nasa-gesdisc/es-publications-researchareas huggingface dataset:
Irregular rupture propagation and geometric fault complexities during the 2010 Mw 7.2 El Mayor-Cucapah earthquake (2022)

The 2010 MW 7.2 El Mayor-Cucapah, Mexico, earthquake ruptured multiple faults with different faulting mechanisms. Resolving the earthquake rupture process and its relation to the geometric fault complexities is critical to our understanding of the earthquake source physics, but doing so by conventional finite-fault inversion is challenging because modelling errors due to inappropriate assumptions about the fault geometry distort the solution and make robust interpretation difficult. Here, using a potency density tensor approach to finite-fault inversion, we inverted the observed teleseismic P waveforms of the 2010 El Mayor-Cucapah earthquake to simultaneously estimate the rupture process and the fault geometry. We found that the earthquake consisted of an initial normal faulting rupture, which was followed by a strike-slip bilateral rupture towards the southeast and northwest that originated on the northwest side of the epicentre. The southeastern rupture propagated back through the initial rupture area, but with strike-slip faulting. Although the northwestern rupture propagated across the left step in the Puerta fault-accommodation zone, the rupture was temporarily stalled by the associated change of the fault geometry. These results highlight the irregular rupture process, which involved a back-propagating rupture and fluctuating rupture propagation controlled the complexity of the fault system.

Research areas: Earthquakes
A Review of Tsunami Hazards in the Makran Subduction Zone (2020)

The uncertain tsunamigenic potential of the Makran Subduction Zone (MSZ) has made it an interesting natural laboratory for tsunami-related studies. This study aims to review the recent activities on tsunami hazard in the Makran subduction zone with a focus on deterministic and probabilistic tsunami hazard assessments. While almost all studies focused on tsunami hazard from the Makran subduction thrust, other local sources such as splay faults and landslides can be also real threats in the future. Far-field tsunami sources such as Sumatra-Andaman and Java subduction zones, commonly lumped as the Sunda subduction zone, do not seem to pose a serious risk to the Makran coastlines. The tsunamigenic potential of the western segment of the MSZ should not be underestimated considering the new evidence from geological studies and lessons from past tsunamis in the world. An overview of the results of tsunami hazard studies shows that the coastal area between Kereti to Ormara along the shoreline of Iran-Pakistan and the coastal segment between Muscat and Sur along Omans shoreline are the most hazardous areas. Uncertainties in studying tsunami hazard for the Makran region are large. We recommend that future studies mainly focus on the role of thick sediments, a better understanding of the plates interface geometry, the source mechanism and history of extreme-wave deposits, the contribution of other local tsunamigenic sources and vulnerability assessment for all coastlines of the whole Makran region.

Research areas: Earthquakes
Application of Soil Moisture Active Passive (SMAP) Satellite Data in Seismic Response Assessment (2022)

The proven relationship between soil moisture and seismic ground response highlights the need for a tool to track the Earths surface soil moisture before and after seismic events. This paper introduces the application of Soil Moisture Active Passive (SMAP) satellite data for global soil moisture measurement during earthquakes and consequent events. An approach is presented to study areas that experienced high level of increase in soil moisture during eleven earthquakes. Two ancillary datasets, Global Precipitation Measurement (GPM) and Global Land Data Assimilation (GLDAS), were used to isolate areas that had an earthquake-induced increase in soil moisture from those that were due to hydrological processes. SMAP-based soil moisture changes were synthesized with seismic records developed by the United States Geological Survey (USGS), mapped ground failures in reconnaissance reports, and surface changes marked by Synthetic Aperture Radar (SAR)-based damage proxy maps. In the majority of the target earthquakes, including Croatia 2020, Greece 2020, Indonesia 2018, Taiwan 2016, Ecuador 2016, and Nepal 2015, a relationship between the SMAP soil moisture estimates and seismic events was evident. For these events, the earthquake-induced soil moisture response occurred in liquefaction-prone seismic zones. The New Zealand 2016 event was the only study region for which there was a clear inconsistency between SMSMAP and the seismic records. The promising relationship between soil moisture changes and ground deformations indicates that SMAP would be a useful data resource for geotechnical earthquake engineering applications and reconnaissance efforts.

Research areas: Earthquakes
Spatial Extent of Mid‐To Late‐Holocene Sedimentary Record of Tsunamis Along the Southern Kuril Trench, Hokkaido, Japan (2022)

With their complex cycles and rupture modes, infrequent megathrust earthquakes require a high-resolution spatiotemporal record of tsunami inundations over thousands of years to provide more accurate long-term forecasts. The geological record suggests that Mw &gt; 8 earthquakes in the Kuril Trench occurred at intervals of several hundred years. However, uncertainties remain regarding the rupture zone, owing to the limited survey areas and chronological data. Therefore, we investigated the tsunami deposits in a coastal wetland of southeastern Hokkaido, Japan, to characterize the tsunamis that originated from the Kuril Trench over the last 4,000 years. On the Erimo coast, more than seven sand layers exhibited common features of tsunami deposits, such as sheet distributions of several hundred meters, normal grading structures, and sharp basal contacts. According to numerical tsunami simulations, the 17th-century sand layer could be reproduced using a multiple rupture zone model (Mw ∼ 8.8). We used high-resolution radiocarbon dating and tephras to correlate the tsunami deposits from the last 4,000 years with those reported from regions ∼100 km away. The tsunami history revealed here shows good agreement with the histories of adjacent regions. However, the paleotsunamis reported to have occurred in regions &gt;200 km away include events that differ from those in this study, suggesting a diversity of Mw &gt; 8 earthquakes in the Kuril Trench. We clarified the history and extents of earthquake-generated tsunamis along the southwestern end of the Kuril Trench, which were previously unknown. Our results provide a framework for magnitude estimations and long-term forecasts of earthquakes.

Research areas: Earthquakes
Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models (2022)

In seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaiso (Chile) subjected to seismic ground-shaking from one subduction earthquake. We have found that building class reconnaissance, either from prior assumptions by desktop studies with aggregated data (topdown approach), or from building-by-building data collection (bottomup approach), plays a fundamental role in the statistical modelling of exposure. To model the vulnerability of such a heterogeneous building stock, we require that their associated set of structural fragility functions handle multiple spectral periods. Thereby, we also discuss the relevance and specific uncertainty upon generating either uncorrelated or spatially cross-correlated ground motion fields within this framework. We successively show how various epistemic uncertainties embedded within these probabilistic exposure models are differently propagated throughout the computed direct financial losses. This work calls for further efforts to redesign desktop exposure studies, while also highlighting the importance of exposure data collection with standardized and iterative approaches.

Research areas: Earthquakes
Effect of Merging Multiscale Models on Seismic Wavefield Predictions near the Southern San Andreas Fault (2021)

Updating Earth models used by the scientific community in geologic studies and hazard assessment has a significant societal impact but is computationally prohibitive due to the large spatial scale. The advent of urban seismology allowed rapid development of local high-resolution models using short-term dense seismic arrays to become conventional. To incorporate the details in these local models in community models, we developed a technique for constructing window taper functions like the cosine taper in arbitrarily shaped spatial domains on regular grids. We apply our algorithm to the problem of low-frequency ground shaking estimation near the southernmost San Andreas fault by creating two hybrid models. These models consist of basin-scale (top 10 km or less) high-resolution models developed using controlled source data embedded into two popular Southern California Earthquake Center community models. We evaluate the models by computing long period (6-30 s) wavefield energy misfits using 11 earthquakes with moment magnitudes between 3.5 and 5.5 not used in developing any of the models under consideration. One of the hybrid models produces an ∼24% decrease while the other has an ∼0.6% increase in the overall median misfit relative to their original community models. The overlapping misfit values between the models and variability in waveform fit for different events and stations emphasize the difficulties in model validation. Our approach can merge any type of gridded multiscale and multidimensional datasets, and represents a valuable tool for modeling in the computational sciences.

Research areas: Earthquakes
Real-Time Earthquake Intensity Estimation Using Streaming Data Analysis (2016)

Earthquake intensity is one of the key components of the decision-making process for disaster response and emergency services. Accurate and rapid intensity calculations can help to reduce total loss and the number of casualties after an earthquake. Modern intensity assessment procedures handle a variety of information sources, which can be divided into two main categories. The first type of data is that derived from physical sensors, such as seismographs and accelerometers, while the second type consists of data obtained from social sensors, such as witness observations of the consequences of the earthquake itself. Estimation approaches using additional data sources or that combine sources from both data types tend to increase intensity uncertainty due to human factors and inadequate procedures for temporal and spatial estimation, resulting in precision errors in both time and space. Here we present a processing approach for the real-time analysis of streams of data from both source types. The physical sensor data is acquired from the U.S. Geological Survey (USGS) seismic network in California and the social sensor data is based on Twitter user observations. First, empirical relationships between tweet rate and observed Modified Mercalli Intensity (MMI) are developed using data from the M6.0 South Napa, CAF earthquake that occurred on August 24, 2014. Second, the streams of both data types are analyzed together in simulated real-time to produce one intensity map. The second implementation is based on IBM InfoSphere Streams, a cloud platform for real-time analytics of big data. To handle large processing workloads for data from various sources, it is deployed and run on a cloud-based cluster of virtual machines. We compare the quality and evolution of intensity maps from different data sources over 10-min time intervals immediately following the earthquake. Results from the joint analysis shows that it provides more complete coverage, with better accuracy and higher resolution over a larger area than either data source alone.

Research areas: Earthquakes
Bridging earthquakes and mountain building in the Santa Cruz Mountains, CA (2022)

Relative crustal motions along active faults generate earthquakes, and repeated earthquake cycles build mountain ranges over millions of years. However, the long-term summation of elastic, earthquake-related deformation cannot produce the deformation recorded within the rock record. Here, we provide an explanation for this discrepancy by showing that increases in strain facilitated by plastic deformation of Earths crust during the earthquake cycle, in conjunction with isostatic deflection and erosion, transform relative fault motions that produce individual earthquakes to geologic deformations. We focus our study on the data-rich Santa Cruz Mountains, CA, USA and compare predicted and observed quantities for rock uplift, apatite (U-Th)/He thermochronology, topographic relief,
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              Be-based erosion rates, and interseismic surface velocities. This approach reconciles these disparate records of mountain-building processes, allowing us to explicitly bridge decadal measures of deformation with that produced by millions of years of plate motion.
            
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            Plastic yielding during predominantly elastic earthquake cycles reconciles disparate observations of crustal deformation.

Research areas: Earthquakes
Piecemeal Rupture of the Mentawai Patch, Sumatra: The 2008Mw7.2 North Pagai Earthquake Sequence (2017)

The 25 February 2008 M<SUB>w</SUB> 7.2 North Pagai earthquake partially ruptured the middle section of the Mentawai patch of the Sunda megathrust, offshore Sumatra. The patch has been forecast to generate a great earthquake in the next few decades. However, in the current cycle the patch has so far broken in a sequence of partial ruptures, one of which was the 2008 event, illustrating the potential of the patch to generate a spectrum of earthquake sizes. We estimate the coseismic slip distribution of the 2008 event by jointly inverting coseismic offsets from GPS and interferometric synthetic aperture radar. We then estimate afterslip with 5.6 years of cumulative GPS displacements. Our results suggest that the estimated afterslip partially overlaps the coseismic rupture. The overlap of coseismic rupture and afterslip can be explained conceptually by a simple rate-and-state model where the degree of overlapping is controlled by the dynamic weakening and the critical nucleation size in the velocity-weakening area. Comparing our rate-and-state model results with our geodetic inversion results, we suggest that the part of the coseismic rupture that does not overlap with the afterslip may represent a velocity-weakening region, while the overlapping part may represent a velocity-strengthening region.

Research areas: Earthquakes
Towards a Sensitivity Analysis in Seismic Risk with Probabilistic Building Exposure Models: An Application in Valparaiso, Chile Using Ancillary Open-Source Data and Parametric Ground Motions (2022)

Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment.

Research areas: Earthquakes
Opportunities for natural infrastructure to improve urban water security in Latin America (2018)

Governments, development banks, corporations, and nonprofits are increasingly considering the potential contribution of watershed conservation activities to secure clean water for cities and to reduce flood risk. These organizations, however, often lack decision-relevant, initial screening information across multiple cities to identify which specific city-watershed combinations present not only water-related risks but also potentially attractive opportunities for mitigation via natural infrastructure approaches. To address this need, this paper presents a novel methodology for a continental assessment of the potential for watershed conservation activities to improve surface drinking water quality and mitigate riverine and stormwater flood risks in 70 major cities across Latin America. We used publicly available geospatial data to analyze 887 associated watersheds. Water quality metrics assessed the potential for agricultural practices, afforestation, riparian buffers, and forest conservation to mitigate sediment and phosphorus loads. Flood reduction metrics analyzed the role of increasing infiltration, restoring riparian wetlands, and reducing connected impervious surface to mitigate riverine and stormwater floods for exposed urban populations. Cities were then categorized based on relative opportunity potential to reduce identified risks through watershed conservation activities. We find high opportunities for watershed activities to mitigate at least one of the risks in 42 cities, potentially benefiting 96 million people or around 60% of the urbanites living in the 70 largest cities in Latin America. We estimate water quality could be improved for 72 million people in 27 cities, riverine flood risk mitigated for 5 million people in 13 cities, and stormwater flooding mitigated for 44 million people in 14 cities. We identified five cities with the potential to simultaneously enhance water quality and mitigate flood risks, and in contrast, six cities where conservation efforts are unlikely to meaningfully mitigate either risk. Institutions investing in natural infrastructure to improve water security in Latin America can maximize their impact by focusing on specific watershed conservation activities either for cleaner drinking water or flood mitigation in cities identified in our analysis where these interventions are most likely to reduce risk.

Research areas: Floods
Evaluation of extreme soil moisture conditions during the 2020 sahel floods and implications for disease outbreaks (2022)

The June-October 2020 growing season was characterized by sustained and extreme flooding across the African Sahel. One consequence of flooding events such as this is outbreaks of vector borne diseases (VBDs) which are often associated with climate anomalies. In this study, data from the soil moisture active passive (SMAP) mission is used with other soil moisture and precipitation data to show that the 2020 Sahelian growing season was the most extreme over the past four decades, ranking first in seasonally accumulated precipitation, which on average exceeded the climatology by around 300 mm. VBD outbreaks of Rift Valley fever and Chikungunya followed in Mauritania/Senegal and Chad, respectively. In some cases, soil moisture is a better indicator of VBD outbreak risk than precipitation, which has so far been more commonly used in studies of VBD outbreaks. It is expected that this finding will inform future monitoring and prediction efforts for VBD risk.

Research areas: Floods, Public Health
Projections of global-scale extreme sea levels and resulting episodic coastal flooding over the 21st Century (2020)

Global models of tide, storm surge, and wave setup are used to obtain projections of episodic coastal flooding over the coming century. The models are extensively validated against tide gauge data and the impact of uncertainties and assumptions on projections estimated in detail. Global hotspots where there is projected to be a significant change in episodic flooding by the end of the century are identified and found to be mostly concentrated in north western Europe and Asia. Results show that for the case of, no coastal protection or adaptation, and a mean RCP8.5 scenario, there will be an increase of 48% of the worlds land area, 52% of the global population and 46% of global assets at risk of flooding by 2100. A total of 68% of the global coastal area flooded will be caused by tide and storm events with 32% due to projected regional sea level rise.

Research areas: Floods
Automatic flood duration estimation based on multi-sensor satellite data (2020)

Flood duration is a crucial parameter for disaster impact assessment as it can directly influence the degree of economic losses and damage to structures. It also provides an indication of the spatio-temporal persistence and the evolution of inundation events. Thus, it helps gain a better understanding of hydrological conditions and surface water availability and provides valuable insights for land-use planning. The objective of this work is to develop an automatic procedure to estimate flood duration and the uncertainty associated with the use of multi-temporal flood extent masks upon which the procedure is based. To ensure sufficiently high observation frequencies, data from multiple satellites, namely Sentinel-1, Sentinel-2, Landsat-8 and TerraSAR-X, are analyzed. Satellite image processing and analysis is carried out in near real-time with an integrated system of dedicated processing chains for the delineation of flood extents from the range of aforementioned sensors. The skill of the proposed method to support satellite-based emergency mapping activities is demonstrated on two cases, namely the 2019 flood in Sofala, Mozambique and the 2017 flood in Bihar, India.

Research areas: Floods