Central and Eastern United States 

Seismic Source Characterization 

for Nuclear Facilities 

Volume 2: Chapters 5 to 7

U.S. Department of Energy

1000 Independence Avenue SW

Washington, DC 20585

Report # DOE/NE-0140

Electric Power Research Institute

3420 Hillview Avenue

Palo Alto, CA 94304

Report # 1021097

U.S. Nuclear Regulatory Commission

Offi ce of Nuclear Regulatory Research

Washington DC 20555

NUREG-2115

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Central and Eastern United States 

Seismic Source Characterization for 

Nuclear Facilities

Cosponsors

U.S. Department of Energy

1000 Independence Avenue SW

Washington, DC 20585

R. H. Lagdon, Jr.

Chief of Nuclear Safety

Office of the Under Secretary for Nuclear Security, S-5 

M.E. Shields

Project Manager

Office of Nuclear Energy, NE-72

Electric Power Research Institute

3420 Hillview Avenue

Palo Alto, CA 94304

J. F. Hamel 

Program Manager 

Advanced Nuclear Technology 

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research

Washington DC 20555

R.G. Roche-Rivera

NRC Project Manager
DISCLAIMER OF WARRANTIES AND LIMITATION OF LIABILITIES

EPRI DISCLAIMER

THIS DOCUMENT WAS PREPARED AS AN ACCOUNT OF WORK SPONSORED OR 

COSPONSORED BY THE ELECTRIC POWER RESEARCH INSTITUTE, INC. (EPRI). NEITHER 

EPRI, ANY MEMBER OF EPRI, ANY COSPONSOR BELOW, NOR ANY PERSON ACTING ON 

BEHALF OF ANY OF THEM:

(A) MAKES ANY WARRANTY OR REPRESENTATION WHATSOEVER, EXPRESS OR IMPLIED, (I) 

WITH RESPECT TO THE USE OF ANY INFORMATION, APPARATUS, METHOD, PROCESS, OR 

SIMILAR ITEM DISCLOSED IN THIS DOCUMENT, INCLUDING MERCHANTABILITY AND FITNESS 

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(INCLUDING ANY CONSEQUENTIAL DAMAGES, EVEN IF EPRI OR ANY EPRI REPRESENTATIVE 

HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES) RESULTING FROM YOUR 

SELECTION OR USE OF THIS DOCUMENT OR ANY INFORMATION, APPARATUS, METHOD, 

PROCESS, OR SIMILAR ITEM DISCLOSED IN THIS DOCUMENT.

DOE DISCLAIMER

THIS REPORT WAS PREPARED AS AN ACCOUNT OF WORK SPONSORED BY AN AGENCY OF 

THE UNITED STATES GOVERNMENT. NEITHER THE UNITED STATES GOVERNMENT NOR ANY 

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NRC DISCLAIMER

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. 
This publication is a corporate document that should be cited in the literature in the following 

manner:

Technical Report: Central and Eastern United States Seismic Source Characterization for 

Nuclear Facilities. EPRI, Palo Alto, CA, U.S. DOE, and U.S. NRC: 2012. 

iii

SPONSORS’ ACKNOWLEDGMENTS 

The project sponsors would like to acknowledge the following individuals for directing the 

project: 

Coppersmith Consulting, Inc. 

2121 N. California Blvd., #290 

Walnut Creek, CA 94596 

Technical Integration (TI) Lead

K.J. Coppersmith 

Savannah River Nuclear Solutions, LLC 

Savannah River Site 

Building 730-4B, Room 313 

Aiken, SC 29808 

CEUS SSC Project Manager

L.A. Salomone 

This document describes research sponsored by the Electric Power Research Institute (EPRI), 

U.S. Department of Energy (U.S. DOE) under Award Number DE-FG07-08ID14908, and the 

U.S. Nuclear Regulatory Commission (U.S. NRC) under Award Number NCR-04-09-144. 

v 

AUTHORS

This document was prepared by the following investigators: 

Technical Integration Lead Kevin J. Coppersmith

Project Manager Lawrence A. Salomone

Technical Integration Team Chris W. Fuller

Laura L. Glaser

Kathryn L. Hanson

Ross D. Hartleb

William R. Lettis

Scott C. Lindvall

Stephen M. McDuffie

Robin K. McGuire

Gerry L. Stirewalt

Gabriel R. Toro

Robert R. Youngs

Database Manager David L. Slayter

Technical Support Serkan B. Bozkurt

Randolph J. Cumbest

Valentina Montaldo Falero 

Roseanne C. Perman

Allison M. Shumway

Frank H. Syms

Martitia (Tish) P. Tuttle, Paleoliquefaction Data 

Resource

NUREG-2115 DOE/NE-0140 EPRI 1021097

vii 

This document has been

reproduced from the best available copy.

 

ix

ABSTRACT

This report describes a new seismic source characterization (SSC) model for the Central and 

Eastern United States (CEUS). It will replace the Seismic Hazard Methodology for the Central 

and Eastern United States, EPRI Report NP-4726 (July 1986) and the Seismic Hazard 

Characterization of 69 Nuclear Plant Sites East of the Rocky Mountains, Lawrence Livermore 

National Laboratory Model, (Bernreuter et al., 1989). The objective of the CEUS SSC Project is 

to develop a new seismic source model for the CEUS using a Senior Seismic Hazard Analysis 

Committee (SSHAC) Level 3 assessment process. The goal of the SSHAC process is to represent 

the center, body, and range of technically defensible interpretations of the available data, models, 

and methods. Input to a probabilistic seismic hazard analysis (PSHA) consists of both seismic 

source characterization and ground motion characterization. These two components are used to 

calculate probabilistic hazard results (or seismic hazard curves) at a particular site. This report 

provides a new seismic source model. 

Results and Findings

The product of this report is a regional CEUS SSC model. This model includes consideration of 

an updated database, full assessment and incorporation of uncertainties, and the range of diverse 

technical interpretations from the larger technical community. The SSC model will be widely 

applicable to the entire CEUS, so this project uses a ground motion model that includes generic 

variations to allow for a range of representative site conditions (deep soil, shallow soil, hard 

rock). Hazard and sensitivity calculations were conducted at seven test sites representative of 

different CEUS hazard environments. 

Challenges and Objectives

The regional CEUS SSC model will be of value to readers who are involved in PSHA work, and 

who wish to use an updated SSC model. This model is based on a comprehensive and traceable 

process, in accordance with SSHAC guidelines in NUREG/CR-6372, Recommendations for 

Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and Use of Experts. The model 

will be used to assess the present-day composite distribution for seismic sources along with their 

characterization in the CEUS and uncertainty. In addition, this model is in a form suitable for use 

in PSHA evaluations for regulatory activities, such as Early Site Permit (ESPs) and Combined 

Operating License Applications (COLAs).

Applications, Values, and Use

Development of a regional CEUS seismic source model will provide value to those who (1) have 

submitted an ESP or COLA for Nuclear Regulatory Commission (NRC) review before 2011; (2) 

will submit an ESP or COLA for NRC review after 2011; (3) must respond to safety issues 

resulting from NRC Generic Issue 199 (GI-199) for existing plants and (4) will prepare PSHAs 

to meet design and periodic review requirements for current and future nuclear facilities. This 

work replaces a previous study performed approximately 25 years ago. Since that study was 
x 

completed, substantial work has been done to improve the understanding of seismic sources and 

their characterization in the CEUS. Thus, a new regional SSC model provides a consistent, stable 

basis for computing PSHA for a future time span. Use of a new SSC model reduces the risk of 

delays in new plant licensing due to more conservative interpretations in the existing and future 

literature.

Perspective

The purpose of this study, jointly sponsored by EPRI, the U.S. Department of Energy (DOE), 

and the NRC was to develop a new CEUS SSC model. The team assembled to accomplish this 

purpose was composed of distinguished subject matter experts from industry, government, and 

academia. The resulting model is unique, and because this project has solicited input from the 

present-day larger technical community, it is not likely that there will be a need for significant 

revision for a number of years. See also Sponsors’ Perspective for more details.

Approach

The goal of this project was to implement the CEUS SSC work plan for developing a regional 

CEUS SSC model. The work plan, formulated by the project manager and a technical integration 

team, consists of a series of tasks designed to meet the project objectives. This report was 

reviewed by a participatory peer review panel (PPRP), sponsor reviewers, the NRC, the U.S. 

Geological Survey, and other stakeholders. Comments from the PPRP and other reviewers were 

considered when preparing the report. The SSC model was completed at the end of 2011. 

Keywords

Probabilistic seismic hazard analysis (PSHA)

Seismic source characterization (SSC)

Seismic source characterization model

Central and Eastern United States (CEUS)
xi

CONTENTS

Abstract..................................................................................................................................... vii

Contents ....................................................................................................................................ix

List of Figures .........................................................................................................................xxiii

List of Tables ........................................................................................................................ lxxvii 

Executive Summary .............................................................................................................. lxxxv 

Participatory Peer Review Panel Final Report Dated October 24, 2011 .................................. xcv

Project Acknowledgements...................................................................................................... ciii

Sponsor’s Perspective .............................................................................................................. cv 

Abbreviations ........................................................................................................................... cix 

1 INTRODUCTION ..................................................................................................................1-1 

1.1 Background and History ................................................................................................1-1 

1.1.1 EPRI-SOG and LLNL Projects ...............................................................................1-2 

1.1.2 Development of the SSHAC Process ....................................................................1-2 

1.1.3 Implementation of the SSHAC Methodology .........................................................1-3 

1.1.4 Regional SSC Model for Nuclear Facilities.............................................................1-3 

1.1.5 Differences from USGS National Seismic Hazard Mapping Project........................1-4 

1.2 Purpose of the CEUS SSC Project ................................................................................1-5 

1.2.1 Implementation of SSHAC Level 3 Process ...........................................................1-6 

1.2.2 Goals: Stability and Longevity................................................................................1-8 

1.2.3 Interface with Ground Motion Models.....................................................................1-8 

1.3 Study Region............................................................................................................... 1-10

1.4 Products of Project ...................................................................................................... 1-10

1.4.1 Seismic Source Model for Study Region .............................................................. 1-10

1.4.2 Hazard Input Document ....................................................................................... 1-12

1.4.3 Documentation of Technical Bases for All Assessments...................................... 1-12

1.4.4 Other Key Products.............................................................................................. 1-13

1.4.4.1 Data Evaluation and Data Summary Tables ................................................. 1-13
xii

1.4.4.2 Database of Geologic, Geophysical, and Seismological Data....................... 1-13

1.4.4.3 Earthquake Catalog with Uniform Moment Magnitudes ................................ 1-13

1.4.4.4 Updated Paleoseismicity Data and Guidance............................................... 1-14

1.4.4.5 Recommendations for Future Applications of SSC Model ............................ 1-14

2 SSHAC LEVEL 3 ASSESSMENT PROCESS AND IMPLEMENTATION .............................2-1 

2.1 Goals and Activities of a SSHAC Assessment Process .................................................2-2 

2.1.1 Evaluation..............................................................................................................2-4 

2.1.2 Integration .............................................................................................................2-4 

2.2 Roles of CEUS SSC Project Participants.......................................................................2-5 

2.3 CEUS SSC Project Organization...................................................................................2-7 

2.4 Key Tasks and Activities................................................................................................2-9 

2.4.1 Database Development..........................................................................................2-9 

2.4.2 Identification of Significant Issues ........................................................................ 2-10

2.4.3 Workshop #1—Key Issues and Available Data .................................................... 2-10

2.4.4 Workshop #2—Alternative Interpretations............................................................ 2-12

2.4.5 Working Meetings ................................................................................................ 2-13

2.4.6 SSC Sensitivity Model Development.................................................................... 2-14

2.4.7 Workshop #3—Feedback..................................................................................... 2-15

2.4.8 SSC Preliminary Model Development .................................................................. 2-16

2.4.9 Finalization and Review of SSC Draft and Final Model ........................................ 2-17

2.4.10 Documentation................................................................................................... 2-19

2.4.10.1 Development of the Hazard Input Document .............................................. 2-19

2.4.10.2 Development of Earlier Draft Report........................................................... 2-19

2.4.10.3 Draft Report Review ................................................................................... 2-19

2.4.10.4 Final Report Development.......................................................................... 2-20

2.5 Participatory Peer Review Panel ................................................................................. 2-20

2.5.1 Roles and Responsibilities ................................................................................... 2-20

2.5.2 Reviews and Feedback ....................................................................................... 2-20

2.5.3 Fulfillment of SSHAC-Prescribed Scope of Review of Both Technical and 

Process Issues ............................................................................................................ 2-21

2.6 Consistency of CEUS SSC Assessment Process with SSHAC Guidelines.................. 2-22

3 EARTHQUAKE CATALOG ..................................................................................................3-1 

3.1 Goals for the Earthquake Catalog Development............................................................3-1 

3.1.1 Completeness........................................................................................................3-1 
xiii

3.1.2 Uniformity of Catalog Processing ...........................................................................3-2 

3.1.3 Catalog Review......................................................................................................3-3 

3.2 Catalog Compilation ......................................................................................................3-4 

3.2.1 Continental-Scale Catalogs....................................................................................3-5 

3.2.2 Regional Catalogs..................................................................................................3-7 

3.2.3 Catalogs from Special Studies ...............................................................................3-7 

3.2.4 Focal Depth Data...................................................................................................3-8 

3.2.5 Nontectonic Events ................................................................................................3-9 

3.2.6 Identification of Unique Earthquake Entries............................................................3-9 

3.3 Development of a Uniform Moment Magnitude Earthquake Catalog............................ 3-11

3.3.1 Approach for Uniform Magnitude and Unbiased Recurrence Estimation .............. 3-11

3.3.2 Estimation of E[M] for the CEUS SSC Project Catalog......................................... 3-19

3.3.2.1 Effect of Magnitude Rounding on Statistical Tests........................................ 3-19

3.3.2.2 Moment Magnitude Data .............................................................................. 3-20

3.3.2.3 Estimation of E[M] from Body-Wave Magnitudes.......................................... 3-22

3.3.2.4 Estimation of E[M] from ML Magnitudes ....................................................... 3-28

3.3.2.5 Estimation of E[M] from MS Magnitudes ....................................................... 3-29

3.3.2.6 Estimation of E[M] from MC and MD Magnitudes .......................................... 3-30

3.3.2.7 Estimation of E[M] from the Logarithm of Felt Area ...................................... 3-32

3.3.2.8 Estimation of E[M] from the Maximum Intensity, I0 ....................................... 3-32

3.3.2.9 Uniform Moment Magnitude Catalog of E[M] and N* Values......................... 3-36

3.4 Identification of Independent Earthquakes................................................................... 3-37

3.5 Catalog Completeness ................................................................................................ 3-39

4 CONCEPTUAL SEISMIC SOURCE CHARACTERIZATION FRAMEWORK .......................4-1 

4.1 Needs for a Conceptual SSC Framework ......................................................................4-2 

4.1.1 Logic Tree Approach to Representing Alternatives and Assessing 

Uncertainties........................................................................................................ 4-2 

4.1.1.1 Examples of Logic Trees ................................................................................4-3 

4.1.1.2 Assigning Weights to Logic Tree Branches ....................................................4-3 

4.1.2 Data Identification and Evaluation..........................................................................4-5 

4.1.2.1 “Generic” Data Identification to Address Indicators of a Seismic Source.........4-5 

4.1.2.2 Data Evaluation for Particular Seismic Sources: Data Evaluation and 

Data Summary Tables................................................................................................4-7 

4.1.3 Methodology for Identifying Seismic Sources.........................................................4-9 
xiv

4.1.3.1 Hazard-Informed Approach .......................................................................... 4-11

4.1.3.2 Conclusions Regarding the Hazard Significance of Various SSC Issues...... 4-13

4.1.3.3 Criteria for Defining Seismic Sources ........................................................... 4-14

4.2 Master Logic Tree........................................................................................................ 4-18

4.2.1 Description of Logic Tree Elements...................................................................... 4-18

4.2.2 RLME Source Logic Tree..................................................................................... 4-20

4.2.3 Mmax Zones Logic Tree ...................................................................................... 4-22

4.2.4 Seismotectonic Zones Branch.............................................................................. 4-24

5 SSC MODEL: OVERVIEW AND METHODOLOGY..............................................................5-1 

5.1 Overview of Spatial and Temporal Models ....................................................................5-1 

5.1.1 Spatial Model Considerations.................................................................................5-1 

5.1.2 Considerations Regarding Temporal Models .........................................................5-3 

5.1.3 Perspective on CEUS SSC Models........................................................................5-4 

5.2 Maximum Earthquake Magnitude Assessment ..............................................................5-5 

5.2.1 Approaches to Mmax Estimation in the CEUS .......................................................5-6 

5.2.1.1 Bayesian Mmax Approach..............................................................................5-8 

5.2.1.2 Kijko Approach to Mmax Assessment .......................................................... 5-17

5.2.1.3 Weights for the Alternative Mmax Approaches ............................................. 5-20

5.2.1.4 Example Mmax Distributions ........................................................................ 5-20

5.2.2 Other Mmax Issues ............................................................................................. 5-21

5.3 Earthquake Recurrence Assessment........................................................................... 5-22

5.3.1 Smoothing to Represent Spatial Stationarity........................................................ 5-22

5.3.2 Smoothing Approach ........................................................................................... 5-23

5.3.2.1 Development of Penalized-Likelihood Approach and Formulation ................ 5-23

5.3.2.2 Application of the Model and Specification of Model Parameters.................. 5-36

5.3.2.3 Exploration of Model Results in Parameter Space........................................ 5-40

5.3.2.4 Consideration of Constant b-Value Kernel Approaches................................ 5-42

5.3.2.5 Comparison to EPRI-SOG Approach............................................................ 5-45

5.3.2.6 Assessment of the Lombardi Study .............................................................. 5-46

5.3.3 Estimation of Recurrence for RLME Sources ....................................................... 5-47

5.3.3.1 Estimation of Occurrence Rates for the Poisson Model ................................ 5-48

5.3.3.2 Estimation of Occurrence Rates for a Renewal Model.................................. 5-51

5.3.3.3 Incorporating Uncertainty in the Input...........................................................5-52

5.3.3.4 RLME Magnitude Distribution....................................................................... 5-53
xv

5.4 Assessment of Future Earthquake Characteristics ...................................................... 5-54

5.4.1 Tectonic Stress Regime....................................................................................... 5-55

5.4.2 Sense of Slip/Style of Faulting ............................................................................. 5-55

5.4.3 Strike and Dip of Ruptures ................................................................................... 5-55

5.4.4 Seismogenic Crustal Thickness .......................................................................... 5-56

5.4.5 Fault Rupture Area............................................................................................... 5-57

5.4.6 Rupture Length-to-Width Aspect Ratio................................................................. 5-57

5.4.7 Relationship of Rupture to Source Zone Boundaries............................................ 5-58

5.5 Predicted Seismic Moment Rate.................................................................................. 5-58

6 SSC MODEL: RLME SOURCES AND MMAX ZONES BRANCH ........................................6-1 

6.1 RLME Sources ..............................................................................................................6-1 

6.1.1 Charlevoix..............................................................................................................6-3 

6.1.1.1 Evidence for Temporal Clustering...................................................................6-4 

6.1.1.2 Localizing Tectonic Features..........................................................................6-4 

6.1.1.3 Geometry and Style of Faulting ......................................................................6-5 

6.1.1.4 RLME Magnitude............................................................................................6-7 

6.1.1.5 RLME Recurrence..........................................................................................6-8 

6.1.2 Charleston ........................................................................................................... 6-10

6.1.2.1 Evidence for Temporal Clustering................................................................. 6-11

6.1.2.2 Localizing Feature ........................................................................................ 6-12

6.1.2.3 Geometry and Style of Faulting .................................................................... 6-12

6.1.2.4 RLME Magnitude.......................................................................................... 6-15

6.1.2.5 RLME Recurrence........................................................................................ 6-17

6.1.3 Cheraw Fault ...................................................................................................... 6-22

6.1.3.1 Evidence for Temporal Clustering................................................................. 6-23

6.1.3.2 Geometry and Style of Faulting .................................................................... 6-24

6.1.3.3 RLME Magnitude.......................................................................................... 6-25

6.1.3.4 RLME Recurrence........................................................................................ 6-26

6.1.4 Meers Fault.......................................................................................................... 6-28

6.1.4.1 Evidence for Temporal Clustering................................................................. 6-29

6.1.4.2 Localizing Feature ........................................................................................ 6-29

6.1.4.3 Geometry and Style of Faulting .................................................................... 6-30

6.1.4.4 RLME Magnitude.......................................................................................... 6-31

6.1.4.5 RLME Recurrence........................................................................................ 6-34
xvi 

6.1.5 Reelfoot Rift–New Madrid Fault System .............................................................. 6-35

6.1.5.1 Evidence for Temporal Clustering................................................................. 6-40

6.1.5.2 Geometry and Style of Faulting .................................................................... 6-42

6.1.5.3 RLME Magnitude.......................................................................................... 6-44

6.1.5.4 RLME Recurrence........................................................................................ 6-47

6.1.6 Reelfoot Rift—Eastern Rift Margin Fault .............................................................. 6-50

6.1.6.1 Evidence for Temporal Clustering................................................................. 6-53

6.1.6.2 Geometry and Style of Faulting .................................................................... 6-53

6.1.6.3 RLME Magnitude.......................................................................................... 6-54

6.1.6.4 RLME Recurrence........................................................................................ 6-56

6.1.7 Reelfoot Rift—Marianna ...................................................................................... 6-57

6.1.7.1 Evidence for Temporal Clustering................................................................. 6-58

6.1.7.2 Geometry and Style of Faulting .................................................................... 6-59

6.1.7.3 RLME Magnitude.......................................................................................... 6-60

6.1.7.4 RLME Recurrence........................................................................................ 6-61

6.1.8 Reelfoot Rift—Commerce Fault Zone ................................................................. 6-62

6.1.8.1 Evidence for Temporal Clustering................................................................. 6-63

6.1.8.2 Geometry and Style of Faulting .................................................................... 6-64

6.1.8.3 RLME Magnitude.......................................................................................... 6-65

6.1.8.4 RLME Recurrence........................................................................................ 6-66

6.1.9 Wabash Valley .................................................................................................... 6-68

6.1.9.1 Evidence for Temporal Clustering................................................................. 6-69

6.1.9.2 Geometry and Style of Faulting .................................................................... 6-69

6.1.9.3 RLME Magnitude.......................................................................................... 6-72

6.1.9.4 RLME Recurrence........................................................................................ 6-73

6.2 Mmax Distributed Seismicity Source Zones................................................................. 6-74

6.2.1 Definition of Mmax Zones ................................................................................... 6-74

6.2.2 Criteria for Defining the MESE/NMESE Boundary ............................................... 6-75

6.3 Maximum Magnitude Distributions for Mmax Distributed Seismicity Sources............... 6-76

6.3.1 Maximum Observed Earthquake Magnitude ........................................................ 6-76

6.3.2 Mmax Distributions .............................................................................................. 6-77

6.4 Recurrence Parameters............................................................................................... 6-78

6.4.1 Rate and b-Value Maps for Single Zone and Two Zones ..................................... 6-78

6.4.2 Comparison of Recurrence Parameters to Catalog.............................................. 6-79
xvii 

7 SSC MODEL: SEISMOTECTONIC ZONES BRANCH .........................................................7-1 

7.1 Approaches and Data Used to Define Seismotectonic Zones........................................7-1 

7.2 RLME Sources in the Seismotectonic Zones Branch.....................................................7-4 

7.3 Seismotectonic Source Zones .......................................................................................7-4 

7.3.1 St. Lawrence Rift Zone (SLR) ...............................................................................7-4 

7.3.1.1 Background....................................................................................................7-5 

7.3.1.2 Basis for Defining Seismotectonic Zone ....................................................... 7-11

7.3.1.3 Basis for Zone Geometry.............................................................................. 7-12

7.3.1.4 Basis for Zone Mmax.................................................................................... 7-12

7.3.1.5 Future Earthquake Characteristics ............................................................... 7-13

7.3.2 Great Meteor Hotspot Zone (GMH) ..................................................................... 7-15

7.3.2.1 Background.................................................................................................. 7-16

7.3.2.2 Basis for Defining Seismotectonic Zone ....................................................... 7-18

7.3.2.3 Basis for Zone Geometry.............................................................................. 7-19

7.3.2.4 Basis for Zone Mmax.................................................................................... 7-19

7.3.2.5 Future Earthquake Characteristics ............................................................... 7-20

7.3.3 Northern Appalachian Zone (NAP) ...................................................................... 7-21

7.3.3.1 Background.................................................................................................. 7-21

7.3.3.2 Basis for Defining Seismotectonic Zone ....................................................... 7-23

7.3.3.3 Basis for Zone Geometry.............................................................................. 7-24

7.3.3.4 Basis for Zone Mmax.................................................................................... 7-24

7.3.3.5 Future Earthquake Characteristics ............................................................... 7-25

7.3.4 Paleozoic Extended Crust (PEZ).......................................................................... 7-25

7.3.4.1 Background.................................................................................................. 7-26

7.3.4.2 Basis for Defining Seismotectonic Zone ....................................................... 7-32

7.3.4.3 Basis for Zone Geometry.............................................................................. 7-33

7.3.4.4 Basis for Zone Mmax.................................................................................... 7-34

7.3.4.5 Future Earthquake Characteristics .............................................................. 7-36

7.3.5 Ilinois Basin Extended Basement Zone (IBEB) .................................................... 7-37

7.3.5.1 Background.................................................................................................. 7-38

7.3.5.2 Basis for Defining Seismotectonic Zone ....................................................... 7-38

7.3.5.3 Basis for Zone Geometry.............................................................................. 7-40

7.3.5.4 Basis for Zone Mmax.................................................................................... 7-41

7.3.5.5 Future Earthquake Characteristics ............................................................... 7-41

7.3.6 Reelfoot Rift Zone (RR)........................................................................................ 7-42
xviii

7.3.6.1 Background.................................................................................................. 7-42

7.3.6.2 Basis for Defining Seismotectonic Zone ....................................................... 7-46

7.3.6.3 Basis for Zone Geometry.............................................................................. 7-46

7.3.6.4 Basis for Zone Mmax.................................................................................... 7-47

7.3.6.5 Future Earthquake Characteristics ............................................................... 7-48

7.3.7 Extended Continental Crust–Atlantic Margin Zone (ECC-AM).............................. 7-48

7.3.7.1 Background.................................................................................................. 7-49

7.3.7.2 Basis for Defining Seismotectonic Zone ....................................................... 7-53

7.3.7.3 Basis for Geometry....................................................................................... 7-54

7.3.7.4 Basis for Mmax............................................................................................. 7-54

7.3.7.5 Future Earthquake Characteristics ............................................................... 7-55

7.3.8 Atlantic Highly Extended Crust Zone (AHEX)....................................................... 7-55

7.3.8.1 Basis for Defining Seismotectonic Zone ....................................................... 7-56

7.3.8.2 Basis for Geometry....................................................................................... 7-57

7.3.8.3 Basis for Mmax............................................................................................. 7-57

7.3.8.4 Future Earthquake Characteristics ............................................................... 7-57

7.3.9 Extended Continental Crust–Gulf Coast Zone (ECC-GC) .................................... 7-58

7.3.9.1 Basis for Defining Seismotectonic Zone ....................................................... 7-58

7.3.9.2 Basis for Zone Geometry.............................................................................. 7-59

7.3.9.3 Basis for Zone Mmax.................................................................................... 7-62

7.3.9.4 Future Earthquake Characteristics ............................................................... 7-63

7.3.9.5 Possible Paleoliquefaction Features in Arkansas, Louisiana, and 

Mississippi ................................................................................................................ 7-64

7.3.10 Gulf Coast Highly Extended Crust Zone (GHEX) ............................................... 7-65

7.3.10.1 Basis for Defining Seismotectonic Zone ..................................................... 7-66

7.3.10.2 Basis for Zone Geometry............................................................................ 7-66

7.3.10.3 Basis for Zone Mmax.................................................................................. 7-66

7.3.10.4 Future Earthquake Characteristics ............................................................. 7-67

7.3.11 Oklahoma Aulacogen Zone (OKA)..................................................................... 7-68 

7.3.11.1 Basis for Defining Seismotectonic Zone ..................................................... 7-69

7.3.11.2 Basis for Zone Geometry............................................................................ 7-69

7.3.11.3 Basis for Zone Mmax.................................................................................. 7-70

7.3.11.4 Future Earthquake Characteristics ............................................................. 7-70

7.3.12 Midcontinent-Craton Zone (MidC) ...................................................................... 7-70

7.3.12.1 Background ................................................................................................7-71
xix

7.3.12.2 Basis for Defining Seismotectonic Zone ..................................................... 7-76

7.3.12.3 Basis for Zone Geometry............................................................................ 7-77

7.3.12.4 Basis for Zone Mmax.................................................................................. 7-77

7.3.12.5 Future Earthquake Characteristics ............................................................. 7-77

7.4 Maximum Magnitude Distributions for Seismotectonic Distributed Seismicity 

Sources............................................................................................................................. 7-78

7.4.1 Maximum Observed Earthquake Magnitude ........................................................ 7-78

7.4.2 Mmax Distributions .............................................................................................. 7-79

7.5 Recurrence Parameters............................................................................................... 7-80

7.5.1 Rate and b-Value Maps for Single Zone and Two Zones ..................................... 7-80

7.5.2 Comparison of Recurrence Parameters to Catalog.............................................. 7-80

8 DEMONSTRATION HAZARD CALCULATIONS..................................................................8-1 

8.1 Background on Demonstration Hazard Calculations......................................................8-1 

8.2 Demonstration Hazard Calculations ..............................................................................8-2 

8.2.1 Central Illinois Site .................................................................................................8-4 

8.2.2 Chattanooga Site ...................................................................................................8-5 

8.2.3 Houston Site ..........................................................................................................8-6 

8.2.4 Jackson Site ..........................................................................................................8-7 

8.2.5 Manchester Site.....................................................................................................8-9 

8.2.6 Savannah Site .......................................................................................................8-9 

8.2.7 Topeka Site.......................................................................................................... 8-10

9 USE OF THE CEUS SSC MODEL IN PSHA ........................................................................9-1 

9.1 Overview .......................................................................................................................9-1 

9.2 Hazard Input Document (HID) .......................................................................................9-2 

9.3 Implementation Instructions...........................................................................................9-2

9.3.1 Simplifications to Seismic Sources.........................................................................9-2 

9.3.1.1 Charleston RLME...........................................................................................9-3 

9.3.1.2 Charlevoix RLME ...........................................................................................9-3 

9.3.1.3 Cheraw RLME................................................................................................9-4 

9.3.1.4 Commerce Fault Zone RLME.........................................................................9-5 

9.3.1.5 Eastern Rift Margin North RLME ....................................................................9-5 

9.3.1.6 Eastern Rift Margin South RLME....................................................................9-5 

9.3.1.7 Marianna RLME .............................................................................................9-6 

9.3.1.8 Meers RLME ..................................................................................................9-6 
xx 

9.3.1.9 New Madrid Fault System RLME....................................................................9-7 

9.3.1.10 Wabash Valley RLME...................................................................................9-7 

9.3.1.11 Background Sources ....................................................................................9-8 

9.3.2 Accessing the SSC Model and Components from the Website ..............................9-8 

9.3.3 Accessing Project Databases.................................................................................9-9 

9.3.4 Use of SSC Model with Site-Specific Refinements............................................... 9-10

9.4 Hazard Significance..................................................................................................... 9-10

9.4.1 Data Available to Evaluate the Precision of Seismic Hazard Estimates................ 9-10

9.4.2 Observed Imprecision in Seismic Hazard Estimates ............................................ 9-11

9.4.2.1 Area Seismic Sources .................................................................................. 9-11

9.4.2.2 RLME Seismic Sources................................................................................ 9-12

9.4.2.3 Ground Motion Equations............................................................................. 9-15

9.4.2.4 Site Response.............................................................................................. 9-19

9.4.3 Conclusions on the Precision in Seismic Hazard Estimates ................................. 9-19

10 REFERENCES .................................................................................................................10-1 

11 GLOSSARY OF KEY TERMS ..........................................................................................11-1 

A DESCRIPTION OF THE CEUS SSC PROJECT DATABASE............................................. A-1 

A.1 Data Sources ............................................................................................................... A-2 

A.2 Project Database Design and Management ................................................................. A-3 

A.3 Workflow and Data Assessment................................................................................... A-3 

A.3.1 Workflow............................................................................................................... A-3 

A.3.2 Digital Data........................................................................................................... A-4 

A.3.3 Nondigital Data .................................................................................................... A-4 

A.4 Use of Project Database in Model Development ......................................................... A-5 

A.5 Metadata...................................................................................................................... A-5 

A.6 Database Delivery Format............................................................................................ A-6 

B EARTHQUAKE CATALOG DATABASE............................................................................ B-1 

B.1 CEUS SSC Uniform Moment Magnitude Earthquake Catalog...................................... B-1 

B.2 Moment Magnitude Data.............................................................................................. B-2 

B.3 Approximate Moment Magnitude Data ......................................................................... B-3 

B.4 CEUS SSC Project Data .............................................................................................. B-3 
xxi 

C DATA EVALUATION TABLES ............................................................................................. C-1 

Introduction .......................................................................................................................... C-2 

D DATA SUMMARY TABLES ................................................................................................. D-1 

Introduction .......................................................................................................................... D-2 

E CEUS PALEOLIQUEFACTION DATABASE, UNCERTAINTIES ASSOCIATED WITH 

PALEOLIQUEFACTION DATA, AND GUIDANCE FOR SEISMIC SOURCE 

CHARACTERIZATION.............................................................................................................. E-i

E.1 Development of the Paleoliquefaction Database........................................................... E-1 

E.1.1 Database Structure ................................................................................................ E-1 

E.1.2 Regional Data Sets ................................................................................................ E-4 

E.2 Uncertainties Associated with Paleoliquefaction Data ................................................ E-24

E.2.1 Collection of Paleoliquefaction Data ................................................................... E-24

E.2.2 Uncertainties Related to Interpretation of Paleoliquefaction Data........................ E-35

E.2.3 Recommendations for Future Research .............................................................. E-43 

 E.3 Guidance for the Use of Paleoliquefaction Data in Seismic Source

Characterization...................................................................................................................... E-44

E.4 Glossary....................................................................................................................... E-46

E.5 References .................................................................................................................. E-49

E.5.1 References Cited in Paleoliquefaction Database ................................................ E-49

E.5.2 References Cited in Appendix E .......................................................................... E-54

F WORKSHOP SUMMARIES ................................................................................................... F-1 

WORKSHOP 1: KEY ISSUES AND AVAILABLE DATA

DAY 1–TUESDAY, JULY 22, 2008 ....................................................................................... F-1 

DAY 2–WEDNESDAY, JULY 23, 2008............................................................................... F-10

REFERENCES .................................................................................................................... F-17

WORKSHOP 2: ALTERNATIVE INTERPRETATIONS

DAY 1–WEDNESDAY, FEBRUARY 18, 2009 .....................................................................F18

DAY 2–THURSDAY, FEBRUARY 19, 2009........................................................................ F-24

DAY 3–FRIDAY, FEBRUARY 20, 2009 .............................................................................. F-29

REFERENCES .................................................................................................................. F-34

WORKSHOP 3: FEEDBACK

DAY 1–TUESDAY, AUGUST 25, 2009............................................................................... F-42

DAY 2–WEDNESDAY, AUGUST 26, 2009......................................................................... F-49
xxii 

G BIOGRAPHIES OF PROJECT TEAM................................................................................. G-1 

EPRI MANAGEMENT ........................................................................................................ G-2 

PROJECT MANAGER........................................................................................................ G-2 

TI TEAM............................................................................................................................. G-3 

TECHNICAL SUPPORT..................................................................................................... G-7 

DATABASE MANAGER ..................................................................................................... G-9 

PARTICIPATORY PEER REVIEW PANEL ........................................................................ G-9 

SPONSOR REVIEWERS................................................................................................. G-14

H CEUS SSC MODEL HAZARD INPUT DOCUMENT (HID).................................................. H-1 

H.1 Introduction.................................................................................................................. H-1 

H.2 Seismic Source Model Structure and Master Logic Tree.............................................. H-1 

H.3 Mmax Zones Distributed Seismicity Sources ............................................................... H-2 

H.3.1 Division of Study Region ..................................................................................... H-2 

H.3.2 Location of Boundary of Mesozoic Extension ...................................................... H-2 

H.3.3 Magnitude Interval Weights for Fitting Earthquake Occurrence Parameters ........ H-2 

H.3.4 Mmax Zones ....................................................................................................... H-2 

H.3.5 Seismogenic Crustal Thickness ........................................................................... H-2 

H.3.6 Future Earthquake Rupture Characteristics ......................................................... H-3 

H.3.7 Assessment of Seismicity Rates .......................................................................... H-3 

H.3.8 Degree of Smoothing Applied in Defining Spatial Smoothing of Seismicity 

Rates ............................................................................................................................. H-3 

H.3.9 Uncertainty in Earthquake Recurrence Rates....................................................... H-3 

H.3.10 Uncertainty in Maximum Magnitude.................................................................... H-4 

H.4 Seismotectonic Zones.................................................................................................. H-4 

H.4.1 Alternative Zonation Models ................................................................................. H-4 

H.4.2 Magnitude Interval Weights for Fitting Earthquake Occurrence Parameters ......... H-4 

H.4.3 Seismotectonic Zones .......................................................................................... H-5 

H.4.4 Seismogenic Crustal Thickness............................................................................ H-5 

H.4.5 Future Earthquake Rupture Characteristics ......................................................... H-5 

H.4.6 Assessment of Seismicity Rates .......................................................................... H-5 

H.4.7 Degree of Smoothing Applied in Defining Spatial Smoothing of Seismicity 

Rates ............................................................................................................................ H-5 

H.4.8 Uncertainty in Earthquake Recurrence Rates ......................................................H-5 

H.4.9 Uncertainty in Maximum Magnitude ..................................................................... H-6 

H.5 RLME Sources ....................................................................................................H-6 
xxiii

H.5.1 Charlevoix RLME Seismic Source Model ............................................................ H-6 

H.5.2 Charleston RLME Seismic Source Model............................................................. H-7 

H.5.3 Cheraw RLME Seismic Source Model.................................................................. H-9 

H.5.4 Meers RLME Seismic Source Model .................................................................. H-11

H.5.5 New Madrid Fault System RLME Seismic Source Model.................................... H-12

H.5.6 Eastern Rift Margin Fault RLME Seismic Source Model ..................................... H-14

H.5.7 Marianna Zone RLME Seismic Source Model .................................................... H-15

H.5.8 Commerce Fault RLME Seismic Source Model.................................................. H-16

H.5.9 Wabash Valley RLME Seismic Source Model .................................................... H-18

I PPRP REVIEW COMMENTS ................................................................................................ I-1 

CORRESPONDENCE—CONTENTS.................................................................................. I-3 

Participatory Peer Review Panel (PPRP) Letters............................................................ I-3 

Technical Integration (TI) Team and Project Manager (PM) Response to PPRP 

Letters ............................................................................................................................ I-4 

J MAGNITUDE-RECURRENCE MAPS FOR ALL REALIZATIONS AND ALL 

SOURCE-ZONE CONFIGURATIONS .....................................................................................J-1 

K SCR DATABASE USED TO DEVELOP MMAX PRIOR DISTRIBUTIONS ......................... K-1 

K.1 SCR Earthquake Catalog............................................................................................. K-1 

K.2 SCR Crustal Domains .................................................................................................. K-3 

L QUALITY ASSURANCE...................................................................................................... L-1 

L.1 BACKGROUND.............................................................................................................L-1 

L.2 CEUS SSC PROJECT ..................................................................................................L-2 

L.2.1 Introduction............................................................................................................L-2 

L.3 BEST BUSINESS PRACTICES.....................................................................................L-3 

L.3.1 General..................................................................................................................L-3 

L.4 CEUS SSC EARTHQUAKE CATALOG DEVELOPMENT .............................................L-3 

L.4.1 External Review of Earthquake Catalog.................................................................L-3 

L.4.2 Simulation Testing .................................................................................................L-4 

L.4.3 Checks for Consistency in Magnitude Conversion from Intensity ...........................L-4 

L.4.4 Use of Verified Computer Programs.......................................................................L-4 

L.5 RECURRENCE ANALYSIS AND SPATIAL SMOOTHING ............................................L-4 

L.5.1 Introduction............................................................................................................L-4 

L.5.2 Recurrence Comparisons at the Source-Zone Level..............................................L-5 
xxiv 

L.5.3 Recurrence Comparisons for Portions of a Source Zone ......................................L-5 

L.5.4 Examination of Recurrence Maps .........................................................................L-5 

L.5.5 Test with a Synthetic Catalog Homogeneous Seismicity .......................................L-5 

L.5.6 Test for the Adequacy of Eight Maps to Represent Epistemic Uncertainty .............L-6 

L.6 HAZARD CALCULATION SOFTWARE.........................................................................L-6 

L.6.1 Introduction............................................................................................................L-6 

L.6.2 Test for the Treatment of Variable b.......................................................................L-6 

L.6.3 Test for the Treatment of Dipping Ruptures Within a Source Zone ........................L-6 

L.6.4 Tests for Treatment of Epistemic Uncertainty from Sources that Make Small 

Contribution to Hazard....................................................................................................L-6 
xxv 

LIST OF FIGURES

Figure 1.3-1 Map showing the study area and test sites for the CEUS SSC Project............... 1-15

Figure 2.3-1 CEUS SSC Project organization ........................................................................ 2-33 

Figure 2.3-2 Lines of communication among the participants of the CEUS SSC Project........ 2-34 

Figure 2.4-1 Essential activities associated with a SSHAC Level 3 or 4 project 

(Coppersmith et al., 2010).............................................................................................. 2-35 

Figure 3.2-1 Areal coverage of the primary earthquake catalog sources. Top: GSC 

catalog (Halchuk, 2009); bottom: USGS seismic hazard mapping catalog (Petersen 

et al., 2008). Red line denotes boundary of study region. Blue line denotes portion 

of each catalog used for development of project catalog. ............................................... 3-57

Figure 3.2-2 Histogram of ML magnitudes from the GSC SHEEF catalog for the time 

period 1600-1899 and the region east of longitude –105° and south of latitude 53°........ 3-58

Figure 3.2-3 Histogram of ML magnitudes from the GSC SHEEF catalog for the time 

period 1900-1929 and the region east of longitude –105° and south of latitude 53°........ 3-59

Figure 3.2-4 Histogram of ML magnitudes from the GSC SHEEF catalog for the time 

period 1930-1979 and the region east of longitude –105° and south of latitude 53°........ 3-60

Figure 3.2-5 Histogram of ML magnitudes from the GSC SHEEF catalog for the time 

period 1980-2007 and the region east of longitude –105° and south of latitude 53°........ 3-61

Figure 3.2-6 Histogram of ML magnitudes from the revised catalog with GSC as the 

source for the time period 1928-1979............................................................................. 3-62

Figure 3.2-7 Map of the CEUS SSC Project catalog showing earthquakes of uniform 

moment magnitude E[M] 2.9 and larger. Colored symbols denote earthquakes not 

contained in the USGS seismic hazard mapping catalog................................................ 3-63

Figure 3.3-1 Illustration of equivalence of the M* and γ2 corrections to remove bias in 

earthquake recurrence relationships estimated from magnitudes with uncertainty ......... 3-64

Figure 3.3-2 Approximate moment magnitudes from Atkinson (2004b) compared to 

values of M given in Table B-2 in Appendix B for earthquakes in common..................... 3-65

Figure 3.3-3 Approximate moment magnitudes from Boatwright (1994) compared to 

values of M given in Table B-2 in Appendix B for earthquakes in common..................... 3-66

Figure 3.3-4 Approximate moment magnitudes from Moulis (2002) compared to values 

of M given in Table B-2 in Appendix B for earthquakes in common ................................ 3-67

Figure 3.3-5 Difference between MN reported by the GSC and MN or mLg(f) reported by 

the Weston Observatory catalog as a function of time.................................................... 3-68

Figure 3.3-6 Spatial distribution of earthquakes with body-wave (mb, mbLg, MN) and M 

magnitudes in the CEUS SSC Project catalog for the Midcontinent region. Color 

codes indicate the source of the body-wave magnitudes................................................ 3-69

Figure 3.3-7 mb-M data for the earthquakes shown on Figure 3.3-6. Red curve shows 

the preferred offset fit M = mb – 0.28.............................................................................. 3-70
xxvi 

Figure 3.3-8 Residuals from offset fit shown on Figure 3.3-7 plotted against earthquake 

year................................................................................................................................ 3-71

Figure 3.3-9 Spatial distribution of earthquakes with body wave (mb, mbLg, MN) and M 

magnitudes in the CEUS SSC Project catalog for the northeastern portion of the 

study region. Color codes indicate the source of the body-wave magnitudes. ................ 3-72

Figure 3.3-10 mb-M data for the earthquakes shown on Figure 3.3-9. Red curve shows 

the preferred offset fit M = mb – 0.42.............................................................................. 3-73

Figure 3.3-11 Residuals from offset fit shown on Figure 3.3-10 plotted against 

earthquake year ............................................................................................................. 3-74

Figure 3.3-12 Residuals for GSC data from offset fit shown on Figure 3.3-10 plotted 

against earthquake year................................................................................................. 3-75

Figure 3.3-13 Residuals for WES data from offset fit shown on Figure 3.3-10 plotted 

against earthquake year................................................................................................. 3-76

Figure 3.3-14 Residuals for data from sources other than GSC or WES from offset fit 

shown on Figure 3.3-10 plotted against earthquake year ............................................... 3-77

Figure 3.3-15 Difference between body-wave magnitudes reported by LDO and those by 

other sources as a function of year................................................................................. 3-78

Figure 3.3-16 Spatial distribution of earthquakes with reported GSC body-wave 

magnitudes. Red and blue symbols indicate earthquakes with both mb and M 

magnitudes for mb ≥ 3.5. Dashed line indicates the portion of the study region 

considered the “Northeast” for purposes of magnitude scaling. ...................................... 3-79

Figure 3.3-17 M-mb as a function of time for mb data from the GSC shown on Figure 3.3-

16................................................................................................................................... 3-80

Figure 3.3-18 Plot of magnitude differences mbLg – m(3 Hz) for the OKO catalog .................. 3-81

Figure 3.3-19 Final mb-M data set. Vertical dashed lines indicate the magnitude range 

used to develop the scaling relationship. Diagonal line indicates a one-to-one 

correlation. ..................................................................................................................... 3-82

Figure 3.3-20 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

instrumental ML magnitudes........................................................................................... 3-83

Figure 3.3-21 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

instrumental ML magnitudes and M magnitudes............................................................. 3-84

Figure 3.3-22 ML-M data from the CEUS SSC Project catalog and robust regression fit to 

the data .......................................................................................................................... 3-85

Figure 3.3-23 Relationship between MN and ML for the GSC data......................................... 3-86

Figure 3.3-24 Data from the northeastern portion of the study region with ML and MC or 

MD magnitude from catalog sources other than the GSC ............................................... 3-87

Figure 3.3-25 Data from the northeastern portion of the study region with ML and M 

magnitudes from sources other than the GSC................................................................ 3-88

Figure 3.3-26 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

MS ≥ 3 magnitudes......................................................................................................... 3-89

Figure 3.3-27 MS-M data from the CEUS SSC Project catalog and quadratic polynomial 

fit to the data .................................................................................................................. 3-90

Figure 3.3-28 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

MC ≥ 2.5 magnitudes...................................................................................................... 3-91
xxvii 

Figure 3.3-29 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

MC ≥ 2.5 and M magnitudes ........................................................................................... 3-92

Figure 3.3-30 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

MD ≥ 3 magnitudes......................................................................................................... 3-93

Figure 3.3-31 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

both MD and M magnitudes ............................................................................................ 3-94

Figure 3.3-32 MC-M data from the CEUS SSC Project catalog and linear regression fit to 

the data .......................................................................................................................... 3-95

Figure 3.3-33 Spatial distribution of earthquakes with reported MC and MD magnitudes ........ 3-96

Figure 3.3-34 Comparison of MC and MD magnitudes for the LDO and WES catalogs .......... 3-97

Figure 3.3-35 Comparison of MC with MD for at least one of the two magnitude types 

reported in the OKO catalog........................................................................................... 3-98

Figure 3.3-36 Comparison of MC with MD for at least one of the two magnitude types 

reported in the CERI catalog .......................................................................................... 3-99

Figure 3.3-37 Comparison of MC with MD for at least one of the two magnitude types 

reported in the SCSN catalog....................................................................................... 3-100

Figure 3.3-38 Comparison of MC with MD for at least one of the two magnitude types 

reported in other catalogs for earthquakes in the Midcontinent portion of the study 

region ........................................................................................................................... 3-101

Figure 3.3-39 Relationship between M and MC, MD, or ML for the Midcontinent portion of 

the study region............................................................................................................ 3-102

Figure 3.3-40 Comparison of MC and MD magnitudes with ML magnitudes for the region 

between longitudes 105°W and 100°W ........................................................................ 3-103

Figure 3.3-41 Comparison of mb magnitudes with ML magnitudes for the region between 

longitudes 105°W and 100°W....................................................................................... 3-104

Figure 3.3-42 Comparison of mb magnitudes with MC and MD magnitudes for the region 

between longitudes 105°W and 100°W ........................................................................ 3-105

Figure 3.3-43 Spatial distribution of earthquake with ln(FA) in the CEUS SSC Project 

catalog ......................................................................................................................... 3-106

Figure 3.3-44 Catalog ln(FA)–M data and fitted model......................................................... 3-107

Figure 3.3-45 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

reported values of I0 ..................................................................................................... 3-108

Figure 3.3-46 I0 and M data for earthquakes in the CEUS SSC Project catalog. Curves 

show locally weighted least-squares fit (Loess) to the data and the relationship 

published by Johnston (1996b)..................................................................................... 3-109

Figure 3.3-47 I0 and mb data from the NCEER91 catalog. Plotted are the relationships 

between I0 and mb developed by EPRI (1988) (EPRI-SOG) and Sibol et al. (1987). .... 3-110

Figure 3.3-48 Categorical model fits of I0 as a function and M for earthquakes in the 

CEUS SSC Project catalog .......................................................................................... 3-111

Figure 3.3-49 Results from proportional odds logistic model showing the probability of 

individual intensity classes as a function of M............................................................... 3-112

Figure 3.3-50 Comparison of I0 and mb data from the CEUS SSC Project catalog for 

those earthquakes with reported values of M (M set) and the full catalog (full set). 

Locally weighted least-squares fits to the two data sets are shown along with the 
xxviii 

relationship use to develop the EPRI (1988) catalog and the Sibol et al. (1987) 

relationship used in the NCEER91 catalog. .................................................................. 3-113

Figure 3.3-51 Linear fits to the data from Figure 3.3-50 for I0 ≥ V ......................................... 3-114

Figure 3.3-52 Comparison of I0 and mb data from the project, with mb adjusted for the 

difference in mb to M scaling ....................................................................................... 3-115

Figure 3.3-53 Linear fits to the data from Figure 3.3-52 for I0 ≥ V ......................................... 3-116

Figure 3.3-54 Composite I0–M data set used for assessment of I0 scaling relationship........ 3-117

Figure 3.3-55 Linear and inverse sigmoid models fit to the project data for I0 > IV............... 3-118

Figure 3.4-1 Illustration of process used to identify clusters of earthquakes (from EPRI, 

1988, Vol. 1): (a) local and extended time and distance windows, (b) buffer window, 

and (c) contracted window............................................................................................ 3-119

Figure 3.4-2 Identification of secondary (dependent) earthquakes inside the cluster 

region through Poisson thinning (from EPRI, 1988, Vol. 1)........................................... 3-120

Figure 3.4-3 Comparison of dependent event time and distance windows with results for 

individual clusters in the project catalog ....................................................................... 3-121

Figure 3.5-1 Earthquake catalog and catalog completeness regions used in EPRI-SOG 

(EPRI, 1988) ................................................................................................................ 3-122

Figure 3.5-2 CEUS SSC Project earthquake catalog and modified catalog completeness 

regions ......................................................................................................................... 3-123

Figure 3.5-3 Plot of year versus location for the CEUS SSC Project earthquake catalog. 

Red lines indicate the boundaries of the catalog completeness time periods................ 3-124

Figure 3.5-4 (1 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-125

Figure 3.5-4 (2 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-126

Figure 3.5-4 (3 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-127

Figure 3.5-4 (4 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-128

Figure 3.5-4 (5 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-129

Figure 3.5-4 (6 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-130

Figure 3.5-4 (7 of 7) “Stepp” plots of earthquake recurrence rate as a function of time for 

the individual catalog completeness regions shown on Figure 3.5-2 ............................. 3-131

Figure 4.1.1-1 Example logic tree from the PEGASOS project (NAGRA, 2004) showing 

the assessment of alternative conceptual models on the logic tree. Each node of 

the logic tree represents an assessment that is uncertain. Alternative branches 

represent the alternative models or parameter values, and the weights associated 

with each branch reflect the TI Team’s relative degree of belief that each branch is 

the correct model or parameter value. ............................................................................ 4-40

Figure 4.1.1-2 Example logic tree from the PVHA-U (SNL, 2008) project showing the 

treatment of alternative conceptual models in the logic tree ........................................... 4-41
xxix

Figure 4.2.1-1 Master logic tree showing the Mmax zones and seismotectonic zones 

alternative conceptual models for assessing the spatial and temporal characteristics 

of future earthquake sources in the CEUS...................................................................... 4-42

Figure 4.2.2-1 Example of a logic tree for RLME sources. Shown is the tree for the 

Marianna RLME source.................................................................................................. 4-43

Figure 4.2.2-2 Map showing RLME sources, some with alternative source geometries 

(discussed in Section 6.1). ............................................................................................. 4-44

Figure 4.2.3-1 Logic tree for the Mmax zones branch of the master logic tree ....................... 4-45

Figure 4.2.3-2 Subdivision used in the Mmax zones branch of the master logic tree. 

Either the region is considered one zone for purposes of Mmax or the region is 

divided into two zones as shown: a Mesozoic-and-younger extension (MESE) zone 

and a non-Mesozoic-and-younger zone (NMESE). In this figure the “narrow” MESE 

zone is shown ................................................................................................................ 4-46

Figure 4.2.3-3 Subdivision used in the Mmax zones branch of the master logic tree. 

Either the region is considered one zone for purposes of Mmax or the region is 

divided into two zones as shown: a Mesozoic-and-younger extension (MESE) zone 

and a non-Mesozoic-and-younger zone (NMESE). In this figure the “wide” MESE 

zone is shown ................................................................................................................ 4-47

Figure 4.2.4-1(a) Logic tree for the seismotectonic zones branch of the master logic tree ..... 4-48

Figure 4.2.4-1(b) Logic tree for the seismotectonic zones branch of the master logic tree ..... 4-49

Figure 4.2.4-2 Seismotectonic zones shown in the case where the Rough Creek Graben 

is not part of the Reelfoot Rift (RR), and the Paleozoic Extended Zone is narrow 

(PEZ-N) ......................................................................................................................... 4-50

Figure 4.2.4-3 Seismotectonic zones shown in the case where the Rough Creek Graben 

is part of the Reelfoot Rift (RR-RCG), and the Paleozoic Extended Zone is narrow 

(PEZ-N).......................................................................................................................... 4-51

Figure 4.2.4-4 Seismotectonic zones shown in the case where the Rough Creek Graben 

is not part of the Reelfoot Rift (RR), and the Paleozoic Extended Crust is wide 

(PEZ-W)......................................................................................................................... 4-52

Figure 4.2.4-5 Seismotectonic zones shown in the case where the Rough Creek Graben 

is part of the Reelfoot Rift (RR-RCG), and the Paleozoic Extended Crust is wide 

(PEZ-W)......................................................................................................................... 4-53

Figure 5.2.1-1 Diagrammatic illustration of the Bayesian Mmax approach showing (a) the 

prior distribution, (b) the likelihood function, and (c) the posterior distribution. The 

posterior distribution is represented by a discrete distribution (d) for implementation 

in hazard analysis........................................................................................................... 5-72

Figure 5.2.1-2 Diagrammatic illustration of the Bayesian Mmax approach showing (a) the 

prior distribution, (b) the likelihood function, and (c) the posterior distribution. The 

posterior distribution is represented by a discrete distribution (d) for implementation 

in hazard analysis........................................................................................................... 5-73

Figure 5.2.1-3 Median values of mmax−obs as a function of maximum magnitude, mu

, and 

sample size N, the number of earthquakes ≥ M 4.5........................................................ 5-74

Figure 5.2.1-4 Histograms of mmax−obs for extended and non-extended superdomains .......... 5-75
xxx 

Figure 5.2.1-5 Histograms of mmax−obs for Mesozoic-and-younger extended (MESE) 

superdomains and for older extended and non-extended (NMESE) superdomains ........ 5-76

Figure 5.2.1-6 Histograms of mmax−obs for Mesozoic-and-younger extended (MESE) 

superdomains and for older extended and non-extended (NMESE) superdomains 

using age of most recent extension for the age classification ......................................... 5-77

Figure 5.2.1-7 Histograms of mmax−obs for Mesozoic-and-younger extended (MESE) 

superdomains and for older extended and non-extended (NMESE) superdomains 

using final sets indicated by asterisks in Tables 5.2.1-1 and 5.2.1-2 ............................... 5-78

Figure 5.2.1-8 Histograms of mmax−obs for combined (COMB) superdomains using final 

sets indicated by asterisks in Table 5.2.1-3 .................................................................... 5-79

Figure 5.2.1-9 Bias adjustments from mmax−obs to mu for the three sets of superdomain 

analysis results presented in Table 5.2.1-4 ..................................................................... 5-80

Figure 5.2.1-10 Results of simulations of estimates of Mmax using the Bayesian 

approach for earthquake catalogs ranging in size from 1 to 1,000 earthquakes. True 

Mmax is set at the mean of the prior distribution............................................................. 5-81

Figure 5.2.1-11 Comparison of the Kijko (2004) estimates of mu for given values of 

mmax−obs and N, the number of earthquakes of magnitude ≥ 4.5. Also shown is the 

median value of mmax−obs for given mu obtained using Equation 5.2.1-2. ........................ 5-82

Figure 5.2.1-12 Behavior of the cumulative probability function for mu (Equation 5.2.1-9) 

for the K-S-B estimator and a value of mmax−obs equal to 6 ............................................. 5-83

Figure 5.2.1-13 Example Mmax distribution assessed for the Mesozoic-and-younger 

extended Mmax zone for the case where the zone is “narrow” (MESE-N). 

Distributions are shown for the Kijko approach and for the Bayesian approach using 

either the Mesozoic-and-younger extended prior distribution or the composite prior 

distribution. The final composite Mmax distribution, which incorporates the relative 

weights, is shown by the red probability distribution. ...................................................... 5-84

Figure 5.2.1-14 Example Mmax distribution assessed for the Northern Appalachian 

seismotectonic zone (NAP). Distributions are shown for the Kijko approach and for 

the Bayesian approach using either the Mesozoic-and-younger extended prior 

distribution or the composite prior distribution. Note that the Kijko results are shown 

in this example for illustration, even though they have zero weight. The final 

composite Mmax distribution, which incorporates the relative weights, is shown by 

the red probability distribution......................................................................................... 5-85

Figure 5.3.2-1 Likelihood function for rate per unit area in a Poisson process, for multiple 

values of the earthquake count N: (a) arithmetic scale, and (b) logarithmic scale 

used to illustrate decreasing COV as N increases .......................................................... 5-86

Figure 5.3.2-2 Likelihood function for b-value of an exponential magnitude distribution, 

for multiple values of the earthquake count N. The value of b is normalized by the 

maximum-likelihood estimate, which is derived from Equation 5.3.2-5. .......................... 5-87

Figure 5.3.2-3 Histogram of magnitudes in the earthquake catalog used in this section. 

The minimum magnitude shown (M 2.9) is the lowest magnitude used in these 

recurrence calculations................................................................................................... 5-88
xxxi 

Figure 5.3.2-4 Objectively determined values of the penalty function for ln(rate) for Case 

A magnitude weights. Source zones are sorted from smallest to largest. See list of 

abbreviations for full source-zone names. ...................................................................... 5-89

Figure 5.3.2-5 Objectively determined values of the penalty function for beta for Case A 

magnitude weights ......................................................................................................... 5-90

Figure 5.3.2-6 Objectively determined values of the penalty function for ln(rate) for Case 

B magnitude weights ...................................................................................................... 5-91

Figure 5.3.2-7 Objectively determined values of the penalty function for beta for Case B 

magnitude weights. Source zones are sorted from smallest to largest............................ 5-92

Figure 5.3.2-8 Objectively determined values of the penalty function for ln(rate) for Case 

E magnitude weights ...................................................................................................... 5-93

Figure 5.3.2-9 Objectively determined values of the penalty function for beta for Case E 

magnitude weights. Source zones are sorted from smallest to largest............................ 5-94

Figure 5.3.2-10 Mean map of rate and b-value for ECC-AM calculated using Case A 

magnitude weights ......................................................................................................... 5-95

Figure 5.3.2-11 Mean map of rate and b-value for ECC-GC calculated using Case A 

magnitude weights ......................................................................................................... 5-96

Figure 5.3.2-12 Mean map of rate and b-value for ECC-AM calculated using Case B 

magnitude weights ......................................................................................................... 5-97

Figure 5.3.2-13 Mean map of rate and b-value for ECC-GC calculated using Case B 

magnitude weights ......................................................................................................... 5-98

Figure 5.3.2-14 Mean map of rate and b-value for ECC-AM calculated using Case E 

magnitude weights ......................................................................................................... 5-99

Figure 5.3.2-15 Mean map of rate and b-value for ECC-GC calculated using Case E 

magnitude weights ....................................................................................................... 5-100

Figure 5.3.2-16 Sensitivity of seismic hazard at Manchester site to the strength of the 

prior on b...................................................................................................................... 5-101

Figure 5.3.2-17 Sensitivity of seismic hazard at Topeka site to the strength of the prior 

on b.............................................................................................................................. 5-102

Figure 5.3.2-18 Sensitivity of seismic hazard at Manchester site to the choice of 

magnitude weights ....................................................................................................... 5-103

Figure 5.3.2-19 Sensitivity of seismic hazard at Topeka site to the choice of magnitude 

weights......................................................................................................................... 5-104

Figure 5.3.2-20 Sensitivity of seismic hazard from source NAP at Manchester site to the 

eight alternative recurrence maps for Case B magnitude weights ................................ 5-105

Figure 5.3.2-21 Sensitivity of seismic hazard from source MID-C–A at Topeka site to the 

eight alternative recurrence maps for Case B magnitude weights ................................ 5-106

Figure 5.3.2-22 Mean recurrence-parameter map for the study region under the highest 

weighted source-zone configuration in the master logic tree. See Sections 6.3 and 

7.5 for all mean maps................................................................................................... 5-107

Figure 5.3.2-23 Map of the uncertainty in the estimated recurrence parameters, 

expressed as the coefficient of variation of the rate (left) and the standard deviation 

of the b-value (right) for the study region, under the highest weighted source-zone 

configuration in the master logic tree. See Appendix J for all maps of uncertainty........ 5-108
xxxii 

Figure 5.3.2-24 First of eight equally likely realizations of the recurrence-parameter map 

for the study region under the highest weighted source-zone configuration in the

master logic tree. See Appendix J for maps of all realizations for all source-zone 

configurations............................................................................................................... 5-109

Figure 5.3.2-25 Eighth of eight equally likely realizations of the recurrence-parameter 

map for the study region under the highest weighted source-zone configuration in 

the master logic tree. See Appendix J for maps of all realizations for all source-zone 

configurations............................................................................................................... 5-110

Figure 5.3.2-26 Map of geographic areas considered in the exploration of model results..... 5-111

Figure 5.3.2-27 Comparison of model-predicted earthquake counts for the USGS 

Eastern Tennessee area using Case A magnitude weights. The error bars 

represent the 16%–84% uncertainty associated with the data, computed using the 

Weichert (1980) procedure........................................................................................... 5-112

Figure 5.3.2-28 Comparison of model-predicted earthquake counts for the USGS 

Eastern Tennessee area using Case B magnitude weights.......................................... 5-113

Figure 5.3.2-29 Comparison of model-predicted earthquake counts for the USGS 

Eastern Tennessee area using Case E magnitude weights.......................................... 5-114

Figure 5.3.2-30 Comparison of model-predicted earthquake counts for the central New 

England area using Case A magnitude weights............................................................ 5-115

Figure 5.3.2-31 Comparison of model-predicted earthquake counts for the central New 

England area using Case B magnitude weights............................................................ 5-116

Figure 5.3.2-32 Comparison of model-predicted earthquake counts for the central New 

England area using Case E magnitude weights............................................................ 5-117

Figure 5.3.2-33 Comparison of model-predicted earthquake counts for the Nemaha 

Ridge area using Case A magnitude weights ............................................................... 5-118

Figure 5.3.2-34 Comparison of model-predicted earthquake counts for the Nemaha 

Ridge area using Case B magnitude weights ............................................................... 5-119

Figure 5.3.2-35 Comparison of model-predicted earthquake counts for the Nemaha 

Ridge area using Case E magnitude weights ............................................................... 5-120

Figure 5.3.2-36 Comparison of model-predicted earthquake counts for the Miami, FL, 

area using Case A magnitude weights ......................................................................... 5-121

Figure 5.3.2-37 Comparison of model-predicted earthquake counts for the Miami, FL, 

area using Case B magnitude weights ......................................................................... 5-122

Figure 5.3.2-38 Comparison of model-predicted earthquake counts for the Miami, FL, 

area using Case E magnitude weights ......................................................................... 5-123

Figure 5.3.2-39 Comparison of model-predicted earthquake counts for the St. Paul, MN, 

area using Case A magnitude weights ......................................................................... 5-124

Figure 5.3.2-40 Comparison of model-predicted earthquake counts for the St. Paul, MN, 

area using Case B magnitude weights ......................................................................... 5-125

Figure 5.3.2-41 Comparison of model-predicted earthquake counts for the St. Paul, MN, 

area using Case E magnitude weights ......................................................................... 5-126

Figure 5.3.2-42 Recurrence parameters for the ECC-AM, MID-C–A, and NAP 

seismotectonic source zones and Case A magnitude weights computed using an 

objective adaptive kernel approach .............................................................................. 5-127
xxxiii 

Figure 5.3.3-1 Likelihood distribution for rate parameter λ derived using Equation 5.3.3-1 

for N = 2 and T = 2,000 years. Top: normalized probability density function for λ. 

Bottom: resulting cumulative distribution function. Dashed lines show the 

cumulative probability levels for the Miller and Rice (1983) discrete approximation of 

a continuous probability distribution.............................................................................. 5-128

Figure 5.3.3-2 Uncertainty distributions for the age of Charleston RLMEs............................ 5-129

Figure 5.4.4-1 Spatial distribution of earthquakes in the CEUS SSC Project catalog. 

Solid lines indicate the boundaries of the seismotectonic source zones (narrow 

interpretation)............................................................................................................... 5-130

Figure 5.4.4-2 Spatial distribution of earthquakes in the CEUS SSC Project catalog with 

good quality depth determinations used for assessing crustal thickness. Solid lines 

indicate the boundaries of the seismotectonic source zones (narrow interpretation)..... 5-131

Figure 5.4.4-3 Distribution of better-quality focal depths in Mmax source zones .................. 5-132

Figure 5.4.4-4 (1 of 3) Distribution of better-quality focal depths in seismotectonic source

zones ........................................................................................................................... 5-133

Figure 5.4.4-4 (2 of 3) Distribution of better-quality focal depths in seismotectonic source 

zones ........................................................................................................................... 5-134

Figure 5.4.4-4 (3 of 3) Distribution of better-quality focal depths in seismotectonic source 

zones ........................................................................................................................... 5-135

Figure 6.1-1 Map showing the RLME sources characterized in the CEUS SSC model. 

Detailed alternatives to the source geometries are shown on figures associated with 

each RLME discussion................................................................................................. 6-111

Figure 6.1-2a Map showing the RLME sources and seismicity from the CEUS SSC 

earthquake catalog. Some of the RLMEs occur in regions of elevated seismicity, but 

others do not. ............................................................................................................... 6-112 

Figure 6.1-2b Close-up of the Wabash Valley and New Madrid/Reelfoot Rift RLME 

sources and seismicity from the CEUS SSC earthquake catalog. Some of the 

RLMEs occur in regions of elevated seismicity, but others do not. ............................... 6-113 

Figure 6.1.1-1 Logic tree for the Charlevoix RLME source ................................................... 6-114 

Figure 6.1.1-2 Seismicity and tectonic features of the Charlevoix RLME.............................. 6-115 

Figure 6.1.1-3 Magnetic and gravity anomaly maps of the Charlevoix RLME....................... 6-116 

Figure 6.1.2-1a Logic tree for the Charleston RLME source................................................. 6-117 

Figure 6.1.2-1b Logic tree for the Charleston RLME source................................................. 6-118 

Figure 6.1.2-2 Charleston RLME source zones with (a) total magnetic anomaly and (b) 

residual isostatic gravity data ..................................................................................... 6-119 

Figure 6.1.2-3 Postulated faults and tectonic features in the Charleston region ................. 6-120

Figure 6.1.2-4 Postulated faults and tectonic features in the local Charleston area ............ 6-121

Figure 6.1.2-5a Postulated faults and tectonic features in the Charleston region with 

Charleston RLME source zones .................................................................................. 6-122 

Figure 6.1.2-5b Postulated faults and tectonic features in the local Charleston area with 

Charleston RLME source zones ................................................................................... 6-123 

Figure 6.1.2-6 Schematic diagram showing contemporary, maximum, and minimum 

constraining age sample locations................................................................................ 6-124 
xxxiv 

Figure 6.1.2-7 Charleston space-time diagram of earthquakes interpreted from 

paleoliquefaction, contemporary-ages-only scenario ................................................... 6-125 

Figure 6.1.2-8 Charleston space-time diagram of earthquakes interpreted from 

paleoliquefaction, all-ages scenario ............................................................................ 6-126 

Figure 6.1.2-9 Distribution of liquefaction from earthquake A, contemporary-ages-only 

scenario ...................................................................................................................... 6-127 

Figure 6.1.2-10 Distribution of liquefaction from earthquake B, contemporary-ages-only 

scenario ...................................................................................................................... 6-128 

Figure 6.1.2-11 Distribution of liquefaction from earthquake C, contemporary-ages-only 

scenario ...................................................................................................................... 6-129 

Figure 6.1.2-12 Distribution of liquefaction from earthquake D, contemporary-ages-only 

scenario ...................................................................................................................... 6-130

Figure 6.1.2-13 Distribution of liquefaction from earthquake E, contemporary-ages-only 

scenario ...................................................................................................................... 6-131

Figure 6.1.2-14 Distribution of liquefaction from earthquake A, all-ages scenario ............... 6-132 

Figure 6.1.2-15 Distribution of liquefaction from earthquake B, all-ages scenario ............... 6-133 

Figure 6.1.2-16 Distribution of liquefaction from earthquake C, all-ages scenario .............. 6-134 

Figure 6.1.2-17 Distribution of liquefaction from earthquake D, all-ages scenario .............. 6-135 

Figure 6.1.2-18 Distribution of liquefaction from earthquake E, all-ages scenario................. 6-136 

Figure 6.1.2-19 Uncertainty distributions for the age of Charleston RLMEs.......................... 6-137 

Figure 6.1.3-1 Logic tree for the Cheraw fault RLME source................................................ 6-138 

Figure 6.1.3-2 Map (c) and hillshade relief images (a, b, and d) showing location of 

mapped Cheraw fault, possible northeast extension, and paleoseismic locality............ 6-139 

Figure 6.1.3-3 Cheraw RLME source relative to (a) total magnetic anomaly and (b) 

residual isostatic gravity data........................................................................................ 6-140

Figure 6.1.4-1 Meers fault location....................................................................................... 6-141

Figure 6.1.4-2 Logic tree for the Meers fault source ............................................................. 6-142 

Figure 6.1.5-1 Logic tree for the NMFS RLME source ........................................................ 6-143 

Figure 6.1.5-2 Map showing seismicity and major subsurface structural features in the 

New Madrid region ..................................................................................................... 6-144 

Figure 6.1.5-3 Map showing geomorphic and near-surface tectonic features in the New 

Madrid region and locations of NMFS RLME fault sources ......................................... 6-145 

Figure 6.1.5-4 Rupture segments (a) and models (b) for the New Madrid faults from 

Johnston and Schweig (1996) and (c) the NMFS RLME fault sources ........................ 6-146 

Figure 6.1.5-5 Map of NMSZ showing estimated ages and measured sizes of 

liquefaction features ..................................................................................................... 6-147 

Figure 6.1.5-6 Earthquake chronology for NMSZ from dating and correlation of 

liquefaction features at sites (listed at top) along N-S transect across region ............... 6-148 

Figure 6.1.5-7 Probability distributions for the age of the AD 900 and AD 1450 NMFS 

RLMEs ......................................................................................................................... 6-149 

Figure 6.1.5-8 Liquefaction fields for the 1811-1812, AD 1450, and AD 900 earthquakes 

as interpreted from spatial distribution and stratigraphy of sand blows ......................... 6-150
xxxv 

Figure 6.1.6-1a Logic tree for the Reelfoot Rift–Eastern Rift Margin South RLME source. 

Two options for the southern extent of the ERM-S are considered: ERM-SCC 

includes the Crittenden County fault zone, and ERM-SRP includes the postulated 

zone of deformation based on fault picks identified in a high-resolution seismic 

profile along the Mississippi River................................................................................. 6-151

Figure 6.1.6-1b Logic tree for the Reelfoot Rift–Eastern Rift Margin North RLME source..... 6-152 

Figure 6.1.6-2 Map showing structural features and paleoseismic investigation sites 

along the eastern margin of the Reelfoot rift. The inset map shows the locations of 

inferred basement faults that border and cross the Reelfoot rift (Csontos et al., 

2008) and the inferred Joiner Ridge–Meeman-Shelby fault (JR-MSF; Odum et al., 

2010). .......................................................................................................................... 6-153 

Figure 6.1.6-3 Maps showing surficial geology and locations of subsurface investigations 

at (a) Meeman-Shelby Forest State Park locality and (b) Union City site (MSF and 

UC on Figure 6.1.6-2). Modified from Cox et al. (2006) and Odum et al. (2010). .......... 6-154 

Figure 6.1.6-4 Figure showing the timing of events along the eastern Reelfoot rift margin. 

Modified from Cox (2009). ............................................................................................ 6-155 

Figure 6.1.7-1 Logic tree for the Reelfoot rift–Marianna RLME source ................................. 6-156 

Figure 6.1.7-2 Map showing tectonic features and locations of paleoliquefaction sites in 

the vicinity of Marianna, Arkansas ................................................................................ 6-157 

Figure 6.1.7-3 Map showing liquefaction features near Daytona Beach lineament 

southwest of Marianna, Arkansas ................................................................................. 6-158 

Figure 6.1.8-1 Logic tree for the Commerce Fault Zone RLME source................................. 6-159

Figure 6.1.8-2 Map showing tectonic features, seismicity, and paleoseismic localities 

along the Commerce Fault Zone RLME source............................................................ 6-160

Figure 6.1.8-3 Location of the Commerce geophysical lineament and Commerce Fault 

Zone RLME source relative to the (a) regional magnetic anomaly map and (b) 

regional gravity anomaly map....................................................................................... 6-161

Figure 6.1.8-4 Space-time diagram showing constraints on the location and timing of late 

Pleistocene and Holocene paleoearthquakes that may be associated with the 

Commerce Fault Zone RLME source ........................................................................... 6-162 

Figure 6.1.9-1 Logic tree for the Wabash Valley RLME source ............................................ 6-163 

Figure 6.1.9-2 Map showing seismicity, subsurface structural features, paleoearthquake 

energy centers, and postulated neotectonic deformation in the Wabash Valley 

region of southern Illinois and southern Indiana .......................................................... 6-164 

Figure 6.1.9-3 Wabash Valley RLME source relative to (a) magnetic anomaly, and (b) 

residual isostatic gravity data ...................................................................................... 6-165 

Figure 6.2-1 Map showing the two Mmax zones for the “narrow” interpretation of the 

Mesozoic-and-younger extended zone......................................................................... 6-166 

Figure 6.2-2 Map showing the two Mmax zones for the “wide” interpretation of the 

Mesozoic-and-younger extended zone......................................................................... 6-167 

Figure 6.3.1-1 Distributions for m max-obs for the Mmax distributed seismicity source zones .. 6-168 

Figure 6.3.2-1 Mmax distributions for the study region treated as a single Mmax zone ........ 6-169 

Figure 6.3.2-2 Mmax distributions for the MESE-N Mmax zone ........................................... 6-170
xxxvi 

Figure 6.3.2-3 Mmax distributions for the MESE-W Mmax zone .......................................... 6-171

Figure 6.3.2-4 Mmax distributions for the NMESE-N Mmax zone......................................... 6-172 

Figure 6.3.2-5 Mmax distributions for the NMESE-W Mmax zone........................................ 6-173 

Figure 6.4.1-1 Mean map of rate and b-value for the study region under the source-zone 

configuration, with no separation of Mesozoic extended and non-extended; Case A 

magnitude weights ....................................................................................................... 6-174 

Figure 6.4.1-2 Mean map of rate and b-value for the study region under the source-zone 

configuration, with no separation of Mesozoic extended and non-extended; Case B 

magnitude weights ....................................................................................................... 6-175 

Figure 6.4.1-3 Mean map of rate and b-value for the study region under the source-zone 

configuration, with no separation of Mesozoic extended and non-extended; Case E 

magnitude weights ....................................................................................................... 6-176 

Figure 6.4.1-4 Mean map of rate and b-value for the study region under the source-zone 

configuration, with separation of Mesozoic extended and non-extended, narrow 

geometry for MESE; Case A magnitude weights .......................................................... 6-177 

Figure 6.4.1-5 Mean map of rate and b-value for the study region under the source-zone 

configuration, with separation of Mesozoic extended and non-extended, narrow 

geometry for MESE; Case B magnitude weights .......................................................... 6-178 

Figure 6.4.1-6 Mean map of rate and b-value for the study region under the source-zone 

configuration, with separation of Mesozoic extended and non-extended, narrow 

geometry for MESE; Case E magnitude weights .......................................................... 6-179 

Figure 6.4.1-7 Mean map of rate and b-value for the study region under the source-zone 

configuration, with separation of Mesozoic extended and non-extended, wide 

geometry for MESE; Case A magnitude weights .......................................................... 6-180

Figure 6.4.1-8 Mean map of rate and b-value for the study region under the source-zone 

configuration, with separation of Mesozoic extended and non-extended, wide 

geometry for MESE; Case B magnitude weights .......................................................... 6-181

Figure 6.4.1-9 Mean map of rate and b-value for the study region under the source-zone 

configuration, with separation of Mesozoic extended and non-extended, wide 

geometry for MESE; Case E magnitude weights .......................................................... 6-182 

Figure 6.4.2-1 Comparison of model-predicted earthquake counts for study region using 

Case A magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-183 

Figure 6.4.2-2 Comparison of model-predicted earthquake counts for study region using 

Case B magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-184 

Figure 6.4.2-3 Comparison of model-predicted earthquake counts for study region using 

Case E magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-185 

Figure 6.4.2-4 Comparison of model-predicted earthquake counts for MESE-N using 

Case A magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-186 

Figure 6.4.2-5 Comparison of model-predicted earthquake counts for MESE-N using 

Case B magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-187 
xxxvii 

Figure 6.4.2-6 Comparison of model-predicted earthquake counts for MESE-N using 

Case E magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-188 

Figure 6.4.2-7 Comparison of model-predicted earthquake counts for MESE-W using 

Case A magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-189 

Figure 6.4.2-8 Comparison of model-predicted earthquake counts for MESE-W using 

Case B magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-190

Figure 6.4.2-9 Comparison of model-predicted earthquake counts for MESE-W using 

Case E magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-191

Figure 6.4.2-10 Comparison of model-predicted earthquake counts for NMESE-N using 

Case A magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-192 

Figure 6.4.2-11 Comparison of model-predicted earthquake counts for NMESE-N using 

Case B magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-193 

Figure 6.4.2-12 Comparison of model-predicted earthquake counts for NMESE-N using 

Case E magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-194 

Figure 6.4.2-13 Comparison of model-predicted earthquake counts for NMESE-W using 

Case A magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-195 

Figure 6.4.2-14 Comparison of model-predicted earthquake counts for NMESE-W using 

Case B magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-196 

Figure 6.4.2-15 Comparison of model-predicted earthquake counts for NMESE-W using 

Case E magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. .................. 6-197 

Figure 7.1-1 Seismotectonic zones shown in the case where the Rough Creek graben is 

not part of the Reelfoot rift (RR) and the Paleozoic Extended Crust is narrow (PEZN) .................................................................................................................................. 7-83

Figure 7.1-2 Seismotectonic zones shown in the case where the Rough Creek graben is 

part of the Reelfoot rift (RR_RCG) and the Paleozoic Extended Crust is narrow 

(PEZ-N).......................................................................................................................... 7-84

Figure 7.1-3 Seismotectonic zones shown in the case where the Rough Creek graben is 

not part of the Reelfoot rift (RR) and the Paleozoic Extended Crust is wide (PEZ-W)..... 7-85

Figure 7.1-4 Seismotectonic zones shown in the case where the Rough Creek graben is 

part of the Reelfoot rift (RR_RCG) and the Paleozoic Extended Crust is wide (PEZW) .................................................................................................................................. 7-86

Figure 7.1-5 Example of comparing seismotectonic zones with magnetic map developed 

as part of the CEUS SSC Project. .................................................................................. 7-87

Figure 7.1-6 Example of comparing seismotectonic zones with isostatic gravity map 

developed as part of the CEUS SSC Project . ............................................................... 7-88
xxxviii 

Figure 7.1-7 Map of seismicity based on the earthquake catalog developed for the CEUS 

SSC Project.................................................................................................................... 7-89

Figure 7.1-8 Map showing example comparison of seismotectonic zones with seismicity. 

Note the non-uniform spatial distribution of seismicity within the zones. Spatial 

smoothing of a- and b-values accounts for these spatial variations. ............................... 7-90

Figure 7.3-1 Logic tree for the seismotectonic zones branch of the master logic tree............. 7-91

Figure 7.3.1-1 Significant earthquakes and paleoseismology of the SLR seismotectonic 

zone ............................................................................................................................... 7-92

Figure 7.3.1-2 Tectonic features of the SLR seismotectonic zone.......................................... 7-93

Figure 7.3.1-3 Magnetic and gravity anomaly maps of the SLR seismotectonic zone............. 7-94

Figure 7.3.2-1 Significant earthquakes and paleoseismic study area in the region of the 

GMH seismotectonic zone.............................................................................................. 7-95

Figure 7.3.2-2 Igneous rocks attributed to the GMH seismotectonic zone.............................. 7-96

Figure 7.3.2-3 Relocated hypocentral depths and crustal depth of the GMH 

seismotectonic zone....................................................................................................... 7-97

Figure 7.3.2-4 Magnetic and gravity anomaly maps of the GMH seismotectonic zone .......... 7-98

Figure 7.3.3-1 Seismicity of the NAP seismotectonic zone..................................................... 7-99

Figure 7.3.3-2 Magnetic and gravity anomaly maps of the NAP seismotectonic zone .......... 7-100

Figure 7.3.4-1 Seismicity and tectonic features of the PEZ seismotectonic zone ................. 7-101

Figure 7.3.4-2 Magnetic and gravity anomaly maps of the PEZ seismotectonic zone........... 7-102

Figure 7.3.5-1 Map showing seismicity, subsurface Paleozoic and basement structures, 

and postulated energy centers for prehistoric earthquakes........................................... 7-103

Figure 7.3.5-2 Map showing alternative boundaries for Precambrian (proto-Illinois basin) 

rift basins...................................................................................................................... 7-104

Figure 7.3.5-3 Maps showing the IBEB source zone boundaries, seismicity, and 

prehistoric earthquake centers relative to (a) regional magnetic anomalies and (b) 

regional gravity anomalies............................................................................................ 7-105

Figure 7.3.6-1 Map of seismicity and geomorphic features and faults showing evidence 

for Quaternary neotectonic deformation and reactivation. Inset map shows 

basement structures associated with the Reelfoot rift. ................................................. 7-106

Figure 7.3.6-2 Maps showing geophysical anomalies in the Reelfoot rift region................... 7-107

Figure 7.3.7-1 Mesozoic basins within the ECC-AM zone ................................................... 7-108

Figure 7.3.7-2 Seismicity within the ECC-AM and AHEX zones ........................................... 7-109

Figure 7.3.7-3 Magnetic and gravity data for ECC-AM and AHEX zones ............................. 7-110

Figure 7.3.7-4 Estimated locations of the 1755 M 6.1 Cape Ann earthquake ....................... 7-111

Figure 7.3.8-1 Correlation of interpreted transitional crust with the East Coast magnetic 

anomaly ....................................................................................................................... 7-112

Figure 7.3.9-1 The ECC-GC seismotectonic zone................................................................ 7-113

Figure 7.3.10-1 The GHEX seismotectonic zone.................................................................. 7-114

Figure 7.3.11-1 The OKA seismotectonic zone and regional gravity and magnetic data ...... 7-115

Figure 7.3.12-1 Simplified tectonic map showing the distribution of principal basement 

faults, rifts, and sutures in the Midcontinent.................................................................. 7-116
xxxix 

Figure 7.3.12-2 Maps showing major basement structural features relative to (a) regional 

magnetic anomalies and (b) regional gravity anomalies ............................................... 7-117

Figure 7.3.12-3 Seismic zones and maximum observed earthquakes in the MidC zone ...... 7-118

Figure 7.3.12-4 Alternative MidC source zone configurations............................................... 7-119

Figure 7.4.1-1 (1 of 3) Distributions for mmax−obs for the seismotectonic distributed 

seismicity source zones................................................................................................ 7-120

Figure 7.4.1-1 (2 of 3) Distributions for mmax−obs for the seismotectonic distributed 

seismicity source zones................................................................................................ 7-121

Figure 7.4.1-1 (3 of 3) Distributions for mmax−obs for the seismotectonic distributed 

seismicity source zones................................................................................................ 7-122

Figure 7.4.2-1 Mmax distributions for the AHEX seismotectonic zone.................................. 7-123

Figure 7.4.2-2 Mmax distributions for the ECC_AM seismotectonic zone............................. 7-124

Figure 7.4.2-3 Mmax distributions for the ECC_GC seismotectonic zone............................. 7-125

Figure 7.4.2-4 Mmax distributions for the GHEX seismotectonic zone ................................. 7-126

Figure 7.4.2-5 Mmax distributions for the GMH seismotectonic zone................................... 7-127

Figure 7.4.2-6 Mmax distributions for the IBEB seismotectonic zone ................................... 7-128

Figure 7.4.2-7 Mmax distributions for the MidC-A seismotectonic zone ............................... 7-129

Figure 7.4.2-8 Mmax distributions for the MidC-B seismotectonic zone ............................... 7-130

Figure 7.4.2-9 Mmax distributions for the MidC-C seismotectonic zone ............................... 7-131

Figure 7.4.2-10 Mmax distributions for the MidC-D seismotectonic zone ............................. 7-132

Figure 7.4.2-11 Mmax distributions for the NAP seismotectonic zone .................................. 7-133

Figure 7.4.2-12 Mmax distributions for the OKA seismotectonic zone.................................. 7-134

Figure 7.4.2-13 Mmax distributions for the PEZ_N seismotectonic zone.............................. 7-135

Figure 7.4.2-14 Mmax distributions for the PEZ_W seismotectonic zone ............................. 7-136

Figure 7.4.2-15 Mmax distributions for the RR seismotectonic zone .................................... 7-137

Figure 7.4.2-16 Mmax distributions for the RR_RCG seismotectonic zone .......................... 7-138

Figure 7.4.2-17 Mmax distributions for the SLR seismotectonic zone .................................. 7-139

Figure 7.5.1-1 Mean map of rate and b-value for the study region under the source-zone 

configuration with narrow interpretation of PEZ, Rough Creek Graben associated 

with Midcontinent; Case A magnitude weights.............................................................. 7-140

Figure 7.5.1-2 Mean map of rate and b-value for the study region under the source-zone 

configuration with narrow interpretation of PEZ, Rough Creek Graben associated 

with Midcontinent; Case B magnitude weights.............................................................. 7-141

Figure 7.5.1-3 Mean map of rate and b-value for the study region under the source-zone 

configuration with narrow interpretation of PEZ, Rough Creek Graben associated 

with Midcontinent; Case E magnitude weights.............................................................. 7-142

Figure 7.5.1-4 Mean map of rate and b-value for the study region under the source-zone 

configuration with narrow interpretation of PEZ, Rough Creek graben associated 

with Reelfoot rift; Case A magnitude weights................................................................ 7-143
xl

Figure 7.5.1-5 Mean map of rate and b-value for the study region under the source-zone 

configuration with narrow interpretation of PEZ, Rough Creek graben associated 

with Reelfoot rift; Case B magnitude weights................................................................ 7-144

Figure 7.5.1-6 Mean map of rate and b-value for the study region under the source-zone 

configuration with narrow interpretation of PEZ, Rough Creek graben associated 

with Reelfoot rift; Case E magnitude weights................................................................ 7-145

Figure 7.5.1-7 Mean map of rate and b-value for the study region under the source-zone 

configuration with wide interpretation of PEZ, Rough Creek graben associated with 

Midcontinent; Case A magnitude weights..................................................................... 7-146

Figure 7.5.1-8 Mean map of rate and b-value for the study region under the source-zone 

configuration with wide interpretation of PEZ, Rough Creek Graben associated with 

Midcontinent; Case B magnitude weights..................................................................... 7-147

Figure 7.5.1-9 Mean map of rate and b-value for the study region under the source-zone 

configuration with wide interpretation of PEZ, Rough Creek Graben associated with 

Midcontinent; Case E magnitude weights..................................................................... 7-148

Figure 7.5.1-10 Mean map of rate and b-value for the study region under the sourcezone configuration with wide interpretation of PEZ, Rough Creek graben associated 

with Reelfoot rift; Case A magnitude weights................................................................ 7-149

Figure 7.5.1-11 Mean map of rate and b-value for the study region under the sourcezone configuration with wide interpretation of PEZ, Rough Creek graben associated 

with Reelfoot rift; Case B magnitude weights................................................................ 7-150

Figure 7.5.1-12 Mean map of rate and b-value for the study region under the sourcezone configuration with wide interpretation of PEZ, Rough Creek graben associated 

with Reelfoot rift; Case E magnitude weights................................................................ 7-151

Figure 7.5.2-1 Comparison of model-predicted earthquake counts for AHEX using Case 

A magnitude weights. No earthquake counts are shown because this source zone 

contains no seismicity. . .............................................................................................. 7-152

Figure 7.5.2-2 Comparison of model-predicted earthquake counts for AHEX using Case 

B magnitude weights. No earthquake counts are shown because this source zone 

contains no seismicity.. ................................................................................................ 7-153

Figure 7.5.2-3 Comparison of model-predicted earthquake counts for AHEX using Case 

E magnitude weights. No earthquake counts are shown because this source zone 

contains no seismicity. ................................................................................................. 7-154

Figure 7.5.2-4 Comparison of model-predicted earthquake counts for ECC_AM using 

Case A magnitude weights. The error bars represent the 16%–84% uncertainty 

associated with the data, computed using the Weichert (1980) procedure. ................. 7-155

Figure 7.5.2-5 Comparison of model-predicted earthquake counts for ECC_AM using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-156

Figure 7.5.2-6 Comparison of model-predicted earthquake counts for ECC_AM using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-157

Figure 7.5.2-7 Comparison of model-predicted earthquake counts for ECC_GC using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-158

Figure 7.5.2-8 Comparison of model-predicted earthquake counts for ECC_GC using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-159

Figure 7.5.2-9 Comparison of model-predicted earthquake counts for ECC_GC using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-160
xli

Figure 7.5.2-10 Comparison of model-predicted earthquake counts for GHEX using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-161

Figure 7.5.2-11 Comparison of model-predicted earthquake counts for GHEX using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-162

Figure 7.5.2-12 Comparison of model-predicted earthquake counts for GHEX using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-163

Figure 7.5.2-13 Comparison of model-predicted earthquake counts for GMH using Case 

A magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-164

Figure 7.5.2-14 Comparison of model-predicted earthquake counts for GMH using Case 

B magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-165

Figure 7.5.2-15 Comparison of model-predicted earthquake counts for GMH using Case 

E magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-166

Figure 7.5.2-16 Comparison of model-predicted earthquake counts for IBEB using Case 

A magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-167

Figure 7.5.2-17 Comparison of model-predicted earthquake counts for IBEB using Case 

B magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-168

Figure 7.5.2-18 Comparison of model-predicted earthquake counts for IBEB using Case 

E magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-169

Figure 7.5.2-19 Comparison of model-predicted earthquake counts for MidC-A using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-170

Figure 7.5.2-20 Comparison of model-predicted earthquake counts for MidC-A using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-171

Figure 7.5.2-21 Comparison of model-predicted earthquake counts for MidC-A using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-172

Figure 7.5.2-22 Comparison of model-predicted earthquake counts for MidC–B using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-173

Figure 7.5.2-23 Comparison of model-predicted earthquake counts for MidC-B using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-174

Figure 7.5.2-24 Comparison of model-predicted earthquake counts for MidC–B using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-175

Figure 7.5.2-25 Comparison of model-predicted earthquake counts for MidC–C using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-176

Figure 7.5.2-26 Comparison of model-predicted earthquake counts for MidC–C using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-177

Figure 7.5.2-27 Comparison of model-predicted earthquake counts for MidC–C using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-178

Figure 7.5.2-28 Comparison of model-predicted earthquake counts for MidC–D using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-179

Figure 7.5.2-29 Comparison of model-predicted earthquake counts for MidC–D using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-180

Figure 7.5.2-30 Comparison of model-predicted earthquake counts for MidC–D using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-181

Figure 7.5.2-31 Comparison of model-predicted earthquake counts for NAP using Case 

A magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-182
xlii

Figure 7.5.2-32 Comparison of model-predicted earthquake counts for NAP using Case 

B magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-183

Figure 7.5.2-33 Comparison of model-predicted earthquake counts for NAP using Case 

E magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-184

Figure 7.5.2-34 Comparison of model-predicted earthquake counts for OKA using Case 

A magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-185

Figure 7.5.2-35 Comparison of model-predicted earthquake counts for OKA using Case 

B magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-186

Figure 7.5.2-36 Comparison of model-predicted earthquake counts for OKA using Case 

E magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-187

Figure 7.5.2-37 Comparison of model-predicted earthquake counts for PEZ_N using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-188

Figure 7.5.2-38 Comparison of model-predicted earthquake counts for PEZ_N using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-189

Figure 7.5.2-39 Comparison of model-predicted earthquake counts for PEZ_N using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-190

Figure 7.5.2-40 Comparison of model-predicted earthquake counts for PEZ_W using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-191

Figure 7.5.2-41 Comparison of model-predicted earthquake counts for PEZ_W using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-192

Figure 7.5.2-42 Comparison of model-predicted earthquake counts for PEZ_W using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-193

Figure 7.5.2-43 Comparison of model-predicted earthquake counts for RR using Case A 

magnitude weights. Error bars as in Figure 7.5.2-4. .................................................... 7-194

Figure 7.5.2-44 Comparison of model-predicted earthquake counts for RR using Case B 

magnitude weights. Error bars as in Figure 7.5.2-4. .................................................... 7-195

Figure 7.5.2-45 Comparison of model-predicted earthquake counts for RR using Case E 

magnitude weights. Error bars as in Figure 7.5.2-4. .................................................... 7-196

Figure 7.5.2-46 Comparison of model-predicted earthquake counts for RR_RCG using 

Case A magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-197

Figure 7.5.2-47 Comparison of model-predicted earthquake counts for RR_RCG using 

Case B magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-198

Figure 7.5.2-48 Comparison of model-predicted earthquake counts for RR_RCG using 

Case E magnitude weights. Error bars as in Figure 7.5.2-4. ........................................ 7-199

Figure 7.5.2-49 Comparison of model-predicted earthquake counts for SLR using Case 

A magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-200

Figure 7.5.2-50 Comparison of model-predicted earthquake counts for SLR using Case 

B magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-201

Figure 7.5.2-51 Comparison of model-predicted earthquake counts for SLR using Case 

E magnitude weights. Error bars as in Figure 7.5.2-4. ................................................. 7-202

Figure 8.1-1 Map showing the study area and seven test sites for the CEUS SSC Project .... 8-28

Figure 8.1-2 Mean VS profile for shallow soil site................................................................... 8-29

Figure 8.1-3 Mean VS profile for deep soil site....................................................................... 8-30
xliii

Figure 8.1-4 Mean amplification factors for shallow soil site................................................... 8-31

Figure 8.1-5 Mean amplification factors for deep soil site....................................................... 8-32

Figure 8.2-1a Central Illinois 10 Hz rock hazard: mean and fractile total hazard .................... 8-33

Figure 8.2-1b Central Illinois 1 Hz rock hazard: mean and fractile total hazard ...................... 8-34

Figure 8.2-1c Central Illinois PGA rock hazard: mean and fractile total hazard ...................... 8-35

Figure 8.2-1d Central Illinois 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................... 8-36

Figure 8.2-1e Central Illinois 1 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................... 8-37

Figure 8.2-1f Central Illinois PGA rock hazard: total and contribution by RLME and 

background .................................................................................................................... 8-38

Figure 8.2-1g Central Illinois 10 Hz rock hazard: contribution by background source............. 8-39

Figure 8.2-1h Central Illinois 1 Hz rock hazard: contribution by background source............... 8-40

Figure 8.2-1i Central Illinois PGA rock hazard: contribution by background source................ 8-41

Figure 8.2-1j Central Illinois 10 Hz rock hazard: comparison of three source models............. 8-42

Figure 8.2-1k Central Illinois 1 Hz rock hazard: comparison of three source models.............. 8-43

Figure 8.2-1l Central Illinois PGA rock hazard: comparison of three source models............... 8-44

Figure 8.2-1m Central Illinois 10 Hz shallow soil hazard: total and total and contribution 

by RLME and background .............................................................................................. 8-45

Figure 8.2-1n Central Illinois 1 Hz shallow soil hazard: total and contribution by RLME 

and background.............................................................................................................. 8-46

Figure 8.2-1o Central Illinois PGA shallow soil hazard: total and contribution by RLME 

and background.............................................................................................................. 8-47

Figure 8.2-1p Central Illinois 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-48

Figure 8.2-1q Central Illinois 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-49

Figure 8.2-1r Central Illinois PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-50

Figure 8.2-1s Central Illinois 10 Hz hazard: comparison of three site conditions .................... 8-51

Figure 8.2-1t Central Illinois 1 Hz hazard: comparison of three site conditions....................... 8-52

Figure 8.2-1u Central Illinois PGA hazard: comparison of three site conditions...................... 8-53

Figure 8.2-1v Central Illinois 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ............................................................................................................................. 8-54

Figure 8.2-1w Central Illinois 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ............................................................................................................................. 8-55

Figure 8.2-1x Central Illinois 10 Hz rock hazard: sensitivity to Mmax for source IBEB............ 8-56 

Figure 8.2-1y Central Illinois 1 Hz rock hazard: sensitivity to Mmax for source IBEB.............. 8-57

Figure 8.2-1z Central Illinois 10 Hz rock hazard: sensitivity to smoothing options .................. 8-58

Figure 8.2-1aa Central Illinois 1 Hz rock hazard: sensitivity to smoothing options .................. 8-59

Figure 8.2-1bb Central Illinois 10 Hz rock hazard: sensitivity to eight realizations for 

source IBEB, Case A...................................................................................................... 8-60
xliv

Figure 8.2-1cc Central Illinois 10 Hz rock hazard: sensitivity to eight realizations for 

source IBEB, Case B...................................................................................................... 8-61

Figure 8.2-1dd Central Illinois 10 Hz rock hazard: sensitivity to eight realizations for 

source IBEB, Case E...................................................................................................... 8-62

Figure 8.2-1ee Central Illinois 1 Hz rock hazard: sensitivity to eight realizations for 

source IBEB, Case A...................................................................................................... 8-63

Figure 8.2-1ff Central Illinois 1 Hz rock hazard: sensitivity to eight realizations for source 

IBEB, Case B ................................................................................................................. 8-64

Figure 8.2-1gg Central Illinois 1 Hz rock hazard: sensitivity to eight realizations for 

source IBEB, Case E...................................................................................................... 8-65

Figure 8.2-2a Chattanooga 10 Hz rock hazard: mean and fractile total hazard ...................... 8-66

Figure 8.2-2b Chattanooga 1 Hz rock hazard: mean and fractile total hazard ........................ 8-67

Figure 8.2-2c Chattanooga PGA rock hazard: mean and fractile total hazard ........................ 8-68

Figure 8.2-2d Chattanooga 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................... 8-69

Figure 8.2-2e Chattanooga 1 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................... 8-70

Figure 8.2-2f Chattanooga PGA rock hazard: total and contribution by RLME and 

background .................................................................................................................... 8-71

Figure 8.2-2g Chattanooga 10 Hz rock hazard: contribution by background source............... 8-72

Figure 8.2-2h Chattanooga 1 Hz rock hazard: contribution by background source................. 8-73

Figure 8.2-2i Chattanooga PGA rock hazard: contribution by background source.................. 8-74

Figure 8.2-2j Chattanooga 10 Hz rock hazard: comparison of three source models............... 8-75

Figure 8.2-2k Chattanooga is 1 Hz rock hazard: comparison of three source models ............ 8-76

Figure 8.2-2l Chattanooga PGA rock hazard: comparison of three source models................. 8-77

Figure 8.2-2m Chattanooga 10 Hz shallow soil hazard: total and contribution by RLME 

and background.............................................................................................................. 8-78

Figure 8.2-2n Chattanooga 1 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-79

Figure 8.2-2o Chattanooga PGA shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-80

Figure 8.2-2p Chattanooga 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-81

Figure 8.2-2q Chattanooga 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-82

Figure 8.2-2r Chattanooga PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................... 8-83

Figure 8.2-2s Chattanooga 10 Hz hazard: comparison of three site conditions ...................... 8-84

Figure 8.2-2t Chattanooga 1 Hz hazard: comparison of three site conditions......................... 8-85

Figure 8.2-2u Chattanooga PGA hazard: comparison of three site conditions........................ 8-86

Figure 8.2-2v Chattanooga 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ............................................................................................................................. 8-87
xlv

Figure 8.2-2w Chattanooga 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ............................................................................................................................. 8-88

Figure 8.2-2x Chattanooga 10 Hz rock hazard: sensitivity to Mmax for source PEZ-N ........... 8-89

Figure 8.2-2y Chattanooga 1 Hz rock hazard: sensitivity to Mmax for source PEZ-N ............. 8-90

Figure 8.2-2z Chattanooga 10 Hz rock hazard: sensitivity to smoothing options .................... 8-91

Figure 8.2-2aa Chattanooga 1 Hz rock hazard: sensitivity to smoothing options.................... 8-92

Figure 8.2-2bb Chattanooga 10 Hz rock hazard: sensitivity to eight realizations for 

source PEZ-N, Case A ................................................................................................... 8-93

Figure 8.2-2cc Chattanooga 10 Hz rock hazard: sensitivity to eight realizations for 

source PEZ-N, Case B ................................................................................................... 8-94

Figure 8.2-2dd Chattanooga 10 Hz rock hazard: sensitivity to eight realizations for 

source PEZ-N, Case E ................................................................................................... 8-95

Figure 8.2-2ee Chattanooga 1 Hz rock hazard: sensitivity to eight realizations for source 

PEZ-N, Case A............................................................................................................... 8-96

Figure 8.2-2ff Chattanooga 1 Hz rock hazard: sensitivity to eight realizations for source 

PEZ-N, Case B............................................................................................................... 8-97

Figure 8.2-2gg Chattanooga 1 Hz rock hazard: sensitivity to eight realizations for source 

PEZ-N, Case E............................................................................................................... 8-98

Figure 8.2-3a Houston 10 Hz rock hazard: mean and fractile total hazard ............................. 8-99

Figure 8.2-3b Houston 1 Hz rock hazard: mean and fractile total hazard ............................. 8-100

Figure 8.2-3c Houston PGA rock hazard: mean and fractile total hazard ............................. 8-101

Figure 8.2-3d Houston 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-102

Figure 8.2-3e Houston 1 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-103

Figure 8.2-3f Houston PGA rock hazard: total and contribution by RLME and background .. 8-104

Figure 8.2-3g Houston 10 Hz rock hazard: contribution by background source.................... 8-105

Figure 8.2-3h Houston 1 Hz rock hazard: contribution by background source...................... 8-106

Figure 8.2-3i Houston PGA rock hazard: contribution by background source....................... 8-107

Figure 8.2-3j Houston 10 Hz rock hazard: comparison of three source models.................... 8-108

Figure 8.2-3k Houston is 1 Hz rock hazard: comparison of three source models ................. 8-109

Figure 8.2-3l Houston PGA rock hazard: comparison of three source models...................... 8-110

Figure 8.2-3m Houston 10 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-111

Figure 8.2-3n Houston 1 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-112

Figure 8.2-3o Houston PGA shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-113

Figure 8.2-3p Houston 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-114

Figure 8.2-3q Houston 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-115
xlvi 

Figure 8.2-3r Houston PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-116

Figure 8.2-3s Houston 10 Hz hazard: comparison of three site conditions ........................... 8-117

Figure 8.2-3t Houston 1 Hz hazard: comparison of three site conditions.............................. 8-118

Figure 8.2-3u Houston PGA hazard: comparison of three site conditions............................. 8-119

Figure 8.2-3v Houston 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones .... 8-120

Figure 8.2-3w Houston 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones ..... 8-121

Figure 8.2-3x Houston 10 Hz rock hazard: sensitivity to Mmax for source GHEX................. 8-122

Figure 8.2-3y Houston 1 Hz rock hazard: sensitivity to Mmax for source GHEX................... 8-123

Figure 8.2-3z Houston 10 Hz rock hazard: sensitivity to smoothing options ......................... 8-124

Figure 8.2-3aa Houston 1 Hz rock hazard: sensitivity to smoothing options ......................... 8-125

Figure 8.2-3bb Houston 10 Hz rock hazard: sensitivity to eight realizations for source 

GHEX, Case A ............................................................................................................. 8-126

Figure 8.2-3cc Houston 10 Hz rock hazard: sensitivity to eight realizations for source 

GHEX, Case B ............................................................................................................. 8-127

Figure 8.2-3dd Houston 10 Hz rock hazard: sensitivity to eight realizations for source 

GHEX, Case E ............................................................................................................. 8-128 

Figure 8.2-3ee Houston 1 Hz rock hazard: sensitivity to eight realizations for source 

GHEX, Case A ............................................................................................................. 8-129

Figure 8.2-3ff Houston 1 Hz rock hazard: sensitivity to eight realizations for source 

GHEX, Case B ............................................................................................................. 8-130

Figure 8.2-3gg Houston 1 Hz rock hazard: sensitivity to eight realizations for source 

GHEX, Case E ............................................................................................................. 8-131

Figure 8.2-4a Jackson 10 Hz rock hazard: mean and fractile total hazard............................ 8-132

Figure 8.2-4b Jackson 1 Hz rock hazard: mean and fractile total hazard.............................. 8-133

Figure 8.2-4c Jackson PGA rock hazard: mean and fractile total hazard.............................. 8-134

Figure 8.2-4d Jackson 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-135

Figure 8.2-4e Jackson 1 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-136

Figure 8.2-4f Jackson PGA rock hazard: total and contribution by RLME and background .. 8-137

Figure 8.2-4g Jackson 10 Hz rock hazard: contribution by background source .................... 8-138

Figure 8.2-4h Jackson 1 Hz rock hazard: contribution by background source ...................... 8-139

Figure 8.2-4i Jackson PGA rock hazard: contribution by background source ....................... 8-140

Figure 8.2-4j Jackson 10 Hz rock hazard: comparison of three source models .................... 8-141

Figure 8.2-4k Jackson is 1 Hz rock hazard: comparison of three source models.................. 8-142

Figure 8.2-4l Jackson PGA rock hazard: comparison of three source models...................... 8-143

Figure 8.2-4m Jackson 10 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-144

Figure 8.2-4n Jackson 1 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-145
xlvii

Figure 8.2-4o Jackson PGA shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-146

Figure 8.2-4p Jackson 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-147

Figure 8.2-4q Jackson 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-148

Figure 8.2-4r Jackson PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-149

Figure 8.2-4s Jackson 10 Hz hazard: comparison of three site conditions ........................... 8-150

Figure 8.2-4t Jackson 1 Hz hazard: comparison of three site conditions .............................. 8-151

Figure 8.2-4u Jackson PGA hazard: comparison of three site conditions............................. 8-152

Figure 8.2-4v Jackson 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones .... 8-153

Figure 8.2-4w Jackson 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones ..... 8-154

Figure 8.2-4x Jackson 10 Hz rock hazard: sensitivity to Mmax for source ECC-GC............. 8-155

Figure 8.2-4y Jackson 1 Hz rock hazard: sensitivity to Mmax for source ECC-GC............... 8-156

Figure 8.2-4z Jackson 10 Hz rock hazard: sensitivity to smoothing options ......................... 8-157 

Figure 8.2-4aa Jackson 1 Hz rock hazard: sensitivity to smoothing options ......................... 8-158

Figure 8.2-4bb Jackson 10 Hz rock hazard: sensitivity to eight realizations for source 

ECC-GC, Case A ......................................................................................................... 8-159

Figure 8.2-4cc Jackson 10 Hz rock hazard: sensitivity to eight realizations for source 

ECC-GC, Case B ......................................................................................................... 8-160

Figure 8.2-4dd Jackson 10 Hz rock hazard: sensitivity to eight realizations for source 

ECC-GC, Case E ......................................................................................................... 8-161

Figure 8.2-4ee Jackson 1 Hz rock hazard: sensitivity to eight realizations for source 

ECC-GC, Case A ......................................................................................................... 8-162

Figure 8.2-4ff Jackson 1 Hz rock hazard: sensitivity to eight realizations for source ECCGC, Case B.................................................................................................................. 8-163

Figure 8.2-4gg Jackson 1 Hz rock hazard: sensitivity to eight realizations for source 

ECC-GC, Case E ......................................................................................................... 8-164

Figure 8.2-5a Manchester 10 Hz rock hazard: mean and fractile total hazard ...................... 8-165

Figure 8.2-5b Manchester 1 Hz rock hazard: mean and fractile total hazard ........................ 8-166

Figure 8.2-5c Manchester PGA rock hazard: mean and fractile total hazard ........................ 8-167

Figure 8.2-5d Manchester 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-168

Figure 8.2-5e Manchester 1 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-169

Figure 8.2-5f Manchester PGA rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-170

Figure 8.2-5g Manchester 10 Hz rock hazard: contribution by background source............... 8-171

Figure 8.2-5h Manchester 1 Hz rock hazard: contribution by background source................. 8-172

Figure 8.2-5i Manchester PGA rock hazard: contribution by background source.................. 8-173

Figure 8.2-5j Manchester 10 Hz rock hazard: comparison of three source models............... 8-174
xlviii

Figure 8.2-5k Manchester is 1 Hz rock hazard: comparison of three source models ............ 8-175

Figure 8.2-5l Manchester PGA rock hazard: comparison of three source models ................ 8-176

Figure 8.2-5m Manchester 10 Hz shallow soil hazard: total and contribution by RLME 

and background............................................................................................................ 8-177

Figure 8.2-5n Manchester 1 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-178

Figure 8.2-5o Manchester PGA shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-179

Figure 8.2-5p Manchester 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-180

Figure 8.2-5q Manchester 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-181

Figure 8.2-5r Manchester PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-182

Figure 8.2-5s Manchester 10 Hz hazard: comparison of three site conditions...................... 8-183

Figure 8.2-5t Manchester 1 Hz hazard: comparison of three site conditions......................... 8-184

Figure 8.2-5u Manchester PGA hazard: comparison of three site conditions ....................... 8-185

Figure 8.2-5v Manchester 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ........................................................................................................................... 8-186

Figure 8.2-5w Manchester 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ........................................................................................................................... 8-187

Figure 8.2-5x Manchester 10 Hz rock hazard: sensitivity to Mmax for source NAP.............. 8-188

Figure 8.2-5y Manchester 1 Hz rock hazard: sensitivity to Mmax for source NAP................ 8-189

Figure 8.2-5z Manchester 10 Hz rock hazard: sensitivity to smoothing options.................... 8-190

Figure 8.2-5aa Manchester 1 Hz rock hazard: sensitivity to smoothing options.................... 8-191

Figure 8.2-5bb Manchester 10 Hz rock hazard: sensitivity to eight realizations for source 

NAP, Case A................................................................................................................ 8-192

Figure 8.2-5cc Manchester 10 Hz rock hazard: sensitivity to eight realizations for source

NAP, Case B................................................................................................................ 8-193

Figure 8.2-5dd Manchester 10 Hz rock hazard: sensitivity to eight realizations for source 

NAP, Case E................................................................................................................ 8-194

Figure 8.2-5ee Manchester 1 Hz rock hazard: sensitivity to eight realizations for source 

NAP, Case A................................................................................................................ 8-195

Figure 8.2-5ff Manchester 1 Hz rock hazard: sensitivity to eight realizations for source 

NAP, Case B................................................................................................................ 8-196

Figure 8.2-5gg Manchester 1 Hz rock hazard: sensitivity to eight realizations for source 

NAP, Case E................................................................................................................ 8-197

Figure 8.2-6a Savannah 10 Hz rock hazard: mean and fractile total hazard......................... 8-198

Figure 8.2-6b Savannah 1 Hz rock hazard: mean and fractile total hazard........................... 8-199

Figure 8.2-6c Savannah PGA rock hazard: mean and fractile total hazard........................... 8-200

Figure 8.2-6d Savannah 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-201
xlix

Figure 8.2-6e Savannah 1 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-202

Figure 8.2-6f Savannah PGA rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-203

Figure 8.2-6g Savannah 10 Hz rock hazard: contribution by background source ................. 8-204

Figure 8.2-6h Savannah 1 Hz rock hazard: contribution by background source ................... 8-205

Figure 8.2-6i Savannah PGA rock hazard: contribution by background source .................... 8-206

Figure 8.2-6j Savannah 10 Hz rock hazard: comparison of three source models ................. 8-207

Figure 8.2-6k Savannah is 1 Hz rock hazard: comparison of three source models............... 8-208

Figure 8.2-6l Savannah PGA rock hazard: comparison of three source models ................... 8-209

Figure 8.2-6m Savannah 10 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-210

Figure 8.2-6n Savannah 1 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-211

Figure 8.2-6o Savannah PGA shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-212

Figure 8.2-6p Savannah 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-213

Figure 8.2-6q Savannah 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-214

Figure 8.2-6r Savannah PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-215

Figure 8.2-6s Savannah 10 Hz hazard: comparison of three site conditions ........................ 8-216

Figure 8.2-6t Savannah 1 Hz hazard: comparison of three site conditions ........................... 8-217

Figure 8.2-6u Savannah PGA hazard: comparison of three site conditions .......................... 8-218

Figure 8.2-6v Savannah 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax 

zones ........................................................................................................................... 8-219

Figure 8.2-6w Savannah 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones .. 8-220

Figure 8.2-6x Savannah 10 Hz rock hazard: sensitivity to Mmax for source ECC-AM.......... 8-221

Figure 8.2-6y Savannah 1 Hz rock hazard: sensitivity to Mmax for source ECC-AM............ 8-222

Figure 8.2-6z Savannah 10 Hz rock hazard: sensitivity to smoothing options ...................... 8-223

Figure 8.2-6aa Savannah 1 Hz rock hazard: sensitivity to smoothing options ...................... 8-224

Figure 8.2-6bb Savannah 10 Hz rock hazard: sensitivity to eight realizations for source 

ECC-AM, Case A ......................................................................................................... 8-225

Figure 8.2-6cc Savannah 10 Hz rock hazard: sensitivity to eight realizations for source 

ECC-AM, Case B ......................................................................................................... 8-226

Figure 8.2-6dd Savannah 10 Hz rock hazard: sensitivity to eight realizations for source 

ECC-AM, Case E ......................................................................................................... 8-227

Figure 8.2-6ee Savannah 1 Hz rock hazard: sensitivity to eight realizations for source 

ECC-AM, Case A ......................................................................................................... 8-228

Figure 8.2-6ff Savannah 1 Hz rock hazard: sensitivity to eight realizations for source 

ECC-AM, Case B ......................................................................................................... 8-229
l 

Figure 8.2-6gg Savannah 1 Hz rock hazard: sensitivity to eight realizations for source 

ECC-AM, Case E ......................................................................................................... 8-230

Figure 8.2-7a Topeka 10 Hz rock hazard: mean and fractile total hazard............................. 8-231

Figure 8.2-7b Topeka 1 Hz rock hazard: mean and fractile total hazard............................... 8-232

Figure 8.2-7c Topeka PGA rock hazard: mean and fractile total hazard............................... 8-233

Figure 8.2-7d Topeka 10 Hz rock hazard: total and contribution by RLME and 

background .................................................................................................................. 8-234

Figure 8.2-7e Topeka 1 Hz rock hazard: total and contribution by RLME and background... 8-235

Figure 8.2-7f Topeka PGA rock hazard: total and contribution by RLME and background ... 8-236

Figure 8.2-7g Topeka 10 Hz rock hazard: contribution by background source ..................... 8-237

Figure 8.2-7h Topeka 1 Hz rock hazard: contribution by background source ....................... 8-238

Figure 8.2-7i Topeka PGA rock hazard: contribution by background source ........................ 8-239

Figure 8.2-7j Topeka 10 Hz rock hazard: comparison of three source models ..................... 8-240

Figure 8.2-7k Topeka is 1 Hz rock hazard: comparison of three source models................... 8-241

Figure 8.2-7l Topeka PGA rock hazard: comparison of three source models ....................... 8-242

Figure 8.2-7m Topeka 10 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-243

Figure 8.2-7n Topeka 1 Hz shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-244

Figure 8.2-7o Topeka PGA shallow soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-245

Figure 8.2-7p Topeka 10 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-246

Figure 8.2-7q Topeka 1 Hz deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-247

Figure 8.2-7r Topeka PGA deep soil hazard: total and contribution by RLME and 

background .................................................................................................................. 8-248

Figure 8.2-7s Topeka 10 Hz hazard: comparison of three site conditions............................. 8-249

Figure 8.2-7t Topeka 1 Hz hazard: comparison of three site conditions ............................... 8-250

Figure 8.2-7u Topeka PGA hazard: comparison of three site conditions .............................. 8-251

Figure 8.2-7v Topeka 10 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones ..... 8-252

Figure 8.2-7w Topeka 1 Hz rock hazard: sensitivity to seismotectonic vs. Mmax zones....... 8-253

Figure 8.2-7x Topeka 10 Hz rock hazard: sensitivity to Mmax for source MidC-A ................ 8-254

Figure 8.2-7y Topeka 1 Hz rock hazard: sensitivity to Mmax for source MidC-A .................. 8-255

Figure 8.2-7z Topeka 10 Hz rock hazard: sensitivity to smoothing options........................... 8-256

Figure 8.2-7aa Topeka 1 Hz rock hazard: sensitivity to smoothing options .......................... 8-257

Figure 8.2-7bb Topeka 10 Hz rock hazard: sensitivity to eight realizations for source 

MidC-A, Case A............................................................................................................ 8-258

Figure 8.2-7cc Topeka 10 Hz rock hazard: sensitivity to eight realizations for source 

MidC-A, Case B............................................................................................................ 8-259
li

Figure 8.2-7dd Topeka 10 Hz rock hazard: sensitivity to eight realizations for source 

MidC-A, Case E............................................................................................................ 8-260

Figure 8.2-7ee Topeka 1 Hz rock hazard: sensitivity to eight realizations for source 

MidC-A, Case A............................................................................................................ 8-261

Figure 8.2-7ff Topeka 1 Hz rock hazard: sensitivity to eight realizations for source MidCA, Case B..................................................................................................................... 8-262

Figure 8.2-7gg Topeka 1 Hz rock hazard: sensitivity to eight realizations for source 

MidC-A, Case E............................................................................................................ 8-263

Figure 9.3-1 1 Hz sensitivity to rupture orientation at Savannah for the Charleston 

regional source............................................................................................................... 9-24

Figure 9.3-2 10 Hz sensitivity to rupture orientation at Savannah for the Charleston 

regional source............................................................................................................... 9-25

Figure 9.3-3 1 Hz sensitivity to seismogenic thickness at Manchester for the Charlevoix 

area source .................................................................................................................... 9-26

Figure 9.3-4 10 Hz sensitivity to seismogenic thickness at Manchester for the Charlevoix 

area source .................................................................................................................... 9-27

Figure 9.3-5 1 Hz sensitivity to rupture orientation (dip) at Manchester for the Charlevoix 

area source .................................................................................................................... 9-28

Figure 9.3-6 10 Hz sensitivity to rupture orientation (dip) at Manchester for the 

Charlevoix area source................................................................................................... 9-29

Figure 9.3-7 1 Hz sensitivity to seismogenic thickness at Topeka for the Cheraw fault 

source ............................................................................................................................ 9-30

Figure 9.3-8 10 Hz sensitivity to seismogenic thickness at Topeka for the Cheraw fault 

source ............................................................................................................................ 9-31

Figure 9.3-9 1 Hz sensitivity to rupture orientation (dip) at Topeka for the Cheraw fault 

source ............................................................................................................................ 9-32

Figure 9.3-10 10 Hz sensitivity to rupture orientation at Topeka for the Cheraw fault 

source ............................................................................................................................ 9-33

Figure 9.3-11 1 Hz sensitivity to seismogenic thickness at Jackson for the Commerce 

area source .................................................................................................................... 9-34

Figure 9.3-12 10 Hz sensitivity to seismogenic thickness at Jackson for the Commerce 

area source .................................................................................................................... 9-35

Figure 9.3-13 1 Hz sensitivity to seismogenic thickness at Jackson for the ERM-N area 

source ............................................................................................................................ 9-36

Figure 9.3-14 10 Hz sensitivity to seismogenic thickness at Jackson for the ERM-N area 

source ............................................................................................................................ 9-37

Figure 9.3-15 1 Hz sensitivity to seismogenic thickness at Jackson for the ERM-S area 

source ............................................................................................................................ 9-38

Figure 9.3-16 10 Hz sensitivity to seismogenic thickness at Jackson for the ERM-S area 

source ............................................................................................................................ 9-39

Figure 9.3-17 1 Hz sensitivity to seismogenic thickness at Jackson for the Marianna area 

source ............................................................................................................................ 9-40

Figure 9.3-18 10 Hz sensitivity to seismogenic thickness at Jackson for the Marianna 

area source .................................................................................................................... 9-41
lii

Figure 9.3-19 1 Hz sensitivity to seismogenic thickness at Topeka for the Meers fault 

and OKA area sources ................................................................................................... 9-42

Figure 9.3-20 1 Hz sensitivity to seismogenic thickness at Houston for the Meers fault 

and OKA area sources ................................................................................................... 9-43

Figure 9.3-21 10 Hz sensitivity to seismogenic thickness at Topeka for the Meers fault 

and OKA area sources ................................................................................................... 9-44

Figure 9.3-22 10 Hz sensitivity to seismogenic thickness at Houston for the Meers fault 

and OKA area sources ................................................................................................... 9-45

Figure 9.3-23 1 Hz sensitivity to rupture orientation at Houston for the OKA area source ...... 9-46

Figure 9.3-24 10 Hz sensitivity to rupture orientation at Houston for the OKA area source .... 9-47

Figure 9.3-25 1 Hz sensitivity to rupture orientation (dip) at Topeka for the OKA area 

source ............................................................................................................................ 9-48

Figure 9.3-26 1 Hz sensitivity to rupture orientation (dip) at Houston for the OKA area 

source ............................................................................................................................ 9-49

Figure 9.3-27 10 Hz sensitivity to rupture orientation (dip) at Topeka for the OKA area 

source ............................................................................................................................ 9-50

Figure 9.3-28 10 Hz sensitivity to rupture orientation (dip) at Houston for the OKA area 

source ............................................................................................................................ 9-51

Figure 9.3-29 1 Hz sensitivity to rupture orientation (dip) at Topeka for the Meers fault 

source ............................................................................................................................ 9-52

Figure 9.3-30 1 Hz sensitivity to rupture orientation (dip) at Houston for the Meers fault 

source ............................................................................................................................ 9-53

Figure 9.3-31 10 Hz sensitivity to rupture orientation (dip) at Topeka for the Meers fault 

source ............................................................................................................................ 9-54

Figure 9.3-32 10 Hz sensitivity to rupture orientation (dip) at Houston for the Meers fault 

source ............................................................................................................................ 9-55

Figure 9.3-33 1 Hz sensitivity to seismogenic thickness at Jackson for the NMFS fault 

sources .......................................................................................................................... 9-56

Figure 9.3-34 10 Hz sensitivity to seismogenic thickness at Jackson for the NMFS fault 

sources .......................................................................................................................... 9-57

Figure 9.3-35 1 Hz sensitivity to seismogenic thickness at Central Illinois for the Wabash 

Valley area source.......................................................................................................... 9-58

Figure 9.3-36 10 Hz sensitivity to seismogenic thickness at Central Illinois for the 

Wabash Valley area source............................................................................................ 9-59

Figure 9.3-37 1 Hz sensitivity to rupture orientation (dip) at Central Illinois for the 

Wabash Valley area source............................................................................................ 9-60

Figure 9.3-38 10 Hz sensitivity to rupture orientation (dip) at Central Illinois for the 

Wabash Valley area source............................................................................................ 9-61

Figure 9.3-39 1 Hz sensitivity to fault ruptures vs. point source for the Central Illinois site 

from the Mid C–A background source ............................................................................ 9-62

Figure 9.3-40 10 Hz sensitivity to fault ruptures vs. point source for the Central Illinois 

site from the Mid C–A background source...................................................................... 9-63

Figure 9.4-1 COVMH from EPRI (1989) team sources vs. ground motion amplitude for 

seven test sites: PGA (top), 10 Hz SA (middle), and 1 Hz SA (bottom) .......................... 9-64
liii

Figure 9.4-2 COVMH from EPRI (1989) team sources vs. seismic hazard (i.e., annual 

frequency of exceedance) for seven test sites: PGA (top), 10 Hz SA (middle), and 1 

9-Hz SA (bottom)............................................................................................................ 9-65

Figure 9.4-3 COVMH from seismic source experts (PEGASOS project) vs. amplitude 

(top) and annual frequency (bottom)............................................................................... 9-66

Figure 9.4-4 COVK and COVMH from Charleston alternatives for PGA, plotted vs. PGA 

amplitude (top) and hazard (bottom). COVMH is the total COV of mean hazard; see 

Table 9.4-2 for other labels for curves. ........................................................................... 9-67

Figure 9.4-5 COVK and COVMH from Charleston alternatives for 10 Hz, plotted vs. 10 Hz 

amplitude (top) and hazard (bottom). COVMH is the total COV of mean hazard; see 

Table 9.4-2 for other labels for curves. ........................................................................... 9-68

Figure 9.4-6 COVK and COVMH from Charleston alternatives for 1 Hz, plotted vs. 1 Hz 

amplitude (top) and hazard (bottom). COVMH is the total COV of mean hazard; see 

Table 9.4-2 for other labels for curves.. .......................................................................... 9-69

Figure 9.4-7 COVK and COVMH of total hazard from New Madrid for 1 Hz, plotted vs. 1 

Hz amplitude (top) and hazard (bottom). COVMH is the total COV; see the text for 

other labels for curves. ................................................................................................... 9-70

Figure 9.4-8 PGA hazard curves for Manchester test site ...................................................... 9-71

Figure 9.4-9 COVMH of PGA hazard at Manchester site from ground motion equation 

vs. PGA.......................................................................................................................... 9-72

Figure 9.4-10 COV of PGA hazard at Manchester site from ground motion equation vs. 

hazard ............................................................................................................................ 9-73

Figure 9.4-11 COV of 10 Hz hazard at Manchester site from ground motion equations 

vs. hazard....................................................................................................................... 9-74

Figure 9.4-12 COV of 1 Hz hazard at Manchester site from ground motion equations vs. 

hazard ............................................................................................................................ 9-75

Figure 9.4-13 1 Hz spectral acceleration hazard curves for Manchester test site ................... 9-76

Figure 9.4-14 COVMH of PGA hazard at Chattanooga from ground motion equation vs. 

hazard ............................................................................................................................ 9-77

Figure 9.4-15 COVMH of 10 Hz hazard at Chattanooga from ground motion equation vs. 

hazard ............................................................................................................................ 9-78

Figure 9.4-16 COVMH of 1 Hz hazard at Chattanooga site from ground motion equation 

vs. hazard....................................................................................................................... 9-79

Figure 9.4-17 PGA hazard curves for Savannah test site....................................................... 9-80

Figure 9.4-18 COVMH of PGA hazard at Savannah site from ground motion equations 

vs. hazard....................................................................................................................... 9-81

Figure 9.4-19 COVMH of 10 Hz hazard at Savannah site from ground motion equations 

vs. hazard....................................................................................................................... 9-82

Figure 9.4-20 COVMH of 1 Hz hazard at Savannah site from ground motion equations 

vs. hazard....................................................................................................................... 9-83

Figure 9.4-21 PGA hazard curves for Columbia site .............................................................. 9-84

Figure 9.4-22 COVMH of PGA hazard at Columbia from ground motion equations vs. 

hazard ............................................................................................................................ 9-85
liv

Figure 9.4-23 COVMH of 10 Hz hazard at Columbia from ground motion equations vs. 

hazard ............................................................................................................................ 9-86

Figure 9.4-24 COVMH of 1 Hz hazard at Columbia from ground motion equations vs. 

hazard ............................................................................................................................ 9-87

Figure 9.4-25 COVMH of PGA hazard at Chattanooga (New Madrid only) vs. hazard ........... 9-88

Figure 9.4-26 COVMH of 10 Hz hazard at Chattanooga (New Madrid only) vs. hazard.......... 9-89

Figure 9.4-27 COVMH of 1 Hz hazard at Chattanooga (New Madrid only) vs. hazard............ 9-90

Figure 9.4-28 COVMH for PGA and 1 Hz SA vs. ground motion amplitude resulting from 

alternative ground motion experts, PEGASOS project.................................................... 9-91

Figure 9.4-29 COVMH for PGA and 1 Hz SA vs. mean hazard from alternative ground 

motion experts, PEGASOS project................................................................................. 9-92

Figure 9.4-30 COVHAZ from ground motion equations vs. mean hazard for Chattanooga..... 9-93

Figure 9.4-31 COVMH from ground motion equations vs. mean hazard for Central Illinois .... 9-94

Figure 9.4-32 COVMH from soil experts vs. PGA and 1 Hz SA, PEGASOS project ............... 9-95

Figure 9.4-33 COVMH from soil experts vs. mean hazard for PGA and 1 Hz SA, 

PEGASOS project.......................................................................................................... 9-96

Figure 9.4-34 COVMH resulting from site response models vs. mean hazard for four 

sites, 1 Hz (top) and 10 Hz (bottom)............................................................................... 9-97

Figure 11-1 Geologic time scale (Walker and Geissman, 2009)...........................................11-10

Figure A-1 GEBCO elevation data for the CEUS study area (BODC, 2009). ........................ A-22

Figure A-2 CEUS SSC independent earthquake catalog....................................................... A-24

Figure A-3 Bedrock geology and extended crust after Kanter (1994) .................................... A-26

Figure A-4 Crustal provinces after Rohs and Van Schmus (2007) ........................................ A-28 

Figure A-5 Geologic map of North America........................................................................... A-31 

Figure A-6 Locations of geologic cross sections in the CEUS ............................................... A-33

Figure A-7 Precambrian crustal boundary after Van Schmus et al. (1996) ............................ A-35

Figure A-8a Precambrian geology and features after Reed (1993)........................................ A-37

Figure A-8b Explanation of Precambrian geology and features after Reed (1993) ................ A-38

Figure A-9 Precambrian provinces after Van Schmus et al. (2007) ....................................... A-40

Figure A-10 Precambrian units after Whitmeyer and Karlstrom (2007).................................. A-42

Figure A-11 Surficial materials in the conterminous United States after Soller et al. 

(2009)............................................................................................................................ A-44

Figure A-12 Basement and sediment thickness in the USGS Crustal Database for North 

America. Symbol size represents overlying sediment thickness (km); symbol color 

represents basement thickness (km)............................................................................. A-46

Figure A-13 Top of basement P-wave seismic velocity in the USGS Crustal Database for 

North America ............................................................................................................... A-47

Figure A-14 Sediment thickness for North America and neighboring regions ........................ A-49

Figure A-15 Physiographic divisions of the conterminous United States after Fenneman 

and Johnson (1946) ...................................................................................................... A-51

Figure A-16 CEUS SSC free-air gravity anomaly grid. Shaded relief with 315-degree 

azimuth and 30-degree inclination applied..................................................................... A-54
lv

Figure A-17 CEUS SSC free-air gravity anomaly grid. Shaded relief with 180-degree 

azimuth and 30-degree inclination applied..................................................................... A-55

Figure A-18 CEUS SSC complete Bouguer gravity anomaly grid with free-air gravity 

anomaly in marine areas. Shaded relief with 315-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-56

Figure A-19 CEUS SSC complete Bouguer gravity anomaly grid with free-air gravity 

anomaly in marine areas. Shaded relief with 180-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-57

Figure A-20 CEUS SSC residual isostatic gravity anomaly grid. Shaded relief with 315-

degree azimuth and 30-degree inclination applied......................................................... A-58

Figure A-21 CEUS SSC residual isostatic gravity anomaly grid Shaded relief with 180-

degree azimuth and 30-degree inclination applied......................................................... A-59

Figure A-22 CEUS SSC regional isostatic gravity anomaly grid ............................................ A-60

Figure A-23 CEUS SSC first vertical derivative of residual isostatic gravity anomaly grid...... A-61

Figure A-24 CEUS SSC first vertical derivative of Bouguer gravity anomaly grid with 

free-air anomaly in marine areas ................................................................................... A-62

Figure A-25 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

low pass filtered at 240 km ............................................................................................ A-63

Figure A-26 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

high pass filtered at 240 km. Shaded relief with 315-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-64

Figure A-27 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

high pass filtered at 240 km. Shaded relief with 180-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-65

Figure A-28 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

high pass filtered at 120 km. Shaded relief with 315-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-66

Figure A-29 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

high pass filtered at 120 km. Shaded relief with 180-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-67

Figure A-30 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

upward continued to 40 km ........................................................................................... A-68

Figure A-31 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

minus the complete Bouguer (with marine free-air) gravity anomaly upward 

continued to 40 km. Shaded relief with 315-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-69

Figure A-32 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

minus the complete Bouguer (with marine free-air) gravity anomaly upward 

continued to 40 km. Shaded relief with 180-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-70

Figure A-33 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

upward continued to 100 km.......................................................................................... A-71

Figure A-34 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

minus the complete Bouguer (with marine free-air) gravity anomaly anomaly 
lvi 

upward continued to 100 km. Shaded relief with 315-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-72

Figure A-35 CEUS SSC complete Bouguer (with marine free-air) gravity anomaly grid 

minus the complete Bouguer (with marine free-air) gravity anomaly upward 

continued to 100 km. Shaded relief with 180-degree azimuth and 30-degree 

inclination applied.......................................................................................................... A-73

Figure A-36 CEUS SSC horizontal derivative of residual isostatic gravity anomaly grid ........ A-74

Figure A-37 CEUS SSC horizontal derivative of first vertical derivative of residual 

isostatic gravity anomaly grid......................................................................................... A-75

Figure A-38 Corrected heat flow values from the SMU Geothermal Laboratory Regional 

Heat Flow Database (2008)........................................................................................... A-77

Figure A-39 CEUS SSC total intensity magnetic anomaly grid (Ravat et al., 2009). 

Shaded relief with 315-degree azimuth and 30-degree inclination applied..................... A-80

Figure A-40 CEUS SSC total intensity magnetic anomaly grid (Ravat et al., 2009). 

Shaded relief with 180-degree azimuth and 30-degree inclination applied..................... A-81

Figure A-41 CEUS SSC differentially reduced to pole magnetic anomaly grid (Ravat, 

2009). Shaded relief with 315-degree azimuth and 30-degree inclination applied.......... A-82

Figure A-42 CEUS SSC differentially reduced to pole magnetic anomaly grid (Ravat, 

2009). Shaded relief with 180-degree azimuth and 30-degree inclination applied.......... A-83

Figure A-43 CEUS SSC tilt derivative of differentially reduced to pole magnetic anomaly 

grid (degrees) (Ravat, 2009).......................................................................................... A-84

Figure A-44 CEUS SSC horizontal derivative of tilt derivative of differentially reduced to 

pole magnetic anomaly grid (radians) (Ravat, 2009) ..................................................... A-85

Figure A-45 CEUS SSC tilt derivative of differentially reduced to pole magnetic anomaly 

grid (Ravat, 2009).......................................................................................................... A-86

Figure A-46 CEUS SSC amplitude of analytic signal magnetic anomaly grid (Ravat, 

2009)............................................................................................................................. A-87

Figure A-47 CEUS SSC paleoliquefaction database ............................................................. A-89

Figure A-48 CEUS SSC compilation of seismic reflection and seismic refraction lines.......... A-91

Figure A-49 USGS National Seismic Hazard Maps (Petersen et al., 2008)........................... A-93

Figure A-50 USGS NSHM ground motion hazard at spectral acceleration of 1 hz with 2% 

probability of exceedance in 50 years (Petersen et al., 2008)........................................ A-94

Figure A-51 USGS NSHM ground motion hazard at spectral acceleration of 1 hz with 5% 

probability of exceedance in 50 years (Petersen et al., 2008)........................................ A-95

Figure A-52 USGS NSHM ground motion hazard at spectral acceleration of 1 hz with 

10% probability of exceedance in 50 years (Petersen et al., 2008)................................ A-96

Figure A-53 USGS NSHM ground motion hazard at spectral acceleration of 3 hz with 2% 

probability of exceedance in 50 years (Petersen et al., 2008)........................................ A-97

Figure A-54 USGS NSHM ground motion hazard at spectral acceleration of 3 hz with 5% 

probability of exceedance in 50 years (Petersen et al., 2008)........................................ A-98

Figure A-55 USGS NSHM ground motion hazard at spectral acceleration of 3 hz with 

10% probability of exceedance in 50 years (Petersen et al., 2008)................................ A-99

Figure A-56 USGS NSHM ground motion hazard at spectral acceleration of 5 hz with 2% 

probability of exceedance in 50 years (Petersen et al., 2008)...................................... A-100
lvii

Figure A-57 USGS NSHM ground motion hazard at spectral acceleration of 5 hz with 5% 

probability of exceedance in 50 years (Petersen et al., 2008)...................................... A-101

Figure A-58 USGS NSHM ground motion hazard at spectral acceleration of 5 hz with 

10% probability of exceedance in 50 years (Petersen et al., 2008).............................. A-102

Figure A-59 USGS NSHM peak ground acceleration with 2% probability of exceedance 

in 50 years (Petersen et al., 2008)............................................................................... A-103

Figure A-60 USGS NSHM peak ground acceleration with 5% probability of exceedance 

in 50 years (Petersen et al., 2008)............................................................................... A-104

Figure A-61 USGS NSHM peak ground acceleration with 10% probability of exceedance 

in 50 years (Petersen et al., 2008)............................................................................... A-105

Figure A-62 Deformation of the North American Plate interior using GPS station data 

(Calais et al., 2006) ..................................................................................................... A-107

Figure A-63 Stress measurement update for the CEUS (Hurd, 2010) ................................. A-110

Figure A-64 CEUS SSC Project study area boundary......................................................... A-112

Figure A-65 USGS Quaternary fault and fold database (USGS, 2006)................................ A-114

Figure A-66 Quaternary features compilation for the CEUS (Crone and Wheeler, 2000; 

Wheeler, 2005; USGS, 2010)...................................................................................... A-116

Figure A-67 CEUS Mesozoic rift basins after Benson (1992) .............................................. A-118

Figure A-68 CEUS Mesozoic rift basins after Dennis et al. (2004)....................................... A-120

Figure A-69 CEUS Mesozoic rift basins after Schlische (1993)........................................... A-122

Figure A-70 CEUS Mesozoic rift basins after Withjack et al. (1998) .................................... A-124

Figure A-71 RLME zones for the CEUS.............................................................................. A-126

Figure A-72 Mesozoic and non-Mesozoic zones for the CEUS, wide interpretation ............ A-128

Figure A-73 Mesozoic and non-Mesozoic zones for the CEUS, narrow interpretation......... A-129

Figure A-74 CEUS seismotectonic zones model A.............................................................. A-130

Figure A-75 CEUS seismotectonic zones model B.............................................................. A-131

Figure A-76 CEUS seismotectonic zones model C ............................................................. A-132

Figure A-77 CEUS seismotectonic zones model D ............................................................. A-133

Figure E-1 Map of CEUS showing locations of regional data sets included in the CEUS 

SSC Project paleoliquefaction database, including New Madrid seismic zone and 

surrounding region; Marianna, Arkansas, area; St. Louis region; Wabash Valley 

seismic zone and surrounding region; Arkansas-Louisiana-Mississippi region; 

Charleston seismic zone; Atlantic Coastal region and the Central Virginia seismic 

zone; Newburyport, Massachusetts, and surrounding region; and Charlevoix 

seismic zone and surrounding region. ........................................................................... E-68 

Figure E-2 Diagram illustrating size parameters of liquefaction features, including sand 

blow thickness, width, and length; dike width; and sill thickness, as well as some of 

the diagnostic characteristics of these features. ............................................................ E-69

Figure E-3 Diagram illustrating sampling strategy for dating of liquefaction features as 

well as age data, such as 14C maximum and 14C minimum, used to calculate 

preferred age estimates and related uncertainties of liquefaction features..................... E-70

Figure E-4 GIS map of New Madrid seismic zone and surrounding region showing 

portions of rivers searched for earthquake-induced liquefaction features by M. 
lviii

Tuttle, R. Van Arsdale, and J. Vaughn and collaborators (see explanation); 

information contributed for this report. Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983.............................................................. E-71

Figure E-5 GIS map of New Madrid seismic zone and surrounding region showing 

locations of liquefaction features for which there are and are not radiocarbon data. 

Map projection is USA Contiguous Albers Equal Area Conic, North America Datum 

1983.............................................................................................................................. E-72

Figure E-6 GIS map of New Madrid seismic zone and surrounding region showing 

locations of liquefaction features that are thought to be historical or prehistoric in 

age or whose ages are poorly constrained. Map projection is USA Contiguous 

Albers Equal Area Conic, North America Datum 1983................................................... E-73

Figure E-7 GIS map of New Madrid seismic zone and surrounding region showing 

preferred age estimates of liquefaction features; features whose ages are poorly 

constrained are excluded. Map projection is USA Contiguous Albers Equal Area 

Conic, North America Datum 1983. ............................................................................... E-74

Figure E-8 GIS map of New Madrid seismic zone and surrounding region showing 

measured thicknesses of sand blows. Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983.............................................................. E-75

Figure E-9 GIS map of New Madrid seismic zone and surrounding region showing 

preferred age estimates and measured thicknesses of sand blows. Map projection 

is USA Contiguous Albers Equal Area Conic, North America Datum 1983. ................... E-76

Figure E-10 GIS map of New Madrid seismic zone and surrounding region showing 

measured widths of sand dikes. Map projection is USA Contiguous Albers Equal 

Area Conic, North America Datum 1983. ....................................................................... E-77

Figure E-11 GIS map of New Madrid seismic zone and surrounding region showing 

preferred age estimates and measured widths of sand dikes. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983................................ E-78

Figure E-12 GIS map of New Madrid seismic zone and surrounding region illustrating 

preferred age estimates and measured thicknesses of sand blows as well as 

preferred age estimates and measured widths of sand dikes for sites where sand 

blows do not occur. Map projection is USA Contiguous Albers Equal Area Conic, 

North America Datum 1983. .......................................................................................... E-79

Figure E-13 GIS map of Marianna, Arkansas, area showing seismicity and locations of 

paleoliquefaction features relative to mapped traces of Eastern Reelfoot rift margin 

fault, White River fault zone, Big Creek fault zone, Marianna escarpment, and 

Daytona Beach lineament. Map projection is USA Contiguous Albers Equal Area 

Conic, North America Datum 1983. ............................................................................... E-80

Figure E-14 (A) Trench log and (B) ground-penetrating radar profile, showing vertical

sections of sand blows and sand dikes at Daytona Beach SE2 site along the 

Daytona Beach lineament southwest of Marianna, Arkansas. Vertical scale of GPR 

profile is exaggerated (modified from Al-Shukri et al., 2009).......................................... E-81

Figure E-15 GIS map of Marianna, Arkansas, area showing locations of liquefaction 

features for which there are and are not radiocarbon data. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983................................ E-82

Figure E-16 GIS map of Marianna, Arkansas, area showing locations of liquefaction 

features that are thought to be historical or prehistoric in age or whose ages are 

poorly constrained. To date, no liquefaction features thought to have formed during 
lix

1811-1812 earthquakes have been found in area. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983................................ E-83

Figure E-17 GIS map of Marianna, Arkansas, area showing preferred age estimates of 

liquefaction features; features whose ages are poorly constrained are excluded. 

Map projection is USA Contiguous Albers Equal Area Conic, North America Datum 

1983.............................................................................................................................. E-84

Figure E-18 GIS map of Marianna, Arkansas, area showing measured thicknesses of 

sand blows. Map projection is USA Contiguous Albers Equal Area Conic, North 

America Datum 1983..................................................................................................... E-85 

Figure E-19 GIS map of Marianna, Arkansas, area showing preferred age estimates and 

measured thicknesses of sand blows. Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983.............................................................. E-86

Figure E-20 GIS map of Marianna, Arkansas, area showing measured widths of sand 

dikes. Map projection is USA Contiguous Albers Equal Area Conic, North America 

Datum 1983................................................................................................................... E-87 

Figure E-21 GIS map of Marianna, Arkansas, area showing preferred age estimates and 

measured widths of sand dikes. Map projection is USA Contiguous Albers Equal 

Area Conic, North America Datum 1983........................................................................ E-88

Figure E-22 GIS map of St. Louis, Missouri, region showing seismicity and portions of 

rivers searched for earthquake-induced liquefaction features by Tuttle and 

collaborators; information contributed for this report. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983................................ E-89

Figure E-23 GIS map of St. Louis, Missouri, region showing locations of liquefaction 

features, including several soft-sediment deformation structures, for which there are 

and are not radiocarbon data. Map projection is USA Contiguous Albers Equal Area 

Conic, North America Datum 1983. ............................................................................... E-90

Figure E-24 GIS map of St. Louis, Missouri, region showing locations of liquefaction 

features that are thought to be historical or prehistoric in age or whose ages are 

poorly constrained. Map projection is USA Contiguous Albers Equal Area Conic, 

North America Datum 1983. .......................................................................................... E-91

Figure E-25 GIS map of St. Louis, Missouri, region showing preferred age estimates of 

liquefaction features; features whose ages are poorly constrained, including several 

that are prehistoric in age, are not shown. Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983.............................................................. E-92

Figure E-26 GIS map of St. Louis, Missouri, region showing measured thicknesses of 

sand blows at similar scale as used in Figure E-8 of sand blows in New Madrid 

seismic zone. Note that few sand blows have been found in St. Louis region. Map 

projection is USA Contiguous Albers Equal Area Conic, North America Datum 

1983.............................................................................................................................. E-93

Figure E-27 GIS map of St. Louis, Missouri, region showing preferred age estimates and 

measured thicknesses of sand blows. Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983.............................................................. E-94

Figure E-28 GIS map of St. Louis, Missouri, region showing measured widths of sand 

dikes at similar scale as that used in Figure E-10 for sand dikes in New Madrid 

seismic zone. Map projection is USA Contiguous Albers Equal Area Conic, North 

America Datum 1983..................................................................................................... E-95
lx

Figure E-29 GIS map of St. Louis, Missouri, region showing measured widths of sand 

dikes at similar scale as that used in Figures E-42 and E-48 for sand dikes in the 

Newburyport and Charlevoix regions, respectively. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983................................ E-96

Figure E-30 GIS map of St. Louis, Missouri, region showing preferred age estimates and 

measured widths of sand dikes. Map projection is USA Contiguous Albers Equal 

Area Conic, North America Datum 1983........................................................................ E-97

Figure E-31 GIS map of Wabash Valley seismic zone and surrounding region showing 

portions of rivers searched for earthquake-induced liquefaction features (digitized 

from McNulty and Obermeier, 1999). Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983.............................................................. E-98

Figure E-32 GIS map of Wabash Valley seismic zone and surrounding region showing 

measured widths of sand dikes at similar scale as that used in Figures E-10 and E11 for sand dikes in New Madrid seismic zone. Map projection is USA Contiguous 

Albers Equal Area Conic, North America Datum 1983................................................... E-99

Figure E-33 GIS map of Wabash Valley region of Indiana and Illinois showing preferred 

age estimates and paleoearthquake interpretation. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983.............................. E-100

Figure E-34 GIS map of Arkansas-Louisiana-Mississippi (ALM) region showing 

paleoliquefaction study locations. Map projection is USA Contiguous Albers Equal 

Area Conic, North America Datum 1983...................................................................... E-101

Figure E-35 GIS map of Charleston, South Carolina, region showing locations of 

paleoliquefaction features for which there are and are not radiocarbon dates. Map 

projection is USA Contiguous Albers Equal Area Conic, North America Datum 

1983............................................................................................................................ E-102

Figure E-36 GIS map of Charleston, South Carolina, region showing locations of 

historical and prehistoric liquefaction features. Map projection is USA Contiguous 

Albers Equal Area Conic, North America Datum 1983................................................. E-103

Figure E-37 Map of Atlantic coast region showing areas searched for paleoliquefaction 

features by Gelinas et al. (1998) and Amick, Gelinas, et al. (1990a). Rectangles 

indicate 7.5-minute quadrangles in which sites were investigated for presence of 

paleoliquefaction features. The number of sites investigated is shown within that 

quadrangle, if known. Orange and yellow indicate quadrangles in which 

paleoliquefaction features were recognized................................................................. E-104

Figure E-38 Map of Central Virginia seismic zone region showing portions of rivers 

searched for earthquake-induced liquefaction features by Obermeier and McNulty 

(1998).......................................................................................................................... E-105

Figure E-39 GIS map of Newburyport, Massachusetts, and surrounding region showing 

seismicity and portions of rivers searched for earthquake-induced liquefaction 

features (Gelinas et al., 1998; Tuttle, 2007, 2009). Solid black line crossing map 

represents Massachusetts–New Hampshire border. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983.............................. E-106

Figure E-40 GIS map of Newburyport, Massachusetts, and surrounding region showing 

locations of liquefaction features for which there are and are not radiocarbon dates. 

Map projection is USA Contiguous Albers Equal Area Conic, North America Datum 

1983............................................................................................................................ E-107
lxi

Figure E-41 GIS map of Newburyport, Massachusetts, and surrounding region showing 

locations of liquefaction features that are thought to be historical or prehistoric in 

age or whose ages are poorly constrained. Map projection is USA Contiguous 

Albers Equal Area Conic, North America Datum 1983................................................. E-108

Figure E-42 GIS map of Newburyport, Massachusetts, and surrounding region showing 

measured widths of sand dikes. Map projection is USA Contiguous Albers Equal 

Area Conic, North America Datum 1983...................................................................... E-109

Figure E-43 GIS map of Newburyport, Massachusetts, and surrounding region showing 

preferred age estimates and measured widths of sand dikes. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983.............................. E-110

Figure E-44 Map of Charlevoix seismic zone and adjacent St. Lawrence Lowlands 

showing mapped faults and portions of rivers along which reconnaissance and 

searches for earthquake-induced liquefaction features were performed. Charlevoix 

seismic zone is defined by concentration of earthquakes and locations of historical 

earthquakes northeast of Quebec City. Devonian impact structure in vicinity of 

Charlevoix seismic zone is outlined by black dashed line. Taconic thrust faults are 

indicated by solid black lines with sawteeth on upper plate; Iapetan rift faults are 

shown by solid black lines with hachure marks on downthrown side (modified from 

Tuttle and Atkinson, 2010)........................................................................................... E-111

Figure E-45 GIS map of Charlevoix seismic zone and surrounding region showing 

locations of liquefaction features, including several soft-sediment deformation 

structures, for which there are and are not radiocarbon data. Note the location of 

1988 M 5.9 Saguenay earthquake northwest of the Charlevoix seismic zone. Map 

projection is USA Contiguous Albers Equal Area Conic, North America Datum 

1983............................................................................................................................ E-112

Figure E-46 GIS map of Charlevoix seismic zone and surrounding region showing 

locations of liquefaction features that are modern, historical, or prehistoric in age, or 

whose ages are poorly constrained. Map projection is USA Contiguous Albers 

Equal Area Conic, North America Datum 1983............................................................ E-113

Figure E-47 GIS map of Charlevoix seismic zone and surrounding region showing 

preferred age estimates of liquefaction features; features whose ages are poorly 

constrained are excluded. Map projection is USA Contiguous Albers Equal Area 

Conic, North America Datum 1983. ............................................................................. E-114

Figure E-48 GIS map of Charlevoix seismic zone and surrounding region showing 

measured widths of sand dikes. Map projection is USA Contiguous Albers Equal 

Area Conic, North America Datum 1983...................................................................... E-115

Figure E-49 GIS map of Charlevoix seismic zone and surrounding region showing 

preferred age estimates and measured widths of sand dikes. Map projection is USA 

Contiguous Albers Equal Area Conic, North America Datum 1983.............................. E-116

Figure E-50 Photograph of moderate-sized sand blow (12 m long, 7 m wide, and 14 cm 

thick) that formed about 40 km from epicenter of 2001 M 7.7 Bhuj, India, 

earthquake (from Tuttle, Hengesh, et al., 2002), combined with schematic vertical 

section illustrating structural and stratigraphic relations of sand blow, sand dike, and 

source layer (modified from Sims and Garvin, 1995). .................................................. E-117

Figure E-51 Tree trunks buried and killed by sand blows, vented during 1811-1812 New 

Madrid earthquakes (from Fuller, 1912)....................................................................... E-118
lxii

Figure E-52 Large sand-blow crater that formed during 2002 M 7.7 Bhuj, India, 

earthquake. Backpack for scale. Photograph: M. Tuttle (2001).................................... E-119

Figure E-53 Sand-blow crater that formed during 1886 Charleston, South Carolina, 

earthquake. Photograph: J.K. Hillers (from USGS Photograph Library)....................... E-120

Figure E-54 Photograph of sand blow and related sand dikes exposed in trench wall and 

floor in New Madrid seismic zone. Buried soil horizon is displaced downward 

approximately 1 m across two dikes. Clasts of soil horizon occur within dikes and 

overlying sand blow. Degree of soil development above and within sand blow 

suggests that it is at least several hundred years old and formed prior to 1811-1812 

New Madrid earthquakes. Organic sample (location marked by red flag) from crater 

fill will provide close minimum age constraint for formation of sand blow. For scale, 

each colored intervals on shovel handle represents 10 cm. Photograph: M. Tuttle...... E-121

Figure E-55 Sand dikes, ranging up to 35 cm wide, originate in pebbly sand layer and 

intrude overlying diamicton, These features were exposed in cutbank along 

Cahokia Creek about 25 km northeast of downtown St. Louis (from Tuttle, 2000)....... E-122

Figure E-56 Photograph of small diapirs of medium sand intruding base of overlying 

deposit of interbedded clayey silt and very fine sand, and clasts of clayey silt in 

underlying medium sand, observed along Ouelle River in Charlevoix seismic zone. 

Sand diapirs and clasts probably formed during basal erosion and foundering of 

clayey silt due to liquefaction of the underlying sandy deposit. Red portion of shovel 

handle represents 10 cm (modified from Tuttle and Atkinson, 2010). .......................... E-123

Figures E-57 (A) Load cast formed in laminated sediments of Van Norman Lake during 

1952 Kern County, California, earthquake. Photograph: J. Sims (from Sims, 1975). 

(B) Load cast, pseudonodules, and related folds formed in laminated sediment 

exposed along Malbaie River in Charlevoix seismic zone. Sand dikes crosscutting 

these same laminated sediments occur at a nearby site. For scale, each painted 

interval of the shovel handle represents 10 cm (modified from Tuttle and Atkinson, 

2010)........................................................................................................................... E-124

Figure E-58 Log of sand blow and uppermost portions of related sand dikes exposed in 

trench wall at Dodd site in New Madrid seismic zone. Sand dikes were also 

observed in opposite wall and trench floor. Sand blow buries pre-event A horizon, 

and a subsequent A horizon has developed in top of sand blow. Radiocarbon dating 

of samples collected above and below sand blow brackets its age between 490 and 

660 yr BP. Artifact assemblage indicates that sand blow formed during late 

Mississippian cultural period (300–550 yr BP or AD 1400–1670) (modified from 

Tuttle, Collier, et al., 1999). ......................................................................................... E-125

Figures E-59 (A) Photograph of earthquake-induced liquefaction features found in 

association with cultural horizon and pit exposed in trench wall near Blytheville, 

Arkansas, in New Madrid seismic zone. Photograph: M. Tuttle. (B) Trench log of 

features shown in (A). Sand dike formed in thick Native American occupation 

horizon containing artifacts of early Mississippian cultural period (950–1,150 yr BP). 

Cultural pit dug into top of sand dike contains artifacts and charcoal used to 

constrain minimum age of liquefaction features (modified from Tuttle and Schweig, 

1995)........................................................................................................................... E-126

Figure E-60 In situ tree trunks such as this one buried and killed by sand blow in New 

Madrid seismic zone offer opportunity to date paleoearthquakes to the year and 

season of occurrence. Photograph: M. Tuttle. ............................................................. E-127
lxiii

Figure E-61 Portion of dendrocalibration curve illustrating conversion of radiocarbon age 

to calibrated date in calendar years. n example, 2-sigma radiocarbon age of 2,280–

2,520 BP is converted to calibrated date of 770–380 BC (from Tuttle, 1999)............... E-128

Figure E-62 Empirical relation developed between A horizon thickness of sand blows 

and years of soil development in New Madrid region. Horizontal bars reflect 

uncertainties in age estimates of liquefaction features; diamonds mark midpoints of 

possible age ranges (from Tuttle et al., 2000).............................................................. E-129

Figure E-63 Diagram illustrating earthquake chronology for New Madrid seismic zone for 

past 5,500 years based on dating and correlation of liquefaction features at sites 

(listed at top) across region from north to south. Vertical bars represent age 

estimates of individual sand blows, and horizontal bars represent event times of 

138 yr BP (AD 1811-1812); 500 yr BP ± 150 yr; 1,050 yr BP ± 100 yr; and 4,300 yr 

BP ± 200 yr (modified from Tuttle, Schweig, et al., 2002; Tuttle et al., 2005). .............. E-130

Figure E-64 Diagram illustrating earthquake chronology for New Madrid seismic zone for 

past 2,000 years, similar to upper portion of diagram shown in Figure E-63. As in 

Figure E-63, vertical bars represent age estimates of individual sand blows, and 

horizontal bars represent event times. Analysis performed during CEUS SSC 

Project derived two possible uncertainty ranges for timing of paleoearthquakes, 

illustrated by the darker and lighter portions of the colored horizontal bars, 

respectively: 503 yr BP ± 8 yr or 465 yr BP ± 65 yr, and 1,110 yr BP ± 40 yr or 1055 

± 95 yr (modified from Tuttle, Schweig, et al., 2002).................................................... E-131

Figure E-65 Maps showing spatial distributions and sizes of sand blows and sand dikes 

attributed to 500 and 1,050 yr BP events. Locations and sizes of liquefaction 

features that formed during AD 1811-1812 (138 yr BP) New Madrid earthquake 

sequence shown for comparison (modified from Tuttle, Schweig, et al., 2002)............ E-132

Figure E-66 Liquefaction fields for 138 yr BP (AD 1811-1812); 500 yr BP (AD 1450); and 

1,050 yr BP (AD 900) events as interpreted from spatial distribution and 

stratigraphy of sand blows (modified from Tuttle, Schweig, et al., 2002). Ellipses 

define areas where similar-age sand blows have been mapped. Overlapping 

ellipses indicate areas where sand blows are composed of multiple units that 

formed during sequence of earthquakes. Dashed ellipse outlines area where 

historical sand blows are composed of four depositional units. Magnitudes of 

earthquakes in 500 yr BP and 1,050 yr BP are inferred from comparison with 1811-

1812 liquefaction fields. Magnitude estimates of December (D), January (J), and 

February (F) main shocks and large aftershocks taken from several sources; 

rupture scenario from Johnston and Schweig (1996; modified from Tuttle, Schweig, 

et al., 2002). ................................................................................................................ E-133 

Figure E-67 Empirical relation between earthquake magnitude and epicentral distance to 

farthest known sand blows induced by instrumentally recorded earthquakes 

(modified from Castilla and Audemard, 2007).............................................................. E-134

Figure E-68 Distances to farthest known liquefaction features indicate that 500 and 

1,050 yr BP New Madrid events were at least of M 6.7 and 6.9, respectively, when 

plotted on Ambraseys (1988) relation between earthquake magnitude and 

epicentral distance to farthest surface expression of liquefaction. Similarity in size 

distribution of historical and prehistoric sand blows, however, suggests that 

paleoearthquakes were comparable in magnitude to 1811-1812 events or M ~7.6 

(modified from Tuttle, 2001)......................................................................................... E-135

Figure H-1-1 Region covered by the CEUS SSC model........................................................ H-44
lxiv

Figure H-2-1 Master logic tree for the CEUS SSC model...................................................... H-45

Figure H-3-1 Logic tree for the Mmax zones branch of the master logic tree......................... H-46

Figure H-3-2 Mesozoic extended (MESE-W) and non-extended (NMESE-W) Mmax 

zones for the “wide” interpretation ................................................................................. H-47

Figure H-3-3 Mesozoic extended (MESE-N) and non-extended (NMESE-N) Mmax zones 

for the “narrow” interpretation ........................................................................................ H-48

Figure H-4-1(a) Logic tree for the seismotectonic zones branch of the master logic tree....... H-49

Figure H-4-1(b) Logic tree for the seismotectonic zones branch of the master logic tree....... H-50

Figure H-4-2 Seismotectonic zones shown in the case where the Rough Creek Graben 

is not part of the Reelfoot Rift (RR) and the Paleozoic Extended zone is narrow 

(PEZ-N)......................................................................................................................... H-51

Figure H-4-3 Seismotectonic zones shown in the case where the Rough Creek Graben 

is part of the Reelfoot Rift (RR-RCG) and the Paleozoic Extended zone is narrow 

(PEZ-N)......................................................................................................................... H-52

Figure H-4-4 Seismotectonic zones shown in the case where the Rough Creek Graben 

is not part of the Reelfoot Rift (RR) and the Paleozoic Extended zone is wide (PEZW) ................................................................................................................................. H-53

Figure H-4-5 Seismotectonic zones shown in the case where the Rough Creek Graben 

is part of the Reelfoot Rift (RR-RCG) and the Paleozoic Extended zone is wide 

(PEZ-W)........................................................................................................................ H-54

Figure H-5-1 Logic tree for the RLME source branch of the master logic tree ....................... H-55

Figure H-5-2 Location of RLME sources in the CEUS SSC model ........................................ H-56

Figure H-5.1-1 Logic tree for Charlevoix RLME source ......................................................... H-57

Figure H-5.1-2 Charlevoix RLME source geometry ............................................................... H-58

Figure H-5.2-1(a) Logic tree for Charleston RLME source .................................................... H-59

Figure H-5.2-1(b) Logic tree for Charleston RLME source .................................................... H-60

Figure H-5.2-2 Charleston RLME alternative source geometries........................................... H-61

Figure H-5.3-1 Logic tree for Cheraw RLME source.............................................................. H-62

Figure H-5.3-2 Cheraw RLME source geometry.................................................................... H-63

Figure H-5.4-1 Logic tree for Meers RLME source ................................................................ H-64

Figure H-5.4-2 Meers RLME source geometries ................................................................... H-65

Figure H-5.5-1 Logic tree for NMFS RLME source................................................................ H-66

Figure H-5.5-2 New Madrid South (NMS) fault alternative RMLE source geometries: 

Blytheville Arch-Bootheel Lineament (BA-BL) and Blytheville Arch-Blytheville fault 

zone (BA-BFZ) .............................................................................................................. H-67

Figure H-5.5-3 New Madrid North (NMN) fault alternative RMLE source geometries: New 

Madrid North (NMN_S) and New Madrid North plus extension (NMN_L)....................... H-68

Figure H-5.5-4 Reelfoot Thrust (RFT) fault alternative RMLE source geometries: 

Reelfoot thrust (RFT_S) and Reelfoot thrust plus extensions (RFT_L) .......................... H-69

Figure H-5.6-1 Logic tree for ERM-S RLME source .............................................................. H-70

Figure H-5.6-2 Logic tree for ERM-N RLME source .............................................................. H-71

Figure H-5.6-3 ERM-S RLME source geometries.................................................................. H-72
lxv

Figure H-5.6-4 ERM-N RLME source geometry .................................................................... H-73

Figure H-5.7-1 Logic tree for Marianna RLME source ........................................................... H-74

Figure H-5.7-2 Marianna RLME source geometry................................................................. H-75

Figure H-5.8-1 Logic tree for Commerce Fault Zone RLME source ....................................... H-76

Figure H-5.8-2 Commerce RLME source geometry .............................................................. H-77

Figure H-5.9-1 Logic tree for Wabash Valley RLME source .................................................. H-78

Figure H-5.9-2 Wabash Valley RLME source geometry ........................................................ H-79

Figure J-1 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 1....................................................................................................... J-2 

Figure J-2 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 2....................................................................................................... J-3 

Figure J-3 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 3....................................................................................................... J-4 

Figure J-4 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 4....................................................................................................... J-5 

Figure J-5 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 5....................................................................................................... J-6 

Figure J-6 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 6....................................................................................................... J-7 

Figure J-7 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 7....................................................................................................... J-8 

Figure J-8 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 8....................................................................................................... J-9 

Figure J-9 Map of the coefficient of variation of the rate and the standard deviation of the 

b-value for the study region under the Mmax zonation, with no separation of 

Mesozoic extended and non-extended; Case A magnitude weights ............................... J-10

Figure J-10 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 1..................................................................................................... J-11

Figure J-11 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 2..................................................................................................... J-12

Figure J-12 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 3..................................................................................................... J-13
lxvi 

Figure J-13 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 4..................................................................................................... J-14

Figure J-14 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 5..................................................................................................... J-15

Figure J-15 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 6..................................................................................................... J-16

Figure J-16 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 7..................................................................................................... J-17

Figure J-17 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 8..................................................................................................... J-18

Figure J-18 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with no separation of 

Mesozoic extended and non-extended; Case B magnitude weights ............................... J-19

Figure J-19 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 1..................................................................................................... J-20

Figure J-20 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 2..................................................................................................... J-21

Figure J-21 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 3..................................................................................................... J-22

Figure J-22 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 4..................................................................................................... J-23

Figure J-23 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 5..................................................................................................... J-24

Figure J-24 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 6..................................................................................................... J-25

Figure J-25 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 7..................................................................................................... J-26

Figure J-26 Map of the rate and b-value for the study region under the Mmax zonation, 

with no separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 8..................................................................................................... J-27

Figure J-27 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with no separation of 

Mesozoic extended and non-extended; Case E magnitude weights ............................... J-28
lxvii

Figure J-28 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 1..................................................................................................... J-29

Figure J-29 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 2..................................................................................................... J-30

Figure J-30 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 3..................................................................................................... J-31

Figure J-31 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 4..................................................................................................... J-32

Figure J-32 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 5..................................................................................................... J-33

Figure J-33 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 6..................................................................................................... J-34

Figure J-34 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 7..................................................................................................... J-35

Figure J-35 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 8..................................................................................................... J-36

Figure J-36 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with separation of 

Mesozoic extended and non-extended; Case A magnitude weights ............................... J-37

Figure J-37 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 1..................................................................................................... J-38

Figure J-38 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 2..................................................................................................... J-39

Figure J-39 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 3..................................................................................................... J-40

Figure J-40 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 4..................................................................................................... J-41

Figure J-41 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 5..................................................................................................... J-42

Figure J-42 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 6..................................................................................................... J-43
lxviii

Figure J-43 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 7..................................................................................................... J-44

Figure J-44 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 8..................................................................................................... J-45

Figure J-45 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with separation of 

Mesozoic extended and non-extended; Case B magnitude weights ............................... J-46

Figure J-46 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 1..................................................................................................... J-47

Figure J-47 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 2..................................................................................................... J-48

Figure J-48 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 3..................................................................................................... J-49

Figure J-49 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 4..................................................................................................... J-50

Figure J-50 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 5..................................................................................................... J-51

Figure J-51 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 6..................................................................................................... J-52

Figure J-52 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 7..................................................................................................... J-53

Figure J-53 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 8..................................................................................................... J-54

Figure J-54 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with separation of 

Mesozoic extended and non-extended; Case E magnitude weights ............................... J-55

Figure J-55 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 1..................................................................................................... J-56

Figure J-56 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 2..................................................................................................... J-57

Figure J-57 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 3..................................................................................................... J-58
lxix

Figure J-58 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 4..................................................................................................... J-59

Figure J-59 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 5..................................................................................................... J-60

Figure J-60 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 6..................................................................................................... J-61

Figure J-61 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 7..................................................................................................... J-62

Figure J-62 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case A magnitude 

weights: Realization 8..................................................................................................... J-63

Figure J-63 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with separation of 

Mesozoic extended and non-extended; Case A magnitude weights ............................... J-64

Figure J-64 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 1..................................................................................................... J-65

Figure J-65 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 2..................................................................................................... J-66

Figure J-66 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 3..................................................................................................... J-67

Figure J-67 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 4..................................................................................................... J-68

Figure J-68 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 5..................................................................................................... J-69

Figure J-69 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 6..................................................................................................... J-70

Figure J-70 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 7..................................................................................................... J-71

Figure J-71 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case B magnitude 

weights: Realization 8..................................................................................................... J-72

Figure J-72 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with separation of 

Mesozoic extended and non-extended; Case B magnitude weights ............................... J-73
lxx 

Figure J-73 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 1..................................................................................................... J-74

Figure J-74 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 2..................................................................................................... J-75

Figure J-75 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 3..................................................................................................... J-76

Figure J-76 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 4..................................................................................................... J-77

Figure J-77 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 5..................................................................................................... J-78

Figure J-78 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 6..................................................................................................... J-79

Figure J-79 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 7..................................................................................................... J-80

Figure J-80 Map of the rate and b-value for the study region under the Mmax zonation, 

with separation of Mesozoic extended and non-extended; Case E magnitude 

weights: Realization 8..................................................................................................... J-81

Figure J-81 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the Mmax zonation, with separation of 

Mesozoic extended and non-extended; Case E magnitude weights ............................... J-82

Figure J-82 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

1 ..................................................................................................................................... J-83

Figure J-83 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

2 ..................................................................................................................................... J-84

Figure J-84 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

3 ..................................................................................................................................... J-85

Figure J-85 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

4 ..................................................................................................................................... J-86

Figure J-86 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

5 ..................................................................................................................................... J-87

Figure J-87 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

6 ..................................................................................................................................... J-88
lxxi 

Figure J-88 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

7 ..................................................................................................................................... J-89

Figure J-89 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

8 ..................................................................................................................................... J-90

Figure J-90 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with narrow 

interpretation of PEZ; Case A magnitude weights........................................................... J-91

Figure J-91 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

1 ..................................................................................................................................... J-92

Figure J-92 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

2 ..................................................................................................................................... J-93

Figure J-93 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

3 ..................................................................................................................................... J-94

Figure J-94 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

4 ..................................................................................................................................... J-95

Figure J-95 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

5 ..................................................................................................................................... J-96

Figure J-96 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization

6 ..................................................................................................................................... J-97

Figure J-97 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

7 ..................................................................................................................................... J-98

Figure J-98 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

8 ..................................................................................................................................... J-99

Figure J-99 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with narrow 

interpretation of PEZ; Case B magnitude weights......................................................... J-100

Figure J-100 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

1 ................................................................................................................................... J-101

Figure J-101 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

2 ................................................................................................................................... J-102

Figure J-102 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

3 ................................................................................................................................... J-103
lxxii

Figure J-103 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

4 ................................................................................................................................... J-104

Figure J-104 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

5 ................................................................................................................................... J-105

Figure J-105 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

6 ................................................................................................................................... J-106

Figure J-106 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

7 ................................................................................................................................... J-107

Figure J-107 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

8 ................................................................................................................................... J-108

Figure J-108 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with narrow 

interpretation of PEZ; Case E magnitude weights......................................................... J-109

Figure J-109 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

1 ................................................................................................................................... J-110

Figure J-110 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

2 ................................................................................................................................... J-111

Figure J-111 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

3 ................................................................................................................................... J-112

Figure J-112 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

4 ................................................................................................................................... J-113

Figure J-113 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

5 ................................................................................................................................... J-114

Figure J-114 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

6 ................................................................................................................................... J-115

Figure J-115 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

7 ................................................................................................................................... J-116

Figure J-116 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case A magnitude weights: Realization 

8 ................................................................................................................................... J-117

Figure J-117 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with narrow 

interpretation of PEZ; Case A magnitude weights......................................................... J-118
lxxiii

Figure J-118 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

1 ................................................................................................................................... J-119

Figure J-119 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

2 ................................................................................................................................... J-120

Figure J-120 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

3 ................................................................................................................................... J-121

Figure J-121 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

4 ................................................................................................................................... J-122

Figure J-122 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

5 ................................................................................................................................... J-123

Figure J-123 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

6 ................................................................................................................................... J-124

Figure J-124 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

7 ................................................................................................................................... J-125

Figure J-125 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case B magnitude weights: Realization 

8 ................................................................................................................................... J-126

Figure J-126 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with narrow 

interpretation of PEZ; Case B magnitude weights......................................................... J-127

Figure J-127 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

1 ................................................................................................................................... J-128

Figure J-128 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

2 ................................................................................................................................... J-129

Figure J-129 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

3 ................................................................................................................................... J-130

Figure J-130 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

4 ................................................................................................................................... J-131

Figure J-131 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

5 ................................................................................................................................... J-132

Figure J-132 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

6 ................................................................................................................................... J-133
lxxiv

Figure J-133 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

7 ................................................................................................................................... J-134

Figure J-134 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with narrow interpretation of PEZ; Case E magnitude weights: Realization 

8 ................................................................................................................................... J-135

Figure J-135 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with narrow 

interpretation of PEZ; Case E magnitude weights......................................................... J-136

Figure J-136 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 1 ... J-137

Figure J-137 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 2 ... J-138

Figure J-138 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 3 ... J-139

Figure J-139 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 4 ... J-140

Figure J-140 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 5 ... J-141

Figure J-141 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 6 ... J-142

Figure J-142 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 7 ... J-143

Figure J-143 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 8 ... J-144

Figure J-144 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with wide 

interpretation of PEZ; Case A magnitude weights......................................................... J-145

Figure J-145 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 1 ... J-146

Figure J-146 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 2 ... J-147

Figure J-147 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 3 ... J-148

Figure J-148 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 4 ... J-149

Figure J-149 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 5 ... J-150

Figure J-150 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 6 ... J-151

Figure J-151 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 7 ... J-152

Figure J-152 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 8 ... J-153
lxxv 

Figure J-153 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with wide 

interpretation of PEZ; Case B magnitude weights......................................................... J-154

Figure J-154 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 1 ... J-155

Figure J-155 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 2 ... J-156

Figure J-156 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 3 ... J-157

Figure J-157 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 4 ... J-158

Figure J-158 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 5 ... J-159

Figure J-159 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 6 ... J-160

Figure J-160 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 7 ... J-161

Figure J-161 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 8 ... J-162

Figure J-162 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with wide 

interpretation of PEZ; Case E magnitude weights......................................................... J-163

Figure J-163 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 1 ... J-164

Figure J-164 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 2 ... J-165

Figure J-165 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 3 ... J-166

Figure J-166 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 4 ... J-167

Figure J-167 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 5 ... J-168

Figure J-168 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 6 ... J-169

Figure J-169 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 7 ... J-170

Figure J-170 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case A magnitude weights: Realization 8 ... J-171

Figure J-171 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with wide 

interpretation of PEZ; Case A magnitude weights......................................................... J-172

Figure J-172 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 1 ... J-173
lxxvi 

Figure J-173 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 2 ... J-174

Figure J-174 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 3 ... J-175

Figure J-175 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 4 ... J-176

Figure J-176 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 5 ... J-177

Figure J-177 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 6 ... J-178

Figure J-178 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 7 ... J-179

Figure J-179 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case B magnitude weights: Realization 8 ... J-180

Figure J-180 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with wide 

interpretation of PEZ; Case B magnitude weights......................................................... J-181

Figure J-181 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 1 ... J-182

Figure J-182 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 2 ... J-183

Figure J-183 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 3 ... J-184

Figure J-184 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 4 ... J-185

Figure J-185 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 5 ... J-186

Figure J-186 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 6 ... J-187

Figure J-187 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 7 ... J-188

Figure J-188 Map of the rate and b-value for the study region under the seismotectonic 

zonation, with wide interpretation of PEZ; Case E magnitude weights: Realization 8 ... J-189

Figure J-189 Map of the coefficient of variation of the rate and the standard deviation of 

the b-value for the study region under the seismotectonic zonation, with wide 

interpretation of PEZ; Case E magnitude weights......................................................... J-190

Figure K-1 Comparison of relationships between number of reporting stations and 

moment magnitude presented in Johnston et al. (1994) and Johnston (1996b)............. K-41

Figure K-2 Comparison of relationships between isoseismal areas and moment 

magnitude presented in Johnston et al. (1994) and Johnston (1996b)........................... K-42
lxxvii 

LIST OF TABLES

Table 2.2-1 Technical Meetings Conducted as Part of the CEUS SSC Project ...................... 2-29

Table 2.2-2 Contributors to the CEUS SSC Project................................................................ 2-30

Table 3.2-1 Summary of Earthquakes Added–USGS Earthquake Catalog by Time 

Period............................................................................................................................. 3-44

Table 3.2-2 Summary of Earthquakes Added–USGS Earthquake Catalog by Source............ 3-45

Table 3.3-1 Conversion Relationships Used–Develop Uniform Moment Magnitudes E[M] ..... 3-46

Table 3.4-1 Comparison of CEUS SSC Catalog Declustering Results Obtained Using the 

EPRI (1988) Approach with the Gardner Knopoff (1974) Approach................................ 3-47

Table 3.5-1 Probability of Detection and Equivalent Periods of Completeness for the 

CEUS for Magnitude Weighting Case A ......................................................................... 3-48

Table 3.5-2 Probability of Detection and Equivalent Periods of Completeness for the 

CEUS for Magnitude Weighting Case B ......................................................................... 3-51

Table 3.5-3 Probability of Detection and Equivalent Periods of Completeness for the 

CEUS for Magnitude Weighting Case E ......................................................................... 3-54

Table 4.1.2-1 Sample table indicating particular types of data that can be considered in 

the identification and characterization of seismic sources (Table 2, ANSI/ANS-2.27-

2008).............................................................................................................................. 4-26

Table 4.1.2-2 Sample table identifying the types of data that can be considered for 

characterizing different types of seismic sources, and an evaluation of the relative 

usefulness or credibility of the various data types (Budnitz et al., 1997) ......................... 4-27

Table 4.1.2-3 Table showing the “generic” (not source-specific) evaluation of data to 

address indicators of a unique seismic source. The table indicates the TI Team’s 

assessment of the types of data that can be used to address the indicators and 

their relative usefulness.................................................................................................. 4-28

Table 4.1.2-4 Example of Data Evaluation Table for the Illinois Basin–Extended 

Basement Zone (IBEB)................................................................................................... 4-34

Table 4.1.2-5 Example of Data Summary Table for the Extended Continental Crust–

Atlantic Margin (ECC-AM) and Atlantic Highly Extended Crust (AHEX) Zones ............... 4-35

Table 4.1.3-1 Criteria Used to Define the Seismotectonic Zones and Mmax Zones ............... 4-37

Table 4.2.2-1 RLME Sources................................................................................................. 4-38

Table 4.2.4-1 Seismotectonic Zones ...................................................................................... 4-39

Table 5.2.1-1 Mesozoic-and-Younger Extended Superdomains (MESE) ............................... 5-60

Table 5.2.1-2 Older Extended and Non-Extended Superdomains (NMESE) .......................... 5-61

Table 5.2.1-3 Composite SCR Superdomains (COMP).......................................................... 5-62

Table 5.2.1-4 Results of Analyses of Updated SCR Superdomains ....................................... 5-63
lxxviii 

Table 5.2.1-5 Source Zones, P(mu > 81⁄4) Values, and Weights on Kijko (2004) K-S-B 

Estimates ....................................................................................................................... 5-64

Table 5.2.1-6 Mmax Distributions for the Two Example Seismic Sources .............................. 5-65

Table 5.3.2-1 Alternative Cases Considered for the Magnitude-Dependent Weights ............. 5-65

Table 5.3.3-1 Miller and Rice (1983) Discrete 5-Point Approximation to a Continuous 

Probability Distribution and the Modified Form Used in This Study................................. 5-65

Table 5.4-1 Assessment of Default Characteristics of Future Earthquakes in the CEUS........ 5-66

Table 5.4-2 Characteristics of Future Earthquakes for Individual Seismic Sources ................ 5-68 

Table 5.4-3 Estimates of D90 for Individual Seismic Source Zones......................................... 5-71

Table 6.1-1 Summary of Data Used to Assess RLME Recurrence Frequencies .................... 6-80

Table 6.1.1-1 Charlevoix RLME Recurrence Frequency ........................................................ 6-83

Table 6.1.2-1 Summary of Interpreted Charleston Earthquake Ages and Sizes from 

“Contemporary Ages Only” Scenario.............................................................................. 6-84

Table 6.1.2-2 Summary of Interpreted Charleston Earthquake Ages and Sizes from “All 

Ages” Scenario............................................................................................................... 6-84

Table 6.1.2-3 Charleston Liquefaction Feature Ages Used to Assess Ages of Prehistoric 

Earthquakes ................................................................................................................... 6-85

Table 6.1.2-4 Charleston RLME Recurrence Frequency for Poisson Model........................... 6-86

Table 6.1.2-5 Charleston RLME Recurrence Frequency for Renewal Model.......................... 6-87

Table 6.1.3-1 Range of Cheraw Fault Estimated Magnitudes (M) .......................................... 6-88

Table 6.1.3-2 Cheraw RLME In-Cluster Recurrence Frequency............................................. 6-89

Table 6.1.3-3 Cheraw RLME In-Cluster Slip Rates ................................................................ 6-89

Table 6.1.3-4 Cheraw RLME Out-of-Cluster Recurrence Frequency...................................... 6-90

Table 6.1.3-5 Cheraw RLME Out-of-Cluster Slip Rates.......................................................... 6-90

Table 6.1.4-1 Range of Estimated Meers Fault Earthquake Magnitudes (M).......................... 6-91

Table 6.1.4-2 Meers RLME In-Cluster Recurrence Frequency............................................... 6-91

Table 6.1.4-3 Meers RLME Out-of-Cluster Recurrence Frequency ........................................ 6-91

Table 6.1.5-1 Preferred Ages for Paleoearthquakes in the New Madrid Region1

................... 6-92

Table 6.1.5-2 Magnitude Comparisons for New Madrid 1811-1812 Earthquake 

Sequence....................................................................................................................... 6-93

Table 6.1.5-3 Liquefaction Constraints on Age of AD 1450 NMFS RLME .............................. 6-94

Table 6.1.5-4 Liquefaction Constraints on Age of AD 900 NMFS RLME ................................ 6-95

Table 6.1.5-5 NMFS In-Cluster RLME Recurrence Frequency—Poisson Model .................... 6-96

Table 6.1.5-6 NMFS In-Cluster RLME Recurrence Frequency—Renewal Model ................... 6-96

Table 6.1.5-7 NMFS Out-of-Cluster RLME Recurrence Frequency—Poisson Model ............. 6-96

Table 6.1.6-1 Range of ERM-S Estimated Magnitudes (M).................................................... 6-97

Table 6.1.6-2 Range of ERM-N Estimated Magnitudes (M).................................................... 6-98

Table 6.1.6-3 ERM-S RLME Recurrence Frequency.............................................................. 6-98

Table 6.1.6-4 ERM-N RLME Recurrence Frequency ............................................................. 6-99

Table 6.1.7-1 Marianna RLME Recurrence Frequency .......................................................... 6-99
lxxix

Table 6.1.8-1 Range of Commerce Fault Zone RLME Estimated Magnitudes (M) ............... 6-100

Table 6.1.8-2 Commerce Fault Zone RLME Recurrence Frequency .................................... 6-101

Table 6.1.9-1 Liquefaction Evidence for Prehistoric Earthquakes in the Southern Illinois 

Basin ............................................................................................................................ 6-102

Table 6.1.9-2 Wabash RLME Recurrence Frequency .......................................................... 6-109

Table 6.2-1 Alternative Mmax Zonation Models ................................................................... 6-109

Table 6.3.2-1 Maximum Magnitude Distributions for Mmax Distributed Seismicity 

Sources........................................................................................................................ 6-110

Table 7.1-1 Data Summary and Data Evaluation Tables for Seismotectonic Zones in 

Appendices C and D ...................................................................................................... 7-81

Table 7.4.2-1 Maximum Magnitude Distributions for Seismotectonic Distributed 

Seismicity Sources ......................................................................................................... 7-82

Table 8.1-1 Description of Seven Test Sites .......................................................................... 8-13

Table 8.2.1-1 Mean and Select Fractiles for Rock Hazard at Central Illinois: Digital Data

for Figures 8.2-1a through 8.2-1c ................................................................................... 8-14

Table 8.2.2-1 Mean and Select Fractiles for Rock Hazard at Chattanooga: Digital Data 

for Figures 8.2-2a through 8.2-2c ................................................................................... 8-16

Table 8.2.3-1 Mean and Select Fractiles for Rock Hazard at Houston: Digital Data for 

Figures 8.2-3a through 8.2-3c ........................................................................................ 8-18

Table 8.2.4-1 Mean and Select Fractiles for Rock Hazard at Jackson: Digital Data for 

Figures 8.2-4a through 8.2-4c ........................................................................................ 8-20

Table 8.2.5-1 Mean and Select Fractiles for Rock Hazard at Manchester: Digital Data for 

Figures 8.2-5a through 8.2-5c ........................................................................................ 8-22

Table 8.2.6-1 Mean and Select Fractiles for Rock Hazard at Savannah: Digital Data for 

Figures 8.2-6a through 8.2-6c ........................................................................................ 8-24

Table 8.2.7-1 Mean and Select Fractiles for Rock Hazard at Topeka: Digital Data for 

Figures 8.2-7a through 8.2-7c ........................................................................................ 8-26

Table 9.4-1 Available Information for Determining the Precision of Mean Hazard .................. 9-21

Table 9.4-2 Summary of an Example Logic Tree Representing Uncertainties for the 

Charleston Seismic Zone ............................................................................................... 9-21

Table 9.4-3 Basic Weights Given in EPRI (2004) for Ground Motion Equations..................... 9-22

Table 9.4-4 Ground Motion Equations and Weights Used in USGS 2008 National Hazard 

Map for CEUS................................................................................................................ 9-23

Table 9.4-5 Minimum COVMH Values Observed in Seismic Hazard ....................................... 9-23

Table A-1 CEUS SSC GIS Database...................................................................................... A-7 

Table B-1 Earthquake Catalog ................................................................................................ B-6 

Table B-2 Moment Magnitude Data..................................................................................... B-312

Table B-3 Approximate Moment Magnitude Data................................................................ B-324

Table C-5.4 Data Evaluation Future Earthquake Characteristics............................................. C-3 

Table C-6.1.1 Data Evaluation Charlevoix RLME.................................................................... C-9 

Table C-6.1.2 Data Evaluation Charleston RLME ................................................................. C-14

Table C-6.1.3 Data Evaluation Cheraw Fault RLME ............................................................. C-30
lxxx 

Table C-6.1.4 Data Evaluation Oklahoma Aulacogen RLME ................................................. C-36 

Table C-6.1.5 Data Evaluation Reelfoot Rift–New Madrid Fault System RLMEs ................... C-42 

Table C-6.1.6 Data Evaluation Reelfoot Rift–Eastern Margin Fault(s) RLMEs ....................... C-51 

Table C-6.1.7 Data Evaluation Reelfoot Rift–Marianna RLME ............................................... C-62 

Table C-6.1.8 Data Evaluation Reelfoot Rift–Commerce Fault Zone RLME .......................... C-67 

Table C-6.1.9 Data Evaluation Wabash Valley RLME ............................................................ C-75 

Table C-7.3.1 Data Evaluation St. Lawrence Rift Zone ......................................................... C-83 

Table C-7.3.2 Data Evaluation Great Meteor Hotspot Zone ................................................... C-92 

Table C-7.3.3 Data Evaluation Northern Appalachian Zone ................................................... C-99 

Table C-7.3.4 Data Evaluation Paleozoic Extended Crust Zone .......................................... C-105 

Table C-7.3.5 Data Evaluation Illinois Basin-Extended Basement Zone .............................. C-112 

Table C-7.3.6 Data Evaluation Reelfoot Rift Zone ................................................................ C-124 

Tables C-7.3.7/7.3.8 Data Evaluation Extended Continental Crust—Atlantic ....................... C-131 

Tables C-7.3.9/7.3.10 Data Evaluation Extended Continental Crust–Gulf Coast ................ C-138 

Table C-7.3.12 Data Evaluation Midcontinent-Craton Zone ................................................ C-146 

Table D-5.4 Data Summary Future Earthquake Characteristics ............................................... D-3 

Table D-6.1.1 Data Summary Charlevoix RLME .................................................................... D-10 

Table D-6.1.2 Data Summary Charleston RLME .................................................................... D-17 

Table D-6.1.3 Data Summary Cheraw Fault RLME ................................................................ D-35 

Table D-6.1.4 Data Summary Oklahoma Aulacogen RLME ................................................... D-38 

Table D-6.1.5 Data Summary Reelfoot Rift–New Madrid Seismic Zone (NMSZ) Region ....... D-44 

Table D-6.1.9 Data Summary Wabash Valley RLME ............................................................. D-92 

Table D-7.3.1 Data Summary St. Lawrence Rift Zone (SLR) ............................................... D-121 

Table D-7.3.2 Data Summary Great Meteor Hotspot Zone (GMH) ....................................... D-141 

Table D-7.3.3 Data Summary Northern Appalachian Zone (NAP) ....................................... D-151 

Table D-7.3.4 Data Summary Paleozoic Extended Crust Zone ............................................ D-163 

Table D-7.3.7 Data Summary Extended Continental Crust Zone–Atlantic Margin (ECCAM) ................................................................................................................................ D-191 

Table D-7.3.9 Data Summary Extended Continental Crust Zone–Gulf Coast (ECC-GC) ..... D-225 

Table D-7.3.12 Data Summary Midcontinent-Craton Zone (MidC) ....................................... D-240 

Table E-1.2-1. Summary of Information on Liquefaction Features in Regional Data Sets........ E-5 

Table E-1.2-2 Summary of Type and Prevalence of Paleoliquefaction Features ..................... E-7 

Table E-2.1.3. Summary of Dating Techniques Used in Paleoliquefaction Studies................ E-30 

Table E-2.2. Uncertainties Related to Interpretation of Paleoearthquake Parameters ........... E-36 

Table 1: Key Questions and Topics That Workshop 2 Presenters Were Asked to 

Address ............................................................................................................................ F-35 

Table H-3-1 Weighted Alternative Seismogenic Crustal Thickness Values for Mmax 

Zones .............................................................................................................................. H-20 

Table H-3-2 Aleatory Distributions for Characterization of Future Earthquake Ruptures 

for Mmax Zones .............................................................................................................. H-20 
lxxxi 

Table H-3-3 Maximum Magnitude Distributions for Mmax Distributed Seismicity Sources .... H-20

Table H-4-1 Seismotectonic Source Zones ........................................................................... H-21

Table H-4-2 Weighted Alternative Seismogenic Crustal Thickness Values for 

Seismotectonic Zones ................................................................................................... H-21

Table H-4-3 Aleatory Distributions for Characterization of Future Earthquake Ruptures 

for Seismotectonic Zones .............................................................................................. H-22

Table H-4-4 Maximum Magnitude Distributions for Seismotectonic Distributed Seismicity 

Sources......................................................................................................................... H-24

Table H-5.1-1 Charlevoix RLME Magnitude Distribution ....................................................... H-25

Table H-5.1-2 Annual Frequencies for Charlevoix RLME Events Data Set 1: 1870 and 

1663.............................................................................................................................. H-25

Table H-5.1-3 Annual Frequencies for Charlevoix RLME Events Data Set 2: 3 

Earthquakes in 6–7 kyr BP............................................................................................ H-25

Table H-5.1-4 Annual Frequencies for Charlevoix RLME Events Data Set 3: 4 

Earthquakes in 9.5–10.2 kyr BP .................................................................................... H-26

Table H-5.2-1 Charleston RLME Magnitude Distribution ....................................................... H-26

Table H-5.2-2 Annual Frequencies for Charleston RLME Events Poisson Model, 2,000-

Year Time Period Earthquakes 1886, A, B, and C......................................................... H-26

Table H-5.2-3 Annual Frequencies for Charleston RLME Events Poisson Model, 5,500-

Year Time Period Earthquakes 1886, A, B, and C......................................................... H-27

Table H-5.2-4 Annual Frequencies for Charleston RLME Events Poisson Model, 5,500-

Year Time Period Earthquakes 1886, A, B, C, and D .................................................... H-27

Table H-5.2-5 Annual Frequencies for Charleston RLME Events Poisson Model, 5,500-

Year Time Period Earthquakes 1886, A, B, C, and E .................................................... H-27

Table H-5.2-6 Annual Frequencies for Charleston RLME Events Poisson Model, 5,500-

Year Time Period Earthquakes 1886, A, B, C, D, and E................................................ H-28

Table H-5.2-7 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.3, 2,000-Year Time Period Earthquakes 1886, A, B, and C..................................... H-28

Table H-5.2-8 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.5, 2,000-Year Time Period Earthquakes 1886, A, B, and C..................................... H-28

Table H-5.2-9 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.7, 2,000-Year Time Period Earthquakes 1886, A, B, and C..................................... H-29

Table H-5.2-10 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.3, 5,500-Year Time Period Earthquakes 1886, A, B, and C..................................... H-29

Table H-5.2-11 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.5, 5,500-Year Time Period Earthquakes 1886, A, B, and C..................................... H-29

Table H-5.2-12 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.7, 5,500-Year Time Period Earthquakes 1886, A, B, and C..................................... H-30

Table H-5.2-13 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.3, 5,500-Year Time Period Earthquakes 1886, A, B, C, and D ................................ H-30

Table H-5.2-14 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.5, 5,500-Year Time Period Earthquakes 1886, A, B, C, and D ................................ H-30
lxxxii 

Table H-5.2-15 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.7, 5,500-Year Time Period Earthquakes 1886, A, B, C, and D ................................ H-31

Table H-5.2-16 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.3, 5,500-Year Time Period Earthquakes 1886, A, B, C, and E................................. H-31

Table H-5.2-17 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.5, 5,500-Year Time Period Earthquakes 1886, A, B, C, and E................................. H-31

Table H-5.2-18 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.7, 5,500-Year Time Period Earthquakes 1886, A, B, C, and E................................. H-32

Table H-5.2-19 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.3, 5,500-Year Time Period Earthquakes 1886, A, B, C, D, and E............................ H-32

Table H-5.2-20 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.5, 5,500-Year Time Period Earthquakes 1886, A, B, C, D, and E............................ H-32

Table H-5.2-21 Annual Frequencies for Charleston RLME Events BPT Renewal Model, α

= 0.7, 5,500-Year Time Period Earthquakes 1886, A, B, C, D, and E............................ H-33

Table H-5.3-1 Cheraw RLME Magnitude Distribution............................................................ H-33

Table H-5.3-2 Annual Frequencies for Cheraw RLME Events In-Cluster Case, Data Set: 

2 Earthquakes in 20–25 kyr........................................................................................... H-33

Table H-5.3-3 Annual Frequencies for Cheraw RLME Events In-Cluster Case, Data Set: 

3 Earthquakes in 20–25 kyr ........................................................................................... H-34

Table H-5.3-4 Slip Rates for Cheraw Fault In-Cluster Case, Data Set: 3.2–4.1 m in 20–

25 kyr ............................................................................................................................ H-34

Table H-5.3-5 Annual Frequencies for Cheraw RLME Events Out-of-Cluster Case, Time 

Between Clusters .......................................................................................................... H-34

Table H-5.3-6 Slip Rates for Cheraw Fault Out-of-Cluster Case, Data Set: 7–8 m in 0.4–

2.0 myr.......................................................................................................................... H-35

Table H-5.4-1 Meers RLME Magnitude Distribution .............................................................. H-35

Table H-5.4-2 Annual Frequencies for Meers RLME Events In-Cluster Case........................ H-35

Table H-5.4-3 Annual Frequencies for Meers RLME Events Out-of-Cluster Case................. H-36

Table H-5.5-1 NMFS RLME Magnitude Distribution .............................................................. H-36

Table H-5.5-2 Annual Frequencies for NMFS RLME Events In-Cluster Case, Poisson 

Model ............................................................................................................................ H-36

Table H-5.5-3 Annual Frequencies for NMFS RLME Events In-Cluster Case, BPT Model, 

α = 0.3........................................................................................................................... H-37

Table H-5.5-4 Annual Frequencies for NMFS RLME Events In-Cluster Case, BPT Model, 

α = 0.5........................................................................................................................... H-37

Table H-5.5-5 Annual Frequencies for NMFS RLME Events In-Cluster Case, BPT Model, 

α = 0.7........................................................................................................................... H-37

Table H-5.5-6 Annual Frequencies for NMFS RLME Events Out-of-Cluster Case, 

Poisson Model............................................................................................................... H-38

Table H-5.6-1 ERM-S RLME Magnitude Distribution............................................................. H-38

Table H-5.6-2 ERM-N RLME Magnitude Distribution............................................................. H-38

Table H-5.6-3 Annual Frequencies for ERM-S RLME Events Data Set: 2 Earthquakes in 

17.7–21.7 kyr ................................................................................................................ H-39
lxxxiii 

Table H-5.6-4 Annual Frequencies for ERM-S RLME Events Data Set: 3 Earthquakes in 

17.7–21.7 kyr ................................................................................................................ H-39

Table H-5.6-5 Annual Frequencies for ERM-S RLME Events Data Set: 4 Earthquakes in 

17.7–21.7 kyr ................................................................................................................ H-39

Table H-5.6-6 Annual Frequencies for ERM-N RLME Events Data Set: 1 Earthquake in 

12–35 kyr ...................................................................................................................... H-40

Table H-5.6-7 Annual Frequencies for ERM-N RLME Events Data Set: 2 Earthquakes in 

12–35 kyr ...................................................................................................................... H-40

Table H-5.7-1 Marianna RLME Magnitude Distribution ......................................................... H-40

Table H-5.7-2 Annual Frequencies for Marianna RLME Events Data Set: 3 Earthquakes 

in 9.6–10.2 kyr............................................................................................................... H-41

Table H-5.7-3 Annual Frequencies for Marianna RLME Events Data Set: 4 Earthquakes 

in 9.6–10.2 kyr............................................................................................................... H-41

Table H-5.8-1 Commerce RLME Magnitude Distribution....................................................... H-41

Table H-5.8-2 Annual Frequencies for Commerce RLME Events Data Set: 2 

Earthquakes in 18.9–23.6 kyr........................................................................................ H-42

Table H-5.8-3 Annual Frequencies for Commerce RLME Events Data Set: 3 

Earthquakes in 18.9–23.6 kyr........................................................................................ H-42

Table H-5.9-1 Wabash RLME Magnitude Distribution ........................................................... H-42

Table H-5.9-2 Annual Frequencies for Wabash RLME Events Data Set: 2 Earthquakes

in 11–13 kyr................................................................................................................... H-43

PPRP Comment Response Table..............................................................................(Appendix I)

Table K-1 SCR Earthquake Catalog........................................................................................ K-5 

Table K-2 SCR Domains Updated from Johnston et al. (1994) ............................................. K-34

EXECUTIVE SUMMARY 

The Central and Eastern United States Seismic Source Characterization for Nuclear Facilities 

(CEUS SSC) Project was conducted over the period from April 2008 to December 2011 to 

provide a regional seismic source model for use in probabilistic seismic hazard analyses 

(PSHAs) for nuclear facilities. The study replaces previous regional seismic source models 

conducted for this purpose, including the Electric Power Research Institute–Seismicity Owners 

Group (EPRI-SOG) model (EPRI, 1988, 1989) and the Lawrence Livermore National 

Laboratory model (Bernreuter et al., 1989). Unlike the previous studies, the CEUS SSC Project 

was sponsored by multiple stakeholders—namely, the EPRI Advanced Nuclear Technology 

Program, the Office of Nuclear Energy and the Office of the Chief of Nuclear Safety of the U.S. 

Department of Energy (DOE), and the Office of Nuclear Regulatory Research of the Nuclear 

Regulatory Commission (NRC). The study was conducted using Senior Seismic Hazard Analysis 

Committee (SSHAC) Study Level 3 methodology to provide high levels of confidence that the 

data, models, and methods of the larger technical community have been considered and the 

center, body, and range of technically defensible interpretations have been included. 

The regional seismic source characterization (SSC) model defined by this study can be used for 

site-specific PSHAs, provided that appropriate site-specific assessments are conducted as 

required by current regulations and regulatory guidance for the nuclear facility of interest. This 

model has been designed to be compatible with current and anticipated ground-motion 

characterization (GMC) models. The current recommended ground-motion models for use at 

nuclear facilities are those developed by EPRI (2004, 2006a, 2006b). The ongoing Next 

Generation Attenuation–East (NGA-East) project being supported by the NRC, DOE, and EPRI 

will provide ground-motion models that are appropriate for use with the CEUS SSC model. The 

methodology for a SSHAC Level 3 project as applied to the CEUS SSC Project is explained in 

the SSHAC report (Budnitz et al., 1997), which was written to discuss the evolution of expert 

assessment methodologies conducted during the previous three decades for purposes of 

probabilistic risk analyses. The methodological guidance provided in the SSHAC report was 

intended to build on the lessons learned from those previous studies and, specifically, to arrive at 

processes that would make it possible to avoid the issues encountered by the previous studies 

(NRC, 2011).

The SSHAC assessment process, which differs only slightly for Level 3 and 4 studies, is a 

technical process accepted in the NRC’s seismic regulatory guidance (Regulatory Guide 1.208) 

for ensuring that uncertainties in data and scientific knowledge have been properly represented in 

seismic design ground motions consistent with the requirements of the seismic regulation 

10 CFR Part 100.23 (―Geologic and Seismic Siting Criteria‖). Therefore, the goal of the SSHAC 

assessment process is the proper and complete representation of knowledge and uncertainties in 

the SSC and GMC inputs to the PSHA (or similar hazard analysis). As discussed extensively in 

lxxxv
Executive Summary 

the SSHAC report (Budnitz et al., 1997) and affirmed in NRC (2011), a SSHAC assessment 

process consists of two important sequential activities, evaluation and integration. For a Level 3 

assessment, these activities are conducted by the Technical Integration (TI) Team under the 

leadership of the TI Lead. As described in NRC (2011), 

The fundamental goal of a SSHAC process is to carry out properly and document completely the 

activities of evaluation and integration, defined as: 

Evaluation: The consideration of the complete set of data, models, and methods proposed by 

the larger technical community that are relevant to the hazard analysis. 

Integration: Representing the center, body, and range of technically defensible interpretations 

in light of the evaluation process (i.e., informed by the assessment of existing data, models, 

and methods). 

Each of the assessment and model-building activities of the CEUS SSC Project is associated with 

the evaluation and integration steps in a SSHAC Level 3 process. Consistent with the 

requirements of a SSHAC process, the specific roles and responsibilities of all project 

participants were defined in the Project Plan, and adherence to those roles was the responsibility 

of the TI Lead and the Project Manager. The technical assessments are made by the TI Team, 

who carry the principal responsibility of evaluation and integration, under the technical 

leadership of the TI Lead. The Database Manager and other technical support individuals assist 

in the development of work products. Resource and proponent experts participate by presenting 

their data, models, and interpretations at workshops and through technical interchange with the 

TI Team throughout the project. The Participatory Peer Review Panel (PPRP) is responsible for a 

continuous review of both the SSHAC process being followed and the technical assessments 

being made. The project management structure is headed by the Project Manager, who serves as 

the liason with the sponsors and the PPRP and manages the activities of all participants. The 

SSHAC Level 3 assessment process and implementation is discussed in depth in Chapter 2 of 

this report. 

Each of the methodology steps in the SSHAC guidelines (Budnitz, 1997) was addressed 

adequately during the CEUS SSC Project. Furthermore, the project developed a number of 

enhancements to the process steps for conducting a SSHAC Study Level 3 project. For example, 

the SSHAC guidelines call for process steps that include developing a preliminary assessment 

model, calculating hazard using that model in order to identify the key issues, and finalizing the 

model in light of the feedback provided from the hazard calculations and sensitivity analyses. 

Because of the regional nature of the project and the multitude of assessments required, four 

rounds of model-building and three rounds of feedback were conducted. These activities ensured 

that all significant issues and uncertainties were identified and that the appropriate effort was 

devoted to the issues of most significance to the hazard results. A comparison of the activities 

conducted during the CEUS SSC Project with those recommended in the SSHAC guidelines 

themselves (Section 2.6) led to the conclusion that the current standards of practice have been 

met for a SSHAC Study Level 3 process—both those that are documented in the SSHAC report 

and those that resulted from precedents set by projects conducted since the SSHAC report was 

issued. 

lxxxvi
Executive Summary 

The catalog of past earthquakes that have occurred in a region is an important source of 

information for the quantification of future seismic hazards. This is particularly true in stable 

continental regions (SCRs) such as the CEUS where the causative mechanisms and structures for 

the occurrence of damaging earthquakes are generally poorly understood, and the rates of crustal 

deformation are low such that surface and near-surface indications of stresses in the crust and the 

buildup and release of crustal strains are difficult to quantify. Because the earthquake catalog is 

used in the characterization of the occurrence of future earthquakes in the CEUS, developing an 

updated earthquake catalog for the study region was an important focus of the CEUS SSC 

Project. The specific goals for earthquake catalog development and methods used to attain those 

goals are given in Chapter 3. 

The earthquake catalog development consists of four main steps: catalog compilation, 

assessment of a uniform size measure to apply to each earthquake, identification of dependent 

earthquakes (catalog declustering), and assessment of the completeness of the catalog as a 

function of location, time, and earthquake size. An important part of the catalog development 

process was review by seismologists with extensive knowledge and experience in catalog 

compilation. The result is an earthquake catalog covering the entire study region for the period 

from 1568 through the end of 2008. Earthquake size is defined in terms of the moment 

magnitude scale (Hanks and Kanamori, 1979), consistent with the magnitude scale used in 

modern ground-motion prediction equations (GMPEs) for CEUS earthquakes. A significant 

contribution of the CEUS SSC Project is the work conducted to develop an updated and 

consistent set of conversion relationships between various earthquake size measures 

(instrumental magnitudes and intensity) and moment magnitude. 

The conceptual SSC framework described in Chapter 4 was developed early in the CEUS SSC 

Project in order to provide a consistent approach and philosophy to SSC by the TI Team. This 

framework provides the basic underpinnings of the SSC model developed for the project, and it

led to the basic structure and elements of the master logic tree developed for the SSC model. In 

considering the purpose of the CEUS SSC Project, the TI Team identified three attributes that are 

needed for a conceptual SSC framework: 

1. A systematic, documented approach to treating alternatives using logic trees, including 

alternative conceptual models for future spatial distributions of seismicity (e.g., stationarity); 

alternative methods for expressing the future temporal distribution of seismicity (e.g., 

renewal models, Poisson models); and alternative data sets for characterizing seismic sources 

(e.g., paleoseismic data, historical seismicity data). 

2. A systematic approach to identifying applicable data for the source characterization, 

evaluating the usefulness of the data, and documenting the consideration given to the data by 

the TI Team. 

3. A methodology for identifying seismic sources based on defensible criteria for defining a 

seismic source, incorporating the lessons learned in SSC over the past two decades, and 

identifying the range of approaches and models that can be shown to be significant to hazard. 

Each of these needs was addressed by the methodology used in the project. For example, the 

need for a systematic approach to identifying and evaluating the data and information that 

underlie the source characterization assessments was met by the development of Data Summary 

lxxxvii
Executive Summary 

and Data Evaluation tables. These tables were developed for each seismic source to document 

the information available at the time of the CEUS SSC assessments (the Data Summary tables) 

and the way those data were used in the characterization process (the Data Evaluation tables). 

Given the evolution of approaches to identifying seismic sources, it is appropriate to provide a 

set of criteria and the logic for their application in the CEUS SSC Project. In the project, unique 

seismic sources are defined to account for distinct differences in the following criteria: 

Earthquake recurrence rate 

Maximum earthquake magnitude (Mmax) 

Expected future earthquake characteristics (e.g., style of faulting, rupture orientation, depth 

distribution) 

Probability of activity of tectonic feature(s) 

Rather than treat these criteria as operating simultaneously or without priority, the CEUS SSC 

methodology works through them sequentially. Further, because each criterion adds complexity 

to the seismic source model, it is applied only if its application would lead to hazard-significant 

changes in the model. In this way, the model becomes only as complex as required by the 

available data and information. 

The CEUS SSC master logic tree is tied to the conceptual SSC framework that establishes the 

context for the entire seismic source model. The master logic tree depicts the alternative 

interpretations and conceptual models that represent the range of defensible interpretations, and 

the relative weights assessed for the alternatives. By laying out the alternatives initially, the 

subsequent detailed source evaluations were conducted within a framework that ensures 

consistency across the sources. Important elements of the master logic tree are as follows: 

Representation of the sources defined based on paleoseismic evidence for the occurrence of 

repeated large-magnitude earthquakes (RLMEs, defined as two or more earthquakes with 

M ≥ 6.5). 

Alternatives to the spatial distribution of earthquakes based on differences in maximum 

magnitudes (Mmax zones approach). 

Representation of uncertainty in spatial stationarity of observed seismicity based on 

smoothing of recurrence parameters. 

Representation of possible differences in future earthquake characteristics (e.g., style, 

seismogenic thickness, and orientation of ruptures), which lead to definition of 

seismotectonic zones in the logic tree (seismotectonic zones approach). 

The methodologies used by the project to make the SSC assessments are discussed in Chapter 5. 

The heart of any SSC model for PSHA is a description of the future spatial and temporal 

distribution of earthquakes. Continued analysis of the historical seismicity record and network 

monitoring by regional and local seismic networks has led to acceptance within the community 

that the general spatial patterns of observed small- to moderate-magnitude earthquakes provide 

predictive information about the spatial distribution of future large-magnitude earthquakes. The 

analyses leading to this conclusion have focused on whether the observed patterns of earthquakes 

lxxxviii
Executive Summary 

have varied through time; therefore, in effect, this is an assessment of uncertainty in whether 

small- to moderate-magnitude earthquakes have been relatively stationary through time.

However, the available data on larger-magnitude earthquakes and their relationship to the spatial 

distribution of smaller earthquakes based on the observed record are quite limited. These data are 

not sufficient to allow confidence in the predictions generated by empirical spatial models. For 

this reason, geologic and geophysical data are needed to specify the locations of future 

earthquakes in addition to the observed patterns of seismicity. 

Detailed studies in the vicinity of large historical and instrumental earthquakes, and liquefaction 

phenomena associated with them, coupled with field and laboratory studies of geotechnical 

properties, are leading to a stronger technical basis for (1) placing limits on the locations of 

paleoearthquakes interpreted by the distribution of liquefaction phenomena and (2) defining their 

magnitudes. In some cases, the paleoseismic evidence for RLMEs is compelling, and the TI 

Team has included the RLME source in the SSC model. The locations of RLME sources 

notwithstanding, the spatial distribution of distributed seismicity sources has advanced in PSHA 

largely because of the assumption of spatial stationarity, and the SSC and hazard community 

uses approaches to ―smooth‖ observed seismicity to provide a map that expresses the future 

spatial pattern of recurrence rates. The CEUS SSC model is based largely on the assumption, 

typical in PSHA studies, that spatial stationarity of seismicity is expected to persist for a period 

of approximately 50 years. 

Estimating Mmax in SCRs such as the CEUS is highly uncertain despite considerable interest 

and effort by the scientific community over the past few decades. Mmax is defined as the upper 

truncation point of the earthquake recurrence curve for individual seismic sources, and the 

typically broad distribution of Mmax for any given source reflects considerable epistemic 

uncertainty. Because the maximum magnitude for any given seismic source in the CEUS occurs 

rarely relative to the period of observation, the use of the historical seismicity record provides 

important but limited constraints on the magnitude of the maximum event. Because of the 

independent constraints on earthquake size, those limited constraints are used to estimate the 

magnitudes of RLME. For distributed seismicity source zones, two approaches are used to assess 

Mmax: the Bayesian approach and the Kijko approach. In the Bayesian procedure (Johnston et 

al., 1994), the prior distribution is based on the magnitudes of earthquakes that occurred 

worldwide within tectonically analogous regions. As part of the CEUS SSC Project, the TI Team 

pursued the refinement and application of the Bayesian Mmax approach becauses it provides a 

quantitative and repeatable process for assessing Mmax. 

The TI Team also explored alternative approaches for the assessment of Mmax that provide 

quantitative and repeatable results, and the team identified the approach developed by Kijko 

(2004) as a viable alternative. While the Kijko approach requires fewer assumptions than the 

Bayesian approach in that it uses only the observed earthquake statistics for the source, this is 

offset by the need for a relatively larger data sample in order to get meaningful results. Both 

approaches have the positive attribute that they are repeatable given the same data and they can 

be readily updated given new information. The relative weighting of the two approaches for 

inclusion in the logic tree is source-specific, a function of the numbers of earthquakes that are 

present within the source upon which to base the Mmax assessment: sources with fewer 

earthquakes are assessed to have little or no weight for the Kijko approach, while those with 

lxxxix
Executive Summary 

larger numbers of events are assessed higher weight for the Kijko approach. In all cases, because 

of the stability of the Bayesian approach and the preference for ―analogue‖ approaches within the 

larger technical community, the Bayesian approach is assessed higher weight than the Kijko 

approach for all sources. 

A major effort was devoted to updating the global set of SCR earthquakes and to assessing 

statistically significant attributes of those earthquakes following the approach given in Johnston 

et al. (1994). In doing so, it was found that the only significant attribute defining the prior 

distribution is the presence or absence of Mesozoic-or-younger extension. The uncertainty in this 

assessment is reflected in the use of two alternative priors: one that takes into account the 

presence or absence of crustal domains having this attribute, and another that combines the entire 

CEUS region as a single SCR crustal domain with a single prior distribution. The use of the 

Bayesian—and Kijko—approach requires a definition of the largest observed magnitude within 

each source, and this assessment, along with the associated uncertainty, was incorporated into the 

Mmax distributions for each seismic source. Consideration of global analogues led to the 

assessment of an upper truncation to all Mmax distributions at 81⁄4 and a lower truncation at 51⁄2. 

The broad distributions of Mmax for the various seismic source zones reflect the current 

epistemic uncertainty in the largest earthquake magnitude within each seismic source. 

The CEUS SSC model is based to a large extent on an assessment that spatial stationarity of 

seismicity will persist for time periods of interest for PSHA (approximately the next 50 years). 

Stationarity in this sense does not mean that future locations and magnitudes of earthquakes will 

occur exactly where they have occurred in the historical and instrumental record. Rather, the 

degree of spatial stationarity varies as a function of the type of data available to define the 

seismic source. RLME sources are based largely on paleoseismic evidence for repeated largemagnitude (M ≥ 6.5) earthquakes that occur in approximately the same location over periods of a 

few thousand years. On the other hand, patterns of seismicity away from the RLME sources 

within the Mmax and seismotectonic zones are defined from generally small- to moderatemagnitude earthquakes that have occurred during a relatively short (i.e., relative to the repeat 

times of large events) historical and instrumental record. Thus, the locations of future events are 

not as tightly constrained by the locations of past events as for RLME sources. The spatial 

smoothing operation is based on calculations of earthquake recurrence within one-quarter-degree 

or half-degree cells, with allowance for ―communication‖ between the cells. Both a- and bvalues are allowed to vary, but the degree of variation has been optimized such that b-values 

vary little across the study region. 

The approach used to smooth recurrence parameters is a refinement of the penalized-likelihood 

approach used in EPRI-SOG (EPRI, 1988), but it is designed to include a number of elements 

that make the formulation more robust, realistic, and flexible. These elements include the 

reformulation in terms of magnitude bins, the introduction of magnitude-dependent weights, 

catalog incompleteness, the effect of Mmax, spatial variation of parameters within the source 

zone, and the prior distributions of b. A key assessment made by the TI Team was the weight 

assigned to various magnitude bins in the assessment of smoothing parameters (Cases A, B, 

and E). This assessment represents the uncertainty in the interpretation that smaller magnitudes 

define the future locations and variation in recurrence parameters. Appropriately, the penalizedlikelihood approach results in higher spatial variation (less smoothing) when the low-magnitude 

xc
Executive Summary 

bins are included with high weight, and much less variation (higher smoothing) in the case where 

the lower-magnitude bins are given low or zero weight. The variation resulting from the final set 

of weights reflects the TI Team’s assessment of the epistemic uncertainty in the spatial variation 

of recurrence parameters throughout the SSC model. 

The earthquake recurrence models for the RLME sources are somewhat simpler than those for 

distributed seismicity sources because the magnitude range for individual RLMEs is relatively 

narrow and their spatial distribution is limited geographically such that spatial variability is not a 

concern. This limits the problem to one of estimating the occurrence rate in time of a point 

process. The data that are used to assess the occurrence rates are derived primarily from 

paleoseismic studies and consist of two types: data that provide estimated ages of the 

paleoearthquakes such that the times between earthquakes can be estimated, and data that 

provide an estimate of the number of earthquakes that have occurred after the age of a particular 

stratigraphic horizon. These data are used to derive estimates of the RLME occurrence rates and 

their uncertainty. 

The estimation of the RLME occurrence rates is dependent on the probability model assumed for 

the temporal occurrence of these earthquakes. The standard model applied for most RLME 

sources in this study is the Poisson model, in which the probability of occurrence of an RLME in 

a specified time period is completely characterized by a single parameter, λ, the rate of RLME 

occurrence. The Poisson process is ―memoryless‖—that is, the probability of occurrence in the 

next time interval is independent of when the most recent earthquake occurred, and the time 

between earthquakes is exponentially distributed with a standard deviation equal to the mean 

time between earthquakes. For two RLME sources (Reelfoot Rift–New Madrid fault system and 

the Charleston source), the data are sufficient to suggest that the occurrence of RLMEs is more 

periodic in nature (the standard deviation is less than the mean time between earthquakes). For 

these RLME sources a simple renewal model can also be used to assess the probability of 

earthquake occurrence. In making an estimate of the probability of occurrence in the future, this 

model takes into account the time that has elapsed since the most recent RLME occurrence. 

The CEUS SSC model has been developed for use in future PSHAs. To make this future use 

possible, the SSC model must be combined with a GMC model. At present, the GMPEs in use 

for SCRs such as the CEUS include limited information regarding the characteristics of future 

earthquakes. In anticipation of the possible future development of GMPEs for the CEUS that will 

make it possible to incorporate similar types of information, a number of characteristics of future 

earthquakes in the CEUS are assessed. In addition to characteristics that might be important for 

ground motion assessments, there are also assessed characteristics that are potentially important 

to the modeling conducted for hazard analysis. Future earthquake characteristics assessed include 

the tectonic stress regime, sense of slip/style of faulting, strike and dip of ruptures, seismogenic 

crustal thickness, fault rupture area versus magnitude relationship, rupture length-to-width aspect 

ratio, and relationship of ruptures to source boundaries. 

Chapters 6 and 7 include discussions of the seismic sources that are defined by the Mmax zones 

and the seismotectonic zones branches of the master logic tree. Because of convincing evidence 

for their existence, both approaches include RLME sources. The rarity of repeated earthquakes 

relative to the period of historical observation means that evidence for repeated events comes 

xci
Executive Summary 

largely from the paleoseismic record. By identifying the RLMEs and including them in the SSC 

model, there is no implication that the set of RLMEs included is in fact the total set of RLMEs 

that might exist throughout the study region. This is because the presently available studies that 

locate and characterize the RLMEs have been concentrated in certain locations and are not 

systematic across the entire study region. Therefore, the evidence for the existence of the RLMEs 

is included in the model where it exists, but the remaining parts of the study region are also 

assessed to have significant earthquake potential, which is evidenced by the inclusion of 

moderate-to-large magnitudes in the Mmax distributions for every Mmax zone or seismotectonic 

zone. 

In Chapter 6, each RLME source is described in detail by the following factors: (1) evidence for 

temporal clustering, (2) geometry and style of faulting, (3) RLME magnitude, and (4) RLME 

recurrence. The descriptions document how the data have been evaluated and assessed to arrive 

at the various elements of the final SSC model, including all expressions of uncertainty. The 

Data Summary and Data Evaluation tables (Appendices C and D) complement the discussions in 

the text, documenting all the data that were considered in the course of data evaluation and 

integration process for each particular seismic source. 

Alternative models for the distributed seismicity zones that serve as background zones to the 

RLME sources are either Mmax zones or seismotectonic zones. The Mmax zones are described 

in Chapter 6 and are defined according to constraints on the prior distributions for the Bayesian 

approach to estimating Mmax. The seismotectonic zones are described in Chapter 7 and are 

identified based on potential differences in Mmax as well as future earthquake characteristics. 

Each seismotectonic zone in the CEUS SSC model is described according to the following 

attributes: (1) background information from various data sets; (2) bases for defining the 

seismotectonic zone; (3) basis for the source geometry; (4) basis for the zone Mmax (e.g., largest 

observed earthquake); and (5) future earthquake characteristics. Uncertainties in the 

seismotectonic zone characteristics are described and are represented in the logic trees developed 

for each source. 

For purposes of demonstrating the CEUS SSC model, seismic hazard calculations were 

conducted at seven demonstration sites throughout the study region, as described in Chapter 8. 

The site locations were selected to span a range of seismic source types and levels of seismicity. 

The results from the seismic hazard calculations are intended for scientific use to demonstrate the 

model, and they should not be used for engineering design. Mean hazard results are given for a 

range of spectral frequencies (PGA, 10 Hz, and 1 Hz) and for a range of site conditions. All 

calculations were made using the EPRI (2004, 2006) ground-motion models such that results 

could be compared to understand the SSC effects alone. Sensitivity analyses were conducted to 

provide insight into the dominant seismic sources and the important characteristics of the 

dominant seismic source at each site. The calculated mean hazard results are compared with the 

results using the SSC model from the 2008 U.S. Geological Survey national seismic hazard maps 

and the SSC model from the Combined Operating License applications for new nuclear power 

reactors. The hazard results using the CEUS SSC model given in Chapter 8 are reasonable and 

readily understood relative to the results from other studies, and sensitivities of the calculated 

hazard results can be readily explained by different aspects of the new model. The TI Team 

concludes that the SSC model provides reasonable and explainable calculated seismic hazard 

xcii
Executive Summary 

results, and the most important aspects of the SSC model to the calculated hazard (e.g., 

recurrence rates of RLME sources, recurrence parameters for distributed seismicity sources, 

Mmax) and their uncertainties have all been appropriately addressed. 

Presumably, the GMC model input to the PSHA calculations will be replaced in the future by the 

results of the ongoing NGA-East project. The calculated hazard at the demonstration sites in 

Chapter 8 comes from the regional CEUS SSC model and does not include any local refinements 

that might be necessary to account for local seismic sources. Depending on the regulatory 

guidance that is applicable for the facility of interest, additional site-specific studies may be 

required to provide local refinements to the model. 

To assist future users of the CEUS SSC model, Chapter 9 presents a discussion on the use of the 

model for PSHA. The basic elements of the model necessary for hazard calculations are given in 

the Hazard Input Document (HID). This document provides all necessary parameter values and 

probability distributions for use in a modern PSHA computer code. The HID does not, however, 

provide any justification for the values, since that information is given in the text of this report. 

Chapter 9 also describes several simplifications to seismic sources that can be made to increase 

efficiency in seismic hazard calculations. These simplifications are recommended on the basis of 

sensitivity studies of alternative hazard curves that represent a range of assumptions on a 

parameter’s value. Sensitivities are presented using the test sites in this study. For applications of 

the seismic sources from this study, similar sensitivity studies should be conducted for the 

particular site of interest to confirm these results and to identify additional simplifications that 

might be appropriate. For the seismic sources presented, only those parameters that can be 

simplified are discussed and presented graphically. The sensitivity studies consisted of 

determining the sensitivity of hazard to logic tree branches for each node of the logic tree 

describing that source. The purpose was to determine which nodes of the logic tree could be 

collapsed to a single branch in order to achieve more efficient hazard calculations without 

compromising the accuracy of overall hazard results. 

Finally, this report provides a discussion of the level of precision that is associated with seismic 

hazard estimates in the CEUS. This discussion addresses how seismic hazard estimates might 

change if the analysis were repeated by independent experts having access to the same basic 

information (geology, tectonics, seismicity, ground-motion equations, site characterization). It 

also addresses how to determine whether the difference in hazard would be significant if this 

basic information were to change and that change resulted in a difference in the assessed seismic 

hazard. This analysis was performed knowing that future data and models will continue to be 

developed and that a mechanism for evaluating the significance of that information is needed. 

Based on the precision model evaluated, if an alternative assumption or parameter is used in a 

seismic hazard study, and it potentially changes the calculated hazard (annual frequency of 

exceedence) by less than 25 percent for ground motions with hazards in the range 10–4

to 10–6, 

that potential change is within the level of precision at which one can calculate seismic hazard. It 

should be noted, however, that a certain level of precision does not relieve users from performing 

site-specific studies to identify potential capable seismic sources within the site region and 

vicinity as well as to identify newer models and data. Also, this level of precision does not 

relieve users from fixing any errors that are discovered in the CEUS SSC model as it is 

xciii
Executive Summary 

implemented for siting critical facilities. In addition, NRC has not defined a set value for 

requiring or not requiring siting applicants to revise or update PSHAs. 

Included in the report are appendices that summarize key data sets and analyses: the earthquake 

catalog, the Data Summary and Data Evaluation tables, the paleoliquefaction database, the HID, 

and documentation important to the SSHAC process. These data and analyses will assist future 

users of the CEUS SSC model in the implementation of the model for purposes of PSHA. The 

entire report and database will be provided on a website after the Final Project Report is issued. 

The TI Team, Project Manager, and Sponsors determined the approach for quality assurance on 

the CEUS SSC Project in 2008, taking into account the SSHAC assessment process and national 

standards. The approach was documented in the CEUS SSC Project Plan dated June 2008 and 

discussed in more detail in the CEUS SSC Report (Appendix L). Beyond the assurance of quality 

arising from the external scientific review process, it is the collective, informed judgment of the 

TI Team (via the process of evaluation and integration) and the concurrence of the PPRP (via the 

participatory peer review process), as well as adherence to the national standard referred to in 

Appendix L, that ultimately lead to the assurance of quality in the process followed and in the 

products that resulted from the SSHAC hazard assessment framework. 

xciv
October 24, 2011 

Cliff Munson 

Senior Technical Advisor 

Office of New Reactors 

U.S. Nuclear Regulatory Commission 

Washington, DC 20555 

Robert Roche 

Project Manager 

Office of Nuclear Regulatory Research 

U.S. Nuclear Regulatory Commission 

Washington, DC 20555 

 

Richard H. Lagdon, Jr. 

Chief of Nuclear Safety 

Office of the Under Secretary for Nuclear 

Security, S-5 

U.S. Department of Energy 

1000 Independence Avenue SW 

Washington, DC 20585 

Thomas P. Miller 

Senior Technical Advisor 

Office of Nuclear Energy, NE-72/GTN 

U.S. Department of Energy 

1000 Independence Avenue SW 

Washington, DC 20585 

 

Jeffrey F. Hamel 

Advanced Nuclear Technology Program 

Manager 

Electric Power Research Institute 

3420 Hillview Avenue 

Palo Alto, CA 94304 

Gentlemen: 

Reference: Central and Eastern United States Seismic Source Characterization for Nuclear 

Facilities Project: Participatory Peer Review Panel Final Report

Introduction 

This letter constitutes the final report of the PPRP1

 (“the Panel”) for the Central and Eastern 

United States Seismic Source Characterization for Nuclear Facilities Project (the “CEUS SSC 

Project” or “the Project”). The eight Panel members (Jon P. Ake, Walter J. Arabasz, William J. 

Hinze, Annie M. Kammerer, Jeffrey K. Kimball, Donald P. Moore, Mark D. Petersen, J. Carl 

Stepp) participated in the Project in a manner fully consistent with the SSHAC Guidance.2

 The 

Panel was actively engaged in all phases and activities of the Project’s implementation, including 

final development of the Project Plan and planning of the evaluation and integration activities, 

which are the core of the SSHAC assessment process. 

                                                       

1

 Participatory Peer Review Panel 

2

 Budnitz, R. J., G. Apostolakis, D. M. Boore, L. S. Cluff, K. L. Coppersmith, C. A. Cornell, and P. A. 

Morris, 1997. Recommendations for Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty

and the Use of Experts (known as the “Senior Seismic Hazard Analysis Committee Report,” or the

“SSHAC Guidance”). NUREG/CR-6372, U. S. Nuclear Regulatory Commission. TIC; 235076. 

Washington, DC. 

xix 

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PPRP Final Report, CEUS SSC PROJECT October 24, 2011 

xx

The Panel’s involvement, described more fully later in this letter, also included review of 

analyses performed by the Project to support the evaluation and integration processes, review of 

interim evaluation and integration products, and review of the interim draft project report and the 

final project report. Additionally, panel members participated in specific analyses as resource 

experts, and panel members were observers in or participated as resource experts in eight of the 

eleven Technical Integrator Team (TI Team) working meetings held to implement the integration 

phase of the assessment process. We want to express our appreciation for the opportunity to 

participate in the CEUS SSC Project in this way. 

In the remainder of this letter we provide our observations and conclusions on key elements of 

the project implementation process, and we summarize our reviews of the draft and final project 

reports. As we explain in our comments, assurance that the center, body, and range of the 

technically-defensible interpretations (“CBR of the TDI”)3 have been properly represented in the 

CEUS SSC Model fundamentally comes from implementing the structure and rigor of the 

SSHAC Guidance itself. We are aware that the SSHAC Guidance is accepted by the Nuclear 

Regulatory Commission and the Department of Energy for developing seismic hazard models 

that provide reasonable assurance, consistent with the seismic safety decision-making practices 

of these agencies, of compliance with their seismic safety policies and regulatory requirements. 

For these reasons, we describe aspects of the SSHAC Guidance to provide context for our 

observations and conclusions. 

Project Plan: Conformity to the SSHAC Assessment Process 

The SSHAC Guidance recognizes that observed data, available methods, models, and 

interpretations all contain uncertainties. These uncertainties lead to alternative scientific 

analyses and interpretations. In other words, experts in the broad technical community do not 

hold a single interpretation. Accepting this scientific situation, the SSHAC assessment process is 

designed to engage the scientific community in an orderly assessment of relevant data, methods, 

models, and interpretations that constitute current scientific knowledge as the basis for 

development of a seismic hazard model that represents the CBR of the TDI. 

The assessment process is carried out by means of two main activities: evaluation and

integration.

4

 In implementation, the evaluation activities are structured to inform the integration 

activities. The evaluations are carried out by means of workshops in which the TI Team engages 

proponents of alternative interpretations that represent the range of relevant current community 

knowledge. Resource experts in the various relevant data sets are also engaged. The workshops 

have the dual purposes of, first, evaluating the degree to which alternative interpretations are 

supported by observed data and, second, defining uncertainties in the degree to which the 

interpretations are defensible, given the observed data. Integration is carried out by individual 

evaluator experts or evaluator expert teams (Level 4 process) or by a Technical Integrator (TI) 

Team (Level 3 process) who, informed by the evaluation activities, characterize the range of 

                                                       

3 See Section 2.1 in the CEUS SSC Final Report for discussion of concepts relating to the center, body, 

and range of the “technically-defensible interpretations” vs. the center, body, and range of the “informed 

technical community.” 

4 For an excellent discussion of this two-stage process, see Practical Implementation Guidelines for 

SSHAC Level 3 and 4 Hazard Studies, USNRC NUREG-XXXX, Draft for Review, Office of Nuclear 

Regulatory Research, May 2011. 

xcvi
PPRP Final Report, CEUS SSC PROJECT October 24, 2011 

 xxi 

defensible alternative interpretations in an integrated hazard model and assess the scientific 

uncertainty distribution. Based on our review of the Project Plan and our subsequent discussions 

with the Project Team, we concurred that the Plan conformed with the SSHAC Guidance,

incorporating lessons learned from fourteen years experience using the Guidance, and that the 

planned implementation was structured to properly carry out the SSHAC assessment process for 

development of the CEUS SSC Model. 

SSHAC Level 3 Assessment Process 

The SSHAC Guidance describes implementation processes for four levels of assessment 

depending on the scientific complexity of the assessment and the intended use of the assessed 

hazard model. For an assessment such as the regional SSC model for the Central and Eastern 

United States, which will be used at many sites for making safety and licensing decisions for 

nuclear facilities, the SSHAC Guidance recommends using an assessment Level 3 or Level 4. 

There are process differences between a Level 3 and Level 4 implementation, but the objective is 

the same: to obtain from multiple proponent experts information that supports an informed 

assessment of the range of existent relevant interpretations and associated uncertainties that 

together represent current community knowledge and to perform an informed assessment of the 

CBR of the TDI. We understand that within the SSHAC assessment process “technically 

defensible” means that observed data are sufficient to support evaluation of the interpretation and 

the corresponding uncertainty. 

In a Level 4 assessment process a TI Team facilitates the assessment, identifying and engaging 

proponent and resource experts, performing supporting analyses, and conducting knowledge 

evaluation workshops and assessment integration working meetings. Multiple experts or teams 

of experts perform as evaluators of the range of existent interpretations and as integrators of the 

hazard model. The individual evaluator experts or evaluator expert teams take ownership of 

their individual or team assessments. In a Level 3 assessment all of these activities are 

consolidated under a single TI Team consisting of a TI Lead, multiple evaluator experts 

representing the scope of required scientific expertise, and experienced data and hazard analysts. 

As we noted earlier in this report, assurance that the CBR of the TDI is properly represented in a 

hazard model comes from rigorously implementing the SSHAC assessment process itself. We 

note that an important lesson learned from multiple implementations of the SSHAC Guidance

over the past fourteen years is that the Level 3 and Level 4 assessment processes provide 

comparably high assurance that the relevant scientific knowledge and the community uncertainty 

distribution are properly assessed and represented in the hazard model. The Level 3 assessment 

is significantly more integrated and cohesive and is more efficient to implement. These 

considerations led us to endorse use of the Level 3 assessment for implementation of the CEUS 

SSC Project in our Workshop No. 1 review letter. During the course of the Project we observed

that the higher level of cohesiveness inherent in the Level 3 assessment process leads to 

significantly improved communication, facilitating the experts’ performance of their technical 

work. 

xcvii
PPRP Final Report, CEUS SSC PROJECT October 24, 2011 

xxii

Overall Project Organization 

A complex project with multiple sponsors such as the CEUS SSC Project cannot be successful 

unless it is well organized and energetically managed so that the various participants understand 

the interconnectedness of their activities and perform their technical work as a cohesive group. 

In this regard the adopted project management structure allowed the Project Manager to provide 

integrated overall project leadership, manage the database development activities, and effectively 

maintain communication with the PPRP and project sponsors while allowing TI Team lead to 

concentrate on the structural and technical activities of the assessment as the Project unfolded. 

We conclude that the project organization was effective overall and particularly so with regard to 

facilitating the TI Team’s implementation of the assessment process. 

Implementing the SSHAC Level 3 Assessment Process 

Irrespective of the level of implementation, evaluation and integration are the main activities of a 

SSHAC assessment. The evaluation activities aim to identify and evaluate all relevant available 

data, models, methods, and scientific interpretations as well as uncertainties associated with each 

of them. The integration activities, informed by the evaluations, aim to represent the CBR of the 

TDI in a fully integrated SSC model. 

Evaluation 

Consistent with the SSHAC Guidance the evaluation phase of the CEUS SSC project 

accomplished a comprehensive evaluation of the data, models, methods, and scientific 

interpretations existent in the larger technical community that are relevant to the SSC model. In 

significant part the process was carried out in three structured workshops, each focusing on 

accomplishing a specific step in the evaluation process. 

The first workshop (WS-1) focused on evaluations of relevant geological, geophysical, and 

seismological datasets (including data quality and uncertainties) and on identification of hazardsignificant data and hazard-significant SSC assessment issues. It became clear that a number of 

issues relating to the earthquake catalog, the paleoliquefaction data set, the potential-field 

geophysical data, updating procedures for assessing maximum earthquake magnitude, and 

development of procedures for assessing earthquake recurrence would require focused analyses. 

These analyses were appropriately carried out within the TI Team working interactively with 

appropriate resource experts recognized by the larger scientific and technical community. 

WS-2 focused on evaluations of the range of alternative scientific interpretations, methods, and 

models within the larger scientific community and on corresponding uncertainties. WS-3 

focused on evaluations of hazard feedback derived at seven representative test locations using a 

preliminary CEUS SSC model. Specifically, the workshop focused on the identification of the 

key issues of most significance to completing the SSC model assessment. 

Experience has shown that evaluations to gain understanding of the quality of various data sets 

and uncertainties associated with them are essential for fully informing an SSC assessment. We 

observed that in WS-1 resource experts for the various data sets did a high-quality job of 

describing the data sets and giving their perspective about the data quality and associated 

uncertainties. We conclude that the understanding of data quality and uncertainties gained in 

WS-1 together with continued interactions between the TI Team and data resource experts 

xcviii
PPRP Final Report, CEUS SSC PROJECT October 24, 2011 

 

significantly informed the TI Team’s evaluations. The TI Team’s evaluations of the data quality 

and uncertainties are well documented in the innovative “Data Summary Tables” and “Data 

Evaluation Tables” included in the Project Report. Importantly, the TI Team continued to 

effectively engage data resource experts in productive analyses of potential-field geophysical 

data, the earthquake catalog, development of the paleoearthquake data set (including an 

integrated assessment of the paleoliquefaction data in order to extend the earthquake catalog), the 

development of methods for assessing maximum earthquakes, and the development of 

earthquake recurrence analyses. All of these focused analyses strongly informed the assessment 

process. Moreover, documentation of the analyses resulted in stand-alone products of the Project 

that will serve future users of the CEUS SSC Model.

The compilation and evaluation of potentially relevant methods, models, and alternative 

scientific interpretations representing the community knowledge and corresponding uncertainties 

must be considered the core process activity of any SSHAC assessment. This step was largely 

carried out in WS-2. Success in defining the community knowledge depends on fully engaging 

proponent experts representing the range of methods, models, and interpretations existent at the 

time. Full engagement means that the proponent experts completely and clearly describe their 

interpretations and the data that support them and provide their individual evaluations of 

corresponding uncertainties. We observed that the actions taken by the Project and TI Team to 

explain the workshop goals and to guide participants toward meeting those goals was very 

productive. We conclude that the workshop was highly successful in meeting the stated goals 

and that it fully met the expectation of the SSHAC Guidance with respect to evaluating the range 

of alternative scientific interpretations. The discussions during the workshop and between the TI 

Team and Panel following the workshop evolved the “SSC Framework” concept, which 

provided transparent criteria that framed the TI Team’s systematic identification and assessment 

of seismic sources throughout the CEUS. 

Feedback from hazard calculations and sensitivity analyses is an important step in a SSHAC 

assessment to understand the importance of elements of the model and inform the final 

assessments. For development of a regional SSC model to be used for site-specific probabilistic 

seismic hazard analyses (PSHAs) at many geographically distributed sites, feedback based on the 

preliminary model is particularly important. Following WS-2 a preliminary SSC model termed 

“the SSC sensitivity model,” was developed and used for hazard sensitivity calculations that 

were evaluated in WS-3. While the SSC sensitivity model was clearly preliminary, the 

evaluation of sensitivity results that took place in WS-3 provided important feedback for 

completing analyses and for supporting the TI Team’s development of the preliminary CEUS 

SSC model. The Panel was able to review the preliminary model and provide feedback in a 

subsequent project briefing meeting on March 24, 2010. 

Together the three workshops provided the TI Team interactions with the appropriate range of 

resource and proponent experts. These experts were carefully identified to present, discuss, and 

debate the data, models, and methods that together form the basis for assuring that the CBR of 

the TDI have been properly represented in the hazard model. Experts representing academia, 

government, and private industry participated. The TI Team also reached out to a wide range of 

experts as they developed the database and performed the integration activities to develop the 

SSC model. The Panel participated throughout this process, and is satisfied that the TI Team 

fully engaged appropriate experts to accomplish the goals of a SSHAC Guidance. 

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PPRP Final Report, CEUS SSC PROJECT October 24, 2011 

xxiv

Integration 

Consistent with the SSHAC Guidance, integration is the process of assessing the CBR of the TDI 

and representing the assessment in the SSC model. Informed by the evaluation process, the 

integration process includes representation of the range of defensible methods, models, and 

interpretations of the larger technical community together with new models and methods 

developed by analyses during the evaluation and integration process. 

For the CEUS SSC Project, development of the earthquake catalog, methods for assessing and 

representing maximum earthquake magnitudes, and methods for earthquake recurrence 

assessment continued during the integration process. The Panel reviewed all the analyses at 

various stages of development and provided comments and recommendations. The TI Team 

performed the integration process by means of eleven working meetings. Members of the Panel 

participated in most of these working meetings as observers or resource experts. The full Panel 

participated in the discussions during both feedback meetings and provided formal comments 

and recommendations following the meetings. We observed that the integration process was

thorough and that it acceptably complied with the SSHAC Guidance. Based on our participation 

and observations we conclude that the integrated CEUS SSC Model appropriately represents the 

center, body, and range of current methods, models and technically defensible interpretations. 

PPRP Engagement 

Consistent with the SSHAC Guidance, the Panel was fully engaged in peer-review interactions 

with the TI Team and the Project Manager of the CEUS SSC Project throughout the entire 

project period—from development of the Project Plan in early to mid 2008 through production of 

the Final Project Report in mid to late 2011.5 The Panel provided both written and oral peerreview comments on both technical and process aspects at many stages of the Project’s 

evolution. Key PPRP activities, leading up to this final report, have included: 

• Review of the Project Plan. 

• Formulation of a PPRP implementation plan, specifically for the CEUS SSC Project, to 

ensure adherence to the general guidance provided by SSHAC and NUREG-1563 for the 

scope and goals of a PPRP review. 

• Involvement in each of the three Project workshops, including advising in the planning 

stage; participating collectively as a review panel during the workshop (and individually 

as resource experts when requested by the TI Team), providing timely comments on 

technical and process issues; and submitting a written report of the Panel’s observations 

and recommendations following each workshop. 

• Development and implementation of a process, together with the TI Team, to document 

the resolution of recommendations made in PPRP formal communications. 

• Participation as observers (and occasionally as resource experts when requested by the TI 

Team) in eight of the TI Team’s 11 working meetings. 

• Peer-review and written comments, including several informal reports, on the TI Team’s 

intermediate work products, particularly early versions of the CEUS SSC Model. 

                                                       

5

 See CEUS SSC Final Report: Section 2.5, Table 2.2-1, and Appendix I 

c
PPRP Final Report, CEUS SSC PROJECT October 24, 2011 

 

• Direct interaction with the TI Team and Project Manager in more than 20 teleconferences 

and four face-to-face briefings—in addition to the three workshops and eight working 

meetings of the TI Team noted above. 

• Extensive, critical peer-review of the Project’s 2010 Draft Report and 2011 Final Report. 

The Panel, collectively and individually, fully understood the SSHAC Guidance for a structured 

participatory peer review and the requirements for a Level 3 assessment process; had full and 

frequent access to information and interacted extensively with the TI Team and Project Manager 

throughout the entire project; provided peer-review comments at numerous stages; and, as 

documented within the Final Project Report, was fully engaged to meet its peer-review 

obligations in an effective way. 

Project Report 

The SSHAC Guidance makes clear that adequate documentation of process and results is crucial 

for their understanding and use by others in the technical community, by later analysis teams, 

and by the project sponsors. The Panel understood what was needed to conform to the SSHAC 

requirements, and it was committed to ensuring that the documentation of technical details 

associated with the CEUS SSC Model in the Project Report was clear and complete. The Panel 

was equally committed to ensuring the transparency of process aspects of the project, both in 

implementation and in description in the Project Report. 

The Panel provided lengthy compilations of review comments (see Appendix I of the Project 

Report) for both the 2010 Draft Report and the 2011 Final Report. These included hundreds of 

comments, categorized as general, specific, relating to clarity and completeness, or editorial. 

The massive amount of detail provided by the TI Team in the Project Report and the 

intensiveness of the Panel’s review comments both reflect great diligence and a mutual 

understanding by the TI Team and the PPRP of the thoroughness and high quality of 

documentation expected in the Project Report. 

The Project Manager and the TI Lead provided review criteria to the Panel for both the draft and 

final versions of the Project Report. The criteria for reviewing the Draft Report6

 covered the 

range of technical and process issues consistent with requirements of the SSHAC Guidance, 

including draft implementation guidance (see footnote #4). Key criteria, among others, include 

sufficiency of explanatory detail; adequate consideration of the full range of data, models, and 

methods—and the views of the larger technical community; adequate justification of the data 

evaluation process, logic-tree weights, and other technical decisions; proper treatment of 

uncertainties; and conformance to a SSHAC Level 3 assessment process. To be clear, the PPRP 

is charged with judging the adequacy of the documented justification for the CEUS SSC Model 

and its associated logic-tree weights. The TI Team “owns” the Model and logic-tree weights. 

Criteria for reviewing the Final Report focused on reaching closure to comments made on the 

Draft Report and ensuring that no substantive issues remained unresolved. To that end, among 

its many review comments on the Final Report the Panel identified “mandatory” comments, 

which the TI Team was required to address in the final version of the Project Report. 

                                                       

6

 See PPRP report dated October 4, 2010, in Appendix I of CEUS SSC Final Report 

ci
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PROJECT ACKNOWLEDGMENTS 

This study was sponsored by the Electric Power Research Institute (EPRI) Advanced Nuclear 

Technology Action Plan Committee, the U.S. Department of Energy (DOE) Office of Nuclear 

Energy and Office of the Chief of Nuclear Safety, and the U.S. Nuclear Regulatory Commission 

(NRC) Office of Nuclear Regulatory Research. Technical experts from the DOE, NRC, U.S. 

Geological Survey, Defense Nuclear Facility Safety Board, industry, and academia participated 

in the study as part of the Technical Integration (TI) Team or as members of the Participatory 

Peer Review Panel (PPRP). Any statements, opinions, findings, conclusions, or 

recommendations expressed in this material are those of the authors and do not necessarily 

reflect those of the participating or sponsoring agencies. 

Jeffrey F. Hamel was the EPRI Advanced Nuclear Technology Program Manager. Lawrence A. 

Salomone of Savannah River Nuclear Solutions, LLC, served as the Project Manager for the 

study. Kevin J. Coppersmith of Coppersmith Consulting Inc., served as the lead for the TI Team. 

J. Carl Stepp of Earthquake Hazards Solutions, and Walter J. Arabasz, Research Professor 

Emeritus of Geology and Geophysics at the University of Utah, served as Co-chairmen for the 

PPRP. The entire Central and Eastern United States Seismic Source Characterization Project 

Team and their roles are discussed in Section 2 and are shown on the project oganization chart 

(Figure 2.3-1) of the report. 

The authors of the report wish to acknowledge the contributions of the following people: the 

resource experts who participated in Workshop 1, the proponent experts who participated in 

Workshop 2, and the technical experts who provided valuable insights, perspective, and 

references throughout the study. The names of all these contributors are listed in Table 2.2-2. 

In addition, the authors of the report appreciate the support of Geraldine Moore-Butler as 

administrative assistant and Nancy L. Sutherland as technical editor for the project. This report 

was assembled at AMEC. 

ciii
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SPONSORS’ PERSPECTIVE 

This report describes a new seismic source characterization model for the Central and Eastern 

United States (CEUS) for use in probabilistic seismic hazard analysis (PSHA) for nuclear 

facilities. PSHA has become a generally accepted procedure for supporting seismic design, 

seismic safety and decision making for both industry and government. Input to a PSHA consists 

of seismic source characterization (SSC) and ground motion characterization (GMC); these two 

components are necessary to calculate probabilistic hazard results (or seismic hazard curves) at a 

particular geographic location. 

The 1986 Electric Power Research Institute and Seismicity Owners Group (EPRI-SOG) study 

included both an SSC and GMC component. Recent applications for new commercial reactors 

have followed U.S. Nuclear Regulatory Commission (NRC) regulatory guidance (RG 1.208) by 

using the EPRI-SOG source model as a starting point and updating it as appropriate on a sitespecific basis. This CEUS SSC Project has developed a new SSC model for the CEUS to replace 

the SSC component of the EPRI-SOG study. 

The CEUS SSC Project was conducted using a Senior Seismic Hazard Analysis Committee 

(SSHAC) Level 3 process, as described in the NRC publication, Recommendations for 

Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and Use of Experts 

(NUREG/CR-6372). The goal of the SSHAC process is to represent the center, body, and range 

of technically defensible interpretations of the available data, models, and methods. The CEUS 

SSC model is applicable to any site within the CEUS and can be used with the EPRI 2004/2006 

GMC model to calculate seismic hazard at any site of interest. Long-term efforts to replace the 

EPRI 2004/2006 GMC model with the Next Generation Attenuation Relationships for Central 

and Eastern North America obtained from the NGA-East Project is scheduled for completion in 

2014. 

The updated CEUS SSC model provides industry and government with the following: a new 

model for the commercial nuclear industry to perform PSHAs for future reactor license 

applications; the NRC to support its review of early site permit (ESP) and construction and 

operating license (COL) applications; and the U.S. Department of Energy (DOE) to support 

modern PSHAs to meet design and periodic review requirements for its current and future 

nuclear facilities. Specific benefits of the model are as follows: 

Consistency: For many sites, seismic sources at distances up to 300 km (186 mi.) or more 

significantly contribute to hazard at some spectral frequencies. Consequently, seismic hazard 

models for many sites have significant geologic overlap. If done separately, there is a 

likelihood of conflicting assessments for the same regions. A regional source model allows 

for consistent input into a PSHA. An updated conceptual SSC framework that provides a 

cv
Sponsors’ Perspective

consistent basis for identifying and characterizing seismic sources in the CEUS has been 

developed. The NRC will no longer need to review each time each applicant’s regional SSC

model when the accepted CEUS SSC model is used. This will avoid lengthy review of the 

regional SSC model in ESP and COL applications for sites within the CEUS that use the 

accepted regional CEUS SSC model to develop its site-specific SSC model. 

Stability: This CEUS SSC model was developed using the accepted state-of-practice 

SSHAC methodology that involved the following tasks: 

o Development of a comprehensive database and new tools for documenting the data 

consideration process. 

o Multiple workshops to identify applicable data, debate alternative hypotheses, and 

discuss feedback. 

o Multiple working meetings by the Technical Integration (TI) Team to develop the SSC 

model and fully incorporate uncertainties. 

o Technical advancements in a number of areas, such as developing a uniform earthquake 

catalog, developing an updated approach for assessing maximum magnitude, compiling 

data evaluation tables, incorporating paleoseismic data, and using spatial smoothing 

tools. 

o Participatory peer review, including four panel briefings, multiple interactions, and 

periodic formal feedback. 

o Proper documentation of all process and technical aspects of the project. 

Experience has shown that stability is best achieved through proper and thorough 

characterization of our knowledge and uncertainties, coupled with the involvement of the 

technical community, regulators, and oversight groups. 

Greater Longevity: An explicit goal of the SSHAC methodology is to represent the center, 

body, and range of the technically defensible interpretations of the available data, models,

and methods. Using the SSHAC process provides reasonable assurance that this goal has 

been achieved. Representing the center, body, and range of interpretations at the time of the 

study means that as new information is acquired and various interpretations evolve as a 

result, the current thinking at any point is more likely to be addressed in the study. As new 

information becomes available, an existing SSC will require periodic reviews to evaluate the 

implications of the new findings. The need for updates to a particular study is now better 

understood as a result of findings of the CEUS SSC Project sensitivity studies to determine 

the significance of source characteristics. 

Cost and Schedule Savings: The CEUS SSC model can be used to perform a PSHA at any 

geographic location within the CEUS. It is applicable at any point within the CEUS, subject 

to site-specific refinements required by facility-specific regulations or regulatory guidance. 

Having stable, consistent input into a regional PSHA will reduce the time and cost required 

to complete a commercial nuclear site’s ESP or COL licensing application, prepare a DOE 

site’s PSHA, and develop design input for new commercial and DOE mission-critical nuclear 

facilities.

cvi
Sponsors’ Perspective 

cvii 

 Advancement of Science: The CEUS SSC Project provides new data, models, and methods. 

This information was shared at three workshops with international observers as a means to 

provide technology transfer for application in other regions. The CEUS SSC earthquake 

catalog, which merges and reconciles several catalogs and provides a uniform moment 

magnitude for all events, and the CEUS SSC paleoliquefaction database provide a new 

baseline for future research and updates. New approaches used in this project for spatial 

smoothing of recurrence parameters, assessment of maximum magnitude, and systematical 

documentation of all data considered and evaluated also benefit future research and PSHA 

updates. 

The sponsors of the CEUS SSC Project are utilities and vendors on the EPRI Advanced Nuclear 

Technology Action Plan Committee, the DOE Office of Nuclear Energy, the DOE Office of the 

Chief of Nuclear Safety, and the NRC Office of Nuclear Regulatory Research. Technical experts 

from the DOE, NRC, U.S. Geological Survey (USGS), and Defense Nuclear Facility Safety 

Board (DNFSB) participated in the study as part of the TI Team or as members of the 

Participatory Peer Review Panel (PPRP). 

The product of the CEUS SSC Project is a robust peer-reviewed regional CEUS SSC model for 

use in PSHAs. This model will be applicable to the entire CEUS, providing an important 

baseline for future research and updates. The CEUS SSC Project demonstrates that a SSHAC 

Level 3 approach can achieve the goals of considering the knowledge and uncertainties of the 

larger technical community within a robust and transparent framework. The value of the new 

CEUS SSC model has been enhanced by the participation of key stakeholders from industry, 

government, and academia who were part of the CEUS SSC Project Team. 

Looking forward, the NRC will publish NUREG-2117 (2012), Practical Implementation 

Guidelines for SSHAC Level 3 and 4 Hazard Studies that provides SSHAC guidance on the need 

to update a regional model. The guidance covers updating both regional and site-specific 

assessments. It addresses the “refinement” process of starting with a regional model and refining 

it for site-specific applications. 
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ABBREVIATIONS 

AD anno domini (in the year of the Lord) 

AFE annual frequency of exceedance 

AIC Akaike information criterion 

ALM Alabama-Louisiana-Mississippi (zone of possible paleoseismic features) 

AM Atlantic Margin (seismotectonic zone) 

AHEX Atlantic Highly Extended Crust (seismotectonic zone) 

ANSS U.S. Advanced National Seismic System 

ANT Advanced Nuclear Technology 

APC Action Plan Comittee 

BA Blytheville arch 

BC before Christ 

BCFZ Big Creek fault zone 

BFZ Blytheville fault zone 

BL Bootheel lineament 

BMA Brunswick magnetic anomaly 

BP before present 

BPT Brownian passage time 

BTP Branch Technical Position 

CAD computer-aided design

cix
Abbreviations 

CBR center, body, and range 

CCFZ Crittenden County fault zone 

CDZ Commerce deformation zone 

CENA Central and Eastern North America

CERI Center for Earthquake Research and Information 

CEUS Central and Eastern United States 

CFZ Commerce fault zone 

CFR Code of Federal Regulations 

CGL Commerce geophysical lineament 

CGRGC Cottonwood Grove–Rough Creek graben 

CI confidence interval 

CNWRA Center for Nuclear Waste Regulatory Analysis 

COCORP Consortium for Continental Reflection Profiling 

COCRUST Consortium for Crustal Reconnaissance Using Seismic Techniques 

COL combined construction and operating license 

COLA combined operating license application 

COMP composite prior, composite superdomain 

CON contemporary (with earthquake occurrence) 

COV coefficient of variation 

CPT cone penetration test 

CVSZ Central Virginia seismic zone 

D&G Dewey and Gordon (1984 catalog) 

DEM digital elevation model 

cx
Abbreviations 

DNFSB Defense Nuclear Facilities Safety Board 

DOE U.S. Department of Energy 

DWM Division of Waste Management 

ECC Extended Continental Crust 

ECC-AM Extended Continental Crust–Atlantic Margin (seismotectonic zone) 

ECC-GC Extended Continental Crust–Gulf Coast (seismotectonic zone) 

ECFS East Coast fault system 

ECFS-C East Coast fault system—central segment 

ECFS-N East Coast fault system—northern segment 

ECFS-S East Coast fault system—southern segment 

EC-SFS East Coast–Stafford fault system 

ECMA East Coast magnetic anomaly 

ECRB East Continent rift basin 

ECTM Eastern Canada Telemetered Network 

E[M] expected moment magnitude listed in the CEUS SSC catalog for an earthquake 

ENA eastern North America 

EP Eau Plain shear zone 

EPRI Electric Power Research Institute 

EPRI-SOG Electric Power Research Institute–Seismicity Owners Group 

ERM Eastern rift margin 

ERM-N Eastern rift margin—north

ERM-RP Eastern rift margin—river (fault) picks 

ERM-S Eastern rift margin—south

cxi
Abbreviations 

ERM-SCC Eastern rift margin—south/Crittenden County 

ERM-SRP Eastern rift margin—south/river (fault) picks 

ERRM Eastern Reelfoot Rift Margin 

ESP early site permit 

ESRI Environmental Systems Research Institute 

ETSZ Eastern Tennessee seismic zone 

EUS Eastern United States 

FAFC Fluorspar Area fault complex 

FGDC Federal Geographic Data Committee 

ft foot or feet 

FTP file transfer protocol 

ft/s feet per second 

ft/yr feet per year 

FWLA Fugro William Lettis & Associates 

FWR Fort Wayne rift 

Ga billion years ago 

GC Gulf Coast 

GCVSZ Giles County, Virginia, seismic zone 

GHEX Gulf Coast Highly Extended Crust (seismotectonic zone) 

GIS geographic information system 

GLTZ Great Lakes tectonic zone 

GMC ground-motion characterization (model) 

GMH Great Meteor Hotspot (seismotectonic zone) 

cxii
Abbreviations 

GMPE ground-motion prediction equation 

GMRS ground-motion response spectra 

GPR ground-penetrating radar 

GPS global positioning system 

GSC Geological Survey of Canada 

Gyr gigayears (109 years) 

HF Humboldt fault 

HID hazard input document 

I0 maximum intensity 

IAEA International Atomic Energy Agency

IBEB Illinois Basin Extended Basement (seismotectonic zone) 

IPEEE Individual Plant Examination for External Events 

IRM Iapetan rifted margin 

ISC International Seismological Centre 

ITC informed technical community 

ka thousand years ago 

K-Ar potassium-argon 

km kilometer(s) 

km2 square kilometer(s) 

km/sec kilometers per second 

K-S Kijko-Sellevoll 

K-S-B Kijko-Sellevoll-Bayes 

kyr thousand years 

cxiii
Abbreviations 

LDO Lamont-Doherty Earth Observatory (catalog) 

LHS Latin hypercube sampling 

LLNL Lawrence Livermore National Laboratory 

ln(FA) logarithm of felt area (with felt area measured in km2) 

LS least squares 

LSA La Salle anticlinal belt 

LWLS locally weighted least squares 

m meter(s) 

M magnitude 

M, MW moment magnitudes 

Ma million years ago 

MAR Marianna (RLME source) 

mb body-wave magnitude (short period) 

mbLg body-wave magnitude determined from higher-mode (Lg) surface waves

MC coda magnitude 

MCMC Markov Chain Monte Carlo 

MD duration magnitude 

MESE Mesozoic and younger extended crust 

MESE-N Mesozoic-and-younger extended crust or Mmax zone that is ―narrow‖

MESE-W Mesozoic-and-younger extended crust or Mmax zone that is ―wide‖

mi. mile(s) 

mi.2 square mile(s) 

MIDC midcontinent 

cxiv
Abbreviations 

MidC Midcontinent-Craton (seismotectonic zone) 

Mfa felt-area magnitude 

ML local magnitude 

Mmax, Mmax maximum magnitude 

MMI modified Mercalli intensity 

mm/yr millimeters per year 

MN Nuttli magnitude 

Mo Scalar seismic moment 

MRS Midcontinent rift system 

m/s meters per second 

MS surface-wave magnitude 

MSF Meeman-Shelby fault 

Mw 

Myr million years 

NAD83 North American Datum of 1983 

NAP Northern Appalachian (seismotectonic zone) 

Nd neodymium 

NEDB National Earthquake Database 

NEI Nuclear Energy Institute 

NEIC National Earthquake Information Center 

NF Niagara fault zone 

NMESE Non-Mesozoic and younger extended crust

NMESE-N Mesozoic-and-younger extended crust or Mmax zone that is ―narrow‖

cxv
Abbreviations 

NMESE-W Mesozoic-and-younger extended crust or Mmax zone that is ―wide‖

NMFS New Madrid fault system 

NMN New Madrid North fault 

NMS New Madrid South fault 

NMSZ New Madrid seismic zone 

NN New Madrid north (fault segment as designated by Johnston and Schweig, 1996) 

NOAA National Oceanic and Atmospheric Administration 

NPP nuclear power plant(s) 

NR Nemaha Ridge 

NRC U.S. Nuclear Regulatory Commission 

NRHF Nemaha Ridge–Humboldt fault

NSHMP National Seismic Hazard Mapping Project 

NW New Madrid west (fault segment as designated by Johnston and Schweig, 1996) 

OKA Oklahoma aulacogen (seismotectonic zone) 

OKO Oklahoma Geological Survey Leonard Geophysical Observatory (catalog) 

OSL optically stimulated luminescence 

Pa probability of activity (of being seismogenic) 

PEZ Paleozoic Extended Crust (seismotectonic zone) 

PGA peak ground acceleration 

PM Project Manager 

PPRP Participatory Peer Review Panel 

PSHA probabilistic seismic hazard analysis 

PVHA probabilistic volcanic hazard analysis 

cxvi
Abbreviations 

RCG Rough Creek graben 

RF Reelfoot fault 

RFT Reelfoot thrust (fault) 

RLME repeated large-magnitude earthquake (source) 

RR Reelfoot rift zone 

RS Reelfoot South (fault segment) 

SA spectral acceleration 

SCL St. Charles lineament 

SCML south-central magnetic lineament 

SCR stable continental region 

SCSN South Carolina Seismic Network 

SEUS Southeastern United States (catalog) 

SEUSSN Southeastern United States Seismic Network 

SGFZ Ste. Genevieve fault zone 

SHmax maximum horizontal stress, compression, or principal stress 

SLR St. Lawrence rift (seismotectonic zone) 

SLTZ Spirit Lake tectonic zone 

SLU Saint Louis University (catalog) 

SNM Sanford et al. (2002 catalog) 

SOG Seismicity Owners Group 

SPT standard penetration test 

SRA Stover, Reagor, and Algermissen (1984 catalog) 

SRTM Shuttle Radar Topography Mission 

cxvii
Abbreviations 

SSC seismic source characterization 

SSE safe shutdown earthquake 

SSHAC Senior Seismic Hazard Analysis Committee 

Str&Tur Street and Turcotte (1977 catalog) 

SUSN Southeastern United States Network 

TC technical community 

TFI technical facilitator/integrator 

TI technical integration 

USGS U.S. Geological Survey 

USNSN U.S. National Seismograph Network 

UTC Coordinated Universal Time 

VP/VS ratio of P-wave velocity to S-wave velocity 

WES Weston Observatory (catalog) 

WIPP Waste Isolation Pilot Project 

WQSZ Western Quebec seismic zone 

WRFZ White River fault zone 

WUS Western United States 

WVFS Wabash Valley fault system 

WVSZ Wabash Valley seismic zone 

WWSSN World-Wide Standardized Seismograph Network 

cxviii
5-1 

5

CHAPTER 5 

SSC MODEL: OVERVIEW AND METHODOLOGY 

5.1 Overview of Spatial and Temporal Models 

The heart of any SSC model for PSHA is a description of the future spatial and temporal 

distribution of earthquakes. The earliest PSHA models identified seismic source zones within 

which the spatial distribution of earthquakes was assumed to be uniform. The temporal 

distribution of earthquakes was assumed to follow a Poisson process, and the sizes of 

earthquakes within the zones were assumed to follow an exponential distribution. In more 

tectonically active areas such as the WUS, the recognition of active faults allowed the spatial 

models to evolve such that they were able to include the fault sources as well as the background 

source zones within which they lie. Further, the development of fault-specific paleoseismic data 

regarding the timing, amount of slip per earthquake, and geologic slip rate provided a new class 

of temporal models that could use this information directly in the PSHA. 

In the meantime, the evolution of spatial and temporal models within stable continental regions 

(SCRs) such as the CEUS has taken place differently and more slowly. Despite continued 

geologic investigations, the search for the causative faults giving rise to observed seismicity has 

yielded very few cases where a definitive argument can be made for having identified an active 

fault in the sense that this is commonly identified in the WUS. With notable exceptions such as 

the Meers fault and the Cheraw fault, the best-defined cases of localized seismicity and 

deformation occur in the New Madrid region, where individual fault-like sources can be called 

out and characterized. Even in locales such as Charleston, where geologic and geophysical 

studies have continued over the decades, uncertainties persist regarding the unique association of 

the observed historical seismicity and the one or more causative faults that are responsible. 

5.1.1 Spatial Model Considerations 

Continued analysis of the historical seismicity record and network monitoring by regional and 

local seismic networks has led to acceptance within the community that the general spatial 

patterns of observed small-to-moderate magnitude earthquakes provide predictive information 

about the spatial distribution of future large-magnitude earthquakes. The analyses leading to this 

conclusion have focused on whether the observed patterns of earthquakes have varied through 

time; therefore, in effect, this is an assessment of whether small- to moderate-magnitude 

earthquakes have been relatively stationary through time. Studies such as those by Kafka (2007, 

2009) suggest that this has generally been the case and that we can with some level of confidence 

use the spatial pattern of smaller earthquakes to predict the future pattern of smaller earthquakes. 
Chapter 5 

SSC Model: Overview and Methodology 

5-2 

However, the available data on larger-magnitude earthquakes and their relationship to the spatial 

distribution of smaller earthquakes based on the observed record is quite limited and not 

sufficient to allow an empirical spatial model to arrive at such a conclusion with confidence. We 

have some cases like Charlevoix and New Madrid where a spatial concentration of smallermagnitude earthquakes is occurring generally within the region of larger historical earthquakes. 

However, we also have counter-examples like the Eastern Tennessee seismic zone, which is 

defined by a highly concentrated zone of small to moderate earthquakes without any larger 

events in the historical record. Likewise, the Charleston region is associated with a pattern of 

observed seismicity that is not particularly remarkable for drawing attention to the location of the 

1886 earthquake. 

Perhaps the most dramatic finding in recent years is paleoseismic evidence for the occurrence of 

prehistoric large-magnitude earthquakes in the CEUS. For obvious reasons, the earliest 

paleoseismic studies occurred in the locales of large historical earthquakes (e.g., New Madrid, 

Charleston), and subsequent studies moved to other regions (e.g., Wabash Valley, Charlevoix, 

Eastern Tennessee). With a few exceptions, the paleoseismic information developed at these 

locations appears to be related to secondary shaking effects such as liquefaction rather than 

observed fault displacements. As a result, uncertainties exist about both the locations and sizes of 

the earthquakes. Detailed studies of historical and instrumental earthquakes, and liquefaction 

phenomena associated with them, coupled with field and laboratory studies of geotechnical 

properties, are leading to a stronger technical basis for placing limits on the locations of 

paleoearthquakes interpreted by the distribution of liquefaction phenomena and for defining their 

magnitudes. In some cases, the paleoseismic evidence for repeated large-magnitude earthquakes 

is so compelling that the TI Team has concluded that a RLME source must be included in the 

SSC model. In other cases, there is suggestive evidence of potential liquefaction earthquakes, 

such as the postulated Alabama-Louisiana-Mississippi (ALM) zone. In that situation, 

consideration is given to possible evidence for a prehistoric earthquake, but inclusion as an 

RLME source is not warranted (see Section 7.3.9 for a discussion). The establishment of several 

RLME sources as spatial components of the CEUS SSC model is an important advancement over 

previous studies and reflects the evolution taking place within the technical community. 

Notwithstanding the locations of RLME sources, the spatial distribution of distributed seismicity 

sources has advanced in PSHA based largely on the assumption of spatial stationarity, as 

discussed in Section 5.3.2.1 of this report. For example, the EPRI-SOG project and the U.S. 

National Seismic Hazard Mapping Project (Petersen et al., 2008) use different approaches to 

“smooth” observed seismicity to provide a map that expresses the future spatial pattern of 

seismicity. In reality, the a-values, or rates per unit area, and b-values are subject to the 

smoothing operation, and various calculation approaches are carried out. Because of the support 

in the community for these approaches to representing the future spatial distribution of 

seismicity, they have been explored thoroughly as part of the CEUS SSC Project. Various 

adaptive kernels were evaluated along with the penalized maximum-likelihood approach that is a 

refinement of the approach used in the EPRI-SOG project. The refined approach subdivides the 

region into one-quarter-degree cells and specifies the degree of “communication” between 

adjacent cells. As discussed in Section 5.3.1, the approach was selected because, although it is 

based on the same conceptual model of spatial stationarity as the kernel approach, it offers the 
Chapter 5 

SSC Model: Overview and Methodology 

5-3 

ability to allow for spatial variability in both a- and b-values, and it was found to provide 

comparable results to the adaptive kernel when a constant b-value was assumed. 

5.1.2 Considerations Regarding Temporal Models 

For purposes of SSC model assessments, the “temporal” issue concerns both the sizes of future 

earthquakes as well as their frequency of occurrence (average rate and aperiodicity). With time 

and study the earthquake research community in the WUS has developed information that 

suggests that the assumption of an exponential distribution of magnitudes may not be appropriate 

for individual faults. Poissonian models are memoryless and do not incorporate information 

about the timing or size of prior earthquakes. Studies of fault displacements, including the timing 

and displacement per event, and physical notions of strain accumulation and release provide 

information for modeling where a source currently resides in the seismic cycle. Such “real-time” 

and “renewal” models have found their way into some SSC model assessments where the 

dominant sources are highly active plate-boundary faults. 

In contrast to plate-boundary SSC models, the fundamental information source for the 

assessment of temporal models in the CEUS is the catalog of historical and instrumental 

earthquakes. Though uneven in coverage and incomplete back through time, the catalog is the 

cornerstone for assessing recurrence rates for most seismic sources in the CEUS. Thus, 

significant effort was devoted to developing an earthquake catalog for the CEUS SSC Project

with moment magnitudes for all earthquakes and for analyzing its completeness as a function of 

time and location. Beyond the catalog, in the CEUS, the modeling of temporal behavior has 

benefited most from paleoseismic investigations at the RLME sources. An ever-increasing 

database of paleoliquefaction studies, which have been compiled as part of the CEUS SSC 

Project (Appendix E), provides information on the approximate sizes and timing of largemagnitude events. In effect, these studies extend the historical observations back a few thousand 

years. Despite their uncertainties, the studies provide clues about the nature of the repeated 

pattern of larger earthquakes through time at individual seismic sources. A number of studies 

conducted within SCRs including the CEUS have concluded that large earthquakes are not 

evenly spaced in time, but rather occur as “clusters” of earthquakes that are separated from other 

clusters by long “intercluster” periods of quiescence. 

For each RLME source, the available data were evaluated in order for the TI Team to assess 

whether temporally clustered behavior has been observed and, if so, whether the source is 

currently within or outside of a temporal cluster. In either case, the temporal behavior is modeled 

as a Poisson process. The TI Team further evaluated the available data to assess whether the 

application of a renewal model would be appropriate for the RLME sources. The physical 

underpinning of a renewal model is a quasi steady state loading process applied to a fault. These 

models have been given relatively high weight in characterizing earthquake occurrences on plate 

boundary faults, even though there may not be a well-developed paleoseismic history (e.g., 

Working Group, 2003). Two of the RLME sources defined by the TI team have reasonably welldeveloped paleoseismic histories: New Madrid and Charleston. However, the physical process of 

steady state loading being applied to these sources is more problematic. In addition, the specific 

causative faults associated with the New Madrid RLME sources are only moderately understood 

and the fault or faults associated with the Charleston RLME source are poorly understood. 
Chapter 5 

SSC Model: Overview and Methodology 

5-4 

Therefore, giving due consideration to the larger technical community’s views regarding 

recurrence models for these RLME sources, the TI team concluded that applying the renewal 

model to these two RLME sources should have some weight, although it is relatively low. For all 

of the other RLME sources, the available data were judged not to be sufficient to allow for the 

application of such models with any confidence. The methodology for characterizing RLME 

recurrence is given in Section 5.3.3 and the specific data and recurrence assessments related to 

the Charleston and New Madrid RLME sources are given in Sections 6.1.2 and 6.1.5, 

respectively. 

For distributed seismic source zones, the earthquake catalog provides the fundamental basis for 

assessing recurrence and, as described previously, for describing its future spatial distribution. 

Consistent with common practice in the assessment of seismicity within large seismic sources, 

the observed seismicity is assessed to follow a truncated exponential magnitude distribution (e.g. 

Cornell and Van Marke, 1969) and Poissonian behavior. 

5.1.3 Perspective on CEUS SSC Models 

At the time of the preparation of this report, there were a number of promising research areas 

pertaining to spatial and temporal models that had not reached the level where they could be 

included in the SSC model with confidence. Examples include models proposed as part of the 

ongoing debate on “characteristic” earthquakes or, simply stated, the tendency for a specific fault 

to generate earthquake magnitudes that are not exponentially distributed in magnitude. The TI 

Team reviewed this continuing dialogue within the community, but concluded that the models 

were not applicable to the kinds of sources being characterized in the CEUS. Models of faultspecific behavior were not judged to be applicable in the CEUS unless and until seismogenic 

faults were identified and data regarding their behavior was gathered. Rather, the intent of the 

RLME sources is to model only the recurrence of repeated large earthquakes in a specific 

location. As such, the RLME sources represent a source of seismic hazard that is in addition to 

the hazard resulting from the occurrence of distributed seismicity modeled by the distributed 

seismicity sources. The addition of the RLME recurrence with that derived from observed 

seismicity within the distributed seismicity sources allows for a departure from the general 

truncated exponential recurrence behavior in specific locations. This simple approach to 

incorporating the data available in the CEUS is described in Sections 5.3.3.4 and 6.1. 

Another area of ongoing research with potential implications for recurrence behavior relates to 

geodetic strain rate measurements. No doubt, the systematic gathering of geodetic data 

throughout the CEUS for purposes of identifying and analyzing tectonic strain is crucial for the 

understanding of contemporary deformation processes. Its importance is acknowledged and its 

promise in the decades ahead is undeniable. However, in 2010, the CEUS technical community’s 

understanding of the meaning of a short-term (few decades) strain signal relative to seismic 

source characteristics is embryonic. The spatial distribution and temporal stability of such strains 

is not known, and there is no clear method for translating these strain signals into spatial and 

temporal SSC models. One need only witness the ongoing debates in the WUS on the 

discrepancies between long-term geologic slip rates and short-term geodetic strain rates to lose 

confidence that, in the complete absence of geologic slip rates, the geodetic results can be used. 
Chapter 5 

SSC Model: Overview and Methodology 

5-5 

As a corollary, the types of analyses carried out in the WUS to “test” the reasonableness of a 

seismic source model are generally not applicable in the CEUS. For example, the integrated 

moment rate derived for a region from the summed fault slip rates (derived from geologic 

studies) cannot be developed and, as a result, cannot be compared to the observed moment rate 

for the same region based on the seismicity record. Likewise, given the generally sparse geodetic 

networks and short period of observation, the uncertainties in attempting to compare the 

recurrence rates for seismic sources derived from seismicity with those developed from geodetic 

data are unacceptably large. It is acknowledged in this report that local well-studied areas such as 

the central New Madrid region may eventually provide clues or even constraints on the temporal 

behavior of seismic sources. Research in these areas is encouraged, but the current data do not 

allow for direct incorporation into the CEUS SSC model. 

5.2 Maximum Earthquake Magnitude Assessment 

This section describes the methodology that was used in the CEUS SSC Project to assess Mmax 

for all seismic sources. Estimating Mmax in SCRs such as the CEUS is highly uncertain despite 

considerable interest and effort by the scientific community over the past few decades. Mmax is 

defined as the upper truncation point of the earthquake recurrence curve for individual seismic 

sources, and the typically broad distribution for any given source reflects considerable epistemic 

uncertainty. Because the maximum magnitude for any given seismic source in the CEUS occurs 

rarely relative to the period of observation, the use of the historical seismicity record provides 

important but limited constraints on the magnitude of the maximum event. At annual frequencies 

of interest for conventional buildings (approximately 10–2 to 10–3/yr), the hazard results are 

usually not particularly sensitive to the maximum magnitude. However, at annual frequencies of 

interest for nuclear facilities (10–3 to 10-7), the influence of Mmax can be very significant. For 

this reason, focus on the Mmax issue has been driven by PSHAs conducted for nuclear facilities. 

In view of the importance of Mmax revealed by the EPRI-SOG project (EPRI, 1988), a major 

study sponsored by EPRI was carried out in the early 1990s to attempt to quantify the knowledge 

and uncertainties in Mmax for purposes of PSHA (Johnston et al., 1994). The approach 

advocated in the EPRI Mmax study is based on analogies between the CEUS and other SCR 

areas. To develop the analogies, two key activities needed to be conducted: (1) development of a 

worldwide seismicity catalog of moderate to large earthquakes with systematic moment 

magnitudes for all events, and (2) identification and characterization of the regions worldwide 

that can be considered analogous tectonically to the CEUS. The results of those efforts were the 

first of their kind and led to considerable advances in the research (e.g., Johnston, 1996a). 

The EPRI Mmax study also focused on the use of a Bayesian procedure for estimating Mmax, in 

which the prior distribution is based on the earthquake magnitudes of events that occurred 

worldwide within tectonically analogous regions. At the time the study was conducted, there was 

considerable focus on the occurrence of large earthquakes within formerly rifted or extended 

crust. For example, the 1811-1812 New Madrid earthquakes were interpreted to have occurred 

within the Reelfoot rift, which exhibits evidence of multiple episodes of extension but is 

currently within a compressive stress regime. Despite the anecdotal evidence for the occurrence 

of the largest SCR earthquakes within extended crust, the statistical analyses in Johnston et al. 

(1994) did not provide strong evidence that any particular tectonic characteristic—or 
Chapter 5 

SSC Model: Overview and Methodology 

5-6 

combination of characteristics—is correlated with maximum earthquake size. The best 

correlations at the time suggested that sites of major Paleozoic and younger extension appeared 

to have the potential for a larger Mmax (i.e., a higher mean of the prior distribution), but the 

analyses also indicated that the standard deviation of the prior distribution was larger. 

From the beginning of the CEUS SSC Project, the TI Team pursued the refinement and 

application of the Bayesian Mmax approach (Johnston et al., 1994). An evaluation of alternative 

approaches to assessing Mmax in the CEUS (Wheeler, 2009) concluded that the Bayesian Mmax 

approach, as well as other approaches that were based on tectonic analogues, was worthy of 

pursuit within the technical community. The Bayesian Mmax approach has the advantage that it 

provides a quantitative and repeatable process for assessing Mmax. The approach is described 

below in Section 5.2.1.1 along with the updates to the Johnston et al. (1994) characterization of 

Mmax for SCRs. The TI Team also explored alternative approaches for the assessment of Mmax 

that provide quantitative and repeatable results, and the team identified the approach developed 

by Kijko(2004) as a viable alternative. In his evaluation of statistical approaches for estimating 

Mmax, Wheeler (2004) noted that problems of small samples and rare large earthquakes 

continue to hinder testing of statistical models in SCRs. Nevertheless, the Kijko (2004) approach 

requires fewer assumptions than the Bayesian approach in that it uses only the observed 

earthquake statistics for the source, but this is offset by the need for a relatively larger data 

sample in order to get meaningful results. The Kijko (2004) approach is described in Section 

5.2.1.2. 

5.2.1 Approaches to Mmax Estimation in the CEUS 

The CEUS SSC model incorporates two types of seismic sources: RLME sources and 

distributed-seismicity source zones of various types. The RLME sources are characterized by 

their sizes and recurrence rates derived primarily from the paleoseismic record and, despite 

variations in the seismic source zone configurations, are assumed to always exist in the model. 

RLME sources include those in the New Madrid area, Wabash Valley, Charleston, Charlevoix, 

and Meers fault, among others. Because of the independent constraints on earthquake size, those 

constraints are used to estimate the magnitudes of RLMEs, and the assessment of Mmax 

discussed here is not applicable to RLME sources. Rather, this discussion is applicable to the 

distributed-seismicity source zones, which exist in different forms depending on whether the 

Mmax zones or the seismotectonic zones branches of the master logic tree are being followed. 

The assessment of Mmax for distributed seismicity sources (source zones) in the CEUS SSC 

Project has been designed to incorporate the uncertainties in both the conceptual models and the 

parameter values associated with each model. Based on the review and evaluation of the 

Bayesian method and consideration of other methods that exist within the larger technical 

community, it was decided that the assessment would need to include alternative conceptual 

models for Mmax. In particular, it was decided that alternative prior distributions should be 

considered for the Bayesian approach, and that an alternative to the Bayesian approach should be 

considered. 

The TI Team decided to use two alternative approaches as a basis for estimating the Mmax 

distributions for distributed seismicity sources: (1) the Bayesian procedure, which uses the prior 
Chapter 5 

SSC Model: Overview and Methodology 

5-7 

distributions from an update and evaluation of the global SCR data; and (2) the Kijko (2004) 

procedure, which uses the observed seismicity within a region to provide a direct (or posterior) 

assessment of Mmax. The Bayesian approach is representative of a category of approaches that 

rely on drawing analogies to tectonically comparable regions in order to estimate the Mmax for 

the source of interest. These approaches are based on the ergodic assumption that one can 

substitute time (the short period of observation) for space (other SCRs). The Kijko approach is 

representative of an alternative category of models that rely on the observations of seismicity 

entirely within the zone of interest. Because the occurrence of Mmax is typically rare relative to 

the period of observation, these approaches assume a particular frequency distribution of 

earthquake sizes and, to be able to apply them with confidence to larger or very active regions, 

rely on significant numbers of observed earthquakes to provide stable estimates. 

Both the Bayesian and Kijko approaches have their pros and cons. They both have the positive 

attribute that they are repeatable given the same data and that they can readily be updated given 

new information. The Bayesian approach is arguably more stable because of the use of a prior 

distribution that, even in the absence of a significant number of earthquakes in the zone of 

interest, can still provide a result. However, the prior distributions for Mmax are developed 

based on analogies to other “tectonically comparable” regions, which can be a source of 

uncertainty, and based on evaluation of those regions relative to a highly uncertain set of 

characteristics that are postulated to be important to Mmax. The advantage of the Kijko approach 

is that it does not require the identification of analogue regions or assessments of the 

characteristics of those regions. However, as applied the approach relies on the assumption that 

the distribution of earthquake magnitudes follows a doubly truncated exponential distribution. 

Moreover, the approach does not provide stable results when the number of observed 

earthquakes is low. 

From the standpoint of their specific use in the CEUS SSC model, there are other considerations 

in evaluating the two approaches. The key difference between the Kijko approach and the 

Bayesian approach is that the Kijko approach does not have a prior distribution; it uses only the 

earthquakes within the source of interest. The prior distribution is based on analogies to other 

parts of the world and the assumption that those events are applicable to the estimation of 

maximum magnitudes within the source of interest. A potential problem is that the global SCR 

database includes earthquakes from RLME sources (e.g., New Madrid, Charleston, and perhaps 

others worldwide that we suspect might have RLMEs). In the CEUS SSC model, however, the 

Bayesian approach is being applied to non-RLME sources, so we are possibly overestimating 

Mmax by using RLMEs globally to develop our prior distributions. The Kijko approach has 

some appeal because, by definition, it uses only data from the CEUS and only the earthquake 

catalog that does not include RLMEs. Care must be taken to avoid instability due to small 

numbers of earthquakes, but this can be accomplished by examining the statistics of the 

calculations, as provided for in the Kijko approach, and by giving the approach less weight when 

numbers of events are too low for stable estimates. Also, the seismic sources of interest in the 

CEUS SSC model tend to be larger regions with a significant number of earthquakes, thus 

mitigating the likelihood of instability. 
Chapter 5 

SSC Model: Overview and Methodology 

5-8 

The application of the Bayesian and Kijko approaches to assessing Mmax for the CEUS SSC 

Project is described below in Sections 5.2.1.1 and 5.2.1.2. The approach to weighting the 

alternative approaches for particular seismic sources is described in Section 5.2.1.3. 

5.2.1.1 Bayesian Mmax Approach 

The Bayesian Mmax approach is illustrated on Figure 5.2.1-1. The approach is based on 

estimating Mmax by drawing analogies to regions that are comparable to the CEUS (i.e., SCRs) 

and using that information to establish prior distributions on Mmax for distributed seismicity 

sources (source zones) in the CEUS. Part (a) of Figure 5.2.1-1 shows the prior distribution 

developed by Johnston et al. (1994) for extended continental crust. The prior distribution is then 

updated with source-specific information about the number and sizes of observed earthquakes. 

The update is expressed as a likelihood function, part (b) of Figure 5.2.1-1, which is zero for all 

values below the maximum observed magnitude, has a peak near the maximum observed, and 

then becomes essentially constant at larger magnitudes. The prior distribution is then convolved 

with the likelihood function to arrive at a posterior distribution of Mmax, shown in part (c) of the 

figure. The continuous posterior distribution is then represented by a discrete distribution for use 

in hazard analysis, as shown in part (d). 

The likelihood function used to update the prior is derived from the earthquake recurrence model 

applied to the source region. The model used in this study is an exponential distribution for the 

sizes of earthquakes occurring with a source region. This is the standard model applied to regions 

where multiple individual sources contribute to the occurrence of earthquakes. The likelihood 

function for possible values of Mmax, mu

, based on the exponential model is (e.g., Johnston, 

1994) is

[ ] { } obs

u N u

obs

u

u

mmb mm

mm

mL

−

−

−

−− − ≥

<

=

0 max

max

for ))(10ln(exp1

0 for 

[ ] (5.2.1-1) 

where b is the Gutenberg-Richter b-value, N is the number of recorded earthquakes with 

magnitudes equal to or larger than a minimum value m0, and mmax−obs is the largest recorded 

earthquake. The likelihood function has two effects on the prior. The first is to truncate the lower 

tail of the prior distribution at the value of the maximum observed earthquake. The shape of the 

likelihood function is controlled by the value of N, the number of earthquakes between m0 and 

mmax−obs . In most cases, the value of N is small such that the likelihood function is relatively flat 

with a small peak at mu

 equal to mmax−obs , as shown in part (b) of Figure 5.2.1-1. As a result, the 

primary effect is to produce a posterior distribution with a similar shape to the prior, as shown in 

part (c) of Figure 5.2.1-1. When N becomes large, the likelihood function becomes very peaked 

at mmax−obs and has a major effect on the prior distribution. Figure 5.2.1-2 repeats the example of 

Figure 5.2.1-1 with the value of N increased from 2 to 10. In this case, the posterior distribution 

also becomes very peaked near mmax−obs . It is important to note that the influence of size of N is 

relative to the magnitude range m0 to mmax−obs . Because of the exponential distribution of 

magnitude sizes, increasing N by reducing m0 for a given value of mmax−obs has no effect on the 
Chapter 5 

SSC Model: Overview and Methodology 

5-9 

likelihood function as long as the increase in N is consistent with the b-value of the source 

region. 

Because typical applications involve small values of N, the shape of the posterior Mmax 

distribution is similar to that of the prior. Thus, specification of the prior distribution is of 

primary importance in defining the Mmax distribution. The Johnston et al. (1994) Mmax prior 

distributions were developed from a study of SCR earthquakes. The process involved 

subdividing the SCR into tectonic domains on the basis of characteristics such as crustal 

extension, crustal age, age of major deformation, state of stress, and orientation of predominant 

structural grain relative to stress. A catalog of SCR earthquakes was developed in which moment 

magnitudes were assessed for each earthquake. The SCR earthquake catalog was then used to 

assess the largest observed earthquake in each domain. The mean and standard deviation of these 

values for specified subsets of the SCR domains provided normal distributions for mmax−obs . The 

last step in converting the distribution for mmax−obs into a prior distribution for mu

 was to make a 

bias correction to account for the fact that mmax−obs is in nearly all cases less than mu

. The bias 

correction is based on the assumption that the size distribution of earthquakes in a source region 

corresponds to a truncated exponential distribution between a specified minimum magnitude m0

and the maximum magnitude for the region, mu

. Using this assumption, the cumulative 

probability distribution for the largest earthquake in a sample of size N given a specified value of 

mu

 is (Johnston et al., 1996):

{ }

{ } u

obs

N

u

obs

obs mmm

mmb

mmb mF ⎥ ≤≤

⎦

⎤ ⎢

⎣

⎡

−− −

−− − = −

−

− 0 max

0

max 0

max for 

))(10ln(exp1

)(10ln(exp1 ) [ ] (5.2.1-2) 

Figure 5.2.1-3 shows median (50th percentile) values of mmax−obs as a function of mu

 and N. 

These values were used to make a bias adjustment from mmax−obs to mu

 by selecting a value of mu

such that the median value of the maximum observed, mmax−obs ˆ , equals the actual observed value. 

An example is illustrated on Figure 5.2.1-3 for the case in which the value of mmax−obs equal to 

5.7 for a sample size of 10 earthquakes equal to or larger than m0 of 4.5. The N = 10 curve shown 

on Figure 5.2.1-3 indicates that a mu

 value of 6.3 produces a value of mmax−obs ˆ equal to 5.7. Thus 

a magnitude of 6.3 represents the bias-adjusted value of mu

 for the source. 

The relationships shown on Figure 5.2.1-3 indicate that for a given value of N, the value of 

mmax−obs ˆ reaches an asymptotic level as mu increases. Thus it is not possible to make meaningful 

bias corrections for large values of mmax−obs unless the sample size is large. This fact led Johnston 

et al. (1994) to use domain pooling to increase the sample size. Tectonic domains that had the 

same characteristics (e.g., same type of crust, same age, same state of stress) were combined into 

a “superdomain” under the assumption that the common set of characteristics would correlate 

with a common value of mu

. The mean value of mmax−obs in a set of superdomains was then biasadjusted to produce a mean value of mu

 using the average sample size in the superdomains. This 

bias adjusted value of mu

 along with the standard deviation of mmax−obs was used as a prior 

distribution for Mmax. 
Chapter 5 

SSC Model: Overview and Methodology 

5-10 

Given the importance of the prior distribution in most applications of the Bayesian Mmax 

approach, the CEUS SSC Project focused its efforts on development of updated prior 

distributions. This involved updating the SCR data sets and performing new statistical analyses. 

The SCR data sets used to develop the Johnston et al. (1994) Mmax prior distributions consist of 

the SCR earthquake catalog and the set of SCR domains. The SCR earthquake catalog was 

updated for this study. The principal source for this update was the catalog published by Schulte 

and Mooney (2005) that extended the SCR catalog of Johnston et al. (1994) from the end of 1990 

to the end of 2003 as well as added additional earthquakes for the earlier time period identified in 

the literature. Earthquakes occurring in SCRs for the period 2004 through 2008 were added from 

the Harvard Moment Tensor (HMT) catalog. All earthquakes were assigned moment magnitudes 

and magnitude uncertainties based on the values given in Johnston et al. (1994) and Schulte and 

Mooney (2003). These values were updated using the relationships and assessments presented in 

Johnston (1996a, 1996b) as well as data from the CEUS SSC catalog for earthquakes in the 

CEUS. Moment magnitudes from the HMT catalog were assigned a nominal uncertainty of 0.1-

magnitude unit standard deviation. Moment magnitudes for specific earthquakes, such as the 

1811-1812 New Madrid sequence and the 1886 Charleston earthquake, were assigned according 

to the current literature. Appendix K presents the updated SCR earthquake catalog. 

Updating the basis for Johnston et al.’s (1994) division of the SCR crust into 255 tectonic 

domains was beyond the scope of this project. However, the assignments of age, stress state, and 

stress structure angles to the 255 SCR domains were reviewed and updated using recent 

information. Appendix Table K-2 lists the 255 SCR domains defined by Johnston et al. (1994) 

and the updated domain characteristics defined for each. The boundaries of these domains are 

included in the Project database. 

The updated SCR catalog was then used to assess the value of mmax−obs for each domain and the 

sample size N representing the number of earthquakes ≥ M 4.5. Following the approach of 

Johnston et al. (1994), an equivalent sample size corrected for completeness is obtained for each 

domain. Johnston et al. (1994) estimated catalog completeness intervals for various portions of 

the SCR. These were used to define the completeness-corrected equivalent earthquake count for 

each domain based on the catalog completeness period for magnitudes equal to mmax−obs . The 

typical case is that for magnitudes smaller than mmax−obs the catalog completeness periods are 

shorter than those for mmax−obs . Assuming that earthquake occurrence rates are stationary in time 

for the period covered by the catalog, then the maximum likelihood estimate of the rate of 

earthquakes of magnitude mi is given by the number of earthquakes, N(mi) in the completeness 

period for mi divided by the length of the completeness period, TC(mi). An estimate of the total 

number of earthquakes of the smaller magnitude that would have been recorded in the 

completeness period for mmax−obs is then given by the estimated rate of occurrence for magnitude 

mi multiplied by TC( mmax−obs ): 

)(

)( )( max

Completene Corrected ss )(T periodIn C

iC

C obs

i m mT

mT N Nm i

− = × (5.2.1-3) 
Chapter 5 

SSC Model: Overview and Methodology 

5-11 

The values of )( NCompletene Corrected ss mi are then summed to provide the completeness-corrected 

sample size for each domain. These values are listed in Appendix Table K-2. 

The updated domain data set was then used to assess appropriate prior distributions. The first 

step reviewed was the development of the superdomains by pooling domains with the same 

characteristics. Johnston et al. (1994) found that separation of the domains into extended and 

non-extended crust was the most meaningful initial classification. They then used other domain 

characteristics to develop superdomains within these two classes. For the non-extended crust 

domains, the characteristics used were crustal age, stress state, and whether the predominant 

structures within a domain are favorably oriented with respect to stress (labeled as source stress 

angle). These three attributes were used to group the 146 non-extended domains into a small 

number of superdomains. The characterization of the extended crust domains included additional 

factors such as the type of crust adjacent to the domain, the presence or absence of cross 

structures, and the presence or absence of multiple features. These additional characteristics were 

used by Johnston et al. (1994) to assign the 109 extended domains to superdomains. The result of 

using more characteristics to define extended crust superdomains was to increase the number of 

possible superdomains at the expense of reducing the sample size in each. Therefore, it was 

decided to use the same three characteristics—age, stress, and source stress angle—as the basis 

for defining both extended and non-extended superdomains. This provided a consistent basis for 

superdomain definition and also increased the average sample size in the extended 

superdomains. The result was 15 active (i.e., containing earthquakes) non-extended 

superdomains and 15 active extended superdomains. Figure 5.2.1-4 shows histograms of mmax−obs

for the extended and non-extended superdomains. 

The significance of the extended and non-extended superdomain classifications was examined by 

comparing the statistics of mmax−obs for the two classes. The results indicated that the extended 

and non-extended superdomain sites had similar mean values of mmax−obs . Applying a Student’s 

t-test (with the Welsh modification for unequal variances) to compare the two samples yielded a 

very high probability (p-value) of 0.99 that the two populations from which the samples were 

drawn (extended superdomains and non-extended superdomains) have the same mean. This 

suggested that the classification scheme for Mmax priors for extended and non-extended crust 

needed to be revisited. 

Examination of the values of mmax−obs in the extended crust superdomain set suggested that the 

larger values of mmax−obs occurred in the domains with Mesozoic and younger ages. Accordingly, 

an alternative grouping of superdomains was tested in which extended superdomains of 

Mesozoic and younger ages formed one group, designated MESE, and the older extended and the 

non-extended superdomains formed the second group, designated NMESE. Figure 5.2.1-5 shows 

histograms of mmax−obs for these two sets of superdomains. Application of the Student’s t-test to 

these two samples yielded a lower p-value of 0.46, suggesting that it is more likely that the two 

populations have different mean values. 

Building on the concept that a relatively young age of extension is an important factor, a new age 

classification was assigned to each extended domain based on the age of the most recent 
Chapter 5 

SSC Model: Overview and Methodology 

5-12 

extension episode. These age assignments are listed in Appendix Table K-2. The resulting sets of 

superdomains containing the Mesozoic and younger extended superdomains (MESE) are listed 

in Table 5.2.1-1, and those containing older extended and non-extended superdomains (NMESE) 

are listed in Table 5.2.1-2. Figure 5.2.1-6 shows histograms of mmax−obs for the revised 

superdomains. Using these two classifications resulted in a further reduction in the p-value 

obtained from the Student’s t-test to 0.31. 

An additional step taken was to remove from the samples those superdomains for which the 

stress classification is “Unknown” as it is likely that they would be classified as either 

compressive or extensive with more data. The “Unknown” source–stress angle classification was 

retained because it includes cases where there is no clear structural grain in the domain. In 

addition, superdomains made up of a single domain or those with a single earthquake were 

removed, assuming that the information was too limited to assess mmax−obs for these cases. The 

set of superdomains used in the final test are flagged in Tables 5.2.1-1 and 5.2.1-2. 

Figure 5.2.1-7 shows histograms of mmax−obs for this final set of superdomains. Application of the 

Student’s t-test to these two samples yielded a p-value of 0.09, indicating a reasonable likelihood 

that the mean mmax−obs values for the two populations are different. 

The fact that the computed p-value for the two samples listed in Table 5.2.1-1 is not as low as 

conventional values used to indicate statistical significance (e.g., a value of 0.05) indicates that in 

fact the distinction between Mesozoic and younger extension and older extension and nonextension is not important to the assessment of Mmax. Therefore, a second grouping of domains 

into superdomains was performed using only age, stress, and source stress angle. The resulting 

composite superdomains (COMP) are listed in Table 5.2.1-3 and the assignment of each of the 

domains to these combined superdomains is indicated on Appendix Table K-2. Figure 5.2.1-8 

shows a histogram of mmax−obs for the combined superdomains. 

The remaining step in computing the priors was to compute the mean and standard deviation of 

mmax−obs and perform a bias correction to adjust the mean of mmax−obs to the mean of mu. The SCR 

catalog contains many earthquakes whose moment magnitudes were estimated from 

macroseismic data and are, therefore, subject to considerable uncertainty. It is important to 

capture the impact of this uncertainty on the estimates of the mean and standard deviation of 

mmax−obs . The process used to compute the statistics of mmax−obs for each group of superdomains is 

as follows. 

The updated SCR catalog was used to construct an earthquake catalog for each superdomain. As 

discussed in Section 3.3.1, it is important to take into account the background distribution for 

earthquake size in computing the statistics of earthquake sizes. Assuming that earthquake size 

conforms to a truncated exponential distribution, then the density function for earthquake 

magnitude is exponential in shape— mf m)exp()( M ∝ −β , where β is the Gutenberg-Richter 

b-value expressed in natural log units [β = b×ln(10)]. If it is assumed that uncertainty in the 

observed value of magnitude can be represented by a normal distribution, ),(~ | ˆ MNf σ MM , then 

using Bayes’s Theorem, the distribution for the true size of an observed earthquake is 

proportional to the product of the normal and exponential distributions. The result is a normal 
Chapter 5 

SSC Model: Overview and Methodology 

5-13 

distribution centered on the expected magnitude E[M] given by Equation 3.3-5 (repeated below 

for ease of reference). 

] ˆ [ ˆ ][ E −= βσ2 MMMM (5.2.1-4) 

In Equation 5.2.1-4, Mˆ is the observed value of magnitude for the earthquake and σ is the 

standard deviation of the estimate. Thus, for the case of direct observation of moment magnitude 

from data, the effect is to shift the expected value of the true magnitude from Mˆ to E[M] by the 

amount 2 − βσ . However, as discussed in Section 3.3.1, the estimation of moment magnitude 

using regressions against other size measures (other magnitude scales or shaking intensity 

measures) directly produces the estimate E[M]. This situation applies to the majority of the 

earthquakes in the SCR database. The magnitudes listed in Table K-1 are values of E[M]. In the 

cases where the magnitudes were estimated from correlations with other size measures, then the 

values listed in Table K-1 are taken directly from the source. In the case where actual moment 

magnitudes are observed, then E[M] is obtained using Equation 5.2.1-4. The value of β used was 

estimated from the combined catalog of earthquakes in the superdomains, allowing for 

differences in the rate of activity and average catalog completeness among the superdomains. 

Using the values of E[M] and σ[M] for earthquakes in the SCR database, a catalog of 

earthquakes associated with each superdomain was simulated and the statistics of mmax−obs for the 

superdomain set was computed. The simulation process was repeated 10,000 times to generate a 

composite estimate of the mean and standard deviation of mmax−obs for the three sets of 

superdomains listed in Tables 5.2.1-1, 5.2.1-2, and 5.2.1-3. The results are listed in Table 

5.2.1-4. The mean values of mmax−obs were then adjusted to a mean value of mu

 by applying the 

bias correction process given by Equation 5.2.1-2 and illustrated on Figure 5.2.1-9. The average 

sample sizes and b-values for each group of superdomains are also listed in Table 5.2.1-3. Figure 

5.2.1-9 shows the three bias adjustment curves and Table 5.2.1-4 lists the resulting values of 

mean mu

. After evaluation the results of the above analysis, as well as considering the meaning 

of prior distributions, it was assessed that the uncertainty in assigning prior distributions for 

maximum magnitude to the CEUS sources should incorporate two alternative conceptual 

models: a “two-priors” distribution model and a “single-prior” (composite) distribution model. 

These alternatives are described below. 

5.2.1.1.1 Two-Priors Distribution Model 

The results of the updated statistical analysis show that the most significant separation of the 

SCR database is between superdomains that show Mesozoic-and-younger extension and those 

that do not. The data used are based on the domains in the SCR database, defined by their most 

recent age of extension and known characteristics of tectonic stress, and on those superdomains 

with more than one domain and more than a single earthquake. This subdivision shows 

reasonable statistical significance (i.e., there is a relatively low p-value of 0.09, indicating that 

based on the difference in the mean values, there is a low probability that the two data sets came 
Chapter 5 

SSC Model: Overview and Methodology 

5-14 

from the same data population), but the statistical significance is not strong. Using the biasadjusted values listed in Table 5.2.1-4, the Mmax priors for the “two-prior” model are as follows: 

 Mean Mmax Sigma

Mesozoic and younger extension (MESE): 7.35 0.75 

Non-Mesozoic and younger extension (NMESE): 6.70 0.61 

These prior distributions are assigned to the applicable Mmax zones of the CEUS SSC study 

area, whose boundary and uncertainty have been appropriately accounted for in the SSC model 

(Section 6.2.1). Also, each seismotectonic zone is assigned one of these prior distributions (or 

both are assigned with associated weights) to obtain its appropriate prior distributions. 

5.2.1.1.2 Composite-Prior Distribution Model 

This model assumes that a single, composite-prior distribution is appropriate throughout the 

region covered by the CEUS SSC seismic source model. The composite prior represents the 

concept that the characteristics within SCRs that control Mmax cannot be identified with 

confidence, despite our considerable effort to do so. Therefore, the only distinction made is that 

the applicable global database must be from SCRs (as defined in Johnston et al., 1994), but no 

subdivisions are imposed beyond that. This alternative conceptual model is consistent with the 

relatively weak statistical significance of any subdivision of the SCR as indicators of Mmax. 

Using the values listed in Table 5.2.1-4, the prior distribution for the composite data set is as 

follows: 

 Mean Mmax Sigma 

Composite (COMP): 7.20 0.64 

5.2.1.1.3 Relative Weights 

The “two-priors” model is assessed to have slightly higher weight (0.6) than the “compositeprior” model (0.4). Higher weight reflects the fact that there is some statistical significance to the 

separation of the data into the two Mmax zones, as well as an expectation that the locations of 

geologically recent crustal extension should have ample faults of sufficient dimensions for larger 

earthquakes. However, a stronger weight than 0.6 is not assessed because the statistical 

significance of the separation is not strong and could only be evaluated after multiple domains 

were combined into superdomains to increase sample size for statistical evaluation. 

5.2.1.1.4 Truncation of the Prior Distributions 

The Mmax prior distributions described above are represented by unbounded normal 

distributions. However, there is likely an upper limit to the size of earthquakes that can occur in 

the CEUS and a bound on the minimum size of the maximum magnitude, as well. 

The upper tail of the maximum magnitude distributions for all distributed seismicity seismic 

sources is truncated at M 81⁄4. This value is selected primarily on the basis of empirical data. M 8 
Chapter 5 

SSC Model: Overview and Methodology 

5-15 

1⁄4 envelopes the largest magnitude events ever recorded in SCRs. The largest events reported in 

the SCR earthquake database include the 1668 M 7.87 Yellow Sea China earthquake, the M 7.8 

New Madrid earthquake, and the 1819 M 7.8 Kutch earthquake (Appendix K). M 81⁄4 also 

approximates the largest crustal earthquakes recorded anywhere in the world outside of 

subduction zones, including the 1905 Mw 8.1-8.5 Bulnay earthquake (375 km rupture length) 

(Prentice et al., 2010), the 1949 M 8.1 Queen Charlotte earthquake (300–490 km rupture length) 

(Bostwick, 1984; Rogers, 1986), and the 1957 M 8.0–8.1 Gobi Altay earthquake (260 km 

rupture length; Prentice et al., 2010). The estimated rupture lengths for these earthquakes are 

comparable to or significantly longer than the rupture lengths of the largest strike-slip crustal 

earthquakes included in the Wells and Coppersmith (1994) and Hanks and Bakun (2002) 

worldwide databases that are used to develop empirical relationships for magnitude and fault 

rupture parameters. The Bulnay earthquake is poorly recorded, and estimates of magnitude are 

based on physical dimensions of the rupture (M 8.1, Schwartz et al., 1998) and analysis of 

historical Wiechert seismograms (M 8.2–8.5; Schlupp and Cisternas, 2007). Published 

magnitude estimates for the 1957 Gobi Altay earthquake range from M 7.8–8.3 (Prentice et al., 

2010), with a preferred value of M 8.1 (USGS Earthquake Database, 2010; Choi et al., 2009). 

Based on these empirical observations of the largest crustal events that have occurred anywhere 

in the world, our estimate of M 81⁄4 as the upper-bound truncation of the maximum magnitude 

distribution reasonably captures the epistemic uncertainty in maximum magnitude. This value is 

larger than the magnitude of any observed SCR earthquakes. 

The prior distributions are also truncated at the minimum magnitude that is assessed to be 

technically defensible, given a consideration of the observed magnitudes of earthquakes that 

have occurred with SCRs worldwide. Review of the values ofmmax−obs listed in Tables 5.2.1-1, 

5.2.1-2, and 5.2.1-3 for the superdomains used to develop the prior distributions indicates a 

minimum value of 5.5. Conceptually, this value should be increased slightly by the bias 

adjustment described above. However, bias adjustments are typically small at these low 

magnitudes (Figure 5.2.1-9). In addition, the parameter being assessed is the minimum of a 

distribution, which should be below the minimum observed. Therefore, it was assessed that an 

appropriate lower truncation point for the prior distributions is M 51⁄2. 

5.2.1.1.5 Addressing Criticism of the Bayesian Approach 

Kijko et al. (2009) have criticized the use of the Bayesian approach for estimation of Mmax as 

producing results that are biased low. They demonstrate the issue by performing sumilations of 

catalogs of earthquakes generated from an exponential distribution with a known Mmax (set at 

the mean of a hypothetical Mmax prior distribution) and then estimating the Mmax using the 

posterior distribution generated from the product of the prior with the sample likelihood function 

(e.g., the lower right-hand plots on Figures 5.2-1 and 5.2-2). Discussions with the lead author (A. 

Kijko, pers. comm., 2011) indicate that Kijko et al. (2009) use the mode of the posterior as the 

point estimate of Mmax. However, the application of the Bayesian Approach for Mmax 

estimation in the CEUS SSC Project uses the full posterior distribution. A better point estimate 

of this result is the mean of the posterior rather than the mode. The effect of the use of the mode 

versus the mean can be clearly seen by comparing the posterior distributions on Figures 5.2.1-1 

and 5.2.1-2. On Figure 5.2.1-1, the sample size is small and the posterior distribution has a shape 

very similar to the prior with only a minor shift in the mode. The shift in the mean between the 
Chapter 5 

SSC Model: Overview and Methodology 

5-16 

prior and the posterior is even less. On Figure 5.2.1-2, the sample size is large and the likelihood 

function has dramatically affected the shape of the posterior such that the mode occurs at the 

maximum observed value. However, the posterior distribution does extend to magnitudes larger 

than the maximum observed such that the mean would be a larger value. 

The effect of use of the mode of the posterior, as in Kijko et al. (2009), versus the mean of the 

posterior, a more appropriate point estimate of the results used in the CEUS SSC Project, is 

illustrated on Figure 5.2.1-10. A prior distribution for maximum magnitude with a mean of 6.9 

and a standard deviation of 0.5 was assumed. Various size samples of exponentially distributed 

earthquakes were then simulated from an exponential distribution of magnitudes truncated at the 

mean of the prior, 6.9. For each sample the likelihood function was used to develop a posterior 

distribution. The mean and the mode of this posterior were then computed. The process was 

repeated for 1000 simulations of each sample size. The average values of the mean and mode for 

each sample size are plotted on Figure 5.2.1-10. These results confirm the conclusion of Kijko et 

al. (2009) that the mode of the posterior is a biased estimate of Mmax, with the bias to smaller 

values. However, the mean of the posterior does not display any significant bias. Therefore, it is 

concluded that the application of the Bayesian approach using the full posterior distribution 

should not lead to biased estimates of Mmax. 

5.2.1.1.6 Application to CEUS Distributed Seismicity Sources 

The application of the Bayesian Mmax approach requires development of the likelihood function 

Equation 5.2.1-1 from the assessment of the maximum observed earthquake in each source and 

the number of earthquakes larger than a specified minimum magnitude. The assessment of these 

parameters was based on the project earthquake catalog (Chapter 3), and descriptions of the 

largest earthquakes in each source are provided in Chapters 6 and 7. The minimum magnitude 

used for the earthquake counts is M 4.7, as this is at the lower limit of one of the magnitude 

intervals used in the earthquake catalog analysis and there is a focus on earthquakes of 

significance for a hazard analysis. The magnitude estimates for the earthquakes in the CEUS 

catalog are subject to uncertainty. This uncertainty was incorporated into the assessment of 

mmax−obs using the procedure described above for the SCR domains by simulating 100,000 sets of 

earthquake magnitudes for the domain catalogs, selecting the largest magnitude for each 

simulated catalog, and then binning these values in 0.1-magnitude units to develop a distribution 

for mmax−obs . In some cases, there is uncertainty in assigning the largest observed earthquake to a 

particular source, due to uncertainty in location for earthquakes near source boundaries. This 

uncertainty was incorporated by developing alternative catalogs including or excluding the 

particular earthquake, developing simulated distributions for mmax−obs for each case, and then 

combining the results to produce a composite distribution. 

The uncertainty distribution for mmax−obs was incorporated into the assessment of Mmax 

distributions for the distributed seismicity sources by developing a likelihood function for each 

possible value of mmax−obs using Equation 5.2.1-1, using this likelihood function with the 

appropriate prior to develop a posterior Mmax distribution, and then weighting this posterior by 
Chapter 5 

SSC Model: Overview and Methodology 

5-17 

the probability assigned to the value of mmax−obs . The sum of these weighted posteriors represents 

the composite Mmax distribution for the source. 

5.2.1.2 Kijko Approach to Mmax Assessment 

The Kijko approach (Kijko, 2004) provides an assessment of Mmax based on only the observed 

distribution of earthquakes in a region. As described in Kijko (2004), the cumulative distribution 

for mmax−obs in a source zone is given by

[ ]

⎪

⎪

⎪

⎩

⎪

⎪

⎪

⎨

⎧

>

≤≤

<

= −

u

N u

m M

mm

mmmmF

mm

mF obs

1

)(

0

)( 0

0

max (5.2.1-5) 

where FM(m) is the cumulative probability distribution for magnitude and parameters m0, mu

, and 

N as defined above in Section 5.2.1.1. Kijko (2004) shows that the expected value of mmax−obs is 

given by the expression 

∫ −

− =

u m

m

obs

obs m

m

mdF ME m

0

d

d

)( )( max

max (5.2.1-6) 

Integration by parts yields

∫ − − −=

u

obs

m

m

m

u ME obs mmFm

0

max )( d)( max (5.2.1-7) 

which leads to the expression: 

∫ − = − +

u

obs

m

m

obs m

u MEm mmF

0

max )( d)( max (5.2.1-8) 

Kijko (2004) presents three alternative relationships for the application of Equation 5.2.1-8. The 

first is based on application of the truncated exponential distribution for FM(m), leading to the 

distribution for )( max mFm −obs given by Equation 5.2.1-2. This is designated the K-S (KijkoSellevoll) estimator by Kijko (2004). The second relationship incorporates uncertainty in β (the 

b-value) and takes the form
Chapter 5 

SSC Model: Overview and Methodology 

5-18 

⎪

⎪

⎪

⎪

⎩

⎪

⎪

⎪

⎪

⎨

⎧

>

≤≤ ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

−+ −

<

= −

u

u

N

q

m

mm

mmm

mmp

p C

mm

mF obs

1

1

0

)( 0

0

0

max β (5.2.1-9) 

where 2 / p = σβ β , ( )

2

/ = σβ β q , and [ { } ] 1

0 /(1 −

−+−=

q u

β mmppC . This second formulation is 

designated the K-S-B (Kijko-Sellevoll-Bayes) estimator by Kijko (2004). The third formulation 

makes no assumption about the form of the magnitude distribution. Instead, it used a kernel 

density estimation technique to estimate the form of the magnitude distribution from the 

observed magnitudes. This form, designated the N-P-G form in Kijko (2004) was not 

investigated for application in the CEUS SSC. Its intended use is to cases where characteristic 

earthquake type behavior is observed. In the CEUS SSC model, known earthquakes of this type 

are modeled by a separate set of RLME sources. With these earthquakes addressed by separate 

sources, the remaining earthquakes in the Project catalog display an approximately exponential 

distribution, which are addressed by the K-S and K-S-B estimators. 

The behavior of the K-S and K-S-B estimators as a function of mmax−obs and N is shown on 

Figure 5.2.1-11. The values of mu

 were computed by iteratively solving Equation 5.2.1-8 until 

convergence. Note that the estimates for the K-S estimator reach a point where the iterative 

solutions do not converge. The K-S-B estimator converges for all values of mu

 tried. Also shown 

on Figure 5.2.1-11 is the relationship between mu

 and the median value given by Equation 

5.2.1-2, indicating that the bias adjustment used in developing the Bayesian priors is nearly 

equivalent to the Kijko (2004) estimators of mu

. This is not surprising given that they are based 

on similar formulations. 

The relationships shown on Figure 5.2.1-11 indicate that the Kijko estimators for the expected 

value of mu

 are subject to the same need for large values of N as the bias adjustment relationship 

used to develop the Bayesian priors. In order to apply the approach to situations where N is 

small, an additional constraint must be used. This constraint is supplied by the assumption of a 

limiting size for CEUS earthquakes that was used to truncate the Bayesian prior distributions in 

Section 5.2.1.1. Kijko (2004) presents the following relationship for the cumulative probability 

function for mu

: 

)(1)()( max max m obs zmFmFzmP u u −==< −obs − (5.2.1-10) 

Figure 5.2.1-12 shows the behavior of Equation 5.2.1-10 as a function of N. For values of N

below about 100, the value of ) ( u mF reaches a limiting value less than 1.0 as mu

 approaches 

infinity (∞). Kijko (2004) discusses this limiting value of ) ( u mF as an indicator of the 

probability that the K-S or K-S-B estimator provides meaningful results. 
Chapter 5 

SSC Model: Overview and Methodology 

5-19 

As indicated by Figure 5.2.1-12, the cumulative distribution function ) ( u mF does not provide a 

complete probability distribution for mu

 in the unbounded case. However, if a limiting value for 

mu

 is imposed, then ) ( u mF can be truncated at this point and renormalized to produce a 

probability distribution for mu

. 

While this approach allows one to construct a proper probability distribution for mu

 regardless of 

the value of N and mmax−obs , it involves truncation of substantial probability mass for most 

practical applications. The truncated probability mass is given by P(mu

 > 81⁄4) calculated using 

Equation 5.2.1-10. The assessment was made that the point where the truncated probability mass 

equals the remaining probability mass, P(mu

 > 81⁄4) = 0.5, represents the limit of applicability of 

the Kijko Mmax approach. 

The application of a lower truncation point for Mmax distributions at M 51⁄2 requires a 

modification of the approach. The first step is to compute the unbounded cumulative distribution 

function ) ( u mF using Equation 5.2.1-10. This distribution is modified by imposing the 

requirement that mu

 must be ≥51⁄2 by computing its derivative, removing the probability mass 

below 51⁄2, if any, and then renomalizing. The effective result is to increase the value of 

P(mu

 > 81⁄4) for those cases where the maximum observed magnitude is less than 51⁄2. 

After a variety of exploratory calculations and considerations, the following key constraints were 

made in the application of the Kijko approach to assessment of Mmax for the CEUS SSC model: 

• The K-S-B approach (Kijko, 2004) that incorporates the uncertainty in b-value for the 

exponential distribution will be used, with an upper truncation at M 81⁄4 and a lower 

truncation at M 51⁄2. 

• Uncertainties in the magnitude of the largest earthquake in each source are assessed using the 

approach described in Section 5.2.1.1.5. 

• For those sources with a maximum observed magnitude derived from the paleoseismic 

record, the Kijko approach cannot be used because the approach assumes a complete record 

(historical earthquakes are adjusted for catalog completeness). We have no approach to 

formally evaluate the completeness of the paleoseismic record. An exploratory calculation 

using, for example, the four earthquakes identified for the Illinois Basin Extended Basement 

(IBEB) source, which has the largest number of observed paleoseismic earthquakes for any 

seismic source in the model, confirms that a high value of F(mu

 > 81⁄4) results from 

consideration of these events. Therefore, giving zero weight to the Kijko approach is 

reasonable. 

• The weighting scheme for the use of the Bayesian approach versus the Kijko approach 

should be source-specific (to account for the numbers and magnitudes of observed 

earthquakes). In no case should the Kijko approach be given higher weight than the Bayesian 

approach, considering the higher reliance on the Bayesian approach (and similar analogybased approaches) by the technical community. 
Chapter 5 

SSC Model: Overview and Methodology 

5-20 

5.2.1.3 Weights for the Alternative Mmax Approaches 

Because the probability that Mmax is much greater than 8 is a measure of the statistical stability 

of the Kijko approach—and is noted by its author as providing a measure of whether the 

approach is producing meaningful Mmax estimates—it is used as an index for weighting the 

Kijko versus Bayesian approaches. At values of P(mu

 > 81⁄4) = 0.5 and higher, the Kijko 

approach is assessed to have zero weight. Likewise, at P(mu

 > 81⁄4) = 0, where Kijko’s approach 

is at its strongest with large numbers of larger earthquakes, the Kijko approach is assessed to 

have equal weight (0.5) relative to the Bayesian approach. With these endpoints, a linear 

relationship is developed that provides the weight for the Kijko approach as a function of the 

calculated value of P(mu

 > 81⁄4) for the source of interest. 

Using the linear relationship between P(mu

 > 81⁄4) values and the Kijko weights, the calculated 

weights for the Kijko approach for the various source zones are shown in Table 5.2.1-5. Using 

the assumptions discussed previously and the cutoff of a P(mu

 > 81⁄4) value equal to or greater 

than 0.5, it can be seen that the Kijko approach is given zero weight for several sources: for some 

sources, the Kijko approach is given zero weight because the paleoseismic record is used to 

constrain the size of the maximum observed event; for others, zero weight is given because of 

the high P(mu

 > 81⁄4) values. 

5.2.1.4 Example Mmax Distributions 

Using the Bayesian and Kijko approaches in the manner described in this section, Mmax 

distributions were developed for both the Mmax zones (Section 6.2.3) and for the seismotectonic 

zones (Section 7.4.2). An example of how these distributions are displayed is given on Figures 

5.2.1-13 and 5.2.1-14. As a reminder, in the master logic tree, the Mmax zones approach is 

assessed a weight of 0.4, versus 0.6 for the seismotectonic zones approach. Given the Mmax 

zones approach, the weight assessed for a single, composite zone is 0.4, versus 0.6 for two 

Mmax zones. Given two Mmax zones, the weight assessed for the “narrow” interpretation of 

Mesozoic and younger extended zone (MESE-N) configuration is 0.8, versus a weight of 0.2 

assessed for the “wide” interpretation (MESE-W). 

Figure 5.2.1-13 shows the Mmax distribution for the Mesozoic and younger extended zone 

(MESE-N), which is one of the Mmax zones. Shown in all of the plots, regardless of the assessed 

weights, are the results for the Kijko approach, the Bayesian approach using the composite prior 

distribution, and the Bayesian approach using a MESE or non-MESE prior distribution. The 

weights assessed for the Kijko approach in Table 5.2.1-5 are functions of the P(mu

 > 81⁄4) value 

and whether paleoseismic data is used to define the size of the maximum observed magnitude. 

As discussed in Section 5.2.1.1.3, the weight assessed for the “two-priors” model is 0.6, and to 

the “composite” model, 0.4. Mmax estimates for each of these prior distributions are given along 

with their weights, which are the product of the Kijko versus Bayesian weights and the twopriors versus composite-prior weights. The final composite Mmax distribution is shown by the 

thick red histogram that reflects the probability mass function at 0.1-magnitude increments. 

A second example of Mmax distribution is shown on Figure 5.2.1-14 for the Northern 

Appalachian (NAP) seismotectonic zone. The same convention is used in the labeling and 
Chapter 5 

SSC Model: Overview and Methodology 

5-21 

display of the results for the Kijko and Bayesian approaches. In this case, the weight assessed for 

the Kijko approach is zero, based on a P(mu

 > 81⁄4) being greater than 0.5. The results of the 

Kijko approach are shown simply for purposes of comparison, but they are not incorporated into 

the final composite Mmax distribution, shown in red. 

For use in the hazard calculations, the maximum magnitude distributions for each source are then 

represented by a five-point discrete approximation to an arbitrary continuous distribution 

developed by Miller and Rice (1983). (The use of a discrete representation of a continuous 

distribution is described in more detail in Section 5.3.3.1.3.) The distributions for the two 

example sources are listed in Table 5.2.1-6. 

5.2.2 Other Mmax Issues 

One of the key uncertainties regarding the assessment of Mmax for seismic sources in the CEUS 

is spatial variation of Mmax throughout any given seismic source. That is, is it realistic to 

assume that a single Mmax distribution developed for a seismic source applies to all locations 

within that source? To a large extent, this issue is resolved within more active regions where 

active faults have been identified and Mmax can be assessed on a fault-specific basis using 

approaches such as fault rupture dimensions. In SCRs like the CEUS, however, the physical 

bases for specifying differences in Mmax spatially are not known with confidence. Unless 

specific faults can be identified that are the causative structures, the use of fault dimensions to 

constrain Mmax is problematic. The tectonic history of a region and the presence of significant 

geologic structures suggest that such structures might host future larger earthquakes, but no 

systematic studies have been conducted to show that the presence or absence of older geologic 

structures leads to differences in Mmax potential. Further, many SCRs show evidence of 

significant older geologic structures, but they show no evidence of large earthquake occurrence 

(Johnston et al., 1994). Also, in his inventory and evaluation of possible Mmax approaches, 

Wheeler (2009, pp. 12-13) cites the difficulties in using local geologic structures to estimate 

Mmax when there is no direct geologic evidence for young faulting. 

Using current approaches, the broad distributions of Mmax developed for seismic sources in the 

CEUS are assumed to be entirely epistemic and applicable throughout the source of interest. If 

the spatial variation of Mmax were known, that is, if it were possible to say that one part of the 

source should have a higher Mmax than another part, then that variation could be captured as 

aleatory variability. The result might be two epistemic distributions—one for regions marked by 

higher Mmax and one for regions with lower Mmax—and both distributions could be narrower 

than the current distribution for the entire source. At present, if there is a basis for identifying a 

spatial variation in Mmax, that information is used in the CEUS SSC Project to identify a 

separate seismic source (see Section 4.2.3). The Mmax distributions for the seismic sources in 

the CEUS developed for the Mmax zones (Section 6.3.2) and for the seismotectonic zones 

(Section 7.4.2) are quite broad in many cases to reflect the current uncertainties that exist with 

the estimation of Mmax within an SCR. It is hoped that the estimation of Mmax will continue to 

be a focus of research efforts in the scientific community, and that those efforts will lead to 

reductions in the epistemic uncertainties that currently exist. 
Chapter 5 

SSC Model: Overview and Methodology 

5-22 

5.3 Earthquake Recurrence Assessment 

5.3.1 Smoothing to Represent Spatial Stationarity 

The CEUS SSC model is based to a large extent on an assessment that spatial stationarity of 

seismicity will persist for time periods of interest for PSHA (approximately the next 50 years for 

engineered structures). Stationarity in this sense does not mean that future locations and 

magnitudes of earthquakes will occur exactly where they have occurred in the historical and 

instrumental record. Rather, the degree of spatial stationarity varies as a function of the type of 

data available to define the seismic source. RLME sources are based largely on paleoseismic 

evidence for repeated large-magnitude (M ≥ 6.5) earthquakes that occur in approximately the 

same location over periods of a few thousand years. Uncertainties in the locations and sizes of 

these events are a function of the types of data available (e.g., fault-specific repeated 

displacements on the Meers fault, and shaking effects over a relatively small region for the 

Marianna source). Because the record that defines the RLME sources spans a relatively long 

time period and records large-magnitude events, repeated events for these sources are expected 

to occur within a restricted location defined by the RLME source. 

On the other hand, patterns of seismicity away from the RLME sources within the Mmax and 

seismotectonic zones are defined from generally small- to moderate-magnitude earthquakes that 

have occurred during a relatively short (i.e., relative to the repeat times of large events) historical 

and instrumental record. Thus the locations of future events are not as tightly constrained by the 

locations of past events as for RLME sources. As discussed below in Section 5.3.2, the spatial 

smoothing operation is based on calculations of earthquake recurrence within one-quarter-degree 

or half-degree cells, with allowance for “communication” between the cells. Both a- and bvalues are allowed to vary, but the degree of variation has been optimized such that b-values 

vary little across the study region. Also, a-values are neither “spiky,” reflecting too strong of a 

reliance on the exact locations and rate densities of observed events, nor too smooth, reflecting 

the belief that the observed record does not provide a spatial constraint on rate density variation. 

Likewise, the recurrence calculation considers weighting of magnitudes in the recurrence rate 

calculations; thus moderate events are assigned more weight than smaller events. 

Ultimately, any smoothing operation of seismicity is founded on expert judgment related to the 

expected future distribution of moderate- to large-magnitude events. The CEUS SSC model 

gives strong consideration to locations of RLME sources as being spatially stationary through the 

future time periods of interest. The smoothing operation within the distributed seismicity zones 

results in variations in a- and b-values over scales that were judged by the TI Team to be 

reasonable, given the technical community’s views on spatial stationarity and the relationship 

between observed small- to moderate-magnitude seismicity and future moderate- to largemagnitude seismicity. 
Chapter 5 

SSC Model: Overview and Methodology 

5-23 

5.3.2 Smoothing Approach 

5.3.2.1 Development of Penalized-Likelihood Approach and Formulation 

5.3.2.1.1 Model for the Penalized-Likelihood Function of Recurrence Parameters 

This section introduces and discusses the formulation for the calculation of earthquake 

recurrence parameters for one source zone (or one cell within a source zone) under very simple 

assumptions, then reformulates and expands the formulation to include a number of elements that 

make the formulation more robust, realistic, and flexible. These elements include the 

reformulation in terms of magnitude bins, and the introduction of magnitude-dependent weights, 

catalog incompleteness, the effect of maximum earthquake magnitude (Mmax), spatial variation 

of parameters within the source zone, and the prior distributions of b. 

The first model to consider is the basic model, first presented by Aki (1965) and others. In this 

formulation, the number of earthquakes with magnitudes in the interval between m and m + dm

that occur in a source zone, within a time period of duration T, follows a Poisson probability 

distribution, with mean given by the following expression: 

0

)( 0 ( ) mmdmeATdmmMmn mm =+<≤ ≥ β −− νβ (5.3.2-1)

where A is the area of the source zone (in units of equatorial degrees squared), T is the time 

period of interest (i.e., the duration of the catalog in years), ν is the rate per unit time and per unit 

area for earthquakes with magnitude greater than or equal to m0 (the lowest magnitude 

considered in the recurrence analysis), and β is the slope of the exponential magnituderecurrence law (i.e., the b-value times ln[10]). In addition, it is assumed that the number of 

earthquakes in non-overlapping magnitude intervals is independent, so that earthquake 

occurrences in time represent a marked Poisson process.

Before going further, it is useful to make some comments about the above formulation. First, 

Mmax is not considered at this early stage. Second, the magnitude m0 is not the same as the 

lower-bound magnitude considered in the hazard integration; it is typically much smaller. This 

project uses m0 equal to moment magnitude 2.9. Finally, many of the assumptions in this initial 

formulation will be relaxed later in this section. Still, this initial formulation serves as a building 

block for the more general formulation and is helpful because it lends itself to the development 

of useful insights about the methodology. 

Data input to this first simplified model consist of the list of earthquake magnitudes in the 

catalog; i.e., Kmmm N ,, 21 , where N is the number of earthquakes in the catalog. In this project, 

these magnitudes are all moment magnitudes, and some of them may have been converted to 

moment magnitude from the magnitude, epicentral intensity, or felt area in the primary catalogs 

(see Section 3.3). In addition, the catalog is considered complete over the time period T, for all 

magnitudes above m0 . A somewhat surprising feature of the Poisson process is that the 

occurrence times of these earthquakes are immaterial, as long as the earthquakes occurred within 
Chapter 5 

SSC Model: Overview and Methodology 

5-24 

the time period T of the catalog. This property is actually a natural consequence of the “lack of 

memory” property of the Poisson process. 

The likelihood function for the model parameters takes the form 

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ = − ∏ ∫

∞

−−

=

−−

0

0 0 )(

1

)( (),( exp)

m

mm N

i

mm eAT dmeTA β i β l βνβν βν (5.3.2-2)

where all multiplicative constants that are independent of the parameters have been omitted 

because they do not affect the results. In this equation and in the equations that follow, index i

denotes the earthquakes in the catalog and N denotes the number of such earthquakes. Note that 

the integral is equal to T in this special case because T is independent of magnitude (and can be 

moved out of the integral) and the exponential probability density function integrates to unity.

This simplification does not apply in the more realistic case to be considered later, where the 

completeness time depends on magnitude. 

In general, the likelihood function indicates the degree of consistency between the parameters 

that one wants to estimate (in this case, ν and β ) and the available data (in this case, the 

number of earthquakes and their magnitudes during a time period T). If the data are abundant, the 

likelihood function has a narrow shape, indicating low uncertainty. If the data are scarce, the 

likelihood function has a broad shape, indicating high uncertainty. In the context of the 

maximum-likelihood method, one chooses the parameters that maximize the likelihood function 

and one estimates the uncertainty using the second derivatives of the natural log of the 

likelihood, evaluated at the point of maximum likelihood. 

To derive Equation 5.3.2-2, one can formulate the Poisson likelihood function for each small 

interval of width dm, using Equation 5.3.2-1, multiply these likelihoods, and then compute the 

limit of this product as dm approaches 0, taking into account that when dm is very small, the 

number of earthquakes in an interval is either 0 or 1. 

Note that the integral in Equation 5.3.2-2 is equal to T in this special case because T is 

independent of magnitude (and can be moved out of the integral) and what remains inside the 

integral (i.e., the the exponential probability density function) integrates to unity. This 

simplification does not apply in the more realistic case to be considered later, where the 

completeness time depends on magnitude. If we apply this simplification, we note that the 

likelihood function is separable into a product of factors that depend on the rate ν and factors 

that depend on the exponential slope β , i.e., 

∏=

− −− = ×

N

i

ATN i mm eAT e

1

)( )(),( )( ν β 0 l νβν β (5.3.2-3)

Note that the ν -dependent portion and the β -dependent portions of the likelihood function are 

separable, This separability is lost later, as the formulation is made more robust and realistic. 
Chapter 5 

SSC Model: Overview and Methodology 

5-25 

The first (ν -dependent) portion in the above equation is the traditional likelihood for a Poisson 

distribution. The second ( β -dependent) portion is the traditional likelihood for an exponential 

distribution. 

This separability also implies that the maximum-likelihood estimates of ν and β are decoupled 

in this simple case. In particular, by taking the logarithm of the above expression, differentiating 

with respect to each parameter, making the result equal to 0, and solving for the parameter, we 

obtain the following well-known results for the maximum-likelihood estimates of ν and β : 

AT

N

ν ML = (5.3.2-4)

∑=

= −

N

i

i

ML

mm

N 1

0 )( 11

β (5.3.2-5)

The last result was first derived independently by Aki (1965) and Utsu (1965). Note that in the 

case where N = 0, the maximum-likelihood estimate of the rate ν is zero. On the other hand, if 

one is working with the entire likelihood function (in order to represent an epistemic 

uncertainty), one sees that the ν-dependent portion of the likelihood in Equation 5.3.2-3 for N = 0 

follows an exponential distribution, which happens to have a mean value of 1/(AT) (i.e., the 

value in Equation 5.3.2-4 corresponding to N = 1). Thus, consideration of the full-likelihood 

function for ν gives rise to a natural “floor” in regions of low seismicity. 

Note also that this likelihood function for the Poisson portion has sharper peaks (i.e., lower 

coefficient of variation, or COV) when N is large, indicating that only a narrow range of values 

of ν are consistent with the catalog. In contrast, the distribution is broad when N is small 

(becoming as broad as the exponential distribution when N = 0). This is illustrated on Figure 

5.3.2-1. 

Similarly, Figure 5.3.2-2 shows the likelihood function for the b-value, for different values of N. 

Again, the COV decreases as N increases. 

Equation 5.3.2-3 is in fact easier to derive than the equivalent 5.3.2-2. One begins by introducing 

the standard assumptions that the number of earthquakes follows a Poisson distribution, 

independent of the magnitudes, and that the magnitudes are exponential and independent 

identically distributed (iid). Equation 5.3.2-3 then follows automatically as the product of the 

Poisson probability mass function and the N exponential probability density functions (again, 

omitting multiplicative constants that are independent of the parameters ν and β ). 

This simple formulation of the magnitude-recurrence model is useful as a starting point but is not 

always robust and sufficient in practice. The remainder of this section describes the various 

modifications to the formulation, in order to make it more robust and flexible. 
Chapter 5 

SSC Model: Overview and Methodology 

5-26 

The first difficulty arises from the continuous nature of the above formulation, which assumes 

that the exponential assumption applies at both small and large scales. In practice, the 

exponential assumption may not apply at small scales (i.e., over differences of a few tenths of a 

magnitude units, or less), for a number of reasons. Most importantly, some of the earthquake 

magnitudes in the catalog have been effectively binned into integer epicentral intensity and then 

converted to magnitude. Other possible causes include problems in the conversion to moment 

magnitude, edge effects, or the phenomenon investigated by Lombardi (2003). 

This deviation from exponentiality is illustrated by Figure 5.3.2-3, which shows a histogram of 

the magnitudes in the earthquake catalog developed in Chapter 3 and used later in this section for 

the calculation of recurrence parameters. Focusing on the left portion of this figure (say, 

magnitudes lower than 3.5), one notices that the data deviate substantially from a smooth 

exponential shape. These deviations are not consistent with the exponential model, given the 

very large earthquake counts in these bins. These large earthquake counts mean that the 

continuous formulation of the likelihood may incorrectly interpret the local slope of the 

histogram around magnitude 3 as containing information about the exponential slope β . 

In order to avoid these potential problems, the likelihood function is reformulated in terms of the 

earthquake counts in discrete magnitude bins, with bin sizes appropriately selected so that 

magnitudes converted from intensity fall in the middle of these bins. 

 Considering bins of δ magnitude units (i.e., first bin between magnitudes m0 and m0 + δ , 

second bin between m0 + δ and m0 + 2δ , etc.), one can write the likelihood function 

⎥

⎦

⎤ ⎢

⎣

⎡ = ∏ − ∑

∞

=

∞

=1 1

exp)(),(

k

k

k

n ATpk TpA k l νβν ν (5.3.2-6)

where nk is the number of earthquakes in the k-th magnitude bin ( 1

0 0

+ <≤k k

mmm ), 

[ ] [ )(exp)(exp)( ] 0

1

pp mm 00 0 mm

k k

kk −−−−−== + ββ β (5.3.2-7)

is the probability mass associated with the k-th magnitude bin, and 00 kmm −+= )1( δ k is the 

magnitude at the lower end of the k-th magnitude bin. One can obtain Equation 5.3.2-6 from 

Equation 5.3.2-2 by replacing each occurrence of the exponential density (exp[ ) β β −− mm 0

with the value of pk for the magnitude bin where m falls. By working with earthquake counts in 

discrete bins, sensitivity to small-scale deviations from the exponential model (i.e., deviations at 

scales of of a few tenths of a magnitude unit or smaller) is removed, resulting in a more robust 

formulation. We note that the expression for the likelihood function in Equation 5.3.2.6 is is still 

a separable function of ν and β , although one cannot easily solve for β ML . 
Chapter 5 

SSC Model: Overview and Methodology 

5-27 

Perhaps the best known example of this discrete-magnitude formulation for the likelihood 

function is the paper by Weichert (1980). The discrete-magnitude formulation was also used in 

the EPRI-SOG project. 

It is also worth noting that the number nk in Equation 5.3.2-6 is not necessarily an integer 

number. This project accounts for the effect of uncertainty in magnitude by calculating an “event 

factor” for each earthquake (see Chapter 3). Thus, nk represents the sum of the event factors for 

all the earthquakes in the k-th magnitude bin. 

A second modification is required because the assessment may result in a lower weight for lower 

magnitude bins. For instance, the magnitude-recurrence law may deviate from exponential, or 

the magnitude-conversion models or completeness model may be less reliable for lower 

magnitudes. The USGS (Petersen et al., 2008) use of alternative low-magnitude cutoffs may be 

viewed as a special case of magnitude-dependent (or magnitude- and time-dependent) weights.

One can represent these weights by the quantities ww 21 ,, K (indexed by k, the magnitude-bin 

number; note also that these weights do not necessarily add to 1, and the resulting weightedlikelihood function is

⎥

⎦

⎤ ⎢

⎣

⎡ =∏ − ∑

∞

=

∞

=1 1

exp)(),(

k

kk

k

wn ATpk wTpA kk l νβν ν (5.3.2-8)

The introduction of weights, resulting in Equation 5.3.2-8, is equivalent to raising the portion of 

the likelihood function associated with magnitude bin k to a power 1 wk ≤ . Raising to a power 

less then 1 has the effect of flattening this portion of the likelihood, without shifting the location 

of its peak. For instance, if there are 1 n earthquakes in the first magnitude bin, and this bin is 

given a weight of 0.1, the associated portion of the likelihood becomes flatter (as if it had only 

10/ 1 n earthquakes), but the location of its peak remains unchanged (recall Figures 5.3.2-1 and 

5.3.2-2). 

We note that the summation in the above equation cannot be simplified after the introduction of 

the weights. As a result, it is impossible to obtain the maximum-likelihood estimates of ν and β

in closed form. 

A third modification is necessary to account for magnitude-dependent catalog completeness. 

Following EPRI-SOG (1986), earthquakes in magnitude bin k are counted if they occurred after 

a certain date k t ,0 , even if the catalog is not fully complete after that date, and the associated 

catalog duration is characterized by the Equivalent Period of Completeness, which is defined as 

∫ =

present

t

kE D

k

dtktPT

,0

);( , (5.3.2-9)
Chapter 5 

SSC Model: Overview and Methodology 

5-28 

where ktP );( D is the detection probability for magnitudes in bin k at time t. The detection 

probabilities and equivalent periods of completeness are calculated in Section 3.5 using the 

EPRI-SOG methodology for determining completeness (which includes a penalized-likelihood 

analysis of recurrence). For the purposes of this discussion, it is assumed that the equivalent 

period of completeness is the same within the source zone under consideration and for all 

magnitudes in a certain magnitude bin. In the final model to be developed here, it will be 

assumed that the equivalent periods of completeness are constant within each cell comprising the 

source zone. Another assumption in this derivation is that all earthquakes under consideration 

(which have magnitudes Kmmm N ,, 21 ) occurred after their corresponding dates mk i )(,0t .

After introducing magnitude-dependent completeness, the likelihood function becomes 

⎥

⎦

⎤ ⎢

⎣

⎡ =∏ − ∑

∞

=

∞

= 1

,

1

, exp)(),(

k

kkkE

k

wn pAT kkE wpTA kk l νβν ν (5.3.2-10)

A fourth modification is necessary to account for maximum magnitude Mmax . In the case of a 

single Mmax value, Equation 5.3.2.7 is modified by considering that portions of a magnitude bin, 

or the entire bin, may be above Mmax , resulting in the expression 

[ ] [ ]

[ ] [ ]

k

k k k

k k k

k

mM

mm mM mMm

Mp mm mm Mm

max 0

1

00 max 0 0 max 0

max

1

0 0

1

max 00 0

0 for

for)(exp)(exp

for)(exp)(exp)(

<

−−−−− <<

−−−−−= <

+

+ +

β β

β β

(5.3.2-

11)

There should be a normalizing constant in the above equation, but this constant is very nearly 

equal to unity (because m0 is 2.9 and Mmax is 5.5 or greater) and can be neglected in this case. 

For the case where there is epistemic uncertainty in Mmax (which is represented in this project by 

a five-point discrete distribution), one can use the expected value (with respect to M max ) of the 

pk given by Equation 5.3.2-11; that is, 

[ )( ] = max kMk MpEp max (5.3.2-

12)

where ] [ max • EM denotes the expect-value operation with respect to uncertainty in Mmax . Another 

consequence of introducing M max is that the number of magnitude bins becomes finite. In the 

equations that follow, Q will denote the highest bin with a nonzero value of pk . 

Up to this point, the formulation does not include spatial variation of parameters within a source 

zone. Consideration of spatial variation is necessary in this project because the assumption of 

geographically constant rate and b-value is not necessarily applicable to some of the large source 

zones developed in Chapter 4. There are two commonly used approaches to introduce spatial 
Chapter 5 

SSC Model: Overview and Methodology 

5-29 

variation of seismicity within a source zone; namely, the penalized-likelihood (EPRI-SOG, 

1986) and kernel approaches (e.g., Frankel, 1995; Stock and Smith, 2002). This project uses the 

penalized-likelihood approach, with a number of methodological refinements. A discussion of 

the two approaches and their merits is presented in Section 5.3.2.4. 

The first step in the penalized-likelihood approach is to divide the source zones into cells for the 

purposes of the recurrence-model evaluation and hazard calculations. This division is often done 

along parallels and meridians. This project uses a cell dimension of one-quarter degree by onequarter degree. For source zones of large dimensions, the cell size is increased to one-half degree 

by one-half degree for computational efficiency. Cells near source-zone boundaries have smaller 

areas and irregular shapes, generated so that the geometry of a source zone is honored in the 

recurrence and hazard calculations, without any quantization error. 

The likelihood function is then formulated separately for each cell in the source zone. The joint 

likelihood function for the values of ν and β in all M cells within the source zone takes the form: 

∏ ∏( ) ∑ = = = ⎪

⎭

⎪

⎬

⎫

⎪

⎩

⎪

⎨

⎧

⎥

⎦

⎤ ⎢

⎣

⎡ = −

M

j

Q

k

Ejj k

Q wjkn

k

Ejj jkpjkTA wjkpjkTA

k

1 1

),(

,1

l ,βν )( ν ),(),( exp ν ),(),( (5.3.2-13) 

where vectors ,βν contain the values of ν and β in all cells within the source zone, j is the index 

for the cells (j=1, ..., M). Also, the notation has been changed slightly from previous equations, 

so that jkT ),( E , ) ,( jkn , and ) ,( jkp are the equivalent period of completeness, earthquake 

count, and truncated-exponential bin probability (Equation 5.3.2.12) for magnitude bin k and 

cell k . 

Because cells are small and most cells do not contain enough earthquakes to allow the reliable 

estimation of ν j and β j using these earthquakes alone, and because very large variations in ν

and β (particularly the latter) between adjacent cells are not considered physically realistic, one 

introduces penalty functions that penalize those solutions where ν and β have large variations 

between adjacent cells. Thus the solution to the penalized-likelihood problem represents an 

optimal compromise between consistency with the data (as indicated by a high value of the 

likelihood) and smoothness (as indicated by a low value of the penalty function). For a given 

value of the smoothing parameters, the likelihood has a stronger effect on the solution in cells 

where data are abundant because only a narrow range of values are consistent with the data.

This project utilizes a penalty function based on the Laplacian operator, which represents a 

generalization of the second derivative to multiple dimensions, and is commonly used in 

applications of this kind (e.g., Fukuda and Johnson, 2008). For a function f(x,y) in two 

dimensions, the Laplacian operator and its lowest-order finite difference approximation are given 

by 
Chapter 5 

SSC Model: Overview and Methodology 

5-30 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

Δ

− −

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

Δ

− −=

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

Δ

Δ++−Δ−

⎟ +

⎠

⎞ ⎜

⎝

⎛

Δ

Δ++−Δ− ≈

≈ ∂

∂

+

∂

∂ =Δ

2 2

2

2

2

2

2

2

),(),( 2 ),(),( 2

2/),(),(2/),( 2

2/),(),(2/),( 2

y

yxfyxf

x

yxfyxf

y

yyxfyxfyyxf

x

yxxfyxfyxxf

y

f

x

f f

x y

(5.3.2-14)

where yxf ),(x

 is the average value of f in the two cells adjacent to the (x,y) cell in the x

direction. In the special case of =Δ Δyx , the finite-difference Laplacian at (x,y) is proportional 

to the difference between yxf ),(x

 and the average of the values in the four adjoining cells (not 

counting diagonal cells that share a vertex with the cell under consideration). This project defines 

the Laplacian in terms of distances in kilometers (rather than in degrees) because this makes 

more physical sense, resulting in ) Δ Δyx = cos(/ Latitude and yielding a slightly more 

complicated expression for the finite-difference Laplacian. Based on the above, and assuming a 

normal distribution for variations in β between a cell and its neighbors, the penalty function for 

β over the entire source source zone is of the form 

∏= Δ Δ

Δ ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ Δ = −

M

j

j

b f

1

2

2

1

exp 2

1 );(

β β

β σ

β

σπ

β σ (5.3.2-15)

where the product extends over all cells, σ Δβ controls the degree of smoothing, and 

⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ − +⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ − −=Δ

1

),(),(

)Latitude(cos

),(),(

2

1

2

jj

y

jj

j

jj

x

jj

j

β β β β yxyxyxyx β (5.3.2-16)

Because Δy is constant, it can be absorbed into σ Δβ . The change from a factor of 2 to a factor of 

1⁄2 in the definition of Δβ j is introduced for the sake of consistency with the EPRI-SOG 

formulation, and its effect is absorbed into σ Δβ . For a cell at the edges of the source zone, 

),( jj

x

β yx or ),( jj

y

β yx is calculated using only cells on one side. 

The penalty term ) ;( ν σ Δν f ν for the rate is constructed in the same manner, except that the 

Laplacian term Δν j is calculated in terms of ν )ln( instead of ν itself.
Chapter 5 

SSC Model: Overview and Methodology 

5-31 

It is useful to consider the effect of σ Δβ (and the corresponding σ Δν for rate), which control the 

degree of smoothing. A lower value favors solutions with less variation between adjacent cells. 

In the limit, infinitesimally small values of σ Δν and/or σ Δβ lead to constant ν and/or β

throughout the source zone. At the other extreme, very large values of σ Δν and σ Δβ is 

equivalent to determining ν and β separately for each cell, considering only the earthquakes in 

that cell, without any consideration of spatial continuity. 

The two penalty terms, ) ;( ν σ Δν f ν and ) ;( β β σ Δβ f , multiply the likelihood function in Equation 

5.3.2-13, favoring solutions that are consistent with the data and, simultaneously, show less 

variation between parameters ν )ln( and β in adjacent cells. One can fix the penalty terms σ Δν

and σ Δβ and then solve the penalized-likelihood problem. In this case one can view the penalty 

terms as prior distributions on the degree of smoothness of ) ln(ν and β . 

Alternatively, one can solve simultaneously for the optimal values of ν , β , and σ Δν and σ Δβ .

In this case, σ Δν and σ Δβ are often called hyperparameters. Larger values of these 

hyperparameters reduce the penalizing effect of the exponential penalty term in Equation 

5.3.2-15 and tend to increase the value of the penalized likelihood (by allowing a very close 

match between model predictions and data in each individual cell). At the same time, these larger 

values of σ Δβ in the denominator of Equation 5.3.2-15 tend to decrease the value of the 

penalized likelihood. The value of σ Δβ at which this optimal balance is achieved depends on the 

earthquake data, in particular, how many earthquakes there are and how they are distributed in 

latitude-longitude-magnitude space. This project will refer to the estimates of σ Δν and σ Δβ

obtained using this approach as the objective estimates of these hyperparameters. They are 

objective in the sense that they are determined automatically from the data, using the mechanism 

described above. 

This optimal balance between the exponential term and the denominator in Equation 5.3.2-15, 

which leads to the objective estimate of the smoothing parameter, arises frequently in statistics. 

Perhaps the best known example is the calculation of the standard deviation of normally 

distributed data using the method of maximum likelihood.

EPRI-SOG (1986) used a similar formulation for the penalty terms, except that the cosine term is 

not included, the average of neighboring cells includes diagonal cells that share a vertex with the 

cell under consideration, and the smoothing parameters are assessed by the expert teams on the 

basis of their evaluations, aided by statistical tests. The presence of the cosine term is justified on 

physical arguments (see above); the omission of the diagonal terms makes the definition 

consistent with the standard finite-difference definition of the Laplacian operator.

Following EPRI-SOG (1986), this project introduces an additional penalty term, in the form of a 

prior distribution for β j . The product of the prior distributions for all cells in the source zone 

takes the form 
Chapter 5 

SSC Model: Overview and Methodology 

5-32 

∏= ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ − = −

M

j

j f

1

2

prior

2

1

exp 2

1 )('

β β

β σ

ββ

σπ

β (5.3.2-17)

It may possible to determine β prior and σ β objectively, but this was not done in this project. 

Instead, β prior was specified as the value of β obtained for the entire study region (see regional 

b-values obtained in Section 3.5), and σ β was selected on the basis of the EPRI-SOG (1986) 

experience and sensitivity runs. 

There is a subtle difference between Equations 5.3.2-15 and 5.3.2-17. The former favors 

solutions with spatially uniform β , regardless of the value of β , while the latter promotes 

values of β near β prior . 

The complete penalized-likelihood, which may also be viewed as a posterior distribution, is 

constructed as the product of the joint likelihood for all the cells in the source zone (Equation 

5.3.2-13), the smoothness penalty terms (Equation 5.3.2-15 and its counterpart for ) ln(ν ), and 

the prior distribution of β (Equation 5.3.2-17). We write this quantity as 

,X βνβν β)(');();()()( ν σ βν σ ββ p fff = Δ Δ l (5.3.2-18)

where 

[ ] = σ σ ΔΔ βν X βν ,,, (5.3.2-19)

is the complete vector of parameters and hyperparameters. It will be called the state vector in the 

section that follows. 

Equation 5.3.2-18 cannot be solved analytically for the penalized maximum-likelihood estimates 

of the parameters. Furthermore, we need more than point estimates of the recurrence parameters. 

Modern PSHA requires an assessment of the epistemic uncertainty associated with these 

estimates—including correlations between the recurrence parameters of cells in the same 

geographical region, which may jointly affect the hazard at one site. Therefore, this project needs 

to characterize the entire multidimensional joint distribution of X (this distribution is given by 

Equation 5.3.2-18 times a normalizing constant). An additional, practical requirement is that one 

must represent the epistemic uncertainty in a computationally efficient manner. This can be 

accomplished by means of a small number of alternative “maps” of the recurrence parameters. 

Sections 5.3.2.1.2 and 5.3.2.1.3 present an approach to fulfill this need.
Chapter 5 

SSC Model: Overview and Methodology 

5-33 

5.3.2.1.2 Modeling the Joint Distribution of Recurrence Parameters 

The approach used to generate alternative maps of the recurrence parameters uses a technique 

known as Markov Chain Monte Carlo (MCMC), in particular, the Metropolis algorithm 

(Metropolis et al., 1953). MCMC is frequently used to generate multiple realizations from a 

complex multi-dimensional probability distribution by constructing a Markov chain that has this 

distribution as its limiting or stationary distribution. In this case, the distribution of interest is 

given by Equation 5.3.2-18 (times a constant). This distribution represents the central tendency 

and epistemic uncertainty of the vector [ ] = σ σ ΔΔ βν X βν ,,, , which contains the recurrence 

parameters for all cells, plus the two hyperparameters. The number of dimensions of X is 

M + 22 , where M is the number of cells in the source zone. 

A Markov chain is a discrete-time1

 probabilistic model with states X(1), X(2), X(3), X(4), ...., in 

which the conditional probability distribution of the state at time t+1 (denoted X(t+1)), given the 

states at earlier times, depends only on the immediately previous state (X(t)

). This conditional 

probability distribution of X(t+1) given X(t)

 is known as the transition probability. If a Markov 

chain meets certain requirements, it possesses a limiting or stationary distribution, which will be 

reached asymptotically after many realizations, regardless of the initial state. A mechanical 

analogy is a linear damped oscillator under harmonic loading. After a sufficiently long time, the 

oscillator will reach a steady-state amplitude (and, as a consequence, a steady-state probability 

distribution for the instantaneous displacement), regardless of its initial conditions. Further 

details on Markov chains may be found in Parzen (1962). 

MCMC constructs a discrete-time Markov chain with the following properties: (a) the Markov 

chain has a stationary or limiting distribution, and (b) this limiting distribution is equal to the 

joint distribution of interest (i.e., the penalized likelihood function p(X) given by Equation 

5.3.2-18). Thus, one can use this sequence to obtain realizations from that distribution. A number 

of initial realizations are discarded because they are affected by the initial conditions. Then, a 

number of realizations are generated and summary statistics are calculated from them. 

In the Metropolis MCMC algorithm, a new realization X(t+1) is generated from X(t) by the 

following two-step procedure: (1) generate a new candidate state X′ by drawing from a trial 

distribution q(X′|X(t)) that depends only on X(t) and is symmetrical (i.e., q(X′|X(t)) = q(X(t)|X′)), 

and (2) accept the new trial state with probability 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = )(

)'( ,1min accept t)( p

p P

X

X

(5.3.2-20)

If the new state is accepted (i.e., if a standard uniform random number generator draws a value 

lower than Paccept), X′ becomes the new state X(t+1). Otherwise, the new state X(t+1) is equal to X(t). 

 

1

 The word “time” is not used in a strict chronological sense here. Instead it is used to represent a sequence of 

discrete realizations of a mathematical process. 
Chapter 5 

SSC Model: Overview and Methodology 

5-34 

In this project, the Metropolis algorithm is implemented locally, as follows. For each cell j, trial 

values of ) ln(ν j and β j are drawn from uniform distributions centered at the current values of 

these parameters, the penalized likelihood function is calculated for these trial values, and the 

values are accepted or rejected using Equation 5.3.2-20 and a random-number generator. The 

only portions of the penalized likelihood that are reevaluated each time are the likelihood 

function for cell j, the penalty terms for cell j and for its neighboring cells within the source zone, 

and the prior distribution of β j . After going through all cells, trial values of the hyperparameters 

σ Δν and σ Δb are drawn in a similar manner, the penalized likelihood is recalculated, and the 

values are accepted or rejected. In this step, only the smoothness-penalty terms for all cells are 

recalculated. This process is repeated a large number of times. 

The widths of the uniform distributions are controlled by the analyst. These widths affect the 

acceptance rate, which in turn affects the numerical efficiency of the algorithm.

Recommendations as to the optimal acceptance rates vary; a common recommendation is values 

in the range between 20% and 40% (e.g., Ntzoufras, 2009). After discarding some of the initial 

realizations of X(t), one generates a large number of realizations to represent the joint distribution 

of the state vector [ ] = σ σ ΔΔ βν X βν ,,, . The section that follows describes the approach to obtain 

eight equally likely realizations of X (i.e., eight alternative maps to represent the joint 

distribution of ν and β and the two hyperparameters), including their correlation structure.

5.3.2.1.3 Development of Alternative Recurrence Maps 

The approach presented below constructs alternative maps of the recurrence parameters ν and 

β that jointly represent the central tendency and statistical uncertainty in the recurrence 

parameters, including correlations between the recurrence parameters of cells in the same 

geographical region (which may jointly affect the hazard at one site). At the same time, the 

number of alternative recurrence maps must be kept small for the sake of efficiency in the hazard 

calculations. The approach used here is a combination of well known techniques. 

The first step in this formulation is to generate many realizations of the state vector 

[ ] = σ σ ΔΔ βν X βν ,,, using the MCMC algorithm described above and then use these realizations 

to calculate the mean vector mX and the covariance matrix SX of X. This covariance matrix 

contains information about the marginal variance of ν and β in each cell, the correlation 

between ν and β in each cell, as well as the correlation between parameters in neighboring 

cells.

The second step is to perform an eigenvalue decomposition of the covariance matrix SX .

Because this matrix is a covariance matrix, it is positive-semi-definite, so that all eigenvalues are 

positive or zero. Let 2

22

2

2

2

1 ,,, K ααα M + be the eigenvalues of SX , ordered from largest to 

smallest, and let 21 22 ,,, K φφφ M + be the associated eigenvectors.
Chapter 5 

SSC Model: Overview and Methodology 

5-35 

An important property of this eigenvalue decomposition is that of orthogonality, meaning that 

the dot product of φr and φs is equal to 1 if r = s and 0 if r ≠ s. Taking advantage of 

orthogonality, one can show that a random vector X

~ constructed using the following 

randomized linear combination of the eigenvalues 

∑

+

=

+=

22

1

~ M

k

mX X φ kk ε (5.3.2-21)

where 2221 ,, M + ε ε Kε are independent random variables with mean zero and variances 

2

22

2

2

2

1 ,,, K ααα M + , has mean mX and covariance matrix SX . This implies that a synthesized 

realization of X

~ generated using Equation 5.3.2-21 has the correlation properties of the random 

vector [ ] = σ σ ΔΔ βν X βν ,,, that we want to simulate. This technique, based on the eigenvalue 

decomposition of the covariance matrix, is used in many disciplines, under a variety of names; 

e.g., Karhunen–Loève expansion, principal component analysis, and empirical orthogonal 

functions (see, for example, Preisendorfer, 1988). 

In many applications of this technique, only a few terms are required in Equation 5.3.2-21 

because the eigenvalues decrease rapidly in size. This is not the case in this application, and it 

may be necessary to use a large number of terms (up to a few hundred) in the summation in order 

to represent 99% of the total variance of X.

The third step is to generate eight realizations of the ε ’s and then use these to generate 

realizations of X

~ using Equation 5.2.2-21, with each realization representing an alternative 

recurrence map. This is done using a technique known as Latin Hypercube sampling or LHS 

(Iman and Conover, 1980). The technique will be described in the context of Equation 5.3.2-21, 

where we want to generate eight realizations of the random vector [ ] 2221 ,, = M + ε ε ε Kε and we 

want these realizations to provide a good representation of the underlying distributions, despite 

the small number of realizations. We also assume, for the sake of convenience, that the 

components of ε have normal distributions (this assumption and its implications are discussed 

later). The process is as follows: 

1. Divide the sample space of each normally distributed j ε into eight intervals, with each 

interval containing an equal probability of 1/8. These intervals will have unequal lengths. 

2. Within each interval z (z=1, 2, ,,,8), generate a random value jz ε that follows the conditional 

distribution within the interval. The resulting values form a sequence with 

jj 21 j8 ε ε K<<< ε . 

3. For each j, generate an independent random permutation of 21 8 ,,, jj j ε ε K ε . After this 

permutation, 21 8 ,,, jj j ε ε K ε are no longer an increasing sequence. The result is eight random 

realizations of the random vector [ ] 2221 ,, = M + ε ε ε Kε . Because the eight values for each j

were drawn from the eight equal-probability intervals, the distribution of j ε is well 
Chapter 5 

SSC Model: Overview and Methodology 

5-36 

approximated by the eight realizations. Because of the random permutations, the correlation 

coefficient between the eight realizations of any two 1j ε and 2j ε has an expected value of 0 

and is likely to be low. 

4. Generate eight alternative realizations of X

~ using the eight permuted ε vectors and Equation 

5.3.2-21. 

5. Convert each realization of X

~ (actually, all but its last two elements) into values of ν and b

for each cell in the source zone, and use these two values to calculate ν )5( , the rate of 

earthquakes above magnitude 5. 

The resulting eight alternative maps represent the uncertainty in recurrence parameters that 

results from the limited duration of the catalog. If the smoothing parameters are treated as 

uncertain and estimated objectively from the data, the eight alternative maps also include the 

uncertainty about the appropriate values of the smoothing parameters. 

This approach presented below constructs the alternative realizations of ν and β as linear 

combinations of normally distributed random quantities. Thus, it produces normally distributed 

quantities. This normal distribution is consistent with the distribution shapes of ν and β shown 

in Figures 5.3.2-1 and 5.3.2-2, which approach normal shapes as the number of earthquakes 

approaches 10. Although there may be a few earthquakes in each cell, the presence of the penalty 

terms tends to “pool” the data from many adjacent cells, resulting in a larger value of the 

“effective” earthquake count. 

The initial implementation of this approach required that the number of realizations be a power 

of 2 because the first few epsilons were sampled using two-point distributions. This number was 

set to 8 because 4 was considered insufficient and 16 imposed a high computational burden for 

the hazard calculations. In the present Latin Hypercube implementation, the restriction of a 

power of 2 no longer exists, but the choice of eight realizations was retained. Tests indicate that 

eight realizations, together with Latin Hypercube sampling, provide an adequate representation 

of the mean and fractiles of the hazard. 

5.3.2.2 Application of the Model and Specification of Model Parameters 

5.3.2.2.1 Calculations 

Calculations were performed for all the seismotectonic and Mmax-region source zones identified 

in Chapter 4. The catalog had all dependent earthquakes removed; earthquakes associated with 

the RLME sources were also removed from this catalog to avoid double-counting (see 

Chapter 3). 

The MCMC formulation was used to generate a large number of realizations (typically 15 

million), of which roughly the first 25% were discarded because they were affected by the initial 

conditions. The evolution of recurrence parameters at a few points was examined in each run to 

verify that this number was sufficient, in the sense that the system had reached a steady state. In 

some instances, this number had to be increased and sometimes the width of the MCMC trial 
Chapter 5 

SSC Model: Overview and Methodology 

5-37 

distribution had to be altered. The cell sizes for all seismotectonic source zones except MidC was 

0.25 degrees in order to have the ability to resolve any sharp gradients in parameters that may 

occur in the more active regions. For reasons of computational efficiency, the cell size for MidC 

and for the Mmax source zones was set to 0.5 degrees. Tests with MidC indicated similar results 

for both cell sizes. 

In addition to the algorithmic inputs described above, one must specify the weights for the 

various magnitude bins, the degree of spatial smoothing (including the option of objective 

smoothing), and the mean value and standard deviation of the prior distribution on b. Section 

5.3.2.1.1 provides details on how these quantities enter the calculations and the rationale for their 

use. 

Table 5.3.2.1 shows the five cases that were initially considered for the weights to the magnitude 

bins. These five alternative sets of weights span a wide range, in order to investigate the effect of 

giving lower weights to the lower-magnitude bins. Case E was introduced later, as an 

intermediate case between Cases C and D, because Case E was considered too extreme. 

Some or the reasons for giving lower weights to the lower magnitude bins were discussed earlier. 

For instance, the magnitude-recurrence law may deviate from exponential, or the magnitudeconversion models or completeness model may be less reliable for lower magnitudes. In this 

regard, it is useful to remember that only earthquakes with magnitudes greater than 5 (4 if the 

CAV filter is being used) are important for seismic hazard and risk for nuclear facilities. The 

only reason for considering lower magnitudes is that the M > 4 data alone are not sufficient for 

determining both the magnitude-recurrence law and the spatial distribution for earthquakes of 

engineering interest. Because the magnitude weights also affect the degree of smoothing2

, one 

must also consider the issue of spatial stationarity; i.e., whether the spatial pattern of past, small, 

earthquakes is representative of the spatial pattern of future, hazard-significant, earthquakes. 

Cases A through E were designed to cover a broad range of alternatives regarding magnitude 

weights. 

Based on calculations performed earlier in the project, only Cases A, B, and E were retained. The 

reasons for dropping Cases C and D were that case C was very similar to Case B and that Case E 

was considered too extreme, relying almost entirely on magnitudes 4.3 and greater, and leading 

to nearly spatially uniform seismicity. The three remaining cases (Cases A, B, and E) were 

examined and compared in terms of their fit to the magnitude-recurrence data and their degree of 

smoothing. Preference for the three cases was nearly equal, except that Case E was given slightly 

more weight because this case is more sensitive to data in the magnitude bins that that control 

seismic hazard. The resulting weights are 0.3, 0.3, and 0.4, for Cases A, B, and E, respectively. 

The mean value for the prior distribution of β (Equation 5.3.2.17) was calculated separately for 

Cases A, B, and E above, by performing a maximum-likelihood recurrence analysis for the entire 

study region, and assuming constant b. Details of these calculations are contained in Section 3.5 

 

2

 When objective smoothing is used, the cases where the lower bins are downweighted result in smoother seismicity. 

This effect will be discussed and explained later in this section. 
Chapter 5 

SSC Model: Overview and Methodology 

5-38 

Two values were considered for the strength of the prior distribution of β , which is specified by 

the standard deviation ) 10ln(/ σ b = σ β . The first value is 0.6 (in units of b), which corresponds 

to a “moderate prior” in the EPRI-SOG (1988) project; we will also refer to this value as a 

moderate prior for b. The second value is 0.3 (in units of b), and we will refer to it as a strong 

prior. We also considered a weak prior (1.2, in units of b) in earlier stages of the project, but this 

value was not considered credible because there is a general consensus in the TI Team that 

spatial variation in b should be mild. 

For all source zones except SLR, the smoothing parameters were determined using the objective 

approach. For each source zone, and for each of the magnitude-bin weights and strengths of the 

prior on b considered, the smoothing parameters σ Δν and σ Δβ were allowed to vary, allowing 

the catalog data themselves to determine their optimal values and associated uncertainty for each 

source zone in an objective manner. Figures 5.3.2-4 through 5.3.2-9 show the values of the 

smoothing parameters and their + one-sigma ranges for magnitude-weight Cases A, B, and E, 

using a moderate prior for b. 

On Figures 5.3.2-4 through 5.3.2-9, the source zones are sorted by size, with the small 

seismotectonic zones on the left side, and the Midcontinent and the Mmax zones on the righthand side. The EPRI-SOG equivalent values (adjusted for differences in cell size) are provided 

for the sake of reference; the equivalence is only approximate because of some of the differences 

mentioned earlier between the two formulations of smoothing and because of potential 

limitations in the adjustment for size. 

On Figure 5.3.2-4, the small- and moderate-size seismotectonic zones show a broad variation in 

the objectively determined values of σ Δν : zones with high seismicity such as Reelfoot Rift show 

higher values (less smoothing), while zones with low seismicity such as AHEX show lower 

values (more smoothing). The large MidC and Mmax zones show similar values as the active 

zones. Relative to the EPRI-SOG values, the objectively determined values indicate less 

smoothing, except for the seismotectonic zones with low seismicity. Comparing Figures 5.3.2-6 

and 5.3.2-8, to Figure 5.3.2-4 we note that the objective approach assigns significantly more 

smoothing to the cases where the lower-magnitude bins are downweighted. The reason for this is 

that the effective number of earthquakes in a source-zone is diminished when the low-magnitude 

data are down-weighted. The objective approach compensates for this smaller sample size by 

imposing more smoothing, thereby reducing spatial resolution. 

On Figure 5.3.2-5, there is zone-to-zone variation in the objectively determined values of σ Δb , 

there is a trend with size, but no trend with seismicity. It is important to notice that there is 

significantly more smoothing on b than for EPRI-SOG, indicating that the data favor a very mild 

geographical variation in b. Comparing Figure 5.3.2-7 and 5.3.2-9 to Figure 5.3.2-3, we note that 

the objective approach assigns slightly higher smoothing on b for the cases in which the lowmagnitude bins are downweighted. 

Figures 5.3.2-10 and 5.3.2-11 illustrate the effect of smoothing and seismic activity by 

comparing the results for the extended-crust source zones ECC-AM and ECC-GC, for case-A 

magnitude weights and moderate prior on b. ECC-AM has higher activity and the objective 
Chapter 5 

SSC Model: Overview and Methodology 

5-39 

procedure assigns to it low smoothing for rates (high σ Δν ). In contrast, ECC-GC has low activity 

and the objective procedure assigns to it approximately 10 times more smoothing for rates. Note 

that the scales for activity rate are different in the two figures. 

It is also useful to compare the above figures to Figures 5.3.2-12 through 5.3.2-15, which show 

results for the same source zones, for Case B and E magnitude weights and moderate prior on b.

Because the effective number of earthquakes is smaller, the objective procedure compensates by 

increasing the smoothing on rate. The effect is much more pronounced in ECC-AM. 

Figures 5.3.2-10 through 5.3.2-15 show that, by considering three alternative sets of magnitude 

weights together with an objective approach for smoothing, we are effectively sampling a broad 

range of smoothing parameters for rate. To further appreciate this, it is useful to examine the 

mean recurrence maps for Cases A, B, and E that will be presented in Sections 6.4 and 7.5. 

For the SLR source zone, the approach described above led to underestimation of the observed 

rates for magnitude 4.3 and higher. To obtain an adequate fit it was necessary to remove the prior 

distribution on β and to constrain the smoothing on β . This constraint was introduced by 

specifying a prior distribution of σ Δβ with a median of 0.01 and a COV of 30%, which appears 

as an additional multiplicative term in Equation 5.3.2-18. The need for this different treatment is 

that SLR appears to have a b-value that is substantially lower than that of the region as a whole, 

and that portions of SLR (particularly in the Charlevoix area) appear have even lower b-values. 

This is consistent with the experience of Petersen et al. (2008), who assign a lower b-value to 

Charlevoix. Figures 5.3.2-10 through 5.3.2-15, and all other figures shown later in this section 

and in Chapter 7 reflect this modified approach for the treatment of the SLR source zone. 

5.3.2.2.2 Sensitivity to Magnitude Weights, Strength of Prior, and Alternative Maps 

The six sets of recurrence maps obtained above were used to perform sensitivity calculations in 

order to quantify and illustrate the effect of the strength of the prior on b and magnitude weights, 

and alternative recurrence maps. Calculations were performed for the host zones under the most 

likely source-zone configuration. These calculations were also performed at other demonstration 

sites, but only representative results will be shown here. 

Figures 5.3.2-16 and 5.3.2-17 show the sensitivity to the strength of the prior on b, for the 

Manchester and Topeka sites. These results show essentially no effect on hazard, a result that 

was observed at other demonstration sites and for both PGA and 1 Hz SA. As a consequence of 

these comparisons, the strong prior on b is deemed unnecessary and is eliminated from further 

consideration. 

Figures 5.3.2-18 and 5.3.2-19 show the sensitivity to magnitude weights for the same two sites. 

These results indicate a moderate effect on hazard, particularly in areas of low seismicity.

Finally, Figures 5.3.2-20 and 5.3.2-21 show the effect of the eight alternative recurrence maps on 

the hazard at the same two sites, for Case B magnitude weights. In both cases, the effect is 

important. 
Chapter 5 

SSC Model: Overview and Methodology 

5-40 

Based on the above comparisons, only the moderate prior on b will be considered (except for 

SLR, where no prior is used), and the logic-tree branches associated with magnitude weights and 

the eight alternative realizations will be retained. 

5.3.2.2.3 Resulting Maps 

Figure 5.3.2-22 shows the map of mean recurrence parameters for the most-likely source-zone 

map in the logic tree. Figure 5.3.2-23 shows the associated uncertainties, in the form of COV of 

the rate and standard deviation of the b-value. Figures 5.3.2-24 and 5.3.2-25 show two 

realizations of the equally likely recurrence maps. Although the last two maps show areas of no 

activity (i.e., white areas), it is important to note that no region has a mean rate of zero (i.e., these 

white areas “move” from one map to another), and that these white areas almost always occur in 

areas of no seismicity. Note also that the areas of high activity change little between the mean 

map and the two realizations, indicating that the uncertainty in rate (in the form of the COV) is 

low in regions with abundant data. 

Maps of mean recurrence parameters for all source-zone configurations are shown in Sections 

6.4 (for Mmax zones) and 7.5 (for seismotectonic zones). All realizations of the alternative maps 

are shown in Appendix J.

5.3.2.3 Exploration of Model Results in Parameter Space 

This section explores the recurrence parameters obtained in the previous section by examining 

and discussing the results obtained at a few specific locations and comparing the recurrence 

parameters to the catalog data. The purpose of these comparisons is to demonstrate consistency 

with the data under a variety of conditions and to gain insights into the behavior of the model 

developed here. These comparisons will focus on the higher-weighted branches of the master 

logic tree (namely, the seismotectonic zonation with the narrow interpretation of PEZ and Rough 

Creek graben in the Midcontinent). Figure 5.3.2-26 shows the local areas considered in these 

comparisons. 

5.3.2.3.1 Regions of High Activity 

The first region to consider is East Tennessee, which is represented by the same polygon used by 

Petersen et al. (2008; see Figure 5.3.2-26). The purpose of this comparison is to demonstrate that 

the penalized-likelihood formulation does not cause unwarranted dilution of highly localized 

seismicity.

Figures 5.3.2-27 through 5.3.2-29 compare the observed seismicity within the polygon to the 

expected counts within the same polygon, as calculated from the recurrence maps source zone 

PEZ-N, which is the host zone for this polygon. For each recurrence map, the expected counts 

are calculated by (1) calculating the expected rate for each magnitude bin using the values of ν

and β for the cells covered by the polygon, taking into account that some cells are only partially 

contained within the polygon and accounting for Mmax (recall Equations 5.3.2-11 and 5.3.2-12), 
Chapter 5 

SSC Model: Overview and Methodology 

5-41 

(2) multiplying this rate by the equivalent period of completeness for that bin, and (3) summing 

the expected counts, beginning at the highest bin. The observed counts do not take integer values 

because they represent effective counts. The error bars on the data represent the 16%–84% range 

of statistical uncertainty and are calculated using the approach by Weichert (1980). Each of the 

eight curves represents expected counts (i.e., rate times equivalent period of completeness) for 

one of the eight equally weighted alternative maps. Figures 5.3.2-27 through 5.3.2-29 use the 

maps for magnitude-weight Cases A, B, and E, respectively. 

Figures 5.3.2-27 and 5.3.2-28 show a close agreement between model and data for Cases A 

and B. As anticipated, the results for Case A show a better fit to the low-magnitude data, while 

the results for Case B show a better fit for magnitude 4.3 and higher. Both figures also show that 

the eight curves are closely spaced, indicating low uncertainty in recurrence parameters in areas 

of high activity. 

The results for Case E on Figure 5.3.2-29 shows lower rates, with the expected counts slightly 

below the error bars for the M 4.3–5.0 magnitude bin. Because the objective smoothing imposes 

more smoothing for Case E, it is not surprising that the expected counts within a small region of 

high activity are somewhat lower than the observed counts. Nonetheless, the expected counts 

from Cases A, B, and E—taken as an ensemble—are consistent with the data, especially when 

the error bars are taken into account. 

Figures 5.3.2-30 and 5.3.2-32 show similar results for a °× 23 ° rectangular region in central 

New England, comprising Massachusetts and southern Vermont and New Hampshire (see Figure 

5.3.2-26). This region overlaps the NAP and ECC-AM seismotectonic zones, which are used to 

calculate the expected counts. Again, there is good agreement between model and data and the 

uncertainty in recurrence is low. 

5.3.2.3.2 Nemaha Ridge Area 

The Nemaha Ridge in Kansas and Oklahoma has experienced two M > 5.0 earthquakes in 

historical times, despite being in an area of moderate seismicity in the Midwest. The geometry 

considered (see Figure 5.3.2-26) is a rough average of the geometries considered by the EPRISOG (1988) project for the Nemaha Ridge. 

Figures 5.3.2-33 through 5.3.2-35 compare seismicity and recurrence parameters in the same 

manner used above. The two earthquakes in the M 5.0–5.7 interval (the highest intervals with 

data) are the April 24, 1867, and April 9, 1952, earthquakes. Figures 5.3.2-33 and 5.3.2-34 

(Cases A and B) show predicted rates that are at or slightly below the one-sigma error bars, 

indicating marginal agreement with the data. Figure 5.3.2-35 (Case E), shows less agreement.

The explanation for this result is that the effect of giving lower weights to the first two 

magnitude bins—which one would have expected to produce a better fit for the higher bins—is 

counteracted by higher smoothing. 

Although the rates of M > 5 earthquakes for this region are slightly underestimated, it is 

important to keep in mind that the TI team, after reviewing the literature on the Nemaha Ridge, 
Chapter 5 

SSC Model: Overview and Methodology 

5-42 

did not see a justification for identifying the Nemaha Ridge as a distinct seismotectonic zone. 

Two M > 5 earthquakes in this region are not sufficient to change that assessment. 

5.3.2.3.3 Regions of Low Activity 

Kernel methods have a tendency to predict very low rates in regions with few or no recorded 

earthquakes because the commonly used Gaussian kernel function decays very rapidly at 

distances greater than twice the kernel width. This problem is discussed by Frankel et al. (1996), 

where the problem is avoided by introducing an alternative “floor” based on a constant weight.

The penalized-likelihood approach developed here does not have this problem. As indicated in 

Section 5.3.2.1.2 and illustrated on Figure 5.3.2-1 for the simple formulation considered at first, 

the likelihood function for zero observed earthquakes allows for nonzero rates and has a mean 

rate of 1/AT, which acts as a natural floor for the activity rate. This result also applies to one cell, 

if there is no penalty function linking the cell’s parameters with its neighbors’. Introduction of 

the penalty function has two effects on this floor. On the one hand, it increases the effective area 

in the denominator, thereby reducing the mean rate. On the other hand, it also elevates the rate if 

there is activity near the cell under consideration. Examination of the maps on Figure 5.3.2-16 

and those in Sections 6.4 and 7.5 suggests that the rates do not drop rapidly as one moves into 

regions of very low activity, as happens with the Gaussian kernel (where the rate decays as 

])/(21exp[

2 − x σ , where x is the distance to the closest earthquake and σ is the kernel size).

Figures 5.3.2-36 through 5.3.2-38 compare seismicity and recurrence parameters for a °× 23 °

rectangular region in the southern Florida Peninsula near Miami (see Figure 5.3.2-26). There is 

good agreement between the recurrence curves and the one earthquake in the catalog. The mean 

annual rate of M 5 or greater is approximately 0.01 earthquakes (for an area of approximately 5.5 

squared equatorial degrees). These figures also show a large spread between the alternative 

recurrence curves (especially for the reduced-magnitude weights), indicating a high uncertainty 

in rates. 

Figures 5.3.2-39 through 5.3.2-41 provide similar comparisons for a °× 23 ° rectangular region 

in northern Minnesota, around St. Paul (see Figure 5.3.2-26). Although there are no earthquakes 

within this area, the model predicts activity rates that are comparable to those obtained for 

Miami. 

These two sets of results demonstrate the effect of a natural floor that arises from consideration 

of the full likelihood function for the rate. This natural floor has the advantage that it does not 

require any external assumptions regarding the spatial extent that should be used to determine the 

floor rate. 

5.3.2.4 Consideration of Constant b-Value Kernel Approaches 

In addition to the penalized-likelihood approach, this project evaluated kernel approaches as 

alternatives for the calculation of recurrence parameters. Both fixed size (e.g., Frankel, 1995) and 

adaptive (e.g., Stock and Smith, 2002) were evaluated and exercised in the early stages of this 
Chapter 5 

SSC Model: Overview and Methodology 

5-43 

project. In the end, only the penalized-likelihood approach was retained in the logic tree. The 

rationale for this decision is provided below. 

The first consideration is the specification of kernel size. In most applications of the kernel 

method for PSHA applications (e.g., Petersen et al., 2008), the kernel size is fixed spatially and is 

assessed subjectively, although methods exist for the objective selection of kernel size (e.g., 

Silverman, 1986). The adaptive kernel approach of Stock and Smith (2002) is partially objective. 

It begins with an arbitrary kernel size, and then it applies a location-dependent adjustment that 

depends on the density of data. This approach can be made fully objective, as illustrated below.

In contrast to the approach used in most previous PSHA applications, the penalized-likelihood 

approach employed in this project is objective, in the sense that it determines the optimal degree 

of smoothing for each source zone (recall Figures 5.3.2-4 through 5.3.2-9), finding the best 

tradeoff between statistical precision and spatial resolution. This consideration of objectivity is 

not as important as those that follow, however. Although objective approaches are desirable, 

there are situations in PSHA where informed judgment is required because the data and 

statistical models are not sufficient. 

The second consideration is adaptability. Fixed kernel approaches cannot provide higher spatial 

resolution where data are abundant and lower resolution where data are sparse. The adaptive 

kernel approach provides adaptability by performing an initial calculation of rate and then 

adjusting the kernel size for each location based on the result of this calculation. The penalizedlikelihood approach provides adaptability because the likelihood function is narrower where data 

are abundant and broader where data are sparse (recall Figures 5.3.2-1 and 5.3.2-2). As a result, 

the relative effect of the penalty terms (which tends to reduce roughness in the recurrence 

parameters) is weaker where data are abundant and stronger where data are sparse. The 

comparisons shown earlier for East Tennessee demonstrate the adaptability of the penalizedlikelihood approach. 

The third consideration is that of geographical variation of b. The kernel approaches (both fixed 

and adaptive), as they have been implemented so far for PSHA, do not allow for geographical 

variation in b. In contrast, the penalized-likelihood approach allows for geographical variation in 

b. Furthermore, smoothing on rate and on b is controlled by separate smoothing parameters, 

allowing for more variation in rate and less variation in b, as the data and the technical 

community’s intuition suggest. This ability to allow variation in b is important for large source 

zones thousands of kilometers across and encompassing different tectonic settings, such as those 

in the Mmax branches of the master logic tree. For these large source zones, some geographical 

variation in b should not be precluded a priori.

The fourth consideration is the quantification of epistemic uncertainty. The two kernel 

approaches, as they have been implemented so far for PSHA, provide a simplistic representation 

of epistemic uncertainty in rate and b. This representation essentially treats the source zone as 

having constant rate and b for the purposes of calculating uncertainty, and then assigns the 

resulting COV in rate and standard deviation in b to the entire source zone. This approach 

underestimates the true uncertainty. It is possible to obtain more realistic estimates of the 

uncertainty by using bootstrapping (i.e., fitting the kernel model to multiple synthetic catalogs), 

but the number of alternative maps required to obtain a stable estimate of the uncertainty in 
Chapter 5 

SSC Model: Overview and Methodology 

5-44 

hazard is likely to be large. The penalized-likelihood approach combined with MCMC provides a 

realistic representation of uncertainty in the hazard because it samples the entire penalizedlikelihood function for the cells, thereby providing an estimate of the uncertainty in both rate and 

b for each cell, and the associated correlations. In particular, this uncertainty, as measured by the 

COV, is higher in regions of low activity than in regions of high activity (again, recall Figures 

5.3.2-1 and 5.3.2-2). In addition, the penalized-likelihood approach also incorporates the 

epistemic uncertainty in the smoothing parameters, as represented by the error bars on Figures 

5.3.2-4 through 5.3.2-9). Considering multiple kernel sizes in the logic tree (e.g., Petersen et al., 

2008) also captures this uncertainty, but in a subjective manner. Furthermore, the penalizedlikelihood approach combined with MCMC and with the eigenvalue-based sampling scheme 

presented here provides an efficient representation of epistemic uncertainty (including 

correlations between cells) by means of eight alternative maps. 

A fifth consideration is the rates in regions of very low seismicity. The fixed kernel approach, 

and to a lesser extent the adaptive kernel approach, yield very low estimates in these regions.

This problem may be resolved by the introduction of a somewhat artificial floor level, or by 

using a different kernel shape. The penalized-likelihood approach, on the other hand, provides a 

natural floor that is consistent with the data (or lack thereof) in these regions. This floor is based 

on the understanding that the observation of zero earthquakes during a certain time interval does 

not necessarily imply a rate of zero, but it does imply that the rate is unlikely to be moderate or 

high. 

In relation to these regions of low seismicity, there may be valid economical and structuralengineering reasons for imposing minimum design values in building codes—and these values 

may exceed the hazard computed from the natural or artificial floor values discussed here. These 

considerations are the responsibility of code-writing committees and should be kept separate 

from the process of estimating recurrence parameters and computing seismic hazard. 

A sixth consideration is that the choice between penalized likelihood and kernel smoothing is a 

choice between statistical tools, not a choice between different conceptual models regarding the 

spatial distribution of future seismicity. Both approaches implement the same conceptual model, 

but apply different statistical tools—each with its own strengths and weaknesses, as discussed 

above. 

To illustrate this last point, it is useful to compare the result from the penalized-likelihood and 

kernel-smoothing methods for selected source zones (and magnitude-weight Case A), using the 

same catalog and completeness model. Figure 5.3.2-42 shows the recurrence parameters 

calculated for three of the seismotectonic zones, spanning a broad range of source-zone size and 

rate density). These results were obtained using an initial kernel size calculated by crossvalidation (Silverman, 1986), and then applying an adaptive-kernel (Stock and Smith, 2002). 

This approach is an objective and adaptive implementation of the Gaussian kernel method. 

Comparison of the rates on Figure 5.3.2-42 to the corresponding portions of Figure 5.3.2-22 

shows a good agreement in most regions, particularly in regions of high activity such as portions 

of NAP and regions of moderately low activity such as portions of ECC-AM. The main 

difference is in the areas of very low activity (e.g., central Texas, northern North Dakota, 

offshore areas in the northeast of the study region), where the kernel approach predicts 
Chapter 5 

SSC Model: Overview and Methodology 

5-45 

essentially zero rates but the penalized-likelihood approach predicts low (but nonzero) rates. 

Another fundamental difference is that the kernel approach, as currently implemented, does not 

produce spatially variable estimates of uncertainty such as those shown on Figure 5.3.2-23. 

All these considerations led the project TI Team to the decision to retain only the penalizedlikelihood approach (together with MCMC and eigenvalue-based sampling) for the purpose of 

calculating recurrence parameters and their uncertainty. 

5.3.2.5 Comparison to EPRI-SOG Approach 

The penalized-likelihood approach used in this project has a number of elements in common 

with the EPRI-SOG (1988) methodology, but there are also substantial differences in 

implementation. This section summarizes and discusses the common elements and the 

differences in the calculation of recurrence parameters between this project and the EPRI-SOG 

project. 

The basic formulation of the problem is the same for this project and the EPRI-SOG project. 

Both projects divide a source zone into rectangular cells, (using partial cells at the edges to honor 

the geometry of the source zone), both projects formulate the likelihood function for ν and β in 

each cell using magnitude bins, both projects introduce penalty functions (in terms of ] ln[ν and 

β ) that increase continuity between cells, and both projects introduce a prior distribution for β . 

There are some differences in the way the penalty terms are computed. In particular, this project 

uses the standard form of the finite-difference Laplacian operator, using a slight adjustment to 

correct for the effect of latitude on the East-West size of the finite-difference grid. In contrast, 

the EPRI-SOG project uses the difference between a cell and the average of all its neighbors 

(which is not too different from the average of the Lapacians computed along the longitudelatitude grid and along a grid rotated 45 degrees from it, without correcting in either case for 

difference in the size of the finite-difference grid). The effect of these differences is believed to 

be small, and the approach used in this project is preferable because it is isotropic with respect to 

distances in kilometers. There are also differences in parameterization (i.e., this project uses 

standard deviations σ Δν and σ Δβ , while the EPRI-SOG project uses quantities that multiply the 

squared difference between a cell and its neighbors), but these differences are of no consequence. 

The main difference between this project and the EPRI-SOG project is in the treatment of 

epistemic uncertainty. This project captures epistemic uncertainty by working with the full 

penalized likelihood function, which contains all information about the “center, body, and range” 

of the distribution of recurrence parameters, as well as information about the correlation between 

recurrence parameters in nearby cells. This penalized likelihood function is sampled using 

Markov Chain Monte Carlo (MCMC), which generates many realizations of the recurrence 

parameters. These realizations are then used to construct eight representative realizations by 

computing the covariance matrix of the recurrence parameters, and then using a Karhunen–

Loève expansion of this covariance matrix, together with Latin Hypercubes to generate a set of 

eight realizations that represent the mean and epistemic uncertainty in recurrence parameters. In 

contrast, the EPRI-SOG methodology works only with the maximum penalized likelihood 
Chapter 5 

SSC Model: Overview and Methodology 

5-46 

estimates of the recurrence parameters. The EPRI-SOG study implemented a “bootstraping” 

procedure in its software (i.e., generating multiple synthetic catalogs and performing the 

maximum penalized likelihood calculations for each catalog) to quantify uncertainty, but this 

procedure was never used by the EPRI-SOG (1988) project in production calculations that went 

all the way to hazard (and it is believed to be impossible in practice, due to the number of 

alternative recurrence maps required). 

Another difference relates to the smoothing parameters σ Δν and σ Δβ . This project calculated 

optimal values of these parameters using an objective approach, while the EPRI-SOG project 

specified multiple values of the equivalent smoothing parameters using expert opinion (aided by 

statistical diagnostics). This project also treated σ Δν and σ Δβ as free hyperparameters in the 

MCMC, thereby capturing their epistemic uncertainty and the effect of that uncertainty on the 

uncertainty in ν and β . 

There is also a small difference in the treatment of magnitude uncertainty in the catalog. This 

project counts earthquakes by using “event factors” different from unity, as discussed earlier. In 

contrast, the EPRI-SOG project uses a uniform magnitude M* different from the best-estimate 

magnitude. Analysis and numerical tests in Chapter 3 indicates that the two approaches are 

equivalent in principle, but the use of event factors is preferable because it avoids edge effects at 

the lower magnitudes. 

An area in common is the calculation of completeness times. Prior to performing recurrence 

calculations for each team, source zone, and smoothing option, the EPRI-SOG (1988) project 

performed a coupled recurrence and completeness analysis, using a zoneless penalized 

maximum-likelihood formulation for recurrence, together with certain assumptions regarding 

completeness (e.g., the detection probability does not decrease with time or with magnitude). 

This project followed the same approach, using the same EPRI-SOG formulation and software, 

but using the new catalog and an updated map of the completeness region. These calculations are 

documented in Section 3.5. 

5.3.2.6 Assessment of the Lombardi Study 

In a study of the 1990–2001 M > 1.9 Southern California earthquakes, Lombardi (2003) 

observes that the catalog of all events (i.e., main shocks and aftershocks combined) follows an 

exponential magnitude distribution, but the catalog of main shocks deviate from exponential, 

with flattening at low magnitudes. Lombardi then proposes the following model: (a) the 

magnitude distribution for the population of all events is exponential, and (b) the magnitude 

distribution of main events may be constructed as the distribution of the maximum of N

independent identically distributed (iid) exponential magnitudes, where N is the number of 

events in a cluster (as determined by the declustering algorithm). This model predicts a mainshock magnitude-recurrence curve that deviates from exponential in the M 1.9–2.5 range, and 

this deviation is observed in the data. 
Chapter 5 

SSC Model: Overview and Methodology 

5-47 

One physical problem with this model is the assumption of iid magnitudes within a cluster. One 

would expect that the same physical factors that introduce tight spatial and temporal clustering of 

earthquakes would also introduce correlation in their magnitudes. 

There are also a number of alternative explanations for the observed deviation from 

exponentially distributed main shocks. One possible explanation is that the 1900–2001 Southern 

California catalog may not be complete down to M 1.9. In fact, Felzer (2008) finds that the 

lowest complete magnitudes for Southern California during the period 1993–1997 are in the M

2.7–3.0 range and that completeness down to magnitudes near 2.0 was only achieved during the 

period 2000–2007. Another possible explanation is edge effects associated with incomplete 

clusters that include some aftershocks with M < 1.9 and a main event with M > 1.9 (and for 

which N has been underestimated). 

Even if the observed deviation from exponentiality were real and not an artifact of 

incompleteness or edge effects, there are a number of reasons why it would not have large 

practical implications for this project. The reason for this is that this deviation is localized, 

extending only over the lowest 0.3- to 0.5-magnitude units. This project (and, to a lesser degree, 

EPRI-SOG) use alternative sets of magnitude weights to allow for deviations from exponentiality 

and other problems that may arise with magnitudes near the cutoff. Recall that magnitude-weight 

Cases B and E (which, together, carry 70% of the total probability in the logic tree) give 10% 

and 0% weight to the first magnitude bin (see Table 5.3.2-1). In addition, the formulation of the 

likelihood function in terms of magnitude bins does not work with the local slope of the 

magnitude-recurrence data, reducing the effect of any localized deviations from exponentiality. 

Finally, the completeness analysis for magnitude-weight Cases A and B would likely 

compensate for any deviation from exponentiality by altering the completeness times. 

In summary, even if the deviations from main shock exponentiality postulated by Lombardi 

(2003) were real, they would have no effect on the b-values computed in this project. 

5.3.3 Estimation of Recurrence for RLME Sources 

The earthquake recurrence models for the RLME sources are somewhat simpler than those 

described in Section 5.3.2 in that the magnitude range for individual RLMEs is relatively narrow 

and their spatial distribution is limited geographically such that spatial variability is not an issue. 

(Note that for simplicity in this section and later in the report, the term RLME is used to refer to 

the actual past earthquakes and the forecast future occurrences; the term RLME source is used to 

refer to the seismic source used to model the spatial and temporal distribution of the RLMEs.) 

This limits the problem to one of estimating the occurrence rate in time of a point process. The 

data that is used to assess the occurrence rates are derived primarily from paleoseismic studies 

and consist of two types. In many cases, the data provide estimated ages of the paleoearthquakes 

such that the times between earthquakes can be estimated. In other cases, the data provide an 

estimate of the number of earthquakes that have occurred post the age of a particular 

stratigraphic horizon. These data can be easily used to derive estimates of the RLME occurrence 

rates and their uncertainty. 
Chapter 5 

SSC Model: Overview and Methodology 

5-48 

The estimation of the RLME occurrence rates is dependent on the probability model assumed for 

the temporal occurrence of these earthquakes. The standard model applied in most PSHA studies 

and the one adopted for most RLME sources in this study is the Poisson model in which the 

probability of occurrence of an RLME in a specified time period is completely characterized by a 

single parameter, λ, the rate of RLME occurrence. The approaches used to assess λ and its 

uncertainty are described in Section 5.3.3.1. The principal features of the Poisson process are that 

it is “memoryless”—the probability of occurrence in the next time interval is independent of 

when the most recent earthquake occurred, and the time between earthquakes is exponentially 

distributed with a standard deviation equal to the mean time between earthquakes. 

For two RLME sources, the data are sufficient to suggest that the occurrence of RLMEs is more 

periodic in nature (the standard deviation is less than the mean time between earthquakes). For 

these RLME sources a simple renewal model can also be used to assess the probability of 

earthquake occurrence. This model takes into account the time that has elapsed since the most 

recent RLME occurrence in making an estimate of the probability of occurrence in the future. 

The probability of occurrence for renewal models is time-dependent in that the probability of 

occurrence in the next time interval is dependent upon the elapsed time since the most recent 

earthquake. The approaches used to assess the RLME occurrence probabilities for a renewal 

model are presented in Section 5.3.3.2. 

5.3.3.1 Estimation of Occurrence Rates for the Poisson Model 

The estimation of the uncertainty distribution for the rate parameter λ of a Poisson process uses 

the following general framework: 

• Define a likelihood function that represents the probability of seeing the observed sample of 

data given a specified rate parameter λ. 

• Compute the likelihood values for a full range of the rate parameter λ. 

• Normalize these likelihood values to create a probability distribution for λ. 

• Incorporate uncertainty in the input data by repeating the process for the weighted alternative 

data sets and computing a weighted combination of the resulting probability distributions 

for λ. 

• Represent the resulting probability distribution by a discrete approximation for 

implementation in hazard analysis. 

The likelihood functions used to implement this process depend upon the type of paleoseismic 

data available. The recurrence data fall into two general categories. In the first, the data consist 

of an estimate of the number of earthquakes that have occurred after the deposit of a datable 

stratigraphic horizon, but estimates of the actual ages of the individual earthquakes are not 

available. These type of data are analogous to the assessments made for historical seismicity 

where the data consist of the number of earthquakes that have occurred within the period of 

catalog completeness. The second type of paleoseismic data are estimates of the actual ages of 

individual earthquakes. If these data are available, they provide estimates of the intervals 

between individual earthquakes that can be used to assess the average recurrence interval of 
Chapter 5 

SSC Model: Overview and Methodology 

5-49 

RLMEs. The following subsections describe the mathematical formulation used to assess 

earthquake recurrence rates from these two general types of paleoseismic data. 

5.3.3.1.1 Earthquake Count in a Time Interval 

The data available in this case is an estimate of the number of earthquakes, N, that have occurred 

in a known time interval T. For a Poisson model, the probability of observing N events in time 

interval T is given by 

!

}exp{)( )( NT T Nf

N λ −λ = (5.3.3-1) 

This leads to the likelihood function for a rate parameter of λi given the observed data (N,T): 

!

}exp{)( ),( NT T TNL i

N

i

i

λ λ λ − = (5.3.3-2) 

Figure 5.3.3-1 shows the relative likelihood based probability distribution developed using 

Equation 5.3.3-1 for the case where N equals two earthquakes and T equals 2,000 years. The 

resulting normalized uncertainty distribution for λ is in fact a gamma distribution with a mean 

value of (N+1)/T (e.g., Benjamin and Cornell, 1970). The mean differs from the maximum 

likelihood estimate of λ, which is N/T due to the skewness of the normalized likelihood 

distribution. In the case where the observed count is zero, the mean estimate of λ from the 

normalized likelihood function would be 1/T. This is analogous to the “natural floor” in the 

seismicity-based estimates of earthquake recurrence rates discussed in Section 5.3.2.1.1. 

5.3.3.1.2 Earthquake Recurrence Intervals 

The data available in this case are estimates of the occurrence times of a sequence of N+1 

earthquakes obtained from dating of paleoseismic features or known occurrence times from the 

historical record. The estimated dates for the N+1 earthquakes provide N values of the times 

between earthquakes, ti, plus the open interval since the most recent RLME, t0. The Poisson 

process produces an exponential distribution for the time between occurrences: 

}exp{1)(

}exp{)(

tF t

tf t

λ

λ λ

−−=

= −

 (5.3.3-3) 

This leads to the likelihood function for a rate parameter of λi given the observed data 

(ti, i = 1, N, t0): 

[ ] ⎭

⎬

⎫

⎩

⎨

⎧

⎥

⎦

⎤ ⎢

⎣

⎡ ∏ ∑ +×−=−×= = =

0

1

0

1

0 tFtfttL exp)(1)(),( tt

N

i

i i

N

i

N

i

λ ii i λλ (5.3.3-4) 

The form of the likelihood function indicates that specification of the dates for the intermediate 

events is not needed as the term 0

1

tt

N

i

∑ i + =

 is equal to the elapsed time since the oldest earthquake 
Chapter 5 

SSC Model: Overview and Methodology 

5-50 

in the sequence. The likelihood function given by Equation 5.3.3-4 is equivalent in form to that 

given by Equation 5.3.3-2 and leads to the same gamma-shaped uncertainty distribution for λ

with mean ⎟

⎠

⎞ ⎜

⎝

⎛

+ ∑ + =

0

1

)1( ttN

N

i

i . 

The maximum likelihood estimate of λ from Equation 5.3.3-4 is N/ ⎟

⎠

⎞ ⎜

⎝

⎛

∑ + =

0

1

tt

N

i

i . This differs from 

a common practice of using the inverse of the average of the recurrence intervals due to the 

inclusion of the length of the open interval t0 in the denominator. However, neglecting the open 

interval is ignoring information. The use of Equation 5.3.3-4 is considered more appropriate 

because it incorporates of all of the available information. 

5.3.3.1.3 Representation of Continuous Distribution for λ by a Discrete Approximation 

The logic tree structure is generally used to represent uncertainty in the inputs to a PSHA. In a 

logic tree, uncertainty distributions are represented by a (small) set of discrete alternatives with 

assigned probability weights. Miller and Rice (1983) provide a set of discrete approximations for 

arbitrary continuous probability distributions. Their five-point approximation was chosen to 

represent the distributions for λ developed for the RLME sources. The Miller and Rice (1983) 

five-point discrete approximation is given in Table 5.3.3-1. The first column indicates the 

location of the five discrete values for the variable in terms of their cumulative probability levels 

in the defined continuous distribution. These are illustrated by the five horizontal dashed lines in 

the lower panel of Figure 5.3.3-1. The second column lists the probability weights to be assigned 

to the five discrete values of the variable. The number of decimal points in the probability 

weights given in Miller and Rice (1983) perhaps implies too high a degree of precision. For 

application in the CEUS project, these probability weights are approximated by the values listed 

in the third column. 

Application of the five-point approximation given above to the example shown on Figure 5.3.3-1 

yields a discrete distribution with λ = 00149.0 and 000849 σ λ = .0 . The values for the 

continuous gamma distribution are λ = 0015.0 and 000866 σ λ = .0 , indicating that the discrete 

approximation does a good job of capturing the first two moments of the skewed continuous 

parameter distribution. 

5.3.3.1.4 Use of Fault Slip Rates 

In a few cases, the data used to estimate occurrence rates for RLMEs is in the form of fault slip 

rate. In these cases the value of λ is obtained by converting the fault slip rate into a moment rate 

and then dividing by the seismic moment of an RLME, i.e.: 

RLMEM )(

SA

O

μ λ = (5.3.3-5) 
Chapter 5 

SSC Model: Overview and Methodology 

5-51 

where S is the fault slip rate, A is the total area of the fault surface, μ is crustal rigidity (taken to be 

3×1011 dynes/cm2

), and RLMEM )( O is the average seismic moment of an RLME. The fault slip 

rate is computed by dividing the cumulative fault offset, Dcum, by the length of time over which it 

occurred, T: 

T

D S cum = (5.3.3-6) 

5.3.3.2 Estimation of Occurrence Rates for a Renewal Model 

A renewal model for the occurrence probability of earthquakes is applied when the data suggest 

a more periodic behavior for the occurrence times between earthquakes than implied by the 

Poisson model. There are a variety of distributions that have been used to model the variability in 

the time between events, such as the lognormal, Weibull, and gamma distributions. Recently, 

Matthews et al. (2002) have proposed a model based on the inverse Gaussian distribution for 

inter-arrival times of repeated large ruptures on a fault. This model, termed the Brownian 

Passage Time (BPT) model was used by the Working Group (2003) to assess the probabilities of 

large earthquakes in the San Francisco Bay area. Ellsworth et al. (1999) and Matthews et al. 

(2002) propose that the BPT model is more representative of the physical process of strain 

buildup and release on a seismic source than the other distribution forms that have been used for 

renewal models (e.g., the lognormal). Based on these arguments, the BPT model was used in this 

analysis. 

For the BPT model, the time interval between earthquakes, t, is distributed with probability 

density given by 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ − ⎟ − ⎠

⎞ ⎜

⎝

⎛ = t

t

t tf

In

2

2 2/1

32 2

)( exp 2 )(

αμ

μ

πα

μ (5.3.3-7) 

and cumulative probability given by 

( )

( ) αμμ

αμμ

α

///)(

///)(

)]([)]([)(

2

1

2

/2

1

2

tttu

tttu

tuetutF

+=

−=

−Φ+Φ=

 (5.3.3-8) 

where μ is the mean inter-arrival time (repeat time), α is the aperiodicity coefficient (COV of t), and 

Φ( ) is the standard normal cumulative probability function. 

Given a sample of N time intervals and one open interval since the most recent earthquake, t0, the 

likelihood function for the observed data set is given by 

[ ])(1)(),( 0

1

L tFtf

N

i

∏ i −×= =

αμ (5.3.3-9) 
Chapter 5 

SSC Model: Overview and Methodology 

5-52 

with f(t) and F(t) given by Equation 5.3.3-7 and 5.3.3-8, respectively. Because of the very limited 

size of the data samples for the RLME sources where the model is applied, estimation of the 

aperiodicity coefficient, α, is highly uncertain. Therefore, the value of α is constrained to values 

reported from examination of larger data sets. Based on examination of a number of data sets, the 

Working Group (2003) developed an uncertainty distribution for the aperiodicity coefficient for the 

BTP model consisting of three weighted values for α of 0.3 (weight 0.2), 0.5 (weight 0.5), and 0.7 

(weight 0.3). The Working Group (2003) weighted distribution was adopted to constrain the value 

of α. 

The process described in Section 5.3.3.1 was used to develop a likelihood-based distribution for μ

given a specified value of α. A broad range of values for μ were input into Equation 5.3.3-9 to 

compute likelihood values. These likelihoods were then normalized to form a probability 

distribution for μ for each of the three values of α. This distribution was then represented by the 

discrete five-point approximation from Miller and Rice (1983) described above. 

For the renewal recurrence model, the probability of an earthquake in the next time interval Δt is 

given be the expression: 

)(1

)()( event ( ) to in time

0

0 0

00 tF

tFttF P ttt renewal −

+ Δ − =Δ+ (5.3.3-10) 

The basic PSHA formulation used to assess the site hazard assumes that the occurrence of 

individual earthquakes conforms to a Poisson process. In order to combine the hazard from 

earthquakes defined by a renewal process into the total hazard, an equivalent Poisson rate is defined 

such that a Poisson process will give a probability of at least one earthquake in time interval Δt that 

is equal to the probability given by Equation 5.3.3-10. The equivalent Poisson rate, λrenewal, is given 

by the expression: 

[ ] P tttt λrenewal −−= renewal event (1ln 00 + Δ /) to in time Δ (5.3.3-11) 

A time period of 60 years was chosen as the time period of interest for application (20-year license 

life plus 40-year plant design life). The time t0 was set at January 1, 2011. The corresponding values 

of λrenewal computed from the five weighted values of μ were then used as a discrete uncertainty 

distribution for the rate of RLMEs. Distributions are developed for each value of α, resulting in a 

total of 15 weighted alternative RLME rates. 

5.3.3.3 Incorporating Uncertainty in the Input 

The typical uncertainties encountered in characterizing the occurrence rates for RLME sources 

are uncertainties in the data set (i.e., specification of the number of earthquakes and the time 

span of their occurrence) and uncertainties in the actual ages of individual earthquakes or the age 

of the offset stratigraphic horizon used to define the time span. 

Uncertainties in the appropriate data set are handled by creating a probability distribution for 

occurrence rate for each data set and then including these alternatives in the seismic source 

model logic tree as weighted alternatives. Examples of this are the alternative time periods of 
Chapter 5 

SSC Model: Overview and Methodology 

5-53 

complete paleoseismic reporting (e.g., 2,000 vs. 5,500 years) and the alternative number of 

RLME earthquakes that are evident in the data for the Charleston RLME, discussed in Section 

6.1. A number of the other RLME source models also include alternative estimates of the 

number of RLMEs that have occurred in the recent past as discrete alternative models in the 

seismic source model logic tree. 

Uncertainty in the age of individual earthquakes or the age of the offset marker horizon are 

typically expressed as a 90% or 95% confidence interval on the before present (BP) age, or as an 

age range (e.g., 10,000 to 12,000 years for the age of a marker horizon). This type of uncertainty 

is incorporated into the uncertainty distribution for the RLME rate parameter by simulating 

values of the age of the i

th RLME or of the total time span T from the expressed uncertainty 

distribution. The resulting values of ti or T are then used to develop a likelihood based 

continuous probability distribution for the rate parameter. The process is then repeated multiple 

times and the resulting probability distributions averaged to produce a composite continuous 

distribution for the rate parameter. This composite distribution is then represented by the fivepoint discrete approximation described above. 

For two of the RLME sources the available paleoseismic data consists of multiple samples 

providing constraints on the timing of past RLME occurrences. For the Charleston RLME, two 

types of data are used. One consists of samples whose ages are considered to be contemporary 

with the earthquake occurrence, denoted as CON ages. Each sample has its own age estimate 

with associated uncertainties. A distribution for the age of the associated RLME was developed 

by computing the relative likelihood that a range of possible ages produced the sample of age 

dates, assuming that the uncertainty in each age can be approximated by a normal distribution 

with the specified uncertainty ranges. These relative likelihoods were then normalized to produce 

a probability distribution for the RLME age. Figure 5.3.3-2 shows the resulting distributions for 

the ages of the five most recent Charleston RLMEs preceding the 1886 earthquake, labeled as 

“Con Ages.” 

The second type of sample data for the Charleston RLME is those that provide constraints on the 

event age in terms of representing points in time either before or after each earthquake 

occurrence. This additional age data was used to modify the CON age distributions by simulating 

ages from the CON age distribution and from the distribution for the constraining sample age 

and rejecting those simulations that violate the age constrains. The resulting earthquake age 

distributions are shown on Figure 5.3.3-2 as the “All Ages” distributions. 

These two sets of age distributions were then used to develop uncertainty distributions for the 

RLME occurrence rate. 

5.3.3.4 RLME Magnitude Distribution 

The RLME sources are intended to model the repeated occurrence of large earthquakes of similar 

size. The expected magnitude of the RLME is estimated from various sources of data and its 

uncertainty is expressed by a probability distribution in the RLME source logic tree. In addition, 

it is anticipated that there will be variability in the actual magnitude of each earthquake when it 

occurs, requiring the need for specifying an aleatory uncertainty for earthquake magnitude. For 
Chapter 5 

SSC Model: Overview and Methodology 

5-54 

this study, a simple uniform distribution is assumed, which implies maximum uncertainty. The 

width of this distribution is set to be the expected RLME magnitude ± 1⁄4-magnitude units, 

resulting in a range of 1⁄2-magnitude units. A 1⁄2-magnitude unit range implies a factor of 3 range 

in source dimensions and over a factor of 5 range in seismic moment. The 1⁄2-magnitude range 

was chosen as a typical representation of the variability of repeated large earthquakes occurring 

on a single source (e.g., Youngs and Coppersmith, 1985). 

5.4 Assessment of Future Earthquake Characteristics 

The CEUS SSC model has been developed for use in future PSHAs. To make this future use 

possible, the SSC model must be combined with a ground-motion characterization (GMC) 

model. At present, the ground-motion prediction equations (GMPEs) in use for SCRs such as the 

CEUS include limited information regarding the characteristics of future earthquakes. In 

contrast, GMPEs for active tectonic environments often include multiple characteristics, 

including style of faulting as defined by sense of fault slip and distance to the fault rupture. In 

anticipation of the possible future development of GMPEs for the CEUS that will make it 

possible to incorporate similar types of information, a number of characteristics of future 

earthquakes in the CEUS are assessed in this section. In addition to characteristics that might be 

important for ground-motion assessments, there are also assessed characteristics that are 

potentially important to the modeling conducted for hazard analysis. For example, assuming that 

the PSHA models earthquakes as finite fault ruptures, information is then needed about the 

relationship between magnitude of the earthquake and rupture dimensions, length-to-width 

aspect ratios, and the relationship between the rupture and the seismic source zone boundaries. 

The assessment by the TI Team of future earthquake characteristics was carried out in two parts. 

In the first, a set of characteristics believed to be representative of the entire CEUS study region 

was assessed. This set of characteristics is termed “default” because, in the absence of local data 

for a particular region, it would provide a basis for use in the PSHA calculations. The default 

characteristics and their assessed values are given in Table 5.4-1. The second assessment 

involved making estimates of the future earthquake characteristics for the individual seismic 

sources. These assessments were made by the TI Team by evaluating source-specific data. A 

summary of the source-specific assessments is given in Table 5.4-2. A brief description of the 

future earthquake characteristics is given below. 

The assessment of future earthquake characteristics for the entire CEUS study region is given in 

Table 5.4-1. Also included in Table 5.4-1 are representative references to data and interpretations 

that have been evaluated in the assessment of these characteristics. It should be noted that these 

references usually cite local or site-specific studies, and not evaluations across the entire CEUS 

SSC study region, because such studies are not available on a regional scale. In addition, the 

references only provide data for consideration by TI Team members in their assessments of the 

future earthquake characteristics; the assessed values in column 2 of the table are based on the 

assessments by the TI Team of the default characteristics that represent the current state of 

scientific knowledge” for the CEUS in the absence of source-specific information. 

In the characterization of individual seismic sources, if source-specific data suggest a difference 

from the default case, the characteristics were assessed for that particular source. The source-
Chapter 5 

SSC Model: Overview and Methodology 

5-55 

specific assessments summarized in Table 5.4-2 are discussed for each RLME source and Mmax 

source in Chapter 6 and for each seismotectonic zone in Chapter 7. The discussions in Chapters 6 

and 7 include a description of the assessments of the future earthquake characteristics, as well as 

the technical bases for the weights applied to the alternatives. As indicated in Table 5.4-2, those 

assessments that are the same as the default assessments are shown as italics; those assessments 

that are different from the default assessments due to source-specific information are shown in 

plain text. 

Subsequent to the finalization of the model for developing the HID and hazard calculations, 

minor revisions to the future earthquake characteristics were made to the ECC-AM and ECC-GC 

sources. The final characteristics are given in Table 5.4-2. These characteristics have little to no 

effect on the hazard, given the ground motion models that were used for the hazard calculations. 

However, future users of the CEUS SSC model should consider the characteristics given in 

Table 5.4-2 to be the final assessments for the CEUS SSC model. 

The Data Evaluation table for the assessment of default characteristics of future earthquakes in 

the CEUS is presented in Appendix Table C-5.4, and the Data Summary table in Appendix Table 

D-5.4. Each of the future earthquake characteristics is described below. 

5.4.1 Tectonic Stress Regime 

Some GMPEs provide different relationships as a function of compressional or extensional 

tectonic stress regimes. A variety of data sets, including the stress data compiled for the project 

by Zoback (2010), indicate the CEUS study region lies within a contemporary tectonic stress 

regime that is compressional. 

5.4.2 Sense of Slip/Style of Faulting 

Sense of slip of future earthquakes, which defines the style of faulting, is assessed based on a 

variety of data sets, including earthquake focal mechanisms, stress indicators, and the 

relationship between stress orientations and the geologic structure. The result of the assessment 

given in Table 5.4-1 is aleatory variability, which reflects the expected relative frequency of 

strike-slip versus reverse faulting averaged across the study region. 

5.4.3 Strike and Dip of Ruptures 

It is assumed that the GMPE for the CEUS will be capable of incorporating information about 

the characteristics of earthquake sources, modeled as finite faults in much the same manner as 

earthquake sources ares modeled in the WUS. Therefore, Table 5.4-1 includes a number of 

assessment results that address the expected geometry of future ruptures and, in some cases, the 

relationship of the geometry to earthquake magnitude. A key attribute of the geometry is the 

strike and dip (i.e., orientation) of the rupture surfaces. Assessment of the strike of future rupture 

surfaces was made using information from earthquake focal mechanisms, the structural grain of 

major fold and fault systems—unless the grain is judged to have no relationship to contemporary 

earthquake properties; and tectonic stress data in regard to the orientations and magnitudes of 
Chapter 5 

SSC Model: Overview and Methodology 

5-56 

principal stresses. Assessment of the dip of future rupture surfaces was dependent on style of 

faulting and derived from empirical data related to observed ruptures and evaluations of physical 

properties. 

5.4.4 Seismogenic Crustal Thickness 

From the standpoint of high-frequency energy release and seismic hazard, an important 

consideration is the geometry of the rupture within the seismogenic part of the crust. The 

thickness of the seismogenic crust (also called the seismogenic layer or seismogenic zone) varies 

spatially, but the results of the assessment shown in Table 5.4-1 represent an epistemic 

assessment of the average crustal thickness across the study region. This distribution can be 

modified locally to account for unusually thick or thin seismogenic crust at the scale of an 

individual seismic source. The assessment of seismogenic crustal thickness is based on the focal 

depth distributions of well-studied earthquakes, usually those lying within local or regional 

seismic networks, such that hypocentral depth can be determined with a high degree of 

confidence. However, uncertainties in focal depth across the study region vary considerably as a 

function of available hypocenter information. 

Given a focal depth distribution, physical considerations given by various researchers suggest 

that the base of the seismogenic zone is identified as lying near the base of the observed focal 

depths. For example, Scholz (1998) identifies the 300°C isotherm as corresponding to the onset 

of dislocation creep in quartz, which he interprets to control the seismic/aseismic transition zone 

by Scholz (1998). Tanaka (2004) and Tanaka and Ito (2002) compares high-quality thermal 

measurements and seismicity depth data to examine the conept that temperature is a fundamental 

parameter for determining the thickness of the seismogenic zone. Their gridded heat flow or 

geothermal gradient and D90, the depth above which 90% of earthquakes occur, correlated well 

with each other. The evaluated temperatures for D90 range between 250°C and 450°C. The 

consistency of temperature for D90 over a large depth interval almost all over the Japanese 

Islands leads these researchers to conclude that temperature is the dominant factor governing the 

focal depth in the crust. However, other evaluators have used criteria, such as the 95th percentile 

of the focal depth distribution. Given these alternative interpretations, and the uncertainty in 

focal depth assessments across the the study region, the generic and zone-specific assessments of 

crustal thickness presented in Tables 5.4-1 and 5.4-2 were made. 

As discussed in Chapter 8, uncertainty in crutal thickness is not a significant contributor to 

uncertainty in seismic hazard in the CEUS because the current ground motion prediction 

equations have only limited sensitivity to depth. However, in anticipation of future advances in 

the characterization of ground motions for CEUS earthquakes, additional analysis of focal depth 

data are presented. Given the assumption that the criterion of D90 is the correct interpretation of 

the base of the seismogenic layer, a high-quality focal depth data set was compiled based on 

those earthquakes having the best-resolved focal depths. The calculation of D90 is made for each 

of the seismic source zones. The assessment of seismogenic thickness and its uncertainty is, in 

turn, a function of the number of earthquake focal depths that exist for each source. A 

bootstrapping approach was used that uses the assumption that the random uncertainty in the 

focal depth of any given earthquake is about ±2 km and the uncertainty in the actual thickness is 

a function of the number of number of earthquakes that define D90. 
Chapter 5 

SSC Model: Overview and Methodology 

5-57 

Figure 5.4.4-1 shows the spatial distribution of earthquakes in the CEUS SSC Project catalog 

with E[M] magnitudes of 2.2 and greater. Figure 5.4.4-2 shows the spatial distribution of 

earthquakes in the CEUS SSC Project database having the best-resolved focal depths. This 

include smaller earthquakes for which E[M] magnitudes were not computed. In general, the 

spatial distribution of earthquakes with better quality depth determinations is similar to that of 

the full catalog. However, some areas, such as the Gulf Coast region and the upper Great Plains 

have limited coverage. 

Figure 5.5.4-3 shows histograms of focal depth for earthquakes within the Mmax source zones 

and Figure 5.5.4-4 shows histograms of focal depth for earthquakes within the seismotectonic 

source zones. Several of the seimotectonic source zones have limited to very limited data 

(AHEX, ECC-GC, GHEX, and OKA). Assessment of D90 for these sources was therefore based 

on assumed similarity with other sources. As discussed in Section 3.2.4, an attempt was made to 

identify fixed depth earthquakes. Dips in the histograms for a number of source zones at depths 

of 5, 10, and 18 km indicates that for some of the earthquakes flagged fixed depths may not be 

fixed. However, adding synthetic data to representing estimates of the number of missing 

earthquakes did not result in a significant difference in the estimate of D90. 

Bootstrap samples of focal depths were drawn from the observed focal depth distributions for 

each source zone. A normally distributed random depth error with a standard deviation of 2 km 

was added to each focal depth. The bootstrap samples were then used to compute an uncertainty 

distribution for D90. Table 5.4-3 lists the results of the analyses. The uncertainty range for D90 is 

typically ±1 km about the observed value. Three of the source zones (AHEX, GHEX, and OKA 

have too few good quality focal depths to make an assessment and the results for ECC-GC may 

also be too broad due to the limited sample size. 

The results presented in Table 5.4-3 can be used as part of use of the CEUS SSC model in sitespecific applications and to incorporate potential advancements on ground motion modeling. 

5.4.5 Fault Rupture Area 

In the hazard analysis, each event is associated with a moment magnitude from the recurrence 

relationship and, as a result, can be associated with a rupture area that is a function of that 

magnitude. A variety of empirical relationships between magnitude and rupture area have been 

proposed in the literature, most leading to very similar results for crustal earthquakes. Because of 

those similarities, it was judged sufficient to use a single relationship to represent the range of 

estimates. The relationship used (Somerville et al., 2001) was developed specifically for 

application in eastern North America, thus it is deemed to be applicable to the CEUS for this 

assessment. In the future, consideration should be given for updating this assessment with more 

recent relationships such as that given by Leonard (2010). 

5.4.6 Rupture Length-to-Width Aspect Ratio 

Given a rupture area, the shape of the rupture must be defined within the seismogenic crust. 

Based on an evaluation of observed ruptures for moderate-to-large earthquakes, an assessment 
Chapter 5 

SSC Model: Overview and Methodology 

5-58 

was made of the length-to-width aspect ratio. For smaller rupture areas, the aspect ratio is 

assessed to be equi-dimensional or one-to-one. For progressively larger rupture areas, the 

downdip width of the rupture surface, which varies depending on dip angle, will eventually 

involve the entire seismogenic crustal thickness. At still larger rupture areas, only rupture length 

will increase, leading to progressively larger aspect ratios. Such a model will result in large 

aspect ratios for large strike-slip earthquakes and somewhat lower aspect ratios for the samemagnitude reverse earthquakes, which is consistent with empirical observations. For the smaller 

equi-dimensional ruptures, the depth of the rupture surface is related to the focal depth 

distribution, following the approach given in NAGRA (2004, p. 174). That approach uses the 

focal depth distribution as a basis for the relative likelihood of the center pointof ruptures 

occurring at any particular depth. Given the small magnitudes of these earthquakes, the effect of 

this assumption on hazard is small. 

5.4.7 Relationship of Rupture to Source Zone Boundaries 

For a finite-fault SSC model, the locations of future earthquakes are defined by an epicenter and 

an associated rupture, the geometry of which is represented by the assessment results as 

discussed above in Sections 5.4.3 through 5.4.6. The event epicenters lie within the seismic 

source zone of interest, but it is also possible that the associated ruptures may propagate outside 

the source zone, depending on the properties assessed for the source boundary. If the source 

boundary is assessed as “leaky,” then ruptures will be allowed to extend beyond the boundary; if 

they are “strict,” the ruptures will be confined within the boundary. The earthquake epicenter is 

assumed to lie at the midpoint of the rupture length. Therefore, a leaky rupture would entail no 

more than 50% of the rupture length (for the particular case where the epicenter is located at the 

zone boundary). The assessment of whether a boundary is leaky or strict is related to the 

orientation of rupture surfaces and the expected orientation of ruptures in the adjacent seismic 

source zones. Sharp source boundaries defined by distinct changes in expected rupture 

geometries are likely to be strict boundaries. For example, a boundary of a seismic source zone 

that marks the distinct change in orientation of future earthquake ruptures would likely be 

assessed as having a strict boundary so that ruptures from one source with a particular orientation 

are not modeled with that orientation in the adjacent source. In all cases, the lengths of ruptures 

that are assessed to occur within seismic sources are checked to be sure that their rupture 

dimensions would not exceed the dimensions allowed within the source (and rupture across the 

source boundary, as applicable) for the earthquake magnitudes that are assessed. Across the 

region, the general continuity of expected rupture orientations results in the default assessment of 

leaky boundaries for most seismic source zones. 

5.5 Predicted Seismic Moment Rate 

The CEUS SSC seismic source model developed in Chapters 4, 5, and 6 provides an assessment 

of earthquake recurrence rates for the entire CEUS study region. These recurrence rates were 

used to compute the predicted mean seismic moment rate for the study region. The table below 

summarizes these results. Two thirds of the seismic moment rate results from the recurrence of 

New Madrid RLMEs. The remaining contribution is evenly split between the remaining RLME 

sources and the distributed seismicity sources. 
Chapter 5 

SSC Model: Overview and Methodology 

5-59 

Predicted Seismic Moment Rate for CEUS SSC Model 

Source 

Seismic Moment Rate 

(dyne-cm/year) 

Distributed Seismicity 3.2×1024

New Madrid RLME 1.0×1025

Remaining RLMEs 3.4×1024

Total 1.7×1025

Johnston et al. (1994) assessed a seismic moment rate for the SCR region of North America both 

including and excluding the New Madrid 1811-1812 earthquake sequence. Their assessment is 

listed in the table below in terms of seismic moment rate per 105

 km2. Also listed are the mean 

moment rates predicted using the CEUS SSC model and the area encompassed by the CEUS 

SSC seismic source model of 7.8 × 106

 km2. The results are similar excluding the New Madrid 

earthquakes and with a factor of 2 including the New Madrid earthquakes. Johnston et al. (1994) 

used moment magnitudes M 8.1–8.3. The characterization of the New Madrid RLME for the 

CEUS SSC model results in a mean magnitude for these earthquakes in updated magnitude 

assessments for these earthquakes s for these earthquakes are approximately M 7.5. The one-half 

magnitude difference in the moment magnitudes assigned to these earthquakes translates into 

approximatelty a factor of 5 in seismic moment. Thus, the difference in seismic moment rate 

assigned to the New Madrid sequence based on magnitude assessments for the three earthquakes 

easily accounts for differences in the estimated moment rate for the CEUS. Based on these 

comparisons it is concluded that the seismic moment rate predicted by the CEUS SSC model is 

consistent with the values estimated by Johnston et al. (2004). 

Seismic Moment Rates for the SCR Portion of North America 

Comparison Case 

Seismic Moment Rate Density 

(dyne-cm/year/105

 km2) 

Johnston et al. (1994) CEUS SSC Model 

Including New Madrid 4.5×1023 2.2×1023

Excluding New Madrid 1.07×1023 0.8×1023
Chapter 5 

SSC Model: Overview and Methodology 

5-60

Table 5.2.1-1 

Mesozoic-and-Younger Extended Superdomains (MESE) 

Superdomain 

Number

Total 

Area 

(km2)

No. of 

Domains Type Age Stress

Source

Stress 

Angle

mmax obs

From 

Catalog

Number of 

Earthquakes 

M ≥ 4.5

SE01* 1326660 6 EC CZ C F 6.3 65.8

SE02* 4369994 15 EC CZ C NF 7.9 871.7

SE03* 2125357 7 EC CZ C UK 7.3 32.9

SE04 1651160 1 EC CZ E NF 6.2 16.1

SE05 2149008 4 EC CZ U UK 5.2 4

SE06* 4057142 10 EC MZ C F 7.3 63.2

SE07* 5323365 21 EC MZ C NF 7.8 557.2

SE08* 3638444 8 EC MZ C UK 6.5 21.9

SE09 1272700 1 EC MZ E F 6.2 4

SE10* 1279577 4 EC MZ E NF 5.9 13

SE11 1196907 2 EC MZ E UK 5.2 1

SE12 4314292 14 EC MZ U UK 5.6 8

SE13 31132 1 EC PC C F 0 0

SE14 507439 2 EC PC C NF 5.5 8.5

SE15 22629 1 EC PC E UK 6.5 2

SE16 556326 3 EC PC U UK 5.4 1

SE17 82782 1 EC PZ C F 5.5 4.1

SE18 570732 4 EC PZ C NF 6.5 8.2

SE19 27315 1 EC PZ C UK 5.3 3

SE20 1257982 3 EC PZ U UK 6.1 11.3

* Indicates superdomain used to develop prior distribution. 

C—Compressive F—Favorable orientation PC—Precambrian

CZ—Cenozoic MZ—Mesozoic PZ—Paleozoic

E—Extensive NE—Non-extended crust U—Unknown

EC—Extended crust NF—Unfavorable orientation
Chapter 5 

SSC Model: Overview and Methodology 

5-61

Table 5.2.1-2 

Older Extended and Non-Extended Superdomains (NMESE) 

Superdomain 

Number

Total Area 

(km2)

No. of 

Domains Type Age Stress

Source

Stress 

Angle

mmax obs

From 

Catalog

Number of 

Earthquakes

M ≥ 4.5

SE13 31132 1 E PC C F 0 0

SE14* 507439 2 E PC C NF 5.5 8.5

SE15 22629 1 E PC E UK 6.5 2

SE16 556326 3 E PC U UK 5.4 1

SE17 82782 1 E PZ C F 5.5 4.1

SE18* 570732 4 E PZ C NF 6.5 8.2

SE19 27315 1 E PZ C UK 5.3 3

SE20 1257982 3 E PZ U UK 6.1 11.3

SN01 33900 1 NE MZ C F 0 0

SN02* 805784 2 NE MZ C NF 6.2 46.5

SN03* 835876 2 NE MZ C UK 6.4 92.6

SN04 599472 3 NE MZ U UK 5 2

SN05* 9759298 16 NE PC C F 6.7 225.2

SN06* 19633024 17 NE PC C NF 7.3 277.8

SN07* 34329412 38 NE PC C UK 6.8 765.6

SN08* 1519341 3 NE PC E F 5.7 22

SN09* 1689145 3 NE PC E NF 6.6 401.2

SN10* 2039146 3 NE PC E UK 5.6 13.4

SN11 9474115 20 NE PC U UK 6.4 37.1

SN12* 2592956 7 NE PZ C F 6.4 294.4

SN13* 1870538 6 NE PZ C NF 6.4 75.9

SN14* 6518060 16 NE PZ C UK 6.8 110.4

SN15 3645521 9 NE PZ U UK 5.7 12.7

* Indicates superdomain used to develop prior distribution. 

C—Compressive F—Favorable orientation PC—Precambrian

CZ—Cenozoic MZ—Mesozoic PZ—Paleozoic

E—Extensive NE—Non-extended crust U—Unknown

EC—Extended crust NF—Unfavorable orientation
Chapter 5 

SSC Model: Overview and Methodology 

5-62

Table 5.2.1-3 

Composite SCR Superdomains (COMP) 

Superdomain 

Number

Total Area 

(km2)

Number

of 

Domains Type Age Stress

Source

Stress 

Angle

mmax obs

From 

Catalog

Number of 

Earthquakes

M ≥ 4.5

SD01* 1326660 6 NA CZ C F 6.3 65.8

SD02* 4369994 15 NA CZ C NF 7.9 871.7

SD03* 2125357 7 NA CZ C UK 7.3 32.9

SD04 1651160 1 NA CZ E NF 6.2 16.1

SD05 2149008 4 NA CZ U UK 5.2 4

SD06* 4091042 11 NA MZ C F 7.3 63.2

SD07* 6129149 23 NA MZ C NF 7.8 603.7

SD08* 4474320 10 NA MZ C UK 6.5 114.5

SD09 1272700 1 NA MZ E F 6.2 4

SD10* 1279577 4 NA MZ E NF 5.9 13

SD11 1196907 2 NA MZ E UK 5.2 1

SD12 4913764 17 NA MZ U UK 5.6 10

SD13* 9790430 17 NA PC C F 6.7 225.2

SD14* 20140460 19 NA PC C NF 7.3 286.3

SD15* 34329412 38 NA PC C UK 6.8 765.6

SD16* 1519341 3 NA PC E F 5.7 22

SD17* 1689145 3 NA PC E NF 6.6 401.2

SD18* 2061775 4 NA PC E UK 6.5 15.4

SD19 10030441 23 NA PC U UK 6.4 38.1

SD20* 2675738 8 NA PZ C F 6.4 298.5

SD21* 2441270 10 NA PZ C NF 6.5 84.1

SD22* 6545375 17 NA PZ C UK 6.8 113.4

SD23 4903503 12 NA PZ U UK 6.1 24

* Indicates superdomain used to develop prior distribution. 

C—Compressive F—Favorable orientation PC—Precambrian

CZ—Cenozoic MZ—Mesozoic PZ—Paleozoic

E—Extensive NE—Non-extended crust U—Unknown

EC—Extended crust NF—Unfavorable orientation
Chapter 5 

SSC Model: Overview and Methodology 

5-63

Table 5.2.1-4 

Results of Analyses of Updated SCR Superdomains 

Superdomain 

Set

Average 

Number of 

Earthquakes 

≥4.5

Average 

b-value

Mean 

mmax obs

Standard 

Deviation

Bias 

Adjusted 

Mean m

u

MESE 232 0.85 7.05 0.75 7.35

NMESE 180 1.02 6.48 0.61 6.70

COMP 248 0.94 6.88 0.64 7.20
Chapter 5 

SSC Model: Overview and Methodology 

5-64

Table 5.2.1-5 

Source Zones, P(mu > 81⁄4) Values, and Weights on Kijko (2004) 

K-S-B Estimates 

Source P(m

u

> 81⁄4)

Weight Assigned to 

Kijko Approach

Study Region (paleo eq) 0.84 0

MESE-N 0.44 0.06

MESE-W (paleo eq) 0.83 0

NMESE-N (paleo eq) 0.87 0

NMESE-W 0.27 0.23

AHEX 1 0

ECC-AM 0.45 0.05

ECC-GC 0.78 0

GHEX 0.8 0

GMH 0.81 0

IBEB (paleo eq) 0.72 0

MidC-A 0.26 0.24

MidC-B 0.26 0.24

MidC-C 0.26 0.24

MidC-D 0.26 0.24

NAP 0.58 0

OKA 0.69 0

PEZ-N 0.65 0

PEZ-W 0.49 0.01

RR 0.67 0

RR-RCG 0.43 0.07

SLR 0.48 0.02

Note: ―Paleo eq‖ indicates that the zone uses paleoseismic evidence to constrain 

the size of the largest observed earthquake in that zone. In those cases, the 

Kijko approach is assigned zero weight. 
Chapter 5 

SSC Model: Overview and Methodology 

5-65

Table 5.2.1-6 

Mmax Distributions for the Two Example Seismic Sources 

Weight

Maximum Magnitude for:

MESE-N NAP

0.101 6.1 5.8

0.244 6.3 6.4

0.310 6.6 6.9

0.244 7.0 7.5

0.101 7.8 8.0

Table 5.3.2-1 

Alternative Cases Considered for the Magnitude-Dependent Weights 

Case M 2.9–3.6 M 3.6–4.3 M 4.3–5.0 M 5.0–5.7 M 5.7–6.4 M > 6.4

A (wt = 0.3) 1 1 1 1 1 1

B (wt = 0.3) 0.1 1 1 1 1 1

C 0 1 1 1 1 1

D 0 0.1 1 1 1 1

E (wt = 0.4) 0 0.3 1 1 1 1

Note: The cases used in the final calculations and the weights assigned to them are shown in bold. 

Table 5.3.3-1 

Miller and Rice (1983) Discrete 5-Point Approximation to a Continuous 

Probability Distribution and the Modified Form Used in This Study 

Cumulative Probability Level of 

Continuous Distribution

Assigned Probability 

Weight

Modified Probability 

Weight

0.034893 0.10108 0.101

0.211702 0.24429 0.244

0.5 0.30926 0.310

0.788298 0.24429 0.244

0.965107 0.10108 0.101
Chapter 5 

SSC Model: Overview and Methodology 

5-66

Table 5.4-1 

Assessment of Default Characteristics of Future Earthquakes in the CEUS 

Future Earthquake 

Characteristic

TI Team Assessments

(Relative frequencies or 

weighted alternatives) References1

Tectonic Stress Regime Compressional Zoback (2010)

Sense of Slip/Style of Faulting Treat as aleatory (relative 

frequency):

2:1 strike-slip:reverse

Focal mechanisms:

New Madrid (Shumway, 2008; 

Horton et al., 2005)

Eastern Tennessee (Chapman et 

al., 1997)

Central Virginia (Kim and 

Chapman, 2005)

St. Lawrence (S. Mazzotti,

Wksp 2)

Southern Great Lakes (Dineva et 

al., 2004)

Wabash Valley (Kim, 2003)

Pennsylvania (Seeber et al.,

1998)

CEUS (Zoback, 2010; Heidbach 

et al., 2008; van Lanen and 

Mooney, 2007)

Charleston (P. Talwani, Wksp 2)

Zoback (1992)

Strike and Dip of Ruptures Aleatory distribution:

N50W (0.2)

N-S (0.2)

N35E (0.4)

N60E (0.1)

E-W (0.1)

Dip is a function of sense of slip:

Strike-slip (90°–60°) (uniform)

Reverse (30°–60°) (uniform)

Either direction (50:50)

van Lanen and Mooney (2007)

Sibson and Xie (1998)

Zoback (1992)

Marshak and Paulsen (1997)

(NW trends)
Chapter 5 

SSC Model: Overview and Methodology 

5-67

Future Earthquake 

Characteristic

TI Team Assessments

(Relative frequencies or 

weighted alternatives) References1

Seismogenic Crustal Thickness Epistemic distribution:

13 km (0.4)

17 km (0.4)

22 km (0.2)

Sibson (1984, 2007)

van Lanen and Mooney (2007) 

for ENA 

Mai et al. (2005)

Atkinson (2004a)

Sykes et al. (2008)

P. Talwani (Wksp 2)

Fault Rupture Area Function of magnitude:

Use Somerville et al. relation 

for ENA

Somerville et al. (2001)

Rupture Length-to-Width Aspect 

Ratio

Function of rupture area:

1:1 for smaller ruptures

With progressively larger 

areas, when rupture width 

equals seismogenic crustal 

thickness, extend only the 

length

Wesnousky (2008)

Toro approach in NAGRA (2004)

Relationship of Rupture to 

Source Zone Boundaries

Epicenter is at center of 

rupture length (map view)

All boundaries are ―leaky‖;

rupture is allowed to extend 

beyond boundary. (Note: If 

boundary is ―strict,‖ rupture 

cannot extend beyond 

boundary, although epicenter 

can be near boundary)

1. References provide insight into the assessment of characteristics; however, they do not uniquely define them 

for purposes of the CEUS SSC study. Those assessments were made by the TI Team.
Chapter 5 

SSC Model: Overview and Methodology 

5-68

Table 5.4-2 

Characteristics of Future Earthquakes for Individual Seismic Sources 

Source Sense of Slip1 Rupture Strike1 Rupture Dip1

Source 

Boundaries

Seismogenic 

Crustal 

Thickness2

RLME Sources

Charlevoix Reverse Uniform 0°–360° Uniform 40°–60° Leaky 25 km (0.8)

30 km (0.2)

Charleston

—Large Strike-slip

NE parallel to 

long axis (0.8)

NW parallel to 

short axis (0.2)

90° Strict

13 km (0.4)

17 km (0.4)

22 km (0.2)

Charleston

—Local Strike-slip NE parallel to long axis 90° Strict

13 km (0.4)

17 km (0.4)

22 km (0.2)

Charleston

—Narrow Strike-slip NE parallel to long axis 90° Leaky at ends

13 km (0.4)

17 km (0.4)

22 km (0.2)

Cheraw Normal-oblique On fault trace 

(NE)

50° NW (0.6)

65° NW (0.4)

Strict

13 km (0.4)

17 km (0.4)

22 km (0.2)

Commerce Strike-slip NE parallel to 

long axis of zone 90° Leaky at ends

13 km (0.4)

15 km (0.4)

17 km (0.2)

ERM-N Strike-slip NE parallel to 

long axis of zone 90° Leaky at ends

13 km (0.4)

15 km (0.4)

17 km (0.2)

ERM-S Strike-slip NE parallel to 

long axis of zone 90° Leaky at ends

13 km (0.4)

15 km (0.4)

17 km (0.2)

Marianna Strike-slip NE 45° (0.5)

NE 45° (0.5)

90° Leaky at ends

13 km (0.4)

15 km (0.4)

17 km (0.2)

Meers—

Fault

Strike-slip (0.5)

Reverse (0.5)

On fault Strike-slip 90°

Reverse 40° SW Strict 15 km (0.5)20 km (0.5)

Meers—

Random in 

OKA

Reverse 

oblique

Parallel to long 

axis of zone Uniform 40°–90° Strict 15 km (0.5)20 km (0.5)

NMFS

NMN, NMS: 

Strike-slip

RMT: reverse

On fault NMN, NMS: 90°

RFT: 40° SW Strict

13 km (0.4)

15 km (0.4)

17 km (0.2)
Chapter 5 

SSC Model: Overview and Methodology 

5-69

Source Sense of Slip1 Rupture Strike1 Rupture Dip1

Source 

Boundaries

Seismogenic 

Crustal 

Thickness2

Wabash 

Valley

2/3 Strike-slip

1/3 Reverse

Strike parallel to 

the long axis of 

the zone (0.8)

N50W (0.1)

N20W (0.1)

2/3 Strike-slip,

90°

1/3 Reverse, 

40°–60°

Strike-slip, 90°

Reverse, 40°

Leaky 17 km (0.7)

22 km (0.3)

Seismotectonic Zones

AHEX 2/3 Strike-slip

1/3 Reverse

N50W (0.1)

N-S (0.1)

N25E (0.4)

N60E (0.3)

E-W (0.1)

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Leaky

8 km (0.5)

15 km (0.5)

ECC-AM 2/3 Strike-slip

1/3 Reverse 

N50W (0.2)

N-S (0.2)

N35E (0.4)

N60E (0.1)

E-W (0.1)

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Leaky 

13 km (0.6)

17 km (0.3)

22 km (0.1)

ECC-GC 2/3 Strike-slip

1/3 Reverse

Uniform 0° to 

360°

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Leaky

13 km (0.6)

17 km (0.3)

22 km (0.1)

GHEX 2/3 Strike-slip

1/3 Reverse

Uniform 0° to 

360°

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Leaky 8 km (0.5)

15 km (0.5)

GMH 4/5 Reverse

1/5 Strike-slip

N50W (0.4)

N20W (0.4)

E-W (0.2)

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Leaky 25 km (0.5)

30 km (0.5)

IBEB

SS (0.1)

RO (0.1)

R (0.3)

SS (0.2)

SS (0.3)

N50W (0.1)

N20W (0.1)

N-S (0.3)

E-W (0.2)

N40E (0.3)

90°

70 E (0.5), 70 W 

(0.5)

40E/W 

(0.4);70E/W (0.3)

90°

90°

Strict

13 km (0.4)

17 km (0.4)

22 km (0.2)
Chapter 5 

SSC Model: Overview and Methodology 

5-70

Source Sense of Slip1 Rupture Strike1 Rupture Dip1

Source 

Boundaries

Seismogenic 

Crustal 

Thickness2

PEZ 2/3 Strike-slip

1/3 Reverse

N50W (0.2)

N-S (0.2)

N35E (0.4)

N60E (0.1)

E-W (0.1)

Strike-slip (90°–

60°) (uniform

Reverse (30°–

60°) (uniform)

Leaky

13 km (0.4)

17 km (0.4)

22 km (0.2)

MidC

2/3 Strike-slip

1/3 Reverse

N50W (0.2)

N-S (0.2)

N35E (0.4)

N60E (0.1)

E-W (0.1)

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Strict

13 km (0.4)

17 km (0.4)

22 km (0.2)

NAP 1/3 Strike-slip

2/3 Reverse

N50W (0.2)

N-S (0.2)

N35E (0.4)

N60E (0.1)

E-W (0.1)

Strike-slip (90°–

60°) (uniform)

Reverse (30°–

60°) (uniform)

Leaky

13 km (0.4)

17 km (0.4)

22 km (0.2)

OKA Reverse 

Oblique

Parallel to long 

axis of zone Uniform 45°–75° Leaky 15 km (0.5)20 km (0.5)

RR and 

RR-RCG

SS (0.2)

R (0.35)

SS (0.5)

SS (0.2)

SS (0.2)

N50W (0.2)

N10W(0.35)

E-W (0.05)

N30E (0.2)

N55E (0.2)

90°

70 E/W (0.5), 40 

E/W (0.5)

90°

90°

90°

Strict

13 km (0.4)

15 km (0.4)

17 km (0.2)

SLR 1/3 Strike-slip

2/3 Reverse

N25E (0.2)

N40E (0.2)

N70E (0.2)

N50W (0.15)

N70W (0.15)

N-S (0.05)

E-W (0.05)

Strike-slip (90°–

60°) (uniform

Reverse (30°–

60°) (uniform)

Leaky 25 km (0.5)

30 km (0.5)

Note: Default characteristics are indicated in italics. 

1. Weights reflect aleatory variability; weights are therefore relative frequencies. 

2. Weights reflect epistemic uncertainty; weights are therefore relative credibility that the given thickness is 

correct. 
Chapter 5 

SSC Model: Overview and Methodology 

5-71

Table 5.4-3 

Estimates of D90 for Individual Seismic Source Zones 

Seismic Source 

Zone

5

th Percentile D90

(km)

D90 from Observed 

Focal Depths

(km)

95th Percentile 

D90

(km)

MESE-N 16 17 18

MESE-W 17 18 19

NMESE-N 17 18 19

NMESE-W 15 16 17

AHEX — — —

ECC-AM 11 12 13

ECC-GC 12 16 20

GHEX — — —

GMH 22 23 24

IBEB 18 19 21

MIDC-A 15 16 17

MIDC-B 15 16 17

MIDC-C 15 16 17

MIDC-D 15 16 17

NAP 15 17 20

OKA — — —

PEZ-N 18 19 20

PEZ-W 18 19 20

RR 12 13 14

RR-RCG 12 13 14

SLR 19 20 21

Note: Cells with ―—‖ indicate source zones with too few earthquakes from which to obtain an estimate. 
Chapter 5 

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5-72

Figure 5.2.1-1 

Diagrammatic illustration of the Bayesian Mmax approach showing (a) the prior distribution, (b) the likelihood function, and (c) 

the posterior distribution. The posterior distribution is represented by a discrete distribution (d) for implementation in hazard 

analysis. 

Notes: Prior is normal distribution with mean M 6.4 and standard deviation 0.85. Likelihood function is based on two observed 

earthquakes larger than M 4.5, with the largest being 5.3. 

(a) Prior Distribution

0

0.001

0.002

0.003

0.004

0.005

4 5 6 7 8 9

Magnitude

Probability

(b) Likelihood Function

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

4 5 6 7 8 9

Magnitude

Likelihood

(c) Posterior Distribution

0

0.002

0.004

0.006

4 5 6 7 8 9

Magnitude

 Probability

(d) Discrete Distribution

0

0.1

0.2

0.3

4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0

Magnitude

Probability
Chapter 5 

SSC Model: Overview and Methodology 

5-73

Figure 5.2.1-2 

Diagrammatic illustration of the Bayesian Mmax approach showing (a) the prior distribution, (b) the likelihood function, and (c) 

the posterior distribution. The posterior distribution is represented by a discrete distribution (d) for implementation in hazard 

analysis. 

Notes: Prior is normal distribution with mean M 6.4 and standard deviation 0.85. Likelihood function is based on 10 observed earthquakes 

larger than M 4.5, with the largest being 5.3. 

(a) Prior Distribution

0

0.001

0.002

0.003

0.004

0.005

4 5 6 7 8 9

Magnitude

Probability

(b) Likelihood Function

0

1

2

3

4

5

6

7

4 5 6 7 8 9

Magnitude

Likelihood

(c) Posterior Distribution

0

0.005

0.01

0.015

4 5 6 7 8 9

Magnitude

 Probability

(d) Discrete Distribution

0

0.1

0.2

0.3

0.4

4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0

Magnitude

Probability
Chapter 5 

SSC Model: Overview and Methodology 

5-74

Figure 5.2.1-3 

Median values of 

mmax obs

 as a function of maximum magnitude, m

u

, and sample size N, 

the number of earthquakes ≥ M 4.5 

Note: Dashed lines show bias correction for a 

mmax obs

 of 5.7 with a sample size of 10. 
Chapter 5 

SSC Model: Overview and Methodology 

5-75

Figure 5.2.1-4 

Histograms of 

mmax obs

 for extended and non-extended superdomains 
Chapter 5 

SSC Model: Overview and Methodology 

5-76

Figure 5.2.1-5 

Histograms of 

mmax obs

 for Mesozoic-and-younger extended (MESE) superdomains and for 

older extended and non-extended (NMESE) superdomains 
Chapter 5 

SSC Model: Overview and Methodology 

5-77

Figure 5.2.1-6 

Histograms of 

mmax obs

 for Mesozoic-and-younger extended (MESE) superdomains and for 

older extended and non-extended (NMESE) superdomains using age of most recent 

extension for the age classification 
Chapter 5 

SSC Model: Overview and Methodology 

5-78

Figure 5.2.1-7 

Histograms of 

mmax obs

 for Mesozoic-and-younger extended (MESE) superdomains and for 

older extended and non-extended (NMESE) superdomains using final sets indicated by 

asterisks in Tables 5.2.1-1 and 5.2.1-2 
Chapter 5 

SSC Model: Overview and Methodology 

5-79

Figure 5.2.1-8 

Histograms of 

mmax obs

 for combined (COMB) superdomains using final sets indicated by asterisks in Table 5.2.1-3 
Chapter 5 

SSC Model: Overview and Methodology 

5-80

Figure 5.2.1-9 

Bias adjustments from 

mmax obs

 to m

u

 for the three sets of superdomain analysis results 

presented in Table 5.2.1-4 
Chapter 5 

SSC Model: Overview and Methodology 

5-81

4

4.5

5

5.5

6

6.5

7

7.5

0 200 400 600 800 1000

Number of Earthquakes

Magnitude

Max_Obs

Posterior mode

Posterior mean

True Mmax

Figure 5.2.1-10

Results of simulations of estimates of Mmax using the Bayesian approach for earthquake 

catalogs ranging in size from 1 to 1,000 earthquakes. True Mmax is set at the mean of the 

prior distribution. 
Chapter 5 

SSC Model: Overview and Methodology 

5-82

Figure 5.2.1-11 

Comparison of the Kijko (2004) estimates of m

u

 for given values of 

mmax obs

 and N, the 

number of earthquakes of magnitude ≥ 4.5. Also shown is the median value of 

mmax obs

 for 

given m

u

 obtained using Equation 5.2.1-2.
Chapter 5 

SSC Model: Overview and Methodology 

5-83

Figure 5.2.1-12 

Behavior of the cumulative probability function for m

u

 (Equation 5.2.1-9) for the K-S-B 

estimator and a value of 

mmax obs

 equal to 6
Chapter 5 

SSC Model: Overview and Methodology 

5-84

MESE_N

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.06

Bayesian (COMP) weight = 0.376

Bayesian (MESE) weight = 0.564

Composite Distribution

Figure 5.2.1-13 

Example Mmax distribution assessed for the Mesozoic-and-younger extended Mmax zone for the case where the zone is 

“narrow” (MESE-N). Distributions are shown for the Kijko approach and for the Bayesian approach using either the Mesozoicand-younger extended prior distribution or the composite prior distribution. The final composite Mmax distribution, which 

incorporates the relative weights, is shown by the red probability distribution. 
Chapter 5 

SSC Model: Overview and Methodology 

5-85 NAP

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 5.2.1-14 

Example Mmax distribution assessed for the Northern Appalachian seismotectonic zone (NAP). Distributions are shown for the 

Kijko approach and for the Bayesian approach using either the Mesozoic-and-younger extended prior distribution or the 

composite prior distribution. Note that the Kijko results are shown in this example for illustration, even though they have zero 

weight. The final composite Mmax distribution, which incorporates the relative weights, is shown by the red probability 

distribution. 
Chapter 5 

SSC Model: Overview and Methodology 

5-86

Figure 5.3.2-1 

Likelihood function for rate per unit area in a Poisson process, for multiple values of the 

earthquake count N: (a) arithmetic scale, and (b) logarithmic scale used to illustrate 

decreasing COV as N increases
Chapter 5 

SSC Model: Overview and Methodology 

5-87

Figure 5.3.2-2 

Likelihood function for b-value of an exponential magnitude distribution, for multiple values of the earthquake count N. The 

value of b is normalized by the maximum-likelihood estimate, which is derived from Equation 5.3.2-5. 
Chapter 5 

SSC Model: Overview and Methodology 

5-88

Figure 5.3.2-3 

Histogram of magnitudes in the earthquake catalog used in this section. The minimum magnitude shown (M 2.9) is the lowest 

magnitude used in these recurrence calculations. 
Chapter 5 

SSC Model: Overview and Methodology 

5-89

Figure 5.3.2-4 

Objectively determined values of the penalty function for ln(rate) for Case A magnitude weights. Source zones are sorted from 

smallest to largest. See list of abbreviations for full source-zone names. 
Chapter 5 

SSC Model: Overview and Methodology 

5-90

Figure 5.3.2-5 

Objectively determined values of the penalty function for beta for Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-91

Figure 5.3.2-6 

Objectively determined values of the penalty function for ln(rate) for Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-92

Figure 5.3.2-7 

Objectively determined values of the penalty function for beta for Case B magnitude weights. Source zones are sorted from 

smallest to largest. 
Chapter 5 

SSC Model: Overview and Methodology 

5-93

Figure 5.3.2-8 

Objectively determined values of the penalty function for ln(rate) for Case E magnitude weights
Chapter 5 

SSC Model: Overview and Methodology 

5-94

Figure 5.3.2-9 

Objectively determined values of the penalty function for beta for Case E magnitude weights. Source zones are sorted from 

smallest to largest. 
Chapter 5 

SSC Model: Overview and Methodology 

5-95

Figure 5.3.2-10

Mean map of rate and b-value for ECC-AM calculated using Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-96

Figure 5.3.2-11

Mean map of rate and b-value for ECC-GC calculated using Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-97

Figure 5.3.2-12

Mean map of rate and b-value for ECC-AM calculated using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-98

Figure 5.3.2-13

Mean map of rate and b-value for ECC-GC calculated using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-99

Figure 5.3.2-14

Mean map of rate and b-value for ECC-AM calculated using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-100

Figure 5.3.2-15

Mean map of rate and b-value for ECC-GC calculated using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-101

Figure 5.3.2-16

Sensitivity of seismic hazard at Manchester site to the strength of the prior on b 
Chapter 5 

SSC Model: Overview and Methodology 

5-102

Figure 5.3.2-17

Sensitivity of seismic hazard at Topeka site to the strength of the prior on b 
Chapter 5 

SSC Model: Overview and Methodology 

5-103

Figure 5.3.2-18

Sensitivity of seismic hazard at Manchester site to the choice of magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-104

Figure 5.3.2-19

Sensitivity of seismic hazard at Topeka site to the choice of magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-105

Figure 5.3.2-20

Sensitivity of seismic hazard from source NAP at Manchester site to the eight alternative recurrence maps for Case B magnitude 

weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-106

Figure 5.3.2-21

Sensitivity of seismic hazard from source MID-C–A at Topeka site to the eight alternative recurrence maps for Case B magnitude 

weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-107

Figure 5.3.2-22

Mean recurrence-parameter map for the study region under the highest weighted source-zone configuration in the master logic 

tree. See Sections 6.3 and 7.5 for all mean maps. 
Chapter 5 

SSC Model: Overview and Methodology 

5-108

Figure 5.3.2-23

Map of the uncertainty in the estimated recurrence parameters, expressed as the coefficient of variation of the rate (left) 

and the standard deviation of the b-value (right) for the study region, under the highest weighted source-zone configuration 

in the master logic tree. See Appendix J for all maps of uncertainty. 
Chapter 5 

SSC Model: Overview and Methodology 

5-109

Figure 5.3.2-24

First of eight equally likely realizations of the recurrence-parameter map for the study region under the highest weighted 

source-zone configuration in the master logic tree. See Appendix J for maps of all realizations for all source-zone 

configurations. 
Chapter 5 

SSC Model: Overview and Methodology 

5-110

Figure 5.3.2-25

Eighth of eight equally likely realizations of the recurrence-parameter map for the study region under the highest weighted 

source-zone configuration in the master logic tree. See Appendix J for maps of all realizations for all source-zone 

configurations. 
Chapter 5 

SSC Model: Overview and Methodology 

5-111

Figure 5.3.2-26

Map of geographic areas considered in the exploration of model results 
Chapter 5 

SSC Model: Overview and Methodology 

5-112

Figure 5.3.2-27

Comparison of model-predicted earthquake counts for the USGS Eastern Tennessee area using Case A magnitude weights. The 

error bars represent the 16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 5 

SSC Model: Overview and Methodology 

5-113

Figure 5.3.2-28

Comparison of model-predicted earthquake counts for the USGS Eastern Tennessee area using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-114

Figure 5.3.2-29

Comparison of model-predicted earthquake counts for the USGS Eastern Tennessee area using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-115

Figure 5.3.2-30

Comparison of model-predicted earthquake counts for the central New England area using Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-116

Figure 5.3.2-31

Comparison of model-predicted earthquake counts for the central New England area using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-117

Figure 5.3.2-32

Comparison of model-predicted earthquake counts for the central New England area using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-118

Figure 5.3.2-33

Comparison of model-predicted earthquake counts for the Nemaha Ridge area using Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-119

Figure 5.3.2-34

Comparison of model-predicted earthquake counts for the Nemaha Ridge area using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-120

Figure 5.3.2-35

Comparison of model-predicted earthquake counts for the Nemaha Ridge area using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-121

Figure 5.3.2-36

Comparison of model-predicted earthquake counts for the Miami, FL, area using Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-122

Figure 5.3.2-37

Comparison of model-predicted earthquake counts for the Miami, FL, area using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-123

Figure 5.3.2-38

Comparison of model-predicted earthquake counts for the Miami, FL, area using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-124

Figure 5.3.2-39

Comparison of model-predicted earthquake counts for the St. Paul, MN, area using Case A magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-125

Figure 5.3.2-40

Comparison of model-predicted earthquake counts for the St. Paul, MN, area using Case B magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-126

Figure 5.3.2-41

Comparison of model-predicted earthquake counts for the St. Paul, MN, area using Case E magnitude weights 
Chapter 5 

SSC Model: Overview and Methodology 

5-127

Figure 5.3.2-42

Recurrence parameters for the ECC-AM, MID-C–A, and NAP seismotectonic source zones and Case A magnitude weights 

computed using an objective adaptive kernel approach 
Chapter 5 

SSC Model: Overview and Methodology 

5-128

Figure 5.3.3-1 

Likelihood distribution for rate parameter λ derived using Equation 5.3.3-1 for N = 2 and 

T = 2,000 years. Top: normalized probability density function for λ. Bottom: resulting 

cumulative distribution function. Dashed lines show the cumulative probability levels for 

the Miller and Rice (1983) discrete approximation of a continuous probability distribution. 
Chapter 5 

SSC Model: Overview and Methodology 

5-129

Figure 5.3.3-2 

Uncertainty distributions for the age of Charleston RLMEs 
Chapter 5 

SSC Model: Overview and Methodology 

5-130

Figure 5.4.4-1 

Spatial distribution of earthquakes in the CEUS SSC Project catalog. Solid lines indicate the boundaries of the seismotectonic source 

zones (narrow interpretation). 
Chapter 5 

SSC Model: Overview and Methodology 

5-131

Figure 5.4.4-2 

Spatial distribution of earthquakes in the CEUS SSC Project catalog with good quality depth determinations used for assessing crustal 

thickness. Solid lines indicate the boundaries of the seismotectonic source zones (narrow interpretation). 
Chapter 5 

SSC Model: Overview and Methodology 

5-132

Figure 5.4.4-3 

Distribution of better-quality focal depths in Mmax source zones 
Chapter 5 

SSC Model: Overview and Methodology 

5-133

Figure 5.4.4-4 (1 of 3) 

Distribution of better-quality focal depths in seismotectonic source zones 
Chapter 5 

SSC Model: Overview and Methodology 

5-134

Figure 5.4.4-4 (2 of 3) 

Distribution of better-quality focal depths in seismotectonic source zones 
Chapter 5 

SSC Model: Overview and Methodology 

5-135

Figure 5.4.4-4 (3 of 3) 

Distribution of better-quality focal depths in seismotectonic source zones 

6-1

6

CHAPTER 6 

SSC MODEL: RLME SOURCES AND MMAX ZONES 

BRANCH 

As discussed in Section 4.2, the two major branches of the master logic tree define two 

approaches to characterizing the spatial and temporal distribution of seismic sources: the Mmax 

zones approach and the seismotectonic zones approach. As discussed in Section 4.2.1, the 

―Mmax zones‖ model involves (1) the direct use of observed seismicity by spatial smoothing of 

distributed seismicity and (2) the inclusion of RLMEs that are defined primarily by paleoseismic 

evidence. The Mmax zones are defined solely by differences in the prior distribution of Mmax, 

using the Bayesian approach. In contrast, the ―seismotectonic zones‖ model (described in 

Chapter 7), which also includes the RLMEs, involves the use of additional seismotectonic data to 

define the spatial variation in the characteristics of future earthquakes. This chapter defines both 

the RLME sources and the Mmax zones. Section 6.1 describes each of the RLME sources; 

Section 6.2 describes the alternative interpretations of the Mmax zones; Section 6.3 discusses the 

assessment of maximum magnitude for the Mmax zones; and Section 6.4 describes the spatial 

smoothing of recurrence parameters within the Mmax zones. 

6.1 RLME Sources 

By definition, RLME sources are the locations of repeated (more than one) large-magnitude 

(M ≥ 6.5) earthquakes in the historical or paleoearthquake record. Because of the rarity of 

RLMEs relative to the period of historical observation, evidence for these earthquakes comes 

largely from the paleoearthquake record. For example, paleoearthquakes identified by 

interpretations of paleoliquefaction features and fault displacement (paleoseismic) studies 

combined with those in the historical record result in the catalog of large-magnitude earthquakes 

in the central New Madrid region and at Charleston. At Charlevoix, RLMEs are observed in the 

historical record and are supplemented by the paleoearthquake record. For the Meers and Cheraw 

faults as well as the Wabash Valley source, there are no large-magnitude earthquakes in the 

historical record. The RLMEs for these sources are characterized by evaluating repeated surfacefaulting displacements identified in trenches across the faults and, for the Wabash Valley source, 

by interpreting the geographic distribution of paleoliquefaction features. 

The RLME sources considered for the CEUS SSC model are listed in Table 4.2.2-1 and shown 

on Figure 6.1-1, which is an overview map. Detailed maps of the RLME sources, along with 

their alternative geometries, are given in the individual subsections describing each of the 11 

RLME sources (Sections 6.1.1 through 6.1.9). The relationship of the RLME sources to observed 

historical seismicity is enigmatic. Some of the RLME sources are associated with elevated 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-2

seismicity (Figures 6.1-2a and 6.1-2b), such as the central New Madrid faults (Figure 6.1-2b) and 

Charlevoix, but others occur within areas of moderate levels of seismicity (e.g., Charleston and 

Wabash Valley) or even relatively low levels of seismicity (e.g., Cheraw fault). Data evaluation 

tables for each of the 11 RLME sources are in Appendix C. Six data summary tables for the 11 

sources are in Appendix D; a single data summary table (D-6.1.5) is provided for the combined 

New Madrid region sources described in Sections 6.1.5 to 6.1.8. 

By identifying the RLME sources and including them in the SSC model, there is no implication 

that the set of RLME sources included is, in fact, the total set of RLME sources that might exist 

throughout the study region. This is because the presently available studies that have located and 

characterized the RLME sources have been concentrated in certain locations, not conducted 

systematically across the entire study region. If it were possible to identify all RLME sources 

throughout the study region, in much the same way that major faults are identified in a plateboundary tectonic setting, then the earthquake potential of the remaining region might be 

assessed as being secondary to the RLME sources. This type of conclusion cannot be drawn in 

the CEUS, based on current knowledge. Therefore, the evidence for the existence of the RLME 

sources is included in the model, but the remaining parts of the study region are also assessed to 

have potentially significant earthquake potential, which is characterized using either Mmax 

zones (Section 6.2) or seismotectonic zones (Section 7.3). 

The intent of the RLME sources is to model only the recurrence of repeated large earthquakes in 

a specific location. As such, the RLME sources represent a source of seismic hazard that is in 

addition to the hazard resulting from the occurrence of distributed seismicity modeled by the 

distributed seismicity sources—the Mmax zones. In essence, the RLME sources act as fault-like 

seismic sources embedded in large areal seismic source zones. They allow for a departure from 

the general truncated exponential recurrence behavior in specific locations. The expected 

magnitude of the RLMEs that occur in each RLME source is represented by an epistemic

distribution assessed from the available information for each source. As described in Section 

5.3.3.4, given a specific value for the expected RLME magnitude, the size of individual RLMEs 

is modeled by a uniform aleatory distribution over the range of ±0.25 magnitude units about the 

expected value. The assessment of the size and magnitude distribution for the RLME sources is 

independent of the assessment of the maximum magnitude distribution for the distributed 

seismicity sources. As a result, there is overlap in the magnitude ranges in most cases. This 

introduces a small degree of ―double counting‖ in the area covered by the RLME sources. 

However, the earthquakes in the CEUS SSC earthquake catalog that are identified as RLMEs are 

not included in the calculation of earthquake recurrence rates for the distributed seismicity 

sources. 

The assessment of RLME recurrence rates is based on paleoseismic data gathered at each 

location and the methodology described in Section 5.3.3. Table 6.1-1 presents a summary of the 

specific methods and data used for each RLME source. The descriptions of the data and the 

assessment of relative weights assigned to alternative data sets are discussed in the following 

sections. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-3

6.1.1 Charlevoix 

Repeated historical earthquakes have occurred within the Charlevoix region of the lower St. 

Lawrence (Figure 6.1-2a), including the February 5, 1663, M 7 (E[M] 7.00)1; December 6, 1791,

M 5.8 (E[M] 5.50); October 17, 1860, M 6 (E[M] 6.08); October 20, 1870, M 6.5 (E[M] 6.55); 

and March 1, 1925, M 6.3 (E[M] 6.18) earthquakes (Lamontagne et al., 2008). Only two of these 

earthquakes, the 1663 and 1870 earthquakes, are considered RLME earthquakes. The rest are 

considered to be part of seismicity occurring in the distributed seismicity sources. In addition, 

paleoseismic investigations have identified evidence of paleoearthquakes throughout the 

Holocene (Tuttle and Atkinson, 2010; Doig, 1991; Filion et al., 1991) that are spatially restricted 

to the Charlevoix area (Tuttle and Atkinson, 2010). 

Several explanations have been offered for why RLMEs occur within the Charlevoix seismic 

zone. Adams and Basham (1991) attribute seismicity of the SLR system to earthquakes occurring 

on rift structures in the regional stress field of southeast-to-east compression, recognizing that a 

Devonian impact structure also exists in the general area and may be related to the spatial 

concentration of seismicity in the Charlevoix area. The observation that seismicity continues 

beyond the impact structure (crater) with orientations indicative of reactivation of rift faults led 

Adams and Basham (1991) to de-emphasize the role of impact structures. Lamontagne and 

Ranalli (1997) correlate large-magnitude Charlevoix earthquakes to reactivation of rift faults in 

response to the regional stress field. They interpret variations in orientation and style of faulting 

for small-magnitude earthquakes to reactivation of impact-related faults and fractures in response 

to local stress and/or strength conditions. In another paper, Lamontagne and Ranalli (1996) 

attribute earthquakes in the Charlevoix seismic zone to some or all of the following 

circumstances: 

Fracturing above the brittle-ductile transition at depths of at least 25 km (15.5 mi.). 

High pore-fluid pressure at mid- to lower crustal depths where hydration reactions are not 

favored. 

Low coefficients of friction related to highly fractured zones at depth, as opposed to thick 

fault gouges made of clay minerals. 

Results of two-dimensional stress modeling account for the spatial pattern of observed seismicity 

as stress concentration due to the interaction of the crater (local zone of weakness) and rift faults 

(large-scale weak zone) (Baird et al., 2009). Smaller-magnitude, more frequent seismicity occurs 

within the impact crater, and infrequent larger-magnitude earthquakes are localized along rift 

faults (Baird et al., 2009). Mazzotti and Adams (2005) have also observed that the discrepancy 

between modeled seismic moment and strain rates derived from earthquake statistics may 

represent a short-term process such as postglacial rebound. 

A summary of the investigations evaluated for the Charlevoix seismic zone is provided in 

Appendix Table D-6.1.1, and information used in the CEUS SSC Project to characterize this 

 

1

 Magnitudes are reported in the magnitude scale designated in the cited publication. E[M] denotes the value of the 

expected moment magnitude listed in the CEUS SSC catalog for the earthquake. It is reported to two decimal places 

to indicate that it is a calculated value. See the discussion in Section 3.3.1. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-4

RLME zone is presented in Appendix Table C-6.1.1. The logic tree for the Charlevoix RLME 

source is shown on Figure 6.1.1-1. 

6.1.1.1 Evidence for Temporal Clustering 

The first node of the logic tree (Figure 6.1.1-1) addresses the issue of temporal clustering of 

earthquakes in the present tectonic stress regime (see Section 5.1.2). The historical earthquakes 

identified as RLMEs are the February 5, 1663, M 7 (E[M] 7.00), and the October 20, 1870, M

6.5 (E[M] 6.55), earthquakes. Recently, Tuttle and Atkinson (2010) reported evidence, based on 

a minimum magnitude to produce paleoliquefaction features, for three or more M ≥ 6.2 

earthquakes during the past 10,000 years. These earthquakes include one historical earthquake 

possibly associated with either the 1663, 1870, or 1925 earthquake, and two prehistoric 

earthquakes occurring approximately 5,000 and 10,000 years ago. The available information on 

the size and location of these earthquakes and the geologic evidence for long-term slip rates or 

recurrence intervals are insufficient to evaluate whether the Charlevoix RLME source exhibits 

evidence for temporal clustering. Therefore, this node of the logic tree is not applicable to the 

Charlevoix RLME source. 

6.1.1.2 Localizing Tectonic Features 

The late Proterozoic–early Paleozoic SLR, which passes through the Charlevoix RLME source 

zone, is attributed to the opening of the Iapetus Ocean (Tremblay and Lemieux, 2001) and is 

characterized within the SLR seismotectonic zone in Section 7.3.1. The St-Laurent fault strikes 

N20-50E and dips 60–70 degrees to the southeast, forming a northeast-trending, southeastdipping half graben oriented parallel to the main axis of the SLR system (Tremblay and 

Lemieux, 2001). High-resolution seismic profiles in the St. Lawrence estuary indicate that the 

Laurentian Channel trough transitions from a half graben to a graben structure from southwest to 

northeast (Tremblay et al., 2003). 

Two major fault orientations (N40-70W and N20-40E) are found outside the Charlevoix impact 

zone, with minor fault sets trending east to west to N80W and north to south to N20E (Lemieux 

et al., 2003). Fault rocks consist of fault breccia, cataclastite, foliated gouge, and pseudotachylyte 

with a minimum thickness of 20 m (66 ft.) near Sault-au-Cochon (Tremblay and Lemieux, 

2001). Fault rocks exposed at Cap-Tourmente consist of zones of protocataclasite, cataclasite, 

and fault breccia 10–15 m (33–49 ft.) thick (Tremblay and Lemieux, 2001). Changes in strain 

rate, pressure, temperature, and fluid conditions are required for formation of cataclastic rocks, 

pseudotachylytes, and fault gouge within the same environment, suggesting that a single, 

progressive tectonic event along the SLR resulted in this distribution of fault rocks (Lemieux et 

al., 2003). The St-Laurent fault crosses the Charlevoix impact crater without any major 

deflection in strike or without any fault offsets within or at the boundaries of the structure, 

indicating that impact-related faulting did not significantly alter the orientation of preexisting 

structures and that reactivation of the St-Laurent fault is younger than the impact structure 

(Tremblay and Lemieux, 2001). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-5

Within the Charlevoix impact crater the St-Laurent fault is also characterized by a welldeveloped and extensive series of cataclastic rock, gouge, and pseudotachylyte, as well as 

polymictic clastic matrix breccias restricted to the impact crater (Tremblay and Lemieux, 2001). 

Fragments of cataclastic breccia are present, suggesting recurrent brecciation during incremental 

faulting events associated with the St-Laurent fault. Fault orientations are more scattered within 

the impact crater but are similar to the northwest- and northeast-trending faults of the entire rift 

system (Lemieux et al., 2003). The spread of orientations within the central portion of the crater 

is attributed to the impact-related polygonal pattern of normal faults, whereas the northwest and 

northeast fault sets represent the youngest reactivation of the SLR (Lemieux et al., 2003). 

The SLR system has experienced multiple stages of reactivation. Stratigraphic evidence of 

Ordovician growth faulting during late stages of the Taconic orogeny in platform deposits near 

Charlevoix includes major variations in thickness laterally within the Ordovician section, the 

presence of slump deformation features induced by faulting in almost all stratigraphic units, the 

preservation of pseudotachylyte within synsedimentary breccias, and the occurrence of fault 

breccia clasts (Lemieux et al., 2003). Tremblay et al. (2003) speculate that additional episodes of 

reactivation of faulting in the SLR system are younger than the Devonian-age Charlevoix impact 

crater. Truncation of Devonian impact-related structures by northeast-southwest and northwestsoutheast faults is consistent with Mesozoic fault reactivation due to rifting of the North Atlantic 

region (Lemieux et al., 2003). Tremblay et al. (2003) attribute some fault throw along the SLR 

system to the opening of the Central Atlantic in the Jurassic and/or seafloor spreading of the 

North Atlantic during the Cretaceous. 

Because the occurrence of RLMEs in the Charlevoix zone cannot be associated with a specific 

feature, future RLMEs are modeled as occurring randomly within the RLME source zone, as 

indicated on the second node of the logic tree (Figure 6.1.1-1). 

6.1.1.3 Geometry and Style of Faulting 

The geometry of the Charlevoix RLME source, shown on Figure 6.1.1-2, is defined to 

encompass the locations of earthquakes with M > 6, mapped rift faults, and the Charlevoix 

impact crater. Gravity and magnetic data sets delineate Grenville and Appalachian crust (Figure 

6.1.1-3) and were not used to constrain the geometry for the Charlevoix RLME source. 

Lamontagne (1999) observed that small to moderate earthquakes of the Charlevoix seismic zone 

occur between, not along, rift faults and extend northeast of the impact structure as a result of the 

asymmetric placement of rift faults through the crater (Baird et al., 2009). Large-magnitude 

earthquakes are thought to occur along weakened rift faults that concentrate stress into the crater 

(Baird et al., 2009). The geometry for the Charlevoix RLME source zone was modified from the 

Charlevoix source zone of the GSC H model (Adams et al., 1996; Adams and Halchuck, 2003). 

Tuttle and Atkinson (2010) consider a narrower geometry for the Charlevoix seismic zone that is 

more localized along rift faults. A single geometry for the Charlevoix RLME source that 

envelops both interpretations is used, as indicated by the third node of the logic tree shown on 

Figure 6.1.1-1. 

The location of causative faults within the Charlevoix RLME source is uncertain. In addition, 

using a relationship between magnitude and rupture length (e.g., Leonard, 2010), the lengths of 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-6

ruptures that would be associated with the postulated RLMEs are in the range of 30–80 km (19–

50 mi.), similar to the 30 by 85 km (19 by 53 mi.) dimensions of the RLME source. Given the 

small source size and uncertain fault locations, the boundaries of the Charlevoix RLME source 

are leaky, allowing ruptures to extend beyond the source boundary by 50 percent. 

Hypocentral depths for earthquakes in the Charlevoix seismic zone occur as deep as 29 km (18 

mi.), although most earthquakes occur between 8 and 15 km (5 and 9.5 mi.) (Lamontagne and 

Ranalli, 1996). Comparing this depth distribution to rheological models of the region, 

Lamontagne and Ranalli (1996) attribute earthquakes in the Charlevoix seismic zone to one or 

more of the following: faulting above the brittle-ductile transition at depths of at least 25 km 

(15.5 mi.); high pore-fluid pressure below the onset of ductility for hydrated feldspar at about 

350°C; and a low coefficient of friction, possibly related to unhealed zones of intense fracturing. 

The distribution of spatially clustered earthquakes within the Charlevoix seismic zone indicates 

that very few earthquakes have occurred on the same fractures with similar focal mechanisms, 

implying that these fault zones occur in highly fractured rocks (Lamontagne and Ranalli, 1997). 

The thickness of seismogenic crust is modeled with equal weight on 25 and 30 km (16 and 19 

mi.), as shown on the fourth node of the logic tree (Figure 6.1.1-1). 

Tremblay et al. (2003) observe several orientations of faulting within the Charlevoix RLME 

source. Northeast-trending longitudinal faults parallel to the main axis of the rift show three 

trends (N25E, N40E, and N70E) and generally dip between 60 and 90 degrees to the southeast, 

although a minor number dip to the northwest. Crosscutting transverse faults show two trends 

(N70W and N50W) and dip to the northeast or southwest; these orientations are consistent with 

the horst-and-graben geometry of the SLR system. Both sets of faults are high-angle faults with 

dip angles averaging 75–80 degrees. The pitch of fault lineations is greater than 70 degrees, 

indicating that most structures are dip-slip faults (Tremblay et al., 2003). Lemieux et al. (2003) 

observed the largest variation in fault trends within the central portion of the impact crater, which 

still displayed a dominant northwest-southeast orientation. 

Lamontagne (1999) observed that faulting style inferred from focal mechanisms within the 

Charlevoix RLME source indicates reverse to oblique-reverse faulting on fault planes with 

highly variable orientations, and he assumed that these ruptures occur on preexisting southeastdipping faults. Adams and Basham (1991) report that structural complexity in the form of 

distributed fracturing and ring faulting within the impact crater may be responsible for more 

varied focal mechanisms within Charlevoix. Focal mechanisms for earthquakes of magnitude >3 

show reverse faulting, whereas smaller-magnitude earthquakes indicate some strike-slip and 

normal faulting, suggesting that local stress conditions affect rupture style (Lamontagne and 

Ranalli, 1997). Fault-plane solutions for recent small earthquakes located within the Charlevoix 

seismic zone are predominantly reverse events on steeply dipping planes, but a number of events 

have a significant strike-slip component, some on northwest-striking planes and some on more 

shallowly dipping planes (Lamontagne, 1987; Adams et al., 1989; Wetmiller and Adams, 1990). 

Analysis by Li et al. (1995) of rupture directions for two M 4 events indicates that focal 

mechanisms have east-dipping planes. Bent (1992) determined a reverse mechanism for the 1925 

MS 6.2 (E[M] 6.18) Charlevoix earthquake with a strike of N42° ± 7°E, dip of 53° ± 7°, and rake 

of 105° ± 10° and favors a southeast-dipping solution based on observed seismicity and mapped 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-7

faults. Dips for the January 11, 1986, MN 4.0 (E[M] 3.40) and the March 18, 1987, MN 3.3

(E[M] 2.79) earthquakes range between 42 and 59 degrees to the south (Lamontagne and 

Ranalli, 1997). Because of the variability exhibited in mapped structures and focal mechanisms, 

future ruptures for the Charlevoix RLME source are modeled as randomly oriented reverse 

events with dips between 45 and 60 degrees in either direction. 

6.1.1.4 RLME Magnitude 

The February 5, 1663, earthquake is the largest observed historical earthquake within the 

Charlevoix seismic zone. Lamontagne et al. (2008) use a best estimate for the magnitude of M 7. 

This estimate is based on felt effects in Quebec City, Trois-Rivières, Montreal, Boston, and New 

York and on reported landsliding along the St. Lawrence, Shipshaw, Betsiamites, Pentecote, 

Batiscan, and Saint-Maurice rivers (Lamontagne et al., 2008; Gouin, 2001). Using similar 

observations of intensity from felt reports and accounts of landsliding and liquefaction, Ebel 

(1996) assigned a magnitude of M ≥ 7.0 ± 0.5 to the 1663 Charlevoix earthquake and concluded 

that the magnitude of the 1663 event is somewhat larger than the 1925 Charlevoix earthquake. 

Ebel (2006b) later postulated that, if the total length of the Charlevoix seismic zone (70 km, or 

43.5 mi.) produced a single rupture approaching M 7.5 during the 1663 event, all modern 

seismicity represents aftershocks from this event. Ebel (2009) notes that this rupture length could 

produce a main-shock magnitude of M 7.1–7.5. He interpreted MMI VI reports at Roxbury, 

Massachusetts, as a mbLg 7.5 (M 7.8) using an intensity-attenuation relationship, and as a M 7.5

using recent ground-motion attenuation relationships. These lines of evidence led him to assign a 

magnitude of M 7.5 ± 0.3 to the 1663 Charlevoix event. Recent discussions with Ebel (pers. 

comm., 2009) indicate that he prefers a magnitude of 7.2–7.5.

Paleoliquefaction features occurring along the Gouffre, Malbaie, and Ouelle rivers (Figure 

6.1.1-2) in the Charlevoix area (Appendix E, Section 1.2.8.1) provide evidence of three 

generations of earthquake-induced liquefaction within the last 10,000 years (Tuttle and Atkinson, 

2010). The spatial distribution of these features and the lack of paleoliquefaction evidence to the 

south in the Trois Rivières area can be attributed to paleoearthquakes of M ≥ 6.2 in the 

Charlevoix seismic zone (Tuttle and Atkinson, 2010). The prehistoric earthquakes are considered 

RLMEs (M ≥ 6.5) given the range of magnitudes (M 6.2–7.0) capable of explaining the spatial 

distribution of observed liquefaction features (Tuttle and Atkinson, 2010). Recent work by Locat 

(2008) places the M 7 1663 earthquake near Saguenay, based on the distribution of largely 

undated landslide deposits throughout the region and subaqueous mass movements in the St. 

Lawrence estuary, Saguenay fjord, and nearby lakes. This work illustrates the role of landsliding, 

in addition to liquefaction, in recording paleoearthquakes in the region. However, better 

constraints on timing of events are required for correlating deformation with specific events and 

geotechnical studies of susceptibility are required for determining the location and magnitude of 

those events. Consequently, the results of the Locat (2008) study were not used in the 

characterization of the 1663 Charlevoix earthquake. 

Based on the information above, the distribution for RLME magnitude tabulated below was 

developed. This magnitude distribution places most of the weight on the preferred magnitude 

from Lamontagne et al. (2008) and incorporates uncertainty from the paleoliquefaction record 

and recent estimates from Ebel (2009). Aleatory variability in the size of an individual 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-8

Charlevoix RLME is modeled as a uniform distribution of ±0.25 M units centered on the 

expected RLME magnitude value (Section 5.3.3.4). 

Expected Charlevoix RLME 

Magnitude

(M) Weight

6.75 0.2

7.0 0.5

7.25 0.2

7.5 0.1

6.1.1.5 RLME Recurrence 

The remaining nodes of the Charlevoix RLME logic tree address uncertainties in the 

specification of the annual frequency of RLMEs. 

Recurrence Methods and Data 

Paleoseismic investigations provide evidence of persistent earthquake activity through the 

Holocene. Filion et al. (1991) interpreted two earthquake-induced landslides by dating tree rings 

in the base of flow materials of dammed lakes along the Rivière du Gouffre, which is located 

within the Charlevoix seismic zone. Doig (1990) identified silt layers in lakes as recording 

earthquake-induced landslides and inferred a variable recurrence rate for the Charlevoix seismic 

zone: a recurrence interval of 120 years from 320 BC to AD 800; 270 years from AD 800 to

1500; and 75 years from AD 1500 to the present. Some silt layers in the section were correlated 

with historical earthquakes from 1638, 1663, 1791, 1870, and 1925 (Doig, 1990). These 

observations are difficult to quantitatively incorporate within earthquake recurrence calculations 

since silt layers may be due to nontectonically induced landslides; however, if the cause is 

tectonic, these silt layers can be attributed to either local moderate-sized earthquakes or distant 

large-magnitude earthquakes. Assigning a magnitude, location, and recurrence for the features 

identified by Doig (1990) would require a detailed chronology of regional landslide features and 

geotechnical assessments of their strength. Therefore, the recurrence for the Charlevoix RLME 

source is modeled from the 1663 and 1870 earthquakes and two prehistoric earthquakes 

identified by Tuttle and Atkinson (2010), which does include geotechnical assessments of 

liquefaction potential of host sediments in the evaluation of magnitude and location for these 

paleoearthquakes. 

Tuttle and Atkinson (2010) provide evidence of at least three Holocene paleoearthquakes in 

Charlevoix with M ≥ 6.2, including one historical event with a bracketed age of at least 540 yr 

BP. Tuttle and Atkinson (2010) argue that the 540 yr BP features could be assigned to one of 

three historical Charlevoix earthquakes since 1660. This set of liquefaction features is therefore 

included in the recurrence assessment as either the 1663 or 1870 earthquake. Two prehistoric 

paleoearthquakes are included in the assessment of Charlevoix RLME recurrence. The oldest 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-9

generation of features interpreted as having been formed by paleoearthquakes includes 

pseudonodules and related folds along the Malbaie River, and pillars and convolute bedding 

along the Gouffre River formed between 10,120 and 9,410 yr BP (Tuttle and Atkinson, 2010). A 

paleoearthquake of intermediate age is identified by sand dikes and load casts formed since 

5,040 yr BP (Tuttle and Atkinson, 2010). Dionne (2001) reports evidence of a sea-level lowstand 

of 10 m (33 ft.) along the south shore of the St. Lawrence estuary between 6 and 7 ka based on 

the elevations of intertidal or subtidal deposits overlying the erosional surface of marine clay and 

covered by emergent organic layers. This lowstand may have reduced the completeness of the 

paleoliquefaction record during that time, indicating that the three events observed by Tuttle and 

Atkinson (2010) in the past 10 kyr should be viewed as a minimum. 

The available data suggest three possible alternatives for assessing the RLME recurrence rates: 

the historical record and the two alternative geologic records of 6–7 kyr and 9.5–10.2 kyr. The 

alternatives for the number of RLMEs in each time period are the 1870 and 1663 earthquakes in 

the historical period (data set 1); the 1870 and 1663 earthquakes with one paleoearthquake in 

6–7 kyr (data set 2); and the 1870 and 1663 earthquakes with two paleoearthquakes in 9.5–10.2 

kyr (data set 3). The assessment of RLME recurrence puts the greatest weight on the 6–7 kyr 

geologic record [0.6] because geologic conditions affecting the susceptibility of sediments are 

not likely to have changed since the sea level lowstand at 6–7 ka and thus the geological record 

is expected to be reasonably complete. The longer, 10 kyr, geologic record may be affected by 

incompleteness in the period before 6–7 ka, and is thus given lower weight [0.2], one-third of the 

weight assigned to the shorter geologic period. The historic period is also given lower weight 

[0.2] because it contains a small sample (two earthquakes) and the short recurrence interval 

between the 1663 and 1870 earthquakes could have occurred by chance (e.g., with approximately 

10 percent probability for a Poisson process with the average return period based on the 6–7 kyr 

record). 

The three alternative data sets represent two types of data. Data set 1 consists of earthquakes 

with known times of occurrence and is analyzed by the ―Earthquake Recurrence Intervals‖ 

approach, while data sets 2 and 3 represent ―Earthquake Counts in a Time Interval.‖ The 

common logic tree format used for the RLME sources includes a node for Recurrence Method 

and a node for Recurrence Data. The weights assigned to the three alternative data sets are used 

to assign the weights to the branches for these two nodes in the RLME logic tree. For the 

Recurrence Method node, the ―Earthquake Recurrence Intervals‖ approach is assigned a weight 

of 0.2, the weight assigned to data set 1, and the ―Earthquake Count in a Time Interval‖ approach 

is assigned a weight of 0.8, the sum of the weights assigned to data sets 2 and 3. For the 

Recurrence Data node on the ―Earthquake Recurrence Intervals‖ branch, data set 1 then gets a 

conditional weight of 1.0. For the Recurrence Data node on the ―Earthquake Count in a Time 

Interval‖ branch, data set 2 gets a conditional weight of 0.75 (= [0.6]/[0.8]) and data set 3 gets a 

conditional weight of 0.25 (= [0.2]/[0.8]. 

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model, with a weight of 1.0 for the Charlevoix RLME source, as there are not sufficient data to 

justify including an alternative model. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-10

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs. These distributions were developed using the methodology described in Section 

5.3.3.1. For data set 1 the relative likelihood of various values of the recurrence rate parameter 

was developed using Equation 5.3.3-4 and the observations of one closed recurrence interval 

between the 1663 and 1870 earthquakes and one open interval post the 1870 earthquake. The 

resulting relative-likelihood-based distribution was represented by the five-point discrete 

distribution listed in Table 6.1.1-1. For data set 2 the relative-likelihood-based distribution was 

developed using Equation 5.3.3-2, with N equal to three earthquakes and T uniformly distributed 

between 6 and 7 kyr. The distribution for data set 3 was also developed using Equation 5.3.3-2, 

with N equal to four earthquakes and T uniformly distributed between 9.5 and 10.2 kyr. The 

resulting distributions for RLME recurrence frequency are listed in Table 6.1.1-1. 

6.1.2 Charleston 

The September 1 (August 31 local time), 1886, E[M] 6.90, earthquake that occurred in the 

Charleston, South Carolina, area is the largest historical earthquake ever recorded in the Eastern 

United States. This earthquake produced modified Mercalli intensity (MMI) X shaking in the 

epicentral area near Charleston, and was felt as far away as Chicago (Johnston, 1996c). Strong 

ground shaking during the 1886 Charleston earthquake resulted in extensive liquefaction, which 

was expressed primarily as sand-blow craters at the ground surface (Dutton, 1889). Because no 

primary tectonic surface rupture has been identified as the causative structure for the 1886 

earthquake, a combination of geologic, geophysical, geomorphic, and instrumental seismicity 

data have been used by multiple investigators to suggest several different faults as the potential 

source for Charleston-area seismicity (e.g., Behrendt et al., 1981; Talwani, 1982; Hamilton et al., 

1983; Behrendt and Yuan, 1987; Marple and Talwani, 2000; Weems and Lewis, 2002; Talwani 

and Katuna, 2004; Dura-Gomez and Talwani, 2009; Talwani and Dura-Gomez, 2009; Chapman 

and Beale, 2008, 2010). 

The existence of pre-1886 sand-blow craters and other paleoliquefaction features that occur 

throughout coastal South Carolina also provides evidence for prior strong ground motions during 

prehistoric large earthquakes in the region (e.g., Obermeier et al., 1989; Weems and Obermeier, 

1990; Amick et al., 1990a, 1990b; Talwani and Schaeffer, 2001; Talwani et al., 2008). 

Paleoliquefaction studies conducted in coastal South Carolina since the 1980s provide evidence 

that the Charleston seismic source exhibits RLMEs and appears to be confined to the Charleston 

area. Based on the strong field evidence for RLMEs derived from the study of liquefaction and 

paleoliquefaction features, the Charleston seismic zone is characterized as an RLME source. 

Appendix Table D-6.1.2 (data summary table) lists the references that were reviewed to 

characterize the Charleston RLME source, and Appendix Table C-6.1.2 (data evaluation table) 

lists the data that were explicitly used to constrain the characterization of this RLME source. 

Neither the 1886 nor the prehistoric (i.e., pre-1886) earthquakes in the Charleston area can be 

definitively attributed to any specific fault or fault zone at the present time. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-11

6.1.2.1 Evidence for Temporal Clustering 

The first node of the logic tree (Figure 6.1.2-1) addresses the issue of temporal clustering of 

earthquakes in the present tectonic stress regime (see Section 5.1.2). The rates of deformation 

suggested by paleoliquefaction data and the lack of surface features that would be expected if 

those deformation rates persisted over the long term lead to the conclusion that either the recent 

sequence of earthquakes is an isolated occurrence in time, or such sequences occur as clusters 

with long intercluster periods of seismic quiescence. The recurrence behavior of the large 

earthquakes in the Charleston seismic zone therefore may be highly variable through time, such 

that periods of activity alternate with periods of quiescence. Section 5.1.2 provides a definition 

and discussion of the temporally clustered earthquake model. 

Geologic and geomorphic observations suggest that inter-event times of large earthquakes in the 

Charleston seismic zone since the mid-Holocene (approximately hundreds to a few thousand 

years; see Section 6.1.2.5) are not characteristic of the region over longer-term periods. For 

example, based on reprocessed seismic reflection data, Chapman and Beale (2008, 2010) note 

evidence of a steeply dipping, down-to-the-east normal fault with approximately 200 m (656 ft.) 

of vertical offset in early Mesozoic sedimentary and volcanic rocks. They also report that 

overlying Cretaceous and Tertiary coastal plain sediments show approximately 10 m (33 ft.) of 

reverse up-to-the-east minor reverse displacement. Based on the minor amounts of Cretaceousand-younger vertical separation associated with subsurface faults in the Charleston area, the midHolocene to modern seismicity rates inferred from the paleoliquefaction record are not 

interpreted to be indicative of the longer-term behavior of the Charleston seismic zone. 

Additionally, geomorphic observations suggest that the high rate of recurrence of large 

earthquakes within the Charleston seismic zone inferred from mid-Holocene to modern 

seismicity is not indicative of the longer-term behavior of the Charleston seismic zone. A 

protracted period of large earthquakes recurring on the order of hundreds to a few thousand years 

apart would produce tectonic landforms with clear geomorphic expression, such as those present 

in regions of the world with comparably high rates of moderate to large earthquakes. For 

example, faults in the Eastern California shear zone with submillimeter-per-year slip rates and 

recurrence intervals on the order of about 5,000 years have clear expression in the landscape 

(Rockwell et al., 2000). The fact that such landforms are not evident in the Charleston area 

suggests that the Charleston source may have a recurrence rate that is highly variable through 

time. Therefore, sequences of earthquakes spaced about 500 to 1,000 years apart may be 

followed by quiescent intervals of many thousands of years. 

Based on the geologic and geomorphic lines of evidence discussed above, the high rate of midHolocene to modern seismicity in the Charleston seismic zone is not interpreted to be a longlived phenomenon. However, because no data definitively demonstrate whether the Charleston 

seismic zone is currently in or out of a temporal cluster, the Charleston RLME seismic source is 

modeled as ―in‖ a temporal cluster with a weight of 0.9 and ―out‖ of a temporal cluster with a 

weight of 0.1 in this study (Figure 6.1.2-1). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-12

6.1.2.2 Localizing Feature 

The second node of the Charleston RLME source logic tree indicates whether future earthquakes 

in the Charleston seismic zone will be associated with a specific localizing tectonic feature 

(Figure 6.1.2-1). As described in Section 6.1.2.3, numerous faults are postulated in the 

Charleston area, but there is no direct evidence that any structure is an active tectonic feature. 

Moreover, the 1886 earthquake is not definitively attributed to any particular fault or fault zone. 

Therefore, the ―Random in Zone‖ option is given a 1.0 weight in the model. This modeling 

decision reflects the interpretation that future Charleston earthquakes will not necessarily occur 

on any known fault or fault zone, but rather somewhere within the alternative configurations for 

the Charleston RLME source shown on Figure 6.1.2-2. 

6.1.2.3 Geometry and Style of Faulting 

The third through fifth nodes of the Charleston RLME source logic tree address parameters that 

characterize source geometry, seismogenic crustal thickness, and rupture orientation for the 

Charleston RLME seismic source zones (Figure 6.1.2-1). The source characterization for 

Charleston comprises the following three alternative configurations (Figure 6.1.2-2): 

Charleston Local—The small ―local‖ configuration includes the 1886 meizoseismal area 

(Bollinger, 1977); the preponderance of 1886 liquefaction features (e.g., Dutton, 1889; 

Talwani and Schaeffer, 2001); instrumentally located earthquakes in the Middleton Place–

Summerville seismic zone (Madabhushi and Talwani, 1993); and numerous postulated faults 

(e.g., Weems and Lewis, 2002; Talwani and Katuna, 2004; Bartholomew and Rich, 2007; 

Talwani and Dura-Gomez, 2009). 

Charleston Narrow—The ―narrow‖ configuration contains postulated north-northeast-striking 

structures, including the postulated Woodstock fault (Talwani, 1982); the southern segment 

of the postulated East Coast fault system (Marple and Talwani, 2000); and one interpretation 

of the location of Chapman and Beale’s (2009) ―fault C.‖

Charleston Regional—The large ―regional‖ configuration envelops most of coastal South 

Carolina, including the preponderance of pre-1886 paleoliquefaction features and postulated 

faults, and extends offshore to include the Helena Banks fault zone (Behrendt and Yuan, 

1987). 

For seismogenic crustal thickness, the fourth node of the logic tree (Figure 6.1.2-1), the three 

alternative Charleston source configurations adopt values and weights (shown in brackets) of 15 

km (9 mi.) [0.2], 20 km (12 mi.) [0.4], and 25 km (16 mi.) [0.4]. Seismogenic crustal thickness in 

the Charleston area is not well constrained, but available data are consistent with these values. 

Bollinger (1983) indicates that seismogenic thickness in the Charleston area is poorly 

constrained, but he estimates a value of 12 km (7.5 mi.) for the 1886 earthquake on the basis of 

empirical scaling relations. Dura-Gomez and Talwani’s (2009) relocated small-magnitude 

earthquakes in the Charleston area indicates depths to 16 km (10 mi.), with most hypocenters 

between 3 and 13 km (2 and 8 mi.) depth. Moreover, the CEUS SSC Project default values for 

seismogenic crustal thickness are consistent with those used in previous SSCs for Charleston. 

Bollinger (1992) adopts depths of 14 and 25 km (8.5 and 15.5 mi.) for his ―Local Charleston‖ 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-13

and ―SC Piedmont and Coastal Plain‖ zones, respectively. Chapman and Talwani (2002) adopt a 

value of 25 km (15.5 mi.) in their source characterization developed for the South Carolina 

Department of Transportation. Silva et al. (2003) adopt values of 16 and 20 km (10 and 12.5 mi.) 

depth, inferred from contemporary seismicity. 

The remaining data used to constrain each of these three alternative configurations are 

summarized below and are shown on Figures 6.1.2-3, 6.1.2-4, 6.1.2-5a, and 6.1.2-5b. Additional 

descriptions of the data constraining the Charleston model are provided in Appendix Table 

C-6.1.2. 

Charleston Local Source 

The Charleston Local source configuration is an approximately 100 by 50 km (60 by 30 mi.) 

northeast-elongated zone centered on the 1886 Charleston meizoseismal area (area of greatest 

damage) (Figures 6.1.2-5a and 6.1.2-5b). The Charleston Local source completely incorporates 

the 1886 earthquake MMI X isoseismal (Bollinger, 1977); the majority of identified Charlestonarea tectonic features and inferred fault intersections (e.g., Weems and Lewis, 2002; Talwani and 

Katuna, 2004; Bartholomew and Rich, 2007; Talwani and Dura-Gomez, 2009); and the majority 

of reported 1886 liquefaction features (e.g., Dutton, 1889; Talwani and Schaeffer, 2001). The 

Charleston Local source also envelops instrumentally located earthquakes in the Middleton 

Place–Summerville seismic zone (Tarr et al., 1981; Tarr and Rhea, 1983; Madabhushi and 

Talwani, 1993). The Charleston Local source excludes the northern extension of the southern 

segment of the postulated East Coast fault system (Marple and Talwani, 2000) because this 

system extends well north of the meizoseismal zone and is included in the Charleston Narrow 

source geometry. The Charleston Local source also excludes outlying liquefaction features, 

because liquefaction occurs as a result of strong ground shaking that may extend well beyond the 

extent of the causative fault. 

In summary, the Charleston Local source configuration envelops (1) the meizoseismal area of the 

1886 earthquake; (2) the area containing the majority of local tectonic features (although many 

have large uncertainties associated with their existence and activity); (3) the Middleton Place–

Summerville seismic zone; and (4) the area of greatest density of 1886 liquefaction and 

prehistoric liquefaction. These four observations suggest that future earthquakes having 

magnitudes comparable to that of the 1888 Charleston earthquake most likely will occur within 

the volume of crust defined by the Charleston Local source configuration. Therefore, because a 

preponderance of evidence supports the interpretation that the seismic source for the 1886 

Charleston earthquake is located in a relatively restricted area defined by the Charleston Local 

source, the Charleston Local source is given a relatively high weight of 0.50 in the model. 

Future ruptures in the Charleston Local source are oriented northeast, parallel to the long axis of 

the zone and the regional structural grain of the Appalachian orogen. Future ruptures are 

modeled as occurring on vertical strike-slip faults. All boundaries of the Charleston Local source 

are strict, such that ruptures are not allowed to extend beyond the zone boundaries. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-14

Charleston Narrow Source 

The Charleston Narrow source configuration is an approximately 65 by 30 km (40 by 20 mi.), 

north-northeast-oriented source (Figures 6.1.2-5a and 6.1.2-5b). The geometry of the Charleston 

Narrow source is constrained on the basis of postulated faults and tectonic features in the 

Charleston area, including (1) the proposed Woodstock fault (Talwani, 1982); (2) the zone of 

river anomalies (Marple and Talwani, 1993) and the southernmost portion of the southern 

segment of the proposed East Coast fault system (Marple and Talwani, 2000); (3) the proposed 

Woodstock, Ashley River, Sawmill Branch, Lincolnville, and Charleston faults (Talwani and 

Dura-Gomez, 2009); and (4) one interpretation of the location of ―fault C‖ by Chapman and 

Beale (2009), based on reprocessed seismic reflection lines. These postulated faults and tectonic 

features strike generally northeast and are located in the same narrowly constrained area. 

However, the Charleston Narrow source is not modeled as any particular fault, but rather as an 

area that represents the possibility that one or more of these features may exist and may be 

active. As described below in Section 6.1.2.5 (Recurrence), the Brownian Passage Time (BPT) 

renewal model is applied with low weight to the Charleston Narrow source configuration 

because it is the most ―fault-like‖ of the alternative configurations.

The northeast and southwest extents of the narrow source are defined by fault mapping from 

Dura-Gomez and Talwani (2009) and Talwani and Dura-Gomez (2009). Marple and Talwani’s 

(2000) depiction of the southern segment of the East Coast fault system extends northeast 

beyond the narrow source configuration. However, according to Dura-Gomez and Talwani 

(2009) and Talwani and Dura-Gomez (2009), evidence for the existence and activity of the East 

Coast fault system is greatest in the south (within the narrow source configuration) and decreases 

northeastward (beyond the narrow source configuration). The northeast and southwest 

boundaries of the Charleston Narrow source configuration are leaky, such that ruptures that 

initiate within the zone are allowed to extend beyond the zone boundaries in those directions, but 

by no more than 50 percent of the rupture length beyond the boundary. 

The Charleston Narrow source configuration includes postulated faults with varying degrees of 

evidence of existence, none of which has clear evidence for Neogene activity. The Charleston 

Narrow source configuration is given a 0.30 weight in the CEUS SSC model. 

Future ruptures in the Charleston Narrow source are oriented north-northeast, parallel to the long 

axis of the zone. Future ruptures are modeled as occurring on vertical strike-slip faults. As 

described above, the northeast and southwest boundaries of the Charleston Narrow source are 

leaky, whereas the northwest and southeast boundaries of the Charleston Narrow source are 

strict, and ruptures are not allowed to extend beyond the zone boundaries to the northwest and 

southeast. 

Charleston Regional Source 

The Charleston Regional source configuration is an approximately 260 by 150 km (160 by 95 

mi.) source that entirely envelops both the local and narrow zones. The regional source extends 

to the northeast and southwest to capture the preponderance of prehistoric paleoliquefaction 

features; to the southeast to include the offshore Helena Banks fault zone (Behrendt and Yuan, 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-15

1987); and inland to capture earthquakes in the Bowman seismic zone (Tarr et al., 1981; Tarr and 

Rhea, 1983; Smith and Talwani, 1985). The elongation and orientation of the Charleston 

Regional source is roughly parallel to the regional structural grain of the Appalachian orogen as 

well as to the elongation of 1886 isoseismals (Bollinger, 1977; Figures 6.1.2-5a and 6.1.2-5b). 

The large area covered by the Charleston Regional source reflects the uncertainty associated with 

the seismic source or sources that produced the 1886 and prehistoric earthquakes. The size of the 

regional source configuration is based partially on consideration of the liquefaction magnitudebound relation developed for the CEUS (Olson et al., 2005b; Olson, 2009) and the mapped 

extent of paleoliquefaction features. The inlandmost paleoliquefaction features are found along 

the Edisto River, approximately 80 km (50 mi.) from the coast (Figures 6.1.2-3 and 6.1.2-5a; 

Obermeier, 1996, figure 7.6) and typically are smaller than those found nearer the coast. The 

regional source extends inland of these features, however, in recognition of the fact that 

liquefaction susceptibility generally decreases further inland due to material properties and 

saturation level. The regional source extends offshore because, based on the distribution of 

liquefaction and paleoliquefaction features, the possibility of an offshore seismic source cannot 

be precluded. Moreover, the regional source extends offshore to include the northeast-striking 

Helena Banks fault system, as is clearly shown by multiple seismic reflection profiles, and is 

interpreted to exhibit Late Miocene offset (Behrendt et al., 1983). Furthermore, the occurrence of 

at least one light-magnitude earthquake in 2002 (November 11, E[M] 3.98) suggests a possible 

spatial association of seismicity with the mapped trace of the Helena Banks fault system. 

The preponderance of evidence supports the interpretation that the seismic source for Charleston 

RLMEs is located in a relatively restricted area defined by either the Charleston Local or Narrow 

source configurations. The larger volume of crust represented by the Charleston Regional source 

configuration allows for the possibility that Charleston RLMEs are produced by a fault of faults 

beyond the 1886 meizoseismal zone and beyond the area containing the majority of postulated 

Charleston faults. The Charleston Regional source configuration is given a 0.20 weight in the 

CEUS SSC model. 

For future rupture orientations in the Charleston Regional source configuration, two alternatives 

exist: (1) future ruptures oriented parallel to the long axis of the source (northeast) with 0.80 

weight, and (2) future ruptures oriented parallel to the short axis of the source (northwest) with 

0.20 weight. In these and all cases for Charleston, future ruptures are modeled as occurring on 

vertical strike-slip faults. All boundaries of the Charleston Regional source are strict, such that 

ruptures are not allowed to extend beyond the zone boundaries. 

6.1.2.4 RLME Magnitude 

The sixth node of the Charleston RLME source logic tree defines the magnitude of future large 

earthquakes in the Charleston RLME source, and assigned weights (Figure 6.1.2-1). Estimates 

for magnitude are based on estimates of magnitude for the 1886 Charleston earthquake and on 

geotechnical estimates of magnitudes of prehistoric earthquakes in coastal South Carolina. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-16

Estimates of 1886 Earthquake Magnitude 

Estimates for the magnitude of the 1886 Charleston earthquake typically are in the high-6 to 

mid-7 range, with more modern estimates generally nearer the low end of this range. For 

example, a geotechnical assessment of 1886 liquefaction data led Martin and Clough (1994) to 

estimate M 7–7.5 for the 1886 Charleston earthquake. Johnston (1996c) estimates M 7.3 ± 0.26 

for the earthquake, based on isoseismal area regressions accounting for eastern North America 

anelastic attenuation. The best estimate by Bakun and Hopper (2004) is M 6.9, with a 95 percent 

confidence level corresponding to a range of M 6.4–7.1, based on isoseismal area regression, 

including empirical site corrections. Most recently, Talwani (2009) studied empirical fault 

length–magnitude relationships and geotechnical assessments of the 1886 and prehistoric 

Charleston earthquakes and derives a best estimate of M 7.0 for the 1886 earthquake. The CEUS 

SSC earthquake catalog assigns E[M] 6.90 to the 1886 Charleston earthquake. 

Geotechnical Estimates of Prehistoric Earthquake Magnitudes 

Geotechnical estimates for the magnitudes of prehistoric earthquakes typically are based on one 

or more of the following factors: (1) empirical relations between size of paleoliquefaction 

features (e.g., dike width) and magnitude; (2) characterization of in situ sediment properties and 

the degree of strong ground motion required to liquefy those sediments; (3) distance separating 

the most distal paleoliquefaction feature from a known or assumed earthquake location; and (4) 

areal extent of the paleoliquefaction field produced by a single earthquake. Dike widths and 

other paleoliquefaction-feature dimensional data are lacking for the Charleston region, so 

magnitude estimates for prehistoric Charleston earthquakes are based on in situ soil properties 

and the spatial distribution of paleoliquefaction features. Geotechnical estimates for the 

magnitudes of prehistoric earthquakes in the Charleston seismic zone vary widely, but typically 

are in the high-5 to high-7 range. These widely varying magnitude estimates reflect the 

uncertainties associated with the use of paleoliquefaction data (see Appendix E, CEUS 

Paleoliquefaction Database, Uncertainties Associated with Paleoliquefaction Data, and Guidance 

for Seismic Source Characterization). 

Hu et al. (2002a, 2002b) describe methodologies and provide estimates for the magnitudes of 

prehistoric Charleston earthquakes based on geotechnical estimates of in situ soil properties. 

They report magnitude estimates ranging from M 6.8 to 7.8 for ―large‖ regional Charleston 

earthquakes, and from M 5.5 to 7.0 for possible ―moderate‖ local earthquakes at Georgetown, 

South Carolina. A subsequent study by Leon et al. (2005), which includes two of the same three 

coauthors as Hu et al. (2002a, 2002b), presents lower magnitude estimates for prehistoric 

Charleston earthquakes. Leon (2003) and Leon et al. (2005) present geotechnical assessments of 

magnitude for Charleston prehistoric earthquakes that account for the effects of sediment aging. 

Their magnitude estimates range from M 5.5 to 7.2 for ―large‖ regional Charleston earthquakes 

and from M 4.3 to 6.4 for possible ―moderate‖ local earthquakes at Bluffton and Georgetown, 

South Carolina. Using standard penetration test, cone penetration test, and shear-wave velocity 

data, Gassman et al. (2009) suggest a preferred magnitude range of M 6.7–7.0 for prehistoric, 

historic, and future earthquakes in the Charleston seismic zone. Based on the interpretation of 

prehistoric Charleston earthquakes developed as part of the CEUS SSC Project (see Section 

6.1.2.5—Recurrence), paleoliquefaction fields are similar to the 1886 earthquake liquefaction 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-17

field in location and extent. As such, the prehistoric earthquakes that formed these fields likely 

had magnitudes similar to the 1886 earthquake. 

Charleston RLME Magnitude 

The Charleston RLME source magnitude distribution for future large earthquakes is based on 

assessment of the currently available data, interpretations of the range of magnitude estimates for 

the 1886 and prehistoric Charleston earthquakes, and the assumption that future large 

earthquakes will have magnitudes similar to these earthquakes. The magnitude distribution 

includes a total of five discrete magnitude values from M 6.7 to 7.5, each separated by 0.2 M

units (Figure 6.1.2-1). It includes a discrete value of M 7.3 to represent Johnston’s (1996c) mean 

estimate for the 1886 earthquake, as well as a higher value of M 7.5 to capture a low probability 

that future large earthquakes in the Charleston seismic source will be greater than M 7.3. To 

represent Bakun and Hopper’s (2004) best estimate of the 1886 Charleston earthquake 

magnitude, the Charleston RLME source magnitude distribution includes a discrete value of 

M 6.9. The magnitude distribution also includes a lower value of M 6.7 to capture a low 

probability that future large earthquakes in the Charleston seismic source will be less than M 6.9. 

The resulting RLME magnitude distribution is tabulated below. This distribution results in a 

weighted mean magnitude of M 7.1 for the Charleston RLME seismic source. Aleatory 

variability in the size of an individual Charleston RLME is modeled as a uniform distribution of 

±0.25 M units centered on the expected RLME magnitude value (Section 5.3.3.4). 

Expected Charleston RLME 

Magnitude

(M) Weight

6.7 0.1

6.9 0.25

7.1 0.3

7.3 0.25

7.5 0.1

6.1.2.5 RLME Recurrence 

The remaining nodes of the Charleston RLME source logic tree (i.e., nodes seven through 

twelve) address the uncertainty modeling of the of Charleston RLMEs (Figure 6.1.2-1). Section 

1.2.6 of Appendix E provides additional information on paleoliquefaction features in coastal 

South Carolina. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-18

Recurrence Method 

The recurrence data for the Charleston RLME source consists of ages of past RLMEs estimated 

from the paleoliquefaction record. Therefore, node seven of the logic tree indicates that 

recurrence for the Charleston RLME source is based solely on the ―Earthquake Recurrence 

Intervals‖ approach. 

Time Period 

The eighth node of the Charleston RLME source logic tree assesses length and completeness of 

the paleoliquefaction record, which are sources of epistemic uncertainty in the CEUS SSC 

(Figure 6.1.2-1). The paleoliquefaction record along the South Carolina coast extends from 1886 

to the mid-Holocene, approximately 5,500 yr BP (Talwani and Schaeffer, 2001). The consensus 

of scientists who have evaluated these data is that the paleoliquefaction record of earthquakes is 

complete only for approximately the past 2,000 years and that liquefaction events likely are 

missing from the older portions of the record (Talwani and Schaeffer, 2001). For this reason, this 

study places more weight on the paleoseismic record from the most recent 2,000 years of record. 

The perception that the paleoseismic record may be incomplete from 2,000 to 5,500 yr BP is 

based on the argument that past fluctuations in sea level have produced intervals of low water 

table conditions, and thus low liquefaction susceptibility, during which large earthquakes may 

not be represented in the paleoliquefaction record (Talwani and Schaeffer, 2001). While this 

assertion may be true, it is also possible that the paleoliquefaction record may be complete back 

to the mid-Holocene (Talwani and Schaeffer, 2001). Based on these arguments, the 

approximately 2,000-year record of Charleston earthquakes is given a 0.80 weight in the model, 

and the approximately 5,500-year record is given a 0.20 weight. 

Earthquake Count 

The ninth node of the Charleston logic tree addresses the uncertainty in the number of RLMEs 

that have occurred in the Charleston RLME source (Figure 6.1.2-1). Alternative interpretations 

of the distribution of paleoliquefaction features include a total of four large earthquakes in the 

past approximately 2,000 years and between four and six large earthquakes in the past 

approximately 5,500 years. The alternative characterizations represented in the logic tree are 

based on (1) interpreted length of the paleoliquefaction record, (2) interpreted types of 

constraining ages, and (3) evaluations of the area distribution and interpretations of which of the 

prehistoric liquefaction features were caused by large-magnitude earthquakes centered in the 

Charleston area and which were caused by moderate-magnitude local earthquakes. 

Talwani and Schaeffer (2001) combine previously published data with their own studies of 

paleoliquefaction features in the South Carolina coastal region to derive possible earthquake 

recurrence histories for the region. They estimate recurrence intervals of approximately 550 to 

1,000 years and interpret the possibility of both moderate- and large-magnitude earthquakes 

(roughly M 6+ and 7+, respectively). The CEUS SSC Project supplements Talwani and 

Schaeffer’s (2001) compilation of Charleston paleoliquefaction data with data from other studies 

(e.g., Noller and Forman, 1998; Talwani et al., 2008) (see Section 1.2.6 of Appendix E). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-19

Talwani and Schaeffer (2001) identify individual earthquake episodes based on regional 

correlations of prehistoric sand-blow craters with overlapping calibrated radiocarbon ages having 

1-sigma (68.3 percent confidence interval) error bands. The standard in paleoseismology, 

however, is to use calibrated radiocarbon ages with 2-sigma (95.4 percent confidence interval) 

error bands (e.g., Grant and Sieh, 1994). Likewise, in paleoliquefaction studies, to more 

accurately reflect the uncertainties in radiocarbon dating and age estimates of paleoliquefaction 

features, Tuttle (2001) advises the use of calibrated radiocarbon dates with 2-sigma error bands 

(as opposed to narrower 1-sigma error bands). On Tuttle’s (2001) recommendation, the CEUS 

SSC Project recalibrated and reported the conventional radiocarbon ages presented in Talwani 

and Schaeffer (2001) with 2-sigma error bands (see Appendix E and the CEUS SSC 

paleoliquefaction database). This recalibration was performed with the radiocarbon calibration 

program OxCal version 4.1 (Bronk Ramsey, 2009) using the radiocarbon calibration curve of 

Stuiver et al. (1998). The recalibrated 2-sigma radiocarbon ages form the basis of the CEUS SSC 

Project analyses of the timing, location, and magnitude of paleoearthquakes that induced 

liquefaction in the vicinity of Charleston, South Carolina. 

For the Charleston data set, two types of radiocarbon ages are used to constrain the timing of 

formation of prehistoric sand-blow craters, namely contemporary (or ―con‖) radiocarbon ages, 

and radiocarbon ages that provide maximum or minimum age constraints on a sand-blow crater 

(Figure 6.1.2-6). Contemporary ages are those ages interpreted by Talwani and Schaeffer (2001) 

as closely approximating the time of formation of the sand-blow crater. The data for determining 

contemporary ages include fragile twigs or stems that became entrained in fine-grained deposits 

within crater deposits during or very soon after crater formation, and that are thus approximately 

equivalent in age with time of formation of the feature. Maximum and minimum ages are 

provided by carbon samples collected from stratigraphic positions below and above a 

paleoliquefaction feature, respectively. Typically, the estimated ages of paleoliquefaction 

features from maximum/minimum pairs of radiocarbon samples are broader than those provided 

by contemporary radiocarbon ages. For this reason, contemporary ages are preferred. 

Another reason for preferring contemporary age constraints concerns the specific geologic 

environment in which the Charleston region sand-blow craters are found. The vast majority of 

the sand-blow craters are located on the crests of beach ridges in geologic units that are tens to 

hundreds of thousands of years old or more (McCartan et al., 1984; Obermeier, 1996). Moreover, 

LiDAR data indicate that the vast majority of these sand-blow craters features are located on 

local topographic highs, representing areas removed from active deposition that are characterized 

by ongoing soil formation, stripping, and reworking processes. Considering the geologic 

environment where the sand-blow craters occur, it is unclear exactly what radiocarbon ages from 

maximum/minimum samples collected from stratigraphic positions above and below the 

paleoliquefaction features may mean. However, as described below, the timing of prehistoric 

earthquakes in the Charleston region is largely constrained by contemporary ages, with the 

maximum/minimum ages primarily used as possible evidence for constraining spatial extent, and 

thus the magnitude, of some of the prehistoric liquefaction fields. 

Figures 6.1.2-7 and 6.1.2-8 are space-time diagrams showing the 2-sigma radiocarbon age 

constraints on paleoliquefaction features in the Charleston region as vertical lines, and 

interpreted earthquakes as colored horizontal bars. Age constraints from samples, or pairs of 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-20

samples, used to define each earthquake are shown as vertical colored bars. Appendix E provides 

a detailed description of the methodologies and uncertainties associated with interpreting 

prehistoric earthquakes from paleoliquefaction data. 

Figure 6.1.2-7 shows the prehistoric earthquake scenario based on contemporary age constraints 

only. Figures 6.1.2-9 through 6.1.2-13 show in map view the spatial distribution of 

paleoliquefaction features associated with each interpreted earthquake in the ―contemporary ages 

only‖ scenario. In this scenario, four large-magnitude regional earthquakes (1886, A, B, and C) 

have occurred in the past approximately 2,000 years. Two additional earthquakes (D and E) 

occurred in the past approximately 5,500 years. Yet, based on the possibly limited spatial extent 

of the liquefaction fields associated with earthquakes D and E, it is unclear from the 

―contemporary ages only‖ scenario whether earthquakes D and E were large-magnitude regional 

earthquakes with liquefaction fields similar to that produced by the 1886 earthquake, or whether 

they were moderate-magnitude local earthquakes. Table 6.1.2-1 summarizes the age constraints 

and sizes (regional or local) of interpreted prehistoric Charleston earthquakes A through E from 

the ―contemporary ages only‖ scenario.

Figure 6.1.2-8 shows the prehistoric earthquake scenario based on contemporary and 

maximum/minimum age constraints (the ―all ages‖ scenario). In this figure, the 

maximum/minimum age constraints are shown as vertical dashed lines to differentiate them from 

the solid vertical lines that represent contemporary age constraints. Unpaired maximum or 

minimum age constraints are shown as up or down arrows, respectively, and typically are not 

useful for interpreting prehistoric earthquakes. Figures 6.1.2-14 through 6.1.2-18 show in map 

view the spatial distribution of paleoliquefaction features associated with each interpreted 

earthquake in the ―all ages‖ scenario. The results of the ―contemporary ages only‖ and ―all ages‖ 

scenarios are nearly identical in terms of the timing of past earthquakes in coastal South 

Carolina. 

However, there are potentially important differences between the two scenarios with respect to 

the interpreted geographic extent of liquefaction in prehistoric earthquakes D and E. Specifically, 

earthquakes D and E in the ―contemporary ages only‖ scenario may have produced localized 

liquefaction fields (Figures 6.1.2-13 and 6.1.2-14) and therefore may have been moderatemagnitude earthquakes. The ―all ages‖ scenario, however, indicates that earthquake D and 

possibly earthquake E produced regional liquefaction fields (Figures 6.1.2-17 and 6.1.2-18) and, 

therefore, likely were large magnitude. Table 6.1.2-2 summarizes the age constraints and sizes 

(regional or local) of interpreted prehistoric Charleston earthquakes A through E. 

The ninth node of the Charleston logic tree shows weights for the possible combinations of 

prehistoric large earthquakes for the approximately 2,000-year and 5,500-year records (Figure 

6.1.2-1). Earthquake chronologies based on the ―contemporary ages only‖ scenario are assigned 

a weight of 0.80 because, as discussed above, contemporary ages provide the best 

approximations of the timing of formation of Charleston area sand-blow craters. Earthquake 

chronologies based on the ―all ages‖ scenario are assigned a weight of 0.20 because, as discussed 

above, it is unclear exactly what radiocarbon ages from maximum/minimum samples collected 

from stratigraphic positions above and below the paleoliquefaction features may mean. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-21

Earthquake Recurrence Model 

The tenth node of the Charleston RLME source logic tree defines the earthquake recurrence 

models used for the regional, local, and narrow source zones (Figure 6.1.2-1). For the regional 

and local sources, only the Poisson model is used. For the more ―fault-like‖ narrow source zone, 

the Poisson model is assigned 0.90 weight, and the BPT renewal model is assigned 0.10 weight. 

Use of the BPT renewal model requires specification of the coefficient of variation of the repeat 

time for RLMEs, parameter α. As discussed in Section 5.3.3, the uncertainty distribution for α

developed by Working Group (2003) was adopted. This distribution is shown on the eleventh node 

of the Charleston RLME source logic tree (Figure 6.1.2-1). Section 5.3.3 provides additional 

information regarding the use of the earthquake recurrence models. 

RLME Annual Frequency 

The final (twelfth) node of the logic tree addresses the uncertainty distributions for the annual 

frequency of RLMEs (Figure 6.1.2-1). These distributions were developed using the 

methodology described in Sections 5.3.3.1 and 5.3.3.2. For the Poisson model, the relative 

likelihood of various values of the recurrence rate parameter was developed using Equation 

5.3.3-4 and the observations of the time intervals between the selected paleoearthquakes and the 

open interval post the 1886 earthquake. For the renewal model, the relative likelihoods of various 

values of the mean recurrence interval for RLMEs were developed using Equations 5.3.3-7, 

5.3.3-8, and 5.3.3-9 for each set of past RLMEs and specified value of coefficient of variation. 

The resulting parameters were then used to compute the equivalent annual frequency of RLMEs 

using Equations 5.3.3-10 and 5.3.3-11. 

The data used for the recurrence rate calculations are the time intervals between individual 

RLMEs for the renewal model case, and the age of the oldest RLME for the Poisson case. These 

are calculated from the age estimates for each past RLME. With the exception of the 1886 

earthquake, these ages are estimated from two types of data, as described above, and are subject 

to uncertainty. One type of data consists of age dates for samples whose ages are considered to 

be contemporary with the earthquake occurrence, denoted as CON ages. Each sample has its own 

age estimate with associated uncertainty. Table 6.1.2-3 lists the sample age data used for each 

prehistoric earthquake. These data are shown on Figures 6.1.2-7 and 6.1.2-8. For this analysis, 

the range in CON ages of the samples listed in Table 6.1.2-3 was treated as a two-sigma 

uncertainty estimate. The uncertainty was approximated by a normal distribution with mean 

equal to the center of the age range and standard deviation equal to 1⁄4 of the uncertainty range. 

For the i

th sample associated with RLME A, the probability distribution for the true age of 

earthquake A is then given by the normal probability distribution: 

2

2

)(

exp)(

i

i

A

A

i

A

AAf

(6.1.2-1) 

where 

Ai

and 

2

Ai

are the mean and variance of the age of sample Ai, respectively. The 

likelihood for the age of A, given all of the associated sample ages, then becomes 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-22 n

i

n AAfAAL i

1

1..

)()(

(6.1.2-2) 

Equation 6.1.2-2 was used to compute the relative likelihood of possible ages for each RLME 

using the associated liquefaction feature age data in Table 6.1.2-2. These relative likelihoods 

were then normalized by their sum to produce the uncertainty distributions for the age of each 

RLME shown on Figure 6.1.2-19 with the label ―Con Ages.‖

The second type of data associated with the Charleston RLMEs is samples that provide 

constraints on the event age in terms of representing points in time either before or after each 

earthquake occurrence. These additional age data, labeled in Table 6.1.2-2 as either ―B‖ for 

before the earthquake or ―A‖ for after the earthquake, were used to modify the CON age 

distributions by simulating ages from the CON age distributions shown on Figure 6.1.2-19 and 

from a normal distribution for the constraining feature age, and rejecting those simulations that 

violate the age constraints. The process was repeated until 10,000 possible ages were obtained 

for each RLME; these were then ranked to produce the cumulative distributions labeled ―All 

Ages‖ on Figure 6.1.2-19. 

The uncertainty distributions for RLME annual frequency were then computed by repeatedly 

simulating samples of RLME dates from the age distributions shown on Figure 6.1.2-19 and 

computing a relative likelihood distribution for RLME rate from each sample. The resulting 

distributions were then combined to produce a composite distribution for RLME rate, assigning 

0.8 weight to RLME ages sampled from the Con Ages distributions and 0.2 weight to ages from 

the All Ages distributions. These composite distributions were then represented by five-point 

discrete approximations. The resulting distributions for RLME recurrence frequency are listed in 

Tables 6.1.2-4 and 6.1.2-5 for the Poisson and Renewal models, respectively. 

6.1.3 Cheraw Fault 

The Cheraw fault trends northeast and is located on the High Plains in southeastern Colorado, 

approximately 140 km (85 mi.) east of the Rocky Mountain range front (Crone and Machette, 

1995; Crone, Machette, Bradley, et al., 1997; Crone and Wheeler, 2000; Figure 6.1-1). The fault, 

which has a down-to-the-northwest throw, lies on the western side of the Las Animas arch, a 

relatively low-relief, 300 km (183 mi.) long, positive structural feature in southeastern Colorado 

(Curtis, 1988). The crest of the arch lies approximately 20–40 km (12–24 mi.) east of the Cheraw 

fault. 

Crone, Machette, Bradley, et al. (1997) note that the total throw of the fault is not substantial 

(only tens of meters are demonstrable) and that the fault does not appear to have a long history of 

recurrent movement. From interpretation of a structure-contour map of the top of the Lower 

Cretaceous Dakota Sandstone presented by Sharps (1976), Crone, Machette, Bradley, et al. 

(1997) estimate 6–8 m (20–26 ft.) of down-to-the-northwest throw, which is comparable to the 

amount of throw on early Quaternary alluvial deposits. 

The Cheraw fault, which is mapped for a distance of 46 km (28 mi.), forms a subtle, northwestfacing scarp that can be traced for at least 30 km (18 mi.; Kirkham and Rogers, 1981; Crone, 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-23

Machette, Bradley, et al., 1997). Based on the following, Kirkham and Rogers (1981) concluded 

that the Cheraw fault has been active in the Quaternary: the presence of this scarp, vegetation 

lineaments, linear ponds, sinkholes, and dissolution pits along the fault trace; the apparent 

ponding of alluvium against the scarp where the scarp interrupts the gradient of local drainages; 

and the apparent displacement of the middle Rocky Flats Alluvium. 

The fault was first recognized during regional geologic mapping by the USGS (Scott, 1970; 

Sharps, 1976; Kirkham and Rogers, 1981; Scott et al., 1978). Further paleoseismic field 

investigations of the Cheraw fault conducted by the USGS provided evidence for multiple 

surface-faulting earthquakes during the late Pleistocene and Holocene (Crone and Machette, 

1995; Crone, Machette, Bradley, et al., 1997). Based on the results of these studies, the Cheraw 

fault is characterized as an RLME fault source. 

Characterization of the Cheraw fault is based on references cited in the following subsections 

and in Appendix Tables C-6.1.3 Data Evaluation and D-6.1.3 Data Summary. The logic tree for 

the Cheraw RLME source is shown on Figure 6.1.3-1. Locations of tectonic features and key 

localities where detailed paleoseismic investigations have been conducted to evaluate the 

location and activity of the Cheraw fault are shown on Figure 6.1.3-2. The location of the 

Cheraw fault relative to total magnetic anomaly and residual isostatic gravity data is shown on 

Figure 6.1.3-3. 

6.1.3.1 Evidence for Temporal Clustering 

The first node of the logic tree (Figure 6.1.3-1) addresses the issue of temporal clustering of 

earthquakes in the present tectonic stress regime (see Section 5.1.2). The Cheraw fault lies within 

a seismically quiescent region of eastern Colorado, but has evidence for two to three surface 

ruptures in the past 20–25 kyr (Crone, Machette, Bradley, et al., 1997). Crone, Machette, 

Bradley, et al. (1997) concluded that three surface-rupturing earthquakes (at about 8, 12, and 20–

25 ka) are recorded in a trench excavated across the Cheraw fault. The evidence for the 

penultimate earthquake as presented by Crone, Machette, Bradley, et al. (1997) is not as 

definitive as the evidence for the earliest and latest earthquakes (Dr. A. Crone, USGS, electronic 

comm., April 21, 2010). Based on both review of the trench logs and data used to support the 

interpretation of three earthquakes reported by Crone, Machette, Bradley, et al. (1997) and 

communications with Dr. A. Crone, the likelihood that the latest Pleistocene displacement on the 

Cheraw fault is the result of two surface ruptures is given a weight of 0.4, and the published 

interpretation of three earthquakes is given a slightly higher weight (0.6). 

Crone, Machette, Bradley, et al. (1997) speculate that earthquakes older than about 25 kyr must 

have occurred before about 100 ka because of the time needed to incise, widen, and backfill the 

paleo-stream channel that is now filled with latest Pleistocene deposits (Crone and Wheeler, 

2000). The cumulative vertical offset on the Cretaceous shale is 3.2–4.1 m (10.5–13.5 ft.), which 

is the total offset of the two or three late Quaternary earthquakes (Crone, Machette, Bradley, et 

al., 1997). Crone and others (Crone, Machette, and Bowman, 1997; Crone, Machette, Bradley, et 

al., 1997) suggest that these earthquakes may be part of a pattern of temporal clustering of 

earthquakes in which one or more earthquakes occur in a short period of time (10–15 kyr) and 

that the interval of high activity is bounded by longer intervals (>100 kyr) of inactivity. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-24

Based on the geomorphic and geologic lines of evidence described above, the within-cluster 

branch of the logic tree is given a weight of 0.9, and the out-of-cluster branch is given a weight 

of 0.1 (Figure 6.1.3-1). There is no evidence to suggest the Cheraw fault is out of a cluster based 

on the fact that the time elapsed since the last Holocene earthquake (approximately 8,000 years; 

Crone, Machette, Bradley, et al., 1997) is not longer than the mean intracluster recurrence rate 

for two or three earthquakes in 20–25 kyr (approximately 13,158 or 8,333 years). This weighting 

is consistent with the weightings for other RLMEs that exhibit clustered behavior (e.g., New 

Madrid seismic zone, Meers fault). 

6.1.3.2 Geometry and Style of Faulting 

The Cheraw fault is well expressed as a topographic feature on the Shuttle Radar Topography 

Mission (SRTM) topographic data along its entire 46 km (28 mi.) long mapped extent; a subtle 

northwest-facing scarp is present along at least 30 km (18 mi.; Crone, Machette, Bradley, et al., 

1997). Dan Clark (Geoscience Australia) recently suggested that the fault may extend farther to 

the northeast, based on review of the Shuttle Radar Topographic Mission (SRTM) data, but no 

field investigation of this possible extension has been conducted (Dr. A. Crone, USGS, 

electronic comm., March 3, 2010). The possible northeast extension (approximately 16 km [10 

mi.]) parallels and appears to coincide in part with a railway line. Thus, it is not certain if the 

feature is a culture feature or a culturally modified tectonic feature. 

The second and third branches of the logic tree indicate that the Cheraw RLME source is 

modeled as a fault source and that two alternative total lengths of the fault are considered. The 

topographically well-expressed 46 km (28 mi.) long fault is given highest weight (0.8); the 

longer (extended) length of 62 km (38 mi.), which is based solely on interpretation of SRTM 

topographic data, is given much lower weight (0.2) pending confirmation by field investigations. 

Based on the paleoseismic evidence for multiple surface ruptures on the Cheraw fault, it likely 

extends to seismogenic depths. There is little seismicity within the vicinity of the Cheraw fault 

from which to assess the thickness of seismogenic crust. The generic distribution of 13 km 

(weight of 0.4), 17 km (weight of 0.4), and 22 km (weight of 0.2) is used. 

The downdip geometry of the Cheraw fault is not well known. In the near-surface trench 

exposures, the main fault dips steeply (70–80 degrees) to the northwest. The dip at depth, 

however, is uncertain. Crone and Wheeler (2000) give an average dip of 66 degrees based on the 

average dip of the main fault as mapped by Crone, Machette, Bradley, et al. (1997) in the only 

exposure of the fault, a 3–4 m (10–13 ft.) deep trench. The USGS characterization of the fault for 

use in the National Seismic Hazard Maps uses a dip of 60 degrees (2002 National Seismic 

Hazards—Fault Parameters database). Based on the observation of a steeply dipping main fault 

near the ground surface and analogy to well-documented seismogenic normal faults with dips of 

approximately 50 degrees at seismogenic depth in the Western United States, the following dip 

values and associated weights are used in this study to characterize the Cheraw fault: 50°NW 

(0.6), 65°NW (0.4). 

The sense of motion on the Cheraw fault is not well known, but it is inferred to be a down-to-thenorthwest normal fault based on the attitude of the faults exposed in the trench across the scarp 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-25

(Crone, Machette, Bradley, et al., 1997). No compelling evidence of lateral slip was observed on 

the Cheraw fault, and normal displacement is consistent with the attitude (steeply dipping to the 

northwest) and orientation (northeast-southwest strike) of the fault scarp in the prevailing stress 

field of the Midcontinent (east-northeast to northeast maximum horizontal stress direction) 

(Dr. A. Crone, USGS, electronic comm., January 11, 2010). 

6.1.3.3 RLME Magnitude 

The magnitude distribution for the Cheraw RLME source is defined using magnitude estimates 

from empirical relationships relating earthquake magnitude to fault rupture characteristics. 

Potential rupture lengths, rupture areas, and displacement-per-event data from trenching 

investigations are considered. The following relationships are used: 

Wells and Coppersmith (1994)—surface rupture length, subsurface rupture length, maximum 

displacement, average displacement, and rupture area for all faults. 

Somerville et al. (2001)—rupture area. 

The rupture characteristics that were used in these relationships were defined as described below. 

Rupture Length 

Two alternative rupture lengths are considered: 46 km (28.5 mi.), the total length of the well 

documented Quaternary faulting, and 30 km (18.5), the length of the fault with geomorphic 

expression of recent faulting. 

Average and Maximum Displacement 

Paleoseismic trenching investigations provide data for estimating a cumulative post-25 ka 

vertical displacement of approximately 3.2–4.1 m (10.5–13.5 ft.) (similar to the 3.3 m [10.8 ft.] 

estimated from the drilling results at this site [Crone and Machette, 1995]) and displacement per 

event of approximately 1.5 m (5 ft.); 1.1–1.6 m (3.6–5.2 ft.); and 0.5–1.1 m (1.6–3.6 ft.), 

respectively, for the three most recent earthquakes (oldest to youngest) (Crone, Machette, 

Bradley, et al., 1997). However, as discussed in Section 6.1.3.4, the evidence for the penultimate 

earthquake is not conclusive, and the displacements measured for this earthquake and the 

younger earthquake may have occurred in a single earthquake. Based on these observations, the 

average slip per earthquake at this site would range from 1.1 to 2.1 m (3.6 to 6.9 ft.); the 

maximum slip during a single earthquake would range from 1.6 m (5.2 ft.) to as much as 2.6 m 

(8.5 ft.). 

The trench site was selected because it is along a part of the fault where a prominent scarp is 

present on deposits incised into and therefore, younger than Rocky Flats Alluvium. Given the 

location of the site along the central part of the Quaternary fault and the prominence of the scarp 

at this locality, it is likely that these measured vertical offsets represent maximum rather than 

average displacements. However, since there is insufficient information to judge whether the 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-26

displacements per earthquake measured at the sole trench site along the Cheraw fault represent 

average or maximum values, both relationships are considered. 

Rupture Area 

Potential rupture area for the Cheraw fault rupture was estimated using rupture length, fault dip, 

and downdip fault width estimates for the Cheraw fault. Empirical relationships defined by Wells 

and Coppersmith (1994) for all slip types and by Somerville et al. (2001) for CEUS earthquakes 

are used to estimate magnitude from fault area. 

Based on the resulting magnitudes from these parameters (rupture length, displacement per 

event, and rupture area; see Table 6.1.3-1), the maximum magnitude distribution tabulated below 

was assigned to the Cheraw fault. 

Expected Cheraw RLME 

Magnitude

(M) Weight

6.8 0.3

7.0 0.3

7.2 0.3

7.4 0.1

6.1.3.4 RLME Recurrence 

The remaining nodes of the Cheraw RLME logic tree address the uncertainties in modeling the 

recurrence rate of Cheraw RLMEs 

Recurrence Method 

Two types of data are available for assessing the recurrence frequency of Cheraw RLMEs. The 

first is the average slip rate of the fault and the second is the number and timing of previous 

RLMEs, allowing application of the ―Earthquake Recurrence Intervals‖ approach. These two 

approaches are considered equally viable for assessing RLME annual frequency and are given 

equal weight in the Cheraw RLME source logic tree (Figure 6.1.3-1). 

Recurrence Data 

The average latest Pleistocene to Holocene slip rate on the Cheraw fault is on the order of 0.14–

0.18 mm/yr; more rigorous calculations based on timing and displacement data inferred from the 

trench excavation allow for a range of values between 0.23 and 0.09 mm/yr (Crone and Wheeler, 

2000). These slip rate values apply to periods of time when the fault is in an active phase. During 

that time, two or three surface rupturing earthquakes have occurred, with the oldest occurring 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-27

20-25 ka. As outlined above in Section 6.1.3.1, the evidence for the penultimate earthquake 

reported by Crone, Machette, Bradley, et al. (1997) is less definitive than the evidence for the 

earliest and latest earthquakes, but the three-event scenario is still slightly favored by Dr. Crone, 

one of the principal investigators for the trenching investigation. Based on review of the data and 

discussions with Dr. Crone, the published interpretation of three earthquakes is therefore slightly 

favored (weight of 0.6) over two (weight of 0.4). 

A long-term average slip rate can be estimated for the Cheraw fault. Drilling results from the 

USGS investigations show that about 7–8 m (23–26 ft.) of throw has occurred on the Cheraw 

fault since deposition of an alluvial deposit tentatively correlated with the early Pleistocene 

Rocky Flats Alluvium estimated to be 1.2 Ma (Crone and Wheeler, 2000). These data yield a 

best-estimate long-term slip rate of ≤0.007 mm/yr (Crone and Wheeler, 2000). It is noted, 

however, that subsequent work on the Rocky Flats Alluvium along the Colorado Front Range 

using terrestrial cosmogenic nuclide dating techniques has shown that the age of Rocky Flats 

Alluvium ranges between about 400 ka and 2 Ma, with age increasing with distance from the 

range front (Riihimaki et al., 2006). The long-term average slip rate thus could be a factor of two 

higher or lower than the best-estimate rate if a broader age uncertainty is considered. 

Because of the temporal clustering of earthquakes, it may not be appropriate to characterize the 

rate of movement on the fault using the long-term average. If it is assumed that the total 

displacement occurred in two intervals of clustered behavior comparable to the recent one from 

approximately 25 to 8 ka, the interval of time between the clusters could be several hundred 

thousand years. 

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model with weight 1.0 for the Cheraw RLME source as there are not sufficient data to justify 

including an alternative model. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs. These distributions were developed using the methodology described in Section 

5.3.3.1. 

For the ―in-cluster‖ case and the ―Earthquake Recurrence Intervals‖ approach, the relative 

likelihood of various values of the recurrence rate parameter was developed using Equation 

5.3.3-4 and the observation of one or two closed recurrence intervals and one open interval post 

the 20-25 ka earthquake. Thus the value of 

0

1

tt

N

i

i

was assumed to be uniformly distributed 

between 20 and 25 ka with N either 1 or 2. The resulting discrete uncertainty distributions for 

RLME annual frequency are listed in Table 6.1.3-2. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-28

For the in-cluster slip-rate case, the fault slip rates were assessed by dividing the late Quaternary 

vertical offset by the age of the oldest earthquake in the trench. Uncertainty in the offset was 

incorporated by sampling from a uniform distribution between 3.2 and 4.1 m (10.5 and 13.5 ft.),

and uncertainty in the age was incorporated by sampling from a uniform distribution between 20 

and 25 ka. The results of 10,000 simulations were ranked to produce a cumulative distribution 

for slip rate. Because the range of results was narrow (0.13 to 0.20 mm/year), the three-point 

approximation developed by Keefer and Bodily (1983) was used to define the discrete 

distribution for recurrence rate listed in Table 6.1.3-3.

―Out-of-cluster‖ RLME recurrence rates for the Cheraw fault are based on the estimated elapsed 

time between the Holocene/late Pleistocene earthquakes and the penultimate earthquake cluster. 

Longer recurrence intervals of either 200, 350, or 500 kyr are expected based on the geomorphic 

evidence for a minimum period of at least 100 kyr between the oldest earthquake recorded in the 

trench and the previous earthquake, and the observation that only two or three surface-rupturing 

earthquakes (similar in size to the recent surface-rupturing earthquakes) have occurred. These 

values are assigned equal weight and were inverted to produce RLME frequencies. The resulting 

distribution for out-of-cluster RLME frequency is listed in Table 6.1.3-4. 

The out-of-cluster slip rate for the Cheraw fault was assessed by dividing the total offset of the 

Rocky Flats Alluvium by its estimated age. The total offset is assumed to be uniformly 

distributed between 7 and 8 m (23 and 26 ft.). The age of the alluvium is most likely between 1.2 

and 2 Ma, but could be as young as 0.4 Ma. A trapezodial probability density function with 

uniform probability between 1.2 and 2 Ma, tapering to zero at 0.4 Ma, was used to represent this 

uncertainty. A distribution for long-term slip rate was developed by repeatedly sampling from 

the offset and age distributions and ranking the resulting values of slip rate. The results were then 

approximated using the Miller and Rice (1983) five-point discrete approximation to produce the 

out-of-cluster slip-rate distribution listed in Table 6.1.3-5. 

6.1.4 Meers Fault 

The Meers fault in southwestern Oklahoma (Figure 6.1.4-1) is the southern boundary of the 

Wichita frontal fault system, which separates the early Paleozoic Anadarko basin to the northeast 

from the late Paleozoic (Carboniferous) Arbuckle-Wichita-Amarillo uplift of the Ouachita 

orogeny to the southwest (Jones-Cecil, 1995; McConnell, 1989). During the Carboniferous, 

predominately oblique, left-lateral, and reverse slip along the Wichita frontal fault system 

uplifted the Wichita and related mountains and generated about 10 km (6 mi.) of total structural 

relief. Slip on the Meers fault contributed to approximately 2 km (1 mi.) of down-to-the-north 

vertical offset (Jones-Cecil, 1995). 

Paleoseismic studies of the Meers fault conducted in the late 1980s and the 1990s documented 

late Cenozoic reactivation of the Meers fault, including two Holocene surface-rupturing events 

with left-lateral reverse slip (Crone and Luza, 1990; Kelson and Swan, 1990; Swan et al., 1993). 

Based on the evidence for RLMEs, the Meers fault is characterized as an RLME source. 

Appendix Table D-6.1.4 lists the references that were reviewed in developing the 

characterization of the Meers RLME source, and Appendix Table C-6.1.4 lists the data that were 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-29

explicitly used in constraining the characterization. Figure 6.1.4-2 shows the Meers RLME 

source logic tree. 

6.1.4.1 Evidence for Temporal Clustering 

The first node of the logic tree (Figure 6.1.4-2) addresses the issue of temporal clustering of 

earthquakes in the present tectonic stress regime (see Section 5.1.2). Based on stratigraphic 

relations observed within trenches, soil pits, and hand auger samples, Swan et al. (1993) 

demonstrated that the Meers fault experienced two surface-rupturing earthquakes within the last 

approximately 3,000–4,000 years. However, based on observations of offset ridge crests across 

the fault, it is also apparent that there have been previous earthquakes on the fault (Crone and 

Luza, 1990; Ramelli and Slemmons, 1986; Swan et al., 1993). Swan et al. (1993) used 

correlations between soils observed along the Meers fault and more distant, dated soils to argue 

that any previous earthquakes along the Meers fault occurred prior to 200–500 ka. Based on 

these observations, the Meers fault appears to exhibit clustered earthquake behavior. 

Accordingly, the Meers fault can be classified currently as either ―in‖ or ―out‖ of an earthquake 

cluster. 

The in-cluster branch of the logic tree is given a weight of 0.8 and the out-of-cluster branch a 

weight of 0.2. The weights reflect that there is no evidence to suggest the Meers fault is out of a 

cluster, based on the fact that the time elapsed since the last Holocene event (approximately 

1,500 years) (Swan et al., 1993) is shorter than the weighted mean intracluster recurrence rate 

(approximately 2,300 years); see discussion of recurrence rates below. The weights also reflect 

that there is no evidence of current activity along the fault (i.e., seismicity). 

6.1.4.2 Localizing Feature 

The second branch of the logic tree (Figure 6.1.4-2) describes whether future earthquakes 

associated with the Meers fault structure are expected to be localized along the Meers fault scarp 

(―Fault‖ on the logic tree), or whether they may occur along other structures within the 

Oklahoma aulacogen with the same rates as observed on the Meers (―Random in Zone‖ on the 

logic tree). The inclusion of this branch on the logic tree represents the interpretation that, while 

none of the other faults associated with the Oklahoma aulacogen and Arbuckle-Wichita-Amarillo 

uplift have observed Quaternary faulting (e.g., Crone and Wheeler, 2000; Ham et al., 1964; 

Hanson et al., 1997; Swan et al., 1993; Wheeler and Crone, 2001; Williamson, 1996), there is the 

possibility that Meers-like earthquakes (e.g., similar magnitudes and recurrence rates) could 

occur on other faults within the aulacogen. 

Meers-like ruptures within the aulacogen are allowed only on the out-of-cluster branch of the 

logic tree, reflecting the interpretation that the spatial migration of Meers-like earthquakes will 

occur only if the Meers fault is out of a cluster (i.e., there can be only one Meers-like structure 

active within the aulacogen at any given time). This interpretation is based on the fact that there 

is no evidence of Quaternary activity on other faults within the aulacogen. On the out-of-cluster 

branch we give a low weight of 0.1 to the possibility of migrating Meers-like earthquakes 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-30

because there are no observations supporting the existence of other active faults within the 

aulacogen. 

6.1.4.3 Geometry and Style of Faulting 

The third through fifth branches of the logic tree describe the source geometry and style of 

faulting (Figure 6.1.4-2). 

The surface trace of the Meers fault is easily identified on aerial photographs for a total distance 

of approximately 26 km (16 mi.) as a south-down topographic escarpment (Ramelli et al., 1987; 

Crone, 1994). The scarp over much of this distance has been visited by various researchers and is 

attributed to Holocene rupture along the Meers fault (e.g., Crone and Luza, 1990; Kelson and 

Swan, 1990; Ramelli and Slemmons, 1990; Ramelli et al., 1987; Swan et al., 1993; Crone, 1994). 

In addition to this prominent scarp along the Meers fault, an approximately 11 km (6.8 mi.) 

southeast extension of the Meers fault scarp (Figure 6.1.4-1) was identified by Ramelli et al. 

(1987) and Ramelli and Slemmons (1990) by analyzing low-sun-angle aerial photography. The 

southeast extension is more subtle and discontinuous than the originally identified 26 km (16 

mi.) long scarp. Ramelli and Slemmons (1990) argue that the southeastern continuation of the 

scarp shares the same history of events on the Meers fault, judging by its alignment with the 

original scarp, the consistent down-to-south separation across the scarp, its proximity to the 

original scarp, and the presence of a small drainage channel aligned parallel to the scarp and 

across the pattern of local drainage networks. However, Ramelli and Slemmons (1990) also 

acknowledge uncertainty in the structural relationship between the northwest and southeast 

scarps due to a left step in the scarp near the junction of the two scarp strands, and due to the 

absence of a scarp across East Cache Creek (Figure 6.1.4-1). In addition, field evaluation of the 

southeast extension of the scarp has not been possible because the scarp traverses the Fort Sill 

Military Reservation, where access is restricted (Ramelli and Slemmons, 1990; Ramelli et al., 

1987; Crone, 1994). 

One researcher (Cetin, 2003) has suggested that the Meers fault scarp also extends 30 km 

(19 mi.) to the northwest of the prominent scarp described above (Figure 6.1.4-1). Cetin (2003) 

proposed this extension based on what he describes as ―displaced terrace deposits of Pleistocene 

age, displaced, buried and/or overthickened soil horizons, fault-related colluvium deposits 

(colluvial wedges) found near and only on the downthrown side of the fault, active seepage near 

the fault, deflection of stream alignments and the land use pattern along the fault.‖ However, as 

summarized by Wheeler and Crone (2003), the evidence presented by Cetin (2003) for 

Quaternary faulting is not conclusive. 

To account for the potential northwest extension, the characterization of the Meers fault used 

here includes two alternate interpretations of the extent of the active Meers fault trace (third 

branch on logic tree). The alternate interpretations for fault length are (1) the approximately 37 

km (23 mi.) trace as defined by Ramelli and Slemmons (1990) and Ramelli et al. (1987); and 

(2) an extended trace that includes the approximately 30 km (19 mi.) extension defined by Cetin 

(2003). The interpretations are given weights of 0.9 and 0.1, respectively. The low weight for the 

extended trace reflects that Cetin’s (2003) hypothesized northwest extension is not supported by 

robust, well-documented evidence and not widely supported by the expert community. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-31

When Meers-like earthquakes are allowed to migrate off the fault on the out-of-cluster branch, 

the earthquakes are limited to occurring within the Oklahoma aulacogen. 

The seismogenic thickness for the Meers fault is modeled as either 15 km or 20 km (9.3 mi. or 

12 mi.) with equal weights. These depths are based on the depth distribution of seismicity within 

Oklahoma (Luza and Lawson, 1993). 

The Meers fault is well recognized as a down-to-the-south oblique fault dominated by left-lateral 

slip (e.g., Swan et al., 1993; Wheeler and Crone, 2003). Based on trench exposures and a shallow 

seismic reflection survey, the Meers fault in the shallow subsurface (to over 150 m [490 ft.] 

depth) is thought to be near-vertical to slightly northeastward-dipping (Crone and Luza, 1990; 

Miller et al., 1990; Ramelli and Slemmons, 1990; Swan et al., 1993). However, regional well 

data, seismic reflection data, and comparison of the Meers fault to other faults in the Wichita 

frontal fault system suggest that at depth the Meers fault dips approximately 40 degrees to the 

southwest (Good et al., 1983; McConnell, 1989). Given the uncertainty as to what the best single 

dip is to characterize the Meers for future earthquake ruptures, a vertical and 40-degree 

southwest dip are given equal weights for earthquakes on the Meers fault. When Meers-like 

earthquakes are allowed for the out-of-cluster branch of the logic tree, they are characterized 

with a strike of N60W (i.e., approximately parallel to the faults of the Amarillo-WichitaArbuckle uplifts) and a random dip between 90 and 40 degrees to the southwest. 

The uncertainty in the Meers fault dip also drives uncertainty as to whether the fault is best 

characterized as an oblique normal or reverse fault. An oblique-reverse interpretation is preferred 

based on the observations in the shallow subsurface (Swan et al., 1993). The obliquity of slip 

along the fault is not well constrained because of the lack of robust horizontal and vertical 

control points in the same trenches that can be used to estimate net slip. Published estimates of 

horizontal-to-vertical slip ratios have ranged from 1.3:1 (Kelson and Swan, 1990; Swan et al., 

1993) to greater than 5:1 (Crone and Luza, 1990). 

6.1.4.4 RLME Magnitude 

The sixth branch of the logic tree describes the earthquake magnitudes for the Meers RLME 

(Figure 6.1.4-2). 

The Meers fault RLME source is modeled using a maximum moment earthquake model where 

the earthquake magnitude is characterized using a distribution of characteristic magnitudes 

representing epistemic uncertainty in the potential magnitude of future earthquakes. The 

magnitude distribution was defined using magnitude estimates from empirical relationships 

relating earthquake magnitude to fault rupture characteristics. The following relationships were 

used: 

Wells and Coppersmith (1994)—rupture length, maximum displacement, average 

displacement, and rupture area for strike-slip, reverse, and all faults. 

Hanks and Bakun (2002)—rupture area. 

Ellsworth (2003)—rupture area. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-32

Somerville et al. (2001, 2005)—rupture area. 

The rupture characteristics that were used in these relationships were defined as described below. 

Rupture Length 

Three rupture lengths for the Meers fault were used to estimate earthquake: 26 km, 37 km and 67 

km (16 mi., 23 mi., and 42 mi.). The 26 km (16 mi.) length is based on the widely accepted 

extent of Holocene rupture along the Meers fault. The 37 km (23 mi.) length includes the 

southeast extension to the Meers fault that was mapped by Ramelli and Slemmons (1990) and 

Ramelli et al. (1987) using low-sun angle photography (see Section 6.1.4.1). The 67 km (42 mi.) 

extent takes into account the approximately 30 km (19 mi.) long northwest extension of the fault 

proposed by Cetin (2003). 

Average and Maximum Displacement 

Only the study by Swan et al. (1993) is used to constrain displacement estimates because it is the 

only study to have recognized and explicitly measured displacements for the two Holocene 

events. Based on the results of their investigations, Swan et al. (1993) estimated that the average 

net slip per event along the fault is between 1.75 and 3 m (5.74 and 9.8 ft.), and the maximum 

net displacement is 3.5 to 5.25 m (12 and 17.2 ft.). These estimates are poorly constrained 

because Swan et al. (1993) were able to measure displacement at only a few locations; they 

measured only one net displacement (as opposed to just vertical or horizontal) and based most of 

the estimates on stratigraphic offsets of alluvial and colluvial material as well as paleochannel 

thalwegs exhumed in trenches, both of which can be difficult to use in developing accurate 

displacement estimates. 

Rupture Area 

Potential rupture area for the Meers fault rupture was estimated using rupture length, fault dip, 

and downdip fault width estimates for the Meers fault. A lower-bound rupture area of 390 km2

(151 mi.2) was calculated using the 26 km (16 mi.) estimate of Holocene rupture length (Ramelli 

and Slemmons, 1990; Ramelli et al., 1987), a fault dip of 90 degrees, and a downdip fault width 

of 15 km (9.3 mi.) based on the depth distribution of observed seismicity in the Oklahoma region 

(Luza and Lawson, 1993). The fault dip of 90 degrees was used for the minimum-bound estimate 

for the following reasons: 

There have been no studies that have reconciled the discrepancy between the shallow, nearvertical northeast dip of the fault and the deeper, moderate southwest dip of the fault (Crone 

and Luza, 1990; McConnell, 1989; Miller et al., 1990; Ramelli and Slemmons, 1990; Swan 

et al., 1993). 

There are few direct measurements of the Meers fault dip at depth (Crone, 1994; McConnell, 

1989). 

This estimate is meant to be a minimum bound. An upper-bound rupture area of 1,150 km2

was calculated using the 37 km (23 mi.) estimate of Holocene rupture length (Ramelli and 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-33

Slemmons, 1990; Ramelli et al., 1987); a fault dip of 40 degrees southwest; and a downdip 

fault width of 20 km (12 mi.), based on the depth distribution of observed seismicity in the 

Oklahoma region (Luza and Lawson, 1993). 

Estimated magnitude ranges from these relationships and fault characteristics are presented in 

Table 6.1.4-1. Note that the Wells and Coppersmith (1994) displacement relationships for 

reverse faults were not used because they are reported as not significant at the 95 percent 

probability level. Based on these estimates, the following distribution for the expected RLME 

magnitude for the Meers fault was developed: 

Expected Meers RLME 

Magnitude

(M)

Weight

6.6 0.1

6.7 0.45

6.9 0.3

7.3 0.1

7.4 0.05

The above distribution reflects the following preferences. 

Magnitudes from the 26 km (16 mi.) rupture length estimate were given the highest weight 

because (1) the scarp is best expressed along the 26 km (16 mi.) long segment, potentially 

suggesting that Holocene ruptures were restricted to this length; and (2) rupture length is the 

most robust directly measurable characteristic of the Holocene ruptures compared to 

estimates of displacement and area, which require more assumptions to derive. 

Magnitudes from the 37 km (23 mi.) rupture length estimate were given moderate weight 

because (1) future earthquakes may extend along the entire 37 km of the scarp, and (2) there 

is no available information on the timing of events along the extended scarp. 

Magnitudes from the 67 km (42 mi.) rupture length estimate were given the lowest weight 

because there is no evidence that a rupture has occurred along this entire length. 

Magnitudes from the 390 km2(151 mi.2) rupture area are given low to moderate weight 

because they reflect a reasonable interpretation of the potential rupture area of the Holocene 

earthquakes yet are a less direct measure of the Holocene events than the rupture length. 

Magnitudes from the 1,150 km2(444 mi.2) rupture area are given low weight because it is 

unlikely that any of the Holocene ruptures have the maximum bound area (i.e., maximum 

length, maximum depth, and shallow dip). 

Magnitudes from the displacement estimates are given low weights because the 

displacements are poorly constrained by the data collected by Swan et al. (1993). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-34

6.1.4.5 RLME Recurrence 

The remaining branches of the logic tree describe the assessment of RLME recurrence rates. 

Recurrence Method 

The data available for assessing the recurrence rate of the Meers RLMEs provide assessments of 

the timing of past earthquakes. Thus the ―Earthquake Recurrence Intervals‖ approach is used 

with weight 1.0 (Figure 6.1.4-2). 

Recurrence Data 

Recurrence rates are determined using inter-event times from the Holocene ruptures for (1) the 

out-of-cluster branch when earthquakes occur randomly within the OKA zone, and (2) the incluster branch when earthquakes occur on the Meers fault trace. For the out-of-cluster branch 

when the earthquakes occur on the Meers fault trace, the time elapsed between the last preHolocene earthquake and the Holocene earthquake cluster is used to define the recurrence rate. 

All recurrence rates are determined from the results of the Swan et al. (1993) study because it is 

both the most detailed study and the only study to have recognized and dated two Holocene 

earthquakes on the Meers fault. 

Out-of-cluster recurrence rates for the Meers fault are based on the estimated elapsed time 

between the Holocene earthquakes and the penultimate earthquake cluster. Swan et al. (1993) 

estimated that the elapsed time between the Holocene cluster and the next most recent 

earthquake was between 200 and 500 kyr. 

Intracluster recurrence rates for the Meers fault are based on estimates of the time elapsed since 

the first Holocene earthquake and the number of observed events in the Holocene. The date of 

the first Holocene earthquake is constrained by eight radiocarbon ages presented by Swan et al. 

(1993). From this suite of ages, the tightest constraining minimum and maximum ages are used 

to define the uncertainty in the date of the first Holocene earthquake. For example, four 

radiocarbon ages between approximately 7,000 and 3,000 yr BP constrain the maximum age of 

the earthquake, but only the tightest constraining age (2,918 calibrated years BP) is used. 

The maximum age of the earthquake is constrained by sample PITT-0478 of Swan et al. (1993). 

This sample was collected at the ―Valley‖ site of Swan et al. (1993; Figure 6.1.4-1) from an 

alluvial deposit near the bottom of the trench that was clearly offset by the fault. The calibrated 

radiocarbon age for this sample is 2,918 yr BP. The minimum age of the earthquake is 

constrained by sample PITT-0478 of Swan et al. (1993). This sample was collected at the 

―Southeast Ponded Alluvium‖ site of Swan et al. (1993; Figure 6.1.4-1) from an alluvial deposit 

interpreted to have ponded against the fault scarp after the first Holocene earthquake. The 

calibrated radiocarbon age for this sample is 2,093 yr BP. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-35

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model with weight 1.0 for the Meers RLME source as there are not sufficient data to justify 

including an alternative model. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs (Figure 6.1.4-2). These distributions were developed using the methodology 

described in Section 5.3.3.1. For the in-cluster case, the relative likelihood of various values of 

the recurrence rate parameter was developed using Equation 5.3.3-4 and the observations of one 

closed recurrence interval between the ~1,500 ka and the ~2,900 ka earthquakes and one open 

interval post the ~1,500 ka earthquake. The value of 

0

1

tt

N

i

i

was assessed to be uniformly 

distributed between 2,153 and 2,968 years, with N equal to 1. The resulting relative-likelihoodbased distribution was represented by the five-point discrete distribution listed in Table 6.1.4-2. 

For the out-of-cluster case, the range of return periods for clusters of 200–500 kyr was 

represented by three equally likely values of 200, 350, and 500 kyr. These return periods are 

inverted to produce the distribution for out-of-cluster RLME frequency listed in Table 6.1.4-3. 

The weighting reflects the evaluation that there is no evidence to support a preferred return 

period. 

6.1.5 Reelfoot Rift–New Madrid Fault System 

The New Madrid region is the source of the 1811-1812 New Madrid earthquake sequence, which 

includes the three largest earthquakes to have occurred in historical time in the CEUS. Extensive 

geologic, geophysical, and seismologic studies have been conducted to characterize the location 

and extent of the likely causative faults of each of these earthquakes and to assess the maximum 

magnitude and recurrence of earthquakes in this region. Appendix Table D-6.1.5 provides a 

summary of recent publications pertinent to the identification and characterization of seismic 

sources in this region. Based on the results of these studies, a system of faults within the New 

Madrid seismic zone (NMSZ) in the northern Reelfoot rift has been identified as an RLME 

source (herein referred to as the New Madrid fault system [NMFS] RLME source). Appendix 

Table C-6.1.5 lists the data that were explicitly used to constrain the characterization of this 

RLME source. The logic tree showing the characterization of the NMFS RLME sources is 

shown on Figure 6.1.5-1. 

Models that have been proposed to explain the origin of stresses driving active deformation in 

the CEUS and specifically in the NMSZ are summarized in Appendix Table D-6.1.5. Several of 

these provide explanations for localization of seismicity and recurrence of large-magnitude 

earthquakes in the NMSZ, as follows:
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-36

The presence of a rift pillow underlying the Reelfoot rift (Mooney et al., 1983) causes local 

stress concentration (Grana and Richardson, 1996). 

A weak subhorizontal detachment fault exists in the lower crust above the rift pillow that 

causes local stress concentration (Stuart et al., 1997). 

High local heat flow creates high ductile strain rates in the upper mantle and lower crust, 

causing seismicity in the upper crust (Liu and Zoback, 1997). 

Glacial unloading north of the NMSZ at the close of the Wisconsinan increased seismic 

strain rates in the NMSZ and initiated the Holocene seismicity (Grollimund and Zoback, 

2001). Modeling studies by Grollimund and Zoback (2001) show that the removal of the 

Laurentide ice sheet approximately 20,000 years ago (ka) changed the stress field in the 

vicinity of New Madrid, causing seismic strain rates to increase by about three orders of 

magnitude. The modeling predicts that the high rate of seismic energy release observed 

during late Holocene time is likely to continue for the next few thousand years (Grollimund 

and Zoback, 2001). 

Some local or regional perturbation of the stress field, pore pressure, or thermal state is 

responsible for triggering viscous relaxation of a weak lower-crustal zone within an elastic 

lithosphere. This may cause a sequence of fault ruptures in short recurrence intervals. A 

likely explanation for this perturbation is recession of the Laurentian ice sheet approximately 

14 ka (Kenner and Segall, 2000; Kenner, 2003). Kenner and Segall (2000) and Kenner 

(2003) suggest that this model explains the apparently contradictory observations of the 

Holocene increase in seismic strain rate in the NMSZ relative to long-term geologic and 

geomorphic observations that do not support steady-state deformation at these rates. Model 

predictions mostly are consistent with earthquake magnitude, coseismic slip, recurrence 

intervals, cumulative offset, and surface deformation rates in the NMSZ. In particular, the 

computed interseismic strain rates may be undetectable with available geodetic data, 

implying that low observed rates of strain accumulation cannot rule out future largemagnitude earthquakes. 

Low-permeability seals form around the fault zone as stress accumulates, raising the pore 

pressure until an earthquake happens. Temporal clustering may reflect the evolution of pore 

fluid pressure in a fault zone (Crone et al., 2003). 

Accelerated late Wisconsinan and Holocene denudation above the NMSZ due to the 

confluence of the Mississippi and Ohio rivers stepping north to Thebes Gap, perhaps in 

combination with the retreating Laurentide forebulge, may have been sufficient to initiate 

Holocene seismicity by causing a perturbation in the local stress field (the Kenner and Segall 

model [2000]; Van Arsdale et al., 2007). 

Descent of the ancient Farallon slab into the deep mantle beneath central North America as 

inferred from high-resolution seismic tomography induces a highly localized flow and 

stresses directly below the NMSZ. This localization arises because of structural variability in 

the Farallon slab and the low viscosity of the sublithospheric upper mantle. It is hypothesized 

that the mantle-flow-induced surface depression and associated local focusing of bending 

stresses in the upper crust may operate analogously to previous crustal loading scenarios, 

with one difference being that the slab-related loads reside in the mantle (Forte et al., 2007). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-37

Fault weakening can lead to repeated earthquakes on intraplate faults (Lyakhovsky et al., 

2001). The predicted patterns vary with the weakening history. Clusters of large intraplate 

earthquakes can result from fault weakening and healing, and the clusters can be separated by 

long periods of quiescence. Stress triggering and migration cause spatiotemporal clustering 

of earthquakes (Li et al., 2009). 

Strain in the NMSZ over the past several years has accumulated too slowly to account for 

seismicity over the past approximately 5,000 years, hence excluding steady-state fault 

behavior. Fault loading, strength, or both may vary with time in the plate interior. Time 

variations in stress could be due to local loading and unloading from ice sheets or sediments 

or to earthquakes on other faults (Calais and Stein, 2009). 

The NMSZ is associated with a local, northeast-southwest-trending, low-velocity anomaly in 

the lower crust and upper mantle, instead of a high-velocity intrusive body as proposed in 

previous studies. The low-velocity anomaly is on the edge of a high-velocity lithospheric 

block, consistent with the notion of stress concentration near rheological boundaries. This 

lithospheric weak zone may shift stress to the upper crust when loaded, thus leading to 

repeated shallow earthquakes (Zhang et al., 2009b). 

Stress changes are caused by the Quaternary denudation/sedimentation history of the 

Mississippi valley. Flexural stresses are sufficient to trigger earthquakes in a continental crust 

at failure equilibrium. The resulting viscoelastic relaxation leads to failure again on the main 

fault (lower-strength threshold) and neighboring faults. In the absence of significant far-field 

loading, this process can only maintain seismic activity for a few thousand years (Calais et 

al., 2009). 

The principal seismic activity within the upper Mississippi embayment is interior to the Reelfoot 

rift along the NMSZ. The NMSZ consists of three principal trends of seismicity: two northeasttrending arms and a connecting northwest-trending arm (Figure 6.1.5-2). This seismicity pattern 

has been interpreted as a northeast-trending right-lateral strike-slip fault system with a 

compressional left-stepover zone (Russ, 1982; Chiu et al., 1992; Schweig and Ellis, 1994), 

referred to as the NMFS. The south arm is coincident with the subcrop Blytheville arch; the 

central arm is coincident with the subcrop Pascola arch and surface Lake Country uplift; and the 

north arm trends at a low angle to the western margin of the Reelfoot rift (Figures 6.1.5-2 and 

6.1.5-3). Johnston and Schweig (1996) identify the following fault segments within the central 

fault system of the NMSZ: Blytheville arch (BA); Blytheville fault zone (BFZ); Bootheel 

lineament (BL); New Madrid West (NW); New Madrid North (NN); Reelfoot fault (RF); 

Reelfoot South (RS; Figure 6.1.5-4). They outline three rupture scenarios associating each of the 

three 1811-1812 earthquakes with fault segments (individually or in various combinations) using 

historical accounts and geologic evidence. Their interpretation is consistent with the spatial 

distribution and source characteristics of contemporary NMSZ seismicity (Hough and Martin, 

2002). 

The December 16, 1811, earthquake (referred to variously by different authors as the D1, D16, 

or NM1 earthquake) is believed to have occurred on the south arm of seismicity (possibly the 

Cottonwood Grove–Ridgley fault system) associated with the BA, a major crustal transpressional 

fault structure identified from seismic reflection data (Figure 6.1.5-2). Mueller et al. (2004) and 

Bakun and Hopper (2004a) infer a location for this earthquake on the northern end of the BA 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-38

(just south of the intersection of the BL and the BFZ (also referred to as the Cottonwood Grove 

fault). Two alternative geometries for the main fault rupture are outlined by Johnston and 

Schweig (1996): BA/BL (preferred) or BA/BFZ (Figure 6.1.5-4). More recent studies by 

Guccione et al. (2005) have documented evidence for multiple faulting earthquakes along the 

central part of the BL, and it is recommended that the BL be renamed the Bootheel fault (Figure 

6.1.5-3). Along the central part of the BL, a less than 10.2 ka Pleistocene braidstream sand has 

been displaced vertically approximately 3 m (10 ft.) and an approximately 2.4 ka Holocene 

paleochannel has been displaced horizontally at least 13 m (43 ft.; Guccione et al., 2005). 

The causative fault for the January 23, 1812, earthquake (referred to variously by different 

authors as the J1, J23, or NM2 earthquake) is generally inferred to be the northern seismicity arm 

of the NMSZ (segment NN; Figure 6.1.5-4). Baldwin et al. (2002) suggest that the North 

Farrenburg lineament may be associated with NN and represent the surface expression of 

coseismic rupture from the January 23, 1812, earthquake. Johnston and Schweig (1996) also 

consider an alternative scenario in which the source for the January 23, 1812, earthquake is the 

west-trending zone of seismicity that lies along the trend of the RF (S#3 on Figure 6.1.5-4b). In 

this alternative model, both the NN and RF ruptured in the February 7, 1812, earthquake. 

Microearthquake data from the northeastern NMSZ show three alignments that extend from New 

Madrid, Missouri, into western Kentucky and southern Illinois that may represent extensions of 

the NMSZ and therefore alternative locations for the NM2 rupture (Braile et al., 1986; Wheeler, 

1997; Woolery and Street, 2002; Shumway, 2008) (Figure 6.1.5-2). Braile et al. (1997) identified 

two parallel trends of concentrated seismicity approximately 70 and 90 km (43.5 and 56 mi.) 

long that extend north-northeast from the central NMSZ to within 14.4 km (9 mi.) of the 

Illinois/Kentucky border (Wheeler, 1997; Woolery and Street, 2002). Shumway (2008) identifies 

these two parallel trends and a third, shorter alignment (approximately 40 km [25 mi.] long) 

running east-northeast from just south of Charleston, Missouri, to just north of Bardwell, 

Kentucky. 

Mueller et al. (2004) and Hough et al. (2005) infer that the J23 (NM2) main shock may have 

been a remotely triggered earthquake with a location some 200–250 km (124–155 mi.) north of 

the New Madrid earthquake in the Wabash Valley of southern Illinois and Indiana. Bakun and 

Hopper (2004a) discount more northerly locations, based on the absence of 1811-1812 

liquefaction features that would indicate a source in that region. They follow Johnston and 

Schweig (1996) in assigning the NM2 earthquake to the NN segment. Cramer et al. (2006) 

suggest that unilateral rupture within the New Madrid fault zone could have led to extraordinary 

strong ground motions to the east.

The February 7, 1812, earthquake (referred to variously by different authors as the F1, F7, or 

NM3 earthquake) occurred on the RF, which connects the two other fault zones through the 

stepover region (Johnston and Schweig, 1996). The Reelfoot scarp is the surface expression of a 

west-dipping reverse fault that lies within the left-stepping restraining bend between two dextral 

strike-slip arms of the NMSZ (Russ, 1982; Sexton and Jones, 1986; Kelson et al., 1992, 1996; 

Schweig and Ellis, 1994) (Figure 6.1.5-3). The fault and associated fold are defined by 

microearthquakes (Pujol et al., 1997); seismic reflection profiles (Sexton and Jones, 1986; Odum 

et al., 1998; Van Arsdale et al., 1999); surface topography; shallow trench excavations (Russ, 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-39

1982; Kelson et al., 1992, 1996; Mueller et al., 1999); and borehole data (Mihills and Van 

Arsdale, 1999; Champion et al., 2001). Using the constraints on fault geometry derived from 

interpretation of microearthquakes and seismic reflection profiles and the amounts of surface 

deformation based on geomorphic and trenching investigations, the slip rate for the RF is 

estimated (Mueller et al., 1999; Van Arsdale, 2000; Champion et al., 2001) (Appendix Table 

D-6.1.5). Mueller and Pujol (2001) use these constraints on geometry, slip rate, and displacement 

during historical and prehistoric earthquakes to estimate the rate of late Holocene moment 

release and the magnitudes of earthquakes for the two most recent strain cycles. 

Maximum magnitudes in the New Madrid region are based largely on the analysis of intensity 

data from the 1811-1812 earthquake sequence (Johnston, 1996b; Johnston and Schweig, 1996; 

Hough et al., 2000; Mueller et al., 2004; Bakun and Hopper, 2004a; Hough and Page, 2011) and, 

to a lesser degree, on magnitude assessments inferred from paleoliquefaction features (Tuttle, 

Schweig, et al., 2002) (Appendix Table D-6.1.5). Cramer (2001) calculates the range of 

magnitudes (M 6.5–7.8) for fault segments that capture the range of uncertainty in the 

dimensions of the segment rupture (length and width (≤19 km [11.8 mi.]) of the seismogenic 

crust) and choice of magnitude/area relationship (Wells and Coppersmith [1994] or Somerville 

and Saikia [2000] area-magnitude relationships). Mueller and Pujol (2001) provide an additional 

assessment of past earthquake magnitudes through detailed mapping of the geometry and area of 

the RF, combined with estimates of fault slip rate, recurrence, and displacement in individual 

earthquakes to estimate the rate of late Holocene moment release(Appendix Table D-6.1.5). 

Constraints on the recurrence of large-magnitude earthquakes in the NMSZ come from 

paleoliquefaction studies (Saucier, 1991; Tuttle, 1999, 2001; Craven, 1995a; Li et al., 1998; 

Tuttle and Schweig, 1996, 2000, 2001; Tuttle, Lafferty, and Schweig, 1998; Tuttle, Collier, et al., 

1999; Tuttle et al., 2000; Tuttle, Schweig, et al., 2002; and Tuttle and Wolf, 2003; Appendix E) 

and from evaluation of fault-related deformation along the Reelfoot scarp (Kelson et al., 1992, 

1996). The age constraints for these earthquakes are summarized in Table 6.1.5-1. Findings from 

these studies indicate that major earthquakes occurred in the New Madrid region in ~AD 900 

(900–1,200 yr BP relative to AD 1950) and ~AD 1450 (350–650 yr BP relative to AD 1950) 

(Figures 6.1.5-5 and 6.1.5-6; Tuttle and Schweig, 2001; Tuttle, Schweig, et al., 2002). 

Saucier (1991) presents evidence for a significant earthquake in the northern part of the New 

Madrid region in AD 489 (1461 yr BP) ± 50 yr (Appendix E). Tuttle et al. (2005) recognized a 

New Madrid event about 2350 BC ± 200 yr that included several large, closely timed 

earthquakes, but state that the paleoearthquake record may be incomplete before AD 300 and 

that additional research is needed to assess whether the rate of earthquakes during the past 1,200 

years is typical of the longer-term behavior. Tuttle, Schweig, et al. (2002) note that, given 

uncertainties in dating liquefaction events, the recurrence time between the three most recent 

New Madrid earthquakes (AD 900, AD 1450, and 1811-1812) may have been as short as 200 

years or as long as 800, with an average of 500 years. Tuttle (2001) notes that similarities in the 

size and spatial distributions of historical (1811-1812) and paleoliquefaction features indicate 

that the NMSZ was the likely source of the two paleoearthquakes that are recognized regionally. 

Saucier (1989) first recognized compound sand blows that formed during the 1811-1812 

earthquake sequence. Tuttle, Schweig, et al. (2002) document evidence that prehistoric sand 

blows, like those formed during the 1811-1812 earthquakes, probably are compound structures 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-40

resulting from multiple earthquakes closely clustered in time (i.e., earthquake sequences). The 

current preferred age estimates of earthquakes from 2-sigma radiocarbon maximum and 

minimum age constraints and, in some instances, archeological data as outlined in Appendix E 

are given in Table 6.1.5-1. 

6.1.5.1 Evidence for Temporal Clustering 

The first node of the logic tree (Figure 6.1.5-1) addresses the issue of temporal clustering of 

earthquakes in the present tectonic stress regime (see Section 5.1.2). 

Various observations suggest that the high rate of seismicity within the NMSZ in the Holocene is 

not characteristic of the region over longer-term periods. Schweig and Ellis (1994) note that 

extensive seismic reflection data in the New Madrid seismic zone show relatively small 

cumulative fault offsets in the post-Cretaceous Mississippi embayment sediments (e.g., Hamilton 

and Zoback, 1982). Van Arsdale (2000) concluded based on seismic reflection and trench data 

that slip rates on the RF during the Holocene are at least four orders of magnitude higher than 

during the Pleistocene. 

Other geomorphic observations also suggest that the NMSZ became more active within the past 

few thousand years and that this activity is part of the most recent cluster of large earthquakes. 

Longer-term geomorphic records suggest that periods of clustered activity within the NMSZ are 

interspersed with longer intervals of inactivity (Holbrook et al., 2006). The concept that the locus 

of seismicity and active faulting may shift or migrate within the Reelfoot rift region was 

suggested by McBride, Nelson, and Stephenson (2002) to explain the changes in rates of activity 

for faults of the Fluorspar Area fault complex within the northern Reelfoot rift, and more 

recently by others to explain the apparent discrepancies between long-term deformation rates on 

faults within the NMSZ (McKenna et al., 2007) and the evidence for possible temporally 

clustered earthquakes in the southern part of the rift near Marianna, Arkansas (Tuttle, 2009). 

Geodetic data suggest that present strain accumulation across the NMSZ is near zero (Calais et 

al., 2005; Smalley et al. 2005) and that strain has accumulated too slowly to account for the 

paleoseismicity recorded over the past approximately 5,000 years, thereby ruling out steady-state 

fault behavior (Newman et al., 1999; Calais and Stein, 2009; Calais et al., 2009; Li et al., 2007, 

2009; McKenna et al., 2007). 

Alternative interpretations of geodetic strain in the region of the NMSZ have been reported in the 

literature. Using analysis of geodetic measurements from a permanent GPS array in midAmerica that was installed in the mid- to late 1990s, Smalley et al. (2005) suggest relatively 

rapid rates of strain of the order of 10–7

per year, comparable in magnitude to those across active 

plate boundaries, and consistent with known active faults in the region. Relative convergence 

across the RF estimated from this study is ~2.7 ± 1.6 mm/year. Relative fault-parallel, rightlateral motion of ~1 mm/year was measured across the southern right-lateral strike-slip fault 

zone, which is highlighted by a prominent northeast-trending and vertical zone of 

microseismicity and right-lateral focal mechanisms. Surface velocities at distances beyond a few 

fault dimensions (far-field) from active faults, however, do not differ significantly from zero. 

According to Smalley et al. (2005), it is not certain whether the driving force behind the current 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-41

surface velocities is related to post-1811-1812 seismic processes or to the accumulation of a 

locally sourced strain. Others speculate that the recent small earthquakes in the NMSZ are 

aftershocks of the large earthquakes of 1811-1812 (Ebel et al., 2000; Stein and Newman, 2004; 

McKenna et al., 2007). The geodetic data indicate, however, that aseismic slip is almost certainly 

required across faults (or shear zones) within the upper few kilometers of the surface (Smalley et 

al., 2005). 

More recent interpretation of geodetic results in the NMSZ shows motions between 0 and 1.4 

mm/yr, and two opposing interpretations of these data are suggested (Calais and Stein, 2009). As 

outlined by Calais and Stein, the upper bound is consistent with steady-state behavior, in which 

strain accumulates at a rate consistent with a repeat time for M ~ 7 earthquakes of about 600–

1,500 years, as seen in the earthquake record. The lower bound cannot be reconciled with this 

record, which implies that the recent cluster of large-magnitude earthquakes does not reflect 

long-term fault behavior and may be ending. New analysis suggests strain rates lower than 

1.3 × 10–9/yr, less than predicted by a model in which large earthquakes occur because the 

NMSZ continues to be loaded as a deeper weak zone relaxes (e.g., Kenner and Segall, 2000). At 

a steady state, a rate of 0.2 mm/yr implies a minimum repeat time of 10 kyr for low M = 7 

earthquakes having approximately 2 m (6.5 ft.) of coseismic slip and a repeat time of longer than 

100 kyr for M = 8 earthquakes. 

In summary, geodetic and geologic observations suggest that both temporal clustering and spatial 

migration of seismicity occurs within the Reelfoot rift, and various researchers have argued that 

the NMSZ faults are not presently accumulating strain at a rate consistent with that recorded by 

the late Holocene paleoliquefaction record and that they may be entering a less active period 

(e.g., Calais and Stein, 2009; McKenna et al., 2007). A recent review by the Independent Expert 

Panel on New Madrid Seismic Zone Earthquake Hazards of the current national seismic hazard 

maps in the region of the NMSZ considered claims that the apparent lack of current deformation 

may indicate that the process driving NMSZ earthquakes has ceased, but members of the panel 

and other experts consider such claims unlikely (NMSZ Expert Panel, 2011). This possibility is 

acknowledged but is given relatively low weight in the source model for several reasons: the 

relatively short geodetic record, uncertainties in the potential variability in strain accumulation 

over such short periods, and gaps in the state of knowledge regarding the relationship between 

the crustal motion measured by space geodesy and the elastic strain that is released by 

earthquakes. The NMSZ Expert Panel (2011) notes that the integration of GPS data in NMSZ 

seismic hazard analysis is limited by two main factors: (1) limitations of the existing GPS data 

and (2) lack of physical understanding of how stress accumulation on faults is related to surface 

deformation in intracontinential regions. Three options are considered in the CEUS SSC source 

characterization (Figure 6.1.5-1): 

The recent behavior of all three of the faults in the NMFS as inferred from paleoliquefaction 

studies (in a period of clustered earthquakes) is interpreted to be representative of the rate of 

future earthquakes (i.e., the recent period of activity for the three faults will continue into the 

future at the same rate; weight of 0.9). 

The NMSZ is shutting down as suggested by geodetic observations that show little or none of 

the interseismic motion expected before a future large earthquake (i.e., out of a period of 

clustered earthquakes; Newman et al., 1999; Calais et al., 2005). In this case, the hazard is 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-42

modeled by the underlying seismotectonic zone (Reelfoot rift zone) on the seismotectonic 

branch of the master logic tree or by global spatial smoothing of seismicity on the Mmax 

branch of the logic tree (weight of 0.05). 

Only the Reelfoot thrust (RFT) fault, which shows geomorphic evidence of an earlier phase 

of activity inferred from fluvial geomorphology (Holbrook et al., 2006), is considered to be 

in an active phase. In this case, the RFT is currently producing RLMEs at a lower rate 

(weight of 0.05). 

6.1.5.2 Geometry and Style of Faulting 

Fault sources included in the characterization of the NMFS RLME source are (1) the New 

Madrid South (NMS) fault; (2) the New Madrid North (NMN) fault; and (3) the RFT (Figure 

6.1.5-4c). The first two levels of the logic tree (Figure 6.1.5-1) for these sources address the 

uncertainty in the technical community regarding the location and extent of the causative faults 

that ruptured during the 1811-1812 earthquake sequence. This uncertainty is represented by 

alternative geometries for the NMS, NMN, and RFT faults. The locations of the faults that make 

up the New Madrid characteristic earthquake sources are shown on Figures 6.1-2b, 6.1.5-3, and 

6.1.5-4. 

For the NMS fault source, two alternatives are considered, as described by Johnston and Schweig 

(1996): (1) the BA-BL (Blytheville arch-Bootheel lineament), and (2) the BA-BFZ (Blytheville 

arch-Blytheville fault zone). Although modern seismicity is occurring primarily along the BFZ, 

Johnston and Schweig (1996) present arguments suggesting that the BA-BL is the most likely 

location for the main NM1(D1) earthquake and that major NM1(D1) aftershocks occurred on the 

BFZ (the northeast extension of the Cottonwood Grove fault). Recent studies by Guccione et al. 

(2005) document that the presence of recent surface deformation and an offset Holocene channel 

across the BL (Bootheel fault). Therefore, slightly greater weight is given to BA/BL (weight of 

0.6) (total length of 133 km [82.5 mi.]) than to BA-BFZ (weight of 0.4) (total length of 115 km 

[72 mi.]). 

Two alternative total lengths are considered for the NMN fault source: NMN-S and NMN-L. The 

first, which is given the highest weight (0.7), allows for rupture of the 56.4 km (35 mi.) fault 

segment (NN; Figure 6.1.5-4) as defined by Johnston and Schweig (1996). Cramer (2001) uses a 

similar value (59 km [36.7 mi.]) as the length of this fault source. The alternative, NMN-L, 

which has a total length of 95 km (59 mi.), allows for the fault to extend north, including the 

westernmost of two trends of northeast-aligned seismicity noted by Wheeler (1997) and 

Shumway (2008; Figure 6.1.5-2). McBride et al. (2003) observe evidence in seismic profiles for 

reactivation of northeast-trending structures near Olmstead, Illinois, along the trend of the 

westernmost seismicity alignment. They conclude that the graben structure in this area has been 

reactivated as a fault-propagation fold that apparently affects Holocene sediments near the 

ground surface. Wheeler et al. (1997) and other researchers argue for a structural northern 

boundary to the rift in this region (see Appendix Table D-6.1.5). The northern extension 

(NMN-L; Figure 6.1.5-4c) is not as well defined by seismicity as the NMN-S segment is. Also, 

the recurrence interval of large-magnitude earthquakes in the northern Mississippi embayment 

appears significantly longer than the recurrence interval for NMSZ earthquakes based on 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-43

paleoliquefaction studies. Given these observations, the longer (97 km [60.3 mi.]) fault length 

(NMN-L) is given less weight (0.3) than the shorter (60 km [37.3 mi.]) fault length (NMN-S). 

Johnston and Schweig (1996) conclude from historical accounts that the NM3 (F1) earthquake 

occurred on the RF, and they identify three possible segments of the fault: a central 32 km (19.9 

mi.) long reverse fault defined by the RF scarp between the two northeast-trending strike-slip 

faults; a 35 km (21.7 mi.) long segment, Reelfoot South (RS), that extends to the southeast; and a 

40 km (24 mi.) long segment west of the New Madrid North fault (Figure 6.1.5-4a). Seismicity 

and geomorphic data indicate that the southeast segment is slightly shorter (25–28 km [15.5–17.4 

mi.]) than indicated by Johnston and Schweig (Van Arsdale et al., 1999; Mueller and Pujol, 

2001). Cramer (2001) uses a total length of 60 km (37.3 mi.) for the RF. The alternative fault 

rupture scenarios of Johnston and Schweig (1996) include rupture of a 40 km (24 mi.) long 

northwest fault segment (Figure 6.1.5-4b). 

Cramer (2001) assigns a length of 33 km (20.5 mi.) to this segment, which he refers to as the 

west arm. Mueller and Pujol (2001) note that this westerly arm is imaged as a vertical fault that 

terminates the RFT. They interpret the westerly arm as a left-lateral strike-slip fault 

kinematically linked to the RFT. Bakun and Hopper (2004) suggest a preferred epicenter location 

at the northern end of the RS segment. Hough and Martin (2002) show a slightly different 

geometry for the northwestern portion of the fault and do not interpret the historical 1811-1812 

earthquake ruptures to have extended to the rift margin on the southeast. Van Arsdale et al. 

(1999) and Mueller and Pujol (2001) argue that the RF is continuous from New Madrid southeast 

to near Dyersburg, Tennessee. Alternatively, Csontos and Van Arsdale (2008) conclude that two 

segments of the fault, which they refer to as the Reelfoot North and Reelfoot South faults, are 

discrete segments that may not rupture as one fault. These two faults differ in strike, dip, depth, 

area, and basement displacement; further, the Reelfoot South fault does not have a surface scarp. 

Csontos and Van Arsdale (2008) note that the Reelfoot North fault is symmetric from its 

maximum fold amplitude of 11 m (36 ft.) northwest of Reelfoot Lake (Champion et al., 2001). 

They believe that the fold amplitude (scarp height) diminishes to near zero at the eastern edge of 

the Mississippi River floodplain, and that this is not consistent with what would be expected if 

the RF had ruptured over its entire 70 km (43.5 mi.) of mapped bedrock length as one plane 

during its Holocene history. 

Two alternative fault geometries are included in this study: (1) the RFT-S fault that is based on 

the observed length of concentrated seismicity that is consistent with a reverse fault geometry 

(i.e., Chiu et al. 1992; Mueller and Pujol, 2001; Hough and Martin, 2002; Csontos and Van 

Arsdale, 2008); and (2) a longer fault (RFT-L) that allows for extensions to the northwest (the 

northwest segment of Johnston and Schweig [1996] and Cramer [2001]) and to the southeast to 

the margin of the Reelfoot rift. The shorter length (46.2 km [28.6 mi.]), which has geomorphic 

and seismologic evidence for reverse slip is given higher weight (0.7) than the alternative, longer 

fault (RFT-L; 82.8 km [51.3 mi.]) (weight of 0.3), which also includes the western fault segment 

that shows evidence for strike-slip movement. 

Recent analysis and relocation of 19 earthquakes (M ≤ 3.6) in the northeastern part of the 

NMSZ, using a velocity model of the Mississippi embayment with appropriate depths to bedrock 

beneath seismic stations, shows that only 2 of the earthquakes occurred at depths between 13 and 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-44

15 km (8.1 and 9.3 mi.; Shumway, 2008). Herrmann and Ammon (1997) show depths of up to 16 

km (10 mi.) for earthquakes in the Reelfoot rift. Based on these data, the following distribution 

for seismogenic crustal thickness is used to characterize the New Madrid fault system RLME 

sources: 13 km (8.1 mi.; weight of 0.3), 15 km (9.3 mi.; weight of 0.5), and 17 km (10.6 mi.; 

weight of 0.2). 

The style of faulting for each of the fault sources is based on geologic and seismologic 

observations. The NMS fault is modeled as an oblique right-lateral strike-slip fault based on the 

following: focal mechanisms (Herrmann and Canas, 1978; Chiu et al., 1992); geologic evidence 

for a right-laterally offset Holocene channel along the Bootheel fault (Guccione et al., 2005); and 

the near-surface expression of flower structures associated with strike-slip and oblique 

movement of deeper, reactivated boundary faults as interpreted from seismic profile data (Odum 

et al., 1995). The RFT fault is modeled as a reverse fault dipping an average of 40 degrees 

southwest (the average being measured from near the surface to seismogenic depth) (Herrmann 

and Canas, 1978; Chiu et al., 1992, Mueller and Pujol, 2001; Van Arsdale, 2009). It is noted that 

the western end of the RFT-L may be steeper and more strike-slip, but for this regional 

assessment that has not been explicitly modeled. The NMN fault is modeled as a right-lateral 

strike-slip fault based on focal mechanisms (Shumway, 2008) and apparent right-lateral 

deflections of drainages and geophysical anomalies (Baldwin et al., 2002). 

6.1.5.3 RLME Magnitude 

Seismic source characterizations of the New Madrid seismic source zone typically consider the 

1811-1812 earthquakes to represent the maximum earthquake for this source. Table 6.1.5-2 

summarizes recent estimates of the magnitude of the New Madrid 1811-1812 main shocks. 

Bakun and Hopper (2004b) provide preferred estimates of the locations and moment magnitudes 

and their uncertainties for the three largest earthquakes in the 1811-1812 sequence near New 

Madrid. Their preferred intensity magnitude MI, which is their preferred estimate of M, is 7.6 

(6.8–7.9 at the 95 percent confidence interval) for the December 16, 1811, earthquake (NM1); 

7.5 (6.8–7.8 at the 95 percent confidence interval) for the January 23, 1812, earthquake (NM2); 

and 7.8 (7.0–8.1 at the 95 percent confidence interval) for the February 7, 1812, earthquake 

(NM3). The intensity magnitude MI is the mean of the intensity magnitudes estimated from 

individual MMI assignments. In their analysis, Bakun and Hopper (2004b) consider two 

alternative eastern North America (ENA) intensity attenuation models, which they refer to as 

models 1 and 3. As indicated in Table 6.1.5-2, these two models give significantly different 

results for larger-magnitude earthquakes. Bakun and Hopper state that because these models are 

empirical relations based almost exclusively on M < 6 calibration earthquakes, ―there is no way 

to confidently predict which relation better represents the MMI distance data for M 7 

earthquakes in ENA‖ (Bakun and Hopper, 2004b, p. 66). They present arguments supporting 

their preference for model 3, but do not discount the results based on model 1. 

Dr. Susan Hough (written comm., August 23, 2004) concluded that there are insufficient data 

regarding the calibration of ENA earthquakes larger than M > 7 to rely strictly on ENA models 

as was done in Bakun and Hopper (2004b). She offered arguments to support M 7.6 (her 

preferred estimate of the size of the 2003 Bhuj earthquake) as a reasonable upper bound for the 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-45

largest of the earthquakes in the 1811-1812 New Madrid earthquake sequence, which is

consistent with the estimates cited by Hough et al. (2000) and Mueller et al. (2004). 

More recently, Hough has conducted new analyses and has revisited the intensity assignments, 

developing a set of ―consensus intensities‖ for the four largest earthquakes in the New Madrid 

earthquake sequence (the three main shocks and a fourth large aftershock) based on independent 

assignments from four experts with experience in analysis of historical earthquakes: Duncan 

Agnew, Paola Albini, Kenneth Burke, and Stacey Martin (Hough and Page, 2011). The 

consensus intensity values are systematically (almost universally) lower than those estimated by 

Hough et al. (2000). Using the method developed by Bakun and Wentworth (1997) and two 

CEUS attenuation relations developed by Bakun et al. (2003) and Bakun and Hopper (2004), 

Hough and Page (2011) estimate magnitudes using the consensus values as well as the 

independent assignments by the four experts. The magnitude values are lower than those 

estimated by Hough et al. (2000). 

Tuttle, Hengesh, et al. (2002) discuss the Mw 7.7 Bhuj earthquake in the Kachchh region of India 

as a potential analog for the New Madrid earthquakes based on similarities in the tectonic and 

geologic settings between the two regions as well as on the extent and scale of paleoliquefaction 

that occurred in the Bhuj earthquake relative to the paleoliquefaction features in the NMSZ 

region. Tuttle, Hengesh, et al. (2002) note that if the Ambraseys (1988) relationship between 

magnitude and distance to the farthest liquefaction formed during an earthquake reflects 

intraplate earthquakes, then the Bhuj earthquake, which has a slightly shorter maximum distance 

to liquefaction than the NMSZ earthquakes, supports an estimate of Mw ≥ 7.6 for the size of the 

1811-1812 earthquakes. 

Mueller et al. (2004) use instrumentally recorded locations of recent earthquakes (assumed by 

Mueller et al. to be aftershocks of the 1811-1812 sequence) and models of elastic stress change 

to develop a kinematically consistent rupture scenario for the main-shock earthquakes of the 

1811-1812 New Madrid sequence. In general, the estimated magnitudes for NM1 and NM3 used 

in their analysis (M = 7.3 and M = 7.5, respectively) are consistent with those previously 

published by Hough et al. (2000). Mueller et al.’s results (2004) suggest that the NM1 and NM3 

main shocks occurred on two contiguous faults: the strike-slip Cottonwood Grove fault and the 

RFT, respectively. The locations of the NM1 and NM3 earthquakes on the Cottonwood Grove 

and RFT, respectively, are relatively well constrained. In contrast to the earlier Hough et al. 

study (2000) that located the NM2 earthquake on the NN, Mueller et al. (2004) suggest a more 

northerly location for the NM2 earthquake, possibly as much as 200 km (124.3 mi.) to the north 

in the Wabash Valley of southern Indiana and Illinois. Hough et al. (2005) also infer a similar 

more northerly location. 

Using Bakun and Wentworth’s method (1997), Mueller et al. (2004) obtain an optimal location 

for the NM2 main shock at 88.43°W, 36.95°N and a magnitude of M 6.8. They note that the 

location is not well constrained and could be fit almost as well by locations up to 100 km (62 

mi.) northwest or northeast of the optimal location. Mueller et al. (2004) conclude that the three 

earthquakes on the contiguous faults increased stress near fault intersections and end points, in 

areas where present-day microearthquakes have been interpreted as evidence of primary mainshock rupture. They suggest that their interpretation is consistent with established 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-46

magnitude/fault area results, and does not require exceptionally large fault areas or stress drop 

values for the New Madrid main shocks. 

With respect to the location of the NM2 earthquake, Bakun and Hopper (2004b) also discuss the 

paucity of MMI assignments available for this earthquake to the west of the NMSZ and the 

resulting uncertainty in its location. They note that the two MMI sites closest to the NMSZ 

provide nearly all of the control on the location of this earthquake and that, based on these two 

sites, a location northeast of their preferred site is indicated. They indicate, however, that the lack 

of 1811-1812 liquefaction observations in western Kentucky, southern Illinois, and southern 

Indiana precludes an NM2 location in those areas. Bakun and Hopper (2004b) follow Johnston 

and Schweig (1996) in selecting a preferred location on the NMN fault. Dr. Steve Obermeier 

confirmed that liquefaction features in the Wabash Valley region that would support the more 

northerly location preferred by Mueller et al. (2004) are absent (S. Obermeier, pers. comm., 

August 24, 2004). He noted that he had looked specifically in the area mentioned in the Yearby 

Land account that was cited by Mueller et al. (2004) and observed evidence for only small sand 

blows and dune sands, but did not see features of the size and origin described in that account. 

Dr. Arch Johnston (written comm., August 31, 2004) indicated that the earlier estimates of 

Johnston (1996b) are likely to be high by about 0.2–0.3 magnitude units. More recently, 

Johnston expressed concerns regarding the estimation of magnitude for the 1811-1812 

earthquakes from intensity data and indicated that he is working on developing revised estimates 

based on the assumption that the seismicity represents aftershocks from the 1811-1812 

earthquakes (pers. comm., February 16, 2010). This analysis is not yet complete. 

A review of published estimates (e.g., Bakun and Hopper, 2004b; Mueller et al., 2004; Hough 

and Page, 2011) indicates that uncertainty and differing views remain within the research 

community regarding the size and location of the 1811-1812 earthquakes. Based on review of the 

publications described in the preceding paragraphs and on communications with Drs. Bakun, 

Hough, and Johnston, the maximum magnitude for the NMFS faults (NMN, NMS, and RFT 

faults) is assessed as follows. 

Equal weight (one-third) is given to estimates based on Bakun and Hopper (2004b), Hough 

and Page (2011), and the Johnston revisions (written comm., August 31, 2004) to Johnston 

(1996b). 

Results from both intensity attenuation relations (models 1 and 3) in the Bakun and Hopper 

estimate (2004b) are used. Based on Bakun and Hopper’s preference for model 3, weights of 

0.75 and 0.25 are assigned to model 3 and model 1, respectively. 

In the case of the Hough and Page estimates (2011), which also use the Bakun and Hopper 

(2004b) attenuation models, similar weights of 0.75 and 0.25, are assigned to values based on 

model 3 and model 1, respectively. 

The resulting RLME magnitude distribution for each of the three faults is given in the table 

below. Rupture sets 1 and 2 correspond to the revised Johnston estimates (1996b); rupture sets 3 

and 4 correspond to the Bakun and Hopper estimates (2004b); and rupture sets 5 and 6 

correspond to the Hough and Page estimates (2011).
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-47

As discussed in the following section, the present interpretation of the paleoearthquake data is 

that the two prehistoric earthquake ruptures that occurred before the 1811-1812 sequence also 

consisted of multiple large-magnitude earthquakes. Therefore, for this assessment, the modeled 

earthquake scenario includes rupture of multiple (two to three) fault sources. Furthermore, the 

arguments for the high- versus low-magnitude assessments for the individual faults are 

considered to be highly correlated. Therefore, six alternative sets of ruptures were produced from 

the distributions developed previously for each fault, as shown in the logic tree on Figure 6.1.5-1 

and tabulated below. 

Rupture Set

Expected NMFS RLME Magnitude for:

NMS RFT NMN Weight

1 7.9 7.8 7.6 0.167

2 7.8 7.7 7.5 0.167

3 7.6 7.8 7.5 0.25

4 7.2 7.4 7.2 0.083

5 6.9 7.3 7.0 0.25

6 6.7 7.1 6.8 0.083

The magnitudes tabulated above represent the uncertainty distribution for the expected 

magnitude for the RLME for each fault within the NMFS. The size of the next RLME is assumed 

to vary randomly about the expected value following a uniform distribution over the range of 

0.25 magnitude units (Section 5.3.3.4). 

6.1.5.4 RLME Recurrence 

The remaining nodes of the NMFS RLME source logic tree address the assessment of earthquake 

recurrence rates. 

Recurrence Method 

The data available for assessing the recurrence rate of the NMFS RLMEs provide assessments of 

the timing of past earthquakes. Thus the ―Earthquake Recurrence Intervals‖ approach is used 

with weight 1.0 (Figure 6.1.5-1). 

Recurrence Data 

The best constraints on recurrence of NMFS RLME sources derive from paleoliquefaction 

studies throughout the New Madrid region and from paleoseismic investigations of the RF scarp 

and associated fold. Using studies of hundreds of earthquake-induced paleoliquefaction features 

at more than 250 sites, Tuttle, Schweig, et al. (2002, 2005) concluded that (1) the fault system 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-48

responsible for the New Madrid seismicity generated sequences of two to three very large 

earthquakes in ~2350 BC, ~AD 900, ~AD 1450, as well as in 1811 and 1812; (2) given 

uncertainties in dating liquefaction features, the time between the past three earthquakes may be 

as short as 200 years or as long as 800 years, with an average of 500 years; (3) the 

paleoliquefaction record between 2350 BC and AD 900 is probably incomplete; and (4) some of 

the prehistoric sand blows are compound structures, resulting from multiple earthquakes (i.e., 

earthquake sequences) occurring closely spaced in time.

Out-of-cluster recurrence rates for the NMFS are based on dates presented in Holbrook et al. 

(2006). Holbrook et al. (2006) present a reconstruction of Holocene Mississippi River channels 

from maps of floodplain strata to identify channel perturbations reflective of major 

displacements on the RFT. This evaluation, in combination with the paleoliquefaction 

chronology developed by Tuttle et al. (2002, 2005), provides evidence of temporal clustering of 

earthquakes in a compressive Midcontinent intraplate on short-term cycles (months), as well as 

evidence for longer-term reactivation cycles (104–106). The study makes a case for a ~1,000-year 

cluster of earthquakes with 102 year spacing on the RF, beginning with a coseismic slip event 

near the end of the middle Holocene at ~2200 to ~1600 BC. This Holocene cluster appears 

separated from the modern episode of seismicity (beginning ~AD 900) by at least 1,700 years of 

tectonic quiescence. 

Earthquake Recurrence Model 

The Poisson and renewal recurrence models are given weights of 0.75 and 0.25, respectively 

(Figure 6.1.5-1). As discussed in Section 5.1.2, the renewal model is considered more 

appropriate on a physical basis if a fault is responding to quasi-steady-state loading, producing 

more periodic occurrences of large earthquakes. This would suggest that a weight of 0.5 or larger 

be applied to the renewal model. However, it is not clear that such a physical process applies to 

the NMFS, even though there is evidence for periodic occurrence of large earthquakes. 

Therefore, the weight assigned to the renewal model is reduced to 0.25. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs (Figure 6.1.5-1). These distributions were developed using the methodology 

described in Sections 5.3.3.1 and 5.3.3.2. For the Poisson model, the relative likelihood of 

various values of the recurrence rate parameter was developed using Equation 5.3.3-4 and the 

observations of the time intervals between the selected paleoearthquakes and the open interval 

post the 1812 earthquakes. For the renewal model, the relative likelihoods of various values of 

the mean recurrence interval for RLMEs were developed using Equations 5.3.3-7, 5.3.3-8, and 

5.3.3-9 for each set of past RLMEs and specified value of coefficient of variation. The resulting 

parameters were then used to compute the equivalent annual frequency of RLMEs using 

Equations 5.3.3-10 and 5.3.3-11.

The data used for the recurrence rate calculations are the time intervals between individual 

RLMEs for the renewal model case and the age of the oldest RLME for the Poisson case. These 

are calculated from the age estimates for each past RLME. With the exception of the 1811-1812 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-49

earthquakes, these ages are estimated from two types of data, as described above. Uncertainty 

distributions for the ages of the two previous RLME sequences were developed from age dating 

of liquefaction features. Tables 6.1.5-3 and 6.1.5-4 list liquefaction features associated with the 

AD 900 and 1450 RLMEs, respectively (see the CEUS SSC Project paleoliquefaction database, 

Appendix E). The second and third columns list the minimum and maximum ages for these 

features defined as time before January 1, 2011. The ages were chosen based on the age range 

for the liquefaction features. The remaining columns of each table list possible ages for the two 

RLME sequences. The cells in each row contain an ―X‖ when the age range for the liquefaction 

feature is in conflict with the RLME age at the top of the column. For example, the second 

feature in Table 6.1.5-3, ―MarkedT01-01,‖ has an age range of 511–591 years before January 1, 

2011. Those columns of the table with RLME ages outside of this range are marked with an ―X.‖ 

The first feature, ―Tyr01-01‖ has an age range of 211–711 years, which allows all of the possible 

ages listed in the column headings. Thus, no cells are marked with an ―X‖ for this feature.

The last row of Tables 6.1.5-3 and 6.1-5-4 lists the number of liquefaction features whose age 

estimates are inconsistent with the specified RLME ages. As indicated, there are no RLME ages 

that do not conflict with at least one liquefaction feature age range. However, there are possible 

RLME ages where the number of liquefaction feature age conflicts is small compared to the total 

number of features. For example, age estimates for the AD 1450 RLME in the range of 511–590 

years are in conflict with the ages for 2–4 liquefaction features, while age estimates outside this 

range are in confict with 6–8 features. Similarly, age estimates for the AD 900 RLME in the 

range of 1,011–1,211 years are in conflict with the ages for 1–4 liquefaction features, while age 

estimates outside this range are in conflict with the ages for 7 or more liquefaction features. 

The data listed in Tables 6.1.5-3 and 6.1.5-4 were used to construct distributions for the age of 

the two RLMEs. The limits of possible ages were defined based on the age limits that are 

inconsistent with the ages of four or fewer liquefaction features. This age range was chosen 

because the number of feature age inconsistencies grows quickly outside this range. A 

trapezoidal probability density function was constructed using these age limits and assigning 

equal probability to ages that were in conflict with the ages of fewer features. The assigned 

probability density functions and the resulting cumulative distribution functions for RLME age 

are shown on Figure 6.1.5-7. 

The uncertainty distributions for in-cluster RLME annual frequency were then computed by 

repeatedly simulating samples of RLME dates from the age distributions shown on Figure 

6.1.5-7 and computing a relative likelihood distribution for RLME rate from each sample. The 

resulting distributions were then combined to produce a composite distribution for RLME rate. 

These composite distributions were then represented by five-point discrete approximations. The 

resulting distributions for RLME recurrence frequency are listed in Tables 6.1.2-5 and 6.1.2-6 

for the Poisson and Renewal models, respectively. 

The out-of-cluster RLME rate for the NMFS was estimated from the data presented in Holbrook 

et al. (2006), who indicate initiation of NMFS clusters of large earthquakes 1,000 years ago (the 

start of the current cluster) and 4,000 years ago (the start of the previous cluster). These data 

correspond to one closed interval and one open interval. Using the likelihood formulation of 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-50

Equation 5.3.3.4, the distribution for out-of-cluster RLME frequency listed in Table 6.1.5-7 was 

developed. 

The paleoliquefaction data gathered in the New Madrid region indicates that the prehistoric 

earthquakes have occurred in sequences closely spaced in time that are similar to the 1811-1812 

sequence. Figure 6.1.5-8 shows the estimated earthquake sizes and locations for the 1811-1812 

sequence (from Johnston and Schweig, 1996) and the two previous sequences. These data 

indicate that the RF has ruptured in all three sequences, but the NMN and NMS sources may not 

have produced large earthquakes in all three sequences. The available data allow for the 

possibility that the third earthquakes on the NMN and NMS sources may have been dependent 

earthquakes, on the order of a unit magnitude smaller than the main earthquakes. However, it is 

also possible that the paleoliquefaction record is not completely known for these earthquakes and 

they may have been comparable in size to the larger historical earthquakes. These observations 

were used to construct two alternative scenarios for the relative frequency of earthquake 

sequences on the central New Madrid fault sources, one in which all three components produce 

large earthquakes in each RLME sequence and one in which the NN component ruptures in two 

out of three RLME sequences. During preliminary model development, it was found that these 

two alternatives produced minimal difference in computed hazard. Therefore, the recurrence 

model presented here only includes the alternative of all three components. 

6.1.6 Reelfoot Rift—Eastern Rift Margin Fault 

Several studies have concluded that the eastern Reelfoot rift margin is a fault zone characterized 

by recurrent movement in the Quaternary, with the most recent earthquake at some localities 

occurring within the Holocene (e.g., Crone, 1992; Luzietti et al., 1992; Crone and Schweig, 

1994; Cox et al., 2006). Based on the results of these studies and preliminary results of seismic 

surveys along the Mississippi River that show evidence for near-surface faulting (Dr. B. 

Magnani, Center for Earthquake Research and Information, U. of Memphis, pers. comm., May 

29, 2009), two independent sources of RLMEs, referred to as the Eastern Rift Margin South 

(ERM-S) and North (ERM-N) RLME sources, are included in the seismic source model. 

Uncertainties in the location, rate, and size of earthquakes that may occur on these two RLME 

sources are outlined in logic trees (Figures 6.1.6-1a and 6.1.6-1b). Locations of tectonic features 

and key localities where detailed geophysical surveys and subsurface explorations have been 

conducted to evaluate the location and activity of faults and paleoliquefaction features along the 

eastern margin of the Reelfoot rift zone are shown on Figure 6.1.6-2 and discussed below. 

Additional information used to identify and characterize RLME sources along the eastern margin 

of the Reelfoot rift zone is summarized in Appendix Tables C-6.1.6 and D-6.1.5. 

The Crittenden County fault zone (CCFZ), located in northeastern Arkansas about 25 km (15.5 

mi.) northwest of Memphis, Tennessee, is a northeast-trending zone of high-angle (up-to-thenorthwest throw) reverse faulting that extends at least 32 km (20 mi.; Crone, 1992). The CCFZ, 

which has no known surface expression, was one of the first structures along the southeastern 

Reelfoot rift margin to be identified from interpretation of seismic profiles as a potential source 

of damaging earthquakes (Crone, 1992; Luzietti et al., 1992; Williams et al., 1995). The CCFZ 

roughly coincides with the southeastern margin of the northeast-trending Reelfoot rift (Figure 

6.1.6-2). Based on this coincidence, Crone (1992) suggests that preexisting, west-dipping normal 
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faults within the rift may have been reactivated as reverse faults with up-to-the-west movement 

during the Late Miocene and Tertiary. 

A history of recurrent fault movement from the Mesozoic into the Quaternary is interpreted by 

Williams et al. (1995) using seismic data (Vibroseis, Mini-Sosie, shotgun, and weight drop) and 

drillhole data. High-resolution seismic-reflection and refraction data show deformed and faulted 

beds of Pleistocene (and possibly Holocene) age above the deeper, well-imaged CCFZ in Eocene 

and older strata. The possible association of these shallow deformation features with the CCFZ 

suggests that recurrent movement may have occurred on the fault zone in the Quaternary 

(Williams et al., 1995). However, the lack of a clear connection between the near-surface faults 

that disrupt the Quaternary section and the main flexure and faults at depth leads to some 

uncertainty in the interpretation of the shallow faults. The sense of vertical offset in Quaternary 

deposits is opposite to the net structural relief in the underlying rift and on the deeper structure. 

Reflections from the Quaternary-Eocene unconformity show warping, dip, or interruptions in 

places over the CCFZ that suggest a length of at least 16 km (10 mi.) of near-surface 

deformation; this deformation may represent Quaternary or Holocene movement (Luzietti et al., 

1992). 

Williams et al. (1995) interpret one seismic profile to show that the unconformity between 

Eocene and overlying Quaternary deposits (referred to as the QE unconformity) has 5 m (16.5 

ft.) of relief and is faulted approximately 2 m (6.5 ft.), both down to the west across one trace of 

the CCFZ. A second profile shows a fault with approximately 1 m (3.3 ft.) of down-to-the-east 

throw. The deformation extends into the overlying deposits, and a Holocene reflector is 

deformed by a rootless, second-order structure that is interpreted to be a bending-moment fault 

formed in response to the monoclinal bulge caused by the subjacent main reverse fault or an 

oblique-slip component in a strike-slip regime (Williams et al., 1995). Mihills and Van Arsdale 

(1999) also suggest that Holocene uplift may be associated with the CCFZ. 

Chiu et al. (1997) report a distinct seismicity lineation that appears to be associated with the 

southeastern Reelfoot rift margin approximately 25 km (15.5 mi.) to the northeast of the CCFZ. 

They noted that focal mechanisms suggest that minor faulting on this margin is characterized by 

right-lateral strike-slip with high-angle thrust faulting. The faulting is generally consistent with 

an east-west-oriented, maximal, horizontal, compressional stress, similar to the regional stress 

regime. Based on analysis of intensity data, Hough and Martin (2002) conclude that a large 

aftershock of the December 11, 1811, New Madrid earthquake (M 6.1 ± 0.2) occurred within the 

southwestern one-third to one-half of this band of seismicity. 

Paleoseismic and geomorphic investigations along the eastern margin of the Reelfoot rift from 

Meeman-Shelby Forest State Park (approximately 25 km [15.5 mi.] north of Memphis) to the 

Tennessee-Kentucky border are presented by Cox and others (Cox, Van Arsdale, and Harris, 

2001; Cox, Van Arsdale, et al., 2001; Cox, Van Arsdale, and Larsen, 2002; Cox et al., 2006) 

(Figure 6.1.6-2). The results of these investigations show that the southeastern rift margin 

coincides with a 150 km (93 mi.) long linear topographic scarp from near Memphis to the 

Tennessee-Kentucky line; S-wave reflection profiles, auger data, and trench excavations reveal 

late Wisconsinan-Holocene surface faulting and late Holocene liquefaction associated with this 

fault-line scarp (Cox, Van Arsdale, and Harris, 2001; Cox, Van Arsdale, et al., 2001; Cox, Van 
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6-52

Arsdale, and Larsen, 2002; Cox et al., 2006). Cox, Van Arsdale, and Harris (2001), following 

Fisk (1944), refer to this fault as the Big Creek fault. Cox, Van Arsdale, et al. (2001) and other 

researchers (e.g., Csontos et al., 2008) subsequently refer to this zone of faults as the 

southeastern or eastern Reelfoot rift margin fault system. Based on variation in sense of throw 

along strike and flower-structure geometry observed in seismic profiles, Cox and others (Cox, 

Van Arsdale, et al. 2001; Cox, Van Arsdale, and Larsen, 2002) conclude that this fault is a strikeslip fault and is currently accommodating right-lateral strain along the boundary of the hanging 

wall of the RFT. Significant right-lateral offset (8–15 m [26.2–49.2 ft.) and vertical (≥3 m 

[9.8 ft.] of up-to-the-west throw) displacement of a late Pleistocene fluvial channel 

(approximately 20 ka) is inferred from stratigraphic and structural relationships observed in 

paleoseismic trenches at the Porter Gap locality (Cox, Van Arsdale, and Larsen, 2002). This 

offset is the result of multiple (at least two) surface faulting earthquakes, the most recent being 

between 2,000 and 2,500 years ago (Cox, Van Arsdale, and Larsen, 2002; Cox et al., 2006). 

Evidence for Holocene faulting also is observed in paleoseismic trenches at the Meeman-Shelby 

Forest paleoseismic site, and constraints on timing of the most recent earthquakes at this site and 

the Porter Gap site allow for the possibility of a single late Holocene rupture of ≥80 km (50 mi.) 

(Cox et al., 2006; Figure 6.1.6-2). Paleoliquefaction surveys along the Hatchie and Obion rivers 

near Covington and Dyersburg, Tennessee, to date have not identified paleoliquefaction features 

of this age, but the ages of some prehistoric liquefaction features along the two rivers have not 

yet been constrained (Dr. M. Tuttle, pers. comm., March 5, 2010). Along the northern part of the 

fault zone at the Union City site, seismic profiling and push-core transect data suggest only 1.5 m 

(5 ft.) of down-to-the-northwest faulting of early Wisconsinan Roxana Loess, with no 

discernable deformation of late Wisconsinan Peoria Loess (Cox et al., 2006). Cox et al. (2006) 

speculate that this segment turned off (or activity decelerated significantly) in the late 

Pleistocene-Holocene on the northeastern part of the fault zone north of the intersection of the 

RFT and the eastern margin of the rift. 

One of the key structures identified in seismic data in the vicinity of the Meeman-Shelby Forest 

paleoseismic trenching locality is a high-angle (about 75 degrees), west-dipping reverse fault that 

Williams et al. (2001) identified and named the Meeman Shelby fault (MSF; Figure 6.1.6-3a). 

Cox and others (Cox, Van Arsdale, and Larsen, 2002; Cox et al., 2006) correlate this fault pick 

with a northeast-trending fault along the bluff escarpment. As imaged in a high-resolution MiniSosie seismic reflection line, the MSF displaces Paleozoic and Cretaceous units 70 and 40 m 

(230 and 131 ft.), respectively; deformation of the overlying Eocene strata is expressed primarily 

as an up-to-the-west fold with amplitude of about 50 m (164 ft.) at the base (Williams et al., 

2001). Similar structures (i.e., having up-to-the-west folding) are observed in seismic profiles 

along the CCFZ, which lies approximately 18 km (11 mi.) to the west at its northernmost 

mapped location, and along a N33°E trend, approximately 33 km (20.5 mi.) northeast of the 

Meeman-Shelby vibroseis line (Williams et al., 2001). In a more recent paper, Odum et al. 

(2010) reevaluated the Mini-Sosie seismic reflection line and now suggest that the MSF is a 

N13°W trending fault that correlates with the eastern boundary fault of Joiner Ridge, a 10–15 km 

(6.2–9.3 mi.) wide by approximately 50 km (31 mi.) long structure defined by the uplift of the 

Pliocene-Pleistocene unconformity surface (Csontos et al., 2008). 
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The westernmost pick of the MSF as imaged on the Mini-Sosie line also lines up with a series of 

three fault picks identified in a high-resolution seismic survey conducted along the Mississippi 

River from Caruthersville, Missouri, to Helena, Arkansas (Dr. B. Magnani, CERI, U. of 

Memphis, pers. comm., May 29, 2009) (Figure 6.1.6-2). A line drawn through these fault picks 

(ERM-RP) projects along an approximately N30°E trend through the original Meeman-Shelby 

fault pick identified by Williams et al. (2001). Although there is currently no independent 

evidence that a fault of this trend is present at this location, a similar N30°E trend is exhibited by 

the postulated Memphis and Ellendale faults, which Van Arsdale et al. (2002) describe as 

possible Quaternary (and Holocene in the case of the Ellendale fault) active structures. 

6.1.6.1 Evidence for Temporal Clustering 

The first node of the logic tree addresses the issue of temporal clustering of earthquakes in the 

present tectonic stress regime (Figure 6.1.6-1). The available data regarding number and timing 

of recent earthquakes and long-term slip rates for the ERM sources are not sufficient to evaluate 

whether the ERM RLME sources exhibit evidence for temporal clustering. Therefore, this branch 

of the tree is not applicable to the Reelfoot rift ERM-S and ERM-N RLME sources. 

6.1.6.2 Geometry and Style of Faulting 

The primary basis for characterizing two independent RLME sources along the eastern margin of 

the rift is the apparent differences in the timing and recency of late Pleistocene and Holocene 

surface deformation inferred from paleoseismic investigations (Cox, Van Arsdale, and Harris, 

2001; Cox, Van Arsdale, et al., 2001; Cox, Van Arsdale, and Larsen, 2002; Cox et al., 2006). 

Based on the evidence for cumulative slip, as well as on the timing and recency of faulting along 

the rift margin, Cox, Van Arsdale, and Harris (2001) suggest that lateral slip on the southeastern 

rift margin (ERM-S) is greatest southwest of the restraining bend (adjacent to the Reelfoot thrust 

hanging wall). In this area, 25 m (82 ft.) of reverse separation underlies the bluff along the 

southern part of the margin. On the northern segment (ERM-N), the rift margin is characterized 

by a less prominent scarp (9 m [29.5 ft.] high) and a lack of seismicity. 

The location of late Quaternary faulting has been identified at only a few localities where 

detailed paleoseismic trenches, geophysical surveys, and drilling have been conducted (Figure 

6.1.6-2). The zone of bedrock faulting associated with the Reelfoot rift margin, however, is 

considerably wider. In the vicinity of the CCFZ, the zone of basement faults may be on the order 

of 4–8 km (2.5–5 mi.) wide (Hildenbrand, 1982; Crone, 1992). Csontos and Van Arsdale (2008) 

show the zone to be as much as 10–12 km (6.2–7.5 mi.) wide north of Memphis (Figure 6.1.6-2 

inset). Uncertainty in the width of the zone of faulting and location of future ruptures along this 

margin is therefore represented by a zone rather than a single fault. 

The location, and extent, of the ERM-N is based primarily on Cox, Van Arsdale, et al. (2001). 

The ERM-N source zone is centered on the pronounced topographic escarpment and lineament 

identified by Cox, Van Arsdale, et al. (2001; Figure 6.1.6-3b). The basis for the dashed extension 

of the ERM-N into Kentucky as shown by Cox et al. (2006) is not discussed in that publication, 

and this feature is not topographically expressed in the digital elevation model data. Cox, Van 
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6-54

Arsdale, and Harris (2001) speculate that a basement fault may have controlled the emplacement 

of the Big Foot pluton that appears to coincide with a boundary between two drainage basin 

asymmetry domains to the north of Union City. There is no supporting data to demonstrate that a 

Quaternary fault is present; thus in the absence of topographic evidence for the extension of the 

fault to the north, the dashed extension is not included directly in the characterization of the 

ERM-N RLME source. However, the northern end of the ERM-N is treated as a leaky boundary 

(i.e., it is not a barrier to future fault ruptures) allowing ruptures to propagate further to the 

northeast along the dashed extension. 

The location of the ERM-S segment is based on faults observed in paleoseismic trenches, 

geophysical surveys, and alignments of geomorphic features (Cox et al., 2006). Based on the 

orientation of the ERM fault in the current stress field, on the linear geometry of the fault system 

inferred from geomorphology, and on focal mechanisms of minor faulting along the margin, the 

predominant sense of slip for this fault system is considered to be right-lateral strike-slip with a 

component of reverse slip. Cox et al. (2006) interpret Holocene right-lateral slip on the basis of 

focal plane mechanisms of contemporary seismicity and evidence for right-lateral offset of late 

Pleistocene channel deposits. 

To the south of the Meeman-Shelby Forest State Park area, evidence for latest Pleistocene to 

Holocene activity is noted for the CCFZ (Williams et al., 1995) and possibly for a N30°E trend 

defined by the fault picks identified in the recent river seismic survey (ERM-RP) (Dr. B. 

Magnani, Center for Earthquake Research and Information, U. of Memphis, pers. comm., May 

29, 2009). These two alternatives are included as the southern extension of the ERM-S (Figure 

6.1-2b). The validity and continuity of the ERM-RP as a continuous fault have not been 

confirmed. For this reason, this alternative (ERM-SRP) is given less weight (0.4) than the ERMSCC (weight of 0.6), which is a known fault having Quaternary and possible Holocene activity. 

Within the zones associated with the ERM-N, the ERM-SCC and ERM-SRP faults are 

distributed uniformly throughout the zone subparallel to the preferred fault traces; the faults are 

modeled as vertical strike-slip faults. Both the northeastern and southwestern ends of the zones 

are modeled as leaky to allow for uncertainty in the extent of possible reactivated faults along the 

rift margin. 

The probability distribution used to model seismogenic thickness for the NMFS RLME source 

(Section 6.1.5.2), which is consistent with analysis of focal mechanisms along the ERM (Chiu et 

al., 1997), is used to model the ERM RLME sources: 13 km (8 mi.; weight of 0.3), 15 km (9.3 

mi.; weight of 0.5), and 17 km (10.6 mi.; weight of 0.2). 

6.1.6.3 RLME Magnitude 

There are little (ERM-S) or no (ERM-N) data except for possible fault length that provide direct 

constraints on the magnitude of prehistoric earthquakes along the southeastern margin of the 

Reelfoot rift. 

The ERM-S source extends for a distance of approximately 114 km (71 mi.). The fault is similar 

in length and style of faulting to the New Madrid South fault (discussed in Section 6.1.5). There 
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6-55

are only limited paleoseismic data from which to identify the length of fault ruptures or the size 

of individual displacements for prehistoric earthquakes on this fault zone. Information on timing 

of earthquakes shown on Figure 6.1.6-4, which is discussed below in Section 6.1.6.4, allows for 

the possibility of a ≥80 km (50 mi.) long rupture between the Porter Gap and Meeman-Shelby 

Forest sites, but does not preclude shorter ruptures (Cox et al., 2006). Vertical displacement of 

0.5 m (1.6 ft.) and right-lateral offset of 0–2 m (0–6.6 ft.) during the most recent earthquake at 

the Porter Gap site are reported by Cox et al. (2006). 

Ruptures of ≤80 or 114 km (≤50 or 71 mi.), assuming seismogenic depths ranging from 13 to 17 

km (8.1 to 10.5 mi.), yield magnitude estimates ranging from ≤M 7.0/ M 7.4 (Wells and 

Coppersmith [1994] magnitude-length and magnitude-area relationships) to ≤M 7.4/M 7.6

(Somerville et al. [2001] magnitude-area relationship, median) (Table 6.1.6-1). Displacements of 

0.5 or 2.1 m (1.5 or 6.9 ft.) (calculated oblique slip) would suggest magnitudes of M 6.5–7.1 to 

as much as M 6.7–7.3 based on empirical relationships for magnitude from maximum or average 

displacement, respectively (Table 6.1.6-1).

Given the uncertainty in the dimensions of paleoruptures, a wide range of values that capture the 

range in RLME magnitude estimates suggested by limited fault-specific data and analogy to the 

NMS fault is used to characterize the southern segments of the ERM south of the intersection 

with the Reelfoot rift. The resulting distribution for the expected RLME magnitude is tabulated 

below. 

Expected ERM-S RLME Magnitude

(M) Weight

6.7 0.15

6.9 0.2

7.1 0.2

7.3 0.2

7.5 0.2

7.7 0.05

The ERM-N segment is approximately 73 km (45.5 mi.) long, which is more comparable in 

length to the New Madrid North (NMN) fault. There are no data on paleoearthquake rupture 

dimensions that can be used to estimate magnitude. Ruptures of 73 km (45.5 mi.), assuming a 

seismogenic depth ranging from 13 to 17 km (8 to 10.6 mi.), yield magnitude estimates ranging 

from M 7.0 (Wells and Coppersmith [1994] magnitude-area relationship) to M 7.4 (Somerville 

et al. [2001] magnitude-area relationship, median) (Table 6.1.6-2). A distribution similar to that 

used for the ERM-S, but with a lower maximum value based on the shorter total length, is used 

to characterize the ERM-N. The distribution is tabulated below. 
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Expected ERM-N RLME Magnitude

(M) Weight

6.7 0.3

6.9 0.3

7.1 0.3

7.4 0.1

6.1.6.4 RLME Recurrence 

The remaining nodes of the ERM RLME logic trees address the estimation of recurrence rate of 

RLMEs. 

Recurrence Method 

The data available for assessing the recurrence frequency of ERM RLMEs consist of the number 

of earthquakes that postdate a specific geologic stratum. Therefore, the ―Earthquake Count in a 

Time Interval‖ approach is used to assess RLME recurrence frequency. 

Recurrence Data 

Paleoseismic investigations indicate that several paleoearthquakes have occurred along and 

within the southeastern part of the Reelfoot rift. Figure 6.1.6-4 is a summary diagram showing 

the relative timing and slip information inferred from paleoseismic investigations at the Porter 

Gap and Meeman-Shelby Forest localities on the ERM-S. The youngest calibrated radiocarbon 

ages of sediments predating the latest faulting earthquake (~0.5 m [1.6 ft.] vertical displacement) 

are 4,100–3,900 yr BP at Shelby County and 2,790–2,740 yr BP at Porter Gap (Cox et al., 2006). 

Radiocarbon ages from sediments postdating the latest faulting are 2,120–1,800 yr BP at Shelby 

County and 945–765 yr BP at Porter Gap. Minor liquefaction adjacent to the fault observed at 

the Porter Gap site is similar in age to widespread liquefaction features in the New Madrid region 

that are associated with an earthquake that occurred 2,750 yr BP ± 150 yr (Appendix E). An 

interpreted offset Wisconsinan paleochannel at Porter Gap records an unknown number of 

surface faulting earthquakes. It is assumed that at least two and possibly four earthquakes of a 

size similar to the recent earthquake have occurred at this locality in the past approximately 20 

kyr. The infrared stimulated luminescence analysis ages of samples from the offset channel fill 

are 19,600 yr BP ± 1,900 yr and 19,900 yr BP ± 1,740 yr (Cox et al., 2006). 

The recurrence data for the ERM RLME sources are more limited than for the NMFS RLME 

source. Except for the Porter Gap locality along the ERM-S segment that has a reported slip rate 

based on an offset channel, the recurrence data for the other segments of the ERM RLME source 

consists of an estimated number of earthquakes within a time period (inter-earthquake intervals 

or elapsed time intervals are not well constrained). There is no specific information regarding the 

timing of recent earthquakes on the CCFZ or inferred ERM-RP faults. 
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The northern segment of the southeastern rift margin fault system (ERM-N) appears to be less 

active than the segment to the south. Paleoseismic data from the Union City site are insufficient 

to estimate the timing or number of earthquakes that formed the 9 m (29.5 ft.) high scarp. The 

most recent faulting at a site near Union City along the northern segment of the fault appears to 

postdate Sangamon–early Wisconsinan terrace deposits (60–35 ka), but predate late Wisconsinan

Peoria Loess (?) (ca. 24–12 ka; Cox, Van Arsdale, et al., 2001). Paleoliquefaction features in 

Kentucky dated at 11,300 yr BP ± 200 years (Appendix E) could be related to an earthquake on 

the ERM-N. However, these features are approximately 40 km (25 mi.) north of the northeastern 

end of the ERM-N source, and their correlation to the most recent earthquake recorded at the 

Union City site is uncertain. Based on these observations, one or possibly two earthquakes have 

occurred on the ERM-N fault source since 12–35 ka. Due to uncertainty in what fault produced 

the paleoliquefaction features in western Kentucky, highest weight (0.9) is given to the evidence 

for a single earthquake on the ERM-N at the Union City site since 12–35 ka. 

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model with weight 1.0 for the ERM-S and ERM-N RLME sources as there are not sufficient data 

to justify including an alternative model. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs (Figure 6.1.6-1). These distributions were developed using the methodology 

described in Section 5.3.3.1. The relative-likelihood-based distribution was developed using 

Equation 5.3.3-2. 

For the ERM-S RLME source, the number of past earthquakes, N, was set at two, three, or four. 

The interpretation of the data does not favor one of these three values, so they are given equal 

weight in the RLME logic tree (Figure 6.1.6-1a). The time period T is treated as uniformly 

distributed over the range of 17.7–21.7 kyr. The resulting distributions for RLME recurrence 

frequency are listed in Table 6.1.6-3. 

For the ERM-N RLME source, the number of past earthquakes, N, was set at one or two, with 

weights of 0.9 and 0.1, respectively, as indicated above (Figure 6.1.6-1b). The time period T is 

treated as uniformly distributed over the range of 12–35 kyr. The resulting distributions for 

RLME recurrence frequency are listed in Table 6.1.6-4.

6.1.7 Reelfoot Rift—Marianna 

Earthquake-induced liquefaction features, including large sand blows comparable in size to the 

NMSZ sand blows, have been identified near Marianna, Arkansas, about 75 km (46.5 mi.) 

southwest of Memphis, Tennessee (Tuttle et al., 2006; Al-Shukri et al., 2005, 2006, 2009). These 

sand blows, which are located 80 km (50 mi.) south of the southwestern end of the NMSZ, 

formed between about 5 and 10 ka and predate paleoearthquakes attributed to the NMSZ. The 
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presence of the features suggest a nearby source of Holocene RLMEs in the southeastern part of 

the Reelfoot rift outside of the NMSZ, which is herein referred to as the Marianna (MAR) 

RLME source. Paleoliquefaction features used to define the MAR source zone also are at least 

30 km (19 mi.) south of the southern limits of the ERM RLME sources (Figures 6.1-2b and 

6.1.6-2). The possibility that some of the earthquakes that triggered paleoliquefaction in the 

Marianna area originated on faults associated with the ERM RLME sources is considered as 

discussed below. A logic tree outlining the source characterization parameters for the MAR 

RLME source is shown on Figure 6.1.7-1. Data and observations used to characterize the MAR 

RLME source are summarized in Appendix Tables C-6.1.7 and D-6.1.7. Figures 6.1.7-2 and 

6.1.7-3 show the locations of paleoliquefaction sites and structural features in the Marianna 

region in the southern part of the Reelfoot rift. 

Tuttle et al. (2006) observed that a large sand blow at the Daytona Beach site near Marianna, 

which formed about 3500 BC (5,500 yr BP), may correlate with smaller sand blows to the 

northeast and southwest up to 175 km (108.7 mi.) away. Al Shukri et al. (2005) identified an 

earthquake at the Nancy 1 site near Marianna that occurred shortly after 4,850–4,800 yr BP. AlShukri et al. (2009) identified additional older paleoliquefaction features at the Daytona Beach 

Southeast site: those that formed about 10 ka and others that possibly predate 10 ka. A 

compound sand blow that formed about 4800 BC (6,800 yr BP) at the St. Francis 500 site may 

have formed as the result of several very large, closely timed earthquakes. 

The location(s) of the earthquake source(s) responsible for these paleoliquefaction features is not 

known, but the size of the sand blows implies strong ground shaking at Marianna (Al-Shukri et 

al., 2005). A fault zone associated with the eastern Reelfoot rift margin is judged as a likely 

source for several reasons: its great length (approximately 300 km [186.5 mi.]); history of 

seismic activity; late Wisconsinan–early Holocene fault movement in western Tennessee; and 

structural relationship to the New Madrid fault system (Tuttle et al., 2006). Other potential fault 

sources in the vicinity of Marianna include the Big Creek fault zone and the White River fault 

zone. 

A northwest-trending lineament defined by sand blows extends from the Daytona Beach locality 

to the northwest and southeast; the lineament initially defined to be approximately 10 km (6 mi.) 

in length (Tuttle et al., 2006) has been extended to a total length of 17 km (10.5 mi.) based on 

additional trenching and ground-penetrating radar surveys (Al Shukri et al., 2009; Al Quadi, 

2010) (Figures 6.1.7-2 and 6.1.7-3). Its length, linear morphology, and parallelism to the nearby 

White River fault zone support the interpretation that the lineament may be fault controlled 

rather than related solely to lateral spreading (Al-Shukri et al., 2009). Al-Shukri et al. (2009) also 

identified a fracture in a trench exposure with a strike of N50°W (subparallel to the lineament) 

that crosscuts the sand blows. Although suggestive of being structurally controlled, further work 

is needed to verify by geologic and/or geophysical studies that strata below the sand layer that 

liquefied are faulted. 

6.1.7.1 Evidence for Temporal Clustering 

The first node of the logic tree for the MAR RLME source (Figure 6.1.7-1) addresses the issue of 

temporal clustering of earthquakes in the present tectonic stress regime. Available published and 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-59

unpublished information on the timing of paleoearthquakes in the Marianna region that is 

compiled in the paleoliquefaction database (Section 6.1.7.4) indicates that four earthquakes 

occurred during the time period from approximately 10 to 4.8 ka and that no late Holocene 

paleoliquefaction features have been identified to date. Tuttle (2009) cites the absence of late 

Holocene earthquakes in the southern rift as possible evidence that the locus of activity within 

the Reelfoot rift migrates over periods of 5–15 kyr. The data, while suggestive of possible 

temporal clustering, do not clearly demonstrate that the causative structures are in a period of 

inactivity. It also is unclear whether some of the paleoliquefaction features are due to 

earthquakes that originated on the Eastern Rift Margin (ERM) RLME source described above in 

Section 6.1.6. These uncertainties are represented by the equal weight assigned to the ―in‖ versus 

―out‖ of a cluster models. In the case of the ―out-of-a-cluster‖ model, the characterization 

defaults to the background (either the Mesozoic-and-younger Mmax zone or the Reelfoot rift 

seismotectonic zone). 

6.1.7.2 Geometry and Style of Faulting 

The location of the causative structure(s) for the earthquakes that produced the Marianna 

paleoliquefaction features is not well constrained based on the present state of knowledge, but 

there is evidence to indicate that at least some of the features are related to earthquakes on a local 

fault. The MAR RLME zone used for this study encompasses the paleoliquefaction sites that 

have been used to define the northwest-trending Daytona Beach lineament as well as the more 

distant Nancy and St. Francis sites near Marianna and Marianna Gap, respectively. The zone 

includes structures that have been considered as possible sources of the earthquakes that 

produced the paleoliquefaction, including the ERM RLME faults, Big Creek fault, and White 

River fault (Tuttle et al., 2006). 

Northeast-trending faults, including possible structures related to the ERM faults and the 

subparallel Big Creek fault, are likely to be reactivated as predominantly strike-slip faults with a 

reverse component, based on focal mechanisms recorded in the southern Reelfoot rift (Chiu et 

al., 1997) and general orientation within the present north-northeast-directed maximum 

horizontal stress field (Zoback, 1992b). The eastern Reelfoot rift margin affects the regional 

drainage pattern in both the St. Francis basin and the Western Lowlands (Spitz and Schumm, 

1997). The Big Creek fault zone parallels the Reelfoot rift margin and marks the boundary 

between south-trending Wisconsinan valley-train deposits and southwest-trending Holocene 

meander-belt deposits (Fisk, 1944; Krinitzsky, 1950). 

The northwest-trending White River fault zone (WRFZ) is characterized as a steeply dipping, 

predominantly strike-slip fault with a small up-to-the-southwest component of reverse slip (Fisk, 

1944; Krinitsky, 1950). Schumm and Spitz (1996) and Spitz and Schumm (1997) show the 

WRFZ as a left-lateral strike-slip fault. Schumm and Spitz (1996) note that the WRFZ is defined 

by numerous geologic and topographic features, which include a northwest-trending magnetic 

lineament, northwest-trending basement faults within the Western Lowlands, northwest-trending 

Paleozoic faults in the Ozark Uplands, extremely angular northwest-trending salients in the 

valley margins, tributaries to the L’Anguille River that form a drainage pattern parallel to the 

WRFZ, and the breach and offset of the southern end of Crowley’s Ridge that may be 

structurally controlled. Schumm and Spitz (1996) observe that many of the anomalous features 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-60

are located on Pleistocene and Holocene deposits, indicating that much of the suggested 

deformation may be as young as Holocene in age. Csontos et al. (2008) describe the WRFZ as an 

up-to-the-south fault, based on gravity, magnetic (Hildenbrand and Hendricks, 1995; 

Langenheim and Hildenbrand, 1997), and seismic reflection data (Howe, 1985). 

Based on these observations, two equally weighted orientations that subparallel the sides of the 

MAR zone are used to model fault ruptures: vertical, northeast-trending strike-slip faults and 

vertical northwest-trending strike-slip faults. The faults suggested as possible sources for the 

earthquakes that generated the Marianna paleoliquefaction features extend beyond the 

boundaries of the MAR zone. Uncertainties in the location of the epicenters and extent of 

paleoearthquakes in this region are accounted for by assuming that all boundaries to the MAR 

zone are leaky. 

The probability distribution used to model seismogenic thickness for the Reelfoot rift as a whole 

(see Section 7.3.6) and other RLME sources in the Reelfoot rift (e.g., the New Madrid fault 

system and the ERM RLME sources [Sections 6.1.5.2 and 6.1.6.2]) is used to model the MAR 

RLME zone: 13 km (8 mi.; weight of 0.3), 15 km (9.3 mi.; weight of 0.5), and 17 km (10.5 mi.; 

weight of 0.2). This distribution also is consistent with seismogenic depths of between 14 and 16 

km (8.7 and 10 mi.) for well-located earthquakes along the southeastern margin of the rift. 

6.1.7.3 RLME Magnitude 

The magnitudes of RLMEs in the MAR zone are not well constrained. The size of the largest 

paleoliquefaction features observed in trenches and imaged by ground penetrating radar surveys 

are comparable to the largest paleoliquefaction features observed in the NMSZ. 

The maximum magnitude probability distribution for the MAR RLME magnitude gives 

relatively equal weight to a range of values estimated for the New Madrid South (NMS) fault 

based on the estimated size of the December 16, 1811, earthquake. The resulting distribution is 

tabulated below. 

Expected Marianna RLME 

Magnitude

(M)

Weight

6.7 0.15

6.9 0.2

7.1 0.2

7.3 0.2

7.5 0.2

7.7 0.05
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-61

6.1.7.4 RLME Recurrence 

The remaining branches of the logic tree describe the assessment of RLME recurrence rates. 

Recurrence Method 

The data available for assessing the recurrence rate of the Marianna RLMEs provide assessments 

of the timing of past earthquakes. Thus the ―Earthquake Recurrence Intervals‖ approach is used 

with weight 1.0 (Figure 6.1.7-1). 

Recurrence Data 

Four ages of paleoliquefaction features are known from paleoliquefaction studies to date 

(Appendix E). Estimated event ages (BP = before 1950) are as follows: 

Nancy1— 4,825 yr BP ± 25 yr (4.8 ka)

Nancy2—5,460 yr BP ± 130 yr and 5,620 yr BP ± 40 yr (5.5 ka and 5.6 

ka)

Daytona Beach—5,440 yr BP ± 130 yr (5.4 ka)

Daytona Beach SE2—9,855 yr BP ± 295 yr and one event before that 

(9.9 ka and before 9.9 ka) 

St. Francis 500—6,805 yr BP ± 95 yr (6.8 ka)

Sand blows of similar age (5.5 ka) at Nancy2 and Daytona Beach probably formed during the 

same earthquake. Slightly older sand blows at Nancy2 (5.6 ka) could also have formed during 

the same earthquake. Because the age estimates of these sand blows are based on close 

maximum age constraints, the 4.8 and 5.5 ka sand blows could not have formed during the 6.8 ka 

earthquake (recorded at St. Francis 500). It also seems unlikely that the 9.9 ka sand blow formed 

during the 6.8 ka earthquake. 

The most likely sequence of earthquakes along the Daytona Beach lineament includes 

earthquakes at 4.8 ka, 5.5 ka, and 9.9 ka, and another earthquake before that during the late 

Wisconsinan. The 6.8 ka earthquake recorded at the St. Francis site looks like an additional 

earthquake and may be related to an earthquake sequence resulting from multiple ruptures near 

the intersection of the ERM and the WRFZ. The two equally weighted data sets consist of either 

three or four earthquakes, with the oldest occurring approximately 9.9 ka. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-62

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model with weight 1.0 for the Marianna RLME source as there are not sufficient data to justify 

including an alternative model. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs. These distributions were developed using the methodology described in Section 

5.3.3.1. The relative likelihood of various values of the recurrence rate parameter was developed 

using Equation 5.3.3-4 and the observations of two or three closed recurrence intervals and one 

open interval post the 9.9 ka earthquake. The value of 

0

1

tt

N

i

i

was assumed to be uniformly 

distributed between 9.6 kyr and 10.2 kyr with N equal to either 2 or 3. The resulting relativelikelihood-based distributions were represented by the five-point discrete distribution listed in 

Table 6.1.7-1. 

6.1.8 Reelfoot Rift—Commerce Fault Zone 

The Commerce geophysical lineament (CGL) is a 600 km long (373 mi.), 5–10 km (3–6 mi.) 

wide, northeast-trending gravity and magnetic anomaly that trends subparallel to and west of the 

Reelfoot rift (Hildenbrand and Hendricks, 1995). Recent studies have identified surface 

geomorphic anomalies, paleoseismic evidence for latest Pleistocene to Holocene tectonic 

deformation, and geologic structures coincident with the vertical surface projection of the CGL 

in southeastern Missouri along what is referred to as the Commerce section of the CGL (Baldwin 

et al., 2006). The following lines of evidence, both direct and indirect, for Quaternary fault 

activity along the Commerce section of the CGL in southeast Missouri, have been reported in the 

published literature as outlined by Baldwin et al. (2006) and Givler and Baldwin (2009). 

Anomalous west-flowing drainages on Crowley’s Ridge (Cox, 1988; Fischer-Boyd and 

Schumm, 1995). 

Displacement of late Tertiary and Pleistocene to Holocene deposits (Harrison and Schultz, 

1994; Harrison et al., 1999, 2002) along northeast-striking faults favorably oriented to be 

reactivated in the present-day stress field. 

Paleoliquefaction features within the Western Lowlands of southeastern Missouri that, in 

part, coincide with the CGL (Vaughn, 1991, 1992, 1994). 

Presence of diffuse contemporary seismicity in partial alignment with the CGL (Harrison and 

Schultz, 1994; Langenheim and Hildenbrand, 1997). 

Geophysical evidence of Tertiary and Quaternary deformation coincident with the surface 

traces of previously mapped bedrock faults in the Bloomfield Hills and Benton Hills 

(Stephenson et al., 1999; Odum et al., 2002). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-63

Evidence of late Pleistocene to early Holocene deformation on the Idalia Hill fault zone 

based on geomorphic mapping, acquisition of seismic reflection, and ground-penetrating 

radar data, coupled with paleoseismic trenching and borehole information collected at the 

South Holly Ridge site, near Idalia, Missouri (Baldwin et al., 2006). 

Preliminary results of ongoing investigations of the Penitentiary fault, an apparent en echelon 

continuation of the Commerce fault to the northeast into southern Illinois, also provide 

evidence in multiple seismic lines of interpreted latest Pleistocene and possible early 

Holocene (?) faulting. The continuation of the Penitentiary fault to the northeast is poorly 

constrained; the geomorphic expression of a reactivated fault-line scarp is not apparent to the 

north (Odum et al., 2002; Baldwin et al., 2008; Givler and Baldwin; 2009). 

Based on these observations, an RLME fault source that encompasses faults and probable faultrelated geomorphic features exhibiting evidence of repeated late Pleistocene and Holocene 

activity is included in the source model. A logic tree summarizing the characterization of this 

RLME source, referred to as the Commerce Fault Zone RLME source, is shown on Figure 

6.1.8-1. The Commerce Fault Zone RLME source is modeled as a strike-slip fault zone 

extending south from the northern limit of the mapped Penitentiary fault (Tamms, Illinois) to the 

southern end of the paleoseismic sites near Qulin Ridge (Qulin, Missouri), where evidence for 

Quaternary activity (paleoliquefaction and anomalous stream deflections) has been documented 

(approximately at the Missouri-Arkansas border), a distance of about 120 km (75 mi.; Figure 

6.1.8-2). Evidence for late Quaternary deformation and repeated latest Pleistocene to Holocene 

faulting along the CGL also is observed to the north in southern Illinois and Indiana. This 

deformation is considered in the characterization of the Wabash Valley RLME source (discussed 

in Section 6.1.9). 

Locations of tectonic features and key localities where detailed geophysical surveys and 

subsurface explorations have been conducted to evaluate the location and activity of faults and 

paleoliquefaction features along the Commerce Fault Zone RLME source are shown on Figure 

6.1.8-2 and are discussed below. Additional information used to identify and characterize an 

RLME source along the Commerce section of the CGL is summarized in Appendix Tables C6.1.8 and D-6.1.8. 

6.1.8.1 Evidence for Temporal Clustering 

The first node of the logic tree for the Commerce Fault Zone RLME source (Figure 6.1.8-1) 

addresses the issue of temporal clustering of earthquakes. Early studies (Vaughn, 1994; Harrison 

et al., 2002) near Qulin Ridge and the English Hills, respectively, suggested that there may be 

evidence for two late Holocene earthquakes on structures related to the CGL, which could imply 

that the fault/fault zone is in a more active period of deformation. However, as noted below in 

Section 6.1.8.4, the liquefaction and secondary faulting used to document these Holocene 

earthquakes may be related to strong ground motion from earthquakes occurring elsewhere in the 

Reelfoot rift. There is no evidence to support large-magnitude earthquakes along the Idalia Hill 

or Penitentiary faults directly southwest and northeast of the English Hills as would be expected 

if large-magnitude earthquakes had ruptured the fault zone in the late Holocene. The available 

data regarding number and timing of recent earthquakes and long-term slip rates for the 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-64

Commerce Fault Zone RLME source are not sufficient to evaluate whether this RLME source 

exhibits evidence for temporal clustering. Therefore, this branch of the tree is not applicable to 

this source. 

6.1.8.2 Geometry and Style of Faulting 

The Commerce Fault Zone RLME source is modeled as a fault zone that encompasses late 

Pleistocene and possible Holocene active faults identified from geophysical, geomorphologic, 

and geologic data that are coincident with CGL defined by gravity and magnetic anomalies 

(Hildenbrand and Hendricks, 1995; Figure 6.1.8-3). Specific features used to define this RLME 

source are the Penitentiary fault (Givler and Baldwin, 2009; Baldwin et al., 2008); the 

Commerce fault (Palmer, Hoffman, et al., 1997; Palmer, Shoemaker, et al., 1997; Harrison and 

Schultz, 1994; Harrison et al., 2002); the Idalia Hill fault zone (Baldwin et al., 2006); and faults 

imaged in seismic data near Qulin Ridge (Stephenson et al., 1999) that align with an anomalous 

deflection of the St. Francis River (Fischer-Boyd and Schumm, 1995; Figure 6.1.8-2). 

At most of the sites where detailed geophysical and subsurface paleoseismic studies have been 

conducted, deformation occurs across a broad zone up to a kilometer or slightly more in width. 

In some areas, such as in the English Hills where north-northeast-striking faults at Thebes Gap 

appear to splay north from the Commerce fault, the zone of Quaternary faulting encompasses the 

entire width of the CGL (e.g., Harrison et al., 1999; Figure 6.1.8-2). A zone the width of the 

entire CGL is therefore used to capture the uncertainty in the location of deformation that may be 

related to the Commerce Fault Zone RLME source. In the hazard analysis, future ruptures are 

distributed uniformly within this zone. 

Recent analysis and relocation of 19 earthquakes (M ≤ 3.6) in the northeastern part of the 

NMSZ, using a velocity model of the Mississippi embayment with appropriate depths to bedrock 

beneath seismic stations, show that 2 of the earthquakes occurred at depths between 13 and 15 

km (8 and 9.3 mi.; Shumway, 2008). Herrmann and Ammon (1997) show depths of up to 16 km 

(10 mi.) for earthquakes in the Reelfoot rift. Based on these data, the following distribution for 

seismogenic crustal thickness is used to characterize the Commerce Fault Zone RLME source: 

13 km (8 mi.; weight of 0.3), 15 km (9.3 mi.; weight of 0.5), and 17 km (10.6 mi.; weight of 0.2). 

The Commerce Fault Zone RLME source is modeled as a zone of vertical strike-slip faulting 

based on the following geologic and seismologic observations: 

The style of neotectonic and older deformation in the Thebes Gap area is consistent with 

strike-slip deformation along near-vertical structures (Harrison et al., 1999). 

Near-vertical faults and complex flower-like structures are observed in seismic data at 

multiple locations along the CGL (Stephenson et al., 1999; Harrison et al., 1999; Baldwin et 

al., 2006, 2008). 

The regional northeast strike of the faulting is favorably oriented for right-lateral 

transpressive slip in the present north-northeast-directed maximum horizontal stress field 

(Zoback, 1992). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-65

Focal mechanism analysis of a M 3.85 (E[M] 3.83) earthquake (February 5, 1994) along the 

northward-projected trend of the Commerce fault zone shows motion was primarily rightlateral strike-slip along a north-northeast azimuth (Herrmann and Ammon, 1997). 

Ruptures within the Commerce Fault Zone RLME source are modeled as striking N47°E, 

subparallel to the Commerce and Penitentiary faults within the zone. The northwest and 

southeast boundaries are fixed based on the width of the CGL as defined from geophysical data 

and mapped faults. The northeast and southwest boundaries of the zone are considered leaky 

boundaries to allow for ruptures to extend along the trend of the CGL into adjacent less well 

studied areas where there is not a sufficient paleoseismic record to demonstrate or preclude 

recent activity along a similar rheological boundary. 

6.1.8.3 RLME Magnitude 

The Commerce Fault Zone RLME source extends for a distance of approximately 120 km (75 

mi.). There are only limited paleoseismic data from which to identify the length of fault ruptures 

or the size of individual displacements for prehistoric earthquakes on this fault zone. Information 

on timing of earthquakes shown on Figure 6.1.8-4, which is discussed below in Section 6.1.8.4, 

allows for the possibility of a rupture involving the entire fault source (120 km [75 mi.]) in a 

single earthquake or possibly two or more smaller earthquakes. A late Pleistocene earthquake 

may have ruptured the southern half (55–63 km [34–39 mi.]). Baldwin et al. (2006) cite evidence 

for 2.0–2.2 m (6.6–7.2 ft.) of separation of a late Pleistocene–early Holocene colluvium/paleosol 

in trenches across the Idalia Hill fault zone; this separation may represent tectonic slip (possibly 

combined vertical and horizontal slip) during the most recent surface faulting earthquake at that 

site. 

Ruptures of 55–65 km (37–40 mi.) or 120 km (75 mi.)—the southern half or entire length, 

respectively—assuming a seismogenic depth ranging from 13–17 km (8–10.5 mi.), yield 

magnitude estimates ranging from M 6.9–M 7.5 (Wells and Coppersmith, 1994) for a 

magnitude-area and magnitude-length relationships to M 7.2–M 7.7 (Somerville et al., 2001) for 

magnitude-area relationship, median. A displacement of 2.0–2.2 m (6.6–7.2 ft.) would suggest 

magnitudes of M 7.0–7.1 and M 7.2–7.3 based on empirical relationships for magnitude from 

maximum or average displacement, respectively (Wells and Coppersmith, 1994; Table 6.1.8-1). 

Smaller ruptures, however, cannot be precluded, based on the available data. 

Given the uncertainty in the dimensions of paleo-ruptures, and the broad range of uncertainty 

considered even for 1811-1812 earthquakes, of which the NMN (NM2 earthquake) may be an 

analog for the Commerce source (see Table 6.1.5-2), the distribution tabulated below that 

captures a wide range in RLME magnitude estimates is used. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-66

Expected Commerce Fault 

Zone RLME Magnitude

(M) Weight

6.7 0.15

6.9 0.2

7.1 0.2

7.3 0.2

7.5 0.2

7.7 0.05

6.1.8.4 RLME Recurrence 

The remaining branches of the logic tree describe the assessment of RLME recurrence rates. 

Recurrence Method 

The data available for assessing the recurrence rate of the Commerce Fault Zone RLME provides 

assessments of the timing of past earthquakes. Thus the ―Earthquake Recurrence Intervals‖

approach is used with weight 1.0 (Figure 6.1.8-1). 

Recurrence Data 

The ages of earthquakes interpreted from stratigraphic and structural relations observed in 

trenches and from paleoliquefaction earthquakes at sites along the Commerce section of the CGL 

are shown on Figure 6.1.8-4. The colored bars show possible rupture scenarios (i.e., ruptures that 

are permitted by the timing of earthquakes documented at the four paleoseismic localities). The 

paleoseismic investigation localities are ordered from south to north. 

Paleoliquefaction studies in the Western Lowlands along the southern part of the Commerce 

section of the CGL provide evidence for at least four poorly constrained prehistoric earthquakes, 

which are related to the NMSZ and/or structures associated with the CGL (Vaughn, 1994; Tuttle, 

Lafferty, and Schweig, 1998; Tuttle, Chester, et al., 1999) (Figure 6.1.8-2). Vaughn (1994) 

estimates the timing of four prehistoric earthquakes that, from oldest to youngest, occurred at 

about (1) 23,000–17,000 yr BP; (2) 13,400–9,000 yr BP, (3) AD 240–1020; and (4) AD 1440–

1540. In the CEUS SSC paleoliquefaction database, these are assigned the following ages: 

22,750 yr BP ± 650 yr; 12,600 yr BP ± 200 yr; 1,050 yr BP ± 150 yr; and 500 yr BP ± 150 yr. 

The two most recent earthquakes of Vaughn (1994) likely are related to paleoearthquakes 

associated with seismic sources within the NMSZ (Tuttle, Schweig, et al., 2002). Baldwin et al. 

(2006) note that the two earlier paleoliquefaction earthquakes may correlate to earthquakes on 

nearby CGL structures, based on the earthquake’s apparent older age and greater size. The 

timing of these earthquakes is compatible with the timing of poorly constrained earthquakes 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-67

interpreted at the South Holly Ridge site on the Idalia fault, approximately 30 km (19 mi.) to the 

northeast. 

At the South Holly Ridge site, analysis of trench, borehole, and ground-penetrating radar data 

constrains the timing of the most recent earthquake on the Idalia fault to between the latest 

Pleistocene —about18 ka—and early Holocene (pre-7.7 ka). Evidence for a penultimate 

earthquake predates 23–18 ka (Baldwin et al., 2006). 

Evidence of Quaternary and probable Holocene deformation involving near-surface faults in the 

Benton Hills and Thebes Gap areas has been documented by Harrison and Schultz (1994); 

Harrison et al. (1999); Palmer, Hoffman, et al. (1997); Palmer, Shoemaker, et al. (1997); 

Stephenson et al. (1999); and Odum et al. (2002) (see Data Summary table D-6.1.5; Figure 

6.1.8-2). Harrison et al. (1999) document evidence for four episodes of Quaternary faulting: one 

in late- to post-Sangamon, pre- to early Roxana time (between 60 and 50 ka); one in syn- or postRoxana, pre-Peoria time (between 35 and 25 ka); and two to possibly three in post-Peoria time 

(<17 ka). At least two earthquakes may have occurred in the latest Holocene (just after 2-sigma

calibrated calendar ages of 3747–3369 BC and AD 639–968) (Harrison et al., 2002). The 

youngest in the Benton Hills may represent secondary tectonic deformation correlative with a 

NMSZ earthquake (Harrison et al., 1999).

The timing of recent earthquakes on the Penitentiary fault are not well constrained at this time; 

preliminary analysis of data from paleoseismic investigations indicates latest Pleistocene and 

possible early Holocene faulting (Givler and Baldwin, 2009). 

The possibility that most or the entire Commerce Fault Zone RLME source ruptured during an 

earthquake approximately 23,000 yr BP is permitted, but not required by the available data. The 

syn- or post-Roxana period of deformation observed on structures in the English Hills broadly 

overlaps with earthquakes recorded at the South Holly Ridge site on the Idalia Hill fault 

(Baldwin et al., 2006), with paleoliquefaction in the Western Lowlands near Qulin (Vaughn, 

1994), and possibly with poorly constrained earthquakes on the Penitentiary fault (Baldwin et al., 

2008). The available data also suggest the possibility of an earthquake involving only the 

southern part of the fault; the latest Pleistocene earthquake observed at the South Holly Ridge 

site (18,500–7,600 yr BP) broadly overlaps with the paleoliquefaction in the Western Lowlands 

(Vaughn, 1994). 

The middle to late Holocene deformation earthquakes observed in the English Hills, however, 

are not evident on the easternmost fault strands of the Idalia Hill fault at the South Holly Ridge 

site, approximately 30 km (19 mi.) to the south or at the Penitentiary site about 19 km (12 mi.) to 

the north (Baldwin et al., 2006, 2008). Thus it is not clear that the middle to late Holocene 

earthquakes recorded on faults within the English Hills and by paleoliquefaction in the Western 

Lowlands near Qulin are related to large-magnitude earthquakes on faults within the Commerce 

Fault Zone RLME source. The preferred interpretation (weight 0.75) is that two earthquakes 

have occurred in the past 23 kyr with the possibility (weight 0.25) that the count is three 

earthquakes. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-68

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model with weight 1.0 for the Commerce Fault Zone RLME source as there are not sufficient 

data to justify including an alternative model. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs (Figure 6.1.8-1). These distributions were developed using the methodology 

described in Section 5.3.3.1. The relative likelihood of various values of the recurrence rate 

parameter was developed using Equation 5.3.3-4 and the observations of one or two closed 

recurrence intervals and one open interval. The value of 

0

1

tt

N

i

i

was assumed to be uniformly 

distributed between 18.9 and 23.6 kyr with N equal to either 1 or 2. The resulting relativelikelihood-based distributions were represented by the five-point discrete distribution listed in 

Table 6.1.8-2. 

6.1.9 Wabash Valley 

Mapping and dating of liquefaction features throughout most of the southern Illinois basin and in 

parts of Indiana, Illinois, and Missouri have identified energy centers for at least eight Holocene 

and latest Pleistocene earthquakes having estimated moment magnitudes of M 6 to ~7.8 

(Obermeier et al., 1991; Munson et al., 1997; Pond and Martin, 1997; Obermeier, 1998; McNulty 

and Obermeier, 1999; Tuttle, Chester, et al., 1999) (Table 6.1.9-1). The proximity of the energy 

centers for the two largest earthquakes inferred from the paleoliquefaction data (referred to as the 

Vincennes and Skelton paleoearthquakes), both of which are located within 25–40 km (15.5–25 

mi.) of Vincennes, Indiana, suggests that there is a source of RLMEs (~M = 6.7–7.8) in the 

Wabash Valley region. These two paleoearthquakes are located in the general vicinity of the 

most numerous and strongest historical earthquakes (M 4–5.5) in the lower Wabash Valley of 

Indiana and Illinois (Obermeier, 1998). A logic tree outlining the characterization of the Wabash 

Valley RLME source for this study is presented on Figure 6.1.9-1. Other prehistoric earthquakes 

identified from paleoliquefaction studies in southern Illinois and southern Indiana are considered 

in the characterization of the Illinois basin-extended basement seismotectonic zone (Section 

7.3.5) and the modification of the Mmax priors. 

The locations of tectonic features and the key localities in the Wabash Valley region of southern 

Illinois and southern Indiana where studies have been conducted to evaluate evidence for 

tectonic surface deformation, the location and activity of faults, and extent of paleoliquefaction 

features are shown on Figure 6.1.9-2 and are discussed below. Figure 6.1.9-3 shows the Wabash 

RLME source relative to total magnetic anomaly and residual isostatic gravity data. Additional 

information used to identify and characterize the Wabash Valley RLME source is summarized in 

Appendix Tables C-6.1.9 and D-6.1.9). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-69

6.1.9.1 Evidence for Temporal Clustering 

The first node of the logic tree for the Wabash Valley RLME source considers the issue of 

temporal clustering of earthquakes in the present tectonic stress regime (Figure 6.1.9-1). The 

paleoliquefaction evidence used to identify the Wabash Valley RLME source, which is discussed 

in Section 6.1.9.4, includes two earthquakes in the latest Pleistocene to Holocene. The record is 

not sufficient to recognize periods of temporal clustering (i.e., faster or slower rates of activity). 

Therefore, this branch of the tree is not applicable to the Wabash Valley RLME source. 

6.1.9.2 Geometry and Style of Faulting 

The geometry of the Wabash Valley RLME source zone is based on consideration of a variety of 

structural, geologic, geomorphic, and paleoseismologic observations and hypotheses as outlined 

below. 

A broad flexure (bend or stepover) in bedrock structure has been postulated to concentrate 

stress in this region (Hildenbrand and Ravat, 1997). This bend or stepover lies near the 

northern terminus of an approximately 600 km (375 mi.) long magnetic and gravity 

lineament, referred to as the Commerce geophysical lineament (CGL), which extends from 

Vincennes, Indiana, far into Arkansas. Late Quaternary faulting recently has been identified 

near this lineament, close to the Missouri-Illinois border (Langenheim and Hildenbrand, 

1997) (see discussion of the Commerce Fault Zone RLME source, Section 6.1.8). Wheeler 

and Cramer (2002) discuss the concept of a left stepover functioning as a restraining bend if 

the CGL is acting as a right-lateral strike-slip fault in the current tectonic environment. 

McBride and Kolata (1999) note a possible relationship between the most deformed region of 

the Precambrian basement yet to be identified beneath the Illinois basin (the Enterprise 

subsequence) and some of the largest twentieth-century earthquakes in the central 

Midcontinent. This region roughly coincides with the area of the broad flexure in the CGL. 

Morphometric analysis of the land surface, detailed geologic mapping, and structural analysis 

of bedrock in the Wabash Valley generally indicate westward tilting of the modern land 

surface, preferred channel migration to the west side of the valley (see inset on Figure 

6.1.9-2), a convex longitudinal profile of the Wabash River where it crosses the La Salle 

anticlinal belt, and increased river incision into the floodplain downstream of the anticlinal 

belt. These geomorphic anomalies occur along the western edge of the CGL in the restraining 

bend region (Fraser et al., 1997). 

Evaluation of recently acquired industry seismic-reflection profile data from southern Illinois 

provides additional insights as to the causative structures for recent earthquakes. McBride et 

al. (1997) and McBride, Hildenbrand, et al. (2002) report a northeast-trending zone of 

dipping reflectors and diffractions that they interpret as a zone of intrusions or a zone of 

deformation, or both. McBride, Kolata, et al. (2002) suggest that the zone, which lies along 

the CGL, may represent thrust faults deep within crystalline basement, faults that may be 

subject to reactivation. The largest instrumentally recorded earthquake in the Illinois basin, 

which occurred on November 9, 1968, had a moment magnitude of M 5.4 (Johnston, 1996a) 

or mbLg 5.5 (McBride, Hildenbrand, et al., 2002) (E[M] 5.32). Its focal mechanism has a 

nodal plane that is subparallel to the zone of dipping reflections, a midcrustal hypocenter that 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-70

is located within the zone, and a seismic moment that corresponds to a rupture zone 

approximately the same size as one of the reflectors. McBride et al. (1997) and McBride, 

Hildenbrand, et al., (2002) note that earthquakes may be nucleating along compressional 

structures in crystalline basement and thus may occur in parts of the basin where there are no 

obvious surface faults or folds. They conclude that shallow Paleozoic structures are 

―decoupled‖ from deeper, possibly seismogenic, structures. The results of their study suggest 

that a seismogenic source just north of the New Madrid seismic zone in the Wabash Valley 

area consists, in part, of thrusts in the basement localized along igneous intrusions that are 

locally coincident with the CGL. 

McBride et al. (2007) further evaluate major structures within the Illinois basin, including the 

Wabash Valley fault system (WVFS) and the La Salle anticlinal belt (LSA). Based on results 

of reprocessing seismic reflection profiles, combined with earthquake hypocenter parameters, 

three distinct seismotectonic environments are defined in the upper crust in the southern 

portion of the Illinois basin. First, a fault pattern that appears to correspond to the steep nodal 

plane of a strike-slip mechanism earthquake (April 3, 1974, mb4.7, E[M] 4.29) is interpreted 

to be a deeply buried rift zone or zone of intense normal faulting underpinning a major 

Paleozoic depocenter of the Illinois basin (Fairfield basin). Second, a similar earthquake 

(June 10, 1987, mb 5.2, E[M] 4.95) and its well-located aftershocks define a narrow zone of 

deformation that occurs along and parallel to the frontal thrust of the LSA. Third, the 

hypocenter of the largest earthquake in the study area (November 9, 1968, mb 5.5, 

E[M] 5.32) as outlined above may be spatially associated with a prominent zone of dipping 

middle crustal reflections, just west of the WVFS, which have been interpreted as a deeply 

buried blind thrust. 

Holocene activity is evidenced on faults within the WVFS. The WVFS is a linear northeastsouthwest band of narrow graben structures that lie within the southern part of the Illinois 

basin (Bristol and Treworgy, 1979; Treworgy, 1981; Sexton et al., 1986; Kolata and Nelson, 

1991; Rene and Stanonis, 1995; Bear et al., 1997; Hildenbrand and Ravat, 1997; Woolery, 

2005). The WVFS consists of a series of high-angle normal faults and strike-slip faults with 

trends between N15°E and N50°E. These faults lie within and form the borders of the 

northeast-trending Grayville graben. The Grayville graben (~20 km [~12.5 mi.] wide, ~0.7

km [~0.4 mi.] maximum basement relief, and <40 km [25 mi.] long) underlying the Wabash 

Valley developed during late Precambrian-Cambrian (Iapetan) rifting, perhaps in response to 

stress concentrations generated by a bend in the Reelfoot–Rough Creek–Rome rift system 

(Hildenbrand and Ravat, 1997). Although some workers (e.g., Sexton et al., 1986) have 

suggested that the WVFS may be a northward extension of the Reelfoot rift, others have 

noted that both the dike pattern and mapped WVFS terminate near the Reelfoot–Rough 

Creek–Rome rift system (Hildenbrand and Ravat, 1997) and that fault displacements of the 

WVFS decrease southward in the direction of the NMSZ (Bear et al., 1997). The WVFS 

offsets the Pennsylvanian and older units with vertical offsets of as much as 145 m (480 ft.) 

along the faults (Nelson, 1995; Bristol and Treworgy, 1979). Woolery (2005) describes highangle deformation associated with one of the faults in the WVFS, the Hovey Lake fault, 

extending above the Paleozoic bedrock and into upper Quaternary sediment. Timedisplacement calculations from the data show approximately 10.5 m (34.4 ft.) of offset on the 

top-of-bedrock horizon, located 7.7 m (25.3 ft.) below ground surface, suggesting fault 

movement at this site as late as ~37 ka. More recent Holocene deformation is evidenced by 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-71

folding and faulting of sediments across the Uniontown scarp, a prominent scarp on the 

floodplain of the Ohio River that is interpreted to be associated with the Hovey Lake fault 

(Counts et al., 2009a, 2009b; Van Arsdale et al., 2009). 

Analysis of the June 18, 2002, Mw 4.6 (E[M] 4.38) earthquake, which occurred on a steeply 

dipping fault within the WVFS at a depth of about 18 km (11 mi.), may suggest that buried 

faults associated with a possible Precambrian rift system are being reactivated by the 

contemporary east/east-northeast-trending regional horizontal compressive stress (Kim, 

2003). The source mechanism determined from regional waveform analysis is predominantly 

strike-slip along near-vertical nodal planes (dips 82 and 84 degrees), striking 28 and 297 

degrees. The close proximity of the epicenter to the trace of the Caborn fault (WVFS) and 

good agreement between the strike and dip of that fault and source mechanism for the June 

2002 earthquake suggest that the earthquake occurred on that fault. 

Analysis of geodetic data in the southern Illinois basin suggests systematic northwestward 

motion of about 0.5–0.7 mm/yr (0.02–0.03 in.) with respect to the Stable North American 

Reference Frame. Block models, which assume boundaries along the Cottonwood Grove 

fault system–Rough Creek graben and the WVFS, indicate marginal block velocities with 

possible strike-slip motion along the WVFS, and east-west motions along the CGRCG 

(Hamburger et al., 2008). 

The causative structures for the paleoearthquakes are not known. The Wabash Valley RLME 

source zone encompasses the structural features, postulated neotectonic deformation, and 

locations of the inferred energy centers for the Vincennes and Skelton earthquakes described 

above (Figure 6.1.9-2). Characteristics for future earthquake ruptures in the WV RLME source 

zone are given in Table 5.4-2. 

Given the uncertainty in the location of the causative faults, the boundaries of the Wabash Valley 

RLME source zone are modeled as leaky. 

Two alternative depths are used to estimate the seismogenic thickness of the crust in the Wabash 

Valley RLME source zone: 17 km (10.6 mi.; weight of 0.7) and 22 km (13.7 mi.; weight of 0.3). 

Higher weight is assigned to the shallower depth based on the evidence for reactivations of 

structures in the upper 15–17 km (9.3–10.6 mi.) of crust as inferred from recent seismicity 

(McBride et al., 2007). This depth is more likely to represent the average depth of seismogenic 

crust throughout the RLME source zone. The greater seismogenic thickness is consistent with the 

focal depth of the 1968 earthquake, which is postulated to have ruptured a reverse fault in the 

basement in the Fairfield basin, a localized basin within the southern Illinois basin. 

Earthquakes in the in the Wabash Valley RLME source zone are modeled as a mixture of vertical 

strike-slip and reverse (with a random dip in the range of 40–60 degrees) based on the focal 

mechanisms for recent earthquakes (Figure 6.1.9-2). Due to the wide range in style, orientation, 

and focal depth of recent earthquakes and variability of structural trends within the zone, the 

aleatory variability in future earthquakes within the Wabash Valley RLME source is expected to 

be as follows: 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-72

strike—parallel to the long axis of the zone [0.8] 

2/3 strike-slip, 90 degrees

1/3 reverse, uniform 40–60 degrees to the west

N50°W [0.1] strike-slip, 90 degrees

N20°W [0.1] reverse, uniform 40–60 degrees to the west

6.1.9.3 RLME Magnitude 

The magnitude assessments for the Wabash Valley RLME source are based on recent analysis of 

paleoliquefaction features associated with the Vincennes and Skelton energy centers in the 

vicinity of the lower Wabash Valley of southern Illinois and Indiana. The magnitude of the 

largest paleoearthquake in the lower Wabash Valley (the Vincennes-Bridgeport earthquake), 

which occurred 6,011 200 yr BP, was estimated to be M 7.5 using the magnitude-bound 

method (Obermeier, 1998). Use of a more recently developed magnitude-bound curve for the 

CEUS based on a value of M ~ 7.6–7.7 for the largest of the 1811-1812 New Madrid 

earthquakes (reduced from the higher M 8 used in the older curve) gives a lower estimate of M

7.1–7.3 depending on the minimum (115 km [71.5 mi.]) and maximum (153 km [95 mi.]) 

distance, respectively, of distal paleoliquefaction features related to this paleoearthquake (Olson 

et al., 2005b). The lower-bound relationship developed by Castilla and Audemard (2007) from a 

worldwide database gives a range of M 7.0–7.3 for the same minimum and maximum distance 

values. 

Estimates based on a suite of geotechnical analyses (cyclic stress and energy stress methods) 

range from M 7.5 to 7.8 (summarized in Obermeier et al., 1993). The highest value of M 7.8 is 

based on geotechnical studies using the energy-acceleration method (a possibly flawed energy 

method, see Table 6.1.9-1) (Pond and Martin, 1997). A reanalysis of this earthquake has been 

done by Green et al. (2004a, 2004b; Green et al., 2005) using more recent ground-motion 

attenuation relationships for the central United States, review of approximately 50 boring logs 

presented by Pond and Martin (1996) to select appropriate standard penetration test values for 

the reanalysis, and the most recent magnitude scaling factors suggested by Youd et al. (2001). 

Using the cyclic stress method, the best estimate of the magnitude for the Vincennes-Bridgeport 

earthquake based on all these solutions ranges from M 7+ to 7.5. The energy-based solution 

developed by Green (2001) that circumvents the use of the magnitude scaling factor, which is a 

significant, questionable factor in the use of the cyclic stress method in the central United States, 

gives a value of M ~ 7.5 for each of the four newer ground-motion attenuation relationships 

(Green et al., 2004b). The more recent evaluations by Green et al. (2005) have considered the 

influence of aging effects on liquefaction susceptibility and concluded that for moderately 

susceptible sites like those in southern Illinois, the small changes expected given the types of 

sediments would have little influence on the interpretation of paleomagnitude (Obermeier et al., 

2001; Obermeier, pers. comm., August 2003). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-73

The next largest earthquake, the Skelton paleoearthquake, occurred 12,000 1,000 yr BP (Hajic 

et al., 1995; Munson et al., 1997; Obermeier, 1998). The magnitude of this earthquake is 

estimated to be M 7.1–7.3 by Munson et al. (1997; using a magnitude-bound approach) or M 7.3 

by Pond and Martin (1997; using a possibly flawed energy-stress method; see Table 6.1.9-1). 

Olson et al. (2005b) gives an estimate of M 6.7 for this paleoearthquake, and the lower-bound 

relationship of Castilla and Audemard (2007) would yield a value of M 6.3. The estimated 

values of the size of the epicentral area of this paleoearthquake are clearly minimums, as deposits 

of an age that would preserve a record of this earthquake are not widespread. 

The difference in the estimated sizes of the Vincennes and Skelton paleoearthquakes is on the 

order of 0.5 to 1 magnitude units. This probably represents a combination of the aleatory 

variability in the size of individual Wabash RLMEs and epistemic uncertainties in the 

approaches and data used to estimate the magnitudes of the prehistoric earthquakes. Therefore, a 

broad probability distribution is used to capture the range in uncertainty in the magnitude of 

earthquakes in the Wabash Valley RLME. This distribution is tabulated below. 

Expected Wabash Valley 

RLME Magnitude

(M) Weight

6.75 0.05

7.0 0.25

7.25 0.35

7.5 0.35

6.1.9.4 RLME Recurrence 

The remaining branches of the logic tree describe the assessment of RLME recurrence rates. 

Recurrence Method 

The data available for assessing the recurrence rate of the Wabash Valley RLMEs provide 

assessments of the timing of past earthquakes. Thus the ―Earthquake Recurrence Intervals‖

approach is used with weight 1.0 (Figure 6.1.9-1). 

Recurrence Data 

The available data for characterizing the recurrence rate of Wabash Valley RLMEs are the 

estimated ages for the Vincennes-Bridgeport and Skelton paleoearthquakes described above. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-74

Earthquake Recurrence Model 

As discussed in Section 5.3.3, the Poisson model is used as the default earthquake recurrence 

model with weight 1.0 for the Wabash Valley RLME source as there are not sufficient data to 

justify including an alternative model. 

RLME Annual Frequency 

The final node of the logic tree addresses the uncertainty distributions for the annual frequency 

of RLMEs. These distributions were developed using the methodology described in Section 

5.3.3.1. The relative likelihood of various values of the recurrence rate parameter was developed 

using Equation 5.3.3-4 and the observations of one closed recurrence interval between the 

Vincennes-Bridgeport and Skelton paleoearthquakes and one open interval post the VincennesBridgeport paleoearthquake. The value of 

0

1

tt

N

i

i

was assumed to be uniformly distributed 

between 11 and 13 kyr with N equal to 1. The resulting relative-likelihood-based distributions 

were represented by the five-point discrete distribution listed in Table 6.1.9-2. 

6.2 Mmax Distributed Seismicity Source Zones

In the Mmax zones branch of the master logic tree, the two components of the SSC model are the 

RLME sources and the Mmax distributed seismicity sources or, simply, Mmax zones. As 

discussed in the criteria for identifying seismic sources (Section 4.1.3.3), after earthquake 

recurrence rate, the most important criterion for identifying a seismic source is potential 

differences in Mmax. The Mmax zones branch considers only this parameter in defining 

alternative zonation models. 

6.2.1 Definition of Mmax Zones 

The Bayesian approach to estimating Mmax, described in Section 5.2.1.1, uses a prior 

distribution that is defined based on a statistical analysis of the global SCR database. The 

statistical analyses carried out for the CEUS SSC Project indicate only a marginally significant 

difference in prior distributions between Mesozoic-and-younger extended crust (MESE) and 

non-Mesozoic-and-younger crust (NMESE). For example, the p-value associated with the 

separation of these two data sets is 0.14 (see Section 5.2), which indicates that there is a 14 

percent chance that the two data sets were derived from the same population, such that they 

would be expected to have the same mean value. To account for the uncertainty in whether the 

SCR database can be separated with confidence into two prior distributions, two alternatives are 

considered in the Mmax zones model: (1) two Mmax zones that are defined by two prior 

distributions (MESE and NMESE), and (2) a single Mmax zone that represents a single prior 

distribution. The first model is assigned slightly higher weight (0.6) than the single zone model 

(0.4). Preference is given to the first model because there is marginal statistical significance for 

the separation of the SCR database into the two parts, but there is also a reasonable likelihood 

that there is no reliable separation of the SCR database with confidence. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-75

Alternative configurations for the two Mmax zones are shown on Figures 6.2-1 and 6.2-2. The 

separation reflects the assessment of those parts of the study region that show evidence of 

Mesozoic-and-younger extension (MESE) and those parts that do not (NMESE). Criteria used to 

make this assessment are described in Section 6.2.2. The uncertainty in that assessment is 

represented by the two alternatives: (1) the ―narrow‖ MESE that is distinguished by clear major 

Mesozoic-and-younger extensional features, and (2) the ―wide‖ MESE whose western boundary 

is drawn to include more questionable evidence for such features. Because of the more 

technically defensible evidence for the narrow interpretation, it is assigned a weight of 0.8, and 

the wide interpretation is assigned a weight of 0.2. 

6.2.2 Criteria for Defining the MESE/NMESE Boundary 

The breakup of the supercontinent of Pangaea into Laurasia to the north and Gondwana to the 

south resulted in Mesozoic extension of the crust and consequent development of the Atlantic 

Ocean (Triassic), the passive Atlantic margin (Jurassic), and the Gulf of Mexico (from Triassic 

to Jurassic). As a result of this extension, both the Atlantic and Gulf Coast margins generally 

consist of three crustal domains. For the Atlantic margin, the domains comprise rifted continental 

crust of Appalachian origin lying principally beneath the Coastal Plain and continental shelf, 

oceanic crust underlying the continental rise, and the intervening 50–100 km (30–60 mi.) wide 

zone of transitional, or rift-stage, crust (Klitgord et al., 1988; Holbrook, Reiter, et al., 1994). 

Crustal domains in the Gulf of Mexico region consist of thick transitional crust, thin transitional 

crust, and newly formed oceanic crust (Buffler and Sawyer, 1985; Marton and Buffler, 1994; 

Salvador, 1991a, 1991b; Sawyer et al., 1991). Mesozoic extension associated with opening of the 

Atlantic Ocean and Gulf of Mexico also resulted in extensional reactivation of Paleozoic 

structures within the St. Lawrence rift, Reelfoot rift, and Northern Appalachians (Tremblay et al., 

2003; Lemieux et al., 2003; Wheeler, 1997; Faure et al., 2006). Lesser amounts of Mesozoic 

extension may have occurred within the Rough Creek and Grayville grabens (Wheeler, 1997; 

Wheeler and Cramer, 2002). The extent of possible Mesozoic reactivation of older Iapetan rift 

structures inferred to be present in basement rock beneath the Appalachian detachment or older 

basement structures cratonward of the well-defined Mesozoic rifts is not well constrained. 

Cretaceous-and-younger extension also occurred in response to thermal processes and related 

uplift in the northeastern United States and eastern Canada as portions of the North American 

Plate rode over Cretaceous hotspots (McHone, 1996; Cox and Van Arsdale, 1997, 2002; 

Morgan, 1983; Crough, 1981; Sleep, 1990). 

The cratonward limit of significant Mesozoic-and-younger extension is inferred from a variety of 

geologic, geophysical, and seismologic data. Criteria used to define this boundary are listed 

below, ordered from most diagnostic to least definitive for identifying Mesozoic-and-younger 

extension. 

1. Grabens and sedimentary rift basins of Mesozoic age. 

2. Mesozoic-and-younger plutons. 

3. Extensive distributed brittle normal faults and basaltic (thoeliitic) dikes of Mesozoic-andyounger age. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-76

4. Evidence for Mesozoic-and-younger regional uplift and unroofing with associated normal 

faulting or fault reactivation. 

5. Localized extensional reactivation of pre-Mesozoic structures. 

6. Favorably oriented older extensional faults (e.g., Iapetan rift faults proximal to regions of 

Mesozoic rifting). 

Regions that generally meet the first three to four criteria are included in the MESE-narrow 

(MESE-N) zone. This zone includes the ECC-AM, ECC-GC, AHEX, GHEX, RR, SLR, NAP, 

GMH, and PEZ-N seismotectonic zones described in Section 7.0 (Table 6.2-1). A description of 

the geologic observations and data that demonstrate Mesozoic-and-younger extension in these 

zones, and the basis for the definition of the cratonward limit (boundary) of the respective units 

used to define the MESE-N boundary are provided in Section 7.0. 

The MESE-wide (MESE-W) boundary encompasses regions that have less definitive evidence 

for significant Mesozoic-and-younger extension. These regions include areas that have known or 

possible Iapetan-rift faults that may have been reactivated during the Mesozoic (e.g., the Rough 

Creek and Grayville grabens, Rome Trough-Kentucky River fault system) and older Precambrian 

compressional structures, such as the Clarendon-Linden fault and Central Metasedimentary Belt 

boundary structure in western New York and Ontario, Canada, that have evidence of extensional 

reactivation during latest Precambrian/early Paleozoic Iapetan rifting, but have less definitive 

evidence for Mesozoic reactivation. The MESE-W zone differs from the MESE-N in that it 

adopts the wide alternative geometries for the Paleozoic Extended Zone (PEZ-W); Reelfoot rift 

(with Rough Creek graben, RR-RCG); and the Illinois Basin Extended Basement (IBEB) zone 

(Table 6.2-1). Due to the limited Mesozoic deformation or lack of clear evidence of significant 

Mesozoic extension in these regions, low weight (0.2) is assigned to this alternative boundary. 

The boundaries of these zones are discussed in the descriptions of these seismotectonic source 

zones in Section 7.0. 

6.3 Maximum Magnitude Distributions for Mmax Distributed Seismicity 

Sources 

This section presents the Mmax distributions for the Mmax distributed seismicity sources. The 

methodology used to develop these distributions is presented in Section 5.2.1. The steps involved 

are identification of the maximum observed earthquake in each distributed seismicity source 

(described in Section 6.3.1) and then application of the quantitative approaches developed in 

Section 5.2.1 to produce the composite Mmax distributions (described in Section 6.3.2). 

6.3.1 Maximum Observed Earthquake Magnitude 

The maximum observed earthquake magnitude, 

mmax obs

, represents the size of the largest nonRLME observed to have occurred within each source. The value of this magnitude is used in 

developing the likelihood function for the Bayesian Mmax approach (Section 5.2.1.1) and is a 

parameter of the Kijko approach (Section 5.2.1.2). Two sources are used to assess 

mmax obs

. One 

is the CEUS SSC earthquake catalog developed for this study (Section 3); the other is the 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-77

compilation of identified paleoearthquakes that are not associated with RLME sources. The latter 

consists of the four non-RLMEs that have been identified in southern Illinois/southern Indiana. 

These earthquakes are discussed in Section 7.3.5. These earthquakes have estimated magnitudes 

of M 6.2–6.3 and represent the largest non-RLMEs in the study region. 

The largest historical non-RLMEs identified in the project catalog are listed below by Mmax 

zone. 

Mmax Distributed 

Source

Largest Historical Earthquake

Date E[M]

Study Region September 16, 1732 6.25

MESE-N September 16, 1732 6.25

MESE-W September 16, 1732 6.25

NMESE-N May 31, 1897 5.91

NMESE-W May 16, 1909 5.72

The 1732 earthquake occurred in the St. Lawrence region; the 1897 earthquake occurred in Giles 

County, Virginia; and the 1909 earthquake occurred at the border of North Dakota, Montana, and 

Canada. 

Uncertainty in 

mmax obs

was incorporated into the Mmax assessment using the procedure 

described in Section 5.2.1.1.6. The uncertainties in the magnitudes for the catalog of historical 

earthquakes or paleoearthquakes for each source were used to develop simulated catalogs of 

earthquake magnitudes. The largest values for each simulation were then used to develop a 

distribution for 

mmax obs

. Figure 6.3.1-1 shows the resulting distributions for 

mmax obs

. The blue 

curve on each plot shows the distribution developed for 

mmax obs

, and the red vertical line 

indicates the nominal observed magnitude. The phrase ―paleo‖ in the plot legend indicates that 

the set of paleoearthquakes is the controlling set for determining 

mmax obs

and was the set used to 

develop the Mmax distributions. The 1882 E[M] 5.58 earthquake, which is discussed in Section 

7.3, occurred very near the boundary between the ECC-GC and OKA seismotectonic zones, and 

the uncertainty in its location is addressed by including alternative locations. To be consistent 

with the assessments for the seismotectonic zones, the 1882 earthquake is considered to have 

occurred in either the MESE zones or the NMESE zones. However, because this earthquake is 

not the largest historical earthquake in either zone, the alternative locations have only a small 

effect on the distributions for 

mmax obs

. 

6.3.2 Mmax Distributions 

Mmax distributions were developed for each Mmax distributed seismicity source using the 

Bayesian and Kijko methods. For the Bayesian Mmax approach, the alternative priors described 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-78

in Section 5.2.1.1 were used. For the study region, only the composite prior is used, as the single 

source zone model is based on no difference between Mesozoic extended and non-extended 

crust. The remaining Mmax zones are assigned the composite prior with weight 0.4, and either 

the MESE or NMESE prior with weight 0.6. Figures 6.3.2-1 through 6.3.2-5 show the resulting 

Mmax distributions obtained by each method. Indicated in the legend of each figure are the 

weights assigned to the individual Mmax methods following the weighting approach described in 

Section 5.2.1.1. The final weighted composite distributions are indicated by the thick red bars on 

each plot. 

The Mmax distributions for the study region and the MESE-W and NMESE-N Mmax zones 

utilize the paleoearthquake record to define the distribution for 

mmax obs

. Because the number of 

paleoearthquakes is small, the Kijko method is assigned zero weight in these cases. The Kijko 

method is given appreciable weight (0.23) only for the NMESE-W Mmax zone. 

The continuous distributions shown on Figures 6.3.2-1 through 6.3.2-5 were used to construct 

five-point discrete approximations for use in hazard analyses. These distributions are listed in 

Table 6.3.2-1. The differences in the distributions for NMESE-N and NMESE-W reflect the 

presence or absence of the Wabash Valley paleoearthquakes within the boundary of the source 

zone. 

6.4 Recurrence Parameters 

The recurrence parameters (i.e., rate and b-values) for the Mmax zones were calculated using the 

methodology and parameters described in Section 5.3.2. Briefly, this methodology divides the 

source zone into cells of dimensions a quarter or half degree and then calculates the rate and bvalue in each cell using the likelihood function of the data in that cell, together with penalty 

functions that tend to smooth the cell-to-cell variation in the rate or the b-value. In addition, this 

procedure characterizes epistemic uncertainty in the recurrence parameters by generating eight 

alternative maps of the recurrence parameters. 

6.4.1 Rate and b-Value Maps for Single Zone and Two Zones 

Figures 6.4.1-1 through 6.4.1-9 show the mean recurrence maps for the three alternative 

configurations of the Mmax zones distributed seismicity source zones and the three choices of 

magnitude weights (i.e., Cases A, B, and E). Maps of the calculated uncertainties in recurrence 

parameters, as well as alternative recurrence maps that represent that uncertainty (eight 

alternative maps for each source-zone configuration), are shown in Appendix J. 

The maps in this section show more pixelation than the maps in Section 7. This is because the 

cell size had to be increased to half a degree to overcome computer run-time limitations. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-79

6.4.2 Comparison of Recurrence Parameters to Catalog 

Figures 6.4.2-1 through 6.4.2-15 compare the expected counts from the recurrence maps for each 

source zone to the observed earthquake counts within the zone. The error bars on the data 

represent the 16–84 percent range of statistical uncertainty in the counts and are calculated using 

the approach by Weichert (1980). Each of the eight curves represents expected counts (i.e., rate 

times equivalent period of completeness) for one of the eight equally weighted alternative maps, 

taking Mmax into account. 

These comparisons indicate a good agreement between predicted and observed rates. The only 

exception is the MESE-N source zone, for which the recurrence model has a slight tendency to 

underestimate the rates for magnitude 5.7 and higher. This is the result of deviations of the data 

from the exponential magnitude distribution. The actual discrepancy is smaller than it appears in 

the figures. If one were to consider the effect of uncertainty in Mmax on the recurrence curves, 

the curves would spread out at these higher magnitudes, with some of the curves coming closer 

to the data. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-80

Table 6.1-1 

Summary of Data Used to Assess RLME Recurrence Frequencies 

RLME Source Recurrence Method Recurrence Data

Charlevoix

Earthquake recurrence intervals

Equation 5.3.3-4

Data Set 1

N = 1, 

0

1

tt

N

i

i

= 348 yr

Earthquake count in a time interval

Equation 5.3.3-2

Data Set 2

N = 3, T uniformly distributed between 6 and 7 kyr

Data Set 3

N = 4, T uniformly distributed between 9.5 and10.2 kyr

Charleston

Earthquake recurrence intervals

Equation 5.3.3-4 for Poisson case

Equation 5.3.3-9 for renewal model case

Earthquake data defining intervals

1886 Earthquake

Earthquake A: 95% interval on Con age 523 to 618 yr BP

95% interval on All age 523 to 617 yr BP

Earthquake B: 95% interval on Con age 910 to 1,063 yr BP

95% interval on All age 920 to 1,065 yr BP

Earthquake C: 95% interval on Con age 1,569 to 1,854 yr BP

95% interval on All age 1,637 to 1,888 yr BP

Earthquake D: 95% interval on Con age 3,338 to 3,684 yr BP

95% interval on All age 3,334 to 3,642 yr BP

Earthquake E: 95% interval on Con age 4,868 to 5,277 yr BP

95% interval on All age 4,924 to 5,320 yr BP
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-81

RLME Source Recurrence Method Recurrence Data

Cheraw Fault

Earthquake recurrence intervals

Equation 5.3.3-4

In-cluster data

N = 1 or 2, 

0

1

tt

N

i

i

uniformly distributed between 20 and 25 kyr

Out-of-cluster assessment

200, 350, or 500 kyr cluster recurrence interval 

Slip rate

Equation 5.3.3-5

In-cluster data

D uniformly distributed between 3.2 and 4 m; T uniformly distributed 

between 20 and 25 kyr

Out-of-cluster data

D uniformly distributed between 3.2 and 8 m; T between 0.4 and 2 Myr 

(uniformly distributed between 1.2 and 2.0 Myr, tapering to 0 at 0.4 

Myr)

Meers Fault Earthquake recurrence intervals

Equation 5.3.3-4

In-cluster data

N = 1, 

0

1

tt

N

i

i

uniformly distributed between 2,153 and 2,968 yr

Out-of-cluster assessment

200, 350, or 500 kyr cluster recurrence interval

New Madrid 

Fault System 

Earthquake recurrence intervals 

Equation 5.3.3-4 for Poisson case

Equation 5.3.3-9 for renewal model case

Earthquake data defining in-cluster intervals

1811-1812 earthquake sequence

AD 1450 earthquake sequence: 95% interval on age 461 to 523 yr BP

AD 900 earthquake sequence: 95% interval on age 979 to 1,147 yr BP

Out-of-cluster data

N = 1, 

0

1

tt

N

i

i

= 4,000 yr
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-82

RLME Source Recurrence Method Recurrence Data

Eastern Rift 

Margin—South 

Earthquake count in a time interval

Equation 5.3.3-2

N = 1, 2, or 3, T uniformly distributed between 17.7 and 21.7 kyr

Eastern Rift 

Margin—North 

Earthquake count in a time interval

Equation 5.3.3-2

N = 1 or 2, T uniformly distributed between 12 and 35 kyr

Marianna Earthquake recurrence intervals 

Equation 5.3.3-4

N = 2 or 3, 

0

1

tt

N

i

i

uniformly distributed between 9.6 and 10.2 kyr

Commerce Fault 

Zone

Earthquake recurrence intervals 

Equation 5.3.3-4

N = 1 or 2, 

0

1

tt

N

i

i

uniformly distributed between 18.9 and 23.6 kyr

Wabash Valley Earthquake recurrence intervals 

Equation 5.3.3-4

N = 1, 

0

1

tt

N

i

i

uniformly distributed between 11 and 13 kyr
6-83

Table 6.1.1-1 

Charlevoix RLME Recurrence Frequency 

RLME Frequency

(earthquakes/year)

Data Set 1 Data Set 2 Data Set 3 Weight

9.3E-03 1.3E-03 9.8E-04 0.101

6.7E-03 8.4E-04 6.7E-04 0.244

4.2E-03 5.7E-04 4.7E-04 0.310

2.2E-03 3.7E-04 3.2E-04 0.244

7.7E-04 1.9E-04 1.8E-04 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-84

Table 6.1.2-1 

Summary of Interpreted Charleston Earthquake Ages and Sizes from 

―Contemporary Ages Only‖ Scenario 

Earthquake

Age

(years BP)

No. of 

Constraining 

Features

No. of 

Constraining 

Ages

SW-NE 

Extent

(km)

Dist. to 

Energy 

Center

(km)*

Assessment: 

Regional or 

Local?

1886 64 — 200 100 Regional

A 536–655 6 7 190 110 Regional

B 982–1,046 7 12 175 110 Regional

C 1,524–1,867 5 5 160 150 Regional

D 3,472–3,559 5 7 100 100 Local?

E 4,864–5,281 1 1 — 90 Local?

* Assumes approximate center of 1886 Charleston meizoseismal area as energy center. 

Table 6.1.2-2 

Summary of Interpreted Charleston Earthquake Ages and Sizes from ―All Ages‖ Scenario 

Earthquake

Age

(years BP)

No. of 

Constraining

Features

No. of 

Constraining 

Ages

SW-NE 

Extent 

(km)

Dist. to 

Energy 

Center

(km)*

Assessment: 

Regional or 

Local?

1886 64 — — 200 100 Regional

A 536–655 6 7 190 110 Regional

B 982–1,046 8 14 175 110 Regional

C 1,569–1,867 6 7 250 150 Regional

D 3,472–3,559 6 9 190 100 Regional

E 4,821–5,281 2 3 80? 90 Local?

* Assumes approximate center of 1886 Charleston meizoseismal area as energy center. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-85

Table 6.1.2-3 

Charleston Liquefaction Feature Ages Used to Assess Ages of Prehistoric Earthquakes 

Prehistoric 

Earthquake Site ID Age Type*

Minimum Age

(yr BP)

Maximum Age

(yr BP)

A BLUF-C-11 CON 316 680

A BLUF-B-8 CON 475 655

A BLUF-A-4 CON 307 905

A BLUF-A-7 CON 316 678

A HLYD-125 CON 536 680

A SP-SPN CON 317 667

B CG-1 CON 796 1174

B HLYD-XVII CON 662 1356

B HLYD-XIV CON 982 1291

B SP-SPMR-1 CON 690 1056

B SP-SPMR-2 CON 687 1691

B SP-BWL CON 741 1049

B GTWN-A CON 663 1315

B SP-BWR A 766 1053

B SP-BWR B 1141 1383

C FHS-1 CON 1524 1867

C SP-SPS CON 1178 2148

C OLN-A CON 794 2679

C MM-1 CON 1400 2303

C MB-3 CON 1145 2306

C BLUF-A-5 A 1569 1969

C BLUF-A-5 B 2001 2331

D BLUF-D-14 CON 2880 3835

D BLUF-D-15 CON 2965 3680

D TMH-A CON 2045 4416

D TMH-C CON 3415 4075

D TMH-ARP CON 3215 3845

D GPWY-A A 1870 2152

D GPWY-A B 3450 3827

E GPWY-D CON 4864 5281

E TMH-D A 4821 6176

E TMH-D B 5045 8189

* CON = Contemporary with earthquake; B = before earthquake; A = after earthquake 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-86

Table 6.1.2-4 

Charleston RLME Recurrence Frequency for Poisson Model 

RLME Frequency

(earthquakes/year)

Weight

Post-2,000 

yrs

Earthquakes 

1886, A, B, 

and C

Post-5,500 

yrs

Earthquakes 

1886, A, B, 

and C

Post-5,500 

yrs

Earthquakes 

1886, A, B, C, 

and D

Post-5,500 

yrs

Earthquakes 

1886, A, B, C, 

and E

Post-5,500 

yrs

Earthquakes 

1886, A, B, C, 

D, and E

4.7E-03 4.7E-03 2.7E-03 1.9E-03 2.2E-03 0.101

3.1E-03 3.1E-03 1.9E-03 1.3E-03 1.5E-03 0.244

2.1E-03 2.1E-03 1.3E-03 9.2E-04 1.1E-03 0.310

1.3E-03 1.3E-03 8.8E-04 6.4E-04 7.8E-04 0.244

6.8E-04 6.8E-04 5.0E-04 3.4E-04 4.6E-04 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-87

Table 6.1.2-5 

Charleston RLME Recurrence Frequency for Renewal Model 

RLME Frequency

(earthquakes/year)

Weight

Post-2,000 

yrs

Earthquakes 

1886, A, B, 

and C

Post-5,500 

yrs

Earthquakes 

1886, A, B, 

and C

Post-5,500 yrs

Earthquakes 

1886, A, B, C, 

and D

Post-5,500 

yrs

Earthquakes 

1886, A, B, C, 

and E

Post-5,500 

yrs

Earthquakes 

1886, A, B, C, 

D, and E

α = 0.3

6.4E-05 6.8E-05 3.5E-07 4.5E-09 1.5E-08 0.101

7.6E-06 8.0E-06 2.5E-08 2.0E-10 8.7E-10 0.244

9.5E-07 1.0E-06 2.2E-09 1.2E-11 7.0E-11 0.310

8.5E-08 9.2E-08 1.4E-10 5.4E-13 4.4E-12 0.244

2.3E-09 2.5E-09 2.7E-12 6.4E-15 8.2E-14 0.101

α = 0.5

1.4E-03 1.4E-03 2.2E-04 5.2E-05 7.0E-05 0.101

3.8E-04 3.9E-04 4.5E-05 8.2E-06 1.3E-05 0.244

9.5E-05 9.8E-05 9.3E-06 1.4E-06 2.5E-06 0.310

1.7E-05 1.7E-05 1.4E-06 1.7E-07 3.7E-07 0.244

1.0E-06 1.1E-06 7.6E-08 7.0E-09 2.1E-08 0.101

α = 0.7

2.6E-03 2.7E-03 1.0E-03 5.2E-04 5.7E-04 0.101

9.8E-04 9.9E-04 3.3E-04 1.4E-04 1.6E-04 0.244

3.2E-04 3.3E-04 9.5E-05 3.4E-05 4.5E-05 0.310

7.1E-05 7.3E-05 2.0E-05 6.1E-06 9.2E-06 0.244

5.6E-06 5.8E-06 1.5E-06 3.9E-07 7.6E-07 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-88

Table 6.1.3-1 

Range of Cheraw Fault Estimated Magnitudes (M) 

Approach Rupture Length1

Max. 

Displacement2

Average 

Displacement3 Rupture Area4 Rupture Area5

Parameter 

Value

30 km

(18.5 mi.)

46 km

(28.5 mi.)

1.6 m

(5.2 ft.)

2.6 m

(8.5 ft.)

1.1 m

(3.6 ft.)

2.1 m

(6.9 ft.)

430 

km2

(L = 

30 km

SD = 

13 km

Dip = 

65°)

1,020 

km2

(L = 

46 km

SD = 

17 km

Dip = 

50°)

1,321 

km2

(L = 

46 km

SD = 

22 km

Dip = 

50°)

430 km2

(30 km ×

14.3 km)

(assumes 

65° dip)

1,020 

km2

(L = 

46 km

SD = 

17 km

Dip = 

50°)

1,321 

km2

(L = 

46 km

SD = 

22 km

Dip = 

50°)

Estimated 

Magnitude 

(M)

6.6/6.6 6.9/6.9 6.8/6.8 6.9/7.0 6.8/7.0 7.0/7.2 6.6/6.7 7.0/7.0 7.1/7.1 7.0 7.4 7.5

1 Wells and Coppersmith (1994)—Subsurface rupture length (km) to magnitude (M), normal fault/all types 

2 Wells and Coppersmith (1994)—Maximum displacement (m) to magnitude (M), normal fault/all types 

3 Wells and Coppersmith (1994)—Average displacement (m) to magnitude (M), normal fault/all types 

4 Wells and Coppersmith (1994)—Area (km2) to magnitude, normal fault/all types 

5 Somerville et al. (2001)—Area (km2) to magnitude 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-89

Table 6.1.3-2 

Cheraw RLME In-Cluster Recurrence Frequency 

RLME Frequency

(earthquakes/year)

Weight

2 Earthquakes 

in 20–25 ka

3 Earthquakes 

in 20–25 ka

2.4E-04 3.1E-04 0.101

1.3E-04 1.9E-04 0.244

7.6E-05 1.2E-04 0.310

3.8E-05 7.2E-05 0.244

1.4E-05 3.2E-05 0.101

Table 6.1.3-3 

Cheraw RLME In-Cluster Slip Rates 

RLME Fault Slip Rate

(mm/year) Weight

0.14 0.185

0.16 0.630

0.19 0.185
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-90

Table 6.1.3-4 

Cheraw RLME Out-of-Cluster Recurrence Frequency 

RLME Frequency

(earthquakes/year) Weight

5.0E-06 0.333

2.9E-06 0.334

2.0E-06 0.333

Table 6.1.3-5 

Cheraw RLME Out-of-Cluster Slip Rates 

RLME Fault Slip Rate

(mm/year) Weight

0.0038 0.101

0.0043 0.244

0.0054 0.310

0.0072 0.244

0.011 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-91

Table 6.1.4-1 

Range of Estimated Meers Fault Earthquake Magnitudes (M) 

Approach Rupture Length Max. Displacement

Average 

Displacement Rupture Area

Parameter 

Value

26 km 

(16 mi.)

37 km 

(23 mi.)

67 km 

(42 mi.)

3.5 m 

(12 ft.)

5.25 m 

(17.2 ft.)

1.75 m 

(5.74 ft.)

3.0 m 

(9.8 ft.)

390 km2

(151 mi.

2

)

1,150 km2

(444 mi.

2

)

Estimated 

Magnitude (M) ~6.7 ~6.9 ~7.1 7.1–7.2 7.2–7.4 7.1–7.3 7.3–7.5 6.6–7.0 7.1–7.4

Table 6.1.4-2 

Meers RLME In-Cluster Recurrence Frequency 

RLME Frequency

(earthquakes/year) Weight

2.1E-03 0.101

1.2E-03 0.244

6.7E-04 0.310

3.4E-04 0.244

1.2E-04 0.101

Table 6.1.4-3 

Meers RLME Out-of-Cluster Recurrence Frequency 

RLME Frequency

(earthquakes/year) Weight

5.0E-06 0.333

2.9E-06 0.334

2.0E-06 0.333
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-92

Table 6.1.5-1 

Preferred Ages for Paleoearthquakes in the New Madrid Region1

AD 1811-1812

500 yr BP ± 150 yr (350–650 yr BP)

1,050 yr BP ± 150 yr (900–1,200 yr BP)

2,750 yr BP ± 150 yr; sand blow of this age at only one site (Eaker 2); sand 

dike at Porter Gap (2,600–2,900 yr BP)

2,902 yr BP ± 2,138 yr; possibly same as Holbrook’s event ~1000 BC or 

2,514–3,560 yr BP

4,300 yr BP ± 150 yr (4,150–4,450 yr BP)

1

 Age in years BP, relative to AD 1950 (see Appendix E) 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-93

Table 6.1.5-2 

Magnitude Comparisons for New Madrid 1811-1812 Earthquake Sequence 

Study NM1 NM2 NM3

Johnston (1996b) M 8.1 ± 0.3 M 7.8 ± 0.3 M 8.0 ± 0.3 

Johnston (pers. comm., 

Aug. 31, 2004) 

M 7.8–7.9 M 7.5–7.6 M 7.7–7.8 

Johnston (pers. comm., 

Feb. 16, 2010) 

Currently has no new information that would change his previous estimates. 

He noted that he is disillusioned with using intensity data to estimate 

moment magnitude and thinks that overinterpretation of the data using site 

correction, etc. is a problem.

Bakun and Hopper 

(2004b)

MI 7.6 

(M 7.2–7.9)

(preferred model 3) 

MI 7.5 

(M 7.1–7.8)

(preferred model 3)

MI 7.8 

(M 7.4–8.1)

(preferred model 3) 

MI 7.2 

(M 6.8–7.9)

(model 1) 

MI 7.2 

(M 6.8–7.8)

(model 1) 

MI 7.4 

(M 7.0–8.1) 

(model 1) 

Bakun (electronic 

comm., Feb. 3, 2010—

no change, use entire 

range of uncertainty 

cited in Bakun and 

Hopper, 2004b)

M 6.8–7.9 M 6.8–7.8 M 7.0–8.1

Hough et al. (2000) M 7.2–7.3 (using 

isoseismal method of 

Johnston, 1996)

M 7.0–7.3(using 

method of Bakun and 

Wentworth, 1997)1

M ~ 7.012(located on 

the New Madrid North 

fault) (using isoseismal 

method of Johnston, 

1996)

M 7.4–7.5 (using 

isoseismal method of 

Johnston, 1996)

Mueller and Pujol (2001) – – M 7.2–7.4

(preferred M 7.2–7.3) 

Mueller et al. (2004) M 7.3 M 6.8 (located within the 

Wabash Valley of 

southern Illinois/ 

southern Indiana) 

M 7.5 

Hough and Page (2011) M 6.69/6.85 (min) to 

M 6.85/7.08 (max)

(full range of experts)

M 6.7 (model 1)/6.9 

(model 3)

3

M 6.72/6.86 (min) to 

M 6.91/7.09 (max)

(full range of experts)

M 6.8 (model 1)/7.0 

(model 3) (NM location)

3

M 6.5 (model 1)/6.7 

(model 3) (IL location 

near 1968 event) 3

M 6.83/7.02 (min) to 

M 7.21/7.50 (max)

(full range of experts)

M 7.1 (model 1)/7.3 

(model 3)

3

Scaling relationships

M 6.8 (assume 35 km 

length, 15 km width, 1 m 

slip) 

1

 Based on intensity values reported in Hough et al. (2000) and Bakun and Wentworth (1997) method as noted in 

Hough and Page (2011). 

2

 The estimated location and magnitude of this earthquake are revised in Mueller et al. (2004). 

3

 Using method of Bakun and Wentworth (1997) and published attenution models; following Bakun et al. (2003) 

and Bakun and Hopper (2004) these are referred to as models 1 and 3. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-94

Table 6.1.5-3 

Liquefaction Constraints on Age of AD 1450 NMFS RLME 

Liquefaction 

Feature

Maximum Age

(years before 

1/1/2011)

Minimum Age

(years before 

1/1/2011)

Age of AD 1450 RLME

(years before 1/1/2011)*

351 471 511 556 561 571 590 601

Tyr01-01 711 211

MarkedT01-01 591 511 X X X

MarkedT01-03 591 511 X X X

HatchieR31-02 1551 221

Nodena01-01 561 341 X X X

KochD01-01 1021 351

LittleR09-02 696 466 X

Eaker01-01 601 271

Yarbro01-01 591 341 X

Yarbro03-03 591 341 X

Crav01-01 601 331

ObionR216-02 811 611 X X X X X X X X

Dodd01-01 721 556 X X X

Cagle01-01 591 321 X

ObionR200-02 711 591 X X X X X X X

CurrentR02-01 701 561 X X X X

Wilhelmina01-05 571 471 X X X

No. of Samples with Age Range Outside of Specific Age 8 6 4 3 2 3 4 8

* X indicates sample age range does not include specified date. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-95

Table 6.1.5-4 

Liquefaction Constraints on Age of AD 900 NMFS RLME 

Liquefaction 

Feature

Maximum Age

(years before 

1/1/2011)

Minimum Age

(years before 

1/1/2011)

Age of AD 900 RLME

(years before 1/1/2011)*

801 1011 1021 1131 1211 1221

CentralD01-01 1221 771

Eaker03-01 1211 611 X

Eaker03-03 1211 611 X

Eaker02-01 1541 1011 X

Bugg01-01 1211 1011 X X

Hueys01-01 1211 1011 X X

Haynes01-02 1211 611 X

Arch01-01 1351 801

Dill01-01 1101 521 X X X

NewFrnk03-01 1221 1021 X X

NewFrnk04-01 1371 1131 X X X

Johnson05-01 1211 1011 X X

Wilhelmina01-03 1236 1106 X X X

Tow01-01 1472 1020 X X

HillH01-01 1221 1011 X

No. of Samples with Age Range Outside of Specific Age 9 4 2 1 1 7

* X indicates sample age range does not include specified date. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-96

Table 6.1.5-5 

NMFS In-Cluster RLME Recurrence Frequency—Poisson Model 

RLME Frequency

(earthquakes/year) Weight

6.0E-03 0.101

3.7E-03 0.244

2.4E-03 0.310

1.4E-03 0.244

6.2E-04 0.101

Table 6.1.5-6 

NMFS In-Cluster RLME Recurrence Frequency—Renewal Model 

RLME Frequency

(earthquakes/year)

α = 0.3 α = 0.5 α = 0.7 Weight

3.5E-03 4.8E-03 4.4E-03 0.101

1.1E-03 2.2E-03 2.2E-03 0.244

3.2E-04 8.9E-04 1.0E-03 0.310

6.4E-05 2.6E-04 3.4E-04 0.244

4.7E-06 3.1E-05 4.7E-05 0.101

Table 6.1.5-7 

NMFS Out-of-Cluster RLME Recurrence Frequency—Poisson Model 

RLME Frequency

(earthquakes/year) Weight

1.3E-03 0.101

7.2E-04 0.244

4.2E-04 0.310

2.2E-04 0.244

8.0E-05 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-97

Table 6.1.6-1 

Range of ERM-S Estimated Magnitudes (M) 

Approach Rupture Length1

Max. 

Displacement2

Average 

Displacement3 Rupture Area4 Rupture Area5

Parameter 

Value

≤80 km 

(50 mi.)

114 km

(71 mi.)

0.5 m

(1.5 ft.)

2.1 m

(6.9 ft.)

0.5 m

(1.5 ft.)

2.1 m

(6.9 ft.)

≤1,040

km2

(L ≤ 

80 km 

SD =

13 km)

1,215 

km2

(L =

80 km 

SD =

15 km)

1,938

km2

(L =

114 km,

SD =

17 km)

≤1,040

km2

(L ≤ 

80 km 

SD =

13 km)

1,215 

km2

(L =

80 km

SD =

15 km)

1,938

km2

(L=

114 km,

SD =

17 km)

Estimated 

Magnitude 

(M)

≤7.2/7.2 7.4/7.4 6.6/6.5 7.1/6.9 6.8/6.7 7.3/7.2 ≤7.1/7.0 7.1/7.1 7.3/7.3 ≤7.4 7.4 7.6

1

 Wells and Coppersmith (1994)—Subsurface rupture length (km) to magnitude (M), strike-slip/all types 

2

 Wells and Coppersmith (1994)—Maximum displacement (m) to magnitude (M), strike-slip/all types 

3

 Wells and Coppersmith (1994)—Average displacement (m) to magnitude (M), strike-slip/all types 

4

 Wells and Coppersmith (1994)—Area (km2

) to magnitude, strike-slip/all types 

5

 Somerville et al. (2001)—Area (km2) to magnitude 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-98

Table 6.1.6-2 

Range of ERM-N Estimated Magnitudes (M) 

Approach

Rupture 

Length1 Rupture Area2 Rupture Area3

Parameter 

Value

≤73 km

(45.5 mi.)

≤949 km2

(L = 73 km,

SD = 13 km)

1,095 km2

(L = 73 km,

SD = 15 km)

1,241 km2

(L = 73 km,

SD = 17 km)

≤949 km2

(L = 73 km,

SD = 13 km)

1,095 km2

(L = 73 km,

SD = 15 km)

1,241 km2

(L = 73 km,

SD = 17 km)

Estimated 

Magnitude (M)

≤7.1/7.2 ≤7.0/7.0 7.1/7.1 7.1/7.1 ≤7.3 7.4 7.4

1

 Wells and Coppersmith (1994)—Subsurface rupture length (km) to magnitude (M), strike-slip/all types 

2

 Wells and Coppersmith (1994)—Area (km2) to magnitude, strike-slip/all types 

3

 Somerville et al. (2001)—Area (km2) to magnitude 

Table 6.1.6-3 

ERM-S RLME Recurrence Frequency 

RLME Frequency

(earthquakes/year)

Weight

2 Earthquakes in 

17.7–21.7 kyr

3 Earthquakes in 

17.7–21.7 kyr

4 Earthquakes in 

17.7–21.7 kyr

3.5E-04 4.3E-04 5.0E-04 0.101

2.1E-04 2.8E-04 3.4E-04 0.244

1.4E-04 1.9E-04 2.4E-04 0.310

8.0E-05 1.2E-04 1.6E-04 0.244

3.6E-05 6.2E-05 9.0E-05 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-99

Table 6.1.6-4 

ERM-N RLME Recurrence Frequency 

RLME Frequency

(earthquakes/year)

Weight

1 Earthquake in 

12–35 kyr

2 Earthquakes 

in 12–35 kyr

2.9E-04 3.9E-04 0.101

1.5E-04 2.2E-04 0.244

8.0E-05 1.3E-04 0.310

4.0E-05 7.2E-05 0.244

1.4E-05 3.2E-05 0.101

Table 6.1.7-1 

Marianna RLME Recurrence Frequency 

RLME Frequency

(earthquakes/year)

Weight

3 Earthquakes 

in 9.6–10.2 kyr

4 Earthquakes 

in 9.6–10.2 kyr

6.9E-04 8.4E-04 0.101

4.2E-04 5.5E-04 0.244

2.7E-04 3.7E-04 0.310

1.6E-04 2.4E-04 0.244

7.2E-05 1.2E-04 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-100

Table 6.1.8-1 

Range of Commerce Fault Zone RLME Estimated Magnitudes (M) 

Approach Rupture Length1

Max. 

Displacement2

Average 

Displacement3 Rupture Area4 Rupture Area5

Parameter 

Value

≤55 km

(34 mi.)

120 km

(75 mi.)

2.0 m

(6.6 ft.)

2.2 m

(6.9 ft.)

2.0 m

(6.6 ft.)

2.2 m

(6.9 ft.)

≤715

km2

(L ≤ 

55 km,

SD =

13 km)

975 km2

(L = 

65 km,

SD =

15 km)

2.040

km2

(L = 

120 km,

SD =

17 km)

≤715

km2

(L ≤

55 km,

SD =

13 km)

975 km2

(L = 

65 km,

SD =

15 km)

2,040

km2

(L = 

120 km,

SD =

17 km)

Estimated 

Magnitude 

(M)

≤6.9/7.0 7.4/7.5 7.0/6.9 7.1/6.9 7.3/7.2 7.3/7.2 ≤6.9/6.9 7.0/7.0 7.4/7.3 ≤7.2 7.3 7.7

1

 Wells and Coppersmith (1994)—Subsurface rupture length (km) to magnitude (M), strike-slip/all types 

2

 Wells and Coppersmith (1994)—Maximum displacement (m) to magnitude (M), strike-slip/all types 

3

 Wells and Coppersmith (1994)—Average displacement (m) to magnitude (M), strike-slip/all types 

4

 Wells and Coppersmith (1994)—Area (km2) to magnitude, strike-slip/all types 

5

 Somerville et al. (2001)—Area (km2) to magnitude 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-101

Table 6.1.8-2 

Commerce Fault Zone RLME Recurrence Frequency 

RLME Frequency

(earthquakes/year)

Weight

2 Earthquakes in 

18.9–23.6 kyr

3 Earthquakes 

in 18.9–23.6 kyr

2.5E-04 3.3E-04 0.101

1.4E-04 2.0E-04 0.244

8.0E-05 1.3E-04 0.310

4.0E-05 7.6E-05 0.244

1.4E-05 3.4E-05 0.101
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-102

Table 6.1.9-1 

Liquefaction Evidence for Prehistoric Earthquakes in the Southern Illinois Basin 

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

Lower Wabash Valley

VincennesBridgeport ~25 km (~15 

mi.) west of 

Vincennes, 

Indiana

≥0.5 m (≥1.6 ft.) dike 

width; 115 km (71.5 mi.) 

minimum to 153 km 

(95 mi.) maximum 

distance from inferred 

energy center

~6,100 200 yr 

BP

M 7.5–7.8 

(magnitude-bound, cyclic stress, and 

energy stress methods) 

Munson et al. 

(1997)

Obermeier (1998)

Obermeier et al. 

(1993) 

M 7.8 

(energy-stress)2

Pond and Martin 

(1997)

M 7.1–7.3

(updated magnitude-bound curve)

Olson et al. 

(2005b)

M ~ 7.5 (back-calculated ground 

motion characteristics from 

paleoliquefaction effects)

Green et al. 

(2005)

M 7.99 ± 0.27 (preliminary results—

probabilistic approach using magnitude 

bounds and back-calculations to 

address uncertainties). 

Olson et al. 

(2007)
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-103

Table 6.1.9-1 (continued)

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

M ~ 7.5 ± 0.3

Prior distribution from magnitudebound method combined with 

likelihood function from sites of 

observed liquefaction (or no 

liquefaction) to yield posterior 

distribution. Considers uncertainties in 

back-calculation analyses.

Olson (2009)

≥M 7.0 (115 km epicentral distance);

≥M 7.3 (153 km epicentral distance);

(minimum magnitude-bound curve)

Castilla and 

Audemard (2007)

Skelton ~40 km (~25 

mi.) SW of 

Vincennes, 

Indiana

≥0.5 m (≥1.6 ft.) dike 

width; 50–60 km (31–37 

mi.) maximum distance 

from inferred energy 

center

~12,000 

1,000 yr BP

M ~ 7.1 

(summary of magnitude-bound and 

geotechnical analysis results)

Hajic and Wiant 

(1997)

Obermeier (1998)

M 7.1–7.3 (magnitude bound) Munson et al. 

(1997)

M 7.3 (energy stress)2

Pond and Martin 

(1997)

M 6.7 (updated magnitude bound) Olson et al. 

(2005b

≥ M 6.3 (63 km epicentral distance);

(minimum magnitude-bound curve)

Castilla and 

Audemard (2007)

Single site near 35 km (22 mi.) Very small and restricted 4,000 500 yr Near threshold Munson et al. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-104

Table 6.1.9-1 (continued)

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

Iona, Indiana SE of 

Vincennes, 

Indiana, near 

Iona

(probably limited to 5 km 

[3.1 mi.])

BP (M ~ 5.5–6.0 to <6.7) (1997)

Obermeier (1998)

Central and Southern Indiana

Vallonia East Fork 

valley ~100 km 

(~62 mi.) east 

of the Wabash 

Valley seismic 

zone 

≥0.5 m (1.5 ft.); 36 km 

(22.5 mi.) maximum 

distance from inferred 

energy center

3,950 250 yr 

BP

M ≥ 6.9 (magnitude bound) Munson et al. 

(1997)

Obermeier (1998)

M 7.1 (energy stress)2

Pond and Martin 

(1997)

M 6.3 (updated magnitude bound) Olson et al. 

(2005b)

≥ M 5.7 (36 km epicentral distance);

(minimum magnitude-bound curve)

Castilla and 

Audemard (2007)

MartinsvilleWaverly~30–50 km 

(~18–30 mi.) 

SW of 

Indianapolis, 

Indiana 

(location poorly 

constrained)

≥0.15 to ≤0.5 m (≥5 to 

≤1.6 ft.); 28 km (17.5 mi.) 

maximum distance from 

inferred energy center

Geotechnical analyses 

demonstrate that these 

features are not 

associated with the 

M ~ 7.5 Vincennes 

Between 8,500 

and 3,500 yr 

BP

M 6.8 (magnitude bound) Munson et al. 

(1997)

Obermeier (1998)

M 6.9 (energy stress)2

Pond and Martin 

(1997)

M 6.2 (updated magnitude bound) Olson et al. 

(2005b)
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-105

Table 6.1.9-1 (continued)

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

earthquake ≥ M 5.5 (28 km epicentral distance);

(minimum magnitude-bound curve)

Castilla and 

Audemard (2007)

Single site near 

Elnora, Indiana

60 km (37 mi.) 

E-NE of 

Vincennes 

Limited areal extent 2,000 500 yr 

BP

M ≥ 5.5–6.0 Munson et al. 

(1997)

Obermeier (1998)

Single site along 

Indian Creek, 

Indiana

~50 km (~31 

mi.) S-SW of 

Indianapolis 

Single site ~20,000 yr BP Unknown Munson et al. 

(1997)

Obermeier (1998)

Ohio River region—Absence of paleoliquefaction in Ohio River sediments along the Indiana-Kentucky and Illinois-Kentucky borders suggests that 

this area has not experienced severe ground shaking in the past 4,500 years (Munson et al., 1997). However, Munson et al. (1997) suggest that a 

5–6 m (16.4–19.7 ft.) thick clay cap may have kept sand dikes from penetrating to levels above the current maintained water level of the Ohio 

River.

Central and Southern Illinois

Springfield ~35 km (~22 

mi.) NE of 

Springfield, 

Illinois

Maximum dike width 0.4 m 

(1.3 ft.); 35 km (22 mi.) 

maximum distance from 

inferred energy center

One, possibly 

two, events 

between 5,960 

± 60 yr BP and 

7,380 ± 90 yr 

BP

M 6.2–6.8

M 5.5 (second event)

Hajic et al. (1995)

McNulty and 

Obermeier (1999)

M 6.2 (updated magnitude bound) Olson et al. 

(2005b)

≥ M 5.7 (35 km epicentral distance);

(minimum magnitude-bound curve)

Castilla and 

Audemard (2007)
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-106

Table 6.1.9-1 (continued)

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

Shoal Creek 

(Germantown, 

Illinois)

Centered in 

vicinity of lower 

Shoal Creek 

near its 

confluence with 

Kaskaskia 

River:

~65 km (~40 

mi.) E-SE of St. 

Louis, Missouri. 

Alternative 

location: 

Centralia fault 

(Du Quoin 

monocline)

Maximum dike width 1.55 

m (5 ft.); 35 km (22 mi.) 

maximum distance from 

inferred energy center

~5,670 80 yr 

BP

4520 BC ± 200 

yr

M 6.5 (lower limit) McNulty and 

Obermeier (1999)

M 6.2 (updated magnitude bound) Olson et al. 

(2005b)

≥ M 5.7 (35 km epicentral distance);

(minimum magnitude-bound curve)

Castilla and 

Audemard (2007)

Alternative scenarios:

M 7.0 (Shoal Creek)

M 7.5 (Centralia/Du Quoin)

Tuttle, Chester, et 

al. (1999)

Cache River Cache River 

from Sandusky 

to the 

Mississippi 

River

Dike width 1–9 cm

(0.4–3.5 in.)

Two ages: 

maximum age 

AD 1020–1250 

for younger and 

possibly older 

event(s) 

Age estimates 

of Middle 

Holocene 

liquefaction 

features are of 

poor quality 

(cannot 

preclude they 

could be 

associated with 

Unknown

Middle Holocene events could have 

formed as a result of a very large 

earthquake originating from a distant 

source such as the NMSZ or a smallermagnitude earthquake from a closer 

source such as the Commerce 

geophysical lineament. 

Chester and 

Tuttle (2000)

Tuttle (2005b)
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-107

Table 6.1.9-1 (continued)

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

the 4520 BC ±

200 yr (Shoal 

Creek) event).

n/a Big Muddy 

River 

No new sites identified. 

Geologic conditions not 

favorable for liquefaction.

n/a All paleoliquefaction dikes in the region 

could possibly be induced by 

paleoearthquakes that occurred near 

the potential seismogenic sources 

identified by reanalysis of seismic 

reflection data. Maximum possible 

magnitude for a basement-involved 

fault in the region is between M 6 and 

just above M 7.

Su and McBride 

(1999)

Southeastern Missouri

Big Muddy and 

Meramec rivers

~30 km (~20 

mi.) SW of St. 

Louis, Missouri 

Dikes 0.1–1 cm (.04–.4 in.) 

wide; maximum dike at 

MR25W site is 20 cm (7.9 

in.) wide

Big Muddy 

River: post9070 BC and 

possibly prior to 

4240 BC

Meramec 

River: post13,210 BC.

Several 

features are 

estimated to 

have formed 

during the late 

Holocene and 

Holocene. No 

Three scenarios:

Local, M > 5.2–6.0

Shoal Creek, M 7.0

Centralia fault, M 7.5

Results of liquefaction potential 

analysis (cyclic stress method using in 

situ geotechnical testing results for 

three possible source layers) showed 

that a local (M > 5.25–6.0) earthquake 

would induce liquefaction for the upper 

and middle layer; a M 6.75 earthquake 

in Germantown, Illinois (~80 km [~50 

mi.] from site) would not induce 

liquefaction in any layer; a M 7.5 along 

Centralia fault–Du Quoin monocline 

(~100 km [~62 mi.] from site) would 

Tuttle, Chester, et 

al. (1999)

Tuttle (2005b)
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-108

Table 6.1.9-1 (continued)

Inferred Energy 

Center for

Earthquake(s) Location

Size and Distribution 

of Features Age1

Estimated

Magnitude Reference(s)

liquefaction 

features have 

yet been 

attributed to the 

4,520 ± 200 yr 

BP (Shoal 

Creek) 

earthquake. 

Maximum age 

of 20 cm (7.9 

in.) wide dike at 

MR 25W site is 

4340–3990 BC. 

Stratigraphic

relations 

suggest it might 

be as young as 

800 BC.

induce liquefaction in the upper and 

middle layers; a M 7.8 along the same 

structure would induce liquefaction in 

all three layers; a M 8 earthquake 

produced by northern New Madrid fault 

would not induce liquefaction. 

1

 Ages given in yr BP are uncorrected radiocarbon ages.

2

 The energy-stress method used by Pond and Martin (1997) is flawed (energy attenuation relations used should not be used for liquefaction analysis and the 

results are not reliable [S. Obermeier, pers. comm., May 13, 2003]). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-109

Table 6.1.9-2 

Wabash RLME Recurrence Frequency 

RLME Frequency

(earthquakes/year) Weight

4.4E-04 0.101

2.5E-04 0.244

1.4E-04 0.310

7.2E-05 0.244

2.4E-05 0.101

Table 6.2-1 

Alternative Mmax Zonation Models 

Mesozoic Extended—Narrow Model Mesozoic Extended—Wide Model

MESE-N NMESE-N MESE-W NMESE-W

AHEX MidC-A AHEX MidC-D

ECC-AM IBEB ECC-AM OKA

ECC-GM OKA ECC-GM

GHEX GHEX

RR RR-RCG

SLR SLR

NAP NAP

GMH GMH

PEZ-N IBEB

PEZ-W
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-110

Table 6.3.2-1 

Maximum Magnitude Distributions for Mmax Distributed Seismicity Sources 

Weight Assigned to Mmax

Maximum Magnitude for:

Study Region MESE-N NMESE-N MESE-W NMESE-W

0.101 6.5 6.4 6.4 6.5 5.7

0.244 6.9 6.8 6.8 6.9 6.1

0.310 7.2 7.2 7.1 7.3 6.6

0.244 7.7 7.7 7.5 7.7 7.2

0.101 8.1 8.1 8.0 8.1 7.9
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-111

Figure 6.1-1 

Map showing the RLME sources characterized in the CEUS SSC model. Detailed alternatives to the source geometries are 

shown on figures associated with each RLME discussion. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-112

Figure 6.1-2a 

Map showing the RLME sources and seismicity from the CEUS SSC earthquake catalog. Some of the RLMEs occur in regions of 

elevated seismicity, but others do not. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-113

Figure 6.1-2b 

Close-up of the Wabash Valley and New Madrid/Reelfoot Rift RLME sources and seismicity from the CEUS SSC earthquake 

catalog. Some of the RLMEs occur in regions of elevated seismicity, but others do not. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-114

Figure 6.1.1-1 

Logic tree for the Charlevoix RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-115

Figure 6.1.1-2 

Seismicity and tectonic features of the Charlevoix RLME 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-116

Figure 6.1.1-3 

Magnetic and gravity anomaly maps of the Charlevoix RLME
SSC Model: RLME Source

Figure 6.1.2-1a Logic tree for the Charleston RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 6-118 

Figure 6.1.2-1b Logic tree for the Charleston RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-119

Figure 6.1.2-2 

Charleston RLME source zones with (a) total magnetic anomaly and (b) residual isostatic gravity data
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-120

Figure 6.1.2-3 

Postulated faults and tectonic features in the Charleston region
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-121

Figure 6.1.2-4 

Postulated faults and tectonic features in the local Charleston area
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-122

Figure 6.1.2-5a

Postulated faults and tectonic features in the Charleston region with Charleston RLME source zones
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-123

Figure 6.1.2-5b

Postulated faults and tectonic features in the local Charleston area with Charleston RLME source zones
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-124

Figure 6.1.2-6 

Schematic diagram showing contemporary, maximum, and minimum constraining age 

sample locations
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-125

Figure 6.1.2-7 

Charleston space-time diagram of earthquakes interpreted from paleoliquefaction, contemporary-ages-only scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-126

Figure 6.1.2-8 

Charleston space-time diagram of earthquakes interpreted from paleoliquefaction, all-ages scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-127

Figure 6.1.2-9 

Distribution of liquefaction from earthquake A, contemporary-ages-only scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-128

Figure 6.1.2-10

Distribution of liquefaction from earthquake B, contemporary-ages-only scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-129

Figure 6.1.2-11

Distribution of liquefaction from earthquake C, contemporary-ages-only scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-130

Figure 6.1.2-12

Distribution of liquefaction from earthquake D, contemporary-ages-only scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-131

Figure 6.1.2-13

Distribution of liquefaction from earthquake E, contemporary-ages-only scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-132

Figure 6.1.2-14

Distribution of liquefaction from earthquake A, all-ages scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-133

Figure 6.1.2-15

Distribution of liquefaction from earthquake B, all-ages scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-134

Figure 6.1.2-16

Distribution of liquefaction from earthquake C, all-ages scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-135

Figure 6.1.2-17

Distribution of liquefaction from earthquake D, all-ages scenario
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-136

Figure 6.1.2-18

Distribution of liquefaction from earthquake E, all-ages scenario 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-137

Figure 6.1.2-19 

Uncertainty distributions for the age of Charleston RLMEs 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-138

Figure 6.1.3-1 

Logic tree for the Cheraw fault RLME source
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-139

Figure 6.1.3-2 

Map (c) and hillshade relief images (a, b, and d) showing location of mapped Cheraw fault, possible northeast extension, and 

paleoseismic locality
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-140

Figure 6.1.3-3 

Cheraw RLME source relative to (a) total magnetic anomaly and (b) residual isostatic gravity data 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-141

Figure 6.1.4-1 

Meers fault location 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-142

Figure 6.1.4-2 

Logic tree for the Meers fault source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-143

Figure 6.1.5-1 

Logic tree for the NMFS RLME source
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-144

Figure 6.1.5-2 

Map showing seismicity and major subsurface structural features in the New Madrid region
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-145

Figure 6.1.5-3 

Map showing geomorphic and near-surface tectonic features in the New Madrid region and locations of NMFS RLME fault 

sources
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-146

Figure 6.1.5-4 

Rupture segments (a) and models (b) for the New Madrid faults from Johnston and Schweig (1996) and (c) the NMFS RLME fault 

sources
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-147

Figure 6.1.5-5 

Map of NMSZ showing estimated ages and measured sizes of liquefaction features
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-148

Figure 6.1.5-6 

Earthquake chronology for NMSZ from dating and correlation of liquefaction features at sites (listed at top) along N-S transect 

across region
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-149

Figure 6.1.5-7 

Probability distributions for the age of the AD 900 and AD 1450 NMFS RLMEs

0

0.005

0.01

0.015

0.02

0.025

0 200 400 600 800 1000 1200 1400

Earthquake Age (years before 1/1/2011)

Probability Density

AD 900

AD 1450

0

0.2

0.4

0.6

0.8

1

0 200 400 600 800 1000 1200 1400

Earthquake Age (years before 1/1/2011)

Cumulative Probability

AD 900

AD 1450
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-150

Figure 6.1.5-8 

Liquefaction fields for the 1811-1812, AD 1450, and AD 900 earthquakes as interpreted from spatial distribution and stratigraphy 

of sand blows 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-151

Figure 6.1.6-1a

Logic tree for the Reelfoot Rift–Eastern Rift Margin South RLME source. Two options for the southern extent of the ERM-S are 

considered: ERM-SCC includes the Crittenden County fault zone, and ERM-SRP includes the postulated zone of deformation 

based on fault picks identified in a high-resolution seismic profile along the Mississippi River. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-152

Figure 6.1.6-1b

Logic tree for the Reelfoot Rift–Eastern Rift Margin North RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-153

Figure 6.1.6-2 

Map showing structural features and paleoseismic investigation sites along the eastern margin of the Reelfoot rift. The inset 

map shows the locations of inferred basement faults that border and cross the Reelfoot rift (Csontos et al., 2008) and the 

inferred Joiner Ridge–Meeman-Shelby fault (JR-MSF; Odum et al., 2010).
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-154

Figure 6.1.6-3 

Maps showing surficial geology and locations of subsurface investigations at (a) Meeman-Shelby Forest State Park locality and 

(b) Union City site (MSF and UC on Figure 6.1.6-2). Modified from Cox et al. (2006) and Odum et al. (2010). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-155

Figure 6.1.6-4 

Figure showing the timing of events along the eastern Reelfoot rift margin. Modified from Cox (2009). 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-156

Figure 6.1.7-1 

Logic tree for the Reelfoot rift–Marianna RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-157

Figure 6.1.7-2 

Map showing tectonic features and locations of paleoliquefaction sites in the vicinity of Marianna, Arkansas 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-158

Figure 6.1.7-3 

Map showing liquefaction features near Daytona Beach lineament southwest of Marianna, Arkansas 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-159

Figure 6.1.8-1 

Logic tree for the Commerce Fault Zone RLME source
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-160

Figure 6.1.8-2 

Map showing tectonic features, seismicity, and paleoseismic localities along the Commerce Fault Zone RLME source
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-161

Figure 6.1.8-3 

Location of the Commerce geophysical lineament and Commerce Fault Zone RLME source relative to the (a) regional magnetic 

anomaly map and (b) regional gravity anomaly map 
Chapter 6 

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6-162

Figure 6.1.8-4 

Space-time diagram showing constraints on the location and timing of late Pleistocene 

and Holocene paleoearthquakes that may be associated with the Commerce Fault Zone 

RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-163

Figure 6.1.9-1 

Logic tree for the Wabash Valley RLME source 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-164

Figure 6.1.9-2 

Map showing seismicity, subsurface structural features, paleoearthquake energy centers, and postulated neotectonic 

deformation in the Wabash Valley region of southern Illinois and southern Indiana
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-165

Figure 6.1.9-3 

Wabash Valley RLME source relative to (a) magnetic anomaly, and (b) residual isostatic gravity data
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-166

Figure 6.2-1 

Map showing the two Mmax zones for the ―narrow‖ interpretation of the Mesozoic-and-younger extended zone
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-167

Figure 6.2-2 

Map showing the two Mmax zones for the ―wide‖ interpretation of the Mesozoic-and-younger extended zone
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-168

Figure 6.3.1-1 

Distributions for 

mmax obs

 for the Mmax distributed seismicity source zones 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-169

Study Region (Paleoearthquakes)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 1

Composite Distribution

Figure 6.3.2-1 

Mmax distributions for the study region treated as a single Mmax zone 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-170

MESE-N

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.06

Bayesian (COMP) weight = 0.376

Bayesian (MESE) weight = 0.564

Composite Distribution

Figure 6.3.2-2 

Mmax distributions for the MESE-N Mmax zone 
Chapter 6 

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6-171

MESE-W (Paleoearthquakes)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 6.3.2-3 

Mmax distributions for the MESE-W Mmax zone 
Chapter 6 

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6-172

NMESE-N (Paleoearthquakes)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (NMESE) weight = 0.6

Composite Distribution

Figure 6.3.2-4 

Mmax distributions for the NMESE-N Mmax zone 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-173

NMESE-W

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.23

Bayesian (COMP) weight = 0.308

Bayesian (NMESE) weight = 0.462

Composite Distribution

Figure 6.3.2-5 

Mmax distributions for the NMESE-W Mmax zone 
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6-174

Figure 6.4.1-1 

Mean map of rate and b-value for the study region under the source-zone configuration, with no separation of Mesozoic 

extended and non-extended; Case A magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-175

Figure 6.4.1-2 

Mean map of rate and b-value for the study region under the source-zone configuration, with no separation of Mesozoic 

extended and non-extended; Case B magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-176

Figure 6.4.1-3 

Mean map of rate and b-value for the study region under the source-zone configuration, with no separation of Mesozoic 

extended and non-extended; Case E magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-177

Figure 6.4.1-4 

Mean map of rate and b-value for the study region under the source-zone configuration, with separation of Mesozoic extended 

and non-extended, narrow geometry for MESE; Case A magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-178

Figure 6.4.1-5 

Mean map of rate and b-value for the study region under the source-zone configuration, with separation of Mesozoic extended 

and non-extended, narrow geometry for MESE; Case B magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-179

Figure 6.4.1-6 

Mean map of rate and b-value for the study region under the source-zone configuration, with separation of Mesozoic extended 

and non-extended, narrow geometry for MESE; Case E magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-180

Figure 6.4.1-7 

Mean map of rate and b-value for the study region under the source-zone configuration, with separation of Mesozoic extended 

and non-extended, wide geometry for MESE; Case A magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-181

Figure 6.4.1-8 

Mean map of rate and b-value for the study region under the source-zone configuration, with separation of Mesozoic extended 

and non-extended, wide geometry for MESE; Case B magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-182

Figure 6.4.1-9 

Mean map of rate and b-value for the study region under the source-zone configuration, with separation of Mesozoic extended 

and non-extended, wide geometry for MESE; Case E magnitude weights 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-183

Figure 6.4.2-1 

Comparison of model-predicted earthquake counts for study region using Case A magnitude weights. The error bars represent 

the 16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-184

Figure 6.4.2-2 

Comparison of model-predicted earthquake counts for study region using Case B magnitude weights. The error bars represent 

the 16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-185

Figure 6.4.2-3 

Comparison of model-predicted earthquake counts for study region using Case E magnitude weights. The error bars represent 

the 16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-186

Figure 6.4.2-4 

Comparison of model-predicted earthquake counts for MESE-N using Case A magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-187

Figure 6.4.2-5 

Comparison of model-predicted earthquake counts for MESE-N using Case B magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-188

Figure 6.4.2-6 

Comparison of model-predicted earthquake counts for MESE-N using Case E magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-189

Figure 6.4.2-7 

Comparison of model-predicted earthquake counts for MESE-W using Case A magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-190

Figure 6.4.2-8 

Comparison of model-predicted earthquake counts for MESE-W using Case B magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-191

Figure 6.4.2-9 

Comparison of model-predicted earthquake counts for MESE-W using Case E magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-192

Figure 6.4.2-10

Comparison of model-predicted earthquake counts for NMESE-N using Case A magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-193

Figure 6.4.2-11

Comparison of model-predicted earthquake counts for NMESE-N using Case B magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-194

Figure 6.4.2-12

Comparison of model-predicted earthquake counts for NMESE-N using Case E magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-195

Figure 6.4.2-13

Comparison of model-predicted earthquake counts for NMESE-W using Case A magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-196

Figure 6.4.2-14

Comparison of model-predicted earthquake counts for NMESE-W using Case B magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 6 

SSC Model: RLME Sources and Mmax Zones Branch 

6-197

Figure 6.4.2-15

Comparison of model-predicted earthquake counts for NMESE-W using Case E magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 

7-1

7

CHAPTER 7 

SSC MODEL: SEISMOTECTONIC ZONES BRANCH 

As discussed in Section 4.2.1, the conceptual framework for assessing the CEUS SSC model is 

characterized by two alternative branches of the master logic tree: the Mmax zones branch and 

the seismotectonic zones branch. The seismotectonic zones branch subdivides the CEUS SSC 

region according to differences in the seismic source assessment criteria described in Section 

4.1.3.3. A common element of both the Mmax zones and the seismotectonic zones branches is 

the RLME sources. Because the paleoearthquake data that indicate the presence, location, and 

size of the RLMEs are essentially independent from data used to assess seismotectonic sources, 

the RLME branch is present in both models. The seismotectonic zones approach allows the 

incorporation of additional information related to the characteristics of future earthquakes. 

Therefore, this approach is assessed a higher weight than the Mmax zones approach in the master 

logic tree, as discussed in detail in Section 4.2.1. An overview of the factors used to identify and 

characterize the seismotectonic zones is given in Sections 7.1 and 7.2, followed by a detailed 

discussion of each of these zones in Section 7.3. 

7.1 Approaches and Data Used to Define Seismotectonic Zones 

The conceptual basis for the seismotectonic zones branch of the master logic tree is that regional 

differences in characteristics related to recurrence rates, Mmax, future earthquake characteristics, 

and/or the probability of activity of tectonic features are best addressed by identifying a source 

zone (see Section 4.1.3.3). Likewise, the regional differences in these characteristics provide the 

bases for defining individual seismotectonic zones. Although the recurrence rates within the 

zones are allowed to vary according to the smoothing of observed seismicity, the other 

characteristics are assumed to be uniform within the zone. For example, a seismotectonic zone 

may possess characteristics that would lead to a different Mmax than adjacent zones, including a 

different prior distribution or different maximum observed earthquake. A seismotectonic zone 

might also be characterized by earthquakes resulting from reverse fault displacement, while 

adjacent zones might be characterized by larger components of strike-slip displacement. 

Likewise, a seismotectonic zone might best be characterized as having thicker seismogenic crust 

than adjacent zones. A seismotectonic zone may also be defined if tectonic features or groups of 

tectonic features are identified that have a significant probability of activity, but as discussed in 

Section 4.1.3.3, such features have not been identified on a regional basis as part of this study. 

The geometries of the seismotectonic zones are largely a function of the major tectonic domains 

within which a given SSC characteristic is assessed to be relatively uniform (Figures 7.1-1 

through 7.1-4) and different from the characteristics of adjacent zones. In most cases, the 

characteristics that define the zones are expected differences in future earthquake characteristics 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-2

such as rupture orientation, depth distribution, and style of faulting. A summary of the future 

earthquake characteristics for each seismotectonic zone is given in Table 5.4-2. The boundaries 

of the seismotectonic zones are derived from interpretations in the literature of regional 

geophysical, geologic, and tectonic data sets. In addition, data developed as part of the CEUS 

SSC Project, such as magnetic and gravity data (Figures 7.1-5 and 7.1-6), were examined for 

defining the zones. As discussed in Section 5.4.7, zone boundaries are defined as being either 

―leaky‖ or ―strict‖ with respect to whether future earthquake ruptures are assessed to extend 

across a zone boundary. 

As described in Section 4.1.2.2 and included in Appendices C and D, Data Evaluation and Data 

Summary tables have been developed for each of the seismotectonic zones. These tables are an 

important resource for the reader, as they supplement the discussions of each zone given in this 

section. The Data Summary tables specify the various data sets that were reviewed and 

considered by the TI Team during the course of its assessments. The Data Evaluation tables 

provide an evaluation of the quality of the data and the degree of reliance placed by the team on 

the data during the assessment process. The reader is advised to consult both tables when 

reviewing the descriptions to better understand how the available data were applied to define the 

characteristics of each seismotectonic zone. Tables developed for RLME sources are also 

relevant for some of the seismotectonic zones. Table 7.1-1 shows which table numbers are 

associated with each of the seismotectonic zones. 

To illustrate the definition of a seismotectonic zone by way of a specific example, the St. 

Lawrence Rift (SLR) seismotectonic zone (discussed in Section 7.3.1 and shown on Figures 

7.1-1 and 7.3.1-1) is outlined by the region assessed to be a terrane of known and inferred 

northeast-trending normal faults that formed parallel to the passive margin of Laurentia during 

the late Proterozoic–early Paleozoic opening of the Iapetus Ocean and underwent continental 

extension during the most recent extensional tectonic episode in the Mesozoic. The data 

considered in the identification and characterization of this zone are presented in Data Summary 

Table D-7.3.1 (Appendix D), and the data evaluated to provide a basis for characterizing the 

zone are given in Data Evaluation Table C-7.3.1 (Appendix C). The detailed assessments of the 

available data for the SLR zone are given in Section 7.3.1, including the basis for identifying the 

SLR as a seismotectonic zone and the location of the zone boundary (Section 7.3.1.2). The set of 

future earthquake characteristics for the SLR zone is given in Table 5.4-2. This zone is adjacent 

to the Northern Appalachian zone to the south and differs from it in the expected strikes of future 

ruptures and in the thickness of the seismogenic crust. The boundaries to the SLR zone are 

assessed to be ―leaky,‖ such that future earthquake epicenters would lie within the zone, but 

ruptures, the strike of which is given in Table 5.4-2 and the length and width of which are 

magnitude-related (as discussed in Section 5.4), could extend beyond the zone boundaries. 

Given the regional nature of the CEUS SSC model and the need for it to be reviewed for possible 

local refinement for site-specific application (see discussion in Section 4.1.3), the sensitivity to 

the exact location of seismotectonic zone boundaries is not expected to be large. Therefore, 

explicit quantification of the uncertainty in zone boundary location is included in the model for 

only a couple of cases, such as the western boundary of the Paleozoic Extended Crust (PEZ 

narrow or wide) and the inclusion or exclusion of the Rough Creek graben in the Reelfoot Rift 

seismotectonic zone (RR-RCG). 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-3

It is important to note that, in the discussion of the seismotectonic zones, the TI Team was well 

aware of previous SSC models developed for the CEUS through the years for both site-specific 

and regional hazard evaluations. Some of these studies relied on different approaches and criteria 

for identifying seismic source zones from those used in this study (Section 4.1.3). As a result, it 

may appear that some of the ―tried-and-true‖ approaches to drawing seismic source zone 

boundaries have been ignored or not considered in the CEUS SSC Project. For example, the 

spatial distribution of seismicity is decidedly non-uniform in the CEUS (Figure 7.1-7), and a 

common approach to identifying seismic sources in some past studies was to enclose zones of 

concentrated seismicity. Specific examples include the Central Virginia seismic zone and the 

Eastern Tennessee seismic zone (ETSZ). Acknowledging that these zones of elevated seismicity 

in the historical period of observation likely represent zones of future elevated rates, the method 

of implementing this concept in the CEUS SSC model is spatial smoothing of a- and b-values, 

rather than drawing source zone boundaries. Further, both the Mmax zones and the 

seismotectonic zones branches of the master logic tree provide for such smoothing regardless of 

where source zone boundaries are drawn. Therefore, given that some seismotectonic zones show 

spatial variations in observed rates of past earthquakes (Figure 7.1-8), these variations are 

accounted for in the smoothing model. 

Another common characteristic of previous SSC models is identifying prominent tectonic 

features as potential seismic source zones. Examples include the Midcontinent rift, which 

displays strong gravity and magnetic anomalies, or the numerous Mesozoic extensional faults 

and basins along the eastern margin of the CEUS. In a general sense, the seismotectonic zones 

accommodate the regional tectonic domains within which these types of tectonic features occur, 

provided that they meet the criteria for identifying a seismic source (Section 4.1.3.3). The SLR is 

defined by a different prior distribution for estimating Mmax from that of some adjacent regions, 

and the zone encloses the major Paleozoic extensional features of the St. Lawrence rift system. 

However, the zone boundary is drawn not because it is a tectonic feature, but because of 

expected differences with adjacent zones in Mmax, as well as other future earthquake 

characteristics (e.g., style of faulting, rupture orientation, thickness of seismogenic crust). 

In contrast, features such as the Midcontinent rift are not assessed to lead to different Mmax or 

future earthquake characteristics from adjacent regions, nor does the feature have a high 

probability of activity (Pa > 0.5) that could lead to a significant potential hazard. Therefore, using 

the hazard-informed approach discussed in Section 4.1.3, these types of tectonic features are not 

called out in the SSC model. Other types of tectonic features that are not identified explicitly are 

faults and other features that might have local significance, unless there is a clear consensus 

within the technical community that the feature should be assessed a high Pa and considered 

seismogenic. For example, recent and ongoing studies of faults in the vicinity of the ETSZ 

postulate that these faults are related to the zone either as causative faults or as secondary faults 

resulting from displacement on faults at depth (see Section 7.3.4). However, these postulated 

associations are judged to lack definitive support for use in this SSC model as a result of the 

preliminary nature of the studies. Even the Charleston RLME source characterization does not 

rely on an individual fault or faults as seismic sources, given the lack of definitive geologic 

evidence for young faulting in the Charleston area. However, the range of hypotheses for the 

location of the Charleston source fault is encompassed by the source zones as they are currently 

defined. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-4

7.2 RLME Sources in the Seismotectonic Zones Branch 

The RLME sources are described in Section 6.1 under the Mmax zones branch of the master 

logic tree. Because the RLME sources are defined and characterized by independent 

paleoseismic data that are not affected by the presence or absence of seismotectonic zones or 

Mmax zones, they are assumed to exist in exactly the same manner as on the Mmax zones 

branch of the master logic tree. 

7.3 Seismotectonic Source Zones 

The logic tree structure for the seismotectonic source zones is shown on Figure 7.3-1. The first 

two levels of the logic tree address the basic source zoneation. The first level addresses the 

location of the boundary between the PEZ and the Midcontinent-Craton (MidC) zone. 

Characterization of the uncertainty in this boundary parallels the uncertainty in the 

MESE/NMESE boundary for the Mmax zones and arises from uncertainty in characterizing the 

western extent of Mesozoic extension. The second level of the logic tree addresses the 

uncertainty in the eastern extent of the RR zone—whether or not it includes the Rough Creek 

graben. These two logic tree branches lead to the four alternative seismotectonic zonation 

configurations shown on Figures 7.1-1 through 7.1-4. 

The next level of the logic tree addresses uncertainty in the choice of weights on magnitude 

ranges used in computing the seismicity rates. These are discussed in Section 7.5. 

Descriptions of the individual seismotectonic zones are presented below. 

7.3.1 St. Lawrence Rift Zone (SLR) 

The SLR seismotectonic zone consists of crust initially rifted during the late Proterozoic–early 

Paleozoic opening of the Iapetus Ocean; faults within the rifted crust were subsequently 

reactivated during the Paleozoic and Mesozoic. This seismotectonic zone is characterized by 

elevated rates of seismicity and contains significant historical earthquakes, including the 1935 

Timiskaming M 6.2 (E[M] 6.02)1

earthquake, the 1988 Saguenay M 5.9 (E[M] 5.84) earthquake, 

and historical earthquakes from Charlevoix (Figure 7.3.1-1). Historical earthquakes and 

paleoseismic evidence suggest that the entire rift system is capable of generating moderate- to 

large-magnitude earthquakes. Compressional reactivation of favorably oriented Iapetan faults has 

been postulated as the causal mechanism for several seismically active regions in eastern North 

America, including the SLR, Charlevoix, and the lower St. Lawrence Valley in Quebec, Canada 

(Adams and Basham, 1991). As the result of an analysis of earthquakes in stable continental 

regions (SCRs) worldwide, Johnston et al. (1994) determined that zones of rifted crust in SCRs 

correlate directly with increased earthquake activity when compared to zones of nonrifted SCRs 

in regard to number and maximum magnitude of earthquakes. The seismic source 

 

1

 Magnitudes are reported in magnitude scale as designated in the cited publication. E[M] denotes the value of the 

expected moment magnitude listed in the CEUS SSC catalog for an earthquake. It is reported to two decimal places 

to indicate that it is a calculated value. See the discussion in Section 3.3.1.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-5

characterization of the SLR seismotectonic zone is based on a review of published material that 

is summarized in the Data Summary table for the SLR zone (Appendix Table D-7.3.1). Explicit 

references and data that were used as the basis for source characteristics of SLR are identified in 

the Data Evaluation table (Appendix Table C-7.3.1). 

7.3.1.1 Background 

7.3.1.1.1 Iapetan Rifting

Breakup of the Mesoproterozoic supercontinent of Rodinia occurred as diachronous rifting along 

the margins of Laurentia. Rifting began on the western margin of Laurentia between 780 and 680 

Ma, and continued to the eastern margin between 620 and 550 Ma from Newfoundland into the 

southern Appalachian Mountains (Whitmeyer and Karlstrom, 2007), resulting in the opening of 

the Iapetus Ocean (Faill, 1997a). Kumarapeli (1985) proposed that a mantle plume initiated 

Iapetan rifting along the Sutton Mountains triple junction, resulting in the development of the St. 

Lawrence valley system and aulacogens of the Ottawa-Bonnechere and Saguenay grabens 

(Kumarapeli and Saull, 1966; Kumarapeli, 1985, 1993). Based on geochronological studies of 

the Sutton Mountains volcanics, Kumarapeli (1993) established the following sequence: (1) 

rifting initiated at 590 Ma and continued for 35 Myr; (2) rifting ceased about 554 Ma after an 

outburst of alkaline to transitional basalts at the Sutton Mountains triple junction; and (3) a 

period of rift-facies clastic sedimentation followed until the rift-drift transition at 550 Ma. Riftrelated lava flows (Figure 7.3.1-2) are observed along the entire eastern margin of Laurentia now 

preserved in Appalachian thrust sheets, including the Skinner Cove Formation of western 

Newfoundland (McCausland and Hodych, 1998); the Mont St-Anselme Formation and Lac 

Matapédia flows of Quebec (Hodych and Cox, 2007); the Tibbit Hill Formation of Vermont and 

Quebec (Kumarapeli et al., 1988); the Pinney Hollow metarhyolite of central Vermont (Walsh 

and Aleinikoff, 1999); the Caldwell Group lavas of southern Quebec (Bedard and Stevenson, 

1999); and the Nassau Formation of eastern New York and western Massachusetts (Ratcliffe, 

1987). Major and trace element studies of the lava rocks confirm a mantle source consistent with 

plume activity (St. Seymour and Kumarapeli, 1995; Abdel-Rahman and Kumarapeli, 1998). 

Puffer (2002) compiled a database of high field-strength elements for late Neoproterozoic to 

early Paleozoic flood basalts, revealing that superplume activity peaked at 550 Ma at the Sutton 

Mountains triple junction. The 564 Ma Catoctin Formation of southeastern Pennsylvania and 

central Virginia and the 758 Ma Mount Rogers Formation of southwestern Virginia and North 

Carolina and Tennessee record a more complex history of Iapetan rifting in the southeastern 

United States (Aleinikoff et al., 1995) and are discussed in Section 7.3.4.1. 

Iapetan rifting is also recorded by widespread dikes and intrusions throughout the SLR and the 

Ottawa-Bonnechere and Saguenay aulacogens (Figure 7.3.1-2). The Grenville dike swarm of the 

Ottawa-Bonnechere graben (Kamo et al., 1995) and the Adirondack dike swarm of New York 

(Abdel-Rahman and Kumarapeli, 1998) are coeval with the 590 Ma Sutton Mountains 

volcanism, implying that the dike swarms were emplaced within a relatively short time span at 

the onset of rifting. Alkalic intrusions within the Ottawa-Bonnechere graben yielding an early 

Cambrian age of approximately 565 Ma and syn-rift carbonatite complexes of the Saguenay 

graben dated at 565 Ma support the view that these aulacogens formed as part of a single event 

(Kumarapeli, 1985). This interpretation is supported by subsequent ages of the 577 Ma Callander 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-6

Complex near Lake Nipissing in the western end of the Ottawa-Bonnechere graben (Kamo et al., 

1995) and the 564 Ma Mt. Rigaud syenite of Quebec (McCausland and Hodych, 1998). Higgins 

and van Breemen (1998) attribute the 565 ± 4 Ma Sept Iles layered mafic intrusion of the Gulf of 

St. Lawrence to emplacement of plume melts along rift faults that developed after emplacement 

of dike swarms. Additional details are provided in Appendix Table D-7.3.1. This rifted margin is 

expressed as promontories and embayments defined by northeast-striking normal faults and 

northwest-striking transform faults along the margins of Laurentia (Thomas, 1991; 2006; Lavoie 

et al., 2003). 

In southeastern Canada, Iapetan rifting is expressed along the St. Lawrence River valley (Section 

7.3.1.1.2) and associated with the Ottawa (Section 7.3.1.1.4) and Saguenay (Section 7.3.1.1.5) 

failed arms, or aulacogens, that formed transverse to the faulted edge of the ancient continental 

margin (Adams et al., 1995). These aulacogens are defined by zones of approximately east-westtrending normal faults that extend into the Canadian Shield and have not undergone significant 

total extension (Adams et al., 1995). Large-magnitude earthquakes located within the Charlevoix 

area (Figure 6.1.1-1) are characterized as part of the Charlevoix RLME seismic source zone 

(Sections 6.1.1 and 7.3.1.1.3), whereas the moderate-magnitude seismicity at Charlevoix is 

characterized as part of the SLR seismotectonic zone. Adams et al. (1995) argue that seismicity 

clusters observed throughout the Iapetan margin are a temporal artifact and characterize the 

possible future activity of the region by incorporating these clusters into a regional zone. The 

following subsections address the geologic, geophysical, and seismic characteristics of the crust 

within the SLR seismotectonic zone, which exhibits variable rates of seismicity. 

7.3.1.1.2 St. Lawrence Rift 

The late Proterozoic–early Paleozoic St-Laurent fault, which is attributed to opening of the 

Iapetus Ocean, forms a northeast-trending, southeast-dipping half graben lying along the main 

axis of the SLR system (Tremblay and Lemieux, 2001). High-resolution seismic profiles in the 

St. Lawrence estuary indicate that the Laurentian Channel trough transitions from a half graben 

to a graben structure from southwest to northeast (Tremblay et al., 2003). The St-Laurent fault 

trends N20 to 50E, dips 60–70 degrees to the southeast (Tremblay and Lemieux, 2001; Tremblay 

et al., 2003), and is crosscut by the Cap-Tourmente fault at Cap-Tourmente, Quebec. West of 

Cap-Tourmente, the Montmorency Falls fault occupies the same structural position as the StLaurent fault, suggesting that they formed as en echelon faults oblique to the axis of the SLR 

(Tremblay and Lemieux, 2001). The Cap-Tourmente fault possibly represents a transfer fault 

acting as an oblique relay structure between two longitudinal normal faults (Tremblay and 

Lemieux, 2001). St. Julien and Hubert (1975) observe that east-west and N30E steeply southeastdipping normal faults active between late Precambrian and the Late Ordovician times cut 

Cambrian and Ordovician platform rocks in southwestern Quebec. Results of the Quebec-Maine 

seismic reflection surveys provide evidence of closely spaced en echelon normal faults with 

displacements between 200 and 1,000 m (656 and 3,280 ft.), interpreted as fossilized Iapetan 

growth faults below the Appalachian detachment surface (Spencer et al., 1989). These normal 

faults are imaged on the northwestern portion of seismic line QM2001 northwest of the BaieVert–Brompton line (Spencer et al., 1989). 
Chapter 7 

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7-7

Multiple phases of reactivation of the SLR are in evidence. The St-Laurent fault crosses the 

Devonian Charlevoix impact crater without major deflection, suggesting post-impact reactivation 

(Lemieux et al., 2003). The St-Laurent fault influenced the deposition of Ordovician sediments 

during late stages of the Taconian orogeny by syndepositional faulting, preserved as major lateral 

thickness variations within these platform rocks, presence of slump deformation in almost all 

stratigraphic units, preservation of pseudotachylyte within synsedimentary breccias, and 

occurrence of fault breccia clasts (Lemieux et al., 2003). Truncation of Devonian impact-related 

structures by northeast-southwest and northwest-southeast fault sets is consistent with Mesozoic 

fault reactivation due to rifting of the North Atlantic region (Lemieux et al., 2003). Tremblay et 

al. (2003) attribute some fault throw along the SLR fault system to opening of the Central 

Atlantic in the Jurassic and/or seafloor spreading of the North Atlantic during the Cretaceous. 

Faults located in Quebec near Montreal, where the southern portion of the SLR approaches the 

Ottawa-Bonnechere graben, provide evidence for northwest-southeast extension associated with 

the opening of the Iapetus Ocean; west-northwest/east-southeast compression followed by minor 

north-northwest compression associated with Appalachian thrusting; northeast-southwest and 

north-northwest/south-southeast extension associated with the opening of the Atlantic-Labrador 

Ocean; and northeast-southwest compression postdating these events (Rocher et al., 2003). 

In addition to large-magnitude historical earthquakes located within the Charlevoix RLME 

source area (Sections 6.1.1 and 7.3.1.1.3), the September 16, 1732, modified Mercalli intensity 

(MMI) VIII (E[M] 6.25) Montreal earthquake (Leblanc, 1981) and the September 5, 1944, M 5.8 

(E[M] 5.71) Cornwall-Massena earthquake (Bent, 1996b) are also located along the main axis of 

the SLR. 

7.3.1.1.3 Charlevoix RLME Source 

Adams and Basham (1991) attribute seismicity of the SLR system to earthquakes occurring on 

rift structures in the regional stress field of southeast-to-east compression, recognizing that a 

Devonian impact structure also exists in the general area and may be related to the spatial 

concentration of seismicity in the Charlevoix area. Two major fault orientations (N40-70W and 

N20-40E) are found outside the Charlevoix impact zone, with minor fault sets trending east to 

west to N80W and north to south to N20E (Lemieux et al., 2003). Lemieux et al. (2003) 

observed the largest variation in fault trends within the central portion of the impact crater, which 

still displayed a dominant northeast-southwest orientation. Lamontagne and Ranalli (1997) 

attribute large-magnitude Charlevoix earthquakes to reactivation of rift faults in response to the 

regional stress field. They interpret variations in orientation and style of faulting for smallmagnitude earthquakes to reactivation of impact-related faults and fractures in response to local 

stress and/or strength conditions. In another paper, Lamontagne and Ranalli (1996) attribute 

earthquakes in the Charlevoix seismic zone to some or all of the following circumstances: 

Fracturing above the brittle-ductile transition at depths of at least 25 km (15.5 mi.). 

High pore-fluid pressure at mid- to lower crustal depths where hydration reactions are not 

favored. 

Low coefficients of friction related to highly fractured zones at depth, as opposed to thick 

fault gouges made of clay minerals. 
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7-8

Results of two-dimensional stress modeling account for the spatial pattern of observed seismicity 

as stress concentration due to the interaction of the crater (local zone of weakness) and rift faults 

(large-scale weak zone; Baird et al., 2009). Smaller-magnitude, more frequent seismicity occurs 

within the impact crater, and infrequent larger-magnitude earthquakes are localized along rift 

faults (Baird et al., 2009). Tuttle and Atkinson (2010) observed paleoliquefaction features in the 

Charlevoix area—but not to the south in Trois Rivières, Quebec—that suggest stationarity of 

large-magnitude earthquakes within the Charlevoix RLME seismic source zone. Although the 

February 5, 1663, M 7 (E[M] 7.00) and October 20, 1870, M 6.5 (E[M] 6.55) earthquakes are 

modeled as RLME in Section 6.1.1, the December 6, 1791, M 5.8 (E[M] 5.50); October 17, 

1860, M 6 (E[M] 6.08); and March 1, 1925, M 6.3 (E[M] 6.18) earthquakes do not meet the 

RLME criterion of exceeding M 6.5 and are thus assigned to the SLR seismotectonic zone. The 

Charlevoix Data Summary and Data Evaluation tables (Tables D-6.1.1 and C-6.1.1) present 

additional details about the Charlevoix RLME zone. 

7.3.1.1.4 Ottawa-Bonnechere Graben 

The Ottawa-Bonnechere graben extends for approximately 700 km (435 mi.) into the Canadian 

Shield (Kumarapeli and Saull, 1966; Kumarapeli, 1985, 1993) from the Sutton Mountains salient 

of the central Appalachian orogen. The graben is inferred to extend eastward beneath the 

Appalachian thrust sheets for approximately 30 km (19 mi.) by Kumarapeli (1993), based on 

observations that the Early Cretaceous Monteregian intrusions reported by Foland et al. (1986) 

are emplaced along the graben faults. Alkalic intrusions within the Ottawa-Bonnechere graben 

yield an early Cambrian age of approximately 565 Ma (Kumarapeli, 1985). A tholeiitic diabase 

dike swarm associated with the graben is dated at 590 Ma, implying that the initiation of rifting 

was a late Proterozoic event (Kumarapeli, 1985). 

The faults defining the Ottawa-Bonnechere graben generally strike west-northwest and offset 

Silurian strata (Forsyth, 1981). Rimando and Benn (2005) report three periods of faulting in 

Cambro-Ordovician sedimentary rocks within the eastern end of the Ottawa-Bonnechere graben, 

near Ottawa, Ontario, Canada, as follows: 

The oldest generation of faults, formed in response to a horizontal maximum principal 

compressive stress (σ1) oriented northwest, are kinematically congruent with the compression 

direction associated with closing of the Iapetus Ocean. 

A second generation of faults, which indicate a west-northwest-oriented σ1, coincide with 

emplacement of Cretaceous carbonatite dikes. 

A third generation of faults indicate a southwest-oriented σ1 consistent with the postCretaceous stress field for eastern North America. 

The Ottawa-Bonnechere graben and associated basement faults acted as localized zones of 

weakness in the early stage of Cretaceous extension, resulting in reorientation of the regional 

stress field and formation of the localized zone of north-south-directed extension (Faure et al., 

1996b). Results of the 1982 Canadian Consortium for Crustal Reconnaissance Using Seismic 

Techniques (COCRUST) long-range seismic refraction experiment show a sharp, step-like 

displacement of the Moho beneath the south shoulder of the Ottawa-Bonnechere graben, 
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7-9

confirming the deep-seated nature of the faults associated with the graben and penetration of 

mantle melts into the crust (Mereu et al., 1986). In addition, the COCRUST surveys show a 

poorly defined Moho at unusually shallow depths beneath the graben (Mereu et al., 1986). 

Adams and Basham (1991) recognized two distinct bands of seismicity within the Western 

Quebec seismic zone. They attribute the west-northwest-trending band of seismicity along the 

Ottawa River between Ottawa, Ontario, and Lake Timiskaming to rift faults of the OttawaBonechere graben and the more northern band to the Great Meteor hotspot (Section 7.3.2). The 

second band of seismicity in the Western Quebec seismic zone trends north-northwest, extends 

from Montreal to the Baskatong Reservoir, and is attributed to crustal fracturing associated with 

the passage of a Cretaceous hot spot track as discussed in Section 7.3.3. Adams et al. (1995) 

consider the 1935 M 6.2 (E[M] 6.02) Timiskaming earthquake, which occurred at a depth of 

10 km (6 mi.) near the Quebec-Ontario border, the paradigm earthquake for the OttawaBonnechere graben. The January 1, 2000, MN 5.2 (E[M] 4.62) Kipawa earthquake is located near 

the 1935 epicenter and exhibits northwest-southeast-striking reverse faults that may be 

associated with northwest-trending lineaments under Lake Kipawa that have been interpreted as 

faults (Bent et al., 2002). 

In the western portion of the Ottawa-Bonnechere graben, Doig (1991) interprets two 

paleoearthquakes based on inferred landslide deposits in lakes located near the epicenter of the 

1935 Timiskaming earthquake. As discussed in Section 6.1.1.5, this method of interpreting 

earthquake-induced landslide deposits cannot distinguish between local small-magnitude 

earthquakes and distant large-magnitude earthquakes, but these results qualitatively suggest that 

the Ottawa-Bonnechere graben has experienced recurring moderate-magnitude earthquakes. 

Aylsworth et al. (2000) attribute widespread landsliding and irregular subsidence along the 

Ottawa River in the eastern portion of the graben to two paleoearthquakes occurring at about 

7,060 and 4,550 BP that could be as large as the 1663 Charlevoix (M 7) earthquake (Section 

7.3.1.3). 

7.3.1.1.5 Saguenay Graben 

The Saguenay graben, which also represents a failed arm of the Iapetan passive margin 

(Kumarapeli, 1985), extends into the Precambrian Canadian Shield for approximately 300 km 

(186 mi.) northwest from the St. Lawrence Valley. The graben margins are defined by the Lac 

Tchitogama, Ste-Marguerite River, and Lake Kenogami east-west-striking normal faults (Du 

Berger et al., 1991). Syn-rift carbonatite complexes dated at 565 Ma suggest an early Cambrian 

age for the Saguenay graben (Kumarapeli, 1985). Some of the graben-bounding faults offset 

Ordovician limestone by as much as 500 m (1,640 ft.) and are marked by prominent topographic 

scarps with 100–300 m (328-984 ft.) of relief (Du Berger et al., 1991). Lavoie et al. (2003) 

attribute middle to late Cambrian debris flow units preserved in southern Quebec and western 

Newfoundland to reactivation of the Saguenay graben. Longuépée and Cousineau (2005) 

interpret the Anse Maranda Formation as sediments deposited in deep subbasins along a narrow 

shelf south of the Saguenay graben. Roden-Tice, Brandt, and Tremblay (2009) observe apatite 

fission-track age discontinuities across the Sainte-Marguerite and Lac Kenogami faults, 

suggesting Late Triassic to Early Jurassic and Middle Jurassic reactivation, respectively, across 

the faults. Adams et al. (1995) characterized the 1988 Saguenay M 5.9 (E[M] 5.84) earthquake, 
Chapter 7 

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7-10

which occurred at a depth of 27 km (17 mi.), as the paradigm earthquake for the Saguenay 

graben. Prior to this earthquake, seismicity rates for the Saguenay graben were extremely low 

(Adams et al., 1995). Paleoliquefaction investigations conducted by Tuttle et al. (1990, 1992) 

and Tuttle (1994) in the Saguenay graben area revealed liquefaction features within 26 km (16 

mi.) of the epicenter of the 1988 Saguenay earthquake, and included evidence for an older 

earthquake of unknown magnitude occurring at AD 1420 ± 200 yr.

Other investigations also provide geologic evidence for repeated earthquakes in Saguenay. Doig 

(1998) determined a recurrence interval ranging from 350 to 1,000 years based on evidence of 

earthquake-induced landslide deposits within lakes near the epicenter of the 1988 Saguenay 

earthquake. As discussed in Sections 6.1.1.5 and 7.3.1.1.4, these observations are difficult to 

quantitatively incorporate within recurrence calculations because silt layers may be due to 

nontectonic landslides, and if they are tectonic, these silt layers can be attributed to either local 

moderate-sized earthquakes or distant large-magnitude earthquakes. These results do, however, 

suggest that the Saguenay graben has experienced recurring moderate-magnitude earthquakes. 

Recent work by Locat (2008) places the 1663 M 7 earthquake near Saguenay, based on the 

distribution of largely undated landslide deposits throughout the region and subaqueous mass 

movements in the St. Lawrence estuary, Saguenay fjord (Syvitski and Schafer, 1996; Urgeles et 

al., 2002; St-Onge et al., 2004), and nearby lakes. These studies by Doig (1998), Locat (2008), 

Syvitski and Schafer (1996), Urgeles et al. (2002) and St-Onge et al. (2004) illustrate the role of 

landsliding, in addition to liquefaction, as a mechanism for recording paleoearthquakes in the 

region. As discussed in Section 6.1.1.3, better constraints on timing of earthquakes are required 

for correlating deformation with specific earthquakes and determining location and magnitude of 

those earthquakes. 

7.3.1.1.6 Lower St. Lawrence 

Adams et al. (1995) attribute aseismic regions that clearly separate seismicity of the Lower St. 

Lawrence from that in the Charlevoix area as temporal artifacts, and relate the Lower St. 

Lawrence cluster of seismicity to a separate seismic source zone, the Bas St. Laurent zone in the 

GSC H model (Adams et al., 1996; Adams and Halchuk, 2003). Lamontagne et al. (2003) 

propose that this localized Lower St. Lawrence cluster of seismicity occurs in Precambrian 

basement where intersecting faults may be weakened by crustal fluids, hydrostatic pressure, or 

fault gouge, and that emplacement of the Sept-Iles layered igneous complex may have further 

fractured this portion of crust. Lamontagne et al. (2004) attribute the March 16, 1999, MN 5.1 

(E[M] 4.45) Côte-Nord earthquake, whose focal mechanisms exhibited northwest-trending nodal 

planes to rupture of northwest-striking faults associated with magnetic and gravimetric 

lineaments, as opposed to northeast-southwest-trending rift faults. 

7.3.1.1.7 Adirondack Mountains 

Kumarapeli and Saull (1966) interpret fault scarps along the western margin of the Champlain 

Valley to St. Lawrence rifting. Iapetan normal faults within the Adirondack Mountains occur 

within the Adirondack dike swarm (Kamo et al., 1995; Figure 7.3.1-2). Kamo et al. (1995) 

established that the Grenville dike swarm of the Ottawa-Bonnechere graben is coeval with the 
Chapter 7 

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7-11

590 Ma Sutton Mountains triple junction, and Abdel-Rahman and Kumarapeli (1998) determined 

that the Adirondack dike swarm of New York is geochemically similar to the Grenville dike 

swarm, implying that both swarms are coeval and comagmatic with Sutton Mountains 

volcanism. Focal mechanism interpretations for the April 20, 2002, M 5.0 (E[M] 4.91) Au Sable 

Forks, New York, earthquake show reverse faulting consistent with reactivation of a north-southstriking structure (Pierre and Lamontagne, 2004; Seeber et al., 2002). The October 7, 1983, mb

5.1 (E[M] 4.84) Goodnow, New York, earthquake also is related to reverse faulting oriented 

north-south (Nábĕlek and Suárez, 1989). North-south-trending structures in the Lake Champlain 

area include normal faults associated with Iapetan rifting and high-angle reverse faults associated 

with Taconic compression (Seeber et al., 2002). Roden-Tice et al. (2000) inferred Late Jurassic 

exhumation of the High Peaks section of the Adirondack Mountains, which continued along the 

northern, northwestern, and southwestern margins of the Adirondack Mountains into the 

Cretaceous, with a suggestion of renewed unroofing in the Eocene. This exhumation is thought 

to have been accommodated by reverse-slip reactivation of north-northeast-trending normal 

faults (Roden-Tice et al., 2000). Subsequent work by Roden-Tice and Tice (2005) indicates that 

differential unroofing in the southeastern Adirondack Mountains and central New England may 

have been accommodated by Late Cretaceous fault reactivation. 

7.3.1.2 Basis for Defining Seismotectonic Zone 

The SLR seismotectonic zone delineates crust initially rifted during the late Proterozoic–early 

Paleozoic opening of the Iapetus Ocean and subsequently reactivated during the Mesozoic 

opening of the Atlantic Ocean, meeting the criterion for separating crust of the SLR on the basis 

of maximum earthquake magnitude. As discussed in Section 7.3.1.1, although the rates of 

seismicity vary throughout the rift, moderate- to large-magnitude earthquakes are observed 

throughout the seismotectonic zone. Previous interpretations of the Iapetan rifted margin (IRM; 

Wheeler, 1995; Adams et al., 1995) have included crust that is characterized as part of the 

Northern Appalachian (Section 7.3.3) and Paleozoic Extended Zone (Section 7.3.4) 

seismotectonic zones. Crust of the SLR seismotectonic zone is distinguished from these two 

zones on the basis of age, history of reactivation, and earthquake characteristics. 

The SLR seismotectonic zone is defined by mantle plume–initiated Iapetan rifting along the 

Sutton Mountains triple junction (Kumarapeli, 1985, 1993) that resulted in normal faulting along 

the main axes of the St. Lawrence rift and the Ottawa-Bonnechere and Saguenay grabens 

(Kumarapeli and Saull, 1966; Kumarapeli, 1985, 1993; Tremblay et al., 2003; Lemieux et al., 

2003). The IRM extends south of the SLR and lies buried beneath the Northern and Southern 

Appalachian Mountains (Wheeler, 1995). Compressional reactivation of favorably oriented 

Iapetan faults has been postulated as the causal mechanism for several seismically active regions 

in eastern North America (Adams and Basham, 1991). Adams et al. (1995) observe that 

seismicity of the IRM is largely expressed as reverse-slip faulting mechanisms in Canada and 

strike-slip mechanisms in the United States. Faults exposed within the SLR exhibit multiple 

phases of reactivation, including during the Mesozoic (Tremblay et al., 2003; Lemieux et al., 

2003; Rocher et al., 2003; Rimando and Benn, 2005). Faure et al. (2006) observe east-west- and 

northwest-southeast-oriented extensional stress regions in Quebec based on stress tensor analysis 

of regional- and mesoscopic-scale faults, which indicate that Mesozoic extension was 
Chapter 7 

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7-12

widespread and extended at least 400 km (250 mi.) from the Atlantic margin. Apatite fissiontrack ages from the Adirondack Mountains and New England indicate widespread Mesozoic 

uplift and erosion that locally display age discontinuities, suggesting reactivation of preexisting 

structures (Roden-Tice et al., 2000; Roden-Tice and Tice, 2005; Roden-Tice, West, et al., 2009). 

As presented in Section 7.3.1.1, the presence of moderate- to large-magnitude historical 

earthquakes and paleoseismic data indicate that the entire rift system is capable of generating 

moderate to large earthquakes. 

7.3.1.3 Basis for Zone Geometry

The geometry for the SLR seismotectonic zone incorporates crust exhibiting evidence of Iapetan 

rifting, either by faulting or intrusion of rift-related volcanic rocks. The spatial extent of dikes 

and intrusions is generally larger than graben-bounding normal faults (Figure 7.3.1-2). 

Therefore, the geometry for SLR is modified from the IRM and Adirondack source zones of the 

GSC regional model (Adams et al., 1996; Adams and Halchuk, 2003) and the IRM boundary by 

Wheeler (1995) to incorporate the following data sets. The SLR seismic source zone boundary 

along the Adirondack Mountains and Ottawa-Bonnechere graben incorporates the Sutton 

Mountains triple junction, Grenville and Adirondack dike swarms, and Iapetan normal faults as 

mapped by Kamo et al. (1995). 

Mapped locations of Iapetan lava flows (McCausland and Hodych, 1998; Hodych and Cox, 

2007; Kumarapeli et al., 1988; Walsh and Aleinikoff, 1999; Bedard and Stevenson, 1999; 

Ratcliffe, 1987) are preserved within Appalachian thrust sheets and therefore do not provide a 

reliable eastern boundary for the SLR seismotectonic zone. The eastern boundary of the zone 

coincides with the Baie Verte–Brompton line of Moench and Aleinikoff (2003) to capture 

normal growth faulting observed below the Appalachian detachment in the northern 

Appalachians by Spencer et al. (1989). These boundaries are not well-imaged in potential field 

data (Figure 7.3.1-3). Du Berger et al. (1991) observed that the 1988 Saguenay earthquake is 

located outside the Saguenay graben. Therefore, the geometry of this graben is modified from 

that proposed by Higgins and van Breeman (1998) based on the spatial distribution of smallmagnitude earthquakes in the dependent earthquake catalog. The main axis of the SLR 

seismotectonic zone was drawn to include these small-magnitude earthquakes. The northeastern 

portion of zone is also truncated beyond the edge of the project boundary. 

7.3.1.4 Basis for Zone Mmax 

A paleoseismic study conducted by Aylsworth et al. (2000) in the eastern portion of the OttawaBonnechere graben provides evidence for two moderate- to large-magnitude Holocene 

earthquakes. Landslide deposits occurring in the Leda Clay, which was deposited in the 

Champlain Sea, have normalized radiocarbon ages between 1,870 and 5,130 yr BP, with the 

majority of ages clustering at 4,550 yr BP. This age is significantly younger than paleochannel 

abandonment, so these landslides deposits are attributed to a paleoearthquake. Disturbed, 

hummocky terrain exhibiting local relief between 3 and 8 m (9.8 and 26 ft.) is located east of 

these landslide deposits within the flat erosional plane of the Ottawa River, and is likely related 

to landsliding. Faulted, upturned, and warped sediment is also exposed for 500 m (1,640 ft.) 
Chapter 7 

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7-13

along a ditch, and nearby excavations contain sand lenses, a small flame structure, and a sand 

boil feature. Large patches of sand occur randomly on the surface. All these features have a 

radiocarbon age of 7,060 ± 80 yr BP. 

Based on analogy to the 1663 Charlevoix earthquake, these earthquakes were estimated to 

represent a magnitude of M ≥ 7 (Aylsworth et al., 2000). Subsequent trenching by Aylsworth 

and Lawrence (2003) documented lateral spreading and deformation of sediments and surface 

subsidence within a deep bedrock basin (180 m [590 ft.]) at 7,060 yr BP. In one location, 2 m 

(6.5 ft.) of fluidized sand is interpreted to have been emplaced along a sand dike during an 

earthquake associated with either ground cracking due to lateral spreading or in situ block 

rotation (Aylsworth and Lawrence, 2003). Assessing the magnitude and location of the 

earthquake causing these features is complicated by the observations that fine sand interbedded 

with the Leda Clay induces lower cyclic resistance and that deep, steep-sided basins amplify 

ground motions. A comparison with other earthquakes led Aylsworth and Lawrence (2003) to 

estimate the magnitude of the earthquake to which these features are related to be at least M ≥ 

6.2, and likely M ≥ 6.5. The field observations conducted for these studies are consistent with 

appropriate evidence for paleoliquefaction as outlined in Appendix E. However, geotechnical 

investigations to constrain the cyclic stress ratio for these materials are required for constraining 

magnitude and location of these paleoearthquakes. It is also important to understand that these 

features could be caused by a paleoearthquake located in the SLR or Great Meteor Hotspot 

(GMH) seismotectonic zones, or that they could be caused by larger, more distant earthquakes 

associated with the Charlevoix RLME source. Future research may provide information to 

update the maximum magnitude distributions for these zones. 

Given that the magnitude of the largest observed earthquake lies within the range of uncertainty 

of the magnitudes estimated by Aylsworth and Lawrence (2003), Mmax for the SLR seismic 

source zone was assessed using historical seismicity. The largest observed earthquakes in SLR 

include the September 16, 1732, E[M] 6.25; March 1, 1925, E[M] 6.18; and November 1, 1935, 

E[M] 6.08 earthquakes. As part of the EPRI study on earthquakes in SCRs, Kanter (1994)

classified the St. Lawrence–Ottawa domain (Domain 227) as a Paleozoic rift that was reactivated 

in the Cretaceous. Therefore, the maximum magnitude distribution for the SLR seismotectonic 

zone was determined by applying a Mesozoic and younger prior to the largest observed 

earthquake. The resulting Mmax distribution is presented in Section 7.4.2.

7.3.1.5 Future Earthquake Characteristics 

Earthquakes in southeastern Canada are classified as mainly thrust earthquakes (Adams et al., 

1995; Du et al., 2003). Bent et al. (2003) determined focal mechanisms for M > 4 earthquakes 

occurring in eastern Canada between 1994 and 2000 and documented the mechanisms as 

predominantly reverse. Bent (1996a) determined a reverse mechanism for the November 1, 1935, 

mb 6.1 Timiskaming earthquake (Figure 7.3.1-1) and preferred a moderately dipping northweststriking plane. The January 1, 2000, MN 5.2 (E[M] 4.62) Kipawa earthquake (Figure 7.3.1-1) is 

located near the 1935 epicenter and exhibits northwest-southeast reverse faults dipping to the 

northeast (Bent et al., 2002). Du et al. (2003) determined thrust motion along either a 

southwesterly steeply dipping (68 degrees) or northeasterly dipping (30 degrees) nodal plane for 
Chapter 7 

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7-14

the Kipawa earthquake. Bent et al. (2003) observed that focal mechanisms in the Western 

Quebec seismic zone have a strong component of thrust faulting, with at least one nodal plane 

striking northwest-southeast, consistent with reactivation of the Ottawa-Bonnechere graben. Bent 

(1996b) determined an oblique thrust mechanism for the September 5, 1944, M 5.8 (E[M] 5.71) 

Cornwall-Massena earthquake (Figure 7.3.1-1), located at the eastern edge of the OttawaBonnechere graben along the St. Lawrence River. Bent (1996b) could not determine which nodal 

plane was the fault plane, given that the regional seismicity trend is consistent with the northwest 

plane, and mapped faults are more consistent with the northeast plane. 

Bent et al. (2003) report that mechanisms for the October 22, 1998, and March 16, 1999, Lower 

St. Lawrence earthquakes (Figure 7.3.1-1) exhibit evidence for oblique-thrust faulting over a 

wide range of possible dips (30–68 degrees). Lamontagne et al. (2004) favor the northwest nodal 

plane of the March 16, 1999, MN 5.1 (E[M] 4.45) Côte-Nord earthquake based on agreement 

with an alignment of aftershocks. The focal mechanism determined by Du et al. (2003) for this 

earthquake favors northeast- and southwest-trending nodal planes for this earthquake. 

Focal mechanisms for two earthquakes in the Adirondack Mountains indicate north-southstriking nodal planes. Focal mechanisms for the April 20, 2002, M 5.0 (E[M] 4.91) Au Sable 

Forks, New York, earthquake (Figure 7.3.1-1) show reverse faulting along a north-south-striking 

nodal plane, with aftershocks indicating an intermediate dip to the west (Seeber et al., 2002). The 

October 7, 1983, mb 5.1 (E[M] 4.84) Goodnow, New York, earthquake (Figure 7.3.1-1) also 

exhibits north-south-striking reverse faults dipping 60 degrees to the west (Nabelek and Suarez, 

1989). 

Adams and Basham (1991) report that structural complexity in the form of distributed fracturing 

and ring faulting within the Charlevoix impact crater may be responsible for more varied focal 

mechanisms within the Charlevoix RLME source. Focal mechanisms for earthquakes of 

magnitude >3 show reverse faulting, whereas smaller-magnitude earthquakes indicate some 

strike-slip and normal faulting, suggesting that local stress conditions may affect rupture style 

(Lamontagne and Ranalli, 1997). Fault plane solutions for recent small earthquakes located 

within the Charlevoix RLME source are predominantly thrust earthquakes on steeply dipping 

planes, but there are also a number of earthquakes with a significant strike-slip component, some 

on northwest-striking planes and some on more shallowly dipping planes (Lamontagne, 1987; 

Adams et al., 1989; Wetmiller and Adams, 1990). Analysis of rupture directions for two M 4 

earthquakes by Li et al. (1995) indicate that focal mechanisms have east-dipping planes. Bent 

(1992) determined a thrust mechanism for the 1925 MS 6.2 (E[M] 6.18) Charlevoix earthquake 

with a strike of N42° ± 7°E, a dip 53° ± 7°, and rake 105° ± 10°, and favors a southeast-dipping 

solution based on observed seismicity and mapped faults. Dips for fault surfaces related to the 

January 11, 1986, MN 4.0 (E[M] 3.40) and the March 18, 1987, MN 3.3 (E[M] 2.79) earthquakes 

range between 42 and 59 degrees to the south (Lamontagne and Ranalli, 1997). 

Future ruptures occurring in the SLR seismotectonic zone are modeled with two-thirds weight as 

reverse mechanisms and one-third weight as strike-slip. Given the wide variability in structural 

orientations and focal mechanisms, the strike of future ruptures contains northeast, northwest, 

north-south, and east-west alternative orientations with the following percentages: N25E (20%), 

N40E (20%), N70E (20%), N50W (15%), N70W (15%), N-S (5%), and E-W (5%).
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Earthquakes within eastern Canada can have anomalously deep hypocenters compared to the 

adjacent craton. Bent and Perry (2002) relocated earthquakes in eastern Canada occurring 

between 1992 and 2000 and concluded that moderate-magnitude earthquakes in the OttawaBonnechere graben have depths in the 11–16 km (7–10 mi.) range but may occur at variable 

depths in the crust. Hypocentral depths for the 1935 Timiskaming and 1944 Cornwall-Massena 

earthquakes are 10 and 20 km (6 and 12.5 mi.), respectively (Bent 1996a, 1996b). Bent and Perry 

(2002) also observed that earthquakes in the Lower St. Lawrence extend to 27 km (17 mi.) in

depth. The 1988 Saguenay earthquake was anomalously deep, occurring at a depth of 28 km 

(17.5 mi.; Somerville et al., 1990). Based on the above information, thickness of seismogenic 

crust for the SLR seismic source zone is modeled with equal weights at 25 and 30 km (15.5 and 

18.5 mi.). 

7.3.2 Great Meteor Hotspot Zone (GMH) 

The Great Meteor Hotspot (GMH) seismotectonic zone lies within the Western Quebec seismic 

zone as defined by Adams and Basham (1991). This seismotectonic zone is characterized by 

moderate seismicity, including the 1975 M 4.2 (E[M] 4.17) Maniwaki and 1978 M 4.1 

(E[M] 3.82) St. Donat earthquakes (Adams and Basham, 1991); the October 19, 1990, M 4.6 

(E[M] 4.53) Mont-Laurier earthquake (Lamontagne et al., 1994; Du et al., 2003); and the 

February 10, 1914, ML 5.5 (E[M] 5.10) Saint-André-Avellin earthquake (Bent, 2009; Figure 

7.3.2-1). Adams and Basham (1991) have suggested that the band of seismicity north of the 

Ottawa River within the Western Quebec seismic zone is due to crustal fractures that formed as 

the North American Plate rode over a Cretaceous hotspot (Crough, 1981). 

Section 7.3.2.1.1 presents alternative hypotheses for Cretaceous volcanism, including mantle 

plume, lithospheric processes, and/or small convection cells. Regardless of the mechanism for 

Cretaceous volcanism, Sections 7.3.2.1.2 and 7.3.2.1.3 also present evidence of faulting, uplift, 

and geophysical anomalies associated with Cretaceous alkaline rocks. Ma and Eaton (2007) 

propose that seismicity of the Western Quebec seismic zone represents blind intrusions 

associated with entrapment of mantle-derived melt at the transition from kimberlite dikes to 

plutons of the Monteregian Hills. Modern seismicity may be localized along these intrusions 

either by weakened faults and shear zones as a result of reheating of the crust by the hotspot 

track, or by stress concentrations associated with the emplacement of major bodies in more felsic 

crust (Ma and Eaton, 2007). Elevated seismicity rates are present within Grenville-age crust that 

lacks Iapetan rifting but exhibits Cretaceous volcanism and reactivation, and these form the basis 

of the GMH seismotectonic zone. 

The source characterization of the GMH seismotectonic zone is based on a review of published 

material that is summarized in the Data Summary table for the GMH zone (Appendix Table 

D-7.3.2). Explicit references and data that were used as the basis for source characteristics of 

GMH are identified in the Data Evaluation table (Appendix Table C-7.3.2).
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7-16

7.3.2.1 Background 

7.3.2.1.1 Geological Evidence 

Cretaceous volcanism in eastern Canada and New England has been attributed to intrusions 

along preexisting zones of weakness (McHone, 1996) and movement of the Great Meteor 

hotspot track (Morgan, 1983; Crough, 1981; Sleep, 1990) beneath eastern North America. (The 

Great Meteor hotspot is named after the Great Meteor seamount in the central Atlantic Ocean 

[Morgan, 1983]). Morgan (1983) attributed the age distribution of these rocks to two hotspot 

tracks passing through New England at different times: the Verde hotspot track at 160 Ma and 

the Meteor hotspot at about 120 Ma (Figure 7.3.2-2). Geologic evidence for the hotspot (see 

Appendix Table D-7.3.2) consists of an alignment of mapped alkalic intrusions from the 

Monteregian Hills of Quebec (Poole, 1970) through the White Mountain magma series in New 

Hampshire (Zartman, 1977), the Cretaceous seamounts of offshore New England (Duncan, 

1984), the Corner Rise (recorded when the Mid-Atlantic Ridge crossed over the hotspot), to the 

Great Meteor seamount (11–17 Ma) in the Central Atlantic (Morgan, 1983; Figure 7.3.2-2). 

Rock types and chronology of igneous activity related to the GMH can be summarized as 

follows: 

Alkaline intrusive rocks of the Monteregian Hills form circular plugs with steep walls and 

lacoliths within a 241.5 km (150 mi.) long west-trending line between Montreal and Lake 

Megantic of Quebec (Poole, 1970). These intrusions range in age from 84 to 123 Ma, with 

many dates falling between 100 and 115 Ma (Poole, 1970). 

Alkaline rocks of the White Mountain plutonic suite were emplaced over three rather broad 

pulses of magmatism at 220–235 Ma, 155–200 Ma, and 95–125 Ma, but lack any regular 

time-transgressive pattern of ages (Zartman, 1977; Figure 7.3.2-2). 

Duncan (1984) observed that radiometric ages for dredged volcanic rocks from seven of the 

New England seamounts increase in age from the southeast (82.9 Ma for the Nashville 

seamount) to the northwest (103 Ma for the Bear seamount; Figure 7.3.2-2) and fall within a 

longer age progression to the Corner seamounts (70–75 Ma). 

Subsequent mapping by Heaman and Kjarsgaard (2000) extended the GMH track to the 

Rankin Inlet on the west side of James Bay. They identified four periods of kimberlite 

magmatism (at 196, 180–176, 148–146, and 142–134 Ma) along a northwest-southeast trend 

from Rankin Inlet through to the Attawapiskat, Kirkland Lake, and Timiskaming fields 

(Figure 7.3.2-2). These results support a single hotspot track. 

McHone (1996) concluded that lithospheric processes were necessary to start and stop the 

generation of magma from the same source in the mantle. He proposed that heterogeneous 

source areas, coupled with tectonic reactivation of crustal structures, were required to explain the 

wide distribution of intrusions in space and time and the different styles of igneous activity 

expressed onshore and offshore. Heaman and Kjarsgaard (2000) proposed that interaction of the 

hotspot with thinned continental lithosphere toward the continental margin can account for the 

transition from kimberlitic dikes to alkaline intrusions east of Montreal. Subsequent synthesis by 

McHone (2000) attributes Cretaceous magmatism to shallow linear upwelling and convection 

following Jurassic rifting. Matton and Jebrak (2009) propose that periodic reactivation of deep-
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7-17

seated preexisting zones of weakness during major stages of Atlantic tectonic evolution, 

combined with coeval asthenospheric upwelling due to edge-driven convection and continental 

insulation flow, enhanced the ascent of alkaline magmas. Shallow, small-scale upwelling during 

periodic structural reactivation provides a better mechanism for Cretaceous alkaline magmas 

than a mantle plume model (Matton and Jebrak, 2009). 

7.3.2.1.2 Evidence for Reactivation 

Faure et al. (1996b) recognize two distinct phases of Cretaceous extension based on paleostress 

analysis of Cretaceous dike trends and regional- and mesoscopic-scale faults from the 

Monteregian plutons that differ from regional stress fields related to opening of the Atlantic 

ocean (Faure et al., 2006). Paleostress analysis of Jurassic normal faults and dike trends in the 

Quebec and New England Appalachian Mountains distinguishes east-west- and northwestsoutheast-oriented extensional stress regimes (Faure et al., 2006). Fault stress tensors indicate 

that most east-west to east/southeast–west/northwest–oriented stress is found in the Montreal and 

Gaspe area, possibly related to regional partitioning of stress along north-south-trending 

structures in the Champlain Lake valley and the northeast-southwest-trending structures of the 

St. Lawrence rift basin (Faure et al., 2006). An initial Late Triassic east-west extension related to 

the formation of rift basins in the Bay of Fundy and South Georgia and a later Early Jurassic 

east/southeast–west/northwest-oriented extension related to the central Atlantic rift system is 

more consistent with the two-phase rifting models for the opening of the Atlantic Ocean (Faure 

et al., 2006). Subsequent Cretaceous extension consists of an older widespread northeastsouthwest-trending extension and a younger north-south-oriented extension restricted to the 

Montreal area (Faure et al., 1996b). 

Northwest-southeast- to west-northwest-/east-southeast-trending normal faults trend obliquely to 

the Ottawa-Bonnechere graben and have stress orientations that vary between north/northeast–

south/southwest near Ottawa and Montreal and east/northeast–west/southwest in southern 

Quebec (Faure et al., 1996b). East-west-trending normal faults are predominantly found in the 

Montreal area and along the axis of the Monteregian Hills, have similar orientations to regional 

Cretaceous dikes, and have crosscutting relationships indicating they are younger than 

northwest-southeast-trending faults (Faure et al., 1996b). The Ottawa-Bonnechere graben and 

associated basement faults may have acted as localized zones of weakness in the early stage of 

Cretaceous extension, resulting in reorientation of the regional stress field and formation of the 

localized north-south-directed extension (Faure et al., 1996b). Although Faure et al. (1996b) 

attribute these two Cretaceous extensions to an initial northeast-southwest extension event 

associated with rifting between Labrador and Greenland at 140 Ma and opening of the South 

Atlantic at 130 Ma and a subsequent north-south-oriented extension corresponding to global 

fragmentation of Pangaea when Iberia separated from Newfoundland, Faure et al. (2006) 

recognize that the lack of Mesozoic rift basins in central New England and Quebec may be due 

to high topographic elevation induced by a regional thermal event. 

Crough (1981) suggests that the passage of the GMH caused a 600 km (373 mi.) wide zone of 

epeirogeny (broad regional vertical motion) during the Cretaceous and early Tertiary in 

southeastern Canada and New England, resulting in erosion of at least 1 km (0.6 mi.) in Montreal 

and as much as 6–7 km (3.7–4.3 mi.) in New England. Recent thermochronology studies provide 
Chapter 7 

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7-18

evidence for epeirogeny that was accompanied by Late Cretaceous reactivation of faults. RodenTice et al. (2000) interpreted two periods of unroofing of the Adirondack Mountains from apatite 

fission-track dating that must be explained by tectonic denudation processes: Late Jurassic–Early 

Cretaceous (160–120 Ma) throughout the region and Early–Late Cretaceous (~110–80 Ma) in the 

southeast. Roden-Tice et al. (2000) support the hypothesis that this Early–Late Cretaceous uplift, 

contemporaneous with intrusion of the Monteregian Hills plutons, can be attributed to 

differential unroofing resulting from reactivation normal faults. Roden-Tice and Tice (2005) 

attribute the widespread unroofing during the Middle Jurassic–Late Cretaceous to remnant 

heating from the GMH track, accommodated by extensional reactivation of faults in the 

Adirondack Mountains and New Hampshire. Roden-Tice, West, et al. (2009) integrate these 

results with apatite fission-track ages from northeastern Vermont, New Hampshire, and western 

Maine and conclude that normal reactivation of orogen-parallel faults accommodating northwestsoutheast extension is associated with remnant heating from passage of the GMH during the Late 

Cretaceous. 

7.3.2.1.3 Geophysical Evidence 

A remnant thermal anomaly is inferred to exist in the upper mantle and lower lithosphere, based 

on several types of geophysical evidence. Travel-time inversions of teleseismic results from 

southern Ontario image a low-velocity corridor between 50 and 300 km (31 and 186.5 mi.) depth 

that crosscuts regional structures of the Grenville province (Rondenay et al., 2000). These results 

are attributed to a zone of contrasting thermal-compositional-anisotropic properties related to the 

GMH (Rondenay et al., 2000). Subsequent work by Li et al. (2003) using Rayleigh wave paths 

confirms the presence of a broad, low-velocity layer in the upper mantle beneath eastern New 

York and central New England between depths of 60 and 140 km (37 and 225 mi.). This 

anomaly is interpreted as the lateral contrast between relatively thick lithosphere beneath western 

New York and Pennsylvania and the warm asthenosphere beneath the thinned New England 

lithosphere, caused by thermal erosion associated with the Cretaceous hotspot (Li et al., 2003). 

Crustal thickness and average P-wave and S-wave velocity (Vp/Vs) ratio maps derived from 

teleseismic receiver functions illustrate thin crust (Figure 7.3.2-3) and variable Vp/Vs ratio 

northeast of the Ottawa-Bonnechere graben coincident with the Western Quebec seismic zone 

(Eaton et al., 2006), possibly indicating mafic intrusions within felsic crust (Ma and Eaton, 

2007).

7.3.2.2 Basis for Defining Seismotectonic Zone 

Ma and Eaton (2007) recognize that seismicity cannot be easily correlated with Grenville or 

Iapetan structures within this zone and conclude that the GMH provides the only compelling 

explanation for seismicity within the Western Quebec seismic zone. Seismicity may result from

either weakened crust caused by reheating or from stress concentrations caused by strength 

contrasts between mafic and felsic crust (Ma and Eaton, 2007), as indicated by the variable Vp/Vs

observed by Eaton et al. (2006). Crust of the GMH seismotectonic zone is distinguished from the 

adjacent craton on the basis of Cretaceous volcanism and extension, meeting the criterion for 

separating crust of the GMH on the basis of maximum earthquake magnitude. GMH crust lacks 

Iapetan-age faulting and the repeated reactivation expressed within the St. Lawrence rift (SLR) 
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7-19

seismotectonic zone (Section 7.3.1). Additionally, the earthquakes within this seismotectonic 

zone have a depth distribution similar to the SLR seismotectonic zone. However, earthquakes of 

the GMH seismotectonic zone exhibit thrust mechanisms with predominantly northwest-striking 

nodal planes, whereas those of the SLR seismotectonic zone generally exhibit greater variability 

in the strike of nodal planes and a component of strike-slip faulting. Earthquakes of the Northern 

Appalachian and Extended Continental Crust–Atlantic Margin seismotectonic zones have 

shallower depth distributions than the GMH zone. 

7.3.2.3 Basis for Zone Geometry 

The GMH seismotectonic zone lies within the Western Quebec seismic zone, as defined by 

Adams and Basham (1991), who recognized two distinct bands of seismicity within the Western 

Quebec zone. One band trends west-northwest along the Ottawa River between Ottawa and Lake 

Timiskaming, is associated with rift faults of the Ottawa-Bonnechere graben, and is interpreted 

to be part of the SLR seismotectonic zone (Section 7.3.1). The second band trends northnorthwest, extends from Montreal to the Baskatong Reservoir, and is attributed to crustal 

fracturing associated with the passage of a Cretaceous hotspot track. Ma and Eaton (2007) 

propose that seismicity of the Western Quebec seismic zone represents blind intrusions 

associated with entrapment of mantle-derived melt at the transition from kimberlite dikes to 

plutons of the Monteregian Hills. The geometry for the GMH source zone is adopted from the 

Gatineau (GAT) source zone of the GSC H model (Adams et al., 1996; Adams and Halchuk, 

2003) and was compared to data sets listed in the Data Evaluation table (Appendix Table 

C-7.3.2). Given the uncertainty in a plume model as a mechanism for the cause of Cretaceous 

volcanism presented in Section 7.3.2.1.1, alternative geometries based on segments of the 

proposed hotspot track were not considered in the CEUS SSC model. 

The geometry of the GMH zone is consistent with a region of thinner crust northeast of the 

Ottawa-Bonnechere graben observed by Eaton et al. (2006) and with the progressive change 

from kimberlitic melts in the interior of the craton to more voluminous crustal magmatism as the 

hotspot interacted with a progressively thinner lithosphere (Ma and Eaton, 2007). Earthquakes of 

the Kapuskasing cluster, located 100 km (62 mi.) northwest of the zone and separated by an 

aseismic area, have focal depths (4–20 km [2.5–12.4 mi.]; Figure 7.3.2-3) and mechanisms 

(reverse with northwest-striking nodal planes) located along strike of the kimberlite dike portion 

of the hotspot track (Ma et al., 2008). Adams and Basham (1991) postulate that elevated rates of 

seismicity in western Quebec are due to thermally stressed and fractured crust, whereas 

plutonism in New England may have healed deep crustal fractures. Therefore, the geometry for 

the GMH seismotectonic zone encompasses the volume of crust likely to produce frequent 

moderate earthquakes associated with thermally stressed crust. Gravity and magnetic maps do 

not correlate well with seismicity and seismogenic structures (Figure 7.3.2-4) given that the 

mechanisms for earthquakes associated with the GMH track involve thermal weakening. 

7.3.2.4 Basis for Zone Mmax 

No paleoseismic investigations have been performed within the GMH seismotectonic zone. A 

paleoseismic study conducted by Aylsworth et al. (2000; Figure 7.3.2-1), located south of the 
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7-20

GMH within the SLR seismotectonic zone (Section 7.3.1.3), provided evidence for two 

moderate- to large-magnitude paleoearthquakes in the Holocene. Subsequent trenching by 

Aylsworth and Lawrence (2003) documented lateral spreading, surface subsidence, and sediment 

deformation occurring at 7,060 yr BP. As discussed in Section 7.3.1.3, additional research is 

required to constrain the location and magnitude of earthquakes causing this deformation. Ma 

and Eaton (2007) observe that the Mont-Laurier earthquake clusters are located near the 

paleoseismic investigations along the Ottawa River documented by Aylsworth et al. (2000) and 

Aylsworth and Lawrence (2003) and may represent persistent aftershocks of past large 

earthquakes. The maximum observed earthquake for the GMH seismotectonic zone is therefore 

derived from historical and instrumental earthquakes. The largest observed earthquake within the 

zone is the February 1914 E[M] 5.10 Saint-André-Avellin earthquake. 

Kanter (1994) classified crust of the GMH seismotectonic zone as exposed middle Proterozoic 

non-extended crust. However, as described above, Cretaceous uplift (Roden-Tice and Tice, 

2005; Roden-Tice, West, et al., 2009) and Cretaceous mesoscopic-scale normal faulting (Faure et 

al., 1996) provide evidence for Mesozoic extension. Therefore, the maximum magnitude 

distribution for this zone was determined by applying the likelihood function based on the largest 

observed earthquake to the Mesozoic and younger prior distribution. 

7.3.2.5 Future Earthquake Characteristics 

The GMH has been associated with clusters of midcrustal seismicity by Ma and Eaton (2007). 

Ma and Atkinson (2006) attribute the wide hypocentral depth distribution (2–25 km [1.2–15.5

mi.]) for relocated earthquakes in the Western Quebec seismic zone to faults of through-going 

crustal extent or faults of varying depths in the crust. Ma and Atkinson (2006) also note that the 

clustering of focal depths at 5, 8, 12, 15, and 22 km (3, 5, 7.5, 9.3, and 13.7 mi.) may reflect 

layering related to different seismogenic properties within the crust. Ma and Eaton (2007) report 

that shallow earthquakes with relocated depths less than 8 km (5 mi.) are randomly distributed, 

with reverse mechanisms that can be attributed to glacial isostatic adjustment. Ma and Eaton 

(2007) also note that earthquakes with intermediate depths define a linear band of earthquakes, 

and deep earthquakes (greater than 17 km [10.5 mi.] in depth) are localized as clusters at 

Maniwaki and Mont-Laurier. Focal depths for this deep zone extend to 30 km (18.5 mi.; CEUS 

SSC Project earthquake catalog). Seismogenic thickness for the GMH seismotectonic zone is 

modeled with equal weight for 25 and 30 km (15.5 and 18.5 mi.).

Earthquakes within the GMH seismotectonic zone exhibit reverse mechanisms. Bent et al. (2003) 

observe that focal mechanisms can be classified as either thrust or oblique-thrust in response to 

northeast compression. Ma and Eaton (2007) note that these reverse mechanisms have 

southwest-trending P-axes that change to east-west-trending P-axes in the southern portion of the 

zone. Bent (1996a) acknowledges that interpreting which nodal plane for mechanisms within the 

Western Quebec seismic zone corresponds to the fault plane is ambiguous, given that seismicity 

trends northwest and some mapped structures trend northeast. Mechanisms in the southern part 

of the Western Quebec seismic zone, corresponding to the Ottawa graben of the SLR

seismotectonic zone, display more variability in strike and exhibit more strike-slip behavior 

(Bent, 1996a) compared to mechanisms of the GMH seismotectonic zone. Lamontagne et al. 
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7-21

(1994) determined a steeply north-dipping, east-west-oriented nodal plane with a reverse 

mechanism for the October 19, 1990, Mont-Laurier earthquake. Du et al. (2003) observe that 

mechanisms for earthquakes in the Western Quebec seismic zone have strikes of one of their 

nodal planes parallel to the general trend of seismicity. Future ruptures are modeled as 100 

percent reverse faulting. The strike of ruptures is modeled with three orientations consisting of 

N50W (0.4), N20W (0.4), and EW (0.2). The dip of ruptures consists of the default 

characteristics for both styles. Ruptures are allowed to extend beyond the zone boundary. These 

characteristics are presented in Table 5.4.2. 

7.3.3 Northern Appalachian Zone (NAP) 

The Northern Appalachian (NAP) seismotectonic zone (Figures 7.3.3-1 and 7.3.3-2), which is 

characterized by moderate-magnitude, shallow seismicity (Adams et al., 1995), contains crust 

assembled outboard of the Laurentian margin in the Taconic, Salinian, and Acadian orogenies 

and deformed by these events and the subsequent Alleghanian orogeny and Mesozoic extension 

associated with opening of the Atlantic Ocean (see the data summary in Appendix Table D7.3.2). This seismicity occurs above the continental margin within crust of Appalachian terranes 

(Spencer et al., 1989). 

7.3.3.1 Background 

7.3.3.1.1 Geological Evidence 

Crust of the NAP seismotectonic zone postdates Iapetan rifting. The late Cambrian–Middle 

Ordovician Penobscottian orogeny amalgamated composite terranes within arcs of the Iapetus 

Ocean (Murphy and Keppie, 2005). These magmatic arcs, which developed in the late Cambrian 

within the Theic Ocean, were obducted to the Laurentian margin during the Middle–Late 

Ordovician Taconic orogeny (Faill, 1997a; Moench and Aleinikoff, 2003). This deformation 

produced north-south- to northeast-southwest-trending reverse conjugated brittle faults under a 

pure compressional stress regime late in the development of the orogeny (Faure et al., 2004). 

This Taconic compressional event also resulted in reactivation of Iapetan faults in the SLR 

seismotectonic zone as east-northeast/west-southwest dextral and northwest-southeast sinistral 

faults (Rocher et al., 2003; Faure et al., 2004). 

The Late Ordovician–Silurian Salinic orogeny accreted the Gander, Avalon, Nashoba, and 

Carolina terranes to Laurentia during the closing of the Iapetus Ocean during the LaurentiaAvalonia collision (Murphy and Keppie, 2005). Silurian metamorphism (430–410 Ma) in the 

northern Appalachian Mountains is attributed to retrograde metamorphism following the main 

compression event (Tremblay and Castonguay, 2002). Compression of the Salinian orogeny 

involved southeast-directed transport of the Taconian crustal wedge followed by normal faulting 

(Saint-Joseph and Baie Verte–Brompton faults) and development of the fault-bounded 

sedimentary basins of the Connecticut Valley–Gaspé trough (Tremblay and Castonguay, 2002). 

Tremblay and Pinet (2005) attribute the late-stage extension to supracrustal extensional collapse 

caused by late-stage delamination of the lithospheric mantle in a southeast-dipping subduction 

zone. 
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7-22

The Devonian Acadian orogeny has been attributed to either the collision of Avalonia with 

Laurentia or the accretion of the Meguma terrane; however, recent work indicates that the 

Meguma terrane is the passive margin on the southern margin of Avalonia (Murphy and Keppie, 

2005). Murphy and Keppie (2005) interpreted the Acadian orogeny as forming along an Andeantype margin that possibly overrides a plume and swell. Acadian metamorphism is well dated as 

385–375 Ma in the southern part of the Dunnage zone (Tremblay et al., 2000). Deformation from 

the Acadian orogeny is expressed as east-southeast/west-northwest compression in a 

transpressional regime producing east-northeast/west-northwest dextral and northwest-southeast 

sinistral strike-slip faults that crosscut Taconian thrust faults in the Appalachian Mountains of 

Quebec and New Brunswick (Faure et al., 2004). This deformation also resulted in reactivation 

of Iapetan structures in the SLR seismotectonic zone (Faure et al., 2004; Rocher et al., 2003). 

There is general consensus that the late Carboniferous–Permian Alleghany orogeny was due to 

terminal collision between Gondwana and Laurentia-Baltica that closed the Rheic Ocean and 

resulted in the formation of Pangaea (Murphy and Keppie, 2005). The Alleghanian orogeny 

produced decollement tectonism in the central and southern Appalachian Mountains along with 

early penetrative shortening, late low-angle thrusts, low-grade metamorphism, and 

transpressional shear zones. Rocks of the northern Appalachians exhibit relatively high-grade 

metamorphism of Taconic and Acadian crust and deformation of Appalachian deposits near the 

Hudson Valley (Faill, 1998). Although no structures within the northern Appalachians have been 

unequivocably assigned to Alleghanian deformation, brittle faults of the northern Appalachians 

exhibit three phases of compression: an early north-northwest/south-southeast compression, a 

north-northeast/south-southwest compression, and a late west-northwest/east-southeast 

compression (Faure et al., 1996a). 

Mesozoic rifting resulted in the breakup of Pangaea. This rifting is associated with the separation 

of the North American and African plates and produced rift basins along the Atlantic seaboard 

that are situated landward of the hinge zone of the continental margin. This landward region 

experienced considerably less crustal thinning than did the region seaward of the hinge zone that 

includes the deeper marginal sedimentary basins (Klitgord et al., 1988). Faure et al. (2006) 

identified two phases of extension: an initial Late Triassic east-west extension related to the 

formation of rift basins in the Bay of Fundy and South Georgia, and Early Jurassic eastsoutheast/west-northwest extension related to the central Atlantic rift system. 

Apatite fission-track ages across the Norumbega fault zone in southern coastal Maine reveal a 

30–50 Myr discontinuity, suggesting that this fault shows 2 km (1.2 mi.) of vertical offset in the 

Late Cretaceous (West and Roden-Tice, 2003). Roden-Tice and Tice (2005) attribute the 

widespread unroofing during the Middle Jurassic–Late Cretaceous, accommodated by northwestsoutheast extensional reactivation of faults in the Adirondack Mountains and New Hampshire, to 

remnant heating from the Great Meteor hotspot track. 

7.3.3.1.2 Geophysical Data 

Refraction studies across northern New England image crust between 36 and 40 km (22 and 25 

mi.) thick from Maine to Vermont (Hughes and Luetgert, 1991; Taylor and Toksöz, 1982), to 44 

km (27 mi.) thick in New Brunswick and southeastern Quebec (Taylor and Toksöz, 1982). 
Chapter 7 

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7-23

Regional seismic profiles of the Quebec-Maine transect image normal faults in the passive 

margin beneath the master decollement overlain by the St. Lawrence platform and allochthonous 

continental margin sediments and volcanics accreted during the Taconic orogeny (Stewart et al., 

1993). These normal faults do not appear to extend east of the Baie Verte–Brompton line 

(Stewart et al., 1993). 

7.3.3.1.3 Seismicity 

Various special studies provide better constraints for historical earthquakes: Leblanc and Burke 

(1985) determined the location for the March 21, 1904, mbLg 5.9 (E[M] 5.73) Passamaquoddy 

Bay earthquake and three other earthquakes. Burke (2004) revised magnitudes and locations for 

historical earthquakes within the Central Highlands, Moncton, and Passamaquoddy Bay 

subzones. He also later provided complete documentation, with felt areas, for all historical 

earthquakes in New Brunswick (Burke, 2009). Ruffman and Peterson (1988) researched 

historical earthquakes in Nova Scotia under contract with the Geological Survey of Canada and 

provided lists of new and fictitious earthquakes. Unfortunately, this study did not provide 

intensity or felt-area information for determining magnitudes and locations of historical 

earthquakes, and it could be improved upon with further research. 

Ebel (1996) reviewed felt reports in Trois Rivières, Quebec, and Boston, Massachusetts, for the 

June 11, 1638, earthquake and placed the epicenter within the seismically active part of central 

New Hampshire with a magnitude of 6.5 ± 0.5 (E[M] 5.32). Ebel et al. (1986) analyzed historical 

seismograms for two earthquakes occurring in December 1940 near Ossipee, New Hampshire: 

the December 20 ML 5.3 (E[M] 5.08) and December 24 ML 5.4 (E[M] 5.13) earthquakes. 

Instrumental seismicity consists of small- to moderate-magnitude earthquakes, including the 

January 19, 1982, MC 4.7 (E[M] 4.23) Gaza, New Hampshire, earthquake (Brown and Ebel, 

1985) and the January 9, 1982, mbLg 5.7 (E[M] 5.47) Miramichi earthquake (Wetmiller et al., 

1984). 

7.3.3.2 Basis for Defining Seismotectonic Zone 

Crust of the NAP seismotectonic zone postdates Iapetan rifting and therefore should be excluded 

from the SLR and PEZ seismotectonic zones. Terranes of this zone formed outboard of the 

Laurentian margin after Iapetan rifting and were subsequently accreted to the passive margin. 

Normal faulted basement underlying the Taconic master decollement (St. Julien and Hubert, 

1975; Spencer et al., 1989) exhibits en echelon normal faults associated with development of the 

Iapetan passive margin as interpreted from seismic profiles (Spencer et al., 1989). These normal 

faults are depicted at the base of the aulochthonous continental margin sediments northwest of 

the Baie Verte–Brompton line. This crust is included within the SLR seismotectonic zone 

(Section 7.3.1). 

Crust of the NAP seismotectonic zone formed in the Paleozoic and experienced multiple phases 

of extension, including normal faulting in the late stages of the Salinian orogeny (Tremblay and 

Castonguay, 2002) and extensional reactivation of both the Ammonoosuc fault in the Mesozoic 

(Moench and Aleinikoff, 2003) and the Norumbega fault zone in the Late Cretaceous (Stewart et 
Chapter 7 

SSC Model: Seismotectonic Zones Branch

7-24

al., 1993; West and Roden-Tice, 2003). Therefore, the NAP seismotectonic zone meets the 

criterion for application of a Mesozoic and younger prior distribution for maximum earthquake 

magnitude. Crust of the NAP seismotectonic zone is separated from the Extended Continental 

Crust–Atlantic Margin (ECC-AM) seismotectonic zone on the basis of lack of Alleghanian 

structure and Mesozoic rift basins. 

The style of extension within the NAP seismotectonic zone differs from the ECC-AM 

seismotectonic zone (Section 7.3.7) by exhibiting a lack of fault-bounded rift basins. This 

difference has been attributed to Early Jurassic pluton emplacement associated with the White 

Mountain magma series in central New England, which created a topographic high that resisted 

extension (Faure et al., 2006). Roden-Tice, West, et al. (2009) attribute this topographic 

elevation to regional unroofing during the Cretaceous. Additionally, fault rupture characteristics 

for the NAP seismotectonic zone are predominantly reverse (Du et al., 2003; Bent et al., 2003), 

and seismicity of the NAP seismotectonic zone occurs in the upper 10 km (6 mi.) of the crust. 

7.3.3.3 Basis for Zone Geometry 

The geometry for the NAP seismotectonic zone is modified from the Northern Appalachians 

source zone of the GSC (Adams et al., 1996; Adams and Halchuk, 2003). Adams et al. (1995) 

characterized this source zone for use in Canadian seismic hazard maps (Adams et al., 1996; 

Adams and Halchuk, 2003) as extending from the landward limit of Mesozoic extensional 

faulting to the seaward limit of thinned Grenville crust of the Iapetan passive margin. The 

northwestern boundary of NAP coincides with the Baie Verte–Brompton line of Moench and 

Aleinikoff (2003) to restrict Iapetan normal faults below the Taconic decollement to the SLR 

seismotectonic zone. The southeastern boundary follows the Cobequid-Chedabucto fault system 

in Nova Scotia (Pe-Piper and Piper, 2004) and the northern limit of the Fundy Basin and Gulf of 

Maine along coastal Maine (Klitgord et al., 1988), which exhibit clear Mesozoic activity. The 

southwestern boundary was drawn to exclude the Hartford basin, which falls within the ECCAM seismotectonic zone. The northeastern boundary of the NAP seismotectonic zone follows 

the project boundary. 

7.3.3.4 Basis for Zone Mmax 

As part of the EPRI study on earthquakes of stable continental regions, Kanter (1994) classified 

crust of the NAP seismotectonic zone as exposed Paleozoic non-extended crust. However, as 

described above, the NAP seismotectonic zone has experienced several contrasting stress 

regimes, including several phases of extension: Cambrian growth faulting beneath the master 

decollement (St. Julien and Hubert, 1975; Stewart et al., 1993; Spencer et al., 1989); normal 

faulting in the late stages of the Salinian orogeny (Tremblay and Castonguay, 2002); extensional 

reactivation of the Ammonoosuc fault in the Mesozoic (Moench and Aleinikoff, 2003); and 

recurring movement along the Norumbega fault zone (Stewart et al., 1993; West and RodenTice, 2003). Because extension has occurred since the Mesozoic, the maximum magnitude 

distribution for this zone was determined by applying a Mesozoic and younger extension prior, 

updated by a likelihood function based on the largest observed earthquake. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-25

There is some uncertainty about the largest observed earthquake within the NAP seismotectonic 

zone. The largest observed earthquakes include the March 21, 1904, E[M] 5.73, followed by the 

June 11, 1638, E[M] 5.32 and December 24, 1940, E[M] 5.6 earthquakes. There is also some 

possibility that the largest observed earthquake in the ECC-AM seismotectonic zone (1755 E[M]

6.10 Cape Ann earthquake) applies to the NAP seismotectonic zone. Bakun et al. (2003) have a 

preferred location for the 1755 E[M] 6.10 Cape Ann earthquake near the boundary between 

ECC-AM and NAP, with the area defining 95 percent confidence level for the earthquake 

location spread across both seismotectonic zones. Ebel (2006a) estimates the location within 

ECC-AM farther southeast than the Bakun et al. (2003) location based on attenuation of felt 

effects. Therefore, the probability that the 1755 Cape Ann earthquake modifies the prior for the 

NAP seismotectonic zone is assigned a weight of 0.4. The resulting Mmax distributions are 

presented in Section 7.4.2.

7.3.3.5 Future Earthquake Characteristics 

As noted by Adams et al. (1995), all earthquakes in the NAP seismotectonic zone with known 

depths are relatively shallow (less than 10 km, or 6 mi.), the prime example being the Miramichi 

earthquake sequence of 1982 (Wetmiller et al., 1984). Ebel et al. (1986) determined depths of 8 

km (5 mi.)for both 1940 earthquakes. Relocating depths of earthquakes within the NAP 

seismotectonic zone has not been as active an area of research as other seismically active regions 

of Eastern Canada and the northeastern United States. The default depth distribution as described 

in Section 5.4 is applied to the NAP seismotectonic zone. 

Ebel and Bouck (1988) present focal mechanisms for small to moderate earthquakes occurring in 

New England between 1981 and 1987. These mechanisms are predominantly reverse with a 

component of strike-slip. These mechanisms have variable strike directions, including northeastsouthwest, northwest-southeast, north-south, and east-west. Synthetic seismograms for the 

December 20, 1940, Ossipee earthquake provide evidence for a predominantly thrust mechanism 

with either a north-south- or east-west-striking nodal plane (Ebel et al., 1986). Bent et al. (2003) 

observe a combination of thrust and strike-slip faulting in mechanisms for the July 14, 1994, and 

July 15, 1998, New Brunswick earthquakes. Bent et al. (2003) do not observe a consistent trend 

in stress axes orientation. Both solutions exhibit one west-southwest- to west-striking plane 

(Bent et al., 2003)—and the 1994 earthquake has one near north-south nodal plane. The June 16, 

1995, Lisbon, New Hampshire, Mw 3.7 (E[M] 3.17) and August 21, 1996, Berlin, New 

Hampshire, Mw 3.4 (E[M] 3.45) earthquakes have predominantly reverse mechanisms with 

northwest-striking nodal planes. The Lisbon earthquake contains an oblique component (Du et 

al., 2003). Future ruptures within the NAP seismotectonic zone are modeled with 1/3 weight as 

strike-slip and 2/3 weight as reverse with default dip characteristics. The distribution for rupture 

strike is modeled as N50W (20%), NS (20%), N35E (40%), N60E (10%), and EW (10%). 

7.3.4 Paleozoic Extended Crust (PEZ) 

The concept that extended crust may have different seismogenic characteristics (i.e., maximum 

magnitude and related moment rate) than non-extended or Precambrian rifted crust in SCRs has 

been applied to the identification and characterization of regional seismic source zones. Based on 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-26

a global analysis of earthquakes in SCRs, Johnston et al. (1994) concluded that zones of rifted 

crust in SCRs exhibit a higher rate of seismic activity, normalized to a given unit area of crust, 

than nonrifted crust and Precambrian rifts; these zones also have different maximum magnitude 

priors (see discussion in Section 5.2).2

This interpretation by Johnston et al. (1994) resulted in 

efforts to characterize the limit of early Paleozoic (Iapetan) extension within the craton in the 

CEUS by defining the margin of Iapetan rifting. As characterized by Wheeler (1995), the Iapetan 

rifted margin (IRM) encompasses that portion of continental crust that includes known and 

inferred normal faults that formed parallel to the passive margin of Laurentia during the late 

Proterozoic–early Paleozoic opening of the Iapetus Ocean. Compressional reactivation of 

favorably oriented Iapetan faults has been suggested as the causal mechanism for several 

seismically active regions in eastern North America, including Giles County, Virginia, and 

eastern Tennessee (Bollinger and Wheeler, 1988; Wheeler, 1995; Powell et al., 1994). Adams et 

al. (1995) observe that seismicity of the IRM is largely expressed as reverse-slip faulting 

mechanisms in Canada and strike-slip mechanisms in the United States. The IRM concept is 

incorporated in source characterization for the national seismic hazard maps for the United States 

(Petersen et al., 2008) and Canada (Adams et al., 1995). 

For the CEUS SSC Project, crust of the IRM source zone of Wheeler (1995) and Adams et al. 

(1995) has been divided into the St. Lawrence rift (SLR; Section 7.3.1); Northern Appalachian 

(NAP; Section 7.3.3); and Paleozoic Extended Crust (PEZ; this section) seismotectonic zones 

according to geologic criteria established by this project for separating crust on the basis of 

Mmax and future earthquake characteristics. The following discussion addresses the geologic, 

geophysical, and seismic characteristics of the PEZ seismotectonic zone (Figure 7.3.4-1). This 

discussion, as well as the seismic source characterization of the PEZ, is based on a review of 

published material, summarized in the Data Summary table for the PEZ (Appendix Table 

D-7.3.4). Explicit references and data that were used as the basis for source characteristics of 

PEZ are identified in the Data Evaluation table (Appendix Table C-7.3.4). 

7.3.4.1 Background

As discussed in Section 7.3.1.1, breakup of the Mesoproterozoic supercontinent of Rodinia 

occurred as diachronous rifting along the margins of Laurentia. Rifting began on the western 

margin of Laurentia between 780 and 680 Ma during opening of the paleo-Pacific Ocean, and 

resulted in the separation of Australia, Antarctica, south China, and Siberia from Laurentia 

(Whitmeyer and Karlstrom, 2007). This event also resulted in failed rifting along the eastern 

margin of Laurentia (Whitmeyer and Karlstrom, 2007), as evidenced by both the continental 

rift-facies volcanic Mount Rogers Formation of the Virginia/North Carolina Blue Ridge and the 

largely nonvolcanic Ocoee rift deposits farther to the southwest (Faill, 1997a). Successful rifting 

of the eastern margin of Laurentia occurred between 620 and 550 Ma and culminated in the 

rifting of the Argentina Precordillera terrane from the Ouachita embayment (Whitmeyer and 

Karlstrom, 2007). This second phase of rifting is recorded by the volcanic rocks of the Catoctin 

 

2

 As discussed in Section 5.2, analysis of the updated worldwide data set completed for this study suggests that crust 

extended during the Paleozoic cannot be differentiated from non-extended or Precambrian rifted crust and that the 

more statistically significant difference is between Mesozoic and younger crust and older extended/nonextended 

crust.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-27

Formation; sedimentary clastics of the Chilhowee group of Virginia, Maryland, and 

Pennsylvania (Faill, 1997a); and lavas, dikes, and intrusions formed along the eastern margin of 

Laurentia extending north to Labrador (Kumarapeli et al., 1988; Kamo et al., 1995; Higgins and 

van Breemen, 1998; McCausland and Hodych, 1998; Bédard and Stevenson, 1999; Walsh and 

Aleinikoff, 1999; Hodych and Cox, 2007). Within the PEZ seismotectonic zone, these events 

occurred 758 Ma for the Mount Rogers Formation and 564 Ma for the Catoctin rift (Aleinikoff et 

al., 1995; Figure 7.3.4-1). 

The IRM is expressed as promontories and embayments defined by northeast-striking normal 

faults and northwest-striking transform faults along the margins of Laurentia (Thomas, 1991; 

2006; Lavoie et al., 2003). The Peters Creek Formation of southeastern Pennsylvania and 

northern Maryland (Figure 7.3.4-1) may represent deposits transported along an Iapetan rift–

related transform fault linking the southern Lynchburg rift basin with a comparable rift basin in 

southern New England (Valentino and Gates, 1995). The IRM influenced the location of salients 

and angular recesses during subsequent Appalachian orogenesis and Atlantic rifting (Thomas, 

2006). A master detachment separates overthrusted Paleozoic Appalachian terranes from the 

relatively intact continental crust of North America that includes IRM structures (Spencer et al., 

1989; Cook et al., 1979; McBride et al., 2005). In the southern Appalachians, the Consortium for 

Continental Reflection Profiling (COCORP) seismic-reflection data in Tennessee and Georgia 

show the master detachment to be ~6 km (3.5 mi.) deep at the western flank of the Appalachians 

and ~10 km (6 mi.) deep in the Piedmont zone, then quickly steepening to ~35 km (22 mi.) deep 

beneath the peri-Gondwanan Carolina terrane to the east, where it merges with the Moho (Cook 

et al., 1979; McBride et al., 2005). 

The western extent of significant extensional structures associated with the IRM is not well 

defined. The IRM exhibits some tectonic inheritance from Grenville structures. For example, the 

trace of the Alabama-Oklahoma transform corresponds to the probable location of a large-scale 

dextral bend in the Grenville front that subsequently localized the Ouachita salient and 

Mississippi embayment (Thomas, 2006). The New York–Alabama (NY-AL) lineament 

represents a crustal-scale right-lateral strike-slip fault that may have formed during either a late 

postcontractional stage of the Grenville orogeny, Iapetan rifting, or Appalachian orogenesis 

(Steltenpohl et al., 2010). The NY-AL lineament locally parallels and coincides with linear fault 

segments that border the Rome trough (Steltenpohl et al., 2010). Rift-parallel graben systems of 

the Rome trough formed inboard from the rifted margin during late synrift extension (Thomas, 

2006) and may represent inboard extension of Iapetan rifting along the Mesoproterozoic East 

Continent rift basin (Drahovzal, 1997; Stark, 1997). It appears that a part of the fault along the 

southern margin of the trough was reactivated as a normal fault that underwent west-side-down 

dip-slip displacement during the formation of the Rome trough (Steltenpohl et al., 2010). To the 

north, crust northwest of the NY-AL lineament appears to have behaved as a coherent block 

(Steltenpohl et al., 2010). The Michigan basin experienced late Cambrian–Early Ordovician 

subsidence that evolved into different styles and geometry of subsidence in response to 

subsequent Appalachian tectonic events, indicating that Iapetan rifting did not affect the 

Michigan basin (Howell and van der Pluijm, 1999). 

The following subsections present geologic and seismic information for zones of elevated 

seismicity within the continental crust of the PEZ seismotectonic zone. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-28

7.3.4.1.1 Giles County, Virginia, Seismic Zone (GCVSZ) 

Earthquake foci at Giles County in southwestern Virginia define a tabular zone that strikes 

N44 E and dips steeply to the southeast within Precambrian basement lying beneath 

Appalachian thrust sheets (Bollinger and Wheeler, 1983, 1988). This zone, referred to as the 

Giles County, Virginia, seismic zone (GCVSZ), is about 40 km (25 mi.) long, 10 km (6 mi.) 

wide, and 5–25 km (3–15.5 mi.) deep (Bollinger and Wheeler, 1982, 1983; Bollinger et al., 

1991). The zone is oriented about 20 degrees counterclockwise from the east-northeasterly trend 

of the overlying structures in the Valley and Ridge province and subparallel to the northeasterly 

trend of the central Appalachian structures in the northern part of the state (Bollinger et al., 

1991). 

Possible differential uplift of Tertiary and younger New River fluvial terraces in southwestern 

Virginia in the area of the GCVSZ has been postulated as resulting from movement on a series of 

small faults exposed in the terraces (i.e., the high-angle Pembroke faults of Law et al., 1993). 

The location and relative displacement of the Pembroke faults is consistent with orientation of 

the GCVSZ and principal-stress estimates from focal-mechanism studies (Mills, 1986). The 

Pembroke faults and a broad antiformal fold exposed in unconsolidated fluvial deposits have 

raised questions about the possibility of surface tectonic faulting that may be related to seismic 

activity in this region (Bollinger et al., 1992; Law et al., 1993; Robinson et al., 1993). The age of 

the deformed sediments, which lie at 55 m (180 ft.) above the current level of the New River, is 

estimated as 1.5 ± 0.4 Ma or 2.0 ± 0.4 Ma based on analysis of cosmogenic 26Al and 10 Be 

present in the deposits (Granger et al., 1997; Law et al., 1998). Therefore, the age of this 

deformation, whether tectonic or nontectonic in nature, is latest Pliocene to Pleistocene. 

The east-northeast-/west-southwest-trending antiform in these sediments extends over a 

horizontal distance of at least 95 m (312 ft.) from limb to limb and plunges 70 degrees toward 

N64 E. Two grabens are associated with the antiform, one in the hinge zone and one on the 

south-southeast-dipping limb. The grabens are downward-narrowing structures defined by at 

least five extensional faults having apparent dip-slip offsets of 1–2.8 m (3.3–9.2 ft.). These faults 

are marked by 10–20 cm (4–7.8 in.) wide zones of clay-rich infilling. Based on the orientation of 

striae on surfaces within the fault zones, displacements of 11.4 m (37.4 ft.), 1.84 m (6 ft.), 1.1 m 

(3.6 ft.), and 3 m (9.8 ft.) are indicated for four of these faults. Judging from electrical resistivity 

surveys, the major graben is a linear feature that can be traced for a distance of 100–130 m (300–

400 ft.). Recent geophysical investigations (Robinson et al., 1993), however, have not been 

successful in imaging anything below a depth of approximately 35 m (115 ft.), and thus the 

downdip extent of these structures is unknown. Law et al. (1994) presented three models to 

explain the formation of the fold and fault structures at this site: landsliding, solution collapse, 

and basement faulting of tectonic origin. Although some researchers have noted that the 

correlation between surface faults and subdetachment seismogenic structures may be tenuous or 

completely lacking (e.g., Chapman and Krimgold, 1994), Law et al. (1994, 1997) concluded 

from a review of the available data and interpretations that a tectonic origin cannot be ruled out. 

Additional geophysical and subsurface investigations of these structures provide further 

constraints on the origin of the fold and faults. Robinson et al. (2000) show that voids occurring 

in the terrace sediments may result from cavity collapse in the underlying limestone, and that no 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-29

features occur in the limestone basement that correspond to the fold and graben structure in the 

terrace deposits. Williams et al. (2000) map a linear depression in the limestone bedrock surface 

that corresponds to the graben in the terrace deposits, and note that the fold and graben structure 

has a linear nature that is not consistent with a subcircular sinkhole. Law et al. (2000) show that 

the nature of fine structure in some of the terrace deposits is consistent with sedimentation in a 

depression formed by limestone solution, followed by inversion to form the anticlinal structure. 

These observations appear to indicate that some or all of the observed deformation is nontectonic 

in origin. Additional surficial mapping by Anderson and Spotila (2001) of fractures in bedrock 

outcrops shows that the orientation of many small fractures is not consistent with topography or 

with karst-related subsidence. Anderson and Spotila (2001) note that one set of northeasttrending fractures crosscuts the regional structural trend, is oriented consistent with the trend of 

the underlying seismic zone, and may be a surface manifestation of rupture in the seismic zone. 

None of the field evidence, however, provides any direct evidence for Quaternary displacement 

on these fractures. 

7.3.4.1.2 Eastern Tennessee Seismic Zone (ETSZ) 

The Eastern Tennessee seismic zone (ETSZ) is a well-defined, northeasterly trending belt of 

seismicity, 300 km (186 mi.) long by less than 100 km (62 mi.) wide, within the Valley and 

Ridge and Blue Ridge physiographic provinces of eastern Tennessee and parts of North Carolina, 

Georgia, and Alabama (Johnston et al., 1985, Bollinger et al., 1991; Powell et al., 1994; 

Chapman et al., 2002). This area is one of the most active seismic regions in eastern North 

America in terms of the rate of small (i.e., M < 5) earthquakes. 

The earthquakes are spatially associated with major potential field anomalies (King and Zietz, 

1978; Johnston et al., 1985; Bollinger et al., 1991; Powell et al., 1994; Kaufmann and Long, 

1996; Vlahovic et al., 1998; Chapman et al., 2002). For example, the western margin of the 

ETSZ is associated with a prominent gradient in the total intensity magnetic field marking the 

NY-AL lineament (Chapman et al., 2002). Alternative structural models have also been 

postulated to explain the association of seismicity with these anomalies. Powell et al. (1994) 

proposed that the ETSZ is an evolving seismic zone in which slip on north- and east-striking 

surfaces is slowly coalescing into a northeast-trending strike-slip zone running along or near the 

northwest boundary of the Ocoee block in eastern Tennessee. Strike-slip motion would be 

consistent with both the sharp nature of this boundary, as inferred from its magnetic signature, 

and the orientation of the boundary in the contemporary stress field. Powell et al. (1994) 

suggested that the ETSZ seismic activity results from the regional stress field, and the activity is 

coalescing near the juncture between a relatively weak, seismogenic block (the Ocoee block of 

Johnston et al., 1985) and the relatively strong crust to the northwest, which may be strengthened 

by mafic rocks associated with an inferred Keweenawan-age rift (1,100 Ma; Keller et al., 1982). 

Powell et al. (1994) also noted that the densest seismicity and the largest of the instrumentally 

located epicenters in the ETSZ generally lie close to and east of the NY-AL magnetic lineament 

between latitudes 34.3°N and 36.5°N, and west of the Clingman magnetic lineament. 

Based on detailed analyses of the pattern and focal mechanisms of earthquakes in the ETSZ, 

Chapman (1996) and Chapman et al. (1997) present a more refined picture of the nature of 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-30

faulting in the region. Using a revised velocity structure model (Vlahovic et al., 1996), focal 

mechanisms and hypocentral locations were updated. Statistical analysis of trends in the 

earthquake focal mechanisms suggests that earthquakes occur primarily by left-lateral strike-slip 

on east-west-trending faults, and to a lesser degree by right-lateral slip on north- and northeasttrending faults. The hypocenters suggest that possible east-west-trending fault sources are up to 

50–100 km (31–62 mi.) long and lie east of, but adjacent to, the NY-AL lineament. This more 

refined picture is consistent with a tectonic model in which seismogenic faulting is localized 

along a sharp contrast in crustal strength, reflecting competency as represented by the NY-AL 

lineament. 

An alternative model to explain the localization of seismicity in the eastern Tennessee region is 

given by Long and Kaufmann (1994). After an analysis of the velocity structure of the region, 

they conclude that the seismically active areas are not apparently constrained by the crustal 

blocks defined by the NY-AL lineament, but rather their locations are determined by lowvelocity regions at midcrustal depths. They suggest that the data support the conjecture that 

intraplate earthquakes occur in crust that may be weakened by the presence of anomalously high 

fluid pressures. Their data suggest that only a portion of the NY-AL lineament is consistent with 

the interpretation of this lineament as a contact between two crustal blocks having different 

properties. 

Steltenpohl et al. (2010) propose in recent work that seismicity of the ETSZ may be localized 

along a N15°E-trending magnetic low anomaly in the Ocoee block. They observe that seismicity 

occurs south of the NY-AL lineament and follows this trend within the magnetic anomalies. This 

anomaly coincides with the subsurface extension of the Amish anomaly beyond the NY-AL 

lineament and is interpreted to represent metasedimentary gneissic rocks. The modern stress field 

is compatible with that which initiated dextral motion along the NY-AL lineament. The magnetic 

grain of the gneissic rocks and depositional anisotropies could control the spatial pattern of 

modern seismicity, given the lack of known faults. 

Chapman et al. (2002) conclude that the linear segments, and the locations of their terminations, 

may reflect a basement fault structure being reactivated in the modern stress field. They state that 

physical processes for reactivation of basement faults could involve a weak lower crust and/or 

increased fluid pressures within the upper to middle crust. There may be a marginal correlation 

between the seismicity and major drainage pattern and general topography of the region, 

suggesting a possible hydrological element linkage (Chapman et al., 2002). 

7.3.4.1.3 Clarendon-Linden Fault System 

The Clarendon-Linden fault system is located in upstate New York south of Lake Ontario 

(Figure 7.3.4-1) and comprises a broad zone of faults with small displacements in lower 

Paleozoic bedrock. The fault system is at least 77 km (48 mi.) long and 7–17 km (4–10.5 mi.) 

wide and is spatially coincident with a north-trending geophysical (combined magnetic and 

gravity) lineament within the basement rock (Fakundiny and Pomeroy, 2002). The fault system 

extends for approximately 150 km (93 mi.) from just north of the Pennsylvania border (Jacobi 

and Fountain, 1993) to the north shore of Lake Ontario (Hutchinson et al., 1979). 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-31

Closely spaced small-offset step faults characterize the Clarendon-Linden fault system in 

outcrops of Devonian rocks (Jacobi and Fountain, 1993, 1996, 2002). By integrating surface 

stratigraphy, structure, soil gas, and lineaments, Jacobi and Fountain (2002) recognized as many 

as 10 parallel, segmented faults across the fault system in southwestern New York State. The 

main strand of the Clarendon-Linden fault system is highly segmented, steeply east-dipping in 

the north and west-dipping in the south, and displays a maximum vertical displacement of about 

80 m (262 ft.; Jacobi and Fountain, 1993). Cumulative offset across the Clarendon-Linden fault 

system is as high as 130–200 m (426–656 ft.), according to well log, outcrop, and seismic data 

(Jacobi and Fountain, 1996). Forsyth, Milkereit, Zelt, et al. (1994); Milkereit et al. (1992); and 

Zelt et al. (1994) suggested that the Clarendon-Linden fault system is part of a wider zone of 

small Paleozoic faults that lie above the crest of a northeast-trending Precambrian bedrock high 

(i.e., the Iroquoian high). 

The Clarendon-Linden fault system is inferred to extend northeastward beneath Lake Ontario, 

coincident with a bathymetric lineament known as the Scotch Bonnet Rise (Hutchinson et al., 

1979). The Scotch Bonnet Rise is a west-facing bedrock ridge that exhibits approximately 20 m 

(66 ft.) of relief and may be related to faulting (Anderson and Lewis, 1975). Hutchinson et al. 

(1979) collected seismic data across the Scotch Bonnet Rise and, within the resolution of their 

data (approximately 2–3 m [6.6–9.8 ft.]), observed no evidence for postglacial Holocene faulting 

across this feature. Both the Clarendon-Linden fault system and the Scotch Bonnet Rise coincide 

with the east flank of a magnetic anomaly and the west edge of a series of Bouguer gravity 

anomalies, both of which can be traced from west-central New York to the north shore of Lake 

Ontario (Hutchinson et al., 1979). 

Deep seismic-reflection data suggest that the Clarendon-Linden fault system is coincident with 

structures associated with the Elzevir-Frontenac terrane boundary zone of the Grenville province 

(Milkereit et al., 1992; Zelt et al., 1994; Forsyth, Milkereit, Zelt, et al., 1994; Easton and Carter, 

1995). Seismic-reflection profiles show the gently east-dipping ductile thrusts of the ElzevirFrontenac boundary zone extending up to the Precambrian/Paleozoic contact in the region of the 

Clarendon-Linden fault system (Forsyth, Milkereit, Zelt, et al., 1994; Jacobi and Fountain, 

1996). However, the Precambrian structures do not lead directly to individual Clarendon-Linden 

faults (Jacobi and Fountain, 1996). The Salmon River fault, which is exposed approximately 30 

km (18.5 mi.) north of Lake Ontario, is believed to be the northern extension of the ClarendonLinden fault system (McFall, 1993). Farther north, the projection of the Clarendon-Linden fault 

system and Salmon River faults coincide with the Robertson Lake mylonite zone in the Canadian 

Shield (McFall, 1993; Easton and Carter, 1995). The surface continuity of inferred faults 

constituting the Clarendon-Linden fault system is not strongly supported by the reprocessed 

seismic data examined by Ouassaa and Forsyth (2002). Ouassaa and Forsyth (2002) also noted 

that north-northeast-trending curvilinear magnetic and gravity anomalies parallel, but are not 

restricted to, the principal trend of the postulated Clarendon-Linden fault system. 

The Clarendon-Linden fault system probably represents brittle reactivation of a major Grenville 

structure (Hutchinson et al., 1979; Seeber and Armbruster, 1995). The detailed map pattern of 

the Clarendon-Linden fault system shows that the north-south-trending faults comprise numerous 

short segments connected by oblique northwest-trending transfer faults, similar to that in rift 

settings (Jacobi and Fountain, 1996). This geometry suggests that the underlying east-dipping 
Chapter 7 

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7-32

Precambrian thrusts could have acted as a detachment surface, possibly during Iapetan rifting 

(Jacobi and Fountain, 1996). Culotta et al. (1990) correlated the Clarendon-Linden fault system 

with a continental-scale magnetic lineament, the Amish anomaly, which is crosscut by the 

NY-AL lineament (Culotta et al., 1990). This anomaly is interpreted as a major Grenville terrane 

boundary that separates the Elzevir and Frontenac tectonic blocks (Culotta et al., 1990). 

The Clarendon-Linden fault system is associated with a well-defined cluster of seismicity, which 

is referred to as the Attica seismic zone (Seeber and Armbruster, 1995). This zone contains the 

1929 mb 5.2 (E[M] 4.72) Attica earthquake, numerous natural small-magnitude earthquakes, and 

several induced earthquakes associated with salt brine recovery at Dale, New York (Fletcher and 

Sykes, 1977). Seeber and Armbruster (1995) suggest that the 1929 earthquake may have been 

artificially triggered, as the brine fields in Dale were already active in 1929. Dineva et al. (2004) 

relocated hypocenters from earthquakes occurring between 1990 and 2001 that delineate clusters 

of earthquakes beneath Lake Ontario. They report that their cluster C is parallel to the 

Clarendon-Linden fault system but shifted slightly to the southeast by about 4 km (2.5 mi.). 

During the 1990–2001 recording period for their analysis, Dineva et al. (2004) note that little 

seismic activity occurred along the Clarendon-Linden fault system, with only two earthquakes 

near the southern end. 

7.3.4.2 Basis for Defining Seismotectonic Zone 

As described in Section 7.3.4.1, reactivation of Iapetan rift–related structures has been postulated 

as a causal mechanism for localizing seismicity in the Appalachian Mountains, St. Lawrence, 

and eastern Great Lakes regions. Well-documented Iapetan faults that were reactivated during 

the Mesozoic are included in the SLR seismotectonic zone (Section 7.3.1). Likewise, thinned 

Iapetan crust under the Atlantic coastal plain that experienced significant extension during the 

Mesozoic is included in the ECC seismotectonic zone (Section 7.3.7). Postulated Iapetan 

structures beneath the Appalachian detachment west of the Piedmont gravity anomaly gradient 

are not easily identified and are interpreted only from limited seismic and borehole information. 

The PEZ seismotectonic zone encompasses IRM crust in that region, which exhibits some 

evidence of early Paleozoic rifting or extension. 

Extended crust of the PEZ seismotectonic zone does not exhibit clear evidence of rift faulting. 

The deep seismic data collected in Lakes Ontario and Erie (e.g., Milkereit et al., 1992; Forsyth, 

Milkereit, Davidson, et al., 1994; Forsyth, Milkereit, Zelt, et al., 1994; Zelt et al., 1994; White et 

al., 1994) do not show high-angle extensional structures or extensional deformation within the 

PEZ seismotectonic zone on the scale of the Ottawa graben faults or the St. Lawrence rift faults, 

providing very strong evidence that a failed rift arm does not extend into the lake. Faulted lower 

Paleozoic rocks in the northeastern Lake Ontario region (e.g., Grier, 1995; Williams, 1991) 

generally exhibit maximum offsets on the order of several tens of meters. Normal faulting within 

the PEZ seismotectonic zone is associated with the Rome trough, Clarendon-Linden fault 

system, and CMBBZ, which represent extensional reactivation of Grenville structures, as 

opposed to rift structures. 
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Because Mesozoic extension within the PEZ seismotectonic zone is equivocal, crust of the SLR, 

ECC-AM, and ECC-GC seismotectonic zones is separated from the PEZ seismotectonic zone 

based on the more definitive evidence of Mesozoic extension in those zones. However, it is 

difficult to preclude that subdetachment structures within the PEZ seismotectonic zone that are 

currently active were not also reactivated during Mesozoic opening of the Atlantic Ocean 

(Swanson, 1986; Williams, 1978; Pratt et al., 1988; Cook et al., 1979; McBride et al., 2005). 

Therefore, the PEZ seismotectonic zone is differentiated from the adjacent Midcontinent-Craton 

(MidC) seismotectonic zone to accommodate alternative Mmax priors (see discussion in Section 

7.3.4.4). 

7.3.4.3 Basis for Zone Geometry 

The PEZ seismotectonic zone characterizes crust extended in the Paleozoic inboard of the rifted 

margin. Iapetan normal faults likely decrease in size, abundance, and slip gradually and 

irregularly northwestward into the North American craton over a distance of perhaps 100–200 

km (60–120 mi.; Bollinger and Wheeler, 1988). The eastern margin of the Paleozoic 

Appalachian terranes beneath the detachment corresponds to a gravity anomaly gradient 

underlying the Piedmont that is inferred to represent thinning of crust (Pratt et al., 1988) (Figure 

7.3.4-2). Bollinger and Wheeler (1988) suggested that the steep eastward rise in the Bouguer 

gravity anomaly field is the eastern limit for the Iapetan normal faults and that most of the faults 

occur in the relatively intact continental crust of North America west of the gravity anomaly 

gradient. This gravity anomaly gradient, referred to as the Appalachian (Piedmont) gravity 

gradient, is interpreted to mark the transition from thick continental to less thick, and possibly 

more mafic (transitional), crust to the east (James et al., 1968; Kane and Long, 1981; Hatcher 

and Zietz, 1980; Hutchinson et al., 1983). Wheeler (1996) interprets this boundary as the hinge 

zone of the IRM. Two alternative geometries are considered for PEZ, namely, the PEZ Narrow 

and PEZ Wide. The criteria for defining these two alternatives are discussed below. 

7.3.4.3.1 PEZ Narrow 

The PEZ Narrow (PEZ-N) geometry is defined based on structural and seismologic evidence that 

provides the most convincing evidence for the presence of Iapetan faults or rift sediments below 

the detachment (Wheeler et al., 1995). This alternative is given the highest weight (0.8) because 

of the strength of this evidence. The western boundary of the PEZ-N alternative geometry 

follows the Birmingham basement fault system in Alabama and the NY-AL lineament to the 

northeast. Crust northwest of the NY-AL lineament appears to have behaved as a rigid, 

somewhat coherent block, and its sharp boundary against the anomaly implies the edge of this 

competent block (Steltenpohl et al., 2010). King and Zeitz (1982) suggested that the lineament 

acted as buttress during the Paleozoic and limited Appalachian deformation east of it. Seismicity 

is observed below the detachment in Giles County and eastern Tennessee, supporting the concept 

that these earthquakes involve reactivation of Iapetan structures below the detachment surface. 
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7-34

7.3.4.3.2 PEZ Wide 

The PEZ Wide (PEZ-W) geometry extends to the west to capture additional crust that was 

extended to a lesser degree during opening of the Iapetan Ocean. Given that Iapetan rift 

structures and significant extension are assumed to decrease to the west, and the evidence for 

extensional reactivation is limited, a low weight (0.2) is assigned to the PEZ-W alternative. 

The western boundary of the PEZ-W alternative geometry follows the Rome trough in Kentucky 

and West Virginia and the CMBBZ in Ontario. Wheeler (1995) interpreted the ClarendonLinden fault system of upstate New York as the westernmost limit of Iapetan faulting in the 

vicinity of the Great Lakes. The Clarendon-Linden fault system appears to be associated with a 

Grenville shear zone at depth. Movement along the Clarendon-Linden fault system records 

Iapetan reactivation (Seeber and Armbruster, 1995) of the Grenville Elzevir-Frontenac boundary 

zone, indicating the extent of the extensional stress field and not the location of through-going 

rift faults. Lower Paleozoic extensional reactivation also is exhibited farther west on the CMBBZ 

(Milkereit et al., 1992; Forsyth, Milkereit, Davidson, et al., 1994). Recent interpretation of 

seismic lines and regional magnetic data place the western boundary of the CMBBZ on the west 

side of the Mississauga domain as defined by O’Dowd et al. (2004).

The western boundary of the PEZ-W continues southward to the western margin of the Rome 

trough, following the Kentucky River fault system (Van Arsdale, 1986, Potter et al., 1995; 

Steltenpohl et al., 2010). Subsidence of the Rome trough may represent inboard extension of 

Iapetan rifting along the Mesoproterozoic East Continent rift basin (Drahovzal, 1997). Stark 

(1997) attributes development of the Rome trough and reactivation of the Kentucky River fault 

system to reactivation of the East Continent rift complex during Iapetan extension. The western 

boundary of the Rome trough coincides with the western limit of Grenvillian contractional 

deformation (i.e., Grenville front) and the eastern boundary of the East Continent rift basin 

(Drahovzal et al., 1992). 

7.3.4.4 Basis for Zone Mmax 

Paleoseismic investigations from the Rome trough, eastern Tennessee, and the vicinity of the 

Clarendon-Linden fault system do not provide evidence for large-magnitude earthquakes in these 

areas of historically higher seismicity. Van Arsdale and Sergeant (1992) trenched terrace 

materials along the Kentucky River fault system, which forms the northern boundary of the 

Rome trough, and observed evidence for folding and faulting within the last five million years, 

and probably within the last million years. The absence of post-Paleozoic deposits prevents the 

determination of Mesozoic or Tertiary reactivation (Van Arsdale and Sergeant, 1992). Whisner 

et al. (2003) performed paleoseismic reconnaissance investigations in a 300 km2(186 mi.2) area 

within the most active part of the ETSZ and found no evidence of large prehistoric earthquakes. 

An NRC-sponsored research effort was initiated in the ETSZ in the last half of 2009 to help 

clarify the late Quaternary earthquake history and hazard potential of this seismic zone. At 

locations east to northeast of Knoxville, Tennessee, with late Quaternary terrace deposits, 

Vaughn et al. (2010) report the occurrence of outcrop-scale strike-slip, reverse, and normal faults 

and prevalent fractures; minor paleoliquefaction features; and anomalous fractured and disrupted 
Chapter 7 

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7-35

features attributed to liquefaction and forceful expulsion of groundwater during one or more 

major late Quaternary earthquakes. These preliminary observations suggest that the ETSZ has 

produced surface faulting and generated one or more strong earthquakes during late Quaternary 

time. However, these preliminary results could not qualify that RLMEs had occurred in the 

ETSZ, and were therefore insufficient to determine whether the ETSZ could be considered an 

RLME zone and treated accordingly in the CEUS SSC Project. 

A paleoliquefaction study of the Clarendon-Linden fault system was conducted by Tuttle et al. 

(2002). These investigations observed a lack of earthquake-induced liquefaction features in 

geologic units susceptible to liquefaction, suggesting that the fault system did not generate large 

M > 6 earthquakes during the past 12,000 years. Tuttle et al. (2002) conclude that the fault 

system could have produced small and moderate earthquakes, but probably not large earthquakes 

during the late Wisconsinan and Holocene. Because this lack of evidence for paleoliquefaction 

features may not indicate an absence of past earthquakes, the maximum magnitude for the PEZ 

seismotectonic zone is modeled by historical seismicity. 

Paleoseismic investigations in other areas of the PEZ seismotectonic zone have not been carried 

out. Therefore, the maximum magnitude for PEZ-N and PEZ-W is assessed using historical 

earthquakes. The largest observed earthquake in the PEZ seismotectonic zone is the 1897 Giles 

County earthquake (MMI = VIII, mb = 5.7; E[M] 5.91), which occurred within this zone near the 

Virginia–West Virginia border (Bollinger and Hopper, 1971). The next largest earthquakes are 

also located near Giles County and include the 1861 E[M] 5.63 and 1852 E[M] 5.21 

earthquakes. The largest recorded earthquakes associated with the ETSZ are the 1973 MS 4.63

(E[M] 4.01) Maryville, Tennessee, earthquake (Stover and Coffman, 1993) (mb 4.6; Bollinger et 

al., 1991) and the April 2003 M 4.6 (E[M] 4.53) Fort Payne earthquake that occurred in 

northeastern Alabama near the Georgia border. 

A likelihood function based on the moment magnitude of the 1897 Giles County earthquake is 

used to update two prior distributions representing alternative interpretations of the age of most 

recent activation of extensional features in the PEZ seismotectonic zone (NMESE and MESE, 

see Section 5.2). The geometries of the PEZ seismotectonic zone are defined largely by the limit 

of Iapetan rifting in the late Precambrian and early Cambrian. However, some researchers have 

suggested thatMesozoic extension continued west into crust of the PEZ seismotectonic zone. 

Faure et al. (2006) performed paleostress analysis of mesoscopic faults and emplacement of 

Jurassic dikes in Quebec and New Brunswick and concluded that preexisting Neoproterozoic, 

Taconic, Acadian, and Alleghanian structures within this zone were reactivated during the 

opening of the Atlantic Ocean and are kinematically linked to faults bounding Mesozoic basins. 

This work suggests that Atlantic rifting was a widespread extensional event extending as far as 

400 km (244 mi.) into the plate (Faure et al., 2006). Pliocene and younger deformation within 

Giles County (Law et al., 1993, 1998) and the Rome trough (Van Arsdale and Sergeant, 1992) 

can be considered a proxy for Mesozoic activity. Therefore, some weight is given to a Mesozoic 

and younger prior for the PEZ seismotectonic zone. The resulting Mmax distributions are 

presented in Section 7.4.2. 

 

3

 MS = surface-wave magnitude.
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7-36

7.3.4.5 Future Earthquake Characteristics 

Earthquakes within the PEZ seismotectonic zone exhibit predominantly strike-slip focal 

mechanisms with a variety of orientations. Therefore, default characteristics for fault orientation 

are used, but style of faulting parameters is modified to give a higher weight to strike-slip (0.80) 

than to reverse (0.20) faulting based on the focal mechanism information described below. The 

default orientations are therefore modeled with the default characteristics for future earthquakes. 

Bollinger and Wheeler (1988) propose that earthquakes in Giles County consist of strike-slip 

faulting below the Appalachian detachment on steeply dipping (>70 degrees) planes. They 

attribute right-lateral slip on northerly striking nodal planes or left-lateral slip on easterly striking 

nodal planes (Bollinger and Wheeler, 1988) to a series of down-to-the-east, subdetachment faults 

associated with Iapetan rifting (Gresko, 1985). The P-axis estimates (i.e., maximum compressive 

stress axes) are uniformly of a northeasterly (north-northeast to east-northeast) trend with 

subhorizontal inclination, and are similar to the orientation of P-axis estimates elsewhere in the 

region (Bollinger and Wheeler, 1988). 

Focal mechanisms in eastern Tennessee indicate strike-slip faulting on steeply dipping planes 

and a uniform regional stress field with horizontal maximum compression trending N70E 

(Chapman et al., 2002). Most mechanisms involve either right-lateral motion on north-southoriented planes or left-lateral slip on east-west-oriented planes (Chapman et al., 1997). Chapman 

et al. (2002) also note that a smaller population shows right-lateral motion on northeasterly 

trending planes, parallel to the overall trend of the seismicity. The seismicity is not uniformly 

distributed; rather, epicenters form northeasterly trending en echelon segments (Chapman et al., 

2002). 

Focal mechanisms near the Great Lakes are also predominantly strike-slip. Herrmann (1978) 

reported that focal mechanism studies of two shallow (2–3 km, or 1.2–1.9 mi.) earthquakes in 

1966 and 1967 in the Attica area suggested that seismicity occurs along approximately northnortheast-trending Clarendon-Linden faults. The 1966 earthquake (mb = 4.6 [E[M] 4.26]) yielded 

solutions with one nodal plane striking north-northeast and dipping steeply to the east, and a 

second striking west-northwest and dipping steeply to the south. If the north-northeast solution is 

accepted, then the fault motion was primarily right-lateral strike-slip with a reverse component. 

The 1967 earthquaket (mb = 4.4 [E[M] 4.07]) yielded solutions with one nodal plane striking 

north-northeast and dipping steeply to the east, and a second west-northwest-striking plane 

dipping moderately to the south. Again, accepting the north-northeast solution indicates rightlateral and reverse slip on the fault. Herrmann (1978) selected the north-northeast nodal plane as 

the most likely fault plane solution, based on the well log data (Van Tyne, 1975) indicating 

north-northeast-trending Clarendon-Linden faults. He noted, however, that the west-northwest 

trend could not be totally discounted. Kim et al. (2006) determined a predominantly strike-slip 

double-couple moment tensor with a strike of 8 degrees east of north and dipping to the east (50 

degrees) for the August 4, 2004, Lake Ontario earthquake. 

Kim et al. (2006) determined a precise hypocentral depth of 4 ± 2 km (2.4 ± 1.2 mi.) mechanism 

for the August 4, 2004, Mw 3.1(E[M] 3.11) earthquake located in Lake Ontario. This shallow 

depth is consistent with other well-located earthquakes near Lakes Erie and Ontario, including 
Chapter 7 

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7-37

the 1966 Attica earthquake (2 km [1.2 mi.]); the 1967 Attica earthquake (3 km [1.8 mi.]); the 

1998 Pymatuning, Pennsylvania, earthquake (2 km [1.2 mi.]; Du et al., 2003); the 2001 

Ashtabula, Ohio, earthquake (2 km [1.2 mi.]); and the 1986 Perry, Ohio, earthquake. These 

observations suggest a broad-scale strike-slip faulting stress regime with a shallow seismogenic 

layer in the Erie-Ontario Lowlands. Dineva et al. (2004) provide the depth distribution for 

relocated hypocenters in the Great Lakes region. These data are consistent with the shallow 

hypocentral depths mentioned above. However, the entire distribution has a 95th percentile depth 

of approximately 16 km (10 mi.). Ma and Atkinson (2006) determined focal depths for small to 

moderate earthquakes in southern Ontario and northern New York that range from 2 to 15 km 

(1.2 to 9 mi.). Focal depths of most earthquakes in ETSZ range from 5 to 22 km (3 to 13.4 mi.) 

and lie beneath detached Alleghanian thrust sheets (Vlahovic et al., 1998; Chapman et al., 2002). 

Therefore, the thickness of seismogenic crust is modeled using the default alternatives. 

7.3.5 Ilinois Basin Extended Basement Zone (IBEB) 

Southern Indiana and southern Illinois are characterized by higher rates of seismicity than 

adjacent craton regions. Braile et al. (1984) proposed that two branches or arms of the Reelfoot 

rift, the Wabash Valley and St. Louis arms, extend into southern Indiana and southeast Missouri, 

respectively. Although subsequent studies (e.g., Wheeler and Cramer, 2002) have demonstrated 

that highly extended rifted crust does not extend into these regions as far as Braile et al. (1984) 

proposed, the interpretation of seismic profiles and the mapping and dating of paleoliquefaction 

features in the southern Illinois basin provide evidence for multiple paleoearthquakes having 

magnitudes larger than historical earthquakes that have occurred in this region. The two largest 

paleoearthquakes that appear to be localized within the Wabash Valley are included in the 

Wabash Valley RLME source zone (Section 6.1.9). Four additional paleoearthquakes estimated 

to be approximately M 6.2–6.3 are recorded by more widely distributed liquefaction features and 

inferred energy centers for moderate-sized earthquakes beyond the limits of the Wabash Valley 

RLME source (Table 6.1.9-1; Figures 7.3.5-1, 7.3.5-2, and 7.3.5-3). These earthquakes are 

considered in the characterization of the Illinois Basin Extended Basement (IBEB) 

seismotectonic zone. 

An additional energy center near St. Louis, referred to as the Meramec River energy center, is 

not included in the IBEB zone. The Meramec energy center lies outside the areas of extended 

Precambrian basement used to define the zone boundaries (Section 7.3.5.3); it has been 

postulated that paleoliquefaction features here could be the result of smaller (M < 6.0) local 

earthquakes or larger earthquakes (M 7.0–7.5) originating on structures in the southern Illinois 

region (e.g., the Du Quoin monocline/Centralia fault that lies within the IBEB) (Tuttle, Chester 

et al., 1999; Tuttle, 2005b). The Wabash Valley RLME source zone as described in Section 6.1.9 

is an independent zone that characterizes only RLMEs. Earthquakes of magnitudes less than the 

RLME maximum magnitude are modeled based on recurrence parameters for the IBEB 

seismotectonic zone. 
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7-38

7.3.5.1 Background 

McBride, Hildenbrand, et al. (2002) and McBride et al. (2007) have completed integrated 

analyses of geophysical, industry seismic reflection profile, and well data to evaluate possible 

fault sources for historical earthquakes in the southern Illinois basin. These studies suggest that 

both Precambrian basement and Paleozoic structures within the southern Illinois basin have been 

reactivated by recent moderate-sized earthquakes, and that to a large degree, Paleozoic structures 

may be decoupled from deeper seismogenic Precambrian basement structures. Although some 

historical earthquakes, such as the 1987 mb 5.2 (E[M] 4.95) earthquake, may be associated with 

a fault-propagation fold representing possible reactivation of a basement fault that originated 

during the Laramide orogeny), McBride et al. (2007) suggest that a clear association of 

seismicity with mapped structural trends is not well documented throughout the southern Illinois 

basin.

McBride et al. (2007) note that the post-Mississippian structure and stratigraphy of the Illinois 

basin’s thick Paleozoic sedimentary section have been investigated using petroleum industry 

boreholes and limited seismic reflection profiles (e.g., Sexton et al., 1986; Kolata and Nelson, 

1991; Bear et al., 1997; McBride and Nelson, 1999). The seismic stratigraphy and composition 

of the Precambrian basement upper crust have been less well characterized (Pratt et al., 1992; 

Van Schmus et al., 1996; Potter et al., 1997; McBride and Kolata, 1999; McBride et al., 2003), 

and thus the deep structure of the basin remains poorly understood. 

Historical epicenter relocation studies by the USGS, based on the method of Bakun and 

Wentworth (1997), have repositioned moderate- to large-magnitude earthquakes over or near 

major structural axes in the southern Illinois basin (e.g., Du Quoin monocline; Cottage Grove 

fault system; La Salle anticlinal belt) (Bakun et al., 2003; Bakun and Hopper, 2004a). 

The Du Quoin monocline has been suggested by some researchers (Su and McBride, 1999; 

Tuttle, Chester, et al., 1999; Tuttle, Schweig, et al., 2005) as a possible causative source for the 

earthquake that resulted in the paleoliquefaction features in the Shoal Creek–Kaskaskia River 

region of south-central Illinois. 

Other prehistoric earthquakes, such as the Springfield paleoearthquake, cannot be readily 

correlated to mapped structures in the Paleozoic cover rocks, but may be associated with a 

magnetic anomaly (Figure 7.3.5-3). 

7.3.5.2 Basis for Defining Seismotectonic Zone 

The following observations suggest that there are fundamental differences in the crust underlying 

the southern Illinois basin that will influence the maximum magnitude and future earthquake 

characteristics relative to the surrounding regions: 

There is evidence of several moderate-sized paleoearthquakes and higher rates of 

instrumental seismicity in parts of this region that are not recognized in the adjoining craton 

regions. 
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7-39

The southern part of the Illinois basin is one of the most structurally complex areas of the 

Midcontinent (McBride et al., 2007). McBride et al. (2007) note that (1) Proterozoic rift 

faults distinct from those bounding the Grayville graben (in the Wabash Valley RLME 

source zone [Section 6.1.9]) are imaged in Precambrian basement rock below a thick 

sequence of Precambrian layered volcanic rocks; (2) the circular to oval pattern of the 

sequences in plan view argue against a linear rift geometry and and is instead suggestive of a 

large rhyolitic collapsed caldera complex; and (3) newly observed mantle reflectivity beneath 

the Illinois basin indicates significant upper-mantle heterogeneity compared with other parts 

of the United States studied using reflection methods. These observations suggest that crust 

beneath the Illinois basin is distinct from that of the neighboring craton. 

An extensive series of moderately dipping reflectors interpreted to be faults is present in the 

basement. The 1968 mb 5.5 earthquake may have occurred in response to reactivation of one 

of these inferred faults. 

Association of dipping crustal reflectors and gently arched Paleozoic strata suggests an 

additional, but limited, degree of Phanerozoic (post-Precambrian) reactivation of structures 

spatially associated with the strongly deformed deep structure. Moderate-sized historical 

earthquakes that appear to be spatially associated with Precambrian basement faults and with 

Paleozoic faults suggest continued reactivation of older basement features as well as younger 

Paleozoic structures (McBride et al., 2007). 

Stresses induced by Mesozoic rifting possibly extended into the southern Illinois basin, 

resulting in reactivation of deep structures. This concept was initially postulated by Braile et 

al. (1984). Although evidence for Mesozoic rifting is primarily limited to reactivation of 

basement structures in the Grayville graben (included in the Wabash Valley RLME source, 

Section 6.1.9), more distal effects cannot be ruled out. The IBEB is defined in part to allow 

for use of both the non-Mesozoic and younger extended (NMESE) and the Mesozoic and 

younger extended (MESE) Mmax prior distributions in the assessment of maximum 

magnitude. 

Multiple hypotheses have been presented to explain the localization and high rates of Holocene 

activity within the adjacent Reelfoot rift and the New Madrid region to the south (see Section 

6.1.5). Some of these mechanisms may also apply to the southern Illinois and southern Indiana 

region, as follows: 

The presence of intrusive rocks in the Precambrian basement may cause a local stress 

concentration. 

Glacial unloading at the close of the Wisconsinan increased seismic strain rates in the region. 

Descent of the ancient Farallon slab into the deep mantle beneath central North America as 

inferred from high-resolution seismic tomography induces a highly localized flow and 

stresses in the Midcontinent. 

This region, like the NMSZ, may be a lithospheric weak zone on the edge of a high-velocity 

lithospheric block that transfers stress to the upper crust when loaded, thus leading to 

repeated shallow earthquakes. 
Chapter 7 

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7-40

None of the individual characteristics alone are sufficient to define the IBEB as a separate 

seismotectonic zone. However, when considered in combination, they support the contention that 

the IBEB has different seismogenic characteristics and possibly a different Mmax prior 

compared with the neighboring regions. 

The IBEB source zone is defined to characterize sources of moderate- to large-magnitude 

earthquakes (excluding those attributed to the Wabash RLME source) that may occur on deep 

structures in the Precambrian basement and in as Paleozoic faults that extend into the overlying 

Paleozoic sedimentary rocks. 

7.3.5.3 Basis for Zone Geometry 

The roughly oval-shaped Illinois basin, overlying parts of Illinois, Indiana, western Kentucky, 

and southeastern Missouri, contains as much as 7,000 m of Cambrian through Pennsylvanian 

sedimentary rock units (Buschbach and Kolata, 1991; Nelson, 1995; Figure 7.3.5-2). The basin is 

bisected by the La Salle anticlinal belt and the Wabash Valley fault system, both of which have 

expression in the Paleozoic strata. 

The extent of the older Precambrian basement structural features is less well known. McBride, 

Hildenbrand, et al. (2002) identify a proto-Illinois basin based on interpretation of geopotential 

field data; petroleum industry borehole logs (Buschbach and Kolata, 1991); and deep crustal 

seismic data. McBride et al. (2001) report that the first vertical derivative of the reduced-to-pole 

magnetic intensity anomaly map shows a subdued magnetic intensity character associated with 

the Proterozoic rifting and/or layered volcanic sequences in Precambrian basement as inferred 

from deep seismic reflection profiles. The pattern continues to the north and east beyond the 

limits of the deep reflection profile data. The margins of the layered volcanic sequences, 

especially to the south and west, are marked by prominent coincident closed-contour magnetic 

and gravity anomalies, which reflect, at least in part, mafic igneous source intrusions that may be 

related to the original thermal event that produced the Proterozoic Eastern Granite-Rhyolite 

province (1,480–1,450 Ma; McBride et al., 2001) (Figure 7.3.5-3). Other researchers (e.g., Pratt 

et al., 1992; Baranoski et al., 2009, Drahovzal, 2009) have identified rift basin sediments in the 

Precambrian basement below the Paleozoic cover rocks in southern Illinois and southern Indiana. 

Drahovzal et al. (1992) characterize these basement rocks as the western part of the East 

Continent rift basin. Baranoski et al. (2009) also interpret clastic rift basins associated with the 

East Continent rift basin under most of the southern Illinois basin and a basaltic rift basin 

extending into northern Illinois (Figure 7.3.5-2). 

The boundaries of the IBEB are drawn to roughly encompass the various interpretations of 

basement rift sediments and the areas where moderate-sized prehistoric earthquakes have been 

identified from paleoliquefaction studies. Because the boundary of the IBEB is not well defined 

by these data and its exact geographic location is uncertain, it is treated as ―leaky,‖ such that 

ruptures that nucleate within the zone may also propagate outside the uncertain geographic 

boundary of the source zone. 
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7-41

7.3.5.4 Basis for Zone Mmax 

The Mmax distribution for the IBEB uses only the Bayesian approach, as outlined in Section 5.2. 

The three largest historical earthquakes recorded within the zone are the September 27, 1891, 

E[M] 5.52; August 15, 1891, E[M] 4.97; and April 18, 2008, E[M] 5.30 earthquakes. Four 

prehistoric earthquakes inferred from the paleoliquefaction studies have estimated magnitudes 

that are larger than the historical earthquakes. These are the ~M 6.3 Vallonia, ~M 6.2 Shoal 

Creek, ~M 6.2 Springfield, and M 6.2 Waverly earthquakes (Figure 7.3.5-1; Table 6.1.9-1). 

For the Bayesian approach, three alternative priors are considered: COMP, a composite (weight 

of 0.4); NMESE, non-Mesozoic and younger extended (weight of 0.48); and MESE, Mesozoic 

and younger extended (weight of 0.12). The NMESE prior is given a high weight (0.48) based on 

the lack of evidence for Mesozoic mafic intrusions and significant Mesozoic or younger 

extension throughout the IBEB zone. Less weight is given to the possibility that stresses 

associated with Mesozoic extension in the adjacent Reelfoot rift may have propagated into the 

IBEB zone, giving rise to some reactivation of structures in both the Precambrian basement and 

the overlying Paleozoic cover. The COMP prior also is given a relatively high weight (0.4) based 

on the uncertainty in the characteristics that influence maximum magnitude. The prior 

distribution in each case is truncated and modified based on the evidence for the four moderatesized paleoearthquakes (M 6.2–6.3) in the zone that are not modeled as RLMEs. Due to the 

uncertainty in the sizes of these paleoearthquakes, which are based primarily on the magnitudebound curve presented by Olson et al. (2005b), a sigma of 0.25-magnitude units is used in the 

development of an updated likelihood function. The derived Mmax distribution for IBEB is

presented in Section 7.4.2. 

7.3.5.5 Future Earthquake Characteristics 

Characteristics for future earthquake ruptures in the IBEB source zone are given in Table 5.4-2. 

The aleatory variability in the future earthquake characteristics assigned to the IBEB is based on 

the following: 

Consideration of focal mechanisms in the southern Illinois basin region, which are a mixture 

of interpreted north-northeast-trending strike-slip and reverse mechanisms (Taylor et al., 

1989; McBride, Hildenbrand, et al., 2002; McBride et al., 2007; Larson, 2002; Hamburger et 

al., 2008; Larson et al., 2009; Withers et al., 2009; Yang et al., 2009). 

Orientations of mapped Paleozoic structures (Nelson, 1995). 

Orientations of Precambrian basement faults and inferred structures (McBride et al., 2007). 

The expected style of faulting and fault dip vary with the fault orientation and are inferred based 

on comparison to focal mechanisms and fault geometry, which is also inferred based on analysis 

of seismic profiles and seismicity data. The majority of earthquakes having well-constrained 

focal mechanisms show strike-slip movement. Therefore, strike-slip behavior overall is judged to 

be more likely. However, reverse faulting mechanisms for historical earthquakes also have been 

associated with reactivated Precambrian basement and Paleozoic structures (McBride et al., 

2007). 
Chapter 7 

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7-42

The depth of future ruptures is based on reported depths of seismicity within the IBEB (Taylor et 

al., 1989; McBride, Hildenbrand, et al., 2002; McBride et al., 2007; Hamburger et al., 2008; and 

Yang et al., 2009). The deepest well-constrained earthquake hypocenters in the Fairfield basin, a 

relatively deep part of the Illinois basin, are located at depths of 20–22 km (12.4–13.7 mi.; 

(McBride et al., 2007; Yang et al., 2009). However, the average depth throughout the IBEB zone 

based on other historical earthquakes may be less. Therefore, a range of values from 13 to 22 km 

(8 to 13.7 mi.) is used to model the average seismogenic depth within the zone. 

7.3.6 Reelfoot Rift Zone (RR)

The Reelfoot Rift (RR) seismotectonic zone beneath the northern Mississippi embayment is 

interpreted as a Cambrian aulacogen (Ervin and McGinnis, 1975; Thomas, 1991). The crystalline 

basement rocks defining the rift have been mapped from gravity, magnetic, and seismic 

refraction and reflection data, as well as from subsurface information derived from a few deep 

petroleum exploration wells (Hildenbrand, 1982; Mooney et al., 1983; Hildenbrand and 

Hendricks, 1995; Langenheim and Hildenbrand, 1997; Dart and Swolfs, 1998; Parrish and Van 

Arsdale, 2004; Csontos et al., 2008; Csontos and Van Arsdale, 2008). The RR zone includes the 

Reelfoot graben as defined by gravity, magnetic, and seismic data, as well as the regions 

marginal to the rift graben where crustal extension also is indicated by secondary structures and 

Mesozoic mafic and ultramafic plutons (Hildenbrand and Hendricks, 1995). 

RLME sources within the RR zone are independent sources that characterize only RLMEs; these 

sources include the New Madrid Fault System (NMFS; Section 6.1.5), Eastern Rift Margin 

(ERM; Section 6.1.6), Marianna (MAR; Section 6.1.7), and Commerce Geophysical Lineament 

(CGL; Section 6.1.8) RLMEs. 

The source characterization of the RR described in the following text is based on a review of 

published material outlined in the Data Summary table for the Reelfoot Rift–New Madrid Fault 

System (Appendix Table D-6.1.5-1). Explicit references that were used as the basis for source 

characteristics are identified in the Data Evaluation table for the RR zone (Appendix Table 

C-7.3.6). 

7.3.6.1 Background 

7.3.6.1.1 Evolution of the Reelfoot Rift 

Csontos et al. (2008) outline the major tectonic events and evolution of the Reelfoot rift. The 

following observations are primarily summarized from Csontos et al. (2008) and cited 

references: 

The Reelfoot rift graben structures are part of the Reelfoot rift–Rough Creek graben–Rome 

trough intracratonic rift zone that formed during the disassembly of Rodinia and opening of 

the Iapetus Ocean in late Proterozoic time (Thomas, 1976; 2006). Rifting may have been 

initiated by an upwelling mantle plume that developed along terrane boundaries (Dart and 

Swolfs, 1998). Alternatively, the Reelfoot rift may be a consequence of right-lateral strike-
Chapter 7 

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7-43

slip motion along a northwest-oriented transform fault that formed the Paleozoic continental 

margin of southeastern Laurentia (Thomas, 1991). 

An anomalously dense layer is present at the base of the crust and thickens beneath a broad 

northeast-trending graben that formed during the initial stages of Iapetan rifting. The thickest 

part of the anomalous crust underlies the region of greatest seismic activity within the 

geographic limits of the Reelfoot rift (Hildenbrand, 1982). 

Cambrian Reelfoot rifting occurred primarily along large normal faults that appear to become 

listric with depth (Nelson and Zhang, 1991). However, the straight margin faults suggest that 

the northeast-trending rift structures originated as strike-slip faults (Hildenbrand, 1985). 

A maximum of 7 km (4.3 mi.) of sediment accumulated in the Reelfoot graben during rifting 

that continued into middle Cambrian time, while outside the rift only 1.5 km (0.9 mi.) of 

contemporary sediments accumulated. Regional subsidence and sedimentation continued 

during the late Cambrian–Middle Ordovician time (Dart and Swolfs, 1998). From Middle 

Ordovician to Pennsylvanian time, subsidence and uplift alternated due to distal effects of the 

Taconic, Acadian, and Alleghanian orogenies.

Structural reactivation of the Reelfoot rift began during the late Paleozoic with the assembly 

of Pangaea (Thomas, 1985). An unconformity atop the Paleozoic rock units represents midCretaceous uplift and erosion. Sense of slip along many preexisting normal faults within the 

Central United States was inverted to reverse slip during the Paleozoic collisional processes 

(Marshak and Paulsen, 1996). 

Cox and Van Arsdale (1997, 2002) proposed that the regional mid-Cretaceous uplift and 

subsequent subsidence of the Mississippi embayment occurred as the North America Plate 

drifted over the Bermuda hotspot. 

Late Cretaceous and Cenozoic sediments record transgressive-regressive sequences within 

the Mississippi embayment trough (Thomas, 1985). 

Fluvial erosion and deposition during the Pliocene resulted in deposition of the Upland 

Complex, a terrace of the ancestral Mississippi-Ohio River system (Van Arsdale et al., 2007). 

Crowley’s Ridge formed from erosion of the Western Lowlands by the ancestral Mississippi 

River, erosion of the Eastern Lowlands by the ancestral Ohio River, and Quaternary 

reactivation of ridge-bounding faults (Van Arsdale et al., 1995). 

Repeated periods of glacial meltwater escape, sea-level change, loess deposition, and 

structural deformation have produced various river terraces, river courses, lakes, and areas of 

warping during the Quaternary (Autin et al., 1991; Schweig and Van Arsdale, 1996). Four 

processes affected base level through the Quaternary: glacio-eustatic sea-level changes, 

variations in rates and patterns of sediment yield, climatic changes, and tectonic activity. 

The principal seismic activity within the upper Mississippi embayment currently is interior to 

the Reelfoot rift along the NMSZ. 
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7-44

7.3.6.1.2 Major Structures 

Major basement structures and tectonic features associated with the Reelfoot rift graben are 

shown on Figure 7.3.6-1; structural and tectonic features inferred from interpretation of 

geopotential field data (gravity and magnetic) are shown on Figure 7.3.6-2. Using a structurecontour map and a three-dimensional computer model of the top of the Precambrian crystalline 

basement, Csontos et al. (2008) show the Reelfoot rift to consist of two major basins, separated 

by an intrarift uplift, that are further subdivided into eight subbasins bounded by northeast- and 

southeast-striking rift faults, some of which have been reactivated as reverse or oblique-slip 

faults. 

Tectonic landforms within the central Mississippi River valley are directly linked to the 

underlying Reelfoot rift faults (Figure 7.3.6-1; Mihills and Van Arsdale, 1999; Csontos et al., 

2008; Csontos and Van Arsdale, 2008). Recent seismologic, geologic, and geophysical studies 

have associated some of these basement faults within the NMSZ with large-magnitude historical 

earthquakes that occurred in 1811 and 1812. These faults are referred to as the New Madrid fault 

system (NMFS). Quaternary displacement also has been documented along the Eastern Rift 

margin (Cox, Van Arsdale, and Harris, 2001; Cox, Van Arsdale, et al., 2001; Cox et al., 2006); 

Western Rift Margin (Van Arsdale et al., 1995; Baldwin et al., 2005); Axial fault (Van Arsdale, 

1998; Guccione et al., 2000); Reelfoot fault (Russ, 1982; Kelson et al., 1996; Mueller et al., 

1999; Van Arsdale et al., 1999; Champion et al., 2001); and Fluorspar Area fault complex 

(Nelson et al., 1997; Nelson, Denny et al. 1999; McBride, Nelson, and Stephenson, 2002; SAIC, 

2002; Woolery et al., 2009). In addition, the Lake County uplift, which is essentially coincident 

with the seismicity between the central and northern 1811-1812 earthquakes shown on Figure 

7.3.6-1, the Reelfoot Lake basin, the southern half of Crowley’s Ridge, the Big Lake and Lake 

Saint Francis Sunklands area, and Joiner Ridge are interpreted to be tectonic or tectonically 

influenced landforms (Csontos et al., 2008). 

NMSZ faults have also modified Mississippi River gradients and influenced sedimentary 

processes during the Quaternary (Schumm and Spitz, 1996; Spitz and Schumm, 1997; Guccione, 

Mueller, et al., 2002; Guccione, 2005; Holbrook et al., 2006). Johnston and Schweig (1996) have 

proposed that the Bootheel lineament produced one of the major earthquakes of the 1811-1812 

sequence. Guccione et al. (2005) confirmed Quaternary displacement along the Bootheel 

lineament and suggested the feature should be referred to as a fault. However, Csontos (2007) 

mapped the Precambrian basement unconformity and the Pliocene-Pleistocene unconformity 

surfaces within the Reelfoot rift, and sees no evidence of vertical displacement or hypocenter 

alignment along the Bootheel fault. This lack of vertical displacement may be due to a very 

young Bootheel fault with relatively minor displacement, or the actual fault displacement may be 

primarily strike-slip. 

The NMFS, Quaternary active faults along the northwestern and southeastern margins of the 

zone (i.e., the ERM and CGL fault zones, respectively), and unknown structures in the southern 

part of the rift near Marianna, Arkansas, are characterized as RLME sources (NMFS, ERM, 

MAR , and CGL RLME sources; Figure 6.1-1). Section 6.1 provides a detailed description of 

these RLME sources. 
Chapter 7 

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7-45

The Fluorspar Area fault complex (FAFC) structures, which originated as normal faults during 

latest Proterozoic and early Cambrian time coincident with the formation of the northeasttrending faults associated with the Reelfoot rift, have experienced periodic reactivation in postPennsylvanian, pre-Cretaceous, and late Neogene–Quaternary time (Nelson, Denny, et al., 1999; 

McBride, Nelson, and Stephenson, 2002). The FAFC structures were very active, with evidence 

for large-magnitude earthquakes as reflected by surface manifestation of faulting as far back as 

latest Pleistocene (Nelson, Denny, et al., 1999; McBride, Nelson, and Stephenson, 2002). 

Despite efforts to identify and document evidence for Holocene activity on several of the FAFC 

structures, no convincing evidence of Holocene activity has been identified on any of the faults 

(E. Woolery, pers. comm., February 9, 2010). Reported evidence supporting Holocene 

displacement on one of the major faults within this system, the Barnes Creek fault (SAIC, 2002), 

is very equivocal based on the following observations: 

There is an apparent absence of faulting observed in the upper younger deposits (i.e., 

presence of only a fracture). 

The origin of the observed fracture is uncertain (e.g., possibly related to roots). 

There is an absence of distinct stratigraphic evidence for Holocene displacement on this fault 

and other faults within the FAFC (WLA, 2006; E. Woolery, pers. comm., February 9, 2010). 

There also is a general lack of paleoliquefaction evidence for large-magnitude earthquakes in the 

northern Reelfoot rift that cannot be attributed to the New Madrid earthquakes. Older, weathered 

paleoliquefaction features in western Kentucky to the east of the FAFC appear to have formed 

within the past 4,850 years (WLA, 2006; Appendix E). An older earthquake, the source of which 

has not been determined, is recorded by older paleoliquefaction features dated at 11,300 yr BP ± 

200 yr (Appendix E). Rupture along the northern Eastern Rift margin fault, or along one of the 

Wabash Valley fault zone structures (e.g., the Hovey Lake fault) that exhibit evidence for 

possible latest Pleistocene displacement, is considered to be a likely source of the earthquake that 

produced these older paleoliquefaction features. 

Because of the lack of definitive evidence for Holocene or latest Pleistocene faulting of the 

FAFC, McBride, Nelson, and Stephenson (2002) propose a dynamic structural model that 

suggests a mechanism by which seismicity and active (Holocene) faulting have shifted within the 

central Mississippi Valley, away from the FAFC, over the last several ten thousand years. There 

is no evidence to indicate that the FAFC should be modeled as an RLME source, and a 

seismicity-based estimate of recurrence on the FAFC is consistent with the latest 

Pleistocene/Holocene record. 

Quaternary reactivation of faults bounding Crowley’s Ridge, a topographic ridge that spans the 

western margin of the Reelfoot rift in northeastern Arkansas and southeastern Missouri, is 

inferred from interpretation of high-resolution geophysical data and geomorphic relationships 

(Van Arsdale et al., 1992, 1995). Van Arsdale et al. (1995) infer that the faults bounding the 

ridge likely are right-lateral strike-slip faults that appear to have been active in late Wisconsinan

time. This ridge, which is subparallel to the CGL in northeastern Missouri, diverges in trend 

from the CGL in northeastern Arkansas (Figure 7.3.6-1). Because no definitive evidence for 

recurrent late Pleistocene deformation has been identified along Crowley’s Ridge, if faults 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-46

bounding this ridge are active, they may have much lower slip rates than faults identified in the 

Thebes Gap/Benton Hill region. Therefore, potential slip on faults along Crowley’s Ridge is 

represented by earthquakes occurring in the RR seismotectonic or Mmax zone. 

Other structures postulated as potential Quaternary neotectonic features (e.g., Joiner Ridge 

[Csontos et al., 2008] and a north-northwest-trending Meeman-Shelby fault–Joiner Ridge 

boundary fault [Odum et al., 2010]) also do not offer sufficient evidence to be modeled as RLME 

sources. 

7.3.6.2 Basis for Defining Seismotectonic Zone 

The following observations suggest that there are fundamental differences in the crust underlying 

the RR that will influence maximum magnitude and future earthquake characteristics relative to 

the surrounding regions: 

The RR graben structures were reactivated during Mesozoic rifting and experienced 

Mesozoic and younger plutonic activity. The extended crust within and adjacent to the 

central rift basin contrasts with the surrounding, more stable non-extended crust. 

The higher rate of seismicity within the RR and the occurrence of multiple Quaternary active 

faults and tectonic landforms within the RR, in addition to the identified RLME sources, 

suggest that tectonic strain has been localized within and adjacent to the rift. Multiple 

hypotheses have been presented to explain the localization and high rates of Holocene 

activity within the rift and the New Madrid region (see Section 6.1.5).

The RR is expected to have distinct differences in future earthquake characteristics compared 

to surrounding regions. For example, focal depths for a well-located earthquake in the RR

show that the seismogenic crust is not as deep as in parts of the Illinois Basin Extended 

Basement (IBEB) seismotectonic zone to the north. Detailed seismic surveys (e.g., Pratt, 

2009), studies of the crustal architecture of the basin, and deformation of the PliocenePleistocene unconformity surface (Csontos et al., 2008) provide specific information about 

the orientation of structures that may have experienced Quaternary reactivation, and this 

information can be used to differentiate the earthquake characteristics for the RR (Section 

7.3.6.5) from the default values used for the adjacent Midcontinent-Craton (MidC) and 

Extended Continental Crust–Gulf Coast (ECC-GC) zones. 

7.3.6.3 Basis for Zone Geometry 

The first branch of the RR logic tree (Figure 7.3-1) addresses the uncertainty about the inclusion 

of the Rough Creek graben (RCG) into the RR source zone. The RCG represents the eastward 

extension of extensional deformation related to formation of the intracontinental rift system 

during Precambrian to earliest Cambrian rifting of North America (Braile et al., 1982, 1986; 

Kolata and Nelson, 1991). Initial development involved strike-slip and extensional faulting 

related to the development of the Reelfoot rift, probably in latest Proterozoic or early Cambrian 

time. Some of the structures may have been reactivated in post-Pennsylvanian time, probably 

during the late Paleozoic Ouachita orogeny (Kolata and Nelson, 1991). The RCG is bounded on 
Chapter 7 

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7-47

the north by the south-dipping, listric Rough Creek fault and on the northwest by the 

Shawneetown fault (Nelson and Lumm, 1987; Kolata and Nelson, 1991). The southern boundary 

approximately follows the Pennyrile fault system (Nelson and Lumm, 1987), which forms the 

southern margin to the Paleozoic syn-rift deposits (Kolata and Nelson, 1991). The RCG in 

western Kentucky is structurally connected to the northern portion of the RR that includes the 

Fluorspar area of southern Illinois (Soderberg and Keller, 1981; Kolata and Nelson, 1991; Potter 

and Drahovzal, 1994). Wheeler (1997), however, defines a boundary in this region between the 

RCG and the Reelfoot rift/Fluorspar area based on changes in the strikes of single large faults, 

the location of a Cambrian transfer zone, and the geographic extent of alkaline igneous rocks that 

provide three independent estimates of the location of a structural boundary between the rift and 

graben. 

Faults associated with the RCG show strong evidence for initiation during late Proterozoic–

Cambrian Iapetan-phase rifting and reactivation during the mid to late Paleozoic AppalachianOuachita orogeny (Heyl, 1972; Soderberg and Keller, 1981; Thomas, 1991; Noger, 1988, Kolata 

and Nelson, 1991; Potter et al., 1995). Mesozoic activity on RCG faults also is suggested by 

post-Permian displacements and regional correlation of extensional deformation associated with 

post-Permian to pre-Cretaceous rifting of the Pangaea continental landmass (Kolata and Nelson, 

1991). However, the lack of clearly associated alkaline igneous rocks of Mesozoic age in the 

RCG (Wheeler, 1997) suggests that Mesozoic reactivation of deep-penetrating faults was 

limited. 

Based on these observations, lower weight (0.333) is given to the inclusion of the RCG in the RR 

zone and higher weight (0.667) is given to limiting the RR to the more seismically active part of 

the rift that also experienced greater Mesozoic extension. 

7.3.6.4 Basis for Zone Mmax

The Mmax distribution for the RR is based on the two approaches outlined in Section 5.2: the 

Bayesian approach and the Kijko [2004] approach. For the Bayesian approach, the Mesozoic and 

younger prior is used in addition to the composite prior. The prior is truncated by the two largest 

historical earthquakes recorded within the zone: the January 5, 1843, and October 31, 1895 

earthquakes, which are interpreted to be M 6 (E[M] 6.00) earthquakes (Bakun et al., 2003). The 

1811-1812 sequence of earthquakes and other large-magnitude prehistoric earthquakes 

recognized in the RR are included in the characterization of the RR RLME sources (NMFS, 

ERM, MAR, and CGL).

The weights for the Bayesian and Kijko approaches for the RR zone and the weighted composite 

posterior maximum-magnitude probability distribution for the RR zone are presented in Section 

7.4.2. 
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7-48

7.3.6.5 Future Earthquake Characteristics 

Characteristics for future earthquake ruptures in the RR source zone are given in Table 5.4-2. 

The aleatory variability in the future earthquake characteristics assigned to the RR is based on 

the following: 

Consideration of focal mechanisms (Zoback, 1992; Shumway, 2008). 

Orientations of RLME fault sources and faults that do not meet the criteria for RLME 

sources but have evidence of reactivation in the Quaternary (e.g., the north-northeasttrending FAFC faults, the north-trending faults bounding the southern part of Crowley’s 

Ridge). 

Orientations of basement faults and inferred structures that deform the Pliocene-Pleistocene 

unconformity (Csontos et al., 2008). 

The expected style of faulting varies with fault strike and is inferred based on comparison to 

focal mechanism and fault geometry interpreted from seismic profiles and seismicity data. The 

majority of earthquakes having well-constrained focal mechanisms show strike-slip movement 

(Zoback, 1992; Shumway, 2008). Therefore, strike-slip behavior is judged to be more likely. 

Faults and postulated structures with trends subparallel to the Reelfoot thrust fault, however, are 

expected to behave as reverse faults in the present tectonic stress environment. 

Seismogenic depth is based on reported depths of seismicity within the RR (Zoback, 1992; Chiu 

et al., 1992, 1997; Herrmann and Ammon, 1997; Mueller and Pujol, 2001; Shumway, 2008; 

Csontos and Van Arsdale, 2008). In the central and northern part of the rift, seismicity is 

observed at depths between 5 and 15 km (3.1 and 9.3 mi.); (Chiu et al., 1992; Shumway, 2008). 

Along the southeastern margin of the rift, seismicity is slightly deeper, with earthquakes 

recorded between 13.9 and 22.8 km (8.6 and 14.2 mi.). The average depth of seismicity across 

the entire zone, which takes into account uncertainties in the velocity model and measurements, 

is considered to range from 13 to 17 km (8 to 10.6 mi.). 

Specific parameters and weights used to characterize future ruptures in the RR are given in 

Table 5.4-2. 

7.3.7 Extended Continental Crust–Atlantic Margin Zone (ECC-AM) 

The Extended Continental Crust–Atlantic Margin (ECC-AM) seismotectonic zone was defined 

to include the region characterized by the presence of extended continental crust developed 

during Mesozoic rifting along the Atlantic Ocean basin margin. This seismotectonic zone 

extends from Georgia to Nova Scotia and includes onshore portions of the Piedmont and Coastal 

Plain provinces as well as most of the offshore continental shelf region (Figures 7.3.7-1 and 

7.3.7-2). 

Breakup of the supercontinent of Pangaea and formation of the Atlantic Ocean basin in the 

Triassic and Jurassic produced the present-day passive Atlantic margin, which can be divided 

into three general zones based on several characteristics, including crustal structure, composition, 

and thickness. These zones, from west to east are (1) rifted and extended continental crust 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-49

beneath the Piedmont, Coastal Plain, and continental shelf; (2) a 50–100 km wide (31–62 mi.) 

zone of highly extended transitional crust; and (3) mafic oceanic crust lying beneath the 

continental rise (Klitgord et al., 1988; Holbrook, Reiter, et al., 1994). The ECC-AM 

seismotectonic zone includes only the rifted and extended portion of the continental crust. The 

narrow zone of highly extended transitional crust is included in the AHEX seismotectonic zone 

(see Section 7.3.8). 

This chapter discusses the geologic, seismic, and geophysical characteristics of the ECC-AM

seismotectonic zone. The information presented is based on a review of the published material 

summarized in the Data Summary table for the ECC-AM and the AHEX seismotectonic zones 

(Appendix D, Table D-7.3.7). Explicit references and data that were used as the basis for source 

characteristics of the ECC-AM are identified in the Data Evaluation table of Appendix C (Table 

C-7.3.7).

7.3.7.1 Background 

7.3.7.1.1 Crustal Structure

A distinguishing structural feature of the Mesozoic extended crust within the ECC-AM is that it 

includes an older, east-dipping Paleozoic master basal detachment surface separating 

overthrusted Paleozoic Appalachian terranes from the underlying rocks of the North American 

craton. For example, in the southern Appalachian Mountains, the Consortium for Continental 

Reflection Profiling (COCORP) seismic reflection data from Tennessee and Georgia show the 

master detachment to be ~6 km (~3.5 mi.) deep at the western flank of the mountains (west of 

ECC-AM), ~10 km (~6 mi.) deep in the Piedmont, and then quickly steepening to ~35 km (~22 

mi.) depth beneath the peri-Gondwanan Carolina terrane to the east, where it merges with the 

Moho (Cook et al., 1979; McBride et al., 2005). In general, therefore, Paleozoic thrust sheets 

above the master detachment surface change across the Appalachian orogenic belt in the 

ECC-AM from dominantly ―thin-skinned‖ in the west over the North American craton, to 

dominantly ―thick-skinned‖ in the accreted terranes to the east over the cratonic margin (Klitgord 

et al., 1988).

The formation of the Appalachian orogen in the Paleozoic was followed in the Mesozoic by 

extension that resulted in formation of the present-day Atlantic Ocean. Extension occurred 

primarily in the eastern foothills of the Appalachian Mountains, the Piedmont, and Coastal Plain 

regions as the rifting propagated southward, initiating the separation of North America and 

Africa in Late Permian time. Continued rifting in the Late Triassic created elongate, northeasttrending rift basins, primarily as half grabens, from the Gulf of Mexico to the Grand Banks 

(Figure 7.3.7-1). A second phase of rifting in the Early Jurassic opened extensional marginal 

basins, such as the offshore Carolina and Baltimore Canyon troughs, as the extensional onshore 

basins ceased to be active (Klitgord et al., 1988). Generally, bounding faults of Mesozoic 

extensional basins follow the crustal fabric of the Paleozoic orogenies, and several Mesozoic 

normal faults have been demonstrated to be reactivated Paleozoic thrust faults (Withjack et al., 

1998). 
Chapter 7 

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7-50

During most of the Late Triassic, onshore half grabens were created that are bounded by faults 

extending into the lower crust, except along the northeast Atlantic margin, where rift basins tend 

to be local, rather than widespread, and bounded by listric normal faults (Manspeizer et al., 1989; 

Withjack et al., 1998). This difference between basins in the northeast and southeast of the 

ECC-AM has been attributed to Early Jurassic pluton emplacement associated with the White 

Mountain Magma Series in central New England, which created a topographic high that may 

have resisted extension (Faure et al., 2006). Roden-Tice, West, et al. (2009) attribute this 

topographic elevation to regional unroofing during the Cretaceous, resulting from passage of the 

Great Meteor hotspot (see Section 7.3.2). As a result, the southeast portion of the ECC-AM 

underwent a relatively greater degree of extension, and faults extended to lower crustal levels. 

7.3.7.1.2 Geophysical Anomalies 

Given the presence of the relatively shallow Appalachian thrust sheets in the western parts of the 

ECC-AM, geophysical markers may provide the best means to define deep structural boundaries 

along the Atlantic margin and the ECC-AM. Gravity anomaly profiles across the Appalachian 

Mountains show a gravity anomaly low in the Valley and Ridge province, with a parallel gravity 

anomaly high in the Piedmont (Hutchinson et al., 1983; Karner and Watts, 1983; Cook, 1984). 

Pratt et al. (1988) concluded that this gravity anomaly gradient, when combined with 

geophysical data documenting an eastward-shallowing Moho and east-dipping reflectors, 

represents a thinning of continental crust toward the inferred late Precambrian–early Paleozoic 

continental margin lying beneath the Piedmont and marks the location of a Taconic collision 

zone at depth. Pratt et al. (1988) propose that this buried margin has persisted as a zone of 

weakness, which could explain the spatial correlation of the Piedmont gravity anomaly high with 

Mesozoic rift basins from Massachusetts to southern Georgia (Swanson, 1986; Hutchinson et al., 

1986; Williams, 1978; Pratt et al., 1988). In either case, the Appalachian gravity anomaly 

gradient appears to define a fundamental structural boundary that is the western limit of thinned, 

extension-dominated crust lying east of the Appalachian Mountains. 

The East Coast magnetic anomaly (ECMA) is a major geophysical feature of the North 

American Atlantic margin, extending from Georgia to Nova Scotia (Figure 7.3.7-3). Combined 

multichannel and wide-angle seismic studies of the Atlantic margin have shown that the ECMA 

is spatially correlated with a zone of transitional igneous crust, largely comprised of basalts and 

mafic intrusions, marking the seaward transition from rifted continental crust to mafic oceanic 

crust that extends along the entire Atlantic margin (Austin et al., 1990; Holbrook, Purdy, et al., 

1994; Holbrook, Reiter, et al., 1994; LASE Study Group, 1986; Trehu et al., 1989). The 

magnetic anomaly that defines the ECMA changes trend offshore of Georgia. This east-westtrending onshore portion of the magnetic anomaly has been identified as the Brunswick magnetic 

anomaly (BMA; Figure 7.3.7-3). The BMA cuts across the South Georgia rift, as well as several 

other pre-Cretaceous features, suggesting that it must be related to a deeper and older structure 

(Daniels et al., 1983). COCORP seismic reflection data, combined with magnetic anomaly 

modeling results, suggest that this structure is either a subducted slab, or subcontinental mantle,

trapped during the Alleghanian collision (McBride and Nelson, 1988). The BMA therefore 

demarcates the structural boundary between the North American craton and the Florida–South 

Georgia microcontinent, known as the Suwannee, or Wiggins-Suwannee, suture. 
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7.3.7.1.3 Major Structures 

The ECC-AM includes an abundance of major shear zones and faults, most of which are related 

to the Paleozoic accretion of terranes during the Appalachian orogenies. Prominent examples are 

the Brevard fault zone, a largely strike-slip fault in Georgia, South Carolina, and North Carolina 

that transported west-directed thrusts to the southwest along the Inner Piedmont during the 

Neoacadian and Alleghanian orogenies; the Central Piedmont suture of Georgia, the Carolinas, 

and Virginia that was the possible Alleghanian thrust ramp for the Carolina terrane; and the East 

Piedmont fault system, which bounds the Alleghanian metamorphic core of the southern 

Appalachian Mountains (Hatcher et al., 2007). 

Mesozoic normal faults bound the rift basins throughout the ECC-AM (Figure 7.3.7-1). The 

location and geometry of these rift basins are interpreted to have been controlled mainly by 

existing Paleozoic structures, which were reactivated as brittle normal faults when the Mesozoic 

extension direction was at a high angle to the preexisting fault (Cook et al., 1981; Schlische, 

1993). The East Piedmont fault system, for example, was the dominant structure controlling 

basin development in the southern Appalachians, forming the Danville, Farmville, and 

Richmond basins (Swanson, 1986). Rift basins of the northern Appalachian Mountains, such as 

the Gulf of Maine and Fundy Basin, can be similarly correlated with specific reactivated 

Paleozoic faults (Swanson, 1986). 

Cretaceous and younger faults within the ECC-AM are predominantly oriented north-south to 

northeast-southwest (Prowell, 1988). Prowell (1988) indicates that post-Cretaceous movement 

on these faults is reverse slip, with limited evidence for strike-slip movement. Within the 

ECC-AM source zone, several northeast-striking reverse fault zones in fault systems have 

experienced Cenozoic activity (Prowell, 1983, 1988; Wentworth and Mergner-Keefer, 1983). 

Some of these include the Stafford fault system in northeastern Virginia (Mixon and Newell, 

1977; Newell, 1985; Pavich et al., 1989); the subsurface Brandywine fault system in 

southwestern Maryland (Jacobeen, 1972); the Belair fault zone in eastern Georgia (Prowell and 

O’Connor, 1978; Bramlett et al., 1982); the Everona–Mountain Run fault zone and the Dutch 

Gap fault in Virginia (Pavlides et al., 1983; Prowell, 1988; Pavlides, 1994); the Hares Crossroads 

fault in North Carolina (Prowell, 1983); and the Cooke and offshore Helena Banks faults 

(Behrendt et al., 1983) near Charleston, South Carolina. These faults typically strike north to 

northeast, exhibit steep dips, and displace sedimentary rocks of Late Cretaceous–Miocene (100–

5.3 Ma) age. Individual vertical fault zone displacements generally are tens of meters, with a 

maximum cumulative offset of as much as 80 m (262.5 ft; Prowell, 1988). The available 

stratigraphic data generally show greater displacement on older units, indicating progressive 

displacement through time. Vertical slip rates range from 0.0003 to 0.0015 meters per thousand 

years (m/ka) during the past 110 Ma, averaging 0.0005 m/ka (Prowell, 1988). 

The occurrence of late Cenozoic movement along the faults mapped in the ECC-AM is difficult 

to assess because of poor exposure, lack of suitable stratigraphy, relatively small displacements, 

and low slip rates on these faults. Possible Quaternary displacement on north- and northeaststriking faults appears to be reverse slip. However, the available evidence for postulated 

Quaternary movement provides little constraint on possible strike-slip movement. For example, 

possible Pleistocene (1.8 Ma to 11 ka) activity is suggested on the Everona–Mountain Run fault 
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zone in central Virginia based on displacement of gravel deposits considered to be of late 

Cenozoic or Pleistocene age (Pavlides et al., 1983; Pavlides, 1994; Crone and Wheeler, 2000). 

Geomorphic relationships (Mayer and Wentworth, 1983) and possible faulted fluvial terraces at 

Fredricksburg, Virginia, along an extension of the Stafford fault system (Darton, 1950) may 

indicate post-Pliocene movement (post–1.8 Ma). There is no direct evidence, however, for 

Quaternary movement on any of the strands of the Stafford fault system. Furthermore, activity of 

these north- to northeast-striking reverse faults is difficult to reconcile with the observed 

northeast-southwest orientation of contemporary maximum horizontal compressive stress for the 

Atlantic Coastal Plain defined by Zoback and Zoback (1989) and Zoback (1992). 

7.3.7.1.4 Seismicity 

Like most of the CEUS, seismicity within the ECC-AM is spatially variable, with moderate 

concentrations of earthquake activity separated by areas of very low seismicity. The most 

prominent of these zones of seismicity are located in the Central Virginia seismic zone and the 

greater New York City–Philadelphia area. To a lesser degree, these prominent zones include 

clusters of seismicity in the Charleston, South Carolina, area; the Piedmont region of South 

Carolina and Georgia; and New England (Figure 7.3.7-2). As characterized by Bollinger et al. 

(1991), hypocenters in the Atlantic Coastal Plain are distributed throughout the upper 13 km (8 

mi.) of crust where focal mechanisms indicate a north-northeast maximum horizontal 

compressive stress. The largest earthquake within the ECC-AM is the 1886 Charleston 

earthquake. Due to the strong paleoliquefaction evidence for RLMEs in the Charleston area, a 

separate RLME seismic source zone is defined for Charleston (see Section 6.1.2). 

The Central Virginia seismic zone (CVSZ) is an area of persistent seismic activity in the 

Piedmont province of Virginia, extending approximately 120–150 km (75–93 mi.) west of 

Richmond with a north-south width of about 100 km (62 mi.). The relative paucity of 

paleoliquefaction features along the coastlines and riverways of Virginia makes it unlikely that 

the CVSZ has produced M > 7 earthquakes in the last 5,000 years (Obermeier and McNulty, 

1998). The largest historical earthquake in this zone is the 1875 Goochland County earthquake, 

with a reported intensity of MMI VII and an estimated magnitude of mb 5.0 (Bollinger and 

Hopper, 1971). In general, however, the CVSZ is defined by small, shallow earthquakes, threequarters of which occur at depths <11 km (7 mi.; Bollinger and Sibol, 1985). As the southern 

Appalachian detachment is at least 12 km (7.5 mi.) deep in this part of the Piedmont (Keller et 

al., 1985; de Witt and Bayer, 1986), CVSZ seismicity is interpreted to occur on the Paleozoic 

and Mesozoic faults that lie above the Precambrian basement. Outside the CVSZ, the broad 

pattern of seismicity in eastern North America suggests an aseismic upper crust and the 

occurrence of strike-slip faulting below the Appalachian detachment, with focal mechanisms 

yielding a northeast-southwest orientation for the maximum horizontal compressive stress. This 

stress orientation is consistent with the ridge-push forces resulting from continuous seafloor 

spreading at the mid-Atlantic ridge, which Zoback and Zoback (1989) proposed as the origin of 

the contemporary regional stress field in the CEUS. 

For the New York–Philadelphia region, Sykes et al. (2008) used historical earthquake catalogs 

with their own instrumentally located earthquake database to compile a history of seismicity 

covering the years 1677–2006. Sykes et al. (2008) find earthquakes to be concentrated in mid-
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Proterozoic to Ordovician terranes bordering the Newark basin, with hypocenters tracing out 

northeasterly swaths that roughly parallel the trend of the Appalachian Mountains. The most 

active of these zones is a 35 km (22 mi.) wide belt east and southeast of the Newark basin, which 

is the location for the largest historical earthquake in this region (i.e., a magnitude 5.25, a felt 

magnitude of Sykes that relates felt area to mbLg). Of the 383 earthquakes in the Sykes et al. 

(2008) local catalog, 95 percent occurred at depths shallower than 12.5 km (8 mi.). Both the New 

York–Philadelphia region and CVSZ are characterized by a majority of earthquakes occurring at 

depths shallower than the Appalachian detachment, in contrast to the deeper levels of seismicity 

in the Eastern Tennessee and Giles County seismic zones, which occur nearly exclusively below 

the detachment surface. Both of these seismic zones are located within the Paleozoic Extended 

Crust (PEZ) seismotectonic source (see Section 7.3.4). As is the case in the CVSZ, specific faults 

responsible for seismicity around the Newark basin are not well defined. However, focal 

mechanisms around the Newark basin conform to the broad stress field found throughout the 

Atlantic margin and are consistent with a N64°E orientation of maximum horizontal compressive 

stress (Sykes et al., 2008). 

Northeastern Massachusetts, southeastern New Hampshire, and southernmost Maine have 

experienced many small, and several moderate, earthquakes during the past 400 years. The two 

most notable earthquakes, the 1727 felt-area magnitude 5.5 Newburyport and the 1755 M 6.1 

(E[M] 6.10) Cape Ann earthquakes in Massachusetts, induced liquefaction and caused damage to 

buildings (Ebel, 2000, 2001). During a paleoseismology study in the Newburyport area in the 

late 1980s, Tuttle and Seeber (1991) found both historical and prehistoric liquefaction features. 

The historical features were attributed to the 1727 earthquake, and the prehistoric features were 

estimated to have formed during the past 4,000 years. More recent searches for earthquakeinduced liquefaction features in the region yielded only one small sand dike (Tuttle, 2007, 2009). 

The limited paleoliquefaction features in New England, which do not provide sufficient 

information to characterize the recurrence, geometry, or Mmax parameters of the ECC-AM 

seismotectonic source, are further discussed in Appendix E. 

7.3.7.2 Basis for Defining Seismotectonic Zone 

The basis for defining the ECC-AM seismotectonic zone centers primarily on the assessments of 

Johnston et al. (1994) that Mesozoic and younger extended crust has produced all M ≥ 7 stable 

craton earthquakes worldwide, and that extended or rifted crust may provide a basis for 

differentiating Mmax. In this study of global earthquakes and SCR tectonic domains, Johnston et 

al. (1994) found that the subdivision between rifted and nonrifted crust is significant and that 

SCR earthquake activity is concentrated in extended crust. As presented in Section 5.2, the SCR 

database and analysis of the data given in Johnston et al. (1994) was updated as part of the CEUS 

SSC Project. This updated analysis supports the basis for separating Mesozoic and younger 

extended crust to establish a prior distribution of Mmax. The statistical significance for this 

separation, however, is not strong. 

Defining the ECC-AM as a seismic source also differentiates it from adjoining regions of the 

crust that appear capable of producing different Mmax earthquakes or future earthquake rupture 

characteristics. For example, the ECC-AM is separated from the ECC-GC (Gulf Coast) because 
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the structural grain of the two seismotectonic zones is different and will likely give rise to 

different future rupture characteristics (e.g., particularly rupture orientation). Crust of the 

ECC-AM seismotectonic zone is separated from Mesozoic extended crust of the Northern 

Appalachian (NAP) seismotectonic zone (Section 7.3.3) because of both the lack of rift basins 

expressed in the NAP and the multiple phases of reactivation and differences in future 

earthquake rupture characteristics. 

7.3.7.3 Basis for Geometry 

The geometry of the ECC-AM is based on the concept of including those portions of crust that 

underwent significant Mesozoic extension expressed as rifting. The geometry of the ECC-AM 

zone is similar to the Eastern Seaboard domain defined by Kanter (1994), which includes 

extended Paleozoic basement of the eastern United States and Nova Scotia as well as the 

continental shelf. The western boundary of the ECC-AM, which is defined by the Piedmont 

(Appalachian) gravity anomaly gradient (e.g., Bollinger and Wheeler, 1988; Figure 7.3.7-3) and 

corresponds closely to the Piedmont/Avalon terrane boundary of Williams and Hatcher (1983), 

generally follows the western edge of the Triassic-Jurassic onshore basins or the boundaries of 

the structural blocks in which they occur. In New England and eastern New York, the western 

boundary of the ECC-AM incorporates crust that has experienced Cretaceous uplift west of the 

Hartford basin (Roden-Tice and Tice, 2005) and deep-velocity anomalies associated with the 

Cretaceous Great Meteor hotspot (Li et al., 2003). Across Nova Scotia, the ECC-AM western 

boundary generally follows the Cobequid-Chedabucto fault system (Pe-Piper and Piper, 2004; 

Murphy and Keppie, 2005). The eastern boundary of the ECC-AM follows the western margin of 

the ECMA. The southern boundary of the ECC-AM generally follows the Brunswick magnetic 

anomaly (BMA), which marks the Wiggins-Suwannee suture (Hatcher et al., 2007). 

7.3.7.4 Basis for Mmax 

As with all seismotectonic zones defined for the CEUS-SSC Project, the Mmax distribution for 

the ECC-AM is derived using two different approaches (see Section 5.2). For the Bayesian 

approach, both the Mesozoic and younger extended (MESE) and composite (COMP) priors are 

used for this seismotectonic zone because the zone is defined by the presence of extended 

continental crust that was rifted during Mesozoic extension. The Kijko method was also used to 

assess Mmax for the ECC-AM. These methods are discussed further in Section 5.2, and the 

Mmax distributions and weighting schemes for ECC-AM are presented in Section 7.4. 

The largest observed earthquake in the ECC-AM seismotectonic zone is the 1755 M 6.1 (E[M] 

6.10) Cape Ann, Massachusetts, earthquake. However, there is some uncertainty as to whether 

this earthquake occurred in the ECC-AM since it lies near the boundary between the ECC-AM 

and the NAP zones. As shown on Figure 7.3.7-4, the location preferred by Bakun et al. (2003) 

lies within the ECC-AM, but the area defining a 95 percent confidence level for the earthquake 

location straddles the seismotectonic boundary. A study by Ebel (2006a) estimates the location 

within the ECC-AM farther southeast from the Bakun et al. (2003) preferred location (Figure 

7.3.7-4). The Bakun et al. (2003) model addresses uncertainty by mapping the 67 percent and 95 
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7-55

percent confidence levels for its location, whereas the Ebel study (2006a) provides only an 

estimated epicentral area. 

The uncertainty in location of the 1755 Cape Ann earthquake is included in this assessment of 

Mmax by assigning a 0.6 weight for a location within the ECC-AM, and a corresponding 0.4 

weight that the earthquake is located not in the ECC-AM but farther north in the NAP. The 

higher weight is assigned for the location within the ECC-AM since the more recent study by 

Ebel (2006a) places the earthquake within the ECC-AM. Therefore, the Cape Ann earthquake is 

used (with a weight of 0.6) to represent the largest earthquake within the ECC-AM. The next 

largest earthquake within the ECC-AM is the E[M] 5.32 earthquake that occurred on June 11, 

1638. This earthquake, which is located farther offshore than the 1755 Cape Ann earthquake, is 

also used (with a weight of 0.4) to represent the largest earthquake within the zone. 

7.3.7.5 Future Earthquake Characteristics 

The future rupture characteristics assigned to the ECC-AM seismotectonic zone are listed in 

Table 5.4-2. For the ECC-AM, the sense of slip, rupture dip, and source boundaries are assigned 

default characteristics (Tables 5.4-1 and 5.4-2). The characteristics of seismogenic crustal 

thickness and rupture orientation are assigned unique values for ECC-AM. The extended 

continental crust within the ECC-AM is assigned a greater seismogenic thickness than the more 

highly extended transitional crust of AHEX because the crustal thickness defined by depth to the 

Moho is distinctly greater in the ECC-AM. Seismogenic thickness values of 13, 17, and 22 km 

(8, 10.5, and 13.5 mi.) are assigned weights of 0.6, 0.3, and 0.1, respectively, for the ECC-AM. 

In contrast, the adjacent highly extended AHEX is assigned seismogenic thickness values of 8 

and 15 km (5 and 9.5 mi.) with equal weights as discussed in Section 7.3.8. The ECC-AM 

distribution reflects a greater seismogenic thickness than the AHEX, but a slightly lesser 

thickness than most of the more cratonward seismotectonic zones which have default 

seismogenic thickness distributions of 13, 17, and 22 km (8, 10.5, and 13.5 mi.), with weights of 

0.4, 0.4, and 0.2, respectively (Table 5.4-1). The rupture orientation distribution assigned to the 

ECC-AM modifies the weights of the default orientations of N50 W, N-S, N35 E, N60 E, and 

E-W (Table 5.4-1) such that most of the weight is given to the north and northeast orientations. 

For the ECC-AM, the individual weights assigned to the rupture orientations of N50 W, N-S, 

N35 E, N60 E, and E-W are 0.1, 0.2, 0.4, 0.2, and 0.1, respectively (Table 5.4-2). 

7.3.8 Atlantic Highly Extended Crust Zone (AHEX) 

The Atlantic highly extended crust (AHEX) seismotectonic zone represents the region of highly 

extended crust that is the transition between the extended, thick continental crust of the ECC-AM 

and the significantly thinner mafic oceanic crust of the Atlantic Ocean basin. This zone lies 

entirely offshore and approximately follows the continental shelf edge from Georgia to Nova 

Scotia (Figure 7.3.7-1). 

Extension during the Triassic and Jurassic rifting of the Atlantic Ocean basin produced the 

relatively broad zone of extended continental crust of the ECC-AM and the adjacent narrow 

AHEX zone of highly extended transitional crust that was more intensely modified by rifting. 
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The greater amount of rifting in the 50–100 km (31–62 mi.) wide AHEX zone resulted in a 

greater thinning of the crust and the introduction of significant components of new igneous 

material, largely basalts, and mafic intrusions (Klitgord et al., 1988; Holbrook, Reiter, et al., 

1994). 

This chapter discusses the geologic, seismic, and geophysical characteristics of the AHEX 

seismotectonic zone. The information presented is based on a review of the published material 

summarized in the Data Summary table for both the ECC-AM and AHEX seismotectonic zones 

(Appendix D, Table D-7.3.7). Explicit references and data that were used as the basis for source 

characteristics in the AHEX are identified in the Data Evaluation table of Appendix C (Table 

C-7.3.7). 

7.3.8.1 Basis for Defining Seismotectonic Zone 

Following the methodology for defining seismotectonic zones (see Chapter 4), the AHEX 

seismotectonic zone is included as a zone distinct from the ECC-AM zone because the AHEX 

zone is expected to exhibit a lesser seismogenic thickness to influence future earthquake 

characteristics. The sparse seismicity in the AHEX does not allow seismogenic thickness, and 

hence, dimensions of future ruptures, to be characterized directly from the depths of recorded 

earthquakes. Rather, the crustal thickness defined by depth to the Moho provides the best proxy 

for assessing seismogenic thickness compared with that of the adjacent extended continental 

crust. The eastward-thinning wedge of highly extended transitional crust that characterizes the 

AHEX zone is significantly thinner than the approximately 35–40 km thick (21.5–25 mi.) 

extended continental crust of the adjacent ECC-AM seismotectonic zone. Crustal-scale seismicreflection profiles derived from multichannel and wide-angle seismic studies offshore of South 

Carolina (Holbrook, Purdy, et al., 1994), Virginia (Holbrook, Reiter, et al., 1994), and Nova 

Scotia (Funck et al., 2004) indicate that the AHEX zone ranges in thickness from about 15 to 30 

km (9.5 to 18.5 mi.). The decreasing crustal thickness away from the continent strongly argues 

that the seismogenic thickness (typically thinner than the crust or depth to the Moho) should also 

be thinner in the AHEX than in the ECC-AM. These same studies also reveal that the zone of 

transitional crust of the AHEX zone corresponds to the strong positive East Coast magnetic 

anomaly (ECMA). As shown on Figure 7.3.8-1, Holbrook, Purdy, et al. (1994) and Holbrook, 

Reiter, et al. (1994) interpret the eastern limit of rifted continental crust to correspond to the 

western margin of the ECMA, and the western limit of oceanic crust to correspond to the eastern 

margin of the ECMA. In seismic Line 801 from Holbrook, Reiter, et al. (1994), located on 

Figure 7.3.8-1, the AHEX zone beneath the ECMA is interpreted as comprising rift-related 

basalts and mafic intrusive rocks up to 25 km (15.5 mi.) thick (Holbrook, Reiter, et al., 1994, 

Figure 15). 

Crust of the AHEX seismotectonic zone is also compositionally different than the extended 

continental crust of the ECC-AM. The more mafic composition of the AHEX is defined by the 

ECMA, a major geophysical feature of the North American Atlantic margin, extending from 

Georgia to Nova Scotia (Figure 7.3.7-3). Combined multichannel and wide-angle seismic studies 

of the Atlantic Ocean margin have shown that the ECMA is spatially correlated with a zone of 

transitional igneous crust, marking the seaward transition from rifted continental crust to mafic 
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oceanic crust that extends along the entire Atlantic margin (Austin et al., 1990; Holbrook, Purdy, 

et al., 1994; Holbrook, Reiter, et al., 1994; LASE Study Group, 1986; Trehu et al., 1989), 

implying that the basalts and underlying mafic intrusives produce the high magnetic values of the 

anomaly (Talwani et al., 1992). The ECMA is interpreted as the result of rift-related magmatism 

during the first pulse of seafloor spreading (Sheridan et al., 1993; Holbrook, Purdy, et al., 1994; 

Holbrook, Reiter, et al., 1994; Talwani et al., 1995; Oh et al., 1995; Talwani and Abreau, 2000). 

The ECMA therefore marks a profound geological boundary beyond which very little continental 

crust occurs (Holbrook, Reiter, et al., 1994). 

7.3.8.2 Basis for Geometry 

The boundary of the AHEX was largely defined based on the location of the ECMA. This 

magnetic anomaly corresponds to the highly extended transitional crust comprising the AHEX 

(Figure 7.3.8-1). The western margin of the AHEX corresponds to the seaward extent of 

continental crust that was rifted and extended in the Mesozoic, and the eastern margin of AHEX 

corresponds to the landward extent of oceanic crust. Although the boundary of the AHEX is 

generally well defined by high total magnetic values (Figure 7.3.8-1), the boundary is 

gradational, and thus local uncertainty about the location of the boundary between AHEX and 

ECC-AM seismotectonic zones could be on the order of tens of kilometers. 

7.3.8.3 Basis for Mmax 

The Mmax distribution for the AHEX was developed using the Bayesian approach, which uses 

global prior distributions developed for SCRs (see Section 5.2). Because the AHEX is defined as 

highly extended transitional crust that was rifted during Mesozoic extension, the Mesozoic and 

younger extended prior (MESE) is used for this zone with the composite prior (COMP). The 

Kijko method was not used for the AHEX due to the low number of earthquakes observed within 

the zone. The largest observed earthquake within the AHEX is the September 24, 1996, E[M] 

2.89 earthquake. The derived Mmax distributions for the AHEX are presented in Section 7.4. 

7.3.8.4 Future Earthquake Characteristics 

The future rupture characteristics assigned to the AHEX seismotectonic zone are listed in Table 

5.4-2 and, with the exception of seismogenic thickness and rupture orientation, are the same as 

those assigned to the ECC-AM. The more highly extended transitional crust within the AHEX is 

assigned two equally weighted seismogenic thicknesses of 8 and 15 km (5 and 9.5 mi.), which 

reflects a shallower seismogenic thickness than that for the ECC-AM. These values are estimates 

of seismogenic thickness that are not well constrained by data. Because large faults within this 

zone likely formed during extension and are therefore likely to be oriented parallel to the long 

axis of the zone and perpendicular to the maximum extension direction, a distribution of rupture 

directions that are asymmetrically weighted in favor of northeast-striking (i.e., N25 E and 

N60 E) ruptures was assigned for the AHEX, while also allowing for ruptures striking northsouth, east-west, and N50 W (Table 5.4-2). 
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7.3.9 Extended Continental Crust–Gulf Coast Zone (ECC-GC) 

The breakup of the supercontinent of Pangaea and the formation of the Gulf of Mexico in the 

Triassic and Jurassic resulted in the development of three large crustal domains in the Gulf of 

Mexico region. From north to south, these domains are thick transitional crust, thin transitional 

crust, and newly formed oceanic crust (Buffler and Sawyer, 1985; Marton and Buffler, 1994; 

Salvador, 1991a, b; Sawyer et al., 1991). The Extended Continental Crust–Gulf Coast (ECC-GC) 

seismotectonic zone is the thick transitional crust domain (Figure 7.3.9-1). The thin transitional 

crust domain, the Gulf Highly Extended Crust (GHEX) seismotectonic zone, is discussed in 

Section 7.3.10. 

The thick transitional crust domain within the Gulf of Mexico region represents continental crust 

that was thinned during the opening of the Gulf of Mexico. In general, the thick transitional crust 

is characterized by basement highs (e.g., Sarasota arch, Middle Ground arch, Wiggins uplift, 

Monroe uplift, Sabine uplift) and intervening lows (e.g., South Florida basin, Tampa embayment, 

Apalachicola basin, Mississippi Salt basin, North Louisiana Salt basin, East Texas basin) that 

occur along the Gulf margin from Florida to Texas (Sawyer et al., 1991). Crustal thicknesses 

within the thick transitional crust vary between approximately 20 and 40 km (12 and 25 mi.), 

with the thinnest crust occurring within the basement lows, and the thicker, relatively less 

extended crust occurring in association with the basement highs. 

Most of the mid-Jurassic and younger subsidence and sedimentation within the thick transitional 

crust domain occurred in the basement lows, as reflected by the thick salt deposits that occur in 

many of these basins (Buffler and Sawyer, 1985; Marton and Buffler, 1994; Sawyer et al., 1991). 

Combined with the thin transitional crust to the south (discussed in Section 7.3.10), the total 

amount of thinning of continental crust in Gulf region is thought to have accommodated 50 

percent of the relative plate motion during the rifting of Pangaea and opening of the Gulf of 

Mexico (Dunbar and Sawyer, 1987). Despite the significant amount of extension that has 

occurred in the thick transitional crust domain, very few accommodating structures have been 

identified, in part due to masking by the thick sedimentary sequence that overlies the area of 

extended crust (Buffler and Sawyer, 1985; Marton and Buffler, 1994; Sawyer et al., 1991). 

The source characterization of the ECC-GC described in the following text is based on a review 

of published material (see Appendix Table D-7.3.9). Explicit references that were used as the 

basis for source characteristics are identified in Appendix Table C-7.3.9. 

7.3.9.1 Basis for Defining Seismotectonic Zone 

Following the methodology for defining seismotectonic zones presented in Chapter 4, the 

ECC-GC is defined as a distinct seismotectonic zone because it is anticipated that this zone will 

have an Mmax distribution different from that of neighboring zones. In particular, the ECC-GC 

has experienced Mesozoic extension and thus the appropriate Mmax prior is different from that 

applicable to other regions of the CEUS that have not experienced Mesozoic extension. The 

ECC-GC zone is defined as distinct from the equivalent zone along the Atlantic margin (i.e., the 

Extended Continental Crust–Atlantic Margin seismotectonic zone, or ECC-AM, as discussed in 
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Section 7.3.7), based on differences in expected future rupture characteristics. In particular, the 

dominant structural grain for the ECC-AM is roughly north-northeast and subparallel to the 

margin of Mesozoic extension along the East Coast, regional structures in the Appalachian 

orogen, and the modern Atlantic coastline. There is no preferred dominant structural grain in the 

ECC-GC because there is considerable variability and uncertainty in the orientation of structures 

that accommodated the opening of the Gulf of Mexico (see Section 7.3.9.4). 

The ECC-GC is also distinguished from the highly extended crust to the south, which lies within 

the GHEX zone, as discussed in Section 7.3.10, based on a difference in expected future 

earthquake characteristics. This difference is related to the interpretation that the GHEX 

seismotectonic zone is characterized by a thinner seismogenic crust than the ECC-GC zone 

because the GHEX zone is more highly extended (see Sections 7.3.7.10.4 and 7.3.7.9.4). 

7.3.9.2 Basis for Zone Geometry 

7.3.9.2.1 Southern Boundary 

Most of the southern boundary of the ECC-GC zone, from west Texas to the eastern Gulf of 

Mexico, is defined as the transition between thick and thin transitional crust domains (Figure 

7.3.9-1). In general, the boundary between these domains is not well defined because of the lack 

of a clear distinction in geologic characteristics of the two domains, and because of the difficulty 

in observing geologic differences between the zones due to the thick accumulation of sediment 

deposited atop the rifted Mesozoic crust. Some of the fundamental geologic differences between 

the thick and thin transitional crust domains are as follows: 

The thin transitional crust has undergone more extension. 

The thin transitional crust has been thinned more uniformly, as opposed to the basin-anduplift style of extension in the thick transitional crust. 

The pattern of magnetic anomaly trends within the thin transitional crust are roughly marginparallel, as opposed to margin-perpendicular in the thick transitional crust domain (e.g., 

Figure 7.1-5; Buffler and Sawyer, 1985; Marton and Buffler, 1994; Sawyer et al., 1991).

In many places along the Gulf margin, these geologic contrasts are coincident with a hinge zone 

in the basement topography, marking where the shallow-dipping basement of the less subsided, 

thick transitional crust abuts the more subsided and more steeply dipping thin transitional crust. 

This hinge zone correlates with the location of an Early Cretaceous carbonate platform that 

rimmed the Gulf of Mexico basin (Buffler and Sawyer, 1985; Harry and Londono, 2004; Sawyer 

et al., 1991). Presumably, the location of the platform reflects the contrast in subsidence between 

the thick and thin transitional crust domains. This platform has been called upon by many 

authors to infer the location of the boundary between thick and thin transitional crust (Buffler 

and Sawyer, 1985; Ewing and Lopez, 1991; Harry and Londono, 2004; Marton and Buffler, 

1994; Sawyer et al., 1991). 

Given the lack of readily identifiable and distinct geologic differences between the thick and thin 

transitional crust domains, there is considerable uncertainty in the location of this boundary. 
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Therefore, the interpretation of the thick to thin transitional crust boundary presented by Sawyer 

et al. (1991) is used for defining the southern boundary of the ECC-GC; the uncertainty in the 

location of this boundary is on the order of 50–100 km (31–62 mi.). 

South of Florida, the southern boundary of the ECC-GC zone is defined by the location of the 

Nortecubana fault along the north coast of Cuba. This fault marks the former suture zone of the 

Caribbean and North American plates and thus delineates the southern limit of Mesozoic 

extension within the Gulf of Mexico at this longitude (Kanter, 1994). This fault system was 

active until about Middle Eocene time, and it accommodated relative convergence of the Bahama 

platform and Cuba (Gordon et al., 1997). The current boundary between the Caribbean and 

North American plates is on the southern side of Cuba. 

7.3.9.2.2 Western Boundary 

The western boundary of the ECC-GC zone is defined as the easternmost extent of the Gulf of 

Mexico coastal plain as determined by the onset of topographic relief associated with the Sierra 

Madre Oriental, the Coahuila folded province, and other topographic features of the eastern 

Mexico peninsula (Figure 7.3.9-1). Uncertainty in this boundary is on the order of several to tens 

of kilometers (several to tens of miles) at most, given that it is relatively well defined based on 

topography. The Sierra Madre Oriental and the Coahuila folded province are structural domains 

produced by Laramide-age fold-and-thrust tectonics, and they exhibit some evidence of Tertiary 

extension associated with development of the Basin and Range and the Rio Grande rift (Cook et 

al., 1979; Dickerson and Muehlberger, 1994; Gray et al., 2001; Murray, 1961). 

7.3.9.2.3 Eastern Boundary 

Some researchers consider the eastern limit of transitional crust associated with the opening of 

the Gulf of Mexico to be delineated by the northwest-trending Bahamas fracture zone that 

extends from roughly the southeastern tip of the Florida peninsula to the northwest part of the 

Gulf of Mexico. This interpretation is largely based on (1) the extent of Mesozoic volcanic rocks 

observed in wells in southern Florida; (2) distinct boundaries seen in the gravity and magnetic 

anomalies of Florida; and (3) the presence of the Suwannee terrane, a relatively unextended 

portion of the African continent that was accreted to North America during the rifting that 

formed the Atlantic Ocean and Gulf of Mexico, between the Bahamas fracture zone and southern 

Georgia (Marton and Buffler, 1994; Salvador, 1991a; Sawyer et al., 1991; Thomas, 2006). 

In spite of this tectonic interpretation, the eastern boundary of the ECC-GC zone is defined as the 

edge of the Atlantic margin continental shelf and the Blake plateau (Figure 7.3.9-1), and thus 

includes the Suwannee terrane within the ECC-GC. The decision to include the Suwannee 

terrane, all of Florida, and parts of southern Georgia in the ECC-GC is based on the following 

considerations: 

Mesozoic extension is documented within these regions (e.g., rifted crust off eastern Florida, 

the Apalachicola basin, and the South Georgia rift) (Daniels et al., 1983; Kanter, 1994; 

Klitgord et al., 1984). 
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A boundary between the ECC-GC and ECC-AM occurs along the Wiggins-Suwannee suture 

that represents the late Alleghanian suture separating the southern Appalachians from 

Gondwana (African-affinity rocks). This suture marks the southern termination of the 

dominant Appalachian structural grain and subsequent northeasterly striking structures that 

formed or reactivated during Mesozoic rifting of the Atlantic. 

Given the different orientations of spreading between the Atlantic and Gulf and the dominant 

northeast structural grain of the Appalachians, it is anticipated that the Suwannee terrane, all of 

Florida, and parts of southern Georgia will likely have future earthquake rupture characteristics 

more similar to other portions of the ECC-GC than to the ECC-AM (see Section 7.3.9.2.4). 

7.3.9.2.4 Northern Boundary 

The northern boundary of the ECC-GC is intended to represent the northernmost extent of 

Mesozoic crustal thinning associated with the rifting of Pangaea and the opening of the Gulf of 

Mexico. The northernmost extent of Mesozoic extension is roughly coincident with the edge of 

Iapetan margin that formed during Paleozoic extension (within approximately 100 km, or 62 mi.; 

Thomas, 1988, 2006). However, there is considerable variability in the relative location of the 

Paleozoic and Mesozoic extensional boundaries. In Texas, the location of both boundaries is not 

well defined. Faulting of Mesozoic-aged basement is hypothesized by some to have extended as 

far north as the Balcones fault zone in central Texas (Collins, 2004; Pindell et al., 2000; Sawyer 

et al., 1991), but some interpretations of the edge of Iapetan margin are gulfward of this fault 

zone (see Wheeler and Frankel, 2000, and references therein). In this region, the northern edge of 

the ECC-GC is defined as the edge of the Iapetan margin by the USGS in its national seismic 

hazard maps (Petersen et al., 2008; Wheeler and Frankel, 2000) for the following reasons: 

There is considerable uncertainty in the boundary of Mesozoic rifting in the region. 

In many other locations along the Gulf of Mexico, structures associated with the Iapetan 

margin localized Mesozoic extension (Sawyer et al., 1991; Thomas, 1988). 

This boundary lies within the zone of Mesozoic rifting proposed by different researchers 

(e.g., Kanter, 1994; Pindell and Kennan, 2001; Pindell et al., 2000; Sawyer et al., 1991). 

At the longitude of Arkansas and Louisiana, the Southern Arkansas fault zone is commonly 

interpreted as the northern extent of transitional crust, based on the presence of Triassic-age red 

beds that fill grabens associated with the fault zone (Sawyer et al., 1991; Thomas, 1988). In this 

region, however, the northern boundary of the ECC-GC zone is drawn farther north, 

encompassing more of southern Arkansas and abutting the southern extents of the Oklahoma 

Aulacogen (OKA) and RR seismotectonic zones. The source zone is extended north of the South 

Arkansas fault zone for several reasons: 

There is evidence of Late Cretaceous volcanism north of the fault zone and south of the 

Reelfoot rift that, while not related to the Mesozoic opening of the Gulf of Mexico, suggests 

that this region has undergone deformation more recently than the Midcontinent-Craton 

seismotectonic zone to the north (Baksi, 1997; Byerly, 1991; Hendricks, 1988; Hildenbrand 

and Hendricks, 1995). 
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It does not seem tectonically reasonable to have a relatively thin sliver of crust without 

Mesozoic extension sandwiched between the northern extent of the ECC-GC zone and the 

southern extent of the Reelfoot rift zone, both of which are zones with Mesozoic extension.

It does not seem appropriate to include the potential liquefaction features discussed by Cox 

and other researchers (Cox, 2009; Cox et al., 2007; Cox, Larsen, Forman, et al., 2004) within 

the Midcontinent-Craton seismotectonic zone when, if these features represent actual 

paleoseismic earthquakes, they may be related to reactivation of Mesozoic and Paleozoic 

structures (e.g., Alabama-Oklahoma transform fault; see Section 7.3.9.5; Gordon and Cox, 

2008; Thomas, 1988; Thomas, 2006). 

From Mississippi to western Alabama, the boundary of the ECC-GC zone is defined by the 

location of the Alabama-Oklahoma transform, a transform fault originally formed during the 

opening of the Iapetus Ocean and later reactivated during the Mesozoic opening of the Gulf of 

Mexico and the Atlantic Ocean (Sawyer et al., 1991; Thomas, 1988). The location of this 

boundary is relatively well known based on its expression in magnetic anomaly data. 

From Alabama to Georgia, the northern boundary of the ECC-GC is defined by the late 

Alleghanian Wiggins-Suwannee suture, which underlies the South Georgia rift basin and 

approximately coincides with the Brunswick magnetic anomaly (BMA; McBride and Nelson, 

1988; McBride et al., 2005; Hatcher et al., 2007). This suture represents the southern termination 

of the dominant Appalachian structural grain and subsequent structures that formed or 

reactivated during Mesozoic rifting of the Atlantic. 

In general, the entire northern boundary of the ECC-GC is not well defined, and uncertainty in 

the location of the boundary is on the order of 50–100 km (31–62 mi.).

7.3.9.3 Basis for Zone Mmax 

As with all the seismotectonic zones, the Mmax distribution for the ECC-GC is derived using 

two different approaches (see Section 5.2). For the Bayesian approach, the MESE and COMP 

priors are used for this seismotectonic zone because the zone geometry is defined by the extent 

of Mesozoic extension. For both approaches, three weighted alternative characterizations are 

used to represent uncertainty in the largest observed earthquake within the zone, as follows: 

Alternative 1: The largest observed earthquake is the October 22, 1882, E[M] 5.58 

earthquake.

Alternative 2: The largest observed earthquake is the October 24, 1997, M 4.9 E[M] 4.88 

earthquake.

Alternative 3: The largest observed earthquake is the potential paleoearthquake identified 

from the studies of Cox and other researchers and is characterized with a potential magnitude 

distribution of 5.0 (0.1), 5.5 (0.4), 6.0 (0.4), and 6.5 (0.1) (see discussion in Section 7.3.9.5). 

Alternative characterizations 1 and 2 represent the use of historical and instrumental seismicity 

to define the largest observed earthquake, and Alternative 3 represents the use of paleoseismicity 
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to define the largest observed earthquake within the zone. For this project, 0.2 weight is given to 

using the potential paleoearthquake as the largest observed earthquake within the zone (see 

Section 5.2), so Alternative 3 is given 0.2 weight in truncating the prior. Alternatives 1 and 2 

combined are given the remaining 0.8 weight, and individually they are weighted 0.4 each. The 

October 22, 1882, E[M] 5.58 earthquake is the largest earthquake in the zone, and the October 

24, 1997, E[M] 4.884.9 earthquake is the second largest earthquake within the zone. The even 

weighting between the two alternative characterizations reflects the observation that the October 

22, 1882, E[M] 5.58 earthquake occurs close to the eastern edge of the OKA zone boundary (see 

Figure 7.3.11-1), and that there is significant uncertainty in its location because the location is 

based on historical accounts. Similar to the treatment of this earthquake for the OKA zone (see 

Section 7.3.11.3), the possibility that this earthquake occurred outside the ECC-GC zone is 

captured with the 0.4 weight on the October 24, 1997, E[M] 4.88 earthquake as the largest in the 

zone. 

It should be noted that for the Alternative 3 case where the maximum observed magnitude is 

based on the potential paleoearthquake, the magnitude distribution for maximum observed 

earthquake needs to take into account the probability that the largest historical earthquake is 

either the 5.58 or 4.9. Taking this weighted historical earthquakes into account, the actual 

maximum observed magnitude distribution for Alternative 3 is 5.0 (0.05), 5.5 (0.2), 5.58 (0.25), 

6.0 (0.4), 6.5 (0.1). 

The final Mmax distribution for the zone is presented in Section 7.4 

7.3.9.4 Future Earthquake Characteristics 

Future earthquakes within the ECC-GC are modeled using the default characteristics for the 

CEUS, with the exception of the strike of fault ruptures and weighting of seismogenic thickness 

values. It is anticipated that future moderate to large earthquakes will most likely occur along 

preexisting basement structures associated with the opening of the Gulf of Mexico, and the two 

types of structures most likely to be reactivated are normal faults roughly perpendicular to the 

rifting direction that accommodated the extension, and transform faults subparallel to the rifting 

direction that accommodated differential spreading rates. However, there is considerable 

uncertainty in the orientation of these structures throughout the ECC-GC zone because there are 

several kinematic models for opening of the Gulf of Mexico, all of which imply different 

orientations for the two fault types, and, in general, each of the models has internal variation in 

orientation of the two fault types within different regions of the ECC-GC zone (e.g., the western 

vs. eastern Gulf of Mexico) (Anderson and Schmidt, 1983; Buffler and Sawyer, 1985; Buffler et 

al., 1980; Dunbar and Sawyer, 1987; Hall et al., 1982; Hall and Najmuddin, 1994; Klitgord et al., 

1984; Marton and Buffler, 1994; Pindell, 1985, 1993; Pindell and Kennan, 2001; Pindell et al., 

2006; White, 1980). Combining the uncertainty from these two factors, it is difficult to identify a 

preferred range of orientations, so the expected strike of future ruptures within the ECC-GC is

modeled as randomly oriented. 
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7.3.9.5 Possible Paleoliquefaction Features in Arkansas, Louisiana, and 

Mississippi 

Cox and other researchers (Cox, 2002, 2009; Cox, Forman, et al., 2002; Cox, Harris, et al., 2004; 

Cox and Larsen, 2004; Cox, Larsen, Forman, et al., 2004; Cox, Larsen, and Hill, 2004; Garrote 

et al., 2006; Cox et al., 2007; Cox and Gordon, 2008; Gordon and Cox, 2008) have conducted 

several studies in the southeastern Arkansas, northeastern Louisiana, and western Mississippi 

(ALM) areas, investigating what they interpret to be paleoliquefaction features possibly related 

to moderate to large earthquakes occurring along the Saline River fault zone in southern 

Arkansas. Collectively, this group of proposed paleoliquefaction features is referred to as the 

ALM features. Briefly, the basis for the researchers’ interpretation is as follows: 

They observed roughly circular sandy deposits in aerial photographs throughout the Arkansas 

and Mississippi river valleys between southeastern Arkansas and northeastern Louisiana that 

they interpret to be seismically induced sand blows. 

They trenched sandy deposits at seven locations, and within the trenches they interpret 

multiple sand-venting episodes that can be correlated between trench sites based on 

stratigraphic relationships observed in the trenches, and dating of the sand units. 

They proposed that there is evidence of Quaternary fault rupture in the Saline River area 

along the trend of the Oklahoma-Alabama transform, a transform boundary during the 

Paleozoic rifting related to opening of the Iapetus Ocean and the Mesozoic rifting that 

formed the Gulf of Mexico. 

As part of the CEUS SSC Project, the results of the studies by Randel Cox (University of 

Memphis) and his colleagues were evaluated to determine whether there was evidence of either 

RLMEs, and thus evidence for a RLME source zone, or of a single Quaternary earthquake that 

would impact the determination of the maximum observed earthquake within the ECC-GC zone. 

To establish whether the proposed ALM paleoliquefaction data supported the presence of an 

RLME source, criteria established as part of the CEUS SSC Project were used for identifying 

earthquake-induced liquefaction features. These criteria focus on the identification of sand 

blows, sand-blow craters, and sand dikes because these features are the only reliable indicators of 

earthquake-induced liquefaction. Characteristics of these liquefaction features are described in 

Appendix E. With these criteria, project team members evaluated in detail the ALM features 

presented by Cox and other researchers. This evaluation included reviews of published papers, 

including trench logs; conversations with Cox; and reviews of original field notes, field trench 

logs, and field photographs taken by Cox as part of the various studies. 

The conclusions of the evaluation are as follows: 

There is no unequivocal evidence for repeated large earthquakes in the exposures. 

There is little, if any, unequivocal evidence for large (M > 6) earthquakes in the studied 

exposures. 

The best evidence for a paleoearthquake is a possible small (<6 cm wide) feeder dike shown 

in the field logs and on photographs of the Portland, Arkansas, trench site. It remains unclear 
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whether this possible small dike is the result of (1) a moderate-magnitude local earthquake, 

(2) a larger, more distant earthquake, or (3) non-earthquake processes. Other small sand dikes 

may occur in other trenches. 

In summary, the conclusion was made that the paleoliquefaction data from the ALM region are 

preliminary and do not provide adequate evidence for a source of RLMEs in the ALM area. 

Therefore, an RLME source zone is not defined based on the ALM features. 

The studies of Cox and other researchers were also evaluated to determine whether they provided 

evidence of any Quaternary paleoearthquakes that would impact the characterization of the 

ECC-GC zone. Following from the methodology of using the maximum observed earthquake 

within a seismotectonic zone in defining the Mmax distribution, a paleoearthquake magnitude 

could define the largest observed earthquake. As stated above, the possible sand dike in the 

Portland trench is the strongest evidence for a paleoearthquake within the ALM region. In 

general, the magnitude threshold for liquefaction is about M 5. The magnitude threshold in 

Holocene fluvial deposits in the Mississippi River floodplain is about M 6.3 (i.e., the magnitude 

of the 1895 Charleston, Missouri, earthquake). Therefore, a local earthquake in the magnitude 

range of M 5 to 6.5 could be responsible for the formation of the sand dike. 

Based on our evaluation of the uncertainty in this possible magnitude, the magnitude of the 

paleoearthquake was characterized using the following magnitude distribution: M 5.0 (0.1), M

5.5 (0.4), M 6.0 (0.4), and M 6.5 (0.1). This magnitude distribution is one of the options used in 

truncating the Mmax prior for the zone (see Section 7.3.9.3). The apparent lack of unequivocal 

liquefaction features at other sites across the ALM region argues against a large local earthquake. 

Alternatively, the Portland sand dike could be the result of a large distant earthquake, perhaps 

centered near Marianna, Arkansas. 

The Quaternary fault rupture in the Saline River area as proposed by Cox et al. (2000) was not 

considered in developing estimated paleoearthquake magnitudes because it is not thought that 

there is strong evidence for Quaternary fault rupture at that location. This appraisal of the 

evidence for Quaternary activity is based on (1) the fact that the faults described by Cox et al. 

(2000) are all relatively small displacement fault splays that have evidence of Eocene offsets, 

and at best equivocal evidence of Pliocene to Pleistocene offsets; and (2) the fact that there has 

been no additional published research conducted to support Quaternary offsets along these faults 

(e.g., Wheeler, 2005). 

7.3.10 Gulf Coast Highly Extended Crust Zone (GHEX) 

The breakup of the supercontinent of Pangaea and the formation of the Gulf of Mexico in the 

Triassic and Jurassic resulted in the development of three large crustal domains in the Gulf of 

Mexico region. From north to south, these domains are the thick transitional crust, the thin 

transitional crust, and the newly formed oceanic crust (Buffler and Sawyer, 1985; Marton and 

Buffler, 1994; Salvador, 1991a, 1991b; Sawyer et al., 1991). The Gulf Highly Extended Crust 

(GHEX) seismotectonic zone is the thin transitional crust domain (Figure 7.3.10-1). 
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The thin transitional crust within the Gulf of Mexico region represents continental crust that has 

undergone considerable thinning associated with the opening of the Gulf of Mexico. In contrast 

to the thick transitional crust that is 20–40 km (12.5–25 mi.) thick (see Section 7.3.9), the thin 

transitional crust is generally 8–15 km (5–9.3 mi.) thick (Sawyer et al., 1991). This relatively 

thin crust subsided more quickly than the thick transitional crust during and following the 

opening of the Gulf of Mexico allowing for the deposition of thick nonmarine and marine 

sediments, including the salt deposits that are characteristic of the Gulf of Mexico region. These 

thick sedimentary sequences—and in particular, the salt deposits—have made it difficult to 

seismically image geologic structures that may have accommodated the extension of the thin 

transitional crust (Buffler and Sawyer, 1985; Marton and Buffler, 1994; Sawyer et al., 1991). 

However, magnetic data suggests that structures within the thin transitional crust are generally 

oriented parallel to the trend of the Gulf margin (Sawyer et al., 1991). 

The source characterization of the GHEX seismotectonic zone described in the following text is 

based on a review of published material; these same materials were also used for Section 7.3.9 

Extended Continental Crust—Gulf Coast (see Appendix Table D-7.3.9). Explicit references that 

were used as the basis for source characteristics are identified in Appendix Table C-7.3.9.

7.3.10.1 Basis for Defining Seismotectonic Zone 

Following the methodology for defining seismotectonic zones (see Chapter 4), the GHEX zone is 

included as a zone distinct from the ECC-GC zone because the GHEX zone is expected to have 

different future earthquake characteristics. In particular, based on the reduced crustal thickness of 

the GHEX zone (8–15 km [5–9.3 mi.]), the seismogenic thickness of the zone should be less than 

that of the ECC-GC zone. 

7.3.10.2 Basis for Zone Geometry 

The boundaries of the GHEX seismotectonic zone are defined by the boundary between the thin 

and thick transitional crust (see Section 7.3.9.2 for discussion of this boundary) and the boundary 

between the oceanic crust and the thin transitional crust (Figure 7.3.10-1). The oceanictransitional crust boundary of Bird et al. (2005) defines the zone because it is one of the more 

recent interpretations of the crustal extent that takes into account the latest data, and because it is 

within the range of extents estimated by previous researchers (e.g., Buffler and Sawyer, 1985; 

Hall and Najmuddin, 1994; Marton and Buffler, 1994; Pindell et al., 2000; Sawyer et al., 1991). 

7.3.10.3 Basis for Zone Mmax 

As with all the seismotectonic zones, the Mmax distribution for the GHEX zone is derived using 

two different approaches (Section 5.2). However, the Kijko approach was given zero weight for 

this zone because of the low P-value (see Section 5.2.1.3). For the Bayesian approach, the MESE 

and COMP priors are used because the zone geometry is defined by the extent of Mesozoic 

extension. Two weighted magnitudes are used to represent uncertainty in the largest earthquake 

occurring within the zone. 
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The largest earthquake from the catalog within the zone is the February 10, 2006, E[M] 4.85 

earthquake, referred to as the Green Canyon earthquake. The earthquake occurred along the 

Sigsbee escarpment off Louisiana. Nettles (2007) has interpreted this earthquake as a gravitydriven landslide based on the lack of high-frequency energy in the waveforms, slow rise time, 

preliminary focal mechanism determinations, and location on the Sigsbee escarpment. 

Preliminary conclusions of Dellinger et al. (2007a, b) also support this interpretation, but these 

studies acknowledge that neither a consensus nor conclusive interpretation of the earthquake 

mechanism has been determined. Furthermore, efforts to relocate the earthquake cannot 

constrain the depth of the earthquake to within the range expected for a landslide mechanism 

(Dewey and Dellinger, 2008), and there have been no peer-reviewed studies of the earthquake 

published in the scientific literature. 

In addition to the February earthquake, the September 10, 2006, E[M]5.82 earthquake occurred 

just outside the zone by approximately 15 km (9 mi.; Figure 7.3.10-1). The magnitudes of these 

two earthquakes are equally weighted as the maximum observed earthquake within the zone for 

the following reasons: 

There is uncertainty in whether or not the February earthquake was caused by a landslide or 

discrete fault rupture. 

There is considerable uncertainty in the exact location of the oceanic-transitional crust 

boundary (e.g., Bird et al., 2005; Buffler and Sawyer, 1985; Hall and Najmuddin, 1994; 

Marton and Buffler, 1994; Pindell et al., 2000; Sawyer et al., 1991). 

Given that uncertainty, it is possible that the September earthquake occurred in transitional, 

and not oceanic, crust. 

The final Mmax distribution for this zone is presented in Section 7.4. 

7.3.10.4 Future Earthquake Characteristics 

Future earthquakes within the GHEX seismotectonic zone are modeled with the default 

characteristics for the CEUS with the exception of the strike of fault ruptures and the 

seismogenic thickness of crust within the zone. Similar to the ECC-GC zone, it is likely that 

future moderate to large earthquakes will occur along preexisting basement structures associated 

with the opening of the Gulf of Mexico, and the structures most likely to be reactivated are 

normal faults roughly perpendicular to the rifting direction (i.e., roughly parallel to the coastline) 

that accommodated the extension and transform faults subparallel to the rifting direction (i.e., 

roughly perpendicular to the coastline) that accommodated differential spreading rates. However, 

there is considerable uncertainty in the orientation of these structures throughout the GHEX zone 

because there are several kinematic models for the opening of the Gulf of Mexico, all of which 

imply different orientations for the two fault types, and in general, each of the models has 

internal variation in the orientation of the two fault types within different regions of the ECC-GC 

zone (e.g., the western vs. eastern Gulf of Mexico) (Anderson and Schmidt, 1983; Buffler and 

Sawyer, 1985; Buffler et al., 1980; Dunbar and Sawyer, 1987; Hall et al., 1982; Hall and 

Najmuddin, 1994; Klitgord et al., 1984; Marton and Buffler, 1994; Pindell, 1985, 1993; Pindell 

and Kennan, 2001; Pindell et al., 2006; White, 1980). Combining the uncertainty from these two 
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factors, it is difficult to identify a preferred range of orientations, so the expected strike of future 

ruptures within the GHEX zone is modeled as randomly oriented. 

The large amounts of crustal thinning in the GHEX zone has resulted in crustal thicknesses for 

the thin transitional crust that are generally between 8 and 15 km (5 and 9.3 mi.; Sawyer et al., 

1991). Because of this thinning, the seismogenic thickness of the crust within the zone should be 

less than the default values for the CEUS. For the GHEX zone the seismogenic thickness is 

assumed to be limited by the approximate crustal thickness (i.e., 8–15 km [5–9.3 mi.]). For 

simplicity and because the crustal thickness is not uniformly known within the GHEX zone, 

these two end-member seismogenic thicknesses are weighted evenly. 

7.3.11 Oklahoma Aulacogen Zone (OKA) 

The Oklahoma aulacogen (OKA) seismotectonic zone (Figure 7.3.11-1) is interpreted as a failed 

rift arm that formed in the late Proterozoic to early Cambrian. Many of the original rift-related 

structures were subsequently reactivated and/or overprinted during the late Paleozoic Ouachita 

orogeny. The geologic history of the aulacogen generally is represented as consisting of four 

phases (Gilbert, 1983b; Keller and Stephenson, 2007; McConnell and Gilbert, 1990; Perry, 

1989): 

1. The initial late Proterozoic–early Cambrian rifting and associated magmatism. 

2. A period of post-rift subsidence in the middle Paleozoic. 

3. Compressional deformation associated with the late Paleozoic Ouachita orogeny. 

4. Mesozoic and Cenozoic stability with the exception of the noted Quaternary slip observed on 

the Meers fault. 

The main stage of rifting that led to the breakup of Rodinia along what is now the eastern margin 

of North America occurred between approximately 620 Ma and 550 Ma (Thomas, 2006; 

Whitmeyer and Karlstrom, 2007). Within this stage of large-scale rifting, the initiation of 

extension within the OKA is marked by the intrusion of rift-related basaltic magma at 

approximately 600 Ma (Gilbert, 1983b; McConnell and Gilbert, 1990). Magmatism associated 

with aulacogen formation continued until approximately 500 Ma (Gilbert, 1983b). The rifting 

presumably was accommodated along a series of normal faults approximately parallel to the 

trend of the aulacogen, but the original extensional faults have been either masked or reactivated 

during subsequent tectonic events, making identification of rift-related faults difficult (Brewer et 

al., 1983; Gilbert, 1982; Gilbert, 1983b; Keller and Stephenson, 2007; Perry, 1989). 

During the middle Paleozoic (Cambrian through early Mississippian), the region surrounding the 

aulacogen was tectonically stable and characterized by subsidence that initiated significant basin 

deposition in the present-day Anadarko basin (Perry, 1989). This period of tectonic quiescence 

ended in the late Paleozoic during the Pennsylvania Ouachita orogeny that marked the closing of 

the Iapetus Ocean and the formation of the supercontinent Pangaea. In the region of the 

Oklahoma aulacogen, the Ouachita orogeny led to the formation of the Wichita, Arbuckle, and 

Amarillo uplifts, which partially were accommodated along reactivated normal faults from the 

original aulacogen formation. These uplifts and related structures now overprint the structural 
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expression of the aulacogen (Brewer, 1982; Brewer et al., 1981; Brewer et al., 1983; Good et al., 

1984; Perry, 1989). Since the cessation of the Ouachita orogeny, the region surrounding the 

OKA has been tectonically stable with the exception of the Quaternary activity observed on the 

Meers fault (Crone and Luza, 1990; Gilbert, 1983a; Swan et al., 1993; see Section 6.1.4). No 

other faults associated with the Wichita, Arbuckle, and Amarillo uplifts or the OKA have 

demonstrated Quaternary activity. 

The source characterization of the OKA described in the following text is based on a review of 

published material (see Appendix Table D-6.1.4). Explicit references that were used as the basis 

for source characteristics are identified in Appendix Table C-6.1.4. 

7.3.11.1 Basis for Defining Seismotectonic Zone 

Following the CEUS SSC methodology for defining seismotectonic zones (see Chapter 4), the 

OKA is included as a distinct zone because we expect it to have distinct differences in future 

earthquake characteristics compared to surrounding regions. Compared to the default future 

earthquake characteristics applied to the CEUS in our model, we expect the OKA to have the 

following differences: 

Style of faulting: Left-lateral oblique-reverse fault dominated by strike-slip motion based on 

the observed slip of the Meers fault (see Section 6.1.4). 

Strike of ruptures: N60°W 15° based on the observed strike of faults in the Wichita, 

Arbuckle, and Amarillo uplifts (e.g., Ham et al., 1964; Texas BEG, 1997). 

The basis for defining the distinct future earthquake characteristics for the aulacogen is the 

observation of the characteristics of the Quaternary activity on the Meers fault, a fault within the 

Wichita frontal fault system (see Section 6.1.4). Despite the lack of evidence for any Quaternary 

activity on any other geologic structures within the aulacogen, the strong structural expression of 

the aulacogen and uplifts indicates that any future moderate to large earthquakes in the aulacogen 

are likely to have characteristics similar to those of the Meers fault. 

7.3.11.2 Basis for Zone Geometry 

The geometry of the OKA seismotectonic zone is defined to envelop the extent of (1) the 

aulacogen as defined by gravity and magnetic anomaly data (CEUS SSC gravity and magnetic 

anomaly data; Figure 7.3.11-1); and (2) mapped faults related to the Arbuckle, Amarillo, and 

Wichita uplifts (e.g., Ham et al., 1964; Texas BEG, 1997). The southeastern extent of the zone is 

defined by the limit of crustal thinning associated with the Mesozoic opening of the Gulf of 

Mexico. This envelope is meant to capture both the region of crust that was the center of rifting 

and magmatism during the opening of the aulacogen, and faults within this potentially weakened 

crust and associated with the Arbuckle, Amarillo, and Wichita uplifts and the Ouachita orogeny. 

Given the uncertainty in the extent of the aulacogen and the uplift-related faults, there is 

considerable uncertainty in the boundary of the OKA. It is not possible to quantify this 

uncertainty, but it is likely on the order of 50 km (31 mi.) or more. 
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It should be noted that the OKA zone was not extended into New Mexico, Colorado, and Utah 

despite evidence for magmatism and geopotential anomalies in these regions that have been 

attributed to the Cambrian rifting of the OKA (e.g., Keller and Stephenson, 2007; Larson et al., 

1985). The decision to limit the OKA source zone to the extent presented here was based on the 

lack of evidence for Quaternary faulting within the New Mexico, Colorado, and Utah regions of 

Cambrian rifting; the fact that the Arbuckle, Amarillo, and Wichita uplifts do not extend that far; 

and the fact that most of these regions are outside of the study area. 

7.3.11.3 Basis for Zone Mmax 

As with all the seismotectonic zones, the Mmax distribution for the OKA zone is derived using 

two different approaches (see Section 5.2). However, for this zone, the Kijko approach was given 

zero weight because of the low P-value (see Section 5.2.1.3). For the Bayesian approach, the 

NMESE and COMP priors are used for this zone due to the absence of Mesozoic extension 

within the OKA. Two weighted scenarios are used to represent uncertainty in the largest 

earthquake observed within the zone. The largest earthquake within the zone is the July 30, 1925,

E[M] 5.24 earthquake (Figure 7.3.11-1). However, the October 22, 1882, E[M] 5.58 earthquake 

is located just to the west of the zone and likely has significant uncertainty in its location because 

that location is based on historical accounts. To capture the possibility that the 1882 earthquake 

did occur within the OKA zone, two equally weighted options for the largest observed 

earthquake in the zone are considered: E[M] 5.58, based on the 1882 earthquake, and E[M]5.24,

based on the 1925 earthquake. The final Mmax distribution for this zone is presented in Section 

7.4.2.

7.3.11.4 Future Earthquake Characteristics 

As described above, we model future earthquakes within the OKA seismotectonic zone using the 

default characteristics for the CEUS, as discussed in Section 5.4, with the exception of the style 

of faulting and rupture strike. Default values are used because there is little to no information to 

strongly support alternative values. Based on the observations of Quaternary slip on the Meers 

fault, the style of faulting for future earthquakes within the OKA is constrained to be left-lateral, 

oblique-reverse fault dominated by strike-slip motion (see Section 6.1.4). Based on the observed 

orientation of faulting associated with the Wichita, Arbuckle, and Amarillo uplifts, the strike of 

future ruptures within the OKA is constrained to be parallel to the long axis of the zone (e.g., 

Ham et al., 1964; Texas BEG, 1997). 

7.3.12 Midcontinent-Craton Zone (MidC) 

The continental interior (Midcontinent-Craton), which consists of those regions that have not 

been incorporated into Phanerozoic orogens of the continental margin, comprises two geologic 

provinces: the Canadian Shield, where Precambrian metamorphic and igneous basement rocks 

crop out at the ground surface, and the platform, where Precambrian basement rocks lie beneath 

a veneer of sedimentary strata (Marshak and Paulsen, 1997). 
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The following text provides a discussion of the geologic, seismic, and geophysical characteristics 

of the Midcontinent-Craton (MidC) seismotectonic zone. This discussion, as well as the seismic 

source characterization of the MidC, is based on a review of published material that is 

summarized in the Data Summary table for the MidC zone (Appendix Table D-7.3.12). Explicit 

references and data that were used as the basis for source characteristics of MidC are identified 

in the Data Evaluation table (Appendix Table C-7.3.12). 

7.3.12.1 Background 

7.3.12.1.1 Precambrian Crustal Basement Structure 

The Central United States is underlain by several Precambrian terranes, including the Superior 

province (2,700 Ma); Penokean orogen (1,880–1,830 Ma); Northern Central Plains orogen 

(1,880–1,700 Ma); Southern Central Plains orogen (1,700–1,600 Ma); Eastern Granite-Rhyolite 

province (1,470 ± 30 Ma); Southern Granite-Rhyolite province (1,370 ± 30 Ma); Midcontinent 

rift system (1,100–1,000 Ma); and Grenville province (1,100–800 Ma; Atekwana, 1996; Van 

Schmus et al., 1996). 

Whitmeyer and Karlstrom (2007) present a plate-scale model for the Precambrian growth and 

evolution of the North American continent. The core of the North American continent, including 

the Canadian Shield, was formed in the Paleoproterozoic (1,600–2,500 Ma) by plate collisions. 

The thick, buoyant, and compositionally depleted mantle lithosphere that now underlies North 

America, although dominantly of Archean (>2,500 Ma) age, took its present shape due to 

collisional orogenesis and likely has a scale of mantle heterogeneity similar to that exhibited in 

the overlying crust. 

In marked contrast, the lithosphere of southern North America (i.e., much of the continental 

United States) was built by progressive addition of a series of dominantly juvenile volcanic arcs 

and oceanic terranes accreted along a long-lived southern (based on present coordinates) plate 

margin. The lithospheric collage that formed from dominantly juvenile terrane accretion and 

stabilization (1,800–1,000 Ma) makes up about half of the present-day North American 

continent. Throughout—and as a result of—this long-lived convergent cycle, mantle lithosphere 

below the accretionary provinces was more hydrous, fertile, and relatively weak compared to 

mantle lithosphere under the Archean core. 

Mooney and Ritsema (2009) hypothesize that greater lithospheric strength correlates with lower 

rates of continental crustal seismicity and with lower maximum magnitude. They suggest that 

high lithospheric S-wave velocities that are typical of cratonic lithosphere correspond to high 

integrative lithospheric strength. By comparing global maps of S-wave velocity anomalies at a 

depth of 175 km (108 mi.) and the moment magnitudes of earthquakes in the overlying crust, 

Mooney and Ritsema (2009) conclude that the maximum magnitude for SCRs underlain by 

S-wave velocity anomalies of >3.5 percent, which includes a large portion of the Archean- and 

Neoproterozoic-age Precambrian continental interior of the CEUS, appears to be M 7. Analysis 

of the magnitudes of earthquakes in stable continental regions worldwide indicates that a broader 

range of magnitudes may better represent the uncertainty in maximum magnitude (Section 5.2).
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7.3.12.1.2 Major Precambrian Basement Structures 

Major Precambrian basement features have been interpreted by various workers based on 

interpretation of geologic data from drilling, deep crustal seismic profiles, and interpretation of 

geopotential field data (e.g., Braile et al., 1986; Pratt et al., 1989; Atekwana, 1996; Marshak and 

Paulsen, 1997). Sims et al. (2005) present a preliminary structure map of Precambrian basement 

rocks based on interpretation of geologic and magnetic data (Figure 7.3.12-1). They suggest that 

the systematics of major regional post-assembly Precambrian basement structures throughout the 

continental United States point to a common causal mechanism for their development. A major 

driving force for plate movement is deep-mantle flow resulting from seismic anisotropy beneath 

the continents and mechanical coupling and subsequent shear between the lithosphere and 

asthenosphere. Two orthogonal sets of shear zones and faults are predominant in the continent: 

(1) northeast-striking partitioned ductile shear zones and (2) northwest-trending strike-slip 

ductile-brittle faults (Sims et al., 2005).

The northeast-striking shear zones are interpreted by Sims et al. (2005) as resulting from 

northwest-southeast shortening, apparently formed during the interval 1,760–1,700 Ma. The 

northwest-trending (1,700–1,500 Ma) transcurrent fault system consists of west-northwest to 

northwest synthetic faults and northerly trending antithetic transfer faults. The deformation 

during this interval is attributed to transpressional-transtensional deformation (i.e., strike-slip 

deformation that deviates from simple shear because of a component of shortening or extension 

orthogonal to the deformation zone). The northeast- and northwest-oriented shears and faults 

mimic orthogonal teleseismic images of the upper mantle. These structures were reactivated 

during the Mesoproterozoic (1,000–1,600 Ma) and later times. The kinematics of regional 

Precambrian basement structures within the continental United States suggest that deformation 

since at least early Proterozoic time has been predominantly transpressional. Transcurrent 

lithospheric structures formed during Proterozoic mantle deformation are oriented obliquely to 

the southwestward (absolute) motion of the North American Plate. Stress caused by traction 

between the asthenosphere and lithosphere during the southwestward drift focused on preexisting 

block boundaries that have repeatedly reactivated basement zones of weakness, thus localizing 

sedimentation, magmatism, and generation of ore deposits (Sims et al., 2005). 

Marshak and Paulsen (1997) identified similar north-northeast and west-northwest trends that 

break up the continental interior of the United States into roughly rectangular blocks. They refer 

to these as the Midcontinent fault and fold zones and suggest that the current intraplate stress 

field of North America is sufficient to cause slight movements of crustal blocks in the interior, 

thereby triggering seismicity. Marshak and Paulsen (1997) also note that differential epeirogenic 

movements (the gradual uplift, subsidence, or tilting of broad areas relative to their 

surroundings) have affected sedimentary thicknesses and facies throughout the region. These 

movements occurred episodically through the Phanerozoic (post-Precambrian), giving rise to 

reactivated regional-scale (>200 km [>124 mi.] diameter) basins, domes, and arches. 

7.3.12.1.3 Geophysical Anomalies 

As noted by Hinze and Hildenbrand (1988), information on the crystalline crust of the Eastern 

United States from direct observations, drilling, and sparse crustal seismic studies is limited. 
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Regional gravity and magnetic anomaly data provide more uniform coverage and can be used to 

estimate the strength of the crust and lithosphere and to map and characterize (1) zones of 

weakness such as paleorifts, sutures, and faults; (2) regions of potential stress amplifications 

such as plutons and irregularities in fault zones; and (3) basement terranes of generally consistent 

structural pattern that may delimit coherent regional seismic zones. 

Some of the more prominent geophysical anomalies are shown on Figures 7.3.12-1 and 7.3.12-2, 

including the Midcontinent gravity high associated with the Midcontinent rift (Hinze et al., 

1997); gravity and magnetic anomalies associated with the East Continent rift basin (Drahovzal 

et al., 1992); geophysical lineaments such as the Commerce geophysical lineament (CGL; 

Langenheim and Hildenbrand, 1997; Hildenbrand and Hendricks, 1995); the south-central 

magnetic lineament (SCML; Hildenbrand et al., 1983); and the neodymium (Nd) isotopic 

boundary (also referred to as the St. Charles lineament [SCL]), which probably represents the 

southeast limit of Paleoproterozoic crust (Van Schmus et al., 1996; Harrison and Schultz, 2002; 

Van Schmus et al., 2007); and sutures such as the Great Lakes tectonic zone (GLTZ), Spirit Lake 

tectonic zone (SLTZ), Eau Plain shear zone (EP), and Niagara fault zone (NF; Hinze, 1996; Van 

Schmus et al., 2007). 

7.3.12.1.4 Seismicity 

Seismicity within the MidC zone is spatially variable, with moderate concentrations of 

earthquake activity separated by areas of very low seismicity. Previously recognized zones of 

seismicity are the Anna seismic zone in Ohio, the Northeast Ohio seismic zone, and a zone of 

moderate seismicity in the vicinity of the Nemaha ridge in Kansas (Figure 7.3.12-3). 

Reconnaissance paleoliquefaction surveys conducted to date have not identified evidence for 

large-magnitude (M > 7) earthquakes in these zones. Preliminary conclusions from these studies, 

which are discussed in the following descriptions of the zones, are that M > 7 earthquakes 

probably have not occurred in these regions in the past few thousand years. Moderate-sized 

earthquakes (M 6 to < M 7), however, cannot be precluded based on the extent and completeness 

of the surveys and the existing geologic characteristics (e.g., liquefaction susceptibility, quality 

of exposure, age of deposits). The available information does not support defining RLME 

sources associated with these zones of more concentrated seismicity. 

Anna Seismic Zone—This zone, also called the Western Ohio seismic zone, coincides with 

northwest-southeast-trending basement faults associated with the Fort Wayne rift (Figure 

7.312-2) in Shelby, Auglaize, and nearby counties (Hansen, 1993; Baranoski, 2002). Ruff et al. 

(1994) attribute seismicity to the Anna-Champaign, Logan, and Auglaize faults. This zone has 

produced at least 40 felt earthquakes since 1875, including earthquakes in 1875, 1930, 1931, 

1937, 1977, and 1986 that caused minor to moderate damage (Hansen, 1993). The July 12, 1986, 

earthquake near the town of St. Marys in Auglaize County was the largest earthquake to occur in 

the zone since 1937 (Hansen, 1993). For the 1986 magnitude (mb) 4.5 (E[M] 4.37) earthquake,

Schwartz and Christensen (1988) determined a hypocenter of 5 km (3 mi.) and a focal 

mechanism (strike = 25°, dip = 90°, rake = 175°) representing mostly strike-slip, with a small 

oblique component approximately parallel to the Anna-Champaign fault and a nearly horizontal 

P- (maximum compressive stress) axis oriented east-northeast. The earthquake produced a MMI 

VI intensity (Schwartz and Christiansen, 1988). Obermeier (1995) investigated stream banks in 
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7-74

the vicinity of Anna, Ohio, and portions of the Auglaize, Great Miami, Stillwater, and St. Marys 

rivers and found no evidence of paleoliquefaction features indicative of a magnitude 7 

earthquake in the past several thousand years. Obermeier (1995) noted that although there was 

sufficient outcrop to preclude with some confidence an earthquake larger than magnitude 7, the 

paucity of outcrop did not preclude the possibility of prehistoric earthquakes of lower 

magnitudes. Crone and Wheeler (2000) designated the Anna seismic zone a Class C feature4

based on the occurrence of significant historical earthquakes and the lack of paleoseismic 

evidence. 

Northeast Ohio Seismic Zone—This zone, also called the Ohio-Pennsylvania seismic zone, 

defines an approximately 50 km (30.5 mi.) long, northeast-southwest-trending zone of 

earthquakes south of Lake Erie on the Ohio-Pennsylvania border (Dineva et al., 2004). The 

largest historical earthquake in this zone was the January 31, 1986, mb 5.0 (E[M] 4.65) 

earthquake located about 40 km (25 mi.) east of Cleveland in southern Lake County, Ohio. The 

earthquake produced MMI VI to VII at distances of 15 km (9 mi.) from the epicenter (Nicholson 

et al., 1988). Aftershocks with magnitudes ranging from 0.5 to 2.5 and focal depths ranging from 

2 to 6 km (1.2 to 3.7 mi.) occurred in a tight cluster about 1 km (0.6 mi.) wide and oriented 

north-northeast. Focal mechanisms represent predominantly oblique, right-slip motion on nearly 

vertical planes oriented N15° to 45°E, with a nearly horizontal P-axis consistent with the modern 

stress regime (Nicholson et al., 1988). 

The January 31, 1986, earthquake and aftershocks were within 12 km (7.3 mi.) of deep wastedisposal injection wells, and the earthquake sequence is possibly due to injection activities at the 

wells that reactivated favorably oriented preexisting fractures (Nicholson et al., 1988). However, 

the relative distance of the wells from the earthquake cluster (12 km [7.3 mi.]), as well as the 

lack of large numbers of earthquakes that are typical of induced sequences, a history of small to 

moderate earthquakes in the region preceding well activities, and the attenuation of the pressure 

field with distance from the wells—all argue for a natural origin for the earthquakes (Nicholson 

et al., 1988). 

Nicholson et al. (1988) observe that the 1986 cluster is coincident with a N40°E trending gravity 

and magnetic anomaly. Seeber and Armbruster (1993) and Dineva et al. (2004) also associate the 

Northeast Ohio seismic zone with the Akron magnetic boundary, which is also called the Akron 

magnetic anomaly or lineament (Figure 7.3.12-2). Seeber and Armbruster (1993) speculate that 

the Akron magnetic boundary may be associated with the Central Metasedimentary Belt 

boundary zone as a continental-scale Grenville-age structure. Since the Akron lineament is 

imaged as ductile shear zones on regional seismic lines and no structures are observed in the 

overlying Paleozoic sediments, Seeber and Armbruster (1993) acknowledge that the geometry of 

brittle faulting within or near this ductile deformation may have a complex relationship with the 

geometry of these shear zones. 

In 1987, the first in a series of earthquakes continuing to 2003 occurred within the Northeast 

Ohio seismic zone near Ashtabula in Ashtabula County, Ohio, northeast of the 1986 earthquakes 

 

4

 See Section 4.1.3.3 for definition of fault and feature categories used by the USGS to characterize Quaternary and 

possible Quaternary features in the CEUS. 
Chapter 7 

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(Nicholson et al., 1988; Seeber and Armbruster, 1993; Hansen et al., 2001; Seeber et al., 2004). 

The largest earthquakes in the sequence include an initial mbLg 3.8 (E[M] 3.61) earthquake on 

July 13, 1987; a mbLg 2.6 foreshock earthquake on January 19, 2001; a mbLg 4.3 (E[M] 3.86) 

earthquake on January 26, 2001, which had an MMI of VI; followed by a mbLg 3.0 (E[M] 2.92) 

earthquake on June 3, 2001, and a mbLg 2.4 earthquake on June 5, 2001 (Hansen et al., 2001). 

The latest subsequence started in July 2003 with a mbLg 2.5 earthquake (Seeber et al., 2004) 

Seeber et al. (2004) discuss these fore-/main-/aftershock sequences and interpretations of these 

earthquakes using information obtained from three short-term deployments of portable 

seismographs (in 1987, 2001, and 2003) and from regional broadband seismograms. The main 

observations and conclusions from this analysis are as follows: 

A persistent earthquake sequence in northeast Ohio includes multiple, distinct fore-/main-

/aftershock sequences that illuminate two nearly vertical, east-trending faults approximately 

4 km (2.5 mi.) apart. The first motions are consistent with left-lateral strike-slip movement 

on an east-west-striking fault. The seismicity is closely associated with injection of waste 

fluid in the basal Paleozoic formation from 1986 to 1994. 

All the earthquakes originated from a relatively small area (~10 km [~6 mi.] wide) and are 

assumed to form a single sequence of casually related earthquakes. 

Felt earthquakes started in 1987, a year after the onset of injection. At that time, earthquakes 

were located 0.7–2.0 km (0.4–1.2 mi.) from the injection site. Seismicity continued and in 

2001, five and a half years after the end of injection, hypocenters were then 5–9 km (3–5.6 

mi.) from the injection site. The only known episode of seismicity in Ashtabula is closely 

associated with the 1986–1994 Class 1 injection, and the pattern of hypocenters is consistent 

with one expected for the high pore-pressure anomaly spreading from the injection site. 

This spatial and temporal correlation is strong evidence that the seismicity was triggered by 

the injection. 

A paleoseismic liquefaction field study along two of the larger drainages in northeast Ohio, the 

Grand River and the Cuyahoga River, was conducted by Obermeier (1995) and involved 

reconnaissance along approximately 25 km (7.6 mi.) of stream bank. No evidence of liquefaction 

was observed along either transect. Although the scarcity of suitable exposures precludes 

definitive statements about prehistoric earthquakes, this led Crone and Wheeler (2000) to 

classify the Northeast Ohio seismic zone as a Class C feature. Conditions and ages of the 

sediment encountered along each of these rivers as noted by Obermeier (1995) were summarized 

in the report, as follows: 

Radiocarbon data from along the Grand River show that many of the exposures searched are 

at least 2,000 years old. Many others are probably mid-Holocene in age, based on depth and 

severity of weathering. A few scattered sites are earliest Holocene in age. Liquefaction 

susceptibility at many of the sites examined is at least moderate. 

Numerous exposures along the Cuyahoga River are at least a few thousand years in age, and 

scattered exposures are up to 8,000 years old, based on radiocarbon data. Conditions are 

favorable for forming liquefaction effects at many places. 
Chapter 7 

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It is unlikely that sediments exposed in a sand pit near the Ashtabula-Trumbull county line 

experienced strong ground shaking through most or all of Holocene time. The groundwater 

table has probably been shallow enough through all or much of the Holocene to provide 

conditions favorable to liquefy the thick sand deposits overlain by a silt cap that are exposed 

in the quarry walls. 

Nemaha Ridge–Humboldt Fault Seismic Zone—Historical felt earthquakes and instrumentally 

recorded microseismicity are loosely associated with basement structures in northeastern Kansas. 

Wheeler and Crone (2001) note that two damaging earthquakes in 1867 (Wamego earthquake) 

and 1952, which were assigned magnitudes of M 5.54 and M 5.66, respectively, by Johnston 

(1994), occurred in the vicinity of the Humboldt fault zone on the Nemaha uplift. Niemi et al. 

(2004) and Bakun and Hopper (2004a) also suggest a possible association of the 1867 Wamego 

earthquake with the basement Nemaha Ridge–Humboldt fault structures, which lie to the east 

and roughly parallel to the Proterozoic Midcontinent rift system. Seeber and Armbruster (1991) 

assigned the 1867 earthquake a magnitude of 5.2. Bakun and Hopper (2004a) assign a magnitude 

(2σ range) of MI 4.9 (4.5–5.2) to the earthquake. The 1867 and 1952 earthquakes are assigned 

magnitudes of E[M] 5.50 and E[M] 5.29 in the CEUS SSC Project catalog. 

Niemi et al. (2004) conducted field reconnaissance investigations to evaluate evidence for 

paleoliquefaction in the epicentral region of the 1867 Wamego earthquake. Field investigations 

confirm that sedimentary deposits with moderate liquefaction susceptibility are present in the 

vicinity of Wamego and Wabaunsee, Kansas, the preferred source location of the 1867 Wamego 

earthquake. Soft-sediment deformation features, including flame and dish structures, are present 

in late Holocene floodplain deposits of the Kansas River and appear to be concentrated in the 

horseshoe bend region of the Kansas River near Wamego and Wabaunsee, Kansas. Results of the 

reconnaissance suggest that liquefaction features (e.g., clastic dikes), which may be attributed to 

seismically induced liquefaction, are present but may not be pervasive in this region. Niemi et al. 

(2004) concluded from the results of their reconnaissance that these data suggest that the 1867 

Wamego earthquake with a reported magnitude of 5.2 (Seeber and Armbruster, 1991) may 

characterize the seismic source in this region. Although the available data suggest that the 

earthquake that triggered the paleoliquefaction features could have been close to the thresholdsized earthquake that may trigger paleoliquefaction (approximately M 5.4–5.8; Olson et al., 

2005), the available data do not preclude the possibility that the earthquake was larger. There is 

not sufficient information at this time to characterize an RLME source associated with the 

Nemaha Ridge–Humboldt fault region. 

7.3.12.2 Basis for Defining Seismotectonic Zone 

The MidC seismotectonic zone represents continental crust that has not experienced Mesozoic or 

younger crustal extension. Defining the MidC seismotectonic zone centers primarily on the 

concept that continental crust that has not experienced Mesozoic or younger crustal extension 

will have a different maximum magnitude probability than crust that has experienced Mesozoic 

or younger extension (Johnston et al., 1994; see also updated analysis in Section 5.2). 
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The MidC zone is also defined as a seismic source in part to differentiate it from some adjoining 

regions of the crust that that are interpreted as producing different future rupture characteristics. 

For example, the trend of future ruptures in the adjoining Illinois Basin Extended Basement 

(IBEB), Reelfoot Rift (RR), and Oklahoma Aulacogen (OKA) seismotectonic zones reflects 

preferred orientations of structures in those zones, which differ from the trend of ruptures 

modeled for the MidC. 

7.3.12.3 Basis for Zone Geometry 

Four alternative geometries are considered based on alternative geometries of adjacent zones. 

These are shown on Figure 7.3.12-4. The northern and western boundaries of all alternative 

MidC zones are the study region boundaries. The eastern boundary is defined by either the 

western boundary of the Paleozoic Extended Crust (PEZ) and RR wide or narrow geometries 

(see Sections 7.3.4 and 7.3.5, respectively). The southern boundary west of the RR is defined by 

the northern boundary of the Extended Continental Crust–Gulf Coast (ECC-GC) and OKA 

seismotectonic zones (Sections 7.3.9 and 7.3.11, respectively). 

7.3.12.4 Basis for Zone Mmax 

The Mmax distribution for the MidC source zone is based on the two approaches, Kijko (2004) 

and Bayesian, as outlined in Section 5.2. 

For the Kijko approach, the P-values for the four MidC alternative geometries (MidC-A, 

MidC-B, MidC-C, and MidC-D) are all 0.03; therefore, in all cases this approach is weighted 

0.24. 

For the Bayesian approach, both the composite (COMP) prior and the non-Mesozoic and 

younger extension (NMESE) prior are used; the NMESE is selected based on the evidence for no 

Mesozoic or younger extension in the craton region of the Midcontinent. The priors are truncated 

and modified using the likelihood function based on the largest historical earthquakes recorded 

within the zone: the May 16, 1909, E[M] 5.72; November 15, 1877, E[M] 5.50; and March 28, 

1964, E[M] 4.84 earthquakes. The location of the largest earthquake in this zone, the May 16, 

1909, E[M] 5.72 earthquake at a latitude/longitude intersection in eastern Montana near the 

Canadian border suggests this earthquake is poorly constrained. 

The weights for Kijko and Bayesian approaches for the RR zone also are discussed in Section 

7.4.2, and the weighted composite posterior maximum-magnitude probability distribution for the 

RR zone is provided in Section 7.4.2. The derived Mmax distributions for the MidC 

seismotectonic zone are presented in Section 7.4.2. 

7.3.12.5 Future Earthquake Characteristics 

The MidC seismotectonic zone uses default characteristics for future rupture characteristics 

listed in Table 5.4-2. The MidC zone encompasses a large intracratonic region characterized by 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-78

deeply buried Precambrian structures for which independent interpretational constraints are 

limited. The available data for the CEUS on style of faulting, focal mechanisms, and depth of 

well-constrained earthquakes used to develop the ―default‖ characteristics as outlined in Table 

5.4-1 include information from the MidC region. 

7.4 Maximum Magnitude Distributions for Seismotectonic Distributed 

Seismicity Sources 

This section presents the maximum earthquake magnitude (Mmax) distributions for the 

seismotectonic distributed seismicity sources. The methodology used to develop these 

distributions is presented in Section 5.2.1. The steps involved in the process are identification of 

the maximum observed earthquake in each distributed seismicity source (described in Section 

7.4.1) and then application of the quantitative approaches developed in Section 5.2.1 to produce 

the composite Mmax distributions (described in Section 7.4.2). 

7.4.1 Maximum Observed Earthquake Magnitude 

The maximum observed earthquake magnitude, 

mmax obs

, represents the largest non-RLME 

earthquake observed to have occurred with each source. The value of this magnitude is used in 

developing the likelihood function for the Bayesian Mmax approach (Section 5.2.1.1) and is a 

parameter of the Kijko approach (Section 5.2.1.2). Two resources are used to assess 

mmax obs

. 

One is the CEUS SSC Project catalog developed for this study (Chapter 3) and the other is 

identified paleoearthquakes that are not treated as RLMEs. The latter consist of the four nonRLME paleoearthquakes that have been identified in the IBEB seismotectonic zone and the 

potential liquefaction earthquake in the ECC_GZ zone. These earthquakes are discussed in 

Sections 7.3.5.4 and 7.3.9.5 for the IBEB and ECC_GC zones, respectively. The largest nonRLME historical earthquakes identified in the CEUS SSC Project catalog for each 

seismotectonic source zone are described in Section 7.3 in the subsection for each zone. 

Uncertainty in 

mmax obs

was incorporated into the Mmax assessment using the procedure 

described in Section 5.2.1.1.6. The uncertainties in the magnitudes for the catalog of historical 

earthquakes or paleoearthquakes for each source were used to develop simulated catalogs of 

earthquake magnitudes. The largest values for each simulation were then used to develop a 

distribution for 

mmax obs

. Figure 7.4.1-1 shows the resulting distributions for 

mmax obs

. The blue 

curve on each plot shows the distribution developed for 

mmax obs

, and the red vertical line 

indicates the nominal observed magnitude. The phrase ―paleo‖ in a plot legend (see IBEB on 

Figure 7.4.1-1) indicates that the set of paleoearthquakes is the controlling set for determining 

mmax obs

and was the set used to develop the Mmax distributions. For a number of zones, 

alternative earthquake catalogs (as indicated in the plot legends) were used to address the 

uncertainty in assigning particular earthquakes to the zone. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-79

7.4.2 Mmax Distributions

Mmax distributions were developed for each seismotectonic distributed seismicity source using 

the Bayesian and Kijko methods. For the Bayesian Mmax approach, the alternative priors 

described in Section 5.2.1.1 were used. Figures 7.4.2-1 through 7.4.2-17 show the resulting 

Mmax distributions obtained by each method. Indicated in the legend of each figure are the 

weights assigned to the individual Mmax methods following the weighting approach described in 

Section 5.2.1.1. The final weighted composite distributions are indicated by the thick red bars on 

each plot. 

The weights assigned to the Kijko method are tabulated below. In general, the numbers of 

earthquakes in many of the seismotectonic source zones are too few to allow weight to be 

applied to the Kijko method. 

Seismotectonic 

Source Zone

Weight Assigned to 

Kijko Method

AHEX 0

ECC_AM 0.05

ECC_GC 0

GHEX 0

GMH 0

IBEB 0

MidC-A 0.24

MidC-B 0.24

MidC-C 0.24

MidC-D 0.24

NAP 0

OKA 0

PEZ_N 0

PEZ_W 0.01

RR 0

RR_RCG 0.07

SLR 0.02

The continuous distributions shown on Figures 7.4.2-1 through 7.4.2-17 were used to construct 

five-point discrete approximations for use in hazard analyses. The resulting Mmax distributions 

are listed in Table 7.4.2-1. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-80

7.5 Recurrence Parameters 

The recurrence parameters (i.e., rate and b-values) for the seismotectonic zones were calculated 

using the methodology and parameters described in Section 5.3.2. Briefly, this methodology 

divides the source zone into cells of dimensions a quarter or half degree and then calculates the 

rate and b-value in each cell using the likelihood function of the data in that cell together with 

penalty functions that tend to smooth the cell-to-cell variation in the rate or the b-value, as 

discussed in Section 5.3.2.1. In addition, this procedure characterizes epistemic uncertainty in the 

recurrence parameters by generating eight alternative maps of the recurrence parameters. 

7.5.1 Rate and b-Value Maps for Single Zone and Two Zones 

Figures 7.5.1-1 through 7.5.1-12 show the mean recurrence maps for the four alternative 

configurations of the seismotectonic zones’ distributed seismicity source zones and the three 

choices of magnitude weights (i.e., Cases A, B, and E presented in Section 5.3.2.2). Maps of the 

calculated uncertainties in recurrence parameters, as well as alternative recurrence maps that 

represent that uncertainty (eight alternative maps for each source-zone configuration), are shown 

in Appendix J. 

The SLR zone exhibits lower b-values than other zones. This zone was fit using somewhat 

different smoothing parameters, as described in Section 5.3.2. 

7.5.2 Comparison of Recurrence Parameters to Catalog 

Figures 7.5.2-1 through 7.5.2-51 compare the expected counts from the recurrence maps for each 

source zone to the observed earthquake counts within the zone. The error bars on the data 

represent the 16–84 percent range of statistical uncertainty in the counts and are calculated using 

the approach by Weichert (1980). Each of the eight curves represents expected counts (i.e., rate 

times equivalent period of completeness) for one of the eight equally weighted alternative maps, 

taking Mmax into account. 

These comparisons indicate a good agreement between predicted and observed rates. For some 

zones, such as ECC_AM, the recurrence model over- or underestimates the observed rates for a 

magnitude bin, but these discrepancies are not unexpected in bins with low earthquake counts. 

These comparisons also illustrate the effect of earthquake counts on rate uncertainty at the 

source-zone scale. The eight alternative curves are nearly identical for MidC-A (Figures 7.5.2-19 

through 7.5.2-21), which has hundreds of earthquakes in the low-magnitude range. In contrast, 

the eight curves differ by a factor of 2 to 5 for OKA (Figures 7.5.2-35 and 7.5.2-36), which has 

earthquake counts more than one order of magnitude lower. The results for OKA also illustrate 

the effect of the magnitude weights on the uncertainty in rates. The behavior of the uncertainty in 

rate at smaller scales is similar to that observed in these figures and is shown more clearly in the 

maps showing uncertainty (see Appendix J). 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-81

Table 7.1-1 

Data Summary and Data Evaluation Tables for Seismotectonic Zones in Appendices C and D 

Section Source (with Acronym) Data Table

7.3.1 St. Lawrence Rift (SLR) C-7.3.1, D-7.3.1

7.3.2 Great Meteor Hotspot (GMH) C-7.3.2, D-7.3.2

7.3.3 Northern Appalachian (NAP) C-7.3.3, D-7.3.3

7.3.4 Paleozoic Extended Crust (PEZ) C-7.3.4, D-7.3.4

7.3.5 Illinois Basin Extended Basement (IBEB) C-7.3.5, D-6.1.9

7.3.6 Reelfoot Rift Zone (RR) C-7.3.6, D-6.1.5

7.3.7 Extended Continental Crust–Atlantic Margin (ECC-AM) C-7.3.7, D-7.3.7

7.3.8 Atlantic Highly Extended Crust (AHEX) C-7.3.7, D-7.3.7

7.3.9 Extended Continental Crust–Gulf Coast (ECC-GC) C-7.3.9, D-7.3.9

7.3.10 Gulf Coast Highly Extended Crust (GHEX) C-7.3.9, D-7.3.9 

7.3.11 Oklahoma Aulacogen (OKA; incl. Meers Fault) C-6.1.4, D-6.1.4

7.3.12 Midcontinent-Craton (MidC) C-7.3.12, D-7.3.12
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-82

Table 7.4.2-1 

Maximum Magnitude Distributions for Seismotectonic Distributed Seismicity Sources 

Weight

Maximum Magnitude for:

AHEX ECC_AM ECC_GC GHEX GMH IBEB

MidC-A, 

MidC-B, 

MidC-C, and 

MidC-D NAP OKA

PEZ_N 

and 

PEZ_W RR RR_RCG SLR

0.101 6.0 6.0 6.0 6.0 6.0 6.5 5.6 6.1 5.8 5.9 6.2 6.1 6.2

0.244 6.7 6.7 6.7 6.7 6.7 6.9 6.1 6.7 6.4 6.4 6.7 6.6 6.8

0.310 7.2 7.2 7.2 7.2 7.2 7.4 6.6 7.2 6.9 6.8 7.2 7.1 7.3

0.244 7.7 7.7 7.7 7.7 7.7 7.8 7.2 7.7 7.4 7.2 7.7 7.6 7.7

0.101 8.1 8.1 8.1 8.1 8.1 8.1 8.0 8.1 8.0 7.9 8.1 8.1 8.1
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-83

Figure 7.1-1 

Seismotectonic zones shown in the case where the Rough Creek graben is not part of the Reelfoot rift (RR) and the Paleozoic 

Extended Crust is narrow (PEZ-N)
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-84

Figure 7.1-2 

Seismotectonic zones shown in the case where the Rough Creek graben is part of the Reelfoot rift (RR_RCG) and the Paleozoic 

Extended Crust is narrow (PEZ-N)
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-85

Figure 7.1-3 

Seismotectonic zones shown in the case where the Rough Creek graben is not part of the Reelfoot rift (RR) and the Paleozoic 

Extended Crust is wide (PEZ-W)
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-86

Figure 7.1-4 

Seismotectonic zones shown in the case where the Rough Creek graben is part of the Reelfoot rift (RR_RCG) and the Paleozoic 

Extended Crust is wide (PEZ-W)
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-87

Figure 7.1-5 

Example of comparing seismotectonic zones with magnetic map developed as part of the CEUS SSC Project
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-88

Figure 7.1-6 

Example of comparing seismotectonic zones with isostatic gravity map developed as part of the CEUS SSC Project
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-89

Figure 7.1-7 

Map of seismicity based on the earthquake catalog developed for the CEUS SSC Project
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-90

Figure 7.1-8 

Map showing example comparison of seismotectonic zones with seismicity. Note the non-uniform spatial distribution of 

seismicity within the zones. Spatial smoothing of a- and b-values accounts for these spatial variations.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-91 

Figure 7.3-1 

Logic tree for the seismotectonic zones branch of the master logic tree 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-92

Figure 7.3.1-1 

Significant earthquakes and paleoseismology of the SLR seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-93

Figure 7.3.1-2 

Tectonic features of the SLR seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-94

Figure 7.3.1-3 

Magnetic and gravity anomaly maps of the SLR seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-95

Figure 7.3.2-1 

Significant earthquakes and paleoseismic study area in the region of the GMH seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-96

Figure 7.3.2-2 

Igneous rocks attributed to the GMH seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-97

Figure 7.3.2-3 

Relocated hypocentral depths and crustal depth of the GMH seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-98

Figure 7.3.2-4 

Magnetic and gravity anomaly maps of the GMH seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-99

Figure 7.3.3-1 

Seismicity of the NAP seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-100

Figure 7.3.3-2 

Magnetic and gravity anomaly maps of the NAP seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-101 

Figure 7.3.4-1 

Seismicity and tectonic features of the PEZ seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-102

Figure 7.3.4-2 

Magnetic and gravity anomaly maps of the PEZ seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-103 

Figure 7.3.5-1 

Map showing seismicity, subsurface Paleozoic and basement structures, and postulated energy centers for prehistoric 

earthquakes
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-104

Figure 7.3.5-2 

Map showing alternative boundaries for Precambrian (proto-Illinois basin) rift basins
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-105 

Figure 7.3.5-3 

Maps showing the IBEB source zone boundaries, seismicity, and prehistoric earthquake centers relative to (a) regional magnetic 

anomalies and (b) regional gravity anomalies
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-106

Figure 7.3.6-1 

Map of seismicity and geomorphic features and faults showing evidence for Quaternary neotectonic deformation and 

reactivation. Inset map shows basement structures associated with the Reelfoot rift.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-107 

Figure 7.3.6-2 

Maps showing geophysical anomalies in the Reelfoot rift region
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-108

Figure 7.3.7-1 

Mesozoic basins within the ECC-AM zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-109 

Figure 7.3.7-2 

Seismicity within the ECC-AM and AHEX zones
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-110

Figure 7.3.7-3 

Magnetic and gravity data for ECC-AM and AHEX zones
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-111 

Figure 7.3.7-4 

Estimated locations of the 1755 M 6.1 Cape Ann earthquake
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-112

Figure 7.3.8-1 

Correlation of interpreted transitional crust with the East Coast magnetic anomaly
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-113 

Figure 7.3.9-1 

The ECC-GC seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-114

Figure 7.3.10-1 

The GHEX seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-115 

Figure 7.3.11-1 

The OKA seismotectonic zone and regional gravity and magnetic data
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-116

Figure 7.3.12-1 

Simplified tectonic map showing the distribution of principal basement faults, rifts, and sutures in the Midcontinent
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-117 

Figure 7.3.12-2 

Maps showing major basement structural features relative to (a) regional magnetic anomalies and (b) regional gravity anomalies
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-118

Figure 7.3.12-3 

Seismic zones and maximum observed earthquakes in the MidC zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-119 

Figure 7.3.12-4 

Alternative MidC source zone configurations
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-120

Figure 7.4.1-1 (1 of 3) 

Distributions for 

mmax obs

 for the seismotectonic distributed seismicity source zones 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-121

Figure 7.4.1-1 (2 of 3) 

Distributions for 

mmax obs

 for the seismotectonic distributed seismicity source zones 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-122

Figure 7.4.1-1 (3 of 3) 

Distributions for 

mmax obs

 for the seismotectonic distributed seismicity source zones 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-123 

AHEX

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 7.4.2-1 

Mmax distributions for the AHEX seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-124

ECC-AM

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.05

Bayesian (COMP) weight = 0.38

Bayesian (MESE) weight = 0.57

Composite Distribution

Figure 7.4.2-2 

Mmax distributions for the ECC_AM seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-125 

ECC-GC

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 7.4.2-3 

Mmax distributions for the ECC_GC seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-126

GHEX

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 7.4.2-4 

Mmax distributions for the GHEX seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-127 

GMH

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 7.4.2-5 

Mmax distributions for the GMH seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-128

IBEB (Paleoearthquakes)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.12

Bayesian (NMESE) weight = 0.48

Composite Distribution

Figure 7.4.2-6 

Mmax distributions for the IBEB seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-129 

MidC-A

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.24

Bayesian (COMP) weight = 0.302

Bayesian (NMESE) weight = 0.456

Composite Distribution

Figure 7.4.2-7 

Mmax distributions for the MidC-A seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-130

MidC-B

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.24

Bayesian (COMP) weight = 0.302

Bayesian (NMESE) weight = 0.456

Composite Distribution

Figure 7.4.2-8 

Mmax distributions for the MidC-B seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-131 

MidC-C

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.24

Bayesian (COMP) weight = 0.302

Bayesian (NMESE) weight = 0.456

Composite Distribution

Figure 7.4.2-9 

Mmax distributions for the MidC-C seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-132

MidC-D

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.24

Bayesian (COMP) weight = 0.302

Bayesian (NMESE) weight = 0.456

Composite Distribution

Figure 7.4.2-10 

Mmax distributions for the MidC-D seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-133 

NAP

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 7.4.2-11

Mmax distributions for the NAP seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-134

OKA

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (NMESE) weight = 0.6

Composite Distribution

Figure 7.4.2-12

Mmax distributions for the OKA seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-135 

PEZ-N

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.12

Bayesian (NMESE) weight = 0.48

Composite Distribution

Figure 7.4.2-13

Mmax distributions for the PEZ_N seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-136

PEZ-W

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.01

Bayesian (COMP) weight = 0.396

Bayesian (MESE) weight = 0.119

Bayesian (NMESE) weight = 0.475

Composite Distribution

Figure 7.4.2-14

Mmax distributions for the PEZ_W seismotectonic zone
Chapter 7 

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7-137 

RR

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Bayesian (COMP) weight = 0.4

Bayesian (MESE) weight = 0.6

Composite Distribution

Figure 7.4.2-15

Mmax distributions for the RR seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-138

RR-RCG

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.07

Bayesian (COMP) weight = 0.372

Bayesian (MESE) weight = 0.558

Composite Distribution

Figure 7.4.2-16

Mmax distributions for the RR_RCG seismotectonic zone 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-139 

SLR

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

Maximum Magnitude Probability Weight

Kijko weight = 0.02

Bayesian (COMP) weight = 0.392

Bayesian (MESE) weight = 0.588

Composite Distribution

Figure 7.4.2-17

Mmax distributions for the SLR seismotectonic zone
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-140

Figure 7.5.1-1 

Mean map of rate and b-value for the study region under the source-zone configuration with narrow interpretation of PEZ, Rough 

Creek graben associated with Midcontinent; Case A magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-141 

Figure 7.5.1-2 

Mean map of rate and b-value for the study region under the source-zone configuration with narrow interpretation of PEZ, Rough 

Creek graben associated with Midcontinent; Case B magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-142

Figure 7.5.1-3 

Mean map of rate and b-value for the study region under the source-zone configuration with narrow interpretation of PEZ, Rough 

Creek graben associated with Midcontinent; Case E magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-143 

Figure 7.5.1-4 

Mean map of rate and b-value for the study region under the source-zone configuration with narrow interpretation of PEZ, Rough 

Creek graben associated with Reelfoot rift; Case A magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-144

Figure 7.5.1-5 

Mean map of rate and b-value for the study region under the source-zone configuration with narrow interpretation of PEZ, Rough 

Creek graben associated with Reelfoot rift; Case B magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-145 

Figure 7.5.1-6 

Mean map of rate and b-value for the study region under the source-zone configuration with narrow interpretation of PEZ, Rough 

Creek graben associated with Reelfoot rift; Case E magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-146

Figure 7.5.1-7 

Mean map of rate and b-value for the study region under the source-zone configuration with wide interpretation of PEZ, Rough 

Creek graben associated with Midcontinent; Case A magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-147 

Figure 7.5.1-8 

Mean map of rate and b-value for the study region under the source-zone configuration with wide interpretation of PEZ, Rough 

Creek graben associated with Midcontinent; Case B magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-148

Figure 7.5.1-9 

Mean map of rate and b-value for the study region under the source-zone configuration with wide interpretation of PEZ, Rough 

Creek graben associated with Midcontinent; Case E magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-149 

Figure 7.5.1-10

Mean map of rate and b-value for the study region under the source-zone configuration with wide interpretation of PEZ, Rough 

Creek graben associated with Reelfoot rift; Case A magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-150

Figure 7.5.1-11

Mean map of rate and b-value for the study region under the source-zone configuration with wide interpretation of PEZ, Rough 

Creek graben associated with Reelfoot rift; Case B magnitude weights 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-151 

Figure 7.5.1-12

Mean map of rate and b-value for the study region under the source-zone configuration with wide interpretation of PEZ, Rough 

Creek graben associated with Reelfoot rift; Case E magnitude weights
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-152

Figure 7.5.2-1 

Comparison of model-predicted earthquake counts for AHEX using Case A magnitude weights. No earthquake counts are shown 

because this source zone contains no seismicity. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-153 

Figure 7.5.2-2 

Comparison of model-predicted earthquake counts for AHEX using Case B magnitude weights. No earthquake counts are shown 

because this source zone contains no seismicity. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-154

Figure 7.5.2-3 

Comparison of model-predicted earthquake counts for AHEX using Case E magnitude weights. No earthquake counts are shown 

because this source zone contains no seismicity.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-155 

Figure 7.5.2-4 

Comparison of model-predicted earthquake counts for ECC_AM using Case A magnitude weights. The error bars represent the 

16%–84% uncertainty associated with the data, computed using the Weichert (1980) procedure. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-156

Figure 7.5.2-5 

Comparison of model-predicted earthquake counts for ECC_AM using Case B magnitude weights. Error bars as in Figure 

7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-157 

Figure 7.5.2-6 

Comparison of model-predicted earthquake counts for ECC_AM using Case E magnitude weights. Error bars as in Figure 

7.5.2-4.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-158

Figure 7.5.2-7 

Comparison of model-predicted earthquake counts for ECC_GC using Case A magnitude weights. Error bars as in Figure 

7.5.2-4.
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-159 

Figure 7.5.2-8 

Comparison of model-predicted earthquake counts for ECC_GC using Case B magnitude weights. Error bars as in Figure 

7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-160

Figure 7.5.2-9 

Comparison of model-predicted earthquake counts for ECC_GC using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-161 

Figure 7.5.2-10

Comparison of model-predicted earthquake counts for GHEX using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-162

Figure 7.5.2-11

Comparison of model-predicted earthquake counts for GHEX using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-163 

Figure 7.5.2-12

Comparison of model-predicted earthquake counts for GHEX using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-164

Figure 7.5.2-13

Comparison of model-predicted earthquake counts for GMH using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-165 

Figure 7.5.2-14

Comparison of model-predicted earthquake counts for GMH using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-166

Figure 7.5.2-15

Comparison of model-predicted earthquake counts for GMH using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-167 

Figure 7.5.2-16

Comparison of model-predicted earthquake counts for IBEB using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-168

Figure 7.5.2-17

Comparison of model-predicted earthquake counts for IBEB using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-169 

Figure 7.5.2-18

Comparison of model-predicted earthquake counts for IBEB using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-170

Figure 7.5.2-19

Comparison of model-predicted earthquake counts for MidC-A using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-171 

Figure 7.5.2-20

Comparison of model-predicted earthquake counts for MidC-A using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-172

Figure 7.5.2-21

Comparison of model-predicted earthquake counts for MidC-A using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-173 

Figure 7.5.2-22

Comparison of model-predicted earthquake counts for MidC–B using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-174

Figure 7.5.2-23

Comparison of model-predicted earthquake counts for MidC-B using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-175 

Figure 7.5.2-24

Comparison of model-predicted earthquake counts for MidC–B using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-176

Figure 7.5.2-25

Comparison of model-predicted earthquake counts for MidC–C using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-177 

Figure 7.5.2-26

Comparison of model-predicted earthquake counts for MidC–C using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-178

Figure 7.5.2-27

Comparison of model-predicted earthquake counts for MidC–C using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-179 

Figure 7.5.2-28

Comparison of model-predicted earthquake counts for MidC–D using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-180

Figure 7.5.2-29

Comparison of model-predicted earthquake counts for MidC–D using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-181 

Figure 7.5.2-30

Comparison of model-predicted earthquake counts for MidC–D using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-182

Figure 7.5.2-31

Comparison of model-predicted earthquake counts for NAP using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-183 

Figure 7.5.2-32

Comparison of model-predicted earthquake counts for NAP using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-184

Figure 7.5.2-33

Comparison of model-predicted earthquake counts for NAP using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-185 

Figure 7.5.2-34

Comparison of model-predicted earthquake counts for OKA using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-186

Figure 7.5.2-35

Comparison of model-predicted earthquake counts for OKA using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-187 

Figure 7.5.2-36

Comparison of model-predicted earthquake counts for OKA using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-188

Figure 7.5.2-37

Comparison of model-predicted earthquake counts for PEZ_N using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-189 

Figure 7.5.2-38

Comparison of model-predicted earthquake counts for PEZ_N using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-190

Figure 7.5.2-39

Comparison of model-predicted earthquake counts for PEZ_N using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-191 

Figure 7.5.2-40

Comparison of model-predicted earthquake counts for PEZ_W using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-192

Figure 7.5.2-41

Comparison of model-predicted earthquake counts for PEZ_W using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-193 

Figure 7.5.2-42

Comparison of model-predicted earthquake counts for PEZ_W using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-194

Figure 7.5.2-43

Comparison of model-predicted earthquake counts for RR using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-195 

Figure 7.5.2-44

Comparison of model-predicted earthquake counts for RR using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-196

Figure 7.5.2-45

Comparison of model-predicted earthquake counts for RR using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-197 

Figure 7.5.2-46

Comparison of model-predicted earthquake counts for RR_RCG using Case A magnitude weights. Error bars as in Figure 

7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-198

Figure 7.5.2-47

Comparison of model-predicted earthquake counts for RR_RCG using Case B magnitude weights. Error bars as in Figure 

7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-199 

Figure 7.5.2-48

Comparison of model-predicted earthquake counts for RR_RCG using Case E magnitude weights. Error bars as in Figure 

7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-200

Figure 7.5.2-49

Comparison of model-predicted earthquake counts for SLR using Case A magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-201 

Figure 7.5.2-50

Comparison of model-predicted earthquake counts for SLR using Case B magnitude weights. Error bars as in Figure 7.5.2-4. 
Chapter 7 

SSC Model: Seismotectonic Zones Branch 

7-202

Figure 7.5.2-51

Comparison of model-predicted earthquake counts for SLR using Case E magnitude weights. Error bars as in Figure 7.5.2-4. 
BIBLIOGRAPHIC DATA SHEET

(See instructions on the reverse)

NRC FORM 335

(12-2010)

NRCMD 3.7

U.S. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER

 (Assigned by NRC, Add Vol., Supp., Rev.,

 and Addendum Numbers, if any.)

NUREG-2115

Vol. 2

3. DATE REPORT PUBLISHED

MONTH

January

YEAR

2012

4. FIN OR GRANT NUMBER

K6877

2. TITLE AND SUBTITLE

Central and Eastern United States Seismic Source Characterization for Nuclear Facilities

Volume 2: Chapters 5 to 7

5. AUTHOR(S)

G. Stirewalt (NRC), L. Salomone (Savannah River Nuclear Solutions, LLC), S. McDuffie (DOE),

K. Coppersmith (Coppersmith Consulting, Inc), Fugro William Lettis & Associates, Inc.: C. Fuller,

R. Hartleb, W. Lettis, S. Lindvall, R. McGuire, G. Toro, D. Slayter, R. Cumbest, A. Shumway, F.

Syms, AMEC Geomatrix, Inc: L. Glaser, K. Hanson, R. Youngs, S. Bozkurt, V. Montaldo Falero,

R. Perman, R. McGuire (Risk Engineering), M. Tuttle (M. Tuttle & Associates)

6. TYPE OF REPORT

Technical

7. PERIOD COVERED (Inclusive Dates)

8. PERFORMING ORGANIZATION - NAME AND ADDRESS (If NRC, provide Division, Office or Region, U.S. Nuclear Regulatory Commission, and mailing address; if contractor,

U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Washington DC 20555

9. SPONSORING ORGANIZATION - NAME AND ADDRESS (If NRC, type "Same as above"; if contractor, provide NRC Division, Office or Region, U.S. Nuclear Regulatory Commission, 

U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Washington DC 20555

provide name and mailing address.)

and mailing address.)

10. SUPPLEMENTARY NOTES

11. ABSTRACT (200 words or less)

This report describes a new seismic source characterization (SSC) model for the Central and Eastern United States (CEUS). It

will replace the Seismic Hazard Methodology for the Central and Eastern United States, EPRI Report NP-4726 (July 1986) and

the Seismic Hazard Characterization of 69 Nuclear Plant Sites East of the Rocky Mountains, Lawrence Livermore National

Laboratory Model, (Bernreuter et al., 1989). The objective of the CEUS SSC Project is to develop a new seismic source model

for the CEUS using a Senior Seismic Hazard Analysis Committee (SSHAC) Level 3 assessment process. The goal of the

SSHAC process is to represent the center, body, and range of technically defensible interpretations of the available data,

models, and methods. Input to a probabilistic seismic hazard analysis (PSHA) consists of both seismic source characterization

and ground motion characterization. These two components are used to calculate probabilistic hazard results (or seismic hazard

curves) at a particular site. This report provides a new seismic source model.

12. KEY WORDS/DESCRIPTORS (List words or phrases that will assist researchers in locating the report.)

Probabilistic seismic hazard analysis (PSHA)

Seismic source characterization (SSC)

Seismic source characterization model

Central and Eastern United States (CEUS)

14. SECURITY CLASSIFICATION

13. AVAILABILITY STATEMENT

unlimited

(This Page)

unclassified

(This Report)

unclassified

15. NUMBER OF PAGES

16. PRICE

NRC FORM 335 (12-2010)

U.S. Department of Energy, 1000 Independence Avenue SW, Washington DC 20585

Electric Power Research Institute, 3420 Hillview Avenue, Palo Alto, CA 94304

U.S. Department of Energy, 1000 Independence Avenue SW, Washington DC 20585

Electric Power Research Institute, 3420 Hillview Avenue, Palo Alto, CA 94304