to obtain splitting parameters from seismic data.
Preliminary results of SI from stations inferred to have multi-layer anisotropy correlate with results presented with the theoretical expressions. Further
development is required to refine the SI results obtained from this continually
improving method. Results from this finer-constrained measurement process
will be contributed as constraints for azimuthal anisotropy full waveform
tomography of the southwest Pacific upper mantle and transition zone.

Applications and Discoveries in Cryoseismology Across
Spatial and Temporal Scales
Oral Session • Thursday 2 May • 4:30 pm PacificConveners: Rick Aster, Colorado State University (rick.aster@colostate.edu); John Cassidy, Natural Resources Canada,
Geological Survey of Canada (john.cassidy@nrcan-rncan.
gc.ca); Jan Dettmer, University of Calgary (jan.dettmer@
ucalgary.ca); Jeremy M. Gosselin, University of Calgary(jeremy.gosselin@ucalgary.ca); Celeste Labedz, Universityof Calgary (celeste.labedz@ucalgary.ca); John-Morgan
Manos, University of Washington (jmanos@uw.edu); Elisa
McGhee, Colorado State University (elisa.mcghee@colostate.

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edu); Stephanie Olinger, Harvard University (stepholinger@
fas.harvard.edu); Rachel Willis, Colorado School of Mines(rwillis1@mines.edu)
Integrated Geophysical and Temperature Sensing
Techniques Towards Scalable Monitoring of Permafrost
Variability in Utqiaġvik, AK
TOUREI, A., Colorado School of Mines, Colorado, USA, tourei@mines.
edu; JI, X., Pennsylvania State University, Pennsylvania, USA, xhji@psu.edu;
MARTIN, E. R., Colorado School of Mines, Colorado, USA, eileenrmartin@
mines.edu; XIAO, M., Pennsylvania State University, Pennsylvania,
USA, mzx102@psu.edu; ROCHA DOS SANTOS, G. F., Pennsylvania
State University, Pennsylvania, USA, grd5166@psu.edu; CZARNY, R.,
Pennsylvania State University, Pennsylvania, USA, rkc5556@psu.edu; ZHU,
T., Pennsylvania State University, Pennsylvania, USA, tyzhu@psu.edu;
WANG, Z., Pennsylvania State University, Pennsylvania, USA, ziyiwang@psu.
edu; RYBAKOV, S., University of Alaska Fairbanks, Alaska, USA, srybakov@
alaska.edu; HALLISSEY, M., Pennsylvania State University, Pennsylvania,
USA, mjh6708@psu.edu; NICOLSKY, D., University of Alaska Fairbanks,
Alaska, USA, djnicolsky@alaska.edu; JENSEN, A., University of Alaska
Fairbanks, Alaska, USA, ajensen@alaska.edu
Climate change is causing an increase in permafrost thaw, affecting bothanthropogenically disturbed areas adjacent to infrastructure and undisturbed
tundra regions. In this research, we use multiple geophysical methods—active
and passive multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and ground temperature sensing—to study heterogeneity in permafrost’s geophysical characteristics in Utqiaġvik, Alaska.
To scale permafrost monitoring spatially and temporally, we deployed 2 kmof distributed acoustic sensing (DAS) and distributed temperature sensing(DTS) cables that continually record passive seismic and temperature data fora three-year duration. MASW results from the active-source survey reveal a
low-high-low shear wave velocities (Vs) pattern in most locations. A notable
inverse correlation is observed between in-situ Vs and ground temperature.
The Vs profiles and electrical resistivity profiles reveal cryostructures such as
cryopeg and ice-rich zones in the permafrost layer. Corroboration of thesegeophysical observations with permafrost core samples’ stratigraphy andsalinity measurements further validates these findings. This combination ofgeophysical and temperature sensing methods, along with permafrost coresampling, confirms a robust approach to assessing permafrost’s spatial variability in coastal environments. Continuous imaging of permafrost seismic
structure through ambient noise DAS tomography, utilizing active-source
survey Vs profiles as baseline models, may provide benchmarks for the rate ofchange in permafrost along the Arctic Ocean coast, thereby informing climate
modeling efforts. Further, our results also indicate that civil infrastructure systems such as gravel roads and pile foundations affect permafrost by thickening
the active layer, lowering the Vs, and reducing heterogeneity. We show how
the resulting Vs profiles can be used to estimate critical parameters for designing buildings in permafrost regions and maintaining existing infrastructure
in polar regions.
Observations From an Active Seismic Distributed Acoustic
Sensing Survey, Combatant Col, British Columbia
MANOS, J. M., University of Washington, Washington, USA, jmanos@
ow.edu; LIPOVSKY, B., University of Washington, Washington, USA, bpl7@
uw.edu; GRÄFF, D., University of Washington, Washington, USA, graeffd@
uw.eduActive seismic surveys in glaciological settings can provide insights into glacier thickness, basal structure, and glacier-bed interface conditions. Thesesurveys often require large investments in instrumentation, personnel, andcamp infrastructure; however, distributed optical fiber sensing provides astable, low maintenance platform for high spatio-temporal seismic samplingof the cryosphere. In conjunction with ice core drilling, opportunistic distributed acoustic sensing (DAS) deployments may be performed down remnant
boreholes once ice cores are retrieved. Here, we present results of an active
seismic survey conducted using Betsy Gun® seismic sources on a high alpine
glacier in British Columbia. A Sintela Onyx DAS interrogator was used tosample both a borehole deployed cable and surface deployed cable. The borehole fiber extended ~218 m deep into the glacier ice and the surface cable
extended ~300 m from the borehole. Seismic shots were placed in ~1 m deep
boreholes drilled in wet surface snow along the surface fiber route and in
boreholes spaced ~100 m radially away from the borehole fiber. In addition
to active seismics, Combatant Col hosts many passive seismic events such as
rockfall and avalanches originating from nearby Mt. Waddington and Mt.

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Combatant. Preliminary investigations reveal resonant borehole tube waves
likely caused by nearby passive seismic sources. Rayleigh wave dispersion is
also evident on surface trenched cable. These observations show promise formodeling glacier ice thickness and revealing glacier-bed interface characteristics currently elusive in this area.
Plucking Base Notes: Seismic Character of a Potential
Glacial Quarrying Event at Saskatchewan Glacier, CanadianRocky Mountains
STEVENS, N. T., Pacific Northwest Seismic Network, Washington, USA,ntsteven@uw.edu; HANSEN, D. D., University of Wisconsin-Madison,
Wisconsin, USA, ddhansen3@wisc.edu; ZOET, L. K., University of WisconsinMadison, Wisconsin, USA, lzoet@wisc.edu; ALLEY, R. B., Pennsylvania State
University, Pennsylvania, USA, rba6@psu.edu
Glaciers are one of the most powerful geomorphic forces on Earth, carving
landscapes through a combination of abrasion and quarrying. These rock fracturing processes produce seismic emissions, as observed in experimental conditions and predicted in numerical theory. Glacier seismicity also arises fromprofoundly diverse sources, which hinders our ability to substantiate causal
relationships between field observations and glacier bed processes. Recent
bed-proximal seismic observation of a subglacial asperity provided unparalleled insights on the seismic character of abrasion that supports numericaland experimental theory (Gräff et al., 2021). Similar empirical support has notbeen reported for quarrying.
Abundant and accurately locatable glacier-bed seismicity observed witha dense surface array at Saskatchewan Glacier in August 2019 provided new
empirical support for hydrologically modulated transient slip mechanics(Stevens et al., accepted). This catalog also contains a burst of hundreds of bedproximal events clustered on the headwall of an overdeepening as glacier slip
accelerated on the morning of August 10th; a normally aseismic time within
the diurnal seismic cycles observed during this month. The timing, position,and dynamic context of this seismic cluster is consistent with characteristics
of subglacial quarrying experiments and relevant numerical theory (Cohen etal., 2006). Here we present detailed analysis of this potential quarrying event,refining the event catalog through manual reanalysis, double-difference relocation, and source parameter estimation to further motivate causal linkages toglacier quarrying theory.
Cohen, D. and 4 others, 2006, Role of transient water pressure in
quarrying: A subglacial experiment using acoustic emissions. JGR-ES. doi:
10.1029/2006JF000439.
Gräff, D. and 5 others, 2021, Fine structure of microseismic glacial stickslip. GRL. doi: 10.1029/2021GL096043.
Stevens, N.T., and 6 others, Accepted, Icequake insights on transient
glacier slip mechanics near channelized subglacial drainage. EPSL. doi:
10/1016/j.epsl.2023.118513
Ross Ice Shelf Lamb Wave Propagation and Permanent
Displacement Induced by Whillans Ice Stream Slip Events
WIENS, D. A., Washington University in St. Louis, Missouri, USA, doug@
wustl.edu; ASTER, R. C., Colorado State University, Colorado, USA, Rick.
Aster@colostate.edu; NYBLADE, A. A., Pennsylvania State University,
Pennsylvania, USA, aan2@psu.edu; BROMIRSKI, P. D., University ofCalifornia, San Diego, California, USA, pbromirski@ucsd.edu; GERSTOFT,
P., University of California, San Diego, California, USA, gerstoft@ucsd.edu;
STEPHEN, R. A., Woods Hole Oceanographic Institution, Massachusetts,
USA, rstephen@whoi.edu
Ice shelves are generally assumed to move slowly and steadily from their
grounding lines to the ice front. Here we report the detection of ice-propagating extensional Lamb (plate) waves accompanied by pulses of permanent
ice shelf displacement, observed by a network of co-located GNSS receivers
and broadband seismographs deployed on the Ross Ice Shelf in 2014-2016.
The extensional waves and ice shelf displacement are produced by the onceor twice daily tidally triggered basal slip events of the Whillans Ice Stream(WIS), which flows into the ice shelf. The extensional waves are observed onbroadband seismographs as two or three non-dispersive long-period (20 -100s) pulses spanning 15-30 minutes, radiated at the three main sites of basal
slip acceleration identified by previous studies of the WIS. The extensional
wave initial particle motions are nearly horizontal and radial to the WIS, andare detected at distances of greater than 500 km. The propagation velocityof 2.8 km/s is intermediate between the shear and compressional ice velocities, with velocity and particle motions consistent with theoretical predictions for thin-plate extensional Lamb waves. Following the first extensional
wave arrival, GNSS observations show that the entire ice shelf is displaced
about 0.06 meters in a direction away from the WIS, with peak velocity thatwww.srl-online.org•

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is more than an order of magnitude above the normal flow rate. The observed
maximum particle velocities of about 0.0002 m/s imply peak dynamic strainson the order of 10-7, comparable to strains from earthquake surface waves
that trigger ice quakes. These results demonstrate that stick-slip events in ice
streams can produce elastic waves and short-term strain pulse that propagate
across the entire downstream ice shelf.
Seismology at South Pole, Antarctica: History and Future
Opportunities
ANTHONY, R. E., U.S. Geological Survey, New Mexico, USA, reanthony@usgs.gov; DUVERNOIS, M., University of Wisconsin–Madison, Wisconsin,
USA, michael.duvernois@icecube.wisc.edu; ASTER, R. C., Colorado State
University, Colorado, USA, Rick.Aster@colostate.edu; BAINBRIDGE, G.,
Nanometrics, Ottawa, Canada, geoffreybainbridge@nanometrics.ca; BRAUN,
J., University of Wisconsin-Madison, Wisconsin, USA, jim.braun@icecube.
wisc.edu; CHERWINKA, J., University of Wisconsin-Madison, Wisconsin,
USA, jcherwinka@psl.wisc.edu; DE ARMOND, J., U.S. Geological Survey,
New Mexico, USA, jdearmond@usgs.gov; GRULKE, S. L., University of
Wisconsin-Madison, Wisconsin, USA, sgrulke@wisc.edu; KROMER, E.,
KBR, New Mexico, USA, ekromer@contractor.usgs.gov; SANDSTROM, P.,
University of Wisconsin-Madison, Wisconsin, USA, sandstrom@icecube.
wisc.edu; SHEN, W., Stony Brook University, New York, USA, weisen.shen@stonybrook.edu; STOUP, V., KBR, New Mexico, USA, vstoup@contractor.
usgs.gov; TANNER, G., U.S. Geological Survey, New Mexico, USA, gtanner@usgs.gov; WEBER, J., University of Wisconsin-Madison, Wisconsin, USA,jeff.weber@icecube.wisc.edu; ZHAN, Z., California Institute of Technology,
California, USA, zwzhan@caltech.edu
The U.S. government has operated a seismometer at South Pole, Antarctica(SPA) since the construction of Amundsen-Scott station in 1957. The current station (QSPA) has been highly utilized for the detection and location of
global earthquakes and nuclear explosions, studies of swell activity and sea ice
around Antarctica, and cryoseismology. However, long-period (> 40 s) noiselevels compromise ambient ground motion observations on all three of thestation’s borehole broadband seismometers. These high noise levels arise fromboth instrument self-noise and susceptibility to magnetic field variations,
ultimately compromising the ability to make unique normal mode and tidal
loading observations at the rotation axis of Earth. To improve long-period
seismic observations at the South Pole, the U.S. Geological Survey is collaborating with the IceCube Neutrino Observatory to install a Nanometrics
Trillium 360 GSN seismometer at 2.4 km depth within the Antarctic icecap.
This presentation will discuss progress toward developing the technology toemplace a sensor at such depths, including an overview of drilling technology used within IceCube. Additionally, opportunities to further advance thefield of cryoseismology by leveraging the extensive infrastructure and physics
experiments conducted out of Amundsen-Scott will be highlighted. Future
opportunities include re-instrumenting QSPA, installing quasi-permanent
broadband seismic arrays, and interrogating dark fiber (e.g., DAS) associatedwith this infrastructure.

Applications and Discoveries in Cryoseismology Across
Spatial and Temporal Scales [Poster Session]
Poster Session • Thursday 2 May
Conveners: Rick Aster, Colorado State University (rick.aster@colostate.edu); John Cassidy, Natural Resources Canada,
Geological Survey of Canada (john.cassidy@nrcan-rncan.
gc.ca); Jan Dettmer, University of Calgary (jan.dettmer@
ucalgary.ca); Jeremy M. Gosselin, University of Calgary(jeremy.gosselin@ucalgary.ca); Celeste Labedz, Universityof Calgary (celeste.labedz@ucalgary.ca); John-Morgan
Manos, University of Washington (jmanos@uw.edu); Elisa
McGhee, Colorado State University (elisa.mcghee@colostate.

edu); Stephanie Olinger, Harvard University (stepholinger@
fas.harvard.edu); Rachel Willis, Colorado School of Mines(rwillis1@mines.edu)
poster 182
Machine Learning for Icequake Detection and Location
Across the Eastern Shear Margin of Thwaites Glacier, West
Antarctica
GONZALEZ, L. F., University of Texas at El Paso, Texas, USA, lfgonzalez95@
hotmail.com
The dynamics and potential migration of the Eastern Shear Margin of
Thwaites Glacier could play a critical role in the stability of the West Antarctic
Ice Sheet and future sea-level rise projections. The current position of thisboundary is inferred to be weakly controlled by basal properties and topography. Additionally, recent observations of a transition from frozen to thawed
bed beneath this shear margin and evidence for a water system, could indicate
a potential control on the strength of the bed and potentially allow future outward migration. Previous passive seismic studies of basal crevassing, stick-slip
events, and their relationship with englacial and subglacial water have shedlight on glacier basal conditions. To investigate the type and extent of theseseismic events in addition to changes in basal conditions, we use a 2-year passive seismic dataset, from December 2019 to January 2022, from two 7-stationarrays, TIME1 and TIME2, crossing Thwaites’ Eastern Shear Margin. We follow an icequake detection, location, template-matching, and relocation routine using easyQuake, EQcorrscan, and hypoDD. Although results provide an
icequake catalog for events around both seismic arrays, we focus on a clusterof 1757 events, located a few kilometers from the TIME1 array in an area ofslow-moving ice. We interpret these icequake observations and implications
for the stability of Thwaites’ shear margin and the broader West Antarctic Ice
Sheet.
poster 183
Probabilistic Multiphysics Inference for Permafrost
Characterization and Earthquake Site Hazards Assessment
GOSSELIN, J. M., University of Calgary, Calgary, Canada, jeremy.gosselin@ucalgary.ca; DETTMER, J., University of Calgary, Calgary, Canada, jan.
dettmer@ucalgary.ca; SHAHSAVARI, P., University of Calgary, Calgary,
Canada, pejman.shahsavari@ucalgary.ca
Permafrost thaw negatively impacts ecosystems and infrastructure throughout northern regions, which are warming at greater than double the global
average rate. Permafrost plays a crucial role for soil stiffness and shear
strength, and its degradation is a source for increasing risks of natural hazards, including landslides, thaw subsidence, and earthquake-related hazards.
The severities of these impacts remain poorly studied, and mitigation efforts
require better subsurface characterization and monitoring of temporal permafrost changes, as well as improved constraints on permafrost mechanical(poro-elastic) properties. This work considers the potential of permafrost
characterization with probabilistic multiphysics inference of non-invasive
geophysical observations. Our analysis employs a probabilistic (Bayesian)framework for robust characterization of uncertainties in inferred permafrost
properties. We demonstrate this analysis with synthetic audio-magnetotelluric, seismic surface-wave dispersion, and seismic horizontal-to-vertical ratio
data under varying permafrost conditions. The complementary information
contained in the different data types, and the probabilistic estimation of objective data weights, enables higher-resolution inference of shallow subsurface
properties than can be achieved by independent inference from individual
data types. This is particularly attractive for permafrost characterization andmonitoring, which considers strong elastic and electrical resistive signatures.
Finally, inferred shallow Earth structure under varying permafrost conditions
are used to estimate parameters for typical seismic site hazard classification
and assessment. Our initial results indicate climate-change likely has, andwill, influence earthquake site hazards. Furthermore, our work represents an
initial step towards improved permafrost characterization for seismic hazard
assessment with robust uncertainty quantification while avoiding subjective
inversion practices.
poster 184
Bayesian Surface Wave Dispersion Data Inversion of
Glaciated Environments
LANTERI, A., ETH Zurich, Zurich, Switzerland, ariane.lanteri@erdw.ethz.
ch; GEBRAAD, L., ETH Zürich, Zürich, Switzerland, larsgebraad@gmail.com;
ZUNINO, A., ETH Zürich, Zürich, Switzerland, andrea.zunino@erdw.ethz.

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ch; KEATING, S., ETH Zürich, Zürich, Switzerland, scott.keating@erdw.ethz.
ch; KLAASEN, S., ETH Zürich, Zürich, Switzerland, sara.klaasen@erdw.ethz.
ch; JONSDOTTIR, K., Icelandic Meteorological Office, Reykjavik, Iceland,
kristin.jonsdottir@vedur.is; HOFSTEDE, C., Alfred Wegener Institute,
Bremerhaven, Germany, Coen.Hofstede@awi.de; EISEN, O., Université deStrasbourg, Bremerhaven, Garemany. Strasbourg, France, olaf.eisen@awi.de;
ZIGONE, D., Université de Strasbourg, Strasbourg, France, zigone@unistra.
fr; FICHTNER, A., ETH Zürich, Zürich, Switzerland, andreas.fichtner@erdw.
ethz.chWe present a probabilistic approach to the inversion of surface wave dispersion data from glacial environments for various material parameters.
This is intended to (i) investigate the non-linearity of the problem and thenon-uniqueness of the solution, and (ii) properly quantify uncertainties
and trade-offs. The method is based on an approximation to a 1-D stratified
model of the medium under investigation. We then apply this approach toseismic data from Distributed Acoustic Sensing (DAS) experiments deployedon the Vatnajökull ice sheet located on Grímsvötn volcano in Iceland, andthe Northeast Greenland Ice Stream (NEGIS). We use a Bayesian inference
approach, implemented with a Hamiltonian Monte Carlo (HMC) algorithm.
Exploiting derivative information for efficient sampling of high-dimensionalmodel spaces, HMC approximates the posterior probability density with a collection of sampled models. Applied specifically to multi-mode surface wave
dispersion measurements, HMC yields an ensemble of models of 1-D anisotropic stratified media parameterised in terms of the P-wave velocities Vpv
and Vph, the S-wave velocities Vsv and Vsh, the anisotropy parameter η, anddensity ρ. Besides estimating the properties of the medium, and in contrast
to deterministic approaches, this method allows statistical studies to be carried out on the recovered models, such as exploiting the parameter statistical
moments for uncertainty quantification, or assessing non-linearity by examining trade-offs between parameters.
poster 185
Unsupervised Detection and Characterization of
Glaciogenic Noise Sources in Greenland During Winter
MAIER, N., Los Alamos National Laboratory, New Mexico, USA, nmaier@lanl.gov
Glaciers and ice sheets are seismologically rich environments, where ice fracturing, stick-slip basal motion, and subglacial fluid flow all generate distinct
signals which can be used to characterize different glaciogenic processes.
Recently it was found that meltwater produced during summer and storedin partially frozen surface lakes can be released in winter, resulting large scale
ice-flow accelerations that potentially impact long-term ice dynamics and sealevel rise. To better understand these unique events and other poorly observed
wintertime processes, we develop an unsupervised signal detection and classification workflow using UMAP and ST-DBSCAN algorithms to identify andcharacterize glaciogenic noise sources in Greenland. Here, we focus on multiple years of data from a single seismic station near the terminus of JakobshavnIsbræ, the fastest-flowing outlet glacier in Greenland. We show the wintertime
noisescape rapidly transitions from a multi-month quiescent period to thatwith frequent impulsive events and background noise changes. We use UMAP
and ST-DBSCAN to sequence these changing events into different classes ofsignals which we interpret using a combination of polarization analysis, crosscorrelation, modeling, and supplementary datasets of ice dynamic and temperature changes. The results highlight both the benefits of using an unsupervised tool to parse glaciogenic signals which would likely go undetected
elsewise, as well as the difficulty of using a single station to fully attribute themto specific glacier processes.

failure of near-front crevasses that culminate in calving (Aster et al., 2021).
Ice shelf rifting, fracture, and flexure have also been interpreted from seismic
events detected across the expanse of the ice shelf from the full array of 34
seismographs in this deployment (e.g., Baker et al., 2021). We are establishing a catalog of swell-induced short-period seismic events spanning the complete dataset at the three ice-front stations by analyzing swell (0.03–0.12 Hz)
and high-frequency (0.5–5 Hz) band-pass filtered seismograms. Subeventsfrom the dataset will be extracted through the stacking of transient event
peak detections to produce matched filter templates. The templates will beprocessed with an efficient cross-correlation analysis (Senobari et al., 2019)
to complete the catalog and characterize the subevent categories. The catalog
will be leveraged to examine oceanic controlling mechanisms of cryo-seismic
phenomena. Ocean parameters will include wave height and direction, swell(storm) origin, wave period, and sea ice state. Icefront icequakes are most frequent during the austral summer in the absence of sea ice which attenuates
ocean swell (Chen et al., 2019). Antarctic sea ice minimum extent reachedthe lowest minimum in the 44-year record in February of 2023 (Purich &Doddridge, 2023), and seismic observations from this dataset will inform andbenchmark the ice-ocean processes that influence stability at the ice shelf edge.
poster 187
Distributed Acoustic Sensing Reveals What’s in Store(Glacier)
OLINGER, S., Stanford University, California, USA, solinger@stanford.
edu; LIPOVSKY, B., University of Washington, Washington, USA, bpl7@
uw.edu; DENOLLE, M., University of Washington, Washington, USA,mdenolle@uw.edu; BOOTH, A., University of Leeds, Leeds, United Kingdom,
A.D.Booth@leeds.ac.uk
The Greenland ice sheet is the largest contributor to present global mean sea
level rise, and dynamics of Greenland glaciers therefore exert a primary influence on the extent of present and future sea level rise. Frictional, deformational, and hydrological processes near the ice sheet bed control the dynamics
of many glaciers, yet our understanding of glacier dynamics relies predominantly on surface measurements, and observing glacier processes at depth
remains a challenge. While borehole seismic deployments provide continuousrecordings of elastic waves near the glacier bed at a high temporal resolution, the spatial extent of such deployments is often limited to a single point.
Novel fiber optical techniques like distributed acoustic sensing (DAS) retain
the high temporal resolution of traditional borehole seismic deployments
while providing excellent spatial resolution throughout the entire thicknessof the glacier. Here, we explore three days of continuous DAS data recorded
between July 6 and July 9, 2019 at Store Glacier in West Greenland. To image
the velocity structure of the ice, we compute ambient noise cross-correlations
for the entire dataset. Correlation functions stacked over a duration of one
hour reveal P-waves and S-waves that propagate from the near-surface at average velocities consistent with the results of an active source survey carried out
using the same fiber deployment (Booth et al, 2020). We perform ambient
noise cross correlation using data recorded by each channel to characterizespatiotemporal variation in glacier strain. Our results suggest that the broad
region within a few kilometers of the borehole experiences diurnal periodicity in glacier strain with minimal depth variation, consistent with behavior
predicted by a classic simplified model of glacier flow over a deformable bed(MacAyeal, 1989). However, our results also suggest that the region immediately local to the borehole experiences a more complicated strain regime that
may be explained by bumpy bedrock topography or complex basal hydrology.

poster 186
Microseismicity Catalog of Icequakes Induced by Ocean
Swell at the Ross Ice Shelf Ice-Front
MCGHEE, E., Colorado State University, Colorado, USA, elisa.mcghee@colostate.edu; ASTER, R. C., Colorado State University, Colorado, USA, rick.
aster@colostate.edu

poster 188
Array-based Characterization of Seismicity from a Glacial
Lake Outburst Flood
SAWI, T. M., U.S. Geological Survey, California, USA, tsawi@usgs.gov;
HOLTZMAN, B. K., Columbia University, New York, USA, benh@ldeo.
columbia.edu; BEAUCÉ, E., Columbia University, New York, USA, ebeauce@ldeo.columbia.edu; WALTER, F., WSL Swiss Federal Institute for Forest,
Snow and Landscape Research, Birmensdorf, Germany, fabian.walter@wsl.ch;
SEYDOUX, L., Université Paris Cité, Paris, France, seydoux@ipgp.fr

Ice shelves are a critical physical impediment to the flow of grounded ice
toward the ocean, thereby mitigating subsequent impacts to sea level. Ocean
wave interactions with ice shelves generate a continuous background wave
field of high frequency Lamb, and other plate-guided waves that can trigger
micro-icequakes (magnitude ~ -2.5), and calving. Three broadband seismographs deployed approximately 2 km from the ice front of the Ross Ice Shelfin west Antarctica between 2014-2017 (e.g., Bromirski et al., 2015) establishedthat 8-30 s period ocean swell generates impulsive high-frequency seismicity. In some cases, these seismic impulses are associated with the multistage

As Earth’s climate warms, it is increasingly important to monitor the dynamic
and hydraulic conditions at glaciers, especially those that can generate catastrophic glacial lake outburst floods (GLOF). Gornergletscher is the second
largest glacier in the Swiss Alps and for decades has hosted a GLOF event
every summer, releasing millions of cubic meters of water on top of, throughand underneath the ice in a matter of days [1]. We detect and characterize
seismic tremor related to the GLOF event using a five-station Geophone arraywith an aperture of approximately 400 m installed over a five-week period inshallow boreholes in the glacier within 500 m of the lakefront. We calculate

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array coherency matrices as a function of frequency and time [2], then apply
an unsupervised machine-learning algorithm, SpecUFEx [3], to reduce thearray coherency matrices into low-dimensionality based on concurrent lakelevel and GPS measurements. Some clusters coincide with the onset of the
GLOF, suggesting that our technique could offer a means of detecting outburst
floods to complement or replace other observation methods, i.e., in situ lakelevel measurements. One cluster captures a period of previously discovered
harmonic tremor generated from stick-slip events located near the ice-bed
interface [4], and other clusters appear to contain times of newly detected
harmonic or quasi-harmonic tremor as well. We localize the newly detected
tremor near the ice-bed interface, suggesting that stick-slip induced tremor
may occur throughout the GLOF event, rather than just on a single day. By
combining an array-based approach with unsupervised machine learning, we
can characterize glacial tremor to better understand the dynamic behavior of
Gornergletscher, especially as it pertains to catastrophic GLOF events.
Works Cited: [1] Huss et al., (2007). Journal of Glaciology [2] Seydoux
et al., (2016a) Geophysical Journal International [3] Holtzman et al., (2018).
Science Advances [4] Umlauft et al., (2021). Geophysical Research Lettersposter 189
Controlled-Source Seismic Imaging of Mcmurdo Ice Shelf
Near Williams Airfield
SELDON, Y., University of Texas at El Paso, Texas, USA, yseldon@miners.
utep.edu; KARPLUS, M. S., University of Texas at El Paso, Texas, USA,mkarplus@utep.edu
Understanding the structure and thickness of the McMurdo Ice Shelf and theocean environment below is important from an operational as well as scientific perspective. The McMurdo Ice Shelf is part of the Ross Ice Shelf, andice shelf mass loss has been observed due to warming ocean conditions in
the Ross Sea. During December 2021, the Thwaites Interdisciplinary Margin
Evolution (TIME) project team conducted a seismic survey along an 1100-m
seismic line near William’s Airfield on McMurdo Ice Shelf. We deployed
twenty-four MagseisFairfield, Z-Land Generation 2, 5-Hz, 3-component
seismic nodes at 50-m spacing for 30 days. Both passive and active seismic
sources were captured, with a day of controlled seismic sources generated by a
12-lb sledgehammer at 23 locations with 50-m spacing, with 3 hammer strikes
at each location to stack and enhance the signal. The hammer signal generated 80–100 Hz frequency observed in the spectrograms, which was used todevelop four corner filtered shot gathers to observe wave propagations. We
process the controlled-source refraction data to define a velocity model ofthe ice shelf and environment below using Python ObsPy tools. Corrected
and filtered data were imported to Shearwater Reveal to visualize the seismic
data and make observations about the data quality and wave propagation. The
survey was also a methods test for the use of seismic nodes for ice shelf (andglacier) imaging with controlled sources, and we discuss lessons learned for
future deployments.
poster 190
Unsupervised Clustering of Cryoseismic Events Recorded
by Distributed Acoustic Sensing at Rhonegletscher,
Switzerland
WILLIS, R., Colorado School of Mines, Colorado, USA, rwillis1@mines.
edu; GRIMM, J., ISTerre, Université Grenoble Alpes, Grenoble, France,
julius.grimm@univ-grenoble-alpes.fr; STANEK, F., Silixa, Borehamwood,
United Kingdom, frantisek.stanek@silixa.com; EDME, P., ETH Zürich,
Zürich, Switzerland, pascal.edme@erdw.ethz.ch; FICHTNER, A., ETH
Zürich, Zürich, Switzerland, andreas.fichtner@erdw.ethz.ch; LIPOVSKY, B.,
University of Washington, Washington, USA, bpl7@uw.edu; PAITZ, P., Swiss
Federal Institute for Forest, Snow and Landscape Research WSL, Zürich,
Switzerland, patrick.paitz@wsl.ch; WALTER, F., Swiss Federal Institute for
Forest, Snow and Landscape Research WSL, Zürich, Switzerland, fabian.
walter@wsl.ch; SIEGFRIED, M., Colorado School of Mines, Colorado, USA,
siegfried@mines.edu; MARTIN, E., Colorado School of Mines, Colorado,
USA, eileenrmartin@mines.edu
Higher fidelity monitoring and better quantification of mountain glacier processes remain a key priority as climate change transforms glaciated regions
into landscapes of rocks, debris, ice-debris complexes, and glacial lakes. Our
capability to monitor these highly dynamic and hazardous conditions for local
communities remains limited by a lack of data at high spatial and temporal
resolution. Distributed Acoustic Sensing (DAS) provides a unique opportunity to capture detailed spatiotemporal variations within and around a glacier.
We focus on a DAS experiment from Rhonegletscher (Switzerland), during

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which we recorded data continuously for one month in 2023 using a 9 km
fiber-optic cable on the ice surface. This deployment extended from the accumulation zone to near the glacier terminus, providing a unique perspective
on glacial processes across surface balance regimes. The data captured environmental noise (e.g., wind, precipitation events) and acoustic signals from avariety of glacial processes, including surface fracturing and basal icequakes.
DAS monitoring results in large data volumes, rendering manual event picking and classification as well as real time data telemetry practically unfeasible.
Instead, we used automated processing tools and unsupervised clustering forevent detection and classification with the goal of generating a comprehensive, classified catalog of cryoseismicity in the Rhonegletscher. We generated
a low-dimensional feature representation of the data from the automated processing tools and used this data as input for an unsupervised clustering algorithm. We compared the clusters’ signal characteristics and spatiotemporal
distribution with potential forcing mechanisms, including comparison withenvironmental data such as temperature and wind to assist in the identification or correlation of source processes. Our automated pipeline for DAS
data analysis provides a new, high-resolution perspective on Rhonegletscher’s
response to short-term environment forcing and a pathway for leveraging themassive data volumes produced by DAS installations for real-time monitoringof alpine environments.

Assessing Seismic Hazard for Critical Facilities andInfrastructure—Insights and Challenges
Oral Session • Friday 3 May • 2:00 pm PacificConveners: Céline Beauval, ISTerre, Université Grenoble
Alpes (celine.beauval@univ-grenoble-alpes.fr); Glenn
Biasi, U.S. Geological Survey (gbiasi@usgs.gov); OlgaJoan Ktenidou, National Observatory of Athens (olga.
ktenidou@noa.gr); Andreas Skarlatoudis, AECOM (andreas.
skarlatoudis@aecom.com)
Challenges in Site-Specific Seismic Hazard Analyses for
Mine Tailings Storage Facilities in South America
WONG, I., Lettis Consultants International, California, USA, wong@lettisci.
com; GRAY, B., Lettis Consultants International, California, USA, gray@lettisci.com; GIVLER, R., Lettis Consultants International, California, USA,
givler@lettisci.com; WU, Q., Lettis Consultants International, California,
USA, wu@lettisci.com; DARRAGH, R. B., Pacific Engineering & Analysis,
California, USA, bbalindavis@gmail.com; BUBECK, A., Lettis Consultants
International, California, USA, bubeck@lettisci.com
The recent increased need for site-specific probabilistic seismic hazard analyses (PSHAs) of mine tailings storage facilities (TSFs) has been driven by recent
failures worldwide that resulted in significant loss of life and environmental
damage. As a result, the Global Industry Standard on Tailings Management
was developed, setting guidelines for both the design of new TSFs and evaluations of existing TSFs, with seismic design criteria for high- to extremeconsequence structures being adopted for return periods of 2,475 to 10,000
years. These long return periods present challenges to mine owners as theyoften result in high design ground motions in seismically active regions suchas those along the South America subduction zone. We have performed sitespecific seismic hazard analyses for TSFs throughout South America (e.g.,
Colombia, Ecuador, Peru, Chile, and Argentina). One of the challenges in performing such analyses in these countries is that prior seismic hazard evaluations have often underestimated the hazard for several reasons. First, there has
been an over-reliance on the historical seismicity record due to the belief thatthe historical record alone would accurately predict future hazard. Second,
existing Quaternary fault databases are often incomplete, which commonly
results in the discovery of previously unrecognized Quaternary sources or recharacterization of known faults. When local fault sources are incorporated,
they commonly include narrow epistemic uncertainties that are poorly supported with available data. Third, hazard analyses in South America have not
kept pace with rapidly evolving ground motion models (GMMs). The recently
developed NGA-Subduction GMMs have presented major challenges becauseof the significant increase in hazard over previous models. Finally, there has
been a lack of adequate characterization of site effects with GMMs and Vs30
being used when the site conditions would call for site response analyses, e.g.,thin soil or weathered rock sites.

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Landfill Design Ground Motion at the Paducah Gaseous
Diffusion Plant (Central United States)
WANG, Z., University of Kentucky, Kentucky, USA, zmwang@uky.edu;
CARPENTER, N., University of Kentucky, Kentucky, USA, seth.carpenter@uky.eduThe Paducah Gaseous Diffusion Plant, a Superfund site near Paducah,
Kentucky, in the central United States, is a former uranium enrichment plant
owned by the U.S. Department of Energy (DOE). Due to its proximity to the
New Madrid Seismic Zone, ground motion hazard is a concern for the site’s
waste disposal facilities related to site cleanup, such as the landfill and the
CERCLA disposal cell. Site effect is also a concern because the site sits on thicksediments (about 100 m) over hard Paleozoic bedrock. The Environmental
Protection Agency regulation (Title 40) requires that the maximum expectedhorizontal acceleration with a 90 percent or greater probability that the acceleration will not be exceeded in 250 years, or the acceleration based on a sitespecific seismic risk assessment, is considered for the landfill seismic design.
The acceleration with a 90 percent or greater probability that the acceleration
will not be exceeded in 250 years is equivalent to the acceleration with a 2
percent probability of exceedance in 50 years or 2,500-year return period. A
probabilistic seismic hazard analysis (PSHA) conducted for the site in 1999
resulted in a peak horizontal ground acceleration (PGA) of 0.80g on top ofrock and 0.51g on the surface with a 2,500-year return period. These highestimated accelerations made it difficult for the U.S. DOE to obtain a permit
from the federal and state regulators to construct a landfill or CERCLA cell at
the site. A deterministic seismic hazard analysis (DSHA) was conducted forthe site in 2010 and resulted in a PGA of 0.36g on top of rock and 0.33g on thesurface. The federal and state regulators accepted the PGA of 0.33g on the surface for seismic design of the landfill at the Paducah Gaseous Diffusion Plant
in 2012. We will present a brief history of seismic hazard assessment for the
Paducah Gaseous Diffusion Plant and discuss the strengths and weaknesses of
PSHA and DSHA for developing design ground motions for critical facilities
and infrastructure.
Characterizing Uncertainty in the Canadian National
Seismic Hazard Model
KOLAJ, M., Natural Resources Canada, Ottawa, Canada, michal.kolaj@
nrcan-rncan.gc.ca; ADAMS, J. A., Natural Resources Canada, Ottawa,
Canada, John.Adams@nrcan-rncan.gc.ca
A major effort is underway for the critical review of the included epistemic
uncertainty in the Canadian seismic hazard model and the influence on hazard products other than the mean. Within the Canadian engineering community, mean hazard is used for most designs and safety analyses, even for
critical infrastructure and facilities. While site-specific models are required
for most high-importance structures, the national model is often used as ascreening tool or for comparison against site-specific results. Understanding
the full distribution of epistemic uncertainty is warranted. At a minimum
there needs to be a renewed focus on upper fractile (84th, 90th, 95th percentile) hazard, because the upper tail of the distribution is likely the tail thatwill most often challenge the engineered performance of a structure during alarge earthquake. However, estimating upper fractile values brings additionalmodel-building challenges. This presentation will focus on how uncertainty
is currently included in the Canadian national seismic hazard model and on
areas of research currently being explored to improve the characterization andcommunication of epistemic uncertainty within Canada’s PSHA models.
Importance of Site-Specific Ground Motion Data for
Critical Facilities
HASSANI, B., BC Hydro, Burnaby, Canada, behzad.hassani@bchydro.com;
YAN, L., BC Hydro, Burnaby, Canada, li.yan@bchydro.com
For rigid structures of critical facilities situated on hard rock, accurate characterization of ground motions at high frequencies is critical. Empirical groundmotion models (GMMs) typically lack enough observational data on hardrock sites, and predictions from the GMMs may carry substantial uncertainties. To adjust the seismic hazard for hard rock site condition, the current
state-of-practice is to perform a VS-kappa0 (kappa0 is the near-surface highfrequency attenuation parameter) host-to-target correction to develop hardrock correction factors. However, in absence of site-specific ground motion(SSGM) data, the modeling parameters and their corresponding epistemic
uncertainties are not well quantified, which leads to unreliable hard rock correction factors and hard rock adjusted seismic hazard results.
We have carried out an alternative approach to characterize the hardrock site response (HRSR) in probabilistic seismic hazard analysis (PSHA)
using SSGM data. The approach relies on estimation of non-ergodic HRSR at

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Seismological Research Lettersa given site using SSGM recorded on broadband seismographs. Using nonergodic site response, we effectively remove the site-to-site variability fromPSHA while accounting for epistemic uncertainty of HRSRs which are wellquantified with sufficient recorded SSGM data. This approach can be implemented even for regions with low-to-moderate seismicity rate, where earthquakes with M > 3 recorded at distances > 50 km are common. Since 2020,
we have instrumented multiple BC Hydro’s critical dam facilities in British
Columbia, Canada, to characterize the non-ergodic HRSR. Depending on therate of seismicity and the level of noise at a given facility, we were able to collect sufficient SSGM data within 1-3 years. In addition, having multiple seismic stations at selected facilities has enabled us to explore the degree of topographic effects on HRSR. The non-ergodic HRSR can differ significantly fromgeneric HRSR specifically at high frequencies, and the observed differences
are likely due to factors that are not considered in typical ground response
analysis (e.g., 2D, 3D effects).
Site-Response Assessment Using Empirical Techniques for
Nuclear Sites in South-Eastern France: Comparisons WithSsr and Numerical Simulation Estimates.
BUSCETTI, M., French Alternative Energies and Atomic Energy
Commission, Saint-Paul-lez-Durance / Grenoble, France, margaux.buscetti@
cea.fr; TRAVERSA, P., Electricité de France, Aix-en-Provence, France, paola.
traversa@edf.fr; HOLLENDER, F., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance / Grenoble, France, fabrice.
hollender@cea.fr; PERRON, V., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance, France, Vincent.PERRON@
cea.fr; MOCZO, P., Comenius University Bratislava, Brastilava, Slovakia,
peter.moczo@fmph.uniba.sk; KRISTEK, J., Comenius University Bratislava,
Bratislava, Slovakia, Jozef.Kristek@fmph.uniba.sk; GALIS, M., Comenius
University Bratislava, Bratislava, Slovakia, martin.galis@uniba.sk
Site-specific Seismic Hazard Estimates is becoming the standard practicefor critical facilities such as nuclear sites. This involves taking into accountthe specific characteristics and seismic response behaviour of the site understudy as accurately as possible. To assess the seismic site response, Standard
Spectral Ratio (SSR) or 1D (2D/3D) numerical modelling are usually used.
Nevertheless, the SSR method requires choosing a reference site near thetarget one, and for ground motion numerical simulations, costly geotechnical and geophysical measurements are needed. Since several years, empirical approaches based on national/regional ground motion databases, suchas empirical ground-motion models (GMMs) and Generalized Inversion
Techniques (GITs), have proven that reliable site response could be obtainedwith respect to a given reference condition which does not have to be a real
station located close to the target one. The aim of this work is to assess thereliability and robustness of site responses obtained using GITs and GMMs
regressions techniques (site residual δS2S) for a sedimentary site located ina low to moderate seismic context (south-eastern France) where SSRs andtransfer functions computed by numerical simulations (1D/2D/3D) are available. For comparisons, they are all computed with respect to the same reference station installed on outcropping rock close to the basin. Two types ofgeneralized inversion techniques (Oth et al. 2011 and Grendas et al. 2022) and
one ground motion model (Traversa et al. SSA abstract) have been used. They
are based on the Epos-France database (Buscetti et al. In prep), consisting ofearthquakes of M_l≥3 that have occurred in mainland France or surrounding countries. Finally, with the aim of assessing the minimum amount of datanecessary to obtain reliable site responses using each technique, the original
dataset has been decimated. The results will be presented in the perspectiveof providing a rough estimate of the minimum recording time required forseismic instruments to provide reliable site response at critical facilities.
Issues in the Selection of Design Values for Surface Fault
Rupture for Critical Facilities Using Probabilistic Fault
Displacement Hazard Analysis
ABRAHAMSON, N. A., University of California, Berkeley, California, USA,abrahamson@berkeley.edu
For most applications, the approach to fault displacement hazard is avoidance through use of setbacks from active faults; however, for some lifelines,
an active fault must be crossed. In other cases, new faults are discovered atexisting critical infrastructure that need to be addressed. Historically, deterministic approaches have been used to estimate design fault displacement, but
probabilistic fault displacement hazard analysis (PFDHA) is being used more
frequently. The PFDHA follows a similar approach as standard probabilistic
seismic hazard analysis (PSHA) used for ground motion, but there are issues
that affect PFDHA that are not common in PSHA. The first issue is the selection of the design fault displacement based on the hazard curve. Often, thewww.srl-online.org•

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return period for the fault displacement is simply set at the same return period
as the ground motion for the structure; however, the objective should be tohave similar risk for fault displacement and ground motion, not similar hazard. Because the fault displacement hazard only includes events that rupture
to the surface at the site, the hazard curves are flat at small displacements. If
the recurrence interval for surface rupturing events at the site is not muchlarger than the selected return period, then the displacement at a given return
period will be sensitive to the uncertainty in the activity rate. For example, anincrease in the slip rate of a factor of 2 can lead to a factor of 6 increase in thedisplacement at the specified rerturn period. If a risk-targeted displacement isdeveloped based on the same risk level used for buildings, the displacement
can be a factor of 3 larger than the displacement for the 2500-yr return period.
In many cases, simply using the displacement based on the mean hazard for a
specified return period will not be appropriate for the design of critical infrastructure. GIven the sensitivity of the PFDHA results, alternative approaches
to selecting the design displacement should be considered, such as using themedian displacement from the distribution of displacements for events causing surface rupture at the site.
Exposure of Australia’s Infrastructure to Ground Surface
Rupture Hazard
QUIGLEY, M., University of Melbourne, Melbourne, Australia, mark.
quigley@unimelb.edu.au; WERNER, T., University of Melbourne, Melbourne,
Australia, tim.werner@unimelb.edu.au; YANG, H., Zhejiang University,
Hangzhou, China, haibin.yang@zju.edu.cn
Australia has hosted at least 11 surface-rupturing earthquakes since 1960, with
moment magnitudes (Mw) between 4.7 and 6.6. The Australian Neotectonic
Features Database (NFD) hosts an inventory of over 400 Australian intraplate faults, fault-related folds, and other features that are demonstrated orsuspected to relate to earthquakes large enough to deform the Earth’s surface. Recent re-analyses of earthquake data have resulted in updated scaling
relationships and slip distribution functions, for utility in probabilistic fault
displacement hazard analyses. Geospatial comparisons of Australia’s energy,
resource, and transport infrastructure (e.g., dams, pipelines, transport) withhistorical and neotectonic ground surface rupture traces enables developmentof a proximity / overlap-based rating scheme for prioritising infrastructure
mitigation / adaptation measures. This talk will present preliminary resultsfrom a suite of ongoing research programs on fault mapping, paleoseismology, and infrastructure exposure analyses at a variety of spatial scales acrossthe continent.
Studies of Fragile Geologic Features in Central New
England, USA, and Northeastern New Zealand
STIRLING, M. W., University of Otago, Dunedin, New Zealand, mark.
stirling@otago.ac.nz; PRATT, T. L., U.S. Geological Survey, , USA, tpratt@usgs.gov
We provide an overview of studies of fragile geological features (FGFs) in
New England, USA, and New Zealand. The New England studies focus on
FGFs in Massachusetts, New Hampshire, and western Maine. The FGFs arelarge erratic boulders that became delicately balanced during melting of theLaurentide ice sheet 21,000 to 15,000 years ago. Each FGF was photographedfor development of a 3-dimensional model to quantify the fragility (shaking
required to topple the FGF), and seismometers were briefly installed both on
and away from the FGF to measure the response of the boulder to push tests
and ambient noise. The age and fragility of the FGFs appear to show compatibility with the U.S. National Seismic Hazard Model (NSHM), likely due to theabsence of large earthquakes (Mw>7) in the region since the FGF emplacement and short period motions from moderate earthquakes (5<Mw<7) being
insufficient to topple the rocks. The New Zealand studies focus on FGFs in theeast coast of the North Island, where the new NSHM shows major increases
in hazard relative to earlier models. At the time of writing this abstract only
reconnaissance efforts had been carried out, with studies of the fragility andage of specific FGFs planned for early 2024.
Fault-Displacement Models for Aggregate, Principal, andDistributed Displacements
LAVRENTIADIS, G., California Institute of Technology, California, USA,glavrent@caltech.edu; ABRAHAMSON, N. A., University of California,
Berkeley, California, USA, abrahamson@berkeley.edu

component of the slip vector. The FDMs are developed based on the Fault
Displacement Hazard Initiative Project Dataset comprised of 75 events withmagnitude ranging from 4.9 to 8.0. The model for the aggregate displacement isformulated first in the wavenumber domain to incorporate seismology-based
constraints for the extrapolation of the magnitude scaling of median displacements to large-magnitude events and then transformed to the space domain
to facilitate its implementation. The space domain model is then empiricallyadjusted to account for small-to-moderate magnitude scaling, displacement
tapering near the edges, and the effect of segmentation. Segments are usedin the development of the original model to capture the slip variability better. For applications in which segments cannot be determined in advance, an
FDM is provided, with the number, lengths, and locations of the segments
included as part of the aleatory variability. The principal-displacement FDM
is developed next as an adjustment to the aggregate-displacement FDM. The
total distributed displacement is determined based on the aggregate to principal difference, and probabilistic models are developed to compute the number, location, and partition of total distributed slip into individual ruptures.
A key feature of the new FDMs is the use of a power-normal distribution for
the aleatory variability of aggregate and principal displacements, leading tonarrower distributions of displacements for large magnitudes compared toexisting FDMs. Furthermore, for large-magnitude earthquakes, the expected
maximum displacements implied by the proposed model are consistent withthe observed maximum displacements along strike, supporting the narrower
shape of the upper tail of the power-normal distribution for large-magnitude
events.
Looking for Kappa in the US and the UK Using Noise
Modeling
KTENIDOU, O. J., National Observatory of Athens, Athens, Greece, olga.
ktenidou@noa.gr; PIKOULIS, E. V., University of Patras, Patras, Greece,
pikoulis@ceid.upatras.gr; DARRAGH, R. B., Pacific Engineering andAnalysis, El Cerrito CA, USA, bbalindavis@gmail.com; SILVA, W. J., PacificEngineering and Analysis, El Cerrito CA, USA, pacificengineering@juno.
com; ALDAMA-BUSTOS, G., Jacobs, London, UK, Guillermo.AldamaBustos@jacobs.com
In this contribution we combine our experiences from two PSHA studies(using SSHAC protocol) performed for nuclear facilities: Idaho National
Laboratory project in the US and Bradwell B project in the UK. We share anddiscuss the challenge of estimating high-frequency site attenuation, namely
the spectral decay parameter kappa. The data quality assessment stage was crucial in identifying the usable data and their usable frequency band, especiallyat high frequencies. Several issues made the work particularly challenging inboth cases, necessitating careful consideration of uncertainties: 1. All recordings came from distances larger than 100 km, significantly increasing epistemic uncertainties stemming from regional (path) attenuation and variability
in crustal properties. 2. Most of the recordings were of small magnitude, sothat the stress drop (corner frequency) uncertainty became a definitive factor
in selecting the usable bandwidth and hence the appropriate estimation methods for kappa. 3. The uncertainties from the trade-off between site attenuationand site amplification were often considerable. 4. The datasets were small andof poor quality, with low signal strength, and many of the recordings were
unusable according to typical signal-to-noise criteria. Such limitations wereaddressed by a signal-enhancing technique based on stochastic noise modeling. This models the noise that contaminates the earthquake signal and corrects the spectrum for it, rather than avoid it. Thus, the recorded data wererendered usable at much higher frequencies than traditionally possible, and insome cases heretofore unusable recordings were added, enhancing the datasets in quality and quantity.

Assessing Seismic Hazard for Critical Facilities andInfrastructure—Insights and Challenges [Poster Session]
Poster Session • Friday 3 May
Conveners: Céline Beauval, ISTerre, Université Grenoble
Alpes (celine.beauval@univ-grenoble-alpes.fr); Glenn
Biasi, U.S. Geological Survey (gbiasi@usgs.gov); Olga-

As part of this study, we present new fault displacement models (FDMs)
for aggregate, principal, and distributed displacements based on the net

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Joan Ktenidou, National Observatory of Athens (olga.
ktenidou@noa.gr); Andreas Skarlatoudis, AECOM (andreas.
skarlatoudis@aecom.com)
poster 127
Implementation of Interconnected Fault Systems in PSHA:
Testing Existing Algorithms in Different Tectonic Context
EL KADRI, S., Université Grenoble Alpes, Grenoble, France, sarah.el-kadri@univ-grenoble-alpes.fr; BEAUVAL, C., Université Grenoble Alpes, Grenoble,
France, celine.beauval@univ-grenoble-alpes.fr; BRAX, M., National Council
for Scientific Research, Bhannes, Lebanon, brax@cnrs.edu.lb; KLINGER, Y.,
IPGP, Paris, France, klinger@ipgp.fr
Probabilistic Seismic Hazard studies aim at quantifying the recurrence ofground-motions, based on earthquake occurrence models and groundmotion models. Most source models built for PSHA integrate faults in a rigid
way. Within a predefined fault, ruptures can occur on individual segments oron a combination of segments. Ruptures that would involve segments fromdifferent predefined faults are not included in the model. The source model
thus most often includes only a subset of the future ruptures that may occur
on the fault system. In the last decade several research groups have proposed
algorithms for implementing faults in a more realistic way. The first and mostwell-known is the OpenSHA algorithm (Field et al. 2014; Milner and Field
2021), applied on the well-characterized fault system in California. Later on,
the SHERIFS algorithm has been proposed (Chartier et al. 2017, 2019), it issimpler than OpenSHA and requires less input parameters. Both algorithms
rely on the concept of interconnected fault systems, with rules established todefined which combinations of segments are possible, as well as different techniques to distribute the moment rate budget available in the system over thedifferent earthquake ruptures. We analyze the potential of these algorithms
over fault systems with varied levels of deformation: the Sumatran fault system(~15 mm/year), the Levant fault system (~4-5 mm/year), the Java Back-Arc
Thurst Fault (~1-2 mm/year). We aim at understanding how the algorithms
use the information available in the fault system (slip rate estimates, segmentation, paleoseismic earthquakes, historical earthquakes) to produce a set of
ruptures with associated rates. We show that the way the scaling relationshipis applied (either total length or total area) has a strong impact on the hazard results. We analyze critically the source models obtained, accounting for
uncertainties, as well as the hazard levels obtained. Overall, the general trend
is towards a decrease of hazard values with respect to a classical implementation of faults, but in some circumstances hazard values may also increase.
poster 128
Magnitude Dependency of Spectral Decay Parameter(Kappa) at Rock Stations from Event Dataset that is
Restricted Only from Events that are Originated around
Eastern Anatolian Fault (EAF)
BIRO, Y., Independent consultant, Zürich, Switzerland, yesimbiro@bluewin.
ch
The decay of the high frequency ground motion amplitudes of Fourier spectrum, namely the spectral decay parameter, κ (kappa), is highly utilized anddebated in the scientific community in the last decade due to its significant
effect on earthquake hazard evaluations and results. A dataset with a good
spread of magnitude variety in near site as well as far site recordings is needed
to be able to check if this parameter is magnitude dependent or not. Due topaucity of data worldwide, especially hard rock sites, this dependency was
not debated in full coverage, and the parameter is assumed to have the same
decay tendency for high magnitude possible events with the evaluated κ values from low seismic records in the low seismic target regions. AFAD station
spread around East Anatolian Fault has provided a decent dataset especiallyafter the January 2020 Elazığ earthquake of Mw6.8, and the Mw7.7 and Mw7.6
Kahramanmaras earthquakes of February 2023. The results of these datasets
are evaluated in terms of differences in different magnitude bins. Also, KOERI
dataset provided a good insight on the magnitude dependency for the same
region. Especially the results of AFAD Stations Stn4404 with Vs30 1380 m/s,
Stn2302 and Stn2305 with Vs30 907 m/s, and Stn 2409 with Vs30 875 m/s will
provide insight for low seismic, hard rock regions if only taking the low seismic data to arrive at zero epicentral spectral decay parameter, κ0 could bereasonable or not. Future investigations to account for magnitude dependency
and its relations will be the next generation debate in terms of κ and hazard
evaluations.

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Seismological Research Lettersposter 129
Monitoring and No-Money-Toring of Oil and Gas
Production in Southern Italy
BRAUN, T., Istituto Nazionale di Geofisica e Vulcanologia, Arezzo, Italy,
thomas.braun@ingv.it; DANESI, S., Istituto Nazionale di Geofisica e
Vulcanologia, Bologna, Italy, stefania.danesi@ingv.it
Mother Nature does not mind if monitoring agreements are active, andsometimes earthquakes may occur at times, when seismic monitoring is notadequately covered by fundings. In this case the question rises, whether monitoring should be continued anyway, or it should be rather suspended, following the economic availability of a dedicated project. This is the inauspicious
circumstance when No-Money-toring starts.
According to the governmental guidelines, in 2017, the role of the competent authority for the Monitoring of the Oil and Gas production in the Agri
Valley (VA), has been assigned to INGV. The main concessionaire in the VA(South Italy) is the ENI oil-company, operating 25 productive wells locatedbetween the eastern side of the basin and the eastern ridge. With a production
rate of around 90,000 oil barrels/day, the VA oil field is the largest on-shore
oil field in Europe. Since the 1990s, hydrocarbons have been exploited from ahigh-productive reservoir, through production wells drilled down to a depthof 2-3 km below sea level. Since June 2006, wastewater associated with theoil production was re-injected, at around 3000m depth, into the CM2-well,an unproductive marginal section of the carbonate reservoir. Injection rates
rarely reached peaks of 2800-3000 m3/d (normal 2000 m3/d), while the wellhead pressure never exceeded 13-14 MPa. CM2 can be classified as a longterm, high-rate disposal well.
In the middle of the COVID-19 pandemic in April 2021, the two-year
experimental period ended, and was extended for a further 12 months. Dueto an unfavorable combination of individual administrative difficulties by the
public administrations involved, financial funding was interrupted in April
2022. This led to a contractual and financial discontinuity for a period of morethan 20 months. However, INGV decided to continue the monitoring activity; a decision that turned out to be useful, given the non-neglectable seismic activity, occurring during the year 2023. Our contribution will report on
scientific and non-scientific aspects experienced during the Monitoring and
No-Money-toring phase of the VA-project.
poster 130
Insights From Distinct Element Method Models on Fault
Scarp Morphology in Thrust and Reverse Fault
Earthquakes.
CHIAMA, K., Harvard University, Massachusetts, USA, kchiama@g.
harvard.edu; BEDNARZ, W., Brown University, Rhode Island, USA, william_
bednarz@brown.edu; MOSS, R., California Polytechnic State University, San
Luis Obispo, California, USA, rmoss@calpoly.edu; SHAW, J. H., Harvard
University, Massachusetts, USA, shaw@eps.harvard.edu
We seek to better understand and forecast the near-surface coseismic deformation that occurs as a result of large magnitude thrust and reverse fault
earthquakes using geomechanical models. We developed a distinct element
method (DEM) model to evaluate the physical processes that control the pattern of ground surface ruptures on thrust and reverse faults. In prior work,
we used 45 initial 2D DEM models to develop a classification system for fault
scarp morphology (monoclinal, pressure ridge, and simple scarps) each ofwhich can subsequently modified by hanging wall collapse. These relationships are supported by natural rupture patterns from recent and paleo-earthquakes across a range of geologic settings. In this next phase of our study, wetested a suite of 3,425 2D DEM experiments in dense, medium-dense, andloose sediment in a model 50 m wide with 3, 5, and 10 m of sediment depth.
These models include homogeneous and heterogeneous sediment mechanics,
a range of fault dips (20 – 70º), and displacements of up to 5 m. We used amachine learning model (based on computer vision) to take measurements of
the DEM experiments every 5 cm of slip on the fault at depth. This resulted
in ~250,000 measurements of the homogeneous DEM models, which enabledrobust statistical relationships between model parameters (slip, fault dip, sediment strength, and sediment depth) with the observed surface deformation
characteristics (scarp height, width, and dip as well as the tendency to form
backthrusts and secondary fault splays). These relationships are supported bynatural rupture patterns from recent and paleo-earthquakes across a range
of geologic settings. In conjunction with these natural examples, our models
provide a basis to more accurately forecast ground surface deformation characteristics that will result from future earthquakes based on limited information about the earthquake source and local sediment properties.

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poster 131
Overcoming Factors That Limit the Predictive Power ofProbabilistic Fault Displacement Hazard Models
ELLIOTT, A., U.S. Geological Survey, California, USA, ajelliott@usgs.gov;
HAMMER, M., U.S. Geological Survey, California, USA, mhammer@usgs.
gov; VERMEER, J., U.S. Geological Survey, California, USA, jvermeer@usgs.
gov; DELONG, S., U.S. Geological Survey, Minnesota, USA, sdelong@usgs.
gov; KOTTKE, A., Pacific Gas & Electric Company, California, USA, arkk@
pge.com; MADUGO, C., Pacific Gas & Electric Company, California, USA,
c7m0@pge.com; SARMIENTO, A., University of California, Los Angeles,
California, USA, c7m0@pge.com

poster 133
Comparison of Methods to Produce Virtual Ruptures for
Background Seismicity
YUST, M., Slate Geotechnical Consultants, California, USA, myust@slategeotech.com; LARGENT, M., Slate Geotechnical Consultants,
California, USA, mlargent@slategeotech.com; WILLIAMS, T., Slate
Geotechnical Consultants, California, USA, twilliams@slategeotech.com;
WATSON-LAMPREY, J., Slate Geotechnical Consultants, California, USA,jwatsonlamprey@slategeotech.com; MONTALDO-FALERO, V., WSP
Global, California, USA, valentina.montaldo@wsp.com; STAMATAKOS, J.,Southwest Research Institute, Texas, USA, john.stamatakos@swri.org

Fault displacement models provide surface slip probability distributions andare a key component of Probabilistic Fault Displacement Hazard Analyses(PFDHA). Relatively high residuals between predicted slip and slip observedin historical ruptures reflect large aleatory variability common across themodels. We investigate variables that may modulate the amplitude of coseismic surface slip in order to refine slip predictions to match observations.
Using new empirical models developed from the UCLA Fault Displacement
Hazard Initiative global rupture database, we compare model residuals against
variables thought to modulate surface slip, including depth to bedrock, topographic slope, relief, hypocentral and centroid distance, and number of fault
strands.
Our initial findings show that the strongest source of discrepancy corresponds to portions of ruptures that violate the simple form of the predictive models, particularly where secondary faults are involved, reflecting thechallenge of synthesizing slip observations in zones of complex geometry andmultiple fault traces. This challenge is not easily overcome because models
tend to have simple representations of slip distributions that do not capture
real-world complexities. We propose that model predictions can be throughcareful selection of observational data that satisfy the premise of the model,that is, those which lie along the modelled fault trace(s). Conversely, quantifying fault complexity is a common objective warranting the inclusion ofslip distributed off of a principal trace. For next generation fault displacement
models, resolving accurate slip predictions for individual strands in areasof fault complexity may require careful filtering and selection of data on acase-by-case basis rather than through automated amalgamation approaches,though a hybrid method is possible. Robust interrogation of geological or geometric characteristics that modulate slip systematically at a global scale will
first require refinement or filtering of the input observations to address casesthat violate model assumptions.

Virtual ruptures have become the standard of practice for modeling potential future earthquakes within source zones for probabilistic seismic hazard
analyses (Bommer and Montaldo-Falero, 2020). The benefit of using virtual
ruptures over point sources is the direct availability of distance metrics, suchas rupture (Rrup) and Joyner-Boore (RJB) distances, needed for ground motion
models (GMM). Point sources provide only epicentral (Repi) or hypocentral(Rhyp) distances, and therefore require a conversion (i.e. Scherbaum et al.,2004, EPRI, 2004, 2013, and Thompson and Worden, 2018) in most cases,
which can result in an underestimation of hazard (Bommer and Akkar, 2012).
A significant challenge lies in the absence of standardized algorithms for
producing virtual ruptures, with different code developers following different
algorithms without any validated results as reference. The goal of this study
is to start the validation and comparison process of two virtual rupture generator programs, similar to the study performed for seismic hazard programs(Hale et al., 2018). The two virtual rupture generators (VRG) within this study,referred to as VRG1 and VRG2, have different methods of placing, scaling,
and assigning seismicity to the virtual ruptures. The two VRGs consist of one
developed by Slate Geotechnical Consultants, Inc. and another developed by
WSP Global Inc.
Multiple scenarios are run through the two VRGs and the resulting
distance distributions are compared. Each scenario examines the impact ofindividual parameters, such as spatial distribution and rupture geometry, on
the resulting distance metrics. A small number of scenario comparisons are
discussed in depth as they illustrate differences in methodologies and results,
as well as two scenarios that were used in a simple hazard analysis to show thesensitivity to differences in the VRGs.

poster 132
Time-Domain Seismic Response Retrieval from Ambient
Noise Recorded by the Existing Seismometer of Dams
Based on Interferometric Processing
KURODA, S., National Agriculture and Food Research Organization,
Tsukuba city, Japan, skuroda@affrc.go.jp
The seismometers installed at dams in Japan have recorded numerous seismic events, including significant earthquakes. These records are invaluable foranalyzing the response of dams during seismic activities, providing insights
into their behavior and allowing for the derivation of indices reflecting the
dynamic properties of the structures. Applying the principles of seismic interferometry, we employed its methods to the seismic records of dams, estimating both the properties of seismic wave propagation and the dynamic characteristics of the structures.
In this presentation, we assess the applicability of seismic interferometry to the seismic records of dams, specifically its use with small vibration
records obtained from existing dam seismometers. These records encompass
data from minor earthquakes, where the maximum acceleration is less than 1
cm/s², as well as ambient noise expected to include waveforms of latent microtremors. Through waveform analysis spanning over 10 hours, we demonstrate
the capability to extract time-domain response waveforms from the records ofsmall vibrations resembling those obtained from seismic records of significant
earthquakes (maximum acceleration exceeding 2 cm/s²). Importantly, theseresults highlight the potential for interferometric processing to be consistently
applied, not only to seismic events but also to seemingly trivial records, suchas ambient noise. This aspect has traditionally been overlooked by the existing
seismometers of dams are primarily designed to measure seismic waves withstrong amplitudes. We will also present a case study involving recent significant earthquake events.

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poster 134
The Role of Epistemic Uncertainty Estimations in Seismic
Safety Decision Making and Relation to Levels of Input
Model Simplification
LIOU, I. Y., University of California, Davis, California, USA, iyliou@ucdavis.
edu; ABRAHAMSON, N. A., University of California, Berkeley, California,
USA, abrahamson@berkeley.edu
Epistemic uncertainty and aleatory variability are key concepts in probabilistic seismic hazard analysis (PSHA). The classifiation into either epistemicor aleatory depends on the level of simplificatoin used in the seismic source
characterization and in the ground-motion model. For a selected level ofsimplification, epistemic uncertainty is scientific uncertainty in the modeled
earthquake effects while aleatory variability is the variability from unmodeled
earthquake effects. Models with greater simplification will have larger aleatory
variability and smaller epistemic uncertainty than models with less simplification. Although common PSHA practice is focused on the mean hazard,
which is not affected by the partitioning of epistemic uncertainty and aleatory
variability, the evaluation and quantification of the epistemic uncertainty isoften required for seismic hazard studies for critical infrastructure projects.
Therefore, the level of model simplification should be clearly defined in the
PSHA to allow the users to be able to interpret what the epistemic uncertainty
range represents. A common assumption is that the true hazard will lie within
the epistemic uncertainty range; however, we show that this will generally not
be the case for models with greater simplification and larger aleatory variability, such as ergodic GMMs. The most common use of epistemic uncertainty is to identify the key inputs that can be improved and reduced throughadditional data collection and improvement. Less discussed are the potential
uses of epistemic uncertainty in engineering practice. Though regulations
and codes typically specify that the mean hazard be used for determining thedesign ground motions, the performance of the structure can be evaluatedto higher fractiles of the hazard. To help meet societal needs for earthquake
resilience, the damage state of the structure can be considered in the development of emergency action plans to respond to the expected consequences if
the ground motions for the higher fractiles are correct.

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poster 135
Using 3D Seismic Simulations to Determine Structural
Designs That Best Preserve Structural Integrity of Buildings
in an Earthquake
RONNETT, M., EarthquakeSim, Illinois, USA, earthquakesim@gmail.com
Many parts of the world experience highly destructive earthquakes several
times within a century. Many cities that are at high risk of experiencing suchan earthquake have increased in population. This underscores the need toaddress major structural vulnerabilities in existing and future constructionin order to mitigate the destructive effects of seismic activity on those structures. However, many are hesitant to reinforce these structures due to cost
constraints and determining the optimal structural reinforcement would
require extensive testing. However, using real-world shake-table simulations
on physical models to test the structural integrity of a building is very expensive. The costs associated with the construction of the model are extensive,
often costing millions of dollars. It often takes months just to construct themodel upon which the testing is done.
Virtual earthquake simulations dramatically reduce the time and costrequired to test the physical effects of seismic activity of varying intensity on
different types of structures, thus aiding in the discovery of novel structural
engineering solutions that mitigate the destructive effects of seismic activity
on those structures. By simulating in a 3D virtual physics simulator, one canefficiently determine the optimal structure to best preserve structural integrityof buildings and other structures without the cost of physical materials andshaketables.

Characteristics and Mechanics of Fault Zone Rupture
Processes, from Micro to Macro Scales
Oral Session • Thursday 2 May • 8:00 am PacificConveners: Xiaowei Chen, Texas A&M University (xiaowei.
chen@tamu.edu); Yifang Cheng, University of California,
Berkeley (chengyif@berkeley.edu); Zhe Jia, Universityof California, San Diego (z5jia@ucsd.edu); Junle Jiang,
University of Oklahoma (jiang@ou.edu)
Temporally-Varying Creep Behavior on the East Anatolian
Fault and the End of the 2023 Pazarçik Rupture
FUNNING, G. J., University of California, Riverside, California, USA,
gareth@ucr.edu; HOFSTETTER, C., University of California, Riverside,
California, USA, chofs002@ucr.edu; ÖZARPACI, S., Yıldız Technical
University, Istanbul, Turkey, ozarpaci@yildiz.edu.tr
The 80 km-long Pütürge segment of the East Anatolian fault connects the endof the rupture zone of the February 2023 M7.8 Pazarçik earthquake in the SW
to Lake Hazar in the NE. The NW half of the segment ruptured at depth in theJanuary 2020 M6.7 Sivrice earthquake, but less is understood about the behavior of the SW half. Given the lack of a major structural barrier to the continuation of the Pazarçik rupture, we consider the possibility that frictional
conditions—specifically a transition from stick-slip to aseismic creep—could
explain why that rupture ended where it did.
To assess this hypothesis, we process InSAR data from ascending anddescending tracks of the Sentinel-1 satellites that cover the Pütürge segment,from three time periods—before, between and after the two earthquakes—
using the ISCE and MintPy software. We take short, fault-perpendicularprofiles through the velocities and time series we produce to investigate possible creep behavior. We find that: 1) the Pütürge segment was creeping in the
period 2014-2020, before the Sivrice earthquake, at rates that peak at ~6 mm/
yr at its NE end, and decrease along-strike to effectively zero at its SW end;2) the post-Sivrice earthquake deformation includes ~10 cm of surface creep
between February and July 2020 along the Sivrice rupture zone, followed bya M~5.8 creep event on the fault immediately to the SW of that zone; and3) the post-Pazarçik earthquake deformation (~10 cm of surface creep in 8
months) is concentrated along the SW-most section of the Pütürge segment,in the zone where there had been little creep before or after the Sivrice earthquake. This continuous and complex shallow creep along the Pütürge segment
suggests that creep did play a role in ending the Pazarçik rupture, and alsothat the limited postseismic creep seen after that event is a result of the releaseof the majority of the stored elastic strain along the segment after the Sivrice
earthquake.

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Modeling Rupture Propagation Into Creeping Faults by
Thermal Pressurization
STEPHENSON, O., California Institute of Technology, California, USA, oliver.
stephenson@caltech.edu; VESCU, V., California Institute of Technology,
California, USA, vvescu@caltech.edu; LAPUSTA, N., California Institute ofTechnology, California, USA, lapusta@caltech.edu
Different sections of faults, like the San Andreas (SAF), accommodate stressvia stick-slip under velocity-weakening friction or through gradual creep ina velocity-strengthening regime. When a rupture reaches a region of slow
slip, thermal pressurization of pore fluids can enable rapid weakening anddynamic failure of the creeping zone (Noda and Lapusta, Nature, 2013). We
explore whether a theoretical Mw 7 earthquake, which propagates towards
the creeping section, could generate enough thermal pressurization to rupture through the creeping section, building upon recent observations that thecreeping section of the SAF may have experienced large seismic slip (Coffey
et al., Geology, 2022). At the same time, the 2004 Mw 6 Parkfield earthquake
did not significantly propagate into the creeping section. The highly simplified
model of the simulated fault consists of locked and creeping segments, depthaveraged to consider only variations with its length and embedded within a
2-D linearly elastic isotropic medium. The fault is governed by a logarithmic
rate-and-state friction law with thermal pressurization of pore fluids due toshear heating, with the diffusion of heat and fluids from the fault. We vary
three thermal pressurization parameters (the coupling coefficient between
temperature and pore pressure change, hydraulic diffusivity, and half-width of
the actively shearing layer) and the effect of the off-fault inelasticity to find the
combinations that lead to dynamic rupture through the creeping region whenthe event size is large enough. Our preliminary results indicate that there areindeed plausible parameter combinations for which Mw 6 events arrest, but
Mw 7 events dynamically rupture the creeping segment. We will report on ourcurrent exploration of the fuller parameter space and ways of explaining thesimulation results with theoretical considerations.
Across-Slab Propagation and Low Stress Drops of Deep
Earthquakes in the Kuril Subduction Zone
TURNER, A. R., University of Texas at Austin, Texas, USA, alice.turner@jsg.
utexas.edu; FERREIRA, A. M. G., University College London, London, United
Kingdom, a.ferreira@ucl.ac.uk; BRANTUT, N., University College London,
London, United Kingdom, n.brantut@ucl.ac.uk; FACCENDA, M., Università
di Padova, Padova, Italy, manuele.faccenda@gmail.com; KENDALL, E., GFZ
Potsdam, Potsdam, Germany, elodie.kendall.14@ucl.ac.uk; BERBELLIN, A.,
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, Bologna,
Italy, andrea.berbellini@ingv.it
Deep earthquakes occur when subducting slabs dive into the mantle at depthsof up to 700 km, where pressure is up to 100 times greater than in the crust.
These high pressures and temperatures should prevent the occurrence ofearthquakes, and it is still unclear how deep earthquakes start or propagate
under these conditions. In our recently published study, we inverted seismic waveforms using a second-degree moments approach for the spatial
dimensions, duration and stress drop of eight deep-focus earthquakes (Mw
6.7—7.7) in the Kuril subduction zone. We find stress drops of 1—10 MPa,
and after adjusting for changes in rigidity with depth, we find that the spatial dimensions and durations of the deep earthquakes are similar to crustal
earthquakes. We also measured values of the radiated efficiency (the ratio ofradiated energy over available strain energy). For these earthquakes, radiatedefficiency >1 is observed, suggesting that undershooting is prevalent in deep
earthquakes, consistent with laboratory-derived weakening mechanisms.
When we compared the earthquake spatial extents to thermal subduction
models, we found these deep earthquakes were confined to the coolest partof the slab, with temperatures T<1000 °C, similar to shallow events. Hence,
despite different triggering mechanisms, the same physics seems to control the
rupture propagation of shallow and deep earthquakes.
Fault Zone Material Heterogeneities May Trigger
Repeating Earthquakes in Kanto, JapanHUANG, Y., University of Michigan, Michigan, USA, yiheh@umich.edu;
IDE, S., University of Tokyo, Tokyo, Japan, ide@eps.s.u-tokyo.ac.jp; KATO,
A., University of Tokyo, Tokyo, Japan, akato@eri.u-tokyo.ac.jp; YOSHIDA, K.,
Tohoku University, Sendai, Japan, keisuke.yoshida.d7@tohoku.ac.jp; JIANG,
C., Australian National University, Canberra, Australia, chengxin.jiang1@
anu.edu.au
Fault zones feature small-scale material heterogeneities that strongly affectwhere earthquake ruptures initiate and terminate. In this presentation, weshow that fault zones that repeatedly rupture during earthquakes in Kanto,www.srl-online.org•

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Japan also exhibit anomalous material properties. The Kanto region in Japanis situated in a special tectonic setting where the Philippine Sea plate is “sandwiched” between the Okhotsk and Pacific plates, generating small to moderate-magnitude earthquakes that repeat within days to years along the plateinterface between the Pacific plate and the Philippine Sea plate at 60-70 km.
We apply a waveform cross-correlation approach to measure the in-situ Vp/
Vs ratios of earthquake patches. We find anomalously low Vp/Vs ratios (~1.5)in these earthquake source regions, suggesting the fault zone rocks may havedistinct mineral compositions, e.g., high concentration of alpha-quartz. We
also estimate the stress drop of M>3.4 earthquakes using the spectral ratio
method, leading to a median stress drop of 4.6 MPa. The typical stress drop
values suggest the effective normal stress is much lower than the lithostaticpressure and the fault zone may also contain abundant fluid. Thus, a combination of different mineral compositions and richness in fluid can promotevelocity-weakening behaviors and generate repeating earthquakes at 60-70
km. Our earthquake cycle simulations based on the frictional parameters of
wet quartz can reproduce M~4 earthquakes that alternate between full andpartial ruptures every 2-5 years, which are similar to the recurrence intervalsof M~4 earthquakes at 60-70 km.
The Alto Tiberina Near Fault Observatory: A State of Art
Monitoring Infrastructure for Studying Earthquakes Faults
and Preparatory Phases
CHIARALUCE, L., Istituto Nazionale di Geofisica e Vulcanologia, Roma,
Italy, lauro.chiaraluce@ingv.it
Near Fault Observatories (NFO) are research infrastructures developed in
the framework of the European Plate Observing System (EPOS), towards apan-European organization for Solid Earth Sciences providing raw data andscientific products, collected by a suite of geophysical communities, based on
the FAIR principles. S
NFOs consist of advanced networks of multi-parametric sensors continuously monitoring the chemical and physical processes related to the underlying Earth instabilities governing active faults evolution and the genesis ofearthquakes. Such a methodological approach, currently applicable only at
local scale, is based on extremely dense networks and less common instruments located at surface and within shallow boreholes within few kilometersfrom active faults where background activity is high and large earthquakes
are expected.
The NFO community is composed by 6 permanent members plus 2
observers placed in different tectonic regimes. The Alto Tiberina fault (ATF)
in the Northern Apennines of Italy is the target of the Alto Tiberina Near
Fault Observatory (TABOO-NFO); a 60-km long low-angle normal fault(dip <20°) able to generate a M7 earthquake not present in the historicalcatalogues. Microseismicity is released at a consistently high rate on the ATF
plane, including repeating earthquakes that together with a steep gradient incrustal velocities measured by GNSS and transient surface motion, lasting forfew months and coinciding with seismic swarms, support the hypothesis that
portions of the ATF are creeping aseismically.
Recent studies document that any given patch of a fault can creep, nucleate slow earthquakes and host large earthquakes (e.g., Iquique, Tohoku andParkfield), encouraging a revolution in our way of thinking about how faults
accommodate slip. However, the interaction between creep, slow and regularearthquakes is still poorly documented by observations.
TABOO is currently collecting unique data needed to address suchquestions with significant implications for seismic hazard and risk assessment
globally.
Dynamic Rupture Simulations on the Alpine Fault, New
Zealand: Investigating the Role of Fault Geometry on
Rupture Size and Behavior Over Multiple Earthquake
CyclesLOZOS, J., California State University, Northridge, California, USA, julian.
lozos@csun.edu; WARREN-SMITH, E., GNS Science, Lower Hutt, New
Zealand, e.warren-smith@gns.cri.nz; TOWNEND, J., Victoria University of
Wellington, Wellington, New Zealand, john.townend@vuw.ac.nz
The right-lateral transpressional Alpine Fault is the primary plate boundary fault on the South Island of New Zealand. At a broad scale, its onshore
surface trace between Milford Sound in the southwest, and the branching
Marlborough Fault System in the northeast consists of two planar sections
connected by a major geometrical boundary at Martyr River. This boundaryis characterized by both a dip change of as much as 40° over an along-strike
length of only ~5 km. Several previous studies suggest that changes in dip
along a strike-slip fault can affect rupture dynamics. It is therefore possible

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that this geometrical feature affects conditional earthquake segmentation
behavior on the Alpine Fault, as documented by the extensive paleoseismic
record.
We use the 3D finite element method to simulate multiple cycles ofdynamic ruptures on the southwestern ~320 km of the Alpine Fault. We
embed the faults in a 1D velocity structure and impose heterogeneous initialtractions computed using seismologically estimated local principal stress orientations and magnitudes computed using a critically-stressed crust model.
We simulate the coseismic period using dynamic rupture simulations, thenaccount for the interseismic period by incrementing shear stress based on a set
time between events. For each dynamic rupture simulation, we compare themodeled rupture lengths and surface slip values to geologic and paleoseismic
studies to ensure that we are producing physically-plausible simulations consistent with observations. We find that the dip change at the segment boundary is not inherently a barrier to rupture within single events, but that stresschanges associated with rupture through this boundary in one earthquake cansometimes lead to segmentation in the next one. Our results suggest that rupture hazard on the Alpine Fault may depend both on the slip distribution ofand the timing since the previous large earthquake. This also implies that bothfault geometry in and of itself and long-term stress patterns resulting fromthat geometry are important considerations for hazard assessment on othergeometrically-complex faults.
Deformation Partitioning, Directivity Effects, and StressDrop of Seismicity Along the Main Marmara Fault Offshore
Istanbul/Türkiye in the Light of an Overdue M7+
Earthquake
BOHNHOFF, M., GFZ Potsdam, Potsdam, Germany, bohnhoff@gfzpotsdam.de; CHENG, X., GFZ Potsdam, Potsdam, Germany, xiang@gfzpotsdam.de; MARTINEZ-GARZON, P., GFZ Potsdam, Potsdam, Germany,
patricia@gfz-potsdam.de; BECKER, D., GFZ Potsdam, Potsdam, Germany,
dbecker@gfz-potsdam.de; KWIATEK, G., GFZ Potsdam, Potsdam, Germany,
kwiatek@gfz-potsdam.de; COTTON, F., GFZ Potsdam, Potsdam, Germany,
fcotton@gfz-potsdam.de
The Marmara section of the North Anatolian Fault zone (NAFZ) in northwestern Türkiye is late in its seismic cycle and expected to produce a large M>7
earthquake in direct vicinity to the Istanbul metropolitan region. Monitoring
the NAFZ below the Sea of Marmara is a challenge due to absence of near-fault
islands except for its eastern section. High resolution seismic monitoring has
been achieved through setting up the borehole-based GONAF (GeophysicalObservatory at the North Anatolian Fault) infrastructure monitoring seismicity as well as slow deformation transients.
Analyzing the occurrence of repeating earthquakes as indicator forseismic creep we identify several repeater families below the eastern and –to a lesser extent- also below the central Sea of Marmara. We conclude ona systematic transition of deformation along the Main Marmara Fault fromdominantly creeping in the west , an intermittent state of locked-creeping
deformation at its central part, and the fully locked Princess Islands segment immediately south of Istanbul. Small, but statistically significant, spatialstress-drop variations are observed among some segments of the fault. Lower
average stress-drop values are observed in zones surrounding earthquake
repeaters, which may imply a weaker fault along the creeping region. Recent
M>5 earthquakes along the Main Marmara Fault did not exhibit significant
changes in the mean stress-drop, suggesting no reduction of fault stress levelor fault strength due to the occurrence of these events. To improve rupture
scenarios for the pending large Marmara earthquake we estimate the rupture
directivities for 30 M>3.5 earthquakes along the Main Marmara Fault. We
constrained earthquake moment tensors for these events providing evidence
for their potential fault planes and observe a predominant eastward rupture
direction for half of the events, most of them located along the western andcentral parts of the Main Marmara Fault. This suggest that about 50% of theanalyzed events displayed a preferential orientation of energy release towards
Istanbul, hence probably increasing the ground shaking in a major event.
Insight Into Depth Variations in Effective Stress and Fault
Strength From Geodynamic-Seismic Cycle and Earthquake
Dynamic Rupture Modeling
MADDEN, E. H., San Jose State University, California, USA, elizabeth.
madden@sjsu.edu; GABRIEL, A. A., University of California, San Diego,
California, USA, liese.gabriel@gmail.com; ULRICH, T., Ludwig Maximilian
University of Munich, Munich, Germany, thomas.ulrich@lmu.de; VAN
DINTHER, Y., Utrecht University, Utrecht, Netherlands, ylonavandinther@

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gmail.com; VAN ZELST, I., Technische Universität Berlin, Berlin, Germany,
iris.vanzelst@dlr.de
The local stress regime and fault strength together exert first order control on
fault mechanics and earthquake rupture dynamics. However, these characteristics remain elusive, especially at the level of detail desirable for initiating
numerical simulations of large earthquakes on complex fault networks, which
now are computationally possible. Linking between a geodynamic-seismic
cycling model and a dynamic earthquake rupture model suggests that theeffective stress field near a fault and the static and dynamic fault strength vary
non-linearly with depth and are materially dependent. We present two model
scenarios that contrast earthquakes resulting from (1) these heterogeneous
initial conditions and (2) more commonly used, simpler initial conditions.
Although the maximum fault strength is similar in both scenarios, the heterogeneous initial conditions in (1) result in larger fault slip, but lower average
dynamic stress drop and lower rupture velocity. In addition, we observe thatseismic waves traveling through complex materials around the fault in (1), as
opposed to the homogeneous material in (2), influence earthquake rupturestyle and shallow slip accumulation. In both scenarios, the pore fluid pressure(Pf) increases linearly with depth. We further share how fault mechanics andearthquake dynamics are influenced by a simple change in the linear variationof Pf from sublithostatic to lithostatic, in which Pf is slightly less than, but constantly offset from, the lithostatic stress. If Pf follows a sublithostatic gradient,then pre-earthquake effective normal stress increases with depth. If Pf follows
the lithostatic gradient, then normal stress is relatively constant with depth. As
a result, a lithostatic Pf gradient moves peak slip and peak slip rate up-dip, andproduces a more constant stress drop across the megathrust. These insights
underscore the need to better understand initial earthquake conditions froma variety of sources, including collaborative modeling, in order to advance ourunderstanding of earthquake initial conditions, fault strength and earthquake
behavior.
Deep Slip Occurs Prior to Surface Creep Events on the San
Andreas Fault
GITTINS, D. B., University of Colorado Boulder, Colorado, USA, daniel.
gittins@colorado.edu; HAWTHORNE, J. C., University of Oxford, Oxford,
United Kingdom, jessica.hawthorne@earth.ox.ac.uk
Scientists have used creepmeters to observe the surface expression of creep
events along the San Andreas Fault since the 1960s. These creep events represent episodic slip bursts that have a duration of 1–2 days with a small amountof steady background creep between events (e.g., Gittins & Hawthorne, 2022;
Gladwin et al., 1994; Nason et al., 1974; Schulz, 1989). During a creep event,the fault typically slips a few millimeters over several hours to days, with events
separated by a few weeks to months. At the surface, creep events accommodate >50% of slip along the San Andreas Fault (Gittins & Hawthorne, 2022),
but the evolution of slip at depth is less well constrained because of a lack ofdepth resolution provided by the current creepmeter design.
To observe deeper—down to 10 km—we use strainmeters. This study
investigates the deep slip associated with surface recordings of creep events.
We analyze strain observations in the 10 hrs before and during creep events atthe northern end of the Central San Andreas Fault. We identify 71 offsets inthe strain time series created by short bursts of slip within longer creep events.
Then, we perform a grid search to determine the location, depth, and magnitude of these slip bursts by modeling rectangular slip patches in a homogeneous elastic half-space. We find that these slip bursts occur up to 7 km
from the recorded location of surface rupture associated with the longer creep
event, as observed by creepmeters. 42–55% of the slip bursts are likely to occur
below 4 km depth and have moments equivalent to Mw 3.2–4.1 earthquakes.
Our observations suggest that creep events are not always simply shallow, triggered phenomena. They originate spontaneously from a range of locations,
including depths that are comparable to the depths of nearby earthquakes.
Creep events also show complex propagation histories, triggering several slip
locations as they propagate horizontally. These strain offsets within creep
events show a nucleation and propagation history that needs further exploration, perhaps with a more optimal instrument configuration and design.
Simulating the Formation and Evolution of Complex
Fracture Patterns Arising From Shallow Strike-Slip Faulting
With Finite and Discrete Element Analyses
BADEN, C. W., U.S. Geological Survey, California, USA, cbaden@usgs.gov;
NEVITT, J. M., U.S. Geological Survey, California, USA, jnevitt@usgs.gov;
GARCIA, F. E., University of Michigan, California, USA, fegarcia@umich.edu
Shallow strike-slip faulting generates complex distributions of deformationthat range from networks of en-echelon fractures and contractional and exten-

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Seismological Research Letterssional structures to through-going shear zones expressed at Earth’s surface.
Distributed inelastic deformation accommodated by these features affects theamount of fault slip that reaches Earth’s surface, thereby biasing slip estimatesused for probabilistic seismic hazard and fault displacement hazard analyses.
These well-documented fractures and shear structures have been studied inlaboratory, field, and numerical analyses, but field interpretations are typicallylimited to 2D perspectives, and numerical investigations often cannot resolve
discrete, localized shear structures.
In this investigation, we use 3D finite element method (FEM) and 3D
discrete element method (DEM) models to examine how changes in shallow
fault zone structure, material properties, and strike-slip loading conditions
affect the predicted distributions of fault slip and strain. We use the uniqueadvantages of FEM models (e.g., computational efficiency and straight-forward material parameterizations) and DEM models (e.g., improved resolving
power in capturing discrete shear-zone structure development and evolution) to understand how material properties of the shallow crust, such as theinternal angle of friction, cohesion, and dilatancy, affect the shallow fault zone
fracture patterns in strike-slip faulting regimes. Our models suggest that DEM
particle-packing densities and inferred material dilatancy strongly influence
the complexity of shallow shear zones, where branching shear structures thatdevelop within dilatant materials contrast with subvertical, planar structuresthat form in non-dilatant materials. In these models, the evolution of material dilatancy with increasing fault slip also influences the expression of fault
zone deformation as fault slip continues to accrue. We compare our resultswith data-constrained field sites to understand how these models may informsurface displacement and deformation distribution predictions surrounding
strike-slip faults.

Characteristics and Mechanics of Fault Zone Rupture
Processes, from Micro to Macro Scales [Poster Session]
Poster Session • Thursday 2 May
Conveners: Xiaowei Chen, Texas A&M University (xiaowei.
chen@tamu.edu); Yifang Cheng, University of California,
Berkeley (chengyif@berkeley.edu); Zhe Jia, Universityof California, San Diego (z5jia@ucsd.edu); Junle Jiang,
University of Oklahoma (jiang@ou.edu)
poster 74
Constraining 3D Fault Geometry With a Data-Driven
Approach at the San Andreas—Calaveras Fault Junction
ALONGI, T., U.S. Geological Survey, California, USA, talongi@usgs.gov;
ELLIOTT, A., U.S. Geological Survey, California, USA, ajelliott@usgs.gov;
SKOUMAL, R., U.S. Geological Survey, California, USA, rskoumal@usgs.
gov; HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@usgs.
gov; HARRIS, R. A., U.S. Geological Survey, California, USA, harris@usgs.
gov; SHELLY, D., U.S. Geological Survey, Colorado, USA, dshelly@usgs.gov
Accurately characterizing three-dimensional (3D) fault geometry is crucial
for understanding earthquake behavior and refining seismic hazard models.
However, detailed subsurface fault structure is often unknown, particularly
in complex fault networks. This study presents a data-driven approach toreconstruct 3D fault geometries by leveraging mapped surface traces, double-difference relocated earthquake hypocenters, and newly computed andimproved focal mechanisms (Shelly et al., 2022; Skoumal et al., 2022). Our
method integrates established machine learning techniques for event clustering to associate nearby events together and assigning events to mapped faults,
offering improvements in resolving intricate fault networks.
Preliminary synthetic tests demonstrate that incorporating focal mechanism information significantly improves the accuracy of hypocenter clustering in anastomosing fault systems. Applying this methodology to the wellstudied San Andreas-Calaveras fault junction reveals an unexpected findingthat continuous quasi-linear trends of seismicity are erroneously subdivided
by the clustering algorithm. We propose a refinement that combines adjacentclusters with similar orientations, resulting in a more accurate depiction of
the fault network.
This research provides a low-user-input workflow for reconstructing
multiple fault geometries at depth from readily available data. By analyzing thereconstructed fault network, we shed light on the complex structures involvedin accommodating the partitioning of slip at San Andreas-Calaveras fault
junction and highlight the potential differences in fault network morphology
between locked and creeping sections of the San Andreas Fault. Our find-www.srl-online.org•

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ings will contribute to a more comprehensive understanding of earthquake
dynamics and improve constrains on fault connectivity for rupture forecasts.
poster 75
Unveiling Shallow Earthquake Ruptures in the Ryukyu
Area: A Comprehensive Study Through Bp Imaging andRegional Cmt Catalog
JIAN, P., National Taiwan University, Taipei, Taiwan, prjian@ntu.edu.tw;
TSENG, T., National Taiwan University, Taipei, Taiwan, tailintseng@ntu.
edu.tw; HSU, Y., Academia Sinica, Taipei, Taiwan, yaru@earth.sinica.edu.
tw; YANG, H., National Taiwan University, Taipei, Taiwan, hsinyingtw@
gmail.com; TANG, C., Tohoku University, Sendai, Japan, tang.chi-hsien.b8@
tohoku.ac.jp
In the last few centuries, the absence of significant interplate or tsunamigenic
earthquakes has led to ambiguous conclusions regarding the coupling rate in
the Ryukyu subduction zone. Estimations of large slip-deficit rates from GPSdata and the discovery of slow earthquakes suggest both strong and weak coupling rates. Despite these geophysical observations, the seismic database forsmall to large earthquakes remains incomplete due to the limited coverageof seismic networks. Discrepancies in focal depths between the JMA event
catalog, GCMT, and NIED CMT solutions further challenge understanding seismogenic structures. To address this, our study aims to enhance the
CMT catalog covering small to large earthquakes (M≥4) from 2000 to 2022.
We include three broadband networks to ensure better azimuth coverage:
BATS (Broadband Array in Taiwan for Seismology), F-net from NIED, andFJ-network (Fujian Earthquake Agency). The AutoBATS MT algorithm is
adapted to facilitate the necessary epicenter scanning for CMT inversion. For
the western Ryukyu area, our inversion results for larger earthquakes are overall consistent with the GCMT solutions. For earthquakes larger than 6.0, we
also apply Multiple signal classification (MUSIC) back-projection imaging todetermine the causative fault planes, rupture extends, and durations. The rupture properties of major earthquakes and the comprehensive regional CMT
catalog may offer additional insights into future studies on coupling rates.
poster 76
Probing Transient Rheology and Spatial Heterogeneity of
Faults Using Repeating Earthquakes and Deformation DataJIANG, J., University of Oklahoma, Oklahoma, USA, jiang@ou.edu; TAIRA,
T., University of California, Berkeley, California, USA, taira@berkeley.edu
Fault zone rheology and heterogeneity have fundamental controls on earthquakes and fault behavior. Constraining these intrinsic fault properties
requires high-resolution geophysical observations and faces enduring challenges due to a lack of in-situ measurements and validations. Here we use
continuous seismic and geodetic observations following the 2004 Mw6.0
Parkfield earthquake of the San Andreas fault to image rapidly evolving transient faulting processes and thereby constrain fault zone rheology and heterogeneity. For seismic observables, we compare several characteristicallyrepeating earthquake (CRE) catalogs to obtain refined event identificationand estimate the in-situ fault slip history at depth assuming a model of single
asperity surrounded by creep and a common scaling relation of recurrence
interval and fault slip. For geodetic observables, we combine high-rate GNSS
(Global Navigation Satellite System) and InSAR time series (Interferometric
Synthetic Aperture Radar) displacement data. To optimize the disparate andyet complimentary spatiotemporal resolutions of GNSS and InSAR, we design
a new two-step strategy to retain the GNSS-based high temporal resolution offinite-fault afterslip models while incrementally ingesting additional spatialconstraints from less-frequently sampled, high-density InSAR deformation
fields. We compare and reconcile the two independent approaches, based on
the CRE scaling and geodetic finite-fault slip models, to estimate spatiallyand temporally-varying postseismic fault slip history in the seismogenic crust.
The derived or inferred fault slip histories are used to estimate the rheologicallaws and parameters for fault zones based on theoretical models. The alongdip and lateral variations of fault properties, along with discrepancies in seismic and geodetic estimates, help us further interpret the heterogeneous stateof fault zones.

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Number 2B•

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poster 77
Illuminating the Jericho Fault from A New Local Seismic
Network
KLINGER, A. G., Geological Survey of Israel, Jerusalem, Israel, adam_klinger@hotmail.com; KURZON, I., Geological Survey of Israel, Jerusalem,
Israel, ittaik@gsi.gov.il
The Jericho Fault is an active fault segment located north of the Dead Sea
Lake. It is considered the source of significantly large earthquakes in theregion, such as the 6.25 magnitude earthquake in 1927[AS1] and is classified
as a locked fault. Although a significant amount of work has been reported on
the Jericho Fault, several key questions remain unanswered. Firstly, can we
provide direct seismological evidence of the fault from earthquakes? Whatis the fault width in seismogenic depths? Is the fault completely seismicallyquiet towards low magnitudes (i.e., below 1)? Answering these questions will
improve seismic hazard estimates and provide information on micro-seismicity along locked faults.
From one year of data (06/22 – 06/23) we find 63 seismic events in therange of -0.54 < 0.84, that are below the detection threshold of the permanentregional network. We support the observation of a locked fault towards the
microseismic range as most events lie off-fault. Additionally, microseismicity
there does not follow a Gutenberg-Richter power-law distribution. Therefore,
it questions the validity of using power-law distributions to estimate the maximum magnitude. The Jericho Fault releases significantly less seismic moment
than the Anza gap (a seismically quiescent segment of the San Jacinto Fault),
indicating a particularly quiet fault. The whole fault appears to be creepingfrom ~0-20 Km aseismically with tiny release of seismic energy, supporting
observations from geodetic studies. More strain energy could be accumulating, and release as relatively large earthquakes compared to fault segments that
release seismic moment more frequently. Secondly, we analyse trapped waves,which reveals information about the damaged section of the Jericho Fault
zone. We observe trapped waves across our local array and to our knowledge
this is the first direct seismological evidence from earthquakes of a coherent
zone of damaged rock that trends northwards from the Dead Sea Lake.
poster 78
Fault Network Geometry’s Control on Earthquake Rupture
Behavior
LEE, J., Brown University, Rhode Island, USA, jaeseok_lee@brown.edu;
TSAI, V. C., Brown University, Rhode Island, USA, victor_tsai@brown.edu;
HIRTH, G., Brown University, Rhode Island, USA, greg_hirth@brown.edu;
TRUGMAN, D. T., University of Nevada, Reno, Nevada, USA, dtrugman@
unr.edu; CHATTERJEE, A., University of Nevada, Reno, Nevada, USA,achatterjee@unr.edu
While fault slip behavior has been predominantly attributed to local fault
plane properties such as frictional parameters and roughness, the role of larger
scale fault geometry has remained relatively unexplored. Emerging observations highlight the importance of fault system geometry in the mechanics
governing earthquake rupture processes. Drawing from compiled observations, we study how the geometrical complexities of fault networks impact
various aspects of fault slip behavior, including how these complexities affectfault creep and earthquake source spectra. We quantify fault network complexity by measuring the degree of surface fault trace misalignment and the
local variability of earthquake focal mechanisms. We investigate the relationships between metrics of fault complexity and surface creep rates, earthquake
corner frequencies, and earthquake moment rate function complexity, demonstrating that complex fault networks suppress fault creep, lead to higher
earthquake corner frequencies, and introduce complexities in the moment
rate functions. We interpret these observations as a consequence of geometric locking, which inhibits fault creep, and the elastic loading and unloadingof discrete fault structures, which leads to enhanced high-frequency seismic
radiation. Our study is based on a dataset of diverse geophysical parameters
gathered from California, supplemented by measurements from Japan, central
Italy, and worldwide. The observations from independent sources, spanning
different scales and geological regions, consistently support our hypothesisthat complex fault systems contribute significantly to complex earthquake
ruptures. Our findings demonstrate the potential for a new framework inwhich earthquake rupture behavior is governed primarily by fault network
geometry.

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poster 79
Posterior Exploration of Bayesian Kinematic Finite-Fault
Earthquake Source Models
VITERI LOPEZ, J., University of Oklahoma, Oklahoma, USA, jose.a.viteri.
lopez-1@ou.edu; JIANG, J., University of Oklahoma, Oklahoma, USA, jiang@ou.eduThe Bayesian inversion framework for earthquake source imaging yields anensemble of posterior models, as opposed to conventional inversion methods that produce individual optimal solutions. Yet, using Bayesian posterior
solutions for predicting stress and displacement fields, and their associateduncertainty has been under-explored. Here, we quantitatively characterize
the uncertainty structure and predictive observables of kinematic finite-fault
earthquake rupture models from published Bayesian inversions for several
large megathrust earthquakes, including 2011 Mw9.0 Tohoku, 2014 Mw8.1
Iquique, 2015 Mw8.3 Illapel, 2016 Mw7.8 Pedernales, and 2015 Mw7.8 Gorkha.
These events can be grouped into distinct types according to slip patterns:
tsunamigenic (Tohoku, Illapel), no trench-breaking (Iquique, Pedernales, andGorkha), and multi-patch (Illapel) rupture scenarios. Employing homogeneous and layered elastic structures, we compute and compare surface deformation and normal and shear stress on the fault plane for each event. In allcases, surface deformation manifests itself in a transitional way with uplift
occurring closer to the trench and smaller subsidence effects in the downdip direction. Compact large vertical seafloor deformation is prominent forevents with tsunamigenic slip. Distributions of significant rupture observables
are usually confined to the area directly above the prescribed fault geometries.
Stress change appears to be event-dependent due to variable rupture patterns
across events. We will leverage posterior model ensembles to rigorously evaluate error propagation in surface displacement and stress change, address how
error varies as function of distance from the trench, and evaluate scale-dependent correlation between model parameters. Future work will include computing elastodynamic ground motion and stress changes during these events.
poster 80
Comparing Fault Zones that Host Induced and Tectonic
Earthquakes in Oklahoma and California
NEO, J., University of Michigan, Michigan, USA, neoj@umich.edu; HUANG,
Y., University of Michigan, Michigan, USA, yiheh@umich.edu; GABLE, S.,
University of Michigan, Michigan, USA, gablesyd@umich.edu
We have developed a new approach to detect and image fault zone structures through the azimuthal variation of earthquake spectra. The spatial
distribution of earthquake clusters where the high-frequency amplification
is observed could shed light on the characteristics of the fault damage zone.
Our previous studies show that the Ridgecrest fault zone structure is more
coherent along strike compared to that of the Parkfield region. Our results
also demonstrate the fault zone structure can extend up to ~10 km given theobservation of high-frequency energy from earthquake clusters. Our method
has only been applied in tectonic regions thus far, but understanding the fault
zone structure in induced seismicity regions is also important as it can provide
pathways for fluid propagation. Hence, we plan to investigate induced earthquakes in Oklahoma and more tectonic earthquakes in Southern California.
For example, possible candidates include the Fairview, Oklahoma region comprising near-vertical narrow strike-slip faults and the San Jacinto fault zone,
which comprises three fault strands with different structure. We will use thestacked P-wave velocity spectra of M<3 earthquake clusters from broadband
stations to identify any azimuthal variation in high-frequency energy. We
aim to apply our method to search for fault damage zone structures in thoseregions in order to enhance our understanding of the co-evolution of fault
zones and earthquake cycles.
poster 81
Systematic Measurements of Rupture Directivity for
Small-to-Moderate Earthquakes in California
PATTON, A., University of Nevada, Reno, Nevada, USA, ampatton@nevada.
unr.edu; TRUGMAN, D. T., University of Nevada, Reno, Nevada, USA,
dtrugman@unr.edu
Rupture directivity is an important but poorly characterized earthquake
source property that can have a direct effect on the azimuthal distributionof ground motions and hence earthquake hazard. Directivity has been measured for many moderate-to-large earthquakes in California, but systematic
measurements for smaller earthquakes are needed to obtain a more complete
picture of the underlying rupture and fault mechanisms that control directivity and amplified ground motion. Developed by Ross & Ben-Zion (2016)
and expanded by Calderoni et al. (2023), the directivity index is a measure of

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Seismological Research Lettersazimuthal difference in the spectral ratio between a target event and a nearby
empirical Green’s function (EGF) event, averaged over a frequency range spanning the target and EGF corner frequencies. Here, we generalize this approachby calculating the azimuthal distribution of the directivity index, which allows
for inference of dominant rupture direction in cases where the rupture planeis unknown a priori. We apply this technique to assess spatiotemporal patterns in rupture directivity characteristics for small earthquakes throughout
California that are well-recorded by recent network expansions in the state.
We use synthetic tests to establish the quantitative relation between directivity index measurements and physical rupture properties, and also develop
a system for ranking the quality of each EGF or combination of EGFs usedin the measurements to improve the robustness of the results. Preliminary
results show success for small-to-moderate strike-slip earthquakes in the San
Jacinto Fault Zone, and we aim to expand that work to include M3+ eventsin throughout the state, as well as test the method on earthquakes in dip-slip
regimes.
poster 82
Lithospheric Structure of the Hispaniola and Puerto Rico/
Virgin Islands Microplates Using Teleseismic and Local Data
ROSERO RUEDA, S., Baylor University, Texas, USA, sandra_rosero1@
baylor.edu; PULLIAM, J., Baylor University, Texas, USA, jay_pulliam@baylor.edu; HUERFANO, V., University of Puerto Rico, Puerto Rico, USA,
victor@prsnmail.uprm.edu; POLANCO RIVERA, E., Universidad Autónoma
de Santo Domingo, Santo Domingo, Dominican Republic, eugenio.fisico@gmail.com; LEONEL, J., Universidad Autónoma de Santo Domingo, Santo
Domingo, Dominican Republic, jleonel78@uasd.edu.do
The complex tectonics and high seismic activity of the Caribbean-North
American plate boundary region is well documented. Hispaniola, in particular, has a history of devastating earthquakes with numerous aftershocks, but
a better understanding of regional tectonics, as well as reliable estimates ofseismic and tsunami hazards, await the development of a detailed 3D seismic velocity model and a comprehensive earthquake catalog with accurate
locations. Moreover, the region experiences earthquakes to depths of ~200km beneath eastern Hispaniola and the Mona Passage, the causes of which
are not well understood. Various authors suggest that these earthquakes may
result from the interactions between converging tectonic plates, or due to thesubduction of the North American plate’s slab edge beneath Puerto Rico, orfrom activity along a subduction transform edge propagator fault, but thesehypotheses require further investigation.
To better constrain regional seismicity and advance our understandingof lithospheric structure in the region, this study leverages data recorded by
local seismic networks to perform 3D seismic travel time tomography. Seismic
stations have monitored the region comprehensively for the last decade, so
the recorded data enable the development of a more detailed and accurate
3D model than has been possible previously. We measured ~5,609 teleseismic P-wave travel times from 189 earthquakes with magnitudes >5.5 recordedby 90 stations. Additionally, we have ~307,000 P (and S) arrivals from welllocated local events (M>2.7). The model space is divided into two layers, crustand mantle, and is delimited by latitudes 15°S and 26°N and longitudes 58.75°E
and 85°W. Nodes are spaced 14.5 km apart in depth and 25 km laterally in thecrust and 20 km apart in depth and 40 km laterally in the mantle. The final
3D model is found with five iterations, in which raytracing is performed after
each iteration until residuals change less than 5% between iterations.
poster 83
Investigation of Earthquake Nucleation Processes: A Case
Study of the 2019 Ridgecrest Earthquake Sequence
WANG, Y., University of Miami, Florida, USA, yidan.wang@earth.miami.
edu; LIN, G., University of Miami, , USA, glin@earth.miami.edu; FAN, W.,
University of California, San Diego, , USA, wenyuanfan@ucsd.edu
Understanding the nucleation processes of earthquakes is crucial in seismology. The 2019 Ridgecrest earthquake sequence, notable for its high seismicity
rate, complex fault interactions, and the occurrence of the significant mainshock (Mw7.1) with abundant foreshocks, provides a unique case for studying
earthquake nucleation processes. Despite previous analyses and modeling ofseismic data, there remains considerable debate regarding the specific triggers
and fault interactions that led to the 2019 Ridgecrest earthquakes, indicatinga crucial need for further investigation. We aim to examine the near-source
structure and faulting environment in the Ridgecrest region by studying
83,000 events spanning five years before and after the Ridgecrest mainshockwith their corresponding first arrival times and waveform data. We will construct a high-precision earthquake relocation catalog based on the threedimensional seismic velocity model and waveform cross-correlation data.

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Furthermore, we plan to image the spatiotemporal evolution of the fault zone
structures using a high-resolution in situ Vp/Vs method, offering potential
new insights into the nucleation processes of the Ridgecrest earthquake. Ourfindings will shed light on the possible role of fluid dynamics and fault interactions in influencing the seismic behavior observed during the Ridgecrest
earthquake sequence.
poster 84
New Zealand’s South Westland Alpine Fault: What’s Down
There and How Does It Make Earthquakes Stop?
WARREN-SMITH, E., GNS Science, Lower Hutt, New Zealand,
warrense89@googlemail.com; TOWNEND, J., Victoria University of
Wellington, Wellington, New Zealand, john.townend@vuw.ac.nz; LOZOS, J.,
California State University, Northridge, California, USA, julian.lozos@csun.
edu; CHAMBERLAIN, C. J., Victoria University of Wellington, Wellington,
New Zealand, calum.chamberlain@vuw.ac.nz; EBERHART-PHILLIPS, D.,
GNS Science, Lower Hutt, New Zealand, d.eberhart-phillips@gns.cri.nz
Approximately half of past major Alpine Fault earthquakes have arrested close
to the transition from the listric Central Segment to the sub-vertical South
Westland Segment. Here, the fault undergoes notable changes in geometry, slip
rate, kinematics, bounding lithology, resolved stress, seismogenic behaviourand frictional properties, all of which have the potential to influence throughgoing rupture behaviour. Unravelling which factors contribute to observed
conditional rupture arrest here—and therefore assessing likely future rupture
behaviour—requires a combination of detailed observations about the fault’s
physical state to inform realistic, physics-based earthquake rupture models.
Recent work to produce precise relocations of thousands of earthquakes
and their focal mechanisms has illuminated the structure and microseismic
behaviour of the segment boundary leading to improved quantification of thespatial variability in physical factors mentioned above. Here, we present theseresults and build on our observations to use those local earthquake phasearrivals in 3D tomographic models of the segment boundary in unprecedented
resolution. We present preliminary Vp, Vs and Vp/Vs models revealing largescale changes in crustal structure across the segment boundary, high-velocity
bodies associated with the Dun-Mountain ultramafic terrane and Livingstone
Fault, and compare these with newly relocated seismicity to identify active
structures. Our full suite of observations are then used to inform a series of 3D
finite-element dynamic simulations of earthquakes along the fault. Iterative
geometric and stress parameterisations allow us to assess the relative role different physical factors play in allowing ruptures to either propagate through,or terminate at the segment boundary. We find that successive on-fault stresschanges from a series of earthquakes around the geometrical boundary can
reproduce rupture arrest consistent with the paleoseismic record and surface
slip values.
poster 85
Spatio-Temporal Slip Distributions of Deep Short-Term
Slow Slip Events in the Nankai Subduction Zone Using
Gnss, Tilt, and Strain Data
YABE, S., Geological Survey of Japan, Tsukuba, Japan, s.yabe@aist.go.jp;
OCHI, T., Geological Survey of Japan, Tsukuba, Japan, tadafumi.ochi@
aist.go.jp; MATSUMOTO, N., Geological Survey of Japan, Tsukuba, Japan,
n.matsumoto@aist.go.jp; MATSUZAWA, T., National Research Institute for
Earth Science and Disaster Resilience, Tsukuba, Japan, tkmatsu@bosai.go.jp
Slow slip events (SSEs) have been repeatedly observed on the deep plateinterface at ~30-40 km depth in the Nankai subduction zone, Japan. These
SSEs have been monitored using three types of geodetic data: GNSS, tilt, andstrain. GNSS has strength in their station density, whereas its sensitivity tocrustal deformation is lower than tilt and strain. Tilt and strain has strength
in their sensitivity to crustal deformation, but their station is much less than
GNSS. In addition, tilt and strain has unique noise like Brownian motion,
which makes us difficult to analyze those data. In this study, we develop theintegrated inversion method using the three types of data for spatio-temporal
slip distributions of deep SSEs in the Nankai subduction zone.
We first test the performance of the developed method using synthetic
datasets. We calculated crustal deformation due to synthetic SSEs in the
Shikoku region with three different magnitudes (Mw 5.7, 6.0, and 6.3). We also
calculate synthetic observation noise (Gaussian noise for GNSS and Brownian
noise for tilt and strain). The summed signals of these two synthetic values
are considered as pseudo-observation, and we applied the developed method.
We tested all possible combinations of data types and checked whether theassumed spatio-temporal slip distributions are well reproduced. We tested theresolution of the developed method using checkerboard test as well. We will
also report preliminary results for real data application in the Shikoku region.

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Cordilleran Strike-Slip Faults as Seismogenic andSeismological Features
Oral Session • Thursday 2 May • 4:30 pm PacificConveners: Richard Lease, U.S. Geological Survey (rlease@usgs.gov); Sean Regan, University of Alaska Fairbanks(sregan5@alaska.edu); Sarah Roeske, University of California,
Davis (smroeske@ucdavis.edu); Trevor S. Waldien, South
Dakota School of Mines and Technology (trevor.waldien@
sdsmt.edu)
Is the Rocky Mountain–Tintina Trench Tectonically Active?
FINLEY, T., University of Victoria, Victoria, Canada, tfinley@uvic.ca; NISSEN,
E., University of Victoria, Victoria, Canada, enissen@uvic.ca; CASSIDY, J.,
University of Victoria, Victoria, Canada, john.cassidy@nrcan-rncan.gc.ca;
LEONARD, L., University of Victoria, Victoria, Canada, lleonard@uvic.ca;
SETHANANT, I., University of Victoria, Victoria, Canada, isethanant@uvic.
ca; SALOMON, G., University of Victoria, Victoria, Canada, guysalomon@
uvic.ca; PRUSH, V., New Mexico Institute of Mining and Technology, New
Mexico, USA, veronica.prush@nmt.edu; MILLER, B., British Columbia
Ministry of Forests, Prince George, Canada, brendan.miller@gov.bc.ca
The Rocky Mountain–Tintina Trench (RMTT) is one of the most conspicuous topographic lineaments on Earth, stretching from Montana through theeastern Canadian Cordillera and into Alaska. It is the locus of major Eocenetranstensional faulting and marks a step-change in lithospheric thickness,
strength, and thermal properties. There is a moderate level of seismicity in thevicinity of the RMTT, and several historical earthquakes have caused shaking
and minor damage. However, little is known about the paleoseismic recordof the RMTT and the potential for larger and more damaging earthquakes
along it. Improving this record is important for the safety of the ~135k people that live along the RMTT, as well as the dams, pipelines, highways, andrail corridors that cross it. Here we review high-resolution topographic data(drone and airborne lidar and ArcticDEM) along the Canadian portion of the
RMTT and examine in detail several potentially fault-deformed Quaternary
landforms. In the southern RMTT near the town of Fairmont Hot Springs(50.3°N), a Holocene alluvial fan surface is disrupted by a 4-m-high westfacing scarp. Electrical resistivity tomography reveals a listric normal fault
beneath the scarp—kinematics that are at odds with contemporary compressive crustal stress patterns. Near the town of Mackenzie (55.1°N), seismicreflection surveys and outcrop observations are suggestive, but not conclusive, of fault-deformed glacial till. At the British Columbia - Yukon border(60°N) a subtle linear mound disrupts glaciofluvial outwash gravels, indicating Holocene strike-slip rupture. In northwestern Yukon, near Dawson City
(64°N), a 120-km-long series of scarps and “mole-tracks” disrupts a ~3 Ma
landscape, but a 200 ka glacial moraine overlying the fault is undeformed, suggesting that activity on this segment of the RMTT has waned in the mid-tolate Quaternary. These results are the first conclusive evidence of Quaternarysurface-rupturing earthquakes along the RMTT and, in addition to the implications for seismic hazard, significantly change our understanding of the
Cenozoic evolution of the Canadian Cordillera.
Evolution of Subsidiary Faults Associated With the
Migration of the Mount Mckinley Restraining Bend, Denali
Fault, Alaska
BEMIS, S. P., Virginia Tech, Virginia, USA, sbemis@vt.edu; BENOWITZ, J.
A., University of Colorado Boulder, Colorado, USA, jeffapplebenowitz@gmail.
com; GOEHRING, B. M., Los Alamos National Laboratory, New Mexico,USA, bgoehring@lanl.gov; PRIDDY, M. S., Virginia Tech, Virginia, USA,mspriddy@vt.edu; TERHUNE, P. J., N/A, Alaska, USA, patrickjterhune@
yahoo.com
The model of a migrating Mount McKinley restraining bend (MMRB) isestablished based on patterns of active faulting, topography, glaciers, andlow-T thermochronology, but the connection between this migration and thepatterns of local seismicity, and longer-term geomorphic markers is unclear.
Previous analyses of Kantishna Cluster seismicity show that these earthquakes
do not approximate discrete fault planes, yet correspond broadly with known
active structures. We seek to derive a model of crustal deformation evolution
associated with the MMRB that incorporates major regional geologic and geophysical phenomena. To constrain this model, we present new constraints on
the rates and distribution of active faulting and combine this with the recordof shallow seismicity and new geophysical observations. New results fromSeismological Research Letters

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terrestrial cosmogenic nuclide and luminescence dating of offset landforms,
improved fault trace mapping and offset measurement from higher resolution
topographic data, and new thermochronologic constraints refine our understanding of the extent, magnitude, and style of active faulting through the
MMRB. We propose that the sub-clusters of low-magnitude seismicity with
the Kantishna Cluster reflect individual ‘process zones’ of distributed fracturing and faulting associated with the development and propagation of faults
outward from the migrating restraining bend. The geophysically-imaged
sub-horizontal detachment beneath the Kantishna Hills occurs in a region
exhibiting a longer record of distal deformation north of the MMRB as demonstrated by the uplift of the Kantishna Hills anticline. As cumulative upliftof the Kantishna Hills anticline decreases to the west, both the seismicity andthe northern extent of active deformation abruptly step closer to the Denali
fault. This concentration of deformation between the Hines Creek and Denali
faults appears to reflect a shorter period of time interacting with the restraining bend and a lack of development of a deeper detachment to transfer strain
into the foreland.
Residual Yakutat Microplate Velocity Drives Rapid Thrust
Faulting North of the Central Denali Fault
BENDER, A. M., U.S. Geological Survey, Alaska, USA, abender@usgs.
gov; LEASE, R. O., U.S. Geological Survey, Alaska, USA, rlease@usgs.gov;
RITTENOUR, T., Utah State University, Utah, USA, tammy.rittenour@usu.
edu
Plate convergence rates strongly influence seismicity and mountain building inboard of convergent margins, but the distribution and kinematics ofstructures accommodating far-field convergence can be elusive. In interior
Alaska, Yakutat microplate convergence drives late Pleistocene–recent rightslip on the Denali Fault, but westward-decreasing slip rates leave substantial
residual Yakutat motion unaccounted for. Here, we show that the Northern
Foothills thrust slip accommodates a modern 4.4 mm/yr geodetic velocity
gradient equivalent to ~78% of the total ~5.6 mm/yr residual Yakutat convergence along the central Denali Fault. Infrared-stimulated luminescence agesof strath terrace deposits (4–67 ka; 6 sites) quantify Totatlanika River bedrock
incision across the 1947 Mw 7.1 thrust earthquake epicentral region. Incision
rates increase northward abruptly from <1 mm/yr to 4.8–5.6 mm/yr acrossthe range-front anticline overlying the blind thrust tip. Rapid 6.7 mm/yr slip
on a steep thrust ramp modeled beneath the northern Alaska Range front
accommodates the geodetic gradient, drives rock uplift at rates equivalent tomeasured incision rates, and implies that large earthquakes like the 1947 event
may recur with 500–1400-yr frequency. Results illuminate focused seismogenic strain inboard of a complex convergent margin, and demonstrate thatthe pace of continental indentation in Alaska doubles prior expectations withdirect implications for extant seismic hazard estimates.
Seismic Imaging of the Eastern Alaska Range Crustal
Structure
MILLER, M. S., Australian National University, Acton, Australia, meghan.
miller@anu.edu.au; ZHANG, P., Australian National University, Canberra,
Australia, ping.zhang@anu.edu.au; PICKLE, R., Australian National
University, Canberra, Australia, robert.pickle@anu.edu.au; WALDIEN, T.
S., South Dakota School of Mines & Technology, South Dakota, USA, trevor.
waldien@sdsmt.edu; ROESKE, S., University of California, Davis, California,
USA, smroeske@ucdavis.edu
The Denali fault is an active right-lateral continental strike-slip fault that transects the North American Cordillera from northern British Columbia to theBering Sea shelf. The structural evolution of the Denali fault as a major continental fault system that has accommodated hundreds of kilometers of displacement implies that the fault is a significant geophysical feature. However,the complex and diverse geology surrounding the fault, and variability ingeologic and geophysical data resolution, cause the perceived geophysical signature of the fault to be spatially variable. Here, we explore the geologic evolution of the eastern Alaska Range and the central portion of the Denali fault byintegrating new understanding of the geologic framework with new seismic
images of the crustal structure. Our new seismic images utilize all available
data (1999-2022) from both temporary and permanent broadband seismometers available from the IRIS DMC. These data include the recently deployed
ICED array (Z5 network) that targeted the eastern Alaska Range and adjacentsection of the Denali Fault that had previously been under-resolved by the
TA and other temporary deployments. We combine new ambient noise based
tomography inferring the shear wave velocities, P receiver functions to define
the Moho topography, and a new machine learning based catalog of seismicity
together to infer the structural heterogeneity of the crust around the Denali
fault. Complimentary geophysical information from this section of the fault

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corroborates geologic observations indicating that the Denali fault is a primary lithospheric-scale boundary, with some sections that clearly indicate astep across the Moho.
The Crustal Magmatic Structure Beneath the Denali
Volcanic Gap in Central Alaska Across the Denali Fault
RABADE, S., University of Utah, Utah, USA, san.rabade@gmail.com; LIN,
F., University of Utah, Utah, USA, fanchi.lin@utah.edu; TAPE, C., Universityof Alaska Fairbanks, Alaska, USA, ctape@alaska.edu; WARD, K. M., South
Dakota School of Mines & Technology, South Dakota, USA, kevin.ward@
sdsmt.edu; ALLAM, A., University of Utah, Utah, USA, amir.allam@utah.edu
Within the active subduction system, the presence of the Denali Volcanic Gap(DVG), a ~400 km region separating active volcanism of the Aleutian Arc
to the west and the Wrangell volcanoes to the east, remains enigmatic. It is
unclear if the subduction system is producing and storing magmatic material
at the bottom of the crust or if high stresses in the crust impede the transportof material in the mid-crust, thus stalling volcanic activity. To better understand the effects of tectonic forces in the south-central Alaska upper crust,
we present a 270 km long and 15 km deep 2-D shear wave velocity model ofsouth-central Alaska across the Denali fault. We use data from a linear temporary node deployment with more than 300 geophone stations and broadband stations available in the area. We use single beamforming/slant stacking
to enhance the ambient noise cross-correlation signals and simultaneously
measure location-dependent Rayleigh wave phase velocity and ellipticity or
horizontal to vertical (H/V) amplitude ratios. We perform 1-D Markov chain
Monte Carlo joint inversions of Rayleigh wave phase velocities and H/V ratios
to calculate the shear wave velocity profile. Our main observations include a
low-velocity zone below the Denali Volcanic Gap, the fold-and-thrust belt in
the northern flank of the Alaska Range, and the Denali fault as a narrow localized low-velocity anomaly extending to at least 12 km depth. The low-velocity
anomaly below the DVG could be associated with the accumulation of melt
storage of subduction-related material in the mid-crust.

Cordilleran Strike-Slip Faults as Seismogenic andSeismological Features [Poster Session]
Poster Session • Thursday 2 May
Conveners: Richard Lease, U.S. Geological Survey (rlease@usgs.gov); Sean Regan, University of Alaska Fairbanks(sregan5@alaska.edu); Sarah Roeske, University of California,
Davis (smroeske@ucdavis.edu); Trevor S. Waldien, South
Dakota School of Mines and Technology (trevor.waldien@
sdsmt.edu)
poster 86
Refining the Nature of Distributed and Localized SlipPartitioning of the Totschunda-Fairweather to Denali
Corridor Using Earthquake Relocations and Focal
Mechanisms
BIEGEL, K., University of Calgary, Calgary, Canada, katherine.biegel@ucalgary.ca; GOSSELIN, J. M., University of Calgary, Calgary, Canada,
jeremy.gosselin@ucalgary.ca; DETTMER, J., University of Calgary, Calgary,
Canada, jan.dettmer@ucalgary.ca; COLPRON, M., Yukon Geological Survey,
Whitehorse, Canada, maurice.colpron@yukon.ca; ENKELMANN, E.,
University of Calgary, Calgary, Canada, eva.enkelmann@ucalgary.ca; CAINE,
J. S., U.S. Geological Survey, Colorado, USA, jscaine@usgs.gov
Southeastern Alaska and southwestern Yukon are at the plate boundary
between the Pacific and North American plates and the Yakutat microplate.
The region is undergoing complex active deformation due to the oblique collision of the Yakutat microplate with North America. Transpressional deformation is accommodated 300 km inboard from the plate boundary by large displacement, regional-scale faults, including the Fairweather, Denali, and DukeRiver fault systems. Monitoring in the region is limited due to the remote setting and year-round snow and glacial coverage. In the last decade, regional
seismic networks have significantly expanded, leading to an increased density of stations largely attributed to the deployment of Transportable Arraystations, many of which were converted to permanent stations in the Alaska
regional network. In this study, we relocate more than 5,000 earthquakes
between 2010 and 2021. These earthquake relocations show reduced uncertainty, particularly in depth, and allow us to show that brittle regime deforma-

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tion occurs on a shallow fault network in the upper 10 km of the crust. The
region has a shallow brittle-plastic transition consistent with elevated crustal
temperatures across the Cordillera. We interpret and classify deformational
kinematics across this corridor by combining earthquake relocations with
regional focal mechanism solutions. The focal mechanism catalog includes
374 novel low-magnitude focal mechanism solutions. Our interpretive fault
map includes the postulated Totschunda-Fairweather Connector fault, whichhelps to explain regional deformation. We identify new faults, such as theKathleen Lake fault. Our interpretation includes a simplified conceptualmodel that describes the region characterized by transpression with distributed and localized slip partitioning. This study provides a current snapshot of
active seismic deformation on a well-defined shallow network of faults occurring within this continually evolving oblique convergent tectonic regime.
poster 87
Revisiting the Enigmatic Magnitude-7 Denali Fault
Earthquake of July 7, 1912
TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu;
LOMAX, A., ALomax Scientific, Mouans Sartoux, France, alomax@free.fr
The 2002 Mw 7.9 Denali fault earthquake ruptured 341 km within central
Alaska. Its occurrence prompted a search for evidence of earlier earthquakes
on the Denali fault, the most recent candidate being a Ms 7.2 earthquake on
July 7, 1912. The enigma of the 1912 earthquake is twofold. First, the maximum reporting shaking intensity—documented by the Parker-Browne Denali
mountaineering expedition—is ~250 km west of damaged trees documented
by Carver et al. (2004), while empirical scaling suggests a rupture length ofabout 60-80 km for a magnitude 7.2 earthquake. We revisit the 1912 earthquake with two approaches: 1) probabilistic relocation of epicenter using
globally recorded arrival times, and 2) compilation and reassessment of shaking intensity reports to estimate a macroseismic epicenter. Our preferred
instrumental epicenter is west of the Parks Highway, in agreement withthe maximum reported shaking by the Parker-Browne expedition. We also
examine data choices that result in instrumental epicentral estimates that are
toward the east and closer to the documented tree damage. We explore two
possibilities for the 1912 earthquake, all of which assume the Denali fault
as the host. The first scenario is that there was a single, exceptional earthquake having a long rupture and strong shaking, relative to its magnitude.
The second scenario is that there were two earthquakes: a large one (M 7.2)
in the west, near the Parks Highway, and a smaller one (M 6.5-7) in the east,near the Richardson Highway. The large event occurred on 1912-07-07 andproduced the global arrival times and the strongest felt report near Denali,
while the smaller event occurred minutes to months after the large event andwas responsible for the tree damage reported by Carver. Further analysis of
instrumental data, felt reports, and paleoseismic results may help discriminate
among these scenarios.

Creating Actionable Earthquake Information Products
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Tiegan Hobbs, Geological Survey of Canada(thobbs@eoas.ubc.ca); Sabine Loos, University of Michigan(sloos@umich.edu); Marísa A. Macías, U.S. Geological
Survey (mmacias@usgs.gov); Jessie K. Saunders, California
Institute of Technology (jsaunder@caltech.edu); David Wald,
U.S. Geological Survey (wald@usgs.gov)
Improving Rapid Earthquake Characterization for Tsunami
Early Warning for Aotearoa New Zealand and theSouthwest Pacific
LACOUA, L. Z., University of Otago, Dunedin, New Zealand, luce.lacoua@
postgrad.otago.ac.nz; FRY, B., GNS Science, Lower Hutt, New Zealand, b.fry@
gns.cri.nz; GORMAN, A., University of Otago, Dunedin, New Zealand,
andrew.gorman@otago.ac.nz; LIAO, Y. M., GNS Science, Lower Hutt,
New Zealand, m.liao@gns.cri.nz; FOUNDOTOS, L., GNS Science, Lower
Hutt, New Zealand, l.foundotos@gns.cri.nz; JAMELOT, A., CEA/DASE/
Laboratoire de Géophysique de Tahiti, Papeete, French Polynesia, France,
jamelot@labogeo.pf; ZWECK, C., GNS Science, Lower Hutt, New Zealand,c.zweck@gns.cri.nz
Aotearoa New Zealand, located in the Southwest Pacific Ocean, is vulnerable to tsunamis. The Rapid Characterization of Earthquakes and Tsunami

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www.srl-online.org(RCET) project, led by GNS Science (Geological and Nuclear Sciences), aims
to improve rapid analysis of large local and regional earthquakes to determine their tsunamigenic potential and better capture the rupture process. To
this end, we are focusing on refining a W-phase solution (automated moment
tensor inversions) on a regional scale. Unlike simpler automated magnitude
determinations routinely used to analyze earthquakes in Aotearoa New
Zealand, the W-phase does not saturate with magnitude, making it better
at quantifying Mw for the largest earthquakes. It also provides the centroid,
rather than the hypocenterre of an earthquake, allowing better estimation of
the spatial distribution of shaking impacts. For these reasons we are developing synthetic earthquake waveforms to refine W-phase inversions for Mw~5+ earthquakes in New Zealand and Mw 6.5+ earthquakes in the southwest
Pacific, including the Hikurangi-Kermadec subduction zone. The current tsunami early warning procedure calculates W-phase solutions within 20 minutes of earthquake origins with aim of reducing it to 5-10 minutes.
Using a large set of large magnitude events adapted to New Zealandand Hikurangi-Kermadec context, we refine our understanding of the limits
regional W-phase inversion. We focus on the minimum magnitude we canaccurately estimate, the minimal station coverage required and the complexityof the source that can be apprehended by the W-phase.
We simulate earthquake waveforms using a catalog of synthetic ruptureson the Hikurangi-Kermadec subduction zone. To generate the waveforms, we
use SPECFEM3D Globe, a finite element method-based software that simulates wave propagation through a global velocity model of the Earth. These
synthetic waveforms are then postprocessed and inverted to obtain a W-phasesolution. Preliminary results define which minimum waveform resolution
is required to observe a W-phase and that a simple centroid moment tensor
source provides an adequate W-phase solution.
Site-Specific, Extended Shakemaps for Earthquake
Engineering Applications
THOMPSON, E. M., U.S. Geological Survey, Colorado, USA, emthompson@usgs.gov; HEARNE, M., U.S. Geological Survey, Colorado, USA, mhearne@
usgs.gov; WORDEN, C. B., U.S. Geological Survey, Colorado, USA,cbworden@contractor.usgs.gov; QUITORIANO, V., U.S. Geological Survey,
Colorado, USA, vinceq@contractor.usgs.gov; CUNNINGHAM, A. E., U.S.
Geological Survey, Colorado, USA, acunningham@usgs.gov; WALD, D. J.,
U.S. Geological Survey, Colorado, USA, wald@usgs.gov
The U.S. Geological Survey product that gives the estimated shaking intensity
for earthquakes globally is called ShakeMap. It provides maps of estimatedground motion intensity metrics (IMs) in the minutes and hours following
an earthquake. Providing this information as quickly as possible is criticalfor emergency responders and the public. In contrast, the response timeline
for specialized use cases such as code compliance, damage analyses, fragility
curve development, and examining triggering thresholds for ground failure
is less compressed than for emergency responders, and more detailed information would be useful. Here, we describe recently developed tools to provide ShakeMap estimates of spectral acceleration in 22 periods (matching thecurrent U.S. National Seismic Hazard Model periods) as well as orientationindependent components. We refer to ShakeMap products that include these
extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool in Python called the “ShakeMap
Sampling Tool” (SST) that gives all the estimated shaking metrics for a specificlocation (or list of locations). Additionally, we developed a web application
where users can input locations of interest and view/download the SST results.
Through this system, we can also provide composite ShakeMaps—maps ofthe maximum value of each IM across a sequence—which is especially usefulfor overall loss estimates. Composite ShakeMaps can also be used to provide
a site-specific shaking history for analyzing repeated shaking to structures.
The composite ShakeMap, combined with the extended IM products, facilitates forensics at building and infrastructure sites for which damage may beof concern, as described in the Disproportionate Damage Earthquake trigger specified in the International Existing Building Code and in developing
ATC-145 “Guidelines for Post-Earthquake Assessment, Repair, and Retrofit
of Buildings”.
Geonet’s Shaking Layer Tool: Understanding andIncorporating User Needs into Shaking Layers for
Aotearoa, New Zealand
CHARLTON, D., GNS Science, Auckland, New Zealand, d.charlton@gns.cri.
nz; HOULTHAM, J., GNS Science, Lower Hutt, New Zealand, j.houltham@
gns.cri.nz; HORSPOOL, N., GNS Science, Lower Hutt, New Zealand,n.horspool@gns.cri.nz; GODED, T., GNS Science, Dunedin, New Zealand,
T.Goded@gns.cri.nz; KAISER, A., GNS Science, Lower Hutt, New Zealand,
A.Kaiser@gns.cri.nz; CHADWICK, M., GNS Science, Lower Hutt, New

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Zealand, M.Chadwick@gns.cri.nz; GROOM, J., GNS Science, Lower Hutt,
New Zealand, j.groom@gns.cri.nz; ABBOTT, E., GNS Science, Lower Hutt,
New Zealand, e.abbott@gns.cri.nz; MORATALLA, J., GNS Science, Lower
Hutt, New Zealand, j.moratalla@gns.cri.nz
Following a damaging earthquake, emergency managers are in great needfor reliable shaking information to be able to make decisions and increase
their situational awareness. Until now, these decisions in New Zealandneeded to be made with incomplete geographical information, relying solely
on observed data points from either strong-motion stations or felt reports.
The New Zealand Shaking Layers project has been designed to fill in that gap:
through the use of the software ShakeMap configured to satisfy New Zealand’scharacteristics, a tool is now available that provides shaking intensity maps
for Peak Ground Acceleration, Peak Ground Velocity, Modified Mercalli
intensity, and spectral acceleration at different periods. This project is a collaboration between GeoNet, New Zealand’s geohazards data and monitoring
programme, and the Rapid Characterisation of Earthquake and Tsunami(R-CET) science programme.
Alongside undertaking new physical science and software development,
we used a combination of social science research methods and user testing tounderstand more about Shaking Layers’s potential users. Here, we will present the results of a 2021-2022 public survey of over 1600 New Zealanders on
their preferences for earthquake event information. Preliminary results showthat 77% of participants stated that ‘shaking intensity information’ was either
extremely or very important on a map after the earthquake scenario presented
to them. Shaking intensity information would help them to determine if theyshould stay put or try and evacuate to safety and whether they should be concerned for family members. ‘Earthquake size’ (92%) and ‘Epicenter’ (86%)
were the most useful types of information for those surveyed. Participants
noted that this information allows for rapid decision making of tsunami
threat in particular. Maps of expected landsliding and liquefaction were also
extremely and very useful for the vast majority of participants. These results(in combination with techncial user feedback and persona development) provided clear guidance during the design process ensuring our product meetsuser needs.
Improved Rapid Source and Shaking Characterization
Using Large Seismic Array Observations
WANG, D., China University of Geosciences, Wuhan, China, dunwang2004@
yahoo.com; CHEN, W., Lanzhou Institute of Seismology, China Earthquake
Administration, Lanzhou, China, cwk2000@yeah.net; WALD, D., U.S.
Geological Survey, Colorado, USA, wald@usgs.gov
Rapid and accurate determination of finite source models and seismic intensity maps for damaging earthquakes are paramount for effective earthquake
disaster mitigation and subsequent secondary hazard estimation. However,obtaining such estimates in the initial hours after a large event remains challenging, particularly for earthquakes with large source extents in regions withlimited local seismic observations. In this study, we present improvements
over our earlier strategy based on back-projection array technologies. Our
approach involves estimating the source energy radiation utilizing multiple
regional seismic array contributions, obtaining stable estimates of the fault
geometry and subevent relative amplitudes. By combining Ground Motion
Models and the estimated subevent distribution, we calculate Peak Ground
Velocities (PGVs) directly by applying PGV-based site corrections using the
USGS global Vs30 database. Alternatively, we can project the resulting subevents (high frequency radiators) onto fault geometries for use in estimatingshaking with USGS ShakeMap. We evaluate our algorithm using representative earthquakes that occurred in recent years, including the 2024 Mw 7.5
Japan earthquakes.
Though we observe variations in our results obtained from different
array geometries, the inferred fault planes approximate the finally determined
rupture area well and the seismic intensity maps we produce exhibit a highdegree of similarity with ShakeMaps constrained by strong motion and macroseismic data, where available. A noteworthy benefit of this approach is it
does not rely on real-time local strong-motion observations. Ultimately, we
intend to automate these algorithms, enabling the issuance of reliable seismic
intensity maps shortly after damaging earthquakes. Such efforts could benefit
post-earthquake decision-making and tsunami hazard evaluation.
Reference: Chen, W., Wang, D., Si, H., & Zhang, C. (2022). Rapid
Estimation of Seismic Intensities Using a New Algorithm That Incorporates
Array Technologies and Ground-Motion Prediction Equations (GMPEs).
BSSA, 112(3), 1647-1661.

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A Growing Catalogue of Short-Period Earthquake Rupture
Histories From Multi-Array Back-Projection
VERA SANHUEZA, F., GFZ Potsdam, Potsdam, Germany, fvera@gfzpotsdam.de; TILMANN, F., GFZ Potsdam, Potsdam, Germany, tilmann@gfzpotsdam.de; SAUL, J., GFZ Potsdam, Potsdam, Germany, saul@gfz-potsdam.
deFor large earthquakes, the distribution of the high intensity zone depends tofirst order on the direction and length of rupture propagation. Furthermore,
the speed of rupture propagation has a major influence through directivity
effects. Of particular concern are rupture segments propagating at supershear speeds, which emit a shockwave-like pulse in the forward direction.
Teleseismic back-projection imaging has emerged as a powerful tool for constraining the rupture propagation of large earthquakes with relatively little
user input and capturing the high-frequency behavior of the fault, which ismost relevant for impact, at least for most building types. However, its application often suffers from artifacts related to the receiver array geometry. We
developed a teleseismic backprojection technique that can accommodate datafrom multiple arrays. Combined processing of P and pP waveforms may further improve the resolution. The method is suitable for defining arrays ad-hoc
to achieve a good azimuthal distribution. We present a catalog of short-period
rupture histories (0.5–2.0 Hz) for all earthquakes from 2010 to 2023 with Mw≥ 7.5 and depth less than 200 km (62 events). The method provides automatic
estimates of rupture length, directivity, speed, and aspect ratio, a proxy for
rupture complexity. We obtained short-period rupture length scaling relations
that are in good agreement with previously published relations based on total
slip. Rupture speeds were consistently in the sub-Rayleigh regime for thrustand normal earthquakes, whereas a tenth of strike-slip events propagated at
supershear speeds. Many rupture histories exhibited complex behaviors, e.g.,
rupture on conjugate faults, bilateral propagation, and dynamic triggering by
a P wave. For megathrust earthquakes, ruptures encircling asperities were frequently observed, with down-dip, up-dip, and balanced patterns, with emissions up-dip of the main asperity more common than suggested by earlier
publications. In the presentation, we will also consider the realtime potentialof the algorithm.
Visual Communication of Aftershock Forecasts Driven byUser Needs
SCHNEIDER, M., U.S. Geological Survey, California, USA, max.
schneider15@gmail.com; WEIN, A. M., U.S. Geological Survey, California,
USA, awein@usgs.gov; VAN DER ELST, N., U.S. Geological Survey, California,
USA, nvanderelst@usgs.gov; MCBRIDE, S. K., U.S. Geological Survey,
California, USA, skmcbride@usgs.gov; BECKER, J., Massey University,
Palmerston North, New Zealand, j.becker@massey.ac.nz; CASTRO, R.,
Center for Scientific Research and Higher Education in Ensenada, Ensenada,
Mexico, raul@cicese.mx; DIAZ, M., Ministry of Environment and Natural
Resources, San Salvador, El Salvador, mdiaz@ambiente.gob.sv; GONZALEZHUIZAR, H., Center for Scientific Research and Higher Education in
Ensenada, Ensenada, Mexico, hgonzalez@cicese.mx; HARDEBECK, J., U.S.
Geological Survey, California, USA, jhardebeck@usgs.gov; MICHAEL, A. J.,
U.S. Geological Survey, California, USA, ajmichael@usgs.gov; MIXCO, L.,
Ministry of Environment and Natural Resources, San Salvador, El Salvador,lmixco@ambiente.gob.sv; PAGE, M., U.S. Geological Survey, California,
USA, mpage@usgs.gov; PALOMO, J., Ministry of Environment and Natural
Resources, San Salvador, El Salvador, jocelyn.figueroa@ambiente.gob.sv
The U.S. Geological Survey releases aftershock forecasts following large (M5+)
earthquakes in the U.S. and associated territories. Forecasts show the expected
number (and range) of aftershocks in a specified area for various magnitude
thresholds and time durations. Forecasts are released using a product template that contains tables and text. Visualizing these aftershock forecasts canmore effectively communicate this information. In this research, we seek to
identify which forecast visualizations (including maps) can serve a variety ofuser groups. In 2023, we held workshops with members of target user groups,
including emergency managers, civil engineers, critical infrastructure operators, firefighters, public health officials, the media, and other science communicators. In these workshops, users performed small-group activities toelicit specific user needs on the dimensions of aftershock forecast informationneeded by their role (informational needs) and how this information would
optimally be displayed (product needs). We conducted these workshops in the
United States, Mexico and El Salvador to understand which forecast products
may be effective across countries. Many users reported needing maps of shaking hazard to support their work. We find a greater variation in user needs
across profession than country, and that user needs also vary with time. We
identify common categories of use cases across the disparate professions andconnect users’ informational and product needs to these user archetypes. We

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discuss practical implications for effective visual communication of aftershock
forecasts and other natural hazards.
Tomorrow’s Cities: An Interdisciplinary Decision Support
Environment for Risk Sensitive Urban Planning and Design
GALASSO, C., University College London, London, United Kingdom,c.galasso@ucl.ac.uk; Tomorrow’s Cities Programme Working Group,
The University of Edinburgh, Edinburgh, United Kingdom, support@
tomorrowscities.org
Understanding, modeling, quantifying, and managing future risks fromnatural hazards is becoming increasingly crucial as the climate changes, thehuman population grows, asset wealth accumulates, and societies become
more urbanized and interconnected in many parts of the world. This is especially true in low-income contexts. The 2015-2030 Sendai Framework for
Disaster Risk Reduction recognizes this need, emphasizing the importance of
preparing for the disasters that our world may face tomorrow through strategies to minimize uncontrolled development/densification in hazardous areas.
Assessing and communicating future natural hazard risk can support decision-making on urban development in planning and designing less-exposed
and more resilient cities and regions. This presentation discusses these efforts,
introducing the risk-based, pro-poor urban planning and design framework(and its implementing Decision Support Environment, DSE) developed
within the Tomorrow’s Cities project, the United Kingdom Research andInnovation (UKRI) Global Challenge Research Fund (GCRF) Urban Disaster
Risk Hub. The Hub aims to support the delivery of the United Nations’Sustainable Development Goals and priorities 1 to 3 of the Sendai Frameworkfor Disaster Risk Reduction. Specifically, the Tomorrow’s Cities DSE integrates
physics-based natural hazard modeling, dynamic exposure and vulnerability
modeling of infrastructure systems and networks (physical and social), consideration of multi-hazard scenarios, and participatory approaches for identifying impact metrics tailored to the specific context and needs of marginalized communities. The presentation showcases the Tomorrow’s Cities DSE
implementation in Kathmandu, Nepal, where methodologies and guidelines
for action-oriented, pro-poor, earthquake-risk-based decision-making are coproduced with local, national, and global stakeholders and research partners.
Exploring the Ethical Tensions and Communication
Challenges of Publicly Available Global Aftershock
Forecasting From Science Agencies
MCBRIDE, S. K., U.S. Geological Survey, California, USA, skmcbride@usgs.
gov; MICHAEL, A. J., U.S. Geological Survey, California, USA, ajmichael@usgs.gov; SCHNEIDER, M., U.S. Geological Survey, California, USA,mschneider@usgs.gov; HARDEBECK, J., U.S. Geological Survey, California,
USA, jhardebeck@usgs.gov; WEIN, A. M., U.S. Geological Survey, California,
USA, awein@usgs.gov; LLENOS, A. L., U.S. Geological Survey, Colorado,
USA, allenos@usgs.gov; WALD, D., U.S. Geological Survey, Colorado, USA,wald@usgs.gov; PAGE, M., U.S. Geological Survey, California, USA, mpage@usgs.gov; VAN DER ELST, N., U.S. Geological Survey, California, USA,nvanderelst@usgs.gov
Aftershock forecasting is an important tool that helps decision makers andvarious publics to understand what the future could look like in an earthquake sequence, after a large mainshock. The U.S. Geological Survey produces
aftershock forecasts for various uses and audiences post-earthquake, assistingin decision making for those impacted. This information is available in several ways: domestically, an aftershock communication template is available tothe public post Magnitude 5+ earthquakes; and, internationally, a product isshared with the Bureau for Humanitarian Assistance for events with PAGER
alerts at the orange and red-level for fatalities. Given that the USGS alreadyproduces these, what is the ethical responsibility to make these international
forecasts more available for public safety considerations? Further, by communicating these forecasts publicly beyond the United States borders, what
are the considerations of scientific sovereignty of nations? What potential isthere for miscommunication of forecasts in other nations, with diverse cultural and linguistic backgrounds? This presentation explores these ethicaland social tensions, reporting on a group of listening sessions with scientificand response community members from around the world in 2022 and 2023.
Further, we suggest some solutions to these issues as well as future pathways,
including aftershock forecasting triggered by impact levels e.g. PAGER levels,
rather than magnitude.

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Development of Rapid Earthquake Damage Estimation
System to Expedite Rescue Efforts in the Post-Disaster
Phase
PATCHETT, M., University of Victoria, Victoria, Canada, megumipatchett@gmail.com; HOBBS, T. E., Natural Resources Canada, Vancouver, Canada,
thobbs@eoas.ubc.ca
In the first several hours following an earthquake, decision makers such as
emergency managers have few fast options to gain situational awareness. They
are often forced to rely upon calls to overloaded 911 lines, reports from first
responders, reconnaissance along disrupted roadways by emergency personnel, or, after a day or two, aerial surveillance performed by the military.
However, the first 24 to 48 hours are crucial for life-saving following a major
earthquake. Situational awareness can be significantly improved using existing seismic risk modeling tools adapted for use with near-real-time seismic
ground motion data typically available within tens of minutes. This work
presents a new initiative to develop a Rapid Earthquake Damage Estimation(REDE) tool for earthquakes in Canada, similar to the United States
Geological Survey’s TwoPAGER. We explore best practices and determine thefeasibility of using rapidly available seismic data from the upcoming Canadian
Earthquake Early Warning network in the first-generation Canadian Seismic
Risk Model (CanSRM1) framework to model the impacts on people, the built
environment, and the economy from an earthquake within 10-20 minutes ofa major event. In particular, we focus on results most relevant to life safety
and early response: collapsed buildings, entrapment injuries, hospital demand
surge, roadway debris which may block response, and immediate mass careneeds like shelter requirements. It will help prioritize rescue and reconnaissance efforts, and can serve as a base of evidence for early resource allocation
including federal requests for assistance. This tool is expected to be replaced
within tens of hours by direct observations and aerial surveys as they become
available. Information has been collected about how such a tool might be usedby stakeholders: first responders, emergency managers and critical infrastructure operators. Based on the resulting prototype, a viable product is anticipated to be completed by late 2024.
Improving the Usability of Near-Real-Time Earthquake
Information for Equity-Focused Decision-Making ThroughEarthquake Scenario ExercisesMACÍAS, M. A., U.S. Geological Survey, Colorado, USA, mmacias@usgs.
gov; LOOS, S., University of Michigan, Michigan, USA, sloos@umich.
edu; REDDY, E., Colorado School of Mines, Colorado, USA, reddy@mines.
edu; WALD, D. J., U.S. Geological Survey, Colorado, USA, wald@usgs.gov;
KNODEL, E. J., U.S. Geological Survey, Colorado, USA, eknodel@usgs.
gov; MCGOWAN, S., Federal Emergency Management Agency, Colorado,
USA, sean.mcgowan@fema.dhs.gov; MARANO, K., U.S. Geological Survey,
Colorado, USA, kmarano@usgs.gov
Following an earthquake, near-real-time information provides valuable dataon potential impacts like economic losses and fatalities to the public and decision-makers in the emergency management, humanitarian, finance, and othersectors. However, earthquake impact information is often designed without
formal user input or a focus on socially vulnerable communities, resulting
in information that is not necessarily suited for equity-focused disaster management decisions. In this research, we investigated user needs for equityfocused impact data. Following initial focus groups with a broad set of users
from various sectors, we developed a mockup showing additional metrics of
exposure and loss that highlight socially vulnerable populations in a way that
addresses user needs. We then developed earthquake scenario exercises for atargeted group of users to gain feedback on the mockup through a usability
testing workshop. Workshop participants included nine emergency managers
from the Federal Emergency Management Agency (FEMA), the California
Governor’s Office of Emergency Services (CalOES), the American Red Cross,and Innovative Emergency Management. Following qualitative analysis, workshop results revealed that equity-focused impact metrics have the potential
to influence more equity-focused emergency management decision-making,incorporating equity-focused decision-making into scenario exercises caninfluence equity-focused emergency management decision-making, and usercentered design can be beneficial in hazard impact product development. For
near-real-time impact information at the USGS, we have identified the needfor more accessible visualizations and language. More broadly, this researchhighlights how a user-centered and equity-focused design process can create
meaningful interactions with stakeholders who can ultimately use products to
support vulnerable populations after future earthquakes.

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Creating Actionable Earthquake Information Products[Poster Session]
Poster Session • Wednesday 1 May
Conveners: Tiegan Hobbs, Geological Survey of Canada(thobbs@eoas.ubc.ca); Sabine Loos, University of Michigan(sloos@umich.edu); Marísa A. Macías, U.S. Geological
Survey (mmacias@usgs.gov); Jessie K. Saunders, California
Institute of Technology (jsaunder@caltech.edu); David Wald,
U.S. Geological Survey (wald@usgs.gov)
poster 75
Post-Earthquake Liquefaction Mapping by Semi-Supervised
Machine Learning Using Partially Labeled Imagery
ASADI, A., Tufts University, Massachusetts, USA, adel.asadi@tufts.edu;
BAISE, L. G., Tufts University, Massachusetts, USA, laurie.baise@tufts.edu;
SANON, C., Tufts University, Massachusetts, USA, christina.sanon@tufts.
edu; KOCH, M., Boston University, Massachusetts, USA, mkoch@bu.edu;
CHATTERJEE, S., Michigan Technological University, Michigan, USA,schatte1@mtu.edu; MOAVENI, B., Tufts University, Massachusetts, USA,babak.moaveni@tufts.edu
This study explores a new method to identify and map soil liquefaction areasfrom aerial images after earthquake events. Traditionally, liquefaction isrecorded through field visits as geographic points, leading to incomplete data.
Comprehensive mapping of affected areas is crucial for developing accurate
prediction models. The research introduces a machine learning approach thatleverages partially labeled data from expert visual assessments to detect andmap unlabeled liquefaction areas. This method aims to increase mapping’s
spatial accuracy, and it was tested on aerial images from the 2011 Christchurch
earthquake, using existing partial data as a reliable ground-truth source. First,
the study compares a new semi-supervised learning technique (self-trainingclassification) with traditional supervised learning. This approach is designed
to overcome the challenges of limited and spatially incomplete labeled data.
Second, it evaluates the effectiveness of various image features (color transformations, statistical indices, and texture components) in improving classification accuracy. Building footprints were also used to refine the results by
excluding building roofs from the analysis. Additionally, the study employed
the Fuzzy C-Means clustering algorithm to categorize liquefaction samples
into two distinct classes (dry and wet). The final results showed that the semisupervised method, especially when using selected high-ranked features, outperforms traditional methods and provides more complete spatial maps ofliquefied areas.
poster 76
Investigating Different Methodologies for a Sar Coherence
Change Detection Product
BURGI, P. M., U.S. Geological Survey, Colorado, USA, pburgi@usgs.gov
The U.S. Geological Survey (USGS) provides rapid (within 30 minutes) estimates of earthquake-induced building damage and ground failure following significant events. These products are based solely on pre-event data andevent-specific shaking estimates and do not include direct observations ofdamage or ground failure following an earthquake. To this end, the USGS isdeveloping an intermediate-timeframe pipeline for post-earthquake products(within days to a week) that combines the current rapid estimation productswith post-event observations with the goal of more accurately identifying themost affected areas. As a vital component of this pipeline, the USGS plansto generate an in-house Synthetic Aperture Radar (SAR) coherence-based
Change Detection Map (CDM) using pre- and post-earthquake satellite observations to identify regions exhibiting surface property changes attributable todamage and ground failure. While NASA produces a similar product called
the Damage Proxy Map (DPM), the USGS CDM is specifically being developed for integration into the USGS earthquake product pipeline. Here, we
examine various methodologies to generate CDMs, with a focus on optimizing CDM robustness. We explore sample area dimension, the functional formof sampled coherence (e.g., boxcar versus Gaussian), and the combinations of
SAR pairs (e.g., sequential-only versus multi-pairs). We generate CDMs using
both Sentinel-1 (~30 m resolution) and Wide Ultrafine Radarsat-2 data (~10m resolution), the latter of which has not yet been used to generate post-earthquake damage estimates. We compare our results against damage and landslide observations derived from high-resolution optical data (PlanetLab andWorldView, ~1-5 m resolution) from the 2023 Mw 6.8 Morocco earthquake.

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By exploring different CDM generation methodologies, we can constrain a
CDM product’s accuracy and spatial limitations in identifying building-specific damage and resolving decimeter-scale ground failure.
poster 77
New Earthquake Tsunami Preparedness Magazine forNorthern California
DENGLER, L. A., California State Polytechnic University, Humboldt,
California, USA, lad1@humboldt.edu; OZAKI, V., California State
Polytechnic University, Humboldt, California, USA, vicki.ozaki@gmail.com;
UYEKI, A., California State Polytechnic University, Humboldt, California,
USA, akuyeki@gmail.com
The Redwood Coast Tsunami Work Group released a new edition of “Livingon Shaky Ground” on the anniversary of the December 20, 2022, M 6.4
Ferndale earthquake. This is the 7th edition and fourth major revision of themagazine first published in 1993 in response to the 1992 Cape Mendocino
earthquakes. The magazine series is aimed towards residents and visitors of
the predominantly rural part of California north of Santa Rosa and includes
background on what causes earthquakes and tsunamis, what to expect, andhow to prepare for them. From inception, the Shaky Ground magazines havefocused on positive messaging and clearly outlining steps everyone can taketo become more resilient. There were three goals in the 2023 edition: update
earthquake and tsunami information, include sections on new technologies
and programs, and make the magazine more readable, accessible, and inclusive. The timeline now includes the three significant earthquakes that haveoccurred in the region and adjacent offshore areas since the previous edition
and a section on the Ferndale earthquake. Also added is a section on the tsunami hazards from the 2022 Tonga volcanic explosion. The new magazine
features a page on what ShakeAlert is, what to expect, and how to react. It
also includes expanded sections on children, the mobility challenged, andmitigation programs such as Brace and Bolt, and CERT teams. In response to
the most frequently questions, pages have been added on earthquake basics
including magnitude and aftershocks, and common misconceptions. To makethe magazine more readable and attractive, the font size has been increased,
four pages added, two thirds of the illustrations/photographs replaced, andpeople of diverse backgrounds featured. The intended audience is the generalpublic, but the magazine also serves as a guidebook for regional outreach programs including CERT training and will become part of our on-line K-12 curriculum program. The magazine is currently available electronically at https://
rctwg.humboldt.edu/home, a Spanish translation is in progress, and print versions will be available in early 2024.
poster 78
Integration of Seismic Monitoring and Involvement ofCivil Protection Volunteers for an Effective PostEarthquake Response
CAMASSI, R., Istituto Nazionale di Geofisica e Vulcanologia - INGV,
Bologna, Italy, romano.camassi@ingv.it; FAENZA, L., Istituto Nazionale
di Geofisica e Vulcanologia - INGV, Bologna, Italy, licia.faenza@ingv.it;
ERCOLANI, E., Istituto Nazionale di Geofisica e Vulcanologia - INGV,
Bologna, Italy, emanuela.ercolani@ingv.it; BRUNELLI, M., Civil Protection
Emilia-Romagna, Bologna, Italy, marco.brunelli@regione.emilia-romagna.
it; PONDRELLI, S., Istituto Nazionale di Geofisica e Vulcanologia - INGV,
Bologna, Italy, silvia.pondrelli@ingv.it; BACCI, L., Civil Protection EmiliaRomagna, Bologna, Italy, lorenzo.bacci@regione.emilia-romagna.it
After a significant seismic event, timely identification of severely affectedareas is crucial to coordinate support actions for the population. INGV, in
collaboration with OGS, theNational Institute of Oceanography and AppliedGeophysics, has established a close partnership with Emilia Romagna’s
Regional Civil Protection Agency to develop an innovative real-time monitoring strategy. Since 2019, a network of civil protection volunteers has been
implemented to monitor earthquake effects. Volunteers, previously trained
through a cooperative learning process, respond to a targeted questionnaire,
providing data on the perception of the event’s impact on specific locations.
This active learning approach directly involves volunteers in the process, facilitated by seismologists, promoting practical and lasting learning.
Thanks to the participation of volunteers already involved in risk communication projects, the project effectively connects with local communities.
The project has a dual purpose: on the one hand, data collected by volunteers
are transformed into macroseismic intensity and integrated into ShakeMap in
real-time, improving its spatial coverage. On the other hand, the project acts
as a social bond, strengthening the connection between the population andlocal authorities and monitoring entities. The success of this initiative has led
to the expansion of the project to other Italian regions, with the future goal of

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covering the entire national territory. The synergy between seismic monitoring and active community involvement proves to be a promising model for a
rapid and inclusive response in post-seismic situations.
poster 79
Applying ShakeCast to Monitor Earthquake Hazards for
Pipeline Infrastructure
HILLE, M., BGC Engineering Inc., Colorado, USA, mhille@bgcengineering.
ca; ZELLMAN, M., BGC Engineering Inc., Colorado, USA, mzellman@
bgcengineering.ca; MODNEY, T., BGC Engineering Inc., Edmonton,
Canada, tmodney@bgcengineering.ca; WIDMANN, B., BGC Engineering
Inc., Colorado, USA, bwidmann@bgcengineering.ca; DUCKWORTH, W.,
BGC Engineering Inc., Colorado, USA, cduckworth@bgcengineering.ca;
ZALESKI, M. P., BGC Engineering Inc., Vancouver, Canada, mzaleski@
bgcengineering.ca; TEELUCKSINGH, M., BGC Engineering Inc., Vancouver,
Canada, mteelucksingh@bgcengineering.ca; FRAZIER, J., BGC Engineering
Inc., Colorado, USA, jfrazier@bgcengineering.ca
Earthquakes threaten buried pipelines through multiple modes of grounddeformation, including liquefaction, coseismic landsliding, surface fault displacement, and ground shaking. The 2019 Pipelines and Hazardous Materials
Administration “Mega Rule” (49 CFR § 192.613) requires natural gas transmission pipeline operators to inspect their pipelines within 72 hours of an
extreme event that has the potential to impact pipelines via soil deformation,
including earthquakes. Pipeline operators in the US are therefore in need ofan earthquake monitoring system that can rapidly alert when a potentiallydamaging earthquake occurs in the vicinity of their pipeline asset.
BGC Engineering has integrated the USGS ShakeCast product into ourgeohazard management software, CambioTM, to aid operators in monitoring for earthquakes and to support post-event response. ShakeCast ingests
ShakeMaps in near-real-time and compares shaking intensity against damage thresholds at locations of interest. The Cambio-ShakeCast module alerts
operators with threshold exceedance related to potential damage to buried
pipelines, either directly through transient pipe strain induced by seismic
wave propagation, or indirectly from liquefaction, coseismic landsliding, or
fault rupture. We monitor for threshold exceedance at points spaced at regular intervals along the pipeline and at mapped locations where the pipelinecrosses terrain susceptible to liquefaction and coseismic landsliding, or known
locations of active surface faults. Ground shaking thresholds were developed
considering case histories of earthquake-induced pipeline damage, industry
standards for seismic design and hazard assessments, and operator experiences. Recommended alert responses range from “information-only” to “prepare for immediate response” and are tailored to specific operator programsand the requirements of the Mega Rule. The integration of ShakeCast into
Cambio addresses the pressing need from US pipeline operators for earthquake monitoring and creates an opportunity for continued innovation andas ShakeCast develops and we learn from operator experiences and responses.
poster 80
Making the Crowdsourced “Did You Feel It?” System More
Accessible: A Global Analysis
KNODEL, E. J., U.S. Geological Survey, Colorado, USA, eknodel@usgs.
gov; LOOS, S., University of Michigan, Michigan, USA, sloos@umich.
edu; QUITORIANO, V., U.S. Geological Survey, Colorado, USA, vinceq@
contractor.usgs.gov; WALD, D., U.S. Geological Survey, Colorado, USA,wald@usgs.gov
The U.S. Geological Survey’s (USGS) ‘Did You Feel It?’ (DYFI) system is aninternet tool that collects shaking intensity observations through crowdsourcing. It produces maps and provides supplementary data to ShakeMap, which
offers near-real-time maps of ground motion resulting from significant earthquakes around the globe. However, barriers such as technology and language
make DYFI an unequally accessible tool, which can lead to a limited scientificunderstanding of an earthquake’s impact in certain regions. Here, we analyze
users’ global interaction with DYFI to evaluate its accessibility. We employ web
analytics to quantify how users access DYFI and perform inference modelingto predict each country’s response rate to DYFI. The panel dataset built for thismodel combines physical earthquake parameters from the USGS with socioeconomic variables from the World Bank and the Central Intelligence Agency
for 151 countries from 2009 to 2020. Our web analytics show that users predominantly access DYFI through mobile devices. Additionally, results fromthe inference model reveal that socioeconomic parameters, including primarylanguage spoken and GDP per capita, alongside physical earthquake parameters such as average shaking intensity, have a significant effect on a country’s
response rate to DYFI. As a result of these two forms of analysis, we establish
a tiered ranking of countries to prioritize for improved DYFI awareness andVolume 95•

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accessibility. This ranking considers regions of the world lacking seismic station coverage that face barriers to DYFI access, such as language, technology,
or other factors. Consequently, the USGS has prioritized the evaluation of
DYFI’s performance on mobile devices and has initiated the incorporation of
additional languages into the DYFI system. Furthermore, our analyses suggest
specific nations with low response rates could benefit from targeted outreachin conjunction with sister agency partners in each country.
poster 81
Global Structural Health Monitoring via MyShake: An
Economical and Accessible Smartphone-Based Approach
KUMAR, U., University of California, Berkeley, California, USA,
utpalkumar@berkeley.edu; MARCOU, S., University of California, Berkeley,
California, USA, savvas.marcou@berkeley.edu; PATEL, S., University ofCalifornia, Berkeley, California, USA, sarina.patel@berkeley.edu; ALLEN, R.
M., University of California, Berkeley, California, USA, rallen@berkeley.edu
Structural Health Monitoring (SHM) is essential for the safety, reliability, andcost-effectiveness of structures over their lifespan. Traditional SHM methods
rely on custom sensor deployments, requiring significant time, manpower,
and resources. However, the ubiquity of smartphones with accelerometerspresents a unique opportunity for widespread, affordable SHM. We showcase
the MyShake smartphone app, developed at UC Berkeley and part of the Early
Warning California initiative. This free app, downloaded globally over 2.9 million times, utilizes smartphone accelerometers to monitor civil infrastructure
health through waveform recordings during significant shaking events.
MyShake leverages these smartphones to form a rapid-response network
for monitoring civil structures. During events such as earthquakes and severe
weather, stationary MyShake phones record and transmit seismic data. Since
these phones are usually inside buildings, the data can reveal structural behavior. The app’s ability to gather data enables us to assess the structural integrityof buildings where users are located.
Our controlled experiments validate this method, resulting in a database of modal frequencies from various buildings. Continuously monitoringthese frequencies allows us to detect changes that may signal structural damage. Thus, MyShake offers a scalable, cost-effective solution for global SHM,
enhancing civil structure safety and reliability. We also discuss scientific andtechnical challenges in large-scale operational deployment and suggest potential solutions.
poster 82
ShakeCast: Pivoting USGS Products to Respond to User
Needs
LIN, K., U.S. Geological Survey, Colorado, USA, klin@usgs.gov; CHEECK,
L., U.S. Geological Survey (contractor), Colorado, USA, lcheek@contractor.
usgs.gov; SMITH, K. K., U.S. Geological Survey, Colorado, USA, kksmith@usgs.gov; THOMPSON, E. M., U.S. Geological Survey, Colorado, USA,emthompson@usgs.gov; WALD, D., U.S. Geological Survey, Colorado, USA,wald@usgs.gov
ShakeCast® is a U.S. Geological Survey (USGS) software application that
automatically retrieves ShakeMap shaking estimates and performs analyses
using fragility functions for buildings and lifelines, developed with support
from external organizations interested in using ShakeMap for automatic
decision-making. The ShakeCast system identifies which facilities or lifeline segments are most likely impacted by an earthquake—and thus whichshould be prioritized for inspection and response—and sends notifications
to responsible parties in the minutes after an event. ShakeCast can improvecritical lifeline situational awareness, inspection prioritization, and reduce
response times after a significant earthquake by focusing inspection efforts on
the most damage-susceptible facilities in severely shaken areas. Improvements
to ShakeCast are done in conjunction with upgrades to the ShakeMap application. As a user-focused application, ShakeCast’s initial specifications weredeveloped working iteratively with the California Transportation Department(Caltrans). Caltrans became ShakeCast’s primary early adopter and promoter
among other agencies and utilities. Later, feedback and engagement with othercritical lifeline and facility users guided technical innovations and productmodifications. However, the practicalities of any automatic application, with
operational complexities that are not necessarily user-friendly, can be technically challenging for some users. In this presentation, we focus on balancing robust and secure operational applications with the needs of critical users
with a wide range of technical abilities and computational environments. We
also provide an update to the technical specifications regarding the code base,dependencies, documentation, and deployment options. Lastly, we highlightrecent ShakeCast case histories where critical infrastructure users employed
the ShakeMap/ShakeCast combination in their decision-making.

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poster 83
Guidelines on Using (Uncertain) Macroseismic Data in
ShakeMap
QUITORIANO, V., U.S. Geological Survey, California, USA, vinceq@
contractor.usgs.gov; WALD, D. J., U.S. Geological Survey, Colorado, USA,wald@usgs.gov; WORDEN, C. B., U.S. Geological Survey, Colorado, USA,cbworden@contractor.usgs.gov; THOMPSON, E. M., U.S. Geological Survey,
Colorado, USA, emthompson@usgs.gov
The U.S. Geological Survey (USGS) collects macroseismic intensity (MI) datafrom users worldwide through the “Did You Feel It?” (DYFI) system. DYFI isa primary MI source for USGS ShakeMap, which combines ground motion
data with rupture parameters, site conditions, and ground motion models(GMMs) to estimate the spatial distribution of ground shaking. Despite theirutility in ShakeMap, the potential for outliers and larger uncertainties makes
it challenging to include crowdsourced intensity data operationally. We report
here on developing guidelines for incorporating crowdsourced MI data into
ShakeMap. We take advantage of our newly developed MI database to reassess the uncertainty of the MI assignment as a function of intensity and thenumber of responses (nresp), demonstrating that higher intensities have more
uncertainty. This is consistent with the known challenge of assigning higher,
damaging intensity levels, even by experts. From an operational perspective,
crowdsourced MIs are more consistent at lower intensities and can be readily
used automatically. Higher intensities, particularly with few entries per locale,
are more uncertain and require further downweighing with respect to othershaking estimates. We approach this problem with two strategies to quantify
uncertainties: 1) We analyze MI residuals to understand trends with nresp,
MI, and the source of the MI data (e.g., DYFI, historical, or assigned), thenassign MI uncertainties as a function of intensity by adding (heuristically) a
constant such that the relative weight of the macroseismic data for a single
response approaches that of the GMM contribution. 2) We simulate the richMI databases using a Monte Carlo approach to ensure that the uncertainty
assessments are consistent with the levels of variability observed in the data.
poster 84
Creating Earthquake Early Warning Post-Alert Information
Products: Harnessing Existing Earthquake Information
Tools to Depict Alerting Efficacy
SAUNDERS, J. K., California Institute of Technology, California, USA,jsaunder@caltech.edu; WALD, D. J., U.S. Geological Survey, Colorado, USA,wald@usgs.gov
Here, we leverage existing post-earthquake information products to exploreand develop graphical representations that depict earthquake early warning(EEW) alert performance, targeting components that will satisfy both technical and public audiences. Existing post-earthquake information products(including ShakeMap, “Did You Feel It?” [DYFI], and PAGER) offer provenexamples of communicating the complexity of earthquake shaking and its
impacts. Communicating the efficacy (accuracy and timeliness) of EEW alerts
brings additional challenges, as quantifying and summarizing alert timeliness are not straightforward. For EEW systems like the ShakeAlert system
for the West Coast of the United States, EEW alert information is updated as
the earthquake progresses and alerts are issued via multiple platforms using
various alert thresholds, so no single map can readily communicate EEW alert
efficacy. We thus need to reconcile comprehensive reporting against agreeable visualizations. By considering ShakeMap shaking estimates—constrainedby DYFI-reported intensities and station observations—as a baseline forground-truth experiences, we quantify how many potential recipients there
were of timely versus late and missed alerts with respect to the actual shaking experienced. The maps and other visualizations we propose could be afirst step toward communicating objective and quantifiable alerting successes
while putting the alerting challenges into a spatial perspective. Coupled with
reports of users’ alerting experiences, reactions, and perceived utility (Goltz
et al., this meeting), we can examine EEW alerting efficacy quantitatively andqualitatively. By leveraging existing, familiar technologies and data alreadyproduced—augmented with depictions of warning timeliness—post-event
EEW information follow-up products we put forward could be both intuitiveand informative, helping people connect what just happened regarding EEWalerts with the shaking they felt from the earthquake.
poster 85
A Framework for Implementing a New Intensity Metric for
USGS’s Shakemap: Cumulative Absolute Velocity (CAV)SMITH, K., U.S. Geological Survey, Colorado, USA, kyle36smih85@
gmail.com; THOMPSON, E. M., U.S. Geological Survey, Colorado, USA,emthompson@usgs.gov; WORDEN, C. B., U.S. Geological Survey, Colorado,

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USA, cbworden@contractor.usgs.gov; WALD, D., U.S. Geological Survey,
Colorado, USA, wald@usgs.gov
The U.S. Geological Survey’s (USGS) ShakeMap has been providing rapid,
global estimates of earthquake shaking characteristics for decades. USGS has
provided ground shaking characteristics as maps of intensity measures (IM)such as peak ground velocity, peak ground acceleration, spectral acceleration (at three periods), and macroseismic intensity. These products have beeneffectively used by emergency managers, loss modelers, engineers concerned
about post-event structural performance, and even for insurance products.
However, more advanced IMs offer important benefits for characterizing the
ground shaking intensity by accounting for energy and duration of shaking,which have the potential to be useful for applications that include assessing
the potential for failure involving landslides, liquefaction, and critical infrastructure. These metrics include cumulative absolute velocity (CAV), Arias
intensity, significant duration, and permanent static displacement. We present
a framework for implementing CAV in ShakeMap. There are numerous models to estimate CAV, because they were developed for specific regions and tectonic environments. We start by developing a database of recorded CAV values for a specific region along with predicted CAV values from ground motion
models (GMMs). We use OpenQuake to predict CAV values with GMMs,
but since many GMMs of CAV are not currently available in OpenQuake, wemust contribute them. Since the USGS produces ShakeMaps on a global scale,
it is imperative that we test and expand the suitability of the models for all
possible regions and tectonic environments, which can then be done for otherIMs. We expect our work to improve hazard assessment of landslides, liquefaction, and infrastructure, and advance earthquake science and operations.

Cryptic Faults: Advances in Characterizing Low Strain
Rate and Environmentally Obscured Faults
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Theron Finley, University of Victoria (tfinley@uvic.ca); Tiegan Hobbs, Geological Survey of Canada (tiegan.
hobbs@NRCan-RNCan.gc.ca); Barrett Salisbury, Alaska
Division of Geological & Geophysical Surveys (barrett.
salisbury@alaska.gov); Lydia Staisch, U.S. Geological Survey(lstaisch@usgs.gov)
An Ongoing Search for Active Faults in Major Seismic
Zones of Québec, Eastern Canada
GOURDEAU, A., McGill University, Montréal, Canada, aubegourdeau@
gmail.com; WANG, K., Brown University, Rhode Island, USA, kaiyuan_
wang@brown.edu; LALY, M., Canadian Coast Guard College, Sydney,
Canada, maximilien.laly@dfo.mpo.gc.ca; PRUSH, V. B., New Mexico Instituteof Mining and Technologies, New Mexico, USA, veronica.prush@nmt.edu;
ROWE, C., McGill University, Montréal, Canada, christie.rowe@mcgill.
ca; NACKERS, C., Polytechnique Montréal, Montréal, Canada, claudine.
nackers@polymtl.ca; MARK, H., Woods Hole Oceanographic Institution,
Massachusetts, USA, hmark@whoi.edu; MORRIS, I., New Mexico Instituteof Mining and Technologies, New Mexico, USA, isabel.morris@nmt.edu;
ROSSET, P., McGill University, Montréal, Canada, philippe.rosset@affiliate.
mcgill.ca; LAMOTHE, M., Université du Québec à Montréal, Montréal,
Canada, lamothe.michel@uqam.ca; TARLING, M., McGill University,
Montréal, Canada, tarlingmatthew@gmail.com; CHOUINARD, L., McGill
University, Montréal, Canada, luc.chouinard@mcgill.ca
Southern Québec lies in an intracratonic setting that has experienced historical damaging earthquakes (e.g. 1732 M5.8 Montréal, 1663 M7 Charlevoix,
1935 M6.2 Témiscamingue). Despite the fact that approximately half ofQuébec’s population lives within one of the identified seismic zones, no studies to date have identified surface-rupturing faults. The lack of paleoseismic
datasets and specific earthquake source scenarios impedes hazard estimatesand risk preparedness, and is due in part to the province’s very young geomorphic surface. Since the last glacial maximum at ~21 ka, marine and lacustrine
deposition dominated until a few thousand years ago, removing much of the
Quaternary record of fault activity.
The study aims to develop a systematic criteria for fault scarp identification in this low-relief, deglaciated landscape, by adapting criteria usedin the Fennoscandian Peninsula. We manually searched 2016 lidar-derived
digital elevation models (DEMs) within three populated seismic zones to
identify potential post-glacial surface-rupturing faults. We present the firstwww.srl-online.org•

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geomorphic map of possible post-glacial fault scarps in Québec. One scarp
was investigated with geophysical surveys, and we excavated the first paleoseismic trench in Québec, which did not find evidence of Quaternary faulting.
This study paved the way for paleoseismic studies in the province and createda network of geoscientists/governmental agencies aware of, and invested in,paleoseismic studies. We hope our study can be used to optimize future paleoseismic research in the province of Québec and similar intracratonic deglaciated landscapes.
Timescales of Surface Faulting Preservation in Stable
Continental Regions From Landscape Evolution Modelingand the Geomorphic and Historical Record
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; REITMAN, N., U.S. Geological Survey, Colorado, USA, nreitman@
usgs.gov
Large surface-rupturing intraplate earthquakes in stable continental regions
are infrequent, with recurrence intervals of thousands to hundreds of thousands of years. The landscape preservation of surface ruptures is controlled
by many factors, including earthquake depth, magnitude, and recurrence
interval, climate, anthropogenic modification, and pre-existing topography
or geomorphology. As such, recurrence intervals—and therefore seismic hazard—may be biased or inaccurate from the landscape record alone. In thisstudy, we take a two-pronged approach to better understand how surface ruptures of primarily dip-slip events may be preserved in the landscape. First, we
use a 2D scarp diffusion model to explore how different parameters influence
the creation and erosion of fault scarps. These parameters include the magnitude of surface rupture vertical offset (likely related to depth and magnitude offaulting), climate (using diffusion rate as a proxy for precipitation), erodibility(related to underlying surface material), and recurrence interval of similar
magnitude events. Second, we compile information on historical surface ruptures in intraplate settings in a variety of climates, including the central andeastern North America, Australia, Europe, Mongolia, India, and West Africa.
We then use data from the compilation to assign parameter value ranges forthe models. We use vertical offsets of 30 to 300 cm, recurrence intervals of 500
yr to 20 kyr, diffusion rates of 0.001 to 0.01 m2/yr, and erodibility values from0.001 to 0.006 yr-1 on both flat and sloping surfaces with cm- and m-scaleroughness. We find that recurrence interval and erodibility strongly influence
the timescales of scarp preservation in the landscape, whereas vertical offset
and climate have less influence. We compare the timescales of scarp preservation in the landscape evolution modeling results with observations from thehistorical and paleoseismic record. This study highlights the factors influencing scarp preservation in intraplate settings and implications for calculating
the seismic hazard of a region based on the landscape record.
The 2018 Kaktovik, Alaska Earthquakes and Their Context:
Insights From Seismotectonics, Insar Geodesy, and StaticStress Changes
ROLLINS, C., GNS Science, Kelburn, New Zealand, c.rollins@gns.cri.nz;
FREYMUELLER, J. T., Michigan State University, Michigan, USA, freymuel@msu.edu; XUE, X., Michigan State University, Michigan, USA, xuexuemi@
msu.edu; HOLTKAMP, S. G., University of Alaska Fairbanks, Alaska, USA,stephen.holtkamp@gmail.com; LOGAN, T. A., University of Alaska Fairbanks,
Alaska, USA, talogan@alaska.edu; MEYER, F. J., University of Alaska
Fairbanks, Alaska, USA, fjmeyer@alaska.edu; PATTON, J. R., California
Geological Survey, California, USA, jason.patton@conservation.ca.gov
On August 12, 2018, a Mw=6.4 earthquake struck in the northeast Brooks
Range southwest of Kaktovik, Alaska, followed by a Mw=6.0 event to the east
six hours later and a multi-year-long aftershock sequence. Although they fortunately caused no injuries or damage, the Kaktovik earthquakes are notable
for at least five reasons: 1) they occurred just south of the petroleum-rich 1002
Area of the Arctic National Wildlife Refuge; 2) they dwarf the previous largest
earthquakes recorded in Arctic Alaska (M=5.3-5.4); 3) they occurred ~1,000
km from the southern Alaska convergent margin in a presumably low-strainrate region; 4) their strike-slip character contrasts with their geologic setting
in a fold-and-thrust belt; and 5) the USArray Transportable Array and theSentinel-1A satellite pair allow them to be studied in high temporal and spatial resolution. We first examine the seismotectonic context and evolution of
the Kaktovik sequence by assembling an integrated earthquake catalogue fornortheast Alaska from eight sources. The catalogue reveals a history of seismicity in the northeast Brooks Range (including many strike-slip events), as
well as a possible uptick in seismicity rate around the eventual epicenter of thesecond large (Mw=6.0) Kaktovik earthquake in the half-hour or so preceding
it. To assess how the Kaktovik earthquakes fit into their seismotectonic context, and how they might modulate future seismicity through stress transfer,

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we use Interferometric Synthetic Aperture Radar (InSAR) to build slip modelsof the earthquakes. The InSAR displacements can be fit well by slip on a planar rupture based on the focal mechanism of the Mw=6.4 event and a lineation observed in the ascending-track interferogram, or a nonplanar rupture
built from features of the descending-track interferogram. Using these two
slip models, we calculate that the Kaktovik sequence slightly increased the
Coulomb stress ~50 km to the south at the site of a subsequent Mw=5.3 earthquake in July 2019, and also increased Coulomb stress on faults to the northand/or northwest towards the coast.
Deciphering Low-Rate Faulting on the Landscape Above
the Marsh Creek Anticline in Arctic Alaska
BENDER, A. M., U.S. Geological Survey, Alaska, USA, abender@usgs.gov;
CRADDOCK, W., U.S. Geological Survey, Virginia, USA, wcraddock@usgs.
gov; CONNORS, C. D., U.S. Geological Survey, Virginia, USA, cconnors@
usgs.gov; GOOLEY, J., U.S. Geological Survey, Alaska, USA, jgooley@usgs.
gov; LEASE, R. O., U.S. Geological Survey, Alaska, USA, rlease@usgs.gov
In regions of rapid contractional deformation (≥1 mm/a), rivers adjust to
earthquake-induced differential rock uplift by steepening, narrowing, and/or
incising terraces. Such landscape signatures constrain the location and millennial tempo of active faulting but may be subdued or absent where tectonic
rates are low. Hence, understanding how rivers interact with low-rate tectonic
deformation is key to characterizing long-term seismic potential where strong
earthquakes are infrequent but nonetheless destructive. For example, ~1000
km north of the 53 mm/a Yakutat-North America collision at Alaska’s southern margin, the northeastern Brooks Range hosts low geodetic velocities (<1mm/a) but strong historic earthquakes (≤Mw 6.4). There, we are conducting
a geomorphic study of a composite structure long thought to take up muchof the contemporary tectonic budget and termed the Marsh Creek anticline.
Topographic profiles reveal a north-dipping limb with ~100 m of relief,
implying monoclinal surface folding above a north-dipping blind thrust fault
imaged in seismic reflection data. The Katakturuk River and Marsh Creekdrain the Brooks Range upstream of the fold and traverse the structure’s
topographic crest on the Arctic Coastal Plain, where both rivers cut ≤60 m
into weak Paleogene strata and bend ≤3 km west, leaving three inner bend
fill terrace levels ≤16 m above the channel. Absent downstream changes inchannel slope or width, we hypothesize that episodic differential uplift acrossthe Marsh Creek structure reduces river gradients upstream of the fold, driving aggradation of coarse bedload from upstream and forcing the channel toerode westward and vertically into friable Paleogene strata, thus producing
river bends and progressively abandoning fill terraces. We collected cosmogenic 10Be samples to constrain erosion rates upstream of the fold and, inconcert with 14C and luminescence dating, bracket timing of terrace abandonment and incision rates. Results will test our hypothesis that the observed
landscape records sediment production upstream of the fold that outpaces
earthquake-induced incision.
Utilising UAV Lidar to Investigate Potential Late
Quaternary Surface Ruptures Along the San Juan Fault on
Vancouver Island, BC
SALOMON, G. W., University of Victoria, Victoria, Canada, guysalomon@
uvic.ca; FINLEY, T., University of Victoria, Victoria, Canada, tfinley@uvic.ca;
NISSEN, E., University of Victoria, Victoria, Canada, enissen@uvic.ca
Identifying active crustal faults within the northern Cascadia forearc ischallenging due to low rates of recorded seismicity, late Quaternary glacial
scouring, and dense vegetation that often obscures fault-related geomorphology. However, recent research has identified surface ruptures along theLeech River, Beaufort Range, and XEOLXELEK-Elk Lake faults on southern
Vancouver Island, which each pose a considerable risk to the >500,000 people
that live in this area. We investigate the San Juan Fault (SJF), another putative
active fault within this region. The SJF is an 80 km long, E-W striking, terranebounding fault, which displays a conspicuous topographic lineament similar
to the known-active Leech River fault located ~10 km to the south. Originallya collisional suture between the Wrangellia and Pacific Rim terranes, it is last
known to have accommodated left-lateral slip during the Eocene driven byaccretion of the outboard Crescent-Siletz terrane. The position of the SJF in
the forearc of the active Cascadia subduction, its favourable orientation relative to the regional stress field, and its strong topographic signature have led
some to hypothesise that it is seismically active, but no convincing evidence
has been found yet. We utilise both airborne lidar and uncrewed aerial vehicle(UAV) lidar to map the surface trace of the SJF. The UAV lidar is capable ofcollecting much higher density point clouds (2-3X that of conventional airborne lidar) and thus produce sub-meter resolution bare earth models, allowing for identification of fine-scaled features. A scarp-like feature is evident

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in the lidar data, but it is unclear whether it records Quaternary surface rupture or differential erosion during glaciation, a challenge commonly faced bytectonic geomorphologists working in previously glaciated terrain. We lookfor evidence of late Quaternary reactivation along the eastern half of the SJF(offsets to glacial landforms and river channels, and scarp morphology) andconsider sites where paleoseismic studies could confirm a tectonic origin.

4000 years BP (10 events before, 22 events after). This may reflect preservation, but all of the fault zones have terrestrial stratigraphic records that extend
to the late glacial, suggesting the post-glacial stratigraphic record along eachfault zone is complete. Paleoseismic recurrence broadly agrees with recurrence calculated using geodetic data, while recurrence estimated from seismic
catalogs is shorter.

Late Pleistocene and Protohistoric Earthquakes on
Forelimb Thrusts Within the Seattle Fault Zone:
Implications for Independent Hanging Wall Deformation
Rates
ANGSTER, S., U.S. Geological Survey, Washington, USA, sangster@usgs.gov;
SHERROD, B. L., U.S. Geological Survey, Washington, USA, ssherrod@usgs.
gov; STAISCH, L., U.S. Geological Survey, Oregon, USA, lstaisch@usgs.gov;
PEARL, J. K., The Nature Conservancy, Arizona, USA, jessie.pearl@TNC.
ORG; JOHNS, W., Lettis Consultants International, California, USA, johns@
lettisci.com

Towards Improved Understanding of Regional Tectonics
and Faulting at the Mendocino Triple Junction from
Geomorphic Investigation
DELONG, S., U.S. Geological Survey, Minnesota, USA, sdelong@usgs.gov;
VERMEER, J., U.S. Geological Survey, California, USA, jvermeer@usgs.gov;
PATTON, J. R., California Geological Survey, California, USA, jason.patton@conservation.ca.gov; SION, B., Desert Research Institute, Nevada, USA,
brad.sion@dri.edu; HAMMER, M., U.S. Geological Survey, California, USA,mhammer@usgs.gov; TREXLER, C., U.S. Geological Survey, California, USA,
ctrexler@usgs.gov; HEMPHILL-HALEY, M., California State Polytechnic
University, Humboldt, California, USA, mark@humboldt.edu; KELSEY, H.,
California State Polytechnic University, Humboldt, California, USA, hmk1@
humbolt.edu; LEROY, T., Pacific Watershed Associates, California, USA,
toml@pacificwatershed.com; ROBINSON, M., Pacific Watershed Associates,
California, USA, micheller@pacificwatershed.com; MCPHERSON, R.,
California State Polytechnic University, Humboldt, California, USA, bomac@
humboldt.edu; MCLAUGHLIN, R., U.S. Geological Survey, California, USA,
rjmcl@usgs.gov

The Seattle fault zone (SFZ) preserves a long-term deformation record ofnorth-directed reverse faulting, although the majority of paleoseismic studies show evidence for multiple Holocene ruptures on ancillary bedding planebackthrusts within the hanging wall fold of the main fault. These paleoseismic
studies elucidate the complex nature of hanging wall deformation within the
SFZ and motivate our approach for evaluating fault-related folds for seismic
hazard. In this study, we focus on two recently identified <2 km-long fault
scarps located ~30 km apart along the SFZ that, unlike the previously studied south-facing scarps of the north-dipping backthrusts, are north-facing
and spatially correlative with the main blind fault traces of the SFZ. Throughgeomorphic mapping, paleoseismic trenching, Bayesian analyses of 14C ages,
and dendrochronology, we show that these north-facing scarps are underlain
by south-dipping thrusts that yield evidence of three earthquakes. The oldest earthquake identified within the trenches across each scarp temporally
overlap during the late Pleistocene but are likely separate events, while theyoungest is constrained to the late Holocene on the western-most scarp andis possibly Historic. To understand the structural significance of these faults
relative to the main blind fault(s) and backthrusts, we combine ground-basedmagnetic transects, oriented perpendicular to the fault scarps on Bainbridge
Island, with measured bedrock sections. Our analysis reveals that the highresolution magnetic signals reflect the lithologic variability in the underlying Tertiary bedrock. The main fault location is apparent from broad changes
in the magnetic data, but the fault scarps lack a distinct and coherent signal
between the two transects, suggesting that the north-facing fault scarp is alsoa fold-associated fault. Our results further emphasize the independent ruptureof the fold-associated faults, which also display shorter recurrence intervals
than the main fault(s) of the SFZ. This study highlights the cryptic nature ofassessing thrust and reverse fault systems for seismic hazard analysis
Recurrence of Large Upper-Plate Earthquakes in the Salish
Lowland, Washington State, USA
SHERROD, B. L., U.S. Geological Survey, Washington, USA, bsherrod@
usgs.gov; STYRON, R., GEM Foundation, Oregon, USA, richard.styron@
globalquakemodel.org
Our paleoearthquake database consists of 32 earthquakes over the last 15,000
years on ten fault zones in the Salish lowland (Elk Lake fault, Boulder Creek
fault, Bellingham coastal faults, Darrington-Devil’s Mountain-Leech Riverfault zone, North Olympics fault zone, Southern Whidbey Island fault zone,
Seattle fault zone, Canyon River-Saddle Mountain fault zone, Tacoma fault
zone, and Olympia fault zone). We take the OxCal modeled probability distributions for each earthquake age and calculate Highest Density Intervals(HDIs) for each earthquake. Subsequent Monte Carlo sampling used the HDIs
to calculate the order of earthquakes and recurrence intervals. Recurrence
calculations used earthquake pairs determined by the ordering analysis tosample recurrence intervals from the HDIs. The result is a large sample ofrecurrence intervals from the ordered earthquake pairs, from which we draw
summary values, including average recurrence interval (ARI). The Seattle
fault zone is the most active fault in the region (nine events) and has thesmallest ARI (1400±260 years); the largest earthquake of this sequence is the923CE earthquake. The next most active are the North Olympics fault zone
(four, possibly five events, ARI=2285±1195 years), and the Darrington-Devils
Mountain-Leech River fault zone (four events, ARI=3355±675). The ARI
across the region for all 32 events is 820±534 years.
Earthquakes ages have less error after 4000 years BP but dating quality declines for earlier events. This may be a function of preservation (not asmuch material to sample) and possibly sample quality (delicate plant fossils vs.
charcoal). We observe that overall earthquake rate apparently increases after

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Hazard associated with the transition from the dextral San Andreas Fault system to the Cascadia subduction zone in the Mendocino triple junction (MTJ)
region is complex and in need of ongoing research using up-to-date methods.
This area has high rates of seismicity and is characterized by an enigmatic network of faults having some combination of compressional and dextral motionthat has been difficult to constrain, perhaps complemented by diffuse shearing
and folding. The densely vegetated mountains, river valleys, and coast appear
to record strikingly variable patterns of tectonic uplift, subsidence, and fluvial
and coastal erosion that cause ongoing drainage divide shifts, unusual stream
channel longitudinal profiles, and variable amounts of topographic development. These patterns have also been indicated by geodetic surveys following
historic earthquakes. The geomorphic characteristics can be interrogated tounderstand the regional tectonics, which can in turn be used, in combination
with analysis of recently released lidar topographic data, to identify locationsof active faulting. We are currently working to generate a suite of catchment
erosion rates from cosmogenic isotope inventories within and adjacent to the
Mattole and Eel Rivers. We are mapping and dating uplifted fluvial terraces
along the Mattole and Eel Rivers, and marine terraces from along the MTJ
coast. This is complemented by generation of quantitative landscape metrics
including channel steepness index and chi. We are also mapping active fault
traces and expanding collaborative work on known high-potential paleoseismic sites. Our long-term objectives include better understanding of the connections between, and geometry of, the San Andreas, Maacama, and Bartlett
Springs Faults and the southern Cascadia onshore fault network, better
understanding of the linkages between tectonics, stream capture, and criticalanadromous fish habitat, and better understanding of how topographic development and fault activity are related, with an eye towards improving hazard
models.
Geophysical Validation of Tidally Calibrated Strains From
the Novel Alto Tiberina Near Fault Observatory
Strainmeter Array (TABOO-NFO-STAR)HANAGAN, C. E., U.S. Geological Survey, Colorado, USA, chanagan@usgs.gov; MANDLER, E., Istituto Nazionale di Geofisica e Vulcanologia,
Rome, Italy, eugenio.mandler@ingv.it; BENNETT, R. A., University of
Arizona, Arizona, USA, rb0@arizona.edu; CHIARALUCE, L., Istituto
Nazionale di Geofisica e Vulcanologia, Rome, Italy, lauro.chiaraluce@ingv.it;
GOTTLIEB, M., EarthScope Consortium, , USA, mike.gottlieb@earthscope.
org; GUALANDI, A., Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy, adriano.gualandi@ingv.it; HUGHES, A., University of Arizona, Arizona,
USA, anhughes@arizona.edu; WADE, J., EarthScope Consortium, , USA,
wade.johnson@earthscope.org; MENCIN, D., EarthScope Consortium, ,USA, david.mencin@earthscope.org; PIERDOMINICI, S., GFZ Potsdam,
Potsdam, Germany, simona.pierdominici@gfz-potsdam.deSix borehole tensor strainmeters, installed between Fall 2021 to Spring 2022,
comprise a strainmeter array along the Alto Tiberina fault system (STAR),
Italy. The array provides an opportunity to investigate deformation from seismic and aseismic slip on hazardous high- and low-angle normal faults. Prior
to use in tectonic applications, the strainmeters require in-situ calibrationwww.srl-online.org•

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and correction for non-tectonic signals. We tidally calibrate the instruments
and test the results against environmental signals and signals from coseismic
deformation associated with polarized compressional body waves and static
offsets originating from local to teleseismic distances. Calibrated analyses
demonstrate that the STAR sites deviate from typical assumptions of isotropic,
homogeneous conditions, with four of the six strainmeters (TSM3-6) exhibiting negative areal coupling that complicates analysis of surface loads. For
coseismic deformation, the results show interstation precision and accuracy
to nanostrain levels. Potential complications for interpreting deformation
at TSM3 may arise from dynamically triggered near-borehole fracture slip
and fluid flow, but apparently only in response to high strain rates, while low
strain rates remain consistent with our expectations. Although use of the tidal
calibrations seems valid for TSM1, 2, 3, 5, and 6, future improvement may bepossible as longer, stable timeseries become available, with particular attention to TSM4. Overall, the present analyses demonstrate expanded geodetic
capability for detecting nanostrain deformation in the Alto Tiberina Near
Fault Observatory, which other observatories have shown would be needed todetect slow, transient slip, and both coseismic and dynamic strain from local
to teleseismic earthquakes.
The Parguera Fault: Quaternary Reactivation of a Fault inSouthwest Puerto Rico
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.
gov; ORTEGA DIAZ, V., University of Puerto Rico at Mayagüez, Puerto Rico,
USA, victor.ortega4@upr.edu; HUGHES, K., University of Puerto Rico at
Mayagüez, Puerto Rico, USA, kenneth.hughes@upr.edu; LÓPEZ-VENEGAS,
A., University of Puerto Rico at Mayagüez, Puerto Rico, USA, alberto.lopez3@
upr.edu; LYNCH, E., U.S. Geological Survey, Colorado, USA, elynch@usgs.
gov; TAN, M., U.S. Geological Survey, Colorado, USA, mtan@usgs.gov;
MAHAN, S., U.S. Geological Survey, Colorado, USA, smahan@usgs.gov;
GRAY, H., U.S. Geological Survey, Colorado, USA, hgray@usgs.gov; SHAH,
A. K., U.S. Geological Survey, Colorado, USA, ashah@usgs.gov; PRATT, T.,
U.S. Geological Survey, Virginia, USA, tpratt@usgs.gov
Puerto Rico is located in a seismically active oblique plate boundary and has
experienced historical moderate to large earthquakes. However, the locationand kinematics of active faults on Puerto Rico remain mostly unclear. Here,
we present evidence of a previously unrecognized east-west-trending normal fault in southwest Puerto Rico, which we name the Parguera fault. At
the northwestern edge of seismicity from the 2019-ongoing southwest Puerto
Rico seismic sequence, near the coastal town of La Parguera, we mapped a setof east-west oriented scarps that cross multiple generations of alluvial fans.
Our mapping consists of both remote, sub-meter resolution lidar-derived topographic interpretations and field observations. We also apply optically stimulated luminescence (OSL) geochronology and subsurface datasets (ground
penetrating radar and aeromagnetic data).
The scarps mapped on the lidar-derived topography are discontinuous,cross elevation contours, and extend at least 12 km laterally, with up to a 2 m,
primarily down-to-the-south vertical offset of geomorphic surfaces. In someplaces, the scarp coincides with a pre-existing unnamed bedrock fault that
separates Cretaceous basalts and Parguera limestone or juxtaposes different
Cretaceous basalt units. The scarp location is also consistent with discontinuities in subsurface data, supporting the presence of a fault at depth, whereaeromagnetic data highlight discontinuities in the underlying basement rocks
coincident with the mapped scarps. Based on field observations, the faulted
alluvial fans may be correlative with previously mapped Holocene-age fansalong the southern flank of the Lajas Valley, just a few km to the north, which
we hope to confirm with pending OSL ages. We interpret that the scarps
across possible Holocene-age fans, supported by subsurface data, indicate thepresence of a previously unrecognized Quaternary-active normal fault that
may represent reactivation of an older bedrock fault. Evaluation of this feature
will serve to improve our understanding of the seismic hazards and tectonic
history of Puerto Rico.

Cryptic Faults: Advances in Characterizing Low Strain
Rate and Environmentally Obscured Faults [Poster
Session]Poster Session • Wednesday 1 May
Conveners: Theron Finley, University of Victoria (tfinley@uvic.ca); Tiegan Hobbs, Geological Survey of Canada (tiegan.
hobbs@NRCan-RNCan.gc.ca); Barrett Salisbury, Alaska
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Division of Geological & Geophysical Surveys (barrett.
salisbury@alaska.gov); Lydia Staisch, U.S. Geological Survey(lstaisch@usgs.gov)
poster 86
Seismic Imaging and Structure of the West Napa Fault
Near Calistoga, California
CHAN, J. H., U.S. Geological Survey, California, USA, jchan@usgs.gov;
CATCHINGS, R. D., U.S. Geological Survey, California, USA, catching@usgs.
gov; GOLDMAN, M. R., U.S. Geological Survey, California, USA, goldmark@usgs.gov; PHILIBOSIAN, B. E., U.S. Geological Survey, California, USA,bphilibosian@usgs.gov; SICKLER, R. R., U.S. Geological Survey, California,
USA, rsickler@usgs.gov; CRILEY, C. J., U.S. Geological Survey, California,
USA, ccriley@usgs.gov; VERMEER, J., U.S. Geological Survey, California,
USA, jvermeer@usgs.gov; SAMUEL, D., U.S. Geological Survey, Louisiana,
USA, dsamuel@usgs.gov; GOMEZ, A., U.S. Geological Survey, California,
USA, agomez@usgs.gov; CUNETTA, N., U.S. Geological Survey, California,
USA, ncunetta@usgs.gov; COMSTOCK, K., U.S. Geological Survey,
California, USA, kcomstock@usgs.gov; CHAFFEUR, J., U.S. Geological
Survey, California, USA, jchaffeur@usgs.gov
The 24 August 2014 Mw 6.0 South Napa, California, earthquake caused extensive structural damage in the City of Napa, California. The causative fault,
the West Napa Fault (WNF), continues northward from the City of Napa toSaint Helena, California, and post-earthquake investigations suggest an additional fault section extending past Calistoga. We evaluated the structure andgeometry of the WNF near Calistoga, California by conducting an activesource, high-resolution (2-m shot and receiver spacing) seismic imaging survey across the suspected trace of the fault. We deployed two parallel seismicarrays using 3-component nodal seismometers and recorded P- and S-waves
generated from vertical sledgehammer impacts on a steel plate and horizontal
sledgehammer impacts to an aluminum block, respectively. We used refraction tomography to develop 2-D VP, VS, VP/VS, and Poisson’s ratio models,and Multichannel Analysis of Surface Waves (MASW) to develop additional
VS(Rayleigh- and Love-wave) models. The VPmodel for the southern arrayshows a low-velocity zone with velocities between 1900 and 2200 m/s near thesuspected trace of the fault. We observe an increase in depth of the 1500 m/s
VPcontour (top of groundwater) coincident with the near-surface location of
the low-velocity zone, which suggests the fault acts as a barrier to groundwater
flow. Our VStomographic model for the southern array shows lower VS westof the suspected location of the fault. Based on our refraction tomography andsurface-wave models, we interpret a steeply west-dipping main fault and possibly a minor splay approximately 40 m to the east of the near-surface trace.
poster 87
Geologic and Geomorphic Evidence for Possible
Reactivation Along the Dry Creek Fault Zone and Hoadley
Fault, Cryptic Faults in the Northern Sacramento Valley
and Surrounding Areas
VON DASSOW, W., U.S. Bureau of Reclamation, Colorado, USA,
wvondassow@usbr.gov; KLINGER, R., U.S. Bureau of Reclamation,
Colorado, USA, rklinger@usbr.gov; BESANA-OSTMAN, G., U.S. Bureau
of Reclamation, Colorado, USA, gbesanaostman@usbr.gov; REEDY, T., U.S.
Bureau of Reclamation, Colorado, USA, treedy@usbr.gov
Observations along the Dry Creek fault zone (DCFZ) and Hoadley fault(HF) suggest that there are cryptic, Quaternary faults present throughout
the northern Sacramento Valley and into the southern Klamath Mountains.
Bedrock mapping along the DCFZ identifies distributed folds, fractures, andfaults in pre-Tertiary bedrock across a deformation zone approximately 3 km
wide and 12 km long located north of Redding, CA. Extended, interconnectedsurface lineaments may be 38 km total length. Surficial geomorphic mapping
does not identify discrete surface displacements in late Quaternary erosionalsurfaces and fluvial terraces along the DCFZ. Instead, a broad deformation
zone in bedrock is oriented sub-parallel to Inks Creek fold belt structures.
A fault strand on the northwestern margin of the zone generally coincides
with the alignment of several Quaternary surface back edges that form adiffuse, irregular escarpment. On the south side of the deformation zone, aheavily weathered, unlithified sedimentary deposit identified on an intermediate terrace in the Sacramento River sequence appears to be in fault contact
with Paleozoic bedrock. The deposit appears to predate the terrace and its
age is uncertain. Absent some topographic expression, deformation in otherTertiary to Quaternary deposits or surfaces indicates deformation probably
predates the terrace sequence, which is younger than ~0.8 Ma.

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Southwest of Whiskeytown Reservoir, a subtle northwest-striking,irregular, and discontinuous escarpment crosses Quaternary fan surfaces in
the Boulder Creek drainage along the northern strand of the Hoadley fault inthe southern Klamath Mountains. The escarpment is subparallel to ridgelines,
bedrock foliations, and is mapped as a normal fault. There is up to ~10 mof vertical separation along the escarpment and is consistent with a normal
sense of motion. Nearby exposures did not have clear evidence of faulting inboulder-rich fan deposits. Together, these observations point to late Cenozoic
re-activation of multiple faults at different orientations in the relatively lowstrain setting of north-central California.

traces) is about 16 m and late Pleistocene fans are displaced between 1.75 and4.2 m. A possible displacement of 0.75 m is recorded in a latest Pleistocene
fan. Soils developed into late Pleistocene surfaces along the Buffalo Valley fault
are characterized by thick (>1 m) textural B-horizons associated with stage
III+ carbonate development suggesting the surfaces are greater than 100 ka.
In progress 10Be surface exposure dates from surficial boulders and 10Be depth
profile analyses from the soil pits will place age constraints on displaced deposits, and be used to estimate fault slip rates. These data will allow developmentof earthquake recurrence estimates for refinement of seismic hazard models,and for assessment of blind geothermal systems in the region.

poster 88
Constraints on Late-Quaternary Fault Displacement andTectonic Hazards in the Sacramento–San Joaquin Delta,
Northern California, From Shallow Sediment Cores Acrossthe Pittsburg–Kirby Hills Fault System
TREXLER, C., U.S. Geological Survey, California, USA, ctrexler@usgs.gov;
VERMEER, J., U.S. Geological Survey, California, USA, jvermeer@usgs.
gov; HAMMER, M., U.S. Geological Survey, California, USA, mhammer@
usgs.gov; DOYLE, M., U.S. Geological Survey, California, USA, madeline.
doyle@sjsu.edu; WILLIAMS, T., U.S. Geological Survey, California, USA,
trevorw7991@gmail.com

poster 90
Late Pleistocene Kinematics of the Great Southern Puerto
Rico Fault Zone, Puerto Rico
LYNCH, E. M., U.S. Geological Survey, Colorado, USA, elynch@usgs.gov;
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.
gov; ORTEGA DIAZ, V. G., University of Puerto Rico at Mayagüez, Puerto
Rico, USA, victor.ortega4@upr.edu

Seismic sources and their associated hazards within the Sacramento-San
Joaquin Delta region of north-central California (“the Delta”) are poorly characterized, due to slow slip rates that combine to accommodate no more than
~5 mm/yr of plate-boundary-parallel slip and that do not keep pace with thefluvial and tidal processes that dominate the geomorphology of the region.
Local topographic highs in the western Delta suggest that some structures
accommodate vertical displacement, but the age and rate of this deformation
is not known. Tidal marshes preserve stratigraphy that can be used to constrain fault offsets and timing across active structures, providing insights torefine our understanding of Quaternary fault activity within the Delta.
The ~100-m-high Kirby Hills are at the core of a positive flower structure
within the north-south trending Pittsburg–Kirby Hills Fault System (PKHFS),
and are surrounded on three sides by tidal slough. The PKHFS originated in
the Late Cretaceous as an extensional system associated with the Rio Vista
forearc basin. In the modern tectonic regime, apparent reverse displacementof Eocene bedrock across the PKHFS suggests the possibility of active uplift
or transpression across the structure, but the modern kinematics and rates ofdeformation on the PKHFS are not well constrained.
Shallow (<6 m depth) subsurface stratigraphy from 15 hand-auger
cores in the Montezuma Slough tidal marsh, along strike of the PKHFS to
the south of the Kirby Hills, provides insights into Quaternary deformation
across the PKHFS. A peaty deposit overlies the PKHFS in the northern partof the marsh. This layer is thinner within the PKHFS (~1-2 m) than outsideit (~3+ m), consistent with relative uplift within the fault zone and suggestingthat the positive flower structure that forms the Kirby Hills is producing vertical displacement in the late Quaternary. Radiocarbon ages of subsurface peat
samples within the fault zone are older than peat ages at comparable depths
elsewhere in the Delta, suggesting relative uplift within the PKHFS during the
Holocene.
poster 89
Characterization of Slip Rates Across the Buffalo Valley,
Buena Vista Valley, and Southern Shoshone Faults, Central
Nevada
KOEHLER, R. D., University of Nevada, Reno, Nevada, USA, rkoehler@unr.
edu; STIRLING, M. W., University of Otago, Dunedin, New Zealand, mark.
stirling@otago.ac.nz
The Buffalo Valley, Buena Vista Valley, and southern Shoshone faults areactive range front normal faults that accommodate extension within theslowly deforming Basin and Range province in central Nevada. The faults areincluded as crustal sources in the 2023 update of the USGS National Hazard
model, but with an absence of any earthquake recurrence data. Observations
from lidar hillshades and field transects indicate the presence of progressively
displaced alluvial fans along each fault. Here we present surficial geologic maps
and vertical displacement estimates for the three faults. Additionally, we present descriptions of soil pits from displaced surfaces along the Buffalo Valley
fault. Deformation along the Buena Vista and southern Shoshone faults is primarily concentrated along a singular fault strand. Vertical displacements fromthree alluvial fan surfaces along the Buena Vista fault include 1.5 m, 4 m, and
15 m. Along the southern Shoshone fault, alluvial surfaces are displaced 2.2 m
and 10 m. Deformation along the Buffalo Valley fault is distributed across several parallel strands. Cumulative displacement across the oldest surface (three

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At the Northern Caribbean Plate Boundary Zone, geodetic data show differential motion between the Puerto Rico-Virgin Islands (PRVI) microplate andneighboring Hispaniola. The precise location of this microplate boundary isunclear over geologic timescales. This differential motion may be accommodated through distributed deformation on multiple faults located throughout
southwestern Puerto Rico, with lateral motion and/or shortening predicted byvarious tectonic models. Recently, several onshore faults in southern Puerto
Rico were recognized as Quaternary-active. However, the kinematics of thesefaults—particularly any lateral component—remain largely unconstrained.
This is due in part to extensive erosional and anthropogenic landscapemodification, steep relief, and frequent landsliding, limiting the preservationof geomorphic features that could serve as recorders of fault motion. Herewe constrain the kinematics of the Great Southern Puerto Rico fault zone
(GSPRFZ), an onshore fault considered for inclusion in the upcoming 2025
USGS National Seismic Hazard Model update for Puerto Rico and the U.S.
Virgin Islands. Integrating <1-m lidar-derived topography, historical air photos, and field mapping, we identify a series of ~50–1200-m-long fault scarps
and lineaments that trend northwest-southeast and extend for ~25 km acrossthe southern coastal plain. Fault scarps are primarily south-facing, cut acrosstopography, and displace Quaternary deposits and landforms. We document
multiple offset geomorphic markers, including channel thalwegs and interfluves formed in deposits previously mapped as Quaternary piedmont alluvial
plain. We observe both vertical (south-side-down) and right- lateral m-scale
displacements, which indicate that the GSPRFZ may accommodate right-lateral oblique motion in the late Pleistocene, consistent with northeast motionof PRVI away from Hispaniola. Additional studies are needed to determine
the kinematics of other onshore Puerto Rico faults and better understandhow these faults may be accommodating deformation at the PRVI-Hispaniola
microplate boundary.
poster 91
A Comprehensive Search for Evidence of Active Faulting in
the Southern Coast Mountains of British Columbia,
Canada: Progress and Preliminary Results
MENDOZA, R., University of British Columbia, Vancouver, Canada,
rmendoza@eoas.ubc.ca; HOBBS, T. E., Geological Survey of Canada,
Vancouver, Canada, tiegan.hobbs@NRCan-RNCan.gc.ca; SALOMON, G.,
University of Victoria, Victoria, Canada, guysalomon@uvic.ca; FINLEY,
T., University of Victoria, Victoria, Canada, tfinley@uvic.ca; NISSEN, E.,
University of Victoria, Victoria, Canada, enissen@uvic.ca; LAWRENCE, M.,
BC Hydro, Burnaby, Canada, martin.lawrence@bchydro.com; MENOUNOS,
B., University of Northern British Columbia, Victoria, Canada, brian.
menounos@unbc.ca
The southern Coast Mountains of British Columbia are situated in the inner
northern forearc of the Cascadia Subduction Zone. They are traditionallyviewed as the static backstop for the northward moving Oregon coast block.
While many faults have been mapped in the Coast Mountains, conclusive evidence of Holocene displacement has not been observed. The recent discoveriesof surface ruptures along the Leech River, Beaufort Range, and XEOLXELEKElk Lake faults on neighboring Vancouver Island underscore the importanceof reexamining the faults in the southern Coast Mountains, which could posea significant hazard to densely populated areas including Metro Vancouver.
However, this effort is challenged by glaciated, mountainous geomorphology,
and dense vegetation.

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We collated digital elevation models of varying coverages and scales,from 1-arc-second satellite data to meter-scale lidar data. Particular attention
was paid to locations of previously mapped faults and seismicity. We identified
escarpments related to regional-scale lineaments at Bowen Island, AlouetteLake, Coquitlam Mountain, and Nahatlatch Lake, in addition to known fault
systems such as the Fraser River Fault. We conducted field surveys in 2022 and2023 to collect ground observations where the linear features appear to intersect Holocene sediments. In some areas, we deployed a UAV lidar scanner
to obtain ultra-high resolution topographic data. At one site in the Britannia
Shear Zone, we observed a 20-cm offset in the soil profile on opposite sides
of a fault exposure, but the UAV lidar did not reveal a scarp extending fromthe outcrop. In addition to vegetation cover and glacial erosion, we have beenchallenged by unpredictable weather, difficult access to remote sites, and alack of sufficiently fine-grained Holocene sedimentary deposits to potentially
record sub-meter-scale displacements. Future plans include helicopter-based
lidar surveys of remote areas and sub-bottom profiling in lakes that may better preserve offsets in Holocene stratigraphy. The results of this project will beincorporated into Canada’s national seismic hazard and risk models.
poster 92
Investigating Holocene-Active Faulting in the Strait ofGeorgia, British Columbia Through Archived Seismic
Reflection Data
PODHORODESKI, A., University of Victoria, Victoria, Canada, anna.
podhorodeski@gmail.com; DOUGLAS, K., Geological Survey of Canada,
Sidney, Canada, karen.douglas@nrcan-rncan.gc.ca; HOBBS, T., Geological
Survey of Canada, Vancouver, Canada, tiegan.hobbs@nrcan-rncan.gc.ca;
LEONARD, L., University of Victoria, Victoria, Canada, lleonard@uvic.ca;
SCHAEFFER, A., Geological Survey of Canada, Sidney, Canada, andrew.
schaeffer@nrcan-rncan.gc.ca
Previous evidence of Holocene-active faulting in the central Strait of Georgia
has been observed through limited interpretations of seismic reflection,bathymetric relief, and seismicity datasets. However, in part due to a dearth ofattention and historic unavailability of subsurface data, our understanding ofsuch active faulting in the region is incomplete. This has resulted in piecemeal
knowledge of the presence, spatial extent, and seismogenic capacity of faults
in the region, despite their potential hazard to critical infrastructure near
the city of Vancouver, British Columbia. Thick deposits of Holocene muds, aresult of rapid sedimentation in the Fraser River Delta, limit the usefulness of
3.5 kHz sub-bottom profiling techniques and may rapidly infill surface fault
expressions, complicating interpretation. Furthermore, modern permitting
requirements associated with minimizing submarine noise make obtaining
the necessary deeper seismic reflection data challenging.
The Geological Survey of Canada (GSC) has a vast archive of paper seismic reflection records in the Strait of Georgia, collected in the 1980s-2000s,
which have been recently scanned and digitized. This presents a new opportunity to examine the subsurface in an area with high potential seismic risk andpartially identified evidence of active faulting. This study utilizes the GSC’s
archived data to look for evidence of Holocene faulting in the central Straitof Georgia. We aim to present preliminary structures identified through thisinvestigation and tie these findings with other recent work to characterizepotentially active faults in the region surrounding Vancouver. Our work highlights the importance of leveraging existing subsurface datasets to fill knowledge gaps and inform hazard assessments.
poster 93
Steps Toward Linking the Kaltag and Tintina Faults inInterior Alaska
SALISBURY, B., Alaska Division of Geological & Geophysical Surveys,
Alaska, USA, barrett.salisbury@alaska.gov
Alaska tectonics are driven by subduction of the Pacific Plate beneath theNorth American Plate at the state’s southern border, causing N–S compression and shearing of southern Alaska to the west. Transpression and rotation
occur over 700 km north of the subduction trench in Interior Alaska, where
the Kaltag–Tintina fault system, a north-convex right-lateral strike-slip arch,spans the entire state. The Tintina fault is a westward extension of a major
tectonic strike valley in Canada, and both it and the Kaltag fault are characterized by linear scarps, slope breaks, swales, and right-lateral offset streams.
Slip rate estimates for the system range from 0.01 to <0.5 mm/yr, suggesting
interseismic periods of thousands to tens of thousands of years and contributing to poor preservation of past activity and large uncertainty in seismic
potential. Despite geomorphic expression, diffuse seismicity, and several
recent M4–5 events, documented Quaternary activity along the two faults issparse and the link between the two faults near the Yukon River Bridge—

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economically crucial infrastructure—is poorly understood. Ongoing workwith new statewide high-resolution imagery and elevation datasets suggeststhat the W–NW striking Tintina fault system bends to the W–SW around Mt.
Schwatka. West of Mt. Schwatka, DGGS collected high-resolution lidar that
confirms disappearance of young deformation into the linear Rogers and Isomcreek valleys near the Yukon River. However, farther W–SW along strike inthe southern Ray Mountains, lidar elevation models reveal ~25 km of youthful
surface rupture, the western end of which represents a ~35 km left step at the
mapped end of the Kaltag fault at Tanana. These newly discovered faults suggest a M6.5 paleoearthquake ~50 km SW of the Yukon River Bridge. Though
the first attempt at traditional paleoseismic trenching was inconclusive, lidar
and field mapping illustrate the variability in geomorphic preservation of fault
activity over short distances and highlight the difficulty in properly characterizing seismic hazard for low strain rate faults in forested, high-latitude terrain.
poster 94
A Detailed Earthquake Catalog for Interior Alaska Fault
Zones
SIMS, N. E., University of Alaska Fairbanks, Alaska, USA, nesims@alaska.
edu; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.
edu
We use network-matched filtering (NMF) and relative earthquake relocation
techniques to derive a detailed catalog of earthquake locations for the Minto
Flats fault zone (MFFZ) in interior Alaska between September 2014 andDecember 2019. The MFFZ is a left-lateral strike-slip fault system situatedbetween the right-lateral Denali and Kaltag faults. It produced a magnitude-6
earthquake in 1995 and has potential for a magnitude-7 earthquake. We systematically test parameters for the NMF and earthquake relocation routines andperform a qualitative check on the final catalog in order to reduce false detections that would skew relocations. Our results provide the most complete catalog for the MFFZ and include deeper events, clusters of shallow seismicity anda complex, and segmented fault structure not observed in the original regional
catalog. We are also able to determine the fault orientation of the northwest
cluster of seismicity containing the 2014 Mw 5.0 event as well as identify a previously unstudied third strand segment in the southwest region of the fault zone.
poster 95
Spatial Patterns of Tectonic Deformation at the Mendocino
Triple Junction Inferred From River Terraces and LandscapeMorphology
VERMEER, J., U.S. Geological Survey, California, USA, jvermeer@usgs.gov;
DELONG, S., U.S. Geological Survey, California, USA, sdelong@usgs.gov;
HAMMER, M., U.S. Geological Survey, California, USA, mhammer@usgs.gov;
PATTON, J. R., California Geological Survey, California, USA, jason.patton@conservation.ca.gov; TREXLER, C., U.S. Geological Survey, California, USA,
ctrexler@usgs.gov; HEMPHILL-HALEY, M., California State Polytechnic
University, Humboldt, California, USA, mark@humboldt.edu; KELSEY, H.,
California State Polytechnic University, Humboldt, California, USA, hmk1@
humboldt.edu; LEROY, T., Pacific Watershed Associates, California, USA,
TomL@pacificwatershed.com; ROBINSON, M., Pacific Watershed Associates,
California, USA, MichelleR@pacificwatershed.com
At the Mendocino triple junction (MTJ), the Cascadia subduction zone, San
Andreas Fault system, and Mendocino Fault meet in a complex deformation
zone. In the immediate MTJ area, from roughly Ferndale to Shelter Cove, CA,previous investigation of the fault networks was primarily through bedrock
mapping, with little differentiation between inactive and active faults, and few
constraints on Quaternary deformation rates. Quantification of crustal deformation is limited to coastal uplift rates derived from emergent Holocene andPleistocene marine terraces, and stream metrics and erosion rates from small
coastal drainages within ~5 km of the coast. In this steep and densely vegetated environment, recognizing spatial variation of inland Quaternary crustal
deformation rates could help identify the presence and location of active faults
where there is little direct surface expression. We use lidar to map fluvial terraces and other geomorphic surfaces along river valleys in the MTJ area up to
30 km inland. Longitudinal profiles, height above river, and morphologicalcharacteristics are used to correlate terrace surfaces along the rivers. In the
Mattole watershed, terraces with different vertical spacings occur along channel reaches having different gradients separated by distinct knickzones. These
patterns may indicate spatially variable uplift rates. Complementary analysisof landscape morphology including hillslope steepness and relief, and river
metrics such as channel steepness index expands the spatial extent of inferred
deformation beyond the terraced river valleys. These analyses must consider
apparent drainage area reduction due to drainage divide migration and stream
capture, which itself provides additional insight into the landscape response

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to tectonic forcing. Spatial variation in apparent uplift rates indicate possible
location and kinematics of crustal faults related to the San Andreas Fault andCascadia subduction zone which are objectives for future study.

Detecting, Characterizing and Monitoring Mass
Movements
Oral Session • Thursday 2 May • 8:00 am PacificConveners: Kate Allstadt, U.S. Geological Survey (kallstadt@
usgs.gov); Clément Hibert, University of Strasbourg (hibert@
unistra.fr); Ezgi Karasozen, University of Alaska Fairbanks/
Alaska Earthquake Center (ekarasozen@alaska.edu); Liam
Toney, U.S. Geological Survey (ltoney@usgs.gov)
Infrasound Array Analysis of Rapid Mass Movements inMountain Regions
JOHNSON, J., Boise State University, Idaho, USA, jeffreybjohnson@boisestate.edu; MARCHETTI, E., Università degli Studi di Firenze, Florence,
Italy, emanuelle.marchetti@unifi.it
Rapid gravity-driven mass movements (RGMMs), such as rock-falls, snow
avalanches, glacier break-off events, debris flows, lahars and pyroclastic
density currents are among the most hazardous phenomena occurring inmountain environments. In the last decades remote monitoring solutions for
RGMMs have been implemented using acoustic signals radiated by these rapidly moving flows. In particular, infrasound observations, which entail soundbelow 20 Hz, has been shown to provide a valuable, low-cost, low-latency,
and relatively straightforward complement to in situ measurements. Here we
present a review of recent infrasound observations comparing various typesof RGMMs highlighting the capabilities and limitations of infrasound arraymonitoring techniques for both research and monitoring applications. We
showcase processing strategies for using low-cost infrasound arrays, withapertures of a few tens of meters, to locate and track moving sources andextract information about their source mechanisms using infrasound energetics. This research provides comparative case studies of diverse flow phenomena using infrasound arrays situated several kilometers from respective
flow paths.
The Mount Rainier Lahar Detection System: Risk Mitigation
for an Unlikely, but Potentially Catastrophic, Event
MORAN, S. C., U.S. Geological Survey, Washington, USA, smoran@usgs.gov;
THELEN, W. A., U.S. Geological Survey, Washington, USA, wthelen@usgs.
gov; IEZZI, A. M., U.S. Geological Survey, Washington, USA, aiezzi@usgs.
gov; KRAMER, R. L., U.S. Geological Survey, Washington, USA, rkramer@usgs.gov; PAUK, B., U.S. Geological Survey, Washington, USA, bpauk@usgs.
gov; MAJOR, J. J., U.S. Geological Survey, Washington, USA, jjmajor@usgs.
gov
Mount Rainier (Washington, USA) last erupted ~1,000 years ago and has experienced tens of eruptions over the last 10,000 years. Of all the hazards associated with Mount Rainier, large lahars pose the greatest risk to communities
downstream of the volcano—more than 90,000 people live in areas that could
be impacted by a future large lahar. Large lahars have reached as far as the
Puget Lowlands (> ~50km) at least 11 times over the last 6,000 years. All but
one was associated with an eruption; the exception is the ~1507 A.D. landslideinitiated Electron Mudflow, for which no evidence of an associated eruption
has been found. Recent studies show that the western flank of Mount Rainier
could produce future non-eruptive landslides and associated large lahars down
the Puyallup and/or Tahoma Creek drainages, potentially reaching nearby
small towns within 5-10 minutes and larger communities within 60 minutes.
The Mount Rainier Lahar Detection System is part of a risk-mitigation
strategy pursued by a group of local, State, and Federal agencies since 1998.
It consists of several components: 1) a real-time network of tens of seismometers, infrasound arrays, tripwires, webcams, and other instruments
located on the flanks of the volcano and along vulnerable drainages operated
and upgraded periodically by the U.S. Geological Survey (USGS) Cascades
Volcano Observatory (CVO) and the Pacific Northwest Seismic Network; 2)
an automated detection system, designed and maintained by CVO, that triggers alarms in two separate county- and State-run 24/7 emergency operations
centers; and 3) a set of protocols and inter-agency agreements among CVO,
Pierce County (Washington) Department of Emergency Management, and
the Washington State Emergency Management Division that delineate each

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agency’s detection, alerting, and/or warning responsibilities, protocols that are
reviewed and tested periodically. CVO’s protocols have required establishinga rotation of scientists who carry a duty phone to provide partners with a
24/7 point of contact, and who are expected to respond within 1-2 minutes toautomated alerts from the detection system.
Characterization of a Debris Flow at Mount Rainier via
Seismoacoustics and a Novel Usage of a Laser Rangefinder
IEZZI, A., U.S. Geological Survey, Washington, USA, aiezzi@usgs.gov;
THELEN, W. A., U.S. Geological Survey, Washington, USA, wthelen@usgs.
gov; BRYANT, E., U.S. Geological Survey, Washington, USA, ebryant@usgs.
gov; GABRIELSON, C., Western Washington University, Washington, USA,gabriec@wwu.edu; MORAN, S. C., U.S. Geological Survey, Washington, USA,smoran@usgs.gov; OBRYK, M. K., U.S. Geological Survey, Washington, USA,mobryk@usgs.gov; PATRICK, M., U.S. Geological Survey, Hawaii, USA,mpatrick@usgs.gov; YOUNGER, F., U.S. Geological Survey, South Carolina,
USA, eyounger@usgs.gov
Mass movements such as debris flows and lahars can occur at volcanoes withor without associated unrest and have the potential to impact life and infrastructure for tens of kilometers downstream with little warning. Many have
low-amplitude emergent onsets and moving source locations, making theirinitial detection and characterization difficult. Small debris flows can occur
at volcanoes due to heavy rainfall or snow- and ice-melt in the summer.
Recordings from such events can be used to develop and test novel monitoring techniques as well as detection and characterization algorithms in theabsence of larger, but less frequent, lahars.
Here we present recordings of a small debris flow at Mount Rainier(Washington, USA) that occurred on August 15, 2023, in the Tahoma Creekdrainage. Mount Rainier has had at least 11 large lahars over the last 6,000
years, including one occurring without evidence of eruptive activity. In
response to this hazard, the USGS and partner agencies operate the Rainier
Lahar Detection System (RLDS) that was recently upgraded and densified.
The current network consists of broadband seismometers, infrasound arrays,
tripwires, and webcams concentrated along multiple potentially hazardous
drainages. The 2023 debris flow was recorded by this network and by a suite of
temporary campaign geophysical equipment. Among these instruments was alaser rangefinder recording at 1 Hz, co-located with a seismometer and infrasound sensor directly adjacent to the channel. The intent was to test its utility
in detecting lahars as a potential replacement for tripwires currently in use toprovide confirmation of a lahar. The laser rangefinder and co-located instruments clearly recorded the flow, in addition to the 10 broadband seismometersand 4 infrasound arrays in the permanent network, as the flow moved down
the drainage. The 2023 debris flow produced recordings that have allowed
us to calibrate and evaluate RLDS algorithms and served as a successful test
for new geophysical equipment that may be useful for detection of lahars at
Mount Rainier and elsewhere.
Identification of Lahar Signals: A Supervised Learning
Model Applied to Monitoring Data of Volcan De Fuego,
Guatemala
BEJAR, G., Michigan Technological University, Michigan, USA, gbejarlo@
mtu.edu; WAITE, G. P., Michigan Technological University, Michigan,
USA, gpwaite@mtu.edu; ESCOBAR-WOLF, R., Michigan Technological
University, Michigan, USA, rpescoba@mtu.edu; JOHNSON, J. B., Boise State
University, Idaho, USA, JeffreyBJohnson@boisestate.edu; BOSA, A., Boise
State University, Idaho, USA, ashleybosa@boisestate.edu; ROCA, A., Instituto
Nacional de Sismologia, Vulcanologia, Meteorologia e Hidrologia, Guatemala
City, Guatemala, aeroca@insivumeh.gob.gt; PINEDA, A., Independent,
Guatemala City, Guatemala, pineda.armando@gmail.com
The rise in popularity of machine learning models has provided improved
tools for identifying and classifying seismic signals of different natures.
Here, we showcase a novel approach that uses a supervised K-nearest neighbor model to detect tremor signals associated with rain-triggered lahars at
Volcan de Fuego, Guatemala. For this, we used a set of three permanent andfive temporary broadband seismometers installed between ~10–350 m fromthe thalweg of two active lahar channels around Fuego. The recorded signals display durations between 0.5–6 hours, high signal-to-noise ratios, andoverall high-frequency activity with lower frequencies active during denser,
high-energy flow portions. We established a binary classifier trained withfeatures that describe the seismic record in the time and frequency domains,
split into 10-minute overlapping windows. The best features for this method
were chosen based on the model’s performance. They included measures ofthe signal’s amplitude, frequency content, and statistical functions of the prior,such as kurtosis, skewness, and entropy. A training set of 5 confirmed lahars

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and equally long background noise was enough to achieve greater than 90%
precision at stations with a comparatively low sampling rate (50 sps). Crossvalidation shows that two of our datasets with higher sampling rates (200 sps)
require a higher number of neighbors to achieve similar precision results:
n<10 at 50 sps vs. n>50 at 200 sps. A post-processing step converts the resulting discrete sample predictions into prediction intervals and discriminates
false positive results. This model detected 161 of 172 observed lahars during
the 2018-2022 period at the longest-running seismic station in one of Volcan
de Fuego’s active channels. While these detections did not always match thetotal duration of observed lahars, they still correctly classified ~95% of thesignal portion attributed to lahar activity during this period. We highlight thepotential of our method for real-time monitoring applications, providing avaluable tool for the timely identification of lahar signals.
Lahar Early Warning at Volcano Santiaguito: A Classicaland a Deep Learning Approach
JOZINOVIĆ, D., ETH Zurich, Zurich, Switzerland, dario.jozinovic@sed.
ethz.ch; MASSIN, F., ETH Zurich, Zurich, Switzerland, frederick.massin@
sed.ethz.ch; ROCA, A., Instituto Nacional de Sismología, Vulcanología,
Meteorología e Hidrología, Guatemala City, Guatemala, aeroca@insivumeh.
gob.gt; CLINTON, J., ETH Zurich, Zurich, Switzerland, jclinton@sed.ethz.ch
The Santiaguito Volcanic Complex is located in Guatemala’s Western Volcanic
Highlands, along the westernmost section of the Central American Volcanic
Arc. Santiaguito presents multiple hazards (including explosions, local
earthquakes, lahars, mudflows, and pyroclastic flows) to the local population, which numbers 1.6 million people within 30 km2 around the volcano.
Lahars are flows of a mixture of a large amount of water and pyroclastic debris(that can include gases) which can rapidly initiate and reach speeds of tensof meters per second down wide barrancas (canyons) making them highly
destructive. Lahar occurrence strongly correlates with rainfall at the volcano
and they are commonplace in the long rainy season. They pose a great hazard
to local inhabitants who regularly cross the channels as they live and workon farms on or near the flanks of the barrancas. INSIVUMEH, the national
seismic and volcano monitoring agency, has recently built a network of 10
seismic stations that can monitor these flows in collaboration with external
agencies. We used the open seismic data from 2022 and 2023 to consolidate a
Lahar catalogue, having a total of 43 Lahars. We then use the Lahar data (91waveforms) from 2022 to train a Siamese Neural Network that uses 5-minutesingle-station waveforms to produce a Deep Learning Lahar detection. We use
the same data to develop a classical Lahar detector that uses ratios between
two different short-term/long-term average amplitude (STA/LTA) characteristic functions implemented in SeisComP. We then test both approaches oncontinuous data from 2023 and compare them. We demonstrate the advantages and disadvantages of both approaches and show that both could be combined for optimal Lahar Early Warning. We show how the classical method,
implemented through SeisComP, is being used to operate an early warning
messaging system. We expect that the developed tools can be portable to othervolcanic areas and even other flow types. Furthermore, we demonstrate theusefulness of Siamese Neural Networks for the development of Deep Learningmodels when a small number of training data is available.
Towards Building a Machine Learning Based Automatic
Detection System for Surface Events in the PacificNorthwest
KHARITA, A., University of Washington, Washington, USA, ak287@uw.edu
Systematic monitoring of mass movements, such as landslides, avalanches,
rockfalls, and debris flows, is vital for mitigating risks in places where such
events threaten to impact people or infrastructure. The Pacific Northwest
Seismic Network (PNSN) detects a subset of surface events as a byproduct of theroutine detection and location workflow for tectonic and volcanic earthquakes.
In this study, we explore a vast range of feature space and model architecture designs for event classification. We found that the random forest algorithm along with a specific set of features is the best model for its generalization over the PNW data sets. We trained our model on a curated set ofwaveforms from Ni et al. (2023) for earthquakes and other seismic sources
recorded by the PNSN over the past 20 years and developed a workflow thatcan be deployed on continuous data. We then used our model to automaticallydetect and characterize events at Mount Rainier, identifying surface events ina month of continuous data from three seismic stations. The model successfully identified all surface events manually picked by PNSN analysts for the
study period with a high classification probability exceeding 0.9. Additionally,
it detected approximately ten times more surface events with a high probability of 0.8, with a subsequent manual review revealing their resemblance
to waveforms of verified surface events or volcanic events. In one attempt toVolume 95•

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validate our new detections, we computed maximum cross-correlation coefficients of detected event waveforms with ground-truthed surface events inthe Earthscope Exotic Seismic Event Catalog for the Mount Rainier region
and found that many of the detected surface event waveforms exhibited highcorrelation coefficient values exceeding 0.9. We also report their approximate
location using phase picking of the onset of the emergent waveforms anduse a grid-search method for determining locations using a uniform velocity model. Ongoing efforts to generate better training catalogs and to verify
new detections involve incorporating additional stations, DAS, eyewitness
accounts, and infrasound data.
Source Characterization of Surface Events in the PacificNorthwest
DENOLLE, M. A., University of Washington, Washington, USA, mdenolle@
uw.edu; SKENE, F., University of Washington, , USA, fskene@uw.edu;
SMOCZYK, N., University of Minnesota, Minnesota, USA, bluescale1999@
gmail.com; NI, Y., University of Washington, Washington, USA, niyiyu@
uw.edu; KHARITA, A., University of Washington, Washington, USA,ak287@uw.edu; MALONE, S., University of Washington, Washington,
USA, smalone@uw.edu; THELEN, W., U.S. Geological Survey, Washington,
USA, wthelen@usgs.gov; HUTKO, A., Pacific Northwest Seismic Network,
Washington, USA, ahutko@uw.edu; STEVENS, N., Pacific Northwest
Seismic Network, Washington, USA, ntsteven@uw.edu; HARTOG, R., PacificNorthwest Seismic Network, Washington, USA, jrhartog@uw.edu
The Pacific Northwest (PNW) is subject to various geohazards due to its active
tectonics, volcanism, and surface processes. The Pacific Northwest Seismic
Network (PNSN) monitors seismic activity in the PNW with a mandate tocharacterize tectonic earthquakes. Volcanoes are relatively well monitored by
the PNSN in terms of determining source origin time, location, and magnitude for volcano-tectonic earthquakes. However, many other event types arelabeled by seismic analysts as “surface events,” which are informally understood as being mass flows of snow or rock avalanches, rockfall, landslides, anddebris flows but are not characterized further by analysts.
We collect seismograms from ~ 8000 events with 5-10 seismic stations
located on six PNW volcanoes; Mounts Hood, Rainier, St. Helens, Baker, andAdams, with the goal to further characterize these surface events. We use an
ensemble deep-learning phase picker to pick the onset of the waveform, whichhelps determine where the emergent signal starts. We then calculate the signal-to-noise ratio (SNR) and only pick traces with sufficiently high SNR. We
also pick the time of the peak amplitude in the envelope function to track thecentroid time of the event. We locate event onsets and centroids using a simple
grid-search algorithm. We estimate a potential direction of motion (flow) andvelocity using 1) Doppler effects measured from the seismogram’s spectral
content and 2) the difference between the centroid and event onset times andlocations. We analyze these directions and velocities relative to high-resolution digital elevation models and discuss the potential and limitations of thismethod as a prototype for detecting debris flow or lahar in the Cascades.
Dissecting Seismic Signals to Estimate Landslide Volume
COLLINS, E., U.S. Geological Survey, Colorado, USA, ecollins@usgs.gov;
ALLSTADT, K. E., U.S. Geological Survey, Colorado, USA, kallstadt@usgs.
gov; TONEY, L. D., U.S. Geological Survey, Colorado, USA, ltoney@usgs.gov
Determining the size of a landslide based solely on the seismic signal it produces could be a useful tool for rapid event characterization, response, andearly-warning systems. In this study, we work towards establishing a generalrelationship between the seismic signal and the physical properties of large,
rapid landslides that are detected by regional seismic networks. To do this, weanalyze the seismic signals for known landslide events and determine which
combination of seismic parameters best predict landslide characteristics ofinterest, primarily volume.
We analyze events from the Exotic Seismic Events Catalog (ESEC), a published catalog including information on the seismic detection and physical properties (e.g., volume, runout distance, and drop height) of 290 seismogenic landslides. This collection spans several continents, which provides us with a diverse
dataset to work with. We focus on large (>105 m3) mass movements with fall,slide, and avalanche movement types because they are seismically detectable
at regional scales and generate observable long-period (>20 s) signals that we
can invert to obtain the force history of the landslide’s bulk motions. We analyze parameters in the high-frequency range (1-5 Hz) to represent the portionof seismic energy produced by smaller-scale processes, such as disrupted flow
and granular interactions. We also include characteristics of the force histories
inverted from the long-period signals which represent the bulk movement of
the failure mass. We find that envelope rise time, envelope area, and maximum
force scale logarithmically with volume, whereas peak frequency and maximum

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amplitude have a less-defined relationship. Using this information, we perform a
multivariate linear regression to develop an empirical relationship between theseparameters and independently estimated volumes (usually via remote sensing),
as reported in the ESEC. We find that a combination of envelope rise time, envelope area, and maximum force, derived solely from seismic analysis, provide a
reasonable estimate of landslide volume with well-defined uncertainties.
Radial Backprojection Imaging of Recent Mass Movements
in Alaska
HANEY, M. M., U.S. Geological Survey, Alaska, USA, mhaney@usgs.
gov; TONEY, L., U.S. Geological Survey, Colorado, USA, ltoney@usgs.gov;
KARASOZEN, E., University of Alaska Fairbanks, Alaska, USA, ekarasozen@
alaska.edu
Backprojection imaging has shown utility for locating seismic events using
waveform data, without requiring timing information from clear phasearrivals. Processes imaged with backprojection include earthquake rupture,
volcanic tremor, and surficial mass movements. Here we develop a novel
backprojection method using the radial horizontal component, instead of
the conventional technique utilizing the vertical component, and apply it torecent mass movements in Alaska. Use of the radial horizontal component isdesigned to image the source region with Rayleigh waves, which are efficiently
generated by surficial seismic sources. Although radial backprojection offers
many advantages to vertical backprojection, including improved signal-tonoise ratio (SNR) of the image and the ability to image the source location with
only two stations, its application requires additional details in order to quantitatively interpret the normalized amplitude of the backprojection image. For
vertical backprojection, a normalized amplitude between 0 and 1 indicateseither perfectly destructive (0) or perfectly constructive (1) stacking of thevertical waveforms at different stations. In contrast, a normalized amplitude of
1 for radial component backprojection indicates perfectly constructive stacking of signals exhibiting exclusively radial particle motion (i.e., no transverse
component). We apply this novel radial backprojection method to a glacialcalving event at Barry Arm on December 15, 2022, a landslide on the Kenai
Peninsula near Seward on September 15, 2022, and a large ice-rock avalanche
at Iliamna volcano on June 21, 2019. These case studies demonstrate the ability of radial backprojection to locate a source with as few as two stations andthe improved SNR of the radial backprojection image compared to vertical backprojection. We also discuss the similarities and differences between
radial backprojection and the method known as radial semblance developedby Kawakatsu et al. (2000; JVGR) and Almendros and Chouet (2003; BSSA).
Enhancing Real-Time Landslide Detection for Improved
Tsunamigenic Landslides in Alaska
KARASOZEN, E., University of Alaska Fairbanks, Alaska, USA,ezgikarasozen@gmail.com; WEST, M. E., University of Alaska Fairbanks,
Alaska, USA, mewest@alaska.edu
In response to the increasing prevalence of mass movements, such as landslides,
coupled with the urgent need for early warning systems, this study presents significant advancements in refining real-time landslide detection. Currently, we
run a real-time landslide detector based on long-period seismic data within the
dynamic landscape of southern Alaska. Over the past year, we have compiled adiverse dataset encompassing landslides (0.2 - 10 M m3), as well as regional (M3-5) and teleseismic seismic events that triggered false detections.
In this study, we refine detection techniques by combining historicallandslides, which benefit from well-studied properties, with a diverse set oflandslides detected in real time during the 2023 season. We employ a rangeof waveform similarity measures, explore different signal processing criteria,
and assess various detection thresholds to derive sets of statistics aimed atenhancing detection performance. Our primary objective is to substantially
improve accuracy and reliability in the early detection of landslides, with aparticular focus on tsunamigenic events. The ultimate goal of this research isto provide a robust and efficient solution for early detection of tsunamigenic
landslides, contributing to improved warning systems and mitigation strategies in coastal regions.

model mass trajectories unfolding in space and time. These events may also
be analyzed as point sources with moment tensors, though this approach may
not always apply for complex events with tortuous runout trajectories, multiple simultaneous detachments, slow slip, and emergent signals. Despite theircomplexity, these events may also produce a more coherent long-period signal which in the far field may be analyzed with moment tensors. When applicable, moment tensor analysis of landslides provides a way to routinely andquickly characterize mass movement events which can aid in providing prompt
response and warning. In the present study we examine a dataset of seismic
events in Alaska identified as icequakes or avalanches by the Alaska Earthquake
Center and estimate the source mechanisms (moment tensors) of five eventsfrom the recorded waveform data. These five events occurred in the Southeast
Alaska between 2005-2016 and were massive rock and ice avalanches with
reported volumes on the order of 30-60 million m3, weighing between 20-100
billion kg. Due to the large size, these events were observed at seismic stations
located thousands of kilometers away. Some events occurred during deployment of the USArray network in Alaska and Canada which allowed us to examine datasets containing hundreds of stations. The best fitting solutions produce
synthetics seismograms that agree with long-period observational data. We
analyze the moment tensors in terms of their source-types, which reveal negative isotropic (collapse or dilatational) parameters, and we discuss these andother gravitational mass movements from mining sites. We also discuss work
towards operational implementation for routine analysis of similar events.
The Seismic Puzzles of the 2022 Chaos Canyon Landslide in
Rocky Mountain National Park
ALLSTADT, K. E., U.S. Geological Survey, Colorado, USA, kallstadt@
usgs.gov; COE, J., U.S. Geological Survey, Colorado, USA, jcoe@usgs.
gov; COLLINS, E., U.S. Geological Survey, Colorado, USA, ecollins@usgs.
gov; RENGERS, F., U.S. Geological Survey, Colorado, USA, frengers@usgs.
gov; MANGENEY, A., Université Paris Cité, Paris, France, mangeney@
ipgp.fr; ESSER, S., National Park Service, Colorado, USA, scott_esser@
nps.gov; PURSLEY, J., U.S. Geological Survey, Colorado, USA, jpursley@usgs.gov; YECK, W., U.S. Geological Survey, Colorado, USA, wyeck@usgs.
gov; BELLINI, J., U.S. Geological Survey, Colorado, USA, bellini@usgs.gov;
BRADY, L., U.S. Geological Survey, Colorado, USA, lrbrady@usgs.gov
On 28 June 2022, ~2 million m3 of ice-rich debris mobilized from the southeast flank of Hallett Peak in Rocky Mountain National Park, sliding about 245
m in ~2 minutes, and narrowly missing a group of climbers downslope in
Chaos Canyon. The size and energy of this event was evident in eyewitness
videos and reflected in the ground vibrations it generated, recorded up to 70
km away. Using eyewitness accounts, field and remote sensing techniques, historic climate data, and seismic evidence, we pieced together a detailed timeline of this landslide stretching back decades to when the slope started moving
as air temperatures warmed. In this talk, we focus on June 28, and on theseismic aspects of the landslide event.
We first describe how we used the seismic signals and eyewitness
accounts to piece together a complex sequence of events starting with a gradual build-up in rock fall activity and culminating in three energetic sliding
episodes. We also discuss a seismic “red herring”: a M1.4 earthquake-like signal ~1 min prior to the main sliding event that initially appeared to be coming from the landslide, but that later evidence, including a repeating earthquake analysis, revealed to be a blast from reservoir construction 36 km eastof the park. Videos show some sliding was already underway when the blast
occurred making it unlikely that it triggered the slide, but the weak shaking
it induced at the landslide (~0.001% g) could have influenced slide behavior.
Finally, we investigated why the main event did not generate observable longperiod seismic signals related to bulk mass accelerations that are typical oflarge, rapid landslides by modeling the event using the SHALTOP numerical landslide model. We found that this landslide was actually slower and lessmobile than most landslides of similar size, resulting in long-period signalsthat were too low amplitude to be observable. In summary, we combined
diverse evidence and techniques to understand this event, and the seismic signals were valuable in helping unravel this unusual landslide sequence.

Seismic Collapse Mechanisms of Large (M~4) Rock and Ice
Avalanches in Southeast Alaska
ALVIZURI, C., Norwegian Seismic Array, Kjeller, Norway, celso.alvizuri@
norsar.no; RUPPER, N., University of Alaska Fairbanks, Alaska, USA,naruppert@alaska.edu; KARASOZEN, E., University of Alaska Fairbanks,
Alaska, USA, ekarasozen@alaska.edu

New Insights on the Åknes Rockslide (Norway) Using
Borehole Microseismic Data
LANGET, N., NORSAR, Kjeller, Norway, nadege@norsar.no; OYE, V.,NORSAR, Kjeller, Norway, volker@norsar.no; GRØVAN ASPAAS, A., NVE& University of Oslo, Oslo, Norway, agas@nve.no; LACROIX, P., Université
Grenoble Alpes, Grenoble, France, pascal.lacroix@univ-grenoble-alpes.fr;
RENARD, F., University of Oslo, Oslo, Norway, francois.renard@mn.uio.no

Mass movement events such as landslides and rock and ice avalanches are
traditionally analyzed at seismological observatories as single forces that

The Åknes rockslide, located in Western Norway, is one of the most thoroughly instrumented rockslides in the world. Since the 2000s, it has been

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equipped with various instruments measuring its displacement (extensometers, GPS, lasers,…). Measured movements are in the order of 1 to 3 cm/yr.
As part of the monitoring system, eight geophones were installed at thesurface around the backscarp of the slide in 2005. Although the data are only
recorded in triggered mode, the large amount of data collected over the years
has proven useful to characterize different types of events related to the slide
movements.
More recently, a borehole was instrumented with eight geophones continuously recording at 1000 Hz down to a depth of 50 m, crossing two sliding
planes. There, seismic events characterized by a very high frequency content
and a short duration can be detected. These events are likely located very
close to the borehole. In particular, periods of intense seismic activity could
be identified. The detailed analysis of the waveforms during such periods
reveals series of repeating events interrupted by quiescence phases that could
be interpreted as creeping on different patches of the shear zone. At least oneof these periods could be correlated with an increase in the water pressure at
the depth of the corresponding shear zone.
How Do Slow-moving Landslides Maintain Steady Motion?
XU, Y., University of California, Berkeley, California, USA, yuankunx@
berkeley.edu; BÜRGMANN, R., University of California, Berkeley, California,
USA, burgmann@berkeley.edu; BILHAM, R., University of Colorado Boulder,
Colorado, USA, Roger.Bilham@colorado.edu
Slow-moving landslides predominantly manifest steady motion, in striking
contrast to rapid runaway landslides that accelerate and fail catastrophically.
However, we do not fully understand how slow-moving landslides arrest andstabilize their motion. Better understanding of the underlying mechanisms
potentially holds the key to illuminate their slow-to-fast motion transition andalso offers insights on frictional faulting processes. To approach this problem, we deployed dense instrumentation on the slow-moving (~1.5 cm/d)
Slumgullion landside in Colorado from 2022 to 2023. The sensors encompass
four surface creepmeters along its southern edge, four embedded strainmeterson the slide, and six GPS receivers and 150 nodal seismometers covering the
middle section. These sensors record data at one-minute or higher rates. We
complemented the field measurements with high-resolution TerraSAR-X andPAZ SAR repeat acquisitions.
From the 2.5-μm-precision creepmeter and strainmeter data, weobserved coupled slip and strain events that migrate along the slide on a tenday timescale, appearing as accelerations or decelerations in slip rate and axial
strain with wavelengths of ~100 m. From creepmeters along the southernedge, we have also observed slip signatures of episodic acceleration-deceleration in duration of minutes and magnitude of sub-millimeters. These distinct
slip patterns seemingly resemble fault creep that consists of a relatively sharp
acceleration followed by gradual slowdown. The observed motion propagation and high-rate creep signals suggest possible changes in landslide shear
strength, which may be related to pore-pressure feedback and/or rate-dependent material strength. We are actively processing the collected GPS, SAR, andnodal seismic data to extend our observations form the marginal transform tointerior parts of the slide. These additional data may allow distinguishing thefrictional properties and strength of the basal and lateral landslide boundaries. Findings from this work are anticipated to shed light on the mechanism ofslow-to-fast slip in landslides and tectonic faults.

Some of these events resulted from landslides that produced distinctive seismic signals, but in only some of these cases was this seismic signal
automatically characterized as a landslide. These went unnoticed until later,when their dramatic impacts were discovered by locals or through examining satellite imagery. Comparing the events reveals patterns that could informmitigation strategies, including assessment, targeted seismic monitoring, andprobabilistic hazard mapping. Fortunately, these recent events have had only
minimal human impact. However, there are several sites with dramatic signsof slope instability above lakes fringed with human infrastructure and popularwith visitors. It’s critical that we improve assessment, planning, and monitoring related to these hazards before we have the benefit of tragic hindsight.

Detecting, Characterizing and Monitoring Mass
Movements [Poster Session]
Poster Session • Thursday 2 May
Conveners: Kate Allstadt, U.S. Geological Survey (kallstadt@
usgs.gov); Clément Hibert, University of Strasbourg (hibert@
unistra.fr); Ezgi Karasozen, University of Alaska Fairbanks/
Alaska Earthquake Center (ekarasozen@alaska.edu); Liam
Toney, U.S. Geological Survey (ltoney@usgs.gov)
poster 55
The MVO Rockfall Location System 24 Years On:
Reimplementation, and Re-Analysis of Pyroclastic Flow
Trajectories
THOMPSON, G., University of South Florida, Florida, USA, thompsong@usf.eduMontserrat, West Indies. On March 20th, 2000, heavy rainfall induced 4 hoursof progressively intensifying lahars and pyroclastic flows, reaching the ocean
in most directions. Most of Montserrat’s population lived close to the Belham
Valley, which was greatly impacted. Having recently re-joined MVO after a
3.5 year absence, this event gave new impetus to an idea that I had originally
had in July 1996 from observing the bar graphs of the RSAM system: could
we devise a real-time system for the location of pyroclastic flows, based on
the distribution of amplitudes across the seismic network? Within 24 hours,
I had a near-real-time “rockfall location system” running, featuring a crude
shrinking grid search, and sending alarms by SMS. By databasing the estimated trajectories, “heatmaps” of rockfall activity could be plotted between
pairs of dates/times, to reveal which parts of the dome were growing/collapsing, giving us a sort of seismic-X-ray vision to peer through the persistent
cloud that shrouded the lava dome. However, given the fast-paced nature ofa volcanic crisis, a systematic evaluation of performance did not occur and,
unfortunately, this software and the corresponding database was lost in June
2003, when I departed MVO. We have re-created this system as an ObsPybased package, and hundreds of event trajectories are being recomputed. In
this presentation, we will assess system performance, and see what lessons canbe learned about the Montserrat eruption.

Big Tsunamis in Little Lakes
HIGMAN, B., Ground Truth Alaska, Alaska, USA, hig314@gmail.com;
KARASOZEN, E., Alaska Earthquake Center, Alaska, USA, ekarasozen@
alaska.edu; GEERTSEMA, M., Ministry of Forests, Lands and Natural
Resource Operations, Prince George, Canada, marten.geertsema@gmail.
com; SCHWARTZ, S., University of California, Santa Cruz, California, USA,syschwar@ucsc.edu

poster 56
Using Infrasound to Detect Snow Avalanches and Inform
Forecasts in Alaska
ALBERT, S. A., Sandia National Laboratories, New Mexico, USA, salber@sandia.gov; FLEIGLE, M. J., Sandia National Laboratories, New Mexico, USA,mjfleig@sandia.gov; SCHAIBLE, L. P., Sandia National Laboratories, New
Mexico, USA, dpschai@sandia.gov

The past decade has seen a spate of dramatic tsunamis, largely going unnoticed, triggered by landslides into small water bodies. This presentation will
explore examples since 2016 in British Columbia and Alaska, including thoselisted below:

Slab avalanches occur when an unstable mass of consolidated snow breaks
away from a mountain slope. These events can damage key infrastructure suchas roads, railways, and powerlines. It is expected that climate change will leadto increased avalanche activity. Avalanche forecasts, which are key to mitigating hazards, partially rely on visual observations, which cannot be made during low visibility. Infrasound observations, which work in all visibility conditions, have proven useful in the detection and characterization of avalanches
in Utah and Canada. However, there is limited research using infrasound to
detect and characterize avalanches in maritime snowpacks (those locatednear coastlines). Specific to Alaska, a need exists to effectively discriminate
between earthquakes and avalanches. We deployed an infrasound network
in Tutl’uh (Turnagain Arm), Alaska, USA to capture natural and triggeredavalanches. This presentation will detail the deployment and discuss plans fordata analysis.

Location
Date			
Cowee Creek
30 Dec 2016
Elliot Creek
28 Nov 2020
Brabazon Range~12 Aug 2021
Upper Pederson Lagoon 15 Apr 2022
Ecstall River
1 Sep 2022

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Landslidevolume (Mm3)

Maximum
runup (m)

0.5
18
~10
~1
5+

?
> 100
~30
~7
?

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SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.

from debris flows at near-field stations and for modeling debris flows in thedrainage.

poster 57
Deep Transfer Learning Framework for Regional Landslide
Mapping Using Post-Event Imagery
ASADI, A., Tufts University, Massachusetts, USA, adel.asadi@tufts.edu;
BAISE, L. G., Tufts University, Massachusetts, USA, laurie.baise@tufts.edu;
CHATTERJEE, S., Michigan Technological University, Michigan, USA,schatte1@mtu.edu; KOCH, M., Boston University, Massachusetts, USA,mkoch@bu.edu; MOAVENI, B., Tufts University, Massachusetts, USA, babak.
moaveni@tufts.edu

poster 59
Investigating Seismic Signals From the Barry Arm
Landslide
DAVY, G. K., University of Alaska Fairbanks, Alaska, USA, gdavy@alaska.
edu; KARASOZEN, E., University of Alaska Fairbanks, Alaska, USA,ekarasozen@alaska.edu; WEST, M. E., University of Alaska Fairbanks, Alaska,
USA, mewest@alaska.edu; LYONS, J., U.S. Geological Survey, Alaska, USA,
jlyons@usgs.gov

Landslides, often occurring in mountainous regions and triggered by earthquakes or heavy rainfall, are a major natural disaster. Traditionally, identifying landslides involves manually analyzing optical remote sensing imagery,a process that is both slow and labor-intensive. This study proposes an automatic landslide detection method using advanced deep learning techniques.
Previous research in this area has focused on using RGB channels from both
before and after the event, along with other data sources like digital elevation
models, for change detection. However, the effectiveness of deep learning inthis context depends heavily on the availability of high-quality, large datasets,
which can be a challenge in the immediate aftermath of a landslide. This study
specifically explores the transferability of a deep learning model trained ondata from the 2016 Kumamoto Earthquakes. It tests the model’s effectivenessin detecting landslides caused by different events: the 2018 Hokkaido earthquake and the 2017 Asakura Rainfall, both in Japan. These events were chosen
for their regional similarities, including terrain, vegetation, urban areas, geology, and landcover. The proposed deep convolutional neural network model
uses a ResNet50-based DeepLabV3+ framework, which facilitates automatedlandslide feature extraction from post-event images. This approach does not
require fine-tuning for each specific event or the development of unique training data sets. The model demonstrated high accuracy in identifying landslides
from the 2016 Kumamoto Earthquakes and performed well in the two unseen
events. The impacts of different tile sizes, number of tiles, imagery resolution,and data augmentation techniques are investigated to provide instructions on
best practices.
poster 58
Quantifying Seismic Properties of a River Channel atMount Rainier for Use in Debris-Flow Monitoring andAnalysis
CONNER, A. E., University of Oregon, Oregon, USA, aconner2@uoregon.
edu; THOMAS, A. M., University of Oregon, Oregon, USA, amt.seismo@
gmail.com; ALLSTADT, K. E., U.S. Geological Survey, Colorado, USA,kallstadt@usgs.gov; COLLINS, E., U.S. Geological Survey, Colorado, USA,ecollins@usgs.gov; THELEN, W. A., U.S. Geological Survey, Washington,
USA, wthelen@usgs.gov
One of several challenges in interpreting properties of surface processes, suchas debris flows, from seismic waves is developing accurate Green’s functions
for the environments through which the waves propagate. The waves generated from these processes are primarily recorded at local sensors, and theheterogeneous quality of the surface environment greatly affects the waves
over relatively short distances. In particular, the high-frequency energy thatis primarily generated by many surface processes is highly attenuated by nearsurface materials. Our research focuses on understanding some common seismic properties of channel material in the Tahoma Creek drainage at Mount
Rainier, USA, to accurately analyze the seismic waves from seasonal debris
flows in the drainage, the most recent of which occurred on 15 August 2023.
To investigate the seismic properties of the channel material, we deployed 9
nodal seismometers on 9 August 2022 in a ~70 m linear array perpendicular
to Tahoma Creek. We used a hammer to create seismic impulses adjacent tothe active channel to calculate surface wave velocities and Q, the quality factor for attenuation, for 10 Hz frequency bands between 20 Hz and 55 Hz. The
20 Hz to 55 Hz band encompasses both the majority of energy generated byour hammer blows and contained in our empirical Green’s functions for thechannel. The 2023 debris flow waveforms that were recorded on additional,
nearby temporary stations also primarily contained energy between ~20 Hz
and 40 Hz. As the channel is mostly composed of loose gravel, sand, and silt,
we find that the surface wave velocities and values for Q are very low and typically decrease with increasing frequency. The surface wave velocities are lessthan 200 m/s and the values for Q are less than 40 for all frequency bands. We
will use the results to correct the amplitudes of the empirical Green’s functions that we created for the region and extend the Green’s functions to theactive channel. These results will be crucial for interpreting the seismic signals

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Barry Arm is a glacier carved fjord located in Prince William Sound, AK.
The slopes are steep and unstable and have the potential for catastrophic failure and to cause landslide-driven tsunamis - a significant hazard for nearby
coastal communities.
With the threat of major slope failure looming overhead, identifying andinterpreting seismic signals seen on the Barry Arm Landslide is important torapid warning of tsunamis. We analyze seismic signals in this region beginning in the summer of 2020 to better understand slope mechanisms and possible precursor signals that may assist with warning time. Local glaciers andfrequent earthquakes in the area add to the complexity of the problem.
Utilizing two seismic stations, one positioned atop the slide and theother situated about 3 km away - across the fjord, we identify different styles ofseismic signals associated with the Barry Arm Landslide. These signals differ
from each other in terms of their shape, duration, amplitude and frequency.
We are able to distinguish these signals from glacier noise by waveform style,comparing amplitudes on different sides of the fjord, and by infrasound backazimuth. Our seismic station situation is unique as we have two local stations
that provide detailed insight into the activities occurring in the area.
We use detection algorithms (like STA/LTA) to develop time histories ofeach event type. These time histories can be compared to other environmental
factors including precipitation, temperature, and deformation of the slope. By
comparing seismicity with movement of the slope (identified though groundbased radar and remote sensing observations) and possible triggering factors
our goal is to identify seismic signals that may indicate deep-seated movement of the slope that can be potentially associated with catastrophic failure.
This study contributes to effective risk mitigation and the protection of coastal
communities.
poster 60
Seismology Versus Infrasound: Which Monitoring
Technique Is Better for Detecting Advancing Lahars?
ROCA, A., INSIVUMEH, Guatemala City, Guatemala, a100kr2611@gmail.
com; PINEDA, A., independent, Chimaltenango, Guatemala, pineda.
armando@gmail.com; JOHNSON, J., Boise State University, Idaho, USA,jeffreybjohnson@boisestate.edu; MOCK, J., Boise State University, Idaho,
USA, jerrymock@boisestate.edu; BEJAR, G., Michigan Technological
University, Michigan, USA, gbejarlo@mtu.edu; WAITE, G. P., Michigan
Technological University, Michigan, USA, gpwaite@mtu.edu
Recent studies have reported on remote detection of small secondary
lahars using infrasound (low frequency acoustic) arrays at Fuego Volcano(Guatemala). They demonstrated that the frequent small secondary lahars
generate a unique infrasound signature that is detectable when the lahar ismore than 5 km away from the recording site. At Fuego’s Ceniza drainage
these early warning detections precede the arrival of the actual lahar by asmuch as 20 to 30 minutes. This precursor can be enough time to provide an
early notification and complement subsequent alerts triggered by AFM systems (geophone seismology), which are particularly effective when situatedadjacent to a drainage. AFMs, using relatively high frequency seismic sensing,is a much more established tool for monitoring lahar activity. In this work
we evaluate the advantages and disadvantages of infrasound versus seismic
monitoring the small secondary lahars at Fuego.
We use a dataset of dozens of lahars from 2022 during which a seismoacoustic installation was situated adjacent to Ceniza at 14 km flow distancefrom the volcano. We observe that AFM monitoring has some distinct advantages, over infrasound, including a fundamentally less-noise signal associatedwith the passing of the flow. Infrasound monitoring at Fuego, in particular,
is complicated by multiple other sources of signal and noise, such as fromvolcanic vent activity, thunderstorms, aircraft, and wind. An advantage toinfrasound, however, is that it appears to be uniquely sensitive to more distantsources. While high frequency seismic ground vibrations appear to attenuate
relatively rapidly, such that the lahars are not seismically detectable further
than a few kilometers, arrays of (as few as two) infrasound sensors appear
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niques where the direction of incident infrasound is constrained by knowledge of the volcano’s drainages. With knowledge of the lahar’s flow path infrasound can be used to reliably detect many (but not all) of the lahar signals up
to tens of minutes before they arrive at the monitoring site.
poster 61
Repeated Seismicity Conditions Paraglacial Valleys for
Slope Failure in Prince William Sound, Alaska
MCCREARY, M. E., University of Utah, Utah, USA, molly.mccreary@utah.
edu; MOORE, J., University of Utah, Utah, USA, Jeff.moore@utah.edu;
JENSEN, E., University of Utah, Utah, USA, Ejensen@usgs.gov; GISCHIG,
V., ETH Zürich, Zürich, Switzerland, Gischigv@ethz.ch
Paraglacial valley rock slopes in Prince William Sound, Alaska are locatedwithin a highly active seismic region and are susceptible to damage fromearthquake shaking in conjunction with cycles of glaciation. We hypothesizethat because ice is rigid at high co-seismic strain rates, glaciers buttress adjacent ice-contact rock slopes during earthquakes reducing seismic damage,and that as glaciers retreat, the portion of the rock slope susceptible to seismic
damage increases. Repeated earthquakes over time thus help condition icefree areas of paraglacial valleys for slope failure. We use numerical modelingto assess rock mass damage generated by seismic loading at times of different
glacier elevations from the Last Glacial Maximum to present. Our models are
based on in-situ conditions at Serpentine Glacier Valley, which contains several large, active landslides. Results show the evolution of spatially distributed
rock slope damage generated by individual earthquakes, and how a history of
repeated seismicity in Serpentine Valley generates rock mass damage conditioning areas of the slope for failure during present-day ice retreat. Glaciers
buttress adjacent rock slopes during earthquakes reducing damage in areas ofice contact, while slopes above the glacier incur greater co-seismic fracturing.
Over time, earthquake induced damage is maximized in areas that are mostoften ice free, as well as at slope breaks and crests susceptible to topographic
amplification.
poster 62
Optimizing Landslide Detection and Validation ThroughSentinel-1 Radar Imagery: Case Studies of Hokkaido andHiroshima in Japan
THAPA, M., University of Oklahoma, Oklahoma, USA, manoj.thapa@ou.edu; JIANG, J., University of Oklahoma, Oklahoma, USA, jiang@ou.edu;
REGMI, N., University of Oklahoma, Oklahoma, USA, netraregmi@ou.edu
Satellite-based (optical and radar) imaging techniques are frequently
employed for landslide detection with short time intervals, especially for
emergency response, risk assessment, and hazard mitigation. While radar
imagery overcomes many limitations associated with optical imagery, it isstill constrained by various noise and distortions, potentially resulting in
the underestimation of significant landslides and an increased prevalence ofsmaller landslides. The primary objective of this study is to develop a methodology that can enhance the detection accuracy of different-sized landslides
using radar imagery. We utilize multi-temporal imagery from the C-band
Sentinel-1 satellites, which are freely available on the Google Earth Engine
platform, to analyze the rainfall-triggered landslides in Hiroshima and earthquake-induced landslides in Hokkaido, Japan, across different time frames.
We investigate the change in the backscattering intensity coefficient of radar
images with VV (vertical transmit-vertical receive) polarization and test theeffectiveness of speckle filtering and range-doppler terrain correction using
the SNAP software. We explore different cutoffs of the backscattering intensity coefficient, which increase the performance of the area under the ROC
curve, to determine the threshold that best captures significant changes associated with landslide events. We choose the same threshold for distinguishinglandslide and non-landslide areas in the backscattering intensity maps withand without speckle filtering. For validation, we quantitatively compare oursatellite-based detection results with the high-resolution optical-based landslide inventories in terms of the spatial overlap, sizes, and scaling properties oflandslides. The results indicate that filtering Sentinel-1 images enables morerobust detection of larger landslides and simultaneously reduces false negatives for smaller landslides. These additional processing steps hold promise
for more accurate and efficient landslide monitoring at various spatial scales
and potentially over time.

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poster 63
Landslide Susceptibility Assessment Using Earthquake
Ground Motion for Different Return Periods in Rasuwa
District, Central Nepal
THAPA, M., University of Oklahoma, Oklahoma, USA, manoj.thapa@ou.edu; PRADHAN, A. M. S., Water Resources Research and Development
Center, Government of Nepal, Lalitpur, Nepal, anantageo@hotmail.
com; CHAMLAGAIN, D., Tribhuvan University, Kathmandu, Nepal,
deepakchamlagain73@gmail.com; JIANG, J., University of Oklahoma,
Oklahoma, USA, jiang@ou.edu; REGMI, N., University of Oklahoma,
Oklahoma, USA, netraregmi@ou.edu
This study in Rasuwa district focuses on characterizing co-seismic landslideprone areas by integrating peak ground acceleration (PGA) data expected
for various earthquake return periods into a composite map that combinesseismic hazard and landslide susceptibility mapping (LSM). Probabilistic seismic hazard assessment (PSHA) is employed to generate seismic hazard maps,
depicting PGA for 50%, 10%, 5%, and 2% probability of exceedance (PE)over 50 years. Notably, hazard levels increase from the northern to southernparts of the study area, with the highest PGAs recorded at 0.19g, 0.35g, 0.45g,
and 0.55g, respectively. Simultaneously, logistic regression (LR) is utilized for
LSM, analyzing 890 co-seismic landslides with 23 different conditioning factors (CF). Standardization of continuous and categorical CF variables is conducted for the coefficients of each factor map. The relative relief emerges as themost significant predictor among the various factors, and the LSM results areclassified into five susceptibility indexes. High susceptibility areas concentrate
along both banks of the Trishuli River, the main drainage system in the southern part of the study area.
Validation of the LSM model is carried out using the area under the
ROC curve and statistical inferences method, demonstrating good agreementwith previous landslide occurrences. Composite maps reveal an increase insusceptible areas from 50% to 2% PE in 50 years, with high and very high susceptibility indexes increasing sequentially with rising PGA. The integration ofseismic hazard maps and LSM offers a comprehensive understanding of coseismic landslide-prone zones over different timeframes, providing valuable
insights for development planning. These results hold practical implications
for formulating and revising building code provisions, implementing slope
improvement measures, guiding generalized land use planning, and informing subsequent management strategies.
poster 64[Un]supervised Clustering of [Non-]Earthquake Signals
Commonly Recorded on Regional Seismic Networks
TONEY, L., U.S. Geological Survey, Colorado, USA, ltoney@usgs.gov;
ALLSTADT, K. E., U.S. Geological Survey, Colorado, USA, kallstadt@usgs.
gov; COLLINS, E., U.S. Geological Survey, Colorado, USA, ecollins@usgs.
gov; YECK, W., U.S. Geological Survey, Colorado, USA, wyeck@usgs.gov
It is well known that surficial mass movements (SMMs), such as landslides
and rock falls, have seismic signatures distinct from other routinely-recorded
seismic sources like earthquakes and explosions. However, overlaps between
the characteristics of these signals can still make it difficult to discriminate
between source types during operational seismic monitoring. This ambiguity
motivates the development of automated techniques for seismic signal classification. Furthermore, seismic differentiation within the broad class of SMMs
has additional scientific and rapid response value. Examination of SMM seismic waveforms highlights a particularly strong contrast between the signals
produced by primarily vertical processes — i.e., “falls” — versus processes
that have a non-negligible horizontal component — e.g., landslides and avalanches, or “slides” in our abbreviated terminology.
Here, we present a machine learning (ML) classification scheme for differentiating between seismic signals generated by falls versus slides. We additionally include shallow earthquakes and blasts because these are most similar
to SMM signals and are commonly recorded on regional seismic networks.
These classes, therefore, are the most useful for automated classification. We
neglect debris flows in this study because of their much longer durations andlow amplitudes. Our signals derive from waveform picks in the Exotic Seismic
Events Catalog, a diverse collection of non-earthquake seismogenic surface
events, and the ANSS Comprehensive Earthquake Catalog. We use a shallow,
feature-based approach to classification using statistical metrics extracted fromwaveforms. Feature importance metrics provide insight into the ML methods
we use, which leverage both unsupervised techniques (to assess the diversityof seismic signals in our training dataset via clustering) and supervised techniques (to train and evaluate a classifier). We picture our classification workflow as one modular element of a larger non-earthquake assessment workflowthat includes detection and location as preliminary (or concurrent) steps.

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poster 65
Seismically-Derived Ground Tilt From Rainfall-Triggered
Lahars at Volcán De Fuego, Guatemala
WAITE, G. P., Michigan Technological University, Michigan, USA, gpwaite@
mtu.edu; BEJAR, G., Michigan Technological University, Michigan,
USA, gbejarlo@mtu.edu; JOHNSON, J. B., Boise State University, Idaho,
USA, jeffreybjohnson@boisestate.edu; ESCOBAR-WOLF, R., Michigan
Technological University, Michigan, USA, rpescoba@mtu.edu; ROCA, A.,
Instituto Nacional de Sismología, Vulcanología, Meteorología e Hidrología(INSIVUMEH), Guatemala City, Guatemala, aeroca@insivumeh.gob.gt;
MÉRIDA, R., Instituto Nacional de Sismología, Vulcanología, Meteorología
e Hidrología (INSIVUMEH), Guatemala City, Guatemala, ermerida@
insivumeh.gob.gt; BOSA, A., Boise State University, Idaho, USA, ashleybosa@boisestate.edu; PINEDA, A., Unaffiliated, Guatemala City, Guatemala, pineda.
armando@gmail.com
Broadband seismometers deployed for lahar detection may also respond toload-induced ground rotation near the lahar channel. We analyzed tilt signals
on two permanent and four temporary broadband stations deployed along two
active secondary lahar channels on the flanks of Volcán de Fuego, Guatemala
over parts of three years. These rainfall-triggered lahars occur mainly between
May and October and have durations from 30 minutes to 6 hours. Seismic stations were located at distances from 10 to 350 m from the channels and havecorner frequencies at 60 or 120 seconds. These deployments were designed forlahar detection at relatively high frequencies at which lahars are most energetic. The seismograms exhibit clear signals below the instrument corners thatsuggest the lahar masses produce rotation at the stations. We began with a catalog of lahars for years 2021-2023. For each lahar, tilt was derived using a standard approach for signals below the instrument corner: integrating the raw
signal; applying a low-pass filter below the instrument corner; and multiplying
by a scale factor. The derived tilt signals are fairly complex and vary between
stations within a single drainage for a given lahar event. Typical signals havea relatively sharp onset followed by multiple pulses within a single lahar event
which are generally consistent with the timing of later flow surges as indicatedby the high-frequency seismicity. The tilt particle motions are not necessarily
perpendicular to the channel and are often elliptical. Finite-difference modeling using a UAS-derived high-resolution DEM suggests topographic effects
produce mismatches between back-azimuth and particle motion direction of
10-25º. In a small number of cases, we combine time-lapse camera images
with the lahar records to estimate the lahar masses. This study builds on earlier
work that demonstrates the utility of broadband seismometers as tiltmeters ina variety of natural settings.
poster 66
The September 16, 2023 Greenland Event: Mysterious
Days-Long Monochromatic Very Long-Period Signal
Triggered by a Landslide
CARRILLO-PONCE, A., GFZ Potsdam, Potsdam, Germany, carrillo@gfzpotsdam.de; PETERSEN, G., GFZ Potsdam, Potsdam, Germany, gesap@
gfz-potsdam.de; CESCA, S., GFZ Potsdam, Potsdam, Germany, cesca@gfzpotsdam.de; HEIMANN, S., University of Potsdam, Potsdam, Germany,sebastian.heimann@uni-potsdam.de; WALTER, T., GFZ Potsdam, Potsdam,
Germany, thomas.walter@gfz-potsdam.de; DAHM, T., GFZ Potsdam,
Potsdam, Germany, dahm@gfz-potsdam.dePeculiar, energetic seismic signals were generated close to the Dickson Fjord,a remote area of East Greenland on September 16, 2023, followed by a large
tsunami, which impacted the northern shore of Ella Island. Using highresolution Planet Labs Dove mini-satellite imagery we identify that a landslide occurred on the Southern side of the Dickson Fjord on the same day.
Seismic signals were recorded at regional to teleseismic distances. Besides afirst strong transient signal in the range of 0.02-0.06 Hz, which we attribute to
the landslide, a very long (~50 hours), low-frequency, monochromatic (~0.01
Hz) signal was observed at teleseismic distances. We modeled full waveform
broadband seismic data to invert for the seismic sources for both types of signals using moment tensor and single force models. The first transient signal
is well reproduced at regional distances by single and double source models,
which are consistent with the landslide process. The long lasting oscillating
signal is modeled at teleseismic distances by a damped dipole oscillator, which
reproduces the pattern of Love and Rayleigh waves observed at different azimuths. By combining different data and source models with the Fjord systemgeometry, we are able to reconstruct the complex source process.

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Earth’s Structure from the Crust to the Core
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Keith Koper, University of Utah (kkoper@gmail.
com); Jeroen Ritsema, University of Michigan (jritsema@umich.edu); Vera Schulte-Pelkum, University of Colorado(vera.schulte-pelkum@colorado.edu)
A High-Resolution Body Wave Tomography Super-VirtualInterferometry of the Rio Grande Rift
BARMAN, D., Baylor University, Texas, USA, debajeet_barman1@baylor.
edu; PULLIAM, J., Baylor University, Texas, USA, jay_pulliam@baylor.edu
The Rio Grande rift stretches from southern Colorado through New Mexico
into Mexico and it separates the eastern Great Plains from the southern
Colorado Plateau. To explore the relationship between the rift, the adjacent
Basin and Range Province, and the Colorado Plateau, we used seismic recordings of earthquakes from the La Ristra seismic deployment to model seismic
P velocities in the uppermost mantle beneath this region via Super-virtual
Refraction Interferometry. This technique improves the accuracy of Pn measurements by increasing its signal-to-noise Ratio via the Super-virtual Green’s
Function. We use data from over 50 earthquakes, mostly along the Gulf of
Alaska’s convergent plate boundary. This technique is useful for Moho modeling and understanding the structure of the Rio Grande rift. It enhances theamplitude of the Pn phase for seismograms recorded at distant stations, fromsmall-magnitude earthquakes, and/or in the presence of seismic attenuation
due to, for example, partial melt.
Specifically, we used vertical component broadband seismograms from58 different stations to create super-virtual refraction studies. The process
involves two primary steps to obtain the refracted Pn phases. We first estimate
the classical refraction by computing cross-coherence between seismograms
observed in two seismic stations. We then stack the virtual Green’s Functions
for a number of earthquakes that occurred in the Pacific Ocean, which aremostly colinear with the La Ristra seismic array. In the second step we convolve the seismogram of the closest station of a given station pair with thestacked virtual Green’s function. The output is stacked over seismograms
for all recorded earthquakes and then used for Pn refraction tomography tomodel Pn velocities beneath the La Ristra seismic deployment.
The Poisson’s Raio Surrounding the Subduction
Megathrust
MANN, M., Brown University, Rhode Island, USA, michael_mann@brown.
edu; ABERS, G. A., Cornell University, New York, USA, abers@cornell.edu;
FULTON, P. M., Cornell University, New York, USA, pfulton@cornell.edu
Hydrologic and lithologic variations along the plate interface in subduction zones control the strength and slip behavior of megathrust faults. Manymodels of plate interface fault slip behavior invoke high pore-fluid pressure
to explain the variability in rupture behavior. High pore-fluid pressure can
explain apparently high Poisson’s ratio (> 0.33, Vp/Vs > 2) within a lowvelocity zone (LVZ) along the plate interface, often inferred from studies ofthe scattered P-to-S seismic wavefield. We further investigate this region witharray-based deconvolution which allows for identification of the receiverside, surface-reflected and back-scattered P-to-P wavefield, and which has
finer resolution than the upgoing P-to-S scattered wavefield. Using the timing of surface-reflected P-to-S and P-to-P scattered phases in both the Alaska
and Cascadia subduction zones, inversions for LVZ properties result in Vp/
Vs < 2. Using both array-based and time-domain deconvolved teleseismic
waveforms, we show that Vp/Vs estimates that depend on the upgoing P-to-S
scattered phases might be biased toward high Vp/Vs (> 2.2) owing to theirlower volume resolution and the inherent frequency limitations in extracting these signals from P coda. These results indicate that anomalously highVp/Vs found while including the upgoing (direct) P-to-S scattered mode may
instead be an artifact of using band-limited signals or scattered-phase interference. These findings remove the observational requirement for a thick regionof high pore-fluid pressure and allow for alternative hypotheses to explain thesuite of fault slip behavior along the subduction zone plate interface.
Improving the Salt Lake Basin Velocity Model Using
Multi-Year Nodal Geophone Arrays
KIM, H., University of Utah, Utah, USA, hkim.geo@gmail.com; LIN, F.,
University of Utah, Utah, USA, FanChi.Lin@utah.edu; PECHMANN, J. C.,
University of Utah, Utah, USA, james.pechmann@utah.edu; MCKEAN, A. P.,
Utah Geological Survey, Utah, USA, adammckean@utah.gov; HARDWICK,

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C. L., Utah Geological Survey, Utah, USA, christianhardwick@utah.gov;
SMITH, K. D., Utah Geological Survey, Utah, USA, kayladsmith@utah.gov;
VAN DAM, T., University of Utah, Utah, USA, tonie.vandam@utah.edu
An accurate high-resolution velocity model is critical for evaluating the
ground shaking hazard from moderate to large local earthquakes. The current community velocity model (CVM) for the Salt Lake Basin in Utah wasconstructed mostly based on legacy gravity measurements, supplemented bysparsely distributed well logs and legacy active-source seismic profiles. Since
2018, the seismic data coverage of the Basin has substantially improved withthe addition of data from three nodal geophone experiments: a 2018 32-nodelinear array across the East Bench fault of the Salt Lake City segment of theWasatch fault zone, a 2020 217-node Magna earthquake (Mw 5.7) aftershockarray, and a 2023 38-node multi-month distributed array deployed to investigate hydro-geophysical signals. In this presentation, we will summarize
our recent effort to improve the Salt Lake Basin CVM by adding new constraints derived from the nodal data. Specifically, we will show that the first
positive peak of receiver functions in the Salt Lake Basin is sensitive to the
P-to-S conversion at the base of the semi-consolidated sediment layer, which
rapidly changes depth across the East Bench fault. Moreover, good correlations exist between the delay time of the first receiver function peak, Rayleighwave ellipticity, and the local gravity anomaly, demonstrating the potentialof jointly inverting the three datasets to refine the 3D basin model. We havedetermined a preliminary model by jointly inverting receiver function waveforms and Rayleigh wave ellipticities plus phase velocities. The results indicate
a greater thickness of unconsolidated and semi-consolidated sediments, compared to the existing CVM, between the East Bench fault and the West Valley
fault zone. This area underlies the most densely populated parts of Salt Lake
City. Our new velocity model will contribute to improved earthquake hazard
assessments by enabling more accurate numerical ground motion simulations
for realistic earthquake scenarios.
Seismic Structure of Northern Alaska From Ambient Noise
Adjoint Tomography
CHOW, B., University of Alaska Fairbanks, Alaska, USA, bhchow@alaska.
edu; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.
edu
Northern Alaska is a remote, arctic region roughly 1000 km from the nearest
plate boundary at the Alaska-Aleutian subduction zone. Physiographically,
the region is dominated by the east-west trending Brooks Range and the adjacent Colville Basin and North Slope region. Seismically, northern Alaska ischaracterized by diffuse bands of seismicity, distributed crustal deformation,and moderate-sized earthquakes (M<6). In this work, we take advantage ofyears of high-quality seismic data from the EarthScope Transportable Array toundertake a seismic imaging study of northern Alaska. Our goal is to generate
a 3D, high-resolution velocity model of structure below the region, in order toimprove our understanding of the regional tectonics. To accomplish this, weuse adjoint tomography, a seismic imaging method which seeks to minimize
differences between seismic data and synthetically-generated waveforms fromnumerical simulations of wave propagation. We use the empirical Green’s
function (EGF) dataset of C. Liu et al. (2022), which is derived from ambient
seismic noise and provides excellent data coverage of the region. Preliminary
results demonstrate that our inversion is sensitive to crust and upper mantle
structure, and it is able to resolve lateral velocity variations which show similarities to known geologic and tectonic features. Current efforts aim to invert
the EGF dataset for a target period band of 8–50s. We present ongoing workfrom this project, including an updated, anisotropic velocity model, and key
tectonic interpretations.
Using Local and Regional Travel Time Data From the ISC to
Estimate Lithospheric Velocity Structure
PASYANOS, M. E., Lawrence Livermore National Laboratory, California,
USA, pasyanos1@llnl.gov
While a great deal of seismic data is openly available, there are still someregions not well-covered by stations with open waveform data. In many of thesecases, however, arrival data from stations is contributed to the International
Seismological Centre (ISC). In the absence of waveform data, how effectively
can we utilize available ISC data to determine velocity structure? We havedeveloped a method of using simplified ray paths to model regional phases,
and use this method to model Pn, Pb, Pg, Sn, Sb, and Sg phases from crustal
events in East Asia. The travel times are then used to tomographically invert
for P-wave and S-wave velocities in the crust and upper mantle, as well as corresponding source terms, which can accommodate errors in origin time andVolume 95•

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depth, and site terms, which can accomodate local station conditions (e.g.,Vs30). We start with the simplest parameterization (layer over a half-space)
and then introduce additional complexity (e.g., variable Moho thickness,
additional crustal layers) to gauge its effect on our model. Preliminary results
show some success in retrieving the expected variations in crust and mantle
velocities from the seismo-tectonic structure, but a higher-order parameterization might be needed to capture the overall complexity of the region. We
can test the predictive nature of the models with the observed travel times
from ground-truth (GT) events not used in the development of the model. If
proven to be effective, we can readily apply the method to other regions where
waveform data may be limited.
Intraplate Volcanism in Northeast China Controlled by the
Underlying Heterogeneous Lithospheric Structures
CHEN, Q., Chinese Academy of Sciences, Beijing, China, chenqf@mail.
iggcas.ac.cn; FAN, X., Chengdu University of Technology, Chengdu, China,
fanxingli@cdut.edu.cn; AI, Y., Chinese Academy of Sciences, Beijing, China,
ysai@mail.iggcas.ac.cn
The origin and mantle dynamics of the Quaternary intraplate sodic and potassic volcanism in northeast China have long been intensely debated. Here we
present a high-resolution three-dimensional crust and upper mantle S-wave
velocity model of northeast China by combining ambient noise and earthquake two-plane wave tomography based on unprecedented regional dense
seismic arrays. Our seismic images highlight a strong correlation between thebasalt geochemistry and upper mantle seismic velocity structure: sodic volcanoes are all characterized by prominent low seismic velocities in the uppermost mantle, while potassic volcanoes still possess a normal but thin upper
mantle “lid” depicted by high seismic velocities. Linking our tomographic
images with previous petrological and geochemical study results, we propose that the heterogeneous lithospheric structures beneath northeast China
control the style of mantle dynamics in producing the Quaternary sodic andpotassic intraplate volcanism. The very young Wudalianchi and Nuominhepotassic volcanism is likely caused by the interaction between the asthenospheric low-degree melts and the overlying subcontinental lithosphericmantle, whereas the more widespread Quaternary sodic volcanism is directly
sourced from the upwelling asthenosphere as a result of localized lithosphericthinning and destruction.
Seismic Evidence for a Melt-Rich LithosphereAsthenosphere Boundary Along the Base of Young Slab at
Cascadia
WANG, X., Chinese Academy of Sciences, Beijing, China, wangxin@mail.
iggcas.ac.cn; CHEN, L., Chinese Academy of Sciences, Beijing, China, lchen@mail.iggcas.ac.cn; WANG, K., Geological Survey of Canada, Sidney, Canada,kelin.wang@NRCan-RNCan.gc.ca; CHEN, Q., Chinese Academy of Sciences,
Beijing, China, chenqf@mail.iggcas.ac.cn; ZHAN, Z., California Institute ofTechnology, California, USA, zwzhan@gps.caltech.edu; YANG, J., Chinese
Academy of Sciences, Beijing, China, jianfengyang1989@gmail.com
Knowing the nature of the Lithosphere-Asthenosphere Boundary (LAB),
which separates the stronger lithosphere from the underlying weaker asthenosphere, is fundamental to understanding how plate tectonics works. For
the oceanic lithosphere, the LAB is generally imaged as a negative seismic
discontinuity and is widely thought to indicate the presence of partial melt.
A melt-rich LAB would mechanically decouple lithospheric plates from theasthenosphere and thus facilitate plate motion. However, the fate of a meltrich LAB is unclear after these plates descend into the mantle at subduction
zones. To date, the LAB beneath subducting slab (hereinafter referred to as
slab-LAB) has been reported only in subduction zones in Japan and New
Zealand, and in both cases the age of the subducting plate is very old (~120130 Ma). In contrast, no slab-LAB has ever been reported where young plates
are subducting. Here, we provide strong evidence for the presence of slab-LAB
at Cascadia, where the subducting plate is as young as ~10 Ma. Using teleseismic waveforms recorded by dense arrays and a coherent receiver function
imaging technique, here we image the slab-LAB at Cascadia in the form of alarge (9.81.5) decrease in shear-wave velocity over a very small (<3 km) depth
interval. We consider the imaged slab-LAB to be compelling evidence for thecontinuation of the melt-rich plate LAB after subduction. Similarly large andsharp seismic velocity reduction at the bottom of both old and young slabs, aswell as along the base of oceanic plates before subduction, possibly represents
widespread presence of melt. The melt-rich slab-LAB may strongly influencesubduction dynamics and viscoelastic earthquake cycles.

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Mantle Upwelling, Continental Sutures, and LAB Structure
Identified From a Suite of Seismic Data Types in the
Eastern United States
BRUNSVIK, B. R., University of California, Santa Barbara, California, USA,
brennanbrunsvik@ucsb.edu; EILON, Z., University of California, Santa
Barbara, California, USA, eilon@geol.ucsb.edu; LYNNER, C., University of
Delaware, Delaware, USA, clynner@udel.edu
The eastern US was constructed over several Wilson cycles, with multiple
continent-scale sutures preserved in the geologic record. During the breakup
of Pangea, the eastern North American lithosphere was heavily modified, with
implications for ongoing mantle dynamics along the margin. Previous seismological imaging has lacked needed resolution to assess how ancient boundaries and recent processes manifest throughout the lithosphere. We present
a high-resolution, plate-scale seismic tomography model of the eastern US.
We inverted seismic velocity using Rayleigh and Love wave phase velocity,
Rayleigh wave ellipticity, and Sp and Ps receiver function data. This combination of data provides resolution from the crust to the asthenosphere, constraining both absolute velocity and the depths of velocity discontinuities. We
produce maps of crustal properties, mantle velocity, lithospheric depth andmid-lithospheric discontinuities. A sharp step in lithospheric thickness at theAppalachian front explains mantle upwellings that may erode the base of theplate and shape modern Appalachian topography. We identify low-velocity
structures in the lithospheric-mantle that align with the Grenville front andmay be remnants of Rodinia assembly. Heavily modified lithosphere east of
the Appalachians is a legacy of post-Pangean extension, CAMP magmatism,
and ongoing dynamics.
Crustal Structure of Eritrea from Receiver Function
Analysis
GAUNTLETT, M. Z., University of Oxford, Oxford, United Kingdom, miriam.
gauntlett@linacre.ox.ac.uk; STEPHENSON, S. N., University of Oxford,
Oxford, United Kingdom, simon.stephenson@earth.ox.ac.uk; KENDALL, J.,
University of Oxford, Oxford, United Kingdom, mike.kendall@earth.ox.ac.uk;
OGDEN, C., University of Leicester, Leicester, United Kingdom, chris.ogden@
leicester.ac.uk; HAMMOND, J. O. S., University of London, London, United
Kingdom, james.hammond@bbk.ac.uk; HUDSON, T., University of Oxford,
Oxford, United Kingdom, thomas.hudson@earth.ox.ac.uk; GOITOM, B.,
University of Bristol, Bristol, United Kingdom, berhegoitom14@gmail.com;
OGUBAZGHI, G., Eritrea Institute of Technology, Himbrti, Mai Nefhi,
United Kingdom, ogubazghi_ghebrebrhan@yahoo.com
Located near the Afar Triple Junction, Eritrea hosts the Danakil microplateand is undergoing the final stages of on-land rifting. To better understand thenature of the Eritrean crust and continental breakup, we calculate teleseismic
receiver functions across Eritrea and Afar. We estimate the Moho depth andbulk crustal VP/VS ratio using the H-κ stacking method. The heterogeneity of
our crustal thickness results (~35 km — ~19 km) indicates that the Danakil
microplate has undergone stretching and crustal thinning, and that rifting ishighly localised in the Gulf of Zula. By investigating the relationship between
crustal thickness and topographic elevation in Eritrea and Afar, we estimate
the regional crustal density as ρc ≈ 2950 kg m-3, which is denser than the
global average of ρc ≈ 2880 kg m-3. Our results demonstrate very strongly
positive residual topography in the region. We propose that this topography
is supported by the mantle plume responsible for the onset of rifting in East
Africa, generating uplift due to the presence of a hot thermal anomaly beneaththe plate and by thinning of the lithospheric mantle. We also observe high VP/
VS ratios of > 1.9 in Eritrea. Our results demonstrate the presence of partial
melt in the crust, and that magma-assisted extension continues to be important in the final stages of continental breakup.
Surface-Wave Diffraction Stripes: Measurement,
Observables, Explanation, Modeling and Inversion
KOLÍNSKÝ, P., Institute of Geophysics of the Czech Academy of Sciences,
Prague, Czechia (Czech Republic), petr.kolinsky@ig.cas.cz; BELINIĆ TOPIĆ,T., University of Zagreb, Zagreb, Croatia, tena.belinic.topic@gfz.hr; VECSEY,
L., Institute of Geophysics of the Czech Academy of Sciences, Prague, Czechia(Czech Republic), vecsey@ig.cas.cz; WORKING GROUP, t., AlpArray,
Zurich, Switzerland, petr.kolinsky@volny.cz
Peculiar stripe-like patterns of amplitude variations and arrival angle deviations of teleseismic surface waves have been observed thanks to large dense
networks of broadband seismic stations, such as USArray in the United States,
NECESSArray in China and recently AlpArray (2015-2019) in Europe. There
are several properties of the stripes, which show that the pattern is not causedby the structure beneath the observation location—the large dense network,

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Seismological Research Lettersbut rather imported with the wavefield to the network from outside. One of
the most striking observables is the lateral shift of the stripes with varying
periods of surface waves. We proposed and tested a hypothesis that these patterns are caused by diffraction and consequential interference after the wavefield has passed a single small-scale scatterer. The wavefield carries the imprintof the scatterer for thousands of kilometers and allows for localizing the position of the scatterer, its size and strength.
We summarize the observation of stripe-like patterns for several earthquakes recorded by the AlpArray seismic network, which was distributed
over the greater Alpine region in Europe and consisted of 290 temporary
and more than 300 permanent broadband stations. We show how for different earthquakes the interference pattern moves across the network when the
period of surface wave changes. We give examples of patterns in group velocity measured at every station individually, in arrival angles (slowness vector,
phase velocity) measured by sub-array beamforming and we show how thepattern emerges when we calculate the gradients of phase wavefronts similar
to eikonal tomography. We observe the pattern also in the polarization of surface waves and their amplitudes. We discuss how all these observables match
together and how the modeling explains them. We show that it is possible
to invert the observed interference pattern to locate the scatterer which had
caused it, giving examples of particular upper-mantle low-velocity bodies andplumes. We also discuss how the phase and group travel times distorted byinterference can affect global and regional tomography.
The Continental Collision and Rifting in East North
America Margin Revealed by Full Waveform Tomography
LEI, T., University of Toronto, Toronto, Canada, tin.lei@mail.utoronto.
ca; WANG, K., University of Science and Technology of China, Anhui,
China, wangk@ustc.edu.cn; HE, B., University of Texas at Dallas, Texas,
USA, binhebj@gmail.com; DU, N., University of Toronto, Toronto, Canada,
nanqiao.du@mail.utoronto.ca; LIU, T., University of Toronto, Toronto,
Canada, tianshi.liu@mail.utoronto.ca; LIU, Q., University of Toronto, Toronto,
Canada, liuqinya@gmail.com
The East North America Margin (ENAM) represent a passive continental margin that has undergone several stages of collision and rifting throughout geological history. Notably, the formation and breakup of Rodinia and later, theassembly and breakup of Pangea. The strong collision resulted in the uplift of
the Appalachian Mountains, while the period of extension was accompaniedby extensive magma upwelling and the formation of sedimentary basins. The
complex geological history makes the ENAM an ideal natural laboratory forstudying continental collision and rifting processes. Our study focuses on several regions with dense array deployment, and they are SESAME array (Parker
et al., 2013) in Southern Appalachians, MAGIC array (Long et al., 2020) in
central Appalachians and SEISConn array (Long and Aragon, 2020) in northern Appalachians. With three case studies, we aim to compare the similarities
and differences in the evolution at different locations along ENAM.
We employed a joint full-waveform inversion (FWI) approach utilizing ambient noise data and teleseismic data based on the precise 3DSpectral Element Method (SEM) solver. This methodology enabled the creation of high-resolution isotropic shear wave velocity models in the three
regions. Upon comparing these models, we observed a consistent variationin Moho depth along the Appalachians. Notably, the central and northern
Appalachians exhibited a more pronounced depth variation than the southern Appalachians. Additionally, we investigated the anisotropic structure ofthese regions, revealing robust positive radial anisotropy along the terraneboundaries in all three areas, likely resulting from the Mesozoic rifting event.
Nevertheless, the anisotropy pattern differed between the southern and northern Appalachians, suggesting distinct collision and splitting dynamics. The
inverted models provide intricate subsurface insights beneath ENAM and represent a valuable dataset to enhance our comprehension of continental collision and rifting processes.
P-Wave Attenuation Structure and Melting Processes of
the Tonga-Lau Mantle Wedge
ZHANG, Y., Michigan State University, Michigan, USA, yurong@msu.edu;
WEI, S., Michigan State University, Michigan, USA, swei@msu.edu; BYRNES,
J. S., Northern Arizona University, Arizona, USA, Joseph.Byrnes@nau.edu;
TIAN, D., China University of Geosciences, Wuhan, China, dtian@cug.edu.
cn; WANG, F., Michigan State University, Michigan, USA, wangfa16@msu.edu;
BEZADA, M., University of Minnesota, Minnesota, USA, mbezada@umn.edu
The fast-converging Tonga subduction zone and its adjacent Lau back-arc
form a complex system where the melting mechanisms show significant alongstrike variations. To estimate melt fraction and further investigate the thermal and rheological structures in the Tonga Lau mantle wedge, we present an

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improved P-wave attenuation tomography model. We first incorporate independently constrained source parameters to invert for the path-average attenuation operator t*. Then, based on the refined t* dataset, we apply a BayesianMarkov chain Monte Carlo technique to image the Tonga-Lau subduction
system’s 3D P-wave attenuation structure. Compared to previous models, thisnew Qp model is built upon a more accurate 3D velocity tomography modeland utilizes more precise parameterizations in a spherical coordinate system.
The new results exhibit high attenuation anomalies in the Tonga-Lau back-arc
mantle and beneath the Taveuni Volcano. With the help of the Very Broadband
Rheology (VBR) Calculator (Havlin et al., 2021), we can quantitively estimate
along-strike variations in melt fraction and temperature. Preliminary results
show an increasing trend of melt fraction from south to north. The highest
melt fraction reaches up to ~6.5% beneath the Central Lau Spreading Center.
Illuminating Earth’s Inner Core Fine-Scale Heterogeneity
With Small Aperture Arrays
WU, S., Lawrence Berkeley National Laboratory, California, USA, a06859a35@
gmail.com; PANG, G., Cornell University, New York, USA, yuupgn@gmail.
com; KOPER, K., University of Utah, Utah, USA, keith.koper@utah.edu
The Earth’s inner core is seismically heterogeneous at scales of 1–10 km. The
fine-scale heterogeneity is manifested in high-frequency (1–4 Hz) backscattered energy following reflections (PKiKP) from the inner core boundary andis very difficult to observe, resulting in a lack of a comprehensive probe. In thisstudy, we utilize small-aperture seismic arrays—designed to detect tiny signals
from underground nuclear explosions—to characterize the inner core heterogeneity in a global scale. We use all the viable data from earthquakes (Mw ≥5.7) within the past 2–3 decades recorded at distances of 50°–75° from an array.
With array processing, we develop a framework for detection and extractionof the inner core scattered energy, which is characterized as emergent, growing, and spindle-shaped PKiKP coda. We found that individual seismic traces
lacking clear evidence of PKiKP coda waves reveal the scattering characteristics when stacked together, implying the inner core scattering is ubiquitous.
Furthermore, we employ a modified phonon-based simulation to model thescattering strength to construct the first global three-dimension inner core
heterogeneity model. Our model shows the scattering strength substantially
increases 500–800 km beneath the inner core boundary across the globe. The
enhanced scattering implies an irregular solidification evolution of Earth’s core.
Waveform Changes Due to Moving Scatterers - Application
to the Inner Core
WANG, R., University of Southern California, California, USA, ruoyanw@
usc.edu; VIDALE, J., University of Southern California, California, USA,jvidale@usc.edu
Fine-scale heterogeneity in Earth’s inner core (IC) has been identified fromscattering of PKIKP. The differential rotation of the IC is expected to alignwith Earth’s rotation axis according to geodynamical modeling and seismic
evidence (Wang & Vidale, EPSL 2022). For a similar differential rotation of theIC, equatorial and polar raypaths may exhibit distinct changes in scattering(Pang & Koper, 2022). Understanding the sensitivity of different raypaths tothe shift of IC scatterers can facilitate our interpretation of inner core motion.
Here we perform 2D wavefield scattering simulations using the spectral-elemental toolkit Salvus. We analyze the variation of forward-scatteringand back-scattering waveforms as the heterogeneity is shifted radially along
and transversely across the raypath. The radial and transverse movementsof heterogeneity approximately correspond to equatorial and polar raypaths
sampling the IC. The back-scattering and the forward scattering geometry
approximates the PKIKP raypaths with different distances.
Distinct variation patterns in the PKiKP coda are observed between
the two directions of shift (heterogeneity shift is 1 cell, with RMS variations
about 10%) and the two raypaths. For forward-scattering, a radial shift almost
doesn’t change the waveforms, whereas transverse shifts result in significant
waveform variations; for the back-scattering case, a radial shift mainly delays
or advances the phase, while transverse shift leads to both timing and amplitude changes. The evolution with lapse time of the waveform similarity andtime shifts, also have distinct patterns, which will be discussed in detail.
Distinguishing the effect of the moving scatterers across different geometries will contribute to constraining the rotation of the IC and will provide adeeper general understanding of scattering behavior.
2020-2030. A Golden Decade for Very Broad Band Planetary
Seismology and Seismic Imaging of Mars and Moon
Interiors
LOGNONNÉ, P. H., Université Paris Cité, Paris, France, lognonne@
ipgp.fr; PANNING, M. P., Jet Propulsion Laboratory, California, USA,

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mark.p.panning@jpl.nasa.gov; BANERDT, W. B., Jet Propulsion Laboratory,
California, USA, wbruce@banerdt.net; CEYLAN, S., Eidgenössische
Technische Hochschule Zürich, Zürich, Switzerland, savas.ceylan@erdw.ethz.
ch; CLINTON, J., Eidgenössische Technische Hochschule Zürich, Zürich,
Switzerland, jclinton@sed.ethz.ch; DELBO, M., Observatoire de la Côted’Azur, Nice, France, delbo@oca.eu; DE RAUCOURT, S., Université Paris Cité,
Paris, France, deraucourt@ipgp.fr; DRILLEAU, M., Institut de l’Aéronautiqueet de l’Espace, Toulouse, France, melanie.drilleau@isae.fr; GARCIA, R.,
Institut de l’Aéronautique et de l’Espace, Sup-Aéro, Toulouse, France,raphael.garcia@isae-supaero.fr; GIARDINI, D., Eidgenössische Technische
Hochschule Zürich, Zürich, Switzerland, domenico.giardini@erdw.ethz.ch;
KAWAMURA, T., Université Paris Cité, Paris, France, kawamura@ipgp.fr;
KNAPMEYER-ENDRUN, B., Deutsches Zentrum für Luft- und Raumfahrt,
Köln, Germany, brigitte.knapmeyer-endrun@dlr.de; KIM, D., Imperial College
London, London, United Kingdom, doyeon.kim@imperial.ac.uk; NUNN, C.,
Jet Propulsion Laboratory, California, USA, ceri.nunn@jpl.nasa.gov; PIKE,
W. T., Imperial College, London, United Kingdom, w.t.pike@imperial.ac.uk;STÄHLER, S., ETH Zurich, Zürich, Switzerland, simon.staehler@erdw.ethz.
ch; SAMUEL, H., Université Paris Cité, Paris, France, samuel@ipgp.fr
The Mars NASA InSight mission re-started seismology in planetary science,
40 years after Apollo and Viking.
SEIS, InSight’s French led international seismometer, operated from2/2019 to 12/2022. Thanks to its ground installation and wind shielding, thevery-broad-band (VBB) sensors of SEIS achieved ultra-low noise levels during
the first half of the night. This enabled a very low detection threshold, down tomoment magnitude MW=1 regionally and 4 on a global scale.
More than 1300 events during the 4 years of operation were detectedby the MarsQuake Service from VBB data, including a MW =4.7 marsquakethat excited surface waves and likely normal modes. Eight impacts were also
confirmed by orbital crater imaging, two with MW =4 and very large craters.
Nearly half of the events were located near Cerberus Fossae, where possibly
volcanic seismo-tectonics is ongoing.
Through these seismic events, SEIS provided the first seismic modelsof Mars, from the 40 km thick crust beneath InSight down to the core. Thesemodels revealed the stratigraphy of the crust, including through surface
wave anisotropy, the structure and thickness of the thermal lithosphere andthe presence of a molten silicate layer at the bottom of the mantle beneatha partially molten layer. Comparisons of these Martian interior and seismic
properties with those of the Moon and Earth, obtained from Apollo and Earthseismic networks, are now possible, opening a new research field: comparative
planetary seismology
And SEIS will continue its journey to the Moon with the JPL/CNES/
IPGP Farside Seismic Suite, which will deploy in 2026 one of the spare sensors of InSight VBBs in the farside Schrödinger basin. FSS will operate thisvertical VBB with performance at 1 Hz more than 10x better the Apollo seismometers. Data will be processed by the FSS LunarQuake Service and will becompleted by Earth based impact flash monitoring. We therefore conclude
with the science goals of this new mission in terms of deep interior imaging,as well as perspectives in terms of global seismic network on the Moon, if
complemented by other missions deploying seismometers.

Earth’s Structure from the Crust to the Core [Poster
Session]Poster Session • Thursday 2 May
Conveners: Keith Koper, University of Utah (kkoper@gmail.
com); Jeroen Ritsema, University of Michigan (jritsema@umich.edu); Vera Schulte-Pelkum, University of Colorado(vera.schulte-pelkum@colorado.edu)
poster 1
Cenozoic Uplift and Volcanism of Hangai Dome, Central
Mongolia Triggered by Lower Mantle Upwellings
BAO, X., Zhejiang University, Hangzhou, China, xwbao@zju.edu.cn; WU, Y.,
Zhejiang University, Hangzhou, China, ykwu@zju.edu.cn
The mechanisms of surface uplift of Hangai Dome (>2 km) and formationof Cenozoic intraplate volcanism in central Mongolia remain vigorously
debated. Here we directly investigate the mantle transition zone (MTZ)
structure beneath central Mongolia to explore whether the deep mantle geodynamical processes have played a role. Our results reveal significant MTZ
thinning of 8–13 km in three subareas mainly caused by the uplifted 660-km

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discontinuity (~10 km). In addition, the 410-km discontinuity is depressedbeneath the Hangai Dome (~6 km) and the northern portion of the study area
(10–15 km). These observations provide direct evidences for intracontinental
mantle upwellings from the lower to the upper mantle, causing the Cenozoic
uplift and basaltic volcanism of central Mongolia. Furthermore, these mantle
upwellings are relatively sluggish compared to canonical mantle plumes basedon the small magnitude of MTZ thinning and thus relatively moderate thermal anomaly within the MTZ (62–100 K).
poster 2
Single-Station Teleseismic Data Analysis and Structure
Imaging on Both Earth and Mars
CHEN, L., Chinese Academy of Sciences, Beijing, China, lchen@mail.iggcas.
ac.cn; WANG, X., Chinese Academy of Sciences, Beijing, China, wangxu@
mail.iggcas.ac.cn; WANG, X., Chinese Academy of Sciences, Beijing, China,
wangxin@mail.iggcas.ac.cn; YANG, R., Chinese Academy of Sciences, Beijing,
China, yangrh2021@mail.iggcas.ac.cn
Analysis of single station, multicomponent teleseismic data has been recently
performed with success in high-resolution imaging of shallow crustal structures (up to ~10 km depth), bridging the gap in between fine-scale (~km)
near-surface seismic exploration and large-scale (several tens to hundreds
and thousands of kilometers) deep passive-source imaging. A key idea in suchsingle station data analysis is to utilize the frequency dependence of amplitude
ratios between the horizontal and vertical components of teleseismic bodywaves, which is sensitive to the absolute velocity value and its variation withdepth at the target station. The associated single-station based new imaging
method is capable of achieving a vertical resolution of ~0.5 km, about oneorder of magnitude higher than other teleseismic methods commonly used
for shallow crustal imaging. Here we present the details of the method and its
applications to a number of continental tectonic zones of various structuralfeatures. We show that the method is flexible and effective for both cases ofdense arrays and sparse station distributions. In particular, by expanding thesingle-station analysis scheme to mitigate the effects of strong noise and data
insufficiency, we demonstrate the applicability of the imaging method to the
InSight low-frequency marsquake data in constraining the subsurface structure of Mars.
poster 3
Full-Waveform Inversion of the Upper Mantle Beneath the
Arabia-Eurasia Collision Zone
CLENNETT, E. J., University of Texas at Austin, Texas, USA, edward.
clennett@utexas.edu; LIU, C., University of Texas at Austin, Texas, USA,lcj2012@utexas.edu; GRAND, S. P., University of Texas at Austin, Texas, USA,steveg@jsg.utexas.edu; BECKER, T. W., University of Texas at Austin, Texas,
USA, twb@ig.utexas.edu
Despite being one of the most recent major orogenic events, the timing of the
Arabia-Eurasia collision is still debated. Much of the discrepancy arises due
to uncertainties over the amount of continental subduction of the Arabianpassive margin and the timing of a hard collision of cratonic Arabian lithosphere with Eurasia. However, subducted continental lithosphere and underthrusted cratons can be imaged using high resolution seismic tomography, as
has recently been demonstrated in the Himalayan region (Liu, 2023). In thisstudy, we perform a full waveform inversion of mantle structure beneath theTurkish-Iranian plateau, using regional earthquakes, which have good horizontal and vertical resolution in the upper mantle. We use a normalized crosscorrelation misfit function, which fits both the phase and relative amplitudeof multi-path arrivals (Tao et al., 2017). This allows us to extract additional
information from complex triplicated waves that provide good coverage of theupper mantle. We present preliminary results of our model of upper mantle
structure beneath the Middle East and use it to test different tectonic scenarios
for the Arabia-Eurasia collision.
References:Liu, C. (2023). Constraining East Asia Tectonics From Full Waveform
Seismic Tomography (PhD Thesis). The University of Texas at Austin. Tao,K., Grand, S. P., & Niu, F. (2017). Full-waveform inversion of triplicated datausing a normalized-correlation-coefficient-based misfit function. Geophys. J.
Int., 210, 1517–1524.

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Finite Difference Approach to Seismic Wavefield ModelingAcross the Hawaii-Emperor Ridge
FUJIMOTO, M., University of Hawaii at Manoa, Hawaii, USA, megumif7@
hawaii.edu; DUNN, R., University of Hawaii at Manoa, Hawaii, USA, dunnr@
hawaii.edu
Volcanic seamount chains are widespread throughout ocean basins. P-wave
travel time tomography allows for imaging the interiors of these volcanoes,
but that requires proper waveform identification of seismic phases that propagate across complex volcanic structures. Current limitations on the numberof seismic phases included in tomographic analyses results in less detailed
images and a poorer understanding of geological structures than may be possible. In previous studies (Dunn et al., 2019; Watts et al., 2021; Xu et al., 2022;
MacGregor et al., 2023), several seismic phases were identified in recorded
sections collected along the Hawaiian-Emperor Chain. However, interpretingthe origins of some of these phases remains challenging, and others remaina mystery. In this study, we developed an idealized seamount model basedon the seismic structure of Jimmu Guyot (Xu et al., 2022) and calculate theseismic P-SV wavefield for various source and receiver positions using a finite
difference wavefield modeling code (Levander, 1988; Lata and Dunn, 2020).
Our goal is to model observed seismograms and identify additional phases,
including P-to-S converted waves. We also intend to verify recent tomographic
images of the Hawaiian-Emperor Seamount Chain made by travel time inversion via wavefield matching. By resolving any ambiguities and pinpointing
new seismic phases, we aim to enhance future seismic images of the HawaiianEmperor Chain and contribute to improvements in our knowledge of thenature of specific structures, such as volcanic cores (a high-density and highwave-speed interior core of the seamount), the hypothesized magmatic underplating of the oceanic crust by mantle melts rising beneath the volcanic chain,and the nature of the Moho and oceanic crust beneath these volcanic edifices.
poster 5
Global Shear-Wave Amplitude Observations using Full
Waveform Modeling
GHOSH, A., Colorado School of Mines, Colorado, USA, ayonghosh@mines.
edu; BOZDAG, E., Colorado School of Mines, Colorado, USA, bozdag@
mines.edu; RITSEMA, J., University of Michigan, Michigan, USA, jritsema@umich.edu
Amplitudes of seismic phases provide unique constraints on the elastic andanelastic structure of the mantle. In this study, we analyze observed and synthetic seismograms to explore how wave-speed gradients and the anelastic
structure of the mantle influence the amplitude of major shear waves S, SS,
SSS, ScS and Sdiff and how the existing global models explain them. Our
observations are the ratios of the amplitudes of these body-wave phases andamplitudes predicted for the PREM model (Dziewonski & Anderson 1981)
and Global CMT source parameters. We also define measurements as thelogarithmic ratio of the amplitudes of multiple phases, such as SS/S and SSS/
SS, to minimize source and receiver effects and discriminate the influence of
the upper and lower mantle. These ratios from synthetic seismograms showmuch better agreement with those observed from real data. We do not see
much variation in SS/S ratios according to their bounce point variation incontinental or oceanic crust.
Using the 3D global seismic wave propagation solver SPECFEM3D_
GLOBE for 55 global earthquakes we computed amplitude ratios for two
global mantle and crustal models: 1) S40RTS (Ritsema et al. 2011) with andwithout Crust2.0 (Bassin et al. 2000), and 2) GLAD-M25 (Lei et al. 2020) with
1D Q models (PREM and QL6, respectively). Amplitude ratios for synthetic
seismograms with 1D crustal structures cannot explain the observed amplitude measurement patterns. 3D mantle and 3D crustal models better explain
the observed global patterns, and the 3D mantle models predict a consistenteffect of the 3D heterogeneities on the amplitude ratios. We explore the possibility of using these measurements as misfit functions in adjoint tomography
by looking at their kernels. We also try to understand the effect of the scale
length of the heterogeneities in the observed amplitude ratios.
poster 6
Building a Community Velocity Model for the Cascadia
Region and Beyond
HOOFT, E., University of Oregon, Oregon, USA, emilie@uoregon.edu;
DELPH, J. R., Purdue University, Indiana, USA, jdelph@purdue.edu;
GRANT, A., U.S. Geological Survey, Washington, USA, agrant@usgs.gov;
SAHAKIAN, V. J., University of Oregon, Oregon, USA, vjs@uoregon.edu;
SHARE, P., Oregon State University, Oregon, USA, sharep@oregonstate.edu;
STEPHENSON, W. J., U.S. Geological Survey, Colorado, USA, wstephens@www.srl-online.org•

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usgs.gov; TOOMEY, D. R., University of Oregon, Oregon, USA, drt@uoregon.
edu; WIRTH, E., U.S. Geological Survey, Washington, USA, emoriarty@
usgs.gov; MACGUIRE, R. R., University of Illinois Urbana-Champaign,
Illinois, USA, rossrm@illinois.edu; LI, G., University of Southern California,
California, USA, guolingl@usc.edu
Multi-scale information on P-wave and S-wave velocities and density in a tectonically active region is fundamental to a deeper understanding of subsurface processes (e.g., mantle hydration, Moho topography, crustal lithology),
as input to other science activities (e.g., seismicity relocation, Green’s function
estimation), and, especially at shallow depths, to better quantify seismic hazard. The recently NSF-funded Cascadia Region Earthquake Science Center(CRESCENT) paves the way to build a multi-scale community velocity model(CVM) of the Cascadia region (https://cascadiaquakes.org/cvm/). This model
will be a first-order product for other CRESCENT working groups’ scienceand will help make significant advances in our understanding of the Cascadia
subduction zone structure and associated hazards.
The CRESCENT CVM working group will combine active and passive
seismic data acquired onshore and offshore in a region spanning the entire
Cascadia subduction zone, from the Juan de Fuca Plate to well into the backarc along the Idaho-Montana border and from the Mendocino triple junction (~38°N) to the Queen Charlotte fault (~52°N). We will start with low
wavenumber data to resolve regional-scale structure into the upper mantle
using Bayesian joint inversions of P-wave radial receiver functions and ambient noise-derived Rayleigh waves. Subsequently, upper crustal structure (lateral resolution of <5 km) will be incorporated using information from active
source datasets, P- and S- wave travel times, and higher frequency ambient
noise data from higher density networks including legacy and recent datasets. Later model generations will incorporate a geotechnical layer. Formal
uncertainty analysis will be completed for each generation of the model andwe will validate the final model against recorded waveforms (ideally up to >1Hz) from regional and moderate-sized events. The various generations of the
CVM will be available for CRESCENT-related science and community users
in various formats. CVM building and validation is a Cascadia communitywide effort and mechanisms for contributing will be presented.
poster 7
Complex Upper Mantle Flow Beneath the Southern Korean
Peninsula Constrained by Shear Wave Splitting andNumerical Mantle Convection Simulation
JO, K., Korea University, Seoul, South Korea, jkyeongjun@gmail.com; SONG,
J., Seoul National University, Seoul, South Korea, wjdgns230@gmail.com;
KIM, S., Korea University, Seoul, South Korea, seongryongkim@korea.ac.kr
Seismic anisotropy in the upper mantle, which can be developed by the alignment of anisotropic minerals, such as olivine, provides a means for indirectly
analyzing mantle dynamics, including asthenospheric mantle flow. Seismic
anisotropy beneath the southern Korean Peninsula (SKP) was measured
by shear wave splitting analyses and the upper mantle flow was simulated
through numerical mantle convection modeling. The SKP is located at theeastern margin of the Eurasian plate. Subduction boundaries between theEurasian, Pacific, and Philippine Sea plates are located to the east of the SKP. A
significant lateral variation in lithospheric thickness within the SKP has beenreported, ranging from ~80 km in the east to ~130 km in the southwest acrossa lateral distance of ~200 km, implying the potential for a small-scale complex mantle flow driven by a sharp lithospheric thickness gradient. The fast
direction of seismic anisotropy in the SKP can be separated into two groups:
N-S direction dominant in the east and NW-SE direction dominant in thesouthwest. The deflected pattern around the southwest SKP was observed andinterpreted to reflect asthenospheric mantle flow deflected around the thicker
lithosphere.
In the mantle convection modeling, a horizontal mantle flow was initially driven by imposing a horizontal temperature gradient in the model
domain. Similar to seismic anisotropy, the simulated mantle flow calculatedwith realistic lithospheric thickness variations around the SKP was also separated into two groups. Notably, significant deflection in asthenosphere mantle flow was simulated at the shallow depth (~100 km) around the thicker
lithosphere in the southwestern SKP, whose pattern was roughly consistent
with the observed seismic anisotropy. Our results showed that complex asthenospheric mantle flow in NE Asia can be developed by interaction between
background mantle flow with laterally and vertically small-scale variations inlithospheric thickness at the continental margin.

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poster 8
Advancing the Resolution of Mid-Mantle Structures:
Full-Waveform Box Tomography of the Yellowstone Mantle
Plume
KUMAR, U., University of California, Berkeley, California, USA, utpalkumar@
berkeley.edu; LYU, C., University of California, Berkeley, California, USA,
lyuchao@berkeley.edu; MUNCH, F., Institute of Geophysics, ETH Zurich,
Zurich, Switzerland, federico.munch@erdw.ethz.ch; ROMANOWICZ, B.,
University of California, Berkeley, California, USA, barbarar@berkeley.edu
The Yellowstone mantle plume is a narrow, low shear-velocity feature in thelower mantle, exhibiting a horizontal deflection at approximately 1000 km
depth, similar to other plumes and subducted slabs, suggesting a rheologicalchange at that level (Nelson and Grand, 2018). To improve resolution at midmantle depths, we utilize full waveforms of body and surface waves.
Employing ‘box tomography’, we integrate a global 3D solver,
SPECFEM3D_globe (Tromp et al., 2008), for wavefield calculation outside
the region of interest, and RegSEM (Cupillard et al., 2012) for internal computations using the Spectral Element Method (SEM). The background global
3D model, SEMUCB_WM1 (French and Romanowicz, 2014), which faintly
resolves a low-velocity plume beneath Yellowstone extending to the coremantle boundary (French and Romanowicz, 2015), is used for initial wavefield computations, which are recorded at the box boundaries. This includes
body waveforms from distant quakes for mid- to lower-mantle structure
illumination.
To conduct box tomography, we initially compute the required global
wavefields in the reference 3D model down to a 20 s period and record thesefields on the box boundaries. Inversion iterations within the box reduce thecutoff period from 40 s to 20 s, with depth range expansion. The crustal structure is constrained using surface wave dispersion data down to a 16 s period.
Our results, derived from multiple inversion iterations using a Gauss-Newton
optimization and a physics-based Hessian computed with normal mode perturbation theory (NACT, Li and Romanowicz, 1995), will be presented.
poster 9
Imaging the Deformation Belt of Western Hispaniola Using
Multi-Component Ambient Noise Cross-Correlations
LEE, H., University of California, Riverside, California, USA, hlee423@ucr.
edu; RABADE, S., University of Utah, Utah, USA, san.rabade@utah.edu;
LIN, F., University of Utah, Utah, USA, FanChi.Lin@utah.edu; DOUILLY, R.,
University of California, Riverside, California, USA, robyd@ucr.edu
Hispaniola Island is located at a complex boundary between the North
American and Caribbean plates, resulting in a series of fold-and-thrust belts
and active fault zones. Several seismic imaging studies have been conducted tounderstand the regional structure of Hispaniola. These studies, combined withgeological observations, provide an outline of the crustal structure in the area,
revealing thinner crust (~20km) in the northern and southern domains and a
thicker crust (~40km) in the central part of western Hispaniola. However, theresolution of these results is limited. Receiver function analysis is only sensitive to the structural discontinuities beneath stations, whereas local earthquake tomography is restricted by earthquake observations, in which event
detection in this region is challenging.
Therefore, in this study, we investigate the crustal structure across western Hispaniola (Haiti) using a different approach. We perform multi-component noise cross-correlation and measure Rayleigh wave phase velocity andellipticity (horizontal-to-vertical (H/V) amplitude ratio) within the period
range of 3-18 s. The data used in this study are mainly from 27 broadband
stations deployed from April 2013 to June 2014 along a north-south transect
across the island. The H/V and phase velocity results exhibit consistent patterns related to the geology and tectonics of this region. Sedimentary basins
exhibit higher H/V values, while mountain areas show lower H/V. In terms ofphase velocity, higher velocities are observed in stations located in northernand southern Haiti, likely reflecting the more mafic crust composition compared to the lower velocities observed in the central part. We also conduct a
joint inversion of H/V and phase velocity to construct a 2-D shear wave velocity model across western Hispaniola. This 2-D shear velocity model provides
more constraints on the shallower crust (< 5km). A better understandingon the shallow crustal structure is particularly important for seismic hazard
assessment in this area, which has recently experienced two major earthquakes in 2010 and 2021.

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poster 10
The Crust was Strengthened or Weakened After Mantle
Plume: Evidence from Tarim Basin
LI, W., Chinese Academy of Sciences, Beijing, China, liwentao@mail.iggcas.
ac.cn; WANG, X., Chinese Academy of Sciences, Beijing, China, wangxu@
mail.iggcas.ac.cn; LIANG, X., Chinese Academy of Sciences, Beijing, China,
liangxf@mail.iggcas.ac.cn; ZUO, S., Chinese Academy of Sciences, Beijing,
China, 312984437@qq.com; SHILIN, L., Southern University of Scienceand Technology, Shenzhen, China, lislmonkey@163.com; QU, C., Chinese
Academy of Sciences, Beijing, China, quchen760511@163.com; TIAN, X.,
Chinese Academy of Sciences, Beijing, China, txb@mail.iggcas.ac.cn; CHEN,
L., Chinese Academy of Sciences, Beijing, China, lchen@mail.iggcas.ac.cn
Widely distributed early-Permian basalts and rhyolites in Tarim Basin were
speculated as products of mantle plume, however the interaction between
the mantle plume and the shallow cratonic lithosphere remains ambiguous.
Here, we constrain the S-wave velocity structures to 15 km depth utilizing
multi-frequency receiver function data from two temporary broadband seismic arrays in the Tarim Basin. There is a large-scale S-wave velocity discontinuity at bottom of Permian strata showing significant rising for the westernbasin, but without apparent undulations for eastern basin. Besides, massivehigh velocity anomalies at the western basin, spatially correlated with thepreviously proposed mantle plume head, suggest Permian plutonic intrusions
in western basin. These intrusive heterogeneities may change the strength of
the shallow crust and cause focused deformation under subsequent tectonic
activities, leading to folding and faulting of strata in western basin during
the Cenozoic. Our findings indicate that the activities of mantle plume may
destroy the integrity of the craton by changing the composition distribution
in the lithosphere.
poster 11
Using Multiple Voronoi Partitions to Conduct Array-Based
Ambient Noise Surface Wave Imaging
LI, Z., Southern University of Science and Technology, Shenzhen, China,
lzb5868@mail.ustc.edu.cn; DONG, S., Southern University of Science andTechnology, Shenzhen, China, Dongsh@mail.ustc.edu.cn; SHI, C., Southern
University of Science and Technology, Shenzhen, China, Dongsh@mail.ustc.
edu.cn; CHEN, X., Southern University of Science and Technology, Shenzhen,
China, chenxf@sustech.edu.cn
With the advancement of array-based surface wave technology, a breakthrough has been achieved in obtaining high-mode surface wave dispersion
curves from ambient noise cross-correlation to detect subsurface structures.
Compared to using only fundamental surface wave dispersion curves, including high-mode surface wave dispersion curves in multi-modal surface wave
inversion can effectively enhance constraints on subsurface structures, especially low-velocity structures. However, the study area needs to be divided
into multiple subarrays when conducting three-dimensional velocity structure imaging due to the necessity of array data for each dispersion extraction.
The size and shape of these subarrays may impact the effectiveness of the final
dispersion extraction.
In this work, we propose a method based on randomly generating
Voronoi polygons for repeated subdivision subarrays to circumvent the needto select array size and shape. This method primarily involves iteratively generating random Voronoi polygons to create different partitions. These dispersion curves extracted from one partition are treated as samples of all points
within the corresponding Voronoi polygon. After sufficient iterations, statistical methods can be employed to obtain dispersion curves for various points inthe study area and estimate the associated errors. Furthermore, this method
can address the issue of varying array scales required to extract different
modes’ dispersion curves. We will illustrate the specific methodology using
the imaging of Lasso dense arrays as an example, hoping that this method will
effectively enhance the applicability of array surface wave techniques.
poster 12
Challenges and Triumphs Seismic Surveying in a Historic
Underground Metals MineMCBRIDE, J., Brigham Young University, Utah, USA, john_mcbride@byu.
edu; LAMBECK, L., DT Mining, Utah, USA, Lex@DTMiningllc.com; REY, K.
A., Brigham Young University, Utah, USA, kd7kmp@gmail.com; NELSON, S.
T., Brigham Young University, Utah, USA, steve_nelson@byu.edu; KEACH,
II, R., Utah Geological Survey, Utah, USA, billkeach@utah.gov
Seismic surveying within mine adits underground (e.g., >100 m) has many
benefits, including the absence of low-velocity weathered overburden as well
as no topography. Further, being literally immersed in the target zone means

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Seismological Research Lettersthat structure and stratigraphy mapped in the adit are more readily correlated to the results of the seismic surveys. On the other hand, undergroundsurveys present unique challenges, including logistics of deploying an energy
source, emplacement of geophones in solid rock, reverberation from the adit,
and safety. We present the results of seismic surveying in the Deer Trail Minein south-central Utah (USA) discovered in 1878. The mine is located along
the eastern side of the Tushar Range, which forms a transition between the
Colorado Plateau to the east and the Great Basin to the west. The surveys utilized a narrow (~3x3 m) mostly horizontal adit, 120-510 m below ground surface. The country rock consists of highly fractured and mineralized Permian toPennsylvanian quartzites, shales, and limestones. Exploration targets include
shear zones and potentially reactive clean limestone intervals. A short (~375m) test common midpoint (CMP) profile was surveyed with an accelerated
weight-dropper (45 kg) energy source, using a source and receiver spacing of 3
m recorded over 96 channels. The test confirmed the ability to map very shallow (<50 m) small-scale structures, such as faults that were previously mappedin the adit. The production CMP survey covered ~1680 m with an explosive
source (mostly 300 g in 1.5-m deep shot holes) recorded over 264 channels,
source and receiver spacing at 6 m. A static recording array was used for bothsurveys with 4.5-Hz vertical geophones. The CMP profile imaged sparse horizontal and dipping reflectors down to about 500 m, tentatively interpreted aslithologic variations in the limestone or as shear zones. Our study demonstrates
the potential for high-resolution seismic exploration in an unconventional andchallenging setting to guide exploitation of deeply buried mineral resources.
poster 13
Searching for Blind Faults Beneath Metropolitan Los
Angeles: Preliminary Results From the 2023 San Fernando
Valley ArrayPERSAUD, P., University of Arizona, Arizona, USA, ppersaud@arizona.edu;
JUAREZ-ZUNIGA, A., University of Arizona, Arizona, USA, ajzu@arizona.
edu; CLAYTON, R., California Institute of Technology, California, USA,
clay@gps.caltech.edu
The San Fernando Valley (SFV) in Southern California is one of the mostdensely populated regions of the greater Los Angeles area. This region isprone to large damaging earthquakes such as the 1994 (Mw6.7) Northridge
and the 1971 (Mw6.7) San Fernando events that both occurred on a blindthrust faults. Many studies have investigated the structure of the SFV using
seismic reflection data, borehole logs, gravity and magnetic data, and deep
seismic refraction profiles. Despite these efforts, the resolution of existing
Earth models for the region is relatively low. This limits the high-frequency
content that can be achieved in wavefield simulations for accurate earthquake
hazard modeling and our ability to interpret near-surface structures and identify concealed or blind faults.
To improve the structural characterization of the SFV basin, a groupof 29 volunteers installed 140 three-component SmartSolo nodal seismic stations across the basin on 21 October 2023. The deployment was comprisedof a 15-km long linear array of 49 nodes spaced ~300 m apart, across theNorthridge Hills fault and near the epicenter of the Northridge earthquake
and a grid of 91 nodes that covered the SFV with an interstation distance of~2500 m. Our arrays recorded continuously for ~30 days and captured 21
magnitude>5.5 earthquakes with epicentral distances of 30-90 degrees. We
will present preliminary results from ambient noise tomography and receiver
function imaging to investigate the seismic structure of the basin and changes
across faults. Our study aims to improve ground motion simulations for the
SFV and contribute to more accurate estimations of earthquake hazards.
poster 14
Receiver Function Inversion at Erebus Volcano, Antarctica,
With Multi-Station Weighting
REISINGER, R., University of Texas at El Paso, Texas, USA, rachelleareis@
gmail.com; CHAPUT, J., University of Texas at El Paso, Texas, USA,jachaput@utep.edu; ASTER, R. C., Colorado State University, Colorado, USA,
rick.aster@colostate.edu; GRAPENTHIN, R., University of Alaska Fairbanks,
Alaska, USA, rgrapenthin@alaska.edu
Erebus volcano, located on Ross Island, Antarctica, has an open convecting lava lake with Strombolian style eruptions. The volcano features a complex magmatic structure that is related to a hypothesized hot spot upwelling
despite a lack of conclusive local crustal studies. Previous active source tomography and coda interferometry studies have noted strong shallow scattering
structures associated with low velocities in the upper edifice, but the Moho
depth has only been regionally constrained to an estimated 18 - 20 km depth.
To better resolve this and corroborate other large-scale crustal structures,
we use twenty-seven seismic stations distributed on the Erebus edifice fromwww.srl-online.org•

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the Tomo-Erebus, MEVO, and GSN seismic networks with over two hundred earthquakes between 2007 - 2010 to compute P-wave receiver functions(PRFs). These are supplemented by icequake and ambient noise derived surface wave dispersion curves, resulting in a joint Bayesian Markov chain Monte
Carlo (MCMC) inversion for spatially weighted sub-arrays of the network. By
using multi-station inversions, we assume the deeper structures are similar
across stations but have greater variance closer to the surface to account for
edifice heterogeneity. After inverting, we note a strong shallow discontinuity
between 1 - 5 km, corroborated by ongoing scattering images, and a general
Moho depth between 18 - 22 km.
poster 15
Shallow Imaging of the Valles of Caldera, Northern New
Mexico: Preliminary Results From Ambient Noise
Tomography
RODRIGUEZ, E. E., Los Alamos National Laboratory, New Mexico, USA,
eer@lanl.gov; DONAHUE, C., Los Alamos National Laboratory, New Mexico,USA, cmd@lanl.gov; ROBERTS, P. M., Los Alamos National Laboratory,
New Mexico, USA, proberts@lanl.gov; MAIER, N., Los Alamos National
Laboratory, New Mexico, USA, nmaier@lanl.gov
The Valles Caldera in northern New Mexico is part of the Jemez Volcanic
Field, formed from two rhyolitic eruptions <1.5 Ma. The caldera resides atthe confluence of several major tectonic regimes; to the west, the caldera isbounded by the Colorado Plateau and Laramide structures and to the east,
overlies the Rio Grande Rift. We present a preliminary ambient noise tomography model of the Valles Caldera and its relationship to the Rio Grande Rift,using data from the Los Alamos Seismic Network (LASN). In this inversion,
we use 14 broadband stations from LASN which span ~40 km across theCaldera and Rio Grande Rift. Vertical (ZZ) component cross-correlations for
98 station-pairs were computed using one-hour overlapping time windows
spanning from 2018 to the 2024. Phase and group velocity analysis are estimated using traditional frequency-time analysis. The LASN dataset, spanningover five decades, offers an opportunity for comprehensive temporal and spatial analyses across the Valles Caldera. Preliminary results show low Rayleighwavespeeds beneath the caldera, extending beneath the east extension of theJemez Volcanic Field and Rio Grande Rift.
poster 16
Lithospheric Modification in Northeastern Alaska
Interpreted From Full-Wave Ambient Noise Tomography
SASSARD, V., Purdue University, Indiana, USA, vincent.sassard@outlook.
com; YANG, X., Purdue University, Indiana, USA, xtyang@purdue.edu;
RIDGWAY, K. D., Purdue University, Indiana, USA, ridge@purdue.edu;
FLESCH, L. M., Purdue University, Indiana, USA, lmflesch@purdue.edu
Subduction margins undergo long-term deformation over geologic time thatcan deform the overriding plate for hundreds of kilometers. Numerical modeling of subduction dynamics and deformation of overriding plates suggest
far-field (1000s km) inboard deformation as the result of shallow subduction.
Previous studies of the upper plate of northeastern Alaska focus primarily on
data from surface deformation using geodetic measurements. However, the3-D deeper structural modification of the overriding lithosphere is unclear.
The Yakutat microplate in Alaska is a shallowly dipping subducting slab characterized by high coupling with the overriding North American Plate. The
collision of the Yakutat microplate with the North American continent reactivated a system of right-lateral strike-slip faults across Alaska and Yukon,
including the Denali Fault in southern Alaska and the Tintina Fault in eastern
Alaska. Here, we use full-wave ambient noise tomography to produce a highresolution image of northeastern Alaska, covering the eastern Brooks Range,
the Porcupine Shear Zone, the Yukon Flats Basin, and the Tintina Fault. We
will present the shear-wave velocity structure of the lithosphere and discuss
the lithospheric modification and the surface geologic record in northeastern Alaska associated with the shallow subduction of the Pacific plate and theYakutat microplate along the southern Alaska convergent margin.
poster 17
High-Resolution Moho Depth Mapping Beneath the Italian
Peninsula and Carpatho-Pannonian Region Using P-Wave
Coda Autocorrelation
THAPA, H. R., North Carolina Central University, North Carolina, USA,hthapa@nccu.edu; VLAHOVIC, G., North Carolina Central University,
North Carolina, USA, gvlahovic@nccu.edu
Peninsular Italy, renowned for its intricate tectonic history involving subduction and continental collision, has been a focal point for significant seismic

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activity, particularly along NW-SE trending normal fault systems. Recent
destructive earthquakes in the Central Apennines emphasize the imperative
for a comprehensive understanding of the region’s crustal structure, earthquake mechanics, and high-resolution seismic monitoring. Meanwhile, theCarpatho-Pannonian region (CPR), has exhibited heightened seismicity incertain areas, necessitating focused attention due to its hazard implications.
This study utilizes P-wave coda autocorrelation to image crustal discontinuities, including the Moho, in both Peninsular Italy and the CPR, contributing
valuable insights to the understanding of their geodynamics.
Our results, derived from 251 broadband stations, present a Moho depth
range of 20-60 km beneath the Italian peninsula. The SE-NW profile acrossthe Po Plain delineates a shallower Moho towards the Tyrrhenian Sea anda deepening trend towards the northern Apennines. Central Italy exhibits ashallower Moho adjacent to both the Tyrrhenian and Adriatic seas, with asignificant thickening up to 60 km in the central region. The substantial thickening of the Moho in central Italy suggests localized crustal uplift and compression, possibly linked to tectonic forces associated with the convergence of
the aforementioned plates. Sicily’s Moho depth ranges from 30-40 km, witha relatively thicker Moho observed in central Sicily. We observe the thicker
Moho in a region where previous studies reported a higher strain rate. Thisfurther supports the notion that regions with increased geological activity
exhibit a thicker crust. This correlation underscores the importance of considering crustal thickness variations in seismic hazard assessments, as areas witha thicker crust may potentially experience more significant seismic activity.
This methodology will be extended to the Carpatho-Pannonian Region for acomprehensive analysis of crustal discontinuities and Moho depth.
poster 18
Shallow Seismic Structure of the Canary Islands Using
Local Earthquakes Recorded on an Amphibious Seismic
Network
VILLASENOR, A., Spanish National Research Council, Hospitalet de
Llobregat, Spain, antonio.villasenor@csic.es; DÍAZ-SUÁREZ, E. A., Instituto
Geográfico Nacional, Santa Cruz de Tenerife, Spain, eadiaz@mitma.es; DEL
FRESNO, C., Instituto Geográfico Nacional, Madrid, Spain, cdelfresno@
mitma.es; DOMÍNGUEZ-CERDEÑA, I., Instituto Geográfico Nacional, Santa
Cruz de Tenerife, Spain, ifdominguez@mitma.es; DANNOWSKI, A., Geomar,
Kiel, Germany, adannowski@geomar.de; GREVEMEYER, I., Geomar, Kiel,
Germany, igrevemeyer@geomar.de; LANGE, D., Geomar, Kiel, Germany,dlange@geomar.de; CABIECES Diaz, R., Real Instituto y Observatorio de la
Armada, San Fernando, Spain, rcabdia@roa.es; BARTOLOMÉ, R., Spanish
National Research Council, Barcelona, Spain, rafael@icm.csic.es
The study of the seismic structure beneath the Canary Islands using local
earthquakes has been in the past hampered by the sparse distribution ofrecording stations and low seismic activity. Recently, the number of permanent stations from monitoring networks has significantly increased, frombarely one seismometer per island in the early 2000s to more than 10 stations
in each of the most seismically active ones. Similarly, temporary deploymentsof broadband stations have also taken place in most of the islands, further
increasing the station density. Finally, ocean bottom seismometers have also
been deployed to monitor recent volcanic eruptions. On the other side, thenumber of recorded earthquakes has also greatly increased. This is due mainly
to the seismicity associated with the 2011-2012 El Hierro and 2021 La Palma
eruptions, but also because of the improvements in the detection capabilitiesof the monitoring network.
Here we present new P and S wave velocity regional models of the
Canary archipelago and higher resolution models for the islands of TenerifeGran Canaria, La Palma and El Hierro. The bulk of the arrival time data used
to obtain these models comes from the Instituto Geográfico Nacional (IGN)
permanent monitoring network. We have augmented this dataset by incorporating arrival time data from recent temporary deployments, obtained using
Deep Learning phase pickers. Because of the increased coverage of this newdataset, we are able to image features such as crustal thickness variations,magmatic intrusions, and regions of shallow (crustal) and deep (uppermost
mantle) magma storage.
Funding has been provided by Spanish Ministry of Science andInnovation projects PID2020-114682RB-C31 and PID2020-114682RB-C32.
poster 19
Slab Morphology and Mantle Wedge Processes in the
Tonga Subduction Zone Revealed by Body-wave Doubledifference Tomography
WANG, F., Michigan State University, Michigan, USA, wangfa16@msu.edu;
WEI, S., Michigan State University, Michigan, USA, swei@msu.edu; WIENS,

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D. A., Washington University in St. Louis, Missouri, USA, doug@wustl.edu;
ADAMS, A., Colgate University, New York, USA, aadams@colgate.edu
The Tonga subduction zone has the fastest convergence rate, and hosts about
two-thirds of the world’s deep-focus earthquakes (300-700 km). Previous
studies of deep-focus earthquakes suggest a relic slab separated from the
Tonga slab beneath the Fiji islands. Moreover, the mantle wedge dynamics
are complicated beneath the Lau Back-arc Basin, as the slab-controlled flux
melting interacts with the decompression melting beneath back-arc centers.
In this study, we use both regional and global body wave datasets to image the
Tonga subduction zone to about 800 km depth. The regional datasets include
arrivals from ocean bottom and land-based temporary seismograph deployments. In our results, the high-velocity slab extends beyond the bottom of the
mantle transition zone (MTZ), at least 200 km away from a separate highvelocity structure in the MTZ to its west. This high-resolution 3D velocity
model will provide valuable information on the subduction dynamics, mantle
wedge melting processes, and the origin of abundant deep earthquakes in the
Tonga subduction zone.
poster 20
Direct Inversion of Ambient Noise Multi-Modal Surface
Wave Dispersions for 3D Velocity Structures
ZHANG, G., Southern University of Science and Technology, Shenzhen,
China, zhanggh@sustech.edu.cn; YU, C., Southern University of Science andTechnology, Shenzhen, China, yucq@sustech.edu.cn; CHEN, X., Southern
University of Science and Technology, Shenzhen, China, chenxf@sustech.edu.
cn
Ambient noise-based surface wave tomography of subsurface structures ranging from shallow sediments to the upper mantle has been carried out in various regions, which is crucial for understanding regional tectonic evolution
and seismic hazard mitigation. Surface wave dispersions can be extracted byeither the conventional two-station method or the recently developed arraybased method. Yet, both encounter certain inherent limitations: the two-station
method cannot extract high-mode surface-wave dispersion, while array-based
methods have relatively low spatial resolution. In this study, we introduce a novel
direct inversion scheme of ambient noise multi-modal surface wave dispersions.
First, we calculate cross-correlations among all station pairs in a dense array following the standard ambient noise data processing workflow. Then, we apply thearray-based Frequency-Bessel transformation to calculate multi-modal dispersion spectra for cross-correlation functions from station pairs distributed along
the same line. Multi-modal dispersion data can be picked using an artificial neural network. Finally, we iteratively update the 3D velocity model by fitting themulti-modal dispersion data with theoretical predictions from the model. We
validate our new method using data from a dense array in Southern Yunnan,
China. We obtain a high-resolution velocity model of the study region, whichaligns well with known geological structures. Our new method can potentiallybe applied to other regions with dense arrays for subsurface structural imaging.
poster 21
S-Wave Seismic Data Interpretation for Channel Sand
Reservoir at Sanhu Area, West China
ZHANG, R., University of Louisiana at Lafayette, Louisiana, USA, rui.zhang@louisiana.edu
The Qigequan Formation at the Sanhu area of the Qaidam Basin in western China is a significant gas production formation. However, the conventional P-wave seismic survey conducted in this region reveals the presenceof extensive gas clouds that strongly attenuate P-waves, resulting in substantial uncertainty regarding the subsurface structure. To address this challenge,
we undertook a 3D9C (three-dimensional nine-component) seismic survey,
producing direct S-wave data unaffected by gas clouds, yielding remarkably
clearer subsurface images with a higher level of confidence. The processing of
the S-wave data largely utilized conventional P-wave processing techniques,with the exception of shear wave splitting, which produced distinct Fast (S1)and Slow (S2) S-wave datasets. The shear wave splitting includes estimationof the anisotropy orientation and rotation of the horizontal components into
corresponding normal and perpendicular directions Notably, the S2 data
exhibited superior quality compared to the S1 data, enabling us to apply various seismic attributes techniques to extract geological features. Among many
seismic attributes, we present seismic envelope and spectral decomposition
with RGB blending application results. To validate our findings, we cross-referenced the seismic attributes and inversion results with well-log and production data, revealing a pronounced spatial correlation between the gas reservoir
and channel structure. Consequently, we have identified channel structures as
the prime targets for potential gas reservoirs.

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Seismological Research Lettersposter 22
Multi-Scale, Finite-Frequency Body Wave Tomography With
Relative Kernels
BEN MANSOUR, W., Washington University in St. Louis, Missouri, USA,walid.benmansour@seismo.wustl.edu; WIENS, D., Washington University in
St. Louis, Missouri, USA, doug@wustl.edu; MAUPIN, V., University of Oslo,
Oslo, Norway, valerie.maupin@geo.uio.no
The subduction of the Chile Spreading Ridge beneath South America beginning 12-16 Myr ago opened a gap in the subducting slab beneath southern
Patagonia. Paleo-reconstructions show a northward migration of the Chile
Triple Junction to its present location around 46oS, but structure anomalies and geodynamic processes associated with the slab window have beenpoorly understood. The geographical extent of the slab window was previously inferred from the spatial distribution of magma composition and theanalysis of seismic waveforms from temporary seismic arrays (2004-2006)
near the Chile Triple Junction. The recent deployment of broadband seismic
instruments in Patagonia by the GUANACO experiment (2018-2021) and theChilean National Seismic Network present an opportunity to image the slab
window and associated structures in more detail. Here, we use teleseismic P
and S wave travel time residuals to carry out finite-frequency tomography.
We compute the travel time residuals in high frequency (0.3-1.5Hz) and low
frequency (0.03-0.125 Hz) bands and invert them to P and S-wave 3D models taking advantage of the different finite-frequency kernels obtained fromdifferent frequency bands. Crustal corrections are determined from a recent
regional scale shear velocity model of shallower structure derived from surface wave tomography and receiver functions [Mark et al, 2022]. Our new
seismic models show the transition between the Nazca slab associated with
fast upper mantle velocity anomalies and the slab window with slow velocity anomalies. The southern extent of the slab window and the presence ofa thicker continental lithosphere observed beneath the Austral-Magallanes
Basin are consistent with the recent surface wave tomography results. In thispresentation, we will discuss the 3-D geometry of the subducted slab and theeffect on the mantle flow pattern derived from shear wave splitting results[Ben-Mansour et al., 2022], the spatial distribution of volcanism (arc versus
backarc regions) and the support of the present-day surface topography witha dynamic contribution from the mantle across Patagonia.

End-to-End Advancements in Earthquake Early Warning
Systems
Oral Session • Friday 3 May • 2:00 pm PacificConveners: Ronni Grapenthin, University of Alaska
Fairbanks (rgrapenthin@alaska.edu); Angie I. Lux, Berkeley
Seismology Laboratory (angie.lux@berkeley.edu); Mouse
Reusch, University of Washington (topo@uw.edu); Brian
Terbush, Washington State Emergency Management
Division (Brian.Terbush@mil.wa.gov); Fabia Terra, Berkeley
Seismology Laboratory (terra@berkeley.edu)
Improvement in Magnitude Estimation Performance witha Combined PGD-PGV Scaling Law for the G-Fast
Earthquake Early Warning Module
DEGRANDE, J., University of Washington, Washington, USA, jdegran@uw.edu; CROWELL, B., University of Washington, Washington, USA,crowellb@uw.edu
Early estimation of earthquake magnitude is essential for earthquake and tsunami early warning systems and rapid response to these events. We propose
a new method to estimate earthquake magnitude using a scaling law relating peak ground velocities (PGVs) and peak ground displacements (PGDs)
derived from Global Navigation Satellite Systems (GNSS) data from a global
dataset (Crowell et.al, 2023). Peak ground velocities indicate the level of damaging shaking while peak ground displacements are diagnostic of the maximum moment release, so obtaining observations at the highest fidelity andunderstanding their relationship is crucial for rapid earthquake magnitude
estimation through the use of scaling laws. We collected high-rate (1Hz)
GNSS observations for earthquakes ranging in magnitude from Mw 4.9 to 9.1.
The three-component GNSS velocities were computed with the SNIVEL software package, which uses the time-differenced carrier-phase method, and thethree-component GNSS displacements were computed with the precise point
positioning code GipsyX from JPL. The peak ground velocities and displace-www.srl-online.org•

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ments were computed by taking the maximum of the square root of the sum ofeach component squared. With this dataset, we explore the evolution of PGV
and formally combine it with the PGD scaling law proposed by Crowell et.al,(2013), which forms the core of the G-FAST module in ShakeAlert. We test
the new law against the existing performance in G-FAST using the PGD-only
approach, with regards to both timing of alerts and accuracy of magnitude
estimates, and investigate the downstream impacts on ground motion andtsunami prediction in the context of operational early warning. Additionally,
we investigate case studies of large magnitude events with ground motions
over large areas to assess the performance of the PGV correction term. We finish by developing a framework for how this additional term would be implemented in the G-FAST earthquake early warning module operationally.
Finite-Fault Rupture Detector (FinDer) for Earthquake Early
Warning and Rapid Impact Estimates: Recent
Developments using Large International Earthquakes
BÖSE, M., ETH Zurich, Zurich, Switzerland, mboese@sed.ethz.ch;
ANDREWS, J., GNS Science, Lower Hutt, New Zealand, jen.andrews@
gns.cri.nz; SAUNDERS, J., California Institute of Technology, California,
USA, jsaunder@caltech.edu; MASSIN, F., ETH Zurich, Zurich, Switzerland,
frederick.massin@sed.ethz.ch; CEYLAN, S., ETH Zurich, Zurich, Switzerland,savas.ceylan@erdw.ethz.ch; FELIZARDO, C., California Institute ofTechnology, California, USA, claude@caltech.edu
Rapid fault rupture information is important for estimating seismic groundmotion and impact in large earthquakes, which is critical for earthquake
early warning (EEW) and rapid response systems. The Finite-Fault Rupture
Detector (FinDer) algorithm computes earthquake finite source models(either line-sources or complex rupture polygons) by comparing seismic
amplitude distributions with precomputed templates. The algorithm has been
adopted by the United States West Coast ShakeAlert EEW system and by otherreal-time systems, such as in Switzerland, Central America, New Zealand, andItaly. Recent improvements to FinDer address challenges of real-time operations, such as dealing with instrument failures during strong shaking, rupture
along complex fault geometries, as well as fault slip estimation using FinDerS.
We demonstrate FinDer’s new features by running waveform playbacks ofglobal earthquakes, including the 2023 M7.8 Kahramanmaraş sequence inTurkey, the 2016 M7.8 Kaikoura earthquake in New Zealand, and M7.8 scenario earthquakes along the San Andreas Fault in California. The resulting
earthquake source models show that FinDer(S) is able to provide timely andaccurate earthquake and ground motion information for EEW. FinDer(S) can
also improve rapid impact estimates after damaging earthquakes by providing
fault rupture information much faster than traditional finite-fault slip models.
Generalized Neural Networks for Universal Real-Time
Earthquake Early Warning
ZHANG, X., East China University of Technology, Nanchang, China, zxiong@mail.ustc.edu.cn; ZHANG, M., Dalhousie University, Halifax, Canada, miao.
zhang@dal.ca
Deep learning enhances earthquake monitoring capabilities by mining seismic waveforms directly. However, current neural networks, trained within
specific areas, face challenges in generalizing to diverse regions. Here, we
employ a data recombination method to create generalized earthquakes
occurring at any location with arbitrary station distributions for neural network training. The trained models can then be applied universally with different monitoring setups for earthquake detection and parameter evaluationfrom continuous seismic waveform streams. This allows real-time Earthquake
Early Warning (EEW) to be initiated at the very early stages of an occurring
earthquake. When applied to substantial earthquake sequences across Japanand California (US), our models reliably report earthquake locations andmagnitudes within 4 seconds of the initial P-wave arrival, with mean errors of
2.6-6.3 km and 0.05-0.17, respectively. The generalized neural networks facilitate universal applications of real-time EEW, eliminating complex empiricalconfigurations typically required by traditional methods.
Investigating Seismic Site Amplification for Improved
Earthquake Early Warning in Canada
PIETRONIRO, E., University of Ottawa, Ottawa, Canada, epiet081@uottawa.
ca; PERRY, H., Canadian Hazards Information Service, Natural Resources
Canada, Ottawa, Canada, claire.perry@NRCan-RNCan.gc.ca; CRANE, S.,
Canadian Hazards Information Service, Natural Resources Canada, Ottawa,

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Canada, stephen.crane@NRCan-RNCan.gc.ca; AUDET, P., University ofOttawa, Ottawa, Canada, pascal.audet@uottawa.ca
A well-implemented Earthquake Early Warning (EEW) system can warn
populations and critical infrastructure operators about imminent shaking due
to earthquakes. The Canadian EEW network covers regions of high seismic
hazard, dense population, and critical infrastructure. In some regions, site
amplification due to soft soils and sediments are expected to cause deviations
from predicted ground motion which impact EEW magnitude estimates.
The goal of this study is to provide empirical site amplification factors thatreflect deviations from expected ground motion with respect to a hard rock(reference) site at EEW stations. We calculate the horizontal-to-vertical spectral ratios (HVSRs) at each site using ambient seismic noise and estimate thepredominant site period using a systematic Gaussian curve-fitting algorithm.
From a total of 75 Canadian EEW stations investigated, 26% show site amplification compared to 6% of the Canadian National Seismograph Network(CNSN), which are predominantly located on bedrock. We have assessed
the relationship between the existing catalogue of CNSN station magnituderesiduals, predominant site period, and amplification at the site. While station magnitude residuals are used to estimate site-specific amplification at
CNSN stations, EEW stations do not contribute to the Canadian National
Earthquake Database (NEDB) magnitude estimates, therefore the HVSR
ambient noise method is used for site-specific amplification estimates at thesestations. Finally, we evaluate and compare EEW P-wave magnitude estimateswith S-wave magnitudes from the NEDB. One method of calculating magnitude in the EEW system uses peak displacement up to the first 4 secondsof the P-wave arrival, while the NEDB catalogue relies primarily on S-wavebased magnitude estimates. Our comparative analysis aims to characterize therelationship(s) between EEW and NEDB magnitudes in western and eastern
Canada, how site factors influence EEW magnitude estimates and how application of site amplification factors can improve EEW magnitude estimates.
Predicting Ground Motion Waveforms for Earthquake Early
Warning Using Convolutional Long Expressive Memory
Models
LYU, D., International Computer Science Institute, California, USA,dongweilyu@gmail.com; NAKATA, R., Lawrence Berkeley National
Laboratory, California, USA, rie.nakata.r@gmail.com; ERICHSON, B.
N., International Computer Science Institute, California, USA, erichson@
icsi.berkeley.edu; NAKATA, N., Lawrence Berkeley National Laboratory,
California, USA, nnakata@lbl.gov; REN, P., Lawrence Berkeley National
Laboratory, California, USA, pren@lbl.gov; PITARKA, A., Lawrence
Livermore National Laboratory, California, USA, pitarka1@llnl.gov
Earthquake early warning systems are developed to mitigate immediate threats
after the onset of large earthquakes and deployed worldwide including thewest coast of the United states. Once detecting P-waves at sensors close to theepicenter, the system estimates the earthquake location, magnitude and fault
geometry and predicts ground motion intensity parameters to issue a warning
prior to the strong motion arrivals. Errors in the parameter estimation, especially magnitudes, lead to false alert or missing warning opportunities and theuse of empirical ground motion models precludes accurate representation of
the complex source, path and and site-term variabilities. Alternatively, groundmotion intensities or waveforms can be forecasted by combining physicsbased simulation and data assimilation, which can remove arrival detection
and magnitude estimation, but their prediction accuracy remains insufficient.
We propose convolutional Long Expressive Memory Models, a novel
sequence-to-sequence learning approach in machine learning (ML) to accelerate the inference time, while simulating complex spatio-temporal wave
propagation phenomena. We test our approach by forecasting physics-based
simulation waveforms for earthquakes along the Hayward Fault in the San
Francisco Bay Area. We train the ML using >900 small point-source earthquakes (<0.5 Hz) recorded at sparsely distributed stations. Once trained, using
the early portion of waveforms, the ML can predict the rest of waveforms on
the fly at arbitrary sensor locations. The predicted and groundtruth waveforms
show remarkable agreement, and the spatially heterogeneous peak ground
velocities are well predicted. We then use the point-source trained model topredict large M finite-fault cases, a challenging domain shift problem for ML.
Our ML method can predict up to M6 ground motions, suggesting strong
potentials in generalization. To apply to real earthquakes, we envision to train
ML models using many real small M earthquakes and a smaller number oflarger M data, and achieve fast high-fidelity prediction based on observations.

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Engineering Earthquake Early Warning
GALASSO, C., University College London, London, United Kingdom,c.galasso@ucl.ac.uk
The most cutting-edge advances in earthquake early warning (EEW) havebeen primarily concentrated on real-time seismology. However, to maximize
the potential of EEW as a credible tool for seismic resilience enhancement,
there remains a strong need to develop next-generation end-to-end decisionsupport systems that use interpretable probabilistic impact-based estimatesand account for malfunctions (i.e., false alarms) towards more risk-informed
stakeholder decision-making on EEW installation/alert triggering. This presentation addresses this challenge, showcasing a series of recent significant
EEW contributions.
First, I present the results of a state-of-the-art feasibility study for EEW
conducted across Europe, representing the only attempt in the literature to
spatially combine traditional seismologically driven EEW decision criteria(i.e., lead time) with proxy risk-oriented measures for earthquake impact andalert accuracy. These results show that, under certain conditions, EEW could
be particularly effective for areas in Greece, Italy, and Turkey. The findings
offer a unique transnational perspective on EEW’s potential relevant to various stakeholders interested in leveraging the technology.
I then present an innovative approach for enhanced risk-informed decision-making on triggering EEW alerts. The proposed methodology integrates
earthquake-engineering-related seismic performance assessment procedures/
metrics (e.g., costs, downtime, and casualties) with multi-criteria decisionmaking tools within an end-to-end probabilistic framework that robustly
tracks uncertainties. Such a methodology enables explicit consideration of
end-user preferences (importance) towards the predicted consequences in
the context of alert issuance. The proposed approach is demonstrated using
various case-study infrastructure systems in Europe, for which the optimal
decision (i.e., “trigger” or “don’t trigger” an EEW alert) is investigated acrossa range of ground-motion intensities finding that the best action for a given
level of ground shaking can change depending on stakeholder preferences.
Toward Earthquake Early Warning in Nevada
KINKEL, D., University of Nevada, Reno, Nevada, USA, dkinkel@unr.edu;
TRUGMAN, D., University of Nevada, Reno, Nevada, USA, dtrugman@unr.
edu
Nevada is one of the most seismically active states, with numerous active fault
systems across the state and in bordering regions. Nevada has a notable history of large, M 6 and greater, earthquakes and increased risk due to the mostpopulated areas lying in some of the most hazardous sections of the state.
Earthquake early warning systems aim to lower the risk of earthquakes bysending alerts to potentially affected people before shaking arrives at theirlocation. ShakeAlert is the current EEW system in place in the U.S., but it only
operational in the West Coast states of California, Oregon, and Washington at
the moment. Our research is focused on testing the feasibility of Nevada’s seismic network for EEW and determining what changes to the network or EEWprocesses might be needed for ShakeAlert to expand to Nevada. The results
obtained for Nevada could also provide new insights into EEW that can beapplied to other parts of the US. Using hazard maps and current network configurations, we created upgrade scores to qualitatively show the current stateof the network and the locations where adding new stations would lead tothe most improvements. We explore this further using grids of potential new
stations and simulated earthquakes to test the effects of adding new stations
to the current network. One aspect of the ShakeAlert workflow is estimating the magnitude of an earthquake as it occurs using the peak displacement
measured at individual stations. This relation was created using a limited data
set that did not include Nevada earthquakes, so we are testing whether thisrelation holds true in Nevada or if a new regional relation needs to be created.
We are also looking at using site terms and studying trends across geographic
groupings to improve accuracy.
Evaluation of the Ocean Networks Canada Earthquake
Early Warning System: Magnitude Estimation and Site
Condition
BABAIE MAHANI, A., Ocean Networks Canada, Victoria, Canada,alirezab@uvic.ca
Ocean Networks Canada (ONC) began developing an Earthquake Early
Warning (EEW) system for southwestern British Columbia in 2015, which has
been operational as of April 2023. The system detects earthquakes based on
rapid detection of P waves and determine epicentral location and magnitude.
Alerts are then generated and sent to infrastructure subscribers. Here, we take

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and site condition at individual stations.
Overall, the ONC EEW system somewhat underestimates magnitudes
for larger events (>4) while overestimating smaller earthquakes compared to
Natural Resources Canada and USGS. We attribute these discrepancies to several factors, including the use of different stations, procedures, and methodologies to detect earthquakes among different agencies. Based on the average
difference between station and event magnitude, we observed that there areseveral stations that systematically generate larger or smaller magnitudes by asmuch as 1 magnitude unit (and higher). In general, with exception of a small
number of stations at close distances, no strong evidence of non-linearity
could be observed at the stations (onshore and offshore). Overall, offshoresites show site fundamental frequency (fpeak) and its peak amplitude (Apeak)in the range of ~1.7-6 Hz and ~0.4-1.2 (in base-10 log unit), respectively,
whereas onshore sites show ~1-6 Hz for fpeak and ~0.3-0.7 (in base-10 log unit)
for Apeak. There are slight trends in station terms versus fpeak and Apeak where
station terms decrease with increasing fpeak and increase with increasing Apeak.
The dependence of station terms on fpeak and Apeak provides an explanation
for the high and low magnitude values calculated at several stations. As there
is a correlation between fpeak and Apeak where lower amplification (Apeak) is
expected for higher fpeak values, systematic calculations of high or low magnitudes at stations can be related to site condition with stations located on softer
geological materials be more prone to higher magnitude estimates than thoseon hard rock conditions.
Impact Assessment of Eew Systems in Central America
ORIHUELA, B., ETH Zurich, Zurich, Switzerland, benazir.orihuela@sed.
ethz.ch; CLINTON, J., ETH Zurich, Zurich, Switzerland, jclinton@sed.ethz.
ch; PAPADOPOULOS, A., Moody’s RMS, Zurich, Switzerland, athanasios.
papadopoulos@sed.ethz.ch; DANCIU, L., ETH Zurich, Zurich, Switzerland,
laurentiu.danciu@sed.ethz.ch; BÖSE, M., ETH Zurich, Zurich, Switzerland,mboese@sed.ethz.ch; MASSIN, F., ETH Zurich, Zurich, Switzerland,
frederick.massin@sed.ethz.ch; STRAUCH, W., Instituto Nicaragüense deEstudios Territoriales, Managua, Nicaragua, wilfried.strauch@yahoo.com;
YANI QUIYUCH, R., Instituto Nacional de Sismología, Vulcanología,
Meteorología e Hidrología, Guatemala City, Guatemala, royani@insivumeh.
gob.gt; MIXCO, L., Ministerio de Medio Ambiente y Recursos Naturales, San
Salvador, El Salvador, lmixco@ambiente.gob.sv
Since 2016, the ATTAC (Alerta Temprana de Terremotos en América
Central) project has been developing national Earthquake Early Warning(EEW) systems across Central America, through collaboration between the
Swiss Seismological Service at ETH Zurich and national seismic agencies in
Nicaragua (INETER), Costa Rica (OVSICORI), Guatemala (INSIVUMEH)
and El Salvador (MARN). The four countries now provide public alerts
through mobile applications. As the national EEW systems have moved into
an operational status, the selection of recommended protective actions thatcan reduce casualties becomes crucial. The essential premise of EEW is that
seconds matter. Therefore, a well-educated public that responds promptly
and adequately is indispensable to a successful outcome. However, no official‘written’ guidance on recommended protective actions exists in any country
in Central America.
We used a recently proposed framework (Papadopoulos et al., 2023) tocombine the regional seismic risk model (Global Earthquake Model, Silva
et al., 2018), EEW warning times depending on the spatial distribution of
the seismic network, and the behavior of individuals during earthquakes(Orihuela et al., 2023) to quantify the impact of EEW systems on reducing
earthquake-induced casualties. On average, when considering major earthquakes, the implementation of EEW systems has demonstrated the potential
to reduce casualties (i.e, injuries and fatalities) within the range of 14-18%.
This percentage can be substantially improved through the implementationof key factors: (1) protective actions tailored to the building characteristics;
70% of the region’s buildings are single-story structures, immediate evacuation should be prioritized while occupants in multi-story structures might bebetter advised to drop cover and hold on (DCHO); (2) improving the public
response, educational programs and earthquake drills can influence individuals to react promptly; (3) increasing the warning time by densification andexpansion of the seismic network and improving EEW methods.
Performance of Operational Earthquake Early Warning
Across Central America.
MASSIN, F., ETH Zurich, Zurich, Switzerland, fmassin@ethz.ch; CLINTON,
J., ETH Zurich, Zurich, Switzerland, jclinton@sed.ethz.ch; BOSE, M., ETH
Zurich, Zurich, Switzerland, maren.boese@sed.ethz.ch; BURGOA, B.,
Observatorio Vulcanológico y Sismológico de Costa Rica, Heredia, Costa
Rica, billyburgoa@gmail.com; MARROQUIN, G., Ministerio de Mediowww.srl-online.org•

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Ambiente y Recursos Naturales, San Salvador, El Salvador, gmarroquin@
marn.gob.sv; MUÑOZ, C., Observatorio Vulcanológico y Sismológico de
Costa Rica, Heredia, Costa Rica, camilo.sismo@gmail.com; ORIHUELAGONZALES, B., ETH Zurich, Zurich, Switzerland, benazir.orihuela@sed.
ethz.ch; PROTTI QUESADA, M., Observatorio Vulcanológico y Sismológico
de Costa Rica, Heredia, Costa Rica, marino.protti.quesada@una.cr;
STRAUCH, W., Instituto Nicaragüense de Estudios Territoriales, Managua,
Nicaragua, wilfried.strauch@ineter.gob.ni; YANI QUIYUCH, R., Instituto
Nacional de Sismología, Vulcanología, Meteorología e Hidrología, Guatemala
City, Guatemala, royani@insivumeh.gob.gt
Over the past year, operational public Earthquake Early Warning (EEW) alerts
have become available across Central America via cell phone applications.
Given the elevated earthquake risks, vulnerable building stock, and rising
population density, the adoption of EEW systems in the region has substantial
potential to safeguard lives. The “Alerta Temprana de Terremotos en América
Central” (ATTAC) project, involving seismological agencies from Guatemala,
El Salvador, Nicaragua, and Costa Rica, along with the Swiss Seismological
Service (SED) at ETH Zurich, has concluded after 8 years with the releaseof public operational national EEW systems. Each of the four participating
countries now offers public alerts through a mobile application available on
both iOS and Android devices. As of January 2024, the Costa Rican Android
application (the first that was released) has tens of thousands of users, providing notifications with less than an additional 4-second delay, 1.5 seconds
in median. In Managua, Nicaragua, the Japanese-developed EWBS system isalso used for fix-site alerting via digital television (also implemented but not
publicly deployed in El Salvador and Costa Rica). Each of the independent
national EEW systems utilises high-quality seismic networks and the ETHZ
SeisComP EEW (ESE) system with the Virtual Seismologist and FinDer EEW
algorithms. First alerts for on-shore seismicity are typically available within
8-15 seconds after origin time, while offshore or deep events are identified
within 20-25 seconds. In this submission, we summarize the alert configuration of the systems and review the performance so far, with a focus on key
events, including the October 2023 M5.3 earthquake in Central Costa Rica,
one of the first key tests of the system. We also reflect on fluctuating usage
numbers and early feedback on the system so far.
Exploring Five Years of Social Science and Education
Research for Shakealert, the Earthquake Early Warning
System for the West Coast of the United States
MCBRIDE, S. K., U.S. Geological Survey, California, USA, skmcbride@usgs.
gov; DE GROOT, R. M., U.S. Geological Survey, California, USA, rdegroot@
usgs.gov; SUMY, D. F., National Science Foundation, Virginia, USA, dsumy@
nsf.gov
As of May 2021, rollout of public alerting of the ShakeAlert Earthquake
Early Warning (EEW) System, has been completed in Washington, Oregon,
and California. Critical questions remain about what people understand andexpect from ShakeAlert, including if they know what to do when they receive
an alert. To evaluate whether the ShakeAlert System has been successful inanswering these key research questions, the U.S. Geological Survey (USGS)
developed the Social Science Working Group in 2019. The USGS collaborates
with partners from universities, emergency management and other state agencies, the National Science Foundation, and USGS licensed alert distribution
partners to implement a social science initiative focusing on three goals. First,
to understand earthquake risk perception, protective action knowledge, andbasic earthquake preparedness across Washington, Oregon, and California
populations. Second, how to apply social science research to inform the
ShakeAlert communication, education, outreach, and technical engagement(CEO&TE) programs. Third, to develop a monitoring and evaluation plan for
CEO&TE programs for ShakeAlert. The ShakeAlert social science initiative
focuses on research that is currently underway and plans future directions
to reach our goals. This presentation outlines the various publications thathave been published or are in draft, future projects, and how social scienceand educational research has been integrated into the ShakeAlert System toimprove outcomes for users of the system.
The Development of a Real-Time Urban Earthquake Early
Warning System for Asset-Level Protection for Increased
Community RestorationMARTÍ, A. T. J., University of British Columbia, Vancouver, Canada,
andytjm@student.ubc.ca; DAISS, I., Rogers Communications, Vancouver,
Canada, Ivelina.Daiss@rci.rogers.com; MARTÍ, J. R., University of British
Columbia, Vancouver, Canada, jrms@ece.ubc.ca; VENTURA, C. E., Universityof British Columbia, Vancouver, Canada, ventura@civil.ubc.ca; ANDJELIC,
D., University of British Columbia, Vancouver, Canada, dandjeli@icics.ubc.

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ca; CHHABRA, A., Rogers Communications, Brampton, Canada, Amitabh.
Chhabra@rci.rogers.com
A Real-Time Urban Earthquake Early Warning System is being developed at
the University of British Columbia. This system is based on a dense grid of
low-cost seismic stations mounted on infrastructure (i.e., buildings, bridges,
power substations) every 50 to 100 m apart. The edges in the grid are represented with transmission line models that decouple the adjacent nodes withthe wave’s propagation time, making it very computationally efficient. Eachstation consists of a MEMS tri-axial accelerometer, a Raspberry Pi processing
board and a 5G communication module. As soon as the wave is detected, thegrid model will calculate, in a few milliseconds, the predicted values at all othernodes before the wave arrives. As the wave progresses, the predicted values are
updated. With this solution, we can achieve a high spatial and high temporal
resolution. The fine spatial resolution captures the variability in geologicalconditions within a city. Combining this high resolution with existing fragility curves, we can predict the level of damage at the individual infrastructurelevel. In addition, discriminating automatic protective actions can be taken,
such as disconnecting electrical circuit breakers to prevent fires, a major causeof damage and death. Detailed real-time knowledge of the damage level at
each infrastructure is integral for post-earthquake recovery. During a disaster,when multiple support systems fail simultaneously, decisions about where to
deploy resources must be made based on the consequences to the community.
These decisions require tools that consider each infrastructure’s current stateof damage and the strength of the interdependencies each has with the others.
With the use of an interdependencies optimization tool, prioritized response
actions can be taken to restore habitability to the community as quickly as
possible for increased community resilience and well-being.
What It Takes to Implement Earthquake Early Warning in
the Real WorldSTEELE, W. P., University of Washington, Washington, USA, wsteele@uw.edu; LOTTO, G., University of Washington, Washington, USA, glotto@
uw.eduThe ShakeAlert Earthquake Early Warning System, fully operational in
California, Oregon, and Washington, is a public-private partnership between
the US Geological Survey, several cooperating universities, and several
licensed technical partners. The public side of the ShakeAlert System (i.e.,
USGS and partnering universities) is responsible for collecting and analyzing
earthquake data. The private side of the ShakeAlert System (i.e., licensed technical partners) is responsible for delivering alerts and initiating automatedactions to protect people and infrastructure. Without a robust marketplaceof technical partnerships, earthquake early warning information would notreach the public. Therefore, when considering expanding EEW to the public
in a new location, such as Alaska, it is crucial to consider the resources needed
to build, grow, and sustain technical partnerships. This presentation will cover
the process of developing and nurturing the technical partnerships needed forearthquake early warning implementation, including a discussion of common
challenges and roadblocks faced during the ShakeAlert rollout on the US West
Coast from 2019-2024.
From Shakealert to Post-Earthquake Assessment—
Improving Situation Awareness of Building Managers andOccupants
PARROTT, B., Kinemetrics, Inc., California, USA, jbp@kmi.com; FRANKE,
M., Kinemetrics, Inc., California, USA, mf@kmi.com; SKOLNIK, D.,
Kinemetrics, Inc., California, USA, das@kmi.com
Early warning systems must be optimized through a combination of science and technology that provide a foundation to deliver alerts in the formof actionable information in a manner relevant to the recipient of the alert.
The effect of the potential disconnect between the understanding of these systems’ technical innovations and the layperson’s human behavioral need canbe seen in the perceived issues in the early deployments of some of the mostrobust early warning systems. If the system serves the scientific community
but does not meet the needs of the information users, the value of the system
can be called into question. Earthquake early warning systems (EEWS) serve
multiple participants and must address the needs of each in a manner consistent with their expectations—detailed technical information for scientists
and engineers, actionable information for emergency responders, and safety
instructions for the general public.
Maximizing the effect of EEWS requires that they be integrated into
the everyday systems and processes of those who rely on them. Typically, thewarning comprises a simple, understandable display of instructions to Drop,
Cover, and Hold On, including estimated timing and intensity associated with

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their location. Following the shaking, however, emergency management personnel and responders require another level of information to help guide theiractions and decisions. For this reason, our platform delivers earthquake early
warning messages as an element of a larger workflow incorporating information on the impact of ground motion on their structures, details of potential
non-structural impact within their structures, and a mobile app that enables
occupants to submit injury and hazard reports. Emergency response personnel can use the platform to perform safety checks, evaluate the overall impact
on their structures and occupants, and manage their emergency response.
This approach informs and integrates the procedures of the response team aswell as the occupants within the structures, resulting in a more comprehensive
and effective system.
The Ojai California Earthquake of August 20, 2023:
Earthquake Early Warning Performance and Alert Recipient
Response in the m5.1 EventGOLTZ, J. D., University of Colorado Boulder, California, USA, jamesgoltz@
gmail.com; WALD, D. J., U.S. Geological Survey, Colorado, USA, wald@usgs.
gov; MCBRIDE, S. K., U.S. Geological Survey, California, USA, skmcbride@usgs.gov; REDDY, E., Colorado School of Mines, Colorado, USA, reddy@
mines.edu; QUITORIANO, V., U.S. Geological Survey (Contractor),
Colorado, USA, vinceq@contractor.usgs.gov; SAUNDERS, J., California
Institute of Technology, California, USA, jsaunder@caltech.edu
A magnitude 5.1 earthquake in California rarely generates more than momentary notice—a headline in local newspapers and a mention with footage on
the evening news—then fades into obscurity for most people. But this earthquake which occurred near the city of Ojai is significant for seismologists,social scientists, emergency managers, policy makers and others who are
engaged in implementing and improving earthquake early warning (EEW)
technology and in assessing its value in public warnings. In this earthquake,
ShakeAlert, the EEW system for the West Coast of the United States operated
by the US Geological Survey (USGS), was publicly activated and, for the firsttime, a substantial number of those who received alerts provided feedback
on various aspects of the alerts they received. To capture data related to public attitudes and assessments regarding this and future alerts, a supplemental
questionnaire was developed and associated with the ‘Did You Feel It?’ (DYFI)
earthquake reporting system, also operated by the USGS. The DYFI system
received over 14,000 felt reports; 2,490 of these by people who received or
expected to receive an alert prior to the onset of earthquake motion at theirlocations. This paper analyzes the aggregate results of these EEW user reports,
touching on respondent’s situation upon receiving the alert, characteristicsof the alert received and, perhaps most important, how the alert recipient
responded if received prior to feeling earthquake motion. The new DYFI EEW
supplemental questionnaire also inquired about respondent views of alert usefulness and preferences in future alerts. Our report provides a first glimpse
of a range of behaviors, attitudes, and assessments by users of the recently
implemented EEW system for the US West Coast.
High-Rate Real-Time Gnss Installation and Data Acquisitionat the Alaska Earthquake Center
PARIS, G., University of Alaska Fairbanks, Alaska, USA, gmparis@alaska.edu; HOLTKAMP, S., University of Alaska Fairbanks, Alaska, USA,sgholtkamp@alaska.edu; KHAN, S., University of Alaska Fairbanks, Alaska,
USA, sfkhan@alaska.edu; UNDERWOOD, L., University of Alaska Fairbanks,
Alaska, USA, lbunderwood@alaska.edu; FARRELL, A., University of Alaska
Fairbanks, Alaska, USA, akfarrell@alaska.edu; GRAPENTHIN, R., Universityof Alaska Fairbanks, Alaska, USA, rgrapenthin@alaska.edu; MURPHY, N.,
University of Alaska Fairbanks, Alaska, USA, nwmurphy@alaska.edu; WEST,
M., University of Alaska Fairbanks, Alaska, USA, mewest@alaska.edu
Global Navigation Satellite System(GNSS) is an increasingly integral part ofassessing rare, but large, earthquakes. Geodetic capabilities provide an extra
layer of scientific investigation which is not only prerequisite to earthquake
early warning (EEW) in Alaska, but also provide a better understanding of theongoing seismic activity in the region. To date, we have upgraded 7 seismic
sites across Alaska to include GNSS receivers and have developed a framework for acquiring and archiving this data at the Alaska Earthquake Center(AEC). As part of this integration, we’ve had to navigate the entire process ofadapting an additional technology, including site selection, installation, reliable communications back to our datacenter, acquiring the data, and building a preliminary quality control procedure. GNSS receivers are installed atexisting seismic monitoring stations that are capable of supporting remote,real-time data acquisition using the same power and communication systems.
Recent GNSS installations consist of a VeraChoke antenna with a Septentrio
PolarRx5 receiver. The VeraChoke antennas are mounted on polar masts,

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Seismological Research Letterswhich are anchored to a solid rock surface. We are using two applications provided by BKG (Bundesamt für Kartographie und Geodäsie) to acquire GNSS
data: an NTRIP caster and client. Each receiver is configured to broadcast
real-time data to an NTRIP caster, which serves as an accessible connection
point for a user to access the GNSS data streams. The NTRIP client accesses
the broadcasts by connecting to the caster, then saving the data streams to
RINEX files. AEC collects 1 Hz observational data and stores it into 1 hour
files. These recent installations and the workflows we built have allowed us
to develop skills in field installation, data acquisition, data management, andquality control, hopefully paving the way for more effective and expansive
GNSS applications in the coming years.
The Potential Contribution of Real-Time Distributed Slip
Models to Subduction Zone Earthquake Early Warning in
the Context of Ground Motion Thresholds and Alerting
Strategy
MURRAY, J. R., U.S. Geological Survey, California, USA, jrmurray@usgs.gov
Earthquake early warning systems like ShakeAlert estimate source parameters(e.g., Mw and location) in order to calculate anticipated shaking. Users receive
alerts where forecast ground motion (GMpred) exceeds a pre-set alert threshold, tA. Alert timeliness can improve if tA < tT, the target shaking level forwhich we hope to alert users (Minson et al., Sci. Adv. 2018). ShakeAlert uses
two seismic algorithms that estimate parameters of a point or line source representing the earthquake. Large (e.g., M8.0+) subduction interface earthquakes’
offshore location, magnitude, and rupture extent are a challenge to accurate
real-time source characterization. This work evaluates if the BEFORES algorithm (Minson et al., JGR, 2014), which infers temporally-evolving, threedimensional distributed slip models (DSMs) from real-time global navigation
satellite system data, can improve performance. Previously (Murray, AGU Fall
Mtg. 2023, NH13C-0690), I compared alert outcomes using BEFORES’ DSMs
to those from published post-event DSMs and point source models (“bestcase” parameter estimates) as well as models from ShakeAlert’s existing algorithms. Outcomes were quantified by correct, missed, and over alerts relative
to ShakeMaps (GMobs) using tA = MMI 4 and tT = MMI 6. For two events it
was also possible to evaluate alert timeliness. Most source models had similarcorrect alert performance to ShakeMap for the chosen thresholds, even when
GMobs and GMpred differed by >1 MMI unit. These thresholds led to overalerts (GMpred > tA, GMobs < tT) for large areas, even for the ShakeMaps.
BEFORES caused larger over alert areas than retrospective DSMs but did notincrease the total over alert area compared to ShakeMap for the earthquakes
and thresholds tested. BEFORES showed potential to improve timeliness andreduce missed alerts. Here I present follow-on work suggesting BEFORES
may improve alerting for higher tA (e.g., an MMI 5 “take action” threshold),and I consider BEFORES’ contribution in the context of unilateral subduction
interface ruptures and preemptive alerting of a large region if the Mw estimate
exceeds a certain value.
Toward Earthquake Early Warning in Alaska
FOZKOS, A., University of Alaska Fairbanks, Alaska, USA, afozkos@alaska.
edu; WEST, M., University of Alaska Fairbanks, Alaska, USA, mewest@alaska.
edu; RUPPERT, N., University of Alaska Fairbanks, Alaska, USA, naruppert@
alaska.edu; GRAPENTHIN, R., University of Alaska Fairbanks, Alaska, USA,rgrapenthin@alaska.edu; PARCHETA, C., University of Alaska Fairbanks,
Alaska, USA, ceparcheta@alaska.edu; HOLTKAMP, S., University of Alaska
Fairbanks, Alaska, USA, sgholtkamp@alaska.edu; MURPHY, N., Universityof Alaska Fairbanks, Alaska, USA, nwmurphy@alaska.edu; NADIN, E.,
University of Alaska Fairbanks, Alaska, USA, enadin@alaska.edu
The complexity of Alaska presents several challenges for earthquake early
warning systems. These include the presence of offshore earthquakes, transform boundaries and crustal faults extending hundreds of kilometers, deep
earthquakes, and a complicated coastline. This variety, combined with population centers spread far apart, make it challenging to anticipate early warning
system performance and to design a network accordingly. As Alaska begins
to plan for early warning, we present here a set of scenarios and proposed
network plans. Our objective is to begin envisioning how, and how well, early
warning might function in Alaska. We present warning time estimates forgroups of deterministic earthquake scenarios along major faults in Alaska.
These scenarios are designed to be meaningful test cases for Alaska EEW
while also exploring how changes in source characteristics—such as magnitude, depth, location, and fault system—impact the timeliness of warnings.
We use simple travel-time estimates, source time models, and the current
seismic network to model hypothetical detection and alert times. We thencompare warning times to peak ground motions obtained with ShakeMap 4
to determine the warning effectiveness. Our conservative results suggest the

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potential for timely warning for shallow earthquakes for ground motions up
to intensity V. More ideal scenarios, including deep earthquakes, could receive
advance warning up to intensity VII. Informed by these results, we present
preliminary concepts for how to build a network capability of delivering thislevel of warning or better.
Application of the Support Vector Machine Classifier inEarthquake Magnitude Estimation
ZAICENCO, A. G., Weir-Jones Engineering Consultants, Vancouver, Canada,
anton.zaicenco@weir-jones.com; WEIR-JONES, I., Weir-Jones Engineering
Consultants, Vancouver, Canada, iainw@weir-jones.com
The ability of an Earthquake Early Warning (EEW) algorithm to resolve reliably the event magnitude from a few stations is critical for an efficient EEWapplication. When applied to a single-station seismic record, traditional
approaches based on tc and Pd methods exhibit somewhat larger errors thanthe machine-learning methods. We use the Support Vector Machine (SVM)
method with a Gaussian kernel to predict magnitude from a single station triaxial record. Unlike other approaches, raw records are used without downsampling or converting them to a vector of parameters. Preliminary investigations
demonstrated that SVM approach is superior to the Deep Neural Networks as
it provides better accuracy both in the training and validation data sets. The
subset of the KiK-net database generated by the NIED strong-motion seismograph network incorporates ~4,000 triaxial records of P waves over the magnitude range 5.5-7.6. This was used to train the SVM model and investigate theaccuracy of the results by means of the normalized confusion matrix. Results
demonstrated that the confusion matrix is almost diagonal, which suggeststhat the spectral norm of this matrix is a good measure of the accuracy ofthe solution. Several techniques were evaluated for the pre-processing of the P
wave records to investigate their influence on the solution with the intention ofproviding a rigorous physics-based interpretation of the results.
The outcomes of this study will be implemented in the network based
EEW system operated by the Greater Vancouver Water District. The system
was designed, built, and commissioned in 2021/2022 as part of the pilot project “EEW and Strategic Response System”. The project deliverables included arobust EEW application, and a Structural Health Monitoring service for someof the critical infrastructures operated by Metro Vancouver. Currently, the system is being utilized by operations staff within the water system infrastructure.
Enhancing Offshore Earthquake Early Warning with a
Submarine DAS Array in Monterey Bay, California
GOU, Y., University of California, Berkeley, California, USA, yuancong_
gou@berkeley.edu; ALLEN, R. M., University of California, Berkeley,
California, USA, rallen@berkeley.edu; ZHU, W., University of California,
Berkeley, California, USA, zhuwq@berkeley.edu; CHEN, L., University ofCalifornia, Berkeley, California, USA, liwei_chen@berkeley.edu; TAIRA,
T., University of California, Berkeley, California, USA, taira@berkeley.edu;
HENSON, I., University of California, Berkeley, California, USA, ihenson@
berkeley.edu; MARTY, J., University of California, Berkeley, California,
USA, jmarty@berkeley.edu; BREKKE, K., Monterey Bay Aquarium ResearchInstitute, California, USA, knute@mbari.org; NEUHAUSER, D., Universityof California, Berkeley, California, USA, dougneuhauser@berkeley.edu;
PARDINI, B., University of California, Berkeley, California, USA, bpardini@berkeley.edu; THOMPSON, S., University of California, Berkeley, California,
USA, stephen.thompson@berkeley.edu; YARTSEV, V., OptaSense, California,
USA, Victor.Yartsev@optasense.com; ZHANG, J., University of California,
Berkeley, California, USA, junlizhang@berkeley.edu; ZUZLEWSKI, S.,
University of California, Berkeley, California, USA, stephane@berkeley.edu;
ROMANOWICZ, B., University of California, Berkeley, California, USA,barbarar@berkeley.edu
Detecting offshore earthquakes in real-time is challenging for traditional landbased seismic networks due to insufficient station coverage. Application of
DAS to submarine cables has the potential to extend the reach of seismic networks and thereby improve real-time earthquake detection and Earthquake
Early Warning (EEW). We present results testing modified point-source EEW
algorithms (EPIC) with data from SeaFOAM DAS deployment (52 km-longsubmarine cable) in Monterey Bay, CA. The region is seismically active with
the nearby San Andreas Fault system, and the offshore San Gregorio Fault
system (SGFs) which the cable crosses.
Around 1.5 year’s data has been collected by the permanent SeaFOAM
project, including more than 10 offshore events on the SGFs. We developed
a workflow that can be migrated to other DAS cables to detect earthquakes
in real-time. We took a transfer learning approach with recorded local earthquakes to get a locally optimized PhaseNet-DAS machine learning model for
P and S arrivals picking. We used a grid search method with available picks

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from the whole DAS array and a local 1D velocity model to locate the earthquakes. A calibrated empirical strain rate-to-magnitude equation is used toperform a real-time estimation of the magnitude. We extended our analysis
to more recorded earthquakes and demonstrated the independent earthquake
detection ability of an offshore DAS array. In the future, this DAS-specific
EEW algorithm will be integrated into the existing EPIC algorithm for testing. This approach has the potential to extend earthquake detection for EEW
offshore, thereby increasing warning times significantly.

End-to-End Advancements in Earthquake Early Warning
Systems [Poster Session]
Poster Session • Friday 3 May
Conveners: Ronni Grapenthin, University of Alaska
Fairbanks (rgrapenthin@alaska.edu); Angie I. Lux, Berkeley
Seismology Laboratory (angie.lux@berkeley.edu); Mouse
Reusch, University of Washington (topo@uw.edu); Brian
Terbush, Washington State Emergency Management
Division (Brian.Terbush@mil.wa.gov); Fabia Terra, Berkeley
Seismology Laboratory (terra@berkeley.edu)
poster 17
Improving Seismic Networks for the Earthquake Early
Warning Mission
BIASI, G., U.S. Geological Survey, California, USA, gbiasi@usgs.gov;
STUBAILO, I., California Institute of Technology, California, USA, stubailo@
caltech.edu; ALVAREZ, M. G., U.S. Geological Survey, California, USA,malvarez@usgs.gov
A seismic network supporting the Earthquake Early Warning (EEW) mission
must prioritize speed of detection for potential earthquakes of consequence.
We present methods for estimating annualized station expected contributions
to the EEW mission for improving network effectiveness in the presence oflimited resources for station coverage and maintenance. The expected rate ofa station contributing to earthquake detection depends strongly on location.
Stations near high slip-rate faults are more likely to participate in EEW earthquake detection than are stations near low slip-rate faults or in locations awayfrom active faults altogether. The annualized rate of participation in detection
at any point can be obtained from data associated with the USGS National
Seismic Hazard Maps.
A station’s contribution can be measured in terms of the improvement
in detection time that it provides, the area it covers, the areas around it at various shaking intensity levels, and the number of people who have more time toprepare for shaking at various intensity levels because the station is on duty.
As others have seen, time to earthquake detection depends on nearby station
density. For a network denser in urban areas and sparse in outlying areas, likethe network for the USGS ShakeAlert system, a hyperbolic relationship is seen
between detection time improvement and numbers of people helped by the
improvement. For example, urban Los Angeles area stations improve detection by tenths or hundredths of a second, but millions are (marginally) helped,
while rural stations can help detection by a second or more, but few live nearintense shaking. When damage models are linked to shaking intensities, station contributions can be measured in terms related to protecting people andproperty, a core USGS National Earthquake Hazard Reduction Program priority. Understanding station contributions can inform maintenance priorities
and station sitings or relocations to improve seismic network effectiveness andmaintainability.
poster 18
Picket Fence: An Earthquake Alert System for the Ligo
Detectors
BONILLA, E. L., Stanford University, California, USA, edgard@stanford.edu;
AGUILAR, I., Stanford University, California, USA, isaac007@stanford.edu;
LANTZ, B., Stanford University, California, USA, blatz@stanford.edu
The Advanced LIGO detectors are leading the field of gravitational wave
astronomy. The detectors measure the change in length of 4-km long resonantinterferometers to attometer precision to achieve their goal. Not surprisingly,
the resonance condition for operation is delicate and can be lost if elaborate
isolation of external disturbances is not complete. The Rayleigh waves produced by earthquakes challenge this isolation. In the past five years, LIGO has

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implemented a control configuration called earthquake (EQ) mode to allow
LIGO instruments to maintain resonant operation or “lock” during earthquake events whose strength would have previously impaired their functioning, which helped restore some of their duty cycle. EQ mode works best when
it can be used preemptively, before the arrival of surface waves to the LIGO
observatories.
The ‘Picket Fence’ is a newly implemented early alert system aimed toincrease the warning time for surface waves approaching the LIGO observatories, enabling the possibility to engage EQ mode before their arrival. It works
by monitoring seismic signals from an array of seismic stations hundreds ofkilometers away from each LIGO site. The stations are streamed in real-timeusing a SeedLink connection. The work presented shows the effectiveness of
the Picket Fence in providing between 30 and 100 seconds of accurate forewarning for most teleseismic events of interest for the functioning of the
LIGO detectors. This development has the potential to increase the duty cycleof the detectors, boosting their scientific output. We also show a preliminary
study of the potential benefits of including such an early warning system into
the automated control workflow of the observatories.
poster 19
Examination of Usage Rates for the Multi-Hazards San
Diego County Emergency App to Improve Earthquake Early
Warning
BRUDZINSKI, M. R., Miami University, Ohio, USA, brudzimr@muohio.
edu; SUMY, D., National Science Foundation, Virginia, USA, danielle.
sumy@gmail.com; GOMEZ, K., Miami University, Ohio, USA, gomezka2@
miamioh.edu; JORDAN, P., San Diego County Office of Emergency Services,
California, USA, Patty.Jordan@sdcounty.ca.gov; ROBLES, M., San Diego
County Office of Emergency Services, California, USA, Michael.Robles@
sdcounty.ca.gov; BRICENO, Y., San Diego County Office of Emergency
Services, California, USA, Yuliana.Briceno@sdcounty.ca.gov; REA, S., San
Diego County Office of Emergency Services, California, USA, Stephen.Rea@
sdcounty.ca.gov; POWELL, M., Peraton, Virginia, USA, mpowell@peraton.
com; MILLS, K., Peraton, Virginia, USA, kmills@peraton.com; PARHAM, T.,
Peraton, Virginia, USA, Thomas.Parham@peraton.com
One of the global targets of the Sendai Framework for Disaster Risk Reduction
is to ‘substantially increase the availability of and access to multi-hazard early
warning systems and disaster risk information and assessments to people
by 2030’. To accomplish this, the systems need to be tailored to user specificneeds, have a broad scope of communication channels, and disseminate critical timely hazard information to affected communities. The efficacy of thesesystems, including earthquake early warning (EEW), requires integratingideas from a range of stakeholders, including government, academia, andindustry. A key problem for smartphone applications is attrition, with a recent
study showing that an earthquake detection app had high attrition rates of>90% within a year. In this study, we investigated the usage over time of themulti-hazard warning smartphone app SD Emergency, developed by the San
Diego County Office of Emergency Services and Peraton, its IT provider. As
the only multi-hazard smartphone app in the US that delivers ShakeAlertpowered EEW alerts, we hypothesized SD Emergency would have lower attrition rates. By comparing install and uninstall data for Android and iOS, wefound that the app maintained a retention rate above 50% over the past 6
years. This was based on stable uninstall rates which we interpret as due toregular alerting (~70 alerts per year). Yet even on days with no alerts, there
were twice as many installs as uninstalls. There were also frequent spikes ininstall rates during both natural (e.g., earthquake, fire, weather) and anthropogenic (e.g., boil water notice, oil spill) events. Fire accounted for 55% of allalerts and similarly accounts for ~60% of peaks in the app install rate. Install
rates increased dramatically as the number of alerts per day increased, without
commensurate increases in the uninstall rate. Considering that earthquakes
accounted for <1% of alerts, the multi-hazard alerting strategy substantially
improves the likelihood people will retain EEW capabilities, increasing theefficacy of alerting and maintaining critical communication pathways.

sifiers that distinguish between different types of incoming signals with a highdegree of accuracy when applied to testing datasets. But how well do these
ML classifiers perform when implemented in a real-time Earthquake Early
Warning (EEW) system?
ShakeAlert is the US West Coast EEW system, which now delivers alertsof impending shaking from earthquakes to users throughout California,
Oregon, and Washington. The Earthquake Point-source Integrated Code(EPIC) (formerly ElarmS) algorithm is one of two algorithms currently running in the production ShakeAlert EEW System. EPIC is fast, usually the first
ShakeAlert algorithm to alert, and can create accurate point-source estimatesof earthquake magnitudes and locations using a minimum of 1 sec of datafrom one station, and 0.5 sec of data from three additional stations.
We implemented the Meier et al., 2019 ML classifier into the EPIC algorithm with the goal of reducing the number of false triggers coming into thesystem. This version of EPIC (“mEPIC”) has been running in real-time sinceApril 2023. In this presentation, we give an overview of the real-time mEPIC
algorithm and its performance over the past year.
poster 21
Engage With Your Regional Museums, Parks, and Libraries
for Community Resilience
PRECIADO MENDEZ, R. G., Oregon Museum of Science and Industry,
Oregon, USA, rpreciadomendez@omsi.edu; BENNE, M., Oregon Museumof Science and Industry, Oregon, USA, mbenne@omsi.edu; DE GROOT,
R., U.S. Geological Survey, California, USA, rdegroot@usgs.gov; HERRÁN,C., Oregon Museum of Science and Industry, Oregon, USA, cherran@omsi.
edu; CRAYNE, J., Oregon Museum of Science and Industry, Oregon, USA,jcrayne@omsi.edu
Decades of evidence have demonstrated the unique educational impacts offree-choice learning environments (FCLEs), including their effectivenessfor earthquake education and confirming their value as partners in endto-end Earthquake Early Warning (EEW) communication systems. FCLEs
include museums, parks, libraries, and other informal educational settings.
Cross-disciplinary teams of researchers and educators, organized by USGS
ShakeAlert®, have been studying conditions and opportunities to develop an
emerging, evidence-based model of FCLE cooperation and mutual learning
for the benefit of public EEW end users. This model is being realized through apartnership of Washington, Oregon, and California FCLEs called Earthquake
Public Information Centers (EPIcenters).
To build this partnership, EPIcenter leaders, including the authors, havebeen conducting multi-method research. For example, researchers documented the history, milestones, and recommendations of three previous efforts,
an earlier EPIcenter model, the Great ShakeOut, and the work of the associated ShakeAlert Educational Resources Working Group (ERWG). Researchers
assessed the potential of FCLEs in Washington, Oregon, and California by
documenting the number and type of FCLEs, their location relative to seismic risk, their existing earthquake education activities, and the geographic
distance people need to travel to reach those activities. Researchers conductedinterviews to learn about the effectiveness of recent collaboration models in
the FCLE field. EPIcenter leaders also gathered input from current staff at
FCLEs through interviews and questionnaires. This research confirms that
FCLEs want to, and can effectively, support emergency response and public
education; at the same time, the research confirms that to do so they need the
support of their regional scientists, EEW technical partners, and emergency
response resources. Therefore, to be effective, the EPIcenter partnership modelneeds the public to engage with their regional FCLEs so that they can integratecurrent resources, information, and response expectations into their activities.

poster 20
Implementation of a Machine Learning Classifier in the
Real-Time EPIC Earthquake Early Warning Algorithm
LUX, A. I., University of California, Berkeley, California, USA, angie.lux@
berkeley.edu; HENSON, I., Berkeley Seismological Laboratory, California,
USA, ihenson@berkeley.edu; MEIER, M., ETH Zürich, Zürich, Switzerland,menandrin.meier@erdw.ethz.ch; ALLEN, R. M., University of California,
Berkeley, California, USA, rallen@berkeley.edu

poster 22
Recent Earthquake Early Warning Research andDevelopments at the Southern California Seismic Network
SAUNDERS, J. K., California Institute of Technology, California, USA,jsaunder@caltech.edu; BIONDI, E., California Institute of Technology,
California, USA, ebiondi@caltech.edu; BOESE, M., ETH Zurich, Zurich,
Switzerland, maren.boese@sed.ethz.ch; BUNN, J., California Institute ofTechnology, California, USA, julian.bunn@caltech.edu; COCHRAN, E.,
U.S. Geological Survey, California, USA, ecochran@usgs.gov; FELIZARDO,
C., California Institute of Technology, California, USA, claude@caltech.edu;
GOOD, A., California Institute of Technology, California, USA, agood@
caltech.edu; HEATON, T., California Institute of Technology, California,
USA, heatont@caltech.edu; HUSKER, A., California Institute of Technology,
California, USA, ahusker@caltech.edu

Machine Learning (ML) has been a hot topic in numerous research domains
in recent years. In the field of seismology, researchers have developed ML clas-

We highlight recent earthquake early warning (EEW) algorithm developments conducted by researchers at the Caltech Southern California Seismic

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Network (SCSN), with specific application to the ShakeAlert EEW system
for the West Coast of the United States (US). ShakeAlert is a cooperative
project between the US Geological Survey and partner institutions, including Caltech. Alongside providing seismic data streams to ShakeAlert using
the infrastructure of the SCSN, the Caltech SCSN helps operate and develop
several of the component algorithms in ShakeAlert, particularly the FiniteFault Rupture Detector (FinDer) and the Earthquake Information to Ground
Motion (eqInfo2GM) algorithms. The FinDer algorithm estimates earthquake source parameters by matching observed shaking to pre-computed
templates. Ground-motion-based assessments of FinDer alert performance
will help determine whether updating the ground-motion models in thetemplates will improve alert accuracy. The eqInfo2GM algorithm calculates
median-expected shaking distributions used by ShakeAlert to determine alert
regions. Proposed refinements to the ground-motion modeling proceduresin eqInfo2GM, including adjustments to the ground-motion models and therepresentative site-effect grid, reconcile ground-motion prediction differences
between the ShakeAlert grid and contour alert products as well as improveprediction accuracy.
We also discuss additional developments in EEW approaches that may
be considered for future incorporation into ShakeAlert, including the groundmotion-based Propagation of Local Undamped Motion (PLUM) algorithm
and Distributed Acoustic Sensing (DAS) applications. Recent PLUM developments include the addition of attenuation into the forward-prediction procedure, which brings PLUM predictions closer to the median-expected groundmotion predictions currently used in ShakeAlert. DAS-related EEW efforts
focus on two areas: augmenting seismic data streams with DAS-derived data;
and developing DAS-specific EEW algorithms that utilize machine learning and strain-based scaling relationships to rapidly detect and characterize
earthquakes.
poster 23
Preliminary Multilingual Survey Results on San Diego
County’s Sd Emergency Multi-Hazards App to Improve
Equity in Disaster Risk Reduction
SUMY, D., National Science Foundation, Virginia, USA, danielle.sumy@
gmail.com; BRUDZINSKI, M. R., Miami University, Ohio, USA, brudzimr@
muohio.edu; GOMEZ, K., Miami University, Ohio, USA, gomezka2@
miamioh.edu; BRICENO, Y., San Diego County Office of Emergency Services,
California, USA, Yuliana.Briceno@sdcounty.ca.gov; JORDAN, P., San Diego
County Office of Emergency Services, California, USA, Patty.Jordan@
sdcounty.ca.gov; ROBLES, M., San Diego County Office of Emergency
Services, California, USA, Michael.Robles@sdcounty.ca.gov; REA, S., San
Diego County Office of Emergency Services, California, USA, Stephen.Rea@
sdcounty.ca.gov
The USGS and its partners began testing public alerting with ShakeAlert®
earthquake early warning (EEW) to cell phones in California in October 2019and in Oregon and Washington in 2021. Public EEW aims to reach individuals’ devices before strong earthquake shaking occurs, so they can take protective actions such as ‘Drop, Cover, and Hold On’ (e.g., McBride et al., 2021).
Individuals can receive a ShakeAlert-powered alert on their cell phones via
various smartphone applications, including the University of CaliforniaBerkeley’s MyShake and San Diego County (SDC)’s SD Emergency app.
However, there have been few tests to best understand if people who downloaded an early warning app remain engaged for the long-term, which could
inhibit their usefulness. Further, the apps are likely missing individuals who
speak English as a second language or who have limited English proficiency(LEP). California hosts the largest LEP population (>20% of residents) in the
United States. SDC (and their app SD Emergency) serves a diverse community of over 3.3 million people with a population of ~34% Hispanic/Latinx
in ethnicity and hosts a large immigrant and refugee population that speaks
varied languages. We surveyed SDC residents to find out about (1) theirearthquake experiences; (2) their hazard warning experiences; (3) their familiarity with the SD Emergency app and whether they use the app for EEW orother hazards such as wildfire; (4) barriers to alert comprehension; (5) theiranticipated responses to EEW; and (6) potential improvements to the app thatwould best fit their language requirements. We will highlight preliminary
results from the surveys offered in English, Spanish, Chinese, Tagalog, Arabic,
and Vietnamese, which were the languages that SDC was most interested in.
Building language equity into EEW broadly will help accomplish the United
Nations Sendai Framework’s disaster risk reduction goals to “substantially
increase the availability of and access to multi-hazard early warning systems
and disaster risk information and assessments to people by 2030”.

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poster 24
Magnitude Station Corrections to Improve Initial
Magnitude Estimates for ShakeAlertTERRA, F., University of California, Berkeley, California, USA, terra@berkeley.edu; LOMBARD, P. N., Retired, University of California, Berkeley,
California, USA, lombard@berkeley.edu; WILLIAMSON, A., Universityof California, Berkeley, California, USA, amy.williamson@berkeley.edu;
UHRHAMMER, R., Retired, University of California, Berkeley, California,
USA, ruhrhammer@gmail.com; TAIRA, T., University of California,
Berkeley, California, USA, taira@seismo.berkeley.edu; LUX, A. I., Universityof California, Berkeley, California, USA, angie.lux@berkeley.edu
In the early stages of the ShakeAlert earthquake early warning (EEW) system,
it was considered a success to analyze, locate, and report an earthquake warning promptly. The initial magnitude estimate of the earthquake, within the firstfew seconds, has a large impact on the area of alert. We have investigated how
to better estimate the initial magnitude, including (a) using machine learning
to train the dataset; (b) re-evaluating the initial magnitude scaling relationshipestimate using a larger dataset; and (c) including amplitude station corrections
to account for non-linear characteristics of station effects.
ShakeAlert does currently not use station corrections in normal automatic location and magnitude detection. We propose to include magnitude
station corrections, which are an amplitude correction factor applied to themagnitude initial estimate. We have also developed station correction factors using vertical amplitudes to match the initial P-wave magnitude estimate model more closely. We began by developing a comprehensive list ofmagnitude station corrections for ShakeAlert sites in the West Coast of the
US including UCB, Caltech, PNSN and NRCan network. We have made theassumption that the methodology used to develop the amplitude correction
factor is not important since most of the networks use different methods inthe development of the datasets.
At UCB, dML station corrections were developed using the methodology of Uhrhammer et al. 2011 which uses the horizontal amplitudes selectedon synthetic Wood-Anderson time series. For ShakeAlert, it is important tohave a correction for the P-wave (or vertical data) since the initial magnitude
estimates use the first few seconds of event data in the time domain. Therefore,
we expand the Uhrhammer study to vertical component data of ShakeAlertsites. For vertical data we filter, pick station amplitudes, and determine station
corrections.
Preliminary results show the impact of the inclusion of station corrections on the initial magnitude estimates as shown by case histories for the Oct
2023 Isleton and Aug 2023 Ojai earthquakes.
poster 25
Low-Latency Digitization, Communication and Alerting for
Earthquake Early Warning Systems: Güralp Minimus
LINDSEY, J. C., Guralp Systems Ltd., Reading, United Kingdom, jlindsey@
guralp.com; WATKISS, N. R., Guralp Systems Ltd., Reading, United Kingdom,
nwatkiss@guralp.com; HILL, P., Guralp Systems Ltd., Reading, United
Kingdom, phill@guralp.com; O’NEILL, J., Guralp Systems Ltd., Reading,United Kingdom, joneill@guralp.com
Earthquake Early Warning Systems (EEWS) must combine low-latency digitization, communication, and computational processes to be effective. Thismaximizes the time between the characterization of an event and the warning of the population, thereby providing the longest warning time. Güralp
Systems Ltd. (GSL) has developed the Minimus digitizer with a range of smart
features that reduce latency to 40ms from signal input to digital output.
Minimus makes use of standard processing techniques such as causal
FIR filters to reduce the digitization delay. GSL has also developed andequipped Minimus with the proprietary GDI-link streaming protocol to further reduce the delays in data communication. GDI-link streams data sampleby-sample and will dynamically adjust to the available bandwidth, therefore
providing a fast and reliable communication protocol compared to traditional
packetization protocols. This results in the transmitted data having a dramatically lower mean latency.
Minimus combines familiar STA/LTA algorithms with simple machinereadable event messages to alert operators and populations to impending
ground shaking. When in a triggered state, the Minimus will instantly senda Common Alert Protocol (CAP) event message to a designated receivercontaining the station metadata that indicates an event has occurred. The
Minimus will locally compute the PGA, PGV and PGD parameters from thetriggered event and will subsequently send these calculations as a secondary
CAP message. CAP messaging makes use of existing internet infrastructure
and is already widely used in public communications which will aid EEW network operators with regards to implementation.

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The Minimus has been designed as either a standalone digitizer or canbe integrated into the Fortimus accelerometer and the Certimus broadband
seismometer. The integrated systems provide compact and easy-to-deploy systems that are suitable for widescale EEW deployments.

ESC-SSA Joint Session: Climate Change andEnvironmental Seismology
Oral Session • Friday 3 May • 2:00 pm PacificConveners: Robert E. Anthony, U.S. Geological Survey(reanthony@usgs.gov); Allison Bent, Natural Resources
Canada (allison.bent@nrcan-rncan.gc.ca); Michael
Dietze, Georg-August-University (mdietze@gfz-potsdam.
de); Shujuan Mao, Stanford University (sjmao@stanford.
edu); Robert Mellors, University of California, San Diego(rmellors@ucsd.edu); Siobhan Niklasson, New Mexico
Institute of Mining and Technology (siobhan.niklasson@
student.nmt.edu)
Multi-Decadal Analysis of the Global Microseism in
Climate Context
ASTER, R. C., Colorado State University, Colorado, USA, rick.aster@colostate.edu
It has been recognized for over a century that the oceans produce a continuous microseism signal that is detectable everywhere on Earth. Standardized
global digital seismographic networks such as the GSN and GEOSCOPE now
facilitate the uniform analysis of microseism energy across more than three
decades including recently accelerating anthropogenic climate change. The
globally observable primary microseism signal at 14–20 s period is a particularly apt proxy for global near-coastal wave energy because it is produced
by propagating ocean wave tractions on the seafloor at depths of less thana few hundred m and does not require the interfering wave conditions necessary for the secondary microseism source process. For continuous verticalcomponent seismic records beginning in the late 1980s, robust trend estimation reveals increasing primary microseism amplitudes at significance at
41 of 52 long running GSN stations and decreasing trends at just eight sites
confined to the North and West Pacific region and at two in the southern
United States. Greatest absolute rates of increase are observed for PMSA on
the Antarctic Peninsula with amplitude and energy trends through August2022 () of 0.0370.008 nm/s2/y (0.360.08 %/y) and 4.161.07 (nm/s)2/y (0.580.15%/y), respectively. Assuming linearity and consistent ocean-seismic coupling,
the rate of global near-coastal ocean wave energy increase is 0.270.03 %/y forthe full record and 0.350.04 %/y beginning 1 January 2000. 61-day-smoothedprimary microseism signal station histories regionally cluster to beyond 50o of
separation, demonstrating large spatial integration kernels. Similar analysis of
the 8–14 s secondary microseism signal shows smaller temporal trends attributed to the additional ocean conditions necessary for its excitation. Primaryand secondary histories show consistent station-specific seasonal phase relationships. Primary intensities also correlate with El Nino and La Nina conditions, with increasing energy in the southwest Pacific under positive ENSO
conditions and in the southeast Pacific for negative ENSO conditions.
Seismic Imprints of a Hurricane Landfall: Deciphering the
Atmosphere-Generated Signals From Large-Eddy
Simulation of Turbulence
JI, Q., Stanford University, California, USA, qingji@stanford.edu; DUNHAM,
E. M., Stanford University, California, USA, edunham@stanford.edu; DEY, I.,
Stanford University, California, USA, ipshi91@stanford.edu
One potential scenario of climate change is that tropical storms could become
more intense, which will pose greater impacts upon their landfalls in coastal
regions. The seismic ambient noise generated by these storms provides opportunities to study their imprints from a seismological view, and potentiallyfacilitate the observation and understanding of their evolution.
We present a case study of Hurricane Isaac in 2012 which made landfall as Category 1 on the coast of Louisiana. This storm passed through theTransportable Array (TA) seismic stations on land, which had co-located seismometers and infrasound pressure sensors. One specific station TA.645A isright on the hurricane track and provides valuable in-situ surface pressure
and seismic recordings within the hurricane. High-resolution wavelet spec-

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trograms identify a clear calm hurricane eye. We demonstrate that within the
period band ~ 20 - 100 s, seismic signals are directly contributed by turbulent
surface pressure fluctuations through the local quasi-static coupling mechanism. The same turbulent pressure measurement can also be connected tosurface wind reanalysis snapshots obtained from atmospheric studies.
We further perform numerical modeling of the seismic signals recorded
inside the hurricane eyewall, where the strong azimuthal winds dominate. We
use the open-source code Cloud Model 1 (CM1, Bryan & Fritsch, 2002) toperform a Large Eddy Simulation (LES) of turbulence within the hurricane
boundary layer. This turbulent pressure field provides a realistic input formodeling seismic noise from the atmosphere, and we compute synthetic signals using quasi-static elastic Green’s functions. The modeled surface pressureand vertical displacement have similar amplitudes and coherence patterns tothose observed in the real data. This lays the foundation for future work thatcombines in-situ seismic observations of hurricane landfall with atmosphericmodeling to better constrain hurricane physics. It also demonstrates how seismic data can supplement the currently limited atmospheric datasets obtainedby reconnaissance flights into hurricanes.
How Fast, How Deep, and How Much? — Rapid Assessmentof Groundwater Recharge From 2023 California Storms
With Seismic Sensing
MAO, S., Stanford University, California, USA, sjmao@stanford.edu;
BEROZA, G. C., Stanford University, California, USA, beroza@stanford.edu;
ELLSWORTH, W. L., Stanford University, California, USA, wellsworth@stanford.edu
From the last day of 2022, California was struck by a series of storms frommultiple atmospheric rivers, inflicting extensive damage and hardship on
Californians. These intense storms have also alleviated California’s historical drought, rapidly refilling surface reservoirs; however, it remains unclear
how much water, at which depth, and at what time scale California’s depleted
underground reservoirs have absorbed. Understanding these aspects is crucial for assessing the state’s water deficit and facilitating data-informed water
management.
In this study, we use existing seismological data to understand thenatural recharge of aquifers in Metropolitan Los Angeles (LA) during therecord-wet winter of 2023. With data from 65 broadband seismographs of
the Southern California Seismic Network, we analyze spatiotemporal changes
in seismic velocity (dv/v) using the ambient field across LA from January 1,
2003, to October 31, 2023. These dv/v measurements exhibit strong correlations with records of hydraulic head and satellite gravimetry, serving as an
informative proxy for groundwater storage. At shallow depths, dv/v responds
rapidly to precipitation events, while at deeper depths, dv/v shows a delayed
response at seasonal to inter-annual scales. After the 2023 California Storm
series, dv/v at shallower depths almost fully recovered, whereas at greater
depths, less than 25% of total dv/v loss in the past two decades was recovered.
Furthermore, our dv/v imaging across the LA metropolitan area highlights
prominent aquifer replenishment in San Gabriel Valley and Raymond Basin,
likely from mountain recharge. This study showcases the potential of ambient
field seismology to provide new insights into groundwater fluctuations at different depths. This understanding is crucial for enhancing sustainable water
management especially amidst extreme weather patterns.
Monitoring Groundwater Dynamics at Lyon Water
Catchment Using Seismic Attenuation Variations From
Train Signals
PINZON RINCON, L., Université Grenoble Alpes, GRENOBLE, France,
laurapinzonrincon@yahoo.es; NZIENGUI BÂ, D., Université Grenoble
Alpes, GRENOBLE, France, destin.nziengui-ba@univ-grenoble-alpes.fr;
MORDRET, A., Université Grenoble Alpes, GRENOBLE, France, aurelien.
mordret@gmail.com; BRENGUIER, F., Université de Grenoble Alpes,
GRENOBLE, France, florent.brenguier@univ-grenoble-alpes.fr; COUTANT,O., Université Grenoble Alpes, GRENOBLE, France, olivier.coutant@univgrenoble-alpes.fr
Understanding and monitoring groundwater dynamics are crucial undertakings in contemporary hydrology and hydrogeophysics. Monitoring subsurface
physical properties using single seismic stations poses a challenge. We introduce a novel methodology to monitor subsurface attenuation variations using
train signals. We can measure the seismic attenuation over time by quantifying the relationship between these variations and the train signal frequency
content.
This single-station approach allows local continuous subsurface monitoring, providing new observables to understand the groundwater dynamics.
Lyon water catchment presents an excellent case study due to its recharge

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system and good instrumentation. It is a complex and strategic site that provides 87% of the city’s drinking water. Being located near a highly urbanizedarea, the aquifer is very sensitive to pollution risks. The site uses an artificial
recharge system through several infiltration basins built around the pumping areas to protect the groundwater from river pollution and maintain the
groundwater level.
We applied this method during four weeks when two major eventsoccurred at Lyon water catchment: a flood following the release of a dam
upstream of the wellfield and a few days later, a 8-day controlled water infiltration experiment. By comparing measured attenuation with environmental
observations (e.g., rainfall, bassin level, Piezometer level, noise correlationbased velocity changes), we can gain valuable insights into the complex interactions within the aquifer system.
Our research showcases the potential of using seismic attenuation variations from train signals to study and monitor groundwater dynamics in acontext like Lyon water catchment. Seeking continuous monitoring offered bythis method will lead to a deeper understanding of subsurface processes andcontribute to better management of vital groundwater resources.
Merits of Installing Environmental Sensors at Seismic
Stations
TANIMOTO, T., University of California, Santa Barbara, California, USA,toshirotanimoto@ucsb.edu
The EarthScope Transportable Array (TA) in Alaska is a unique seismic network because most stations have co-located pressure, temperature, and wind
sensors. We will point out some merits of having such co-located environmental sensors and stress their importance.
First, the combined analysis of seismic and pressure data allows us toseparate two types of seismic noise; one is the ordinary seismic noise, consisting of propagating body and surface waves, and the other is ground deformation caused by the local pressure loading. This loading effect can be confirmed
from two pieces of evidence; the coherence between seismic and pressure
data and the phase difference between pressure and vertical seismic displacement. By selecting data from a high-pressure range, we can apply the compliance method and derive shallow elastic structures for a depth range of about
50-100m. Second, the combined analysis of temperature and seismic noise
allows us to identify the major effects of near-surface melting in summer, primarily in the permafrost area. Some stations show a thousand-fold increase inhorizontal noise in summer at 0.01-0.03 Hz in comparison to the frozen state
in winter. This anomalous horizontal noise can be seen at low frequencies (<0.1 Hz) and is most likely related to the tilt effects as its amplitude increases
towards lower frequencies. Third, the way the noise level returns to the frozen, low-noise state after the major melting varies from station to station. For
many stations, this return occurs well after the surface temperature becomes
negative in September or October. Some stations require time until March of
the following year to return to the frozen state. These data suggest that themelt layer remains at depth for a long time even after surface temperaturedrops below freezing, creating a sandwiched molten layer between the developing ice from the surface and the underlying permafrost ice. These results
and perspectives have been gained because of the availability of co-locatedseismic and environmental data and underscore the importance of installing
environmental sensors at seismic stations.
Leveraging Distributed Fiber Optic Sensing for Year-RoundObservation of Sea Ice and Submarine Permafrost:
Successes and Lessons Learned From the Beaufort Sea,
Alaska.
BAKER, M. G., Sandia National Laboratories, New Mexico, USA, mgbaker@
sandia.gov; STANCIU, C., Sandia National Laboratories, New Mexico, USA,astanci@sandia.gov; ABBOTT, R. E., Sandia National Laboratories, New
Mexico, USA, reabbot@sandia.gov; FREDERICK, J. M., Sandia National
Laboratories, New Mexico, USA, jmfrede@sandia.gov
Arctic sea ice and submarine permafrost are key indicators and positive-feedback mediators of global climate change. Sea ice extent is a major component of global albedo, and sea ice thickness provides thermal insulation to the
Arctic Ocean. Submarine permafrost in the Beaufort Sea is known to containextensive reservoirs of gas hydrates which would release globally significant
amounts of methane if thawed. The Arctic is insufficiently monitored, relative
to its importance, due to its remoteness and logistical challenges. For the past
three years, we have recorded distributed acoustic and temperature sensing
on a commercial submarine telecommunications cable in the Beaufort Sea,
Alaska, to test the capabilities of these technologies for temporospatial monitoring of polar coastal processes. We present an overview of our significant
findings, including acoustic-gravity detection of sea ice extent, thickness, andVolume 95•

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dynamics, and tomographic and thermodynamic imaging of permafrost distribution. Sandia National Laboratories is managed and operated by NTESS
under DOE NNSA contract DE-NA0003525.
Storms, Sea Ice, and Microseismic Noise in Alaska
JOHN, S., University of Alaska Fairbanks, Alaska, USA, sjohn19@alaska.edu;
WEST, M., University of Alaska Fairbanks, Alaska, USA, mewest@alaska.edu
This study investigates how environmental drivers like ocean storms and sea
ice affect microseismic noise across Alaska. Ocean storms have long been
understood to be the primary driver of microseism noise. At the same time,
sea ice suppresses the formation of waves in oceans, dampening microseism
production. By examining the long-term correlation of microseismic noiseand ocean wave height, we find that the secondary microseismic noise (5-10s)
across the whole state is mainly affected by the sea state in the Gulf of Alaska.
We also find that the waves in the eastern Gulf produce higher amplitude
microseism than the west. Findings from these long-term correlations aresubstantiated by observed patterns during individual storms. Similar correlation analysis also reveals that the microseismic noise in the 1-2s period
band is primarily driven by ocean waves closer to the coast. Seasonally, inthe 1-2s period, we observe an abrupt reduction of seismic power due to theonset of sea ice. Because the 1-2s period microseismic noise is driven primarily by waves near the coast, it is coastal ice that is primarily responsible forthis dampening effect. These findings are useful in understanding the role ofclimate in microseismic noise across Alaska. Phenomena with societal significance are visible directly in the microseismic noise, including the onset
and progressive break up of sea ice, the movement of storms across the open
oceans, and the arrival and end of the annual storm season. In this study, weshow how to calculate ocean storm parameters like position, track, and temporal evolution using microseismic noise records. Declining sea ice coupledwith increasing extratropical cyclones is also known to accelerate the rate ofcoastal erosion in Alaska, posing serious threats to the Arctic communities
and ecology. We identify the coastal erosion period from the microseismic
noise in the 1-2s period band as it is influenced by both sea ice and coastal sea
state. We also compare and contrast the yearly variation of the coastal erosion
period in northern Alaska on a decadal time scale.
Correlation of Environmental Factors With Seismic Records
on the Alaska Geophysical NetworkHESLOP, J., University of Alaska Fairbanks, Alaska, USA, jheslop@
alaska.edu; MURPHY, N., University of Alaska Fairbanks, Alaska, USA,nwmurphy@alaska.edu; WEST, M., University of Alaska Fairbanks, Alaska,
USA, mewest@alaska.edu; PARCHETA, C., University of Alaska Fairbanks,
Alaska, USA, ceparcheta@alaska.edu; RUPPERT, N., University of Alaska
Fairbanks, Alaska, USA, naruppert@alaska.edu; MCFARLIN, H., Universityof Alaska Fairbanks, Alaska, USA, hlmcfarlin@alaska.edu; HOLTKAMP,
S., University of Alaska Fairbanks, Alaska, USA, sgholtkamp@alaska.edu;
FARRELL, A., University of Alaska Fairbanks, Alaska, USA, akfarrell@alaska.
edu; STUEFER, M., University of Alaska Fairbanks, Alaska, USA, mstuefer@alaska.edu; NICKOLSKY, D., University of Alaska Fairbanks, Alaska, USA,
djnicolsky@alaska.edu; MACPHERSON, K., University of Alaska Fairbanks,
Alaska, USA, kamacpherson@alaska.edu; FEE, D., University of Alaska
Fairbanks, Alaska, USA, dfee1@alaska.edu; JOHN, S., University of Alaska
Fairbanks, Alaska, USA, sjohn19@alaska.edu; QUIGLEY, C., University of
Alaska Fairbanks, Alaska, USA, caquigley@alaska.edu
The Alaska Geophysical Network (AGN), maintained by the Alaska
Earthquake Center (AEC), consists of over 250 remote monitoring stations
located across the state of Alaska. Each station records real-time, or near realtime, seismic data. Roughly half the stations include weather and infrasoundsensors collecting real-time data in parallel with the seismic sensors. Manyof the stations also include continuous near-surface soil temperature sensors.
This combination of co-located sensors combined with the broad geographic
coverage of the network provides a robust and unique dataset for investigating
and modeling a range of environmental and geophysical conditions, and theirinterplay, in arctic and subarctic regions.
Seismic data are influenced by a variety of environmental factors,
including weather and ground conditions. Hence, seismic and network diagnostic records can be used to model environmental conditions in regions withsparse observations, and seismic network performance can be forecast basedon environmental conditions. Some applications of this co-located, crossdisciplinary data we and collaborating organizations have been exploring are:associating seismic data with wind and sea ice conditions; utilizing weather
data collected on our network to generate fire weather forecasts; and using
infrasound data to estimate seismic velocity and earthquake magnitudes. At
multiple stations, we have observed higher wind speeds correlate to increased

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seismic noise. Environmental factors such as increased vegetation height,
lack of snow cover, and thawing permafrost ground led to increased noisein the seismic records. In the Arctic, climate change is projected to increase
vegetation heights via shrub expansion, decrease sea ice cover, cause less stable ground due to warming and thawing permafrost, and have higher windspeeds. Combining these findings, we anticipate increasing seismic noise in
the Arctic over the coming decades.
An Extraordinary Tsunamigenic Rockslide Into a Greenland
Fjord Rang the Earth for 9 Days
SVENNEVIG, K., Geological Survey of Denmark and Greenland,
Copenhagen, Denmark, ksv@geus.dk; HICKS, S. P., University College
London, London, United Kingdom, stephen.hicks@ucl.ac.uk; FORBRIGER,
T., Black Forest Observatory, Geophysical Institute, Karlsruhe Institute ofTechnology, Karlsruhe, Germany, thomas.forbriger@kit.de; LECOCQ, T.,
Royal Observatory of Belgium, Brussels, Belgium, thomas.lecocq@seismology.
be; WIDMER-SCHNIDRIG, R., Black Forest Observatory, University of
Stuttgart, Stuttgart, Germany, widmer@gis.uni-stuttgart.de; MANGENEY,
A., Institut de Physique du Globe de Paris, Paris, France, mangeney@ipgp.
fr; HIBERT, C., Institut Terre et Environnement de Strasbourg, Strasbourg,
France, hibert@unistra.fr; KORSGAARD, N. J., Geological Survey ofDenmark and Greenland, Copenhagen, Denmark, njk@geus.dk; LUCAS,
A., Institut de Physique du Globe de Paris, Paris, France, lucas@ipgp.
fr; SATRIANO, C., Institut de Physique du Globe de Paris, Paris, France,
satriano@ipgp.fr; ANTHONY, R. E., U.S. Geological Survey, New Mexico,USA, reanthony@usgs.gov; MORDRET, A., Université Grenoble Alpes,
Grenoble, France, aurelien.mordret@univ-grenoble-alpes.fr; SCHIPPKUS,
S., Universität Hamburg, Hamburg, Germany, sven.schippkus@uni-hamburg.
de; RYSGAARD, S., Aarhus University, Aarhus, Denmark, rysgaard@au.dk;
BOONE, W., Flanders Marine Institute, Oostende, Belgium, wieter.boone@
vliz.be; GIBBONS, S., Norges Geotekniske Institutt, Oslo, Norway, steven.
gibbons@ngi.no; COOK, K. L., University of Grenoble Alpes, Grenoble,
France, kristen.cook@univ-grenoble-alpes.fr; GLIMSDAL, S., Norges
Geotekniske Institutt, Oslo, Norway, sylfest.glimsdal@ngi.no; LØVHOLT,
F., Norges Geotekniske Institutt, Oslo, Norway, finn.lovholt@ngi.no; VAN
NOTEN, K., Royal Observatory of Belgium, Brussels, Belgium, koen.
vannoten@seismology.be; EBELING, C., University of California, San Diego,
California, USA, cebeling@ucsd.edu; VOSS, P. H., Geological Survey ofDenmark and Greenland, Copenhagen, Denmark, pv@geus.dk
Climate change is preconditioning large landslides in polar regions throughseveral mechanisms including hillslope debruttressing from glacial retreat,
permafrost degradation, and changes in precipitation. Tsunamigenic landslides have occurred recently in Greenland (Kalaallit Nunaat), but there havebeen no previously documented occurrences on the east coast of the island.
On 16 September 2023, we observed an unprecedented monochromatic verylong period (VLP) seismic signal at 10.88 mHz that was recorded on someseismic stations for 9 days following the event and was found to originate from
East Greenland. We demonstrate how this event started with a 25 M m3 glacial
thinning-induced rockslide impacting within Dickson Fjord which triggered
a 200 m high tsunami that caused extensive damage to the Danish researchbase at Ella Island, ~65 km down fjord. Simulations show the tsunami stabilized into a 5 m high transverse seiche within Dickson Fjord, oscillating at afrequency similar to the VLP surface waves. However, the observed ultra-longseismic duration may reflect an elusive component of the source. Due in partto the event occurring after the summer travel and field season, no fatalities
were associated with this event. Analysis of historical seismic data revealed
four previously unknown VLP events of similar period; a subsequent event
also occurred on 11 October 2023. The four most recent events have occurredsince 2016 and, based on satellite altimetry, are correlated with landslides inDickson Fjord. Ongoing warming will increase the societal risk posed by tsunamigenic landslides in polar regions including Greenland and Alaska.
Insights for Adjacent Sciences—Connecting Science, Art
and Deep Knowledge for Climate Adaptation and
Mitigation
STRICKERT, G. E. H., University of Saskatchewan, Saskatoon, Canada,graham.strickert@usask.ca; BRADFORD, L. E. A., University of Saskatchewan,
Saskatoon, Canada, lori.bradford@usask.ca; HELGASON, W., University of
Saskatchewan, Saskatoon, Canada, warren.helgason@usask.ca
Climate change has exerted profound and far-reaching impacts on the world’s
water resources, including the atmosphere, glaciers, lakes and rivers, groundwater systems, energy, gas exchange, and living systems. While seismology
and hydrology have historically operated as distinct disciplines, a promising avenue for advances lies in their potential synergy. A cross-disciplinary

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approach to earth systems change that integrates social and physical sciences,indigenous knowledge and artistic pursuits can significantly augment our
understanding of climate change, thereby informing adaptive strategies andmitigation efforts. Here, we present insights for adjacent sciences derived froma decade of transdisciplinary research in Canadian water security supportedby the Global Water Futures program. The authors are establishing integrated
observatories for cold region hydrological processes, such as freeze-up andbreak-up, including their impact on gas exchange in various landscapes.
Integrating existing seismic networks with hydro-metric stations can enhance
our understanding of climate change, water security, and the developmentof effective adaptation strategies. The data collected in one field may havebroader applicability across multiple disciplines, expanding the boundaries ofknowledge-sharing. Collaborative endeavors involving artists, scientists, andcustodians of deep knowledge can yield fresh perspectives and insights that
hold substantial value for science, policymakers, and society. Tools originallydesigned for seismic data analysis not only benefit geologic investigations but
are also useful in fields such as hydrology (e.g. river ice break up), social-ecological systems (e.g. Wetland drainage), and even biology (e.g. animal migration). Recognizing and valuing research contributions from diverse domains,irrespective of their direct relevance to one’s field, fosters dynamic and productive transdisciplinary collaborations. By harnessing these multifaceted
approaches, we can elevate our understanding of climate change’s impact onwater resources and generate novel solutions to enhance water security.

ESC-SSA Joint Session: Climate Change andEnvironmental Seismology [Poster Session]
Poster Session • Friday 3 May
Conveners: Robert E. Anthony, U.S. Geological Survey(reanthony@usgs.gov); Allison Bent, Natural Resources
Canada (allison.bent@nrcan-rncan.gc.ca); Michael
Dietze, Georg-August-University (mdietze@gfz-potsdam.
de); Shujuan Mao, Stanford University (sjmao@stanford.
edu); Robert Mellors, University of California, San Diego(rmellors@ucsd.edu); Siobhan Niklasson, New Mexico
Institute of Mining and Technology (siobhan.niklasson@
student.nmt.edu)
poster 26
Successful Deployment of an 21km SMART Cable With
Force-Feedback Seismometer and Accelerometers in the
Mediterranean Sea
LINDSEY, J. C., Guralp Systems Ltd., Reading, United Kingdom, jlindsey@
guralp.com; O’NEILL, J., Guralp Systems Ltd., Reading, United Kingdom,joneill@guralp.com; NICHOLSON, B., Guralp Systems Ltd., Reading, United
Kingdom, bnicholson@guralp.com; WATKISS, N., Guralp Systems Ltd.,
Reading, United Kingdom, nwatkiss@guralp.com; MARINARO, G., Istituto
Nazionale di Geofisica e Vulcanologia, Rome, Italy, giuditta.marinaro@ingv.it;
SIMEONE, F., Istituto Nazionale di Geofisica e Vulcanologia (INGV), Rome,
Italy, francesco.simeone@ingv.it; DAVIDE, E., Istituto Nazionale di Geofisicae Vulcanologia, Rome, Italy, davide.embriaco@ingv.it
Autonomous Ocean Bottom Seismometer (OBS) deployments pose a large
degree of risk due to the inherent lack of data communication during installation resulting in 12+ months before data collection. Cabled solutions provide
real-time data during deployment, sometimes with the opportunity to adjust
the instrument before it is left to operate remotely. However, cabled solutions
are inherently financially and logistically challenging both in terms of seismic hardware and arguably more significantly, deployment hardware (ships,
ROVs, cables, etc.). The geographical reach of these experiments is also often
limited to within a few hundred kilometers of the coast. These constraints
often mean cabled OBS are beyond the scope of most scientific bodies.
Güralp Systems, in collaboration with INGV, has successfully manufactured and demonstrated a method of reducing financial and logisticalconstraints and extending geographical range by utilizing force-feedback
seismic instrumentation in cabled OBS systems. The recent successful deployment of the InSEA Wet Demo SMART (Science Monitoring And Reliable
Telecommunications) cable displays a world first in how science can partnerwith industry to achieve this.
SMART cables are primarily telecommunication cables that secondarily
serve as hosts for scientific monitoring equipment. Commercial viability for

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these systems relies on the cable being laid in a commercially standard manner, thereby minimizing additional deployment costs and reducing barriers
to cooperation with cable laying companies. GSL and INGV deployed 3 seismometer-accelerometer pairs housed inline repeaters along the 21km cable
length using standard cable-laying techniques to show proof of concept. The
system also features a series of high-performance temperature and pressure
sensors that can be used for larger-scale oceanographic monitoring.
This pioneering installation using telecommunication cables marks asignificant step towards drastically improving local knowledge of inaccessible
oceanic regions as well as global azimuthal coverage for teleseismic events, allin real-time.
poster 27
Using Deep Learning to Detect Vehicle Related Signals
From Seismic Records
CHAI, C., Oak Ridge National Laboratory, Tennessee, USA, chaic@ornl.
gov; MARCILLO, O., Oak Ridge National Laboratory, Tennessee, USA,
marcillooe@ornl.gov; MACEIRA, M., Oak Ridge National Laboratory,
Tennessee, USA, maceiram@ornl.gov; KEREKES, R., Oak Ridge National
Laboratory, Tennessee, USA, kerekesra@ornl.gov
In the interest of safety and security, it is imperative for research and industry facilities to effectively monitor vehicle movements within their premises.
While cameras have traditionally been employed for this purpose, concerns
over privacy and susceptibility to light or weather conditions have prompted
the exploration of alternative technologies. Seismic sensors, due to their unobtrusive nature and ability to capture ground motions generated by vehicle
movements, present a promising solution. To assess the feasibility of utilizing
seismic sensors for vehicle detection, we conducted a comprehensive study.
We deployed three sets of nodal-type seismic stations in proximity to a roadat the main campus of Oak Ridge National Laboratory. Each station set wascollocated with a camera to cross-reference and validate the data. The labelsof detected vehicles were processed using the images recorded by the cameras. We then use these labels, along with the corresponding seismic signals,
to train a deep learning model. Over the course of the station deployment,
an extensive dataset comprising more than 500,000 seismic signals and labels
was gathered. Using this dataset, we trained a deep learning model designed
to categorize whether a seismic signal contains a vehicle-related signature ornot. As the deep learning model can use either a seismogram or a spectrogram as input, we evaluated the model performance for both cases. The results
show that using a spectrogram leads to better model performance. Our model
achieved an impressive F1-score exceeding 0.9. These findings underscorethe potential of seismic sensors as a valuable complementary tool for vehicle
monitoring, offering a resilient and privacy-conscious alternative to camerabased systems.
poster 28
Monitoring Groundwater Using Ambient Seismic NoiseD’AMICO, S., University of Malta, Msida, Malta, sebastiano.damico@um.edu.
mt; GALONE, L., University of Malta, Msida, Malta, luciano.galone@um.edu.
mt; PANZERA, F., University of Catania, Catania, Italy, francesco.panzera@
unict.it; COLICA, E., University of Malta, Msida, Malta, emanuele.colica@
um.edu.mt; FUCKS, E., National University of La Plata, La Plata, Argentina,
efucks@fcnym.unlp.edu.ar; CAROL, E., National University of La Plata, La
Plata, Argentina, eleocarol@fcnym.unlp.edu.ar; CELLONE, F., National
University of La Plata, La Plata, Argentina, fcellone@fcnym.unlp.edu.ar;
RIVERO, L., Universitat de Barcelona, Barcelona, Spain, lrivero@ub.edu;
AGIUS, M. R., University of Malta, Msida, Malta, matthew.agius@um.edu.mt
The management of groundwater resources forms a crucial component of
national policies. Different countries around the world are experiencing crises in groundwater availability as a result of a number of economic, social,and environmental conditions. Therefore, efficient management of groundwater resources is dependent on accurate knowledge and understanding of
the behavior and variability of the aquifers. Such knowledge is often lacking
or limited to sparse and highly localized information. This study focuses on
analyzing ambient seismic noise recorded in two different geological environments: the island of Malta (central Mediterranean) and the Río de laPlata Coastal Plain (Argentina). The latter features partially interconnected
coastal aquifers developed in thick sedimentary deposits. In contrast, theMalta hydrogeology is mainly controlled aquifers that occur in limestonerocks. In the Argentina case study, the analysis reveals two HVSR peaks, with

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the first one associated with the sediment-basement interface and the highfrequency one linked to a shallower stratigraphic discontinuity. Temporal
analysis of the high-frequency peak highlights cyclical patterns correlatedwith estuarine levels, suggesting a relationship between variations in seismic
velocities and tidal dynamics. Comparisons with aquifer data support thisinterpretation. For the Maltese island, variations in amplitude spectra which
can be related to the variation of the upper water table. This work has been
supported by DEMUWA project which is financed by the Malta Council for
Science and Technology through the Space Research Fund (Building Capacity
in the Downstream Earth Observation Sector), a program supported by theEuropean Space Agency. Funds were also made available through the IPAS
(Internationalisation Partnership Awards Scheme), funded by the Malta
Council for Science and Technology.
poster 29
Influence of the Hurricane Otis on the Mexican Seismic
Network
DOMINGUEZ, L. A., Universidad Nacional Autónoma de México, Coyoacán,Ciudad de México, Mexico, ladominguez12@gmail.com; QUINTANAR, A.,
Universidad Nacional Autónoma de México, Mexico City, Mexico, arturo.
quintanar@atmosfera.unam.mx; CRUZ-ATIENZA, V. M., Universidad
Nacional Autónoma de México, Mexico City, Mexico, atienza@igeofisica.
com; GÓMEZ-RAMOS, O., Universidad Nacional Autónoma de México,
Mexico City, Mexico, octavio@igeofisica.unam.mx; PLATA-MARTINEZ, R.,
Universidad Nacional Autónoma de México, Mexico City, Mexico, raymundo.
plata@gmail.com; VILLAFUERTE, C., Universidad Nacional Autónoma deMéxico, Mexico City, Mexico, villafuerte.cd@gmail.com
The hurricane Otis became the most destructive meteorological phenomenon
ever recorded in Mexico. Strong winds up to 300km/h caused intense damage
to the coastal infrastructure causing disruption that lasted for several weeks.
This unexpected event started as a tropical depression which evolved into a
category 5 hurricane within an unprecedented short period of time. From
October 24th, 2023 (03:00 local time) through October 25th (00:00 local time),
the system evolved from a tropical storm to a category 5 hurricane, causingwidespread damage in the port city of Acapulco. As the hurricane approached
the coast, the low pressure induced low-frequency seismic waves that spreadout across Mexico being recorded by several permanent seismic stations. In
this study, we examine to which extent this low-frequency waves travel within
the crust and the role that the geometry of the subducting slab played in theconfinement of the energy.
poster 30
Glacier Seismology Application
GERMENIS, N. G., Geobit Instruments, Patra, Greece, ngermenis@geobitinstruments.com
Seismology at glaciers and ice sheets has the potential to remotely track waterflow and changes in the frictional properties of glacier and ice sheet beds.
To better understand the frictional properties of the bed of the Greenland
Ice Sheet and its response to meltwater input from the ice sheet surface, we
installed an array of GEObit and other compact, posthole-type seismometers.
Following 5 months of continuous operation, visited only once to redrill the
sensors following melt out to the surface, the sensors were recovered. Both the
GEObit and other sensors behaved comparably, recording tens of thousandsof small (<M1) icequakes. While the majority of icequakes originated fromshallow depths near the ice sheet surface, hundreds of these icequakes havecharacteristics consistent with an origin at the ice sheet base. We examined thespatial and temporal patterns of these icequakes to reveal the heterogenous
frictional properties of the ice sheet bed.
In this work GEObit equipment was used for the seismic monitoring of
the glaciers and they performed great. The sensors (C100 borehole seismometers) were placed into post holes of 1.5 5m depth drilled into the ice. The dataloggers (model Sri32 - older version of the GEOthree datalogger) were placedat the surface, into Peli type cases. The seismographs were able to get powerfrom a small 35Ah battery and a small solar panel because of their low power
requirements. The sensor bandwidth is 10sec to 98Hz and the sensitivity is
1500V/m/s. The digitizer uses high resolution 32bit ADC and up to 1000sps.
The data are stored into a microSD card with capacity 32Gbytes, enough tostore more than a year’s data. The sensors left to operate unattended for several
months, recording at 100sps. At the end of the recording period, the data were
downloaded from the microSD cards to the computer for processing.

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poster 31
Estimation of the Source Region of Secondary Microseism
Generated by Pacific Typhoons Using CTBTO Seismic Arrays
KIM, Y., Chonnam National University, Gwangju, South Korea, kyuna@jnu.
ac.kr; SHEEN, D., Chonnam National University, Gwangju, South Korea,
dhsheen@jnu.ac.kr
Secondary microseism (SM) or double-frequency microseism, observed
worldwide around the 8-second period, is known to occur due to non-linear
interaction of opposing oceanic wavefields of similar wavenumbers (LonguetHiggins, 1950). Hence, monitoring SM can serve as a proxy for comprehending oceanic activities and contribute to a better understanding of couplings
between the atmosphere, ocean and solid earth. However, there is a debate
regarding whether SMs are predominantly excited near coastlines in shallow
water regions or whether it is possible to generate SMs in deep-sea regions.
In this study, we initially investigated variations in power spectral densities of
SMs at costal and island seismic stations nearby the track of Pacific typhoons
in 2022, as well as at Comprehensive Nuclear-Test-Ban Treaty Organization(CTBTO) seismic arrays in Asia and Australia. We then compared these variations with the ocean wave model of Wave Watch III. The source regions of SMs
recorded at CTBTO arrays were estimated through the triangulation method,
utilizing back azimuths obtained from frequency-wavenumber analysis. Thesesource regions were then compared with the best track data provided by the
Joint Typhoon Warning Center (JTWC).
poster 32
Global Observation of an Up to 9 Day Long, Recurring,
Monochromatic Seismic Source Near 10.9 mHz AssociatedWith Tsunamigenic Landslides in a Northeast Greenland
Fjord
WIDMER-SCHNIDRIG, R., University of Stuttgart, Stuttgart, Germany,
widmer@gis.uni-stuttgart.de; MORDRET, A., Université Grenoble Alpes,
Grenoble, France, aurelien.mordret@univ-grenoble-alpes.fr; SVENNEVIG,
K., Geological Survey of Denmark and Greenland, Copenhagen, Denmark,ksv@geus.dk; HICKS, S. P., University College London, London, United
Kingdom, stephen.hicks@ucl.ac.uk; FORBRIGER, T., Karlsruhe Institute ofTechnology, Karlsruhe, Germany, thomas.forbriger@kit.de; LECOCQ, T.,
Royal Observatory of Belgium, Brussels, Belgium, thomas.lecocq@seismology.
be; MANGENEY, A., Université Paris Cité, Paris, France, mangeney@ipgp.fr;
HIBERT, C., Université de Strasbourg, Strasbourg, France, hibert@unistra.
fr; KORSGAARD, N. J., Geological Survey of Denmark and Greenland,
Copenhagen, Denmark, njk@geus.dk; LUCAS, A., Université Paris Cité, Paris,
France, lucas@ipgp.fr; SATRIANO, C., Université Paris Cité, Paris, France,
satriano@ipgp.fr; ANTHONY, R. E., U.S. Geological Survey, New Mexico,USA, reanthony@usgs.gov; SCHIPPKUS, S., Universität Hamburg, Hamburg,
Germany, sven.schippkus@uni-hamburg.de; RYSGAARD, S., Aarhus
University, Aarhus, Denmark, rysgaard@au.dk; BOONE, W., Flanders Marine
Institute, Oostende, Belgium, wieter.boone@vliz.be; GIBBONS, S., Norges
Geotekniske Institutt, Oslo, Norway, steven.gibbons@ngi.no; COOK, K. L.,
University Grenoble Alpes, Grenoble, France, kristen.cook@univ-grenoblealpes.fr; GLIMSDAL, S., Norges Geotekniske Institutt, Oslo, Norway, sylfest.
glimsdal@ngi.no; LØVHOLT, F., Norges Geotekniske Institutt, Oslo, Norway,
finn.lovholt@ngi.no; VAN NOTEN, K., Royal Observatory of Belgium,
Brussels, Belgium, koen.vannoten@seismology.be; VOSS, P. H., Geological
Survey of Denmark and Greenland, Copenhagen, Denmark, pv@geus.dk;
EBELING, C., University of California, San Diego, California, USA, cebeling@
ucsd.edu; ., G., Geological Survey of Denmark and Greenland, Copenhagen,Denmark, ksv@geus.dk
We report the discovery of an unprecedented, monochromatic low-frequency
seismic source arising from the fjords of North-East Greenland. Following
a landslide and tsunami event in Dickson fjord on 16 September 2023, seismic waves were detected by broad-band seismometers worldwide. Bothfrequency and phase velocity of the waves are consistent with fundamental
mode Rayleigh- and Love-waves. However, the decay rate of these waves ismuch slower than predicted for freely propagating surface waves. Therefore,
we infer a long-lasting and slowly decaying source process. Although the 16
September 2023 event was by far the largest, analysis of historical seismic data
has revealed five other previously undetected events, all with a fundamental
frequency between 10.85 and 11.02 mHz. Of these six events, the signal of thelargest two events initially decayed with a quality factor, Q close to Q=500.
This increased to Q=3000 within the first 10 hours and could thus be detected
for up to nine days. The smaller four events had a slow decay-rate (Q>1000)
for their entire duration. In comparison, the global average attenuation ofRayleigh waves at these frequencies is Q=117 for PREM, thus precluding asingle, impulsive source for these signals.

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Gleaning archives of optical and SAR satellite images reveals that atleast four of the six events could be temporally correlated with landslides inDickson fjord. However, such rapid transient events cannot explain the long
duration of the radiated seismic waves. Our modelling of the largest eventshows that a transversal seiche in Dickson fjord, excited by a landslide induced
tsunami, can account for both the monochromatic low frequency signal aswell as its seismic signal amplitude and radiation pattern. However, our seichemodelling indicates that the seiche should have Q < 250. Therefore, it remains
unclear what keeps the seiche going for the entire duration of the observed
seismic signal. However, the phase coherence of the VLP signal leads us toconjecture that an undetermined, in-phase, force feedback mechanism may
be at work to continuously add energy into the system.
poster 33
Exploration of Decadal Crustal Velocity Changes
Associated With Tidal-Induced Strain Using Seismic NoiseWU, S., Lawrence Berkeley National Laboratory, California, USA, a06859a35@
gmail.com; NAKATA, N., Lawrence Berkeley National Laboratory, California,
USA, nnakata@lbl.gov
Earth’s tide modulates the volumetric strain within the subsurface that
impacts groundwater level. Through in-situ measurement in a well, it is possible to deduce hydrological response (i.e., permeability) by analyzing the timelags between predicted tidal forces and the corresponding changes in waterlevels. In this presentation, we explore a non-invasive, single-station method
to understand the capability of monitoring subsurface permeability using adecade of continuous seismic data from northern Chile. We extract coherent
wavefields by 6-component noise correlation at a single station. The velocity
variations are measured with a 30-minute resolution based on the changes
in the coda wavefields of correlation functions at frequency range of 3–7 Hz
over time. The seismic velocity reflects subsurface elasticity and is sensitive
to ground motion, precipitation, pressure and temperature changes. Our
decade-long, time-lapse velocity variations exhibit diurnal and semidiurnal
cycles likely influenced by solar tides and radiation. Furthermore, we observea robust semidiurnal cycle related to lunar tides, M2. The M2 cycle is expected
to exclusively link to volumetric strain modulation and free from effects ofthermal strain. Therefore, our discussion will center on the potential hydrological implications specifically focusing on the observed lunar tides cycle.
poster 34
Resolving Temporal Variations in Subsurface Velocity and
Attenuation Structure Across the Taklimakan Desert Using
Road Traffic Seismic Signals
ZHAO, L., Chinese Academy of Science, Beijing, China, zhaolulu3jlu@163.
com; MENG, H., Southern University of Science and Technology, Beijing,
China, menghr@sustech.edu.cn; LIANG, X., Chinese Academy of Science,
Beijing, China, liangxf@mail.iggcas.ac.cn
Monitoring temporal changes in subsurface structure is crucial for interpreting how the Earth’s media interacts with factors such as temperature, fluids,
and stress. In this study, we resolve the temporal variation of velocity andattenuation in the Taklimakan Desert using traffic-induced ground motions
recorded by three broadband seismographs located near highways. We firstcompute the H/V spectral ratios of the 3-component data and track the swingsof the peaks and valleys to estimate the velocity changes. To characterize
Q-values, we then model the vertical spectra of ballistic waves generated bymassive road traffic events. The results reveal temporal variations in the sandsubsurface, with velocity changing by up to 4% and Q-value by up to 10% in
the frequency band of 10-45 Hz. These changes show a positive correlation
with seasonal temperature fluctuations but are negatively modulated by local
precipitation with negligible lags. This suggests that changes in the cohesionof the shallow sand layer are primarily induced by thermoelastic strain andfluid effects.

From Earthquake Recordings to Empirical GroundMotion Modelling
Oral Session • Thursday 2 May • 8:00 am PacificConveners: Carlo Cauzzi, ORFEUS, Swiss Seismological
Service, ETH Zürich (carlo.cauzzi@sed.ethz.ch); Fabrice
Hollender, CEA Cadarache (fabrice.hollender@cea.fr);
Vincent Perron, CEA Cadarache (vincent.perron@cea.fr);

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Zafeiria Roumelioti, University of Patras (zroumelioti@
upatras.gr); Paola Traversa, Electricite de France (paola.
traversa@edf.fr)
From Satellites to Soil Response: Analyzing Body Wave
Velocity Variations at Shallow Depths in Sync With
Satellite Soil MoistureKYRIOU, A., University of Patras, Patras, Greece, a.kyriou@ac.upatras.
gr; ROUMELIOTI, Z., University of Patras, Patras, Greece, zroumelioti@
upatras.gr; HOLLENDER, F., French Alternative Energies and Atomic Energy
Commission, Cadarache / Grenoble, France, fabrice.hollender@cea.fr
Several recent studies have shown that the cyclicity of meteorological seasonsis imprinted as time variations in the velocity of shear waves, VS, at shallow
depths. This has been known for decades from laboratory tests but has only
recently been verified using actual earthquake records. However, this dependence has not been sufficiently studied to understand its implications for geotechnical soil characterization or even soil response during earthquake shaking. In this direction, we study 1218 earthquake records from the ARGONET
vertical array of accelerographs located on the Island of Cephalonia, Greece.
The data, which are publicly available at https://argonet-kefalonia.org/data/
argonet_data/, cover the period from June 2015 to October 2022, i.e., they are
distributed over more than seven complete hydrological cycles. We apply themethod of seismic interferometry by deconvolution to study the variationsof both VS and P wave velocity values (VP) at different depth intervals corresponding to different station pairs of the vertical array. We compare resultswith satellite soil moisture data from the Soil Moisture Active Passive (SMAP)mission of the National Aeronautics and Space Administration (NASA), andwith data from the European Centre for Medium-Range Weather Forecasts(ECMWF) in the framework of Copernicus Climate Change Service. The
accuracy of the satellite soil moisture data for such a site-specific analysis isverified by comparisons with in-situ data from the meteorological and soil
moisture monitoring stations of the ARGONET infrastructure. Our results
confirm the already known seasonal variation of VS and show a similar pattern for VP, which is inversely correlated with the amount of water in the shallow soil layers. Satellite soil moisture data are found to be highly comparable
to in-situ measurements, which is particularly encouraging for using them tostudy the interactions between meteorological factors and soil response during earthquake shaking not only at regional, but also at local scales.
Seeking for Dependencies of the High-Frequency “Kappa”
Parameter of Earthquake Spectrum on Weather/climate
Conditions
GRENDAS, I., University of Patras, Patras, Greece, grendasioannis@gmail.
com; ROUMELIOTI, Z., University of Patras, Patras, Greece, zroumelioti@
upatras.gr; HOLLENDER, F., French Alternative Energies and Atomic Energy
Commission, Cadarache / Grenoble, France, fabrice.hollender@cea.fr
Nowadays the influence of a site’s surface geological conditions on earthquake ground motion is well known. Several techniques have been proposed
and applied at many sites around the world evaluating their so-called Site
Amplification Factor (SAF), as well as their high frequency decay empiricalfactor, kappa-zero (κ0). SAF and κ0 control the ground motion and its simulation at a site, and they are considered significant for reliable seismic hazard
assessment. Toward understanding the factors that can shape the high-frequency part of the earthquake spectrum, we investigate the existence of seasonal patterns in the variation of the Standard Spectral Ratio (SSR) and delta
kappa (Δκ~Δκ0) of the CK0 surface station of the ARGONET vertical array ofaccelerometers (Cephalonia Island, Greece), installed on top of sedimentarylayers, with respect to the CK83 borehole station, installed in the bedrock at~83m depth. The SSR and Δκ factors have been computed based on acceleration records of 964 earthquakes that have been recorded by the ARGONET
array over a period of ~7.5 years. We detect and quantify the seasonal variation of these two factors, which clearly reflect the similar variation of thecorresponding SAF and κ0 factors of the CK0 station, reasonably consideringthat there is no weather effect at the depth of the reference station. Based on
the SSRs, seasonal variation is clearly observed in the horizontal motion of
CK0, but only in the high frequency range of 17-34Hz. A seasonal patternis also observed in the vertical component of CK0, albeit in the even higher
frequency range of about 40-55Hz. Δκ is subsequently determined at 4 different frequency ranges (fe to fend), for fe=6 and 10 Hz and fend=25 and 35Hz. As
expected, Δκ bears the seasonal variation observed in the SSRs. Our results
confirm the well-known dependence of κ on the frequency range used for its
measurement and suggest that one of the reasons for this dependence, at least

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in soft soils, is the seasonal variation of their response associated with changes
in their water content and possibly other weather/climate related factors.
Beyond Site Response: On the Importance of Installation
Depth on the Quality of Seismic Recordings - Example ofMeasurements Carried Out at Epos-France Seismological
Network Stations
HOLLENDER, F., French Alternative Energies and Atomic Energy
Commission, Saint-Paul-lez-Durance / Grenoble, France, fabrice.
hollender@cea.fr; IACOBUCCI-JUND, H., University of Strasbourg,
Strasbourg, France, helene.jund@unistra.fr; DOUSTE-BACQUÉ, I.,
Université Grenoble Alpes, Grenoble, France, isabelle.douste-bacque@univgrenoble-alpes.fr; RISCHETTE, P., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance / Grenoble, France, pauline.
rischette@cea.fr; BUSCETTI, M., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance / Grenoble, France, margaux.
buscetti@cea.fr; PERRON, V., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance, France, vincent.perron@cea.
fr; TRAVERSA, P., Electricité de France, Aix-en-Provence, France, paola.
traversa@edf.fr; MAUFROY, E., Université Grenoble Alpes, Grenoble, France,
emeline.maufroy@univ-grenoble-alpes.fr
Recording ground motions is essential to estimate the seismic hazard. Signals
from the databases are often considered to be in free-field, i.e. at the natural
surface of the ground, without disturbances due to buildings or neighboring
structures. Nevertheless, analysis of the seismological networks has highlighted the coexistence of numerous installation methods, and in particular the depth of installation (station installed in post-hole, in tunnel, in thebasement of buildings…). We present results obtained at several sites, mainly
Epos-France seismological stations, belonging to the French accelerometric(RAP) and broad-band (RLBP) networks.
At these sites, we set up temporary surface stations placed verticallyabove the deep permanent stations. We then calculated SSR ratios on signal segments corresponding to earthquakes. We observed strong signal deamplifications at certain frequencies due to destructive interference between
upgoing and downgoing waves. These effects are visible at high frequencies
from very shallow depths (sometimes even less than one meter in the caseof soft soils). We discuss the importance of these effects on the use of depthrecorded signals for ground motion parameters and magnitude estimation.
We also draw attention to the disadvantages of using these stations as reference stations if no corrections are made (e.g. as part of the application of thegeneralized inversion method - GIT).
Perturbations of Free-Field Seismic Recordings Caused by
Soil-Structure Interaction, From the Effects of Buildings to
the Impact of Coupling Slabs: Preliminary Results From
Empirical Studies Carried Out in Greece.
RISCHETTE, P., Université Grenoble Alpes, Saint-Paul-lez-Durance /Grenoble, France, pauline.rischette@cea.fr; HOLLENDER, F., Université
Grenoble Alpes, Saint-Paul-lez-Durance / Grenoble, France, fabrice.
hollender@cea.fr; THEODOULIDIS, N., Institute of Engineering Seismology
and Earthquake Engineering, Thessaloniki, Greece, ntheo@itsak.gr;
ROUMELIOTI, Z., University of Patras, Patras, Greece, zroumelioti@upatras.
gr; PERRON, V., CEA DES, DIMP, CADARACHE, Saint-Paul-lez-Durance,
France, vincent.perron@cea.fr; TRAVERSA, P., Electricité de France, Aixen-Provence, France, paola.traversa@edf.fr; MAUFROY, E., Université
Grenoble Alpes, Grenoble, France, emeline.maufroy@univ-grenoble-alpes.
fr; BUSCETTI, M., Université Grenoble Alpes, Saint-Paul-lez-Durance/ Grenoble, France, margaux.buscetti@cea.fr; DOUSTE-BACQUÉ, I.,
Université Grenoble Alpes, Grenoble, France, isabelle.douste-bacque@univgrenoble-alpes.fr; KONIDARIS, A., TEI Ionion Nison, Argostoli, Greece,
agiskonidaris@gmail.com
A proper and reliable measurement of ground motion is essential for an accurate estimate of seismic hazard. Current ground motion databases used todevelop Ground Motion Models (GMM) rarely provide information about
the station housing and sensor installation conditions. Therefore, users often
assume these sensors are installed in free-field condition, i.e. at the natural
surface of the ground without disturbances related to nearby buildings or
structures. Nevertheless, analysis of information collected from seismological networks worldwide has highlighted a large variety of sensor installation modalities, including the housing typology and seismometers coupling.
Recent studies have shown that different installation conditions can have asignificant impact at high frequencies on the recorded motion, in comparison with true free-field measurements. This study focuses on the impact ofsoil-structure interaction at different scales. First, the effect of buildings is

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addressed by analysing ground motion recorded by sets of sensors installedinside and very close to structures hosting several Greek key accelerometerstations, with respect to free-field measurements. Moreover, those buildings
are founded on different types of soil. We observe that the effect of the soilstructure interaction is more significant on soft sites, than on stiff to hard rockones. Second, and at a smaller scale, we investigate the impact of soil-sensor
coupling. To this aim, within the framework of the “ArgoSlab” experiment led
in Argostoli on Kefalonia Island, Greece, about thirty seismometers have been
installed (i) on concrete slabs of different size and shape, (ii) on seismic pillars, (iii) inside manholes, (iv) outdoor or sheltered, and then compared to
free-field stations’ recordings. To provide a reliable interpretation, our process
has been based on both earthquake recordings and ambient noise in each case.
Our results show amplifications (e.g. pillars installations) or deamplifications(e.g. stations in manholes) that can be significantly greater than a factor of 3 atcertain frequencies, depending on the type of installation.
Seismic Station Installations and Their Impact on Recorded
Signals and Derived Quantities
CASTELLARO, S., Università di Bologna, Bologna, Italy, silvia.castellaro@
unibo.it; MUSINU, G., Enser, Faenza, Italy, giuseppe.musinu@enser.it;
ALESSANDRINI, G., Istituto Nazionale di Oceanografia e di Geofisica
Sperimentale, Trieste, Italy, giulia.alessandrini.93@gmail.com
The role of local geology in controlling ground motion has long been acknowledged. Consequently, increasing attention is paid to the assessment of the geophysical properties of the soils at the seismic stations, which impact the station
recordings and a series of related quantities, particularly those referring toseismic hazard estimates and response spectra at low periods.
Not the same level of attention is dedicated to the seismic station installation, to the point that it is generally believed that housings and shelters containing seismic instruments are of no interest, because they can only affectfrequencies well above the engineering range of interest.
Using examples from seismometric and accelerometric stations, we
describe the (1) housing, (2) foundation, and (3) pillar effects on the seismic records. We propose a simple working scheme to identify the existence ofpotential installation-related issues and to assess the frequency fidelity rangeof response of a seismic station to ground motion.
Our scheme is developed mostly on ambient noise recordings and, thus,
surface waves. The hope is that, besides the parameters that start to be routinely introduced in the seismic archives (VS30, soil classes, etc.), the assessment of the maximum reliable frequency, under which no soil–structureinteraction is expected, also becomes a mandatory information.
In our experience, for some installation sites, the maximum reliable frequency can even be less than a very few hertz.
Three Relational Databases in Support of Model
Development for Earthquake Hazard Products
HEARNE, M. G., U.S. Geological Survey, Colorado, USA, mhearne@
usgs.gov; CUNNINGHAM, A. E., U.S. Geological Survey, Colorado, USA,acunningham@usgs.gov; KNODEL, E. J., U.S. Geological Survey, Colorado,
USA, eknodel@usgs.gov; AMBRUZ, N. B., U.S. Geological Survey, Colorado,
USA, nambruz@usgs.gov; AAGAARD, B. T., U.S. Geological Survey,
Colorado, USA, baagaard@usgs.gov; THOMPSON, E. M., U.S. Geological
Survey, Colorado, USA, emthompson@usgs.gov; WORDEN, C. B., U.S.
Geological Survey, Colorado, USA, cbworden@contractor.usgs.gov
The U.S. Geological Survey (USGS)’s hazard products, including ShakeMap
and the National Seismic Hazard Model, fundamentally rely on groundmotion models (GMMs) provided by a broad community of developers.
GMMs are needed for instrumental intensity metrics (IMs), macroseismic
intensities (MI), and the relations that convert between them. The development and use of these models also require explanatory parameters such as
earthquake moment magnitude, focal mechanism, site parameters (such as
the time-averaged shear-wave velocity to 30-meters depth), depths to shearwave velocity horizons, and surface geology. Given the global earthquake
monitoring mission of the USGS National Earthquake Information Center, we
are well positioned to provide many of the data and site parameters describedabove. We operate the “Did You Feel It?” system, which contains millionsof MI records. We also maintain the Advanced National Seismic System
Comprehensive Catalog (ComCat), which contains QuakeML (an Extensible
Markup Language format for earthquake data) summaries of more than 2 million global earthquakes. Finally, our center leads the development of gmprocess, a software package used to process earthquake ground-motion data andgenerate IMs. Querying large numbers of QuakeML records from ComCat
and associating them with IM/MI records is computationally intractable, as
downloading QuakeML for many thousands of records and extracting infor-

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Seismological Research Lettersmation can take many hours. To facilitate the analysis of IMs, we are developing three relational databases for (1) instrumental IMs, (2) MIs, and (3)earthquake catalog data. The schema designs of these databases must capture
all relevant information about each input data set such that users can efficiently access the information necessary to address a broad range of researchand operational goals. By integrating these three databases with sources of siteparameters such as surface geology, our goals are to (1) minimize time spent
by researchers compiling data for engineering seismology studies and (2) optimize the process of model development to better support USGS earthquake
hazard products.
A Magnitude Invariant Workflow for Automated End-toEnd Ground Motion Processing
LAVRENTIADIS, G., California Institute of Technology, California, USA,glavrent@caltech.edu; SHI, Y., California Institute of Technology, California,
USA, yshi5@caltech.edu; ADAY, K., California Institute of Technology,
California, USA, kaday@caltech.edu; ASIMAKI, D., California Institute ofTechnology, California, USA, domniki@caltech.edu
The proliferation of seismic instruments, and associated explosion of groundmotion data, will soon make it possible for ground motion models to computethe seismic hazard at site-specific scales. This exciting possibility, however, ishindered in part by the non-automated processing of ground motion timeseries for engineering applications. In this work, we used recent advancements
in artificial intelligence and operator learning to address this bottleneck. Our
ultimate goal is to develop a magnitude-invariant end-to-end workflow for
automated ground motion processing. Here, we present two components ofthis work: P-wave arrival detection and time series denoising. Our P-wave
arrival detection is based on the recently published algorithm PhaseNO; originally developed for continuous data, our implementation is tailored to strong
motion events, detects the arrival of P-waves with a high degree of accuracy,
and, as such can be used to identify time series with multiple events and evaluate whether they can be separated based on heuristic ground motion intensity
criteria. The time-series denoising step is based on wavelet filter decomposition and short-time Fourier Transforms. Compared to filtering that relies on
subjective criteria of choosing corner frequencies and accordingly limits theusable frequency range, denoising yields a much broader usable frequency
range. Both P-wave arrival detection and denoising algorithms are evaluatedon hybrid datasets of simulated noiseless and noise-contaminated broadband
ground motions. The validated framework is applied to a strong motion dataset of magnitudes 3.0 to 7.1 events recorded between 2011 and 2021 in theWestern United States containing approximately ten million three-component
acceleration time histories. The fully parallel open-source workflow and processed time series will be made available to support ground motion model
development efforts, such as the ongoing project NGA-W3.
Epistemic Uncertainty Associated to Parametric and
Non-Parametric Git Results Related to Initial
Parametrization and Target Region Dataset: Application on
the Epos-France Database.
BUSCETTI, M., French Alternative Energies and Atomic Energy
Commission, Saint-Paul-lez-Durance / Grenoble, France, margaux.buscetti@
cea.fr; TRAVERSA, P., Electricité de France, Aix-en-Provence, France, paola.
traversa@edf.fr; HOLLENDER, F., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance / Grenoble, France, fabrice.
hollender@cea.fr; PERRON, V., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance, France, Vincent.PERRON@
cea.frUnderstanding ground motion behaviour and dependencies is essential for
Seismic Hazard Assessment, and several approaches have been implemented
such as the Generalized Inversion Techniques (GITs). They allow decomposing the Fourier amplitude spectrum of the seismic signal into the three main
contributions of ground-motion: the source, the attenuation and the site
response. However, these techniques rely on several initial assumptions, suchas defining a geographical area where crustal attenuation is considered homogeneous or setting parameters necessary to run the inversions. These choices
are not straightforward and can have non-negligible impact on the results,
particularly in the case of a sparse dataset. Hence, it is necessary to assess
epistemic uncertainty associated to results obtained by such approaches. To
this aim, we perform sensitivity tests for two different GIT algorithms: oneparametric (Grendas et al. 2022), where source and attenuation terms are constrained a priori using physical models, and one non-parametric (Oth et al.
2011), for which the physical models are fitted in post-inversion phase. These
approaches are applied on the Epos-France database (Buscetti et al. in prep)
containing recordings for M_l≥3 earthquakes that occurred in France andwww.srl-online.org•

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neighbouring countries during the 1996-2021 period. First, plural inversions
are performed in the Alps region (area with the largest number of recordings),
where initial parameters vary. The results of these inversions allow us quantifying the epistemic uncertainties related to both, the inversion algorithm andthe inversion parametrization on source parameters (M_w,f_c), attenuation
parameters (Q,γ) and site terms, as well as to identify potential biases related
to some inconsistent parametrizations. In a second step, the most coherent
parametrization is used to perform inversions in different geographical areasof France, in order to discuss uncertainty relative to the chosen region and toillustrate the impact of the amount and quality of available regional data on
the epistemic uncertainties associated to the GIT results.
Ground Motion Models Uncertainties and Variability: The
Impact of Seismic Station Installation Conditions andEarthquake Catalog Quality
TRAVERSA, P., Électricité de France, Aix-en-Provence, France, paola.
traversa@edf.fr; BUSCETTI, M., French Alternative Energies and Atomic
Energy Commission, Saint-Paul-lez-Durance, France, margaux.buscetti@
cea.fr; ARROUCAU, P., Électricité de France, Aix-en-Provence, France,
pierre.arroucau@edf.fr; KOTHA, S. R., Université Grenoble Alpes, Grenoble,
France, sreeram-reddy.kotha@univ-grenoble-alpes.fr; HOLLENDER, F.,
French Alternative Energies and Atomic Energy Commission, Saint-Paullez-Durance, France, fabrice.hollender@cea.fr; RISCHETTE, P., French
Alternative Energies and Atomic Energy Commission, Saint-Paul-lezDurance, France, pauline.rischette@cea.fr; PERRON, V., French Alternative
Energies and Atomic Energy Commission, Saint-Paul-lez-Durance, France,
vincent.perron@cea.fr
In the framework of ground motion and seismic hazard assessment and particularly in low to moderate seismic activity regions, the use of locally recorded
ground motions has recently gained in popularity, for example in adjusting
existing Ground Motion Models (GMM) developed in other regions of theworld or in developing non-ergodic models. However, in low-to-moderate
seismicity regions as continental France, available ground motion recordings
are mostly related to small magnitude earthquakes, for which the information
associated to the earthquake source parameters (3D location and magnitude)
is often affected by large uncertainties. Moreover, information about seismic station installation conditions (housing, type of soil-sensor coupling…)
is most often lacking in ground motion databases worldwide, and groundmotion developers generally assume that sensors are installed in free-field.
In this context, with the objectives of exploring possible biases androbustly characterizing GMM variabilities, this work illustrates the benefit ofboth, accounting for seismic station installation conditions and disposing ofa good quality earthquake catalog in the development of empirical groundmotion models. A simple GMM based on EPOS-France ground motion dataset (Buscetti et al., subm.) is developed exploiting available information on
the sensor installation conditions and using earthquake catalogs of different
quality. The results highlight that a significant portion of the site-related variability in GMMs is related to the impact of the variety of sensor installation
modalities and that inaccuracies in the earthquake catalogs can be responsible
for potential biases in GMMs event-related variability. Accounting for these
metadata allows to improve the characterization of the GMM variability and,overall, to contribute to the improvement of seismic hazard studies accuracy
in low-to-moderate seismicity countries.
Earthquake Ground Motion Insights From the USGS Lake
Almanor, California, Aftershock Nodal Array Deployment
PARKER, G. A., U.S. Geological Survey, California, USA, gparker@usgs.gov;
BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@usgs.gov;
HIRAKAWA, E. T., U.S. Geological Survey, California, USA, ehirakawa@
usgs.gov; CATCHINGS, R. D., U.S. Geological Survey, California, USA,catching@usgs.gov; GOLDMAN, M. R., U.S. Geological Survey, California,
USA, goldman@usgs.gov; CHAN, J. H., U.S. Geological Survey, California,
USA, jchan@usgs.gov; SICKLER, R. R., U.S. Geological Survey, California,
USA, rsickler@usgs.gov
We investigate both source effects, such as rupture directivity, and the effectsof shallow geologic structure on site response, in a ground-motion analysis of aftershocks of the May 11, 2023, M5.5 and May 12, 2023, M5.2 Lake
Almanor, California, earthquakes. The Lake Almanor earthquakes occurred
near the 2013 M5.7 Canyondam earthquake sequence in the vicinity of
Canyon Dam, an embankment dam on the north fork of the Feather River
used for hydroelectricity generation. The 2023 M5.5 and M5.2 earthquakes
both caused MMI 6 shaking and generated over 7000 and 1000 felt reports,
respectively. On May 12, the U.S. Geological Survey deployed 34 nodal seismometers (nodes) around Lake Almanor in an approximately 40 by 25 km

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array that recorded more than 25 M > 2.5 aftershocks over the following 2
months at epicentral distances as small as 5 km and with dense azimuthal
coverage. The nodes recorded continuous 3-component waveforms at a 2-ms
sampling interval, and have been validated against permanent network seismic instrumentation. We use the USGS software gmprocess (Hearn et al.,2019) to perform quality control, apply filters and baseline corrections, andto compute waveform intensity measures (IMs) from the recorded nodal data
and data from regional seismic networks. We compute residuals between aground-motion model and the observed IMs, and then partition them into
components representing repeatable source, path, and site effects. We utilize
the azimuth distribution of stations to investigate rupture directivity effects
and the correlation of path and site effects with the regional geologic structure. We leverage information about path and site effects from the recorded
aftershocks to improve our understanding of the M5.5 and M5.2 earthquakes.
Results from this analysis could be used to improve seismic hazard characterization for infrastructure in the Lake Almanor region.
Ground Motion and Entropy
CLEMENTS, T., U.S. Geological Survey, California, USA, tclements@usgs.
gov; COCHRAN, E., U.S. Geological Survey, California, USA, ecochran@usgs.gov; BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@
usgs.gov; MINSON, S., U.S. Geological Survey, California, USA, sminson@
usgs.gov; YOON, C., U.S. Geological Survey, California, USA, cyoon@usgs.
gov
How ordered is earthquake ground motion? We examine this question
through the framework of entropy, a concept from information theory thatmeasures the uncertainty or disorder in a set of data. For example, a lower
seismic entropy implies a higher certainty of specific ground motion levels
occurring, whereas higher entropy levels could indicate more complex source,
wave propagation, and site effects, leading to increased uncertainty in shaking predictions. Here, we seek to quantify the entropy of both ground motion
phase and amplitude. To do so, we discretize 3-component acceleration waveforms in a spherical coordinate system, where each (East, North, Vertical)
time sample is mapped to a pixel on a sphere of radius norm(E, N, Z). We partition all acceleration waveforms, from a data set containing ~18,000 earthquakes, 1.3 million waveforms, and ~10 billion total samples, recorded by theJapanese National Research Institute for Earth Science and Disaster Resilience(NIED) K-NET and KiK-net networks from 1997–2023, into logarithmicallyspaced amplitude bins and equal-area pixels distributed over a sphere. We
calculate entropy as S = -sum(P * log P), where P(bin) is the probability of aground motion sample (E,N,Z) being in a particular amplitude bin or pixel.
We find that ground motion amplitudes have lower entropy, or more order,
than phases. Physically, this means ground motion amplitudes concentrate atlevels far below the peak ground acceleration, whereas phases more evenly
sample the focal sphere, though we observe peaks in phase angles near +-90
and 0 degrees polarity, coinciding with expected polarities of P-waves andS-waves, respectively. Our entropy calculations could aid in the generation ofrealistic ground motions, especially for the challenging problem of simulating
physical high-frequencies.
Comparisons of Recent Prediction Models of GroundMotion and Seismic Duration for Mexican Interplate andIntraslab Earthquakes Including the Vertical Component
and V/H RatiosGARCÍA-SOTO, A., Universidad de Guanajuato, Guanajuato, Mexico,adgarcia@ugto.mx; JAIMES, M., National Autonomous University of Mexico,
UNAM, Mexico City, Mexico, mjaimest@iingen.unam.mx
Ground motion prediction equations (GMPEs) are a key part of seismic engineering, since the peak ground accelerations (PGA), peak ground velocities(PGV) and spectral pseudoaccelerations (SA) are used to determine seismic
intensities that engineering structures are expected to be subjected to undercertain seismic scenarios. They are also employed for the so-called probabilistic seismic hazard assessment (PSHA) and are the basis of some provisions
contained within seismic design codes. Predictive ground-motion duration
models are not as common, although seismic duration is also a very relevant
parameter to designing structural systems under seismic excitations. GMPEs
and ground-motion duration models can be developed for the horizontal
component, traditionally considered the most critical one in terms of seismic
demands imposed to buildings, infrastructure and other engineering structures. However, recent literature points out the need for seismic prediction
models for the vertical component, including the relation between seismic
intensities from the vertical component and the horizontal component (V/H
ratios). Recent GMPEs and duration models of the horizontal and verticalcomponents of ground-motion for Mexico, based on updated databases which

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include great earthquakes as the date coincidental 19 September 1985 and2017 seismic events, are compiled and compared in this study. It is concluded
that GMPEs and ground-motion duration models should be region-, mechanism-, site- and component-specific to be adequate for seismic engineering
purposes. Salient findings of all the considered models are highlighted.
Using Proxies Obtained From Horizontal-to-Vertical
Spectral Ratio to Reduce the Epistemic Uncertainty in
Ground Motion Models
YAZDI, M., Mott MacDonald, Washington, USA, mohammad.yazdi20@
gmail.com; ANDERSON, J. G., University of Nevada, Reno, Nevada, USA,jga.seismo@gmail.com; MOTAMED, R., University of Nevada, Reno, Nevada,USA, motamed@unr.edu
The effects of site characteristics in ground motion models (GMMs) are usually predicted by shear-wave velocity of top 30 m (VS30) or depth to 1.0 km/s
shear-wave isosurface (Z1.0). However, these parameters are limited to observations of the top 30m of the soil stratigraphy or inferred from models, respectively. Previous research showed that the horizontal-to-vertical spectral ratio(HVSR) technique can be used to estimate site fundamental frequency and its
corresponding amplitude, which can, in turn, reduce uncertainties in GMMs.
This study uses a large data set from the KiK-net strong motion network andpresents a maximum-likelihood estimate of site fundamental frequency (fml)
and its corresponding amplitude (Aml) for 699 sites across Japan. First, groundmotion recordings are selected and processed. The Fourier Amplitude Spectra
and Response Spectra of the recordings are computed in this step. Second, the
HVSR is calculated for the recordings. Then, fml and Aml are estimated foreach site using previously developed methodology that is based on maximumlikelihood approach. The process of estimation is automated to diminish bias
and quantify the uncertainty in the estimations. As a result, the estimatedparameters (site fundamental frequency and the corresponding amplitude in
the HVSR curve) are compared to an independent study in order to validate
the automated approach and the maps for these parameters are presented.
These additional parameters reduce the uncertainty (i.e., site-to-site variability) in estimates of response spectra by 2% to 19%, depending on the spectral
period and the GMM used as a reference.
Are Ground Motions Different for Aftershocks or
Earthquakes Doublets?
BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@usgs.gov;
PARKER, G. A., U.S. Geological Survey, California, USA, gparker@usgs.gov;
ABRAHAMSON, N. A., University of California, Berkeley, California, USA,abrahamson@berkeley.edu; HANKS, T. C., U.S. Geological Survey, California,
USA, thanks@usgs.gov
As seismic hazard analysis moves away from the Poisson assumption, there isa need for ground-motion models for dependent events. We revisit the question of whether ground motion levels are systematically different between
mainshocks, aftershocks, and earthquake doublets. Differing ground motion
could imply inherently different source processes or interactions and isimportant for hazard and risk analyses. This question lingers, in part, due
to how an aftershock is defined: in the NGA-West2 project, on-fault aftershocks, close in space and time to a corresponding mainshock, were singled
out. Previous studies have shown that high-frequency ground motion (e.g.,
Abrahamson et al., 2014) and stress drop (e.g., Baltay et al., 2019) for theseaftershocks is about 35% lower than mainshocks. This could be attributed to
on-fault aftershocks re-rupturing weakened patches on the mainshock fault
plane, and thus less efficiently generating high-frequency radiation. On theother hand, Abrahamson et al. (2014) found that ground motion for longer
periods is larger for aftershocks, with the physical explanation outstanding.
We reevaluate these observations using recent stress-drop estimates andground-motion observations over a range of periods, for the 2019 Ridgecrest
sequence, the 2023 Turkiye sequence, and the NGA-West3 database, keeping
the same aftershock definition as in NGA-W2. The M6.4 and M7.1 Ridgecrest,
and M7.8 and M7.5 Turkiye doublets show no relative difference in groundmotion between each of the two main events at any period, implying thatinteractions between these doublet events do not affect their generated groundshaking, and thus we should continue to treat them as independent eventsin ground-motion modeling. While smaller high-frequency ground motion
for aftershocks is good news, it is important to consider these systematic disparities when developing non-ergodic ground-motion models from data that
includes many aftershocks. If on-fault aftershocks truly have different source
physics, giving rise to depleted or enhanced ground motion, this sheds lightinto stress interactions and fault asperities.

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Why Did the Pulse-Like Ground-Motion Differ Three Timesin Pgv and Tp Within a 3 Km Wide Near-Fault Region of the2023 Mw 7.8 Turkiye Earthquake?
HUANG, J., National Center for Research on Earthquake Engineering,Taipei, Taiwan, jyhuang@narlabs.org.tw; SUNG, C., University of California,
Berkeley, , USA, karensung@berkeley.edu; KUO, C., National Central
University, Taoyuan, Taiwan, chkuo@ncu.edu.tw; LIN, C., National Center for
Research on Earthquake Engineering, Taipei, Taiwan, cmlin@narlabs.org.tw
Over 25 pulse-like velocity (VP) waveforms were observed in the near-fault
region of the 2023 Turkiye Mw 7.8 earthquake, which were extracted by Shahi
and Baker’s (2014) method. The extracted pulse-like ground motions have apeak ground velocity (PGV) and pulse period (Tp) range of 25 to 184.2 cm/s
and 1.8 to 15.6 s, respectively, which were in a distance range of rupture distance (Rrup) within 0.33 to 54 km. Significant intensity differences in the VP
were observed at three stations within a 3 km wide near-fault region, Antakya,
one of the major disaster regions, and observed as the second-largest PGV ofthe extracted VPs. The Rrup of the three stations is 0.33, 2.1, and 3.5 km forstation codes 3126, 3123, and 3131, respectively. However, the corresponding extracted PGV and Tp showed a two- to three-times difference within
the three stations from PGV of 119.9, 175.4, and 60.3 cm/s and Tp of 3.4, 2.6,
and 13.2 s. This is difficult to explain by the median prediction of the modern
nonergodic ground motion models. In this study, by removing a possible causefrom the coseismic static offset (fling step), the directivity pulse is evaluated by
the velocity-pulse simulation procedure (Huang et al., 2024), which is derived
from the stochastic finite-fault ground-motion simulation method, a baseline
correction method, and a fling-step removal model. The result indicated thatthe directivity pulse provides a 50 to 60 cm/s PGV, which was recorded by therock site 3131 and enlarged two times from linear site response and recordedby the softest soil site 3126. The three times PGV observed at 3123 was generated by simultaneously linear site response and a super shear behavior at thenear-source portion. The closest station, 3126, did not suffer the highest PGVin this region because of the soil nonlinearity in the latter portion of the S
arrival. Finally, the longest 13.2 s Tp is caused by a 130 cm coseismic deformation from the fling-step, which occurred after the VP arrival and did not show
an apparent longer period in the other two stations.

From Earthquake Recordings to Empirical GroundMotion Modelling [Poster Session]
Poster Session • Thursday 2 May
Conveners: Carlo Cauzzi, ORFEUS, Swiss Seismological
Service, ETH Zürich (carlo.cauzzi@sed.ethz.ch); Fabrice
Hollender, CEA Cadarache (fabrice.hollender@cea.fr);
Vincent Perron, CEA Cadarache (vincent.perron@cea.fr);
Zafeiria Roumelioti, University of Patras (zroumelioti@
upatras.gr); Paola Traversa, Electricite de France (paola.
traversa@edf.fr)
poster 154
Frequency-Dependent Transfer Functions for Hydroseisms
in Devils HoleBONNER, J. L., Desert Research Institute, Texas, USA, jesse.bonner@dri.edu;
SYMONS, N., Desert Research Institute, New Mexico, USA, Neill.Symons@
dri.edu; RUSSELL, C., Desert Research Institute, Nevada, USA, Chuck.
Russell@dri.edu
Devils Hole is a highly sensitive aquifer system situated in southern Nevadathat exhibits notable water level variations, referred to as seiches or hydroseisms, in response to significant seismic events worldwide. This study investigates the dynamic response of seiches in Devils Hole to ground displacement
triggered by large earthquakes and aims to characterize the frequency-dependent transfer function governing the relationship between ground displacement and water level changes. We conducted a comparative analysis using
USGS water level measurements recorded at a frequency of 0.2 Hz frommultiple large seismic events that occurred between 2020 and 2021. These
measurements were juxtaposed with long-period, three-component seismic
data obtained from nearby seismic stations in Furnace Creek and Shoshone,
California. Our analysis reveals that the hydroseismic activity is predominantly impervious to Love wave ground motion but is significantly influenced
by Rayleigh wave motions, as well as subsequent wave reflections and refractions off the interior walls of Devils Hole.

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We used a multi-filter analysis to derive Rayleigh wave dispersion curves
from the water level data. We also applied spectral analysis techniques to discern the frequency characteristics of both ground motion and seiche signals.
Preliminary findings suggest a repeatable frequency-dependent relationshipbetween ground displacement and water level fluctuations in Devils Hole. For
example, in the case of a 20-second Rayleigh wave with a 1 cm displacement,
we observed a 20-second period of hydroseisms with an approximate displacement of 25 ± 10 cm. As the periods decrease below 20 seconds, hydroseism
reflections from the interior walls of Devils Hole assume greater prominencein the signals, resulting in extended wave trains for water level fluctuations
compared to the seismic Rayleigh waves. These outcomes contribute significantly to our understanding of aquifer response to seismic events. Ongoing
research efforts include refining the transfer function analysis and further
deepening our understanding of this captivating natural phenomenon.
poster 155
High Frequency Seismic Waves of Normal and Leaky Modes
Excited by Heavy Trains
FENG, X., Southern University of Science and Technology, Shenzhen,
China, fengxp@sustech.edu.cn; LI, Z., Southern University of Science andTechnology, Shenzhen, China, lizb@sustech.edu.cn; CHEN, X., Southern
University of Science and Technology, Shenzhen, China, chenxf@sustech.edu.
cn
Ambient seismic noise tomography has far-reaching applications from shallow sub-surface, regional, continental to global imaging scales over the past
two decades. Recently, some individuals have successfully extracted both normal-mode and leaky-mode dispersion curves from high frequency seismic
ambient noise recorded by dense seismic arrays using the frequency-Bessel(F-J) transform. These findings obtain more reliable Vs and Vp models by
simultaneously fitting these two types of dispersion data, since normal-mode
dispersion curves are more sensitive to Vs than Vp while leaky-mode dispersion curves are opposite. The influence factors, like the excitation sources andseismic velocity model, however, are not analyzed systematically in previous
researches. Here we collect ambient noise recordings from a two-km long
linear-shape seismic array laying along a railway track in New Mexico, theUnited States of America to process for obtaining hourly high-quality dispersion data by the F-J transform array stacking technique. We show that there
is a strong positive correlation between the signal to noise ratios of dispersion
curves of normal and leaky modes and the train traffic volume. This result
tells us that we need to make full use of seismic noise generated by trains oreven trucks to investigate the subsurface Vs and Vp structure utilizing dispersion data of normal and leaky modes, facilitating new findings for civilengineering.
poster 156
Progress on the Characterization of Epos-France
Accelerometric (Rap) and Broad-Band (Rlpb) Network
Station: Focus on Implemented Methodologies
HOLLENDER, F., CEA DES, DIMP, CADARACHE / UGA, ISTerre, SaintPaul-lez-Durance / Grenoble, France, fabrice.hollender@cea.fr; BURLOT,
R., UGA, ISTerre, Grenoble, France, remy.burlot@univ-grenoble-alpes.fr;
RISCHETTE, P., CEA DES, DIMP, CADARACHE / UGA, ISTerre, SaintPaul-lez-Durance / Grenoble, France, pauline.rischette@cea.fr; DOUSTEBACQUÉ, I., UGA, ISTerre, Grenoble, France, isabelle.douste-bacque@univgrenoble-alpes.fr; WATHELET, M., UGA, ISTerre, Grenoble, France, marc.
wathelet@univ-grenoble-alpes.fr; CORNOU, C., UGA, ISTerre, Grenoble,
France, cecile.cornou@univ-grenoble-alpes.fr; PERRON, V., CEA DES,
DIMP, CADARACHE, Saint-Paul-lez-Durance, France, vincent.perron@cea.
fr; MAUFROY, E., UGA, ISTerre, Grenoble, France, emeline.maufroy@univgrenoble-alpes.fr
The characterization of seismological stations, whether they are broad-bandor strong-motion, is essential for a better use of the databases. In particular, it involves determining several important proxies (such as the value ofVS30) or a complete velocity profile of S-wave propagation to the geophysicalbedrock. We present the progress in the station characterizations carried out
on the French seismological networks (RAP and RLBP), both in mainland
France and the French West Indies. In addition to the results obtained, we
present the acquisition geometries selected and the data processing applied,which is essentially based on MASW measurements to determine the dispersion curves of surface waves at high frequencies, and on FK-type processing
applied to passive array data for intermediate and low frequencies.
Our acquisitions do not limit themselves to targeting a depth of investigation of 30 m for the sole purpose of determining the VS30 parameter. In

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most cases, the use of large array apertures (several hundreds of meters) let us
characterize the depth and Vs of the seismological bedrock.
We also comment on the real improvements made possible by threecomponent FK approaches (e.g. RTBF, ARDS, ARTBF) proposed by Wathelet
et al. (2018, 2024), compared with more conventional approaches (e.g. HRFK).
poster 157
Separation of Intrinsic and Scattering Seismic Wave
Attenuation in the Crust of Central and South-Central
AlaskaMAHANAMA, A., University of Memphis, Tennessee, USA, mahanama@memphis.edu; CRAMER, C. H., University of Memphis, Tennessee, USA,
ccramer@memphis.edu; GABRIELLI, S., National Institute of Geophysics andVolcanology, Palermo, Italy, simona.gabrielli@ingv.it; AKINCI, A., National
Institute of Geophysics and Volcanology, Palermo, Italy, aybige.akinci@ingv.it
Conducting a thorough analysis of seismic hazards is essential for evaluating the potential impact of earthquakes on both structural damage and lossof life in a given area, especially in regions like Alaska, known for frequent
seismic activity. The precision of seismic hazard evaluations relies heavily on
the dependability of ground motion prediction equations, which forecast the
anticipated ground shaking at specific locations. However, in areas with notable disparities in crustal attenuation, such as Alaska, the reliability of theseequations may be compromised. The average Lg Q in Alaska significantly surpasses that in the western U.S. and Canada, influencing seismic hazard assessments by affecting the magnitude and duration of ground shaking. Failing toconsider these regional variations in crustal attenuation can lead to inaccurate
hazard assessments.
To gain a deeper understanding of the underlying factors contributing tothis issue, this research proposes the application of Coda Q analysis to investigate the roles of scattering and intrinsic crustal attenuation in central andsouth-central Alaska. The investigation will specifically target earthquakes
with magnitudes ranging from 2 to 6.5, occurring within an epicentral distance of 20km to 200km between December 2014 and December 2020, withfocal depths of less than 30km. Utilizing the Multiple Lapse Time Window(MLTW) method with the center frequencies ranging from 0.75 to 12.0 Hz,
the study aims to distinguish between intrinsic and scattering crustal attenuation by analyzing seismic energy in three-time windows: 0-15 s, 15-30 s, and30-45 s, measured from the S arrival. By analyzing the regionalized valuesof intrinsic and scattering attenuation and their frequency dependencies, thestudy aims to interpret the causes for regional variations of crustal attenuation of central and south-central Alaska. This understanding can potentiallyenhance geological and tectonic interpretations, ultimately leading to therefinement of ground-motion prediction equations applicable in seismic hazard assessments.
poster 158
How Can Shaking Observations From the MyShake
Smartphone Platform Inform Free-Field Ground Motion
Residual Estimates?
MARCOU, S., University of California, Berkeley, California, USA, savvas.
marcou@berkeley.edu; ALLEN, R. M., University of California, Berkeley,
California, USA, rallen@berkeley.edu
Ground motion spatial variability can be significant, especially in shortperiod intensity measure metrics such as pseudo-spectral acceleration (PSA)at periods <1s and peak ground acceleration (PGA). As such, densifying data
coverage could potentially reveal finer-level detail when modeling spatial
distributions of ground shaking in individual events, as well as in ensemble
empirical site response modeling. Acceleration waveforms recorded via
the MyShake smartphone app provide one such dataset. MyShake has beendelivering ShakeAlert earthquake early warning messages to the public since
October 2019. It also provides recorded waveforms using the onboard accelerometer once triggered. This capability has enabled us to construct a waveform
database that heavily samples the near-field (epicentral distances <30 km)
for M3-5 events. Using MyShake data in California from 2019 to early 2023,
we derive predictive models for smartphone-recorded peak accelerations,
including one incorporating simple building corrections. Using our models,
we calculate MyShake within-event residuals, and compare these to free-field
residuals for PGA and 0.3 s PSA. We illustrate how these residuals illuminate small-scale structure in ground motion spatial trends in these, while also
matching with independent empirical constraints of free-field site response.
Finally, we discuss how MyShake residual correlation with free-field residuals
could be used to reduce modeling uncertainties in schemes that model spatial
distribution of ground shaking, such as ShakeMap.

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poster 159
Estimating Hazard From Crustal Sources: An Empirical
Observation ApproachMARTÍNEZ-JARAMILLO, D., Universidad Nacional Autónoma de México,
Querétaro, Mexico, danmartinezjar@geociencias.unam.mx; ZÚÑIGA
DÁVILA-MADRID, F., Universidad Nacional Autónoma de México,
Querétaro, Mexico, ramon@geociencias.unam.mx; KOTHA, S., Universitè
Grenoble Alpes, Grenoble, France, reddy.kotha@univ-grenoble-alpes.fr
This study aims to estimate ground motion near the source. This estimation
depends, at the very least, on factors such as the rupture type, the specificpath of propagation, and site parameters. We employ an empirical approachbased on the analysis of the Near Source Strong Motion database (NESS 2.0)
(Sgobba et al., 2021). The empirical approach involves interpreting and plausibly estimating the main characteristics influencing rupture, which significantly modifies ground motions across various spectral periods in the nearsource. We estimate and compare Ground Motion Models (GMM) with intensity real data obtained from various tectonic regions and earthquake sources,
assessing their residuals. Our analysis is structured into two parts. The firstpart focuses on individual parameters in each GMM for events with similar
slip-rupture conditions. The second part involves a nested-residuals analysis,
which can be initially divided into terms capturing effects not parametrized
by GMMs.
The directivity effect causes shear-wave energy from all points on thefault to arrive at nearly the same time at the station in the direction of the
rupture’s propagation. Similarly, rupture velocity increases ground motion as
the radiation for each point into the fault occurs faster, arriving at the station
in a shorter time interval (Aagard et al., 2001). The significance of hypocentral depth lies in its control over the radiation pattern (Dujardin et al., 2021).
Additionally, the depth of the top of the rupture influences slip behavior; as
it deepens, fewer slips (shaking) occur in the softer surface material of themedia (Aagard et al., 2001). Conversely, seismogenic depth determines thepotential area involved in the rupture, as significant earthquakes (greater than~6) typically nucleate at the base of the seismogenic layer, rupturing the entire
seismogenic crust in depth (Scholz, 2019). This influence extends to the earthquake size.
poster 160
Multi-Resolution Basin Terms for Ground Motion Models inCentral and Eastern North America
MEYER, E. H., Tufts University, Massachusetts, USA, elise.meyer@tufts.
edu; DIOSLAKI, A., Merrimack College, Massachusetts, USA, dioslakia@
merrimack.edu; NIE, S., Tufts University, Massachusetts, USA, shiying.nie@
tufts.edu; ZHAN, W., University of Central Florida, Florida, USA, weiwei.
zhan@ucf.edu; KAKLAMANOS, J., Merrimack College, Massachusetts, USA,
KaklamanosJ@merrimack.edu; BAISE, L. G., Tufts University, Massachusetts,
USA, Laurie.Baise@tufts.edu
Current ground motion models (GMMs) in Central and Eastern North
America (CENA) rely on the time-averaged shear-wave velocity in the upper
30 m of the site (VS30) as the primary site variable. Prior to recent publications (Boyd et al., 2023), sediment thickness and basin terms have not been
consistently available in CENA. In recent years, CENA has seen an increase in
the volume and resolution of ground motion datasets including recently published datasets like the Central and Eastern U.S. Earthquake Ground Motion
Database: 2010 to 2020 (Thompson et al. 2023) which builds on previously
published ground motion data such as NGA-East (Goulet et al, 2014). At thesame time, new geologic, and geotechnical datasets such as and the Atlantic
and Gulf Coastal Plains Sediment Thickness model (Boyd et al., 2023) andthe UCLA Shear-wave Velocity Database (Kwak et al., 2021) have also beendeveloped. The goal of this work is to integrate these datasets along with additional geospatial datasets to define a set of multi-resolution basin and site
effect terms for use in CENA for ground motion modeling. By integratingthese datasets, as well as other geospatial variables including basin geomorphology and geology, we gain a better understanding of path and site effects in
CENA, with a specific focus on observed and simulated basin amplification of
long-period ground motions (T > 1 s). The proposed multi-resolution basinterms combine surficial geology, geomorphologic basin classifications, sediment thickness data, hydrologic data, and geotechnical data, to create a spatially continuous basin term for use in GMMS in CENA. Linear mixed-effects
regression will be used to decompose GMM residuals to investigate complex
basin, site, region, and geology effects in CENA using the dataset, with a goalof reducing epistemic uncertainty in future CENA ground motion prediction.

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Seismological Research Lettersposter 161
The Effect of Short Wavelength Topography on Seismic
Recordings: Results of Experiments Conducted on
Kefalonia Island in Greece.
RISCHETTE, P., French Alternative Energies and Atomic Energy
Commission, Saint-Paul-lez-Durance / Grenoble, France, pauline.
rischette@cea.fr; HOLLENDER, F., French Alternative Energies andAtomic Energy Commission, Saint-Paul-lez-Durance / Grenoble, France,
fabrice.hollender@cea.fr; THEODOULIDIS, N., Institute of Engineering
Seismology and Earthquake Engineering, Thessaloniki, Greece, ntheo@itsak.
gr; ROUMELIOTI, Z., University of Patras, Patras, Greece, zroumelioti@
upatras.gr; PERRON, V., French Alternative Energies and Atomic Energy
Commission, Saint-Paul-lez-Durance, France, vincent.perron@cea.fr;
TRAVERSA, P., Electricité de France, Aix-en-Provence, France, paola.
traversa@edf.fr; MAUFROY, E., Université Grenoble Alpes, Grenoble,
France, emeline.maufroy@univ-grenoble-alpes.fr; BUSCETTI, M., French
Alternative Energies and Atomic Energy Commission, Saint-Paul-lezDurance / Grenoble, France, margaux.buscetti@cea.fr; DOUSTE-BACQUÉ,I., Université Grenoble Alpes, Grenoble, France, isabelle.douste-bacque@univ-grenoble-alpes.fr; KONIDARIS, A., TEI Ionion Nison, Argostoli,
Greece, agiskonidaris@gmail.com
In recent years, seismological networks around the world have been considerably expanded, enabling the creation of databases with a rising number ofearthquakes. Nevertheless, the description of the installation conditions ofseismological stations are often missing from the networks metadata. In mostcases, Ground Motion Models (GMMs) developers assume that these stations
are in free-field conditions, i.e. located at the natural surface of the groundwithout nearby disturbing structures. However, the investigation of seismological networks has revealed the coexistence of many different installation
methods, including, for instance the coupling of seismometers, housing of
permanent stations, or the installation of some stations at the foot of a scarp.
Recent studies have also shown that these installation conditions can havea significant impact on the recorded motion, compared with true free-fieldmeasurements. Among these various installation methods, this study takes
a particular interest in the effect of topography at short wavelengths. To thisend, an experiment has been conducted on Krani Hill on Kefalonia Island in
Greece. Ground motion recorded at sensors installed along a profile goingfrom the foot to the top of a cliff of about twenty meters high, are comparedamong them and with respect to a reference site. Other seismometers havebeen set up along the cliff, top and bottom, to analyze a potential polarization effect. Recordings of earthquakes and ambient noise have been studied
to provide the most possibly comprehensive analysis. The results show a slight
amplification of the signal at the top of the cliff and a clear de-amplification at
its foot. The clearest effect is a marked polarization of the signal near the scarp.
poster 162
Geospatial Variable Based Site Terms for Nonergodic
Ground Motion Models
ROBERTS, M. E., Tufts University, Massachusetts, USA, maggie.roberts@
tufts.edu; GASKINS BAISE, L., Tufts University, Massachusetts, USA, laurie.
baise@tufts.edu; KAKLAMANOS, J., Merrimack College, Massachusetts,
USA, kaklamanosj@merrimack.edu; ZHAN, W., University of Central
Florida, Florida, USA, Weiwei.Zhan@ucf.edu; NIE, S., Tufts University,
Massachusetts, USA, shiying.nie@tufts.edu
This work presents a non-ergodic site response model for California for use
with the Boore, Stewart, Seyhan, and Atkinson (2014) (BSSA14) groundmotion model (GMM), using geospatial variables. Geospatial variables suchas elevation, water table depth, soil thickness, and distance to the coast havebeen found to capture the spatial pattern of geologic deposits (Wald andAllen, 2007; Zhu et al., 2015), and have been used to develop geospatial liquefaction models (Zhu et al., 2015; 2017). At the same time, ground motion
databases have grown in recent years, making it possible to better capture
the complexity of site effects spatially, and as a result, quantify the repeatable effects that local surface geology has on ground motion intensity. This
project uses the DesignSafe Ground Motion database (Ji et al., 2022) for thestate of California, containing over 57,000 ground motion recordings pairedwith geospatial variables as additional site terms beyond Z1.0 and VS30 (e.g.
elevation, depth to water, soil thickness, surficial geology). Ground motion
residuals are calculated for the database between the observed peak groundaccelerations (PGA) and the BSSA14 predicted PGAs, which uses VS30 as theprimary site response parameter. Mixed effects regression is performed on
the residuals using geospatial explanatory variables to partition the residual,
in order to produce updated site terms that account for the corresponding
influence of the geospatial variables. The developed non-ergodic geospatial

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site terms result in a reduction in inter-site residual variability for PGA values,
when compared to the conventional VS30 based site terms. The development of
a non-ergodic site term for use in California using geospatial variables highlights the predictive power of geospatial data and accounts for its impact on
ground motion intensity.
poster 163
NGA-Subduction Region-Specific Ground Motion Models
Using Machine Learning Algorithms
SEDAGHATI, F., AON, Illinois, USA, farhad.sedaghati@aon.com; PEZESHK,S., University of Memphis, Tennessee, USA, spezeshk@memphis.edu
In this study, we derive data-driven ground motion models (GMMs) on a
global scale and region-specific basis for subduction earthquakes. We employ aweighted average ensemble model that combines four distinct nonparametricsupervised machine learning algorithms: Artificial Neural Network, KernelRidge Regressor, Random Forest Regressor, and Support Vector Regressor. To
accomplish this, individual models are trained using a subset of the NGA-Sub
dataset, comprising 9,559 recordings from 153 interface and intraslab earthquakes recorded at 3,202 different stations. Hyperparameter optimization iscarried out through a grid search for each model. Subsequently, the four models are combined using an equal-weighted average ensemble approach, leveraging ensemble modeling to capitalize on the strengths of diverse machinelearning algorithms and mitigate their respective weaknesses. The ensemble
model incorporates moment magnitude, rupture distance, VS30, ZTOR, tectonic, and regional parameters as input variables. GMMs predict horizontal
component ground motion intensity measures, including PGD, PGV, PGA,
and 5%-damped PSA values at spectral periods ranging from 0.01 to 10 seconds in a logarithmic scale. While no specific functional form is defined, theresponse spectra, as well as the scaling trends for distance and magnitude in
the weighted average ensemble model, are consistent and comparable to theother NGA-Sub GMMs, but with slightly lower standard deviations.
To analyze variability, a mixed effects regression is employed to partition
total aleatory variability into between-event, between-station, and event-sitecorrected components. The resulting global GMMs are applicable to interface
earthquakes with magnitudes ranging from M4.9 to M9.12, rupture distancesfrom 14 to 1,000 km, and ZTOR values up to 47 km for sites with VS30 values
between 95 and 2,230 m/sec. For intraslab events, the global GMMs are applicable to magnitudes ranging from M4.0 to M8.0, rupture distances from 28
to 1,000 km, and ZTOR values from 30 to 200 km for sites with VS30 values
between 95 and 2,100 m/sec.
poster 164
Ground Motion Models Using Machine Learning
Techniques Based on the NGA-West2 Data
SEDAGHATI, F., AON, Illinois, USA, farhad.sedaghati@aon.com; PEZESHK,S., University of Memphis, Tennessee, USA, spezeshk@memphis.edu
In this study, we derive ground motion models (GMMs) for the average horizontal component resulting from shallow crustal continental earthquakesin active tectonic regions by analyzing a subset of the NGA-West2 dataset.
This subset encompasses 14,518 recordings from 285 earthquakes recorded
at 2,347 different stations. Constructing these models involves employing four nonparametric supervised machine learning (ML) algorithms: theArtificial Neural Network, Kernel-Ridge Regressor, Random Forest Regressor,
and Support Vector Regressor, each producing an individual model. Then, aweighted average ensemble approach is employed to merge these four models
into a robust unified model for predicting various ground motion intensity
measures, including peak ground displacement, peak ground velocity, peakground acceleration, and 5%-damped pseudo-spectral acceleration. The
model incorporates moment magnitude, rupture distance, VS30, and ZTOR as
input parameters.
The ensemble modeling strategy seeks to reduce drawbacks or deficiencies inherent in different ML algorithms while leveraging their advantages,
and thus, addressing epistemic uncertainty. Despite the absence of a predefined functional form, the model effectively captures prominent features
observed in ground motions, such as saturation, geometrical spreading,anelastic attenuation, and nonlinear site amplification. The response spectraand scaling trends related to magnitude, distance, VS30, and ZTOR are consistent and comparable with the NGA-West2 GMMs, which include several
additional input parameters. A mixed-effects regression analysis is applied
to divide the total aleatory uncertainty into between-event, within-station,and event-site-corrected components. The model applies to earthquakes withmagnitudes ranging from 3.0 to 8.0, rupture distances extending up to 300
km, and spectral periods spanning from 0 to 10 seconds.

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poster 165
Developing a Hybrid Ground-Motion Modeling Framework
for the Himalayan Region of India
SHARMA, S., Indian Institute of Technology Gandhinagar, Gandhinagar,
India, sharmashikha494@gmail.com
In addressing the challenge of ground-motion modeling in the Indian context,
where unavailability of recorded ground-motion data for the scenarios that
dominate hazards across the major urban centers within the Indo-Gangetic
plains is scarce, it poses a significant challenge. To overcome this limitation,
conventional practice involves the utilization of ground-motion models(GMMs) calibrated on data from regions like California and Japan. To mitigate this issue, we develop a hybrid ground-motion modeling framework inwhich adjustments in global GMMs are performed to account for the differences in seismological characteristics such as anelastic attenuation and stressdrop. Initially, we employ a strong-motion dataset from small-to-moderatemagnitude events to derive seismological parameters aligned with the tectonic
conditions of the study area (northern part of India). This involves a generalized inversion of Fourier spectral ordinates for the study region. In the next
step, these parameters are adjusted with the magnitude and distance scaling of
the global GMMs in the Fourier spectral domain. The adjusted Fourier spectra are then converted to response spectral ordinates using random vibration
theory. Our analysis is based on a recently compiled and uniformly processedstrong-motion dataset for the Himalayan region, comprising approximately
190 earthquake events with 798 records, where moment magnitudes (Mw)exceed 3 and recorded distances (REpi) less than 500 km. To illustrate theeffectiveness of our proposed framework, we demonstrate its application
using a host GMM (calibrated on the NGA-West2 database) for Fourier spectral ordinates (Bora et al., 2019). For comparative purposes, we also incorporate a response spectral GMM (Chiou and Youngs, 2014) into our study.
poster 166
Domain Confusion in Dispersions Picking Based on Neural
Network and the Learning Features From Dispersion
Spectrograms
SONG, W., Southern University of Science and Technology, Shenzhen, China,
11930823@mail.sustech.edu.cn; CHEN, X., Southern University of Scienceand Technology, Shenzhen, China, chenxf@sustech.edu.cn
Ambient noise tomography has been widely used to obtain the shear-wave
velocity for underground structure of the Earth, and there is a key point in dispersion spectrogram where people need to pick dispersion curves manually.
By the frequency-Bessel (F-J) transform, the dispersion spectrogram not only
provides reliable fundamental dispersion curve, but also rich higher modesof dispersion curves. However, manual picking will consume much time andenergy for researchers. Consequently, using neural network to pick dispersions automatically has great significance. In the field of computer vision, thefeature of data from different source domains has a certain degree of difference. If we ignore these differences in the data, the trained neural network
will have an issue of data limitation, and the performance will be weak. By
analyzing lots of dispersion spectrograms, we have summarized the learningfeatures of neural network from spectrograms. In addition, based on our findings we have applied domain confusion in training and testing neural network. After domain confusion, we can make one neural network learn dispersion spectrograms from multi sources, and its performance is stronger than
before. The trained neural network can effectively process large number oftest data and help us easily obtain more dispersion curves automatically. The
proposed study can provide a deep insight into the denoising of dispersion
spectrograms by neural network.
poster 167
Monitoring Temporal Velocity Variations of Shallow
Subsurface and Engineering Structures Using 6c SingleStation Measurement
YUAN, S., Colorado School of Mines, Colorado, USA, syuan@mines.edu;
MARTIN, E., Colorado School of Mines, Virginia, USA, eileenrmartin@
mines.edu; BERNAUER, F., Ludwig-Maximilians-Universität München,
Munich, Germany, felix.bernauer@lmu.de
Monitoring seismic velocity variations offers valuable insights into near-surface processes like soil compaction and groundwater changes, aiding environmental studies. In engineering, these variations can indicate structural damage in buildings, bridges, dams, and tunnels. Continuous monitoring helps
identify potential risks, enabling preventive maintenance and ensuring safety
and resilience of structures. In this study, we propose a six-component (6C)
single-station measurement. The proposed method relies on the joint analysis

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of translational and rotational ground motion recordings obtained from a collocated seismometer and rotational sensor. This innovative approach merges
the capabilities of a small-scale seismic array with the cost-efficiency of single-station surface measurements. It enables the extraction of seismic velocities from both active and passive seismic sources. Unlike cross-correlationbased seismic interferometry methods, such as ambient noise tomography,
the proposed measurement does not rely on the theoretical assumption of
the equipartition of noise sources, which is normally not satisfied in practice.
More significantly, the used amplitude-ratio-based algorithm for proposed
measurement will suppress the influence of seismic sources and mitigate thewave propagation effects, making the method more sensitive to near-receiversubsurface structures. The proposed measurement ensures near-receiver sensitivity and repeatability, allowing for the detection of small perturbations inthe subsurface and engineering structure properties even in dynamic environments with changing noise sources. As a result, the proposed measurement iswell-suited for monitoring site-specific seismic velocity variations. We verified
the efficacy of the proposed 6C measurement through both synthetic and realworld examples, including near-surface and engineering applications.

From Faults to Fjords: Earthquake Evidence in Terrestrial
and Subaqueous Environments
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Danny Brothers, U.S. Geological Survey(dbrothers@usgs.gov); Tina Dura, Virginia Polytechnic
Institute and State University (tinadura@vt.edu); Jenna Hill,
U.S. Geological Survey ( jhill@usgs.gov); Kristin Morell,
University of California, Santa Barbara (kmorell@ucsb.edu);
Belle Philibosian, U.S. Geological Survey (bphilibosian@usgs.
gov); Derek Sawyer, Ohio State University (sawyer.144@osu.
edu); Drake Singleton, U.S. Geological Survey (dsingleton@
usgs.gov); Katleen Wils, University of Innsbruck (katleen.
wils@uibk.ac.at); Rob Witter, U.S. Geological Survey(rwitter@usgs.gov); Mark Zellman, BGC Engineering,(mzellman@bgcengineering.ca)
Effect of Marine Reservoir Variations on the Temporal
Correlation of Earthquake Evidence on the Central andSouthern Hikurangi Subduction Zone
CLARK, K. J., GNS Science, Lower Hutt, New Zealand, k.clark@gns.cri.nz;
PIZER, C., University of Innsbruck, Innsbruck, Austria, Charlotte.Pizer@
uibk.ac.at; HOWARTH, J., Victoria University of Wellington, Wellington,
New Zealand, Jamie.Howarth@vuw.ac.nz; LITCHFIELD, N., GNS Science,
Lower Hutt, New Zealand, N.Litchfield@gns.cri.nz; HOWELL, A., GNS
Science, Lower Hutt, New Zealand, A.Howell@gns.cri.nz
A key question in New Zealand subduction zone hazard studies is if, or how
often, the Hikurangi subduction zone ruptures both the central and southernparts of the subduction zone vs just southern section ruptures. To address
this we rely on the temporal correlation of different types of earthquake andtsunami evidence from widely spaced sites. At several key sites the radiocarbon chronologies are constrained by terrestrial radiocarbon dates but at
most, particularly marine terrace and paleotsunami sites, the chronology isdominated by marine radiocarbon ages. Calibration of the marine radiocarbon ages combines the marine calibration curve and a local marine reservoir
offset (ΔR). Changes between versions of the global marine calibration curve(Marine20 vs Marine13 curves) have minimal impacts on modeled earthquake ages. However, over the past 3 years we have undertaken a study ofmarine reservoir variation around New Zealand and find regional differencesin ΔR of up to 100 years. Focussing on the Hikurangi subduction zone, wheremarine reservoir measurements have increased from 14 to 45, we found an
average ΔR for the whole margin is appropriate, rather than subdividing themargin as we have previously done. However, marine radiocarbon ages should
not be acquired from two subduction paleoearthquake sites with limestone
catchments or from molluscs from some particular environments. Overall it
would be ideal to eliminate marine radiocarbon ages from the paleoearthquake chronologies as the uncertainties on individual ages are large but few
alternative geochronology tools exist at many study sites. As we incorporate
offshore turbidite ages from the central Hikurangi subduction zone into the

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Seismological Research Lettersmargin-wide compilations of paleoseismology, understanding the offshore
marine reservoir becomes increasingly important. The new marine reservoir
values call for a re-evaluation of paleoearthquake temporal correlations, andexamination of evidence for central and southern Hikurangi subduction zone
ruptures.
An 8000-Year Holocene Earthquake Record From theNorthern Cascadia Forearc: Evidence for Multiple Sourcesat Lake Crescent, Washington
LEITHOLD, E. L., North Carolina State University, North Carolina, USA,leithold@ncsu.edu; WEGMANN, K., North Carolina State University, North
Carolina, USA, kwwegman@ncsu.edu; COLIP, G. D., U.S. Geological Survey,
Virginia, USA, gdcolip@usgs.gov
Lake Crescent is a deep, steep-sided lake within the forearc of the northern
Cascadia subduction margin on the northern Olympic Peninsula in western
Washington. Like other lakes worldwide, Lake Crescent’s stratigraphy points
to an earthquake-recording sensitivity that depends on the climate, sedimentaccumulation rates, and shaking intensity. Starting about 8,000 years ago,
two distinctive types of event deposits began to accumulate in the lake. Fourmeter-scale mass transport deposits resulted from multiple large mass failureson subaerial and subaqueous slopes triggered by ruptures along the North
Olympic Fault Zone beneath the lake. On the other hand, twenty decimeterscale turbidites correlate to much smaller mass failures on the lake’s subaqueous slopes. The turbidites have age ranges that overlap with regional offshore
and onshore paleoseismic records, including those derived from deep-sea turbidites, Vancouver Island lakes and fjords, and Cascadia salt-water marshes.
While these correlations suggest that most of the Lake Crescent turbidites
formed during great Cascadia subduction earthquakes, we cannot rule outthat some had other sources, including nearby crustal faults. Importantly,
deposits correlative to two regional earthquakes that multiple researchers
postulate to have occurred at the subduction interface around 500-600 and
800-900 years ago are absent to poorly developed at Lake Crescent but are represented in the stratigraphy of Ozette Lake, located 60 km to the west of Lake
Crescent and closer to the subduction trench. The differences between these
two lakes suggest that shaking during these subduction zone events was sufficiently attenuated in the landward direction so that Lake Crescent’s underwater slopes were minimally affected. Additionally, no turbidites formed in
Lake Crescent in the 324 years since the last great subduction zone earthquakeof 1700 CE, implying that shaking from crustal earthquakes has not exceeded
the necessary local threshold for turbidite emplacement during this period.
Variations in Mass Transport Deposits That Record Strong
Ground Motion Events in Western Prince William Sound,
AlaskaSINGLETON, D. M., U.S. Geological Survey, California, USA, dsingleton@
usgs.gov; BROTHERS, D. S., U.S. Geological Survey, California, USA,dbrothers@usgs.gov; HAEUSSLER, P. J., U.S. Geological Survey, Alaska,
USA, pheuslr@usgs.gov; WITTER, R., U.S. Geological Survey, Alaska, USA,rwitter@usgs.gov; HILL, J. C., U.S. Geological Survey, California, USA, jhill@usgs.gov; KLUESNER, J., U.S. Geological Survey, California, USA, jkluesner@usgs.gov; BALSTER-GEE, A., U.S. Geological Survey, California, USA,abalster-gee@usgs.gov
The fjords of Prince William Sound (PWS) overlie the westernmost AlaskaAleutian subduction zone, including the epicentral region of the 1964 Mw
9.2 Great Alaska Earthquake. In 1964, intense shaking generated widespread
destabilization and failure of submerged fjord sediments, which in turn generated devastating tsunamis that impacted several coastal communities in PWS.
While sediments in some fjords failed catastrophically in 1964, others did
not, suggesting that a complex interplay between basin physiography, sediment accumulation, and shaking intensity determines the degree of instability
that develops within each local fjord depositional system. In summer 2020,
the USGS collected a suite of nested multi-channel seismic and high-resolution Chirp data in several fjords of western Prince William Sound, as well as
short-barrel, percussion-driven gravity cores to characterize the top ~2 m of
sediment.
The effect of the 1964 earthquake has previously been identified in several of the surveyed basins (e.g., Passage Canal and Dangerous Passage) as
a 5-10+ m thick deposit. Deposits with similar character and stratigraphic
position, but with variable thickness (~0.3m to 15m) are observed in everybasin surveyed, and we interpret these deposits to result from sediment remobilization in 1964. The ubiquity of the 1964 deposit imaged in chirp and MCS
data implies that ground motions were sufficient to remobilize detectable levels of sediment. The variability in deposit character, however, suggests thatvariations in sediment supply precondition certain basins for larger failureswww.srl-online.org•

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than others. Using the 1964 deposits as a template, we investigate the potential
relationship between pre-conditioning factors and strong ground motion inremobilizing sediment and extend this investigation past the historical period
to previous strong ground motion events. The results of this study may haveimportant implications for quantifying the relationships between seismicparameters (i.e., shaking intensity), and the sedimentary response (i.e., total
volume remobilized and thickness of the resulting deposit).
Long Lacustrine Sedimentary Records in South-Central
Chile Evaluate the Spatiotemporal Variability of
Megathrust Earthquakes
NIEDERSTÄTTER, M., University of Innsbruck, Innsbruck, Austria,
Markus.Niederstaetter@uibk.ac.at; MORENO, V., University of Innsbruck,
Innsbruck, Austria, Valentina.Moreno@uibk.ac.at; WILS, K., Universityof Innsbruck, Innsbruck, Austria, Katleen.Wils@uibk.ac.at; VAN DAELE,
M., Ghent University, Ghent, Belgium, Maarten.VanDaele@UGent.be;
KONZETT, J., University of Innsbruck, Innsbruck, Austria, Juergen.Konzett@uibk.ac.at; MELNICK, D., Núcleo Milenio CYCLO, Valdivia, Chile, Daniel.
Melnick@uach.cl; PINO, M., Universidad Austral de Chile, Valdivia, Chile,
mariopino@uach.cl; DE BATIST, M., Ghent University, Ghent, Belgium, marc.
debatist@ugent.be; URRUTIA, R., University of Concepción, Concepción,
Chile, rurrutia@udec.cl; STRASSER, M., University of Innsbruck, Innsbruck,
Austria, Michael.Strasser@uibk.ac.at; MOERNAUT, J., University of
Innsbruck, Innsbruck, Austria, Jasper.Moernaut@uibk.ac.at
Along the Valdivia Segment of the Chilean subduction zone, giant full-segment ruptures such as the 1960 CE (Mw 9.5) earthquake occur on average
every ~300 years. Between these events, great partial ruptures such as the 2016
CE, 1837 CE, 1737 CE or the prehistorical 1455 CE earthquakes are known tooccur. However, their contribution to overall stress relieve remains unclear,mostly because the along-strike extent and down-dip location of such preinstrumental ruptures are poorly constrained. Therefore, comprehensive studies on the spatiotemporal variability of these ruptures is crucial to validate
earthquake cycle models and improve seismic hazard assessment in SouthCentral Chile.
Paleoseismic records obtained from short sediment cores in elevenlakes along the Valdivia Segment allowed us to study the along-strike extent
of known (pre)historic partial ruptures during the last two millennia. New
long-core records from Lago Rupanco and Lago Huillinco additionally allow
evaluating the temporal and down-dip rupture variability by expanding the
paleoshaking record to the last ca. 5000-8000 years (Lago Rupanco) andlinking it to tsunami records (Lago Huillinco). The lacustrine sedimentary
imprint of earthquakes causing strong shaking can consist of turbidites, masstransport deposits or in-situ soft sediment deformation structures. Highresolution core scanning (X-CT, XRF, MSCL, etc.) allows us to detect andcharacterize these event layers in numerous cores and identify those related tomegathrust earthquakes to then assess the related earthquake shaking quantitatively. Correlation of regional tephra layers, for which precise ages can beobtained independently, improve the radiocarbon-based age-depth models,
resulting in more accurate paleoseismic age control and estimations of recurrence intervals. These lacustrine records will significantly enhance our understanding of the spatiotemporal variability of full and partial ruptures of the
Valdivia segment. The analysis of sedimentary records from different lakes
will increase our process understanding on the formation of seismogenic andtsunamigenic event layers.
Quantitative Calibration of the Lacustrine Seismograph
Using Sedimentary Imprints of Recent Megathrust
Earthquakes in South-Central Chile
WILS, K., University of Innsbruck, Innsbruck, Austria, katleen.wils@ugent.be;
MONTALVA, G., University of Concepción, Concepción, Chile, gmontalva@
udec.cl; MOERNAUT, J., University of Innsbruck, Innsbruck, Austria, jasper.
moernaut@uibk.ac.at; VAN DAELE, M., Ghent University, Ghent, Belgium,
maarten.vandaele@ugent.be; DE BATIST, M., Ghent University, Ghent,
Belgium, marc.debatist@ugent.be
Accurate seismic hazard assessment strongly relies on paleoseismic research,
providing long timescales of past seismic shaking, hereby potentially also
revealing earthquakes that were larger than the highest-magnitude earthquakes known from historical or instrumental records. In this respect, lakes
often provide long and highly sensitive shaking records, and lacustrine paleoseismology has evolved into an invaluable methodology for reliable reconstructions of earthquake recurrence intervals around the world. A thoroughunderstanding of the relation between the component(s) of strong groundmotion (e.g. PGA, PGV, duration) and the resulting sedimentary signature is,however, still missing. As a result, characterization of the source parameters ofVolume 95•

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paleo-earthquakes, such as magnitude and location, up to now relies solely on
qualitative or semi-quantitative considerations.
Previous studies have aimed at calibrating the lacustrine seismograph byattributing the occurrence or absence of coseismic imprints (e.g. turbidites)
to intensities of seismic shaking. These intensity values are usually expressedon the macroseismic scale, as such information is more readily available compared to instrumental data for recent as well as historical earthquakes. These
are, however, relatively subjective ground motion measures, unable to capture
the various aspects of strong ground motion. In this study, we determine therelationship between quantitative ground motion measures on the bottom of alake and the sedimentary shaking imprints identified therein. To achieve this,
we focus on the sedimentary signature of instrumentally recorded megathrustearthquakes in south-central Chile. This includes the 1960 Mw 9.5 Valdivia
earthquake and the 2010 Mw 8.8 Maule earthquake. A compilation of existing
sedimentological data shows that coseismic deposits related to either of these
events are identified in over 20 lakes. By linking the imprint characteristics
for both earthquakes to the local ground motions, we bridge the gap between
sedimentology and seismology, opening perspectives towards quantitative
characterization of paleo-earthquakes.
Seismic Imaging Beneath Iceberg Lake, Alaska: SedimentCharacteristics and Fundamental Site Response Parameters
Beneath a Drained Lake With an Alaskan-Aleutian
Subduction Zone Paleoseismic Record
LIBERTY, L. M., Boise State University, Idaho, USA, lliberty@boisestate.
edu; HAEUSSLER, P. J., U.S. Geological Survey, Alaska, USA, pheuslr@usgs.
gov; OTHEIM, L. T., Boise State University, Idaho, USA, LarryOtheim@
boisestate.edu; SINGLETON, D. M., U.S. Geological Survey, California, USA,dsingleton@usgs.gov; WESSON, R. L., U.S. Geological Survey, Colorado,
USA, rwesson@gmail.com; VAN DAELE, M., Ghent University, Ghent,
Belgium, Maarten.VanDaele@ugent.be
The emerging field of lacustrine paleoseismology requires an understanding of a lake’s response to earthquake ground shaking. We acquired seismic
data across the drained Iceberg Lake, Alaska valley floor to characterize basin
sediments and ground motions associated with earthquakes along the eastern
portions of the Alaskan-Aleutian subduction zone. The glacier-dammed lake,
located in the Wrangell-St. Elias National Park, drained in 1999. From exposedand cored lake-bottom sediments, the lake shows a 1500+ year history. Our
hammer seismic profiles along three transects provide basin thickness andseismic velocity (Vs30) estimates for lake sediments and surrounding bedrock. Coupled with microtremor measurements from 12 three-component
Nodal geophones, we calculate horizontal-to-vertical (H/V) spectral ratiosthat provide a predominant site frequency (F0) at each measured location.
We identify ~50 m of saturated sediments on top of bedrock at the basin
depocenter, suggesting a long post-glacial (~14 ka?) record. Vs30 values are
consistent with site D-Class stiff soils beneath the Iceberg Lake basin margins
and interfluve, and E-Class soft soils within the central basin. F0 estimatesfrom our Nodal data range from less than 2 Hz at sites that lie on the valley
floor to more than 50 Hz at our bedrock station without sediment and therefore no low frequency basin resonance. Sites along the basin margins recordedintermediate F0 values, consistent with shallower bedrock depths comparedto the basin center. We find a match between F0 derived from microtremor
analyses and from Vs30 and bedrock depths derived from hammer seismic
data. Through empirical relationships, we correct Vs30 for overburden pressure from past lake levels and compare lake floor slopes with Vs30 values todevelop a basin-wide site response model. These data provide inputs to assessground motions along subduction zones from megathrust, intraslab, andcrustal earthquakes using lake sediments. By coupling our results with thelake’s paleoseismic record, we improve our understanding of seismic shaking
in subduction zone coastal environments.
The Subaerially Exposed Iceberg Lake Sediments: A ~1000
Yr Long Paleoseismic Record From the Eastern Edge of the
Alaska Subduction ZoneVAN DAELE, M., Ghent University, Ghent, Belgium, maarten.vandaele@
ugent.be; VERCRUYSSE, P., Ghent University, Ghent, Belgium, Pieterjan.
Vercruysse@UGent.be; WITTER, R., U.S. Geological Survey, Alaska, USA,rwitter@usgs.gov; LOSO, M., National Park Service, Alaska, USA, Michael_Loso@nps.gov; SINGLETON, D., U.S. Geological Survey, California, USA,dsingleton@usgs.gov; LISSON, K., Ghent University, Ghent, Belgium,
Kamill.Lisson@UGent.be; LIBERTY, L., Boise State University, Idaho, USA,lliberty@boisestate.edu; HAEUSSLER, P. J., U.S. Geological Survey, Alaska,
USA, pheuslr@usgs.gov; WESSON, R. L., U.S. Geological Survey, Colorado,

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USA, rwesson@gmail.com; OTHEIM, L., Boise State University, Idaho, USA,
LarryOtheim@boisestate.edu
Paleoseismic records are scarce on and around the Yakutat terrane, at theeastern edge of the Alaskan-Aleutian subduction zone. In this region at thetransition between subduction and transform tectonics, the earthquake hazard comes primarily from faults bounding the Yakutat microplate, and fromwithin the subducting Yakutat slab. Several of these fault zones hosted historical earthquakes such as the 1899 Mw 8.1 Yakutat Bay, 1958 Mw 7.9 Lituya Bay
and 1979 Mw 7.4 Saint Elias earthquakes. In such a complex setting, whichis compounded by extensive ice cover, traditional paleoseismic methods(trenching) do not work well. In contrast, lacustrine paleoseismic shaking
records have more potential to provide comprehensive paleoseismic records.
Here, we study the sediments of Iceberg Lake, a glacier-dammed lake inthe eastern Chugach mountains, within the Wrangell - St Elias National Park
& Preserve. The lake drained during several outburst floods after 1999 CE,
which exposed the lake bed and, through active erosion, the lacustrine sediments. In August 2022 we examined 6 outcrops in various sedimentary settings, from sandy delta to deep basin. We described the exposures, created 3D
outcrop models using Structure-From-Motion photogrammetry and sampled
sediments. Between annually laminated background sediments, we identified sediment gravity flow deposits and in-situ soft-sediment deformation
features, such as convoluted bedding, dewatering structures and sand blows,
inferred to be related to seismic shaking in prior studies. Cross-correlation ofthese beds between sites, and with previously studied and dated outcrops andcores, reveal that the most recent deposits can be linked to historical 1899,
1958, 1964 and 1979 CE earthquakes. We further identify an event that caused
widespread gravity flows around 1920 CE, as well as similar pre-1899 events,
such as a significant one in the second half of the 17th century. We conclude
that Iceberg Lake is an excellent recorder of seismic shaking and has strong
potential of preserving a high-quality paleoseismic record for the northernpart of the Yakutat terrane.
The Great Salt Lake as a Recorder of Sublacustrine Surface
Rupture and Strong Shaking in the Wasatch Front Region,
Utah
DUROSS, C. B., U.S. Geological Survey, Colorado, USA, cduross@usgs.gov;
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@
usgs.gov; THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA,jjobe@usgs.gov; BRIGGS, R. W., U.S. Geological Survey, Colorado, USA,rbriggs@usgs.gov; SINGLETON, D. M., U.S. Geological Survey, California,
USA, dsingleton@usgs.gov; NICOVICH, S. R., U.S. Geological Survey,
Colorado, USA, snicovich@usgs.gov; NELSON, A. R., U.S. Geological Survey- Emeritus, Colorado, USA, anelson@usgs.gov
The Great Salt Lake (GSL) is a broad (30-km-wide), shallow (≤15-m-deep),and low-relief saline endorheic lake adjacent to the Wasatch Front regionof Utah. Here, we explore the GSL as a potential recorder of Wasatch Front
earthquakes and attempt to disentangle evidence of strong shaking and sublacustrine surface rupture. We focus on the western margin of Antelope Island,
where sublacustrine scarps along the Great Salt Lake fault (GSLF) span theeastern lake margin, and previous subbottom Chirp data and piston coressuggest Holocene surface ruptures as young as ~0.6 ka. In our study, Chirp
data show GSLF hanging-wall deformation, growth faulting, and stratal
onlap in support of multiple Holocene ruptures, with the youngest within~1 m (~1.2 ms) of the lake bottom. We also interpret 14 <2-m-long gravity
cores arranged in three fault-normal transects. Photo logs, X-ray computed
tomography, multi-sensor data, and grain-size measurements show lacustrine
sediments characterized by light to dark gray, flat to wavy laminated, brineshrimp-fecal-pellet-derived silt and fine sand. These background sediments
are punctuated by massive ≤41-cm-thick disturbance horizons, which range
from homogenites to normally graded silt and sand beds with evidence of
sediment resuspension and transport. After evaluating possible mechanismsof sediment disturbance, we are most confident in a tectonic interpretation.
We describe and correlate these disturbance horizons among the cores andconstrain their timing using radiocarbon ages of terrestrial plant remains andcharcoal included in Bayesian models. Preliminary results suggest that GSL
sediments record strong shaking from large-magnitude (likely surface rupturing) Wasatch fault earthquakes as well as the most recent GSLF rupture. We
plan to refine the GSL disturbance horizon chronology, compare to compilations of terrestrial Wasatch fault paleoearthquakes, and evaluate whether the
GSL acts as a reliable Wasatch Front lacustrine seismograph.

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Seismological Research Letters

Sediment Shear Strength Development Within Terminal
Basins of the Japan Trench and Lower Slope: Insights Into
Seismic Strengthening and Earthquake Paleoseismology
From R/V Sonne Expedition SO251 (Eager-Japan) and IODP
Expedition 386
SAWYER, D. E., Ohio State University, Ohio, USA, sawyer.144@osu.edu;
STRASSER, M., University of Innsbruck, Innsbruck, Austria, michael.
strasser@uibk.ac.at
Recent findings have demonstrated that the Quaternary sedimentary fill in
hadal basins along the Japan Trench, consists of two distinct deposition styles:
slow background deposition punctuated with rapid event beds of variable
thickness. In this study, we examine this bimodal basin fill pattern to investigate shear strength and how shear strength changes over time during burial
and exposure to seismic activity. We compare strength profiles of basin sediment to sites located on the lower slope where sedimentation is expected to
be low and prone to sediment bypass, erosion, and seismic strengthening. We
compile shear strength data from R/V Sonne Expedition SO251 (EAGERJAPAN) that acquired piston cores in the basins and the slope, and IODP
Expedition 386 that acquired 29 giant piston cores in 15 basin sites. We find:2 distinct shear strength profiles: sediments in the deep basins have low-tonormal shear strengths while sites on the slope have anomalously high shear
strengths. A further finding in the basin sites is that the shear strength profiles of thick near-seafloor acoustically transparent units in subbottom data
have lower-than-normal shear strengths. We interpret: the low-to-normal
basin strengths are likely representative of relatively high sedimentation rates
including raid, episodic pulses of sediment from earthquake-triggered event
beds. Further, in young event beds that are still undergoing consolidation,
this may be used as a novel way to constrain age of the event bed to complement traditional age-dating techniques. In contrast, slope sites may be prone
to a combination of erosion and seismic strengthening, leaving sediments
strengthened.
Beyond the Waves: Integrating Rock Physical Properties for
Deeper Seismic Understanding
CASTILLO, R., Ohio State University, Ohio, USA, castillo.271@buckeyemail.
osu.edu; SAWYER, D. E., Ohio State University, Ohio, USA, sawyer.144@osu.
edu; STRASSER, M., University of Innsbruck, Austria, michael.strasser@uibk.
ac.at; KEEP, M., The University of Western Australia, Perth, myra.keep@uwa.
edu.auTechnological advances are driving Earth Sciences into the era of big data.
Machine learning (ML) techniques offer potential for the advancement of submarine paleoseismology because of the need to integrate large datasets madeat various scales with physical properties offering microscale, sediment coreoffering mesoscale, and geophysical data providing macroscale insights. Thisdata integration is vital for the goal of distinguishing between earthquake- andnon-earthquake-generated event beds. At its simplest definition, an event bed
can be treated as an anomaly for which anomaly detection ML can be applied
to identify similarities or differences for faster analysis and characterization.
IODP (International Ocean Drilling Program) Expedition 386 collected
a comprehensive dataset of cores, physical/chemical data, and geophysicalprofiles in the northern basins of the Japan Trench. Our goal is to test ML
capabilities to complement traditional efforts to identify event beds. We focus
on Site M0084 where an acoustically thick unit occurs near the top of thesedimentary sequence above a few other potential event beds that occur inotherwise relatively simple stratigraphy. First, we test ML application withsynthetic seismograms to link cores to geophysical properties at this site as it iscomprised of thick event beds, not prone to resolution issues. Next, we utilize
convolution neural networks for anomaly detection of sediment core imagery
to refine and incorporate synthetic trace results with the various datasets. In
the future, this framework based on physical properties and geophysical data
can be extended across the Japan Trench, incorporating more expedition sites
for further event bed detection.
Repeated Coseismic Uplift of Coastal Lagoons Above thePatton Bay Splay Fault System, Montague Island, Alaska,
USA
DEPAOLIS, J., Virginia Tech, Virginia, USA, jessicad@vt.edu; DURA, T.,
Virginia Tech, Virginia, USA, tinadura@vt.edu; WITTER, R., U.S. Geological
Survey, Alaska, USA, rwitter@usgs.gov; HAEUSSLER, P. J., U.S. Geological
Survey, Alaska, USA, pheuslr@usgs.gov; BENDER, A., M., U.S. Geological
Survey, Alaska, USA, abender@usgs.gov; CURRAN, J. H., U.S. Geologicalwww.srl-online.org•

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April 2024

Survey, Alaska, USA, jcurran@usgs.gov; CORBETT, R., East Carolina
University, North Carolina, USA, corbettd@ecu.edu

Inc., Vancouver, Canada, dmaxwell@bgcengineering.ca; ENOS, R., BGC
Engineering Inc., Oregon, USA, nenos@bgcengineering.com

Coseismic slip on the Patton Bay Splay Fault System during the 1964 Mw 9.2
Great Alaska Earthquake contributed to local tsunami generation and vertically uplifted shorelines on Montague Island, Prince William Sound (PWS)by as much as 11 m. Sudden uplift of the island caused coastal lagoons along
the northwestern coast to gradually drain leading to changes in depositional
environment from marine lagoon to freshwater muskeg which created a
sharp, laterally continuous stratigraphic contact between silt and overlying
peat. Here, we characterize the geomorphology, sedimentology, and diatom
ecology signatures across the 1964 earthquake stratigraphic contact and threesimilar, widespread prehistoric contacts within the stratigraphy of the Hidden
Lagoons locality. We find that all four contacts signal instances of abrupt
coastal uplift with radiocarbon, 137Cs, and 210Pb dating methods constraining them to ages that, within error, overlap the timing of independently constrained megathrust earthquakes in PWS–1964 CE, 760-870 yr BP, 2500-2700
yr BP, and 4120-4500 yr BP. Changes in fossil diatom assemblages across theinferred prehistoric earthquake contacts reflect ecological shifts consistent
with repeated draining of a lagoon system caused by >3 m of coseismic uplift,
similar to the environmental changes across the 1964 earthquake contact. Our
observations provide evidence for instances of splay fault ruptures that haveoccurred close in time, within less than a century, of four of the last eight
megathrust earthquakes over the past ~4,200 years in PWS. These results provide new information about potential rupture dynamics and tsunami risks
associated with future combined megathrust-splay fault system ruptures
which should be considered in hazards assessments.

The Iditarod Nixon Fork fault (INFF) and the Boss Creek and Holitna sections of the Denali fault (BCF and HF) in west-central Alaska are included as
Quaternary faults in active fault databases and as crustal fault sources in the
USGS 2023 Alaska Seismic Hazard Model. Information about the activity ofthese structures and their associated seismic hazard parameters (i.e. slip rate,
recurrence, geometry) is sparse due to a lack of detailed studies. We evaluatedthese faults to address uncertainties and data gaps as part of a seismic source
characterization for the Donlin Gold Project. The study included lidar collection along 130 km of the INFF, desktop geomorphic mapping and criteriabased evaluation of faults and lineaments within 100 km of the Project site,
aerial and ground-based reconnaissance of prioritized faults and lineaments,
and collection of 14C, 10Be TCN, IRSL, and tephra samples to constrain agesof displaced surfaces and estimate slip rates for the INFF, BCF, and HF.
Along the INFF, our mapping and reconnaissance confirmed strong geomorphic evidence of late Quaternary faulting extending southwest of Moore
Creek, AK, for 100 to 125 km. Right-lateral slip along the INFF has displaced
tributaries of Bonanza Creek 18±6m. Using IRSL ages of ~32-38 ka and ~2223 ka from two loess deposits that mantle the faulted surfaces, we estimate apreliminary maximum slip rate of ~0.5-1 mm/yr. Geomorphic evidence of
Quaternary faulting is weak to absent for an additional 75 to 100 km of thefault extending southwest to the Kuskokwim River. Along the Denali fault,
14C ages from a test pit in an abandoned Holitna River channel confirms atleast one surface rupture in the past ~1000 years, consistent with the presenceof en-echelon fissures in muskeg at Itulilik Creek. Four 10Be TCN ages fromboulders on a displaced LGM moraine complex (20-23 ka) will be combinedwith offset reconstructions to estimate preliminary slip rates at the junctionof the BCF and HF. These findings confirm significantly more Holocene slip
farther west on the Denali fault than previously estimated.

Re-Examination of the 1958 Huslia Earthquake Sequenceand Regional Tectonics of the Northwestern Koyukuk
Basin, Alaska in Light of Post-1974 Seismicity, Mapped
Faults and Geophysical Data
DOSER, D. I., University of Texas at El Paso, Alaska, USA, didoser56@
gmail.com; BAKER, M. R., Consultant, Alaska, USA, bakergrd@cs.com;
HAEUSSLER, P. J., U.S. Geological Survey, Alaska, USA, pheuslr@usgs.gov
In 1958 a Mw 6.8 earthquake and several Mw>5.3 aftershocks occurred in thenorthwestern Koyukuk Basin near the village of Huslia (~ 400 km northwestof Denali). Tectonically, this region is located between the compressional
forces due to the collision of the Pacific and Yakutat plates and extensional
forces associated with the extrusion of western Alaska. Since 1969 several
earthquake swarms with Mw 4-5 events have occurred ~50 km northwest of
Huslia in the western Purcell Mountains, including a swarm in 2019-2022
with over 9500 events. Previous studies have suggested the 1958 mainshock
occurred on a northeast striking, southeast dipping normal fault. This senseof rupture is inconsistent with the focal mechanisms and trends of post-1973
seismicity within the 1958 epicentral region that indicate strike-slip movement along northwest trending faults. A recently mapped east-west trending
fault scarp located along the southern front of the Purcell Mountains is also
inconsistent with northeast striking normal faulting. To better characterize
the 1958 sequence and its relation to mapped faults and regional tectonics,
we measure scarp profiles across the Purcell Mountains scarp, relocate historical seismicity, analyze first motions and waveforms of pre-1974 events,and model potential fields geophysical data. Our preliminary results suggest
regional deformation is occurring along both east-west and northwest trending structures.
Confirmation of Late Quaternary Surface Faulting andPreliminary Slip Rates for the Iditarod-Nixon Fork Fault
and the Boss Creek and Holitna Sections of the Denali
Fault in West-Central Alaska
ZELLMAN, M., BGC Engineering Inc., Colorado, USA, mzellman@
bgcengineering.com; DUCKWORTH, W., BGC Engineering Inc., Colorado,
USA, cduckworth@bgcengineering.com; KOEHLER, R. D., Nevada Bureauof Mines and Geology, Nevada, USA, rkoehler@unr.edu; ZALESKI, M. P.,
BGC Engineering Inc., Vancouver, Canada, mzaleski@bgcengineering.ca;
OSTENAA, D. A., Ostenaa Geologic, LLC, Colorado, USA, Deano3geo@
gmail.com; HORNSBY, K. T., BGC Engineering Inc., Colorado, USA,khornsby@bgcengineering.com; WHELAN, N. E., BGC Engineering
Inc., Halifax, Canada, nwhelan@bgcengineering.ca; RITTENOUR, T. M.,
Utah State University, Utah, USA, tammy.rittenour@usu.edu; HIDY, A. J.,
Lawrence Livermore National Laboratory, California, USA, hidy3@llnl.gov;
ZIMMERMAN, S. R., Lawrence Livermore National Laboratory, California,
USA, zimmerman17@llnl.gov; MAXWELL, D. A., BGC Engineering

Volume 95•

Number 2B•

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www.srl-online.org

A New Generation of High-Precision Dating Techniques for
Coseismically-Killed or Damaged Trees
BLACK, B. A., University of Arizona, Arizona, USA, bryanblack@arizona.
edu
Dendrochronological techniques are uniquely high precision, establishing theexact calendar year of formation for each tree ring in a sample set. Thus, if atree was killed by seismic activity, the exact calendar year and even season of
the earthquake can be determined by establishing the year of the final ring
formed under the bark. If trees have been disturbed but not killed, growth or
anatomical anomalies can also place seismic events in time.
High dating precision is typically accomplished via crossdating in which
synchronous, time-specific growth patterns are matched among trees of agiven species and region, beginning with live-collected trees, and extending
back in time with dead-collected trees. There are, however, important limitations, even assuming wood is well preserved. Dead-collected trees must
contain ring sequences long enough (usually 150 years or more) to establish
confident growth-pattern matches. There must also be sufficient year-to-year
growth variability and a minimum of irregularities or distortions. Yet wood
samples often violate these criteria, especially roots, which are often the bestpreserved part of dead trees.
Newly emerging techniques are likely to help overcome limitations ofdating with ring widths. First, the oxygen-18 content of tree rings often covaries among trees, and even species, more strongly than width. Preliminary datain the Pacific Northwest indicates that wood samples with short sequences,distorted rings, and little year-to-year growth variability can be crossdated
using oxygen-18. Single-year cosmogenic spikes in radiocarbon, known as“Miyake Events,” provide another new approach for one-year dating precision of paleo-earthquakes. Finally, “wiggle matching” multidecadal series ofradiocarbon values from tree rings may narrow uncertainties to within a year
or two for wood that lived within the past several thousand years. Combined,
these techniques could enable the dating of wood samples, including roots,that could not have been crossdated using ring widths, and initiate a new generation of high-resolution paleoseismic reconstructions.
Precisely Dating Seismically Triggered Debris Avalanches in
the Northern California Coast Range
PEARL, J. K., The Nature Conservancy, Arizona, USA, jessie.pearl@tnc.org;
KELSEY, H., California State Polytechnic University, Humboldt, California,
USA, hmk1@humboldt.edu; ANGSTER, S., U.S. Geological Survey,
Washington, USA, sangster@usgs.gov; CALDWELL, D., Stillwater Sciences,
California, USA, dylan@stillwatersci.com; PRYOR, I., Stillwater Sciences,

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California, USA, ian@stillwatersci.com; SHERROD, B. L., U.S. Geological
Survey, Washington, USA, bsherrod@usgs.gov
Determining the timing and cause for prehistoric hillslope failures has provendifficult in the western US, yet critical as it ties directly into ground motion
estimates for future hazardous events. This knowledge gap is important toconfront, however, as these avalanche failures are candidates to have been
triggered by earthquakes along active plate boundaries, where sources include
crustal faults, plate boundaries, and intraslab events. Here, we identify two
exceptionally large prehistoric debris avalanche failures in the Coast Ranges
of northern California that are well suited for studying the timing (to the exactyear) and cause (what triggered the failure) as the densely forested landscapeenables the effective use of dendrochronology and high-resolution radiocarbon. This high precision geochronology allows us to identify time of failure,
and the legacy of landslide studies in the region provides context for evaluating a climatic versus a seismic trigger as the most likely failure mechanism. We
find that the two debris avalanche sites are physiographically suited to accommodate topographic amplification of seismic shaking, and through a suite ofmultiproxy evidence, we establish that likely time of failure of the two debris
avalanches to be 1906 CE and 933 CE, respectively. In the first instance, theyear 1906 CE is the year of the San Francisco earthquake on the Pacific/North
American plate boundary, and in the second instance, the year of failure, 933
CE, falls within the broad age range (850-966 CE) that probably includes theyear of the antepenultimate earthquake on the Cascadia subduction zone asrecorded in coastal marshes in Humboldt Bay, California. The precise age on
the 933 CE debris avalanche could trim down the uncertainty on a Cascadia
subduction zone event from 116 years to one year. Utilizing debris avalanche
records from sites suitable to record seismic shaking improves understandingof plate-boundary earthquake timing and extent of shaking.
Diatom-Based Coseismic Subsidence Estimates Spanning a~4,500 Year History of Cascadia Subduction Zone Ruptures
Along the Southcentral Coast of Oregon
BRUCE, D., Virginia Tech, Virginia, USA, bruced@vt.edu; DURA, T., Virginia
Tech, Virginia, USA, tinadura@vt.edu; WITTER, R., U.S. Geological Survey,
Alaska, USA, rwitter@usgs.gov; KELSEY, H., California State Polytechnic
University, Humboldt, California, USA, hmk1@humboldt.edu; HEMPHILLHALEY, E., California State Polytechnic University, Humboldt, California,
USA, ehhaley@gmail.com
Estimating coseismic subsidence produced by past Cascadia Subduction Zone
(CSZ) megathrust earthquakes is crucial for understanding rupture dynamics, particularly magnitudes of paleoseismic slip. Past CSZ earthquakes are
expressed in tidal wetland stratigraphy as sharp contacts between saltmarsh
peat and overlying intertidal mud, indicating rapid coseismic subsidence.
Recent statistical methods (transfer functions) use microfossils (e.g., foraminifera, diatoms) to quantify coseismic subsidence across these abrupt
peat-mud contacts. Transfer functions estimate the amount of coseismic
subsidence by analyzing land/sea-level relationships before and after earthquakes. While foraminifera-based estimates reveal variability in subsidencealong-strike during the 1700 CE CSZ rupture, equivalent foraminifera-based
estimates for pre-1700 CE earthquakes are scarce. Tidal wetlands along theCoquille River estuary in southcentral Oregon preserve evidence of 12 CSZ
ruptures over the last ~7,000-years, but preliminary work indicates low numbers of calcareous foraminifera in deposits older than the 1700 CE rupture,complicating reconstructions of subsidence. In this study, we use diatoms, a
microscopic algae with resilient biosiliceous hard parts, as a complementaryalternative for subsidence reconstructions due to their preservation potential
in low pH environments. Using a diatom-based transfer function, we analyze seven CSZ earthquake contacts (1700 CE to ~4,500 yr BP) from Fahys
Creek, a Coquille River tributary. Additionally, we present new (between 3-6)
radiocarbon age dates for CSZ earthquake contacts, to aid in earthquake correlation. Our diatom analysis reveals variability in subsidence estimates overmultiple earthquake cycles, suggesting variable rupture patterns for successive
CSZ ruptures. The new subsidence estimates deepen our understanding of theheterogeneous nature of CSZ ruptures through time. Future work will entail
combining estimates from Fahys Creek with estimates for pre-1700 CE CSZ
earthquakes at other sites to build a comprehensive examination of alongstrike rupture characteristics of the CSZ.
Constraints on Cascadia Subduction Zone
Paleoearthquakes from Terrestrial Shaking Proxies andCoseismic Land-level Change
GRANT, A., U.S. Geological Survey, Washington, USA, agrant@usgs.gov;
WIRTH, E., U.S. Geological Survey, Washington, USA, emoriarty@usgs.gov;

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DUNHAM, A., U.S. Geological Survey, Washington, USA, adunham@usgs.
gov; LAHUSEN, S., U.S. Geological Survey, Washington, USA, slahusen@
usgs.gov; MAURER, B., University of Washington, Washington, USA,adunham@usgs.gov; MCPHILLIPS, D., U.S. Geological Survey, California,
USA, dmcphillips@usgs.gov
The impacts and nature of past great Cascadia Subduction Zone (CSZ) earthquakes, and the risk posed to the Pacific Northwest from future events, arepoorly constrained. Past work using evidence from written histories, paleoliquefaction, coastal subsidence, and near- and far-field tsunami deposits
allow for a wide-range of earthquake rupture styles, magnitudes, and shaking
intensities for a given ‘event’ in the geologic record. However, most studies
focus on a single geologic proxy to investigate these events. Here, we present an integrated method for assessing the likelihood of simulated CSZ earthquakes using a combination of terrestrial shaking proxies and estimates ofcoastal land-level change throughout Cascadia. Complementary constraints
on minimum and maximum paleoshaking intensities from coastal landslides,liquefaction, and fragile geologic features are combined with coseismic coastal
subsidence estimates to leverage a diverse and geospatially continuous set of
constraints on past CSZ earthquake rupture scenarios. This integrated paleoseismic record is compared to a suite of CSZ earthquake simulations for megathrust earthquakes of magnitude 8.65–9.15 with varying down-dip extents
of slip and source characteristics to compute misfit between the geologic
record and simulated ground motions. We assess misfit between the geologic
record and simulations at a full-margin scale to assess global performanceand identify local discrepancies along-strike to identify possible variations insource behavior. To assess the sensitivity of these results to different modeling approaches, we test different statistical methods for integrating the geologic proxy data, calculating the misfit, and incorporating geochronologicaluncertainty. Preliminary results show the sensitivity to how different geologic
proxies are integrated on preferred earthquake simulations, as well as how
incorporating subaqueous data (i.e., offshore and lacustrine) could further
improve these models.
A Cycle of Memory Creation, Erasure, and Solid to FluidLike State Transitions Encoded Within Granular
Assemblages Sheared by Faults
DASENT, J., University of California, San Diego, California, USA, jdasent@
ucsd.edu; KILBURN, R., University of California, San Diego, California,
USA, rkilburn@ucsd.edu; WRIGHT, V., University of California, San Diego,
California, USA, vwright@ucsd.edu; SCHARER, K., U.S. Geological Survey,
California, USA, kscharer@usgs.gov; MANGA, M., University of California,
Berkeley, California, USA, manga@seismo.berkeley.edu
A hallmark of many processes in Earth’s subsurface [e.g., landslides, groundrupturing earthquakes, liquefaction, and crystal-rich magmas] is the transitions in states that granular assemblages undergo, from structurally arrested tocreeping to flowing. The frictional jamming and material memory theoreticalframeworks argue that volume fraction and shear stress govern such transitions and that the material records the transitions. We use x-ray microtomography to determine if the three-dimensional re-arrangement and fracturingof grains within assemblages collected from two paleoseismic sites along thesouthern San Andreas fault record frictional jamming phenomenologies.
Analyses reveal that fault zone granular assemblages transition between one
or more interrelated but geometrically localized and mesoscopic deformation
states that change assemblages’ stability during the seismic cycle. These states
include [1-2] bulk and localized grain re-arrangements, [3] individual grain
fracturing, and [4] localized zones of grain fracturing. Grain re-arrangement
is primarily a global phenomenon. Grain size and non-rattlers exert control
over grain fracturing and re-arrangements. Coseismic shear erases anisotropic fabric memory developed during aseismic shear and introduces its own.
Shear stress magnitude and elastoplasticity control memory creation anderasure and thus vary with distance from a fault strand. Our findings imply[1] that sheared fault zone sediments experience a cycle of memory creationand erasure accompanied by differing deformation phases and thus hold aninvaluable record of how shallow faults move coseismically and aseismically,and [2] that frictional jamming and material memory remain promising unifying theories for granular flow, even considering naturally imposed disorder.
Lost and Found: Evidence of the Penultimate Earthquakeon the Hebgen and Red Canyon Faults, Montana
HECKER, S., U.S. Geological Survey, California, USA, shecker@usgs.gov;
STENNER, H. D., Geohazards International, Washington, USA, hstenner@
gmail.com; SCHWARTZ, D. P., U.S. Geological Survey (retired), California,
USA, dschwartz@usgs.gov; COSTA, C. H., Universidad Nacional de San Luis,

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San Luis, Argentina, costa@unsl.edu.ar; HAMILTON, J. C., U.S. Geological
Survey (retired), California, USA, jhamilton@usgs.gov
The 1959 Mw 7.3 Hebgen Lake, Montana, earthquake, one of the largestrecorded continental normal-faulting earthquakes, occurred on a structurally complex pair of overlapping normal faults (Hebgen and Red Canyon)
at the eastern end of the Centennial Tectonic Belt near Yellowstone National
Park. In this study, we document from historical photographs the short-lived
existence of a steep prehistoric scarp above the 1959 surface ruptures. At several locations, the preexisting scarp was rapidly regraded as the 1959 scarp
retreated upslope, and within a few decades, the scarp bevel had largely disappeared. Post-earthquake investigators had recognized that the 1959 scarps
near south end of the Red Canyon fault were superimposed on similar older
scarps (Myers and Hamilton, 1964); however, it’s unclear the extent to which
this observation has affected measurements of 1959 scarp heights and baseline
studies of how scarps degrade with time.
A photo taken in 1959 at a site where we trenched the central Hebgenfault (“Section 31” alluvial fan) provides geomorphic confirmation of a displacement event inferred from subsurface relations. We present paleoseismic
evidence of this young penultimate earthquake (PUE) and of a relatively longinterval separating it from earlier faulting. Recycling of soil organic matterfrom older colluvial-wedge deposits into the PUE wedge complicates estimation of its age, although several 14C ages (~600 yr B.P.) on detrital charcoal
and wood near the base of the PUE wedge are congruent with the youthfulsteepness (~30-40°) of the scarp as estimated from photography. An older
scarp bevel above the 1959/PUE scarp at the Section 31 site is, in contrast,
gently sloping (~20°) and stable enough to have a soil B horizon developed
beneath it. Evidence on both faults indicates that slip in the PUE was similar
to that in 1959, suggesting that event magnitude and pattern of rupture werealso similar. The rapid post-1959 loss of morphologic evidence of the PUE
scarp demonstrates that a simple fault scarp, even modest in size, should not
be assumed to represent a single earthquake.
Unveiling Seismic Hazards: Paleoseismic Insights From the
La Venta Fault in the Forearc Mountains, MexicoRAMÍREZ-HERRERA, M., Universidad Nacional Autónoma de México,
Mexico City, D.F., Mexico, maria_teresa_ramirez@yahoo.com; GAIDZIK, K.,
University of Silesia, Katowice, Poland, k.gaidzik@gmail.com; DOMINGUEZ,
L. A., ENES UNAM Morelia, Morelia, Mexico, ladominguez@enesmorelia.
unam.mx; COCA, O., Universidad Nacional Autónoma de México, Ciudad de
México, Mexico, OswaldoCoca8@gmail.com; VARGAS E., V. H., Universidad
Nacional Autónoma de México, CIUDAD DE MÉXICO, Mexico, victorvargas.
esp@gmail.com
Understanding the potential earthquake activity of unknown active faults is
crucial for assessing seismic hazards in continental interiors. Despite advancements, our knowledge of earthquakes on crustal faults away from plate boundaries, particularly in forearcs, remains incomplete. This study addresses thisgap by utilizing paleoseismic records, conducting a LIDAR flight to develop a
DTM in the highly vegetated mountains, mapping geomorphological features,
performing a geophysical survey including electric resistivity and georadar,and excavating a paleoseismic trench along the central section of the La Venta
Fault, named Agua del Perro. The trench revealed six rupturing events overthe last 8000 years.
The surface expression of this fault is subtle, characterized by a gentle
scarp, minor stream offsets, and a shutter ridge. Our data show evidence of
surface fault rupturing with lateral displacement up to ~80 cm per event andvertical displacement up to 44 cm. The most recent event occurred around the14th century, registering a calculated magnitude of Mw 6.9. Given the fault’s
location, our findings suggest a significant seismic risk to local communities
along the fault and populations in larger cities like Chilpancingo, Acapulco,and Mexico City. The study also highlights potential damage to infrastructure, such as the La Venta Dam, and associated hazards, including flooding
and rock falls. This research emphasizes the importance of recognizing thepotential hazard posed by crustal intraplate faults away from plate boundaries
in the forearc mountains.

From Faults to Fjords: Earthquake Evidence in Terrestrial
and Subaqueous Environments [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Danny Brothers, U.S. Geological Survey(dbrothers@usgs.gov); Tina Dura, Virginia Polytechnic

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Institute and State University (tinadura@vt.edu); Jenna Hill,
U.S. Geological Survey ( jhill@usgs.gov); Kristin Morell,
University of California, Santa Barbara (kmorell@ucsb.edu);
Belle Philibosian, U.S. Geological Survey (bphilibosian@usgs.
gov); Derek Sawyer, Ohio State University (sawyer.144@osu.
edu); Drake Singleton, U.S. Geological Survey (dsingleton@
usgs.gov); Katleen Wils, University of Innsbruck (katleen.
wils@uibk.ac.at); Rob Witter, U.S. Geological Survey(rwitter@usgs.gov); Mark Zellman, BGC Engineering,(mzellman@bgcengineering.ca)
poster 43
Lacustrine Paleoseismic Evidence From Two Large Lakes in
Cascadia: Preliminary Comparisons of Post-Glacial
Sediment Records From Ozette and Whatcom Lakes,
Washington
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@usgs.
gov; HILL, J., U.S. Geological Survey, , USA, jhill@usgs.gov; SINGLETON,
D., U.S. Geological Survey, , USA, dsingleton@usgs.gov; DEROSIER, B.,
U.S. Geological Survey, , USA, bderosier@usgs.gov; SHERROD, B. L., U.S.
Geological Survey, , USA, bsherrod@usgs.gov; PADGETT, J., U.S. Geological
Survey, , USA, jpadgett@usgs.gov; PONTON, C., Western Washington
University, , USA, pontonc@wwu.edu; KLUESNER, J., U.S. Geological Survey,, USA, jkluesner@usgs.gov; STAISCH, L., U.S. Geological Survey, , USA,lstaisch@usgs.gov; DARTNELL, P., U.S. Geological Survey, , USA, pdartnell@
usgs.gov; RITCHIE, A., U.S. Geological Survey, , USA, aritchie@usgs.gov
We present a suite of geophysical and geological evidence for earthquaketriggered mass transport deposits (MTDs) and related turbidite deposition in
two of Washington’s largest lakes: Ozette and Whatcom. Ozette Lake is ideallysituated along the outer coast and above the locked portion of the northern
Cascadia megathrust, but is relatively isolated from active crustal faults andintra-slab earthquakes. Whatcom Lake is farther inboard of the subduction
zone where shaking is expected to be less severe during megathrust ruptures,but is more proximal to active crustal faults. High-resolution bathymetrydata, sub-bottom Chirp profiles, and sediment cores (spanning the last ~14
kyr B.P.) are used to characterize the post-glacial stratigraphic framework ofboth lakes. We examine paleoseismic proxies within the lacustrine sediments,
present an initial comparison of the two datasets, and explore implications
for earthquake timing and recurrence between these two sites in western
Washington. Both lakes contain stacked sequences of MTDs and Mazama ash
marker-beds; the physical characteristics of the event deposits vary considerably depending on proximity to primary depocenters, steep slopes, and subaqueous deltas. In Ozette, more than 150 radiocarbon ages bracket the timingof 34 event deposits emplaced since ~14 kyr B.P; these are easily differentiatedfrom watershed processes and interpreted to have been generated by intense
megathrust shaking, yielding a recurrence interval of ~420 years. Stratigraphic
analyses and radiocarbon dating from Whatcom reveal a more complicateddepositional history. Thick (1–5 m) MTDs and thinner (<10 cm) turbidite
event beds appear to have been generated from different sources of shaking,and possibly from non-seismic watershed processes. Some of the thick MTDs
failed synchronously along submerged slopes during two distinct intervals of
the Holocene, whereas more than 20 turbidites are observed within the same
section. Shaking from nearby earthquakes (crustal faults?) may have triggered
the MTDs, but determining a source for the turbidites is a focus of ongoingand future analyses.
poster 44
Earthquake–triggered Submarine Landslides in Kachemak
Bay, Alaska: New Constrains on Distribution and Timing
Based on Marine Geophysical and Geological Data
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@
usgs.gov; HAEUSSLER, P., U.S. Geological Survey, , USA, pheuslr@usgs.
gov; HILL, J., U.S. Geological Survey, , USA, jhill@usgs.gov; WATT, J., U.S.
Geological Survey, , USA, jwatt@usgs.gov; SNYDER, G., U.S. Geological
Survey, , USA, gsnyder@usgs.gov; SINGLETON, D., U.S. Geological Survey,, USA, dsingleton@usgs.gov; KLUESNER, J., U.S. Geological Survey, ,USA, jkluesner@usgs.gov; DEROSIER, B., U.S. Geological Survey, , USA,bderosier@usgs.gov; LA SELLE, S., U.S. Geological Survey, , USA, slaselle@

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usgs.gov; WITTER, R., U.S. Geological Survey, , USA, rwitter@usgs.gov;
PADGETT, J., U.S. Geological Survey, , USA, jpadgett@usgs.gov
Fjords of the Kenai Peninsula were severely shaken during the 1964 Mw 9.2
Great Alaska Earthquake resulting in widespread subaqueous slope failure.
Destructive tsunamis generated by underwater landslides impacted several of
the coastal communities, including ~6–8 meter-high waves in Resurrection
Bay. Although less destructive, Kachemak Bay and the town of Homer also
experienced intense sea waves in 1964 a few minutes after intense shaking
began, damaging portions of the Homer spit and harbor, and causing overallsubsidence. Early reports suspected submarine landslides in Kachemak Bay
played a role, but direct observational evidence was not available. New geomorphic mapping in Kachemak Bay, based on NOAA multibeam bathymetrydata, identifies a complex of submarine landslides along the southern flankof the bay with mass transport deposits that extend several kilometers into
the basin. The headscarps are mostly concentrated along subaqueous deltas
downstream of the Grewingk and Portlock glaciers. Large earthflows, slumps,
and blocky failures are also observed near the head of the bay.
In summer 2022, the USGS collected a dense grid of Chirp subbottom
profiles in Kachemak Bay to characterize the Holocene sedimentation patterns and examine the spatial and temporal distribution of submarine landslides. A suite of 27 sediment cores were collected to sample the upper ~2
m of sediment and develop preliminary age models. Preliminary analyses ofthese integrated datasets suggest that multiple phases of failure have occurred
throughout the bay in the past. The most recent complex of deltaic failuresappears to have occurred synchronously and most likely during 1964 earthquake (pending results of Cs137 dating). In addition to the stacked sequencesof thick MTDs that are observed in several of the depocenters, 10–12 event
beds (turbidites?) are seismically imaged within a small, isolated sub-basin
and may provide evidence of repeated shaking events. Lastly, we present a
preliminary assessment of landslide-generated tsunami sources and discuss
the potential for Kachemak Bay to contain a valuable marine paleoseismicarchive.
poster 45
Possible Quaternary Faulting on the Picuris-Pecos Fault on
the Eastern Margin of the Española Basin, New Mexico
CLINE, M. L., U.S. Bureau of Reclamation, Colorado, USA, mcline@usbr.gov;
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; REITMAN, N., U.S. Geological Survey, Colorado, USA, nreitman@
usgs.gov; BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.
gov; ELLETT, N., U.S. Bureau of Reclamation, Colorado, USA, nellett@usbr.
gov
The north-south-trending continental Rio Grande Rift (RGR) extends for~1,000 km from Chihuahua, MX to northern Colorado, USA. Within the central RGR, the Española Basin is a ~60 km wide, west-tilted half graben withlow seismicity rates, low slip rates on Quaternary-active faults (0.01–0.1 mm/yr), and a low geodetic extension rate. The western-basin-bounding Pajarito
fault system has generated surface rupture during large (>M6) earthquakes
during the Holocene, and there is strong evidence for late Pleistocene and possibly Holocene surface ruptures on other faults within the basin. On the eastern side of the basin, the Picuris-Pecos fault (PPF) forms the eastern boundaryof the RGR. While most of the extensional strain is partitioned to active faults
on the western side of the basin, we show that new neotectonic mapping on
1 m lidar-derived topography indicates that at least one strand of the PPF has
displaced moraines that are undated, but presumably date to the last glacial
maximum based on regional correlations. Field reconnaissance of the lineaments confirmed the presence of <1 m-high, down-to-the-west and downto-the-east scarps that offset several moraine crests and younger surfaces
between the moraines. On another strand, abrupt, NNE-trending topographic
lineaments persist for at least ~7 km and are part of a discontinuous, ~65
km-long lineament set that traverses the western side of the Sangre De Cristo
Mountains. The lineaments cross disparate geological units and topography,
suggesting they have a tectonic origin. Field reconnaissance confirmed thepresence of the lineaments, which form topographic benches that cross steep,
bedrock-mantled slopes obliquely in places. 10Be exposure dating of boulders
on the displaced moraines and additional mapping along other lineaments on
the trace of the PPF will improve our understanding of the most recent surface
deformation and location of the PPF, in addition to better characterization ofsite-specific and regional seismic sources.

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Seismological Research Lettersposter 46
Lacustrine Paleoseismic Investigation in the South
Washington Cascade Range: Geophysical andSedimentological Observations From Keechelus, Kachess,
and Cle Elum Lakes
DEROSIER, B., U.S. Geological Survey, California, USA, bderosier@usgs.
gov; SINGLETON, D., U.S. Geological Survey, California, USA, dsingleton@
usgs.gov; BROTHERS, D. S., U.S. Geological Survey, California, USA,dbrothers@usgs.gov; SHERROD, B. L., U.S. Geological Survey, Washington,
USA, bsherrod@usgs.gov; HILL, J., U.S. Geological Survey, California, USA,jhill@usgs.gov; DARTNELL, P., U.S. Geological Survey, California, USA,
pdartnell@usgs.gov
Lacustrine sediments within Keechelus, Kachess, and Cle Elum Lakes, locatedwithin the Yakima River Basin in the western Cascade Range (WA, USA), may
hold records of strong ground motion occurring within the Pacific Northwest.
Multibeam bathymetry, high-resolution seismic profiles, and sediment coredata recently collected from these three deepwater lakes image subaqueous
landslides, buried mass transport deposits (MTDs), and tephra deposits,
which aided the correlation of stratigraphic markers amongst the three lakes.
Using 42 (1.0-1.8m) percussion-driven gravity cores, we analyzed the physicalproperties and age of sediment deposited during the last ~7.5 kyr B.P. Withineach lake, we find a 50-100 m-thick sedimentary sequence that includes 10-15
m of Holocene sediments that conformably overlay thick late Pleistocene sediments. Three Mt. Helens tephra deposits are found in each lake, and Mazama
ash was sampled in Lake Keechelus.
Stacked sequences of MTDs within each lake were mapped in 3D todetermine each deposit’s source location (e.g., delta versus non-delta). MTDs
sourced from multiple locations are inferred to be shaking–induced. While
we do not observe definitive evidence for deposits generated by historicalmegathrust (e.g., 1700), intraslab, or crustal (e.g., 1872) events, we present
strong evidence for comparatively large and synchronous megaturbidite
deposition in each lake at 2468-2716 cal yr B.P. The coincident timing, thelarge volume of remobilized sediment, and the depositional style suggest considerable ground motion occurred in the Yakima River Valley; therefore, we
favor a proximal source of this shaking event (e.g., an active structure within
the Olympic-Wallowa Lineament). However, we continue to assess otherpotential sources for shaking, such as the Southern Whidbey Island Fault ora Cascadia megathrust event. This study highlights the value of lacustrine
paleoseismic approaches in regions where surficial fault deformation has been
obscured in the geologic record or where traditional paleoseismic techniques
are not feasible.
poster 47
Comprehensive High-Resolution Geophysical Mapping and
Sediment Coring in Lake Chelan, Wa: A Deep, Steep
Lacustrine Environment Dominated by Mass Transport
Processes
DEROSIER, B., U.S. Geological Survey, California, USA, bderosier@usgs.gov;
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@usgs.
gov; SHERROD, B. L., U.S. Geological Survey, Washington, USA, bsherrod@
usgs.gov; SINGLETON, D., U.S. Geological Survey, California, USA,dsingleton@usgs.gov; DARTNELL, P., U.S. Geological Survey, California,
USA, pdartnell@usgs.gov; LONG, P., Lake Chelan Research Institute,
Washington, USA, phillong@nwi.net; ANGSTER, S., U.S. Geological Survey,
Washington, USA, sangster@usgs.gov
Lake Chelan (WA, USA), the third deepest lake in the contiguous UnitedStates, may hold records of glacial retreat and advance, volcanic eruptions, andearthquakes. For example, the 1872 Washington State Earthquake (M6.5–7)
ruptured the Spencer Canyon fault near the southern end of Lake Chelan.
Shaking from the 1872 earthquake was of such intensity that it altered local
aquifers, triggered liquefaction of unconsolidated sediments, and large seiches
within Lake Chelan. Lake Chelan may provide a geological dataset to calibrate
the lake’s lacustrine sedimentary response to the 1872 earthquake. In 2023,
the USGS conducted a 3-week field operation in Chelan to acquire high-resolution multibeam bathymetry data, Chirp sub-bottom profiles, and sedimentcores. These new data reveal pervasive morphological evidence for slope failure, mass transport deposits (MTDs), subaqueous deltas, and relic glacial features (e.g., kettles). Here, we present preliminary results of detailed geomorphic and stratigraphic mapping throughout the lake. Chelan can be divided
into two physiographic basins: the deeper (up to 460 m) and narrower (~2–3
km wide) Lucerne Basin to the north, and the shallower (up to 130 m), wider(5–10 km) Wapato Basin to the south. The Lucerne Basin is dominated by very
steep flanks and subaqueous deltas fed by fluvial catchments; the depocenters
are dominated by coarser-grained sediment and stacked MTDs. The Wapato

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Basin contains numerous slide scars, scarps, debris aprons along the gently
sloping margins, and abundant kettle structures infilled with fine-grainedlacustrine sediments. Sediment cores sampled several of the youngest MTDs;
their relation to the 1872 earthquake is pending results of 14C and radionuclide dating. Furthermore, cores from condensed sections of the Wapato
basin contain numerous ash deposits and bottom out in late Pleistocene glacial sediment. Our initial results suggest that Chelan contains several sourcesof MTDs, with the Lucerne Basin most affected by fluvial processes and the
Wapato Basin being a better candidate for paleoseismic investigations.
poster 48
Introducing the Science Goals for the Cascadia Region
Earthquake Science Center (Crescent) Cascadia
Paleoseismology Working Group (Cpal)
DURA, T., Virginia Tech, Virginia, USA, tinadura@vt.edu; HAWKES, A.,
University of North Carolina Wilmington, North Carolina, USA, hawkesa@
uncw.edu; WITTER, R., U.S. Geological Survey, Alaska, USA, rwitter@usgs.
gov; STAISCH, L., U.S. Geological Survey, Oregon, USA, lstaisch@usgs.gov;
KELSEY, H., California State Polytechnic University, Humboldt, California,
USA, Harvey.Kelsey@humboldt.edu; HEMPHILL-HALEY, E., California
State Polytechnic University, Humboldt, California, USA, Eileen.HemphillHaley@humboldt.edu
Funded in 2023 by the National Science Foundation, the Cascadia Region
Earthquake Science Center (CRESCENT) is the nation’s first subduction zone
earthquake hazards center. The goals of CRESCENT are todevelop a better
foundational understanding of Cascadia subduction zone earthquakes, promote diversity and train the next generation of geoscientists, and providea systematic approach to collaboration between researchers in academia
and government agencies with mandates to provide hazard information to
the public. A fundamental challenge in characterizing hazards along the
Cascadia subduction zone is the lack of an instrumentally recorded megathrust earthquake. Due to this limitation, we must rely on paleoseismic studies to characterize the frequency, timing, and associated coseismic displacement of prehistoric Cascadia earthquakes. Under CRESCENT, the Cascadia
Paleoseismology Working Group (CPAL) will employ detailed stratigraphic
mapping of subsidence and tsunami evidence and new high-resolution analysis of cores including CT scanning, geochemical, and microfossil analyses toreconstruct coseismic land-level change and tsunami inundation during past
Cascadia subduction zone earthquakes. To help build larger quantitative paleoseismic datasets of subsidence along the Cascadia subduction zone, CPAL
will develop a shared, community-built diatom and foraminifera databasethat will increase accessibility and standardize microfossil analysis. CPAL will
also work with the members of the USGS Powell Center Cascadia Earthquake
Hazards group to develop and expand an online database of geologic observations that provide evidence for subsidence, shaking, and ground failure frompast Cascadia subduction zone earthquakes and inundation from associatedtsunamis. CPAL will directly collaborate with modelers to integrate the new
and improved quantitative paleoseismic datasets and utilize the database ofgeologic observations to validate numerical models of subduction zone earthquakes and tsunamis and better assess hazards along the Cascadia subductionzone.
poster 49
Detection Thresholds for Large to Great Subduction
Earthquakes in South-Central Alaskan Marshes
ENGELHART, S. E., Durham University, Durham, United Kingdom,
simon.e.engelhart@durham.ac.uk; WOODROFFE, S. A., Durham University,
Durham, United Kingdom, s.a.woodroffe@durham.ac.uk; WOOD, K. L.,
Durham University, Durham, United Kingdom, kaitlin.l.wood@durham.
ac.uk; SHENNAN, I., Durham University, Durham, United Kingdom, ian.
shennan@durham.ac.uk; WITTER, R., U.S. Geological Survey, Alaska, USA,rwitter@usgs.gov
Coastal marshes provide records of the recurrence of great earthquakes in the
Prince William Sound section of the Alaskan megathrust, with widespread
evidence of surface deformation >1 m during seven great earthquakes in thelast 4000 years. In the Kodiak section, there is paleoseismic evidence for four
ruptures which occurred independent of the Prince William Sound sectionin the past 2000 years, each resulting in decimeter-scale subsidence. Basedon records from subduction zones worldwide, it is suggested that subduction
earthquakes ≤Mw8.5 displace the coast by <0.3 m and likely leave equivocal orno geologic evidence in coastal marshes. Recent studies suggest that in certain
circumstances a detection limit of ~0.1 to 0.2 m may be possible. A better
understanding of the lower limit of detection is essential for assessing seismic

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hazards of Alaskan earthquakes that are smaller than Mw9 but still pose significant risk.
We undertook fieldwork during September 2023 at Girdwood andOcean View, Anchorage to test a methodology aimed at making marsh recordsof past great earthquakes in this region more complete. We focus efforts on theupper tidal marsh zone into the perimarine zone (where freshwater wetlands
persist under the control of relative sea level). In these coastal peat forming
environments, the most precise quantitative estimates of submergence can bereconstructed. At Ocean View, we traced the stratigraphic contact of the 785 ±10 cal yr BP earthquake inland from the seaward extent of the marsh where itis expressed as a peat-to-silt contact until it changes to a peat-to-peat contact.
This peat-to-peat contact, representing a known earthquake and associatedsubmergence serves as an analogue to describe subsidence-derived changes indiatom assemblages from longer peat records. This allows us to assess whether,in perimarine to upper tidal marsh zones (where organic sedimentation dominates for the majority of an earthquake cycle), we can identify and quantify
previously unknown episodes of decimeter-scale coseismic submergence representing earthquakes ≤Mw8.5 in this region over the last millennium.
poster 50
Geotechnical Properties of Quaternary Marine Sedimentsof the Eel River Plateau, Southern Cascadia Margin
FITZGERALD, B. L., Ohio State University, Ohio, USA, fitzgerald.263@
osu.edu; SAWYER, D. E., Ohio State University, Ohio, USA, sawyer.144@
osu.edu; HILL, J. C., U.S. Geological Survey, California, USA, jhill@usgs.gov;
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@usgs.
gov; SINGLETON, D., U.S. Geological Survey, California, USA, dsingleton@
usgs.gov
Submarine landslides are frequently triggered by earthquakes but there canbe a variety of factors that trigger or precondition a slope to failure including
weak layers in the sediment, storm waves, and sediment unroofing. Although
earthquakes can trigger submarine landslides, active margins have fewer submarine landslides than passive margins despite having higher levels of seismicity. This observation supports the concept of seismic strengthening whichsuggests that sediment exposed to repeated earthquake shaking dewaters
and densifies causing enhanced strength. We focus on the southern end of
the Cascadia Subduction Zone, where the highest historical seismicity rate
along the Cascadia margin has occurred due to the northward migration of
the Mendocino Triple Junction, resulting in a broad regional uplift. Moreover,there is a high volume of terrestrial sediment input in this area from the EelRiver and other fluvial systems that feed into the southern end of the Cascadia
Subduction Zone. Despite the high levels of seismicity and the high volumeof sediment accumulation, recent studies document a distinct lack of slope
failure on the upper slope. Given this observation, we aim to understand thephysical properties that contribute to the slope stability in this region, including whether there is enhanced strength or other mechanical differences thatmight play a role in enhanced slope stability. We measure undrained shear
strength using a fall cone device, grain size, and Atterberg limits and integratethem with CT scans, photographs, physical property logs, and radiocarbon
dates. Using this collected data we will be able to provide a new insight into
the slope stability of the region that will further the understanding of the possible implications for regional geohazards and how they can affect offshore
infrastructure.
poster 51
A Refined Chronology of Tsunami Deposition at Discovery
Bay, Washington StateGARRISON-LANEY, C., University of Washington, Washington, USA,
cegl@uw.edu; PADGETT, J. S., U.S. Geological Survey, California, USA,jpadgett@usgs.gov; PILARCZYK, J. E., Simon Fraser University, Burnaby,
Canada, jessica_pilarczyk@sfu.ca; GIANG, A., Simon Fraser University,
Burnaby, Canada, anthony_giang@sfu.ca
A tidal marsh at the head of Discovery Bay preserves the largest number oftsunami deposits in Washington State (USA). The location is an excellent
geologic recorder of tsunamis because of its wave-amplifying, funnel-shaped
morphology, an abundant sediment supply, and a tidal marsh that has sufficient accommodation space and preservation potential to preserve deposits.
At Discovery Bay there are as many as ten 2-10 cm thick tsunami deposits, andat least six thinner layers < 2 cm thick that span the last ~3,000 years. Someof the thicker deposits undoubtedly resulted from Cascadia subduction zone
earthquakes, based on both tsunami modeling and deposit ages. However, thenumber of deposits at Discovery Bay exceeds the number of known Cascadia
earthquakes in the same time span, so additional tsunami sources including
crustal faults, tsunamigenic landslides, and distant Pacific subduction zones

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may also be represented. One of the thinner deposits is probably from the1964 Alaska Prince William Sound tsunami, which was observed at the site.
Two decades ago, tsunami deposits were first described and dated
at Discovery Bay. We build on previous efforts with new observations andchronologic data. In 2007, part of the marsh that had been previously diked
was restored to marshland, thus allowing access to a wider distribution ofdeposits than originally described. We present new stratigraphic mapping oftsunami deposits from two 3 meter-long vibracores, 38 gouge cores, and three
cleared channel bank outcrops. To confirm visual stratigraphy in the vibracores, we obtained high resolution CT density imagery and X-ray fluorescencedata. New bracketing maximum and/or minimum radiocarbon ages and
137Cs concentration data were used to create multiple Bayesian age-depth
models, each with different assumptions, to (1) determine which model ismost appropriate for this dataset and (2) identify the differences in age estimates that may be imposed by model choice. Our new chronology increases
confidence in regional source correlations and identifies deposits that likely
have non-Cascadia sources.
poster 52
Reconnaissance Implies a Potentially Complete Record of
Holocene Earthquakes in Esther Lake Above the AlaskaAleutian Megathrust
HAEUSSLER, P. J., U.S. Geological Survey, Alaska, USA, pheuslr@usgs.
gov; WITTER, R., U.S. Geological Survey, Alaska, USA, rwitter@usgs.gov;
SINGLETON, D. M., U.S. Geological Survey, California, USA, dsingleton@
usgs.gov; MARCUSON, R. K., U.S. Geological Survey, California, USA,rmarcuson@usgs.gov; BROTHERS, D. S., U.S. Geological Survey, California,
USA, dbrothers@usgs.gov; KAUFMAN, D., Northern Arizona University,
Arizona, USA, darrell.kaufman@nau.edu
We investigated Esther Lake, Alaska, to evaluate its potential for lacustrine
paleoseismology, specifically for its likelihood to yield a record of megathrust earthquakes. The lake is trenchward of prior lacustrine paleoseismology
studies in southcentral Alaska, and it lies in the epicentral region of the 1964
Mw9.2 earthquake. Esther Lake is located in north-central Prince WilliamSound, formed after deglaciation around 12.9 kya, and lies in a mountainous region dominated by high precipitation and perennial headwater snowfields. Despite such hydrologic conditions, Esther Lake hosts no significant
stream deltas, and thus little sediment enters the lake. We collected multibeam
echosounder (MBES) bathymetry data, 2-16 kHz Compressed High-Intensity
Radar Pulse (CHIRP) seismic data, and 20 short (<2 m) percussion-driven
gravity cores that we scanned via computerized tomography (CT) and multisensor core logger.
The bathymetry and CHIRP data reveal sediment (<12m thick) is deposited in 9 isolated basins no more than 100 m across. The distinctive seismic
stratigraphy of each basin is nearly identical, showing a succession of acoustically transparent ~1 m-thick packages separated by high-amplitude reflections. We divide the sediment, which is generally organic-rich and mineralpoor (<5%) into two main types: “event deposits” and “intra-event deposits”.
The intra-event deposits are typically dark brown fine-grained organic richmaterial, in which we find no identifiable macrofossils, and almost no mineralmatter except distinctive light-colored tephras that display high radiodensity
and magnetic susceptibility. We interpret these horizons as the high-amplitude CHIRP reflectors. The event deposits are brown organic-rich turbidites
that fine upward and commonly contain organic macrofossils and granitederived micas at the base. Initial radiocarbon samples have been submitted fordating. We infer that Esther Lake has the potential to have a nearly complete
record of Holocene earthquakes dominated by megathrust events.
poster 53
Cataloging the Date of Last Event (DOLE) Across theWestern U.S.
HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@usgs.gov;
BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.gov; TAN,
M., U.S. Geological Survey, Colorado, USA, mtan@usgs.gov
The elapsed time since the most recent earthquake (the open interval) on
a given fault is a primary constraint required for time-dependent seismic
hazard analyses. Additionally, the timing of the most recent earthquake andpaleoseismic chronologies are key targets in earthquake geology research.
The high density of paleoseismic studies in California and along the Wasatch
front, along with historical earthquakes, have focused attention of prior timedependent probabilistic seismic hazard analyses (PSHA) in these regions.
These hazard models generally yield a relative decrease in the probability ofmoderate-to-large ruptures on faults with recent ruptures (e.g., 1999 Hector
Mine rupture, CA), and a relative increase of rupture rates on faults that may

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Seismological Research Lettersbe late in the seismic cycle (e.g., Brigham City section of Wasatch fault, UT).
To enable the proposed expansion of time-dependent PSHA analysis acrossthe western U.S., we augmented the western U.S. NSHM fault sections database with paleoseismic and historic date of last event (DOLE) data. We added~70 sites to the ~60 existing sites previously compiled within California andalong the Wasatch fault. Additionally, we added ~10 historical rupture extents
to the compilation. This compilation includes paleoseismic investigations as
points and expands those site observations onto existing NSHM fault subsection geometries as lines. Translating site observations to rupture extents
remains challenging, and we take a minimum-length approach as was done inprevious time-dependent PSHA in California. On faults without a paleoseismic or historic event, we use a regionalized onset of historical settlement todemarcate the minimum time since a large earthquake has occurred. In addition to implementation in time-dependent PSHA, we hope this compilation
will be useful to the earthquake geology community as we develop modelsof earthquake occurrence through space and time, better constrain geologic
slip rates, and plan future paleoseismic trench investigations, among otherapplications.
poster 54
Tectonic Oversteepening, Sediment Accretion, and Lower
Slope Failure in the Cascadia Subduction Zone—A Recipefor Abyssal Seismoturbidites and Insights Into Earthquake
History
HILL, J. C., U.S. Geological Survey, California, USA, jhill@usgs.gov;
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@usgs.
gov; WATT, J. T., U.S. Geological Survey, California, USA, jwatt@usgs.gov;
PAULL, C. K., Monterey Bay Aquarium Research Institute, California, USA,paull@mbari.org; CARESS, D., Monterey Bay Aquarium Research Institute,
California, USA, caress@mbari.org; PADUAN, J. B., Monterey Bay Aquarium
Research Institute, California, USA, paje@mbari.org
Seismic strengthening and related processes are often cited to explain thedearth of large submarine landslides on active margins; however, recent
examination of seafloor bathymetry has revealed extensive mass wasting of
the continental slope along the Cascadia Subduction Zone. Hill et al. (2022)
suggested these failures may be the primary source of abyssal seismoturbidites
that comprise the longest earthquake records in the region. Deriving robust
earthquake recurrence estimates from these records though, requires rigorous investigation of the processes of slope development and failure preconditioning. From 2019-2023, the USGS and MBARI conducted extensive geophysical surveys and geologic sampling along the Cascadia margin, including>6700 km of Sparker MCS and Chirp subbottom data, 470 sediment cores(380 <2m ROV-based vibracores, 90 6-8m piston cores), along with AUV 1-mbathymetry and subbottom data. These data offer an unprecedented look at
the structure and morphology of the deformation front and provide insightto the mechanics of earthquake triggered slope failure. Northern Cascadia ischaracterized by steeply dipping, asymmetric, landward vergent thrust folds
with steeper seaward limbs prone to translational block slides along bedding
planes. In central Cascadia, low angle, imbricate thrust faults have created a
stepped terrace morphology with steep ledges. Failures occur at the forelimbof the fold, exposing truncated strata at the seafloor. In southern Cascadia,
steeply dipping thrust faults create lower relief folds, yet failures occur on the
4-6° seaward face of the frontal thrusts. Two factors appear key in preconditioning the slopes for failure: (1) the dynamic uplift and permanent deformation creates oversteepening; (2) accretion of abyssal plain sediment into
the outer wedge provides unlimited recharge of relatively weak and unstablematerial. These two processes appear to be keeping pace with earthquake triggering and outweigh the effects of compaction induced strengthening.
poster 55
Marine Seismoturbidites in the Cascadia Subduction Zone:
Filling the Gaps and Refining the Offshore Records ofEarthquake Shaking
HILL, J. C., U.S. Geological Survey, California, USA, jhill@usgs.gov; WATT,
J. T., U.S. Geological Survey, California, USA, jwatt@usgs.gov; PAULL, C.
K., Monterey Bay Aquarium Research Institute, California, USA, paull@mbari.org; CARESS, D., Monterey Bay Aquarium Research Institute,
California, USA, caress@mbari.org; BROTHERS, D. S., U.S. Geological
Survey, California, USA, dbrothers@usgs.gov; GWIAZDA, R., Monterey
Bay Aquarium Research Institute, California, USA, rgwiazda@mbari.org;
LUNDSTEN, E., Monterey Bay Aquarium Research Institute, California,
USA, eve@mbari.org; NIEMINSKI, N., U.S. Geological Survey, California,
USA, nora.nieminski@alaska.gov; PADGETT, J. S., U.S. Geological Survey,
California, USA, jpadgett@usgs.gov; PADUAN, J. B., Monterey Bay Aquarium

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Research Institute, California, USA, paje@mbari.org; RODRIGUEZ, K., U.S.
Geological Survey, California, USA, karodriguez@contractor.usgs.gov
The Cascadia Subduction Zone has a well-developed marine paleoseismic
record, yet uncertainties in age and correlation among deposits over long
distances, as well as questions about triggering mechanisms make it difficult
to distinguish the length and magnitude of shaking in past events. Hill et al.
(2022) proposed that pervasive mass wasting of the lower slope in Cascadia
is a primary source of abyssal seismoturbidites that would avoid many of thepitfalls and arguments commonly made against turbidite stratigraphy andallow for new sampling locations that fill critical spatial gaps in the existing
records. To test this hypothesis, we collected 8-9m piston cores from 20 newsites in central and northern Cascadia, on the abyssal plain proximal to thedeformation front and from isolated lower slope basins. Several of these sites
are complemented by detailed AUV bathymetry and subbottom data, alongwith transects of closely spaced, ROV-based <2m vibracores. Our preliminary
age dating shows these new sites contain a robust record of Holocene abyssal
turbidites that are most likely derived from strong earthquake shaking. Initialradiocarbon dating and age models from several of our sites suggest chronologic correlation of the seismoturbidites along large stretches of the margin.
There are distinct differences in deposit characteristics (e.g., range of grain
sizes or number of pulses) that vary over both time and space, and likely reflect
the inputs of multiple slope failure sources during a given event. The type anddegree of earthquake triggered slope failure is variable along the margin, suchthat some locations may contain extra and/or missing events, highlighting theneed for detailed chronology. The spatial density of these new sites combinedwith the existing records offers a valuable opportunity to assess variability inearthquake rupture patterns along the Cascadia margin and provide insight
into extent of slope failure along the margin. Our results also suggest similar
seismoturbidite records may be found outside of submarine canyon systems
on other subduction margins with a similar steep slope morphology.
poster 56
Urban Paleoseismology of the Taylorsville Fault - New Data
and Challenges from one of the Last Remaining Trench
Sites on the West Valley Fault Zone, Utah
HISCOCK, A. I., Utah Geological Survey, Utah, USA, adamhiscock@utah.
gov; KLEBER, E. J., Utah Geological Survey, Utah, USA, emilykleber@utah.gov; MCDONALD, G. N., Utah Geological Survey, Utah, USA,
gregmcdonald@utah.gov; HYLLAND, M. D., Utah Geological Survey, Utah,
USA, mikehylland@utah.gov; MCLEAN, J. H., University of Utah, Utah,
USA, jhopemclean@gmail.com; STARACE, A., University of Utah, Utah,
USA, andrewstarace@gmail.com; DUROSS, C. B., U.S. Geological Survey,
Colorado, USA, cduross@usgs.gov; MAHAN, S. A., U.S. Geological Survey,
Colorado, USA, smahan@usgs.gov; RASMUSSEN, K., Utah Geological
Survey, Utah, USA, kristir@utah.gov; WILLIAMS, E. F., Utah Geological
Survey (resigned), Utah, USA, egwilliams1227@gmail.com; GIRAUD, R. E.,
Utah Geological Survey (retired), Utah, USA, rich124swe@gmail.com
The intrabasin West Valley fault zone (WVFZ) in Salt Lake Valley, Utah, comprises two subparallel main strands—the Granger fault (western strand) andTaylorsville fault (eastern strand)—and is antithetic to the Wasatch fault zone
(WFZ). Both strands trend through the densely populated Salt Lake Valley,
making sites suitable for fault trenching very sparse. A scarp trenched at the
Airport East site on the Taylorsville fault in 2015 has now been destroyed byurban development. In 2022, we conducted a fault-trench study at the Indiana
Avenue site, one of the last remaining suitable trench sites on the Taylorsvillefault. This site was previously a green-waste landfill; however, a relatively
undisturbed, small (1.5 m) fault scarp crosses the site. The elevation of the site(1288 m) suggests it was submerged by multiple pluvial lake cycles during thelate Pleistocene and Holocene, including lakes Bonneville and Gilbert. The site
is at or just below the shoreline of the early Holocene highstand of the Great
Salt Lake (1288–1289 m), and below shorelines related to the Gilbert lake episode (1294–1297 m). Our trenches exposed a sand deposit likely related to theregression of Lake Bonneville, a clay-marl deposit likely related to the Gilbert
episode and very similar to deposits in other WVFZ trenches, a paleo-Jordan
River floodplain silty-sand deposit, and several clay-rich wetland deposits.
Both trenches showed evidence of fault-related monoclinal warping, but only
one trench showed evidence of discrete faulting in the footwall. Trench depth
was limited due to shallow groundwater at the site. Due to these constraints,
our trenches only revealed evidence for one or possibly two surface-rupturing
earthquakes. Radiocarbon and optically stimulated luminescence samples
provide age control on deposits and earthquake timing. These data will help
us compare ages of deposits and earthquake timing to the Airport East andother WVFZ studies, and improve our understanding of the seismogenic relationship between the WVFZ and WFZ.

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poster 57
Middle to Late Pleistocene Faulting on the Puye Fault
Zone, Española Basin, New Mexico
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; CLINE, M. L., Bureau of Reclamation, Colorado, USA, mcline@
usbr.gov; REITMAN, N., U.S. Geological Survey, Colorado, USA, nreitman@
usgs.gov; BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.
gov; SION, B., Desert Research Institute, Nevada, USA, brad.sion@dri.edu;
MAHAN, S., U.S. Geological Survey, Colorado, USA, smahan@usgs.gov;
GRAY, H., U.S. Geological Survey, Colorado, USA, hgray@usgs.gov; ELLETT,
N., Bureau of Reclamation, Colorado, USA, nellett@usbr.gov
The Española Basin in the central Rio Grande Rift (RGR) of northern New
Mexico is a slowly deforming, 60-km-wide region with low geodetic extension rates (~1 mm/yr) and low-slip-rate (0.01–0.1 mm/yr) Quaternary-active
faults. While previous work suggests that deformation is accommodated by
the Pajarito fault on the western side of the basin, new evidence from neotectonic mapping on 1-m lidar-derived topography and offset geomorphic
surfaces suggests that additional RGR faults may have higher slip rates thanpreviously thought. We focus on the Puye fault, a distributed fault system inthe central-western Española Basin. The fault zone has at least four subparallel primary strands that offset the same geomorphic surface with a primarily
down-to-the-east sense of motion. The fault trends north-south and mapped
scarps extend at least 12 km. The highest scarps record up to 12 m of net vertical separation. We excavated three 1- to 2-m-deep pits atop the faulted surface to collect cosmogenic 10Be and optically stimulated luminescence (OSL)
samples to constrain surface ages, pedogenic character, and calculate a slip
rate on the Puye fault system. Based on soil development and correlation withsimilar regional surfaces, we estimate this surface could be Middle Pleistocene(~130 - 774 ka), pending geochronology results. If the age for the faulted
surface is middle-late Quaternary, slip rates may exceed known rates on the
Pajarito fault (0.1 mm/yr). In a wash that intersects the primary scarp, we
observed ~1 m of down-to-the-east offset of fluvial sand and gravel units in a
cutbank exposure. Pending OSL ages from the cutbank will test the hypothesisthat this exposure records recent fault activity. The presence of smaller offset
amounts on potentially younger inset deposits, if confirmed, would indicate
the Puye fault system has accommodated several large earthquakes during the
middle to late Pleistocene. The results of this work will be used to characterize
the Puye fault and reduce uncertainties in inputs for site-specific probabilistic
seismic hazard analyses at nearby dams and regional seismic hazard models.
poster 58
Chirp Correlation and Acoustic Characterization of
Lacustrine Turbidite Deposits in Lake Ozette, Wa Using
Ct-Derived Density, Synthetic Seismograms, and Advanced
Chirp Processing
KLUESNER, J., U.S. Geological Survey, California, USA, jkluesner@usgs.gov;
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@usgs.
gov; SNYDER, G., U.S. Geological Survey, California, USA, grsnyder@usgs.
gov; LA SELLE, S., U.S. Geological Survey, California, USA, slaselle@usgs.gov;
SINGLETON, D., U.S. Geological Survey, California, USA, dsingleton@usgs.
gov; BALSTER-GEE, A., U.S. Geological Survey, California, USA, abalstergee@usgs.gov; SHERROD, B. L., U.S. Geological Survey, Washington, USA,bsherrod@usgs.gov
Lacustrine turbidite deposits provide a high-resolution record of earthquake
shaking. Turbidite deposits are characterized by graded, fining-upwards
sequences deposited by turbulent flows, which can generate pronounced
impedance contrasts in chirp data depending on the composition and thickness relative to background sediment. Turbidite acoustic expression is also
controlled by the characteristics of the chirp sound source and the signal
processing applied. Identifying turbidite beds within chirp data using a setof specific acoustic properties enables us to map the spatial and temporal distribution of the sandy turbidite beds and allows the selection of coring sites
for sampling and dating. We utilize two composite sediment cores measuring
12-14 m in length, additional short cores, and chirp profiles from Lake Ozette
in NW Washington to quantitatively characterize and precisely compare
proximal and distal turbidite deposits from their source. Advanced processing is applied to the chirp data to broaden the frequency spectrum, allowing for detection of sand beds thinner than 1 cm. Where chirp data intersect
the core sites, a stochastically representative wavelet is extracted for synthetic
trace modelling. Gas expansion cracking in cores introduces inaccuracies ingamma bulk density measurements, resulting in synthetic seismograms that
do not correlate with the chirp data. To obtain reliable density measurements,
we use CT scans of the cores to determine the intensities of uncracked sediments, followed by the fitting of a regression curve limited to the gamma den-

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sity values with void space in CT images < 2.5%. This regression curve predicts bulk density values using the CT intensity values that are combined with
p-wave velocities to generate a synthetic seismogram. The resulting synthetics
allow use to accurately correlate with the core-chirp data and demonstrate theacoustic variations of turbidites from proximal to distal sites. Additionally,
our findings emphasize both the ability and limitation of using chirp data toobserve variations in thickness, density, and vertical separation of turbidite
deposits.
poster 59
How Do Large Lakes in the Seattle Area Respond to
Different Sources of Seismic Shaking? Revisiting Lake
Washington and Lake Sammamish With New HighResolution Data
KLUESNER, J., U.S. Geological Survey, California, USA, jkluesner@usgs.
gov; HILL, J., U.S. Geological Survey, California, USA, jhill@usgs.gov;
BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@usgs.
gov; SHERROD, B. L., U.S. Geological Survey, Washington, USA, bsherrod@
usgs.gov; CONRAD, J., U.S. Geological Survey, California, USA, jconrad@usgs.gov; DEROSIER, B., U.S. Geological Survey, California, USA, bderosier@usgs.gov; SINGLETON, D., U.S. Geological Survey, California, USA,dsingleton@usgs.gov; DARTNELL, P., U.S. Geological Survey, California,
USA, pdartnell@usgs.gov
The Puget Sound region is susceptible to a variety of seismic hazards, including intraslab and crustal earthquakes, as well as megathrust earthquakes
from the Cascadia Subduction Zone. To better characterize these hazards,
the USGS is working on a multiyear project at sites spanning the Olympic
Peninsula coast to the eastern Cascades to understand how sources of groundmotion from different faults manifest in the lake basins. Here, we present
results from two large lakes in the Seattle area: Lake Washington and Lake
Sammamish because both lakes are located within a zone projected to experience strong to very strong ground motions during a Cascadia megathrust
event. Additionally, these lakes are also surrounded by several crustal faults,
and have experienced historical shaking due to deep intraslab earthquakes.
The USGS led two multi-week field campaigns in 2021 (Lake Sammamish)and 2024 (Lake Washington) acquiring high-resolution bathymetry data,
chirp subbottom profiles, and sediment cores. In both lake basins, bathymetricdata reveal multiple slope failures along the flanks, while chirp data uncoverdetails of post-glacial sedimentation patterns, including evidence for older,buried mass transport deposits and deformation associated with the Seattle
fault. Mazama ash deposits identified throughout the Lake Sammamish stratigraphy, in cores and subbottom data, provide chronological markers that areused to build preliminary age-depth models. Our preliminary interpretationsuggests that most of the larger subaqueous mass transport deposits visible
in the bathymetry are pre-Holocene, whereas previous work suggests thatlarge failures observed in Lake Sammamish may be linked to earthquake(s)in the Seattle and Saddle Mountain fault zones in 923-924 CE. The apparent
absence of subsequent large-scale slope failures here raises questions aboutbasin’s response to shaking from Seattle fault ruptures. Ongoing work includes
detailed stratigraphic mapping, additional age dating of turbidite event deposits, and comparison with a series of lakes across latitudinal and longitudinal
gradients in the Pacific Northwest.
poster 60
Variations of the 1959 m7.3 Hebgen Lake Earthquake
Record in Four Proximal Lacustrine Systems, West
Yellowstone Region, USA
NICOVICH, S. R., U.S. Geological Survey, Colorado, USA, snicovich@usgs.
gov; DUROSS, C. B., U.S. Geological Survey, Colorado, USA, cduross@usgs.
gov; THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.
gov; HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@usgs.
gov; LINDBERG, N. S., U.S. Geological Survey, Colorado, USA, nlindberg@
usgs.gov; TAN, M. M., U.S. Geological Survey, Colorado, USA, mtan@usgs.
gov; RODYSILL, J. R., U.S. Geological Survey, Virginia, USA, jrodysill@usgs.
gov; GAVILLOT, Y., Montana Bureau of Mines and Geology, Montana, USA,ygavillot@mtech.edu
The M7.3 1959 Hebgen Lake earthquake in southwestern Montana is oneof the largest earthquakes recorded within the Intermountain West, UnitedStates. Ground-shaking and hanging-wall subsidence caused an approximately 6-meter-high seiche in Hebgen Lake, liquefaction features in adjacent valleys, a massive landslide that dammed the Madison River to form
Earthquake Lake, and increased activity in hydrothermal systems of the
Yellowstone caldera. Accordingly, lakes within the southern Madison and

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Seismological Research Letterseastern Centennial Valleys, ≤25 km from the epicenter, experienced shakingof Modified Mercalli Intensity VI-VII. We characterize how the 1959 earthquake signature is recorded in the stratigraphic record of four lakes in this areathat have varying morphometric and hydrologic properties such as depth,
shape, surface area, and catchment area. We present data from 24 sedimentcores along transects of Wade Lake (9 cores), Cliff Lake (5 cores), Hebgen
Lake reservoir (3 cores), and Henry’s Lake (7 cores). Each lake records background sediment consisting of laminated to thinly bedded silt and sand with
distinct sedimentary disturbances such as 1) normally graded sand beds, 2)
massive, poorly sorted deposits, and 3) macro floral debris, all likely indicators of the 1959 Hebgen earthquake. To test this hypothesis, we use fallout
radionuclide 137Cs, where concentrations become measurable after 1954 CE
and the maximum value indicates 1963 CE. Preliminary 137Cs concentrations
and their locations in the Henry’s Lake core support the interpretation of the
disturbance horizons being formed by the 1959 earthquake. Fallout 137Cs data
are pending to constrain the timing of disturbance horizons for the remaining three lakes. Comparing characteristics of the 1959 event deposit in thesefour lakes will illuminate how differences in lake morphometry or setting may
impact lacustrine records of strong ground shaking. Ultimately these observations will help calibrate how Intermountain West lakes record strong shaking
and facilitate comparisons to both terrestrial and lacustrine paleoseismic data
globally.
poster 61
Evidence of Past Earthquakes Preserved in Coast Redwood
Trees Along the Northern San Andreas Fault
CARROLL, A., California State Polytechnic University, Humboldt, California,
USA, allyson.carroll@gmail.com; PHILIBOSIAN, B., U.S. Geological
Survey, California, USA, bphilibosian@usgs.gov; SILLETT, S., California
State Polytechnic University, Humboldt, California, USA, prof.sillett@gmail.
com; ANTOINE, M., California State Polytechnic University, Humboldt,
California, USA, marie.antoine@humboldt.edu; KOZACI, O., Pacific Gas &Electric Company, California, USA, ozgur.kozaci@pge.com; WILLARD, J.,
U.S. Geological Survey, California, USA, j.willard@usu.edu; CUNETTA, N.,
U.S. Geological Survey, California, USA, cunettn@wwu.edu; ELLIOTT, A.,
U.S. Geological Survey, California, USA, ajelliott@usgs.gov
Prior to the 1906 San Francisco earthquake, the rupture history of the North
Coast section of the San Andreas Fault is not well constrained. Current age
bounds for the penultimate event are broad, generally spanning over a century(e.g., 1660–1812), based on radiocarbon dating of trench exposures and turbidites. Dendrochronology has the potential to provide much tighter constraints
by crossdating growth rings associated with direct and indirect impacts totrees growing on or adjacent to surface ruptures, but past attempts to utilize
long-lived coast redwoods (Sequoia sempervirens) failed due to difficulties incrossdating this species. Here, we leverage recently developed regional reference chronologies for a new dendroseismological investigation of Sequoia
sempervirens trees and stumps along the San Andreas Fault near Gualala andFort Ross, California. We developed the novel technique of using rope climbing to collect samples in the vicinity of external indicators of potential seismic damage on living trees, such as reiterated trunks that formed after top
breaks, sympodial growth (expressed as trunk kinks), and rightening of trunkleans. We collected increment cores (up to 56 m above ground) from nine
living trees, as well as sections from 23 stumps of historically logged trees that
may extend the record further. These records are being analyzed for growthchanges and anatomical indicators. We have found tree ring indicators of the1906 earthquake including likely initiation dates for reiterated trunks, wood
anatomical indicators, and locally absent growth rings. We show within-tree
variation in the expression of dendroseismological indicators. We detail several disturbance events that may represent the penultimate earthquake, withthe caveat that non-seismic causes cannot yet be confidently excluded because
these trees grow in a disturbance-prone environment. As part of ongoing
research, we plan for additional sampling of damaged trees as well as continuing our efforts to fully crossdate all samples in order to confidently identify the
penultimate earthquake by its contemporaneous effects in many trees.
poster 62
Ground Surface Rupture Complexity on the Northern
Alpine Fault, Aotearoa New Zealand
LA GRECA, J., University of Melbourne, Melbourne, Australia, jlagreca@
student.unimelb.edu.au; QUIGLEY, M., University of Melbourne, Melbourne,
Australia, mark.quigley@unimelb.edu.au; LANGRIDGE, R., GNS Science,
Lower Hutt, New Zealand, R.Langridge@gns.cri.nz; MORGENSTERN,
R., GNS Science, Lower Hutt, New Zealand, r.morgenstern@gns.cri.nz;

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KULESZA, O., University of Melbourne, Melbourne, Australia, okulesza@
student.unimelb.edu.au
Lidar data and field observations are used to investigate the factors influencing
rupture morphology complexity along the Northern Alpine Fault in Aotearoa
New Zealand. Structural and geomorphic mapping covering approximately
220 kilometres of the fault reveals enhanced rupture complexity at fault
junctions and distinct variations in rupture complexity with geological andtopographic variations. Measurement of fault zone widths at 50-meter intervals and fault corrugation analysis is used to quantify along-strike complexity. Rupture mapping results are used to speculate on rupture processes andextents in past and future Alpine Fault earthquakes.
poster 63
Using Modern Fires to Estimate Charcoal Age Inheritanceat Paleoseismic Sites in California
SCHARER, K., U.S. Geological Survey, California, USA, kscharer@usgs.gov;
MCPHILLIPS, D., U.S. Geological Survey, California, USA, dmcphillips@
usgs.gov; LEIDELMEIJER, J., U.S. Geological Survey, Colorado, USA,jleidelmeijer@usgs.gov; KIRBY, M., California State University, Fullerton,
California, USA, mkirby@fullerton.edu
The age of past earthquakes is typically calculated from radiocarbon-dated
sequences of late Holocene deposits. Radiocarbon dates on charcoal provide
a maximum age for the deposits because the age of plant material burned,
the frequency of fire, and the rapidity of transport for detrital pieces makethe charcoal age older than the deposit age. This age difference, known as the“inherited age” can be tens to hundreds of years but most studies assume itis short and do not formally address the impact on event dating. To quantify
inherited age in the California Transverse Ranges, we dated charcoal deposits from two recent fires that burned at two paleoseismic sites along the San
Andreas Fault (the Grand Fire in 2013 at Frazier Mountain and the Bobcat
Fire in 2020 at Pallett Creek). The genus (e.g., Quercus, Arctostaphylos) or
plant part (grass, leaf, bark) were identified for each of 53 dated samples prior
to dating. We find that (1) inherited ages are the same at both sites despite
differences in catchment size and fire histories, (2) short-lived or annual plantparts (grasses, leaves) or composite samples of fine charcoal are typically
younger than twig or wood samples from longer-lived genus, and (3) combining all dates, the average charcoal age precedes the date of the deposit by ~25
cal years (300-year 95% range).
We next use the distribution of inherited ages as an empirical prior in
Bayesian modeling of late Holocene deposits within OxCal (Bronk Ramsey,2021). First, we correct the inherited age distribution to account for larger
radiocarbon calibration uncertainties for dates prior to 1955 CE. The corrected inherited age distribution has mean age of ~90 cal years (470-year 95%
range). Second, we examine how using this corrected distribution impacts
layer and earthquake ages in a synthetic stratigraphic model. We find thatlayer and earthquake ages are younger when the prior is applied, but rather
than a static offset, the effect is variable and limited by the amount of time
between dated layers. Future efforts will examine the effect on existing paleoseismic sites such as Pallett Creek and Frazier Mountain.
poster 64
Refined Timing and Estimates of Coseismic Subsidence at
the Southern Cascadia Subduction Zone: Combining
Modern Dendrochronology, Age Modeling, and Relative
Sea-level Reconstruction Techniques in the Eel River Valley,CA
LA SELLE, S., U.S. Geological Survey, California, USA, slaselle@usgs.gov;
PADGETT, J. S., U.S. Geological Survey, California, USA, jpadgett@usgs.gov;
BLACK, B. A., University of Arizona, Arizona, USA, bryanblack@arizona.
edu; KELSEY, H. M., California State Polytechnic University, Humboldt,
California, USA, hmk1@humboldt.edu; WITTER, R., U.S. Geological Survey,
Alaska, USA, rwitter@usgs.gov; SHERROD, B. L., U.S. Geological Survey,
Washington, USA, bsherrod@usgs.gov
Geologic evidence from tsunamis and great earthquakes in the Cascadia
Subduction Zone is observed at dozens of sites along the coasts of California,
Oregon, Washington, and British Columbia. Paleoseismic data at the southernmost of these sites, the Eel River valley, is key to determining the alongstrike heterogeneity in rupture characteristics during the most recent, 1700
CE, and older subduction zone earthquakes. Three decades ago, paleoseismic
data was first documented at the lower Eel River valley, but conventional dating techniques and microfossil-based paleoenvironmental reconstructions
provided coarse estimates on the timing and amount of coseismic subsidence.
These coarse estimates place limited confidence on correlations between theVolume 95•

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Eel River event stratigraphy and more precise chronologies at sites further
north. Recent advancements in age-depth modeling, dendrochronology, andpaleo-environmental reconstructions provide the opportunity to reexamine
the tidal wetland sequences at the Eel River valley.
To improve estimates of earthquake timing and coseismic subsidence,
we apply a radiocarbon sampling strategy that includes inter-event stratigraphy, construct multiple Bayesian age-depth models, use a fossil foraminifera
Bayesian transfer function, and employ dendrochronological dating on treeroots. We reoccupied previously described sites to collect new sediment cores.
We present preliminary results based on 15 radiocarbon ages and changes
in fossil foraminifera assemblages across two mud-over-peat contacts.
In-growth-position Sitka spruce root wads emerge from cutbanks at two sites
along the Eel River. These root wads are just below the shallowest subsidence
contact, which is capped by silty sand. We collected 25 root samples to obtaintree ring widths and stable oxygen isotope data to correlate between individual trees at the two sites, crossdate to nearby old-growth redwood records andpotentially determine the calendar year-of-death. Refined earthquake ages
and more precise coseismic subsidence estimates will advance understandingof past Cascadia earthquake ruptures and their ensuing hazards.
poster 65
Off the Beaten Path: Preliminary Results of Reconnaissance
Paleoseismic Surveys in Remote Alaskan Lakes
SINGLETON, D. M., U.S. Geological Survey, California, USA, dsingleton@
usgs.gov; HAEUSSLER, P. J., U.S. Geological Survey, Alaska, USA, pheuslr@
usgs.gov; BROTHERS, D. S., U.S. Geological Survey, California, USA,dbrothers@usgs.gov; WITTER, R., U.S. Geological Survey, California, USA,rwitter@usgs.gov; KAUFMAN, D., Northern Arizona University, Arizona,
USA, darrell.kaufman@nau.edu; HILL, J. C., U.S. Geological Survey,
California, USA, Jhill@usgs.gov; JENSEN, B. J. L., University of Alberta,
Edmonton, Canada, bjjensen@ualberta.ca
South-central Alaska contains hundreds of remote lakes that cannot be
accessed by road but are nevertheless in locations that experience strong
ground motions related to Alaska-Aleutian plate boundary seismicity. To
facilitate scientific investigations of these remote lakes, the U.S. Geological
Survey (USGS) developed a highly portable surveying platform (includingtransportation via float plane), capable of collecting both high-resolution subbottom and multi-beam bathymetry data, as well as ~2m long percussiondriven gravity cores. This study will show preliminary results from two remotelakes, Chelatna Lake located ~150 km north of Anchorage and Allison Lakelocated south of Port Valdez.
Chirp and bathymetry data in both lakes show evidence for widespreadslope failures, including a large 4+ meter thick mass transport deposit (MTD)
that extends across the entire lake basin in Chelatna Lake. Sediment corescontain varved stratigraphy (i.e., annual laminations), which are interrupted
by silty-sand fining upwards event deposits, interpreted as either seismicallyor climatically generated turbidites, as well as some tephras. Radionuclide age
models (i.e., Cs137/Pb210) suggests that both lakes have recorded historicalearthquakes including the 1964 Mw 9.2 Great Alaska Earthquake. The sediment record at Chelatna Lake contains evidence for up to 23 earthquakes in
the last ~1800 years. The combination of varved stratigraphy (with potentiallyannual age resolution), the sensitivity to both historical earthquakes and climate events, together with evidence for older (likely) earthquake-triggered
MTDs, motivates expanded coring operations at both lakes. In the Summerof 2024, a collaboration between Northern Arizona University and the USGS
will deploy a UWITEC hybrid coring platform capable of recovering 12-18m
long piston cores. Cores of this length have the capability of recovering longrecords that may span many earthquake cycles and extend the climate proxyrecord to the early Holocene or beyond.
poster 66
A Comparative Study of Earthquake Ground-Shaking Site
Effects From Lacustrine Sediments in a Subduction Zone
Setting Using Active and Passive Seismic Methods
WILS, K., University of Innsbruck, Innsbruck, Austria, katleen.wils@ugent.
be; LIBERTY, L., Boise State University, Idaho, USA, lliberty@boisestate.edu;
MONTALVA, G., University of Concepción, Concepción, Chile, gmontalva@
udec.cl; HAEUSSLER, P., U.S. Geological Survey, Alaska, USA, pheuslr@
usgs.gov; VAN DAELE, M., Ghent University, Ghent, Belgium, maarten.
vandaele@ugent.be
Lacustrine paleoseismology has evolved into a primary technique to reconstruct the recurrence of ground motion at a given site. Different types of sedimentary shaking imprints (e.g., turbidites, landslides) have been linked to various seismic ground motion parameters (e.g., intensity, duration, frequency

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content). Understanding the depositional characteristics of such imprints thus
has great potential to improve local seismic hazard estimations. By defining
ground-motion threshold values for the appearance and absence of certain
coseismic imprints, earthquake magnitude and source location can be estimated via ground-motion modelling. However, up to now the input for thesemodels has remained limited to rather qualitative measures of strong groundmotion that are poorly physically constrained (i.e., macroseismic intensity).
This is partly related to the gap in our understanding of the site characteristics
of lake sediments, as direct observations of seismic shaking on the bottom ofa lake are scarce.
To get a first idea on the variability of ground-shaking site effects in lakes
and how these relate to the depositional environment, we study two sites insouthern Chile and south-central Alaska located at ~200 km from the subduction trench by analyzing ambient noise geophone array registrations aswell as hammer seismic data. The Alaskan site consists of a 4.4 km² drained
proglacial lake in mountainous terrane (Iceberg Lake) containing ~1500 yearsof outcropping sediments in an actively eroding environment. In Chile, measurements were performed along the shores of the 860 km² piedmont Lago
Llanquihue, where lake sediments with an (up to now) unclear age are buriedat shallow depth. Preliminary analysis shows that Vs30 values are very similar, while H/V spectral ratios and fundamental frequencies are more variable
within and between sites, emphasizing the need for detailed site studies in any
lacustrine paleoseismic study. Ongoing analysis will focus on understanding
the origin of these differences, and how this knowledge can contribute to theinterpretation of other lacustrine paleoseismic records.
poster 67
Temporal Clues Point to an Along-Strike Cascadia
Megathrust Rupture Sequence Between 680–950 Years Ago
WITTER, R., U.S. Geological Survey, Alaska, USA, rwitter@usgs.gov;
STAISCH, L., U.S. Geological Survey, Oregon, USA, lstaisch@usgs.gov;
NELSON, A., U.S. Geological Survey, Colorado, USA, alannels@gmail.com;
KELSEY, H., California State Polytechnic University, Humboldt, California,
USA, hmk1@humboldt.edu; PADGETT, J., U.S. Geological Survey, California,
USA, jpadgett@usgs.gov
Globally, subduction zones have ruptured piecewise in sequences of greatearthquakes, yet conclusive evidence of along-strike ruptures of separate sections of the Cascadia megathrust, occurring within decades to centuries, isscarce. Here, we reevaluate ages for stratigraphic evidence of earthquakes overa ~270-year interval and show that the ages are consistent with three separate
ruptures of the northern, central, and southern sections of the Cascadia megathrust. Most ages for coseismic coastal subsidence, tsunami inundation, andseismic shaking use radiocarbon methods with age uncertainties that span
decades to centuries. Many studies use the overlap of age ranges (probability
density functions, PDF) to infer maximum rupture length based on temporal correlation of dated evidence from Cascadia sites tens of kilometers apart.
We take a different approach and look for differences in ages, in the interval 680–950 years ago, for great earthquakes at 10 sites that span a distanceof 860 km between the Strait of Juan de Fuca, WA and Humboldt Bay, CA.
Prior studies used PDF overlaps of ages in the same time interval at these sites
to infer a ~610 km-long rupture between Humboldt Bay and the ColumbiaRiver. However, when grouped by site proximity and combined using OxCal(Bronk Ramsey, 2009), the PDFs fail a X2 goodness-of-fit test. The statisticallydifferent combined PDFs along strike support an alternative hypothesis ofsequential rupture of the southern (950–870), northern (890–790), and central (760–680 cal yr BP) sections. Stratigraphic support for piecewise rupture
includes: tsunami and shaking deposits in Bradley Lake that suggest rupturesof adjoining central and southern sections; and contact W at Willapa Bay,
which may mark less coastal subsidence during a northern rupture. Althoughstatistical tests cannot rule out full-margin rupture, the data also support the
hypothesis of along-strike rupture sequences. New dating techniques (dendrochronology, luminescence) and alternative age models can further test
full-margin versus piecewise rupture hypotheses to improve Cascadia earthquake hazards assessments.

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From Geodynamics to Earthquake Rupture, Models That
Cross Time- and Length-Scales
Oral Session • Friday 3 May • 4:30 pm PacificConveners: Matthew Knepley, University at Buffalo(knepley@gmail.com); Louis Moresi, Australian National
University (louis.moresi@anu.edu.au)
Linking Geodynamic-Seismic Cycling Models With
Earthquake Dynamic Rupture Models: 5 Choices toConsiderMADDEN, E. H., San Jose State University, California, USA, elizabeth.
madden@sjsu.edu; VAN DINTHER, Y., Utrecht University, Utrecht,
Netherlands, ylonavandinther@gmail.com; GABRIEL, A. A., University ofCalifornia, San Diego, California, USA, liese.gabriel@gmail.com; ULRICH,
T., Ludwig Maximillian University, Munich, Germany, thomas.ulrich@lmu.
de; VAN ZELST, I., Technische Universität Berlin, Berlin, Germany, iris.
vanzelst@dlr.de
By linking a subduction zone geodynamics and seismic cycling model (SCM)
to a dynamic earthquake rupture model (EQM), we produce a realistic megathrust earthquake from initial conditions that are physically consistent with
one another and long term subduction. The SCM (van Dinther et al. 2013,2014) begins with a geodynamics phase, then transitions to a seismic cycle
phase in which slip instabilities arise spontaneously without a prescribedfault. The material properties, stress field and fault strength parameters at thestart of one SCM slip event are mapped to the EQM. The fault geometry is
set a priori in the EQM using the locations of maximum strain rate over theentire SCM slip event. The EQM is run with SeisSol (Pelties et al. 2012, 2014),
which captures the complete rupture dynamics and seismic wave propagation. We highlight certain linking choices for discussion and future consideration: (1) 2D to 3D mapping: We assume that the fault geometry, material
properties, stress and frictional parameters from the 2D SCM are constant in
the along-strike direction in the 3D EQM, a technically simple approach thatlikely does not reflect subduction zone characteristics. (2) Poisson’s ratio, ν:
The SCM assumes incompressible rock with ν = 0.5, which is valid over longtime frames, but not appropriate for modeling earthquake rupture dynamics. We choose ν = 0.25 for the EQM, but note that v influences slip magnitudes. (3) Static fault strength: We assume that the effective mean stress in
the SCM is equivalent to the effective normal traction along the EQM fault,
which appears appropriate up to ~30 km depth in these models, but alternatives could be considered. (4) Frictional weakening: Coseismic weakening isbetter modeled in the EQM than in the SCM, challenging our use of the SCM
to assign dynamic coefficients of friction and slip-weakening distances. In
addition, the SCM includes rate-strengthening in shallow sediments, which ishonored in the EQM only by varying the coefficients of dynamic friction here.
(5) The topography developed during the SCM is not mapped to the EQM.
Using a Multi-Cycle, Physics-Based Earthquake Simulator to
Explore Rupture Connectivity for Seismic Hazard: The
Aotearoa New Zealand Example
HOWELL, A., University of Canterbury, Christchurch, New Zealand,
andrew.howell@canterbury.ac.nz; PENNEY, C., University of Canterbury,
Christchurch, New Zealand, camilla.penney@canterbury.ac.nz; MCLENNAN,
T., Seequent Ltd, Christchurch, New Zealand, tim.mclennan@seequent.com;
SEEBECK, H., GNS Science, Lower Hutt, New Zealand, h.seebeck@gns.cri.nz;
WILLIAMS, C. A., GNS Science, Lower Hutt, New Zealand, c.williams@gns.
cri.nz; LIAO, Y., University of Canterbury, Christchurch, New Zealand, yiwun.
liao@canterbury.ac.nz; NICOL, A., University of Canterbury, Christchurch,
New Zealand, andy.nicol@canterbury.ac.nz; FRY, B., GNS Science, Lower
Hutt, New Zealand, b.fry@gns.cri.nz
Recent earthquakes demonstrate how complex earthquake rupture processes
can be: examples include the multi-fault 2016 M7.8 Kaikōura (Aotearoa New
Zealand) and 2019 M7.1 Ridgecrest earthquakes and the 2023 Kahramanmaraş
earthquake sequence (Türkiye). It is important to account for the possible
future occurrence of multi-fault earthquakes and sequences in seismic andtsunami hazard models. However, this is often challenging due to uncertainties on the timing of paleoearthquakes and the short duration of the historical
record. To date, efforts to incorporate multi-fault rupture into seismic hazard
models have often relied on empirical relationships, which are constrainedby few M≥7.5 earthquakes, and multi-fault earthquakes have been largely
ignored in probabilistic tsunami hazard models. Physics-based earthquake
simulators like RSQSim — built on simple models of loading and stress trans-

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fer across a fault network — offer an alternative pathway toward identificationof groups of faults that may rupture simultaneously in a multi-fault earthquake or closely spaced in time during complex earthquake sequences.
We present a 90 thousand-year synthetic earthquake catalog createdusing RSQSim and a 3D model of 469 crustal and subduction faults. We compare rupture connectivity of synthetic events in this catalog with the ruptures
used as inputs for the 2022 Aotearoa New Zealand Seismic Hazard Model(NZSHM22). We find that: (1) Rupture connectivity of earthquakes in our
synthetic catalog is high, with 46% of MW≥7.0 earthquakes rupturing multiple faults; (2) the longest earthquake ruptures in the synthetic catalog are
significantly shorter than the longest ruptures in NZSHM22; and (3) inclusionof the Hikurangi subduction interface in the model increases rupture connectivity among crustal faults, but not the overall along-strike length of crustal
ruptures. Further sensitivity testing is required, but initial models indicate thatphysics-based earthquake simulators represent a promising way to generate
multi-fault earthquake inputs for seismic and tsunami hazard models.
Bridging the Gap Between Millions of Years andMilliseconds in Visco-Elasto-Plastic Subduction Earthquake
Sequence Models
KOELZER, A. J., Utrecht University, Utrecht, Netherlands, a.j.koelzer@uu.nl;
DE VOS, M., Utrecht University, Utrecht, Netherlands, mhinadevos@gmail.
com; GERYA, T., ETH Zürich, Zürich, Switzerland, taras.gerya@erdw.ethz.ch;
VAN DINTHER, Y., Utrecht University, Utrecht, Netherlands, y.vandinther@uu.nl
Deformation in subduction zones is characterized by the interaction of multiple deformation processes that occur over a wide range of temporal andspatial scales. Basing earthquake sequence models on continuum mechanics allows simulating a large spectrum of visco-elasto-plastic deformation,
including earthquake dynamics, spontaneous fault evolution, lithosphericdeformation, mantle flow, and topographic evolution [1]. Such seismo-tectonic models have been unable to resolve coseismic time scales, hence notproviding insight into all stages of the seismic cycle. Understanding the interaction between slab, overriding plate, and mantle on sub-year time scales has
therefore been difficult. We simulate the coupled mechanical and thermal
evolution of a subduction zone with a visco-elasto-plastic rheology. We selfconsistently evolve a mature subduction zone with a heterogeneous subduction channel by simulating the subduction of a 2D slab for 4 million years.
Adopting an invariant reformulation of rate- and state-dependent friction
and an adaptive time stepping scheme [2] enables us to span the gap between
millions of years of tectonic evolution and milliseconds of seismic rupture.
We resolve all relevant time scales of the seismic cycle in a realistic subduction zone setting. Depending on the characteristic slip distance and the ratioof seismogenic zone width over nucleation size W/h*, we generate slow slip
events with slip rates between 10-8 m/s and 10-4 m/s and earthquakes withslip rates on the order of m/s. Earthquake nucleation and propagation is fully
resolved and leads to the generation of seismic waves. Earthquakes nucleatein the heterogeneous subduction channel near the 350°C isotherm and propagate upwards to arrest at the up-dip velocity-strengthening segment. We willcomment on technical challenges, enabling cross-scale modeling of increasingly complex scenarios and its potential.
References[1] van Dinther et al., JGR, 2013b, doi.org/10.1002/2013JB010380[2] Herrendörfer et al., JGR, 2018, doi.org/10.1029/2017JB015225
Fully Dynamic Earthquake Cycle Modeling to Explore
Interactions Between Large Earthquakes and Slow Slip
Events on Heterogeneous Faults
TANG, Z., Texas A&M University, Texas, USA, zztang@tamu.edu; DUAN, B.,
Texas A&M University, Texas, USA, bduan@tamu.edu; MENG, Q., Universityof California, Los Angeles, California, USA, qingjun23@g.ucla.edu
Recent observations show interactions between large earthquakes and slow
slip events (SSEs). To understand physics underlying these observations, weneed to resort to physics-based models that can capture both spontaneously
dynamic rupture during large earthquakes and quasi-static deformation processes (including slow slip events) between earthquakes. These models crossmultiple time- and length-scales. In this study, we apply a recently developed
method for this type of models, a Finite Element Method (FEM) dynamic
earthquake simulator, EQdyna, to perform fully dynamic earthquake cycle
modeling on a shallow-dipping subduction plane to investigate interactions
between large earthquakes and SSEs. The method distinguishes itself fromclassical, quasi-dynamic earthquake simulators in the community that do not
capture spontaneous rupture propagation. We are particularly interested in
how heterogenous frictional properties on the fault plane dictate generation

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of large earthquakes and SSEs and their interactions over multiple earthquake
cycles. In our models, multiple asperities with unstable slip frictional properties are distributed on a subduction plane with conditional stable frictional
properties. We vary the asperities’ sizes and locations to explore their effects.
Our preliminary results successfully reproduce depth-dependent modes ofSSEs observed at the Hikurangi subduction zone in New Zealand that shallower SSEs happen more frequently with shorter durations at low stress.
Notably, our findings elucidate distinct loading effects of SSEs associated withsmall asperities at different depths on large earthquakes. In addition, models
with numerous tiny asperities reveal a higher SSE occurrence frequency, suggesting these areas act as barriers for large earthquake rupture propagation.
Insights Into Fault Interactions in Central New Zealand
Using Paleoearthquake Records and Earthquake Simulators
HUMPHREY, J. A., University of Canterbury, Christchurch, New Zealand,jade.humphrey@pg.canterbury.ac.nz; HOWELL, A., University of Canterbury,
Christchurch, New Zealand, andrew.howell@canterbury.ac.nz; PENNEY,
C., University of Canterbury, Christchurch, New Zealand, camilla.penney@canterbury.ac.nz; NICOL, A., University of Canterbury, Christchurch, New
Zealand, andy.nicol@canterbury.ac.nz; LITCHFIELD, N., GNS Science,
Lower Hutt, New Zealand, n.litchfield@gns.cri.nz; VAN DISSEN, R., GNS
Science, Lower Hutt, New Zealand, r.vandissen@gns.cri.nz; FRY, B., GNS
Science, Lower Hutt, New Zealand, b.fry@gns.cri.nz; LANGRIDGE, R., GNS
Science, Lower Hutt, New Zealand, r.langridge@gns.cri.nz
Forecasting the probability and magnitude of future large magnitude earthquakes is typically dependent on available paleo- and historical earthquake
information. In Aotearoa-New Zealand (A-NZ) historical records (post
1840AD) demonstrate that many large earthquakes (e.g., >Mw 7.0) rupture
multiple faults with complex rupture patterns and/or trigger additional earthquakes. To improve understanding of the importance of temporally clusteredearthquakes, we compare the timing of earthquakes between active faults incentral A-NZ using paleoseismic and historical records and a synthetic earthquake catalogue. To support this comparison we have revised paleoseismic
records for key faults to determine the frequency of spatial-temporally clustered earthquakes. These short geological records (e.g., < 20 kyr) are compared to synthetic earthquake catalogues produced by physics-based RSQSim
simulations for timescales of ~300 kyr. The paleo-record indicates that earthquakes on neighbouring faults are often close in age, suggesting spatio-temporal interactions between faults. Due to uncertainties in the radiocarbon
dating, this clustering could arise from multi-fault ruptures and/or triggered
slip in separate earthquakes. Both scenarios are represented in the RSQSim
catalogues, with co-rupture of the Hikurangi subduction thrust and upper
plate faults being common. Multi-fault and triggered earthquakes both suggest stress interactions between faults on timescales of seconds to hundreds ofyears and temporally variable seismic hazards. These fault interactions haveimportant implications for time-dependent seismic hazard in central A-NZ
and will be explored further using RSQSim models.

From Geodynamics to Earthquake Rupture, Models That
Cross Time- and Length-Scales [Poster Session]
Poster Session • Friday 3 May
Conveners: Matthew Knepley, University at Buffalo(knepley@gmail.com); Louis Moresi, Australian National
University (louis.moresi@anu.edu.au)poster 94
Bridging Spatial and Temporal Scales in Modeling
Coseismic and Interseismic Crustal Deformation with
PyLithAAGAARD, B. T., U.S. Geological Survey, Colorado, USA, baagaard@
usgs.gov; KNEPLEY, M. G., University at Buffalo, SUNY, New York, USA,knepley@gmail.com; WILLIAMS, C. A., GNS Science, Lower Hutt, New
Zealand, c.williams@gns.cri.nz
We present an overview of PyLith’s current capabilities for modeling coseismic and interseismic crustal deformation across a broad range of spatial andtemporal scales. PyLith is an open-source finite-element code designed formodeling earthquake faulting processes by solving partial differential equations, with faults modeled as dislocations on interior interfaces. For solving
the elasticity equation PyLith includes two formulations: (1) an implicit formulation without inertia (quasistatic), which is generally used for modeling

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interseismic viscoelastic or elastoplastic deformation on time scales of years,
and (2) an implicit-explicit formulation with inertia (dynamic), which is generally used for modeling coseismic elastic or elastoplastic deformation on thetime scales of seconds. We use finite-element discretizations, time-stepping
algorithms, and solvers from the Portable, Extensible Toolkit for Scientific
Computation (PETSc) to provide users with scalable options for modelingdeformation on spatial scales ranging from tens of meters to hundreds of kilometers and temporal scales ranging from milliseconds to hundreds of years.
Our multiphysics formulation provides flexibility in specifying a variety ofphysics with one or more governing equations; we have implemented elasticity, incompressible elasticity, and poroelasticity. We are currently working towards including adaptive mesh refinement capabilities to broaden therange of spatial scales modeled in a single simulation. This is also a steppingstone towards coupling the quasistatic and dynamic formulations to model
earthquake cycles with propagating seismic waves during coseismic deformation and viscoelastic relaxation during interseismic deformation. PyLith
is developed and distributed through the Computational Infrastructure for
Geodynamics (https://geodynamics.org/resources/pylith) and includes source
code, binary packages, online documentation (https://pylith.readthedocs.io),
video tutorials, and a Docker container for software development.
poster 95
Spatiotemporal Evolution of Postseismic Stress andAftershocks Following the 2010 Mw 8.8 Maule Earthquake
BODUNDE, S., University of Oklahoma, Oklahoma, USA, ssbodunde@ou.edu; JIANG, J., University of Oklahoma, Oklahoma, USA, jiang@ou.edu
Following major earthquakes in subduction zones, transient deformation andaftershocks occur. The spatiotemporal behavior of seismicity and its controlling physical mechanisms continue to be debated among geoscientists. Here,
we focus on the space-time distribution of postseismic stress changes andaftershocks in subduction zones with a case study of the 2010 Mw8.8 Maule
earthquake in Chile. Previous studies have identified pore pressure diffusion
as a possible mechanism of the aftershocks that followed the 2014 Mw8.1
Iquique earthquake and linked the spatial migration of aftershocks aroundthe rupture region of the 2015 Illapel earthquake to poroelasticity. Motivatedby these examples, we design three-dimensional finite-element models to
explore the seismic and aseismic megathrust behavior during the Maule
earthquake sequence. We first compare results from our 3D models with thecoseismic displacements of the Maule event. We then use time-dependent 3Dmodels to simulate postseismic afterslip, poroelastic rebound, and viscoelastic
relaxation and characterize the spatiotemporal patterns of the deformation
and Coulomb stress change. Poroelasticity produces positive and negative
Coulomb stresses above and below the fault plane, respectively, with its temporal decay faster than viscoelastic Coulomb stresses. The viscoelastic scenario produces mainly positive Coulomb stresses that are concentrated within
and below the slab, with stress amplitudes depending on the viscoelastic rheology and crustal thickness. However, the viscoelastic stresses are at least twoorders of magnitude smaller than poroelastic stresses, indicating its potential
impact mainly on long-term triggering of seismicity. We next compare thecharacteristics of postseismic deformation and stress changes in our models
with the aftershocks from Maule to understand the mechanisms that control
seismicity evolution in space and time.
poster 96
Geodynamic Modeling of Flat Slab Subduction Driving
Microplate Tectonics in Alaska
JADAMEC, M. A., University at Buffalo, SUNY, New York, USA, mjadamec@
buffalo.edu; HAYNIE, K. L., University at Buffalo, SUNY, New York, USA,klhaynie@buffalo.edu; KNEPLEY, M. G., University at Buffalo, SUNY, New
York, USA, knepley@buffalo.edu
The Aleutian-Alaska subduction zone (AAS) forms the northern boundaryof the Pacific Ring of Fire, a tectono-physiographic term for the collectionof subduction zones that outwardly flank the eastern, northern, and western
perimeters of the Pacific Ocean. The AAS is characterized by ocean-ocean
subduction in the west (Aleutian segment) and by ocean-continent subduction in the east (Alaska segment). We present high-resolution, 3D visco-plastic models of the Alaska subduction zone that examine the effect of laterally
variable plate coupling on the 3D dynamic feedback between the upper- anddown-going plates. In particular, the models examine the role of localized
increased plate coupling in the flat slab region on the microplate motion of
the portion of south-central Alaska located both above the flat slab and southof the Denali fault, hereafter referred to as the southern Alaska microplate(SAK). The results show a variably coupled subduction interface and weak
Denali fault shear zone produce higher plateness for the SAK and a better fit

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to observed variability in long-term slip rates along the length of the Denali
Fault shear zone. Further, by incorporating a 3D tectonic configuration, themodels show the SAK (not the North American plate (NAM)) overlies theflat slab segment of the subduction zone. Given that the 1964 Great Alaska
earthquake epicenter occurs where SAK (not NAM) is the upper plate, themodels suggest a large-scale tectonic framework for this event wherein the
SAK plays a key role; namely, the tectonic regime of southern Alaska is analogous to that of oblique flat slab subduction driving large-scale motion of the
SAK, with the Great Alaska earthquake situated in this domain of restrictedescape. This implies that the long-term tectonics of the Denali fault shear zone
and flat slab subduction interface are interconnected through the motion of
the intervening SAK. Therefore, treating these features as interconnected may
be important for future hazard assessment modeling in Alaska.
poster 97
Fast and Slow Earthquakes in Alaska: Insights From
Three-Dimensional Thermal Structure and Slab
Dehydration
JI, Y., Chinese Academy of Sciences, Beijing, China, 31911431@qq.com; QU,
R., Chinese Academy of Sciences, Beijing, China, qurui@itpcas.ac.cn; ZHU,
W., Chinese Academy of Sciences, Beijing, China, zhuweiling@itpcas.ac.cn
Fast and slow earthquakes are predominantly generated along faults constituting active plate boundaries. Characterized by repeated devastating earthquakes and frequent slow slip events and tremors, the Alaska megathrustpresents a chance to better know the complicated dynamics of a subduction
system changing from steep to shallow dips associated with enigmaticallyabundant fast and slow seismic events. Based on three-dimensional thermal
modeling, we find that the downgoing metamorphosed oceanic crust containing bound water releases a large amount of fluid and causes the recurrence offast and slow earthquakes by elevated pore fluid pressure and hydrofracturing.
The seismogenic interface and the slow slip events (SSEs) identified beneaththe Upper Cook Inlet coincide well with the slab metamorphic dehydration
regions. The observed slow earthquakes with quasi-stable fault slips preferentially occur, accompanied by high dehydration and temperature downdip
along the transition zone.
poster 98
Modeling the Proposed Deep Slab-Deformation Processes
Behind Potential Precursory Signals Preceding Large
Subduction Zone Earthquakes
LEMUS, I. C., University of California, Berkeley, California, USA, ilemus@
berkeley.edu; BADEN, C. W., University of California, Berkeley, California,
USA, c.w.baden@berkeley.edu; CHANARD, K., Université de Paris, Paris,
France, kristel.chanard@gmail.com; WANG, L., Ohio State University, Ohio,
USA, wang.1115@osu.edu; BÜRGMANN, R., University of California,
Berkeley, California, USA, burgmann@berkeley.edu
Recent studies suggest that large-scale, transient signals in GNSS velocities,
satellite gravity measurements, and intermediate-depth foreshock occurrences may precede large earthquakes in subduction zones. Specifically, investigations focused on the 2011 Mw 9.0 Tohoku-Oki and the 2010 Mw 8.8 Maule
earthquakes found that these precursory signals preceded the respective main
shocks by 2-8 months. If correctly resolved, these deformation signals appear
to record a rapid geodynamic process occurring deep within subduction
zones and may be instrumental in the initiation of some megathrust earthquakes. While qualitative models have been proposed to explain the physical processes behind these potential precursory signals, such as an intra-slab
extension, mineral phase changes, and large-scale fluid flow, numerical models exploring Earth’s geodynamic response to these processes have yet to beinvestigated.
Here, we use the finite element code Pylith to model geodynamic processes that plausibly occur deep within subduction zones, and that could
produce the potential precursory signals observed. Given the high density of
GNSS stations across Japan, we focus on the deformation preceding the 2011
Mw 9.0 Tohoku-Oki Earthquake. We model the intraslab extension and mineral phase change processes to obtain predicted surface displacements andcompare those to GNSS observations of deformation prior to the earthquake.
We explore how changes in rheological properties and subduction zone structure impact modeled predictions of surface displacement and gravity measurements for the tested geodynamic mechanisms. The model predictions anddata comparisons will provide valuable insights into the plausibility of the
proposed physical processes in generating the observed geodetic signatures.
Furthermore, these models will help to establish how transient deformation
deep within subduction zones may be expressed at Earth’s surface independent of their timing with respect to great earthquakes.

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poster 99
Geodynamic Models Connecting the Seismic Timescale to
the Tectonic Timescale
MORESI, L., Australian National University, Canberra, Australia, louis.
moresi@anu.edu.au; YANG, H., Zhejiang University, Hangzhou, China,
haibin.yang@zju.edu.cn; GIORDANI, J., Sydney University, Sydney,
Australia, julian.giordani@sydney.edu.au; KNIGHT, B., Curtin University,
Perth, Australia, ben.knight@curtin.edu.au
In Yang et al [2023], we demonstrated a numerical approach to solving thecoupled tectonic and seismic-rupture problem in three dimensions using amodified version of the Underworld python software package that is optimised for tectonic and geodynamic modelling (www.underworldcode.org).
We were able to meet a number of simple benchmark cases by introducing
momentum terms and a non-linear, viscoelastic constitutive model with ratestate frictional behaviour in a priori specified fault zones.
This is a very intense computational problem that identified a numberof pain-points for generalising our formulation to understand the two-way
interaction between tectonics and earthquake cycles. These include: very large
variations in resolution between fault regions and the embedding lithosphere;
and comparable changes in the timestepping requirements between tectonic
deformation and co-seismic deformation. In Underworld, the tracking ofmaterial properties, momentum / stress-history terms, and damage over significant strain is handled by a swarm of Lagrangian particles which we determined also required very high resolution.
We report our latest developments on a spatially-adaptive, unstructured,
highly parallel, Lagrangian/Eulerian numerical tool (Underworld3) which is
specifically targetted at problems of this nature. Underworld3 is designed tobe particularly user-friendly - it integrates with the jupyter notebook system,
is fully introspective and is fully integrated with the sympy package whichallows mathematical introspection as well as the usual ability to probe running code that is common in jupyter.
--Yang, H., Moresi, L., Weng, H., & Giordani, J. (2023). Numerical
Modeling of Earthquake Cycles Based On Navier‐Stokes Equations With
Viscoelastic‐Plasticity Rheology.Geochemistry, Geophysics, Geosystems, 24(9),e2023GC010872. https://doi.org/10.1029/2023GC010872

How Well Can We Predict Broadband Site-Specific Ground
Motion and Its Spatial Variability So Far?
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Morteza Bastami, International Institute ofEarthquake Engineering and Seismology (m.bastmi@iiees.
ac.ir); Mohamad M. Hallal, University of California, Berkeley(mhallal@berkeley.edu); Chunyang Ji, North Carolina
State University (cji3@ncsu.edu); Andrés Olivar Castaño,
University of Potsdam (andres.olivar-castano@uni-potsdam.
de); Marco Pilz, GFZ Potsdam (pilz@gfz-potsdam.de)Site Response Characteristics from Ambient Noise Data
Recorded on Degrading Warm Permafrost in Bethel,
Alaska.
GOOZEN, A., University of Alaska Anchorage, Alaska, USA, annikagoozen@
yahoo.com; ZHAO, Y., University of Alaska Fairbanks, Alaska, USA, yzhao8@
alaska.edu; DUTTA, U., University of Alaska Anchorage, Alaska, USA,udutta2@alaska.edu; YANG, Z., University of Alaska Anchorage, Alaska,
USA, zyang2@alaska.edu
Permafrost is experiencing accelerated warming due to anthropogenic activities and climate change. The intricate relationship between permafrost degradation and seismic attributes is significant to regions where both phenomena
are prevalent, as it can exacerbate seismic hazards. There is a notable knowledge gap about this relationship. The current study aims to address the gap
by analyzing twelve months of recorded ambient noise time series data from
two accelerometers located on warm permafrost in Southwest Alaska. Bothaccelerometers were three-component EpiSensors connected with a 24-bit
Delta-Sigma converter with a dynamic range of approximately 136 dB per
channel (Etna-2 of Kinemetrics). Data from each sensor was sampled at 250
samples per second. An open-source, web-based application called HVSRweb
was employed for horizontal-to-vertical spectral ratio (HVSR) processing;a processing window length of 60 seconds was used to create 60-time win-

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dow lengths of 60 seconds each. The microtremor HVSR method provided
insights into how the site response differs between winter and summer seasons. Comprehensive analysis of the time series data collected from the two
seismic sensors during winter and summer revealed an obvious correlation
between the frozen or unfrozen active layer conditions and ground motion
amplification. Ground motion amplification was notably higher during summer with an unfrozen active layer. The peak fundamental frequency (f0) of
the HVSR has also been shifted towards the higher frequency side during thewinter months due to frozen ground. These findings demonstrate the relationship between permafrost degradation and ground motion amplification,emphasizing the importance of permafrost degradation on seismic attributes.
These observations are crucial for understanding and predicting the potential
impact of permafrost degradation on the built infrastructure in future seismic
events.
Improving the Performance of the SSRh Site-Response
Assessment Techniques on a Dense Array in the Koutavos
Basin (Greece)
PERRON, V., Atomic Energy and Alternative Energies Commission, centred’étude de Cadarache, France, vincent.perron@cea.fr; RISCHETTE, P.,
Atomic Energy and Alternative Energies Commission, centre d’étude de
Cadarache, France, pauline.rischette@cea.fr; THEODOULIDIS, N., Instituteof Engineering Seismology and Earthquake Engineering, Thessaloniki,
Greece, ntheo@itsak.gr; ROUMELIOTI, Z., University of Patras, Patras,
Greece, zroumelioti@upatras.gr; HOLLENDER, F., Atomic Energy andAlternative Energies Commission, Cadarache / Grenoble, France, fabrice.
hollender@cea.fr; CORNOU, C., University Grenoble Alpes, Grenoble,
France, cecile.cornou@univ-grenoble-alpes.fr; CHALJUB, E., University
Grenoble Alpes, Grenoble, France, emmanuel.chaljub@univ-grenoble-alpes.
fr; WATHELET, M., University Grenoble Alpes, Grenoble, France, marc.
wathelet@univ-grenoble-alpes.fr; COUTANT, O., University Grenoble Alpes,
Grenoble, France, olivier.coutant@univ-grenoble-alpes.fr; BUSCETTI, M.,
Atomic Energy and Alternative Energies Commission, centre d’étude de
Cadarache, France, margaux.buscetti@cea.fr; KONIDARIS, A., TEI Ionion
Nison, Argostoli, Greece, agiskonidaris@gmail.com
Earthquake site effects have a major impact on the seismic hazard. However,
evaluating the site response over a broad frequency range and with a highspatial resolution remains difficult. Empirical site effect assessment has shown
good reliability up to high frequencies but relies on earthquake recordings,
which requires long station deployments. In contrast, seismic ambient noise
can be rapidly recorded anywhere at any time. The hybrid standard spectral
ratio (SSRh) combines both the spectral ratio from earthquake recordings
at a few sites and the spectral ratio from ambient noise recordings at manysites from short duration deployments. Here we present and discuss the SSRh
results from a dense array of 51 seismic nodes deployed in the Koutavos Basinin Greece. We report a good agreement between the SSRh method and thereferenced method based on earthquake observations. Furthermore, we quantitatively evaluate the performance of applying various statistical and signal
processing procedures in order to improve the SSRh method.
A Simple Way of Estimating Site Effect With Respect to a
Distant Rock-Reference Site: Application of the Standard
Spectra Ratio Technique Based on Coda Waves
GRENDAS, I., University of Patras, Thessaloniki / Patras, Greece, igrendas@
geo.auth.gr; HOLLENDER, F., CEA, Cadarache / Grenoble, France, fabrice.
hollender@cea.fr; PERRON, V., CEA, Cadarache Grenoble, France,
Vincent.PERRON@cea.fr; THEODOULIDIS, N., Institute Of Engineering
Seismology & Earthquake Engineering, Thessaloniki, Greece, ntheo@itsak.gr;
BUSCETTI, M., CEA, Cadarache / Grenoble, France, Margaux.BUSCETTI@
cea.fr; TRAVERSA, P., EDF, Aix-en-Provence, France, paola.traversa@edf.fr
In recent years, site effect is considered having a major impact on the earthquake ground motion. Site effects can be described by the Site spectral
Amplification Factor (SAF) which is directly controlled by surface geologicalconditions (briefly: hard rock to loose sediments into valleys). Several simple
or more sophisticated techniques have been introduced in recent decades,with advantages and disadvantages leading to certain limitations. One of themost commonly applied SAF estimation techniques is the so-called Standard
Spectra Ratio (SSR) (Borcherdt, 1970). However, this technique can only beapplied if there is a rock reference station close to the studied site. This condition is obviously restrictive for all sites where no reference/rock station is
installed nearby. In this study, the SSR technique is studied and examinedbased on Coda wave recordings, using time segments corresponding to thesame travel time, based on more distant reference stations (thus bypassing
the criterion of the nearby reference site). It should be noted that this tech-

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nique, named SSRc (for SSR on coda waves), is simple to implement. It is analternative to the more complex methods developed previously by Philips andAki, (1986) and Grendas et al.,(2022a), which also use Coda waves, attempting
and partially succeeding in relaxing the criterion of proximity to the reference
site. The valid application of this new SSRc technique is supported based on
analytical attenuation equations and synthetic parameters, as well as based on
actual earthquake data. More specifically the SSRc technique is successfully
applied here at several stations in two different seismicity contexts in wester
Greece and southeastern France with high seismicity and low-to-moderate,
respectively, using relatively distant reference stations (e.g. up to ~100km).
The computed average SAF results, as well as their uncertainty, are encouraging compared to corresponding results extracted by alternative methodologies
and different dataset, supporting thus further application and investigation of
the proposed, and rather simple, SSRc technique.
CD-VAE-GMG: Conditional Dynamic Variational
Autoencoder for Earthquake Ground Motion Generation
REN, P., Lawrence Berkeley National Laboratory, California, USA, pren@lbl.gov; NAIMAN, I., Ben-Gurion University of the Negev, Beersheba, Israel,naimani@post.bgu.ac.il; LACOUR, M., University of California, Berkeley,
California, USA, maxlacour@berkeley.edu; NAKATA, R., Lawrence Berkeley
National Lab, California, USA, rnakata@lbl.gov; NAKATA, N., Lawrence
Berkeley National Lab, California, USA, nnakata@lbl.gov; BI, Z., Lawrence
Berkeley National Lab, California, USA, zfbi@lbl.gov; MALIK, O. A., Lawrence
Berkeley National Lab, California, USA, oamalik@lbl.gov; MOROZOV,
D., Lawrence Berkeley National Lab, California, USA, dmorozov@lbl.gov;
AZENCOT, O., Ben-Gurion University of the Negev, Beersheba, Israel,
aizencot@gmail.com; ERICHSON, N. B., Lawrence Berkeley National Lab,
California, USA, erichson@lbl.gov; MAHONEY, M. W., Lawrence Berkeley
National Lab, California, USA, mmahoney@stat.berkeley.edu
Simulating earthquake ground motions is crucial for assessing seismic hazards and ensuring the safety and resilience of critical infrastructure. However,obtaining ground motion data across a wide geographic area with high spatialsampling is challenging and resource-intensive, especially for regions with
infrequent seismic activity. This work proposes a novel Conditional Dynamic
Variational Autoencoder (CD-VAE) framework to predict new seismogramsfrom unobserved earthquakes at new sources and site locations. Specifically,
we leverage the Short-Time Fourier Transform (STFT) to extract the timefrequency information and utilize the probabilistic autoencoder to learn thelatent distributions based on the amplitude spectrogram. Both prior andposterior distributions are constructed with variational sequential models(i.e., recurrent neural networks) to facilitate capturing temporal dynamics.
Furthermore, we apply the phase retrieval method to estimate the phase information from the reconstructed amplitude spectrogram and use inverse STFT
to recover the corresponding waveforms. Moreover, our model is conditionedon specific physical parameters, such as earthquake magnitudes and the coordinates of sources and stations. This method is easy and stable for optimization compared with previous Generative Adversarial Network (GAN) models. We use a rich set of small-magnitude earthquake records from the San
Francisco Bay Area. From 1.4 million horizontal component traces recorded
at 266 sensors for 737 earthquakes, we select 5194 traces based on S/N ratios.
The generated ground motions follow the PGV-magnitude and PGV-distance
relationships of the observations. The Fourier amplitude spectra values show
good agreement between observed and generated data over an entire range of
frequencies (2-15 Hz) used in this study. We further checked the kinematics of
the waveforms by picking P and S wave arrivals using PhaseNet. S wave arrivals are well reproduced while generated P arrivals tend to be earlier than theobservation. These evaluations demonstrate the effectiveness of the proposed
methods.
Euro-Mediterranean Hard-Rock Reference Ground Motion
Model by Git-Based Site Response Deconvolution
SHIBLE, H., SEISTER, Châtenay-Malabry, France, hussein.shible@seister.
fr; HOLLENDER, F., French Alternative Energies and Atomic Energy
Commission, Saint-Paul-lez-Durance / Grenoble, France, fabrice.hollender@
cea.fr; TRAVERSA, P., Electricité de France, Aix-en-Provence, France, paola.
traversa@edf.fr; BAUMONT, D., SEISTER, Châtenay-Malabry, France, david.
baumont@seister.fr; AMERI, G., SEISTER, Gémenos, France, gabriele.
ameri@seister.fr; THEODOULIDIS, N., Institute of Engineering Seismology& Earthquake Engineering, Thessaloniki, Greece, ntheo@itsak.gr
In the framework of site-specific seismic hazard assessment, the definition ofreference motion is a crucial step. Reference motion is generally associatedwith hard-rock conditions, characterized by S-wave velocity (VS) exceeding
2000 m/s. However, ground motion recorded at sites with such conditions

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is poorly represented in existing strong-motion databases. Thus, the validity
domains of most empirical ground motion models (GMMs) are not representative of reference rock conditions. In order to overcome this limitation,
we apply a deconvolution of site responses from strong-motion recordings toestimate ground motion at reference conditions in the Euro-Mediterranean
context.
The first step was to compile a large database by aggregating the ESM
database and additional data from the Greek, French, and Spanish networks.
The second step was to estimate site response at network stations by carryingout parametric and non-parametric generalized inversion techniques (GIT).
A careful selection of hard-rock reference stations was chosen to constrain
the inversions. The database signals are then deconvolved using the site terms
obtained by GIT, which makes it possible to virtually bring the sites of theentire database to very high VS values (bedrock conditions).
GMMs are then determined for reference conditions and the results are
discussed.
Observed Strong Motions and Site Effects During the Jan.
1, 2024 Noto-Hanto Earthquake in Japan and Its
Reproduction Based on a Priori Information
KAWASE, H., General Building Research Corporation of Japan, Suita,
Japan, h-kawase@gbrc.or.jp; ITO, E., Building Research Institute, Tsukuba,
Japan, ito@sere.dpri.kyoto-u.ac.jp; SUN, J., Kyoto University, Uji, Japan, sun.
jikai.8n@kyoto-u.ac.jp
On January 1, 2024, the Noto-Hanto earthquake of Mw7.6 occurred a little offshore of the Noto Peninsula in Japan. The shaking caused devastating damage
to wooden houses in rural cities and towns and local roads and expressways
on the peninsula. The casualties were over 200, and the number of collapsedbuildings could be over 10,000. The primary source of strong ground motions
was the western side of the whole fault segment, which was extended bilaterally to SSW and NNE directions for about 70 to 80 km from the epicenter at
the peninsula’s tip. About 20 strong motion stations are operated by NIED and
JMA within 60 km of the fault. The source was a south-dipping thrust fault,
the activity of which forms the Noto Peninsula. The highest observed PGA
was 2.7 g at one K-NET (NIED) site, ISK006 in Shiga Town, while the highest observed PGV was 1.5 m/s at ISK005 in Anamizu Town. We have visualevidence of the cyclic mobility phenomenon at ISK005, so the pore water pressure may play an important role at this site.
Before the earthquake, we performed the generalized inversion analysis (GIT) to separate source, path, and site terms from about 60,000 strong
motion records in Japan for both the S-wave portion with the maximum duration of 15 seconds and the whole duration of motion. The resultant horizontalsite amplification factor for the former is named sHSAF, while the latter is
wHSAF. If we have no significant basin effects, their spectral shapes are quite
similar, with some amplitude difference up to 2 times. If the sites are locatedinside sedimentary basins, a large discrepancy in amplitude in the smaller (0.1
~1 Hz) frequency range can be seen because of the strong generation of thebasin-induced surface waves. At 20 sites inside the Noto Peninsula, we cannot
find such a site with a large contribution of the basin-induced surface waves,and therefore, we can use the 1D assumption to extract sHSAF or wHSAF
from the observed data. We would like to show the validation exercise forour strong motion prediction technique based on GIT by using the observed
strong motion data in the epicentral area of this earthquake.
Exploring the Spatial Correlation of Ground Motions
During the 2019 Ridgecrest Earthquake Sequence
COCHRAN, E. S., U.S. Geological Survey, California, USA, ecochran@usgs.
gov; PARKER, G. A., U.S. Geological Survey, California, USA, gparker@usgs.
gov; MINSON, S. E., U.S. Geological Survey, California, USA, sminson@usgs.
gov; BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@usgs.
gov
We consider patterns in spatial correlations of recorded ground motions
during the 2019 Ridgecrest earthquake sequence. Ground motions are
known to vary widely from their median expected values, yet their spatial
distributions are not entirely random. To accurately estimate hazard acrossdistributed systems we must understand how ground motions correlate overa range of inter-station distances. The spatial correlation of ground motions
has been widely studied, but data are lacking at short interstation distances.
The 2019 Ridgecrest earthquake sequence presents a unique opportunity to
examine spatial correlations at a range of interstation distances. Following the
Ridgecrest earthquake, the permanent seismic network (Hauksson et al., 2020)
was augmented with tens of strong motion and broadband sensors that were
installed for several months (Cochran et al., 2020). Additionally, nodal seismic sensors were deployed for two-months at 585 recording sites with stationwww.srl-online.org•

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spacing as low as 100 m (Catchings et al, 2020). Using the gmprocess software
package (Hearne et al., 2019), we determine peak ground velocity (PGV) andacceleration (PGA) for 16,416 recordings from 120 earthquakes (M3.3-M5.0).
For each event and station pair, we compute the correlation of the within
event residuals determined from the fit to the median ground motion modelof Boore et al. (2014), considering local site conditions (Thompson 2020). We
use the typical assumption that all locations separated by a given distance will
have the same correlation and fit the results with an exponential semivariogram model (e.g., Baker and Chen, 2020). We find a nominal correlation distance (i.e., range measured from the fit to the exponential model) for PGA
and PGV of approximately 20 km, similar to what has been found for otherregions. We also explore whether the correlation distances vary spatially bydetermining correlation distances for sets of stations distributed around the
Ridgecrest source rupture.

ing, and the source and site random effects. We also include a novel distancedependent random effect on the source which removes the path effects thatare sometimes mapped in the source random effect in traditional analysis.
From the ergodic residu- als, a non-ergodic GMM is developed which captures the spatial variability of the source, site and path effects. The coordinate-specific source, site and paths effects show spatial correlation patterns
which can be accurately modeled via Gaussian Processes (GP) that allow us to
extrapolate them in space at unobserved source and site locations conditionally to observations and under physical constraints. As a result, the standard
deviation of the residuals at high frequencies is reduced by a factor of 2 fromthe ergodic GMM compared to the non-ergodic GMM (1.1 to 0.52 at 15Hz).
Going forward, the residuals of the ergodic GMM can be used as inputs tomachine learning to develop non-ergodic path effects at high frequencies thatcan be compared to the results of the non-ergodic GMM based on GP.

Use of Weak Motion Data to Constrain Site-Specific Ground
Motion Estimates
ANBAZHAGAN, B., Virginia Tech, Virginia, USA, balakumar@vt.edu;
RODRIGUEZ-MAREK, A., Virginia Tech, Virginia, USA, adrianrm@vt.edu;
VANTASSEL, J., Virginia Tech, Virginia, USA, jpvantassel@vt.edu; KOTTKE,
A., Pacific Gas & Electric Company, California, USA, ARKK@pge.com

Comparison of the Spatial Correlation of Non-Ergodic
Terms in GMMs Utilizing Empirical and Simulation Data
From Diverse Regions
SUNG, C., University of California, Berkeley, California, USA, karensung@berkeley.edu; ABRAHAMSON, N. A., University of California, Berkeley,
California, USA, abrahamson@berkeley.edu

With the increasing recognition of the importance of non-ergodic components in a seismic hazard analysis, it is becoming increasingly more important
to obtain site-specific amplification functions along with their uncertainties.
The most common approach is performing site response analyses backed bydetailed site characterization with measures of uncertainty. However, evendetailed site response is still associated with significant epistemic uncertainty.
An alternative approach would be utilizing recorded ground motions recordedat the site, if any, to constrain site effects. This approach is only viable if sufficient records are available at the site, which is generally not the case. However,for a seismically active region (such as California), rate of occurrence of small
magnitude earthquakes (i.e., Mw<4.5) can be high enough for weak groundmotions to be recorded using a temporarily deployed station within a practical
timeframe, especially for the design of critical structures. This then raises thequestion: Can weak ground motions resulting from small magnitude events
be used to constrain site effects? This study attempts to answer this question by
investigating weak ground motions recorded in California from earthquakes
with magnitudes ranging from 2.5 to 4.5. Using the ground motion recordings
near two sites in Northern California, a generalized inversion technique wasused to constrain source, path, and site terms, from which the site-specifictransfer function with measures of uncertainty was estimated. The estimatedtransfer functions were compared with analytical transfer functions computed
using 1-D site response analyses for two stations. The analytical transfer functions at these sites are slightly larger than the empirically constrained counterparts, thus overpredicting ground motions. Single-station variability atthese stations suggests the empirical transfer functions are stable when there
are enough ground motion recordings at the site. The approach proposed inthis study can be employed to empirically constrain site response using weakrecorded ground motions.

Recent studies, such as those by Sung et al. (2023) and Lavrentiadis et al.
(2023), have developed non-ergodic GMMs, which incorporate the spatial
distribution behavior of source, path, and site. These studies utilized the varying coefficient model (VCM) approach to account for the source, path, andsite effects on ground-motion scaling for a specific site and source pair. The
VCM considers the non-ergodic terms as spatially correlated random variables following assumed prior distributions, and it incorporates two hyperparameters derived from the posterior distribution: the correlation length andvariance for each non-ergodic term. The hyperparameters aid in predicting
the spatially correlated non-ergodic terms to adjust the ergodic model at a
specific site. In recent studies, the hyperparameters have been estimated forsix specific regions (California, France, Japan, Taiwan, Utah, and Cascadia)
based on empirical data or simulation data. The non-ergodic terms include
two site terms (one region site term that is spatially correlated and one uncorrelated site term), two path terms (one related to Q effects and one related
to the 3-D velocity structure effects), and one source term. We compare thecorrelation lengths for the four spatially correlated terms for these six regions.
Within the frequency range of 0.2-20 Hz, the correlation lengths from the
VCM for the non-ergodic source, path, and site terms are in the ranges of
20-50 km, 15-45 km, and 10-30 km, respectively. A consistent result is thatthe correlation lengths for the source and site terms at frequencies higher than
10Hz are large (10s of km), which seems counterintuitive, but this may reflect
regional kappa differences related to regional geology. In regions without
enough data to estimate region-specific hyperparameters, the sets of hyperparameters from the six regions can be used in the forward prediction of the
non-ergodic effects using the available region-specific ground-motion data.

Ergodic and Non-Ergodic Ground-Motion Models for Small
Magnitude Earthquakes in the San Francisco Region
LACOUR, M., University of California, Berkeley, California, USA,maxlacour@ucdavis.edu; ABRAHAMSON, N. A., University of California,
Berkeley, California, USA, abrahamson@berkeley.edu; NAKATA, R.,
Lawrence Berjkeley National Laboratory, California, USA, rnakata@lbl.gov;
NAKATA, N., Lawrence Berkeley National Laboratory, California, USA,nnakata@lbl.gov; REN, P., Lawrence Berkeley National Laboratory, California,
USA, pren@lbl.gov
An important issue in the propagation of seismic waves at high frequencies
into numerical simulations is the lack of knowledge of the 3-D velocity structure at short wavelengths. Empirical ground-motion data include the effectsof the 3-D crustal structure at high frequencies, but to have enough observations, record- ings from small-magnitude events are used. To use the smallmagnitude data to evaluate path effects requires a reference ergodic groundmotion model (GMM) to remove the average scaling and a non-ergodic
GMM to identify regions with strong path effects.
In this study, we focus on the small magnitude earthquakes in the San
Francisco region within 50km of the Hayward fault. From all the recordings
available in the NCEDC in that region, only the recordings with a signal-tonoise ratio S/N > 3 are selected. The resulting dataset includes about 5,000
recordings from 346 events recorded at 151 stations, with magnitude 1.5 to
4 at rupture dis- tance Rrup < 100km. From this dataset, an ergodic GMM isdeveloped, which includes the traditional magnitude, distance and depth scal-

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Toward an Alternative Approach for Using VS Profiles in
Estimating Seismic Site Response
PRETELL, R., University of Nevada, Reno, Nevada, USA, rpretell@unr.edu;
KATUWAL, S., University of Nevada, Reno, Nevada, USA, skatuwal@nevada.
unr.eduTwo techniques dominate the assessment of seismic site response in engineering practice. First, ground motion models (GMMs) that use the slowness at
the top 30 m (VS30) as a proxy to capture the effects of the shallow sedimentson the site amplification. Second, 1D site response analyses (1D SRAs) thatuse shear-wave velocity (VS) profiles. It is expected that 1D SRAs lead to moreaccurate site response estimates at frequencies higher than a given site’s fundamental frequency, as the entire VS profile is used and provides additional
information compared to VS30 alone. However, various studies have shownthat 1D SRA-based site response estimates carry a significant bias and uncertainty. These observations raise the question of whether the information carried by VS profiles adds additional value in 1D SRAs compared to VS30 in
GMMs or whether alternative approaches for leveraging VS profiles to estimate site response can be developed.
We investigate the ability of VS profile-related parameters to contributeto the predictability of site response in the linear elastic range. A systematic
evaluation using synthetic VS profiles is conducted to examine the ability ofVS profile-related parameters to add to the predicting ability of VS30 alone in
GMMs. VS profile-related parameters considered in this study include (1) the
maximum impedance contrast between consecutive soil layers, (2) the impedance contrast between the bedrock and the deepest soil layer, and (3) the VS
profile gradient. Preliminary results confirm that the investigated parameters

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have the potential to increase the predictive ability of site response models. In
this presentation, I will show the trends observed for various site conditions,and preliminary results from an initial assessment using observations from
borehole array sites.
Resonance vs Shape of Sedimentary Basins
CASTELLARO, S., Università di Bologna, Bologna, Italy, silvia.castellaro@
unibo.it; MUSINU, G., Enser, Faenza, Italy, giuseppe.musinu@enser.it
The dynamic behaviour of sedimentary basins is traditionally studied in theframe of 1D plane-parallel conditions, when the aspect ratio of the basin is
low, or by means of 3D numerical models, trying to replicate the real case.
The latter, however, require not always available parameters and rely on notalways verifiable assumptions. Between the idealized 1D and the real 3D cases,
an intermediate 2D idealized case can be conceived, whose properties constitute an important link to overcome the limitations of the 1D approaches andtowards the understanding of the complexity of real 3D cases. This intermediate case was studied in the ‘80s by means of analytical approaches and is here
more systematically explored, by exploiting the power of numerical methods.
Thus, we study the relations between the modal frequencies of idealized 2D
sedimentary filled basins and their geometrical properties, under different
Vs gradients, to show what information, often unused, might be hidden in
the resonance frequencies of basins. We show that when a basin geometry is
not known, but its modal frequencies have been experimentally assessed, theproposed relations offer a quick estimate of its aspect ratio, maximum depth,
and equivalent shear-wave velocity of the sedimentary filling. When the basingeometry is known, the proposed relations offer a prediction of the expected
modal sequence, thus helping in the design of future field surveys to bettercharacterize the basin fill. The proposed relations help understanding themain parameters governing the modal sequence in a basin and to quantify therole and the weight of each parameter. This also provides constraints on theinformation and the degree of accuracy effectively needed in the input parameters of site response analysis. The conceptual elements will be presented in ahistorical perspective.
Impact of Shallow Subsurface Stratigraphic Architecture
on Shear-Wave Velocity Prediction: Examples From the Po
Plain and Other Coastal Lowlands of Italy
AMOROSI, A., University of Bologna, Bologna, Italy, alessandro.amorosi@
unibo.it; DI MARTINO, A., University of Bologna, Bologna, Italy, andrea.
dimartino4@unibo.it
Detailed knowledge of shallow subsurface geology is essential to evaluate
ground response analysis and seismic site characterization. However, for theinvestigation of the shallow velocity structure, stratigraphic architecture isoften largely oversimplified. In this study, by adopting refined characterizationof sediment cores, we portray a new modeling approach that can be applied toa wide range of coastal plains with no topographic relief, and used for reliableprediction of S-wave velocities at the scale of the whole sedimentary basin.
Within the uppermost 30 m, modern alluvial plains and coastal lowlands exhibit predictable facies architectures that reflect sedimentary evolution under global climate and sea-level changes. Following 25 years of
research into the late Quaternary stratigraphy of the Po River plain, in Italy,
we carried out the geophysical characterization of seven sedimentary units(lithofacies associations) that accumulated in distinct depositional environments (floodplain, swamp, fluvial channel, lagoon/bay, beach, shelf) or underparticular conditions (paleosols). Individual lithofacies associations are typified by: (i) unique mechanical properties that cannot be captured by traditional engineering geology databases, (ii) distinctive (sheet-like, lenticular,
or wedge-shaped) geometries, (iii) specific Vs values that can be estimatedthrough Down-Hole measurements and calibration with high-resolution
analysis of sediment cores. The thickness of unconsolidated Holocene deposits (and thus the position of the engineering bedrock) was observed to vary
remarkably (10-55 m) from site to site, especially across the buried Adriatic
paleovalleys, in a predictable manner. Using accurate three-dimensional models of facies architecture, we can predict the proportion of different lithologies
along a stratigraphic column, and thus estimate shallow shear-wave velocity
profiles at any point. The resulting Vs30 map enables precise soil classificationthat primarily reflects subsurface geology and that can be used effectively forseismic site effect evaluation and earthquake engineering design purposes.

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Near-Surface Attenuation Estimated With Coda Waves:
Insights From Numerical Simulations and Empirical
Observations
JI, C., North Carolina State University, North Carolina, USA, cji3@ncsu.
edu; CABAS, A., North Carolina State University, North Carolina, USA,amcabasm@ncsu.edu; PILZ, M., GFZ Potsdam, Potsdam, Germany, pilz@gfzpotsdam.de; KOTTKE, A., Pacific Gas & Electric Company, California, USA,albert.kottke@gmail.com
Site-specific seismic hazard assessments require appropriate characterizations
and quantification of near-surface attenuation, which can be highly affectedby local geologic structures—also known as site effects. Site effects are a complex function of both shallow and deep geological conditions, topography andother factors, which cannot be explicitly parameterized by commonly usedsite parameters like the time-average shear wave velocity for the top 30 m
(Vs30). Recently, site-specific k0 has received increasing interest because of
its ability to capture the attenuation properties of near-surface materials, but
accurate characterization of this parameter has yet to be discovered. In thisstudy, a site-specific k0 is partitioned into a specific-specific increment anda regional contribution characterized by coda waves. Coda waves, which are
the backscattering waves of body waves, are expected to be less affected by theshallow soil deposits and more sensitive to the regional variations of hard rockattenuations at depth. Thus, recent studies attempted to measure the regionalk0 from surface ground motions. However, the differences between the physics underlying direct body-wave attenuation (i.e., P-wave and S-wave) andcoda-wave attenuation are still unclear. The limited understanding of the coda
wave propagation mechanism in complex media suggests further investigation is needed. In this work, we firstly examine the applicability to measureregional k0 with coda waves. Using ground motions from the DesignSafe
database, no correlations are observed between the S-wave and coda wave k0.
One-dimensional simulations are introduced to further study the coda propagation mechanism and associated variability.
Site-Specific Response Spectra Estimation at DesignatedSeismic Stations of the Puerto Rico Strong Motion Program
Seismic Network
HUERTA-LÓPEZ, C. I., University of Puerto Rico at Mayagüez, Puerto Rico,
USA, carlos.huerta@upr.edu; SUAREZ-COLCHE, L. E., University of Puerto
Rico at Mayagüez, Puerto Rico, USA, luis.suarez3@upr.edu; MARTÍNEZCRUZADO, J. A., University of Puerto Rico at Mayagüez, Puerto Rico, USA,jmac2861@gmail.com
Site-specific response spectra were estimated at sites location of designatedpermanent seismic stations of the Puerto Rico Strong Motion Program
Seismic Network (PRSMP-SN). Models of response spectrum are widely usedin earthquake-resistant buildings design. However, they do not necessarily
represent the behavior of a specific earthquake, and the soil amplification ispoorly incorporated. Site-specific response spectra have the merit to overcome
the two issues mentioned above. Designated sites of the PRSMP-SN were previously characterized by means of active-, and passive-MASW in order to estimate the VS30 shear-wave velocities, and the site transfer function estimation
using ambient vibration measurements. Results of the 2D VS-Z profiles of thestudied sites and their site/soil classification according to NEHRP range fromsoil type D, and C for the majority of the sites. Shear-wave velocity range were
between 260 to 300 m/s (Stiff-soil), to 350 to 680 m/s (Soft-rock). In terms of
NEHERP VS30 the soil type classification the majority of the sites still on the
category of soil type C. Results of the site-specific response spectra characteristics are discussed in terms of applications of engineering seismology.

How Well Can We Predict Broadband Site-Specific Ground
Motion and Its Spatial Variability So Far? [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Morteza Bastami, International Institute ofEarthquake Engineering and Seismology (m.bastmi@iiees.
ac.ir); Mohamad M. Hallal, University of California, Berkeley(mhallal@berkeley.edu); Chunyang Ji, North Carolina

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State University (cji3@ncsu.edu); Andrés Olivar Castaño,
University of Potsdam (andres.olivar-castano@uni-potsdam.
de); Marco Pilz, GFZ Potsdam (pilz@gfz-potsdam.de)poster 120
Application of Conditional Dynamic Variational
Autoencoder for Simulating Ground Motions in the
Geysers Geothermal Field
BI, Z., Lawrence Berkeley National Laboratory, California, USA, zfbi@lbl.
gov; REN, P., Lawrence Berkeley National Laboratory, California, USA, ren.
pu@northeastern.edu; NAKATA, R., Lawrence Berkeley National Laboratory,
California, USA, rnakata@lbl.gov; NAKATA, N., Lawrence Berkeley National
Laboratory, California, USA, nnakata@lbl.gov
Accurate simulation of ground motions caused by induced seismicity isimperative for engineering operations to mitigate large events and for advancing our understanding of source physics through correlating with stress,
strain and fluid flow monitoring. We focus on the Geysers geothermal fieldin northern California, whose induced seismicity activities have been linked
to geothermal energy production. Physics-based simulations require a large
computational cost and are susceptible to uncertainties in subsurface velocity
models. Deep generative models are attractive alternatives that directly utilize
observations. Based on the conditional dynamic variational autoencoder for
ground motion simulation (CD-VAE-GMG) model developed for small natural earthquakes in the San Francisco Bay Area, we aim to generate region-specific waveforms associated with induced seismic events. We introduce a novel
dynamic Variational Autoencoder design to ensure the statistical features of
the waveform envelopes and spectra shapes to be consistent with observationsin the time-frequency and time domains simultaneously.
Our model is trained to approximate the probability distribution of a vast
dataset of ground motions in the Geysers geothermal field. It simulates threecomponent waveforms conditioned on earthquake magnitudes, epicentral
distances, and earthquake depths. The training dataset comprises waveforms
from over 30,000 earthquakes with magnitudes ranging from 0 to 4, recorded
at 90 stations. Preliminary results demonstrate the effectiveness of the model.
Generated seismic waveforms match the observed waveforms in both timeand frequency domains, but some discrepancies remain in peak values andspectral shapes. We are improving the performance through data expansion,model tuning, and comprehensive validation. This study showcases the potential of machine learning techniques in simulating ground motion waveforms
caused by the induced seismicity and enhancing their prediction. We further
envision that our approach will become valuable for improving earthquake
hazard assessment and gaining insights into seismic source physics.
poster 121
Lateral Variation in Coda Wave Attenuation in Sikkim
Himalaya
SINGH, C., Indian Institute of Technology Kharagpur, Kolkata, India,
chandrani@gg.iitkgp.ac.in; DUTTA, A., Indian Institute of Technology
Kharagpur, Kolkata, India, abhi.dutta1995@iitkgp.ac.in
Spatial variations of coda wave attenuation (Qc) have been investigated in the
Sikkim Himalaya. We have used data from 2062 local earthquakes having an
epicentral distance of 130 km that were recorded by a dense network of 27
broadband seismic stations across the entire Sikkim region between April
2019 and May 2022. Variations of Qc with frequency suggest notable contrast
across the region manifesting diverse tectonics beneath Sikkim Himalaya. A
consistent high attenuation zone has been observed in central Sikkim, regions
close to curvilinear trends of MCT, where seismicity is mostly concentrated.
Northern Sikkim exhibits high Q values at all the frequencies where clear
arrivals from Moho have been observed from receiver functions study forthe seismic stations located in the north. The spatial distributions of Q0 (Qc )structure of the region is further investigated to examine the detailed attenuation characteristics across the region. It shows the differences in the attenuation characteristics across the region. A high attenuation pocket is evident in
the central segment while northern Sikkim shows less attenuative medium.
Our results reflect less complex crustal architecture below the northern partcompared to the central portion of the Sikkim Himalaya.
poster 122
Inversion of Earthquake-HVSR in the Anchorage Basin,
Alaska, for Delineation of Shallow Sedimentary Structures
DUTTA, U., University of Alaska Anchorage, Alaska, USA, udutta2@alaska.
edu; THORNLEY, J., WSP Global, Alaska, USA, john.thornley@wsp.com;

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YANG, Z., University of Alaska Anchorage, Alaska, USA, zyang2@alaska.edu;
ZHAO, Y., University of Alaska Fairbanks, Alaska, USA, yzhao8@alaska.edu;
STEPHENSON, W., U.S. Geological Survey, Colorado, USA, wstephens@
usgs.gov
The Anchorage strong-motion network has been operational in and aroundAnchorage, Alaska, since 1995. The stations are primarily Kinemetrics forcebalanced accelerometers with sampling rates of 200 Hz. Many seismologicalstudies have been conducted using the recorded data collected from these stations. An earlier study utilized strong-motion records of 95 earthquakes ofmagnitude 4.5 and above between 2004 and 2019, including the November
30, 2018, MW7.1 Anchorage Earthquake, to compute the earthquake horizontal-to-vertical-spectral-ratio (e-HVSR) at 35 strong-motion stations acrossAnchorage. A total of 1,727 three-component recordings were used for the
e-HVSR analysis. These records were processed, and the e-HVSR was calculated for each station over the 0.25–10 Hz frequency range. In this study, an
inversion of the e-HVSR data from each strong-motion station was performed
to obtain a 1-D layered earth soil profile for understanding the subsurface
characteristics at individual sites. The inversion searches for models that satisfy least-squares fit criteria using a very fast simulated annealing algorithm
and selected statistical tools, e.g., parameter correlation matrix and marginal
posterior probability density function for quantitative assessments of eachmodel. Where available, shear wave velocity data from the shallow boreholes
were set a priori during the inversion analysis. The inversion results indicate
the presence of higher-velocity (400–550 m/s) sediments at a relatively shallow (10–20 m) depth in the eastern part of the basin, at the foothills of the
Chugach Mountains, in comparison to the western and northwestern parts of
the Anchorage area. The inversion modeling of the e-HVSR results from thesites on the western and northwestern sides indicates sediments with lower
shear wave velocities (250 –350 m/s) at 30-50 m depth. A detailed analysisof the 1-D inversion results and a comparison to the local geology is alsopresented.
poster 123
Measuring Shallow Seismic Attenuation in the PacificNorthwest of the United States Using Ambient Noise
Seismology
FENG, K., University of Washington, Washington, USA, kffeng@uw.edu;
DENOLLE, M., University of Washington, Washington, USA, mdenolle@
uw.edu; NI, Y., University of Washington, Washington, USA, niyiyu@uw.edu
Owing to the impact on ground motion levels, seismic attenuation is one of
the major components of seismic hazard assessment. Active tectonic regions
tend to exhibit elevated attenuation and complex structures. This is notably
evident in the Pacific Northwest of the United States, a region known for
its combination of active volcanoes and active tectonics. We employ passive
noise interferometry on hundreds of broadband seismic stations in the PacificNorthwest to measure seismic attenuation properties. The NoisePy package
is utilized to calculate the single-station correlation functions from both permanent and temporary stations. Subsequently, we model the envelope of thecross-correlation coda waves by using the 2-D radiative transfer equation forscalar waves to estimate the intrinsic absorption parameters of Rayleigh waves.
Through the best fit between observed and synthetic energy density functionsof the envelopes of the coda, we derive the intrinsic absorption parameterof the medium. We analyze the data in multiple frequency bands, obtain the
intrinsic absorption parameter, and transfer it into intrinsic attenuation factor Q. Finally, we explore the spatial variations in the observed attenuation
parameters and discuss their values in the geodynamical context of the region.
poster 124
Relating Peak and Cumulative Ground Motions for
Earthquakes in the San Francisco Bay Area
HIRAKAWA, E. T., U.S. Geological Survey, California, USA, ehirakawa@
usgs.gov; PARKER, G. A., U.S. Geological Survey, California, USA, gparker@
usgs.gov; BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@
usgs.gov
We examine ~5000 ground motion records from 39 Mw3.5–6 earthquakes in
the San Francisco (SF) Bay Area with the goal of understanding site conditions leading to amplification in either the form of sharp velocity pulses or
longer duration resonant motion. Most estimates of seismic hazard are influenced by predicted peak ground velocity or acceleration (PGV or PGA). These
quantities are, in general, affected by higher frequency motions (>1Hz), andthus may not be good indicators of the kind of shaking that threatens long
period structures, such as tall buildings or bridges. Also, the peak motions do
not inform us about the duration or total dynamic load to a structure, which

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may be weakened after several successive pulses of significant amplitude. Thisis important for structures around the SF Bay shoreline, where sites in very
low velocity bay mud experience long duration ringing at ~1 Hz (Hirakawa
and Aagaard, 2022). This type of resonant motion is likely the cause of the collapse of the Cypress Viaduct during the 1989 Loma Prieta earthquake (Rogers,
1991).
We compute PGV and cumulative absolute displacement (CAD) for the
SF Bay Area ground motion records. CAD, the time integral of the absolute
horizontal velocity, inherently increases with PGV since it involves integrationof the largest velocity pulse but also incorporates additional motions. Sites thatexperience long duration ringing will have larger CAD than average. We consider each ground motion record in normalized PGV-CAD space and rotate
the dataset into principal components. We refer to the first principal component as the “primary intensity” which accounts for the expected increase in
CAD with PGV. We refer to the second principal component as the “excess
shaking”, which may be thought of as extra (or deficit) cumulative motion
apart from what would be typical for a given PGV. We investigate site-specifictrends in these two quantities and consider possible relations with subsurface
geology. The results of this study will expand our definition of site response
beyond changes to shaking amplitude, with direct application to the SF Bay
Area.
poster 125
A Comparative Study Between the Resonance Frequency
by Hvsr Analysis and Bedrock Depth in Western Busan,
Korea
KANG, S., Pusan National University, Geumjeong-gu, South Korea, sukang@pusan.ac.kr; KIM, K., Pusan National University, Geumjeong-gu, South Korea,
kwanghee@pusan.ac.kr; LEE, S., Pusan National University, Geumjeong-gu,
South Korea, pyroclas@pusan.ac.kr
Nakdong River is one of the major rivers in Korea that runs through the Busan
metropolitan area. During the 1.6 km long bridge construction across the river,twenty-seven boreholes were drilled to measure the depth of the bedrock.
This study determines the resonance frequencies at the borehole sites using
the HVSR (Horizontal-to-vertical spectral ratio) technique and compares
the results with direct measurements. Bedrock depths from the 27 boreholemeasurements vary from 38 to 70 meters. Although their variations are notserious along the 3.8 km long route, a relatively sharp decrease in the bedrock
depth was noticed near the borehole NSB-5 (~38 meters). We collected ambient noise data at locations near 27 boreholes in 2022 and estimated resonant
frequencies using the HVSR technique. Resonance frequencies from HVSRvary from 0.9 Hz to 1.3 Hz. A relatively high resonance frequency, 1.3 Hz, isestimated at NSB-5, which is consistent with the observations from the direct
measurements from boreholes. Details of the boring logs indicate that the sedimentary layers consist of multiple lithologic layers, including reclaimed soil,
silt sand, silt clay, and sand-mixed silt gravel. Since their impedance contrasts
are not significant, it is not evident from the HVSR curves. This study demonstrated a significant correlation between the depth of bedrock identified
in boreholes and the resonance frequency obtained through HVSR analysis
using microtremor observations. HVSR analysis effectively reflected the bedrock depth at the microtremor observation sites.
poster 126
Preliminary Site Characterization for Earthquake Hazard
Assessment Using Ambient Vibration Techniques in Haines
Junction, Yukon
LEISHMAN, T., University of Victoria, Victoria, Canada, tessleishman@gmail.com; GOSSELIN, J. M., University of Calgary, Calgary, Canada, jeremy.
gosselin@ucalgary.ca; DETTMER, J., University of Calgary, Calgary, Canada,
jan.dettmer@ucalgary.ca; CASSIDY, J., National Resources Canada, Sidney,
Canada, john.cassidy@nrcan-rncan.gc.ca; KANG, T., Pukyong National
University, Busan, South Korea, tskang@pknu.ac.kr
In this paper, regional mapping of soil stiffness is carried out to improve theunderstanding of seismic hazards in southwest Yukon, Canada, where local
amplification hazards are largely unknown. Ambient vibration (AV) measurements record microtremor seismic noise at broadband frequencies (0.1-128
Hz) and are used to calculate the horizontal-to-vertical spectral ratio andidentify resonant frequencies at sites. In situ estimation of fundamental frequency f0 is used to characterize sites and map local site amplification hazards.
We present preliminary site characterization using a combination ofarray and single station AV measurements from 23 sites in Haines Junction,
Yukon. Fundamental frequencies ranging from 0.3-0.8 Hz are identified at thesites. The preliminary results suggest lateral spatial variation in fundamental

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frequencies, with higher frequencies identified north of Haines Junction andlower frequencies identified in south-central Haines Junction. We attributethese observations to the basin of the Dezadeash River. Identification of discrete layering in the shallow subsurface (~2.5-12 m depth) at some sites suggests the presence of an active permafrost layer. Lateral heterogeneity is foundacross some sites, potentially the result of either near-surface (active layer) or
deeper (depth to bedrock) lateral variability.
poster 127
Influence of Buried Geometries on Ground Response
Analysis: The Case of the Pescara Paleovalley System
DI MARTINO, A., University of Bologna, Bologna, Italy, andrea.
dimartino4@unibo.it; SGATTONI, G., Istituto Nazionale di Geofisica e
Vulcanologia, Sezione di Bologna, Bologna, Italy, giulia.sgattoni@ingv.it;
PURRI, F., University of Bologna, Bologna, Italy, federico.purri@studio.
unibo.it; AMOROSI, A., University of Bologna, Bologna, Italy, Alessandro.
amorosi@unibo.it
Detailed ground response analyses (GRAs) require a deep understanding of
the geophysical properties and geometry of sediment bodies; however, GRAs
have focused traditionally on vertical characterization, underestimating theimportance of depositional architecture and the lateral variability of buried
geometries. In this context, late Quaternary paleovalley systems represent acomplex geological environment and a potential threat due to their unconsolidated infill, sharp contrast with adjacent substrates, and complex lenticulargeometries, which have often been oversimplified in the attempt to model sitespecific seismic effects. In this study, we employed a dense stratigraphic framework comprising continuous core stratigraphic descriptions, an extensive
network of microtremor measurements, Down-Hole tests, and undisturbed
samples for the estimation of shear modulus decay (G/G0) and damping
ratio (D%) to get robust, local data to perform GRA of the Pescara paleovalley system. Through the correlation of high-resolution stratigraphic data andmicrotremor measurements, we mapped resonance frequencies, highlighting
rapid changes in the frequency range of interaction with common building
types, and built the 3D geophysical depth model. The facies architecture wasreconstructed through a cross-section transversal to the paleovalley axis andimplemented into a 2D finite element model. GRA revealed higher seismic
amplification (reaching a factor of 4) compared to simpler geological contexts,
strongly linked to the buried paleovalley geometry, and peaked at frequencies between 0.9 and 1.3 Hz in the paleovalley center and up to 5 Hz towards
the flanks. We computed the response spectra and compared them with those
proposed by the Eurocode 8 guideline (EC8), which relies on soil category
and Vs30. Remarkably, the strong amplifications observed show a significant
underestimation of spectral accelerations compared to EC8. In this work, we
modeled the seismic amplification due to the buried paleovalley body, highlighting the importance of integrating geophysical and subsurface geological
data to achieve high-resolution GRA.
poster 128
Influence of Seasonal Frozen Soil on High-Frequency
Attenuation (κ0)
HAENDEL, A., GFZ Potsdam, Potsdam, Germany, ahaendel@gfz-potsdam.
de; PILZ, M., GFZ Potsdam, Potsdam, Germany, pilz@gfz-potsdam.de;
COTTON, F., GFZ Potsdam, Potsdam, Germany, fcotton@gfz-potsdam.de
When estimating site effects in terms of amplification or attenuation of seismic
waves, it is usually assumed that the seismic properties of the ground are constant over time. In recent years, several studies have shown that near-surface
shear wave velocities can be subject to a variety of environmental parameters,such as temperature, precipitation or groundwater level, leading to a variationof shear wave velocity with time. Similar observations have been partly madefor seismic attenuation, but studies investigating the influence of seasons on
seismic attenuation are very limited.
Herein, the parameter κ0 is commonly utilized to describe the sitespecific attenuation at high frequencies. We have calculated the differencein κ0 between surface and borehole station pairs of the KiK-net network in
the northeastern corner of Hokkaido, Japan. We observe that Δκ0 is almost
constant from May to November, but increases rapidly from late November
to early January. In January and February, Δκ0 is about 0.05 s higher than in
the summer (increased high-frequency attenuation), before returning to its
original value between March and April. This observation can be explainedby seasonally frozen soils of the upper few tens of centimeters, which add an
additional layer of increased shear wave velocity to the geological 1-D velocity
model below a station, thus increasing the high-frequency attenuation.

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poster 129
Combining Simulated and Empirical Nonergodic Ground
Motion Models for Southern California
SMITH, J., U.S. Geological Survey, Colorado, USA, jamesasmith@usgs.gov;
ENGLER, D. T., U.S. Geological Survey, Colorado, USA, dengler@usgs.gov;
MOSCHETTI, M. P., U.S. Geological Survey, Colorado, USA, mmoschetti@
usgs.gov; PARKER, G. A., U.S. Geological Survey, California, USA, gparker@
usgs.gov; THOMPSON, E. M., U.S. Geological Survey, Colorado, USA,emthompson@usgs.gov; PETERSON, R. H., Colorado School of Mines,
Colorado, USA, rhpeterson@usgs.gov
Partially nonergodic ground motion models (N-GMMs) have been developed
from simulated data (e.g., Sung and Abrahamson, 2022) and from recorded
ground motions (e.g., Parker and Baltay, 2022). Southern California is an
example where both N-GMMs can be applied; the Parker and Baltay (2022)
model is based on recorded ground motions from the greater Los Angeles
region, and Moschetti et al. (2023) is developing similar factors for this region
from Cybershake. These approaches have complementary benefits; for example, empirical data is limited at large magnitudes that are well-represented in
the simulation data. Conversely, simulated data are limited by the accuracy of
the three-dimensional velocity model while empirical data more accurately
capture the effects of path and site. We repeat the analyses of Parker and Baltay(2022) using each of the four NGAWest2 ground motion models (ASK14,
BSSA14, CB14, and CY14) as a common reference model for the empiricaland simulated datasets. We use a maximum likelihood method, as an alternative to the empirical semivariogram approach of Parker and Baltay (2022),
to compute the spatial correlation between site response terms as a functionof period for each dataset. In addition, we explore using cross-variograms toestimate the spatial cross-correlation between the empirical N-GMM andsimulation-based N-GMM as a function of period. Finally, we examine correlations between the simulation factors and surface geology and topography
in Southern California. These results combine two sources of constraints on
ground motion models and can be used to inform U.S. Geological Survey
products such as the National Seismic Hazard Model and ShakeMap.
poster 130
Shear Wave Velocity Structure Beneath a Dense Seismic
Array in the Presence of Local Noise Sources Using
Matched Field Processing
SONI, Y., Baylor University, Texas, USA, yashwant_soni1@baylor.edu;
PULLIAM, J., Baylor University, Texas, USA, jay_pulliam@baylor.edu
The presence of local sources in the ambient seismic wavefield causes bias
in the estimation of surface wave dispersion via seismic interferometry (SI).
Here we use Matched Field Processing (MFP) to capture local noise sources
and then extract more accurate surface wave phase velocity dispersion curves
from data recorded by a dense array of 2639 Fairfield Nodal Zland 1C nodes
deployed near Sweetwater, TX. These short period instruments recorded
continuously for 11 days, including signals from Vibroseis trucks at various
locations.
MFP is an array processing method that conducts a grid search of correlations between a recorded wavefield and a synthetic wavefield generated
by forward modeling. For each potential source location, an estimate of thephase match is computed between both wavefields over a certain frequency
band, taking coherency of the wavefields across stations into account. The
relative spatial phase differences between all sensors of the array patch can be
expressed as a Cross Spectral Density Matrix (CSDM). A 3D energy spectrum
matrix is obtained at each frequency and the peak of the energy spectrum
matrix corresponds to the location of the dominant noise source. The velocity
vector at the location of the noise source is extracted along the velocity axis as
the velocity distribution for the current frequency. Velocity vectors that correspond to each frequency are then normalized and stitched together along thefrequency axis to obtain the frequency-velocity energy spectrum, which is thedispersion energy map of the current data segment. Finally, we stack all thedispersion energy images from a single data segment to obtain a more stabledispersion energy map. This dispersion curve is then inverted using a Markov
Chain Monte Carlo (MCMC) approach to retrieve the 1D shear wave velocity
model beneath the patch of the array under consideration. Preliminary results
show that MFP produces a more accurate dispersion curve in the 4-20 Hz
frequency range than SI-based surface wave methods in the presence of local
noise sources.

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poster 131
Constraining Shear-Wave Velocity Profiles in Anchorage,
Alaska, Through Inversion of Microtremor Horizontal-toVertical Spectral Ratios
STEPHENSON, W. J., U.S. Geological Survey, Colorado, USA, wstephens@
usgs.gov; DUTTA, U., University of Alaska Anchorage, Alaska, USA,udutta2@alaska.edu; LINDBERG, N. S., U.S. Geological Survey, Colorado,
USA, nlindberg@usgs.gov; LEEDS, A., U.S. Geological Survey, Colorado,
USA, aleeds@usgs.gov; GOOZEN, A., University of Alaska Anchorage,
Alaska, USA, annikagoozen@yahoo.com; THORNLEY, J., WSP Global,
Alaska, USA, john.thornley@wsp.com
We modify shear-wave velocity (VS) profiles, obtained from modeling ofactive-source multimethod site characterization data at 19 strong motion
stations in the Anchorage, Alaska, region using microtremor horizontalto-vertical-spectral-ratio (mHVSR) data. The acquisition sites were locatedthroughout the City of Anchorage and northward through the Eagle Riverand Palmer-Wasilla areas. We deployed one 20-s-to-100-Hz three-component broadband seismometer for mHVSR data acquisition as part of ourmultimethod site characterization approach. We first calculate the mHVSR
curves through standard processing techniques (time-series detrending,mean amplitude removal, bandpass filtering from 0.5 to 50 Hz, calculation oftime-window averaged Fourier amplitude spectra, spectral smoothing). Then
we model the mHVSR fundamental frequency (F0) through inversion by anelitist genetic algorithm (EGA) technique. The initial VS models at each sitewere developed from iterative least-squares joint inversion of active-source
P- and S-wave refraction data complemented with Rayleigh and Love dispersion data, as previously described by Stephenson et al. (2022). However, thesemodels were often limited to less than 50 m depth because of acquisition logistics, particularly at sites in urban areas, and these models commonly were
not sufficiently deep to predict the observed mHVSR F0. By adding a layer
beneath the initial model depths and allowing up to 10% variability in theshallow layers defined by the active-source model, we extend the VS profiles
to greater depth through the EGA inversion of the mHVSR data. In addition,
the mHVSR modeling generally corroborate the depths of shallow high VS
impedance boundaries in the initial active-source models. The new VS profiles
incorporating mHVSR modeling will be used in support of ground motion
modeling and related earthquake hazards studies in the region.
poster 132
Seismic Site Characterization of Sikkim Himalaya Using
HVSR
UTHAMAN, M., Indian Institute of Technology Kharagpur, Kolkata,
India, mitutm710@iitkgp.ac.in; SINGH, C., Indian Institute of Technology
Kharagpur, Kolkata, India, chandrani@gg.iitkgp.ac.in; SINGH, A., Indian
Institute of Technology Kharagpur, Kolkata, India, arun@gg.iitkgp.ac.in;
BOSE, S., Indian Institute of Technology Kharagpur, Kolkata, India,
shirishbose@gmail.com
The northeastern state of Sikkim lying in the central segment of the Himalaya
orogen is a seismically active region which was plagued by the recent 2011
Mw6.9 earthquake. Analysis of local earthquakes recorded at the recently
deployed seismic network of 27 broadband seismic stations revealed multiple seismically active domains with peculiar stress orientations. This makes
it imperative to study the site characteristics crucial for determining the
local site conditions in the face of prevalent seismic activity. In this study, we
compute the horizontal-to-vertical spectral ratio (HVSR) of ambient noisefor local site characterization using the resulting peak amplification (A0)and resonant frequency (f0). Since our network was operational during the
COVID-19 pandemic, we have used the night time data during the lockdown
period to ensure analysis of the most stationary part of noise. HVSR curves areobserved to be varying distinctly with regional geology. Stations installed overthe sedimentary basin exhibit high A0at low f0, signifying the underlying thickdeposits and sharp impedance contrast. Multiple dipping sheets of the Lesser
Himalayan Duplex (LHD) could possibly be responsible for the double amplification peaks observed at stations installed over and around the LHD. The
high elevation topography of Higher Himalaya experiences great wind speeds,
which has the tendency to induce anomalously high A0at low f0evidenced bystations installed in northern Sikkim. We plan to further investigate how thesites respond during earthquakes, and also monitor if the HVSR trends vary
temporally.

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Illuminating Complex, Multiplet Earthquake Sequencesat Kahramanmaras (Turkiye), Herat (Afghanistan), andBeyondOral Session • Thursday 2 May • 8:00 am PacificConveners: Aybige Akinci, National Institute ofGeophysics and Volcanology (aybige.akinci@ingv.it); Pınar
Büyükakpınar, GFZ Potsdam (pinar@gfz-potsdam.de);
Gareth Funning, University of California, Riverside (gareth@ucr.edu); Alice-Agnes Gabriel, University of California, San
Diego (algabriel@ucsd.edu); Mohammadreza Jamalreyhani,
SUSTech, China (jamalreyhani@sustech.edu.cn); Edwin
Nissen, University of Victoria (enissen@uvic.ca)
The October 2023 Herat, Afghanistan Earthquake
Quadruplet - Aftershock Locations and Moment Tensors
BRAUNMILLER, J., University of South Florida, Florida, USA, jbraunmiller@
usf.edu; GHODS, A., Institute for Advanced Studies in Basic Sciences, Zanjan,
Iran, aghods@iasbs.ac.ir
A series of four magnitude Mw=6.3 earthquakes struck the Herat province
in northwestern Afghanistan in October 2023 causing widespread destruction and killing almost 1,500 people (information from the World HealthOrganization). All four main events have thrust mechanisms. Rupture likely
occurred on blind thrust faults as no surface ruptures have been reported
precluding a clear interpretation of fault dip direction(s). Fault segmentation, which could cause delayed rupture on adjacent segments, cannot be
addressed due to the low resolution of existing earthquake locations as theevents occurred far from seismic networks. The distance from the epicentral
area to the closest permanent seismic stations in northeastern Iran is about
150 km and to the closest station in the east, the IRIS station in Kabul, about
650 km. To improve understanding of spatial relations and faulting styles, we
use data from the Iranian seismic networks and from other stations at regional
distances to locate the sequence and to obtain moment tensor solutions. Our
preliminary results from locating over 100 earthquakes from 7 October to
20 November 2023 reveals a roughly 50x20 km distribution elongated in
the west-northwest direction that coincides well with the uplift region fromInSAR data (from LiCSAR). Moment tensors of the main events and 10 aftershocks (Mw 4.1-5.8) indicate predominantly thrust faulting on roughly eastwest oriented faults. The shallow centroids of ~3-5 km for the main events
suggest ruptures may have reached close to the surface perhaps explaining
the localized strong destruction. Our results are consistent with rupture on ablind fault structure north of the right-lateral Herat (or Hari Rud) fault andsouth of the Siakhubulak fault. The Herat fault system is the dominant physiographic feature that connects the Arabia-Eurasia and India-Eurasia collisionzones and, combined with sub-parallel thrust faults such as the one(s) active
in 2023, accommodates any remaining relative plate motions.
Long-Term Seismicity of the East Anatolian Fault System
and Its Relationship With the 2023 Mw 7.8 & 7.6
Kahramanmaraş (Se Türkiye) Earthquake Doublet
ZHOU, Y., University of California, Riverside, California, USA, yijian.zhou@
email.ucr.edu; DING, H., Peking University, Beijing, China, ddhy@pku.
edu.cn; GHOSH, A., University of California, Riverside, California, USA,aghosh@ucr.edu; GE, Z., Peking University, Beijing, China, zge@pku.edu.cn
The destructive 2023 Mw 7.8 & 7.6 Türkiye doublet (abbreviated as M1 & M2)
breaks multiple fault segments along the East Anatolia Fault (EAF) system,
forming one of the largest continental doublets ever recorded. To understand
why the 2023 event developed to such a scale, we reconstructed a high-resolution long-term earthquake catalog ranging from 2020-2023 to better characterize the EAF fault behavior before and after the mainshocks. We adopt
a deep learning-driven cataloging workflow called TED (Zhou et al. 2019,2024), i.e. Training-based Earthquake Detection that applies Self-Attention
RNN (SAR) for phase picking. We downloaded continuous broad-band datafrom AFAD and FDSN, forming a network of 64 stations that covers the whole
EAF region. Our final catalog contains 38,424 events before the 2023 doublet
and 85,520 aftershocks, which is a ~3 times increase of the AFAD catalog.
We find that seismicity before the 2023 doublet are low along the ruptured segment of EAF, except for the branch fault that nucleate M1 (abbreviated as nucleation branch thereafter). Similar quiescent feature was foundalong the Çardak-Sürgü Fault (CSF) that is responsible for M2. This pattern

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Seismological Research Lettersagrees with the fact that the ruptured segments are strongly locked during
preseismic period. We specifically analyze the seismically active nucleation
branch, and found that (1) microseismicity were dynamically triggered by the2020 Mw 6.8 event, and (2) 3 seismic swarms were developed in 6 months
before the mainshock. Both observations suggest that the nucleation branch
was critically stressed before the earthquake. On the eastern end of EAF rupture, i.e. the western end of 2020 rupture, seismicity revealed a sharp change
in fault dip. Moreover, preliminary results show that 4 repeater sequences of
ML 2.0-2.6 exist in the gap between the 2020 & 2023 rupture, which occur
both before and after the 2023 doublet, indicating fault creep. Thus, long-term
seismicity helps constrain the fault coupling condition of EAF, and provides
insights on the nucleation and termination of the 2023 Türkiye doublet.
The Kahramanmaras (Turkey) Earthquake Multiplet
Sequence Revealed by Deep Learning Computer Vision
TAN, F., University of Victoria, Victoria, Canada, fengzhou.tan@gmail.com;
NISSEN, E., University of Victoria, Victoria, Canada, enissen@uvic.ca; KAO,
H., Geological Survey of Canada, Sidney, Canada, HonnKao@gmail.com
The February 6, 2023 Kahramanmaras (Turkey) earthquake multiplet
involved two mainshocks ~9 hours apart on neighboring faults within the
Arabia-Anatolia collision. The first M 7.8 event, the largest ever recordedon the East Anatolian Fault, and the subsequent M 7.6 event, collectively
resulted in over 50,000 fatalities. Accurately detailing this earthquake multiplet sequence, including the interval between the two mainshocks as well as
subsequent aftershocks, is important for advancing our understanding of seismogenic processes and regional tectonics, which in turn underpin earthquake
science and hazard mitigation. Deep learning is becoming a powerful tool forseismological analysis, and our new algorithm, the Source Untangler Guided
by Artificial intelligence image Recognition (SUGAR) (Tan et al., submitted),
has proven to outperform skillful human analysts and popular AI and non-AI
workflows in delineating complex earthquake sequences. SUGAR applies a 3D
computer vision technique to the brightness video produced by the SourceScanning Algorithm (Kao and Shan, 2004), guiding the phase association andmaking it possible to locate small events with poorly discernible waveforms,
even when occurring concurrently. In this study, we retrain a SUGAR modelwith seismic stations in Turkey and apply it to the Kahramanmaras earthquake
sequence from before the first mainshock to the end of April 2023. SUGAR’s
unusual ability at untangling complex signals is especially valuable in the earlystage of the sequence, such as the ~9-hour interval between mainshocks. The
SUGAR catalog has ~6 times as many events as the routine KOERI catalog.
Results indicate that the first M 7.8 earthquake initiated on a secondary, westdipping fault branch and propagated to the main subvertical East Anatolian
Fault. The M 7.8 mainshock rupture terminated short of the 2020 M 6.8 Elazig
earthquake, but remote aftershocks were triggered on the NE side of the 2020
rupture. The M 7.6 earthquake ruptured the Savrun-Cardak fault, but left aclear gap between it and the M 7.8 earthquake.
Surface Expression of the Narlı and East Anatolian Fault
Rupture Intersection in the 2023 M7.8 Pazarcık, Türkiye
Earthquake
DUROSS, C. B., U.S. Geological Survey, Colorado, USA, cduross@usgs.gov;
REITMAN, N. G., U.S. Geological Survey, Colorado, USA, nreitman@usgs.
gov; HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@usgs.
gov; MASON, H., U.S. Geological Survey, Colorado, USA, hmason@usgs.
gov; LAVRENTIADIS, G., California Institute of Technology, California,
USA, glavrent@caltech.edu; ASIMAKI, D., California Institute of Technology,
California, USA, domniki@caltech.edu; MILLINER, C., California Institute ofTechnology, California, USA, milliner@caltech.edu; KARAKAŞ, M., Istanbul
Technical University, Istanbul, Turkey, karakas17@itu.edu.tr; SEÇEN, B.,
Hacettepe University, Ankara, Turkey, bahadir.secen@hacettepe.edu.tr
Field observations of surface rupture and displacement in multisegment or
multifault earthquakes contribute to our understanding of how rupture initiation, propagation, and arrest are expressed at the earth’s surface. The 2023
M7.8 Pazarcık earthquake in southeastern Türkiye represents a unique case of
rupture initiation on the subsidiary Narlı fault, northward propagation, andtriggering of bilateral East Anatolian fault (EAF) rupture. We evaluate thisrupture sequence using field observations. In June 2023, we mapped parts of
the M7.8 earthquake rupture north of the epicenter and recorded 68 measurements of left-laterally displaced cultural and natural features. We focused on
a 30-km-long reach of the EAF that lacked previous field or remote observations of surface rupture and included the projected intersection with thenorthernmost Narlı fault. Field data show 10 km of previously unobserved
EAF surface rupture northeast of Çiğli that is laterally continuous, locally distributed, and right stepping. Left-lateral EAF offset measurements range fromwww.srl-online.org•

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~1.8 to 6.8 m. Along a northeastern extension of the Narlı fault near Tetirlik,
we observed 5 km of subtle and discontinuous rupture with 0.3–0.7 m of leftlateral displacement. We infer that EAF–Narlı fault interaction is expressedas 1) northeast-trending scarps along the eastern of two possible Narlı fault
connections inferred from satellite observations, 2) a change in EAF displacement from ~2–5 m southwest to 6–7 m northeast of this intersection, and 3) adecrease in the lateral continuity of the EAF surface rupture at this projectedintersection. This work highlights the importance of making systematic fieldbased rupture observations as it provides key data to constrain the kinematicsof the M7.8 EAF rupture and provides benchmark field observations for comparison to remotely sensed displacement data.
Seismic Analysis of the 2023 Earthquake Sequence inSoutheast Türkiye: Insights From Mainshocks andAftershocks
BÜYÜKAKPINAR, P., GFZ Potsdam, Potsdam, Germany, pinar@gfzpotsdam.de; PETERSEN, G., GFZ Potsdam, Potsdam, Germany, gesap@gfzpotsdam.de; VERA SANHUEZA, F., GFZ Potsdam, Potsdam, Germany, felipe.
orlando.vera.sanhueza@gfz-potsdam.de; METZ, M., GFZ Potsdam, Potsdam,
Germany, mmetz@gfz-potsdam.de; CESCA, S., GFZ Potsdam, Potsdam,
Germany, cesca@gfz-potsdam.de; AKBAYRAM, K., Bingöl University, Bingol,
Turkey, kakbayram@gmail.com; SAUL, J., GFZ Potsdam, Potsdam, Germany,saul@gfz-potsdam.de; DAHM, T., GFZ Potsdam, Potsdam, Germany, torsten.
dahm@gfz-potsdam.de
Two Mw 7.7 and 7.6 earthquakes struck southeast Türkiye on February 6,
2023. The series of earthquakes resulted in extensive destruction and tensof thousands of fatalities in Türkiye and Syria. Using complimentary source
characterization methodologies and local, regional, and teleseismic data, weinvestigate both mainshocks and aftershocks. While the details of the fault
network are resolved by centroid moment tensor inversion for 221 aftershocks(Mw ≥ 3.7), back-projection analysis and finite source inversion for the mainshocks reveal coseismic slip, rupture length, and propagation mode along themain faults. Activating the nearby East Anatolian fault zone (EAFZ), the initial mainshock nucleated on a splay fault which is ~20 km off from the main
fault zone. Along approximately 500 km, it ruptured bilaterally on many previously partially dormant fault segments, first toward the northeast and thento the south-southwest during 117 s. The east-west oriented Sürgü-Misis fault
zone (SMFZ) was ruptured by the second mainshock, over ~115 km within 32
s with a slip of 7 m. The reconstruction of slip in the Bayesian bootstrap-based
probabilistic joint inversion scheme exploits the model space and trade-offof extended source parameters for the two mainshocks. Source time functions are retrieved without pre-assumptions, and sub-shear rupture velocities
are found. Interestingly, the stress drops retrieved from the extended source
model were quite different between the mainshocks, with values of 5 and 11
MPa, respectively. The kinematic rupture is also used to calculate slip-induced
stress changes which are compared with spatial aftershock distributions. We
retroactively reconstruct rupture details using aftershocks with heterogeneous
moment tensors including strike-slip, normal, and thrust events. This not only
sheds new light on the geometry and behavior of large structures along the
SMFZ but also maps the geometry of various segments along the main strandof the EAFZ. Our research provides valuable insights into the complex rupture
evolution and fresh perspectives on the catastrophic earthquake sequence of2023.
High-Resolution Fault Imaging From Fault Zone Guided
Waves Recorded by Dense Arrays in the Aftershock Zone of
the 2023 Kahramanmaras Earthquake Sequence inSouthern Türkiye
PENG, Z., Georgia Institute of Technology, Georgia, USA, zpeng@gatech.edu;
MACH, P. V., Georgia Institute of Technology, Georgia, USA, pmach3@gatech.
edu; DING, C., Georgia Institute of Technology, Georgia, USA, cding64@
gatech.edu; YALVAC, O., University of Missouri, Missouri, USA, oyzgb@
missouri.edu; SEVIM, F., Scientific and Technological Research Council of
Türkiye, Gebze, Turkey, fatih.sevim@tubitak.gov.tr; TAPIRDAMAZ, M. C.,
Scientific and Technological Research Council of Türkiye, Gebze, Turkey,
mustafa.tapirdamaz@tubitak.gov.tr; TARANCIOĞLU, A., Scientific andTechnological Research Council of Türkiye, Gebze, Turkey, adil.tarancioglu@
tubitak.gov.tr; ERGIN, M., Scientific and Technological Research Councilof Türkiye, Gebze, Turkey, mehmet.ergin@tubitak.gov.tr; ZOR, E., Scientificand Technological Research Council of Türkiye, Gebze, Turkey, ekrem.
zor@tubitak.gov.tr; SANDVOL, E., University of Missouri, Missouri, USA,
sandvole@missouri.edu

the East Anatolian Fault (EAF) in Southern Türkiye, and a M7.5 event near
Ekinözü in Kahramanmaraş Province nine hours later. These events were followed by numerous aftershocks around both mainshock rupture zones. To
better capture the ongoing aftershock sequence, we deployed up to 200 5-Hz
Smartsolo nodal stations and 16 broadband/strong motion stations acrossnearly the entire rupture zone for more than three months. Our array also
includes a one-month deployment of an ultra-dense fault zone profile acrossthe Pazarcık segment of the EAF and the Sakçagöz-Narlı Fault (SNF) where
the M7.8 mainshock initiated. In this study, we present clear evidence of seismic waves generated by fault zone structures and use them for high-resolution
imaging of the low-velocity damage zone (LVDZ) across the EAF. We first
select ~80 events within 20 km of the array center (C000), which is situated at
the surface rupture of the M7.8 mainshock. We then rotate the two horizontal
components to fault-parallel and fault-normal directions, and visually identify
fault zone trapped waves (FZTWs) as long-period dispersive waves due tointernal reflections within the LVDZ following the direct S waves at stations
immediately surrounding the EAF. We find that FZTWs are recorded at morestations east of the array center rather than to the west, likely indicating an
asymmetry in the LVDZ. Alternatively, it is related to the presence of quaternary basin with an estimated thickness of ~250 m based on the HVSR method.
Our preliminary analysis shows that aftershocks directly beneath both twoparallel faults can generate FZTWs recorded at stations along the Pazarcık
segment of the EAF. Our next step is to quantify the degrees of FZTWs forevents at different locations, and combine both FZTWs and time delays of
direct P and S waves to better constrain the depth extent and geometry of thedamage zone associated with the M7.8 mainshock.
Strong Ground Motion Characterization for the 6 February
2023 Mw 7.8 Pazarcık Earthquake in Kahramanmaraş,Türkiye
TANG, Y., King Abdullah University of Science and Technology, Thuwal,
Saudi Arabia, tangyuxiang56@gmail.com; ŞEŞETYAN, K., Boğaziçi
University, Istanbul, Turkey, ksesetyan@gmail.com; MAI, M., King Abdullah
University of Science and Technology, Thuwal, Saudi Arabia, martin.mai@kaust.edu.sa
The devastating 2023 Mw 7.8 Pazarcık earthquake, had a profound impact onsouth-central Türkiye and northwestern Syria, resulting in over 50,000 casualties and widespread damage. To better understand earthquake source properties and wave-propagation effects, we analyze strong ground-motion data
recorded at ~230 stations. Our study involves determining regional distancedependent attenuation using the Fourier acceleration amplitude spectrum(FAS) within the frequency 0.1 – 20 Hz. An apparent near-source saturation
effect necessitates the incorporation of an additional finite-fault factor for
distance scaling. We conduct uncertainty and sensitivity analyses, considering variable decay rates in the geometric spreading model. Significant duration of ground motions is modelled for two different measurements basedon Arias intensity. We then construct a site amplification model incorporating both VS30-scaling and peak ground acceleration (PGA)-scaling. Source
parameters are then determined by fitting a theoretical Brune’s ω2 model witha reference Fourier source spectrum at 1.0 km. Our estimates result in a meancorner-frequency 0= 0.036 Hz, a Brune stress drop Δσ = 4.79 MPa, and a reference rock site (VS30 = 800 m/s) κ0 = 0.051 s. Analyzing near-source pulse-likewaveforms, we demonstrate that the mismatch of peak ground velocity (PGV)
between our model and near-fault observations is due to rupture directivity.
Finally, we compare ground motions of the Mw 7.8 Pazarcık event to those of
Mw 7.6 Elbistan and the 2020 Mw 6.7 Sivrice earthquakes. We find that theattenuation effects for the three events are identical in the frequency range~0.2 – 6.0 Hz, with only minor differences in site responses above ~5.0 Hz.
Source-spectra comparisons clearly indicate complex source properties for
all three events. Our ground-motion analyses contribute to a better understanding and modeling of regional properties of attenuation, site response,and event-based source characteristics that are important for future regionspecific seismic hazard assessment.
Conjugate Strike-Slip Faulting in the Truckee Basin of
California, Northern Walker Lane
PIERCE, I. K. D., U.S. Bureau of Reclamation, Colorado, USA, ian@
nevada.unr.edu; KOEHLER, R., Nevada Bureau of Mines and Geology,
Nevada, USA, rkoehler@unr.edu; OWEN, L., North Carolina State
University, North Carolina, USA, lewis.owen@ncsu.edu; WESNOUSKY,
S., Nevada Seismological Laboratory, Nevada, USA, wesnousky@unr.edu;
FIGUEIREDO, P. M., North Carolina State University, North Carolina, USA,The 2023 Kahramanmaras earthquake sequence includes a M 7.8 earthquake
initiated near Nurdağı in Gaziantep ruptured for more than 300 km along

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paula_figueiredo@ncsu.edu; KHASHCHEVSKAYA, D., North Carolina State
University, North Carolina, USA, dkhashc@ncsu.edu
The Walker Lane belt is a ~150 km wide zone of distributed and discontinuous transtensional faulting that roughly follows the California-Nevada border from Death Valley to Mohawk Valley, CA. This belt accommodates ~25%of the relative dextral transform motion between the North American andPacific Plates. In the Northern Walker Lane, this dextral shear is accommodated across a series of normal-fault bound basins in conjunction with both
northwest-striking right-lateral faults and conjugate northeast-striking leftlateral faults.
We present new lidar-based mapping in the Truckee Basin showing that
the Polaris, Truckee, and Dog Valley are active conjugate strike-slip faults
cutting a prominent sequence of glacial landforms and deposits emanatingfrom the adjacent Sierra Nevada crest. Our paleoseismic trenching study ofthe ~25-km-long northeast-striking left-lateral Dog Valley fault provides
evidence for one earthquake that occurred ~8.5–8.3 ka and a younger earthquake that postdates 8.3 ka. Three-dimensional trenches show that the mostrecent earthquake produced 115 cm of left-lateral slip. We present 29 new
preliminary 10Be and 36Cl cosmogenic exposure ages of boulders from glacial
moraines and outwash terraces in the Truckee basin. These ages provide limits
on the late-Pleistocene (post-140 ka) slip rates of the ~35-km-long northweststriking Polaris and Truckee faults. The age of a displaced glacial outwash
channel shows that the Polaris fault has a right-lateral slip rate of 0.45+0.28/0.06 mm/a. Our mapping shows that the Truckee fault is a right-oblique slip
fault and forms the northerly continuation of the West Tahoe fault. Glacial
moraines displaced by the Truckee fault provide a right-lateral slip rate of
0.22+0.09/-0.04 mm/a and a vertical slip rate of 0.12+0.09/-0.06 mm/a. The sum ofthese two faults’ dextral slip rates is less than half the maximum limit of ~3
mm/a of northwest-directed right-lateral shear measured by GPS across thebasin. Taken together, these three conjugate faults raise questions in light ofrecent conjugate earthquake sequences in both the Walker Lane and abroad.
How Often Do Subduction Interfaces and Overriding
Upper-Plate Faults Rupture in the Same Earthquake (OrClose Enough in Time to Be the Same Situation)?
ROLLINS, C., GNS Science, Kelburn, New Zealand, c.rollins@gns.cri.
nz; PENNEY, C. E., University of Canterbury, Christchurch, New Zealand,camilla.penney@canterbury.ac.nz; HOWELL, A., University of Canterbury,
Christchurch, New Zealand, andrew.howell@canterbury.ac.nz; FRY, B., GNS
Science, Lower Hutt, New Zealand, b.fry@gns.cri.nz; NICOL, A., Universityof Canterbury, Christchurch, New Zealand, andrew.nicol@canterbury.ac.nz
Many global cities such as Anchorage, Karachi (Pakistan), Guayaquil(Ecuador) and Wellington (New Zealand) are located in strain-partitioned
environments. For these cities, the worst-case-scenario earthquake might bea joint rupture of the subduction zone and one or more upper-plate faults.
For example, the worst-case-scenario earthquake for Wellington would
be a joint rupture of the southern Hikurangi interface and the southern
Wellington Fault: the first would pose a tsunami hazard, the second would
rupture lifelines, and both would cause strong shaking. However, the likelihoods and characteristics of joint ruptures are not particularly well understood, as there are only a handful of well-known cases of them (among which
are the 1964 M=9.2 Alaska, 1855 M=8.2 Wairarapa and 2016 M=7.8 Kaikoura
earthquakes). In applications of physics-based earthquake simulators to New
Zealand within the RNC national science challenge programme, joint subduction/upper-plate ruptures occur frequently (e.g., Shaw et al., 2022), but it isuncertain how much this behaviour is controlled by modelling assumptions
and details of model setup. To ground-truth the earthquake simulators, welook at the largest recorded subduction earthquakes around the world andexamine how many of them also involved slip on upper-plate faults, or wereclosely followed by large upper-plate aftershocks. We also examine potential interactions between subduction-interface and upper-plate seismicity in
Hikurangi earthquake sequences in 1961 and 1990. Finally, we note that bothcosesismic and early aftershock triggering of upper plate faults, as commonly
seen in simulators, have significant consequencs for event response and emergency management systems stress testing.
2021 and 2022 North Coast California Earthquake
Sequences Light Up Gorda Plate Faults Beneath the North
American Plate
HELLWEG, M., University of California, Berkeley, California, USA,
hellweg@berkeley.edu; DREGER, D. S., University of California, Berkeley,
California, USA, ddreger@berkeley.edu; LOMAX, A., ALomax Scientific,
Mouans-Sartoux, France, alomax@free.fr; MCPHERSON, R. C., California

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State Polytechnic University, Humboldt, California, USA, robert.mcpherson@
humboldt.edu; DENGLER, L. A., California State Polytechnic University,
Humboldt, California, USA, lad1@humboldt.edu
The Mendocino Triple Junction (MTJ), north of 40N and west of 122W, is
one of California’s tectonically most active and complex regions. Two earthquake sequences in the MTJ region, beginning on 2021-12-20 (2021) and2022-12-20 (2022), respectively, highlight the faults in the Gorda plate as it
subducts beneath the North American plate. Upgrades to the instrumentation in the region in recent years allow a detailed exploration of the seismicity
and finite faulting associated with these earthquakes, in order to better define
the faults within the subducting Gorda plate, as well as their modes of rupture. The December 2021 sequence began with a doublet, separated by ~11s in time and 30 km in space. Detailed analysis indicates that the first event
was offshore (2021-OFF) on the Mendocino fault (MF) between the Pacificand Gorda plates. The second event was onshore (2021-ON) at a depth of 24
km within the subducting Gorda plate and was most likely triggered by the
S-waves of 2021-OFF. Simultaneous finite source modeling of the two events
indicates that they have about the same magnitude, M~6.1, despite the waveforms of 2021-OFF appearing smaller in recordings because it was more distant from all recording stations which are onshore. The source analysis showsthat 2021-OFF ruptured eastward along the MF, and 2021-ON ruptured to
the NE. The 2022 sequence began with a mainshock (2022-MS, M6.4) justoff Cape Mendocino to the NW of 2021-ON, also on a fault within the Gorda
plate. Its largest aftershock (2022-AS, M5.4) took place 11 days later about 40
km to the ESE of the main fault rupture. Finite source analysis of 2022-MS
indicates that it ruptured NE, toward the towns in the area and caused damage
exacerbated by 2022-AS.

Illuminating Complex, Multiplet Earthquake Sequencesat Kahramanmaras (Turkiye), Herat (Afghanistan), andBeyond [Poster Session]
Poster Session • Thursday 2 May
Conveners: Aybige Akinci, National Institute ofGeophysics and Volcanology (aybige.akinci@ingv.it); Pınar
Büyükakpınar, GFZ Potsdam (pinar@gfz-potsdam.de);
Gareth Funning, University of California, Riverside (gareth@ucr.edu); Alice-Agnes Gabriel, University of California, San
Diego (algabriel@ucsd.edu); Mohammadreza Jamalreyhani,
SUSTech, China (jamalreyhani@sustech.edu.cn); Edwin
Nissen, University of Victoria (enissen@uvic.ca)
poster 67
Coulomb Stress Variation and Frictional Properties Control
Postseismic Fault Slip and Late Aftershocks of the 2022
Zagros Earthquake Sequences: Deductions From BayesianInference and Insar Observations
ZHAO, X., GFZ Potsdam, Potsdam, Germany, xiong@gfz-potsdam.de;
DAHM, T., GFZ Potsdam, Potsdam, Germany, dahm@gfz-potsdam.de;
VASYARA-BATHKE, H., GFZ Potsdam, Potsdam, Germany, vasbath@gfzpotsdam.de; XU, C., Wuhan University, Wuhan, China, cjxu@sgg.whu.edu.cn
On 1 July 2022, a doublet of earthquakes both with magnitudes of Mw 6.0
occurred within two hours in the south-eastern part of the Zagros Mountains
near the Persian Gulf in Iran. The earthquakes were relatively shallow andcaused significant co- and postseismic surface deformation, which could
be measured using ascending and descending InSAR scenes. We used thesedata to invert the geometry of the co-seismic slip and to simulate postseismic deformation mechanisms of the two mainshocks, repectively. A Bayesianinference approach confirmed that the two mainshocks occurred on two distinct faults with similar strike angles but different dip angles and fault depths.
The maximum afterslip is concentrated in the shallow portion of the faults
and reached approximately 0.45 m. We distinguish the temporal evolution ofkinematic and stress-driven afterslip and infer significant variations in frictional properties, particularly between the Hormoz salt layer and its uppersedimentary cover. Friction is stronger above the salt layer and the relaxation
time of the afterslip is shorter there. The model confirms and quantifies thedecoupling role of the salt layer during and after earthquakes in the southeastern foothills of the Zagro Mountains.

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poster 68
Rupture History and Elastic Interaction of the 2022
Multiple Earthquakes in the Zagros Mountains, Iran
METZ, M., GFZ Potsdam, Potsdam, Germany, mmetz@gfz-potsdam.de;
ASAYESH, B., GFZ Potsdam, Potsdam, Germany, maleki@gfz-potsdam.
de; AREF, M., University of Potsdam, Potsdam, Germany, mohammad.
mohseni.aref@uni-potsdam.de; JAMALREYHANI, M., Southern Universityof Science and Technology, Shenzhen, China, jamalreyhani@sustech.edu.
cn; BÜYÜKAKPINAR, P., GFZ Potsdam, Potsdam, Germany, pinar@gfzpotsdam.de; DAHM, T., GFZ Potsdam, Potsdam, Germany, torsten.dahm@
gfz-potsdam.de
Earthquake multiplets are defined as two or more consecutive earthquakesthat occur within a short period of time and have a comparable magnitude
and therefore differ from the typical mainshock-aftershock distribution. Within two hours on the 1st of July 2022, three earthquakes of Mw 5.8–6.0 hit the SE
Fars Arc (FA), Iran. The FA is the 700-km-long, easternmost segment in theforeland of the Zagros continental collision zone, which is characterized by~10 km thick sediments including extended evaporitic layers causing folding,thin and thick sheet sliding, syn- and anticline formations and extensive strain
decoupling. This exceptional setting in the FA and the Zagros mountains also
hosts frequent earthquake doublets.
Here we investigate the co-seismic deformation and elastic interaction between both the large mainshocks and 120 aftershocks. We use seismic and satellite deformation data with well-proven and newly developed
earthquake parameter estimation tools. Our results indicate the activation ofthrust faults within the lower sedimentary cover (<10 km) along with highaftershock activity at significantly larger depths (10 - 15 km). The two largest earthquakes of the triplet (both Mw ~ 6.0) ruptured the lower sediments
at depths of 4–9 km, likely occurring on a south-dipping splay fault to the
mapped Zagros Foredeep Fault beneath an anticline. The third, smaller, Mw
5.8 event occurred one minute before the second large event, and indicateseither an early activation of deeper strata or a possible foreshock co-locatedon the mainshock faults. The comprehensive analysis of main- and aftershocks
using available seismic and ground deformation data unravels the interactionof the July–December 2022 sequence with the sedimentary layers both aboveand below the evaporitic decoupling zone.
poster 69
Nodal Seismometer Array Recordings of Aftershocks of the
6 February 2023 Mw 7.8 and Mw 7.6 Kahramanmaraş,Turkiye Earthquake Sequence
CATCHINGS, R. D., U.S. Geological Survey, California, USA, catching@usgs.
gov; CELEBI, M. K., U.S. Geological Survey, California, USA, celebi@usgs.
gov; GOLDMAN, M. R., U.S. Geological Survey, California, USA, goldman@usgs.gov; CHAN, J. H., U.S. Geological Survey, California, USA, jchan@usgs.
gov; SICKLER, R. R., U.S. Geological Survey, California, USA, rsickler@usgs.
gov; ERDEM, J. E., U.S. Geological Survey, California, USA, jeerdem@usgs.
gov; ALVER, F., Ministry of Interior Disaster and Emergency Management
Authority, Ankara, Turkey, fatih.alver@afad.gov.tr; KILICARSLAN, O.,
Ministry of Interior Disaster and Emergency Management Authority, Ankara,
Turkey, omer.kilicarslan@afad.gov.tr
Aftershocks of the 6 February 2023 Mw 7.8 and 7.6 Kahramanmaraş, Türkiye
Earthquake Sequence extended more than 550 km along the NE-SW-trending
East Anatolian fault (EAF) and about 200 km along the E-W-trending Sürgü –Çardak fault (SCF) to its intersection with the EAF. Events from this sequence
were recorded by the Türkish National Seismic Network (TNSN TU), which
operates 321 stations (AFAD, 1990), and the Türkish National Strong Motion
Network (TNSMN–TK), which operates 826 stations (AFAD, 1973) inTürkiye. Stations of these large networks are dispersed throughout the country, and the spacing between stations is highly variable, particularly within
the aftershock area of the 2023 Kahramanmaraş sequence. To better evaluate
aftershocks, causative faults, regional ground motions, and regional seismic
velocities using more uniformly spaced stations, the U.S. Geological (USGS)
and the Türkish Ministry of Interior Disaster and Emergency Management
Authority (AFAD) recorded aftershocks from July 2023 until December 2023
using nodal seismometers. The nodal seismometers were deployed as (1) atwo-dimensional grid of 3-component seismometers (> 400 km in longest
dimension) and (2) three linear 3-component arrays across known or suspected causative faults. The 2-D nodal seismometer stations were spaced at~30-km intervals, and stations of the linear arrays were spaced at either 0.5 or
1 km. A total of 126 nodal seismometers were deployed, and although many ofthem were retrieved by early December 2023, some of the nodal seismometers
were left in the field to continue recording until about January 2024. The combined networks (TU, TK, and Nodal) are expected to provide data for devel-

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oping an event catalog of unprecedented detail for the region, from which
subsurface fault locations and connectivity can be better evaluated, regional
ground motions can be better modeled, and regional P- and S-wave velocity
models can be developed.
poster 70
High-Resolution Three-Month Aftershock Catalog using
Nodal Stations of the 2023 Kahramanmaraş Earthquake
Sequence in Southeastern Türkiye
MACH, P. V., Georgia Institute of Technology, Georgia, USA, pmach3@
gatech.edu; PENG, Z., Georgia Institute of Technology, Georgia, USA, zpeng@gatech.edu; SANDVOL, E., University of Missouri, Missouri, USA, sandvole@missouri.edu; ERGIN, M., Scientific and Technological Research Council of
Türkiye, Gebze, Turkey, mehmet.ergin@tubitak.gov.tr; ZOR, E., Scientificand Technological Research Council of Türkiye, Gebze, Turkey, ekrem.zor@
tubitak.gov.tr; TAPIRDAMAZ, M. C., Scientific and Technological ResearchCouncil of Türkiye, Gebze, Turkey, mustafa.tapirdamaz@tubitak.gov.tr;
SEVIM, F., Scientific and Technological Research Council of Türkiye, Gebze,
Turkey, fatih.sevim@tubitak.gov.tr; TARANCIOĞLU, A., Scientific andTechnological Research Council of Türkiye, Gebze, Turkey, adil.tarancioglu@
tubitak.gov.tr; YALVAC, O., University of Missouri, Missouri, USA, oyzgb@
missouri.edu; DING, C., Georgia Institute of Technology, Georgia, USA,
cding64@gatech.edu
The Kahramanmaraş earthquake doublet on February 2023 in Southeastern
Türkiye started with a Mw 7.8 earthquake at Sakçagöz-Narlı Fault rupturing
the East Anatolian Fault (EAF) for more than 300 km. Nine hours later, a Mw
7.5 earthquake occurred near Ekinözü; this earthquake ruptured nearly 100
km along the adjacent Çardak fault. Both mainshocks have triggered a great
number of aftershocks along the faults and surrounding areas in the complex Maras triple junction. To better map the ongoing aftershock sequence,
we deployed approximately 200 5-Hz SmartSolo nodal stations and 16 broadband/strong motion seismic stations across the rupture zone focusing on
major clusters and potential areas under threat, for more than three months
starting in May 2023. These SmartSolo nodal stations are set with a sampling
rate of 500 Hz to record higher quality waveforms from smaller aftershocks,
as compared with a 100 Hz sampling rate from typical broadband stations.
In this work, we start with the earthquake catalog with more than 15,000
events in the same period of nodal deployment from the Turkey Disaster andManagement Authority (AFAD) catalog. The P and S arrivals are picked, using
the PSIR method, in the nodal stations and used as templates for subsequent
matched-filter detection (MFD). We also apply a deep-learning phase picker
called EQTransformer and its association method to the continuous nodal
records to help identify more events that were not listed in the AFAD catalog, which adds more template events for the MFD. Our preliminary results
show that MFD can detect micro-earthquakes hidden in the noise with verysmall magnitudes. Waveform-based relocation methods are then applied to
all detected events to build a more complete catalog. With a higher resolution
catalog, fault and seismic structures, especially splay faults along the EAF andthe adjacent faults can be identified and imaged for an improved understanding of potential seismic hazards in this region. Additionally, we expect to better decipher the physical mechanism of aftershocks and processes that drive
the evolution of seismicity in Southeastern Türkiye.
poster 71
Investigating the Türkiye-Syria and Afghanistan 2023
Seismic Sequences
SVIGKAS, N., Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy, nikos.svigkas@ingv.it; ATZORI, S., Istituto Nazionale di Geofisica e
Vulcanologia, Rome, Italy, simone.atzori@ingv.it; STRIANO, P., Consiglio
Nazionale delle Ricerche, Napoli, Italy, striano.p@irea.cnr.it; BONANO,
M., Consiglio Nazionale delle Ricerche, Napoli, Italy, bonano.m@irea.cnr.
it; VAVLAS, N., Aristotle University of Thessaloniki, Thessaloniki, Greece,
navavlas@geo.auth.gr; TOLOMEI, C., Istituto Nazionale di Geofisica e
Vulcanologia, Rome, Italy, cristiano.tolomei@ingv.it; KIRATZI, A., Aristotle
University of Thessaloniki, Thessaloniki, Greece, kiratzi@geo.auth.gr;
CASU, F., Consiglio Nazionale delle Ricerche, Napoli, Italy, casu.f@irea.
cnr.it; BIGNAMI, C., Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy, christian.bignami@ingv.it; DE LUCA, C., Consiglio Nazionale delle
Ricerche, Napoli, Italy, deluca.c@irea.cnr.it; POLCARI, M., Istituto Nazionale
di Geofisica e Vulcanologia, Rome, Italy, marco.polcari@ingv.it; FRANZESE,
M., Consiglio Nazionale delle Ricerche, Rome, Italy, franzese.m@irea.cnr.
it; ANTONIOLI, A., Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy, andrea.antonioli@ingv.it; MANUNTA, M., Consiglio Nazionale delle
Ricerche, Napoli, Italy, manunta.m@irea.cnr.it; MONTERROSO, F., Consiglio
Nazionale delle Ricerche, Napoli, Italy, monterroso.f@irea.cnr.it; ROA, Y.,

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Consiglio Nazionale delle Ricerche, Rome, Italy, roa.y@irea.cnr.it; LANARI,
R., Consiglio Nazionale delle Ricerche, Napoli, Italy, lanari.r@irea.cnr.it
We present our results for the strong earthquakes in Türkiye-Syria andAfghanistan that occurred in 2023. For the former, our analysis incorporates InSAR results derived from the SAOCOM-1, Sentinel-1 and ALOS-2
satellites. We applied both conventional interferometry and the Pixel Offset
tracking technique to quantify surface deformations caused by the impactfulearthquakes, resulting in substantial structural failures and multiple fatalities. Employing a combination of non-linear and linear inversions, we utilised
high-resolution Synthetic Aperture Radar (SAR)-based datasets as input. Thisfacilitated the creation of two meticulously segmented variable slip fault models for the M 7.8 and M 7.5 events, employing a multiscale sampling approach
to fully harness the potential of the high-resolution radar data. This approachallowed for a detailed examination and definition of the specific characteristics of each segment of the extensive tectonic structures that triggered theevents on the 6th of February 2023. Subsequently, this model was employed
to examine the distribution of the intensity of ground motions in the affected
region. In the context of the northwestern Afghanistan sequence, we processed
Sentinel-1 SAR data from both Ascending and Descending orbits to estimate
surface displacement using the InSAR technique. Through a sequential application of non-linear and linear optimization, we identified the causative faults
for the sequence of three M 6.4 events occurring on 7, 11, and 15 October.
poster 72
Measuring Afterslip From the February 2023 Mw 7.8
Pazarcık Earthquake Using Optical Images and Radar Data
TAN, M., U.S. Geological Survey, Colorado, USA, mtan@usgs.gov;
REITMAN, N., U.S. Geological Survey, Colorado, USA, nreitman@usgs.gov;
BURGI, P. M., U.S. Geological Survey, Colorado, USA, pburgi@usgs.gov;
BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.gov
The East Anatolian fault, a major plate boundary transform fault in southern Türkiye, has hosted many large earthquakes - most recently the 2020
Mw 6.8 Elazığ earthquake and the 2023 Mw 7.8 Pazarcık earthquake of the 6
February 2023 Kahramanmaraş earthquake doublet. Previous studies suggest
a ~40 km long potentially locked section of the longer Pütürge fault segment.
This region north of the 2023 rupture and south of the 2020 rupture did notexhibit surface rupture from either earthquake. Whether this area is at riskof an earthquake or if afterslip can fully account for missing displacement in
the region remains an open question. We explore this question with remotesensing methods. Using Sentinel-2 and Planet optical images, we calculatecoseismic displacement profiles across the northern Pazarcık rupture, which
ruptured 45 km of the 95 km Pütürge segment. We investigate afterslip fromthe 2023 Pazarcık earthquake using Sentinel-1 interferograms in the region
between the 2020 and 2023 ruptures. Our work aims to quantify surface displacement and distribution along the northern Pütürge section; image the
Pütürge section to understand its seismic potential; and better constrain theinteractions of multiple large earthquakes along a plate boundary fault.
poster 73
Decoding the Rupture Kinematics of the 2023 Mw 7.8 and
Mw 7.5 Kahramanmaraş Earthquake Doublet: Insights
From Comprehensive Seismic and Geodetic Analysis
XU, L., University of California, Los Angeles, California, USA, xuliuw1997@
ucla.edu; MOHANNA, S., University of California, Los Angeles, California,
USA, saeedmohanna@g.ucla.edu; MENG, L., University of California, Los
Angeles, , USA, lsmeng@g.ucla.edu; JI, C., University of California, Santa
Barbara, , USA, ji@geol.ucsb.edu; AMPUERO, J., Université Côte d’Azur,
VALBONNE, France, ampuero@geoazur.unice.fr; YUNJUN, Z., Chinese
Academy of Sciences, Beijing, China, yunjunzgeo@gmail.com; HASNAIN,
M., University of California, Los Angeles, , USA, mshasnain@g.ucla.edu;
CHU, R., Chinese Academy of Sciences, Wuhan, China, chur@apm.ac.cn;
LIANG, C., Peking University, Beijing, China, cunren.liang@pku.edu.cn
We investigate the rupture kinematics and slip distributions of the recent Mw
7.8 and Mw 7.5 earthquake doublet which struck the East Anatolian Fault(EAF), the Narlı Fault (NF), and the Sürgü Fault near Kahramanmaraş,Turkey, on Feb 6, 2023. Employing a comprehensive dataset that includes
distant and local seismic data, high-rate GNSS recordings, InSAR, and SAR
images, we apply joint finite fault inversion and slowness enhanced back-projection to unravel the intricacies of the rupture process. Back-projection andfinite fault inversion consistently reveals an asymmetric bilateral rupture for
the Mw 7.5 event: a supershear west branch and a subshear east branch, eachapproximately 65 km in length. The supershear branch is further validated
through the identification of Mach cones and Mach waves. For the Mw 7.8

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Seismological Research Lettersmainshock, our detailed examination uncovers a nuanced rupture process:initiation and propagation commence on the NF, with bilateral propagation
occurring upon reaching the junction with the EAF. The rupture then extends
120 km to the northeast at 3.05 km/s and 200 km to the southwest at 3.11
km/s. Furthermore, the initiation of slip on the EAF before the arrival of the
rupture from the NF suggests a remote triggering relationship between themain fault and the splay fault. To delve into this relationship and the dynamics of rupture triggering from the splay fault to the main fault, we employ
dynamic stress calculations. Our study aspires to provide critical insights into
the propagation of rupture on complex faults, contributing valuable knowledge applicable to large strike-slip fault systems globally.

Induced Earthquakes: Source Characteristics,
Mechanisms, Stress Field Modeling and Hazards
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Asiye Aziz Zanjani, Southern Methodist
University (aazizzanjani@smu.edu); Farzaneh Aziz Zanjani,
University of Miami (fzanjani@earth.miami.edu); Nadine
Igonin, University of Texas at Dallas( Nadine.Igonin@
utdallas.edu)
Structural Controls on Induced Earthquake Sequence’s
Growth and Slip Behavior
PENNINGTON, C. N., Lawrence Livermore National Laboratory, California,
USA, cnpennin@gmail.com; CHEN, X., Texas A&M University, Texas, USA,
xiaowei.chen@exchange.tamu.edu
To examine how the fault structures within Oklahoma control induced earthquake behavior, we examine both 3D seismic data and seismogenic faults.
We utilize the LArge-n Seismic Survey in Oklahoma (LASSO), a dense nodal
array with >1800 sensors, to characterize multiple small (<1 km in length)
seismogenic faults. The identified faults’ orientations are then compared to
the local stress field to determine how their behavior is affected by how welloriented they are in the stress field for failure. The seismogenic faults earthquakes temporal behavior indicates that optimally oriented are driven more
often by event-event triggering, while non-optimally oriented faults are driven
more often by fluid diffusion. These faults structural behavior mimics what isobserved in faults characterized in nearby 3D seismic data and could either
represent small isolated faults or small segments of larger complex immaturefaults. The immature fault structures indicated by both the seismogenic faults
and 3D seismic not only affect seismogenic sequence development, but also
the slip of larger events that occur on them. To confirm this, we compare
slip distributions between low (Oklahoma) and high deformation regions(California). The low deformation regions have more prominent and well
separated slip patches, which is a behavior indicative of immature faults. Thisbehavior does not change if the event was induced or not. These observations
suggest that the initial underlying stress distribution, strength and orientationof induced faults in low deformation regions are the primary controlling factors of the slip distribution, while the major driving forces of sequence development such as pore pressure perturbations or earthquake interactions playa secondary role.
Seismic Hazard Analysis for Hydraulic-Fracture Triggered
Earthquakes in Oklahoma
WALTER, J., Oklahoma Geological Survey, Oklahoma, USA, jwalter@ou.edu;
OGWARI, P. O., Oklahoma Geological Survey, Oklahoma, USA, pogwari@ou.edu; THIEL, A., Oklahoma Geological Survey, Oklahoma, USA, athiel@ou.edu; WOELFEL, I., Oklahoma Geological Survey, Oklahoma, USA,iewoelfel@ou.edu; MACE, B., Oklahoma Geological Survey, Oklahoma,
USA, brandon.mace@ou.edu; HAYMAN, N., Oklahoma Geological Survey,
Oklahoma, USA, hayman@ou.edu
It has been well-publicized that Oklahoma experienced an unprecedented
increase in seismicity starting about 2010 and continuing today. That seismicity peaked in 2015 when there were ~900 M3.0 or greater earthquakes thatyear, relative to a tectonic background rate of just 1-2 M3.0 or greater earthquakes per year prior to 2009. Many of those events are now understood tohave been induced by wastewater disposal, some of which caused moderate
but not widespread damage to the rural communities in which they occurred.
While most public and regulatory attention has historically been focusedon wastewater disposal into the Ordovician-age Arbuckle Group as a causal

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mechanism, in the last few years hydraulic fracturing (HF) triggers most of
the induced seismicity in the state. We will report on our recent efforts tocategorize HF-triggered seismicity, over the last decade, through statisticalanalysis. During the last decade and increasingly as the network has expanded
and event detectability has improved through implementation of machinelearning, we find that almost 16% of HF completions are associated with theoccurrence of an earthquake. Of those ~8,000 earthquakes associated with
HF, ~1,000 were felt and reported to the USGS DYFI. We will discuss a coupleof anomalous cases of larger than expected reported intensities, which include
significant amplification of seismic waves due to local geology. One of those
was a M3.2 HF-triggered earthquake that led to reports of light damage insouthern Canadian County, OK. Our findings have important implications
for mitigation of HF well completion seismicity as it is occurring and canguide best practices for future long-term geostorage and geothermal projects.
Undocumented Cases of Induced Seismicity in Oklahoma
and Texas
GRIGORATOS, I., ETH Zurich, Zurich, Switzerland, iason.grigoratos@
sed.ethz.ch; SAVVAIDIS, A., University of Texas at Austin, Texas, USA,alexandros.savvaidis@beg.utexas.edu
Identifying the causal factors behind elevated seismicity rates in areas withmultiple overlapping oil and gas activities has always been a challenging issue.
Often enough the dominant causal factor masks cases triggered by secondary
operations. Using the framework presented in Grigoratos et al. (2020; 2022)
our analysis hindcasts seismicity rates on spatial grid using either HydraulicFracturing (HF) or Salt Water Disposal (SWD) data as input and compares
them against the null hypothesis of solely tectonic loading. In the end, eachblock is assigned a p-value, indicating the statistical confidence of its causal
link with either HF or SWD operations. Here, we present results for the Eagle
Ford (EF) play in Texas and parts of Oklahoma (OK). Our results confirm
previous studies that linked most of the seismicity in the EF and OK with
HF and SWD, respectively. That said, we also identified clusters of seismicity
triggered by HF in OK that spatially overlap with areas affected by SWD, as
well as clusters triggered by SWD in the EF that spatially overlap with areas
affected by HF. Finally, we also found that at least one cluster of earthquakes
in the western part of EF play, along the border with Mexico, is related only
to SWD. Our analysis highlights that overlapping oil and gas activities might
trigger seismicity at different depth intervals, without the latter necessarily
being in hydraulic communication.
Regional Moment Tensors for Texas
HERRMANN, R. B., St. Louis University, Missouri, USA, robert.b.herrmann@
gmail.com; BENZ, H. M., U.S. Geological Survey, Colorado, USA, benz@usgs.
gov
Easy access to digital waveform data from TexNet and other networks permits the determination of regional moment tensors, earthquake magnitude
and seismic structure within Texas. Our catalog of over 175 moment tensors is dominated by events in the Delaware and Midland Basins of western
Texas, being complete for Mw > 3.4, with some events having Mw as low as
2.9. Source depths vary between 3 and 12 km, with over half between 8 and
10 km. The Saint Louis University generic western US velocity model (WUS)fits waveforms well. Events in the Delaware Basin are characterized by normal faulting along a 60 km E-W trend, while events in the Midland Basinare aligned in an NE-SW direction with a mixture of normal and strike-slip
mechanisms. A determination of regional ML and mLg for each event showsthat high frequency ground motion out to several hundred km is similar tothat of the stable continental interior of the central and eastern US rather than
to that of the western US.
There has not been much success in determining moment tensors for thesmaller number of events in the Eagle Ford Basin in the southeast of the state,lacking an appropriate velocity model. To address that need, ambient noise
processing using the continuous waveform data of TexNet is being performed
to augment the dispersion data set previously distributed by Herrmann et al(2021, SRL 92, pp. 3642-3656). The derived dispersion can be used to checkthe appropriateness of using the WUS velocity model in the west.
Cross-Examining Methods for Determining Source
Mechanisms for Induced Earthquakes in the Permian Basin
AZIZ ZANJANI, F., University of Miami, Florida, USA, fzanjani@earth.
miami.edu; SAVVAIDIS, A., University of Texas at Austin, Texas, USA,alexandros.savvaidis@beg.utexas.edu; HUANG, G. D., University of Texas
at Austin, Texas, USA, dino.huang@beg.utexas.edu; DOMINO, J., University

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of Texas at Austin, Texas, USA, jessica.domino@texnetops.org; CHEN, Y.,
University of Texas at Austin, Texas, USA, yangkang.chen@beg.utexas.edu
Establishing the causal link between induced earthquakes and oil and gas
operations in the Permian Basin depends on accurately assessing the 3-D distribution of seismic sources and their mechanism. The local recordings of the
Texas Seismological Network (TexNet), established in 2017, provide a unique
opportunity to determine the source characteristics of induced earthquakes
in Texas. As one of the main initiatives of the TexNet, the overarching goal ofthis study is to identify an optimal approach for the regular and automateddetermination of source mechanisms using TexNet real-time seismic data. In
this study, we implemented waveform moment tensor inversion (MTI) using
Gisola to analyze over 150 earthquakes in the Delaware and Midland subbasins. Gisola utilizes an automated algorithm and conducts a 4-D spatiotemporal MT grid search to determine a preferred solution for the source.
We then performed a comparative analysis among reported solutions fromvarious sources (e.g., SLU, rCMT, scmtv, NEIC) to cross-examine the consistency in results. Despite general uniformity among different solutions for thesource mechanism, the centroid depths derived from Gisola and scmtv consistently appear shallower than that of other solutions. Differences in solutions
may be associated with the choice of frequency range used in the modeling,
the resolution of centroid locations, the effect of the velocity model, and/or
varying station geometry. We also derived focal mechanisms from the P-wave
first-motion polarities using HASH for earthquakes that have sufficient azimuthal coverage. Among the 70 earthquakes examined for initial polarities,
58 yielded solutions with HASH, and 26 of those solutions were non-unique.
This study underscores the robustness of Gisola in providing high-quality
seismic solutions for a wide range of magnitudes (> 2.2) using TexNet data,offering a valuable contribution to the ongoing efforts to comprehend andaddress induced seismicity in the Permian Basin.
Spatiotemporal Evolution of Induced Earthquakes in theSouthern Delaware Basin, Reeves-Pecos, West Texas
AZIZ ZANJANI, A., Southern Methodist University, Texas, USA,aazizzanjani@smu.edu; DESHON, H. R., Southern Methodist University,
Texas, USA, hdeshon@smu.edu; SAVVAIDIS, A., University of Texas atAustin, Texas, USA, alexandros.savvaidis@beg.utexas.edu
Accurate source characteristics are crucial for assessing the evolution of
induced seismicity associated with oil and gas operations and subsurface
stress changes in space and time. This study examines the spatial and temporal patterns of seismogenic rupture on critically stressed faults in the Southern
Delaware Basin (SDB), west Texas (Reeves and Pecos counties). Utilizing the
Hypocentroidal Decomposition method (HD) (www.seismo.com/mloc),
we conducted two nested inversions. First, we established a virtual point inspace and time, known as Hypocentroid, using a core cluster of local events.
We then determined the relative location of all events with respect to thisHypocentroid. The HD relocation improves relative spatial resolution byincorporating data calibration and weighting and mitigates the influence ofthe 1-D velocity model on earthquake location. We relocated over 6000 events
post-2017 provided from the Texas Seismological Network (TexNet) catalog
and 73 events from the TXAR catalog (2009-2017) (Frohlich et al., 2020). We
supplemented the TXAR and TexNet catalogs by incorporating regional differential times from waveform cross-correlation and local single-station S-P
differential times at hypocentral distances less than 10 km, respectively.
After relocation, the mean seismogenic depth of 1.5 km below sea levelaligns with the depth of the shallow injection unit, the Bone Spring formation,and is consistent with smaller-scale studies in the region. The spatial correlation between pre- and post-2017 seismicity, along with temporal patterns,
maps the expansion of active lineaments in length and number, particularly
to the southeast of the study region, as injection activities have evolved. While
deeper seismicity is notably absent, this study cannot rule out the involvementof basement faults due to temporal variability in data availability and reduced
spatial resolution for deeper seismicity. Our results confirm a prominent
influence of pressurization from shallow wastewater injection zones on shallow NW-trending strata-bound faults and the temporal migration of earthquakes along adjacent rupture zones.
Seismicity Triggering in the North Delaware Basin, West
Texas, USA
SAVVAIDIS, A., University of Texas at Austin, Texas, USA, alexandros.
savvaidis@beg.utexas.edu; LOMAX, A., ALomax Scientific, Mouans-Sartoux,
France, alomax@free.fr; HUANG, G., University of Texas at Austin, Texas,
USA, dino.huang@beg.utexas.edu; CHEN, Y., University of Texas at Austin,
Texas, USA, yangkang.chen@beg.utexas.edu; ALVAREZ, N., University ofTexas at Austin, Texas, USA, natalva@utexas.edu; DOMINO, J., University

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of Texas at Austin, Texas, USA, jessica.domino@texnetops.org; BURKE, G.,
University of Texas at Austin, Texas, USA, grace.burke@austin.utexas.edu;
FERRER, F., University of Texas at Austin, Texas, USA, fernando.ferrer@
texnetops.org; SIERVO, D., University of Texas at Austin, Texas, USA, daniel.
siervo@beg.utexas.edu; SALLES, V., University of Texas at Austin, Texas, USA,
victor.salles@beg.utexas.edu; FLECK, P., University of Texas at Austin, Texas,
USA, preston.fleck@beg.utexas.edu; UKU, B., University of Texas at Austin,
Texas, USA, bede.uku@beg.utexas.edu; MCCABE, C., University of Texas
at Austin, Texas, USA, cooper.mccabe@beg.utexas.edu; O’SULLIVAN, V. J.,
University of Texas at Austin, Texas, USA, vincent.osullivan@beg.utexas.edu
As part of the intraplate tectonic regime within the continental US, the seismicity rate in Texas is expected to be low. However, the seismicity rate inWest Texas has steadily increased since 2009, and significantly accelerated
since 2020. Notably, the Texas Seismological Network (TexNet) has reported
49 M≥4 earthquakes (all after 2020) and 3 M≥5 earthquakes (all after 2022).
In the area of the North Delaware basin of Texas, the first M4+ earthquake(2020-02-18, 13:28:06) occurred in the area of Mentone, followed one month
later by a main event (M4.9; 2020-03-26, 15:16:27). The seismogenic structurethat hosts the Mentone cluster is a normal fault striking WSW-ENE, with theseismicity distributed around or above the basement. The presence of nearby
long-term deep wastewater injection in the area strongly suggests that theseismicity is due to the oil and gas operations.
In contrast, ~11km to the southeast of the Mentone cluster, seismicity with its first M3+ earthquake on Jan 25th 2021, shows a complex, normal
faulting system near the area of Coalson Draw. Since then, the Coalson Draw
seismic zone has been very active, with two notable M5+ events (M5.4, 202211-16 21:32:44 & M5.2 2023-11-08 10:27:49 ). The seismicity is apparently
spanning ~5 km in depth and stretching across the basin-basement interface
at about 5 km depth. Following an increase of seismicity in September 2021
(6 M4+ events occurred between September 3rd and October 3rd, 2021), in
October 2021 the injection volume has been reduced at approximately 20 km
to the north of the Coalson Draw sequence, due to concerns of deep injection
being the causal factor of seismicity in the area. Additionally, the hypocenterof the M4.9 Mentone event is closer (~11km) to the deep injection than theCoalson Draw sequence (~20km). These relations suggest that the Coalson
Draw sequence might have been initiated by deep wastewater injection, andlater the seismicity rate has accelerated (M3+ events) due to dynamic triggering mechanisms (i.e., earthquake-to-earthquake triggering), eventually resulting in the occurrence of the first M5+ event.
Potential Poroelastic Triggering of the 2020 M 5.0 Mentone
Earthquake in the Delaware Basin, Texas, by Shallow
Injection Wells
LUI, S., University of Toronto, Toronto, Canada, semechah.lui@utoronto.ca;
TAN, X., University of Toronto, Toronto, Canada, xy.tan@mail.utoronto.ca
The Delaware basin in Texas, one of the largest oil and gas production sites
in the United States, has been impacted by widespread seismicity in recent
years. The M 5.0 earthquake that occurred in March 2020 near the town of
Mentone is one of the largest induced earthquakes recorded in this region.
Characterizing the source parameters and triggering mechanism of thismajor event is imperative to assess and mitigate future hazard risk. A former
study showed that this event may be attributed to the deep injection nearby.
Interestingly, the earthquake is in proximity to shallow injection wells withmuch larger total injection volume. In this study, we investigate the role ofthese shallow injection wells in the triggering of the M 5.0 event despite theirfarther distance from the mainshock than the deep wells. We first performsource-parameter inversion and earthquake relocation to determine the precise orientation of the south-facing normal-fault plane where the mainshock
occurred, followed by fully coupled poroelastic stress modeling of the changeof Coulomb failure stress (CFS) on the fitted fault plane caused by shallow
injection in the region. Results show that shallow wells included in our analysis caused close to 20 kPa of CFS change near the mainshock location, dominated by positive poroelastic stress change. Such perturbation surpasses thegeneral triggering threshold of faults that are well aligned with the local stressfield and suggests the nonnegligible role of these shallow wells in the triggering of the mainshock. We also discuss the complex effect of poroelastic stressperturbation in the subsurface and highlight the importance of detailed geomechanical evaluation of the reservoir when developing relevant operationaland safety policies.
Using Converted Phases to Investigate Induced Seismicity
in the Midland Basin, Texas
DESHON, H. R., Southern Methodist University, Texas, USA, hdeshon@smu.edu; ROSENBLIT, J., Southern Methodist University, Texas, USA,

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Seismological Research Lettersjrosenblit@smu.edu; HUANG, G., University of Texas at Austin, Texas, USA,
dino.huang@beg.utexas.edu; SAVVAIDIS, A., University of Texas at Austin,
Texas, USA, alexandros.savvaidis@beg.utexas.edu
Wastewater injection triggers seismic activities in the Midland basin,west Texas, where the seismic events as large as M5.2 have been recorded.
Mitigation requires understanding the role of shallow (<1.5 km subsurface)versus deep (2.3-3.4 km subsurface) injection, and the determination of causal
factors is complicated by the uncertainties of hypocentral depths (+/-3 km),which may be associated with the complicated basin geology and inadequate
network coverage over time. Here, we use body wave conversions common forshallow earthquakes in sedimentary basins to constrain hypocentral depths.
We first generate a series of synthetic seismograms to gain an intuitive understanding of the subsurface characteristics that lead to the converted phases,
and investigate how the waveform is influenced by various source parametersand velocity models. Sonic logs show that the Silurian-Devonian+Ellenburger(SD+E) and the San Andres (SA) formations provide significant impedancecontrasts between layers to generate converted body waves (sP). These sP
phases are potentially identifiable to earthquake analysts with epicentral distance less than 10 km. The clarity of the converted phases depends on radiation pattern, focal depth, and geology along the propagation paths. Changes toquality factors (Qp and Qs) and density did not produce any notable changes
to shape and signal-to-noise of the synthetic sP. Synthetic tests indicate thatthe relative timings of converted phases are directly controlled by earthquake depths, and the amplitude of converted phases is strongly tied to theamplitude of the S-wave. Events located in the basement will yield two main
converted phases, one from the SD+E boundary and one from the SA. The
velocity contrast at the top of the SD+E yields an identifiable converted phase
whose S-sP time could be incorporated into earthquake location algorithms.
Converted phases have the greatest clarity (signal-to-noise) at depths greaterthan 6 km and operationally should be picked on data between 2-10 km event
station distances. Lastly, we provide comparisons between the synthetic waveforms and real data.
Fault Reactivation During Induced Seismicity Sequences inSouthern Kansas
RIES, R., Stanford University, California, USA, riesr@stanford.edu;
BEROZA, G. C., Stanford University, California, USA, beroza@stanford.
edu; ELLSWORTH, W., Stanford University, California, USA, wellsworth@stanford.edu
Using machine learning enhanced catalogs, it is possible to study the evolution of earthquake sequences in great detail owing to the significant decreasein magnitude of completeness compared to routine catalogs. We use theenhanced catalog of Park et al. (The Seismic Record, 2022) for Oklahoma andSouthern Kansas to examine the spatial and temporal evolution of seismicity
on individual faults in southern Kansas. In the Park et al. study it was foundthat individual faults commonly activate multiple times. To better understand the nature of reactivation we refine the hypocentral locations using
the slope of the cross spectrum to measure sub-sample differences in travel
time between highly correlated events. We obtain precise relative locations
for earthquakes occurring along individual fault structures with an accuracyof 10-20 m. Along one isolated, 2.5 km-long fault we find approximately 10%of the events are “true” repeaters (>50% overlap in rupture area). Interevent
times vary widely, between a few hours and several months with no clear trendwith magnitude. Repeating earthquakes concentrate along the central portionof the fault indicating that the same portion of the fault slipped more thanonce during the sequence. Of note, the largest repeaters in the sequence, ML
3.2 and 3.1 occurred shortly after the fault became seismically active and just
3 days apart. This raises the question of the re-failure mechanism. Further
investigations will be needed to determine the role of aseismic slip (potentiallyrevealed by small repeaters), stress interaction and/or progressive weakening
from rising pore pressure as the re-triggering mechanism.
Detailed Analysis of Microseismic Activity Associated with
Shutdowns of the San Emidio Geothermal Plant, Nevada
THURBER, C. H., University of Wisconsin–Madison, Wisconsin, USA,cthurber@wisc.edu; GUO, H., University of Wisconsin–Madison, Wisconsin,
USA, hao.guo@wisc.edu; CUNNINGHAM, E., Oak Ridge National
Laboratory, Tennessee, USA, cunningham.erin4@gmail.com; ROECKER,
S. W., Rensselaer Polytechnic Institute, New York, USA, roecks@rpi.edu;
HAMPTON, J., University of Wisconsin-Madison, Wisconsin, USA, jesse.
hampton@wisc.edu; LORD, N. E., University of Wisconsin-Madison,
Wisconsin, USA, lord@geology.wisc.edu; SOBOL, P., University of Wisconsin-

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Madison, Wisconsin, USA, psobol@wisc.edu; FEIGL, K. L., University of
Wisconsin-Madison, Wisconsin, USA, feigl@wisc.edu

nadine.igonin@UTDallas.edu; EATON, D., University of Calgary, Calgary,
Canada, eatond@ucalgary.ca

We are analyzing dense seismic array data encompassing shutdowns of the
San Emidio geothermal plant in Nevada in 2016 and 2022. In 2016, an arrayof ~1,300 vertical-component seismographs operated by Microseismic Inc.
recorded for about a week. In 2022, an array of 450 three-component seismographs was deployed as part of the WHOLESCALE project, covering most of
the northern ~2/3 of the 2016 array footprint at twice the instrument spacing, and recorded for about a month. The data are being analyzed with two
workflows to detect and locate the microseismic events. The first generates
a microseismic event catalog directly from the raw continuous seismic data.
The second produces high-precision event locations via a sequence of repicking arrivals, waveform cross-correlation, and double-difference relocation.
Analysis of the 2022 data set reveals intense seismic activity commencing
soon after shutdown and returning to the previous background rate shortly
after restart. The events fall into several main clusters that include some linear features. Preliminary results for the 2016 data set show a similar patternof heightened activity during the shutdown, revealing an order of magnitude more events than a previous catalog estimated using a back-projection
approach. As the catalog size allows, statistic-physics models analyzing spacetime connections as well as magnitude clustering are explored.
The work presented herein has been funded in part by the Office ofEnergy Efficiency and Renewable Energy (EERE), U.S. Department of Energy,
under Award Numbers DE-EE0007698 and DE-EE0009032. The seismic
instruments deployed in 2022 were provided by the Incorporated ResearchInstitutions for Seismology (now the EarthScope Consortium) through the
PASSCAL Instrument Center at New Mexico Tech. Data collected will be available through the EarthScope Data Management Center. The facilities of the
EarthScope Consortium are supported by the National Science Foundation’s
Seismological Facility for the Advancement of Geoscience (SAGE) Award
under Cooperative Support Agreement EAR-1724509.

Earthquake locations with well-constrained uncertainties allow for interpreting fault systems and fault activation mechanisms for large datasets. Improved
precision and reduced uncertainty of relative locations can aid in understanding fault plane geometry and provide images of fault activation from induced
seismicity. Double-pair double-difference relocation is an adaptation of eventpair relocation that incorporates station-pair differential travel times, whichis particularly useful for dense networks. The additional information fromstation pairs limits the impact of velocity model uncertainties, reducing theimpact of velocity model errors in locations. For reservoir applications withinduced seismicity, this benefit is pronounced at depths where large velocity
contrasts due to reservoir layers occur. In such areas, source locations can bepoor from the traditional event-pair relocation method. We present doublepair double-difference relocation results for 4,000 induced events from monitoring near Fox Creek, Alberta. Because of highly correlated waveforms with
a 0.9 cross-correlation coefficient cut-off, including station-pair information
increases data from 2.5 million cross-correlation differential times to 62.8 million data points. The relative uncertainties in the double-pair relocated catalog are zero-mean and 1-2 m for all three spatial parameters, which improves
upon the event-pair relocations with relative uncertainties of 3 m in X and
Y and 4 m in depth and nonzero means in the range of 50 m in Y and 100
m in Z due to directional anisotropy. Double-pair relocations lead to spatial
clustering of events at discrete depths, which is consistent with the geologyof the stimulated zone, comprising thin layers of stronger carbonates embedded within weaker shales. Using double-pair double-difference, we provide a
precise fault map, including 3D least-squares planar fits for earthquake clusters. The fault map confirms prior studies about existing faulting in the region,
particularly that the study area is part of a larger structural corridor, likely aflower structure exhibiting Riedel shear behavior.

Source Characteristics of Microseismicity Occurring During
Operational Shut-in Periods at the Coso Geothermal Field,
California
HOLMGREN, J. M., Norwegian Seismic Array, Kjeller, Norway, joanna.
holmgren@norsar.no; KAVEN, J., U.S. Geological Survey, California, USA,okaven@usgs.gov; OYE, V., Norwegian Seismic Array, Kjeller, Norway, volker.
oye@norsar.no
Throughout its 30+ years of energy production, the Coso Geothermal Field(CGF) in California has regularly experienced both tectonic and induced
microseismicity. While distinguishing between these two types of earthquakes
can be difficult, knowledge of the interplay between operational parameters
and the reservoir’s seismic response can shed light on key factors affecting thestress field and the reservoir’s productivity.
In this study, we examine daily production and microseismicity datafrom the CGF between 1996 and 2010 to gain insight into the evolution of its
stress field and how it has been affected by long-term production. Using 27
seismic stations from a local network, we analyse the source characteristics of
60,000+ earthquakes with moment magnitudes between -1 and 3.3. We findthat most of the seismicity occurs towards the southern and eastern sectionsof the field, coinciding with the regions of the CGF where most of the fluids
are reinjected. Additionally, these regions with higher seismicity rates tend
to experience an abrupt increase in seismicity rates during the yearly power
plant maintenance periods and wellbore shut-ins. Increased seismicity during
shut-in periods has been observed previously at other geothermal fields andspatially linked to production wellbores. Through waveform cross-correlationand seismic event relocation, we identify distinct clusters of microseismicity
re-occurring during these shut-ins. These observations may suggest that certain fracture and fault sections respond quicker to changes in pore pressure
and poroelastic stresses within the geothermal system. Better understandingof these relationships can de-risk geothermal operations and optimize productivity of the field.
Double-Pair Double-Difference Relocation for Dense
Network Improves Depth Precision of Induced Seismicity,
Leading to a Detailed 3D Fault Geometry Model
BIEGEL, K., University of Calgary, Calgary, Canada, katherine.biegel@ucalgary.ca; DETTMER, J., University of Calgary, Calgary, Canada, jan.
dettmer@ucalgary.ca; IGONIN, N., University of Texas at Dallas, Texas, USA,

Multi-Sensor Microseismic Monitoring of the Quest CCS
site, Alberta, Canada
LANGET, N., NORSAR, Kjeller, Norway, nadege@norsar.no; GOERTZALLMANN, B. P., NORSAR, Kjeller, Norway, bettina@norsar.no; BAIRD,
A., NORSAR, Kjeller, Norway, alan@norsar.no; IRANPOUR, K., NORSAR,
Kjeller, Norway, kamran@norsar.no; KÜHN, D. K., NORSAR, Kjeller,
Norway, daniela@norsar.no; VERNIER, J., Total Energies, Pau, France,
jerome.vernier@external.totalenergies.com; REBEL, E., Total Energies, Pau,
France, estelle.rebel@total.com; OATES, S., Shell, Amsterdam, Netherlands,
Steve.Oates@shell.com
Nowadays, Carbon Capture and Storage appears as one of the solutions
to reduce the amount of CO2 in the atmosphere. At the Quest CCS site inAlberta, Canada, injection of CO2 started in 2015 with one million tonnes per
year and ongoing until 2040. Microseismic monitoring has been part of the
MMV plan since the beginning of the project, aiming to mitigate the potential
risks associated with the injection. The closer area around Quest has been
seismically quiet before injection operation started. A string of eight 3-component geophones was installed in a deep monitoring well. In addition, 153
surface nodes arranged in mini-arrays were temporarily deployed and a DAS
cable installed in one of the injection wells was interrogated during a periodof six months.
More than 600 microseismic events of magnitude ranging from -2 to
0.8 were detected and located within the area of review. All events have been
located in the Precambrian basement below the reservoir causing no containment threat. This rich dataset allows for the comparison of the different
monitoring technologies against each other both in terms of detectability andlocatability of events. We demonstrate how signal processing and array processing techniques can significantly lower the event detection threshold. Event
location uncertainties can be reduced by combining various data.
Advanced InSAR Analysis of Groningen’s Subsurface
Deformation: Enhancing Understanding of Reservoir
Rheology and Induced Seismicity Modeling
LI, Y., California Institute of Technology, California, USA, yuexinli@caltech.edu; ACOSTA, M., California Institute of Technology, California,
USA, acosta@caltech.edu; SIRORATTANAKUL, K., California Instituteof Technology, California, USA, ksirorat@caltech.edu; BOURNE, S., Shell,
Amsterdam, Netherlands, Stephen.Bourne@shell.com; AVOUAC, J.,
California Institute of Technology, California, USA, avouac@caltech.edu
In the context of the increasing incidence of induced seismicity linked tohydrocarbon extraction, our study presents a comprehensive analysis of subsurface deformation at the Groningen gas field in the Netherlands, a notable

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example of seismic activity associated with gas production. Employing a multidisciplinary approach, we integrate InSAR data (RADARSAT2, TerraSAR-X,
Sentinel-1), GNSS, and optical leveling to investigate the reservoir’s timedependent deformation. We leverage Independent Component Analysis(ICA) to distinguish deformation sources, offering insights into the intricate
interplay of subsurface operations. We observed pronounced decadal subsidence across the Groningen field, with spatial variations in subsidence rates
highlighting local compressibility differences. Notably, ICA uncovered significant seasonal fluctuations in the Norg area, with a 20 mm amplitude over a
5x5 km region, correlating with gas storage cycles and revealing a previously
obscured deformation signal. Through comparative analysis of long-term subsidence and Norg’s seasonal deformation against various model predictions,
including linear poroelastic and rate-type compaction models (RTiCM),
we identified evidence of inelastic compaction in the reservoir. This insight,
manifested as a time-dependent increase in apparent compressibility (Cm), is
pivotal for advancing seismicity forecast models. Our results contribute significantly to understanding the hydromechanical processes governing induced
seismicity and highlight the need for integrated geomechanical modeling inmanaging seismic risks in Groningen and similar settings.

Induced Earthquakes: Source Characteristics,
Mechanisms, Stress Field Modeling and Hazards [Poster
Session]Poster Session • Wednesday 1 May
Conveners: Asiye Aziz Zanjani, Southern Methodist
University (aazizzanjani@smu.edu); Farzaneh Aziz Zanjani,
University of Miami (fzanjani@earth.miami.edu); Nadine
Igonin, University of Texas at Dallas( Nadine.Igonin@
utdallas.edu)
poster 96
The Critical State of Stress Preceding the Prague m5.7
Earthquake
ALFARO-DIAZ, R. A., Los Alamos National Laboratory, New Mexico, USA,
rad@lanl.gov; CHEN, T., Los Alamos National Laboratory, New Mexico, USA,tchen@lanl.gov; CARMICHAEL, J. D., Los Alamos National Laboratory, New
Mexico, USA, joshuac@lanl.gov
Here we examine induced seismicity, a consequence of contemporary oil andgas extraction methods. We focus on understanding the role of large earthquakes in triggering subsequent seismic activities via transient dynamic stressing. Central to our investigation is Prague, Oklahoma, a region characterizedby natural, induced, and dynamically triggered seismicity. We analyze approximately 1.5 years of data (2010 - 2012) gathered from EarthScope’s USArray
Transportable Array (TA), supported by an advanced local earthquake catalog. We investigate 254 teleseismic earthquakes (magnitude ≥ 6), and identify
cases of increased seismic activity in Prague, Oklahoma, integrating a robust
statistical approach. Notably, our findings indicate evidence of heightened
triggered seismicity preceding the 2011 Mw 5.7 Prague earthquake, implying
a state of critical stress prior to the event. This research highlights the complex
interactions of static, induced, and transient stresses, offering vital insights forunderstanding and potentially mitigating induced seismicity.
poster 97
A 3-Dimensional P-Wave Tomography Model of the Pecos,
Texas Region of the Delaware Basin
FAITH, J. L., Los Alamos National Laboratory, New Mexico, USA, jfaith@lanl.gov; KARPLUS, M. S., University of Texas at El Paso, Texas, USA,mkarplus@utep.edu; DOSER, D. I., University of Texas at El Paso, Texas, USA,
doser@utep.edu; SAVVAIDIS, A., University of Texas at Austin, Texas, USA,alexandros.savvaidis@beg.utexas.edu
With increasing earthquakes in the Delaware Basin since 2009, earthquake
studies, including accurate hypocenters, are critically needed in the Delaware
Basin to identify the structures producing earthquakes, and to determine ifthey are related to unconventional petroleum development and production.
In 2018, with funding from the Texas Seismological Network (TexNet), theUniversity of Texas at El Paso deployed and maintained a network of 25
Magseis Fairfield Z-Land Generation 2 5-Hz seismic nodes in the Pecos,
Texas region of the Delaware Basin, known as The Pecos Array. The network
was deployed from November 2018 until the beginning of January 2020, with

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Seismological Research Lettersan additional two months of data recorded in September and October 2020.
The network collected continuous 3-component data with a 1000-Hz sampling rate. The spacing of the nodes varied from ~2 km in town to ~10 km
farther away from the city center. The Pecos Array was used to conduct a local
3-D P-wave tomography study in the Pecos, Texas region using the SIMULPS
software. Previous tomography studies have been conducted to derive aP-wave velocity model of the entire Permian Basin, but these studies covereda broader area, and their best velocity results were in the upper 35 km of thecrust. With our denser array, localized earthquakes, and increased ray coverage in the Pecos, Texas area, we have created a detailed 3-D velocity modelfor the top 8 km of this region. We observe velocity values that are consistent
with reported geologies in the basin, and slower velocities on faults compared
to areas without faults. We found that our new model is ~25% slower between
depths 2–6 km compared to the DB1D regional velocity model that TexNet
uses to locate their public catalog.
poster 98
Pore Pressure Effect on Coulomb Stress Change andTriggering of Earthquakes in Raton Basin, Colorado-New
Mexico Region
FUENTES, F. A., University of Colorado Boulder, Colorado, USA, fafu5236@
colorado.edu; MENDOZA, M. M., University of Colorado Boulder, Colorado,
USA, manuel.Mendoza@colorado.edu; BROWN, M. R. M., Northern Illinois
University, Illinois, USA, mbrown18@niu.edu; GE, S., University of Colorado
Boulder, Colorado, USA, ges@colorado.edu; SHEEHAN, A. F., University ofColorado Boulder, Colorado, USA, Anne.Sheehan@colorado.edu
The Raton Basin, located in southern Colorado and northern New Mexico, isan actively producing hydrocarbon basin that has undergone increased seismicity since 2001, which is attributed to anthropogenic perturbations resulting from wastewater injection. To better understand how changes in porepressure and shear stress along faults give rise to earthquake sequences, weinvestigate the spatio-temporal evolution of static Coulomb stress changes
associated with nine seismic events of magnitude Mw>4 that occurred in the
Raton Basin between 2001 and 2011. Examining the distribution of stressprovides insights into whether subsequent earthquake events in the region
are triggered or delayed. Wastewater injection operations in the region haveraised pore pressures in nearby fault zones, increasing the likelihood of inducing slip or triggering earthquakes on critically stressed faults. Pore pressure
effect cannot be neglected, and we further examine how it affects Coulomb
stress. Our analysis reveals that the 2011 Mw 5.3 earthquake, the largest magnitude event occurred in the basin, was likely triggered by cumulative static
stress changes and pore pressure increases resulting from the prior seismicity
from 2001 to 2005. We find notable differences of approximately 0.1 MPa in
our models of stress change when including versus excluding the effects ofpore pressure. This is significantly higher than the 0.01 MPa change typicallyconsidered sufficient to trigger seismicity. Our results show that pore pressure
can significantly affect modeled Coulomb stress changes over time. Carefulmonitoring of pore pressure changes, combined with modeling of stress interactions across regional fault networks, is critical for understanding induced
seismicity hazards in regions undergoing continued wastewater injection.
Incorporating pore pressure data into stress change models enhances theinsights into earthquake triggering and aftershock forecasting.
poster 99
The Minimal Effect of Solid-Earth Tides on Earthquake Ratein Oklahoma and Kansas
GLASGOW, M. E., U.S. Geological Survey, California, USA, mglasgow@
usgs.gov; RUBINSTEIN, J. L., U.S. Geological Survey, California, USA,jrubinstein@usgs.gov; HARDEBECK, J., U.S. Geological Survey, California,
USA, jhardebeck@usgs.gov
Natural stress oscillations from Earth’s tides provide short-timescale, semirepeatable tests of fault strength. Given that induced earthquakes occur along
critically stressed faults due to high fluid pressures, it is possible that there
would be a correlation between the small stress changes imposed by Earth tides
and induced earthquake rates. We investigate this using a machine-learningbuilt earthquake catalog spanning 2010-2020 (Park et al., 2022) that contains~300,000 events in northern Oklahoma and southern Kansas and numericalmodeling of the solid-earth tides. We use Schuster’s p-value to test whether
there is a statistically significant correlation between the semidiurnal tidal
phase and the earthquake rate. Schuster’s test assumes that each earthquake
is independent; therefore, we declustered the earthquake catalog using three
approaches (Reasenberg, nearest-neighbor distance, and phase bin method).
For all three declustered catalogs, we found that the ~3 kPa volumetric stresschange from solid Earth tides does not significantly (p-value>0.05) affect the

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earthquake rate when the full study region and ten year time period were considered. We tested the effect of the tides on various space discretization andtime windows of the earthquake catalog and generally observed a minimal
effect of solid Earth tides on the earthquake rate, often less than that expectedby random chance (5 %). Preliminary results for the spatial variations in tidal
triggering from 2015-2017 reveal 6 % (3 out of 47) of the 20x20 km cells are
significantly correlated to the solid Earth tides. Two of the three cells are inclose proximity to regions with high rates of wastewater injection. Of particular interest is the region near Cushing, Oklahoma which has a p-value of 0.002
and an elevated earthquake rate from -120 to 90 phase angle. This area is inclose proximity, ~15 km, to the largest total volume of wastewater injection,~500 M barrels injected by 2017.
poster 100
Hindcasting the 1993 - 2023 Wirdum Induced Earthquake
Sequence
VAN DER HEIDEN, V., Utrecht University, Utrecht, Netherlands,
v.vanderheiden@uu.nl; ULRICH, T., Ludwigs Maximilians University,
Munich, Germany, thomas.ulrich@lmu.de; BUIJZE, L., Netherlands
Organization for Applied Scientific Research, Utrecht, Netherlands, loes.
buijze@tno.nl; VAN ISSELT, M., Utrecht University, Utrecht, Netherlands,
m.a.c.vanisselt@students.uu.nl; VAN DE WIEL, L., Utrecht University,
Utrecht, Netherlands, l.y.vandewiel@uu.nl; GABRIEL, A. A., University ofCalifornia, San Diego, California, USA, algabriel@ucsd.edu; MATENCO,
L., Utrecht University, Utrecht, Netherlands, l.c.matenco@uu.nl; VAN
WEES, J., Netherlands Organization for Applied Scientific Research, Utrecht,
Netherlands, jan_diederik.vanwees@tno.nl; VAN DINTHER, Y., Utrecht
University, Utrecht, Netherlands, y.vandinther@uu.nl
On October 8th 2022, a ML 3.1 earthquake struck the village of Wirdum,
20 km from the city of Groningen in the Netherlands. The earthquake could
be linked to a 4.3 km fault cross-cutting a gas reservoir, the Wirdum fault.
The Wirdum fault segment experienced over 30 prior earthquakes since its
reactivation due to gas production, including a ML 2.5 (2019) and a ML
2.7 (2015). Current hazard models lack the capability of both hindcasting asequence of induced earthquakes over decades and studying the source andsurface processes. For this a physics-based prediction framework is needed.
Using high-quality data of the Groningen gas field, we re-interpreted the fault
geometry. Constrained by well-log data we load the realistic fault geometry
with heterogeneous pre- and post-production stresses using a semi-analytical
2.5D poroelastic stress solution (PANTHER; Buijze, 2024). Based on extensive
laboratory experiments we use heterogeneous friction and elastic parameters
to account for variable along-strike on-fault reservoir offset and bi-material
regions, embedded in a detailed geological model. We derive the critical stresslevels at which we simulate the three ML 2.5+ earthquakes of the Wirdum
sequence through data-driven 3D dynamic rupture modelling (SeisSol).
Results show predicted critical levels of on-fault stresses similar to observed
reservoir pressure at times of each earthquake. Each earthquake nucleates
spontaneously through stress loading. Simulated hypocentres are controlled
most by variations in fault dip (its first M1’s), although other fault geometry
aspects are important as well. Rupture arrest is dominantly controlled by onfault stress heterogeneity resulting from along-strike kilometre-scale undulations of the fault geometry. Calculated first arrivals for each earthquake largely
agree with observed seismograms. This physics-based hindcasting framework
for induced seismicity will be used to forecast future earthquakes on the
Wirdum fault. We will build forth on this for seismic hazard assessment andMmax estimates in Groningen and towards a successful contribution of sustainable subsurface solutions.
poster 101
Quake-Dfn, A Software for Simulating Sequences ofInduced Earthquakes in a Discrete Fault Network
IM, K., California Institute of Technology, California, USA, kjim@caltech.
edu; AVOUAC, J., California Institute of Technology, California, USA,avouac@caltech.edu
We present an earthquake simulator, Quake-DFN, which allows simulating
sequences of earthquakes in a 3-D Discrete Fault Network governed by rateand state friction. The simulator is quasi-dynamic with inertial effects being
approximated with radiation damping and a lumped mass. The lumped massterm allows accounting for inertial overshoot and, in addition, makes thecomputation more effective. Quake-DFN is validated against three benchmark problems: (i) the rupture of planar fault with uniform prestress (SEAS
BP5-QD), (ii) the propagation of a rupture across a step-over separating twoparallel planar faults (RSQSim and FaultMod), and (iii) a branch fault systemwith a secondary fault splaying from a main fault (FaultMod). Examples ofVolume 95•

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injection-induced earthquake simulations are shown for three different fault
geometries: (i) a planar fault with a wide range of initial stresses, (ii) a branching fault system with varying fault angles and principal stress orientations,and (iii) a fault network similar to the one that was activated during the 2011
Prague earthquake sequence in Oklahoma. The simulations produce realistic
earthquake sequences. The time and magnitude of the induced earthquakes
observed in these simulations depend on the difference between the initial
friction and the residual friction μi - μf, the value of which quantifies thepotential for run-away ruptures (ruptures that can extend beyond the zoneof stress perturbation due to the injection). The discrete fault simulations
show that our simulator correctly accounts for the effect of fault geometry
and regional stress tensor orientation and shape. These examples show that
Quake-DFN can be used to simulate earthquake sequences, most importantly
magnitudes, possibly induced or triggered by a fluid injection near a known
fault system.
poster 102
Crustal Rheological Layering Revealed in Multiscale
Signals of Natural and Anthropogenic Processes at
Pawnee, Oklahoma
JIANG, J., University of Oklahoma, Oklahoma, USA, jiang@ou.edu;
BODUNDE, S., University of Oklahoma, Oklahoma, USA, ssbodunde@ou.edu; WALTER, J., University of Oklahoma, Oklahoma, USA, jwalter@ou.edu; CARPENTER, B., University of Oklahoma, Oklahoma, USA, brett.
carpenter@ou.edu; VITERI LOPEZ, J., University of Oklahoma, Oklahoma,
USA, Jose.A.Viteri.Lopez-1@ou.edu
Oklahoma has experienced a significant increase and decrease in humaninduced earthquakes in the past decade. The Mw5.8 Pawnee earthquake in2016 is the largest recorded event linked to wastewater injection, rupturing apreviously unmapped Sooner Lake Fault (SLF). Two months after the event,eight continuous Global Navigation Satellite Systems (GNSS) stations were
deployed around the SLF, adding to the growing monitoring networks inthe state. Here, we use multi-year geophysical observations from the Pawnee
region to estimate the spatiotemporal evolution of seismicity and strain andprobe the rheological properties of intraplate faults and crustal layers. We process the GNSS position time series to reveal transient signals due to crustal
processes from late 2016 to 2022. The largest rapid deformation signals coincide with an M3.9 event within earthquake swarms in 2019. Interestingly, theGNSS stations farthest from the faults primarily exhibit subsidence, attributable to poroelastic deformation due to changes in injection activities into shallower rock formations. In contrast, near-fault stations show larger horizontal
movements and uplift, suggesting an origin of faulting processes. Over therecorded post-seismic period, seasonal signals predominate the vertical GNSS
components, whereas the horizontal components show similar steady trends,
with intrastation differences in average rates below ~1 mm/yr. The lack of spatially localized, transient geodetic strain suggests that postseismic fault slip iseither persistently weak over years or short-lived within two months of the
Pawnee event. We further estimate decadal GNSS secular rates over a larger
region and find differential movements of ~1 mm/yr between the Pawnee
array and nearby stations, which may be explained by the viscoelastic flow of
the lower crust. We derive updated source models of the Pawnee mainshockand swarm events to estimate stress changes and assess the contributions ofaseismic slip and poroelastic and viscoelastic deformation.
poster 104
Fluid-Induced Aseismic Slip May Explain the Non-SelfSimilar Source Scaling of the Induced Earthquake
Sequence Near the Dallas-Fort Worth Airport, Texas
LUI, S., University of Toronto, Toronto, Canada, semechah.lui@utoronto.ca;
JEONG, S., University of Toronto, Toronto, Canada, seongju.jeong@utoronto.
ca; TAN, X., University of Toronto, Toronto, Canada, xy.tan@mail.utoronto.ca
Numerous studies have reported the occurrence of aseismic slip or slow slip
events along faults induced by fluid injection. However, the underlying physical mechanism and its impact on induced seismicity remain unclear. In thisstudy, we develop a numerical model that incorporates fluid injection on a
fault governed by rate-and-state friction to simulate the coupled processes ofpore-pressure diffusion, aseismic slip, and dynamic rupture. We establish afield-scale model to emulate the source characteristics of induced seismicity
near the Dallas-Fort Worth Airport (DFWA), Texas, where events with lower
stress drops have been observed. Our numerical calculations reveal that the
diffusion of fluid pressure modifies fault criticality and induces aseismic slip
with lower stress drop values (<1 MPa), which further influence the timing
and source properties of subsequent seismic ruptures. We observe that thelevel of pore-pressure perturbation exhibits a positive correlation with aseis-

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mic stress drops but a reversed trend with seismic stress drops. Simulations
encompassing diverse injection operations and fault frictional parameters
generate a wide spectrum of slip modes, with the scaling relationship ofmoment (M0) with ruptured radius (r0) following an unusual trend, M0∝r04.4,
similar to M0∝r04.7 observed in the DFWA sequence. Based on the consistent scaling, we hypothesize that the lower-stress-drop events in the DFWA
may imply less dynamic ruptures in the transition from aseismic to seismic
slip, located in the middle of the broad slip spectrum, as illustrated in our
simulations.
poster 105
DC or Non-DC? Exploring Uncertainties and Resolution
Limitations for Source Mechanism Studies in a Complex
EGS Environment
NIEMZ, P., University of Utah, Utah, USA, pniemz.seismology@gmail.com;
RUTLEDGE, J., Santa Fe Seismic LLC, New Mexico, USA, rutledge@swcp.
com; PETERSEN, G., GFZ Potsdam, Postdam, Germany, gesap@gfz-potsdam.
de; FINGER, C., Fraunhofer Research Institution for Energy Infrastructureand Geothermal Systems, Bochum, Germany, claudia.finger@ieg.fraunhofer.
de; PANKOW, K. L., University of Utah, Utah, USA, Kris.Pankow@utah.edu
The causal connection between high-pressure fluid injections and induced
seismicity is well known. The source processes of individual microseismic
events and their interaction as an ensemble are less well understood andmay depend on the geological preconditions and the injection design. Two
endmembers of plausible acting mechanisms are pure shear, represented bya double-couple (DC), and pure tensile opening, represented by non-DC
components of the moment tensor. Between the two endmembers, there are
mixed-mode events and the mixed occurrence of both shear-dominated andtensile-dominated events. Differentiating between these mechanisms andresolving the non-DC component can be challenging in many EGS. Surface
monitoring might provide good azimuthal coverage but cannot record relatively small-magnitude events at depth. Borehole monitoring, while closer tothe source area, may suffer from the reduced azimuthal coverage required toreliably resolve differences in the source mechanism. Most EGS projects sufferfrom these inherent difficulties in resolving the source mechanisms of the predominantly small-magnitude events, thereby introducing significant uncertainties in inversion results. Our limited knowledge of the velocity structureof the subsurface may also bias the result, eventually hindering the reliable
resolution of non-DC and DC components. Understanding these limitations
is key for following interpretations of acting larger scale processes, such as
the development of a rather simple hydraulic fracture or the activation of acomplex fracture network mainly driven by slip along preexisting faults andfractures.
We systematically explore these uncertainties and shed light on using
full-probabilistic inversion schemes relying on first-motion polarities, amplitude ratios, spectra, and full-waveforms using real and synthetic data related
to the Utah FORGE, a large-scale experimental EGS.
poster 106
Wastewater Disposal and Hydraulic Fracturing Interaction
Propagating Seismicity in Oklahoma
OGWARI, P. O., University of Oklahoma, Oklahoma, USA, pogwari@ou.edu;
WALTER, J. I., University of Oklahoma, Oklahoma, USA, jwalter@ou.edu;
ALLEN, B., University of Oklahoma, Oklahoma, USA, benjamin.m.allen-1@
ou.edu; THIEL, A., University of Oklahoma, Oklahoma, USA, athiel@ou.edu;
WOELFEL, I., University of Oklahoma, Oklahoma, USA, iewoelfel@ou.edu;
MACE, B., University of Oklahoma, Oklahoma, USA, brandon.mace@ou.edu
Wastewater injection and hydraulic fracturing processes have independently
been attributed to induced seismicity in Oklahoma. When the two processes
occur concurrently in close spatial proximity, an interaction of the perturbed stress can accelerate slip, inducing seismicity on a fault. We analyze
a sequence in eastern Oklahoma, near the town of Quinton, where an earthquake sequence occurred over a several year timespans in 2019-2022, adjacent
to hydraulically-fractured well completions and a large volume injection well.
We use this insight to better understand the interaction between wastewater
injection and hydraulic fracturing processes and evaluate their respective roles
in inducing earthquakes. We analyze the frequency content of the broadband
seismograms to detect possible fluid movement on the seismogenic faults byanalyzing waveforms recorded at the same station to discount the influenceof the ray path and site conditions. Analysis of the energy frequency spectrum (i.e., frequency index) indicates a temporal variation of frequencies that
has increasingly low frequency events correlated with times of active wastewater injection. The increasing low frequency content events coincides withan increased rate of seismicity. Upon the cessation of injection, the low fre-

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quency content in events decreases over time as the seismicity rate decreases.
Constrained earthquake focal depths from a relocated catalog indicate thatthe low frequency earthquakes occur only within the sedimentary formations
along with the high frequency dominated earthquakes, even though the later
extends into the basement. We postulate the hydraulic fracturing process
reactivates faults that are hydraulically connected to the wastewater injection
well that subsequently allow fluid propagation into the seismogenic faults, as
observed from the spatiotemporal distribution of the earthquakes. We conducted lab experiments for different earthquake excitation scenario for faults
saturated with fluid and compare to semi-saturated faults. We will present an
updated analysis of simulation of earthquake excitation on faults with variable
fluid content.
poster 107
Centroid Full Moment Tensor Analysis Reveals Geologicaland Injection Related Constraints of Induced Seismicity at
the Experimental Otaniemi EGS Site, Helsinki Region,
FinlandRINTAMÄKI, A. E., University of Helsinki, Helsinki, Finland, annukka.
rintamaki@helsinki.fi; HILLERS, G., University of Helsinki, Helsinki,
Finland, gregor.hillers@helsinki.fi; HEIMANN, S., University of Potsdam,
Potsdam, Germany, sebastian.heimann@gfz-potsdam.de; DAHM, T., GFZ
Potsdam, Potsdam, Germany, dahm@gfz-potsdam.de; KORJA, A., University
of Helsinki, Helsinki, Finland, annakaisa.korja@helsinki.fi
In 2018 and 2020 two ~6 km deep geothermal wells in Otaniemi, Helsinkiregion, Finland were stimulated to develop an experimental enhanced geothermal system. The stimulations activated pre-existing fracture networks
and induced thousands of small earthquakes. We present the results of centroid full moment tensor (MT) analysis using the probabilistic seismic source
analysis framework Grond and fitting P- and S-waves in the time domain from~30 stations within 9-km of the drill site. Although the Precambrian shieldsetting permits using a half space velocity model, channel-wise time shift andamplitude corrections are used to account for small scale crustal variations.
The competent medium with low attenuation combined with carefully definedcorrections allow the resolution of good MT solutions that reflect the complexities of the source process and source volume.
MT solutions of 301 Mw0.3-2.0 induced events have uniform reverse
mechanisms, which is in apparent conflict with the reported regional strikeslip stress field. The average DC component is 80 % and spatially separated
DC component clusters reveal small differences in local fracture orientations.
The average non-DC component is 20 %, but the non-DC components display clear spatial patterns. In non-DC components a difference is observed
between the 2018 and 2020 MT solutions, the 2018 solutions having an average compressive component and the 2020 solutions having an average opening component. Within the 283 events of the 2018 induced seismicity the
CLVD component trends towards negative values with increasing distancefrom injection well. The ISO component over the full set of 301 events shows
clear spatial variation that seems not to be related to the positioning relative
to the injection wells, but is potentially geologically controlled. We discuss thepotential causes of the difference in non-DC components between the two
injections including different pre-existing medium and fluid properties in theinjection locations, and pore pressure changes following the first stimulation.
poster 108
Inferring Maximum Magnitudes From the Ordered
Sequence of Large Earthquakes
SCHULTZ, R., ETH Zurich, Zürich, Switzerland, ryan.schultz@sed.ethz.ch
The largest magnitude earthquake in a sequence is often used as a proxy for
hazard estimates, as consequences are often predominately from this single
event. In this paper, the statistical concept of order statistics is adapted toinfer the maximum magnitude (MMAX) of an earthquake catalogue. A suite
tools developed here can discern MMAXinfluences through hypothesis testing, quantify MMAXthough maximum likelihood estimation, or select thebest MMAXprediction amongst several models. The efficacy of these tools isbenchmarked against synthetic and real-data tests, demonstrating their utility. Ultimately, thirteen cases of induced seismicity spanning wastewater disposal, hydraulic fracturing, enhanced geothermal systems are tested for volume-based MMAX. I find that there is no evidence of volume-based processes
influencing any of these cases. To the contrary, all these cases are adequately
explained by an unbounded magnitude distribution. These implications
towards mitigating induced seismicity and inferring source processes are discussed. Overall, this suite of tools will be important for better understanding
earthquakes and managing their risks.

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poster 109
Constraining the Non-Double-Couple Components of Local
Events Recorded by Dense Nodal Array
YANG, L., Southern University of Science and Technology, Shenzhen, China,lichun.yang.geo@gmail.com; WANG, R., Southern University of Science andTechnology, Shenzhen, China, wangrj@sustech.edu.cn
Traditional seismic source assumptions (i.e., double-couple model) may not
fully describe small-moderate magnitude events with non-negligible explosive or non-linear features (i.e., non-double-couple components, non-DC).
However, in local distances, constraining these non-DC components is challenged by complex 3D velocity structures that restrain the successful simulation of seismograms. Alternatively, using polarities and amplitudes to resolve
full moment tensors presents significant potential with the recent boost of
the dense nodal array. This study introduces an algorithm combining different far-field observations (i.e., direct P-wave polarities, amplitudes, and S/Pamplitude ratios) to characterize and visualize the non-DC components ofsmall earthquakes. The optimal moment tensor and associated uncertainties
are determined through a grid search over 6-D moment tensor space, andthen projected onto lune plot for virtualization (Tape & Tape 2012). The efficiency and accuracy are tested with both synthetic data and field observations
near a hydraulic-fracturing well (ToC2ME) in Western Canada. The reliability of our metric is quantified via the angular difference ω (i.e., range from0 to 180) between two moment tensors. The range of possible solutions andmismatches increases from ω=1.6 at noise free to ω=15 when 10-times field
noises are added. In addition, our metric shows strong resistance to structure
heterogeneity under such dense array coverage: the optimal solutions can still
be resolved with perturbations on station-based layered-velocity models as
high as 40%. Our inversions for 167 M>1 events within ToC2ME agree with
Zhang et al., 2019, with 93% of events displaying ω<20. Furthermore, whencompared with the known hydraulic-fracturing operations, our reassessed
non-DC components exhibit more interpretable physical processes. Our proposed moment tensor inversion algorithm for dense arrays could serve formany other anthropogenetic involved local-scale settings, especially where
uncertainty evaluation and virtualization for non-DC couple components areneeded.
poster 110
Unraveling the Subsurface Mosaic: Implications of Tectonic
Structures and Fault Orientations on Induced Seismicity
WANGARI, V. N. N., Dedan Kimathi University of Technology, Nyeri, Kenya,
iamwangarik@gmail.com
Pre-existing geological frameworks like tectonic structures, fault orientations, and pore pressure diffusion, contribute to an intricate relationship withinduced earthquakes. This study seeks to develop a holistic understandingon the influence of geologic factors on induced seismic events, by employing
3D fault imaging and InSAR modeling methodologies. The aim is to createa detailed spatial map showing the distribution and orientation of tectonic
structures and faults in the Olkaria Geothermal Complex in Kenya, an areasusceptible to induced seismicity from Geothermal Power Production. The
study aims to uncover patterns and correlations contributing to a comprehensive understanding of the dynamic processes at play beneath the Earth’s surface
by exploring the interplay between these geological features and induced seismicity. The research anticipates an outcome of a refined spatial representationof tectonic elements and valuable insights into the role of fault orientationsin influencing the occurrence and magnitude of induced seismic events. This
research approach underscores its potential to advance our comprehension of
induced seismicity, informing strategies on responsible resource exploitationin regions impacted by human activities like enhanced geothermal systems,
oil and gas production, fluid injection in mining, and carbon capture.
poster 111
On Delayed Triggering of Earthquakes by Anthropogenic
Activities
YANG, H., Chinese University of Hong Kong, Hong Kong, China, hyang@cuhk.edu.hk; ZI, J., Chinese University of Hong Kong, Hong Kong, China,
zijinping@link.cuhk.edu.hk; YANG, Y., Chinese University of Hong Kong,
Hong Kong, China, yuyunyang@cuhk.edu.hk
It is common to observe relatively large earthquakes that occurred after completion of anthropogenic activities. Such delayed triggering poses a significant
challenge in hazard assessment, yet its mechanism remains elusive. Here wefocus on the Weiyuan shale gas field, Sichuan Basin, where the largest earthquake (Mw 5.0) occurred 3 months after the shut-in of nearby fracking wells.
We first construct a high-resolution earthquake catalog, illustrating that theVolume 95•

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source fault of the 2019 Mw 5.0 earthquake was activated one year ahead.
After frackings were completed nearby, the rate of seismicity decreases until
the mainshock occurrence. To explore the mechanism of 3-month delay, wethen develop a fault model in 2D antiplane shear governed by rate-and-state
friction, coupled to pore pressure diffusion. We take into account three past
injections at different wells, and inject fluids in three stages into the velocity
strengthening (VS) part of the fault. A velocity weakening (VW), seismogenic
patch is placed some distance away from the injector. We observe that after
injection stops, aseismic slip is able to propagate further from the VS part of
the fault into the VW patch, making it more susceptible to earthquake nucleation. Even though the first and second injections failed to rupture the fault,
they both contributed to bringing the fault closer to failure. Eventually, theadditional stress perturbation from post-injection aseismic slip due to thethird injection triggered an earthquake, which occurred about 3 months after
injection stopped.
This type of delayed earthquake triggering due to post-injection aseismic
slip from multi-stage injection has not been explored before, and we believe
it is highly plausible that such an effect is not unique to our study region. It
may be a viable mechanism to explain other induced earthquakes that occur
sometime after well shut-in. Apart from pore pressure diffusion and poroelastic effects, post-injection aseismic slip should also be taken into account whenassessing the hazard of earthquakes trailing well stimulation completion.
poster 112
Source Mechanisms Inversion of Induced “Seismicity”
During Laboratory Hydraulic Fracturing
YUAN, H., Tsinghua University, Beijing, China, yuan-z20@mails.tsinghua.
edu.cn; GU, C., Tsinghua University, Beijing, China, guchch@mit.edu;
ZHONG, Y., Tsinghua University, Beijing, China, zhongyc22@mails.tsinghua.
edu.cn; WU, P., Tsinghua University, Beijing, China, wup23@mails.tsinghua.
edu.cn; CHEN, Z., Tsinghua University, Beijing, China, zhuoyu-c21@mails.
tsinghua.edu.cn; KANG, B., Tsinghua University, Beijing, China, kbr19thu@
gmail.com
This paper presents a laboratory study focused on hydraulic fracturing withina shale specimen. During the study, in-situ acoustic emissions were monitored
using a 24-sensor array, with four sensors placed on each of the sample block’s
surfaces. The large shale specimen featured a pre-existing natural fracture
spanning the entire sample. To replicate authentic subsurface stress conditions, a true tri-axial compression system applied confining stress. Fluid wasintroduced through a central borehole within the specimen until a hydraulicfracture developed along a pre-cut notch situated at the borehole’s edge. This
newly formed hydraulic fracture was oriented perpendicular to the pre-existing natural fracture.
We employ a quantitative analysis approach to study hydrofracturing
processes, focusing on the localization and source mechanism inversion of
induced labquakes recorded by the 24-sensor array. Utilizing waveform-based
inversion techniques, our study reveals key insights into the hydraulic fracture
growth and the activation of natural fractures that trigger these recorded labquakes. This research offers a comprehensive understanding of the dynamics
involved in hydraulic fracturing processes.
poster 113
How Induced Earthquakes Response to Pre-Existing
Fractures and Hydraulic Fracturing Operations? a Case
Study in South China
LI, D., China University of Mining and Technology, Beijing, China, dewei.li@
student.cumtb.edu.cn; ZHANG, M., Dalhousie University, Halifax, Canada,miao.zhang@dal.ca; ZHENG, J., China University of Mining and Technology,
Bejing, China, zhengjing8628@163.com; PENG, S., China University of
Mining and Technology, Beijing, China, psp@cumtb.edu.cn
Hydraulic fracturing in shale gas production can induce damaging earthquakes, making it crucial to understand and mitigate the induced seismicity.
The Cen’gong shale gas block in South China offers extensive data—3D seismic, geological structure, microseismic data, and detailed stimulation operations—allowing a comprehensive investigation into induced earthquakes by
hydraulic fracturing. Using a dense temporary seismic array and deep-learning workflows, we build a high-precision earthquake catalog and determine
their focal mechanisms. Pre-existing fractures are identified through the Ant
Tracking attribute derived from the 3D seismic data. We analyze the distribution, frequency, magnitude, and focal mechanisms of induced earthquakes,
compare them spatially with the distribution of the pre-existing fractures,and track their temporal changes during and after hydraulic fracturing. Most
induced earthquakes occurred along pre-existing fractures, exhibiting larger
magnitudes and persisting post-stimulation. Focal mechanisms remain con-

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sistent throughout and after the stimulations. Abrupt drops in injection pressure often coincide with significant earthquakes. Our observations reveal thatinduced earthquakes initiated from the far side of the fractures, and thenlinearly migrated along the pre-existing fractures. This directional migration
pattern is explained by differential stresses along the fractures. Our analysis
suggests that both pre-existing fractures and stimulation operations significantly influence induced earthquake occurrences. Therefore, enhancing ourcomprehension of pre-existing fractures and optimizing stimulation operations can migrate earthquake hazards in shale gas production.

Integrative Assessment of Soil-Structure Interaction andLocal Site Effects in Seismic Hazard Analysis [Poster
Session]Poster Session • Friday 3 May
Conveners: Swasti Saxena, Pacific Northwest National
Laboratory (swasti.saxena@pnnl.gov); Mohammad Yazdi,
Mott MacDonald (mohammad.yazdi@mottmac.com);
Peiman Zogh, University of Nevada, Reno (pzogh@unr.edu)
poster 136
Assessment and Results From New Bayesian SPAC Analysis
for 1D Velocity Profiles Compared to Traditional MASW in
Puerto Rico
TORO ACOSTA, C., University of Puerto Rico at Mayagüez, Puerto Rico,
USA, cherilyn.toro@upr.edu; VANACORE, E., University of Puerto Rico at
Mayagüez, Puerto Rico, USA, elizabeth.vanacore@upr.edu; PACHHAI, S.,
University of Utah, Utah, USA, surya.pachhai@utah.edu; STEPHENSON, W.
J., U.S. Geological Survey, Colorado, USA, wstephens@usgs.gov
In March of 2022, a collaborative research initiative between the United States
Geological Survey and the University of Puerto Rico at Mayagüez led to theacquisition and processing of average shear wave measurements to a depthof 30 meters (Vs30) at 22 seismic stations across Puerto Rico employing, inpart, conventional Multichannel Analysis of Surface Waves (MASW) methodologies. However, estimation of velocity profiles using the MASW technique
is a nonlinear process, and rigorous estimation of uncertainty in Vs profiles
and Vs30, while crucial for proper physical interpretation, is a challenging
problem. The uncertainty in MASW Vs profiles can stem from both theoretical challenges (e.g., higher modes, topography, near and far field effects,
insufficient source energy, unknown model parameterization) as well as measurement errors (e.g., noisy geophone recordings). Here, we present a newphase of the investigation wherein select MASW-analyzed sites in Puerto Ricowill undergo reevaluation using a Bayesian Spatial Autocorrelation (SPAC)
method using microtremor array data collected with temporary small-aperture nodal arrays. Having both MASW and SPAC datasets will provide theopportunity for a comparative analysis between the two methodologies for
ocean island environments. The Bayesian SPAC methodology we use provides a rigorous estimation of uncertainty in Vs and Vs30 when compared to
the MASW models we developed through a least-squares iterative modelingapproach. Based on preliminary SPAC results, the study will be expanded toinclude new sites not necessarily suitable for traditional active-source multimethod data collection. The additional site selections will be guided by theseismic resilience needs articulated by local communities throughout PuertoRico. This expansion is conceived as part of a collective impact earthquake
science initiative, aligning research endeavors with the practical requirementsof the community.
poster 137
Seismic Response in Pyramids of the Chichén Itzá Area,
MéxicoCARDENAS-SOTO, M., Universidad Nacional Autónoma de México,
Coyoacán, Mexico, martinc@unam.mx; ESCOBEDO-ZENIL, D.,
Universidad Nacional Autónoma de México, Mexico City, Mexico, dzenil@
unam.mx; CIFUENTES-NAVA, G., Universidad Nacional Autónoma deMéxico, Mexico City, Mexico, gercifue@igeofisica.unam.mx; SÁNCHEZGONZÁLEZ, J., Universidad Nacional Autónoma de México, Mexico City,
Mexico, jesus.sanchez@ingenieria.unam.edu; MARTÍNEZ-GONZÁLEZ,J., Universidad Nacional Autónoma de México, Mexico City, Mexico, jose.
martinez@ingenieria.unam.edu; ARGOTE-ESPINO, D., Instituto Nacionalde Antropología e Historia, Mexico City, Mexico, efenfi@gmail.com;
SANDOVAL-QUINTANA, O., Universidad Nacional Autónoma de México,

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Morelia, Mexico, osirissandovalq@gmail.com; LÓPEZ-GARCIA, P., Instituto
Nacional de Antropología e Historia, Mexico City, Mexico, dplopez@prodigy.
net.mx; CARRILLO-VARGAS, A., Universidad Nacional Autónoma deMéxico, Morelia, Mexico, armando@igeofisica.unam.mx
We analyzed the seismic response of three archaeological structures in the
Chichén Itzá area, Yucatán, Mexico, to provide elements that track their preservation. We measured ambient seismic noise with broad-band seismographs
for three days, and we used the HVSR method and transfer functions to quantify vibration frequencies. The results show that the site frequency is 1.3 Hz.
However, in the pyramids under study, especially the Kukulkan Pyramid, also
called The Castle, the fundamental frequency is 5.1 Hz with a relative amplification of around 6. Our results show that the pyramids behave like soft soil
on a rigid layer. In the case of the Kukulkan Pyramid, the noise recording at its
base allows us to observe an effect of kinematic interaction due to the difference in rigidity between the subsoil and the structure. We did not observe any
directional effect on HVSR curves due to the internal anisotropy of the pyramids. The estimated internal shear velocity is 255 m/s (considering the seismic
response is of topographic origin). This velocity corresponds to non-compact
materials resting on competent substratum with velocities larger than 1000m/s, materials that are susceptible to stress changes that may eventually leadto structural deterioration. The findings of this study suggest that continuous
monitoring and instrumentation of the lower levels is needed to evaluate theinfluence of sub-structures during the pre-construction stages and to determine whether there are other effects due to the karstic nature of the subsoil.
poster 138
Site Response Analysis and Its Significance at Nonlinear
Sites
LEE, J., Mott MacDonald, California, USA, jongwon.lee@mottmac.com;
BAYUDANTO, A., Mott MacDonald, California, USA, alvin.bayudanto@mottmac.com; YAZDI, M., Mott MacDonald, Washington, USA, mohammad.
yazdi@mottmac.com; RONG, W., Mott MacDonald, California, USA,wenyong.rong@mottmac.com; WALKER, M., Mott MacDonald, California,
USA, martin.j.walker@mottmac.com
This study presents a case history of one-dimensional time-domain nonlinear site response analysis for a major infrastructure project in the San Joséarea, California, USA. The subsurface material of the study site consists of
Holocene alluvial deposits with interbedded and crosscut clays and silts,
sands, and gravels. Two levels of design earthquakes were considered herein
associated with the return periods of 225 and 975 years. For each designlevel, site response analyses were performed to propagate a suite of elevenpairs of horizontal input ground motions at the reference soil horizon (adepth of about 75 m; VS30 of about 490 m/s) through a site-specific groundmodel. Also, a series of sensitivity evaluations were also conducted for verifying and enhancing understanding of dynamic response of the study site.
The site response analysis results show the site exhibits high nonlinearity, deamplifying short-to-intermediate period content (0.01 to 1 s) while amplifying long period content. A comparison of surface response spectra from thesite response analysis versus ground motion models and probabilistic seismic
hazard analysis (PSHA) is presented herein highlighting the design implications of conducting site response analyses at soft sites, where high nonlinearity
is anticipated.
poster 139
Ambient Vibration Testing of Canada’s Tallest Wood Frame
Building
LEISHMAN, T., University of Victoria, Victoria, Canada, tessleishman@gmail.com; VENTURA, C. E., University of British Columbia, Vancouver,
Canada, ventura@civil.ubc.ca; MOTAMEDI, M., University of British
Columbia, Vancouver, Canada, mmotamedi@civil.ubc.ca; CASSIDY, J.,
Natural Resources Canada, Sidney, Canada, john.cassidy@nrcan-rncan.gc.ca;
DOSSO, S. E., University of Victoria, Victoria, Canada, sdosso@uvic.ca
The objective of this research is to study the dynamic characteristics of therelatively new and increasingly popular class of tall wood frame buildings
to better understand their natural mode frequencies and shapes. This study
quantifies the dynamic characteristics of the tallest wood frame building in
Canada, the 18-storey Brock Commons building, located in Vancouver, British
Columbia. Identification of the modal characteristics of the building can contribute to understanding the dynamic behaviour of tall wood buildings in
general, especially to better model and predict their behaviour under seismic
loading by parameterization of numerical models. In situ ambient vibration
tests were conducted on the structure and the enhanced frequency domain
decomposition technique was employed to carry out a complete operationalwww.srl-online.org•

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modal analysis of the building. Translational modes in x- and y-directions aswell as torsional and rocking modes are identified, ranging in frequency from0.940-9.232 Hz. Results show the fundamental period of 1.064 s is lower thanthe period predicted by a finite element model (2.0 s), suggesting the building
is less flexible than estimated. The identification of rocking modes similar to
the natural frequency of the surrounding soil suggest that soil-structure interaction contributes to these modes; however, a soil-specific study is required tofurther explore these effects.
poster 140
Wind Turbines as a Metamaterial-Like Urban Layer: An
Experimental Investigation Using a Dense Seismic Array
and Complementary Sensing Technologies
PILZ, M., GFZ Potsdam, Potsdam, Germany, pilz@gfz-potsdam.de; ROUX,
P., University Grenoble Alpes, Grenoble, France, philippe.roux@univgrenoble-alpes.fr; MOHAMMED, S. A., University Grenoble Alpes, Grenoble,
France, shoaib-ayjaz.mohammed@univ-grenoble-alpes.fr; GARCIA, R. F.,
Institut Supérieur de l’Aéronautique et de l’Espace, Toulouse, France, Raphael.
GARCIA@isae.fr; STEINMANN, R., GFZ Potsdam, Potsdam, Germany,steinre@gfz-potsdam.de; AUBERT, C., University Grenoble Alpes, Grenoble,
Germany, coralie.aubert@univ-grenoble-alpes.fr; BERNAUER, F., Ludwig
Maximilian University of Munich, Munich, Germany, fbernauer@geophysik.
uni-muenchen.de; GUÉGUEN, P., University Grenoble Alpes, Grenoble,
France, philippe.gueguen@univ-grenoble-alpes.fr; OHRNBERGER, M.,
University of Potsdam, Potsdam, Germany, mao@geo.uni-potsdam.de;
COTTON, F., GFZ Potsdam, Potsdam, Germany, fcotton@gfz-potsdam.de
A fundamental difficulty in earthquake engineering is the deflection andcontrol of the impacts of the complex urban seismic wavefield on the built
environment. The interactions between the soil and the structures, as well
as between the structures, have a significant impact on the lateral variety ofground motion with respect to earthquake damage. Here we report on a study
investigating the hypothesis that flexural and compressional resonances ofa large number of structures—in this case wind turbines in a wind farm—strongly influence the propagation of the seismic wavefield. A large-scale geophysical experiment demonstrates that surface waves are strongly damped inseveral distinct frequency bands when interacting at the resonances of a set ofwind turbines. The ground-anchored arrangement of these turbines produces
unusual amplitude and phase patterns in the observed seismic wavefield aswell as differences in the intensity ratio between stations inside and outside
the wind farm and in surface wave polarization. Additional geophysical equipment (e.g. an optical fiber, rotational and barometric sensors) was used toprovide essential explanatory and complementary measurements. A numerical model of the turbine also confirms the mechanical resonances that are
responsible for the strong coupling between the wind turbines and the seismic
wavefield observed in certain frequency ranges of engineering interest.
poster 141
Site-City Interaction in the Valley of Mexico: 3D
Simulations and Observations
RAMIREZ-GUZMAN, L., Universidad Nacional Autonoma de Mexico,
Mexico, Mexico, lramirezg@iingen.unam.mx; CARRILLO LUCIA, M. A.,
Universidad Nacional Autonoma de Mexico, Mexico City, Mexico, mcarrillol@
iingen.unam.mx; CONTRERAS, M. G., Universidad Nacional Autonoma de
Mexico, Mexico, Mexico, mcontrerasr@iingen.unam.mx; BAÑUELOS, D.,
Universidad Nacional Autonoma de Mexico, Mexico, Mexico, dbanuelosg@
iingen.unam.mx
We investigate the built environment’s impact on ground motion in Mexico
City. Our research is based on robust velocity and city models, the details of
which are thoroughly discussed, and numerical simulations. In our velocity
model, we incorporated over two hundred one-dimensional profiles obtained
from a noise tomography of the southern part of Mexico City. Additionally,
we integrated more than one hundred geotechnical profiles into a regional
velocity model. The shear beams, representing the utilized buildings, are thefirst comprehensive digital model of the Mexico City metropolitan area. The
building inventory was compiled by merging LIDAR information from theValley of Mexico, data from the current building inventory published by thegovernment of Mexico City, and data available from the metropolitan areaof the State of Mexico. Regarding system modeling, we conducted finite element simulations using data from a local earthquake and the M7.1 2017
Puebla-Morelos earthquake. Preliminary analyses, valid up to 1Hz, reveal anincrement in ground motion duration attributable to the presence of buildings. Also, we observe a velocity reduction at ground level in areas with highbuilding density, along with the formation of waveguides channeling energy
in several areas of the lake zone due to arrays of structures. We compared ourVolume 95•

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simulations with the reported damage during the Puebla-Morelos event. Ourfindings indicate that the observed damage levels are better explained when
considering the city than in simulations that ignore the city.
This work was supported by UNAM-PAPIIT IT104223.
poster 142
Seismic Response of Nenana Sedimentary Basin, Central
AlaskaSMITH, K., Academia Sinica, Colorado, USA, kyle36smih85@gmail.com;
TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu;
TSAI, V. C., Brown University, Rhode Island, USA, victor_tsai@brown.edu
Nenana basin in central Alaska is a long (90 km), narrow (12 km), and deep
(7 km) sedimentary basin aligned with an active fault zone producing Mw>= 6 earthquakes. From 2015 to 2019, 13 broadband seismic stations were
deployed in the region as part of the Fault Locations and Alaska Tectonics
from Seismicity project. These stations recorded a wide range of earthquakes,
including Mw 3–4 directly below the basin as well as several regional earthquakes Mw > 6. These 43 local and regional earthquakes, in addition to fiveteleseismic events and continuously recorded ambient noise, provide a data set
that we use to quantify the response of Nenana basin to the seismic wavefield.
We calculate spectral ratios between each station and a bedrock reference
station for 48 earthquakes. We find amplification of 11–14 dB (amplification
ratio 3.5–5.0) for low frequencies (0.1–0.5 Hz), and 8–15 dB (amplification
ratio 2.5–5.6) for high frequencies (0.5–4.0 Hz) on the vertical component.
At low frequencies, amplification of the earthquake wavefield agrees well withamplification of seismic noise, with both data sets exhibiting stronger amplification on the horizontal components, in comparison with the vertical component. Furthermore, stations overlying the deeper part of the basin exhibit
stronger amplification, whereas stations at the margin of the basin exhibit
minimal low-frequency amplification. At higher frequencies, amplification
occurs at both deeper basin stations and also marginal basin stations. Our
study establishes a catalog of diverse events for future theoretical and numerical studies that can use Nenana basin to better understand the complex influence of sedimentary basins on the seismic wavefield.
poster 143
State of the Art in Seismic Metamaterials
STEPHANE, B., Aix Marseille Université, Saint-Fons, France, stephan.
brule@yahoo.com
Studies on structured soils, including seismic metamaterials, have shown
the existence of complex wave phenomena within and around the structured zone. The aim is to assess areas where seismic or vibratory energy isconcentrated, and to decide whether it would be worthwhile to exploit themby judiciously placing piezoelectric energy sensors. The article presents what
is already being done with vibration sensors implanted in civil engineering
structures and shows the potential interest of seismic metamaterials in thiscontext. The modification of the surface signal by both structured soil and surface resonators meets the challenges of Civil Engineering through the effects
of soil-structure interaction. Seismic metamaterials can therefore not only
be considered for building protection, lensing and minimizing the effects ofpotentially deleterious Rayleigh waves, but also have potential applications inenergy harvesting using ambient seismic noise.

Learning Across Geological, Geophysical & Model-Derived
Observations to Constrain Earthquake Behavior
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Kimberly Blisniuk, San José State University(kimberly.blisniuk@sjsu.edu); Roland Bürgmann, R.,
University of California, Berkeley (burgmann@berkeley.
edu); Elizabeth Madden, San José State University (elizabeth.
madden@sjsu.edu)
Strain Accommodation Along the Northeast Altyn Tagh
Fault System and the Potential for a Future LargeMagnitude, Multi-Fault Rupture
YANG, H., China Earthquake Administration, Beijing, China,
yanghaibo2015@gmail.com; YANG, X., China Earthquake Administration,
Beijing, China, yangxiaoping-1@163.com; CUNNINGHAM, D., Eastern
Connecticut State University, Connecticut, USA, cunninghamw@easternct.

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edu; HUANG, X., China Earthquake Administration, Beijing, China,
xiongnan_h@sohu.com
Large continental strike-slip fault systems typically comprise a principal displacement zone and subordinate splay faults, exhibiting complex geometry
and variations in fault distribution. Understanding the architecture, interconnections, and synchronous rupture patterns of these faults is crucial forcomprehending their tectonic evolution, strain distribution, and earthquake
behavior. Here we provide a comprehensive analysis of Quaternary deformation, interconnection, and late Holocene ruptures along the EW-trending
Nanjieshan Fault (NJSF), a major branch fault of the Altyn Tagh Fault (ATF)
system. The calculated strike-slip rate of the master NJSF is ~0.5 mm/a since~45 ka, consistent with the low slip rates observed on other faults NW of the
ATF. Moreover, the NJSF may have experienced an exceptionally high slip ratesince the late Pleistocene, implying a potential change in fault strain distribution along the northern ATF. New trench data across the NJSF reveals threesurface-rupturing events in the last 2500 years. Significantly, these millennium-scale events coincide temporally with the last two major earthquakes
documented on the principal ATF, suggesting quasi-simultaneous rupture
behavior. We conclude that accurate evaluation of paleoearthquake magnitudes and potential rupture behavior on major continental strike-slip fault
systems should include field studies of both the principal fault and subordinate branching faults.
Partitioning of Oblique Convergence During Simultaneous
Rupture of a Megathrust and Splay Fault: Observations
From the Western Nepal Fault System
BEMIS, S. P., Virginia Tech, Virginia, USA, sbemis@vt.edu; CURTISS, E.
R., Virginia Tech, Virginia, USA, elizabethrc@vt.edu; MURPHY, M. A.,
University of Houston, Texas, USA, mmurphy@central.uh.edu; TAYLOR,
M. H., University of Kansas, Kansas, USA, mht@ku.edu; STYRON, R., GEM
Foundation, Oregon, USA, richard.h.styron@gmail.com; HOXEY, A. K. R.,
University of Kansas, Kansas, USA, andrew.hoxey@ku.edu; CHAMLAGAIN,
D., Tribhuvan University, Kathmandu, Nepal, deepakchamlagain73@gmail.
com
The subaerial megathrust system of the Himalaya provides opportunities
for examining subduction zone - splay fault behavior using methods thatare difficult for the typical submarine subduction zone environments. Some
major historic megathrust ruptures (e.g., the 1964 Good Friday earthquake
in Alaska) have produced simultaneous displacement on sub-parallel splay
faults, but how common is this splay-fault behavior and what role does it playin slip partitioning in subduction zones undergoing oblique convergence? In
the Himalayan orogen, we examine the Western Nepal fault system, a generally NW-trending series of faults that cut obliquely across the structuralgrain of the Himalayan orogen and is interpreted to intersect with the Main
Himalayan Thrust (MHT) at depth. Paleoseismic investigations along mostof the fault system reveal youthful surface ruptures, and while several sites
have limited temporal resolution, several of these sites specifically constrain
the occurrence of a surface-rupturing earthquake within the past 700 years.
This timing overlaps with the Great 1505 Himalayan earthquake, the only historic rupture of the MHT interpreted to have ruptured beneath the WNFS.
The trace of the WNFS across topography illustrates a typically moderate tosteep N to NE dip and landforms offset across the fault define long-term rightlateral and extensional motion, with relative proportions of lateral vs. extensional slip increasing to the NW along the fault system. Based on the lack of
documented large historic earthquakes in the area of the WNFS, we proposethat the WNFS ruptured simultaneously with the rupture of the megathrustin the 1505 earthquake, or as several smaller earthquakes that are below thecurrent limit of detection from pre-instrumental records. The slip-partitioning across the Himalaya of western Nepal is accommodated by earthquakes
occurring on faults bounding a sliver of the orogenic wedge, and the potential
for simultaneous ruptures of these faults (MHT and WNFS) presents a new
scenario for seismic hazard assessment of the region.
Architecture of an Active Tsunamigenic Splay Fault:
Outcrop to Micro-Scale Structure of the Patton Bay Fault,
Montague Island, Alaska
FINTEL, A., University of Washington, Washington, USA, afintel@uw.edu;
TOBIN, H., University of Washington, Washington, USA, htobin@uw.edu;
HAEUSSLER, P., U.S. Geological Survey, Alaska, USA, pheuslr@usgs.gov
In the 1964 Mw 9.2 megathrust earthquake in south-central Alaska, the Patton
Bay splay fault hosted coseismic rupture both offshore and on Montague
Island with up to 10m of throw along the surface. The offshore expression ofthis fault has been proposed to be a source of the subsequent local tsunami.

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Tsunami-genesis can be influenced by surface rupture of shallow, megathrustrelated splay faults and how they transfer seismic slip from a megathrust rupture path to the surface. The 1964 rupture came to the surface along the Strike
Creek strand of the PBF fault, but the locus of major long-term displacement
is the nearby Deception Creek strand, which is well-exposed on an intertidal
wave-cut platform. This unique on-land exposure of an active megathrust
splay fault presents the opportunity to investigate the fault zone architecture
and mechanical properties from host rock to fault core. Macro- and microstructural observations are being used to determine the fault zone and fault
rock properties that reflect earthquake processes. Microstructural analysis
includes identifying potential cataclasite formation, fluidized fault rocks, foliated fault gouge, shear sense, and mineralogical or geochemical signatures offrictional heating, each potentially a signature of past seismicity. We identified field-scale structural zones including hanging wall and footwall damage
zones and a fault core. The fault zone is ~150-m wide, with damage zones
made up of highly fractured bedrock, disrupted bedding, cataclasite-richpatches, and a nearly continuous gouge-rich fault core ~8-m wide. The damage zones have varying degrees of disrupted and intensely fractured bedding
and local cataclasite formation. This exposed fault exhibits structural variations consistent with a mature brittle fault with a single principal slip zone thatis surrounded by a fractured damage zone. These structural characteristics
have been described in other seismogenic splay fault studies and support theconclusion that Deception Creek fault is the primary strand of the Patton Bay
Fault on Montague Island and has historically ruptured in great earthquakes.
Paleoseismic Investigations of Quaternary Active Faults in
the Forearc and Backarc of the Central Pacific Northwest,
u.s.a.
STREIG, A. R., Portland State University, Oregon, USA, streig@pdx.edu;
DUNNING, A., Portland State University, Oregon, USA, adunning@pdx.
edu; BENNETT, S. E., U.S. Geological Survey, Oregon, USA, sekbennett@
usgs.gov; MADIN, I., Portland State University, Oregon, USA, madin@pdx.
edu; WELLS, R. E., U.S. Geological Survey, Oregon, USA, rwells@usgs.gov;
HORST, A., GRI, Oregon, USA, AHorst@gri.com; BALCO, G., Berkeley
Geochronology Center, California, USA, balcs@bgc.org; AMIDON, W.,
Middlebury College, Vermont, USA, wamidon@middlebury.edu
Oblique northeast-directed subduction of the Juan de Fuca plate and northward impingement of the Sierra Nevada block drive clockwise rotation of
the PNW region relative to stable North America. Our work has yielded
new observations of surficial deformation across the central Cascade Arc inOregon (OR) where the rates and timing of faulting during the past 100,000
years are largely unconstrained. We combine lidar and field-based mapping to
identify Quaternary active structures, characterize their slip rates, and where
possible, constrain the timing of prehistoric surface rupturing earthquakes.
In eastern OR, on the Strawberry Mountain fault, we document extensional
faulting in a region broadly inferred to be compressional - related to Yakima
Fold and Thrust deformation. Here, we document 2 post-LGM earthquakes
and calculate a slip rate of 0.18 ± 0.02 mm/yr since the late Pleistocene.
The central Cascade volcanic Range is defined by a lower relief ancestral
Eocene to Miocene arc forming the western foothills and is offset relative tothe active high Cascades arc, a result of ~ 1°/My clockwise rotation for thelast 16 My. The westward escape of the forearc creates a space problem, earlier
research shows that the arc creates new crust on the trailing edge, and we
document structural accommodation of tectonic extension by normal faulting. We observe numerous N-S trending extensional faults through both thehigh and ancestral arc. On the Mt Hood fault zone we map glacial moraines
from the most recent glaciation, 21.2 ka ± 3 based on our new He3 surface
exposure ages, offset by 2.7 m high scarps. A trench across an uphill facing
scarp revealed 2 post-LGM surface rupturing earthquakes, and 2.3 m of total
vertical separation. In the OR Coast Range on the Gales Creek Fault, we map
right laterally deflected drainages, aligned springs, and side-hill benches. A
paleoseismic trench here revealed evidence of three surface rupturing earthquakes in the last ~8,800 yr. We speculate that the earthquake timing may belinked to large on-shore stress changes in the crust immediately following a
megathrust subduction zone earthquake.
Coseismic Temperature Proxies and their Applications to
Understanding Earthquake Rupture and Seismic Hazard
COFFEY, G. L., GNS Science, Lower Hutt, New Zealand, g.coffey@gns.cri.
nz; SAVAGE, H. M., University of California, Santa Cruz, California, USA,hsavage@ucsc.edu; POLISSAR, P. J., University of California, Santa Cruz,
California, USA, ppolissa@ucsc.edu; COX, S. E., Columbia University, New
York, USA, cox@ldeo.columbia.edu; HEMMING, S. R., Columbia University,

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New York, USA, sidney@ldeo.columbia.edu; MORGENSTERN, R., GNS
Science, Lower Hutt, New Zealand, r.morgenstern@gns.cri.nz
During an earthquake, frictional resistance along a fault can lead to the generation of high temperatures. The temperature rise that occurs provides clues
into an earthquake’s size and rupture dynamics as temperature is dependent
on various earthquake properties like displacement and frictional energy.
Numerous thermal proxies have been developed to evaluate coseismic temperature rise including but not limited to biomarkers, pseudotachylyte, vitrinite reflection, and calcite decomposition.
Here, we present results of work integrating these proxies and what they
can teach us about earthquakes with a particular focus on biomarkers, which
are organic molecules present in some rocks that are progressively alteredwith increasing temperature and duration of heating. These proxies provide
a means of constraining the displacement during an earthquake along bedrock faults where traditional paleoseismic techniques cannot be applied. They
also enable quantification of the frictional energy dissipated during slip andtherefore, insight into the earthquake energy budget. We also present recent
and ongoing work on faults in California and New Zealand, which couples
biomarker thermal maturity with K/Ar dating to assess when these faults lastexperienced the high temperatures associated with earthquake slip, and hence
when they were last active.
Inter-Seismic Slip in Caldera Collapse Earthquake Cycles
CROZIER, J. A., U.S. Geological Survey, California, USA, crozierjosh1@
gmail.com; ANDERSON, K. R., U.S. Geological Survey, California, USA,
kranderson@usgs.gov; SEGALL, P., Stanford University, California, USA,segall@stanford.edu
In most tectonic settings, multiple complete characteristic earthquake cycles
have not been observed and loading histories can be complicated, which limits the extent to which field-scale fault frictional behavior can be resolved.
Empirical rate-and-state dependent friction formulations based on smallscale lab experiments are a standard starting point, and there is experimental
and observational evidence for the importance of processes such as dynamic
weakening. However, the relevant physical mechanisms and potentiallyheterogeneous parameters controlling friction are generally not well constrained. In this work, we approach field-scale fault mechanics by studying
caldera collapse at basaltic volcanoes, which has been observed to occur via
sequences of multiple discrete ring fault earthquakes. We focus specifically on
the well-monitored 2018 eruption of Kīlauea Volcano, which exhibited large
amounts of both co- and inter-seismic slip. We use 2D axisymmetric earthquake cycle simulations, with fully dynamic elasticity and compressible viscous fluid flow, which show that standard rate-and-state friction formulations
cannot readily produce the amount of co- and inter-seismic slip observed.
We investigate whether adding dynamic weakening and asperities to primarily velocity-strengthening faults can better explain seismic and geodetic data.
Additionally, we explore what depth-dependent fault properties and physical weakening mechanisms (e.g., thermal pressurization or shear heating)are most consistent with observations. These findings have implications forunderstanding fault mechanics in general, fault properties in volcanic andgeothermal settings, and the dynamics of collapse eruptions.
The Influence of Preexisting Geologic Structures on
Coseismic Surface Deformation During the 2019 M7.1
Ridgecrest, California, Earthquake
NEVITT, J. M., U.S. Geological Survey, California, USA, jnevitt@usgs.gov;
BROOKS, B., U.S. Geological Survey, California, USA, bbrooks@usgs.gov;
BADEN, C., U.S. Geological Survey, California, USA, cbaden@usgs.gov;
HARDEBECK, J., U.S. Geological Survey, California, USA, jhardebeck@usgs.
gov; AAGAARD, B. T., U.S. Geological Survey, Colorado, USA, baagaard@
usgs.gov; GARCIA, E., University of Michigan, Michigan, USA, fegarcia@
umich.edu; LOCKNER, D., U.S. Geological Survey, California, USA,
dlockner@usgs.gov; KILGORE, B., U.S. Geological Survey, California, USA,bkilgore@usgs.gov; BEELER, N., U.S. Geological Survey, Washington, USA,nbeeler@usgs.gov; MOORE, D., U.S. Geological Survey, California, USA,dmoore@usgs.gov; YEAGER, S., U.S. Geological Survey, California, USA,syeager@usgs.gov; ERICKSEN, T., U.S. Geological Survey, California, USA,
tericksen@usgs.gov; RUTH, D., U.S. Geological Survey, California, USA,druth@usgs.gov
We investigate how preexisting structures influenced the 2019 M7.1
Ridgecrest, California earthquake rupture at the tens-of-kilometers and meterscales by combining field and remote sensing observations, laboratory analysis, and mechanical modeling. At the longest scales, the fault geometry appears
to be inherited from the surrounding late Jurassic Independence dike swarm

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www.srl-online.org(IDS), mapped with satellite imagery and airborne lidar data. In the field, we
observe multiple fracture sets surrounding the dikes, including dike-parallel
fractures that add to the pervasive structural fabric that existed prior to fault
initiation. Based on the common geometries and observed deformation, we
conclude that the Ridgecrest source faults likely evolved through reactivationof IDS structures. Consequently, we show through a series of finite-element
models that the inherited fault geometry strongly controlled the coseismic
slip distribution, producing elevated slip (~3-4 m compared to <~1 m elsewhere) within a ~12-km-long section of the rupture oriented ~20 degrees
more northerly than elsewhere. Part of this maximum slip zone lies within
the China Lake Playa where the rupture localized into knife-edge echelon
segments separated by meter-scale left steps. We explore surface rupture processes at this length scale using discrete element models, which suggest thatthe development of such a narrow deformation zone is encouraged by loosely
packed granular material that produces minimal dilation during shear. We
analyze samples collected from the surface rupture using scanning electron
microscopy techniques and find that a sequence of evaporite minerals coat
the rupture surface, including halite that flows ductilely around broken clastsof carbonate mud. These observations suggest that the 2019 surface rupture
may have reoccupied preexisting fractures, perhaps formed during a previous
surface-rupturing earthquake. Over the range of scales considered, combining
field, laboratory, and modeling methods illustrates the importance of preexisting structures in controlling where and how earthquake deformation accrues.
Bayesian Dynamic Source Inversion of the 2004 Parkfield
Earthquake: Insights From Linked 3D Dynamic Rupture andAfterslip Modeling Constrained by Gps and Strong
Motions
SCHLIWA, N., Ludwig Maximilians University of Munich, Munich,Germany, nico.schliwa@geophysik.uni-muenchen.de; GABRIEL, A. A.,
University of California, San Diego, California, USA, algabriel@ucsd.edu;
PREMUS, J., Côte d’Azur University, Nice, France, Jan.PREMUS@univcotedazur.fr; GALLOVIČ, F., Charles University, Prague, Czechia (Czech
Republic), frantisek.gallovic@matfyz.cuni.cz
The 2004 Mw 6.0 Parkfield earthquake is one of the best-observed events
ever. Since then, computational capabilities and methods have tremendously
advanced, enabling the illumination of the source process with unprecedented
detail. We present a 3D Bayesian dynamic rupture finite-fault inversion of the2004 Parkfield earthquake where the model parameters consist of the spatiallyvariable prestress and friction parameters. We use a fast-velocity-weakening
rate-and-state friction law to simulate the coseismic and postseismic rupture phases in the same modeling framework. Strong motion and GPS data,
including three months of postseismic displacements, constrain the inversion.
We use a parallel tempering Markov chain Monte Carlo approach to tackle thenon-linear high-dimensional inversion problem.
The Bayesian approach provides an ensemble of models fitting thedata from which we infer the mean and variability of various kinematic anddynamic parameters. We provide estimates of stress drop, fracture energy,
and radiation efficiency, which are constrained by the data and the underlying physics. The coseismic rupture transitions from pulse-like to crack-likeas it propagates towards the creeping section of the San Andreas fault. The
pulse-like phase generates most of the seismic radiation while the crack-like
rupture dominates the coseismic GPS recordings. We observe different rupture arrest mechanisms imprinting on the subsequent afterslip evolution.
Afterslip concentrates within two major patches above the coseismic rupturezone separated by a barrier that also delays the coseismic rupture. Parts of thefault that already slipped coseismically continue to host afterslip. We find a
gradual increase in afterslip rise time and identify different modes of afterslip.
Our results provide new insights into earthquake rupture complexity and thetransition from the coseismic to the postseismic phase.
Multi-Cycle Evolution of Seismicity and Fault Zone for a
Fault Network
MIA, M., University of Illinois Urbana-Champaign, Illinois, USA, mmia2@
illinois.edu; ABDELMEGUID, M., California Institute of Technology,
California, USA, meguid@caltech.edu; ELBANNA, A. E., University of
Illinois Urbana-Champaign, Illinois, USA, elbanna2@illinois.edu
Seismic activity exists in a variety of scales from small tremors to large earthquakes resulting in severe economic and societal impacts. It is crucial tounderstand the mechanism behind the rupture of complex fault systems andhow it evolves with time to better inform the seismic hazard models. Here, we
model sequences of earthquakes and aseismic slip for a fault network having
a primary fault and multiple secondary faults with different size and orientations. We incorporate Drucker-Prager plasticity with pressure dependent

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yield criterion to capture the off-fault bulk response. The friction is modelled
by a rate and state dependent friction law. We assume 2D plane strain deformation and utilize an in-house hybrid numerical scheme, FEBE, combing
finite element (FEM) and spectral boundary integral (SBI) methods to resolve
both fast dynamic events and slow interseismic deformation.
The simulation results show emergence of complex seismicity including spatiotemporal clustering, foreshocks, and aftershocks. We observe coseismic activation of the secondary faults during the rupture propagation on
the primary fault as well as the migration of aseismic slip between the nearby
secondary faults. Foreshocks happen on the secondary faults when the lengthof the secondary faults is greater than the nucleation length. The initial phaseof the seismic cycle exhibits partial ruptures on the primary fault with more
distributed seismicity on the secondary faults. Later, the seismicity tends tobecome more concentrated on the primary fault with full fault spanning rupture. The evolution of off-fault plasticity for the fault network shows more
plastic deformation near the ends of the secondary faults that experiences
activation. This plastic strain is indicative of off-fault damage and demonstrate
the possible non-equilibrium evolution of seismicity and fault zone hosing a
network of faults. Our findings may enlighten the understanding of the seismic source mechanics for complex fault zones and the long-term evolution of
the fault zone with multi-cycle earthquakes.
Bayesian Inference of Rheological Parameters From
Observations Before and After the Tohoku Earthquake
MARSMAN, C., Utrecht University, Utrecht, Netherlands, c.p.marsman@
uu.nl; VOSSEPOEL, F., Delft University of Technology, Delft, Netherlands,
f.c.vossepoel@tudelft.nl; D’ACQUISTO, M., GFZ Potsdam, Potsdam,
Germany, mariod@gfz-potsdam.de; VAN DINTHER, Y., Utrecht University,
Utrecht, Netherlands, y.vandinther@uu.nl; GOVERS, R., Utrecht University,
Zeist, Netherlands, r.govers@uu.nl
We seek to quantify bulk viscoelastic flow, afterslip, and locking, within arheological framework that is consistent over the entire earthquake cycle. We
address this using an ensemble smoother. We construct a 2D finite element
seismic cycle model with a power-law rheology in the mantle. A priori information, such as a realistic temperature field and a coseismic slip distribution,is integrated into the model. Model pre-stresses are initialized during repeatedearthquake cycles wherein the accumulated slip deficit is released entirely. We
tailor the last earthquake to match the observed co-seismic slip of the 2011
Tohoku earthquake. The heterogeneous rheology structure is derived fromthe temperature field and experimental flow laws. Additionally, we simulate
afterslip using a thin, low-viscosity shear zone with a Newtonian rheology.
We focus on constraining power-law flow parameters for the mantle, and theshear zone viscosity.
We assimilate 3D GEONET GNSS displacement time series acquired
before and after the 2011 Tohoku earthquake. The data require separate viscoelastic domains in the mantle wedge above and below ~50 km depth, and in
the sub-slab mantle. Power-law viscosity parameters are successfully retrieved
for all three domains. The trade-off between the power-law activation energy
and water fugacity hinders their individual estimation. The wedge viscosity is>1019 Pa·s during the interseismic phase. Postseismic afterslip and bulk viscoelastic relaxation can be individually resolved from the surface deformation
data. Afterslip is substantial between 40-50 km depth and extends to 80 km
depth. Bulk viscoelastic relaxation in the wedge concentrates above 150 km
depth with viscosities <1018 Pa·s. Landward motion of the near-trench region
occurs during the early postseismic period without the need for a separate
low-viscosity channel below the slab.
Surveying Active Fault Zones in California Using Quakes-I
Wide-Swath Airborne Stereoimagery
ZINKE, R., Jet Propulsion Laboratory, California Institute of Technology,
California, USA, robert.zinke@jpl.nasa.gov; DONNELLAN, A., Jet
Propulsion Laboratory, California Institute of Technology, California, USA,
andrea.donnellan@jpl.nasa.gov; APPLEGATE, R., Jet Propulsion Laboratory,
California Institute of Technology, California, USA, ryan.t.applegate@jpl.
nasa.gov; PADGETT, C., Jet Propulsion Laboratory, California Institute ofTechnology, California, USA, curtis.w.padgett@jpl.nasa.gov
We present new and continuing results from fault surveys collected by the
QUAKES-I airborne stereoimager. Recent decades have seen a proliferation ofstereoimaging techniques for mapping fault zone structure, measuring offset
geomorphic features, and characterizing earthquake dynamics by correlating
images collected before and after surface ruptures. Despite the merits of suchstudies, stereoimaging surveys are often expensive, logistically difficult, and/or time-consuming to carry out. For example, stereoimaging is often accomplished at fine scales (kilometers or less) by drone surveys, or at broad scales

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Seismological Research Lettersthrough purchase of high-resolution satellite imagery. Additionally, airborne
lidar surveys can be flown to cover > 100-km-long ruptures, but are often confined to a narrow (~1 km) swath width due to limitations of the scanner, andmay consequently miss distributed deformation. In contrast, the Quantifying
Uncertainty and Kinematics in Earth Systems Imager (QUAKES-I) presents
an instrument for capturing high-resolution (~1 m pixel) imagery over a wideswath (up to ~12 km) aboard a taskable aircraft that can cover a few thousand
km of fault length in a single day. Using commercial photogrammetric software, the stereoimages can be converted to a 3D point cloud, a color orthomosaic, and a digital surface model (DSM). In some cases (e.g., sparse vegetation), the point cloud can be reliably classified and a digital terrain model(DTM) can be produced. The results presented here showcase examples fromsurveys of > 1,500 km of active fault traces in CA and the western U.S., collected in June 2021 and October 2022. Faults and fault systems surveyed
include the San Andreas fault, the Hayward-Calaveras fault system, and partsof the eastern California shear zone. Using these image products, we map primary and subsidiary fault features, and displaced geomorphic markers. These
images further constitute a “before” data set for comparison following potential future large earthquakes.
Improvements to Fault Displacement Models: Examples
From the 2023 M7.8 Pazarcık, Türkiye Earthquake
MASON, H. B., U.S. Geological Survey, Colorado, USA, hmason@usgs.gov;
LAVRENTIADIS, G., California Institute of Technology, California, USA,glavrent@caltech.edu; ASIMAKI, D., California Institute of Technology,
California, USA, domniki@caltech.edu; HATEM, A. E., U.S. Geological
Survey, Colorado, USA, ahatem@usgs.gov; DUROSS, C. B., U.S. Geological
Survey, Colorado, USA, cduross@usgs.gov; REITMAN, N. G., U.S. Geological
Survey, Colorado, USA, nreitman@usgs.gov; MILLINER, C., California
Institute of Technology, California, USA, milliner@caltech.edu; KARAKAŞ,M., Istanbul Technical University, Istanbul, Turkey, karakas17@itu.edu.tr;SEÇEN, B., Hacettepe University, Ankara, Turkey, bahadir.secen@hacettepe.
edu.trFault displacement models are used to predict fault surface rupture along
strike as a function of earthquake magnitude. They are useful for numerous
reasons, including, for instance, forecasting the displacement of an underground pipeline crossing a fault during a future earthquake scenario (i.e., adeterministic analysis). In addition, they are the backbone of probabilistic
fault hazard displacement analyses, and thus, are important for advancing
seismic design guidelines. Improving fault displacement model accuracy andprecision requires collecting field data, and in particular, making high-quality fault displacement measurements with robust estimates of measurement
uncertainty. With the foregoing motivation, we traveled to south Türkiye tocomplete ten days of fieldwork in June 2023 following the 6 February 2023
M7.8 Pazarcık Earthquake. In the field, wemeasured fault displacement andestimated uncertainty using traditional surveying techniques, GNSS, and terrestrial lidar scans. We also chose sites with varying quality of offset featurereconstructions to investigate the effect of quality on measurement uncertainty. Our fault displacement measurements led to numerous observations
for how to improve fault displacement models. Our fieldwork highlighted theadvantages and disadvantages of the measurement techniques as a functionof piercing point definition. In particular, we determined some post-earthquake reconnaissance best practices for balancing the need to capture as manyhigh-quality fault displacement measurements as possible with the correlativeneed to develop robust measurement uncertainty estimates. We compare ourresults to previous fault displacement models and make observations about
magnitude scaling, the effects of geologic conditions, and faulting complexity.
The results from our work have implications for improving post-earthquake
reconnaissance practices and have produced data that can be used by futurefault displacement modelers.
Characterizing Surface Fault Displacement Uncertainty and
Its Effects on Probabilistic Fault Displacement Hazard.
Example From the 2023 M7.8 Pazarcık, Türkiye Earthquake
LAVRENTIADIS, G., California Institute of Technology, California, USA,glavrent@caltech.edu; MASON, H. B., U.S. Geological Survey, Colorado,
USA, hmason@usgs.gov; ASIMAKI, D., California Institute of Technology,
California, USA, domniki@caltech.edu; HATEM, A. E., U.S. Geological
Survey, California, USA, ahatem@usgs.gov; DUROSS, C. B., U.S. Geological
Survey, Colorado, USA, cduross@usgs.gov; REITMAN, N. G., U.S. Geological
Survey, Colorado, USA, nreitman@usgs.gov; MILLINER, C., California
Institute of Technology, California, USA, milliner@caltech.edu; KARAKAŞ,M., Istanbul Technical University, Istanbul, Turkey, karakas17@itu.edu.tr;

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April 2024SEÇEN, B., Hacettepe University, Ankara, Turkey, bahadir.secen@hacettepe.
edu.tr
Surface fault displacement poses a significant threat to distributed infrastructure systems, and as such, they need to withstand long return period events.
Thus, properly characterizing the upper percentiles of the fault displacement
distribution has a large impact on the design requirements. Using the 2023
M7.8 Pazarcık earthquake as an example, we developed an open-source software to characterize the measurement uncertainty in surface fault displacement of Global navigation satellite system (GNSS) fault-perpendicular profiles of offset features and rank the contribution of each component. For every
iteration, both sides of the surveyed feature are extended into the rupture zone
based on a principal component projection, and the displacement is measured
parallel to the strike of the rupture. Considered components of uncertainty
include: (1) location error in the horizontal and vertical direction, (2) rupture
location uncertainty, (3) rupture azimuth uncertainty, and (4) interpretation
uncertainty on which survey points are used to project the feature into thefault zone. We compared the distribution of estimated displacements against
field-based methods and evaluated the impact of displacement uncertainty
in the development of fault displacement models (FDMs). Ongoing analyses
indicate that field-based displacement values are generally in agreement withthe mean of the modeled displacement distributions and that reported minimum and maximum displacements correspond to the modeled 2nd and 98th
percentiles. To quantify the impact of displacement uncertainty on FDMs, weorganized the collected profiles into good, mediocre, and poor quality, estimated the uncertainty for each class, and generated synthetic datasets basedon the previous rules. Regressing FDMs with and without considering theuncertainty of displacements showed that omitting the uncertainty of displacement during the regression process inflates the aleatory variability, which
overestimates design values at large return periods.
Relating Large-Volume Landslides and Potentially Active
Faults Using Geotechnical Analyses in the Pocuro Fault
System, Central Andes (32°-33°s)
SEPÚLVEDA, S. A., Simon Fraser University, Burnaby, Canada, ssepulve@
sfu.ca; URREJOLA-SANHUEZA, J. T., Universidad de Chile, Santiago, Chile,jose.tomas.urrejola@gmail.com; PINTO, L., Universidad de Chile, Santiago,
Chile, lpinto@uchile.cl; MOREIRAS, S. M., National Council for Scientificand Technical Research, Mendoza, Argentina, moreiras@mendoza-conicet.
gob.arLarge-volume landslide deposits are frequent in seismically active mountainregions, such as the central Andes. Their clustered geographic distribution
close to tectonically active fault systems suggests that their most likely trigger
are shallow crustal earthquakes from nearby faults . We investigate landslides
along the Pocuro Fault System (PFS) in the Chilean Andes (32°-33°S), using amethod developed in the Argentinean central Andes to link large rock slides
with potentially active faults by applying geological and geotechnical earthquake engineering tools, including numerical modelling back-analyses andapplication of ground motion models. Recent studies of the PFS have foundthat at least one major branch has Quaternary activity. We thus hypothesizethat other faults of the system may be potentially active. A landslide inventory was updated for the region, obtaining morphometric parameters of thelandslides. Detailed field and lab geotechnical assessments including testing of
selected rock slides were performed to be used as models of a representative
number of slides that were analysed using 2D seismic slope stability backanalyses. Given the lack of historic ground motion records, seismic records
from abroad considering similar source mechanisms and earthquake parameters were selected to run the analyses. Then, the landslides found to be likely
seismically triggered were related to nearby faults of the PFS, identifying thosefaults more probable to have induced the landslides and an earthquake magnitude range consistent with both the fault geometry and the slopes destabilization. Further research will look to combine these results from geo-engineering
analyses with pending geochronological studies of the landslides and faults.
This would provide useful information on the frequency and magnitude ofancient, large shallow crustal earthquakes, aiding the characterization ofseismic hazard in a region where the contribution of shallow seismicity toseismic hazard has not been accounted for to date. This work is funded by
ANID-Fondecyt 1200871 grant (L. Pinto) and the FRBC Endowment Fund(S. Sepúlveda).
Measuring Gaps Between Geodetic, Geologic, and Seismic
Moment Rates Across the Western U.S.: How to Determine
a Budget for Earthquake Rates?
HATEM, A. E., U.S. Geological Survey, Colorado, USA, ahatem@usgs.gov;
BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.gov;

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POLLITZ, F., U.S. Geological Survey, Washington, USA, fpollitz@usgs.gov;
REITMAN, N., U.S. Geological Survey, Colorado, USA, nreitman@usgs.gov;
TAN, M., U.S. Geological Survey, Colorado, USA, mtan@usgs.gov
Updated geodetic, geologic, and seismic datasets compiled for the 2023 U.S.
National Seismic Hazard Model (NSHM23) provide new views of moment
rates across the western U.S. We use these updated datasets to assess regional
estimates of off-fault deformation by asking: is geodetic moment completely
resolved by earthquakes? There is a long-held assumption that better characterization of fault networks will yield better agreement between geodetic
and geologic moment rates. We find that this is not the case because newly
added faults tend to be short and have low slip rates. Using updated datasets,
this discrepancy appears persistent and not significantly reducible by adding
faults, incorporating geologic slip rate uncertainty, or increasing fault plane
area. Furthermore, the gap cannot be closed with seismicity moment rates
alone. Rather, such a difference is emblematic of volumetric crustal strain, andis therefore only partially associated with diffuse deformation around faults,
typically termed “off-fault deformation.” When we consider smaller areas for
moment rate comparisons using a grid approach rather than broad tectonic
regions, the gap between geodetic and geologic moment rates decreases as
the influence of volumetric processes (i.e., distant off-fault deformation) is
minimized. Some volumetric processes that may contribute to this quantity
may include volcanic activity, hydrologic changes, rotations at the boundaries
of fault systems, folding, post-seismic transients, interseismic locking on the
Cascadia megathrust, shallow and deep creep on crustal faults, lower crustal
flow, mid-crustal detachments, and some spatially variable combination of
the above. These processes are not the same as diffuse deformation associatedwith a particular fault zone (e.g., hanging wall deformation and distributed
cracking). Before geodetic off-fault deformation is incorporated into seismic
hazard analyses or physics-based rupture simulations, we must understand
if and how these broad-scale processes contribute to the earthquake engine.

Learning Across Geological, Geophysical & Model-Derived
Observations to Constrain Earthquake Behavior [Poster
Session]Poster Session • Wednesday 1 May
Conveners: Kimberly Blisniuk, San José State University(kimberly.blisniuk@sjsu.edu); Roland Bürgmann, R.,
University of California, Berkeley (burgmann@berkeley.
edu); Elizabeth Madden, San José State University (elizabeth.
madden@sjsu.edu)
poster 173
Rupture Geometry and Static Stress Changes of the 2022
Mw 7.0 and Mw 6.4 Earthquakes in Abra, Philippines
CATUGAS, S. A., University of the Philippines Diliman, Quezon City,
Philippines, sacatugas1@up.edu.ph; AURELIO, M. A., University of thePhilippines Diliman, Quezon City, Philippines, maurelio@nigs.upd.edu.
ph; DIANALA, J. B., University of the Philippines Diliman, Quezon City,
Philippines, jddianala@nigs.upd.edu.phIn the second half of 2022, the province of Abra in the island of Luzon,
Northern Philippines was struck by two large magnitude earthquakes in a spanof less than three months and within a 20- kilometer radius. On July 27, 2022,
at 8:43 am (Philippine Standard Time), the area was struck by a magnitude
Mw 7.0 earthquake that caused intense ground shaking. The epicenter was
located at 17.64° N latitude, 120.63° E longitude, at a focal depth of 15 km. On
October 25, 2022, at 10:59 p.m. (PST), a magnitude Mw 6.4 earthquake struck
the same area, at an epicenter located only about 18 kilometers northeast of
the July earthquake epicenter, at the same focal depth of 15 km. Destruction
in both earthquakes included collapsed residential and commercial buildings,
structural damage in century-old heritage churches, government buildings,
bridges, and roads. Ground deformation included numerous landslides in themountainous regions, and liquefaction in riverbeds and coastal areas. While
infrastructure damage was significant, surface ground rupture was not evident after both earthquakes. The epicentral areas are known to be prone toearthquakes due to the presence of the Philippine Fault System (PFS) there.
However, the focal mechanism solutions of the main shocks suggest gently
dipping fault planes which are not consistent with the known geometry of
the PFS and its branches in the area. Instead, the distribution of the aftershocks, nodal plane geometries, Coulomb Stress Transfer (CST) modeling andSeismological Research Letters

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analysis by radar interferometry suggest that the earthquake-generating faults
project surface ruptures located further west, following the location and trendof other PFS fault branches. These temporally and spatially closely spaced Julyand October earthquakes pose new questions on the current knowledge about
the PFS in northern Luzon, but also provide new insights that contributein understanding the nature and earthquake behavior of complex fault systems, including fault asperities, post-earthquake stress transfer, seismic ratechanges, aftershock evolution and earthquake triggering.

carried out as specified by the user in input parameters. The user must analyze
and choose one or more combinations that suit the tectonic conditions of theregion. Once done, the program allows graphing the MFD of all selected solutions and generates source parameters for seismic hazard calculations [e.g.,
beta (β), b-value, a-value, cumulative seismic rate (N(m))]. Two application
cases are presented: one in the southeast of Spain with slow fault systems andanother in Guatemala where faults are fast due to the interaction of the North
American and Caribbean plates.

poster 174
Investigating Early Earthquake Rupture Characteristics
With Borehole Strainmeters
DYBING, S. N., University of Oregon, Oregon, USA, sydneydybing@gmail.
com; MELGAR, D., University of Oregon, Oregon, USA, dmelgarm@uoregon.
edu; BARBOUR, A. J., U.S. Geological Survey, California, USA, abarbour@
usgs.gov; CANITANO, A., Academia Sinica, Taipei, Taiwan, canitano@earth.
sinica.edu.tw; GOLDBERG, D. E., U.S. Geological Survey, Colorado, USA,degoldberg@usgs.gov

poster 176
A New View on Interseismic Locking of the Hikurangi
Megathrust Along the North Island of New Zealand
GOVERS, R., Utrecht University, Utrecht, Netherlands, r.govers@uu.nl;
BIJLSMA, E., Utrecht University, Utrecht, Netherlands, e.m.bijlsma@uu.nl;
VOS, S., Utrecht University, Utrecht, Netherlands, s.vos@uu.nl

Recent studies have suggested the existence of weak determinism in theearthquake rupture process—the concept that the final magnitude of a large
earthquake can be estimated using data early on after earthquake origination,
before the rupture process is complete across the fault. It is hypothesized that
ruptures begin as disorganized, accelerating cracks, and then transition toa more organized slip pulse propagating out from the hypocenter, with theproperties of this slip pulse correlating to the final magnitude of the earthquake. As these properties can be ascertained from features of early seismic
wave arrivals on displacement recordings, applications of this knowledge
have the potential to improve the timeliness and accuracy of earthquake early
warning. However, traditional measurement techniques can be problematicwhen analyzing for determinism due to magnitude saturation in seismic dataand high noise in geodetic data, which obscures P-wave arrivals. We explore a
new method of analyzing the early rupture process using borehole strain sensors instead; as these instruments can record both small and large perturbations in strain, we can both observe the P-wave arrivals and avoid saturation at
higher magnitudes. We began with a homogeneous slip model, where slip proceeds from the hypocenter in a uniform ring with a set rupture velocity of 2.8
km/s, as in Goldberg et al. (2018). We modeled earthquakes with magnitudes
ranging from M6.5-8.5 by setting average rise times for each event according
to the scaling relation described in Melgar and Hayes (2017). We then used
the SW4 wave propagation modeling code to forward-model strain observations and found that generally within 5-10 seconds of data arriving at eachstation, earthquakes were distinguishable by magnitude. Next, we examined
real earthquake horizontal-component borehole strainmeter data from events>M5 in the 2019 Ridgecrest Sequence. In analyzing the earliest-arriving data
(less than ~20s after the P-wave arrival), we observed that there are different
regimes of growth over time, potentially indicative of different rupture modes.
poster 175
Hybrid Model: A Tool for Combining Fault and Area
Sources in Seismic Hazard Assessment
GAMBOA-CANTÉ, C., Universidad Politécnica de Madrid, Madrid, Spain,
carlosjose.gamboa@alumnos.upm.es; RIVAS-MEDINA, A., Universidad
Politécnica de Madrid, Madrid, Spain, alicia.rivas@upm.es; ORNELASAGRELA, A., Universidad Politécnica de Madrid, Madrid, Spain, af.ornelas@alumnos.upm.es; BENITO, B., Universidad Politécnica de Madrid, Madrid,
Spain, mariabelen.benito@upm.es
We present an update to the methodology proposed by Rivas-Medinas et al.
(2018) for combining fault and zone sources in seismic hazard calculations.
Initially, the method distributed the seismic potential of the region between
the zone and faults based on observed seismicity (seismic catalog) within arange of minimum magnitude (Mmin) to maximum completeness magnitude(MMC). The expert had to predefine MMC and the maximum magnitude forthe zone (Mmax zone), significantly influencing the method’s solution for distribution. This made the method applicable only to faults with low slip rates(slow faults), as high slip-rate faults (fast faults) led to inconsistent results. To
solve this, the hybrid method has been enhanced through an iterative process,aiming to assist the expert in reducing decision-making in key parameters forseismic source characterization (e.g., MMC magnitude, Mmax zone magnitude,
fault b-value, zone b-value).
For this purpose, a tool has been developed using R-studio and Python
programming languages, featuring a user-friendly interface for ease of use andcomprehension. As a result, a set of possible solutions is provided, displaying different combinations in which the magnitude-frequency distribution(MFD) model can be adopted to maintain system balance, and distribution is

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The largest earthquakes in subduction zones occur where significant interseismic slip deficit has accumulated on the plate interface. Slip deficit accumulates
most quickly in mechanically locked regions, and these also cause the regions
around them to accumulate slip deficit; therefore, large earthquakes are typically expected to rupture in and around locked areas. Resolving the locations
and dimensions of these mechanically locked zones from kinematic geodesy(leveling, GNSS and/or InSAR time series) has been difficult, particularly
when the overriding plate is subject to multiple drivers of active deformation
at significant rates, like the Pacific Northwest and Alaska.
We focus on the North Island of New Zealand, where GNSS velocities
show the superposition of locking of the Hikurangi megathrust and backarc
extension in the Taupo system. To be able to use both horizontal and vertical time series data we develop a mechanical model with the 3D geometryof the Hikurangi slab from Slab2 (Hayes et al., 2018). The slab and shallow
overriding plate are taken to be elastic, and the mantle wedge and sub-slab
asthenosphere have linear viscoelastic properties. We discuss the relevanceof including major trench-parallel faults that bound forearc blocks, like the
Wairarapa fault. We show results of assuming the megathrust locking patternfound in previous studies, and the corresponding backarc extension imprint
on the North Island. We discuss how prior information may help improve thereliability of locking estimates, and Bayesian inference methods that aim toconstrain the uncertainties of future megathrust locking estimates.
poster 177
Geological Constraints on the Seismic Activity of the
Mid-section of the Minjiang Fault in the Eastern Margin of
the Tibet Plateau
HAN, Z., China Earthquake Administration, Beijing, China, zjhan0904@163.
com; GUO, P., China Earthquake Administration, Beijing, China,
guopengpoli@163.com; ZHOU, C., China Earthquake Administration,
Beijing, China, imzhouchao@126.com; NIU, P., China Earthquake
Administration, Beijing, China, niupengfei0814@163.com; LI, J., China
Earthquake Administration, Beijing, China, imzhouchao@126.com
The Minjiang Fault, located in the western boundary of the Minshan active
block, is situated above a large-scale, east-dipping electrical structure boundary zone. The upward flow of the Songpan-Ganzi lower-crust low-resistivity
layer beneath the Minshan active block provides an important driving force forthe frequent large earthquakes along the Minjiang Fault. In this study, we constrained the seismic activity of the mid-section of the Minjiang Fault througha detailed analysis of three paleoseismic trenches and the dating of samples.
Our study found that at the Gusicun section, the occurrence ages of three
paleoearthquake events (EG3, EG2, and EG1) are estimated to be 10827-4034
aBP, 3907-2023 aBP, and 1945-685 aBP, respectively. At the Lajichang section,
the occurrence ages of the EL3, EL2, and EL1 events are 6159-5820 aBP, 39042305 aBP, and 2139-300 aBP, respectively. In addition, the Luoshigou trench’s
most recent event (ES1) occurred in 3258-1171 aBP. By using the incremental
dating method, the ages of the three paleoearthquake events (E3, E2, and E1)along the fault are estimated to be 6158-5829 aBP, 3283-2292 aBP, and 19801130 aBP, respectively. The elapsed time since the most recent event is estimated to be 2021-1201 aBP. Using the OxCal software, the average earthquake
recurrence period of the fault is estimated to be 2218±262 years (μ±2σ), witha variation coefficient of 0.64.
According to the study, no fresh surface/near-surface rupture corresponding to the Diexi earthquake was found in the mid-section of the
Minjiang Fault, and the dating results of the most recent earthquake event do
not match the Diexi earthquake. Therefore, the Diexi earthquake is not closely
related to the mid-section of the Minjiang Fault. Due to the recent occurrenceof a major earthquake close to the recurrence interval, combined with the seis-www.srl-online.org•

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mic activity characteristics around the Minshan active block, it is necessary to
pay attention to the future seismic hazard of the Minjiang Fault.
poster 178
Seismic Structure, Lithospheric Deformation andSeismicity of the Indian Plate in Sikkim Himalaya
SINGH, A., Indian Institute of Technology Kharagpur, Kolkata, India, arun@
gg.iitkgp.ac.in; UTHAMAN, M., Indian Institute of Technology Kharagpur,
Kolkata, India, mitutm710@iitkgp.ac.in; JANA, N., Indian Institute ofTechnology Dhanbad, Dhanbad, India, niptikaj@iitism.ac.in
Seismic structure, lithospheric deformation and seismogenic capacity of
the Indian plate in Sikkim Himalaya is poorly understood amidst the wellexplored regions of Bhutan, Nepal and Tibet. Study of this region is key tounderstanding the evolutionary past, on-going collisional dynamics and its
implication on future seismic hazard potential. A well thought seismic experiment was planned in 2019 with the installation of 27 broadband seismic stations covering Sikkim Himalaya. The network was operational till May, 2023.
Precious data gathered from this project have been crucial in providing highresolution crustal images using 12,288 receiver functions, robust earthquake
catalouge of 1,496 earthquakes, and patterns of mantle deformation. The
observations reveal an intermittent contrast in amplitudes related to Main
Himalayan Thrust, contrary to prominent and continuous arrivals from thisboundary from Nepal Himalaya. Prominent seismicity clusters in the upper
crust follow this layer and are marked by the presence of low velocity zones.
The seismic activity indicates active shearing along Main Himalayan Thrust in
response to collision. Lower crust is observed to possess an imbricated Moho
possibly resulting due to accumulation from crustal shortening, which is corroborated with seismicity exhibiting thrusting mechanism. The convergencein this segment of Himalaya can be thus stated to be partially accommodated
by imbricate structures in the upper and lower crust. Sandwiched between
upper and lower crust is the dextrally deforming mid-crustal DhubriChungthang Fault Zone postulated to be segmenting the Himalayan arc.
Seismicity studies delineate the northward discontinuation of the seismogenic
extent of this fault beyond Chungthang in Sikkim. Distinct deformation isobserved across Dhubri-Chungthang Fault Zone by the fast-axis orientations
determined from core-refracted shear waves. Complex dynamics coupledwith intricate geometry of the faults pose an intermediate risk of occurrenceof a great earthquake in Sikkim Himalaya raising the cause of concern of seismic hazard potential in the region.
poster 179
Earthquake Rate Modelling Tools to Explore Uncertainties
in Fault Source Parameters The Case of the Alboran Sea
PEREA, H., Institut de Ciencies del Mar, Barcelona, Spain, hperea@icm.csic.es;GÓMEZ-NOVELL, O., Universidad Complutense de Madrid, Madrid, Spain,
octgomez@ub.edu; JIMÉNEZ, M., Museo Nadional de Ciencias Naturales,
Madrid, Spain, mjjimenez@mncn.csic.es; GARCÍA, M., Museo Nadionalde Ciencias Naturales, Madrid, Spain, mgarcia@mncn.csic.es; LOZANO,L., Instituto Geográfico Nacional, Madrid, Spain, lllopezdemedrano@
mitma.es; GARCÍA-MAYORDOMO, J., Instituto Geológico y Minero deEspaña, Madrid, Spain, julian.garcia@igme.es; SÁNCHEZ-ROLDÁN, J.,
Universidad Complutense de Madrid, Madrid, Spain, jl.sanchez.roldan@ucm.
es; CANARI, A., Institut de Ciencies del Mar, Barcelona, Spain, acanari@icm.
csic.es; MARTÍNEZ-LORIENTE, S., Institut de Ciencies del Mar, Barcelona,
Spain, smartinez@icm.csic.es
The Alboran Sea accommodates part of the current NW-SE convergence
between the African and Eurasian plates (4-5 mm/yr). Despite it is considered as a relatively low tectonic deformation region with diffuse seismicity,large earthquakes (IEMS>IX) have occurred since historical times. One of themain issues for the characterization of the seismic hazard in the Alboran Sea,
common to many low-deformation regions, lies in accurately constraining
the seismic parameters that define fault activity and their behavior (i.e., slip
rates, recurrence or multi-fault rupture capability). This issue is further aggravated by the fact that these faults are mostly located offshore, making theirinvestigation more challenging. As a result, most faults in the Alboran Sea
have poor slip and activity rate estimates, while their capability to interact andrupture in complex rupture patterns has not been explored yet. In this study,
we compute several models of earthquake rupture rates for the Alboran Sea
with the SHERIFS code and using a systematic parameter exploration tree
to determine the parameters of each model. We base the exploration tree on
the slip rate and multi-fault rupture scenarios, allowing us to investigate theepistemic uncertainty linked to these parameters. To check the feasibility of
the computed earthquake rates of each model, we compare them with theobserved seismicity rates in the region. As a result, this enables us to identify

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which parameter combinations best match the recorded seismicity, prioritizing those that perform better for the hazard assessment. In addition, these
optimal values might be used as indicators for further studies focused on better constraining the fault parameters, as well as for preliminary fault-based
seismic hazard assessments. By extension, the limitations of the modellingin terms of slip rate budget distribution and fault rupture scenarios can also
be used to determine which areas should be prioritized for further research.
We expect that the results of our work enhance discussion among researchers
working in the area and motivate further investigations into fault dynamics.
poster 180
Mapping Finite-Fault Slip in 3D From Spatial Correlation
Between Seismicity and Point-Source Coulomb Stress
ChangeLOMAX, A., ALomax Scientific, Mouans Sartoux, France, anthony@alomax.
net
The main fault slip and energy release of earthquakes occurs many kilometers below the Earth’s surface at seismogenic depth. Complete understandingof large earthquakes requires mapping the orientation, extent and amount of
this fault slip. Such finite-fault slip maps are typically obtained from inversion of measured or inferred surface phenomena, such as fault offsets, shaking
intensity, and time-varying or differential ground motion from seismograms,
GNSS or InSAR. Here we introduce and illustrate a procedure for mapping
finite-fault slip directly from seismicity and aftershocks—phenomena occurring at seismogenic depth around an earthquake rupture. For specified source
and receiver faults, we construct 3D maps of source-fault slip by correlationof point-source Coulomb failure stress change (ΔCFS) kernels across the spatial distribution of seismicity around an earthquake. This procedure finds forpoints in 3D space what fault slip best explains, through ΔCFS, the surrounding distribution of seismicity. These seismicity-stress maps show potential, relative, finite-fault slip; they can also be used directly for quasi data-driven aftershock forecasting, and as prior constraint for other slip inversion methods.
We confirm that the seismicity-stress procedure recovers the location ofa synthetic point-source given random seismicity predicted by ΔCFS for the
point-source. We next show slip maps from this procedure for the ParkfieldCA area that match well other estimates of co- and post-seismic slip for the2004 M6 Parkfield earthquake, and of nearby, long-term slip related to fast
creep. We further confirm agreement between co- and post-seismic slip
obtained by this procedure and by other methods for the 2021 M6 Antelope
Valley CA normal-faulting earthquake. Finally, we show for the 2018 M7.1
Anchorage AK intra-slab earthquake how the seismicity-stress procedure,
combined with multi-scale precise hypocenter relocation, can resolve theenigma of which mainshock faulting plane ruptured (the shallow, east-dipping plane), and clarify what structures in the slab were activated in the energetic aftershock sequence.
poster 181
Microseismicity and Fault Structure in the Daliangshan
Subblock Within the Southeastern Tibetan Plateau
MA, J., Chinese Academy of Sciences, Beijing, China, majinzhi21@mails.ucas.
ac.cn; XIAO, Z., Chinese Academy of Sciences, Beijing, China, xiaozhuowei@
mail.iggcas.ac.cn; LI, L., Chinese Academy of Sciences, Beijing, China,
cuglilong@163.com; AI, Y., Chinese Academy of Sciences, Beijing, China,
ysai@mail.iggcas.ac.cn
The Daliangshan subblock is located between the Tibetan Plateau and theSouth China block, characterized by intense tectonic deformation and complex fault structures. In this study, we analyze more than two years of continuous seismic records recorded by a recently deployed dense seismic array from
December 2018 to April 2021. We used a recently developed machine learning-based earthquake location workflow (ESPRH) to construct a high-precision earthquake catalog for the region and obtained ~3000 earthquakes. Then,
we mapped our final seismic location results to an existing S-wave velocity
structure obtained through ambient seismic noise tomography. The seismicity
distribution not only confirms the nature of the faults marked on the map but
also delineates the detailed geometry of the unmapped faults. Earthquakes
mainly occur at the boundaries of high- and low-velocity bodies or on highvelocity bodies, which is consistent with the tomography result. Combining
the focal mechanism solution of historical earthquakes and the fault geometryof this paper, we also observed that the western side of the Daliangshan blockis dominated by strike-slip faults, and the fault properties on the eastern side
are complex. This tectonic phenomenon is attributed to the fact that during
the lateral extrusion of the southeastern edge of the Chuandian fragments,
the northeastern part of the Daliangshan subblock was squeezed by the South
China block more strongly than its southwestern part was.

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poster 182
Mapping Outerrise Normal (and other) Dip-slip Fault
Parameters using Semi-automated and Newly Developed
Python Toolbox
NIELSON, Q., Georgia Institute of Technology, Georgia, USA, qnielson17@
gatech.edu; LOSASSO, E., Georgia Institute of Technology, Georgia, USA,elosasso3@gatech.edu; NEWMAN, A., Georgia Institute of Technology,
Georgia, USA, anewman@gatech.edu
Previous studies report that there is a connection between the propagationof tsunamis and outer-rise normal fault characteristics in deep sea trench
regions. However, the true seismic and tsunami potential of these faults arepoorly understood, as their driving forces are controlled more from plate
bending forces than tectonic rates. Such is the example along the Puerto Ricotrench, where bathymetry reveals large normal faults outward of the trench,and its risk to nearby populations is not yet quantified. To help quantify theseismogenic and tsunami potential here, we created a set of tools to semiautomatically determine basic fault properties from topographic relief. We
use bathymetric data compiled in the Global Multi-Resolution Topography(GMRT) synthesis. The data is presented as shaded relief within a Python figure that the operator visually inspects for suspected faults, selecting either anumber of points or endpoints defining the raised footwall along one sideof the fault. From here, transects are automatically determined orthogonal to these points, and the elevation, gradients, and extent of curvature are
extracted. These are used to determine breaks in slope along the scarp associated with lower-bounds on fault offset, as well as extrapolated points toaccount for erosion and deposition along the scarp crown and toe, estimating
the original, uneroded fault traces along the same transects. From these profiles, we then calculated the median and distribution of dip and offset values,for evaluation of the magnitude and robustness of individual fault profiles.
With the compiled and cataloged dataset of significant outerrise faults, we
can incorporate convergence rates to determine the total slip rate across thesefaults, putting an upper-bound on the earthquake and tsunami potential ofthese faults. Given the generalizable nature of this tool, we next plan to apply
it to outerrise behaviors at other subduction zone environments.
poster 183
Diatom Evidence of Tsunami Inundation Extent Following
the Great Ca. 1700 Ce Earthquake(s) at the Salmon River
Estuary, Oregon, USA
PRIDDY, M., Virginia Tech, Virginia, USA, mspriddy@vt.edu; DURA, T.,
Virginia Tech, Virginia, USA, tinadura@vt.edu; HAWKES, A., Universityof North Carolina Wilmington, North Carolina, USA, hawkesa@uncw.edu;
KELSEY, H., California State Polytechnic University, Humboldt, California,
USA, hmk1@humboldt.edu; LA SELLE, S., U.S. Geological Survey, California,
USA, slaselle@usgs.gov; WITTER, R., U.S. Geological Survey, Alaska, USA,rwitter@usgs.gov
Although the Cascadia Subduction Zone (CSZ) has not experienced a great(>Mw 8) megathrust earthquake in more than 300 years, coastal marshes along
the CSZ preserve widespread stratigraphic evidence from the most recent
great earthquake, or series of earthquakes, circa (ca.) 1700 CE. At the Salmon
River estuary, stratigraphic evidence of earthquake subsidence and tsunami
inundation ca. 1700 is preserved as intertidal wetland soils sharply cappedby sand overlain by intertidal silt. The inland extent of sandy deposits above
buried wetland soils has been used as a minimum inundation constraint intsunami modeling. However, observations of modern tsunamis have demonstrated that the true inundation extent can exceed the inland limit of sandy
sediment deposition by 50% or more in extensive, relatively flat, coastal plains,while mud-sized tsunami sediments can be deposited up to the full extent
of inundation. Because sediment availability, site morphology, and deposit
preservation contribute to the variability in tsunami deposit thickness, highresolution tsunami deposit mapping is necessary to accurately estimate theinundation extents of prehistoric tsunamis. Through careful analyses of fossil
diatoms, grain size, and computed tomography (CT) scans, we search for evidence of tsunami inundation in the fine-grained sediment above earthquake
subsidence contacts in cores beyond the previously mapped inland extent oftsunami-deposited sand from the ca. 1700 CE rupture at the Salmon Riverestuary. Preliminary results show the diatom assemblage observed within the
sandy portion of the mapped tsunami deposit are also found in silty sediments above the ca. 1700 CE earthquake subsidence contact at sites beyond
the mapped inland extent of sandy tsunami deposits. Fragmentation of diatoms is consistent with transport in a tsunami both in sandy and silty tsunami
sediments. Delineating the full extent of tsunami inundation along the CSZ
provides more accurate constraints for tsunami and earthquake source mod-

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poster 184
Moment Tensor Analysis for Earthquakes in Armenia
SAHAKYAN, E., Institute of Geological Sciences of the Republic of Armenia,
Yerevan, Armenia, elya.sahakyan@gmail.com; BABAYAN, G., Instituteof Geological Sciences of the Republic of Armenia, Yerevan, Armenia,
gevorgbabayanevn@gmail.com; SARGSYAN, L., Institute of Geological
Sciences of the Republic of Armenia, Yerevan, Armenia, s.sargsyan.lilit@gmail.
com; GEVORGYAN, M., Institute of Geological Sciences of the Republic of
Armenia, Yerevan, Armenia, gevmikayel@gmail.com; NABELEK, J., Oregon
State University, Oregon, USA, john.nabelek@oregonstate.edu
The Republic of Armenia and the neighboring areas are located in the central
part of the Arabia-Eurasia collision zone, characterized by active seismicity.
Moment tensor analysis (MTA) was carried out for the earthquakes (M>=3.0)
that occurred in the territory of Armenia from 2017 to 2021. The data for thisanalysis were collected from a temporary broadband regional network, part ofthe project Collaborative Research: The Uplift and Seismic Structure (CNET).
The inversion for the moment tensor, centroid depth, and source time function involves modeling the entire 3-component seismograms (Nabelek and
Xia, 1995). For each earthquake, seismograms were band-pass filtered toenhance the signal. Earthquakes of magnitude 3.0 and greater were wellrecorded by many stations, resulting in well-resolved estimated parameters.
Most events suitable for the moment-tensor analysis occurred in Javakheti
and northwest Armenia regions and are right-lateral strike-slip, with twooutliers, normal fault and thrust fault. A right-lateral strike-slip event near
Vanadzor is consistent with the slip on the Pambak-Sevan fault. The most significant event (Mw=4.7) near Yerevan has a mixed strike-slip-thrust mechanism with a west-oriented tension axis. For this event was also calculated focal
mechanism solution using P-wave first motion method, which shows that this2021 M4.9 earthquake is characterized by a thrust fault mechanism with astrike-slip component (Sargsyan L., et al. 2022). The discussion of historicalseismicity that has occurred over the course of a century in direct proximity to Yerevan, demonstrates that the Yerevan Fault and Parakar sub-fault areseismically active systems. The problem of possible NW and SE extensions of
the Yerevan fault was addressed.
poster 185
Preliminary Constraints on Quaternary Fault Activity in the
Malawi Rift from New High-resolution Bathymetry andSeismic Data
SHILLINGTON, D. J., Northern Arizona University, Arizona, USA, donna.
shillington@nau.edu; SCHOLZ, C. A., Syracuse University, New York, USA,cascholz@syr.edu; CHINDANDALI, P. R. N., Northern Arizona University,
Arizona, USA, prc65@nau.edu; WOOD, D., Syracuse University, Arizona,
USA, dawood05@syr.edu; GREENLEE, J. M., Syracuse University, New York,USA, jmgreenl@syr.edu; BRANNON, M. A., Syracuse University, New York,USA, mabranno@syr.edu; MOUCHA, R., Syracuse University, New York,USA, rmoucha@syr.edu; XUE, L., Syracuse University, New York, USA,lxue07@syr.edu; TIMBA SCIENCE PARTY, M., Malawi Department ofSurveys, Monkey Bay, Malawi, donna.shillington@nau.edu
Active rifts such as the Malawi Rift in the East Africa Rift System host faults
capable of hosting large earthquakes. Many questions remain on the distribution of deformation, fault growth and linkage, and influence of surface
processes on fault behavior. The potential of >100-km-long border faults tohost large earthquakes has long been recognized, but recent earthquakes up to
M6 near Karonga, Malawi highlight the earthquake hazard posed by intrarift
faults, including faults below Lake Malawi. Existing seismic reflection imaging
shows that many intrarift faults offset the lake floor and youngest sediments,
providing further evidence that they are active. However, these profiles are
generally too sparse and low resolution to constrain fault lengths and recent
activity. We plan to acquire high-resolution bathymetric data to image thegeometries and linkage of faults beneath Lake Malawi and CHIRP data to
map sediments and faults up to ~50-100 m below the lake bottom. A teamof US and Malawian scientists plan to acquire multibeam bathymetric and
CHIRP data in several focus regions in the North and Central Basins of Lake
Malawi in January-February 2024 aboard the M/V Timba, a ship operated
by the Malawi Department of Surveys. This will be the first time that modern bathymetric data have been collected in Lake Malawi. New geophysicaldata will be integrated with existing seismic and drilling data to determine thepositions, geometries, and Quaternary slip rates on faults below Lake Malawi.
In this presentation, we will show preliminary results from this new project.

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poster 186
Constraining Earthquake Nucleation using Response of
Seismicity to Transient Slow-slip Event and Hydrological
Surface Load
SIRORATTANAKUL, K., California Institute of Technology, California,
USA, ksirorat@caltech.edu; AVOUAC, J., California Institute of Technology,
California, USA, avouac@caltech.edu
The seismicity rate often fluctuates with varying effective stress in the Earth’s
crust. Common sources of stress perturbations include spontaneous slow-slip
events, large-scale hydrological loading, solid Earth tides, and anthropogenic
factors related to fluid injection or gas extraction. By studying how the driving stress relates to variations in seismicity rate, we can better understand theearthquake nucleation process. Here, we consider two case studies from different spatial and temporal scales. The first case study is the 2020 Westmorland,
California earthquake swarm that lasted approximately five days. 5-min sampled GPS and InSAR reveal a shallow Mw 5.19 slow-slip event that started 12hours prior to the onset of seismicity. Using a stress-driven model based on
rate-and-state friction, we can explain the overall spatial and temporal evolution of seismicity using the transient stress from the slow-slip event, including the time lag between the slow-slip event and the onset of seismicity. The
second case study considers the annual modulation of the seismicity rate in
California. We decluster the catalog using the nearest-neighbor approach andsearch for periodicities using the Schuster spectrum. For areas with detectable seasonal modulation of seismicity, we find a correlation between theamplitude of seismicity rate modulation and the amplitudes of driving stressdue to seasonal changes in surface hydrological loads. Furthermore, the peakseismicity rate occurs approximately one month after the peak stressing rate.
Both case studies reveal that earthquake nucleation is not instantaneous. The
constrained frictional-stress parameter is also consistent with one another at
a few kPa, suggesting a smaller rate-and-state direct effect than those typicallymeasured in the laboratory, the prevalence of high fluid pore pressure, or a
combination, at least for the areas where the earthquakes occurred.
poster 187
Towards Systematic Kinematic Source Models of
Historically Large Earthquakes
SOLARES-COLÓN, M. M., University of Oregon, Oregon, USA, msolares@
uoregon.edu; MELGAR, D., University of Oregon, Oregon, USA, dmelgarm@uoregon.edu; BATO, M. G., Jet Propulsion Laboratory, California Institute ofTechnology, California, USA, mary.grace.p.bato@jpl.nasa.gov
We are interested in systematically analyzing large ruptures to establish scalinglaws of kinematic properties, such as rise times, slip rates, and rupture speeds.
The challenge is that kinematic models for large (M6+) events are often produced with heterogenous methodologies and datasets. This makes synthesis ofgeneral behaviors challenging and results ambiguous. Additionally, as methods continue to develop, past events with good observations do not necessarily have slip models produced with modern methods. Thus, retrospective
analysis of slip distributions is fundamental to allow us to further investigate
general characteristics of source parameters during a rupture.
Here we will discuss our plans to retrospectively process significant
ruptures with new inversion techniques that are capable of jointly inverting teleseimsic body and surface waves, static and high-rate GNSS, InSAR,
strong motion and tsunami data. We will highlight the approach by focusing
on the M9.1 Tohoku-oki earthquake to showcase the advantages of the new
approach. This earthquake in 2011 stands as one of the largest ruptures everrecorded and most closely observed earthquake in history due to the dense
array of seismic and geodetic instrumentation in Japan. This provided an
unprecedented opportunity to study this megathrust event and collect datanear source.
This analysis extends beyond the great M9.1 Tohoku-oki earthquake,actively contributing to the ongoing reevaluation of finite-fault models forlarge earthquakes dating back to the 1990s, while also incorporating regional
data when available. Ultimately, we aim to refine source scaling properties oflarge earthquakes worldwide. Therefore, we will present our proposed workflow that involves not only systematizing the inversion process but also thecreation of standardized and analysis-ready input source products. This is particularly important for InSAR and GNSS, which are quickly expanding theirtemporal and spatial sampling of crustal deformation worldwide.
poster 189
Study on the Latest Activity and the Maximum Potential
Earthquake in the Middle Section of the Minjiang Fault
ZHOU, C., China Earthquake Administration, Beijing, China,
imzhouchao@126.com; HAN, Z., China Earthquake Administration, Beijing,

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China, zjhan0904@163.com; GUO, P., China Earthquake Administration,
Beijing, China, guopengpoli@163.com; NIU, P., China Earthquake
Administration, Beijing, China, niupengfei0814@163.com
The Indo-Asian collision has resulted in the rapid uplift of the Tibet Plateau,
forming the Minshan active block on the northeastern margin of the plateau.
The Minshan active block is characterized by high intensity and frequencyof seismic activity, with many of the seismogenic structures located withindensely populated valleys flanked by high terrain. The large earthquakes andassociated geological hazards, such as massive landslides, have caused significant loss of life and property in this region. Therefore, it is crucial to evaluate
the fault activity and seismic hazard in this area. The Minjiang fault, locatedat the western boundary of the Minshan active block, has been extensively
studied through field investigations. However, the lack of continuous surface
exposures in the middle segment of the fault has limited research on its latest activity and maximum potential earthquake, hindering the assessmentof seismic hazard in the area. In this study, we conducted detailed remotesensing image interpretation and field investigations of the middle segmentof the Minjiang fault to quantitatively evaluate its latest activity, maximum
potential earthquake magnitude, and seismic hazard. The middle segment of
the Minjiang fault is a Holocene active fault. Using the empirical formulas,
we estimated its maximum potential earthquake magnitude to be approximately Ms7.3. We also suggest the existence of two seismic hazard zones on
the periphery of the Minshan active block, including the southern segmentof the Huya fault and the middle segment of the Minjiang fault. The research
provides data support for the assessment of seismic and geological hazards
in this region, and enhances the further understanding of the tectonic deformation patterns and dynamic mechanisms of the northeastern margin of the
Tibet Plateau.

Leveraging Cutting-Edge Cyberinfrastructure for Large
Scale Data Analysis and Education
Oral Session • Thursday 2 May • 4:30 pm PacificConveners: Alice-Agnes Gabriel, University of California, San
Diego (algabriel@ucsd.edu); Henry Berglund, EarthScope
Consortium (henry.berglund@earthscope.org); Marine A.
Denolle, University of Washington (mdenolle@uw.edu);
Tim Dittmann, EarthScope Consortium (tim.dittmann@earthscope.org); Zoe Krauss, University of Washington(zkrauss@uw.edu); Eileen Martin, Colorado School of Mines(eileenrmartin@mines.edu); Amanda Thomas, Universityof Oregon (amthomas@uoregon.edu); Chad Trabant,
EarthScope Consortium (chad.trabant@earthscope.org); Ian
Wang, University of Texas at Austin (iwang@tacc.utexas.edu)
Advancing USGS Scientific Modeling Through Cloud
Computing
HAYNIE, K. L., U.S. Geological Survey, Colorado, USA, khaynie@usgs.gov;
HUNSINGER, H., U.S. Geological Survey, Colorado, USA, hhunsinger@usgs.
gov; MARTINEZ, E., U.S. Geological Survey, Colorado, USA, emartinez@
usgs.gov; BRITO SILVERIA, L., U.S. Geological Survey, Colorado, USA,lbritosilveira@usgs.gov; CASSIDY, K., U.S. Geological Survey, Colorado,
USA, kcassidy@usgs.gov; HEARNE, M., U.S. Geological Survey, Colorado,
USA, mhearne@usgs.gov; HUNTER, E., U.S. Geological Survey, Colorado,
USA, ehunter@usgs.gov; BROWN, J., U.S. Geological Survey, Colorado, USA,jdbrown@usgs.gov; GOLDBERG, D., U.S. Geological Survey, Colorado, USA,degoldberg@usgs.gov; YECK, W., U.S. Geological Survey, Colorado, USA,wyeck@usgs.gov; DEANE, C., U.S. Geological Survey, Commonwealth of theNorthern Mariana Islands, USA, cdeane@usgs.gov
The U.S. Federal Government released an Executive Order to carry out a
Cloud Smart strategy aimed at adopting cloud-based solutions for modernizing cyberinfrastructure, enhancing security, and providing the American people with higher quality services and products (https://cloud.cio.gov/strategy/).
Software developers at the U.S. Geological Survey (USGS) Geologic Hazards
Science Center (GHSC) are adopting this strategy by moving IT infrastructure from on-premises servers to the cloud. Here, we give an overview of how
the GHSC is running various scientific applications on the cloud. We will
discuss the hybrid cloud systems (a cloud architecture that lies between lift-

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and-shift and purely cloud native approaches) used for running 1) the USGS
earthquake-triggered global ShakeMap and down-stream near-real-time
Ground Failure product, 2) user-initiated high-throughput computing simulations of seismic site response using the finite element platform OpenSees, 3)
a semi-automatic approach for running finite fault inversions, and 4) USGS
slab models via a web form request. Adopting the Cloud Smart strategy has
not only educated GHSC developers on the capabilities of cloud computing
but has prompted the development of new USGS earthquake hazard products(e.g., the Sequence Product, which links USGS event pages for foreshocks,
mainshocks, and aftershocks), and has shifted seismic workflows (e.g., aftershock relocations) to follow cloud-native serverless approaches. We will also
address examples of how USGS scientists interact with these cloud systems,
benefits and drawbacks of migrating to the cloud, associated costs, and how
one can get started with cloud computing.

highlight on the capability to access very large datasets that this paradigm
change will allow. In addition to documentation, EarthScope will provide anotebook hub to support easy and democratized access to compute adjacentto the data. Workshops will be developed and conducted both in person andonline to train researchers how to use these new resources and generally transition their work to the cloud. With the ability to apply cloud computing todeep geophysical data sets the future is bright, and we are excited to enable thisfor multiple geoscience domains.

Parallel Processing of Large Seismic Data Sets With Mspass
WANG, C., University of Texas at Austin, Texas, USA, chenxiaowang@utexas.
edu; WANG, Y., University of Texas at Austin, Texas, USA, iwang@tacc.
utexas.edu; PAVLIS, G. L., Indiana University, Indiana, USA, pavlis@indiana.
edu; MOHAPATRA, S., University of Texas at Dallas, Texas, USA, sasmita@
utdallas.edu; MA, J., University of Texas at Austin, Texas, USA, jinxin.ma@
utexas.edu

New seismic sensing technologies such as distributed acoustic sensing (DAS)
and low-cost accelerometer nodes are making it easier than ever before tocontinuously collect high-resolution, large-scale seismic data. Public seismology data archives are struggling to host the full datasets, research teams spend
huge amounts of time and/or electricity to transfer the full datasets, and ourability to interactively visualize and rapidly understand these data is hinderedby their large size. When data acquisition settings are selected appropriately(e.g. not oversampled in time or space), lossy compression techniques allow
us to greatly reduce the size of the data without introducing the limitations ofsubsampling (e.g. array aliasing). However, lossy compression techniques areunable to exactly reconstruct our original array data at the same precision they
were recorded at. While prior studies have characterized the errors introduced
into the raw and reconstructed data for some types of lossy compression, we
aim to understand the extent to which these errors propagate into meaningful changes in our characterization of seismic signals, including through template matching and event picking workflows. We quantitatively compare thechanges in an open DAS dataset (the Bradys Hot Springs PoroTomo data)
under varying levels of lossy compression using singular value decomposition(SVD) compression, wavelet-based compression, and zfp compression strategies. We show the quantitative tradeoffs in event catalogs resulting from template matching of data that has undergone substantial levels of compression.
Further, we quantify the distribution of array-wide event pick time changes,
which are shown to incur little to no average bias. We have released opensource, fully reproducible codes for comparing compression strategies for all
workflows in this study to encourage others to use these tools in evaluating thesuitability of lossy compression for sharing other datasets.

The size and accessibility of seismology data have undergone a transformativechange due to large-scale projects like the USArray component of Earthscope.
This has ushered in an era of unprecedented data resources for the seismology
community. Collaborative endeavors like SCOPED (Seismic COmputational
Platform for Empowering Discovery) aim to provide data and computation asa service, with MsPASS (Massive Parallel Analysis System for Seismologists)
as a pivotal component within this platform. MsPASS is open-source, fully
containerized, operates on parallel schedulers, and utilizes a NoSQL databasefor data management. These features make it the only framework in existence
today for generic seismic processing on systems of any scale. The newest
release of MsPASS (v2.0) has major enhancements in parallel IO capabilities,
prototype methods for working on cloud computering systems, and improvements to documentation. Current work is focused on added interoperability
with existing Machine Learning packages, such as SeisBench and PhaseNet.
We will demonstrate current capabilities with results from processing a large
dataset of all broadband channels located within the contiguous United Statesthat operated during the USArray recording period. MsPASS can also leverage AWS Lambda functions for preprocessing data hosted on the cloud. We
demonstrate the improvement in throughput performance with a workflow
processing the SCEDC dataset on AWS. Another notable development is theseamless integration of MsPASS into large HPC systems through the SCOPED
Gateway, a science gateway facilitating seismic data processing as a service
over the web. This not only boosts the accessibility and flexibility of MsPASS
but also significantly lowers the intellectual entry barrier often encounteredwith new software systems. With these new developments, we aim to transform MsPASS into a community tool for large-scale seismic data processing,
thereby enhancing capabilities, fostering collaboration, and innovating data
mining within the seismology community.
Enabling Large Data Analysis on the Earthscope Data
Repositories
TRABANT, C., EarthScope Consortium, District of Columbia, USA, chad.
trabant@earthscope.org; DITTMANN, T., EarthScope Consortium, Districtof Columbia, USA, tim.dittmann@earthscope.org; BRAVO, T. K., EarthScope
Consortium, District of Columbia, USA, tammy.bravo@earthscope.org;
WEEKLY, R. T., EarthScope Consortium, District of Columbia, USA, robert.
weekly@earthscope.org; JOHNSON, S., EarthScope Consortium, District ofColumbia, USA, scott.johnson@earthscope.org; HAMILTON, A., EarthScope
Consortium, District of Columbia, USA, alex.hamilton@earthscope.org;
BERGLUND, H., EarthScope Consortium, District of Columbia, USA, henry.
berglund@earthscope.org; MENCIN, D., EarthScope Consortium, Districtof Columbia, USA, david.mencin@earthscope.org; CARTER, J., EarthScope
Consortium, District of Columbia, USA, jerry.carter@earthscope.org
In 2024, all geophysical data managed by the EarthScope consortium for
NSF’s GAGE and SAGE facilities will be stored in a commercial cloud system.
This move will enable EarthScope and the research communities it supports
to leverage the enormous capabilities of cloud computing. To fully utilize theabundant compute, cost-effectiveness, and direct access to huge data sets inthe cloud, data processing systems need to be adapted for this new paradigm.
EarthScope has initiated a project to create resources that will help researchers transition their data analyses to this environment. These resources areintended to help researchers working at different scales, with a particular

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Seismological Research Letters

Exploring the Impact of Lossy Compression on Passive
Seismic Event Detection and Arrival Time Precision
ISSAH, A. S., Colorado School of Mines, Colorado, USA, aissah@mines.edu;
MARTIN, E. R., Colorado School of Mines, Colorado, USA, eileenrmartin@
mines.edu

Towards End-to-End Earthquake Monitoring Using a
Multitask Deep Learning Model
ZHU, W., University of California, Berkeley, California, USA, zhuwq0@gmail.
com
Advancements in seismic data processing provide crucial insights into earthquake characteristics. Conventional methods used for earthquake monitoringtasks, such as earthquake detection and phase picking, are being enhancedby the rapid advancements in deep learning. However, most current efforts
focus on developing separate models for each specific task, leaving the potential of an end-to-end framework relatively unexplored. To address this gap, we
expend the PhaseNet model to create a multitask framework. This enhanced
model, PhaseNet+, can simultaneously perform talks of phase arrival time
picking, first motion polarity determination, and earthquake source parameter prediction. The outputs from these perception-based models can thenbe processed by specialized physics-based algorithms to accurately determine
earthquake location and focal mechanism. Our approach aims to enhanceseismic monitoring by adopting a more unified and efficient approach.

Leveraging Cutting-Edge Cyberinfrastructure for Large
Scale Data Analysis and Education [Poster Session]
Poster Session • Thursday 2 May
Conveners: Alice-Agnes Gabriel, University of California, San
Diego (algabriel@ucsd.edu); Henry Berglund, EarthScope
Consortium (henry.berglund@earthscope.org); Marine A.
Denolle, University of Washington (mdenolle@uw.edu);
Tim Dittmann, EarthScope Consortium (tim.dittmann@earthscope.org); Zoe Krauss, University of Washington

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(zkrauss@uw.edu); Eileen Martin, Colorado School of Mines(eileenrmartin@mines.edu); Amanda Thomas, Universityof Oregon (amthomas@uoregon.edu); Chad Trabant,
EarthScope Consortium (chad.trabant@earthscope.org); Ian
Wang, University of Texas at Austin (iwang@tacc.utexas.edu)
poster 33
SCOPED Update: A Cloud and HPC Software Platform for
Computational Seismology
DENOLLE, M. A., University of Washington, Washington, USA, mdenolle@
uw.edu; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu; WANG, Y., University of Texas at Austin, Texas, USA, iwang@tacc.utexas.edu; BOZDAG, E., Colorado School of Mines, Colorado, USA,bozdag@mines.edu; WALDHAUSER, F., Columbia University, New York,USA, felixw@ldeo.columbia.edu; BEAUCE, E., Columbia University, New
York, USA, ebeauce@ldeo.columbia.edu; CHOW, B., University of Alaska
Fairbanks, Alaska, USA, bhchow@alaska.edu; FENG, K., University ofWashington, Washington, USA, kffeng@uw.edu; FREEMAN, N., University ofTexas at Austin, Texas, USA, nfreeman@tacc.utexas.edu; GARCIA JURADO
SUAREZ, C., University of Washington, Washington, USA, carlosg@uw.edu;
NAGASO, M., Colorado School of Mines, Colorado, USA, masaru.nagaso@
mines.edu; NI, Y., University of Washington, Washington, USA, niyiyu@
uw.edu; OH, S., University of Texas at Austin, Texas, USA, oh.jae.steven@utexas.edu; ORSVURAN, R., Colorado School of Mines, Colorado, USA,rorsvuran@mines.edu; SAWI, T., Columbia University, New York, USA,tsawi@ldeo.columbia.edu; STUBBS, J., University of Texas at Austin, Texas,
USA, jstubbs@tacc.utexas.edu; THETFORD, J., University of Texas atAustin, Texas, USA, j.thetford@utexas.edu; THURIN, J., University of Alaska
Fairbanks, Alaska, USA, jthurin@alaska.edu; WANG, C., University of Texas
at Austin, Colorado, USA, iwang@tacc.utexas.edu; WANG, K., Columbia
University, New York, USA, kw2988@ldeo.columbia.edu
The goal of the SCOPED (Seismic COmputational Platform for Empowering
Discovery) project is to develop a cyberinfrastructure that enables hybrid
model-data research in seismology. The open-source software development
will make it easier for researchers to connect and collaborate via common
platforms like GitHub and containers like Docker. Seismological research istypically either data-driven or model-driven. Data-driven workflows are wellsuited for cloud infrastructure, while model-driven workflows are best suitedfor HPC. The SCOPED platform includes tools for data discovery, theoreticalseismology, wavefield simulations, and inversion workflows for velocity Earthmodels and earthquake source characterization. The platform containerizes
our seismological software to run on both HPC and cloud platforms. Tutorials
are also included to guide new users on how to run the software. Additionally,
the SCOPED Gateway is available as a preliminary implementation, whichenables these containers as services over the web.
In this SCOPED update, we present several advances. First, we demonstrate using the SCOPED gateway for HPC simulations of seismic wavefields
and their inversion using MTUQ and SPECFEM. In addition, we will discuss
the current and future I/O problems and potential remedies for large-scale
full-waveform inversions on HPC systems. Second, we demonstrate cloudnative workflows on Amazon WebServes (AWS). We demonstrate how to
do ambient noise seismology with NoisePy, deep-learning seismology using
SeisBench and QuakeFlow, and unsupervised ML for source characterizationand discovery. We demonstrate how to use AWS tools and Infrastructureas-a-service tools such as Coiled to abstract cloud systems for easier access.
Finally, we show how SCOPED ways to bridge cloud and HPC using the
SeismoDB data lake.
poster 34
Updates to the U.S. Geological Survey’s ProductDistribution Layer and Impacts on Comcat and Realtime
Systems
HUNSINGER, H., U.S. Geological Survey, Colorado, USA, hhunsinger@usgs.
gov; MARTINEZ, E., U.S. Geological Survey, Colorado, USA, emartinez@
usgs.gov; BROWN, J., U.S. Geological Survey, Colorado, USA, jdbrown@usgs.
gov; CLOUTET, Z., U.S. Geological Survey, Colorado, USA, zcloutet@usgs.
gov; HAYNIE, K., U.S. Geological Survey, Colorado, USA, khaynie@usgs.gov;
HUNTER, E., U.S. Geological Survey, Colorado, USA, ehunter@usgs.gov;
LASTOWKA, L., U.S. Geological Survey, Colorado, USA, llastowka@usgs.gov
The U.S. Geological Survey’s (USGS) Product Distribution Layer (PDL;
https://ghsc.code-pages.usgs.gov/hazdev/pdl/docs/) is a tool integral to manysystems, including, but not limited to, the ANSS Comprehensive Catalog ofVolume 95•

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seismic events (ComCat; https://earthquake.usgs.gov/data/comcat/), Realtime feeds (e.g. https://earthquake.usgs.gov/earthquakes/feed/v1.0/geojson.
php), the latest earthquakes map and list (https://earthquake.usgs.gov/earthquakes/map/), and automated data delivery to Advanced National Seismic
System (ANSS) contributors. PDL and these affiliated systems are critical
for receiving and distributing large amounts of earthquake data in near realtime. In recent years, the Geologic Hazards Science Center’s (GHSC) Hazards
Development Team (HazDev) has worked to move PDL systems from onpremises servers into the Cloud. A non-exhaustive list of the benefits of thesemigrations include scalability, enhanced security, and the ability to implement
continuous integration/continuous deployment (CI/CD) and Infrastructure
as Code (IaC) for fast system deployment and recovery.
The purpose of this talk is two-fold. First, we will detail the large-scale
ComCat database upgrade that occurred following the significant events ofthe 2023 Kahramanmaraş earthquake sequence, which exposed limitations in
the cloud system, and we will discuss the observed effectiveness of Amazon
Web Services (AWS) relational database service’s (RDS) scalability before andafter the upgrade. Second, we will outline ongoing work to improve PDL’s Javaclient and systems, and we will discuss the implications for our data consumers and producers.
poster 35
Alaska Earthquake Center’s Workforce Development
Program Takes ShapeNADIN, E. S., Alaska Earthquake Center, Alaska, USA, enadin@alaska.
edu; LOW, G., Alaska Earthquake Center, Alaska, USA, glow2@alaska.edu;
WEST, M. E., Alaska Earthquake Center, Alaska, USA, mewest@alaska.edu;
MOHLER, M., Alaska Earthquake Center, Alaska, USA, mdmohler@alaska.
edu; PARCHETA, C., Alaska Earthquake Center, Alaska, USA, ceparcheta@
alaska.edu
The Alaska Earthquake Center has committed to helping develop a strong anddiverse Alaskan workforce. In 2022, we joined with the T3 (Teaching ThroughTechnology) Alaska program to bring seismic instrumentation training torural Alaska students in communities across the state. In the first year of the
program, 22 students from 7 communities participated. Now in its second
year, over 30 students from 16 schools are enrolled in the Earth Observation
Club. We have refined how the program runs, and expanded the suite of tools
available for training to align with Alaska Geophysical Network instrumentation. The school-year program relies on a teacher at each school to act as the
local coordinator. An in-person kick-off event forges early connections, andweekly online meetings provide a classroom-type environment for students toconnect and brainstorm ideas for community-based projects. Students discuss
individual community concerns, like permafrost thaw that leads to groundinstability and erosion. They decide on which real-time monitoring tool(s)—seismometer, soil probe, weather station, camera—they will use to collect thedata to make informed community decisions. For example, months-long datafrom a soil temperature profiler in Quinhagak can help the village make an
informed decision on where to place a new road. The students set up and run
their project, and present their efforts at an in-person event in the spring, suchas this year’s SSA meeting.
This year we have also introduced a credentialing program that is aimed
at training students in the field and technical skills needed to troubleshoot, fix,
and install remote seismic stations. The program includes basic, intermediate,
and advanced stages, and culminates in in-person training and the opportunity to apply for summer internships. Our plans for the next few years include
creating credentialing pathways in data analysis, computer systems, and communications, and building industry partnerships for student employment.
poster 36
Cloud-Based Gnss Processing Pipeline for the Shakealert
Earthquake Early Warning System
RONAN, T., EarthScope Consortium, , USA, tim.ronan@earthscope.org;
HAMILTON, A., EarthScope Consortium, , USA, alex.hamilton@earthscope.
org; SIEVERS, C., EarthScope Consortium, , USA, charlie.sievers@
earthscope.org; DITTMANN, T., EarthScope Consortium, , USA, tim.
dittmann@earthscope.org; BERGLUND, H., EarthScope Consortium, , USA,henry.berglund@earthscope.org; TRABANT, C., EarthScope Consortium,, USA, chad.trabant@earthscope.org; CASEY, R., EarthScope Consortium, ,USA, rob.casey@earthscope.org; MCNAMARA, D., EarthScope Consortium,, USA, daniel.mcnamara@earthscope.org; CARTER, J., EarthScope
Consortium, , USA, jerry.carter@earthscope.org; MENCIN, D., EarthScope
Consortium, , USA, david.mencin@earthscope.org
ShakeAlert is an earthquake early warning (EEW) system that modernizes
earthquake response procedures by alerting people and automated systems

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before strong/damaging ground shaking arrives. EarthScope is working with
the United States Geological Survey (USGS) to integrate the Global Navigation
Satellite System (GNSS) data into the ShakeAlert monitoring system. Unlike
seismic data, GNSS positions do not saturate and capture sensor displacement during strong shaking. EarthScope’s Data Services (DS) is developing acloud-native, low-latency processing pipeline that normalizes real-time position streams from various sources, including receivers operated by ShakeAlert
partner networks, raw GNSS observations, and pre-processed position data.
Real-time GNSS position data are used to rapidly determine PeakGround Displacement (PGD) for near source, strong earthquakes ~>Mw6.
Algorithms use PGD data to rapidly estimate the magnitude of an event during, or soon after, the fault rupture sequence. Earthquake size estimates calculated from PGD data are robust and inform the geographical extent of anissued ShakeAlert warning. EarthScope DS designed the cloud-native natureof the newly developed ShakeAlert GNSS processing pipeline to facilitate theintegration of new technologies, including the adaptation of machine learningalgorithms to real-time GNSS and seismic data streams. The new ShakeAlertsystem developed in partnership with the USGS will enable the research andoperational hazard response communities to process and respond to seismic
events accurately by leveraging the advantages of cloud-based operations on
geophysical data.

of instructional design to a degree not possible in traditional courses. The
workshop consists of over 35 interactive assignments with more than 1000
questions. It was designed to engage students in key skills (e.g. seismology,
programming, quantitative literacy), frequently with higher order thinking,and with increasing challenge as the workshop progresses. To explore the efficacy of the instructional design, we created a table of specification categorizing each question from the 2022 course according to skill and Bloom’s Revised
taxonomy. We then compared the distribution of categories to the design
intent and examined each category using facility and discrimination indicesto evaluate students’ performance.
Results indicate the instructional design of the course did not fully alignwith the original intentions. For example, 80% of the questions fell within thelowest 2 levels of Bloom’s taxonomy. In addition, the rigor did not increase
through the workshop. Changes enacted in 2023 increased the number ofhigher order thinking questions, progressively reduced scaffolding, andreduced the number of no-skill questions and increased the number of multiskill questions. To evaluate the impact of these changes on student learning
outcomes, a pre/post test targeting each of the categorized skills was administered in 2023. Results show improved performance for all of the key skills andmore consistent and larger gains for higher order thinking.

poster 37
Deep Implicit Time Series Modeling for Earthquake Phase
Picking on Edge Devices
TSAI, A., University of California, Berkeley, California, USA, aliciatsai@berkeley.edu; CHUANG, L., Georgia Institute of Technology, Georgia, USA,ychuang35@gatech.edu; PENG, Z., Georgia Institute of Technology, Georgia,
USA, zpeng@gatech.edu; EL GHAOUI, L., University of California, Berkeley,
California, USA, elghaoui@berkeley.edu

Machine Learning for Full Waveform Inversion: From
Hybrid to End-to-End Approaches
Oral Session • Friday 3 May • 4:30 pm PacificConveners: Jennifer L. Harding, Sandia National Laboratories(jlhardi@sandia.gov); Mrinal K. Sen, University of Texas atAustin (mrinal@utexas.edu); Hongkyu Yoon, Sandia National
Laboratories (hyoon@sandia.gov)

Earthquake monitoring and understanding seismic activities are pivotal inassessing seismic hazards and ensuring community resilience. One criticalaspect of earthquake analysis involves accurate phase picking, where precise identification of seismic wave arrival times is fundamental for robust
event characterization. Traditionally, seismic phase picking demands laborintensive efforts and often struggles with noises, irregularities, and othercomplexities inherent in seismic data, until the emergence of deep learningbased automatic phase pickers. State-of-the-art models like EQTransformer
and Phasenet have transformed this task, exhibiting remarkable precision in
detecting and classifying seismic phases, significantly augmenting the efficiency of earthquake monitoring. However, these advanced models often
rely on high-powered servers with multiple GPUs, limiting accessibility,
especially for those reliant on mobile or edge devices (e.g. Raspberry Shakes)
that lack significant computing capabilities. To address these challenges, we
explore a novel deep-learning framework—times series modeling with a deep
implicit model—on the seismic phase picking problem. The implicit model
uses a state-driven approach, which distinguishes itself from its traditional,
layered-based deep learning counterparts. It is capable of emulating classical feedforward-based neural networks while offering promise in compressing models without exhaustive retraining. We plan to first train the implicit
model on the STEAD dataset. The trained model will then be compressedby utilizing the low-rank technique. An offline performance test on data collected by Raspberry Pi and Shake will then be performed to understand theeffectiveness of model compression. We hope this approach advances seismicphase picking accuracy and pioneers a pathway to democratize deep learningfor seismic monitoring on resource-constrained devices.
poster 38
Using Learning Analytics to Evaluate the Instructional
Design and Student Performance in a Large-Enrollment
Scientific Computing Workshop
HABERLI, G., Miami University (now at EarthScope Consortium), Ohio,
USA, gillianhaberli@gmail.com; BRUDZINSKI, M. R., Miami University,
Ohio, USA, brudzimr@muohio.edu; HUBENTHAL, M., EarthScope
Consortium, District of Columbia, USA, michael.hubenthal@earthscope.org
Addressing today’s complex scientific challenges will require geoscience curricula to develop skills and competencies, such as scientific computing, inaddition to subdisciplinary content knowledge. Online training shows promise for teaching domain-specific scientific computing and for broadening
access. However, what results in effective course design, pedagogy, and retention needs further exploration. Online courses such as the Seismology Skill
Building Workshop, which helps students build scientific computing skills
through seismology-focused programming, generate rich datasets of student
interactions and performance that can be used to explore the effectiveness

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Seismological Research Letters

Advancing Seismic Full Waveform Inversion: A Hybrid
Approach of Machine Learning and Physical Models for
Improved Generalizability and Efficiency
LIN, Y., Los Alamos National Laboratory, New Mexico, USA, ylin@lanl.gov
Computational seismic full waveform inversion (FWI) is crucial for energy
exploration, civil infrastructure, Earthquake detection and early warning,and so on. However, nearly all of the earth’s interior is inaccessible to direct
observation. Inference of unknown subsurface properties, therefore, relies onindirect and limited seismic measurements taken at or near the surface. The
relevant data analysis capability for solving computational seismic imaging
problems is inadequate, mainly due to the ill-posed nature of the problems
and the high computational costs of solving them. Recently, machine learning (ML) based computational methods have been pursued in the context ofscientific computational imaging problems. Some success has been attained
when an abundance of simulations and labels are available. Nevertheless,
ML models, trained using physical simulations, usually suffer from weakgeneralizability when applied to a moderately different real-world dataset.
Moreover, obtaining corresponding training labels is typically prohibitively
expensive due to the high demand for subject-matter expertise. On the other
hand, different from problems in a typical computer vision context, many
scientific imaging problems are governed by underlying physical equations.
For example, the wave equation, describing how a wave signal is propagatedthrough a subsurface medium over time, is the governing physics for seismic
imaging problems. To fully unleash the power and flexibility of ML for solving large-scale computational seismic FWI problems, I have developed newcomputational methods to bridge the technical gap by addressing the criticalissues of weak generalizability, label scarcity, and high training cost. In thistalk, I will discuss the details of my R&D effort in leveraging both the power ofmachine learning and underlying physics. A series of numerical experiments
are conducted using datasets from synthetic simulations to field applications
to evaluate the effectiveness of the new FWI methods.
Ambient Noise Full Waveform Inversion With Neural
Operators
ZOU, C., California Institute of Technology, California, USA, czou@caltech.
edu; AZIZZADENESHELI, K., Nvidia Corporation, California, USA,kamyara@nvidia.com; ROSS, Z. E., California Institute of Technology,
California, USA, zross@caltech.edu; CLAYTON, R., California Institute ofTechnology, California, USA, clay@gps.caltech.edu
Numerical simulations of seismic wave propagation are central to investigating velocity structures and for improving seismic hazard assessment, but stan-www.srl-online.org•

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dard methods such as finite element or finite difference are computationallyexpensive. Recent studies have shown that a new class of machine learningmodels, called Neural Operators, are able to solve the elastodynamic wave
equation orders of magnitude faster than these conventional numerical methods. Full waveform inversion is a prime beneficiary of the accelerated simulations. Neural operators, combined with automatic differentiation, provide analternative approach to full waveform inversion that does not involve the Born
approximation. It thus can potentially overcome some of the cycle skipping
problems present in traditional adjoint state formulations. Here we demonstrate the first application of Neural Operators for full waveform inversion ona real seismic dataset: several nodal transects collected across the San Gabrieland San Bernardino Basins in the Los Angeles metropolitan area.
Application of TCN, UMAP, and XGBoost to Pg and Lg Wave
Amplitude to Identify Mining vs. Non Mining and Deep vs.
Shallow Events
GODDARD, K., Air Force Technical Applications Center, Florida, USA, kyler.
goddard.2@us.af.mil; SAIKIA, C. K., Air Force Technical Applications Center,
Florida, USA, chandan.saikia@us.af.mil; STANLEY, J., ENSCO, Florida, USA,
joseph.stanley.13.ctr@us.af.mil; PATRICK, T., KBR, Florida, USA, trevor.
patrick.3.ctr@us.af.mil; ZHOU, R., Air Force Technical Applications Center,
Florida, USA, rongmao.zhou@us.af.mil; MENZHI, M., National Center for
S&T, Rabat, Morocco, menzhi@cnrst.ma
Using the CNRS bulletin from the seismic network in Morocco, we collected4542 regional waveforms for both mining and non-mining events occurringaround the station MD31. The events have occurred within 50 to 250 km of
the station. Using this mixed bag of waveforms and criterion that SNR must
be greater than 2, we selected 260 mining and 161 non-mining events to conduct this study. We processed these waveforms to construct a meta-data fileconsisting of the RMS amplitude of the Pg and Lg waves in five frequency
bands at 4-6, 6-8, 8-10, 6-12 and 8-16Hz. The mining events occurred during
the day and they had characteristically strong Pg and weak Lg waves, especially at high frequencies. We observed that while the Pg and Lg amplitude
alone did not separate, the high-frequency Pg/Lg amplitude ratios separated
the two population quite well. Mining events are shallow and occurred at asingle site. For this reason alone we did not perform any MDAC correction tothese amplitudes. The supervised 80:20 and 50:50 training and testing of data
and analysis of the impact factor of the attributes using the XGBoost algorithm illustrated a high level of success in identifying the source types. Usinga supervised trained 90:10 model, we could further identify additional source
types for about 428 events in the area. We are currently applying the TCN and
UMAP to the same data set to determine the performance in the classificationof these events from Morocco. We are now compiling a similar data set inareas where earthquakes occur at many depths, where deep earthquakes may
exhibit strong P and weak-to-moderate level of Lg waves. Our primary focus
is to evaluate the performance of the algorithms in identifying “deep vs shallow” and “mining explosions vs. shallow and deep” earthquakes.
Scaling Up Large Fourier Neural Operator Training in 3D
Seismic Waveform Modeling
KONG, Q., Lawrence Livermore National Laboratory, California, USA,
kong11@llnl.gov; MATZEL, E., Lawrence Livermore National Laboratory, ,USA, matzel1@llnl.gov; ZOU, C., California Institute of Technology, , USA,czou@caltech.edu; CHOI, Y., Lawrence Livermore National Laboratory, ,USA, choi15@llnl.gov; ROSS, Z., California Institute of Technology, , USA,zross@gps.caltech.eud; AZIZZADENESHELI, K., Nvidia, , USA, kamyara@
nvidia.com; RODGERS, A., Lawrence Livermore National Laboratory, , USA,rodgers7@llnl.gov; CLAYTON, R., California Institute of Technology, , USA,
clay@gps.caltech.edu
Recent developments in using Fourier Neural Operators (FNO) to solve 2Dand 3D elastic wave equations provide the basis for using machine learning
tools for seismic wave modeling, thus enabling fast full waveform inversion invarious applications. However, training these models usually requires heavy
computation both in time and hardware, such as HPCs, with limitationsin scaling the model up. In this presentation, we build on the prior efforts(Yang et al., 2023; Zou et al., 2023) to experiment with ways to improve thelarger model training to facilitate the use of this approach in large-scale realworld applications. We test transfer learning, model parallelization, physicsinformed neural operators to make training larger models easier. This evaluation of different approaches provides guidance for future training of large
neural operator models for full waveform inversion applications.

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Physics-Informed Deep Generative Models to Quantify
Uncertainties in the Geophysical Full-Waveform Inversion
ELMELIEGY, A. M., University of Texas at Austin, Texas, USA, abdelrahman.
elmeliegy@jsg.utexas.edu; DHARA, A., University of Texas at Austin, Texas,
USA, adhara@utexas.edu; SEN, M. K., University of Texas at Austin, Texas,
USA, mrinal@utexas.edu; HARDING, J. L., Sandia National Labortories, New
Mexico, USA, jlhardi@sandia.gov; YOON, H., Sandia National Labortories,
New Mexico, USA, hyoon@sandia.gov
Full-waveform inversion (FWI) has the potential to provide high resolution
maps for subsurface velocity models. However, due to the challenges and limitations of FWI, e.g., noisy measurements and the absence of low frequency
content, it is usually hard to obtain reliable subsurface velocity models due tothose uncertainties. Methods based on sampling, e.g., Markov Chain Monte
Carlo (MCMC) were developed to quantify the uncertainties in the FWI.
However, sampling-based methods are generally computationally very expensive. Contrary to sampling methods, the variational-based methods provide
approximate, yet more efficient solutions to the large-scale probabilistic problems such as FWI. We have developed a variational probabilistic framework
for FWI where the goal is to map the seismograms to a distribution of velocity
models (posterior distribution). Given their high potentials in solving challenging probabilistic inverse problems, in this work, we study the feasibility of using deep generative models to reconstruct the posterior probability
distribution of the subsurface velocity model. Specifically, we consider two
generative model architectures, i.e., the variational autoencoder (VAE) andthe invertible neural network (INN) where the input is the shot gathers, andthe output are several samples of velocity models. We use these samples toestimate uncertainties, e.g., compute the mean and standard deviation of the
populations. Moreover, we iteratively update the network parameters in an
un-supervised manner. To achieve this, we backpropagate the FWI gradient
information into the network to guide the network parameters’ update basedon the underlying physics. In this talk, we will present the details of our framework and discuss the outcomes, ongoing efforts and our vision for possible
future directions. SNL is managed and operated by NTESS under DOE NNSA
contract DE-NA0003525.

Machine Learning for Full Waveform Inversion: From
Hybrid to End-to-End Approaches [Poster Session]
Poster Session • Friday 3 May
Conveners: Jennifer L. Harding, Sandia National Laboratories(jlhardi@sandia.gov); Mrinal K. Sen, University of Texas atAustin (mrinal@utexas.edu); Hongkyu Yoon, Sandia National
Laboratories (hyoon@sandia.gov)
poster 100
Physics-Guided Neural Network for Full Waveform
Inversion With Structural Enhancement
BI, Z., Lawrence Berkeley National Laboratory, California, USA, zfbi@lbl.
gov; NAKATA, N., Lawrence Berkeley National Laboratory, California, USA,nnakata@lbl.gov
Seismic velocity modeling plays a critical role in understanding subsurface
structures. Full-waveform inversion (FWI) is a powerful technique thatenables high-resolution velocity modeling by iteratively minimizing the discrepancies between observed and predicted seismic waveforms. However,
the inherent strong nonlinearity of FWI can often lead to convergence inlocal minima, especially when fitting oscillatory waveforms. This challenge
becomes even more pronounced when dealing with insufficient starting models and noisy data characterized by low signal-to-noise ratios.
Our study introduces an innovative learning-based approach to FWI,
which integrates deep learning with physical equations. In this method,
we parameterize the velocity model using a convolutional neural network(CNN). CNN inherently introduces spatial correlations, serving as regularization for the velocity model. This renders deep learning well-suited for FWI,
effectively mitigating noise in model gradients and alleviating issues related to
local minima. The velocity model generated by the CNN is seamlessly incorporated into the acoustic partial differential equation (PDE) solvers used in
traditional FWI. Automatic differentiation is harnessed to compute PDE gradients, facilitating the updating of network parameters through backpropagation. Additionally, inspired by recent developments in structure-tensor
coherence techniques, we further improve FWI through anisotropic diffusionsmoothing. We compute oriented derivatives along directions both perpen-

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dicular and parallel to seismic reflectors, giving rise to oriented structure
tensors. These oriented tensors enhance the representation of lateral velocity
discontinuities, particularly those associated with features that align with dipping structures in the velocity model. The numerical experiments conductedusing the well-established Marmousi model demonstrate better representations of discontinuous and stratigraphic velocity features compared to conventional FWI.
poster 101
Physics-Guided Unsupervised Deep Learning Approach for
the Inversion of Receiver Functions in Dipping andAnisotropic MediaDALAI, B., National Geophysical Research Institute, Hyderabad, India,
bijayanandadalai@gmail.com; KUMAR, P., National Geophysical ResearchInstitute, Hyderabad, India, prakashk@ngri.res.in; SEN, M. K., University ofTexas at Austin, Texas, USA, mrinal@utexas.edu
The converted wave technique namely Receiver function (RF) has been utilized routinely for probing the crust and mantle structures. In the analysisof receiver functions, deterministic physical methods such as inversions are
frequently employed to refine the estimations to image the subsurface realistic
geological structure. Despite their utility, the presence of dipping and anisotropic geological structures very often complicates and can even hinder the
inversion process. To address these complexities, here we introduce a PhysicsGuided unsupervised deep learning approach for the inversion of receiver
function data. We employ unsupervised deep learning, enhanced with
implicit neural representations, allowing for the prediction of inverted Earthmodel parameters: thickness (H), S-wave velocity (Vs), anisotropy, trend,plunge, strike and dip without requiring any labeled data. For determining
the optimal model parameters, the output parameters are used in a forward
modeling scheme to simulate the receiver functions. During training, themodel iteratively adjusts and improves these parameters based on discrepancies between the simulated and observed receiver functions. Inversion resultsfrom both synthetic and field examples from the Indian shield suggest thatphysics-guided unsupervised deep learning approach is effective in inversion
tasks, particularly when dealing with intricate geological settings like dipping
and anisotropic media. With its application aimed at understanding subsurface structures, we believe that this approach holds potential to broaden thecapabilities of subsurface exploration.
poster 102
Towards a Practical Physics-Informed Neural Network
Method for End-to-End Full Waveform Inversion
HARDING, J. L., Sandia National Laboratories, New Mexico, USA, jlhardi@
sandia.gov; LIZAMA, D., Sandia National Laboratories, New Mexico, USA,dlizama@sandia.gov; YOON, H., Sandia National Laboratories, New Mexico,USA, hyoon@sandia.gov; GAUVAIN, S. J., Sandia National Laboratories,
New Mexico, USA, sjgauva@sandia.gov; PRESTON, L. A., Sandia National
Laboratories, New Mexico, USA, lpresto@sandia.gov; SEN, M. K., Universityof Texas at Austin, Texas, USA, mrinal@utexas.edu
Our aim is to explore the viability of end-to-end deep learning (DL) methods
for full waveform inversion (FWI) towards practical use for active-source seismic data shot gathers, which may be able to overcome some of the challengesof traditional FWI. We developed a DL-based FWI method that inputs elastic full-waveform shot gathers along a seismic line and outputs a 2-D P-wave
velocity model. We employ a physics-informed neural network (PINN) thatsolves the acoustic wave equation for enhanced generalizability and physicsbased inverse solution. This method takes a starting velocity model guess anditerates over solving for the acoustic wave equation via PINN with boundary and initial condition constraints, including a point source location andsource function, while fitting the input data for an updated velocity model that
honors the physics. We generate a starting velocity model using a data-drivenneural network trained on over three thousand velocity model and shot gather
pairs. We explore multiple PINN architectures, including a physics-informed(PI)-DeepONet, which is a neural operator that allows for further generalizability and flexibility for enforcing boundary condition constraints (e.g., shot
location and source function).
We find that our current methodology requires long training times foreach inversion when incorporating a PINN and the solution struggles to converge for the source frequencies of interest. The S-wave energy in our elastic data further complicates our training and appears to confuse the NN and
results in poorer solutions. Further research into PINN convergence for thewave equation, ways to limit frequency bias during learning, preprocessing
techniques for sseismic data, and training strategies (e.g., domain decomposition, frequency staging), will pave the way for future end-to-end method that

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SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 103
An Autoencoder-Based Prior for Bayesian Full Waveform
Inversion
HU, S., University of Texas at Austin, Texas, USA, sh.hu@utexas.edu; SEN, M.
K., University of Texas at Austin, Texas, USA, mrinal@utexas.edu; ZHAO, Z.,
University of Texas at Austin, Texas, USA, zeyu@utexas.edu; ELMELIEGY,
A. M., University of Texas at Austin, Texas, USA, abdelrahman.elmeliegy@
jsg.utexas.edu
To quantify the uncertainties of seismic full waveform inversion (FWI), one
can solve FWI in Bayesian inference framework by estimating the posterior probability distribution (PPD) of subsurface model given seismic data.
Sampling-based methods, e.g. Markov chain Monte Carlo (MCMC), draw
samples from the PPD of the Bayesian inference problem and those samples can be used to estimate the PPD and make inference of the model. For
Bayesian FWI problem, MCMC sampling suffers from low-convergence andinefficiency due to the high dimensionality of the model space.
In this abstract, we propose to train an autoencoder based on a subset
of posterior samples and use it as prior for Bayesian FWI problem. We designa convolutional autoencoder (CAE) with a bottleneck latent layer with only a
few variables. By training the CAE, the model space dimension can be reduced
greatly. The proposed workflow starts with a short-run adaptive MCMC chain
in physical domain model space for the FWI problem, generating a subset ofposterior samples. Then the subset samples are used to train the CAE. Lastly,
we run new MCMC chains in latent model space and use the decoder partof the CAE to transform the latent samples to physical domain samples. We
verify the feasibility of the proposed method with Marmousi synthetic model
example. Compared to physical domain MCMC chains, the proposed method
improves the efficiency of MCMC in solving Bayesian FWI problem.

Marine Seismoacoustics
Oral Session • Wednesday 1 May • 4:30 pm PacificConveners: Kasey Aderhold, EarthScope Consortium (kasey.
aderhold@earthscope.org); Helen Janiszewski, University of
Hawai‘i at Mānoa (hajanisz@hawaii.edu); Siobhan Niklasson,
Los Alamos National Laboratory (sniklasson@lanl.gov);
Charlotte Rowe, Los Alamos National Laboratory (char@lanl.
gov)
Rupture Behavior of Large Strike-Slip Earthquakes at
Equatorial Atlantic Oceanic Transform Faults: Constraints
From Hydroacoustic Data
SAMPAIO DE MELO, G., GEOMAR Helmholtz Centre for Ocean ResearchKiel, Kiel, Germany, gdemelo@geomar.de; GREVEMEYER, I., GEOMAR
Helmholtz Centre for Ocean Research Kiel, Kiel, Germany, igrevemeyer@
geomar.de; METZ, D., Comprehensive Nuclear-Test-Ban Treaty Organization,
Vienna, Austria, Dirk.METZ@ctbto.org; LANGE, D., GEOMAR Helmholtz
Centre for Ocean Research Kiel, Kiel, Germany, dlange@geomar.de; KOPP,
H., GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany,hkopp@geomar.de
Oceanic transform faults (OTFs) are tectonic strike-slip plate boundaries
that offset mid-ocean ridges by tens to hundreds of kilometers, thus reaching the globally largest oceanic offset with up to 900 km in the equatorial
Atlantic Ocean (EAO). Earthquakes along OTFs can produce moment magnitudes (Mw) of >7, with global networks monitoring in real time. Previous
studies used teleseismic data, numerical modeling, and thermal constraints
to yield characteristics of the seismic rupture behaviors along the OTFs. In
this study, we take a different approach by using hydroacoustic T-waves arriving at the International Monitoring System hydrophone triplet deployed atAscension Island and belonging to the Comprehensive Nuclear-Test-Ban
Treaty Organization (CTBTO) to study the rupture of 43 strike-slip earthquakes in the EAO. The earthquakes occurred along nine OTFs in EAO with
5.6>Mw<7.1 reported by the Global Centroid Moment Tensor catalog. We use
cross-correlation and arrival-time difference variations to identify the T-wave
source directions (back-azimuth) and compare interceptions of the direc-

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tions with mapped fault traces from multibeam bathymetric data to reveal
the total rupture length of the earthquakes. Our technique is based on soundpropagation through the ocean and provides a new alternative characterization of the rupture behavior of large strike-slip earthquakes. Our preliminary
results show rupture lengths reaching from 5.34±1.0 to 101.98±12.8 km andrupture velocities between 0.83±0.29 and 4.5±0.8 km/s, with a well-correlated
least-square regression between the rupture length and Mw. Most of the earthquakes show a unilateral rupture moving. Furthermore, we also identified atwo-stage (eastward and westward) rupture propagation to the 2016 Mw 7.1
Romanche earthquake like results published by a recent study. This complex
two-stage rupture style was similarly observed in the 2022 Mw 6.6 Vema
earthquake. Therefore, we show that rupture parameters of large strike-slip
earthquakes in OTFs can be revealed not just by commonly used teleseismic
methods but also by solely using hydroacoustic data.
Waveform Modeling of Hydroacoustic Teleseismic
Earthquake Records from Autonomous Mermaid Floats
PIPATPRATHANPORN, S., Princeton University, New Jersey, USA,sirawich@princeton.edu; SIMONS, F. J., Princeton University, New Jersey,
USA, fjsimons@princeton.edu; SIMON, J. D., Princeton University, New
Jersey, USA, jdsimon@alumni.princeton.edu
We present a computational technique to model hydroacoustic waveforms
from teleseismic earthquakes recorded by mid-column MERMAID floats
deployed in the Pacific, taking into consideration bathymetric effects thatmodify seismo-acoustic conversions at the ocean bottom and acoustic wave
propagation in the ocean layer, including reverberations. Our approach
couples axisymmetric spectral-element simulations performed for momenttensor earthquakes in a one-dimensional solid Earth to a two-dimensional
Cartesian fluid-solid coupled spectral-element simulation that captures theconversion from displacement to acoustic pressure at an ocean-bottom interface with accurate bathymetry. We applied our workflow to 1,129 seismogramsfor 682 earthquakes from 16 MERMAIDs owned by Princeton Universitythat were deployed in the Southern Pacific as part of the South Pacific Plume
Imaging and Modeling (SPPIM) project. We compare the modeled synthetic
waveforms to the observed records in individually selected frequency bands
aimed at reducing local noise levels while maximizing earthquake- generated
signal content. The modeled waveforms match the observations very well,with a median correlation coefficient of 0.72, and some as high as 0.95. We
compare our correlation-based travel-time measurements to measurements
made on the same data sets determined by arrival-time picking and ray-traced
travel-time predictions, with the aim of opening up the use of MERMAID
records for global seismic tomography via full-waveform inversion.
Decoding the Submarine Ambient Noise Field withDistributed Acoustic Sensing
FANG, J., California Institute of Technology, California, USA, jfang@
caltech.edu; WILLIAMS, E. F., University of Washington, Washington, USA,efwillia@uw.edu; YANG, Y., California Institute of Technology, California,
USA, yanyang@caltech.edu; BIONDI, E., California Institute of Technology,
California, USA, ebiondi@caltech.edu; ZHAN, Z., California Institute ofTechnology, California, USA, zwzhan@caltech.edu
Microseism constitutes a major component of seismic ambient noise on Earth.
However, a comprehensive understanding of its generation and propagation
were limited by sparse seismic instrumentations in the ocean. Distributed
acoustic sensing (DAS) is bridging this gap by enabling direct measurementsof microseism sources and seafloor sedimentary structures that host theresulting noise field. In this study, we use DAS data from offshore Oregon
to analyze the principal factors that modulate these vibrations, sources andsite amplification. With ambient noise tomography, we obtain the subsurface
velocity structures and can then calculate the relative surface wave amplification along the DAS array. The microseism source distribution can be inverted
from the directional asymmetry of noise cross-correlation signal amplitudes,
which determines the energy received by each DAS channel. The integrationof these two effects satisfactorily predicts the power spectral density (PSD)
observations. At low frequencies, the source heterogeneity is mitigated byminimal attenuation and the site amplification is dominant. Conversely, athigh frequencies, the contribution from local sources becomes crucial as well,and the PSD is a composite outcome of both site and source effects. The spatial
variations of noise can be explained by the interplay between the bathymetry, sedimentary structures and frequency-dependent ocean wave properties.
Consequently, we demonstrate that the ambient noise field on the seafloor
is shaped by both geological features below and ocean activities above. Our
approach also permits a quantitative evaluation of microseism excitation andVolume 95•

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offshore site amplification at a local scale, which provides vital insight for harnessing ocean energy and assessing undersea natural hazards.
Ocean Bottom Turbulence Evolution Observed by ArrayedObs, Dpg, and a Temperature String
CHI, W., Academia Sinica, New Taipei City, Taiwan, wchi@sinica.edu.tw;
YANG, C., Academia Sinica, Taipei, Taiwan, jwnfang@gmail.com; VAN
HAREN, H., Royal Netherlands Institute for Sea Research, Texel, Netherlands,
Hans.van.Haren@nioz.nl
Turbulent mixing in the deep sea is not well understood due to lack of longterm in-situ observation. The breaking of internal waves on sloped seafloor
topography can generate turbulence that is difficult to measure comprehensively due to its multi-scale processes, in addition to the flow-flow, andflow-topography interactions. Here we deploy a high-resolution spatiotemporal array of four ocean bottom seismometers (OBS) and a 200-m verticaltemperature string at 3000-meter water depth in a footprint of 1 X 1 km, inorder to characterize turbulence induced by internal waves. Each OBS is also
equipped with a differential pressure gauge (DPG). We found that the OBS
has recorded signals induced by near-seafloor turbulence, particularly during
typhoon periods. We propose that large-scale inertial breaking has occurredwith upslope transport speeds of 0.2 to 0.5 m s-1. We also found evidenceof small-scale bathymetry causing localized wave breaking. Data from the
DPG and the temperature string also document internal waves and turbulent
motions, with a frequency of 0.002 to 0.1 mHz. Applying beamforming-frequency-wavenumber analysis and linear regress to the arrayed Temperature
sensor and DPG, we estimated a transport speed similar to that derived fromthe OBS. Arrayed OBS can provide complementary observations to characterize deep-sea turbulence.
Searching for Low-Amplitude Shallow Tectonic Tremor in
Cascadia Using Buried Ocean Bottom Seismometers
KRAUSS, Z., University of Washington, Washington, USA, zkrauss@uw.edu;
WILCOCK, W., University of Washington, Washington, USA, wilcock@uw.edu; CREAGER, K., University of Washington, Washington, USA, kcc@
uw.eduTectonic tremor is an indicator of slow slip in the shallow portions of subduction zones, which typically lie offshore. Constraining the extent of shallow tremor is important for earthquake and tsunami hazard assessment,but offshore tremor detection is complicated by emergent oceanic signals
such as T-phases, ship noise, and tremor-like signals from bottom currents.
In the Cascadia subduction zone, shallow tremor has not been conclusively
observed. However, offshore seismic data is limited and noisy, and previous
investigations have only applied traditional land-based network methods. We
explore new techniques to detect low-amplitude tremor signals using a limited ocean bottom seismometer (OBS) network. We analyze seismic data from2014-2023 for two broadband OBS spaced 20 km apart near the deformation
front at ~45.5°N on the Ocean Observatories Initiative Regional Cabled Array.
The OBS are buried and collocated with bottom current meters. We find no
relationship between seismic noise and bottom current speeds at either OBS,
suggesting that the burial of the instruments successfully eliminates currentgenerated noise. We do find that background noise on both OBS is linearly
related to wind speeds. We use this relationship to flag time periods withincreased amplitudes in the frequency band of interest (3-10 Hz for tectonic
tremor) that cannot be attributed to heightened wind speeds. Within flagged
periods, we identify individual emergent signals as tremor candidates. For atest window from July 2018-July 2019, we find > 1,000 candidate 300-s detections present on both stations within flagged periods, most of which are visually assessed as T-phases. We will extend this approach to the full time period
and systematically classify all candidate signals as T-phases, ship noise, or
potential tremor on the basis of signal characteristics, hydrophone recordings,
and comparison to regional earthquake catalogs. In addition to investigating
tremor in shallow Cascadia, this will produce a labeled dataset of emergent
oceanic seismic signals that can be used for detection at other offshore sites
and with future networks.

Marine Seismoacoustics [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Kasey Aderhold, EarthScope Consortium (kasey.
aderhold@earthscope.org); Helen Janiszewski, University of
Hawai‘i at Mānoa (hajanisz@hawaii.edu); Siobhan Niklasson,
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Los Alamos National Laboratory (sniklasson@lanl.gov);
Charlotte Rowe, Los Alamos National Laboratory (char@lanl.
gov)
poster 34
Pushing Boundaries With Ocean Bottom Seismometers(Obs) With a Pool-Ready System: Güralp Aquarius
LINDSEY, J. C., Guralp Systems Ltd., Reading, United Kingdom, jlindsey@
guralp.com; WATKISS, N., Guralp Systems Ltd., Reading, United Kingdom,
nwatkiss@guralp.com; HILL, P., Guralp Systems Ltd., Reading, United
Kingdom, phill@guralp.com; NEDIMOVIĆ, M., National Facility for Seismic
Imaging, Halifax, Canada, mladen@nfsi.ca; CAIRNS, G., National Facility for
Seismic Imaging, Halifax, Canada, gcairns@nfsi.ca
Cabled Ocean Bottom Seismometer (“OBS”) solutions are economically challenging and autonomous OBS systems do not provide operators with seismic
data until recovery. To address this issue Güralp has developed Aquarius, anultra-low-power, free-fall OBS system, operational at any angle and with theability to transmit seismic data in near-real-time from the seafloor without
the use of cables.
The Güralp Aquarius incorporates seafloor-to-surface acoustic communication technology that allows state-of-health and noise performance interrogation during installation followed by retrieval of seismic data throughout
the deployment period.
Omnidirectional broadband seismometer components allow the
Aquarius to land and operate on steep slopes without requiring a gimbal
mechanism that inherently introduces noise and failure modes. Raw data
is recorded uncorrected for orientation to allow users to correct during
post-processing.
These unique features allow the sensor to function on uneven seafloor
as well as transmitting seismic data to the surface where the operator can use
noise characteristics, location, and orientation data to determine if the landing site is suitable.
Intelligent battery design allows for typical 18-month deployments,
with charging being possible alongside data transfer. This allows recharging, downloading and configuration simultaneously on the ship in between
deployments.
Ease of configuration, deployment, and recovery followed by simple
data processing are all central themes to the Aquarius. The capital investment
required to purchase OBS systems often means that the OBS instrument must
be adaptable to a range of use cases.
The Aquarius is in use in 6 different countries and is the unit of choicefor the Canadian OBS pool, comprising 120 units for deployment around theglobe. Aquarius units have been successfully deployed in the Mediterranean,
North Atlantic as well as the North and South Pacific. Here, we focus on themechanics of deployment and recovery for demonstrating to experienced andprospective principle investigators how this system simplifies and improves
confidence in deployment.
poster 35
Probing Further the Cascadia Initiative Data to Detect New
Offshore Events
BITO, H., University of Washington, Washington, USA, hbito@uw.edu;
DENOLLE, M. A., University of Washington, Washington, USA, mdenolle@
uw.edu; NI, Y., University of Washington, Washington, USA, niyiyu@uw.edu;
SHI, Q., University of Washington, Washington, USA, qibins@uw.edu;
KRAUSS, Z., University of Washington, Washington, USA, zkrauss@uw.edu
The Cascadia subduction zone is notorious for being seismically quiet, and its
young, hot, and buoyant subducting slab may narrow the seismogenic zone.
Permanent seismic networks that monitor the region rely heavily on onshore
stations and a few offshore stations on the OOI Regional Cabled Array. The
most spatially complete offshore dataset comes from the Cascadia Initiative(CI) experiment, which successfully deployed over 60 ocean bottom seismometers (OBS) across the entire subduction zone at ~10-month increments,
providing a total of 4-5 years of temporally fragmented data. Several attempts
were made to detect events. Stone et al. (2018) initially found ~271 between
the coast and the deformation front events using conventional network detection methods. Morton et al. (2023) used refined techniques to expand thisconventional catalog with several thousand more events but found few new
offshore events near the subduction front outside of the triple junction.
Recent advancements in Deep Learning have demonstrated notable success in earthquake detection and phase picking from seismograms, particularly in challenging environments in noisy offshore OBS data. Bornstein et al.
(2023) used transfer learning to re-train phase pickers on a curated data set of

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Seismological Research Lettersoffshore records, and Yuan et al. (2023) employed an ensemble deep-learning
approach also to improve phase picking in the same dataset. We use the latter to detect events within continuous data of the CI network. Additionally,
we utilize the PyOcto phase associator developed by Munchmeyer (2023) toassociate and crudely locate the events. We present the preliminary results ofthis search with a direct comparison between the ANSS-USGS catalogs, theStone et al. (2018), and the Morton et al. (2023) catalogs. Preliminary results
indicate that ensemble deep learning finds several additional events near the
subduction front, suggesting that this method can successfully supplement
conventional methods in the ocean-bottom setting.
poster 36
Noise on Ocean Bottom Seismometers: Observations andNew Directions
JANISZEWSKI, H. A., University of Hawaii at Manoa, Hawaii, USA,hajanisz@hawaii.edu; RUSSELL, J., Syracuse University, New York, USA,jbrussel@syr.edu; HOOTS, C., University of Hawaii at Manoa, Hawaii, USA,choots@hawaii.edu; MASO, E., University of Hawaii at Manoa, Hawaii, USA,emaso@hawaii.edu
The proliferation of broadband ocean bottom seismometer (BBOBS) deployments has generated key datasets from diverse marine environments, improving our understanding of otherwise inaccessible ocean basin structure andevolution as well as tectonic and earthquake processes occurring at the plateboundaries. Recent development of community software has made these datasets more accessible and, in turn, the community of scientists using this data
has expanded. This growth in BBOBS data collection is likely to persist withthe arrival of new seismic seafloor technologies and continued scientific interest in marine and amphibious (shoreline crossing) targets. However, the noise
inherent in BBOBS data poses a challenge that is markedly different from thatof terrestrial data. Sources of noise on the seafloor, the degree to which they
couple to the seismometer housing, and their variation with seafloor environment are often not well understood. Here, we compute global trends in
BBOBS noise (e.g., impact of water depth and seismometer type on compliance and tilt noise), and use these observations to motivate more detailed
investigations of novel instrumentation and methodologies for noise characterization and removal. This includes the utility of denoising techniques for
improving ambient-noise-based imaging, comparisons of temporary broadband OBS data with permanent cabled instrumentation, and exploration of
non-traditional (e.g. machine learning based) noise removal strategies.
poster 37
Changing Ambient Noise Patterns in the Beaufort Sea
NIKLASSON, S., New Mexico Institute of Mining and Technology, New
Mexico, USA, siobhan.niklasson@student.nmt.edu; ROWE, C., Los Alamos
National Laboratory, New Mexico, USA, char@lanl.gov; BILEK, S., New
Mexico Institute of Mining and Technology, New Mexico, USA, sbilek@nmt.
edu
The Arctic Ocean is rapidly changing in response to global climate change
forcings, leading to myriad impacts on the Arctic system, including its acoustic environment. As the Arctic warms, the seasonal patterns of the soundscape are disrupted, with changes to the thermohaline stratification of thewater column, reduced summer sea ice extent, a transition in the morphologyof sea ice toward more first-year ice, and increased exposure of the ocean towave-generating winds. The changing ambient noise conditions in the Arctic
Ocean affect ecosystems as well as our ability to use seismoacoustic data todetect acoustic sources of interest. The National Oceanic and Atmospheric
Administration (NOAA) has established a hydroacoustic station in the
Beaufort Sea as part of an effort to track ambient sound levels in United Stateswaters. Records from this hydrophone contain information about geophysical, biological and anthropogenic phenomena contributing to the soundscape.
In this project, we present progress toward mapping seasonal sound patterns
recorded at this station and evaluating their impacts on detecting regional
earthquakes recorded by the hydrophone.
poster 38
RBRquartz³ APT: Innovative Instrumentation for Enhanced
Marine Seismic Monitoring on Ocean Networks Canada’s
NEPTUNE Cabled Observatory
SCHLESINGER, A., Ocean Networks Canada, Victoria, Canada, schlesin@
uvic.ca; HEESEMANN, M., Ocean Networks Canada, Victoria,, Canada,mheesema@uvic.ca; SUN, T., Pacific Geoscience Centre, Geological Surveyof Canada, Sidney, Canada, tianhaozhe.sun@NRCan-RNCan.gc.ca; DAVIS,
E., Pacific Geoscience Centre, Geological Survey of Canada, Sidney, Canada,
earldavis@shaw.ca; DEXTER, J., Ocean Networks Canada, Victoria, Canada,

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dexter@uvic.ca; LECONTE, J., RBR Ltd., Ottawa, Canada, jean-michel.
leconte@rbr-global.com; WANG, Q., RBR Ltd., Ottawa, Canada, qi.wang@
rbr-global.com
In collaboration with Ocean Networks Canada (ONC) and the PacificGeoscience Centre (PGC), RBR Ltd. has developed the RBRquartz³ APT—aninnovative cylindrical instrument designed to measure triaxial Acceleration,
Pressure, and Temperature (APT) in underwater environments. With a compact form factor (approximately 7cm in diameter and 90cm in length), theAPT is typically deployed by pushing it vertically into sub-seafloor sedimentto optimize coupling and to mitigate current-induced noise. Distinguishingitself from conventional strong-motion seismometers, the APT features abroad bandwidth, extending from DC to its sampling rate limit. It is available
in two configurations: a low-power serial instrument suitable for extended
autonomous deployments and an advanced version equipped with ethernet
and NTP timing tailored for cabled Earthquake Early Warning (EEW) applications, each supporting maximum sampling rates of 16 and 20 samples per
second, respectively. Beyond its role in EEW, the APT serves as a multifunctional tool, enabling the concurrent investigation of geodetic, geodynamic,
seismic, and oceanographic phenomena within a unified package.
This presentation showcases data acquired from multiple APTs operated since the prototype’s initial deployment in 2015, particularly those integrated into the NEPTUNE cabled observatory as part of ONC’s EEW system. A comparative analysis is conducted by comparing APT performancewith conventional strong-motion measurements obtained from co-locatedNanometrics Titan instruments. These insights illuminate the APT’s efficacy
in EEW, other seismological, and oceanogrpahic applications. Additionally,
preliminary findings from autonomous APT deployments, in conjunction
with RBRquartz³ BPR|zero self-calibrating Bottom Pressure Recorders arepresented. These autonomous deployments are part of the Northern Cascadia
Subduction Zone Observatory (NCSZO) infrastructure, focusing on monitoring tectonic deformation offshore Vancouver Island.
poster 39
Observations From the Seafloor: Ultra-Low-Frequency
Ambient Ocean-Bottom Nodal Seismology From the Gulf
of Mexico
SHRAGGE, J. C., Colorado School of Mines, Colorado, USA, jshragge@mines.edu; GIRARD, A. J., Colorado School of Mines, Colorado, USA,agirard@mines.edu
Large-scale ocean-bottom node (OBN) arrays of 1000s of multi-component
instruments deployed over 1000s of square kilometers have been used successfully for active-source seismic exploration activities including full waveform inversion (FWI) at frequencies above 2.0 Hz. The analysis of concurrently recorded lower-frequency ambient wavefield data, though, is only justbeginning. A key long-term objective of such ambient wavefield analyses is
to exploit the sensitivity of naturally occurring sub-2.0 Hz energy to build
long-wavelength elastic models to facilitate FWI. However, doing so requires
a detailed understanding of ambient wavefield information recorded on theseafloor including the types, frequency structure and effective source distribution of recorded surface-wave modes, the near-seafloor elastic model
structure, and the sensitivity of recorded wave modes to model structure. We
present an ambient wavefield analysis of (ultra)low-frequency ambient data
(defined as <1.0 Hz) acquired on 2712 conventional OBN stations covering
2750 km2 of the Gulf of Mexico. After applying prestack ambient data preprocessing and cross-coherence interferometry workflows, we demonstrate
that: (1) the resulting virtual shot gather (VSG) volumes contain evidence for
Scholte, leaky Rayleigh and guided P-wave mode propagation between the0.001-1.0 Hz; (2) propagation remains coherent to distances of 80 km or more;and (3) surface-wave scattering from shallow salt-body structure is present in
VSG data. Overall, these observations likely have important consequences forthe early stages of initial model building for elastic FWI analysis in deep-watersettings.
poster 40
High-Resolution Acoustic Seabed Quantification with an
Autonomous Underwater Vehicle
SONNEMANN, T., Portland State University, Oregon, USA, tim@pdx.edu;
DETTMER, J., University of Calgary, Calgary, Canada, jan.dettmer@ucalgary.
ca; HOLLAND, C. W., Portland State University, Oregon, USA, charles.
holland@pdx.edu; DOSSO, S. E., University of Victoria, Victoria, Canada,sdosso@uvic.ca

Mediterranean Sea. The data are acquired by an autonomous underwater
vehicle with a towed source and towed array of hydrophones. The source emits
linear frequency modulated sweeps and the direct and bottom-reflected paths
are processed in terms of reflection coefficients as a function of frequency andangle. The processing procedure accounts for path effects and beam patternof the source. The seabed is parametrized by a sequence of one dimensionalmodels of homogeneous layers with the number of layers treated as unknown.
The homogeneous layers are considered as a porous medium via viscousgrain-shearing theory. Parameter uncertainties are quantified by Bayesianinference and results are shown for sound speed, attenuation, density, andporosity. The seabed properties agree closely with core samples at two control
points. The layering structure agrees closely with an independent sub-bottom
seismic survey. Recovering high resolution seabed properties over large areas
is shown to be feasible, which can be useful for geohazard surveys and more
broadly marine industries, navies and oceanic research organizations.
poster 41
Implementation Plan for the Cascadia Offshore Subduction
Zone Observatory
WILCOCK, W. S. D., University of Washington, Washington, USA, wilcock@uw.edu; HARRINGTON, M. J., University of Washington, Washington, USA,mikeh77@uw.edu; SCHMIDT, D. A., University of Washington, Washington,
USA, dasc@uw.edu; KELLEY, D. S., University of Washington, Washington,
USA, dskelley@uw.edu; TOBIN, H. J., University of Washington, Washington,
USA, htobin@uw.edu; DENOLLE, M. A., University of Washington,
Washington, USA, mdenolle@uw.edu; THOMPSON, M., University ofWashington, Washington, USA, usherm42@uw.edu; CRAM, G. S., Universityof Washington, Washington, USA, cramg@uw.edu; LABRADO, A. L.,
University of Washington, Washington, USA, all91@uw.edu; MANALANG,
D. A., University of Washington, Washington, USA, manalang@uw.edu;
MCGUIRE, C., University of Washington, Washington, USA, chuckmcg@
uw.edu; TILLEY, J. W., University of Washington, Washington, USA, jtilley@uw.edu; ZUMBERGE, M. A., University of California, San Diego, California,
USA, mzumberge@ucsd.edu; SASAGAWA, G. S., University of California,
San Diego, California, USA, gsasagawa@ucsd.edu
The Cascadia Offshore Subduction Zone Observatory (COSZO) is an NSFfunded mid-scale infrastructure project that will add new geophysical capabilities to NSF’s Ocean Observatories Initiative Regional Cabled Array (RCA).
The Cascadia subduction zone is an endmember among global subduction
systems which is characterized by warm young subducting lithosphere blanketed by thick sediment cover and a resulting seismogenic zone that is narrowand shallow. Geodetic observations and a dearth of offshore seismicity near
the plate interface suggest that the megathrust is locked in many places fromnear the coastline to the deformation front. However, off central Oregon, thegeophysical observations are consistent with a narrowly locked megathrustnear the deformation front that transitions to creeping behavior beneath theshelf where there are two distinct clusters of earthquakes on the megathrust,
including repeating and very low frequency earthquakes. Although the RCA
was sited off Newport, Oregon to support coastal oceanography, it is well
positioned to study the transition in megathrust locking off central Oregon.
The COSZO project will add science junction boxes to three primary nodes
on the continental slope and shelf that currently do not support seafloor
geophysical observations. Each science junction box will host a sensor suite
comprising a buried broadband seismometer, strong motion accelerometers,
a low-frequency hydrophone, a pressure gauge, calibrated pressure sensors
and a current meter, and include open ports for additional sensors. A fourth
broadband seismometer and strong motion accelerometer will be added to an
existing science junction box at another site on the shelf. Together with theseismometers and pressure gauges already on the OOI RCA at the Slope Baseand Southern Hydrate Ridge sites, this infrastructure will form a pioneering“critical mass” offshore geophysical observatory to study fault coupling anddeformation of the Cascadia megathrust and the overlying accretionary prismacross a ~100 km section offshore and support efforts to prototype offshore
earthquake and tsunami early warning.
poster 42
CHIRP Acoustic Reflection Imaging: Toward Improved
Signal Processing in Extant Glacial Lakes
WOLLER, K. L., University of Kentucky, Kentucky, USA, kevin.woller@uky.
edu; MCGLUE, M. M., University of Kentucky, Kentucky, USA, michael.
mcglue@uky.edu; THIGPEN, J. R., University of Kentucky, Kentucky, USA,ryan.thigpen@uky.edu; YEAGER, K. M., University of Kentucky, Kentucky,

We infer the structure and acoustic properties of muddy and sandy sediment layers along a 12-km seabed transect on the Malta Plateau in theVolume 95•

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USA, kevin.yeager@uky.edu; WOOLERY, E. W., University of Kentucky,
Kentucky, USA, woolery@uky.edu
Compressed-High-Intensity-Radar-Pulse (CHIRP) acoustic reflection dataacquired in lakes and other shallow water areas are generally recorded as anamplitude envelope for each trace. This format allows real-time imaging andoptimizes planning for rapid follow-up invasive sediment sampling; however, improving the signal-to-noise ratio in this format using typical vendor
visualization software is generally limited to simple gain and bandpass filtering functions. The resultant images are often capable of providing a usable
representation of the shallow sub-bottom geology, but we find further signal
processing (e.g., migration, weighted trace mixing, and/or FX deconvolution,etc.) can significantly improve overall image quality and provide enhanced
ability to discriminate and interpret subtle earthquake-related features, aswell as provide better comparisons with synthetic seismograms. However,these additional processing steps are precluded by the amplitude envelope
format. To overcome this constraint, we calculate the first derivative of theamplitude envelope and apply a bandpass filter (and sometimes rotation) tosimulate a representative full-reflection amplitude waveform, thus allowing
it to be imported into seismic data processing software for the widest rangeof signal-to-noise enhancement algorithms. For investigators without accessto, or expertise with, more sophisticated signal processing programs, these
simple fundamental procedures are often also available in many seismic interpretation software packages. We provide examples of our processing workflow
from two glacial lake basins in the western United States with a history ofseismic hazards: Convict Lake (Sierra Nevada, California) and Jackson Lake
(Grand Teton National Park, Wyoming). Both lakes have steep margin-adjacent topography and prominent axial deltas conducive to slope failures, whichappears to help shape sub-lacustrine depositional processes during earthquakes. Extensive CHIRP and long sediment core datasets from these lakes,
which differ considerably in bathymetric and stratal characteristics, provide
the feedstock for method validation.

Multidisciplinary Approaches for Volcanic Eruption
Forecasting
Oral Session • Thursday 2 May • 2:00 pm PacificConveners: Alberto Ardid, University of Canterbury(alberto.ardid@canterbury.ac.nz); Francesca Bianco, Istituto
Nazionale di Geofisica e Vulcanologia (francesca.bianco@
ingv.it); Társilo Girona, Alaska Volcano Observatory,
University of Alaska Fairbanks (tarsilo.girona@alaska.edu);
Janire Prudencio, Universidad de Granada (janire@ugr.es)
Fracture Insights and Predicting Failures: Acoustic Emission
Study in Peteroa Volcano’s Basalt RockVESGA-RAMÍREZ, A., Comisión Nacional de Energía Atómica, Buenos
Aires, Argentina, alejandravesga@cnea.gov.ar; ZITTO, M. E., Universidad
de Buenos Aires, Buenos Aires, Argentina, mzitto@fi.uba.ar; FILIPUSSI,
D., Universidad Nacional de San Martín, Buenos Aires, Argentina, filipuss@cnea.gov.ar; CAMILIÓN, E., YPF Tecnología, La Plata, Argentina, emilio.
camilion@ypftecnologia.com; PIOTRKOWSKI, R., Universidad Nacionalde San Martín, Buenos Aires, Argentina, Rosap@unsam.edu.ar; GÓMEZ,M., Universidad Tecnológica Nacional, Buenos Aires, Argentina, mpgomez@cnea.gov.ar
Acoustic Emission (AE) is a valuable non-destructive testing method for
detecting and analyzing elastic waves that occur in a material subjected toexternal forces. This research is acutely attuned to the significance of AE in
the context of volcanic monitoring and focuses on the application of AE in the
study of Basalt rock samples extracted from the Peteroa volcano in Argentina.
Uniaxial compression tests were performed on these rocks to investigate theirfracture properties under different stress states until reaching failure. AE
signals were continuously recorded during the experiments and AE parameters were utilized to evaluate the rock’s fracture process. Also, 3D locationof AE events was performed to monitor damage and map microfractures.
Additionally, secondary AE parameters FM/RA, entropy, b-value, AE energy
b-value and energy for frequency band were employed to predict and classify fracture modes, distinguishing between tensile and shear-dominatedfractures. The analysis of accumulated AE hits and their correlation with theapplied force-time curve revealed a significant increase in AE emission rateand energy around a specific critical loading level (2/3 load max approx) indi-

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Seismological Research Letterscating a progressive damage of the rock specimen, possibly associated withmicrofracturing. Furthermore, a decrease in the AE event rate was observed
when the force remained constant, suggesting changes in fracture activity during the compression process. Overall, the accumulated AE hit counts proved
to be a better indicator of intermediate damage than the accumulated energy,
showcasing their potential in tracking the evolution of compression-induced
damage in the rock. The 3D localization of AE events was conducted using
the Simulated Annealing algorithm. To improve localization accuracy andmitigate noise interference, a novel technique utilizing the Akaike information criterion (AIC) on modes obtained through Empirical Ensemble Mode
Decomposition (EEMD) of AE signals was applied.
Small Earthquakes Matter for Triggering Volcanic Unrest
GOMBERG, J., U.S. Geological Survey, Washington, USA, gomberg@usgs.
gov; PREJEAN, S., U.S. Geological Survey, Alaska, USA, sprejean@usgs.gov;
TAVERAS, O., Western Colorado University, , USA, orpat2017@gmail.com;
BODIN, P., University of Washington, , USA, bodin@uw.edu; PACHECO,
J., National University, Heredia, Costa Rica, javier.pacheco.alvarado@una.cr;
PESICEK, J. D., U.S. Geological Survey, Washington, USA, jpesicek@usgs.gov
The occurrence of large earthquakes often inspires questions about theirpotential to trigger volcanic unrest. Most prior studies that address these questions focus on case studies of a single earthquake and its impact on a specificeruption or on changes in eruptive activity at all volcanoes within a certain
distance. Instead of this earthquake-centric strategy we take a novel volcanocentered approach, in which we compare volcanic activity at a single volcano
with a calculated, continuous time series of stress changes due to all potentially
impactful earthquakes. This approach accounts for the facts that the amplitudes of stress changes from small to large earthquakes are comparable within
near-field distances, which roughly scale with earthquake source dimensions,and that the numbers of earthquakes increases as magnitude decreases. We
assume any stress change smaller than typical, ever-present, tidal values of~0.01 MPa may be neglected, and consider spatial decays consistent withearthquake-generated static, quasi-static, and dynamic stress changes. Notingthat stresses may relax over time, particularly in volcanic systems, we also consider a range of temporal decay rates, and we remove earthquakes close to thevolcano that are likely to be driven by the magmatic system itself.
Our approach is general, and we have tested it on the Turrialba, Costa
Rica and Redoubt, Alaska volcanoes, which have different tectonic settingsand eruptive styles. Turrialba has been persistently active since 2010, while
Redoubt has had two short-lived eruptive phases within decades of quiescence. Although we calculate stress changes using a very simple model, preliminary results for a range of plausible models show the summed stresses
from smaller earthquakes closer to a volcano may be more perturbing than
the stress from a single or a few larger more distant earthquakes, particularly if
considering dynamic stress changes. Connecting earthquake-generated stresschanges with volcanic unrest may be more complex than previously thought.
Toward Unbiased Volcano-Seismic Monitoring: Leveraging
Weakly Supervised Learning for Comprehensive Insights
TITOS, M., University of Granada, Granada, Spain, mmtitos@ugr.es;BENÍTEZ, M., University of Granada, Granada, Spain, carmen@ugr.es;
CARTHY, J., University of Granada, Granada, Spain, joseph.carthy@go.ugr.
es; IBÁÑEZ, J., University of Granada, Granada, Spain, jibanez@ugr.es
Real-time monitoring of volcano-seismic signals presents a multifaceted challenge. Typically, automated systems are constructed through the assimilationof vast seismic catalogues, wherein each entry is accompanied by a label denoting its source mechanism. However, the creation of comprehensive catalogues
is hindered by the prohibitive cost associated with data labeling. Althoughcurrent machine learning techniques have demonstrated considerable successin crafting predictive monitoring tools, reliance on catalogue-based learning
introduces potential bias to the system.
In our study, we demonstrate that while monitoring systems successfully
identify nearly 90% of events annotated in seismic catalogues, they may overlook additional information crucial for understanding volcanic behavior. We
discovered that weakly supervised learning approaches exhibit exceptional
capabilities by simultaneously identifying unannotated seismic traces in the
catalogue and rectifying mislabeled entries. By incorporating a system trainedwith a master dataset and catalogue as a pseudo-labeller within the frameworkof weakly supervised learning, we unveil and update information pertaining
to volcanic dynamics.
Our findings suggest the potential for advancing more sophisticatedsemi-supervised models to enhance the reliability of monitoring tools. For
instance, the exploration of advanced pseudo-labelling techniques involving data from multiple catalogues could be pursued. Ultimately, this researchwww.srl-online.org•

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paves the way for the development of universal monitoring tools capable ofaccommodating unforeseen temporal changes in monitored signals acrossvarious volcanic settings.
Volcanic Eruption Forecasts Through Seismic Data
Assimilation: The 2023 Paroxysms of Shishaldin Volcano,
AlaskaGIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.girona@alaska.edu; HANEY, M. M., U.S. Geological Survey, Alaska, USA, mhaney@
usgs.gov; FEE, D., University of Alaska Fairbanks, Alaska, USA, dfee1@alaska.
edu; POWER, J., U.S. Geological Survey, Alaska, USA, jpower@usgs.gov
Establishing connections between geophysical observables and subsurface
processes is critical for detecting volcanic unrest and anticipating eruptions.
One of the most important observables to monitor pre-eruptive volcanic activity is tremor, a more or less persistent ground vibration often recorded at active
volcanoes. Tremor may manifest or alter its characteristics before eruptions;for instance, variations in the dominant frequency, the appearance or disappearance of overtones, and changes in seismic amplitude have been observed
before eruptions. Nevertheless, similar variations can also occur during noneruptive periods or when volcanic activity decreases. Consequently, thisraises important questions: How does tremor reflect subsurface overpressure?
Can we deduce alterations in pressure underneath volcanoes by monitoring
tremor? This study introduces a novel data assimilation framework that integrates seismic data, a physics-based model of volcanic tremor, an optimization approach utilizing genetic algorithms, and time series modeling based onneural networks to track volcanic pressure changes and to produce physicsbased eruption forecasts. Specifically, our physics-based model (an extension
from Girona et al., 2019; https://doi.org/10.1029/2019JB017482) presumes
that tremor occurs when gas randomly enters shallow levels of the volcanic
plumbing system, accumulates temporarily in the subsurface, and transfers to
the surface via permeable flow. The performance of our framework is examined by analyzing the recent 13 paroxysms of Shishaldin Volcano, Alaska,
between July and November in 2023; these paroxysms are ideal for testing
our approach as they were heralded by variations in tremor. Our frameworksuggests that the recent Shishaldin paroxysms resulted from a combinationof magma ascent, escalating gas flux, and conduit sealing, leading to pressure
increases of up to several MPa and increases in eruption probability within
hours to the events. This data assimilation strategy exhibits promising potential to produce physics-based eruption forecasts from seismic tremor data innear-real-time.
Source Mechanism and Catalog Statistics for the Last
Decade of Seismicity at the Campi Flegrei Volcanic
Complex, Italy.
SACCOROTTI, G., Istituto Nazionale di Geofisica e Vulcanologia, Pisa,
Italy, gilberto.saccorotti@ingv.it; BIANCO, F., Istituto Nazionale di Geofisicae Vulcanologia, Napoli, Italy, francesca.bianco@ingv.it; CHIARABBA, C.,
Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy, claudio.chiarabba@
ingv.it; PICCININ I, D., Istituto Nazionale di Geofisica e Vulcanologia, Pisa,
Italy, davide.piccinini@ingv.it
Over the past two years, the rate, spatial extent and magnitude of seismicity
affecting the Campi Flegrei volcanic complex (Italy) have increased dramatically, accompanying ground uplift of up to 15 mm/month. Moment tensor
solutions for the most significant (Md > 3) earthquakes indicate a dominanceof double-couple (DC) and compensated linear vector dipole (CLVD) mechanisms. The statistical significance of these results is however questionable, andfor about 80% of the cases a simple DC mechanism is sufficient to explain
the data. The clustering properties of the catalog are investigated throughthe nearest-neighbor distances (NND) in a combined space-time-magnitude
metric. The early stages of the sequence are characterized by a bimodal patternof NNDs, associated with the background seismicity occurring at large interevent times and distances, and clustered events separated by short temporaland spatial ranges. Such bimodal behavior is typical of environments where
seismicity is purely driven by tectonic loading. Conversely, for the most recent
seismicity the distribution of NNDs merges into a single-mode pattern, similar to what has been observed at Long Valley Caldera (US) and interpreted
in terms of upward migration of volatile-rich volcanic fluids. The b-value ofGutenberg and Richter’s distribution does not vary significantly over time,
and the same holds for Vp / Vs ratio. The thickness of the seismogenic layer
exhibits significant lateral variations, with no clear correlation with the deformation pattern. All these elements suggest that seismicity is mainly driven
by the combination of tensile failure in the central portion of the deforming

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area, and stress accumulation along pre-existing mechanical discontinuities
at its border. The lack of long- and/or very-long-period seismicity, and thesignificance of double-couple components, indicate that either magmatic orhydrothermal fluids are not playing an active role in the seismogenic process.
Nonetheless, fault weakening and/or rupture triggering by fluid pore pressure
increase cannot be excluded.
Resonance in the Earth’s Crust as a Generation Mechanismof Very-Long-Period Volcanic Tremor
XIA, Y., Southern University of Science and Technology, Shenzhen, China,
xiayj@sustech.edu.cn; FENG, X., Southern University of Science andTechnology, Shenzhen, China, fengxp2019@mail.sustech.edu.cn; CHEN, X.,
Southern University of Science and Technology, Shenzhen, China, chenxf@
sustech.edu.cn
Volcanic tremor indicates subsurface magma transport in the conduit andalong sills. As a known precursor to volcanic eruptions, along with increased
gas emissions and ground deformation, these signals have great value for
eruption forecasting. Volcanic tremor contains a unique feature in the verylong-period (VLP) range of approximately 10 s, where the sustained vibration is harmonic and can persist for several cycles. Interestingly, these VLP
features are consistent across different volcanic edifices. Here, we show that
VLP tremor corresponds to distinct seismic resonance in the thin plate of
the Earth’s crust decoupled by subsurface sills filled with molten magma. The
feasibility of the excitation mechanism is validated through a consistent theoretical prediction of VLP spectra at Aso, Stromboli, Kilauea, Erebus, and the
newly-discovered underwater volcano near Mayotte, as well as through consistent magma viscosities obtained via petrological analysis. As well as magma
viscosity, tremor amplitude is strongly influenced by the cross-sectional
dimensions of the magma conduit. This research demonstrates that volcanic
tremor is a direct indicator of pressure variations in the magma chamber thatcan be used to forecast volcanic eruption intensity. In addition, this study
illustrates a geophysical method for evaluating subsurface magma viscosity.
Volcanic Eruption Forecasting Using Shannon Entropy:
2021 Tajogaite Eruption (Spain)
REY-DEVESA, P., University of Granada, Granada, Spain, pablord@ugr.
es; CARTHY, J., University of Granada, Granada, Spain, joseph.carthy@
ugr.es; TITOS, M., University of Granada, Granada, Spain, mmtitos@ugr.
es; BENÍTEZ, C., University of Granada, Granada, Spain, carmen@ugr.es;
D’AURIA, L., Instituto Volcanológico de Canarias, San Cristóbal de la Laguna,
Spain, ldauria@iter.es; IBÁÑEZ, J., University of Granada, Granada, Spain,
jibanez@ugr.es; PRUDENCIO, J., Universidad de Granada, Granada, Spain,
janire@ugr.es
Recent eruptions such as the one that occurred in La Palma (Spain, 2021) havedemonstrated how small eruptions disrupted the economy, environment, andhuman systems, proving how vulnerable we are to these phenomena. Despite
technological advances, it remains unclear if and when melt will solidify atdepth or ascend into shallower systems and lead to eruptions. Thus, one of
the grand challenges of volcanology is to make accurate volcanic forecasts to
reduce volcanic risk. Many volcanological observatories count on how many
events are recorded to make a probabilistic forecast, therefore, they focused
their efforts on automated event detectors and classifiers. Another approach toforecasting volcanic eruptions is to analyze geophysical data to detect changes
or patterns that can be used as precursor elements of a possible volcanic
eruption.
Previous work from Rey-Devesa et al., (2023a,b) has shown that preeruptive variations in Shannon Entropy are a confident short-term volcanic
eruption forecasting tool. SE is a statistical quantifier introduced in the framework of Information Theory and indicates the level of randomness in a system. The range of possible values of SE is between 0 and 1; SE is 0 if all theavailable data belong to the same class, in this case, it is possible to predict theclass of new data; the highest SE value is obtained when the probabilities of all
the class is the same.
In this work, we study the evolution of SE before and during the 2021
Tajogaite eruption in La Palma (Canary Island, Spain) from January 2021 to
December 2022. The results show that the SE drops several hours before theeruption starts and increases when the eruption ends. Hence, SE could be
used as a complementary tool in seismic volcano monitoring, showing its successful behavior before eruptions, giving time enough to alert the populationand prepare for the consequences of an imminent and well-predicted momentof the eruption.

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Automated Identification and Characterization of VeryLong-Period Seismic Events for Applications in Monitoring
Volcanic Activities.
GAMMALDI, S., Istituto Nazionale di Geofisica e Vulcanologia - INGV OV, Napoli, Italy, sergio.gammaldi@ingv.it; DELLE DONNE, D., Istituto
Nazionale di Geofisica e Vulcanologia - INGV - OV, Napoli, Italy, dario.
delledonne@ingv.it; CANTIELLO, P., Istituto Nazionale di Geofisica e
Vulcanologia - INGV - OV, Napoli, Italy, pasquale.cantiello@ingv.it; BOBBIO,
A., Istituto Nazionale di Geofisica e Vulcanologia - INGV - OV, Napol, Italy,antonella.bobbio@ingv.it; DE CESARE, W., Istituto Nazionale di Geofisica e
Vulcanologia - INGV - OV, Napoli, Italy, walter.decesare@ingv.it; ESPOSITO,
A., Istituto Nazionale di Geofisica e Vulcanologia - INGV - OV, Napoli, Italy,antonietta.esposito@ingv.it; PELUSO, R., Istituto Nazionale di Geofisicae Vulcanologia - INGV - OV, Napoli, Italy, rosario.peluso@ingv.it; ORAZI,M., Istituto Nazionale di Geofisica e Vulcanologia - INGV - OV, Napoli, Italy,
massimo.orazi@ingv.it
Real-time applications in seismology play a crucial role in monitoring andsurveilling active volcanoes, serving as invaluable tools for the early detectionof volcanic unrest. Particularly at open-vent active volcanoes like Stromboli
in Italy, the identification of Very Long Period (VLP) seismicity is essential.
VLP seismicity, often associated with mild and persistent explosive activity,
holds significance in volcano monitoring, with variations in occurrence rate
and magnitude serving as potential precursors to an eruption.
In this study, we present a novel method for the automatic real-time
detection and characterization of VLP seismicity at Stromboli. The detection algorithm relies on Three-Component Amplitude (TCA), derived fromwaveform polarization and spectral analysis of continuous recordings. Thisapproach provides crucial information such as time of detection, azimuth,
incidence, amplitude, and frequency of the identified VLP events.
Furthermore, VLP amplitudes obtained from all monitoring network
stations, presented as peak-to-peak amplitudes and mean square amplitudes,
are employed for an automated localization of the seismic VLP source. The
results of our automatic detection algorithm are then compared with thoseobtained through manual and automatic inspections of seismic records, aswell as with VLP time histories from existing published datasets.
The comparative analysis reveals that the VLP detection time series
generated by our automatic algorithm effectively mirrors fluctuations in VLP
activity observed manually by operators over an approximately 20-year period.
This success allows for the integration of our approach into the real-time processing framework employed at Stromboli for ongoing volcano surveillance.
Volcanic Eruption Forecasts Through Seismic Pattern
Recognition: The 2023 Paroxysms of Shishaldin Volcano,
AlaskaGIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.girona@alaska.edu; BURGOS, V., University of Alaska Fairbanks, Alaska, USA,vburgosdelgado@alaska.edu
Identifying patterns within geophysical data is critical for the detection of
volcanic unrest and the forecasting of eruptions. Seismicity, encompassing
volcano-tectonic earthquakes, long-period events, and tremor, among othergeophysical signals, provides pivotal information about the state of unrestof a volcano. Tremor, specifically, tends to exhibit variations in its characteristics during eruption run-up, including changes in dominant frequency,
the emergence or disappearance of overtones, and fluctuations in seismic
amplitude. These variations raise the following question: Can we consistently quantify the probability of eruption based on the recognition of seismic tremor patterns? To address this question, we introduce a pattern recognition based-framework (building upon the work of Dempsey et al., 2020
[https://doi.org/10.1038/s41467-020-17375-2]; Ardid et al., 2023 [https://doi.
org/10.21203/rs.3.rs-3483573/v1]; and Girona and Kyriaki, In Review) thatmerges seismic features from tremor data (e.g., dominant frequency, kurtosis, seismic amplitude, Shannon entropy) with several supervised machinelearning models and Monte Carlo simulations to estimate the probability ofan imminent eruption and its uncertainty. In particular, our framework integrates logistic regression, k-nearest neighbors, linear discriminant analysis,
decision trees, random forest, support vector machine, and neural networkmodels; and is designed to enable retraining, automatically updating the models whenever a new paroxysm takes place. The performance of our approachis assessed using the recent 13 paroxysms of Shishaldin Volcano, Alaska,
occurring from July to November 2023, all of which were preceded by seismic
tremor with escalating amplitude. We find that our framework captures successfully the seismic data trends that correlated with imminent paroxysms,
reflected in a noticeable and consistent increase in the probability of eruption
before the actual eruption occurs. This strategy exhibits promising potential

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Enhancing Eruption Forecasting at Axial Seamount With
Real-Time, Machine Learning-Based Seismic Monitoring
WANG, K., Columbia University, New York, USA, kw2988@ldeo.columbia.
edu; WALDHAUSER, F., Columbia University, New York, USA, felixw@ldeo.
columbia.edu; SCHAFF, D., Columbia University, New York, USA, dschaff@ldeo.columbia.edu; TOLSTOY, M., University of Washington, Washington,
USA, mt290@uw.edu; WILCOCK, W., University of Washington, Washington,
USA, wilcock@uw.edu; TAN, Y., Chinese University of Hong Kong, Hong
Kong, China, yjtan@cuhk.edu.hk
Axial Seamount, an extensively instrumented submarine volcano, lies at theintersection of the Cobb-Eickelberg hot spot and the Juan de Fuca Ridge.
Since late 2014, the Ocean Observatories Initiative (OOI) has operated aseven-station cabled Ocean bottom seismometers (OBS) array that captured
Axial’s last eruption in April 2015. This network streams data in real-time,
facilitating seismic monitoring and analysis for volcanic unrest detectionand eruption forecasting. In this study, we introduce a machine learning(ML) based real-time seismic monitoring framework for Axial Seamount.
Utilizing both supervised and unsupervised ML techniques, we constructed
a comprehensive, high-resolution earthquake catalog, and effectively discriminated between various seismic and acoustic events. These signals include
earthquakes generated by different physical processes, acoustic signals oflava-water interaction, and oceanic sources such as whale calls. Notably, ourunsupervised ML analysis revealed two subgroups of earthquakes that havedifferent spectral features and spatiotemporal behavior before and during
the 2015 eruption. We interpret them as being driven by two distinct mechanisms: earthquakes on the caldera ring faults triggered by tidal stress changes,
and mixed frequency earthquakes (MFEs) generated by brittle crack opening followed by influx of magma or volatile. Our system integrates ML- anddouble-difference based catalog construction and semi-supervised event classification in real time. Operational since 2022, it enables the discriminationand tracking of different seismic events as they occur, including precursory
MFEs that potentially indicate the preparation of an eruption and seafloor
impulsive events that can be used to track magma outflows during an eruption. The high-resolution earthquake catalog and real-time analysis capability
complement the current deformation-based long-term forecasting methods,
providing valuable short-term constraints that may enhance eruption forecasting at Axial Seamount and potentially other volcanoes.

Multidisciplinary Approaches for Volcanic Eruption
Forecasting [Poster Session]
Poster Session • Thursday 2 May
Conveners: Alberto Ardid, University of Canterbury(alberto.ardid@canterbury.ac.nz); Francesca Bianco, Istituto
Nazionale di Geofisica e Vulcanologia (francesca.bianco@
ingv.it); Társilo Girona, Alaska Volcano Observatory,
University of Alaska Fairbanks (tarsilo.girona@alaska.edu);
Janire Prudencio, Universidad de Granada (janire@ugr.es)
poster 46
Information Theory in the Context of Volcano Seismic
Singals for Forecasting PurposesBENÍTEZ, M., Universidad de Granada, Granada, Spain, carmen@ugr.es;
REY-DEVESA, P., Universidad de Granada, Granada, Spain, pablord@ugr.
es; PRUDENCIO, J., Universidad de Granada, Granada, Spain, janire@ugr.
es; MARCELINO, M., Universidad de Granada, Granada, Spain, mmtitos@
ugr.es; IBÁÑEZ, J., Universidad de Granada, Granada, Spain, jibanez@ugr.es
Information Theory is a field that addresses how to send and reconstructmessages, through a noisy channel, with low probability of error, and how
to quantitatively measure the information contained in this message. Studies
performed by Nyquist and Hartley, found that, logarithmic function is themost appropriate to measure the amount of information contained in a message. Shannon complete these studies and propose the Entropy as the measureof the information of a random variable, were each of the possible outcomesof the variable has a defined probability of occurrence and the value associatedwith the outcome is aleatory.

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Important word in Information theory are: Information is related withthe knowledge obtained when a specific event is observed, for example, realizations of a random variable with low probability are less expected and give
more information that one with high probability. Uncertainty is the amountof information we expect an experiment to reveal. For uniform probabilities
distribution the result is unpredictable and the uncertainty is maximum, andif the distribution of probabilities is more concentrated then the result is morepredictable and there is a lower uncertainty. Entropy indicate the amount of
uncertainty associated with a variable when only its distribution is known.
The entropy provided a mathematical way of determining the information
contained in a message. In the context of Information Theory, the Information
is independent of the previous knowledge and only depend of the source via
the probability function of each of the symbols issued.
We propose the application of different definitions of entropy proposedin the literature to the time series of seismic signals of volcanic origin. Taking
into account previous works developed, we consider that it is of interest to
study the evolution throughout the different evolutionary periods of volcanoes. We propose the comparative study of differential entropy, Shannon
entropy, approximation entropy and Rényi entropy.
poster 47
Unraveling Dynamical Influences on Volcanic Structures
Through Seismic Signatures
BRENOT, L., Université libre de Bruxelles, Bruxelles, Belgium, laure.brenot@
ulb.be; CAUDRON, C., Université libre de Bruxelles, Bruxelles, Belgium,corentin.caudron@ulb.be; GIRONA, T., University of Alaska Fairbanks,
Alaska, USA, tarsilo.girona@alaska.edu; LECOCQ, T., Royal Observatory of
Belgium, Bruxelles, Belgium, thomas.lecocq@ulb.be; YATES, A., Université
libre de Bruxelles, Bruxelles, Belgium, alexander.yates@ulb.be; WINDER, T.,
University of Cambridge, Cambridge, United Kingdom, tebw2@cam.ac.uk;
RAWLINSON, N., University of Cambridge, Cambridge, United Kingdom,
nr441@cam.ac.uk; HANEY, M. M., Alaska Volcano Observatory, Alaska,
USA, mhaney@usgs.gov; SHENG, Y., University Grenoble Alpes, Grenoble,
France, yixiao.sheng@univ-grenoble-alpes.fr; BRENGUIER, F., University
Grenoble Alpes, Grenoble, France, florent.brenguier@univ-grenoble-alpes.
fr; MORDRET, A., University Grenoble Alpes, Grenoble, France, aurelien.
mordret@gmail.com; AOKI, Y., University of Tokyo, Tokyo, Japan, yaoki@
eri.u-tokyo.ac.jp; JÓNSDÓTTIR, K., Icelandic Meteorological Office,Reykjavik, Iceland, kristin.jonsdottir@vedur.is
Detecting the transition from volcanic quiescence to unrest is a crucial but
challenging task for volcano monitoring agencies. Using insights drawn fromcontinuous seismic records, this study explores the long-term dynamics of
two volcanoes with the goal of tracking the transition to renewed activity.
First, we investigate seismic velocity changes (dv/v) over time through crosscorrelation of ambient seismic noise using the MSNoise package [Lecocq et al.
2014; https://doi.org/10.1785/0220130073] with the Wavelet Cross-Spectrum
method [Mao et al. 2020; https://doi.org/10.1093/gji/ggz495]. Second, we
examine the kernel sensitivity of the surface waves to identify potential depths
related to dv/v changes based on wave frequency and realistic velocity models.
Finally, we estimate the associated seismic attenuation to identify subsurface
stress changes over time.
By applying these methods to our case studies, we observe and compare
different behaviors, which highlights the importance of continuous monitoring of subsurface variations over time. For instance, we found a decreasing
trend of dv/v at around 2 km depth since August 2021 beneath Askja volcano(Iceland), coinciding with an uplift of up to 65 cm by September 2023 andwith an increased seismicity rate. The sudden shift in the trend of dv/v contrasts with the gradual long-term deflation that has been observed in the lastfew decades.
The 2016 Kumamoto earthquake impacted the Aso volcano in Japan,
causing a decrease in dv/v of 0.5%. The seismic velocity changes suggest ahealing process initiated post-earthquake, which stopped 6 months after with
Aso eruption (0.3% dv/v drop).
During the summer of 2021, there was seismic unrest at Gareloi (Alaska)[AVO website, 2005; https://avo.alaska.edu]. This unrest was detected with theappearance of tremors in addition to persistent long-period activity. The dv/v
result confirmed this observation with a 1% drop around 3 km depth. This
helps to establish a baseline for normal volcanic behavior and contextualize observations, with the aim of characterizing the seismic signatures andchanges associated with volcanic unrest.

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poster 48
Simulating Ground Deformation From Magma Migration
Utilizing a Dipole Source
CANNAVO’, F., Istituto Nazionale di Geofisica e Vulcanologia, Catania, Italy,
flavio.cannavo@ingv.it
The ability to detect and monitor magma movement in volcanic areas is vitalfor predicting eruptions and mitigating associated risks. This research focuseson the simulation of ground deformation resulting from magma migration
using a new dipole source within volcanic regions. Typically, predictive models, either analytical or numerical, incorporating internal Earth forces suchas pressure and volume changes, are employed to infer ground deformation.
Dynamic patterns associated with volcanic deformation sources, such as
inflation and deflation for volumetric sources, and opening and closing fordyke-type sources, are well-established. This study seeks to present an analytical solution for surface deformation caused by the migration of a volumetricsource, specifically applicable to minor movements in an elastic half-space.
The proposed model resembles a volumetric dipole, characterized by an oriented axis connecting the source’s initial and final positions. This approachfacilitates the modeling of ground deformation based on source migration,and the estimation of source migration from measured ground deformation
through data inversion. To evaluate the dipole solution, a comparison is madewith the fundamental volumetric source in terms of its peculiarities, capabilities, and applicability. The examination of continuous deformation data from
GNSS stations on Mt. Etna discloses that a dipole source becomes active several days prior to the December 2018 eruption, providing valuable insight into
the identification of the final magma ascent.
poster 49
Surface-Wave Relocation and Characterization of theOctober 2023 Izu Islands, Japan Earthquake Swarm
DEANE, C. A., U.S. Geological Survey, Colorado, USA, cdeane@usgs.
gov; EARLE, P., U.S. Geological Survey, Colorado, USA, pearle@usgs.gov;
PESICEK, J. D., U.S. Geological Survey, Washington, USA, jpesicek@usgs.
gov; PREJEAN, S. G., U.S. Geological Survey, Alaska, USA, sprejean@usgs.
gov; SHELLY, D. R., U.S. Geological Survey, Colorado, USA, dshelly@usgs.
gov; YECK, W., U.S. Geological Survey, Colorado, USA, wyeck@usgs.gov
From October 1-8, 2023, a moderate-magnitude (4.1 < M <= 6.1) earthquake
swarm occurred in the Izu Islands region of Japan. The swarm included 151
shallow events (depth < 30 km) catalogued by the U.S. Geological Survey andwas categorized by three M >= 6 earthquakes and a cluster of 15 M 4.3 toM 5.4 earthquakes. Many of the earthquakes in the final cluster generated
subsequent T-phases and were associated with tsunami waves, one of which
had a maximum amplitude of 60 centimeters. However, tsunamigenesis formoderate-magnitude earthquakes is unlikely and suggests that the ocean
displacements were generated from a volcanic or landslide source. Shallowdepth earthquakes in the Izu Islands region occur near seamounts and volcanic islands, but the precise characterization of volcano-related seismicity
can be challenging with no local seismic monitoring. Leveraging a surfacewave relative relocation approach, we estimated precise epicentroid locationsof seismic events from the swarm using over 100,000 regional-to-teleseismic
surface-wave relative time shifts. Epicentroid locations show a north-northwest migration of earthquakes over eight days that initiated to the west of
the Sofugan seamount. Moment tensor solutions for several swarm events are
consistent with normal-faulting source mechanisms, while others are consistent with a vertical tension axis compensated-linear-vector-dipole (CLVD).
The locations of epicentroids with CLVD mechanisms relative to those withnormal-faulting mechanisms suggest the presence of two different but concurrent volcanic processes. The linear positioning of the normal-faulting eventsand the presence of CLVD mechanisms are consistent with diking activity
and caldera collapse, respectively. Our relative relocation analysis of the Izu
Islands swarm demonstrates the ability of surface-wave analysis to measure
volcanic unrest and characterize subsequent volcanic behavior. Implemented
in near real-time, surface-wave relative relocation may improve volcano monitoring efforts by providing more precise earthquake locations, time history,
and characterization of seismicity in remote areas.
poster 50
The Relationship Between a 2022-2023 Magmatic Intrusion
at Aniakchak Caldera and the 2021 m8.2 Chignik
Earthquake, Alaska
GRAPENTHIN, R., University of Alaska Fairbanks, Alaska, USA,rgrapenthin@alaska.edu; PARAMESWARAN, R., University of Alaska
Fairbanks, Alaska, USA, rmparameswaran@alaska.edu; ANGARITA, M.,
University of Alaska Fairbanks, Alaska, USA, mfangaritasr@alaska.edu;

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SHREVE, T., University of Alaska Fairbanks, Alaska, USA, tlshreve@alaska.
edu; CHENG, Y., University of Alaska Fairbanks, Alaska, USA, ycheng4@
alaska.edu; POWER, J., U.S. Geological Survey, Alaska, USA, jpower@usgs.
gov; ZHUO, Z., Michigan State University, Michigan, USA, zhuozech@msu.
edu; LOPEZ, T., University of Alaska Fairbanks, Alaska, USA, tmlopez@
alaska.edu; ELLIOTT, J., Michigan State University, Michigan, USA, ellio372@
msu.edu; FREYMUELLER, J. T., Michigan State University, Michigan, USA,freymuel@msu.edu
A sequence of earthquakes at Aniakchak Caldera (AC), Alaska, began in
October 2022 and was accompanied by rapid ground deformation, firstobserved in February 2023. AC is located only ~160 km from the epicenter of
the July 2021 M8.2 Chignik megathrust earthquake, for which co-seismic fault
slip >6 m has been modeled; the observed immediate rapid postseismic afterslip slowed in early 2022. This spatio-temporal relationship, especially if considering down-dip afterslip, motivates us to ask whether the Chignik earthquake and its postseismic deformation contributed to the unrest episode at
AC, and why the neighboring Veniaminof Caldera, with an eruption in April
2021, has shown no or only very recent (Dec 2023-Jan 2024 deep-long period
events) unrest? This is in line with global statistical analyses (e.g., Nishimura,2021), which suggest that eruption likelihood doubles within 5 years for volcanoes within 200 km of M>7.5 earthquakes.
Our L-band interferograms spanning 2022-2023 resolve >60 cm LOS
shortening inside the Aniakchak caldera and GNSS installed in summer 2023
recorded the stop of deformation in September 2023. We can explain the
deformation with a shallow spheroidal inflation source centered under AC at~2.8 km depth with a volume change of about ~28 Mm3. Static normal stress(tensile) increased at both calderas after the Chignik event (0.1-0.3 MPa), suggesting unclamping, which is favorable for magma ascent / bubble formation.
While AC earthquakes relocated with a revised velocity model show that DLP
events started a few weeks after the Chignik earthquake, eventually culminating into shallow volcano tectonic earthquakes, the full catalog spanning 19972023 contains sequences of DLP events without large earthquakes, providing only a weak first order link between the earthquake and volcanic unrest.
Here, we explore connections between the earthquake and the magmaticunrest through modeling of time-delayed magmatic processes such as bubble
formation and magma migration. We furthermore investigate the impact of
postseismic deformation and related additional tensile stress increase on theseprocesses.
poster 51
Characterization of the Onset of the 2021 Great Sitkin
Dome-Building Eruption Through the Trans-Dimensional
Bayesian Inversion of LP Seismicity
KIM, K., University of Alaska Fairbanks, Alaska, USA, kkim39@alaska.edu;
GIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.girona@alaska.edu; ANDERSON, K. R., U.S. Geological Survey, California, USA,
kranderson@usgs.gov
Long-period (LP) volcanic seismicity and tremor are thought to be triggeredby the subsurface transport of magmatic and/or hydrothermal fluids. A mechanistic model of LP events and tremor, called the “leaky gas pocket model”,
was proposed by Girona et al. (2019). This model shows that the transport ofgas through permeable materials (e.g., lava domes) triggers spontaneous LP/
tremor-like pressure oscillations. Building upon the leaky gas pocket model,
our project addresses two key questions regarding LP seismicity and its relation to volcanic activity: (1) To what extent can the leaky gas pocket model
accurately elucidate the physical properties of a volcanic dome? (2) Can thevariation of physical properties during the onset of a dome-building eruption
be explained by the inversion of LP seismicity? To explore these questions, we
integrate the leaky gas pocket model with a reversible-jump (trans-dimensional) Markov Chain Monte Carlo (RJ-MCMC) framework to invert LP seismicity recorded during the early-stages of the 2021 dome-building eruption ofGreat Sitkin volcano (Alaska). With this approach, we aim to comprehensively
quantify the probability density function of the model parameters for each LP
event; these parameters include dome thickness and permeability, gas flowrate and temperature, and seismic attenuation factor, among others. Our preliminary results suggest a gradual accumulation of gas beneath the dome anda possible decrease of dome thickness around the start of the eruption (July 23,2021). This is consistent with a pre-eruptive gas accumulation and pressurization in the shallow volcanic conduit, which we determine in the range from~102 Pa to ~104 Pa. The gas flow rate is constrained within the range from 5
ton/day to 200 ton/day, representing the minimum amount of gas supplied
to the base of the dome (more gas might be released with no contribution toseismicity). Our analysis represents a pioneering physics-based approach to

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poster 52
How Is Differential Shannon Entropy Related to Volcanic
Processes?
REY-DEVESA, P., University of Granada, Granada, Spain, pablord@ugr.es;
GIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.girona@alaska.edu; PRUDENCIO, J., University of Granada, Granada, Spain, janire@
ugr.es; IBÁÑEZ, J., University of Granada, Granada, Spain, jibanez@ugr.es;
BENITEZ, C., University of Granada, Granada, Spain, carmen@ugr.es
Previous studies show that Shannon Entropy (SE) calculated on continuousseismic records can be used to track unrest and eruptive activity at active volcanoes (Rey-Devesa et al., 2023 a, b). SE usually remains constant, and decays
for a short-term period before an eruption occurs, reaching minimum values
just in the run-up to a paroxysm. This has been observed in a large set of different volcanoes around the globe, although it remains unclear how SE relates
to physical processes and how it can be used for improving routine forecasting
strategies.
SE, or Differential Shannon Entropy (DSE) when the source is continuous, is used in information theory to understand the uncertainty of a sourceof information (Shannon, 1948). The uncertainty is related to the amount of
information required for describing the next element in a sequence, or how
predictable a sequence is. Thus, a very probable event is translated as a low
value of uncertainty and DSE. In this context, we can interpret the decay in the
DSE of the seismic signal as an indicator of a reorganization happening in the
volcanic system, approaching an eruptive outcome. However, in the real-timemonitoring scenario, the performance of the feature needs some fine-tunning,since signals usually contain different types of noise (wind, tides, and storms)
that can also generate a decay in the DSE.
In this work, we propose a synthetic analysis of the DSE, studying how it
varies with the type and characteristics of noise. The goal is to identify if DSE
can detect changes in the systematic noise. In addition, we apply the conclusions to a real-life scenario, the eruption of Shishaldin in 2023, associating
every decay of the DSE in one year record to different sources or external
processes.
Preliminary results show that more predictable noises imply lower values of DSE. We also see that the amplitude of the decay and the frequency
band containing the energy of the signal are relevant features to associate thedecay with their sources.
A better understanding of DSE and its evolution is crucial for improving
the quality of the DSE as a volcanic eruption monitoring tool.
poster 53
Systematic Investigation and Comparison of the 2018 and2020 Kīlauea Volcano Eruptions Based on Ambient Seismic
Noise Analysis
VINARSKI, E., University of Miami, Florida, USA, elizabeth.vinarski@earth.
miami.edu; LIN, G., University of Miami, Florida, USA, glin@earth.miami.
edu
Detection of precursors for volcanic eruptions is crucial for mitigating thesoci- etal and environmental impacts of these destructive geological hazards.
Seismic ambient noise analysis has become increasingly popular for revealing temporal velocity variations before and after volcanic eruptions. Thesevariations may inform us of crustal perturbations due to the movement ofmagma, gas, or flu- ids. In 2018, Kīlauea volcano in Hawai’i experienced its
largest Lower East Rift Zone eruption and summit caldera collapse in at least
200 years. After just over a year of quiescence, its summit underwent a seriesof much smaller eruptions from December 2020 to September 2023. In thisstudy, we systematically investigate and compare the 2018 and 2020 eruptions
by applying seismic ambient noise analysis.
We download continuous waveform data from the Incorporated
Research Institutions for Seismology (IRIS), recorded by the Hawaiian
Volcano Obser- vatory broadband seismometers in the summit area and the
Middle East Rift Zone (MERZ) of Kīlauea. After pre-processing of the data,
we perform the stretching technique to solve for velocity changes from 2015
through 2023. We find that while there are velocity decreases for the summit
stations during the 2020 eruption, they are significantly smaller than thosecorresponding to the 2018 eruption. We also observe large variations for the
MERZ stations during the 2020 eruption, indicating magma presence andmigration. Our results sug- gest that combination of horizontal and verticalcomponents in cross-correlation analysis can provide additional knowledge
on magmatic activity. In addition, our estimated velocity variations are larger
than those from previous studies in general. GPS and InSAR data are inte-www.srl-online.org•

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grated to provide further analysis of our results. Our study illustrates how thesubsurface velocity structure varies in response to volcanic eruptions and may
offer new insight into how a volcano readjusts itself after a large eruption.
poster 54
Real-Time Seismic Estimation of Vei: Improving Reduced
Displacement & Introducing the Mvo Energy Magnitude
Scale
THOMPSON, G., University of South Florida, Florida, USA, thompsong@usf.edu; MCNUTT, S. R., University of South Florida, Florida, USA, smcnutt@
usf.edu; RODRIGUEZ CARDOZO, F. R., University of South Florida, Florida,
USA, felixr1@usf.edu
The Volcanic Explosivity Index (Newhall and Self, 1982) was conceived as acrude magnitude scale for past volcanic eruptions, based on field observations
such as volume of material ejected, and eruption column height. Within daysof the Hunga Tonga eruption in January 2022, there was online discussion
about whether to classify it as a VEI 5 based on erupted material (with an
unknown volume in the ocean) or VEI 6 based on pressure and gravity waves
that propagated many times around the globe, similar to the VEI 6 eruptionof Pinatubo in 1991. There were also attempts to estimate VEI based on seismic data. However, these were not new, as there were previous attempts tocorrelate ash column height with seismic amplitude (McNutt 1994) using ameasure called “reduced displacement”, which was described as “a magnitude
scale for volcanic tremor”. Moreover, in year 2000 a real-time volcano-seismic
magnitude scale was implemented at the Montserrat Volcano Observatory.
Reduced pressure is another measurement that can be used when infrasoundor barometric data are available. We propose a simple seismo-acoustic VEIestimator based on reduced displacement, reduced pressure, and energy magnitude, and have implemented these as part of a Python/ObsPy package.

Network Seismology: Recent Developments, Challenges
and Lessons Learned
Oral Session • Wednesday 1 May • 2:00 pm PacificConveners: Blaine Bockholt, Idaho National Laboratory(blaine.bockholt@inl.gov); Renate Hartog, Universityof Washington (jhartog@uw.edu); Kristine L. Pankow,
University of Utah (pankowseis2@gmail.com); Adam Ringler,
U.S. Geological Survey (aringler@usgs.gov); Dmitry Storchak,International Seismological Centre (dmitry@isc.ac.uk)
ISC: Collaborating With Seismic Networks Worldwide
STORCHAK, D., International Seismological Centre, Thatcham, United
Kingdom, dmitry@isc.ac.uk; HARRIS, J., International SeismologicalCentre, Thatcham, United Kingdom, james@isc.ac.uk; DI GIACOMO, D.,International Seismological Centre, Thatcham, United Kingdom, domenico@
isc.ac.uk; GARTH, T., International Seismological Centre, Thatcham,
United Kingdom, tom.garth@isc.ac.uk; GALLACHER, R., International
Seismological Centre, Thatcham, United Kingdom, ryan@isc.ac.uk; POIATA,
N., International Seismological Centre, Thatcham, United Kingdom, natalia.
poiata@isc.ac.uk
The mission of the International Seismological Centre (ISC) is to produce themost long-term and complete Bulletin of instrumentally recorded seismicity on a global scale by running parametric data exchange with ~150 seismic networks in ~100 countries. We also take additional measurements frompublicly available waveforms to improve event source parametrization. For
instance, we aim to better constrain the depths of moderate to large seismic
events by taking the depth phase arrival time measurements and calculating
Probabilistic Point Source Model solutions (ISC-PPSM). We also started taking automated IASPEI-compliant amplitude and period measurements tocomplement similar measurements supplied by networks.
In addition, we produce a number of data products that stem from the
ISC Bulletin and allow the ISC to assist several areas of research. These include
the ISC-EHB dataset (1964-2021), ISC-GEM catalogue (1904-2019), IASPEI
Reference Event List (GT, 1959-2020) and ISC Event Bibliography (19042024). We also maintain supplementary services: the Electronic Archive ofPrinted Station/Network bulletins, the International Seismological Contacts,
and the ISC Dataset Repository. We look forward to further extending ourcollaboration with both permanent and temporary networks worldwide.

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The International Monitoring System Sustainment: A
Technical Strategy
PÉREZ-CAMPOS, X., Comprehensive Nuclear-Test-Ban Treaty
Organization, Vienna, Austria, xyoli.perez.campos@ctbto.org; SID AHMED,
Y., Comprehensive Nuclear-Test-Ban Treaty Organization, Vienna, Austria,
yacine.sid.ahmed@ctbto.org; KRAMER, A., Comprehensive Nuclear-Test-Ban
Treaty Organization, Vienna, Austria, alfred.kramer@ctbto.org; ZAMPOLLI,
M., Comprehensive Nuclear-Test-Ban Treaty Organization, Vienna, Austria,
mario.zampolli@ctbto.org; WOODS, V. T., Comprehensive Nuclear-Test-Ban
Treaty Organization, Vienna, Austria, vincent.woods@ctbto.org; ROCCO,
G., Comprehensive Nuclear-Test-Ban Treaty Organization, Vienna, Austria,
guillermo.rocco@ctbto.org; STEFANOVA, S., Comprehensive NuclearTest-Ban Treaty Organization, Vienna, Austria, stefka.stefanova@ctbto.org;
TEAMS, I., Comprehensive Nuclear-Test-Ban Treaty Organization, Vienna,
Austria, thomas.hoffmann@ctbto.org
The International Monitoring System (IMS) of the Comprehensive Nuclear
Test Ban Treaty Organization (CTBTO) consists of 170 seismic, 60 infrasound,
11 hydroacoustic, 80 radionuclide stations and 16 radionuclide laboratories.
Currently, the network is 90% complete. The network was initially developed,
and deployment began in 1996 when the Treaty was opened for signature.
During the first 12 years, the focus was on the installation and certification of
the stations; operation and maintenance have been part of the daily focus of
the IMS. However, after 25 years of continuous operation, many stations arereaching the end of their life cycle and will need recapitalization. Therefore,
a mid- and long-term sustainment strategy has been developed. This work
will present the technical basis for such a strategy. In the first place, the goal
is to identify the status of each station and to assess the risk of downtime in
the next two years, six years, and beyond. Then, prioritization takes place todefine an action plan for the two immediate years and a foreseen scenario forthe mid- and long-term strategy. The stations’ status and risk assessment aredone every six months, and the action plans are reviewed annually.
The Chilean Seismic Network: An Update
BARRIENTOS, S. E., Universidad de Chile, Santiago, Chile, sbarrien@csn.
uchile.cl; BRAVO, F., Universidad de Chile, Santiago, Chile, fbravo@csn.
uchile.cl; KOCH, P., Universidad de Chile, Santiago, Chile, pkoch@csn.uchile.
cl; BAEZ, J. C., Universidad de Chile, Santiago, Chile, jcbaez@csn.uchile.cl;
RIVET, D., University Côte d’Azur, Sophia Antipolis, France, diane.rivet@
geoazur.unice.fr; TEAM, C., Universidad de Chile, Santiago, Chile, sbarrien@
csn.uchile.clMore than 500 instruments (accelerometers, BB, and GNSS devices), comprise the National Seismic Network, of which 118 are six-component (BB +strong ground motion) transmitting their data in real-time to the Data Center.
The network includes two devices installed on the Chilean Pacific Islands,
one station in the Antarctic Peninsula, and those stations that are part of theIntegrated Plate Boundary Observatory in northern Chile (IPOC).
The main mission of the CSN is to rapidly characterize -within 5 minutesof O.T.- the location and size of earthquakes M≥3.7, particularly those that
could generate tsunamis. Because the main thrust region is mostly concentrated between the trench and the coast, with an average width of about 150
km, the monitoring system is distributed all along the country and includes
real-time GNSS capabilities, both on-site position estimations as well as at a
central server, based on Precise Point Positioning techniques. In near-realtime applications, as well as in the near field, unsaturated direct-displacementestimations based on GNSS observations become critical for the determination of fault finiteness of M ~ 7 (or larger) earthquakes that affect the coastal
part of the country, with their associated significant tsunamigenic potential.
GNSS records also facilitate more robust estimates of magnitude and W-phasesolutions, as well as finite fault models.
This network allows the detection of M>3 earthquakes along the country, including regions not previously monitored permanently. Additional
efforts are concentrated on EEW for central Chile and, during 2023, we
installed three DAS systems (fiber-optic seismology) with Geoazur to increase
the observation capabilities underwater, where most of the large-magnitude
seismicity is generated.
Geophysical and Sea Level Monitoring in Puerto Rico
HUERFANO, V. A., Puerto Rico Seismic Network, Puerto Rico, USA, victor@
prsnmail.uprm.edu
The Puerto Rico Seismic Network (PRSN) and the Puerto Rico Strong Motion
Program (PRSMP) make up the PR network which is the regional authority
for monitoring ground shaking in Puerto Rico and the Virgin Islands. The
mission of the PR is to monitor and rapidly determine the parameters of all

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earthquakes, support the TSP (Tsunami Service Provider) and help the local
and federal monitoring and emergency authorities to disseminate alerts in
the Area of Responsibility to concerned agencies and stakeholders. The PRcompiles the microseismic catalogue, continuous waveforms, and earthquake
effects which serve as a foundation for basic and applied earth science &oceanography research in Puerto Rico and the Caribbean. The PR net also
promote the education and preparedness of our population to mitigate theeffects of a significant earthquake or tsunami, working together with local,
commonwealth and federal partners.
The circum-Caribbean region has a documented history of large damaging earthquakes and tsunamis that have affected coastal areas, including
the events of Jamaica in 1692, the Virgin Islands in 1867, Mona Passage in
1918, the Dominican Republic in 1946, the 2010 Mw 7.0 Haiti event which
killed more than 250,000 people, and the M6.4 in Puerto Rico which affected
severely the southwestern region of the Island. There is clear evidence thattsunamis have been triggered by large earthquakes that deformed the ocean
floor around the Caribbean Plate (CP) boundary. Seismic events originatingin the prominent NE Caribbean fault system are considered to be a near-field
hazard for Hispaniola, Puerto Rico and the Virgin Islands because tsunamis
generated by these events can reach coastal areas within a few minutes after
the earthquake. Sources for regional and teleseismic tsunami-earthquakes
have also been identified in the Caribbean and Atlantic Basins.
The goal of this presentation is to describe the PR system, including thereal time earthquake and tsunami monitoring as well as the specific protocols
used to broadcast earthquake/tsunami messages locally.
Retrospective of the USGS National Earthquake
Information Center Strategic Plan, 2019-23: How We Did
and Future Directions
EARLE, P., U.S. Geological Survey, Colorado, USA, pearle@usgs.gov; HAYES,
G., U.S. Geological Survey, Colorado, USA, ghayes@usgs.gov; YECK, W., U.S.
Geological Survey, Colorado, USA, wyeck@usgs.gov; GOLDBERG, D., U.S.
Geological Survey, Colorado, USA, dgoldberg@usgs.gov; WALD, D., U.S.
Geological Survey, Colorado, USA, wald@usgs.gov; GUY, M., U.S. Geological
Survey, Colorado, USA, mguy@usgs.gov; PATTON, J., U.S. Geological
Survey, Colorado, USA, jpatton@usgs.gov; BARNHART, W., U.S. Geological
Survey, Colorado, USA, wbarnhart@usgs.gov; SHELLY, D., U.S. Geological
Survey, Colorado, USA, dshelly@usgs.gov; BENZ, H., U.S. Geological Survey,
Colorado, USA, benz@usgs.gov
The USGS National Earthquake Information Center (NEIC) monitors
earthquakes 24/7/365 worldwide and reports on US earthquakes cooperatively with US Regional Seismic Networks (RSNs) as part of the Advanced
National Seismic System (ANSS). In 2019, following the international Powell
Center Working Group for Earthquake Monitoring, the NEIC published a
5-year strategic plan. We will present the successes and challenges in meeting the plan’s fundamental and aspirational goals and discuss planned futureadvancements. We seek to input from the community on areas to prioritize for
future strategic planning.
Accomplishments from NEIC’s fundamental goals include improved
earthquake detection with a new Global Associator algorithm, phase-picker
and improved interoperability and coordination with RSNs through site visits and tabletop exercises. Advancements to NEIC’s infrastructure include
expanded redundancy, migration to a service-oriented architecture, webcentric Graphical User Interfaces, and using cloud technologies. ShakeMap
ground motion calculations and PAGER estimates of earthquake fatalities
and economic loss have been improved by expanding scenario capabilities
and redesigning the code to be more modular to support cloud technologies.
The ANSS Comprehensive Catalog (ComCat) now includes more historicalearthquakes and automatic quality control tools. The challenges faced during COVID slowed progress in some areas but motivated improvements in
NEIC’s remote and automatic processing capabilities. Realized NEIC’s aspirational goals include the implementation of machine learning phase identification and timing, improved rupture modeling using remote sensing data
(GNSS, optical imagery, and InSAR), implementation of a sequence-based
web interface that links mainshocks and aftershocks, and advanced modelingof earthquake impacts through the incorporation of ground truth loss information. Future work will expand on these topics and focus on greater automation of real-time solutions and catalog generation using machine learning andarray processing.
Why Non-Seismic Sensors Are Actually Valuable to
Network Seismology: Examples From Alaska
WEST, M. E., University of Alaska Fairbanks, Alaska, USA, mewest@gmail.
com; RUPPERT, N., University of Alaska Fairbanks, Alaska, USA, naruppert@
alaska.edu; GRAPENTHIN, R., University of Alaska Fairbanks, Alaska, USA,

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Seismological Research Lettersrgrapenthin@alaska.edu; MOHLER, M., University of Alaska Fairbanks,
Alaska, USA, mdmohler@alaska.edu
The Advanced National Seismic System (ANSS) provides earthquake data,
products, and monitoring services, built primarily on networks of broadband
and strong motion seismometers distributed across the nation. It is increasingly common to leverage these networks to operate other types of sensing
equipment with objectives ranging from meteorology and wildfire management, to nuclear treaty verification and space weather. We demonstrate herethat these other sensing types can have direct applicability to the seismic mission of networks and related programs including the ANSS.
The seismic network in Alaska has expanded considerably through amix of upgrades and adoptions tied to the NSF EarthScope program, coupledwith strategic investments. Renamed as the Alaska Geophysical Network,
these stations now include some combination of GNSS, weather, infrasound,
webcam, or soil temperature sensing. Recent large earthquakes demonstrate
how GNSS can be integrated directly to make up for displacement and amplitude shortcomings in seismic data. Colocated wind records track the influenceof vegetation, snow, and station design on seismic noise at frequencies critical to regional monitoring. Infrasound has recently been used to reconstructvertical component ground motion in locations where seismic sensors haveclipped. And webcams and weather sensors can facilitate field work logistics
decisions saving thousands of dollars in air transport.
The colocation model does have challenges. It can be difficult to accountfor shared resources, including field logistics, power system needs, communication costs, and computing systems. It is bureaucratically non-trivial
to build collaboration between funding agencies that each have narrow, but
well-defined, missions and accountability. And long-term planning is challenging when many stakeholders represent just a single objective. However,the scientific benefits are clear, and the costs are modest. We see benefit to our
seismic mission in continuing to develop models that facilitate the inclusionof non-seismic data types.
Seismic Network Station Infrastructure as the Basis forMulti-Disciplinary Geophysical StationsPERLIN, M., Nanometrics, Ottawa, Canada, michaelperlin@nanometrics.ca
Geophysical monitoring requires the highest level of performance and reliability from purpose-built and tightly integrated instrumentation and infrastructure. Parallel and separate efforts between different scientific disciplines
seen in the past came at the expense of duplicated infrastructure, telemetry
and power subsystems, and even land use permits. This duplication increases
costs, ultimately limiting station counts and reducing “the reach” of monitoring networks. Recent ambitions to combine multi-disciplinary geophysical applications into streamlined deployments led to initiatives such as theEuropean Plate Observing System (EPOS) and the recent amalgamation of the
SAGE and GAGE programs in the United States.
Modern seismic dataloggers, such as the Nanometrics Centaur, support a wide range of seismo-acoustic sensor interfaces and sensor types while
maintaining ultra-low power consumption, precise timing, and reliable datatransport with automatic back-fill features over flexible telemetry mediums.
These properties transformed the Centaur’s capabilities to act as a highly versatile foundation in multi-disciplinary geophysical station deployments.
Despite initially being designed as a high-performance data recorder forseismic applications, Centaur’s applicability has evolved to include data collection for the infrasonic, geodetic, magnetic, and meteorological domains. This
triggered the development and addition of purpose-built features to support
multi-disciplinary use cases with the same proven performance and reliabilityof a Centaur seismic station.
Both existing and planned capabilities that enable reliable and efficient
multi-disciplinary science are discussed.
Small Aperture Seismic Arrays for Offshore Out-ofNetwork Events
PERRY, H., Natural Resources Canada, Ottawa, Canada, claire.perry@nrcanrncan.gc.ca; CRANE, S., Natural Resources Canada, Ottawa, Canada, stephen.
crane@NRCan-RNCan.gc.ca; EISERMANN, A. S., Tel-Aviv University,
Ramat-Aviv Tel-Aviv, Israel, eisermann@tau.ac.il; ZIV, A., Tel-Aviv University,
Ramat-Aviv, Tel-Aviv, Israel, zivalon@tauex.tau.ac.il; MCCORMACK, D. A.,
Natural Resources Canada, Ottawa, Canada, david.mccormack@NRCanRNCan.gc.ca; SEYWERD, H., Natural Resources Canada, Ottawa, Canada,
henry.seywerd@NRCan-RNCan.gc.ca; ADAMS, J. A., Natural Resources
Canada, Ottawa, Canada, john.adams@NRCan-RNCan.gc.ca; PIETRONIRO,
E., University of Ottawa, Ottawa, Canada, epiet081@uottawa.ca; KOLAJ, M.,
Natural Resources Canada, Ottawa, Canada, michal.kolaj@NRCan-RNCan.
gc.ca; BENT, A. L., Natural Resources Canada, Ottawa, Canada, allison.

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bent@NRCan-RNCan.gc.ca; VAN BRABANT, R., Natural Resources Canada,
Ottawa, Canada, reid.vanbrabant@NRCan-RNCan.gc.ca
Two small-aperture (~350 m) five-element seismic arrays of accelerometers
were installed on southwestern Vancouver Island, British Columbia, Canada,as part of a pilot study related to Earthquake Early Warning (EEW) in Canada.
The location uncertainty for offshore (out-of-network) earthquakes remains
an order of magnitude greater than for most within-network events . Smallaperture arrays installed within existing EEW networks have been shown to
improve EEW performance for out-of-network earthquakes through robust
back-azimuth and slowness vector determination [Eisermann et al., 2019;
Netanel et al., 2021], and are independent of regional velocity model assumptions. To test the ability of both standalone and network-integrated arrays to(1) reduce earthquake location uncertainty for offshore events within 250 kmof the coast and (2) improve EEW alerting timeliness to coastal communities,
we deployed two small-aperture arrays along a coastline known for its highseismic and tsunamigenic hazard. Both arrays are located less than 1 km fromthe Pacific Coast and are approximately 55 km apart, to target offshore seismicity. The first array near Tofino (aperture 361 m) has a minimum element
spacing of 82 m, and the array near Bamfield (aperture 338 m) has a minimum
element spacing of 76 m. Real-time, low-noise, high-gain (1/4g) TitanSMA
accelerometers were installed in single-story buildings with existing power
and various communications infrastructure. Each element installation has astandalone GPS receiver for timing. Preliminary results from these arrays will
be presented and their utility in the context of the existing Canadian EEW
network discussed.
Determining the Feasibility of DAS for Urban Earthquake
Monitoring in Athens, Greece
SMOLINSKI, K. T., ETH Zurich, Zürich, Switzerland, krystyna.smolinski@
erdw.ethz.ch; BOWDEN, D., ETH Zurich, Zürich, Switzerland, daniel.
bowden@erdw.ethz.ch; LENTAS, K., National Observatory of Athens,
Athens, Greece, k.lentas@noa.gr; MELIS, N. S., National Observatory ofAthens, Athens, Greece, nmelis@noa.gr; SIMOS, C., University of Thessaly,
Lamia, Greece, christos.simos@uth.gr; BOGRIS, A., University of West Attica,
Athens, Greece, abogris@uniwa.gr; SIMOS, I., University of West Attica,
Athens, Greece, simos@uniwa.gr; NIKAS, T., University of Athens, Athens,
Greece, tnikas@di.uoa.gr; FICHTNER, A., ETH Zurich, Zürich, Switzerland,
andreas.fichtner@erdw.ethz.ch
As the global network of telecommunication fibers rapidly expands, we often
hear of the increasing potential to apply DAS and other fiber-optic seismology methods over large distances, and in novel and challenging environments.
Many of these fibers are installed within urban environments, and it has been
demonstrated that these can be useful for seismic event detection and shallow subsurface modeling. However, there remains a disconnect between
DAS deployments and traditional long-term/permanent seismic networks. In
particular, we are interested in exploring whether the incorporation of DAS
into seismic networks for regional earthquake detection and monitoring may
prove to be beneficial, and assessing the costs and benefits of such a long-term
deployment.
To do this, we analyze a dataset collected in Athens, Greece from
September–October 2021. Data were collected over 24 km of in-situ fiber
owned by the OTE Group (one of the largest telecommunication companies
in Greece). This study area is chosen due to the significant seismic risk inAthens; due to its proximity to many active fault systems, dense urban population, and a large number of older buildings and structures. We develop a
rapid event-detection workflow, based on standard seismic tools such as STA/
LTA, while also utilizing the high spatial density of DAS to improve the detection rate for small events. We are able to detect several hundred local seismic
events, down to local magnitude 0.55. Given the urban location of our study,
we also apply careful processing to address the challenges of detecting andisolating seismic events within noisy urban DAS data. For suitable events,
we estimate event locations using the DAS data. Finally, we test the event
detection and localization capabilities of DAS, both in comparison to, and in
conjunction with the existing regional network operated by NOA (National
Observatory of Athens).
Towards the Inclusion of Distributed Acoustic Sensing inEarthquake Monitoring and Early Warning Operations
BIONDI, E., California Institute of Technology, California, USA, ebiondi@
caltech.edu; SAUNDERS, J. K., California Institute of Technology, California,
USA, jsaunder@caltech.edu; TEPP, G., California Institute of Technology,
California, USA, gtepp@caltech.edu; YU, E. C., California Institute ofTechnology, California, USA, eyu@caltech.edu; BHADHA, R., California
Institute of Technology, California, USA, rayo@caltech.edu; BHASKARAN,

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A., California Institute of Technology, California, USA, aparnab@caltech.
edu; ACHARYA, P. R., California Institute of Technology, California, USA,pacharya@caltech.edu; ZHAN, Z., California Institute of Technology,
California, USA, zwzhan@caltech.edu; HUSKER, A. L., California Institute ofTechnology, California, USA, ahusker@caltech.edu
Distributed Acoustic Sensing (DAS) instrumentation deployed on existingtelecommunications fiber cables has emerged as a highly effective tool forseismological applications. Its unique capability to convert extensive lengthsof fibers into dense seismic arrays offers unparalleled observational advantages compared to conventional seismic stations. While substantial progresshas been made in utilizing DAS data for earthquake science, considerable
challenges persist when it comes to continuous earthquake monitoring andreal-time data processing algorithms.
Considering the ever-expanding fiber network both onshore and offshore, widespread adoption of DAS has the potential to revolutionize earthquake detection and enhance early warning capabilities. Here, we describe
how we are taking the first steps toward the inclusion of DAS data within
seismic network operations, from providing additional constraints to earthquake detection and localization to improving early warning performance.
We start by highlighting how metadata standards are employed to enable theusage of streamed DAS channels within existing network monitoring procedures. We illustrate how novel machine-learning approaches combined withefficient processing algorithms enable the incorporation of DAS data within
existing seismic network systems as well as the potential definition of the next
generation of monitoring and early warning tools. Specifically, we employedPhaseNet-DAS to fully exploit the high-spatial density nature of DAS to accurately pick earthquake arrival times. Finally, we demonstrate how high-performance computing processing, picking (i.e., PhaseNet-DAS), and localization tools can enable real-time earthquake detection and early warning.
Making Phase-Picking Neural Networks More Consistentand Interpretable
PARK, Y., Los Alamos National Laboratory, New Mexico, USA, ysp@lanl.gov;
DELBRIDGE, B. G., Los Alamos National Laboratory, New Mexico, USA,delbridge@lanl.gov; SHELLY, D. R., U.S. Geological Survey, Colorado, USA,dshelly@usgs.gov
Improving the reliability and interpretability of phase-picking neural networks (herein referred to as NN-pickers) remain as important tasks to facilitate their deployment to seismic monitoring programs. Existing NN-pickers
seek to estimate sample points in a given windowed waveform that is most
likely to represent the arrival of a seismic phase by identifying the peaks in the
output prediction score. Ideally, this score would scale with the confidence ofthe prediction result, so that applying a higher threshold would lead to fewer
false detections. However, it has been reported that predictions from existing
NN-pickers do not necessarily correlate with diagnostic waveform characteristics (e.g. the signal-to-noise ratio) and fluctuate rather arbitrarily depending
on how the continuous waveform data is windowed. This lack of interpretability makes it challenging to control the quality of seismic monitoring products.
Here, we present two approaches to increase the consistency of the existing
NN-pickers and to improve their interpretability. First, we apply an anti-aliasing filter at down- and up-sampling layers inside neural networks, a popular
technique applied within in the computer vision community to make convolutional neural networks more consistent. Second, we alter the training procedure such that shifted versions of the waveforms are systematically includedin the training dataset. We demonstrate the improvements by applying theapproaches to one of the most widely used NN-pickers and test on the waveform data that recorded the 2019 Ridgecrest earthquake sequence from July 4
to July 16. We show that using a batch containing sequentially shifted versionsof a single waveform at each training iteration can significantly improve theconsistency of the NN-picker we tested. We also show that with the help froman anti-aliasing filter, this training strategy can make the output prediction
score scale with the signal-to-noise ratios of waveforms.
Evaluation of Deep Learning Phase Picking Models
PARIKH, N., Los Alamos National Laboratory, New Mexico, USA, nidhip@
lanl.gov; MYREN, S., Los Alamos National Laboratory, New Mexico, USA,
myrenst@lanl.gov; RAEL, R., Los Alamos National Laboratory, New Mexico,USA, rrael@lanl.gov; FLYNN, G., Los Alamos National Laboratory, New
Mexico, USA, garrison@lanl.gov; CASLETON, E., Los Alamos National
Laboratory, New Mexico, USA, ecasleton@lanl.gov
Deep learning phase pickers have been shown to outperform traditional models. Deep learning models are trained using large, labeled datasets and thenapplied to incoming data or new datasets for automated creation of seismic

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catalogs. However, they suffer from the generalizability problem, i.e., theirperformance tends to drop when applied to new regions due to differencesin regional geological structures, sources, measurement instruments, andenvironmental effects. In addition, a large, labeled dataset, required to train
deep learning models from scratch, may not be available for a region of interest. Previous studies have demonstrated improved performance on a new
region when phase picking models are fine-tuned using a labeled dataset corresponding to this new region. In this work, we evaluate and compare threemodels: a model trained using STEAD data (Model 0), a model trained using
INSTANCE data (Model 1), and a model with weights initialized from Model
0 and fine-tuned using INSTANCE data (Model 2). We present our approachfor model performance evaluation and metrics used. Specifically, we evaluate
model transferability through transfer learning by evaluating how the amountof data used for fine-tuning impacts performance of Model 2. Through an
ensemble-based approach, we also perform uncertainty quantification formodel predictions.
A Comparison of Machine Learning Methods of
Association
PENNINGTON, C. N., Lawrence Livermore National Laboratory, California,
USA, cnpennin@gmail.com; MCBREARTY, I., Stanford University,
California, USA, imcbrear@stanford.edu; KONG, Q., Lawrence Livermore
National Laboratory, California, USA, kong11@llnl.gov; WALTER, W. R.,
Lawrence Livermore National Laboratory, California, USA, walter5@llnl.gov
The association of phase picks to form events is one of the most fundamental
components of seismology. Any error in association due to the inclusion of
errant phase picks will introduce errors in the later characterization of theevent, such as its location, magnitude, and focal mechanism. Large and dense
sensor networks, such as nodal arrays (and DAS), offer unique challenges
in association due to vast number of observations, high likelihood of errant
picks or multiple events occurring within the array at the same time. Also thelarge number of stations can greatly increase the time it takes to perform theassociation. For this reason, machine learning might provide a more optimal
method of association. In this work, we examine how well machine learning
methods (e.g., GaMMA, Phaselink, and GENIE) can incorporate dense nodal
arrays into regional networks and how well they handle the density of stations.
We test their capabilities on two nodal deployments, one within Rock Valley
Nevada (80 Nodes), and the LArge-n Seismic Survey in Oklahoma (LASSO)
dense nodal array (>1800 nodes). These two nodal arrays will test two particular issues that the machine learning algorithms might face: 1) The Rock Valley
Array is a small array (<10 kms) within a large regional network and it willallow tests of how the algorithms are able to merge the two during association.
2) The Oklahoma LASSO array spans 10’s of kms and contains multiple earthquake sequences and it will allow tests of each algorithm’s ability to associate
events that might be happening simultaneously. We then compare their associated bulletins to those obtained using Rapid Earthquake Association and
Location algorithm (REAL), a more traditional method of association. We
find that there are often vast differences between findings of certain methods.
Some methods finding roughly half the events of others while others cannot
integrate the nodal array with the regional network. We even find that certain
methods break apart larger events into multiple events. Prepared by LLNL
under Contract DE-AC52-07NA27344.
A Comprehensive Earthquake Focal Mechanism Catalog for
Nevada Obtained Through Deep Learning Algorithms
CHATTERJEE, A., University of Nevada, Reno, Nevada, USA, achatterjee@
unr.edu; SRIKAR, G., University of Nevada, Reno, Nevada, USA,gauravsrikar@nevada.unr.edu; PENNINGTON, C. N., Lawrence Livermore
National Laboratory, California, USA, pennington6@llnl.gov; WALTER, W.
R., Lawrence Livermore National Laboratory, California, USA, walter5@llnl.
gov; TRUGMAN, D. T., University of Nevada, Reno, , USA, dtrugman@unr.
edu
The state of Nevada is one of the most seismically active areas of the UnitedStates, with numerous active fault systems throughout the Walker Lane andBasin and Range tectonic faults. Despite high rates of seismic activity, Nevada
currently lacks a comprehensive catalog of earthquake focal mechanisms that
could be used to better understand seismotectonic processes. Determining the
focal mechanisms of small earthquakes poses a considerable challenge due tothe difficulty of distinguishing phase arrivals and first-motion polarities fromnoise. To address this issue, we augment the first-motion polarity databasemaintained by the Nevada Seismological Laboratory with additional measurements obtained using a convolutional neural network algorithm. We thencomplement polarity data with new measurements of S/P amplitude ratios
to provide additional constraints on event mechanisms. By incorporating

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Seismological Research Lettersboth existing and newly obtained data, we construct a comprehensive focal
mechanism catalog for the state of Nevada from 2008 through 2023, utilizing a revised implementation of the HASH method originally developed by
Hardebeck and Shearer (2002). With the new focal mechanism catalog, weanalyze changes in focal mechanism characteristics resulting from significant
mainshocks like the 2020 Mw6.5 Monte-Cristo and other prominent earthquake sequences like the Spanish Springs, Hawthorne, Nine-Mile Ranch, andSheldon sequences. The enhanced resolution of the new catalog will play a
crucial role in advancing our understanding of the crustal stress field, mechanisms triggering earthquakes, fault zone geometry, and strain partitioning
across the state.
Deep Learning Enhanced Earthquake Catalog for Northern
California
MCBREARTY, I. W., Stanford University, California, USA, imcbrear@stanford.edu; BEROZA, G. C., Stanford University, California, USA, beroza@
stanford.edu
Improving the completeness and accuracy of earthquake catalogs can reveal
new insights into spatio-temporal trends in seismicity, identify fault structuresin improved detail, and provide rich datasets for tomography. We present
work on a comprehensive earthquake catalog for northern California between
2000 - 2023, spanning from Parkfield to the Mendocino Triple Junction, andfrom the west coast into the Sierras and western Nevada. To develop thiscatalog, we use PhaseNet-based picks (Zhu and Beroza, 2018) followed by
GENIE-based association (McBrearty and Beroza, 2023). The original GENIE
is a graph neural network associator that relies on all pairs of source and station nodes. We implement a more memory efficient version that uses only asubset of all source-station pairs. We also experiment with using amplitudes
and phase types in addition to arrival times. These modifications improve theperformance of the model and enable accurate associations across the full spatial domain, despite the heterogeneity in station coverage, source distribution,and time-varying seismic networks.
The combination of these two deep learning processing steps, followedby double-difference relocation (Waldhauser and Ellsworth, 2000), reveals
dense seismicity throughout all of the expected seismogenic zones of northern California, while increasing the rates of detection compared to the USGS
catalog by 4–8x depending on the detection thresholds used. We observe significant earthquake activity at Geysers geothermal field, along the Calaveras
and Hayward faults, and at Long Valley Caldera and the Mendocino Triple
Junction. The highest event activities occur during the 2003 San Simeon, 2004
Parkfield, and the 2014 Napa Valley earthquake sequences. We assess the reliability of the results based on known seismicity, expected earthquakes statistics, and association assignments across the seismic network with respect tosource locations and event magnitudes.
An Agent Based Model to Quantify Gains in Network
Processing
CARMICHAEL, J. D., Los Alamos National Laboratory, New Mexico, USA,joshuac@lanl.gov
Explosion monitoring agencies and state-sponsored seismic networks thatsurveil the globe for signatures of nuclear explosions generally implement
some version of what we call an Event Processing Pipeline (EEP) or just apipeline. Pipelines comprise a sequence of tasks that subject matter experts
and their algorithms (collectively called “agents”) apply to detect, locate andcharacterize the source of such signatures (among other efforts). Both thedetails of agent implementation, such as whether they work in series or parallel, and their individual success rates, such as the probability that a source
depth estimate is accurate, quantify the overall efficacy of an EEP. Researchers
and network operators often question if a particular sequence of monitoring
functions provides a more complete seismic catalog relative to a reference
catalog. Explosion monitoring researchers therefore require the capability
to measure how any loss or improvements to agent cooperation and performance impact the likelihood that EEPs will output an accurately characterized
special event source, over such a reference (baseline) value. Here, we provide
a high-level model of EEP performance and quantify how changes to individual agents improve the overall EEP success rate. In particular, we model an
EEP as a series of monitoring function modules that teams of resource-limited
agents (working in series or parallel) can achieve with specific probabilities.
This model takes the form of a relational object known as a graph. We quantify
improvements to EEP over several operational baseline models in terms ofsuch graphs, which directly relate agent performance to that of an EEP. Lastly,
we demonstrate our method against a simple example that employs correlation detectors against explosion sourced data.

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Seismology as a Service: Portable Product Generation at
the Southern California Seismic Network Using ServiceOriented Architecture and Cloud Computing
YU, E. C., California Institute of Technology, California, USA, eyu@caltech.
edu; TEPP, G., California Institute of Technology, California, USA, gtepp@caltech.edu; TAM, R., California Institute of Technology, California, USA,
rwtam@caltech.edu; BHASKARAN, A., California Institute of Technology,
California, USA, aparnab@caltech.edu; CHEN, S., California Institute ofTechnology, California, USA, schen@caltech.edu; CHOI, J., Nationwide
IT Services, Virginia, USA, jchoi5@caltech.edu; HUSKER, A., California
Institute of Technology, California, USA, ahusker@caltech.edu
Rapid advancements in machine learning, cloud computing, and new datatypes such as DAS bring both opportunities and challenges for seismic networks. These algorithms and technologies can enable networks to produce
more accurate data products in a more timely, and robust manner. Recently,
the Southern California Seismic Network (SCSN) began incorporatingmachine learning picks from the PhaseNet algorithm to produce higher quality phase arrivals and more accurate origins prior to analyst review. Work presented at the 2023 SSA Annual Meeting showed how cloud native services canmake processing scalable in a large sequence. For a network to take advantageof these continually evolving efforts, its staff must be able to evaluate different
algorithms, which require efficient deployment and testing. Networks using
the same code and algorithms may wish to operate them in a cloud, hybrid, oron-premises environment to fit their individual considerations, such as network bandwidth, computational resources, or budget. To deal with this variability, it is important to make network processing components modular andagnostic to the infrastructure. This would expedite testing and enable fasterincorporation of new scientific algorithms, software, and other infrastructure
into operational earthquake monitoring.
In this presentation, we configure the AQMS automated origin refinement process, “hypomag”, to a service-oriented architecture. This workflow
refines and adds phase picks around expected time windows based on thereal-time origin to improve the origin and magnitude. We organize these processing steps into services that could be hosted in the cloud or on premises.
We examine modularity by incorporating different picker services that produce picks based on different algorithms. We also examine scalability and costconsiderations if these services are deployed in AWS. This work will inform
network operators on methods to make their processing flows more adaptableand versatile. It will also familiarize researchers with what is required to makenew algorithms a part of an operational environment.
NEIC Developments: Updates on the U.S. Geological Survey
National Earthquake Information Center’s Earthquake
Monitoring Systems
PATTON, J., U.S. Geological Survey, Colorado, USA, jpatton@usgs.gov;
UY, M., U.S. Geological Survey, Colorado, USA, mguy@usgs.gov; EARLE,
P., U.S. Geological Survey, Colorado, USA, pearle@usgs.gov; YECK, W.,
U.S. Geological Survey, Colorado, USA, wyeck@usgs.gov; COLE, H., U.S.
Geological Survey (Contractor), Colorado, USA, hcole@contractor.usgs.gov
The U.S. Geological Survey (USGS) National Earthquake Information
Center’s (NEIC) real-time global monitoring systems support the NEIC missions to detect earthquakes globally, estimate source parameters, and produce
a reviewed earthquake bulletin. The NEIC continually develops and deploys
seismic algorithms, systems, and interfaces to meet the NEIC’s evolving
needs. NEIC analysts, developers, and researchers have made several significant algorithmic advancements to improve the NEIC’s ability to characterize
earthquakes, including the updates to its W-Phase moment tensor and location algorithms, new web-based services and seismic analysis interfaces, andimprovements to machine learning characterization of seismic phases.
The NEIC has rewritten its W-Phase moment-tensor software to
improve its computational speed and the stability of its automatic solutions
and is now working towards transforming this software into a web service. The
NEIC retired its legacy Fortran locator in favor of a new Java version which
is implemented as a web service. This new locator has additional algorithmic
improvements including slab models to help constrain event depths, updated
statistics of phase-distance specific uncertainties, new strategies to better compute locations with mixed local-to-teleseismic observations, and more robust
uncertainty estimates. The NEIC continues to develop a new seismic analysis
system, Motus, and has largely completed the back-end web data notification
services and a new web-based interface for real-time and research analysis of
W-Phase moment magnitude (Mww). The NEIC is currently developing new
web-based repicking and modernized Catalog Review interfaces, both extensions of the completed Quick-Look interface. The NEIC has developed the
AI-Driven Earthquake Monitor (AIDEM), a python package that provides a

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framework to test and implement machine learning models in our operationalsettings. AIDEM takes continuous waveform data as an input and producesphase detections along with characterization labels provided by single-station
ML models, which are utilized by the NEIC associator to improve detections.
gCent: Geodetic Centroid Products for Earthquake
Monitoring
BARNHART, W., U.S. Geological Survey, Colorado, USA, wbarnhart@usgs.
govThis presentation provides an overview and update of the Geodetic Centroid(gCent) catalog—a satellite imagery-derived earthquake centroid catalog
developed for regional and global earthquake response. Geodetic remotesensing imagery from optical correlation (“pixel tracking”) and interferometric synthetic aperture radar (InSAR) serve an increasingly diverse and important role in earthquake monitoring and response. The geodetic observations
provide precise information for determining the finite fault characteristics ofmoderate to large (magnitude 5 and larger) terrestrial and near-shore earthquakes that compliment seismological approaches. This source informationin turn directly informs USGS/Advanced National Seismic System (ANSS)
Finite Fault Model, ShakeMap, and PAGER products. Since late 2019, we havesystematically processed satellite imagery of earthquakes magnitude 5.5 andlarger, PAGER Yellow and above, and other earthquakes of unique interest. We
then derive source models of earthquakes that produce measurable surface
displacements. This effort has led to a growing earthquake catalog that currently includes >120 earthquakes spanning M4.1-M7.8. In this presentation,
I will give an overview of the rationale for and production of the gCent catalog, highlight key contributions of gCent products in ANSS/USGS earthquake
response efforts, and detail future developments for gCent products and thegCent catalog.
Overcoming Challenges in Near-Field Seismic Velocity
Estimation: Insights from continuos GPS and Strong
Motion Data
RIQUELME, S., Sebastian Riquelme, Santiago, Chile, sebastian.riquelme@gmail.com; CREMPIEN, J., Universidad Catolica, Santiago, Chile,jocrempiend@uc.cl; KOCH, P., University of Chile, Santiago, Chile, pkoch@
csn.uchile.cl
Strong motion data have multiple applications in earthquake seismology.
However, a common problem is obtaining near-field seismic velocity fromstrong motion records. Moreover, they cannot capture the low-frequency portion of ground motion, and thus, double integration is not accurate in obtaining displacements unambiguously. This is often referred to as baseline offset
correction and is mostly due to the tilting of the inertial sensor. The inability to record long-period motions leads to magnitude saturation in the nearfield, and as a result, other seismic parameters are not accurately estimated.
To solve this problem, it is necessary to have a collocated GPS to constrain
the long-period displacement and the integration to match the static offset.
GPS instruments, while noisier than the strong motion sensors, overcome
all these limitations for large earthquake characterization. Here, we compare
seismogeodetic velocity from collocated GPS and strong motion sensors in
the near field for large earthquakes, such as the Mw 9.0 Tohoku-oki, the Mw
7.2 El Mayor-Cucapah, the Mw 8.2 Iquique, and the Mw 8.3 Illapel events. We
provide new rules to correct integration to obtain seismic velocity for cases inwhich no continuous GPS data are available. We will show the implications ofthese strong motion corrections to the data on the application of finite fault
earthquake rupture models and spectrum calculation.
Precision and Accuracy of Earthquake Locators: Insights
From a Synthetic 2019 Ridgecrest Sequence Experiment
YU, Y., Stanford University, California, USA, yuyifan@stanford.edu;
ELLSWORTH, W. L., Stanford University, California, USA, wellsworth@stanford.edu; BEROZA, G. C., Stanford University, California, USA, beroza@
stanford.edu
By solving the inverse problem, various earthquake location programs serveas important tools for the precise determination of earthquake hypocenters.
However, the variety of algorithms and misfit norms raises questions about
the efficiency and accuracy of different methods. With limited knowledge ofthe true velocity structure and sparse seismic network coverage, the efficacyof these tools for accurately pinpointing the true locations remains uncertain.
Some programs incorporate uncertainty analysis; however, due to the inherent nonlinearity of the problem, the reliability of the resultant confidence
measures of earthquake locations deserves some scrutiny. This study embarks
on an evaluation of widely used earthquake location methods through a

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controlled synthetic experiment to compare the outputs of seven programs(HypoDD, GrowClust, HypoInverse, VELEST, XCORLOC, NonLinLoc,
HypoSVI) using the 2019 Ridgecrest earthquake sequence. We calculate arrival times by the Fast-Marching Method using a 3D velocity model
extracted from the SCEC Community Velocity Model with a von Karman
perturbation superimposed to represent unmodeled small scale structure,including elevation effects. We mimic a realistic seismic network monitoring
scenario by introducing picking errors, phase availabilities, and phase outliers
into the synthetic traveltimes. Our comparative analysis of the recovered locations utilizing the uniform traveltime dataset and 1D velocity structure reveals
the superior precision of relative location methods compared to absolute location methods (except VELEST). We demonstrate that near source S phases
are important for constraining the focal depth; however, our study shows thelimited ability of consistently recovering depths under a 1D velocity structure
approximation. As established uncertainty techniques frequently fall short ofencompassing true hypocenters, our findings should motivate revisting earthquake location uncertainty assessment.
Improving Shear-Arrival Time Estimates for Real-Time
Association and Location Algorithms
BAKER, B., University of Utah, Utah, USA, ben.baker@utah.edu;
ARMSTRONG, A. D., University of Utah, Utah, USA, u1072028@utah.edu;
PANKOW, K. L., University of Utah, Utah, USA, Kris.Pankow@utah.edu
Machine learning and, in particular, deep-learning frameworks have markedly changed the capability of regional seismic networks to detect, classify, andquantify seismic phase arrivals. Yet, in real-time seismic monitoring frameworks, our association and location tools are not necessarily well-equipped toutilize these new and improved automatic characterizations. This limitation isparticularly true for shear-wave arrivals which deep-learning detectors appear
to generate at a rate of approximately equal to or greater than primary-wave
arrivals. The main challenge posed by shear-wave arrivals is that in monitoring regions with substantial three-dimensional velocity heterogeneities,
predicting shear-arrival times requires a time-intensive tomography process.
To mitigate this tomography requirement, University of Utah SeismographStations (UUSS) has recently begun to accommodate 3D structural effects
with source-specific station corrections (SSSCs). In this abstract, we review
ongoing work at UUSS that combines conventional phase-specific station corrections with SSSCs to better predict phase arrivals at regional monitoringscales. The correction estimation and implementation strategies to be presented appear to be effective, safe, conceptually simple, data-driven, low-overhead, and well-suited for integration into typical earthquake association andlocation frameworks. Time permitting, we will also review the performance of
these correction strategies in a live-acquisition, real-time environment.
Comparing Three-Dimensional Seismic Velocity Models for
Location Accuracy
BEGNAUD, M., Los Alamos National Laboratory, New Mexico, USA,mbegnaud@lanl.gov; CONLEY, A., Sandia National Laboratories, New
Mexico, USA, acconle@sandia.gov; DAVENPORT, K., Sandia National
Laboratories, New Mexico, USA, kdavenp@sandia.gov; PORRITT, R., Sandia
National Laboratories, New Mexico, USA, rwporri@sandia.gov; BALLARD,
S., Sandia National Laboratories, New Mexico, USA, sballar@sandia.gov;
GAMMANS, C., Los Alamos National Laboratory, New Mexico, USA,
cgammans@lanl.gov
Location algorithms have traditionally relied on one-dimensional (1D) velocity models for fast, seismic event locations. 3D seismic velocity models are
becoming readily available and usually provide more accurate event locations over 1D models. We have previously demonstrated and validated theability to quickly create 3D travel-time lookup surfaces (3DTTLS) for seismic
event location algorithms using an open-source framework (PCalc+GeoTess,
www.sandia.gov/salsa3d, www.sandia.gov/geotess) that easily stores spatiallyvarying data, including 3D travel-time corrections to a standard 1D velocity model. This framework allows for fair and consistent comparisons of 3D
velocity models because the lookup tables can be generated using the exact
ray-tracing algorithm that is preferred for a given 3D model. We have created first-P and first-S 3DTTLS for several publicly available 3D models (e.g.,
RSTT, SALSA3D, G3D, DETOX-P2, etc.). Using several global-scale seismic
events, we compare epicenter location accuracy (LocOO3D, www.sandia.gov/
salsa3d) using 3DTTLS for these 3D models to demonstrate how velocity

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Seismological Research Lettersmodels can be fairly compared for special events. In addition to standard epicenter comparisons, we will investigate combining epicenter determinations
into an ensemble location for each analyzed event.
Regionalization of ML and Its Relation to Mw
HERRMANN, R. B., St. Louis University, Missouri, USA, robert.b.herrmann@
gmail.com; BENZ, H. M., U.S. Geological Survey, Colorado, USA, benz@usgs.
gov
The specification of seismicity rates for Probabilistic Seismic Hazard Analysis
often relies on an empirical relation between ML and Mw for small (M < 4)earthquakes, but this requires a consistent definition of ML that accounts forregional differences in wave propagation. The IASPEI ML definition is ML= log10 (A) + 1.11 log10 R + 00189 R - 2.09, where A is the peak horizontal
amplitude of a simulated Wood-Anderson seismometer in nm, and R is the
hypocentral distance in km (within 1000 km). The first and second distanceterms are interpreted as corrections for geometrical spreading and anelastic
attenuation, respectively, To regionalize, we propose that events with the same
A at short distance (e.g., 10 km) have the same ML, and that only the anelastic
attenuation term varies. Given sufficient observations, a plot of the IASPEI
ML vs R will exhibit a linear trend, which is sufficient to modify the anelastic
attenuation term. The benefits of this approach is that one can always define
an ML, even in a relatively aseismic region, if there are sufficient observations
with distance. In more seismic regions, similar processing of many events
leads to a well determined regional anelastic attenuation correction.
A systematic study of events with M > 3.5 since 2010 has led to the determination of the appropriate anelastic attenuation coefficient for parts of North
America. Still there are large regions for which these coefficients are not available because of a lack of earthquakes. We examine the utility of using independently determined Lg-Q values to fill in these gaps. Finally using a databaseof over 2,500 regional moment tensor inversions for which ML was estimated,
the relation between regional ML and Mw is examined for robustness.
Noisy Stations Make Earthquake Magnitudes Larger
RINGLER, A., U.S. Geological Survey, New Mexico, USA, aringler@usgs.
gov; AMBRUZ, N. B., U.S. Geological Survey, Colorado, USA, nambruz@
usgs.gov; EARLE, P., U.S. Geological Survey, Colorado, USA, pearle@usgs.
gov; KRAGNESS, D., U.S. Geological Survey, Colorado, USA, dkragness@
contractor.usgs.gov; SHELLY, D., U.S. Geological Survey, Colorado, USA,dshelly@usgs.gov; WILSON, D., U.S. Geological Survey, Colorado, USA,dwilson@usgs.gov; YECK, W., U.S. Geological Survey, Colorado, USA,wyeck@usgs.gov
The magnitude of a moderate earthquake (e.g., 4<M<6.5) at a teleseismic
distance is often estimated by way of the body-wave magnitude (mb). mb isestimated at a station by recording the peak-to-peak amplitude, scaling this by
the dominant period, and finally applying an attenuation correction. Using acollection of station mb estimates, it is then possible to estimate the event mb
by way of averaging. In order to understand how sensitive mb estimates are to
local site conditions, we first estimate background noise levels at stations usedby the National Earthquake Information Center (NEIC) for all mb estimates
between January 1, 2021, and January 1, 2023 (over 57,000 events). Then, we
find a direct correlation between station noise levels and the calculated station
mb. For example, stations with background noise levels of 10 nm displacements can routinely produce an overestimate in the station magnitude by 0.5
magnitude units. This suggests that events estimated using only stations inhigh noise environments (e.g., coastal stations) could produce mb values thatare greater than when low-noise stations are used. In order to better understand these phenomena, we produce theoretical and data-driven models that
can help to predict the potential bias in station mb estimates.

Network Seismology: Recent Developments, Challenges
and Lessons Learned [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Blaine Bockholt, Idaho National Laboratory(blaine.bockholt@inl.gov); Renate Hartog, Universityof Washington (jhartog@uw.edu); Kristine L. Pankow,

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University of Utah (pankowseis2@gmail.com); Adam Ringler,
U.S. Geological Survey (aringler@usgs.gov); Dmitry Storchak,International Seismological Centre (dmitry@isc.ac.uk)
poster 1
Picking Regional Earthquake Waveforms With Neural
Networks
AGUILAR, A. L., Stanford University, California, USA, aguilars@stanford.
edu; BEROZA, G. C., Stanford University, California, USA, beroza@stanford.
edu
We present a set of deep learning models trained to perform seismic phasepicking at regional distances. These models use raw seismometer data, as well
as a combination of raw data and featured engineered data. Also, we present a multiview learning approach that takes advantage of having multiple
instruments at the same location, like a seismometer and an accelerometer.
The training of these models was done on a quality controlled dataset of over
1.5 million, 5 minute long three component waveforms that contain both P
and S labeled arrivals. Our base model handles the first arriving P and S waves,
whereas other models handle both the first and secondary arrivals, like picking Pn and Pg, Sn and Sg simultaneously. We show the performance of thesemodels on train/test splits along with deploying the models to continuous data
to find new uncataloged earthquakes.
poster 2
Moment Magnitude Estimation Using Machine Learning
Algorithms for Western United States
ALIDADI, N., University of Memphis, Tennessee, USA, nalidadi@memphis.
edu; PEZESHK, S., University of Memphis, Tennessee, USA, spezeshk@
memphis.edu
Accurately estimating the moment magnitude (Mw) earthquakes are fundamental for risk assessment, seismic hazard analysis, other seismological studies, and structural design. This study presents a comprehensive analysis of
moment magnitude estimation using a dataset from the NGA-West2 databaseof about 21,000 earthquake records. We use machine learning regression techniques to train and test a model to predict Mw considering the following input
features: Peak Ground Acceleration (PGA), 5%-damped pseudo-spectral
acceleration (PSA) at 21 different periods, hypocentral distance (Rhypo), andthe timed-average shear-wave velocity of the upper 30 m of soil (Vs30), fault
mechanism, and the depth to the top of the rupture plane (Ztor). The machinelearning models considered in this study include Artificial Neural Networks,
Support Vector Regression, Random Forest, and Gradient Boosting, each
known for their predictive ability in nonlinear and complex datasets. Treebased algorithms like Random forest and Gradient Boosting offer a moreaccurate model than Support vector and Neural networks. The proposedmodel uses a stacking method to combine different machine-learning techniques to provide a more accurate and robust framework. The proposed
approach overcomes the limitations of conventional techniques by creatinga rapid and straightforward process for estimating Mw. We use mean squareerror (MSE), mean absolute error (MAE), and the coefficient of determination (R2) to indicate that machine learning regression models can significantly
improve moment magnitude estimations.
poster 3
National Strong Motion Project’s Advancements in Station
Health and Integration to the Earthquake Early Warning
System in the San Francisco Bay Area
AMADOR, V. S., San Jose State University, California, USA, veronica.
amadorulloa@sjsu.edu; SCHLEICHER, L. S., U.S. Geological Survey,
California, USA, lschleicher@usgs.gov; CARRASCO RODRIGUEZ, V.,
San Jose State University, California, USA, vcarrascorodriguez@usgs.gov;
CHILDS, D. M., U.S. Geological Survey, California, USA, dmchilds@usgs.gov;
LUNA, E., U.S. Geological Survey, California, USA, eluna@contractor.usgs.
gov; STEIDL, J. H., U.S. Geological Survey, California, USA, jsteidl@usgs.gov;
BLAIR, J. L., U.S. Geological Survey, California, USA, lblair@usgs.gov
The rollout of Earthquake Early Warning (EEW) in the western U.S. highlights an increased need to ensure the continued operation of seismic stationsin urban centers. The United States Geological Survey’s (USGS), Advance
National Seismic System (ANSS), National Strong Motion Project (NSMP)
network, includes seismic stations located on human-built infrastructure tobetter understand how ground motions from earthquakes affect the integrity and performance of structures and seismic risk upon urban regions. The
availability of ground motion records is important for design of earthquake

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resilient infrastructure and to assess safety following a major earthquake. The
NSMP maintains several structural arrays (Buildings: 107, Dams: 77, Bridges:
19, Geotechnical Arrays: 21) and free-field accelerometers (> 450 stations)
across the continental United States and in Alaska, Hawaii, and Puerto Rico,which ensure ground motions from large magnitude earthquakes are recorded
at locations in the near-field fault source. The increase of EEW contributing
stations in the Western U.S. has increased the need for NSMP to strategicallymanage field operations. Here we highlight new tools to manage knowledge of
instrument state of health, planning for ongoing field maintenance campaigns
to keep critical stations operating, and upgrades to modernize equipment toallow for real-time dataflow for our field campaigns in the San Francisco Bay
Area and beyond. To visualize our networks health in a living state, we areleveraging ArcGIS Online Dashboards combined with Jupyter notebook-based
python queries to combine station metadata location and instrumentation
information with instrument state of health (battery voltage, clock quality, dataflow). This presentation will also include advancements NSMP is focusing on
regarding new layout designs that incorporate energy efficient hardware anduser-friendly enclosures to protect and expand the longevity of the station’s
equipment. We are also exploring adopting field-app based notification of fieldvisits to seismic stations to improve field to data exchange of information.
poster 4
Building an Operational Low-Cost Seismic Network in
Ukraine
AMASHUKELI, T., GFZ Potsdam, Potsdam, Germany, tetiana.amashukeli@
gfz-potsdam.de; MALATESTA, L., GFZ Potsdam, Potsdam, Germany,
malatest@gfz-potsdam.de; FARFULIAK, L., Subbotin Institute of Geophysics
of the National Academy of Sciences of Ukraine, Kyiv, Ukraine, myronivska@
gmail.com; HANIIEV, O., Subbotin Institute of Geophysics of the National
Academy of Sciences of Ukraine, Kyiv, Ukraine, aganiev@gmail.com;
KUPLOVSKYI, B., Subbotin Institute of Geophysics of the National Academyof Sciences of Ukraine, Lviv, Ukraine, bohdan_kuplyovsky@yahoo.com;
PROKOPYSHYN, V., Subbotin Institute of Geophysics of the National
Academy of Sciences of Ukraine, Lviv, Ukraine, pvasyl70@gmail.com;
PETRENKO, K., Subbotin Institute of Geophysics of the National Academyof Sciences of Ukraine, Lviv, Ukraine, pekar232@gmail.com
A robust seismic network is vital for ensuring safety and facilitating researchin Ukraine; however, currently the Institute of Geophysics at the National
Academy of Sciences of Ukraine faces challenges in its existing seismic network, limiting its ability to provide accurate seismic information and emphasizing the need for reconstruction. The seismic landscape in Ukraine displays
marked variations, encompassing notable areas like the Carpathians andCrimean-Black Sea segments, alongside considerations for the western andsouthern regions impacted by the Vrancea seismic zone. In response to various challenges, we are initiating the deployment of budget-friendly seismometers, specifically the Raspberry Shake Seismographs, across Ukraine. Firstand foremost, this network is envisioned as a responsive interim solution tobolster the seismic infrastructure across the region while awaiting the deployment of broadband stations. Secondly, this initiative unfolds as an effort toenrich educational experiences within the academic sphere, with a focus onschools and universities in Ukraine. Presently, numerous educational seismic
networks span the globe, underscoring the significance and necessity of disseminating seismic sensors to schools for educational purposes. This initiative
acknowledges the challenges facing Ukraine’s existing seismic network andthe demographics at the Institute of Geophysics. The scarcity of younger scientists entering the field raises concerns about the future of scientific researchin Ukraine.
The GFZ German Research Centre for Geosciences has provided 28
Raspberry Shake Seismographs with laptops, planned for deployment acrossschools and universities in Ukraine. Raspberry Shake 3D Seismographs havebeen installed at the Institute of Geophysics in Kyiv, Lviv Polytechnic National
University, and Ivan Franko National University of Lviv. In November 2023,
educational materials for seismology at middle and high school levels in
Ukraine were developed with the assistance of the GFZ German ResearchCentre for Geosciences.
poster 5
Automated and Efficient Installation of AQMS
ANTOLIK, L., Instrumental Software Technologies, Inc., New York, USA,
lorenantolik@isti.com; FRIBERG, P., Instrumental Software Technologies,
Inc., New York, USA, paulfriberg@isti.com
AQMS is the open source ANSS Quake Management System that wraps
around the Earthworm software system. AQMS is a robust but complex set ofsoftware that requires many components to be correctly installed and config-

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ured for it to work properly. Recent advances in computing such as virtualization and automation have streamlined the build and installation proceduresfor software systems.
In this presentation we introduce a method to automate the installationof AQMS and its many dependencies. The core of this method uses Ansible,
an automation framework developed by Red Hat. Installation tasks known as‘plays’ are organized into ‘playbooks’ and combined to form ‘deployments’. The
installation runs sequentially, and emulates how a human would perform an
installation, but using plays designed to be repeatable yet non-destructive, aconcept known as idempotence.
We discuss advantages of this methodology such as speed, accuracy,
consistency, scalability, configurability and security. Highlighted methods
cover configuration management using git, metadata updates, systems administration tools, and analyst resources. We also demonstrate how this projectutilizes and supports the seismic communities open source projects.
poster 6
Enhancing Data Resiliency With Dual-Feed Telemetry
BHADHA, R., California Institute of Technology, California, USA, rayo@
caltech.edu; BLACK, M. L., California Institute of Technology, California,
USA, mlb@caltech.edu; HOGGRO, C., California Institute of Technology,
California, USA, choggro@caltech.edu; HIRATA, T., California Instituteof Technology, California, USA, thirata@caltech.edu; HUSKER, A. L.,
California Institute of Technology, California, USA, ahusker@caltech.edu;
STUBAILO, I., California Institute of Technology, California, USA, stubailo@
caltech.edu; WATKINS, M. B., California Institute of Technology, California,
USA, mwatkins@caltech.edu; YU, E. C., California Institute of Technology,
California, USA, eyu@caltech.edu; ALVAREZ, M. G., U.S. Geological Survey,
California, USA, malvarez@usgs.gov; BIASI, G., U.S. Geological Survey,
California, USA, gbiasi@usgs.gov; JONES, J. S., U.S. Geological Survey,
California, USA, jjones@usgs.gov
The Southern California Seismic Network (SCSN), operated by Caltech and
USGS, records on average 256 events of M>=3.0 per year including aftershocks
and one M>=6.0 every 3 years. The SCSN utilizes state of the art computing technologies to provide timely earthquake event notification, ShakeMap,
and other data products. Because of its critical role providing real time datafor public safety, the SCSN maintains a robust and resilient network of morethan 350 digital strong motion and broadband seismic stations to achieve thisgoal. We also import real-time data for an additional 170 stations from partner networks. We use a variety of digital data communications, including cell
modems, private microwave network, digital radios, satellite, and the Internet.
This presentation describes how we use dual-feed telemetry to improve resiliency of data delivery.
At the SCSN, all our seismic dataloggers in the field are capable of continuous dual-feed telemetry, i.e., sending the same seismic data to multiple
acquisition servers. To improve the resiliency of our network, we use two
acquisition servers all the time to receive continuous data from most seismic stations. One acquisition server is in the data center in Pasadena, CA,
while the other uses an Elastic Cloud Computing (EC2) instance provided
by Amazon Web Services (AWS). All the 100 sample/second seismic dataacquired are rapidly distributed in 1-second packets via multicast network
protocol to the real-time AQMS (ANSS Quake Monitoring System) servers.
We have redundant AQMS servers locally in Pasadena, and an EC2-based
AQMS instance in AWS.
To accomplish data resiliency, both streams of the 100 sample/second seismic data from each dual-feed station are available continuously to
all the AQMS servers. Each AQMS server uses the fastest 1-second data
packet, between the local and cloud acquisition, for that specific dual-feed
station. Each AQMS system can directly distribute products using ProductDistribution Layer (PDL), email, and SMS, to USGS, FEMA, Cal OES, andother government agencies.
poster 7
Next Generation In-Vault Power Distribution to Increase
Network Reliability and Remote Ops Capability
BLOM, L., University of Alaska Fairbanks, Alaska, USA, ljblom@alaska.
edu; HELMERICKS, J., University of Alaska Fairbanks, Alaska, USA,jghelmericks@alaska.edu; DALTON, S., University of Alaska Fairbanks,
Alaska, USA, sdalton4@alaska.edu
Power management, distribution and control at remote seismic and infrasound stations is foundational to operating a high quality and high uptime
station. The Wilson Alaska Technical Center (WATC) developed a next generation in-vault power distribution unit, the WATC PowerHub, to maximizecommand-and-control and State of Health (SOH) collection in each vault.

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The PowerHub can operate in AC or DC environments and is scalable to suiteach station’s needs and limitations. It was designed to extend the functionality of a modern UPS (uninterruptible power supply) and PDU (power distribution unit) into a cost-effective, low power in-vault solution. The WATC
PowerHub has command and control of up to six independent loads. It monitors the SOH of all charge sources, each independent load, and up to six individual batteries versus a single battery bank. It employs a configurable phased
Low Voltage Disconnect to allow a station operator the ability to define a deescalating phased power down. Using a PCB (printed circuit board) as its base,the WATC PowerHub has a 3-d printed housing and leverages a modular I/O
and relay suite for scalability. The PowerHub improves in-vault commandand-control points and SOH station operators are able to leverage remotely,
significantly improving remote operations, troubleshooting, response time,and in turn increased up-time across the network. In this presentation we
describe the WATC Powerhub and operational improvements observed fromrecent deployments across the globe.
poster 8
Evaluation of Station Performance of the Idaho National
Laboratory Seismic Monitoring Network Using Network
Detection Thresholds
BOCKHOLT, B., Idaho National Laboratory, Idaho, USA, blaine.bockholt@
inl.gov; SANDRU, J., Idaho National Laboratory, Idaho, USA, john.sandru@
inl.gov
The Idaho National Laboratory (INL) Seismic Monitoring Network is locatedin Eastern Idaho and monitors a portion of the Intermountain Seismic Belt.
It has been in place for 50 years and has undergone several major changes.
The most recent of which has been the transition to the Antelope real-time
acquisition system and the implementation of automatic phase picking algorithms to aid in analysis. This study discusses the efforts to evaluate the performance of the INL seismic monitoring network (and other surrounding
stations) using the new real-time acquisition system. The method outlined by
Wilson et al. (2021) is used to develop an empirical relationship between theobservability of local earthquakes as a function of magnitude and distance.
This relationship is used to produce detection thresholds for both P and S
waves for all stations of interest. The INL seismic network has two main goals:
monitor tectonic and volcanic related events and measure ground motions
for input into seismic hazard analysis. Because of these two overall objectives,
several seismic stations are installed near critical facilities and therefore are
not as quiet as stations which are used primarily for earthquake detection.
This is reflected in their detection thresholds, which are much smaller for stations near facilities. This study also shows “holes” in the monitoring network
where the detection of smaller earthquakes is highly dependent on sparsely
placed seismic stations. The results of this study will be used to govern plansfor expansion of earthquake monitoring in Idaho and the surrounding region
and to fine tune the detection thresholds for individual stations.
poster 9
Field Evaluation of Seismic Sensors for Monitoring
Earthquakes, Tsunamis, Volcanoes, and Geodesy
BODIN, P., University of Washington, Washington, USA, bodin@uw.edu;
VENKATESWARA, K., Paroscientific, Inc. & Quartz Seismic Sensors, Inc.,
Washington, USA, krishna@paroscientific.com; WILCOCK, W., Universityof Washington, Washington, USA, wilcock@uw.edu; TOBIN, H., Universityof Washington, Washington, USA, htobin@uw.edu; PAROS, J., Paroscientific,
Inc. & Quartz Seismic Sensors, Inc.,, Washington, USA, paros@paroscientific.
com
Real-time seismic and geodetic networks increase the resilience of societies bymonitoring geophysical hazards and providing high-quality data for underlying scientific studies. Traditional broadband seismometers and tiltmeters do
not have the range to measure strong seismic events, and traditional strong
motion sensors lack the sensitivity or stability to make good long-term geodetic measurements. There is a need for improved, high-resolution measurements of earthquake shaking, tilts, Earth tides, slow-slip events, and geodesy
over a time spectrum spanning fractions of a second to years. Three fundamental science requirements to measure geohazards and geodesy for both
onshore and offshore sites are:
·Low noise floor·Long-term stability·Wide dynamic range (no clipping and omni-directionality)
We tested seismic and tilt sensors in a moderately quiet vault near
Hanford, Washington. We present analyses of sensor performance including
noise floor, short-term examples of local and distant earthquakes, measurements of Earth tides, and long-term stability for slow slip events and geodesy.

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The sensors represent different technologies, including: (1) resonant quartz
crystal - Quartz Seismic Sensors, (2) optical interferometric - Silicon Audio,and (3) conventional broadband—Nanometrics Trillium 120PA. Data are
openly available from the EarthScope DMC archive. Initial results showed thatthe quartz accelerometers and tiltmeters met the most important noise floor
requirements at longer periods (>5s) and their observations of Earth tides
were higher fidelity (better signal to noise) than the broadband seismometer.
The quartz sensors can also make long-term measurements of geodesy that are
only limited by instrument drift. The optical interferometric accelerometers
performed well at higher frequencies, but they are not omni-directional, andtheir design precludes long-term geodetic measurements.
poster 10
Performance of Raspberry Shake vs. Kentucky Seismic andStrong-Motion Network Instruments
SCHMIDT, J. P., University of Kentucky, Kentucky, USA, jon.schmidt@
uky.edu; CARPENTER, S., University of Kentucky, Kentucky, USA, seth.
carpenter@uky.edu; WANG, Z., University of Kentucky, Kentucky, USA,zmwang@uky.edu; KALINSKI, M., University of Kentucky, Kentucky, USA,michael.kalinski@uky.edu
Kentucky is affected by three seismic zones: the New Madrid (NMSZ),
Wabash Valley, and Eastern Tennessee Seismic Zones. The NMSZ is of particular interest as it previously hosted several large earthquakes >7.0 M in 18111812 and maintains the highest seismicity rate in the Central and Eastern U.S.
This heightened risk of strong shaking has motivated improvements in detection capabilities of regional seismic networks for possible implementation ofearthquake early warning (EEW) systems. EEW detection capabilities can be
improved by upgrading existing seismic stations with more sensitive instrumentation, or by densifying the backbone regional network with lower costsensors like Raspberry Shake (RS) devices. Here we tested the performance ofRS geophones and accelerometers by collocating five RS-3D and one RS-4D atfive Kentucky Seismic and Strong-Motion Network (KSSMN) permanent stations and monitoring seismicity. During this two-year deployment, 25 usable
earthquakes (magnitude ≥ 2.5) were recorded. Our comparisons were basedon peak ground velocity (PGV), duration of strong shaking, Arias intensity
values, as well as waveform and spectral amplitudes of the RS devices relative
to the KSSMN instruments. Preliminary results indicate that the PGV andshaking-duration of small magnitude events are very comparable between
RS and KSSMN instruments. Waveforms and spectral amplitudes also match
well between RS and KSSMN instruments, specifically where RS and KSSMN
instruments were installed within the same vault. Other sites where the RS was
located 2-5 m away from the permanent KSSMN instrument exhibited slightly
lower spectral amplitudes than KSSMN instruments. This shift may be related
to unaccounted-for responses of the RS geophones, the installation locationsof the RS relative to the permanent KSSMN instruments, or a combination of
both. Because the ground-motions captured were all weak-motion, the instrument self-noise of the RS-4D’s MEMS strong-motion accelerometer channels
prevented directly comparing its performance.
poster 11
Access to Seismic Waveform Data, Services and Products inthe Euro-Mediterranean Region and Beyond: Status andOutlook of Orfeus Coordinated Programs
CAUZZI, C., ETH Zurich, Zürich, Switzerland, carlo.cauzzi@sed.ethz.
ch; CLINTON, J., ETH Zurich, Zürich, Switzerland, jclinton@sed.ethz.ch;
CRAWFORD, W., Institut de Physique du Globe de Paris, Paris, France,
crawford@ipgp.fr; CUSTÓDIO, S., University of Lisbon, Lisbon, Portugal,
sicustodio@fc.ul.pt; D’AMICO, S., University of Malta, Valletta, Malta,sebastiano.damico@um.edu.mt; EVANGELIDIS, C., National Observatoryof Athens, Athens, Greece, cevan@noa.gr; HABERLAND, C., GFZ Potsdam,
Potsdam, Germany, haber@gfz-potsdam.de; KIRATZI, A., Aristotle
University of Thessaloniki, Thessaloniki, Greece, kiratzi@geo.auth.gr;
LUZI, L., Istituto Nazionale di Geofisica e Vulcanologia, Milan, Italy, lucia.
luzi@ingv.it; KOLÍNSKÝ, P., Czech Academy of Sciences, Prague, Czechia(Czech Republic), petr.kolinsky@ig.cas.cz; ROUMELIOTI, Z., University ofPatras, Patras, Greece, zroumelioti@upatras.gr; SCHAEFFER, J., Université
Grenoble Alpes, Grenoble, France, jonathan.schaeffer@univ-grenoble-alpes.
fr; SIGLOCH, K., Université Côte d’Azur, Sophia Antipolis, France, sigloch@geoazur.unice.fr; SLEEMAN, R., ORFEUS Data Center and Royal Netherlands
Meteorological Institute, De Bilt, Netherlands, reinoud.sleeman@knmi.nl;
STROLLO, A., GFZ Potsdam, Potsdam, Germany, strollo@gfz-potsdam.de
ORFEUS (Observatories and Research Facilities for European Seismology,
http://orfeus-eu.org) is a non-profit foundation that harmonizes the collection, archival and distribution of seismic waveform (meta)data, services

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and products targeted to a broad community of seismological data users, onbehalf of more than 60 participating seismological Institutions (https://orfeus.
readthedocs.io/en/latest/governance.html) representing the community ofEuro-Mediterranean seismic networks and monitoring agencies. ORFEUS
is one of the founding members of EPOS Seismology (www.epos-eu.org/tcs/
seismology) and a fundamental partner of EC-funded projects (http://orfeuseu.org/organization/projects/). ORFEUS services are largely integrated in the
EPOS Data Access Portal (www.ics-c.epos-eu.org). ORFEUS comprises: (i)the European Integrated waveform Data Archive (EIDA; orfeus-eu.org/data/eida); (ii) the European Strong-Motion databases (orfeus-eu.org/data/strong);
and iii) the European mobile intrument pools (orfeus-eu.org/data/mobile).
Products and services for computational seismology are also considered for
integration in the ORFEUS domain. Currently, ORFEUS services provide
access to the waveforms acquired by ~24,000 stations, including dense temporary experiments, with strong emphasis on open, high-quality data. Accessto data and products is ensured through state-of-the-art information andcommunication technologies, with strong emphasis on federated web services, clear policies and licenses, and acknowledging the crucial role playedby data providers. Significant efforts are underway, by ORFEUS participating
institutions, to enhance the existing services to tackle the challenges posed
Big Data, and to actively encourage interoperability and integration of multidisciplinary datasets in seismological and Earth Science workflows. ORFEUS
and its Participants actively collaborate with global and regional initiatives
with similar scope like the FDSN and EarthScope. ORFEUS also implements
Community services that include software and travel grants, webinars, workshops and editorial initiatives.
poster 12
From Dense Seismic Monitoring to Mass-Movement
Hazards and Their Impacts: Demonstrating an Operational
Workflow and Associated Data Services
CAUZZI, C., ETH Zurich, Zürich, Switzerland, carlo.cauzzi@sed.ethz.
ch; BÖSE, M., ETH Zurich, Zürich, Switzerland, mboese@sed.ethz.ch;
CLINTON, J., ETH Zurich, Zürich, Switzerland, jclinton@sed.ethz.ch;
DANCIU, L., ETH Zurich, Zürich, Switzerland, laurentiu.danciu@sed.
ethz.ch; KÄSTLI, P., ETH Zurich, Zürich, Switzerland, kaestli@sed.ethz.
ch; KNUPFER, J., Formerly at ETH Zurich, Zürich, Switzerland, knupferj@
student.ethz.ch; PAPADOPOULOS, A., Formerly at ETH Zurich, Zürich,
Switzerland, athanasios.papadopoulos@sed.ethz.ch; WIEMER, S., ETH
Zurich, Zürich, Switzerland, stefan.wiemer@sed.ethz.ch
We present and discuss a seismological workflow that uses rapid ground shaking information from ShakeMap (https://usgs.github.io/shakemap/) as input
to the calculation of mass-movement hazards and their possible impacts onlifelines. The workflow is demonstrated in the Swiss Alpine region, where
the Swiss Seismological Service (SED) at ETH Zürich (http://www.seismo.
ethz.ch/en/home/) presently operates real-time nation-wide seismic monitoring networks comprising more than 75 broadband, 193 strong-motion,and 23 short-period sensors (e.g., CH network: https://doi.org/10.12686/
SED/NETWORKS/CH; other networks at https://networks.seismo.ethz.ch/),along with a portfolio of real-time and rapid earthquake products including
ShakeMap (https://doi.org/10.1785/0220220087). ShakeMap is used in thisapplication as ground shaking information input to the calculation of massmovement occurrence probabilities - made available as ShakeMap-associatedproducts - which are in turn convolved with lifeline exposure data to estimate
possible impacts along with costs and benefits of selected mitigation actions
during an ongoing earthquake sequence. Based on free and open source software frameworks, the strategy to calculate ground-shaking and mass-movement hazard information is highly portable to other and broader contexts, andinteroperability is being established with the European ShakeMap framework(https://doi.org/10.5194/egusphere-egu23-5937) within ongoing national andEC projects (e.g. https://www.geo-inquire.eu/).
poster 13
Evolution of Volcano Hazards Monitoring of the Cascades
Chain in Washington and Oregon: Cascades Volcano
Observatory
DAROLD, A. P., U.S. Geological Survey, Washington, USA, adarold@usgs.
gov
The U.S. Geological Survey Cascades Volcano Observatory (USGS CVO)
began expanding its geophysical network for monitoring hazards associated with the Cascades Volcanoes throughout Washington and Oregon in
2001. Nine of the Washington and Oregon volcanoes have been classified as
High- or Very-High-Threat by the USGS due to their eruptive history, typesof hazards, and potential impact to populations and infrastructure. CVO’s

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hazard-monitoring goals are to detect and interpret real-time geophysicaland geochemical signals to provide early and accurate warnings of volcanic
unrest and eruptions. Throughout this timeframe CVO has worked in collaboration with the Pacific Northwest Seismic Network (PNSN) with support
from the EarthScope GAGE facility in growing the network to cover 6 of the
9 High- and Very-High-Threat volcanoes. At present the CVO network has
a total of 86 real-time stations including a broad spectrum of stand-alone
and co-located monitoring instrumentation (seismic, infrasound, deformation, gas, and cameras) with metadata and continuous waveform data sharedpublicly in near-real-time and daily GNSS data and metadata available from
EarthScope SAGE & GAGE, respectively. Volcano networks have uniquechallenges regarding power requirements and telemetry paths due to theirremoteness and harsh winter environments. The CVO network has seen significant changes in technology, federal regulations, and funding over the last
several decades that have both hindered and aided the growth of the network.
Changes in federal regulations forced agencies to switch from analog to digitaltelemetry which proved to be a challenge early on but advances in cellular andsatellite telemetry technology along with increases in funding have made theswitch more viable. Even with substantial growth and enhancements, significant monitoring gaps still exist at most Washington and Oregon High- andVery-High-Threat volcanoes. Because of this, CVO’s network will continue
to improve real-time monitoring capabilities to aid scientists in better assessing volcanic processes in near-real time throughout Washington and Oregon.
poster 14
Seismic Network Modernization and Expansion in Ukraine
FARFULIAK, L., Subbotin Institute of Geophysics of the National
Academy of Science of Ukraine, Kyiv, Ukraine, myronivska@gmail.com;
AMASHUKELI, T., Subbotin Institute of Geophysics of NAS of Ukraine;
GFZ German Research Centre for Geosciences, Kyiv, Ukraine, amash.
tanya@gmail.com; ADERHOLD, K., EarthScope Consortium, , USA, kasey.
aderhold@earthscope.org; CHIANG, A., Lawrence Livermore National
Laboratory, California, USA, chiang4@llnl.gov; MACKEY, K., Michigan State
University, Michigan, USA, mackeyke@msu.edu; BURK, D., Michigan State
University, Michigan, USA, burkdani@msu.edu; HANIIEV, O., Subbotin
Institute of Geophysics of the National Academy of Science of Ukraine,
Kyiv, Ukraine, aganiev@gmail.com; KUPLOVSKYI, B., Subbotin Institute ofGeophysics of the National Academy of Science of Ukraine, Lviv, Ukraine,
bohdan_kuplyovsky@yahoo.com; PROKOPYSHYN, V., Subbotin Institute ofGeophysics of the National Academy of Science of Ukraine, Lviv, Ukraine,
pvasyl70@gmail.com; PETRENKO, K., Subbotin Institute of Geophysics of
the National Academy of Science of Ukraine, Kyiv, Ukraine, pekar232@gmail.
com
The Subbotin Institute of Geophysics of the National Academy of Science of
Ukraine started research to expand the Ukrainian National Seismic Network(network code UT) through the installation of permanent broadband seismic
stations. The initiative to expand and modernize of the seismic network in
Ukraine aims to enhance the country’s national seismic monitoring and earthquake response capabilities. It will also facilitate real-time access to high-quality data from newly established stations, benefiting the global scientific community. The initial project was realized with the support and collaborationof the U.S. Department of Energy, Lawrence Livermore National Laboratory,
Michigan State University, and the EarthScope Consortium.
Optimizing the effectiveness of investigating both existing and new seismic sites requires careful consideration of various factors during the initial
selection, preparation, and installation of seismic stations. A crucial aspectof the site selection process for any seismic network involves evaluating theseismic noise levels at potential locations. The ability of a seismic station toaccurately detect earthquakes and capture high-quality waveforms is contingent upon understanding the signal and noise characteristics of the chosensite. In addition to the inherent background noise of the Earth, it is essential
to account for other sources of noise, such as those associated with nearby
infrastructure.
An initial noise survey was conducted for some existing and new sitesof the Ukrainian National Seismic Network: at some existing sites LUBU
(Liubeshka, Lviv district), SHIU (Shidnytsia, Lviv district), PLTV (Poltavacity), and at new sites: SUGL (Mala Uhol`ka, Zakarpattia district), TURU
(Tur`je, Lviv district), and GOSU (Hoshiv, Lviv district). We analyzed andreported the data in the form of both time-history examples and standardized
Probability Density Function noise plots. Seismic spectral analysis is basedon the calculation of Power Spectral Density distribution using a Probability
Density Function following the approach of McNamara and Buland (2004).

poster 15
Hydrothermal Monitoring Site in Norris Geyser Basin,
Yellowstone National Park, Wyoming, United States ofAmerica
FORBES, N. M., University of Utah, Utah, USA, nicholasforbes95@gmail.
com; FARRELL, J., University of Utah, Utah, USA, fishynp@gmail.com;
HALE, J. M., University of Utah, Utah, USA, hale.jmark@gmail.com; TROW,
A. J., University of Utah, Utah, USA, andy.trow@utah.edu; ALEXANDER, J.,
University of Utah, Utah, USA, u1275458@gcloud.utah.edu; POLAND, M.,
U.S. Geological Survey, Washington, USA, mpoland@usgs.gov
Yellowstone National Park houses one of the largest and most active hydrothermal systems in the world containing over half of all known geysers.
Additionally, the largest hydrothermal eruption crater is positioned in northern Yellowstone Lake (Mary Bay) approximately 35 kilometers to the southwest of Norris Geyser Basin. In addition, a small hydrothermal explosion
occurred in the Norris Geyser Basin in 1989 when Porkchop Geyser exploded
sending rocks and hot water/mud many meters from the feature. With suchhigh seismic and hydrothermal risk, a network of monitoring sites is being
developed to actively observe the signals produced by this vast plumbing system. During August of 2024, the University of Utah Seismograph Stations,
U.S. Geological Survey, EarthScope Consortium, and Yellowstone National
Park personnel installed a hydrothermal monitoring site (YNB) in the Norris
Geyser Basin of Yellowstone National Park to complement the existing 3-component broadband site within the basin (YNM). Station YNB is composed ofa 3-channel broadband seismic sensor (sampling at 100Hz), 3-channel infrasound array (sampling at 100Hz), compact weather station, and a full GNSS
monument, and it is the most complete monitoring site in the Yellowstone
region. In this study we will show seismic, infrasound, and geodetic signalsthat have been observed in the short time the station has been deployed andhow data are being processed to assist in the further understanding of the
Yellowstone Volcanic System.
poster 16
Improving Earthquake Monitoring Capabilities in Ohio
With Low-Cost Robust Posthole Vaults
FOX, J. L., Ohio Seismic Network, Ohio, USA, jeffrey.fox@dnr.ohio.gov
The Ohio Seismic Network (OhioSeis) has undergone a significant transformation in instrumentation and vault design over the past decade. The current, modern network has substantially increased the number of earthquake
detections across the region and improved our understanding of local seismic
hazards and faulting mechanisms. Initially planned and created as a small
cooperative network with single-component, narrowband instruments placedindoors, today OhioSeis consists of 29 free-field, broadband stations comprised of a selection of former Transportable Array (TA) vaults, shallow-surface barrel vaults, and more recently, posthole-style vaults. Recent work has
focused on improving the viability and lowering the costs of these postholeemplacements. A complete off-the-shelf solution has been developed that canbe installed permanently or slightly altered for rapid temporary deployments,
such as during aftershock sequences. Depending on emplacement depth, acomplete vault can be installed in as little as two hours for less than $100.
Vault flooding, instrument damage, and station noise impacting OhioSeis
stations have decreased with these new posthole emplacements. Earthquake
catalog magnitude of completeness has been lowered to approximately ML
1.5. Today, OhioSeis is better equipped to detect low-magnitude earthquakes
across the entire state and better serve the public, researchers, planners, andfirst responders with high-quality seismic data.
poster 17
Near Real-Time Earthquake Catalog for the Endeavour
Segment of the Juan De Fuca Ridge: Integrating
Community Code Into Ocean Networks Canada’s Ocean 3.0
Data Portal
HEESEMANN, M., Ocean Networks Canada, Victoria, Canada, mheesema@
uvic.ca; HUTCHINSON, J., Ocean Networks Canada, Victoria, Canada,hutchij@uvic.ca; FERGUSON, E., Ocean Networks Canada, Victoria, Canada,
elif@uvic.ca; BIFFARD, B., Ocean Networks Canada, Victoria, Canada,
bbiffard@uvic.ca; KRAUSS, Z., University of Washington, Washington,
USA, zkrauss@uw.edu; WILCOCK, W. S. D., University of Washington,
Washington, USA, wilcock@uw.edu; SCHLESINGER, A., Ocean Networks
Canada, Victoria, Canada, schlesin@uvic.ca; PIRENNE, B., Ocean Networks
Canada, Victoria, Canada, bpirenne@uvic.ca
Ocean Networks Canada’s NEPTUNE observatory consists of an 800 km fiberoptic cable loop that provides power and real-time communication to a net-

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work of Ocean Bottom Seismometers (OBS) offshore Vancouver Island. The
network covers the northern end of the Cascadia Subduction Zone, the abyssal plain of the Cascadia Basin, and extends all the way out to the Endeavour
Segment of the Juan De Fuca Ridge. Community members Zoe Krauss andWilliam Wilcock developed a sophisticated software package that includes
components programmed in Matlab, Python, and Fortran, which they used
to create a long-term micro-earthquake catalog for the Endeavour Segment,
constructed from OBS observations spanning nearly three decades. The catalog includes the last rupture of the Endeavour Segment that took place via
a sequence of dike emplacements between 1999 and 2005. Since 2016, theearthquake catalog data were obtained from a small network of 3-5 cabled
OBS directly on top of the ridge that are connected to the NEPTUNE observatory. The waveform data are publicly available through the Seismological
Facility for the Advancement of Geoscience (SAGE/IRIS) under the networkcode NV and near-real-time updates of the catalog are made available at
http://endeavour.ocean.washington.edu by the authors of the code.
This presentation shows how we plan to integrate user community
provided code into Ocean Networks Canada’s Oceans 3.0 Data Portal andrun it in an operational environment. We will use the code to generate theEndeavour earthquake catalog as a test case and provide details about the system requirements, different design options, and compare the approach to ourexisting catalog of Earthquake Early Warning detections. Once integrated, thereal-time catalog will provide context for non-seismologists looking at othermeasurements of the hydrothermal system that are available through Oceans
3.0. This catalog development is timely since an increase in seismic activity
hints to a new rupture in the not too distant future.

ALLEN, R. M., University of California, Berkeley, California, USA, rallen@berkeley.edu
The Northern California Earthquake Data Center (NCEDC) is a permanentarchive and distribution center for multiple types of digital data related toearthquakes in central and northern California. The NCEDC is located at
the university of California, Berkeley, and has been accessible to users via
the Internet since mid-1992. Time series data mainly come from broadband,
short period, and strong motion seismic sensors, as well as from other geophysical instruments. Earthquake catalogs include origin time, hypocenter,magnitude, moment tensor, focal mechanisms, phase arrivals, codas, andamplitude data. Metadata and instrument response for seismic sites are accessible in various formats for all data channels archived at the NCEDC. The
NCEDC also provides support for earthquake processing and archiving activities of the Northern California Earthquake Management Center, a componentof the California Integrated Seismic Network (CISN). Data holdings currently
consist of more than 184 TB of data encompassing 29 networks and 2,640
stations. In 2023, the NCEDC archive became part of the AWS (Amazon Web
Services) Open Data Sponsorship Program and all of its data are now mirrored in the cloud (s3://ncedc-pds; us-east-2 region). Tutorials (https://ncedc.
org/db/cloud/getstarted-pds.html) and data structure (https://ncedc.org/
db/cloud.html) are available to facilitate user access to this public data set.
This allows the NCEDC to leverage AWS cloud infrastructure and provide
users the ability to provision gigabit connections to the archive as well as takeadvantage of the computational resources offered by AWS.

poster 18
AdriaArray—a Passive Seismic Experiment to Study the
Geodynamics and Geohazards in Central MediterraneanKOLÍNSKÝ, P., Institute of Geophysics of the Czech Academy of Sciences,
Prague, Czechia (Czech Republic), petr.kolinsky@ig.cas.cz; MEIER, T.,
Christian-Albrechts-Universität zu Kiel, Kiel, Germany, thomas.meier@ifg.
uni-kiel.de; SEISMOLOGY GROUP, t., AdriaArray, Kiel, Prague, Germany,
Czechia (Czech Republic), petr.kolinsky@volny.cz

poster 20
Assessment of Data Quality for the Alaska Geophysical
Network
MCFARLIN, H., Alaska Earthquake Center, Alaska, USA, hlmcfarlin@alaska.
edu; RUPPERT, N., Alaska Earthquake Center, Alaska, USA, naruppert@
alaska.edu; MURPHY, N., Alaska Earthquake Center, Alaska, USA,nwmurphy@alaska.edu; HOLTKAMP, S., Alaska Earthquake Center, Alaska,
USA, sgholtkamp@alaska.edu; HESLOP, J., Alaska Earthquake Center, , USA,jheslop@alaska.edu

The densely populated area around the Adriatic Sea is prone to geohazards
including earthquakes, tsunamis, landslides, flooding and volcanic activity
as the Adriatic Plate is consumed in a tectonically active belt spanning from
Sicily, over the Apennines to the Alps, Dinarides and Hellenides, generating
earthquakes up to magnitude 7. To identify drivers of associated plate deformation, the plate boundaries, slabs, properties of active faults and of the stressfield have to be determined. AdriaArray, a dense plate-scale regional seismic
network deployed in the central Mediterranean, provides data for imaging of
the crustal and upper mantle structure and for the analysis of seismic activity.
The network consists of 1000 permanent and 446 temporary BB stations from
24 mobile pools. 95 % of the planned temporary stations have already been
installed. A homogeneous coverage by broadband stations in an area from
the Massif Central in the west to the Carpathians in the east, from the Alpsin the north to Sicily and the Kefalonia Fault Zone in the south, is achieved.
The backbone network (2022–2025) is complemented by locally densified andLargeN networks, e.g. in the western Carpathians (Poland, Slovakia, Hungary),
along the Dubrovnik fault (Croatia), in the Vrancea region (Romania), and in
Albania. Data recorded by the temporary stations is transmitted in real-timeand archived at 9 nodes of the European Integrated Data Archive (EIDA).
Regular availability and quality checks ensure high data usability. AdriaArray,the largest passive seismic experiment in Europe so far, is based on cooperation between local network operators, mobile pool providers, field teams,
ORFEUS (Observatories and Research Facilities for European Seismology)
and EPOS (European Plate Observing System), encompassing 63 institutions
from 30 countries. They form the AdriaArray Seismology Group, founded in
2022. Collaborative Research Groups are being established to coordinate thedata analysis. We present the maps of the AdriaArray Seismic Network, station properties, coverage, contributing institutions and collaborative research
topics.

One of the Alaska Earthquake Center’s (AEC) core missions is to monitor
geophysical events and conditions in the state of Alaska. These events are typically unique, unpredictable, and unrepeatable, so detecting and characterizingthese requires AEC to maximize its continuous, real-time geophysical monitoring throughout Alaska. AEC maintains 255 geophysical stations, referred
to as the Alaska Geophysical Network (AGN). The environments around
Alaska are varied and often create harsh conditions. Maintaining AEC’s
monitoring capabilities requires constant vigilance to detect, investigate, andtroubleshoot problems at stations, and properly document the issues to support short-term repairs and improve the overall network resilience in the longterm. Data quality control (QC) at AEC includes established protocols forseismic as well as non-seismic data (meteorological, infrasound, GNSS). We
define “QC” broadly as quantitative data that help assess the performance ofstations. QC metrics are derived from the raw data and state-of-health channels and the EarthScope MUSTANG website. This includes data on the overall
station health (data completeness, clock quality, latency), as well as data specific to individual channels (broadband, strong-motion, weather, infrasound).
Standardized QC reports are produced bi-weekly and include percent availability, gaps, and amplitude-related metrics.
In preparation for the next field season, we have conducted a networkwide assessment of the quality of broadband data based on analysis of sensor
mass positions and site noise characteristics. Analysis of regional and temporal trends in mass positions of broadband sensors allows us to identify sites
with chronic instability issues. Analysis of noise characteristics based on PDF
metrics allows us to identify general regional trends and outliers. Additionally,
we apply amplitude-based strong motion metrics to identify malfunctioning
strong motion sensors. We aim to use this analysis for targeted recommendations for field maintenance that may include sensor replacements and/or
improvement to sensor housing.

poster 19
Northern California Earthquake Data Now Available in
AWS CloudMARTY, J., University of California, Berkeley, California, USA, jmarty@
berkeley.edu; ZUZLEWSKI, S., University of California, Berkeley, California,
USA, stephane@berkeley.edu; TAIRA, T., University of California, Berkeley,
California, USA, taira@berkeley.edu; THOMPSON, S., University ofCalifornia, Berkeley, California, USA, stephen.thompson@berkeley.edu;

poster 21
A Review of Recent IDA Sensor Performance
MELLORS, R. J., University of California, San Diego, California, USA,rmellors@ucsd.edu; EBELING, C. W., University of California, San Diego,, USA, cebeling@ucsd.edu; DAVIS, P., University of California, San Diego,
California, USA, pdavis@ucsd.edu; BERGER, J., University of California, San
Diego, California, USA, jberger@ucsd.edu

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The IDA network, which comprises one-third of the Global Seismic Network(GSN), consists of 40 high-quality seismic stations located around the world

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instrumented to support high-fidelity recording of very low-amplitude andvery long-period seismic signals.
IDA stations are distributed about 50/50 between those having vault andborehole-focused infrastructure. At those with the latter, shallow (~7 m) boreholes complement deep (~100 m) boreholes. Both weak- and strong-motion
sensors are included in a standard IDA station instrumentation configuration.
The network-wide upgrade of the no-longer-supported Geotech
KS-54000 and Streckeisen STS-1 instruments to modern very-broadband(VBB) STS-6A and T360 seismometers (manufactured by Streckeisen andNanometrics, respectively) is nearly complete. These “primary” seismometers are complemented with “secondary” instruments---most commonly aStreckeisen STS-2.5 or STS-5A, or a Nanometrics T120---installed on the pieror in the shallow borehole, depending upon station infrastructure.
The ongoing upgrade offers the opportunity to carry out a broad examination of the instrument performance over a period of about a decade. Here
we present results of that investigation.
Anomalies in instrument behavior, identified via power spectral density analysis of ambient seismic noise and variation from nominal instrument
response, are viewed as general proxies for instrument anomalies and hardware failures. Performance tracking has been conducted since the beginningof the VBB sensor upgrades about a decade ago. The overall performance of
VBB instrumentation to date has been somewhat worse than expected, witha significant number of IDA STS-6A complete failures attributed to a faulty
electronic component and additional failures due to other problems.
poster 22
High Frequency Ground Motion and Electrical Calibrationsof Seismometers Used at IMS Stations
MERCHANT, B. J., Sandia National Laboratories, New Mexico, USA,bjmerch@sandia.gov; BLOOMQUIST, D. K., Sandia National Laboratories,
New Mexico, USA, dkbloom@sandia.gov; SLAD, G. W., Sandia National
Laboratories, New Mexico, USA, gwslad@sandia.gov
Calibration of seismometers used in nuclear explosion monitoring systems,
such as the International Monitoring System (IMS), is important for providing confidence in the measurements of ground motion and the resulting
analysis that is performed on the waveform time series data. In this study,
six models of seismometers widely used at IMS stations have been calibratedusing high precision vertical and horizontal shake tables. The calibration procedure follows the ISO 16063-11 standard for primary vibration calibration
by laser interferometry. The sensors are evaluated from 0.1Hz to 50Hz andthe calibration results are directly compared to the sensors’ nominal responsemodels provided by the manufacturers. Electrical calibrations are then performed on the same sensors which mimics how fielded IMS seismometers
are calibrated. The sensors’ response to ground motion, measured with theshake tables, is removed from the electrical calibration data so that the performance of the electrical calibration system itself can be determined. Thismeasured calibration system response is then directly compared to manufacturers’ specifications.
Results from this study offer insight into the higher frequency performance of seismometers used in the IMS and also demonstrate how primaryground motion calibrations can be used to verify sensor performance andidentify issues that relative calibration methods may not detect.
poster 23
Machine Learning Earthquake Catalog Performance for
Characteristic Alaska Settings
NOEL, S. K., University of Alaska Fairbanks, Alaska, USA, sknoel@alaska.
edu; WEST, M. E., University of Alaska Fairbanks, Alaska, USA, mewest@
alaska.edu; RUPPERT, N. A., University of Alaska Fairbanks, Alaska, USA,naruppert@alaska.edu
Globally pre-trained machine learning (ML) earthquake phase-detection
algorithms promise broadscale regional transferability in addition to realtime monitoring applications. These algorithms continue to gain research
popularity and are routinely used to generate earthquake catalogs withthousands of additional events. We apply a globally pre-trained ML earthquake phase-detection algorithm to four different characteristic regions andsequences to generate a ML earthquake catalog. We compare the ML catalog with the Alaska Earthquake Center’s real time (RT) and analyst-reviewed(AR) catalogs. We establish a binary classification framework to compare the
RT and ML catalogs to the AR catalog. We visually assess and label additional
RT and ML events as earthquakes or other signals. Finally, we apply a minimum catalog inclusion criteria based on Alaska Earthquake Center analyst
review standards to additional, visually-confirmed RT and ML catalog earth-

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Seismological Research Lettersquakes, establishing a one-to-one performance comparison between catalogs.
For each region, we find the ML catalog provides a consistently higher matchwith the AR catalog than the RT catalog. However, each region’s ML catalog
introduces additional complications ranging from misidentification of nonearthquake signals to missed detection of large magnitude, felt earthquakes.
These discrepancies warrant further training dataset scrutiny and suggest
the establishment of a location based training dataset is necessary for consistent and reliable ML phase detection performance across the Alaska seismic
network.
poster 24
Monitoring Induced Microseismicity (M>-1) With the Local
Network at the Utah Frontier Observatory for Research in
Geothermal Energy (FORGE)
PANKOW, K. L., University of Utah, Utah, USA, kris.pankow@utah.edu;
WHIDDEN, K., University of Utah, Utah, USA, katherine.whidden@utah.
edu; RUTLEDGE, J., Santa Fe Seismic LLC, New Mexico, USA, rutledge@
swcp.com; PETERSEN, G., GFZ Potsdam, Potsdam, Germany, gesap@gfzpotsdam.de; NIEMZ, P., University of Utah, Utah, USA, peter.niemz@utah.
edu; BRADSHAW, P., NA, Colorado, USA, p.gallagher.bradshaw@gmail.com;
FORBES, N., University of Utah, Utah, USA, u0875540@gcloud.utah.edu
The Utah Frontier Observatory for Research in Geothermal Energy (FORGE)
is a Department of Energy project to develop technology to help de-risk
Enhanced Geothermal Systems (EGS) and eventually make them commercially viable. Part of this technology relates to seismic monitoring for hazard
and for mapping geothermal reservoir development. At Utah FORGE a local
seismic network serves for near-real-time monitoring. In addition, several
temporary seismic experiments were applied including the deployment of
nodal geophones and the instrumentation of deep boreholes with strings ofgeophones and DAS (Distributed Acoustic Sensing). Here, we focus on thelocal seismic network that has been in operation since November 2016. This
network has evolved to the current state that includes: (a) seven surface broadband stations, (b) three surface accelerometers, (c) an ~300m deep borehole
instrumented with both a three-component geophone and an accelerometer,and (d) six 30 - 45m deep boreholes instrumented with either collocatedbroadband and accelerometer sensors or broadband sensors. The horizontal
components for the borehole broadband sensors were oriented using teleseismic surface waves. With this network we achieve an Mcomp of ~0.5 for theimmediate Utah FORGE study area and have detected events down to M -1.0
within the geothermal reservoir, allowing detailed studies of the injectioninduced reservoir response. In addition to meeting the monitoring objectives for the Utah FORGE project, this network provided key information in
the analysis of two natural earthquake swarm regions located in proximity
to Utah FORGE and has identified a persistent source area (potential swarmzone) characterized by events with magnitudes below the completeness of the
Utah Regional Seismic Network.
poster 25
Seismic Data Compression and Telemetry Bandwidth
Considerations for EEWPERLIN, M., Nanometrics, Ottawa, Canada, michaelperlin@nanometrics.ca
Earthquake early warning systems depend on the prompt, reliable arrival ofseismic data at network data centers. Network operators invest significant
resources into the design, installation and operation of real-time acquisition
systems to ensure maximum data completeness and minimum data latency, toallow EEW processing modules to detect events and issue warnings as quickly
as possible.
These mission-critical acquisition systems must perform before, during
and after earthquakes, as main shocks are frequently preceded by foreshocks
and followed by aftershocks, which are often just as dangerous. As such, a key
consideration in the design of these systems is the impact that large earthquakes may have. Seismic data is generally encoded using Steim compression, which is a first difference algorithm. During large events the differences
between samples grow, requiring more bits to record and, thus, increasing thedata volume. This results in a surge in the throughput required during large
events. System designers and network operators must be fully aware of thiseffect and plan for it accordingly.
This study expands on existing work to further characterize the impactof large events on seismic data compression and the corresponding spikes inthroughput which must be supported by real-time acquisition systems. The
study will examine the relationship between compression and various factors,
including station magnitude, hypocentral distance, sample encoding technique, packet size, sample rate and system sensitivity.

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poster 26
Sensor Corrections for Multi-Component Monitoring ofSeismic Translation and Rotation
ROSSI, Y., Ludwig Maximilians University of Munich, University of Oregon,
Munich, Germany, rossi.yara@outlook.com; GUATTARI, F., MAÅGM,Le Mans, France, frederic.guattari@maagm.com; BERNAUER, F., Ludwig
Maximilians University of Munich, Munich, Germany, felix.bernauer@lmu.
de; LIN, C., Academia Sinica, Taipei, Taiwan, youngman@earth.sinica.edu.tw
Seismic sensors are used in a variety of applications, such as monitoring of
volcanic activity, structural changes in buildings, seismic velocity changes due
to anthropogenic activities or seismic ground motion on land or underwater.
All applications depend on the sensors reliably recording the motion above
the frequency-dependent noise level of the sensors. However, many of the sensors in use are susceptible to errors that derive from the rotational motion thatcoexists with the translational motion. For example, inertia motion sensors
that rely on translational acceleration observations, such as strong motion
or broadband sensors, are affected by rotations through changing attitude of
the body to the local frame, leading additionally to gravitational errors andinertial effects such as Coriolis, centrifugal, and Euler forces. GNSS sensors,on the other hand, are affected differently and will show errors due to tilting of the antenna pole or phase wind-up from torsional motion. Without
a collocated rotational sensor it is impossible to distinguish, which part ofthe signal is translation and which is due to rotations. Most of these rotation
effects can be corrected with appropriate methods if the local dynamic andstatic rotations are known. However, to correct for inertial effects, additional
information on the distance between the point of rotation and the sensor itself
is required. This might not be possible in field observations. Unfortunately,
the sensor measuring rotations is also falsified by the dynamic tilt and torsion
which misorient the sensor and additionally the false projection of the Earth’s
rotation rate.
Here, we show how the observations from the rotational sensor can not
only be used to self-correct for misorientation of the body versus the local
system, but additionally correct for the error that derives from the earth’s rotation rate being wrongly projected on the channels. The correction scheme will
be provided using not only Euler angles but also the more precise quaternion
angles. We will present results from the application of different correction
schemes on synthetic test scenarios.
poster 27
Comparative Analysis of Seismic Instrument Installations:Surface Vaulted Pier Mount, Direct Burial, and Bore Hole,
Considering Noise Models
SANDRU, J., Idaho National Laboratory, Idaho, USA, john.sandru@inl.gov
The study conducts a comprehensive analysis of three seismic instrument
installation methods—surface pier mount, direct burial, and bore hole—
employing noise models to assess their suitability for seismic monitoring.
Surface pier mount installations, though providing convenient access, are susceptible to surface noise such as wind and cultural signals. Direct burial minimizes disturbances, enhancing signal fidelity despite installation complexityand environmental risks. Additionally, bore hole installations effectively isolate instruments from surface disruptions, offering superior data precision at
the cost of higher complexity and expense. Moreover, bore hole installations
help mitigate thermal variations.
This analysis thoroughly considers factors like cost-effectiveness, accuracy, complexity, and maintenance, outlining the trade-offs between installation ease and data quality across various scenarios. Future research endeavors aim to refine noise models and explore hybrid approaches for optimized
accuracy, including deeper installations ranging from 500 to 1000 meters. In
conclusion, the study’s integration of noise models enhances the understanding of different installations’ noise reduction capabilities, facilitating informed
decisions in deploying seismic monitoring systems across diverse conditions.
The study underscores the importance of considering installation practicality
and noise impact on data quality for effective decision-making.
poster 28
Applying Machine Learning Salves to Network Build-Out“Growing Pains” at the Pacific Northwest Seismic Network
STEVENS, N. T., University of Washington, Washington, USA, ntsteven@uw.edu; HARTOG, R., University of Washington, Washington, USA,jrhartog@uw.edu; NI, Y., University of Washington, Washington, USA,niyiyu@uw.edu; HUTKO, A., University of Washington, Washington, USA,ahutko@uw.edu; DENOLLE, M., University of Washington, Washington,

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USA, mdenolle@uw.edu; WRIGHT, A. K., University of Washington,
Washington, USA, akwright@uw.deu; DE CRISTOFARO, J., U.S. Geological
Survey, Washington, USA, jdecristofaro@usgs.gov
The Pacific Northwest Seismic Network (PNSN) is the authoritative network for near-real-time seismic event monitoring and catalog developmentin Washington and Oregon. The build-out of the PNSN and surrounding
networks over the past decade resulted in a roughly eight-fold increase in
the number of seismic channels being continuously analyzed by the PNSN.
Presently, PNSN’s Earthworm system only analyzes vertical component data
for automated phase detection and only considers P-wave labels when classifying and associating phase detections. All S-wave characterization is conducted by seismic analysts. The increase in data volume per event, combinedwith the PNSN’s relatively low magnitude threshold (2.95+) for rapid review(less than 10 min post event origin time) produces a substantial increase inworkload for PNSN staff.
Machine-learning (ML) seismic analysis tools demonstrate promising accuracy and performance benchmarks for combined phase detection
and classification tasks, particularly PhaseNet and EQTransformer. These
tools may help soothe growing pains from the PNSN build-out; however,most pretrained models and their applications focus on broadband instrument records, and their performance benchmarks are often based on curated
datasets. Data analyzed by the PNSN come from broadband, strong motion,short period, and ocean bottom instruments, have diverse sampling rates
and site qualities, and are subject to imperfect data continuity. To bridge thisgap, we developed a streaming data workflow that couples SeisBench-hosted
ML models to Earthworm’s memory rings, the performance of which we test
in two pilot studies. The first study assesses the accuracy of picks from pretrained ML models against analyst picks for 7749 PNSN catalog earthquakes.
The second study assesses the computational performance of our workflow
on modern PNSN data traffic. Our initial results indicate that these models
can reasonably replicate analyst characterization of P- and S-wave arrivals andour workflow can attain faster-than-real-time processing, at scale, on modest
computational resources.
poster 29
System Monitoring, Telemetry Quality Control, andPlanning Tools for Scsn
STUBAILO, I., California Institute of Technology, California, USA, istubailo@
gmail.com; BHADHA, R., California Institute of Technology, California,
USA, rayo@caltech.edu; WATKINS, M., California Institute of Technology,
California, USA, mwatkins@caltech.edu; HUSKER, A. L., California Instituteof Technology, California, USA, ahusker@caltech.edu; YU, E. C., California
Institute of Technology, California, USA, eyu@caltech.edu; ALVAREZ, M. G.,
U.S. Geological Survey, California, USA, malvarez@usgs.gov; BIASI, G., U.S.
Geological Survey, California, USA, gbiasi@usgs.gov
The Caltech/USGS Southern California Seismic Network (SCSN) is a modern digital ground motion seismic network. It develops and maintains dataacquisition and delivery systems for rapid earthquake information products
like earthquake origins, magnitude, and ShakeMap as well as for Earthquake
Early Warning (ShakeAlert).
We present recent and ongoing innovations in telemetry, system monitoring, and planning tools that keep the network running efficiently and provide timely, high-quality streaming data. We also are developing a quantitative
approach to evaluate station locations for the ShakeAlert mission that allows
us to calculate station expected contributions in terms of likelihood to detect
earthquakes and benefit to people nearby.
Most SCSN sites deliver data continuously to both cloud (AWS) and terrestrial servers located on the Caltech campus in Pasadena. The second dataacquisition path allows SCSN to keep processing waveforms during extreme
events. Redundant data flows make delivery more disruption tolerant integrating flows for data archiving but requires a special approach to handle
arriving duplicate packets.
We also use a bi-axial shake table to test the instrument and telemetry
performance during shaking. By recreating past seismic events and analyzing
system responses, we can design a more robust seismic site and work with fieldengineers on the installation improvements.
We are developing tools to monitor the system state of health as well,including regular measurements of data transport latency and telemetry link
bandwidth from each datalogger to the data center. Using these results, weanalyze performance of new and established connections and track if theymeet our latency and bandwidth targets.

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poster 30
Quick Look at the Reoccupation and Installation of Seismic
Stations at the NNSS
TURLEY, R., Nevada National Security Sites, Nevada, USA, TurleyRS@
nv.doe.gov; SCALISE, M., Nevada National Security Sites, Nevada, USA,scalisme@nv.doe.gov; ZEILER, C. P., Nevada National Security Sites, Nevada,USA, zeilercp@nv.doe.gov; GOCHENOUR, J., Nevada National Security
Sites, Nevada, USA, gochenja@nv.doe.gov; WHITE, R., Nevada National
Security Sites, Nevada, USA, whiterl@nv.doe.gov; PYLE, M., Lawrence
Livermore National Laboratory, California, USA, pyle4@llnl.gov; PITARKA,
A., Lawrence Livermore National Laboratory, California, USA, pitarka1@llnl.
gov; ICHINOSE, G., Lawrence Livermore National Laboratory, California,
USA, ichinose1@llnl.gov; CHEN, T., Los Alamos National Laboratory, New
Mexico, USA, tchen@lanl.gov; PRESTON, L., Sandia National Laboratory,
New Mexico, USA, lpresto@sandia.gov; YOUNG, B., Sandia National
Laboratory, New Mexico, USA, byoung@sandia.gov; DARRH, A., Sandia
National Laboratory, New Mexico, USA, adarhh@sandia.gov; BAL, A., Sandia
National Laboratory, New Mexico, USA, akbal@sandia.gov; GREEN, D., AWE
Blacknest, Brimpton Common, United Kingdom, dgreen@blacknest.gov.uk
Over the last couple of years, the Nevada National Security Sites (NNSS) has
increased the network footprint through the installation of several new seismic stations and by reoccupying historic locations. The overarching goal is
to improve our coverage for modern experiments; however, there is also adesire to understand the integration of historic measurements to modern systems. Although some of the historic locations have been easily reoccupied,some locations prove a bit more challenging to locate. Additionally, we haveattempted to occupy wells that were not designed for seismic systems. These
challenges provide a unique opportunity to compare site and system effects
in the modern data. We will discuss the challenges of these installations andcompare common signals and noise that are recorded by the modern and historic systems. We have also completed huddle tests in various locations thatcompare the downhole and surface signals. We show, through modeling, thedifference in offset of 100 and 200 m gaps to understand the potential contributions of site effects with re-occupied locations. With the various types of
sensors and data recorders, we have a robust data set to help understand someof the issues facing network operators. We are looking at ways to rapidly identify the quality of new stations and ensure that the continuity between historicmeasurements is maintained in our network.
poster 31
A Decade of the Seattle Liquefaction ArrayWILLIAMS, E. F., University of Washington, Washington, USA, efwillia@
uw.edu; DENOLLE, M., University of Washington, Washington, USA,mdenolle@uw.edu; BODIN, P., University of Washington, Washington,
USA, bodin@uw.edu; STEIDL, J. H., University of California, Santa Barbara,
California, USA, steidl@eri.ucsb.edu
Completed in February 2012, the Seattle Liquefaction Array (UW.SLA)
has now recorded more than a decade of continuous borehole accelerationand pore pressure data at a liquefaction-susceptible site in Seattle’s south ofdowntown (SODO) neighborhood. While the seismically quiescent PacificNorthwest has not produced any earthquakes with appreciable excess porepressure generation at SLA during the past decade, the urban ambient seismic noise of industrial south Seattle provides a rich dataset for near-surface
investigations. Quasi-static surface loading from trains passing by or parking
only 5-30 m from SLA drives pore pressure transients as large as 1 kPa at 52
m depth. By computing downhole horizontal-component cross-correlations
with overlapping 40-s windows, we can measure perturbations in near-surface velocity from ballistic shear waves ~1-50 Hz generated by the trains.
Combining these two datasets, we estimate the nonlinear elastic response of
the sediment to poroelastic stress changes, which is as large as +20% dv/v
(averaged 0-60 m) per 300 Pa (measured at 52 m). We also apply ambient
noise coda wave interferometry to study changes in near-surface velocity andattenuation over seasonal to decadal scales. In the coda of vertical component cross-correlations, we find a decade-long monotonic stiffening trend,with 1-10 Hz Rayleigh wave phase velocity increasing by ~4% from 2012 to2022. The horizontal-component and cross-component correlations are more
complex, showing opposing seasonal trends in dt/t at different windows in thecoda and different frequencies, likely representing a depth-dependent phaselag in poroelastic and/or thermoelastic velocity changes.

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Improving Automatic Post-Processing at the Southern
California Seismic Network With Machine Learning
Algorithms
TEPP, G., California Institute of Technology, California, USA, gtepp@caltech.
edu; YU, E. C., California Institute of Technology, California, USA, eyu@
caltech.edu; ZHU, W., University of California, Berkeley, California, USA,zhuwq@berkeley.edu; JASKI, E., California Institute of Technology, California,
USA, ejaski@caltech.edu; NEWMAN, Z., California Institute of Technology,
California, USA, znewman@caltech.edu; SCHECKEL, N., California Instituteof Technology, California, USA, nick@caltech.edu
During routine seismic network operations, data is automatically analyzed
in real-time to identify seismic events and provide initial locations and magnitudes. Additionally, subnet triggers are used to collect unassociated phasepicks from the real-time system that may correspond to an undetected event.
Automatic post-processing may be applied to small events (M<~3) to add andrefine picks and improve the hypocenter and magnitude before analyst review.
The Southern California Seismic Network currently employs the Earthworm/
AQMS real-time system, which uses a short-term average/long-term average(STA/LTA) phase picker and includes a post-processing module (hypomag).
We aim to improve automatic event picks and hypocenters and to reduceanalyst workload by incorporating machine learning algorithms into our existing systems and workflow. Recently, we integrated the deep-learning picker
PhaseNet into our event post-processing. This new hypoPN module has produced ~2-3 times more automatic picks of slightly better average quality thanthe original hypomag, leading to more accurate hypocenters. However, moretime and analysis are needed to determine whether this change has reduced
analyst workload overall. Following the success of hypoPN, we’ve begun workon automating subnet trigger processing. Weekly trigger counts can reach a
few hundred, with around 10% converted to seismic events. Parsing throughthese triggers takes time from other analyst work for only a small increasein cataloged events. With modern algorithms, automatic trigger processing
should be viable. We plan to apply PhaseNet and the machine-learning eventassociator GaMMA to find seismic events in the triggers, with the ultimate
goal of eliminating the need for analysts to review triggers.
poster 33
Güralp SMART Sensors - A Comparison of Next Generation
Mid-Band Seismometers and Traditional Sensor
Technologies
LINDSEY, J. C., Guralp Systems Ltd., Reading, United Kingdom, jlindsey@
guralp.com; WATKISS, N., Guralp Systems Ltd., Reading, United Kingdom,
nwatkiss@guralp.com; HILL, P., Guralp Systems Ltd., Reading, United
Kingdom, phill@gurlap.com; O’NEILL, J., Guralp Systems Ltd., Reading,United Kingdom, joneill@guralp.com
Mid-band seismometer systems usually have shorter period responses andhigher noise floors when compared to broadband seismometer sensors. These
seismometers have been hugely popular with permanent seismic networks
and temporary experiments alike due to their cost-effectiveness, portability,
and relative ease of deployment, allowing for network densification and rapid
deployments. Güralp have historically led the way with such sensors with the
6T and 40T series, seeing use globally in challenging environments over thelast decades.
The Güralp next-generation smart sensor module is designed to beable to operate at any angle, without the use of a mechanical gimbal system.
This allows for the entire sensor package to be rotated during installation anddeployment without sacrificing data quality and means that all three components of the sensor are manufactured to the same design, eliminating inconsistencies in performance between horizontal and vertical components whilst
still maintaining an orthogonal orientation for redundancy. The new generation of sensor makes use of novel materials and techniques to drastically
improve the noise performance over traditional mid-band sensors.
The sensor components include digital elements to the feedback loop,
allowing for the sensor module to have an onboard serial server. This facilitates greater interoperability with Minimus-based digitizer platforms, including automatic pulling of sensor serial numbers, sensor module SOH channels,
and the ability to remotely adjust the long period corner between options of
1s and 120s. This therefore makes the sensor module incredibly easy to deploy
and mitigates against previous requirements for multiple instruments of varying responses.
The sensor module has now been successfully developed into a numberof different packages for varying deployment scenarios including borehole(the Radian), offshore (Aquarius and Maris), vault (Certimus) and postholewww.srl-online.org•

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(Certis) applications. All packages make use of the latest digital technologies
to reduce power consumption down to <300mW.

New Insights into the Development, Testing andCommunication of Seismicity Forecasts
Oral Session • Thursday 2 May • 4:30 pm PacificConveners: Jose Bayona, University of Bristol (jose.bayona@bristol.ac.uk); Kelian Dascher-Cousineau, University ofCalifornia, Berkeley (kdascher@berkeley.edu); Leila Mizrahi,
Swiss Seismological Service (leila.mizrahi@sed.ethz.c);William Savran, University of Nevada, Reno (wsavran@unr.
edu); Max Schneider, U.S. Geological Survey (mschneider@usgs.gov)
Testing Rate-and-State Predictions of Aftershock Decay
PAGE, M., U.S. Geological Survey, California, USA, pagem@caltech.edu;
VAN DER ELST, N., U.S. Geoological Survey, California, USA, nvanderelst@
usgs.gov; FELZER, K., U.S. Geological Survey, California, USA, kfelzer@usgs.
gov
We analyze aftershocks of the 2019 M7.1 Ridgecrest mainshock to test predictions made by the rate-and-state friction model of Dieterich (1994). Rate-andstate friction predicts that the seismicity rate after a stress step follows Omori
decay, where the Omori c-value, which is the saturation in aftershock rate
observed at small times, is larger for smaller stress steps. Put in the context of
an aftershock sequence, this predicts that the Omori c-value will be systematically larger at greater distances from the mainshock. To our knowledge, thispredicted effect has not been observed. In part this may be because the Omori
c-value is difficult to measure, as it often reflects short-term catalog incompleteness in the mainshock coda rather than true saturation in aftershock rate.
Some have even hypothesized that the true c-value may be zero, or as Kaganand Houston (2005) argued, negative.
We explore the dependence of the Omori c-value on the distance to themainshock by applying the “a-positive” method (van der Elst and Page, 2023)
to Ridgecrest aftershocks. This method is insensitive to short-term aftershock
incompleteness and allows resolution of the true aftershock rate deep into themainshock coda.
Time-Dependent Earthquake Forecasts With Pre-Existing
Populations of Faults: Application to the Groningen Gas
Field, the Netherland
DAHM, T., GFZ Potsdam, Potsdam, Germany, dahm@gfz-potsdam.de;
HAINZL, S., GFZ Potsdam, Potsdam, Germany, hainzl@gfz-potsdam.de
The Groningen gas field, one of the largest producing onshore gas fields in
Europe, is often considered a model test site for induced seismicity. This isdue to the open availability of production and detailed structural and fieldparameters, together with an outstanding effort to monitor shallow, lowmagnitude seismicity from surface and borehole arrays. A key observation
at Groningen is that induced seismicity at depths of about 3 km started witha delay of almost 40 years after the start of production and long after peak
production rates were realised. This can be attributed to the fact that the shallow Rotliegend sediments at 3 km depth and pre-existing fault distributions
are subcritically stressed. Common seismicity models such as Rate and State(RS) or ETAS do not usually take into account pre-existing fault distributions
and pre-stress models.
In this study, we use a recently developed physics-based seismicity
model (TDSR) that assumes pre-existing populations of faults that respondto changes in Coulomb stress. In contrast to the traditional Coulomb Failure(CF) model, which assumes instantaneous triggering when stress exceeds athreshold value, the new model replaces instantaneous triggering with anaverage time to failure that depends exponentially on the absolute stress value.
In the new model, the predictions of both CF and RS are special cases forconstrained initial and boundary conditions. It is more general and flexible
to consider, for example, subcritical initial stress states as commonly assumed
for induced or intraplate seismicity. We estimate the pre-stress distribution at
Groningen based on the background stress field and the existing fault structure. Using this and the temporal evolution of the 2D stress field in the reservoir, we show that the delayed onset, the peak seismicity rate in 2013-2015 andthe decline in observed seismicity today are well explained.

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What Drives the Variability in Earthquake Sequence
Productivity in California and Nevada?
TRUGMAN, D. T., University of Nevada, Reno, Nevada, USA, dtrugman@
unr.edu; BEN-ZION, Y., University of Southern California, California, USA,benzion@usc.edu
It is widely recognized that earthquake sequences exhibit substantial variability in productivity, but the physical mechanisms underlying this observation
remain poorly understood. In this work we focus on resolving systematic variations in the productivity of crustal earthquake sequences in California and
Nevada, the two most seismically active states in the western US. We apply
a well-tested nearest-neighbor algorithm to automatically extract earthquake
sequence statistics from a unified 40-year compilation of regional earthquake
catalogs that is complete to ~M2.5. We then compare earthquake sequence
productivity to geophysical parameters that may influence earthquake triggering processes, including heat flow, temperature at seismogenic depth,
complexity of quaternary faulting, geodetic strain rates, depth to crystalline
basement, and faulting style. We observe coherent spatial variations in earthquake sequence productivity, with higher values in the Walker Lane of eastern
California and Nevada than along the present-day plate boundary fault systemin western California. The results illuminate significant correlations between
productivity and heat flow, temperature, and faulting that contribute to theunderstanding and ability to forecast crustal earthquake sequences in the area.
Modernizing Earthquake Forecasts Testing andExperimentation: CSEP Open-Software Contributions
ITURRIETA, P., GFZ Potsdam, Potsdam, Germany, pciturri@gfz-potsdam.
de; MAECHLING, P. J., University of Southern California, California,
USA, pjmaechling@usc.edu; SAVRAN, W. H., University of Nevada, Reno,
Nevada, USA, wsavran@unr.edu; BAYONA, J., University of Bristol, Bristol,
United Kingdom, jose.bayona@bristol.ac.uk; SILVA, F., University ofSouthern California, California, USA, fsilva@usc.edu; SCHORLEMMER,
D., GFZ Potsdam, Potsdam, Germany, ds@gfz-potsdam.de; WERNER, M.
J., University of Bristol, Bristol, United Kingdom, max.werner@bristol.ac.uk
The Collaboratory for the Study of Earthquake Predictability (CSEP) isan international research community that supports earthquake predictability research through rigorous testing of earthquake forecasting models.
Traditionally, CSEP experiments were facilitated by a server infrastructurethat autonomously performed model evaluations and whose first implementation used centralized servers tightly coupled to the testing software. Openscience initiatives and open-source software development, however, led CSEP
to improve this framework. First, a software toolkit for earthquake forecast
users, pyCSEP, was developed to include the core scientific routines for evaluating forecasts, such as: (1) earthquake catalog access and processing, (2) representations of probabilistic earthquake forecast models, both gridded- andcatalog-based, (3) statistical tests for earthquake forecast evaluation, and (4)visualization routines. pyCSEP is being continuously developed by a community of researchers who vet its source code and keep up with new testing
theoretical methods.
To further improve the experimentation process, CSEP experiments will
be redesigned to (i) safeguard an experiment’s reproducibility, (ii) facilitate
their transparency, accessibility, and persistence, (iii) standardize experimental procedures, and (iv) benchmark experiments for future model developments. To this end, a novel format called Floating Experiment is being
developed and managed by the application floatCSEP. The testing process isdecentralized from a physical infrastructure, aiming at full reproducibility on
any machine, given sufficient computational power. The experiment definition, rules, artifacts, and environment are encapsulated as source code andreadily curated in open-data repositories. These Floating Experiments arethen live reproducibility software packages able to process, update and deliver
results on-demand, both by authoritative institutions and independent users.
The CSEP community envisions pyCSEP and floatCSEP as essential elements
in a larger software ecosystem that can be used together to quantify earthquake hazards and risk.
Operational Earthquake Forecasting in Japan: A Study ofMunicipal Government Planning for an Earthquake
Advisory or Warning in the Nankai Region
GOLTZ, J. D., University of Colorado Boulder, California, USA, jamesgoltz@
gmail.com; YAMORI, K., Kyoto University, Kyoto, Japan, yamori@drs.
dpri.kyoto-u.ac.jp; NAKAYACHI, K., Doshisha University, Kyoto, Japan,
nakayachi@mail.doshisha.ac.jp; SHIROSHITA, H., Kansai University,
Osaka, Japan, hideyuki@kansai-u.ac.jp; SUGIYAMA, T., Kyushu University,

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Fukuoka, Japan, sugitaka.19900427@gmail.com; MATSUBARA, Y., Shiga
University, Hikone, Japan, yu-matsubara@biwako.shiga-u.ac.jp
A team of social scientists from the US and Japan have conducted a study
exploring the extent to which municipal governments in Japan have developed plans for response to an operational earthquake forecast (OEF) fromthe Japan Meteorological Agency (JMA) indicating that seismic activity in the
Nankai Trough region has elevated the short-term probability that a major
earthquake may occur. Employing both survey research and in-depth interviews, the team explored various aspects of the history and science behind thealerting system, guidance from the national government of Japan and planning by local jurisdictions for a possible future Nankai Trough major earthquake. The survey included questions regarding planning actions included
in a response plan for receipt of “special earthquake warning information(SEWI)” as well as questions regarding challenges in the planning process,expectations that an earthquake would follow the issuance of an alert andwhether planning would reduce the number of fatalities and injuries. We also
conducted in-depth interviews that explored the scientific basis for the alerting system and asked working disaster managers in the Nankai region what
they had done to plan and if plans had not been developed, the reasons for notplanning. Our survey netted 469 responses from a total of 736 jurisdictionsin the Nankai region, a response rate of 63.7%. We conducted a total of 17
in-depth interviews. In general, we found that a majority of jurisdictions have
response plans for receipt of an alert from the Japan Meteorological Agency(JMA); however, the plans lacked a number of planning elements considered
important from a disaster management perspective. In addition, many smaller
jurisdictions lacked the staffing, resources and guidance to form comprehensive response plans. Our report identifies both the strengths and weaknessesof existing plans and outlines a program for improving planning in the region.

New Insights into the Development, Testing andCommunication of Seismicity Forecasts [Poster Session]
Poster Session • Thursday 2 May
Conveners: Jose Bayona, University of Bristol (jose.bayona@bristol.ac.uk); Kelian Dascher-Cousineau, University ofCalifornia, Berkeley (kdascher@berkeley.edu); Leila Mizrahi,
Swiss Seismological Service (leila.mizrahi@sed.ethz.c);William Savran, University of Nevada, Reno (wsavran@unr.
edu); Max Schneider, U.S. Geological Survey (mschneider@usgs.gov)
poster 39
The Pattern of Earthquake Magnitude Clustering Based on
Interevent Distance and Time
GOSSETT, D., Miami University, Ohio, USA, gossetd@miamioh.edu;
BRUDZINSKI, M. R., Miami University, Ohio, USA, brudzimr@muohio.
edu; XIONG, Q., University of Wisconsin-Madison, Wisconsin, USA,qxiong26@wisc.edu; HAMPTON, J., University of Wisconsin-Madison,
Wisconsin, USA, jesse.hampton@wisc.edu
The clustering of earthquake magnitudes is poorly understood compared tospatial and temporal clustering. Better understanding of correlations between
earthquake magnitudes could provide insight into the mechanisms of earthquake rupture and fault interactions, and improve earthquake forecastingmodels. In this study we present a novel method of examining how seismic
magnitude clustering occurs beyond the next event in the catalog and evolves
with time and space between earthquake events. We first evaluate the clustering signature over time and space using double-difference located catalogs
from Southern and Northern California. The strength of magnitude clustering
appears to decay linearly with distance between events and logarithmicallywith time. The signature persists for longer distances (more than 50km) andtimes (several days) than previously thought, indicating that magnitude clustering is not driven solely by repeated rupture of an identical fault patch. The
decay patterns occur across different magnitude ranges of the catalog and canbe demonstrated across multiple methodologies of study. These patterns arealso shown to be present in laboratory rock fracture catalogs but are absent in
ETAS synthetic catalogs. Incorporating spatial and temporal decay of magnitude clustering into earthquake forecasting approaches that currently use
ETAS models would likely improve their accuracy.

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ETAS-positive: An Epidemic-Type Aftershock Model That Is
Insensitive to Catalog IncompletenessVAN DER ELST, N., U.S. Geological Survey, California, USA, nvanderelst@
usgs.gov
Earthquake catalogs provide incomplete records of the earthquakes that
occur, due to saturation of the network during periods of high activity.
Incompleteness typically manifests as an early-time plateau in the aftershock
rate, during which the rate exceeds the maximum detection rate of the seismic
network. This complicates the generation and testing of aftershock forecasts,
which need to consider all of the earthquakes that occur, not just those thatmake it into the catalog. Traditional attempts to recover unbiased statistics
involve modeling the time-dependent completeness magnitude, but suchmodels are non-unique and introduce their own biases and uncertainty.
In previous work, I demonstrated how to set up the estimation of common seismicity parameters in a way that minimizes sensitivity to incomplete
data. Using the ‘positive’ statistics approach, parameters are estimated within
nominally complete intervals, defined by pairs of earthquakes where the second is larger than the first. The first earthquake in the pair sets a reference
magnitude above which subsequent earthquakes are likely to be detected,
and a small positive magnitude adjustment ensure arbitrarily high detection
probability. This definition makes no reference to an absolute magnitude ofcompleteness. I previously applied this method to the estimation of the a andb-value of the Gutenberg-Richter distribution; here I extend the approach to
the epidemic-type aftershock sequence (ETAS) model. I define pairs following
the same scheme used for a-positive, where every earthquake defines the startof a ‘complete’ interval terminated by the next larger earthquake. In situations
where there is no next larger earthquake, the open interval is used. The ETAS+
likelihood is then maximized only over these complete intervals.
Applying ETAS+ to global aftershock sequences reveals little evidence
for an early-time plateau in rate, with an Omori c-value of 60 seconds following magnitude 6.5 and larger mainshocks. This is coincident with the times ofthe earliest cataloged aftershocks.
poster 41
Correlations of Deep Low-Frequency and Crustal
Earthquake Activity in Parkfield, Ca, and Implications for
Their Joint Use in Forecasting Frameworks
FARGE, G., University of California, Santa Cruz, California, USA, gafarge@
ucsc.edu; DASCHER-COUSINEAU, K., University of California, Berkeley,
California, USA, kdascher@berkeley.edu; BRODSKY, E., University ofCalifornia, Santa Cruz, California, USA, brodsky@ucsc.edu
Faults exhibit a wide spectrum of slow slip behaviors that shape the distribution of forces on a fault network, thus informing when and where seismicity
occurs. Although it is well documented that large (M>6) slow slip transientscan both trigger seismicity swarms and be influential in the nucleation oflarger earthquakes, the contribution of smaller-magnitude (M<5) slow slip
events to shaping nearby seismicity is still elusive. At the edge of the creeping section of the San Andreas fault near Parkfield, deep slow-slip events are
small enough that they are mostly detected indirectly through the activity of
low-frequency earthquakes (LFEs). Using them as a proxy for deep slip, ourobjective is to understand the inter-dependence of deep slow-slip and seismicity in the upper crust, to assess if LFEs could help forecast shallow seismicity
changes.
In this work, we show that a significant increase in seismicity occurs
both before and after days of high LFE activity. It is consistent with a systematic interaction of deep slow-slip and shallow seismic release. The signal we
detect may very well be a sign that the two catalogs are correlated for otherreasons. We therefore evaluate possible external sources of correlation, including dynamic triggering of both populations from distant earthquakes andinter-dependent detection thresholds for both catalogs. Such effects would
systematically bias any seismicity forecast using LFEs, by interpreting activity
correlation as causal interaction between the populations during the learning phase. We finally assess the added value of incorporating LFE activity as
additional information to predict seismicity using a deep-learning forecastingmodel (RECAST, Dascher-Cousineau et al., 2023). The model learns how to
predict the timing of the next event based on timing and magnitude and is
flexible enough to integrate additional observables to describe the history ofactivity. We therefore train the model to learn from the number of LFEs in ashort period before each earthquake, evaluate the change in forecasting performance and discuss the added-value to the forecasting problem.

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poster 42
Stress Shadows: Insights into Physical Models of
Aftershock Triggering
HARDEBECK, J., U.S. Geological Survey, California, USA, jhardebeck@usgs.
gov; HARRIS, R. A., U.S. Geological Survey, California, USA, harris@usgs.gov
Why some aftershocks appear to occur in stress shadows, regions of Coulomb
stress decrease due to a mainshock, is an open question with implications forphysical and statistical aftershock models. New machine-learning focal mechanism catalogs make it possible to study the fault orientations of aftershocks
occurring in the stress shadows, and test competing hypotheses about their
origins. There are three main hypotheses: (1) Aftershocks appear in shadows because of inaccuracy in the computed stress change. (2) Aftershocks
in the shadows occur on faults with different orientations than the model
receiver faults, and these unexpected fault orientations experience increased
Coulomb stress. (3) Aftershocks in the shadows are triggered by dynamic
stress changes. We test these three hypotheses on the 2016 Kumamoto and2019 Ridgecrest sequences. We test Hypothesis 1 through many realizationsof the stress calculations with multiple mainshock models, multiple receiverfault orientations based on background events, and a range of coefficientsof friction. We find that numerous aftershocks are consistently in the stressshadows. To test Hypothesis 2, we consider whether the individual event focal
mechanisms receive an increase of Coulomb stress. Again, we perform many
realizations of the stress calculation, this time with receiver fault orientations
based on the focal mechanism and its uncertainty. Many of the aftershocks
in the shadows consistently show a Coulomb stress decrease on the planes of
their focal mechanisms. These results imply that aftershocks do occur in stressshadows, many on fault planes receiving a decrease in static Coulomb stress,
contrary to Hypotheses 1 and 2. We test Hypothesis 3 by investigating themodeled dynamic stress changes on the individual event focal mechanisms.
Preliminary results show that while the amplitude of the dynamic Coulomb
stress change is generally lower on the aftershock nodal planes than on theplanes of background events, the amplitude of the dynamic normal stresschange is often 20%-100% higher. This suggests a dynamic triggering mechanism related to changing fault strength.
poster 43
The Generalized Long-Term Fault Memory Model andApplications to Paleoseismic Records
NEELY, J. S., University of Chicago, Illinois, USA, jamesscottneely@gmail.
com; SALDITCH, L., Northwestern University, Illinois, USA, leah.salditch@gmail.com; SPENCER, B. D., Northwestern University, Illinois, USA,bspencer@northwestern.edu; STEIN, S., Northwestern University, Illinois,
USA, s-stein@northwestern.edu
Paleoseismic studies show large variability in earthquake inter-event times
along a fault, with short intervals often separated by long quiescent periods.
Some paleoseismologists have interpreted this variability as a product of anearthquake’s partial strain release with the next earthquake occurring sooner
than expected because of the remaining residual strain. However, commonlyused probabilistic large earthquake recurrence models attribute this variability purely to chance, not the state of strain on the fault. Here, we present analternative probabilistic model, built on the Long-Term Fault Memory model
framework that better reflects the strain accumulation and release process.
This Generalized Long-Term Fault Memory model (GLTFM) predicts that
this inter-event time variability arises from both chance and the state of strain
on the fault. Specifically, it estimates when residual strain is likely present andits impact on the timing of the next earthquake in the sequence. Additionally,
GLTFM assumes that additional accumulated strain always increases earthquake probability. In contrast, the commonly used lognormal and Brownian
Passage Time models predict that the probability of a large earthquake stays
constant or even decreases after it is “overdue” (past the observed average
recurrence interval) so additional accumulated strain does not make an earthquake more likely. GLTFM’s simple implementation and versatility shouldmake it a powerful tool in earthquake forecasting.
poster 44
Prototyping Aftershock Forecast Maps and Products Basedon User Needs
SCHNEIDER, M., U.S. Geological Survey, California, USA, max.
schneider15@gmail.com; ARTIGAS, B., U.S. Geological Survey, California,
USA, bianca.i.artigas@gmail.com
After large earthquakes, aftershock forecasts are released by science agencies
and can inform decisions on earthquake response and recovery by diverse
users (e.g., emergency managers, critical infrastructure operators, and pub-

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lic information officials, among others). Visual design choices for forecast
products can affect how the forecasts are used and understood by such varied groups. We recently held several user workshops in the United States,
Mexico and El Salvador and found that user needs for aftershock forecast
information may vary by profession, use case, country, and with time since
the mainshock. In this study, we prototyped aftershock forecast products to
support the distinct user needs found in our workshops by translating userneeds into design choices for the product. Design choices were also based onliterature-backed best practices in data visualization and cartography for natural hazards. We developed multiple versions of probabilistic shaking forecast
maps, where we varied such design choices as color palette, discretization of
the data, additional map layers and whether to animate the map. Each prototype corresponded to a version of the forecast map aligned with specificuser needs. Additionally, we created non-spatial forecast products arounduser needs, such as tables or graphics for the forecasted probability or number
of aftershocks and how this is forecasted to decrease with time. We carefully
considered how to communicate uncertainty across the huge ranges (ordersof magnitude) often provided by these forecasts. We assessed these forecast
product prototypes with a focus group of our workshop participants from theUnited States, Mexico and El Salvador, revising products based on their feedback. We discuss implications for the visual communication of earthquake
and aftershock forecasts to wide-ranging audiences. Ideas for future testing ofour product prototypes include task-based online experiments where participants use candidate forecast products to perform tasks based on common use
cases for aftershock forecasts.
poster 45
Observations of the Aftershock Sequences ofIntermediate-Depth Earthquakes Beneath Japan
WARREN, L. M., St. Louis University, Missouri, USA, linda.warren@slu.edu;
IGARASHI, T., University of Tokyo, Tokyo, Japan, igarashi@eri.u-tokyo.ac.jp;
KATO, A., University of Tokyo, Tokyo, Japan, akato@eri.u-tokyo.ac.jp
The increasing pressure and temperature with increasing depth in the Earthshould prevent earthquakes from occurring >50 km depth, yet they areobserved occurring down to ~700 km. At intermediate depths, the two mostcommonly proposed mechanisms are dehydration embrittlement and thermal shear instability. These two mechanisms have different implications foraftershock production — dehydration embrittlement would lead to aftershock
patterns similar to those observed for shallow earthquakes whereas thermal
shear instability would result in few aftershocks — so observing and quantifying the temporal decay of intermediate-depth aftershock sequences can help
distinguish the causative source mechanism. Japan’s high earthquake activity, earthquake catalog with a low magnitude of completeness, and contrasting properties of the subducting Pacific and Philippine Sea Plates make it anexcellent location to study intermediate-depth aftershock sequences and how
different factors contribute to aftershock productivity. We analyze the 199
earthquakes in the JMA Unified Earthquake Catalog from 1985-2021 with
MJ≥5.7 at 70-350 km depths and are able to fit the modified Omori’s Law
to quantify the temporal decay for 21 of the aftershock sequences. The aftershocks tend to be clustered around the mainshock, so an aftershock zone canbe drawn that separates the aftershocks from the surrounding backgroundseismicity. Earthquakes within this subjective aftershock zone are used tocharacterize the aftershock sequences. In comparison with shallow aftershock
sequences, the characterized aftershock sequences have a similar temporal
decay exponent p≅1 but much lower productivity. Preliminary results suggestthat productivity is higher in the Pacific Plate than in the Philippine Sea Plate,in the upper plane of the double seismic zone than in the lower plane, and forshallower earthquakes. The characterized sequences last from ~40 days to >30
years. The characterized aftershock sequences are closer to our expectations
for dehydration embrittlement than thermal runaway. Variations in productivity may relate to the amount of fluid available.

Numerical Modeling in Seismology: Developments andApplications
Oral Session • Wednesday 1 May • 8:00 am PacificConveners: Alice-Agnes Gabriel, University of California,
San Diego (algabriel@ucsd.edu); Martin Galis, Comenius
University Bratislava (martin.galis@uniba.sk); Jozef Kristek,
Comenius University Bratislava (kristek@fmph.uniba.sk);
Peter Moczo, Comenius University Bratislava (moczo@fmph.
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uniba.sk); Arben Pitarka, Lawrence Livermore National
Laboratory (pitarka1@llnl.gov); Wei Zhang, Southern
University of Science and Technology (zhangwei@sustech.
edu.cn)Reflection and Transmission of Inhomogeneous Plane
Waves in Thermoporoelastic Media with Two-temperature
Equations of Heat Conduction
HOU, W., China University of Petroleum, QINGDAO, China, hwtupc@163.
com; FU, L., China University of Petroleum, QINGDAO, China, lfu@upc.
edu.cn; CARCIONE, J., National Institute of Oceanography and AppliedGeophysics, Trieste, Italy, jose.carcione@gmail.com
Elastic wave propagation analysis in fluid-saturated high-pressure, hightemperature fields is among the most important and effective methods forgeoresource exploration. Successful explanation and interpretation of deep
resources requires a valid and simple rock physics model that combines rocks’
porous properties and thermal nature.
The theory of thermoporoelasticity introduces mechanical-thermal coupling in poroelasticity. We develop a modified thermoporoelastic model withfluid-saturated by introducing two temperature equations to account for thetemperature differences between the solid skeleton and the pore filling. The
modified two-temperature-generalized thermoporoelastic (TTG) equation isan extension of the classical single-temperature LS, GL, and generalized LStheories. It predicts four compressional waves and one shear wave, i.e., fast P(P1), slow P (P2), thermal (T1), slow thermal (T2), and S waves, based on theanalysis of inhomogeneous plane waves. We derive the reflection and transmission coefficients of a plane wave with the inhomogeneity angle incident
on the interface separating two half-spaces based on the TTG equation. The
coefficients as a function of incidence angle and porosity are presented. We
also develop the corresponding AVO approximation to compare with that of
the Biot poroelastic model and study the fluids’ effects.
The inhomogeneity angle is found to affect the attenuation values of
the P1 and S waves more strongly, with an increase in the angle leading toenhanced attenuation, especially in the range caused by Biot dispersion, while
the dispersion for the other three waves shifts to the high frequencies. The
critical angle of P1 waves increases with porosity until it vanishes, where thevelocity of the P1 wave in the transmission medium is equal to the incidence.
Comparison with the Biot poroelastic case of the water/oil contact shows that
the TTG model reproduces the exact R/T results. The AVO response of oil
and gas reservoirs illustrates the practical applicability of the proposed modeland provides the theoretical basis for the exploration of high-temperature
resources.
Dynamic Rupture Simulation of Caldera Collapse
Earthquakes: Effects of Wave Radiation, Magma Viscosity,and Evidence of Complex Nucleation at Kīlauea 2018
WANG, T. A., Stanford University, California, USA, taiyi@stanford.edu;
DUNHAM, E. M., Stanford University, California, USA, edunham@stanford.
edu; KRENZ, L., Technical University of Munich, Munich, Germany, lukas.
krenz@in.tum.de; ABRAHAMS, L. S., Lawrence Livermore National
Laboratory, California, USA, abrahams3@llhl.gov; SEGALL, P., Stanford
University, California, USA, segall@stanford.edu
All instrumented basaltic caldera collapses generate Mw > 5 very long period
earthquakes. However, previous studies of source dynamics have been limited to lumped models treating the caldera block as rigid, leaving open questions related to how ruptures initiate and propagate around the ring fault,
and the seismic expressions of those rupture dynamics. We present the first
3D numerical model capturing the nucleation and propagation of ring fault
rupture, the mechanical coupling to the underlying viscoelastic magma, andthe associated seismic wavefield. We demonstrate that seismic radiation,neglected in previous models, acts as a damping mechanism reducing coseismic slip by up to half, with effects most pronounced for large magma chamber
volume, high magma compressibility, or large caldera block radius. Viscosityof basaltic magma has negligible effect on collapse dynamics. In contrast, viscosity of silicic magma significantly reduces ring fault slip.
We use the model to simulate the 2018 Kīlauea caldera collapse. Threestages of collapse, characterized by ring fault rupture initiation and propagation, deceleration of the downward-moving caldera block and magma column, and post-collapse resonant oscillations, in addition to chamber pressurization, are identified in simulated and observed (unfiltered) near-fieldseismograms. A detailed comparison of simulated and observed displacement
waveforms corresponding to collapse earthquakes with hypocenters at various

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Seismological Research Lettersazimuths of the ring fault reveals a complex nucleation phase for earthquakes
initiated on the northwest. Our numerical simulation framework will enhance
future efforts to reconcile seismic and geodetic observations of caldera collapse with conceptual models of ring fault and magma chamber dynamics.
What Is the Principal Accuracy Limit of a Seismic
Wavefields Simulated by a Finite-Difference Method?
VALOVCAN, J., Comenius University Bratislava, Bratislava, Slovakia, jaroslav.
valovcan@fmph.uniba.sk; MOCZO, P., Comenius University Bratislava,
Bratislava, Slovakia, moczo@fmph.uniba.sk; KRISTEK, J., Comenius
University Bratislava, Bratislava, Slovakia, jozef.kristek@fmph.uniba.
sk; KRISTEKOVA, M., Slovak Academy of Sciences, Bratislava, Slovakia,
kristekova@savba.sk; GALIS, M., Comenius University Bratislava, Bratislava,
Slovakia, martin.galis@uniba.sk
The finite-difference method is based on spatial discretization of a medium
for which seismic wave propagation and earthquake motion are to be simulated. Moczo et al. (2022) systematically analyzed equations of motion in thewavenumber domain and found that the discrete (grid) representation of theheterogeneous medium must be wavenumber band-limited up to the Nyquist
frequency. Mittet (2021a) reported that if the discrete grid model of medium
coincides with the true medium up to some wavenumber, the simulated wavefield is accurate only up to a half of this wavenumber.
We present results of the comprehensive analysis focused on the principal limits of accuracy of numerically simulated wavefields. The analysis
includes A. wavenumber spectra of a) exact wavefields in a heterogeneous
elastic medium, b) wavenumber band-limited wavefields, c) spatially discretized wavefields, B. spatial dependence of the frequency spectrum of waves
generated by a finite source, C. perturbing wavefields due to a small perturbation of the medium and due to a small wavenumber band-limited perturbation of the medium, D. interaction of an incoming wave with the medium
perturbation through phase difference and wavenumber spectra.
In the synthesis of partial findings, we draw conclusions on the wavenumber limitation of wavefields in the wavenumber band-limited heterogeneous medium, and the principal consequence for the numerical modelingbased on spatial discretization of the computational domain.
Modeling the Seismic Noise Horizontal-to-Vertical Spectral
Ratio in Laterally Irregular Configurations Using the
Diffuse Field Assumption
SANCHEZ-SESMA, F. J., Universidad Nacional Autónoma de México,
CDMX, Mexico, sesma@unam.mx; WEAVER, R. L., University of Illinois
Urbana-Champaign, Illinois, USA, r-weaver@illinois.edu; BAENARIVERA, M. E., Universidad Nacional Autónoma de Mexico, CDMX,
Mexico, mbaenar@gmail.com; PARDO-DAÑINO, J. C., Universidad
Nacional Autónoma de México, CDMX, Mexico, pardo3.14159@gmail.com;
ARCINIEGA-CEBALLOS, A., Universidad Nacional Autónoma de México,
CDMX, Mexico, maac@igeofisica.unam.mx
The horizontal-to-vertical spectral ratio (HVSR) of ambient seismic noise(ASN) is a current measure to assess the predominant soil frequency of agiven site. We assume that ASN field comes from equipartioned, uniform
illumination of random sources and the scattering by heterogeneities leads tosome equilibration that makes a field diffuse. Besides, diffuse fields are closely
related with the Green’s function. Under the diffuse field assumption (DFA)theory asserts that the average directional energy densities (DED) are related
to Green’s function. Therefore, using ASN and under the DFA, the HVSR is
computed with the imaginary parts of the Green’s function. That fact made theinversion of soil properties in depth feasible for horizontally layered media.
However, this is not completely free of uncertainties about the diffuse character of the wavefield and the non-uniqueness of the inversion, subjects that
require further scrutiny. In practice, lateral variations are ignored or integrated with some interpolation. Their study may add physical meaning to thequest because HVSR in irregular layered settings has significant lateral andazimuthal variability. In this work, we model HVSR under the DFA and use
the 3D indirect boundary element method (IBEM) to study an irregular layer
and use an adaptive mesh scheme by accounting for the locality of problem
and the wave diffraction properties. Our preliminary results show that layer
irregularities may lead to “spots” of enhanced wave excitation and suggest theneed for denser field measurements to study lateral variations and azimuthal
variability. Clearly, the potential variations of possible substructures greatly
exceed any information present in HVSR. As ever, one must supplement withextra information, possibly non-seismic, and learn to live with some uncertainty. We discuss results and examine the implications for seismic hazard
assessment.

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The Ongoing Development of Distributional Finitedifference Modeling in Global Seismology
LYU, C., University of California, Berkeley, California, USA, lyuchao@
berkeley.edu; MASSON, Y., Université de Pau et des Pays de l’Adour, Pau,
France, yder.masson@gmail.com; AWAN, M., Lawrence Berkeley National
Laboratory, California, USA, mgawan@lbl.gov; ROMANOWICZ, B.,
University of California, Berkeley, California, USA, barbarar@berkeley.edu
DFDM was recently introduced as a new numerical simulation approachthat combines advantages from classic finite difference and finite element
methods for solving the elastic wave equation (Masson, 2022). Throughtwo/three-dimensional benchmarks against the well-established spectral
element method (SEM) in Matlab, we have demonstrated this algorithm’shigh level of precision, at reduced computational cost with the flexibility todescribe the meshing. We recently started a collaboration with the Application
Performance Group at NERSC to develop a distributed version of the solver in
C++ optimized for use on HPC platforms.
Numerical Simulation of Strong Ground Motion for theMw 6.0 Jishishan Earthquake of 18 December 2023 in
Gansu Province, China
ZANG, N., Southern University of Science and Technology, Shenzhen,
China, zangn@sustech.edu.cn; ZHANG, W., Southern University of Scienceand Technology, Shenzhen, China, zhangwei@sustech.edu.cn; CHEN, X.,
Southern University of Science and Technology, Shenzhen, China, chenxf@
sustech.edu.cn
The Mw6.0 Jishishan earthquake on December 18, 2023 occurred along theeastern edge of the Tibetan Plateau and resulted in significant human casualties. To gain a better understanding of earthquake source properties and wavepropagation effects, we conducted simulations of the strong ground motionin the near field of the fault, incorporating 3D earth structure, finite-fault
rupture, and realistic surface topography. In this study, the topography elevation from SRTM90, a global digital topography dataset is adopted. We utilizeda 3D velocity model of the continental China lithosphere, USTClitho2.0, to
simulate wave propagation in a box-like volume with a dimension of 300 km
× 300 km at the surface and 30 km in depth. Our primary focus lies in theimpact of the slip model on the simulated ground motions. The finite fault-slip
models employed in this study include Zhang’s preliminary rupture modelobtained through iterative deconvolution and stacking of high-rate GPS andstrong motion seismogram data, Zhang’s rupture model obtained throughjoint inversion of teleseismic and strong motion data, Wang’s rupture modeland the GP source model. We apply a hybrid broadband method to simulate
the ground motions within the frequency range 0.1–20 Hz. The low-frequency
seismograms (<1hz) are simulated by 3D non-staggered grid finite-difference
method, which incorporates boundary-conforming grids in the presenceof an irregular free surface.The high-frequency seismograms are calculatedusing the stochastic approach. Then, we combine the high- and low-frequency
seismograms to obtain broadband seismic motion by considering both amplitude and phase matching. We compare the simulated ground motions basedon different finite fault models with the observed near-field records and thecorresponding peak values. Furthermore, an analysis of the differences instrong ground motion calculated from different rupture models is presented.
The results demonstrate the effectiveness of hybrid broadband method in predicting strong ground motion parameters, provided that appropriate Earthstructure and earthquake rupture models are utilized.
A Detailed Analysis of Body Waves Simulated in
Homogenized MediaCUPILLARD, P., Université de Lorraine, Nancy, France, paul.cupillard@univ-lorraine.fr; MULDER, W., TU Delft & Shell Global Solutions, Delft,
Netherlands, W.A.Mulder@tudelft.nl; ANQUEZ, P., Geode-solutions, Pau,
France, pierre.anquez@geode-solutions.com; MAZUYER, A., TotalEnergies,
Saclay, France, antoine.mazuyer@totalenergies.com; ZAKARI, M., CNRS,
Nancy, France, mustapha.zakari@univ-lorraine.fr; BARTHÉLÉMY, J.,
CEREMA, Sourdun, France, jean-francois.barthelemy@cerema.fr
Non-periodic homogenization has proved to be an accurate asymptotic
method for computing long-wavelength equivalent media for the seismic
wave equation, turning small-scale heterogeneities and geometric complexity
into smooth elastic properties. Using homogenized media allows i) decreasing the computation cost of wave propagation simulation and ii) studying theapparent, small-scale-induced anisotropy. After illustrating these two aspects
briefly, we propose to analyze in great detail the accuracy of body waves simulated in homogenized 3D models of the subsurface. First, the behaviour ofhead-, reflected and refracted waves with respect to source-receiver offset,

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maximum frequency and velocity contrast across a planar interface, is investigated. Then, we consider the SEG-EAGE overthrust model to exemplify
how the accuracy of simulated body waves anti-correlates with the distanceto seismic source and the amount of apparent anisotropy. In high apparent
anisotropy regions, we show that the first-order correction provided by thehomogenization theory significantly improves the computed wavefield. The
overall results of this analysis better frame the use of homogenized media inseismic wave simulation.
Efficient Lossy Compression of Simulated 4d Seismic
Wavefields
ZHANG, W., Southern University of Science and Technology, Shenzhen,
China, zhangwei@sustech.edu.cn; WANG, W., Southern University of Scienceand Technology, Shenzhen, China, 11849526@mail.sustech.edu.cn; TANG,
Y., Southern University of Science and Technology, Shenzhen, China, tangyj@
sustech.edu.cn; LEI, T., Southern University of Science and Technology,
Shenzhen, China, leit@sustech.edu.cn
State-of-the-art inversion and imaging technologies, such as Full Waveform
Inversion (FWI) and Reverse Time Migration (RTM) require the ready availability of the forward simulated wavefields or Green function wavefields during gradient calculation. As storing all the wavefield of all time steps, which
a 4D volume, in computer memory is impractical for 3D problems, the mostintuitive strategy would be to store the 4D simulated wavefield data on disk.
However, this will introduce an important bottleneck because of the significant
I/O overhead and decrease in performance. To overcome this bottleneck, weincorporate the efficient lossy compression techniques based on Tucker tensor
decomposition into waveform inversion workflow by storing the compressed
4D simulated wavefield onto the disk instead of reconstruction on-the-fly. For
Tucker tensor decomposition, the simulated seismic wavefield sequence withthree spatial dimensions and a time dimension can be naturally represented as
a 4-way tensor, and then detects the global structure of the tensor and removes
redundant information, resulting in a low-rank representation of the data. We
compared the Tucker-based compression with other common compression
schemes on compression ratio, accuracy, and compression/decompressiontime, and the results show that Tucker-based compression is a good choice
for real-time online compression of 4D simulated wavefield data since it canefficiently compress the wavefield by more than 100x with less than 40% timeoverhead in our tests. To verify the effectiveness of the method in FWI workflow, we use the 3D collocated-grid finite-difference algorithm on curvilinear grids to simulate seismic wavefield in the presence of surface topography(CGFD3D). The efficient lossy compression is applied in the ambient noise
waveform inversion of seismic data in the Longmenshan area, which greatly
speeds up the computation compared with directly outputting the forward
wavefield and strain Green tensor without compression.
Effects of Dip Angle on Rupture Propagation Along Branch
Fault Systems
MARSCHALL, E., University of California, Riverside, California, USA,evanmarschall516@gmail.com; DOUILLY, R., University of California,
Riverside, California, USA, robyd@ucr.edu
An important consideration in assessing seismic hazards is determining what
is likely to happen when an earthquake rupture encounters a geometric complexity such as a branch fault. Previous studies showed parameters such as
branch angle, stress-orientation, and stress heterogeneity as key factors in the
self-determined rupture path on branch faults. However, most of these studies
were conducted in 2-D space or in 3-D with perfectly vertical faults. Many
natural strike slip faults do not form perfectly vertical and have some dipping angle. In this study, we investigate the effects of dipping angle on rupture propagation along a branch fault system. We construct 3-D finite element
meshes where we vary the dip angles (9 geometries in total) of the main andsecondary faults, the stressing angle (Ψ = 20°, 40° and 65°) and the hypocenter
location with nucleation on both the main and secondary segments. We findthat for intermediate stressing angle (Ψ = 40°), a rupture on the main fault
is most likely to propagate across the branch intersection when the secondary fault is dipping. Also, for high stressing angle (Ψ = 65°), a rupture on thesecondary fault is most likely to propagate to the main fault when the secondary fault is shallowly dipping. This is caused by a fast rupture speed on thesecondary fault and the dynamic stress effect that develop with the interaction of the free surface and the dipping secondary fault. These results indicatethat dip angle is an important parameter in determination of rupture path on
branch fault systems, with potentially significant impact for seismic hazard
and should be taken into account in future earthquake modeling.

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Insight From 3D Deterministic Ground Motion Simulations
in Central Italy
AKINCI, A., Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy,
aybige.akinci@ingv.it; PITARKA, A., Lawrence Livermore National
Laboratory, California, USA, pitarka1@llnl.gov; DE GORI, P., Istituto
Nazionale di Geofisica e Vulcanologia, Rome, Italy, pasquale.degori@ingv.it;
ARTALE HARRIS, P., Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy, pietro.artale@ingv.it; BUTTINELLI, M., Istituto Nazionale di Geofisicae Vulcanologia, Rome, Italy, mauro.buttinelli@ingv.it
Starting on August 24, 2016, with the M6.2 Amatrice earthquake, a sequenceof earthquakes has resulted in numerous casualties and significant damage
to buildings in central Italy. Following the Amatrice mainshock (Mw6.2),
the Visso (Mw5.9) and Norcia (Mw6.5) events occurred two months later.
The seismic activity has been meticulously recorded by a dense network ofstrong motion stations, with over 40 stations located within 50 km from thefault rupture. Considering the persistent seismic activity in this region, ourobjective was to develop a tool using a fully deterministic 3D approach to
calculate strong ground motions at higher frequencies, intended for use inseismic hazards and engineering applications. We also examined the impactof the source rupture model in the near-source area. We tested an end-toend modeling capability for strong ground motion simulations, utilizing
the extensive recorded data and predictions from regional Ground Motion
Models (GMMs). The simulations were conducted in the frequency range of
0-3Hz and 0-5Hz using a physics-based deterministic technique to model
earthquake rupture and elastic wave propagation for the Amatrice and Norcia
earthquakes. We employed SW4, a finite difference code designed to use a
topography-conforming curvilinear mesh for modeling surface topography
with high numerical accuracy. Incorporating several rupture scenarios, oursimulations demonstrated a direct correlation between the pattern of nearfault ground motion amplification and the slip distribution over the fault. We
found that large slip patches have a pronounced impact not only on the intensity of ground motion but also on , the inter-event variability of the PGV. In
our simulations, ground motions computed with and without surface topography showed an average PGV that is 30% higher for models incorporating
surface topography in the case of Norcia event. We believe that our results
provide a valuable framework for understanding the physical parameters andhow they contribute to the amplitudes of ground motions observed during
earthquakes in Central Italy.
The 2022 Mw 6.6 Menyuan Earthquake, Qinghai, China: An
Early-terminated Runaway Rupture Revealed by the
Dynamic Rupture Simulations
XU, D., Southern University of Science and Technology, Shenzhen, China,
xudy_cas@163.com; LI, Z., Southern University of Science and Technology,
Shenzhen, China, lizb3@sustech.edu.cn; ZHANG, Z., Southern University of
Science and Technology, Shenzhen, China, zhangzg@sustech.edu.cn; YU, H.,
Southern University of Science and Technology, Shenzhen, China, yuhy3@
sustech.edu.cn; CHEN, X., Southern University of Science and Technology,
Shenzhen, China, chenxf@sustech.edu.cn
The 2022 Mw 6.6 Menyuan earthquake is one of the best-recorded strikeslip events in the northeastern Tibetan plateau. There is still a puzzle about
this event: why did it generate unexpectedly large surface dislocations (about
2.6–3.5 m) relative to its seismic magnitude? To explore the mechanism, we
conducted numerous dynamic rupture simulations with a grid search method
to screen out a preferred dynamic model that fits the geodetic, seismic, andgeological observations well. The results show that the average stress drop of
the nucleation part of the seismogenic fault is relatively high (11 MPa), whichindicates that this event might nucleate with high initial energy as a runaway rupture and be capable of growing into a large earthquake (≥Mw 7.0).
However, the rupture propagating eastward is slowed and terminated by twoconsecutive fault bends of about 10º each, and the westward propagating one
might self-arrest on the south secondary fault after it jumps over the stepover.
Thus, the fault bend and stepover terminate the rupture propagation early.
That’s why the observed magnitude (Mw 6.6) is smaller than the estimated one(Mw 7.1–7.2) based on surface offsets. Our study shows that, due to advancesin computational power and observations (coverage and quality), physicsbased dynamic rupture simulations have entered an era where it is possible tofit the wide variety of observations well, which is vital for further understanding the complex earthquake rupture mechanics. More importantly, our results
imply that some moderate-to-strong earthquakes, which can grow into large
ones, fail to develop into large earthquakes because their rupture propagations

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are terminated early by stress barriers. This new understanding of earthquake
ruptures can provide theoretical guidance for future seismic risk assessments.
Using a Dynamic Earthquake Simulator to Explore ThreeDimensional Multicycle Dynamics of Stepover Faults
DUAN, B., Texas A&M University, Texas, USA, bduan@tamu.edu
Classical earthquake simulators such as RSQsim do not capture spontaneously dynamic rupture propagation, which calls into questions about robustness of rupture extent and path from these simulators on geometrically complex faults from these simulators. We have been developing a finite element
method (FEM) dynamic earthquake simulator to capture both spontaneously
dynamic rupture propagation and other quasi-static processes of earthquake
cycles. The dynamic earthquake simulator is based on EQdyna, an explicit
FEM dynamic solver originally developed for spontaneous rupture propagation along geometrically complex faults and seismic wave propagation in heterogeneous media. We adopt a dynamic relaxation technique to solve quasistatic problems of earthquake cycles using the dynamic solver. Therefore,
the EQdyna-based dynamic earthquake simulator solves both dynamic andquasi-static processes of earthquake cycles in the same FEM framework.
Previous studies on dynamics of stepover faults are primarily in two
dimensions. In this research, we apply the dynamic earthquake simulator to
explore three-dimensional dynamics of stepover faults over multiple earthquake cycles. To our knowledge, this is the first of fully dynamic earthquake
cycle simulations on geometrically complex faults in the scientific community. In this study, we specifically examine effects of different depth profilesof the effective normal stress and different loadings on earthquake patterns
and rupture behaviors of stepover faults over many earthquake cycles. Our
preliminary results show that the depth-dependent effective normal stressresults in more complex event patterns and rupture behaviors than the depthindependent case. For the depth-independent case, different loading rates do
not affect the event pattern much, though faster loading rates result in shorterrecurrence intervals. Our results also suggest that jumping ruptures are moredifficult to occur in three dimensional models than in their two-dimensionalcounterparts over many earthquake cycles.
Entropy Approach to the 2021 Alaska 8.2 Earthquake
VOGEL, E. V., Universidad de La Frontera, Temuco, Chile, eugenio.vogel@ufrontera.cl; SARAVIA, G., Universidad de La Frontera, Temuco, Chile,
gonzalo.saravia@gmail.com; PASTEN, D., Universidad de Chile, Santiago,
Chile, denisse.pasten@uchile.cl; POSADAS, A., Universidad de Almería,
Almería / Granada, Spain, aposadas@ual.es; AGUILERA, M., Universidad
Técnica Federico Santa María, Valparaíso, Chile, michelaguilera.fis@gmail.
com
The year 2021 was abundant in large earthquakes worldwide and the mostimportant was the one of Alaska, Mw 8.2, which generated important aftershock activity. In this paper, we use Tsallis Entropy, Shannon Entropy, andMutability to categorize the various stages of the phenomenon: a) randomseisms; b) increase (decrease) of Tsallis entropy (mutability) years/months
before the big earthquake; c) several seisms with magnitude close or over 7.0;d) a long aftershock regime lasting to present days. From the entropy point ofview, we find similarities and differences in this behavior compared to that of
the recently reported analysis of the Mw 8.1 earthquake of Iquique on April
1, 2014 [1].
We mainly conducted the analysis on the magnitude sequence from
2000-01-01 to 2023-12-31 obtained from the USGS web page. It is clearlyappreciated how Tsallis entropy raises during 2019 in parallel to the decreasein mutability. Then, they abruptly reverse this behavior on the occurrence ofthe large earthquakes of 2020. However, Tsallis entropy (mutability) quickly
increases (decreases) its value to the levels previous to this earthquake withina matter of months, only to sharply collapse (raise) for the 8.2 earthquake of2021. It soon recovers, reaching the levels previous to the 2020 seisms, which
is a worrisome sign. Shannon entropy heels the results for mutability, which ispreferred because of its clearer results in perfect agreement with those got by
Tsallis entropy. We can also do the analysis using the interval sequence (timebetween successive seisms) which is complementary to the one based on magnitudes. The combination of these results define a powerful technique able toshine light on the seismic activity years prior to major quakes and could be apotential indicator for categorizing seismic risk areas.
[1] Tsalllis Entropy and Mutability to Characterize Seismic Sequences: The
Case of 2017-2014 Northern Chile Earthquakes. Denisse Pasten, Eugenio E.
Vogel, Gonzalo Saravia, Antonio Posadas, and Oscar Sotolongo, Entropy 25(2023) 1417 (https://doi.org/10.3390/e25101417).

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On the Dynamic of Peierls Creep at Subduction Zones:
Implication for Intermediate-Depth Lower Plane
Earthquakes
ZHANG, R., Chinese Academy of Sciences, Beijing, China, zhangrui0531@
mail.iggcas.ac.cn; YANG, J., Chinese Academy of Sciences, Beijing, China,
jianfengyang1989@gmail.com; ZHAO, L., Chinese Academy of Sciences,
Beijing, China, zhaoliang@mail.iggcas.ac.cn
Most earthquakes occur within Earth’s subduction zones, where oceanic
plates, possessing negative buoyancy, descend into the underlying asthenosphere mantle at trench boundaries. The interactions between the subducting
slab and the surrounding mantle generate substantial deformation, resulting in double zone seismic in subduction regions, but the controversy ofearthquakes in the lower plane persists. The occurrence of seismic events is
intricately linked to the strength of tectonic plates. Olivine is presumed toinfluence plate strength through its rheological properties. Previous studies
predominantly focused on dislocation and diffusion creep, neglecting the significance of Peierls creep. The wide variance in experimental approaches andflow laws used yields a diverse range of parameters related to Peierls creep.
To examine the impact of Peierls creep on deformation mechanisms
and stress states within subducting slabs, pseudo-two-dimensional numericalmodels were developed using LaMEM. Systematic exploration of parameters
including activation energy, activation volume, and Peierls stress categorizes
model outcomes into three regimes, delineating the effects of Peierls creep
on slab deformation patterns. When Peierls stress or activation energy islow, signifying strong Peierls creep effects and a weak slab, the subduction
angle becomes substantial, eventually leading to a flat lying slab at the base.
Conversely, higher activation energy with the inclusion of activation volume
indicates diminishing Peierls effect and a stronger slab, potentially causingslab retrogradation. Increasing activation energy, Peierls stress, and criticalactivation volume tend to segment the slab, resulting in a moderate subduction angle. Additionally, given the Peierls creep’s alignment with the lower
plane seismic zone within the subduction double seismic zone, there is speculation regarding a potential correlation between lower plane seismic activity
and Peierls creep, offering a novel perspective on seismic origins.
Quadrangular Adaptive Mesh for Elastic Wave Simulationin Smooth Anisotropic MediaRAPENNE, M., Université de Lorraine, Nancy, France, marius.rapenne@
univ-lorraine.fr; CAUMON, G., Université de Lorraine, Nancy, France,
guillaume.caumon@univ-lorraine.fr; CUPILLARD, P., Université deLorraine, Nancy, France, paul.cupillard@univ-lorraine.fr; GOUACHE, C.,
Caisse Centrale de Réassurance, Paris, France, cgouache@ccr.fr
The management of smooth anisotropic media holds significant importancefor seismic wave simulation and imaging. In such media, adaptive meshes
constitute, in principle, an attractive representation to maximize simulation accuracy while minimizing computational cost. However, creating suchmeshes can be difficult, because the optimal local size of the elements is notclearly defined in the case of smooth anisotropic media.
In this work, we present a two-step algorithm to efficiently mesh 2Dthese media for spectral element method (SEM) simulations. Our algorithm
yields quadrangular meshes which adapt the size of the elements to the local
effective and directional S-wave velocity. It first relies on the octree decomposition introduced by Maréchal (2009) to divide the mesh until the size of eachelement edge is adapted to the local minimum wavelength that will be propagated. Then, a smoothing is applied to further optimize the size and shape ofthe elements, which increases the global time-step and, consequently, makes
SEM simulations faster while keeping a good accuracy or even improving it insome cases. The application of our method on a section of the homogenized
Groningen area shows that simulation time can be reduced by a factor up to 3.

Numerical Modeling in Seismology: Developments andApplications [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Alice-Agnes Gabriel, University of California,
San Diego (algabriel@ucsd.edu); Martin Galis, Comenius
University Bratislava (martin.galis@uniba.sk); Jozef Kristek,
Comenius University Bratislava (kristek@fmph.uniba.sk);
Peter Moczo, Comenius University Bratislava (moczo@fmph.

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uniba.sk); Arben Pitarka, Lawrence Livermore National
Laboratory (pitarka1@llnl.gov); Wei Zhang, Southern
University of Science and Technology (zhangwei@sustech.
edu.cn)poster 114
Utilizing Metaheuristic Algorithms for Ground Motion
Selection and Scaling in Structural Time History Analysis
AKHANI, M., University of Memphis, Tennessee, USA, mkhnsnjn@
memphis.edu; ALIDADI, N., University of Memphis, Tennessee, USA,nalidadi@memphis.edu; PEZESHK, S., University of Memphis, Tennessee,
USA, spezeshk@memphis.edu
This study proposes two Metaheuristic Algorithms for structural time history analysis to optimize the selection and scaling of ground motion (GM)
records. The primary goal is to preserve the phase and shape of the response
spectra in the selected records. The methodology efficiently navigates througha vast database of earthquake records, proposing a set of 11 record pairs andcorresponding scaling factors. The outcome is a mean spectrum that closelyaligns with the target spectrum. The application of our research is demonstrated at two distinct sites in the United States: the first in Memphis and thesecond in San Francisco, following the ASCE 7-22 procedure. Selected groundmotions undergo scaling adjustments represented by scalar values within auser-defined range. Additionally, we present error metrics, comparing the target spectrum with the mean spectrum derived from the selected records. To
validate the effectiveness of our approach, a comparative analysis is conductedagainst results obtained from the PEER-NGA web application methodology.
The results highlight our model as a robust and reliable approach for acquiring
suitable GM records for structural time history analysis.
poster 115
Building Geologically Realistic Initial Conditions for
Geodynamic and Seismological Models With the
Geodynamic World Builder
FRATERS, M., University of Florida, Florida, USA, menno.fraters@tutanota.
com; BILLEN, M. I., University of California, Davis, California, USA,mibillen@ucdavis.edu; SAXENA, A., Clemson University, South Carolina,
USA, arushi@clemson.edu; GASSMOELLER, R., University of Florida,
Florida, USA, rene.gassmoeller@ufl.edu; LI, H., University of California,
Davis, California, USA, hylli@ucdavis.edu
Global and location specific geodynamical or seismological forward models
are based on a variety of geological and geophysical data used to determine
the often complex geometry of three-dimensional volumes representing
structures such as layers within tectonic plates, crustal and lithospheric terranes, faults and subducting slabs. Creating such complex geological settings
in 2D, but especially in 3D can be very challenging. Here we present the latest version of the open source code library, the Geodynamic World Builder(GWB). The GWB is designed to greatly enhance the speed of setting up andmodifying such models by parameterization of the problem. The user defines
inputs in a JSON-style parameter file, which is a structured nested list describing tectonic features, e.g. a continental, an oceanic or a subducting plate. Eachof these tectonic features can be divided into layers (which can have variable
thickness) and assigned a specific temperature model (e.g. linear or a platemodel), a compositional label (e.g. uniform) and/or a grain size and orientation model. Complex models are developed by sequentially adding structures
within a 3D domain. For each point in the domain, the GWB can be queried
for the temperature, composition and/or grain size and orientation in thatpoint.
The GWB is written in C++, but can be linked to either geodynamic
or seismological models that require complex model setups in almost any
programming language through its C, C++, Python and Fortran wrappers. It
has already been coupled with the C++ code ASPECT and with the Fortrancodes ELEFANT and SEPRAN. The GWB can also be used as a stand-alone
application for visualization purposes. We will show various examples in both
2D and 3D and in Cartesian and spherical domains. We will share a range ofexamples from building regional subduction models using Bird (2003), Slab
2.0 and Litho1.0 to global mantle models. The GWB has an extensive online
user Manual and a well documented API through Doxygen available throughhttp://geodynamicworldbuilder.github.io and can be used with Linux, OSX
and Windows operating systems.

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poster 116
Passive Source Detection Technology Based on ShortPeriod Dense Seismic ArrayGAMEZ, R., SmartSolo Inc., Texas, USA, richard_gamez@smartsolo.com;
ZOU, L., SmartSolo Inc., Shenzhen, China, lei_zou@smartsolo.com; SHEN,
J., SmartSolo Inc., Shenzhen, China, johann_shen@smartsolo.com; ZHOU,
B., SmartSolo Inc., Shenzhen, China, bo_zhou@smartsolo.com.cn
In the past decade, passive source detection technology based on short period
dense array has increasingly become a domestic and international significant
tool in the field of deep structure exploration. Compared with the traditional
broadband seismic method, this technology has the advantages of high resolution, efficiency, cost saving, and minimal environmental impact. Despite thelow-frequency signals being too weak to detect the deep structures within thelithospheric mantle, the dense station distribution allows imaging of detailed
structures within Earth’s crust. Furthermore, taking advantage of the dense
ray crossing coverage from different directions beneath the array, a stable
image of crust-mantle structures can be imaged by inversion and stack migration. Therefore, the short period dense array detection technology has been
widely used in different fields, such as imaging of deep velocity and interface structure, mineral resources exploration, volcanic activity monitoring,
microseismic high-precision Locations, and geometry and kinematic characteristics: key aspects of seismogenic faults. With the research progress of
short period dense array in the field of imaging study on crustal structuresand microseismic location monitoring. Looking into the future and guided byscientific questions, joint inversion and imaging could be carried out using avariety of geophysical data such as natural earthquake, ambient noise, gravity,
InSAR, GPS and magnetotelluric measurements to acquire the multi-attributecharacteristics of the interested targets, and this method is increasingly developing to an effective way to reduce the non uniqueness of solutions and reveal
the real state of geological bodies. The rapid development of the detection
methods in this area is expected to greatly promote the research of seismology
and geodynamics, and has a broad application prospect in the fields of deep
structure imaging and mineral resources exploration. As the world’s leading
manufacturer of short-period seismic equipment, SmartSolo provides highly
reliable, consistent, and cost-effective short-period seismometer solutions.
poster 117
Effects of Bimaterial Interface on Rupture Along StrikeSlip Branch Faults
MARSCHALL, E., University of California, Riverside, California, USA,evanmarschall516@gmail.com; DOUILLY, R., University of California,
Riverside, California, USA, robyd@ucr.edu; KAME, N., University of Tokyo,
Tokyo, Japan, kame@eri.u-tokyo.ac.jp
Crustal faults often separate material with differing elastic properties.
Dissimilar media around faults has been shown to cause substantial effects
on the rupture process along vertical strike-slip faults. Some previous studies suggest that asymmetry in wave propagation across a bimaterial interface
can introduce normal stress perturbations on the fault around the rupture
front that can lead to asymmetric bilateral or even unilateral rupture propagation. Furthermore, a bimaterial interface can also lead to differences in strain
release across a fault interface for a fixed stress drop. Considering the effects
caused by bimaterial interface on rupture propagation and also the fact thatnatural fault systems can be composed of numerous segments, it is worth
understanding whether these effects can be significant enough to impact
throughgoing rupture across a geometric complexity. Therefore, in this work
we use dynamic rupture simulations with uniform tractions to investigate theeffects of a bimaterial interface on rupture propagation along branch faults. To
do this we construct a planar branch system which consists of a 40 km longmain fault bisected by a 20 km secondary segment, at a branching angle of50°. We assign a zone of stiffer material to one side of the fault system, suchthat both the main and secondary fault separate dissimilar media. We vary thematerial contrast (γ) from 0-0.20 in the zone of stiffer material such that thep-velocity in the stiffer material is Vp*(1+γ), where Vp is the p-velocity in therest of the elastic medium. The results show that when rupture is nucleated on
the main fault it is less likely to rupture the secondary segment as the material contrast increases if the main fault and secondary faults have the same
sense of slip. If the faults have opposite senses of slip, we find that a larger
material contrast promotes rupture propagation on the secondary fault. This
could have implications for assessing seismic hazard in regions with complex
fault systems which separate dissimilar media, in particular which direction
seismic energy may be directed during an earthquake.

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New Constraints on the Seismic Crustal Structure of theSouthern Apennines (Italy): Numerical Modeling of P- andS- Body Waves for Moderate Earthquakes at Regional Scale
SCARPONI, M., Istituto Nazionale di Geofisica e Vulcanologia - INGV,
Rome, Italy, matteo.scarponi@ingv.it; DI LUCCIO, F., Istituto Nazionale diGeofisica e Vulcanologia - INGV, Rome, Italy, francesca.diluccio@ingv.it;
PIROMALLO, C., Istituto Nazionale di Geofisica e Vulcanologia - INGV,
Rome, Italy, claudia.piromallo@ingv.it; SUN, D., University of Science andTechnology of China, Hefei, China, sdy2014@ustc.edu.cn
The Apennines mountain range and the Tyrrhenian back-arc basin originatedin the central Mediterranean area, due to the convergence and collision of
the Eurasia and the Africa-Adria plates. Geological and geophysical studies
reveal variations in structural, tectonic and seismogenic patterns along thechain axis, and across the western Tyrrhenian and eastern Adriatic domains(Di Luccio et al. 2022).
Our focus lies on the southern Apennines, where the Adriatic platesubducts westward under the thinner Tyrrhenian plate, forming a complex“overlapping-Moho” setting. This area exhibits high seismic activity and heterogeneous CO2 gas emissions at the surface. Notably, these emissions ceaseto the east, where high-pressure fluids are trapped in the crust, influencing theseismogenic cycle (Chiodini et al. 2004).
Our approach involves P- and S-body waveform analysis and numericalmodeling of moderate magnitude crustal earthquakes, at the regional scale.
We concentrate on a SW-NE oriented transect cutting across the southern
Apennines chain. Along this path the observed waveforms exhibit significant
variations in frequency content and pulse shape, depending on both distanceand azimuth. We analyze the 2018 Montecilfone (Mmax 5.1) and the 2013
Sannio-Matese (Mmax 5.0) seismic sequences, to examine the characteristics
of westward and eastward wave propagation respectively.
We explore the trade-off between velocity and geometry perturbations
starting from a 1D velocity model (Di Stefano et al. 1999). We upgrade the reference EPcrust model (Molinari et al. 2011) by incorporating external information on Moho and sedimentary layer structures (Spada et al. 2013, Nicolai
and Gambini 2007). By employing the finite difference modeling code from Li
et al. (2014), we generate synthetic waveforms to better fit the observed data,in terms of arrival time, pulse shape and waveform complexity on the threecomponent seismograms. Our results contribute to the understanding of theinterplay between fluids and seismicity in the region, by providing higher
resolution constraints on the structure of the southern Apennines.

The OSIRIS-REx Sample Return Capsule Re-entry:
Geophysical Observations
Oral Session • Wednesday 1 May • 4:30 pm PacificConveners: Chris Carr, Los Alamos National Laboratory(cgcarr@lanl.gov); Brian Elbing, Oklahoma State University(elbing@okstate.edu); Charles Langston, University ofMemphis (clangstn@memphis.edu); Richard Lewis, The
Defense Threat Reduction Agency (richard.d.lewis1.
civ@mail.mil); Yasuhiro Nishikawa, Kochi University ofTechnology (nishikawa.yasuhiro@kochi-tech.ac.jp); Elizabeth
A. Silber, Sandia National Laboratory (esilbe@sandia.gov)
First-Ever Detection of a Re-Entry Capsule With Distributed
Acoustic Sensing (DAS): Initial Results and Data
Comparison With Co-Located Seismic and InfrasoundSensors
CARR, C., Los Alamos National Laboratory, New Mexico, USA, cgcarr@lanl.gov; DONAHUE, C., Los Alamos National Laboratory, New Mexico,USA, cmd@lanl.gov; VIENS, L., Los Alamos National Laboratory, New
Mexico, USA, lviens@lanl.gov; BEARDSLEE, L., Silixa, Montana, USA,luke.b.beardslee@gmail.com; MCGHEE, E., Colorado State University,
Colorado, USA, elisa.mcghee@colostate.edu; DANIELSON, L., Los Alamos
National Laboratory, New Mexico, USA, ldanielson@lanl.gov
On 24 September 2023, the OSIRIS-REX sample return capsule re-entered
Earth’s atmosphere, generating infrasonic and seismic signals. The re-entry
provided an ideal experiment for rapid deployment of fiber-optic cables to besensed with distributed acoustic sensing (DAS) interrogator units (IUs). We

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deployed 12 km of fiber at two locations in Nevada, chosen for their proximity
to the portion of the trajectory with anticipated maximum infrasound generation. At each fiber location, we deployed three co-located seismometers andinfrasound sensors to inform interpretation of DAS data. For nearly the entire
fiber length, we placed the fiber directly on the ground without any trenchingor weights to increase ground coupling. We used three different IUs to sample
the fibers at the two locations: an AP Sensing IU sampled 4.5 km of fiber at
the Eureka Airport and a Silixa IU and an Optodas IU sampled 7.5 km of fiberin nearby Newark Valley. While seismometers and infrasound sensors haverecorded previous space capsule re-entry events, our deployment represents
the first DAS recording of a re-entry.
All our instruments recorded the signal generated by the sample returncapsule. All seismometers and infrasound sensors recorded high SNR signals.
The Silixa DAS data recorded a move out of the signal as it propagated along
the 7-km fiber that can be seen without any pre-processing. We estimate backazimuths to the infrasound-generating source using beamforming techniques
for the Newark Valley data. Finally, we use arrivals recorded with the seismometers and infrasound sensors to interpret the DAS signals.
Array Data From the University of Memphis SeismoAcoustic Coupling Experiment Fielded at the Eureka
County Airport, Nevada
LANGSTON, C. A., University of Memphis, Tennessee, USA, clangstn@
memphis.edu; BAZARGAN, S., University of Memphis, Tennessee, USA,sbzargan@memphis.edu; HORTON, S., University of Memphis, Tennessee,
USA, shorton@memphis.edu; MITRA, I., University of Memphis, Tennessee,
USA, imitra@memphis.edu; ISLAM, S., University of Memphis, Tennessee,
USA, sislam4@memphis.edu
In collaboration with Sandia National Laboratory, the University of Memphis
fielded a seismo-acoustic array experiment at the Eureka County airport torecord the sonic boom from the capsule return of NASA’s OSIRIS-REx mission to the asteroid Bennu. Eureka airport is nearly under the expected trajectory of the incoming capsule that landed in the western Utah desert early
Sunday morning, September 24. The University of Memphis portion of experimental observations consists of fielding a 1 km aperture, 3x6 Golay array,composed of 18 three-component Magseis-Fairfield 5 Hz nodal seismometers, with two sub-arrays of the Golay array each containing an extra seismic node and a 4-element infrasound array. The infrasound instruments werebuilt by VLF Designs expressly for use with a REFTEK 130 DAS. The Golay
array is designed to characterize the slowness and azimuth of the descending
Mach cone that are needed parameters in modeling the conversion from theacoustic wave into P and S waves in the Earth. The Golay array also makes it
possible to analyze any secondary seismic waves that may be generated by the
acoustic N-wave through frequency-slowness analysis. Small-scale (94m), P
and S wave refraction and MASW surveys were performed near each acoustic
array to determine near-surface structure to constrain models of the seismoacoustic interaction. All seismic and acoustic array instrumentation recorded
the audible, “double”, sonic boom from capsule reentry. The incident acoustic
wave impinged on the arrays with an apparent velocity of 2.9 km/s from an
azimuth of N02oE. The infrasound observations show changes in the N-wave
waveform over a distance scale of 1km with smaller secondary coda that may
be related to near-surface seismic reverberations. The seismic data also show
significant later arrivals in the first 1s that indicate conversions and reverberations within the lakebed sediments of Diamond Valley.
Infrasound From the Osiris-Rex Src Re-Entry Observed Near
the Nevada-Utah Border
ELBING, B. R., Oklahoma State University, Oklahoma, USA, elbing@okstate.
edu; WILSON, T. C., Oklahoma State University, Oklahoma, USA, trevor.
wilson@okstate.edu; SPILLMAN, K., Oklahoma State University, Oklahoma,
USA, kate.spillman@okstate.edu; FOX, D., Oklahoma State University,
Oklahoma, USA, douglas.fox@okstate.edu; KC, R. J., Oklahoma State
University, Oklahoma, USA, realk@okstate.edu; HOUGH, E., Oklahoma State
University, Oklahoma, USA, emalee.hough@okstate.edu; YAP, Z., Oklahoma
State University, Oklahoma, USA, zyap@okstate.edu; JACOB, J. D., Oklahoma
State University, Oklahoma, USA, jdjacob@okstate.edu
The OSIRIS-REx Sample Return Capsule (SRC) re-entered the Earth’s atmosphere on the morning of 24 September 2023. The SRC entered the atmosphere
over the Pacific Ocean at a speed of over 43,000 km/hr and a few minutes later
landed in Utah. Our team had microbarometers deployed on the ground near
the border between Nevada and Utah to detect the infrasound (i.e., sound afrequency below human hearing) waves produced by the OSIRIS-REx SRC
re-entry. Most of the sensors were deployed at the Wendover Airport, which

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was nominally 58 km to the north of the SRC trajectory. Our team deployed
15 sensors at the Wendover Airport, which some were co-located with sensors
deployed by the University of Hawaii. Our team deployed three different sensor models (Chaparral Physics, GEM, and WERD) in close proximity to eachother. The Chaparral Physics sensors formed a 4-sensor array with an aperture of 112 m. The additional sensors were arranged to form smaller arraysaround the Chaparral Physics sensors. In addition, two GEM sensors were
deployed between the airport and the SRC trajectory. All the sensors observed
an N-wave arrival followed by broadband coherent rumbling after the initialarrival. This presentation will present the details of this deployment as well as
preliminary results.
Direction-Finding Observation of Vlf Radio Emission Uponthe Reentry of Osiris-Rex Sample Return Cuspule on 24
September 2023
WATANABE, T., Astronomical Society of Japan, Tokyo, Japan, watanabeggl@
gmail.com; KOBAYASHI, M., Nippon Meteor Society, Tokyo, Japan,
gomiki2222@yahoo.co.jp; KATOH, Y., Nagoya University, Nagoya, Japan,
katoh@isee.nagoya-u.ac.jp
After the detection of peculiar VLF radio noises upon the reentry of Hayabusa-2
SRC in 2020 (WGN, the Journal of the IMO 51:3, 2023), direction-finding
radio observations were performed at Pinto Summit, Eureka, Nevada upon
the reentry of the OSIRIS-REx SRC on 24 Sep. 2023 (UTC) in the frequency
region of 100 Hz - 96 kHz. Crossed loop aerials were employed to estimate theazimuthal angle (Az) of an observing radio source. The expected accuracy ofthe measurement is +/- 10 degrees. One vertical rod antenna was also used
to measure the vertical component of the electric field of the radio wave. The
initial polarity of Ez can eliminate the ambiguity in the Az estimation. We
employed a simplified method to estimate the altitudinal angle (Alt) of theradio source by assuming the directivity of the vertical antenna, but an errorof +/-20 degrees or more is expected near the zenith. We checked the consistency between the estimated (Az, Alt) and those of SRC predicted by a simple
model of its trajectory (based on the nominal parameters given in NTRS20150000809). This model is only applicable in the interval before the onset ofsignificant deceleration of the SRC. The SRC’s Entry Interface (EI) epoch was
finally adjusted to 14:42:00 UTC, after an announcement from NASA. Morethan 20 weak non-impulsive radio noises, having similar values of (Az, Alt)to those predicted by the trajectory model, were detected during the intervalof about +/- 25 sec around the peak-heating phase of the reentry (+51 secfrom EI). These signals showed relatively wider frequency spectra than thoseof daytime long-distance sferics. Although the actual trajectory of the reentry
has not been available at this stage, the presence of VLF radio emission upon
the reentry of the SRC is plausible within the level of uncertainty. Intermittent
electric discharges in the environmental plasma of SRC in the fireball phase of
the reentry are suggested to be the sources of observed radio noises.
Airborne Acoustic Observations of the OSIRIS-REx Reentry
BOWMAN, D. C., Sandia National Laboratories, New Mexico, USA,
dbowma@sandia.gov; KRISHNAMOORTHY, S., Jet Propulsion Laboratory,
California, USA, siddharth.krishnamoorthy@jpl.nasa.gov; SILBER, E.
A., Sandia National Laboratories, New Mexico, USA, esilbe@sandia.gov;
POPENHAGEN, S. K., University of Hawaii at Manoa, Hawaii, USA,
spopen@hawaii.edu; GARCES, M. A., University of Hawaii at Manoa, Hawaii,
USA, milton@isla.hawaii.edu
Natural and artificial objects arriving from interplanetary space create powerful acoustic arrivals that contain information about its speed and shape. In
the past, these sound waves were captured solely on ground-based recorders.
However, elevated platforms may be able to sample elements of the acoustic
wavefield unavailable on the Earth’s surface, such as a cleaner source signal,transmission through elevated wave guides (e. g. the ‘atmoSOFAR’ channel),and reflections from the ground. Here we report acoustic arrivals from the 24
September 2023 reentry of the OSIRIS-REx space capsule recorded on balloon-borne platforms ranging from 1.7 to nearly 20 km above ground level.
We compare the amplitude and frequency content of the balloon-recorded
signals to those captured on nearby ground stations. We investigate the propagation path from the source to the elevated receiver. Finally, we assess theorigin and properties of suspected ground reflections observed after the main
arrival passed. Our results have implications for the detection and characterization of incoming objects on Earth and other planets such as Venus. The
reflection signatures also shed light on the properties of lateral sound transmission through surface-bound acoustic ducts. SNL is managed and operated
by NTESS under DOE NNSA contract DE-NA0003525.

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The OSIRIS-REx Sample Return Capsule Re-entry:
Geophysical Observations [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Chris Carr, Los Alamos National Laboratory(cgcarr@lanl.gov); Brian Elbing, Oklahoma State University(elbing@okstate.edu); Charles Langston, University ofMemphis (clangstn@memphis.edu); Richard Lewis, The
Defense Threat Reduction Agency (richard.d.lewis1.
civ@mail.mil); Yasuhiro Nishikawa, Kochi University ofTechnology (nishikawa.yasuhiro@kochi-tech.ac.jp); Elizabeth
A. Silber, Sandia National Laboratory (esilbe@sandia.gov)
poster 68
Infrasound Analysis of the OSIRIS-REx Reentry at the
NVIAR Array
CLARKE, J., Southern Methodist University, Texas, USA, jwclarke@smu.
edu; ARROWSMITH, S., Southern Methodist University, Texas, USA,sarrowsmith@smu.edu; PARK, J., Southern Methodist University, Texas,
USA, junghyunp@smu.edu; ANDERSON, D., Southern Methodist University,
Texas, USA, davida@smu.edu
The OSIRIS-REx capsule, returning collected samples from the Bennu asteroid, passed near a permanent infrasound array, NVIAR, in western Nevada
on September 24, 2023. Southern Methodist University operates NVIAR
composed of a four-element triangular array with an aperture of 1-3 km
and a seven-element, circular infrasound array with a 70-m aperture at thecenter element of NVIAR. The return capsule traveled within 98 km of the
NVIAR array, which recorded multiple infrasound arrivals from the source.
The capsule traveled approximately 12 km/s at its nearest point to NVIAR,
98 km away, resulting in direct, N-wave type records caused by shockwaves.
Beamforming analysis confirms a moving source as the return capsule travels
from west to east past the array. Array processing results indicate three coherent arrivals within a 20-minute record section. Ray tracing analysis using the
projected return path also predicts arrivals from multiple stages of the capsulereentry, not only direct sonic boom arrivals from the closest proximity location to NVIAR. Other predicted arrivals may be from the maximum heating
point, refractions through the thermosphere, and ground-level reflections.
This study provides insight into the infrasound characteristics of a moving,elevated, hypersonic source from bolides and other hypersonic objects.
poster 69
Observation of Osiris-Rex via Shock Wave: Temporary
Observation Network Utilizing Portable Infrasound Sensors
and Comparative Analysis With Hayabusa and Hayabusa2
NISHIKAWA, Y., Kochi University of Technology, Kami, Japan, nishikawa.
yasuhiro@kochi-tech.ac.jp; YAMAMOTO, M., Kochi University ofTechnology, Kami, Japan, yamamoto.masa-yuki@kochi-tech.ac.jp; HASUMI,
Y., Kochi University of Technology, Kami, Japan, h.g.y.00.m.23@gmail.com
On September 24, 2023, National Aeronautics and Space Administration’s
OSIRIS-REx sample return capsule (SRC) re-entered Earth’s atmosphere. The
capsule flew over Nevada, creating a shock wave around it, before landing in
Utah. The Kochi University of Technology team was part of the infrasound/seismic observation team and installed someinfrasound sensors and microphones at Eureka airport in Nevada to capture the atmospheric pressure
perturbations (infrasound and sound) generated by SRC. We successfully
captured infrasound and sound generated from OSIRIS-REx. Our previous
experience with observing HAYABUSA and HAYABUSA 2 (Japan Aerospace
Exploration Agency’s sample return mission) led us to employ the same portable infrasound sensor for this task. In this presentation, we will share theresults of our OSIRIS-REx observations and compare them with our earlier
findings from studying HAYABUSA and HAYABUSA2.
poster 70
Leveraging Infrasound Detections of Sample Return Space
Missions Towards Characterization of Meteors: A Review
SILBER, E. A., Sandia National Laboratories, New Mexico, USA, esilbe@
sandia.gov; BOWMAN, D. C., Sandia National Laboratories, New Mexico,

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USA, dbowma@sandia.gov; ALBERT, S. A., Sandia National Laboratories,
New Mexico, USA, salber@sandia.gov
Upon entering the Earth’s atmosphere at hypervelocity (11.2–73 km/s), large
meteoroids (> ~10 cm) and asteroids (>1 m in diameter) undergo complex
processes as they plunge into dense regions of the atmosphere. These objects
also generate powerful acoustic waves with dominant frequencies below
human hearing, known as infrasound. Depending on atmospheric conditions,infrasound could be detected by ground-based or airborne microbarometers.
Well-documented encounters with asteroids are rare because impacts in thatsize-range are sporadic and largely unpredictable, making dedicated observational campaigns impractical to plan. Unless there are multi-modal detections as well as the presence of physical material (i.e., meteorites), there will
be notable uncertainties pertaining to the derived object parameters. In thequest to better characterize extraterrestrial objects and accompanying physical phenomena, it is possible to leverage space mission sample return capsules (SRCs). SRCs can serve as ‘artificial meteors’ given that they re-enterfrom interplanetary space at speeds corresponding to slow meteoroids. We
will discuss infrasound observations of SRCs since the end of the Apollo era,emphasizing efforts between 2004 and 2021.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 71
The Utility of Infrasound Towards Detection andCharacterization of Bolides
SILBER, E. A., Sandia National Laboratories, New Mexico, USA, esilbe@
sandia.gov
Very bright meteors, also known as fireballs and bolides, are produced when
extraterrestrial objects larger than approximately 10 cm in diameter enter
dense regions of the Earth’s atmosphere. Besides the luminous phenomenon,
bolides also generate shock waves, which decay to low frequency acoustic
waves or infrasound. Depending on initial conditions, atmospheric propagation paths, and the mode of shock production, infrasound emanating from abolide can be detected by microbarometers hundreds and even thousands ofkilometers away. Unlike other sensing modalities that might have geographic(e.g., inaccessible regions), time-of-day (e.g., optical) or other limitations,infrasound can be utilized continuously (day and night) on a global scale.
Hence, infrasound can be leveraged towards detection and localization ofbolides, as well as estimating their explosive yield. Bolide infrasound detections date back to the early 20th century. On June 30, 1908, an extraterrestrial
object exploded over Tunguska, Siberia, generating low frequency acoustic
waves that mark the first known instrumentally observed bolide infrasound.
During the mid-20th century, ten large bolides were detected by infrasoundstations meant for explosion monitoring. Since the mid-1990s, many more
events have been detected via infrasound. However, characterization ofbolides through infrasound is not without its challenges, mainly because no
two bolide events are alike. Systematic studies and data fusion can aid in better constraining some important parameters. Here, a brief primer on bolide
infrasound accompanied by notable examples will be presented.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 72
Infrasound Detection of the OSIRIS-REx Re-Entry: Signal
Characteristics
SILBER, E. A., Sandia National Laboratories, New Mexico, USA, esilbe@
sandia.gov; BOWMAN, D. C., Sandia National Laboratories, New Mexico,USA, dbowma@sandia.gov
Sample Return Capsules (SRCs) enter Earth’s atmosphere with energies
equivalent to decimeter-scale meteoroids. Upon entering dense regions of theatmosphere, these objects generate shockwaves, which decay to low frequency
sound. These acoustic waves can be detected by sensitive instruments positioned on the ground and on high-altitude platforms. Since SRCs are wellcharacterized objects with known parameters (speed, mass, size, etc.), their reentries can be leveraged towards studying meteor phenomena, characterizing
high-altitude shockwave dynamics, improving entry and propagation models,and advancing global monitoring efforts. On September 24, 2023, NASA’s
OSIRIS-REx sample return capsule (SRC) successfully brought particles of the
nearby asteroid Bennu to Earth. The sample return capsule generated shockwaves as it entered the atmosphere, traversing California, Nevada and Utah
before landing at the UTTR. We deployed infrasound and seismic sensors in
Nevada and Utah to capture the signals as a function of distance from the
trajectory and from different parts of the trail. We will discuss signal char-www.srl-online.org•

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acteristics different stations, and how these might relate to SRC altitude andpoint(s) along the trajectory. The results have implications for future observational efforts on Earth as well as capturing shockwave signatures on otherplanetary bodies with atmospheres (e.g., Mars, Titan, Venus). SNL is managed
and operated by NTESS under DOE NNSA contract DE-NA0003525
poster 73
The OSIRIS-REx Sample Return Capsule Re-Entry: Initial
Results From a Historic Geophysical Recording Campaign
Against an ‘Artificial Meteor’
SILBER, E. A., Sandia National Laboratories, New Mexico, USA, esilbe@
sandia.gov; BOWMAN, D. C., Sandia National Laboratories, New Mexico,USA, dbowma@sandia.gov; KRISHNAMOORTHY, S., Jet Propulsion
Laboratory, California, USA, siddharth.krishnamoorthy@jpl.nasa.gov;
CARR, C., Los Alamos National Laboratory, New Mexico, USA, cgcarr@lanl.
gov; HAASER, R. A., Los Alamos National Laboratory, New Mexico, USA,rhaaser@lanl.gov; ELBING, B. R., Oklahoma State University, Oklahoma,
USA, elbing@okstate.edu; GARCES, M. A., University of Hawaii at Manoa,
Hawaii, USA, garces@isla.hawaii.edu; LANGSTON, C. A., University ofMemphis, Tennessee, USA, clangstn@memphis.edu; WEBSTER, J. D.,
Los Alamos National Laboratory, New Mexico, USA, jwebster@lanl.gov;
EISENBERG, D. P., TDA Research, Colorado, USA, deisenberg@tda.com;
LAM, E., Air Force Research Laboratory, Ohio, USA, eric.lam.3@us.af.mil;
FERNANDO, B., Johns Hopkins University, Maryland, USA, bfernan9@
jh.edu; ZEILER, C. P., Nevada National Security Site, Nevada, USA,zeilercp@nv.doe.gov; NISHIKAWA, Y., Kochi University of Technology,
Kami City, Japan, nishikawa.yasuhiro@kochi-tech.ac.jp; LEWIS, R. D.,
Defense Threat Reduction Agency, Virginia, USA, richard.d.lewis1.civ@mail.
mil; OCAMPO GIRALDO, L. A., Idaho National Laboratory, Idaho, USA,
Luis.OcampoGiraldo@inl.gov; ARROWSMITH, S., Southern Methodist
University, Texas, USA, sarrowsmith@mail.smu.edu
Artificial and natural objects entering Earth’s atmosphere at hypervelocity generate powerful acoustic waves, but well-characterized observations of
entries are exceptionally scarce. This is because impacts by small asteroids(1 m in diameter and greater) are rare and random, making it impracticalto plan dedicated observational campaigns. Artificial objects arriving frominterplanetary space have the parameters well known a priori and can serve
as ideal proxies for studying meteoric phenomena and are critical for improving global monitoring; however, only a handful of spacecraft have re-enteredsince the end of the Apollo era. The most recent opportunity presented itself
with the re-entry of NASA’s OSIRIS-REx sample return capsule (SRC) on
September 24, 2023. A multi-institutional effort resulted in the largest to-date
observational campaign to capture geophysical signals generated by an object
as it re-entered the atmosphere from interplanetary space. We will describe
the observational campaign, instruments, and the geographical coverage. We
will also discuss field observations and present initial results. SNL is managed
and operated by NTESS under DOE NNSA contract DE-NA0003525.
poster 74
The First Detection of an ‘Artificial Meteor’ by a Large N
Acoustic Array
SILBER, E. A., Sandia National Laboratories, New Mexico, USA, esilbe@
sandia.gov; BOWMAN, D. C., Sandia National Laboratories, New Mexico,USA, dbowma@sandia.gov; EISENBERG, D. P., TDA Research, Colorado,
USA, deisenberg@tda.com
On September 24, 2023, NASA’s OSIRIS-REx sample return capsule (SRC)
landed in Utah, bringing delicate particles of the nearby asteroid Bennu toEarth. SRC are considered ‘artificial meteors’ since they are analogous tonatural extraterrestrial objects impacting Earth. The SRC entered the atmosphere at hypervelocity over California and flew over Nevada, before slowing down and landing at the Utah Test and Training Range (UTTR). Dense
nodal acoustic arrays, like their seismic cousins, can provide detailed signal
information that is otherwise unavailable using standard array installations.
A large N-array with 118 recently developed nodal sensors was deployed in
Eureka, Nevada enclosing a 100 x 100 m square. The location was near thenominal ground track and approximately 60 km beneath the trajectory. The
large N-array readily detected infrasound signatures related to the ballistic
shockwaves generated by the SRC. We will discuss the utility of dense arrayinstallations towards similar applications. SNL is managed and operated by
NTESS under DOE NNSA contract DE-NA0003525.

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Physics-Based Ground Motion Modeling
Oral Session • Friday 3 May • 8:00 am PacificConveners: Evan Hirakawa, U.S. Geological Survey(ehirakawa@usgs.gov); Kim B. Olsen, San Diego State
University (kbolsen@mail.sdsu.edu); William Stephenson,
U.S. Geological Survey (wstephens@usgs.gov)
Evaluation of Seismic Community Velocity Models With
Simulations of Small Earthquakes
PINILLA RAMOS, C., Statewide California Earthquake Center, California,
USA, camilo.pinilla@berkeley.edu; BEN-ZION, Y., Statewide California
Earthquake Center, California, USA, benzion@usc.edu; ABRAHAMSON,
N. A., University of California, Berkeley, California, USA, abrahamson@
berkeley.edu; MAECHLING, P. J., Statewide California Earthquake Center,
California, USA, maechlin@usc.edu; CALLAGHAN, S., Statewide California
Earthquake Center, California, USA, scottcal@usc.edu; MENG, X., Statewide
California Earthquake Center, California, USA, xiaofenm@usc.edu
Seismic community velocity models (CVMs) are foundational for many basic
and applied topics ranging from derivations of earthquake source properties
to simulations of ground motions. CVM accuracy directly impacts the epistemic uncertainty of synthetic wave fields generated by earthquakes or 3D
physics-based simulations. We present an innovative methodology to evaluate the epistemic uncertainty reflected in key intensity measures of groundmotions related to seismic hazard analysis. This methodology involves simulating point source approximation wavefields from small historic earthquakes
located in different parts of the crustal volume of interest and comparisonsof results to observations. Using small events and the point source approximation facilitates a focus on properties of the CVM rather than finite source
ruptures. Evaluation of differences between observed and synthetic data inspectral amplitude, phase matching, and signal duration allows us to estimate
epistemic uncertainties and identify features and subregions of the CVM
to improve. Here, we apply this framework to evaluate the performance ofCVMs developed for southern and northern California. The evaluation
employs three-dimensional physics-based ground motion simulations of setsof local small earthquakes with magnitudes ranging from 3.5 to 4.5. Becauseof the relatively low ground-motion amplitude induced by these earthquakes,
the soil response is expected to be well-represented as linear at all recording sites. Therefore, the misfit between observed and synthetic waveforms canbe mainly attributed to structural complexities not fully represented in theexamined CVMs and, to a lesser extent, the source parameterization (location,
depth, focal mechanism, source time function). Maps displaying the spatial
distribution of residuals in the spectral domain facilitate the recognition ofareas where each model performs better than the others and provide important guidance for future refinements of the CVMs.
Waveguide or Not? Expected Ground Motions in the
Greater Los Angeles Area From the ShakeOut scenario
YEH, T., San Diego State University, California, USA, tyeh2@sdsu.edu;
OLSEN, K. B., San Diego State University, California, USA, kbolsen@sdsu.
edu
Since its introduction in 2008, the ShakeOut scenario of a M7.8 northwestward rupture on the southern San Andreas fault (SSAF, Jones et al., 2008)
has been widely used as a basis for a world-wide earthquake drill as well as
for estimation of seismic hazard and potential economic losses in Southern
California. Previous ShakeOut studies predicted significant long-period
ground motion amplification in the Los Angeles areas, caused by a waveguidefrom interconnected sedimentary basins (Olsen et al., 2008, 2009; Graves etal., 2008). However, the original ShakeOut simulations omitted surface topography, and subsequent studies have refined the velocity structure of southern
California as well as the SSAF. In this study, we conduct 0-1 Hz 3D numerical wave propagation simulations for the ShakeOut scenario in the Statewide
California Earthquake Center (SCEC) Community Velocity Model (CVM)
version 4.26M01, including updated high-resolution velocity structure of
the Imperial and Coachella Valleys from reflection seismic imaging (Ajala etal., 2019; Persaud et al., 2016) and the northern basins (San Gabriel, Chino
and San Bernardino Basin) from ambient noise imaging (Li et al., 2023), anddetailed geometry of the SSAF (Fuis et al., 2017). We find a reduction of longperiod ground motion levels (measured by spectral accelerations at a periodof 3s, 3s-SA) by up to 55% along the waveguide into the Los Angeles basin,caused by stronger scattering effects from spatial complexity introduced by
the updated CVM in areas outside the basins. Topographic scattering further

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decreases the 3s-SA values by another 40% due to the loss of coherency in thesurface wave train. The addition of high-resolution near-fault models slightly
increases the long-period (6s and longer) ground motion in the basins. The
combined effects of the updated velocity models and surface topography
reduce the maximum peak ground velocities in the waveguide from 250 cm/s
to 100 cm/s. The significantly different ground motion pattern in the densely
populated Los Angeles metropolitan area implies the need to revise seismic
risk accordingly.
Effect of Soil Nonlinearity on Physics-Based Ground
Motion Simulations
ZHANG, W., University of Texas at Austin, Texas, USA, wzhang@tacc.utexas.
edu
Nonlinearity can dramatically affect soil behavior, especially for the soft soils
within the shallow crust and under complex cyclic loadings induced by strong
earthquakes. In the past few decades, numerous constitutive models of soils
have been developed and applied to the analysis of soils and soil-structure systems. However, few physics-based ground motion simulations consider soil
nonlinearity, mainly due to a significant increase in computational cost whennonlinearity is included and a lack of data to calibrate a constitutive model
for a large region. In this study, we adopted a 3D bounding surface plasticity
model, calibrated it using stiffness degradation (G/Gmax) curves for multiple
geology formations, and performed a large-scale broadband (up to 8 Hz) fully
nonlinear physics-based ground motion simulation for a district in Istanbul,
Turkey. In addition, by utilizing the simulated ground motions, we conducted
one-dimensional nonlinear site response analyses (SRA) for a total of 2912
sites. For each site, we compared the time histories and surface shaking intensities, such as PGA, PGV and spectral accelerations, between linear and nonlinear 3D simulations, 1D nonlinear SRAs and an empirical ground motion
model. Results indicate that soil nonlinearity can both significantly amplify
and slightly de-amplify site responses, depending on the soil parameters (e.g.,
Vs30, G/Gmax curves, bedrock depth) of the sites.
3D 0-10 Hz Physics-based Simulations of the 2020 Magna,
Utah Earthquake Sequence
XU, K., San Diego State University, California, USA, kxu4143@sdsu.edu;
OLSEN, K. B., San Diego State University, California, USA, kbolsen@sdsu.edu
The Salt Lake City Segment of the Wasatch fault (WFSLC), where the probability of a M7 earthquake in the next 100 years is estimated to be 16%(McCalpin and Nelson, 2000), is a primary seismic hazard to the Salt Lake
Valley, populated by 1 million+ people. The 2020 Magna, UT, earthquake,
which likely occurred on the WFSLC, generated Peak Ground Accelerations(PGAs) as large as 0.55 g, and was a stern reminder of the seismic hazards forthe area. Here, we present 3D wave propagation simulations of the Magnaearthquake sequence in the Wasatch Front Community Velocity Model(WFCVM, Magistrale et al., 2008) up to 10 Hz to better constrain both linear
and nonlinear parameters in the soils of the Salt Lake Valley. We first validated the WFCVM via linear simulations of a M4.5 aftershock in the Magnasequence. By adding a geotechnical layer outside the basin, a statistical distribution of small-scale velocity heterogeneities with 10% standard deviation,and using frequency-dependent anelastic attenuation as Qs=0.05*Vs (f<1 Hz)
and Qs(f)=0.05*Vs*f0.4 (f>1 Hz, Vs in m/s), we obtained an overall satisfactory
fit to the seismic recordings for the aftershock. Our simulations of the 2020
Magna main shock use finite-fault source models from the Graves-Pitarka
rupture generator, and a preferred source model is chosen with minimal
bias to data at f<1 Hz, where nonlinear effects are expected to be negligible.
Although different plausible source realizations result in factor-of-ten variations in high-frequency synthetic ground accelerations, they generally overestimate those of the recordings, in particular at stations with the largest PGAs,
suggesting the presence of nonlinear soil effects. Then, using a fully hysteretic
multi-yield-surface 3D method (Roten et al., 2023) we find that Darendeli’s(2001) proposed reference strain-depth relations provide excessive dampingof the high-frequency synthetics in the Magna area, with an optimal fit toobservations for reference strains 3 standard deviations larger. Our findings
provide a basis for improved seismic hazard analyses of the greater Salt Lake
City region.

Spe Rock-Valley-Direct-Comparison Chemical Explosions
Near-Field 3-D Ground Motion Simulations and Predictions
EZZEDINE, S. M., Lawrence Livermore National Laboratory, California,
USA, ezzedine1@llnl.gov; VOROBIEV, O., Lawrence Livermore National
Laboratory, California, USA, vorobiev1@llnl.gov
Rock Valley Direct Comparison (RV/DC) is Phase III of the Source Physics
Experiment (SPE) series. The first explosion, RVDC-1, is a 1-ton equivalent
TNT located at 1.8km depth, while the second, RVDC-2, is a 10-ton equivalent TNT located at 1.7km depth. The local geology of the site is complex andencompasses a deep hard-rock (dolomite starting at 1km depth) and the shallow 1km is a mixture of tuff and sedimentary layers, deposited under a rugged
topography. The water table is located nearly 500m deep. The layered beds
are crosscut by a series of faults. The source package is sized to be 3.5 to 4.5
feet diameter emplaced in a 4 to 5 feet diameter ground-zero (GZ) borehole
RV/DC includes two chemical explosion experiments. The characterization of
the geology is limited and includes one straight continuous core-hole (CH),and two directional observation boreholes (OB) cored as needed sporadically. Based on this complex geological conceptual setting, we have conducted3-dimensional non-linear numerical simulations of the ground motions generated from both explosions. First, we used deterministic geophysical properties of the layered model and assessed the response of the system with andwithout the faults to assess their effect on the anisotropic radiation of theground motions. Second, because of the limited characterization of the site,
we have included stochastic variations in the geological layers. We adopted ascheme of including stochastic discrete fractures in the deep dolomite layer(analogue to SPE Phase I), while a continuous stochastic variation of lenses inthe shallow geological layers (analogue to SPE Phase II). Assessing the effect of
those stochastic parametrizations on the overall response of the system wereobtained using a sophisticated interval Monte Carlo method. Material models
have been calibrated to laboratory experiments and assessed under variably
saturation conditions. Differentials of ground motion under different conditions of physical and structural uncertainties are then derived for both RVDC1, RVDC-2, and a hypothetical earthquake.
Modeling Topography and Fault Geometry Effects on
Earthquake Ruptures and Ground Motions Along Double
Compressional Bends
MADERA, N., California State University, Northridge, California, USA,
nmgeosci@gmail.com; LOZOS, J., California State University, Northridge,
California, USA, julian.lozos@csun.edu
Fault geometry is known for affecting the endpoints of earthquake ruptures.
Recent studies suggest that ground surface topography also affects earthquake
ruptures and ground motion, but they do not offer much physical explanations. This project is a dynamic rupture modeling geometrical parameter
study that explores the effects of fault geometry and topography on earthquake ruptures and ground motion on double compressional bends in strikeslip faults. Our primary variables are fault bend angles, and mountain height
and width. Our results show that bend angle has a larger role in controlling
earthquake ruptures than topography does. For bend angles >= 23°, earthquakes stop within the linking segment, while faults with bend angles =< 22°
ruptured entirely, regardless of topography. Higher or lower initial stresses
shift this transition point by only 2° and 1°, respectively. Mountains allow
more of the fault to slip compared to the flat models and produce tails andpatches of slip along the surface. In models with topography, both supershear
and subshear rupture fronts occur. Shallow normal stress perturbations occur
at and behind the subshear rupture front, which increase in length and depth
for taller and wider mountains and increase in number for narrower ones.
Seismic wave reflections within the topography along the linking segment,
and associated normal stress perturbations, produce the tails and patches ofslip along the surface. This effect is largest when the mountain height is larger
than the mountain width. Fault-adjacent topography also increases maximum
ground motions in the near field, particularly directly on the hills.
The Effects of Surface Topography and Basin Layering on
the Earthquake Ground Motion Intensities inIntermontane-Basin Settings
AGRAWAL, H., University of Edinburgh, Edinburgh, United Kingdom,
himanshu.agrawal@ed.ac.uk; NAYLOR, M., University of Edinburgh,
Edinburgh, United Kingdom, mark.naylor@ed.ac.uk
Many densely populated intermontane sedimentary basins in collisional tectonic settings possess high seismic risk due to widely observed basin-specificground motion amplifications. The documented observations show thatground motion predictions in these basins are often poorly constrained due to

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oversight of surrounding surface topography and the absence of sub-surface
information about deeper basin layering, leading to inaccurate hazard assessment. In this study, we systematically evaluate the implications of these two
factors on high-frequency ground motion characteristics, which is crucial forearthquake engineering practices.
Using the Kathmandu sedimentary basin as our case-study area, we
extract a 2D east-west cross-section of length 80km containing high relief
surface topography on either side of the 20km-wide basin. We simulate theeastward travelling Rayleigh waves in a high-resolution domain allowing us
to resolve frequencies up to 5Hz. Our results indicate that the topography
reduces peak ground acceleration (PGA) in the basin by 40% as compared toscenarios when the topography is neglected, particularly shielding frequencies above 2 Hz. We also perform 3D simulations of a shallow thrust-faulting
moment tensor source in the west of the Kathmandu basin to confirm thehigh-frequency attenuation of waves entering the basin area due to the surface
topography. In a simultaneous analysis for basin-specific properties, we findthat the deeper Kathmandu basin layers control the spatial variability in theobserved amplification that has an order of magnitude difference within thebasin compared to the scenarios excluding the deeper basin layers.
We conclude that neglecting topography in ground motion predictions
may lead to an overestimation of ground motion amplification in the basin,
particularly for higher frequencies. A strong emphasis must also be given to
maximise the understanding of deeper basin layers to capture the spatial variability in the ground motions. This is particularly relevant to microzonation
studies where high spatial resolution is needed for risk-mitigation measures.
Analysis of Anomalously Large High-Frequency
Amplification in Chugiak, Ak, From the 2018 Anchorage
Earthquake and Aftershocks
YEH, T., San Diego State University, California, USA, tyeh2@sdsu.edu;
OLSEN, K. B., San Diego State University, California, USA, kbolsen@sdsu.
edu; STEIDL, J. H., University of California, Santa Barbara, California, USA,jsteidl@usgs.gov; HAEUSSLER, P. J., U.S. Geological Survey, Alaska, USA,pheuslr@usgs.gov
A dense, pseudo-linear nodal ~3km long array was deployed in Chugiak,
Alaska (30 km NE of Anchorage, AK) by the USGS from 2021-08-09 to 202109-08 around the permanent NetQuakes station ARTY where an anomoulously large peak-ground acceleration (PGA) of 1.98 g was recorded during
the 2018 Mw 7.1 Anchorage, AK earthquake, as compared to ~0.3 g at a nearbysite. The nodal array data for aftershocks with different magnitudes (ML 1.8 4.3) and azimuths confirm the anomalously large ground motions recordedat the permanent station and show similar PGA amplification at stations up
to ~1 km further to the east of ARTY. The topography and Quaternary geology along the transect are characterized by a series of flat surfaces and steep
slopes, interpreted as kame terraces and outwash fans, which formed during
deglaciation prior to 14 kya. In this study, we perform 3D finite-difference
simulations up to 10 Hz, including the 1m-resolution surface topography, toexplore the cause of these unexpectedly large amplifications. The simulations,computed with a near-surface geotechnical layer (GTL) tapered to 350 m
depth, match the nodal data reasonably well at stations west of ARTY as wellas those near the eastern end of the array towards the mountains, while thismodel underpredicts in the area covered by glacial sediments. The addition ofa layer of glacial sediments near the surface along the array and surroundings
with depth-to-bedrock constrained by water wells and assuming a Vs30 of 400
m/s improves the fit to data from the array considerably, except for underprediction on the N-S component. Our analysis also reveals that PGAs along thearray can be modulated by up to 50% by topography, with the largest effects
along the local topographic gradients. Our study shows that the anomalously
large high-frequency amplification recorded at and near ARTY is caused by
a combination of topographic effects and near-surface low-velocity material.
Findings from a Decade of Ground Motion Simulation
Validation Research and a Path Forward
REZAEIAN, S., U.S. Geological Survey, Colorado, USA, srezaeian@usgs.
gov; STEWART, J. P., University of California, Los Angeles, California, USA,jstewart@seas.ucla.edu; LUCO, N., U.S. Geological Survey, Colorado, USA,

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nluco@usgs.gov; GOULET, C., U.S. Geological Survey, California, USA,goulet@usgs.gov
Simulation of earthquake ground motions has advanced in recent years,
with modelers utilizing various approaches (e.g., deterministic, kinematic,
dynamic, stochastic, and hybrid methods) to represent real ground motions
more accurately. Simulated ground motions have the potential to advanceseismic hazard assessments and structural response analyses, particularly forconditions with limited recorded ground motions such as large magnitude
earthquakes at short source-to-site distances. However, rigorous validationof simulated ground motions is needed for hazard analysts, practicing engineers, or regulatory bodies to be confident in their use. A decade ago, validation exercises were mainly limited to comparisons of simulated-to-observed
waveforms and median values of spectral accelerations for selected earthquakes. The Southern California Earthquake Center (SCEC) Ground Motion
Simulation Validation (GMSV) group was formed to increase coordination
between simulation modelers and research engineers with the aim of devisingand applying more effective methods for simulation validation. Here, we summarize what has been learned in over a decade of GMSV activities, principallyreflecting the views of the SCEC research community but also extending our
findings and suggestions for a path forward to broader U.S. and worldwide
simulation validation efforts. We categorize different validation methods
according to their approach and the metrics considered. These two generalapproaches are to compare validation metrics from simulations to those from
historical records or to those from semi-empirical models. Validation metrics
are categorized into ground motion characteristics and structural responses.
We discuss example validation studies that have been impactful in the past
decade and suggest future research directions. Key lessons learned are thatvalidation is application-specific, our outreach and dissemination need
improvement, and much validation-related research remains unexplored. The
work to be presented is published as a journal paper (Rezaeian et al. 2023,
Earthquake Spectra, doi:10.1177/87552930231212475).
Correlated Noise in Source Time Functions: A Method toGenerate Realistic High Frequency Earthquake Sources
CASTRO-CRUZ, D., King Abdullah University of Science and Technology,
Thuwal, Saudi Arabia, david.castrocruz@kaust.edu.sa; AQUIB, T. T., King
Abdullah University of Science and Technology, Thuwal, Saudi Arabia,
tariqanwar.aquib@kaust.edu.sa; VYAS, J. J., King Abdullah University of
Science and Technology, Thuwal, Saudi Arabia, jagdish.vyas@kaust.edu.sa;
MAI, P. P. M., King Abdullah University of Science and Technology, Thuwal,
Saudi Arabia, martin.mai@kaust.edu.sa
We perform broadband ground motion simulations with a new methodology
to create kinematic sources that account for small-scale rupture heterogeneity, whereby we focus especially on realistic source time functions (STF). Our
broadband kinematic source generator begins with Von Karman patterns tocreate future slip distributions from amplitude and geometry source parameters. Using Mai and Beroza (2002) relationships, findings of Thingbaijam andMai (2016) on slip distribution parameterization, and slip-constrained hypocentre locations (Mai et al., 2005), our rupture generator creates dynamically
self-consistent kinematic source realizations. We then apply the methodology
of Liu et al (2006) to perturb rupture onset times and the local rise times todefine the main parameters of the rupture propagation.
Using a regularized Yoffe as STF, our method describes the local slip evolution at each subfault. As marked in previous studies, the regularized Yoffe
function well replicates, in time and frequency, dynamic STF’s. However, theregularized Yoffe function generates spectral notches in the high-frequency
amplitude spectra. Those notches render the high-frequency source implementation unrealistic, affecting also the total moment rate function and farfield ground motions. To create more plausible rupture realization based on a
Yoffe STF, we propose adding correlated noise. The correlated noise follows a
1D Von Karman random field. The parameters to define this random field are
estimated by comparing STF from dynamic rupture simulations and regularized Yoffe function, using 21 dynamic simulations (from Mai et al., 2018).
Using our rupture generator, we compute the ground motion at different locations, reproducing the mean and standard deviation from GMM in different intensity measures in simulations of M 6.0-7.0. Additionally, our rupture
generator allows us to integrate low-frequency inversions and stochasticallycomplement the high frequency of the original source. In summary, ourimproved pseudo-dynamic kinematic rupture generator produces realistichigh frequency sources essential for seismic hazard analysis.

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Physics-Based Ground Motion Modeling [Poster Session]
Poster Session • Friday 3 May
Conveners: Conveners: Evan Hirakawa, U.S. Geological
Survey (ehirakawa@usgs.gov); Kim B. Olsen, San Diego State
University (kbolsen@mail.sdsu.edu); William Stephenson,
U.S. Geological Survey (wstephens@usgs.gov)
poster 87
A Parametric Analysis on the Behaviors of Seismic Waves
Interacting With Geologic Metamaterials
BESKARDES, G. D., Sandia National Laboratories, New Mexico, USA,gdbeska@sandia.gov; PRESTON, L., Sandia National Laboratories, New
Mexico, USA, lpresto@sandia.gov
The idea of developing seismic invisibility cloaks that render geologic targets
invisible to seismic waves has recently received increased attention for earthquake hazard reduction. Using the concept of invisibility cloaks, previous field
experiments that considered sets of air-filled boreholes (seismic metamaterials) and forests of trees (above-surface resonators) as seismic cloaks successfully demonstrated the feasibility of both for seismic energy suppression at
specific bandwidths for earthquake protection. While the experiments provide a strong motivation for the applicability of seismic cloaking to real world
applications, designing optimal seismic metamaterials specific for a given fieldof interest requires a better understanding of how the design parameters andgeologic factors affect the response of a passing seismic wavefield at geophysical scales.
Here, we investigate the behaviors of seismic waves through geologic
metamaterials with different design parameters by conducting a thoroughnumerical modeling study. An in-house, finite difference modeling code isused to simulate elastic wave propagation in 3D geologic media. Our analysis
particularly focuses on the interactions of a passing seismic wavefield withgeologic media that are transformed into seismic metamaterials via borehole
implantations. We systematically test the influence of geologic metamaterial
design parameters (density and geometry of boreholes) and the complexity of
the host geologic media on wave propagation.
SNL is managed and operated by NTESS under DOE NNSA contract
DE-NA0003525.
poster 88
Updated Regional Seismic Velocity Model for the US
Atlantic and Gulf Coastal Plains Based on Measured Shear
Wave Velocity, Sediment Thickness, Varying Geologic
Structure With Depth, and Lateral Variations
GANN-PHILLIPS, C., North Carolina State University, North Carolina,
USA, cvgann@ncsu.edu; CABAS, A., North Carolina State University, North
Carolina, USA, amcabasm@ncsu.edu
The Atlantic and Gulf Coastal Plains (CPs) consist of thick and soft sediments that overlie a stiff bedrock that increase the amplification and duration of earthquake ground motions. Understanding both the depth and the
dynamic properties of these sediments is critical yet challenging at a regional
scale. Sediment thickness and geology have been shown to be good indicators for regional characterization of shear wave velocity (VS). Due to limited
characterization of the velocity structure within site amplification models in
the region, a new geology-based VS model was previously developed to better characterize the CP sediments so that amplification and hazard levels canbe estimated. This geology-based model was based on measured shear-wave
velocity and sediment thickness, but geologic grouping was only based on surface geology. Median profiles were developed for five surface geologic groups
with no lateral variation within each group. Thus, to further improve thecharacterization of the regional velocity structure, the previously developed
velocity model has been updated to include correlations with stratigraphic
sequences, constraints with depth, and lateral variations within geologic
groups. Additional measured VS data are also incorporated within the model
to increase coverage in data-sparse areas. These updates will be helpful for thedevelopment of new GMMs aiming to characterize systematic site effects via
the time-averaged VS in the top 30 meters (VS30) and sediment thickness in
the region.

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Seismological Research Lettersposter 89
Physics-based Numerical Modeling of Site-specific
Amplification in Ground Motions: A Case Study of
Wellington Basin
LI, D., GNS Science, lower hutt, New Zealand, d.li@gns.cri.nz;
THINGBAIJAM, K., GNS Science, lower hutt, New Zealand, k.thingbaijam@
gns.cri.nz; HILL, M., GNS Science, lower hutt, New Zealand, m.hill@gns.
cri.nz; HOWELL, A., GNS Science, lower hutt, New Zealand, a.howell@
gns.cri.nz; BORA, S., GNS Science, lower hutt, New Zealand, s.bora@gns.
cri.nz; KAISER, A., GNS Science, lower hutt, New Zealand, A.Kaiser@gns.
cri.nz; GERSTENBERGER, M., GNS Science, lower hutt, New Zealand,
M.Gerstenberger@gns.cri.nz
The amplification effect of site-specific near-surface velocity structure plays
a crucial role in modulating ground shaking level, and in turn, contributes
to seismic risk. However, the general understanding of this effect is limited,
owing to complex 3D geological structures and the influence of coseismic
source dynamics on-site response (Olsen, 2000). In this study, we use physicsbased simulations of ground motion to investigate fundamental characteristics of the regional seismic response that may not be easily analyzed using
regional seismic recordings.
We develop numerical models for Wellington City, which is a seismically
active area with multiple active crustal faults and the Hikurangi Subduction
Zone beneath it. This unique geological setting requires investigating potential earthquake ruptures and their effects on ground shaking levels. Several
geological and geotechnical surveys have provided valuable knowledge abouthigh-resolution topography, shallow structures, and fault networks (Hill et al.
2022). We focus on simulating ground motions using either kinematic sourcesor spontaneous coseismic ruptures. Key aspects of our study include (1) incorporation of 3D fault geometry and complex ruptures of multiple faults, (2)utilization of regional 3D basin structure, (3) development of peak groundmotion maps, and (4) evaluation of the impacts of regional topography, seismic attenuation, and 3D geological models on the ground motion levels.
By studying the dynamic earthquake source process, its interaction
with regional geological structures, and its impact on site amplification, we
combine advanced numerical simulations with regional geodetic, geological, and seismological records. Based on the simulated seismic scenarios of
the regional earthquakes, we aim to advance our knowledge of future groundshaking levels in the city and to provide general theoretical references toimprove empirical ground motion models, and consequently, seismic hazard
analysis.
poster 90
Constraining Large Magnitude Event Source and Path
Effects Using Ground Motion Simulations
MENG, X., Statewide California Earthquake Center, California, USA,xiaofenm@usc.edu; GRAVES, R., U.S. Geological Survey, California, USA,rwgraves@usgs.gov; GOULET, C., U.S. Geological Survey, California, USA,cgoulet@usgs.gov
The most promising way to improve Probabilistic Seismic Hazard Analysis isthrough the separation of epistemic and aleatory uncertainties. For example,
wave propagation path effects between a source location and a site should beconsidered as repeatable, with their possible ranges constituting epistemic
uncertainty. However, path effects represented by Ground Motion Models(GMMs) often include unmodeled source effects, such as radiation pattern and directivity, which may lead to bias in seismic hazard assessment.
Moreover, the path effects from one event to one site are assigned to a single
path between one point and a site, regardless of the magnitude and extent
of the rupture. For a large magnitude earthquake, seismic waves can travelfrom any point along the rupture plane that extends hundreds of kilometers.
Hence the single travel path assumption for large magnitude earthquakes ispotentially flawed.
The purpose of this study is to use ground motion simulations to investigate how source and path effects for large magnitude events can be represented in non-ergodic GMMs. We simulate earthquakes occurring on a fault
plane with a large range of magnitudes, and sites covering a large range of rupture distances and azimuths. We first develop a non-ergodic GMM, in whichradiation pattern and directivity effects are modeled using existing relationships. Then, we compare the mean path effects among groups of events withdifferent magnitudes and examine any differences in dependence on distanceand azimuth using two approaches. The first approach only considers smaller
events that have the same shortest path to a site as a co-located larger event,while the second approach considers all smaller events on the larger event
fault plane regardless of source to site path length. The results indicate that itis difficult to satisfactorily approximate the path effects of larger events withwww.srl-online.org•

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that of smaller events using either approach. This finding complicates our ultimate goal of developing guidelines for how large magnitude ruptures can beadequately represented within non-ergodic GMMs.
poster 91
The Case of the Missing Frequencies: Reduction of
Artificial Spectral Deficiency in Semistochastic Broadband
Simulation
NYE, T., University of Oregon, Oregon, USA, tnye@uoregon.edu; DYBING,
S., University of Oregon, Oregon, USA, sdybing@uoregon.edu; MELGAR, D.,
University of Oregon, Oregon, USA, dmelgarm@uoregon.edu; SAHAKIAN,
V. J., University of Oregon, Oregon, USA, vjs@uoregon.edu
Semistochastic broadband simulation is a common method used to efficiently
generate realistic full spectrum waveforms. For such methods, deterministic
low frequency (e.g., < 1 Hz) waveforms are combined with stochastic highfrequency (e.g., > 1 Hz) waveforms using a matched filter, which involves lowpass filtering the low frequency data, highpass filtering the high frequency
data, and summing the filtered time-series. Oftentimes, a common filter corner frequency (fcc) of 1 Hz is used for both the lowpass and highpass filters.
However, this induces an artificial deficiency in the broadband spectra, which
can have considerable effects on the resulting ground motion and seismic
hazard assessments, especially in the field of earthquake engineering where
the frequencies of ground motion hold significance. We investigate this phenomenon for Japan, Chile, and the Cascadia subduction zones, and explore
various approaches to minimize the spectral deficiency, including varying thefcc, varying the filter order, and using a two-corner frequency approach. We
find that each approach, to some extent, reduces the deficiency and influences
the ground motion (PGD, PGA, PGV, and SA). However, no single approach
universally improves all ground motion intensity measures for events of varying magnitude. We suggest addressing this matter on a case-by-case basis.
poster 92
3D Ground Motion Simulations of the 1755 Lisbon
Earthquake
PATEL, A., San Diego State University, California, USA, apatel7716@sdsu.
edu; OLSEN, K., San Diego State University, California, USA, kbolsen@sdsu.
edu; YEH, T., San Diego State University, California, USA, tyyeh316@gmail.
com; CUSTÓDIO, S., University of Lisbon, Lisbon, Portugal, susanacustodio@
campus.ul.pt
A recurrence of the 1755 Lisbon earthquake would be devastating for presentday Portugal. However, despite widespread research into the possible sources
for the event, the associated fault(s) and magnitude of the earthquake arestill uncertain. Previous simulation studies have used velocity models withrelatively coarse resolution (Grandin et al., 2007) or stochastic modeling techniques that exclude potentially important wave propagation effects (Carvalho
et al., 2004; Carvalho, Zonno, et al., 2008). Here, we use 3D physics-based
simulation in the recent PRISM3D reference model for Iberia (Arroucau etal., 2021), that we validate against data from a 2018 M4.3 earthquake near
Lisbon. We obtain an optimal fit to the 0-1 Hz strong motion recordings ofthe validation event using a geotechnical layer with a tapering depth of 350 m,
a statistical distribution of small-scale heterogeneities with a standard deviation of 5 percent, and anelastic attenuation for S-waves using Qs = 0.1Vs (Vsin m/s). We then use the validated model to simulate 0-1 Hz wave propagation for 40+ plausible earthquake scenarios across proposed fault structures. Most of the single fault sources tested for the 1755 Lisbon earthquake
inadequately replicate the observed Modified Mercalli Intensity (MMI) pattern from the event, while other scenarios violate reported tsunami arrivals
or ground motion durations. However, we find that a Mw8.3 scenario eventon the Guadalquivir Bank Fault generates MMI patterns most comparable to
the reports. Moreover, the combined wavefield from a Mw8.4 event on the
Marques de Pombal Fault with that of a (possibly triggered) Mw7.75 earthquake on the Tagus Abyssal Plain fault yields a satisfactory fit to the isoseismal
data from the 1755 earthquake.
poster 93
Extended Finite-Fault Ground Motion Modeling
Framework: Sensitivity Analysis of Number of Sub-Faults
SINGH, O., Indian Institute of Technology Gandhinagar, Gandhinagar, India,
omkar.singh@iitgn.ac.in
Ground motion stochastic simulations are essential for various engineering applications, specifically in seismic hazard assessment and calibration ofground motion models (GMMs). Such simulations are often employed for the
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simulations are often affected by various seismological parameters of source,
path and site. Thus, the present study optimizes the seismological parameters stress drop (source) and kappa (site) and performs sensitivity analysisof the number of sub-faults. For the calibration of parameters and sensitivity
analysis, a subset of the NGA West2 database (particularly for the California
region) is employed. We utilized a total of 600 events and 4,615 records for
Moment magnitude (Mw) > 3 and Joyner Boore distance (RJB) < 100 km. The
optimal value of stress drop and kappa was determined using grid search procedure. Our observations indicate that as the number of sub-faults within simulations increases, the optimized stress drop value tends to decrease. Further,increasing the number of sub-faults was found to have a negligible effect on
the residuals (i.e. log(PSAobs/PSAsim)), only adding to the computationalburden and complexity. Thus, our study suggests use of one sub-fault forsimilar simulations. We also performed comparison with NGA-West2 GMMs
(Abrahamson et al., 2014; Boore et al., 2014; Campbell and Bozorgnia, 2014;
Chiou and Youngs, 2014; Idriss, 2014) and found consistent results with the
GMSS2.0 simulations for different numbers of sub-faults. Thus our findings
provide valuable insights to improve the GMMs by optimizing stress drop,
kappa and reducing the computational resource and time.

Planetary Seismology
Oral Session • Wednesday 1 May • 4:30 pm PacificConveners: Isabella Seppi, University of Alaska Fairbanks(irseppi@alaska.edu); Yuan Tian, University of Alaska
Fairbanks (ytian4@alaska.edu).
Near Surface Excitation of the Martian Ground as
Measured by Insight
POU, L., Jet Propulsion Laboratory, California Institute of Technology,
California, USA, sophal.l.pou@jpl.nasa.gov; PANNING, M. P., Jet
Propulsion Laboratory, California Institute of Technology, California, USA,
mark.p.panning@jpl.nasa.gov; KEDAR, S., Jet Propulsion Laboratory,
California Institute of Technology, California, USA, sharon.kedar@jpl.nasa.
gov; STAHLER, S. C., ETH Zurich, Zurich, Switzerland, simon.staehler@
erdw.ethz.ch; DAHMEN, N. J., ETH Zurich, Zurich, Switzerland, nikolaj.
dahmen@erdw.ethz.ch; SCHMERR, N. C., University of Maryland, Maryland,
USA, nschmerr@umd.edu; SCHMELZBACH, C., ETH Zurich, Zurich,
Switzerland, cedric.schmelzbach@erdw.ethz.ch; BANFIELD, D. J., Cornell
University, New York, USA, banfield@astro.cornell.edu; MURDOCH, N.,
Université de Toulouse, Toulouse, France, naomi.murdoch@isae-supaero.fr;
STOTT, A., Université de Toulouse, Toulouse, France, alexander.stott@isaesupaero.fr; LORENZ, R. D., John Hopkins University, Maryland, USA, Ralph.
Lorenz@jhuapl.edu; LOGNONNÉ, P., Université Paris Cité, Paris, France,lognonne@ipgp.fr; BANERDT, W. B., Jet Propulsion Laboratory, California
Institute of Technology, California, USA, william.b.banerdt@jpl.nasa.gov
The InSight mission landed on Mars in November 2018 and deployed for the
first time a seismometer, the SEIS instrument, on its surface. For more than
two Martian years it recorded several thousands of marsquakes and other seismic events, allowing us to study diurnal and seasonal variations in seismicity
to better understand the local atmospheric conditions and characterize theMartian interior. Among the many signals recorded by SEIS is a prominentmode around 2.4 Hz. Possible explanations for this signal include a specific lander mode due to the solar arrays, or a local ground substructure as
described notably in Hobiger et al. 2020.
In this study, we test the hypothesis of Hobiger et al. 2020 that the 2.4
Hz dominant background noise and Horizontal to Vertical (H/V) ratio arecaused by a seismic low velocity zone between 30m and 75m by simulating
the amplitude of the 2.4Hz peak observed during marsquakes and during thequiet Martian night. We generate Green’s functions of the ground substructure
for high-incidence-angle teleseismic events and for regional surface sources.
Subsequently we test the ground response to these excitations by convolving
the simulated sources with the appropriate Green’s functions.
We simulate a teleseismic marsquake at a given distance by superimposing a distance-dependent attenuated random signal that mimics the observed
scatter of the Martian crust. Background noise is simulated by generating asignal with the frequency and amplitude characteristics of the InSight day andnight pressure data.
We show that the simulated amplitudes of the 2.4Hz signal during teleseismic quakes are consistent with SEIS observations. Furthermore, also consistent with InSight observations, the background noise simulation is visible
during the night, but is drowned by the elevated ambient environmental noise
during daytime.

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To test the link between the numerous 2.4 Hz events and excitation of
the lander’s solar array from wind bursts, a coupled model of the excitation of
the InSight Lander and the subsurface structure will be needed.

ch; KAWAMURA, T., Institut de Physique du Globe de Paris, Paris, France,
kawamura@ipgp.fr; CHARALAMBOUS, C., Imperial College, London,
United Kingdom, constantinos.charalambous@imperial.ac.uk; GIARDINI,
D., ETH Zurich, Zurich, Switzerland, domenico.giardini@erdw.ethz.ch

Evaluation of Lunar Seismicity Parameters Based on
Analysis of Newly Discovered Shallow Moonquakes in the
Apollo Seismic Data
ONODERA, K., University of Tokyo, Bunkyo-ku, Japan, onodera@eri.utokyo.ac.jp

NASA’s InSight seismometer operated on Mars from 12.2018 - 12.2022. Since
the mission is complete, the Marsquake Service (MQS) is preparing a finalreference catalogue encompassing seismicity recorded across the entire mission. The analysis of marsquake is challenging, given the availability of onlya single station, low magnitudes events with large epicentral distances, andstrongly varying background noise. These factors collectively result in low
event signal-to-noise ratios (SNR). Our reference catalogue heavily leverages
a deep learning denoising approach to mitigate the noise contamination. We
show that denoising performs comparably to fine-tuned bandpass filtering athigh SNRs, and clearly outperforms it at low SNRs, with respect to accurate
waveform and amplitude retrieval, as well as onset picking.
We produce a denoised waveform data set for all >1300 events in the
MQS v14 catalogue. For the HF event family, we apply automated phase picking for the first time. For the LF family, consisting of around 100 events, we
review each event, improving the event characterisation and location by new
or updated phase picks and polarisation.
We find many new features that were missing in earlier catalogues. We
find aftershocks and demonstrate that several complicated LF event waveforms can be explained by marsquake doublets—two similar strong quakes
from similar locations that produce overlapping waveforms—that locate
in Cerberus Fossae. In addition, we show that the unusual sequence on Sol
1157 consists of numerous marsquakes which are among the strongest events
located at epicentral distances beyond Cerberus Fossae.

From 1969 to 1977, the first lunar seismic observation was carried out during
the Apollo missions, bringing us about 13,000 seismic events and opening thepath to studying lunar seismicity and its internal structure. The lunar seismic
events are roughly classified into four groups: deep moonquakes, meteoroid
impact events, shallow moonquakes, and thermal moonquakes. Among them,shallow moonquakes are the rarest events on the Moon. While thousands ofevents have been identified for deep moonquakes, meteoroid impacts, andthermal moonquakes, only 28 shallow moonquakes were detected before(e.g., Nakamura et al., 1981). Despite their small population, shallow moonquakes show much larger energy release than any other lunar seismic events(e.g., Goins et al., 1981). Therefore, they are important for understanding theseismicity of the Moon. Recently, Onodera (2023) discovered 46 new shallow
moonquakes, allowing us to renew the lunar seismicity parameters (such as
the magnitude of completeness, seismicity rate, and b-value).
In the presentation, followed by the characterization of the newly discovered shallow moonquakes, I will show the estimated seismicity parameters
for the Apollo 14, 15, and 16 landing sites and discuss the regionality of seismic activity on the Moon.
A Novel Statistical Technique to Distinguish Lunar Impacts
From Shallow Moonquakes
TURNER, A. R., University of Texas at Austin, Texas, USA, alice.turner@jsg.
utexas.edu; GULICK, S. P. S., University of Texas at Austin, Texas, USA, sean@ig.utexas.edu; TRUGMAN, D. T., Nevada Seismological Laboratory, Nevada,USA, dtrugman@unr.edu; CIVILINI, F., NASA Goddard Space Flight Center,
Maryland, USA, francesco.civilini@nasa.gov; ONODERA, K., Institut dePhysique du Globe Paris, Paris, France, onodera@ipgp.fr
Between 1967 and 1977, The Apollo seismic network recorded thousands ofsignals, such as impacts and shallow moonquakes (Nakamura et al., 1981).
Correctly classifying seismic signals is crucial for assessing lunar impact andseismicity rates. However, 60% of the original events remain unclassified due
to low-quality data and the time required to analyse the data. We introduce
a semi-automated and objective method for discriminating shallow moonquakes from impacts. First, we convert short- and long-period spectrograms
to smoothed probability density functions. Then, we calculate the K-L divergence for pairs of events. The K-L divergence is a nonparametric measure of
the differences between the two probability distributions; a K-L divergence of
0 indicates an identical pair of signals. We test this new statistical method onclassified events in the catalogue. Preliminary results show a K-L divergenceof > 1 between previously identified shallow moonquakes and impacts but
a divergence of < 0.5 between pairs of shallow moonquakes; shallow moonquakes are more similar to each other than to impacts. Thus, the K-L divergencecan discriminate between shallow moonquakes and impacts. Additionally, we
analyse the short period time series of the seismic signals recorded at station
S15 using the Python package tsfresh, which automatically calculates over1200 time-series features. We again test this method on classified events inthe catalogue. Spectral features, such as Fourier entropy and autocorrelation,vary systematically between shallow moonquakes and impacts. A recent study(​​Onodera et al., 2023) identified ~40 new shallow moonquakes, and we apply
the same tsfresh algorithm to these newly identified events. The newly identified moonquakes have autocorrelation and Fourier entropy values similar tothe previously catalogued moonquakes. Along with supporting reanalysis of
the Apollo seismic signals, we suggest these methods to distinguish the lunar
seismic signals could apply to future lunar seismic data.
A Reference Marsquake Catalogue
CLINTON, J., ETH Zurich, Ottikon, Switzerland, jclinton@sed.ethz.ch;
CEYLAN, S., ETH Zurich, Zurich, Switzerland, savas.ceylan@erdw.ethz.
ch; DAHMEN, N. J., ETH Zurich, Zurich, Switzerland, nikolaj.dahmen@
erdw.ethz.ch; STAEHLER, S., ETH Zurich, Zurich, Switzerland, simon.
staehler@erdw.ethz.ch; HORLESTON, A., University of Bristol, Bristol,
United Kingdom, Anna.Horleston@bristol.ac.uk; DURAN, C., ETH Zurich,
Zurich, Switzerland, cecilia.duran@erdw.ethz.ch; KIM, D., Imperial College,
London, United Kingdom, doyeon.kim@imperial.ac.uk; ZENHAEUSERN,
G., ETH Zurich, Zurich, Switzerland, geraldine.zenhaeusern@erdw.ethz.

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Regional-Scale Hazard, Risk and Loss Assessments
Oral Session • Thursday 2 May • 4:30 pm PacificConveners: Ashly Cabas, North Carolina State University(amcabasm@ncsu.edu); John Cassidy, Geological Survey ofCanada (john.cassidy@nrcan-rncan.gc.ca); Rodrigo Costa,
University of Waterloo (rodrigo.costa@uwaterloo.ca); Cassie
Gann-Phillips, North Carolina State University (cvgann@ncsu.edu); Mike Greenfield, Greenfield Geotechnical (mike@greenfieldgeotechnical.com); Tiegan E. Hobbs, Geological
Survey of Canada (thobbs@eoas.ubc.ca); James Kaklamanos,
Merrimack College (kaklamanosj@merrimack.edu); Albert
Kottke, Pacific Gas and Electric Company, (albert.kottke@
pge.com); Sabine Loos, University of Michigan (sloos@umich.edu); Cristina Lorenzo-Velazquez, North Carolina
State University (clorenz@ncsu.edu); Andrew Makdisi, U.S.
Geological Survey (amakdisi@usgs.gov); Hong-Kie Thio,
AECOM (hong.kie.thio@aecom.com); Eric Thompson, U.S.
Geological Survey (emthompson@usgs.gov); David Wald,
U.S. Geological Survey (wald@usgs.gov); Erin Wirth, U.S.
Geological Survey, (emoriarty@usgs.gov)
Probabilistic Approach for Site Response Analysis andSeismic Microzonation
ANSAL, A., Ozyegin University, ISTANBUL, Turkey, atilla.ansal@ozyegin.
edu.tr
The purpose of site response analysis is to estimate probable earthquake characteristics on the ground surface to mitigate earthquake damage for the newbuildings as well as for the existing building stock. The uncertainties in source
characteristics, soil profile, soil properties, and characteristics of the building inventory would introduce critical uncertainties associated with theseanalyses. At this stage, the probability distribution of the related earthquake
parameters on the ground surface may be determined considering all possible input acceleration time histories, site profiles, and dynamic soil properties. One option, the variability in earthquake source and path effects may beconsidered using a large number of acceleration records compatible with thesite-dependent earthquake hazard. Likewise, a large number of soil profiles

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may be used to account for the site condition variability. A seismic microzonation methodology is proposed based on the probabilistic assessment of thesefactors involved in site response analysis. The second important issue in theseismic microzonation procedure is the selection of microzonation parameters. The purpose is mitigation of structural damage, it is possible to adopt
earthquake parameters like cumulative average velocity (CAV) or Housnerintensity (HI) that was observed to have a better correlation with building
damage during past earthquakes. The main approach is to develop a microzonation procedure for ground shaking intensity considering probabilistic
values of ground motion parameters.
Analysis of Shakemap Residuals for Spatially Variable Site
Terms
CUNNINGHAM, A. E., U.S. Geological Survey, Colorado, USA,acunningham@usgs.gov; KNODEL, E. J., U.S. Geological Survey, Colorado,
USA, eknodel@usgs.gov; HEARNE, M. G., U.S. Geological Survey, Colorado,
USA, mhearne@usgs.gov; THOMPSON, E. M., U.S. Geological Survey,
Colorado, USA, emthompson@usgs.gov; WORDEN, C. B., U.S. Geological
Survey, Colorado, USA, cbworden@contractor.usgs.gov; WALD, D. J., U.S.
Geological Survey, Colorado, USA, wald@usgs.gov
The U.S. Geological Survey (USGS) has produced and archived ShakeMaps
for many decades as part of its earthquake monitoring efforts. The resulting
ShakeMap Atlas contains thousands of recent and historical maps whose primary purpose is for calibrating the Prompt Assessment of Global Earthquakes
for Response (PAGER) loss models. Here we develop spatially variable site
terms (SVST), which could be considered a “partially non-ergodic” groundmotion model (GMM) adjustment. Currently, ShakeMap assumes a constant spatial correlation structure across all events and regions. Given the
global extent and data quantity available from ShakeMap, we investigate thisassumption by looking for trends in the spatial correlation of model parameters with variables such as magnitude, tectonic environment, number ofavailable records for a given station, and geographic region. Adding the SVST
adjustment will incorporate repeatable variability into scenarios to capture
physical phenomena traditionally unaccounted for by GMMs that underpin
the ShakeMap interpolation method. Because real-time ShakeMaps are conditioned on recorded data for a given event, the impact of SVSTs will be lesssubstantial, especially in areas with dense network coverage. However, theseempirical factors will improve extrapolation between stations due to larger
correlation lengths of the repeatable site effects. The “Did You Feel It?” (DYFI)
system responses often have much greater spatial coverage than instrumental
data for a large percentage of earthquakes yet take time to become available.
In contrast, the SVSTs that we derive here will be available for the first versionof ShakeMap. Further, DYFI responses can exhibit areas of missing data inwhich the most highly-damaged area is not covered because residents in theseregions may be more concerned with safety than providing DYFI responses,
and/or internet connectivity could be lost. These innovative SVST factors
would be able to help fill in such regions.
Regionalized Earthquake Source Models of Subduction
Interface Earthquakes
SKARLATOUDIS, A., AECOM, California, USA, andreas.skarlatoudis@
aecom.com; THIO, H. K., AECOM, California, USA, hong.kie.thio@aecom.
com; SOMERVILLE, P., AECOM, California, USA, paul.somerville@aecom.
com; AHDI, S. K., AECOM, California, USA, sean.ahdi@aecom.com;
CONDON, S., Scott.Condon, California, USA, scott@scondon.com
In Skarlatoudis et al. (2016; Sea16) we developed a set of global scaling relations between seismic moment (M0) and physical source properties such as
earthquake rupture area (S), total asperity area (Sa), slip (D), and fault width(W), for large subduction interface events. That set of relations reduced thealeatory variability in the prediction of these source parameters. Since their
publication, they have been used to predict ground motions and tsunamis from great subduction earthquakes for various applications (e.g. USGS
NSHM).
Since the development of the database used in Sea16, 79 additional
subduction interface events with published finite-fault solutions have beencatalogued in the USGS Finite Fault database, the Online Database of Finite
Fault Rupture Models (SRCMOD), and the Next-Generation Attenuation
Subduction (NGA-Sub) database, nearly tripling the available data. In our
search for subduction interface events, we use the Slab2.0 subduction-zone
geometries. These additional models are used to update the Sea16 set of scaling relations, further improving the predictions of various source properties
and more accurately quantifying uncertainties.
We augmented the Sea16 database with the additional models that
became available in recent years, and developed an updated set of global scal-

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ing relations. Further, for the subduction zones with an adequate number ofearthquakes in our database, we examined regionalized versions of the scaling
relations and provide possible explanations for the observed regional differences in subduction interface ground motions by seeking correlations withthe many parameters (e.g. trench-normal velocity, thrust dip angle, subduction partitioning) that were considered by other researchers.
The NGA-Sub project also quantified strong regional differences in
the ground motions expected from various subduction zones. The observed
regionalization of ground motions is likely the result of differences in the geological, geometrical, and mechanical properties of plate-boundary interfaces
and the kinematic and dynamic processes of megathrust rupture generationin each region.
Region-Specific Geospatial Liquefaction Model for Alaska
by Bayesian Model Updating of the Global Liquefaction
Model
SHIRZADI, H., Tufts University, Massachusetts, USA, hooman.shirzadi@
tufts.edu; ASADI, A., Tufts University, Massachusetts, USA, adel.asadi@tufts.
edu; BAISE, L. G., Tufts University, Massachusetts, USA, laurie.baise@tufts.
edu; MOAVENI, B., Tufts University, Massachusetts, USA, babak.moaveni@
tufts.edu
Global geospatial liquefaction models are currently being used to predict theprobability of liquefaction occurring after an earthquake. However, these models are limited in their ability to generalize to new regions because they are only
trained on data from previous events using a global dataset. Additionally, thegeology, saturation, and seismic activity of different regions can vary greatly,
making it desirable to develop specific liquefaction models for each region.
A recent example is the Mw 7.1 Anchorage, Alaska earthquake that occurredon November 30, 2018. This earthquake caused widespread liquefaction innatural fluvial-estuarine environments and damaged and tilted residentialbuildings in southern Anchorage. In this study, a regional geospatial liquefaction prediction model is developed for Alaska using liquefaction observations
from the 2018 Anchorage earthquake. For this purpose, a Bayesian logistic
regression model was trained to combine the knowledge from the existing
global model and the region-specific relations between geospatial explanatory
variables for the Anchorage region. This can be done by selecting the priordistribution of the model coefficients from the global model and then sequentially updating the model for each liquefaction observation from the region tofind the posterior probability distribution of the model parameters. To createa balance between the information gained from the global model and regionaldata, prior and likelihood functions are weighted to create an optimal liquefaction prediction model. The resulting model shows a more accurate liquefaction detection in the Alaska region.
A Regional Earthquake-Triggered Landslide Susceptibility
Map of the Cook Inlet Region, Southcentral Alaska
ELLISON, S. M., U.S. Geological Survey, Colorado, USA, sellison@usgs.
gov; ALLSTADT, K. E., U.S. Geological Survey, Colorado, USA, kallstadt@
usgs.gov; THOMPSON, E. M., U.S. Geological Survey, Colorado, USA,emthompson@usgs.gov; MARTINEZ, S. N., U.S. Geological Survey,
Colorado, USA, snmartinez@usgs.gov
Cook Inlet spans southcentral Alaska from the Gulf of Alaska to theAnchorage and Matanuska-Susitna boroughs, and the surrounding watershedholds the state’s largest population. Cook Inlet is also a forearc basin of the
Aleutian Trench, one of the most seismically active subduction zones globally. Surficial geologic units in the region include many loosely consolidated
glacial sediments. The region has experienced devastating landslides, especially those triggered by the 1964 Great Alaska earthquake. These factors, inaddition to the availability of detailed regional geologic maps, elevation models, and regional earthquake-triggered ground failure inventories, make the
Cook Inlet region an important location for landslide susceptibility mapping.
Motivated by the need to improve the global U.S. Geological Survey (USGS)
near-real-time ground failure product with higher-quality regional information, we developed an earthquake-triggered landslide susceptibility map for
the Cook Inlet region. We adapted methods originally proposed by Wilson
and Keefer (1985) which combine slope and rock strength to assign classesof relative landslide susceptibility. The resulting relative landslide susceptibility classes range from 0 to 10, with a general trend of shallower slopes andstronger rocks showing less susceptibility, and steeper slopes and weakerrocks being more susceptible. We use this map as the input for two modeling approaches: 1) the HAZUS methodology and 2) a qualitatively updated
version of the global model used by the USGS landslide near-real-time product. We compare these results to two newly available detailed inventories ofearthquake-triggered ground failure from two large earthquakes in the region:

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the 1964 Great Alaska Earthquake and the 2018 Anchorage Earthquake. We
note that even though we use the susceptibility map with earthquake triggers,
the map is also useful for landslide hazards in general and uses a susceptibility
classification method common to other regional maps.
Development of a Physics-Guided Non-Ergodic Ground
Motion Model for the Groningen, Netherlands Region
LAVRENTIADIS, G., California Institute of Technology, California,
USA, glavrent@caltech.edu; ORAL, E., California Institute of Technology,
California, USA, elifo@caltech.edu; ADAY, K., California Institute ofTechnology, California, USA, kaday@caltech.edu; ASIMAKI, D., California
Institute of Technology, California, USA, domniki@caltech.edu
We present the development of a non-ergodic ground motion model (GMM)
for the Groningen natural gas field in the Netherlands. Non-ergodic GMMs
are a promising development in probabilistic seismic hazard analysis as they
offer the potential to reduce the aleatory variability that controls the seismic
hazard, especially in larger return periods. This reduction in aleatory variability is accompanied by epistemic uncertainty in regions with sparse observation or a systematic shift in the median ground motion in regions with dense
recordings. In order to further reduce the range of epistemic uncertainties,
a series of 3D wave propagation simulations on a 3D velocity model for
Groningen were performed, illuminating seismic wave propagation paths not
represented in the empirical datasets. These simulations are currently limited
to a maximum frequency of 5 Hz with plans to extend them to 10 Hz. The
non-ergodic model is formulated as a Gaussian Process where the systematic source and site effects are expressed as spatially varying coefficients that
depend on the event and site coordinates. A physics-informed kernel function
is developed to describe the systematic path effects that takes into accountthe correlation between entire rays. Assimilating large sets of empirical andsimulated data necessitated the development of efficient sparse approximations and the use of high-performance computing. Using the Sparse Cholesky
Factorization following the procedure described by Schafer et al. (2021), wewere able to reduce the memory and computational complexity from O(N2)and O(N3) to O(N log(N)d) and O(N log(N)2d), respectively. While the use of
the open-source coding language Julia, which is optimized for parallel computing scalability, allowed us to take advantage of the additional resources in
HPC environments for the GP regression.
Developing a Data-centric Workflow for Seismic Source
Model Construction and Testing
STYRON, R. H., Global Earthquake Model Foundation, Oregon, USA,richard.styron@globalquakemodel.org; PAGANI, M., Global Earthquake
Model Foundation, Pavia, Italy, marco.pagani@globalquakemodel.org;
JOHNSON, K. E., Global Earthquake Model Foundation, Pavia, Italy, kendra.
johnson@globalquakemodel.org; BAYLISS, K., Global Earthquake Model
Foundation, Pavia, Italy, kirsty.bayliss@globalquakemodel.org
Constructing and calibrating seismic source models for Probabilistic Seismic
Hazard Assessment involves integrating disparate datasets into a cohesivewhole, amidst substantial incompleteness and uncertainty in most observations. To build seismic source models repeatably, efficiently and with a maximal amount of data, the Global Earthquake Model Foundation has developed
an evolving workflow based on open-source tools for modeling crustal fault
networks, subduction zones, and distributed seismicity.
Initial fault network characterization is conducted using Oiler, a tectonic block modeling code. Oiler inverts geodetic velocity and geologic slip
rate data to estimate fault slip rates and partial coupling at subduction zones.
Subfault to multifault ruptures in the fault network are generated using Fermi
through graph-theoretic methods, with occurrence rates calculated from fault
slip rates and magnitude-frequency distribution (MFD) constraints througha choice of solvers. Shallow off-fault seismicity is modelled by zonal gridded
point sources with occurrence rates smoothed according to past seismicity.
Subduction zone interfaces and slab sources are modeled separately. Theinterface is represented by a nonplanar fault surface, accommodating floating
ruptures conforming to the MFD derived from the seismic catalog and tectonic convergence rate. The subducted slab is modeled through gridded finite
ruptures. Model components derived from instrumental seismicity rely on ahomogenized seismic catalog classified to the main tectonic domains by event
proximity to surfaces delineating the domains. The model’s fidelity to seismicity data is evaluated using Hamlet (Hazard Model Evaluation and Testing),
which conducts sanity checks and statistical analyses, comparing simulated
seismic catalogs to observed data for the whole model domain, or spatial subdomains, individual logic tree branches, or source typologies. Hamlet can also
address the goodness of fit of each epistemic uncertainty hypothesis expressed

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via the source model logic tree. We present use cases of these tools in models
of different sizes and regions.
Developing Software to Assess the Seismic Risk of Natural
Gas Infrastructure: OpenSRAZHENG, B., Slate Geotechnical Consultants, California, USA, bzheng@slategeotech.com; LARGENT, M., Slate Geotechnical Consultants,
California, USA, mlargent@slategeotech.com; WATSON-LAMPREY, J., Slate
Geotechnical Consultants, California, USA, jwatsonlamprey@slategeotech.
com; BRAY, J., University of California, Berkeley, California, USA, jonbray@berkeley.edu; ABRAHAMSON, N. A., University of California, Berkeley,
California, USA, abrahamson@berkeley.edu; GAVRILOVIC, S., SimCenter,
UC Berkeley, California, USA, gavrilovic@berkeley.edu; RUTQVIST, J.,
Lawrence Berkeley National Laboratory, California, USA, jrutqvist@lbl.gov;
HUTCHINSON, T., University of California, San Diego, California, USA,
tahutchinson@eng.ucsd.edu; MCCALLEN, D., University of Nevada, Reno,
Nevada, USA, dbmccallen@lbl.gov; SOGA, K., University of California,
Berkeley, California, USA, soga@berkeley.edu; THOMPSON, S., LCI,
California, USA, thompson@lettisci.com; O’ROURKE, T., Cornell University,
New York, USA, tdo1@cornell.edu; BAIN, C., GEI Consultants, California,
USA, cbain12@gmail.com; HUTABARAT, D., University of California,
Berkeley, California, USA, dhutabarat@berkeley.edu; PANTOLI, E., WTW,
Colorado, USA, elide.pantoli@gmail.com; ELFASS, S., University of Nevada,Reno, Nevada, USA, elfass@unr.edu; LINDVALL, S., LCI, California, USA,lindvall@lettisci.com; SASAKI, T., Lawrence Berkeley National Laboratory,
California, USA, tsubasasasaki@lbl.gov; ZHANG, Y., Lawrence Berkeley
National Laboratory, California, USA, yqzhang@lbl.gov; LUU, K., Lawrence
Berkeley National Laboratory, California, USA, keurfonluu@lbl.gov;
JORDAN, P., Lawrence Berkeley National Laboratory, California, USA,
pdjordan@lbl.gov; FOXALL, B., Lawrence Berkeley National Laboratory,
California, USA, bfoxall@lbl.gov; HUBBARD, P., University of California,
Berkeley, California, USA, phubbard@berkeley.edu; WANG, J., University ofCalifornia, Berkeley, California, USA, james.ccw@berkeley.edu
Owners and regulators require performance-based earthquake engineering(PBEE) assessment procedures to proactively and cost-effectively make riskinformed decisions regarding the seismic performance of their infrastructure.
An efficient PBEE tool is required to assess the potential performance of theirsystem during an earthquake, to identify components that are most vulnerable, and to mitigate components that have the highest risk. This presentation
will provide an overview of the 1) research performed on seismic demandand capacity models, laboratory testing, and finite element modeling, and 2)
implemented findings from the research into a new open-source seismic risk
analysis program called OpenSRA.
The overview of OpenSRA will include details on the easy-to-use graphical user interface, the state-of-the-art models addressing different seismic
demands (e.g., ground shaking, fault rupture, liquefaction, and landslide), andthe new fragility models for buried pipelines, wells, caprocks, and surficial
elements. The graphical user interface provides a fully interactive map canvas
for visualization of the inputs (e.g., infrastructure, ground motions, GIS data)and outputs (probability of failure) over different basemaps of California. The
software allows end-users to select the analysis models according to the resolution of the available data (i.e., statewide, regional, or site-specific) and adjust
uncertainties in the model parameters to study the risk. Finally, OpenSRA
implements an efficient algorithm called polynomial chaos expansion for risk
analysis that can be orders of magnitude faster than traditional analysis (i.e.
Monte Carlo sampling). Overall, OpenSRA provides the industry an efficient
program to understand the seismic risk of natural gas infrastructure and an
environment easily adaptable to other types of infrastructure and natural
hazards.
Addressing Challenges in Regional Seismic Risk
Assessments in British Columbia: M9 Cascadia Subduction
Zone Earthquakes, Deep Sedimentary Basin Amplification
and Non-Ductile Reinforced Concrete Shear Wall Buildings
MOLINA HUTT, C., University of British Columbia, Vancouver, Canada,
carlos.molinahutt@civil.ubc.ca; KAKOTY, P., University of British Columbia,
Vancouver, Canada, preetish.kakoty@ubc.ca
This presentation aims to address some of the challenges associated with conducting regional seismic risk assessments in Southwest British Columbia: (1)the lack of ground motion recordings of M9 Cascadia Subduction Zone (CSZ)
earthquakes; (2) the presence of the Georgia sedimentary basin, which canamplify ground motion shaking, particularly in the medium-to-long period
range, and is not accounted for in current building codes; and (3) the large
concentration of tall nonductile reinforced concrete shear wall (RCSW) build-www.srl-online.org•

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ings constructed prior to the 1980s, which are of special concern because they
predate modern seismic codes and are clustered in densely populated areas,
raising concerns about the risks to life, property, and recovery from large
earthquakes.
Physics-based ground motion simulations of 30 plausible M9 CSZ
earthquakes, which explicitly consider basin effects, are benchmarked against
existing ground motion models to develop site-specific and period-dependentbasin amplification factors. A framework to incorporate these factors into
uniform hazard spectra (UHS) calculations, to enable the inclusion of theseeffects in the design and assessment of buildings, is proposed.
The collapse risk of older tall RCSW buildings is assessed via nonlinear response history analysis of 3D numerical models of 25 representativearchetypes generated by means of a predictive model that leverages a detailed
inventory of such buildings. Collapse risk is quantified using hazard estimatesof Canada’s national seismic hazard model, which neglects basin effects, anda “hybrid” hazard model that considers basin amplification. A scenario-based
seismic performance assessment, under the M9 CSZ earthquakes previously
introduced, to quantify economic losses and recovery times in these buildings,
is also carried out.
The results aim to inform seismic policy development in British
Columbia, in particular, ongoing efforts by the City of Vancouver to address
seismic risks in its aging building infrastructure.
Using Comparative Subductology to Constrain Future
Subduction Zone Earthquake Losses
WALD, D. J., U.S. Geological Survey, Colorado, USA, wald@usgs.gov; HAYES,
G., U.S. Geological Survey, Colorado, USA, ghayes@usgs.gov; HAYNIE, K. L.,
U.S. Geological Survey, Colorado, USA, khaynie@usgs.gov; JAISWAL, K. S.,
U.S. Geological Survey, Colorado, USA, kjaiswal@usgs.gov; MARANO, K.,
U.S. Geological Survey, Colorado, USA, kmarano@usgs.gov
On its hundredth anniversary, we recount details of the M8 September 1923
Great Kanto earthquake, the most devastating natural disaster in Japanese historical times. This event destroyed most of Yokohama and Tokyo, attributable
to the combined impacts of shaking, liquefaction, landslides, tsunami, and(primarily) fires, which resulted in over 105,000 fatalities. Although smaller
in magnitude than other great Japanese earthquakes, including the M9 2011
Tohoku earthquake, the proximity of the subducting Philippines plate interface beneath the populated Tokyo region resulted in much more damage thanother events in Japan’s seismic history. In fact, despite being well-constrainedby Slab 2.0 and regional models, interface proximity to the exposed population is often overlooked, and we emphasize this point via basic comparative
subductology—that is, by comparing subduction zone characteristics worldwide. We do so first qualitatively by visual geometric comparisons and thenquantitatively using ShakeMap and PAGER to compare shaking intensity
and losses for significant cities above subduction zones worldwide. Though
there are large uncertainties in several aspects of the hazard problem—suchas seismogenic rupture extents, radiation complexity, and basin amplification—others are relatively well-constrained, including the potential source
geometry. On the loss estimation side, there are also significant uncertainties,
such as limited building inventories and fragilities, yet we can characterize
the exposed population and overall vulnerabilities reasonably well. We showthat once shaking is well-constrained via its source geometry, PAGER models
perform well enough to infer and compare losses for future events. The central
theme of this presentation is that source geometry and population, two wellcharacterized features of the loss estimation challenge, are well-known andcritical diagnostics for future loss estimates via scenario realizations.

Regional-Scale Hazard, Risk and Loss Assessments [Poster
Session]Poster Session • Friday 3 May
Conveners: Ashly Cabas, North Carolina State University(amcabasm@ncsu.edu); John Cassidy, Geological Survey ofCanada (john.cassidy@nrcan-rncan.gc.ca); Rodrigo Costa,
University of Waterloo (rodrigo.costa@uwaterloo.ca); Cassie
Gann-Phillips, North Carolina State University (cvgann@ncsu.edu); Mike Greenfield, Greenfield Geotechnical (mike@greenfieldgeotechnical.com); Tiegan E. Hobbs, Geological
Survey of Canada (thobbs@eoas.ubc.ca); James Kaklamanos,
Merrimack College (kaklamanosj@merrimack.edu); Albert
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Kottke, Pacific Gas and Electric Company, (albert.kottke@
pge.com); Sabine Loos, University of Michigan (sloos@umich.edu); Cristina Lorenzo-Velazquez, North Carolina
State University (clorenz@ncsu.edu); Andrew Makdisi, U.S.
Geological Survey (amakdisi@usgs.gov); Hong-Kie Thio,
AECOM (hong.kie.thio@aecom.com); Eric Thompson, U.S.
Geological Survey (emthompson@usgs.gov); David Wald,
U.S. Geological Survey (wald@usgs.gov); Erin Wirth, U.S.
Geological Survey, (emoriarty@usgs.gov)
poster 156
Empirical Response of Subduction-Zone Ground Motions in
the Cook Inlet Basin of Alaska
AHDI, S. K., AECOM, California, USA, sahdi@g.ucla.edu; PARKER,
G. A., U.S. Geological Survey, California, USA, gparker@usgs.gov;
SKARLATOUDIS, A., AECOM, California, USA, andreas.skarlatoudis@
aecom.com
Soft sediments and basins amplify ground shaking from earthquakes acrossa range of periods of engineering interest, and characterization of areas withpotential strong shaking is critical for seismic design of buildings and infrastructure. Particularly important is the Cook Inlet region in Southern Alaska,
an important commercial seaway that encompasses most of the state’s population and is located near the Alaska subduction zone. The last major effort
to update ground-motion models (GMMs) in Alaska, NGA-Subduction,compiled data through 2018 but did not consider basin amplification. Since
then, multiple large (M7.2–8.2) subduction-zone interface earthquakes haveoccurred. Here, we seek to evaluate the efficacy of NGA-Sub basin-responsemodels for three well-recorded events. Although stations encompass a region
beyond the extent of basin depths (Zx, the depth to specific shear-wave velocity isosurfaces) obtained from the Cook Inlet basin model, we hypothesizethat using Zx values from specific basin models can yield improvements in
GMM performance of in-basin stations over using default VS30-based Zx
values built into the GMMs, as demonstrated in a related study for shallowcrustal earthquakes recorded in western U.S. basins.
Our goal is to determine whether using newly published estimates of(1) VS30 (the time-averaged shear-wave velocity in the upper 30 m) based on
P-wave receiver functions, and (2) sedimentary basin depth (parameterized asZx) improve GMM performance in southern Alaska. We compute two sets ofground-motion residuals, using either the default or new site and basin inputs,
correct them for nonlinear site response from strong shaking intensities, andperform mixed-effects regressions to account for event- and station-specificeffects. We then evaluate GMM performance by comparing the scaling ofresiduals with VS30 and Zx against the published scaling models and comparing the statistical moments of the two sets of residuals. This work can improve
estimates of regional seismic hazard analyses, including future updates to the
U.S. Geological Survey’s National Seismic Hazard Model in Alaska.
poster 157
Physics-based Seismic Hazard Assessment Using Multi-cycle
Earthquake Simulations: Influence of Segment
Connectivity and Strength Distribution
ASPIOTIS, T., King Abdullah University of Science and Technology,
Jeddah, Saudi Arabia, theodoros.aspiotis@kaust.edu.sa; ZIELKE, O., King
Abdullah University of Science and Technology, Jeddah, Saudi Arabia, olaf.
zielke@kaust.edu.sa; MAI, M. P., King Abdullah University of Science andTechnology, Jeddah, Saudi Arabia, martin.mai@kaust.edu.sa
During the past decades, numerous seismic hazard assessment (SHA) studies have been conducted to help mitigate earthquake-related casualties andeconomic losses. However, the short instrumental period of recorded earthquakes poses a challenge to accurately estimate the recurrence rates of potentially hazardous earthquakes. Hence, a rigorous SHA should not rely solely
on past seismic events or on deterministic extreme scenarios. Instead, novel
approaches such as numerical multi-cycle rupture simulations producing synthetic seismic catalogs can be used to enhance the reliability of the SHA.
The mega-project of NEOM, located within the seismic active region of
the gulf of Aqaba (GoA), the southern extension of the Dead Sea fault zone,
has attracted increased scientific attention due to the region’s susceptibility to large-magnitude earthquakes (e.g., 1995 M7.3 Nuweiba earthquake).
Therefore, we conduct physics-based simulations using a multi-cycle engine(MCQsim) to create long-term synthetic seismic catalogs. We model different

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seismic-source realizations varying the spatial gaps among the strike-slip segments as well as the strength distribution throughout the complex fault systemof the GoA. The resulting synthetic catalogs provide a possible pathway toquantify epistemic uncertainties that arise from poorly constrained parameter
space (e.g., fault geometry and frictional strength). By analyzing MCQsim
catalogs spanning tens-of-thousands of years, we infer the recurrence rates
and complex patterns of multi-segment ruptures. Furthermore, we establish a
workflow to incorporate these rupture scenarios into the probabilistic seismic
hazard assessment framework of OpenQuake to compute exceedance probabilities of different ground-motion intensity measures. Our findings indicatethat both spatial fault continuity and strength distribution affect the resulting
long-term multi-cycle catalogs and hence have a measurable impact on peakground accelerations and uniform hazard spectra.
poster 158
Seismic Hazard Assessments for the Jackson Purchase
Region (Upper Mississippi Embayment) Using Reelfoot
Fault Scenarios and Site-Specific Vs Profiles
CARPENTER, S., University of Kentucky, Kentucky, USA, seth.carpenter@uky.edu; WANG, Z., University of Kentucky, Kentucky, USA, zmwang@uky.
edu
The New Madrid Seismic Zone (NMSZ) produced at least three magnitude 7.0
or greater earthquakes in the winter of 1811-1812. This Zone, which can affectseveral population centers in the central U.S., underlies the Upper Mississippi
Embayment, a southward-plunging, broad basin containing up to a kilometerof unlithified sediments. Seismic hazards in the region are therefore affectedby both the large, active faults and strong site effects. Because large NMSZ
earthquakes have not occurred in the instrumental period, and their recurrence probabilities are difficult to estimate, scenario-based hazard assessment provides an appropriate tool to estimate ground-motion hazards for theregion. In addition, numerous studies have indicated the inadequacy of theubiquitous Vs30 parameter to account for site effects in the Embayment andthat site-specific Vs profiles are needed to reliably estimate seismic hazard inthis region.
Here, we simulated time-histories across the Jackson Purchase Region(JPR; the Kentucky part of the Embayment) for moment magnitude (M)6.8, M 7.2, and M 7.6 scenario earthquakes on the Reelfoot Fault, the thrustfault in the NMSZ understood to be responsible for the largest event of the
1811-1812 sequence. The modeling accounts for finite-fault effects using thestochastic-source model. Simulated time-histories were then input into 1D
equivalent-linear site-response analyses conducted at each site. For the 1D
analyses, we used site-specific Vs profiles developed from surface reflection
and refraction studies and a recently developed 3D JPR sediment Vs model.
There is considerable uncertainty in the bedrock Vs in the Embayment and weused the average of the estimates determined at the two deep vertical seismicarrays in the JPR. The resultant scenario-based hazard maps not only reflect
regional variability in ground-motions due in part to nonergodic site-effects,
but also are straightforward for stakeholders and communities to understandand use. Future scenario-based seismic hazard assessments in the JPR may be
improved by incorporating 3D wave propagation effects.
poster 159
A Remarkable Absence of Liquefaction: Data-Driven
Lessons From the 2014 South Napa Earthquake
GREENFIELD, M. W., Greenfield Geotechnical, Oregon, USA, mike@greenfieldgeotechnical.com
The M6.0 2014 South Napa earthquake is often recognized for having aremarkable absence of liquefaction. But why? We investigate the subsurface soil and groundwater conditions in the vicinity of the fault rupture to
determine the potential reasons that liquefaction observations were nearly
absent, despite rigorous reconnaissance efforts. Through an analysis of several thousand borehole-based samples and monitoring well observations, we
determined that the near absence of liquefaction was not remarkable but was
rather predictable. First, the borehole data in the vicinity of Napa indicate thatthe Holocene alluvial soils tend to be more clay-like than elsewhere in the San
Francisco Bay region. Second, the groundwater at the time of the earthquake
was significantly lower than the typical elevation due to a prolonged drought.
The combination of these factors resulted in a low probability of liquefaction.
While the low groundwater levels at the time of the earthquake were fortuitous from a liquefaction perspective, groundwater levels can be highly variable. We also investigate the potential for liquefaction under different groundwater conditions with a novel spatial and temporal groundwater model. The
groundwater model is based on a relatively simple 2D flow analysis coupledwith a Gaussian Process regression scheme to interpolate the groundwater

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ground damage would have been more severe. Likewise, the influence of sea
level rise associated with climate change impacts groundwater conditions,which would further increase the probability of liquefaction.
poster 160
Offshore Seismic Hazards in Southern Cascadia
MCPHERSON, R. C., California State Polytechnic University, Humboldt,
California, USA, bob.mcpherson@humboldt.edu; PATTON, J. R., California
Geological Survey, California, USA, jason.patton@conservation.ca.gov;
DREGER, D. S., University of California, Berkeley, California, USA, ddreger@berkeley.edu; DENGLER, L. A., California State Polytechnic University,
Humboldt, California, USA, lad1@humboldt.edu; HELLWEG, M., Universityof California, Berkeley, California, USA, hellweg@berkeley.edu; LOMAX, A.,
ALomax Scientific, Mouans-Sartoux, France, alomax@free.fr
Large (6.5-7.5) earthquakes within the Gorda plate offshore of northern
California have been damaging communities in the region for more than
one hundred years. Many models have been proposed to explain the occurrence of these intraplate events, a response of the Gorda plate being squeezed
in a tectonic die. The most recent of these intraplate earthquakes took place
on December 20th, 2022, causing extensive damage in the towns of Rio Dell,
Fortuna, Loleta, and Ferndale. We demonstrate that this event occurred on
the same patch of the same fault as an earthquake 47 years ago, on June 7th,
1975. Additionally, we find that “stationary” intraplate faults capable of hosting recurring events are not unique to the 2022-1975 pair. There are at least
five offshore faults in southern Cascadia with a history of multiple damaging
earthquakes.
poster 161
Modelled Impacts of Rupture on the Newly DiscoveredXEOLXELEK-Elk Lake Fault, BC, Canada
HOBBS, T. E., Natural Resources Canada, Vancouver, Canada, thobbs@
eoas.ubc.ca; PATCHETT, M., University of Victoria, Victoria, Canada,
megumipatchett@gmail.com; SILVA, V., Global Earthquake Model
Foundation, Pavia, Italy, vitor.silva@globalquakemodel.org; RAO, A., Global
Earthquake Model Foundation, Pavia, Italy, anirudh.rao@globalquakemodel.
org; KIM, J., BC Ministry of Transportation and Infrastructure, Vancouver,
Canada, jenna.kim@gov.bc.ca
Canada has not experienced a fatality from earthquake shaking since 1870.
This relative seismic quiescence, and the lowered public perception of risk thatis causes, are at odds with a national risk assessment that estimates a meanvalue of nine fatalities per year from earthquake shaking. Additionally, it isestimated that a major earthquake near an urban center could cause hundreds
or even thousands of fatalities for the country, in addition to tens of thousands of ruined buildings and infrastructure assets and up to tens of billionsof dollars in direct financial losses, without accounting for secondary perils.
The newly discovered XEOLXELEK-Elk Lake Fault on the Saanich Peninsula,
British Columbia, poses a threat to the major population center of Victoria
as well as several important pieces of infrastructure on Vancouver Island. Its
shallow extent and proximity to housing will pose additional challenges by
thwarting earthquake early warning and potentially creating localized fault
displacement damage that residential homes are not designed to withstand.
In this study, the Canadian Seismic Risk Model framework is used toassess the impact of earthquakes on the XEOLXELEK-Elk Lake Fault, in termsof building damage, life safety, and disruption. Attention will also be paid tothe major highways in the area, which connect Victoria to mainland British
Columbia via the BC Ferries terminal in Swartz Bay. These results can beused by emergency managers, planners, and other decision makers to justify
needed preparedness and mitigation work to respond to this newly discovered
fault line.
poster 162
A Future Scenario Earthquake and Ground Motion Hazards
for Kathmandu, Nepal
KOKETSU, K., Keio University, Fujisawa, Japan, koketsu@sfc.keio.ac.jp;
MIYAKE, H., University of Tokyo, Tokyo, Japan, hiroe@eri.u-tokyo.ac.jp;
OKUMURA, K., Hiroshima University, Higashi Hiroshima, Japan, kojiok@
hiroshima-u.ac.jp; SUZUKI, H., OYO Corporation, Saitama, Japan, suzukiharuhiko@oyonet.oyo.co.jp
We constructed a new distribution of the rupture zones of great historical earthquakes along the Main Himalayan Thrust (MHT) by integrating
the distribution in a previous study and the results of recent trench surveys.

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Additionally, recent Global Navigation Satellite System (GNSS) observations
revealed that the boundary between the Indian and Eurasian plates is strongly
coupled from the southern boundary of the MHT to a depth of approximately
10 km and there is almost no lateral change in the coupling. This implies that
all regions along the MHT have similar rates of strain increase. Therefore, it ismost probable that the rupture zone of the oldest previous event will rupture
as a future scenario earthquake. In the new distribution, the 1255 earthquake
is the oldest. However, large earthquakes have already occurred in 1934 and2015 within its rupture zone. Thus, we adopted the area obtained by removing
the 1934 and 2015 rupture zones from the western part of the 1255 rupturezone. As this area is close to Kathmandu, we assumed that it would be the rupture zone of a possible scenario earthquake for seismic hazards in Kathmandu.
The relationship between the rupture zone size and seismic moment of the2015 earthquake falls between the scaling formulas for crustal earthquakes
and plate boundary earthquakes, but closer to the former formula. Therefore,
we constructed a characterized source model based on the former formula.
We simulated broadband ground motions in Kathmandu using this source
model, our 3-D velocity structure model, and a hybrid method combining
the finite difference method and the stochastic Green’s function method. We
obtained the peak ground accelerations (PGAs) of simulated ground motions,and calculated the seismic intensities in the modified Mercalli scale from the
PGAs as indexes of hazards for Kathmandu. Intensities IX were identified in
the center of the Kathmandu Valley, and we mostly found intensities VIII and
VII in the area surrounded by the sedimentary boundary and the southernmost part of the valley.
poster 163
Unraveling Seismic Complexity: Repeating Rupture
Patterns and Varied Seismogenic Environments in the
Mexico Subduction Zone
LIU, C., China University of Geosciences, Wuhan, China, liuchengli@cug.
edu.cn; HE, P., China University of Geosciences, Wuhan, China, phe@cug.
edu.cn; LAY, T., University of California, Santa Cruz, , USA, tlay@ucsc.edu;
XIONG, X., China University of Geosciences, Wuhan, China, Xiongxiong@
cug.edu.cn
Accurately determining the locations of repeating or quasi-repeating large
earthquakes allows for a more reliable estimation of recurrence periods andthe identification of seismic gaps. In this study, we systematically investigate
the complexity of earthquakes within the Mexico Subduction Zone. Using
waveform comparisons, we identify six sets of repeating rupture patterns,
and subsequently refine the slip models of historical events through joint
finite fault inversion method. Our findings indicate significant differences intectonic activities between the northern (Jalisco-Michoacan) and southern(Guerrero-Oaxaca) segments of the Mexico Subduction Zone. By clarifying
these differences, we provide valuable insights for future seismic risk assessments along the Mexico Subduction Zone, enabling a more accurate andregion-specific understanding of the potential impact of earthquakes. This
research serves as a foundation for enhancing preparedness measures andresilient infrastructure development, particularly in regions where the seismogenic environment poses unique challenges.
poster 164
Influence of Site Effects’ Spatial Variability on Spatially
Variable Ground Motion Intensity Measures
LORENZO-VELAZQUEZ, C., North Carolina State University, North
Carolina, USA, clorenz@ncsu.edu; CABAS, A., North Carolina State
University, North Carolina, USA, amcabasm@ncsu.edu
Spatially variable ground motions (GMs) challenge the assessment and designof largely distributed infrastructure in earthquake-prone areas. The spatial
variability of GMs is a complex function of source heterogeneities, varying ray propagation paths, and varying local soil conditions. Because soil
properties can be spatially correlated at nearby locations, the expected site
response affecting civil infrastructure systems will also be spatially correlated.
Therefore, the spatial correlation structure of soil properties can inform thespatial correlation of GM intensity measures (IMs). Current spatial correlation
models treat site effects either as a fixed amplification factor or as randomized
amplifications, but site effects are neither. In this work, we evaluate the significance of the spatial correlation for different site parameters corresponding to
Kiban-Kyoshin Network (KiK-net) stations with respect to the observed spatial correlation of GM IMs residuals from collocated events including the 2011
Tohoku earthquake sequence. This earthquake sequence caused significant
damage, such as pipeline ruptures due to the strong shaking in the Tohoku
and Kanto regions. These co-located events provide an opportunity to capturesite-specific correlations while isolating the influence of both source and path

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effects on correlation structures. Particularly, the residual analysis of GM IMs(e.g., spectral acceleration; SA) was performed using a ground motion model(GMM) to remove the effects of attenuation with distance and further examine the correlation of the IMs at different periods of interest. Preliminary findings show that the spatial distribution of GM IMs is affected by the variation ofgeology and topographic conditions captured by site parameters.
poster 165
Towards Probabilistic Tsunami Risk Estimates Using
Stochastic Earthquake Sources
MELGAR, D., University of Oregon, Oregon, USA, dmelgarm@uoregon.
edu; EGUCHI, R., ImageCat, , USA, rte@imagecatinc.com; KOSHIMURA,
S., Tohoku Unviersity, Sendai, Japan, koshimura@irides.tohoku.ac.jp;
CROWELL, B., University of Washington, Washington, USA, crowellbw@
uw.edu; LEE, Y., ImageCat, California, USA, yjl@imagecatinc.com;
ESQUIVIAS, G., ImageCat, California, USA, gre@imagecatinc.com; HU,
Z., ImageCat, California, USA, zh@imagecatinc.com; SANTELLANES, S.,
University of Oregon, Oregon, USA, ssantel2@uoregon.edu; SMALL, D.,
University of Oregon, California, USA, dsmall2@uoregon.edu
Tsunami hazard acalculation methodologies have undergone significant evolution in recent years with significant attention being placed on the probabilistic tsunami hazard assessment formalism. The next logical step is to extend
the focus from purely hazard-centric perspectives to inclusive evaluations ofrisk and loss. The most substantial challenges of this shift are twofold: accurate
estimation of likely seismic sources and defining the exposure of any given
region, both demanding appropriate modeling of rupture dynamics and highresolution hydrodynamics, as well as determining useful fragilities. Here we
propose an approach that integrates stochastic rupture simulations, advanced
inundation modeling, and exposure assessment. Through amalgamating thesedisparate elements into a cohesive framework, we aim to provide a comprehensive tool that not only quantifies the potential for seismic activity and consequent tsunami hazard, but also robustly predicts the associated risk and loss.
We will present results from a prototype workflow utilizing this methodology, and discuss its potential applicability in probabilistic calculations for any
subduction system globally. Furthermore, we will illustrate the scalability ofthis innovative model, asserting its feasibility for global implementation. This
step forward offers a promising avenue for significant improvements in our
understanding of tsunami hazards, risks, and their potential impacts on both
local and global scales.
poster 166
Seismic Geohazards in Italy: Seismic Geohazards in Italy:
An Integrated Geotechnical Earthquake Hazard Assessment
Map
MITRA, D., Risk Management Solutions, California, USA, dmitra@rms.com;
NATH, R. R., Moody’s RMS, Noida, India, ritu.nath@rms.com; SETHI, S.,
Moody’s RMS, Noida, India, Shipra.Sethi@rms.com; ADARSHI, N., Moody’s
RMS, Noida, India, Namita.Adarshi@rms.com
The study presents an integrated approach to assess three co-seismic geohazards: site amplification, liquefaction, and landslides for Italy. The noveltyof the approach lies in the construction of 30m x 30m geotechnical spatial
grids by adopting a systematic framework, considering the local site response
characteristics. The results are discussed in terms of three individual maps:
time-averaged shear wave velocity to 30m depth (Vs30), liquefaction, andlandslide susceptibilities. Due diligence is given to assess the pertinent hazards
for major areas viz. Central Apennines, Southern Italy, Sicily, and the Adriatic
Coast. The study also focuses on Northern Italy where the supplementaryrisks viz. liquefaction and lateral spreading were widely observed post the2012 Emilia Romagna sequence. We present a novel Vs30 map based on
constraining Vs30 observations within multiple secondary parameters suchas surficial geology and Multi-Resolution Valley Bottom Flatness (MrVBF)
for unconsolidated geology units. The improvements result in a reductionof around 15–30% in residual standard deviation in Holocene depositions.
A matrix of multidisciplinary datasets that includes geological, hydrological,
geotechnical, and terrain data is used to assess the liquefaction susceptibilityof Italy. The results provide both lateral and vertical displacements which arefurther validated using historical observations in Italy. Earthquake-induced
landslide hazard assessment is carried out using a bi-variate statistical modelof Landslide Susceptibility Zonation (LSZ), augmented with a multi-criteria
structured decision technique. Four landslide controlling parameters: geological units, slope angle, slope roughness, and Peak Ground Acceleration are
considered to produce an LSZ map for 5 historical earthquake events. The
resultant geotechnical site hazard maps provide an exhaustive representationof local site effects and coseismic instabilities in cognizance of seismic risk.

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The study offers valuable insights for establishing a framework for disasterrisk reduction.
poster 167
An Empirical Bayesian Kriging Approach for Site Period
Mapping of Santiago Basin, Chile
MITRA, D., Risk Management Solutions, California, USA, dmitra@rms.com
Seismic site classification plays an important role in the estimation of site
amplification, which directly influences earthquake-induced damages. Siteeffects are strongly dependent on site-specific conditions as well as the spatial
distribution of the geotechnical parameters in the region. Since the fundamental site period depends on the subsurface condition, surficial maps suchas terrain or geology have a high probability of being well constrained only
to shallow depths. At the same time, it is hard to find a consistent source of
bedrock depth parameters around the globe. The use of geostatistical methods
such as ordinary kriging or simple kriging can resolve this issue by relying ona spatial variogram for predictions at unsampled locations. However, uneven,or sparse data distribution usually creates unrealistic patterns. This study proposes the use of the Empirical Bayesian kriging interpolation method for site
period mapping in Santiago basin, Chile. A low-precision model using depth
to basement is used as prior information and ~200 fundamental site period
measurements are considered as precision data within the basin. This study
shows that the spatial prediction accuracy can be further improved over theordinary kriging approach using the Empirical Bayesian kriging technique.
poster 168
Understanding Regional Site-Amplification Effects in the
San Francisco Bay Region, California Through GroundMotion Analysis and Modeling of Regional Seismic
Velocity Structure
MOSCHETTI, M. P., U.S. Geological Survey, Colorado, USA, mmoschetti@
usgs.gov; AAGAARD, B. T., U.S. Geological Survey, Colorado, USA,baagaard@usgs.gov; BOYD, O. S., U.S. Geological Survey, Colorado, USA,olboyd@usgs.gov
We explore the relationship between regional site amplification and seismic
velocity profiles in the San Francisco Bay region of California through groundmotion analysis and modeling of one-dimensional profiles from threedimensional seismic velocity models. We compute Fourier amplitude groundmotions using a dataset of 34,000 records from 200 M>3.3 earthquakes. The
site terms are computed from mixed-effects regressions of the ground-motion
residuals, relative to the Bayless and Abrahamson (2019; BA19) groundmotion model (GMM), and partitioned into bias, event, and station-specificcomponents. We first evaluate the effect on data misfit from the use of siteparameters—time-averaged shear-wave speed to 30 m (VS30) and depth to the
1-km/s shear-wave horizon (Z1). The impact of the and parameters on fits
from the BA19 GMM is assessed by comparing sets of site terms that result
from the use of uniform reference VS30, VS30-only, and from VS30-Z 1 -pairs at
each site when evaluating the GMM. We identify regions of persistent longperiod (T>1 s) misfit, which indicate site response that differs from that of the
GMM. For all sites, we extract profiles from the U.S. Geological Survey San
Francisco Bay region seismic velocity model (Aagaard and Hirakawa, 2021)
and the National Crustal Model (Boyd, 2020). Using Thompson-Haskell
propagator matrix methods, we compute amplifications from the profiles andcompare the period-dependent trends in amplification with the trends in the
ground-motion residuals. With a primary focus on the sedimentary basins of
the region, we explore the effect of seismic velocity structure on the groundmotion misfits. Understanding the causes of varying site amplifications will be
an important step towards integrating nonergodic GMMs in regional seismic
hazards assessments and may lead to improved models to predict site responsethat extend beyond the San Francisco Bay region.
poster 169
Development of a Seismically Induced Landslide
Susceptibility Scale for Greece for Addressing Data
Imbalance
NATH, R. R., Moody’s RMS, NOIDA, India, ritu.nath@rms.com; MITRA, D.,
Moody’s RMS, California, USA, Devjyoti.Mitra@moodys.com
The persistent conundrum of data imbalances in landslide susceptibility zonation (LSZ) practices leads us to develop a data driven heuristic scale of LSZ
which is used to integrate landslide and seismic hazards for Greece. Threelandslide controlling parameters viz. slope angle, slope roughness and friction
angle are integrated with one seismic parameter: Peak Ground Acceleration

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Seismological Research Letters(PGA) to generate the seismically induced LSZ map of Greece. The landslide database is prepared using the USGS ScienceBase-Catalog for Lefkada
Earthquake, 2003. As only 274 landslide events are available for this earthquake, there is an accentuating problem of data/inventory imbalance which
results in overfitting/underfitting of weights. Application of traditional LSZ
models with such limited dataset generally shows exacerbated effects of one
landslide controlling parameter and often neglects the impact of others. Thismight produce an LSZ map which is heavily skewed towards the overfitted
controlling parameter. To address this issue, we develop a LSZ scale using
Frequency Ratio, Information Value and Fuzzy Cosine Amplitude methods
where concurrency of weights for each thematic layer of landslide controllingparameters are established. In the next phase, a scale of 1 to 9 is derived basedon the established concurrency, and the consistency of the decision is further
checked using a multi-criteria structured technique: Analytical Hierarchy
Process (AHP). If the consistency ratio (CR) for each decision is less than
10%, it is accepted, else the process is revised. Once all the weights (now inthe range of 1 to 9) are calculated, they are overlaid arithmetically in a GIS
environment to produce the final seismically induced LSZ map of Greece.
The resultant LSZ map demarcates the study area into five distinct zones oflandslide susceptibility with 77% predictive accuracy. The study demonstrates
the applicability of the proposed LSZ scale for areas with problems of data/
inventory imbalances.
poster 170
National Seismic Hazard Assessment for Azerbaijan Using
New Seismic Data and Ground Motion Simulations
ONUR, T., Onur Seemann Consulting, Inc., Victoria, Canada, onur.
osc@gmail.com; GOK, R., Lawrence Livermore National Laboratory,
District of Columbia, USA, gok1@llnl.gov; YETIRMISHLI, G., Azerbaijan
National Academy of Sciences, Baku, Azerbaijan, gyetirmishli@gmail.com;
HERRERA, C., Onur Seemann Consulting, Inc., Victoria, Canada, carlos@
onurseemann.com; GODOLADZE, T., Ilia State University, Tbilisi, Georgia,
tea_godoladze@iliauni.edu.ge; BONDAR, I., Research Institute for Geologicaland Geochemical Research, Budapest, Hungary, bondar.istvan@csfk.mta.hu;
PITARKA, A., Lawrence Livermore National Laboratory, California, USA,pitarka1@llnl.gov; CHIANG, A., Lawrence Livermore National Laboratory,
California, USA, chiang4@llnl.gov
A new probabilistic seismic hazard assessment (PSHA) was carried out
in Azerbaijan under the Seismic Cooperation Program at the Lawrence
Livermore National Laboratory. The study started with a Caucasus-wide
compilation of an earthquake database. Next, Mw was calculated for about
400 earthquakes using Coda Calibration Technique. Azerbaijan had manystations where modern digital seismometers were co-located with Soviet-era
equipment, which was instrumental in developing magnitude conversion
relations between Mw and Soviet era magnitude scales. Following magnitude
harmonization, catalogue completeness intervals were computed. In addition,
earthquake relocation was carried out providing more accurate locations anddepths for earthquakes, better delineating a subduction structure that havebeen the subject of past investigations. Two versions of the PSHA-ready catalogue were generated, one with declustering applied and one without. Known
active faults with geologic slip rates in this region are sparse, but a few wereidentified in neighbouring countries that might impact Azerbaijan. A source
model was put together using both the seismic activity rates based on theearthquake catalogue and the identified active faults. Azerbaijan has a strong
motion network that has about 40 accelerometers. Contemporary groundmotion models (GMMs) from US, Japan, Europe and Middle East were
tested against recorded data, which showed that the ground motion attenuation in much of Azerbaijan is generally slower than active tectonic regions
like California, but faster than stable continental regions like Eastern North
America. The difference also varies by frequency/period of vibration. The reason for the difference appears to be not tectonic in origin but rather due tothick sedimentary layers in the Kura basin. In order to quantify these effects,
we perform 3-D hybrid ground motion simulations to inform the selection of
the GMMs and the weights to use in the PSHA. We present preliminary resultsthat have been well-received by the engineering community in Azerbaijan andare currently being considered for use in the building code update.
poster 171
Data-Driven Performance Evaluation of Ground Motion
Models Applicable for Active Crustal Region in Italy
PARAMASIVAM, B., Moody’s RMS, California, USA, balaji.paramasivam@
moodys.com; KIM, S., Moody’s RMS, California, USA, sangwoo.kim@

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moodys.com; SEYHAN, E., Moody’s RMS, California, USA, emel.seyhan@moodys.com
The influence of regional crustal wave propagation effects and complex geologic structures has been observed in strong motion records in Italy. Thesephenomena are critical and are captured by ground motion models (GMM)
for developing regional seismic hazard maps. The aim of present work is toselect and rank GMMs applicable in active crustal regions of Italy for seismic hazard analysis. In this study, we evaluated the relative performance of
15 active crustal GMMs, including regional, pan-European, globally derived
default and regionally adjusted ones. We compiled a comprehensive strong
motion flatfile containing over 43,000 recordings from ESM and ITACA
between 1969-2022. First, we processed the strong motion records to remove
duplicates and selected only records having magnitudes greater than 4.5.
Then, residual analysis was performed using strong motion records from rocksite stations (having VS30 of 600-1000 m/s) and all stations with varying VS30.
We analyzed the influence of minimum magnitude, rupture distance, andfault mechanism on overall bias and between event as well as within-event
residuals. Finally, data-driven scoring methods were employed, using univariate (LLH) and multi-variate (mLLH) logarithmic scores, to assess relative
performance of GMMs. Regional level seismic hazard analysis was also performed using selected candidate GMMs, by assigning weight of 1.00. Resultsof residual analyses showed that almost all GMMs are over-predicting at the
short period due to regional factors, where the degree of over-prediction issignificant among earlier version of pan-European and global GMMs. On
the other hand, almost all GMMs were under-predicting at the long periods(approximately after 1-2 seconds). In general, regional and pan-European
GMMs showed relatively better performance (in terms of better LLH andmLLH scores), by capturing regional characteristics than global and global
model with regional adjustments. Finally, rock-level hazard maps, corresponding to VS30 of 760 m/s and 475-year return period, revealed that regionalmodels exhibit lower hazard than pan-European model.
poster 172
Dependence of Seismic Hazard Assessment on the
Observation Time Interval: Insights From Physics-Based
Simulated Seismicity in Southeastern Spain
PASCUAL-SÁNCHEZ, E., Universidad Complutense de Madrid, Madrid,
Spain, epsanchez@ucm.es; ÁLVAREZ-GÓMEZ, J. A., Universidad
Complutense de Madrid, Madrid, Spain, jaalvare@ucm.es; GARCÍAMAYORDOMO, J., Instituto Geológico y Minero de España, Madrid, Spain,
julian.garcia@igme.es; HERRERO-BARBERO, P., Geosciences Barcelona,
Barcelona, Spain, pherrero@geo3bcn.csic.es
The magnitude-frequency distribution (MFD), which defines the seismicity
of a region, is obtained using the earthquake record. In slow-moving fault
systems, where seismicity is low to moderate, earthquake catalogues may
not cover the full seismic cycle of active faults. This implies that seismogenic
sources may be incompletely characterized on Probabilistic Seismic Hazard
Assessment (PSHA), since the quantification of seismic hazard is associatedwith the specific time period during which earthquake catalogue have beenrecorded. To evaluate the dependence that exists between seismic hazard andthe observation interval, this study develops some PSHAs based on synthetic
seismicity. The selected site is the Eastern Betics Shear Zone in SE Spain,
where some damaging earthquakes have occurred. The synthetic seismicityof this fault system consists of a million-year earthquake catalogue generated using the RSQSim earthquake simulator. The digital model considers thegeometry, slip rates and friction properties of major faults. From the global
synthetic catalogue, ten thousand sub-catalogues have been obtained. Their
duration has been selected to be equivalent to that of the actual earthquake
record (i.e. 1,000 years). Each sub-catalogue shows different features in their
MFDs, which can be quantified by the distribution of values of the slope of
the Gutenberg-Richter relationship, the annual earthquake rate and the maximum magnitude. A hundred sub-catalogues have been randomly selected to
conduct individual PSHA. Seismic hazard curves have been obtained for thecities of Murcia, Lorca, Alicante, Vera, Torrevieja and Almería using R-CRISIS.
These curves reveal that each sub-catalogue leads to different return periods
for specific values of Peak Ground Acceleration (PGA). The variability coefficient was used to quantify hazard variability, with a maximum value of 58%
found in Torrevieja for a PGA=1g and a minimum of 10% in Almeria for
a PGA=0.02g. These results show that seismic hazard depends on the timeinterval during which an earthquake catalogue is recorded. This dependence
increases for large PGA values.

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poster 174
Improving Geospatial Liquefaction Prediction Models by
Optimizing Non-Liquefaction Points Sampling: A Case
Study of the 2023 Kahramanmaras, Turkey Earthquake
Sequence
SHIRZADI, H., Tufts University, Massachusetts, USA, hooman.shirzadi@
tufts.edu; BAISE, L. G., Tufts University, Massachusetts, USA, laurie.baise@tufts.edu; MOAVENI, B., Tufts University, Massachusetts, USA, babak.
moaveni@tufts.edu
To create geospatial liquefaction prediction models, we need to observe bothliquefaction and non-liquefaction points to use this information to extract
the value of explanatory geospatial proxies like VS30, distance to water, etc.
Reconnaissance teams usually report only the location of liquefaction; therefore, to sample non-liquefaction points, we need to make different assumptions. In the literature, a donut-shaped area with an inner radius of 1 km
and an outer radius of 15 km is used to create a fishnet with desired grid sizeand sample non-liquefaction points. This study looks at the critical aspect of
non-liquefaction point sampling strategies and how the geometric properties of the donut-shaped non-liquefaction sampling region around the liquefaction observation affect the accuracy and generalizability of the resulting
model. This study uses the extensive reconnaissance reports from the 2023
Kahramanmaras, Turkey Earthquake Sequence to compare different samplingstrategies based on their impact on the accuracy of the logistic regression
model. We use the inner and outer radii of the donut-shaped non-liquefaction
sampling buffer as optimization variables to do a grid search over the different
combinations of them. The resulting models are then compared in terms ofbalanced accuracy, area Under the ROC Curve (AUC), precision, and recall.
The insights gained from this study will help refine the methodology for creating geospatial liquefaction prediction models and provide valuable guidancefor optimizing earthquake risk assessment strategies.
poster 175
Correlating Resonance Frequency From Hvsr With Vs30
Along the Wasatch Fault, Northern Utah, USA
SMITH, K., Brigham Young University, Utah, USA, smithk86666@gmail.
com; MCBRIDE, J., Brigham Young University, Utah, USA, john_mcbride@
byu.edu; HARRIS, R., Brigham Young University, Utah, USA, rharris@byu.
edu; WORTHEN, B., Brigham Young University, Utah, USA, boworthen@icloud.com
The Wasatch Fault Corridor of northern Utah has an increasingly high seismic
risk due to rising population density. Vs30 (time-averaged subsurface shearwave velocity for the upper 30 meters) is the key parameter to determine
how a site will respond to earthquake shaking; however, finding Vs30 usuallyrequires an intensive array-based measurement with an active seismic source.
The horizontal to vertical spectral ratio (HVSR) single-sensor technique
is passive, unintrusive, and more convenient, potentially allowing for rapid
assessment if a transformation can be obtained between Vs30 and the fundamental resonance frequency (f0) provided by the HVSR for the shallowest
stratigraphic layers. The purpose of our study is to evaluate the effectivenessof correlating the Vs30 with HVSR f0 to either supplement or replace Vs30
measurements. Reoccupying previously surveyed Vs30 sites in Utah County,
Utah, we measured the f0 using HVSR with a three component TROMINO
seismometer. The sites are located on the hanging wall (west) of the Wasatch
fault zone amongst alluvial and lacustrine Quaternary sediments. For eachsite, we recorded ambient noise for 20 minutes and computed the amplitude frequency spectra for the three components (N-S, E-W (“H”), up-down(“V”)), then converted these to H/V response as a function of frequency, fromwhich we observed the f0 of the site by choosing the highest H/V spectral
peak. The f0 ranged between 0.28 and 1.09 Hz for all sites. To produce thebest transformation of Vs30 to f0, we selected those measurements for which
the lowest-frequency prominent H/V peak was observed within the spectrum.
Sixteen out of the 23 measurements were selected due to their well-expressed
H/V spectral peaks and lower uncertainties. The linear regression between
Vs30 as a function of f0 resulted in a moderate positive correlation. Further
work will include collection of more HVSR measurements to increase theaccuracy of our study.
poster 176
Epistemic Uncertainty and Aleatoric Variability within
Probabilistic Liquefaction Analysis
THUM, T., Virginia Tech, Virginia, USA, tat2@vt.edu; RODRIGUEZMAREK, A., Virginia Tech, Virginia, USA, adrianrm@vt.edu; STAFFORD, P.

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J., Imperial College London, London, United Kingdom, p.stafford@imperial.
ac.uk; GREEN, R. A., Virginia Tech, Virginia, USA, rugreen@vt.edu
In probabilistic seismic hazard analyses (PSHA), well established approaches
have been developed for handling aleatory variability and epistemic uncertainty related to ground motion models and the associated predictive variables. However, extending these concepts to probabilistic liquefaction analyses (PLA) raises questions about how uncertainties are accounted for in thedevelopment of liquefaction triggering models. Specifically, in some of themore recently developed probabilistic triggering models, uncertainties in theestimated seismic demand and the measured in-situ test metrics associatedwith liquefaction and no-liquefaction case histories have and have not been
considered, resulting in triggering models reflective of “total” and “model”
uncertainties, respectively. How these triggering models are used within a
PLA and the division between the aleatory variability and epistemic uncertainty related to the triggering model and associated predictive variables are
explored herein.

Research Advances in “High-Impact”, “Under-Studied”
Earthquakes and Their Impacts on Communities [Poster
Session]Poster Session • Friday 3 May
Conveners: Susan Bilek, New Mexico Institute of Mining
and Technology (susan.bilek@nmt.edu) Marianne Karplus,
University of Texas at El Paso (mkarplus@utep.edu); Zhigang
Peng, Georgia Institute of Technology (zpeng@gatech.edu);
Elizabeth Vanacore, University of Puerto Rico (elizabeth.
vanacore@upr.edu); Aaron A. Velasco, University of Texas at
El Paso (aavelasco@utep.edu)
poster 144
Impact of November 2023 Earthquake in Western Nepal.
DHAKAL, H., Tribhuvan University, kathmandu, Nepal, hari2797@gmail.
com
On 3 November 2023 5.6 M earthquake struck Nepal, with epicenter in
Jajarkot of Karnali province. Several aftershocks have occurred since. Tremors
were felt across North India.
According to the National Disaster Risk Reduction and Management
Authority (NDRRMA) 153 people have been killed and 140 injured.
Thousands of families were left under the open sky as rescuers searched forsurvivors in the mountainous villages where the earthquake struck.
With the completion of the government’s search and rescue operation,
the number of deaths stands at 153 (Male: 70, Female: 83) and 338 (Male: 138,
Female: 200) injured. The initial findings of the Government’s Initial Rapid
Assessment (IRA) launched on 05 November say over 4,000 homes were damaged in the hardest hit districts. Following the initial assessment of the remote
damage assessment of available secondary data satellite images USGS data andearthquake risk model, around 1.3 million people might have been exposed
and about 0.25 million people may need humanitarian assistance.
According to the National Emergency Operation Centre (NEOC), by 15
November, approximately 62,000 homes were affected (35,455 partially damaged, 26,557 completely damaged) by the earthquake. Some 250,000 people
were affected by the earthquake and require humanitarian assistance. The situation is further compounded as rainwater is posing a significant risk to partially damaged homes that are fragile and face the risk of collapsing. Survivorsof the earthquake are also beginning to report health issues related to increasingly cold weather. Public health authorities have warned of outbreaks of communicable and vaccine-preventable diseases in the affected areas as thousandsof people are displaced, compromising health and hygiene standards.
So, in this paper I will explore the current situation in the Earthquake
affected area and what needs to be done to the people of Western Nepal whichis affected by this Earthquake.
poster 145
Examining the 1953 Kefalonian Earthquakes, From a Social
Perspective.
GALANOS, N., National and Kapodistrian University of Athens,
ATHENS, Greece, ngalanos@geol.uoa.gr; KOUSKOUNA, V., National andKapodistrian University of Athens, ATHENS, Greece, vkouskouna@geol.

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Seismological Research Lettersuoa.gr; SAKELLARIOU, N., Museo Nacional de Ciencias Naturales, Madrid,
Spain, nikolaos.sakellariou@mncn.csic.es; GALANOS, G. S., Municipality of
Lixouri, Lixouri, Greece, ouranoselios123@gmail.com
The Ionian islands, situated at the most western part of Greece, experienced
the domination of Venice from 14th until the 19th century, and Great Britain
from 1815 to 1864, when they were annexed to Greece. Isolated from themainland of Greece, the culture of the inhabitants was influenced by their rulers, mostly the Venetians, with a severe impact on their social and economic
life. Earthquakes, from historical to modern times, were the most influential
disaster in their culture, leaving traces on the mentality, architecture and literature of the population in Zakynthos, Kefalonia, Ithaki and Lefkada islands.
The 1953 earthquake series (9 August M6.4, 11 August M6.8 and 12 AugustM7.2) is a characteristic example of how a natural disaster seriously affected
the everyday life of the population, mainly in Kefalonia, Ithaki and Zakynthos.
Their effects were many casualties, whole towns and villages covered by debris
and fires, leading to homelessness, and pleas for aid. The earthquakes also hadsignificant psycho-social repercussions on the locals, especially to womenand children. Most of the population was poor, similar to the rest of Greeks,trying to recover from WWII and the civil war. According to the authorities
reports and the local and international press, the first to arrive for aid on 13
August were battleships of the British Royal Navy, United States and Israel,
which were conducting a military drill offshore Kefalonia, followed by ships
from Italy, carrying water supplies, two days later. The King of Greece arrived
on 14 August and ordered the military to dispose the debris. Of great importance was the financial assistance from France, Sweden and Switzerland who“adopted” villages of Kefalonia, reconstructing them from scratch (e.g. Agia
Efthymia and Lakithra). Additionally, international humanitarian organizations, such as Red Cross and CARE, rushed to provide aid (food, tents, etc.).
The 1953 earthquakes were a milestone in the history of Greece, leading tointernal migration, and influencing the perception of time scales to pre- andpost-earthquake.
poster 146
Seismic Hazard and Risk in Lae City, Papua New Guinea(PNG)
GRIFFIN, J. D., Geoscience Australia, Cook, Australia, jonathan.griffin@
ga.gov.au; CUMMINS, P. R., Geoscience Australia, Canberra, Australia,
Phil.Cummins@ga.gov.au; CLARK, D. J., Geoscience Australia, Canberra,
Australia, Dan.Clark@ga.gov.au; EDWARDS, M., Geoscience Australia,
Canberra, Australia, Mark.Edwards@ga.gov.au; ESPI, J., University of Papua
New Guinea, Port Moresby, Papua New Guinea, joseph.espi@upng.ac.pg;
BETASOLO, M., Papua New Guinea University of Technology, Lae, Papua
New Guinea, Mirzi.betasolo@pnguot.ac.pg; JONDA, L., University of Papua
New Guinea, Port Moresby, Papua New Guinea, leojonda@upng.ac.pg;
WANTEPE, G., Papua New Guinea University of Technology, Lae, Papua
New Guinea, grace.wantepe@pnguot.ac.pg; GHASEMI, H., Geoscience
Australia, Canberra, Australia, Hadi.Ghasemi@ga.gov.au; CORBY, N.,
Geoscience Australia, Canberra, Australia, Neil.Corby@ga.gov.au; RYU,
H., Geoscience Australia, Canberra, Australia, Hyeuk.Ryu@ga.gov.au; PAI,
A., Papua New Guinea University of Technology, Lae, Papua New Guinea,
Andrew.pai@pnguot.ac.pg; STANAWAY, R., Quickclose, Canberra, Australia,
richard.stanaway@quickclose.com.au; KEMP, J., Griffith University, Brisbane,
Australia, j.kemp@griffith.edu.au; WEHNER, M., Geoscience Australia,
Canberra, Australia, martin.wehner@ga.gov.au
Lae is Papua New Guinea’s second largest city, most significant port, and amajor economic hub critical to PNG’s development. It also straddles the
Ramu-Markham Fault Zone (RMFZ), which accommodates convergence
rates of approximately 50 mm/yr associated with the arc-continent collision between the Australian and South Bismarck plates. Recently publishedupdates to PNG’s national seismic hazard assessment have identified that Lae
is exposed to high seismic hazard. In order to better understand and mitigate this threat, a comprehensive seismic hazard and risk assessment has been
undertaken for the city. This work has included: detailed mapping of active
fault traces from lidar elevation models; an earthquake geology study to constrain the timing of past large earthquakes by dating flights of uplifted fluvial
terraces; a GNSS survey to constrain fault slip rates; a microzonation survey
to understand site amplification and liquefaction potential; and a building
inventory survey that has captured relevant engineering data for more than
3300 structures in the city. Fault mapping has shown that the RMFZ bifurcateswest of the city, with one strand continuing to the east 10 km north of the city
(as previously mapped), and a second strand (previously unmapped) trending southeast through Lae itself. GNSS results suggest that about a quarter ofthe plate convergence rate is accommodated along this second strand, likely
contributing to higher seismic hazard estimates for the city. Integration of thewww.srl-online.org•

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hazard information with the building survey data and an assessment of thevulnerability of key building types is creating a picture of concentrated earthquake risk in the Lae urban area, port and airport. Ongoing work is focusedon updating PNG’s building standards, with a particular focus on criticalinfrastructure including bridges.
poster 147
The “Earthquake Suitcase”—A Research-Inspired
Educational Tool for Earthquake Vulnerable Communities
KOUSKOUNA, V., National and Kapodistrian University of Athens, Athens,
Greece, vkouskouna@geol.uoa.gr; SAKKAS, G., KEMEA Center for Security
Studies, Athens, Greece, g.sakkas@kemea-research.gr; SAKELLARIOU, N.,
Spanish National Research Council, Madrid, Spain, nikolaos.sakellariou@
mncn.csic.es; GALANOS, N., National and Kapodistrian University ofAthens, Athens, Greece, ngalanos@geol.uoa.gr; RIDGE, H., Boulder Valley
School District, Colorado, USA, heather.ridge@bvsd.org
The “Earthquake Suitcase” is a travelling laboratory, designed and developed
to inform, educate and familiarize the public in earthquake prone areas withearthquakes and their impacts, aiming in reaching people at remote locations,unable to visit a natural history museum. It includes presentation and videos on the earthquake basics (why, how and where large earthquakes occur,
their effects on people, objects and buildings/infrastructure), reading material, hands-on exercises and instructions to build a family emergency plan, thecontents of an earthquake emergency bag, interactive educational toys, leaflets
and a model small-scale shake table. This is a stable platform, upon whicha moving platform is fixed. The upper platform converts the initial manually controlled rotary motion to axial motion, thus simulating ground shaking. It is equipped with two model buildings of different vulnerability and an
accelerometer recording the simulated motion. It may produce various levelsof shaking, thus simulating higher and lower ground accelerations of various
frequencies. The supplied software/mobile app provides various signal analysis options of the simulated “event”. Persons with knowledge of Physics may
perform spectral analysis of the simulated event and compare the response ofmodel buildings to the different levels of shaking. The suitcase is presented in
the Europe-wide public event “Researchers’ Night” and in Greek classrooms,
evaluated by schoolchildren and their educators, as an example for disaster
preparedness. It was also used in the partnership project “Supporting Socialand Emotional Learning” between Greek and US Fulbright alumni to develop
resources that bring a strong awareness of mental health needs to practices in
educational settings and refugee camps, where the earthquake phenomenon
was used as an analogy of mass trauma-producing disaster, aiming at simulating the circumstances, due to which adolescents are likely to be traumatized.
The suitcase and the earthquake lesson were presented in US classrooms, thus
embedding social and emotional learning into science content.
poster 148
High-Impact Earthquakes on Hidden, Secondary Faults
Within the Sparsely Instrumented Golden Triangle Regionof Laos, Thailand, and Myanmar
SETHANANT, I., University of Victoria, Victoria, Canada, isethanant@uvic.
ca; NISSEN, E., University of Victoria, Victoria, Canada, enissen@uvic.ca;
BERGMAN, E., Global Seismological Services, Colorado, USA, bergman@csd.net; OLIVA, S., University of Victoria, Victoria, Canada, soliva@uvic.
ca; POUSSE-BELTRAN, L., Université Grenoble Alpes, Grenoble, France,
lea.pousse@univ-grenoble-alpes.fr; KARASOZEN, E., University of Alaska
Fairbanks, Alaska, USA, ezgikarasozen@gmail.com
The Golden Triangle region of Laos, Thailand, and Myanmar (SE IndiaEurasia collision zone) is crossed by >100 km-long, NE-striking sinistral
faults, host to events of up to Mw 6.8 (2011 Tarlay). In the past decade, six Mw≥5.5 events struck the area, providing new insights into its active tectonics.
The largest of these, the 2019 Mw 6.2 Sainyabuli, Laos earthquake, struck 40
km from a major reservoir and 90 km from a UNESCO World Heritage Site,
illustrating the need to reassess the earthquake potential of this area despite its
modest background seismicity. In this study, we solved for source parametersof three Mw ≥5.5 events using Sentinel-1 InSAR. The Sainyabuli mainshock
ruptured a previously unknown, 24 km-long, NNW-trending, dextral strikeslip fault with little topographic expression, with slip focused above 12 km
but leaving a pronounced shallow slip deficit. InSAR modelling of the othertwo Mw ≥5.5 events also revealed rupture on NW-trending, ~10 km-long,unmapped faults. Collectively, this shows that the region contains conjugate

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faults long enough to generate damaging earthquakes but which are little evident in the topography. To understand the seismicity depth distribution andits implication for seismogenic thickness, we also relocated 198 well-recorded
events between 1978–2022 using mloc software. We overcame the challengeof limited local-regional station coverage by incorporating seismic sequencesfrom across a broad area into the relocation cluster. Since these events also
share teleseismic station recordings, the collective local-regional coverage
is improved. The calibrated catalog contains focal depths of 6–24 km, eachwith ±4 km uncertainties. The seismicity cut off thus extends far deeper thanthe Sainyabuli mainshock slip, potentially leaving an unruptured deeper fault
as an ongoing hazard. Our combined geodetic and seismological approachshows that shorter, NW-oriented faults should be considered alongside thelonger NE-trending faults in hazard models and earthquake scenarios. Our
study also provides a blueprint for relocating earthquakes in other sparsely
instrumented regions.
poster 149
The Center for Collective Impact in Earthquake Science(C-CIES)VELASCO, A. A., University of Texas at El Paso, Texas, USA, aavelasco@
utep.edu; WEIDNER, J., University of Texas at El Paso, Texas, USA,jweidner@utep.edu; KARPLUS, M. S., University of Texas at El Paso, Texas,
USA, mkarplus@utep.edu; BILEK, S., New Mexico Institute of Mining andTechnology, New Mexico, USA, sbilek@nmt.edu; BOLTON VALENCIUS,
C., Boston College, Massachusetts, USA, valenciu@bc.edu; BRUDZINSKI,
M. R., Miami University of Ohio, Ohio, USA, brudzimr@miamioh.edu;
CHANDRASEKHAR, D., University of Utah, Utah, USA, D.Chandrasekhar@utah.edu; EBEL, J. E., Boston College, Massachusetts, USA, john.ebel@bc.edu;
HOBBS, T., Geological Survey of Canada, Vancouver, Canada, tiegan.hobbs@
nrcan-rncan.gc.ca; HURTADO, J. M., University of Texas at El Paso, Texas,
USA, jhurtado@utep.edu; JAUME, S., College of Charleston, South Carolina,
USA, JaumeS@cofc.edu; JONES, E., University of Texas at Houston, Texas,
USA, eric.c.jones@uth.tmc.edu; KAFKA, A., Boston College, Massachusetts,
USA, kafka@bc.edu; LIN, Y., University of New Mexico, , USA, ycl@unm.edu;
NUNEZ, A., University of Texas at El Paso, Texas, USA, amnunez9@utep.
edu; PANKOW, K. L., University of Utah, Utah, USA, pankow@seis.utah.edu;
PENG, Z., Georgia Institute of Technology, Georgia, USA, zpeng@gatech.
edu; SAVVAIDIS, A., University of Texas at Austin, Texas, USA, alexandros.
savvaidis@beg.utexas.edu; TIEN, I., Georgia Institute of Technology, Georgia,
USA, itien@ce.gatech.edu; VANACORE, E., University of Puerto Rico at
Mayagüez, Puerto Rico, USA, elizabeth.vanacore@upr.edu; ALVILLAR, M.,
University of Texas at El Paso, Texas, USA, mvalvillar@utep.edu
The Center for Collective Impact in Earthquake Science (C-CIES), funded asa Track 1 planning grant by NSF’s Centers for Innovation and Community
Engagement in Solid Earth Geohazards program, aims to address fundamental science questions related to earthquakes by implementing a collective
impact (CI) model for science and community engagement. CI solves complex problems though the creation a network of community members, organizations, and institutions by adopting a common agenda, centralized support, continuous communication, mutually reinforcing activities, and sharedmeasurement. The science and engineering driver of C-CIES is to study highconsequence, low frequency of incidence (HC-LoFI) events. The mission is toincrease societal resilience to earthquakes through collective impact hazard
research with a vision to become an interdisciplinary research center rooted
in equity, diversity, and engagement. The core values of the center are scientific integrity, equity, excellence, diversity, access, justice, inclusion, andcollective impact. The goals of the center are to: 1) Advance convergent andtransdisciplinary earthquake science and engineering research, 2) Recruit,retain, and train the next generation of diverse, interdisciplinary Earth scientists and leaders, 3) Establish a foundation of CI in Earthquake Science forshared, value-driven research that is responsive to the needs of communities,
and is transferable and scalable to other geohazards, and valuable to other disciplines, and 4) Develop strong CI management structure for the center thattranslates results of scientific discovery into actions that can improve resilience and reduce risk from geohazars. C-CIES is currently undertaking pilot
projects that will address faulting, earthquakes, and their impacts, and which,upon evaluation, may be promoted to full projects as the center launches in
one year. Using collective impact, we aim to change the way geoscience is conducted by answering fundamental community-driven science questions thatwill have a broad, positive impact.

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Seismic Cycle-Driven Sea-Level Change Over Decades toCenturies: Observations and Projections [Poster Session]
Poster Session • Friday 3 May
Conveners: Kate J. Clark, GNS Science (k.clark@gns.cri.
nz); Andrew Howell, University of Canterbury (andrew.
howell@canterbury.ac.nz); Jeonghyeop Kim, University ofWashington (jey.kim@uw.edu)
poster 150
Validation of Probabilistic Coseismic Coastal Deformation
Models using Geologic and Geomorphic Evidence
CLARK, K. J., GNS Science, Lower Hutt, New Zealand, k.clark@gns.cri.
nz; HOWELL, A., GNS Science, Lower Hutt/Christchurch, New Zealand,
A.Howell@gns.cri.nz; DELANO, J., University of Canterbury, Christchurch,
New Zealand, jaime.delano@pg.canterbury.ac.nz; LITCHFIELD, N., GNS
Science, Lower Hutt, New Zealand, N.Litchfield@gns.cri.nz
Incorporating the likelihood of sudden earthquake-driven coastal uplift or
subsidence into sea level change forecasts is important in tectonically active
countries such as Aotearoa New Zealand (A-NZ). Several historical earthquakes in A-NZ have demonstrated the impacts that sudden coastal displacement can have on society, the environment and infrastructure. A proof-ofconcept probabilistic model that forecasts coseismic vertical displacement
over 100 years in the Wellington Region of A-NZ has been developed, andthere is an intention to expand this model nationwide. Alongside this is aneed to develop methods of validating the probabilistic coseismic coastal
deformation results. Validation of the coastal deformation model can be done
through a comparison with historical and some prehistoric coastal deformation data. The A-NZ historical record is short (~185 years) but there have been
6 earthquakes that have caused coastal deformation within this period. The
prehistoric coastal deformation record is much longer but precisely how wecompare geologic and geomorphic evidence of past coastal uplift and subsidence with modeling results is challenging. For example, the modeled coseismic displacements represent a mix of permanent and elastic tectonic deformation but the geomorphic record preserves net permanent displacement
over multiple seismic cycles, so the geomorphic record may under-represent
displacements from primarily elastic subduction zone earthquakes. We are
exploring whether net uplift/subsidence rates from Pleistocene marine terraces are a useful source of data, or whether recurrence intervals and singleevent displacement data from Holocene sedimentary and geomorphic records
are preferable. However, using single-event displacement necessitates someunderstanding of the preservation and detection limits of various coastal
paleoseismic proxies. Regardless of the approach, model validation is important for establishing confidence in the results and for targeting which model
input parameters may benefit from further research.
poster 151
How Will Earthquakes Change Sea Level? a Probabilistic
Coast-Seismic Hazard Model
DELANO, J., University of Canterbury, Christchurch, New Zealand,jaimedelano@gmail.com; HOWELL, A., University of Canterbury,
Christchurch, New Zealand, a.howell@gns.cri.nz; CLARK, K. J., GNS Science,
Lower Hutt, New Zealand, K.Clark@gns.cri.nz; ROLLINS, C., GNS Science,
Lower Hutt, New Zealand, c.rollins@gns.cri.nz; STAHL, T., University ofCanterbury, Christchurch, New Zealand, timothy.stahl@canterbury.ac.nz;
SEEBECK, H., GNS Science, Lower Hutt, New Zealand, h.seebeck@gns.cri.
nz; LEVY, R., GNS Science, Lower Hutt, New Zealand, r.levy@gns.cri.nz;
NAISH, T., Victoria University of Wellington, Wellington, New Zealand,
timothy.naish@vuw.ac.nz
Coseismic uplift and subsidence can cause near-instantaneous meter-scale
relative sea level changes that may exacerbate or reverse the effects of ongoing sea level rise. Characterizing hazards in tectonically active coastal regions,
therefore, requires careful consideration of coseismic vertical deformation.
We developed a proof-of-concept probabilistic model that forecasts coseismic
vertical displacement over 100 years in the Wellington Region of Aotearoa
New Zealand. This model repurposes fault source, earthquake rupture, andepistemic uncertainty data from the New Zealand National Seismic Hazard
Model (NZ NSHM) to quantify the magnitude, direction, location, andlikelihood of vertical displacement from both crustal fault and subduction
interface earthquakes. The model results suggest that both crustal fault andsubduction sources contribute to significant (>0.2 m) vertical displacement
hazard at most coastal Wellington sites. In general, the subduction interface

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contributes more to subsidence hazard while crustal faults contribute more to
uplift hazard, though proximity to specific faults and fault geometry influence
the hazard at specific sites. Coseismic subsidence, in particular, can be generated by both crustal and subduction earthquakes and should be considered insea-level rise forecasts and resilience planning. Future versions of this model
may benefit from refinements to crustal fault geometries at depth and subduction interface rupture extents. Overall, this study highlights how assumptions
and choices in regional scale hazard models underpin coseismic multi-hazard
analysis. With the appropriate considerations, however, ground-shaking hazard models may also be useful for estimating coseismic vertical deformation
and associated sea level changes in other regions worldwide, particularly
where several different seismic sources contribute to hazard.
poster 152
Toward Resilient Coastal Communities: A Probabilistic
Assessment of Co- and Inter-Seismic Vertical Land Motion
KIM, J., University of Washington, Washington, USA, jeonghyeop.kim@
gmail.com; SCHMIDT, D., University of Washington, Washington, USA,dasc@uw.edu; PEARSON, A., University of Washington, Washington, USA,aerp@uw.edu
The Cascadia subduction zone stands out for its capacity to generate great
megathrust earthquakes in the future, which can cause abrupt coastal subsidence of a few meters. Thus, it is critical to understand the probabilistic natureof vertical land motion (VLM) along the Pacific Northwest shoreline to minimize the effects on coastal communities and to inform community planners ofpossible outcomes. Here, we present a probabilistic framework to assess futuretectonic VLM to aid in planning. Considering both inter- and co-seismic scenarios, we derive probability density functions (PDFs) of future tectonic VLM
for various locations along the coastline. For coseismic PDFs, we first calculate elastic vertical responses at coastal areas to 37,500 “fakequakes” (Melgar,
2021), using a boundary-element modeling tool. We then construct PDFs
guided by the logic tree for the National Seismic Hazard Map (NSHM) andgeological constraints. Interseismic PDFs are obtained using a geodetic locking model. We scale these PDFs by multiplying estimated likelihoods of coand inter-seismic scenarios for a return period of interest. We estimate theselikelihoods using a Brownian recurrence model that incorporates the mean
recurrence interval and aperiodicity of past earthquakes as inputs. Using theturbidite catalog from Goldfinger et al. (2017), for example, we calculated thelikelihood of a full-margin megathrust earthquake within the next 50 years tobe ~ 15 %, which is consistent with the value used by the NSHM. Applying thetotal probability theorem, we merge the scaled PDFs to generate total PDFs
of tectonic VLM and the associated hazard curves for the coastal areas. This
final product, when coupled with sea-level rise and tsunami models, enables
community planners to better assess the hazards for coastal communities in
the Pacific Northwest. Our comprehensive probabilistic framework may be
applied to other subduction zones to foster a better understanding of potential
seismic hazards and offer insights to strengthen resilient planning and disaster
preparedness efforts worldwide.
poster 153
Decade-to-Century Scale Vertical Earthquake-Cycle
Deformation at Subduction Zones: Implications for
Cascadia and Nankai
LI, S., Chinese Academy of Sciences, Beijing, China, shaoyangli@mail.iggcas.
ac.cn; CHEN, L., Chinese Academy of Sciences, Beijing, China, lchen@mail.
iggcas.ac.cn
Despite significant progresses in studying subduction earthquake cycles, their
vertical deformation is still not well understood. Here, we use a generic viscoelastic earthquake-cycle model that has recently been validated by horizontal
observations to explore the dynamics of vertical earthquake-cycle deformation. Subjective to two dimensionless parameters (i.e., the ratio of earthquake
recurrence interval T to mantle Maxwell relaxation time tM (T/tM) and theratio of downdip seismogenic extent D to elastic upper plate thickness Hc (D/Hc)), our modeled viscoelastic deformation shows significant spatiotemporaldeviations from the simple time-independent elastic solution. Caution thus
should be exercised in interpreting fault kinematics with vertical observations
if ignoring Earth’s viscoelasticity. By systematically exploring the two parameter spaces, we further investigate three vertical characteristics, i.e., the pivot
line near the coast (CPL), the uplift zone (UZ) landward above the downdip
seismogenic extent, and the secondary subsidence zone (SSZ) in the backarc region. We find that they all can be time-dependent, influenced by D/Hc
and T/tM. CPL location and UZ width are mainly controlled by D/Hc and T/
tM, respectively. The presence of SSZ is found prevalent during the interseismic phase due to viscous mantle flow driven by ongoing megathrust locking,www.srl-online.org•

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April 2024consistent with observations in Cascadia and Nankai. The maximum uplifting rate of UZ and maximum subsiding rate of SSZ are likely controlled by
the plate convergence rate inferred from the observations in Cascadia andNankai. These findings suggest that vertical crustal deformation bears fruitful information about subduction-zone dynamics and are potentially used
for inversions after careful forward validations, deserving properly-designed
monitoring.
poster 154
Assimilation of Vertical Land Movement Observations andModels to Support Sea Level Rise Planning Along theShorelines of the Cascadia Subduction Zone
MILLER, I. M., University of Washington, Washington, USA, immiller@
uw.edu; SCHMIDT, D., University of Washington, Washington, USA, dasc@
uw.edu; PEARSON, A., University of Washington, Washington, USA, aerp@
uw.edu; KIM, J., University of Washington, Washington, USA, jeykim@
uw.eduDeformation associated with the Cascadia Subduction Zone (CSZ) drives
complex and highly variable patterns of vertical land movement (VLM), thatcan locally modify expected sea level trends, and therefore complicate thedevelopment of, and confidence in, sea level rise projections. Relative sea levelprojections for Washington State utilized vertical land movement estimatesderived from multiple sources, including continuous GPS databases, a singledifferencing approach using tide-gauge data, and repeat leveling of survey
control monuments near highways.The observations were assimilated with atectonic deformation model of the Cascadia Subduction Zone to develop a
best-fit surface for the study area, along with its associated uncertainty. The
best fit VLM surface and its uncertainty was principally guided by the observations; but in locations with sparse data, the tectonic deformation model
dominates the fit of the surface. The results suggest considerable variability incoastal vertical land movement in coastal Washington State, ranging from 0-3
mm/yr over spatial scales of 10s-of-kms. Using a Monte Carlo approach, vertical land movement estimates and their uncertainties are integrated into sea
level projections at high resolution, and the variability in vertical land movement translates into spatial differences in projected relative sea level change of~0.3 m by 2100. The analysis was limited in a variety of ways, though: Perhaps
most importantly the VLM estimates derived with this approach relied oninterseismic VLM observations, and therefore did not model possible future
VLM that might influence relative sea level along the shoreline of the CSZ. A
new assessment, supported by NSF through the Cascadia CoPes Hub, uses
more robust approaches, updated observational data sets, and will provide
new insights about relative sea level patterns and projections across the entire
shoreline of the CSZ, including a probabilistic approach to the impact of amegathrust earthquake. The work can provide a template for sea level riseplanning in other regions of the world with active tectonic margins.
poster 155
Complex Earthquake Deformation Drives Relative SeaLevel Change Where Oblique Contraction Focuses Rock
Uplift West of the Fairweather Fault, Southeast Alaska
WITTER, R., U.S. Geological Survey, Alaska, USA, rwitter@usgs.gov;
KELSEY, H., California State Polytechnic University, Humboldt, California,
USA, hmk1@humboldt.edu; LEASE, R., U.S. Geological Survey, Alaska, USA,rlease@usgs.gov; BENDER, A., M., U.S. Geological Survey, Alaska, USA,abender@usgs.gov; SCHARER, K., U.S. Geological Survey, California, USA,kscharer@usgs.gov; HAEUSSLER, P., U.S. Geological Survey, Alaska, USA,pheuslr@usgs.gov; BROTHERS, D. S., U.S. Geological Survey, California,
USA, dbrothers@usgs.gov
Along the Yakutat-(Pacific)-North America plate boundary in southeast
Alaska, episodic earthquake deformation controls relative sea-level (RSL)change by driving rapid rock uplift along Earth’s fastest slipping (≥49 mm/yr)
ocean-continent transform fault, the Fairweather fault. Between Icy Point andLituya Bay, the near-vertical Fairweather fault focuses rock uplift and rapid
right-lateral slip by accommodating both vertical and fault-parallel strain during ruptures with a substantial vertical-slip component and separate, predominantly strike-slip events. We use 1-m resolution digital elevation models andoffshore seismic reflection profiles to map active faults and uplifted marine
and fluvial terraces, and document past reverse fault earthquakes with a maximum of 3–5 m coseismic uplift per event. We differentiate the tectonic fromthe glacial isostatic contribution to RSL over the past 7 ka by comparing RSL
curves at Icy Point and tectonically stable Icy Strait. Radiocarbon and luminescence dating provide timing to estimate 4.6–9.0 mm/yr Holocene rock

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uplift rates. These rates result from plate-boundary strain that is partitioned
onto west-verging reverse faults that form, together with the steeply dipping
Fairweather fault, a 10-km-wide, asymmetric, positive flower structure along
a 20°, 30-km-long restraining double bend in the Fairweather fault. The principal reverse fault in the flower structure is the offshore, blind Icy Point-Lituya
Bay fault, above which 9–12 uplifted marine shorelines imply Holocene ruptures every 460–1040 years. Evaluated over a range of dips, the uplift on thisreverse fault implies a maximum of 3.1–10 m dip-slip per event and estimatedearthquake magnitudes of Mw 7.0–7.5. Our findings suggest that, first, obliqueslip on the Fairweather fault at seismogenic depths occurs with and without
co-rupture on the reverse fault. Second, sudden vertical land movements during earthquakes can dominate RSL changes along restraining bends in strikeslip plate boundaries. Therefore, projections of global sea level rise also must
include regional tectonic vertical deformation along plate boundaries.

Seismic Monitoring, Modelling and Management Needed
for Geothermal Energy and Geologic Carbon Storage
Oral Session • Thursday 2 May • 8:00 am PacificConveners: Erkan Ay, Shell (Erkan.Ay@shell.com); Kai Gao,
Los Alamos National Laboratory (kaigao@lanl.gov); Chet
Hopp, Lawrence Berkeley National Laboratory (chopp@lbl.
gov); Lianjie Huang, Los Alamos National Laboratory (ljh@lanl.gov); Federica Lanza, ETH Zürich (federica.lanza@
sed.ethz.ch); Nori Nakata, Lawrence Berkeley National
Laboratory (nnakata@lbl.gov); Annemarie MuntendamBos, Delft University of Technology (A.G.MuntendamBos@tudelft.nl); Kristine L. Pankow, University of Utah(pankowseis2@gmail.com); Ryan Schultz, ETH Zürich (ryan.
schultz@sed.ethz.ch); Nana Yoshimitsu, Kyoto University(yoshimitsu.nana.6i@kyoto-u.ac.jp); Yingcai Zheng,
University of Houston (yzheng24@central.uh.edu)
DOE’s Best Practices for Addressing Induced Seismicity
Associated With Enhanced Geothermal Systems
MAJER, E., Lawrence Berkeley National Laboratory, California, USA,elmajer@lbl.gov; ROBERTSON-TAIT, A., GeothermEx, California, USA,
Ann1@slb.com; NELSON, J., Wilson IHRIG, California, USA, jnelson@
wilsonihrig.com; SAVY, J., Consultant, California, USA, jbsavy@gmail.com;
WONG, I., Lettis Consultants International, California, USA, wong@lettisci.
com
In 2004 the U.S. Department of Energy (DOE) initiated and participated in
an international activity to develop a “Protocol” to address both technicaland public acceptance issues surrounding Enhanced Geothermal Systems(EGS)-induced seismicity. This resulted in an International Energy Agency(IEA) Protocol in 2009 followed by a DOE Protocol in 2012 which served as
general guidelines to geothermal operators for the siting, design and operation of EGS systems. The guidance was also used by regulators and to informthe public. Although the DOE Protocol was used and followed by several
geothermal operators, the DOE felt a complementary “Best Practices” document was needed and which was developed in 2014. Much has happened in
the world of induced seismicity in the past decade resulting in an update of
the “Best Practices” document. The increased attention to induced seismicity
worldwide, in general, has led to a dramatic increase in research in the causes,
impact, and control of induced seismicity. Increased attention has not only
been placed on EGS induced seismicity but also on other technologies requiring fluid injection. Notable examples of significant induced seismicity havebeen from wastewater disposal from oil and gas operations, carbon captureand sequestration, and various waste fluid disposal projects. Like the Protocol,
the updated Best Practices is intended to be a living document and to supplement the existing DOE Protocol. It reflects the state-of-the-art knowledge andpractices, both technical and non-technical. It is not, however, intended to bea state-of-the-science document. The focus is on current proven technologies.
As methods, experience, knowledge, and regulations change, so will the Best
Practices.

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Geophysical Monitoring of Anthropic Underground
Operations in Italy: An Operative Center for Risk
Mitigation.
SACCOROTTI, G., Istituto Nazionale di Geofisica e Vulcanologia, Pisa, Italy,
gilberto.saccorotti@ingv.it; ANDERLINI, L., Istituto Nazionale di Geofisica e
Vulcanologia, Bologna, Italy, letizia.anderlini@ingv.it; ANSELMI, M., Istituto
Nazionale di Geofisica e Vulcanologia, Roma, Italy, mario.anselmi@ingv.it;
BRAUN, T., Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy, thomas.
braun@ingv.it; CACIAGLI, M., Istituto Nazionale di Geofisica e Vulcanologia,
Bologna, Italy, marco.caciagli@ingv.it; CARANNANTE, S., Istituto Nazionale
di Geofisica e Vulcanologia, Milano, Italy, simona.carannante@ingv.it;
ERRICO, M., Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy,
maddalena.errico@ingv.it; FAMIANI, D., Istituto Nazionale di Geofisica e
Vulcanologia, Roma, Italy, daniela.famiani@ingv.it; GARCIA, A., Istituto
Nazionale di Geofisica e Vulcanologia, Bologna, Italy, alexander.garcia@ingv.
it; MOLINARI, I., Istituto Nazionale di Geofisica e Vulcanologia, Bologna,
Italy, irene.molinari@ingv.it; MORELLI, A., Istituto Nazionale di Geofisica e
Vulcanologia, Bologna, Italy, andrea.morelli@ingv.it; SALIMBENI, S., Istituto
Nazionale di Geofisica e Vulcanologia, Bologna, Italy, simone.salimbeni@ingv.
it; VASSALLO, M., Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy,maurizio.vassallo@ingv.it; ZACCARELLI, L., Istituto Nazionale di Geofisica e
Vulcanologia, Bologna, Italy, lucia.zaccarelli@ingv.it; ZERBINATO, P., Istituto
Nazionale di Geofisica e Vulcanologia, Bologna, Italy, paolo.zerbinato@ingv.it
Following the deadly M≈6 earthquakes that struck the Emilia-Romagna
region (northern Italy) in May 2012, public concern raised whether thoseshocks could have been triggered by the nearby activities of oil and gas production and storage. In response to that concern, in 2014 and 2016 the Italian
Oil & Gas Safety Authority (DGS-UNMIG) issued guidelines (ILG) regulating procedures, responsibilities and roles in the monitoring of georesources
exploitation, specifically hydrocarbon exploitation, waste-water injection,
natural gas storage and geothermal energy production. The ILG define standards for the monitoring of pore pressure, microseismicity and ground deformation and guide the application of a four-stage traffic light protocol (actually applied exclusively for reinjection of waste water), depending on location,
magnitude, and peak ground motion of the recorded seismicity. Within thisframework, the Italian National Institute of Geophysics and Volcanology(INGV) instituted in 2017 the Center for the Monitoring of Subsoil Activities(CMS), as the structure dedicated to the collection, analysis, interpretationand modeling of data associated with the anthropic exploitation of georesources. We present the structure and operating principles of the CMS, its IT
architecture, and the organization of the monitoring procedures. Such principles were designed for delivering reliable products supporting the decision
tools adopted by authorities for risk management. We also discuss the main
criticalities thus far emerged, which concern: [1] the unbiased assessment ofbackground seismicity when pre-existing, nearby active plants are already inoperation; [2] the discernment between tectonic and triggered seismicity, incase the monitored activity is located in a tectonically active region (as mostly
happens in Italy); [3] the robust evaluation of uncertainties in all the monitored parameters; [4] the possible overlapping between the attention areas ofadjacent reservoirs, possibly operated by different subjects; [5] The procedures
to be adopted for activities (namely: CO2 storage) not yet foreseen by the ILG.
An Open-Source Tool for Operational Forecasting ofInduced Seismicity (Orion)
KROLL, K., Lawrence Livermore National Laboratory, California, USA,kroll5@llnl.gov; SHERMAN, C. S., Lawrence Livermore National Laboratory,
California, USA, sherman27@llnl.gov; GEFFERS, G., Lawrence Livermore
National Laboratory, California, USA, geffers1@llnl.gov; WANG, C.,
Lawrence Livermore National Laboratory, California, USA, wang140@llnl.
gov; HE, D. J., Lawrence Livermore National Laboratory, California, USA,
he12@llnl.gov; LAYLAND-BACHMANN, C. E., Lawrence Berkeley National
Laboratory, California, USA, cebachmann@lbl.gov
Forecasting induced seismicity activity is one of the challenges facing thegrowing fields of geothermal energy production and carbon sequestration.
Historically, the forecasting process has required significant effort fromexperts in seismology, geomechanics, and reservoir engineering in order tomanage data, evaluate models of subsurface processes, and to calibrate andinterpret the results from a range of forecasting models. The Operational
Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by the National
Risk Assessment Partnership (NRAP) and the Science-informed Machine
Learning for Accelerating Real Time Decisions in Subsurface Applications(SMART) Initiative to address these issues. One of the major design goals for
ORION was to build a tool that is responsive to the needs of users ranging

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forecasting engine. The forecasting engine takes available reservoir property,
well and fluid injection, and observed seismic catalog data as inputs and produces a set of temporal and spatio-temporal seismic forecasts.
The in-situ fluid pressurization rate (dpdt) is one of the key factors thatdrives the forecast model predictions. Rather than evaluating a full-physics
model of the reservoir, ORION has options that allow the user to estimate
dpdt using efficient closed-form solutions (e.g. the Theis model), machinelearning models, other reduced order models, or to interpolate pre-computed
results from external tools. The forecasting engine implements multiple,
redundant forecasting methods that are based on statistical principles and/or
physical models. ORION uses a decision-tree model to mediate between thesedifferent forecasts and produce an ensemble model.
This work was performed under the auspices of the U.S. Departmentof Energy by Lawrence Livermore National Laboratory under contract
DE-AC52-07NA27344.
Forecasting the Next Largest Earthquake During EGS
Stimulations
GRIGORATOS, I., ETH Zurich, Zurich, Switzerland, iason.grigoratos@sed.
ethz.ch; KWIATEK, G., GFZ Potsdam, Potsdam, Germany, kwiatek@gfzpotsdam.de; WIEMER, S., ETH Zurich, Zurich, Switzerland, stefan.wiemer@
sed.ethz.ch
Most traffic-light systems (TLS) related hydraulic fracturing stimulations still
adopt the maximum observed magnitude as the decisive metric to aid decision making by stakeholders. However, waiting for the red-light magnitude to
be observed is not a proactive stance, especially given that jumps of up to two
magnitude units are evidently common enough between events. Clearly there
is a need to actively forecast rather than to passively record the size of the next
largest earthquake (NLE). In this study, we demonstrate that we can do justthat using an ensemble of 6 existing models from the literature designed withsimilar purposes in mind (Shapiro et al. 2013; McGarr 2014; Mendecki 2016;van der Elst et al. 2016; Galis et al. 2017; Cao et al. 2020). Following a logictree approach, these 6 models are calibrated and dynamically weighted in nearreal-time using as sole inputs the initial parts of the earthquake catalogs andthe reported injection rates. The proposed forecasting tool is tested against
19 past stimulations from 9 different Enhanced Geothermal Systems aroundthe world (Helsinki, Basel, Soultz, Cooper Basin, Pohang, FORGE, Paralana,
Newberry). Overall, the results indicate a consistent (across sites and time)and accurate estimation of the next largest magnitude with a tight uncertainty range (1σ) of less than 0.5 magnitude units. Our proposed framework
underestimated the next largest magnitude only in two occasions (out of the
19 stimulations), while reliably maintaining a tight safety margin of less than
1 magnitude unit. We recommend that the forecasted NLE replaces the largest
observed magnitude as the default metric adopted by future TLS governing
any type of fluid-injection operation.
Stress-Based Forecasting of Seismicity Induced by
Geothermal Operations and CO2 Storage.
AVOUAC, J., California Institute of Technology, California, USA, avouac@
caltech.edu
The need for more and cleaner energy and for sequestration of large quantities
of CO2 in geological formations to mitigate climate change is driving various
activities involving extracting or injecting fluids from the subsurface. These
activities induce deformation and can eventually activate faults. Fault slip canbe either seismic or aseismic. Fault activation can be a benefit, for example inthe context on geothermal energy as it is a way to enhance fluid circulation.
It is also a source of hazard as significant, potentially damaging earthquakes
might be induced as has been observed a number of geothermal operations. In
the context of carbon dioxide or gas storage, faulting of the caprock could, in
addition to exposing surface infrastructure to seismic hazard, jeopardize themechanical integrity of a reservoir. We will review recent progress made inunderstanding these processes based on the study of case examples where we
combine remote sensing, GPS geodesy, and seismic monitoring on the observational side and us a versatile modelling framework to relate reservoir operations to deformation and seismicity. The model accounts for the possibility oftriggering faulting and earthquakes due to pore-pressure diffusion and poroelastic stress changes. It accounts for the time-dependent nature or earthquake
nucleation and for the possibility that the faults might be in a relaxed stateof stress of stress. We will show that this modelling applies to a wide range
of operations and can provide the foundation for effective methods to forecast earthquakes and faulting due to anthropogenic activities. These methods

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could in principle be used to mitigate and eventually control fault activationand seismicity during reservoir operations.
Factors Controlling Rate and Magnitudes of Induced
Seismicity
KIM, T., California Institute of Technology, California, USA, tkim5@caltech.
edu; AVOUAC, J., California Institute of Technology, California, USA,avouac@caltech.edu
Advancements central to the world’s transition to a greener economy such as
geothermal energy are hampered by a lack of understanding and control of the
maximum magnitude event. We develop a physical model for induced seismicity rate and identify the dominant factors on induced event magnitudes in
the context of a control and optimization framework that may be utilized forsophisticated design of injection schedules.
Induced seismicity observed during Enhanced Geothermal Stimulation(EGS) at Otaniemi, Finland is reproduced by a physical model based on porepressure diffusion and rate-and-state friction. The physical model produces
simulations closest to the observations when assuming rate-and-state friction
for shear failure with a diffusivity matching the pressure build-up at the wellhead at onset of injections. At the same time, pressure drawdown immediately
following shut-in’s is best modelled with a lower diffusivity, indicating a significant change in diffusivity through fracture opening and closure. The physicalmodel shows that the time-dependent nucleation process significantly affects
the spatial evolution of seismicity. This implies that neglecting rate-and-state
effects can bias estimates of fluid diffusivity from the seismicity triggering
front. The potential of the model to serve as a forecasting tool is demonstrated
by a pseudo-forecast that closely matches the entire seismicity rate history,
using only the first injection stage as the training period.
Next, we focus on the magnitude-frequency distribution of seismicity
and how they may correlate to the injections. We observe a dominant, negative correlation of the b-value and Mmax to depth, and additional negative
correlations to cumulative injected volume. We observe a non-linear relationship between magnitudes and distance from the injection source, similarly
to the geothermal stimulation operation in Basel. We aim to identify thedominant factor from injections and possibly the initial conditions of thenucleation sources that is consistent with the non-linear relationship of themagnitudes to distance.
How to Tame an Earthquake (Analogue)
SCHULTZ, R., ETH Zurich, Zürich, Switzerland, ryan.schultz@sed.ethz.ch
Subsurface fluids are important to earthquake physics since they influence
every phase of the earthquake cycle: from inducing earthquakes, generating
slow slip, dynamically weakening a fault, to producing afterslip. Despite thisprominent role, comparatively little thought has been directed toward intentionally controlling fault slip. I take the spring-slider as the simplest analogue
for an earthquake and train a deep reinforcement learning agent to design
fluid injection that reins-in slip motion. These reining algorithms can mitigate
stick-slip instability via a three-step process. First, by injecting to induce slip
nucleation; second, by harnessed withdrawal that governs slip speed; third,
by injection-driven steady-state sliding. I discuss the relevance to prior studies, implications for induced seismicity mitigation, and future potential forearthquake control. These results suggest that earthquake (analogues) could
be tamed with carefully designed injection policies.
Picoseismic Response of Hectometer-Scale Fracture
Systems to Stimulation With Cm-Scale Resolution Under
the Swiss Alps, in the Bedretto Underground Laboratory
OBERMANN, A., ETH Zurich, Zurich, Switzerland, anne.obermann@sed.ethz.ch; ROSSKOPF, M., ETH Zurich, Zurich, Switzerland, martina.
rosskopf@erdw.ethz.ch; DURAND, V., ETH Zurich, Zurich, Switzerland,virginie.durand@geoazur.unice.fr; PLENKERS, K., Gesellschaft fürMaterialprüfung und Geophysik mbH, Bad Nauheim, Germany, k.plenkers@
gmug.eu; BRÖKER, K., ETH Zurich, Zurich, Switzerland, kai.broeker@
erdw.ethz.ch; GHOLIZADEH DOONECHALY, N., ETH Zurich, Zurich,
Switzerland, nima.gholizadeh@erdw.ethz.ch; PIO RINALDI, A., ETH Zurich,
Zurich, Switzerland, antoniopio.rinaldi@sed.ethz.ch; MA, X., ETH Zurich,
Zurich, Switzerland, xiaodongma.rocks@gmail.com; VILLIGER, L., ETH
Zurich, Zurich, Switzerland, linus.villiger@sed.ethz.ch; HERTRICH, M.,
ETH Zurich, Zurich, Switzerland, marian.hertrich@erdw.ethz.ch; GISCHIG,
V., ETH Zurich, Zurich, Switzerland, gischigv@ethz.ch; ZAPPONE, A., ETH
Zurich, Zurich, Switzerland, alba.zappone@sed.ethz.ch; MAURER, H., ETH
Zurich, Zurich, Switzerland, hansruedi.maurer@erdw.ethz.ch; WIEMER, S.,

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ETH Zurich, Zurich, Switzerland, stefan.wiemer@sed.ethz.ch; GIARDINI,
D., ETH Zurich, Zurich, Switzerland, domenico.giardini@erdw.ethz.ch
We performed a series of hydraulic stimulations at 1.1 km depth in the
Bedretto underground laboratory in the Swiss Alps. The goal was to achieve
an unprecedented detailed and profound understanding of hydromechanicaland seismic processes during hydraulic reservoir development with a dense
multi-sensor monitoring network. With our seismic network that includes
various sensor types with different sensitivities, we succeeded in characterizing induced seismicity down to the pico-seismicity level (Mw<-4), thus
illuminating details of a complex fracture network more than 100 m fromthe injection locations. Here, we present the experiments and seismic catalogs
as well as a comparative analysis of event number per injection, magnitudes,
b-values, seismogenic index and reactivation pressures. During a first-orderdata analysis, we could make the following observations:-We find that the ultra-high frequency seismic network with custommade AE sensors, allows us to observe seismicity over 3 orders of magnitude
scale. Thanks to collocated accelerometers and acoustic emission sensors, AE
sensors could be calibrated in-situ and adjusted moment magnitudes could be
implemented into the seismic catalog.
-The volume impacted by the stimulations in different intervals differs
significantly with a lateral extent from a few meters to more than 150 m. Most
intervals activated multiple fractures. Only during the stimulation of an interval located next to a dominant shear zone, an extended single fracture wasactivated, which is likely attributed to the dominant shear zone in this area.
The seismic clouds typically propagate upwards towards more permeable,
shallow depth on parallel dipping planes that are consistent with the stressfield and seem to a large extent associated with preexisting open fractures.
-The reactivation pressures hint at hydraulic shearing as the dominant
process, since the elastic fracture opening appears to be mostly aseismic.
-The seismicity shows no distinct deviation from “normal” behavior
with regard to Gutenberg Richter or McGarr.
Characterization of Fracture Activation During EGS
Stimulation Using Waveform Cross-Correlation: An
Example Application at Utah ForgeASIRIFI, R., Texas A&M University, Texas, USA, richard_asirifi@tamu.edu
One of the many technical challenges in the safe stimulation of Enhanced
Geothermal Systems (EGS) is the control of induced seismicity. Fluid injections during simulation may cause induced earthquakes. Microseismicity
analysis provides real-time risk management, and detailed knowledge of activated fracture size, orientation, stress state and seismogenic potential. Due
to subsurface heterogeneity within the reservoir, analysis of microseismicity
is strongly influenced by the surrounding medium. Waveform cross-correlation utilizing the full wavefield of microseismic events, and can significantly
improve the fracture characterization. Here, we apply waveform cross-correlation analysis to microseismic events during stage 3 of 2022 stimulation at the
FORGE site to detect similar event clusters, and asperities with nearly identical waveforms, and obtain improved in-situ seismic parameters. The FrontierObservatory for Research in Geothermal Energy (FORGE) is a geothermal
project located at Milford, Utah, providing pioneer research and insights in
EGS with a comprehensive microseismic monitoring network including nodal
arrays, borehole arrays and DAS fibers. The 2022 stimulation features over
20,000 microseismic events over three stages. We identify ten similar clusters
from cross-correlated waveforms with a minimum CC coefficient of 0.65 fromat least 8 stations. Analysis of cluster propagation and orientation reveals fracture planes with low b values being activated first, suggesting the activation ofa planar structure with similar orientation to natural fractures at this site. We
identify successive activation of different clusters, in particular, some clusters
with larger events were activated post shut-in. To characterize the seismogenic
potentials of different fractures, and their relationship with injection history,
we obtain improved magnitudes based on precise relative magnitude measured from principal component analysis of aligned waveforms, and characterize magnitude-frequency for different fractures
Circulation Experiments at Utah Forge: Post-Shut-in
Fracture Growth Revealed by Limited Near-Surface
Monitoring
NIEMZ, P., University of Utah, Utah, USA, pniemz.seismology@gmail.com;
MCLENNAN, J., University of Utah, Utah, USA, jmclennan@egi.utah.edu;
PANKOW, K. L., University of Utah, Utah, USA, Kris.Pankow@utah.edu;
RUTLEDGE, J., Santa Fe Seismic LLC, New Mexico, USA, rutledge@swcp.

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com; ENGLAND, K., E-K Petro Consulting LLC, Texas, USA, kwengland@
comcast.net
The Utah Frontier Observatory for Research in Geothermal Energy (FORGE)
is a large-scale experimental facility de-risking Enhanced Geothermal
Systems (EGS). Full-scale testing allows the study and development of new
tools, methodologies, and strategies to improve the economic viability of EGS
and mitigate induced seismic activity. After the completion of an injectionproduction well doublet at a depth of 2.5 km within basement rock, four circulation experiments were conducted in July 2023. These experiments showedthat the two wells were successfully connected via the fracture network created during the 2022 stimulation treatments, which were pumped to evaluate
different injection methods required to form a heat exchange system.
We analyze the microseismic activity induced during the circulation
experiments using only five (near-)surface stations of the regional permanent seismic network and state-of-the-art full-waveform-based methods for
detection and location. The microseismicity rates and magnitudes (<M0.45)
induced during the circulation experiments are similar to those observed
during the 2022 stimulations. This was unexpected when considering fluid
flow through pre-stimulated rock volumes. During the circulation experiments, flow data indicated that highly productive reservoir volumes were bothaseismic and seismically active. The seismic activity occurred predominantly
after shut-in of the last two circulation stages. It is attributed to the complex
dynamics of opening, further propagating, and closing of hydraulic fracturesduring circulation in the absence of major conductive features that allow for
substantial flow into the production well. The complexity of the fracture network created within a granitoid rock, such as that at FORGE, can result inpoorly stimulated volumes within the zones that are mapped by large-scale
microseismic clouds. Hence, the presence of microseismic activity may not
guarantee the presence of stimulated fractures that can enable efficient fluid
flow, and the lack of microseismic activity does not imply the lack of stimulated fractures.
Geophysical Monitoring for Feeding Decision Support
Tools: The Crucial Role of Uncertainty for a Sound
Management of Induced Seismicity
GARCIA, A., Istituto Nazionale di Geofisica e Vulcanologia, sezione di
Bologna, Bologna, Italy, alexander.garcia@ingv.it; ZAHEER, A., Università di
Bologna, Bologna, Italy, abdulmoiz.zaheer2@unibo.it; FAENZA, L., Istituto
Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, Bologna, Italy, licia.
faenza@ingv.it; DANESI, S., Istituto Nazionale di Geofisica e Vulcanologia,
Sezione di Bologna, Bologna, Italy, stefania.danesi@ingv.it; BRAUN, T.,
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Roma 1, Arezzo,
Italy, thomas.braun@ingv.it; ERRICO, M., Istituto Nazionale di Geofisica e
Vulcanologia, Sezione di Bologna, Bologna, Italy, maddalena.errico@ingv.it;
ZERBINATO, P., Istituto Nazionale di Geofisica e Vulcanologia, Sezione di
Bologna, Bologna, Italy, paolo.zerbinato@ingv.it
Geophysical monitoring is a frequently used tool to manage the potential
effects of underground anthropogenic activities. Different parameters such as
earthquake hypocentral location and magnitude, peak ground motions, andground deformation, among others, are growingly used as input for decision
support tools (e.g., traffic-light systems) that are implemented for managing
induced seismicity. Such decisional systems define the operative reactions to
be enacted once a seismic event occurs near a certain anthropogenic underground activity. The outcome of the geophysical monitoring in such cases iscritical, since any decision taken, on the basis of the information provided by
the monitoring data, involves a great deal of responsibility. In this context,
any effort for a reliable evaluation of the parameters feeding the decision support tool is as important as the determination of its “near-to-reality” uncertainty. Here, by ‘near-to-reality’ uncertainty, we refer not only to formal errors
resulting from fitting a given model but also to the effects of all the ‘known
unknowns’ in the modeling process. A careful assessment of uncertainties
becomes crucial for rational decision making. In this work we analyze different sources of uncertainty that can be relevant for the determination of different geophysical parameters generally used for managing induced seismicity. We use a logic-tree-based ensemble modeling approach for framing the
problem in a decision-making context. We find that often-neglected epistemic
uncertainties (i.e., arising when considering alternative plausible modelingapproaches or data) can be considerably larger and more representative of thestate of knowledge than the standard errors that are usually reported. Due tothe potential impact of decision making under uncertainty, we stress that an
objective evaluation of epistemic uncertainties associated with any parameterused to support decisional processes must be a priority for the scientific community. The implementation of this approach is framed within the activities of
the INGV’s Center of Monitoring Underground Activities in Italy.

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B-Positive for Induced Seismicity Catalogs With TimeVarying Incompleteness? Proceed With Caution.
MUNTENDAM-BOS, A. G., Delft University of Technology, Delft,
Netherlands, a.g.muntendam-bos@tudelft.nl
The relative frequency of large versus small earthquakes is characterized by theb-value of the earthquake magnitude-frequency distribution. The b-positive
method, recently introduced by Van der Elst (2021) to estimate the b-value intransient incomplete catalogs, is based on the Laplacian distribution of magnitude differences. The method was developed to handle time-varying incompleteness in aftershock sequences and was found to be much more robust to
unknown or variable incompleteness due to network limitations. However,
the method still requires some minimum cutoff value M’c above which theb-value can be accurately derived.
More recently, the method has also been applied to induced seismicity
sequences with time-varying incompleteness in the catalogs. These assessments generally adopt small minimum cutoff values, similar to the values
presented for aftershock sequences. The results show significantly different
time-variations in b compared to the traditional Gutenberg-Richter exponential maximum likelihood estimates. However, turns out these low cutoff values
lead to significant underestimations of the actual b-values. Closer analysis on
synthetic catalogs shows that a significant trade-off exists between the minimum value M’c and the magnitude range over which incompleteness occurs,
the scale parameter σ describing how quickly 100% detection is achieved. As
time-varying incompleteness may also imply time-varying σ, the implication
for the interpretation of time-varying b-values is very significant. Analysis of
the Groningen induced seismicity catalog demonstrates this further. As theb-value is one of the critical parameters controlling seismic hazard and risk,
the b-positive estimate should thus be handled with due care.
Heimdall: A Graph-Based Seismic Detector and Locator for
Microseismicity
BAGAGLI, M., University of Pisa, Pisa, Italy, matteo.bagagli@dst.unipi.
it; GRIGOLI, F., University of Pisa, Pisa, Italy, francesco.grigoli@unipi.it;
BACCIU, D., University of Pisa, Pisa, Italy, davide.bacciu@unipi.it
The application of Machine Learning (ML) has significantly transformed
traditional tasks in observational seismology such as phase picking andassociation, earthquake detection and location, and magnitude estimation.
Despite progress, the use of ML-based classical workflows in microseismic
data analysis still poses challenges. We present HEIMDALL, a grapH-basedsEIsMic Detector And Locator for microseismicity, powered by the latest
advancements in Deep Learning (DL) methodologies. HEIMDALL utilizes
an attention-based, spatiotemporal graph-neural network for detecting seismic events. It also implements a waveform-stacking approach for event location, leveraging output probability functions over a dense regular grid. We
tested HEIMDALL using a month-long waveform dataset from December
2018, obtained during the COSEIMIQ project (active from December 2018
to August 2021) at the Hengill Geothermal Field in Iceland. This dataset is
optimal for testing seismic event detection and location algorithms due to its
high seismicity rate (over 12,000 events in about two years) and the presenceof burst sequences with very short interevent times (e.g., less than 5 seconds).
We evaluated HEIMDALL’s performance by comparing the catalog we
generated with those produced by two different DL methods, as well as one
manually created by ISOR for the same timeframe. The DL algorithms tested
included (i) MALMI, a waveform-based location algorithm, and the recent(ii) GENIE graph-neural-network algorithm. To optimize GENIE for our
specific study area, we repicked continuous waveforms using the PhaseNet
algorithm and trained a new model. We discuss the advantages and limitations of each method and explore potential enhancements for detecting andlocating microseismic events, with a focus on monitoring induced seismicity
at Enhanced Geothermal System (EGS) sites.
Characterizing Subsurface Structures for Geologic Carbon
Storage at Iron Mountain in Utah
LI, D., Los Alamos National Laboratory, New Mexico, USA, davidzli@lanl.
gov; HUANG, L., Los Alamos National Laboratory, New Mexico, USA, ljh@
lanl.gov; GAO, K., Los Alamos National Laboratory, New Mexico, USA,kaigao@lanl.gov; CHEN, B., Los Alamos National Laboratory, New Mexico,USA, bailianchen@lanl.gov; ZHENG, Y., University of Houston, Texas, USA,yzheng24@central.uh.edu; WU, B., University of Houston, Texas, USA,bwu8@central.uh.edu; EL-KASSEH, G., New Mexico Tech, New Mexico,USA, george.el-kaseeh@nmt.edu; MOODIE, N., University of Utah, Utah,

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USA, nathan.moodie@m.cc.utah.edu; JAGNIECKI, E., Utah Geological
Survey, Utah, USA, ejagniecki@utah.gov
Subsurface structure imaging and fault detection are crucial for site characterization and risk assessment of geologic carbon storage. We use 2D surface
seismic data acquired at Iron Mountain, Utah, USA to characterize subsurface
structures. These seismic data were acquired using vibroseis sources along
three 2D walkaway lines at the surface of the survey area. The source spacing of each survey line is about 91 m and the receiver spacing is about 45 m.
The lengths of the seismic lines are around 9 km. We build 2D velocity models along three seismic survey lines using first-arrival traveltime tomography
and prestack depth migration velocity analysis. We then use prestack depth
migration to produce high-resolution images of subsurface structures. Finally,
we employ a machine learning algorithm to delineate faults on the migration
images. Our results provide valuable information for studying the feasibilityof geologic carbon storage at Iron Mountain in Utah.
3D Fault Detection on a Seismic Migration Image at theLightning Dock Geothermal Area
HUANG, L., Los Alamos National Laboratory, New Mexico, USA, ljh@lanl.
gov; WU, B., University of Houston, Texas, USA, bwu8@central.uh.edu; GAO,
K., Los Alamos National Laboratory, New Mexico, USA, kaigao@lanl.gov; LI,
D., Los Alamos National Laboratory, New Mexico, USA, davidzli@lanl.gov;
ZHENG, Y., University of Houston, Texas, USA, yzheng24@central.uh.edu;
SWYER, M., Cyrq Energy, Inc, Nevada, USA, michael.swyer@cyrqenergy.
com
Lightning Dock Geothermal (LDG), is an operating power plant in Hidalgo
County, southwest New Mexico, USA. LDG LLC conducted a 3D activesource surface seismic survey in 2011 using accelerated weight drop sources
for subsurface characterization. The 3D seismic survey covered a region of
approximately 4 km in the east-west direction and approximately 3.5 km in
the north-south direction. This 3D seismic survey used a simple square pattern to distribute source and receivers. The survey used a total of 17 receiverlines with a quasi-equal spacing of 660 ft and with an orientation of the northsouth direction, and a total of 21 source lines with a quasi-equal spacing of 600
ft and with an orientation of the east-west direction. Within the source lines
or the receiver lines, the source interval is 110 ft and the receiver interval is
220 ft. We perform migration velocity analysis and prestack depth migration
to produce a high-resolution subsurface image, and then delineate faults on
the migration image using a machine learning method. Our results provide
valuable information for siting new wells to improve the geothermal energy
production at the Lightning Dock geothermal area.

Seismic Monitoring, Modelling and Management Needed
for Geothermal Energy and Geologic Carbon Storage[Poster Session]
Poster Session • Thursday 2 May
Conveners: Erkan Ay, Shell (Erkan.Ay@shell.com); Kai Gao,
Los Alamos National Laboratory (kaigao@lanl.gov); Chet
Hopp, Lawrence Berkeley National Laboratory (chopp@lbl.
gov); Lianjie Huang, Los Alamos National Laboratory (ljh@lanl.gov); Federica Lanza, ETH Zürich (federica.lanza@
sed.ethz.ch); Nori Nakata, Lawrence Berkeley National
Laboratory (nnakata@lbl.gov); Annemarie MuntendamBos, Delft University of Technology (A.G.MuntendamBos@tudelft.nl); Kristine L. Pankow, University of Utah(pankowseis2@gmail.com); Ryan Schultz, ETH Zürich (ryan.

schultz@sed.ethz.ch); Nana Yoshimitsu, Kyoto University(yoshimitsu.nana.6i@kyoto-u.ac.jp); Yingcai Zheng,
University of Houston (yzheng24@central.uh.edu)
poster 88
Applying Dynamic Fracture Propagation and Activation
Models to Microseismicity Generation in a Geothermal
Development Project at Blue Mountain, Nevada
AWE, E., Texas A&M University, Texas, USA, eaawe86@gmail.com
EQdyna is a Finite Element Method (FEM) code for simulating dynamic
fracture propagation and seismic wave propagation in elastic or elastoplastic
medium. In this project EQdyna is applied towards the microseismic activity that is caused by hydraulic fracturing (HF), specifically focusing on the
propagation of the opening fractures and its effect on nearby shear fractures.
Using EQdyna, pre- selected propagation distances are varied to investigate
the effects on the characteristics of the induced events and observed seismic
signals. The induced events occurring here are believed to be a result of theshearing that occurs on pre-existing natural fractures (NF) in response to the
dynamic stresses that are induced as HF propagation occurs. A three-case scenario is explored to determine the most likely cause for micro-seismicity thatis observed in a geothermal development project at Blue Mountain, Nevada
due to the stimulation of a geothermal well system. In these scenarios HF
propagation will be explored using propagation termination points that arelocated just before, directly on (fracture network amalgamation), or just after
a NF is encountered, it is believed that these scenarios will produce different microseismic distributions due to different driving forces. Distributed
Acoustic Sensing (DAS) technology will be integrated into the model throughutilization of a strategically placed seismic station network that will act as asensing cable placed parallel to a specified NF. The goal of this investigation
is to determine the scenario that can most be associated with the microseismicity occurring at the site, by creating a model containing a geometry andproperties similar to what exists at the real-world field site.
poster 89
End-to-End High-Quality Geophysics Workflow to Analyze
Das-Acquired Induced Seismicity
CALVEZ, J. L., SLB, Texas, USA, JCalvez2@slb.com; MIZUNO, T., SLB, Texas,
USA, tmizuno@slb.com; AY, E., Shell, Texas, USA, ERKAN.AY@SHELL.
COM
Cost-effective, easy to deploy make distributed acoustic sensors a tool ofchoice for long-term induce seismic monitoring either independently or in
conjunction to 3C sensors. We propose a DAS-based end-to-end workflow for
induced seismic monitoring operation.
First, to maximize the rock volume monitored while minimizing assets
deployed, we perform a survey modeling leveraging an accurate velocity
model while including attenuation and background noise previously gathered.
Second, we model the waveforms associated to the various types of failure
mechanisms likely to occur considering known geological and geomechanicaldata so to compare with waveforms issued from the failure locii as seen by
the sensors. Third, we use a simulator of DAS-acquired passive seismic data
observed in previous similar jobs to output data at real-time speed to verify theviability and effectiveness of the acquisition geometry and the processing system consider to monitor the long-term passive seismic activity. Fourth, knowing that an accurate velocity model is required to properly estimate source
location, source parameters, and source mechanism of a detected microseismic event, we use a new method to simultaneously invert for the hypocenterand the velocity model to provide a robust long-term monitoring workflow.
Thus, bypassing the repeated use of man-made, man-controlled sources tocalibrate the velocity model while including scenarios when the velocity fieldevolves with time due to induced changes associated with operations. Fifth, weleverage a new real-time processing flow that involves image processing techniques applied to induced seismic datasets. This approach mimics an expert
geophysicist’s view to identify passive seismic events acquired using DAS datataking advantage of an algorithm integrating both image processing and traditional geophysical processing.
poster 90
Application of State of Stress Analysis Tool (SoSAT) to
Estimate Risk of Induced Seismicity From CO2 Injections
SAXENA, S., Pacific Northwest National Laboratory, Washington, USA,swasti9226@gmail.com; HAAGENSON, R. J., Pacific Northwest National
Laboratory, Washington, USA, ryan.haagenson@pnnl.gov; WANG, W.,

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Pacific Northwest National Laboratory, Washington, USA, wenjing.wang@
pnnl.gov; APPRIOU, D., Pacific Northwest National Laboratory, Washington,
USA, Delphine.Appriou@pnnl.gov; BURGHARDT, J. A., Pacific Northwest
National Laboratory, Washington, USA, jeffrey.burghardt@pnnl.gov
The sequestration, storage, and utilization of anthropogenic carbon emissions
is projected to play a major role in mitigating the accumulation of greenhouse gases worldwide. CO2 can be injected under supercritical fluid conditions into subsurface geologic units like saline aquifers, basalt formations,depleted/matured oil and natural gas reservoirs. The focus of this study is todemonstrate the application of State of Stress Analysis Tool (SoSAT), developed under the National Risk Assessment Partnership (NRAP), in estimating
the probability of failure due to hydraulic fracture or seismic fault activation,
both of which are major risks anticipated under incremental CO2 injection
pressure. SoSAT uses a Bayesian approach for geomechanical uncertainty
quantification and risk assessment. Various constraints, including those basedon stress measurement, regional stress environment, and borehole breakouts,
can be applied to constrain the posterior probability distribution of in-situ
stresses. This allows for the computation of the risk associated with induced
seismicity. The ultimate goal is to create a seismic risk index map for the western USA for the Carbon Utilization and Storage Partnership (CUSP) which
will provide guidance on CO2 injection operations for commercial-scale carbon storage.
poster 91
Toward Improving the Assessment of Induced Earthquakes
in the Rome Trough of West Virginia
CARPENTER, S., University of Kentucky, Kentucky, USA, seth.carpenter@uky.edu; SCHMIDT, J. P., University of Kentucky, Kentucky, USA, jon.
schmidt@uky.edu; HICKMAN, J. B., University of Kentucky, Kentucky, USA,john.hickman@uky.edu; SPARKS, T. N., University of Kentucky, Kentucky,
USA, sparks@uky.edu; GREB, S., University of Kentucky, Kentucky, USA,
greb@uky.edu; WANG, Z., University of Kentucky, Kentucky, USA, zmwang@uky.edu; KELLEY, M., Battelle, Ohio, USA, kelleym@battelle.org
As part of the Midwest Regional Carbon Initiative, a project funded by DOE
and managed by Battelle, the potential for inducing earthquakes from future
geologic CO2 storage (GCS) is being assessed across a 20-state region of thenortheastern quadrant of the U.S. Recent studies of induced seismicity (IS) in
the project area, specifically in Illinois, Indiana, Ohio, Pennsylvania, and West
Virginia, suggest that an injection zone’s proximity to crystalline basement
is a major factor related to IS susceptibility. To assist with identifying candidate reservoirs for GCS with low IS susceptibility, we investigated correlations
between earthquake activity and geologic structure using a new earthquake
catalog and a new topographic map of the top of the Precambrian crystalline basement. The earthquake compilation includes events induced or likely
induced by wastewater disposal and fracking and contains all known earthquakes of magnitude 2.2 and greater and all known events of any magnitude
since 2009.
Consistent with previous studies, we find that earthquakes were typicallyinduced by fluid injections within ~1 km of the top of Precambrian. An exceptional case occurred in West Virginia from 2010 to 2013 near the southeastern boundary of the Rome Trough. In this case, probable IS correlated withfluid injections at heights in the sedimentary strata from ~3.5 km to ~4.5 km
above the Precambrian. These events were reported at anomalously shallow
depths, also well above Precambrian. However, their focal depths are poorly
constrained and seismicity appears diffuse. Here, we attempt to enhance theearthquake catalog and to improve the hypocenter determinations by detecting additional events using continuous broadband datasets from regional
stations and by jointly relocating the events in the region surrounding theinjection activities. Preliminary detections using standard techniques haverevealed only a single earthquake in the nearly two years after the sequenceappeared to end. The next steps will involve enhancing the detections using
machine-learning-based techniques.
poster 92
OhioNET: Reducing Risk from Induced Seismicity Using
Real-Time Seismic Monitoring for Regulation and
Mitigation in Ohio
DADE, S. L., Ohio Department of Natural Resources, Ohio, USA, steven.
dade@dnr.ohio.gov
Over the past decade, induced earthquakes have increased dramatically acrossthe US from expanding anthropogenic operations including brine disposal,
oil/gas production, hydraulic fracturing, and carbon sequestration. In Ohio,the rapid increase in oil and gas operations from the Utica shale indicated

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Seismological Research Lettersthe necessity for a seismic monitoring program as cases of induced seismicity started to emerge in areas with no previous history of seismic activity. In
2012, the Ohio Department of Natural Resources (ODNR), Division of Oil &Gas Resources Management (DOGRM) created the OhioNET seismic network, a real-time seismic monitoring network designed for accurately evaluating seismic events and generating automatic alerts. By gaining this ability,
ODNR-DOGRM began developing best practices through collaboration withresearchers and academia that focused directly on how seismic monitoring
can be used to help mitigate, regulate, and reduce the seismic risk associatedwith induced seismicity. These situations highlighted the need for mitigation
protocols and coordinated communications among staff and industry. ODNR
continues to prioritize science-based results and rulemaking that protects
citizens, the environment, and advances responsible development of natural
resources.
poster 93
Automated Earthquake Detection and Location Applied toLocal-Scale Seismic Monitoring
DZUBAY, A., Instrumental Software Technologies, Inc., New York, USA,
alexdzubay@isti.com; LEIFER, J., Instrumental Software Technologies, Inc.,New York, USA, jeffreyleifer@isti.com; STACHNIK, J., Instrumental Software
Technologies, Inc., New York, USA, joshstachnik@isti.com; FRIBERG, P.,
Instrumental Software Technologies, Inc., New York, USA, paulfriberg@isti.
com
Comprehensive catalogs of microseismicity are crucial to effective monitoring of induced seismicity. Due to the large quantity and low signal-to-noiseof microseismic events, maintenance of such catalogs is labor-intensive.
Recent advances in machine-learning workflows for detection and location
have shown promise as a potential solution to this issue. Here, we use the
BPMF package (backprojection and matched filtering, Beaucé et al., 2023) inconcert with a pre-trained convolutional neural network model (Leifer et al.,AGU 2022) to automatically detect and locate microseismic events inducedby hydraulic fracturing within a local-scale seismic monitoring array. The
array consists of 9 wideband seismometers installed in shallow postholes
with approximately 1 km spacing. Conventional operations consisting of
automatic, real-time processing in Earthworm, manual review, and templatematching provide the basis for this deployment, producing a catalog of 1375
events in the upper 5 km spanning magnitudes from M-0.94 to M2.8 overthe course of 32 days. The machine learning model used in this study wastrained on a proprietary dataset containing data from seven local-scale arrayswith similar characteristics. In comparing the automatically generated catalog
to our conventional operations, we find that the machine learning workflow
recovers more than 90% of the manually reviewed events. However, locations for the recovered events show higher residuals when compared to themanual locations due to small inaccuracies in the arrival times produced by
the BPMF workflow. Additional fine-tuning of the parameters used in backprojection and matched-filtering in conjunction with improvements to thepre-trained picking model should enhance both the percentage of recovered
events and location quality. These results demonstrate the potential of automated machine learning workflows to efficiently generate valuable microseismic catalogs in near real-time. Future applications of this workflow will aim to
improve seismic monitoring capabilities of enhanced geothermal systems andcarbon sequestration projects.
poster 94
Using Deep Learning for High-Resolution Fault Analysis
and Stress Characterization at the Forge Site, Utah
MOHAMMADI GHANATGHESTANI, A., Texas A&M University, Texas,
USA, a-mohamadi@tamu.edu; CHEN, X., Texas A&M University, Texas,
USA, xiaowei.chen@tamu.edu; ASIRIFI, R., Texas A&M University, Texas,
USA, richard_asirifi@tamu.edu
The precise determination of fault location and geometry assumes major
importance in the context of induced seismicity management during reservoir
stimulation. By increasing the size of new datasets, we need new techniques to
get the most information from these datasets. In this study, we used Machine
Learning and Neural Networks to prepare data for focal mechanism determination and stress field evaluation of the FORGE site in Utah. The dataset
used for this purpose is derived from dual-borehole seismic arrays locatedat the FORGE site. Accurately determining focal mechanisms for microseismic events is a challenging task, primarily due to the inherent limitations
in geometric coverage. To eliminate this challenge, we used various seismic
attributes such as P-wave polarities and P/S amplitude ratio, with the aim ofsupplying a robust estimation of the focal-plane mechanisms.

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Our study focuses on the analysis of 1500 microseismic events recorded
during phase 3 stimulation in 2022 at the FORGE site. We used PhaseNet
to pick P and S arrival then we developed A Convolutional Neural Network(CNN) by using Southern California Earthquake Data Center (SCEDC) dataset to predict the first motion polarity. By using this approach, we prepared adataset consisting of 738 events for focal mechanisms inversion. We obtained
681 A and B quality focal mechanisms solutions by using HASH method.
The high-resolution focal mechanisms map shows different patterns at different parts of the site area with more strike-slip fault at shallower depth, while
mixture of reverse and normal faulting at deeper depth. By utilizing MSATSI
package, we estimated the stress field principal axes orientation and relative
magnitude at each section. The stress result shows different stress regimes atdifferent sections, also the stress map showed a clear transition in principal
axes orientation with depth at the FORGE site area.
poster 95
A Comparison of Machine Learning and ArrayBeamforming Methods in Detecting Microearthquakes
Near Cushing, Oklahoma, Using a Dense Nodal Array
CHEN, X., Texas A&M University, Texas, USA, xiaowei.chen@exchange.
tamu.edu; CHENG, Y., University of California, Berkeley, California, USA,chengyif@berkeley.edu; HOEFER, B. A., Texas A&M University, Texas, USA,bhoefer99@gmail.com
Midcontinent seismic activity in the United States has sharply increased
from background levels in the last 15 years. Oklahoma has been at the center
stage for this increase due to the production of oil and gas and the associated injection of fracking fluids and wastewater disposal. While there were
notable large earthquakes, such as the M5 Cushing and Pawnee events, there
are a vast number of smaller events; detecting and cataloging these events canprovide valuable insight into the evolution of the subsurface, leading to better industry practices and a more robust understanding of the impact thatfluid injection has on fault activations. Here, two methods are employed todetect small earthquakes using continuous waveform with a dense nodal
array near Cushing, Oklahoma. Array-beamforming detection requires noprior knowledge of the region’s waveform or local velocity model, which
detects events by comparing inter-station waveform similarity. LOC-FLOW
is a machine learning-based workflow combining several algorithms to detectand locate earthquakes. Both methods have been shown to detect more events
than are contained in previous catalogs and, if automated, can be a hands-off
approach to creating catalogs of high resolution. The merits and drawbacksof each method must be understood to apply them most appropriately. The
array-beamforming method detected thousands of events compared to themachine learning method’s 112 events for the same period. However, arraybeamforming is susceptible to detecting non-tectonic events such as passing
traffic, perhaps owing to its roadside deployment. Event location remains variable between earthquakes detected by both methods, with an average offset of
3.18 km between the 43 co-detected events. Fine-tuning processing parameters will improve the beamforming event detection to remove false detections,such as increasing the maximum inter-station distance for which waveform
similarities are compared, increasing the duration of the time window overwhich waveforms are compared, or considering different sub-arrays. Further
characterization of detected events will be performed.
poster 96
Innovative Use of Broadband Sensors for Carbon Capture
Utilization and Storage (“CCUS”) Monitoring Applications
LINDSEY, J. C., Guralp Systems Ltd., Reading, United Kingdom, jlindsey@
guralp.com; WATKISS, N., Guralp Systems Ltd., Reading, United Kingdom,
nwatkiss@guralp.com; HILL, P., Guralp Systems Ltd., Reading, United
Kingdom, phill@guralp.com; O’NEILL, J., Guralp Systems Ltd., Reading,United Kingdom, joneill@guralp.com
Safe and effective solutions for CO2 injection and storage are becoming
increasingly more important on the global stage as we transition to net-zero.
Carbon Capture Utilization and Storage (“CCUS”) has been identified as a
crucial tool for achieving these goals. Broadband seismometers are being
utilized in all stages of the injection activity lifecycle. For example, the risks
of injection-induced seismicity must be effectively managed to ensure safe
operation, with passive seismic monitoring being a key component of themonitoring strategy.
Operators are making use of a mix of both sub-surface and surface stations to effectively monitor injection operations, with broadband stations
being sparser in their distribution providing a cost-effective alternative andsupplement to dense geophone arrays. Broadband sensors can detect lower
frequencies, providing more accurate moment magnitude (Mw) estimates

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than geophones at larger magnitudes (Mw >2). This is important to gauge thephysical size of any induced rupture and maintain the integrity of any traffic
light monitoring regulations that may be in place.
Güralp Systems Ltd. (“GSL”) has developed a range of medium-motion
broadband systems that focus on ease of use to allow operators to carry out
real-time monitoring. The Güralp smart sensor module can operate at any
angle, a novel feature of broadband seismometers, allowing it to be easily
buried at depth to increase Signal-to-Noise Ratio. This mitigates the need formore costly vault installations. GSL’s Minimus digitizer platform allows for
efficient real-time monitoring networks to be set up to alert for anomalous
seismic events with low latency.
Such sensors have recently been utilized to establish a dense, onshore
array of broadband instruments to monitor the first offshore UK CO2 storage
project at the Endurance structure. Onshore monitoring of offshore storage
offers a cost-effective, real-time strategy when compared to dedicated offshore
monitoring systems. However, array geometry and local geology are important considerations in establishing an array, and constraining event depths isa current challenge.
poster 97
The Utah Frontier Observatory for Research in Geothermal
Energy: A Field Laboratory for Enhanced Geothermal
System (EGS) Development
MOORE, J. N., University of Utah, Utah, USA, jmoore@egi.utah.edu;
MCLENNAN, J., University of Utah, Utah, USA, jmclennan@egi.utah.
edu; PANKOW, K. L., University of Utah, Utah, USA, pankowseis2@
gmail.com; PODGORNEY, R., Idaho National Laboratory, Idaho, USA,robert.podgorney@inl.gov; RUTLEDGE, J., Santa Fe Seismic LLC, New
Mexico, USA, rutledge@swcp.com; MEIER, P., GeoEnergie Suisse, Zurich,
Switzerland, p.meier@geo-energie.ch; DYER, B., GeoEnergie Suisse,
Zurich, Switzerland, b.dyer@geo-energie.ch; KARVOUNIS, D., GeoEnergie
Suisse, Zurich, Switzerland, d.karvounis@geo-energie.ch; BETHMANN,
F., GeoEnergie Suisse, Zurich, Switzerland, f.bethmann@geo-energie.ch;
XING, P., University of Utah, Utah, USA, pxing@egi.utah.edu; BARKER, B.,
University of Utah, Utah, USA, bbarker@egi.utah.edu; JONES, C., Universityof Utah, Utah, USA, cjones@egi.utah.edu; SIMMONS, S., University of Utah,
Utah, USA, ssimmons@egi.utah.edu; DAMJANAC, B., Itasca Consulting
Group, Inc, Minnesota, USA, branko@itascacg.com; FINNILA, A., WSP
Global, montreal, Canada, aleta.finnila@wsp.com
In 2014, the US DOE authorized funding for a field-scale laboratory dedicatedto testing tools and technologies for Enhanced Geothermal System (EGS)
development. The ultimate goal of the project is to create a roadmap for commercialization of EGS. The Frontier Observatory for Research in Geothermal
Energy (FORGE), operated by the University of Utah, was constructed insouthwestern Utah. Since 2016, eight wells have been drilled at the site. The
wells range in vertical depth from 304 - 2896 m. Hot, low permeability granitic
and metamorphic basement rocks that will form the reservoir were found at
depths ranging from 716 - 968 m. Laboratory measurements on core and theresults of injection tests yielded permeabilities of 20-80 microDarcies. Six ofthe wells are vertical and are used for tool testing, seismic monitoring andwater production. The deepest well reached an estimated temperature of
241oC. Two deviated wells were drilled for the injection-production pair thatwill be used to circulate fluids. The injection well was deviated 65° from vertical and drilled to a measured depth (MD) of 3349 m The production well was
drilled parallel and approximately 100 m above the injection well to a MD of
3337 m. Both wells were cased throughout most of their length. Circulation
tests and pressure monitoring demonstrate the two wells are connected.
A permanent monitoring system has been established. It includes fiber
optic cables cemented in the annulus of production casing strings, surface
accelerometers, and concentric rings of near-surface borehole seismometers.
The fiber optic cables allow monitoring of temperature, strain and seismicity. During stimulations, the permanent monitoring network is augmented
with geophone strings in the vertical wells and with surface nodal arrays.
Stimulation of the injection well in 2022 yielded more than 50,000 seismic
events with moment magnitudes (Mw) ranging from -2.3 to +0.5 Mw. These
events occurred as much as 150 m from the injection well. The next stimulation is planned for early 2024.
poster 98
Microseismicity Observation and Structure
Characterization at Cape Modern, Utah
NAKATA, N., Lawrence Berkeley National Laboratory, California, USA,nnakata@mit.edu; WU, S., Lawrence Berkeley National Laboratory,
California, USA, a06859a35@gmail.com; HOPP, C., Lawrence Berkeley
National Laboratory, California, USA, chopp@lbl.gov; ROBERTSON, M.,

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Lawrence Berkeley National Laboratory, California, USA, MCRobertson@
lbl.gov; JUNG, Y., Jeonbuk National University, Jeonju, South Korea,
YunhaJung@lbl.gov; PARK, S., Jeonbuk National University, Jeonju, South
Korea, world263@naver.com; OH, J., Jeonbuk National University, Jeonju,
South Korea, juwon24@jbnu.ac.kr; DADI, S., Fervo Energy, Texas, USA,sireesh.dadi@fervoenergy.com
To prepare the new stimulation and exploration of geothermal resources
at Cape Modern, Utah, we deploy seismometers, test noise level, and refine
velocity models. Shallow boreholes (a few tens of meters) help to improve thesignal-to-noise ratio with combined with different types of sensors such as
surface nodal sensors. We numerically simulate seismic wavefields generated
by microseismicity using a realistic velocity model and noise level to understand our monitoring capabilities, which helps us to understand the capability of our array for seismicity characterization and magnitude completeness.
Background seismicity ratio before stimulation with the new seismometers
will be discussed. The velocity model are refined using available active seismic
surveys at the Utah FORGE area, which is a neighbor geothermal field to theCape Modern site, using full-waveform inversion. The updated velocity model
has a better shallow subsurface model, especially in the sedimentary layers, toconstrain the location of microseismic events.
poster 99
Weak Soils, Active Faults, and the Inheritance ofGroningen Induced Seismicity: How to Proceed With Safe
Use of the Subsurface for the Energy Transition in the
Netherlands?
VAN DER WAL, J. L. N., Dutch State Supervision of Mines, Den Haag,
Netherlands, j.vanderwal@sodm.nl; MUNTENDAM-BOS, A. G., Dutch
State Supervision of Mines, Den Haag, Netherlands, A.G.Muntendam-Bos@
sodm.nl; SCHOUTEN, M. W., Dutch State Supervision of Mines, Den Haag,
Netherlands, m.schouten@sodm.nl
The Netherlands is known for its induced seismicity by gas exploration in the
Groningen field. The earthquakes are unique for their high ground motionsat relatively low magnitudes (ML≤3,6). This is partly due to local site amplification by unconsolidated surface geology, which is common throughout
the country. Consequently, buildings in the region sustained structural andnon-structural damage. Along with slow progress of building reinforcements,
implemented to mitigate the increased seismic risk, this led to cessation ofGroningen gas production in 2023. Currently, the Netherlands is moving toa renewable energy market. This requires considerate, safe use of the subsurface e.g. for geothermal heat production and storage of hydrogen and carbon dioxide in salt caverns or former gas reservoirs. Such a transition also
impacts areas that may not have experienced subsurface activities yet. This ischallenging for two reasons: citizens worry they will be faced with a ‘second
Groningen’—reflecting a potential loss of the social license to operate—and
there is less knowledge of the subsurface.
To add to the complexity is the natural seismic hazard: the southeastern
Netherlands contains the Ruhr Valley Graben, an active, slowly deforming
rift system. The largest instrumental earthquake here was the 1992 ML=5,8
Roermond event. However, recurrence intervals are long and not all faults—
and their reactivation potentials—are known. Nevertheless, local events
have also been linked to geothermal heat production and to post-coal mining groundwater ingress. State Supervision of Mines, the Dutch authority formining safety, aims to understand risks of induced seismicity, within the local
tectonic context and also beyond the area impacted by Groningen gas exploration. To do so, research must be done simultaneously with the developmentof renewable energy sources and storage sites. How does one ensure the safetyof people and protection of the environment during this transition whileaccounting for the many subsurface uncertainties? What research should beprioritized, what (pragmatic) choices can and/or need to be made?
poster 100
Application of Static Stress Drops and Similarity of Seismic
Events Induced by Underground Fluid Injection in
Characterization of Seismogenic Zones on the Example of
The Geysers Geothermal Field
STASZEK, M., Polish Academy of Sciences, Warszawa, Poland, mstaszek@
igf.edu.pl; RUDZIŃSKI, Ł., Polish Academy of Sciences, Warszawa, Poland,rudzin@igf.edu.pl; WISZNIOWSKI, J., Polish Academy of Sciences,
Warszawa, Poland, jwisz@igf.edu.pl
Characterization of seismogenic zones in the areas of underground fluid injection is an important issue for seismic hazard assessment in such destinations.
It is well known that subsurface discontinuities can be successfully imaged

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Seismological Research Lettersusing multiplets, i.e. seismic events with very similar waveforms. On the other
hand, recently static stress drop of earthquakes has been suspected to reflect
the strength of rocks. In this study we propose to utilize combined information from spatiotemporal multiplet analysis and statistical assessment of static
stress drop variability to characterize the origin zones of injection induced
seismicity. As an example, we present results obtained using dataset from
Prati-9 and Prati-29 injection wells at The Geysers geothermal field. With theuse of multiplet analysis followed by double-difference relocation we imaged
three fractures and one fault within the reservoir and described their different
seismic response to injection. Moreover, we statistically proved the occurrenceof independent spatial and temporal variations of static stress drop of eventsand interpreted them as an image of differences in strength of discontinuities.
Obtained results prove the fact that the information obtained from multiplet
and stress drop analyses is complementary and can be interpreted together.
In order to check the utility of proposed method for the purposes of hazard assessment, we related the locations of the strongest events in the cluster
to identified discontinuities. Moreover, we assessed the maximum expectedmagnitude basing on the dimensions of identified fault. Finally, we calculated
the effect of analyzed events on the surface (PGV, PHV, PVV) and related
obtained values to observed stress drop differences. This research was supported by research project no. 2022/45/N/ST10/02172, funded by the National
Science Centre, Poland, under agreement no. UMO-2022/45/N/ST10/02172.
This work was also partially supported by a subsidy from the Polish Ministryof Education and Science for the Institute of Geophysics, Polish Academy of
Sciences. This research was supported in part by PLGrid Infrastructure.
poster 101
Mapping of the Seismic B-Value Before and After Mine
Collapse Main Shocks, Rudna Mine, SW Poland
SOBIESIAK, M. M., University of Kiel, Kiel, Germany, monika.sobiesiak@
ifg.uni-kiel.de; STASZEK, M., Polish Academy of Sciences, Krakow, Poland,mstaszek@igf.edu.pl; LEPTOKAROPOULOS, K., MathWorks, Cambridge,
United Kingdom, K.Leptokaropoulos@soton.ac.uk; RUDZINSKI, L., Polish
Academy of Sciences, Krakow, Poland, rudzin@igf.edu.pl
Rudna Deep Copper Mine, located in SW Poland, is known for producing alarge number of seismic events on a daily basis in a magnitude range starting below M0 and often ending in large mine collapses with magnitudes overM4. In previous work (Sobiesiak et al., 2022), we were able to enhance existing data sets with induced seismicity from the mine by using the software
BackTrackBB (BTBB) (Poiata et al., 2016). This automated detection and location procedure resulted in three large daily data sets from ~6000 and up to ~10000 events per day enhancing the catalogs mainly in the range of small scale
events. This work permitted a first attempt to apply short term hazard assessment on a daily basis using SHAPE software (Leptokaropoulos and Lasocki,2020) which would be a crucial aspect for early warning procedures.
Aiming at additional information on processes around the major mine
collapses, we decided to perform a mapping of the seismic b-value of the
Gutenberg-Richter relation using the software ZMAP (Wiemer et al., 2000).
As the b-value possesses the dual capability of displaying ambient stresses
as well as changes in material properties and thus mirrors the interaction
between internal structures and outer forces, we choose this parameter todecipher more about processes on going in time and space around majormine shocks. The sheer number of events on relatively small volumes further
support the method and makes the statiscical approach more stable. Here,
we present the results of this mapping procedure for three daily data sets of
induced seismicity from Rudna Mine and compare it to the results gained
from the application of a short term hazard assessment.
poster 102
Focal Mechanisms of Microseismicity at the Decatur,
Illinois, CCS Site Inverted From Multiple Borehole Seismic
Arrays
WOO, J., Los Alamos National Laboratory, New Mexico, USA, woo@lanl.gov;
TING, C., Los Alamos National Laboratory, New Mexico, USA, tchen@lanl.
gov
Underground fluid injection can trigger earthquakes by activating hidden
fault systems favorable to diffusive pore pressures with local stress fields.
Tracking down microearthquakes during passive seismic monitoring in fluid
injection sites enables imaging fault systems and estimating their seismic productivity. Along with the hypocentral distribution of microseismicity in thefluid injection field, focal mechanisms of earthquakes directly provide thegeometries of fault systems and instabilities with respect to the regional stressfield. While borehole sensors near injection wells effectively detect microseismicity by suppressing ambient noise near the surface, the co-location ofwww.srl-online.org•

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sensors at different levels limits the analysis of the radiation patterns fromdifferent faulting types. In this study, we examine fault mechanisms of microseismicity at the Decatur CO2 injection site by using recordings at two borehole seismic arrays. The first P-motions of two borehole arrays still do not
suffice to determine the focal mechanisms. The coherence measurement of the
S/P amplitude ratios at sensors within individual arrays further constrains theuncertainty of focal mechanisms. This contradicts the unstable S/P amplitude
measurements associated with site-specific calibrations at surface sensors. We
validate the solutions obtained from first motion polarity and S/P amplitude
ratios by comparing solutions of a few events for which surface and boreholesensors observe the first P-wave motions. The obtained focal mechanism solutions generally match the distribution of earthquakes and the local maximum
stress direction. The subtle variation of focal mechanisms in each earthquake
cluster represents either the heterogeneity of the fault system or the local-scale
perturbation of the stress field. Our observation highlights the importance ofinstalling multiple borehole arrays to investigate focal mechanisms of small
earthquakes to estimate small-scale fault systems.
poster 103
Microseismicity Moment Tensor Estimation Using Surface
and Downhole Geophone Arrays at Utah FORGE
WU, S., Lawrence Berkeley National Laboratory, California, USA, a06859a35@
gmail.com; NAKATA, N., Lawrence Berkeley National Laboratory, California,
USA, nnakata@lbl.gov
Microseismicity associated with the 2022 spring stimulation at Utah FORGE
exhibits magnitudes from -2 to 0. The concurrent passive seismic monitoring
system was consisted of a dozen of downhole geophones along two wells anda ~200-geophone surface array. Geophones emplaced downhole within granite were < 1 km from the stimulation locations and the recorded seismicity
waveforms have high signal-to-noise ratio (SNR). On the other hand, the surface array was generally ~2.5 km away deployed on the sediment layer, whichcauses high attenuation of signals and only events close to M0 are recordedwith reasonable SNR. Despite the limitation, the surface array has strengthof azimuthal coverage that is crucial for moment tensor solution. Therefore,
in this study, we leverage complementary information from both geophonearrays based on their P polarities and amplitudes.
Beginning with the set of ~M0 events, for the surface array, we perform
beamforming and a noise-suppression filter to align and enhance the incoming P energy, which outperforms linear stacking methods. Meanwhile, for the
downhole array, we employ an SNR detection and visual inspection to identify the first arrivals. The resultant moment tensors reveal strike-slip mechanisms with fault strikes consistent with the known geologic formation. Next,
we aim to retrieve the moment tensor for smaller events (< M0) that exhibit
high similarity with the ~M0 events. To achieve this, we apply cluster analysis
and waveform correlation. For the highly similar event (correlation coefficientlarger than 0.9), we refine the SNR detection picks using correlation lag time
for downhole data and we adapt the first arrival information from the corresponding surface data. We will further discuss the sensitivity from the aspectsof first-arrival detection, moment-tensor inversion, and the applicability ofthe similarity-based method within this specific geothermal setting.
poster 104
Shear-wave Splitting Observed in the Geysers Geothermal
Field to Monitor the Spatiotemporal Crustal Conditions
YOSHIMITSU, N., Kyoto University, Nishikyo-ku, Japan, yoshimitsu.
nana.6i@kyoto-u.ac.jp
S waves propagate in an anisotropic medium separate orthogonally to eachother, called shear wave splitting. Mineral properties or crust cracks are considered as the heterogeneous structure to split shear waves. The characteristics of the heterogeneous structure are estimated from the leading shear wave
polarization direction (LSPD) and the travel time difference (DT). Some studies pointed out local heterogeneity, for example, faults and dense cracks, affectthe direction of the LSPD. In a geothermal field, crack status is affected by
the increase and decrease of water as a result of the power plant operation. If
we could utilize shear wave splitting observed from microearthquakes in thegeothermal fields, it would be useful for spatiotemporal reservoir monitoring.
The Geysers geothermal field locates in northern San Francisco. Inthat region, rich seismic network is provided by The Northern California
Earthquake Data Center (NCEDC). I select five three component stations,
LCK, FFA, ESM, ACR, and DRH. These stations have a small incident angle
from the source and less impact from reflection and surface waves. LCK, FFA,
ESM, ACR locate the eastern side of the swarm activity, and DRH locates thewestern side. The sampling frequency is 500 Hz. There are 30 earthquakes
observed from 2020 to 2023, with magnitudes between 3.0 and 4.0, latitudes

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between 38.5 and 39.0, and longitudes between -123 and -122. DSPD and DT
are estimated from the Cross-correlation method (e.g., Shin and Meyer, 1990),
with a 1-second time window.
The stations LCK, FFA, and ESM show the predominant polarization
direction for the northeast, while ACR does not show a strong polarization
direction. The characteristics of the polarization direction are consistent
with the shear wave splitting research in this region (Elkibbi and Rial, 2005).
Though the LSPD estimates showed relatively large variation, there are noclear temporal changes for three years. DRH shows a similar predominantpolarization direction while it is located in a distant area from the current
active swarm area.
poster 105
A Cost-Effective GCS Monitoring Approach Using Localized
Seismic Waves
ZHENG, Y., University of Houston, Texas, USA, yzheng12@uh.edu; SUN, M.,
University of Houston, Texas, USA, msun@central.uh.edu; HUANG, L., Los
Alamos National Laboratory, New Mexico, USA, ljh@lanl.gov
As geological carbon storage (GCS) is being adopted worldwide, monitoring
possible CO2 migration in the subsurface is needed to ensure conformanceand containment. A scalable turnkey solution is favored over repeated dense
data acquisition (4D seismic) for GCS monitoring. Expensive time-lapse
3D seismic monitoring has been used in CO2-enhanced oil recovery (EOR)
fields, but its use in GCS is not economically feasible. We propose a cost-effective GCS monitoring approach using localized seismic waves and permanentsource arrays. Given the spatially finite nature of the localized wave, we only
need a few geophones on the surface to record scattered localized seismic
wavefields. To quantify the amount of CO2 using time-lapse changes of localized seismic waves, we conduct lab measurements of the P-wave velocity anddensity for supercritical CO2-saturated brine under various pressure-temperature conditions and a fluid substitution equation. Our monitoring approach
using localized seismic waves could be a turnkey solution to cost-effective,
long-term GCS monitoring.
poster 106
A Risk-Based Adaptive Monitoring Planning Tool Based on
Elastic-Wave Sensitivities for Cost-Effective Seismic
Monitoring for Geologic Carbon Storage
TIAN, Y., Lawrence Livermore National Laboratory, California, USA, tian7@
llnl.gov; YANG, X., Lawrence Livermore National Laboratory, California,
USA, yang25@llnl.gov; HUANG, L., Los Alamos National Laboratory, New
Mexico, USA, ljh@lanl.gov; GAO, K., Los Alamos National Laboratory,
New Mexico, USA, kaigao@lanl.gov; VASYLKIVSKA, V., National Energy
Technology Laboratory, Oregon, USA, Veronika.Vasylkivska@netl.doe.gov;
GASPERIKOVA, E., Lawrence Berkeley National Laboratory, California,
USA, egasperikova@lbl.gov
Geologic carbon storage (GCS) is a viable approach to reducing CO2 emissions into the atmosphere. The risk of CO2 leakage from GCS operations is ofconcern to regulators, operators, and the public. Monitoring is indispensable
for a GCS project to detect CO2 leakage and account for CO2 mass in storage
formations. The US DOE sponsors the National Risk Assessment Partnership(NRAP) project to develop a risk-based adaptive monitoring planning(RAMP) tool for the selection, evaluation, and optimization of monitoring
technologies. RAMP will be useful to support the deployment of large-scale
GCS projects. This presentation focuses on optimal 2D surface seismic monitoring design through elastic-wave sensitivity analysis for detecting and imaging CO2 plumes. We simulate a hypothetical GCS scenario at the Kimberlina
site in Southern San Joaquin Valley, California, and generate 2D elastic-wave
sensitivity data with respect to seismic velocity models at six timesteps (80,85, 90, 95, 100, and 125 years) after the start of CO2 injection with a focus on
the post injection phase. We develop a 2D seismic survey design tool using
simulated elastic-wave sensitivity data. An optimal monitoring design provides seismic source and receiver locations with high sensitivities to the target monitoring region(s). This source-receiver configuration varies with timefor either detection or imaging and is adaptive with time according to CO2
migration and/or leakage. For cost-effective monitoring, the RAMP tool provides the minimum number of sources and receivers required to meet themonitoring objectives.
Acknowledgments
This work was performed under the auspices of the U.S. Departmentof Energy by Lawrence Livermore National Laboratory under Contract
DE-AC52-07NA27344, by Lawrence Berkeley National Laboratory underContract DE-AC02-05CH1123, by Los Alamos National Laboratory underContract 89233218CNA000001, and work at National Energy Technology

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Laboratory was performed under Field Work Proposal No. 1025009. This
manuscript was reviewed and released LLNL-ABS 859038.

Seismoacoustic, Geodetic and Other GeophysicalInvestigations of Active Volcanoes
Oral Session • Friday 3 May • 8:00 am PacificConveners: Josh Crozier, U.S. Geological Survey (jcrozier@usgs.gov); Ricardo Garza-Giron, Colorado State University(rgarzagi@ucsc.edu); Margaret Glasgow, U.S. Geological
Survey (mglasgow@usgs.gov); Alicia Hotovec-Ellis, U.S.
Geological Survey (ahotovec-ellis@usgs.gov); John J. J. Lyons,
U.S. Geological Survey (jlyons@usgs.gov); Diana Roman,
Carnegie Science (droman@carnegiescience.edu)
Using Deep Long-Period Earthquakes to Constrain
Magmatic Volatile Transport at Mauna Kea
SCHOLZ, K. J., University of Oregon, Oregon, USA, kscholz@uoregon.edu;
THOMAS, A. M., University of Oregon, Oregon, USA, amt.seismo@gmail.
com; TOWNSEND, M. R., Lehigh University, Pennsylvania, USA, met423@
lehigh.edu
Seismic signals generated at volcanoes, such as deep long-period earthquakes(DLPs), can result from diverse physical processes, posing challenges for theinterpretation of such signals. However, Mauna Kea provides a unique setting
to explore the processes behind DLPs due to a large and well-characterizedcatalog of these events. Between 2000 and 2019, beneath Mauna Kea, over 1
million DLPs occurred near periodically with interevent times between 7 to
12 minutes. Wech et al. (2020) cataloged and characterized these events, locating them at ~22 km b.s.l. beneath Mauna Kea and constraining their primarily
non-double-couple source mechanisms. The authors proposed a conceptualmodel for these repeating events where stalled, crystallizing mush at the baseof the crust results in second-boiling driven degassing. The degassing supplies
magmatic volatiles to an overlying network of pre-existing fractures generating the DLPs. From this conceptual model, we have developed a physicsbased numerical crack model for these repeating DLPs from which we compute synthetic seismograms. By tuning the model parameters and comparing
the resulting synthetic seismograms to observed seismograms, we successfully
reproduce observations such as the p-wave first motions and the amplitudesof these events. Furthermore, the range of suitable parameters from the tuned
crack model provides valuable insight into the elastic properties of the rocksurrounding the fractures, fracture system size and geometry, and magmatic
volatile supply rates to the fractures—quantities otherwise poorly constrained
at lower crustal depths in magmatic plumbing systems. More broadly, thisapproach improves our understanding of one potential source of seismicity
at volcanoes and provides novel insight into passive degassing of magmatic
volatiles.
Probing Magma Storage and Transport Beneath Pāhala,
Hawai‘i
JANISZEWSKI, H. A., University of Hawaii at Manoa, Hawaii, USA,hajanisz@hawaii.edu; BENNINGTON, N., U.S. Geological Survey, Hawaii,
USA, nbennington@usgs.gov; WIGHT, J., University of Hawaii at Manoa,
Hawaii, USA, jcwight@hawaii.edu; GLASGOW, M., U.S. Geological Survey,
California, USA, mglasgow@usgs.gov
Deep (> 20 km below sea level) earthquakes occur along mantle fault zones
beneath the southern coast of the Island of Hawai‘i, near the active volcanic
centers of Kīlauea, Mauna Loa, and Kama‘ehuakanaloa (formerly Lō‘ihi).
Previously, long-period tremor and a recent ten-fold increase in seismicity
at these depths since 2019 centered beneath the town of Pāhala have been
observed. We hypothesize that magma transport processes trigger some ofthe deep seismicity along these mantle faults. These may potentially provide
pathways for magma to the summit storage systems of these volcanoes via
sub-horizontal mantle fault zones. Detailed seismicity studies in this region
have relied on 1-D velocity models; construction of local 3-D velocity models
to better understand relationships between magma storage and earthquake
processes has been precluded by the scarcity of seismic instruments deployedin this region. In summer 2022, we conducted a three-month deployment of
80 continuously recording three-component seismic nodes extending fromthe epicentral region of the Pāhala swarm towards Kīlauea’s summit. This

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included a dense line of nodes to enhance imaging of geologic structuresembedded within a sparser grid designed for precise earthquake detection
and location. We use a machine-learning based workflow to detect and locate
earthquakes with this novel dataset. The earthquake dataset complements
imaging from receiver functions and is used for body wave tomography,
which together provide improved constraints on crustal and upper mantle
structures in the region. The combined interpretation of these datasets willshed light on the magmatic structure and processes that have contributed tothe dramatic increase in seismicity since 2019.
Seismic Velocity Changes at Mauna Loa Derived From
Seismicity Prior to and During Its 2022 Eruption
HOTOVEC-ELLIS, A. J., U.S. Geological Survey, California, USA, ahotovecellis@usgs.gov
Mauna Loa’s short-lived eruption from late November to early December
2022 marked the culmination of nearly a decade of elevated seismic activity and geodetic inflation. The volcano has been monitored by a network ofpermanent, primarily single-component short-period seismometers with
open data since 2012. I used the continuous waveform data from that network to generate a catalog of seismicity using the open source “REDPy”
Python package. This catalog enhances the Hawaiian Volcano Observatory’s
public seismic catalog with additional detections and groups earthquakes by
waveform similarity. Analysis of subtle differences in the recordings of theearthquakes in this catalog yields a history of changes in the shallow seismic
velocity structure of the volcano. Seismic velocity changes are thought to besensitive to changes in strain, and therefore might be expected during volcanic
unrest and eruption. Indeed, initial results show a decrease in seismic velocity
centered on the summit beginning in September 2022, corresponding to theonset of a vigorous precursory swarm of seismic activity and shallow inflation. During the eruption itself, I observe a complex spatiotemporal pattern,perhaps due in part to dike opening along the Northeast Rift Zone. Seismic
velocity changes associated with non-volcanic sources such as large regional
earthquakes and seasonal climate changes are also observed, investigated, andcompared with supporting data. An open question in this work is whether
the changes observed in September 2022 were unique to the pre-eruptiveincrease in unrest, which has direct implications for the use of this technique
as a monitoring tool.
A Catalog of Automated Focal Mechanisms for
Microearthquakes at Axial Seamount Based on Waveform
Cross-Correlation
ZHANG, M., University of Washington, Washington, USA, mczhang8@
uw.edu; WILCOCK, W., University of Washington, Washington, USA,wilcock@uw.edu; WALDHAUSER, F., Columbia University, New York, USA,felixw@ldeo.columbia.edu; WANG, K., Columbia University, New York, USA,
kw2988@ldeo.columbia.edu; SCHAFF, D., Columbia University, New York,USA, dschaff@ideo.columbia.edu; TOLSTOY, M., University of Washington,
Washington, USA, mt290@uw.edu; TAN, Y., Chinese University of Hong
Kong, Hong Kong, China, yjtan@cuhk.edu.hk
Axial Seamount is a submarine volcano at the intersection of the Cobb
hotspot and the Juan de Fuca Ridge. The last eruption in 2015 was recorded by
7 ocean bottom seismometers on the Ocean Observatories Initiative Regional
Cabled Array. A small number of manual composite focal mechanisms (FMs)obtained by Levy et al. (2018) confirmed that the motion on an outward dipping ring fault beneath the summit caldera reversed during the 2015 eruption.
Our earthquake catalog for Axial Seamount comprises ~150,000 hypocentersfrom 2015-2024. A large data set of FMs would provide constraints on thegeometry and deformation of the caldera ring faults, the impacts of magma
movement and hydrothermal process on faulting, and the evolution of crustal
stresses through the eruptive cycle. To generate FMs automatically, we incorporate the methodology of Shelly et al. (2016) which determines polarities
by maximizing congruence with signed waveform correlation coefficients.
We first tested the approach on subsets of 5000 earthquakes from the east
and west walls of the caldera. We obtained 53,000 polarities which show a
95% consistency with the sign of the cross-correlation coefficients and a 99%
accuracy rate when benchmarked against 3,000 manual picks. Considering
just earthquakes with at least five polarities and 5 S/P amplitude ratios, we created 680 groups of ~15 earthquakes with fully consistent polarities and similar
locations and S/P ratios. Finally, we used the HASH program to generate composite FMs. The hypocenters beneath the west wall mostly fall on an outward
dipping ring fault and most FMs are normal faults consistent with this fault
plane. The hypocenters in the test data set beneath the east wall have a more
complex distribution and the focal mechanism similarly show more variation,
consistent with the influence of ring faulting and deformation in the regions

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where dikes are injected during spreading events. We are presently extending
the approach to the entire catalog and based on the number of earthquakes
with sufficient polarities and S/P ratios, expect to obtain ~7,000 composite
FMs.
The Influence of Multiple Scattered Waves on the Spectral
Stability of Volcanic Tremors
BRACALE, M., Université Grenoble Alpes, Saint Martin D’Heres, France,
mirko.bracale@univ-grenoble-alpes.fr; CAMPILLO, M., Université Grenoble
Alpes, Saint Martin D’Heres, France, michel.campillo@univ-grenoble-alpes.
fr; SHAPIRO, N., Université Grenoble Alpes, Saint Martin D’Heres, France,
nikolai.shapiro@univ-grenoble-alpes.fr; BROSSIER, R., Université Grenoble
Alpes, Saint Martin D’Heres, France, romain.brossier@univ-grenoble-alpes.
fr; MELNIK, O., Université Grenoble Alpes, Saint Martin D’Heres, France,
oemelnik@gmail.com
The conventional understanding of the stability observed in the spectral content of volcanic tremors attributes it primarily to the consistency of the source
mechanism generating these signals. In our study, we perform a more detailed
examination of the origin of seismo-volcanic signals through numerical simulations utilizing spectral elements methods. Our findings reveal that the stablefeatures observed in the signal spectrum can be produced by interference ofmultiply scattered waves on strong structural heterogeneity within the volcano plumbing system, arising from a complex distribution of magmatic sills
and dikes. To simulate the plumbing system’s heterogeneity, we used a modelof its growth by multiple injections of magma into surrounding crustal rocks(Melnik 2022). By computing the propagation of waves in this medium overextended durations, we show that the highly heterogeneous structure results
in a strong multiple scattering of seismic waves whose interference creates adistinctive signature in the signal spectra. This phenomenon holds true evenwhen considering a source spectrum that exhibits randomness. Our results
provide valuable insights into the heterogeneous structure of volcano plumbing systems that is expressed in the observed complexity and stability of thespectra of the seismo-volcanic signals. This study broadens our comprehension of volcanic processes and emphasizes the significance of multiple scattering of seismic waves within volcanic media.
Local Infrasound Monitoring of Lava Eruptions at
Nyiragongo Volcano (d.r. Congo) Using Urban and NearSource Stations
BARRIÈRE, J., European Center for Geodynamics and Seismology,
Walferdange, Luxembourg, julien.barrière@ecgs.lu; OTH, A., European
Center for Geodynamics and Seismology, Lintgen, Luxembourg, adrien.oth@web.de; D’OREYE, N., National Museum for Natural History, Luxembourg,
Luxembourg, ndo@ecgs.lu; SUBIRA, J., Goma Volcano Observatory, Goma,
Democratic Republic of the Congo, jos_sm@outlook.com; SMITTARELLO,
D., European Center for Geodynamics and Seismology, Walferdange,
Luxembourg, delphine.smittarello@ecgs.lu; BRENOT, H., Royal Belgian
Institute for Space Aeronomy, Uccle, Belgium, brenot@aeronomie.be;
THEYS, N., Royal Belgian Institute for Space Aeronomy, Uccle, Belgium,
nicolas.theys@aeronomie.be; SMETS, B., Royal Museum for Central Africa,
Tervuren, Belgium, benoit.smets@africamuseum.beDuring eruptions, volcanoes produce air-pressure waves inaudible for thehuman ear called infrasound, which are very helpful for detecting early signsof magma at the surface. Compared to violent ash-rich explosions, recording more discrete atmospheric disturbances from effusive eruptions remains
a practical challenge depending on the distance to the source. In contrast
with powerful volcanic explosions, close-range deployment of instruments
around the active vent (for instance < 15 km) is generally needed for continuously monitoring long-living lava effusion or degassing as observed at
open-vent volcanoes, such as Kīlauea (Hawaii) or Nyiragongo (D.R. Congo).
Nyiragongo, towering above a 1-million urban area, hosted the world’s largest
lava lake up to 2021, which was drained during the third known flank eruption of this volcano on 22 May 2021. We analyzed local infrasonic records
between January 2018 and April 2022. A persistent acoustic signature fromthe crater before and after the flank eruption was detected up to the volcano
observatory facilities in Goma city center about 17 km from its crater. We also
explore these records for characterizing the temporal and spatial evolutionof the flank eruption on May 22, 2021. These ~4-year results show remarkable local recordings of eruptive infrasound from near-source and city-based
stations and have significant implication for optimizing future monitoring
efforts in a harsh field environment. Remote observations from space (grounddeformation, gas emissions, thermal anomalies) can also provide essential
information about the eruptive state of a volcano and were jointly analysedwith infrasound records. The multidisciplinary approach with infrasound andVolume 95•

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space-based observations of the intra-crater activity leads to a comprehensive
picture of Nyiragongo’s eruptive activity during this period.
Here Comes the Boom! Tracking Audible Acoustics Across
Aotearoa New Zealand From the 2022 Eruption of Hunga
Volcano
LAMB, O., GNS Science, Taupō, New Zealand, o.lamb@gns.cri.nz; CLIVE,
M., GNS Science, Lower Hutt, New Zealand, m.clive@gns.cri.nz; LAWSON,
R., GNS Science, Lower Hutt, New Zealand, r.lawson@gns.cri.nz; POTTER,
S., GNS Science, Lower Hutt, New Zealand, S.Potter@gns.cri.nz; KILGOUR,
G., GNS Science, Taupō, New Zealand, G.Kilgour@gns.cri.nz; JARVIS, P. A.,
GNS Science, Lower Hutt, New Zealand, p.jarvis@gns.cri.nz; HARRISON, S.,
GNS Science, Lower Hutt, New Zealand, s.harrison@gns.cri.nz; SCOTT, B.,
GNS Science, Taupō, New Zealand, B.Scott@gns.cri.nz
On 15 January 2022, Hunga volcano in the Kingdom of Tonga erupted inwhat is thought to be one of the largest volcanic eruptions in recent history.
Atmospheric disturbances caused by the eruption generated long-range
audible sounds that were reported around the world, including the length of
Aotearoa New Zealand. This unusual phenomenon presented a rare opportunity to document and analyse the long-range propagation of audible volcanic
acoustics from both geophysical and social perspectives. In response to theevent, public feedback was obtained via a crowdsourced survey to understandthe spatial and temporal distribution of eruption sound observed across NZ.
The results of the survey complemented a dense geophysical record, including data from microphones, barometers, seismometers, and strong-motion
accelerometers.
In all, over 1700 members of the public from across the country reported
hearing “booming” noises on 15 January 2022. On average, 5 “booms” were
heard over a 2-hr period with half the respondents reporting a “light” or“moderate” perceived loudness, commensurate to 60–79 dB. Manual analysis of shockwave-like waveforms recorded by a seismo-acoustic station in the
North Island found >140 events across two distinct wavepackets within thesame time period, of which 7 had amplitudes >60 dB. Detailed analysis ofseismo-acoustic data from across Aotearoa New Zealand clearly highlights thetwo acoustic wavepackets propagating north-to-south on 15 January. The first
wavepacket coincided with the Lamb wave generated by the main explosive
phase of eruption. However, the second wavepacket propagated at a slower
apparent velocity (~270 m/s) and was likely associated with an atmosphericgravity wave generated during a later phase of the Hunga eruption sequence.
This presentation highlights how crowdsourced data can engage the wider
public in volcanology, how joint analysis with geophysical data is shedding
new light on a historic eruption, and how such multi-disciplinary studies may
be used to understand future volcanic activity.
Internal Gravity Waves During the 2023 Eruption of
Shishaldin Volcano, Alaska
HANEY, M. M., U.S. Geological Survey, Alaska, USA, mhaney@usgs.gov;
FEE, D., University of Alaska Fairbanks, Alaska, USA, dfee1@alaska.edu;
LYONS, J. J., U.S. Geological Survey, Alaska, USA, jlyons@usgs.gov
The 2023 eruption of Shishaldin volcano, Alaska, produced several significant explosive events between mid-July and early November. Similar eruptive
styles at the volcano had been instrumentally observed during previous eruptions in 1999 and 2020. Here we report on high-quality acoustic recordings ofthe eleventh explosive event (Event 11, September 25 13:35 UTC) on two local
infrasound sensors within 7 km of the volcano. We also analyze air-to-groundcoupling on three broadband seismometers, two of which are co-located with
the infrasound sensors. Event 11 had the distinction of being among the mostpowerful of the explosive events and it occurred during a time period of low
wind noise, resulting in excellent signal-to-noise ratio. Restitution over a wide
frequency band reveals acoustic signals with low frequencies down to at least
0.75 mHz (22 minutes period) following the start of the paroxysmal phase.
In this period range, acoustic-gravity wave phenomena are expected. The
low-frequency signals had maximum peak-to-peak pressure amplitudes ofapproximately 100 Pa, similar to previously reported observations of internal
gravity waves at Montserrat (Ripepe et al., 2016; Sci. Rep.). Such internal gravity waves offer a novel way to quantify the time history of mass eruption rateand estimate overall erupted volume. From the local seismo-acoustic data,
we show that the low frequency atmospheric waves propagated with a groupvelocity on the order of 10 m/s, much lower than the usual speed of sound andconsistent with internal gravity wave properties. Furthermore, polarization
analysis of the associated air-to-ground coupled wave at a three-component
seismometer indicates transverse particle motion, again in line with the characteristics of internal gravity waves. Using a 3D time-domain finite-difference
code, we model the acoustic-gravity wavefield and infer details of the erup-

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tion source, including mass eruption rate and source altitude. We additionallyanalyze internal gravity waves from other explosive events during the 2023
eruption.
Seismic and Infrasound Signals from the 2023 Shishaldin
Volcano, Alaska Eruption
FEE, D., University of Alaska Fairbanks, Alaska, USA, dfee1@alaska.edu;
HANEY, M. M., U.S. Geological Survey, Alaska, USA, mhaney@usgs.gov;
TAN, D., University of Alaska Fairbanks, Alaska, USA, ptan@alaska.edu
On July 12, 2023, Shishaldin Volcano, Alaska commenced a months-long eruption consisting of at least 13 discrete explosive events. In addition to hazardous ash plumes and tephra fall, these eruptive episodes exhibited similar intereruptive durations and increases in seismic and infrasound tremor amplitudes
prior to each explosive eruption. Here we focus on analyzing the three local
seismic and infrasound stations at Shishaldin and describe their notable features. We utilize a recently introduced Machine Learning tool (VOISS-Net)
to detect and classify the seismic spectral characteristics (Tan et al., 2024)
to determine the type, onset, and duration of seismicity. We also compute
reduced displacement and infrasound pressure to analyze amplitude variability over time. We find that the eruptive episodes were preceded by hours
to days of broadband seismic tremor. The seismic amplitudes increased prior
to the paroxysmal phase and often had a double-peaked shape. Infrasoundsignals, when not masked by wind noise, generally follow similar trends tothe seismic data and often display a transition from discrete explosions to sustained signals. The paroxysmal phases had notable ground-coupled acoustic
waves in the seismic spectra above ~3 Hz, complicating interpretation. The
seismic and infrasound data from these eruptions were critical for eruption
monitoring by the Alaska Volcano Observatory, and were the foundation ofnumerous eruption forecasts. We demonstrate that the signal classifications
and trends we observe here have utility for eruption monitoring and forecasting at other volcanoes worldwide.
Reference:Tan, D., Fee, D., Girona, Haney, M. M., Witsil, A., Wech, A. (2024)“Investigation of tremor and explosion sequences from the 2021-2022 eruption of Pavlof Volcano, Alaska using deep learning”. SSA Annual Meeting
Abstracts.
A Seismic Sequence Capturing Magmatic Fluid Ascent andPhreatomagmatic Eruptions at Semisopochnoi Volcano,
AlaskaLYONS, J. J., U.S. Geological Survey, Alaska, USA, jlyons@usgs.gov; TAN, D.,
University of Alaska Fairbanks, Alaska, USA, ptan@alaska.edu; HOTOVECELLIS, A., U.S. Geological Survey, California, USA, ahotovec@usgs.gov;
LOPEZ, T., University of Alaska Fairbanks, Alaska, USA, tmlopez@alaska.
edu; GRAPENTHIN, R., University of Alaska Fairbanks, Alaska, USA,rgrapenthin@alaska.edu; IEZZI, A., U.S. Geological Survey, Washington,
USA, aiezzi@usgs.gov; FEE, D., University of Alaska Fairbanks, Alaska, USA,dfee1@alaska.edu; HANEY, M. M., U.S. Geological Survey, Alaska, USA,mhaney@usgs.gov
The 2018-2023 phreatomagmatic eruption of Semisopochnoi volcano, Alaska
was well-recorded with local seismic and infrasound data following a network
upgrade in 2021. The dataset provides an excellent opportunity to investigate
precursory and syn-eruptive geophysical signals from a phreatomagmatic
eruption. We generated explosion and long-period (LP) event catalogs throughnovel implementations of the REDPy repeating event detector. The explosions
show a high degree of infrasound waveform similarity in hundreds of events
over more than a year, indicating a repeating source mechanism. The seismic
LP catalog shows that events began over a month prior to renewed explosive
activity at the beginning of August 2021, and that the frequency index (FI) of
LPs changed ~10 days prior to the onset of explosions. We applied a recently
developed machine learning tool (VOISS-Net) to identify abundant broadband and harmonic tremor recorded before and during the renewed explosive activity, along with LPs and explosions. The tremor catalogs complement
the LP and explosion catalogs by filling out the seismic sequence with all thedominant signal types. Harmonic tremor was observed during just two shorttime periods — most notably ~10 days prior to the onset of explosive activity,
concurrent with the change in FI of LP events. Broadband tremor was widely
observed following the onset of explosive activity.
Together, these catalogs reveal a seismic sequence of renewed unrest thatstarted with several weeks of LP events, followed by LPs with lower FI values
and harmonic tremor in the days prior to explosive activity, and finally theonset of discrete explosions and broadband eruption tremor. We interpret thissequence as the ascent of a new pulse of magmatic fluids that first interactedwith the hydrothermal system to produce LPs, followed by harmonic tremor,

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Seismological Research Lettersand that ultimately drove explosive eruptions and periods of continuous ash
emissions. The VOISS-Net tool represents a major advancement in our ability
to classify multiple signal types from continuous waveforms over months toyears, with potential for near real-time applications.
Investigation of Tremor and Explosion Sequences from the2021-2022 Eruption of Pavlof Volcano, Alaska using Deep
Learning
TAN, D., University of Alaska Fairbanks, Alaska, USA, ptan@alaska.edu;
FEE, D., University of Alaska Fairbanks, Alaska, USA, dfee1@alaska.edu;
GIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.girona@alaska.edu; HANEY, M. M., U.S. Geological Survey, Alaska, USA, mhaney@
usgs.gov; WITSIL, A., Applied Research Associates, North Carolina, USA,
alexjcwitsil@gmail.com; WECH, A., U.S. Geological Survey, Alaska, USA,awech@usgs.gov
Volcanoes can show variable behavior and unrest mechanisms over the courseof long eruptions. However, systematically documenting discrete episodes of
elevated seismicity and infrasound can be challenging and laborious, especially if monitoring parameters remain heightened or if the eruption lasts
for months or years. The 2021-2022 eruption of Pavlof Volcano, Alaska is
an example of a 1.5 year long eruption characterized by intermittent explosions, lava effusion, and low-level ash emissions. Although reliably monitoredby the local seismo-acoustic network, satellites, and webcams, the volcano
exhibited transitions in unrest regimes which are non-trivial to distill andanalyze. In this work, we leverage the diverse tremor and explosion dataset from this eruption to construct an extensive set of labeled seismic andinfrasound spectrograms. The labeled spectrograms, representing classes ofdifferent tremor types, explosions, earthquakes, and noise, are then used totrain VOISS-Net—a convolutional neural network for each data type. Then,the trained models are applied to classify two years of seismic and infrasounddata bounding the 2021-2022 eruption, and we implement a local networkwide weighting scheme to collapse station-specific classifications into a single result to reduce uncertainty. We find that our machine learning derived
timeline highlights explosion-rich phases in the eruption embedded withinmonths of broadband tremor, as well as explosion-poor phases that coincidewith increased thermal output and, at times, observed lava effusion. Beyond
general comparisons with multidisciplinary observations and eruption chronology, our approach also reveals interesting explosion-tremor sequences that
demonstrate pre-explosive quiescence, microseismicity, and/or transitions intremor spectra. We additionally demonstrate the transferability of our methods to earlier Pavlof Volcano eruptions (2007, 2013, 2014 and 2016), and elucidate the inter-eruption variability of the volcano’s characteristic seismicity.
Unique Seismic and Eruption Precursors to the 1996
Magmatic Eruptions of Popocatépetl: Coupled andFluidized Bed Events.
MCCAUSLAND, W., U.S. Geological Survey, Washington, USA,
wmccausland@usgs.gov; CABALLERO JIMENEZ, G. V., Centro Nacional dePrevención Desastres, Cuidad de México, Mexico, gema.caballero.jimenez@
gmail.com; GUEVARA ORTIZ, E., Centro Nacional de Prevención Desastres,
Ciudad de México, Mexico, eguevara@cenapred.unam.mx; TRUJILLOCASTRILLÓN, N., Servicio Geológico Colombiano, Manizales, Colombia,
canytas@gmail.com; VALDÉS GONZÁLEZ, C. M., Universidad Nacional
Autónoma de México, Ciudad de México, Mexico, cmvaldes_1@hotmail.com;
GÓMEZ VÁZQUEZ, Á., Centro Nacional de Prevención Desastres, Ciudadde México, Mexico, agomez@cenapred.unam.mx; DELGADO GRANADOS,
H., Universidad Nacional Autónoma de México, Ciudad de México, Mexico,
hugo@geofisica.unam.mx; WHITE, R. A., U.S. Geological Survey, California,
USA, rwhite@usgs.gov
Volcanic seismicity is generated by stress changes caused by many processes
occurring at different temporal and spatial scales, including those involvedin transporting magma and fluids from the mantle to the surface. Precursory
seismicity at Popocatépetl followed three of the four stages in White and
McCausland’s (2019; doi.org/10.1016/j.jvolgeores.2019.03.004) seismic andgeologic model of precursory volcanic seismicity. Seismicity began in 1990
with Stage 2, distal volcano tectonic (VT) seismicity, and peaked in magnitude and rate in late 1993 and early 1994. Then Stage 3 proximal vent-clearing
seismicity dominated while CO2 and SO2 emissions peaked. Stage 3 continued
after initial vent-clearing eruptions in December 1994 through the eruptionof the first domes in 1996. Stage 3 included three unique types of seismicity, fluidized bed events (tremor with coincident gas emissions that fluidize
vent deposits) and two types of coupled events: 1) spasmodic burst coupled
events, a burst of VTs coupled with a large eruptive explosion, and 2) explosion couplet coupled events, a pair of events with a deeper first event and shal-www.srl-online.org•

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low second event that correlates with a gas emission or explosion. Spasmodic
burst coupled events accompanied the initial 21 December 1994 and second
5 March 1996 eruptions. Starting mid-January 1995, fluidized bed eventsoccurred with continuing emissions after initial eruptions while SO2 emissions were elevated. Fluidized bed events and SO2 emissions waned in lateMarch. After the 5 March 1996 eruption, Stage 4 final magma ascent seismicity began as explosion couplets, and their properties were useful for forecasting magmatic eruptions at Popocatépetl volcano. Explosion couplet properties
systematically changed as the magma approached the surface the first threetimes between March and June 1996: interevent times (time between thefirst and second event) decreased by a factor of 4, while the amplitude ratio
between the second and first event increased by a factor of 5. Consistent gas,visual and seismic observations enabled this direct correlation of gas, magmaand seismic phenomena.
Constraining Links Between Seismicity and Eruptive
Processes for the December 2018 Flank Eruption at Mt Etna
EYLES, J., Massachusetts Institute of Technology, Massachusetts, USA,jeyles95@mit.edu; FRANK, W. B., Massachusetts Institute of Technology,
Massachusetts, USA, wfrank@mit.edu; POLI, P., University of Padova, Padua,
Italy, piero.poli@unipd.it
Volcanic systems produce a range of eruptive styles and durations; determining whether future eruptions will be explosive or effusive is key for reducing the hazards faced by local communities. Volcanic seismicity is a powerfulindicator of activity at volcanoes worldwide, providing information on volcanic structures and subsurface processes such as magmatic fluid transport.
Mt. Etna is the largest volcano in Europe and is continuously monitored by a
substantial seismic network; this provides an ideal location to quantitatively
constrain links between eruptive styles and seismicity. During periods ofintense volcanic activity, many seismic events will go undetected. Repeating
earthquakes are events that have identical waveforms, implying that they arefrom the same source origin and mechanism. A matched filter search identifies repeats of template events, including those which are hidden behind thenoise, and can increase a seismic catalogue by a factor of 10. The detected
seismicity is categorised into families of repeating and non-repeating sources,
and is analysed alongside subsurface observations to decipher information on
how the source process varies through time. Here we focus on a flank eruptionin December 2018 which saw a large increase in seismicity during the firstfew days of the eruption. We use 483 events detected by the INGV seismic
catalogue in December 2018 as templates for a matched filter search, detecting
over 35,000 events during the month. We use a combination of relative andabsolute location methods to further constrain hypocenter locations for thedetected events. This is used to establish a framework that links subsurface
processes and structures, providing a quantitative comparison with the vastand complex eruptive history of Mt. Etna.
Tracking Seismicity in an Underfunded Institution: The
Case of La Soufrière St Vincent Volcanic Eruption 2020–
2021
CONTRERAS-ARRATIA, R., Universidad Católica de Temuco, Temuco,
Chile, rodrigo.ca@uct.cl
An unusual volcanic transition was recorded at La Soufrière Volcano in theLesser Antilles during the 2020-2021 eruptive episode. Initial activity was aneffusive phase that lasted three months and turned explosive on 9 April 2021.
Although the transition was recognized when it occurred and people weretimely evacuated thanks to the detection of subtle geophysical patterns, thiswork attempts to extract more detailed information from the seismic dataset
to improve the monitoring of future events. Due to network limitations andthe low amplitudes of the recorded signals, the elaboration of a conceptualmodel from earthquake locations turned out to be challenging. Accordingly,
new analysis methods were developed, including: seismic interferometry using
cross-correlation functions to locate the sources of tremor and explosions anda fluid-filled crack model to quantify the bulk modulus of magma stored in thesystem and translate it to gas content. Both are now applied in quasi-real time
for the interpretation of future unrest. The VT locations feature a NNW-SSE
alignment across the eruption site with focal depths shallower than 4 km. The
banded tremor located at shallow levels (~1 km depth) and the explosions featured two distinct behaviors, deepening of sources as the eruption progressed,
as well as the activation of near-surface sources associated with the eruptive
jet. A fluid-filled crack model points to an injection of gas into the system
on 9 April, which amounts to approximately 76% gas-volume fraction. We
propose a volatile injection equivalent to a 7% gas-volume fraction entering
the system on 12 March; however, it was not energetic enough to produce

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changes in the extrusion rate. Seismological analyses support the conceptualmodel proposed by Joseph et al. (2022), where a dome sealed the system witha minimal amount of gas exsolved (0.7% gas-volume fraction). For the onsetof the explosive phase, the system accumulated enough gases to produce thedome collapse and cleared the vent, decreased the internal pressure and triggered fragmentation.
Understanding Volcanic Tremors Based on Seismic Network
Analysis
SHAPIRO, N. M., Institut des Sciences de la Terre, Grenoble, France, nikolai.
shapiro@univ-grenoble-alpes.fr; JOURNEAU, C., University of Oregon,
Oregon, USA, cyrilj@uoregon.edu; SOUBESTRE, J., Institut des Sciencesde la Terre, Chambery, France, jean.soubestre@gmail.com; BARAJAS, A.,
Institut des Sciences de la Terre, Grenoble, France, andres.barajas-ramirez@
univ-grenoble-alpes.fr; SEYDOUX, L., Institut de Physique du Globe deParis, Paris, France, seydoux@ipgp.fr; MELNIK, O., Institut des Sciences dela Terre, Grenoble, France, oleg.melnik@univ-grenoble-alpes.fr; BRACALE,
M., Institut des Sciences de la Terre, Grenoble, France, mirko.bracale@univgrenoble-alpes.fr; CAMPILLO, M., Institut des Sciences de la Terre, Grenoble,
France, michel.campillo@univ-grenoble-alpes.fr
Seismic tremors are largely used for monitoring the volcanic unrest. Single station approaches empirically relate them to the volcanic activity without providing information about their source locations and generation mechanisms.
To advance the understanding of tremors, we developed a method based on
the o network covariance matrix and is adapted to detect spatially coherent
signals without clear impulsive offsets, to measure their time-frequency properties, and to locate their sources.
We present applications of the network-based analysis to seismic tremors in two volcanic systems: Piton de la Fournaise volcano at la Réunion Island
and Klyuchevskoy Volcanic Group at Kamchatka. In the first case, the distribution of tremor source depths is well correlated with magma gas content,
indicating that the tremor generating mechanism is controlled by the shallow magma degassing. In the second case, the tremors sources are distributed
over a wide range of depths and the tremor activity is characterized by rapid
migrations. Overall, the tremor properties at the Klyuchevskoy volcanic groupindicate the existence of a highly dynamic trans-crustal magmatic system.
The tremors contain multiple narrow spectral lines that remain stable
over long periods of time and could be reminiscent of the particular source
properties. Alternatively, we argue that they can be due to the interferenceof multiple seismic waves resulting from a strong scattering. We perform
numerical experiments with propagating seismic waves in a medium containing multiple melt-rich pockets as can be expected in an active magmatic system. We demonstrate that such type of media heterogeneity leads to a strong
scattering and results in source spectra containing multiple spectral peaks,
similar to observations of tremors. The shape of these peaks is controlled by
the propagation effects and remains stable for fixed source position and media
properties. Therefore, variations of tremor spectral patterns can be used todetect changes in the volcano-plumbing systems such as moving positions of
the seismic activity sources or variations of the media properties.

Seismoacoustic, Geodetic and Other GeophysicalInvestigations of Active Volcanoes [Poster Session]
Poster Session • Friday 3 May
Conveners: Josh Crozier, U.S. Geological Survey (jcrozier@usgs.gov); Ricardo Garza-Giron, Colorado State University(rgarzagi@ucsc.edu); Margaret Glasgow, U.S. Geological
Survey (mglasgow@usgs.gov); Alicia Hotovec-Ellis, U.S.
Geological Survey (ahotovec-ellis@usgs.gov); John J. J. Lyons,
U.S. Geological Survey (jlyons@usgs.gov); Diana Roman,
Carnegie Science (droman@carnegiescience.edu)
poster 68
Surface Deformation at the Socorro Magma Body: A
Natural Laboratory for Probing Mush and Magma in the
Mid-Crust
BLOCK, G. A., University of New Mexico, New Mexico, USA, gblock@unm.
edu; ROY, M., University of New Mexico, New Mexico, USA, mroy@unm.
edu; GRAVES, E., University of Alaska Fairbanks, Alaska, USA, egraves4@

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alaska.edu; GRAPENTHIN, R., University of Alaska Fairbanks, Alaska, USA,rgrapenthin@alaska.edu
Surface deformation measurements play a key role in illuminating magmatransport at active volcanoes. However, it is often challenging to untangle
shallow volcanic deformation signals from deeper magma dynamics. The
Socorro Magma Body (SMB) is a seismically-inferred mid-crustal magma
body which lacks an upper crustal magma transport system, providing a rareopportunity to directly link geodetic measurements with mid-crustal magma
dynamics. New InSAR observations confirm a pattern of central surface upliftsurrounded by a region of subsidence (previously coined “sombrero” deformation) has persisted for over 100 years at the SMB with minimal change to
its wavelength or magnitude. Seismic observations suggest the presence of alarge (>100 km width), seismically slow region surrounding the inferred SMB.
This low velocity zone may be caused by thermal weakening and/or partial
melt related to the magma body. Inspired by these observations, we develop
numerical models that explore the interactions between a weaker-thanambient, compliant region (CR) surrounding a pressurizing sill-like source.
Episodic pressurization (potentially due to melt injection and/or volatile
exsolution) within a viscoelastic CR drive a sombrero deformation pattern,
producing good agreement in width, magnitude, and duration with InSAR
and previous GPS and leveling studies. Long lasting sombrero deformation in
our models is dependent both on a sufficiently weakened (low viscosity) CR
and an asymmetric (re-/de-)pressurization cycle. Building on these results, weinvestigate how time and temperature dependent rheology of the CR, together
with poroelastic effects, may manifest in surface deformations. Additionally,
to explore more complex volcanic systems, we include a second, shallower
pressurizing source within the CR. Our goal is to understand how multiple
magma bodies within a weaker-than-ambient CR may interact and drive complex surface deformation at volcanoes.
poster 69
Automated Detection of Volcanic Seismicity Using
Network Covariance and Image Processing
MAHER, S., Zanskar Geothermal & Minerals, Inc., Utah, USA, smaher@
usgs.gov; DAWSON, P., U.S. Geological Survey, California, USA, dawson@
usgs.gov; HOTOVEC-ELLIS, A., U.S. Geological Survey, California, USA,ahotovec-ellis@usgs.gov; THELEN, W., U.S. Geological Survey, Washington,
USA, wthelen@usgs.gov; MATOZA, R., University of California, Santa
Barbara, California, USA, rmatoza@ucsb.edu
Seismicity at restless volcanoes commonly features a variety of signal types
reflecting both tectonic and fluid-driven source processes. However, traditional catalogs of seismicity are often incomplete, especially with respect toevents with emergent onsets such as those driven by the dynamics of magmatic and hydrothermal fluids. The detection of all discrete events and seismic tremor regardless of the underlying source processes would therefore
improve the ability of monitoring agencies to forecast eruptions and mitigate
their associated hazards. We present a workflow for generalized detection ofseismic events based on the eigenvalue decomposition of the network covariance matrix. We invoke new approaches for data-preprocessing and apply
image processing techniques (i.e., noise reduction, smoothing, and thresholding of the spectral width image) to enable event detection and classification.
Our unsupervised workflow requires no model building, data labelling, or apriori knowledge regarding event types. This approach can simultaneously
detect continuous and short duration events and provide information about
the frequency content of the signals. We test the workflow on a 15-month
record of seismicity from Mammoth Mountain, California (7/2012–10/2013)and detect 62% of long-period events and 94% of volcano-tectonic events inthe existing Northern California Earthquake Data Center catalog. In addition, thousands of new events and tremor signals are detected. The method issuitable for near-real time analysis of continuous waveforms and can provide
a valuable supplement to existing algorithms to improve the completeness ofcatalogs used for monitoring volcanoes.
poster 70
Long-Period Earthquakes in the Yellowstone Volcanic
System: When, Where, Why?
FARRELL, J., University of Utah, Utah, USA, jamie.farrell@utah.edu; HALE,
M., University of Utah, Utah, USA, jmhale@seis.utah.edu; BAKER, B.,
University of Utah, Utah, USA, ben.baker@utah.edu
Long-Period earthquakes (LPs) have been observed at many volcanic systems
throughout the world including Kilauea, Long Valley, and the Cascades just to
name a few. However, LPs have never been documented in the over 50 years

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that may be LP events. Both these events occurred in 2021 and are enrichedin energy below 5 Hz. We present data on these two potential Yellowstone LP
earthquakes as well as results using them as templates and searching throughcontinuous waveform data in Yellowstone for more potential LP events.
poster 71
Mining for Hidden Seismicity at Mount St. Helens
HIRAO, B. W., University of Oregon, Oregon, USA, bhirao@ucsc.edu;
THOMAS, A. M., University of Oregon, Oregon, USA, amt.seismo@gmail.
com; SHELLY, D. R., U.S. Geological Survey, Colorado, USA, dshelly@usgs.
gov; THELEN, W., U.S. Geological Survey, Washington, USA, wthelen@usgs.
gov
Mount St. Helens is the most active and well-instrumented volcano in the
Cascade Range. Seismicity catalogs provide fundamental observations ofactive volcanic and tectonic structures within Mount St. Helens and can reveal
its deep-seated volcanic plumbing system. We develop a more comprehensive seismicity catalog at Mount St. Helens by making use of novel machinelearning algorithms and traditional matched-filter procedures to detect previously unidentified earthquakes from continuous seismic data recorded frompermanent seismometers (networks UW, CC, and PB) from 2009 to 2023.
With our new seismicity catalog, we hope to further address several outstanding problems surrounding the nature of seismicity at Mount St. Helens andCascade volcanism. Such inquiries may inform the relationship between seismicity amongst deep and shallow depth structures, stress transfer between
the volcanic conduit and chamber due to magma transport, and potential forseasonal dependence of shallow volcanic earthquake swarms.
Our workflow uses a convolutional neural network trained with analystmade phase picks from Mount St. Helens to identify P- and S-wave phasearrivals, which are then associated with GaMMA–a Gaussian Mixed Modelclustering algorithm and located by grid search of three-dimensional P- andS-wave velocity travel time grids from the shallow crust velocity models ofKiser et al. (2019). To maximize our detection capabilities and measure differential travel times, we then apply a continuous matched-filter with templatesconsisting of previously cataloged earthquakes and newly detected earthquakes from our machine learning algorithm. Lastly, we locate or relocate
all detected earthquakes with the GrowClust3D double-difference location
algorithm.
poster 72
Ground-Tilt Caused by Atmospheric Lamb Waves From the2022 Tonga Eruption Recorded at Fiji and Pinon Flat
Observatory
ICHINOSE, G., Lawrence Livermore National Laboratory, California, USA,ichinose1@llnl.gov; MELLORS, R. J., University of California, San Diego,
California, USA, rmellors@ucsd.edu
Ground tilt is commonly attributed to atmospheric pressure changes such as
hurricanes and strong storms. In these cases, ground tilt has been measured ashorizontal-to-vertical component pseudo spectral amplitude ratios and correlated to barometric pressure (e.g., Anthony et al., 2014; Tanimoto and Wang,2018). Directly comparing time histories, with amplitude and phase, between
air-pressure and rotational motions or strain tilt-meters is not performed asstorms are not distinct events. We used the atmospheric Lamb waves inducedby the 2022 Hunga-Tonga volcanic eruption to directly compare the barometric pressure change to ground tilt estimated from array-derived strain at the
Pinon Flat Observatory (PFO). PFO is 8658 km from the eruption and operates a broadband seismic array, a rotational seismometer, and strain meter.
The PFO maximum rotation rate is 4x10-9 radians/sec which is similar to tilt
recorded by magnitude 3 earthquake at a distance of 800 km. We also findgood agreement between Monasavu Fiji (MSVF) low-frequency transverse
component displacements to barometric pressure time histories suggesting
MSVF was also affected by ground tilt at 750 km distance. The response of
MSVF air-to-ground coupling to a low-pressure pulse may have mysteriously
caused the absence of high-frequencies signals > 1 Hz. These observation
underscores the potential of including more strain and barometric pressure
sensors into seismic network monitoring for the detection and modeling of
atmospheric pressure waves. Prepared by LLNL under Contract DE-AC5207NA27344. LLNL-ABS-858923.

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poster 73
Soundquakes: Seismo-Infrasonic and Seismo-Infra-Seismic
Phases During a Swarm of Earthquakes at Kilauea Volcano
on September 30th, 2021
JOHNSON, J., Boise State University, Idaho, USA, jeffreybjohnson@boisestate.edu; JOLLY, A., U.S. Geological Survey, Idaho, USA, ajolly@usgs.gov;
ANDERSON, J. F., Boise State University, Idaho, USA, jacobanderson152@
boisestate.edu
Seismic waves produced by earthquakes can shake the ground and produce
infrasound either local to an infrasound station (i.e., primary infrasound) orfrom locations away from the recording site, which then propagate sound subhorizontally toward the station (secondary infrasound). This study focuseson infrasonic waves generated by ~20 earthquakes occurring during a onehour period prior to a summit eruption of Kilauea starting at 01:21 UTC on
September 30th, 2021. These small earthquakes (M<=2.7) were shallow (<2km) and all but two were located near the Halema’uma’u crater. A network of
three infrasound arrays located about 3 km E, ENE, and ESE of Halema’uma’ucrater was operational during this swarm and recorded prominent (infrasonic) air phases from these earthquakes.
The infrasound arrays were capable of detecting infrasound and also
determining apparent velocities, which ranged from those expected forhorizontal sound to faster velocities associated with primary infrasound.
Backazimuth projection of the infrasound showed that secondary sourcesfrom a single ‘soundquake’ typically lasting tens of seconds originated from a
range of directions apparently from different topography around the Kilauea
Caldera excited by ground motion. Several locations, including the westerncaldera walls of Kilauea, appear to be particularly pronounced ‘hotspots’ forinfrasound generation. The networked array of sensors is useful for triangulating many of these sources using reverse time migration and beam information.
The unique topology of the Kilauea infrasound network of arrays permits particularly high resolution mapping of earthquake infrasound radiators.
A significant finding is the prevalence of earthquake infrasound and its (perhaps) poorly appreciated impact upon the seismic wavefield. Similarly-shaped
signal envelopes for the coda wave decay for both infrasound and seismicenergy suggests that some of the infrasound is re-transmitted to the ground.
This energy, contributing to the seismic coda, represents the prevalence ofan underappreciated seismo-infrasonic-seismic phase in the seismic records.
poster 74
Laboratory Experiments on Gas-Driven Volcanic Tremorand Long Period Seismicity
KIM, K., University of Alaska Fairbanks, Alaska, USA, kkim39@alaska.edu;
SPINA, L., Instituto Nazionale Di Geofisica E Vulcanologia, Sezione di Roma1,
Rome, Italy, laura.spina@ingv.it; TADDEUCCI, J., Instituto Nazionale Di
Geofisica E Vulcanologia, Sezione di Roma1, Rome, Italy, jacopo.taddeucci@
ingv.it; PENNACCHIA, F., Instituto Nazionale Di Geofisica E Vulcanologia,
Sezione di Roma1, Rome, Italy, francesco.pennacchia@ingv.it; CORNELIO,
C., Instituto Nazionale Di Geofisica E Vulcanologia, Sezione di Roma1, Rome,
Italy, chiara.cornelio@ingv.it; SPAGNUOLO, E., Instituto Nazionale Di
Geofisica E Vulcanologia, Sezione di Roma1, Rome, Italy, elena.spagnuolo@
ingv.it; GIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.
girona@alaska.edu
Volcanic tremor and long-period (LP) events are seismic signals linked tomagmatic/hydrothermal fluid processes. Previous theoretical research suggests that the accumulation of gas beneath permeable caps within the shallow volcanic conduit leads to spontaneous pressure oscillations that can
produce volcanic tremor and LP events (Girona et al., 2019; https://doi.
org/10.1029/2019JB017482). Here we explore experimentally this hypothesis
as a function of gas flux and geometry and permeability of the permeable cap.
We devised an experimental setup comprising a vertically-arranged cylindrical pipe (4 cm internal diameter) which, from base to top, includes: 1) a water
infill; 2) an air pocket; 3) a permeable cap; and 4) an upper pipe open to air. We
injected air into the water at the base of the pipe using a set of gas flow metersand monitored pressure oscillations in the air pocket beneath the permeable
cap, tracked vibrations (acceleration) of the pipe, and recorded pressure signals in the upper pipe above the cap using a microphone. Different permeability, pore arrangements, and thickness of the cap were explored. Preliminary
results show that gas flow through the water without permeable cap generates
low-frequency pressure oscillation (< 1~5 Hz) in the free air above, potentiallyrelated to bubble bursts. In the presence of the permeable cap, pressure oscillations in the 2-150 Hz frequency band appear in the air pocket beneath thecap, implying resonance due to gas accumulation. Different characteristics ofthe porous media, such as straight capillary pores and spongy materials withvarying permeability, generate distinct waveform features, including different

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vibrations and microphone signals. For example, gas flow through straightcapillary pores exhibits periodic peaks in microphone records, suggesting thatpermeable gas flow may control periodic volcanic outgassing. Our study offersa laboratory approach to unveil the seismoacoustic signals linked to gas circulation within porous media and serves as a reference for explaining volcano
monitoring signals in natural settings.
poster 75
Monitoring Unrest at a Supervolcano: Insights From the2022-23 Unrest Episode at Taupō Volcano, Aotearoa New
Zealand
LAMB, O., GNS Science, Taupō, New Zealand, o.lamb@gns.cri.
nz; HREINSDÓTTIR, S., GNS Science, Lower Hutt, New Zealand,
S.Hreinsdottir@gns.cri.nz; POWER, W., GNS Science, Lower Hutt, New
Zealand, W.Power@gns.cri.nz; BANNISTER, S., GNS Science, Lower Hutt,
New Zealand, S.Bannister@gns.cri.nz; RISTAU, J., GNS Science, Lower Hutt,
New Zealand, j.ristau@gns.cri.nz; MILLER, C., GNS Science, Taupō, New
Zealand, c.miller@gns.cri.nz; MESTEL, E., Victoria University of Wellington,
Wellington, New Zealand, el.mestel@vuw.ac.nz; ILLSLEY-KEMP, F., Victoria
University of Wellington, Wellington, New Zealand, finnigan.illsleykemp@
vuw.ac.nz; JACOBS, K., GNS Science, Lower Hutt, New Zealand, k.jacobs@
gns.cri.nz; HAMLING, I., GNS Science, Lower Hutt, New Zealand,i.hamling@gns.cri.nz; SPESIVTSEV, A., GNS Science, Lower Hutt, New
Zealand, a.spesivtsev@gns.cri.nz; ROGER, J., GNS Science, Lower Hutt, New
Zealand, j.roger@gns.cri.nz; GUSMAN, A., GNS Science, Lower Hutt, New
Zealand, a.gusman@gns.cri.nz; WANG, X., GNS Science, Lower Hutt, New
Zealand, x.wang@gns.cri.nz; BURBIDGE, D., GNS Science, Lower Hutt, New
Zealand, D.Burbidge@gns.cri.nz
Taupō is a large caldera volcano located beneath a lake in the North Islandof Aotearoa New Zealand and most recently erupted ~1800 years ago. The
volcano has experienced at least 16 unrest episodes since 1872, many of whichwere characterised by increased seismic activity. In May 2022 the volcano
entered a new unrest period with increased earthquake activity and grounddeformation within the caldera. The unrest was notable for two reasons: (1)the Volcanic Alert Level for Taupō was raised from VAL 0 to VAL 1 for the
first time, and (2) a M 5.7 in November 2022 was one of the largest magnitude
earthquakes detected beneath the lake for at least 50 years, triggering a small
yet complex tsunami within the lake. The unrest ended in May 2023 whenseismic activity returned to background levels. This presentation aims to givean overview of seismic, geodetic, and tsunami observations during the unrest
and what indications these give on the state of the volcanic system during theunrest.
Over 1780 earthquakes were automatically detected beneath the lakeover the 13-month unrest period, the highest number recorded during instrumented unrest episodes at the volcano. Four distinct phases were identified
based on weekly earthquake detection rates, with relocations suggesting activity was focused around overlapping caldera structures beneath the lake. A
rapid 50 mm/yr inflation was detected at a GNSS station located within thelake, peaking during the M 5.7 earthquake with 18 cm uplift and 25 cm horizontal movement. Modelling of the GNSS data suggests the inflation source
was located at 4-8 km depth beneath the lake. The lake tsunami was recordedby three water-level gauges and a survey was conducted to record inundation
heights around the lake. Analysis suggests the small tsunami was generated by
two sources: a sub-lacustrine landslide near the town of Taupō, and upward
movement of the lakebed. Altogether, we suggest the 2022-23 unrest episodeat Taupō volcano was caused by an intrusion of magma at depth with seismic
activity generated by reactivation of faults beneath the lake.
poster 76
Imaging the Magma Plumbing System Below Okmok
Volcano Using Full-Wave Ambient Noise Tomography
LIZIK, Y., Purdue University, Indiana, USA, ylizik@purdue.edu; MAURER,
J., Missouri University of Science and Technology, Missouri, USA, jmaurer@
mst.edu; YANG, X., Purdue University, Indiana, USA, xtyang@purdue.edu;
KUPRES, C. A., Purdue University, Indiana, USA, ckupres@purdue.edu
Volcanic eruptions can pose a substantial threat to society, causing significant
impacts on economic and social activities during their eruptive periods. To
advance volcano monitoring, eruption forecasting, and hazard assessment, an
improved understanding of the magmatic processes and plumbing systems
beneath active volcanoes is essential. Okmok Volcano in the eastern Aleutian
Arc represents a complex magmatic system, distinguished by decades-longdevelopment of eruptive cones and short-term seismicity migrations. Its eruption cycle follows a cyclic pattern of magma reservoir recharge and discharge
events with documented eruptions styles ranging from effusive to explosive.

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Previous seismic imaging studies imply Okmok has multiple magma sources
at varying depths, supported by geodetic observations, yet the structure andgeometry of these magma reservoirs remain poorly defined. Our study aims
to construct a high-resolution 3-D seismic velocity model of Okmok down
to a depth of 15 km below sea level using full-wave ambient noise tomography. The resulting model will enable us to locate possible magma sourcesbeneath the volcano using an expanded seismic dataset. To support our interpretations, we will incorporate the imaging results with geodetic observations,deformation modeling, and volcano seismicity. The results of this multidisciplinary investigation will deepen our understanding of volcanic processes
and magma dynamics at Okmok and, by extension, hold relevance for otheractive volcanoes.
poster 77
Crustal Structure of the Laguna Del Maule Volcanic Field
Using Receiver Functions
NOLT-CARAWAY, S., New Mexico Institute of Mining and Technology,
New Mexico, USA, san264@nau.edu; PORTNER, D., New Mexico Institute of
Mining and Technology, New Mexico, USA, daniel.portner@nmt.edu
The Laguna del Maule (LdM) volcanic field in central Chile has had considerable postglacial rhyolitic eruptions supplied by a shallow, crustal magma reservoir. Today, this reservoir is characterized by extensive seismicity and periods of inflation. Geophysical studies have shown there is a low density, highconductivity, low seismic velocity anomaly inferred to contain partial melting
up to 14%. Geodetics and seismicity studies also show the likely source of
inflation and seismicity coincides with the low velocity anomaly, implying
active recharge from a deeper source. While the presence of an upper crustal
magma reservoir is consistent in prior geophysical imaging, questions remain
regarding the detailed geometry of the reservoir and how it fits within thetranscrustal magmatic system feeding LdM. Using seismic stations deployed
between 2015-2018, we conduct receiver function analysis to get better constraints on the detailed crustal structure below LdM. Preliminary results show
there is heterogeneity across the LdM volcanic field and a weak Moho. There
are several strong mid-crustal conversions that are spatially limited. These
mid-crustal conversions may indicate a more complex upper-mid crustal reservoir system. A weak moho signature may imply a weak or gradual structural
crust-mantle transition.
poster 78
Seismological Models and Seismicity Patterns in the Kivu
Rift and Virunga Volcanic Province (D.R. Congo)
SUBIRA, J., Goma Volcano Observatory, Goma, Democratic Republic of
the Congo, jos_sm@outlook.com; BARRIÈRE, J., European Center for
Geodynamics and Seismology, Walferdange, Luxembourg, julien.barriere@
ecgs.lu; CAUDRON, C., Université Libre de Bruxelles, Brussels, Belgium,corentin.caudron@gmail.com; OTH, A., European Center for Geodynamics
and Seismology, Lintgen, Luxembourg, adrien.oth@web.de; D’OREYE, N.,
National Museum for Natural History, Luxembourg, Luxembourg, ndo@
ecgs.lu; HUBERT-FERRARI, A., Université de Liège, Liège, Belgium, aurelia.
ferrari@uliege.be; KERVYN, F., Royal Museum for Central Africa, Tervuren,
Belgium, francois.kervyn@africamuseum.be
The Kivu Rift is located in the bordering region of the Democratic Republic ofCongo and Rwanda, in the Western branch of the East African Rift. The active
volcanoes Nyamulagira and Nyiragongo in the Virunga Volcanic Province
threaten the city of Goma and neighbouring agglomerations. Urbanisation inthat region undergoes sustained rapid growth, and the region currently counts
1 million inhabitants today. In 1977, 2002 and 2021, eruptions of Nyiragongo
caused major disasters. Destructive earthquakes can also affect the region, as
the Kalehe (Mw 6.2) earthquake in 2002 along the western shore of Lake Kivu,
or in 2008 in Bukavu (Mw 5.9), south of Lake Kivu.
Between 2013 and 2022, the first dense real-time telemetered broadband
seismic network in the Kivu Rift region (KivuSNet) was gradually deployedin the frame of several research projects and was fully operational with a sufficient station coverage (>10 stations) since October 2015. Due to the fundamental importance of monitoring the seismicity in this region, substantial efforts were made for setting up this permanent network with real-timedata acquisition, which thus rapidly became the main seismic network of theGoma Volcano Observatory for daily routine monitoring work.
This contribution will present the lessons learned from more than 61/2
years (October 2015–June 2022) of continuous seismic monitoring in the theKivu basin as well as the current status of seismological information derived
from these data, including a robust 1D seismic velocity model and calibrated
local magnitude scale for the Kivu Rift region. The complete seismicity catalogue (volcanic and tectonic events) has been relocated and the main seismic

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Seismological Research Letterspatterns will be discussed with a special emphasis on how this new knowledge
can help the Goma Volcano Observatory in improving its monitoring tasks.
poster 79
Seismicity Classification From Eruptions: Analysis of
Hawaiian and Aleutian Island Volcanoes
RINTY, S., University of Memphis, Tennessee, USA, srinty@memphis.
edu; GOEBEL, T. H., University of Memphis, Tennessee, USA, thgoebel@
memphis.edu
Volcanic eruptions produce different types of seismic signals, and monitoring these signals is crucial for understanding underlying processes. Associatedseismic signals can be classified as volcano-tectonic (VT), long-period (LP),tremor, explosive, tornillo, and hybrid events. Classification using standard
and machine learning algorithms are commonly based on features selected in
the time and frequency domain. Such features include, for example, dominantfrequency band, power spectral density, energy ratios, duration, peak amplitude, and rate of amplitude decay.
Here, we analyze seismicity associated with major eruptive phases of theKilauea volcano, Hawaii, Okmok, and Akutan volcano, Alaska. Cyclical pressure variation due to recurring inflation and deflation during caldera collapse
is likely to influence the associated seismicity. We are motivated to understandhow the caldera collapse sequence and the eruption phases influenced thetypes of seismic events.
We are focusing on spectrogram analysis based on both spectral andtemporal characteristics of events for this study. The selected stations arewithin 5 to 25km from the caldera, to avoid noise and site effects related tovolcanic processes. VT events have a clear P and S wave arrivals. Spectrograms
and power spectral density show that the frequency range of VT is above 5 Hz
and can be up to 30 Hz. LPs show a lack of distinguishable phase arrivals, anddurations are longer than those of VTs. The peak frequency of LP is mostly
within 5 to 10 Hz.
The sampling rate of the waveforms is 100 Hz. We computed the energy
ratio of spectral energy below a threshold frequency of 3Hz, 5Hz, and 10Hz to
the total energy. This energy ratio shows a clear bimodal distribution for 5Hz,
which helped to differentiate the VT and LP events based on their energy.
Tremors are characterized by relatively consistent amplitude and over very
long durations and time periods of minutes to hours. We successfully classified VT, LP, and tremors from the seismic events during the eruption period.
poster 80
Analysis of the Seismicity Recorded Before the May 22,2021 Eruption of Nyiragongo Volcano, Democratic Republicof the Congo
SADIKI, A., Goma Volcano Observatory, Goma City, Democratic
Republic of the Congo, sadikiarsenetb@gmail.com; KYAMBIKWA, A.,
Goma Volcano Observatory, Goma, Democratic Republic of the Congo,
albertuskabi@gmail.com; NAMOGO, D., Goma Volcano Observatory,
Goma, Democratic Republic of the Congo, didiernamogo02@gmail.com;
DIOMI, L., Goma Volcano Observatory, Goma, Democratic Republic of theCongo, laetitiadiominsona@gmail.com; MUNGUIKO, O., Goma Volcano
Observatory, Goma, Democratic Republic of the Congo, munguikolive@
gmail.com; BALEZI, G., Goma Volcano Observatory, Goma, Democratic
Republic of the Congo, balezimapendogentil17@gmail.com; SIFA, L., Goma
Volcano Observatory, Goma, Democratic Republic of the Congo, lydiesifarr@
gmail.com; MASHAGIRO, N., Goma Volcano Observatory, Goma,
Democratic Republic of the Congo, nichemashagiro@gmail.com; BALAGIZI,C., Goma Volcano Observatory, Goma, Democratic Republic of the Congo,balagizi.charles@gmail.com; MAVONGA, G., Goma Volcano Observatory,
Goma, Democratic Republic of the Congo, mavotulu@gmail.com
We present an overview of the different seismic precursors of the Nyiragongo
volcano eruption on May 22, 2021, as well as a statistical analysis of the seismic swarms recorded during the pre-eruptive period. The analysis of the seismic activity of Nyiragongo volcano during the pre-eruptive period shows that
there was a particular seismicity composed of hybrid and/or volcano-tectonic
type events that characterized the long-period seismic swarm recorded abouta month before the May 2021 eruption. In February 2016, similar seismic
activity was observed at Nyiragongo volcano, which led to the opening of a
new vent within Nyiragongo’s main crater on February 29, 2016, and which
remained active until the May 2021 eruption.
During the period from January 2016 to May 2021, the lava lakeremained very active with significant fluctuation as evidenced by the Real
Seismic Amplitude measurement at Rusayo and Kibati stations. The increase
and stabilization of the lava lake to a higher level resulted in an increase andaccumulation of stress on the flanks of the volcano since the lava lake had

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already reached a higher critical level. Whether in January 2016, November
2016 or April 2021, we show that this particular type of so-called hybrid seismic events recorded during a swarm at Nyiragongo volcano could lead to an
eruption either inside the main crater (February 2016) or on the flanks in
May 2021.
poster 81
Seismic Source Scaling of Volcano-Seismic Events: Tracking
Magma Plumbing System Overpressure and Volume
Through Macroscopic Seismic Source Parameters
NIU, J., Chinese Academy of Sciences, Beijing, China, jniu@mail.iggcas.ac.cn;
SONG, T., University College London, London, United Kingdom, alex.song@ucl.ac.uk
Volcano-seismic resonances are often manifested as long-period (LP), verylong-period (VLP) events, or volcanic tremors. Unlike tectonic earthquakes
and low-frequency earthquakes, volcano-seismic resonance reflects magmaticor hydrothermal fluid dynamics occurring at shallow depths during either
quiescent or eruptive episodes. Although experimental and numerical simulations have recognized fundamental microscopic dynamics associated withgas-liquid interaction and fluid-solid interaction in the volcano plumbing system, quantitative assessment of the underlying dynamics is often retrospective. Here we explore source scaling relationship for volcano-seismic eventsfrom a global perspective and derive a theoretical model to understand such
scaling related to overpressure and pressurized volume in magmatic systems,
which could provide crucial information in evaluating the state of the systemstability and the potential of incoming eruptions.
In this report, we compile macroseismic source parameters, specifically the peak seismic moment rate and the magnitude of single force fromvolcano-seismic events in 26 active volcanoes, displaying a prominent scaling
trend, i.e., 10-3~10-4 s/m. Following the framework developed by Nishimura(1998), we devise a generic framework, which relates the system overpressure
and pressurization volume to macroscopic seismic source parameters, as wellas the acoustic properties of the fluid near the seismic source (i.e., sound speed
and density).
We find that the estimated overpressures associated with volcano-seismic events in the 26 active volcanoes ranges in 104-108 Pa, clustered at ;106-107
Pa, whereas the estimated volume ranges in 103-1011 m3, clustered at ~106 m3
and ~108 m3, respectively. We will discuss the uncertainties associated withthe estimated overpressure and volume and how these quantities vary against
magma composition, volcanic activities (e.g., magmatic vs. hydrothermal)
and the type of volcano-seismic event (e.g., non-destructive vs. eruptive).
poster 82
Eruption Dynamics of the 2022 Mauna Loa Eruption
Revealed Through Tremor
THELEN, W., U.S. Geological Survey, Washington, USA, wthelen@usgs.
gov; IEZZI, A. M., U.S. Geological Survey, Washington, USA, aiezzi@usgs.
gov; CHANG, J. C., U.S. Geological Survey, Hawaii, USA, jchang@usgs.gov;
DOTRAY, P., U.S. Geological Survey, Hawaii, USA, pdotray@usgs.gov
Mauna Loa, Hawaii erupted for 12 days in 2022 following nearly 38 years of
repose. The eruption began after several years of intermittent unrest, including inflation and earthquake swarms, however the only actionable precursor
was approximately one hour of strong seismicity and tremor before the startof the eruption. The eruption started in the summit and eventually migrated
into the NE rift zone over approximately three hours, eventually establishingthe dominant fissure eight kilometers from the summit. On December 10, thefissure stopped erupting, ending the eruption.
During the eruption, seismic tremor was common and continuous andthus we can use the characteristics of tremor to reveal details of the eruption throughout the sequence. In particular, we use amplitude-based location
methods to track changes in vent location and dike propagation. In the precursory phase of the eruption, we find tremor locations throughout the upper
8 km of the volcano and then immediately before the eruption within theupper 4 km of the volcano. Once the eruption starts, tremor depths shallow
to the surface and remain stable for 2.5 hours before tremor locations deepenand shift into the NE Rift Zone. Analysis of tremor spectra show the likely
presence of two simultaneous source of tremor, one in the summit associatedwith lava fountaining, and another deeper source associated with dike propagation. Tremor locations further detail dike propagation downrift until thestable fissure, Fissure 3, becomes dominant. Tremor locations cluster aroundthe Fissure 3 vent until the end of the eruption when locations slowly migrateback uprift toward the summit.

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poster 83
Using Remote Hydroacoustic Recordings to Track Volcanic
Unrest Near the Ta‘ū Islands, American Samoa
WECH, A., U.S. Geological Survey, Alaska, USA, awech@usgs.gov; HANEY,
M. M., U.S. Geological Survey, Alaska, USA, mhaney@usgs.gov; CHANG, J.
C., U.S. Geological Survey, Hawaii, USA, jchang@usgs.gov; JOLLY, A., U.S.
Geological Survey, Hawaii, USA, ajolly@usgs.gov; YOON, C., U.S. Geological
Survey, California, USA, cyoon@usgs.gov
A seismic swarm near Ta‘ū Island, a volcanic island in eastern American
Samoa, occurred from July to October 2022. The earliest unrest was noted
as felt reports in late July, and instrumentation varied in the beginning of thesequence as the Hawaiian Volcano Observatory responded by installing temporary and then permanent seismometers to monitor the activity. The network
variability made it difficult to characterize the earliest seismicity and contextualize the entire sequence to discriminate between an underlying tectonic or
volcanic source. Here we present results analyzing hydroacoustic detections
from International Monitoring System hydrophone arrays near Wake Island,
4500 km northwest of Ta‘ū volcano. Using least-squares beamforming analysis, we create a catalog of T-wave detections from the direction of Ta‘ū volcano
to track the earthquake rate. Both the rate and hydroacoustic pressures, which
we interpret as a proxy for earthquake magnitude, gradually increased fromlate July to August, peaking on August 19 (rate) and August 24 (magnitude),
before gradually decreasing to background in late September. Minutes-longbursts of tremor were also contemporaneously recorded from the moment
the permanent broadband seismometers were installed on August 20. Tremor
activity continued throughout the rest of August, peaking on August 25,
before ending in early September. These tremor bursts were band-limited to~1-5 Hz and were recorded as S-waves at a distal station on Tutuila Island,
230 km to the west of Ta‘ū Island. Our preliminary results do not constrain
the earthquake or tremor locations (which may not be co-located), but weinterpret the increase in earthquake size and rate, together with the occurrence and characteristics of the tremors, to be the result of magmatic activity
beneath Ta‘ū, volcano.
poster 84
Inversion of Multiple Concurrent Resonant Oscillations atKīlauea Volcano During Very-Long-Period Seismic Events
Informs Magma System Properties.
WILDE, K. L., University of Oregon, Oregon, USA, kwilde@uoregon.edu;
KARLSTROM, L., University of Oregon, Oregon, USA, leif@uoregon.edu;
CROZIER, J. A., U.S. Geological Survey, California, USA, jcrozier@usgs.gov;
LYNN, K. J., U.S. Geological Survey, Hawaii, USA, klynn@usgs.gov
Kīlauea Volcano in Hawai‘i (USA) is one of the most active and best studied
volcanoes in the world. From 2008-2018, it experienced an open-vent eruption at the summit, allowing for the collection of diverse datasets. Thousandsof very long period (VLP) seismic events (signals with periods T >2 seconds)
were recorded in the summit region throughout this time. These signals havebeen inferred to signify perturbations in the shallow subsurface motions ofmelt and gas, which can provide insight into the evolving geometry of themagmatic system and magma properties such as temperature, viscosity, andvolatile content. In this study, we focus on two common modes of resonance:a vertical conduit-magma reservoir sloshing mode (T ~35-43 s) and a conduit
organ pipe mode (T ~2-4 s), both excited by rock fall events on the lava lake
surface. Over timescales of days-weeks, these modes generally exhibit quasiconstant resonant periods, but the quality factor can be highly variable. We
interpret this as a change in magma fluid properties, such as temperature or
bubble content, within the shallow (<2 km) summit transport system. We
invert the two distinct associated resonant modes from individual VLP eventswith a petrologically-informed model of wave propagation in a multiphase,viscous, stratified magma column representing the lava lake-conduit-reservoir system to seek further constraints on magma properties and transport
geometry during that period. We augment seismic data with geodetic constraints on reservoir geometry/pressure and MgO glass thermometry data toconstrain the temperature of the lava lake (1151-1158 range, +/- 10 degC),
both of which help define the background state of the magma column prior to
VLP events. We use footage of the lake surface to confirm the origin of VLP
excitation. This approach will provide us with a well-constrained snapshot of
the subsurface geometry and magmatic properties at the times of the VLP
events, and thus can better inform our understanding of coinciding eruptive
processes.

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poster 85
Seismic Velocity Changes Across Multiple Eruption Cycles
at Shishaldin Volcano in the Eastern Aleutian Arc
YANG, X., Purdue University, Indiana, USA, xtyang@purdue.edu;
FREYMUELLER, J. T., Michigan State University, Michigan, USA, freymuel@msu.edu; KUPRES, C. A., Purdue University, Indiana, USA, ckupres@purdue.edu; DENOLLE, M. A., University of Washington, Washington, USA,mdenolle@uw.edu; HANEY, M. M., U.S. Geological Survey, Alaska, USA,mhaney@usgs.gov
Volcanic eruptions can be disastrous, so understanding the development of
eruptive activity has significant implications for volcanic monitoring, prediction, and hazard assessment. One of the critical eruptive parameters is thevariation of the subsurface structure (e.g., seismic velocities) before, during,
and after the eruption. Previous studies have documented three stages of seismic velocity changes at active volcanoes: pre-eruptive decrease, co-eruptiveincrease, and post-eruptive decrease. Despite these established patterns, somevolcanic eruptions deviate from the observed three stages, raising uncertainties about the repeatability of velocity change patterns at the same volcano
across different eruptions. In this study, using ambient noise cross- and autocorrelations, we estimate the seismic velocity changes over two decades (20032023) at Shishaldin Volcano in the eastern Aleutian volcanic arc, covering four
documented eruptions in 2004, 2014, 2019, and 2023. We utilize continuousrecords from 9 seismic stations to characterize the spatiotemporal distributionof seismic velocity changes based on same-station and cross-station ambient
noise correlations. The seismic velocity changes show a notable pre-eruptiveincrease and co-eruptive decrease associated with the 2014 eruption, which
had the most degassing activities among the four eruptions. The velocitychanges may reflect the pre-eruptive pressurization and co-eruptive depressurization associated with magma and gas recharge and discharge events. We
will compare the velocity change results with changes in surface deformation
patterns from geodetic measurements. The results from this study will help us
understand the control of eruptive structural changes and the predictabilityof eruptive activities.
poster 86
Seismicity, Ambient Noise Tomography, andAnthropogenic Noise via the Auckland-Hauraki Node Arrayin New Zealand
ZHANG, P., Australian National University, Canberra, Australia, ping.
zhang@anu.edu.au; PICKLE, R., Australian National University, Canberra,
Australia, Robert.Pickle@anu.edu.au; MILLER, M. S., Australian National
University, Canberra, Australia, meghan.miller@anu.edu.au
The Northern North Island of New Zealand (including Auckland) is 400+ km
from the Hikurangi Plate margin, making it one of the country’s most stableregions. However, it features several active faults and experiences regular seismicity. It is also home to the Auckland Volcanic Field, a collection of ~53
monogenic intraplate eruptions with the most recent occurring ~600 years
ago (e.g. Hopkins et al., 2021). The region is also home to the Hauraki Rift,an active continental rift widening oblique to the subduction zone at a rate of~1 mm/yr (Pickle, 2019). Both these features were investigated in mid-2023
via a 50+ station broadband node array (AHNA, X5, 2023), using SmartSolo
BD3C-5 instruments recording for ~30 days. Despite historically wet conditions, the nodes were sensitive to periods upwards of ~15 seconds and wereable to resolve crustal structure to depths of 25 km via ambient noise tomography. Over 100 earthquakes were also recorded during this occupation, manyof which were associated with an earthquake swarm within the Hauraki Riftthat began earlier in the year. The network also was able to characterize trends
in anthropogenic noise in and around the greater Auckland region.

Seismology in the Oceans: Pacific Hemisphere and Beyond
Oral Session • Thursday 2 May • 8:00 am PacificConveners: James Gaherty, Northern Arizona University(james.gaherty@nau.edu); Jianhua Gong, Indiana University(gongjian@iu.edu); HyeJeong Kim, University of Utah(hyejeong.kim@utah.edu); YoungHee Kim, Seoul National

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University (younghkim@snu.ac.kr); Joshua Russell, Syracuse
University (jbrussel@syr.edu); Lindsay Worthington,
University of New Mexico (lworthington@unm.edu)
Structure of the Cascadia Margin Offshore Northern
Oregon (44.5-46deg N) From Casie21-OBS Wide-Angle
Seismic Profiles
CANALES, J., Woods Hole Oceanographic Institution, Massachusetts, USA,jpcanales@whoi.edu; JIAN, H., Woods Hole Oceanographic Institution,
Massachusetts, USA, hjian@whoi.edu; MANN, M., Brown University,
Rhode Island, USA, michael.mann@whoi.edu; MILLER, N., U.S. Geological
Survey, Massachusetts, USA, ncmiller@usgs.gov; CARBOTTE, S., Columbia
University, New York, USA, carbotte@ldeo.columbia.edu; HAN, S., Universityof Texas at Austin, Texas, USA, han@ig.utexas.edu; BOSTON, B., Auburn
University, Alabama, USA, boston@auburn.edu
The 2021 Cascadia Seismic Imaging Experiment ocean bottom seismometer
deployment (CASIE21-OBS) is an NSF- and USGS-supported controlledsource marine seismic survey conducted offshore Cascadia in May-July 2021
(Carbotte et al., in review; Canales et al., 2023, doi:10.1785/0220230010). The
main goal of CASIE21-OBS was to collect a modern, open-access wide-angle
seismic reflection/refraction dataset that would enable scientists to develop
P- and S-wave velocity models of the structure of the accretionary prismand down-going plate along most of the Cascadia margin between northern
Vancouver Island and southern Oregon. In this presentation we report 2-D Vp
models obtained from traveltime tomography of sedimentary (incoming andaccreted), crustal and mantle arrivals recorded along three of the CASIE21OBS profiles (PD10, PD12, and PD13). These profiles cross the Cascadia margin offshore northern Oregon between latitudes ~44.5°-46°N in a region that
includes the offshore northern edge of the Franciscan terrane and variable
offshore extension of the Siletz terrane —both of which are thought to playa role in the deformation characteristics of the accretionary prism and thegeometry and deformation of the subducting Juan de Fuca plate (JdF)— as
well as a transition from seaward to landward vergence near ~45°N. Profile
to profile, our models document important along-strike variability in continental platform seismic velocities arising from the presence/absence of theaccreted volcanic terranes. Profile PD13 in the seaward-vergent section of themargin shows more complex and heterogeneous seismic structure in both
crustal and accreted sediments when compared to landward-vergent profiles
PD10 and PD12. We tentatively attribute this difference to prevalence of fluid
drainage fracture networks traversing the down-going JdF crust and slope
sediments in seaward-vergent regions compared to stratigraphic-dominatedfluid migration patterns in landward-vergent regions (e.g., Johnson et al.,2006, doi:10.2973/odp.proc.sr.204.125.2006).
A Newly Identified Mass-Transport Deposit in the Guaymas
Basin, Gulf of California: Implications for Regional
Tectonics and Continental Slope Stability
PIÑA, A., California Institute of Technology, California, USA, lpinapae@
caltech.edu; STOCK, J., California Institute of Technology, California,
USA, jstock@caltech.edu; LIZARRALDE, D., Woods Hole Oceanographic
Institution, Massachusetts, USA, dlizarralde@whoi.edu; BERNDT, C.,
Geomar, Kiel, Germany, cberndt@geomar.de; GONZÁLEZ-FERNÁNDEZ,
A., Center for Scientific Research and Higher Education in Ensenada,
Ensenada, Mexico, mindundi@cicese.mx; MARSAGLIA, K., California
State University, Northridge, California, USA, kathie.marsaglia@csun.
edu; MARTÍN-BARAJAS, A., Center for Scientific Research and Higher
Education in Ensenada, Ensenada, Mexico, amartin@cicese.mx; GALLEGOSCASTILLO, C., Center for Scientific Research and Higher Education in
Ensenada, Ensenada, Mexico, cgallegos@cicese.mx
We report a significant mass transport deposit (MTD) in the southeastern
Guaymas Basin, central Gulf of California, Mexico, which is a young marginal
rift basin characterized by active seafloor spreading. We interpret 16 highresolution seismic reflection profiles across the E-SE basin margin. Withinthese data we identify an ~85-m-thick, wedge-shaped unit with a dominantly
transparent seismic reflection character, though containing some small packages of laterally discontinuous reflectors, and a bumpy upper surface. We
interpret this unit to be a MTD that originated from the Yaqui Delta region of
the Sonoran margin and infer that a combination of high sedimentation rate
and active tectonics contributed to the MTD event. The presence of buried‘flower structures’ within the data indicates that the MTD buried part of thetransform fault separating Guaymas Basin and the continental Sonoran margin. The MTD appears to have occurred near the transform/spreading-centerintersection. That intersection and the axial graben, the surface expression ofwww.srl-online.org•

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extension, have since jumped northwestward, apparently in response to the
MTD emplacement, creating a second, northern seafloor graben, where previously there had only been one in Guaymas Basin. The MTD extends to theNE margin of the northern graben, thins to the SE of the basin, partially fills
the southern graben, and has been faulted and overlain by younger sediments
since emplacement. These inferences are based on a geological and structuralinterpretation of ~708 km of high-resolution multichannel seismic reflection
data. We estimate the area and volume of the observed MTD to be 3346 km2
and 303.3 km3, respectively. Our results contribute to the understanding of
the tectonic evolution of the Guaymas Basin and provide new insights into
the interaction between continental slope failure at active continental margins, spreading-center tectonics, and high flux of sediment transport into thisyoung spreading system in the Central Gulf of California.
Implications of Multi-Layer High-Vp/Vs Seafloor Sediments
Characterized Using Passive Ocean Bottom Seismic Data:
Toward Improving Crustal and Mantle Structure Analysis
KIM, H., University of Utah, Utah, USA, hkim.geo@gmail.com;
KAWAKATSU, H., University of Tokyo, Tokyo, Japan, hitosi@eri.u-tokyo.
ac.jp; AKUHARA, T., University of Tokyo, Tokyo, Japan, akuhara@eri.utokyo.ac.jp; TAKEUCHI, N., University of Tokyo, Tokyo, Japan, takeuchi@
eri.u-tokyo.ac.jp
Body-wave analysis of the sub-oceanic crust and mantle structure is often
challenged by the response of seafloor sediment layers that overwrite propagating body waves. Kim et al. (2023; JGRse) introduced a novel method tocharacterize the in-situ structure of the seafloor sediment using teleseismic
body waves recorded by ocean bottom seismometers (OBSs). The method
resolves the impedance and the Vp/Vs value of each sediment layer, which isimportant in predicting the strength of the shallow layer reverberations. We
show that a single layer model explaining PS-P time and a multi-layer modelfrom the new method show different waveforms in both high- (~1 Hz) andlow-frequency (< 0.3 Hz) ranges.
We apply the methodology to data from various OBS arrays in the
Pacific to estimate in-situ sediment structures. The sediment models show
multiple layers in some regions, including the top water-saturated layer with
low S-wave velocity and high Vp/Vs values. The scaling relationship of Vp/Vs
to Vp shows higher values than the previously discussed ones (e.g., Brocher,
2005; Hamilton, 1979). Furthermore, the sediment layer model constrained
from the body waves exhibit agreement in predicted Rayleigh wave admittance with the sediment model from the Rayleigh wave admittance (Bell et al.,2015). In this presentation, we will discuss how the in-situ high-Vp/Vs multilayer sediment model differs in predicting the reverberation effects on receiver
function analysis for ocean bottom seismometers. Additionally, we will discuss the potential of integrating Rayleigh wave admittance into our body wave
approach to enhance the resolution of crust and mantle structure at depths.
Estimating the Extent of Low-temperature Ductile
Deformation in the Lithosphere Using Seismic Anisotropy
Measurements Around the Alpine Fault
MARK, H. F., Woods Hole Oceanographic Institution, Massachusetts, USA,hmark@whoi.edu
How strong is the lithosphere? This simply posed question is central to
our understanding of active tectonics, but the answer is not at all simple.
Laboratory experiments extrapolated to geologic conditions typically indicatethat at temperatures below ~600°C, the lithosphere is strong and deforms inthe brittle regime. However, recent novel experiments and dislocation mobility models have suggested that the lithosphere can undergo ductile deformation at relatively low temperatures (<600-800°C). Reconciling these experimental results with geodynamic models indicating that the generation andmaintenance of plate boundaries requires a strong lithosphere remains afundamental challenge for plate tectonic theory. Here, I present preliminary
results using seismic anisotropy as a proxy for viscous strain to investigate
how the lithosphere deforms at low temperatures around the Alpine Fault inSouth Island, New Zealand. Previous studies in this region have shown thatviscous strain associated with relative motion across the Australia-Pacific plateboundary is accommodated in a zone up to 200 km wide, but have not beenable to determine whether that deformation is occurring in the lithosphere orin the warmer asthenosphere due to limited spatial and/or depth resolution.
I use existing data from GeoNet stations and a temporary ocean bottom seismometer deployment to calculate receiver functions with harmonic-percussive separation and dereverberation filters to mitigate high noise levels, andapply harmonic decomposition to constrain azimuthal anisotropy in the lithosphere-asthenosphere system across and around the South Island. Receiver
functions provide information on local structure beneath each instrument,

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making it possible to map spatial variations in anisotropy attributed to viscous
deformation around the Alpine Fault.
Crustal and Uppermost Mantle Structure North of the
Gloria Fault Inferred From OBS-Recorded Surface Waves
PINZON, J., University of Guadalajara, Guadalajara, Mexico, juanpvmelak@
gmail.com; CUSTÓDIO, S., Universidade de Lisboa, Setubal, Portugal,susana@fc.ul.pt; SILVEIRA, G., Universidade de Lisboa, Lsibon, Portugal,
mdsilveira@fc.ul.pt; KRÜGER, F., University of Potsdam, Potsdam, Germany,Frank.Krueger@geo.uni-potsdam.de; JOÃO, M., Universidade de Lisboa,
Lisbon, Portugal, jmata@fc.ul.pt; LUIS, M., Universidade de Lisboa, Lisbon,
Portugal, lmmatias@fc.ul.pt
The DOCTAR array encompassed 12 broadband Ocean Bottom Seismometers(OBSs) that operated on the seafloor for ~1 year north of the Gloria fault, at
the African-Eurasia plate boundary in the north Atlantic. The array had shortinter-station distances of 10-20 km and aimed mainly at the application ofarray techniques to teleseismic data and to study the seismicity of the Gloria
fault. However, the data recorded by this array can also be used to study theshallow Earth structure. Here, we analysed the dispersion of surface waves
from both ambient noise (short periods, <14 s) and from teleseismic earthquakes (longer periods, > 14 s). Based on the inferred surface wave dispersion observations, we then computed first a 1D vertically layered model forthe entire region, and subsequently a 3D laterally varying model of S-wave
velocities.
The 1D Vs model shows a top layer of sediments with a low Vs of 1.05
km/s; this low velocity is in agreement with previous observations for theregion and likely results from the presence of water in the sediments. Below
the sediments, Vs increases in the crust from 3.3 to 4.5 kms. We find an
unusual high velocity of 4.9 km/s in a 20 km thick layer at depths between 16
km and 36 km. We suggest that this unusual fast velocity indicates the presence of harzburgite, which is formed as a residue of enhanced mantle melting. We hypothesize that such enhanced melting might have resulted fromthe proximity between the slow-spreading mid-Atlantic ridge and the Azores
mantle plume. A low-velocity zone is then found deeper, at 70 km depth,
which we associate with the LAB. The 3D models shows that the shallow
crustal is mostly horizontally layered below the DOCTAR array. However, italso shows some small-amplitude oscillations of the crustal structure.
This work was funded by the Portuguese Fundação para a Ciência
e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC)–
UIDB/50019/2020(https://doi.org/10.54499/UIDB/50019/2020),
UIDP/50019/2020(https://doi.org/10.54499/UIDP/50019/2020),
LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020).
Overthickened Lithosphere Beneath the Blanco Transform
Faults
BAO, X., Southern University of Science and Technology, Shenzhen,
China, baoxy@sustech.edu.cn; DAI, A., Southern University of Science andTechnology, Shenzhen, China, 12031279@mail.sustech.edu.cn; YANG, Y.,
Southern University of Science and Technology, shenzhen, China, yangyj@
sustech.edu.cn; HU, J., Southern University of Science and Technology,
shenzhen, China, hujs@sustech.edu.cn; ZHANG, W., Southern University of
Science and Technology, shenzhen, China, zhangwei@sustech.edu.cn
The complex interaction between mid-ocean ridges and oceanic transform
faults demands validation of the half-space cooling model for the thermal
evolution of oceanic lithosphere at the ridge-transform systems. Seismic
tomography is key for accurately deciphering the lithosphere structures in thetransform faults. Thanks for the unprecedented opportunity provided by anocean-bottom seismometer experiment at the Blanco Transform Faults (BTF)of the northeastern Pacific, here we present a three-dimensional seismic velocity tomographic model of the lithosphere and top asthenosphere beneath thisfault system. We carried out data pre-processing of the OBS data by removing
the tilt and compliance noises for the vertical-component waveforms, correcting for the clock drift via an improved noise cross-correlation function
method, verifying the polarity of the vertical component and determining
the horizontal orientations via a phase-tracking method. We then extracted
dispersion measurements from teleseismic Rayleigh waves and the empiricalGreen’s functions retrieved from ambient noise, as well as the amplitude ratio
between the radial and vertical components (H/V ratio) of Rayleigh waves.
These measurements were applied to a jointly inversion of phase-velocities
and H/V ratios for the S-wave velocity model via surface-wave tomography
and a Bayesian Monte Carlo method. The most shocking finding in the modelis that high velocities dominate the uppermost mantle of the eastern BTF.
We attribute the velocity variation in the mantle primarily to temperature
variation and establish new isotherms along the BTF. Unlike previous studies,

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our 600°C isotherm well correlates the depth extent of earthquake sourcesbeneath the whole BTF. The lithosphere-asthenosphere boundary beneaththe eastern BTF indicated by the model-predicted 1200°C isotherm is deeper
than that derived from the half-space cooling model. Our results suggest thelithosphere had been thickened for millions of years prior to the formation ofa mature oceanic transform system.
The Anelastic Fingerprint of Small-Scale Convection:
Grain-Size Reduction in Pacific Asthenosphere Revealed by
Regional Shear Attenuation
RUSSELL, J. B., Syracuse University, New York, USA, jbrussel@syr.edu;
DALTON, C., Brown University, Rhode Island, USA, colleen_dalton@brown.
edu; HAVLIN, C., University of Illinois Urbana-Champaign, Illinois, USA,chavlin@illinois.edu; HOLTZMAN, B., Columbia University, New York,USA, benh@ldeo.columbia.edu; EILON, Z., University of California, Santa
Barbara, California, USA, eilon@geol.ucsb.edu; GAHERTY, J., Northern
Arizona University, Arizona, USA, james.gaherty@nau.edu; FORSYTH, D.,
Brown University, Rhode Island, USA, donald_forsyth@brown.edu
The cooling and thickening of oceanic lithosphere as it spreads from the midocean ridge is fundamental to plate tectonics, and the base of this thermalboundary layer represents one of the largest temperature gradients in theplanet. Yet, the thermo-mechanical processes that occur below the plate as
it interacts with the warmer low-viscosity asthenosphere are still debated,
especially at intermediate and old ages. If dynamic processes are present, theyshould impact the asthenosphere’s physical state (temperature, grain size, viscosity, melt fraction) and be seismically observable using regional datasets.
Here, we use Rayleigh waves recorded on broadband ocean-bottom seismometers to constrain profiles of shear attenuation and velocity through theasthenosphere at three experiments in the central and southwest Pacific representing intermediate age (~40–90 Ma) oceanic plate. At all three locations,
we observe a high-attenuation peak (low Qμ) centered at 100–150 km depth
corresponding with the low-velocity zone. Two experiments located in thesouth Pacific display remarkably high attenuation (Qμ ~ 25–35)—among thehighest observed to date beneath ordinary oceanic plate—and both locations
exhibit lineations in the gravity field. The magnitude of the attenuation peakvaries between sites but does not simply covary with seafloor age, suggestingheterogeneity in dynamic processes within the low-viscosity zone beneath the
Pacific plate that persist to at least ~90 Myr.
By jointly inverting our observations within a Bayesian frameworkthat considers melt stability and uses laboratory-derived relations for mantle
anelasticity from the Very Broadband Rheology calculator (VBRc), we showthat the high-attenuation, low-velocity zone can be explained by grain-size
reduction (≤ 5 mm) consistent with active deformation within a low-viscosity
channel. This channel is also damp (~150–500 ppm H2O) and contains lowdegree partial melt (< 0.3%). We consider a ~50 km thin layer of remarkably
high attenuation in the asthenosphere to be an anelastic hallmark of sub-lithospheric small-scale convection.
An Ocean-Bottom View of Mantle Convection Beneath the
Pacific BasinGAHERTY, J., Northern Arizona University, Arizona, USA, james.gaherty@
nau.edu; EILON, Z., University of California, Santa Barbara, California, USA,eilon@geol.ucsb.edu; RUSSELL, J., Syracuse University, New York, USA,jbrussel@syr.edu; PHILLIPS, J., Northern Arizona University, Arizona, USA,jp2888@nau.edu; HARIHARAN, A., University of California, Santa Barbara,
California, USA, ahariharan@ucsb.edu; DALTON, C., Brown University,
Rhode Island, USA, colleen_dalton@brown.edu; FORSYTH, D., Brown
University, Rhode Island, USA, donald_forsyth@brown.edu
The Pacific basin provides an outstanding natural laboratory to study a rangeof tectonic and upper-mantle dynamic processes, including seafloor spreading, midplate volcanism, and multiscale thermal convection. Historically,
geophysical insights into these processes were limited to low-resolution,
long-wavelength imaging due to the restriction of instrumentation to continents and islands. Recent advances in ocean-bottom seismometry have now
enabled high-resolution investigation of these processes using localized (few
100s-km aperture) broadband arrays. We present emerging results from the
ORCA (OBS Research into Convecting Asthenosphere) project, comprising
two 12-month seismic arrays in the central and southwest Pacific. ORCA wasdesigned to image upper-mantle wavespeeds in two regions where satellitederived gravity variations display linear structures suggestive of small-scale
upper-mantle convection, one at intermediate plate age (30-40 Ma), and one
at old plate age (90 Ma+). At the younger site, we find linear blobs of fast andslow material (~250–300 km wavelength), parallel to the gravity features, that
we infer to represent cold sinking and warmer rising material beneath the

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low-Q (~25–35) asthenosphere, suggesting grain-size reduction combinedwith a small amount of partial melt (<0.3%) play an important role in controlling rheology. Seismic anisotropy varies strongly within and between regions,with distinctive variations with depth that suggest regional differences inthe scale and strength of deformation controlled by seafloor spreading,lithosphere-asthenosphere coupling, and pressure- and temperature-driven
asthenospheric flow. By combining these results with previous analyses fromacross the Pacific, we are gaining an improved understanding of the processes
controlling the formation and evolution of the ocean plates and the highly
dynamic convective system beneath them.
Deep Learning for Deep Earthquakes in Oceans: Insights
From Obs Observations of the Tonga Subduction Zone
WEI, S. S., Michigan State University, Michigan, USA, swei@msu.edu; XI,
Z., Michigan State University, Michigan, USA, xiziyi@msu.edu; ZHU, W.,
University of California, Berkeley, California, USA, zhuwq@berkeley.edu;
BEROZA, G. C., Stanford University, California, USA, beroza@stanford.edu;
JIE, Y., Michigan State University, Michigan, USA, jieyaqi@msu.edu; SALOOR,
N., Michigan State University, Michigan, USA, nooshinsaloor2014@u.
northwestern.edu
Applications of machine learning in seismology have greatly improved ourcapability of detecting earthquakes in large seismic data archives. Most ofthese efforts have been focused on continental shallow earthquakes, but here
we introduce an integrated deep-learning-based workflow to detect deep
earthquakes recorded by a temporary array of ocean-bottom seismographs(OBSs) and land-based stations in the Tonga subduction zone. We develop a
new phase picker, PhaseNet-TF, to detect and pick P-,S-, and PS-wave arrivals
in the time-frequency domain. The frequency-domain information is critical for analyzing OBS data, particularly the horizontal components, because
they are contaminated by signals of ocean-bottom currents and other noise
sources in certain frequency bands. PhaseNet-TF shows a much better performance in picking S waves compared to its predecessor PhaseNet. The
predicted phases are associated using an improved Gaussian Mixture Model
Associator GaMMA-1D and then relocated with a double-difference package
teletomoDD. We further enhance the model performance with a semi-supervised learning approach by iteratively refining labeled data and retraining
PhaseNet-TF. This approach effectively suppresses false picks and significantly
improves the detection of small earthquakes. The new catalog of Tonga deep
earthquakes contains more than 10 times more events compared to the reference catalog that was analyzed manually. This deep-learning-enhanced catalog reveals Tonga seismicity in unprecedented detail, and better defines thelateral extent of the double-seismic zone at intermediate depths and the location of 4 large deep-focus earthquakes relative to background seismicity. The
newly picked arrivals offer new potentials for deciphering deep earthquake
mechanisms, refining tomographic models, and understanding subduction
processes.
Earthquakes and Slab Morphology in Southern Mariana
and Yap Subduction Zones
YANG, H., Chinese University of Hong Kong, Hong Kong, China, hyang@cuhk.edu.hk; ZHU, G., Chinese Academy of Sciences, Qingdao, China,
zhugaohua@qdio.ac.cn
The Southern Mariana and Yap subduction zones have attracted enormous
attention of scientific investigators and explorers during recent decades.
Since late 2016, near-field active and passive source seismic experiments has
been carried out by deploying Ocean Bottom Seismographs (OBS) in various
terms. Both active and passive source tomographic images clearly indicate awell hydrous incoming Pacific plate, which is consistent with the observed
pervasive normal faults in the out-rise region. Numerous earthquakes havebeen detected from the OBS recordings, and their locations delineate the subducting plate as well as deep out-rise faults. The slab geometry in southern
Mariana shows significant along-trench variations, with earthquake depths
ranging from 120 to 240 kms. In comparison, the slab beneath the Yap trench
exhibits a steep dip angle, with earthquakes concentrated in depths less than
80 km. The contrasting slab morphology in southern Mariana and Yap is likely
resulted from subduction of the Caroline ridge, a buoyant oceanic plateau thatwas formed during Oligocene-Miocene. After collision with the trench, thesubducting slab beneath the Yap trench gradually steepened. However, the dip
angle of the slab beneath southern Mariana is relatively gentle, possibly due tothe oblique subduction direction.

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Seismology in the Oceans: Pacific Hemisphere and Beyond[Poster Session]
Poster Session • Thursday 2 May
Conveners: James Gaherty, Northern Arizona University(james.gaherty@nau.edu); Jianhua Gong, Indiana University(gongjian@iu.edu); HyeJeong Kim, University of Utah(hyejeong.kim@utah.edu); YoungHee Kim, Seoul National
University (younghkim@snu.ac.kr); Joshua Russell, Syracuse
University (jbrussel@syr.edu); Lindsay Worthington,
University of New Mexico (lworthington@unm.edu)
poster 23
Upper Mantle Velocity Structure Beneath the Galapagos
Archipelagos From the Analysis of Pn Wave Recorded by
Broadband Seismic Instruments and Mermaids
BEN MANSOUR, W., Washington University in St. Louis, Missouri, USA,walid.benmansour@seismo.wustl.edu; NOLET, G., Université de la Côted’Azur, Sophia Antipolis, France, nolet@princeton.edu
Over the past two decades, global scale seismic velocity models have
improved thanks to increased seismic station density and advancements inhigh-performance computing infrastructure and algorithms. However, theoceanic domain, accounting for 3/4 of the earth’s surface, shows lower resolution in comparison to the continental domain. The deployment of Mobile
Earthquake Recorder in Marine Areas by Independent Divers (MERMAIDs)
around the Galapagos in 2014 and in the South Pacific in 2018-2019 demonstrated the potential of this new generation of data acquisition in the Ocean
and their ability to generate reliable seismic data. To map the extension of
the Galapagos mantle plume beneath the oceanic crust, we merged data fromeight MERMAIDs and broadband seismic stations. This improved the resolution of the seismic velocity model and expanded data coverage throughout
the ocean domain. We use travel times of refracted waves Moho from regional
shallow events (<40 km) with epicentral distance between 2o and 16oandMw>5.5 to image the 3-D uppermost mantle velocity structure. This contribution will highlight the new Pn velocity anomalies maps and compare themwith recent models like the Regional Seismic Travel Time model. We will discuss the potential and limitations of our approach, specifically in regards todata selection and modeling. Additionally, we will discuss geodynamic implication associated with the Galapagos mantle plume and its interaction withthe spreading ridge.
poster 24
Seismic Structure of the Young Oceanic Cocos Plate From
the Ridge to the Trench Axis Offshore the Mexico
Subduction ZoneBÉCEL, A., Columbia University, New York, USA, annebcl@ldeo.columbia.
edu; HAGEMEIER, D., Columbia University, New York, USA, ahagemeier@ldeo.columbia.edu; ACQUISTO, T. M., Columbia University, New York, USA,acquisto@ldeo.columbia.edu; CRUZ-ATIENZA, V. M., Universidad Nacional
Autónoma de México, Mexico City, Mexico, cruz.atienza@gmail.com;
BOSTON, B., Auburn University, Alabama, USA, brianb@ldeo.columbia.edu;
SHILLINGTON, D. J., Northern Arizona University, Arizona, USA, Donna.
Shillington@nau.edu; SHUCK, B., Columbia University, New York, USA,bshuck@ldeo.columbia.edu; HAN, S., University of Texas at Austin, Texas,
USA, han@ig.utexas.edu; REAL-PÉREZ, J., Universidad Nacional Autónoma
de México, Mexico City, Mexico, real@igeofisica.unam.mx; WARD, G.
A., Northern Arizona University, , USA, gaw97@nau.edu; ITO, Y., Kyoto
University, Kyoto, Japan, ito.yoshihiro.4w@kyoto-u.ac.jp
Characterizing the seismic structure of oceanic plates is crucial for assessing
hazards in subduction zones, including earthquakes and volcanic eruptions.
Moreover, it also contributes to our understanding of biodiversity and theevaluation of resources in proximity to the ridge axis or seamounts. Several
key locations globally present a unique opportunity to investigate the evolution of oceanic plates from accretion to subduction at the trench axis along
a single seismic profile with consistent acquisition parameters and processing schemes. Here, we focus on two active-source seismic profiles acquiredin 2022 aboard the R/V Langseth as part of the ¡ME GUSTA! Seismic
Experiment. These profiles explore the region from the East Pacific Rise to thetrench axis offshore of the Guerrero seismic gap—an area that remains largely
unexplored. These profiles, acquired with slightly different orientations to follow a flow line, sample a 0-12.5 Ma oceanic crust accreted at fast to ultra-fast

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spreading rates. The processing of the multibeam and the multichannel seismic data allows for the characterization of a very thin sediment cover (< 50m),
small changes in basement roughness, and intraplate features such as a small
rift. Velocity models from traveltime tomography of the 15-km long streamer
data reveal reduced upper crustal velocities near the ridge axis between 0 and
2.5 Ma, attributed to vigorous hydrothermal circulation. Farther away fromthe ridge axis and flanks, upper crustal velocities increase due to the closure ofpores and precipitation of hydrous minerals and are very similar to the global
average. A modest reduction in velocity in the bending area suggests slight
reactivation of favorably oriented abyssal hill faults, consistent with slightly
higher fault throws measured approaching the trench axis. We propose thatthe reactivation of abyssal hill faults is only modest due to the inherent weakness of the young Cocos crust. Comparison with other young plates such as
the Juan de Fuca plate will allow us to further refine our understanding ofaccretionary and evolutionary processes.
poster 25
Adjoint Waveform Tomography of the Cascadia Subduction
Zone Using CASIE21 Controlled-Source Data
BRUNSVIK, B. R., University of California, Santa Barbara, California,
USA, brennanbrunsvik@ucsb.edu; MILLER, N., U.S. Geological Survey,
Massachusetts, USA, ncmiller@usgs.gov; EILON, Z., University of California,
Santa Barbara, California, USA, eilon@geol.ucsb.edu; JIAN, H., Woods
Hole Oceanographic Institution, Massachusetts, USA, hjian@whoi.edu;
CANALES, J., Woods Hole Oceanographic Institution, Massachusetts, USA,jcanales@whoi.edu
We apply adjoint waveform tomography to CASIE21-OBS data to produce a
2D velocity model crossing the seismogenic zone of the Cascadia Subduction
Zone offshore Washington. Cascadia is capable of producing large (M~9)
earthquakes and tsunamis. Slab and velocity models exist for Cascadia, but,prior to the 2021 controlled-source Cascadia Seismic Imaging Experiment(CASIE21), higher-resolution models were restricted to a few profiles or small
3D volumes. Regionally comprehensive 3D models also exist, but are generally
low resolution and/or inaccurate, particularly under the submarine forearc
where variations in shallow fault structure and material properties can havesignificant effects on earthquake rupture. CASIE21 airgun shots along profiles
crossing the submarine forearc offshore Oregon, Washington, and Vancouver
Island were recorded by a towed streamer, ocean-bottom seismometers(OBS), and onshore seismic arrays. We tested the feasibility of applying the
SPECFEM code’s adjoint waveform tomography capability to image Vp andVs using these controlled-source data. Here, we show results from a 2D test
case using OBS data. Sensitivity kernels calculated from first-break traveltime delays show strongest sensitivity at basement depths, and up to ~15 km
depth in the seismogenic zone. After a preliminary inversion, travel times offirst-break phases were ~16% more consistent with OBS data compared to avelocity model based on the streamer data alone. Future targets include an
inversion of amplitudes from several seismic phases and their reverberations,comparison with results from conventional wide-angle traveltime tomography, and 3-D application using more lines from CASIE21.
poster 26
Seismicity of the Atlantis Massif Oceanic Core Complex:
2005-2006 OBS Data Revisit
DEWAELSCHE, P., Indiana University, Indiana, USA, pedewa@iu.edu;
GONG, J., Indiana University, Indiana, USA, gongjian@iu.edu
An oceanic core complex (OCC) forms through the exhumation of lowercrustal and upper-mantle rocks on the seafloor via slip on detachment faults
rooted below mid-ocean ridges. Due to the challenges of seafloor observation, few studies have investigated dynamic processes of OCC at depth, suchas hydrothermal circulation, faulting, and magmatic activities. The Atlantis
Massif OCC, situated at approximately 30°N, 42°W along the Mid-Atlantic
Ridge, was monitored by a network of five ocean bottom seismometers (OBS)
from 6/5/2005 to 3/25/2006. In this study, we leverage recent advancements inmachine-learning methods for earthquake detection and location to reprocess
the OBS data, aiming to gain insights into magmatic, faulting, and fluid flow
processes beneath the OCC.
We implement a machine-learning-enabled workflow using four opensource software to detect and locate microseismicity at Atlantis Massif OCC.
PhaseNet, a deep-neural-network-based seismic arrival time picking method,
returned over 100,000 picks for both P and S phases for four stations. Nearly
160,000 total phase picks were then used by GaMMA, a machine-learn
phase associator, to associate phases with seismic events. Only events withmore than seven total P and S picks are saved, which results in 31,118 associated events. COMPLOC was used for earthquake location, yielding ~25,700

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locatable events. The vast majority of events located in this stage appear to
be under the Mid-Atlantic Ridge valley between 5 and 13 km depth, with afair number of events located under the oceanic core complex itself. Relative
relocation of earthquake hypocenters based on waveform cross-correlation
data was performed using GrowClust to refine initial location estimates anddetermine clusters of events. Two main sequences of events along the ridge
can be observed and account for about 35.5% of the total events. Our preliminary location result is consistent with previous study of Collins et al, 2012, but
has more than two times of total events. We will first focus on the two main
sequences along the ridge to understand faulting and magmatic activities at
the OCC-ridge system.
poster 27
P-Wave Anisotropic Velocity Model of the Galápagos
Plume
HUFSTETLER, R. S., University of Oregon, Oregon, USA, beckh@
uoregon.edu; HOOFT, E. E. E., University of Oregon, Oregon, USA, emilie@
uoregon.edu; TOOMEY, D. R., University of Oregon, Oregon, USA, drt@
uoregon.edu; VANDERBEEK, B. P., University of Padua, Padua, Italy,
brandon.p.vanderbeek@gmail.com
The Galápagos plume and nearby spreading center create a novel setting
to study how hot mantle plumes interact physically and chemically with
mid-ocean ridges. This area is well studied geochemically, geophysically,
and geodynamically (e.g., Schilling, 1982; Hooft et al., 2003; Ito & Bianco,2014). Geodynamic models reproduce many aspects of the region, but there
remain discrepancies between observations and geodynamic predictions. The
IGUANA teleseismic experiment (1999-2003) used 12 seismometers on theislands to image the plume and found anomalously low Vs material that near
200 km depth, well below the thermal lithosphere, tilts northward toward the
spreading center (Villagómez et al., 2014). This is not predicted by geodynamic models and may be driven by pressure gradients or small-scale convection in the asthenosphere. However, features consistent with S-wave imaging
results are notable absent from unpublished isotropic P-wave tomographymodels. One possible explanation is the trade-off between thermally-induced
velocity variations that can reduce seismic velocities and mantle upwellingthat can increase seismic velocities for vertically traveling P waves. Here, we
analyze the IGUANA data to determine if including seismic anisotropy inthe tomographic inversion produces P-velocity models consistent with priorS-wave imaging. We jointly invert cross-correlated P and S delays for hexagonal anisotropic elastic parameters with an arbitrarily oriented symmetry axis.
By leveraging both datasets and accounting for the anisotropic properties ofthe mantle, we aim to better constrain the geometry of the Galápagos plumeand associated mantle flow field.
poster 28
Shear Wave Velocity Structure of the Upper Mantle
Beneath the Oldest Pacific Seafloor Revealed by FiniteFrequency Traveltime Tomography
KIM, Y., Seoul National University, Seoul, South Korea, yh1230@gmail.com;
KANG, H., University of Florida, Florida, USA, khsmile7@gmail.com; HUNG,
S., National Taiwan University, Taipei, Taiwan, shung@g.ntu.edu.tw; LIN, P.,
National Taiwan University, Taipei, Taiwan, pylin.patty@gmail.com; ISSE, T.,
University of Tokyo, Tokyo, Japan, tisse@eri.u-tokyo.ac.jp; KAWAKATSU,
H., University of Tokyo, Tokyo, Japan, hitosi@eri.u-tokyo.ac.jp; LEE, S., Seoul
National University, Seoul, South Korea, smlee@snu.ac.kr; UTADA, H.,
University of Tokyo, Tokyo, Japan, utada@eri.u-tokyo.ac.jp; TAKEUCHI, N.,
University of Tokyo, Tokyo, Japan, takeuchi@eri.u-tokyo.ac.jp; SHIOBARA,
H., University of Tokyo, Tokyo, Japan, shio@eri.u-tokyo.ac.jp; SUGIOKA, H.,
Kobe University, Kobe, Japan, hikari@pearl.kobe-u.ac.jp
This study presents the first three-dimensional S-wave velocity structure ofupper mantle beneath the oldest Pacific seafloor using finite-frequency traveltime tomography. We use teleseismic records from the Oldest-1 experiment,
which deployed eleven broadband ocean-bottom seismometers on the oldest
Pacific baisin in the west Pacific. We measure relative traveltime residuals of
the traverse S waveforms filtered at three frequency bands between 8–32 s,
using a multichannel cross correlation method. The obtained S-wave traveltime residuals show peak-to-peak variations of ±3 s across the array. S tomography results reveal S-wave velocity anomalies (δlnVS) ranging within ±6%.
We find a fast-Vs anomaly at depths of 100–190 km beneath eastern part of thearray. Additionally, slow-Vs anomalies are found to the southwest and northeast, at approximately 100–250 km and 100–300 km in depth, respectively.
The overall distribution of slow- and fast-velocity anomalies of S tomographymodel is found similar with P tomography model. Our preliminary Vp/Vs
model shows elevated Vp/Vs values (δln(Vp/Vs) > 2%) for the slow-Vs anoma-

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Seismological Research Letterslies, whereas relatively moderate Vp/Vs values (δln(Vp/Vs) = 1–2%) are found
for the fast-Vs anomaly. The differences in Vp/Vs may imply compositionalvariation of upper mantle across the Oldest-1 array site.
poster 29
A New 3D Reference Velocity Model for Offshore Cascadia
Based on CASIE21 Data
MILLER, N., U.S. Geological Survey, Massachusetts, USA, ncmiller@usgs.gov;
CANALES, J., Woods Hole Oceanographic Institution, Massachusetts, USA,jcanales@whoi.edu; CARBOTTE, S., Columbia University, Massachusetts,
USA, carbotte@ldeo.columbia.edu; HAN, S., University of Texas at Austin,
Texas, USA, han@ig.utexas.edu; BOSTON, B., Auburn University, Alabama,
USA, boston@auburn.edu
We developed a new 3D reference velocity model for the offshore portion of
the Cascadia Subduction Zone based on controlled-source seismic data fromthe 2021 Cascadia Seismic Imaging Experiment (CASIE21). This initial modelhas two main goals: (1) provide a next-generation 3D velocity model of thesubmarine forearc and shallow subducting plate and (2) prototype a 3D modelbuilding approach that can integrate constraints from a variety of mostly-2D,
controlled-source seismic datasets. The input constraints to this initial model
are CASIE21 2D Vp models built for pre-stack depth migration of ultra-longoffset multichannel seismic data. The 3D model is constructed by defining
velocity and surface geometry control points and then interpolating between
them. Surfaces are interpolated first and then used to guide 3D interpolationof velocities. Selection of the control points is inherently subjective, but themodel building process itself is automated, enabling objective and quantitative evaluation of control point quality and influence on the 3D model via
validation tests (e.g. travel-time misfits). Interpolation can use conventional(e.g., kriging) and/or machine learning (e.g., random forest and neural network) methods. Output models consist of surface and material meshes withmaterial parameter values and geostatistical uncertainties assigned. Meshes
can use different geometries (e.g., tetrahedral, hexahedral) and have uniform
or variable resolutions, depending on the interpolation method. Currently,
efforts are focused on Vp modeling, but a future model could expand to othermaterial parameters (e.g., Vs, density, resistivity). Output meshes can be produced in common formats (e.g., VTK) with the resolution and mesh geometry needed for specific applications (e.g., travel-time tomography, waveformmodeling, ground-motion simulation).
poster 30
Seismicity Observation in the Oldest Pacific Plate Using
Pacific Array (Oldest-1) Data
PARK, J., Seoul National University, Seoul, South Korea, zip1900@snu.ac.kr;
KIM, Y., Seoul National University, Seoul, South Korea, younghkim@snu.
ac.kr; ISSE, T., University of Tokyo, Tokyo, Japan, tisse@eri.u-tokyo.ac.jp;
KIM, K., Pusan National University, Busan, South Korea, kwanghee@pusan.
ac.kr; SHIOBARA, H., University of Tokyo, Tokyo, Japan, shio@eri.u-tokyo.
ac.jp; KAWAKATSU, H., University of Tokyo, Tokyo, Japan, hitosi@eri.utokyo.ac.jp; LEE, S., Seoul National University, Seoul, South Korea, smlee@
snu.ac.kr; UTADA, H., University of Tokyo, Tokyo, Japan, utada@eri.utokyo.ac.jp; TAKEUCHI, N., University of Tokyo, Tokyo, Japan, takeuchi@
eri.u-tokyo.ac.jp; SUGIOKA, H., Kobe University, Kobe, Japan, hikari@pearl.
kobe-u.ac.jp
The oldest part of the Pacific plate (the “Pacific triangle”), located approximately 900 km east of the Mariana Trench, has been considered the moststable oceanic intraplate region due to its age (~170–180 Ma). Seismic records
recorded by the Oldest-1 Array, consisting of 11 broadband ocean bottom
seismometers (BBOBS) and 12 pressure gauges, provide a great opportunity
to investigate the stress state in the old oceanic lithosphere from the local toregional seismicity in the oldest Pacific. Although the array geometry is originally designed to probe upper-mantle seismic properties, high-quality BBOBS
data (Kawano et al., 2023) made the detection and location of microseismicity
possible. In this study, we present a one-year catalog of intraplate seismicity
that includes 17 earthquakes with mb(Sn) magnitudes ranging from 0.9 to
3.7 in and around the array. This earthquake records can serve as an important dataset to clarify the relationship between seismicity, tectonic stresses andgeological setting in the oldest Pacific.
Based on locations, a total of 17 events are grouped into two with one
group of ten events and the other of seven. The first group of ten events forms
two clusters with five events per group. One cluster shows a high degree ofwaveform similarity (correlation coefficient exceeding 0.92), and their epicenters are located in close proximity to 200-300 m high knolls with the location uncertainty of 100 m. The other cluster is located 16 km apart from theOgasawara fracture zone, but aligns closely with its strike. Seven earthquakes

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for the second group are sparsely populated within the array; in particular,
three events exhibit clear T-phase and are located near seamounts whichmight contribute to the T-phase excitation. Although the seismicity is low
overall, their spatial scattering and clustering might suggest meaningful correlations between the seismicity and preexisting zones of weakness or geological features on the seafloor.
poster 31
The Upflow Experiment: Data Report for 49 Ocean Bottom
Seismometer Deployment in the Azores-Madeira-Canaries
Region, Atlantic Ocean
TSEKHMISTRENKO, M., University College London, London, United
Kingdom, m.tsekhmistrenko@ucl.ac.uk; FERREIRA, A., University College
London, London, United Kingdom, a.ferreira@ucl.ac.uk; MIRANDA,
M., IPMA, Lisbon, Portugal, miguel.miranda@ipma.pt; TILMANN, F.,
GFZ Potsdam, Berlin, Germany, tilmann@gfz-potsdam.de; HARRIS, K.,
University College London, London, United Kingdom, katrina.harris@ucl.
ac.ik; HICKS, S., University College London, London, United Kingdom,
stephen.hicks@ucl.ac.uk; HOSSEINI, K., University College London, London,
United Kingdom, Kasra.hosseini@ucl.ac.uk; MARIGNIER, A., University
College London, London, United Kingdom, augustin.marignier.14@ucl.
ac.uk; SAOULIS, A., University College London, London, United Kingdom,alex.saoulis@ucl.ac.uk; BARANBOOEI, S., Dublin Institute for Advanced
Studies, Dublin, Ireland, samane@cp.dias.ie; CABIECES DIAZ, R., Spanish
Navy Observatory, San Fernando, Spain, rcabdia@gmail.com; CARAPUÇO,M., IPMA, Lisbon, Portugal, mafalda.carapuco@ipma.pt; FERREIRA, H.,
IPMA, Lisbon, Portugal, henrique.ferreira@ipma.pt; CORELA, C., Universityof Lisbon, Lisbon, Portugal, ccorela@fc.ul.pt; DUARTE, J., University of
Lisbon, Lisbon, Portugal, jlduarte@fc.ul.pt; NERES, M., University of Lisbon,
Lisbon, Portugal, marta.neres@ipma.pt; RAMOS, L., University of Lisbon,
Lisbon, Portugal, luis.ramos@primemarineship.pt; SCHLAPHORST, D.,
University of Lisbon, Lisbon, Portugal, dschlaphorst@fc.ul.pt; GEISSLER,W. H., AWI, Bremerhaven, Germany, wolfram.geissler@awi.de; SCHMIDTAURSCH, M., AWI, Bremerhaven, Germany, Mechita.Schmidt-Aursch@awi.
de; LANGE, D., GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel,
Germany, dlange@geomar.de; KRÜGER, F., University of Potsdam, Potsdam,
Germany, Frank.Krueger@geo.uni-potsdam.de; REIN, T., University of
Potsdam, Potsdam, Germany, theresa.rein@uni-potsdam.de; KE, K., GFZ
Potsdam, Potsdam, Germany, kuanyu@gfz-potsdam.de; MAKUS, P., GFZ
Potsdam, Potsdam, Germany, makus@gfz-potsdam.de; LOUREIRO, A.,Agência Regional para o Desenvolvimento da Investigação, Funchal, Portugal,
afonsoloureiro@afonsoloureiro.net
UPFLOW has been one of the largest ocean bottom seismometer (OBS)
experiments targeting mantle upwelling so far. Its goal is to constrain upward
mantle flow, which is crucial to understanding global mantle flow. UPFLOW
deployed 50 and recovered 49 OBS in a ~1,000 x 2,000 km2 area in the
Azores-Madeira-Canaries region with an average station spacing of 150-200km,starting in July 2021 for ~13 months. The experiment included institutions from five different countries: Portugal (IPMA, IDL, Univ. of Lisbon,
ISEL), Ireland (DIAS), UK (UCL), Spain (ROA) and Germany (University of
Potsdam, GFZ, GEOMAR, AWI). Most of the instruments had three-component broadband seismic sensors (mostly​T~120 s) and hydrophones, but threedifferent designs of OBS frames were used. Our analysis shows 94% data completeness and overall high-quality data, notably a substantial noise decrease invertical component long-period data (T>30s) compared to previous experiments. Horizontal component data show reasonable quality, enabling theestimation of seismometer orientations using body and surface waves from149 earthquakes. Earth’s free oscillations with frequencies as low as ~1.8 mHz
following two Mw > 8 earthquakes are observed on vertical components, after
applying tilt and compliance corrections they are visible at nearly all sites. We
show illustrative recordings of teleseismic and local events, and non-seismic
signals (whales, instrument resonances)., demonstrating the potential of the
UPFLOW dataset to address many outstanding questions not only in solid
Earth sciences but also in oceanography and marine biology.
poster 32
Using Deep Learning Algorithms to Study Seismicity
Changes Preceding and Following the 2021 Central
Hikurangi Slow Slip Event, New Zealand
KWONG, S., Victoria University of Wellington, Wellington, New Zealand,
stephen.kwong@vuw.ac.nz; SAVAGE, M. K., Victoria University of
Wellington, Wellington, New Zealand, martha.savage@vuw.ac.nz; WARRENSMITH, E., GNS Science, Lower Hutt, New Zealand, e.warren-smith@gns.
cri.nz; JACOBS, K., GNS Science, Lower Hutt, New Zealand, k.jacobs@gns.
cri.nz; WALLACE, L., GEOMAR Helmholtz Centre for Ocean Research Kiel,

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Kiel, Germany, lwallace@utexas.edu; MOCHIZUKI, K., University of Tokyo,
Tokyo, Japan, kimi@eri.u-tokyo.ac.jp
Slow Slip Events (SSEs) are aseismic events that release strain built up along
faults. Resolving the mechanisms that drive these events and understanding
the physical changes they cause to a fault zone, are important in improving
our forecasts of when a fault will fail. Subduction zones around the Pacificregularly host SSEs of varying magnitudes and recurrence intervals, but offshore seismic and geodetic instrumentation is required to appropriately characterise their occurrence. The PULSE project (Physical processes UnderLying
Slow Earthquakes) aims to better understand the processes driving slow slip
by building a 2-year microseismicity catalogue offshore New Zealand on the
Hikurangi subduction zone. This will allow us to observe and characterise thephysical changes to a fault zone prior and following slow earthquakes. The
PULSE network consists of 55 onshore (48 seismic, and 7 geodetic) instruments, and 26 offshore (10 seismic and 16 geodetic) instruments and is
focused on the Pōrangahau region in the central Hikurangi, where SSEs occur
approximately every 5 years. This dense PULSE Network will allow us to generate a high resolution, high precision microearthquake catalogue spanning
the slow-slip and inter slow-slip period.
To build the catalogue, we employ the deep learning automatic earthquake picker EQTransformer (Mousavi et al., 2020) to pick the data. The picks
are then associated into distinct events by GaMMA (Zhu et al., 2022). These
events are then first absolutely located with NonLinLoc (Lomax et al., 2010)
and relatively relocated with GrowClust3D (Trugman et al., 2022). We target the Pōrangahau SSE that occurred between May-June 2021. The national
GeoNet network finds ~500 earthquakes in our deployment region over the
SSE period. We can resolve over 4 times as many seismic events and are able
to resolve seismicity offshore near to and underneath the slip patch. This has
allowed us to better understand how seismicity evolves preceding and following SSE activity, with increases in seismicity occurring concurrent with SSE
onset and movement of seismic activity across the SSE period.

Six Decades of Tsunami Science: From the Source of the1964 Tsunami to Modern Community Preparedness
Oral Session • Thursday 2 May • 2:00 pm PacificConveners: Dmitry Nicolsky, University of Alaska Fairbanks(djnicolsky@alaska.edu); Anthony Picasso, Alaska Divisionof Homeland Security & Emergency Management (anthony.
picasso@alaska.gov); Barrett Salisbury, Alaska Divisionof Geological & Geophysical Surveys (barrett.salisbury@
alaska.gov); Elena Suleimani, University of Alaska Fairbanks(ensuleimani@alaska.edu)
The 2021 Antarctic (South Sandwich) Tsunami as Recordedin the North Pacific
RABINOVICH, A. B., Institute of Ocean Sciences, Sidney, BC, Canada,a.b.rabinovich@gmail.com; TSUKANOVA, E., Shirshov Institute of
Oceanology RAS, Moscow, Russia, tsukanovaelizaveta@gmail.com;
THOMSON, R. E., Institute of Ocean Sciences, Sidney, Canada, richard.
thomson@telus.net
On 12 August 2021, a major earthquake occurred in the Antarctic sector of
the Atlantic Ocean near the South Sandwich Islands. This was a complex eventthat was initially reported as a magnitude 7.5 at 18:33 UTC at a deep depthof 47 km followed, three minutes later, by a Mw 8.1-8.3 main shock due torupturing of the shallow subduction zone. The main shock generated a global
tsunami that spread throughout the World Ocean, where it was recorded atsuch remote regions as Kamchatka, the Aleutian Islands, Alaska and British
Columbia roughly 17,000–18,000 km from the source area. To examine thisevent, we used data from a number of coastal tide gauges located within theseregions, along with data from 14 DART stations in the North Pacific and 9
ONC NEPTUNE cable stations offshore of Vancouver Island. The first tsunami waves arrived at the southern coast of British Columbia (BC) about 23 hafter the earthquake and at the northern coast of BC and southeastern Alaska
about 1.0-1.5 hours later. Our numerical model simulations of the event basedon the known seismic parameters and Okada’s equations agree remarkably
well with the open-ocean DART and ONC records, including the recorded
tsunami wave amplitudes and periods. This case clearly demonstrates thateven highly distant tsunamigenic events with source areas located in remote

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oceanic regions can reach the coasts of Alaska and British Columbia and bereliably reproduced by the modern numerical models.
Re-evaluating Global Threat of Tsunamis Generated by
Air-pressure Waves from Volcano Explosions
TITOV, V., National Oceanic and Atmospheric Administration, Washington,
USA, vasily.titov@noaa.gov
The eruption of Hunga Tonga-Hunga Ha’apai (HTHH) on January 15, 2022,
unexpectedly triggered a global tsunami. While the waves had a significant
impact along Pacific coasts, they were also detected at gauges worldwide,
extending beyond the Pacific region. A similar phenomenon occurred globally on August 27, 1883, when the Krakatau explosion generated one of history’s most devastating tsunamis, which was observed and recorded acrossthe world.
Both these global tsunamis were partly caused by air pressure waves
resulting from the volcanic eruptions. The HTHH tsunami provided valuable
observational data, enabling a thorough quantitative assessment using modeling techniques. Tsunami models, constrained by atmospheric pressure wave
(Lamb waves) measurements demonstrated very good comparisons with sealevel recordings globally. We apply the modeling expertise obtained from theanalysis of the HTHH volcanic tsunami generated by the air-pressure waves tore-examine the global tsunami generation by the Krakatau volcano. Analyzingthese events lays the groundwork for evaluating the potential threat posedby this new type of tsunami, which volcanoes and other large-scale explosive
events could produce.
Multi-Scale Geophysical Characterization and Tsunami
Modeling of Active Listric Normal Faults Offshore Grays
Harbor, Wa
WATT, J., U.S. Geological Survey, California, USA, jwatt@usgs.gov; GEIST,
E., U.S. Geological Survey, California, USA, egeist@usgs.gov; LA SELLE, S.,
U.S. Geological Survey, California, USA, slaselle@usgs.gov; HILL, J., U.S.
Geological Survey, California, USA, jhill@usgs.gov
Understanding the role of upper plate crustal faults in subduction zone strain
accumulation and release is fundamental to improving earthquake and tsunami hazard characterization and risk mitigation. Here we take a closer lookat a series of active listric normal faults located ~70 km offshore NW of Grays
Harbor, Washington, to determine how these structures accommodate strain
and how they may contribute to earthquake and tsunami hazards along thecoast. We provide new constraints on the shallow structure and activity ofthese faults and use these observations to develop a suite of tsunami models
that capture a range of possible rupture scenarios including those with andwithout megathrust rupture.
Analysis of multibeam bathymetry and high-resolution sparker andchirp seismic data collected between 2017 and 2023 document two areas ofactive faulting near the heads of Quinault and Grays canyon with individual
fault trace lengths between 5 and 25 km. The faults are characterized by distinct seafloor scarps (heights ranging from 23-57 meters) cutting across theouter shelf and upper slope in water depths ranging from 160-600 meters.
Interpretations of crustal-scale seismic data suggest these structures go listric at shallow depth (~3-4 km). We explore the tsunamigenic potential ofthese faults using estimates of fault rupture area derived from a combinationof near-surface and crustal-scale seismic data. Preliminary GeoCLAW models of tsunami propagation and inundation resulting from listric normal fault
sources predict maximum wave amplitudes along the coastline of less than
one meter, with arrival times varying from 35 to 55 minutes. However, themodeled tsunami impacts from the listric fault source are overshadowed bythose from megathrust sources. While these listric faults alone may not posea significant tsunami hazard to coastal Washington, their presence may reflectrepeated large-scale co-seismic seaward motion of the outer wedge, enablinglarge amounts of shallow slip and tsunamigenesis similar to that observed
during the 2011 Tohoku earthquake in Japan.
Real-Time Prediction of Tsunami Amplitude Using GaussianProcess Regression
NICHOLS, T., National Tsunami Warning Center, Alaska, USA, terry.
nichols@noaa.gov
Tsunami Warning Centers depend on coastal tide gauges to measure tsunami
wave heights for rapid decision making and alerting. To isolate the tsunami
signal from the tidal background, a physics-based harmonic analysis model
is often used to predict the tides. This prediction is then subtracted fromobserved data, ideally leaving a tsunami-only waveform plus noise. However,

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this model is less accurate in waterways where complex bathymetry and freshwater input introduce complications that are not accounted for in the model.
In such cases, determining tsunami wave height is challenging because thetide is poorly modeled, making it difficult for Tsunami Warning Centers to
produce accurate measurements.
Data-derived methods such as Gaussian processes may be used toaddress this need. Gaussian processes are a nonparametric, Bayesian approachthat avoids issues with traditional physics-based analyses. This method uses
a radial basis kernel function to capture data structure, and its propertiesare determined directly from tide data through a set of hyperparameters.
The study demonstrates improved algorithm performance using tide data
recorded in Valdez, AK, during the February 27, 2010 Chilean tsunami; theMarch 11, 2011 Tohoku tsunami; and the January 15, 2022 Tonga tsunami.
A Behavioral Theory Framework for Tsunami Preparedness
GRANT LUDWIG, L., University of California, Irvine, California, USA,lgrant@uci.edu
As stated in the session description “educating the public, counteracting disaster amnesia and preserving the memories of tsunamis for future generations
are all important tasks that the tsunami community will be working on for
decades.” Perhaps the biggest challenge is motivating coastal communities andindividual residents to ACT on the education, knowledge and memories toprepare for future tsunamis. Social scientists developed the Protective Action
Decision Model to describe how individuals are motivated to take action toprotect themselves from natural and other hazards. Public health researchers have developed and tested health behavior theories for application incampaigns to improve public health. These theories include the health belief
model, ecological model and self-efficacy model. According to the healthbelief model, there are several factors that motivate a change in behavior
when a person is faced with a threat. These factors include the extent to which
a person feels vulnerable, the perceived danger or severity of the threat, thereal or perceived barriers to taking action, and the perceived effectiveness oftaking action. The self-efficacy model includes a sense of control, which overlaps with factors in the health belief model. The ecological model of behavior focuses on the social environment, including individual “intrapersonal”,
interpersonal, institutional and community factors, as well as public policy.
A health promotion program would incorporate elements of these 3 models
to motivate behavioral change. A typical health promotion campaign would
have the following elements that are directly relevant to tsunami risk reduction: 1) Belief in personal threat, e.g. “I am susceptible to tsunami”; 2) Belief
in response efficacy, e.g. “There is something I can do that will lessen tsunami
threat”; 3) Belief in personal efficacy, e.g. “ I am capable of taking action”; and
4) Belief that new behaviors are consistent with group norms, e.g. “My peers
support this action”.

Six Decades of Tsunami Science: From the Source ofthe 1964 Tsunami to Modern Community Preparedness[Poster Session]
Poster Session • Thursday 2 May
Conveners: Dmitry Nicolsky, University of Alaska Fairbanks(djnicolsky@alaska.edu); Anthony Picasso, Alaska Divisionof Homeland Security & Emergency Management (anthony.
picasso@alaska.gov); Barrett Salisbury, Alaska Divisionof Geological & Geophysical Surveys (barrett.salisbury@
alaska.gov); Elena Suleimani, University of Alaska Fairbanks(ensuleimani@alaska.edu)
poster 168
Depth Variation in Megathrust Rupture Leads to Mature
Tsunami Gap in Metropolitan Chile
CARVAJAL, M., Pontificia Universidad Católica de Valparaíso, Concon,
Chile, matias.carvajal@pucv.cl; CISTERNAS, M., Pontificia Universidad
Católica de Valparaíso, Valparaiso, Chile, marco.cisternas@pucv.cl; WANG,
K., Geological Survey of Canada, Sidney, Canada, kelin.wang@NRCanRNCan.gc.ca; MORENO, M., Pontificia Universidad Católica de Chile,
Santiago, Chile, marcosmoreswitt@gmail.com; WESSON, R. L., Geophysicist,
Colorado, USA, rwesson@gmail.com; CONTRERAS-REYES, E., Universidad

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de Chile, Santiago, Chile, edcontrr@gmail.com; MELNICK, D., Universidad
Austral de Chile, Valdivia, Chile, daniel.melnick@uach.cl“Seismic gaps” refer to segments along active geologic faults that have not ruptured in a time period comparable with the recurrence intervals of past earthquakes, and are therefore expected to rupture at any time. This concept usuallydescribes spatial variations in earthquake recurrence in the strike dimension.
However, modern seismological observations show that rupture can occur at
a variety of depths, so that the lack of a seismic gap in the strike direction
may not indicate the lack of a seismic gap in the dip direction. This recognition has important hazard implications. For example, within a given strike
segment of a subduction megathrust, an earthquake may rupture only one
depth section, with another section still accumulating energy for a future large
earthquake. Here, we present unambiguous historical evidence for the presence of such an unruptured depth section in metropolitan Chile. In this area,
four earthquakes greater than magnitude 8 (1730, 1822, 1906 and 1985) were
documented in the written history, but only the first (1730) of this sequence
was accompanied by a large tsunami. By combining newly found first-handaccounts of coastal uplift and tsunamis with coupled deformation-tsunami
models, we show that the three post-1730 earthquakes failed to produce large
tsunamis because their rupture zones were confined to relatively large depths
beneath land. In contrast, the large tsunami in 1730 was the consequence oflarge slip of the shallow section of the megathrust beneath the sea. Because theshallow section has not ruptured in a time period comparable with the recurrence intervals of prehistoric tsunamis (2-6 centuries), it creates a “tsunami
gap” today along Chile’s most populated coast that could be filled by a large
tsunami at any time. Similar tsunami gaps are likely present in other subduction zones and should be addressed in hazard analysis and risk mitigation.
poster 169
Constraining Offshore Coupling in the 1946 Tsunami
Earthquake Rupture Area
CHAVARRIA ESQUIVEL, N., Georgia Institute of Technology, Georgia,
USA, nchavarria6@gatech.edu; NEWMAN, A., Georgia Institute ofTechnology, Georgia, USA, anewman@gatech.edu
One of the most important challenges currently in geodesy is accurately modeling the coupling behavior offshore in subduction zone environments. This islargely because most observations of coupling-induced deformation are madeon land, where geodetic data are largely unable to resolve the behavior morethan about 40 km offshore. This includes the near-trench region, making seafloor geodetic methods vital for capturing such behavior that leads to large
earthquakes and tsunamis, like the 1946 Aleutian “tsunami earthquake” thatgenerated an unexpectedly large tsunami presumably because of enhancednear-trench slip. In this region, both community- and PI-driven projects
are underway to capture such deformation in Alaska using GNSS-Acoustic
methods. Here, we evaluate the proposed distributions of the seafloor equipment, planned for deployment in Summer 2024 surrounding the 1946 tsunami earthquake inferred rupture area. Some of these sites will be locatedas close to the trench as possible (rated to 6000 m water depth), providing
new information on current elastic deformation that cannot be obtained anyother way. From our results, we determine the resolvability of the subduction
deformation of this specific region, by analyzing the improvement provided
by the spatial distribution among the stations in the current proposed geometric distribution. With this analysis, we expect to answer the extent to whichquestions regarding the current coupling state of the 1946 Aleutian tsunami
earthquake area can be answered given the planned instrument distribution.
poster 170
Efficient Forward Modelling of Tsunamis Using theSpectral-Element Method
GHARTI, H., Queen’s University, Kingston, Canada, hng1@queensu.ca;
FITZGERALD, J., Queen’s University, Kingston, Canada, 17jcf1@queensu.ca
We developed an open-source tool for the forward modelling of tsunamis.
We utilize the spectral element method, aiming to enhance the accuracy andefficiency of tsunami simulations. The spectral element method is a higherorder finite element method that is extensively used in forward and adjoint
modelling of seismic wave propagation due to its inherent advantages, suchas higher accuracy, stability, and efficiency. Specifically, we solve the shallow
water wave equation on curvilinear coordinates to accommodate Earth’s curvature. We employ ETOPO 2022 as a reference for the bathymetry. We perform comprehensive simulations of the Indian Ocean tsunami induced by the2004 Sumatra-Andaman Earthquake and the Pacific Ocean tsunami inducedby the 2010 Chilean earthquake.

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poster 171
Adding Tsunami Observations and Modeling to the USGS
Finite Fault Modeling Procedure
GOLDBERG, D. E., U.S. Geological Survey, Colorado, USA, degoldberg@
usgs.gov; KOCH, P., University of Chile, Santiago, Chile, pkoch@csn.uchile.cl;
MELGAR, D., University of Oregon, Oregon, USA, dmelgarm@uoregon.edu;
HUNSINGER, H., U.S. Geological Survey, Colorado, USA, hhunsinger@usgs.
gov; HAYNIE, K., U.S. Geological Survey, Colorado, USA, khaynie@usgs.gov
The U.S. Geological Survey National Earthquake Information Center (NEIC)
is expanding its earthquake finite fault modeling capabilities to include tsunami modeling and the inversion of tsunami observations. In preliminary
testing, we find that the quality of the earthquake source characterization is
improved by consideration of offshore data from Deep ocean Assessment andReporting of Tsunamis (DART) buoys. We demonstrate new tools within the
NEIC’s finite fault modeling software (Wavelet and simulated Annealing SliP;
WASP) developed to interact with the tsunami modeling software, GeoClaw.
These updates support forward modeling of the expected tsunami from an
offshore finite fault model, allowing early estimates of the ocean response tofault motions. However, earthquake source characterization from terrestrial
observations alone is not always compatible with the resulting tsunami (e.g.,2020 M7.6 Sand Point, Alaska), which motivates operationalizing joint inversion of earthquake and tsunami observations. Tsunami amplitudes provide
critical constraints on the updip extent of slip, the kinematics of rupture, andthe amplitude of vertical deformation. Updates to WASP seamlessly call on
GeoClaw to facilitate the calculation of tsunami Green’s functions. WASP theninverts DART observations of the tsunami alongside terrestrial seismic andgeodetic observations of the causative earthquake. GeoClaw is then called
once again to enable tsunami propagation modeling. In this presentation, weshowcase the implementation of the updated WASP software package andshare results from joint inversions of tsunamigenic earthquakes, demonstrating the gains afforded by including DART observations.
poster 172
The What, When and Whys of Alert Progression During
Tsunamigenic Events: A Simple Generative Approach to
Forecasting Decision Points and Developing Heuristics
HEATH, B., National Tsunami Warning Center, Alaska, USA, benjamin.
heath@noaa.gov; OHLENDORF, S., National Tsunami Warning Center,
Alaska, USA, summer.ohlendorf@noaa.gov; KIM, Y., National Tsunami
Warning Center, Alaska, USA, yooyin.kim@noaa.gov; GRIDLEY, J., National
Tsunami Warning Center, Alaska, USA, james.gridley@noaa.gov
Due to the possibility of imminent tsunami inundation after large earthquakes, tsunami warning centers make fast, real-time decisions about which
regions to alert. For initial alerts, the centers typically assume a worst-casescenario as there often aren’t sufficient preliminary constraints to resolve
event tsunamigenesis. This strategy mitigates the risk posed by the tsunami
and simplifies the decision making process. However, it also communicatesserious impacts that may not come to pass, and can thereby be a source offrustration for alerted populations. These populations, some of whom may
have evacuated, may have to wait hours before the worst-case assumptions canbe refuted and the event resolved. Here, in order to alleviate the uncertainty
inherent in event progression and to better explain/simplify event decisionmaking, we propose a method focused on identifying when, where, and why
plausible hazard likelihoods are expected to update during an individual
event. We develop a simple generative model that maps event observations
to a probabilistic description of future impacts at the coast, and show how themodel can be used to both highlight upcoming decision points and develop
straightforward event-specific heuristics (rules of thumb) that simplify thedecision making process. For example, the model can recognize that a specific open ocean water-level observation exceeding some threshold will be thefirst determining factor in whether or not a warning level observation (>1m waves) will be realized at a coastal location. The model is trained using
an array of precomputed Alaska Tsunami Forecast Model (ATFM) outputs,
including forecasted tsunami amplitudes for large subduction zone earthquakes in the Pacific. This model does not improve final forecast accuracy, butrather provides a real-time, decision-first framework to highlight what amplitude thresholds need to be measured when in order to reduce initial forecast
uncertainty and crystallize anticipated impacts. The goal of this model is toprovide a basic, explainable, robust, data-oriented framework that informs thedecision making process.

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poster 173
Estimating Tsunami Vulnerability along Western Coast of
India
JHA, K., National Centre for Earth Science Studies, Thiruvananthapuram,India, krishna.jha2211@gmail.com
India has a long coastline of roughly 1500 km along its western margins.
Tsunami hazards along western coast of India have been under-studied, comparative to the eastern coast. The major hazard of tsunami along western coast
comes from Makran subduction zone. However, other features in Arabiansea and Western and Northern Indian ocean may pose also pose a threat, in
terms of tsunami. Seafloor topography reveals various tectonic features thatcan possibly trigger tsunamis. These comprise of Indian ocean mid-oceanic
ridge including carlsberg ridge, owen fracture zone, among others. These features primarily have earthquakes of strike-slip in origin. It has been shownthat stirke-slip earthquakes have potential of generating tsunamis, contrary
to popular belief. Slope failure, favourable bathymetry, large dip angle, aresome of the feature which faciliates tsunamigenic nature of strike-slip earthquakes. Another common reason of tsunami is underwater landlslides. One
such region is Indus canyon, in the north western indian ocean. In this study,
possible tsunami harzard estimation for the western coast of India have been
done, by taking hypothethical earthquake scenarios along several features in
Arabian sea and North and North west Indian ocean. Inundation and Run-Upfor each case has been discussed, higlighting vulnerability of the region.
poster 174
Precise Point Positioning of Ships to Detect Tsunamis
MANASTER, A. E., University of Colorado Boulder, Colorado, USA,adam.manaster@colorado.edu; SHEEHAN, A. F., University of Colorado
Boulder, Colorado, USA, anne.sheehan@colorado.edu; GOLDBERG, D.
E., U.S. Geological Survey, Colorado, USA, degoldberg@usgs.gov; ROTH,
E. H., University of Alaska Fairbanks, Alaska, USA, ehroth@alaska.edu;
BARNHART, K. R., U.S. Geological Survey, Colorado, USA, krbarnhart@
usgs.gov
Precise Point Positioning (PPP) of ships could be a useful addition to existing tsunami detection frameworks. Leveraging Global Navigation Satellite
System (GNSS) data to precisely track the movements of marine vessels canunveil anomalies in sea surface height indicative of tsunamis. Results are presented for the R/V Sikuliaq, a research vessel commissioned by the Universityof Alaska Fairbanks that has operated an external Trimble MPS865 Modular
GNSS Heading Receiver since 2019. Raw RINEX GNSS data files with a sampling rate of 1 Hz from the ship were processed with PRIDE PPP-AR, an
open-source software for PPP applications developed by the GNSS ResearchCenter of Wuhan University. Utilizing this software, in tandem with further
post-processing, we demonstrate the efficacy of harnessing ship positioning
data for tsunami detection in two case studies: (1) the M8.2 earthquake that
occurred offshore Chignik, Alaska on July 29, 2021, when the ship was intransit in the Pacific Ocean (kinematic), and (2) the Lowell Point landslide
near Seward, Alaska on May 8 (UTC), 2022, when the ship was in port in
Resurrection Bay (stationary). For both instances, orthometric height (height
above mean sea level) was calculated from the ship elevation data, tides weremodeled through OSU Tidal Prediction Software (OTPS) and removed fromthe resultant time series data, and signal processing techniques were employed
for further analysis. The tsunami generated by the earthquake was not detectable, given its small size (synthetic models give 2 cm tsunami height at ship
location); however, the diurnal and semidiurnal tides were well-observed
using GNSS receiver data from the moving ship. Conversely, the tsunami was
detectable for the landslide event the clear signal suggests dominant wave
periods of less than one minute and an amplitude of approximately 5 cm. The
standard deviation of the post-processed vertical position time series differedin both cases: 1.3 cm for the stationary case and 4 cm for kinematic case;noise in these readings can be attributed to wind and other atmospheric disturbances, as well as movement of the ship.
poster 175
Testing Crustal Fault Tsunami Sources in the Salish Sea:
Comparing Modeled Inundation With the Geologic Record
at Discovery Bay, WA
WEI, Y., University of Washington, Washington, USA, yong.wei@noaa.gov;
GARRISON-LANEY, C., University of Washington, Washington, USA, cegl@
uw.edu; MOORE, C., National Oceanic and Atmospheric Administration,

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Washington, USA, christopher.moore@noaa.gov; PELLS, C., University ofWashington, Washington, USA, clint.pells@noaa.gov
Crustal faults across the Salish Sea are capable of producing M7+ earthquakes and hazardous tsunamis in Puget Sound and the Strait of Georgia. A
better understanding of the history of Salish Sea tsunamis and their sources
will improve tsunami hazard assessments in Washington State and British
Columbia. The Seattle and Tacoma faults are well-studied tsunami sources,
but other Salish Sea crustal faults are just starting to be evaluated for their tsunami hazard. One way to advance our understanding of crustal fault tsunami
hazards is to compare modeled tsunami inundation from various sources
with geologic evidence for past tsunamis. The tidal marsh at Discovery Bay,
Washington, is an excellent geologic recorder of past tsunamis because of its
wave-amplifying funnel-shaped morphology, an abundant sediment supply,
and a terminal tidal marsh that has preserved tsunami deposits in the marsh
stratigraphy. With at least 10 tsunami deposits of thicknesses between 2-10 cm
thick, and at least 6 thinner layers under 1 cm thick spanning the last ~3,000
years, the deposits at Discovery Bay likely represent not only tsunamis generated by the Cascadia subduction zone, but also those generated by crustal
faults, landslides, or tsunamis from other Pacific subduction zones. To better
understand potential crustal fault sources of Discovery Bay tsunami deposits, we test high-resolution tsunami inundation models of the Skipjack Island,
Darrington-Devils Mountain, South Whidbey Island, Seattle, and Tacoma
fault zones. We also test tsunami inundation models of the 1700 C.E. Cascadia
subduction zone and 1964 Great Alaskan earthquake tsunamis, both of whichhave probable deposits at Discovery Bay. Some of the crustal fault sources wetested appear to be more likely to cause flooding at Discovery Bay than others and may be the sources for deposits whose ages do not align with known
Cascadia earthquakes.
poster 176
KOERI Activities in Tsunami Early Warning and Risk
Mitigation System in the Eastern Mediterranean and Its
Connected Seas
OZENER, H., Bogazici University, Istanbul, Turkey, ozener@boun.edu.tr;
CAMBAZ, M., Bogazici University, Istanbul, Turkey, didem.samut@boun.
edu.tr; TURHAN, F., Bogazici University, Istanbul, Turkey, fatih.turhan@
boun.edu.tr; GÜNEŞ, Y., Bogazici University, Istanbul, Turkey, gunesy@boun.
edu.tr; DENIZ HISARLI, P., Bogazici University, Istanbul, Turkey, pdeniz@boun.edu.tr; ÇOK, Ö., Bogazici University, Istanbul, Turkey, ozkan.cok@boun.edu.tr; ERGUN, T., Bogazici University, Istanbul, Turkey, afacan@boun.
edu.tr; ÖĞÜTCÜ, Z., Bogazici University, Istanbul, Turkey, ogutcu@boun.
edu.tr; POLAT, R., Bogazici University, Istanbul, Turkey, remzi.polat@boun.
edu.tr; SUVARIKLI, M., Bogazici University, Istanbul, Turkey, suvarikl@
boun.edu.tr; TEOMAN, U., Bogazici University, Istanbul, Turkey, ugurt@
boun.edu.tr; KEKOVALI, K., Bogazici University, Istanbul, Turkey, kekovali@
boun.edu.tr; ALTUNCU POYRAZ, S., Bogazici University, Istanbul, Turkey,
selda.altuncu@boun.edu.tr; KALAFAT, D., Bogazici University, Istanbul,
Turkey, kalafato@boun.edu.tr
Kandilli Observatory and Earthquake Research Institute (KOERI) tsunami warning system provides services in the Eastern Mediterranean,
Aegean, Marmara and Black Seas under the UNESCO Intergovernmental
Oceanographic Commission (IOC) - Intergovernmental Coordination Group(ICG) for the Tsunami Early Warning and Mitigation System in the NorthEastern Atlantic, the Mediterranean and Connected Seas (NEAMTWS).
KOERI’s Regional Earthquake and Tsunami Monitoring Center (RETMC)
was established on the foundations of the KOERI National Earthquake
Monitoring Center (NEMC) by adding observation, analysis and operational
capability related to tsunami early warnings after an extensive preparatory
period between 2009 and 2011. The center initiated its test-mode 7/24 operational status as a national tsunami warning center in 2011, and after a oneyear period it became operational as a candidate tsunami warning center for
NEAMTWS on 1 July 2012. KOERI continues monitoring and disseminating
messages in the NEAM region together with other TSPs; CENALT (Centred’Alerte aux Tsunamis-France), NOA (National Observatory of AthensGreece), INGV (Instituto Nazionale di Geofisica e Vulcanologia-Italy), and
IPMA (Instituto Português do Mar e da Atmosfera-Portugal), completing fullcoverage of the tsunami-prone regions monitored by NEAMTWS. KOERI
issued 45 tsunami warning message disseminated since 1 July 2012, including the remarkable events, such as the 20 July 2017 Bodrum–Kos Mw 6.6, 30
October 2020 Samos–Izmir Mw 6.9, 06 February 2023 Gaziantep Mw7.7 and
20 February 2023 Hatay Mw6.3 earthquakes. KOERI monitors 28 tide gauge
stations operated by General Directorate of Mapping and KOERI in Türkiye
and nowadays enlarges its sea-level network with inserting an additional 20
stations along the coast of the Marmara Sea. This presentation will focus onwww.srl-online.org•

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the KOERI’s Tsunami Early Warning and Risk Mitigation Activities in NEAM
region.
poster 177
Estimation of the Tsunami Hazard for the Bering and
Chukchi Seas Based on Numerical Modeling of TransOceanic and Local Tsunamis
MEDVEDEVA, A. E., Shirshov Institute of Oceanology RAS, Moscow,
Russia, Alisa.bannikova@gmail.com; FINE, I. E., Institute of Ocean Sciences,
Sidney, Canada, IFine54@gmail.com; MEDVEDEV, I., Shirshov Instituteof Oceanology RAS, Moscow, Russia, medvedev@ocean.ru; KULIKOV,E., Shirshov Institute of Oceanology RAS, Moscow, Russia, kulikove@ocean.ru; RABINOVICH, A. B., Institute of Ocean Sciences, Sidney, BC,
Canada, a.b.rabinovich@gmail.com; YAKOVENKO, O., Shirshov Institute of
Oceanology RAS, Moscow, Russia, tsucen@ocean.ru
The tsunami hazard for the Bering and Chukchi seas has been estimated basedon numerical modeling of eight major far-field earthquakes in the Pacific
Ocean (1946 Aleutian, 1952 Kamchatka, 1960 Chile, 1964 Alaska, 1965 Rat
Islands, 1957 Andreanof Islands, 2011 Tohoku, and 2012 Haida Gwaii), andone near-field earthquake in the Bering Sea (2017 Commander Islands). Tide
gauge records of the 2011 Tohoku tsunami from St. Paul Island, Port Moller
and Nome in the Bering Sea were used to validate the model. According toour numerical simulations, the tsunami generated by the Mw 9.5 1960 Chilean
earthquake would have produced the strongest response in the Bering Sea
wave amplitudes up to 2.7 m, while for the 1952 Kamchatka tsunami (thesecond strongest response) the maximum wave amplitudes would have been
up to 1.5 m. The 1964 Great Alaska earthquake (Mw 9.2) did not produce a
substantial tsunami in the Bering Sea because the Alaska Peninsula sheltered
the region from incoming tsunami waves. We have also estimated the penetration effectiveness for the distant tsunamis into the Bering Sea and theninto the Chukchi Sea/Arctic Ocean. According to our computations, a typicalattenuation coefficient for the straits through the Aleutian Islands is 0.75, on
average, while the corresponding coefficient for the Bering Strait is 0.29. Basedon these estimates, we conclude that the likelihood of tsunami penetrating
into the Arctic Ocean from remote Pacific sources is low. Even for a powerful event, such as the 1960 Chilean tsunami, the tsunami wave amplitudes
in the Chukchi Sea leading into the Arctic Ocean would not exceed a few
centimeters. However, for the Bering Sea, tsunami waves from major distantearthquakes can be significant.
poster 178
Real Time Tsunami Run-Up Estimation From Real Time
Finite Fault Models
RIQUELME, S., Sebastian Riquelme, Santiago, Chile, sebastian.riquelme@gmail.com; FUENTES, M., University of Chile, Santiago, Chile, maufuent@uchile.cl
Often, Tsunami Early Warning relies on a precomputed set of scenarios forplaces near the tsunami generation zone. These scenarios are non realistic andare computed from a uniform constant slip over the rupture surface, becauseof the short reaction time for the local authorities to manage the threat. Here,
we present a new development to be implemented on Early Warning Systems,
that allows real time tsunami modeling using the W-Phase solution of theseismic source and the finite fault model inversion to evaluate tsunami threat
levels. A fast linear approximation of shallow water equations turns into a
numerical solver that can be implemented on a parallel thread. As a case study,
the proposed method is applied in Chile. The results show that it is possible toobtain consistent and realistic threat levels and arrival times for the tsunami
in progress within times useful for Tsunami Early Warning, since the earthquake origin time.The proposal considers realistic heterogeneous and kinematic fault models of seismic sources obtained rapidly using continuous GPS,strong motion and broadband records, expanding the evaluation capabilities
of Early Warning Systems and diminishing the bias imposed by precomputed
scenarios, by using the source solution for the particular earthquake that generated the tsunami in progress.
poster 179
Measuring and Forecasting the Background Open Ocean
Tsunami Spectrum
SANTELLANES, S. R., University of Oregon, Oregon, USA, sean.sants@
gmail.com; MELGAR, D., University of Oregon, Oregon, USA, dmelgarm@uoregon.edu
he background open-ocean tsunami spectrum (BOOTS) is an under-studied
topic in the tsunami sciences. It describes the spectrum of oscillations that

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occur out in the open-ocean within the tsunami band (1 min-2 hrs). It plays
a key role in understanding the local site response at coastal sea level stations,which can be extended to show the tsunami site response at locations where
no sea level data is available. The objective of our research is to measure the
BOOTS and its noise and forecast these variables using a graphical neuralnetwork.
For the analysis, we use data from the recovered bottom pressure recorders of DART stations, which have a sampling rate of 15 seconds. With thissampling rate, it is possible to measure the BOOTS over the full tsunami band.
The quality-controlled de-tided pressures are used in the calculation of power
and amplitude spectra. These spectra are computed every two weeks for each
DART station for as long as fidelity data are available. Tsunami events anywhere in the Pacific and Atlantic basins over the time frame of 2000-2022 arefiltered out to ensure that the spectra are mainly that of the background oscillations. Spectra generally have a simple log-linear decay, so we utilize a leastsquares inversion to compute the slope and intercept of the spectra— e.g., theenergy and noise of the background state. From these spectra, we construct atime-series of the two parameters that shows the temporal variation for each
DART station. We then use these data as inputs to forecast these parameters
via a graphical neural network.
poster 180
The Role of Climate-Change Sea Level Rise Exacerbating
California’s Tsunami Hazards
SEPULVEDA, I., San Diego State University, California, USA, isepulveda@
sdsu.edu; MOSQUEDA, A., San Diego State University, San Diego, Chile,amosqueda6783@sdsu.edu
A new era of engineering is arising in which coastal risk assessments are carried out in a more holistic manner. One key improvement is the incorporationof compounding processes. New tsunami hazard evaluations, for example,
shall integrate the influence of tides and climate-driven sea level changes. In
terms of magnitude, they could be comparable to tsunamis of interest at certain regions, such as those threatening the Southern California coast. New
non-stationary probabilistic tsunami hazard assessment (nPTHA) methods
are developed to incorporate the mean sea level changes due to a warming climate and the uncertainty of the tidal phase at the moment of tsunami occurrence. Results show that sea level rise shifts hazard curves towards greater
values, while tides cause a diffusion making the tails of hazard distributions
heavier.
As an illustration, the developed nPTHA is employed for assessing tsunami hazards in San Francisco, Long Beach and San Diego due to earthquakes
in the Alaska-Aleutian and Cascadia subduction zones. The nPTHA is carried out by generating synthetic random earthquakes, by simulating tsunami
scenarios in the framework of a stochastic reduced order model (SROM) andby employing a surrogate model that simulates the effects of tides and sea
level rise. When analyzing the Maximum Considered Tsunami (MCT) results,
defined as the sea level exceeded with a probability of 2% in 50 years in building codes, we observe significant exacerbation of the hazard at the assessedregions. MCT maps in Long Beach Port, for example, exhibit an increasebeyond 60% when considering the NOAA’s moderate-high sea level rise projection. These results suggest that critical coastal infrastructure, projected toserve several decades in the California coast, shall incorporate a nPTHA in
the design process.
poster 181
In Search of the Missing Tsunami: Is There a Tsunami Threat
to Anchorage?
SULEIMANI, E., University of Alaska Fairbanks, Alaska, USA, ensuleimani@
alaska.edu; SALISBURY, J. B., Alaska Division of Geological & GeophysicalSurveys, Alaska, USA, barrett.salisbury@alaska.gov; NICOLSKY, D.,
University of Alaska Fairbanks, Alaska, USA, djnicolsky@alaska.edu;
PICASSO, A., Alaska Division of Homeland Security and Emergency
Management, Alaska, USA, anthony.picasso@alaska.gov
The historic tsunami events have led to a common misconception that theUpper Cook Inlet (UCI) is completely immune to tsunami impacts. A coordinated effort to evaluate tsunami hazards in the area, as a part of the Alaska
tsunami inundation mapping program, has been recently completed.
Tsunamis were not reported in Anchorage during the Great Alaska
earthquake. One possible explanation was that the 1964 rupture did not produce a substantial amount of slip in the presently creeping Kenai segment of
the plate interface, which resulted in a relatively small amount of energy entering Cook Inlet. Another potential reason for the unreported tsunami was thetiming of the arrival of the wave: after midnight at low tide.

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Tsunami inundation models used in hazard assessment studies usuallyemploy static-tide runs with the Mean High Water vertical datum, because
dynamically coupled tsunami-tide models are hard to implement. However,UCI is a shallow water body with extreme tidal ranges of up to 10 meters,
which makes tsunami-tide interactions crucial for accurate hazard assessment.
We perform numerical modeling of the 1964 tsunami in UCI by dynamicallycoupling the tsunami model with tides, and suggest that a 3-meter high tsunami did occur, but was unnoticed in Anchorage due to its arrival on low tidethat was 5 meters below Mean Sea Level. Our further modeling shows thatthe inundation zone, corresponding to the tsunami calculated on a high statictide, is larger than that computed with dynamically coupled tide, therefore
our tsunami inundation maps do not underestimate potential hazard due tostatic-tide modeling.
Our understanding of the tsunami threat in UCI has been significantly
revised since 1964. We considered tsunami sources similar to that of the 2011
Tohoku tsunami, and included tsunami-tide interactions in the tsunami hazard analysis due to extreme tidal ranges in UCI. Our future task is to educate
coastal residents and various stakeholders about this rare but real tsunami
threat. The public outreach campaign is now underway in Anchorage andother communities in UCI.

Special Applications in Seismology
Oral Session • Wednesday 1 May • 4:30 pm PacificConveners: Heather McFarlin, Alaska Earthquake Center(hlmcfarlin@alaska.edu) and Nate Murphy, Alaska
Earthquake Center (nwmurphy@alaska.edu)
Is Dynamically Triggered Seismicity Comparable to
Background Seismicity?
DESALVIO, N. D., University of California, San Diego, California, USA,ndesalvio@ucsd.edu; FAN, W., University of California, San Diego, California,
USA, wenyuanfan@ucsd.edu; BARBOUR, A. J., U.S. Geological Survey,
Washington, USA, abarbour@usgs.gov
Earthquakes can be dynamically triggered by the passing waves of events fromdistant faults. Identifying dynamic triggering mechanisms offers tangible hopein revealing earthquake nucleation processes. Delayed dynamic triggering isfrequently observed, and such cases are likely driven by nonlinear processes
that differ from typical stress triggering. This brings into question whether or
not they reflect the same nucleation processes. Here we investigate the physical mechanisms of triggered seismicity in southern California using a variety of independent datasets related to faulting environments and earthquake
source characteristics. Within the spatial and temporal resolution afforded bythese data, we find weak correlations between triggering occurrence and surface fault trace complexity, focal mechanism diversity, and fault type. Such low
correlations suggest similar faulting environments for the triggered and background seismicity. We find that the triggered seismicity may have lower stressdrop and b-value estimates compared to background seismicity. The lower
stress drops and b-values imply that the driving mechanisms might be different between triggered and background earthquakes. Additionally, about 85%
percent of triggered sequences do not begin with the largest event. About 50%of these triggered sequences have migration velocities above 0.25 km/hr andOmori p-values below 0.75. These characteristics suggest that the triggered
seismicity is akin to earthquake swarms, which are often driven by aseismic
slip or fluid migration. These processes are likely reflected in the lower stressdrops and b-values of the triggered seismicity. Our findings suggest that thetriggered seismicity are likely by-products of additional, localized processes
activated by the passing waves, such as aseismic slip or fluid movement.
Ligabue—Large Induced Ground Amplitudes by Urban
Excitations, as Recorded by a 7c-Station
BRAUN, T., Istituto Nazionale di Geofisica e Vulcanologia, Arezzo, Italy,
thomas.braun@ingv.it; FAMIANI, D., Istituto Nazionale di Geofisica e
Vulcanologia, Rome, Italy, daniela.famiani@ingv.it; GOVONI, A., Istituto
Nazionale di Geofisica e Vulcanologia, Rome, Italy, aladino.govoni@ingv.it;
KEIL, S., Ludwig-Maximilians-University, Munich, Germany, S.Keil@lmu.
de; WASSERMANN, J., Ludwig-Maximilians-University, Munich, Germany,
j.wassermann@lmu.de
We deployed a 7C-station as a multiparameter recording setup, composed bya classical broadband seismometer (Nanometrics Trillium Compact Horizon120s), a rotational motion sensor (iXBlue, blueSeis-3A) plus an infrasoundsensor (Chaparral 64 UHP2). Here, we understand Urban Excitations as the

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daily anthropogenic noise (car and railway traffic, power lines, hydraulicpumps, washing machines, etc.) in the city of Florence, temporarily superposed by large oscillations generated during a public performance of the
Italian rock musician Luciano Ligabue. The 7-component station, installed
approximately 650 m eastwards from the concert hall “Nelson Mandela
Forum”, include three translational and three rotational components, which
recorded large amplitudes of seismic ground motion. These 6 degrees-offreedom, in combination with an additional infrasound sensor (0.015-50 Hz,
Nyquist frequency), allowed us to identify the generated wave types, to distinguish between the respective propagation paths, and to discriminate between
the seismic and the acoustic source(s).
The largest seismic amplitudes observed during the two-hours rockconcert appear as discrete monochromatic wave-trains in a predominant frequency range of 2-3 Hz. A parallel and synchronized video recording of themusical event proves that these oscillations correspond exactly to the masterbeat of the respective song (refrain) and are caused by the rhythmically jumping spectators. The seismic beat amplitudes are not amplified due to local site
effects, as suggested by the spectral ratios curve computed on the quiet partof ambient noise, but can be correlated with the number of enthusiastic spectators. Being recorded on the vertical and the radial (E-W) component, themaster beat signals are composed by Rayleigh waves. This is confirmed bydata from the rotational sensor, which hardly records signals below 8-9 Hz
due to its self-noise level. However, the large seismic amplitudes on the HJ2component between 2-3Hz stand out from the self-noise-dominated rotation
rate spectra. Unexpected was the recording of the departing traffic after theend of the concert.
#Utequake: An Outreach Project Combining Real-Time
Large Crowd Seismology and Football
RABADE, S., University of Utah, Utah, USA, san.rabade@gmail.com;
FARRELL, J., University of Utah, Utah, USA, jamie.farrell@utah.edu; HALE,
J. M., University of Utah, Utah, USA, hale.jmark@utah.edu; BLYCKER, W.,
University of Utah, Utah, USA, u0147397@gcloud.utah.edu; MORTON,
E., University of Utah, Utah, USA, emily.morton@utah.edu; FORBES, N.,
University of Utah, Utah, USA, u0875540@utah.edu; PANKOW, K. L.,
University of Utah, Utah, USA, kris.pankow@utah.edu; ROBERSON, P.,
University of Utah, Utah, USA, paul.roberson@utah.edu; WHIDDEN, K.,
University of Utah, Utah, USA, katherine.whidden@utah.edu
The #Utequake project is an outreach initiative from the University of Utah
Seismograph Stations that bridges the gap between science and Athletics. For
this project, we deployed a strong motion station in Rice-Eccles Stadium torecord and correlate in real-time the signals generated by the crowd during
University of Utah football home games. In this work, we showcase the visibility and impact of the project on social media, the University, and local media,
and we will show some comparisons of the largest amplitude signals during
the 2023 season. #Utequake showcases the powerful intersection of scienceand sports, creating a platform for education, entertainment, and community
engagement.
Enhancing Classification Reliability With Anomaly
Detection for Operational Monitoring of Continuous
Seismic Data
VAN DINTHER, C., Université Grenoble Alpes, Grenoble, France,
c.vandinther@gmail.com; MALFANTE, M., Université Grenoble Alpes,
Grenoble, France, marielle.malfante@cea.fr; CHIASSON-POIRIER, L.,
Université Grenoble Alpes, Grenoble, France, laurent.chiasson-poirier@cea.fr; GAILLARD, P., Université Paris-Saclay, Palaiseau, France, pierre.
gaillard@cea.fr; CANO, Y., French Alternative Energies and Atomic Energy
Commission, Arpajon, France, yoann.cano@cea.fr
With the ever-growing amount of seismic data collected, the role of artificial intelligence (AI) for processing and analyzing those recordings becomes
indispensable. Recent years have seen a surge in seismic detection and classification applications. However, the robustness of classification models poses achallenge: the complexity of continuous incoming stream of data is never fully
represented in a training set, and a classification model does not have the ability to detect unexpected behavior and to say “I do not know”. Consequently,
it will erroneously classify unknown samples in one of the predefined classes.
In current work, we improve the reliability of seismic data detection and classification in two different aspects. Using a 32-month seismic dataset from 43
French stations, identifying six classes, a single convolutional neural network(CNN) analyzes the entire multi-stational dataset. Firstly, we explored strategies to mitigate bias in a multi-class classification model due to class-size
imbalances. Best results are obtained by optimizing the loss function regarding class-size, enhancing balanced accuracy by 47%. Secondly, we propose thewww.srl-online.org•

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implementation of an anomaly detection module to mitigate the problem of
misclassification of unknown samples by providing the model the opportunity to say “I do not know where this sample belongs”. We considered foursemi-supervised anomaly detection algorithms, namely one-class SVM, elliptic envelope, isolation forest and local outlier factor. Our findings reveal thatincorporating an anomaly detection module effectively mitigates the misclassification of most novelties as predefined classes. Furthermore, it allows for
detecting unexpected behaviors such as anomalies, class drifts and ambiguous
samples. Thereby enhancing the trustworthiness and reliability of predictions.
Our study indicates that the isolation forest method yields best results for our
specific application.
Towards the Automatic Relocation of Intermediate-Depth
Earthquakes Using Adaptive Teleseismic Arrays
CRAIG, T. J., University of Leeds, Leeds, United Kingdom, t.j.craig@leeds.
ac.uk; BLACKWELL, A., University of Leeds, Leeds, United Kingdom,
ee18ab@leeds.ac.uk; ROST, S., University of Leeds, Leeds, United Kingdom,s.rost@leeds.ac.uk
The accurate location of intermediate-depth earthquakes has proven to
be one of the more enduring problems in global seismic location studies.
Complicated in many cases by a paucity of near-field observational data, thedetermination of accurate source depths for such earthquakes, in particular,
has proven to be elusive. As a result, and despite improvements in recorded
seismic data density and quality, the distribution and controls of these events
remain poorly understood.
Depth phases (near-source surface reflections, e.g. pP and sP) are crucial
for the accurate determination of earthquake source depth using global seismic data. However, such phases are often difficult to detect, suffering from low
signal-to-noise ratios, and are disguised in the P-wave coda, and often sufferfrom an ambiguity as to which depth phase has been observed.
To address this limitation, we develop an automated approach to groupglobally-distributed stations at teleseismic distances into ad-hoc arrays withapertures of 2.5 degrees, before optimising and applying phase-weighted
beamforming techniques to each array. We then use the resulting vespagrams from each medium-aperture array to automatically pick phase arrivals for the direct and depth phases, and determine differential arrival times
between the depth phases and their corresponding direct arrival. These aresubsequently used to invert for a new hypocentre location. We demonstrate
this method by relocating all intermediate-depth events above a magnitude
4.7 associated with a region of northern Chile and the Peruvian flat slab regionof the subducting Nazca plate. We demonstrate that our approach leads toa radical increase in the number of depth phases detected, particularly forsmaller-magnitude events, and makes a substantial difference to the locationof seismicity in intraslab settings, and to the resolution of the seismogenic
structure of the slab.
Receiver Functions in the Los Angeles Basin
VILLA, V., California Institute of Technology, California, USA, vvilla@
caltech.edu; CLAYTON, R., California Institute of Technology, California,
USA, clay@gps.caltech.edu; GKOGKAS, K., University of Utah, Utah, USA,
kos.gkogkas@utah.edu; LIN, F., University of Utah, California, USA, FanChi.
Lin@utah.edu
The Los Angeles Basin (LAB) is of interest to study because its subsurface
geometry and composition can increase the seismic hazard in this metropolitan area. Sedimentary basins can amplify seismic waves and prolong
their shaking. Virtual simulations from an M7.2 event on the San Andreas
Fault show a longer and amplified shaking in the Los Angeles area, whichis fed through channelization of the northern Los Angeles basins. We apply
the time-domain deconvolution methods to exploit the density of the station
along the two linear lines across the LAB and scattered nodal stations. Our
results improve the model of the Los Angeles Basin by applying modern geophysical methods to a newly acquired dataset that densely spans the basin.
Resolving the Structure of the Los Angeles Basin ThroughHigh-Resolution Seismic Tomography
BIONDI, E., California Institute of Technology, California, USA, ebiondi@
caltech.edu; LI, J., California Institute of Technology, California, USA, jxli@
caltech.edu; CLAYTON, R., California Institute of Technology, California,
USA, clay@gps.caltech.edu; ZHAN, Z., California Institute of Technology,
California, USA, zwzhan@caltech.edu
The urban area of Los Angeles is located within a large-scale deep sedimentarybasin that during large earthquakes can considerably amplify the recorded
seismic amplitudes, which in turn may result in considerable damage toVolume 95•

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buildings and infrastructure. The accurate prediction of earthquake groundmotion relies heavily on understanding the basin’s geometry and the seismic
properties of its filling material. Therefore, the accurate characterization of
sedimentary basins is crucial to correctly estimating shaking intensity in these
geological scenarios. Los Angeles stands as one of the most densely monitored
urban areas where a remarkable increase in continuously operated seismic
stations occurred since the 1980s. The Southern California earthquake catalog, comprising over 800,000 events derived from hundreds of thousands ofP- and S-wave arrival times, reflects this extensive seismic network. In addition to the traveltime picks from conventional stations, we also include arrival
times obtained using PhaseNet-DAS applied to distributed acoustic sensing(DAS) datasets collected over a year using preexisting telecommunication
fibers within the urban area. The conventional station data yields more than
16 million P-wave travel times and 8 million S-wave picks, while the DAS
data comprises approximately 1 million and 3 million arrival times for P- andS-waves, respectively. To fully exploit this vast dataset, we apply a matrix-free
Eikonal tomography and double-difference relocation workflow to the traveltime picks accumulated for more than 40 years. The combination of the highspatial density of DAS with the substantial number of cataloged events fromthe conventional station dataset allows us to significantly enhance the existing
velocity models and capture structural details at an unprecedented level ofdetails. Our new model would have important implications for the evaluationof the seismic hazard within Los Angeles and its surroundings.
Upper-Plate Seismicity and Focal Mechanism for Studying
the Stress State in the Mendocino Triple Junction
ISLAM, M., Indiana University, Indiana, USA, mdaislam@iu.edu; GONG, J.,
Indiana University, Indiana, USA, gongjian@iu.edu
The Mendocino Triple Junction (MTJ) is the place where the North America,
Pacific and Gorda plates meet. The interaction between the three plates resultsin frequent and damaging earthquakes that occur not only at major plateboundaries but also within each plate, with the largest and most destructive
one ever recorded being the 1992 M7 Petrolia earthquake within the overriding North America. Intriguingly, North America plate hosts faults withdiverse orientations near MTJ. The 1992 M7 Petrolia earthquake occurred ona westward, shallow dipping thrust fault at about 10 km depth, while most of
the shallow Quaternary faults are strike-slip dominated, oriented in the N-S
and NNW-SSE directions. Such spatially varying fault orientations indicatethat large spatial stress gradients exist in the overriding plate. To better quantify earthquake hazards of the upper plate, a more detailed picture of the stressfield is needed to understand under what conditions these faults are operated. In this study, we use focal mechanism of upper-plate earthquakes in the
MTJ region to infer the state of stress within the overriding plate and how
it changes spatially. We select events between -125.5° to -123° W and 39.5°
to 41.5° N from 2008 to 2022 with a magnitude >2 using the USGS ANSS
Comprehensive Earthquake Catalog and separate earthquakes that are above
the slab interface of the Slab2 model, which results in 816 total events. Threecomponent seismic waveforms are downloaded from IRIS and Northern
California Data Center. The number of available stations near MTJ increases
from 72 in 2008 to 92 in 2022 with a total of 188 permanent and temporary
stations active at different times. Those events are relocated using 3D velocity
model for the MTJ region. We manually pick P wave first motion polarities
in Pyrocko and calculate focal mechanism using HASH program. Our preliminary result shows that there is a range of focal mechanism solutions frommostly strike-slip near the coast and mostly normal faulting further inland.
We will invert these focal mechanisms to quantify the stress fields within theupper-plate.
Complex Deformation of the Northern Deep Tonga Slab
WILLIAMS, A., Washington University in St. Louis, Missouri, USA, adrea@
wustl.edu; WIENS, D. A., Washington University in St. Louis, Missouri, USA,
doug@wustl.edu; BERGMAN, E., Global Seismological Services, Colorado,
USA, bergman@seismo.com
Two-thirds of global deep earthquakes occur within the subducting Tonga
slab. The resulting dense seismicity provides important constraints on slab
deformation and deep earthquake rupture mechanisms. We explore the typeand distribution of deformation and earthquakes in the northern Tonga slab
using relative earthquake relocation and focal mechanism cluster analysis.
Roughly 1000 earthquakes were relocated using a hypocentroidal decomposition method. The arrival time dataset consisted of more than 400,000
arrival times, including regional arrivals from temporary land and ocean
bottom seismometer deployments as well as a variety of teleseismic arrival
phases sourced from the International Seismological Centre (ISC). 345 earthquakes were grouped into commonly occurring focal mechanism types using

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K-means cluster analysis of their P, T, and B axis orientations from the Global
Centroid Moment Tensor (CMT) catalog. The result of combining accurate
relative locations with CMT cluster analysis demonstrates unique seismicity
patterns. An extremely dense plane of seismicity aligns with steeply dipping
focal mechanism nodal planes along the top (southwest) portion of the slab,
indicating a shear zone of less than 5 km width. This near-vertical shear zone
is potentially localized in the subducted crustal layer, and indicates oblique,left lateral, and downward motion of the main part of the slab. To the northeast of the shear zone., This region of the slab shows along-strike extension,
with a lower seismicity rate. However, The largest earthquakes in the northern
deep Tonga slab do not occur within the highly seismic shear zone but in theextensional region of the slab. These observations are difficult to fit within
the framework of a metastable olivine wedge associated with transformational
faulting because of the complex pattern of deformation and the large width of
the seismic region compared to the that of the predicted olivine wedge.

patterns, time-dependent network topology changes, and data gaps can leadto a misrepresentation of the noise, introducing bias.
Here we use a Graph Neural Network (GNN) approach, already applied
to the daily time series, for denoising the high rate GNSS. The GNN’s strengthlies in its ability to handle the spatial heterogeneity of the stations within the
network and accommodate varying numbers of available stations. Neural networks have also shown robustness in addressing temporal gaps, making themsuitable for GNSS time series. To construct the graph, we connect multiple
stations based on rules. It enables the GNN to capture the spatiotemporal
structure of the noise at different levels, from individual stations to sub-networks and the entire network. We can remove unwanted noise by identifying
correlations between stations experiencing similar signal character. To evaluate our method, we apply it to our high-rate GNSS data processed with thePRIDE-PPP ar positioning software, with the goal of resolving large-scale secondary slip fronts in the high-rate GNSS data.

Using Machine Learning Algorithms to Explore theSeismoacoustic Wavefield at an Industrial Facility
CHAI, C., Oak Ridge National Laboratory, Tennessee, USA, chaic@ornl.
gov; MARCILLO, O., Oak Ridge National Laboratory, Tennessee, USA,
marcillooe@ornl.gov; MACEIRA, M., Oak Ridge National Laboratory,
Tennessee, USA, maceiram@ornl.gov; PARK, J., Southern Methodist
University, Texas, USA, junghyunp@mail.smu.edu; ARROWSMITH,
S., Southern Methodist University, Texas, USA, sarrowsmith@mail.smu.
edu; THOMAS, J. O., Consolidated Nuclear Security, LLC, Texas, USA,james.o.thomas@pxy12.doe.gov; CUNNINGHAM, J., Consolidated Nuclear
Security, LLC, Texas, USA, Joshua.Cunningham@pxy12.doe.gov

poster 167
Analysis of Characteristic Repeating Earthquakes in the
Tehuantepec Triple Junction, Mexico
DOMINGUEZ, L. A., Universidad Nacional Autónoma de México, Coyoacán,Ciudad de México, Mexico, ladominguez12@gmail.com; TAIRA, T., Berkeley
Seismological Laboratory, California, USA, taira@berkeley.edu

Operational activities at industrial facilities generate a diverse array of seismic and acoustic signals, providing valuable insights into the characterizationand monitoring of these activities. In an effort to enhance our understanding,nodal seismic stations were strategically deployed intermittently at an industrial facility in Texas. Given the intricate nature of operations and the involvement of high-frequency vibrations, seismic and acoustic sensors were configured to operate at a high sampling rate, exceeding 1000 samples per second.
Over the span of multiple data collection campaigns conducted between 2021
to 2023, a substantial seismic and acoustic dataset was amassed, surpassinga size of 10 TB. While traditional physics-based analysis and modeling havebeen carried out, we have also leveraged machine learning algorithms to delve
into the complex seismoacoustic wavefield at the site. A hierarchical clustering algorithm was applied to seismic signals originated from high-explosive(HE) detonations. A remarkable total of 39 signals related to detonations
were recorded at a single station. The clustering algorithm categorized similar
waveforms into cohesive clusters, enhancing our ability to discern patterns
within the data. A self-supervised machine learning technique has been developed to learn representative characteristics embedded within continuous seismograms, which can then be used to detect anomalies in the seismogram andcontribute to a more comprehensive understanding of the operational dynamics at the facility.

Special Applications in Seismology [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Carl Tape, University of Alaska Fairbanks(ctape@alaska.edu); Michael West, University of Alaska
Fairbanks, (mewest@alaska.edu)
poster 166
Sub-Daily Gnss Denoising Using Graph Neural Network
BACHELOT, L., University of Oregon, Oregon, USA, lbachelo@uoregon.edu;
THOMAS, A. M., University of Oregon, Oregon, USA, amthomas@uoregon.
edu; MELGAR, D., University of Oregon, Oregon, USA, dmelgarm@uoregon.
edu; SEARCY, J., University of Oregon, Oregon, USA, jsearcy@uoregon.edu
Global Navigation Satellite Systems (GNSS) time series have become increasingly precise, enabling researchers to study tectonic motion and transient
deformation, such as Slow Slip Events (SSEs). While daily GNSS data permit
analysis of such events with good accuracy, they lack temporal resolution. On
the other hand, sub-daily GNSS data have lower signal-to-noise ratios making it challenging to identify small amplitude signals. Current GNSS denoising methods, such as stacking, filtering, or common-mode filters (CMFs), areefficient at removing noise from the whole network. However, applying thesemethods to a heterogeneous network of stations with spatially varying noise

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Analysis of the characteristics repeating earthquakes has been extensively
used to examine the fault behavior of plate interfaces in a wide variety of
tectonic settings. It is believed that they are the result of reiterative rupturesfrom a common asperity in an otherwise creeping region. Therefore, resulting in a set of two or more events that produce almost identically waveforms
with similar magnitudes and recurrence times. In this study, we focus on thetemporal variations of the repeating earthquakes in the Tehuantepec triple
junction. On September 8th, 2017, this area was hit by a large M8.2 intraslab
earthquake that significantly redistributed the stress of this region. In a former
study, we found a set of 426 sequences along the flat segment of the subduction zone in the states of Guerrero and Oaxaca. Furthermore, we observeda sustained activity between two nearby large asperities resulting in magnitude M7+ earthquakes. Here, we perform a more extensive search of repeating earthquakes for all events reported by the National Earthquake Center
between 2001 through 2022 by using all the permanent broadband stations
including those around the triple junction in the Tehuantepec region. Thissearch consists of nearly ~1 million waveforms from the 217,285 cataloged
events (3.2<M<4.5). This study complements our studies along the flat portion of the in Guerrero-Oaxaca where repeating earthquakes showed a good
agreement with geodetic observations.
poster 168
Nodal Seismometer Recordings of Aftershocks of the 11
May 2023 Mw 5.5 Lake Almanor Earthquake
GOLDMAN, M. R., U.S. Geological Survey, California, USA, goldman@usgs.
gov; CATCHINGS, R. D., U.S. Geological Survey, California, USA, catching@usgs.gov; SICKLER, R. R., U.S. Geological Survey, California, USA, rsickler@
usgs.gov; CHAN, J. H., U.S. Geological Survey, California, USA, jchan@usgs.
gov; CRILEY, C. J., U.S. Geological Survey, California, USA, ccriley@usgs.gov
On May 11, 2023, an Mw 5.5 earthquake occurred near Lake Almanor,
California, followed by an Mw 5.2 aftershock 19 hours later. Starting on May
13, the US Geological Survey deployed 34 nodal seismometers (nodes) in
the vicinity of Lake Almanor to compliment the local permanent Northern
California Seismic Network (NCSN) stations. As there is only one active
strong-motion station in the immediate vicinity of Lake Almanor and noother strong-motion stations with 25 km of the epicenter, addition of thenodal stations represents a large temporary increase in local stations thatrecorded the aftershock sequence. The nodal stations were spaced approximately 2-3 km apart and consisted of SmartSolo IGU-16HR 3-component
nodes that recorded continuously at a 2-ms sampling interval from May 13
through July 25, 2023. One of the nodal stations was coincident with a station (CGS ID#L 87053) of the permanent network operated by the California
Geological Survey. The nodal stations, combined with the permanent network, provided more densely spaced recordings of events in the area, with the
combined network recording 25 Mw 2.5+ aftershocks, 5 of which were greaterthan Mw 3.0, as determined by the permanent network. The combined dense
nodal and permanent network stations expanded the recording azimuth(nodal stations surrounded most aftershocks) and is expected to significantly
increase the number of events in and the accuracy of the current earthquake
catalog for the region during the deployment period, particularly when evaluated with machine- learning-based methods (Yoon et al., 2015; 2023). From

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the improved catalog, we expect to develop detailed 3D P- and S-wave velocity
models and to better identify subsurface faults in the vicinity of Lake Almanor.
poster 169
Machine Learning as a Tool to Build a Comprehensive
Seismic Catalog for the Island of HispaniolaMUÑOZ, L. F., Baylor University, Texas, USA, luis_munoz4@baylor.edu;
WALTER, J., Oklahoma Geological Survey, Oklahoma, USA, jwalter@ou.edu;
PULLIAM, J., Baylor University, Texas, USA, jay_pulliam@baylor.edu;
LEONEL, J., Universidad Autónoma de Santo Domingo, Santo Domingo,
Dominican Republic, jleonel78@uasd.edu.do; POLANCO RIVERA, E.,
Universidad Autónoma de Santo Domingo, Santo Domingo, Dominican
Republic, eugenio.fisico@gmail.com
The island of Hispaniola, located on the northeastern boundary between the
North American and Caribbean plates, is shared by Haiti and the Dominican
Republic. In this region, the convergent margin to the east transitions to thetransform fault system in the west, leading to frequent earthquakes. Despitea history of devastating seismic events, existing catalogs lack crucial information concerning earthquake hazard, including fault lengths and seismogenic
potential. Building a comprehensive earthquake catalog, including both small
and large magnitude events across the entire region, is essential for reliable
estimates of seismic hazard. Traditional seismic detection methods are timeconsuming and susceptible to errors. Recent advances in machine learning
provide an opportunity to enhance seismic catalogs and produce a better
understanding of earthquake behavior and more accurate hazard assessment.
In this study, we employ machine learning techniques, utilizing theeasyQuake Python package, to analyze seismic data continuously recorded on
Hispaniola from 2014 to 2023. The Earthquake Transformer deep-learning
picker was applied to over 35 seismic stations across the island and its surroundings, successfully detecting and locating more than 121,000 seismic
events. This represents a sixfold increase in the number of identified seismic
events compared to catalogs from the seismic networks of the Dominican
Republic over the same period. The program Hypoinverse was used to relocate
these events, and filters were applied to remove poor locations, ensuring a reliable catalog. Most earthquake locations cluster around faults that are known
to be active, but others reveal patterns that may provide new insights into
earthquake dynamics on Hispaniola. The next steps in this research involverefining locations with HypoDD and employing other machine learning techniques, such as PhaseNet and Generalized Phase Detection, to compare theeffectiveness relative to Earthquake Transformer.
poster 170
Assessment of Atmospheric-Driven Ground Noises for
Dragonfly’s Seismic Observation on Titan
ONODERA, K., University of Tokyo, Bunkyo-ku, Japan, onodera@eri.utokyo.ac.jp; KAWAMURA, T., Institut de Physique du Globe de Paris, Paris,
France, kawamura@ipgp.fr; NISHIDA, K., University of Tokyo, Bunkyo-ku,
Japan, knishida@eri.u-tokyo.ac.jp; SHIRAISHI, H., Institute of Space andAstronautical Science, Japan Aerospace Exploration Agency, Sagamihara,
Japan, siraisi@planeta.sci.isas.jaxa.jp; TANAKA, S., Institute of Space andAstronautical Science, Japan Aerospace Exploration Agency, Sagamihara,
Japan, tanaka@planeta.sci.isas.jaxa.jp; MITANI, T., Institute of Space andAstronautical Science, Japan Aerospace Exploration Agency, Sagamihara,
Japan, mitani.takefumi@jaxa.jp; MURAKAMI, H., Kochi University,
Kochi, Japan, murakami@kochi-u.ac.jp; YAMADA, R., University of Aizu,
Aizu Wakamatsu, Japan, ryamada@u-aizu.ac.jp; KAMATA, S., Hokkaido
University, Sapporo, Japan, kamata@sci.hokudai.ac.jp; KIMURA, J., Osaka
University, Osaka, Japan, junkim@ess.sci.osaka-u.ac.jp; KUROKAWA, H.,
University of Tokyo, Komaba, Japan, hirokurokawa@g.ecc.u-tokyo.ac.jp;
SEKINE, Y., Tokyo Institute of Technology, O-okayama, Japan, sekine@
elsi.jp; TSUJI, T., University of Tokyo, Hongo, Japan, tsuji@sys.t.u-tokyo.
ac.jp; PANNING, M. P., Jet Propulsion Laboratory, California Institute ofTechnology, California, USA, mark.p.panning@jpl.nasa.gov; LORENZ, R. D.,
Johns Hopkins University, Maryland, USA, ralph.lorenz@jhuapl.edu
Dragonfly is one of NASA’s New Frontiers program missions, which is going
to explore the largest Saturn’s moon, Titan in the mid-2030s. The main focusof the mission is “extraterrestrial habitability”, and Titan was selected becauseof its high similarity to our planet compared to other accessible bodies. In
order to deepen our understanding of Titan’s environment and discuss thepossibility of extraterrestrial life, a quadcopter-type spacecraft is going to
fly to various sites on Titan and conduct chemical, meteorological, and geophysical observations on every landing occasion. As a part of the Dragonfly
Geophysics and Meteorology Package (DraGMet), our short-period seis-Volume 95•

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mometer (DraGMet SEIS) will be installed on the spacecraft to investigate theinternal environment of Titan.
The assessment of environmental noises is an important step in seismic
observation because they directly control the quality of the data. On Earth,owing to a dense and worldwide seismic network together with meteorological stations, we can easily evaluate the noise level. However, due to a limited
source of information on extraterrestrial planetary bodies, we are forced torely on numerical modelings or extrapolation from Earth’s analog observations. In this study, we are trying to model a seismic noise induced by atmospheric activities on Titan, referring to terrestrial examples and the InSight
seismic observation on Mars (2018–2022). In the presentation, followed byintroducing the theoretical background and an example of the application to
Martian seismic observation, we will share a preliminary environmental noisemodel of Titan. In addition, we will discuss how the atmospheric-induced
signals can be used for the subsurface investigation.
poster 171
Ground Deformation Caused by Atmospheric Gravity
Waves on Mars: An Independent Assessment of Martian
Crustal Rigidity
ONODERA, K., University of Tokyo, Bunkyo-ku, Japan, onodera@eri.utokyo.ac.jp; NISHIDA, K., University of Tokyo, Bunkyo-ku, Japan, knishida@
eri.u-tokyo.ac.jp; WIDMER-SCHNIDRIG, R., Black Forest Observatory,
Wolfach, Germany, widmer@gis.uni-stuttgart.de; KAWAMURA, T., Institut
de Physique du Globe de Paris, Paris, France, kawamura@ipgp.fr; SPIGA,
A., Institut Pierre-Simon Laplace, Paris, France, aymeric.spiga@lmd.ipsl.fr;
HERNANDEZ-BERNAL, J., Institut Pierre-Simon Laplace, Paris, France,
jorge.hernandez-bernal@lmd.ipsl.fr; STUTZMANN, E., Institut de Physiquedu Globe de Paris, Paris, France, stutz@ipgp.fr; XU, Z., Institut de Physiquedu Globe de Paris, Paris, France, zongboxu@ipgp.fr; HORLESTON, A.,
University of Bristol, Bristol, United Kingdom, Anna.Horleston@bristol.ac.uk;
SCHIMMEL, M., GeoSciences Barcelona, Barcelona, Spain, schimmel@ictja.
csic.es; MURDOCH, N., Institut Supérieur de l’Aéronautique et de l’Espace,
Toulouse, France, naomi.murdoch@isae-supaero.fr
Seismic observations on extraterrestrial bodies always face challenges because
we are forced to perform single-station seismology or sparse network seismology. The former is exactly the case of the NASA InSight (Interior Exploration
using Seismic Investigations, Geodesy and Heat Transport) mission, which
conducted seismic and meteorological observation on Mars (2018–2022).
In such a case, simultaneous observation of seismic and meteorological data(such as atmospheric pressure) is useful for estimating the internal structureof a planet. On Earth, the measurement of the ground deformation due tobackground pressure variations allows us to assess ground rigidity, known as
Sorrells’ theory. Nowadays, this theory is applied to event-driven signals (e.g.,convective vortices, gravity waves) not only on Earth but also on Mars.
Previous studies on Mars estimated the rigidity structure down to tensof meters, focusing on convective vortices, which excite energy around 0.5–
1.0 Hz. To retrieve structure information from greater depth, this study pays
attention to atmospheric gravity waves, whose energy range is around 1 mHz.
In the analysis, we retrieved InSight’s seismic and pressure data for windows
containing atmospheric gravity waves, computed the transfer function (thespectral ratio between pressure and horizontal acceleration), and then estimated Young’s modulus of the Martian crust. In the presentation, followedby an example of analysis for terrestrial gravity waves (especially the Lambwave from the Hunga-Tonga eruption in 2022), we will present the results for
Martian gravity waves and discuss the consistency with the structure obtained
from analyses of Martian quakes.
poster 172
Efficient Cataloging of Low-Frequency Earthquakes With
Deep-Learning Model and Template Matching
PAPIN, L., University of Oregon, Oregon, USA, papinlois@gmail.com;
THOMAS, A. M., University of Oregon, Oregon, USA, amt.seismo@gmail.
com; LIN, J., Lawrence Livermore National Laboratory, California, USA,
lin51@llnl.gov; HAWTHORNE, J., University of Oxford, Oxford, United
Kingdom, jessica.hawthorne@earth.ox.ac.uk
Low-frequency earthquakes (LFEs) are small-magnitude earthquakes that are
depleted in high-frequency content relative to traditional earthquakes of similar magnitude. Typically associated with slow slip events (SSEs), LFEs offer
insights into the space-time evolution of SSEs. However, due to their weaksignals and computationally expensive identification methods, LFEs are notroutinely cataloged in most places. Here, we develop a deep-learning modeltrained on an existing LFEs catalog to detect LFEs in 14 years of continuous
waveform data in southern Vancouver Island. The result shows a significant

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rise in detection rates at individual stations, with over 1 million LFEs during
the study period located by using a grid search approach in a 3D regional
velocity model. Our resulting catalog is consistent with the tremor catalog
during periods of large-magnitude SSEs. However, there are cases where it
registers far more LFEs than the tremor catalog. We highlight a 16-day period
in May 2010, our model detects nearly 3,000 LFEs, whereas the tremor catalog
contains only one tremor in the same region. This suggests the possibility ofhidden small-magnitude SSEs that are undetected by current approaches.
In addition to the presented work, we extend the investigation into LFEs
by employing template matching as a validation method for the detections
outlined in the existing catalog. These detections serve as templates subjected to cross-correlation across signals from various stations on southern
Vancouver Island. The cross-correlation method facilitates the identificationof new detections based on coefficients exceeding a predetermined threshold.
The newly defined detections are then stacked and utilized as refined templates, building a base for an iterative process, enhancing the signal-to-noise
ratio (SNR). The emergence of clear P- and S-wave arrivals from the noise
during this template matching procedure validates the initial detections as
LFEs. This methodology aims to validate the deep-learning model’s detections, contributing to the confirmation of LFEs and uncovering potential hidden seismic activity.

Structure and Behavior of the Alaska-Aleutian Subduction
Zone
Oral Session • Friday 3 May • 8:00 am PacificConveners: Grace Barcheck, Cornell University (grace.
barcheck@cornell.edu); Julie Elliott, Michigan State
University (ellio372@msu.edu); Ronni Grapenthin,
University of Alaska (rgrapenthin@alaska.edu); Donna
Shillington, Northern Arizona University (donna.
shillington@nau.edu); Xiaotao Yang, Purdue University(xtyang@purdue.edu)
Forty-Five Years of the Shumagin Gap: What Recent
Earthquakes Tell Us About This Seismic Gap
HERMAN, M. W., California State University, Bakersfield, California, USA,mherman2@csub.edu; FURLONG, K. P., Pennsylvania State University,
Pennsylvania, USA, kpf1@psu.edu; BENZ, H. M., U.S. Geological Survey,
Colorado, USA, benz@usgs.gov
McCann et al. (1979) identified the 200-km long section of the Alaska-AleutianIslands subduction zone near the Shumagin Islands as a “seismic gap”—anarea that had not hosted a recent M 8.0+ megathrust earthquake and was thus
likely to do so in the future. Since then, interpretations of the Shumagin Gap
have ranged from this initial view of it being overdue for a large event, toit being poorly coupled and unlikely to ever rupture in a large earthquake.
A sequence of large earthquakes starting in 2020 updates our understanding
the seismotectonics of the region. The July 2020 M 7.8 Simeonof megathrust
event, the October 2020 M 7.6 Sand Point intra-slab strike-slip event, the July
2021 M 8.2 Chignik megathrust event, and the M 7.2 megathrust event inJuly 2023 all illuminate aspects of plate interface coupling and its effects onearthquake cycle strain accumulation and release. We combine observationsof these earthquakes with finite element models of subduction zone locking torevisit the nature of the plate interface in the Shumagin Gap. Together, these
allow us to develop a pattern of coupling in the Shumagin Gap that satisfies
seismic, geodetic, and geologic datasets. We find a lateral transition from highcoupling on the plate interface east of the Shumagin Gap to low coupling in
the Shumagin Gap. The Shumagin Gap megathrust is therefore unlikely torupture in a tsunamigenic, M 8.0+ earthquake. This low coupling is not uniform over the depth extent of the Shumagin Gap plate boundary—the downdip edge of the plate interface in the Shumagin Gap hosts moderate (up toM ~7) earthquakes, indicating some locking in this region. Recent offshore
GNSS observations support low coupling on the shallow megathrust acrossthe entire area. The poorly coupled areas of the plate interface in the Shumagin
Gap and the shallow megathrust accumulate partial slip deficit because of
their proximity to nearby locked zones, and can participate in co-seismic
and/or post-seismic slip associated with nearby large events rupturing thoselocked zones.

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Putting the Pieces Together: A Kinematic Coseismic Modelof the Mw 7.2 Alaska Earthquake
DEGRANDE, J., University of Washington, Washington, USA, jdegran@uw.edu; CROWELL, B., University of Washington, Washington, USA,crowellb@uw.edu
A Mw 7.2 earthquake occurred in July 2023 offshore the Alaska Peninsula,
rupturing a western portion of the Shumagin Gap. Three years prior in July
2020, a Mw 7.8 event ruptured the eastern portion of the gap, previously
known for being devoid of large earthquakes over the last century and characterized by low geodetic coupling. Later in 2020, a Mw 7.6 event strike-slip
earthquake potentially ruptured the central portion of the gap as evidenced bytsunami data, updip of the July, 2020 Mw 7.8 earthquake. Deeper postseismic
deformation was evident after the July, 2020 earthquake. Here we investigate
the kinematic rupture of the July, 2023 Mw 7.2 event using a joint inversionof high-rate GNSS, strong motion data, and static offsets recorded during theevent. We utilize MudPy, an open-source, multi-data source modeling andinversion toolkit available on GitHub, with an 800-patch mesh of the subduction slab to assess the slip distribution. We analyze the full sequence of these
events to understand the release of accumulated strain at certain depths inthis portion of the Alaska-Aleutian Subduction Zone. With the recent > Mw 7
events in the Shumagin Gap, we investigate how this Mw 7.2 event fits in relation to the other events within the past three years to gain an understanding of
the coupling of the region and the partial filling of the Shumagin seismic gap
to enhance hazard mitigation and assessment in the region.
A Joint Coseismic and Early Postseismic Study of the 29
July 2021, Mw 8.2 Chignik Earthquake
ZHUO, Z., Michigan State University, Michigan, USA, zhuozech@msu.edu;
FREYMUELLER, J. T., Michigan State University, , USA, freymuel@msu.edu;
XIAO, Z., Kunming University of Science and Technology, Kunming, China,
zhhxiao@whu.edu.cn; ELLIOTT, J., Michigan State University, Michigan,
USA, ellio372@msu.edu; GRAPENTHIN, R., University of Alaska Fairbanks,
Alaska, USA, rgrapenthin@alaska.edu
Understanding the coseismic slip distribution of a megathrust earthquake andthe postseismic mechanisms that follow is a task of both critical importanceand notable difficulty. For the coseismic slip, due to the sparseness of data andregularization in the inversion, it’s common that models that fit the data varyconsiderably from one to another. Postseismic models can receive bias fromthe coseismic slip models, especially for those physically based stress-driven
models. Second, it’s difficult to separate viscoelastic relaxation and afterslip
because of the similarity both in time history and spatial pattern, especiallyin the early postseismic period. Third, there are tradeoffs between parametersin simulation models, for example, the stress change and frictional properties
in afterslip simulation, and the geometry and viscosity in viscoelastic models.
In this study, we show how a joint study of coseismic slip and the postseismic mechanisms of the 29 July 2021, Mw 8.2 Chignik earthquake helps
to resolve these difficulties. We use a joint seismic-geodetic coseismic inversion to determine the coseismic slip distribution, and varying assumptions
about the slip area. We use stress-driven models based on regularized ratestrengthening law to simulate afterslip, and we use the VISCO2.5D software
to simulate viscoelastic relaxation. We find that viscoelastic relaxation models are not sensitive to variations in the coseismic slip models, but afterslip
models provide new constraints on the coseismic slip distribution, as fitting
the postseismic data requires that there be coseismic shear stress increases atparticular places. We find the afterslip and viscoelastic relaxation models arecomplementary in the horizontal component but make opposite predictionsin the vertical component, and that the viscoelastic relaxation vertical predictions are very sensitive to features of the assumed geometry like the thicknessof the lithosphere and the existence of a cold nose to the mantle wedge. By
treating the horizontal and vertical components separately, we can more confidently determine a postseismic model.
Estimating Slip Models and Ground Motion for the 1964
Mw 9.2 Alaska Earthquake
THURIN, J., University of Alaska Fairbanks, Massachusetts, USA, jthurin@
alaska.edu; THIO, H. K., AECOM, California, USA, hong.kie.thio@aecom.
com; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.
edu
We revisit the 1964 Mw 9.2 Alaska earthquake rupture using a reviewed dataset of seismic, tsunami, and geodetic observations, including an extended setof leveling-line measurements. This new dataset motivates us to consider afault model that follows the Slab 2.0 subduction interface and extends further
east from previous models (Plafker, Ichinose) to better match the spatial dis-www.srl-online.org•

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tribution of the known aftershocks. In addition to the updated fault geometry
and additional data, we also used improved and higher-resolution bathymetric effects as well as an advanced tsunami model that computes arrival times
more accurately. For the leveling data, we also solve for a baseline correction,and for all Green’s functions, we correct for the large topographic variations
from trench to shore. Even with the additional data, there is still a large rangeof solutions consistent with the data. Rather than focusing on a “best” fitting
solution, which is highly subjective in this case, we develop a suite of solutions
that are consistent with the data and span a range of inversion constraints
such as rupture speed, rise-time, and weighting. We use this suite of inverted
rupture models to compute realistic static deformation scenarios, using 3D
spectral-element waveform modeling. This allows us to evaluate the slip distribution over the whole region, which we can compare with the existingcoseismic offset maps and geodetic observations.
Earthquake Location Improvements for the AleutianAlaska Subduction Zone by Using Waveform CrossCorrelation Data
LIN, G., University of Miami, Florida, USA, glin@miami.edu
Alaska is one of the most seismically active states in the United States, withmore large earthquakes than the rest of the country. The adjacent Aleutian
Subduction Zone, serving as a convergence boundary between the North
American Plate and the Pacific Plate, has had several notable earthquakes,
some of which were associated with tsunamis. In this presentation, I show thehigh-precision earthquake relocation results by using waveform cross-correlation data and characteristics of seismicity in the Aleutian-Alaska subduction
zone. The current work is focused on the 43,000 earthquakes in 2020. The
majority of these earthquakes occur above 150 km depth and the magnitudes
range from -0.5 to 7.8. In order to improve absolute location accuracies, I first
perform the three-dimensional earthquake relocation based on phase arrival
times through the AKEP model by Nayak et al. (2020), which covers southern-central Alaska. Given the large amount of seismic data, waveforms are
only downloaded for AK, TA and AV network stations from the Incorporated
Research Institutions for Seismology (IRIS). Before cross-correlation, theseismograms are pre-processed (e.g., filter, resample, etc.) to ensure the best
correlation results. The calculation is performed for each event with its closest
neighbors up to 200 within 20 km distance. The final waveform cross-correlation relocation shows dramatic improvements in relative locations and correlates with the geological structures significantly better compared with theinitial locations. The relocation catalog can provide updated constraints on
subduction zone earthquake mechanisms, fault geometries, regional deformation, and ground motion models, which are all essential for assessing seismic
hazards.
Upper Plate Stress in the Alaskan Continental Crust:
Spooky Interactions at a Variety of Distances
LEVANDOWSKI, W., Tetra Tech, Inc., North Carolina, USA, will.
levandowski@tetratech.com; COULTER, C., Tetra Tech, Inc., Alaska, USA,christina.coulter@tetratech.com
To understand the impacts of Alaska-Aleutian subduction on the overlying
crust and far-field continental interior, we compile moment tensors from 3048
earthquakes in the Alaskan continental crust. Inverting these provides thefirst comprehensive statewide stress map, first Alaskan stress model updatein 15 years, and the first to take advantage of improved coverage from the
Earthscope Transportable Array.
Subduction controls near-field stress. Reverse-oblique faulting accommodates radial crustal shortening around the flat-slab segment in southcentral Alaska, from Cook Inlet to the northern Alaska Range foothills andall along the Denali/Totschunda fault system. Similarly, radial shorteningaround the Yakutat block occurs by reverse faulting. Above the slab tear
between these two, however, NW–SE lower crustal extension may result fromincreasing buoyancy due to heating and underplating beneath Prince WilliamSound, the western Chugach and Talkeetna Mountains. The Queen CharlotteFairweather system transitions from oblique shortening near Yakutat Bay to
strike-slip and then to oblique extension south of Haida Gwaii; tsunamigenic
potential cannot be fully understood without accounting for this along-striketransition in faulting style.
Plate-boundary compression wanes with distance into the continent,
controlling maximum stress directions but giving way to variable intraplatedeformation. Strike-slip with secondary N–S contraction dominates the upper
Yukon basin and eastern Brooks Range. Between the Tintina and Kaltag faults,
maximum stress is consistently NNW–SSE, yet secondary extension replaces
contraction. This trend continues westward: Despite compressive boundary tractions, oblique extension is widespread across western Alaska. In theVolume 95•

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Purcell and Baird Mountains, Seward Peninsula and diffusely across southwest Alaska, primarily strike-slip motion includes significant NNE–SSW
stretching roughly parallel to the distant plate boundary, suggesting escapetectonics. Equal parts normal and strike-slip faulting accommodate NW–SE
extension in the western Aleutian backarc and ESE–WSW extension in the
Bering Sea.
A Chicken and Egg Dilemma: Forearc Strain Field andSeismic Behavior in the Andreanof Segment.
CORTÉS RIVAS, V., Northern Arizona University, Arizona, USA, vc553@
nau.edu; SHILLINGTON, D. J., Northern Arizona University, Arizona, USA,
Donna.Shillington@nau.edu; LIZARRALDE, D., Woods Hole Oceanographic
Institution, Massachusetts, USA, dlizarralde@whoi.edu; MARK, H., Woods
Hole Oceanographic Institution, Massachusetts, USA, hmark@whoi.edu;
BOSTON, B., Auburn University, Alabama, USA, boston@auburn.edu
What determines megathrust slip behavior in subduction zones is still under
debate, and the relationship between the preferred slip style over short,earthquake-cycle time scales and long-term patterns of deformation also
remains poorly understood. We collected multichannel seismic data, USGS
legacy reflection data, and gravity data in the Andreanof segment of the
Aleutian Islands to address these questions. This region presents contrasting seismic and locking behavior from west to east. There is a higher recurrence of large earthquakes and tsunamis and higher coupling in the westernsection. Moreover, the oblique subduction leads to strain partitioning. As aconsequence, the upper plate developed strike-slip faults and rotating blocks,
impacting the distribution of compressional and extensional stress.
Observations indicate distinct forearc deformation styles in the easternregion (Atka) and the western region (Adak). Atka has a wide forearc basinwith flat layers, whereas Adak shows more compression by uplifting thefrontal prism and forearc basin shortening, which correlates with the higher
recurrence of megathrust earthquakes. Adak shows intracrustal reflectors that
could be magmatic intrusions, underplating, or old deformational features.
The incoming plate properties, sediments, and trench infill show similar
characteristics in the entire Andreanof segment. Thus we propose that overriding plate properties contribute to the different seismic and deformational
styles. The combination of differences in rheology due to magmatic intrusions, underplating, and/or pre-existing deformation and differences in tectonic stress associated with rotating blocks and the strike-slip systems could
impact fault development and changes in forearc permeability. We explore thehypothesis that the higher shortening in the western section could be more
efficient in releasing pore fluid pressure, increasing the effective stress, which
promotes coupling and deformation.
Structural and Compositional Controls on Megathrust Slip
Behavior Inferred From a 3D, Crustal-Scale, P-Wave
Velocity Model of the Alaska Subduction Zone Spanning
the Incoming and Overriding Plates
ACQUISTO, T. M., Columbia University, New York, USA, acquisto@ldeo.
columbia.edu; BÉCEL, A., Columbia University, New York, USA, annebcl@
ldeo.columbia.edu; CANALES, J., Woods Hole Oceanographic Institution,
Massachusetts, USA, jcanales@whoi.edu; BEAUCE, E., Columbia University,
New York, USA, ebeauce@ldeo.columbia.edu
Earthquake hazard assessment in subduction zones requires an understanding of how large-scale features of both the downgoing and overriding plates
influence megathrust slip behavior. However, questions remain regarding therole of broad structural variability in modulating complex behaviors of megathrust faults. The Alaska subduction zone offshore the Alaskan Peninsula
exhibits along-strike variations in geodetic plate coupling, seismicity, andearthquake rupture style, making it an excellent location for studying thesestructural influences. Here, we focus on the Semidi segment and SW Kodiak
Asperity of the Alaska subduction zone. Plate coupling is typically high inour study area, with the largest degree of locking inferred near Kodiak Island
which hosted part of the 1964 Mw 9.1 event. Coupling decreases to the west,
with recent modeling showing a reduction in size of persistent asperities associated with past (1938-1964) and recent (2021) great earthquakes.
In this presentation, we will explore potential structural and compositional controls on spatial variations in megathrust slip behavior by analyzing a
3D P-wave velocity model within a 400- by 400-km area with resolution down
to 25-30 km depth. The model was computed by traveltime tomography inversion of wide-angle first-arrivals interpreted from active-source ocean bottom
seismometer data acquired as part of the Alaska Amphibious Community
Seismic Experiment (AACSE). Results underscore the heterogeneity of theincoming plate marked by hotspot magmatism, fracture zones, and unevensediment cover. Landward of the trench, variations in backstop geometry andSeismological Research Letters

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slab velocities appear correlated with changes in sediment input and the possible downdip persistence of structural features of the incoming plate. In theoverriding plate, velocity changes provide clearer evidence of differences inmetamorphic grade between terranes and intrusions therein. This presentationwill focus on reconciling these observations with corresponding changes
in megathrust plate coupling as well as with past and recent large earthquakes
in the area.
A Late Miocene to Pliocene Increase in Soft-Sediment
Deformation in Cook Inlet Nonmarine Forearc Basin
Strata—potential Evidence for Larger Magnitude
Earthquakes Associated With Increased Sedimentation in
the Alaska Trench
WARTES, M. A., Alaska Division of Geological & Geophysical Surveys,
Alaska, USA, marwan.wartes@alaska.gov; LEPAIN, D. L., Retired (Alaska
Division of Geological & Geophysical Surveys), Alaska, USA, lepaindavid@
gmail.com; STANLEY, R. G., Retired (U.S. Geological Survey), California,
USA, rickgstan@gmail.com; HELMOLD, K. P., Retired (Alaska Divisionof Oil & Gas), Alaska, USA, helmold@alaskan.com; GILLIS, R. J., Alaska
Division of Geological & Geophysical Surveys, Alaska, USA, robert.gillis@
alaska.gov
Previous analyses of compiled megathrust earthquake data have revealed astatistically significant positive correlation between great events (>Mw8.0)
and thicker sediment fill in the trench. This has been interpreted to reflect theimportant role sediment can play in muting bathymetric relief and smoothing the subduction interface. The reduction in potential asperities may
allow ruptures to propagate for longer distances, increasing the total energy
released. Seismological studies in southern Alaska have imaged a low velocity zone beneath the Kenai Peninsula, consistent with underplated sediment.
This material in the subduction channel is likely sourced from the east, whereimmense volumes of glaciogenic sediment have been routed into the trenchsince Late Miocene time (~7 Ma), reflecting rapid uplift and exhumation of
the Chugach–St. Elias orogen during collision of the Yakutat terrane.
The 1964 Mw9.2 earthquake in southern Alaska produced a variety ofliquefaction features in terrestrial settings, including sedimentary dikes that
fed surface sand volcanoes. Potentially analogous soft-sediment deformation
is locally observed in the Lower and Middle Miocene Tyonek and Beluga
formations along the lower Kenai Peninsula. The relative abundance of thesefeatures increases dramatically in the overlying latest Miocene to Pliocene
Sterling Formation, ranging from complexly folded, convolute bedded sandstone to zones where disrupted laminations grade laterally into structurelessunits. These facies are often closely associated with vertical pipe-like featuresthat are collectively interpreted as evidence for liquefaction during intense,
prolonged seismic shaking. We suggest the notable rise in soft-sediment
deformation at ~ 5–7(?) Ma may reflect an increase in the frequency of verylarge megathrust earthquakes promoted by greater Neogene sediment flux
into the trench. If correct, our study significantly extends the possible recordof large megathrust earthquakes in southern Alaska into deep geologic timeand highlights the value of forearc basins as long-term archives of subduction
zone dynamics.
Variations in the Alaska-Aleutian Subduction Megathrust
Properties Along Strike Using Several Seismic Imaging
Techniques
DALY, K. A., Cornell University, New York, USA, kad278@cornell.edu;
ABERS, G. A., Cornell University, New York, USA, abers@cornell.edu;
MANN, M. E., Brown University, Rhode Island, USA, michael_mann@brown.edu; PANG, G., Cornell University, New York, USA, guanning.pang@cornell.edu; KIM, D., Imperial College London, London, United Kingdom,
doyeon.kim@imperial.ac.uk
The Alaska-Aleutian subduction zone is one of the most seismically active
plate boundaries in the world. Many of the subduction zone characteristics
are linked to the shear zone at the top of the subducting plate. However, ourinterpretation of this region is limited by the discrepancy observed between
seismic imaging techniques. We investigate this discrepancy and changes in
the Alaska subduction zone properties along strike using a combination ofseismic imaging techniques. We analyze data from 34 onshore and offshore
broadband seismic stations from the Alaska forearc, recorded by the Alaska
Amphibious Community Seismic Experiment (AACSE; 2018-2019) and surrounding permanent stations. At each station, we identify high-frequency P
to S (PS; 1-10 Hz) mode conversions from local in-slab earthquakes at the
subducting plate interface. We also generate receiver functions (RFs) fromteleseismic earthquakes (0.03–1.5 Hz) to identify the PS arrivals associatedwith the subducting plate. The PS arrival time is dictated by the depth of

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structures to which the local and RF PS arrivals are sensitive. Using 3D ray
tracing, we find local PS arrivals are sensitive to structures 10 km shallower
than RF PS arrivals. The depth of structures seen by local PS corresponds tothe top of the high reflectivity shear zone in co-located active source profiles,
while the RFs illuminate the oceanic Moho. These results and full waveformmodeling indicate that local PS arrivals are sensitive to finer-scale structures
within the shear zone, while RFs respond to longer-wavelength structures.
Therefore, the discrepancy observed between seismic imaging techniques is
explained by frequency-dependent sensitivity to structure. Local Ps arrivals
are observed across the Kenai, Semidi, and Shumagin segments but are absent
around Kodiak. The lack of local PS conversions below Kodiak could indicate
the shear zone and upper plate have similar seismic properties, or that there is
no shear zone present. Along-strike variability in PS arrivals provides valuable
insight into changes in shear zone properties.
Implications of Yakutat Oceanic Plateau Buoyancy Versus
Variable Interface Coupling on Deformation in SouthCentral Alaska
HAYNIE, K. L., U.S. Geological Survey, Colorado, USA, khaynie@usgs.gov;
JADAMEC, M. A., University at Buffalo, SUNY, New York, USA, mjadamec@
buffalo.edu
The subduction margin of south-central Alaska is marked by oblique flat slab
subduction and subduction-collision of the Yakutat oceanic plateau beneathNorth America. Both subduction of young seafloor and subduction of an oceanic plateau may cause an increase in slab buoyancy that can lead to increased
resistance to subduction as well as significant upper plate deformation.
However, the trade-off between flat slab subduction of young lithosphere versus oceanic plateau subduction on overriding plate deformation in Alaska is
still not well understood. Here we present three-dimensional numerical models of subduction in Alaska to examine: 1) the effects of flat slab subduction
geometry, 2) a localized increase in coupling along the plate boundary interface in the flat slab region, and 3) buoyancy of an oceanic plateau in controlling upper plate deformation. Simulations of flat slab subduction with variable
plate boundary coupling (10^20-10^21 Pa s) and with a simplified compositional buoyancy of the Yakutat oceanic plateau are analyzed. To determine
which set of parameters are most representative of the Alaska subduction system, model results are compared to observations of Wrangell block motion,differential motion across the Denali fault, and with along-strike variations inmountain building. We find that the positive buoyancy from the Yakutat oceanic plateau increases Wrangell block velocity, differential motion across the
Denali fault, as well as the extent of far-field deformation. Models with boththe Yakutat buoyancy and a local increase in plate coupling, however, cause agreater resistance to subduction causing a significant reduction in downgoingplate motion. This suggests a trade-off between the degree of plate coupling
and oceanic plateau buoyancy. Nonetheless, the geodynamic simulations showthat the inclusion of the buoyant oceanic plateau is important for producing positive dynamic topography above the flat slab and increasing Wrangell
block velocity, suggesting that subduction of the Yakutat oceanic plateau is
an important driver of overriding plate deformation in south-central Alaska.
Controls on Bending-Related Faulting Offshore of the
Alaska Peninsula
CLARKE, J., Southern Methodist University, Texas, USA, jwclarke@mail.
smu.edu; SHILLINGTON, D. J., Northern Arizona University, Arizona, USA,donna.shillington@nau.edu; REGALLA, C., Northern Arizona University,
Arizona, USA, Christine.Regalla@nau.edu; GAHERTY, J., Northern Arizona
University, Arizona, USA, james.gaherty@nau.edu; ESTEP, J., Northern
Arizona University, Arizona, USA, justin.estep@nau.edu; WIENS, D. A.,
Washington University in St. Louis, Missouri, USA, doug@wustl.edu; BÉCEL,
A., Columbia University, New York, USA, annebcl@ldeo.columbia.edu;
NEDIMOVIĆ, M. R., Dalhousie University, Halifax, Canada, mladen@dal.ca
Oceanic plates experience extensive normal faulting as they bend and subduct, enabling fracturing of the crust and upper mantle. Debate remains about
the relative importance of pre-existing faults, plate curvature and other factors
in controlling the extent and style of bending-related faulting. The subduction zone off the Alaska Peninsula is an ideal place to investigate controls on
bending-related faulting as the orientation of abyssal-hill fabric with respect
to the trench and plate curvature vary along the margin. Here we characterize bending faulting between longitudes 161°W and 155oW using newly
collected multibeam bathymetry data. We also use a compilation of seismicreflection data to constrain patterns of sediment thickness on the incoming
plate. Although sediment thickness increases by over 1 km from 156°W to
160°W, most sediments were deposited prior to the onset of bending faulting
and thus have limited impact on the expression of bend-related fault strikes

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and throws in bathymetry data. Where magnetic anomalies trend subparallel to the trench (<30°) west of ~156°W, bending faulting parallels magnetic
anomalies, implying bending faulting reactivates pre-existing structures.
Where magnetic anomalies are highly oblique (>30°) to the trench east of
156°W, no bending faulting is observed. Summed fault throws increase to thewest, including where pre-existing structure orientations do not vary between
157-161oW, suggesting that the increase in slab curvature directly influences
fault throws. However, the westward increase in summed fault throws is more
abrupt than expected for changes in slab bending alone, suggesting potential
feedbacks between pre-existing structures, slab dip, and faulting.
Outer-Rise Earthquakes and Their Contribution to Tsunami
Hazards Across the Alaska Subduction Zone
MATULKA, P., Washington University in St. Louis, Missouri, USA,
pmatulka@wustl.edu; WIENS, D., Washington University in St. Louis,
Missouri, USA, doug@wustl.edu; LI, Z., Washington University in St. Louis,
Missouri, USA, zongshan.li@wustl.edu; ABERS, G. A., Cornell University,
New York, USA, abers@cornell.edu; RUPPERT, N., University of Alaska
Fairbanks, Alaska, USA, naruppert@alaska.edu; HAEUSSLER, P., U.S.
Geological Survey, Alaska, USA, pheuslr@usgs.gov; BARCHECK, G., Cornell
University, New York, USA, grace.barcheck@cornell.edu; BERGMAN, E.,
Global Seismological Services, Colorado, USA, bergman@seismo.com
We compare the Shumagin, Semidi, and Kodiak sections of the Alaska subduction zones in terms of their outer-rise seismicity, faulting, and potential
tsunami hazard. We use data from land and ocean-bottom seismometers
deployed during the Alaska Amphibious Community Seismic Experiment(AACSE) and other land-based networks to relocate earthquakes. Seismicity
is highest in Shumagin, with normal faulting extending to 25 km below theseafloor and confined within 50 km of the trench. Semidi has less seismicity extending further from the trench, and the focal mechanisms transition
to strike-slip in the Kodiak segment. In Kodiak, we determine relative locations of aftershocks from the 2018 Mw 7.9 offshore Kodiak earthquake witha hypocentroidal decomposition program. The aftershocks form multiple N-Soriented lines consistent with right-lateral faulting along the N-S nodal planeof the focal mechanisms. TOPAS sub-bottom profiler records show numerous
closely-spaced (~ 5 km) N-S faults throughout the aftershock zone, but no
NE-SW faults. These results demonstrate that the 2018 mainshock consistedof strike-slip faulting along numerous en echelon N-S faults. The along-striketransition in outer-rise focal mechanisms indicates a change in tectonic stressregimes. Normal faulting earthquakes in Shumagin transition to right-lateral
strike-slip earthquakes by the boundary of the Kodiak segment. This transition approximately corresponds to the western extent of the 1964 Alaska
earthquake rupture zone, suggesting it may result from increased seismic
coupling along the megathrust to the east. For Shumagin, assuming a maximum normal faulting depth of 25 km and the observed maximum seafloor
fault length of 48 km (Clarke et al, in press), earthquake scaling laws predicta maximum outer rise earthquake magnitude ~ MW 7.3, which is insufficient
to produce a damaging tsunami. However, if ruptures propagate across fault
segment boundaries, tsunamigenic events of up to ~ MW 8.2 could occur. The
transition to strike-slip faulting in the Kodiak segment and eastward suggests
very limited outer rise tsunami hazard in these regions.
High-Resolution Rayleigh-Wave Tomography Constraints
on Hydration in the Incoming Plate Along the Alaska
Subduction Zone
YAKUBU, T., Northern Arizona Univ., Arizona, USA, ty235@nau.edu;
GAHERTY, J., Northern Arizona University, Arizona, USA, james.gaherty@
nau.edu; SHILLINGTON, D., Northern Arizona University, Arizona, USA,donna.shillington@nau.edu
Subduction zones are known to drive the water cycle on our planet, andwater that penetrates the subduction zone influences fundamental geological processes like the occurrence of large earthquakes and the generation ofarc magmas. However, the initial water content of many subducting slabs ispoorly known. Here we provide new constraints on the distribution of hydration in the incoming Pacific plate offshore of the Alaska Peninsula. We image
crust and shallow-mantle shear velocity and azimuthal anisotropy using
short-period Rayleigh waves derived from 15 months of ambient seismic
noise recorded by 32 ocean-bottom seismometers that were deployed fromoutboard of the outer rise to just inboard of the trench during the Alaska
Amphibious Community Seismic Experiment. After correcting for tilt andcompliance effects on the short-period Rayleigh waves, we observe first-overtone Rayleigh waves with high signal-to-noise ratios at periods of 5-10s. These

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data are useful for constraining velocity in the incoming oceanic crust anduppermost mantle. We measure inter-station phase velocities using a spectrafitting technique, and invert for 2-D phase velocity maps and 1-D and 2-D
estimates of azimuthal anisotropy. Phase velocity maps are then inverted fora 3D model of shear velocity in the crust and upper mantle. Shear velocities
show >5% lateral variations on the incoming plate in both the crust and shallow mantle, with localized low velocities outboard of the Shumagin gap, theSemidi segment, and the Kodiak region. Across the region, we find slower
velocities than expected for normal oceanic mantle and crust, suggesting pervasive hydration. We also find variations in crustal thickness associated withheterogenous plate history. Where well constrained, we find weak azimuthal
anisotropy with peak-to-peak amplitudes of 0-2%, and fast directions that are
oblique to the orientations of both expected seafloor-spreading mantle fabricand observed bending faults. These observations may be consistent with thecompeting anisotropic effects of fault-induced structural heterogeneity, andseafloor-spreading-induced olivine fabric.
Slab Dehydration Linked to Great Earthquake Rupture
Barriers Along the Alaska Peninsula
MOSER, L., Woods Hole Oceanographic Institution, Massachusetts, USA,
lmoser@whoi.edu; CANALES, J., Woods Hole Oceanographic Institution,
Washington, USA, jcanales@whoi.edu; BÉCEL, A., Columbia University, New
York, USA, annebcl@ldeo.columbia.edu
The amount of water entering subduction zones and how this water is stored
within the slab is debated. This limits our understanding of where exactly fluids are released during subduction and thus how the presence of fluids andchanges in pore pressure influence slip behavior along megathrusts. Here
we present 3-D compressional and shear-wave velocity models, and theirratio Vp/Vs, of the Alaska Peninsula subduction zone derived from local
earthquake tomography of the Alaska Amphibious Community Seismic
Experiment dataset. We use these models to investigate the hydration of, andfluid release from, the downgoing plate, and how this impacts megathrust
rupture. First, we identify a wide-spread water reservoir within the upper
mantle, characterized by elevated Vp/Vs resulting from fluid-filled low-aspectratio crack porosity. Second, slab dehydration is inferred from seismic velocity anomalies along the plate interface that we interpret as regions of highpore fluid pressure. These regions bound the rupture zones of the recent 2020
Mw7.8 Simeonof and the 2021 Mw8.2 Chignik earthquakes, demonstrating
how locations of fluid release and elevated pore pressure impact the frictional
properties of the megathrust and act as rupture barriers.
Seismic Structure of Arc Crust in the Andreanof Segmentof the Aleutian Arc from Wide-angle Refraction Data
MARK, H. F., Woods Hole Oceanographic Institution, Massachusetts,
USA, hmark@whoi.edu; LIZARRALDE, D., Woods Hole Oceanographic
Institution, Massachusetts, USA, dlizarralde@whoi.edu; SHILLINGTON,
D., Northern Arizona University, Arizona, USA, donna.shillington@nau.edu;
CORTÉS RIVAS, V., Northern Arizona University, Arizona, USA, vc553@
nau.eduArc crust is thought to be the source of new continental crust at this stageof Earth’s history. However, the basic structure of arc crust, the processes bywhich arc crust bulk composition evolves to match that of continental crust,and the pathways of melt migration and magma storage which control arc
geochemistry are not well understood. The Andreanof segment in the central part of the Aleutian Arc is a relatively undeformed and unrifted segment,
making it an excellent place to study the processes and factors influencing theconstruction and composition of arc crust. Further, geochemical variations in
arc lavas vary along strike within the segment, suggesting that there may bevariations in tectonically controlled volcanic plumbing systems and/or differences in the incoming plate which influence arc construction over relatively
short length scales.
We conducted an active-source seismic study of the Andreanof segment
in August-October 2020, with the goal of imaging the arc in sufficient detail tocharacterize the structure of the crust and any variations in that structure withpotential links to the geochemistry of volcanic products. Here we present aquasi-three dimensional velocity model for a seismic refraction line collectedalong-strike of the segment, incorporating data from active-source shots surrounding several islands and recorded both on 33 short-period ocean bottom seismometers and 34 AVO broadband stations. Notable features include aseismically slow carapace layer up to ~2 km thick, likely comprised of volcanic
flows and rubble; and anomalously slow crustal velocities, especially beneath
the Amlia basin.

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Along-strike Variations in Sub-arc Melting Beneath the
Alaska Peninsula Revealed by Body Wave Attenuation
ZHANG, Z., Michigan State University, Michigan, USA, zhuoran@msu.edu;
WEI, S. S., Michigan State University, Michigan, USA, swei@msu.edu
The diverse volcanic activity at the Alaska Peninsula potentially indicatessubstantial variations in mantle melting processes beneath the arc. Here we
investigate sub-arc melting beneath the Alaska Peninsula by measuring seismic attenuation in the mantle wedge as attenuation is sensitive to fluids, temperature, and partial melting. Our preliminary findings show high attenuation
anomalies at varying depths in the mantle wedge, with notable distinctions intheir lateral extent. In the northeast, high-attenuation anomalies are imaged
beneath major volcanoes and also at greater depths beneath the back arc. In
contrast, beneath the Pavlof volcano in the southwest, high attenuation isimaged at shallower depths down to 60 km. The observed variations suggest
along-strike changes in the thermal structure of the mantle wedge, hydrationof the subducting plate, and mantle flow patterns.
A Possible Slab Window Along the Alaska Subduction Zone
Imaged by Full Wave Ambient Noise Tomography
SASSARD, V., Purdue University, Indiana, USA, vincent.sassard@outlook.
com; YANG, X., Purdue University, Indiana, USA, xtyang@purdue.edu; LIU,
L., University of Illinois Urbana-Champaign, Indiana, USA, ljliu@illinois.edu;
ELLIOTT, J., Michigan State University, Michigan, USA, ellio372@msu.edu
Along-strike heterogeneities of subduction zones have been observed globally with variable behaviors in seismicity, locking fraction, slab dip, and volcanism. The Alaska subduction zone is an ideal natural laboratory to study
the processes controlling the along-strike variability of subduction systems.
Previous studies have demonstrated differences in slab dip, megathrust seismicity, seismic anisotropy, plate interface locking fraction, and variations ofslab hydration partly related to changes in oceanic plate fabrics. However, therelationship between these observations and the 3-D structural segmentation
remains poorly constrained. Here we use full-wave ambient noise tomography to generate a 3-D shear-wave velocity model of the Alaska subduction
zone in the Alaska Amphibious Community Seismic Experiment footprint
along the Alaska peninsula. Our velocity model reveals strong variations in
the geometry and velocity of the subducting Pacific slab. Low-velocity anomalies are present in regions of active volcanism and sediment subduction while
fast-velocity anomalies are observed in the subducting slab. At mantle depths,
low-velocity anomalies correlate with the projected changes in plate fabrics
and the gap of intermediate-depth earthquakes, indicative of a potential slab
window. Our findings suggest that, at the intersection of two plate fabrics, theslab might be relatively weak, which may facilitate tearing of the slab, allowing
the sub-slab asthenosphere to flow through.
The Structure of the Alaskan Mantle: A Full Waveform
Inversion Approach
FROST, D. A., University of South Carolina, South Carolina, USA, dfrost@
seoe.sc.edu; ROMANOWICZ, B., University of California, Berkeley,
California, USA, barbarar@berkeley.edu; ADOURIAN, S., Brown University,
Rhode Island, USA, sevan_adourian@brown.edu
Alaska has a complex subduction history, the remnants of which should bepresent down to the lowermost mantle. However, using existing tomographic
images it has been difficult to trace the long-term subduction patterns. This
partly results from inconsistencies between different global and regional
tomographic models of the area due to methodological limitations and limited sampling. Moreover, travel time tomography has known limitations whenresolving complex mantle structure, particularly when anomalies are strong
and localised. In contrast, Full Waveform Inversion, which seeks to explain
every wiggle of the seismogram, can account for multipathing and wavefront healing that mask strong heterogeneity like slabs and mantle wedges.
Therefore, Full Waveform Inversion can help improve our understanding of
the tectonic history of the Northern Pacific. In particular, it can aid in resolving the thickness of the Yakutat terrain and the width of the subducted slab.
Reducing the computational cost of Full Waveform Inversion is a major
challenge in its application. With this aim in mind, Masson and Romanowicz(2017, GJI) proposed a methodology, called “Box tomography”, in the framework of regional tomography, that allows the coupling of any solvers outside
and inside the target region. With this approach now available for use at large
scale with both sources and stations outside the target region (Adourian et al.,2023), it becomes possible to take into account teleseismic wavefields recorded
at stations located beyond the boundaries of the target region. Thus, we apply
Full Waveform Box Inversion to Alaska. Our inversions so far have resolved astronger and narrower seismic anomaly associated with the subducted Pacific

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from the surface to the core mantle boundary.
Upper Mantle Velocity Structure and Anisotropy of the
Alaskan Subduction Zone from Surface Wave Tomography
ADAMS, A., Colgate University, New York, USA, aadams@colgate.edu;
RAMIREZ, C., Colgate University, New York, USA, cramirez@colgate.edu;
WEN, J., Colgate University, New York, USA, jwen@colgate.edu; LECLERC,
P., Colgate University, New York, USA, pleclerc@colgate.edu
The subduction zone along the southern margin of Alaska is home to numerous active volcanos, and is the most seismically active portion of the UnitedStates. It has hosted several megathrust earthquakes, including the 1964 Great
Alaskan Earthquake, the second largest earthquake in recorded history. The
seismic and volcanic behaviors of the subduction zone, however, undergo dramatic changes along strike, with some areas slipping in great (M>8) events
while other regions deform primarily through creep. Understanding the origins of this variability could lead to important insights into subduction zone
processes and global geophysical hazards. Recent studies have highlighted therole that hydration of the subducting slab and the mantle wedge may playin governing these behaviors. In this study, Rayleigh and Love waves fromteleseismic earthquakes recorded on OBS and broadband land stations from
Alaska Amphibious Community Seismic Experiment are combined withsimilar data from the Alaska Transportable Array and other regional arrays
are used to build Rayleigh and Love wave velocity models. These surface wave
models are inverted for Sv and Sh velocities to solve for radial and azimuthal
anisotropy in the upper mantle beneath the Alaskan subduction zone. Thesemodels of velocity and anisotropy show considerable variation along strikeand support the hypothesis that hydration of the mantle wedge varies with the
Alaskan subduction system.

Structure and Behavior of the Alaska-Aleutian Subduction
Zone [Poster Session]
Poster Session • Friday 3 May
Conveners: Grace Barcheck, Cornell University (grace.
barcheck@cornell.edu); Julie Elliott, Michigan State
University (ellio372@msu.edu); Ronni Grapenthin,
University of Alaska (rgrapenthin@alaska.edu); Donna
Shillington, Northern Arizona University (donna.
shillington@nau.edu); Xiaotao Yang, Purdue University(xtyang@purdue.edu)
poster 104
A Re-Evaulation of Slip During the 2021 M8.2 Chignik,
Alaska Earthquake
BENNETT, A. J. M., Michigan State University, Michigan, USA, benne747@
msu.edu; ELLIOTT, J., Michigan State University, Michigan, USA, ellio372@
msu.edu; GRAPENTHIN, R., University of Alaska Fairbanks, Alaska, USA,rgrapenthin@alaska.edu; FREYMUELLER, J. T., Michigan State University,
Michigan, USA, freymuel@msu.edu
Along the Alaska-Aleutian subduction zone, there have been more large earthquakes during the past century than at any other subduction zone, including
four large M7+ earthquakes since 2020. The largest among these is the 2021
M8.2 Chignik earthquake, which ruptured part of the Semidi segment. Thisrupture started just to the east of a transition from lower to higher couplingon the megathrust. The Chignik earthquake has raised questions about earthquake triggering, relationships between coupling and earthquake rupture,and possible loading of the shallow megathrust. To answer these questions,a robust understanding of the coseismic slip distribution is needed. Multiple
coseismic models have been published, but they show variations in the amplitude and location of slip. To improve our picture of the coseismic slip distribution, we will present new coseismic models of the 2021 Chignik earthquakethat incorporate a larger dataset, including campaign GNSS measurements,
and use two different slab models to test the influence of slab geometry.
The campaign GNSS measurements have been corrected for post-seismic afterslip with existing InSAR data that has been tied with static GNSS
offsets, high rate GNSS data, and teleseismic waveforms. To test how different
slab models affect slip estimates, we develop models that use both Slab2 andan interface model based on active source seismic imaging (ALEUT model).

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At intermediate depths of the megathrust, where the Chignik earthquake
occurred, the ALEUT model suggests a plate interface several kilometers
deeper than the Slab2 model, which coincides with the USGS hypocenter
depth.

improved understanding of earthquake locations in the AASZ (see Nolan etal., this session), will enable us to analyze microseismicity patterns relative tomainshock hypocenters and asperities, and reveal fault zone processes in the
AASZ leading up to a major seismic event.

poster 105
Take the Cook Inlet DAS Earthquake Challenge!
BODIN, P., University of Washington, Washington, USA, bodin@uw.edu;
WILLIAMS, E. F., University of Washington, Washington, USA, efwillia@
uw.edu; SHI, Q., University of Washington, Washington, USA, qibins@
uw.edu; NI, Y., University of Washington, Washington, USA, niyiyu@uw.edu;
LIPOVSKY, B., University of Washington, Washington, USA, bpl7@uw.edu;
GOLOS, E., University of Wisconsin-Madison, Washington, USA, golos@
wisc.edu; GAETE ELGUETA, V. A., University of Washington, Washington,
USA, velgueta@uw.edu; DENOLLE, M., University of Washington,
Washington, USA, mdenolle@uw.edu; ADERHOLD, K., Earthscope, Alaska,
USA, kasey.aderhold@earthscope.org; ABADI, S., University of Washington,
Washington, USA, abadi@uw.edu

poster 107
Introducing the Alaska Broadband Accessory Deployment
for Geophysical Research (BADGER): A New Seismic
Dataset for Investigating Slow Slip and Subduction Zone
Structure
GOLOS, E., University of Wisconsin-Madison, Wisconsin, USA, golos@
wisc.edu; ALEID, M. H., University of Wisconsin-Madison, Wisconsin, USA,
maleid@wisc.edu; LORD, N., University of Wisconsin-Madison, Wisconsin,
USA, lord@geology.wisc.edu; SOBOL, P., University of WisconsinMadison, Wisconsin, USA, psobol@wisc.edu; DENOLLE, M., University ofWashington, Washington, USA, mdenolle@uw.edu; LIPOVSKY, B., Universityof Washington, Washington, USA, bpl7@uw.edu

Our interactive poster illustrates some features of including real-time DAS
seismic array data into regional and local earthquake monitoring using theincreasingly novel approaches of HL (Human Learning) and NI (NaturalIntelligence). Our goal is to stimulate thought and discussion about possibleroles of DAS within regional networks...and to have some serious FUN! From
July 2023 through January 2024 we interrogated two dark fiber arrays on theseafloor of southern Cook Inlet, Alaska producing time series of strain at seismic frequencies (i.e., seismograms). The interrogator is located in Homer on
the Kenai Peninsula and the fibers cover about 170 linear km of seafloor in
two fiber spans. The arrays record earthquake ground motions, a variety ofambient signals (“noise”), and vigorous energy emanating from movement in
the seawater column. The channel and gauge lengths were 9.57m and 23.9m,
respectively. The sampling frequency of earthquake data shown is 25 sps.
GAME SETUP: Virtual gathers of the >17,000 strain seismograms for 10
earthquakes are presented surrounding a map showing epicenters of 10 earthquakes (origin details from the Alaska Earthquake Information Center) eachproducing one of the displayed seismogram gathers. GAME ACTION: The
player fills out and returns a “contest card”, attempting to match each epicenterwith its corresponding and correct data image. The viewer may ask the presenters/authors questions about the array(s), the interrogator, the fiber and its
emplacement, details about acquisition, processing and the individual earthquake source parameters. However, questions about which earthquake source
corresponds (or not) to which display figure are “out of bounds” SCORING:
Each correct answer is worth 2 points; each incorrect answer is worth 1 point(there is value in thinking through the issues!); each null answer earns nopoints. WINNING and PRIZES: The contestant with the highest numericalscore wins and receives a fabulous prize (yet to be determined—don’t get too
excited). In the event of a tie, a random drawing (or largest bribe) will determine the unique winner.
poster 106
Searching for Microseismic Precursors to the July 2020 Mw
7.8 Simeonof, Alaska Earthquake in a Machine-Learning
Enhanced Catalog
FRIEDMAN-ALVAREZ, C., Cornell University, New York, USA, cdf48@
cornell.edu; BARCHECK, G., Cornell University, New York, USA, grace.
barcheck@cornell.edu; NOLAN, S., Cornell University, New York, USA,
sn664@cornell.edu; ABERS, G. A., Cornell University, New York, USA,abers@cornell.edu
Examining patterns of small earthquakes within subduction zones has thepotential to provide insights into the physical processes that control the initiation of great (magnitude M > 7) megathrust earthquakes. The use of machinelearning has enhanced our ability to detect these small events. This study
explores offshore seismic activity in the months leading up to the 22 July
2020 Mw 7.8 Simeonof earthquake in the Alaska-Aleutian Subduction Zone(AASZ) by using a locally-trained machine learning picking model to detectand catalog small seismicity. Detecting small earthquakes in subduction zones
presents a challenge due to their offshore location, where land-based seismic
networks have low sensitivity. Fortunately, recent advances in machine learning-driven detection methods enable the creation of more-complete seismic
catalogs compared with traditional methods, even for offshore seismicity. We
use an EQTransformer picking model trained on 6,764 earthquakes (~123,000
waveforms) recorded on land by the Alaska Amphibious Community Seismic
Experiment to construct an earthquake catalog spanning October 2019 toJuly 2020. Using match filter, we will further expand the catalog, lowering
the magnitude of completeness. Looking forward, this catalog, along with an

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The Cook Inlet region of the Alaska-Aleutian subduction zone spans two areasof recurrent Slow Slip Events (SSEs). The northern zone, coincident with subduction of the Yakutat terrane, has been associated with seismic tremor, while
the southern SSE zone has not. Both tremor and slow slip have been linked tophysical properties of the subducting plate, including crustal fluid content andvariations in lithology and/or metamorphic facies. Seismic observations are
key to understanding how these properties vary spatially, and how they influence slip rate and seismicity style. Thus far, the northern Cook Inlet SSE zone
has been more heavily instrumented. Therefore, we have deployed the Alaska
Broadband Accessory Deployment for GEophysical Research (BADGER)
experiment to enhance data coverage above the southern SSE zone. Eleven
broadband seismometers were installed with dense (10-20 km) spacing on thewestern Kenai Peninsula in November 2022 for a planned two-year deployment. This campaign emphasized inclusive fieldwork practices by choosing
accessible sites and involving community members and K-12 schools.
Scattered-wave imaging, including receiver functions and P wave coda
autocorrelations, constrains seismic wavespeed contrasts across the subduction interface and the subducting plate Moho. Wavespeed can then be linked
to variations in fluid content, lithology, and anisotropy of the subduction
zone. Here we present synthetic tests demonstrating the ability of these imaging methods to distinguish between end-member models of fluid saturation
conditions and metamorphic facies. Subsequently, we present preliminary
results for teleseismic Ps receiver functions and P wave autocorrelations using
the first year of Alaska BADGER data. High noise levels due to the Cook Inlet,
basin reverberations, and near-surface natural and anthropogenic sources,
present challenges. A concurrent Distributed Acoustic Sensing (DAS) experiment on fiber optic cables beneath the Cook Inlet provides exciting opportunities for augmenting the land-based dataset, and for exploring bridges
between DAS and broadband seismic experiments.
poster 108
Mapping the Alaskan Lithosphere Based Upon Joint
Full-Waveform Inversion of Ambient Noise and Local
Earthquake Data
LIU, T., University of Toronto, Toronto, Canada, tianshi.liu@mail.utoronto.
ca; WANG, K., University of Science and Technology of China, Hefei, China,
wangk@ustc.edu.cn; TAPE, C., University of Alaska Fairbanks, Alaska, USA,
ctape@alaska.edu; HE, B., University of Texas at Dallas, Texas, USA, binhebj@
gmail.com; YANG, Y., Southern University of Science and Technology,
Shenzhen, China, yangyj@sustech.edu.cn; TONG, P., Nanyang Technological
University, Singapore, Singapore, tongping@ntu.edu.sg; LIU, Q., University ofToronto, Toronto, Canada, qinya.liu@utoronto.ca
Alaska is one of the most tectonically active regions in North America, withunique and complex geologic structures shaped by multiple episodes of tectonic processes in the geologic history. We aim to construct a high-resolution
shear-velocity model of the entire Alaskan lithosphere to better understandthe tectonic evolution of this region.
We use high-quality broadband seismic data, bolstered by the USArray
deployment in Alaska, to image the shear velocity of the crust and uppermost
mantle. To resolve both shallow and deep structures in the lithosphere, we
jointly use ambient noise data and local earthquake data to perform full-waveform seismic inversion. For ambient noise data, continuous seismic records
are collected and processed to extract the three-component empirical Green’s
functions (EGFs) between station pairs, and frequency-dependent travel-timeshifts are measured between the EGFs and the simulated Green’s functions.
For local earthquake data, instead of directly using the absolute travel-timeshifts, we measure the difference of the frequency-dependent travel-time

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shifts between station pairs, known as double difference (Yuan et al. 2016), toenhance receiver-side resolution and mitigate the effect of inaccurate event
centroid times. The waveforms are filtered at a period band of 12-50s forambient noise data, and 25-120s for local earthquake data, for measurements,
which are then inverted using the adjoint tomography method to obtain the
structural model. The forward and adjoint simulations are carried out using
the SPECFEM3D_Cartesian package on a mesh customized to the dimensionof the study region. The dynamic mini-batch technique (van Herwaarden etal. 2020) is used to accelerate the inversion process.
We present our model from the surface down to 150km depth, revealing
the variation of crustal thickness in this region, magmatic activities and a segmented subducted slab in Southern Alaska. At broad scale, the tomographic
image shows that the Alaskan lithosphere can be divided into three blocks,
each with a distinct tectonic feature.
poster 109
Insights Into Inherited Crustal Features and Southern
Alaska Tectonic History From Sp Receiver Functions andSeismicity
MANN, M., Brown University, Rhode Island, USA, michael_mann@brown.
edu; FISCHER, K. M., Brown University, Rhode Island, USA, karen_fischer@brown.edu; BENOWITZ, J. A., University of Colorado Boulder, Colorado,
USA, jeffapplebenowitz@gmail.com; WECH, A., U.S. Geological Survey,
Alaska, USA, awech@usgs.gov
The deformation history of the crustal blocks across southern Alaska and geometric history of the bounding faults reflect both inherited features and subsequent convergent margin events. Multiple dense (<20-km spacing) arrays ofbroadband seismometers across southern Alaska have previously allowed for
imaging of crustal structure across the region using various seismic imaging
methods. Here, we employ S-to-P receiver functions to investigate the crustal
structure of southern Alaska for signals of dynamic tectonic activity. The subduction zone plate interface and subducting slab Moho are imaged dippingat shallow (<60-km) depths across the southernmost part of the subduction
zone, in agreement with previous P-to-S receiver function imaging. Alongtwo different transects, an inland-dipping (~15°) boundary is imaged intersecting the trace of the Border Ranges Fault at the surface. This feature may
represent an unrotated paleo-subduction (Mesozoic) interface. This observation is combined with previous seismic imaging along both the Border Ranges
Fault and the next seaward terrane-bounding fault—the Contact Fault—to
examine along-strike gradients in the dip of these structures and the relationship between their variable rotation and the history of convergent tectonics along the margin. Along with large (>10-km) crustal thickness offsets
imaged across both the Denali Fault system and the Eureka Creek Fault, thesefeatures provide a test of previous hypotheses for subduction polarity in theregion. Additionally, a sharp positive velocity gradient with increasing depth
is imaged at ~25-km beneath the Copper River Basin, which is most easily
explained as a shallow Moho and may be related to the generation of a new
Wrangell Volcanic Field volcano, resulting from the underlying tear in the
subducting slab. New tremor and low-frequency earthquake locations acrossthe Copper River Basin region contrast with these seismic imaging results andraise questions about the structure and dynamics surrounding the tear in the
subducting Yakutat slab.
poster 110
Examining the Distribution of Earthquakes Within the
Alaska-Aleutian Subduction Zone Using Events Detectedby the Alaska Amphibious Community Seismic Experiment
NOLAN, S., Cornell University, New York, USA, sn664@cornell.edu; ABERS,
G. A., Cornell University, New York, USA, abers@cornell.edu; BARCHECK,G., Cornell University, New York, USA, grace.barcheck@cornell.edu;
FRIEDMAN-ALVAREZ, C., Cornell University, New York, USA, cdf48@
cornell.edu; ROECKER, S. W., Rensselaer Polytechnic Institute, New York,USA, roecks@rpi.edu
Small earthquakes in subduction zones indicate where deformation is taking
place and can help us understand why regions exhibit differences in plate coupling and rupture behavior; however, knowledge of precise earthquake locations relative to large-scale structure is critical for interpretations. Between
May 2018 and September 2019, the Alaska Amphibious Community Seismic
Experiment (AACSE) deployed 30 land stations and 75 ocean-bottom seismometers (OBS) within the Alaska-Aleutian Subduction Zone (AASZ). The
AACSE array in combination with the nearby Earthscope Transportable
Array and permanent stations led to the detection of over 7,200 earthquakes.
These events were located using the same parameters the Alaska Earthquake
Center routinely uses for events detected on their permanent array of land

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stations. The routine catalog placed many events in the general vicinity of
the interplate thrust zone, indicating activity on that fault, but large depth
uncertainties allow for other interpretations. In particular, many of theseearthquakes may be within the downgoing plate as has been observed farther east in the 1964 rupture zone. Inspection of travel times to OBSs directly
above earthquakes confirms that the apparent thrust-zone earthquakes lie
well below the plate interface, showing deformation within the downgoingplate. An additional 15,000 events have been detected within the AACSE
dataset using EQTransformer trained on the AACSE land data. To better
understand the distribution of earthquakes within the AASZ, we conducteda joint velocity-hypocenter inversion to relocate all the events detected by the
AACSE array. A 3D velocity model and station corrections are used in the
inversion to account for the complex sedimentary structure beneath the OBSs.
This catalog in combination with one being developed between the end of
AACSE in October 2019 and the July 22, 2020 Mw 7.8 Simeonof earthquake(see Friedman-Alvarez et al., this session) will help improve our understanding of how the distribution of earthquakes relates to subduction zone structure and seismic cycles.
poster 111
Searching for Tectonic Tremor Along the Lower Cook Inlet
Portion of the Alaska-Aleutian Subduction ZoneOCHOA, E., University of Wisconsin–Madison, Wisconsin, USA, eochoa3@
wisc.edu; GOLOS, E. M., University of Wisconsin–Madison, Wisconsin, USA,golos@wisc.edu
The origin of tectonic tremor along the eastern Alaska-Aleutian subduction
zone remains poorly understood. Tremor has been detected along the subduction interface in the Upper Cook Inlet (UCI) vicinity, where the inferred
Yakutat microplate is undergoing subduction. This tremor is approximately
coincident with slow slip events (SSEs). However, tectonic tremor has notbeen observed in the Lower Cook Inlet (LCI) during SSEs through 2012.
We investigate whether the absence of tremor is intrinsic to SSEs in the LCI
during more recent events using automatic detection. Here we present preliminary results from this effort, focusing on a likely SSE in the LCI after the2016 Old Iliamna earthquake. We selected stations from the Southern Alaska
Lithosphere and Mantle Observation Network (ZE), Alaska Regional Network(AK), and the USArray Transportable Array (TA) within and near the Cook
Inlet that were operating during the SSE. Several months of continuous data
were analyzed to identify and locate any instances of tremor, using the automated location tool Enveloc. We filtered seismic waveforms, computed envelopes, and determined event locations through a 3D grid search that optimized cross-correlations of envelopes between stations. If tremor is absent in
the LCI during the 2016 SSE, this would suggest that there is a fundamental
difference between how slow slip proceeds in the LCI vs. the UCI, which may
be related to physical properties within the subduction zone. Conversely, thepresence of tremor would provide a new seismic observation that can be used
to understand the structure of and interactions between the overriding andsubducting plates in this region. This investigation will help us understandhow seismicity varies temporally and spatially along the Alaska-Aleutian subduction zone, which will contribute to understanding slow slip events, tremor,and megathrust hazards globally.
poster 112
Probabilistic Teleseismic Tomography of the Alaskan
Mantle With Corrections for Distant Structure
OKKONEN, N., Wayne State University, Michigan, USA, gw4488@wayne.
edu; BURDICK, S., Wayne State University, Michigan, USA, sburdick@wayne.edu
Seismic tomography provides a window into the mantle expressions of thetectonic processes that assembled Alaska. Tomographic models have beenused to constrain the accretion of the Yakutat Terrane, the origin of the Denali
Gap and Wrangell Volcanic Field, and the long-term history of the subduction. In order to estimate the uncertainty in models of the Alaskan mantle andthe geometry of structures within it, we apply regional-scale transdimensional
Bayesian tomography. This approach has several advantages, including accurate amplitudes and measures of uncertainty for velocity variations. Targetingthe mid-mantle beneath Alaska requires the use of teleseismic data, but seismic structure outside the area of study introduces traveltime variance that is
not constrained by a regional-scale model. This results in pessimistic error
bars for velocity and reduces the confidence of conclusions drawn from themodel. It is therefore necessary to find a means of compensating for uncertainty introduced by distant structure.
We present a method for estimating these effects and apply it to the
reduction of error bars on a new model of the Alaskan mantle. We demon-www.srl-online.org•

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strate the effectiveness of the method with data calculated in existing global
models before applying it to USArray, global, and local array data. With thecorrected traveltimes, a new model of the Alaskan mantle with improved
uncertainty estimates will be produced, enabling the testing of hypotheses
about mantle structure.
poster 113
Building a 3D Seismic Velocity Model for the Gulf of Alaska
ONYANGO, E. A., University of Alaska Fairbanks, Alaska, USA, eaonyango@
alaska.edu; TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu; MCPHERSON, A., University of Alaska Fairbanks, Alaska, USA,
ammcpherson@alaska.edu
Offshore regions in tectonically active margins such as Alaska or southern
California exhibit extreme structural complexity and produce a wide rangeof earthquake mechanisms and ground motions. A significant challenge inmodeling ground motion at coastal cities is the lack of offshore stations near
the offshore earthquakes, which poses challenges both for understanding theoffshore earthquakes and for imaging the offshore structure. In south-central
Alaska, the active collision and accretion of Yakutat microplate beneath North
America plate creates an extremely complex regional structure, including
low-velocity accretionary strata. The onshore region has been imaged using
permanent stations installed during the STEEP project and augmented by stations from the EarthScope Transportable Array. Most of these tomographic
models include inherent smoothing that cannot capture the sharp interfacesof the offshore setting. By comparison, the offshore region of the Gulf of
Alaska has been studied only with a sparse array of high-resolution 2D velocity models derived from marine studies conducted between the 1980s and2000s. Here we leverage these 2D models to create experimental 3D velocity
models with known geological features, such as a low-velocity accretionary
wedge and the Yakutat block. We then perform 3D seismic wavefield simulations of earthquakes and virtual sources derived from ambient noise crosscorrelations on our experimental models and three tomographic models fromthe EarthScope IRIS EMC repository. These simulations provide insights into
the complexity of the recorded seismic wavefield, as well as the limitations of
our experimental velocity models. The results of this study should enable us
to build a comprehensive 3D seismic velocity model for the Gulf of Alaska.
poster 114
Investigating Temporal Velocity Changes and Plate
Interface Structure in the Southern Mw 9.2 1964 Great
Alaska Earthquake Rupture Area: A Comparative Study ofAmbient Noise and Earthquake Observations Using a
Dense Node ArrayOSASONA, J. O., University of New Mexico, New Mexico, USA, josasona@unm.edu; WORTHINGTON, L. L., University of New Mexico, New Mexico,USA, lworthington@unm.edu; SCHMANDT, B., University of New Mexico,
New Mexico, USA, bschmandt@unm.edu; BARCHECK, G., Cornell
University, New Mexico, USA, grace.barcheck@cornell.edu; ABERS, G. A.,
Cornell University, New York, USA, abers@cornell.edu; ONYANGO, E.,
University of Alaska Fairbanks, Alaska, USA, eaonyango@alaska.edu; DALY,
K. A., Cornell University, New York, USA, kad278@cornell.edu
We present latest findings beneath the Kodiak array employing seismic ambient noise and p-wave coda autocorrelations. Temporal variations observed innoise records offer the potential for high-precision monitoring of changes inelastic properties. These fluctuations, mainly influenced by long-period ocean
waves, lead to clear shifts in observed seismic velocities. Our analysis indicates
fractional variations in the order of 0.01%. We further demonstrate the influences of external phenomena such as tides, temperature, and precipitation onvelocity changes.
Prior studies utilizing the Kodiak node array with receiver functions
have successfully depicted a clear image of the subducting slab. Our research
conducts a detailed comparative analysis between receiver functions, P-wave
coda, and ambient noise autocorrelations. The autocorrelation methods reveal
unique reflectors not previously observed in receiver functions, establishing it
as a valuable complementary imaging technique.
poster 115
Upper Plate Structure in the Alaska Subduction Zone
Across the 2020 and 2021 Ruptures From 2D Wide-Angle
Seismic Data
BURSTEIN, J., Northern Arizona University, Arizona, USA, josh.burstein.3@
gmail.com; SHILLINGTON, D., Northern Arizona University, Arizona,
USA, donna.shillington@nau.edu; BÉCEL, A., Columbia University, New

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York, USA, annebcl@ldeo.columbia.edu; NEDIMOVIĆ, M. R., Dalhousie
University, Halifax, Canada, mladen@dal.ca
The rigidity and permeability of the overriding continental plate are proposed
to influence megathrust behavior in many subduction zones. Here we use 2D
wide-angle seismic data acquired in 2011 to evaluate upper plate controls on
megathrust behavior across the Semidi and Shumagin sectors of the subduction zone off the Alaska Peninsula. The Semidi segment is strongly locked
and regularly ruptures in great (M>8) megathrust earthquakes, such as theM8.2 in 2021. The Shumagin segment is weakly coupled and appears to hostregular M7.x events, such as the M7.8 in 2020, but has not hosted a M>8 in atleast ~170 years. We present 2D P-wave seismic velocity models across thesesegments obtained from joint reflection and refraction tomographic inversion. Model uncertainty was estimated using a Monte Carlo approach. The
resulting P-wave velocity models display large-scale velocity variations in theoverriding plate that are interpreted to represent the extent of the accretionary
prism and accreted crustal terranes that form the overriding plate: the Prince
William and Chugach terranes. In the Semidi segment, recently recognizedshallow slow slip and afterslip appear to be focused beneath the accretionary
prism and younger, lower velocity Prince William Terrane while rupture in
the 2021 earthquake is concentrated below the higher velocity Chugach terrane. In the Shumagin Gap, slip in the 2020 earthquake straddles the Mohoof the overriding plate. Correlations between the downdip extent and style ofslip events and overriding plate structure suggest an upper plate influence on
megathrust behavior here.
poster 116
Comparison of Crustal Magmatic Storage at AleutianVolcanoes, Gareloi and Kanaga, using Teleseismic Receiver
Function Analysis
WANDASAN, C., University of Hawaii at Manoa, Hawaii, USA, caseywan@
hawaii.edu; JANISZEWSKI, H., University of Hawaii at Manoa, Hawaii, USA,hajanisz@hawaii.edu; WYNN, I. V.., University of Hawaii at Manoa, Hawaii,
USA, iwynn@hawaii.edu; POWER, J. A., U.S. Geological Survey, Alaska,
USA, jpower@usgs.gov; HANEY, M. M., U.S. Geological Survey, Alaska, USA,mhaney@usgs.gov
The Aleutian arc is of considerable interest for geophysical and geologic
investigations due to an abundance of 53 historically active volcanoes withseveral eruptions per year. Characterization of crustal magma storage depths
and establishing ties to laterally variable subduction processes along the arc
have been challenging due to the remote and harsh environment. In 2019,
the Alaska Volcano Observatory conducted upgrades to the seismic network
on Gareloi and Kanaga volcanoes in the Andreanof Islands. These upgrades
increased the number of three-component broadband seismometers at these
volcanoes to five and six, respectively. While these volcanoes are locatedonly ~100 km from each other, there are key differences in observed seismic
activity. Both have seismicity persistent through the upper- to mid-crust, but
Gareloi’s rate of low-frequency seismicity is higher, and it is relatively devoidof volcano-tectonic earthquakes. To better understand what this might imply
for crustal magma storage, we use the receiver function (RF) technique toprovide independent constraints on subsurface magmatic system geometry.
We calculate RFs from teleseismic earthquakes with >M5.5 from 2019 to2023. We use the P-to-S converted phases to constrain depths and velocities
of abrupt boundaries in the crust related to magmatic structure. Both Gareloi
and Kanaga provide good targets for this technique; each station producedon average ~419 RFs with overlapping ray path coverage between stations.
We observe arrivals consistent with features in the mid-to-deep crust (~12–25
km depth) at both volcanoes. In addition, the RFs display complex patterns ofback azimuthal variability that vary across stations at an individual volcano.
We aim to interpret these complex arrivals and compare magma storage at
the two volcanoes through forward modeling constraining crustal velocities.
poster 117
Cook Inlet DAS (CI-DAS): A Year-Long Experiment Studying
Structure, Seismicity, Ocean Waves, and Acoustics Offshore
Southern Alaska
WILLIAMS, E. F., University of Washington, Washington, USA, efwillia@
uw.edu; ABADI, S., University of Washington, Washington, USA, abadi@
uw.edu; ADERHOLD, K., EarthScope Consortium, District of Columbia,
USA, kasey.aderhold@earthscope.org; BODIN, P., University of Washington,
Washington, USA, bodin@uw.edu; DENOLLE, M., University of Washington,
Washington, USA, mdenolle@uw.edu; GAETE ELGUETA, V. A., University ofWashington, Washington, USA, velgueta@uw.edu; GOLOS, E. M., Universityof Wisconsin-Madison, Wisconsin, USA, golos@wisc.edu; LIPOVSKY, B.,
University of Washington, Washington, USA, bpl7@uw.edu; NI, Y., University

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of Washington, Washington, USA, niyiyu@uw.edu; SHI, Q., Universityof Washington, Washington, USA, qibins@uw.edu; WILCOCK, W. S. D.,
University of Washington, Washington, USA, wilcock@uw.edu
Since June 8, 2023, a Sintela Onyx interrogator unit from the University ofWashington FiberLab has recorded continuous DAS data across two 85-km
spans of buried seafloor telecom fiber in Alaska’s Lower Cook Inlet: one spanrunning NW from the city of Homer to Iliamna Bay, near Augustine Volcano,and the other running SW towards Kodiak Island. The DAS was deployedwith a NAS for local data storage and both CPU and GPU servers, enabling
real-time edge computing on the continuous data without file transfer. The
DAS data is augmented by a land-based experiment, the Alaska Broadband
Accessory Deployment for GEophysical Research (Alaska BADGER), which
supplies 3C broadband data from the western Kenai Peninsula. Over the first
6.5 months, the DAS system recorded 2881 regional and local earthquakes,
spanning a wide range of magnitudes (Ml 0.6 to Mww 7.2) and depths (~0 to
196 km). Our open-source edge compute software automates daily extractionof earthquake waveforms for USGS ANSS cataloged events and transfer ofthe event data to a server at the University of Washington. Daily reports arealso automatically generated and pushed to researchers by email, summarizing recording statistics in order to monitor data quality. Work is ongoing to
implement a machine-learning based phase picking and denoising workflow,for eventual use in source studies and travel-time tomography. We are also
cross-correlating both ambient noise and earthquake coda waves to constructmulti-modal Scholte wave dispersion curves along each cable and invert
for the shallow velocity structure of Cook Inlet sediments. Results show an
extremely soft sediment layer with a power-law shear-wave velocity profile
overlying a stiff basement, the depth of which varies systematically across theinlet. We also record the quasi-static deformation of the seafloor from ocean
surface gravity waves. By comparing DAS data with a CDIP wave buoy located~500 m from the cable in 40 m water depth, we demonstrate that it is possible
to measure common wave statistics, including mean wave period and significant wave height, using an empirical transfer function approach.
poster 118
Investigation of Magmatic Systems Through Novel Seismic
Receiver Function Analysis at Alaska-Aleutian Arc
Volcanoes
WYNN, I. V., University of Hawaii at Manoa, Hawaii, USA, iwynn@hawaii.
edu; JANISZEWSKI, H. A., University of Hawaii at Manoa, Hawaii, USA,hajanisz@hawaii.edu; POWER, J. A., U.S. Geological Survey, Hawaii, USA,jpower@usgs.gov; HANEY, M. M., U.S. Geological Survey, Alaska, USA,mhaney@usgs.gov; ROMAN, D., Carnegie Institute for Science, District ofColumbia, USA, droman@carnegiescience.edu
The Alaska-Aleutian Arc exhibits along-arc variability in subduction parameters such as sediment input, subduction obliquity, and regional stress states.
Thus, it provides an opportunity to investigate relationships between subduction parameters and crustal magma storage. In recent years, teleseismic
receiver function (RFs) analysis has been increasingly applied at arc volcanoes to extract mid- to lower-crustal (>10 km) magmatic structure. Recent
expansion of broadband instrumentation in the Alaska-Aleutian arc enables
systematic application and further development of this technique to constrain
variability in arc magma storage. Here, we focus on seven target volcanoes:
Pavlof, Shishaldin, Westdahl, Akutan, Makushin, Okmok, and Cleveland.
We extract back azimuthal patterns in receiver functions using both classical and novel methods, including harmonic decomposition and unsupervisedmachine learning, to assess the presence of complex, heterogenous crustal
structure, and to assess its correlation to the volcanic edifice. Data at Akutan,
Cleveland, and Okmok indicate significant local heterogeneity and a high correlation to the volcanic edifice, likely indicating local magmatic storage. Data
at Westdahl and Pavlof indicate less heterogeneity and a low correlation to
the volcanic edifice, possibly indicating more sensitivity to regional structure.
Finally, data at Makushin and Shishaldin express a moderate correlation to
the edifice, likely a result of a superposition of local magmatic and regional
structures. This work contributes to the further development of a versatile RF
workflow for quantiative comparison of observed crustal structure at arc volcanoes, supporting broader efforts to study arc volcanoes comparatively.
poster 119
Testing Machine Learning Phase Pickers to Develop a
High-Resolution Earthquake Catalog With a 398-Instrument
Nodal Array on Kodiak Island, Alaska
ZHU, H., Cornell University, New York, USA, hz647@cornell.edu; AYLING,
S., Binghamton University, New York, USA, sayling1@binghamton.edu;
WORTHINGTON, L. L., University of New Mexico, New Mexico, USA,

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Portable seismic node instruments enable spatially dense seismic data acquisition for high-resolution imaging and event detection in diverse field areas.
The Kodiak node array, deployed during the Alaska Amphibious Community
Seismic Experiment (AACSE), consisted of 398 nodal seismometers deployed
along roads at ∼200–300 m spacing on northeastern Kodiak Island for fourweeks in May-June 2019. The network overlies the southern asperity of the1964 Mw9.2 Great Alaska earthquake and offers a high-resolution snapshotof thrust zone microseismicity several decades after a large megathrust earthquake. Compared with collocated AACSE broadband stations, the node arrayis far more numerous and closely spaced, providing an opportunity to detect
small events which are critical for understanding fault zone structure andearthquake interactions.
Here we create an earthquake catalog using a machine-learning (ML)
workflow. To test existing ML picking models on the node data, we firstcreate a node waveform dataset by manually picking 2,467 P and 2,392 S
from 23 small and local events using event times from the AACSE catalog.
We then use the dataset to test performance on node waveform of 29 pretrained ML picking models available from Seisbench. The picking models
have variable performance on the node waveform dataset. Overall, PhaseNet
pretrained with INSTANCE, EQTransformer pretrained with INSTANCE,
and EQTransformer retrained with local AACSE data resulted in the highest recalls, smallest median residuals, and reasonable number of picks. We
are using these three models as starting models for transfer learning, and will
apply the re-trained models to continuous node data to detect more regional
and low-magnitude earthquakes compared with the AACSE catalog.

Structure, Seismicity and Dynamics of the Queen
Charlotte-Fairweather Fault System [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Collin Brandl, University of New Mexico(cbrandl@unm.edu); Andrew Gase, Western Washington
University (gasea@wwu.edu); Emily Roland, Western
Washington University (rolande2@wwu.edu); Lindsay
Worthington, University of New Mexico (lworthington@unm.edu)poster 154
Transpression Along the Southern Queen Charlotte Fault:
Underthrusting and Strain Partitioning of the Queen
Charlotte Terrace
BRANDL, C. C., University of New Mexico, New Mexico, USA, cbrandl@
unm.edu; WORTHINGTON, L. L., University of New Mexico, New Mexico,USA, lworthington@unm.edu; ROLAND, E. C., Western Washington
University, Washington, USA, rolande2@wwu.edu; WALTON, M. A. L.,
U.S. Naval Research Laboratory, Mississippi, USA, Maureen.Walton@nrlssc.
navy.mil; NEDIMOVIC, M. R., Dalhousie University, Halifax, Canada,
mladen@dal.ca; ADEDEJI, O., University of New Mexico, New Mexico, USA,
oadedeji@unm.edu; CASTILLO CASTELLANOS, J., Dalhousie University,
Halifax, Canada, js405390@dal.ca; GASE, A., Western Washington University,
Washington, USA, gasea@wwu.edu; PHRAMPUS, B. J., U.S. Naval ResearchLaboratory, Mississippi, USA, Benjamin.Phrampus@nrlssc.navy.mil
The Queen Charlotte Fault (QCF) is a part of the Pacific-North America
plate boundary, one of Earth’s fastest slipping continent-ocean transforms,
and the source of some of Canada’s most significant earthquake hazards. The
2012 M7.8 Haida Gwaii thrust earthquake reinvigorated interest in the QCF,
especially in its southern section. Mechanisms to accommodate the extremely
oblique convergence (from ~5-20) fall into two end members: oceanic
crustal thickening or incipient subduction. Both mechanisms could produce
the Queen Charlotte Terrace, an uplifted complex west of the QCF offshore
Haida Gwaii. The Queen Charlotte Terrace’s crustal structure is crucial forunderstanding the tectonics and seismic hazards of this region, but previous
imaging is limited to shallow penetrating, low-resolution studies that leave
most of the deep crustal structure largely unknown. We use multichannel seismic reflection data acquired with a 15 km-long hydrophone streamer to image
the crustal structure offshore Haida Gwaii, including the Pacific plate, theQueen Charlotte Terrace, the QCF, and the North American continental shelf.
Our images reveal a downwarped and faulted Pacific plate, a Queen Charlottewww.srl-online.org•

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Terrace with sub-parallel ridges underlain by landward dipping thrust faults, a
localized strike-slip fault that coincides with the surface trace of the QCF, andminimally deformed shallow (<2 km) sediments along North American shelf.
Beneath the Queen Charlotte Terrace, continuous underthrusting Pacificplate crust and sediments, topped by a décollement, indicates that recent convergence is accommodated by underthrusting. Thrust faults branch off the
décollement and accrete oceanic sediments, building up the Queen Charlotte
Terrace. Oblique slip on the frontal thrusts implies that strain is partially partitioned along Haida Gwaii, so the QCF may be slipping at less than the fullplate rate. Older oblique strike-slip faults close to the western side of the QCF
suggest that the system may have begun with distributed strike-slip on oceanic
basement-cutting faults before evolving towards its current configuration as acrustal sliver.
poster 155
Local Earthquake Monitoring of the Central Queen
Charlotte Fault With an Ocean-Bottom Seismic Array
GASE, A. C., Western Washington University, Washington, USA, gasea@
wwu.edu; ROLAND, E., Western Washington University, Washington, USA,rolande2@wwu.edu; WORTHINGTON, L. L., University of New Mexico,
New Mexico, USA, lworthington@unm.edu; WALTON, M. A. L., U.S.
Naval Research Laboratory, Mississippi, USA, maureen.walton@nrlssc.navy.
mil; BOSTOCK, M., University of British Columbia, Vancouver, Canada,
bostock@eoas.ubc.ca; NEDIMOVIĆ, M., Dalhousie University, Halifax,
Canada, mladen@dal.ca; OLIVA, S. J., University of Victoria, Victoria,
Canada, soliva@uvic.ca; BRANDL, C. C., University of New Mexico, New
Mexico, USA, cbrandl@unm.edu
High-resolution bathymetry data show that most Holocene slip along the central Queen Charlotte Fault (QCF) has occurred along a narrow fault zone near
the edge of the North American continental shelf. Local seismicity along thecentral QCF is poorly determined because the fault is offshore, and the nearest permanent networked seismic station is >70 km away. Yet, this fault cangenerate large, hazardous earthquakes. From August 2021 to September 2022,
we deployed an array of 28 broadband ocean-bottom seismometers (OBS)
along the central QCF within the rupture zone of the 2013 Craig earthquake.
Winter storms and strong tidal currents generate significant noise that complicates signal detection and characterization on shallowly deployed (<300 m
water depth) seafloor instruments, however, 19 of these instruments recorded
useful data for locating nearby earthquakes. We use these stations and 8 networked seismometers to produce an earthquake catalog, using a deep-neuralnetwork-based picking routine. Our preliminary earthquake catalog (~1300
earthquakes) shows strong seasonal variation in the number of events. Thisseasonality may be due to strong secondary microseism noise from winterstorms (0.1-3 Hz) and fin whale calls (15-30 Hz) that are more frequent in
winter months; both mask portions of the local earthquake spectrum. Most
earthquakes are found <10 km from the Queen Charlotte Fault, confirming that most modern tectonic deformation is in a narrow fault zone thatdips gently to the northeast. Preliminary locations show a degree of vertical clustering and most earthquakes are in the mid- and lower-crust (~5-20km). These results suggest that the central QCF is deforming under simple
shear in comparison to more oblique, pure shear deformation to the south.
Earthquake depth distributions and the degree of localization represented the
new seismicity catalog should provide new insight into the rheological conditions along the ocean-continent plate boundary fault. This dataset is also valuable as a prototype for seismic deployments in shallow-water regions of highwave, winter storm and whale activity.
poster 156
Morphologic Expression of Shallow Volcanics and Ice Sheet
Extent Along the Queen Charlotte Fault, Se Alaska andBritish Columbia
KENNEDY, K., Western Washington University, Washington, USA,ktmaekennedy@gmail.com; ROLAND, E., Western Washington University,
Washington, USA, rolande2@wwu.edu; CLARK, D., Western Washington
University, Washington, USA, dhclark@wwu.edu; WORTHINGTON, L.
L., University of New Mexico, New Mexico, USA, lworthington@unm.edu;
BAICHTAL, J., n/a, Alaska, USA, baichtal557@gmail.com; GREENE, G.,
California State, Washington, USA, greene@mlml.calstate.edu; WALTON, M.
A. L., U.S. Naval Research Laboratory, USA, Maureen.Walton@nrlssc.navy.
milTransform faults represent one of the three types of major plate boundaries on
Earth and are the least associated with volcanism. The Queen Charlotte fault(QCF) is the fastest-slipping ocean-continent transform fault in the world at
50-57 mm/yr (Brothers et al., 2020). It hugs the continental slope along west-

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ern North America for >900 km between southern B.C. and southeast Alaska,
roughly coincident with the location of the western extent of the Cordilleranice sheet (CIS) during multiple Pleistocene glaciations. Young (Quaternary)
volcanic features exist within 25 km on both sides of the fault, but the mechanisms driving this volcanism remain uncertain. Coupled with recent fault
trace mapping and lithospheric-scale geophysical imaging of the plate boundary from the Transform Obliquity along the Queen Charlotte and Earthquake
Study (TOQUES) experiment, we explore how the distribution of volcanism
relative to fault structural variations and former ice sheet limits may provide
new insight into the timing and mechanisms of volcanic activity in southeast
Alaska and British Columbia. Using previously published and legacy seafloor
geophysical data, as well as new multibeam bathymetry and sub-bottom profile data along the QCF, we synthesize diverse evidence for young and active
volcanic features along the QCF. We also reassess seafloor morphology forevidence of the extent of the CIS relative to the location of the plate boundaryand currently active fault trace. Mapping the distribution of volcanic activity
along the QCF will provide a more robust explanation of ‘leaky transform’magmatism at conservative boundaries like transform faults.
poster 157
Crustal Velocity Structure of the 2013 m7.5 Craig
Earthquake Source Region With Joint Ocean-Bottom
Seismometer and Streamer Tomography
MARTIN, E. C., Western Washington University, Washington, USA,marti435@wwu.edu; GASE, A., Western Washington University, Washington,
USA, gasea@wwu.edu; ROLAND, E., Western Washington University,
Washington, USA, rolande2@wwu.edu; GARZA, L., Western Washington
University, Washington, USA, garzal2@wwu.edu; WORTHINGTON, L.
L., University of New Mexico, New Mexico, USA, lworthington@unm.edu;
ADEDEJI, O., University of New Mexico, New Mexico, USA, oadedeji@
unm.edu; WALTON, M. A. L., U.S. Naval Research Laboratory, Mississippi,
USA, maureen.walton@nrlssc.navy.mil; NEDIMOVIC, M. R., Dalhousie
University, Halifax, Canada, mladen@Dal.Ca
Fault damage zones are regions of fractured rock that surround a fault’s main
slip interface. Numerical studies show that the presence and depth exent offault damage zones can influence rupture processes and large, pervasive damage zones may promote complex modes of slip. The Queen Charlotte Fault(QCF), located offshore of southeastern Alaska and western British Columbia,
accommodates ~5 cm/yr of right-lateral strike-slip between the Pacific andNorth American plates along a highly localized fault trace. The QCF has
generated several Mw >7 earthquakes in the last century, the most recent
being the 2013 Mw 7.5 Craig earthquake. To better understand the structure
and material properties of the QCF, including the presence and characteristics of a fault damage zone, we conducted first arrival traveltime tomography with crustal refractions recorded on an ultra-long offset marine seismic
streamer and an array of 16 ocean bottom seismometers in the region of the
Craig earthquake. Our high-resolution P-wave velocity model constrains theupper crustal structure across the QCF revealing multiple velocity anomalies through the upper seismogenic zone in the Craig earthquake region. A
prominent low velocity anomaly lies west of the QCF in the Pacific plate crust,
implying past damage in response to oblique collision and flexure. We see no
indication of a pervasive damage zone surrounding the main slip interface of
the QCF, as is reported in studies at oceanic transform faults that use similar
methods. The highly localized nature and lack of an extensive damage zone at
the QCF may contribute to large earthquakes.
poster 158
Crustal Structure Crossing the Queen Charlotte Fault andTrough in the Region of the Haida Gwaii 2012 m7.9 Thrust
Earthquake Using P-Wave Tomography
ROLAND, E., Western Washington University, Washington, USA, emily.
roland@wwu.edu; WORTHINGTON, L. L., University of New Mexico, New
Mexico, USA, lworthington@unm.edu; GASE, A., Western Washington
University, Washington, USA, gasea@wwu.edu; WALTON, M. A. L., U.S.
Naval Research Laboratory, Mississippi, USA, Maureen.Walton@nrlssc.navy.
mil; NEDIMOVIC, M., Dalhousie University, Halifax, Canada, mladen@dal.ca
In 2012, a M7.8 earthquake ruptured offshore the Haida Gwaii region of
British Columbia and generated a small tsunami. The earthquake occurredin a region of the Pacific-North American (Pac-NA) plate boundary where >5
cm/year of transform plate motion is accommodated on the Queen Charlotte
Fault (QCF). Along the southern portion of the QCF, a bend in the plateboundary leads to ~15° of convergence. This convergence has been hypothesized to be accommodated by either crustal shortening, particularly along
the Queen Charlotte Terrace (QCT), a prism-like structure just offshore Haida

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Gwaii, or through underthrusting, more similar to a subduction zone. In thesummer of 2021, the Transform Obliquity on the Queen Charlotte Fault andEarthquake Study (TOQUES) collected wide-angle seismic refraction data
along the QCF, including a ~75 km-long transect that crosses the plate boundary near the epicenter of the 2012 earthquake. Here we present P-wave tomography from this transect, where 5-km-spaced OBS recorded airgun shots of
the R/V Marcus G. Langseth. Records of high-quality crustal and mantle
refractions exist along the full offset of the line, as well as reflections fromthe Pac Moho and NA Moho or lower crust. Refractions were also recorded
on a station on Moresby Island. Arrival-time tomography shows variation inseismic velocities transitioning from the eastern-dipping Pac lithosphere to
the seismically fast and heterogeneous QCT offshore Haida Gwaii. Velocities
support underthrusting of the Pacific slab beneath the QCT but do not show
evidence of continued underthrusting east of the where the QCF has been
mapped as a through-going, high-angle fault. The shallow structure does show
a clear increase in seismic velocities east of the fault at the seafloor, consistent with Miocene uplift of Haida Gwaii, but does not show fault damage.
Evaluating the relative contributions of underthrusting vs. crustal shortening
is not straightforward, as both the shallow dip of the apparent underthrusting
Pac and fast nappe-like structures in the wedge seem to require some of bothdeformation modes to accommodate convergence.
poster 159
Crustal Architecture Across the Queen Charlotte Fault Zone
North of Haida Gwaii, British Columbia From 2d
Tomography
WALTON, M. A. L., U.S. Naval Research Laboratory, Mississippi, USA,maureen.walton@nrlssc.navy.mil; WORTHINGTON, L. L., Universityof New Mexico, New Mexico, USA, lworthington@unm.edu; ROLAND,
E., Western Washington University, Washington, USA, rolande2@wwu.
edu; GASE, A., Western Washington University, Washington, USA, gasea@
wwu.edu; GARZA, L., Western Washington University, Washington, USA,garzal2@wwu.edu; BRANDL, C. C., University of New Mexico, New Mexico,USA, cbrandl@unm.edu; PHRAMPUS, B. J., U.S. Naval Research Laboratory,
Mississippi, USA, benjamin.phrampus@nrlssc.navy.mil; NEDIMOVIC, M.,
Dalhousie University, Halifax, Canada, mladen@Dal.Ca
The Queen Charlotte fault (QCF) is a 900-km-long dextral strike-slip fault
system separating the Pacific Plate from the North American Plate offshore
western British Columbia and southeastern Alaska, and is one of the fastestslipping strike-slip faults in the world, accommodating ~50-57 mm/yr of slip
along a highly localized fault zone. While dominantly a dextral transform system, there remains considerable debate about mechanism(s) of oblique convergent strain accommodation ranging from incipient subduction to intraplate deformation. Additionally, seismogenesis along the active fault zone may
be partially controlled by material contrasts across the fault, but little is known
about the velocity structure at seismogenic depths. Ocean-bottom seismometer (OBS) seismic refraction data collected as part of the 2021 Transform
Obliquity on the Queen Charlotte fault and Earthquake Study (TOQUES)
project were designed to 1) determine the extent of potential Pacific Plate
underthrusting beneath North America and 2) provide insight into the material contrast across the fault at seismogenic depths. We modeled refracted
arrivals recorded by 25 OBS located along a >200-km-long linear transect
crossing the QCF just north of Haida Gwaii, British Columbia. Our resulting
2D tomographic model images the velocities across the fault zone at up to ~30
km depths, providing the first-ever constraints on the lithospheric architecture in this key tectonic region. We observe high P-wave velocities (> 6 km/s)
at relatively shallow depths (<5 km), and greater velocity heterogeneity on the
North American side of the plate boundary that we attribute to the seismically fast Wrangellia and Alexander accreted terranes. We also find that the
QCF aligns with a relatively sharp contrast in seismic velocity, with the slower
velocities on the Pacific side of the plate boundary at seismogenic depths (~520 km in this area). Lastly, our velocity models do not present strong evidence
for underthrusting north of Haida Gwaii, but we do show seismic reflections
within the North American crust at <30 km depths.
poster 160
New Constraints on Crustal Structure and Fault Zone
Architecture in the m7.8 2012 Haida Gwaii Earthquake
Source Region, Offshore British Columbia
WORTHINGTON, L. L., University of New Mexico, New Mexico, USA,lworthington@unm.edu; BRANDL, C. C., University of New Mexico, New
Mexico, USA, cbrandl@unm.edu; ROLAND, E., Western Washington
University, Washington, USA, rolande2@wwu.edu; WALTON, M. A. L., U.S.
Naval Research Laboratory, Mississippi, USA, maureen.walton@nrlssc.navy.
mil; NEDIMOVIC, M., Dalhousie University, Halifax, Canada, mladen@dal.

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wwu.edu; CASTILLO CASTELLANOS, J., Dalhousie University, Halifax,
Canada, js405390@dal.ca; BOSTOCK, M., University of British Columbia,
Vancouver, Canada, bostock@eoas.ubc.ca; JAYE OLIVA, S., University ofVictoria, Victoria, Canada, soliva@uvic.ca; PHRAMPUS, B. J., U.S. Naval
Research Laboratory, Mississippi, USA, benjamin.phrampus@nrlssc.navy.mil;
ADEDEJI, O., University of New Mexico, New Mexico, USA, oadedeji@unm.
edu
The Queen Charlotte Fault (QCF) transform plate boundary offshore western Canada and southeast Alaska accommodates >50 mm/yr of dextral
strike-slip motion between the Pacific (PAC) and North America (NA) plates.
Transpressional deformation occurs offshore Haida Gwaii in the southern
QCF, generating the Queen Charlotte Terrace fold and thrust belt and a M7.8
thrust type earthquake and tsunami in 2012. Multiple existing hypotheses seek
to explain oblique convergence in the southern QCF, ranging from obliquesubduction to crustal shortening and buckling as leading end members,
but crustal-scale imaging in the region has been limited. In 2021-2022, theTransform Obliquity along the QCF and Earthquake Study (TOQUES) collected active-passive marine seismic data along a ~450 km-long section of the
QCF. Here, we focus on long-offset (15-km streamer) multichannel seismicreflection data collected aboard the R/V Marcus G. Langseth that samples the2012 earthquake epicentral region. We observe extensive crustal-scale normal
faulting on the PAC, with vertical offsets up to 500 m at the oceanic Moho andactive deformation up to the seafloor, through 2-3 km-thick sediments. Thesefeatures indicate significant bending of the PAC plate as it enters the deformation zone and are consistent with normal faulting aftershock sequences fromthe 2012 event. The data show evidence for multiple stages of deformation andreworking within the sediments of the Queen Charlotte Terrace. A narrow
region of thrust faulting occurs west of the main QCF trace within a deformed
sedimentary section up to ~8 km thick. The main QCF is expressed as a nearvertical structure imaged at up to ~4 km depth. East of the QCF, strata within
the upper ~1.5 km are minimally deformed, suggesting that compressional
deformation in the shallow terrace is decoupled from the NA backstop. Bright,
low-frequency reflectors beneath the sediments of the QCT potentially represent deformed oceanic basement. We suggest that PAC-NA convergence isaccommodated via underthrusting and PAC plate deformation with minimal
shallow deformation within the NA plate.

Structure, Seismicity and Dynamics of the Queen
Charlotte-Fairweather Fault System
Oral Session • Wednesday 1 May • 4:30 pm PacificConveners: Collin Brandl, University of New Mexico(cbrandl@unm.edu); Andrew Gase, Western Washington
University (gasea@wwu.edu); Emily Roland, Western
Washington University (rolande2@wwu.edu); Lindsay
Worthington, University of New Mexico (lworthington@unm.edu)Aftershock Regions of Mw > 6.7 Earthquakes on the Queen
Charlotte–Fairweather Plate Boundary, 1929 to 2013
TAPE, C., University of Alaska Fairbanks, Alaska, USA, ctape@alaska.edu;
LOMAX, A., ALomax Scientific, Mouans Sartoux, France, alomax@free.fr
For large, early-instrumental (pre-1960) earthquakes, the spatial region ofaftershocks offers the best approximation for the rupture area of the mainshock. This link, introduced by Fedotov (1965) and Mogi (1968), was applied
by Sykes (1971) to a large set of major earthquakes rupturing the northern
Pacific plate boundary, from the westernmost Aleutians to south-central
Alaska (1965, 1957, 1946, 1964) and along the Queen Charlotte-Fairweather(QCF) strike-slip fault system (1958, 1927, 1949). We recently relocated thehistorical aftershocks and updated the aftershock regions for the AleutianAlaska subduction zone (Tape and Lomax, 2022). Here we focus on the Mw> 6.7 earthquakes rupturing the QCF plate boundary. Using a probabilistic
approach (NonLinLoc), we relocated 150 aftershocks arising from 11 mainshocks spanning from 1929-05-26 Ms 7.0 (northwest of Vancouver Island)in the south to 1979-02-08 Mw 7.4 (St. Elias Mountains) in the north. The
analysis of the QCF aftershocks is much more difficult than the analysis of
Aleutian-Alaska aftershocks because the mainshocks are smaller, resulting
in fewer detectable aftershocks based on globally distributed recording stations. With fewer arrival times and aftershocks, the resulting relocations havewww.srl-online.org•

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higher uncertainties and pose challenges for establishing aftershock regions.
Applying a similar approach to all 11 events (early-instrumental and modern), we establish revised aftershock regions, using the known plate boundary location for guidance. We compare our findings with previously publisheddetailed studies dedicated to one or more of these earthquakes.
Kinematics of the Fairweather-Queen Charlotte Transform
System and Deformation Across the Broad Pacific-North
America Plate Boundary Zone
ELLIOTT, J., Michigan State University, Michigan, USA, ellio372@msu.edu
The Fairweather-Queen Charlotte system is a 1200-km long onshore-offshoretransform fault that stretches from British Columbia to southern Alaska.
While the fault system is a active boundary with 6 M7+ earthquakes over the
past century, major questions remain about how relative motion is accommodated across the region. Land-based geodetic data and offshore geomorphic data derived from high-resolution bathymetry suggest different rates offault motion, which leads to different estimates of how much of the total estimated Pacific-North America motion is taken up by the fault system. Using
Euler pole analyses and a combined geomorphic and geodetic dataset, I willdevelop an improved regional tectonic model that allows a more complete
examination of the fault system and how motion is distributed through theplate boundary zone.
The plate configuration surrounding the Fairweather-Queen Charlottesystem is complex. The Yakutat block, an oceanic plateau that moves to thenorthwest, sits to the west of the Fairweather and the northernmost Queen
Charlotte fault. The Pacific plate is assumed to lie to the west of the central
and southern Queen Charlotte fault. Based on geodetic data and Euler poleanalyses, the Yakutat block and the Pacific move distinctly from each other.
Geodetic data show that the coastal margin inboard of the fault system moves
north relative to North America, implying that the fault system does not takeup all relative motion. Adding geomorphic slip rate estimates to the geodetic
data results in predicted motion rates along the Queen Charlotte fault withsignificantly lower degrees of convergence than previous geodetic models.
These new rates require a Northeast Pacific block, which moves to the northwest at a rate different from either Yakutat or Pacific, to lie to the west of thecentral and southern Queen Charlotte fault. The predicted motion of theNortheast Pacific block is not compatible with right-lateral slip along the Gulf
of Alaska shear zone, implying that additional blocks or internal deformationof the northeast Pacific may be required.
The Making of a Future Accreted Terrane: Plate Tectonics of
the Queen Charlotte Fault System and the Development of
the Queen Charlotte Terrace Adjacent to Haida Gwaii
FURLONG, K. P., Pennsylvania State University, Pennsylvania, USA, kpf1@
psu.edu; ROHR, K. M. M., Geological Survey of Canada, Sidney, Canada,
kristin.rohr@NRCan-RNCan.gc.ca; RIEDEL, M., Geomar, Kiel, Germany,
mriedel@geomar.de
The NE-section of the Pacific (PAC) and North America (NAM) plate boundary is generally envisioned as a large-scale transform fault (akin to the San
Andreas) extending from north of Vancouver Island to eastern Alaska.
However its history and present nature along the translational Queen
Charlotte-Fairweather Fault system is less clear - particularly along the
Haida Gwaii margin. There the extent of underthrusting of the Pacific plate
beneath Haida Gwaii, the role of the Queen Charlotte Terrace (QCT) in theplate kinematics, and the way in which the slight obliquity of relative platemotions (~15°) is accommodated all remain unclear and/or contested. As the
PAC - NAM plate motions have changed over the past 20 Ma, the Haida Gwaii
section of the Queen Charlotte fault (QCF) has become progressively moretranspressive. The result is underthrusting of the Pacific plate beneath western Haida Gwaii, and deformation along the continental margin. Earthquakes
along the plate boundary, uplift of the western margin of Haida Gwaii, patterns of plate-interface coupling, and detailed analyses of seismic imagery
along the margin allow us to propose an evolving, multi-component 3-D
structure to the plate boundary in the vicinity of Haida Gwaii.
This plate boundary evolution has led to the QCT adjacent to Haida
Gwaii. Although often linked to the Pacific plate (e.g. it lies outboard of the
QCF), the QCT is integral to the partitioning of oblique motion between the
PAC and NAM plates. This results in the QCT acting as a terrane that is anindependent crustal block with sedimentary structures that differ from theadjacent Pacific plate along an abrupt deformation zone. The QCT shows evidence (through seismicity) of being at most partially coupled along its baseto the Pacific plate, and is also kinematically independent (across the QCF)
of the adjacent Haida Gwaii. We describe the evolution of this present day
plate boundary structure from a simple translational plate boundary (pre-12

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www.srl-online.orgMa), to its current configuration and assess the amounts and timing of underthrusting, uplift, and internal deformation of the QCT terrane.
Slope Evolution and the Accommodation of Oblique
Convergence From the Central to the Northern Queen
Charlotte Fault
ADEDEJI, O., University of New Mexico, New Mexico, USA, oadedeji@unm.
edu; WORTHINGTON, L. L., University of New Mexico, New Mexico, USA,lworthington@unm.edu; BRANDL, C. C., University of New Mexico, New
Mexico, USA, cbrandl@unm.edu; WALTON, M. A. L., U.S. Naval ResearchLaboratory, Mississippi, USA, maureen.walton@nrlssc.navy.mil; ROLAND,
E., Western Washington University, Washington, USA, rolande2@wwu.edu;
GARZA, L., Western Washington University, Washington, USA, garzal2@
wwu.edu; GASE, A., Western Washington University, Washington, USA,gasea@wwu.edu; NEDIMOVIC, M., Dalhousie University, Halifax, Canada,
mladen@dal.ca
The Queen Charlotte Fault (QCF), the transform boundary between the
Pacific and North American tectonic plates offshore Vancouver and southeastern Alaska, experiences rapid deformation at approximately 55 mm/year.
This makes it one of the fastest-slipping continental-oceanic transform systems globally. Transpressional deformation, which occurs along the fault, iscontrolled by variations in fault strike with respect to plate motion leading
to increasing degrees of convergence along strike from north to south. The
Transform Obliquity on the Queen Charlotte Fault and Earthquake Study(TOQUES) gathered new multichannel seismic reflection data along a ~450km fault section in 2021. This work focuses on the northern segment, near
the site of the 2013 Mw 7.5 Craig, Alaska earthquake. Aftershock sequencessuggest that the main QCF dips eastwards or active fault strands exist within
the North American plate. We present seismic profiles crossing the 2013 epicentral region, examining fault zone architecture, crustal deformation mechanisms, and deep structural relationships. The profiles reveal a series of normal
faults within the Pacific crust, a slightly eastward dipping Pacific basement,
and sediments containing multiple vertical faults at the base of the continental slope. The main QCF trace is located on the continental slope. Mid-slope
basins record several deformation stages and host multiple vertical faults. On
the North American continental shelf, we see glacially truncated, east-dipping
strata and minor seafloor sediment deformation. Our observations suggestthat strike-slip deformation may be distributed across multiple structures.
A Spectral Perspective on Fault Geometry and Strike-Slip
Rupture at Plate-Boundary Scales Along the Queen
Charlotte Fault
MILLER, N., U.S. Geological Survey, Massachusetts, USA, ncmiller@usgs.
gov; BROTHERS, D. S., U.S. Geological Survey, California, USA, dbrothers@
usgs.gov
We compare scalograms of fault geometry and yield stress to M~7+ ruptures
along the Queen Charlotte Fault (QCF). Fault geometry controls stress accumulation and release during earthquakes, implying that sizes, locations, andmagnitude distributions of earthquakes should mirror the sizes, locations,and scaling of geometric irregularities on faults. Along the QCF, O(100)-kmscale irregularities in the scalograms mark the extents of all recorded M~7+
ruptures, suggesting that large-scale irregularities act as barriers to rupture.
Converting the geometry scalograms to yield stress shows that ruptures nucleate where yield stress equals average values and terminate in high yield stressregions (i.e., barriers). At scales shorter than total rupture length, co-seismic
slip is, conversely, highest where yield stress is highest, indicating that longer ruptures release stress accumulated at smaller-scale irregularities. Thisbarrier-asperity model is consistent with other spectral measurements. The
O(100)-km scale marks a break in scaling of irregularity height H to length
L ratios: At ~35 to 55 km scales, QCF geometry follows a self-affine H∝L^ζ
scaling with ζ≈0.6. At scales >90 km, ζ≈0.9. The fractal break separates QCF
rupture sizes: Mw 7.5 to 7.9 events are >90 km long, where ζ≈0.9; Mw 6.8 to
7.0 events are ~35 to 55 km long, where ζ≈0.6. No ~55 to 90-km-long ruptures have been recorded on the QCF. Consistently, the ~55 to 90 km transitional band marks an abrupt increase in irregularity amplitude and high yieldstress variation, features that impede rupture. A scaling break at O(100) km isalso apparent in the magnitude-frequency distribution (MFD) of QCF earthquakes. Many more great (M > 7.5, L > 100 km) earthquakes have occurredthan predicted by Gutenberg-Richter scaling, meaning stress is more readily
accommodated by large rather than small ruptures, consistent with predictions from the scalograms. The similar characteristic scaling in fault geometry and rupture distributions may arise from fundamental scale of strike-slip
faulting, such as seismogenic zone depth.

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Tectonics and Seismicity of Stable Continental Interiors
Oral Session • Friday 3 May • 8:00 am PacificConveners: Oliver Boyd, U.S. Geological Survey, olboyd@
usgs.gov; Jessica Thompson Jobe, U.S. Geological Survey,
jjobe@usgs.gov; William Levandowski, TetraTech, will.
levandowski@tetratech.com; Zhigang Peng, Georgia Instituteof Technology, zpeng@gatech.edu; Anjana K. Shah, U.S.
Geological Survey, ashah@usgs.gov
Seismicity and Seismotectonics of the Basque-Cantabrian
Zone and Adjacent Areas of the Pyrenean-Cantabrian
Mountain Belt: New Data From the Siscan and Misterios
Seismic Networks (2014-2020)
OLIVAR-CASTAÑO, A., University of Potsdam, Berlin, Germany, andres.
olivar-castano@uni-potsdam.de; DÍAZ-GONZÁLEZ, A., University of
Oviedo, Oviedo, Spain, albadiaz@geol.uniovi.es; PULGAR, J. A., Universityof Oviedo, Oviedo, Spain, pulgar@uniovi.es; PEDREIRA, D., University of
Oviedo, Oviedo, Spain, dpedreira@uniovi.es; GONZÁLEZ-CORTINA, J.,
University of Oviedo, Oviedo, Spain, jmgcortina@uniovi.es; GALLASTEGUI,J., University of Oviedo, Oviedo, Spain, jgallastegui@uniovi.es; RUIZ, M.,
GeoSciences Barcelona, Barcelona, Spain, mruiz@geo3bcn.csic.es; DÍAZ, J.,
GeoSciences Barcelona, Barcelona, Spain, jdiaz@geo3bcn.csic.es; GALLART,J., GeoSciences Barcelona, Barcelona, Spain, gallartmuset@gmail.com
The Basque-Cantabrian Zone is located in the Pyrenean-Cantabrian
Mountain belt, in the north of the Iberian Peninsula. Specifically, it comprises
the eastern termination of the Cantabrian Mountain Range and its transition to the Western Pyrenees. The region to the west of the Pyrenees has
traditionally been considered to have low seismic activity, and has therefore
attracted less attention from the seismological community than other areas of
the Iberian Peninsula. For this reason, the coverage of permanent seismic stations is sparse, and the present-day seismicity of the Basque-Cantabrian Zone
remains relatively understudied.
To fill this gap in the knowledge of the seismicity in northern Spain, we
deployed two temporary seismic networks covering the Basque-Cantabrianregion and neighboring areas, including the northernmost part of the Iberian
Chain and the Western Pyrenees, from 2014 to 2020. In total we deployed
more than 50 stations, with an average interstation distance of 30 km. During
the 6 years of the study, we built an earthquake bulletin containing more than
1000 located earthquakes with a completeness magnitude of 1.1 Ml, and computed 42 focal mechanisms in a region where this type of data was very scarce.
We used the most accurately located events to improve the understading of
the seismotectonics of the Basque-Cantabrian Zone, identifying the main
active faults in the area, and offering additional data on the local stress field.
We also employed the large dataset of amplitude picks to compute a new magnitude scale suitable for the Basque-Cantabrian Zone.
The Earthquake Swarms of Eastern Maine and Nearby New
Brunswick Since 2006
EBEL, J. E., Boston College, Massachusetts, USA, ebel@bc.edu
In the past couple decades, several swarms of small earthquakes have been
detected in eastern Maine and nearby New Brunswick. The swarms were near
Bar Harbor, Maine in 2006-2007, at Searport, Maine in 2011, at McAdam,
New Brunswick in 2018, near Jonesboro, Maine in August 2022, near Brewer
Maine in December 2022 and January 2023, and near Millinocket, Maine in
December 2022 and January 2023. Each swarm has consisted of several to afew dozen events, with the largest event in any of the swarms being an MLg
4.2 earthquake near Bar Harbor in 2006. Relative locations of the events inthe swarms suggest that they are only one or a couple kilometers in spatial
extent and that they tend to follow known or inferred local geologic structures. The focal mechanisms of the largest events of the swarms indicate thatthe earthquakes in these swarms are responding to the regional approximate
E-W maximum compressive field seen throughout this region, and the events
tend to have thrust focal mechanisms. The swarms all have focal depths ofa few kilometers or less. The swarms do not associate with any single structure or structural trend, although most have occurred just east of or on the
Norumbega Fault, an ancient, major strike-slip fault that runs from eastern
New Brunswick southwest to near the southern tip of Maine. The causes ofthese swarms are unclear, as is their significance for elucidating the earthquake hazard of the region. However, the swarms do indicate which faults in
Maine and New Brunswick might be seismically active in the modern stressfield.

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Seismological Research Letters

Seismotectonic Studies of the Nubia Fault System,
Southwest Aswan Area, Egypt
ELSAYED MOHAMED, M. M., National Research Institute of Astronomy andGeophysics, Cairo, Egypt, sayed.mohamed9870@nriag.sci.eg; ABDALLAH
HAMIMI, Z., Benha University, Cairo, Egypt, zakariahamimi4@gmail.com;
MOHAMED MOUSSA, H., National Research Institute of Astronomy andGeophysics, Cairo, Egypt, hesham@nriag.sci.eg
Numerous active shear systems can easily be detected in the Egyptian Easternand Western-Deserts (ED & WD). Among these systems is the Nubia Fault
System (NFS) which is an eye-catching structural feature in the extreme
southern part of the WD. The NFS is typified by two main trends; E-W(Kalabsha- and Seiyal- Faults; KFZ and SFZ) and N-S (El-Barqa-, Kurkur-,
Khor El-Ramla-, Ghazala-, and Abdu Dirwa- Faults). Propagation of shearing along both trends resulted in the formation of different styles of shear
zone-related folding reflecting transtensional regime. The present work is an
integrated field/structural and seismological approach aiming to decipher the
recent activity and seismic hazard potentiality of the NFS. Several lines ofevidence indicate recent activity including topographic expression and intensive degree of shearing, and severe fragmentation and pulverization. Detailed
investigation of the KFZ and the SFZ proves that both structural elements aretranstensional and frequently segmented. The geometry and kinematic history of the KFZ and the SFZ reveal seismogenic events with a strong movement as deduced from surface rupturing, and remarkable fault breccia andgouge which are good signs for ongoing and recent seismic activity. Notable
activity along the NFS led to low (to moderate) earthquakes with magnitude
up to 5.6 ML. The full moment tensor inversion, which was decomposed
it into three parts Isotropic (ISO), Double Couple (DC) and CompensatedLinear Vector Dipole (CLVD), offers further information about the NFS. The
obtained complete MT for the whole district is characterized by non-DC components which have been represented by ISO and CLVD with average valuesof 22.2 % and 34.4 %, respectively, and DC components with average value of
39.1%. The average value of the non-DC components of the majority of theselected earthquakes is larger than the DC component. Such results indicatethat the seismicity is probably triggered rather than being a pure tectogenic.
Focal Mechanism Analysis of the 2019 Mw 4.9 Wang Nuea
Earthquake and Its Implication for Seismotectonics
CHANSOM, C., Chulalongkorn University, Bangkok, Thailand, chanista.
gg@gmail.com; JITMAHANTAKUL, S., Chulalongkorn University, Bangkok,
Thailand, sukonmeth.j@chula.ac.th; SHENGJI, W., Nanyang Technological
University, Singapore, Singapore, shjwei@ntu.edu.sg
On February 20th, 2019, an Mw 4.9 earthquake occurred in Wang Nuea,
Lampang Province, northern Thailand. The epicenter was located in a tectonically active region with the potential for strike-slip and normal faulting earthquake sources. However, the responsible fault is not well understood because
there are no focal mechanism solutions from available international or local
seismological agencies, such as USGS, GCMT, and TMD for this event, either
the high-resolution seismicity. The objective of the research was to provide a
better understanding of the earthquake mechanism and seismotectonics using
a combination of accurate seismicity, focal mechanisms, and geomorphic
structures. We applied the generalized Cut-and-Paste (CAP) focal mechanism
inversion method to obtain the earthquake focal mechanism and centroid
depth at relatively high-frequency ranges (0.02–0.2 Hz for Pnl and 0.03–0.2
Hz for surface waves). The CAP inversion results show a robust strike-slip
solution for the mainshock, suggesting the NNW-SSE-oriented fault with avertical dip and a depth of 7 km, which is consistent with the near N-S distributed aftershocks. This result is also roughly consistent with the geologically mapped strike of the Wang Nuea Fault and reveals seismic activity along
the fault. The seismicity and focal mechanisms of the earthquakes, as well as
the geomorphic lineament, explain the characteristics of the fault in the N–S
direction. We suggest that similar waveform inversion could be generalized
for focal mechanism inversion in Thailand routinely.
Middle Crustal Earthquakes and Neotectonics in theWestern East Sea (Sea of Japan)
HONG, T., Yonsei University, Seoul, South Korea, tkhong@yonsei.ac.kr;
PARK, S., Yonsei University, Seoul, South Korea, seongjunpark@yonsei.ac.kr;
LEE, J., Yonsei University, Seoul, South Korea, aqualung@yonsei.ac.kr; LEE,
J., Yonsei University, Seoul, South Korea, jeongin6422@yonsei.ac.kr; KIM, B.,
Yonsei University, Seoul, South Korea, kbw8280@yonsei.ac.kr
The East Sea (Sea of Japan) is located in the eastern margin of the Eurasianplate of stable intraplate plate regime. The western East Sea is seismically
active. The seismicity in the western East Sea occur around the paleo riftingwww.srl-online.org•

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structures where seismic and geophysical properties apparently change. The
nature of seismicity in the western East Sea is important information for mitigation of seismic hazards. Both reverse faulting and strike slip earthquakes
occur in the region. The maximum focal depth generally increases with distance from the coast, reaching the peak maximum focal depths of ~32 km in
the continental slope of the western East Sea. Middle crustal earthquakes continue around the paleo-rifting structures that may extend to the lower crustand Moho. Clustered episodic earthquakes occur in four local offshore areas
including the stress-induced areas by the 2016 ML 5.8 Gyeongju earthquakeand 2017 ML 5.4 Pohang earthquake. The spatiotemporal clustering of earthquakes suggests episodic stress release at localized structures. The seismicity properties suggest progressive thrust motions across the crust around thepaleo-rifting structure in the western East Sea.
Seismicity and Structure of SW Australia via the SWAN andWestern Australia Seismic Networks
PICKLE, R., Australian National University, Canberra, Australia, robert.
pickle@anu.edu.au; ZHANG, P., Australian National University, Canberra,
Australia, ping.zhang@anu.edu.au; MOUSAVI, S., Australian National
University, Canberra, Australia, sima.mousavi@anu.edu.au; YUAN, H.,
Department of Energy, Mines, Industry Regulation and Safety, Perth,
Australia, Huaiyu.YUAN@dmirs.wa.gov.au; MURDIE, R., Departmentof Energy, Mines, Industry Regulation and Safety, Perth, Australia, Ruth.
MURDIE@dmirs.wa.gov.au; MILLER, M. S., Australian National University,
Canberra, Australia, meghan.miller@anu.edu.au
The South-West region of Australia is the country’s most seismically active
zone and has experienced ~20 M5+ events in the last 50 years, including themost damaging event in Australian history (1968 M6.8 Meckering). It is also
privy to numerous seismic swarms, including a year-long event which began
in early 2022, captured by the new SWAN network (2P, 2020-2023). As SW
Australia is far from any plate boundary, there is no obvious explanation for
the frequent shallow intra-continental earthquakes here which mostly occur
within the Archean-aged Yilgarn Craton. This area has recently been examined by the 27 broadband stations (SWAN) as well as 130 stations across theambitious new WA-Array rolling network (XO, 2022-2032) which has a linear
array geometry with 40 km station spacing. Between 2020-2023 over 10,000
earthquakes have been located using a Machine Learning phase picker (e.g.
EQTransformer, Mousavi et al. 2020), event associator (e.g. REAL, Zhang etal. 2019) and locator (e.g. NonLinLoc, Lomax et al. 2000). These events havebeen used to derive regional body wave velocity models, centroid moment
tensors, and estimated Greens Functions between each station pair have also
been used to create an ambient noise velocity model. Both models outline the
Yilgarn Craton as well as the thick sedimentary deposits of the Perth Basin,west of the Darling Fault. We also imaged a distinct high-velocity fragmentin the lower crust along the western margin of Yilgarn Craton, east of the
Darling Fault, which may reflect the terrane accretion tectonics. At the time ofwriting, our results are being integrated with other geophysical and geologicalinformation, with the ultimate goal of unveiling the history of Yilgarn and theunusual intra-plate seismicity that has been observed across the oldest craton
on Earth.
Recurrent Large Intraplate Earthquakes on the Jindabyne
Thrust, Southeast Highlands, Australia
GRIFFIN, J. D., Geoscience Australia, Cook, Australia, jonathan.griffin@
ga.gov.au; CLARK, D. J., Geoscience Australia, Canberra, Australia, dan.
clark@ga.gov.au; KEMP, J., Griffith University, Brisbane, Australia, j.kemp@
griffith.edu.au; STIRLING, M. W., University of Otago, Dunedin, New
Zealand, mark.stirling@otago.ac.nz; KING, T., Geoscience Australia,
Canberra, Australia, tamarah.king@ga.gov.au; KULESZA, O., Universityof Melbourne, Melbourne, Australia, okulesza@student.unimelb.edu.au;
LA GRECA, J., University of Melbourne, Melbourne, Australia, j.lagreca@
unimelb.edu.au; SHARMA, A., University of Melbourne, Melbourne,
Australia, ambicas@student.unimelb.edu.au; QUIGLEY, M. C., University of
Melbourne, Melbourne, Australia, mark.quigley@unimelb.edu.au; NINIS, D.,
Seismology Research Centre, Melbourne, Australia, dee.ninis@src.com.au;
PIETSCH, T., Griffith University, Brisbane, Australia, t.pietsch@griffith.edu.
au
The recurrence characteristics of large intraplate earthquakes are poorly
understood, leading to large uncertainties in seismic hazard assessments,
particularly at the low annual probabilities of exceedance important to thedesign and maintenance of critical infrastructure. The southeast highlands ofAustralia have the greatest elevation and topographic relief of anywhere in thecontinent, relatively high seismicity rates, and a number of faults showing geomorphic evidence for neotectonic activity. The region also hosts major dam

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and hydroelectric infrastructure critical to Australia’s water and energy security. Despite this, no paleoseismic studies have previously been undertaken tocharacterise the earthquake potential of faults in the region.
We excavated four trenches on the more than 100 km long Jindabyne
Thrust fault, and one trench on the 24 km long Hill Top Fault, which occurs
in the hanging wall of the Jindabyne Thrust and is truncated by the thrust
at its southern extent. Evidence for multiple large earthquakes was found on
both faults, showing reverse displacement on the Jindabyne Thrust and strikeslip displacement on the Hill Top Fault. Trenches on the Jindabyne Thrust
exposed a thick clay gouge zone within bedrock underlying the faulted alluvial sediments, and single-event displacements are on the order of 1.5–2.0 m.
Optically stimulated luminescence dating of displaced alluvial and colluvial
sediments is being used to constrain the timing of these earthquakes. The
results demonstrate persistent recurrence of large surface-rupturing earthquakes on the Jindabyne Thrust over the Late Quaternary, implying a neotectonic component to range uplift in the south-eastern highlands, and an extant
seismic hazard.
Seismic Evidence of Crustal Modifications Below the North
American Midcontinent
YANG, X., Purdue University, Indiana, USA, xtyang@purdue.edu; STEVENSGODDARD, A., Indiana University, Indiana, USA, alsg@iu.edu; LIU, L.,
University of Illinois Urbana-Champaign, Illinois, USA, ljliu@illinois.edu;
RIDGWAY, K. D., Purdue University, Indiana, USA, ridge@purdue.edu;
SCHMITT, D. R., Purdue University, Indiana, USA, schmitt@purdue.edu; LI,
H., Purdue University, Indiana, USA, li4897@purdue.edu
Despite being relatively stable, the interiors of global cratons preserve clear
evidence of modification on geologic timescales. The North American craton
is the locality of a series of rifts, basins, arches, and domes, varying in size andorientation. Geologic evidence suggests that these features formed throughout the Paleozoic or earlier with limited subsequent deformation. However,
the mechanism(s) that drove the uplift and subsidence of these intracratonic
features is poorly understood. Linking these upper crustal features with deep
crustal and upper mantle processes is an important step in understanding theevolution of “stable” cratons including the timing, rate, and style of cratonic
modification. Here we present new results using a 3-D shear-wave velocity
model from full-wave ambient noise tomography to identify compositionaland structural modifications in the crust across the North American midcontinent. Our results show a heterogeneous crustal structure below major surface tectonic features, suggesting strong crustal modifications related to theformation and evolution of these surface deformations. For example, the late
Mesoproterozoic Midcontinent Rift is underlain by a confined low-velocity
zone along strike in the upper crust, broadening at greater depths. There isa crustal low-velocity layer across most of the study area. This low-velocity
layer is shallower below basins than other regions, varying from 15-20 km
deep below the Illinois and Michigan Basins (Neoproterozoic - Paleozoic) to25-30 km in other regions. The doming of this crustal low-velocity layer below
the basins may be the consequence of crustal uplift before the basin subsidence. We will discuss the implications of the velocity structure for the origin
and evolution of intracratonic deformation, combining other geological andgeophysical constraints.
Crustal Thickness and Radial Anisotropy Below the North
American Midcontinent
LI, H., Purdue University, Indiana, USA, li4897@purdue.edu; YANG, X.,
Purdue University, Indiana, USA, xtyang@purdue.edu; HERR, B., Purdue
University, Indiana, USA, herrb@purdue.edu; LIU, L., University of Illinois
Urbana-Champaign, Illinois, USA, ljliu@illinois.edu; STEVENS GODDARD,
A., Indiana University, Indiana, USA, alsg@iu.edu; PAVLIS, G. L., Indiana
University, Indiana, USA, pavlis@indiana.edu; SCHMITT, D., Purdue
University, Indiana, USA, schmitt@purdue.edu
The relative stability and longevity of cratons preserve the imprints of major
tectonic events on geologic timescales. Seismic observations provide information on compositional and structural variations of the cratonic lithosphere,
shedding light on the dynamic evolution of craton interiors. The North
American craton is an amalgamation of tectonic structures (rifts, basins,
domes, and arches) formed in the Paleozoic and earlier. Here we present
results from averaging eight crustal thickness models covering the North
American midcontinent (the number of models at each grid is variable) andcompare them with other geophysical observations, such as lithosphere thickness and shear-wave velocity model. Our crustal thickness results reveal heterogeneous crustal thickness across tectonic units, with relatively deep (about
45-55 km) Moho beneath the Williston, Illinois, and Appalachian Foreland
Basins and shallower (about 35-42 km) Moho below the Forest City Basin

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and the central and northwestern Michigan Basin. In addition, we will builda radial anisotropy model using ambient noise cross-correlation to investigate
the crustal modification associated with different structural features. We will
examine the relationship among the variation of crustal, lithospheric thickness, seismic isotropic, and anisotropic velocity structures to understand thetectonic evolution of the North American midcontinent. Our study, joining
with geological and geochronological constraints, will contribute to understanding the connection between regional tectonic events (relative timing andscales) and local heterogeneities and, in general, the style and scale of the tectonic evolution of cratonic interiors.
Lithospheric Layering and Seismic Activity of the British
Isles
LEVIN, V., University of Memphis, Tennessee, USA, vadim.levin@memphis.
edu; LEBEDEV, S., University of Cambridge, Cambridge, United Kingdom,sl2072@cam.ac.uk
Recent progress in imaging of the upper mantle made it possible to show aclose correlation of seismic activity of the British Isles with the properties of
their lithosphere. Specifically, sparse seismicity of Ireland appears to be well
explained by the relatively thicker and colder, hence stronger, lithospherebeneath it, while a region of relatively thinner and warmer lithosphere spanning Great Britain hosts vast majority of all recorded earthquakes.
The upper mantle imaging study linking seismicity and lithosphericproperties of the British Isles relies on surface wave data that tend to smooth
abrupt lateral changes in properties. Methods based on mode-converted bodywaves (aka receiver functions) offer excellent lateral resolution and can detect
fine vertical layering in the upper mantle, however their use is hampered by an
overprint of the intra-crustal multiply-reflected waves.
Long-duration continuous broad-band seismological observations provide data necessary to resolve directional and incidence-angle variations inconverted waves, facilitating discrimination of multiple and direct P-S waves
and detection of conversions from vertical gradients in seismic anisotropy.
We recently showed that constraints on the upper mantle layering from
P-S receiver functions agree with thermal constraints on the vertical extent of
the lithosphere in northeastern North America, a region that shares geologicalhistory with the Caledonides of the British Isles. Notably, we resolved lateralchanges in lithospheric layering over distances <50 km, a significant improvement over laterally smooth global models developed using surface waves inthe same region.
We are undertaking a systematic survey of the upper mantle layering
beneath the British Isles using advanced receiver function techniques andrecently collected data. We will present their inference for the vertical extent,layering, and their lateral variation in the lithosphere, with an emphasis on the
anticipated differences between the relatively seismically active Great Britain
and seismically inert Ireland.
Complex and Contrasting Temporal Patterns of Large
Intraplate and Interplate Earthquakes
LIU, M., University of Missouri, Missouri, USA, lium@missouri.edu; CHEN,
Y., Wuhan University, Wuhan, China, yc2023@whu.edu.cn; JIN, X., Wuhan
University, Wuhan, China, xb_jin@whu.edu.cn; LUO, G., Wuhan University,
Wuhan, China, gluo@sgg.whu.edu.cn
Large (or the so-called characteristic) earthquakes are expected to be periodic
or quasi-periodic, but such regular earthquake recurrences are not common
in nature. Instead, most sequences of large earthquake are complex and variable, often showing clusters of events separated by long and irregular intervalsof quiescence. We compiled and analyzed dozens of catalogs of large interplateand intraplate earthquakes and found a clear difference: most sequences oflarge interplate earthquakes are quasi-periodic (COV<1), but most intraplate
earthquakes are clustered (COV>1). The cause of earthquake clustering islikely complicated, but we can show that stress transfers from earthquakeinduced viscoelastic relaxation and fault interaction are among the major factors. Both real and synthetic catalogs show that the periodicity correlates withthe loading rates, which may explain the difference between intraplate andinterplate earthquakes. In intraplate settings where tectonic loading is slow,
stress from viscoelastic relaxation and other processes, including non-tectonic
loading, becomes relatively significant and contributes to irregular earthquake
occurrences. In contrast, fast and steady tectonic loading in interplate fault
zones tends to suppress the effects of these irregular loadings and lead to moreregular occurrence of earthquakes. All sequences of large earthquakes, either
interplate or intraplate, exhibit the statistical signature of the Devil’s Staircase,a fractal property of nonlinear complex systems. In such a system, change ofany part (e.g., rupture of one fault or segment) could impact the whole system.
Thus, earthquake studies need to go beyond the analysis of stress accumula-

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Seismological Research Letterstion and release on individual faults. While predicting the short-term fault
behavior is challenging, useful insights may be gained by studying the systembehavior of faults in a region.
Use of Seismometers in Studies of Precariously Balanced
Rocks (PBRs) in the Eastern U.S.
PRATT, T. L., U.S. Geological Survey, Virginia, USA, tpratt@usgs.gov;
MCPHILLIPS, D., U.S. Geological Survey, California, USA, dmcphillips@
usgs.gov; STIRLING, M., University of Otago, Dunedin, New Zealand, mark.
stirling@otago.ac.nz; FIGUEIREDO, P., North Carolina State University,
North Carolina, USA, paula_figueiredo@ncsu.edu; LINDBERG, N. S., U.S.
Geological Survey, Colorado, USA, nlindberg@usgs.gov
Although seismometers have been placed on natural arches and pillars, andon bedrock to examine site amplifications at precariously balanced rock (PBR)
sites, we are unaware of seismometers being used on PBRs to discern parameters directly relevant to toppling the rocks. To help use PBRs to constrain eastern U.S. ground motions over tens of thousands of years, we have been placing
3-component, 5-Hz seismometers on PBRs and on nearby bedrock surfaces
to record both environmental noise and gentle pushes of the PBRs. Spectral
ratios between the rock and bedrock recordings show one or more prominent
peaks that define the dominant frequencies of rocking during weak, ambient
ground motions. Because the frequency of rocking decreases with increasing
amplitude of rocking, the dominant frequencies during weak motions likely
reveal the highest frequencies relevant to toppling the rocks during strong
ground motions. After giving gentle pushes to perpendicular sides of therocks, particle motion diagrams from the seismometers on the rocks show
the dominant directions of rocking. Increases in frequency with decreasing
amplitude after the pushes confirm that rocking is occurring, which also isconfirmed by visible motions of some rocks. The directions of rocking areuseful for interpreting the orientations of alpha angles most important for
estimating fragility by established methods. The decay in the amplitude ofrocking per cycle allows for determination of the coefficients of restitution,
which previous workers show can be directly related to the alpha angles and,if the heights of the centers of mass are known, the widths of the contact surfaces with the underlying rocks. We have also been measuring the locations
and strengths of the input pushes in preparation for calibrating future 3Dmodeling of the rock responses. These measurements have been made withextremely small angles of perturbation, and stronger rocking may change thedirection and frequency of rocking due to uneven bases to the rocks, but the
weak motion responses help characterize the responses of the PBRs duringinitiation of rocking.
Identifying Probable Fault Planes in Stable Continental
Regions of Canada for Use in Hazard Assessment
BENT, A. L., Natural Resources Canada, Ottawa, Canada, allison.bent@
canada.ca
Seismic hazard assessment has advanced beyond relying solely on magnitude recurrence rates to incorporating additional parameters, such as seismogenic fault characteristics and deformation rates. In the stable craton
of Canada, active faults have been very difficult to identify. Only the 1989
Ungava, northern Quebec, earthquake is clearly associated with a surface rupture. Additional sources of information, such as Globa Navigation Satellite
Systtems and Interferomic Synthetic Aperture Radar which have been invaluable in active tectonic regions have thus far been of limited value for hazard
assessment in cratonic Canada because of poor spatial coverage, the relatively
modest sizes of recent earthquakes and the slow deformation rate. The region,
however, comprises several active seismic zones. Large earthquakes haveoccurred historically and the current seismograph network provides accurate
locations of the many small to moderate earthquakes throughout the region.
Building on an initial study focused on the Western Quebec Seismic Zone,
statistical analyses of focal mechanisms in all seismically active regions ofsoutheastern Canada and the eastern Canadian Arctic are applied to determine probable fault planes. Although some earthquakes occur outside theseismic zones, there are insufficient focal mechanisms to extend the study
to these less active areas. In the Canadian craton, this method has been successful in determining strike direction and dip angles but the results for dip
direction have been largely equivocal, at least in part because thrust faulting
dominates and many depths are poorly constrained. The results, however, areuseful for developing weighting schemes for incorporating fault place information into the hazard assessment. Relocations of active aftershock sequences
for a small number of earthquakes provide additional information about fault
orientations. Although the impetus of this study is to provide input to future
Canadian seismic hazard models, the results will also provide input to otherresearch topics, such as associating earthquakes with actual faults.

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A Machine Learning Re-Analysis of Seismic Archives in the
Northeastern U.S.: Implications for the Nature of Active
Faults and Faulting
BEAUCE, E., Columbia University, New York, USA, ebeauce@ldeo.columbia.
edu; WANG, K., Columbia University, New York, USA, kw2988@ldeo.
columbia.edu; WALDHAUSER, F., Columbia University, New York, USA,felixw@ldeo.columbia.edu; SCHAFF, D., Columbia University, New York,USA, dschaff@ldeo.columbia.edu; KIM, W., Columbia University, New York,USA, wykim@ldeo.columbia.edu
The Northeastern United States, a stable continental region of low strain andseismicity rates, faces unique challenges in understanding the behavior of
active faults that are capable of failing in large events, and the hazard suchlarge events pose to nearby metropolitan areas. Harnessing recent advances
in machine learning (ML) techniques, we re-analyze two decades (2000-2020)of continuous seismic waveform data recorded by the Lamont Cooperative
Seismic Network (LCSN) and neighboring networks. Our approach integrates
supervised machine learning (ML) and cross-correlation template matchingfor (sub-noise) event detection and phase arrival and delay time measurement (PhaseNet, BPMF), unsupervised ML for source characterization anddiscrimination (SpecUFEx), inversion and grid search methods for accurate
absolute hypocenter location (HINV, NLL) and double-difference methods for
precise relative location (HypoDD). In our preliminary analysis we find close
to 100,000 new events, many of them identified as quarry blasts. However,even with conservative detection parameters, we find more than twice as
many locatable events compared to the existing catalog of about 1,000 earthquakes detected during the 20-year period of routine LCSN operation. Initial
results from a 50 km long segment of the Ramapo fault only 50 km west of
the New York City metropolitan, which at the surface indicates a broad zoneof deformation, show a clearly defined, near vertical active fault down to 10
km. These newly detected and relocated earthquakes demonstrate the potential such new catalogs have to gain new insights into active faults and faulting processes in the northeastern U.S. and in other stable continental regions.
Such large, compute intensive re-analysis studies will benefit from ongoing
efforts within the NSF funded SCOPED project that focuses on implementing
such modules on a hybrid HPC-cloud computational platform for use by thebroader scientific community.
Active Seismicity Around a Cretaceous Magmatic Intrusion
in Monchique, SW Iberia
NERES, M., Instituto Português do Mar e da Atmosfera, Lisbon, Portugal,
marta.neres@ipma.pt; CUNHA, G., Instituto Dom Luiz, Faculdade deCiências, Universidade de Lisboa, Lisbon, Portugal, gabicunhac98@gmail.
com; CUSTÓDIO, S., Universidade de Lisboa, Setubal, Portugal, susana@
fc.ul.pt; SOARES, A., Instituto Dom Luiz, Faculdade de Ciências, Universidade
de Lisboa, Lisbon, Portugal, analdyne.soares@campus.ul.pt; VALES, D.,
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Lisbon,
Portugal, dina.vales@ipma.pt; TERRINHA, P., Instituto Português do Mar eda Atmosfera, Lisbon, Portugal, pedro.terrinha@ipma.pt
Monchique is a prominent topographic high in SW Iberia (Europe) thatreaches a maximum altitude of 902 m, standing out from the surrounding
plane of southern Portugal. It is located to the north of the Eurasia-Africa
plate boundary, which locally accommodates a low rate oblique convergence(~5 mm/yr). At the surface Monchique shows alkaline magmas that intruded
during the Late Cretaceous, following the break-up of Pangea. Monchique is awell-known region of hydrothermal activity, with several natural springs andan active natural water bottling industry and spa services. Monchique also
hosts the most active seismic cluster in mainland Portugal when considering
the number of earthquakes. However, most earthquakes in Monchique are of
low magnitude (<M4) and no active seismic faults are mapped in Monchique.
In this work, we present the results of geophysical modelling of theMonchique magmatic intrusion. In particular, we present the results of magmatic and gravity modelling based on locally collected data. The magnetic
data was collected using a drone, which allowed for an improved coverageof the region. The seismicity was relocated using NonLinLoc, which implements a non-linear probabilistic inversion methodology, and an appropriate 3D regional tomographic model. We find that earthquakes align along 4
main lineations that radiate outwards from the intrusion. We also find thatthe intrusion is limited to the topmost 8 km below the surface and that mostearthquakes occur below this depth. We discuss the relationship between theseismicity and the magmatic intrusion, as well as the roles of hydrothermal
fluids and the nearby plate boundary in facilitating and driving the seismicityof Monchique.
This work was funded by the Portuguese Fundação para a Ciência
e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC)—

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UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020),
UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020),
LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020) and project
RESTLESS (PTDC/CTA-GEF/6674/2020, http://doi.org/10.54499/PTDC/
CTA-GEF/6674/2020).
Amplification and Attenuation: Putting the Puzzle
Together for Ground Motions in the Atlantic and Gulf
Coastal Plains
CABAS, A., North Carolina State University, North Carolina, USA,amcabasm@ncsu.edu; GANN-PHILLIPS, C., North Carolina State
University, North Carolina, USA, cvgann@ncsu.edu; JI, C., North Carolina
State University, North Carolina, USA, cji3@ncsu.edu
The Atlantic and Gulf coastal plains (CPs) host the areas of largest seismic
hazard to the Central and Eastern United States. Unique geologic structuresconsisting of nearly-flat, soft, unconsolidated sediments and sedimentaryrock that overlay bedrock and extend laterally hundreds of kilometers in the
Atlantic and Gulf coastal plains exert a significant influence on earthquake
ground motions. Thicknesses of the sedimentary columns can reach 10 km
and they overlay high-velocity bedrock, which results in a strong seismic
impedance contrast. There have been multiple relevant efforts to account for
the effects of geology and sediment thickness in seismic hazard estimations
for the region. In this work, we use the most recent sediment thickness map of
the CPs, surface geology, and a curated compilation of measured shear wave
velocity data to create a seismic velocity model that can inform future effortsof ground motion characterization in the region.
In addition to capturing impedance effects within regional seismic
velocity models, the characterization of attenuation constitutes an importantpiece of the seismic hazard puzzle. Local site attenuation influences groundmotion characteristics in the high-frequency range and can affect the scaling from soft to hard rock. Only a few studies have focused on characterizing
attenuation properties of shallow and deeper portions of the CPs. We aim todevelop a new regional seismic attenuation model by integrating informationfrom multiple attenuation parameters measured and estimated in the region(e.g., Q and kappa) and examining their relationship with geology. Findings
from this work can improve our understanding of site contributions to groundmotion characteristics unique to the CPs, and they can also support future
physics-based ground motion simulations and regional models of groundmotion site amplification.
The 1886 Charleston, South Carolina, Earthquake: Source
Properties and Ground Motions
HOUGH, S. E., U.S. Geological Survey, California, USA, hough@usgs.gov;
BILHAM, R., University of Colorado Boulder, Colorado, USA, rogerbilham@
gmail.com
The 1886 Charleston, South Carolina, earthquake was felt over much of theeastern United States, with magnitude 6.8-7.3 previously estimated from felt
reports. In spite of extensive contemporaneous documentation, the earthquake and Charleston Seismic Zone have remained enigmatic. Bilham andHough (TSR, 2023) recently developed an elastic deformation model for the1886 earthquake using identified geodetic constraints, including a ~4.5-m
dextral offset in a railroad line southeast of Summerville where the track
crosses the previously mapped Summerville fault. The offset was described incontemporary accounts but never considered by subsequent studies. Unlike
other railroad disturbances in the epicentral region it cannot be explained bysite response. The preferred deformation model yields moment magnitude
7.3, but in contrast to conclusions of previous studies, we found no support
for significant slip south of the Ashley River. We also revisited the near- andfar-field intensity distribution using extensive archival accounts. We compare
the intensity distribution, constrained at nearly 1300 locations, with predictions from modern ground motion models (GMMs) and ground motionintensity conversion equations. Although GMMs are characterized by significant epistemic uncertainty for large earthquakes, we show that the intensity
distribution is consistent with average model predictions, assuming Mw 7.3.
Given the complex influence of site response on saturated Atlantic Coastal
Plain (ACP) sediments throughout the epicentral region, the fit to near-field
intensities is insensitive to the rupture length or other detailed rupture properties. Macroseismic intensities can be used together with model predictions
to improve a ShakeMap for the earthquake, but cannot improve the independently determined rupture model or Mw. An apparent concentration of highintensities near Rantowles, west of Charleston, was defined by a multiplicity
of environment effects that are readily explained by dynamic stress effects andsite response on saturated ACP sediments prevalent throughout the low-lying
marshy regions surrounding Charleston.

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Reactivated Paleozoic and Mesozoic Basement Faults in theCharleston, South Carolina, Seismic Zone
SHAH, A. K., U.S. Geological Survey, Colorado, USA, ashah@usgs.gov;
PRATT, T. L., U.S. Geological Survey, Virginia, USA, tpratt@usgs.gov

Microgal-Precision Gravity Imaging Within an Active
Intraplate Fault: The 2020 m5.1 Sparta, Nc Epicentral ZoneLEVANDOWSKI, W., Tetra Tech, Inc., North Carolina, USA, will.
levandowski@tetratech.com

The Charleston, SC, seismic zone is the site of a M~7.0 earthquake in 1886 thatdevastated much of the city. To better understand seismic hazard within thisregion, we used 2019-2020 high-resolution airborne magnetic data, previous
seismic reflection data, and ground penetrating radar (GPR) data to image
basement structures at seismogenic depths that may have had more recent
reactivation. Comparisons between the aeromagnetic data and seismic reflection profiles show NE- and ESE-trending magnetic lineaments associated withfaults visible within pre-Cretaceous strata. Of these, a subset of faults show
disturbances within overlying Cenozoic sediments. This includes the >60-kmlong NE-striking Gants fault, extending from Pinopolis in the NE to an area
between Jacksonboro and Walterboro in the SW and interpreted as a reactivated Paleozoic structure, and the >20-km-long ESE-trending Summervillelineament, which has a western termination at Gants fault and extends alongpart of the Ashley River towards North Charleston and possibly farther east,
and is interpreted as part of a Mesozoic rift structure. Other NE-striking faults
parallel or sub-parallel to Gants fault also show Cenozoic disturbances, andsome evidence of possible Quaternary motion. The Summerville lineament iswell-aligned with a plan-view offset in seismicity and a topographic slope previously observed in lidar data, further supporting associated fault reactivation
over the last < 1 m.yr. Gants fault, which is coincident with and parallel to theseries of paleoshorelines that define the Penholoway Formation but lies several km west of the eastern edge of these shorelines, expresses only small vertical displacements at the shallow (<15 m) erosional unconformity at the baseof Quaternary imaged using GPR. Previous focal mechanisms have shown
both ESE- and NE-trending motion, further supporting slip along similarly
oriented faults. We find, in fact, that numerous faults within the region show
evidence of recent slip, making it very challenging to determine a unique causative fault for the 1886 earthquake.

The 2020 Mw5.1 Sparta, NC mainshock resulted from remarkably shallow(hypocenter < 1.5 km) sinistral-reverse slip on the ESE-striking Little River
Fault (LRF). Moreover, the earthquake caused the first observed surface rupture in the eastern U.S., thus providing the first definitive exposure of an active
intraplate fault in the region and an unprecedented opportunity: A microgravity (microGal-precision relative gravity) survey collected 558 readings at 492
unique locations over 7 days in September 2023 to illuminate structures inthe epicentral region and surface trace at scales ranging from ~2 km to a few
meters. Empirical precision is ±0.006 mGal. The residual gravity anomaly fieldfeatures ENE-trending alternating +/- 1 mGal gravity anomalies across the
LRF footwall. The most prominent high coincides with an erosion-resistant
topographic high that may delineate a garnet/magnetite schist zone within
the Alligator Back metamorphic suite. This anomaly intersects the LRF along
the surface rupture, up-dip from the hypocenter, and its muted signature canbe traced beneath the hanging wall to the epicenter. This anomaly is interpreted to delineate a relatively competent—both with respect to erosion andto brittle deformation—lithology that resists underthrusting and acts as a
macro-asperity along the LRF. The reverse component of the mainshock was
greatest up-dip of the hypocenter, grading eastward (away from the asperity)
to nearly pure strike-slip (Pollitz, 2023). In old, cold, strong continental interiors, along-strike variations in footwall structure may thus control rupture
nucleation and create complex ruptures.

Evidence of Quaternary Deformation in the Ste. Genevieve
Fault Zone, Southeastern Missouri: Preliminary Results
COUNTS, R. C., University of Mississippi, Mississippi, USA, rcounts@
olemiss.edu; VAUGHN, J., KeenGeoserve, LLC, retired, Missouri, USA, jdvcjv5491@charter.net; NELSON, W., Illinois State Geological Survey, Illinois,
USA, jnelson49@gmail.com; DEVERA, J. A., Illinois State Geological Survey,
Illinois, USA, jdevera@illinois.edu; CURRY, B., Illinois State Geological
Survey, Illinois, USA, bcurry@illinois.edu
The Ste. Genevieve fault zone (SGFZ) is a 190 km long, northwest-southeast
trending zone of complex deformation in southeastern Missouri and southern Illinois that separates the Ozark Dome from the Illinois Basin. The SGFZ
has variable deformation along strike, including variations in fault occurrence and spacing, block rotations, changes in the direction of stratigraphic
offset between faults, and deformed noncylindrical and monoclinal folding.
Structural mapping done over many decades shows normal, reverse, strikeslip, and oblique-slip faulting due to more than one phase of fault reactivation.
Structural relief on the Precambrian surface across the SGFZ varies from lessthan 1 km at its northwestern end to nearly 4 km at its southeastern end. Thereis a zone of active seismicity associated with the SGFZ, but there are no known
examples of neotectonic deformation linked to the fault zone.
One possible example of tectonically deformed Quaternary alluvium
lies in a cut bank exposure on Clines Branch in Perry County, Missouri. This
exposure contains a prominent vertical fault that cuts very dense, highly fractured silt deposits. There are several, less obvious silt blocks displaced eastof the fault, and west of the fault is a ~1 m wide zone of fault breccia containing a 0.5 m wide block of Glen Dean limestone that appears uplifted. A
coarse lag deposit is folded into a small anticline above the fault, and eastof the anticline a laminated clayey silt also appears to be folded. The age ofthe faulted silt is inferred to be either Roxanna Silt or the B horizon of theSangamon Geosol, indicating deformation is Late Pleistocene. Luminescenceand 14C samples from the deformed units are currently being processed forgeochronology. Paleoliquefaction features that formed ~11.4 ka to 4.7 years
cal BP on the lower Big Muddy River, 17 km east of Clines Branch in southwest Jackson County, IL, and other small liquefaction features on the lower
Apple Creek, ~16 km to the south in Cape Girardeau County, could be coeval
with deformation at Clines Branch, but additional work is needed to confirm
the deformation is tectonic.

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Tectonics and Seismicity of Stable Continental Interiors[Poster Session]
Poster Session • Friday 3 May
Conveners: Oliver Boyd, U.S. Geological Survey (olboyd@
usgs.go); Jessica Thompson Jobe, U.S. Geological Survey(jjobe@usgs.gov); William Levandowski, TetraTech (will.
levandowski@tetratech.com); Zhigang Peng, Georgia
Institute of Technology (zpeng@gatech.edu); Anjana K. Shah,U.S. Geological Survey (ashah@usgs.gov)
poster 35
Inferring Crustal Stress Distribution Within the Middleton
Place/summerville Seismic Zone, South Carolina
ADEBOBOYE, O. E., Georgia Institute of Technology, Georgia, USA,oadeboboye3@gatech.edu; PENG, Z., Georgia Institute of Technology,
Georgia, USA, zpeng@gatech.edu; JAUME, S., College of Charleston, South
Carolina, USA, jaumes@cofc.edu
The 1886 ~M7 Summerville earthquake in South Carolina remains enigmaticwith no surface faulting evidence. Several studies (Mckinley, 1887; Chapman
et al., 2016; Bilham and Hough, 2023) offer varying source fault interpretations in the Charleston-Summerville region, but the exact fault structure that
ruptured during the 1886 mainshock remains unknown. Ongoing microseismicity near the Middleton Place/Summerville Seismic Zone (MPSSZ), possibly aftershocks of the 1886 mainshock, could shed light on the source fault
and improve our understanding of seismic hazards in the area. Preliminary
analysis of microseismicity in Summerville using a network of 19 temporary
short-period stations from May 2021-May 2023 (Jaume et al., 2021) identified a south-striking, west-dipping zone in the southern seismicity cluster
and a north-south striking near-vertical plane further north (Chen et al.,2023). From February to May 2023, we deployed two linear arrays with 22
stations in the study area. Currently, we reoccupied 14 of the 19 stations by
5-Hz Smartsolo nodes and added 6 new stations near the MPSSZ and in theunder-monitored northern region towards Pinopolis. In this study, we plan
to further develop our current results based on our analysis of 181 events
detected from the first half of the temporary network continuous data presented at the 2023 SSA Annual Meeting (Adeboboye et al., 2023). Our objective is to gain insights into the local crustal stresses and orientations of fault
slips at depth. This begins with applying a modified workflow for building
earthquake catalogs (Neves et al., 2023) to additional data from our recent
experiment. Following this, we obtain focal mechanisms of the area, and constrain their solutions using relative S/P amplitude ratios (Skoumal et al., 2023).
Subsequently, we will use the focal mechanism solutions, combined with ear-www.srl-online.org•

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lier results (e.g., Chapman et al. 2016, Adeboboye et al. 2023), to invert for
the local stress inversion (Hardebeck & Michael, 2006). We expect that these
efforts will provide insights into the source fault of the 1886 earthquake andits connection to present seismicity.
poster 36
Developing Ground Motion Model Using Nonparametric
Machine Learning Techniques for Induced Earthquakes inCentral and Eastern North America (Cena)
ALIDADI, N., University of Memphis, Tennessee, USA, nalidadi@memphis.
edu; PEZESHK, S., University of Memphis, Tennessee, USA, spezeshk@
memphis.edu
Ground motion models (GMMs) play a crucial role in the probabilistic
assessment of seismic hazards and their uncertainties. In this research, wedevelop new GMMs using nonparametric machine learning, including artificial neural networks, kernel ridge, random forest, and gradient boosting
regression techniques. GMM is specifically developed for small-to-moderatemagnitude, potentially induced seismic events in Central and Eastern North
America (CENA). The study assesses the efficacy of various machine learning algorithms in predicting peak ground acceleration (PGA) and 17 different spectral accelerations, considering features like moment magnitude (MW),hypocentral distance (Rhypo), and the timed-average shear-wave velocity of theupper 30 m of soil (Vs30). The training process is conducted using a databaseof about 31,000 ground motion records from CENA, with small and moderate
moment magnitudes ranging between 3.0 and 5.8 and recorded at hypocentral
distances up to 200 km. Traditional GMMs typically rely on linear regression models with predefined functional forms, which may restrict the use ofcomplicated and nonlinear equations. While traditional regression models are
more interpretable, machine learning models have the potential of superior
outcomes given sufficient training data. Error metric analysis indicates that
gradient-boosting regression shows enhanced performance. Additionally, we
have applied a machine learning ensemble approach to merge the regression
results from four different machine learning algorithms. This ensemble technique leads to smoother outcomes.
poster 37
Seismic Networks Important in Lower Seismic Hazard
Environments like Australia
BORLEIS, E., Seismology Research Centre, Richmond, Australia, elodie.
borleis@src.com.au
Australia is a region of low seismicity compared to the rest of the world and soevery earthquake counts. Irrespective of the absolute level of seismic hazard,
understanding the level of hazard is important to infrastructure and communities. Earthquake magnitude recurrence (EMR) plots are used to evaluate theactivity rates of a seismotectonic zone based on the Gutenberg-Richter seismicity recurrence equation. Quantification of the seismicity of a zone requires
an estimate of the detection levels of the seismic network in the area and thecompleteness level of the earthquake catalogue. The magnitude of completeness level of the earthquake catalogue varies with time and is estimated fromthe recorded seismicity as well as from knowledge of the history of the seismic
network in the area. Seismic networks provide the raw data to EMR plots andso are vital in assessing the seismic hazard of a site. Not having a seismic network in place or decommissioning seismic networks will impact on the accuracy and completeness of future earthquake locations. Without this recorded
seismicity the EMR plots can have a large amount of uncertainty associatedwith them and may not appropriately show the hazard in that area. We havecompared EMR plots for a series of seismotectonic zones to investigate theoutcome when local scale seismic networks are decommissioned or such local
scale networks were never in place.
poster 38
Neotectonic Mapping of the Charleston Seismic Zone,
South Carolina
THOMPSON JOBE, J. A., U.S. Geological Survey, Colorado, USA, jjobe@
usgs.gov; BRIGGS, R., U.S. Geological Survey, Colorado, USA, rbriggs@usgs.
gov; COLLETT, C., Oregon Department of Forestry, Oregon, USA, camille.
collett@odf.oregon.gov; SHAH, A. K., U.S. Geological Survey, Colorado,
USA, ashah@usgs.gov; PRATT, T., U.S. Geological Survey, Virginia, USA,
tpratt@usgs.gov
The Charleston, South Carolina, region experienced an ~M7 earthquake in
1886, with widely felt ground shaking and corresponding damage. However,the locations and kinematics of the fault(s) that ruptured in the 1886 earthquake, or faults that may have ruptured during pre-1886 earthquakes, remain

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unknown. There have been multiple previous efforts to map potentially active
faults from seismicity, 3-m lidar-derived topography, and aeromagnetic, seismic reflection, ground-penetrating radar (GPR) surveys. Here, we present
preliminary neotectonic mapping on new <1-m lidar-derived topography of
the 1886 epicentral region. We integrate our observations with existing surface and subsurface datasets and interpretations, including geologic maps,
previous lineament and fault mapping, seismic reflection data, GPR surveys,
and new high-resolution aeromagnetic data. We map east-southeast–westnorthwest-trending and east–west-trending scarps between the Cooper,
Goose, and Ashley Rivers that vertically offset late Quaternary geomorphic
surfaces with a primarily down-to-the-north sense of motion. Sets of scarps
extend for 4 to 6 km, with individual scarps that are 200 m to 1.5 km long.
Some paired scarps suggest the presence of a graben. At least one prominenteast-west scarp that offsets mapped Quaternary deposits aligns with an aeromagnetic lineament that extends towards Summerville. Seismic reflection and
GPR data are not available at the scarp site but are available to the northwest
on the same magnetic lineament. There, the seismic reflection data support
deformation of Cenozoic units. In addition to mapping fault-related scarps,
we also map slumping associated with ground-shaking near a well-known
apparently offset railroad track, suggesting the track was deformed by secondary shaking effects and does not record primary surface rupture. These newobservations may help better constrain the locations of faults that ruptured in
the 1886 or previous earthquakes and lead to an improved understanding ofseismic hazard in the region.
poster 39
Determination of Focal Depth of Offshore Earthquakes
Around the Korean Peninsula Using Depth Phase
LEE, H., Chonnam National University, Gwangju, South Korea, hyunj@jnu.
ac.kr; SHEEN, D., Chonnam National University, Gwangju, South Korea,
dhsheen@jnu.ac.kr
The focal depth of earthquakes is one of the fundamental parameters fordescribing the tectonic process in a region. Especially in an intraplate region
with low seismicity, the accurate determination of the focal depth of earthquakes is crucial, as it can enhance our understanding of subsurface faults andlocal stresses, which can be very difficult to observe with other approaches.
However, estimating the focal depth is more challenging than determining
the epicentral location. Owing to dense seismic network, the focal depth ofearthquakes within the southern Korean Peninsula can be accurately estimated using the traditional location method, which utilizes the arrival timesof various seismic phases. However, offshore earthquakes occurring aroundthe peninsula inherently lack direct seismic arrivals, which are critical for
improving the accuracy of focal depth estimates. This led to discrepancies
in focal depths of offshore events in seismic bulletins cataloged by local andglobal agencies. Alternatively, regional moment tensor inversions could provide reliable focal depth estimates of moderate-sized offshore events aroundthe peninsula (Song et al., 2022). However, focal depths of some offshore
events were determined to too shallow (less than several kilometers). In thisstudy, therefore, we determined the focal depths of offshore events with magnitudes larger than 3.5 occurred around the southern Korean Peninsula from2005 and 2023 using depth phases. To validate our approach, the focal depths
of inland earthquakes, reliably obtained by the previous studies, were determined with a limited number of depth phases. Since the focal depths dependon the velocity model, we also tested the dependency using five local crustal
models and three global models.
poster 40
Africa’s Lithospheric Architecture With Multi-Mode Body
Wave Imaging
LEGRE, J. B., University of Rochester, New York, USA, j.joel.legre@gmail.
com; OLUGBOJI, T. M., University of Rochester, New York, USA, tolugboj@
ur.rochester.edu
Africa’s lithosphere hosts the longest-lived cratons on our planet and records
a rich and diverse tectonic history: plate subduction to the North, a long rift
system in the East, the super swell in the South, and a record of continental
breakup to the West. However, gaps remain in our current efforts to study
its lithospheric layering due to sparse coverage and noisy short-term seismic
deployments. Here, we present a body-wave dataset and model assessment
products for investigating Africa’s lithosphere (ADAMA). We address thechallenge of lithospheric imaging on the continent using sparse and noisy teleseismic body wavefields, i.e., receiver functions and SS precursors. The latterextends lithospheric illumination in regions without station coverage. In bothcases, we explore novel denoising approaches: (1) CRISP-RF (Clean Receiver
Function Imaging with Sparse Radon Filters), which uses sparse Radon trans-

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forms to interpolate the sparse receiver function data and eliminate incoherent noise, and (2) FADER (Fast Automated Detection and Elimination of
Echoes and Reverberations), which deconvolves thin-layer reflections buriedin long-period SS precursors. We improve constraints on bulk crustal structure and lithospheric layering, e.g., from H-k stacking, following CRISP-RF
denoising. We extend spatial sampling and detections of lithospheric layeringby jointly interpreting receiver functions and SS precursors following cepstraldeconvolution of long-period SS precursor waveforms. Our final model, ACEADAMA-BW (Africa’s Continental Layering Evaluated with ADAMA’s Body
Waves), will improve 3-D resolution of lithospheric layering spanning thecratons (West Africa, Tanzania, Congo, Kaapvaal, Zimbabwe), rifts (Gourma,
East African Rift System) and basins (Taoudeni, Goo, Congo) of Africa.
poster 41
Crustal Structure and Mantle Deformation Across theCentral African Plateau, Zambia: Evidence from Receiver
Functions and Shear-Wave Splitting Analysis
KOUNOUDIS, R., University of Oxford, Oxford, United Kingdom, rita.
kounoudis@earth.ox.ac.uk; OGDEN, C. S., University of Leicester, Leicester,
United Kingdom, chris.ogden@leicester.ac.uk; CHIFWEPA, C., Zambian
Geological Survey Department, Lusaka, Zambia, cchifwepa@gmail.com;
FISHWICK, S., University of Leicester, Leicester, United Kingdom, sf130@
leicester.ac.uk; KENDALL, M., University of Oxford, Oxford, United
Kingdom, mike.kendall@earth.ox.ac.uk; DALY, M. C., University of Oxford,
Oxford, United Kingdom, mike.daly@earth.ox.ac.uk
The Central African Plateau comprises numerous Archean cratons sutured inProterozoic to early Cambrian times — the Congo, Bangweulu and Kalaharicratons. In the heart of this region lies the copper-rich Neoproterozoic
Katangan basin. Major deformation zones and complex craton margin fault
zones reflect the region’s tectonic history, which is further complicated by the
Permo-Triassic and Pliocene development of the Southwestern Rift in southern Zambia. The extent to which surface deformation is mirrored to deeper
crustal, and mantle lithospheric depths is uncertain but may also be key toultimately understanding the Cu, Co and Ni mineralisation of the Katangan
Basin. To investigate the tectonics and geodynamics that shaped the region,
we utilise data from the Copper Basin Exploration Science (CuBES) seismic
experiment — a NW-SE-trending, 750km-long profile of 35 broadband seismograph stations deployed across Zambia. Lithospheric deformation fabrics
associated with past and present tectonic deformation are explored via an SKS
splitting study of mantle seismic anisotropy. Crustal and lithospheric mantle
seismic structure are also elucidated via receiver function and surface-wave
analysis, the results of which are compared to bulk-crustal constraints derived
from the modified H-K stacking method of Ogden et al., (2019). Results thus
far reveal variable bulk crustal Vp/Vs ratios along the entire CuBES line, withcrustal thickness contrasts across major tectonic boundaries, and clear evidence for short length-scale variations in upper-mantle seismic anisotropy.
poster 42
Stochastic Inversions of Source, Path, and Site Parameters
for West Texas Earthquakes
PANDEL, B., University of Texas at Austin, Texas, USA, bartikpandel@utexas.
edu; RATHJE, E. M., University of Texas at Austin, Texas, USA, e.rathje@
mail.utexas.edu; SAVVAIDIS, A., University of Texas at Austin, Texas, USA,alexandros.savvaidis@beg.utexas.edu; KOTTKE, A. R., Pacific Gas & ElectricCompany, California, USA, albert.kottke@pge.com
The increase in seismicity in West Texas since 2020 coupled with the enhanced
seismic network coverage by the Texas Seismological Network has generated
significant earthquake data that allows for the study of source, path, and sitecharacteristics in the region. In this research, we utilize a Bayesian parametricinversion technique for broadband spectral decomposition of ground motion
records from seismic events in the Delaware Basin of West Texas. Groundmotion records from earthquakes with reported ML >= 3.0 (largest ML = 5.4)
and hypocentral distances up to 300 km are used to evaluate source, path,and site terms. The dataset consists of 6,477 ground motion records from 354
events recorded at 49 stations. We implement a geometric spreading function with a gradual transition from a near-field geometric spreading rate (γ)
to a fixed far-field spreading rate of 0.5, incorporating a variable transition
distance. Preliminary analyses show a quality factor (Q0) value of 781, frequency dependent anelastic attenuation parameter (η) of 0.70, γ of 1.15, and atransition distance of 76 km. Inverted MW values tend to be smaller than thereported ML values. Inverted stress drop values range from ~3 to 120 bars andthese values increase with increasing magnitude. This finding aligns with theavailable literature for West Texas and other regions. The inversions provide

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frequency-dependent site amplification and the high frequency decay parameter (κ0) for each station. The site amplification varies considerably in amplitude and shape across the stations, and κ0 also varies considerably from 0.008
to 0.057 s. In summary, our study leverages an efficient inversion technique,offering a robust framework for characterizing a seismically active region.
Integrated into the regional context, these findings advance our understanding of seismicity in the Delaware Basin of West Texas from an engineering andseismic hazard perspective such that the results can be used to develop robust
ground motion models for larger events (MW > 5.0) that are of engineeringsignificance.
poster 43
The 2020 Sparta, North Carolina, Earthquake: Insights From
Double-Difference Earthquake Relocations, Regional
Moment Tensor Inversion and Coulomb Static Stress
Transfer
PARIJA, M., Virginia Tech, Virginia, USA, maheshparija@vt.edu;
CHAPMAN, M. C., Virginia Tech, Virginia, USA, mcc@vt.edu; POLLYEA,
R., Virginia Tech, Virginia, USA, rpollyea@vt.edu
The study examined the spatial and temporal distribution of the 2020 Mw 5.1
Sparta, North Carolina foreshock-mainshock-aftershock sequence, recordedby 13 permanent stations of the US national seismic network. The double-difference (HypoDD) earthquake relocation algorithm was applied to the foreshocks, mainshocks, and aftershocks to characterize the fault responsible forthe earthquake. 105 earthquakes that occurred between August 2020 and June
2023 were relocated using a total of 922 P and 942 S differential travel times.
The relocations resulted in five individual clusters, with the primary cluster
involving 57 aftershocks located to the south-west of the mainshock. The
relocation indicates a south-west dipping reverse fault with aftershock hypocenters at depths from 0.2 km down to 12 km. We also computed the mainshock focal mechanism using the regional waveforms recorded with the US
permanent seismic array. This inversion used waveforms bandpassed between
frequencies 0.05 and 0.11 Hz and demonstrates a reverse fault mechanism at a
centroid depth of 3 km for the mainshock. The strike, dip, and rake computedfor the nodal plane are 114, 60, and 64, respectively. We are now examining
the Coulomb static stress transfer relationship between mainshock and theaftershock sequence.
poster 44
Neotectonic Controls on the Meadow Bank Scarp, Wabash
Valley Seismic Zone USA
WOOLERY, E. W., University of Kentucky, Kentucky, USA, woolery@uky.edu; STEPHENSON, W. J., U.S. Geological Survey, Colorado, USA,wstephens@usgs.gov; WOLLER, K. L., University of Kentucky, Kentucky,
USA, kevin.woller@uky.edu; LEEDS, A. L., U.S. Geological Survey, Colorado,
USA, aleeds@usgs.gov; LINDBERG, N. S., U.S. Geological Survey, Colorado,
USA, nlindberg@usgs.gov; ODUM, J., U.S. Geological Survey, Colorado,
USA, jacksonodum@gmail.com; CEARLEY, C. S., U.S. Army Engineer
Research and Development Center, Mississippi, USA, cooper.s.cearley@erdc.dren.mil; COUNTS, R. C., University of Mississippi, Mississippi, USA,rcounts@olemiss.edu
Scarps typically have much steeper slopes than those of the surrounding
topography and are driven by abrupt spatial changes in geologic materials
and/or temporal processes like active faulting. The Meadow Bank scarp (MBS)in southeastern Illinois is widely accepted as satisfying the former but has historically lacked consensus as a tectonically driven scarp. Debate has focusedon the process controlling the pronounced ~10-km-long and 4-to-7-meterhigh down-to-the-east linear feature. Regional seismic reflection and well-log
data suggest the northeast-trending MBS parallels the underlying structural
fabric of the Wabash Valley fault zone and lies within a region of active seismicity. The scarp also acts as a flood plain boundary of the Wabash Riverand is located near the terminus of the Pleistocene glacial advances which
produced frequent “outburst” flood events. To better constrain scarp genesis,
we acquired a 917-m-long, 9-fold, SH-wave seismic-reflection survey acrossthe feature using an 18.24 m landstreamer with twenty-four grouped pairs ofpolarity compatible 4.5 Hz horizontal geophones spaced at 0.76 meters, alongwith a rolling steel wheel and hammer acting as a horizontal impact energy
source. The resultant reflection image indicates a 400-m-wide set of faults thatlie immediately west (inboard) of the scarp face. These faults antiformally fold
and displace the top of Paleozoic bedrock by approximately 8 m at depths of
30 to 50 m. Fault and/or fault-bend-fold deformation appears to extend into
the shallowest Quaternary strata: within the upper 10 meters. Consequently,
we interpret the MBS as formed by the Quaternary-active Wabash fault zone.

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poster 45
Source Characterization of the 2020 Mw 5.1 Sparta, North
Carolina, Earthquake Sequence
WU, Q., Lettis Consultants International, California, USA, wu@lettisci.com;
CHAPMAN, M., Virginia Tech, Virginia, USA, mcc@vt.edu
On August 9, 2020, a Mw 5.1 earthquake shook the Blue Ridge Mountains near
Sparta, North Carolina, causing damage to roads, utility lines, and masonry
structures. This earthquake is the strongest recorded in North Carolina
since the 1916 M 5.2 earthquake near Asheville. Despite its moderate size,
the Sparta mainshock generated the first documented surface rupture due tofaulting in the eastern United States (EUS). The co-seismic surface rupture
was identified along a ~2-km-long ESE-striking, SSW-dipping reverse fault.
The mainshock was preceded by 8 foreshocks with duration magnitude (Md)ranging between 1.8 and 2.6 within the 25 hours before the mainshock andfollowed by hundreds of locatable aftershocks. The focal mechanism of themainshock that we determined using moment tensor inversion reveals a very
shallow (1 km depth) oblique reverse fault striking SE (N118°E) and dipping
52° to SW. This mechanism matches well with the observed surface deformation. Spectral analysis of the mainshock data indicates a corner frequency of
0.77 Hz, corresponding to a Brune stress drop of only 5.7 MPa, unusuallysmall for an EUS mainshock, and the calculated source radius of 1.5 km andaverage slip of 20 cm both agree well with field observations. Preliminary relocations of ~300 events in the sequence using the double-difference algorithm
greatly improved the spatial alignment of the seismicity compared to the original catalog. Notably, in addition to the NW-SE-striking fault associated withthe mainshock fault plane and the surface rupture, the relocated events alsodelineate a conjugate fault trending NE, which intersects the mainshock fault
near the northwest edge of the surface rupture. Ongoing work involves theconstruction of a rupture model for the mainshock, the detection and locationof more events to construct a more complete catalog of the sequence, focal
mechanism determination and stress drop estimation for smaller events in thesequence. Our results will help shed light on the source processes and seismic
hazard assessment in this very low strain rate intraplate setting.

Towards Advancing Earthquake Forecasting andNowcasting: Recent Progress Using AI-Enhanced Methods
Oral Session • Wednesday 1 May • 2:00 pm PacificConveners: Yangkang Chen, University of Texas at Austin(yangkang.chen@beg.utexas.edu); Katsumi Hattori, Chiba
University (khattori@faculty.chiba-u.jp); Lisa G. Ludwig,
University of California, Irvine (lgrant@uci.edu); Dimitar
Ouzounov, Chapman University (ouzounov@chapman.edu);
John Rundle, University of California, Davis (john.b.rundle@
gmail.com)
Towards Deep-Learned Picking at the USGS National
Earthquake Information Center
WELLS, D., U.S. Geological Survey, Colorado, USA, dewells@usgs.gov;
YECK, W., U.S. Geological Survey, Colorado, USA, wyeck@usgs.gov; COLE,
H., U.S. Geological Survey, Colorado, USA, hcole@Contractor.usgs.gov;
PATTON, J., U.S. Geological Survey, Colorado, USA, jpatton@usgs.gov;
SHELLY, D., U.S. Geological Survey, Colorado, USA, dshelly@usgs.gov;
EARLE, P., U.S. Geological Survey, Colorado, USA, pearle@usgs.gov
Phase picking by deep neural networks often outperforms traditional methods at local-regional scales, but the implementation of deep earning in realtime global earthquake detection has received relatively less attention. Deeplearning methods can improve the accuracy, precision, and recall of phasepicks and once trained, can handle large data streams more quickly and withless computational overhead compared to traditional approaches. Deep learning models also are advantageous as they can be designed and trained specifically to meet the requirements of a particular monitoring system. We discuss our design considerations and requirements for a National Earthquake
Information Center (NEIC) machine-learning seismic phase picker, including
the selection of most appropriate training dataset to meet the NEIC’s needs.
We also include how we approach the detection and usage of secondary teleseismic phases. The NEIC heavily relies on first-arriving P and local S picks,
and therefore we train a model specifically to target these features. Finally,
we compare the performance of our new picker to the existing NEIC automatic multi-band filter phase picker, test its performance in conjunction with

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NEIC’s GLASS3 associator, which requires reliable and non-spurious picks
for optimal performance, and discuss the integration of the picker into NEIC’soperational systems.
Evaluating the Application of Machine Learning in Seismic
Site Classification: A Case Study of Vs30 Development in
Po Plain, Italy
MITRA, D., Risk Management Solutions, California, USA, dmitra@rms.com;
SETHI, S., Moody’s RMS, Noida, India, Shipra.Sethi@rms.com
The continuous application of VS30, representing the time-averaged shearwave velocity in the upper 30m, as a proxy for site characteristics, has consistently driven the necessity to enhance methodologies and strive for an
approach that can improve accuracy of the estimation of seismic site classifications. Widely adopted methodologies, including terrain-based, geological,
and hybrid regression-based models, have formed the backbone of research
and applications in VS30 mapping. Recent advancements have witnessed the
expansion of open-source datasets, advancements in satellite and remote sensing data as well as integration of more sophisticated approaches, particularly
those based on Machine Learning (ML) algorithms. Our investigation centers on VS30 mapping in the Po Plain region in Italy, utilizing field data fromover 3000 sites along with other geospatial parameters such as surficial geology, Digital Elevation Models (DEM) based derivatives, and physiographic
divisions. In this study, our objective is to employ ML-based algorithms forcomparing VS30 estimations with conventional geostatistical methods tohighlight the strengths and limitations inherent in these methodologies. The
findings demonstrate the capability of ML predictive algorithms to improve
spatial interdependence across geological, geophysical, and geotechnical data.
The insights derived from this study can be employed to formulate a wellinformed assessment of seismic risk at the local level.
An AI-Assisted Real-Time Earthquake Forecasting Case
Study in China
CHEN, Y., University of Texas at Austin, Texas, USA, yangkang.chen@beg.
utexas.edu; SAAD, O., King Abdullah University of Science and Technology,
Thuwal, Saudi Arabia, engomar91@gmail.com; CHEN, Y., Zhejiang
University, Hangzhou, China, yunfeng_chen@zju.edu.cn; SAVVAIDIS, A.,
University of Texas at Austin, , USA, alexandros.savvaidis@beg.utexas.edu;
FOMEL, S., University of Texas at Austin, Texas, USA, sergey.fomel@beg.
utexas.edu; JIANG, X., Zhejiang University, Hangzhou, China, xiuxuan_
jiang@zju.edu.cn; HUANG, D., University of Texas at Austin, Texas, USA,
dino.huang@beg.utexas.edu; OBOUÉ, I., Zhejiang University, Hangzhou,
China, obouesonofgod1@gmail.com
Earthquake forecasting aims to save human lives and reduce economic loss
by providing early alerts before the occurrence of large destructive earthquakes. It was long considered challenging due to the various uncertain
factors, including data processing artifacts, unknown physical mechanisms,
geological complexity, anthropogenic interventions, etc. With the advent ofartificial intelligence (AI) and gigantic datasets from multiple sources, earthquake forecasting has become more hopeful. In this study, we trained anearthquake forecasting model using a classic random forest algorithm and alarge-scale dataset from West China, where earthquake activities are prevalent. We obtained encouraging real-time testing results on an independent
dataset from the same area. The training data comprises the geo-acoustic(GA) and electromagnetic (EM) data of more than 120 M>3.5 earthquake
events recorded by 150 stations from 10/01/2016 to 12/31/2020. Instead ofusing the continuous waveforms directly, we extract physically meaningful
features to lower the freedom and uncertainty involved in the training process. The real-time forecasting performance reaches above 70% accuracy witha distance error close to 200 miles and a magnitude error below 0.5 Ml. This
research sheds light on more widely tackling the enigmatic earthquake forecasting problems using AI-assisted data-harnessing technologies.
Now-Casting With Real-Time Strong-Motion Response
SpectraFRANKE, M., Kinemetrics, Inc., California, USA, mf@kmi.com;
LINDQUIST, K., Boulder Real Time Technologies, Inc., Colorado, USA,kent@nrtt.com; VERNON, F., University of California, San Diego, California,
USA, flveron@ucsd.edu
Now-casting serves as a crucial and complementary component of Earthquake
Early Warning Systems (EEWS). While EEWS are essential for providing
advanced warning in seismic events, they inherently have blind zones where
the strong shaking arrives before the early warning alert. In these instances,
now-casting steps in to bridge the gap. This approach offers the advantage

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of delivering actionable information within mere seconds after the onset ofsignificant shaking, ensuring that individuals and organizations have immediate guidance for response to the event. Moreover, now-casting is particularly
valuable in situations where implementing preventive measures via EEWS
could be cost-prohibitive. Furthermore, now-casting’s utility extends beyond
areas covered by comprehensive EEWS networks. It remains effective in seismic regions with sparse station coverage, ensuring that earthquake monitoring and response capabilities are not restricted solely to regions with fully
established EEWS infrastructure.
We employ strong-motion response spectra calculated in real timefrom accelerometers to create exceedance alerts for one or more engineering
demand spectra, e.g., Design Response Spectrum (DRS), Operational Basis
Earthquake (OBE), and Safe Shutdown Earthquake (SSE). This approachmeasures true ground motion and doesn’t require an earthquake locationand magnitude, thus these alerts can be calculated within milliseconds andthen disseminated. In addition, the warning carries qualitative information on
possible damage to structures and buildings in the vicinity of a given strongmotion station. We will show data and examples gathered during an experiment in the ANZA network to demonstrate strong-motion response spectra
as a now-casting tool.
Abnormal Low-Magnitude Seismicity Preceding theM6.4-M7.1 2019 Ridgecrest (California) Sequence and theM7.1 2018 Anchorage (Alaska) Earthquake
GIRONA, T., University of Alaska Fairbanks, Alaska, USA, tarsilo.girona@alaska.edu; DRYMONI, K., Ludwig Maximilian University of Munich,
Munich, Germany, kyriaki.drymoni@min.uni-muenchen.de
Empirical analysis indicates that large, locked fault zones concentrate stresses
both within their internal configurations and in their host rock, leading topossible variations in low-magnitude seismic patterns on a regional scale.
However, the intricate spatiotemporal distribution of low-magnitude seismicity, coupled with gaps in previous earthquake catalogs, obstructs the conclusive determination of whether major seismic events are consistently precededby identifiable seismic or tectonic unrest. The advent of novel machine learning-based methodologies provides the oppportunity to decipher subtle andnonlinear patterns from historical seismic events. In this study, we employ anovel multivariate, supervised, machine learning-based algorithm to investigate whether low-magnitude seismicity conceals robust, nonlinear precursory
patterns that could reliably signal forthcoming large-magnitude earthquakes.
Our algorithm integrates a random forest machine learning approach and statistical features derived from openly available earthquake catalog data. The
analysis reveals that the M6.4-M7.1 2019 Ridgecrest (California) sequenceand the M7.1 2018 Anchorage (Alaska) earthquake were preceded by approximately three months of tectonic unrest on regional scales. This unrest manifested as anomalous low-magnitude seismic activity spanning roughly 15-25%of the total area of Southern California and Southcentral Alaska. Further support for our findings comes from finite element solid mechanics models, demonstrating that the presence of large, locked faults can induce uneven variations in the regional stress field when the pore fluid pressure within these fault
segments significantly increases, and thus their internal structure becomes
softer (lower Young’s modulus). These discoveries offer latent avenues formonitoring agencies to potentially detect regions approaching a significant
earthquake (fault rupture) weeks to months before its occurrence.

Towards Advancing Earthquake Forecasting andNowcasting: Recent Progress Using AI-Enhanced Methods[Poster Session]
Poster Session • Wednesday 1 May
Conveners: Yangkang Chen, University of Texas at Austin(yangkang.chen@beg.utexas.edu); Katsumi Hattori, Chiba
University (khattori@faculty.chiba-u.jp); Lisa G. Ludwig,
University of California, Irvine (lgrant@uci.edu); Dimitar

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Ouzounov, Chapman University (ouzounov@chapman.edu);
John Rundle, University of California, Davis (john.b.rundle@
gmail.com)
poster 149
Short-Term Earthquake Forecast Using Precursor
Phenomena
HATTORI, K., Chiba University, Chiba, Japan, khattori@faculty.chiba-u.jp
The year 2023 marks exactly 100 years since the 1923 Taisho Kanto Earthquake,
which was a massive trench earthquake that occurred in the Sagami Trough.
It is known that large-scale trench earthquakes, so-called Kanto earthquakes,
have occurred repeatedly in the Sagami Trough, and that the 1703 Genroku
Kanto Earthquake occurred, causing great damage. On the other hand, there
is also concern about an earthquake directly below the Tokyo metropolitan
area. According to the Cabinet Office, there is a 70% probability of an earthquake directly below the Tokyo metropolitan area occurring within the next
30 years. Earthquake disaster prevention measures are more focused on postevent response. The main pre-earthquake countermeasures are to strengthenbuildings and structures against earthquakes, and there is no system for active
evacuation based on prior information before a disaster occurs, as in the caseof heavy rainfall disasters in the weather, even though the occurrence of anevent is uncertain. In the case of the torrential rain disaster, the decision makers were appropriately informed of crisis avoidance actions and were able tomanage the risks. This is due to the experience of the decision makers and theaccuracy of the advance information. In the case of torrential rain disasters inJapan, typhoons and torrential rains occur somewhere every year, accumulating knowledge and insight into the spatiotemporal events before and after
the event. Observation technology has also advanced, and it is now possible
to grasp the current situation through radar images and other means. Whatabout earthquakes, on the other hand? The government’s view on prior information, except for long-term forecasts, has not been established. The timescale of large earthquakes that cause damage does not match the time scale ofhuman life, and knowledge has not been accumulated efficiently. The preparation for the earthquake directly under the Tokyo metropolitan area and the
direction of future earthquake disaster mitigation research (short-term forecasting research) will be discussed using the ULF geomagnetic field variation.
poster 150
Deep Learning for Higher-Order Aftershock Forecasting in
Near-Real-Time
MIZRAHI, L., ETH Zurich, Zurich, Switzerland, leila.mizrahi@sed.ethz.ch;
JOZINOVIĆ, D., ETH Zurich, Zurich, Switzerland, dario.jozinovic@sed.
ethz.chThe use of machine learning (ML) methods for earthquake forecasting has
recently emerged as a promising avenue, with several recent publications
exploring the application of neural point processes. Such models, in contrast to those currently applied in practice, offer the flexibility to incorporate
additional datasets alongside earthquake catalogs, indicating potential forenhanced earthquake forecasting capabilities in the future.
However, with a forecasting performance that currently remains similar to that of the agreed-upon benchmark, the Epidemic-Type Aftershock
Sequence (ETAS) model, the black-box nature of ML models poses a challenge in communicating forecasts to lay audiences.
The ETAS model has stood the test of time and is relatively simple andcomprehensively understood, with few empirically derived laws describing
aftershock triggering behavior.
A main drawback of ETAS is its reliance on large numbers of simulations of possible evolutions of ongoing earthquake sequences, which istypically associated with long computation times or resources required forparallelization.
In this study, we propose a deep learning approach to emulate the output of the well-established ETAS model, bridging the gap between traditional
methodologies and the potential advantages offered by machine learning. By
focusing on modeling the temporal behavior of higher-order aftershocks, ourapproach aims to combine the interpretability of the ETAS model with thecomputational efficiency intrinsic to deep learning.
Evaluated using commonly applied metrics of both the ML and earthquake forecasting communities, our approach and the traditional, simulationbased approach are shown to perform very similarly in describing synthetic
datasets generated with the simulation-based approach.
Our method has two major benefits over the traditional approach. It isfaster by several orders of magnitude, and it is not susceptible to being influ-

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enced by the presence (or absence) of individual `extreme’ realizations of theprocess, and thus enables accurate earthquake forecasting in near-real-time.
poster 151
Study of the b-Value Change Preceding the 2024 Noto
Peninsula Earthquake M7.6, Japan
LI, W., Chiba University, Chiba, Japan, liwenchao@chiba-u.jp; YOSHINO, C.,
Chiba University, Chiba, Japan, cyoshino@chiba-u.jp; HATTORI, K., Chiba
University, Chiba, Japan, khattori@faculty.chiba-u.jp
On January 1, 2024, an earthquake of magnitude 7.6 occurred in the Noto
Peninsula of Ishikawa Prefecture, Japan. The Noto Peninsula lies on the southeastern margin of the Japan Sea, and the northeastern tip of the Noto Peninsula
has been subject to a swarm seismic activity for the last three years, with thelargest earthquake being a Mw 6.3 event that took place in May 2023. The
Noto earthquake swarm mainly include four regions: northern, northeastern,western, and southern, and the depths are mainly distributed at 10-15km.
This study aims to investigate the statistical characteristics of seismicity ofGutenberg-Richter Law, with a focus on the b-value, an important parameter used in earthquake prediction. And we also introduce the parameter P to
examine the significance level of b-value changes in the temporal variation by
bootstrap approach with Akaike’s Information Criterion (AIC). As the selection of magnitude of completeness (Mc) in the catalog has significant impact
on the results of b-value, in this study, the maximum curvature (MAXC) technique and the bootstrap approach is applied to calculate Mc value. Then theb-value is estimated by the Aki-Utsu maximum likelihood estimation. The
anomalous increase in b-values preceding a main seismic event indicatesheightened and intensified seismic activity, reflecting the accumulation andsubsequent release of stress in the crust. This phenomenon signifies a region
where seismic occurrences become more frequent, signaling the imminent
occurrence of substantial earthquakes.
poster 152
The January 1, 2024, Noto Hanto, Japan, Mw 7.6
Earthquake as a Plausible ‘Dragon King’ Event
LIU, Y., China Earthquake Administration, Beijing, China,
liuyue126liuyue@126.com; ZHANG, Y., China Earthquake Administration,
Beijing, China, yxzhseis@sina.com; WU, Z., China Earthquake
Administration, Beijing, China, wuzl@cea-igp.ac.cn
We query whether the January 1, 2024, Noto Hanto, Japan, MW7.6 earthquake,
which punctuated the intense and long-lasting swarm, can be regarded as a‘Dragon King event’ in the perspective of ‘Dragon King’ theory. We analyzed
the earthquake catalogue from JMA since 2004 which uses MV to quantify
an earthquake and MW to quantify those events with moment tensor solutions. We inspected the frequency-magnitude distribution and generated therank-ordering plots, within a fixed spatial range around the Noto Peninsula,
to determine whether the MW 7.6 event is an outlier which significantly deviates from the power law scaling. We obtained that for the period from 2004 to
2024 the earthquake cannot be regarded as a significant ‘Dragon King’ event,while for the period from 2021 to 2024 the earthquake can be regarded significantly as a ‘Dragon King’ event. This observation seems consistent withthe report that complex precursory behavior has occurred since December
2020, implying the predictability of the ‘Dragon King’ event. We suggest thatdetailed study of this earthquake, based on the previous results of investigation, may contribute to the theory of the mechanism and prediction of a ‘seismic Dragon King’.
poster 153
Building an Enhanced Earthquake Catalogue for Aotearoa
New Zealand: Applying an Automated Workflow With
Cutting-Edge Machine Learning Methods to Mine New
Zealand’s Seismic Data
WILLIAMS, C., Victoria University of Wellington, Wellington, New Zealand,
codee-leigh.williams@vuw.ac.nz; CHAMBERLAIN, C. J., Victoria Universityof Wellington, Wellington, New Zealand, calum.chamberlain@vuw.ac.nz;
TOWNEND, J., Victoria University of Wellington, Wellington, New Zealand,john.townend@vuw.ac.nz
The New Zealand nationwide seismic catalogue produced by GeoNet is primarily focused on ensuring fast hazard communication and response. The
focus on hazard response, combined with the inconsistent nature of the New
Zealand seismograph network, can mean events are mislocated or not locatedat all. We propose and develop a cutting-edge automated workflow to generate research-grade earthquake catalogues for Aotearoa New Zealand and havebegun to apply this to New Zealand’s seismic data. This workflow expands andVolume 95•

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improves the current catalogue, enabling further research into New Zealand’s
tectonic setting and a better understanding of present-day seismic hazard. We
apply uniform identification, classification and location methods to the entire
catalogue, reducing errors and uncertainties introduced by inconsistencies in
the current catalogue.
We use the now well-tested EQTransformer AI seismic picker to efficiently and accurately detect and pick events in a uniform manor. We locate
all events using the NZWide 2.3 3D Velocity Model (Eberhart-Phillips et al.,2022), producing accurate locations and robust uncertainties. We present theresults of initial testing on five distinct regions around Aotearoa as well as
the first years of the enhanced catalogue we have produced. We find differences in manual and automatic picking to be negligible in determination of
final location for most events and that the improved velocity model with theremoval of depth fixing has a much larger influence on final location. In all test
regions, most events locate deeper than initially estimated by GeoNet, thoughsmaller changes in location are observed in more densely monitored regionswith less complex velocity structures. Future work will extend this cataloguing
through time to develop a self-consistent high-quality earthquake cataloguethat will have enhanced capabilities for capturing precursor signals importantfor earthquake forecasting across New Zealand.

Translating Seismic Imaging into Geodynamic
Understanding
Oral Session • Wednesday 1 May • 4:30 pm PacificConveners: Ebru Bozdag, Colorado School of Mines(bozdag@mines.edu); Rebecca Fildes, University ofCalifornia, Davis (rfildes@ucdavis.edu); Menno Fraters,
University of Florida (menno.fraters@ufl.edu); Lorraine J.
Hwang, University of California, Davis (ljhwang@ucdavis.
edu); Andrew Lloyd, Lamont-Doherty Earth Observatory,
Columbia University, (andrewl@ldeo.columbia.edu);
Brandon VanderBeek, Università di Padova (brandonpaul.
vanderbeek@unipd.it)
Integration of Geophysical Constraints in Global Mantle
Flow Models for Insights Into Plate Tectonics
SAXENA, A., Clemson University, South Carolina, USA, arushi@clemson.
edu; DANNBERG, J., University of Florida, Florida, USA, juliane.dannberg@
ufl.edu; GASSMOELLER, R., University of Florida, Florida, USA, rene.
gassmoeller@ufl.edu; FRATERS, M., University of Florida, Florida, USA,menno.fraters@ufl.edu
Integrating seismic imaging into geodynamic models is key to our understanding of the structure and dynamics of Earth’s interior. However, modelingthe physical processes governing mantle flow across a range of length and timescales while integrating different data sets and models still remains a challenging problem.
We here address this challenge using the example of global instantaneous
3-D mantle convection models. Our models combine (1) a heterogeneous density and viscosity distribution inferred from the LLNL-G3D-JPS tomographymodel, (2) subducted slab geometries defined using the Slab2 model (Hayes
et al., 2018), (3) weak plate boundaries from the Global Earthquake Model(GEM, Pagani et al., 2018), (4) crustal thickness from the CRUST1.0 model(Laske et al., 2012) and lithospheric thickness from Priestley et al. (2018), and(5) a recent model of the thermal structure of the lithosphere (Osei Tutu et al.,2018). We build these models in the geodynamic modeling software ASPECTin a modular fashion to allow any combination of the individual features andassociated datasets. This modular design is further supported by an interface
to the Geodynamic World Builder software, which is used to define the thousands of complex fault geometries in our models.
We vary our model parameters to optimize the fit to observed plate
velocities and to quantify the relative importance of forces and individual
datasets. We find that a low-viscosity mid-mantle layer (660–1000 km depth)
is required for slabs to effectively transfer slab pull forces to the surface plates.
Our best-fit models have plate boundaries that are 3 to 4 orders of magnitude
weaker than the surrounding lithosphere and low asthenospheric and midmantle viscosities (~1e20 Pa s). They achieve a 94% directional fit and a speed
residual of 0.7 cm/yr relative to the observed plate motion. In these models,more than three quarters of the average plate velocity is generated by slab pullalone.

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These results advance our understanding of mantle flow and can be used
as global constraints for regional studies of plate boundary dynamics and surface processes.
Immersive Insights: Visualization of Earth’s Interior in VR
and Dome Theaters
HOYLE, A. M., Colorado School of Mines, Colorado, USA, austin_hoyle@mines.edu; ORSVURAN, R., Colorado School of Mines, Colorado, USA,rorsvuran@mines.edu; GHOSH, A., Colorado School of Mines, Colorado,
USA, ayonghosh@mines.edu; YU, K., Denver Museum of Nature and Science,
Colorado, USA, kachun.yu@dmns.org; PETER, D., King Abdullah Universityof Science and Technology, Thuwal, Saudi Arabia, daniel.peter@kaust.edu.sa;
BOZDAG, E., Colorado School of Mines, Colorado, USA, bozdag@mines.edu
This project aimed to integrate three-dimensional global seismic models of
the mantle into Virtual Reality (VR) and planetarium environments. The primary focus of 3D visualization is to allow a more engaging medium in educational and public outreach activities, while promoting deep-Earth sciences.
To demonstrate the use of immersive environments in different branches andscales, we built an interactive user experience for the recent global adjoint
mantle models, i.e., GLAD-M25 (Lei et al. 2020), GLAD-M50-AZI (Bozdag
et al. in prep.), constructed based on full 3D spectral element modeling ofsynthetic seismograms and data sensitivity kernels where crust and mantle
were inverted simultaneously down to the core-mantle boundary. Focusing on
mantle plumes, we have demonstrated these models so far:1) in the VR environments with the Colorado School of Mines MathClub graduate and undergraduate students
2) at the Gates Planetarium of the Denver Museum of Nature & Scienceand the Morrison Planetarium of the California Academy of Sciences.
Our primary challenge involved the incompatibility of Paraviewformatted models with the software used for VR and many planetariums.
Taking advantage of multi-format import and export options within thesesoftware, we used a three-step pipeline. This pipeline involved transitioning
the models from Paraview as a .gltf, commonly used for scientific analysis,
to Blender, serving as an intermediary software to make corrections causedby data loss during the export process. After corrections have been made, themodel is then exported from Blender as an .fbx to be opened in Unity, thesoftware used to build VR environments, or as a .glb file for OpenSpace, avisualization software used in planetariums. The success of these demonstrations shows the versatility of our approach, making scientific data accessible
across multiple platforms, ultimately fostering interest and understanding
among diverse audiences. In coming demonstrations, in addition to plumes,
we will also highlight slabs, seismicity, anisotropy, and other potential geophysical data.
Investigating the Seismic Signature of Galápagos Mantle
Flow Models
AUTUMN, K. R., University of Oregon, Oregon, USA, kautumn@uoregon.
edu; HOOFT, E. E. E., University of Oregon, Oregon, USA, emilie@uoregon.
edu; ITO, G., University of Hawaii at Manoa, Hawaii, USA, gito@hawaii.edu;
FACCENDA, M., University of Padua, Padua, Italy, manuele.faccenda@unipd.
it; VANDERBEEK, B. P., University of Padua, Padua, Italy, brandonpaul.
vanderbeek@unipd.it; TOOMEY, D. R., University of Oregon, Oregon, USA,
drt@uoregon.edu
The Galápagos Archipelago, which lies less than 200 km south of the
Galápagos Spreading Center (GSC), provides a novel setting to study how
mantle plumes, spreading centers, and the lithosphere interact. Numerous
geophysical, geochemical, and petrologic studies have defined variations inmantle temperature and composition, as well as magma flux of the ridgeplume system. What these characteristics imply about upper-mantle rheology
and plume-to-ridge mass and heat transfer is not well understood. To address
this issue, Ito and Bianco (2014) provide two models of plume flow at the
Galápagos Archipelago that account for realistic ridge geometry of the GSC
and varying mantle structure. The first model represents a plume with low viscosity due to temperature-dependent mantle rheology. Fed by a narrow plumestem, plume mantle ponds below the thermal lithosphere and is channeled up
to and along the ridge by the sloping lithosphere. The second model represents
a plume with high viscosity in the upper mantle due to added dependence onwater content, simulating extraction of water by partial melting. A wide plumestem creates a thick plume pond that accumulates under a deeper, dehydrated
compositional lithosphere. To determine the sensitivity of teleseismic data todifferent patterns of mantle flow, this study will generate a synthetic anisotropic seismic dataset of P and S arrivals from these two models and compare theabsolute traveltime differences. Anisotropy will account for lattice-preferredorientation (LPO) of olivine crystals, which are highly anisotropic in seismic

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Seismological Research Lettersvelocity and tend to align in the direction of plastic flow. Due to LPO, mantle flow creates a strong anisotropic pattern that needs to be accounted forin seismic imaging problems. The geometry of the Marine IGUANA (2024)
experiment, consisting of 53 broadband ocean bottom seismometers deployedfor 15 months, will be used as the synthetic teleseismic array. This study will
demonstrate how the two models of plume flow can be distinguished throughtheir seismic signature to inform the interpretation of the observed Marine
IGUANA seismic data.
First Steps Towards Imaging the Antarctic’s 3D Viscosity
Structure Using GPS Observations
LLOYD, A., Columbia University, New York, USA, andrewl@ldeo.columbia.
edu; HOLLYDAY, A. E., Columbia University, New York, USA, andrewh@
ldeo.columbia.edu; POWELL, E., Columbia University, New York, USA,evelynpowell@ldeo.columbia.edu; MITROVICA, J. X., Harvard University,
Massachusetts, USA, jxm@eps.harvard.edu; GOMEZ, N., McGill University,
Montreal, Canada, natalya.gomez@mcgill.ca; LATYCHEV, K., Harvard
University, Massachusetts, USA, klatychev@gmail.com; RICHARDS, F.,
Imperial College London, London, United Kingdom, f.richards19@imperial.
ac.uk; AUSTERMANN, J., Columbia University, New York, USA, jackya@
ldeo.columbia.edu; AL-ATTAR, D., University of Cambridge, Cambridge,
United Kingdom, da380@cam.ac.uk
A critical challenge of Glacial Isostatic Adjustment (GIA) modeling is seeking a combination of mantle viscosity and ice history that satisfies existing
GIA observations. Current approaches vary in their complexity, but all fundamentally rely on solving the forward problem many hundreds of times. Thisis practical if Earth’s viscosity varies with only depth, but quickly becomes
unfeasible if lateral variations in viscosity are considered. In order to limit
the parameter space and ensure a reasonable mantle structure, researchers areinferring 3D mantle viscosity from other geophysical models, such as seismic
tomography. However, the resulting 3D viscosity inferences may not improve
the GIA model’s fit to the data because of shortcomings associated with thegeophysical models, the mapping to viscosity, the rheological model, and theice history.
We take a different approach, inspired by seismic tomography, and use
gradient-based optimization along with the adjoint method to invert solid
Earth deformation measured by Antarctic GPS stations to directly image 3D
mantle viscosity. This iterative inversion ensures that the final GIA model isconsistent with the observations. Here we focus on the setup and methodology of the inversion. First, for our starting viscosity model we adopt a 3D
viscosity inference based on the shear wave speeds of the continental andglobal tomography models ANT-20 and GLAD-M25, respectively. These
inferences are obtained using the inverse calibration scheme of Richards etal. (2020), but for ANT-20 we explore the use of additional calibration constraints to further refine the anelastic calibration parameters and also obtain a
3D inference of Q-1. Next, we examine the viscosity sensitivity kernels for solid
Earth deformation and demonstrate how differential measurements can beused to restrict the spatial extent of the kernel, allowing us to update only the
Antarctic mantle and minimize the influence of errors. Finally, results from asynthetic inversion using the potential Antarctic GPS dataset will be shown.
Instantaneous 3D Tomography-Based Convection and Melt
Generation Beneath the Rungwe Volcanic Province, East
AfricaNJINJU, E. A., University of California, Davis, California, USA, eanjinju@
ucdavis.edu; STAMPS, D., Virginia Tech, Virginia, USA, dstamps@vt.edu;
ATEKWANA, E. A., University of California, Davis, California, USA,eaatekwana@ucdavis.edu; ROONEY, T., Michigan State University, Michigan,
USA, rooneyt@msu.edu; RAJAONARISON, T. A., New Mexico Institute of
Mining and Technology, New Mexico, USA, tahiry.rajaonarison@nmt.edu
Within the Western Branch of the East African Rift (EAR), volcanism is highly
localized, which is distinct from the voluminous magmatism seen throughout
the Eastern Branch of the EAR. We hypothesize that the interaction of plumematerial with the base of the continental lithosphere enables the localizationof melt beneath the Western Branch to regions where there are sharp variations in lithospheric thickness. To test our hypothesis, we investigate sublithospheric mantle flow and melt generation beneath the Rungwe Volcanic
Province (RVP), which is the southernmost volcanic center in the Western
Branch. We use seismically constrained lithospheric thickness and sublithospheric mantle structure to develop an instantaneous 3D thermomechanicalmodel of tomography- based convection (TBC) with the physics for melt
generation beneath the RVP using ASPECT. Shear wave velocity anomalies
suggest excess temperatures reach ~250 K beneath the RVP. We use the excess
temperatures to constrain parameters for melt generation beneath the RVP

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and find that partial melt develops at a maximum depth of ~140 km. Our
TBC model suggests that upwellings from a thermally heterogeneous asthenosphere distributes and localizes deep melt sources beneath the Western
Branch in locations where there are sharp variations in lithospheric thickness.
Even in the presence of a uniform lithospheric thickness in our TBC models,
we still find a characteristic upwelling and melt localization beneath the RVP,
which suggests that sublithospheric heterogeneities exert a dominant control
on upper mantle flow and melt localization in this region. Our TBC models
demonstrate the need to incorporate upper mantle constraints in mantle convection models.

Translating Seismic Imaging into Geodynamic
Understanding [Poster Session]
Poster Session • Wednesday 1 May
Conveners: Ebru Bozdag, Colorado School of Mines(bozdag@mines.edu); Rebecca Fildes, University ofCalifornia, Davis (rfildes@ucdavis.edu); Menno Fraters,
University of Florida (menno.fraters@ufl.edu); Lorraine J.
Hwang, University of California, Davis (ljhwang@ucdavis.
edu); Andrew Lloyd, Lamont-Doherty Earth Observatory,
Columbia University, (andrewl@ldeo.columbia.edu);
Brandon VanderBeek, Università di Padova (brandonpaul.
vanderbeek@unipd.it)
poster 161
Guiding Deep Earthquake Investigation with Subduction
Modeling: Is Thermal Shear Instability Viable in the DeepSlab?
FILDES, R. A., University of California, Davis, California, USA, rfildes@
ucdavis.edu; BILLEN, M. I., University of California, Davis, California, USA,mibillen@ucdavis.edu; THIELMANN, M., University of Bayreuth, Bayreuth,
Germany, Marcel.Thielmann@uni-bayreuth.de
The processes that lead to deep (>70 km) earthquake failure in subducting
lithosphere are an ongoing investigation. The high pressures and temperatures in sinking slabs at these depths inhibit the brittle failure mechanism
understood for shallow earthquake failure. It is currently proposed that deep
earthquakes occur through dehydration embrittlement, transformational
faulting, and/or thermal shear instability (TSI). It was proposed recently
that strain-rate variations, in addition to temperature, control where deep
earthquakes can occur: high strain-rate regions in cold portions of the slab.
However, this high strain-rate constraint hypothesis was not tested using
location-specific subduction modeling, nor did it differentiate between proposed failure mechanisms. Here we present a new methodology that links
location-specific geodynamic subduction modeling with TSI modeling andearthquake observations to investigate the viability of TSI initiating at deep
slab conditions. Subduction model slab geometries are constructed for a specific location based on seismic tomography and observed seismicity. These 2D
location-specific dynamic visco-elastic-plastic subduction models are used todetermine deep slab physical conditions (strain-rate, stress, temperature, andpressure). These location-specific models allow for a more direct comparison
to observations as the results are compared with the deep earthquake observations for the same profile the model was based on. The physical conditions
found in regions overlapping with observed seismogenic regions of the slab
are extracted from the subduction model and used as the initial conditions
in a separate TSI model to test whether TSI can initiate or not at these conditions. This methodology of using the subduction modeling as a lens to guidethe investigation of TSI viability extends the depth range of conditions that
TSI has been investigated under before. The location-specific subduction
modeling is a step forward in constraining the conditions required for deep
earthquake rupture and could be similarly used to investigate other proposed
deep earthquake failure mechanisms.
poster 162
Seismic Imaging of the Mendocino Triple Junction:
Unraveling the Geodynamics of a Fundamental Plate
Boundary Transition
FURLONG, K. P., Pennsylvania State University, Pennsylvania, USA, kpf1@
psu.edu; MCKENZIE, K. A., University of North Carolina at Chapel Hill,

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North Carolina, USA, kmckenzie@unc.edu; HERMAN, M. W., California
State University, Bakersfield, California, USA, mherman2@csub.edu;
BENZ, H. M., U.S. Geological Survey, Colorado, USA, benz@usgs.gov;
VILLASEÑOR, A., Institute of Marine Sciences, Barcelona, Spain, antonio.
villasenor@csic.es
The Mendocino Triple Junction (MTJ) demarcates the fundamental change
along the North American plate boundary from subduction (Cascadia) totranslation (San Andreas). This plate boundary transition initiates the lithospheric shear zone that develops into the San Andreas plate boundary system.
It is one of the most seismogenic regions of North America and a location ofabrupt changes in topography and relief. Over the past several decades ourunderstanding of the tectonics intrinsic to this transition has advanced, but
key questions about the structure and deformational processes at the MTJ
remain. Our new regional tomography of the MTJ region allows us to better
constrain the crust-upper mantle structure and its relationship to the abundant seismicity, and therefore interpret the main controls on San Andreas
plate boundary formation. The high-resolution of the tomography (3 km x 3
km x 0.5 km) allows us to clearly differentiate among the 3 primary components of the plate boundary system - the subducting Gorda Slab, the North
American crust (composed of the Franciscan, Klamath, and Great Valley terranes), and the Pacific plate (including a fragment that extends inland under
the North American crust). We also image the upwelled mantle within the slab
window. Additionally, we observe significant variations in crustal thickness
within the overlying North American crust, associated with the migration of
the MTJ and slab window. Using this new image of the crust-upper mantle
structure in northern California we can interpret that much of the on-shoreand near-shore seismic activity in the region (including most of the larger
events) occurs within the overlying North American crust near or above theslab interface, rather than within the subducting slab. Additionally, this imagery indicates significant variations in crustal thickness of the overlying North
American crust, associated with the migration of the MTJ and slab window.
poster 163
Image of Crust and Upper Mantle of Ne India Based on
Surface Wave Tomography
MUKHOPADHYAY, S., Indian Institute of Technology Roorkee, ROORKEE,
India, sagarfes@gmail.com; KUMAR, N., Wadia Institute of Himalayan
Geology, Dehradun, India, nkumard12@gmail.com; KUMAR, A., National
Centre for Polar and Ocean Research, Vasco Da Gama, India, akiitkgp08@
gmail.com; CHANU, M. N., Indian Institute of Geomagnetism, Shillong,
India, menaka01021993@gmail.com
The Indian Plate (IP) present below the Shillong Plateau (SP) and Mikir Hills(MH) is buckled up. It is because it is in a vice-like grip between the Eastern
Himalayas (EH) to its North, below which it is underthrusting, and the IndoBurma Ranges (IBR) to its East, below which it is subducting. A thick layer of
sedimentary rock is present in the Bengal Basin (BB). Its thickness varies from~10 km to ~20 km from West to East. The E-W trending Dauki fault separates it from the high-velocity Precambrian rocks present at shallow depthsof the SP. The Dauki Fault and the Eastern Hinge Zone (EHZ) demarcate
the northern and western boundaries of the oceanic crust present below theBB from the continental crust to its North and West. Sediments are getting
underthrusted in the southern part of the IBR. The Moho depth varies bothalong and across the trend of the EH. We opine that the along-trend variation is caused by the anticlockwise rotation of the continental part of the IP
after it first collided with the Eurasian Plate (EP) on the western side. Suchrotation has caused crumpling of the crust of the Himalayas along its entire
length. Average Moho depth increases from entire length. Average Moho
depth increases ~40 km in the south to ~70 km in the northern part of thestudy area smoothly in most places but abruptly at other places. The underthrusting process of the IP below the EP varies from place to place. Below the
Nepal Himalayas repeated underthrusting and overthrusting are observed. In
some parts of NE India, it appears that the IP has broken and a new front ofunderthrusting is developing. In the Brahmaputra River Valley, 5–6 km thicksedimentary layers are present. However, the north of the SP and the MH
sedimentary layer is very thin. The Moho depth decreases from ~70 km westof the Yadong-Gulu rift to ~60 km toward the east which may be the effect ofcollision geometry to control the underplating of the IP in this section of LB.
Several low-velocity bodies are observed in the mid-to-lower crust of the LB,
mostly below the N-S trending rift zones indicating the presence of partial
melts or fluid-filled fracture zones.

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poster 164
Transdimensional Mt. Etna Volcano P-Wave Anisotropic
Seismic Imaging
DEL PICCOLO, G., Università di Padova, Padova, Italy, gianmarco.
delpiccolo@phd.unipd.it; LO BUE, R., Università di Padova, Padova, Italy,
rosalia.lobue@unipd.it; VANDERBEEK, B. P., Università di Padova, Padova,
Italy, brandonpaul.vanderbeek@unipd.it; FACCENDA, M., Università di
Padova, Padova, Italy, manuele.faccenda@unipd.it; COCINA, O., Istituto
Nazione di Geofisica e Vulcanologia, osservatorio etneo, Catania, Italy, ornella.
cocina@ingv.it; FIRETTO CARLINO, M., Istituto Nazione di Geofisicae Vulcanologia, osservatorio etneo, Catania, Italy, marco.firettocarlino@
ingv.it; GIAMPICCOLO, E., Istituto Nazionale di Geofisica e Vulcanologia,
osservatorio etneo, Catania, Italy, elisabetta.giampiccolo@ingv.it; MORELLI,A., Istituto Nazionale di Geofisica e Vulcanologia, sezione Bologna, Bologna,
Italy, andrea.morelli@ingv.it; BYRNES, J. S., Northern Arizona University,
Arizona, USA, joseph.byrnes@nau.edu
Transdimensional inference identifies a class of methods for inverse problems
where the number of free parameters is not fixed. In seismic imaging thesemethods are applied to let the data decide the complexity of the models andhow the inferred fields partition the inversion domains. Monte Carlo transdimensional inference is performed implementing the reversible-jump Markov
chain Monte Carlo (rjMcMC) algorithm; the nature of Monte Carlo exploration allows the algorithm to be completely non-linear, to explore multiple
models with different dimensions and meshes and to investigate the underdetermined nature of the tomographic problems. Implementations of thismethod overcome the main limitations of traditional linearized solvers: thearbitrariness in the selection of the regularization parameters, the linearized
iterative approach and in general the collapse of the information behind thesolution into a unique inferred model. We present applications of the rjMcMC algorithm to anisotropic seismic imaging of Mt. Etna using P-waves. Mt.
Etna is one of the most active and monitored volcanoes in the world, typically investigated under the assumption of isotropic seismic speeds. However,since body waves manifest strong sensitivity to seismic anisotropy, we parametrize a multi-fields inversion to account for the directional dependence in theseismic velocities. Anisotropy increases the ill-condition of the tomographic
problems and the consequences of the under-determination are more relevant. When multiple seismic fields - such as speed anomalies and anisotropy- are investigated, the data-sets used may not be able to independently resolve
them, resulting in non-independent estimates and corresponding trade-offs.
Monte Carlo exploration allows for the evaluation of the robustness of seismic anomalies and anisotropic patterns, as well as the trade-offs between
isotropic and anisotropic perturbations, key features for the interpretation of
the tomographic models. The approach is completely non-linear, free of any
explicit regularization and it keeps the computational time feasible, even forlarge data-sets.
poster 165
Ecoman 2.0: An Open-Source Software for Exploring theConsequences of Mechanical Anisotropy in the Mantle.
FACCENDA, M., Università di Padova, Padova, Italy, manuele.faccenda@
unipd.it; VANDERBEEK, B. P., Università di Padova, Padova, Italy,
brandonpaul.vanderbeek@unipd.it; DE MONTSERRAT, A., ETH Zurich,
Zurich, Switzerland, albertdemontserratnavarro@erdw.ethz.ch; YANG, J.,
Chinese Academy of Sciences, Beijing, Colombia, jianfengyang1989@gmail.
com
In this contribution we introduce ECOMAN 2.0, an open-source software
package for (1) modelling the strain-/stress-induced rock fabrics and related
mechanical anisotropy, and (2) performing isotropic and anisotropic inversions using real/synthetic P- and S-wave travel-times and S-wave splitting
parameters.
The strain-induced intrinsic mantle fabrics are modelled inputting thevelocity, pressure, temperature and dominant creep mechanism fields fromlarge-scale mantle flow simulations into D-Rex (Kaminski et al., 2004). This
open-source software has been parallelized using a hybrid MPI and OpenMP
scheme and modified to account for combined diffusion-dislocation creep
mechanisms, LPO of transition zone and lower mantle polycrystalline aggregates (Wadsleyite, Bridgmanite, post-Perovskite), P-T dependence of single
crystal elastic tensors, advection and non-steady-state deformation of crystal
aggregates in 2D/3D cartesian/spherical grids (Faccenda, 2014; Faccenda andCapitanio, 2013).
Extrinsic elastic anisotropy due to grain- or rock-scale fabrics or fluidfilled cracks can also be estimated with the Differential Effective Medium(DEM) (Faccenda et al., 2019). Similarly, extrinsic viscous anisotropy can be

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Seismological Research Lettersmodelled yielding viscous tensors to be used in large-scale mantle flow simulations (de Montserrat et al., 2021).
The elastic tensors can then be interpolated in a tomographic grid for (i)visual inspection of the mantle elastic properties (such as Vp and Vs isotropic
anomalies; radial, azimuthal, Vp and Vs anisotropies), (ii) generating input
files for large-scale synthetic waveform modelling (e.g., SPECFEM3D format),or (iii) P- and S-wave isotropic and anisotropic inversions (e.g., Faccenda andVanderBeek, 2023). The latter can be performed with the new PSI (Platform
for Seismic Imaging) module, which includes recently developed techniques
for seismic anisotropic inversions of body waves (VanderBeek and Faccenda,
2021; VanderBeek et al., 2023).

Understanding and Quantifying the Variability in
Earthquake Source Parameter Measurements
Oral Session • Friday 3 May • 8:00 am PacificConveners: Rachel E. Abercrombie, Boston University (rea@bu.edu); Shanna Chu, U.S. Geological Survey (schu@usgs.
gov); Sydney Gable, University of Michigan (gablesyd@umich.edu); Gene Ichinose, Lawrence Livermore National
Laboratory (ichinose1@llnl.gov); Colin N. Pennington,
Lawrence Livermore National Laboratory (pennington6@llnl.
gov)
Estimating Seismic Attenuation, Site Corrections andGeometrical Spreading From Large Seismic Catalogues
Using Linearized Spectral Ratios and Regression
Regularization Paths
LAPINS, S., University of Bristol, Bristol, United Kingdom, sacha.lapins@
bristol.ac.uk
Estimating source parameters from earthquake signals requires discriminating source properties (e.g. corner frequency and radiation pattern) from path,site and geometrical spreading effects. Commonly used seismic source models incorporate nonlinear combinations of these terms, making it challenging to estimate and isolate these effects from individual event spectra. Here, I
present a linearized spectral ratio approach for simultaneously estimating all
non-source-dependent terms (i.e. quality factor Q, geometrical spreading, andsite-specific κ / average corrections) from large catalogues of low-magnitude(M<3) seismicity. Inter-station spectral ratios are used to cancel the cornerfrequency term from source model equations, leaving only the contributionof path, site and spreading effects to estimate. Large systems of linearized
spectral ratio equations are then constructed for subsequent regression, eachincorporating many events (e.g. 50–100 events) and all available pairwise station combinations. An iterative regularized regression procedure is then used,
where the strength of the parameter regularization is gradually annealed tozero, encouraging the regression algorithm to first estimate ‘global’ site andspreading terms before estimating the more variable Q attenuation terms foreach source-receiver pair. Lastly, distributions are generated for maximum
likelihood estimates of each term by repeatedly applying this approach tosubsets of large seismic catalogues, providing more robust final estimates anduncertainty quantification.
I demonstrate this approach on a machine-learning-derived catalogue
of seismicity from Nabro volcano in Eritrea, comprising nearly 34,000 events.
The resulting estimates are compared against some commonly assumed values (e.g. for average radiation pattern and geometrical spreading) and otherinferred geophysical properties at Nabro, providing interesting insights into
the subsurface properties beneath this volcano. The results also highlightimportant considerations regarding the use of ‘textbook’ values and assumptions of frequency (in)dependence for some source model parameters.
Extraction of Source Parameters for French Seismicity
Based on a Radiative Transfer Approach: Importance for
Attenuation and Site Corrections
HELLER, G., CEA, Arpajon, France, greg68heller@hotmail.fr; SÈBE, O.,
French Alternative Energies and Atomic Energy Commission, Arpajon,
France, olivier.sebe@cea.fr; MARGERIN, L., Université Paul Sabatier
Toulouse, Toulouse, France, ludovic.margerin@irap.omp.eu; TRAVERSA,P., Électricité de France, Aix-en-Provence, France, paola.traversa@edf.fr;
MAYOR, J., Électricité de France, Aix-en-Provence, France, jessie.mayor@edf.

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fr; CALVET, M., Université Paul Sabatier Toulouse, Toulouse, France, marie.
calvet@cea.fr
An accurate magnitude estimation is necessary to evaluate properly the seismic hazard. Unfortunately, magnitudes of small earthquakes are subject tolarge uncertainties due to high-frequency propagation effects, which are generally not accurately considered. To address this issue, we developed a method
to separate source, attenuation and site parameters from the elastic radiativetransfer modeling of the full energy envelopes of seismograms. Our separation method is based on a 2-step inversion procedure. First, for each sourcestation pair, we retrieve optimal frequency-dependent attenuation parameters
fitting the observed energy envelopes in the 0.375-24Hz band. In a second
step, we separate the source spectra and the site amplification relative to (1)the network of stations and (2) a selection of stations showing small amplification (characterized by approximatively flat H/V ratios). From the source spectra, we estimate the moment magnitude Mw, the corner frequency fc and thestress-drop ∆σ. We applied the inversion procedure to more than 16000 waveforms recorded by EPOS-FR stations from 662 earthquakes of magnitudes
Mw ranging from 2.0 to 5.0. We show that the choice of the reference in site
amplification affects in a critical manner source parameters (Mw, fc and ∆σ),highlighting the necessity of a careful selection of the source-site separation
criteria minimizing site amplification bias on the estimated seismic source.
More specifically, we observe an increase of ∆σ with Mw if the site amplification is determined relatively to the whole network of stations. However, if
the site amplification is relative to selected stations with approximatively flat
H/V ratios, ∆σ does not scale with Mw. The resulting magnitudes are compared to existing Mw catalogues in France (Si-Hex, FMHEX-22, Buscetti etal. SSA meeting). The role of attenuation maps is explored according to thestabilization of the site and source terms separation. In the future, we intend
to automate our method and apply it routinely to smaller earthquakes forwhich traditional methods are not readily applicable due to the complexityof waveforms.
A Joint Inversion Method for Computing Earthquake Stress
Drop With Spectra and Spectral Ratios
GUO, H., University of Wisconsin-Madison, Wisconsin, USA, hao.guo@wisc.
edu; THURBER, C. H., University of Wisconsin-Madison, Wisconsin, USA,cthurber@wisc.edu
Earthquake stress drop is fundamentally important for understanding theearthquake rupture process, fault strength, and assessing seismic hazard. It
is commonly calculated with corner frequency, measured from earthquake
spectra, assuming a simple circular rupture model. One significant source oferror in determining stress drop in this way is the trade-off between sourceand path attenuation parameters. To address this issue, we have developed a
new method that uses earthquake spectra and spectral ratios to jointly invert
source and path attenuation parameters. Our synthetic tests show that thismethod can effectively mitigate the trade-off between corner frequency andthe attenuation parameter. We have been applying this method to analyze
earthquakes in the San Francisco Bay Area. In the Bay Area, depth dependence of stress drop was observed in a previous study, but may be due todepth-varying attenuation. Our method accounts for attenuation variations
and our preliminary analysis of a set of earthquakes along the northern
Hayward Fault shows no depth dependence. We will further assess the data
bandwidth requirement for avoiding bias in corner frequency and stress drop.
Earthquake Source Parameter Analysis Using Peak Narrow
Band Displacement Amplitudes
KNUDSON, T., Stanford University, California, USA, trey05@stanford.edu;
ELLSWORTH, W. L., Stanford University, California, USA, wellsworth@stanford.edu; BEROZA, G. C., Stanford University, California, USA, beroza@
stanford.edu; SHAW, B. E., Columbia University, New York, USA, shaw@ldeo.
columbia.edu
We present a source parameter analysis of nearly 13,000 earthquakes in the2019 Ridgecrest sequence as part of the SCEC Stress Drop Validation Study.
We measure an apparent spectrum defined as the maximum amplitude of the
S-wave displacement seismogram after it is passed through a series of bandpass filters. From each seismogram we extract 17 peak amplitude measurements in half-octave bands between 0.125 and 46 Hz. The apparent spectrum
is defined by the half-octave peak amplitudes. Given an S-wave arrival foreach event, this workflow is fully automated and reproducible. We compare
two different methods which use these spectra to measure stress drops.
In the first method, we obtain the source spectrum by applying corrections for site and path effects using a frequency-dependent distance correction based on Richter’s local magnitude relation (-log(A0)). Our frequency-

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dependent attenuation relations account for geometric spreading, attenuation,and local site amplification. We fit an omega-squared Brune model to themedian spectrum from all observing stations to obtain the moment and corner frequency for each event. In the second method, we take spectral ratios
for close pairs of events to isolate the source effects. We employ the asymptotic spectral ratio method to measure relative stress drops using the high andlow frequency levels. This has the benefit that we don’t need to resolve cornerfrequency, which also means we can compare earthquakes of similar magnitude. Using an inversion with all possible earthquake pairs, we compare relative stress drops to our first method. We find that moment magnitude can bereliably measured using both methods for earthquakes at least as small as Mw
1.0. We find an average stress drop of 3.3 MPa and a clear increase in average
stress drop with magnitude.
Three Years of the International SCEC/USGS Community
Stress Drop Validation Study: What Have We Achieved andWhere Next
ABERCROMBIE, R. E., Boston University, Massachusetts, USA, rea@bu.edu;
BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@usgs.gov;
CHU, S., Rice University, Texas, USA, sc273@rice.edu; TAIRA, T., Universityof California, Berkeley, California, USA, taira@berkeley.edu
The SCEC/USGS Community Stress Drop Validation study has engaged awide international community since its launch in 2021. The broad aim of thecollaboration is to improve the quality of estimates of stress drop and related
fundamental earthquake source parameters (corner frequency, source duration, etc.) and their uncertainties, to enable more reliable ground motion forecasting, and to obtain a better understanding of earthquake source physics.
Seismological estimates of stress drop from earthquake spectral measurements
have become standard practice over the last 50 years, but their wide variability,
model dependence and inconsistency between studies have led to controversy
and concerns about how to assess and interpret these measurements.
We present the findings of the community comparative analysis of acommon data set of earthquakes in the 2019 Ridgecrest, California, sequence,focusing on what we have learnt about assessing the accuracy and stabilityof different estimates. We also discuss the development of plans for the nextstage of this community endeavor in which we aim to work towards providing
the optimal characterization of earthquake source parameters for the various
user communities. This will likely include a community experiment involving model-generated synthetic data. We welcome new members to the study,
wishing to observe, learn or more actively participate; more information canbe found at https://www.scec.org/research/stress-drop-validation.
Understanding the Contribution of Site Effects to
Variability in Microearthquake Source Parameter
Measurements Using a Large, Dense Array in Oklahoma
CHANG, H., Massachusetts Institute of Technology, Massachusetts, USA,hilarych@mit.edu; ABERCROMBIE, R. E., Boston University, , USA, rea@bu.edu; NAKATA, N., Lawrence Berkeley National Laboratory, , USA,nnakata@lbl.gov; QIU, H., China University of Geosciences, Wuhan, China,
qiuhongrui@cug.edu.cn; ZHANG, Z., Chinese Academy of Sciences, Beijing,
China, zdzhang@mail.iggcas.ac.cn; PENNINGTON, C. N., Lawrence
Livermore National Laboratory, , USA, pennington6@llnl.gov; KEMNA,
K. B., Ruhr University Bochum, Bochum, Germany, kilian.kemna@rub.
de; COCHRAN, E. S., U.S. Geological Survey, , USA, ecochran@usgs.gov;
HARRINGTON, R. M., Ruhr University Bochum, Bochum, Germany,
rebecca.harrington@ruhr-uni-bochum.de
Untangling whether the wide variability of estimated source parametersindicates real source property variation, or relates to measurement uncertainty and bias, is a challenging yet important task. When predicting groundmotions and modeling earthquake source spectra, the effects of the shallowest, highly attenuating and low velocity layers play an outsize role. Simplifying,or neglecting, the near-surface attenuation and velocity structure in modeling
may lead to bias or uncertainties due to parameter tradeoff. We investigate
the source parameter variability for microearthquakes recorded beneath thedense 1820 station, Large-N Seismic Survey in Oklahoma to understand therelative influences of sediment depth and surficial deposits on earthquake
source parameters and ground motions. We observe large variations in source
parameters (a factor of 2 for corner frequency) and ground motions (over afactor of 3 of site-amplification) at different stations, despite the low-relief andrelatively flat basin basement depth. We take advantage of the dense station
coverage to obtain the velocity and attenuation structure in the top 0.5 km andcompare them with the corner frequency and ground motion measurements.
Despite the smooth lateral structural changes at depth, the near-surface siteattenuation varies significantly across the array with the range of variation

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exceeding the travel-time-dependent attenuation. Known local Quaternary
alluvium and glacial-related shallow deposits play a significant role in absorbing the high frequency energy despite the waves spending a relatively small
portion of travel time in these formations. We show that not recognizing thesite-attenuation can (1) cause site-dependent source parameter measurements, (2) produce tradeoff between the corner frequency, the quality factor
Q, and the spectral falloff parameter n, which result in significant variation
between estimates at nearby stations. Our work shows the importance ofconsidering laterally varying site effects when measuring source parameters
even within a region with seemingly simple structure with little topographic
change.
Demystifying Earthquake Stress Drop Discrepancies Using
Synthetic Source Time Functions
NEELY, J. S., University of Chicago, Illinois, USA, jamesscottneely@gmail.
com; PARK, S., University of Chicago, Illinois, USA, sunnypark@uchicago.
edu; BALTAY, A. S., U.S. Geological Survey, California, USA, abaltay@usgs.
gov
We evaluate how well simple, commonly used stress drop estimation methods
recover known stress drops of synthetic, complex ruptures, constructed by
combining multiple simple kinematic source models. Earthquake stress drop
is a commonly estimated parameter that can provide insight into both earthquake source physics and the resulting ground motion. Stress drop methods usually assume that earthquakes are a symmetric circular crack which
release their energy in a single pulse with a simple source time function (STF).
Real earthquakes, however, often have complex STFs with multiple pulses ofseismic moment release, and studies have shown that stress drop estimates
contain significant uncertainties. We also have limited knowledge of the subsurface structure of the earth and its impact on the observed waveforms, so
recovering the original earthquake signal requires additional assumptions ofmaterial properties and path attenuation.
Therefore, in this study, we seek to investigate how the complexity ofearthquakes and different signal deconvolution assumptions can bias two
common stress drop estimates—the time-domain method (i.e., estimating
rupture duration) and the spectral, frequency-domain method (i.e., estimating corner frequency). We create a synthetic catalog of complex rupture earthquakes (combining multiple simple, circular-crack models with known static
stress drops), quantify their complexity, and estimate their stress drop. We
first assess how accurate the estimation methods are for complex earthquakes
when the rupture process is perfectly known. We then convolve the synthetic
earthquakes with a known Earth model to simulate propagation effects andapply different deconvolution techniques (assuming no knowledge of the truemodel) to recover the source signal and estimate stress drop. This analysis willallow researchers to better assess the potential bias and uncertainty of stressdrop estimates for real earthquakes due to both rupture complexity and theeffects of deconvolution techniques meant to remove propagation effects.
Variable High Frequency Radiation From Complex
Laboratory Ruptures Due to a Normal Stress Bump
CEBRY, S. B. L., Cornell University, New York, USA, sarabethleach@gmail.
com; MCLASKEY, G. C., Cornell University, New York, USA, gcm8ster@gmail.com
Fault heterogeneities such as roughness, stepovers, and other irregularities are
known to affect the spectra of radiated waves during an earthquake, and may
therefore affect earthquake source parameters such as stress drop. To investigate the effect of normal stress heterogeneity on the earthquake spectra, we
produced a series of ruptures on a 0.74 m PMMA laboratory fault with a single, localized bump of increased normal stress. By varying the bump prominence (defined here as the increase in the normal stress on the bump divided
by the average normal stress across the entire fault), we produced earthquakelike ruptures that ranged from smooth, continuous, sample-spanning ruptures to complex ruptures with variable rupture propagation velocity, slip
distribution, and stress drop. Vertical ground motions were measured using
an array of eight piezoelectric sensors calibrated using a ball drop technique.
Radiated seismic waves were strongly affected by the bump prominence.
High prominence bumps produced complex events that radiated more highfrequency energy, relative to low frequency energy, than continuous events
without a bump. In complex ruptures, the high frequency energy showed significant spatial variation in amplitude and timing while continuous ruptures
emitted spatially uniform bursts of high frequency energy. Near field peakground acceleration (PGA) measurements of complex ruptures show nearly
an order of magnitude higher PGA near the bump than on the rest of the fault.
We expect a similar phenomenon to occur in the earth. We propose that for
natural faults, fault geometric heterogeneities, such as roughness or stepovers,

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may act as earthquake gates and can be a spatially heterogeneous source ofenhanced high frequency radiation. This may be a plausible explanation forcommonly observed order of magnitude variations in near-fault PGA such as
during the 2023 Turkey Mw 7.8 and 7.6 earthquakes.
Source Parameter Scaling Relations for Shallow Crustal
Earthquake with a Simple Heterogeneous Source Model
SHIMMOTO, S., University of Tokyo, Bunkyo-ku, Japan, shimmoto@eri.utokyo.ac.jp
In this study, the source parameters of shallow crustal earthquakes (Mw
3.2–6.0) were estimated in Japan by the spectral ratio method developed by
Shimmoto (2022). This spectral ratio method estimates the finite source properties of a homogeneous rectangular source model. Since the rupture area estimated from this spectral ratio method corresponds to the localized rupturearea with large slip, the stress drop was calculated using a simple heterogeneous source model with a single localized area with a concentrated stressdrop. We usually estimate the stress drop of small-to-moderate earthquakes
with the corner frequency method. In this method, we need to determine a
constant (the k value) to relate the corner frequency to the source radius byassuming a source model. However, the stress drop values can differ significantly depending on the source model selection. This study addressed thisissue by calibrating an appropriate average k value by comparing the stressdrop estimated from the S-wave corner frequency to the stress drop estimatedfrom the method proposed by Shimmoto (2022). This study also found thatthe k value can vary considerably for different events. The k value variability
contributes to the potential stress drop uncertainty.
The scaling relations of stress drop, apparent stress, radiation efficiency,
and fracture energy were compiled over a broad magnitude range by combining the source parameter results of this and previous studies. The calibrated kvalue was applied to re-calculate the stress drops of small earthquakes analyzed
in previous studies. The stress drop and apparent stress increase with increasing magnitude up to Mw ~5 and become constant for larger magnitudes. The
radiation efficiency is independent of magnitude and typically ranges from 0.1
to 1.0. The slip dependencies of the source parameters compiled in this study
can be explained consistently by the ones predicted from the slip-weakening
model incorporating the thermal pressurization effect by Rice (2006).
Reducing the Uncertainty of Stress-Drops
KURZON, I., Geological Survey of Israel, Jerusalem, Israel, ikurzon@icloud.
com; LYAKHOVSKY, V., Geological Survey of Israel, Jerusalem, Israel,
vladimir.lyakhovsky@gmail.com; SAGY, A., Geological Survey of Israel,
Jerusalem, Israel, asagy@gsi.gov.il
Stress-drop defines the overall reduction of average stress due to the releaseof stresses due to an earthquake, and should reflect geometrical, rheologicaland dynamic properties of the seismic source. Its variability up to four-orders
made it an enigmatic parameter, and a reason for extensive research. There
have been many efforts to reduce the stress-drop uncertainty, and to perceive
better understanding of the factors controlling its variability. These efforts
focused mainly on observational aspects, in which source properties suchas, corner-frequency and seismic moment, were measured, considering site,
path and additional source properties. Another aspect, that has hardly been
pursued, is to challenge the formulation applied for stress-drop calculation.
One of the basic assumptions is a constant K coefficient, relating corner-frequency with geometrical dimensions of the source. We suggest an alternative
formulation, based on the results of dynamic modelling, in which the K coefficient is not constant and increases with strain-drop (ratio between slip andsource length), resulting in a new equation relating stress-drop with seismic
moment and corner-frequency. While for a constant K coefficient, stress-dropis proportional to a cubed corner-frequency, for the strain-drop dependent K,
stress-drop is proportional to the corner-frequency in a power of 4/3, reducing the impact of corner-frequency uncertainty on the stress-drop. Therefore,
our stress-drop formulation, significantly lowers the stress-drop uncertainty,
and shows better fit to field observations. Using the new formulation, we showthat the stress-drop values range between 5-25 MPa, for dynamic rupture
events with a wide range of seismic moments, and corner-frequencies.
Constraining Source Parameters of Seismic Events
Generated by Circular Gouge Patches on 4-meter-long
Laboratory Fault
OKUBO, K., National Research Institute for Earth Science and Disaster
Resilience, Tsukuba, Japan, kokubo@bosai.go.jp; YAMASHITA, F., National
Research Institute for Earth Science and Disaster Resilience, Tsukuba, Japan,

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yamafuto@bosai.go.jp; FUKUYAMA, E., Kyoto University, Kyoto, Japan,
fuku@bosai.go.jp
The mechanics of the dynamic earthquake ruptures are investigated withthe friction law applied to the fault. The source size, the stress drop, and theenergy budget of the ruptures help us to configure it. The source size is usually estimated with the corner frequency of the radiation via source models
such as Brune (1970) or Madariaga (1976). However, the models assume therupture propagation on the circular patch with a given rupture velocity and ashear wave velocity, which causes a bias in the estimation of the source parameters. In this study, therefore, we control the size and shape of the source byartificially setting thin circular gouge patches on the laboratory fault such that
we constrain the energy budget and the friction law without using predefinedsource models.
We used the 4-meter-long biaxial rock friction apparatus to conduct the
stick-slip experiments with the macroscopic normal stress of 2.0MPa. We set
seven gouge patches with a diameter of 8mm on the fault. We preliminarily
measured the enhanced normal stress on the gouge patch, showing 4.5MPa on
average with the background stress of 2.0MPa. The seismic events are observed
during the propagation of the preslip towards the mainshock, most of whichcorrespond to the location of the gouge patches. We first fit the numericallycomputed waveforms to one of the seismic events and obtained its seismic
moment as 0.31Nm (Mw=-6.4). Given the ruptured size is equivalent to thegouge patch, we obtained the average slip of 0.16μm, the stress drop of 2.1MPa,and the seismic efficiency of 0.17, which are in reasonable ranges concerning
the amount of preslip on the simulated fault and the normal stress on thepatch. However, the observed seismic efficiency was significantly smaller thanthe estimation from Brune’s source model even though the model provides abetter fit on the source size with the best-fit source duration to the gouge patch
size. This study aims to contribute to clarifying such discrepancies by investigating the possible stress and frictional conditions on the controlled patch tocause the ruptures reproducing the observed AE waveforms.
Constraining the Rupture Extent of Mw 6--7 Intraslab
Earthquakes Using Geodetic Data: The 110 Km Deep 2020
Calama Earthquake, Northern Chile
CRAIG, T. J., University of Leeds, Leeds, United Kingdom, t.j.craig@leeds.
ac.uk; LIU, F., University of Leeds, Leeds, United Kingdom, eefl@leeds.ac.uk;
EBMEIER, S., University fof Leeds, Leeds, United Kingdom, s.k.ebmeier@leeds.ac.uk; ELLIOTT, J., University of Leeds, Leeds, United Kingdom,
j.r.elliott@leeds.ac.uk
The driving factors behind large intraslab earthquakes (Mw > 6.5, 40 -- 300 km
depth), along with their potential seismic hazards, are poorly understood due
to limited observational information about the rupture process and extent ofsuch events. This study presents a case study of a 110 km deep Mw 6.8 earthquake from 3rd June 2020 under Northern Chile (the Calama earthquake),for which we attempt to place the best-possible constraints on the locationand extent of the rupture plane. As we show, with careful signal processingof Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data we candetect the low-amplitude coseismic surface displacement field from this earthquake (with peak surface displacements ~6 mm), in spite of its depth. Using
these geodetic data (both our InSAR data and limited near-field GNSS data) to
supplement seismological data allows us to determine the finite extent of thesource fault. For the 2020 Calama earthquake, we obtain a well-constrained
fault plane (with a long, narrow aspect ratio of ~2.5) and relatively high static
stress drop (~40 MPa). Whilst only applied to a single case-study here, thisdemonstrates the capacity for careful analysis of satellite remote sensing data
to provide important additional constraints on intraslab earthquake ruptures,
supplementing what can be learn from seismological-only studies.
Uncertainty Estimates for Moment Tensors and Quantities
Derived From Them From Comparison of Global Catalogs
RÖSLER, B., Center for Scientific Research and Higher Education in
Ensenada, Ensenada, Mexico, boris@cicese.mx; STEIN, S., Northwestern
University, Illinois, USA, s-stein@northwestern.edu; SPENCER, B. D.,
Northwestern University, Illinois, USA, bspencer@northwestern.edu;
RINGLER, A., U.S. Geological Survey, New Mexico, USA, aringler@usgs.gov;
VACKÁŘ, J., Czech Academy of Sciences, Prague, Czechia (Czech Republic),
vackar@irsm.cas.cz
Analysis of moment tensor catalogs gives insight into general properties ofmany earthquakes beyond what can be obtained by studies of individual
earthquakes and allows estimating uncertainties in the determination ofseismic source processes. Traditionally, uncertainties in moment tensors arederived from the misfit between observed and synthetic waveforms. However,Volume 95•

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the differences between moment tensors in the USGS and the Global CMT
Project catalogs are typically an order of magnitude larger than the reported
errors, suggesting that the reported errors substantially underestimate theuncertainty due to different inversion procedures. Differences between
double-couple (DC) components decrease with magnitude, and correlation
between non-double-couple (NDC) components increases, suggesting thatseismic sources of large earthquakes are determined more reliably. A dataset compiled from three global and four regional catalogs shows that NDC
components are essentially independent of magnitude for earthquakes over alarge magnitude range, with a mean deviation from a DC source of about 20%.
Additionally, there is essentially no difference in NDC components between
earthquakes with different fault mechanisms and in different geologic environments. This consistency indicates that most NDC components, especiallyfor smaller earthquakes, do not reflect real source processes and are likely
to be artifacts, presumably due to not accounting for laterally varying Earthstructure during the inversion. Numerical experiments confirm this result.
Generating synthetic seismograms for a perturbed Earth model and invertingthem using the unperturbed Earth model yields NDC components whose size
is similar to the ones reported in global moment tensor catalogs. Comparison
of NDC components in three global catalogs allows quantifying the noise contained in them and shows that the GCMT catalog provides the most precise
NDC components. Furthermore, this comparison reveals that NDC components of large earthquakes are more reliably determined and that the largest
NDC components are more likely to represent real source processes.
Regional Moment Tensor Estimation With 3D Velocity
Models—Application and Assessment to the 2017 Hojedk,
Iran Sequence
RODRIGUEZ CARDOZO, F. R., University of South Florida, Florida,
USA, frodriguezcardozo@gmail.com; BRAUNMILLER, J., University ofSouth Florida, Florida, USA, jbraunmiller@usf.edu; GHODS, A., Institutefor Advanced Studies in Basic Sciences, Zanjan, Iran, aghods@iasbs.ac.ir;
SAWADE, L., Princeton University, New Jersey, USA, lsawade@princeton.
edu; ORSVURAN, R., Colorado School of Mines, Colorado, USA,rorsvuran@mines.edu; BOZDAG, E., Colorado School of Mines, Colorado,
USA, bozdag@mines.edu
The Arabia-Eurasia plate convergence, accommodated in a wide deforming zone, generates a host of moderate-to-large earthquakes in Iran. Using
in-country broadband data from the Iranian Seismological Center and the
Iranian National Seismic Network, we built a moment tensor (MT) databasewith over 2,000 solutions for Mw 3.4 to 7.8 earthquakes from 2004 to 2023
using a single, regional 1D velocity model. We selected a subset of events in
the Hojedk region of central Iran to assess result stability and parameter resolution employing 1D and 3D velocity models. We used the Moment Tensor
Uncertainty Quantification (MTUQ) software, which performs a grid searchover source parameters, for moment tensor estimation and uncertainty analysis. For a 3D model, we used the detailed, adjoint-tomography-derived Middle
East model of Örsvuran et al. (in prep.), which is based on fitting 30-s surface
waves at far-regional distances, and calculated 3D Green’s Functions (GFs)
at various crustal depths for selected Hojedk events using high-performancecomputing (HPC) facilities. We found that the 3D GFs reduce waveform misfits, time shifts, and non-double couple contributions compared to results from
1D-based synthetics for periods as short as ~15-20 s. For 1D synthetics, wefound a good agreement between the MT database results and double couple
and deviatoric MTUQ results. Larger differences are restricted to small eventswith low S/N waveforms observed only at a few close-by stations. Grid searches
over the full MT suggest a wide range of moment tensor solutions are permitted
by relatively long-period data even for events with seemingly well-constrained
double couple sources. We suspect inclusion of shorter-period data (5-10 s)and explicit use of P waves or their polarities will provide tighter constraints
and reduce parameter uncertainty. For Iran, 3D-model refinements, required
to use shorter-period data, can be achieved with available in-country data anda subset of well-constrained solutions from our regional MT database.
Quantifying the Effect of 3D Wavespeed Models on
Moment Tensors Using Synthetic Data in the Middle East
DOODY, C., Lawrence Livermore National Laboratory, California, USA,
doody1@llnl.gov; CHIANG, A., Lawrence Livermore National Laboratory,
California, USA, chiang4@llnl.gov; SIMMONS, N., Lawrence Livermore
National Laboratory, California, USA, simmons27@llnl.gov; RODGERS, A.,
Lawrence Livermore National Laboratory, California, USA, rodgers7@llnl.gov
Moment tensors provide information on seismic source properties including
general fault orientations for tectonic events, non-double-couple components,and seismic moments. To invert for moment tensors, a seismic wavespeed

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model is typically used to calculate Green’s functions. One-dimensional (1D)
wavespeed models are often used to calculate Green’s functions since it iscomputationally inexpensive and works well for many applications. However,using three-dimensional (3D) wavespeed models has been demonstrated toreduce the misfit in moment tensor inversions, particularly in tectonicallycomplex regions (e.g., Chiang et al., 2022; Covellone and Savage, 2012). To
quantify the impacts of using 3D wavespeed models on moment tensor accuracy, we developed a synthetic experiment using earthquake data in the Middle
East region. We computed synthetic waveform data for 25 events using a 3Dmodel of the Middle East and Central Asia (MESWA, Rodgers, 2023) assuming source parameters from the Global Centroid Moment Tensor (GCMT)
catalogue (Ekström et al., 2012). These synthetic data and source parametersserved as the ground truth in the synthetic experiment. To test the impact ofvarious models, we computed Green’s functions for a set of 1D and 3D models.
For the 1D models, we considered PREM (Dziewonski & Anderson, 1983)
and a regional 1D model (Rodgers et al., 1999; Pasyanos et al., 2004). For
the 3D models, we considered the SPiRaL (Simmons et al., 2021) and CSEM
(Fichtner et al., 2018) models. Moment tensors were inverted using a timedomain full waveform moment tensor inversion software (MTTime, Chiang,2020) and compared to the GCMT parameters which serve as the control (i.e.,target moment tensors). We will quantify the differences in the moment tensors using each of the models including uncertainties in the moment tensor
space (e.g., Tape & Tape, 2015) and highlight the significance/importance ofthe 3D structure on the resulting tensor solutions.
This work was performed under the auspices of the U.S. Department ofEnergy by Lawrence Livermore National Laboratory under Contract DE-AC5207NA27344. LLNL-ABS-858875

Understanding and Quantifying the Variability in
Earthquake Source Parameter Measurements [Poster
Session]Poster Session • Friday 3 May
Conveners: Rachel E. Abercrombie, Boston University (rea@bu.edu); Shanna Chu, U.S. Geological Survey (schu@usgs.
gov); Sydney Gable, University of Michigan (gablesyd@umich.edu); Gene Ichinose, Lawrence Livermore National
Laboratory (ichinose1@llnl.gov); Colin N. Pennington,
Lawrence Livermore National Laboratory (pennington6@llnl.
gov)

ing the moment magnitudes that were calculated from the three calibrations.
However, Zagros calibration showed a better estimation of the apparent
stress because the apparent stress that we used as references for the calibrations were located in Zagros zone. We could not find good candidate eventsin Mesopotamia to calculate the apparent stress due to the low seismicity. As
a result of this study, we recommend using Iraq calibration since 10 stations
were used in this calibration giving it the best path correction, and there wereslight differences in the estimated magnitudes of the three calibrations. The
proposed calibration serves as a fundamental step to update the comprehensive earthquake catalog for Iraq and probabilistic seismic hazard assessments.
poster 55
A Comparison of the Stress Drop Estimates Derived From
Different Techniques in Pollino, Italy
CALDERONI, G., Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy, giovanna.calderoni@ingv.it; ABERCROMBIE, R. E., Boston University,, USA, rea@bu.edu
Seismic spectral estimates of earthquake stress drop remain controversial,subject to large uncertainties, despite the fundamental role the source parameter plays in assessing the seismic forecasting in a given area and in improving
ground motion predictions for seismic hazard mitigation. Comparing different measurement techniques to understand how analysis processes affect theresulting estimates of stress drops is a necessary first step to improve resolution. It can also be useful to perform the same procedures using different
data sets. In this study we focus on the Pollino area, southern Apennines,
where structural complexities are thought to control seismic activity. We compare estimates of the Brune-style stress drop for 100 earthquakes (M2.2-5.2)
derived from two techniques: spectral fitting for attenuation, site effects andsource), and spectral ratio fitting in which an empirical Green’s function event
is assumed to remove the path and site effects. In all cases, the Brune (1970)
source is assumed. In the spectral fitting we first assume a regional attenuation
model, and second estimate path attenuation from the high-frequency decayof 8 well-recorded earthquakes (M3.6-5.2), to obtain attenuation-corrected
spectra. We estimate and remove the site term in both cases by averaging theattenuation-corrected spectra for each event, and then computing the difference from the mean event spectrum for each station (assuming the mean site
correction is zero). These differences are averaged over the event ensemble toobtain a mean site term for each station, which is then removed before fitting
the resulting estimates of source spectra to obtain the final source parameter
estimates. In the EGF approach, we divide the spectra of the target events by
those of co-located smaller EGF earthquakes, and fit the resulting spectral
ratios, for each event, at each station, assuming all path and site effects are
removed. We perform the fitting first with no constraints on the stress drop(and corner frequency) of the EGF event, and then with constraints based on
different scaling laws of stress drop to seismic moment.

poster 54
Using a 1-D Radially Symmetric Coda Envelope Model for
Robust Source Scaling in Iraq’s Tectonically Diverse Zones
AL-KAABI, M., University of Arkansas at Little Rock, Arkansas, USA,malkaabi@ualr.edu; MAYEDA, K., Air Force Technical Applications Center,
Florida, USA, kevin.mayeda@us.af.mil; ROMAN-NIEVES, J., Air Force
Technical Applications Center, Florida, USA, jorge.roman-nieves.1@us.af.
mil; CHIANG, A., Lawrence Livermore National Laboratory, California,
USA, chiang4@llnl.gov; MAHDI, H., University of Arkansas at Little Rock,Arkansas, USA, hhmahdi@ualr.edu; AL-SHUKRI, H., University of Arkansas
at Little Rock, Arkansas, USA, hjalshukri@ualr.edu

poster 56
Sensitivity Analysis of Seismic Hazard Parameters for theUnderstanding of Its Uncertainties: A Study Case forCentral America
GAMBOA-CANTÉ, C., Universidad Politécnica de Madrid, Madrid, Spain,
carlosjose.gamboa@alumnos.upm.es; ARROYO-SOLÓRZANO, M., GFZ
Postdam, Postdam, Germany, marroyo@gfz-potsdam.de; RIVAS-MEDINA,
A., Universidad Politécnica de Madrid, Madrid, Spain, alicia.rivas@upm.es;
BENITO, B., Universidad Politécnica de Madrid, Madrid, Spain, mariabelen.
benito@upm.es

Estimation of moment magnitude can be challenging for Iraq due to the strong
lateral heterogeneity of the diverse tectonic zones. In this study, we investigate
the reliability of using 1D coda envelope model for the entire country despite
the lateral effects and the differences in the tectonic zones’ geophysical characteristics. Iraq comprises two main tectonic zones: 1-The Outer Platform which
consist of the northwestern Zagros Fold-Thrust Belt and the Mesopotamian
Foredeep; 2-The Inner Platform that is covering the Iraqi western desert. Dueto the fact that coda waves have a low sensitivity to the source and the pathheterogeneity, a simple 1-D coda envelope model was used. Three separate
coda calibrations were conducted in order to investigate the reliability ofusing one calibration for the country, Iraq calibration, Zagros calibration,and Mesopotamia calibration. 51 events (Mw>4.5) recorded by ten stations
were used for Iraq calibration while for Zagros calibration, 42 events fromthree stations located within Zagros zone were used. The last calibration isfor Mesopotamian Foredeep, where there are 7 stations in this zone. 40 eventswith Mw>5 were enough to calibrate the zone. Ground truth (GT) reference
spectra derived from the coda spectral ratio method were used to constrain
high-frequency site terms. There were no drastic differences when compar-

The parameters involved in seismic hazard calculations introduce both epistemic and random uncertainties that must be controlled to minimize errors
and obtain an accurate seismic model representing expected accelerations in aregion. In this regard, it is essential to apply a sensitivity analysis of the results
provided by seismic hazard calculations to understand the behavior of uncertainties associated with the parameters. Statistical methods (e.g., RMSE, MSE,
and CV) are employed for such analysis, relating observed variables to thosepredicted by the models used, enabling both analytical and spatial examination of interacting parameters in seismic hazard.
Consequently, we conducted a case study for Central America, analyzing the sensitivity of parameters involved in seismic hazard calculations. In
this case, we examined the fitting method for the recurrence model (leastsquares and maximum likelihood), the use of scaling laws, and the application of ground motion models (GMM). Ultimately, we obtained coefficientof variation (CV) maps illustrating the variability of results and highlighting
regions in Central America where these trends are evident. This variability
and sensitivity analysis helped refine the weights and parameters of the logicaltree used to generate new seismic hazard maps for Central America for PGA

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and Sa(1.0s) at return periods of 475, 975, and 2475 years. Additionally, we
compared our results with seismic hazard maps created by other authors in
the region to assess the significance of acceleration variability.
poster 57
Adjoint Earthquake Source Inversion Method Using P-Wave
Spectra and Focal Mechanism Solutions
CHENG, Y., University of California, Berkeley, California, USA, chengyif@berkeley.edu; DREGER, D. S., University of California, Berkeley, California,
USA, ddreger@berkeley.edu; ALLEN, R. M., University of California,
Berkeley, California, USA, rallen@berkeley.edu
Improving characterizations of small earthquake sources advances our understanding of fault structures and seismic mechanics. Traditional methods fordetermining focal mechanisms, stress drops, and rupture directivities are limited by ambiguities in nodal plane identification and the neglect of rupture
directivity, which impedes in-depth analyses and comparisons between earthquakes of varying magnitudes. To address these challenges, we introduce aninnovative adjoint source inversion method that integrates focal mechanism
solutions with P-wave spectra. Initially, we determine the apparent P-wave
corner frequencies for the target event by analyzing the source spectral ratio
between the target event and its surrounding Empirical Green’s Function(EGF) events. We then synthesize corner frequencies with all potential fault
plane orientations derived from the focal mechanism solutions and selectthe optimal fault plane orientation and 3D rupture directivity that best correspond with the observed azimuthal variations of P-wave corner frequencies.
Validated using a synthetic dataset and 2634 M≥1.5 events around theParkfield locked patch, our findings indicate significant unilateral rupture
directivity in 88% of the earthquakes. Of these, 53% occur along the main
fault with various dipping angles, and 47% exhibit high angle to the main
fault with near-vertical dips. Events above the locked patch predominantly
show NE dipping planes with SE directivity, while those below exhibit SW
dipping with NW directivity, suggesting consistent earthquake rupture direction with the hanging wall’s slip direction. Incorporating directivity effects,
84% of events exhibit larger corner frequency, indicating higher stress drops
than those previously estimated without directivity corrections. The proposed
method can help to solve unprecedented detailed spatiotemporal variation ofsmall earthquake properties, including fault orientation, 3D rupture directivity, and stress drop, which offers new perspectives on fault geometry, kinematics, and dynamics.
poster 58
Bayesian Inference for the Seismic Moment Tensor Using
Regional Waveforms and a Data-Derived Distribution of
Velocity Models
CHIANG, A., Lawrence Livermore National Laboratory, California, USA,chiang4@llnl.gov; FORD, S. R., Lawrence Livermore National Laboratory,
California, USA, ford17@llnl.gov; PASYANOS, M., Lawrence Livermore
National Laboratory, California, USA, pasyanos1@llnl.gov
The largest source of uncertainty in any source inversion is the velocity model
used to construct the transfer function employed in the forward model that
relates observed ground motion to the seismic moment tensor. However, standard inverse procedures often does not quantify uncertainty in the seismic
moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. We attempt to incorporate this uncertainty into an
estimation of the seismic moment tensor using a distribution of velocity models calculated in a prior effort based on different and complementary data sets.
The posterior distribution of velocity models is then used to construct Green’s
functions for use in Bayesian inference of an unknown seismic moment tensor using regional waveform data. The combined likelihood is estimated using
data-specific error models and the posterior of the seismic moment tensor isestimated and can be interpreted in terms of most-probable source-type.
poster 59
Characterizing Directivity in Small (M3-5) Aftershocks of
the Ridgecrest Sequence
CHU, S., Rice University, Texas, USA, shanna.chu@rice.edu; BALTAY, A. S.,
U.S. Geological Survey, California, USA, abaltay@usgs.gov; ABERCROMBIE,
R. E., Boston University, Massachusetts, USA, rea@bu.edu
A longstanding issue in source seismology is whether or not the variation
in measured “stress drop” is due to methodological differences or physicalassumptions, which leads to confounding results about predicted groundmotion in regional earthquake hazards and source physics. The spectrum ofseismic radiation is commonly used to derive the stress drop for earthquakes,

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which relates an earthquake’s source dimension to its ground motion. The
first step in using the spectrum to estimate the stress parameter is to separateout source contributions in the raw data from site- and path- effects, which
may be performed in various ways. In this study, we compare two common
methods of deconvolving source spectra from waveform records: using a nonparametric matrix inversion (spectral decomposition) and using an empiricalGreen’s function (eGf) method. Using the example case of the 2019 Ridgecrest
sequence, we classify source spectra into types based on observed spectral
complexity, noting that complex spectral shapes (at both the event and station level) are more likely to yield variable estimates of the stress parameter
when the deconvolution method differs. We show that source directivity
can account for some amount of discrepancy in source parameter estimates
between the two methods. Typically, azimuthal heterogeneity in path is notaccounted for in a spectral decomposition, while eGf methods specificallyaccount for specific paths. We present an approach to understand the variation in corner frequency due to azimuthal variability.
poster 60
DAS Derived Source Characterization of Ridgecrest
Aftershocks Using Coda Spectral Ratios
DELBRIDGE, B. G., Los Alamos National Laboratory, New Mexico, USA,delbridge@lanl.gov; VIENS, L., Los Alamos National Laboratory, New
Mexico, USA, lviens@lanl.gov; ZHAN, Z., California Institute of Technology,
California, USA, zwzhan@caltech.edu; CHEN, X., Texas A&M University,
Texas, USA, xiaowei.chen@exchange.tamu.edu
Distributed acoustic sensing technology provides a new capability to densely
sample the seismic wavefield in difficult or previously inaccessible areas.
However, measurements made on existing telecommunications cables are limited to uniaxial measurements of strain along the buried optical fiber, and theground coupling of the cable is often unknown, hindering determination ofseismic source properties. To overcome these limitations, we use coda spectral
ratios to obtain estimates of the seismic source parameters using relative source
spectra. Waveform envelope measurements of coda waves provide azimuthally
insensitive information about their source spectra and ratios of envelopes fromtwo sources measured by the same sensor can remove path, and crucially for
DAS measurements, the sensor site effects. We demonstrate the effectiveness of
this method using both DAS and traditional seismic measurements of the wellstudied aftershocks of the 2019 Ridgecrest earthquake. We show that the relative source functions obtained using the DAS data are like those obtained using
the traditional seismic data, confirming that the coda spectral ratio method
can overcome the azimuthal and unknown ground coupling limitations ofusing DAS data for the study of seismic source properties. Further, we showthat the derived stress drops and magnitudes are commensurate with those ofother studies which employ more traditional seismic analysis methods.
poster 61
Understanding Sources of Variability and Uncertainty in
the Relative Magnitude Method
GABLE, S., University of Michigan, Michigan, USA, gablesyd@umich.edu;
HUANG, Y., University of Michigan, Michigan, USA, yiheh@umich.edu
A precise understanding of earthquake magnitudes is vital for accurate calculations of magnitude exceedance probabilities and seismic hazard assessment.
However, characterization of earthquake magnitude, particularly for small
events, is complicated by differences in network capabilities and procedures.
Furthermore, the use of differing magnitude scales for events of various sizes
introduces additional challenges and produces disparate magnitude estimates
for the same events. To address the need for a consistent magnitude estimation procedure that can accurately estimate magnitude across a wide magnitude range and in diverse tectonic environments, we investigate the use of therelative magnitude method. This approach utilizes amplitude ratios of highly
correlated waveforms among numerous interlinked event pairs to compute
magnitudes for a group of events. While the relative magnitude method isadvantageous because it can be applied uniformly in various regions anddoes not require distance or attenuation corrections, there are several parameters that currently require human decision which may introduce bias. These
include acceptable thresholds for signal-to-noise ratios and cross-correlation,filtering procedures, sampling windows, and station selection. Our research
focuses on computing new relative magnitudes for events in southern
California, including the 2019 Ridgecrest sequence. We investigate the uncertainty that human decision may impose on the resulting magnitudes and compare our results to other magnitude estimation methods. Finally, we present
our recommendations for routine procedures that minimize uncertainty andvariability in the relative magnitude method, aiming to enhance the utility ofthis method for future users.

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poster 62
Development of Empirical Scaling Relationships Between
Spectral Displacement Amplitudes Measured in the Time
Domain and Earthquake Magnitudes in South Korea
HONG, Y., Chonnam National University, Gwangju, South Korea, ythong@jnu.ac.kr; KIM, B., Chonnam National University, Gwangju, South Korea,
kbobo41@jnu.ac.kr; SHEEN, D., Chonnam National University, Gwangju,
South Korea, dhsheen@jnu.ac.kr
In South Korea, a local magnitude scale using the maximum amplitude of S
waves has been proposed (Sheen et al., 2018). However, the time when the previous study was conducted, there were very limited number of observations
within an epicentral distance of 50 km. For this reason, it is difficult to accurately determine the magnitudes of small earthquakes typically observed onlyat short distances, using the previous scaling relationship. The recent increasein the number of seismic stations in South Korea enables us to develop an
empirical scaling relationship accounting for short distances. In addition, it
is shown that the moment magnitude can be measured for earthquakes as
small as M 2.0 using peak displacement amplitudes (Al-Ismail et al., 2023).
In this study, we collected seismograms of 647 earthquakes occurred in andaround South Korea from 2017 to 2022. Spectral displacement amplitudes of
S waves were measured from vertical components in the time domain using
multiple narrowband filters and in the frequency domain using the multitaper
method. Then, we developed empirical relationships between displacement
amplitudes and seismic moments, separately for each frequency band, anduse them to measure magnitudes. To validate the empirical relationship proposed in this study, we estimated the magnitudes of earthquakes in the 2016
Gyeongju earthquake sequence. Consequently, we demonstrate that spectral
amplitude estimation in the time domain is an effective method for determining the magnitude of small earthquakes.
poster 63
Moment-Rate Spectra, Source Scaling and Spectral Fall-Offin the Korean Peninsula Using the Coda Calibration Tool
(2.0<Mw<5.5): Application to Natural and Man-Made
Sources
MAYEDA, K., Air Force Technical Applications Center, California, USA,kevin.mayeda@gmail.com; ROMAN-NIEVES, J., Air Force TechnicalApplications Center, Florida, USA, jorge.roman-nieves.1@us.af.mil; SON, M.,
Korea Institute of Geoscience and Mineral Resources, Daejeon, South Korea,
kersti@kigam.re.kr
We applied the Coda Calibration Tool (CCT) to local and regional broadband data across the Korean peninsula and Yellow Sea region with the goalof obtaining stable moment-rate source spectra. The 2016 Gyeongju and 2017
Pohang sequences allowed us to compute stable coda spectral ratios that wereused as reference events, an integral step in the CCT calibration methodology.
We are able to measure single-station Mw for events as small as ~2.0, compare earthquake source scaling with other independent methods, and study
the spectral characteristics of shallow induced events as well as man-madesources over the past 20 years. Another important focus of this study was the
spectral fall-off. While source scaling studies must account for the inherent
trade-offs between site, source and path effects, the empirical Green’s function(eGf) approaches, and their variants, have been attractive because common
path and site terms cancel. Source complexity and a priori assumptions canbias eGf results so we plan to address these following challenges in this study,
namely: 1) The spectral models used to fit the data must assume a spectral
fall-off which are also a topic of active debate; 2) Potential issues with source
directivity of either or both events which might bias the results; 3) Sourcecomplexity that can create spectral holes and peaks as reported in a numberof finite-fault inversions; 4) Finally, the assumption of an eGf stress drop can,in theory, bias both the small magnitude corner frequencies and subsequentinterpretation of the overall source scaling.

scaling, or area-length scaling (Scholz, 1982, 1994; Romanowicz, 1982, 1992,
Leonard, 2010). Better constraints on scaling relationships of source parameters will allow for improved estimates of potential future earthquake sizes
and improved forecasts of earthquake hazards.
In this work, we aim to bring a new perspective to scaling relationships byusing an InSAR-derived source parameter dataset. InSAR can provide robust
constraints on key parameters such as fault length by direct measurements
and on other fault parameters by modeling. To compile our dataset, we simultaneously mine the literature for source parameters for InSAR-based studies
and also model recent earthquakes not present in the literature ourselves. For
our own models, we estimate the source parameters (e.g. strike, slip, length)
using a rectangular elastic dislocation model, fitted to downsampled InSAR
data from the Sentinel-1 satellites, whose parameters are estimated using a
Powell algorithm with multiple Monte Carlo restarts. To evaluate scaling relationships, we use statistical approaches (e.g. regression analyses) to quantify
the relationships between the source parameters (e.g. length, width, seismic
moment). Our preliminary results, based on over 200 earthquakes studied
with InSAR, are consistent with a length squared-moment scaling (L2 ∝ Mo),suggesting that slip may be proportional to fault length.
The value of the scaling relationships obtained in this way are only as
robust as the earthquake models and the modeled source parameters. To
assess the likely impact of uncertainties in these parameters, we examine a few
well-studied events, such as the 2015 Gorkha, Nepal and 2019 Ridgecrest, CA
earthquakes, to quantify the variability in published models.
poster 65
Rupture Directivity of Small Earthquakes in Southern
Korean Peninsula
SEO, M., Seoul National University, Seoul, South Korea, 36wnfgodfkd@snu.
ac.kr; HAN, S., Seoul National University, Seoul, South Korea, sangw876@
snu.ac.kr; KIM, W., Columbia University, New York, USA, wykim@ldeo.
columbia.edu; KIM, Y., Seoul National University, Seoul, South Korea,
younghkim@snu.ac.kr
Good knowledge of rupture directivity is crucial for both earthquake physics and seismic hazard mitigation. Analyzing bulk of small earthquakes may
provide insights into the potential mechanism of rupture directivity, but suchstudies have been rare in stable continental regions. The Southern Korean
Peninsula (SKP) hosts a dense network of seismic stations and hence provides
opportunities of investigating the characteristics of earthquake rupture in the
SCR. We analyze the rupture properties of 28 small (ML 2.1–4.1) earthquakes
in SKP since 2019, employing the empirical Green’s function method to calculate the relative source time functions (RSTFs). Adopting the line source
model, we use Bayesian inference to invert key finite source properties—
rupture direction, length, velocity, and degree of asymmetry. This approachallows us to elucidate the characteristics of earthquake rupture by explaining variations in RSTF durations concerning azimuths and ray takeoff angles,
while robustly characterizing parameter uncertainties by considering data
errors and trade-offs.
Our analysis reveals that a majority of events display asymmetrical rupture with a dominant direction in accordance with the nodal plane of focal
mechanism, while a few events exhibit nearly symmetrical rupture. Thisimplies that the rupture directivity may be relatively common for small earthquakes in SCRs, challenging the simplistic assumption of symmetrical circularrupture. We further revisit the 2020 Haenam earthquake sequence that exhibited unusual swarm-like behavior in the lower crust of southwestern SKP. Five
M ≥ 2 events show diverse spectrum of rupture behaviors, ranging from bilateral to unilateral, with contrasting directions. However, we find that the largest
event (ML 3.1) ruptured away from other earlier events, implying that thoseearlier events may have influenced the rupture direction and extent of the largest event. This demonstrates that the detailed analysis of small event ruptures
could enhance our understanding of earthquake sequences in the SKP.

poster 64
Evaluating Scaling Relationships From Insar-Derived
Earthquake Source Parameters
RIVERA, K. M., University of California, Riverside, California, USA,krive050@ucr.edu; FUNNING, G. J., University of California, Riverside,
California, USA, gareth@ucr.edu

poster 66
On the Variability Discrepancy Between PGA and Spectral
Stress Drop: Insight From Double-Corner-Frequency
SpectraSHIMMOTO, S., University of Tokyo, Bunkyo-ku, Japan, shimmoto@eri.utokyo.ac.jp; MIYAKE, H., University of Tokyo, Bunkyo-ku, Japan, hiroe@
eri.u-tokyo.ac.jp

Scaling relationships are key to understanding which earthquake source
parameters—quantities that describe the earthquake source (e.g. fault length,fault width, slip, and seismic moment)—are key to producing large earthquakes. Proposed scaling relationships include the presence or absence ofscaling breaks and the existence of a power law (or not), in length-moment

The stress drop estimated from the corner frequency (spectral stress drop)
is considered an important parameter in ground motion prediction. Cotton
et al. (2013) found that the observed variability of the spectral stress drop is
significantly larger than expected from the observed PGA variability. In thisstudy, we conducted spectral ratio analysis for 34 crustal earthquakes with

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Mw 5.0–7.1 in Japan to resolve this variability paradox. First, we applied thestandard spectral ratio method, which assumes the single-corner-frequency(SCF) spectrum model, to estimate the spectral stress drop Δσfc. Second, weapplied the two-stage spectral ratio method developed in this study. Thismethod enables us to obtain the double-corner-frequency (DCF) spectra atbroadband frequencies. We determined the corner frequency fch by fitting the
SCF model to the DCF model at low and high frequencies. The spectral stressdrop calculated using fch is called the stress parameter Δσfch, which characterizes the intensity of the high-frequency radiation.
The standard deviation of lnΔσfc is 1.0, as high as the ones found in previous corner frequency studies. In contrast, the standard deviation of lnΔσfch
is 0.55, which predicts the standard deviation of lnPGA of 0.44, comparable tothe between-event variability of PGA observed in Japan. The corner frequency
obtained from the standard spectral ratio method crudely corresponds to thelower corner frequency of the DCF model, fca. Thus, the variability discrepancy between Δσfc and PGA could mainly arise from the difference in thevariability of fca and fch of the DCF spectrum. The DCF model successfully
explains the spectra for all events and has the potential to explain both theobserved Δσfc and PGA variabilities. Finally, we found that the deviation of
the observed spectra from the SCF model becomes significant on average as
the magnitude increases. Implementing the DCF model can be important forpredicting ground motions.
poster 67
New Version of the Earthquake Mechanism of
Mediterranean Area (EMMA) Database With a Web-Gis
Interface
VANNUCCI, G., Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy,
gianfranco.vannucci@ingv.it; TARABUSI, G., Istituto Nazionale di Geofisicae Vulcanologia, Bologna, Italy, gabriele.tarabusi@ingv.it; TACCONE, R.,
Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy, ritachiara.
taccone@ingv.it; BIONDINI, E., Università degli Studi di Bologna, Bologna,
Italy, emanuele.biondini2@unibo.it; LOLLI, B., Istituto Nazionale di Geofisica

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e Vulcanologia, Bologna, Italy, barbara.lolli@ingv.it; GULIA, L., Universitàdegli Studi di Bologna, Bologna, Italy, laura.gulia@unibo.it; GASPERINI, P.,
Università degli Studi di Bologna, Bologna, Italy, paolo.gasperini@unibo.it
We present a new version (4.0) of the database of Earthquake Mechanisms of
the Mediterranean Area (EMMA) of “checked” first-motion focal solutions
available from the literature. The EMMA database, developed on MS-ACCESS
and managed by original software, uniforms the different formats of the data
available and try to solve misprints, inaccuracies and inconsistencies thatmake them almost useless for other users (e.g. tests the perpendicularity of
nodal planes and/or P and T axes of all solutions and, when both axes andplanes are given, even their mutual consistency). The database now collects
more than 34,000 focal solutions (~+ 850%, ~560%, ~ +280% with respect
to previous three existing database versions). The EMMA database is not ahomogeneous catalogue because it includes focal mechanisms computed withdifferent methodologies covering different areas and magnitudes, depending on original papers available. We added the missing parameters (e.g. time,magnitude) and, when possible, we link the data to the earthquakes available in other catalogues (e.g. HOmogenized instRUmental Seismic catalogHORUS-, International Seismological Centre -ISC-). We merged EMMA withthe focal mechanisms (mainly by moment tensor inversion) from different
available on-line catalogues ;at global and regional scale (e.g. GCMT, RCMT).
An automatic procedure, based on several criteria, permits to choose the most“representative” (preferred) solution when more than one solution is available
for a same earthquake comparing quantitatively the alternative solutions (e.g.
Kagan angle between solutions, Frohlich ternary diagram representation).
A web-GIS interface based on OpenLayers (an open-source javascript
library) allows now to select (e.g. for areas, magnitude range, time period),
display and export the data suitable to be handled by graphic software and user
written procedures. The EMMA database is a powerful tool for characterising
the tectonic regime and for seismotectonic and deformation analyses, extending the data coverage of other catalogues available for the Mediterranean area
over time and to a lower magnitude threshold.

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Index of Authors
Aagaard, B. T. 1195, 1196,
1290, 1309, 1310, 1333
Abadi, S. 1429, 1431
Abbott, E. 1252
Abbott, R. E. 1217, 1227,
1285
Abdallah Hamimi, Z. 1436
Abdelmeguid, M. 1333
Abercrombie, R. E. 1220,
1448, 1449, 1452, 1453
Abers, G. A. 1268, 1426,
1427, 1429, 1430, 1431
Abrahams, L. S. 1370
Abrahamson, N. A. 1198,
1200, 1240, 1241, 1243,
1292, 1313, 1377, 1378,
1384, 1385
Acharya, P. R. 1355
Acosta, M. 1325
Acquisto, T. M. 1413, 1425
Adams, A. 1276, 1428
Adams, J. A. 1240, 1354
Adarshi, N. 1387
Aday, K. 1290, 1384
Adeboboye, O. E. 1440
Adedeji, O. 1432, 1433, 1434,
1435
Aderhold, K. 1344, 1345,
1362, 1429, 1431
Adourian, S. 1428
Agius, M. R. 1287
Agrawal, H. 1205, 1378
Aguilar, A. L. 1359
Aguilar, I. 1281
Aguilera, M. 1372
Ahdi, S. K. 1197, 1383, 1385,
1386
Ai, Y. 1269, 1337
Akbayram, K. 1319
Akhani, M. 1373, 1374
Akinci, A. 1293, 1318, 1320,
1372
Akuhara, T. 1411
Al-Attar, D. 1446
Albert, S. A. 1265, 1376
Aldama-Bustos, G. 1241
Aleid, M. H. 1429
Alessandrini, G. 1290
Alexander, J. 1362
Alfaro-Diaz, R. A. 1208,
1209, 1212, 1213, 1216,
1326
Alger, E. 1211
Alidadi, N. 1359, 1373, 1441
Al-Kaabi, M. 1452
Allam, A. 1232, 1250
Allen, B. 1328
Allen, R. M. 1255, 1281,
1282, 1293, 1363, 1453
Alley, R. B. 1236
Allstadt, K. E. 1262, 1263,
1264, 1265, 1266, 1267,
1383
Alongi, T. 1246
Al-Shukri, H. 1452
Altekruse, J. M. 1194, 1195,
1196, 1197, 1199
Altuncu Poyraz, S. 1418

1456

|

Alvarez, M. G. 1281, 1360,
1365
Alvarez, N. 1323
Álvarez-Gómez, J. A. 1389
Alver, F. 1321
Alvillar, M. 1391
Alvizuri, C. 1264
Amador, V. S. 1359
Amashukeli, T. 1359, 1362
Ambruz, N. B. 1290, 1358
Ameri, G. 1312
Amidon, W. 1332
Ammon, C. J. 1216, 1217,
1218
Amorosi, A. 1314, 1316
Ampuero, J. 1322
Anbazhagan, B. 1313
Anderlini, L. 1394
Anderson, D. 1376
Anderson, J. F. 1407
Anderson, J. G. 1194, 1292
Anderson, K. R. 1333, 1352
Andjelic, D. 1279
Andrews, J. 1277
Angarita, M. 1351
Angster, S. 1258, 1299, 1300,
1302
Anquez, P. 1203, 1371
Ansal, A. 1382
Anselmi, M. 1394
Anthony, R. E. 1237, 1284,
1286, 1288
Antoine, M. 1306
Antolik, L. 1359
Antolik, M. S. 1219
Antonioli, A. 1321
Aoki, Y. 1351
Applegate, R. 1334
Appriou, D. 1398
Aquib, T. T. 1379
Arciniega-Ceballos, A. 1370
Ardid, A. 1348, 1350
Aref, M. 1321
Argote-Espino, D. 1330
Armstrong, A. D. 1222, 1358
Arroucau, P. 1291
Arrowsmith, S. 1211, 1376,
1377, 1422
Arroyo-Solórzano, M. 1452
Artale Harris, P. 1372
Artigas, B. 1369
Asadi, A. 1254, 1266, 1383
Asayesh, B. 1321
Asero, C. 1225
Asimaki, D. 1290, 1318,
1334, 1384
Asirifi, R. 1395, 1398
Aspiotis, T. 1385
Assadollahi, C. 1200
Aster, R. C. 1225, 1232, 1235,
1236, 1237, 1238, 1274,
1284
Atekwana, E. A. 1446
Atherton, C. 1225
Atkinson, G. M. 1194
Atzori, S. 1321
Aubert, C. 1331
Audet, P. 1277
Aurelio, M. A. 1335

Seismological Research Letters

Austermann, J. 1446
Autumn, K. R. 1446
Avouac, J. 1325, 1327, 1339,
1394, 1395
Awan, M. 1371
Awe, E. 1397
Awender, S. 1212
Ay, E. 1393, 1397
Ayling, S. 1432
Azencot, O. 1312
Azizzadenesheli, K. 1342,
1343
Aziz Zanjani, A. 1322, 1323,
1326
Aziz Zanjani, F. 1322, 1323,
1326
Azzola, J. 1227
Babaie Mahani, A. 1278
Babayan, G. 1338
Babendreier, C. 1198
Baccheschi, P. 1224
Bacci, L. 1254
Bacciu, D. 1396
Bachelot, L. 1422
Bachmann, E. 1204
Baden, C. W. 1246, 1310,
1333
Baena-Rivera, M. E. 1370
Baez, J. C. 1353
Bagagli, M. 1396
Baichtal, J. 1433
Bain, C. 1384
Bainbridge, G. 1237
Baird, A. 1325
Baise, L. G. 1254, 1266,
1294, 1383, 1389
Baker, B. 1216, 1358, 1406,
1407
Baker, J. W. 1194
Baker, M. G. 1214, 1285
Baker, M. R. 1299
Bal, A. 1210, 1366
Balagizi, C. 1408
Balco, G. 1332
Baldwin, W. 1198
Balezi, G. 1408
Ballard, S. 1358
Balster-Gee, A. 1296, 1305
Baltay, A. S. 1291, 1292, 1312,
1315, 1449, 1450, 1453
Banerdt, W. B. 1271, 1381
Banfield, D. J. 1381
Bannister, S. 1407
Bañuelos, D. 1331
Bao, X. 1271, 1411
Barajas, A. 1405
Barama, L. 1208, 1209, 1213
Baranbooei, S. 1415
Barbour, A. J. 1336, 1420
Barcheck, G. 1424, 1427,
1428, 1429, 1430, 1431,
1432
Barker, B. 1399
Barman, D. 1268
Barnhart, K. R. 1418
Barnhart, W. 1354, 1357
Barrientos, S. E. 1353
Barrière, J. 1403, 1408
Barthélémy, J. 1371

Bartolomé, R. 1275
Bastami, M. 1311, 1314
Bato, M. G. 1339
Baumont, D. 1312
Bayless, J. 1198, 1201
Bayliss, K. 1384
Bayona, J. 1367, 1368
Bayudanto, A. 1330
Bazargan, S. 1375
Beardslee, L. 1374
Beaucé, E. 1238, 1341, 1425,
1439
Beaupretre, S. 1231
Beauval, C. 1239, 1241, 1242
Bécel, A. 1413, 1425, 1426,
1427, 1431
Becker, D. 1245
Becker, J. 1252
Becker, T. W. 1233, 1272
Bednarz, W. 1242
Beeler, N. 1333
Begnaud, M. 1212, 1214,
1358
Bejar, G. 1262, 1266, 1268
Belinić Topić, T. 1270
Bellini, J. 1264
Bemis, S. P. 1249, 1332
Bender, A. M. 1250, 1257,
1298, 1299, 1393
Ben-Dor, G. 1232
Benítez, C. 1349, 1352
Benítez, M. 1348, 1350
Benito, B. 1336, 1452
Ben Mansour, W. 1230,
1276, 1413
Benne, M. 1282
Bennett, A. 1221
Bennett, A. J. M. 1428
Bennett, R. A. 1258
Bennett, S. E. 1332
Bennington, N. 1402
Benowitz, J. A. 1249, 1430
Bent, A. L. 1284, 1286, 1354,
1438
Benz, H. M. 1323, 1354,
1358, 1424, 1447
Ben-Zion, Y. 1203, 1367,
1377
Berbellin, A. 1244
Berg, E. M. 1215, 1217
Berger, J. 1363
Berglund, H. 1339, 1340,
1341
Bergman, E. 1391, 1421, 1427
Bernauer, F. 1295, 1331, 1365
Berndt, C. 1410
Beroza, G. C. 1207, 1222,
1284, 1324, 1356, 1357,
1359, 1412, 1449
Besana-Ostman, G. 1259
Beskardes, G. D. 1214, 1380
Betasolo, M. 1390
Bethmann, F. 1399
Bezada, M. 1270
Bhadha, R. 1355, 1360, 1365
Bhaskaran, A. 1355, 1357
Bi, Z. 1312, 1315, 1343
Bianco, F. 1348, 1349, 1350

www.srl-online.org•

Volume 95•

Biasi, G. 1239, 1241, 1281,
1360, 1365
Biegel, K. 1250, 1325
Biffard, B. 1362
Bignami, C. 1321
Bijlsma, E. 1336
Bilek, S. 1215, 1346, 1390,
1391
Bilham, R. 1265, 1439
Bill, C. 1212
Billen, M. I. 1373, 1447
Biondi, E. 1224, 1225, 1226,
1282, 1345, 1355, 1421,
1422
Biondini, E. 1455
Birkey, A. 1233
Biro, Y. 1242
Bishop, J. 1214
Bito, H. 1346
Black, B. A. 1299, 1307
Black, M. L. 1360
Blackwell, A. 1421
Blair, J. L. 1359
Blisniuk, K. 1331, 1335
Block, G. A. 1405
Blom, L. 1360
Blom, P. S. 1212, 1214
Bloomquist, D. K. 1364
Blycker, W. 1420
Bobbio, A. 1350
Bockholt, B. 1353, 1358,
1360
Bodin, P. 1231, 1348, 1360,
1366, 1429, 1431
Bodmer, M. 1211
Bodunde, S. 1310, 1327
Boese, M. 1282
Bogolub, K. R. 1220, 1222
Bogris, A. 1355
Bohnhoff, M. 1222, 1245
Boie, K. 1217
Bolton Valencius, C. 1391
Bonano, M. 1321
Bondar, I. 1388
Bonilla, E. L. 1281
Bonner, J. L. 1292
Boone, W. 1286, 1288
Booth, A. 1238
Bora, S. 1380
Borleis, E. 1441
Bosa, A. 1262, 1268
Bose, S. 1317
Böse, M. 1277, 1278, 1361
Bostock, M. 1433, 1434
Boston, B. 1410, 1413, 1414,
1425
Boukhalfa, H. 1211
Bourne, S. 1325
Bowden, D. 1224, 1228,
1229, 1355
Bowman, D. C. 1210, 1211,
1212, 1218, 1375, 1376,
1377
Boyd, O. S. 1206, 1388, 1436,
1440, 1441
Bozdag, E. 1201, 1204, 1206,
1207, 1229, 1272, 1341,
1445, 1446, 1447, 1451
Bozorgebrahimi, K. 1225

Number 2B•

April 2024

Bracale, M. 1403, 1405
Bradford, L. E. A. 1286
Bradshaw, P. 1364
Brady, L. 1264
Brandl, C. C. 1432, 1433,
1434, 1435
Brannon, M. A. 1338
Brantut, N. 1244
Braun, A. 1203
Braun, J. 1237
Braun, T. 1242, 1394, 1396,
1420
Braunmiller, J. 1213, 1221,
1318, 1451
Bravo, F. 1353
Bravo, T. K. 1340
Brax, M. 1242
Bray, J. 1384
Brekke, K. 1281
Brenguier, F. 1231, 1284,
1351
Brenot, H. 1403
Brenot, L. 1351
Briceno, Y. 1282, 1283
Briggs, R. 1195, 1198, 1259,
1260, 1298, 1302, 1304,
1305, 1306, 1322, 1335,
1441, 1442
Brito Silveria, L. 1339
Brodsky, E. 1368
Bröker, K. 1395
Bromirski, P. D. 1236
Brooks, B. 1333
Broome, S. 1211
Brossier, R. 1403
Brothers, D. S. 1296, 1298,
1301, 1302, 1303, 1304,
1305, 1306, 1307, 1393,
1435
Brown, B. 1211
Brown, J. 1339, 1341
Brown, M. R. M. 1326
Bruce, D. 1300
Brudzinski, M. R. 1221,
1282, 1283, 1342, 1368,
1391
Brumbaugh, D. 1219
Brunelli, M. 1254
Brunsvik, B. R. 1270, 1413
Bryant, E. 1262
Bubeck, A. 1239
Buijze, L. 1327
Bunn, J. 1282
Burbidge, D. 1407
Burdick, S. 1430
Burghardt, J. A. 1398
Burgi, P. M. 1254, 1322
Bürgmann, R. 1265, 1310,
1331, 1335
Burgoa, B. 1278
Burgos, G. 1204, 1214
Burgos, V. 1350
Burk, D. 1362
Burke, G. 1324
Burlacu, R. 1216
Burlot, R. 1293
Burstein, J. 1431
Buscetti, M. 1240, 1289,
1290, 1291, 1294, 1311
Buttinelli, M. 1372
Büyükakpınar, P. 1221, 1318,
1319, 1320, 1321
Byrnes, J. S. 1270, 1448

Caballero Jimenez, G.
V. 1404
Cabas, A. 1314, 1380, 1382,
1387, 1439, 1440
Cabieces Diaz, R. 1275, 1415
Caciagli, M. 1394
Caine, J. S. 1250
Cairns, G. 1346
Caldeira, R. 1228
Calderoni, G. 1452
Caldwell, D. 1299
Callaghan, S. 1377
Calvet, M. 1449
Calvez, J. L. 1397
Camassi, R. 1254
Cambaz, M. 1418
Camilión, E. 1348
Campbell, K. W. 1194
Campillo, M. 1403, 1405
Canales, J. 1410, 1411, 1413,
1414, 1425, 1427
Canari, A. 1337
Canitano, A. 1336
Cano, Y. 1420
Cantiello, P. 1350
Cao, F. 1234
Capdeville, Y. 1204
Carannante, S. 1394
Carapuço, M. 1415
Carbotte, S. 1410, 1414
Carcione, J. 1370
Cardenas-Soto, M. 1330
Caress, D. 1304
Cari Seifert, C. 1211
Carmichael, J. D. 1209, 1212,
1214, 1326, 1356
Carol, E. 1287
Carpenter, B. 1327
Carpenter, N. 1240
Carpenter, S. 1361, 1386,
1398
Carr, C. 1212, 1374, 1375,
1376
Carrasco Rodriguez,
V. 1359
Carrillo Lucia, M. A. 1331
Carrillo-Ponce, A. 1268
Carrillo-Vargas, A. 1330
Carroll, A. 1306
Carter, J. 1340, 1341
Carthy, J. 1348, 1349
Carvajal, M. 1416
Casarotti, E. 1205
Casey, R. 1341
Casleton, E. 1355
Cassidy, J. 1235, 1237, 1249,
1316, 1330, 1382, 1385
Cassidy, K. 1339
Castellaro, S. 1290, 1314
Castillo, R. 1298
Castillo Castellanos,
J. 1432, 1434
Castro, R. 1252
Castro-Cruz, D. 1379
Casu, F. 1321
Catchings, R. D. 1259, 1291,
1321, 1422
Catugas, S. A. 1335
Caudron, C. 1351, 1408
Caumon, G. 1203, 1373
Cauzzi, C. 1288, 1361, 1362
Cearley, C. S. 1442
Cebry, S. B. L. 1450

Volume 95••

Number 2B

April 2024•

Celebi, M. K. 1321
Cellone, F. 1287
Cesca, S. 1268, 1319
Ceylan, S. 1271, 1277, 1382
Chacón, F. 1234
Chadwick, M. 1251
Chaffeur, J. 1259
Chai, C. 1217, 1287, 1422
Chaljub, E. 1311
Chamberlain, C. J. 1206,
1228, 1249, 1445
Chambers, D. J. A. 1224,
1228
Chamlagain, D. 1267, 1332
Chan, J. 1230
Chan, J. H. 1259, 1291, 1321,
1422
Chanard, K. 1310
Chandrasekhar, D. 1391
Chang, H. 1449
Chang, J. C. 1409
Chansom, C. 1436
Chanu, M. N. 1447
Chao, S. 1197
Chapman, M. 1442, 1443
Chaput, J. 1232, 1274
Charalambous, C. 1382
Charalampakis, M. 1225
Charlton, D. 1251
Chatterjee, A. 1247, 1356
Chatterjee, S. 1254, 1266
Chavarria Esquivel, N. 1417
Che, I. 1211
Cheeck, L. 1255
Chen, B. 1396
Chen, H. 1226
Chen, J. 1204
Chen, L. 1269, 1272, 1274,
1281, 1392
Chen, Q. 1269
Chen, S. 1357
Chen, T. 1326, 1366
Chen, W. 1252
Chen, X. 1222, 1244, 1274,
1276, 1293, 1295, 1296,
1349, 1350, 1372, 1398,
1399, 1453, 1454
Chen, Y. 1323, 1438, 1443,
1444
Chen, Z. 1329
Cheng, X. 1245
Cheng, Y. 1244, 1246, 1352,
1399, 1453
Cherwinka, J. 1237
Chhabra, A. 1279
Chi, W. 1345
Chiama, K. 1242
Chiang, A. 1362, 1388, 1451,
1452, 1453
Chiarabba, C. 1349
Chiaraluce, L. 1245, 1258
Chiasson-Poirier, L. 1420
Chi-Durán, R. 1213
Chifwepa, C. 1442
Childs, D. M. 1359
Chindandali, P. R. N. 1338
Choi, J. 1357
Choi, Y. 1343
Chojnicki, K. 1210, 1214
Chouinard, L. 1256
Chow, B. 1205, 1207, 1212,
1269, 1341
Chu, R. 1322

www.srl-online.org

Chu, S. 1448, 1449, 1452,
1453
Chuang, L. 1342
Ciaccio, M. 1205
Cifuentes-Nava, G. 1330
Cisternas, M. 1416
Civilini, F. 1225, 1382
Clark, D. 1433
Clark, D. J. 1390, 1437
Clark, K. J. 1296, 1392
Clarke, J. 1426, 1427
Clayton, B. 1199
Clayton, R. 1232, 1274, 1342,
1343, 1421
Clements, T. 1291
Clennett, E. J. 1272
Cline, M. L. 1302, 1305
Clinton, J. 1263, 1271, 1278,
1361, 1382
Clive, M. 1403
Cloutet, Z. 1341
Coca, O. 1301
Cochran, E. 1282, 1291,
1312, 1449
Cocina, O. 1448
Coe, J. 1264
Coffey, G. L. 1332
Coffey, J. R. 1212
Çok, Ö. 1418
Coker, S. 1221
Cole, H. 1357, 1443
Colica, E. 1287
Colip, G. D. 1296
Collares, M. P. 1228
Collett, C. 1441, 1442
Collins, E. 1263, 1264, 1266,
1267
Collins, G. S. 1212
Collins, J. 1226
Colpron, M. 1250
Colvez, M. 1204
Comstock, K. 1259
Condon, S. 1383
Conley, A. 1215, 1358
Conner, A. E. 1266
Connors, C. D. 1257
Conrad, J. 1306
Contreras, M. G. 1331
Contreras-Arratia, R. 1405
Contreras-Reyes, E. 1416
Cook, K. L. 1286, 1288
Corbett, R. 1299
Corby, N. 1390
Corela, C. 1225, 1228, 1415
Cornelio, C. 1407
Cornou, C. 1293, 1311
Correa, J. 1224, 1228
Cortés Rivas, V. 1425, 1427
Costa, C. H. 1300
Costa, R. 1382, 1385
Cotton, F. 1245, 1316, 1331
Coulter, C. 1425
Counts, R. C. 1440, 1442
Coutant, O. 1284, 1311
Cox, S. E. 1332
Craddock, W. 1257
Craig, T. J. 1421, 1451
Cram, G. S. 1347
Cramer, C. H. 1293
Crane, S. 1277, 1354
Crawford, W. 1361
Crayne, J. 1282
Creager, K. 1231, 1345

Creasy, N. 1210
Crempien, J. 1357
Criley, C. J. 1259, 1422
Crowell, B. 1276, 1387, 1424
Crozier, J. A. 1333, 1402,
1405, 1409
Cruz-Atienza, V. M. 1287,
1413
Cui, C. 1204
Cummins, P. R. 1390
Cunetta, N. 1259, 1306
Cunha, G. 1439
Cunningham, A. E. 1251,
1290, 1383
Cunningham, D. 1331
Cunningham, E. 1217, 1324
Cunningham, J. 1422
Cupillard, P. 1203, 1208,
1371, 1373
Curran, J. H. 1298
Curry, B. 1440
Curtiss, E. R. 1332
Custódio, S. 1225, 1228,
1361, 1381, 1411, 1439
Czarny, R. 1236
Czech, T. L. 1223
D’Acquisto, M. 1334
Dade, S. L. 1398
Dadi, S. 1400
Dahm, T. 1221, 1268, 1319,
1320, 1321, 1328, 1367
Dahmen, N. J. 1381, 1382
Dai, A. 1411
Daiss, I. 1279
Dalai, B. 1344
Dallachiesa, L. 1226
Dalton, C. 1412
Dalton, S. 1360
Daly, K. A. 1426, 1431
Daly, M. C. 1442
D’Amico, S. 1287, 1361
Damjanac, B. 1399
Danciu, L. 1278, 1361
Danesi, S. 1242, 1396
Danielson, L. 1374
Dannberg, J. 1445
Dannemann Dugick,F. 1218, 1219
Dannowski, A. 1275
Darold, A. P. 1361
Darragh, R. B. 1239, 1241
Darrh, A. 1215, 1366
Dartnell, P. 1301, 1302, 1306
Dascher-Cousineau,
K. 1367, 1368, 1369
Dasent, J. 1300
Daubar, I. J. 1212
D’Auria, L. 1349
Davatgari Tafreshi, M. 1197,
1200, 1201
Davenport, K. 1358
Davide, E. 1286
Davis, E. 1346
Davis, P. 1363
Davy, G. K. 1266
Dawson, P. 1406
Deane, C. 1339
Deane, C. A. 1351
De Armond, J. 1237
De Batist, M. 1297
De Cesare, W. 1350
De Cristofaro, J. 1365
De Gori, P. 1372

Seismological Research Letters

|

1457

DeGrande, J. 1276, 1424
de Groot, R. 1279, 1282
Dejneka, Z. 1231
Dekin, W. 1211
Delamere, S. 1212
Delano, J. 1392
Delbo, M. 1271
Delbridge, B. G. 1209, 1212,
1214, 1216, 1227, 1355,
1453
del Fresno, C. 1275
Delgado Granados, H. 1404
Deligne, N. I. 1220
Delle Donne, D. 1350
DeLong, S. 1195, 1243, 1258,
1261
Delorey, A. A. 1232
Delph, J. R. 1272
Del Piccolo, G. 1233, 1448
De Luca, C. 1321
de Montserrat, A. 1448
Deng, K. 1233
Dengler, L. A. 1254, 1320,
1386
Deniz Hisarlı, P. 1418
Denolle, M. 1226, 1227,
1229, 1238, 1263, 1315,
1339, 1340, 1341, 1346,
1347, 1365, 1366, 1410,
1429, 1431
DePaolis, J. 1298
de Raucourt, S. 1271
Derosier, B. 1301, 1302, 1306
DeSalvio, N. D. 1420
DeShon, H. R. 1194, 1323,
1324
Dettmer, J. 1235, 1237, 1250,
1316, 1325, 1347
Development Team, N. 1194
Devera, J. A. 1440
de Vos, M. 1309
Dewaelsche, P. 1413
Dexter, J. 1346
Dey, I. 1284
Dhakal, H. 1390
Dhara, A. 1343
Dianala, J. B. 1335
Diaz, M. 1252
Díaz, J. 1436
Díaz-González, A. 1436
Díaz-Suárez, E. A. 1275
Dietze, M. 1284, 1286
Di Giacomo, D. 1353
Di Luccio, F. 1374
Di Martino, A. 1314, 1316
Ding, C. 1319, 1321
Ding, H. 1318
Ding, L. 1202, 1213
Dingo, H. 1228
Diomi, L. 1408
Dioslaki, A. 1294
Di Stefano, R. 1205
Dittmann, T. 1339, 1340,
1341
Doglioni, C. 1220
Dominguez, L. A. 1287,
1301, 1422
Domínguez-Cerdeña,
I. 1275
Domino, J. 1323
Donahue, C. 1229, 1275,
1374
Dong, S. 1274

1458

|

Donnellan, A. 1334
Donohoe, B. 1215
Doody, C. 1451
Doser, D. I. 1299, 1326
Dosso, S. E. 1330, 1347
Dotray, P. 1409
Doubravová, J. 1221
Douglas, K. 1261
Douilly, R. 1273, 1371, 1374
Douste-Bacqué, I. 1289,
1293, 1294
Downs, D. T. 1220
Doyle, M. 1260
Dreger, D. S. 1213, 1320,
1386, 1453
Drilleau, M. 1271
Drymoni, K. 1444
d’Oreye, N. 1403, 1408
Du, N. 1207, 1270
Duan, B. 1309, 1372
Duarte, J. 1415
Duckworth, W. 1255, 1299
Dunham, A. 1202, 1300
Dunham, E. M. 1284, 1370
Dunn, R. 1272
Dunning, A. 1332
Dura, T. 1296, 1298, 1300,
1301, 1303, 1338
Duran, C. 1382
Duran, K. 1229
Durand, V. 1395
DuRoss, C. B. 1298, 1305,
1306, 1318, 1319, 1334,
1335
Dutta, A. 1315
Dutta, U. 1311, 1315, 1317
DuVernois, M. 1237
Dybing, S. 1336, 1381
Dyer, B. 1399
Dzenitis, B. 1211
Dzubay, A. 1398
Earle, P. 1351, 1354, 1357,
1358, 1443
Eaton, D. 1325
Ebel, J. E. 1391, 1436
Ebeling, C. 1286, 1288, 1363
Eberhart-Phillips, D. 1249
Ebmeier, S. 1451
Edme, P. 1239
Edwards, M. 1390
Egan, S. 1212
Eguchi, R. 1387
Eilon, Z. 1270, 1412, 1413
Eisen, O. 1238
Eisenberg, D. P. 1377, 1378
Eisermann, A. S. 1354
Ekström, G. 1202
Elbanna, A. E. 1333
Elbing, B. R. 1374, 1375,
1376
Elfass, S. 1384
El Ghaoui, L. 1342
Eliassi, M. 1216
El Kadri, S. 1242
El-kasseh, G. 1396
Ellett, N. 1302, 1305
Elliott, A. 1243, 1246, 1306,
1307
Elliott, J. 1352, 1424, 1425,
1428, 1435, 1451
Ellison, S. M. 1383
Ellsworth, W. L. 1284, 1324,
1357, 1449

Seismological Research Letters

Elmeliegy, A. M. 1343, 1344
Elsayed Mohamed, M.
M. 1436
Ely, J. 1214
Emry, E. L. 1210, 1215
Engelhart, S. E. 1303
England, K. 1396
Engler, D. T. 1317
Enkelmann, E. 1250
Enos, R. 1299
Ercolani, E. 1254
Erdem, J. E. 1321
Ergin, M. 1319, 1321
Ergintav, S. 1229
Ergun, T. 1418
Erichson, B. N. 1277
Erichson, N. B. 1312
Ericksen, T. 1333
Errico, M. 1394, 1396
Escobar-Wolf, R. 1262, 1268
Escobedo-Zenil, D. 1330
Espi, J. 1390
Esposito, A. 1350
Esquivias, G. 1387
Esser, S. 1264
Estep, J. 1426
Evangelidis, C. 1225, 1361
Eyles, J. 1405
Ezzedine, S. M. 1211, 1213,
1219, 1378
Faccenda, M. 1233, 1244,
1446, 1448
Faenza, L. 1254, 1396
Faith, J. L. 1326
Falliner, J. 1211
Famiani, D. 1394, 1420
Fan, W. 1248, 1420
Fan, X. 1269
Fang, J. 1345
Farfuliak, L. 1359, 1362
Farge, G. 1368
Farrell, A. 1280, 1285
Farrell, J. 1223, 1362, 1406,
1420
Fast, J. 1211
Fee, D. 1211, 1285, 1349,
1403, 1404
Feigl, K. L. 1325
Feldman, J. 1210
Felizardo, C. 1277, 1282
Felzer, K. 1367
Feng, K. 1226, 1315, 1341
Feng, X. 1293, 1349
Ferguson, E. 1362
Fernando, B. 1212, 1377
Ferreira, A. 1244, 1415
Ferreira, H. 1415
Ferrer, F. 1324
Fichtner, A. 1205, 1229,
1238, 1239, 1355
Field, E. H. 1195
Figueiredo, P. 1319, 1438
Fildes, R. 1201, 1445, 1446,
1447
Fildes, R. A. 1447
Filipussi, D. 1348
Fine, I. E. 1419
Finger, C. 1328
Finley, T. 1249, 1256, 1257,
1259, 1260
Finnila, A. 1399
Fintel, A. 1332
Firetto Carlino, M. 1448

Fischer, K. M. 1430
Fischer, T. 1221
Fishwick, S. 1442
Fitzgerald, B. L. 1303
Fitzgerald, J. 1203, 1417
Fleck, P. 1324
Fleigle, M. J. 1265
Flesch, L. M. 1275
Flynn, G. 1355
Fomel, S. 1443
Fontaine, N. K. 1226
Forbes, N. 1362, 1364, 1420
Forbriger, T. 1227, 1286,
1288
Ford, H. 1232
Ford, S. R. 1453
Forsyth, D. 1412
Foster, D. 1198
Foundotos, L. 1251
Fox, D. 1375
Fox, J. L. 1220, 1222, 1362
Foxall, B. 1384
Foxe, M. 1211
Fozkos, A. 1280
Frank, W. B. 1405
Franke, M. 1279, 1443
Frankel, A. 1196, 1201, 1202
Franzese, M. 1321
Fraters, M. 1201, 1204, 1373,
1445, 1447
Frazier, J. 1255
Frederick, J. M. 1285
Freeman, N. 1341
Freymueller, J. T. 1257, 1352,
1410, 1424, 1428
Friberg, P. 1359, 1398
Friedman-Alvarez, C. 1429,
1430
Fritz, B. 1211
Froehly, A. 1203
Froment, M. 1212
Frost, D. A. 1428
Fry, B. 1251, 1308, 1309, 1320
Fu, L. 1370
Fucks, E. 1287
Fuentes, F. A. 1326
Fuentes, M. 1419
Fujimoto, M. 1272
Fukuyama, E. 1451
Fulton, P. M. 1268
Funning, G. J. 1244, 1318,
1320, 1454
Furlong, K. P. 1424, 1435,
1447
Gable, S. 1248, 1448, 1452,
1453
Gabriel, A. A. 1208, 1245,
1308, 1318, 1320, 1327,
1333, 1339, 1340, 1369,
1373
Gabrielli, S. 1293
Gabrielson, C. 1262
Gaete Elgueta, V. A. 1229,
1231, 1429, 1431
Gaherty, J. 1410, 1412, 1413,
1426, 1427
Gaidzik, K. 1301
Gaillard, P. 1420
Galanos, G. S. 1390
Galanos, N. 1390, 1391
Galasso, C. 1253, 1278
Galis, M. 1240, 1369, 1370,
1373

www.srl-online.org•

Volume 95•

Gallacher, R. 1353
Gallahue, M. 1200
Gallart, J. 1436
Gallastegui, J. 1436
Gallegos-Castillo, C. 1410
Gallovič, F. 1333
Galone, L. 1287
Gamboa-Canté, C. 1336,
1452
Gamez, R. 1374
Gammaldi, S. 1350
Gammans, C. 1212, 1214,
1215, 1358
Gann-Phillips, C. 1380,
1382, 1439, 1440
Gao, K. 1202, 1393, 1396,
1397, 1401
Gao, Y. 1234
Garces, M. A. 1375, 1376
Garcia, A. 1394, 1396
Garcia, E. 1333
Garcia, F. E. 1246
Garcia, J. A. 1208, 1213
Garcia, R. 1212, 1271, 1331
García, M. 1337
Garcia Jurado Suarez,
C. 1341
García-Mayordomo, J. 1337,
1389
García-Soto, A. 1291
Garrison-Laney, C. 1303,
1418
Garth, T. 1353
Garza, L. 1433, 1434, 1435
Garza-Giron, R. 1402, 1405
Gase, A. 1432, 1433, 1434,
1435
Gaskins Baise, L. 1294
Gasperikova, E. 1401
Gasperini, P. 1455
Gassmoeller, R. 1373, 1445
Gaucher, E. 1227
Gauntlett, M. Z. 1232, 1270
Gauvain, S. J. 1216, 1344
Gavillot, Y. 1306
Gavrilovic, S. 1384
Gaylord, J. 1211
Ge, S. 1326
Ge, Z. 1318
Gebraad, L. 1237
Geertsema, M. 1265
Geffers, G. 1394
Geissler, W. H. 1415
Geist, E. 1416
Germenis, N. G. 1287
Gerstenberger, M. 1380,
1381
Gerstoft, P. 1203, 1236
Gerya, T. 1309
Gevorgyan, M. 1338
Gharti, H. 1203, 1417
Ghasemi, H. 1390
Ghods, A. 1318, 1451
Gholizadeh Doonechaly,
N. 1395
Ghosh, A. 1206, 1272, 1318,
1446
Giampiccolo, E. 1448
Giang, A. 1303
Giardini, D. 1271, 1382, 1395
Gibbons, S. 1286, 1288
Gillis, R. J. 1426
Giordani, J. 1311

Number 2B•

April 2024

Girard, A. 1224, 1347
Giraud, R. E. 1305
Girona, T. 1348, 1349, 1350,
1351, 1352, 1353, 1404,
1407, 1444
Girot, D. L. 1199
Gischig, V. 1267, 1395
Gittins, D. B. 1246
Givler, R. 1239
Gkogkas, K. 1232, 1421
Glasgow, M. 1326, 1402,
1403, 1405
Glimsdal, S. 1286, 1288
Glinsky, N. 1203
Gochenour, J. 1215, 1366
Goddard, K. 1343
Goded, T. 1251
Godoladze, T. 1388
Goebel, T. H. 1408
Goehring, B. M. 1249
Goertz-Allmann, B. P. 1325
Goitom, B. 1232, 1270
Gok, R. 1388
Gold, R. 1195
Goldberg, D. E. 1336, 1339,
1354, 1417, 1418
Goldman, M. R. 1259, 1291,
1321, 1422
Golos, E. M. 1429, 1430, 1431
Goltz, J. D. 1280, 1367
Gomberg, J. 1348
Gomez, A. 1259
Gomez, K. 1282, 1283
Gomez, N. 1446
Gómez, M. 1348
Gómez-Novell, O. 1337
Gómez-Ramos, O. 1287
Gómez Vázquez, Á. 1404
Gong, J. 1410, 1413, 1414,
1421
Gonzalez, L. F. 1237
González-Cortina, J. 1436
González-Fernández,
A. 1410
Gonzalez-Huizar, H. 1252
Good, A. 1282
Gooley, J. 1257
Goozen, A. 1311, 1317
Gorman, A. 1251
Gosselin, J. M. 1235, 1237,
1250, 1316
Gossett, D. 1368
Gottlieb, M. 1258
Gou, Y. 1281
Gouache, C. 1208, 1373
Goulet, C. 1379, 1380
Govers, R. 1334, 1336
Govoni, A. 1420
Gradon, C. 1231
Gräff, D. 1236
Grand, S. P. 1272
Granja-Bruña, J. 1198
Grant, A. 1201, 1202, 1272,
1300
Grant Ludwig, L. 1416
Grapenthin, R. 1224, 1274,
1276, 1280, 1281, 1351,
1354, 1404, 1406, 1424,
1428
Graves, E. 1405
Graves, R. 1202, 1380
Gray, B. 1239
Gray, H. 1259, 1305

Greb, S. 1398
Green, D. 1216, 1366
Green, R. A. 1390
Greene, G. 1433
Greenfield, M. W. 1382,
1385, 1386
Greenlee, J. M. 1338
Grendas, I. 1289, 1311
Grevemeyer, I. 1275, 1344,
1345
Gridley, J. 1417
Griffin, J. D. 1390, 1437
Grigoli, F. 1396
Grigoratos, I. 1323, 1394
Grimm, J. 1239
Groom, J. 1252
Grøvan Aspaas, A. 1264
Grulke, S. L. 1237
Gu, C. 1203, 1329
Gualandi, A. 1258
Guattari, F. 1365
Guéguen, P. 1331
Guevara Ortiz, E. 1404
Guilhelm Trilla, A. 1219
Guillot, L. 1204, 1214
Gulia, L. 1455
Gulick, S. P. S. 1382
Gunay, S. 1202
Güneş, Y. 1418
Guo, H. 1324, 1449
Guo, P. 1336, 1339
Gupta, A. 1205, 1234
Gusman, A. 1407
Guy, M. 1354
Gwiazda, R. 1304
Haagenson, R. J. 1397
Haaser, R. A. 1377
Haberland, C. 1361
Haberli, G. 1342
Haendel, A. 1316
Haeussler, P. J. 1195, 1296,
1297, 1298, 1301, 1302,
1307, 1308, 1379, 1393,
1394
Hagemeier, D. 1413
Hainzl, S. 1367
Haji-Soltani, A. 1200
Hale, J. M. 1362, 1406, 1420
Hallal, M. M. 1311, 1314
Hallissey, M. 1236
Hamilton, A. 1340, 1341
Hamilton, J. C. 1301
Hamling, I. 1407, 1408
Hammer, M. 1243, 1258,
1260, 1261
Hammond, J. O. S. 1232,
1270
Hampton, J. 1324, 1368
Han, S. 1410, 1413, 1414,
1454, 1455
Han, Z. 1336, 1339
Hanagan, C. E. 1258
Haney, M. M. 1212, 1220,
1264, 1349, 1351, 1403,
1404, 1409, 1410, 1431,
1432
Haniiev, O. 1359, 1362
Hanks, T. C. 1292
Hansen, D. D. 1236
Hao, S. 1204
Hardebeck, J. 1252, 1253,
1326, 1333, 1369

Volume 95••

Number 2B

April 2024•

Harding, J. L. 1216, 1342,
1343, 1344
Hardwick, C. L. 1268
Hariharan, A. 1412
Harmon, N. 1198
Harrington, M. J. 1347
Harrington, R. M. 1449
Harris, J. 1353
Harris, K. 1415
Harris, R. 1389
Harris, R. A. 1246, 1369
Harrison, S. 1403
Hartog, R. 1263, 1353, 1358,
1359
Hasnain, M. 1322
Hassani, B. 1240
Hasumi, Y. 1376
Hatem, A. E. 1195, 1198,
1246, 1304, 1306, 1318,
1319, 1334, 1335
Hattori, K. 1443, 1444, 1445
Havlin, C. 1412
Hawkes, A. 1303, 1338
Hawthorne, J. C. 1246, 1423
Hayes, G. 1354, 1385
Hayman, N. 1322
Haynie, K. L. 1200, 1310,
1339, 1340, 1341, 1385,
1417, 1426, 1427
Hayward, C. 1211
He, B. 1270, 1429
He, D. J. 1394
He, P. 1387
Hearne, M. G. 1251, 1290,
1339, 1383
Heath, B. 1417
Heaton, T. 1282
Hecker, S. 1300, 1301
Heesemann, M. 1346, 1362
Heimann, S. 1268, 1328
Helgason, W. 1286
Heller, G. 1448
Heller, S. 1198
Hellweg, M. 1320, 1386
Helmericks, J. 1360
Helmold, K. P. 1426
Hemming, S. R. 1332
Hemphill-Haley, E. 1300,
1303
Hemphill-Haley, M. 1258,
1261
Henson, I. 1281, 1282
Herman, M. W. 1424, 1447
Hernandez-Bernal, J. 1423
Herr, B. 1437
Herrán, C. 1282
Herrera, C. 1388
Herrero-Barbero, P. 1389
Herrick, J. A. 1194, 1195,
1196, 1197, 1198, 1199
Herrmann, R. B. 1323, 1358
Hertrich, M. 1395
Heslop, J. 1285, 1363
Heyburn, R. 1216, 1217
Hibert, C. 1262, 1265, 1286,
1288
Hickman, J. B. 1398
Hicks, S. P. 1286, 1288, 1415
Hidy, A. J. 1299
Higman, B. 1265
Hill, J. 1296, 1301, 1302,
1303, 1304, 1306, 1307,
1416

www.srl-online.org

Hill, M. 1380
Hill, P. 1283, 1346, 1366,
1399
Hille, M. 1255
Hillers, G. 1328
Hirakawa, E. T. 1291, 1315,
1377, 1380
Hirao, B. W. 1220, 1406
Hirata, T. 1360
Hirth, G. 1247
Hiscock, A. I. 1305
Hobbs, T. E. 1251, 1253,
1254, 1256, 1259, 1260,
1261, 1382, 1385, 1386,
1391
Hodgkinson, K. M. 1230,
1231
Hoefer, B. A. 1399
Hofstede, C. 1238
Hofstetter, C. 1244
Hoggro, C. 1360
Holden, C. 1206
Holland, C. W. 1347
Hollender, F. 1240, 1288,
1289, 1290, 1291, 1292,
1293, 1294, 1311, 1312
Hollyday, A. E. 1446
Holmgren, J. M. 1325
Holtkamp, S. 1221, 1257,
1280, 1285, 1363
Holtzman, B. 1238, 1412
Homa, D. 1231
Hong, T. 1436
Hong, Y. 1454
Hooft, E. 1220, 1272, 1414,
1446
Hoots, C. 1346
Hopp, C. 1393, 1397, 1399
Horleston, A. 1382, 1423
Hornsby, K. T. 1299
Horspool, N. 1251
Horst, A. 1332
Horton, S. 1375
Hosseini, K. 1415
Hotovec-Ellis, A. 1402,
1404, 1405, 1406
Hou, W. 1370
Hough, E. 1375
Hough, S. E. 1439
Houltham, J. 1251
Howarth, J. 1296
Howell, A. 1296, 1308, 1309,
1320, 1380, 1392, 1393
Hoxey, A. K. R. 1332
Hoyle, A. M. 1229, 1446
Hreinsdóttir, S. 1407
Hsiao, L. 1224
Hsu, Y. 1247
Hu, J. 1411
Hu, S. 1344
Hu, Z. 1387
Huang, D. 1443
Huang, G. 1323, 1324
Huang, J. 1197, 1292
Huang, L. 1393, 1396, 1397,
1401
Huang, X. 1332
Huang, Y. 1226, 1244, 1248,
1453
Hubbard, P. 1384
Hubenthal, M. 1342
Hubert-Ferrari, A. 1408
Hudson, T. 1232, 1270

Huérfano, V. 1248, 1353,
1354
Huerta-López, C. I. 1314
Hufstetler, R. S. 1414
Hughes, A. 1258
Hughes, K. 1259
Hui Lai, V. 1230
Humphrey, J. A. 1309
Hung, S. 1414
Hunsinger, H. 1339, 1341,
1417
Hunter, E. 1339, 1341
Hurtado, J. M. 1391
Husker, A. 1225, 1282, 1355,
1357, 1360, 1365
Hutabarat, D. 1384
Hutchinson, J. 1362
Hutchinson, T. 1384
Hutko, A. 1263, 1365
Hwang, L. J. 1201, 1445,
1446, 1447
Hylland, M. D. 1305
Iacobucci-Jund, H. 1289
Ibáñez, J. 1348, 1349, 1350,
1352
Ichinose, G. 1209, 1216,
1366, 1406, 1448, 1452
Ide, S. 1244
Iezzi, A. 1262, 1404, 1409
Igarashi, T. 1369
Igel, J. 1229
Igonin, N. 1322, 1325, 1326
Illsley-Kemp, F. 1407
Im, K. 1327
Iranpour, K. 1325
Islam, M. 1421
Islam, S. 1375
Issah, A. S. 1231, 1340
Isse, T. 1414
Ito, E. 1312
Ito, G. 1446
Ito, Y. 1413
Iturrieta, P. 1367
Jacob, J. D. 1375
Jacobs, K. 1407, 1415
Jadamec, M. A. 1310, 1426
Jagniecki, E. 1397
Jaimes, M. 1291
Jaiswal, K. S. 1195, 1385
Jamalreyhani, M. 1318,
1320, 1321
Jamelot, A. 1251
Jana, N. 1337
Janiszewski, H. A. 1344,
1345, 1346, 1402, 1431,
1432
Jarvis, P. A. 1403
Jaski, E. 1366
Jaume, S. 1223, 1391, 1440
Jaye Oliva, S. 1434
Jeffery, S. 1226
Jensen, A. 1236
Jensen, B. J. L. 1307
Jensen, E. 1267
Jeong, S. 1327
Jha, K. 1418
Ji, C. 1311, 1314, 1439, 1440
Ji, Q. 1284
Ji, X. 1236
Ji, Y. 1310
Jia, Z. 1244, 1246
Jian, H. 1410, 1411, 1413
Jian, P. 1247

Seismological Research Letters

|

1459

Jiang, C. 1244
Jiang, J. 1222, 1244, 1246,
1247, 1248, 1267, 1310,
1327
Jiang, X. 1443
Jie, Y. 1412
Jih, R. 1209
Jiménez, M. 1337
Jin, G. 1224, 1231
Jin, X. 1438
Jitmahantakul, S. 1436
Jo, K. 1273
João, M. 1411
John, S. 1285
Johns, W. 1258
Johnson, C. 1211
Johnson, J. 1262, 1266, 1268,
1407
Johnson, K. E. 1384
Johnson, K. M. 1196
Johnson, S. 1340
Jolly, A. 1407, 1409
Jonda, L. 1390
Jones, C. 1399
Jones, E. 1391
Jones, J. S. 1360
Jónsdóttir, K. 1238, 1351
Jordan, P. 1282, 1283, 1384
Jordan, T. H. 1194
Journeau, C. 1220, 1405
Jozinović, D. 1221, 1263,
1444
Juarez Garfias, I. 1206
Juarez-Zuniga, A. 1274
Jung, Y. 1400
Justiniano, C. 1199
Kafka, A. 1391
Kaiser, A. 1251, 1380
Kaklamanos, J. 1294, 1382,
1385
Kakodkar, R. R. 1203
Kakoty, P. 1384
Kalafat, D. 1418
Kalinski, M. 1361
Kalkan Ertan, E. 1229
Kamalov, V. 1226
Kamata, S. 1423
Kame, N. 1374
Kang, B. 1329
Kang, H. 1414
Kang, S. 1316
Kang, T. 1316
Kao, H. 1318
Karakaş, M. 1318, 1334
Karamzadeh, N. 1227
Karantzalos, K. 1229
Karasozen, E. 1262, 1264,
1265, 1266, 1391
Karlstrom, L. 1409
Karplus, M. S. 1232, 1239,
1326, 1390, 1391
Karrenbach, M. 1225
Karvounis, D. 1399
Kästli, P. 1361
Kato, A. 1244, 1369
Katoh, Y. 1375
Katuwal, S. 1313
Kaufman, D. 1304, 1307
Kaven, J. 1325
Kawakatsu, H. 1411, 1414
Kawamura, T. 1212, 1271,
1382, 1423
Kawase, H. 1312

1460

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KC, R. J. 1375
Ke, K. 1415
Keach, II, R. 1274
Keating, S. 1238
Kedar, S. 1381
Keep, M. 1298
Keheller, M. 1226
Kehoe, H. L. 1206
Keil, S. 1420
Kekovalı, K. 1418
Kelley, D. S. 1347
Kelley, M. 1398
Kelly, B. 1201
Kelsey, H. 1258, 1261, 1299,
1300, 1303, 1307, 1308,
1338, 1393
Kelson, K. I. 1194
Kemna, K. B. 1449
Kemp, J. 1390, 1437
Kendall, E. 1244
Kendall, J. 1232, 1270
Kendall, M. 1442
Kennedy, K. 1433
Kerekes, R. 1287
Kervyn, F. 1408
Khalkhali, M. 1221
Khan, S. 1280
Kharita, A. 1229, 1263
Khashchevskaya, D. 1320
Kilburn, R. 1300
Kilgore, B. 1333
Kilgour, G. 1403
Kilicarslan, O. 1321
Kim, B. 1436, 1454
Kim, D. 1212, 1271, 1382,
1426
Kim, H. 1268, 1410, 1411,
1413
Kim, J. 1202, 1386, 1392,
1393
Kim, K. 1316, 1352, 1407,
1414
Kim, S. 1273, 1388
Kim, T. 1395
Kim, W. 1439, 1454
Kim, Y. 1288, 1410, 1414,
1415, 1417, 1454
Kimura, J. 1423
King, T. 1437
Kinkel, D. 1278
Kintner, J. A. 1202, 1209,
1216, 1218
Kiratzi, A. 1321, 1361
Kirby, M. 1307
Klaasen, S. 1229, 1238
Kleber, E. J. 1305
Klinger, A. G. 1247
Klinger, R. 1259
Klinger, Y. 1242
Kluesner, J. 1296, 1301, 1305,
1306
Knapmeyer-Endrun,
B. 1271
Knepley, M. 1308, 1309
Knepley, M. G. 1309, 1310
Knight, B. 1311
Knodel, E. J. 1253, 1255,
1290, 1383
Knox, H. 1210, 1211, 1214
Knudsen, K. 1195
Knudson, T. 1449
Knupfer, J. 1361
Kobayashi, M. 1375

Seismological Research Letters

Koch, M. 1254, 1266
Koch, P. 1353, 1357, 1417
Koehler, R. D. 1260, 1299,
1319
Koelzer, A. J. 1309
Koketsu, K. 1386
Kolaj, M. 1240, 1354
Kolínský, P. 1270, 1361, 1363
Konca, O. 1229
Kong, Q. 1209, 1343, 1356
Konidaris, A. 1289, 1294,
1311
Konzett, J. 1297
Koper, K. 1222
Koper, K. D. 1216, 1268, 1271
Kopp, H. 1344
Korja, A. 1328
Korsgaard, N. J. 1286, 1288
Koshimura, S. 1387
Kotha, S. R. 1291, 1294
Kottke, A. 1243, 1313, 1314,
1382, 1385, 1442
Koumantaros, K. 1225
Kounoudis, R. 1442
Kouskouna, V. 1390, 1391
Kozaci, O. 1306
Kraft, T. 1221
Kragness, D. 1358
Kramer, A. 1353
Kramer, R. L. 1262
Krauss, Z. 1339, 1340, 1345,
1362, 1363
Krenz, L. 1370
Krishnamoorthy, S. 1375,
1376
Kristek, J. 1240, 1369, 1370,
1373
Kristekova, M. 1370
Kroll, K. 1394
Kromer, E. 1237
Krüger, F. 1411, 1415
Ktenidou, O. J. 1239, 1241,
1242
Kühn, D. K. 1325
Kuiper, Y. D. 1235
Kulesza, O. 1307, 1437
Kulikov, E. 1419
Kumar, A. 1447
Kumar, N. 1447
Kumar, P. 1344
Kumar, U. 1235, 1255, 1273
Kung, Y. 1217
Kuo, C. 1292
Kuplovskyi, B. 1359, 1362
Kupres, C. A. 1407, 1410
Kuroda, S. 1243
Kurokawa, H. 1423
Kurzon, I. 1247, 1450
Kutz, J. 1227
Kvatadze, R. 1225
Kwiatek, G. 1222, 1245, 1394
Kwong, S. 1415
Kyambikwa, A. 1408
Kyriou, A. 1289
Labedz, C. 1235, 1237
Labrado, A. L. 1347
Lacoua, L. Z. 1251
Lacour, M. 1197, 1312, 1313
Lacroix, P. 1264
La Greca, J. 1306, 1437
LaHusen, S. 1300
Laintz, K. 1211
Laly, M. 1256

Lam, E. 1377
Lamb, O. 1403, 1407
Lambeck, L. 1274
Lamothe, M. 1256
Lanari, R. 1322
Landrø, M. 1225
Lange, D. 1275, 1344, 1415
Langet, N. 1264, 1325
Langkilde, M. 1220
Langridge, R. 1306, 1309
Langston, C. A. 1374, 1375,
1376, 1377
Lanteri, A. 1237
Lantz, B. 1281
Lanza, F. 1393, 1397
Lapins, S. 1448
Lapusta, N. 1244
Largent, M. 1243, 1384
Larmat, C. 1212
La Selle, S. 1301, 1305, 1307,
1338, 1416
Lastowka, L. 1341
Latychev, K. 1446
Lavoué, A. 1231
Lavrentiadis, G. 1241, 1290,
1318, 1334, 1384
Lawrence, M. 1260
Lawson, R. 1403
Lay, T. 1387
Layland-Bachmann, C.
E. 1394
Lease, R. O. 1249, 1250,
1257, 1393
Lebedev, S. 1438
Leclerc, P. 1428
Lecocq, T. 1286, 1288, 1351
Leconte, J. 1347
Lee, H. 1273, 1441
Lee, J. 1247, 1330, 1436
Lee, S. 1316, 1414
Lee, Y. 1387, 1388
Leeds, A. 1317, 1442
Legentil, C. 1203
Legre, J. B. 1441
Lei, T. 1270, 1371
Lei, Z. 1212
Leidelmeijer, J. 1307
Leifer, J. 1398
Leishman, T. 1316, 1330
Leithold, E. L. 1296
Lellouch, A. 1224
Lemus, I. C. 1310
Lentas, K. 1355
Leonard, L. 1249, 1261
Leonel, J. 1248, 1423
LePain, D. L. 1426
Leptokaropoulos, K. 1400
Leroy, T. 1258, 1261
Levandowski, W. 1425,
1436, 1440
Levin, V. 1438
Levy, R. 1392
Lewandowski, N. 1194
Lewis, R. 1374, 1376
Lewis, R. D. 1377
Li, B. 1206
Li, D. 1213, 1329, 1380, 1396,
1397
Li, G. 1203, 1273
Li, H. 1207, 1373, 1437
Li, J. 1225, 1336, 1421
Li, L. 1337
Li, S. 1392

www.srl-online.org•

Volume 95•

Li, W. 1274, 1445
Li, Y. 1234, 1325
Li, Z. 1274, 1293, 1372, 1427
Liang, C. 1234, 1322
Liang, X. 1222, 1274, 1288
Liao, J. 1224
Liao, Y. 1308
Liao, Y. M. 1251
Liberty, L. M. 1297, 1307
Light, T. 1212
Lin, C. 1292, 1365
Lin, F. 1232, 1250, 1268,
1273, 1421
Lin, G. 1248, 1352, 1425
Lin, J. 1423
Lin, K. 1255
Lin, P. 1414
Lin, Y. 1230, 1342, 1391
Lindberg, N. S. 1306, 1317,
1438, 1442
Lindquist, K. 1443
Lindsay, D. 1213
Lindsey, J. C. 1283, 1286,
1346, 1366, 1399
Lindsey, N. 1228
Lindvall, S. 1384
Link, F. 1232, 1234, 1235
Liou, I. Y. 1243
Lipkowitz, P. 1211
Lipovsky, B. 1227, 1229,
1231, 1236, 1238, 1239,
1429, 1431
Lisson, K. 1297
Litchfield, N. 1296, 1309,
1392
Liu, C. 1233, 1272, 1387
Liu, F. 1451
Liu, L. 1428, 1437
Liu, M. 1230, 1438
Liu, Q. 1202, 1207, 1213,
1270, 1429
Liu, T. 1270, 1429
Liu, X. 1207
Liu, Y. 1445
Liu, Z. 1234
Lizama, D. 1344
Lizarralde, D. 1410, 1425,
1427
Lizik, Y. 1407
Llenos, A. L. 1195, 1200,
1220, 1222, 1223, 1253
Lloyd, A. 1201, 1204, 1445,
1446, 1447
Lo Bue, R. 1448
Lockner, D. 1333
Loeberich, E. 1232, 1234,
1235
Logan, T. A. 1257
Lognonné, P. H. 1212, 1271,
1381
Lolli, B. 1455
Lomax, A. 1251, 1320, 1323,
1337, 1386, 1434
Lombard, P. N. 1283
Long, M. D. 1235
Long, P. 1302
Loos, S. 1251, 1253, 1255,
1382, 1383, 1385
Lopez, T. 1352, 1404
López-Garcia, P. 1330
López-Venegas, A. M. 1195,
1199, 1259
Lord, N. E. 1324, 1429

Number 2B•

April 2024

Lorenz, R. D. 1381, 1423
Lorenzo-Velazquez,C. 1382, 1385, 1386
Losasso, E. 1338
Loso, M. 1297
Lotto, G. 1279
Loureiro, A. 1228, 1415
Løvholt, F. 1286, 1288
Low, G. 1341
Lozano, L. 1337
Lozos, J. 1245, 1249, 1378
Lucas, A. 1286, 1288
Luckie, T. W. 1227
Luco, N. 1379
Ludwig, L. G. 1443, 1444
Luhmann, A. J. 1215
Lui, S. 1324, 1327
Luis, M. 1411
Luna, E. 1359
Lundsten, E. 1304
Luo, G. 1438
Luo, Y. 1232, 1235
Lutu-McMoore, E. 1220
Luu, K. 1384
Lux, A. I. 1276, 1281, 1282,
1283
Luzi, L. 1361
Lv, H. 1230
Lyakhovsky, V. 1450
Lynch, E. M. 1259, 1260
Lynn, K. J. 1409
Lynner, C. 1233, 1270
Lyons, J. J. 1266, 1402, 1403,
1404, 1405
Lyu, C. 1273, 1371
Lyu, D. 1277
Ma, J. 1337, 1340
Ma, K. 1224
Ma, X. 1395
MacCarthy, J. K. 1215
MacDonald, M. 1330
Mace, B. 1322, 1328
Maceira, M. 1217, 1287, 1422
Macguire, R. R. 1273
Mach, P. V. 1319, 1321
Macías, M. A. 1251, 1253,
1254
Mackey, K. 1362
Macleod, G. 1211
Macpherson, K. A. 1211,
1285
Madden, E. H. 1245, 1308,
1331, 1335
Madera, N. 1378
Madin, I. 1332
Madugo, C. 1243
Maechling, P. J. 1367, 1377
Magnoni, F. 1205
Mahan, S. A. 1259, 1305
Mahanama, A. 1293
Mahdi, H. 1452
Maher, S. 1406
Mahoney, M. W. 1312
Mai, P. M. 1205, 1206, 1319,
1379, 1385
Maier, N. 1229, 1238, 1275
Majer, E. 1393
Major, J. J. 1262
Makdisi, A. 1382, 1385
Makus, P. 1415
Malatesta, L. 1359
Malfante, M. 1420
Malik, O. A. 1312

Malone, S. D. 1231, 1263
Manalang, D. A. 1347
Manaster, A. E. 1418
Mandler, E. 1258
Manga, M. 1300
Mangeney, A. 1264, 1286,
1288
Mann, M. E. 1198, 1268,
1410, 1411, 1426
Manos, J. M. 1235, 1236,
1237
Mansour, W. B. 1232, 1234
Manunta, M. 1321
Mao, S. 1284, 1286
Marano, K. 1253, 1385
Marcelino, M. 1350
Marchetti, E. 1262
Marcillo, O. 1217, 1287, 1422
Marcou, S. 1255, 1293
Marcuson, R. K. 1304
Margerin, L. 1448
Marignier, A. 1415
Marinaro, G. 1286
Mark, H. F. 1256, 1411, 1425,
1427
Marroquin, G. 1278
Marsaglia, K. 1410
Marschall, E. 1371, 1374
Marsman, C. 1334
Martí, A. T. J. 1279
Martí, J. R. 1279
Martin, E. C. 1433
Martin, E. R. 1224, 1229,
1230, 1231, 1236, 1239,
1295, 1339, 1340, 1341
Martín-Barajas, A. 1410
Martinez, E. 1339, 1341
Martinez, S. N. 1383
Martínez-Cruzado, J.
A. 1195, 1314
Martinez-Garzon, P. 1222,
1245
Martínez-González, J. 1330
Martínez-Jaramillo,
D. 1294
Martínez-Loriente, S. 1337
Marty, J. 1281, 1363
Mashagiro, N. 1408
Maso, E. 1346
Mason, H. B. 1318, 1334
Massin, F. 1263, 1277, 1278
Masson, Y. 1371
Matenco, L. 1327
Matias, L. 1225, 1228
Matoza, R. 1406
Matsubara, Y. 1368
Matsumoto, N. 1249
Matsuzawa, T. 1249
Matulka, P. 1427
Matzel, E. 1343
Maufroy, E. 1289, 1293, 1294
Maupin, V. 1276
Maurer, B. 1300
Maurer, H. 1395
Maurer, J. 1407, 1408
Mavonga, G. 1408
Maxwell, D. A. 1299
May, D. A. 1208
Mayeda, K. 1452, 1454
Mayor, J. 1448
Mazur, M. 1226
Mazuyer, A. 1371
McBrearty, I. W. 1356

Volume 95••

Number 2B

April 2024•

McBride, J. 1274, 1389
McBride, S. K. 1223, 1252,
1253, 1279, 1280
McCabe, C. 1218, 1324
McCallen, D. 1384
McCausland, W. 1404
McCloskey, J. 1205
McCormack, D. A. 1354
McCreary, M. E. 1267
McDonald, G. N. 1305
McFarlin, H. 1285, 1363,
1420
McGhee, E. 1235, 1237, 1238,
1374
McGlue, M. M. 1347
McGowan, S. 1253
McGuire, C. 1347
McKean, A. P. 1268
McKenzie, K. A. 1447
McLaskey, G. C. 1450
McLaughlin, K. L. 1223
McLaughlin, R. 1258
McLean, J. H. 1305
McLennan, J. 1395, 1399
McLennan, T. 1308
McNab, A. 1228
McNamara, D. 1341
McNutt, S. R. 1221, 1353
McPherson, A. 1207, 1213,
1431
McPherson, R. C. 1258,
1320, 1386
McPhillips, D. 1300, 1307,
1438, 1439
Medvedev, I. 1419
Medvedeva, A. E. 1419
Meier, M. 1282
Meier, P. 1399
Meier, T. 1363
Melgar, D. 1336, 1339, 1381,
1387, 1417, 1419, 1422
Melis, N. S. 1355
Mellors, R. J. 1230, 1284,
1286, 1363, 1406
Melnick, D. 1297, 1417
Melnik, O. 1403, 1405
Mencin, D. 1340, 1341, 1342
Mendoza, M. M. 1224, 1228,
1230, 1326
Mendoza, R. 1260
Meng, C. 1203
Meng, H. 1288
Meng, L. 1322
Meng, Q. 1309
Meng, X. 1377, 1378, 1380
Menounos, B. 1260
Menzhi, M. 1343
Merchant, B. J. 1364
Mérida, R. 1268
Mestel, E. 1407
Metz, D. 1344
Metz, M. 1319, 1321
Meyer, E. H. 1294
Meyer, F. J. 1257
Mia, M. 1333
Miao, W. 1207
Miao, Y. 1226
Michael, A. J. 1195, 1200,
1220, 1223, 1252, 1253
Mihai, H. 1225
Milburn, T. W. 1210
Miljkovic, K. 1212
Miller, B. 1249

www.srl-online.org

Miller, C. 1407
Miller, D. J. 1217
Miller, I. M. 1393
Miller, J. A. 1217
Miller, M. S. 1250, 1410,
1437
Miller, N. 1410, 1413, 1414,
1435
Miller, X. 1211
Milliner, C. 1318, 1334
Mills, K. 1282
Milner, K. R. 1196, 1202
Minson, S. E. 1291, 1312
Miranda, M. 1415
Mitani, T. 1423
Mitra, D. 1387, 1388, 1443
Mitra, I. 1375
Mitrovica, J. X. 1446
Mixco, L. 1252, 1278
Miyake, H. 1386, 1454
Mizrahi, L. 1367, 1444, 1445
Mizuno, T. 1397
Moaveni, B. 1254, 1266,
1383, 1389
Mochizuki, K. 1415
Mock, J. 1266
Moczo, P. 1240, 1369, 1370,
1373
Modney, T. 1255
Modrak, R. T. 1202, 1208,
1213
Moernaut, J. 1297
Mohamed Moussa, H. 1436
Mohammadi
Ghanatghestani,A. 1398
Mohammed, S. A. 1331
Mohanna, S. 1322
Mohapatra, S. 1340
Mohler, M. 1341, 1354
Molina Hutt, C. 1384
Molinari, I. 1394
Montaldo-Falero, V. 1243
Montalva, G. 1297, 1307
Monterroso, F. 1321
Moodie, N. 1396
Moore, C. 1418
Moore, D. 1333
Moore, J. 1267
Moore, J. N. 1399
Moran, S. C. 1262
Moratalla, J. 1252
Mordret, A. 1231, 1284,
1286, 1288, 1351
Moreiras, S. M. 1335
Morell, K. 1296, 1301
Morelli, A. 1394, 1448
Morency, C. 1204
Moreno, M. 1416
Moreno, V. 1297
Moresi, L. 1308, 1309, 1310
Morgenstern, R. 1306, 1333
Morozov, D. 1312
Morris, I. 1256
Morten, J. 1225
Morton, E. 1420
Moschetti, M. P. 1195, 1196,
1198, 1201, 1206, 1317,
1388
Moser, L. 1427, 1428
Mosqueda, A. 1419
Moss, R. 1242
Motamed, R. 1292

Motamedi, M. 1330
Moucha, R. 1338
Mousavi, S. 1437
Mueen, A. 1216
Mueller, C. S. 1195
Mukhopadhyay, S. 1447
Mulder, W. 1371
Munch, F. 1273
Munguiko, O. 1408
Muñoz, C. 1279
Muñoz, L. F. 1423
Muntendam-Bos, A.
G. 1393, 1396, 1397,
1400
Murakami, H. 1423
Murdie, R. 1437
Murdoch, N. 1381, 1423
Murphy, J. R. 1217
Murphy, M. A. 1332
Murphy, N. 1280, 1285,
1363, 1420
Murray, J. R. 1280
Murray, R. 1216
Musinu, G. 1290, 1314
Myers, S. 1211
Myren, S. 1355
Nabelek, J. 1338
Nackers, C. 1256
Nadin, E. S. 1280, 1341
Nagaso, M. 1204, 1207, 1341
Naiman, I. 1312
Naish, T. 1392
Nakata, N. 1232, 1277, 1288,
1312, 1313, 1315, 1343,
1393, 1397, 1399, 1449,
1450
Nakata, R. 1277, 1312, 1313,
1315
Nakayachi, K. 1367
Namogo, D. 1408
Nath, R. R. 1387, 1388
Nayak, M. 1212
Naylor, M. 1378
Nedimović, M. R. 1346,
1426, 1431, 1432, 1433,
1434, 1435
Neely, J. S. 1200, 1369, 1450
Neilson, D. T. 1226
Nelson, A. R. 1298, 1308
Nelson, J. 1393
Nelson, P. 1202, 1210, 1214
Nelson, S. T. 1274
Nelson, W. 1440
Neo, J. 1226, 1248
Neres, M. 1415, 1439
Nettles, M. 1202
Neuhauser, D. 1281
Nevitt, J. M. 1246, 1333
Newman, A. 1338, 1417
Newman, Z. 1366
Ni, Y. 1226, 1227, 1263, 1315,
1341, 1346, 1365, 1429,
1431
Nichols, T. 1416
Nicholson, B. 1286
Nickolsky, D. 1285
Nicol, A. 1308, 1309, 1320
Nicolsky, D. 1236, 1415,
1416, 1419
Nicovich, S. R. 1195, 1298,
1306
Nie, S. 1294
Niederstätter, M. 1297

Seismological Research Letters

|

1461

Nielson, Q. 1338
Nieminski, N. 1304
Niemz, P. 1328, 1364, 1395
Nikas, T. 1355
Niklasson, S. 1284, 1344,
1345, 1346
Ninis, D. 1437
Nippress, S. 1217
Nishida, K. 1226, 1423
Nishikawa, Y. 1374, 1375,
1376
Nissen, E. 1249, 1257, 1260,
1318, 1320, 1391
Nissen-Meyer, T. 1226
Niu, J. 1409
Niu, P. 1336, 1339
Njinju, E. A. 1446
Noe, S. 1229
Noel, S. K. 1364
Nolan, S. 1429, 1430
Nolet, G. 1413
Nolt-Caraway, S. 1408
Nomikou, P. 1229
Nunez, A. 1391
Nunn, C. 1271
Nyblade, A. A. 1236
Nye, T. 1381
Nziengui Bâ, D. 1284
Oancea, V. 1217
Oates, S. 1325
Obermann, A. 1395
Oboué, I. 1443
O’Brien, M. S. 1209
Obryk, M. K. 1262
Ocampo Giraldo, L. A. 1377
Ochi, T. 1249
Ochoa, E. 1430
Odum, J. 1442
Ogden, C. 1270
Ogden, C. S. 1217, 1442
Ogubazghi, G. 1233, 1270
Öğütcü, Z. 1418
Ogwari, P. O. 1322, 1328
Oh, J. 1400
Oh, S. 1341
Ohlendorf, S. 1417
Ohrnberger, M. 1221, 1331
Okkonen, N. 1430
Okubo, K. 1450
Okumura, K. 1386
Olinger, S. 1236, 1237, 1238
Oliva, S. J. 1391, 1433
Olivar-Castaño, A. 1221,
1311, 1315, 1436
Olsen, K. B. 1203, 1377,
1378, 1379, 1380, 1381
Olugboji, T. M. 1441
O’Neill, J. 1283, 1286, 1366,
1399
Onodera, K. 1382, 1423
Onur, T. 1388
Onyango, E. A. 1207, 1431
Oral, E. 1384
Orazi, M. 1350
Orihuela, B. 1278
Orihuela Gonzales, B. 1279
Ornelas-Agrela, A. 1336
O’Rourke, T. 1384
Orsvuran, R. 1207, 1341,
1446, 1451
Ortega Diaz, V. G. 1259,
1260
Osasona, J. O. 1431

1462

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Ostenaa, D. A. 1299
O’Sullivan, V. J. 1324
Oth, A. 1403, 1408
Otheim, L. T. 1297, 1298
Ottemöller, L. 1225
Ouzounov, D. 1443, 1444
Owen, L. 1319
Oye, V. 1264, 1325
Ozaki, V. 1254Özarpacı, S. 1244
Ozener, H. 1418
Pacheco, J. 1348
Pachhai, S. 1330
Padgett, C. 1334
Padgett, J. S. 1301, 1302,
1303, 1304, 1307, 1308
Paduan, J. B. 1304
Pagani, M. 1384
Page, M. T. 1223, 1252, 1253,
1367
Pai, A. 1390
Paitz, P. 1239
Palgunadi, K. 1206
Palomo, J. 1252
Pan, S. 1227
Pandel, B. 1442
Pang, G. 1271, 1426
Pankow, K. L. 1223, 1328,
1353, 1358, 1364, 1391,
1393, 1395, 1397, 1399,
1420
Panning, M. P. 1212, 1271,
1381, 1423
Pantoli, E. 1384
Panzera, F. 1287
Papadopoulos, A. 1278, 1361
Papin, L. 1423
Paramasivam, B. 1388
Parameswaran, R. M. 1224,
1351
Parcheta, C. 1280, 1285,
1341
Pardini, B. 1281
Pardo-Dañino, J. C. 1370
Parham, T. 1282
Parija, M. 1442
Parikh, N. 1355
Paris, G. 1280
Park, J. 1211, 1376, 1414, 1415
Park, S. 1400, 1436, 1450
Park, Y. 1355
Parker, G. A. 1291, 1292,
1312, 1315, 1317, 1385
Paros, J. 1360
Parrott, B. 1279
Pascual-Sánchez, E. 1389
Pasten, D. 1372
Pasyanos, M. E. 1209, 1269,
1453
Patchett, M. 1253, 1386
Patel, A. 1381
Patel, S. 1255
Patrick, M. 1262
Patrick, T. 1343
Patton, A. 1248
Patton, J. R. 1257, 1258, 1261,
1386
Patton, J. 1354, 1357, 1443
Pauk, B. 1262
Paull, C. K. 1304
Pavlis, G. L. 1340, 1437
Pearl, J. K. 1258, 1299
Pearson, A. 1392, 1393

Seismological Research Letters

Pechmann, J. C. 1268
Pedreira, D. 1436
Pellerin, J. 1203
Pells, C. 1418
Peluso, R. 1350
Peng, S. 1329
Peng, Z. 1319, 1321, 1342,
1390, 1391, 1436, 1440
Pennacchia, F. 1407
Penney, C. E. 1308, 1309,
1320
Pennington, C. N. 1209,
1322, 1356, 1448, 1449,
1452
Perea, H. 1337
Pereira da Costa, L. 1225
Pérez-Campos, X. 1353
Perlin, M. 1354, 1364
Perron, V. 1240, 1288, 1289,
1290, 1291, 1293, 1294,
1311, 1312
Perry, H. 1277, 1354
Persaud, P. 1274
Pesicek, J. D. 1348, 1351
Peter, D. 1202, 1205, 1207,
1446
Petersen, G. 1223, 1268,
1319, 1328, 1364
Petersen, M. D. 1194, 1195,
1196, 1197
Peterson, R. H. 1317
Petrenko, K. 1359, 1362
Pezeshk, S. 1197, 1200, 1201,
1295, 1359, 1373, 1374,
1441
Philibosian, B. 1195, 1296,
1301, 1306
Philibosian, B. E. 1259
Phillips, J. 1412
Phillips, S. 1209
Phrampus, B. J. 1432, 1434
Picasso, A. 1415, 1416, 1419
Piccinin i, D. 1349
Pickle, R. 1250, 1410, 1437
Pickrell, G. 1231
Pierce, I. K. D. 1319
Pierdominici, S. 1258
Pietroniro, E. 1277, 1354
Pietsch, T. 1437
Pike, W. T. 1271
Pikoulis, E. V. 1241
Pilarczyk, J. E. 1303
Pilz, M. 1311, 1314, 1315,
1316, 1317
Piña, A. 1410
Pineda, A. 1262, 1266, 1268
Pinilla Ramos, C. 1377
Pino, M. 1297
Pinto, A. 1225
Pinto, L. 1335
Pinzon, J. 1411
Pinzon Rincon, L. 1231,
1284
Pio Rinaldi, A. 1395
Piotrkowski, R. 1348
Pipatprathanporn, S. 1345
Pippin, J. E. 1216, 1218
Piraino, P. E. 1217
Pirenne, B. 1362
Piromallo, C. 1374
Pitarka, A. 1210, 1277, 1366,
1370, 1372, 1388, 1389
Pizer, C. 1296

Plata-Martinez, R. 1287
Plenkers, K. 1395
Podgorney, R. 1399
Podhorodeski, A. 1261
Poiata, N. 1353
Polanco Rivera, E. 1248,
1423
Poland, M. 1362
Polat, R. 1418
Polcari, M. 1321
Poli, P. 1405
Polissar, P. J. 1332
Pollitz, F. 1335
Pollyea, R. 1442
Pondrelli, S. 1254
Ponton, C. 1301
Popenhagen, S. K. 1375
Poppeliers, C. 1215
Porritt, R. 1227, 1230, 1358
Portner, D. 1408
Posadas, A. 1372
Posioleva, L. 1212
Potter, S. 1403
Pou, L. 1381
Pousse-Beltran, L. 1391
Powell, E. 1446
Powell, M. 1282
Power, J. A. 1349, 1352, 1431,
1432
Power, W. 1407
Powers, P. M. 1194, 1195,
1196, 1197, 1199
Pradhan, A. M. S. 1267
Pratt, T. L. 1198, 1241, 1259,
1438, 1439, 1440, 1441,
1442
Preciado Mendez, R.
G. 1282
Prejean, S. G. 1348, 1351
Premus, J. 1333
Preston, L. A. 1215, 1216,
1217, 1344, 1366, 1380
Pretell, R. 1313
Price, A. 1209
Priddy, M. S. 1249, 1338
Project Team, N. 1194
Prokopyshyn, V. 1359, 1362
Protti Quesada, M. 1279
Prudencio, J. 1348, 1349,
1350, 1352
Prush, V. B. 1249, 1256
Pryor, I. 1299
Pulgar, J. A. 1436
Pulliam, J. 1248, 1268, 1317,
1423
Purri, F. 1316
Pursley, J. 1264
Pyle, M. 1210, 1366
Qin, L. 1207
Qiu, H. 1207, 1449
Qu, C. 1274
Qu, R. 1310
Quick, S. 1217
Quigley, C. 1285
Quigley, M. C. 1241, 1306,
1437
Quinlan, F. 1226
Quinones, L. A. 1218
Quintanar, A. 1287
Quintanar-Robles, L. 1234
Quitoriano, V. 1202, 1251,
1255, 1256, 1280
Rabade, S. 1250, 1273, 1420

www.srl-online.org•

Volume 95•

Rabinovich, A. B. 1415, 1419
Rael, R. 1355
Rajaonarison, T. A. 1446
Ramirez, C. 1428
Ramirez-Guzman, L. 1331
Ramírez-Herrera, M. 1301
Ramos, L. 1415
Ramos, M. D. 1210, 1215,
1231
Ranasinghe, N. R. 1213, 1218
Rao, A. 1386
Rapenne, M. 1208, 1373
Rasmussen, K. 1305
Rathje, E. M. 1442
Rawlinson, N. 1351
Rea, S. 1282, 1283
Real-Pérez, J. 1413
Rebel, E. 1325
Reddy, E. 1253, 1280
Reedy, T. 1259
Regalla, C. 1426
Regan, S. 1249, 1250
Regmi, N. 1267
Reid-McLaughlin, A. 1224,
1225
Rein, T. 1415
Reisinger, R. 1274
Reitman, N. 1195, 1257,
1302, 1305, 1322, 1335
Reitman, N. G. 1318, 1334
Rekoske, J. M. 1208
Ren, P. 1277, 1312, 1313, 1315
Renard, F. 1264
Rengers, F. 1264
Reusch, M. 1276, 1281
Rey, K. A. 1274
Rey-Devesa, P. 1349, 1350,
1352
Rezaeian, S. 1196, 1379, 1380
Richards, F. 1446
Ridge, H. 1391
Ridgway, K. D. 1275, 1437
Riedel, M. 1435
Ries, R. 1324
Rietbrock, A. 1227
Ringler, A. 1353, 1358, 1359,
1451
Rintamäki, A. E. 1328
Rinty, S. 1408
Riquelme, S. 1357, 1419
Rischette, P. 1289, 1291,
1293, 1294, 1311
Ristau, J. 1407
Ritchie, A. 1301
Ritsema, J. 1268, 1271, 1272
Rittenour, T. M. 1250, 1299
Ritzwoller, M. 1233
Rivas-Medina, A. 1336, 1452
Rivera, K. M. 1454
Rivero, L. 1287
Rivet, D. 1353
Roa, Y. 1321
Roberson, P. 1420
Roberts, M. E. 1294
Roberts, P. M. 1229, 1275
Robertson, M. 1399
Robertson-Tait, A. 1393
Robey, E. 1210
Robinson, M. 1258, 1261
Robles, M. 1282, 1283
Roca, A. 1262, 1263, 1266,
1268
Rocco, G. 1353

Number 2B•

April 2024

Rocha dos Santos, G.
F. 1236
Rodd, R. 1209
Rodgers, A. 1213, 1343, 1451
Rodriguez, E. E. 1275
Rodriguez, K. 1305
Rodríguez-Cardozo,
F. 1213, 1221, 1353, 1451
Rodriguez-Marek, A. 1313,
1389
Rodríguez-Rasilla, I. 1234
Rodriguez Tribaldos,
V. 1224, 1228
Rodysill, J. R. 1306
Roecker, S. W. 1324, 1430
Roeske, S. 1249, 1250
Roger, J. 1407
Rohr, K. M. M. 1435
Roland, E. C. 1432, 1433,
1434, 1435
Rollins, C. 1257, 1320, 1392,
1393
Roman, D. 1402, 1405, 1432
Roman-Nieves, J. 1211, 1452,
1454
Romanowicz, B. 1235, 1273,
1281, 1371, 1428
Ronan, T. 1341
Rondenay, S. 1225
Rong, W. 1330
Ronnett, M. 1244
Rooney, T. 1446
Rosenblit, J. 1324
Rosero Rueda, S. 1248
Rösler, B. 1451
Ross, Z. E. 1342, 1343
Rosset, P. 1256
Rossi, Y. 1365
Rosskopf, M. 1395
Rost, S. 1421
Roth, E. H. 1418
Rougier, E. 1212
Roumelioti, Z. 1289, 1292,
1294, 1311, 1361
Roux, P. 1331
Rowe, C. 1213, 1218, 1256,
1344, 1346, 1347
Roy, M. 1405
Rubinstein, J. L. 1326
Rudziński, Ł. 1400
Ruiz, M. 1436
Rukstales, K. S. 1199
Rundle, J. 1443, 1444
Rupper, N. 1264
Ruppert, N. A. 1280, 1285,
1354, 1363, 1364, 1427
Russell, C. 1292
Russell, J. B. 1346, 1410,
1412, 1413
Ruth, D. 1333
Rutledge, J. 1328, 1364,
1395, 1399
Rutqvist, J. 1384
Rybakov, S. 1236
Ryf, R. 1226
Rysgaard, S. 1286, 1288
Ryu, H. 1390
Saad, O. 1443
Sabatini, R. 1212
Saccorotti, G. 1349, 1394
Sadiki, A. 1408
Sagae, K. 1222
Sagy, A. 1450

Sahakian, V. J. 1272, 1381
Sahakyan, E. 1338
Saikia, C. K. 1202, 1208,
1211, 1343
Sakellariou, N. 1390, 1391
Sakkas, G. 1391
Salaree, A. 1226
Salditch, L. 1200, 1369
Salimbeni, S. 1394
Salisbury, B. 1256, 1259,
1261, 1415, 1416, 1419
Salles, V. 1324
Salomon, G. W. 1249, 1257,
1260
Saloor, N. 1412
Sampaio de Melo, G. 1344
Samuel, D. 1259
Samuel, H. 1271
Sánchez-González, J. 1330
Sánchez-Roldán, J. 1337
Sanchez-Sesma, F. J. 1370
Sandoval-Quintana,O. 1330
Sandru, J. 1360, 1365
Sandstrom, P. 1237
Sandvol, E. 1319, 1321
Sanon, C. 1254
Santellanes, S. R. 1387, 1419
Saoulis, A. 1415
Saravia, G. 1372
Sargsyan, L. 1338
Sarmiento, A. 1243
Sasagawa, G. S. 1347
Sasaki, T. 1384
Sassard, V. 1275, 1428
Satriano, C. 1286, 1288
Saul, J. 1252, 1319
Saunders, J. K. 1251, 1254,
1256, 1277, 1280, 1282,
1355
Savage, H. M. 1332
Savage, M. K. 1415
Savran, W. H. 1220, 1222,
1367, 1368
Savvaidis, A. 1218, 1323,
1324, 1326, 1391, 1442,
1443
Savy, J. 1393
Sawade, L. 1202, 1451
Sawi, T. 1341
Sawi, T. M. 1238
Sawyer, D. E. 1296, 1298,
1301, 1303
Saxena, A. 1373, 1445
Saxena, S. 1214, 1397, 1398
Scalise, M. 1366
Scarponi, M. 1374
Schaeffer, A. 1261
Schaeffer, J. 1361
Schaff, D. 1350, 1402, 1439
Schaible, L. P. 1218, 1265
Scharer, K. 1300, 1301, 1393,
1394
Scheckel, N. 1366
Schimmel, M. 1423
Schippkus, S. 1286, 1288
Schlaphorst, D. 1228, 1415
Schleicher, L. S. 1359
Schlesinger, A. 1346, 1362
Schliwa, N. 1333
Schmandt, B. 1431
Schmelzbach, C. 1381
Schmerr, N. C. 1381

Volume 95••

Number 2B

April 2024•

Schmidt, D. A. 1202, 1347,
1392, 1393
Schmidt, J. P. 1361, 1398
Schmidt-Aursch, M. 1415
Schmitt, D. R. 1437
Schneider, M. 1223, 1252,
1253, 1367, 1368, 1369
Scholz, C. A. 1338
Scholz, K. J. 1402
Schorlemmer, D. 1367
Schouten, M. W. 1400
Schrom, B. 1214
Schulte-Pelkum, V. 1268,
1271
Schultz, R. 1328, 1393, 1395,
1397
Schwartz, D. P. 1300
Schwartz, S. 1265
Scott, B. 1403
Searcy, J. 1422
Sèbe, O. 1448
Seçen, B. 1318, 1334, 1335
Sedaghati, F. 1295
Seebeck, H. 1308, 1392
Segall, P. 1333, 1370
Seismology Group, t. 1363
Sekine, Y. 1423
Selby, N. 1217
Seldon, Y. 1239
Sen, M. K. 1342, 1343, 1344
Seo, M. 1454
Seppi, I. 1219, 1381
Sepulveda, I. 1419
Sepúlveda, S. A. 1335
Şeşetyan, K. 1319
Sethanant, I. 1249, 1391
Sethi, S. 1387, 1443
Sevim, F. 1319, 1321
Seydoux, L. 1227, 1238, 1405
Seyhan, E. 1194, 1197, 1389
Seywerd, H. 1354
Sgattoni, G. 1316
Shah, A. K. 1259, 1436, 1440,
1441
Shahsavari, P. 1237
Shapiro, N. M. 1403, 1405
Share, P. 1272
Sharma, A. 1437
Sharma, S. 1295
Shaw, B. E. 1449
Shaw, J. H. 1242
Sheehan, A. F. 1228, 1231,
1233, 1326, 1418
Sheen, D. 1288, 1441, 1454
Shelly, D. R. 1246, 1351,
1354, 1355, 1358, 1406,
1443
Shen, J. 1374
Shen, W. 1237
Sheng, Y. 1351
Shengji, W. 1436
Shennan, I. 1303
Sherman, C. S. 1394
Sherrod, B. L. 1195, 1258,
1300, 1301, 1302, 1303,
1305, 1307
Shi, C. 1274
Shi, Q. 1226, 1227, 1346,
1429, 1432
Shi, Y. 1290
Shible, H. 1312
Shilin, L. 1274

www.srl-online.org

Shillington, D. J. 1338, 1413,
1424, 1425, 1426, 1427,
1428, 1431
Shimmoto, S. 1450, 1454
Shinohara, M. 1226
Shiobara, H. 1414
Shiraishi, H. 1423
Shiroshita, H. 1367
Shirzadi, H. 1383, 1389
Shome, N. 1194
Shragge, J. C. 1347
Shreve, T. 1352
Shuck, B. 1413
Shumway, A. M. 1194, 1195,
1196, 1197, 1200
Sickler, R. R. 1259, 1291,
1321, 1422
Sid Ahmed, Y. 1353
Siegfried, M. 1239
Siervo, D. 1324
Sievers, C. 1341
Sifa, L. 1408
Sigloch, K. 1361
Silber, E. A. 1374, 1375, 1376,
1377
Sillett, S. 1306
Silva, F. 1367
Silva, V. 1386
Silva, W. J. 1241
Silveira, G. 1411
Simeone, F. 1286
Simmons, N. A. 1204, 1451
Simmons, S. 1399
Simon, J. D. 1345
Simon, V. 1221
Simons, F. J. 1345
Simos, C. 1355
Simos, I. 1355
Sims, N. E. 1261
Singh, A. 1317, 1337
Singh, C. 1315, 1317
Singh, O. 1381
Singh Bora, S. 1201
Singleton, D. M. 1296, 1297,
1298, 1301, 1302, 1303,
1304, 1305, 1306, 1307
Sion, B. 1258, 1305
Sirorattanakul, K. 1325,
1339
Skarlatoudis, A. 1239, 1383,
1385, 1386
Skene, F. 1263
Skolnik, D. 1279
Skoumal, R. 1246
Skoumal, R. J. 1220
Slad, G. W. 1364
Sleeman, R. 1361
Small, D. 1387
Smets, B. 1403
Smith, J. A. 1195, 1196, 1198,
1317
Smith, K. D. 1269
Smith, K. K. 1255, 1256,
1331, 1389
Smittarello, D. 1403
Smoczyk, N. 1263
Smolinski, K. T. 1224, 1228,
1229, 1355
Snively, J. B. 1212
Snyder, G. 1301, 1305
Snyder, T. 1231
Soares, A. 1439
Sobiesiak, M. M. 1400

Sobol, P. 1324, 1429
Soergel, D. 1235
Soga, K. 1384
Sokolkova, E. 1198
Solares-Colón, M. M. 1339
Somerville, P. 1383
Son, M. 1454
Song, J. 1273
Song, T. 1233, 1409
Song, W. 1295
Song, Z. 1230
Soni, Y. 1317
Sonnemann, T. 1347
Soubestre, J. 1405
Spagnuolo, E. 1407
Sparks, T. N. 1398
Spencer, B. D. 1369, 1451
Spesivtsev, A. 1407
Spica, Z. 1226, 1228, 1230
Spiga, A. 1423
Spillman, K. 1375
Spina, L. 1407
Sprinkle, D. 1210
Sprinkle, P. 1214
Srikar, G. 1356
Stachnik, J. 1398
Staehler, S. 1382
Stafford, P. J. 1389
Stahl, T. 1392
Stähler, S. 1271, 1381
Staisch, L. 1256, 1258, 1259,
1301, 1303, 1308
Stamatakos, J. 1243
Stamps, D. 1446
Stanaway, R. 1390
Stanbury, C. 1218
Stanciu, A. C. 1227
Stanciu, C. 1214, 1285
Stanek, F. 1239
Stanley, J. 1343
Stanley, R. G. 1426
Starace, A. 1305
Staszek, M. 1400
St. Clair, J. 1210, 1214
Steele, W. P. 1279
Stefanova, S. 1353
Steidl, J. H. 1359, 1366, 1379
Stein, S. 1369, 1451, 1452
Steinmann, R. 1331
Stenner, H. D. 1300
Stephane, B. 1331
Stephen, R. A. 1236
Stephenson, O. 1244
Stephenson, S. N. 1270
Stephenson, W. J. 1206,
1272, 1315, 1317, 1330,
1377, 1378, 1442, 1443
Stevens, J. L. 1209
Stevens, N. T. 1236, 1263,
1365
Stevens Goddard, A. 1437
Stewart, J. P. 1379, 1380
Stirling, M. W. 1241, 1260,
1437, 1438
Stock, J. 1410
Stone, I. 1201, 1202
Storchak, D. 1353, 1359
Stott, A. 1381
Stoup, V. 1237
Strasser, M. 1297, 1298
Strauch, W. 1278, 1279
Streig, A. R. 1332
Striano, P. 1321

Seismological Research Letters

|

1463

Strickert, G. E. H. 1286
Strickland, C. 1210, 1211
Strollo, A. 1225, 1361
Stubailo, I. 1281, 1360, 1365
Stubbs, J. 1341
Stuefer, M. 1285
Stump, B. 1211
Stutzmann, E. 1423
Styron, R. H. 1258, 1332,
1384
Suarez-Colche, L. E. 1314
Subira, J. 1403, 1408
Sugioka, H. 1414
Sugiyama, T. 1367
Suhendi, C. 1206
Suleimani, E. 1415, 1416,
1419
Sumy, D. F. 1279, 1282, 1283
Sun, D. 1374
Sun, J. 1312
Sun, M. 1401
Sun, T. 1346
Sung, C. 1197, 1292, 1313
Suvarıklı, M. 1418
Suzuki, H. 1386
Svennevig, K. 1286, 1288
Svigkas, N. 1321
Swyer, M. 1397
Symons, N. 1292
Syracuse, E. M. 1213
Taccone, R. 1455
Taddeucci, J. 1407
Tafoya, A. 1211
Taguba, C. 1211
Taira, T. 1247, 1281, 1283,
1363, 1422, 1449
Takeuchi, N. 1411, 1414
Tam, R. 1357
Tan, D. 1404
Tan, F. 1318
Tan, M. 1259, 1304, 1306,
1322, 1335
Tan, X. 1324, 1327
Tan, Y. 1350, 1402
Tanaka, S. 1423
Tang, C. 1247
Tang, Y. 1319, 1371
Tang, Z. 1309
Tanimoto, T. 1285
Tanner, G. 1237
Tape, C. 1205, 1206, 1207,
1209, 1213, 1219, 1234,
1235, 1250, 1251, 1261,
1269, 1331, 1341, 1422,
1424, 1425, 1429, 1434
Tape, W. 1235
Tapırdamaz, M. C. 1319,
1321
Tarabusi, G. 1455
Tarancıoğlu, A. 1319, 1321
Tarling, M. 1256
Taroni, M. 1224
Taveras, O. 1348
Taylor, M. H. 1332
Team, C. 1353
Team, N. 1199
teams, I. 1353
Teelucksingh, M. 1255
Teixeira, M. 1225
Telesca, L. 1220
ten Brink, U. 1198
Teoman, U. 1418
Tepp, G. 1355, 1357, 1366

1464

|

Terbush, B. 1276, 1281
Terhune, P. J. 1249
Terra, F. 1276, 1281, 1283
Terrinha, P. 1439
Thapa, H. R. 1275
Thapa, M. 1267
Theis, L. 1231
Thelen, W. A. 1229, 1262,
1263, 1266, 1406, 1409
Theodoulidis, N. 1289, 1294,
1311, 1312
Thetford, J. 1341
Theys, N. 1403
Thiel, A. 1322, 1328
Thielmann, M. 1447
Thigpen, J. R. 1347
Thingbaijam, K. 1380
Thio, H. K. 1382, 1383, 1385,
1424
Thomas, A. M. 1220, 1266,
1339, 1341, 1402, 1406,
1422, 1423
Thomas, J. O. 1422
Thomas, P. 1194
Thompson, E. M. 1202, 1251,
1255, 1256, 1290, 1317,
1382, 1383, 1385
Thompson, G. 1221, 1265,
1353
Thompson, M. 1347
Thompson, S. 1281, 1363,
1384
Thompson Jobe, J. A. 1198,
1257, 1259, 1260, 1298,
1302, 1305, 1306, 1436,
1440, 1441, 1442
Thomson, R. E. 1415
Thornley, J. 1315, 1317
Thum, T. 1389
Thurber, C. H. 1324, 1449
Thurin, J. 1208, 1213, 1341,
1424
Tian, D. 1270
Tian, J. 1234
Tian, X. 1274
Tian, Y. 1205, 1381, 1401
Tibi, R. 1210, 1215, 1216,
1218, 1219, 1231
Tibuleac, I. M. 1219
Tien, I. 1391
Tilley, J. W. 1347
Tilmann, F. 1225, 1252, 1415
Timba Science Party,
M. 1338
Ting, C. 1400
Titos, M. 1348, 1349
Titov, V. 1416
Tobin, H. J. 1332, 1347, 1360
Toledo, T. 1221
Tolomei, C. 1321
Tolstoy, M. 1350, 1402
Tomorrow’s Cities Pro­
gramme Working
Group 1253
Toney, L. D. 1262, 1263,
1264, 1265, 1267
Tong, P. 1204, 1429
Toomey, D. R. 1220, 1273,
1414, 1446
Toro Acosta, C. 1330
Tourei, A. 1224, 1236
Townend, J. 1206, 1228,
1245, 1249, 1445

Seismological Research Letters

Townsend, M. R. 1402
Trabant, C. 1339, 1340, 1341
Traversa, P. 1240, 1289,
1290, 1291, 1294, 1311,
1312, 1448, 1449
Trexler, C. 1195, 1258, 1260,
1261
Tromp, J. 1202, 1203, 1204
Trow, A. J. 1362
Trugman, D. T. 1220, 1222,
1247, 1248, 1278, 1356,
1367, 1382
Trujillo Castrillón, N. 1404
Tsai, A. 1342
Tsai, V. C. 1247, 1331
Tsekhmistrenko, M. 1415
Tseng, T. 1247
Tsuji, T. 1423
Tsukanova, E. 1415
Turhan, F. 1418
Turley, R. 1210, 1211, 1366
Turner, A. R. 1244, 1382
Turza, K. 1225
Uchide, T. 1222
Uhrhammer, R. 1283
Uku, B. 1324
Ulrich, T. 1245, 1308, 1327
Underwood, L. 1280
Unlu, M. 1229
Urrejola-Sanhueza, J.
T. 1335
Urrutia, R. 1297
Utada, H. 1414
Uthaman, M. 1317, 1337
Uyeki, A. 1254
Vackář, J. 1451
Valdés González, C.
M. 1404
Valencia, N. 1235
Valero Cano, E. 1205
Vales, D. 1439
Valovcan, J. 1370
Vanacore, E. 1199, 1220,
1222, 1330, 1390, 1391,
1392
Van Brabant, R. 1355
Van Daele, M. 1297, 1307
van Dam, T. 1269
VanDeMark, T. F. 1211, 1219
VanderBeek, B. P. 1201,
1205, 1233, 1414, 1445,
1446, 1447, 1448
van der Elst, N. 1223, 1252,
1253, 1367, 1368
van der Heiden, V. 1327
van der Wal, J. L. N. 1400
van de Wiel, L. 1327
van Dinther, C. 1420
van Dinther, Y. 1245, 1308,
1309, 1327, 1334
Van Dissen, R. J. 1196, 1309
van Haren, H. 1345
van Isselt, M. 1327
Van Noten, K. 1286, 1288
Vannucci, G. 1455
Vantassel, J. 1313
van Wees, J. 1327
van Wijk, K. 1228
van Zelst, I. 1246, 1308
Vargas E., V. H. 1301
Vassallo, M. 1394
Vasyara-Bathke, H. 1320
Vasylkivska, V. 1401

Vaughn, J. 1440
Vavlas, N. 1321
Vazquez, L. 1204
Vecsey, L. 1270
Velasco, A. A. 1390, 1391
Velsko, C. 1213
Venkateswara, K. 1360
Ventura, C. E. 1279, 1330
Ventura-Valentin, W.
A. 1221
Vera Sanhueza, F. 1252, 1319
Vercruysse, P. 1297
Vermeer, J. 1243, 1258, 1259,
1260, 1261
Vernier, J. 1325
Vernon, F. 1443
Vescu, V. 1244
Vesga-Ramírez, A. 1348
Vidale, J. 1271
Viens, L. 1227, 1228, 1230,
1374, 1453
Villa, V. 1232, 1421
Villafuerte, C. 1287
Villaseñor, A. 1275, 1447
Villiger, L. 1395
Vinarski, E. 1352
Viteri Lopez, J. 1248, 1327
Vlahovic, G. 1275
Vogel, E. V. 1372
Vohnout, R. 1225
von Dassow, W. 1259
Vorobiev, O. Y. 1213, 1219,
1378
Vos, S. 1336
Voss, P. H. 1286, 1288
Vossepoel, F. 1334
Vyas, J. J. 1379
Wade, J. 1258
Waite, G. P. 1262, 1266, 1268
Wald, D. J. 1202, 1251, 1252,
1253, 1254, 1255, 1256,
1280, 1354, 1382, 1383,
1385
Waldhauser, F. 1341, 1350,
1402, 1439
Waldien, T. S. 1249, 1250
Walker, M. 1330
Wallace, L. M. 1415, 1416
Walter, F. 1238, 1239
Walter, J. I. 1322, 1327, 1328,
1423
Walter, T. 1268
Walter, W. R. 1209, 1210,
1356
Walton, M. A. L. 1432, 1433,
1434, 1435
Wandasan, C. 1431
Wang, A. 1231
Wang, C. 1340, 1341, 1394
Wang, D. 1252
Wang, F. 1270, 1275
Wang, I. 1207, 1339, 1341
Wang, J. 1384
Wang, K. 1256, 1269, 1270,
1341, 1350, 1402, 1416,
1429, 1439
Wang, L. 1310
Wang, Q. 1347
Wang, R. 1271, 1329
Wang, T. A. 1370
Wang, W. 1371, 1397
Wang, X. 1269, 1272, 1274,
1407

www.srl-online.org•

Volume 95•

Wang, Y. 1248, 1340, 1341
Wang, Z. 1236, 1240, 1361,
1386, 1398
Wangari, V. N. N. 1329
Wang-Connelly, J. 1202
Wantepe, G. 1390
Ward, G. A. 1413
Ward, K. M. 1250
Warren, L. M. 1369
Warren-Smith, E. 1245,
1249, 1415
Wartes, M. A. 1426
Wassermann, J. 1420
Watanabe, T. 1375
Wathelet, M. 1293, 1311
Watkins, M. B. 1360, 1365
Watkiss, N. R. 1283, 1286,
1346, 1366, 1399
Watson-Lamprey, J. 1243,
1384
Watt, J. T. 1301, 1304, 1416
Weaver, R. L. 1370
Weber, J. 1237
Webster, J. D. 1377
Wech, A. 1220, 1404, 1409,
1430
Weekly, R. T. 1340
Wegmann, K. 1296
Wehner, M. 1390
Wei, S. S. 1270, 1275, 1412,
1428
Wei, Y. 1418
Weidner, J. 1391
Wein, A. M. 1252, 1253
Weir-Jones, I. 1281
Wells, D. 1443
Wells, R. E. 1332
Wen, J. 1428
Wendt, S. 1221
Werner, M. J. 1367
Werner, T. 1241
Wesnousky, S. 1319
Wesson, R. L. 1297, 1416
West, M. E. 1219, 1264,
1266, 1280, 1285, 1341,
1354, 1364, 1422
Wharton, S. 1211
Whelan, N. E. 1299
Whidden, K. 1223, 1364,
1420
White, R. 1210, 1211, 1366
White, R. A. 1404
Wiboonwipa, N. 1203
Widmann, B. 1255
Widmer-Schnidrig, R. 1227,
1286, 1288, 1423
Wiemer, S. 1361, 1394, 1395
Wiens, D. A. 1225, 1236,
1275, 1276, 1421, 1426,
1427
Wight, J. 1402
Wilcock, W. S. D. 1345,
1347, 1350, 1360, 1362,
1402, 1432
Wilde, K. L. 1409
Willard, J. 1306
Williams, A. 1421
Williams, C. 1445
Williams, C. A. 1308, 1309
Williams, E. 1305
Williams, E. F. 1226, 1227,
1345, 1366, 1429, 1431
Williams, T. 1243, 1260

Number 2B•

April 2024

Williamson, A. 1283
Willis, R. 1236, 1237, 1239
Wils, K. 1296, 1297, 1307,
1308
Wilson, D. 1358
Wilson, T. C. 1375
Winder, T. 1351
Wirth, E. 1201, 1202, 1206,
1273, 1300, 1382, 1383,
1385
Wiszniowski, J. 1400
Withers, K. 1196, 1201
Witsil, A. 1404
Witter, R. 1296, 1297, 1298,
1301, 1302, 1303, 1304,
1307, 1308, 1338, 1393,
1394
Woelfel, I. 1322, 1328
Wolf, J. 1235
Woller, K. L. 1347, 1442
Wong, I. 1239, 1393, 1394
Woo, J. 1400
Wood, D. 1338
Wood, K. L. 1303
Wood, L. 1211
Woodroffe, S. A. 1303
Woods, V. T. 1353
Woolery, E. W. 1348, 1442
Worden, C. B. 1251, 1256,
1290, 1383
Working Group, t. 1270
Worthen, B. 1389
Worthington, L. L. 1410,
1413, 1431, 1432, 1433,
1434, 1435
Wright, A. K. 1365
Wright, V. 1300
Wu, B. 1206, 1396, 1397
Wu, M. 1233
Wu, P. 1329

Wu, Q. 1239, 1443
Wu, S. 1271, 1288, 1399, 1401
Wu, Y. 1271
Wu, Z. 1445
Wu Fung, S. 1229
Wynn, I. V. 1431, 1432
Wynn, N. R. 1219
Xi, Z. 1412
Xia, Y. 1349
Xiao, H. 1225
Xiao, M. 1236
Xiao, Z. 1337, 1424
Xing, P. 1399
Xiong, Q. 1368
Xiong, X. 1387
Xu, C. 1320
Xu, D. 1372
Xu, K. 1378
Xu, L. 1322
Xu, M. 1204
Xu, Y. 1265
Xu, Z. 1212, 1423
Xue, L. 1338
Xue, X. 1257
Yabe, S. 1249
Yakovenko, O. 1419
Yakubu, T. 1427
Yalvac, O. 1319, 1321
Yamada, R. 1423
Yamada, T. 1226
Yamamoto, M. 1376
Yamashita, F. 1450
Yamori, K. 1367
Yan, L. 1240
Yang, C. 1345
Yang, H. 1241, 1247, 1311,
1329, 1331, 1412
Yang, J. 1269, 1373, 1448
Yang, L. 1207, 1329
Yang, R. 1272

Volume 95••

Number 2B

April 2024•

Yang, X. 1275, 1331, 1401,
1407, 1410, 1424, 1428,
1437
Yang, Y. 1224, 1225, 1232,
1329, 1345, 1411, 1429
Yang, Z. 1311, 1315
Yani Quiyuch, R. 1278, 1279
Yap, Z. 1375
Yartsev, V. 1281
Yates, A. 1351
Yavus, E. 1229
Yazdi, M. 1292, 1330
Yeager, K. M. 1347
Yeager, S. 1333
Yeck, W. 1264, 1267, 1339,
1351, 1354, 1357, 1358,
1443
Yeh, T. 1377, 1379, 1381
Yetirmishli, G. 1388
Yin, J. 1225
Yoon, C. 1220, 1291, 1409
Yoon, H. 1342, 1343, 1344
Yoshida, K. 1244
Yoshimitsu, N. 1393, 1397,
1401
Yoshino, C. 1445
Young, B. 1210, 1214, 1366
Young, C. J. 1210, 1215
Younger, F. 1262
Yu, C. 1276
Yu, E. C. 1355, 1357, 1360,
1365, 1366
Yu, H. 1372
Yu, K. 1446
Yu, Y. 1357
Yuan, H. 1329, 1437
Yuan, S. 1224, 1231, 1295,
1296
Yunjun, Z. 1322
Yust, M. 1243

www.srl-online.org

Zaccagnino, D. 1220
Zaccarelli, L. 1224, 1394
Zaheer, A. 1396
Zaicenco, A. G. 1281
Zakari, M. 1371
Zaleski, M. P. 1255, 1299
Zali, Z. 1222
Zampolli, M. 1353
Zang, N. 1371
Zappone, A. 1395
Zeiler, C. P. 1209, 1213, 1215,
1366, 1377
Zellman, M. 1255, 1296,
1299, 1301
Zeng, X. 1230
Zeng, Y. 1195, 1201
Zenhaeusern, G. 1382
Zerbinato, P. 1394, 1396
Zhai, Q. 1225
Zhan, W. 1294
Zhan, Z. 1224, 1225, 1237,
1269, 1345, 1355, 1421,
1453
Zhang, G. 1276
Zhang, J. 1281
Zhang, M. 1277, 1329, 1402
Zhang, P. 1250, 1410, 1437
Zhang, R. 1276, 1373
Zhang, W. 1370, 1371, 1373,
1378, 1411
Zhang, X. 1277
Zhang, Y. 1270, 1384, 1445
Zhang, Z. 1372, 1428, 1449
Zhao, G. 1207
Zhao, K. 1232
Zhao, L. 1288, 1373
Zhao, X. 1320
Zhao, Y. 1311, 1315
Zhao, Z. 1344
Zheng, B. 1384

Zheng, J. 1329
Zheng, Y. 1393, 1396, 1397,
1401
Zhong, Y. 1329
Zhou, B. 1374
Zhou, C. 1336, 1339
Zhou, R. 1202, 1208, 1211,
1343
Zhou, Y. 1206, 1318
Zhou, Z. 1203
Zhu, G. 1412
Zhu, H. 1432
Zhu, T. 1236
Zhu, W. 1281, 1310, 1340,
1366, 1412
Zhuo, Z. 1352, 1424
Zi, J. 1329
Zielke, O. 1385
Zigone, D. 1238
Zimmerman, S. R. 1299
Zinke, R. 1334
Zitto, M. E. 1348
Ziv, A. 1354
Zoet, L. K. 1236
Zogh, P. 1330
Zor, E. 1319, 1321
Zou, C. 1342, 1343
Zou, L. 1374
Zumberge, M. A. 1347
Zúñiga Dávila-Madrid,F. 1294
Zunino, A. 1237
Zuo, S. 1274
Zuzlewski, S. 1281, 1363
Zweck, C. 1251

Seismological Research Letters|1465