U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2017–5013–I–Q

The HayWired Earthquake Scenario—Engineering Implications
Cover. This oblique aerial photograph captures a moment during which San Francisco, California, firefighters are extinguishing a fire 

that occurred shortly after an apartment building collapsed and burned to the ground as a result of the moment-magnitude-6.9 Loma Prieta 

earthquake of 1989. Another apartment building across the street has fallen into the intersection of Beach and Divisadero Streets, bursting out 

the walls of the weak first story as the structure buckled and collapsed. The damage (building collapses, damage to gas pipelines and other 

utilities, and fire) in the city’s Marina District shown here was caused by amplified ground shaking and liquefaction (soils becoming liquid-like 

during shaking).

 Since 1989, these and five other collapsed buildings in San Francisco’s Marina District have been replaced or rebuilt, other buildings’ 

soft first stories have been braced and strengthened, and flexible-conduit gas lines have replaced old, brittle rigid gas lines throughout the 

neighborhood. Such risk-reduction measures, intended to prevent building collapse and to curtail fire following earthquake, have not yet 

been taken in many other areas surrounding San Francisco Bay that have been identified as being susceptible to liquefaction. (Photograph 

copyright Deanne Fitzmaurice/San Francisco Chronicle/Polaris, used with permission.)
The HayWired Earthquake Scenario—

Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

RYAN K. ZINKE, Secretary

U.S. Geological Survey

William H. Werkheiser, Deputy Director 

 exercising the authority of the Director

U.S. Geological Survey, Reston, Virginia: 2018

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

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visit https://store.usgs.gov.

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U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Detweiler, S.T., and Wein, A.M., eds., 2018, The HayWired earthquake scenario—Engineering implications: U.S. Geological 

Survey Scientific Investigations Report 2017–5013–I–Q, 429 p., https://doi.org/10.3133/sir20175013v2.

ISSN 2328-0328 (online)
iii

The 1906 Great San Francisco earthquake (magnitude 7.8) and the 1989 Loma Prieta earthquake (magnitude 6.9) each 

motivated residents of the San Francisco Bay region to build countermeasures to earthquakes into the fabric of the region. 

Since Loma Prieta, bay-region communities, governments, and utilities have invested tens of billions of dollars in seismic 

upgrades and retrofits and replacements of older buildings and infrastructure. Innovation and state-of-the-art engineering, 

informed by science, including novel seismic-hazard assessments, have been applied to the challenge of increasing 

seismic resilience throughout the bay region. However, as long as people live and work in seismically vulnerable buildings 

or rely on seismically vulnerable transportation and utilities, more work remains to be done. 

With that in mind, the U.S. Geological Survey (USGS) and its partners developed the HayWired scenario as a tool to 

enable further actions that can change the outcome when the next major earthquake strikes. By illuminating the likely 

impacts to the present-day built environment, well-constructed scenarios can and have spurred officials and citizens 

to take steps that change the outcomes the scenario describes, whether used to guide more realistic response and 

recovery exercises or to launch mitigation measures that will reduce future risk.

The HayWired scenario is the latest in a series of like-minded efforts to bring a special focus onto potential impacts when the 

Hayward Fault again ruptures through the east side of the San Francisco Bay region as it last did in 1868. Cities in the east bay 

along the Richmond, Oakland, and Fremont corridor would be hit hardest by earthquake ground shaking, surface fault rupture, 

aftershocks, and fault afterslip, but the impacts would reach throughout the bay region and far beyond. The HayWired scenario 

name reflects our increased reliance on the Internet and telecommunications and also alludes to the interconnectedness 

of infrastructure, society, and our economy. How would this earthquake scenario, striking close to Silicon Valley, impact our 

interconnected world in ways and at a scale we have not experienced in any previous domestic earthquake?

The area of present-day Contra Costa, Alameda, and Santa Clara Counties contended with a magnitude-6.8 earthquake in 

1868 on the Hayward Fault. Although sparsely populated then, about 30 people were killed and extensive property damage 

resulted. The question of what an earthquake like that would do today has been examined before and is now revisited in the 

HayWired scenario. Scientists have documented a series of prehistoric earthquakes on the Hayward Fault and are confident 

that the threat of a future earthquake, like that modeled in the HayWired scenario, is real and could happen at any time. The 

team assembled to build this scenario has brought innovative new approaches to examining the natural hazards, impacts, 

and consequences of such an event. Such an earthquake would also be accompanied by widespread liquefaction and 

landslides, which are treated in greater detail than ever before. The team also considers how the now prototype ShakeAlert 

earthquake early warning system could provide useful public alerts and automatic actions.

Scientific Investigations Report 2017–5013 and accompanying data releases are the products of an effort led by the USGS, 

but this body of work was created through the combined efforts of a large team including partners who have come together 

to form the HayWired Coalition (see chapter A). Use of the HayWired scenario has already begun. More than a full year of 

intensive partner engagement, beginning in April 2017, is being directed toward producing the most in-depth look ever at 

the impacts and consequences of a large earthquake on the Hayward Fault. With the HayWired scenario, our hope is to 

encourage and support the active ongoing engagement of the entire community of the San Francisco Bay region by providing 

the scientific, engineering, and economic and social science inputs for use in exercises and planning well into the future.

David Applegate

Associate Director for Natural Hazards, 

 exercising the authority of the Deputy Director

U.S. Geological Survey

Foreword

v

HayWired Review Panel

The HayWired Review Panel, a group whose expertise spans the scope of the HayWired 

scenario, assessed the overarching goals of the project along with the scientific approach and 

oversaw the reviews of each individual chapter in this volume. The panel consisted of Jack 

Boatwright (U.S. Geological Survey, USGS), Arrietta Chakos (Urban Resilience Strategies), 

Mary Comerio (University of California, Berkeley), Douglas Dreger (University of California, 

Berkeley), Erol Kalkan (USGS), Roberts McMullin (East Bay Municipal Utility District), 

Andrew Michael (chair, USGS), David Schwartz (USGS), and Mary Lou Zoback (Build 

Change, Stanford University).

HayWired Coalition Partners

Alameda County Mayors’ Conference

Alameda County Sheriff’s Office, Office of Emergency Services

American Red Cross

Art Center College of Design

ARUP—Design and Engineering Consultants

Association of Bay Area Governments—Metropolitan 

 Transportation Commission

Aurecon

Bay Area Center for Regional Disaster Resilience

Bay Area Council

Bay Area Rapid Transit Authority

Bay Area Urban Area Security Initiative

Bay Planning Coalition

Boston University

Business Recovery Managers Association

California Business, Consumer Services, and Housing Agency

California Department of Public Health

California Department of Transportation

California Earthquake Authority

California Earthquake Clearinghouse

California Geological Survey

California Governor’s Office of Business and 

 Economic Development

California Governor’s Office of Emergency Services

California Independent Oil Marketers Association

California ISO

California Public Utilities Commission

California Resiliency Alliance

California Seismic Safety Commission

Carnegie Melon University Silicon Valley

City and County of San Francisco

City of Berkeley

City of Fremont

City of Hayward

City of Oakland

City of Oakland, Fire Department

City of San Francisco, Department of Emergency 

 Management

City of Walnut Creek

Contra Costa County Mayors’ Conference

Earthquake Country Alliance

Earthquake Engineering Research Institute

East Bay Municipal Utility District 

Federal Emergency Management Agency 

Joint Venture Silicon Valley 

Laurie Johnson Consulting|Research 

March Studios 

Marin Economic Consulting 

MMI Engineering 

Office of the Mayor, City and County of San Francisco 

Pacific Earthquake Engineering Research Center 

Pacific Gas and Electric 

Palo Alto University 

Price School of Public Policy and Center for Risk and 

 Economic Analysis of Terrorism Events, University of 

 Southern California

Rockefeller Foundation—100 Resilient Cities 

San Jose Water Company 

Southern California Earthquake Center 

SPA Risk LLC 

SPUR 

Strategic Economics 

Structural Engineers Association of Northern California 

The Brashear Group LLC 

University of California Berkeley Seismological Laboratory

University of Colorado Boulder 

University of Southern California

U.S. Department of Homeland Security 

U.S. Geological Survey 

Wells Fargo

vii

Contents

Foreword ........................................................................................................................................................iii

 By David Applegate

HayWired Review Panel...............................................................................................................................v

HayWired Coalition Partners .......................................................................................................................v

Chapters

I. Overview of the HayWired Scenario Engineering-Implications Volume .......................................1

By Keith A. Porter

Introduction............................................................................................................................................1

A Recap of Earthquake Hazards ........................................................................................................2

Engineering Implications.....................................................................................................................2

Hazus-MH Analysis .....................................................................................................................2

Societal Consequences of Current Code Performance Objectives ....................................3

A Survey of Public Preferences for the Seismic Performance of New Buildings............5

Earthquake Urban Search and Rescue....................................................................................5

Water-Network Resilience.........................................................................................................6

Repair Costs and Downtime of High-Rise Buildings..............................................................7

Fire Following Earthquake..........................................................................................................8

Benefit of Combining Earthquake Early Warning with Drop, Cover, and Hold On ............9

Future Research.........................................................................................................................10

Conclusion............................................................................................................................................10

References Cited.................................................................................................................................11

J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks ...............................13

By Hope A. Seligson, Anne M. Wein, and Jamie L. Jones 

Abstract................................................................................................................................................13

Introduction..........................................................................................................................................14

Building Inventory Data .....................................................................................................................14

Hazus Results—HayWired Mainshock...........................................................................................18

HayWired Liquefaction Implementation in Hazus................................................................18

HayWired Landslide implementation in Hazus .....................................................................19

HayWired Mainshock Hazus Results .....................................................................................22

Liquefaction Modeling in Selected HayWired Aftershocks ........................................................27

Ground Shaking Results for the HayWired Earthquake Sequence............................................27

Unreinforced Masonry Construction...............................................................................................30

Population Impacts—Casualties .....................................................................................................38

Population Impacts—Displacement and Shelter Requirements................................................38

Combining Losses in the Mainshock and Aftershocks ................................................................41

Repeat Liquefaction ...........................................................................................................................43

Model Limitations and Data Gaps....................................................................................................46

Conclusions..........................................................................................................................................49
viii

Mainshock Assessment ...........................................................................................................49

Aftershock Assessment............................................................................................................49

Acknowledgments..............................................................................................................................50

References Cited.................................................................................................................................51

Appendix. Calculation of Shelter Parameters for the 2008 Southern California ShakeOut 

Scenario ..................................................................................................................................52

 By Kimberley Shoaf

Displacement ..............................................................................................................................52

Shelter Needs.............................................................................................................................53

Other Parameters to Consider .................................................................................................53

References Cited .......................................................................................................................54

K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes ....57

By Keith A. Porter

Abstract................................................................................................................................................57

Introduction..........................................................................................................................................57

Background..........................................................................................................................................58

Implications of Seismic Performance Objectives for the HayWired Scenario ........................60

Impairment Rate at MCER Shaking...................................................................................................61

Validation Using Data from the August 2014 Napa Earthquake..................................................63

Impairment Rate at Other Levels of Shaking..................................................................................63

Fraction and Number of Impaired Buildings at the Societal Level.............................................66

Options for Improving Building-Stock Performance.....................................................................66

Building Impairment Resulting from Ground Failure.....................................................................69

Public Expectations for the Seismic Performance of New Buildings .......................................70

Limitations of this Study.....................................................................................................................72

Summary...............................................................................................................................................72

Conclusion............................................................................................................................................73

References Cited.................................................................................................................................73

L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New

Buildings in California and the New Madrid Seismic Zone ....................................................79

By Keith A. Porter

Abstract................................................................................................................................................79

Introduction..........................................................................................................................................80

Objectives....................................................................................................................................81

Survey Approach .......................................................................................................................82

Respondent Population and Sampling Procedure ...............................................................83

Survey Questions and Responses ...................................................................................................83

Response Rate ...........................................................................................................................83

Role or Relation to Building Codes .........................................................................................84

Current and Preferred Code Objectives.................................................................................84

Preferred Performance Measure ..........................................................................................86

Acceptable Cost for Better Performance..............................................................................87

How Important are These Issues?..........................................................................................88

Respondent Demographics......................................................................................................88

Are Respondents Representative of the Population?...................................................................91

Are Some Groups Willing to Pay More for Better Seismic Performance? ...............................93
ix

Conclusions..........................................................................................................................................94

Study Implications .....................................................................................................................94

Limitations and Research Needs ............................................................................................95

Acknowledgments..............................................................................................................................95

References Cited.................................................................................................................................95

M. An Earthquake Urban Search and Rescue Model and its Application to the HayWired Scenario..99

By Keith A. Porter

Abstract................................................................................................................................................99

Introduction..........................................................................................................................................99

Objective.............................................................................................................................................100

Literature Review..............................................................................................................................100

Literature About People Trapped by Building Collapse.....................................................100

Literature About People Trapped in Elevators ....................................................................103

Methodology......................................................................................................................................103

Methodology for Estimating the Number of People Trapped by Collapse .....................103

Methodology for Estimating the Number of People Trapped in Elevators.....................111

Application to HayWired Scenario ................................................................................................111

People Trapped in Collapsed Buildings, Based on the Building-Code Objectives .......111

People Trapped in Collapsed Buildings, Based on Hazus-MH.........................................112

Scenario Estimate of People Trapped in Collapsed Buildings .........................................116

Number of People Trapped in Stalled Elevators.................................................................116

Conclusions........................................................................................................................................117

USAR Demands Under Current Conditions .........................................................................117

USAR Demands Under Ideal-World Conditions..................................................................118

Limitations..........................................................................................................................................118

Acknowledgments............................................................................................................................118

References Cited...............................................................................................................................118

Appendixes 1 through 12—National Information Service for Earthquake Engineering 

e-Library Images of Building Collapse in California, 1965–2014..................................120

Appendix 1. Santa Rosa (1969) Collapse Images................................................................120

Appendix 2. San Fernando (1971) Collapse Images ...........................................................122

Appendix 3. Imperial Valley (1979) Collapse Images..........................................................141

Appendix 4. Westmorland (1981) Collapse Images ............................................................143

Appendix 5. Coalinga (1983) Collapse Images ....................................................................144

Appendix 6. Morgan Hill (1984) Collapse Images ...............................................................152

Appendix 7. Whittier Narrows (1987) Collapse Images.....................................................154

Appendix 8. Loma Prieta (1989) Collapse Images...............................................................159

Appendix 9. Northridge (1994) Collapse Images.................................................................173

Appendix 10. San Simeon (2003) Collapse Images.............................................................189

Appendix 11. South Napa (2014) Collapse Images.............................................................191

Appendix 12. Earthquakes With No Available Collapse Images......................................192

N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario...195

By Keith A. Porter

Abstract..............................................................................................................................................195

Introduction........................................................................................................................................195

How Water Supply is Important in an Earthquake.............................................................195
x

Study Objectives ......................................................................................................................196

Literature Review..............................................................................................................................197

A Panel Approach to Estimating Water-Supply Impacts ..................................................197

Analytical Approaches to Estimating Water Supply Impacts ..........................................197

Damageability of Buried Pipe ................................................................................................198

Tasks and Methods to Repair Leaks and Breaks ...............................................................202

Time to Repair Pipe Leaks and Breaks.................................................................................202

Serviceability of Water Supply ..............................................................................................205

Lifeline Interaction...................................................................................................................206

Pipeline Damage in Afterslip .................................................................................................210

Measuring Loss of Resilience ...............................................................................................211

Methodology......................................................................................................................................211

Overview of the Methodology ...............................................................................................211

Vulnerability Model..................................................................................................................212

Damage Analysis (Number of Repairs Required)...............................................................214

Restoration Model ...................................................................................................................215

Measuring Water-Supply Resilience....................................................................................223

Optional Stochastic Simulation Methodology ....................................................................223

Accounting for Afterslip and Aftershocks...........................................................................225

Adjusting Hazus-MH’s Lifeline Restoration Model.............................................................226

Mitigation Options ...................................................................................................................227

Summary of the Methodology ...............................................................................................228

Case Study 1—San Jose Water Company ...................................................................................228

San Jose Water Company Asset Definition ........................................................................229

San Jose Water Company Hazard Analysis........................................................................229

San Jose Water Company Damage Analysis......................................................................230

San Jose Water Company Restoration Analysis................................................................236

Validation of San Jose Water Company Restoration Analysis ........................................240

Effect of Lifeline Interaction and Consumable Limits ........................................................242

Case Study 2—East Bay Municipal Utility District......................................................................242

East Bay Municipal Utility District Asset Definition...........................................................242

EBMUD Hazard Analysis ........................................................................................................244

EBMUD Damage Analysis......................................................................................................245

EBMUD Restoration Analysis ................................................................................................251

Validation of EBMUD Damage and Recovery Estimates...................................................254

Effect of Lifeline Interaction and Consumable Limits on EBMUD ...................................255

Performance of Other Water Utilities Based on Hazus-MH......................................................255

Conclusions........................................................................................................................................258

Summary....................................................................................................................................258

Innovations Introduced Here.................................................................................................258

Research Needs ......................................................................................................................260

Acknowledgments............................................................................................................................260

References Cited...............................................................................................................................260
xi

O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for 

the HayWired Earthquake Scenario Mainshock ....................................................................267

 By Ibrahim M. Almuti, Carlos Molina-Hutt, Michael W. Mieler, Nicole A. Paul, and 

 Chad R. Fusco

Abstract..............................................................................................................................................267

Introduction........................................................................................................................................268

Objectives..................................................................................................................................268

Report Structure ......................................................................................................................268

HayWired Ground Motions .............................................................................................................269

Description of Archetype Buildings, Design, and Analysis Assumptions...............................272

Steel Office Tower ...................................................................................................................272

Reinforced-Concrete Residential Tower..............................................................................276

Loss-Assessment Methodology.....................................................................................................278

REDi Downtime Methodology................................................................................................278

Input Parameters .....................................................................................................................280

Replacement Value..................................................................................................................280

Utility Disruption.......................................................................................................................281

Summary of Loss-Assessment Results.........................................................................................281

Conclusion..........................................................................................................................................283

Acknowledgments............................................................................................................................283

References Cited...............................................................................................................................284

Appendix 1. Building Structural and Nonstructural Components ...........................................285

Structural Components...........................................................................................................286

Nonstructural Components....................................................................................................291

Appendix 2. S-SF-B-43—40-Story Steel-Frame Building in San Francisco (Baseline 

Orientation)...........................................................................................................................312

S-SF-B-43 Description ............................................................................................................312

Engineering-Demand Parameters ........................................................................................312

Loss-Assessment Results ......................................................................................................312

Appendix 3. S-SF-R-43—40-Story Steel-Frame Building in San Francisco (Rotated 

Orientation)...........................................................................................................................316

S-SF-R-43 Description.............................................................................................................316

Engineering-Demand Parameters ........................................................................................316

Loss-Assessment Results ......................................................................................................316

Appendix 4. S-SF-B-20—20-Story Steel-Frame Building in San Francisco (Baseline 

Orientation)...........................................................................................................................320

S-SF-B-20 Description ............................................................................................................320

Engineering-Demand Parameters ........................................................................................320

Loss-Assessment Results ......................................................................................................320

Appendix 5. S-SF-R-20—20-Story Steel-Frame Building in San Francisco (Rotated 

Orientation)...........................................................................................................................324

S-SF-R-20 Description.............................................................................................................324

Engineering-Demand Parameters ........................................................................................324

Loss-Assessment Results ......................................................................................................324
xii

Appendix 6. S-OK-B-20—20-Story Steel-Frame Building in Oakland 

(Baseline Orientation).........................................................................................................328

S-OK-B-20 Description............................................................................................................328

Engineering-Demand Parameters ........................................................................................328

Loss Assessment Results.......................................................................................................328

Appendix 7. S-OK-R-20—20-Story Steel-Frame Building in Oakland 

(Rotated Orientation) ..........................................................................................................332

S-OK-R-20 Description............................................................................................................332

Engineering-Demand Parameters ........................................................................................332

Loss-Assessment Results ......................................................................................................332

Appendix 8. C-SF-B-46—42-Story Reinforced-Concrete Building in San Francisco (Baseline 

Orientation)...........................................................................................................................336

C-SF-B-46 Description ............................................................................................................336

Engineering-Demand Parameters ........................................................................................336

Loss-Assessment Results ......................................................................................................339

Appendix 9. C-SF-R-46—42-Story Reinforced-Concrete Building in San Francisco (Rotated 

Orientation)...........................................................................................................................342

C-SF-R-46 Description.............................................................................................................342

Engineering-Demand Parameters ........................................................................................342

Loss-Assessment Results ......................................................................................................345

Appendix 10. C-OK-B-46—42-Story Reinforced-Concrete Building in Oakland (Baseline 

Orientation)...........................................................................................................................348

C-OK-B-46 Description............................................................................................................348

Engineering-Demand Parameters ........................................................................................348

Loss-Assessment Results ......................................................................................................351

Appendix 11. C-OK-R-46—42-Story Reinforced-Concrete Building in Oakland (Rotated 

Orientation)...........................................................................................................................354

C-OK-R-46 Description............................................................................................................354

Engineering-Demand Parameters ........................................................................................354

Loss-Assessment Results ......................................................................................................357

Appendix 12. Inventory of Existing Tall-Building Stock in San Francisco ..............................360

P. Fire Following the HayWired Scenario Mainshock........................................................................367

By Charles Scawthorn

Abstract..............................................................................................................................................367

Introduction........................................................................................................................................367

Purpose......................................................................................................................................368

Background...............................................................................................................................368

Scenario Earthquake and Prevailing Conditions.........................................................................368

Rupture Segment, Magnitude, and Intensity ......................................................................369

Affected Region .......................................................................................................................369

Fire Following Earthquake Aspects of the Scenario...................................................................379

Modeling of Fire Following Earthquake ...............................................................................379

Ignitions.....................................................................................................................................380

Initial Response........................................................................................................................381

Fire Spread................................................................................................................................384

Lifelines......................................................................................................................................384
xiii

Regional and State Response................................................................................................390

Final Burned Area....................................................................................................................391

Uncertainty, Verification, and Validation .............................................................................393

Impacts of Fire Following Earthquake...........................................................................................394

Human Impacts ........................................................................................................................395

Economic and Insurance Impacts ........................................................................................395

Mitigation of Fire Following Earthquake .......................................................................................395

Fire-Service Opportunities .....................................................................................................395

Water-Service Opportunities.................................................................................................396

Building-Standards Opportunities ........................................................................................396

Energy-Industry Opportunities ..............................................................................................396

Conclusion..........................................................................................................................................397

References Cited...............................................................................................................................397

Q. How Many Injuries Can Be Avoided in the HayWired Scenario Through Earthquake Early

Warning and Drop, Cover, and Hold On?..................................................................................401

 By Keith A. Porter and Jamie L. Jones

Abstract..............................................................................................................................................401

Introduction........................................................................................................................................401

Background...............................................................................................................................401

Objectives..................................................................................................................................402

Literature Review..............................................................................................................................402

Methodology......................................................................................................................................403

Estimating Avoided Injuries....................................................................................................403

Estimating the Acceptable Cost to Avoid Injuries ..............................................................404

Survey Design...........................................................................................................................404

Findings...............................................................................................................................................404

Distribution of DCHO Reaction Time.....................................................................................404

Calculation of Benefits............................................................................................................406

Conclusions........................................................................................................................................406

Limitations and Research Needs ...................................................................................................410

References Cited...............................................................................................................................410

Appendix 1. Survey of DCHO Reaction Times .............................................................................412

Appendix 2. HayWired Mainshock Earthquake Early Warning Time Calculation.................427

By Elizabeth S. Cochran, Anne M. Wein, Erin R. Burkett, Douglas D. Given, and 

Keith Porter

References Cited .....................................................................................................................428
xiv

Conversion Factors

U.S. customary units to International System of Units

International System of Units to U.S. customary units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.004047 square kilometer (km2)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L)

Pressure

pound per square inch (lb/in2) 6.895 kilopascal (kPa)

kilopounds per square inch (lb/in2) 6.895 megapascal (MPa)

Cohesion

pound per square foot (lb/ft2) 0.04788 kilopascal (kPa)

Velocity

mile per hr (mi/hr) 1.60934 kilometer per hour (km/hr)

Angle

degree (°) 0.0174533 radian (rad)

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 0.0002471 acre

hectare (ha) 2.471 acre

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2)

square kilometer (km2) 0.3861 square mile (mi2)

Volume

liter (L) 0.2642 gallon (gal)

Pressure

kilopascal (kPa) 0.1450377 pound per square inch (lb/in2)

megapascal (MPa) 0.1450377 kilopounds per square inch (lb/in2)
xv

Multiply By To obtain

Velocity

centimeter per second (cm/s) 0.3937 inch per second (in./s)

centimeter per second (cm/s) 0.0223694 mile per hour (mi/hr)

meter per second (m/s) 3.281 foot per second (ft/s)

meter per second (m/s) 2.23694 mile per hour (mi/hr)

kilometer per hour (km/hr) 0.621371 mile per hour (mi/hr)

Angle

radian (rad) 57.2958 degree (°)

Datum

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Abbreviations and Acronyms

1D one dimensional

2D two dimensional

3D three dimensional

ABAG Association of Bay Area Governments

AIS abbreviated injury scale

ASCE American Society of Civil Engineers

ATC Applied Technology Council

BAREPP Bay Area Regional Earthquake Preparedness Project

BART Bay Area Rapid Transit

BORP Building Occupancy Resumption Program

BSSC Building Seismic Safety Council

Cal OES California Governor’s Office of Emergency Services

Caltrans California Department of Transportation

CalWARN California Water/Wastewater Agency Response Network

CAPSS Citizens Advisory Panel on Seismic Safety or Community Action Plan for Seismic Safety

CDC Centers for Disease Control and Prevention

CERT community emergency response team

CGS California Geological Survey

CPT cone penetration test

CUREE Consortium of Universities for Research in Earthquake Engineering
xvi

DBE design-basis earthquake

DCHO drop, cover, and hold on

DDR demand-to-design ratio

DDR1 1-second DDR

DDRS short-period DDR

DEM digital elevation model

EBMUD East Bay Municipal Utility District

EDP engineering-demand parameter

EERI Earthquake Engineering Research Institute

EEW Earthquake early warning

EQE EQE International

ESIP Earthquake Safety Improvements Program

ETAS epidemic type aftershock sequence

FA amplification factor

FEMA Federal Emergency Management Agency

Fv site coefficient

g acceleration due to gravity

GMPE ground-motion prediction equation

GMPGV geometric mean of the peak ground velocity

hr hour

IBC International Building Code

ICC International Code Council

IDR interstory drift

I

e

 seismic importance factor

IRB institution review board

LA BOMA Los Angeles Building Owners and Managers Association

LADWP Los Angeles Department of Water and Power

LLEQE Life Line Earthquake Engineering software

LPI liquefaction potential index

LRFD load- and resistance-factor design

M magnitude

Ma mega-annum or millions of years ago

MCE maximum considered earthquake

MCER risk-adjusted maximum considered earthquake

MEP mechanical, electrical, and plumbing
xvii

MMI Modified Mercalli Intensity

MRF moment-resisting frame

MSA metropolitan statistical area

Mw moment magnitude

NAD83 North American Datum of 1983

NED National Elevation Dataset

NEHRP National Earthquake Hazards Reduction Program

NGA-West2 Next Generation Attenuation Relationships for Western United States

NIBS National Institute of Building Sciences

NISEE National Information Service for Earthquake Engineering

NIST National Institute of Standards and Technology

NISTIR National Institute of Standards and Technology Interagency Reports

NLRHA nonlinear response-history analysis

NMSZ New Madrid Seismic Zone

NRC National Research Council

P probability

PACT Performance Assessment Calculation Tool

PBEE performance-based earthquake engineering

PBEE-2 second generation Performance-based earthquake engineering

PDT Pacific Daylight Time

PEER Pacific Earthquake Engineering Research Center

PG&E Pacific Gas and Electric Company

PGA peak ground acceleration

PGD permanent ground displacement

PGV peak ground velocity

PHS U.S. Public Health Service

PSA or pSa pseudo-spectral acceleration

PSA03 short-period (0.3-second) pseudo-spectral-acceleration response

PSA10 long-period (1-second) pseudo-spectral-acceleration response

PST Pacific Standard Time

PVC polyvinyl chloride

PWSS portable water-supply system

R2 coefficient of determination

REDiTM Resilience-based Earthquake Design Initiative for the Next Generation of Buildings

RIDR residual interstory drift
xviii

SA spectral acceleration

Sa spectral-acceleration response

SAFRR USGS Science Application for Risk Reduction project

SCEC Southern California Earthquake Center

SDC seismic-design categories

SEAOC Structural Engineers Association of California

SEAONC Structural Engineers Association of Northern California

SEI Structural Engineering Institute

SHZ seismic hazard zone

SIP seismic improvement programs

SJWC San Jose Water Company

SLE serviceability-level earthquakes

SM1 1-second spectral response acceleration parameter

SMS short-period spectral acceleration response parameter

SPUR San Francisco Bay Area Planning and Urban Research Association

SS short-period spectral acceleration response at MCER shaking

T period

UCERF3 Uniform California Earthquake Rupture Forecast, version 3

UPS uninterruptible power supply

URM unreinforced masonry

USAR urban search and rescue team

USD U.S. Dollars

USGS U.S. Geological Survey

VS30 time-averaged shear-wave velocity to a depth of 30 meters

WGS84 World Geodetic Survey 1984

ρ correlation coefficient

Φ standard normal cumulative distribution function


Chapter I

Overview of the HayWired Scenario EngineeringImplications Volume

By Keith A. Porter1

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013]

1

University of Colorado Boulder.

Introduction

The HayWired scenario is a hypothetical yet scientifically 

realistic depiction of an earthquake sequence that begins with a 

moment magnitude (Mw) 7.0 earthquake (mainshock) occurring 

on April 18, 2018, at 4:18 p.m. on the Hayward Fault in the 

east bay part of the San Francisco Bay area, California. The 

hypothetical mainshock has its epicenter in Oakland, and strong 

ground shaking from the scenario causes a wide range of severe 

impacts throughout the greater bay region. In the mainshock, 

the Hayward Fault is ruptured along its length for 83 kilometers 

(about 52 miles), an event significant enough to touch the lives 

of everyone who lives or works in the region.

The HayWired Earthquake Scenario—Engineering 

Implications is the second volume of U.S. Geological Survey 

(USGS) Scientific Investigations Report (SIR) 2017–5013, which 

is planned to be published as three volumes. The previous volume 

of this work (SIR 2017–5013–A–H; Detweiler and Wein, 2017) 

described a Mw 7.0 mainshock on the Hayward Fault, along with 

an aftershock sequence and other geologic hazards. This volume 

(SIR 2017–5013–I–Q) presents engineering impacts that could 

result from the effects of the HayWired scenario. Together with 

environmental, social, and economic impacts (including impacts 

to telecommunications and the internet) that are planned to be 

described in a third volume, these works describe the HayWired 

scenario, which was developed by USGS and its partners. 

The engineering-related implications of the Mw 7.0 

HayWired scenario mainshock and aftershocks for the San 

Francisco Bay region discussed in this volume are based on:

1. An analysis using the Federal Emergency Management 

Agency’s (FEMA) Hazus-MH computer program 

(Federal Emergency Management Agency, 2012a) 

that suggests 800 deaths and 16,000 nonfatal injuries 

(from the shaking hazard alone) could occur, as well as 

property and direct business interruption losses of more 

than $82 billion (for shaking, liquefaction, and landslide 

hazards).

2. A study of the societal consequences of the International 

Building Code’s seismic-performance objectives for 

new buildings. The scenario indicates that, even for 

new buildings, the code protects life well but is not 

robust enough to ensure that hundreds of thousands of 

code-compliant buildings are not red-tagged (rendered 

unsafe to enter or occupy) or yellow-tagged (safe only 

for limited use). As a consequence, even if they were all 

new, code-compliant buildings, a significant fraction of 

the San Francisco Bay region’s buildings—perhaps 1 

in 4—could have no or restricted occupancy. A moreresilient building stock is achievable for an additional 

1 to 3 percent of construction cost and could allow 

95 percent of homes and workplaces to be occupied 

following a powerful earthquake.

3. The first survey of public preferences for the tradeoff 

between cost and building resilience, showing that most 

people expect, prefer, and would be willing to pay for 

greater resilience of the building stock.

4. A new model of urban search and rescue, indicating that 

(1) more than 22,000 people in the region could require 

fire departments to free them from stalled elevators and 

(2) more than 2,400 people could require rescue from 

collapsed buildings.

5. A new, nonproprietary model of water-network resilience 

that accounts for the entire earthquake sequence, lifeline 

(for example, transportation infrastructure and buried 

utilities) interaction, resource limitations, and service restoration over time. This water-network resilience model 

shows that the average east bay resident could lose water 

service for 6 weeks (some for as long as 6 months). Two 

options to help improve these outcomes are evaluated.

6. A state-of-the-art performance-based earthquakeengineering study showing that an earthquake like 

the HayWired mainshock could cause damage 

sufficient to render older regular steel-frame high-rise 

office buildings and new regular reinforced-concrete 
2 The HayWired Earthquake Scenario—Engineering Implications

residential buildings in downtown Oakland and San 

Francisco unusable for as long as 10 months.

7. A study of fire following earthquake showing that the 

HayWired mainshock could cause about 450 large fires 

in counties nearest the fault rupture, burning buildingfloor area equivalent to that of more than 52,000 singlefamily dwellings. Such fires would kill hundreds of 

people and cause property (building and content) losses 

approaching $30 billion. A first joint exercise of portable 

firefighting water-supply systems was also conducted by 

fire agencies in the San Francisco Bay region.

8. An analysis of the benefits of combining earthquake 

early warning (EEW) and drop, cover, and hold on 

(DCHO) actions, including the first study of the time 

it takes people to complete DCHO. Combining EEW 

and DCHO could prevent as many as 1,500 nonfatal 

injuries out of 18,000 estimated nonfatal injuries 

(from shaking and liquefaction hazards combined) 

in the HayWired scenario, a benefit valued at about 

$300 million.

A Recap of Earthquake Hazards

The HayWired Earthquake Scenario—Earthquake 

Hazards volume (Detweiler and Wein, 2017) sets the stage for 

this volume on the engineering implications of the scenario. 

The Hayward Fault is arguably the most urbanized active 

fault in the United States. Therefore, it offers an informative 

case study of the effects of a large urban earthquake on a 

modern U.S. metropolitan region. The earthquake-hazards 

volume described the hypothetical Mw 7.0 HayWired 

scenario mainshock, with additional descriptions of the 

cascading hazards of fault rupture, aftershocks (subsequent 

earthquakes), afterslip (subsequent movement on a fault), 

landslides, and liquefaction (soils becoming liquid-like during 

shaking).

The earthquake hazards volume also describes a largely 

physics-based model of ground motion for the HayWired 

mainshock. The model uses physical modeling of wave 

propagation but with a kinematic (motion-based) rupture 

model. This model of ground motion shows that damaging 

shaking (Modified Mercalli Intensity VI or higher) in the 

scenario occurs over a region of approximately 50,000 square 

kilometers (about 19,000 square miles)—170 kilometers (km) 

(about 105 miles) west to east (from the Pacific Coast to the 

Sierra Nevada) and 300 km (about 185 miles) north to south, 

including almost all the urbanized area of the nine counties 

bordering San Francisco Bay, as well as Santa Cruz County 

to the south. The differences between this largely physicsbased model and conventional ground-motion prediction 

equations were examined, and an explanation was provided of 

why the physics-based model was used to avoid a systematic 

underestimate of damage and loss for the HayWired scenario.

The modeled scenario earthquake sequence causes as much 

as 2 meters (about 6.5 feet) of fault offset either in the form of 

coseismic slip (fault slip during the mainshock) or afterslip. The 

aftershock sequence includes 16 aftershocks of Mw 5.0 or larger 

that occur over 2 years and as far as 50 km (about 30 miles) 

from the Hayward Fault; several of the aftershocks cause local 

damaging ground shaking that is stronger than in the mainshock. 

Earthquake-induced liquefaction and landslides, caused by 

the mainshock, further threaten people, property, and lifeline 

infrastructure in every county in the San Francisco Bay region.

Engineering Implications

The HayWired Earthquake Scenario—Engineering 

Implications volume (this volume) examines how the HayWired 

scenario earthquake sequence would affect buildings, watersupply pipelines, and other infrastructure. Many researchers have 

estimated the engineering impacts of similar earthquakes on the 

Hayward Fault, and several previous studies of San Francisco 

Bay region earthquakes were discussed in chapter A (Hudnut 

and others, 2017). The engineering implications volume is not 

meant to be an exhaustive study of a Hayward Fault earthquake 

like the ShakeOut scenario (Jones and others, 2008), which 

examined a hypothetical Mw 7.8 earthquake on the San Andreas 

Fault in southern California and presented a Hazus-MH analysis 

along with an examination of 18 special engineering topics. This 

volume ignores some important, but already well-studied, topics 

such as soft-story buildings and nonductile-concrete buildings. It 

sacrifices breadth for innovation to explore some engineering and 

infrastructure aspects of a San Francisco Bay region earthquake 

that others have not yet examined, either for a Hayward Fault 

earthquake or indeed for any earthquake.

Hazus-MH Analysis

Chapter J (Seligson and others, this volume) estimates the 

spectrum of damage and loss the San Francisco Bay region would 

experience in the HayWired scenario mainshock using FEMA’s 

public risk-analysis software, Hazus-MH (Federal Emergency 

Management Agency, 2012a). The Hazus-MH analysis uses 

detailed estimates of liquefaction and landslide probability that 

are customized using estimates of shaking from the HayWired 

mainshock. It uses a map of developed area to better constrain 

the effects of the liquefaction and landslide hazards on the 

built environment than would typical Hazus analyses. For 

example, landslide damage is estimated at several probability 

levels to quantify a range of possible impacts to pockets of 

developed areas in large census tracts in the San Francisco Bay 

region. Hazus-MH analysis is done for each of the 16 modeled 

aftershocks of magnitude 5.0 or greater. The analyses estimate 

cumulative damage from aftershocks, explore the vulnerability 

of unreinforced masonry and tilt-up buildings to aftershocks, 

highlight geographic areas where aftershocks produce greater 

damage than does the HayWired mainshock, and show repeat 
Chapter I. Overview of the HayWired Scenario Engineering-Implications Volume 3

damage from liquefaction. The HayWired earthquake sequence 

could cause 800 deaths and about 16,000 nonfatal injuries from 

the shaking hazard alone. If there were even a single collapse of 

a high-rise building, it could greatly increase the casualty figures. 

Direct losses related to damaged building stock are more than 

$82 billion, not including losses from fire following earthquake, 

over the entire scenario earthquake sequence, with very little of it 

insured. These losses, estimated using Hazus-MH, include about:

• $53 billion in building repair costs,

• $17 billion in damage to contents and inventory, and

• $12 billion in direct business interruption (that is, business 

interruption losses and additional expenses suffered by 

building occupants because of damage to their buildings).

Most of these estimated losses in the HayWired scenario 

are attributable to shaking damage (about 86 percent), the rest 

are attributable to liquefaction and landslides. Of the losses due 

to earthquake ground shaking, about 80 percent is attributable to 

the Mw 7.0 mainshock, 12 percent to three aftershocks of Mw 6.0 

to 6.4, and 8 percent to 13 aftershocks of Mw 5.0 to 5.9. Figure 1 

shows that building damage from the mainshock and aftershocks, 

as a percentage of replacement value, is highest (greater than 10 

percent) and most prevalent in Alameda County, followed by 

Contra Costa and Santa Clara Counties. It also shows widespread 

damage throughout the bay region of at least 0.5 percent of 

building replacement costs.

Societal Consequences of Current Code 

Performance Objectives

The Hazus-MH analysis for the HayWired scenario examines 

what happens to the existing building stock in the San Francisco 

Bay region in a powerful earthquake. Many previous studies have 

examined the potential effects of earthquakes on buildings (for 

Figure 1. Map of the San Francisco Bay region, California, showing estimated building-damage ratios 

(repair cost as a percent of building replacement cost) for the hypothetical magnitude-7.0 mainshock and 

aftershocks of the HayWired earthquake scenario on the Hayward Fault. The building-damage ratio was 

calculated using the public risk-analysis software Hazus-MH (Federal Emergency Management Agency, 

2012a) and considered shaking, liquefaction (soils becoming liquid-like during shaking), and landslide 

hazards. %, percent. (From Seligson and others, this volume.)

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

 38°

 37°

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5%

5–10%

>10%

Building damage 

 ratio—damage divided

 by replacement value, 

 expressed as a percent)

County boundary

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of map

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES
4 The HayWired Earthquake Scenario—Engineering Implications

example, Jones and others, 2008). The sometimes shockingly 

large estimates of building damage tend to draw attention to 

certain existing building types that contribute disproportionately 

to the overall damaged building stock, such as older unreinforcedmasonry buildings, nonductile concrete buildings, or older weldedsteel moment-frame buildings. In chapter K (Porter, Societal 

Consequences, this volume), I use this disaster-planning scenario 

for a new purpose—as a lens through which to view the intended 

performance of new buildings. 

The International Building Code (IBC), on which the 

California Building Code is based, aims to protect life safety by 

ensuring that fewer than 1 percent of buildings collapse because 

of earthquake shaking during their 50-year design life. However, 

earthquakes do not randomly affect individual buildings in the way 

traffic accidents affect people, one or a few at a time. Large urban 

earthquakes strike millions of people and hundreds of thousands 

of buildings simultaneously, so when a powerful urban earthquake 

strikes a region, 1 percent of buildings throughout the region could 

collapse simultaneously. The remaining buildings do not survive 

unscathed. Many are damaged to the point that they cannot be 

used, or even economically repaired, after the earthquake. 

Chapter K uses survey data from the Mw 6.9 1989 Loma 

Prieta and Mw 6.7 1994 Northridge, California, earthquakes to 

show that, for every collapsed building, approximately 60 are 

damaged to the point that they are unsafe to enter or occupy (red 

tag) or have their use restricted to a part of the building or to 

limited duration (yellow tag). Many more buildings experience 

damage costing tens of thousands of dollars, often exceeding the 

owners’ financial resources to repair. Again, these results follow 

indirectly from the IBC’s explicit performance objectives for new 

buildings, which means that, with the code’s current performance 

objectives, the State’s existing building stock in 50 years (the 

year 2067) or even 100 years (the year 2117), for example, will 

still pose a serious threat to its economic well-being and the lives, 

livelihoods, and financial stability of the individual people who 

own, live, or work in those buildings. Figure 2 is a map showing 

the impairment of existing buildings in the San Francisco Bay 

region after the HayWired mainshock, even if they all complied 

Figure 2. Map of the San 

Francisco Bay region, California, 

showing impairment of existing 

buildings, if they all complied 

with current building codes, for 

the magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario on the Hayward Fault. 

Impaired buildings include those 

that collapsed, are unsafe to 

occupy, or have restricted use. 

Warmer colors show areas with 

the greatest number of impaired 

buildings. Even if all buildings 

in the bay region complied with 

current building codes, 0.4 percent 

could collapse, 5 percent could be 

unsafe to occupy, and 19 percent 

could have restricted use. For 

only a small percentage cost 

increase, more resilient buildings 

constructed to more stringent 

building codes could allow 

95 percent of the bay region’s 

population to remain in their homes 

and workplaces following such an 

earthquake. (From Porter, Societal 

Consequences, this volume.)

39°

123° 122° 121°

38°

37°

0.0 0.2 0.4 0.6 0.8 1.0

0 20 40 60

20 40 60

MILES

0 KILOMETERS

Fraction of impaired buildings

PA C I F I C O C E A N

Area

of map

CALIFORNIA

San Francisco Oakland

San Jose
Chapter I. Overview of the HayWired Scenario Engineering-Implications Volume 5

with current building codes. Chapter K also shows how stronger 

buildings, costing about 1 to 3 percent more to build (less than the 

cost to reroof most buildings) would suffer about 75 percent less 

damage in terms of collapse, red-tagging, and yellow-tagging in an 

earthquake like that modeled in the HayWired scenario.

A Survey of Public Preferences for the Seismic 

Performance of New Buildings

The IBC strikes a balance for new buildings between better 

performance and less expense, but what does the public prefer? 

Chapter L (Porter, Not Safe Enough, this volume) reports on 

the first survey of the public’s expectations and preferences 

for the seismic performance of new buildings. It turns out 

that the current building code appears to aim for something 

different than the public prefers. A survey of 800 people (400 

Californians and 400 people from the Memphis, Tennessee, 

and St. Louis, Missouri, metropolitan statistical areas near the 

New Madrid Seismic Zone in the Central United States) shows 

that the majority expect new buildings generally to be habitable 

or functional after large earthquakes, not merely safe. Survey 

respondents expressed a willingness to pay at least an additional 

1 percent in construction costs to achieve their preferred degree 

of postearthquake performance (fig. 3). The willingness to 

pay more for better performance crosses geographic, wealth, 

and educational boundaries—people from the Central United 

States express almost the same preferences as do Californians, 

people from lower income households express almost the same 

preferences as those from higher income households, and level 

of education does not seem to affect these preferences.

Earthquake Urban Search and Rescue

How does building collapse in an earthquake affect demands 

on urban search and rescue (USAR) teams? Collapse here is 

defined as the loss of vertical load-carrying capacity in at least part 

of a building’s structural system, which may or may not trap building occupants or passersby. Chapter M (Porter, Earthquake Urban 

Search and Rescue Model, this volume) estimates the number of 

people trapped in collapsed buildings in earthquakes, using a new 

model that draws on an examination of photographs of building 

collapses in California earthquakes of the past 5 decades. This 

examination suggests that, when a California building experiences 

at least some collapse in an earthquake, an average of 25 percent 

of its occupiable area collapses in such a way that occupants could 

be trapped under debris. It seems realistic that an earthquake like 

the HayWired scenario mainshock could trap about 2,500 people 

in 5,000 collapsed buildings. (There are more collapses than occupants, because not every building collapse traps people.)

Chapter M also examines the question of how many people 

would require rescue from stalled elevators in a San Francisco Bay 

region earthquake like the HayWired scenario mainshock. The 

ShakeOut scenario hinted that many people could be trapped in 

stalled elevators when electric power is lost throughout a metropolitan region (Schiff, 2008), but it did not quantify the problem. 

AAXXXX_fig 01

Functional

18%

Occupiable

41%

A

B

Do not know

17%

Life safe

22%

Other

2%

$0/ft2

12%

$1/ft2

20%

$3/ft2

31%

Do not know

17%

$10/ft2

20%

Figure 3. Pie charts showing public preferences for the seismic 

performance of new buildings from a survey of 800 people (400 

Californians and 400 people from the Memphis, Tennessee, and 

St. Louis, Missouri, metropolitan statistical areas near the New 

Madrid Seismic Zone in the Central United States). Most people 

surveyed thought that (A) new buildings should remain occupiable 

or functional after a large earthquake and (B) building buyers 

would be willing to pay as much as an additional $3.00 or more per 

square foot (ft2) to achieve this preferred outcome. %, percentage of 

respondents. (Modified from Porter, Not Safe Enough, this volume.)
6 The HayWired Earthquake Scenario—Engineering Implications

Chapter M uses data about the age distribution of bay-region 

buildings along with the history of elevator emergency-power 

requirements to show that about 25,000 elevators in the bay region 

lack emergency power to operate briefly after an earthquake, 

even to travel to the nearest floor and open doors to let passengers escape. It is reasonable to assume that an earthquake like the 

HayWired mainshock will cause electric power to go out across 

the region as utility operators act to protect generators and transmission stability, causing many buildings to lose power before 

shaking reaches them. Elevator earthquake-safety devices (seismic 

switches or so-called ring-and-string devices) will therefore not 

be triggered. As a result, it seems possible that more than 22,000 

people could be trapped in approximately 4,600 stalled elevators, 

requiring USAR personnel—generally firefighters—to free them 

(fig. 4). The job of extricating more than 22,000 people from 4,600 

stalled elevators, along with about 2,400 people from 5,000 collapsed buildings, would fall to the approximately 19,000 firefighters who work in the San Francisco Bay region, at the same time as 

those firefighters are fighting fires.

Water-Network Resilience

Many authors have studied the effects of earthquakes 

on water-supply systems. Chapter N (Porter, Water-Network 

Resilience, this volume) offers a new water-network resilience 

model with a unique combination of features. It deals with lifeline 

interaction by directly modeling how individual repairs are 

Figure 4. Photograph of firefighters practicing rescue 

techniques to free people trapped in stalled elevators. Firefighters 

tend to provide the vast majority of urban search and rescue 

expertise. After an earthquake like the hypothetical magnitude-7.0 

mainshock of the HayWired earthquake scenario on the Hayward 

Fault in California’s San Francisco Bay region, they would be 

called on to extricate thousands of people trapped in stalled 

elevators and collapsed buildings at a time when they are also 

called on to fight fires. (U.S. Air Force photograph by Senior 

Airman Preston Webb; see Porter, Earthquake Urban Search and 

Rescue Model, this volume.)

slowed by limitations in other lifelines and by human and other 

resource limitations. It quantifies damage and restoration over 

an entire earthquake sequence—that is, considering damage in 

the mainshock, aftershocks, and afterslip. It offers an empirical 

model of water-service restoration as a function of the number 

of pipeline repairs performed (as opposed to more rigorous, but 

computationally demanding, hydraulic analysis). It can be used by 

water-agency staff with a spreadsheet and geographic information 

system (GIS), rather than requiring a consultant with proprietary 

software. It can be implemented either deterministically or 

stochastically, meaning that a sophisticated user can quantify 

uncertainty but is not required to do so. It does not require 

hydraulic analysis of the damaged water-supply system or the 

system as repairs proceed, although that simplification necessarily 

limits insight into how water pressure would vary throughout 

the system. The model offers a procedure to adjust Hazus-MH 

estimates of restoration to account for an earthquake sequence and 

lifeline interaction and corrects for Hazus’ default assumptions 

about the number of available repair crews during a disaster.

The new water-network resilience model is used to 

estimate damage and restoration to counties served by two water 

networks in the San Francisco Bay region for the HayWired 

scenario earthquake sequence (fig. 5)—those of the San Jose 

Water Company (SJWC) and of the East Bay Municipal Utility 

District (EBMUD). The more seriously damaged of the two 

networks would likely be EBMUD because of its proximity 

to the Hayward Fault. In the scenario, EBMUD’s 4,162 miles 

(6,698 km) of pipe suffer about 1,800 breaks and 3,900 leaks 

during the earthquake sequence, equivalent to 1.4 repairs per 

mile of pipe (about 0.85 repairs per kilometer of pipe). More 

than half of water-pipeline damage results directly from ground 

shaking (60 percent); the remaining damage occurs from 

liquefaction (29 percent), landslides (3 percent), and coseismic 

slip (4 percent) and afterslip on the fault (4 percent). In the 

HayWired scenario, the average EBMUD customer would 

be without water for 6 weeks, some for as many as 6 months. 

EBMUD customers suffer a total of 19 million lost service 

days (each day of lost water supply to a service connection). 

That loss can be reduced by half if current efforts to replace 

old, brittle pipe are completed before the next large bay-region 

earthquake occurs, because such pipe is more susceptible to 

earthquake damage, and replacing it would reduce damage 

and therefore restoration time. Also, about 200,000 lost service 

days could be saved by decreasing or eliminating EBMUD’s 

dependence on commercial fuel supplies. In the scenario, 

SJWC suffers less damage—1,000 pipe repairs, of which about 

70 percent are water leaks, the rest breaks—and customers 

would suffer approximately 1 million lost service-days. A 

utility can reduce its reliance on commercial fuel supplies in 

a disaster by installing fuel-storage tanks in its service centers 

or by otherwise ensuring that repair crews have access to fuel. 

Implementing such a fuel plan would reduce SJWC’s losses by 

about 25 percent. If SJWC completes replacement of all brittle 

cast-iron and asbestos-cement pipe (about 25 years at current 

replacement rates) before an earthquake occurs, losses would be 

reduced by about half.
Chapter I. Overview of the HayWired Scenario Engineering-Implications Volume 7

Santa Clara County

73 percent of service returned 

 in 7 days

Full service returned in 30 days

67 percent of service returned 

 in 7 days

Full service returned in 30 days

San Francisco County

35 percent of service returned 

 in 7 days

Full service returned in 90 days

San Mateo County

30 percent of service returned 

 in 7 days

Full service returned in 210 days

Alameda and Contra Costa Counties

Marin County

Full service returned 

 in 7 days

San Francisco County

Full service returned 

 in 7 days

Marin County

95 percent of service returned 

 in 7 days

Full service returned in 30 days

85 percent of service returned 

 in 7 days

Full service returned in 30 days

Santa Clara County

41 percent of service returned 

 in 7 days

Full service returned in 90 days

San Mateo County

47 percent of service returned 

 in 7 days

Full service returned in 210 days

Alameda and Contra Costa Counties

Current 

conditions 

With pipe 

replacement 

and fuel plan

Faster

restoration

of water

service

Prolonged

outages

Figure 5. This illustration shows water-service restoration times 

for counties in California’s San Francisco Bay region following the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired 

earthquake scenario. The image at left shows current conditions, 

and the image at right shows how water-service restoration 

times could be substantially improved if water utilities replaced 

all brittle pipe in their systems and had a fuel-management plan 

and emergency generators with fuel at all pumping stations. (From 

Hudnut and others, 2018, https://doi.org/10.3133/fs20183016, using 

data in Porter, Water-Network Resilience, this volume.)

Repair Costs and Downtime of High-Rise 

Buildings

New earthquake-engineering procedures have emerged 

since the ShakeOut scenario (Jones and others, 2008) that 

allow one to estimate repair costs and duration of loss of 

function for individual, particular buildings. High-rise 

buildings like the one shown in figure 6 are a particular 

concern for the engineering community, because a single 

building can house more than 1,000 people and dozens of 

businesses, making such buildings potential threats to lives 

and livelihoods in the San Francisco Bay region should they 

be damaged in an earthquake. In chapter O (Almufti and 

others, this volume), second-generation, performance-based 

earthquake-engineering procedures are applied to 10 example 

Figure 6. Photograph of a San Francisco Bay area, California, 

high-rise building. High-rise buildings account for roughly 3 percent 

of the total building square footage in the bay area, and each of 

these buildings can house more than 1,000 people and dozens of 

businesses. However, total collapse of such a building appears to 

be unlikely in downtown Oakland or San Francisco in an earthquake 

like the hypothetical magnitude-7.0 mainshock of the HayWired 

earthquake scenario on the Hayward Fault. (Photograph by Ken 

Lund, Creative Commons 3.0, https://www.flickr.com/photos/

kenlund/10753946294; see Almufti and others, this volume.)

buildings. These examples show that an earthquake like the 

Mw 7.0 mainshock of the HayWired scenario could damage a 

pre-1994 (Northridge earthquake) welded-steel moment-frame 

office tower in downtown Oakland or San Francisco such that 

it would require 6 to 13 months to reoccupy and cost 7 to 21 

percent of its replacement cost to repair, mostly because of 

nonstructural damage. Even a modern reinforced-concrete 

high-rise residential building could require 4 to 7 months of 

repairs before it could be reoccupied and cost 3 to 6 percent of 

its replacement cost to repair damaged nonstructural elements. 

Collapse of such high-rise buildings appears to be unlikely in 

downtown Oakland and San Francisco in an earthquake like 

the HayWired mainshock. However, this is not to say that 

other kinds of high-rise buildings could not collapse in these 

or other locations in the bay region.
8 The HayWired Earthquake Scenario—Engineering Implications

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Fire losses, in 

millions of dollars

HayWired 

 rupture

0

1–10

10–50

50–100

100–500

500+

Area

of map

CALIF

San

Francisco

Bay

PACIFIC

OCEAN

San 

Pablo

Bay

123° 122°

38°

37.5°

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Fire Following Earthquake

In chapter P (Scawthorn, this volume), a standard model of 

fire following earthquake is applied to the HayWired scenario. The 

HayWired mainshock could produce about 670 ignitions requiring 

the response of a fire engine, 90 percent of which would occur in 

Alameda, Contra Costa, and Santa Clara Counties. Approximately 

450 of these fires would not be immediately contained such that 

large fires would be likely to merge into numerous conflagrations 

destroying tens of city blocks. The fires would burn approximately 

79 million square feet (about 7.3 million square meters) of 

building floor area, equivalent to more than 52,000 single-family 

dwellings. These fires would kill hundreds of people and cause 

property (building and content) losses approaching $30 billion. 

The property losses are almost fully insured. Fire following 

earthquake in the HayWired scenario would produce one of the 

largest single-loss events in the history of the insurance industry. 

Other potential economic impacts from fire following 

earthquake include the loss of perhaps $1 billion in local tax 

revenues. A number of opportunities exist for mitigating this 

problem, including greatly enhancing the postearthquake 

supply of water for firefighting; the mandatory use of 

automated gas shut-off valves, or seismic shut-off meters, 

in densely built areas; and the use of portable water-supply 

systems. Toward that end, the first joint exercise of fire 

agencies in the San Francisco Bay area to practice the use 

of portable water-supply systems was conducted as part of 

HayWired (fig. 7).

Figure 7. This map of California’s San Francisco Bay region shows areas burned as a result of fires 

caused by the hypothetical magnitude-7.0 mainshock of the HayWired earthquake scenario on the 

Hayward Fault. Warmer colors show areas with greater losses in millions of dollars. Areas (polygons) 

shown are based on distance to the closest fire station. The black line shows the length of the fault 

rupture in the scenario. (From Scawthorn, this volume.)
Chapter I. Overview of the HayWired Scenario Engineering-Implications Volume 9

Google Earth

Data LDEO-Columbia, NSF, NOAA

Image Landsat/Copernicus

Data SIO, NOAA, U.S. Navy, NGA, GEBCO

Data MBARI

0

0

10 20

10 20

30 40 50 KILOMETERS

30 MILES

PACIFIC 

 OCEAN

SAN FRANCISCO BAY

38°

123° 122° 121°

37°

San Jose

San Francisco

Oakland

 Area CALIF

of map

A

Benefit of Combining Earthquake Early Warning 

with Drop, Cover, and Hold On

Since the advent of ShakeOut exercises following the 

publication of The ShakeOut Scenario (Jones and others, 2008), 

every year millions of people worldwide practice drop, cover, 

and hold on (DCHO) earthquake self-protective actions (https://

www.shakeout.org/). During the same period, earthquake early 

warning (EEW) systems have become available (for example, 

the Android phone and iPhone app Yurekuru Call in Japan) to 

warn people about earthquakes in the seconds before strong 

motion arrives. Chapter Q (Porter and Jones, this volume) offers 

a new study of the potential benefits of combining EEW and 

DCHO. It expresses those benefits in terms of avoided injuries 

Figure 8. In the hypothetical magnitude-7.0 mainshock of the HayWired earthquake scenario on the Hayward Fault in California’s San Francisco Bay 

region, combining earthquake early warning (EEW) and drop, cover, and hold on (DCHO) practices could result in as many as 1,500 nonfatal injuries 

being prevented out of 18,000 estimated nonfatal injuries, a benefit valued at about $300 million. A, Satellite image showing EEW times in seconds (s) 

for the HayWired mainshock. The red line, shows the length of the fault rupture in the scenario, and the epicenter (star) is beneath the City of Oakland. 

(Satellite image from Google Earth.) B, Illustration showing how to DCHO (courtesy of ShakeOut.org).

and the acceptable cost to avoid those injuries. A survey was 

made of 500 people who first took DCHO training and then 

reported how long it took them to complete the actions. Using 

these new data and estimates of the advanced warning (as much 

as 25 seconds) that EEW would provide San Francisco Bay 

region residents in the event of an earthquake like the HayWired 

mainshock, it is shown that combining EEW and DCHO 

could prevent as many as 1,500 nonfatal injuries out of 18,000 

estimated nonfatal injuries (from shaking and liquefaction 

hazards) in the HayWired scenario (fig. 8). Using U.S. 

Government standard figures for the acceptable cost to avoid 

future statistical injuries, the combination of EEW and DCHO in 

a powerful bay region earthquake would be a benefit valued at 

approximately $300 million.
10 The HayWired Earthquake Scenario—Engineering Implications

Future Research

The developers of the HayWired earthquake scenario 

did not intend or expect to examine every engineering-related 

issue (or other important topic) arising from a large Hayward 

Fault earthquake, partly because of all the previous work on 

the subject. However, several outstanding engineering issues 

remain unexplored and would be worth examining. A few of 

these include:

1. The cost of performing Applied Technology Council (ATC) 

ATC-20 post-earthquake safety evaluations.—The 1994 

Northridge earthquake resulted in ATC-20 earthquake 

safety-inspection (Applied Technology Council, 2005) of 

100,000 buildings. The HayWired mainshock is a larger 

earthquake than the one in Northridge and takes place in a 

more densely populated urban area, suggesting that many 

more ATC-20 evaluations would be required. California 

has approximately 6,000 certified evaluators, another 4,000 

live elsewhere in the United States (Jim Barnes, California 

Governor’s Office of Emergency Services, oral commun., 

September 29, 2017). Most have other day jobs. They would 

only be briefly available to volunteer to perform ATC-20 

evaluations. It might take weeks or more to complete the 

required ATC-20 evaluations. During that time, many 

occupants would be displaced from their buildings while 

awaiting evaluations. What would be the cost of delayed 

ATC-20 evaluations, and how much time and economic 

value might be saved through automation, such as using 

FEMA’s Rapid Observation of Vulnerability and Estimation 

of Risk (ROVER) software (Federal Emergency Management Agency, 2013)? 

2. Effectiveness of DCHO to avoid injuries during shaking.—People believe DCHO to be effective, but how 

effective, and how can we be sure? Nobody has ever 

tested the effectiveness of DCHO self-protective actions. 

The question matters for several reasons, some of which 

include judging the costs versus benefits of further 

reducing nonstructural hazards, and estimating needs for 

emergency medical care. There is very little information to answer any of these questions, partly because no 

research program seems to currently focus on understanding human injuries in earthquakes.

3. Cost effectiveness of seismic gas-shutoff valves.—It 

seems intuitive that seismic gas-shutoff valves would 

reduce the risk of fires, but they introduce costs—upfront construction costs and costs of reopening the 

valves after an earthquake. Under what conditions are 

the costs justified? The answer is not self-evident.

4. Modeling electric-utility-service damage and restoration.—Electric-service impairment and subsequent 

restoration depends on electric network stability as much 

as it does on physical damage to generation facilities, 

transmission and distribution lines, substations, and 

neighborhood and pole-mounted transformers. It would 

be desirable to construct a model akin to the water-network resilience model introduced here, which does not 

require proprietary software. Such a model of electricutility resilience would need to be able to estimate damage and restoration time, while accounting for lifeline 

interaction, human and other resource limitations, and 

the engineering characteristics of the various components just listed, without requiring sensitive data from 

the electric-service provider.

Conclusion

This chapter and the volume it summarizes describe 

realistic engineering implications of a large earthquake on 

what may be the most urbanized active fault in the United 

States—the Hayward Fault. It is not intended to represent 

a best case, a worst case, or an average case, merely one 

that is worth planning for. It shows how such an earthquake 

could cause more than $82 billion in property loss and direct 

business interruption losses over the modeled earthquake 

sequence, plus another $30 billion in property (building and 

content) losses resulting from fires after the mainshock.

B

Figure 8.—Continued
Chapter I. Overview of the HayWired Scenario Engineering-Implications Volume 11

Because it aims at depth rather than breadth, this volume 

mostly omits a number of important topics that have been 

addressed well elsewhere; for example: 

• What to do about high-risk existing buildings is not

addressed. Interested readers can refer to the San

Francisco Community Action Plan for Seismic Safety

(CAPSS) and Earthquake Safety Improvement Program (ESIP) (see http://sfgov.org/esip/program/) or

to the City of Santa Monica’s comprehensive seismic

retrofit program (see https://www.smgov.net/Departments/PCD/Programs/Seismic-Retrofit/) for valuable

guidance on that topic.

• Very little is discussed about dealing with nonstructural

building components. The interested reader can see

FEMA’s E-74 document (Federal Emergency Management Agency, 2012b).

• There is little discussion about electricity and gas. The

interested reader can refer to Pacific Gas and Electric

Company’s web pages on residential and business

earthquake preparedness (https://www.pge.com/en_

US/safety/emergency-preparedness/natural-disaster/

earthquakes/earthquakes.page).

The HayWired scenario’s developers hope that the 

information here and in other HayWired volumes will inform 

the reader’s decisions about how to prepare for a large 

earthquake, whether by strengthening infrastructure to better 

resist earthquakes or through improved planning to recover 

more quickly despite damage. Ideally, the HayWired scenario 

volumes will help readers collectively improve their own and 

their community’s resilience in future disasters. 

Work that straddles the boundary between engineering 

and social and economic consequences is planned to be 

described in a third HayWired volume. Beyond that, a group 

of government and other organizations called the HayWired 

Coalition (see chapter A, Hudnut and others, 2017; and 

Hudnut and others, 2018) intends to build on the work 

presented here through a series of planning and preparedness 

activities. As HayWired volumes are published, they will be 

made available at https://doi.org/10.3133/sir20175013.

References Cited

Applied Technology Council, 2005, ATC-20-1—Field 

handbook—Procedures for postearthquake safety evaluation of 

buildings: Redwood City, Calif., Applied Technology Council, 

144 p.

Detweiler, S.T., and Wein, A.M., eds., 2017, The HayWired 

earthquake scenario—Earthquake hazards: U.S. Geological 

Survey Scientific Investigations Report 2017–5013–A–H, 126 

p., accessed September 13, 2017, at https://doi.org/10.3133/

sir20175013v1.

Federal Emergency Management Agency, 2012a, Hazus multihazard loss estimation methodology, earthquake model, 

Hazus®-MH 2.1 technical manual: Federal Emergency 

Management Agency, Mitigation Division, 718 p., accessed 

September 13, 2017, at https://www.fema.gov/media-librarydata/20130726-1820-25045-6286/hzmh2_1_eq_tm.pdf.

Federal Emergency Management Agency, 2012b, Reducing the 

risks of nonstructural earthquake damage—A practical guide: 

Federal Emergency Management Agency, FEMA E-74, 885 p., 

accessed September 13, 2017, at https://www.fema.gov/fema-e74-reducing-risks-nonstructural-earthquake-damage.

Federal Emergency Management Agency, 2013, ROVER, 

end-to-end mobile software for managing seismic risk: 

Federal Emergency Management Agency flyer, 1 p., accessed 

September 13, 2017, at https://www.fema.gov/media-library/

assets/documents/21350.

Hudnut, K.W., Wein, A.M., Cox, D.A., Perry, S.C., Porter, 

K.A, Johnson, L.A., and Strauss, J.A., 2017, The HayWired 

scenario—How can the San Francisco Bay region bounce 

back from or avert an earthquake disaster in an interconnected 

world?, chap. A of Detweiler, S.T., and Wein, A.M., eds., The 

HayWired earthquake scenario—Earthquake hazards: U.S. 

Geological Survey Scientific Investigations Report 2017–

5013–A–H, 126 p., accessed September 13, 2017, at https://doi.

org/10.3133/sir20175013v1.

Hudnut, K.W., Wein, A.M., Cox, D.A., Porter, K.A., Johnson, 

L.A., Perry, S.C., Bruce, J.L., and LaPointe, D., 2018, The 

HayWired earthquake scenario—We can outsmart disaster: 

U.S. Geological Survey Fact Sheet 2018–3016, 6 p., https://doi.

org/10.3133/fs20183016.

Jones, L.M., Bernknopf, R., Cox, D., Goltz, J., Hudnut, K., Mileti, 

D., Perry, S., Ponti, D., Porter, K., Reichle, M., Seligson, H., 

Shoaf, K., Treiman, J., and Wein, A., 2008, The ShakeOut 

scenario: U.S. Geological Survey Open-File Report 2008–1150 

and California Geological Survey Preliminary Report 25, 312 p. 

and appendixes, accessed September 13, 2017, at https://pubs.

usgs.gov/of/2008/1150/.

Schiff, A., 2008, The ShakeOut scenario supplemental 

study—Elevators: Denver, Colo., SPA Risk LLC, accessed 

September 13, 2017, at http://www.sparisk.com/pubs/

ShakeOutScenarioElevatorsSchiff.pdf.

Chapter J

HayWired Scenario—Hazus Analyses of the Mainshock 

and Aftershocks

By Hope A. Seligson,1 Anne M. Wein,2 and Jamie L. Jones2

The HayWired Earthquake Scenario—Earthquake Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013]

1

Seligson Consulting, initial efforts conducted while with MMI 

Engineering.

2

U.S. Geological Survey.

Abstract

The HayWired scenario examines a hypothetical 

earthquake (mainshock) with a moment magnitude (Mw) of 

7.0 occurring on April 18, 2018, at 4:18 p.m. on the Hayward 

Fault in the east bay part of California’s San Francisco Bay 

area. Analyses of building damages and direct economic 

losses from the HayWired mainshock and its aftershocks 

have been conducted using Hazus, the Federal Emergency 

Management Agency’s (FEMA) multi-hazard geographic 

information system-based loss estimation methodology and 

software. The initial Hazus analysis of the HayWired scenario 

mainshock (Aagaard and others, 2017)—the baseline default 

run—was conducted by FEMA using Hazus-MH 2.1 with 

improved inventory data originally developed for the 100th 

Anniversary Earthquake Conference commemorating the 1906 

San Francisco earthquake. In this study, the mainshock was 

further analyzed using custom HayWired landslide probability 

and displacement estimates and custom HayWired liquefaction 

probability estimates. The baseline default Hazus shaking and 

liquefaction run was also revised to use the same groundwater 

depth data as used in the U.S. Geological Survey (USGS)

analysis of liquefaction probability.

The aftershock sequence (a catalog of earthquakes 

each with a date/time, magnitude, location, and depth) was 

simulated by the USGS using aftershock statistics. Hazus 

analyses of 16 aftershock events of magnitude 5 or greater 

were performed using the same improved inventory databases 

as the initial analysis of the mainshock. This chapter (1) 

describes the results of the initial and revised Hazus analyses 

of the mainshock (considering shaking, liquefaction, and 

landslide hazards) and aftershocks (considering shaking and 

Hazus default liquefaction in selected events), (2) assesses 

the potential impact of liquefaction and repeated liquefaction, 

(3) reviews expected performance of unreinforced masonry 

construction in the various events, (4) compares population 

displacement and shelter estimates using default parameters 

and custom parameters developed for the Southern California 

ShakeOut scenario, (5) compares various approaches for 

combining losses in the mainshock and aftershocks, and (6) 

identifies knowledge gaps and study limitations.

The results of the mainshock assessment yield building 

losses of $35.2 billion (in 2005 dollars, estimated as 

$43.3 billion in 2016 dollars): $30.3 billion (in 2005 dollars, 

$37.3 billion in 2016 dollars) in damage from shaking, 

$4.6 billion (in 2005 dollars, $5.7 billion in 2016 dollars) in 

damage from liquefaction, and $300 million (in 2005 dollars, 

$360 million in 2016 dollars) in damage from landslide. Over 

the entire earthquake sequence, the total direct economic 

loss can be approximated as $67.0 billion (in 2005 dollars, 

$82.6 billion in 2016 dollars). This includes the following:

• $43.3 billion (in 2005 dollars, $53.3 billion in 2016 

dollars) in building damage for the mainshock and 

all aftershocks, using USGS-modeled liquefaction 

and landslide hazard and probability data for the 

mainshock, where available, and the Hazus default 

liquefaction modeling approach for other areas in the 

mainshock as well as for three aftershocks (M5.98 

Mountain View, M6.4 Cupertino, and M5.42 Oakland). 

The remainder of aftershocks were modeled for 

shaking only.

• $13.8 billion (in 2005 dollars, $17.0 billion in 2016 

dollars) in damage to contents and commercial 

inventories, estimated using the Hazus default 

liquefaction modeling approach for the mainshock and 

the three aftershocks identified above, and considering 

only ground-shaking hazards for the remainder of events.

• $10.0 billion (in 2005 dollars, $12.3 billion in 2016 

dollars) in building damage-related income losses (for 

example, relocation costs, lost rent, and so on), modeled 

in the same manner as contents and inventory damage.
14 The HayWired Earthquake Scenario—Engineering Implications

About 80 percent of the losses from the earthquake 

sequence are from the Mw 7.0 mainshock, 12 percent from 

the three largest aftershocks of Mw 6.0 to 6.4, and 8 percent

from the 13 aftershocks of Mw 5.0 to 5.9. Displaced household 

assessments range from tens of households for the smallest 

aftershocks, to hundreds of households for the largest 

aftershocks, to tens of thousands of households (77,000–

153,000) for the mainshock (based on the 2000 U.S. Census).

Introduction

The HayWired scenario examines a hypothetical 

earthquake (mainshock) with a moment magnitude (Mw) of 7.0 

occurring on April 18, 2018, at 4:18 p.m. on the in the east bay 

part of California’s San Francisco Bay area. The rupture of the 

Hayward Fault starts under the city of Oakland, with fault slip 

progressing north into San Pablo Bay and south to the city of 

Fremont (Aagaard and others, 2017). The mainshock shaking 

data (U.S. Geological Survey [USGS], 2014), simulated 

using a three-dimensional model (Aagaard and others, 2017), 

were used directly in the Federal Emergency Management 

Agency’s (FEMA) damage and loss modeling tool, Hazus 

(FEMA, 2012). The shaking data for the HayWired mainshock 

were also used to derive data for (1) liquefaction probability 

(Jones and others, 2017) and (2) landslide probability and 

displacement (McCrink and Perez, 2017).

The HayWired aftershock sequence has thousands of 

aftershocks and is described in Wein and others (2017). The larger 

aftershocks (magnitude [M]>5) in the sequence simulated for 

the Mw 7.0 HayWired mainshock are identified in table 1. The 

sequence includes two M>6 events (one in Palo Alto and one in 

Cupertino) and spans 2 years. The locations of the 16 aftershocks 

are shown in figure 1. The regional ground-shaking data for these 

aftershocks (USGS, 2015) were also used directly in Hazus.

Building Inventory Data

The initial Hazus analysis conducted for the HayWired 

scenario mainshock was executed using Hazus-MH 2.1 by 

FEMA personnel (Doug Bausch of FEMA Region VIII) using 

the custom ground motion data for the HayWired scenario 

mainshock (USGS, 2014) and enhanced Hazus building 

inventory data originally developed in 2005–2006 as part 

of a modeling effort for the 100th Anniversary Earthquake 

Conference Commemorating the 1906 San Francisco 

Earthquake (Kircher and others, 2006). The Hazus database 

improvements include retrofitted building models for 

unreinforced masonry (URM), non-ductile concrete, and softstory wood frame1 structures; replacement cost escalation factors 

to better reflect actual building inventory values; and enhanced 

mapping schemes (relationships by building occupancy class 

that describe the percentage distribution of square footage 

among various structural types or model building types (MBTs), 

as referred to within Hazus). A total of 22 custom mapping 

schemes were applied at the census-tract level across the bay 

area, reflecting differing building age and height patterns, as 

well as building density; a separate set of schemes were applied 

to San Francisco and Alameda Counties to reflect urban core 

1

Within Hazus, non-ductile concrete is generally represented by “pre-code” 

design level concrete moment frame (model building type C1) and concrete 

frame with URM infill wall (C3) buildings. Pre-code precast concrete frame 

buildings with concrete shear walls (PC2) may also be considered non-ductile. 

Soft-story wood frame is similarly represented by pre-code wood frame (W1 

and W2) buildings.

No. Date Day Time (PDT) Latitude Longitude Location Depth (km) Mag. Short name

1 4/18/2018 1 4:49 p.m. 37.6008 122.0172 Union City 2.60 5.23 UC523

2 4/19/2018 2 4:16 a.m. 37.9630 122.3473 San Pablo 2.60 5.04 SP504

3 4/29/2018 12 11:13 p.m. 38.1916 122.1483 Fairfield 11.05 5.58 FF558

4 5/02/2018 15 8:44 p.m. 37.4829 121.9146 Fremont 7.15 5.10 FR510

5 5/20/2018 33 8:37 a.m. 37.7561 122.1508 Oakland 8.45 5.42 OK542

6 5/28/2018 41 4:47 a.m. 37.3867 122.1780 Palo Alto 15.97 6.20 PA62

7 5/28/2018 41 8:11 a.m. 37.4528 122.1671 Menlo Park 7.26 5.52 MP552

8 5/28/2018 41 6:22 p.m. 37.4604 122.1753 Atherton 7.91 5.11 AT511

9 5/28/2018 41 11:53 p.m. 37.4099 122.1184 Palo Alto 8.36 5.69 PA569

10 6/23/2018 67 8:27 p.m. 37.4391 122.1511 Palo Alto 2.85 5.22 PA522

11 7/01/2018 75 11:19 a.m. 37.4435 122.1561 Palo Alto 8.69 5.26 PA526

12 9/30/2018 166 8:16 p.m. 37.4386 122.0770 Mountain View 11.29 5.98 MV598

13 10/01/2018 167 12:33 a.m. 37.3068 122.0592 Cupertino 14.45 6.40 CU64

14 10/01/2018 167 2:24 a.m. 37.3835 122.0153 Sunnyvale 18.89 5.35 SV535

15 10/01/2018 167 6:10 a.m. 37.3334 121.9541 Santa Clara 7.00 5.09 SC509

16 8/22/2019 492 10:45 p.m. 37.4145 122.1235 Palo Alto 11.98 5.01 PA501

Table 1. Sequence of aftershocks of magnitude 5 or greater of the HayWired earthquake scenario, San Francisco Bay region, California.

[Data from U.S. Geological Survey (2014). Date format is month/day/year. Day is relative to the day the HayWired mainshock event occurred, with April 18, 

2018, counted as day 1. Latitude is in decimal degrees north; longitude is in decimal degrees west. Depth is how far below the Earth’s surface the aftershock 

hypocenter is located. No., event number; PDT, Pacific Daylight Time; km, kilometers; Mag., magnitude; Short name, short event name]
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 15

Figure 1. Map showing epicenters of the mainshock (largest red star) and aftershocks of magnitude 5 or 

greater of the hypothetical HayWired earthquake scenario in the San Francisco Bay region, California.

areas with concentrations of mid-rise and high-rise construction. 

These schemes are considered a substantial improvement over 

the Hazus default mapping schemes, wherein all construction is 

assumed to be low-rise.

Hazus analyses using the custom HayWired liquefaction 

and landslide data, as well as the aftershock shaking data, were 

done using the same improved building inventory as that for 

the initial mainshock Hazus run. Summaries of the improved 

building inventory data are provided in tables 2, 3, and 4, by 

county name, by occupancy, and by structural type, respectively. 

Note that totals may not match exactly as a result of rounding. 

Exposure values (and resulting estimated losses) for the Hazus 

custom bay area inventory data are in 2005 dollars. These 

values can be approximately escalated to 2016 dollars using 

Consumer Price Index (CPI) ratios (see https://www.bls.gov/cpi/

data.htm); the U.S. CPI 2016:2005 ratio is approximately 1.23.

ALAMEDA

SAN MATEO

SANTA CLARA

SONOMA

MARIN

NAPA

SAN

FRANCISCO

SOLANO

SOLANO

CONTRA 

COSTA

122.5° 122°

38°

37.5°

EXPLANATION

County boundary

Hayward Fault

Fault

Mainshock and 

aftershock epicenters

Magnitude

5.0–5.5

5.5–6.0

6.0–6.5

6.5–7.0

0 5 10 20 MILES

0 10 15

15

5 20 KILOMETERS

SAN FRANCISCO BAY

SAN PABLO 

 BAY

Coordinate System: GCS North American 1983

Datum: North American 1983

 Area 

of map CALIF
16 The HayWired Earthquake Scenario—Engineering Implications

Table 2. Improved building inventory data by county used for the Hazus analyses of the HayWired earthquake scenario mainshock and 

aftershock sequence, San Francisco Bay region, California.

[Exposure value reported in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23]

County Building count Building square footage 

(thousands of square feet)

Total exposure value 

(thousands of dollars)

Alameda 413,505 1,134,537 155,699,818

Contra Costa 321,281 717,509 102,806,780

Marin 93,195 237,269 36,050,257

Merced 56,678 117,942 12,901,176

Monterey 109,838 271,611 33,772,799

Napa 45,053 111,729 14,579,197

Sacramento 378,791 890,201 110,561,701

San Benito 16,279 32,842 4,135,710

San Francisco 172,931 671,672 100,178,548

San Joaquin 159,215 358,055 42,755,589

San Mateo 219,815 557,525 84,301,336

Santa Clara 495,282 1,263,479 183,312,185

Santa Cruz 90,140 208,512 28,382,925

Solano 120,823 265,812 34,820,221

Sonoma 169,235 385,085 50,857,518

Stanislaus 130,688 287,260 33,827,997

Yolo 46,049 120,019 14,478,828

Total 3,038,798 7,631,059 1,043,422,585

Hazus occupancy class Building count Building square footage 

(thousands of square feet)

Total exposure value 

(thousands of dollars)

RES1 (single-family homes) 2,702,528 4,324,156 610,850,583

RES2 (manufactured housing) 108,696 117,362 4,151,673

RES3A (multifamily residential: duplex) 60,464 193,083 18,451,037

RES3B (multifamily residential: triplex/quad) 52,642 171,161 17,701,795

RES3C (multifamily residential: 5–9 units) 16,195 163,087 29,271,495

RES3D (multifamily residential: 10–19 units) 7,588 127,115 20,470,095

RES3E (multifamily residential: 20–49 units) 1,447 118,537 18,794,663

RES3F (multifamily residential: 50+ units) 1,781 189,909 29,180,378

RES4 (hotel/motel) 57 22,169 3,395,429

RES5 (institutional dormitories) 4,157 116,399 20,146,620

RES6 (nursing homes) 184 5,184 773,093

COM1 (retail trade) 1,569 396,411 38,858,298

COM2 (wholesale trade) 6,379 227,375 20,214,758

COM3 (personal/repair services) 15,791 174,448 21,226,826

COM4 (offices) 4,125 473,123 70,944,986

COM5 (banks) 5,524 22,853 4,975,356

COM6 (hospitals) 420 25,336 6,678,754

COM7 (medical offices/clinics) 9,710 72,953 13,915,026

COM8 (entertainment/recreation) 23,845 120,160 24,748,686

COM9 (theaters) 231 3,860 559,818

COM10 (parking garages) 0 0 0

Table 3. Improved building inventory data by occupancy class used for the Hazus analyses of the HayWired earthquake scenario 

mainshock and aftershock sequence.

[Exposure value reported in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23]
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 17

Table 3.—Continued

Table 4. Improved building inventory data by model building type used for the Hazus analyses of the HayWired earthquake scenario 

mainshock and aftershock sequence.

[Exposure value reported in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23. ft2, square feet; CIP, cast in place; PC, 

precast; RM, reinforced masonry; URM, unreinforced masonry; w/, with; conc., concrete]

Hazus model building type Building count Building square footage 

(thousands of square feet)

Total exposure value 

(thousands of dollars)

W1 (wood, light frame, ≤5,000 ft2) 2,734,372 4,540,623 634,173,432

W2 (wood, commercial and industrial, >5,000 ft2) 22,888 602,193 87,505,195

S1L (steel moment frame, low-rise) 7,491 123,223 16,882,881

S1M (steel moment frame, mid-rise) 4,747 68,584 9,587,560

S1H (steel moment frame, high-rise) 9,109 109,743 16,598,964

S2L (steel braced frame, low-rise) 4,900 90,922 11,632,242

S2M (steel braced frame, mid-rise) 3,842 52,920 7,014,666

S2H (steel braced frame, high-rise) 2,565 33,002 5,042,406

S3 (steel light frame) 3,779 76,168 8,909,731

S4L (steel frame w/ CIP concrete shear walls, low-rise) 2,529 46,719 6,328,477

S4M (steel frame w/ CIP Concrete shear walls, mid-rise) 2,936 33,876 5,096,293

S4H (steel frame w/ CIP concrete shear walls, high-rise) 1,352 22,107 3,442,221

S5L (steel frame w/ URM infill walls, low-rise) 4,796 89,765 11,334,447

C1L (concrete moment frame, low-rise) 755 25,034 3,225,732

C1M (concrete moment frame, mid-rise) 3,031 33,257 5,193,239

C1H (concrete moment frame, high-rise) 2,865 30,933 4,649,490

C2L (concrete shear wall, low-rise) 13,796 270,262 36,497,177

C2M (concrete shear wall, mid-rise) 9,991 127,918 17,573,591

C2H (concrete shear wall, high-rise) 5,087 49,514 7,368,727

C3L (concrete frame w/ URM infill walls, low-rise) 3,424 46,946 6,464,956

C3M (concrete frame w/ URM infill walls, mid-rise) 3,466 53,021 6,354,659

C3H (concrete frame w/ URM infill walls, high-rise) 1,890 18,651 2,799,477

PC1 (PC concrete tilt-up walls) 5,370 182,812 20,193,977

PC2L (PC concrete frames w/ conc. shear walls, low-rise) 1,060 30,568 3,620,206

PC2M (PC concrete frames w/ conc. shear walls, mid-rise) 622 7,900 1,022,077

PC2H (PC concrete frames w/ conc. shear walls, high-rise) 757 6,612 963,776

Hazus occupancy class Building count Building square footage 

(thousands of square feet)

Total exposure value 

(thousands of dollars)

IND1 (heavy industrial) 3,154 104,632 10,793,540

IND2 (light industrial) 2,992 107,895 9,631,660

IND3 (food/drugs/chemical) 903 49,298 8,382,266

IND4 (metals/minerals processing) 99 6,115 1,035,700

IND5 (high technology) 628 30,336 5,166,822

IND6 (construction) 1,478 82,533 7,333,744

AGR1 (agriculture) 611 34,953 3,068,518

REL1 (churches) 2,654 64,015 10,457,728

GOV1 (government/general services) 2,326 26,109 3,279,910

GOV2 (government/emergency response) 231 2,826 547,978

EDU1 (education/grade schools) 44 38,997 5,277,262

EDU2 (education/colleges and universities) 345 18,668 3,138,088

Total 3,038,798 7,631,058 1,043,422,585
18 The HayWired Earthquake Scenario—Engineering Implications

Hazus Results—HayWired Mainshock

The initial HayWired scenario mainshock was analyzed 

using regional liquefaction susceptibility data developed by the 

USGS and others (Knudsen and others, 2000; as shown in fig. 2), 

in conjunction with the Hazus default approach for computing 

liquefaction displacements and probabilities of occurrence and the 

default assumption of uniform shallow groundwater conditions, to 

produce a baseline “default” Hazus run.

As part of the HayWired earthquake scenario hazard studies, 

more detailed liquefaction probability calculations were performed 

for the mainshock in Alameda and Santa Clara Counties (Jones 

and others, 2017). Likewise, more detailed landslide probability 

and displacement calculations were performed for the mainshock 

for the bay area (McCrink and Perez, 2017). As a result of the 

focused liquefaction study, the baseline Hazus default run was 

modified to reflect a dual groundwater depth assumption (16 feet 

in western Santa Clara County, 5 feet elsewhere) consistent with 

the more detailed study.

Implementing the HayWired mainshock liquefaction and 

landslide data in Hazus required unconventional implementations 

of Hazus. Descriptions of these implementations precede the 

discussion of HayWired mainshock loss results in the following 

sections.

HayWired Liquefaction Implementation in Hazus

Liquefaction probabilities were derived for most of Santa 

Clara and Alameda counties for the HayWired mainshock based 

on a method by Holzer and others (2008, 2010, 2011) (see Jones 

and others, 2017). The liquefaction probabilities were provided 

for 50-meter (m) pixels throughout the coverage area.

The implementation of these data in Hazus required 

creating census tract-based liquefaction probability data. 

National Land Cover Data (NLCD; Homer and others, 

2015) were used to identify pixels located in developed areas 

(identified as low-, medium- or high-intensity development), as 

shown in figure 3. Census tract-level liquefaction probabilities 

Hazus model building type Building count Building square footage 

(thousands of square feet)

Total exposure value 

(thousands of dollars)

RM1L (RM bearing walls w/ wood or metal deck diaphragms, 

low-rise)

46,314 396,562 54,177,952

RM1M (RM bearing walls w/ wood or metal deck diaphragms, 

mid-rise)

5,094 72,129 9,448,147

RM2L (RM bearing walls w/ PC conc. diaphragms, low-rise) 1,747 39,094 5,205,624

RM2M (RM bearing walls w/ PC conc. diaphragms, mid-rise) 1,255 19,765 2,592,305

RM2H (RM bearing walls w/ PC conc. diaphragms, high-rise) 382 3,772 559,241

URML (URM bearing walls, low-rise) 10,965 148,408 19,899,424

URMM (URM bearing walls, mid-rise) 3,919 31,261 4,262,510

MH (mobile homes) 111,702 146,792 7,801,366

Total 3,038,798 7,631,056 1,043,422,168

Table 4.—Continued

were then calculated as the average across pixels with nonzero liquefaction probability in developed areas such that 

(1) liquefaction probabilities in undeveloped areas would not 

influence results, and (2) resulting loss estimates for the census 

tract were assumed uniform in the census tract (consistent with 

the Hazus methodology) and could then be scaled down in 

proportion to how much of the developed area had a non-zero 

probability of liquefaction.

Further, because the Holzer and others method does not 

provide liquefaction displacement values, Hazus-estimated 

displacements were required. Within Hazus, liquefactioninduced spread and settlement displacement estimates, as well 

as liquefaction probability estimates, require the input of maps 

of ground motion, liquefaction susceptibility and groundwater 

depth. For consistency with the liquefaction probability 

calculations, the liquefaction susceptibility data input into Hazus 

was modified from the basic “point-in-polygon” centroidal 

value for each census tract to a weighted (by probability) 

average of the liquefaction susceptibility class in non-zero 

liquefaction probability areas for each census tract. The 

liquefaction susceptibility map (used in the Hazus displacement 

calculations) and the Holzer and others method are both based 

on the same Quaternary geologic map. In addition to the change 

in liquefaction susceptibility input, the assumed uniform 

shallow depth to groundwater (5 feet) was modified to better 

reflect groundwater contour data provided by the California 

Geological Survey and used in the liquefaction probability 

assessment (Jones and others, 2017); in western Santa Clara 

County, groundwater depths of 16 feet have been assumed.

Because the custom probability data were only available 

for part of the study area, Hazus-estimated liquefaction 

probabilities were required for the remainder of the study 

region. This necessitated (1) a Hazus run that incorporated 

the custom (weighted) liquefaction susceptibility to produce 

appropriate displacements in the custom liquefaction study 

area, and (2) a second Hazus run incorporating the custom 

liquefaction probability data (overwriting the Hazus-estimated 

probabilities directly in Hazus’ SQL tables) and interrupting 

Hazus’ computational flow to avoid overwriting the various 
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 19

Figure 2. Map showing liquefaction susceptibility in the San Francisco Bay region, California. Data developed 

by the U.S. Geological Survey (based on Knudsen and others, 2000).

liquefaction hazard data tables. The building damage results 

produced by this second run were then manually scaled 

down by the proportion of development exposed to nonzero liquefaction probabilities to arrive at final losses for the 

developed areas. It should be noted that as a result of conducting 

part of the analysis outside of Hazus, the availability of Hazus 

results normally derived from the modified outputs became 

limited. That is, although we have estimated building damage 

and associated economic loss using the custom liquefaction 

probability, dependent impact estimates, such as casualties 

and shelter, are not available for the customized liquefaction 

assessment.

HayWired Landslide implementation in Hazus

Landslide displacement and probability data were 

provided for the HayWired mainshock for 10-m pixels in 

nine bay area Counties (McCrink and Perez, 2017): Alameda, 

Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa 

Clara, Solano, and Sonoma. The landslide probabilities are 

derived from the displacements, and are categorized as given 

in table 5.

Because the landslide hazard is so localized, census tractlevel representations did not adequately capture the highly variable 

and concentrated nature of the hazard. Accordingly, an alternate 

approach was taken whereby multiple Hazus runs were conducted, 

assuming various displacement/probability combinations, and 

the census tract results were weighted according to the pixel level 

data, outside of Hazus, as described below.

Six Hazus runs were conducted, each assuming uniform 

landslide displacement and probability values for a given category, 

as shown in table 5. These runs yielded loss results for each 

midpoint displacement and probability value, by census tract. 

The Hazus inventory was assumed to be uniformly distributed 

across each census tract (and contributing pixel) within the 

developed area, as defined by NLCD (Homer and others, 2015), 

discussed above. (Developed pixels with landslide displacements 

in Alameda, Marin and Santa Clara counties are shown in fig. 4.) 

The number of developed pixels in each displacement/probability 

range were counted for each census tract. The losses for the 

pixels in each bin were then obtained by multiplying the census 

MONTEREY

MERCED

YOLO

SONOMA

NAPA

STANISLAUS

SOLANO

SAN

JOAQUIN

SANTA

CLARA

MARIN

ALAMEDA

SAN

BENITO

SACRAMENTO

CONTRA

 COSTA

SAN

MATEO

SANTA CRUZ

SAN

FRANCISCO

124° 123° 122° 121° 120°

38°

37°

36°

Hazus study region boundary

County boundary

EXPLANATION

Liquefaction susceptibility

None/not mapped

Very low

Low

Moderate

High

Very high

0

0

20 40 60 80

20 40 60 80

MILES 

KILOMETERS 

PACIFIC

OCEAN

Coordinate System: GCS North American 1983

Datum: North American 1983

 Area 

of map CALIF
20 The HayWired Earthquake Scenario—Engineering Implications

Figure 3. Map showing liquefaction probabilities for the HayWired earthquake scenario 

mainshock computed using the Holzer and others (2008, 2010) method in developed areas of 

Alameda and Santa Clara Counties, California (data modified from Jones and others, 2017).

Oakland

San Jose

Alameda

Hayward

Fremont

Livermore

SAN

MATEO

SANTA

CLARA

ALAMEDA

CONTRA

COSTA

122°15' 122° 121°45'

37°45'

37°30'

37°15'

SAN FRANCISCO BAY

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N. 0 4 8 KILOMETERS

0 4 8 MILES

EXPLANATION

Liquefaction probability

>50 percent

Non-developed land

<5 percent

5–10 percent

10–20 percent

20–30 percent

30–40 percent

County boundary

Area where Holzer and others' (2008, 2010) methods are 

used to map liquefaction probability

40–50 percent

 Area 

of map

CALIF
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 21

Table 5. Landslide displacement categories and associated probability ranges for the HayWired 

earthquake scenario mainshock.

[Data modified from McCrink and Perez, 2017. cm, centimeters; L, low, M, medium, H, high, VH, very high]

Displacement 

range

(cm)

Displacement 

range

(inches)

Assumed landslide 

displacement

(inches)

Landslide 

probability 

category

Probability

range

Assumed 

probability

0–1 0.0–0.4 0.2 L 0.0–0.016 0.008

1–5 0.4–2.0 1.2 M 0.016–0.15 0.08

5–15 2.0–6.0 4.0 H 0.15–0.323 0.237

15–30 6.0–12.0 9.0 VH 0.323–0.335 0.329

30–100 12.0–39.0 25.5 VH 0.335 0.335

100+ 39.0–196 117.5 VH 0.335 0.335

Alameda

Oakland

122°15' 122°10'

37°50'

37°45'

Mill Valley

Sausalito

Belvedere

122°30'

37°55'

San Jose

121°50'

37°25'

A. Alameda County B. Marin County

C. Santa Clara County

0 1 2 KILOMETERS

0

SAN 

MATEO

ALAMEDA

San Jose

CONTRA

COSTA 1 2 MILES

A

C

B

Non-developed land from Multi-Resolution Land Characteristics

Consortium National Land Cover Dataset, 2015.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

EXPLANATION

Secondary roads

Major highways

2–15 percent (1–5 cm)

15–32 percent (5–15 cm)

>32 percent (>15 cm)

0–2 percent (0–1 cm)

Non-developed land

Landslide probability on developed land 

(corresponding displacement, in centimeters [cm])

San 

Francisco

Oakland

Figure 4. Map showing custom landslide probabilities for the HayWired earthquake scenario mainshock in developed areas 

of parts of Alameda (A), Marin (B), and Santa Clara Counties (C), California (data modified from McCrink and Perez, 2017).
22 The HayWired Earthquake Scenario—Engineering Implications

tract-level Hazus result for the bin by the number of pixels in the 

bin, divided by the total number of pixels in the developed area 

of the census tract. The landslide losses were then summed for 

each census tract. This method removed the influence of higher 

displacement estimates in undeveloped areas, assuming uniform 

distribution of building construction (consistent with the Hazus 

methodology). It should be noted, however, that the landslide data 

only pertain to landslide initiation, and do not capture damages 

downstream of landslides in other pixels.

As with the custom liquefaction data implementation, 

because we are conducting part of the landslide analysis 

outside of Hazus, the availability of Hazus results normally 

derived from the modified outputs become limited.

HayWired Mainshock Hazus Results

The final mainshock Hazus analyses may be summarized 

as follows:

• Shaking only

• Shaking and default liquefaction, with modified 

groundwater depth assumption (modified baseline 

default run)

• Shaking, custom liquefaction, and custom landslide 

(custom runs, combined)

A summary of the liquefaction and landslide data available 

by county is provided in table 6. As shown, no liquefaction or 

landslide data were available for the seven outlying counties 

(Merced, Monterey, Sacramento, San Benito, San Joaquin, 

Stanislaus and Yolo). Figure 5 displays the geographic distribution 

of hazards ultimately contributing to building damage for each 

census tract. It should be noted that the custom liquefaction 

data did not cover all census tracts in Alameda and Santa Clara 

Counties (see figs. 3, 5); default liquefaction results were used in 

census tracts not covered by the custom data.

Building damage estimates for the three versions of 

the HayWired scenario mainshock, as described above, are 

summarized in tables 7, 8, and 9 respectively, by county and 

Hazus building damage state. It should be noted that the data in 

tables 7 and 8 are taken directly from Hazus, whereas the data in 

table 9 are approximately derived from resulting distributions of 

building square footage by damage state, multiplied by Hazus’ 

damage state mean percentage loss assumptions and building 

exposure values. Best estimates of loss from shaking and default 

liquefaction have been taken directly from Hazus (tables 7, 8); 

best estimates of loss from the custom liquefaction and landslide 

analyses are taken from the approximate results derived from the 

square footage distributions (table 9). (Estimates of shaking and 

default liquefaction contributing to the values in table 9 may not 

exactly match those in table 8; differences between estimates taken 

directly from Hazus and those derived using the approximate 

square footage damage state distribution average 4 percent at the 

county level.) Table 10 provides the resultant county-level best 

estimates of building damage by hazard.

Table 6. Availability of liquefaction and landslide data for 

counties in the San Francisco Bay region, California.

[Y, yes. Shading indicates counties with no liquefaction or landslide data available]

County Liquefaction 

(default approach)

Liquefaction 

(custom approach) Landslide

Alameda Y1 Y Y

Contra Costa Y Y

Marin Y Y

Merced

Monterey

Napa Y Y

Sacramento

San Benito

San Francisco Y Y

San Joaquin

San Mateo Y Y

Santa Clara Y1 Y Y

Santa Cruz Y

Solano Y Y

Sonoma Y Y

Stanislaus

Yolo

1

Default liquefaction results were used for census tracts in Alameda and 

Santa Clara Counties not covered by the custom liquefaction data.

As noted above, exposure values and losses estimated using 

the custom bay area Hazus inventory data are in 2005 dollars. 

These values may be approximately escalated to 2016 dollars 

using the net CPI ratio of 1.23. Reported and tabulated dollar 

values have been stated in the native 2005 dollars to facilitate 

review and ease comparison.

As shown in the tables, the combined best estimate 

for liquefaction adds more than $4.6 billion to the building 

damage in this event (see table 10). Most of the losses caused 

by liquefaction occur in Alameda County ($3.1 billion), San 

Mateo County ($510 million), and Contra Costa County 

($460 million). Figure 6A shows the geographical distribution 

of Hazus building damage ratio estimates caused by shaking, 

while figure 6B shows the distribution of building damage ratios 

for liquefaction, estimated using the Hazus default liquefaction 

modeling approach and adjusted groundwater depths. 

The difference between default and custom liquefaction 

damage in Alameda and Santa Clara Counties reflect the 

differences in the liquefaction probability and estimated 

displacements at the census tract level. The default and custom 

probabilities are compared in Jones and others, 2017. The use 

of custom liquefaction probability data modestly increases 

liquefaction building damage estimates in Alameda County, 

impacting a broader area than the default approach, but 

substantially decreases damage estimates in Santa Clara County. 

The lower custom liquefaction probability estimates for Santa 

Clara County and southwest Alameda County are reflected in 

the lower damage ratios in the same areas in figure 6B and C.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 23

Figure 5. Map of hazards caused by the HayWired earthquake scenario mainshock contributing to 

building damage estimated for census tracts in the San Francisco Bay region, California.

Coordinate System: GCS North American 1983

Datum: North American 1983

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SAN JOAQUIN

SANTA CLARA

SOLANO

STANISLAUS

MARIN

SAN BENITO

MERCED

ALAMEDA

SACRAMENTO

CONTRA 

COSTA

SANTA CRUZ

SAN 

MATEO

SOLANO

SAN FRANCISCO

 123° 122° 121°

38°

37°

EXPLANATION

County boundary

Contributing Hazards

None

Shaking

Shaking + default liquefaction

Shaking + custom liquefaction

Shaking + landslide

Shaking + default liquefaction + landslide

Shaking + custom liquefaction + landslide

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

CALIF Area 

of maps
24 The HayWired Earthquake Scenario—Engineering Implications

Table 7. Building damage resulting from ground shaking caused by the HayWired earthquake 

scenario mainshock in counties of the San Francisco Bay region, California, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). Damage reported in 2005 dollars; U.S. Consumer 

Price Index 2016:2005 ratio is approximately 1.23]

County Slight Moderate Extensive Complete Total

(thousands of dollars)

Alameda 1,192,789 4,739,455 4,254,356 6,063,511 16,250,111

Contra Costa 742,250 1,867,978 1,200,315 1,560,538 5,371,081

Marin 133,432 126,505 20,149 1,843 281,929

Merced 4,987 1,800 118 2 6,907

Monterey 16,421 6,486 443 2 23,351

Napa 18,538 10,327 1,027 33 29,926

Sacramento 12,409 3,450 176 5 16,040

San Benito 8,435 6,852 1,985 1,387 18,658

San Francisco 585,608 842,303 183,617 25,099 1,636,626

San Joaquin 96,226 61,923 6,610 339 165,099

San Mateo 527,695 778,106 193,827 29,036 1,528,665

Santa Clara 1,272,221 2,314,206 810,956 245,904 4,643,287

Santa Cruz 53,518 31,126 3,179 137 87,960

Solano 86,575 67,398 9,408 782 164,163

Sonoma 20,810 7,291 475 6 28,582

Stanislaus 35,564 16,351 1,387 24 53,327

Yolo 5,069 1,514 84 0 6,667

Total 4,812,547 10,883,071 6,688,112 7,928,648 30,312,379

Table 8. Building damage resulting from ground shaking and default liquefaction caused by the HayWired 

earthquake scenario mainshock in counties of the San Francisco Bay region, California, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). Damage reported in 2005 dollars; U.S. Consumer 

Price Index 2016:2005 ratio is approximately 1.23]

County Slight Moderate Extensive Complete Total

(thousands of dollars)

Alameda 1,134,931 4,623,506 6,094,483 7,248,794 19,101,714

Contra Costa 733,337 1,857,355 1,496,618 1,741,030 5,828,340

Marin 132,990 127,445 44,173 16,077 320,686

Merced1 4,987 1,800 118 2 6,907

Monterey1 16,421 6,486 443 2 23,351

Napa 18,538 10,327 1,027 33 29,926

Sacramento1 12,409 3,450 176 5 16,040

San Benito1 8,435 6,852 1,985 1,387 18,658

San Francisco 582,164 846,023 332,753 116,177 1,877,116

San Joaquin1 96,226 61,923 6,610 339 165,099

San Mateo 518,759 780,983 520,077 222,057 2,041,877

Santa Clara2 1,253,336 2,307,609 1,440,357 636,429 5,637,731

Santa Cruz1 53,518 31,126 3,179 137 87,960

Solano 86,393 67,688 18,389 6,104 178,575

Sonoma 20,810 7,291 475 6 28,582

Stanislaus1 35,564 16,351 1,387 24 53,327

Yolo* 5,069 1,514 84 0 6,667

Total 4,713,887 10,757,729 9,962,334 9,988,603 35,422,556

1

Counties outside the areas of mapped liquefaction susceptibility.

2

Estimates reflect the dual groundwater depth assumption (16 feet in western Santa Clara County, 5 feet elsewhere) made for consistency with the custom liquefaction study
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 25

Table 9. Approximate building damage resulting from ground shaking, custom liquefaction, and landslide caused 

by the HayWired earthquake scenario mainshock in counties of the San Francisco Bay region, California.

[Damage reported in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23]

County Slight Moderate Extensive Complete Total

(thousands of dollars)

Alameda 1,134,930 4,567,748 6,805,683 7,654,758 20,163,118

Contra Costa 746,639 1,808,999 1,661,298 1,787,929 6,004,865

Marin 130,835 117,380 102,445 50,314 400,973

Merced 4,930 1,696 140 2 6,768

Monterey 15,883 6,078 486 2 22,449

Napa 17,625 9,258 1,313 168 28,364

Sacramento 11,651 3,138 193 4 14,986

San Benito 8,516 6,791 2,485 1,427 19,219

San Francisco 596,005 896,174 373,868 118,965 1,985,012

San Joaquin 95,074 58,211 7,898 318 161,500

San Mateo 525,836 767,512 545,032 225,213 2,063,593

Santa Clara 1,283,936 2,318,778 1,163,761 370,790 5,137,265

Santa Cruz 52,599 29,281 4,590 622 87,093

Solano 85,753 63,439 21,460 6,955 177,607

Sonoma 19,652 6,414 3,461 1,846 31,372

Stanislaus 34,412 15,045 1,561 20 51,037

Yolo 4,695 1,326 85 0 6,106

Total 4,768,971 10,677,268 10,695,759 10,219,333 36,361,327

Table 10. Total building damage from the HayWired earthquake scenario mainshock in counties of the San 

Francisco Bay region, California.

[Damage reported in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23. cm/s, centimeters per second; 

PGV, peak ground velocity. Shading indicates no estimated damage from liquefaction or landslide]

County Shaking Default 

liquefaction1

Custom 

liquefaction2

Combined 

best estimate 

liquefaction

Landslide

(within 20-cm/s 

PGV limit)

Combined 

best estimate 

building damage

(millions of dollars)

Alameda 16,250 2,852 3,057 3,081 147 19,478

Contra Costa 5,371 457 457 14 5,842

Marin 282 39 39 84 405

Merced 7 7

Monterey 23 23

Napa 30 0 0 0.4 30

Sacramento 16 16

San Benito 19 19

San Francisco 1,637 240 240 9 1,886

San Joaquin 165 165

San Mateo 1,529 513 513 9 2,051

Santa Clara 4,643 994 264 291 21 4,955

Santa Cruz 88 1 89

Solano 164 14 14 2 180

Sonoma 29 0 5 34

Stanislaus 53 53

Yolo 7 7

Total 30,313 5,109 3,321 4,635 292 35,240

1

With adjusted groundwater depth.

2

Limited to Holzer and others (2008, 2010) method study area.
26 The HayWired Earthquake Scenario—Engineering Implications

Figure 6. Maps showing building damage ratio by causative hazard for the HayWired earthquake scenario mainshock, San Francisco Bay 

region, California, estimated using Hazus (FEMA, 2012). A, Shaking only. B, Default liquefaction (applied where liquefaction computed using the 

Holzer and others [2008, 2010] method was not available). C, Liquefaction computed using the Holzer and others (2008, 2010) method. D, Landslide.

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

D. Landslide

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

38°

37°

C. Custom liquefaction

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

B. Default liquefaction

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

38°

37°

A. Shaking

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

>10%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

EXPLANATION

CALIF Area 

of maps

Coordinate System: GCS North American 1983

Datum: North American 1983

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 27

Landslide building damage, as estimated using the 

custom landslide hazard data, totals $291 million in the nine 

counties in which it was modeled, and is most substantial 

in Alameda County ($147 million) and Marin County 

($84 million). Census tract damage ratios resulting from 

landslide (fig. 6D) are generally modest, peaking at just 

3.3 percent versus 17.1 percent for custom liquefaction and 

45.6 percent for shaking. Figure 7 provides the best estimate 

census tract damage ratio map, combining damage from 

shaking, liquefaction (using custom data where available, 

default data elsewhere), and landslide.

McCrink and Perez (2017) report slope failure 

displacements and probabilities in areas of peak ground velocity 

of 20 centimeters per second (cm/s) and larger; their approach 

has more uncertainty in areas below that threshold. Results 

reported above are those within the 20 cm/s contour. Beyond the 

20 cm/s contour, an additional $145 million in damage could be 

expected, including $41 million in Marin, $27 million in each 

of San Francisco and Santa Clara counties, $20 million in San 

Mateo and $17 million in Sonoma counties.

As a reference point for comparison, the losses from 

the Loma Prieta earthquake were tallied by Holzer (1994) 

as $5.8 billion from shaking, $97 million from liquefaction 

and $30 million from landslides. Loma Prieta earthquake 

landslide losses were 0.5 percent of shaking losses compared 

to 1 percent (or 1.5 percent for the whole area) estimated for 

the HayWired earthquake scenario. Loma Prieta liquefaction 

losses were 1.5 percent of shaking losses, compared to 

15 percent estimated for the HayWired earthquake scenario. 

The higher liquefaction losses for the HayWired earthquake 

scenario are attributed to the developed areas affected by 

liquefaction in close proximity to the fault in Alameda County.

In addition to the summary data provided here, detailed 

results were generated for use by other HayWired researchers, 

including the following:

• The distribution of square footage across the various 

Hazus damage states by Hazus occupancy class 

and census tract, for the combined liquefaction and 

landslide mainshock assessment

• Estimated economic loss associated with building 

damage, by occupancy and county, for the combined 

liquefaction and landslide mainshock assessment

Liquefaction Modeling in Selected 

HayWired Aftershocks

Because the custom liquefaction data were only available 

in Alameda and Santa Clara Counties, and not available for 

the other counties potentially subject to liquefaction (Marin, 

Sonoma, Napa, Solano, Contra Costa, San Mateo, and San 

Francisco) and because custom liquefaction and landslide 

hazard data were only developed for the mainshock, it was 

decided that the focus of the comparative studies of building 

damage in the various aftershocks would primarily be damage 

resulting from ground shaking alone. However, to allow for 

selected comparisons of loss resulting from liquefaction and 

repeated liquefaction, several of the aftershocks were analyzed 

both for shaking only and for shaking and default liquefaction, 

including the M5.98 Mountain View, M6.4 Cupertino, 

and M5.42 Oakland aftershocks. A comparison of damage 

estimates for the mainshock and three selected aftershocks, 

with and without liquefaction assessed using the Hazus default 

approach and the original uniform depth to groundwater 

assumption, is provided in table 11. As noted above, in the 

mainshock, liquefaction is estimated to add approximately 

$5.1 billion in building damage (an additional 17 percent), 

whereas in the selected aftershocks, liquefaction adds between 

$78 million (an additional 15 percent) in the M5.42 Oakland 

aftershock and $218 million (an additional 9 percent) in the 

M6.4 Cupertino aftershock.

Ground Shaking Results for the 

HayWired Earthquake Sequence

Economic loss resulting from building damage caused by 

ground shaking has been estimated for each aftershock, as was 

done for the mainshock. Because Hazus is not able to estimate 

additional damage to damaged buildings, the mainshock and 

aftershocks have been modeled as independent events. That 

is, for each event, the building inventory is assumed to be in 

an undamaged state at the time of the earthquake; previous 

damage resulting from the mainshock or preceding aftershocks 

is not considered. The results of the Hazus analyses are 

summarized in table 12.

As shown in table 12, damage in each of the aftershocks is 

at least an order of magnitude smaller than that of the mainshock. 

The aftershocks that result in the largest economic losses from 

regional building damage are the M6.4 Cupertino ($2.48 billion 

in building damage), M6.2 Palo Alto ($1.37 billion in building 

damage), M5.98 Mountain View ($890 million in building 

damage), and M5.42 Oakland ($510 million in building damage) 

events. The total direct economic losses resulting from these 

aftershocks are $3.81 billion (M6.4 Cupertino), $2.11 billion 

(M6.2 Palo Alto), $1.38 billion (M5.98 Mountain View), and 

$780 million (M5.42 Oakland). For comparison, FEMA’s initial 

estimate of expected damage and loss in the 2014 M6.0 South 

Napa earthquake (including liquefaction), generated using 

the same inventory data as that used to model the HayWired 

earthquake scenario and its aftershocks, totaled $347 million 

in building damage and $575 million in total direct economic 

losses related to building damage (Doug Bausch, written 

commun., Federal Emergency Management Agency, 2014). The 

expected damage in the South Napa event is smaller than the 

four largest HayWired aftershocks, but larger than the remaining 

12 aftershocks. In terms of building damage ratio (defined in 

Hazus as the ratio of repair to replacement cost), the South Napa 

earthquake simulation had an overall building damage ratio of 
28 The HayWired Earthquake Scenario—Engineering Implications

Figure 7. Map showing best estimate building damage ratio for the HayWired earthquake scenario 

mainshock, San Francisco Bay region, California, considering liquefaction computed using the Holzer 

and others (2008, 2010) method and landslide data, where available (Jones and others, 2017; McCrink 

and Perez, 2017).

Coordinate System: GCS North American 1983

Datum: North American 1983

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SAN JOAQUIN

SANTA CLARA

SOLANO

STANISLAUS

MARIN

SAN BENITO

MERCED

ALAMEDA

SACRAMENTO

CONTRA 

COSTA

SANTA CRUZ

SAN 

MATEO

SAN FRANCISCO

123° 122° 121°

38°

37°

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

>10%

Best estimate building 

damage ratio

(damage divided by replacement 

value, expressed as a percent)

EXPLANATION

County boundary

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

CALIF Area 

of maps
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 29

HayWired scenario event

Structural 

damage

Nonstructural 

damage

Total 

building 

damage1

Building 

damage 

ratio2

(percent)

Content 

damage

Inventory 

loss

Building 

damage-related 

income loss

Total direct 

economic 

loss

(millions of dollars) (millions of dollars)

Mainshock shaking only 5,817.2 24,495.2 30,312.4 2.91 8,003.0 305.6 8,012.7 46,633.7

Mainshock shaking + liq. 7,037.5 28,419.5 35,457.0 3.40 9,232.8 376.8 9,059.4 54,126.0

Mainshock liq. loss 1,220.3 3,924.3 5,144.6 0.49 1,229.8 71.2 1,046.7 7,492.3

CU64 shaking only 333.3 2,145.2 2,478.5 0.24 888.3 35.9 405.2 3,807.9

CU64 shaking + liq. 382.9 2,313.5 2,696.4 0.26 948.0 40.0 455.6 4,139.9

CU64 liq. loss 49.6 168.3 217.9 0.02 59.7 4.1 50.4 332.0

MV598 shaking 81.1 813.2 894.3 0.09 382.4 22.3 82.4 1,381.4

MV598 shaking + liq. 104.5 892.7 997.2 0.10 410.0 24.1 105.6 1,536.9

MV598 liq. loss 23.4 79.5 102.9 0.01 27.6 1.8 23.2 155.5

OK542 shaking 32.6 476.8 509.4 0.05 237.3 9.3 24.0 780.0

OK542 shaking + liq. 51.1 536.3 587.3 0.06 256.3 10.2 42.4 896.3

OK542 liq. loss 18.5 59.5 77.9 0.01 19.0 0.9 18.4 116.3

1

Total of structural and nonstructural damage.

2

Ratio of repair to replacement cost, calculated as the total estimated building damage divided by the total building replacement value (as defined in Hazus).

[Data from Hazus (Federal Emergency Management Agency, 2012). See table 1 for explanation of aftershock short names and magnitudes. Damage reported in 

2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23. liq., liquefaction. Shading indicates net loss from the liquefaction hazard]

Table 11. Direct economic losses from the HayWired earthquake scenario mainshock and selected aftershocks, with and without 

default liquefaction, San Francisco Bay region, California, estimated using Hazus.

Table 12. Direct economic losses from ground shaking caused by the HayWired earthquake scenario mainshock and aftershock 

sequence, San Francisco Bay region, California, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). See table 1 for explanation of aftershock short names and magnitudes. Damage reported in 

2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23]

HayWired scenario event

Structural 

damage

Nonstructural 

damage

Total 

building 

damage1

Building 

damage 

ratio2

(percent)

Content 

damage

Inventory 

loss

Building 

damage-related 

income loss

Total direct 

economic 

loss

(millions of dollars) (millions of dollars)

Mainshock 5,817.2 24,495.2 30,312.4 2.91 8,003.0 305.6 8,012.7 46,633.7

UC523 14.9 333.5 348.4 0.03 176.2 12.4 8.2 545.2

SP504 5.6 100.7 106.3 0.01 50.4 1.3 3.7 161.7

FF558 1.1 21.5 22.6 0.00 10.5 0.5 0.6 34.1

FR510 5.9 100.4 106.3 0.01 48.1 3.7 3.1 161.2

OK542 32.6 476.8 509.4 0.05 237.3 9.3 24.0 780.0

PA62 159.9 1,207.6 1,367.5 0.13 525.4 23.6 193.7 2,110.2

MP552 8.4 142.9 151.3 0.01 71.2 2.6 6.9 232.1

AT511 9.2 129.5 138.8 0.01 59.1 2.5 6.0 206.4

PA569 27.3 326.6 353.8 0.03 157.1 7.1 25.7 543.9

PA522 13.3 338.4 351.7 0.03 182.7 7.0 9.1 550.4

PA526 16.7 239.0 255.7 0.02 113.4 5.2 12.1 386.4

MV598 81.1 813.2 894.3 0.09 382.4 22.3 82.4 1,381.4

CU64 333.3 2,145.2 2,478.5 0.24 888.3 35.9 405.2 3,807.9

SV535 32.7 255.8 288.5 0.03 102.2 6.1 23.9 420.7

SC509 14.6 210.3 224.8 0.02 101.6 5.1 10.2 341.8

PA501 6.1 65.6 71.7 0.01 27.1 1.3 3.9 104.0

1

Total of structural and nonstructural damage.

2

Ratio of repair to replacement cost, calculated as the total estimated building damage divided by the total building replacement value (as defined in Hazus).
30 The HayWired Earthquake Scenario—Engineering Implications

0.16 percent, similar to the M6.2 Palo Alto aftershock’s damage 

ratio of 0.13 percent.

Regional building damage patterns, in terms of census tract 

level building damage ratios (total estimated building damage for 

each census tract divided by total building replacement value), 

are mapped in figures 8–11. As shown, the aftershocks with the 

largest losses also show the broadest damage ratio patterns and the 

highest maximum damage ratios.

Building damage is summarized by structural system or 

Hazus’ MBTs (see table 4 for definitions), grouped across building 

height classes, in tables 13 and 14; table 13 provides building 

damage in terms of economic losses (in millions of dollars), 

and table 14 provides the results in terms of building damage 

ratio. Although wood frame construction (MBT W1 and W2) 

makes up the bulk of the exposure (69 percent of exposure, see 

also table 4), damage to this type of construction makes up a 

smaller percentage of the losses (47 percent in the mainshock, 

and between 45 and 56 percent in the aftershocks). Conversely, 

the more vulnerable building types represent larger proportions 

of loss than exposure, including URM (2 percent of exposure, 

6 percent of loss in the mainshock, and as much as 8 percent in 

the M5.42 Oakland aftershock), concrete frame with URM infill 

walls (MBT C3—1 percent of exposure, 5 percent of loss in the 

mainshock, and 2–3 percent of loss in the aftershocks), and steel 

frame with URM infill walls (MBT S5—1 percent of exposure, 

5 percent of loss in the mainshock, and 2–4 percent of loss in the 

aftershocks). This vulnerability is further demonstrated by the 

damage ratios tabulated in table 14; S5, C3, and URM are among 

the MBTs with the largest net damage ratios in the mainshock 

(14, 10, and 7 percent, respectively), along with mobile homes 

(MH—9 percent) and light steel frame (S3—9 percent). Damage 

ratios in the aftershocks are generally two orders of magnitude 

smaller than those of the mainshock, except for the larger 

aftershocks (M6.2 Palo Alto, M5.98 Mountain View, and M6.4 

Cupertino), where the ratios tend to be just one order of magnitude 

smaller than the mainshock. Concentrations of vulnerable building 

types may also result in higher damage ratios from a nearby 

aftershock, such as (1) precast concrete tilt-up wall structures 

(PC1) with a higher damage ratio in the M5.23 Union City 

aftershock than the other M5 aftershocks and (2) S3, S5, and URM 

damage in the M5.42 Oakland aftershock. Building exposure 

(in thousands of dollars) for tilt-up structures (PC1) and low-rise 

URM is mapped in figure 12, highlighting the concentrations of 

these vulnerable buildings near the epicenters of the M5.23 Union 

City and M5.42 Oakland aftershocks.

Unreinforced Masonry Construction

It should be noted that the MBT damage ratios given 

in table 14 represent net damage across the entire 17-county 

study area and include damage for all MBT subclasses (that is, 

subclasses by height and seismic design level); localized damage 

and damage ratios for MBT subclasses may be substantially 

different. For example, for all URM construction (URML and 

URMM), the net damage ratio in the mainshock is 7 percent, but 

census tract damage ratios for pre-code (unretrofitted), low-rise 

URM (URML) range from 0 to 94 percent. Damage to this 

subclass of URM building represents 60 percent of the URM 

damage but just 24 percent of the building square footage. Census 

tract damage ratio maps for pre-code URML construction for the 

mainshock and three of the more damaging aftershocks (M6.4 

Cupertino, M6.2 Palo Alto, and M5.42 Oakland) are provided 

in figure 13. In the mainshock, pre-code URML damage ratios 

in Alameda and Contra Costa Counties are substantial, with 

51 percent of census tracts in these two counties having damage 

ratios exceeding 50 percent. Total loss for pre-code URML in 

the mainshock is $885 million, whereas losses in the selected 

aftershocks are $20.5 million (M6.4 Cupertino), $15.7 million 

(M6.2 Palo Alto), and $17.4 million (M5.42 Oakland)—2.3, 1.8, 

and 2.0 percent of the mainshock loss, respectively. Damage 

ratios in the selected aftershocks are lower than the mainshock 

(all are less than 25 percent), and damage is more localized. 

A small pocket of census tracts has damage ratios between 15 

and 25 percent in Santa Clara County in the M6.4 Cupertino 

aftershock, and a smaller pocket of tracts with damage ratios 

between 5 and 10 percent are on the border of Santa Clara and 

San Mateo Counties in the M6.2 Palo Alto aftershock, and census 

tract damage ratios do not exceed 5 percent in the M5.42 Oakland 

aftershock.

As noted previously, Hazus is not able to estimate additional 

damage to damaged buildings; each analysis conducted for 

this study is independent and assumes that the inventory is in 

an undamaged condition before the earthquake. Given that 

the aftershocks may, in reality, cause damage in areas already 

substantially damaged, it is instructive to examine the URM 

damage results more closely. To assess whether adding the 

aftershock damage to the mainshock damage would result in 

overestimating damage to substantially damaged structures, 

individual census tract level results in the mainshock and the 

aftershocks were reviewed.

At the most basic level, the sum of losses in multiple events 

should not exceed the value of the exposed inventory, assuming 

no repair between events. For pre-code URML, building damage 

in the mainshock represents 18.5 percent of exposure, with a 

maximum census tract damage ratio of 93.8 percent. After adding 

the damage from all aftershocks, the total building damage 

ratio is 20.4 percent, with a maximum census tract damage of 

96.4 percent. Fortunately, for the simulated aftershock sequence, 

census tracts with the largest damage to pre-code URML buildings 

in the aftershocks are not the same as those tracts with substantial 

damage in the mainshock. At the census tract level, the sum of 

economic losses from building damage to pre-code URML in the 

HayWired mainshock and all of its aftershocks does not exceed 

the building’s exposure value.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 31

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

D. M 5.10 Fremont

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

38°

37°

C. M 5.58 Fairfield

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

B. M 5.04 San Pablo

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

38°

37°

A. M 5.23 Union City

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

Epicenter

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of maps

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

Figure 8. Maps showing building damage ratio for HayWired earthquake scenario aftershocks 1–4 (table 1), San Francisco Bay region, 

California, estimated using Hazus (FEMA, 2012): A, magnitude (M) 5.23 Union City; B, M 5.04 San Pablo; C, M 5.58 Fairfield; and D, M 5.10 Fremont.
32 The HayWired Earthquake Scenario—Engineering Implications

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

38°

37°

36°

D. M 5.11 Atherton

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

38°

37°

36°

C. M 5.52 Menlo Park

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

38°

37°

B. M 6.2 Palo Alto

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

123° 122° 121°

38°

37°

36°

A. M 5.42 Oakland

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

Epicenter

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of maps

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

Figure 9. Maps showing building damage ratio for HayWired earthquake scenario aftershocks 5–8 (table 1), San Francisco Bay region, 

California, estimated using Hazus (FEMA, 2012): A, magnitude (M) 5.42 Oakland; B, M6.2 Palo Alto; C, M5.52 Menlo Park; and D, M5.11 Atherton.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 33

Figure 10. Maps showing building damage ratio for HayWired earthquake scenario aftershocks 9–12 (table 1), San Francisco Bay region, California, 

estimated using Hazus (FEMA, 2012): A, magnitude (M) 5.69 Palo Alto; B, M5.22 Palo Alto; C, M5.26 Palo Alto; and D, M5.98 Mountain View.

PACIFIC

OCEAN

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

38°

37°

36°

D. M 5.98 Mountain View

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

38°

37°

36°

C. M 5.26 Palo Alto

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

123° 122° 121°

38°

37°

36°

B. M 5.22 Palo Alto

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

123° 122° 121°

38°

37°

36°

A. M 5.69 Palo Alto

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

Epicenter

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of maps
34 The HayWired Earthquake Scenario—Engineering Implications

Figure 11. Maps showing building damage ratio for HayWired earthquake scenario aftershocks 13–16 (table 1), San Francisco Bay region, 

California, estimated using Hazus (FEMA, 2012): A, magnitude (M) 6.4 Cupertino; B, M5.35 Sunnyvale; C, M5.09 Santa Clara; and D, M5.01 Palo Alto.

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

38°

37°

36°

D. M 5.01 Palo Alto

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

38°

37°

36°

C. M 5.09 Santa Clara

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MERCED

SAN BENITO

MARIN

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

123° 122° 121°

38°

37°

36°

B. M 5.35 Sunnyvale

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

38°

37°

A. M 6.4 Cupertino

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

Epicenter

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of maps

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 35

Table 13. Building damage by model building type from ground shaking caused by the HayWired earthquake scenario mainshock and 

aftershock sequence, San Francisco Bay region, California, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). See table 4 for definitions of Hazus model building types (MBT). See table 1 for explanation of aftershock short names and magnitudes. Damage in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23]

[Data from Hazus (Federal Emergency Management Agency, 2012). See table 4 for definitions of Hazus model building types (MBT). See table 1 for explanation of aftershock short names and magnitudes]

MBT

Building damage (millions of dollars)

Mainshock

UC523

SP504

FF558

FR510

OK542

PA62

MP552

AT511

PA569PA522PA526

MV598

CU64

SV535SC509

PA501

C1 636 3.6 0.9 0.2 1.1 3.7 26.7 1.8 1.3 5.7 3.5 2.9 15.8 53.9 4.6 2.7 0.7

C2 2,095 29.1 9.0 2.2 10.8 35.1 127.7 15.5 14.0 35.8 34.6 25.6 89.5 207.7 28.9 25.5 7.7

C3 1,580 5.3 3.0 0.6 1.8 13.9 41.7 4.2 3.6 8.9 7.9 6.2 22.3 67.5 6.2 5.7 1.7

MH 667 5.8 1.7 0.5 2.5 5.6 18.1 2.0 2.1 5.6 4.1 3.5 14.8 34.1 5.5 4.1 1.5

PC1 788 25.8 2.4 1.2 9.8 16.0 57.1 5.5 6.0 17.4 15.4 12.4 54.2 97.4 21.0 14.6 4.0

PC2 158 3.2 0.5 0.2 1.3 2.0 9.8 0.8 0.9 2.7 2.3 1.8 8.2 18.1 2.9 2.1 0.5

RM1 1,814 30.1 7.2 1.8 9.6 30.8 103.6 12.9 11.6 30.0 31.8 22.1 76.9 175.9 24.3 20.9 6.1

RM2 271 4.7 1.1 0.3 1.5 5.1 17.4 1.9 1.8 5.0 4.6 3.5 12.9 29.6 4.5 3.5 1.0

S1 2,257 16.3 3.3 1.0 5.2 17.9 105.3 7.3 5.3 21.9 14.2 10.8 63.3 185.0 14.4 9.7 2.6

S2 973 17.1 2.8 0.7 6.1 14.4 57.6 5.3 4.6 15.5 13.0 10.1 43.3 98.6 13.2 9.6 2.7

S3 843 9.9 2.2 0.6 3.2 12.9 33.9 3.6 3.6 8.6 7.7 6.3 24.2 51.8 7.9 5.9 2.1

S4 514 4.9 1.4 0.3 1.7 6.1 22.5 2.3 2.0 5.7 5.3 3.9 14.8 39.6 4.6 3.8 1.0

S5 1,561 6.3 2.9 0.6 2.0 20.2 32.5 4.2 3.6 7.7 8.6 5.9 19.9 42.2 4.1 3.9 1.6

URM 1,793 10.0 4.8 0.6 2.3 41.1 35.6 4.2 4.4 8.3 9.3 7.3 21.7 47.2 6.5 5.1 2.1

W1 11,329 135.7 51.2 9.5 36.6 229.1 534.6 61.6 58.6 135.0 145.4 104.2 311.7 1,102.0 112.4 83.7 29.0

W2 3,034 40.6 11.7 2.1 10.7 55.5 143.3 18.1 15.5 40.1 43.9 29.1 100.5 227.8 27.6 23.9 7.4

Total 30,312 348.4 106.3 22.6 106.3 509.4 1,367.5 151.3 138.8 353.8 351.7 255.7 894.3 2,478.5 288.5 224.8 71.7

MBT

Building damage ratio1 (percent)

Mainshock

UC523

SP504

FF558

FR510

OK542

PA62

MP552

AT511

PA569PA522PA526

MV598

CU64

SV535SC509

PA501

C1 5 0.03 0.01 0.00 0.01 0.03 0.20 0.01 0.01 0.04 0.03 0.02 0.12 0.41 0.03 0.02 0.01

C2 3 0.05 0.01 0.00 0.02 0.06 0.21 0.03 0.02 0.06 0.06 0.04 0.15 0.34 0.05 0.04 0.01

C3 10 0.03 0.02 0.00 0.01 0.09 0.27 0.03 0.02 0.06 0.05 0.04 0.14 0.43 0.04 0.04 0.01

MH 9 0.07 0.02 0.01 0.03 0.07 0.23 0.03 0.03 0.07 0.05 0.05 0.19 0.44 0.07 0.05 0.02

PC1 4 0.13 0.01 0.01 0.05 0.08 0.28 0.03 0.03 0.09 0.08 0.06 0.27 0.48 0.10 0.07 0.02

PC2 3 0.06 0.01 0.00 0.02 0.04 0.17 0.01 0.02 0.05 0.04 0.03 0.15 0.32 0.05 0.04 0.01

RM1 3 0.05 0.01 0.00 0.02 0.05 0.16 0.02 0.02 0.05 0.05 0.03 0.12 0.28 0.04 0.03 0.01

RM2 3 0.06 0.01 0.00 0.02 0.06 0.21 0.02 0.02 0.06 0.05 0.04 0.15 0.35 0.05 0.04 0.01

S1 5 0.04 0.01 0.00 0.01 0.04 0.24 0.02 0.01 0.05 0.03 0.03 0.15 0.43 0.03 0.02 0.01

S2 4 0.07 0.01 0.00 0.03 0.06 0.24 0.02 0.02 0.07 0.05 0.04 0.18 0.42 0.06 0.04 0.01

S3 9 0.11 0.02 0.01 0.04 0.14 0.38 0.04 0.04 0.10 0.09 0.07 0.27 0.58 0.09 0.07 0.02

S4 3 0.03 0.01 0.00 0.01 0.04 0.15 0.02 0.01 0.04 0.04 0.03 0.10 0.27 0.03 0.03 0.01

S5 14 0.06 0.03 0.01 0.02 0.18 0.29 0.04 0.03 0.07 0.08 0.05 0.18 0.37 0.04 0.03 0.01

URM 7 0.04 0.02 0.00 0.01 0.17 0.15 0.02 0.02 0.03 0.04 0.03 0.09 0.20 0.03 0.02 0.01

W1 2 0.02 0.01 0.00 0.01 0.04 0.08 0.01 0.01 0.02 0.02 0.02 0.05 0.17 0.02 0.01 0.00

W2 3 0.05 0.01 0.00 0.01 0.06 0.16 0.02 0.02 0.05 0.05 0.03 0.11 0.26 0.03 0.03 0.01

Table 14. Building damage ratio by model building type from ground shaking caused by the HayWired earthquake scenario mainshock and 

aftershock sequence, San Francisco Bay region, California, estimated using Hazus.

1

Ratio of repair to replacement cost, calculated as the total estimated building damage divided by the total building replacement value (as defined in Hazus).
36 The HayWired Earthquake Scenario—Engineering Implications

Figure 12. Maps showing building exposure value in census tracts in the vicinity of two HayWired 

earthquake scenario aftershocks, San Francisco Bay region, California. A, Precast concrete tilt-up wall 

buildings (PC1). B, Low-rise unreinforced masonry buildings (URML). Values are in 2005 dollars; U.S. 

Consumer Price Index 2016:2005 ratio is approximately 1.23. M, magnitude.

123° 122°

38°

37.5°

37.5°

38°

EXPLANATION

M5.23 Union City 

aftershock epicenter

M 5.42 Oakland 

aftershock epicenter

County boundary

Exposure ($1,000)

<20,000

20,000–50,000

50,000–75,000

75,000–100,000

>100,000

A. PC1

B. URML

PACIFIC

OCEAN

PACIFIC

OCEAN

SAN FRANCISCO BAY

SAN FRANCISCO BAY

Coordinate System: GCS North American 1983

Datum: North American 1983

 Area 

of map CALIF

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 5 10 15 20 25 KILOMETERS

0 5 10 15 20 25 MILES
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 37

PACIFIC

OCEAN

ALAMEDA

SANTA CLARA

SOLANO

MARIN

CONTRA COSTA

SAN MATEO

SANTA CRUZ

SONOMA NAPA

SAN FRANCISCO

SACRAMENTO

MONTEREY

122.5° 122°

38°

37°

D. M 5.42 Oakland

0 4 8 12 16 MILES

0 4 8 12 16 KILOMETERS

CALIF Area 

of map

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

SAN 

JOAQUIN CONTRA

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO SACRAMENTO

38°

37°

 123° 122°

C. M 6.2 Palo Alto

0 30 45

45

15 60 MILES

0 15 30 60 KILOMETERS

CALIF Area 

of map

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

38°

37°

B. M 6.4 Cupertino

0 30 45

45

15 60 MILES

0 15 30 60 KILOMETERS

CALIF Area 

of map

PACIFIC

OCEAN

ALAMEDA

SANTA CLARA

SOLANO

MARIN

CONTRA COSTA

SAN MATEO

SANTA CRUZ

SONOMA NAPA

SAN FRANCISCO

SACRAMENTO

MONTEREY

122.5° 122°

38°

37°

A. Mainshock

0 4 8 12 16 MILES

0 4 8 12 16 KILOMETERS

CALIF Area 

of map

<1%

1–5%

5–10%

10–15%

15–25%

25–50%

50–100%

URML-PC building 

damage ratio

(damage divided by 

replacement value, 

expressed as a percent)

County boundary

Epicenter

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

Figure 13. Maps showing building damage ratio for pre-code low-rise unreinforced masonry (URML-PC) for the HayWired 

earthquake scenario mainshock and selected aftershocks, San Francisco Bay region, California, estimated using Hazus (FEMA, 

2012): A, Mainshock; B, magnitude (M) 6.4 Cupertino aftershock; C, M6.2 Palo Alto aftershock; and D, M5.42 Oakland aftershock.
38 The HayWired Earthquake Scenario—Engineering Implications

Table 15. Casualties from ground shaking caused by the HayWired earthquake scenario mainshock and aftershock sequence, San 

Francisco Bay region, California, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). See “Population Impacts: Casualties” section for definitions of casualty severity levels. 

Shading indicates simulated time of occurrence for each event. See table 1 for explanation of aftershock short names and magnitudes]

Time of day Casualty severity

Number of casualties

Mainshock

U523

SP504

FF558

FR510

OK542

PA62

MP552

AT511

PA569PA522PA526

MV598

CU64

SV535SC509

PA501

Day (2 p.m.) Level 1 12,263 13 6 1 6 31 168 9 9 28 13 17 89 323 32 15 6

Level 2 3,007 0 0 0 0 1 13 0 0 1 1 1 6 28 1 0 0

Level 3 461 0 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0

Level 4 837 0 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0

Total 16,568 13 6 1 6 32 183 9 9 29 14 18 95 355 33 15 6

Night (2 a.m.) Level 1 7,827 14 7 1 5 36 146 8 8 28 12 15 76 327 33 14 5

Level 2 1,512 0 0 0 0 1 9 0 0 1 0 0 3 22 1 0 0

Level 3 179 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0

Level 4 340 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0

Total 9,858 14 7 1 5 37 155 8 8 29 12 15 79 351 34 14 5

Commute (5 p.m.) Level 1 10,600 12 5 1 5 29 151 7 8 25 12 14 79 309 30 13 5

Level 2 2,966 0 0 0 0 1 17 0 0 2 0 1 8 37 2 0 0

Level 3 1,300 0 0 0 0 0 10 0 0 1 0 0 6 22 3 0 0

Level 4 834 0 0 0 0 0 3 0 0 0 0 0 1 6 0 0 0

Total 15,700 12 5 1 5 30 181 7 8 28 12 15 94 374 35 13 5

Population Impacts—Casualties

The Hazus methodology estimates indoor and outdoor 

casualties by MBT as a function of each building’s damage 

state. Casualties are estimated at four severity levels as follows 

(FEMA, 2012):

• Severity level 1—“Injuries requiring basic medical aid 

that could be administered by paraprofessionals. These 

types of injuries would require bandages or observation. 

Some examples are: a sprain, a severe cut requiring 

stitches, a minor burn (first degree or second degree on 

a small part of the body), or a bump on the head without 

loss of consciousness. Injuries of lesser severity that 

could be self treated are not estimated by Hazus.”

• Severity level 2—“Injuries requiring a greater degree 

of medical care and use of medical technology such as 

x-rays or surgery, but not expected to progress to a life 

threatening status. Some examples are third degree burns 

or second degree burns over large parts of the body, a 

bump on the head that causes loss of consciousness, 

fractured bone, dehydration or exposure.”

• Severity level 3—“Injuries that pose an immediate 

life threatening condition if not treated adequately 

and expeditiously. Some examples are: uncontrolled 

bleeding, punctured organ, other internal injuries, 

spinal cord injuries, or crush syndrome.”

• Severity level 4—“Instantaneously killed or mortally 

injured.”

The breakdown of Hazus-estimated casualties by severity 

level for the mainshock and each aftershock, for each time of 

day modeled (day, 2 p.m.; night, 2 a.m.; and commute, 5 p.m.), 

is provided in table 15. The HayWired scenario mainshock 

has been modeled as a daytime event occurring at 4:18 p.m.; 

occurrence times for the aftershocks were given in table 1. 

Results in table 15 have been shaded for the time of day closest 

to the modeled occurrence times for each event. Casualties 

in the aftershocks are as much as three orders of magnitude 

smaller than those in the mainshock. Expected casualties in 

most aftershocks are minor (primarily severity level 1 with 

some severity level 2), with the exception of the M6.2 Palo 

Alto and M6.4 Cupertino aftershocks, which also result in a few 

serious injuries (Severity Level 3) or deaths (Severity Level 4).

Population Impacts—Displacement 

and Shelter Requirements

The Hazus shelter model allows users to estimate the 

number of displaced households caused by residential building 

damage and resulting habitability, and the number of people 

seeking public short-term shelter. The number of displaced 

households is derived from the estimated distribution of singlefamily homes and multifamily residential buildings across the 
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 39

Hazus building damage states combined with weighting factors 

(or displacement probabilities) for households residing in 

buildings in each of the various damage states, given in table 16. 

The Hazus model for the number of people seeking publiclyprovided, short-term shelter recognizes that only a portion of 

displaced households will actually use public shelter resources; 

the model uses population data and weighting factors, which 

reflect the income, ethnicity, ownership, and age of the residents 

in the displaced households to estimate the fraction expected to 

seek public shelter (for additional details, refer to chapter 14 of 

the Hazus Technical Manual; FEMA, 2012.). It should be noted, 

however, that the default values for the age and ownership 

weighting factors are set to zero, effectively removing these 

factors from consideration, as shown in table 17.

Table 18 provides the Hazus estimates of displaced 

households and people seeking shelter for the HayWired scenario 

mainshock and each of the aftershocks. These results reflect the 

shelter impacts related to ground shaking only (liquefaction is 

not included) and were estimated using the Hazus default shelter 

model parameters. Expected household displacement in the 

aftershocks is generally minimal, except in the four larger events.

Custom shelter parameters were developed for the 

ShakeOut scenario (Jones and others, 2008), based on 

available population survey data from the 1994 Northridge and 

other California earthquakes (Seligson, 2008), as described in 

the appendix. The default Hazus parameters and the modified 

parameters used in the ShakeOut analysis are provided in 

table 19. Adjustments included modifying the parameters for 

the percentage of households seeking shelter based on building 

damage state to include some shelter-seeking behavior for 

occupants of moderately damaged residential structures 

(normally set to zero in the Hazus default) and modifications 

Table 16. Default damage state factors for the Hazus population displacement model.

Model 

parameter Description Default value

WSFM Displacement weight for single-family homes in the moderate damage state 0.0

WSFE Displacement weight for single-family homes in the extensive damage state 0.0

WSFC Displacement weight for single-family homes in the complete damage state 1.0

WMFM Displacement weight for multifamily residences in the moderate damage state 0.0

WMFE Displacement weight for multifamily residences in the extensive damage state 0.9

WMFC Displacement weight for multifamily residences in the complete damage state 1.0

Table 17. Default weighting and modification factors for the Hazus short-term shelter model. 

Model 

parameter Description Default value

AW Age weighting factor 0

EW Ethnicity weighting factor 0.27

IW Income weighting factor 0.73

OW Ownership weighting factor 0

AM1 Modification factor for percentage of population under 16 years old 0.4

AM2 Modification factor for percentage of population between 16 and 65 years old 0.4

AM3 Modification factor for percentage of population over 65 years old 0.4

EM1 Modification factor for ethnicity: White households 0.24

EM2 Modification factor for ethnicity: Black households 0.48

EM3 Modification factor for ethnicity: Hispanic households 0.47

EM4 Modification factor for ethnicity: Asian households 0.26

EM5 Modification factor for ethnicity: Native American households 0.26

IM1 Modification factor for household income <$10,000 0.62

IM2 Modification factor for household income $10,000–$15,000 0.42

IM3 Modification factor for household income $15,000–$25,000 0.29

IM4 Modification factor for household income $25,000–$35,000 0.22

IM5 Modification factor for household income >$35,000 0.13

OM1 Modification factor for percentage of households that are owner occupied 0.4

OM2 Modification factor for percentage of households that are renter occupied 0.4
40 The HayWired Earthquake Scenario—Engineering Implications

Table 18. Displaced households and shelter demands from ground 

shaking caused by the HayWired earthquake scenario mainshock and 

aftershock sequence, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). See table 1 for explanation of aftershock short names and magnitudes]

HayWired scenario event Displaced households People seeking shortterm shelter

Mainshock 64,410 47,009

UC523 2 1

SP504 2 2

FF558 0 0

FR510 0 0

OK542 19 17

PA62 741 408

MP552 3 2

AT511 2 1

PA569 46 24

PA522 3 2

PA526 5 3

MV598 152 83

CU64 1,880 1,080

SV535 18 11

SC509 3 2

PA501 1 0

Table 19. Hazus shelter model default and custom parameter values developed for the ShakeOut scenario (see appendix).

Model 

parameter Description

Hazus 

default 

value

Custom 

ShakeOut 

value

WSFM Displacement weight for single-family homes in the Moderate damage state 0.0 0.2

WSFE Displacement weight for single-family homes in the Extensive damage state 0.0 0.4

WSFC Displacement weight for single-family homes in the Complete damage state 1.0 1.0

WMFM Displacement weight for multifamily residences in the Moderate damage state 0.0 0.4

WMFE Displacement weight for multifamily residences in the Extensive damage state 0.9 0.65

WMFC Displacement weight for multifamily residences in the Complete damage state 1.0 1.0

AW Age weighting factor 0 No change

EW Ethnicity weighting factor 0.27 No change

IW Income weighting factor 0.73 No change

OW Ownership weighting factor 0 No change

EM1 Modification factor for ethnicity: White households 0.24 0.1

EM2 Modification factor for ethnicity: Black households 0.48 0.2

EM3 Modification factor for ethnicity: Hispanic households 0.47 0.2

EM4 Modification factor for ethnicity: Asian households 0.26 0.1

EM5 Modification factor for ethnicity: Native American households 0.26 0.1

IM1 Modification factor for household income <$10,000 0.62 0.3

IM2 Modification factor for household income $10,000–$15,000 0.42 0.3

IM3 Modification factor for household income $15,000–$25,000 0.29 0.14

IM4 Modification factor for household income $25,000–$35,000 0.22 0.08

IM5 Modification factor for household income >$35,000 0.13 0.05

[Hazus, Federal Emergency Management Agency (2012)]
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 41

Table 20. Displaced households and short-term shelter requirements for the HayWired earthquake scenario 

mainshock, including liquefaction, in counties of the San Francisco Bay region, California, estimated using Hazus with 

default and custom ShakeOut shelter parameters.

County

Hazus default shelter parameters Custom ShakeOut shelter parameters

Displaced 

households

People seeking 

short-term shelter

Displaced 

households

People seeking shortterm shelter

Alameda 51,975 38,430 87,629 28,922

Contra Costa 12,483 8,641 21,856 6,623

Marin 128 121 513 155

Merced 0 0 5 2

Monterey 1 1 25 12

Napa 1 1 29 9

Sacramento 0 0 9 3

San Benito 32 29 54 23

San Francisco 2,251 1,265 11,741 2,986

San Joaquin 11 9 218 87

San Mateo 1,908 1,104 6,167 1,640

Santa Clara 7,649 5,641 24,179 7,408

Santa Cruz 9 13 89 48

Solano 52 39 310 110

Sonoma 0 0 14 4

Stanislaus 1 1 39 16

Yolo 0 0 4 2

Total 76,501 55,295 152,881 48,050

to the income and ethnicity factors considered by the model. 

It should be noted that, based on the default shelter category 

weights (table 17), income is a more important indicator of 

shelter-seeking behavior than ethnicity (that is, IW is larger 

than EW), and those with lower incomes are more likely to 

seek shelter than those with higher incomes (IM1>IM2>IM3). 

The modifications made for the ShakeOut analysis were 

based on data from recent California earthquakes and resulted 

in reductions in the proportions of the population expected 

to seek shelter at all income levels. A comparison of the 

displacement and shelter estimates for the HayWired scenario 

mainshock and those estimated using the custom ShakeOut 

shelter parameters is provided in table 20; both of these 

analyses include the impacts of liquefaction. The net result 

of applying the custom ShakeOut shelter parameters was an 

increase in the estimated number of displaced households 

from 76,500 to more than 150,000 and a slight decrease in the 

number of people seeking shelter from 55,000 to 48,000.

Combining Losses in the Mainshock 

and Aftershocks

Two approaches have been used to bound the estimate 

of potential additional losses suffered as a result of ground 

Table 21. Combined losses from ground shaking caused by the HayWired earthquake scenario 

mainshock and aftershocks, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). Loss reported in 2005 dollars; U.S. Consumer Price 

Index 2016:2005 ratio is approximately 1.23]

Combined event

Building 

damage

Total direct 

economic loss

Net building 

damage ratio

(percent) (millions of dollars)

Mainshock 30,312.4 46,633.7 2.9

Maximum aftershock 3,478.7 5,380.8 0.3

All aftershocks 7,669.4 11,767.1 0.7

Lower Bound 1: mainshock + maximum aftershock 33,791.0 52,014.5 3.2

Lower Bound 2: maximum individual event 30,551.1 47,015.4 2.9

Upper Bound: mainshock + all aftershocks 37,981.8 58,400.8 3.6

[Data from Hazus (Federal Emergency Management Agency, 2012)]
42 The HayWired Earthquake Scenario—Engineering Implications

Coordinate System: GCS North American 1983

Datum: North American 1983

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SAN JOAQUIN

SANTA CLARA

SOLANO

STANISLAUS

MARIN

SAN BENITO

MERCED

ALAMEDA

SACRAMENTO

CONTRA COSTA

SANTA CRUZ

SAN 

MATEO

SOLANO

SAN FRANCISCO

123° 122° 121°

38°

37°

EXPLANATION

County boundary

HayWired aftershocks

Event causing max DR

None

CU64

FF558

FR510

MV598

OK542

PA522

PA62

SP504

UC523

CALIF Area 

of maps

Figure 14. Map showing the HayWired earthquake scenario aftershock causing the maximum 

building damage ratio (max DR) by census tract, the San Francisco Bay region, California. See table 1 

for explanation of aftershock short names and magnitudes.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 43

shaking in the aftershock sequence; a lower bound estimate 

for each census tract has been developed as the sum of 

the mainshock shaking losses and shaking losses from the 

aftershock causing the maximum damage for that census tract, 

and an upper bound estimate has been developed as the sum 

of shaking losses in the mainshock and all of the aftershocks. 

The aftershocks generating the maximum building damage in 

each census tract are identified in figure 14. For most census 

tracts, the largest aftershock (the M6.4 Cupertino) causes the 

largest building damage ratio. Other events causing maximum 

damage ratios for selected census tracts include the M5.58 

Fairfield, M5.10 Freemont, M5.98 Mountain View, M5.42 

Oakland, M5.22 and M6.2 Palo Alto, M5.04 San Pablo, 

and M5.23 Union City aftershocks. In some cases, a more 

distant aftershock causes larger damage ratios than a nearby 

aftershock, as can be seen in parts of Sonoma County, where 

the M6.2 Palo Alto aftershock generates higher damage 

ratios than closer aftershocks. However, the damage ratios in 

Sonoma County are less than 0.1 percent for all aftershocks 

(figs. 8–11).

The upper and lower bound estimates of total loss 

in HayWired scenario events are summarized in table 21. 

Shaking damage in the modeled aftershock sequence adds 

between $3.5 billion (maximum aftershock) and $7.7 billion 

(all aftershocks) to the building damage total—an additional 

11 to 25 percent, respectively.

As an alternate to the lower bound estimate calculated 

above, one could use the maximum loss in all events (that is, 

the maximum shaking loss occurring in either the mainshock 

or any of the aftershocks). For most census tracts, this 

maximum shaking loss occurs in the mainshock, but 49 census 

tracts (out of 2,122 in the 17-county study area) suffer larger 

shaking losses in one of the aftershocks, including 12 census 

tracts where the M6.2 Palo Alto aftershock dominates the 

losses, 35 tracts where the M6.4 Cupertino event generates the 

largest building damage, and 2 census tracts where the M5.58 

Fairfield event generates the largest building damage ratio; 

these tracts are mapped in figure 15, and the resulting losses 

are provided in table 21 as Lower Bound 2. This alternate 

lower bound assumes that no other earthquake adds any 

damage to the maximum damage from one earthquake in each 

census tract and is lower than the initial version; total building 

damage is $30.6 billion versus $33.8 billion in the initial lower 

bound estimate.

The various resulting census tract level building damage 

ratio maps are shown in figures 16 and 17, in the same order 

as presented in table 21. Figure 16 presents the census tract 

shaking damage ratio map for the HayWired mainshock, the 

maximum aftershock, the sum of all aftershocks, and the 

sum of the mainshock and the maximum aftershock (Lower 

Bound 1). Figure 17 provides the final two shaking damage 

ratio maps for the maximum of mainshock and aftershock 

(Lower Bound 2) and the mainshock plus all aftershocks 

(Upper Bound).

Repeat Liquefaction

To examine losses resulting from repeated liquefaction in 

subsequent events, liquefaction impacts within Alameda County 

(evaluated using the Hazus default liquefaction approach and 

uniform depth to groundwater assumption) were reviewed 

at the census tract level for the mainshock and the M5.42 

Oakland aftershock. Alameda County was selected for its 

proximity to the epicenter of the mainshock and the epicenter 

of the Oakland aftershock, as well as the presence of highly 

liquefiable soils (see fig. 2). Maps of expected liquefaction/

lateral spread displacements as estimated by Hazus using its 

default methodology, considering liquefaction susceptibility, 

depth to groundwater (assumed shallow), and probability of 

liquefaction, are provided in figure 18. As shown, many of 

the bay-front census tracts are estimated to have substantial 

expected lateral spread in the mainshock, with some additional 

smaller movements in the M5.42 Oakland aftershock.

As has been noted, Hazus is not able to estimate 

additional damage to damaged buildings; each of the current 

analyses is independent and assumes that the inventory is in 

an undamaged condition before the earthquake. Although this 

may underestimate cumulative damage, it is still instructive 

to examine the potential impact of repeated liquefaction in 

liquefaction prone areas.

In Alameda County, 264 tracts are subject to liquefactioninduced lateral spread displacements in the mainshock; 

131 of these tracts are subject to additional lateral spread 

displacements in the M5.42 Oakland aftershock. Shaking 

and liquefaction losses in these 131 tracts are summarized 

in table 22. Even though liquefaction is less widespread in 

the aftershock, and expected liquefaction damage is minimal 

compared to the mainshock ($77 million versus $1.45 billion), 

liquefaction damage is predicted by Hazus even in events 

with magnitudes less than 6. And in these smaller events, 

liquefaction has the potential to represent a larger proportion 

of the overall damage; in these 131 tracts, building damage 

caused by liquefaction represents 21 percent of the total 

building damage caused by shaking and liquefaction in the 

mainshock but increases to 26 percent in the aftershock.
44 The HayWired Earthquake Scenario—Engineering Implications

YOLO

SONOMA

MONTEREY

NAPA

SOLANO

SANTA

CLARA

MARIN

ALAMEDA

SAN

JOAQUIN

SACRAMENTO

CONTRA COSTA

SAN

BENITO

SANTA CRUZ

SAN

MATEO

STANISLAUS

MERCED

SAN FRANCISCO

123° 122°

38°

37°

Coordinate System: GCS North American 1983

Datum: North American 1983

EXPLANATION

County boundary

HayWired mainshock and aftershocks

Event causing max DR

HayWired mainshock

FF558

CU64

PA62

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

PACIFIC

OCEAN CALIF Area 

of maps

Figure 15. Map showing the HayWired earthquake scenario mainshock or aftershock causing the 

maximum building damage ratio (max DR) by census tract, San Francisco Bay region, California. See 

table 1 for explanation of aftershock short names and magnitudes.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 45

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MARIN

MERCED

ALAMEDA

SACRAMENTO

CONTRA

COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

SAN BENITO

D. Mainshock + maximum aftershock

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MARIN

MERCED

ALAMEDA

SACRAMENTO

CONTRA

COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

SAN BENITO

38°

37°

C. Cumulative aftershock

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MARIN

MERCED

ALAMEDA

SACRAMENTO

CONTRA

COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

SAN BENITO

123° 122° 121°

B. Maximum aftershock

PACIFIC

OCEAN

YOLO

MONTEREY

SONOMA NAPA

SOLANO

SAN JOAQUIN

SANTA CLARA

STANISLAUS

MARIN

MERCED

ALAMEDA

SACRAMENTO

CONTRA

COSTA

SANTA CRUZ

SAN

MATEO

SAN FRANCISCO

SAN BENITO

HayWired M 7.05 

mainshock

123° 122° 121°

38°

37°

A. Mainshock

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5.0%

5.0–10.0%

>10.0%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of maps

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

Figure 16. Maps showing building damage ratio from ground shaking caused by the HayWired earthquake scenario mainshock and 

aftershocks, San Francisco Bay region, California. A, Mainshock building damage ratio; B, Maximum aftershock building damage ratio; C, 

Cumulative aftershock building damage ratio; and D, Mainshock plus maximum aftershock building damage ratio (lower bound 1).
46 The HayWired Earthquake Scenario—Engineering Implications

Figure 17. Maps of building damage ratio from ground shaking caused by the HayWired earthquake scenario mainshock and 

aftershocks, San Francisco Bay region, California. A, Maximum individual event building damage ratio (lower bound 2). 

B, Cumulative (mainshock plus all aftershocks) building damage ratio (upper bound).

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

B. Cumulative

PACIFIC

OCEAN

SONOMA

SAN FRANCISCO

MARIN

CONTRA SAN JOAQUIN

 COSTA

STANISLAUS

MERCED

SAN BENITO

SANTA CRUZ

SANTA CLARA

ALAMEDA

 SAN

MATEO

MONTEREY

NAPA

YOLO

SOLANO

SACRAMENTO

 123° 122° 121°

38°

37°

A. Maximum event

0

<0.1%

0.1–0.5%

0.5–2.5%

2.5–5%

5–10%

>10%

Building damage ratio

(damage divided by replacement 

value, expressed as a percent)

County boundary

EXPLANATION

Coordinate System: GCS North American 1983

Datum: North American 1983

CALIF Area 

of maps

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

0 10 20 30 40 50 KILOMETERS

0 10 20 30 40 50 MILES

Model Limitations and Data Gaps

Hazus was developed by FEMA to “produce loss 

estimates for use by Federal, State, regional and local 

governments in planning for earthquake risk mitigation, 

emergency preparedness, response and recovery” (FEMA, 

2012). At the time of its development in the early 1990s, 

its methods were considered state of the art; little has 

changed in the underlying earthquake methodology since its 

original development. With time, other more comprehensive 

analytical methodologies have been developed by the 

earthquake engineering community, such as Performance 

Based Earthquake Engineering (see, for example, Applied 

Technology Council, 2006). Nevertheless, the Hazus 

framework still provides the only publicly available software 

and methodology that allows for regional earthquake analysis 

anywhere in the United States using pre-packaged (default) 

building inventory data. Studies directly comparing the results 

of the various approaches have yet to be conducted.

It should be noted that although the inventory data used in 

the HayWired analyses were enhanced with improved mapping 

schemes and escalated replacement values, other exposure data 

(building square footage and building counts) were Hazus defaults 

based on 2000 census data for residential occupancies and 2006 

Dun & Bradstreet data for non-residential occupancies. With the 

release of Hazus 2.2 in January of 2015, updated Hazus inventory 

data reflecting 2010 census data for residential occupancies are 

now available. Because these new data are based on revised 

census geographies, they are, unfortunately, currently incompatible 

with the improved mapping schemes developed for the San 

Francisco Bay region based on the 2000 census geometries. In 

the future, to avoid obsolescence of the improved San Francisco 

Bay region mapping schemes, an evaluation and conversion to the 

2010 census geographies will need to be performed.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 47

Figure 18. Maps showing expected liquefaction-induced lateral spread displacements by census tract 

in Alameda County, California, estimated using the Hazus (FEMA, 2012) default approach. A, Spread from 

mainshock. B, Spread from magnitude (M) 5.42 Oakland aftershock.

MARIN

ALAMEDA

SAN MATEO

CONTRA COSTA

SANTA CLARA

122.5° 122°

37.5°

37.5°

HayWired M 7.0 mainshock epicenter

ALAMEDA

SAN MATEO

CONTRA COSTA

SANTA CLARA

MARIN

Oakland M 5.42 epicenter

A. Mainshock

B. M 5.42 Oakland

SAN

FRANCISCO

SAN

FRANCISCO

PACIFIC OCEAN

SAN FRANCISCO BAY

SAN FRANCISCO BAY

Coordinate System: GCS North American 1983

Datum: North American 1983

 Area 

of map

EXPLANATION

County boundary

Alameda County 

 census tracts

Expected lateral spread

None

<5 inches

5–10 inches

10–15 inches

15–20 inches

CALIF

0 5 10 KILOMETERS

0 5 10 MILES
48 The HayWired Earthquake Scenario—Engineering Implications

The current study uses Hazus to assess damage and loss in 

17 earthquake events ranging from M5.0 to M7.0. Hazus’ known 

limitations include increased uncertainty for small events, wherein 

empirical data from past events may be lacking. As stated in the 

Hazus Earthquake Technical Manual, “...the losses from small 

magnitude earthquakes (<M6.0) centered within an extensive 

urban region appear to be overestimated” (FEMA, 2012).

When Hazus was initially developed, it was expected that 

ground motions would be computed within the software using 

standard attenuation functions and reflecting their associated 

uncertainty; fragility function medians and betas (the uncertainty 

term) were developed accordingly. Following Hazus’ initial 

release, the use of real-time USGS ShakeMaps was facilitated to 

support emergency response, bypassing Hazus’ ground motion 

generation capabilities. A subsequent study (Kircher, 2002) 

indicated that the use of recorded ground motions (that is, an 

actual event ShakeMap) should be accompanied by reduced 

fragility function betas, reflecting the reduction in ground motion 

uncertainty for an actual event. The implementation of this 

recommendation within the Hazus framework was focused on the 

emergency response motivation; reduced betas are used whenever 

a ShakeMap is imported. Unfortunately, this does not reflect the 

reality that damaging real earthquake events are rare, and many 

ShakeMaps used with Hazus are scenario ShakeMaps, which 

do not have the benefit of reduced ground motion uncertainty. In 

the current study, it may be appropriate to treat the high-quality 

simulated HayWired mainshock ground motions as having 

a similar level of uncertainty as a real event (that is, reduced 

betas are appropriate), but the aftershock ShakeMaps should, in 

theory, be treated as estimated ground motions with the original 

(not reduced) betas. In practice, Hazus is not designed to allow 

the typical user to easily make such a choice; all imported 

ShakeMaps are treated with the reduced betas, regardless of 

whether they are actual events or hypothetical scenario events.2

If all scenario ShakeMaps could be developed with the same 

2

It should be noted that since October 2016 and the release of Hazus 3.2, 

Hazus now includes a mechanism to import ShakeMap XML grid data and 

recognizes the difference between “scenario” and “actual” events and applies 

the appropriate fragility curve betas.

level of sophistication as the HayWired mainshock and the 

southern California ShakeOut scenario, this issue would be moot, 

suggesting the need for less expensive simulation methods for 

high-quality ShakeMaps. Because the aftershocks evaluated in this 

study are treated with the reduced fragility curve betas, we would 

expect their losses to be underestimated (perhaps counterbalancing 

the overestimation expected for small magnitude events). The 

actual level of underestimation would require testing to quantify, 

but to put it into perspective, Kircher (2002) found a reduction of 

one-third in economic losses for the M6.7 Northridge earthquake 

when using the reduced fragility curve betas.

It was challenging to use finer resolution data for liquefaction 

and landslide hazards, which can vary considerably in a census 

tract, in the Hazus construct. We developed creative ways to 

leverage the Hazus damage estimation methodology in areas where 

the hazards affect the built environment. However, the liquefaction 

probability method (Jones and others, 2017) left us with an 

additional challenge, in that liquefaction-induced displacement 

estimates were not provided. In the future, both probability and 

displacement liquefaction hazard estimates would be needed. 

As noted previously, Hazus is not able to estimate additional 

damage to damaged buildings, making our quantification of 

losses from the full earthquake sequence incomplete. To consider 

cumulative damage in the Hazus context, it would likely require 

the development of new vulnerability functions (that is, capacity 

curves for damaged buildings of various construction types and 

damage states), as well as removal of inventory data for already 

damaged buildings.

Finally, Hazus does not directly produce certain metrics 

that would be valuable to emergency response planning and 

preparedness, including the predicted post-earthquake building 

safety tag, casualty estimates useful for medical response planning, 

and urban search and rescue (USAR) needs. However, several 

aftermarket approaches have been developed to fill these gaps. 

FEMA has developed and implemented spreadsheet-based 

approaches for estimating the number and type of USAR teams 

and personnel required from Hazus damage state distribution 

data by construction type. This tool uses a simplified assignment 

of safety tag from damage state. Public health researchers 

Table 22. Liquefaction-induced building damage for 131 census tracts in Alameda County, 

California, suffering lateral spread displacements from the HayWired earthquake scenario 

mainshock and Oakland M5.42 aftershock, estimated using Hazus.

[Data from Hazus (Federal Emergency Management Agency, 2012). See table 1 for explanation of aftershock short names 

and magnitudes. Damage reported in 2005 dollars; U.S. Consumer Price Index 2016:2005 ratio is approximately 1.23]

HayWired scenario event Building damage 

(millions of dollars)

Building damage ratio 

(percent)

Mainshock, shaking only 6,802 12.7

Mainshock, shaking and liquefaction 8,254 15.4

Mainshock, liquefaction 1,452 2.7

OK542, shaking only 293 0.55

OK542, shaking and liquefaction 369 0.69

OK542, liquefaction 77 0.14
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 49

have studied casualty data collected from the 1994 Northridge 

earthquake and have recommended modification factors to 

extrapolate injuries requiring trauma care, injuries requiring 

Emergency Medical Services (EMS) transport, and emergency 

department visits from Hazus casualty severity level estimates 

(Shoaf and Seligson, 2011).

Conclusions

Mainshock Assessment

In the HayWired scenario mainshock, the “best estimate” 

of building damage totaled $35.2 billion (in 2005 dollars, 

$43.3 billion in 2016 dollars), with $30.3 billion (in 2005 dollars, 

$37.3 billion in 2016 dollars) resulting from shaking, $4.6 billion 

(in 2005 dollars, $5.7 billion in 2016 dollars) from liquefaction, 

and $300 million (in 2005 dollars, approximately $360 million in 

2016 dollars) from landslides.

This estimate is a full order of magnitude greater than 

FEMA’s initial Hazus estimate of $350 million (also in 2005 

dollars) in building damage resulting from the 2014 Napa 

earthquake, suggesting that a HayWired mainshock event would 

cause substantial regional damage and disruption. It should be 

mentioned that the $35 billion HayWired (and $350 million Napa) 

estimate is for direct building damage alone (in other words, for 

structural and nonstructural damage to the region’s buildings) 

and does not include content damage, or building damagerelated direct economic losses (such as lost rent or the cost of 

relocation), nor does it include damage to the region’s utilities and 

transportation infrastructure.

Strong ground shaking in the HayWired mainshock causes 

the bulk of the estimated damage to the regional building stock, 

with liquefaction adding 16 percent to the building damage 

estimates in Alameda and Santa Clara Counties when using 

custom probability data and 14 percent to building damage in 

the six counties modeled using the Hazus default liquefaction 

approach (Contra Costa, Marin, Napa, San Francisco, San Mateo, 

Solano, and Sonoma). Landslide-related building damage adds 

just 1 percent to building damage in the same eight counties.

The utilization of pixel-level liquefaction and landslide 

data for the mainshock presented substantial challenges to 

implementation within Hazus, which is not ideally designed to 

accept input data at this level of refinement. As a result of having 

to combine Hazus results with pixel data outside of Hazus, the 

ability to estimate derivative losses was lost. Although the current 

version of Hazus (Hazus 4.0) has made some improvements in 

data utilization (for example, allowing import of a ShakeMap 

XML grid and averaging ground motions across census tracts 

rather than taking a simple centroidal value), these features were 

not available in the Hazus version used for the HayWired studies 

(Hazus 2.1, for reasons described in the previous section). The 

approach taken here would likely be difficult for the typical 

Hazus user to implement. In particular, interrupting various Hazus 

computations, as was done in the custom liquefaction assessment, 

is not commonly done, and generally not recommended. Further, 

the level of effort required to complete the landslide assessment 

may not be justified by the result; in the current assessment, 

landslide added just 1 percent to the overall building damage 

loss, relative to shaking losses, in counties where landslide was 

modeled. In future studies, users should evaluate how important it 

is to include landslide damage; one compromise approach would 

be to limit the assessment to areas of high landslide susceptibility 

in the regions with the strongest ground shaking (for example, 

limiting the current landslide assessment to Alameda County 

would have captured 50 percent of the estimated landslide 

losses). To consider landslide hazards at a greater level of 

detail, earthquake damage estimation tools that can accept finer 

resolution hazard data would be needed (for example, the Hazus 

earthquake model could be reconfigured to operate at the census 

block level, as the Hazus flood tool currently operates).

Aftershock Assessment

Although most of the simulated aftershocks are expected 

to cause only minor damage, several are large enough to create 

localized damage and losses larger than those of the 2014 

M6.0 South Napa earthquake. For an area still responding to or 

recovering from the larger HayWired mainshock, these damaging 

aftershocks would place additional burdens on potentially limited 

resources.

As has been noted, Hazus does not model damage to 

damaged buildings, but the Hazus results may be used to 

estimate lower and upper bound cumulative losses. Lower 

bound building damage from shaking alone (estimated as the 

maximum loss of any single event in the HayWired sequence) 

exceed $30.6 billion, whereas upper bound estimates of building 

losses (estimated as the sum of loss in the mainshock and all 

aftershocks) are just less than $38 billion.

While the upper and lower bound estimates described 

above address building damage resulting from shaking only, 

there are also a number of other metrics of interest that may 

be approximately combined across events. Over the entire 

earthquake sequence, the total direct economic loss can be 

approximated as $67.0 billion (in 2005 dollars, $82.6 billion in 

$2016), including:

• $43.3 billion (in 2005 dollars, $53.3 billion in 2016 

dollars) in building damage for the mainshock and 

all aftershocks, using USGS-modeled liquefaction 

and landslide hazard and probability data for the 

mainshock, where available, and the Hazus default 

liquefaction modeling approach for other areas in the 

mainshock as well as for three aftershocks (M5.98 

Mountain View, M6.4 Cupertino, and M5.42 Oakland). 

The remainder of aftershocks were modeled for 

shaking only.

• $13.8 billion (in 2005 dollars, $17.0 billion in 2016 

dollars) in damage to contents and commercial inventories, 

estimated using the Hazus default liquefaction modeling 

approach for the mainshock and the three aftershocks 
50 The HayWired Earthquake Scenario—Engineering Implications

identified above, and considering only ground-shaking 

hazards for the remainder of events.

• $10.0 billion (in 2005 dollars, $12.3 billion in 2016 

dollars) in building damage-related income losses (for 

example, relocation costs, lost rent, and so on), modeled in 

the same manner as contents and inventory damage.

The Mw 7.0 mainshock is responsible for about 80 percent 

of the losses from the earthquake sequence, 12 percent from three 

largest aftershocks of Mw 6.0 to 6.4, and 8 percent from the 13 

aftershocks of Mw 5.0 to 5.9. Displaced household assessments 

range from tens of households for the smallest aftershocks to 

hundreds of households for the largest aftershocks to tens of 

thousands of households (77,000–153,000) for the mainshock, 

based on the 2000 U.S. Census.

The Hazus analyses of the HayWired earthquake scenario 

and the set of simulated aftershocks have clarified the relationship 

between this large event and its aftershocks:

• In the HayWired scenario mainshock, liquefaction 

(modeled in the counties for which liquefaction 

susceptibility has been mapped and assessed using the 

Hazus default liquefaction approach) represents 17 percent 

of the total building damage (more than $5 billion). In the 

selected aftershocks for which liquefaction was modeled, 

liquefaction represents between 9 percent (M6.4 Cupertino 

aftershock) and 15 percent (M5.42 Oakland aftershock) of 

the total building damage. As shown by a review of repeat 

liquefaction in the M5.42 Oakland aftershock, additional 

liquefaction could occur even in the smaller aftershocks 

and has the potential to represent a larger proportion of the 

overall damage in these aftershock events.

• For shaking only, damage ratios in the aftershocks are two 

orders of magnitude smaller than those of the mainshock, 

except for the larger aftershocks (M6.2 Palo Alto, M5.98 

Mountain View, and M6.4 Cupertino) which have damage 

ratios one order of magnitude smaller than the mainshock.

• Damage ratios may increase when concentrations of 

potentially vulnerable building types are located near 

an aftershock’s epicenter, for example, tilt-up and URM 

buildings in the M5.23 Union City and M5.42 Oakland 

aftershocks.

• For the simulated aftershock sequence, census tracts with 

the largest damage to pre-code low-rise URM buildings 

are not the same as those tracts with substantial damage 

in the mainshock. At the census tract level, the sum of 

economic losses from building damage to pre-code lowrise URM in the HayWired event and all of its aftershocks 

did not exceed the building exposure value. This supports 

the proposed approach of aggregating losses across the set 

of simulated events, without the risk of estimating losses 

in excess of exposed value.

• The total number of casualties in the aftershocks is as 

much as three orders of magnitude smaller than those in 

the mainshock. Expected casualties in most aftershocks 

are minor (primarily casualty Severity Level 1 with some 

Severity Level 2), and only two events (M6.2 Palo Alto, 

and M6.4 Cupertino) are expected to cause any serious 

injuries (Severity Level 3) or deaths (Severity Level 4).

• Although population displacement resulting from ground 

shaking alone is substantial in the mainshock (displaced 

households exceeds 64,000), expected displacement in 

the aftershocks is generally minimal, except in the four 

larger aftershock events for which estimates of displaced 

households range from 50 (M5.69 Palo Alto) to 1,900 

(M6.4 Cupertino). When custom shelter model parameters 

developed for the ShakeOut scenario are applied to 

the HayWired mainshock, including liquefaction, 

displacement estimates increase from 76,500 to 152,900, 

but the number of people seeking publicly provided shortterm shelter decreases from 55,000 to 48,000.

Acknowledgments

Karen Felzer (U.S. Geological Survey [USGS] Earthquake 

Science Center) simulated the aftershock sequence, and Tim 

MacDonald (USGS Earthquake Science Center) generated the 

aftershock ShakeMaps. Andrew Michael (USGS Earthquake 

Science Center) offered useful suggestions on creating Hazus 

inputs from the USGS ground failure estimations. Doug Bausch 

(Federal Emergency Management Agency [FEMA], at the time) 

set up the Hazus modeling environment for the San Francisco Bay 

area, executed the initial Hazus run for the HayWired mainshock, 

and reviewed this chapter. Sean McGowan (USGS Geologic 

Hazards Science Center [at time, since moved to FEMA]) and 

Jesse Rozzelle (FEMA) also provided expert reviews of this 

chapter. Kim Shoaf (Division of Public Health, University of 

Utah) supplied the customized population and shelter parameters 

and documentation in the appendix. Keith Porter (University 

of Colorado) provided input on the model and data limitations. 

This Hazus analysis was funded by Science Application for Risk 

Reduction (SAFRR) and Land Change Science.
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 51

References Cited

Aagaard, B.T., Boatwright, J.L., Jones, J.L., MacDonald 

T.G., Porter, K.A., Wein, A.M., 2017, HayWired scenario 

mainshock ground motions, chap. C of Detweiler, S.T., and 

Wein, A.M., eds., The HayWired earthquake scenario—

Earthquake hazards: U.S. Geological Survey Scientific 

Investigations Report 2017–5013–A–H, 126 p., https://doi.

org/10.3133/sir20175013v1.

Applied Technology Council, 2006, Next-generation 

performance-based seismic design guidelines; Program plan 

for new and existing buildings: prepared for the Federal 

Emergency Management Agency, FEMA-445, 131 p.

Federal Emergency Management Agency, 2012, Hazus multihazard loss estimation methodology, earthquake model, 

Hazus®-MH 2.1 technical manual: Federal Emergency 

Management Agency, Mitigation Division, 718 p. accessed 

July 18, 2017, at http://www.fema.gov/media-librarydata/20130726-1820-25045-6286/hzmh2_1_eq_tm.pdf.

Holzer, T.L, 1994, Loma Prieta damage largely attributed to 

enhanced ground shaking: Eos, Transactions American 

Geophysical Union, v. 75, no. 26, p. 299–301.

Holzer, T.L., Noce, T.E., and Bennett, M.J., 2008, 

Liquefaction hazard maps for three earthquake scenarios 

for the communities of San Jose, Campbell, Cupertino, 

Los Altos, Los Gatos, Milpitas, Mountain View, Palo Alto, 

Santa Clara, Saratoga, and Sunnyvale, northern Santa Clara 

County, California: U.S. Geological Survey Open-File 

Report 2008–1270, 29 p., 3 plates, and database http://pubs.

usgs.gov/of/2008/1270/.

Holzer, T.L., Noce, T.E., and Bennett, M.J., 2010, Predicted 

liquefaction in the greater Oakland area and northern 

Santa Clara Valley during a repeat of the 1868 Hayward 

Fault (M6.7–7.0) earthquake: Proceedings of the Third 

Conference on Earthquake Hazards in the Eastern San 

Francisco Bay Area October 22–24, 2008.

Holzer, T.L., Noce, T.E., and Bennett, M.J., 2011, Liquefaction 

probability curves for surficial geologic deposits: Environmental 

and Engineering Geoscience, v. 17, no. 1, p. 1–21.

Homer, C.G., Dewitz, J.A., Yang, L., Jin, S., Danielson, P., 

Xian, G., Coulston, J., Herold, N.D., Wickham, J.D., and 

Megown, K., 2015, Completion of the 2011 National Land 

Cover Database for the conterminous United States—

Representing a decade of land cover change information: 

Photogrammetric Engineering and Remote Sensing, v. 

81, no. 5, p. 345–354, accessed December 15, 2016, at 

http://www.asprs.org/a/publications/pers/2015journals/

PERS_May_2015/HTML/files/assets/basic-html/index.

html#345/z#noFlash.

Jones, L.M., Bernknopf, R., Cox, D., Goltz, J., Hudnut, K., 

Mileti, D., Perry, S., Ponti, D., Porter, K., Reichle, M., 

Seligson, H., Shoaf, K., Treiman, J., and Wein, A., 2008, 

The ShakeOut Scenario: U.S. Geological Survey OpenFile Report 2008–1150 and California Geological Survey 

Preliminary Report 25, 312 p. and appendixes, accessed 

April 12, 2017, at https://pubs.usgs.gov/of/2008/1150/.

Jones, J.L., Knudsen, K.L., Wein, A.M., 2017, HayWired 

scenario mainshock—Liquefaction probability mapping, 

chap. E of Detweiler, S.T., and Wein, A.M., eds., The 

HayWired earthquake scenario—Earthquake hazards: U.S. 

Geological Survey Scientific Investigations Report 2017–

5013–A–H, 126 p., https://doi.org/10.3133/sir20175013v1.

Kircher, C.A., 2002, Development of new fragility function 

betas for use with ShakeMaps [unpublished report]: 

prepared for the National Institute of Building Sciences 

(NIBS) and the Federal Emergency Management Agency 

(FEMA), 28 p.

Kircher, C.A., Seligson, H.A., Bouabid, J., and Morrow, G.C., 

2006, When the big one strikes again—estimated losses 

due to a repeat of the 1906 San Francisco earthquake: 

Earthquake Spectra, v. 22, no. S2, p. 297–339.

Knudsen, K.L., Sowers, J.M., Witter, R.C., Wentworth, 

C.M., Helley, E.J., Nicholson, R.S., Wright, H.M., Brown, 

K.M., 2000, Preliminary maps of quaternary deposits and 

liquefaction susceptibility, nine-county San Francisco Bay 

region, California—A digital database: U.S. Geological 

Survey Open-File Report 00-444, accessed at http://pubs.

usgs.gov/of/2000/of00-444/.

McCrink, T.P., Perez, F.G., 2017, HayWired scenario 

mainshock—Earthquake-induced landslide hazards, chap. 

F of Detweiler, S.T., and Wein, A.M., eds., The HayWired 

earthquake scenario—Earthquake hazards: U.S. Geological 

Survey Scientific Investigations Report 2017–5013–A–H, 

126 p., https://doi.org/10.3133/sir20175013v1.

Seligson, H.A., 2008, The ShakeOut scenario supplemental 

study—Hazus enhancements and implementation for the 

ShakeOut scenario earthquake: Denver, Colo., SPA Risk 

LLC, 9 p.

Shoaf, K.I., and Seligson, H.A., 2011, Estimating casualties 

for the southern California ShakeOut, chap. 9 of Spence, 

R., So, E., and Scawthorn, C., eds., Human casualties 

in earthquakes—progress in modelling and mitigation: 

Springer, Advances in natural and technological hazards 

research, v. 29, p. 125–137.

U.S. Geological Survey, 2014, Earthquake planning 

scenario—ShakeMap for HayWired M7.05-scenario: 

U.S. Geological Survey webpage, accessed on May 23, 

2017, at https://earthquake.usgs.gov/scenarios/eventpage/

ushaywiredm7.05_se#shakemap.
52 The HayWired Earthquake Scenario—Engineering Implications

Appendix. Calculation of Shelter Parameters for the 2008 

Southern California ShakeOut Scenario

1

University of Utah.

By Kimberley Shoaf1 

U.S. Geological Survey, 2015, HayWired Aftershock 

Planning Scenarios: U.S. Geological Survey Earthquake 

Hazards Program website, accessed May 13, 2017, 

at http://escweb.wr.usgs.gov/share/shake2/haywired/

archive/scenario.html.

Wein, A.M., Felzer, K.R., Jones, J.L., and Porter, K.A., 2017, 

HayWired scenario aftershock sequence, chap. G of Detweiler, 

S.T., and Wein, A.M., eds., The HayWired earthquake 

scenario—Earthquake hazards: U.S. Geological Survey 

Scientific Investigations Report 2017–5013–A–H, 126 p., 

https://doi.org/10.3133/sir20175013v1.

For the HayWired earthquake scenario, shelter 

parameters for use in Hazus (Federal Emergency Management 

Agency, 2012) were those estimated for the 2008 Southern 

California ShakeOut scenario (Jones and others, 2008) using 

data from two surveys which were conducted by Bourque and 

others following the 1989 Loma Prieta earthquake and the 

1994 Northridge earthquake (Bourque and others, 2002; Shoaf 

and Bourque, 1999). In both of these surveys, residents of the 

impacted counties were asked about their experiences in the 

earthquakes, including questions about damage to their homes, 

injuries, and being displaced from their homes. Respondents 

were asked the following: “As a result of the earthquake, 

did you evacuate your home, or leave it for any period of 

time because of damage, possible damage, or how you were 

feeling?” If they had left their home, they were asked, “Why 

did you evacuate your home?” and given the opportunity to 

identify as many of the possible reasons for leaving as applied 

to their situation. These reasons for evacuation included the 

following: “Own decision because of structural damage,” 

“Suggested by an official,” “No drinking water,” “Gas leaks,” 

“No electrical power,” “Invitation from a friend or relative,” 

“Too upset to stay,” “Afraid of further damage,” “Because of a 

prediction of the next earthquake or aftershock,” or “Other.” In 

the Northridge questionnaire, respondents were also given the 

choice of selecting “Building manager advised.” They were 

also asked where they stayed after leaving their home. These 

are the data that were used to modify the Hazus parameters 

for displacement and shelter needs for the 2008 Southern 

California ShakeOut scenario.

In all, approximately 16 percent of the population were 

displaced from their homes in the Northridge earthquake and 

22 percent in the Loma Prieta earthquake. Hazus estimates for 

shelter needs include two different components—estimates of 

displacement based on building damage states and shelter needs 

modified by a variety of individual and population demographic 

characteristics. Using both the Northridge and the Loma 

Prieta earthquake datasets, we modified both the displacement 

parameters and the shelter needs parameters.

Displacement

In Hazus, displacement is calculated based on the number 

of buildings in different damage states. The original parameters 

in Hazus assumed that everyone in both single and multifamily 

dwellings in the Complete damage state would be displaced. We 

concurred with that estimate. In the standard scheme, Hazus also 

estimates that 90 percent of those in the Extensive damage state in 

multifamily dwellings would be displaced, but that for all others, 

there would be no displacement. Based on crosstab analysis of 

displacement by tagging (red, yellow, green, no tag, no inspection) 

and by single versus multifamily dwelling, we revised the 

estimates for those in the Extensive and Moderate damage states. 

We recognize that tagging is not a perfect match for damage states, 
Chapter J. HayWired Scenario—Hazus Analyses of the Mainshock and Aftershocks 53

but with some smoothing, we equated red tag with Complete 

damage, yellow tag with Extensive damage, and green tag with 

Moderate damage. These results translated into new estimates for 

displacement for the other damage states, as given in table 23.

Shelter Needs

Hazus allows for changes to the shelter needs model by 

applying both weighting factors and modification factors for 

certain demographic characteristics of the population. These 

characteristics include age, ethnicity, household income, 

and ownership. Logistic regression analyses were conducted 

for both the Northridge and the Loma Prieta earthquake 

survey data to estimate the relative importance of these 

characteristics. Unfortunately, only a very small number of 

respondents in either earthquake stayed in a formal shelter. 

Because of the small numbers, we were unable to use “Staying 

in a shelter” as the outcome variable in the regression analysis. 

We therefore used “Displaced” as the outcome variable. The 

results of the regression analyses on the two earthquakes 

were remarkably comparable. For both earthquakes, the only 

demographic characteristics that had a significant impact on 

displacement were ethnicity and income, with income having 

more impact than ethnicity. The overall Weighting Factor 

for ethnicity was not changed. However, as a result of the 

analysis, we revised the individual ethnicity modification 

factors to reflect less variation, with Whites, Asians, and 

Native Americans having a relative weight of 0.1 and Blacks 

and Hispanics having a relative weight of 0.2, as summarized 

in table 24.

Because most of the variance in displacement was explained 

by income, we did not change the overall weighting factor for 

income. However, the income modification factors were reduced 

Table 23. Hazus displacement model damage state factors as 

modified for the 2008 Southern California ShakeOut scenario.

Dwelling type Damage 

state

Old 

parameter

Revised 

parameter

Multifamily dwelling Complete 1.0 1.0

Multifamily dwelling Extensive 0.9 0.65

Multifamily dwelling Moderate 0.0 0.4

Single-family dwelling Complete 1.0 1.0

Single-family dwelling Extensive 0.0 0.4

Single-family dwelling Moderate 0.0 0.2

[For more information on the ShakeOut scenario, see Jones and others (2008)]

Weighting and modification factors Old parameter Revised parameter

Ethnicity weighting factor 0.27 No change

Income weighting factor 0.73 No change

Modification factor for ethnicity: White households 0.24 0.1

Modification factor for ethnicity: Black households 0.48 0.2

Modification factor for ethnicity: Hispanic households 0.47 0.2

Modification factor for ethnicity: Asian households 0.26 0.1

Modification factor for ethnicity: Native American households 0.26 0.1

Modification factor for household income <$10,000 0.62 0.3

Modification factor for household income $10,000–$15,000 0.42 0.3

Modification factor for household income $15,000–$25,000 0.29 0.14

Modification factor for household income $25,000–$35,000 0.22 0.08

Modification factor for household income >$35,000 0.13 0.05

Table 24. Hazus shelter needs model weighting and modification factors as modified for the 2008 Southern 

California ShakeOut scenario.

[For more information on the ShakeOut scenario, see Jones and others (2008)]

as follows: incomes below $10,000 and $10,000–$15,000 were 

weighted equally at 0.3; incomes of $15,000–$25,000 were 

weighted at 0.14; incomes of $25,000–$35,000 were weighted at 

0.08; and incomes above $35,000 were weighted at 0.05.

Other Parameters to Consider

Hazus uses only damage states of buildings to model 

displacement. In both the Northridge and the Loma Prieta 

earthquakes, utility outage was a better predictor of displacement 

than damage to one’s home. The odds ratio of being “displaced 

due to damage to one’s home” in the Loma Prieta earthquake was 

1.9. The comparable odds ratio was 2.7 for “electricity outage” and 

2.4 for “water outage.” Somewhere between 20 and 50 percent 

of those with utility outage will be displaced from their homes. 

Clearly, this overlaps with damaged homes, but many without 

damage will be unable to stay in their homes simply because 

they do not have the needed utilities. Including a parameter for 

utility outage would improve the estimates for shelter needs in 
future modeling. Given that utility outage is highly correlated 

with building damage, utilizing the lower bound parameter of 

20 percent would be appropriate. A final estimate of displacement 

would be 120 percent of the Hazus estimate.

References Cited

Bourque, L.B., Siegel, J.M., and Shoaf, K.I., 2002, Psychological 

distress following urban earthquakes in California: Prehospital 

and Disaster Medicine, v. 17, no. 2, p. 81–90, accessed October 

2, 2012, at http://journals.cambridge.org/download.php?file=/

PDM/PDM17_02/S1049023X00000224a.pdf&code=2bc1e69b

4f70ad90559d97c60a9e146d.

Jones, L.M., Bernknopf, R., Cox, D., Goltz, J., Hudnut, K., 

Mileti, D., Perry, S., Ponti, D., Porter, K., Reichle, M., 

Seligson, H., Shoaf, K., Treiman, J., and Wein, A., 2008, 

The ShakeOut Scenario: U.S. Geological Survey Open-File 

Report 2008–1150 and California Geological Survey Preliminary Report 25, 312 p. and appendixes, accessed April 

12, 2017, at https://pubs.usgs.gov/of/2008/1150/.

Shoaf, K.I, and Bourque, L.B., 1999, Correlates of damage to 

residences following the Northridge earthquake, as reported 

in a population-based survey of Los Angeles County 

residents: Earthquake Spectra, v. 15, no. 1, p. 145–172, 

accessed at http://cat.inist.fr/?aModele=afficheN&cps

idt=1768150.


Chapter K

Societal Consequences of Current Building Code 

Performance Objectives for Earthquakes

By Keith A. Porter

Abstract

When discussing how to reduce future building impairment during earthquakes, structural engineers tend to focus on 

the existing building stock. However, today’s new buildings 

are tomorrow’s existing buildings, and tomorrow’s building 

stock will not be risk free. The leading model building code 

in the United States, the International Building Code (IBC), 

aims to protect the safety of life by providing that a newly 

engineered building will have no more than a 1-percent probability of collapse in the coming 50 years. However, what 

about damage short of collapse? Red-tagged (rendered unsafe 

to enter or occupy) and yellow-tagged (safe only for limited 

use) buildings can significantly impact the performance of the 

building stock as a whole in the months or years after a large, 

but not exceedingly rare, earthquake, such as that simulated 

in the HayWired earthquake scenario. The HayWired scenario 

examines a hypothetical earthquake with a moment magnitude 

(Mw) of 7.0 occurring on April 18, 2018, at 4:18 p.m. on the 

Hayward Fault in the east bay part of California’s San Francisco Bay area. I explore the implications of the current building-code objectives for future large earthquakes by asking this 

question: If the existing building stock were replaced with one 

that entirely complies with current code requirements, what 

would be the consequences in the Big One? If recent studies 

for the Building Seismic Safety Council, Federal Emergency 

Management Agency, and the National Institute of Standards 

and Technology are correct about the collapse fragility of 

engineered buildings, a magnitude (M) 7 earthquake on the 

Hayward Fault could result in the collapse of 8,000 buildings and nearly 500,000 buildings could be impaired—red- or 

yellow-tagged—leaving businesses and households with no or 

restricted use of the buildings they occupy. Low vacancy rates 

for space in the San Francisco Bay area would likely lead to 

the loss of a large number of residents and businesses for the 

region. However, there are simple and relatively inexpensive 

alternatives. If cities required all new buildings to be constructed with an importance factor of 1.5 (a relatively simple 

local modification to the IBC), construction costs would be 

about 1 to 3 percent higher overall and could reduce building 

impairment by 75 percent, keeping several thousand residents 

in their homes and thousands of businesses in operation in the 

event of a M7 earthquake. Additionally, preliminary surveys 

suggest that the public’s expectations for building performance 

may be higher than current code objectives—that is, the public 

wants buildings to be habitable after a disaster, beyond having 

a low probability of collapse. The surveys also indicate that 

the public would be willing to pay 1–3 percent more in construction cost (about 0.5–1.5 percent more in purchase price) 

for buildings that meet this objective. 

Introduction

When discussing how to reduce future earthquake losses, 

structural engineers tend to focus on the existing building 

stock, especially buildings that are fragile and numerous. 

Among these are unreinforced masonry (URM) buildings 

(see, for example, Hess [2008] on URM buildings in the 2008 

ShakeOut scenario—a hypothetical moment magnitude, Mw, 

7.8 earthquake on the San Andreas Fault in southern California), nonductile concrete moment-resisting frame buildings 

(see, for example, Taciroglu and Khalili-Tehrani [2008] in the 

ShakeOut scenario), and large soft-story wood-frame buildings (see, for example, Porter and Cobeen [2012] on San Francisco’s recent effort to manage risk from this building type).

However, today’s new buildings are the existing buildings of tomorrow, and the building stock of tomorrow will not 

be risk free. It is not intended to be. This chapter explores the 

implications of the current leading building code in the United 

States for future natural disasters—the International Building 

Code (IBC). It asks the questions: Where will the current code 

lead, if its current performance objectives are all met? If the 

existing building stock were replaced today with one that complies with current seismic design requirements, what would 

be the consequences? What are some options for cities that 

adopt building codes and engineers who write them, if those 

consequences are unsatisfactory? 

Seismic performance of buildings can be expressed in 

terms of building collapse, post-earthquake safety, functionality, economic loss, and other measures. This chapter focuses 

on collapse and other safety impairment in the sense of the 

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013 ]
58 The HayWired Earthquake Scenario—Engineering Implications

Applied Technology Council’s (ATC) ATC-20 post-earthquake safety inspections. Buildings are red-tagged if they are 

deemed unsafe to enter or occupy and yellow-tagged if they 

are deemed safe for restricted use (ATC, 2005). The ATC-20 

tagging process is an imperfect and sometimes inconsistent 

indicator of building safety, but nonetheless dominates cities’ 

efforts to determine whether buildings are safe to enter and 

occupy after earthquakes and to control the use of damaged 

buildings. 

This chapter is part of the HayWired earthquake scenario, 

which examines a hypothetical earthquake of Mw 7.0 occurring on April 18, 2018, at 4:18 p.m. on the Hayward Fault 

in the east bay part of California’s San Francisco Bay area. 

The simulated earthquake causes Modified Mercalli Intensities of VI–X in the region, with very strong shaking along the 

fault in the densely populated east bay. In a later volume, the 

HayWired scenario will address the economic consequences of 

building damage.

The reader may be aware that some of the content in 

this chapter appears in Porter (2016a). This chapter builds on 

the findings of Porter (2016a) and introduces new material, 

including a discussion on the number of impaired buildings 

in the HayWired scenario, cities’ options for reducing damage in a code-compliant building stock, what-if loss and cost 

estimates if bay area cities were to require all ordinary buildings to be designed with an importance factor of 1.5, and new 

research to elicit public understanding and preferences for the 

performance of a code-compliant building stock.

Background

First, I review some of the important steps that led to the 

seismic design requirements in current building codes. Since 

approximately 1980, engineers have designed California’s 

buildings to achieve a quantified safety objective—that is, 

to ensure that the probability of life-threatening damage to 

any particular structural element or connection is less than 

a specified maximum value, given the occurrence of a fairly 

rare and severe level of shaking. The procedure for doing so 

is called load- and resistance-factor design (LRFD). LRFD 

was developed in the 1970s and early 1980s. Ellingwood 

and others (1980) offer one of the seminal works on LRFD, 

raising LRFD to the status of building-code requirements. In 

that work, the authors provide design parameters that would 

ensure a probability of life-threatening damage of no greater 

than approximately 4 percent given design-level shaking. At 

that time, design-level shaking was defined with a 10-percent 

exceedance probability in 50 years, which equates to a mean 

recurrence interval of 475 years. That 4 percent figure applies 

individually to each component in a building, including the 

beam, column, shearwall, brace, and connection, rather than to 

the building as a whole.

In the 1990s, a procedure called performance-based 

earthquake engineering (PBEE) was developed to manage 

the seismic performance of existing individual buildings as 

a whole system, on the basis of four whole-building performance levels: operational, immediate occupancy, life safety, 

and collapse prevention. See, for example, ATC (1997) for 

more information. 

From the early 1970s through the 2000s, researchers 

working with the Massachusetts Institute of Technology, URS/

John A. Blume and Associates, the Consortium of Universities 

for Research in Earthquake Engineering (CUREE), the Pacific 

Earthquake Engineering Research Center (PEER), and the 

ATC developed another approach to PBEE that quantifies the 

seismic performance of individual buildings in terms of repair 

costs, life-safety impacts, and loss of functionality—in other 

words, dollars, deaths, and downtime. In this study, I refer to 

the procedure as second-generation performance-based earthquake engineering (PBEE-2). See, for example, Czarnecki 

(1973), Kustu and others (1982), Beck and others (1999), Porter and Kiremidjian (2001), Porter (2003), Aslani and Miranda 

(2006), and ATC (2012) for more information.

In the late 2000s, researchers and practitioners working 

with the Federal Emergency Management Agency (FEMA) 

and the National Institute of Building Sciences quantified the 

likely seismic performance of code-compliant buildings in 

terms of the probability that a building would collapse when 

subjected to very rare shaking (the maximum considered 

earthquake, MCE). See ATC (2009) and National Earthquake 

Hazards Reduction Program (NEHRP) Consultants Joint 

Venture (2012) for more information. These authors recommend using the estimated collapse probability as an acceptable probability of collapse for new buildings, suggesting 

that “the probability of collapse due to MCE ground motions 

. . . be limited to 10 percent . . . A limit of twice that value, 

or 20 percent, is suggested . . . for evaluating the acceptability of potential ‘outliers’ . . .” (ATC, 2009). The skeptical 

reader might take issue with the ATC (2009) recommendation because it suggests formulating a performance objective 

only after performance data have already been gathered and 

examined. However, the ATC authors’ objective was to ensure 

that new structural systems would achieve a level of reliability 

consistent with older ones, using collapse probability as the 

consistent reliability objective. The process is similar to the 

way that developers aimed to ensure that new design under 

LRFD would be consistent with the safety of designs performed using allowable stress design, the precursor to LFRD.

Also in the late 2000s, some of the same researchers 

were developing a new basis for building design in which the 

performance objective was to achieve a uniform probability of 

collapse in a given time period. In particular, Luco and others 

(2007) offer a procedure for defining a so-called risk-adjusted 

maximum considered earthquake (MCER) motion such that, if 

a new building satisfied LRFD design requirements at shaking 

based on MCER motion, then the collapse probability in MCER

motion is limited to 10 percent and, more to the point, the 

long-term collapse risk is limited to 1 percent in 50 years (considering all ground motion levels that could occur in those 50 
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 59

years and their estimated recurrence frequency). To illustrate 

this concept, a recent map showing MCER ground motion for 

short-period construction is shown in figure 1. What is meant 

by “based on MCER motion” is that design acceleration is the 

product of the mapped MCER motion multiplied by a factor of 

2/3, a factor to account for site amplification, a factor to take 

advantage of ductility, and, in some cases, a factor to reflect 

greater building importance. Risk-adjusted design has been 

incorporated into U.S. seismic design guidelines (American Society of Civil Engineers [ASCE], 2010) and the IBC 

(International Code Council [ICC], 2012). Though they are 

not both codes, they will hereafter collectively be referred to 

as “the code,” because ASCE-7 is adopted by reference in the 

2012 IBC.

To be clear, the primary performance objective of the 

most recent U.S. seismic design code requirements is to 

ensure that new engineered buildings have no more than a 

1-percent collapse probability over 50 years. There are secondary objectives as well. The 2015 NEHRP Recommended 

Seismic Provisions state that ordinary buildings in earthquakes will “Avoid serious injury and life loss due to structural collapse, failure of nonstructural components or systems, 

and release of hazardous materials . . . and reduce structural 

and nonstructural repair costs where practicable to do so.” 

The mention of reducing nonstructural repair costs refers to 

construction requirements that are believed to cost-effectively 

limit damage, such as bracing large suspended ceilings, as 

shown in figure 2. However, only the collapse probability is 

quantified. Note that the code does not aim to ensure buildings are usable or even repairable after an earthquake, but 

rather that occupants can safely exit a building after designlevel shaking. Engineers sometimes refer to this objective as 

“life-safety performance,” acknowledging that some buildings 

are designed stronger (for example, those housing hazardous 

or essential facilities).

The code appears to achieve its life-safety performance 

objective. Table 1 compares some of the leading threats to 

life in the United States with the modeled earthquake lifesafety risk of continuous 24 hours a day, 7 days a week 

(24/7) occupancy of a building designed to meet the current 

building code. The number of deaths in new buildings during 

earthquakes assumes that the average new building somewhat exceeds the minimum safety requirement, exhibiting a 

0.6 percent probability of collapse in 50 years instead of 1 

percent. It also assumes that collapse affects 25 percent of the 

building area, as described in Porter (Urban Search and Rescue, this volume), and that 10 percent of occupants located 

in collapsed building areas die as a result of the collapse 

(FEMA, 2012a). Deaths in uncollapsed parts of the building 

are omitted from this calculation. Thus, the mortality rate can 

be estimated as 0.006/50 years×0.25×0.10=3×10-6/year, or 0.3 

per 100,000 people per year. The figure would apply to 24/7 

occupancy of buildings that comply with the 2012 IBC—that 

is, in buildings with earthquake loads (as opposed to wind 

loads) that govern the strength of the lateral force resisting 

system. 

120° 110° 100° 90° 80° 70°

45°

40°

35°

30°

25°

Areas where suspected

nontectonic earthquakes

have been deleted

0.8

0.4

0.3

0.2

0.14

0.1

0.06

0.04

0.02

0

EXPLANATION

Spectral response acceleration 

for 5 hertz, expressed as a fraction 

of gravitational acceleration (g)

0 500 1,000 KILOMETERS

0 500 1,000 MILES

Figure 1. Map of risk-adjusted maximum considered earthquake (MCER) shaking for the contiguous United States (modified from 

Petersen and others, 2014).
60 The HayWired Earthquake Scenario—Engineering Implications

Figure 2. Photograph showing examples of building-code 

requirements to limit nonstructural repair costs. Note the diagonal 

wires and vertical post (called a compression post) that support 

the suspended ceiling. (Photograph from Federal Emergency 

Management Agency, 2012a.)

Table 1. Mortality rates due to building collapse during earthquakes compared with other causes of death in the United States.

Peril Deaths per 100,000 people per year Where and when

Heart disease 194 United States 2010 (Heron, 2013)

All accidents 39 United States 2010 (Heron, 2013)

Occupational fatality, roofers 32 United States 2011 (Bureau of Labor Statistics, 2013)

Auto accidents 11 United States 2009 (U.S. Census Bureau, 2012)

Firearms 10 United States 2010 (Heron, 2013)

New building collapse during earthquakes 0.3 24/7 occupancy, wherever earthquake loads govern 

the strength of the lateral force resisting system

Earthquakes past ~50 years 0.007 California 1964–2014 (Wikipedia [2017], drawing on 

a variety of sources)

2. Quantitative code objectives are also expressed in 

terms of collapse probability in MCER shaking. However, in a large earthquake, like that in the HayWired 

scenario, only a small geographic area might experience MCER shaking or greater. What happens at 

lower levels of shaking?

3. Quantitative code objectives are expressed in terms 

of collapse probability for a single building. What 

happens at the societal level, for example, in terms of 

the fraction or number of impaired buildings in the 

epicentral region?

4. Suppose a city or a state, such as California, adopted 

the IBC but decided to modify it to require stronger buildings. What would be the result in terms of 

the fraction or number of impaired buildings in the 

epicentral region? Stiffness also matters for building 

performance, especially repair cost and duration, but 

I focus here on strength, which more strongly affects 

collapse and red tagging. See Multihazard Mitigation Council (2017) for a discussion on the effects of 

greater stiffness as well as strength.

The answers to these questions can inform the public’s 

understanding and expectations for code-compliant buildings 

and the understanding of their elected officials who adopt 

model building codes like the IBC. The remainder of this 

report seeks to answer questions 1–4.

After an earthquake, red- and yellow-tagged buildings 

can be impaired for months. Comerio (2006), who studied 

building restoration after the 1994 Northridge earthquake, 

wrote that:

Initial inspections of more than 440,000 units listed 

7,000 single-family homes, 2,000 mobile homes, 

and 49,000 multifamily units [as] red- and yellowtagged. Three years after the event, when insurance 

claims were tallied, it became clear that moderate 

damage to single-family homes was under-counted 

in the post-event inspections, as more than 195,000 

homeowners made insurance claims, for an average of $30,000 to $40,000 . . . About 40 percent of 

homeowners began repairs within one year. . .For 

Implications of Seismic Performance 

Objectives for the HayWired Scenario

The foregoing brief history discussion of seismic performance objectives raises some interesting questions that can be 

explored with the HayWired scenario.

1. Quantitative building-code objectives are expressed 

in terms of collapse risk during a 50-year building 

design life, considering all possible levels of shaking and their likelihood of occurrence. What about 

other modes of building impairment, namely red- and 

yellow-tagging? As used here, a red tag refers to a 

placard attached to an earthquake-damaged building 

that declares the building unsafe to enter or occupy. A 

yellow tag declares the building to be damaged such 

that its use is restricted. Restrictions might prevent 

the use of part of the building or they might allow 

only brief occupancy (for example, to remove possessions). See figure 3.
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 61

the remainder, it took two to three years to resolve 

the insurance claim, and repairs were likely to be 

delayed until the insurance funding was available. 

The time needed for repairs of large apartment and 

condominium buildings was often longer.

Comerio’s (2006) findings imply that even a yellow-tagged 

building may be unavailable for months or more after the 

mainshock earthquake. In light of Comerio’s observation that 

58,000 housing units were red- or yellow-tagged, but 195,000 

homeowners made insurance claims averaging $30,000 to 

$40,000, it seems that more than 3 times the number of collapsed, red-tagged, and yellow-tagged buildings may be at 

least moderately damaged—that is, with repair costs around 

$30,000 to $40,000. Whereas this study focuses on impaired—

that is, collapsed, red-tagged, and yellow-tagged—buildings, it 

is important to keep in mind that many more buildings may be 

adversely affected by earthquake shaking. 

Impairment Rate at MCER Shaking

To quantify impairment rates of buildings at MCER shaking, I begin with some observations. Figure 4 summarizes the 

results of incremental dynamic analyses of a large number of 

sample buildings (NEHRP Consultants Joint Venture, 2012). 

The figure shows the fraction of nonlinear dynamic analyses 

at MCER-level spectral acceleration response in which the 

building is estimated to have collapsed, as a function of the 

building’s estimated fundamental period of vibration (“design 

period” in the figure). In private conversation, the lead author 

expressed the opinion that many of the sample buildings ought 

to be excluded from this analysis, especially the circled data 

points and all of the data for buildings with design period less 

than 0.5 seconds (C. Kircher, oral commun., May 8, 2014). 

The former should be excluded because they would not 

comply with the current building code, the latter because he 

believes the structural analyses incorrectly associated a threshold level of peak transient drift ratio with collapse. Excluding 

these and taking the average of the remaining data suggests the 

average probability of collapse is 6 percent at MCER shaking.

In addition to collapsed buildings, how many buildings 

are red- or yellow-tagged in MCER shaking? Unfortunately, 

there are no analytical studies of red and yellow tagging comparable to the studies of collapse by ATC (2009) and NEHRP 

Consultants Joint Venture (2012). Table 2 lists evidence for 

the ratio of red tags to collapses, where both are known—an 

admittedly limited dataset. The data suggest approximately 

13 buildings are red-tagged for every collapsed building. 

Table 3 shows evidence for 3.8 yellow tags per red tag. Let 

r denote the ratio of impaired buildings to collapsed buildings. With 13 red tags per collapse and 3.8 yellow tags per 

red tag, r=63 impaired buildings for each collapsed building 

(1+13+13×3.8=63.4), including the collapsed building. The 

data in tables 2 and 3 do not reflect a code-compliant stock 

and they do not account for variability with shaking intensity. 

However, using this empirical evidence is preferable to using 

Hazus-MH software (FEMA, 2012b) or another forward 

analytical model, because engineers generally prefer to rely 

on empirical evidence over analytical results. Remember, I am 

only using evidence from past earthquakes to estimate ratios 

of red tags to collapse and yellow tags to red tags, not rate of 

collapse.

Table 4 summarizes the implications of these findings 

for the building stock in a small area that experienced MCER

shaking. The values in table 4 rely solely on the building 

code’s explicit objective (10 percent collapse probability conditioned on MCER shaking), reduced to provide a best estimate 

rather than an upper limit (6 percent rather than 10 percent), 

and that the ratio of red and yellow tags to collapses of new 

buildings would be the same as has been observed for the 

1989 Loma Prieta and 1994 Northridge earthquakes.

A B

UNSAFE

DO NOT ENTER OR OCCUPY

(THIS PLACARD IS NOT A DEMOLITION ORDER)

This structure has been inspected, found to

be seriously damaged and is unsafe to

occupy, as described below:

Do not enter, except as specifically

authorized in writing by jurisdiction.

Entry may result in death or injury.

Facility Name and Address:

Date

Time

This facility was inspected under

emergency conditions for:

(Jurisdiction)

Inspector ID / Agency

Do Not Remove, Alter, or Cover this Placard

until Authorized by Governing Authority

RESTRICTED USE Caution: This structure has been

inspected and found to be damaged as

described below:

Entry, occupancy, and lawful use are

restricted as indicated below:

Date

Time

This facility was inspected under

emergency conditions for:

(Jurisdiction)

Inspector ID / Agency

(Caution: Aftershocks since inspection

may increase damage and risk.)

Do Not Remove, Alter, or Cover this Placard

until Authorized by Governing Authority

Facility Name and Address:

Figure 3. Images of (A) red and (B) yellow tags used to indicate the level of impairment to an earthquake-damaged building (images 

from Applied Technology Council, 2005).
62 The HayWired Earthquake Scenario—Engineering Implications Collapse probability, in percent

Design period (T ), in seconds

35

30

25

20

15

10

5

0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

EXPLANATION

Bearing-wall systems

Building-frame systems

Moment-frame systems

Collapse probability, in percent

Design period (T ), in seconds

35

30

25

20

15

10

5

0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

EXPLANATION

Bearing-wall systems

Building-frame systems

Moment-frame systems

A

B

Figure 4. Graphs showing collapse probability conditioned on risk-adjusted maximum considered earthquake (MCER) shaking versus 

design period for buildings examined by NEHRP Consultants Joint Venture (2012). The buildings were subjected to multiple nonlinear 

dynamic structural analyses at a level of motion associated with MCER shaking. A, Graph showing all buildings examined by NEHRP 

Consultants Joint Venture (2012). B, Graph excluding the buildings that the lead author of NEHRP Consultants Joint Venture (2012) 

thought should be excluded from the analysis, because they would not comply with current code or did not correctly associate peak 

transient drift ratio with collapse (C. Kircher, oral commun., May 8, 2014). The remaining data define an average collapse probability of 6 

percent for all design periods considered (dashed red line). (Images modified from NEHRP Consultants Joint Venture, 2012.)
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 63

Validation Using Data from the August 

2014 Napa Earthquake

Data acquired from the City of Napa, California, after 

the completion of this analysis can be compared with the 

data in tables 2 and 3. As of October 21, 2014, the City of 

Napa recorded 1,767 yellow tags and 175 red tags (F. Turner, 

California Seismic Safety Commission, written commun., 

March 10, 2015). Damage descriptions acquired from the City 

of Napa in a separate database (K. Wallis, GIS Coordinator for 

City of Napa, written commun., March 12, 2015) suggest 34 

structures appear to meet the definition of collapse. According to FEMA P–154 (ATC, 2015), building collapse means 

that any part of the gravity system experienced dynamic 

instability leading to the loss of load-bearing capacity. The 

dynamic instability leads to severe structural deformation of a 

potentially life-threatening nature, especially falling of all or 

portions of a structure. Note that, as used here, partial building 

collapse means that the dynamic instability occurs only in a 

portion of the building.

The 34 collapses are included among the yellow and red 

tags, such that the ratio of impaired buildings to collapses is 

(1,767+175)/34=57:1. The ratio of yellow to red is higher in 

the 2014 Napa earthquake than in the Loma Prieta and Northridge earthquakes and the ratio of red tags to collapse is lower. 

These two ratios counteract each other to result in a ratio of 

impaired buildings to collapses (57:1) that closely approximates those from the Loma Prieta and Northridge earthquakes 

(63:1).

Impairment Rate at Other Levels of 

Shaking

Until now, I have considered the impairment rates of a 

code-compliant building stock that is shaken to exactly MCER

shaking. Impairment can be estimated at other levels of shaking as well. It is probably higher at higher levels of shaking, 

and lower at lower levels of shaking. Because the strength of 

new buildings varies from place to place depending largely 

on MCER, I define new measures of shaking called demandto-design ratio (DDR), with two varieties: DDRS

 and DDR1

defined as follows.

•	 DDRS is the 5-percent damped spectral acceleration 

response at a period of 0.2 seconds in a particular 

earthquake at a particular location divided by SMS—

the MCER 5-percent damped spectral acceleration 

response parameter at short periods adjusted for site 

class effects, as defined in American Society of Civil 

Engineers/Structural Engineering Institute (ASCE/

SEI) 7-10 section 11.4.3. Note that the subscript in 

DDRS indicates short period, similar to that in SMS. 

Table 2. Red tags and building collapses in select California 

earthquakes.

[NIST, National Institute of Standards and Technology; SEAONC, Structural 

Engineers Association of Northern California; EQE, EQE International; Cal 

OES, California Governor’s Office of Emergency Services, Geographic Information Systems Group]

Earthquake Red tags Collapse Reference

1989 Loma Prieta, 

San Francisco 

Marina District

110 7 NIST (1990), Harris 

and others (1990)

1989 Loma Prieta, 

City of Santa Cruz1

100 40 SEAONC (1990), 

Fradkin (1999)

1994 Northridge2 2,157 133 EQE and Cal OES 

(1995)

Total 2,367 180 Ratio=13:1

1

One hundred red tags is an estimate; 300 red tags county wide, factored 

by number of structures in city versus county, and reduced by number of 

collapses to avoid double counting.

2

One hundred thirty-three collapsed buildings is taken from the ATC-20 

form data in an unpublished database described by EQE and Cal OES 

(1995); red tags reduced by number of collapses to avoid double counting.

Table 3. Yellow and red tags in select California earthquakes.

[SEAONC, Structural Engineers Association of Northern California; EQE, 

EQE International; Cal OES, California Governor’s Office of Emergency 

Services, Geographic Information Systems Group]

Earthquake Yellow tags Red tags Reference

1989 Loma Prieta 3,330 1,114 SEAONC (1990)

1994 Northridge 9,445 2,290 EQE and Cal 

OES (1995)

Total 12,775 3,404 Ratio=3.8:1

Table 4. Performance of new buildings in a small area subjected 

to risk-adjusted maximum considered earthquake (MCER) shaking.

Building condition Percent/ratio Fraction of stock

Collapsed 6 percent of stock 6 percent

Red-tagged and not 

collapsed

13 red tags per collapse78 percent

Yellow-tagged 3.8 yellow tags per 

red tag

Most of the remaining stock
64 The HayWired Earthquake Scenario—Engineering Implications

•	 DDR1 is the 5-percent damped spectral acceleration 

response at a period of 1.0 second in a particular 

earthquake at a particular location divided by SM1—

the MCER 5-percent damped spectral acceleration 

response parameter at a period of 1 second adjusted 

for site class effects as defined in ASCE/SEI 7-10 

section 11.4.3. The subscript in DDR1 and SM1 refers 

to the period length. 

One can map DDRS for a given earthquake scenario by 

normalizing the ground-motion map with respect to ASCE/

SEI 7’s MCER ground motion parameter map for a 5-percent 

damped, 0.2-second spectral acceleration response, adjusted 

for site class SMS. The result for the HayWired scenario mainshock—at least for the study area modeled by Aagaard and 

others (2010)—is shown in figure 5.

I further idealize the collapse capacity of all code-compliant buildings as a lognormally distributed random variable 

measured in terms of DDRS or DDR1. I will use DDRS when 

considering the performance of buildings with period less 

than the corner period, which corresponds to the intersection 

of the constant-acceleration and constant-velocity parts of the 

ASCE/SEI 7 design spectrum and is equal to SM1/SMS. I will 

use DDR1 when the period is at or above the corner period. 

More qualitatively, DDRS provides a better measure for lowrise buildings (less than 3 or 4 stories, or so), whereas DDR1

is the better measure for taller buildings. Taller buildings are 

actually designed based on SM1/T, where T is the building’s 

estimated small-amplitude fundamental period of vibration. If 

I were to define DDR for these taller buildings as the spectral 

acceleration (Sa) response at their fundamental period of vibration, that is, Sa

(T), I could then estimate Sa(T)=Sa(1 second)/T, 

normalize by SM1/T, and the period T would cancel out of the 

numerator and denominator, leaving DDR1 as already defined. 

At the upper limit, I ignore those buildings that are so tall that 

their fundamental period of vibration lies on the constant-displacement portion of the response spectrum. They tend to have 

lateral strength governed by wind loads rather than earthquake 

123° 39°

38°

37°

122° 121°

0 20 40 60

20 40 60

MILES

0 KILOMETERS

PA C I F I C O C E A N

CALIF

0.0 0.2 0.4 0.6 0.8 1.0

Demand-to-design ratio

San Jose

Oakland San Francisco

Area

of map

Figure 5. Map of the San Francisco Bay 

region, California, showing demand-todesign ratio for the moment-magnitude-7.0 

mainshock of the HayWired earthquake 

scenario, calculated for a 5-percent 

damped, 0.2-second spectral acceleration. 

(Map created using OpenSHA Generic 

Mapping Tools Map Plotter; Field and 

others, 2003.)
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 65

loads, so the formulation developed here would grossly overestimate collapse of these buildings. 

By “lognormally distributed” it is meant that this work 

idealizes the collapse capacity of a building (the level of shaking that the building can tolerate without collapsing) as having 

a cumulative distribution function of the form:

 

, (1)

where 

P[A] denotes the probability that statement A is 

true, 

X denotes the uncertain collapse capacity of a 

building measured in terms of DDRS or 

DDR1, 

x is a particular value of X, 

Pc(x) denotes the probability that the building will 

collapse when subjected to shaking of x, 

	 Φ(z) denotes the standard normal cumulative 

distribution function evaluated at z, 

q is the median value of X, and 

b is the standard deviation of ln(X). 

Equation 1 represents a fragility function, which here 

means a relation between a measure of environmental excitation on the x-axis (here, DDR) and the occurrence probability 

of an undesirable outcome on the y-axis (here, collapse). 

Since the undesirable outcome is building collapse, equation 1 

represents a collapse fragility function. Equation 1 is in a form 

that is commonly used by many PBEE-2, loss estimation, and 

probabilistic seismic risk analysis studies to estimate damage 

to structures and components, including collapse. It is not that 

collapse capacity of buildings and building components are 

actually lognormally distributed, but rather that the lognormal often fits observed performance data reasonably well, is 

convenient, has the advantage of decades of tradition, and has 

support in information theory. The mention of information 

theory refers to the fact that the lognormal distribution is the 

maximum-entropy distribution—the one that assumes the least 

information—for a positively valued random variable with 

fixed median and logarithmic standard deviation.

To return to the problem of impairment rate at levels of 

shaking other than at MCER, equation 1 requires two parameters, q and b. Luco and others (2007) examine a range of 

values of b, from 0.6 to 1.0, and settled on b=0.8 as their best 

estimate. This value of b was subsequently used in developing the ASCE/SEI 7-10 maps of MCER and is also applied 

here. With the knowledge that the collapse probability, Pc, is 

Pc(1.0)=0.06 (as calculated in fig. 4), one can calculate q as:

, (2)

which leads to q=3.47. That is, the median collapse DDR is 

3.47, which means the median collapse capacity is 3.47 times 

MCER shaking, whether measured in terms of SMS or SM1.

Now, the collapse probability of an arbitrary, code-compliant, engineered building can be modeled using equation 1 

with q=3.47 and b=0.8. The collapse probability therefore is:

. (3)

As shown in figure 6, one can use this equation to estimate 

that at DDR=0.5, the collapse probability is 0.008, meaning 

that 0.8 percent of buildings are estimated to collapse at half 

of MCER shaking.

When one uses a lognormal fragility function for probabilistic seismic risk analysis and fixes a point on the curve 

near x=0.1 or 0.2 with a credible y-value, the long-term failure 

rate tends to be fairly insensitive to the value of b (Kennedy 

and Short, 1994; Porter, 2017). That means that selecting a 

different value of b than the one suggested by Luco and others (2007) should make little difference, within a reasonable 

range. A lower value of b will tend to decrease the estimated 

number of failures at low values of x and increase the number 

of high values of x, with little change to the total. A similar 

statement can be made about selecting a higher value of b. 

Applying the same ratios of red tags to collapses and 

yellow to red tags determined in the previous sections, one 

can further estimate that under the model used for collapses 

by ASCE/SEI 7-10, approximately half of buildings shaken at 

half the MCER will be impaired (fig. 7).

q =1.0× exp −b×Φ−1

( (0.06))

Pc (x) =Φ ln(x/3.47)

0.8

⎛

⎝

⎜ ⎞

⎠

⎟

P[X ≤ x] = Pc (x) =Φ ln(x/q)

b

⎛

⎝

⎜ ⎞

⎠

⎟

5

10

15

20

25

0 0.5 1 1.5

Collapse probability, in percent

Demand-to design ratio

Figure 6. Graph showing the cumulative distribution function of 

building collapse probability for a range of demand-to-design ratio 

(DDR) values. When DDR is 0.5—that is, half of the risk-adjusted 

maximum considered earthquake (MCER) shaking—the probability 

of collapse is about 0.8 percent.
66 The HayWired Earthquake Scenario—Engineering Implications

Fraction and Number of Impaired 

Buildings at the Societal Level

More generally, the impairment rate (Pi) can be estimated 

as a function of DDR—denoted by Pi(x)—using equation 4. 

To do so, simply multiply equation 3 for collapse probability 

by the ratio of impaired buildings to collapsed buildings: 

, (4)

Using the map of DDR (fig. 5), one can map impairment 

rate spatially, as shown in figure 8. The figure only shows 

impairment results from the shaking model; it does not reflect 

impairment owing to ground failure, including liquefaction, 

landslide, and surface faulting, which would collectively tend 

to increase impairment rates by some unknown, but probably 

smaller, degree. One can then overlay the impairment rate on 

a map of the estimated building stock to estimate the number 

of impaired buildings in a scenario like HayWired. To overlay 

this information, scale the impairment rate by the estimated 

building stock:

, (5)

where 

Ni denotes the number of impaired buildings, 

j is an index to locations in the inventory of 

building stock (such as census blocks), 

n is the number of locations in the inventory, 

xj denotes the shaking in location j expressed in 

terms of DDR, and 

Bj denotes the number of buildings in location j. 

Evaluating equation 5 at the level of census tracts and using 

FEMA’s enhanced building inventory, I find that shaking in 

the HayWired scenario would impair approximately 495,000 

buildings. Table 5 lists the estimated number of shakinginduced impairment to buildings. In this scenario, using an 

average of three people per building (homes, workplaces, or 

other buildings), up to 1.5 million people could be displaced 

from those buildings for months or more while the buildings 

were repaired or replaced.

Options for Improving Building-Stock 

Performance

Cities and states tend to have limited options for modifying the provisions of model building codes like the IBC. 

They tend to lack the necessary resources to do anything other 

than accept or reject the code. However, there is one code 

parameter called the seismic importance factor (denoted by 

Ie in ASCE/SEI 7-10) that one can think of as a volume dial 

to uniformly increase the design strength of ordinary buildings in a community by a constant factor. The City of Moore, 

Restricted use, 40 Usable after

earthquake, 49

Unsafe, 10

Collapse, 0.8

Figure 7. Pie diagram showing the impairment rate, in percent, 

of buildings at one half the risk-adjusted maximum considered 

earthquake (MCER) shaking. Buildings that are considered 

impaired are either collapsed, red-tagged, or yellow-tagged.

Pi(x) = 63.4 ×Φ ln(x/3.47)

0.8

⎛

⎝

⎜ ⎞

⎠

⎟ ≤1.0

Ni = Pi j=1

n

∑ x( j)× Bj

Oklahoma, for example, recovering from a catastrophic 

tornado, recently required that new buildings be designed to 

resist windspeeds 50 percent higher than that required by the 

IBC—that is, 135 miles per hour (mi/hr) rather than 90 mi/hr 

(City of Moore, 2014). Because wind pressure is proportional 

to the square of velocity, the 50-percent increase in design 

windspeed equates to a 125-percent increase in design strength 

(because 1.52=2.25), which means that the City of Moore 

was effectively adopting a wind importance factor of 2.25 

for ordinary buildings. For reference, buildings along much 

of the U.S. Gulf and Atlantic Coasts are required to resist 

windspeeds in excess of 140 mi/hr, so the City of Moore was 

not requiring unprecedented or even particularly uncommon 

design strength.

Suppose all San Francisco Bay area buildings were suddenly replaced with new ones built with Ie

=1.5—that is, 50 

percent stronger than the current code minimum. (Structural 

engineering readers should not infer that this hypothetical 

situation suggests that all buildings are designed as Risk Category IV under ASCE/SEI 7-10, with the attendant additional 

requirements. The situation considered here is that the State of 

California or every jurisdiction adopts the IBC with the exception that ASCE/SEI 7-10 table 1.5-2 is altered so that Ie

=1.5 

for all risk categories.)

Similar to the case in the City of Moore, adopting a 

seismic importance factor of Ie=1.5 would not impose extraordinary or particularly expensive requirements on the design of 

new buildings, at least for much of California. Consider the 

map of short-period MCER shaking in figure 9. The contours 

show the mapped short-period (0.2 second) MCER shaking 
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 67

Figure 8. Map of the San Francisco Bay 

region, California, showing impairment of 

existing buildings, if they all complied with 

current building codes, for the momentmagnitude-7.0 mainshock of the HayWired 

earthquake scenario. Building impairment 

includes collapsed, red-tagged, and yellowtagged buildings. (Map created using 

OpenSHA Generic Mapping Tools Map 

Plotter; Field and others, 2003.)

on rock, denoted by SS in ASCE/SEI 7-10 and measured in 

percent of gravitational acceleration (g). For mapped values 

of 100 or greater (1.0 g or greater), the amplification factor to 

account for site conditions (denoted by Fa in ASCE/SEI 7-10) 

is approximately 1.0, so the map also shows SMS, the MCER

shaking accounting for site conditions other than rock. After 

accounting for common site conditions, SMS in Sacramento, 

California, is approximately 0.8 g, whereas in San Francisco 

SMS varies between 1.5 and 2.3 g. This means that if a lowrise building in western San Francisco were built with an 

importance factor of Ie=1.0, picked up, and moved bodily to 

Sacramento, the building would satisfy seismic design requirements for a building with Ie

 of almost 3.0 in Sacramento. If the 

same building were instead picked up and moved bodily only 

5 miles east inside of San Francisco, it would satisfy seismic 

design requirements for a building with Ie=1.5. Similarly, an 

ordinary building constructed in Concord, California, with 

Ie=1.0 (SMS=2.25 g) and moved 35 miles south near the San 

Jose International Airport (SMS=1.5 g) would satisfy design 

requirements for Ie=1.5. Buildings are built in both locations 

Table 5. Shaking-related building impairment estimates 

for a hypothetical moment-magnitude-7.0 earthquake 

occurring on the Hayward Fault in the east bay part of 

the San Francisco Bay area, like that modeled in the 

HayWired earthquake scenario. 

Building condition Estimated number of buildings

Collapse 8,000

Red-tagged 101,000

Yellow-tagged 386,000

Total 495,000

39°

123° 122° 121°

38°

37°

0.0 0.2 0.4 0.6 0.8 1.0

0 20 40 60

20 40 60

MILES

0 KILOMETERS

Fraction of impaired buildings

PA C I F I C O C E A N

Area

of map

CALIFORNIA

San Francisco Oakland

San Jose
68 The HayWired Earthquake Scenario—Engineering Implications

all the time, practically and cost effectively, which means 

that imposing a design requirement that ordinary buildings 

be designed for Ie=1.5 would be practical and not particularly 

expensive throughout much of the San Francisco Bay area, 

indeed in much, if not all, of California.

Informal discussion between the author and four California engineers suggests that designing to Ie

=1.5 would increase 

construction costs on the order of 1–3 percent (D. Bonneville, 

Degenkolb Engineers, oral commun., January 2015; E. Reis, 

U.S. Resiliency Council, oral commun., April 2014; J. Harris, 

J. R. Harris and Company, oral commun., August 2015; and 

R. Mayes, Simpson, Gumpertz and Heger, Inc., oral commun., January 2015). The estimate is further supported by 

NEHRP Consultants Joint Venture (2013), whose authors find 

that to redesign six particular buildings in Memphis, Tennessee, so that they comply with the 2012 IBC rather than the 

1999 Southern Building Code, their strength would increase 

on average by 60 percent and their construction cost would 

increase between 0 and 1.0 percent. Olshansky and others 

(1998) found a similar estimated marginal cost to increase 

from no seismic design to code minimum. Furthermore, the 

estimated cost to achieve an immediate occupancy performance level rather than life safety for one of the index buildings of the CUREE-Caltech Woodframe Project is similarly 

marginal (Porter and others, 2006). 

If the previous arguments do not convince the skeptical reader, I offer one more. A square-foot cost manual, such 

as RSMeans (2011), shows that approximately 67 percent 

of construction cost of a typical new building is spent on the 

architectural, mechanical, electrical, and plumbing assemblies, 

approximately 17 percent on overhead and profit, and of the 

remaining 16 percent that represents structural cost, approximately half is spent on labor. Most of the remaining 8 percent 

(mostly structural material cost) is spent on the gravity-resisting system: the foundation, floor slabs, columns, and beams. 

Of the small remaining portion that is spent on materials for 

the earthquake load resisting system (perhaps 2 percent), it 

could be increased by 50 percent to achieve a 1-percent overall 

construction cost increase (the purchase price increase would 

be less if land value is considered). However, strength does not 

increase linearly with quantity of material. Quantity need not 

double or even increase by half to achieve a 50 percent stronger building. Strength can increase with the square or a higher 

power of material. For example, a W44×230 wide-flange steel 

shape is about 63 percent stronger than a W30×191 shape, but 

weighs (and therefore costs) only about 20 percent more without requiring any additional labor to install. In this particular 

case, strength increases with more than the square of cost 

(1.202.6=1.63). More extreme cases can be cited. 

In California, a marginal construction cost increase of 

1–3 percent would translate to a smaller marginal development 

cost increase because land can constitute more than half the 

value of a building and its value is unaffected by Ie. Suppose 

the entire 1–3 percent cost increase was passed on to buyers 

Figure 9. Map of risk-adjusted maximum 

considered earthquake (MCER) shaking in 

the San Francisco Bay region, California. 

Map shows contours of maximum-direction, 

short-period (0.2 second) spectral response 

acceleration with 5-percent critical damping 

on sites with 760 meters per second average 

shear wave velocity in the top 30 meters of 

soil. Contours on the map are expressed as 

a fraction of gravitational acceleration (g). 

Contours are shown in increments of 0.1 below 

1.0 g and in increments of 0.25 above 1.0 g. 

(Map modified from Building Seismic Safety 

Council, 2015.)

37°

38°

39°

1

2.0

1.5

0.4

1.5

1.5

1.25

1.0

0.5

1.5

37°

38°

24° 23° 22°

23° 22° 21°

0

0 20

20 40

40 KILOMETERS

MILES

San Jose

Concord

San Francisco Oakland

PA C I F I C O C E A N

Area

of map

CALIFORNIA

EXPLANATION

City

Contour lines—Short-period (0.2 second) 

MCER

 shaking, expressed as a fraction 

of gravitational acceleration (g)

Areas with a constant MCER

 shaking of 

1.50 g
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 69

0

5

10

15

20

25

0.5 1.0 1.5

Collapse probability, in percent

Demand-to-design ratio

Ie = 1.0

Ie = 1.5

Figure 10. Graph showing collapse probability as a 

function of demand-to-design ratio for an importance 

factor (I

e

) of 1.0 and 1.5. Note the significant drop in 

collapse probability for buildings with a higher value of I

e

. 

and not absorbed by a reduction in the value of land and that 

land accounted for half the value of the property (it is often 

much more). The increase in purchase price might range 

between 0.5 and 1.5 percent—that is, on the order of 1 percent. In Porter (Not Safe Enough, this volume), I will examine 

whether the public is willing to pay this increased purchase 

price.

What would be the consequences in terms of building 

impairment in the HayWired scenario mainshock if the State 

of California or every San Francisco Bay area city adopted the 

IBC but required that all new ordinary buildings be designed 

with an importance factor Ie=1.5? One can calculate the effect 

on collapse probability by retaining the assumption that collapse probability is reasonably approximated with a lognormal 

cumulative distribution function, retaining the assumption 

that the standard deviation of the natural logarithm of collapse 

capacity is approximately 0.8, and multiplying the median 

collapse capacity by a factor of 1.5 (fig. 10). Assuming the 

ratios of red tags to collapses and yellow tags to red tags (3.8:1 

and 13:1, respectively) still hold, then the map of impairment 

rate would be that shown in figure 11. Again, results are faily 

insensitive to parameter b.

Evaluating equation 5 at the level of census tracts and 

assuming Ie=1.5 results in the estimate that shaking in the 

HayWired scenario mainshock would impair about 75 percent 

fewer buildings than when Ie=1.0—impairing 130,000 buildings total, rather than 495,000. Table 6 shows a side-by-side 

comparison of building impairment under Ie=1.0 and Ie=1.5 

conditions. Recall that the cost of this reduction in impairment 

might realistically result in a marginal increase in purchase 

price of 0.5–1.5 percent. To put it another way, it may increase 

the monthly mortgage for a new $500,000 house in Concord, 

California, for example, from $3,400 to $3,430. The values in 

table 6, however, do not include buildings that are moderately 

damaged. Recall that Comerio (2006) found that moderately 

damaged housing units numbered three times as many as collapsed, red-tagged, or yellow-tagged buildings after the 1994 

Northridge earthquake.

I consider the Ie=1.0 case that the HayWired mainshock 

would impair 500,000 buildings if all buildings behaved like 

new ones. The San Francisco Bay area contains approximately 

2 million buildings, so 500,000 represents about 25 percent 

of buildings in the area. What happens to the people who live 

or work in those buildings? Vacancy rates in recent years are 

estimated to be approximately 0.5 percent of single-family 

dwellings, 3 percent of residential rental units (U.S. Census 

Bureau, [n.d.]), and 12–15 percent of San Francisco office 

space (Wells Fargo Securities, 2014). These rates are far too 

low to accommodate the displaced homes and businesses, and 

may force people to move out of the area.

With a building stock designed to Ie=1.5, an estimated 

130,000 buildings, or approximately 6 percent of the building 

stock, would be impaired in the HayWired mainshock. Though 

that number still exceeds the vacant stock, it is approximately 

within the bounds called for by the San Francisco Planning 

and Urban Research (SPUR) Shelter-in-Place Task Force 

(2012), an urban-planning policy document that recommends 

housing in San Francisco be resilient enough that 95 percent 

of the population could shelter in place. With doubling up and 

other emergency accommodations, this scenario would be 

more bearable than the alternative Ie=1.0 case.

Building Impairment Resulting from 

Ground Failure

The building impairment estimates thus far discussed 

do not account for ground failure—liquefaction, landslide, 

or surface faulting. The effect of surface faulting can be 

estimated by assuming that every building whose footprint 

crosses a fault rupture where there is offset at the surface 

would be impaired. In the HayWired scenario, surface rupture 

would result in damage to approximately 500 existing buildings, adding about 0.1 percent to the total impairment quantity 

if all buildings were designed to Ie=1.0, or 0.4 percent if all 

buildings were designed to Ie=1.5. However, the damage to the 

code-compliant building stock would probably be much lower, 

for reasons explained next.

The 1972 Alquist-Priolo Fault Zoning Act (California 

Department of Conservation, [n.d.]) requires that local agencies regulate most development projects within about 50 feet 

of an active fault, such as the Hayward Fault. Projects include 

all land divisions and most buildings. The act generally serves 

to prevent new construction on top of a known active fault. 

Single-family wood-frame and steel-frame dwellings as 

high as two stories that are not part of a development of four 

or more units are exempt. Cities are free to impose greater 
70 The HayWired Earthquake Scenario—Engineering Implications

restrictions, such as including the exempt buildings. If every 

city were to extend the restrictions of the 1972 Alquist-Priolo 

Fault Zoning Act to all buildings, and all buildings in the San 

Francisco Bay area were compliant, then there would be no 

buildings damaged by fault rupture.

More recently, ASCE/SEI 7-10 section 11.8 requires a 

geotechnical investigation and report for most new ordinary 

California buildings. The report includes an evaluation of the 

potential for slope instability, liquefaction, total and differential settlement, and surface displacement owing to faulting or 

seismically induced lateral spreading or flow. The report must 

contain recommendations for foundation designs or other measures to mitigate the effects of these hazards. Although section 

11.8 does not preclude damage as a result of ground failure, 

it does tend to prevent it. One can conclude that earthquake 

damage owing to ground failure in code-compliant buildings 

will be minor, probably overshadowed by uncertainty in damage resulting from shaking.

The 2015 NEHRP Provisions Update Committee Chair 

points out that “Our seismic codes don’t do much to address 

liquefaction damage. . . We are doing more in the current 

cycle.” (D. Bonneville, written commun., March 2015). 

Because this chapter addresses the hypothetical situation 

where all buildings are replaced with new ones, I also imagine that liquefaction damage is largely prevented by current 

developments.

Public Expectations for the Seismic 

Performance of New Buildings 

It appears likely that the public is unaware that a codecompliant building stock could perform as described in table 

5, largely because the public has no involvement in the codewriting process. I now review that process.

Seismic design provisions have been present in model 

U.S. building codes since 1927 and have almost continuously 

evolved with new editions of the building codes. (Again, 

recommended provisions, standards, and model building codes 

Figure 11. Map of the San Francisco 

Bay region, California, showing estimated 

building impairment for the momentmagnitude-7.0 mainshock of the HayWired 

earthquake scenario if buildings were 

designed with a seismic importance factor 

(I

e

) of 1.5. Estimated building impairment 

includes collapsed, red-tagged, and 

yellow-tagged buildings. (Map created 

using OpenSHA Generic Mapping Tools 

Map Plotter; Field and others, 2003.)

39°

123° 122° 121°

38°

37°

0.0 0.2 0.4 0.6 0.8 1.0

Fraction of impaired buildings

0 20 40 60

20 40 60

MILES

0 KILOMETERS

PA C I F I C O C E A N

San Francisco Oakland

San Jose

Area

of map

CALIF
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 71

are collectively and loosely referred to here as codes.) Code 

writers are required by engineering codes of ethics—such 

as that of the ASCE (2006)—to “hold paramount the health, 

safety and welfare of the public,” and there is little doubt that 

that mandate constantly informs the code-writing process. 

However, code writers have expended little effort to elicit 

from the public its preferences for the seismic performance of 

new buildings or its preferred tradeoffs of safety and construction cost. Discussions of acceptable seismic performance 

have been largely carried out within the structural engineering community. A philosopher of engineering ethics, Davis 

(2015), has recently concluded that the ASCE Code of Ethics 

implicitly requires that those discussions include a reasonable effort to involve members of the public and that civil 

engineers among the code writers are obligated to consider the 

public’s expressed preferences in the code. Several engineering ethicists strongly agree with Davis’ (2015) findings (see 

Porter, 2016b).

As previously mentioned, U.S. building codes aim to 

protect life safety and limit property damage. The explicit 

intent of the 2009 IBC, for example, is to “establish minimum requirements to safeguard the public health, safety, and 

general welfare . . .” and includes “safety to life and property” 

among its goals (ICC, 2009). The NEHRP Provisions (Building Seismic Safety Council [BSSC], 2009) aim “to avoid 

structural collapse in very rare, extreme ground shaking” and 

“to provide reasonable control of damage to structural and 

nonstructural systems that could lead to injury and economic 

or functionality losses for more moderate and frequent ground 

shaking.” Note the inclusion of protecting the general welfare 

and avoiding property loss along with protecting life safety, 

suggesting that the authors did not feel legally constrained to 

only protect life safety. The NEHRP Provisions could, if its 

authors choose, change the requirements to control economic 

loss as well as to protect life.

For earthquake loads in particular, authors of modern 

codes have assumed it is impractical or uneconomical to 

achieve seismic resistance much greater than what is implicit 

in prior codes. (Here, seismic resistance refers generally to the 

capacity of buildings to resist damage or loss of functionality in earthquakes.) This implies that the authors believe the 

public would be unwilling to pay for safer buildings, such as 

those that would remain functional after very strong shaking. 

ASCE 7 (ASCE, 2010) and, by adoption, the IBC (ICC, 2012) 

measure seismic acceptability on a per-building basis, which 

implies that per-building or per-person risk is the best (or at 

least the most practical) measure of risk.

To say that it is uneconomical to provide greater seismic 

resistance is roughly equivalent to saying that people would 

be unwilling to pay for it (“economical” being a subjective 

judgment, not necessarily measured in terms of, say, benefitcost ratio). Is that true? In some sources (ASCE, 2010; ICC, 

2012) and in others that underlie current code requirements for 

new buildings, there is no examination of the public’s willingness to pay. Building owners and tenants have generally 

not been asked to express their preferences and are typically 

absent from the committees that establish codes. The authors 

of National Bureau of Standards Special Publication 577 

(Ellingwood and others, 1980) expressed the idea that the A58 

standards committee (precursor to ASCE 7) represented “those 

substantially concerned with its [the standard’s] scope and 

provisions.” Although committee members included “a broadspectrum group of professionals from the research community, 

building code groups, industry, professional organizations and 

trade associations,” it did not include representatives of building owners or tenants.

The authors of a FEMA-sponsored workshop on communicating earthquake risk interviewed a small group of primarily commercial real-estate professionals about their preferred 

measures of seismic performance (ATC, 2002). The authors 

expressed the belief that “this workshop represents one of the 

first significant attempts to obtain input on issues of acceptable 

levels of seismic risk used as a basis for design, from other 

than the technical community . . . ,” although they acknowledged that “several important stakeholder groups, notably 

residential and institutional building owners, and retailers were not represented at all.” Only very recently did the 

National Institute of Building Sciences (NIBS, 2012)—NIBS 

is the parent body that led the development of BSSC (2009), a 

foundational document for the IBC—carry out its first survey 

to “get a baseline read about what Americans know or don’t 

know about building codes.” The survey was at a fairly high 

level and did not inquire about the public’s understanding and 

preferences for the seismic performance of new buildings. 

The point is that the public is generally not consulted about 

their preferences for the seismic performance of the buildings 

on which their lives and livelihoods rely. It would be easier, 

perhaps necessary, for engineers to support judgments about 

what is economical if the public were asked what they would 

be willing to pay for greater seismic resistance.

It is necessary to define “the public” for purposes of this 

discussion. Here, I adopt the definition described by Davis and 

Porter (2016), “the public should be understood as including all those anywhere whose lack of information, technical 

knowledge, ability, or conditions for adequate deliberation 

renders them more or less vulnerable to the power that engineers wield on behalf of client or employer. The public is a 

collection or aggregate rather than an organized body. Unlike 

an electorate or corporation, it has interests but no decision 

procedure—no will of its own. The public is an abstraction 

Table 6. Shaking-related building impairment for the momentmagnitude-7.0 mainshock of the HayWired earthquake scenario. 

[Ie, seismic importance factor; numbers are rounded to the nearest 1,000 for 

simplicity]

Building condition Buildings with I

e

=1.0 Buildings with I

e

=1.5

Collapse 8,000 2,000

Red-tagged 101,000 27,000

Yellow-tagged 386,000 101,000

Total 495,000 130,000
72 The HayWired Earthquake Scenario—Engineering Implications

(much like a set in mathematics). In the present context, however, the public does not include engineers, building officials, 

or members of the building industry, because these groups 

largely control the code.” 

Davis (2015) recently showed that the ASCE Code of 

Ethics requires that (1) the public has a role in establishing 

preferred tradeoffs among health, safety, and welfare; (2) 

engineers have an ethical obligation to ask about those preferences (within limits of reasonable effort); (3) engineers have 

an ethical obligation to respond to that information; and (4) 

the public, as used here, does not include builders, developers, 

or structural engineers.

To study public expectations as part of the HayWired scenario, I surveyed the public to ask a series of questions (Porter, 

Not Safe Enough, this volume):

•	 What do you believe to be the performance objectives 

most new buildings are intended to meet in a large 

earthquake?

•	 What do you think the building code should provide?

•	 What do you believe are the building performance 

measures of greatest interest to your community?

•	 What do you consider to be a reasonable tradeoff 

between safer buildings and higher initial construction cost?

•	 How important do you believe the issue is? 

•	 What would be the best way to explore the issue further with local government or community?

The survey seeks information about the public’s and local 

officials’ understanding of and preferences for the seismic 

performance of new buildings that comply with the most modern building codes. In Porter (Not Safe Enough, this volume), 

I carried out a population-based survey of 400 members of 

the public within each of two regions: statewide throughout 

California and the two largest metropolitan statistical areas 

closest to the New Madrid Seismic Zone, namely Saint Louis, 

Missouri, and Memphis, Tennessee. The survey shows that the 

majority of respondents prefer better performance from new 

buildings than the results presented here for code-compliant 

buildings. Most prefer that buildings should be habitable 

or functional after a large earthquake. Survey respondents 

believe the public would be willing to pay 1 to 3 percent 

more in construction costs to achieve a higher level of seismic 

performance.

Limitations of this Study

There are many uncertainties in studies such as this and 

it may be that some parameters used here are unintentionally 

overly conservative. Perhaps the estimated 6-percent collapse rate at MCER shaking drawn from the FEMA and NIST 

analyses (ATC, 2009, and NEHRP Consultants Joint Venture, 

2012) is unrepresentative of real buildings and the true average collapse rate at MCER shaking among new, engineered 

buildings will be much lower. For example, those studies only 

considered hypothetical frame buildings and, on the recommendation of the lead author of the two studies, the 6-percent 

figure reflects a subset of those hypothetical buildings—those 

with period greater than 0.5 seconds. Guidelines developed for 

the Global Earthquake Model present procedures for selecting samples of the general building stock so that the sample 

is representative of the building stock as a whole (Porter and 

others, 2014). A study similar to ATC (2009) and NEHRP 

Consultants Joint Venture (2012), but using a representative 

sample following the Global Earthquake Model procedures, 

could test the validity of the 6-percent figure for the general 

building population. 

Perhaps the logarithmic standard deviation of 0.8 used 

by Luco and others (2007) to calculate MCER is too high. The 

figure could be tested using the representative sample method 

described above (although long-term collapse rates and numbers of collapsed buildings in a single earthquake should be 

fairly insensitive to the exact value of the logarithmic standard 

deviation, as explained above). Perhaps the 63:1 ratio of redand yellow-tagged to collapsed buildings in the Loma Prieta 

and Northridge earthquakes and the 57:1 ratio in the Napa 

earthquake overestimate what would happen in future California earthquakes among code-compliant buildings. Procedures 

presented in ATC (2012) could be used to better estimate the 

ratio of red tags to collapses. ATC-20 tagging data from the 

2014 Napa earthquake, 1994 Northridge earthquake, and 1989 

Loma Prieta earthquakes could be analyzed further to develop 

analytical models for yellow tagging.

Future studies could test the possibility that one or more 

of the parameters derived here do not represent reality and 

result in impairment estimates that are much greater than 

would happen in a real earthquake. However, until better 

estimates are available, the estimates presented here provide 

insight into the unintended consequences of current building 

code performance objectives on large-scale building impairment during a large, but not exceedingly rare, earthquake.

Summary

The IBC attempts to ensure the safety of life in new, 

engineered buildings that are subject to earthquake shaking. 

Current building-code goals include no more than a 1-percent 

collapse probability in 50 years and no more than 10-percent 

collapse probability during MCER shaking. However, the code 

does not control lesser degrees of impairment, such as red 

and yellow tagging, nor does it control the overall number 

of impaired buildings in a large, but not exceedingly rare, 

earthquake, such as the mainshock modeled in the HayWired 

scenario. 

This study shows that in three California earthquakes, 

approximately 60 times as many buildings have been red- or 

yellow-tagged as have collapsed. In one earthquake, three 
Chapter K. Societal Consequences of Current Building Code Performance Objectives for Earthquakes 73

times as many again experienced at least moderate damage—evidenced by insurance claims averaging $30,000 to 

$40,000—without collapsing or being red- or yellow-tagged. 

This chapter also shows that FEMA and NIST research supporting the upper-bound goal of no more than 10-percent collapse probability results in an average 6-percent collapse probability during MCER shaking. This work proposes a collapse 

fragility function for new, engineered buildings whose input 

parameter is the ratio of shaking at the building site to the siteclass-adjusted MCER; the ratio is referred to as the demandto-design ratio (DDR). The impairment fragility function 

takes the form of a lognormal cumulative distribution function 

multiplied by the ratio of total impaired buildings to collapsed 

buildings (63) with an upper bound of 1.0. The logarithmic 

standard deviation of the fragility function can be applied from 

the work of Luco and others (2007) that proposed establishing 

MCER. The median of the collapse fragility function follows 

directly from the observation that 6 percent of new, engineered 

buildings are expected to collapse in MCER shaking, with a 

logarithmic standard deviation. 

Using the map of ground motion in the HayWired scenario mainshock (fig. 5) and ASCE/SEI 7-10’s map of MCER

shaking, adjusted to account for site amplification, this study 

calculates shaking in the HayWired scenario mainshock in 

terms of DDR. The DDR is evaluated for each location in 

FEMA’s 2010 enhanced building inventory for California to 

estimate the number of buildings exposed to ground shaking in the HayWired mainshock for various levels of DDR. 

Using the impairment fragility function derived here, one can 

estimate the number of buildings impaired in the HayWired 

scenario, assuming that all of the buildings behaved as if they 

were new, code-compliant buildings. The result is an estimate 

that approximately 500,000 buildings would collapse, be redtagged, or be yellow-tagged. As many as 1.5 million people 

could be displaced from those buildings for months or more 

while the buildings are repaired or replaced. There are too few 

vacant buildings in the San Francisco Bay area to accommodate this many displaced people, suggesting that many would 

be forced to leave the San Francisco Bay area for at least 

several months, and possibly permanently. 

One possible option for states or cities to reduce future 

building impairment is to adopt the IBC with the modification 

that all risk category I, II, or III buildings must be designed 

with a seismic importance factor (Ie) greater than 1.0. In the 

hypothetical case that all San Francisco Bay area cities require 

design to Ie=1.5, the total number of impaired buildings in the 

HayWired mainshock would be reduced by approximately 75 

percent, to 130,000 impaired buildings. The estimated 500,000 

impaired buildings under current code objectives fails the 

95-percent shelter-in-place performance objective of a San 

Francisco Bay area urban planning organization, SPUR, but 

the reduced impairment with Ie=1.5 (130,000 buildings) meets 

SPUR’s objective. The estimates presented here—500,000 

impaired buildings under current code and 130,000 impaired 

buildings under the what-if scenario—follow solely from current code objectives, the research that established MCER, the 

evidence of collapse, red tags, and yellow tags in California’s 

recent earthquake history, and FEMA’s 2010 enhanced building inventory. 

The construction cost to build new buildings with Ie=1.5 

has been approximately estimated here to be 1–3 percent 

greater than under the current code, or about a 1 percent 

greater purchase price considering land value. Such a marginal cost seems entirely practical. Seismic design procedures 

in ASCE/SEI 7-10 already require buildings on one side of 

San Francisco to be designed with 50 percent greater strength 

than buildings on the other side. As another example, the City 

of Moore, Oklahoma, now requires buildings to be designed 

with 125 percent greater strength than before the devastating 

2013 Moore tornado occurred. 

A survey to elicit the public’s understanding, expectations, and preferences for the code’s seismic performance 

objectives was undertaken as part of the HayWired earthquake 

scenario (Porter, Not Safe Enough, this volume). It shows 

that the majority of the public prefers better performance—

that buildings should be habitable or functional after a large 

earthquake. Survey respondents believe the public would be 

willing to pay 1 to 3 percent more in construction costs to 

achieve a higher level of seismic performance. Some argue 

that civil engineers have an ethical obligation to elicit the 

public’s preferences in drafting seismic design requirements 

(Davis, 2015), suggesting that surveys such as those undertaken as a part of the HayWired scenario may help inform 

the next generation of building-code objectives in seismically 

active areas.

Conclusion

Current code objectives seem to unintentionally produce a high degree of building impairment in a large, but not 

exceedingly rare, earthquake, such as the Mw 7.0 mainshock 

of the HayWired scenario. The impairment, in terms of 

collapsed, red-tagged, or yellow-tagged buildings, would displace a large number of residents from the San Francisco Bay 

region. The building-code objectives appear, based on a large 

survey of Californians and people living in the Saint Louis, 

Missouri, and Memphis, Tennessee, metropolitan statistical 

areas, to be substantially below what the public may prefer 

and may be willing to pay for.

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Abstract

Earlier disaster planning scenarios developed by the 

U.S. Geological Survey (USGS), especially the ShakeOut 

earthquake scenario, suggest the public is unaware of the lifesafety performance objective in U.S. seismic-design standards 

and may want better building performance. As part of the USGS 

HayWired earthquake scenario, I (through the University of 

Colorado Boulder) undertook an effort to explore this hypothesis 

by performing a public survey in California and near the New 

Madrid Seismic Zone in the Central United States. The HayWired 

scenario examines a hypothetical earthquake with a moment 

magnitude (Mw) of 7.0 occurring on April 18, 2018, at 4:18 p.m. 

on the Hayward Fault in the east bay part of the San Francisco Bay 

area. The survey was designed to determine (1) whether the public 

understands the current life-safety objective of the building code’s 

seismic-design requirements, (2) what the public prefers in terms 

of the performance of the building stock in a large earthquake, (3) 

whether the public would be willing to pay the costs for stronger 

buildings, and (4) how important the public finds the issue of the 

seismic performance of buildings. The survey found that, without 

major regional differences, respondents: 

1. Are largely unaware of the life-safety seismic 

performance objective of American Society of 

Civil Engineers ASCE/SEI 7 and the International 

Building Code;

2. Are more interested in controlling total number of 

deaths and injuries in a large earthquake than in 

controlling per-building collapse probability;

3. Are also interested in more than the total number of 

casualties, specifically that buildings should remain 

functional or habitable after a large earthquake (the 

“Big One” in the language of the survey), and prefer 

better performance than the code is intended to 

deliver for new buildings;

Chapter L

Not Safe Enough—A Survey of Public Preferences for the 

Seismic Performance of New Buildings in California and 

the New Madrid Seismic Zone

By Keith A. Porter1

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013]

1

University of Colorado Boulder.

4. Expect better seismic performance than ASCE/SEI 7 

intends to provide;

5. By a large majority, are willing to pay for greater 

seismic safety, with the modal response (the most 

common response) being $3.00 per square foot 

additional construction cost to achieve such a higher 

level of performance;

6. Believe the degree of seismic performance 

of buildings is important or very important—

the response of approximately 80 percent of 

respondents—even in the Central United States 

where earthquakes happen much less frequently than 

in California; and

7. Tend to be somewhat more commonly of European 

descent, wealthier, and more educated than the 

general public, but regression analyses found no 

strong trends in either region relating education to 

acceptable cost for better performance or relating 

household income to acceptable cost for better 

performance;

Key implications of the survey indicate that:

1. There is a potential need for writers of seismicdesign criteria in ASCE/SEI 7 to revisit the seismicperformance objectives for new buildings, considering 

the public’s apparent preferences for better 

performance;

2. There is a need for better communication with the 

public about the building code’s performance objectives 

for new buildings;

3. Practical options for stronger buildings are needed 

that an elected official can select in case they, like 

respondents here, want more from new buildings than 

the life-safety performance objective delivers;
80 The HayWired Earthquake Scenario—Engineering Implications

4. More narrowly, the study has some implications for 

the HayWired scenario. First, the HayWired study of 

the potential outcomes of designing stronger buildings 

addresses a real, measured public preference among 

Californians;

5. Elected officials in the San Francisco Bay area might 

be interested in hearing about public preferences for the 

seismic performance of new buildings; and

6. Those same elected officials might be interested in 

hearing about the costs and benefits of higher design 

requirements, in light of this study and the damage 

estimated by the HayWired scenario in general.

Introduction

This work deals with public preferences for the seismic 

performance of new buildings. Before addressing what the 

public might want, I first briefly discuss what the building 

code presently provides. ASCE/SEI 7–10 (American Society 

of Civil Engineers, 2010) recommends minimum design 

loads for buildings and other structures, including seismicdesign requirements. The 2012 International Building Code 

(IBC; International Code Council, 2012) adopts ASCE/SEI 

7–10 by reference, and the majority of communities adopt 

the IBC, sometimes with minor modifications. Thus, ASCE/

SEI 7 tends to control how buildings perform in earthquakes. 

Oversimplifying somewhat, ASCE/SEI 7 helps to ensure new 

buildings are designed so less than 1 percent will collapse in 

earthquakes during the first 50 years of their existence, called 

their design life. As discussed in Porter (2016), studies by 

the Federal Emergency Management Agency (FEMA) and 

National Institute of Standards (NIST) imply that “fewer 

than 1 percent” means, on an expected-value basis, about 0.6 

percent of buildings will collapse during their design life. 

ASCE/SEI 7 provides various other requirements to control 

repair costs, but essentially the 0.6-percent goal ensures a 

reasonable degree of life safety and is commonly referred to as 

the building code life-safety performance objective.

In Porter (Societal Consequences, this volume), I showed 

that the current building code’s life-safety seismic performance 

objective has a serious unintended consequence—that a magnitude 

7.0 earthquake on the Hayward Fault with an Oakland epicenter 

can impair hundreds of thousands of buildings, potentially 

displacing a million people or more. This earthquake is the 

mainshock of the U.S. Geological Survey’s (USGS) HayWired 

scenario, which examines a hypothetical earthquake with a 

moment magnitude (Mw ) of 7.0 occurring on April 18, 2018, at 

4:18 p.m. on the Hayward Fault in the east bay part of the San 

Francisco Bay area. 

In the opinion of a USGS scientist who deals regularly 

with local governments, and based largely on her experience 

during the development of the ShakeOut earthquake scenario 

(Jones and others, 2008), city councils and mayors “absolutely 

do not know” how a code-compliant building stock designed to 

meet the life-safety objective will perform in a large earthquake, 

and are unsatisfied when they do learn of it (Lucile Jones, 

USGS, oral commun., November 19, 2013). The seismic-design 

requirements adopted by the building code are written with little 

input from the public.

The 1927 Uniform Building Code (International 

Conference of Building Officials, 1927) provided the earliest 

seismic-design provisions in a model building code and 

was based on the experience and judgment of 60 building 

officials. In the subsequent 90 years, professional engineers 

and structural engineers (for the most part) have driven the 

development of seismic-design provisions. Developers of 

load- and resistance-factor design once called for a professionwide debate among structural engineers on the proper seismic 

reliability of new buildings (Ellingwood and others, 1980), but 

there is no record that such a debate ever took place, let alone 

a discussion with the public. 

Of course, state legislatures and city councils adopt or 

adapt model buildings codes such as the IBC on behalf of 

their community. By adopting these codes, there is a measure 

of consent by community officials. Suppose State and local 

officials’ ignorance of the life-safety objective only points to a 

failure to communicate on the part of engineers, code officials, 

or other building professionals. Better communication could 

conceivably address that problem. Imagine then an effort by 

structural engineers and others to explain what the building code 

does and does not provide. If such an effort were undertaken, 

then when a city or State adopts a model building code, one 

could say that well-informed city and State governments that 

adopt the IBC would be giving informed consent on behalf of 

the public to the risk imposed by the code? 

Davis (1991), a philosopher of engineering ethics, 

argues that if one cannot practically formulate and choose 

an alternative to a risk, one cannot give informed consent. 

Whether or not policymakers understand the code’s life-safety 

objectives, most cities and many States lack the resources to 

formulate an alternative to a model code and, therefore, cannot 

give informed consent. Those cities and States that cannot 

formulate and choose an alternative—the elected leaders and 

their constituents—represent “the public” in the sense meant 

by the American Society of Civil Engineers’ (2006) Canon 1 

of its Code of Ethics, which holds that “Engineers shall hold 

paramount the safety, health and welfare of the public . . .” 

Being a member of the public in that sense has consequences—

Davis (2015) has recently shown that the American Society of 

Civil Engineers’ Code of Ethics implicitly requires engineers 

to consult the public’s preferences when writing building 

standards for earthquakes. He excludes from “the public” the 

people who write the building code, such as engineers, building 

officials, and people who work in the building trades. In this 

work, I detail what may be the first effort to elicit the public’s 

preferences for the seismic performance of new buildings 

through a large, rigorous population survey. I conducted the 

survey (through the University of Colorado Boulder) as part 

of the HayWired scenario. See Davis and Porter (2016) for 
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 81

a summary of the survey, along with a discussion of who 

comprises the public in the present context and the ethics of 

consulting the public when establishing performance objectives 

for model building codes. 

Objectives

This report addresses the question, what does the public 

expect and prefer from new code-compliant buildings in a big 

earthquake? Would the public be willing to pay to achieve their 

desired performance objective? It addresses these questions 

through population surveys in two high-hazard earthquakeprone regions. “High hazard” here means at least seismic-design 

category D as defined by ASCE/SEI 7-10 (American Society 

of Civil Engineers, 2010; fig. 1). The study employs a randomsample survey of adults 18 years or older living in two highseismic-hazard geographic regions.

There are many ways to perform a survey; this study uses 

a web-based survey for efficiency. Web-based surveys have 

advantages and pitfalls, as discussed by Dillman and others 

(1998). Potential pitfalls include coverage error (the chance 

that some groups have no chance of selection), sampling error 

(differences between responses of a sample and those of the 

entire population), measurement error (resulting from poorly 

worded questions), and nonresponse error (the difference 

between responses received and ones that would have been 

received from people who declined to respond). Dillman and 

others (1998) offer a number of recommendations to overcome 

these pitfalls, as discussed later.

The survey covers two geographic areas to probe for regional 

differences in public preferences. Those regional differences might 

reflect different degrees of recent experience with earthquakes, 

different wealth, or other regional issues.

The two selected geographic regions for the web-based 

survey discussed in this report are California, virtually all of which 

is in seismic-design category D or above, and a part of the New 

Madrid Seismic Zone in the Central United States. In particular, 

respondents to represent people in the New Madrid Seismic Zone 

were recruited from residents of the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan statistical areas (MSAs), both 

of which qualify as high-seismic-hazard areas as defined here.

An earlier preliminary survey of 66 Californians 

suggested the public was largely unaware of the building 

Figure 1. Map of the contiguous United States showing risk-adjusted maximum considered earthquake (MCER) motion 1-second 

spectral response acceleration parameter (SM1) in percent of acceleration due to gravity (g) for seismic-design categories (SDC) A–E. 

Note that most of California and the New Madrid Seismic Zone in the Central United States—the areas examined in the web-based 

survey discussed in this report—are in seismic-design category D. (Map from Building Seismic Safety Council, 2009.)

Seismic-design category

EXPLANATION

0–10

10–20

20–30

30–45

45–60

60–112.5

>112.5

A

B

C

D

E

N
82 The HayWired Earthquake Scenario—Engineering Implications

code’s seismic performance objectives for new, codecompliant buildings; the public generally wanted more than 

life-safety performance from ordinary buildings, and that 

they would be willing to pay $3.00 to $10.00 per square 

foot more for a code-compliant building stock, in which the 

population could shelter in place after a large earthquake. The 

preliminary survey constituted a so-called convenience sample 

because the respondents could be conveniently accessed 

rather than because they represented a random sample. The 

preliminary survey also tested the survey instrument; meaning 

that I personally administered the survey several times and 

respondents were encouraged to ask questions. None of 

the questions they asked suggested the survey was unclear. 

Furthermore, Dr. Liesel Ritchie, a sociologist with expertise 

in surveys, reviewed the questions and expressed the opinion 

that the language was clear. Data from the preliminary survey 

are not included here, to ensure the convenience sample is not 

mixed with the random sample. See Porter and Davis (2015) 

for details of the preliminary survey. 

At least one other survey has attempted to ascertain 

the public’s confidence in the safety of existing buildings 

(International Association of Plumbing and Mechanical 

Officials and others, 2012). Those authors found, “The majority 

of Americans understands that building codes exist to keep 

us safe. However, beyond that basic fact their knowledge and 

appreciation of building codes appears weak. . . . Americans are 

generally confident that the structures where they live and work 

have adequate safeguards given the types of natural hazards in 

their areas.” The Urban Institute’s (1991) study of the public’s 

willingness to pay for life safety informed later decisions 

about acceptable cost to avoid statistical injuries and fatalities, 

such as can be found in Federal Highway Administration 

(1994). The present report may represent the first population 

survey to elicit the public’s understanding of how the code 

measures seismic performance, its quantitative objective (that 

is, numerically, how safe are new buildings), the public’s 

preferences for seismic performance, and its willingness to pay 

for performance in excess of current code requirements. This 

study is intended primarily to address willingness to pay for 

seismic safety of new buildings, a new risk context domain to 

which one can compare findings in other domains. The survey 

can also be compared with other methods to assess willingness 

to pay. 

Because a public university, the University of Colorado 

Boulder, performed the survey it satisfies regulations designed 

to implement ethical principles and preserve the public trust. 

The 1966 U.S. Public Health Service (PHS) policy, “Clinical 

research and investigation involving human beings,” requires 

an institution review board (IRB) to independently review 

research (Office of the Surgeon General, 1966). The 1974 

PHS policy 45 CFR 46 specifies requirements for institutional 

assurances, IRB review, informed consent and ethical conduct. 

In 1991, 17 Federal agencies issued uniform regulations under 

the title “Common Rule.” The survey discussed here was 

approved by the University of Colorado’s IRB in light of these 

requirements.

Survey Approach

The survey was administered using an online survey 

company, SurveyMonkey.com, because of the ease, speed, and low 

cost of web surveys compared with alternatives such as randomdigit dialing. The survey aimed to elicit at least 400 responses from 

adults 18 years and older throughout the State of California and 

400 adults in the Memphis and St. Louis MSAs. As shown later, 

it had 413 individual responses in California and 401 individual 

responses in Memphis and St Louis. All mentions of those two 

cities refer to the MSA, rather than the incorporated city. Because 

building professions have a significant role in establishing seismicdesign requirements, they do not qualify as “the public” in the 

present context, and so are excluded for the survey. The excluded 

professions include construction, structural design, architecture, 

building trades, building officials, and building inspectors.

The sample size of 400 was chosen for each region because, 

for a population in excess of 10,000,000 people, a sample size 

of 400 provides a ±5-percent margin of error with 95-percent 

confidence. That is, responses to survey questions in each region 

are expected to be within 5 percent of what the population as a 

whole would say, with 95-percent confidence. Considering both 

regions together, the margin is approximately ±3.4 percent. (The 

accuracy of the estimates depends on how representative the 

sample is of the population; this question is addressed later.) 

The large sample size helps to overcome the potential for 

coverage error. As shown later, responses were received from all 

major demographic groups (considering gender, income, education, 

age, race, and ethnicity). Sampling error is inevitable when one 

cannot survey the entire population, but the large sample size limits 

the potential error. Measurement error was minimized through the 

preliminary survey, as previously discussed. Nonresponse error was 

addressed by keeping the survey brief. As will be shown later, the 

high response rate limits nonresponse error.

The survey was administered by a survey company 

according to a human-subjects research protocol approved by 

the University of Colorado Boulder’s IRB on July 2, 2015. 

Survey responses were collected in July 2015. 

The survey asked the following general questions:

1. Do any of the following apply to you? (Asking if 

respondent belongs to any of the excluded building professions that have a relation to existing building codes)

2. Respondent’s role or relation to building codes? (If 

disqualified from further answering the survey by 

answering yes to question 1)

3. Performance objectives that most new buildings are 

intended to meet in a large earthquake?

4. What should the building code provide?

5. Preferred measure of seismic performance?

6. Acceptable cost to increase seismic performance?

7. How important are the issues raised by the survey?
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 83

8. Age?

9. Gender?

10. Race or ethnicity?

11. Education?

12. Household income?

Individual survey responses were aggregated in the form 

of pie diagrams. Respondents took on average 6 minutes to 

complete the survey. 

Respondent Population and Sampling Procedure

The survey aimed to sample at least 400 adults in 

California and 400 adults in the combination of the Memphis 

and St. Louis metropolitan statistical areas, excluding adults 

involved in a buildings profession. SurveyMonkey.com offers 

this explanation of its sampling procedure: 

We take great care to ensure that we have a diverse 

group of members who are interested in sharing their 

opinions with you.

When a panelist joins our community of 

respondents and becomes a SurveyMonkey 

Contribute member, they fill out a profile. This 

profile contains demographic questions (gender, 

age, region, etc.) as well as some other targeting 

characteristics you might care about (cell phone 

usage, job type, and more). 

Incentive Structure

Each time a SurveyMonkey Contribute member 

completes an eligible survey, SurveyMonkey makes 

a contribution to a charity of the member’s choice, 

and the member can choose to enter a sweepstakes.

Recruitment

We recruit Contribute members from a diverse 

population of 45+ million people who take 

SurveyMonkey surveys every month. For example, 

after completing a survey, respondents are redirected 

to a page that may feature an advertisement for 

SurveyMonkey Contribute.

SurveyMonkey Contribute panelists come from the 

United States, the United Kingdom, and Australia. 

You choose the country you’d like your respondents 

to come from. If you need respondents from other 

countries, please contact us.

Although we recruit panelists ages 13 and up, we 

have the ability to target respondents by age and can 

target 18 and older.

Sampling Procedure

We email invitations to respondents who match your 

targeting criteria. Our system selects a random group 

from the SurveyMonkey Contribute member base who 

match the demographic targeting criteria you requested. 

We use a standard template email notification to 

notify respondents that they have a new survey to 

take. It’s not possible to customize the invitation 

email sent by SurveyMonkey Contribute.

Targeting Criteria

We target members based on the information they 

provide to us in their profile.

The more variables or criteria you target, the more 

it constricts the population we can use to build your 

sample. A more constricted sample may slow down the 

pace at which your survey can complete—or even make 

it impossible for us to run your survey at all.

Balancing

If you send your survey to a general audience, your 

results are generally representative of the population 

you’re surveying. We automatically balance results 

according to census data for age and gender, 

whereas location tends to balance out naturally. 

Balancing precision and granularity improves as the 

number of responses increases.

When you choose specific targeting criteria, your 

results are no longer representative of the general 

population because you’re purposefully focusing on 

a particular subset of the population.

(SurveyMonkey, 2015) 

Survey Questions and Responses

The survey asked 12 questions to determine the public’s 

preferences for the seismic performance of new buildings. 

The initial survey question asks whether the respondent 

is employed in the building industry. Employment in that 

industry disqualifies the respondent from answering further 

questions. Incomplete responses are all the people who were 

invited to take the survey but who declined to begin it (N. 

Teckman, written commun., July 14, 2015). 

Response Rate

The survey was sent to a total of 1,506 potential participants. 

The response rate was quite high—60 percent of those eligible 

in California and 56 percent of those eligible in St. Louis and 
84 The HayWired Earthquake Scenario—Engineering Implications

Memphis. Here, response rate refers to the ratio of “completed” to 

the sum of “completed” and “incomplete” responses for example, 

413/(413 + 278)=60 percent. The pie diagrams in figure 2 show the 

number of people disqualified, number of completed responses, and 

number of incomplete responses to the following question:

1. Do any of the following apply to you? (Check all that apply.)

• Employed in the construction industry?

• Employed in the structural design industry?

• Employed in the architecture industry?

• Employed in the building-trades industry?

• Employed as a building official or building inspector?

• None of these apply?

Role or Relation to Building Codes

Figure 3 shows the number and percentage of responses 

from people disqualified to the following question:

2. What is your role or relation to building codes? 

 Please mark all your roles that apply?

• Local elected official?

• Local government staff who advise local officials on 

building codes?

• Building owner?

• Building tenant (renter)?

• Other (please specify)?

(Detailed information about respondent demographics is 

discussed below in Respondent Demographics.)

Figure 4 shows the relation of respondents to building 

codes. (Responses to this and all subsequent questions reflect 

only completed responses, for example, from respondents who 

were qualified for and completed the survey.) 

Current and Preferred Code Objectives

Figure 5 shows the percentage of responses to the 

following question:

3. Although local codes vary, which of these performance 

 objectives do you think most new buildings are intended 

 to meet in a large earthquake? That is, what do you think the 

 current code actually says, not what should it say. Please 

 mark only one answer.

• New buildings will generally be functional after an 

earthquake, and will require minimal repairs.

Figure 2. Pie diagrams for survey of the public’s preferences for the 

seismic performance of new buildings showing response rate in (A) 

California and (B) in the St. Louis, Missouri, and Memphis, Tennessee, 

metropolitan statistical areas. Completed, those completing the 

survey; Incomplete, those who were invited to take the survey but who 

declined to begin it; disqualified, those disqualified from the survey. 

Number and percentage (%) of respondents are shown. 

Incomplete

Disqualified

Completed

413 

 (55%) 

 278 

(37%)

62

(8%)

43

(6%)

Incomplete

Disqualified

Completed

309

(41%)

401

(53%)

A

B

• New buildings will generally be occupiable after an 

earthquake. Although they might require some repairs 

to be fully functional, the occupants will be able to 

remain in the building during the repairs.

• New buildings are safe enough that occupants won’t be 

killed, but are not generally intended to be occupiable 

after the earthquake. That is, a person will be able to exit a 

building safely, but not necessarily be able to go back in.

• I don’t know.
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 85

Figure 3. Pie diagrams for 

survey of the public’s preferences 

for the seismic performance of 

new buildings showing relation 

to building codes for people 

disqualified from participating in 

the survey in (A) California and 

(B) in the St. Louis, Missouri, 

and Memphis, Tennessee, 

metropolitan statistical areas. 

Number and percentage (%) of 

respondents are shown.

Figure 4. Pie diagrams for survey 

of the public’s preferences for 

the seismic performance of new 

buildings showing relation to 

building codes in (A) California 

and (B) in the St. Louis, Missouri, 

and Memphis, Tennessee, 

metropolitan statistical areas. 

Percentage (%) of respondents is 

shown.

B Architecture uilding

trades

Building official

or building 

inspector 

Structural 

design 

Structural 

design 

A B

 4

 (13%)

Building official

or building 

inspector 

 4

(18%)

 4

(18%)

6

(19%)

6

(19%)

Architecture

7

(32%)

15

(49%)

Building

trades

7

(32%)

Elected 

official 

0.25% 0.25%

Elected official 

2.5%

Staff Staff

2.5%

Owner

35.9%

Tenant

22.5%

Other

41.1%

A B

Owner

27.3%

Tenant

39.0%

Other

28.6% 

Figure 5. Pie diagrams for survey 

of the public’s preferences for 

the seismic performance of new 

buildings showing responses to 

“Which of these performance 

objectives do you think most 

new buildings are intended to 

meet in a large earthquake?” in 

(A) California and (B) in the St. 

Louis, Missouri, and Memphis, 

Tennessee, metropolitan 

statistical areas. Percentage (%) 

of respondents is shown.

Functional

18%

Functional

9%

Occupiable

22%

Occupiable

22%

A B

Do not know

43%

Do not know

31%

Life safe

23%

Life safe

26%

Other

3%

Other

3%
86 The HayWired Earthquake Scenario—Engineering Implications

Figure 6 shows the percentage of responses to the 

following question:

4. What should the building code provide? That is, if someone 

 builds a new building in your community and it meets building-

 code requirements for seismic safety, which one of these would

 you most prefer the code to ensure? In some of the responses 

 below I use the term “the Big One,” by which I mean an

 earthquake that might be considered a once-in-a-lifetime event. 

 Please mark only one answer.

• New buildings should generally be functional after the 

Big One, possibly requiring minimal repairs.

• New buildings should generally be occupiable after the 

Big One. Although they might require some repairs to be 

fully functional, the occupants should be able to remain in 

the building during the repairs.

• New buildings should be safe enough that occupants won’t 

be killed, but need not be occupiable after the Big One. 

That is, a person should be able to exit a building safely, 

but not necessarily be able to go back in.

• I don’t know.

Preferred Performance Measure 

Figure 7 shows the percentage of responses to the following question:

5. Which of these building performance measures do you

 think is of greatest interest to your community? That is,

 if the building code controlled only one of these measures, 

 which one should it control? Again, “the Big One” here 

 means an earthquake that might be considered a once-in-a-

 lifetime event. Please mark only one answer.

• The chance that any given building will collapse in 

the Big One. (“Per-building collapse probability” in 

fig. 7.)

Figure 6. Pie diagrams for survey 

of the public’s preferences for 

the seismic performance of new 

buildings showing responses to 

“If someone builds a new building 

in your community and it meets 

building-code requirements for 

seismic safety, which one of these 

would you most prefer the code to 

ensure?” for people in (A) California 

and (B) in the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas. Percentage (%) of 

respondents is shown.

Figure 7. Pie diagrams for survey 

of the public’s preferences for 

the seismic performance of new 

buildings showing responses 

to “Which of these building 

performance measures do you 

think is of greatest interest to your 

community?” in (A) California and 

(B) in the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas. Percentage (%) of 

respondents is shown.

AAXXXX_fig 01

Functional

19%

Occupiable

42%

A

Do not know

16%

Life safe

21%

Other

2%

Functional

16%

Occupiable

40%

B

Do not know

18%

Life safe

24%

Other

2%

A B

Per-building 

collapse

 probability

Per-building

 collapse 

probability

23%

38%

Number of 

 collapses

Number of 

 collapses

12% 10%

Community 

 casualties

Community 

 casualties

48%

14%

Repair 

 cost

9%

Unoccupiable 

 buildings

11%

Repair 

 cost

10%

Unoccupiable 

 buildings

9%

Other

7%

Other

9%
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 87

• The total number of people killed or injured by 

building damage in your community in the Big One. 

(“Community casualties” in fig. 7.)

• The total number of buildings in your community that 

might collapse in the Big One. (“Number of collapses” 

in fig. 7.)

• The number of buildings that would not be occupiable 

after the Big One. (“Unoccupiable buildings” in fig. 7.)

• The total cost to repair damaged buildings in your 

community in the Big One. 

• Something else or some combination of these (please 

specify).

Responses to this question beg for some interpretation. 

The responses suggest respondents are more interested 

in controlling total number of deaths and injuries in a 

large earthquake than in controlling per-building collapse 

probability. Note well that the two measures are not the 

same. Although building collapse drives deaths and injuries 

in earthquakes, the per-building probability is blind to the 

number of simultaneous collapses. A large remote earthquake 

can subject a small town to very strong motion and produce 

high collapse probability among that small number of 

buildings. A large earthquake in a metropolitan area can 

subject a large number of buildings to the same level of 

motion and the same collapse probability. ASCE/SEI 7 does 

not distinguish between the two cases, but the public does.

The public cares very much about the total simultaneous 

numbers. In one of the most cited studies on public risk 

perception, Slovic and others (1981) show that the leading 

factor affecting the public’s perception of risk is “associated 

with lack of control, fatal consequences, high catastrophic 

potential, reactions of dread, inequitable distribution of risks and 

benefits (including transfer of risks to future generations), and 

the belief that the risks are increasing and not easily reducible.” 

They refer to factor 1 as dread risk. This phenomenon partially 

explains why Americans tolerate more than 32,000 deaths per 

year as a result of automobile accidents and more than 11,000 

annual firearm homicides (both of which cause at most only a 

few deaths at a time), but found the 2,996 (nearly simultaneous) 

deaths in the September 11, 2001, attacks on the United States 

traumatic enough to launch two wars that ultimately cost more 

than $1 trillion (Daggett, 2010). 

Acceptable Cost for Better Performance

Figure 8 shows the percentage of responses to the 

following question:

6. This question is intended to obtain information about the

 tradeoffs between safer buildings and higher initial construction

 cost (not retrofit cost). Suppose that in the Big One (a once-

 in-a-lifetime earthquake), up to 1 out of every 5 buildings in 

 your community would collapse or require major repairs, 

 taking a year or more to repair before they could be reoccupied. 

 Also suppose that you could change the building code so that it

 would reduce that fraction to 1 in 100 buildings or less, but at 

 the cost of higher initial construction costs. What additional 

 cost do you think building buyers should be willing to pay to 

 achieve that end? Please mark only one answer.

• The current risk is already tolerable. No additional cost 

seems justified.

• Maybe $1 per square foot, which would increase the 

monthly mortgage for the purchase of a new, typical 

California house from about $2,000 per month to about 

$2,010 per month. [In St Louis and Memphis, instead of 

“...California... $2,000... $2,010....” the question says “...St 

Louis... $750... $758....”]

• Maybe $3 per square foot, which would increase the 

monthly mortgage for the purchase of a new, typical 

California house from about $2,000 per month to about 

$2,030 per month. [In St Louis and Memphis, instead of 

“...California... $2,000... $2,030....” the question says “...St 

Louis... $750... $770....”]

Figure 8. Pie diagrams for survey of 

the public’s preferences for the seismic 

performance of new buildings showing 

responses to “What additional cost 

do you think building buyers should 

be willing to pay to achieve that end 

[acceptable tradeoff between safer 

buildings and higher initial construction 

cost?]” for people in (A) California 

and (B) in the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas. Percentage (%) of 

respondents is shown.

A B

14%

$0/ft2 $0/ft2

10%

$1/ft2

21%

$3/ft2

34%

$3/ft2

28%

$10/ft2

23%

Do not know Do not know

16% 19%

$10/ft2

16%

$1/ft2

19%
88 The HayWired Earthquake Scenario—Engineering Implications

• Maybe $10 per square foot, which would increase the 

monthly mortgage for the purchase of a new, typical 

California house from about $2,000 per month to about 

$2,100 per month. [In St Louis and Memphis, instead of 

“...California... $2,000... $2,100....” the question says “...St 

Louis... $750... $824....”]

• I don’t know, or you would have to measure the cost some 

other way (please specify).

How Important are These Issues?

Figure 9 shows the percentage of responses to the following question:

7. How important are these issues? Please mark only one answer.

• Very important

• Important

• Not very important

• Unimportant

Respondent Demographics

Figure 10 shows the percentage of responses to the 

following question:

8. Age?

• <18

• 18–29

• 30–44

• 45–59

• 60+

Figure 11 shows the percentage of responses to the 

following question:

9. Gender?

• Female

• Male

Figure 12 shows the percentage of responses to the 

following question:

10. Which of the following best describes your race or ethnicity?

 (Check all that apply.)

• White/Caucasian

• African American

• Hispanic

• Asian

• Native American

• Pacific Islander

• Other

Figure 13 shows the percentage of responses to the 

following question:

11. What is the highest level of education you have received?

• Less than high school

• High school/GED

• Some college

• 2-year college degree

• 4-year college degree

• Masters degree

• Doctoral degree

• Professional degree (JD, MD)

Figure 14 shows the percentage of responses to the 

following question:

12. How much total combined money did all members of your 

 HOUSEHOLD earn last year?

• $0 to $9,999

• $10,000 to $24,999

• $25,000 to $49,999

• $50,000 to $74,999

• $75,000 to $99,999

• $100,000 to $124,999

• $125,000 to $149,999

• $150,000 to $174,999

• $175,000 to $199,999

• $200,000 and up

• Prefer not to answer
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 89

Figure 9. Pie diagrams for survey 

of the public’s preferences for 

the seismic performance of new 

buildings showing responses to 

“How important are these issues?” 

for people in (A) California and 

(B) in the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas. Percentage (%) of 

respondents is shown.

Figure 10. Pie diagrams for 

survey of the public’s preferences 

for the seismic performance of 

new buildings showing responses 

to “[What is your] Age?” for 

people in (A) California and (B) 

in the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas. Percentage (%) of 

respondents is shown.

Figure 11. Pie diagrams for 

survey of the public’s preferences 

for the seismic performance of 

new buildings showing responses 

to “[What is your] Gender?” for 

people in (A) California and (B) 

in the St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas. Percentage (%) of 

respondents is shown.

AAXXXX_fig 01

A B

Important

45%

Not very 

important

12%

Not very 

important

15%

Very 

important

27%

Very

 important

38%

Unimportant

5%

Unimportant

6%

Important

52%

AAXXXX_fig 01

A B

60+

25%

18–29

25%

30–44

28%

45–59

25%

60+

25%

18–29

25%

30–44

28%

45–59

25%

<18

0%

<18

0%

A B

Male

47%

Female

53%

Male

31%

Female

69%
90 The HayWired Earthquake Scenario—Engineering Implications

Figure 13. Pie diagrams for survey of the public’s preferences for the seismic performance of new 

buildings showing responses to “What is the highest level of education you have received?” for people 

in (A) California and (B) in the St. Louis, Missouri, and Memphis, Tennessee, metropolitan statistical 

areas. Bold numbers show percentage of respondents. HS/GED, high school degree or General Educational 

Development certificate; JD, doctor of jurisprudence; MD, doctor of medicine.

AAXXXX_fig 01

A B

Caucasian

68 86

8

2

3

14

1

1 1

9

2

3

2

Other

Pacific Islander

Native American

Asian

Hispanic

African American

EXPLANATION

Figure 12. Pie diagrams for survey of the public’s preferences for the seismic performance of new 

buildings showing responses to “Which of the following best describes your race or ethnicity?” for 

people in (A) California and (B) in the St. Louis, Missouri, and Memphis, Tennessee, metropolitan 

statistical areas. Bold numbers show percentage of respondents.

A B

Less than high school

33

18

5 2

3 8

21

10

30

24

3 1 4 9

18

11

PhD degree

Masters degree

4-year degree

2-year degree

Some college

High school/GED

EXPLANATION

JD, MD degree
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 91

Are Respondents Representative of the 

Population?

This section addresses differences between the demographics 

of survey respondents and the population of their state or 

community. If one is to draw any conclusions about what 

American adults think based on what these respondents said, 

one must ask how representative respondents are of the larger 

group. According to SurveyMonkey (2015), respondents 

“represent a diverse group of people and are reflective of the 

general population. However, as with most online sampling, 

respondents have Internet access and voluntarily joined a program 

to take surveys.” Most of the U.S. population regularly uses 

the internet—87 percent according to the Pew Research Center 

(2014). However, not all volunteer to take SurveyMonkey 

surveys. Respondents receive an incentive to take surveys. “Each 

time a SurveyMonkey Contribute member completes an eligible 

survey, SurveyMonkey makes a [$0.50] contribution to a charity 

of the member’s choice, and the member can choose to enter a 

sweepstakes.” 

I quantify how representative the survey seems to be. 

The demographics of the survey do deviate from those of the 

population as a whole. More women than men responded to the 

survey in both regions. Responses included 496 women and 

317 men, or a 3:2 ratio rather than the approximately 1:1 ratio in 

the general public (fig. 15A). Respondents were also generally 

wealthier than the population (fig. 15B). California income 

data are taken from U.S. Census Bureau’s (2015) American 

Community Survey for California households in 2013. Median 

household income data for Memphis and St. Louis MSAs in 2010 

were taken from U.S. Conference of Mayors (2012).

Respondents in both regions report more education than 

the population as a whole (fig. 16). Educational attainment of 

Californians is as of 2009 from U.S. Census Bureau (2012). 

Memphis MSA data are for 2014 from Memphis Chamber 

of Commerce (2015). Data for St. Louis are for 2012 from 

University of Missouri St. Louis, Public Policy Research 

Center (2014). 

More respondents are of European (white/Caucasian) 

descent than the population as a whole (fig. 17). Race and 

ethnicity data are taken from U.S. Census Bureau (2011). 

Survey respondents seem to be more likely to be of 

European descent than the general population in either region. 

They are somewhat wealthier and have more education than 

the general population. These differences may produce a 

difference between survey participants’ responses and those of 

the general population. The next section tests that hypothesis. 

Figure 14. Pie diagrams for survey of the public’s preferences for the seismic performance of new 

buildings showing responses to “How much total combined money did all members of your HOUSEHOLD 

earn last year?” for people in (A) California and (B) in the St. Louis, Missouri, and Memphis, Tennessee, 

metropolitan statistical areas. Bold numbers show percentage of respondents.

AAXXXX_fig 01

A B

$0–9,999

9

3

2

7

12

9

5

15 9

17

12 8

4

2

4

14

4

4

18 7

17

18

$125,000–149,999

$100,000–124,999

$75,000–99,999

$50,000–74,999

$25,000–49,999

$10,000–24,999

EXPLANATION

Household income, in thousands of dollars

$150,000–174,999

$175,000–199,999

>$200,000 

$150,000–174,999
92 The HayWired Earthquake Scenario—Engineering Implications

Figure 15. Histograms of respondent (A) gender and (B) median household income for survey of the public’s preferences 

for the seismic performance of new buildings in the California and St. Louis, Missouri, and Memphis, Tennessee, 

metropolitan statistical areas (MSA). 

Figure 16. Histogram of respondent 

education attainment for survey of the 

public’s preferences for the seismic 

performance of new buildings in the 

California and St. Louis, Missouri, and 

Memphis, Tennessee, metropolitan 

statistical areas (MSA) as compared to 

relevant populations 25 years and older. 

%, percent; HS/GED, high school degree 

or General Educational Development 

certificate; BS, bachelor’s degree; MS, 

master’s degree; CA, California; NMSZ, 

New Madrid Seismic Zone; <, less than.

0

25

50

75

100

Gender, as percentage of population

California

 New Madrid

Seismic Zone

EXPLANATION

A B

Female

Male

$0

$25,000

$50,000

$75,000

$100,000

Median household income, in dollars

California

New Madrid 

Seismic Zone

Memphis

St. Louis

Sample Population Sample Population Sample Population Sample Population

California sample

California population

NMSZ sample

Memphis population

St. Louis population

EXPLANATION

High school 

 or less

 At least 

high school 

 or GED

 At least 

Bachelors 

 degree

 Masters and 

professional degree 

 or higher

Education attained, as percentage of population 

0 25 50 75 100
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 93

Are Some Groups Willing to Pay More 

for Better Seismic Performance?

This section examines whether some groups are more willing 

to pay for better seismic performance than others. Better seismic 

performance is measured here in terms of building impairment. 

Suppose that people also equate better seismic performance 

with more life safety. In such a case, one could compare these 

survey results with expectations from other methods to estimate 

willingness to pay for safety. There is a rich literature addressing 

people’s willingness to pay for safety; I consider just a few sources 

and compare what one may predict from them with observations 

from the present survey.

Needleman (1982) examines several methods to value life 

safety, including lifetime earning potential (the human capital 

approach), questionnaires to ascertain people’s willingness to pay 

to reduce their own risk, observed willingness to pay to reduce 

risk, and observed willingness to take on additional risk for extra 

pay. He found that the last method produced the most reliable 

estimates of people’s valuation of small changes in their own risk, 

and the upper bound, the value of avoiding a fatality, is equivalent 

to 20 times average annual income.

Figure 17. Histogram of respondent race or 

ethnicity for survey of the public’s preferences for 

the seismic performance of new buildings in the 

California and St. Louis, Missouri, and Memphis, 

Tennessee, metropolitan statistical areas (MSA) 

as compared to relevant populations. %, percent; 

NMSZ, New Madrid Seismic Zone.

In Porter (2002), I briefly review various methods to 

estimate willingness to pay for more safety in earthquakes, adding 

to Needleman’s list the application of Stanford-style decision 

analysis, such as proposed by Howard (1980, 1989). In that 

work I show that, if people behaved as predicted by decision 

analysis, they should be more willing to pay for life safety in direct 

proportion to their annual consumption (roughly equivalent to 

household income), which is consistent with Needleman’s finding. 

I also show that under Howard’s decision-analysis framework, 

older people should be less willing to pay for life safety than 

younger people, and men should be less willing to pay for life 

safety than women.

Based on these works, one might suspect that the survey 

results would exhibit a relation between household income 

and willingness to pay for better performance or between 

age and willingness to pay. If either were true, the survey 

would exhibit a sampling error—a difference between 

survey responses and the opinions of the broader population. 

However, a regression analysis of the data from the present 

survey found no strong trend relating household income and 

willingness to pay for better building performance. Nor do the 

survey responses show a relation between education, age, or 

gender and willingness to pay. 

California sample

California population

NMSZ sample

Memphis population

St. Louis population

EXPLANATION

Race, as percentage of population 

Other

Asian

Hispanic

African American

Caucasian

0 25 50 75 100
94 The HayWired Earthquake Scenario—Engineering Implications

The coefficient of determination (R2), between individual 

respondents’ household income and acceptable cost for better 

performance was 0.010 among 350 Californians who provided 

both quantities. It was 0.0001 among 303 people from St. Louis 

and Memphis who provided both quantities. Regression analysis 

to relate acceptable cost and age in years similarly exhibited low 

coefficients of determination—0.001 in St. Louis and Memphis, 

0.002 in California. Men and women were approximately equally 

willing to pay for better seismic performance—in St. Louis and 

Memphis, women were willing to pay 13 percent more on average 

than men, but in California, men were willing to pay 6 percent 

more than women. 

One might also suppose that years of secondary and 

postsecondary education would correlate with acceptable cost 

for better performance. Among 413 Californians who answered 

both questions, R2=0.020, and among 170 people from St Louis 

and Memphis who provided both quantities, R2=0.022. Nor does 

one derive higher coefficients of determination from nonlinear 

regression, fitting polynomials of second, third, or fourth order. 

(Actually the R2 values do rise slightly, but the rise has more to do 

with overfitting than with more information.) 

All these coefficients of determination are too low to reject 

the null hypothesis at the 5-percent significance level, where the 

null hypothesis is that the correlation coefficient (ρ) is in fact 

zero. Put another way, there appears to be no strong relation 

between education and acceptable cost for better performance, 

between household income and acceptable cost for better 

performance, or between respondent age and acceptable cost for 

better performance. 

Conclusions

As part of the HayWired scenario’s study of the unintended 

consequences of the building code’s seismic performance 

objective, I undertook a public survey in two highly seismically 

active regions of the United States—one of California adults and 

another of adults in two metropolitan areas near the New Madrid 

Seismic Zone in the Central United States, namely the Memphis 

and St. Louis MSAs. Sample sizes in both regions (413 adults in 

California and 401 near the New Madrid Seismic Zone) ensure 

that the results reflect the opinions of the public with ±5-percent 

margin of error with 95-percent confidence, at least insofar as 

respondents resemble the public. 

The purpose of the survey was to determine whether the 

public understands the current life-safety objective of the building 

code’s seismic-design requirements; what the public prefers 

in terms of the performance of the building stock in a large 

earthquake; whether the public would be willing to pay the cost of 

stronger buildings; and how important the public finds the issue 

of the seismic performance of buildings. The survey found that 

respondents in both regions: 

1. Are largely unaware of the life-safety seismic performance 

objective of ASCE/SEI 7 and the International Building 

Code;

2. Are more interested in controlling total number of deaths 

and injuries in a large earthquake than in controlling perbuilding collapse probability;

3. Are also interested in more than the total number of 

casualties, specifically that buildings should remain 

functional or habitable after a large earthquake (the “Big 

One” in the language of the survey), and prefer better 

performance than the code is intended to deliver for new 

buildings;

4. Expect better seismic performance than ASCE/SEI 7 intends 

to provide;

5. By a large majority, are willing to pay for greater 

seismic safety, with the modal response (the most 

common response) being $3 per square foot additional 

construction cost to achieve such a higher level of 

performance;

6. Believe that the degree of seismic performance of 

buildings is important or very important—the response 

of approximately 80 percent of respondents, even in the 

Central United States where earthquakes happen much less 

frequently than in California;

7. Are more commonly of European descent, wealthier, and 

more educated than the general public, but regression 

analyses found no strong trends in either region relating 

education to acceptable cost for better performance or 

relating household income to acceptable cost for better 

performance.

Study Implications

The survey implies several needs:

1. The Building Seismic Safety Council, which originates 

many innovations of ASCE/SEI 7, could revisit the 

performance objectives that underlie the seismic-design 

criteria of ASCE/SEI 7, considering (among other issues) 

the public’s preferences as elicited here. 

2. Structural engineers could communicate better with 

elected officials who adopt building codes if they want 

to reduce the public’s apparent misunderstanding of 

the code’s performance objectives for new buildings. 

Engineers might, for example, create brief (1 page or 

so) documents about the community-level outcomes of 

the “Big One,” written in plain English, and targeted 

to elected officials, building owners, urban planning 

organizations, and other stakeholders among the public 

(as meant here). Such documents could perhaps be 

included in an appendix to ASCE/SEI 7, or distributed by 

other means such as by the National Institute of Building 

Sciences to the United States Conference of Mayors, 

and the Building Owners and Managers Association 

International.
Chapter L. Not Safe Enough—A Survey of Public Preferences for the Seismic Performance of New Buildings 95

3. Practical options are needed that elected officials can select 

in case they find the code’s outcomes unacceptable. For 

example, an appendix of ASCE/SEI 7 or of the International 

Building Code could explain the costs and benefits of higher 

design requirements and offer optional adoption language 

to increase required design strength. The optional language 

might locally modify the code to require all ordinary 

buildings (called “risk category II” in ASCE/SEI 7-10) to be 

designed with a seismic importance factor of 1.5.

More narrowly, the study has some implications for the 

HayWired scenario. It suggests that:

1. The HayWired scenario study of the potential outcomes of 

designing stronger buildings (Porter, Societal Consequences, 

this volume) addresses a real, measured public preference 

for more resilient buildings among Californians.

2. Elected officials in the San Francisco Bay area might be 

interested in hearing about public preferences for the seismic 

performance of new buildings. 

3. Those same elected officials might be interested in hearing 

about the costs and benefits of higher design requirements in 

light of this study and the damage estimated by HayWired in 

general.

Limitations and Research Needs

Respondents spanned the domain of age, gender, race and 

ethnicity, educational attainment, and income of both regions, 

so there are no significant unrepresented groups. However, this 

survey only examined two regions. It may be that people in other 

high-hazard areas have different preferences. Further regression 

analysis might detect a trend relating other parameters to preferred 

performance level or to acceptable cost for better performance. 

Respondents seemed to understand the questions, especially 

regarding acceptable cost for better performance, but it may be 

that they would act differently when actually confronted with a 

real purchasing decision. The present survey only begins to study 

the public’s preferences for the seismic performance of new, 

code-compliant buildings. More research might better measure 

any differences between what the code provides and what the 

public wants. It may be interesting to survey engineers and others 

involved in the building trades to explore whether and how 

their preferences differ from those of the public. It would also 

be interesting to explore the question of preferred performance 

measure more deeply, such as degree of preference for each option 

or alternative ways of dealing with probability.

Acknowledgments

Survey questions were drafted with the assistance of the 

National Institute of Building Sciences’ Multihazard Mitigation 

Council Public Expectations Subcommittee—Gary Ehrlich, 

Juliette Hayes, Kevin Mickey, Evan Reis, and Phil Schneider. Dr. 

Liesel Ritchie reviewed survey questions and provided valuable 

advice about wording, demographic questions, and survey size. 

Sharyl Rabinovici (private consultant), Phil Schneider (National 

Institute of Building Sciences), and Anne Wein (USGS) provided 

peer reviews and valuable constructive criticism. The Association 

of Bay Area Governments and the Association of Contingency 

Planners provided opportunities to test and administer the 

preliminary survey. Anne Wein performed some preliminary 

surveys at meetings of the Association of Bay Area Governments. 

The author thanks all these people and organizations. 

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Chapter M

An Earthquake Urban Search and Rescue Model for 

Earthquake Response and its Application to the HayWired 

Scenario

By Keith A. Porter1

of Civil Engineers, 2010). It seems realistic that 2,500 people 

would be trapped in 5,000 collapsed buildings. (Not every 

building collapse traps people). If all buildings were designed 

to be 50 percent stronger than currently required under the 

International Building Code, both figures could be reduced 

by approximately a factor of four. Using statistics about how 

many elevators there are in the United States, how many have 

emergency power, and what fraction of them are occupied 

and traveling between floors, I estimated that loss of power 

in the HayWired mainshock could trap 22,000 people in 

4,500 stalled elevators, placing additional demands on USAR 

personnel. If newer elevators were provided with emergency 

power, the number trapped in elevators could be reduced to 

14,000 people in 3,000 elevators.

Introduction

The HayWired earthquake scenario examines a hypothetical moment magnitude (Mw) 7.0 earthquake (mainshock) 

occurring on April 18, 2018, at 4:18 p.m., on the Hayward 

Fault in the east bay part of the San Francisco Bay area. This 

chapter estimates demand for urban search and rescue (USAR) 

related to building collapse in the HayWired scenario.

What is meant when one says a building has collapsed in 

an earthquake? When it collapses, what does the damage look 

like? The answer matters for at least two reasons. (1) Engineers would like to create second generation, performancebased earthquake engineering (PBEE-2) models of the effects 

of collapse on safety (see, for example, an early effort by Yeo 

and Cornell, 2002). So and Pomonis (2012) recently proposed 

a process for estimating fatalities in collapsed buildings during 

earthquake ground shaking using their engineering judgment 

of fatality rate by building type, informed by fatality data from 

various recent earthquakes. (2) Building collapse affects the 

demand for urban search and rescue. Elevators stalled without 

Abstract

Few researchers have examined the potential for earthquake-induced building collapses and electrical failures to 

trap building occupants. The HayWired earthquake scenario 

examines a hypothetical moment magnitude (Mw) 7.0 earthquake (mainshock) occurring on April 18, 2018, at 4:18 p.m., 

on the Hayward Fault in the east bay part of the San Francisco 

Bay area. To estimate demand for urban search and rescue 

(USAR) related to building collapse in the HayWired scenario, 

I compiled a database of photographic evidence of 73 building 

collapses in California earthquakes between 1965 and 2014. 

The database includes all images in the University of California, Berkeley, National Information Service for Earthquake 

Engineering (NISEE) e-library whose descriptions use any of 

the words “collapse,” “fail,” “fell,” or “parapet,” along with 

data taken from other sources about 14 additional buildings. I 

interpreted each image to estimate the fraction of building area 

that collapsed and the fraction of occupants in the collapsed 

area who would realistically be trapped and require extrication 

by others. The proportions vary by structural material, but on 

average, collapse involves 23 percent of the area of the buildings and traps 66 percent of the occupants in the collapsed 

area. Using this new knowledge and other information about 

the number of collapsed buildings, I can estimate the number 

of people requiring extrication by USAR personnel.

In the case of the HayWired scenario, two alternative 

methods suggest approximately 5,000 buildings could collapse. The two methods are described elsewhere, but briefly, 

they are Hazus-MH (Seligson and others, this volume) and 

the approach described in Porter (2015). The latter essentially 

relies on the model of building collapse underlying the maps 

of risk-adjusted maximum considered earthquake ground 

motions in ASCE Standard ASCE/SEI 7-10 Minimum Design 

Loads for Buildings and Other Structures (American Society 

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013 ]

 1University of Colorado Boulder.
100 The HayWired Earthquake Scenario—Engineering Implications

power may also trap substantial numbers of people who must 

be rescued by USAR personnel (see, for example, Schiff, 

2008). The present HayWired study seeks to (1) clarify what 

is meant by “collapse,” (2) advance demand for mathematical 

modeling of USAR, and (3) illustrate a new model by applying it to the HayWired mainshock.

Objective

This report describes the use of USAR modeling and 

addresses the following questions:

1. When engineers use the word “collapse” to describe 

the seismic performance of a building, what fraction of 

the occupiable floor area deforms severely enough to 

threaten lives in that area? (I offer an empirical answer 

by examining a database of photographs of building collapses. Such an empirical study complements numerous 

analytical assessments of collapse.)

2. What fraction of occupants in the collapsed areas require 

extrication, and by whom? (I answer this question 

by interpreting the image database in light of Federal 

Emergency Management Agency [FEMA] Urban Search 

and Rescue guidelines; for example, PerformTech, Inc., 

2011.)

3. How many elevators are in the affected metropolitan 

area, how many of them are carrying passengers (and 

how many passengers) between floors at the time of the 

earthquake, and what fraction of those elevators have 

emergency power to bring the elevator to a floor and 

open the doors?

To keep the level of effort commensurate with the value 

of the information, I consider only one extensive, although not 

exhaustive, data source—the Earthquake Engineering Online 

Archive provided by the National Information Service for 

Earthquake Engineering (NISEE), University of California, 

Berkeley. NISEE refers to the archive as the NISEE e-library 

(see http://nisee.berkeley.edu/elibrary/). NISEE describes 

the e-library as “a database of significant, publicly funded 

research and development literature, photographs, data and 

software in earthquake, structural, and geotechnical engineering.” I exclude manufactured housing, fences, equipment, and 

bridges from the objective. I also acknowledge that the NISEE 

e-library is not exhaustive. It is treated here as a sample, not as 

documentation of the population of collapsed buildings, with 

the expectation that it is a diverse and representative sample.

One could conceivably address the building collapse 

questions with structural analysis, either instead of, or in addition to, the empirical approach of examining photographic 

evidence. But it seems doubtful that structural analysis would 

reliably reveal the extent of collapse, because structural 

analysis is not yet capable of reliably predicting the onset of 

collapse, its dynamics, and the eventual shape of a collapsed 

building. The authors of FEMA P–695 (Applied Technology 

Council, 2009), for example, identified collapse as the condition that lateral dynamic instability appeared during incremental dynamic analysis, meaning that collapse occurs when 

structural analysis of a mathematical representation of the 

building fails to converge. Failure of a mathematical model to 

converge following the loss of vertical load-carrying capacity 

provides little information about how much of or how far a 

floor or roof diaphragm falls. The authors of FEMA P-695 further cite examples of possible nonsimulated collapse modes, 

meaning collapse modes that a structural analysis might not 

reveal. These include “shear failure and subsequent axial failure in reinforced-concrete columns, fracture in the connections 

or hinge regions of steel moment frame components, or failure 

of tie-downs in light-frame wood shear walls. Component 

failures such as these may be difficult to simulate directly.” 

Another reason to favor an empirical study over an analytical 

study is that empirical models are more credible than analytical ones, at least among the loss-estimation community, where 

an empirical model is always preferred to an analytical one, 

all else being equal. Analytical models often serve to validate 

an empirical one or to provide insight where empirical data 

are lacking. None of this is to say that an analytical study will 

never have anything to offer to the question of area affected 

by collapse, but rather an empirical study seems more likely to 

provide defensible results in the near term for much less effort.

Literature Review

Literature About People Trapped by Building 

Collapse

It is believed that building collapse dominates earthquake 

casualty risk and contributes substantially to USAR demands. 

The 2009 National Earthquake Hazards Reduction Program 

(NEHRP) provisions (Building Seismic Safety Council, 2009) 

assert that “Most earthquake injuries and deaths are caused by 

structural collapse.” Although that statement could be true in 

general, it probably exaggerates the importance of structural 

collapse for nonfatal injuries, at least in California earthquakes 

such as those of the late 1980s and early 1990s, judging by the 

analysis Shoaf and others (1998). The National Fire Protection 

Association (2014) offers descriptive patterns of earthquakeinduced building collapses in earthquakes and explains the 

causes and nature of voids where occupants can escape injury 

in collapsed buildings (fig. 1).

The authors of the Hazus-MH technical manual (Federal Emergency Management Agency, 2012) offer estimates 

of the fraction of occupants in collapsed area who are killed. 

Their estimates draw on the judgment-based ATC-13 (Applied 

Technology Council, 1985), which they “revised based on 

comparison with a limited amount of historical data,” and validated against “several recent events, including the Northridge, 
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 101

Loma Prieta and Nisqually earthquakes . . .” They estimate 

that 10 percent of occupants in collapsed areas of buildings 

are killed and 65 percent are injured to some degree. The two 

leading public models of earthquake risk, Hazus-MH (Federal 

Emergency Management Agency, 2012) and ATC-13 (Applied 

Technology Council, 1985), do not address search and rescue 

demands.

Collapse fragility functions, which estimate the probability that a building will collapse under various levels of 

excitation, are available or can be derived (see, for example, 

Applied Technology Council [2009] or Federal Emergency 

Management Agency [2012]). However, I could find no prior 

work that quantifies the fraction of the building area that collapses when a building experiences some collapse.

When buildings in California collapse, they rarely pancake. That is, they rarely collapse such that the floor or roof 

over every square foot of occupiable floor area drops because 

of the loss of vertical load carrying capacity of the portion of 

the gravity system that supports it. One could conceivably use 

structural analysis to model the collapse behavior of sample 

buildings, but the state of the practice enables structural engineers only to estimate the excitation associated with the onset 

of collapse, as the authors of FEMA P–695 (Applied Technology Council, 2009) did quite extensively. Another approach, 

explored here, is to review postearthquake observations of 

building collapse. The present work focuses on California 

buildings.

The International Building Code (International Code 

Council, 2009) does not use the word “collapse” at all. The 

authors of ASCE/SEI 7-10 (American Society of Civil Engineers, 2010) use the word “collapse” in defining the probabilistic (MCER) ground motion and in describing the anticipated 

maximum probability of failure for earthquake loading. It does 

not define collapse, but it does define progressive collapse as 

“the spread of an initial local failure from element to element, 

resulting eventually in the collapse of an entire structure or 

a disproportionately large part of it.” It also defines the term 

“limited local collapse” with an example: “the containment of 

damage to adjacent bays and stories following the destruction 

of one or two neighboring columns in a multibay structure.”

Wall-fall collapse pattern—heavy wall—

unreinforced-masonry construction

Offset collapse pattern—light-frame construction

Wall-fall collapse pattern—heavy wall—tilt-up construction

Wall-fall collapse pattern—heavy wall—tilt-up construction

Overturn collapse pattern—heavy-floor or heavy-steel construction

Soft first-story collapse pattern—heavy-floor construction

Random-fall collapse pattern—precast-concrete construction

Figure 1. Illustrations of building collapse patterns in earthquakes (modified from National Fire Protection Association, 2014).
102 The HayWired Earthquake Scenario—Engineering Implications

The 2009 NEHRP provisions (Building Seismic Safety 

Council, 2009) mention structural collapse, collapse of small 

structural systems (such as a hospital canopy), and collapse 

of nonstructural components (such as light fixtures, ductwork, 

and piping systems), but they do not define the word. FEMA 

P–695 defines collapse as “including both partial and global 

instability of the seismic-force-resisting system,” excluding 

“local failure of components not governed by global seismic 

performance factors, such as localized out-of-plane failure 

of wall anchorage and potential life-threatening failure of 

nonstructural systems” (Applied Technology Council, 2009). 

It does not include in its consideration of collapse damage to, 

or failure of, “components that are not designated as part of 

the seismic-force-resisting system” because those components 

“are not controlled by seismic-force-resisting system design 

requirements,” and they are therefore not within the scope of 

the project. The authors of FEMA P–695 include among the 

possible definitions of collapse the occurrence of a sidesway 

mechanism, and more generally the “state of lateral dynamic 

instability.”

In more recent work, I and colleagues developing the 

third edition of FEMA P–154 and FEMA P–155 (Applied 

Technology Council, 2015a,b) and proposed the following definition. We generally define building collapse as the condition 

in which “any part of the gravity system experiences dynamic 

instability leading to the loss of load-bearing capacity. The 

dynamic instability leads to severe structural deformation of a 

potentially life-threatening nature, especially falling of all, or 

portions of, a structure. Partial building collapse means that 

the dynamic instability occurs only in a portion of the building . . . In the case of manufactured housing and wood frame 

buildings, building collapse also includes the condition that 

the manufactured home falls off one or more of its supports, 

or the cripple walls of a wood frame building experience a 

sidesway mechanism and lose their vertical load-carrying 

capacity” (Applied Technology Council, 2015b). Building collapse does not include wood frame buildings sliding relative to 

their foundations if there is no vertical drop in any part of the 

floor or roof. Nor is the falling of a parapet from an unreinforced masonry (URM) building or brick veneer or chimney 

from any FEMA building type considered to constitute building collapse.

The United States Federal Emergency Management 

Agency National Urban Search and Rescue Response System (2009) estimates that, of people injured in buildings in 

earthquakes, 50 percent are injured but not trapped, and can 

be aided by emergent, untrained volunteers—civilians—who 

happen to be nearby at the time of the earthquake (fig. 2). 

Another 30 percent are injured and trapped, but not by structural components, for example, by overturning of furniture, 

and are extracted by trained local community emergency 

response teams (CERTs). CERTs are trained to perform search 

and rescue in buildings that have damage to decorative work 

and to interior contents but are not collapsed or fallen from 

their foundations; that would presumably include chimney and 

parapet damage (PerformTech, Inc., 2011). An additional 15 

percent of people injured are rescued from the collapse of light 

structures, such as wood frame construction and manufactured 

housing, by emergency services rescue forces—generally firefighters—without the need for heavy excavation equipment. 

The remaining 5 percent must be extricated by trained urban 

search and rescue forces aided by equipment to penetrate 

heavy structures—masonry, concrete, and structural steel.

There do not appear to be any published statistics on 

the frequency of each collapse pattern or what fraction of 

occupants require extrication by search and rescue personnel, 

although there is limited anecdotal evidence about individual 

buildings, such as Krimgold’s (1988) statistics from the 

12-story Juarez Hospital that collapsed in the 1985 Mexico 

City earthquake.

Trapped

Lightly

trapped

Nonstructure

entrapment

Injured and not 

trapped

Urban

search and

rescue task

force

Light search 

and rescue

Community response 

teams

Spontaneous response

by civilians nearby

5 to 10 percent

15 percent

30 percent

50 

percent

Figure 2. Pyramid charts showing the distribution of assistance in a large earthquake (after National Urban Search and Rescue 

Response System, 2009).
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 103

Literature About People Trapped in Elevators

The vast majority of San Francisco Bay area buildings do 

not have uninterruptible power supplies or emergency generators to power elevators in the absence of commercial power. 

According to National Elevator Industry, Inc. (2014), there are 

900,000 elevator units in the United States, or approximately 

one elevator per 344 people. Each elevator makes an average 

rise of 4 to 5 floors, or 40 feet, and each carries an average of 

5 people per trip. Each passenger averages 4 trips per day, 250 

days per year. According to the Emporis Corporation (2007) 

database of high-rise buildings, there are approximately 600 

high-rise buildings with approximately 3,700 elevators in the 

San Francisco Bay area.

Sample calculations in Strakosch and Caporale (2010) 

suggest that an elevator is in motion with the doors closed 

approximately 30 percent of the time that it is in use with passengers inside. Some elevators have battery power to operate 

briefly to move the cab to a floor and open doors.

According to San Francisco Bay area elevator consultant 

von Klan (written commun., 2015), elevators installed in highrise buildings in the past 40 years or so have been required 

to have emergency power for elevators, and he estimates that 

perhaps 60 percent of high-rise buildings in the bay area were 

constructed since this time. He also estimates that less than 

5 percent of elevators in mid- and low-rise buildings have 

emergency power. Even if there were emergency power available, seismic safety devices installed in newer elevators may 

stop the elevator between floors until a technician inspects the 

elevator.

Methodology

Methodology for Estimating the Number of 

People Trapped by Collapse

The illustrations in figure 1 do not represent an exhaustive typology of collapses that could trap occupants or 

passersby. If a portion of a parapet falls, it does not constitute 

building collapse, but engineers do speak of parapets collapsing, and parapet collapse does not appear in figure 1. I therefore include in collapse (1) the falling of a floor or roof such 

that the clear height is reduced to less than 2 meters (m), and 

(2) the falling of parapets, chimneys, and other elements, but I 

exclude the falling of other contents and movable furnishings, 

such as cubicles. For purposes of estimating the probability 

of being injured or trapped by collapse, I define collapse as 

follows:

Collapse constitutes the condition where, in a portion of 

the building or in the entire building, the gravity load-carrying 

system (for example, its beams, columns, floors, and shear 

walls) loses the ability to carry its own weight and the weight 

of whatever else it supports. That failure leads to severe 

building deformation of a potentially life-threatening nature, 

especially if all or portions of a building fall. The nonstructural 

portions of a building are included in our definition of collapse, 

along with the structural portions, such as parapets, chimneys, 

and porches. Thus, some nonstructural collapses are included 

(parapets, chimneys, and porches), but some structural failures 

are not (permanent lateral displacement of the building relative 

to the foundation where no vertical drop occurs).

I estimate fatality rate and USAR needs in future earthquakes as follows. I estimate fatality rate as the product of the 

collapse probability conditioned on ground motion, the fraction 

of the building floor area that actually collapses when there is 

at least some collapse, and the fraction of occupants in that collapsed area that are killed, as in equation 1:

 (1)

In the equation, F(h) represents the fatality rate in a building (fraction of occupants killed) that is shaken with severity 

h. P(h) denotes collapse probability given shaking h. A denotes 

affected area, that is, the fraction of the building area that collapses, given that at least some collapse occurs. R denotes the 

fatality rate in the collapsed area.

I model search and rescue needs by an analogous equation 

where S(h) and E denote, respectively, the fraction of building 

occupants requiring extrication, and the fraction of occupants in 

the collapsed area who need extrication, as in equation 2:

 (2)

Implicit in equation 2 is the assumption that people are 

uniformly distributed throughout the building: an occupant is 

as likely to be in one place as another. This assumption might 

be conservative; for example, buildings with soft-story conditions are likely to collapse onto the soft story, which tends to 

be less densely occupied garage space rather than more densely 

occupied living space. To account for that fact requires a model 

of the number of buildings that collapse onto soft garage levels. 

I assume for the remainder of this work that one lacks a damage 

model that detailed.

If one already has an estimate of the number of collapsed 

buildings (I denote this number by Nb), then the estimated number of people, Nc

, who are trapped in collapsed buildings and 

require extrication by USAR personnel can be estimated as:

 , (3)

where O(t) denotes the average number of occupants per building at time t, and A and E again denote the fraction of the building area that collapses and the average fraction of occupants in 

the collapsed area who need extrication by USAR personnel, 

respectively. 

One might condition each term in equations 1, 2, and 3 

on building type, era of construction, or other parameters. The 

analyst must estimate the quantity O(t), for example, using estimates of average building area per occupant from Hazus-MH 

F(h) = P(h)× A× R

S(h) = P(h)× A× E

Nc (t) = Nb ×O(t)× A× E
104 The HayWired Earthquake Scenario—Engineering Implications

(Federal Emergency Management Agency, 2012) or ATC-13 

(Applied Technology Council, 1985).

To estimate A, I examined every photograph of a building 

in the NISEE e-library images database from every California 

earthquake in the past 50 years in which the photo description uses the word “collapse,” “fail,” “fell,” or “parapet.” I 

supplemented these images with photos of buildings where I 

knew collapse had occurred. I also added data on tilt-up roof 

collapses in the 1971 San Fernando earthquake extracted from 

a 1973 National Oceanic and Atmospheric Administration 

(NOAA) report that showed building plan area and area of 

roof collapse.

I labeled each building with a building category: wood 

(consisting of FEMA model building types W1, W1A, and 

W2), steel (types S1 through S5), concrete (C1 through C3), 

precast concrete (PC1 and PC2), reinforced masonry (RM1 

and RM2), and unreinforced masonry (URM). To make the 

assignments I used the procedures recommended in FEMA 

P-154 and FEMA P-155 (Applied Technology Council, 

2015a,b). Finally, I aggregated these to four simpler categories: tiltup concrete (PC1), all concrete and precast concrete 

except tiltup, wood, and unreinforced masonry. No other 

building types appeared in the photo database. Of course, 

making these assignments based mostly on photographic evidence can be problematic, because architectural finishes often 

conceal the true structural system. I do not claim complete 

accuracy in making the assignments. Still, it is hard to mistake 

wood, URM, and tiltup construction, especially when one is 

familiar with the historic architectural styles of the region and 

given that collapse tends to peel away architectural finishes. 

I estimated E, the fraction of occupants in the collapsed 

area requiring extrication, as the fraction of the collapsed area 

in which heavy debris or structural elements fell to the floor or 

ground. For example, in the case of bricks littering a sidewalk 

from collapsed parapets or chimneys, it seems reasonable to 

assume that anyone in that debris field would be injured or 

killed and would require extrication by others. In the case of 

collapsed porch roofs resting entirely on the ground or porch, 

anyone beneath the porch would require extrication. In the 

case of houses off their foundations, but where the roof or 

upper floors do not fall, I assume that residents can generally escape through a window or a door that is not blocked. 

It seems realistic that there will be cases of injured or physically disabled people who cannot escape through a window 

unaided, but I assigned E=0 based on the assumption of the 

more likely case, that the occupant is not physically disabled 

or seriously injured.

Social scientists speak of such an approach to sampling 

as a convenience sample, a nonprobability sampling technique 

where subjects are selected because of their convenient accessibility and proximity to the researcher. The main problem 

with convenience sampling is the potential for sampling bias, 

in which one does not know that the sample is representative 

of the entire population. If a database existed of all collapsed 

buildings in a particular earthquake or particular geographic 

region, one could perform a randomized sample or an exhaustive survey and avoid worries about sampling bias, but such a 

database does not exist, so for present purposes I fall back on 

this convenience sample and advocate for a better database in 

the future.

In the present convenience sample, the first California 

earthquake in the 50-year period studied here is the Mw 6.5 

1968 Borrego Mountain earthquake; the last is the Mw 6.0 

2014 South Napa earthquake. In each case, I estimated the 

fraction of the building area affected by the collapse. In many 

cases, particularly ones where only a small portion of a large 

building was affected, the photograph shows the affected area 

but not the overall size of the building, and the building no 

longer exists. In many cases, I found additional evidence of 

the building location and other photographs that show more 

of the building, and in several cases, I estimated building area 

from the area of building shown in Google Earth Pro, which 

includes parcel outlines and recent and historical satellite 

imagery, and has a tool for measuring area. 

The results of my analysis are summarized in table 1. 

The columns list the earthquake associated with the collapse, 

NISEE’s image identifier number, NISEE’s photo description, the building type (using FEMA’s building typology), the 

estimated fraction of the building’s occupiable floor area that 

was affected by the collapse (A), the fraction of occupants 

in the affected area that would require extrication by others 

(E), and the technical qualifications of the people most likely 

to perform the extrication (T). The quantities A and E are 

bounded by 0 and 1. Options for T are labeled by the order 

in which USAR personnel would arrive: 1=emergent civilian 

volunteers (neighbors); 2=CERT; 3=firefighters; and 4=FEMA 

USAR Task Force.

Details of each estimate of A are provided in the appendixes. I binned the fraction of affected area on a quarter orderof-magnitude basis, that is, approximately 10-2, 10-1.75, 10-1.5, ... 

100, which is to say 1 percent, 2 percent, 3 percent, 6 percent, 

10 percent, 18 percent, 32 percent, 56 percent, and 100 percent. From these data, one can create histograms of the data 

as a whole and subdivide by the structural material (wood, 

unreinforced masonry, or concrete).

I estimated T, the technical qualifications of the USAR 

personnel, as 1 (untrained emergent civilian volunteer) if the 

extrication could be done by a single person without tools, as 

in picking up bricks. I assigned T=2 (CERT) if the extrication requires two or more people but no heavy equipment and 

would not violate the CERT training guidelines (PerformTech, 

Inc., 2011). I assigned T=3 if the extrication requires equipment but not heavy lifting or cutting of reinforced concrete, 

such as in the case of a collapsed wood frame building where a 

roof or an upper floor falls onto the floor or furnishings below. 

For example, firefighters extracted Sherra Cox from a collapsed building in the San Francisco Marina District after the 

1989 Loma Prieta earthquake (Scawthorn and others, 1992). I 

assigned T=4 if the extrication requires heavy lifting or cutting 

of reinforced concrete. I made no assignment (T=blank) if 

E=0, that is, no extrication is required.

The database of photos of collapse that I compiled from 

NISEE and the other sources contains 73 California buildings 

that experienced at least some collapse in earthquakes between 
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 105

Table 1. Summary of parameters used in the urban search and rescue (USAR) model for the HayWired earthquake scenario.

[ID, image identifier from Earthquake Engineering Online Archive; type, model building type according to the Applied Technology Council (2015a); A, affected 

area; E, fraction of occupants trapped; T, technical qualifications of USAR personnel; Mw, moment magnitude; %, percent; in., inch; ft, feet; St., Street, Rd., 

Road; Ave., Avenue]

Earthquake ID Damage description Type A E T

Santa Rosa 1969 

(Mw 5.6 and 

5.7)

S3715 Two-story wood frame building off foundations. Foundations 

were rotted and poorly braced. Gas lines ruptured when house 

fell. 718 Beaver St., Santa Rosa, California.

W1 0% 0

S3726 Miramar Building. Collapsed portion of a wall fell on a car. 203 

Old Courthouse Square, Santa Rosa, California.

URM 1% 1.0 1

San Fernando 

1971 (Mw 6.7)

S4473 Damage to porches (probable cripple wall failure?); chimney fell 

away from house. In the vicinity of Knox and Orange Grove 

Streets, in the fault zone.

W1 8% 0.5 3

S4533 Chimney fell towards otherwise undamaged wood frame house. W1 0% 0

S4581 Furniture store. Unreinforced masonry parapet collapsed, 

dumping bricks into the street and on to the sidewalk. Large 

plate-glass windows are gone, presumably shattered by the 

earthquake.

URM 19% 1.0 1

S4597-S4602 Apartments over retail space. Note that the failure of the unreinforced bearing walls did not result in collapse. Unit masonry 

construction, built prior to 1933. Downtown San Fernando 

commercial area.

URM 3% 1.0 1

S4489 Partial collapse on older wood frame house, probable cripple wall 

failure of house. Between Glen Oaks and Hubbard Streets.

W1 0% 0

S4491, S4492 Pink structure at the rear was a residence over a garage. The first 

story collapsed; note remains of automobile under the building.

W1 50% 1.0 3

S4624 Roof to the wall failed first. Ground cracks in the vicinity. Rear 

wall bulged out, and rear roof fell. See S4625-4633. Light 

industrial buildings. Bradley Tract. 12884 Bradley Ave.

TU 11% 0.1 3

Benfe and Coffman (1973, p. 

123)

12840 Bradley Ave. TU 44% 0.1 3

12874 Bradley Ave. TU 12% 0.1 3

12950 Bradley Ave. TU 10% 0.1 3

12881 Bradley Ave. TU 10% 0.1 3

12975 Bradley Ave. TU 23% 0.1 3

13001 Bradley Ave. TU 8% 0.1 3

13069 Bradley Ave. TU 16% 0.1 3

15200 Bledsoe St. TU 19% 0.1 3

15151 Bledsoe St. TU 8% 0.1 3

12860 San Fernando Rd. TU 16% 0.1 3

12806 San Fernando Rd. TU 18% 0.1 3

12744 San Fernando Rd. TU 26% 0.1 3

12814 Bradley Ave. TU 15% 0.1 3

GoddenJ53 Collapse of a split-level wooden home. Large numbers of these 

split-level homes suffered significant damage because of a lack 

of adequate ties between the two levels. The upper level ripped 

away and crushed the lower garage walls, which did not have 

adequate lateral bracing.

W1 33% 1.0 3

S4195 Collapsed Semi-Ambulant Building at Veterans Authority Hospital, built in 1925, masonry construction.URM 50% 1.0 3

S4529 Damage to older house caused by cripple wall collapse. W1 0% 0

S4065 Collapsed tower at southeast corner. Olive View Hospital. Rear 

[east] elevation of Medical Treatment Building.

C2 3.3% 1.0 3
106 The HayWired Earthquake Scenario—Engineering Implications

Earthquake ID Damage description Type A E T

S4070 Ambulance garage collapsed. Olive View Hospital. Southern 

elevation of Medical Treatment Building. See also S4139-44.

C1 100% 0.5 3

S4115, S4117 Soft-story collapse, most evident at upper right of photo. Originally a one- and two-story building, irregular in plan, the first story 

collapsed in the earthquake.

C1 67% 1.0 4

S4519 Collapsed wood frame house under construction on Tucker Street 

near Pacoima Dam.

W1 67% 0.5 3

S4501 Two-story section over garage of this wood frame house on 

Almetz Street has collapsed in the first story. In a new housing 

tract in Sylmar at base of hills and between Olive View and 

Veterans Administration Hospitals.

W1 33% 1.0 3

R0070 Old masonry building in upper center of photo has completely 

collapsed. Constructed in 1925–26, with major additions in 

1938 and 1949, the entire complex was demolished after the 

1971 earthquake and the entire 97 acres were dedicated in 1977 

as Veterans Memorial Park.

URM 100% 1.0 4

Imperial Valley 

1979 (Mw 6.4)

S5584 Cripple wall collapse—wood frame house on G Street in Brawley, 

California.

W1 0% 0

S5585 Cripple wall collapse—wood frame house on G Street in Brawley, 

California.

W1 0% 0

Westmorland 

1981 (Mw 6.0)

N/A Collapsed two-story building on West Main Street in Westmorland, CaliforniaURM 100% 1.0 3

Coalinga 1983 

(Mw 6.2)

GoddenJ52 Chimney collapse of a modern house, 1983 Coalinga earthquake. 

Most of the chimneys were thrown down because of the lack of 

proper connections (straps) to the buildings.

W1 9% 1.0 1

GoddenJ19 This two-story wood frame dwelling underwent a lateral displacement of more than half a meter as illustrated by the slant in the 

porch columns and also fell more than half a meter from its 

foundation, owing to lack of adequate anchorage and support

W1 0% 0

GoddenJ23 Collapse of a wooden porch (owing to lack of proper anchorage 

to the wooden frame of the house and of a proper later-resistant 

supporting system) was owing to vibratory response.

W1 15% 1.0 3

GoddenJ29 The second-story, 8-in. unreinforced solid brick masonry walls of 

this commercial building collapsed because of inadequate tying 

at the floor, roof, and transverse walls.

URM 30% 0.60 1

R0323 Porch running the full width of the church simply pulled away 

from the rest of the building. Built in 1946, the stabilized adobe 

building was heavily damaged but did not collapse. On the 

corner of Jefferson St.

URM 7% 1.0 3

Morgan Hill 

1984 (Mw 6.2)

S5840 Most severely damaged dwelling. Sheathing between first floor 

and foundation was fiberboard with little strength. Morgan Hill, 

California Anderson Lake area.

W1 0% 0

S5839 Dwelling on the left moved, owing to landsliding from the earthquake. Morgan Hill, California, Anderson Lake area.W1 20% 1.0 3

Whittier Narrows 1987 

(Mw 5.9)

S6014 Damage to roof from chimney collapsing. Whittier, California. W1 0% 0

S6023 Chimney collapsed away from the house. Whittier, California. W1 3% 1.0 1

S6020 Chimney fell through porch roof. See S6021 and s6040. Whittier, 

California.

W1 2% 1.0 2

S6022 One chimney collapsed, but not the other. Whittier, California. W1 3% 1.0 1

Loma Prieta 

1989 (Mw 6.9)

LP0042 Wall collapse in unreinforced masonry building. Santa Cruz, 

California.

URM 1% 1.0 1
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 107

Earthquake ID Damage description Type A E T

LP0070 Older building with failed parapets on Main Street. 307 Main 

Street, Watsonville, California.

URM 18% 1.0 1

LP0072 Older building with failed parapets on Main Street. 311 Main 

Street, Watsonville, California.

URM 9.4% 1.0 1

LP0462, LP0460 Collapse of unreinforced brick wall. 6th and Bluxome Streets, 

South of Market District, San Francisco, California.

URM 5.3% 1.0 1

LP0375 Collapse of two four-story apartment buildings (soft ground 

floors). Marina District, San Francisco, California.

W1A 25% 1.0 3

LP0375, S6120 Collapse of two four-story apartment buildings (soft ground 

floors); there were two buildings in the image.

W1A 25% 1.0 3

LP0499 Collapsed apartment building at 2090 Beach Street, after the 

fire was much advanced. Note the firefighter directing water 

onto exposed side of building. Marina District, San Francisco, 

California.

W1A 75% 1.0 3

S6144 Soft-story collapse of apartment building in the Marina District, 

San Francisco, California.

W1A 33% 1.0 3

LP0459 Collapse of unreinforced masonry wall from third floor of building. 235 Front St. at Davis St., Embarcadero/Financial District, 

San Francisco.

URM 2.9% 1.0 1

LP0041 Interior structural failures at Ford’s Department Store. Santa Cruz, 

California.

URM 33% 1.0 3

LP0081-LP0085 Front view of damaged St. Patrick’s church. Watsonville, 

California.

URM 4.5% 1.0 1

LP0087 Damaged bike store with failed parapet. Watsonville, California. URM 25% 1.0 1

LP0090 Pink frame house with failed foundation. Watsonville, California. W1 0% 0

Northridge 1994 

(Mw 6.7)

NR327, NR353, 

NR357, NR358

Collapsed apartment building, three-story wood frame. Northridge, California. According to Todd and others (1994, p. 23), 

four buildings experienced collapse. This is the first.

W1A 33% 1.0 3

Collapsed apartment building, three-story wood frame. Northridge, California. Second building.W1A 33% 1.0 3

Collapsed apartment building, three-story wood frame. Northridge, California. Third building.W1A 17% 1.0 3

Collapsed apartment building, three-story wood frame. Northridge, California. Fourth building.W1A 4% 1.0 3

NR408-409 1004 West Channel Road at Pacific Coast Highway (near Pacific 

Palisades). Damage to two-story masonry building. Heavy 

shear cracking on side walls. Out of plane failure of the second 

story. State Beach Cafe, Santa Monica, California.

URM 13% 1.0 1

NR412-414 Four-story masonry building, 827 Fourth Street, Santa Monica, 

California. Damage to the fourth and third floor of the building. The masonry facade fell out of plane and took with it the 

fourth-floor terrace. This building had been scheduled for a retrofit to begin on Monday, January 17, 1994. Three-layers-thick 

unreinforced masonry. Damage in the top story and balcony. 

Little damage on the sides and below the third story. See also 

NR412–414.

URM 2.1% 1.0 1

20101224 This residential chimney of unreinforced blocks collapsed. W1 2.7% 1.0 1

NR559 Parking structure on Zelzah Ave., California State University, 

Northridge, campus. This is a three-story precast concrete parking structure. Overall view showing collapse at east end of the 

structure.

C1 35% 1.0 4
108 The HayWired Earthquake Scenario—Engineering Implications

Earthquake ID Damage description Type A E T

NR579 Collapse of parking garage floors. See NR459–461 for damage 

to Broadway department store. Fashion Center, Northridge, 

California.

PC1 35% 1.0 4

NR221 Northridge Fashion Island Center. Interior reinforced-concrete 

columns remain standing following collapse of second- and 

third-floor concrete waffle slabs. Intact portion of waffle slab 

roof shows typical slab construction.

C1 78% 1.0 4

NR303 View of partial roof collapse. South elevation, east of front entry. 

View from east. Taken at 3 p.m. California State University, 

Northridge.

C1? 

C2?

1% 1.0 4

NR542, NR543 Complete collapse of parking structure. Los Angeles, California. C1 100% 1.0 4

NR328 Soft-story collapse of apartment building, at Hazeltine Ave. and 

Milbank St. Sherman Oaks, California.

W1A 33% 1.0 3

NR160, NR162 Overall view of Kaiser Permanente office building looking toward 

the northeast. The brick facades at either end of the structure 

have separated from the concrete frame, and the second floor 

of the structure has completely collapsed. The bays at the north 

and south ends of the building are also partly collapsed from 

the second to the fifth floor. Granada Hills, California.

C1 30% 1.0 4

San Simeon 

2003 (Mw 6.7)

NM0001-NM0012 House of Bread, was located in the Mastagni/Acorn Building, 

which collapsed. By the time these pictures were taken, emergency personnel had removed the front wall of the building and 

a great deal of debris. Built in 1892, the clock tower of this unreinforced masonry building had become a symbol of the town 

of Paso Robles. The second story of the building collapsed 

during the earthquake, killing two employees of Ann’s Dress 

Shop. The roof of the building collapsed directly westward onto 

Park Street and landed on a row of parked cars. Debris from the 

north wall went through the roof of an adjacent shop at 1220 

Park Street. Paso Robles, California.

URM 78% 1.0 3

South Napa 

2012 (Mw 6.6)

P9050177, 

P9080152

Don Perico’s Restaurant in Napa. At the time of the earthquake, 

the restaurant was located at 1025 1st St., Napa, California, 

in the west end of the building at lat 38.299029 N., long 

122.285868 W. That address seems to occupy approximately 60 

ft×60 ft. The collapsed wall appears to fill 25 ft by 12 ft, suggesting a collapsed portion of 8.3%.

W2 8.3% 1.0 1

1965 and 2014. The database contains wood, concrete, and 

unreinforced masonry buildings. Areas affected range from 

zero (for example, cripple wall collapse that did not cause 

height reduction of an occupiable area) to 100 percent (for 

example, complete collapse of a parking structure). Among 

the sample of collapsed California buildings of the last 50 

years, the average had 23 percent of its occupiable floor 

affected area. Therefore, on average 23 percent of occupants 

or passersby—people walking within a few feet of the building—could have been trapped or injured by a portion of building falling on them. On average, I estimate that 66 percent 

of occupants in the collapsed area would need extrication by 

USAR personnel, even if only by emergent civilian volunteers. 

Statistics by structural material are shown in table 2.

In California, the 1934 Field Act outlawed the use of 

unreinforced masonry in most buildings. Consequently, URM 

buildings have become rarer in California than elsewhere in 

the Western United States, and many have been retrofitted, 

thus including the data of their past performance could conceivably bias estimates of future performance. Nonetheless, 

removing unreinforced masonry buildings and chimneys from 

the data does not substantially change the average affected 

area. The weighted average considering only tilt-up, other 

reinforced concrete, and wood is 22 percent. If one removes 

the cases where the collapse was limited to or caused by chimney collapse (that is, also removing the case where a chimney 

penetrated a roof), the average increases to 25 percent.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 109

The estimated distribution of minimum USAR technical 

qualifications is shown in table 3. It suggests that most search 

and rescue would have to be done by firefighters, rather than 

by untrained emergent civilian volunteers. This estimate is 

not necessarily inconsistent with figure 2, whose bottom two 

strata are people who are not trapped by collapse and are not 

represented in the collapse photos examined here.

Considering all buildings, the distribution of affected 

area resembles an exponential distribution (though it does not 

pass a Lilliefors, 1967, goodness-of-fit test at the 5-percent 

significance level). An exponential distribution would mean 

that a building is approximately equally likely to collapse on 1 

percent (10-2) of its occupiable area, 2 percent (10-1.75), 3 percent (10-1.5), and so on, through 100 percent (100

). Among the 

wood buildings, the affected area tends to be lower; among the 

nine concrete buildings, the affected area tends to be higher, 

but nearly the full range is exhibited among each building type 

(reinforced concrete, tilt-up unreinforced masonry, and wood), 

as discussed later.

Suppose one wanted to perform a Monte Carlo simulation of USAR needs using a simple parametric model, for 

example, a mathematic idealization of the data presented here. 

To inform such simulations, I evaluated a few common parametric cumulative distribution functions for affected area: uniform, exponential, lognormal, power-law, and the distribution 

shown in equation 4. The equation reflects a model in which 

there is a constant probability f that the affected area is zero. If 

the affected area is nonzero, it is exponentially distributed:

, (4)

where f and L are constants. The affected area data and equation 4 are plotted together in figure 3 for comparison. I refer to 

equation 4 as a frequency-and-exponential-severity model. 

 Of all the forms examined, only the one shown in equation 4 passed the Lilliefors (1967) goodness-of-fit test at the 

5 percent significance level. The Lilliefors test is intended to 

check whether a sample is drawn from a normally distributed 

population with parameters of the distribution estimated from 

the sample. The test is not intended for this frequency-andexponential-severity model. I am aware of no comparable test 

for this frequency-and-exponential-severity model, so let the 

passing of the Lilliefors test merely indicate reasonableness 

in a qualitative manner. A parametric expression similar to 

a power law is also shown in figure 3. It does not fit quite as 

well as the frequency-and-exponential distribution, but it is 

simpler.

Given a building that is modeled as having collapsed, 

one could simulate affected area by inverting equation 4 at the 

value of a sample of a random variable uniformly distributed 

between 0 and 1; that is, if I draw a sample u~U(0,1), then the 

sample of affected area is the following:

 . (5)

The mean number of people trapped in the collapsed area 

can be estimated as n in equation 6 where the symbols ⎣⎦ mean 

“floor,” that is, the largest integer less than or equal to the 

value inside: 

 , (6)

where N denotes the number of occupants in the building and 

E=0.66. Alternatively, to account for building type and to treat 

uncertainty at least to a limited degree, use the cumulative 

distribution function of area affected from figure 3B. Invert the 

expression for P[X≤x] shown in the figure at a random sample of 

U(0,1) to simulate the affected area x. Then calculate n according 

to equation 6 using the value of E from table 2, and invert the 

Table 2. Average affected area (A) and average fraction of 

occupants in collapsed areas requiring extrication (E) in the urban 

search and rescue (USAR) model for the HayWired earthquake 

scenario.

[%, percent]

Material Count Average A Average E

All 73 23% 0.66

Tilt-up concrete 14 17% 0.10

Other concrete 9 50% 0.94

Unreinforced masonry 18 28% 0.98

Wood 32 17% 0.66

All except unreinforced 

masonry

54 22% 0.56

All except chimneys 66 25% 0.65

Table 3. Distribution of minimum technical qualifications for urban search and rescue (USAR) personnel, in percent.

[CERT, community emergency response team; URM, unreinforced masonry]

Technical qualifications All URM Not URM Tilt-up Other concrete Wood Chimney Not chimney

1 Civilian 27 67 11 0 0 23 80 22

2 CERT 2 0 2 0 0 5 20 0

3 Firefighter 59 28 71 100 22 73 0 64

4 USAR Task Force 13 6 16 0 78 0 0 14

P[X ≤ x] =1− f × exp(−Lx);X ≥ 0

x = 0 u ≥ f

= −1

L

ln (1−u)

f

u < f

n = ⎢⎣x × N × E⎥⎦
110 The HayWired Earthquake Scenario—Engineering Implications

binomial cumulative distribution function with parameters n and p, 

where p is another sample of U(0,1). One could go farther, treating 

N as random and using a separate cumulative distribution function 

for affected area that varies by building type, but such a treatment 

is omitted here for brevity. 

If one wanted to use the data presented here for modeling 

future performance of buildings, one must assume that the past 

is indicative of the future. Is it? There does not appear to be 

a correlation between affected area and earthquakes occurring in later years, as shown in figure 4. The trend line has 

almost no slope, and the coefficient of determination (R2) is 

so low (0.0006) that one can be fairly confident that no trend 

actually exists. Because each earthquake affects an existing 

building stock that was built up over decades, the relation 

would be a lagging indicator, meaning a measurable factor 

that changes only after the process it measures has begun to 

follow a particular pattern or trend. But because approximately 

half the building stock was replaced over the five decades 

examined here, if newer buildings tended to experience lower 

collapse areas, one would expect to see a stronger downward 

trend. The implication is that, while collapse probability of an 

arbitrary building in the building stock may or may not change 

over time, if a building does collapse, its collapse area is not 

related to the year of collapse. To be clear, figure 4 does not 

say anything about the collapse probability of older versus 

newer buildings. It says only that, in that subset of buildings 

where at least some collapse occurs, the affected area does not 

vary with the year in which the earthquake occurred. One can 

reasonably assume that buildings in near-future earthquakes 

(the next several decades) will have approximately the same 

distribution of affected area as in the previous five decades. 

Note that the catalog does not indicate the age of the building that collapsed. Newer buildings presumably have a lower 

collapse probability than older buildings, all else being held 

equal, but that issue is separate from the one examined here.

A few additional observations of the nature and extent of 

collapse.

• Figure 5 shows that collapse of buildings with bearing walls composed of wood or unreinforced masonry 

generally affected the smallest total area in these buildings, followed by tilt-up concrete, then other reinforced 

concrete.

• Most collapses involving wood frame buildings affect 

less than 10 percent of the building area, that is, the 

median affected area is less than 10 percent. Furthermore, 95 percent of collapses affect less than half the 

building area. More than 30 percent do not collapse 

into occupied space at all. As shown in figure 5, the 

modal affected area (the tallest bar on the 1⁄4-logincrement bar charts) for wood frame buildings was 

between 0 and 1 percent. A common example of a 

building with such an affected area is one in which 

the unbraced cripple wall collapsed, without the loss 

of load-bearing capacity supporting a ceiling or roof 

above an occupied space (fig. 6A). The median affected 

area (the value with 50 percent probability of being 

exceeded) was between 6 percent and 10 percent of 

building area, commonly the collapse of a chimney or 

porch roof (for example, fig. 6B). The distribution of 

affected area in wood frame collapses is likely biased 

high. The reason for this is that the collapse of brick 

chimneys was likely too widespread and too uninteresting for NISEE e-library contributors to photograph 

instances in proportion to their actual occurrence 

within the population of wood frame buildings with 

collapse.

0.25

0.50

0.75

1.00

0.00 0.25 0.50 0.75 1.00

Cumulative probability

Affected area

P[X≤x] = x0.32

0.25

0.50

0.75

1.00

0.00 0.25 0.50 0.75 1.00

Cumulative probability

Affected area

P[X≤x] = 1 – f e -Lx

f = 0.922

L = 4.52

B

A ×

Figure 3. Graphs showing approximate parametric forms of the 

cumulative distribution function for affected area of all building 

types—A, frequency-and-exponential-severity; B, a simpler 

expression similar to a power law. The axis of affected area spans 

from 0.00 (no area affected) to 1.00 (100 percent of area affected).
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 111

• Although the database includes instances of complete 

collapses of URM buildings, most URM collapses 

affect less than 18 percent of floor area. The modal 

affected area is between 18 and 32 percent of the building area, such as the collapse of brick parapets on the 

sidewalk, parking areas, and lower buildings adjacent 

to the URM building. That is, the URM collapses 

sampled here are commonly more dangerous to neighbors and passersby than to occupants. See figure 7 for 

representative examples. 

• In the case of pre-1971 tilt-up construction examined 

here, most collapses affected less than 18 percent 

of the building area. The modal affected area was 

between 10 and 18 percent of the building area, almost 

always just inside the building perimeter where roofto-wall connection fractures occurred. The interior 

gravity system kept supporting interior subdiaphragms 

(away from the edge) even after perimeter subdiaphragms collapsed. See figure 8 for an example.

• Complete collapses of concrete buildings in California 

have occurred, but they are the exception rather than 

the rule. In most cases, less than 50 percent of the 

floor area is affected. The modal affected area on this 

1⁄4-log-increment scale was between 32 and 56 percent 

of building area. An example of such a modal collapse 

was that of a partial collapse of a parking structure, 

shown in figure 9. No obvious spatial pattern of collapse was observed in these images.

Methodology for Estimating the Number of 

People Trapped in Elevators

It is reasonable to assume that electric power will go 

out across the bay area as soon as substation equipment and 

perhaps buildings in the area near the earthquake’s epicenter 

are damaged. Hence, the vast majority of elevators in the bay 

area will lose power before P-waves trigger seismic switches 

or ring-on-a-string devices. How many people will be in 

elevators with doors closed and traveling between floors when 

power goes out? I take the number of elevators in a metropolitan area Vm as:

 , (7)

where Pm is the population of the metropolitan area, and p is 

the average number of people per elevator, which as noted 

earlier is approximately 344 in the United States. Let Vo of (t) 

denote the number of elevators in motion with people inside 

and no emergency power at time t, and I estimate it as shown 

in equation 8:

 , (8)

where f

b

 denotes the fraction of elevators with emergency 

power, f

o

(t) is the estimated fraction of all elevators that are in 

use at time t, and f

c

 is the fraction of the time that an elevator 

in use with passengers in it is traveling between floors with 

the doors closed, which as noted earlier is on the order of 30 

percent of the time. If the average elevator with passengers has 

d passengers (as previously noted, d≈5), then the number of 

people that will be trapped in elevators Ne can be estimated as 

shown in equation 9:

 . (9)

Application to HayWired Scenario

People Trapped in Collapsed Buildings, Based 

on the Building-Code Objectives

I now turn to the question of urban search and rescue 

needs in the HayWired earthquake scenario. The HayWired 

scenario uses two approaches to estimate building 

damage—(1) based on building-code objectives (the 

Safe Enough approach documented in Porter [2015] and 

Porter [Not Safe Enough, this volume]) and (2) based on a 

combination of empirical observations, structural analysis, 

and engineering judgment, as encoded in the Hazus-MH 

model. FEMA performed a Hazus-MH analysis for the 

y = 0.06x −102

R2 = 0.0006

0

25

50

75

100

1960 1970 1980 1990 2000 2010 2020

Affected area, in percent

Earthquake year

Figure 4. Graph showing affected area of all types of buildings 

versus year of earthquake, 1965–2014.

Vm = Pm

p

Vo (t) =Vm × fo (t)× fc × 1− f ( b )

Ne =Vo (t)× d

= Pm

p × fo (t)× fc × 1− f ( b )× d
112 The HayWired Earthquake Scenario—Engineering Implications

0.00

0.10

0.20

0.30

0.40

0.50

Probability

Affected area, in percent

Reinforced-concrete buildings A

B

C

D

0.00

0.10

0.20

0.30

0.40

0.50

Probability

Affected area, in percent

Tilt-up buildings

0.00

0.10

0.20

0.30

0.40

0.50

Probability

Affected area, in percent

Unreinforced-masonry buildings

0.00

0.10

0.20

0.30

0.40

0.50

Probability

Affected area, in percent

Wood buildings

0 1 2 3 6 10 18 32 56 100

0 1 2 3 6 10 18 32 56 100

0 1 2 3 6 10 18 32 56 100

0 1 2 3 6 10 18 32 56 100

Figure 5. Graphs showing distribution of affected area by 

structural material: A, reinforced-concrete buildings except tilt-up; 

B, tilt-up concrete buildings; C, unreinforced-masonry buildings; 

and D, wood buildings.

mainshock (Doug Bausch, written commun., Federal 

Emergency Management Agency, 2014), and Seligson and 

others (this volume) performed the Hazus-MH analysis for 

selected aftershocks. 

Using the Safe Enough approach, I estimated the number of collapsed buildings in the HayWired mainshock to be 

Nb=7,800—if all buildings were to perform as well as modern 

(code-compliant) buildings—as estimated by a recent FEMA 

study (Applied Technology Council, 2009).

California is home to 38 million people and approximately 

11 million buildings, or approximately 3.5 people per building. If 

80 percent of people were indoors at the time of the earthquake 

(which seems realistic at 4:18 p.m. on a workday and consistent 

with Hazus-MH on an overall average basis), then there would 

be an average of about O(t)=2.8 occupants in each collapsed 

building at 4:18 p.m. As previously observed, the overall average 

fraction of building area that experiences collapse can be taken as 

A≈0.25. The overall average fraction of occupants in the collapsed 

area requiring USAR extrication can be taken as E≈0.66. Thus, if 

all buildings in the bay area just met current code requirements, 

equation 3 can estimate the number of people trapped in collapsed 

buildings:

 

. (10) 

That is, by the approach that uses building-code objectives, I 

estimate 3,600 people trapped in 7,800 collapsed buildings; 

however, many buildings with collapse would not have people 

trapped in them requiring USAR assistance. 

People Trapped in Collapsed Buildings, Based 

on Hazus-MH

Hazus-MH does not estimate the number of people 

trapped in collapsed buildings, but it does estimate the number of buildings in the complete structural damage state and 

the fraction of their area that experiences collapse, the product of which I can take as Nb

×A. Applying the values of E, 

estimated here by structural material, and applying a uniform 

occupant load of 2.8 occupants per collapsed building, I can 

estimate:

 , (11)

where i is an index for the structural materials, Nb,i×Ai is taken 

as the product of Hazus-MH’s estimated number of buildings 

in the complete damage state and its estimate of the fraction 

of that building area that collapses, and Ei is the fraction of 

Nc (t) = Nb ×O(t)× A× E

= 7,800 buildings× 2.8 people

building × 0.25× 0.66

= 3,600 people

Nc (t) = O(t)× ((Nb,i × Ai)× Ei) ∑i
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 113

A

B

Figure 6. Photographs of homes damaged in earthquakes. A, An example of the modal affected area (0 percent) of a 

collapsed wood frame building—in the moment-magnitude-6.4 1979 Imperial Valley, California, earthquake. B, An example of 

the median affected area (6–10 percent)—collapse of a porch roof in the moment-magnitude-6.6 1971 San Fernando Valley, 

California, earthquake. (Photographs by M. Hopper, and V. Bertero, respectively, courtesy of the National Information Service 

for Earthquake Engineering, PEER-NISEE, University of California, Berkeley.) 
114 The HayWired Earthquake Scenario—Engineering Implications

A

B

Figure 7. Photographs of examples of modal (A) and median (B) affected areas in unreinforced masonry (URM) buildings. A, Brick 

building damage in the moment-magnitude 6.9 1989 Loma Prieta, California, earthquake; B, store front collapsed in the momentmagnitude-6.6 1971 San Fernando Valley, California, earthquake. (Photographs by J. Blacklock and E. Schader, respectively, courtesy of 

the National Information Service for Earthquake Engineering, PEER-NISEE, University of California, Berkeley).
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 115

Figure 8. Photograph of an example of both modal and median collapse of tilt-up construction. damage was caused 

in the moment-magnitude-6.6 1971 San Fernando Valley, California, earthquake (Photograph by V. Bertero, courtesy of 

the National Information Service for Earthquake Engineering, PEER-NISEE, University of California, Berkeley.)

Figure 9. Photograph of an example of a partly collapsed reinforced-concrete structure, a parking garage at California 

State University, Northridge, damaged in the moment-magnitude-6.7 Northridge earthquake. (Photograph by P. Weigand, 

courtesy of the National Information Service for Earthquake Engineering, PEER-NISEE, University of California, Berkeley.)
116 The HayWired Earthquake Scenario—Engineering Implications

occupants requiring extrication for structural material i, from 

table 2. See table 4 for results.

How many buildings would Hazus-MH estimate had 

collapsed? Hazus-MH does not provide that estimate, but I can 

infer:

 , (12)

where Mcompl,i denotes Hazus-MH’s estimate of the number 

of buildings of structural material i in the complete structural 

damage state (column 2 in table 4); f

coll|compl,i

 denotes the fraction of area collapsed, given that it is in the complete damage 

state (column 3 in table 4); Ai is the fraction of building area 

that collapses (from table 2); and i is an index for structural 

material. See table 5 for results.

Thus, one can infer from the combination of Hazus-MH’s 

damage estimates and the observations of collapsed buildings 

made here that the HayWired mainshock would trap approximately 1,100 people in 2,100 collapsed buildings. 

Scenario Estimate of People Trapped in 

Collapsed Buildings

Using Hazus-MH damage estimates for the HayWired 

scenario mainshock, 1,100 people will be trapped in 2,100 collapsed buildings, whereas by the Safe Enough approach, 3,600 

people will be trapped in 7,800 collapsed buildings. That the 

two approaches differ by a factor of 3 essentially means that 

they agree within a half order of magnitude, which in the present state of loss modeling represents reasonable agreement.

However, the agreement is actually poorer than that, 

because the Safe Enough figures represent the expected 

behavior of post-1980 construction, and the Hazus-MH 

estimates are of the existing building stock, of which 60 to 

70 percent predates 1980. One would expect the Safe Enough 

estimates to be less than those of Hazus-MH, if both were 

correct; they use the same inventory of buildings. However, 

I use their estimates as benchmarks, their range representing 

two approaches to a realistic answer, and their medians, 2,500 

people trapped in 5,000 collapsed buildings (in round numbers), as realistic estimates for the HayWired scenario.

Number of People Trapped in Stalled Elevators

I turn now to the question of people trapped in elevators. 

In a large bay area earthquake, power would be lost immediately throughout the bay area and return slowly as power 

plants are inspected, load is carefully restored, and damage is 

repaired. When power is lost, most elevators in the bay area 

(those that do not have emergency power) would stop, even 

before P-waves reached the elevators and triggered their ringand-string safety devices. What would be the USAR impacts 

of that loss of power to elevators? How many people would be 

trapped in elevators with their doors closed, traveling between 

floors?

Considering a San Francisco Bay area population of 10 

million and using the previously observed average of one 

elevator per 344 people, one can use equation 7 to estimate the 

number of elevators in the San Francisco Bay area (Vm):

. (13)

Subtracting 60 percent of the estimated 3,700 elevators in 

bay area high-rise buildings that have emergency power, and 

2.5 percent of the remaining elevators and low- and mid-rise 

buildings with emergency power, an estimated 25,300 elevators in the bay area lack emergency power—I estimate 25,000 

in round numbers. Recall the fraction of the time that an elevator that is in use with passengers in it is traveling between 

floors with the doors closed is f

c

≈0.3. I assume that at peak 

Material Number of buildings in complete structural damage state

Fraction of building area collapsed, given complete damage E O(t) Nc

Wood 4,946 0.03 0.66 2.8 274

Steel 1,595 0.05 0.66 2.8 147

Concrete 1,241 0.10 0.94 2.8 327

Precast 71 0.15 0.10 2.8 3

Reinforced masonry 725 0.10 0.66 2.8 134

Unreinforced masonry 639 0.15 0.98 2.8 263

Manufactured housing 4,340 0.03 0 2.8 0

Total 1,148

Table 4. Number of people trapped in collapsed buildings, using Hazus-MH (Federal Emergency Management Agency, 2012) building 

damage estimates by Seligson and others (this volume) for the moment-magnitude-7 mainshock of the HayWired earthquake scenario.

[E, fraction of occupants in collapsed portion of buildings requiring extrication; O(t), number of building occupants per collapsed building on a Thursday at 4:18 

p.m.; Nc, number of people in collapsed buildings requiring extrication]

Mc = Mcompl,i × fcoll|compl,i

i Ai

∑

Vm = Pm

p

= 10,000,000 people

344 people

elevators

= 29,000 elevators
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 117

hours (and 4:18 p.m. on a weekday is likely a peak hour), most 

elevators are in use and most are carrying passengers primarily 

in one direction, so I assume f

o

(t)≈0.6. Then by equation 8, the 

number of elevators stalled with people inside at the time of 

the HayWired mainshock can be estimated as:

. (14)

And as previously noted, the average elevator carries d=5 

people when occupied, so one can use equation 9 to estimate 

Ne, the number of occupants trapped in elevators by the HayWired mainshock: 

 

. (15)

So it seems realistic that on the order of 22,500 people 

could be trapped in 4,500 elevators by the sudden loss of 

electric power after the HayWired mainshock, requiring fire 

department assistance to escape. Untrained first responders 

will be unable to assist the people trapped in elevators because 

technical skills and equipment are required to extricate people 

from elevators. 

It is possible to retrofit some existing elevators with 

emergency power to reduce the demand for elevator rescue. 

Kornfield (San Francisco Department of Building Inspection, 

retired, written commun., 2015) estimates the cost of retrofitting elevators to be on the order of $20,000 per elevator, and 

only 30 to 40 percent of elevators in the bay area could be retrofitted, so retrofit could reduce elevator entrapment to 14,000 

people in 3,000 stalled elevators.

Conclusions

USAR Demands Under Current Conditions

There are currently no public models of urban search and 

rescue demands after earthquakes. Although engineers can 

estimate the number of buildings that collapse in an earthquake, we do not know what fraction of building area experiences collapse when at least some collapse occurs, nor do 

we know what fraction of occupants in those collapsed areas 

require extrication by urban search and rescue personnel.

To estimate the search-and-rescue demands after the HayWired earthquake scenario mainshock, I compiled a photographic database of 72 buildings known to have experienced at 

least some collapse (structural or nonstructural) in 10 California earthquakes in the last 50 years. These include all buildings with images in the NISEE e-library whose description 

includes the word “collapse,” “fail,” “fell,” or “parapet,” plus 

12 tilt-up buildings with roof collapse documented in a NOAA 

report on the 1971 San Fernando earthquake and one collapse 

from the 2014 South Napa earthquake. Slightly more than half 

of these were wood frame buildings, 13 were unreinforced 

masonry, and 9 were of reinforced concrete. I found that on 

average, about 25 percent of the total square footage collapses, 

given that at least some collapse occurs. The fraction varies by 

structural material, from about 17 percent (tilt-up concrete and 

wood) to about 50 percent (cast-in-place reinforced concrete). 

I also estimated the fraction of occupants in the collapsed area 

who would require USAR assistance by various levels of technical expertise, based on CERT training guidelines. Applying 

the observations from these historical California building 

collapses, I estimated that on the order of 2,400 people could 

realistically require extrication from approximately 5,000 

collapsed buildings. Older buildings are generally more likely 

Material

Number in complete 

structural damage 

state

Fraction of area 

collapsed, given 

complete damage

Fraction of area collapsed in collapsed 

buildings

Collapsed 

buildings

Wood 4,946 0.03 0.17 873

Steel 1,595 0.05 0.23 347

Concrete 1,241 0.10 0.50 248

Precast 71 0.15 0.17 63

Reinforced masonry 725 0.10 0.28 259

Unreinforced masonry 639 0.15 0.28 342

Manufactured housing 4,340 0.03 0.00

Total 2,132

Table 5. Number of collapsed buildings, using Hazus-MH (Federal Emergency Management Agency, 2012) 

building damage estimates by Seligson and others (this volume) for the moment-magnitude-7 mainshock of the 

HayWired earthquake scenario.

V0 (t) =Vm × fo (t)× fc × 1− f ( b )

= 25,000× 0.6× 0.3

= 4,500 elevators

Ne =Vo (t)× d

= 4,500 elevators× 5 occupants

elevator

= 22,500 occupants
118 The HayWired Earthquake Scenario—Engineering Implications

to collapse, so the trapped population will tend to be in older 

buildings.

There is no public model of USAR demands resulting from power loss to elevators. However, using relevant 

estimates of the total number of elevators nationwide and local 

experts’ observations that few San Francisco Bay area elevators have emergency power, I estimated that on the order of 

22,500 people would be trapped in 4,500 stalled elevators.

USAR Demands Under Ideal-World Conditions

In Porter (Societal Consequences, this volume), I estimated that the number of collapsed buildings in the HayWired 

mainshock could be reduced by a factor of four if all buildings 

were designed with an earthquake importance factor of I=1.5 

(as defined in American Society of Civil Engineers, 2010). 

Doing so would reduce the number of people trapped in collapsed buildings proportionately, from 2,500 people trapped 

in 5,000 collapsed buildings to perhaps 600 people trapped 

in 1,200 collapsed buildings. Retrofit of newer elevators with 

emergency power could reduce elevator entrapment to 14,000 

people in 3,000 stalled elevators.

Limitations

Other buildings have collapsed in California earthquakes over the last 50 years that do not appear in the NISEE 

e-library or the other sources examined here. The distribution 

of affected area in these images may be biased relative to the 

distribution of affected area in the population of collapsed 

buildings, for example, if photographers who contributed to 

the NISEE e-library preferred to photograph buildings with 

more or less affected area than they would have done if they 

selected collapsed buildings at random to photograph. Absent 

a big California earthquake in which one can deliberately 

select collapsed buildings to examine in an unbiased way, I do 

not know how to test whether the photographers introduced 

bias in this way. However, the presence of numerous buildings 

with affected areas across the entire possible range of 0 to 100 

percent shows that the observations are at least diverse, even if 

their representativeness cannot be known without more data. I 

find the database sufficiently useful for estimating the distribution of affected area, at least until better data—more definitely 

representative—come along. Some readers may object that 

the buildings shown here do not represent an exhaustive list of 

collapsed California buildings, but few surveys are exhaustive. 

Samples commonly provide useful statistical information.

Acknowledgments

Sarah Durphy (Estructure), Craig Stevenson (Aurecon), 

Lawrence Kornfield (San Francisco Department of Building 

Inspection, retired), John Osteraas (Exponent Failure Analysis 

Associates), Marko Schotanus (Rutherford and Chekene), 

George von Klan (GVK-ECS, Inc.), and Anne Wein (U.S. 

Geological Survey) reviewed the draft report and offered valuable comments and recommendations. The author thanks them 

for their contributions.

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120 The HayWired Earthquake Scenario—Engineering Implications

Appendixes 1 through 12—National Information Service for Earthquake 

Engineering e-Library Images of Building Collapse in California, 1965–2014

These appendixes present images of building collapse caused by earthquakes in California in the past 50 years. The appendixes are organized by earthquake in chronological order, beginning with the Borrego Mountain earthquake of 1968 (a list of 

earthquakes with no available images, such as Borrego Mountain, is in appendix 12). Within each section, collapses are documented with their descriptions and other metadata, followed by the author’s estimate of the affected area, and then images of the 

collapse. Unless noted otherwise, metadata and images are from collections in the National Information Service for Earthquake 

Engineering (NISEE) e-library. Permission for their use is granted at http://nisee.berkeley.edu/elibrary/about.html. Note that 

earthquake magnitudes may not exactly match final moment magnitudes determined by the U.S. Geological Survey. Because of 

the large number of images, figures are numbered by appendix.

[Abbreviations used in the appendixes—ft, feet; ft2, square feet; in., inch; %, percent, Calif., California; St., Street, Ave., Avenue; 

Rd., Road. --, no data]

Appendix 1. Santa Rosa (1969) Collapse Images

Image Metadata and Description for Figure 1–1

Karl V. Steinbrugge Collection: S3715

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 1, 1969; 

M5.59

Damage to wood 

frame house in 

the fault zone

Steinbrugge, 

Karl V.

October 6, 1969 North America/ Sonoma 

County/ United States/ 

Santa Rosa/ California

Two-story wood frame building 

off foundations. Foundations 

were rotted and poorly braced. 

Gas lines ruptured when house 

fell. 718 Beaver St., Santa Rosa, 

California.

Figure 1–1. Photograph showing 

two-story wood frame house that 

collapsed in the 1969 Santa Rosa, 

California, earthquake.

Author’s Estimate of Affected Area

0%
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 121

Image Metadata and Description for Figure 1–2

Karl V. Steinbrugge Collection: S3726

Author’s Estimate of Area

Plan area≈13,000 ft2×3 stories. Area littered by bricks≈25 ft×15 ft=1% of 39,000 ft2.

Earthquake date and 

magnitude (M) Title Creator Date Location Description

October 1, 1969; 

M5.59

Damage to wood 

frame house in 

the fault zone

Steinbrugge, Karl V. October 6, 1969 North America/ 

Sonoma 

County/ United 

States/ Santa 

Rosa/ California

Two-story wood frame 

building off foundations. 

Foundations were rotted 

and poorly braced. Gas lines 

ruptured when house fell. 

718 Beaver St., Santa Rosa, 

California.

Figure 1–2. Photograph showing part of a wall 

that collapsed onto a car in the 1969 Santa Rosa, 

California, earthquake. 
122 The HayWired Earthquake Scenario—Engineering Implications

Appendix 2. San Fernando (1971) Collapse Images

Image Metadata and Description for Figure 2–1

Karl V. Steinbrugge Collection: S4473

Author’s Estimate of Affected Area

Approximately (120 ft2 porch)/(1,500 ft2 house)=8.0%.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Damage to wood 

frame house in 

the fault zone

Steinbrugge, 

Karl V.

February 16, 1971 North America/ Los 

Angeles County/ 

United States/ 

San Fernando/ 

California

Damage to porches (probable cripple 

wall failure); chimney fell away 

from house. In the vicinity of Knox 

and Orange Grove Streets, in the 

fault zone.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Chimney damage Schader, Eugene E.-- North America/ Los 

Angeles County/ 

United States/California

Chimney fell towards otherwise undamaged wood frame house.

Figure 2–1. Photograph showing 

damage to a wood frame house after 

the 1971 San Fernando, California, 

earthquake.

Image Metadata and Description for Figure 2–2

Karl V. Steinbrugge Collection: S4533

Author’s Estimate of Affected Area

0%
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 123

Image Metadata and Description for Figure 2–3

Karl V. Steinbrugge Collection: S4581

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Furniture store Schader, 

Eugene E.

February 16, 1971 United States/ 

San Fernando/

California/North 

America/ Los 

Angeles County

Furniture store. Unreinforced masonry 

parapet has collapsed, dumping bricks 

into the street and on to the sidewalk. 

Large plate-glass windows are gone, 

presumably shattered by the earthquake. 

San Fernando, California.

Figure 2–2. Photograph showing 

chimney damage after the 1971 San 

Fernando, California, earthquake.

Author’s Estimate of Affected Area

Plan area≈40 ft×60 ft (?); area littered by bricks≈30 ft×15 ft=19%.

Figure 2–3. Photograph showing 

furniture store damage after the 1971 

San Fernando, California, earthquake.
124 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 2–4

Karl V. Steinbrugge Collection: S4597, S4598, S4599, S4600, S4601, S4602.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Apartments 

over retail 

space

Steinbrugge, 

Karl V.

-- United States/

San Fernando/ 

California/North 

America/ Los 

Angeles County

Apartments over retail space. Note that the 

failure of the nonreinforced bearing walls 

did not result in collapse. Unit masonry 

construction, built prior to 1933. Downtown San Fernando commercial area.

Author’s Estimate of Affected Area

Plan area: 50 ft×75 ft×3 stories; masonry littering 250 ft (?)×15 ft (?)=3%.

Figure 2–4. Photographs (A–F) showing damage to apartments over retail space after the 1971 San Fernando, California, earthquake.

A

C

E

B

D

F
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 125

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Roof to the 

wall failed 

first

Steinbrugge, 

Karl V.

February 18, 1971 North America/ Los 

Angeles County/ 

United States/ Los 

Angeles/California

Roof to the wall failed first. Ground cracks 

in the vicinity. Rear wall bulged out and 

rear roof fell. See S4625–4633. Light 

industrial buildings. Bradley Tract.

Image Metadata and Description for Figure 2–5

Karl V. Steinbrugge Collection: S4624, S4625, S4626, S4628, S4629, S4630, S4631, and S4633

Author’s Estimate of Affected Area

No long shots show the length of any wall, address, or way to estimate overall size of the building. Benfer and Coffman 

(1973, p. 123) show 14 tilt-up buildings in the Bradley Tract with this kind of failure, including the one pictured in S4624. Steinbrugge’s photos seem to show a building on the north side of an east-west street, with failure on along the entire north wall and 

on the southwest bay. That only matches one building: 12884 Bradley Avenue, 131.5 ft wide (east-west) and 276 ft north-south, 

for a total floor area of 36,294 ft2. Collapses appear to cover 26 ft×26 ft on the southwest corner and 26 ft×131 ft on the north 

wall. I estimate 26-ft bays because the panels look approximately square and 131 ft equals 5 bays plus two 6-inch panel thicknesses. Affected area: (6×26 ft×26 ft)/(36,294 ft)=11%. Other tilt-ups in the Bradley Tract: I extracted the map of tilt-up damage 

from Benfer and Coffman (1973, p. 123) and overlaid it in Google Earth Pro, measuring the collapsed area with Google Earth 

Pro’s ruler tool. Results are shown in table 2–1.

Address Collapsed area, in 

square feet

Plan area, in 

square feet

Affected area, in 

percent

12840 Bradley Avenue 21,461 48,400 44

12874 Bradley Avenue 2,460 21,000 12

12884 Bradley Avenue 4,056 36,294 11

12950 Bradley Avenue 3,060 30,240 10

12881 Bradley Avenue 5,678 58,500 10

12975 Bradley Avenue 18,180 77,600 23

13001 Bradley Avenue 6,400 85,050 8

13069 Bradley Avenue 7,030 45,000 16

15200 Bledsoe Street 3,700 19,800 19

15151 Bledsoe Street 4,050 51,800 8

12860 San Fernando Road 4,650 29,340 16

12806 San Fernando Road 11,260 63,400 18

12744 San Fernando Road 26,600 101,400 26

12814 Bradley Avenue 2,400 15,600 15

Table 2–1. Collapsed tilt-up roofs in Bradley Tract, Los Angeles, after the 1971 San Fernando, 

California, earthquake.
126 An Earthquake Urban Search and Rescue Model for Earthquake Response and Application to the HayWired Scenario

A

C

G H

D E F

B

Figure 2–5. Photographs (A–H) 

showing damage to industrial 

buildings in the Bradley Tract, 

Los Angeles, after the 1971 San 

Fernando, California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 127

Image Metadata and Description for Figure 2–6

Karl V. Steinbrugge Collection: S4489

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Older wood 

frame house

Steinbrugge, 

Karl V.

1971 United States/ San Fernando/California/North 

America/ Los Angeles 

County

Porch partial collapse on older wood 

frame house, probable cripple wall failure of house. Between Glen Oaks and 

Hubbard Streets.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Soft-story 

failure

Steinbrugge, 

Karl V.

-- United States/ San Fernando/ California/North 

America/ Los Angeles 

County

Pink structure at the rear was a residence 

over a garage. The first story collapsed, 

note remains of automobile under the 

building.

Author’s Estimate of Affected Area

Plan area≈1,500 ft2 (?); collapsed area where people could be trapped=0%.

Figure 2–6. Photograph showing the partial collapse of a porch on older wood frame house, with probable 

cripple wall failure.

Image Metadata and Description for Figure 2–7

Karl V. Steinbrugge Collection: S4491, S4492

Author’s Estimate of Affected Area

Building area=30 ft×20 ft (?)×2; collapsed area=30 ft×20 ft (?)×1=50%.
128 The HayWired Earthquake Scenario—Engineering Implications

Figure 2–7. Photographs (A, B) showing soft-story failure after the 1971 San Fernando, California, earthquake.

A

B
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 129

Image Metadata and Description for Figure 2–8

William G. Godden (v. 4) Collection: GoddenJ53

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Split-level 

house, San 

Fernando 

Valley

Bertero, Vitelmo V.-- United States/California/ 

North America

Collapse of a split-level wooden home. Large 

numbers of these split-level homes suffered significant damage because of a lack 

of adequate ties between the two levels. 

The upper level ripped away and crushed 

the lower garage walls, which did not have 

adequate lateral bracing.1

1

Additional discussion of this image is available in Godden Set J.

Author’s Estimate of Affected Area

Building area≈15 ft×30 ft×3; collapsed area≈15 ft×30 ft×1=33%.

Figure 2–8. Photograph showing damage to a split-level house after the 1971 San Fernando, California, earthquake.

Image Metadata and Description for Figure 2–9

Karl V. Steinbrugge Collection: S4195

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Severe damage 

to masonry 

building 

Bertero, Vitelmo V.February 

1971

United States/ Los Angeles/ California/ North 

America/ Los Angeles 

County

Collapsed semi-ambulent building, built in 

1925, masonry construction. Structure: Veterans Administration Hospital 

(Sylmar).
130 The HayWired Earthquake Scenario—Engineering Implications

Author’s Estimate of Affected Area

Collapsed area: from this photo, it looks as if the lower story collapsed, so 50%.

Figure 2–9. Photograph showing severe damage 

to masonry building at the Veterans Administration 

Hospital (Sylmar) after the 1971 San Fernando, 

California, earthquake.

Image Data and Description for Figure 2–10

The 1971 San Fernando earthquake (magnitude 6.7) collapsed four buildings at the San Fernando Veterans Administration 

Hospital complex, killing 47 people. The buildings had been built in 1925, before modern building codes were in effect. Image 

and description are from Celebi and Page (2005). 

Author’s Estimate of Affected Area

The view is from the west. The semi-ambulent building was a long building oriented east to west, the second building 

from the south (that is, second from right), in the middle of the photo. Portions of the building are leaning at various angles to 

the north. The wing is a complete loss, but it appears as if it did not pancake. The estimate of 50% from NISEE S4195 seems 

reasonable.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 131

Figure 2–10. Photograph showing four collapsed buildings at the San Fernando Veterans Administration Hospital complex in the 1971 

San Fernando, California, earthquake (from Celebi and Page, 2005).

Image Metadata and Description for Figure 2–11

Karl V. Steinbrugge Collection: S4529

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Damage to 

older dwellings

Olson, Robert A.-- United States/ California/ 

North America/ Los 

Angeles County

Damage to older house caused by cripple 

wall collapse.

Author’s Estimate of Affected Area

Although the cripple wall collapsed, the living space does not appear to have experienced any drop in a roof or ceiling relative to the floor, so 0%.
132 The HayWired Earthquake Scenario—Engineering Implications

Figure 2–11. Photograph showing damage to older dwelling after the 1971 San Fernando, California, earthquake.

Image Metadata and Description for Figure 2–12

Karl V. Steinbrugge collection: S4065

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Collapsed 

tower at 

southeast 

corner

Steinbrugge, 

Karl V.

-- United States/ Sylmar/ 

California/North 

America/ Los Angeles 

County

Collapsed tower at southeast corner. Olive 

View Hospital. Rear (east) elevation of 

Medical Treatment Building. Structure: 

Olive View Medical Treatment Building.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 133

Figure 2–12. Photograph showing collapsed 

tower at Olive View Hospital, Sylmar, after the 

1971 San Fernando, California, earthquake.

Image Data and Description for Figure 2–13

San Fernando earthquake, February 1971, California. Fallen, structurally separated stair tower and leaning north stair tower 

(left) at Olive View Hospital. Emergency vehicles are visible in the foreground. View is from the west. Image taken by Reuben 

Kachadoorian, U.S. Geological Survey.

Author’s Estimate of Affected Area

Each wing appears to be approximately 240 ft×50 ft×5 stories×4 wings=240,000 ft2. The collapsed stair towers appear to be 

approximately 20 ft×40 ft×5 stories×2 towers=8,000 ft2, or 3.3%.
134 The HayWired Earthquake Scenario—Engineering Implications

Figure 2–13. Photograph showing collapsed and leaning stair towers at Olive View Hospital, Sylmar, after the 1971 San Fernando, 

California, earthquake.

Image Metadata and Description for Figure 2–14

Karl V. Steinbrugge Collection: S4070

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Ambulance 

garage collapsed

Steinbrugge, 

Karl V.

-- United States/ Sylmar/ 

California/ North 

America/ Los Angeles 

County

Ambulance garage collapsed. Olive View 

Hospital. Southern elevation of Medical 

Treatment Building. See also S4139–44. 

Structure: Olive View ambulance 

garage.

Author’s Estimate of Affected Area

By inspection (an engineering term meaning “just by looking at it”), 100%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 135

Image Metadata and Description for Figure 2–15

Karl V. Steinbrugge Collection: S4115

Earthquake date 

and magnitude (M) Title Creator Location Description Description

February 9, 1971; 

M6.6

Olive View 

psychiatric 

building

Steinbrugge, 

Karl V.

United States/ 

Sylmar/ California/ North 

America/ 

Los Angeles 

County

Soft-story collapse, most evident at upper right of photo. 

Originally a one- and two-story 

building, irregular in plan, the 

first story collapsed in the earthquake. Structure: Olive View 

Medical Center, Calif.

Ambulance garage collapsed. 

Olive View Hospital. Southern elevation of Medical 

Treatment Building. See also 

S4139–44. Structure: Olive 

View ambulance garage.

Figure 2–14. Photograph showing a collapsed ambulance garage at Olive View Hospital, Sylmar, after the 1971 San Fernando, 

California, earthquake. 

Author’s Estimate of Affected Area

Collapsed area: it appears as if the first story was about twice the area of the second, and all of the area of the first story has 

collapsed, so 67%.
136 The HayWired Earthquake Scenario—Engineering Implications

Figure 2–15. Photograph showing soft-story collapse of psychiatric building at Olive View Hospital, Sylmar, after the 1971 San 

Fernando, California, earthquake.

Image Metadata and Description for Figure 2–16

Karl V. Steinbrugge collection: S4117

Earthquake date 

and magnitude (M) Title Creator Location Description Description

February 9, 1971; 

M6.6

Psychiatric 

building 

collapsed

Olson, Robert A.United States/ 

Sylmar/ California/ North 

America/ Los 

Angeles County

West elevation, psychiatric building. This was a two-story building—the first story collapsed. 

Olive View. Structure: Olive 

View Medical Center, Calif.

Ambulance garage collapsed. 

Olive View Hospital. Southern elevation of Medical 

Treatment Building. See also 

S4139–44. Structure: Olive 

View ambulance garage.

Author’s Estimate of Affected Area

This is another view of the previous building.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 137

Image Metadata and Description for Figure 2–17

Karl V. Steinbrugge Collection: S4519

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Collapsed 

wood frame 

house

Steinbrugge, 

Karl V.

February 16, 1971 United States/ Sylmar/ California/ North America/ Los 

Angeles County

Collapsed wood frame house 

under construction on Tucker 

St. near Pacoima Dam.

Figure 2–16. Photograph showing first story collapse of psychiatric building at Olive View Hospital, Sylmar, after the 1971 San 

Fernando, California, earthquake.

Author’s Estimate of Affected Area

There is no other view of this house. It looks as if the garage (front left) and perhaps half of the living space (in the rear) at 

least partly collapsed, so approximately 67%.
138 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 2–18

Karl V. Steinbrugge Collection: S4501

Figure 2–17. Photograph showing a collapsed wood frame house after the 1971 San Fernando, California, earthquake.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

Soft-story 

failure

Steinbrugge, 

Karl V.

1971 United States/ Sylmar/ California/North America/ Los 

Angeles County

Two-story section over garage of this wood 

frame house on Almetz St. has collapsed in 

the first story. In a new housing tract in Sylmar at base of hills and between Olive View 

and Veterans Administration Hospitals.

Author’s Estimate of Affected Area

There are no other views of this house. Judging by the description, this building resembled S4514 in layout, so approximately 33%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 139

Earthquake date 

and magnitude (M) Title Creator Date Location Description

February 9, 1971; 

M6.6

VA Hospital -- 1971 -- Veterans Administration Hospital (Sylmar). Old masonry 

building in upper center of photo has completely collapsed. Constructed in 1925–26, with major additions 

in 1938 and 1949, the entire complex was demolished 

after the 1971 earthquake, and the entire 97 acres were 

dedicated in 1977 as Veterans Memorial Park. Structure: 

Veterans Administration Hospital (Sylmar).

Image Metadata and Description for Figure 2–19

Robert A. Olson Collection: R0070

Figure 2–18. Photograph showing soft-story failure in a wood frame house after the 1971 San Fernando, California, earthquake.

Author’s Estimate of Affected Area

The collapsed building is the gray-roofed one, which appears to have been a one-story building whose entire area collapsed. 

100%.
140 The HayWired Earthquake Scenario—Engineering Implications

Figure 2–19. Photograph showing damage to the Veterans Administration Hospital, Sylmar, after the 1971 San Fernando, California, 

earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 141

Appendix 3. Imperial Valley (1979) Collapse Images

Image Metadata and Description for Figure 3–2

Karl V. Steinbrugge Collection: S5584

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 15, 1979; 

M7.0

Cripple wall 

collapse

Hopper, Margaret G.October 1979 United States/ California/ 

North America/ Imperial County

Cripple wall collapse—wood frame 

house on G St. 

Author’s Estimate of Affected Area

By inspection, 0%.

Figure 3–2. Photograph showing cripple wall collapse on a wood frame house after the 1979 Imperial Valley, California, earthquake.
142 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 3–3

Karl V. Steinbrugge Collection: S5585

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 15, 1979; 

M7.0

Cripple wall 

collapse

Hopper, Margaret G. October 1979 Brawley, Imperial County, 

Calif.

Cripple wall collapse—wood frame 

house on G St.

Author’s Estimate of Affected Area

By inspection, 0%.

Figure 3–3. Photograph showing cripple wall collapse on a wood frame house after the 1979 Imperial Valley, California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 143

Appendix 4. Westmorland (1981) Collapse Images

Image Metadata and Description for Figure 4–1

National Oceanic and Atmospheric Administration (n.d.)

Earthquake date 

and magnitude (M) Title Creator Date Location Description

April 26, 1981; 

M5.6 

Westmorland 1981 Olsen, Robert O. -- North America/ United 

States/ California

View of a two-story building which 

partly collapsed in the earthquake. 

Note the undamaged one story building on the left. Photo credit: California Governor’s Office of Emergency 

Services Earthquake Program.

Author’s Estimate of Affected Area

100%

Figure 4–1. View of a two-story building on West Main Street, Westmorland, after the April 26, 1981, Westmorland, California, 

earthquake.
144 The HayWired Earthquake Scenario—Engineering Implications

Appendix 5. Coalinga (1983) Collapse Images

Image Metadata and Description for Figure 5–1

William G. Godden (v. 4) Collection: GoddenJ19

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 2-story building, 

Coalinga

Bertero, Vitelmo V. -- North America/ United 

States/ California

This two-story wood frame dwelling 

underwent a lateral displacement of 

more than half a meter, as illustrated 

by the slant in the porch columns, 

and also fell more than half a meter 

from its foundation, owing to lack of 

adequate anchorage and support.

Author’s Estimate of Affected Area

0%

Figure 5–1. Photograph showing lateral displacement of two-story wood frame dwelling after the 1983 Coalinga, California, 

earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 145

Image Metadata and Description for Figure 5–2

William G. Godden (v. 4) collection: GoddenJ52

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 Chimney 

collapse, 

Coalinga

Bertero, Vitelmo V. -- United States/ Coalinga/ California/ 

North America/ 

Fresno County

Chimney collapse of a modern house, 

1983 Coalinga earthquake. Most 

of the chimneys were thrown down 

because of the lack of proper connections (straps) to the building.1

1

Additional discussion of this image is available in Godden Set J.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 Collapse of 

wooden porch, 

Coalinga

Bertero, Vitelmo V. -- United States/ 

California/ North 

America

Collapse of a wooden porch (owing to lack of 

proper anchorage to the wooden frame of the 

house and of a proper lateral-resistant supporting system) owing to vibratory response.1

1

Additional discussion of this image is available in Godden Set J.

Author’s Estimate of Affected Area

There are no other views of this building. Typical single-family dwelling is approximately 1,500 ft2, but this one looks a 

little larger, say 50% larger or 2,250 ft2. Bricks litter an area approximately 20 ft×10 ft=200 ft2, or 9%.

Figure 5–2. Photograph showing chimney collapse of a modern house after the 1983 Coalinga, California, earthquake.

Image Metadata and Description for Figure 5–3

William G. Godden (v. 4) Collection: GoddenJ23
146 The HayWired Earthquake Scenario—Engineering Implications

Author’s Estimate of Affected Area

There are no other views of this building. Typical single-family dwelling is approximately 1,500 ft2. This porch appears to 

have measured 12 ft×20 ft, so 200 ft2 / 1,500 ft2≈15%.

Figure 5–3. Photograph showing collapse of a wooden porch after the 1983 Coalinga, California, earthquake.

Image Metadata and Description for Figure 5–4

William G. Godden (v. 4) collection: GoddenJ29

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 Unreinforced 

brick building, 

Coalinga

Bertero, Vitelmo V. -- United States/ 

California/ North 

America

The second story, 8-in., unreinforced solid brick 

masonry walls of this commercial building 

in Coalinga collapsed, owing to inadequate 

tying at the floor, roof, and transverse walls.1

1

Additional discussion of this image is available in Godden Set J.

Author’s Estimate of Affected Area

There are no other views of this building. It looks as if about half of the upper story of a two-story building collapsed 

(25%), plus bricks litter the perimeter, so say 30%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 147

Image Metadata and Description for Figure 5–5

Robert A. Olson Collection: R0321

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 Heavy wooden 

overhang fell 

on sidewalk

-- -- -- Heavy wooden overhang fell from storefront 

on to the sidewalk. Damaged concrete block 

wall at the right.

Figure 5–4. Photograph showing collapse of an unreinforced brick building after the 1983 Coalinga, California, earthquake.

Author’s Estimate of Affected Area

No long shot to show how long the building is. No address. No estimate of affected area.
148 The HayWired Earthquake Scenario—Engineering Implications

Figure 5–5. Photograph showing a heavy wooden overhang fallen onto sidewalk in the 1983 Coalinga, California, earthquake.

Image Metadata and Description for Figure 5–6

Robert A. Olson Collection: R0323

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; 6.5 Porch pulled away 

from church 

building

-- -- -- Porch running the full width of the church simply 

pulled away from the rest of the building. Built in 

1946, the stabilized adobe building was heavily 

damaged, but did not collapse. On the corner of 

Jefferson St.

Author’s Estimate of Affected Area

There are no other views of this building. Guess building area≈30 ft×90 ft=2,700 ft2, guess porch measured 20 ft×10 ft=7%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 149

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 Veneer also fell 

into the first 

story

Steinbrugge, 

Karl V.

May 3, 1983 North America/ Fresno 

County/ United States/ 

Coalinga/ California

Veneer also fell into the first story. 

All reinforced brick buildings in 

the downtown Coalinga area were 

demolished. 

Figure 5–6. Photograph showing porch pulled away from church building after the 1983 Coalinga, California, earthquake.

Image Metadata and Description for Figure 5–7

Karl V. Steinbrugge Collection: S5765

Author’s Estimate of Affected Area

No long shots, no address, no estimate of affected area.
150 The HayWired Earthquake Scenario—Engineering Implications

Figure 5–7. Photograph showing veneer fallen into first story of downtown building after the 1983 Coalinga, California, earthquake.

Image Metadata and Description for Figure 5–8

Karl V. Steinbrugge Collection: S5773

Author’s Estimate of Affected Area

Building was at E. Durian Avenue and Coalinga Plaza, Coalinga, Calif. (https://www.masonryinstitute.org/pdf/909.pdf), 

possibly 286 Coalinga Plaza. No old satellite imagery. No estimate of plan area. No estimate of effected area.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

May 2, 1983; M6.5 Parapet damaged Steinbrugge, 

Karl V.

May 3, 1983 North America/ Fresno 

County/ United States/ 

Coalinga/ California

Parapet damage. All reinforced brick 

buildings in the downtown Coalinga 

area were demolished. See S5828–

5830 for "after" views.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 151

Figure 5–8. Photograph showing parapet damage to a building in downtown Coalinga after the 1983 Coalinga, California, earthquake. 
152 The HayWired Earthquake Scenario—Engineering Implications

Appendix 6. Morgan Hill (1984) Collapse Images

Image Metadata and Description for Figure 6–1

Karl V. Steinbrugge Collection: S5840

Earthquake date 

and magnitude (M) Title Creator Date Location Description

April 24, 1984; 

M6.19

Most severely 

damaged 

dwelling

Steinbrugge, 

Karl V.

April 28, 1984 United States/ Morgan 

Hill/ California/ North 

America/ Santa Clara 

County

Most severely damaged dwelling. 

Sheathing between first floor and 

foundation was fiberboard with little 

strength. Morgan Hill, California, 

Anderson Lake area.

Author’s Estimate of Affected Area

By inspection, 0%.

Figure 6–1. Photograph showing the most severely 

damaged dwelling in the 1984 Morgan Hill, California, 

earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 153

Earthquake date 

and magnitude (M) Title Creator Date Location Description

April 24, 1984; 

M6.19

Dwelling on the 

left moved owing to landslide

Steinbrugge, 

Karl V.

April 28, 1984 Morgan Hill/ California/ 

North America/ Santa Clara 

County/ United States

Dwelling on the left moved, 

owing to landsliding from the 

earthquake. Morgan Hill, California. Anderson Lake area.

Image Metadata and Description for Figure 6–2

Karl V. Steinbrugge Collection: S5839 and Federal Emergency Management Agency (2002).

Author’s Estimate of Affected Area

The right-hand image is from the FEMA National Earthquake Technical Assistance Training Program training slideset, 

entitled “Postearthquake Safety Evaluation of Buildings” (Federal Emergency Management Agency, 2002). Plan area from top 

to bottom floors appear to be 2:2:1. The bottom floor experienced some collapse, so say 20%.

A

B

Figure 6–2. Photographs (A, B) showing 

dwellings that have moved, owing to 

landslide in the 1984 Morgan Hill, California, 

earthquake.
154 The HayWired Earthquake Scenario—Engineering Implications

Appendix 7. Whittier Narrows (1987) Collapse Images

Image Metadata and Description for Figure 7–1

Karl V. Steinbrugge Collection: S6014

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 1, 1987; 

M6.0

Chimney collapsedSteinbrugge, 

Karl V.

October 3, 1987 United States/ Whittier/ California/North America/ Los 

Angeles County

Damage to roof from chimney collapsing. Whittier, 

California.

Author’s Estimate of Affected Area

By inspection, 0%.

Figure 7–1. Photograph showing damage 

to roof from collapsed chimney after the 1987 

Whittier Narrows, California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 155

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 1, 1987; 

M6.0

Chimney collapsedSteinbrugge, 

Karl V.

October 3, 1987 United States/ Whittier/ California/ North America/ Los 

Angeles County

Chimney collapsed away 

from the house. Whittier, 

California.

Image Metadata and Description for Figure 7–2

Karl V. Steinbrugge Collection: S6023

Author’s Estimate of Affected Area

There are no other views of this house in adjacent records, so assume typical area 1,500 ft2 and that bricks litter an area 

5 ft×10 ft=3%.

Figure 7–2. Photograph showing 

collapsed chimney in a house in Whittier 

after the 1987 Whittier Narrows, California, 

earthquake.
156 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 7–3

Karl V. Steinbrugge Collection: S6020

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 1, 1987; 

M6.0

Chimney damage Steinbrugge, 

Karl V.

October 3, 1987 United States/ Whittier/ California/ North America/ Los 

Angeles County

One chimney collapsed, but not 

the other. Whittier, California.

Author’s Estimate of Affected Area

House looks larger than typical: assume 3,000 ft2. Bricks litter an area 8 ft×8 ft=2%.

A B

Figure 7–3. Image showing collapsed chimney in the 1987 Whittier Narrows, California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 157

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 1, 1987; 

M6.0

Chimney damage Steinbrugge, 

Karl V.

October 3, 1987 United States/ Whittier/ California/ North America/ Los 

Angeles County

One chimney collapsed, but not 

the other. Whittier, California.

Image Metadata and Description for Figure 7–4

Karl V. Steinbrugge Collection: S6022

Author’s Estimate of Affected Area

Assume typical plan area for single-family dwelling of 1,500 ft2. Bricks litter an area approximately 5 ft×10 ft=3%.

Figure 7–4. Photograph showing chimney 

damage from the 1987 Whittier Narrows, 

California, earthquake. 
158 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 7–5

Karl V. Steinbrugge Collection: S6024

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 1, 1987; 

M6.0

May Company 

parking

Steinbrugge, 

Karl V.

October 3, 1987 North America/ Los Angeles 

County/ United States/ 

Whittier/ California

May Company parking structure. Roof failed; damage 

shown is from demolition. 

Whittier, California.

Author’s Estimate of Affected Area

No long shots. Google Earth imagery does not date back to 1987, so there is no way to estimate total area of lot. No estimate of affected area.

Figure 7–5. Photograph showing failure 

of parking structure roof after the 1987 

Whittier Narrows, California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 159

Appendix 8. Loma Prieta (1989) Collapse Images

Image Metadata and Description for Figure 8–1

Loma Prieta Blacklock Collection: LP0042

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Wall collapse in 

unreinforced 

masonry

Blacklock, 

James R.

1989 United States/ Santa Cruz/ 

California/ North America/ 

Santa Cruz County

Wall collapse in unreinforced 

masonry building. Santa Cruz, 

California.

Author’s Estimate of Affected Area

This is the historic Hihn Building, 1205 Pacific Avenue, Santa Cruz, California 95060. The parcel (APN 00507517000) 

covers 8,180 ft2 according to Google Earth. Another photograph with a wider field of vision shows that the building stood two 

stories tall in 1989 (Moore, 2014) Total building area=16,360 ft2. Bricks litter an area about 16 ft×12 ft, or 1%.

A

B

Figure 8–1. Photographs (A, B) showing wall collapse in an 

unreinforced masonry building after the 1989 Loma Prieta, 

California, earthquake.
160 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 8–2

Loma Prieta Blacklock Collection: LP0066

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Parapet and wall 

failures in bakery building

Blacklock, 

James R.

1989 North America/ Santa Cruz 

County/ United States/ 

Watsonville/ California

Parapet and wall failures in 

bakery building. Watsonville, 

California.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Failed parapets 

on Main Street

Blacklock, 

James R.

1989 North America/ Santa Cruz 

County/ United States/ 

Watsonville/ California

Older building with failed parapets on Main St. Watsonville, 

California.

Author’s Estimate of Affected Area

Location: 15 E. Beach Street (at Union Street), Watsonville, California. No long shot. No 1989 satellite imagery exists, so 

there is no estimate of shape or size of the damaged building. No estimate of affected area.

Figure 8–2. Photograph showing parapet and wall failures in Watsonville after the 1989 Loma Prieta, California, earthquake.

Image Metadata and Description for Figure 8–3

Loma Prieta Blacklock Collection: LP0070, LP0072, LP0073, and LP0074
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 161

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Failed brick 

parapet fell on 

sidewalk

Blacklock, 

James R.

1989 North America/ Santa Cruz 

County/ United States/ 

Watsonville/California

Damaged building near Main St. 

Failed brick parapet fell on 

sidewalk

Author’s Estimate of Affected Area

Two buildings are addressed here. The tall building labeled “Canada” on front and back appears to be 307 Main Street, 

Watsonville (see https://www.ngdc.noaa.gov/hazardimages/picture/show/259). According to Google Earth Pro, the lot at 307 

Main Street measures 30 ft×125 ft. The building (now removed) appears to fill the parcel, with a total building area of 7,500 ft2. 

Collapsed parapet and second story wall appears to litter an area about 90 ft long (counting collapsed portions of both long walls, 

on the north and south sides) and perhaps 15 ft wide, for total affected area=(90 ft×15 ft)/(7,500 ft2)=18%. The building with the 

collapsed parapet on its front facade appears to be located at what is now 311 Main Street, Watsonville, the middle one of three 

buildings on what is now one parcel. The center building appears to be about 65 ft wide, with the front 35 ft or so, occupying two 

stories and the back 90 ft a single story. Bricks litter the 65 ft length by 15 ft, for an affected area of (65 ft×15 ft)/(65 ft×125 ft + 

65 ft×35 ft)=9.4%.

A

C D

B

Figure 8–3. Photographs showing failed parapets in Watsonville after the 1989 Loma Prieta, California, earthquake. A, The building 

at the far left is 307 Main Street; the building in the foreground is 311 Main Street. B–D, Three views of the sides and rear of 307 Main 

Street.

Image Metadata and Description for Figure 8–4

Loma Prieta Blacklock Collection: LP0080
162 The HayWired Earthquake Scenario—Engineering Implications

Author’s Estimate of Affected Area

No address, no long shots. There is no way to tell how long this wall is or how deep the building is perpendicular to this 

wall. No estimate of affected area.

Figure 8–4. Photograph showing failed brick parapet fallen onto sidewalk in Watsonville after the 1989 Loma Prieta, California, 

earthquake.

Image Metadata and Description for Figure 8–5

Loma Prieta Blacklock Collection: LP0081–LP0085

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

St. Patrick's 

Church

Blacklock, 

James R.

1989 North America/ Santa Cruz 

County/ United States/ 

Watsonville/ California

Front view of damaged street. 

Patrick's Church. Watsonville, 

California.

Author’s Estimate of Affected Area

Littered area≈200 ft2 at front (east) entrance, about 200 ft2 at south transept, and 50 ft2 at east end of north facade. Plan 

area≈9,070 ft2, and assume 1,000 ft2 of additional galleries. Affected area≈(450 ft2)/(10,000 ft2)=4.5%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 163

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Damaged bike 

store with 

failed parapet

Blacklock, 

James R.

Late 1989 North America/ Santa Cruz 

County/ United States/ 

Watsonville/ California

Damaged bike store with failed 

parapet. Watsonville, California.

Figure 8–5. Photographs (A–E) showing damage to St. Patrick’s Church, Watsonville, after the 1989 Loma Prieta, California, 

earthquake.

A

D E

B C

Image Metadata and Description for Figure 8–6

Loma Prieta Blacklock Collection: LP0087

Author’s Estimate of Affected Area

No other shots. No street name. No indication as to the former location of Watsonville Cyclery. 202 Main Street does not 

look like this. Littered area≈50 ft×12 ft. Plan area≈40 ft×60 ft. Affected area≈25%.
164 The HayWired Earthquake Scenario—Engineering Implications

Figure 8–6. Photograph showing damaged bike store in Watsonville with failed parapet after the 1989 Loma Prieta, California, 

earthquake. 

Image Metadata and Description for Figure 8–7

Loma Prieta Blacklock Collection: LP0090

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Wood frame house 

with failed 

foundation

Blacklock, 

James R.

Late 1989 North America/ Santa Cruz 

County/ United States/ 

Watsonville/ California

Pink frame house with failed 

foundation. Watsonville, 

California.

Author’s Estimate of Affected Area

By inspection, 0%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 165

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

6th and Bluxome St. Dickenson, 

Stephen E.

1989 United States/ California/ 

North America/San Francisco

Collapse of fourth story wall from 

unreinforced brick building at 

6th and Bluxome Streets, San 

Francisco, South of Market. 

Figure 8–7. Photograph showing house with failed foundation in Watsonville after the 1989 Loma Prieta, California, earthquake.

Image Metadata and Description for Figure 8–8

Loma Prieta Collection: LP0462 

Author’s Estimate of Affected Area

Also see LP0460 (below). The location is sometimes reported as near 5th and Townsend Streets, sometimes on Bluxome 

Street near 6th and Townsend Streets. If the latter, the building appears to be 178 Bluxome Street, at the south end of Bluxome 

on the north side of the street (assessor’s parcel number [APN] 3785135), with parcel area 15,300 ft2 according to Google Earth 

Pro. With four stories, the total building area would be 61,200 ft2. The debris runs the length of the facade (135 ft) and twice as 

wide as the sidewalk, perhaps 24 ft. Five people were killed by the wall collapse. Affected area=(135×24)/(61,200)=5.3%.
166 The HayWired Earthquake Scenario—Engineering Implications

Figure 8–8. Photograph showing collapse 

of fourth story wall from unreinforced 

brick building after the 1989 Loma Prieta, 

California, earthquake.

Image Metadata and Description for Figure 8–9

Loma Prieta Collection: LP0460

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Unreinforced brick 

building

Kayen, Robert E. Late 1989 United States/ California/ 

North America/ San 

Francisco

6th and Bluxome Streets, south 

of Market. Collapse of unreinforced brick wall.

Author’s Estimate of Affected Area

Same as LP0462 (above).
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 167

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Collapse of apartment buildingsSeed, Raymond B. Late 1989 United States/ California/ 

North America/ San 

Francisco

Collapse of two four-story apartment buildings (soft ground 

floors). Marina District, San 

Francisco, California.

Figure 8–9. Photograph showing collapse 

of unreinforced brick wall from the 1989 

Loma Prieta, California, earthquake.

Image Metadata and Description for Figure 8–10

Loma Prieta Collection: LP0375

Author’s Estimate of Affected Area

By inspection, two buildings, each with 25% collapse.
168 The HayWired Earthquake Scenario—Engineering Implications

Figure 8–10. Photograph showing collapse of apartment buildings with soft ground floors in the Marina District of San Francisco after 

the 1989 Loma Prieta, California, earthquake.

Image Metadata and Description for Figure 8–11

Loma Prieta Collection: LP0499

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Collapsed building 

in Marina District

Harris, S. P. October 17, 

1989

United States/ California/ 

North America/ San 

Francisco

Collapsed apartment building at 

2090 Beach St, after the fire 

was much advanced. Note 

firefighter directing water 

onto exposed side of building. 

Marina District, San Francisco, 

California.

Author’s Estimate of Affected Area

This had been a four-story building, now with only one story remaining somewhat intact, so 75% collapse.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 169

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Soft-story collapse unknown -- United States/ California/ 

North America/ San 

Francisco

Soft-story collapse of apartment 

building in the Marina District, 

San Francisco, California. 

Figure 8–11. Photograph showing collapsed four-story building in the Marina District, San Francisco, after the 1989 Loma Prieta, 

California, earthquake (photograph from Scawthorn and others, 1992, p. 204, fig. 11).

Image Metadata and Description for Figure 8–12

Karl V. Steinbrugge Collection: S6144

Author’s Estimate of Affected Area

To the author’s personal knowledge, this had been a three-story building, so affected area=67%. What is remarkable about 

this building is that it appears in many photos of the Marina District, almost entirely without identifying information other than 

the neighborhood. One photo caption says the building was at Beach Street and Divisadero Street. The view of the Golden Gate 

Bridge tower in the background tells us that it was at the northwest corner, apparently 3700 Divisadero Street, San Francisco, 

California 94123-1000 (APN 0913037).
170 The HayWired Earthquake Scenario—Engineering Implications

Figure 8–12. Photograph showing soft-story collapse of an apartment building in the Marina District, San Francisco, in the 1989 Loma 

Prieta, California, earthquake.

Image Metadata and Description for Figure 8–13

Loma Prieta Collection: LP0459

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Front and Davis St. Dickenson, 

Stephen E.

Late 1989 United States/ California/ 

North America/ San 

Francisco

Front and Davis Streets. Collapse 

of unreinforced masonry wall 

from third floor of building. 

Embarcadero/ Financial District, San Francisco.

Author’s Estimate of Affected Area

Front Street is parallel to Davis Street, so the recorded location makes no sense. Matching the background buildings, the 

address seems to be 235 Front Street, San Francisco, California, on the northwest corner of Front Street and Halleck Street. The 

view is toward the northwest. The building appears to be on APN 0237047, whose area is 4,960 ft2. Aerial photography dating 

from 1938 and available in Google Earth Pro shows a building of uniform height covering the entire parcel, suggesting a total 

building area of 14,880 ft2. The collapsed wall faces Front Street. The facade length is 72 ft, so the affected area appears to be 

36 ft. I can find no images of the masonry on the sidewalk. I assume it litters an area 36 ft×16 ft wide, for an affected area of (36 

ft×12 ft)/(14,880 ft2)=2.9%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 171

Earthquake date 

and magnitude (M) Title Creator Date Location Description

October 17, 1989; 

M7.09

Interior structural 

failures at department store

Blacklock, 

James R.

Late 1989 North America/ Santa Cruz 

County/United States/

Santa Cruz/ California

Interior structural failures at 

department store. Santa Cruz, 

California.

Figure 8–13. Photograph showing 

collapse of unreinforced masonry wall in 

the Embarcadero/Financial District, San 

Francisco, after the 1989 Loma Prieta, 

California, earthquake.

Image Metadata and Description for Figure 8–14

Loma Prieta Blacklock Collection: LP0041
172 The HayWired Earthquake Scenario—Engineering Implications

Author’s Estimate of Affected Area

This may be Ford’s Department Store, the only department store mentioned in connection with collapse in Santa Cruz after 

the Loma Prieta earthquake. The building was located at the corner of Pacific Avenue and Cathcart Street, Santa Cruz, California. The address is 1101 Pacific Avenue, Santa Cruz, California (APN 00514120000), on the northwest corner of Pacific Avenue 

and Cathcart Street. The parcel measures 20,900 ft2, according to Google Earth Pro. One can see an exhaust vent above the truss 

in the background, so Ford’s Department Store must have been one story tall in this portion of the building. The affected area 

here appears to be perhaps 1,000 ft2. A personal-injury law firm’s website (http://csfwlaw.com/successful_personal_injury_lawsuits) says that the “back of the Ford’s Department Store collapsed,” indicating that the entire interior did not collapse. More 

images from a local blog (Christensen, 2009) and JPG Magazine LLC (2017) suggest that something like the back one-third of 

the store collapsed, or roughly 33%.

Figure 8–14. Photograph showing interior structural failure in a department store in Santa Cruz after the 1989 Loma Prieta, California, 

earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 173

Appendix 9. Northridge (1994) Collapse Images

Image Metadata and Description for Figure 9–1

Northridge Collection: NR327

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Collapsed apartment 

building

Unknown 1994 Northridge/ California/ 

North America/ Los 

Angeles County/ United 

States

Collapsed apartment building, 

three-story wood frame. Northridge, California.

Author’s Estimate of Affected Area

According to Todd and others (1994, p. 23; fig. 9–2), there were four collapsed three-story buildings. The ground story of 

two of the buildings completely collapsed, the ground story of about half of a third three-story building collapsed, and approximately one-eighth of a fourth. Thus, the affected areas are 33%, 33%, 17%, and 4%.

Figure 9–1. Photograph showing collapsed apartment building after the 1994 Northridge, California, earthquake.
174 The HayWired Earthquake Scenario—Engineering Implications

Figure 9–2. Diagram showing parking areas, 

collapsed areas, and locations of deaths on the 

first level of Northridge Meadows Apartments 

after the 1994 Northridge, California, earthquake 

(Todd and others, 1994, p. 23).

Image Metadata and Description for Figure 9–3

Northridge Collection: NR335

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Building components fell onto 

off-ramp

Aschheim, 

Mark A.

January 19, 1994 North America/ Los 

Angeles County/ United 

States/ Los Angeles/ 

California

Building at eastbound off-ramp of 

Route 101 south at Van Nuys 

exit. View to south. Failed building components fell onto offramp. Los Angeles, California.

Author’s Estimate of Affected Area

This building was repaired. It is located at 4717 Van Nuys Boulevard, Sherman Oaks, California 91403. According to 

Google Earth Pro, the building area is 16,094 ft2. There are no long shots or aerial shots to show the extent of the roof collapse. 

No estimate of affected area.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 175

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Northridge Meadows ApartmentsReitherman, 

Robert K.

February 12, 1994 Northridge/ California/ 

North America/ Los 

Angeles County/United 

States

Collapse of ground story in 

Northridge, California. Structure: Northridge Meadows 

Apartments.

Figure 9–3. Photograph showing building components fallen onto off-ramp after the 1994 Northridge, California, earthquake. 

Image Metadata and Description for Figure 9–4

Northridge Collection: NR353

Author’s Estimate of Affected Area

Same as figure 9–1.
176 The HayWired Earthquake Scenario—Engineering Implications

Figure 9–4. Photograph showing collapse of ground story at Northridge Meadows Apartments after the 1994 Northridge, California, 

earthquake.

Image Metadata and Description for Figure 9–5

Northridge Collection: NR357

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Northridge Meadows ApartmentReitherman, 

Robert K.

February 12,1994 Northridge/ California/ 

North America/ Los 

Angeles County/ United 

States

Northridge Meadows Apartments. Collapse of ground 

story. Northridge, California. 

Structure: Northridge Meadows Apartments.

Author’s Estimate of Affected Area

Same as figure 9–1.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 177

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Northridge Meadows ApartmentReitherman, 

Robert K.

February 12, 1994 United States/ Northridge/ California/ North 

America/ Los Angeles 

County

Northridge Meadows Apartments. Collapse of ground 

story. Northridge, California. 

Structure: Northridge Meadows Apartments.

Figure 9–5. Photograph showing collapse of ground story at Northridge Meadows Apartments after the 1994 Northridge, California, 

earthquake.

Image Metadata and Description for Figure 9–6

Northridge Collection: NR358

Author’s Estimate of Affected Area

Same as figure 9–1.
178 The HayWired Earthquake Scenario—Engineering Implications

Figure 9–6. Photograph showing collapse of ground story at Northridge Meadows Apartments after the 1994 Northridge, California, 

earthquake.

Image Metadata and Description for Figure 9–7

Northridge Collection: NR408–NR409

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

2-story masonry 

building

Stojadinovic, 

Bozidar

January 19, 1994 North America/ Los Angeles County/ United 

States/ Santa Monica/ 

California

1004 West Channel Road at 

Pacific Coast Highway (near 

Pacific Palisades). Damage to 

two-story masonry building. 

Heavy shear cracking on side 

walls. Out of plane failure of the 

second story. State Beach Cafe, 

Santa Monica, California.

Author’s Estimate of Affected Area

The address appears to be 108 West Channel Road, Santa Monica, which is adjacent to 112 (it is not 1004). From size of 

replacement building, which fills the lot, the damaged building appears to be 1,500 ft2 in plan, or 3,000 ft2 total. Bricks litter 40 ft 

of facade×10 ft across sidewalk. Affected area is therefore approximately 400 ft2/3,000 ft2=13%.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 179

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Four-story masonry buildingStojadinovic, 

Bozidar

January 19, 1994 North America/ Los 

Angeles County/ 

United States/ Santa 

Monica/ California

Four-story masonry building, 827 

Fourth St. Damage to the fourth 

and third floor of the building. The 

masonry facade fell out of plane and 

took with it the fourth floor terrace. 

This building had been scheduled for 

a retrofit to begin on Monday, January 17, 1994. Three layers of thick 

unreinforced masonry. Damage to the 

top story and balcony. Little damage 

on the sides and below the third story. 

Santa Monica, California.

Figure 9–7. Photograph showing damage to twostory masonry building in Santa Monica after the 

1994 Northridge, California, earthquake.

Image Metadata and Description for Figure 9–8

Northridge Collection: NR413, NR414
180 The HayWired Earthquake Scenario—Engineering Implications

Author’s Estimate of Affected Area

Building still exists and has been repaired. Google Earth Pro says building area=31,314 ft2. Affected area looks like 

(55 ft×12 ft)/(31,314 ft2)=2.1%.

A

B

Figure 9–8. Photograph showing damage to four-story masonry building in Santa Monica after the 1994 Northridge, 

California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 181

Image Metadata and Description for Figure 9–9

Northridge Collection: 201012024

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Collapsed 

unreinforced 

chimney

Reitherman, 

Robert K.

2010 Unknown This residential chimney of unreinforced 

blocks collapsed during the 1994 

Northridge earthquake.

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Parking structure 

on Cal State 

Northridge 

campus

Unknown 1994 Northridge/ California 

/North America/ 

Los Angeles County/ United States

Parking structure on Zelzah Ave., California 

State University, Northridge, campus. 

This is a three-story precast concrete 

parking structure. Overall view showing collapse at east end of the structure. 

Structure: Cal State Northridge Parking

Author’s Estimate of Affected Area

Masonry litters an area about 10 ft×4 ft, or 40 ft2. Assuming a typical 1,500 ft2 home, the affected area is 2.7%.

Figure 9–9. Photograph showing 

collapsed unreinforced chimney 

after the 1994 Northridge, California, 

earthquake.

Image Metadata and Description for Figure 9–10

Northridge Collection: NR559

Author’s Estimate of Affected Area 

From figure 9–11, looks like about 35%.
182 The HayWired Earthquake Scenario—Engineering Implications

Figure 9–10. Photograph showing collapse of a parking structure on the California State University, Northridge, 

campus after the 1994 Northridge, California, earthquake.

Figure 9–11. Photograph from the 1994 Northridge, California, earthquake. Image is from Earth Science World 

Image Bank (2017), which describes it as follows: California State University, Northridge parking structure that 

partly collapsed during the 1994 earthquake. Scientists believe it was the lack of shear walls, being precast, 

and lack of extra steel reinforcements in vertical columns that led to the damage seen here. This is 5 kilometers 

northeast of the epicenter. (Photograph by P.W. Weigand. Copyright California State University, Northridge, 

Geology Department, permission granted per earthscienceworld.org.)
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 183

Image Metadata and Description for Figure 9–12

Northridge Collection: NR579

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Fashion Center 

parking garage

Reitherman, 

Robert K.

February 12, 1994 Northridge/ California/North America/ 

Los Angeles County/ United States

Collapse of parking garage floors. See 

NR459–461 for damage to Broadway 

department store. Fashion Center, 

Northridge, California. Structure: 

Northridge Fashion Center Parking.

Author’s Estimate of Affected Area

From an Atlantic Magazine image (Taylor, 2014), the collapsed area looks like about 35%.

Figure 9–12. Photograph showing collapse of floors in the Northridge Fashion Center parking garage from the 1994 Northridge, 

California, earthquake.
184 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 9–13

Northridge Collection: NR221

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Bullock's retail 

store

Unknown 1994 Northridge/ California/ 

North America/ Los 

Angeles County/ 

United States

Northridge Fashion Island Center. Interior 

reinforced-concrete columns remain 

standing following collapse of secondand third-floor concrete waffle slabs. 

Intact portion of waffle slab roof shows 

typical slab construction. Structure: 

Bullock’s Department Store.

Author’s Estimate of Affected Area

A plan of Bullock’s shows that the building has eight bays in each direction (Bibliop, 2017). It appears that the second 

floor collapsed onto the first floor in all but about 14 square bays: the one on the left and the one in the rear as viewed from the 

photographer’s viewpoint, so 150 out of 192 floor-bays collapsed, or 78%.

Figure 9–13. Photograph showing collapse of second- and third-floor concrete waffle slabs at Bullock’s retail store after the 1994 

Northridge, California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 185

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Oviatt Library, 

Cal State 

campus

McMullin, 

Kurt M.

January 20, 1994 Northridge/ California/ 

North America/ Los 

Angeles County/ 

United States

View of partial roof collapse. South elevation, east of front entry. View from 

east. Taken at 3 p.m. California State 

University, Northridge. Structure: 

Oviatt Library.

Image Metadata and Description for Figure 9–14

Northridge Collection: NR303

Author’s Estimate of Affected Area

Other photographs, omitted for brevity (Northridge Collection numbers NR299, NR300, and NR302), show about 4×1 bays 

of roof collapse. One bay generally refers to the space between two columns, so 4×1 bay means a rectangular space between a 

sequence of five columns in one direction and between two columns in the perpendicular direction. The building has 14 bays 

east to west and 6 bays north to south and 5 floors, according to California State University Northridge’s web page (California 

State University Northridge, 2017). Thus, 4×1 bays on 1 story collapsed out of 5 stories, each with 14×6 bays, suggesting a collapsed area of (4×1)/(5×14×6)=1.0%

Figure 9–14. Photograph showing partial roof 

collapse of Oviatt Library, California State University, 

after the 1994 Northridge, California, earthquake.
186 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 9–15

Northridge Collection: NR543

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Kaiser parking 

structure

Reitherman, 

Robert K.

January 19, 1994 Los Angeles/ California/ North America/ 

Los Angeles County/ 

United States

Complete collapse of parking structure. 

Los Angeles, California. Structure: 

Kaiser Hospital parking.

Author’s Estimate of Affected Area

See also the NISEE e-libraries Northridge Collection, photographs NR519, NR528, NR530, NR539, NR540, NR542, 

NR544, NR545, NR546, NR549, NR551, NR552, NR543, and NR544. All the photo descriptions ostensibly describe the 

Kaiser Hospital parking structure, but it appears there were two parking structures. Some descriptions say “complete collapse” 

and other photos such as NR519, NR528, and NR530 show a parking structure that has not collapsed. Reitherman, in NR549, 

names the location “Kaiser West Los Angeles Medical Center,” which Google says is located at 6041 Cadillac Avenue, Los 

Angeles, California, 90034, which Google Earth locates at lat 34.0384 N., long −118.3757 E. Three satellite images from August 

1989, April 1994, and March 2002, and shown in Google Earth, reveal two parking structures near here; one with a center near 

lat 34.0391 N., long −118.3759 E. appears to be the one that did not collapse. Another with a center at lat 34.0389 N., long 

−118.3733 E. appears in 1989, but is absent in April 1994 (after the earthquake), and it reappears (a replacement) in 2002. I can 

find no aerial images of the latter collapsed structure or long shots to show the extent of the collapse, so I take the affected area 

as 100%.

Figure 9–15. Photograph showing complete collapse of the Kaiser parking structure, Los Angeles, after the 1994 Northridge, California, 

earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 187

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Soft-story 

collapse of 

apartment 

building

Unknown 1994 Sherman Oaks/ California/ North America/ 

Los Angeles County/ 

United States

Soft-story collapse of apartment building, at Hazeltine Ave. and Milbank St., Sherman Oaks, 

California.

Image Metadata and Description for Figure 9–16

Northridge Collection: NR328

Figure 9–16. Photograph showing soft-story collapse of apartment building in Sherman Oaks after the 1994 Northridge, California, 

earthquake.

Author’s Estimate of Affected Area

By inspection, 33%.
188 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 9–17

Northridge Collection: NR160

Earthquake date 

and magnitude (M) Title Creator Date Location Description

January 17, 1994; 

M6.69

Soft-story collapse of apartment buildingUnknown 1994 Sherman Oaks/ California/ North America/ 

Los Angeles County/ 

United States

Soft-story collapse of apartment building, at 

Hazeltine Ave. and Milbank St., Sherman 

Oaks, California.

Author’s Estimate of Affected Area

See also the NISEE e-library’s Northridge Collection, photograph NR162. The collapsed second floor amounts to 20% of 

the building area. The partly collapsed north and south end bays from floors three to five add another 10%, for a total of 30%.

Figure 9–17. Photograph showing second-floor collapse at Kaiser Permanente office building, Granada Hills, after the 1994 Northridge, 

California, earthquake.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 189

Earthquake date 

and magnitude (M) Title Creator Date Location Description

December 22, 

2003; M6.6

View of 

collapsed 

building from 

intersection 

of 12th 

and Park 

Streets

Sakai, 

Junichi

December 23, 2003 Paso Robles/ California/ North 

America/ San 

Luis Obispo 

County/ United 

States

This unreinforced masonry building was 

built in 1892, and its clock tower became 

a symbol for the town of Paso Robles. The 

second story of the building collapsed during the earthquake, killing two employees 

of Ann's Dress Shop as they tried to flee 

onto Park Street. The roof of the building collapsed directly westward onto Park 

Street and landed on a row of parked cars. 

Debris from the north wall went through 

the roof of an adjacent shop at 1220 Park 

Street, Paso Robles, California. Structure: 

Mastagni Building.

Appendix 10. San Simeon (2003) Collapse Images

Image Metadata and Description for Figure 10–1

NISEE Miscellaneous Collection: NM0008

Author’s Estimate of Affected Area

Also see the NISEE e-library’s Northridge Collection, photographs NM0009 and NM0012 for this building and its photographs NM0001–NM0004 for 1220 Park Street. The building at the west end of the 800 block of 12th Street (807 12th Street is 

mentioned in the description of NM0009) and the south end of the 800 block of Park Street appears in September 1994 satellite 

imagery in Google Earth. It has a plan area of approximately 5,960 ft2, so a total area of approximately 11,920 ft2. The collapse 

of the second floor constitutes 5,960 ft2. In addition, the roof collapsed onto 12th Street. The building was approximately 120 ft 

long north to south, and it looks as if the roof covered the sidewalk and half the depth of the diagonal street parking, about 19 ft 

total, so another 120 ft×19 ft=2,280 ft2. The building at 1220 Park Street, just to the north, was a one-story building that appears 

from photograph NM0009 to have had its roof completely collapse under debris falling from the Mastagni Building. The floor 

area of 1220 Park Street looks like 50 ft deep by perhaps 20 ft wide. The total affected area is therefore approximately (5,960 ft2

+ 2280 ft2 + 1,000 ft2)/(11,920 ft2)=78%.

Figure 10–1. Photograph showing collapsed building from intersection of 12th and Park Streets in Paso Robles after the 2003 San 

Simeon, California, earthquake.
190 The HayWired Earthquake Scenario—Engineering Implications

Image Metadata and Description for Figure 10–2

NISEE Miscellaneous Collection: NM0012

Earthquake date 

and magnitude (M) Title Creator Date Location Description

December 22, 

2003; M6.6

Old Clocktower Unknown December 

23, 2003

Paso Robles/ California/ 

North America/ San 

Luis Obispo County/ 

United States

Before and after images of the Old Clocktower. This unreinforced masonry building 

was built in 1892, and its clock tower had 

become a symbol of Paso Robles. The second story of the building collapsed directly 

westward onto Park Street. Paso Robles, 

California.

Author’s Estimate of Affected Area 

The author could not find an image that provides a wide enough perspective to judge the affected area. The image is 

included for completeness. 

A B

Figure 10–2. Photographs of the Old Clock Tower, Paso Robles, before (A) and after (B) the 2003 San Simeon, California, earthquake. 

This unreinforced masonry building was built in 1892, and its clock tower had become a symbol of Paso Robles. The second story of the 

building collapsed directly westward onto Park Street.
Chapter M. An Earthquake Urban Search and Rescue Model for Earthquake Response 191

Earthquake date 

and magnitude (M) Title Creator Date Location Description

August 24, 2014, 

M6.0

Don Perico’s 

Restaurant

Sarah Durphy Unknown Napa/ California/ North 

America/ Napa County/ 

United States

Exterior and interior of Don Perico’s 

Resturant. Napa, California.

Appendix 11. South Napa (2014) Collapse Images

Image Metadata and Description for Figure 11–1

Sarah Durphy: P9050177 (outside) and P9080152 (inside).

Author’s Estimate of Affected Area

At the time of the earthquake, the restaurant was located at 1025 1st Street, Napa, California, in the west end of the building 

at lat 38.299029 N., long -122.285868 E. That address seems to occupy approximately 60 ft×60 ft. The collapsed wall appears to 

fill 25 ft×12 ft, suggesting an affected area of 8.3%.

A

B

Figure 11–1. Photographs (A, B) showing 

damage to Don Perico’s Restaurant in 

Napa in the 2014 South Napa, California, 

earthquake. 
192 The HayWired Earthquake Scenario—Engineering Implications

Borrego Mountain (1968) 

Livermore (1980) 

Mammoth Lakes (1980) 

Cape Mendocino (1980) 

Humboldt County (1980) 

North Palm Springs (1986) 

Oceanside (1986) 

Chalfant Valley (1986) 

Superstition Hills (1987) 

Lake Elsman (1989) 

Sierra Madre (1991) 

Joshua Tree (1992) 

Cape Mendocino (1992) 

Landers (1992) 

Big Bear (1992) 

Eureka Valley (1993) 

Hector Mine (1999) 

Yountville (2000) 

Parkfield (2004) 

Anza (2005) 

Cape Mendocino (2005) 

Alum Rock (2007) 

Chino Hills (2008) 

Inglewood (2009) 

Eureka (2010) 

Pico Rivera (2010) 

El Mayor-Cucapah (2010) 

Borrego Springs (2010) 

Brawley swarm (2012) 

Avalon (2012)

Appendix 12. Earthquakes With No Available Collapse Images


Chapter N

A New Model of Water-Network Resilience, with 

Application to the HayWired Scenario

By Keith A. Porter1

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013]

1

University of Colorado Boulder.

Abstract

Damage to potable water-supply systems can profoundly 

affect a society after an earthquake. For at least 25 years, 

engineers have performed computerized risk analyses of 

earthquake damage to water-supply systems to estimate 

earthquake damage and restoration. A new stochastic simulation 

model is offered here that employs a fairly traditional lossestimation approach but with three notable improvements—

(1) it deals with lifeline interaction by directly modeling 

how individual repairs are slowed by limitations in so-called 

upstream lifelines and other prerequisites; (2) it quantifies 

damage and restoration over the entire earthquake sequence, 

that is, considering damage in the mainshock, aftershocks, 

and afterslip; and (3) it offers an empirical model of service 

restoration as a function of the number of pipeline repairs 

performed (as opposed to more rigorous, but computationally 

demanding, hydraulic analysis). A fourth improvement is that 

it offers a procedure to adjust estimates of restoration from 

the Federal Emergency Management Agency’s Hazus-MH 

computer program to account for an earthquake-sequence’s 

interactions with lifelines and corrects for Hazus-MH’s default 

assumptions about the number of available repair crews.

The model is applied for two water-supply systems in 

California’s San Francisco Bay region subjected to the hypothetical but highly realistic HayWired earthquake sequence—a 

moment magnitude (Mw) 7.0 mainshock on the Hayward Fault 

in the east bay part of the San Francisco Bay area, plus 16 

aftershocks of magnitude 5 or greater occurring over 17 months 

after the mainshock. The model quantifies water-system damage 

and restoration, including delays due to fuel and other lifeline 

limitations, and setbacks in restoration because of aftershocks. It 

estimates the benefit of a fuel-management plan and an accelerated pipe-replacement plan in terms of accelerated restoration 

of service. The model is validated several ways for each of the 

two case-study water-supply systems and seems reasonable. 

One San Francisco Bay region water utility anticipates using the 

model to target vulnerable segments of its system for accelerated pipe replacement.

Introduction

The HayWired scenario examines a hypothetical earthquake 

(mainshock) with a moment magnitude (Mw) of 7.0 occurring 

on April 18, 2018, at 4:18 p.m. on the Hayward Fault in the east 

bay part of California’s San Francisco Bay area. The HayWired 

scenario evaluates, among other things, the potential for damage to 

water-supply systems in the San Francisco Bay region during the 

HayWired mainshock and subsequent aftershocks.

How Water Supply is Important in an Earthquake

People need potable water for daily life. Businesses need 

water for air conditioning and as a raw material for production. 

Water is an input to many natural and manufactured products and 

processes. Damage to a water-supply system can contribute greatly 

to the life-safety and economic consequences of an earthquake, 

as illustrated by the economic analyses performed for the 2008 

ShakeOut scenario (Rose and others, 2011). In that study, the 

authors found that water-supply interruption from a hypothetical 

Mw 7.8 earthquake on the San Andreas Fault in southern California 

could result in $24 billion in business interruption losses when 

macroeconomic responses are not considered and only minimal 

business-resilience actions are taken to reduce the losses. The 

figure that represents more than one third of the $68 billion in 

total business interruption losses and 13 percent of the total of 

property damage plus business interruption. A potable water 

supply is crucial for residences, businesses, government facilities, 

and hospitals and other critical-care facilities. Long aware of the 

importance of water supply and the potential for earthquakes to 

interrupt water supply, earthquake experts recommend that homes 

and businesses have enough water to provide for 1 gallon per 

person per day after a major earthquake to last at least 3 days and 

ideally for 2 weeks.

Loss of water supply in the hypothetical ShakeOut earthquake would also contribute substantially to the fire damage to 

property, which itself could realistically account for $65 billion 

of the $113 billion in property losses (Scawthorn, 2008). The 

ShakeOut scenario was not a worst-case earthquake; the earthquake fault rupture it dealt with has a mean recurrence interval 
196 The HayWired Earthquake Scenario—Engineering Implications

of 150 years, and it has been 300 years since the last rupture. 

Furthermore, the fire simulation assumed mild winds rather than 

the fast, hot, dry, Santa Ana winds that commonly blow in the 

fall and notoriously fan wildfires.

These earlier estimates, although particular to the ShakeOut, 

reflect a general truth—earthquake damage to water-supply 

systems in the United States (and elsewhere) threatens the 

health, safety, and welfare of the population, possibly more 

than earthquake damage to any other utility or other element of 

the built environment, in part because repairs are so costly and 

time consuming. More narrowly, earthquakes can pose a serious 

financial threat to any water supply utility in a seismically active 

region. If a utility cannot deliver water it cannot collect revenues, 

which can threaten its ability to make payroll. Every water utility 

in earthquake country may be at risk.

The HayWired scenario hypothetical mainshock is a 

large but not exceedingly rare Mw 7.0 earthquake that damages 

water-supply systems in the San Francisco Bay region. 

Earthquakes damage water-supply systems, and the damage 

causes other problems, such as for firefighting. The Mw 7.8 

1906 San Francisco earthquake damaged so much of that city’s 

potable water-supply system that pressure dropped too low for 

firefighters to fight the fires that eventually destroyed much of 

the city. The Mw 6.9 1989 Loma Prieta earthquake caused at 

least 761 breaks and leaks to water mains and pipelines made of 

various materials throughout the San Francisco Bay area (Lund 

and Schiff, 1991). The loss of firefighting water supply in San 

Francisco’s Marina District contributed to the fire that damaged 

7 structures, destroying 4 buildings containing 33 apartments 

and flats (Scawthorn and others, 1991). Cast iron, steel, ductile 

iron, plastic, and copper pipes all broke both within and outside 

areas of liquefaction and other ground failure. The Mw 6.0 2014 

South Napa earthquake caused 249 pipeline breaks or leaks 

in the City of Napa, in the northern San Francisco Bay area 

(Douglas DeMaster, Engineer, City of Napa, written commun., 

March 23, 2017).

The largest total number of breaks and leaks and the highest 

repair rate (repairs per mile) in the 1989 earthquake occurred in 

cast-iron pipe subjected to liquefaction-induced ground failure, 

but other materials were also damaged, including ductile iron, 

polyvinyl chloride (PVC), and steel. Pipes were damaged in 1989 

in places that were not known to have experienced ground failure, 

so that damage has been attributed to ground strain associated 

with wave passage, especially Rayleigh surface waves. There 

was no observed liquefaction damage to buried pipeline in Napa 

in the 2014 earthquake, reinforcing the idea that wave passage 

alone can damage buried pipe. Even the modest Mw 4.0 Piedmont, 

California, earthquake of August 17, 2015, caused at least 7 

instances of damage to buried cast iron water-supply pipe in the 

east bay (Bay City News, 2015).

Repairs to an earthquake-damaged water-supply system can 

take months or more. Each repair can take as little as 2 hours to 

repair, but large numbers of repairs and larger pipes can take much 

longer. A 30-inch water main that broke near the UCLA campus 

at 3:30 p.m. on Tuesday July 29, 2014, took almost 5 days, until 

11:00 a.m. Sunday, August 3 to repair (Los Angeles Department 

of Water and Power, 2014). During an earthquake sequence, with 

many simultaneous instances of damage, repairs take longer for 

many reasons. Some of these are:

1. When a pressure zone loses pressure because of many breaks 

and leaks, it can be necessary to repair damage closer to 

the source (that is, nearer the tank, reservoir, or other water 

source) before one discovers damage farther from the source.

2. Similarly, it may be necessary to repair damage to a 

pumping plant, reservoir, or regulator before damage in the 

downstream pipeline network can be addressed.

3. Water districts have an upper limit to their ability to field 

and manage multiple repair crews operating in parallel, even 

when the crews are from outside contractors or from water 

districts that provide mutual aid.

4. Limited supplies of repair resources such as spare pipe, 

clamps, fuel, and repair crews.

5. Damage to other systems—for example, electrical and 

gas—can hinder pipeline repair, and in some cases those 

repairs can cause pipeline damage. Coordination with other 

agencies can conceivably idle repair crews.

6. Aftershocks can hinder repair efforts because they pose an 

ongoing safety threat to repair crews. They can also cause 

new damage or aggravate earlier damage.

Study Objectives

In this work, I attempt to depict a realistic outcome of 

the damage and restoration of water supply in the HayWired 

earthquake sequence. I review available models of earthquakeinduced pipeline damage and repair, propose one for use in the 

HayWired scenario, and apply it to the water-supply systems of 

two San Francisco Bay area water utilities—the San Jose Water 

Company and the East Bay Municipal Utility District (EBMUD). 

These two systems were chosen because they are strongly shaken 

in the scenario, are affected by the mainshock and by aftershocks, 

and were willing to share their system maps. The maps were 

shared under strict requirements of confidentiality, so map details 

are not available to the reader.

This study supplements conventional loss estimation by 

examining the detailed activities involved in discovering and 

repairing water-pipeline damage. It identifies steps in the repair 

process that rely on other lifelines to inform a new model of the 

effects of lifeline interaction to delay water service repairs and 

restoration.

This study focuses on damage and repair of buried water 

pipe, which tends to dominate the effort to restore water supply. 

It considers damage resulting from wave passage, liquefaction, 

landsliding, and fault offset. It ignores earthquake damage to 

other elements in the water-supply system, including raw-water 

aqueducts, tanks, tunnels, canals, valves, and reservoirs. The 

decision to focus this study on buried pipelines without including 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 197

other critical facilities, such as tanks, reservoirs, and tunnels, seems 

reasonable, because a majority of water utilities have implemented 

seismic improvement programs (SIP) that, for the most part, 

focused on seismically retrofitting their tanks, reservoirs, and other 

such facilities but not their old distribution pipelines. As such, old 

distribution pipelines, as an asset class, present the most significant 

seismic vulnerability for most water utilities, because for the most 

part smaller diameter distribution mains were not replaced with 

seismic-resistant mains because it simply wasn’t economically 

feasible to replace them all as part of a SIP.

Elsewhere, the HayWired scenario quantifies damage to 

buildings; this chapter does not address restoration of water 

utilities’ customer base or the change in demand for water as 

homes and businesses relocate because of building damage or 

other reasons.

Literature Review

Before proposing a model to estimate water-supply pipeline 

restoration considering an earthquake sequence and lifeline 

interaction, I first consider some key aspects of previous efforts. 

At least two general approaches exist to estimating damage 

and restoration of water supply after earthquakes—(1) expert 

opinion and (2) engineering analysis. The present work will 

pursue an analytical approach, which requires one to consider 

some important details—pipe damageability, repair effort, 

postearthquake serviceability, lifeline interaction, afterslip, and 

measuring loss of resilience. 

A Panel Approach to Estimating Water-Supply 

Impacts

The ShakeOut scenario (Jones and others, 2008) assessed 

Earth-science impacts, physical damage, and socioeconomic 

impacts of a hypothetical Mw 7.8 southern San Andreas Fault 

earthquake. Among many detailed studies were special studies of 

12 lifelines, 7 of which were performed by panels of employees 

of the utilities at risk. The panel process is described in detail 

in Porter and Sherrill (2011). Briefly, panels meet for several 

hours (generally 4 hours in the case of ShakeOut). Panelists are 

presented with a scenario’s Earth-science impacts and previously 

estimated damage to supposedly upstream lifelines—lifelines 

whose damage would seem to affect the damage or repair to the 

lifeline in question but not vice versa. They then hypothesize 

a realistic outcome of the earthquake on damage and service 

restoration, identifying research needs and mitigation options. 

Panels’ discussion and initial findings are documented in brief 

memos, which are then circulated to the panelists. Panelists 

are asked to review the memos and asked to reconsider lifeline 

interaction in light of damage to supposedly downstream lifelines, 

as well as upstream ones. The process iterates until panelists 

are satisfied with their estimates of damage and restoration. In 

practice in the ShakeOut, as well as in ARkStorm (see Porter 

and others, 2011), only one iteration was used and only two or 

so panelists from each panel actually reviewed and revised the 

write-ups. However, the panel process worked reasonably well. 

Panelists were well qualified and seemed to fairly assess realistic 

earthquake impacts and restoration. They gained insight into 

lifeline interaction, mutual-aid needs, communication capabilities, 

and backup supplies.

Figure 1 shows the water-supply restoration timeline that 

the water-supply panel estimated for strongly shaken (Modified 

Mercalli Intensity, MMI, VIII+) geographic areas using expert 

opinion (Jones and others, 2008). See Porter and Sherrill (2011) 

for electric power restoration curves in ShakeOut and Porter and 

others (2011) for various restoration curves and modes of lifeline 

interaction in the ARkStorm scenario.

Analytical Approaches to Estimating Water 

Supply Impacts

Analytical approaches to estimating impacts to watersupply from an earthquake typically involve acquiring a map 

of a water-supply system, identifying component materials and 

sizes, associating each with one or more vulnerability functions or 

fragility functions (depending on the desired output), estimating 

ground motion and ground-failure severity in one or more 

scenarios, estimating mean damage and sometimes uncertainty 

in damage with reference to the vulnerability functions, and 

sometimes estimating repair costs and duration of loss of function.

The Federal Emergency Management Agency’s (FEMA) 

publication FEMA 224 (Applied Technology Council, 1991), 

Figure 1. Graph showing water-restoration timeline in the ShakeOut 

scenario—a hypothetical magnitude-7.8 earthquake on the southern 

San Andreas Fault—for water customers in areas that experienced 

shaking of Modified Mercalli Intensity VIII or higher (modified from 

Jones and others, 2008).

0

25

50

75

100

0 30 60 90 120 150 180

Water customers receiving service, in percent

Time after earthquake, in days
198 The HayWired Earthquake Scenario—Engineering Implications

Scawthorn and others (1992), Hazus-MH (Federal Emergency 

Management Agency, 2012), the Mid-America Earthquake 

Center’s seismic loss estimation system MAEViz (Mid-America 

Earthquake Center, 2006), and Marconi (Prashar and others, 

2012) all use such an approach. The last three implement their 

methodologies in software, as do many others. In the case of 

Hazus-MH, the software assumes that a water main exists under 

each street, 80 percent of pipes are brittle (such as cast iron), and 

20 percent of pipes are ductile (such as ductile iron). MAEViz and 

Marconi allow the user to specify the location and characteristics 

of each pipe segment. Neither Hazus-MH, MAEViz, nor Marconi 

performs hydraulic analysis. MAEViz and Marconi estimate 

damage. Hazus-MH estimates damage and estimates repair costs 

and system restoration time using methods described later.

Khater and Grigoriu (1989) describe an analytical model 

of water-supply damage and serviceability that does perform 

hydraulic analysis. Coded in software called GISALLE, it 

involves three tasks—(1) generate damage states for water-system 

components consistent with the seismic intensity at the site, (2) 

perform hydraulic analysis for simulated damage state of the 

system, and (3) develop statistics on the available water flow for 

postulated levels of seismic intensity.

Some of the available software, such as MAEViz and Urban 

Infrastructure and Lifelines Interactions of Systems (UILLIS) 

(Javanbarg and Scawthorn, 2012), have the ability to treat lifeline 

interaction—how damage or loss of function in one lifeline system 

affects the functionality or restoration of another. For example, loss 

of power and limitations in fuel supply can affect the functionality 

of a water-supply system or delay repairs. These programs use 

a system-of-systems approach to modeling the lifelines. That is, 

they model two or more lifelines in the same framework, relating 

the condition of an element of one lifeline to the condition of an 

element in another.

Damageability of Buried Pipe

The first step of a water-network resilience analysis once a 

ground-motion map has been developed is to estimate damage. 

Many authors have written extensively about the damageability of 

buried pipe, only some of this work is discussed here.

Vulnerability and Fragility Functions

As used here, a vulnerability function relates the degree 

of damage—in this case, number of breaks or leaks per unit 

length of pipeline—as a function of the degree of environmental 

excitation such as peak ground velocity (PGV). A fragility 

function by contrast measures the probability of reaching or 

exceeding some undesirable state conditioned on the degree of 

environmental excitation. The terminology is not universal but will 

be consistently applied here.

In the present context, vulnerability functions are most 

useful for estimating the number of breaks and leaks in a pipeline 

network subjected to ground shaking (usually referred to as wave 

passage in the pipeline literature), landsliding, and liquefaction. 

However, at a fault crossing, a fragility function is more useful—

here, I am interested in the probability that a pipeline requires 

repair at the point where it crosses the fault, as a function of the 

fault offset and possibly as a function of the angle at which the 

pipeline crosses the fault. Both vulnerability functions and fragility 

functions are commonly conditioned on the pipeline’s engineering 

attributes, such as material, diameter, connections at joints, and 

sometimes soil conditions.

Hazus-MH, O’Rourke and Ayala (1993), and 

Honneger and Eguchi (1992)

The Hazus-MH computer software (Federal Emergency 

Management Agency, 2012) currently uses a vulnerability 

function for pipeline subjected to wave passage by O’Rourke and 

Ayala (1993) and one for pipe in liquefied soil from Honegger 

and Eguchi (1992). The median rates of repairs per kilometer of 

pipeline for these two relations are given by equations 1 and 2, 

respectively:

 , (1)

 , (2)

where PL denotes the probability of liquefaction; K=1.0 for 

asbestos cement, concrete, and cast-iron pipe; K=0.3 for steel, 

ductile iron, and PVC; PGV denotes peak ground velocity 

measured in centimeters per second (cm/s); and PGD denotes 

permanent ground deformation—the absolute distance a point 

on the ground permanently moves due to landsliding, fault 

offset, or liquefaction-induced ground failure—measured in 

inches. Equation 1 draws on a number of observed repairs in 

asbestos cement, concrete, cast iron, and prestressed concrete 

pipe, with diameters between 3 and 72 inches, in four U.S. 

and two Mexican earthquakes experiencing ground motion 

of as much as 50 cm/s of peak ground velocity. (O’Rourke 

and Ayala, 1993, do not publish the number of repairs or 

the lengths of pipe.) O’Rourke and Ayala’s (1993) data for 

equation 1 imply a coefficient of variation in the ratio of 

observed to estimated repair rate of 0.76 and a ratio of mean 

repair rate to median repair rate of 1.22.

The work by Honneger and Eguchi (1992) used to 

develop equation 2 reflects an unknown quantity of pipe and 

number of breaks and leaks. Their data mostly come from 

four earthquakes—1923 Kanto (Japan), 1971 San Fernando 

(California), 1976 Tangshan (China), and 1985 Michoacán 

(Mexico). Pipe diameters range from 4 inches to 48 inches. 

Materials included cast iron, concrete, precast concrete, and steel.

Eidinger (2001)

More recently, Eidinger (2001) proposed two vulnerability 

functions—one for wave passage (that is, ground shaking absent 

liquefaction) and one for permanent ground deformation (that 

is, in the presence of liquefaction or landslide-induced ground 

R K ˆ = × 0.0001 × PGV2.25

R P = ×L K P× GD0.56
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 199

displacement). Equations 3 and 5 present Eidinger’s recommended 

vulnerability functions.

In the equations, Rw (PGV, p) and Rl(PGD, p) denote repair 

rate per 1,000 linear feet of pipe associated with nonexceedance 

probability p, as a result of wave passage and liquefaction, 

respectively. For example, the median repair rate is estimated 

using p=0.5. PGV refers to geometric mean horizontal peak 

ground velocity in inches per second, PGD denotes permanent 

ground displacement relative to pre-earthquake location, measured 

in inches, and Φ-1(p) denotes the inverse standard normal 

cumulative distribution function evaluated at p.

For the reader who is unfamiliar with probability distributions, the standard normal distribution is the bell-shaped curve that 

represents how likely are various possible values of an uncertain 

quantity. Uncertain or random variables can take on a variety of 

probability distributions; the standard normal distribution is one 

of many. It has a peak (the expected or mean value and also the 

value with 50-percent probability of not being exceeded, called 

the median) at 0. Its standard deviation (a measure of how wide 

the bell is, and therefore how uncertain is the random quantity) is 

1.0. Its cumulative distribution function is an S-shaped curve that 

tells the probability that a sample of a quantity with a standard 

normal distribution takes on a value less than or equal to any given 

quantity between ˗∞ and ∞. The inverse of the standard normal 

cumulative distribution function is the value of the uncertain quantity that has a specified probability of not being exceeded. Most 

statistics textbooks provide more information about probability 

distributions (see, for example, Ang and Tang, 1975, or Benjamin 

and Cornell, 1970).

The quantities K1 and K2 are factors to account for pipe 

material, joints, soil corrosivity, and pipe diameter—either small 

(4 to 12 inches diameter) or large (16-inch diameter or greater). 

See table 1 for their values. Eidinger (2001) does not provide 

values for some combinations, so they appear blank in the table. 

The authors acknowledge that permanent ground displacement 

produces damage rates two orders of magnitude greater than wave 

passage and that damage rate in areas with ground failure is fairly 

insensitive to PGD.

The terms exp(β×Φ-1(p)) in equations 3 and 5 reflect that 

the equations treat the repair rate as uncertain and lognormally 

distributed conditioned on the value of PGV or PGD. 

(Lognormal is like normal, except that the natural logarithm 

of the uncertain quantity in question is normally distributed. 

A lognormal variable can take on any positive value but not 

zero or a negative number. The bell shape is skewed to the 

right.) Setting p to 0.5 sets the exp term to 1.0 and makes 

R(p) produce the median (not the mean) repair rate. The mean 

repair rate would be substantially higher than the median. 

Equations 4 and 6 provide the mean (average) repair rate, 

given Eidinger’s values of β shown in equations 3 and 5 and 

Eidinger’s assumption of lognormality. The interested reader 

who is unfamiliar with lognormally distributed variables can 

refer to any of several common textbooks (see, for example, 

Ang and Tang, 1975). The interested reader who is unfamiliar 

with vulnerability functions can refer to Porter (2017a) for a 

short primer.

Equation 3 gives Eidinger’s (2001) pipe vulnerability 

function for wave passage, drawn from 81 sources reporting 

3,350 repairs recorded in 12 earthquakes. The plurality of data 

come from the Mw 6.7 1994 Northridge (California) earthquake. 

The data reflect 38 data points for damage to cast iron, 13 data 

points for damage to steel, 10 data points for damage to asbestos 

Table 1. Eidinger (2001) pipe-vulnerability equation factors K1 and K2, which account for pipe material, joints, soil corrosivity, and pipe 

diameter.

ID Pipe material Joint type Soils Diameter K1 K2

1 Cast iron Cement All Small 1.0 1.0

2 Cast iron Cement Corrosive Small 1.4 1.0

3 Cast iron Cement Noncorrosive Small 0.7 1.0

4 Cast iron Rubber gasket All Small 0.8 0.8

5 Cast iron Mechanical restrained All Small 0.71 0.7

6 Welded steel Lap-arc welded All Small 0.6 0.15

7 Welded steel Lap-arc welded Corrosive Small 0.9 0.15

8 Welded steel Lap-arc welded Noncorrosive Small 0.3 0.15

9 Welded steel Lap-arc welded All Large 0.15 0.15

10 Welded steel Rubber gasket All Small 0.7 0.7

11 Welded steel Screwed All Small 1.3 1.31

12 Welded steel Riveted All Small 1.3 1.31

13 Asbestos cement Rubber gasket All Small 0.5 0.8

14 Asbestos cement Cement All Small 1.0 1.0

15 Concrete with steel cylinder Lap-arc welded All Large 0.7 0.6

16 Concrete with steel cylinder Cement All Large 1.0 1.0

17 Concrete with steel cylinder Rubber gasket All Large 0.8 0.7

18 PVC Rubber gasket All Small 0.5 0.8

19 Ductile iron Rubber gasket All Small 0.5 0.5

1

Assumed here because no K-value is offered by the source.
200 The HayWired Earthquake Scenario—Engineering Implications

cement, 9 data points for damage to ductile iron, and 2 data 

points for damage to concrete. Data reflect PGV values between 

2 and 52 cm/s.

 , (3)

 . (4)

Equations 5 and 6 give Eidinger’s (2001) pipe vulnerability 

function for permanent ground deformation, drawn from 42 data 

points from 4 earthquakes between the Mw 7.8 1906 San Francisco 

earthquake and the Mw 6.7 1989 Loma Prieta earthquake. The 

plurality of data points come from the Mw 7.8 1983 NihonkaiChubu (Japan) earthquake. The plurality of pipe material is 

asbestos cement (20 data points) followed by cast iron (17 data 

points), and a mixture of cast iron and steel—presumably meaning 

that the material was one or the other, but it is not known which 

(5 data points). None of the data appear to reflect ductile iron. 

They reflect PGD values between 0 and 110 inches. In these two 

equations, Rl(PGD, p) denotes the liquefaction-induced damage 

rate associated with nonexceedance probability p, and 

denotes the expected value of the liquefaction-induced damage 

rate:

 

 , (5)

 . (6)

Eidinger (2001) also proposed models for damage to pipe 

that crosses an earthquake fault—one for continuous pipelines 

(equation 7) and one for segmented pipe (equation 8). In the 

equations, PGD denotes mean offset (in inches, in.) over the 

entire length of the fault, presumably at the fault trace rather 

than averaged over the area of the fault, and presumably 

considering coseismic slip and afterslip. In the equations, 

denotes the probability that the pipe crossing the fault will 

break:

 

 

 , (7)

 

 

 

 . (8)

O’Rourke and others (2014)

O’Rourke and others (2014) offer vulnerability functions 

for the median repair rate per kilometer of asbestos cement or 

( ) = × × × ( ) ×Φ ( ) − R P w GV, p K1 0.00187 PGV p exp 1.15 1

R P w ( ) GV = × K P 1 0.003623× GV

R Pl ( ) GD

R Pl ( ) GD = × K P 2 1.39× GD0.319

( ) = × × × ( ) ×Φ ( ) − R Pl GD, p K2 1.06 PGD p exp 0.74 0.319 1

P

= ×

≤

P PGD 0.70

60 in.

0.95

= <

= ≤ ≤

= < ≤

= <

P PGD

PGD

PGD

PGD

0 1 in.

0.5 1 in. 12 in.

0.8 12 in. 24 in.

0.95 24 in.

cast-iron pipes subjected to wave passage. They draw on data 

about 2,051 repairs in 3,400 kilometers (km) of pipe in the Mw 6.2 

February 22, 2011, Christchurch, New Zealand, earthquake and 

the Mw 6.0 June 13, 2011, Christchurch earthquake. The majority 

of pipe length in the database was asbestos cement, but the data 

also included cast iron, PVC, modified PVC, and unnamed other 

materials. The data were drawn from locations with PGV between 

10 and 80 cm/s. Their vulnerability functions are given by 

equations 9 and 10:

 , (9)

 , (10) 

where RAC denotes the median repairs per kilometer of asbestos 

cement pipe, RCI is the analogous value for cast-iron pipe, and 

according to the authors, “GMPGV is the mean of the natural 

logs of the two maximum horizontal peak ground velocity 

(PGV) values taken from ground motion recordings available 

from GNS Science . . . at each station.” Despite that definition 

of GMPGV, the authors seem actually to mean the geometric 

mean of the peak ground velocity values in centimeters per 

second of the two horizontal orthogonal components. (The 

inverse of the natural logarithm of the mean of the natural 

logarithms of two quantities equals their geometric mean.) They 

offer vulnerability functions for pipe subjected to liquefaction, 

where the ground deformation is measured in terms of (1) the 

larger principal component of ground strain in the horizontal 

plane and (2) the rotation of the axis of the pipe about a 

horizontal axis normal to the axis of the pipe, which the authors 

call angular distortion—essentially a differential permanent 

vertical displacement of two points on the pipe axis, divided by 

the distance between the two points.

O’Rourke (2003)

There does not appear to exist any empirical relation 

between fault offset and probability of pipeline damage. A few 

authors offer analytical formulations between offset and stress 

or strain in a pipeline that crosses a fault. O’Rourke (2003) 

summarizes some of these, considering under two conditions that 

depend on the geometry of the pipeline at the fault crossing—(1)

a combination of bending and axial tension and (2) a combination 

of bending and axial compression. For the former, he illustrates 

a relation between tolerable fault offset as a function of distance 

between points at which the pipeline is anchored on either side 

of the fault (which he refers to as “unanchor length”; see fig. 2A) 

and the angle β subtended by the fault and the pipeline, in which 

the offset puts the pipeline in tension. Figure 2A is merely an 

illustration for a particular pipe material and diameter. He offers 

a second analytical relation (fig. 2B) for segmented pipe subject 

to fault offset, again for fault-crossing geometry where offset puts 

the pipe into tension.

log10 ( ) R G AC = × 2.83 log 5 10 ( ) MPGV −

log10 ( ) R G CI = × 2.38 log10 ( ) MPGV − 4.52
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 201

Figure 2. Graphs showing (A) tolerable fault offset versus unanchor length in continuous pipe 

(O’Rourke 2003, citing Kennedy and others, 1977) and (B) tolerable fault offset versus pipe-fault 

intersection angle in segmented pipe (O’Rourke 2003, citing O’Rourke and Trautmann, 1980). (Images 

modified from O’Rourke 2003.) mm, millimeters; cm, centimeters; m, meters; in, inches; ft, feet; %, 

percent; kg/m3, kilograms per cubic meter; X−60, grade of pipe material; εa, maximum axial strain 

due to the elongation of the pipe induced by the fault offset; β, angle at which the pipeline intersects 

a right lateral strike-slip fault; γ, effective unit weight of soil; D, pipe diameter; t, pipe wall thickness; 

δV, vertical component of fault offset; δh, horizontal component of fault offset; Hc, burial depth from 

ground surface to top of pipe; Φ, soil internal friction angle; Φp, contact friction angle.

Unanchor length, in feet

Angle of pipe-fault intersection, β, in degrees

Failure depends 

on lead joint 

location

Failure

Mechanical joints

Lead joints

Extra long restrained 

couplings

Fault offset, in feet Fault displacement

Fault offset, in meters

Unanchor length, in meters

0

0 10 20 30 40 50 60 70 80 90

0

5

10

15

20

1.5

3.0

4.5

6.0

25

0

100

200

300

400

Millimeters Inches

16

12

8

4

200 400 600 800 1,000 1,200 1,400 1,600 1,800

0

60 120 180 240 300 360 420 480 540

β = 60°

β = 60°

β = 45°

β = 45°

β = 30°

γ = 110 pcf

X – 60

D = 3.5 ft (107 cm)

t = 0.56 in (1.43 cm)

Hc

= 3 ft (0.9 m)

εa

= 3 ft (0.9 m)

Hc

= 10 ft (3 m)

εa

= 3.5%

δv

 = 1/4δh

(1,760 kg/m3)

Φ <34° Φp <20°

β = 30°

β = 15°

β = 15°

EXPLANATION A

B
202 The HayWired Earthquake Scenario—Engineering Implications

Tasks and Methods to Repair Leaks and Breaks

The City of Winnipeg (2014) in Canada offers a list of 

tasks to repair a water main break or leak, written for the general 

public. The tasks are shown in chronological order in the lefthand column of table 2. The task list is generally consistent with 

a more detailed checklist created by the American Water Works 

Association (2009), although it omits lists of tools, equipment, 

disinfecting chemicals, documentation, and testing materials. 

Column 2 of table 2 lists my interpretation of rate-limiting factors, 

that is, prerequisites for each task. The rate-limiting factors are 

mostly potential impacts from other lifelines, that is, lifeline 

interactions. If they are unavailable, repairs cannot proceed or 

they proceed more slowly—that is, their rate is limited. These 

items include communications, electricity, fuel, site safety (that 

is, no fire or hazardous material release), roadway access, repair 

crews, and repair supplies (replacement pipe, replacement fittings, 

clamps, and paving materials). Regarding crew availability, public 

and private water agencies plan to provide mutual assistance for 

emergencies (see, for example, California Water/Wastewater 

Agency Response Network, CalWARN, 2009). Crews may have 

to travel from great distances, hundreds of miles or more, so their 

availability can change over time. Table 2 probably omits tasks 

that are unnecessary or trivial for day-to-day repairs but become 

significant in a large earthquake. For example, a water agency may 

also have to arrange repair contracts with contractors, track and 

prioritize repairs, and manage an unusually large number of repair 

crews operating simultaneously.

Lund and Schiff (1991) surveyed operators of pipeline 

utilities, asking them to provide detailed information about 

each pipeline failure they repaired after the 1989 Loma Prieta 

earthquake (see fig. 3 for the survey form). The resulting database 

includes information about 862 pipeline failures among 65 water, 

sewer, drainage, and gas agencies. The data may be useful for 

estimating repair times, so I extracted the following statistics from 

the database.

• Burial depth—Among 67 records with reported burial 

depth, the average was 4.0 feet (ft) and the standard 

deviation was 2.2 ft.

• Break or leak—Among the failures where the respondent 

indicated whether the failure was a break or a leak, it was 

more common for the pipeline to break (336 failures) than 

to leak (140 failures).

• Pipe failure modes—Among pipe failures, the most 

common were circumferential cracks (99), followed by 

splits (43) and corrosion (33). Only one blowout was 

reported.

• Joint failure modes—Almost as common as pipe failures 

were joint failures (102 pulled, 29 cracks at joints, 25 

gasket failures, and 12 other joint failures).

• Fitting failure modes—There were a variety of fitting 

failures (57 threaded couplings, 9 elbows, 6 offsets, 

4 hydrants, 3 tees, and 45 miscellaneous other fitting 

failures).

• Repair methods—The most common repair method was 

to replace the damaged element (185 replacements), 

which was more than twice the number of clamps installed 

(77), followed by mechanical couplings (50), epoxy glue 

(16), and miscellaneous others such as flex couplings and 

pressure grout.

Time to Repair Pipe Leaks and Breaks

To repair damaged water-supply pipe, a repair crew must 

locate the damage, usually eliminate pressure in the pipe by 

closing an upstream valve, excavate the damaged element (usually 

with a backhoe), perform the repair, reopen the upstream valve, 

backfill the excavation, and repave any driving surface over the 

Tasks Rate-limiting factors

Receive a notice from our 311 Centre about a water main break. Communications, electricity

Dispatch a crew to the location. Fuel, site safety (for example, no fire), roadway access, crew availability

Control the leak to reduce the risk to public safety, and private and public 

property. We do this by finding and closing valves.

Contact other utilities to make sure that we can dig without damaging 

other services or endangering staff or the public.

Communications

Pinpoint the location of the leak using an electronic leak detector.

Dig down to the water main and confirm the cause of the leak. Fuel

Repair the water main. Depending on the type of break, we may apply a 

repair clamp or replace a length of pipe.

Pipe, fitting, or repair hardware such as clamps

Open valves to turn the water main back on, flush the water main and 

sample water quality.

Backfill to temporarily restore the excavated area. Fuel

Permanently restore the sod or pavement in the excavated area. Pavement material

Table 2. Water-pipeline repair tasks (City of Winnipeg, 2014), with an interpretation of rate-limiting factors for repairs after an earthquake.
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 203

Figure 3. Image of Lund and Schiff 

(1991) survey form given to operators 

of pipeline utilities, asking them to 

provide detailed information about each 

pipeline failure they repaired after the 

moment-magnitude-6.7 1989 Loma Prieta, 

California, earthquake.

location of the repair. Pipe damage can be repaired by replacing 

the damaged element, by welding over the crack, or by installing 

repair hardware—generally either a clamp that is mechanically 

secured over the damage or a closure ring called a butt strap that 

is welded to the outside of the pipe over the damage. The time 

required to perform the repair depends on several issues:

• How long it takes people to report the damage to the 

utility or otherwise for the utility to become aware of 

and locate the damage, which itself depends on power 

and communication;

• Site accessibility;

• Availability of crews and equipment;

• Availability of fuel and consumable repair material;

• Pipe burial depth;

• Groundwater presence and depth;

• Diameter, material, and jointing of the pipe;

• Impact on water flow (break or leak);

• Nature of the damaged element—whether to pipe, 

joint, or fitting;

• If pipe, whether circumferential crack, longitudinal 

split, corrosion, or other such failure;

• If joint, whether a crack, pull-out, compression failure, 

gasket failure, or other such failure; and

• If fitting, the nature of the fitting (such as elbow, tee, 

cross, offset).

Schiff (1988) offers repair times for 21 individual water-pipe 

repairs after the Mw 5.9 1987 Whittier Narrows earthquake in 
204 The HayWired Earthquake Scenario—Engineering Implications

southern California, mostly of cracks and breaks in 4- to 8-inch 

steel and cast-iron mains. Repair times were reported by the 

City of Whittier water distribution superintendent. Times varied 

between 1 and 16 hours, as shown in table 3. Schiff reports that 

water pressure in Whittier dropped to 50 pounds per square inch 

(psi) from the normal 80 to 100 psi as a result of 40 repairs in 133 

miles of pipe (or 0.06 repairs per 1,000 linear feet of pipe).

EBMUD reports on its mutual assistance to the City of 

Napa after the August 24, 2014, magnitude (M) 6.0 South Napa 

earthquake (East Bay Municipal Utility District, 2014). EBMUD 

crews performed 56 repairs in approximately 252 crew-hours, for 

an average duration of 4.5 hours per repair. It should be noted that 

this average duration for completing repairs does not reflect the 

time it took for the City of Napa or its contractors to complete the 

excavation and backfill (EBMUD crews focused on repair work 

and did not complete excavation/backfill/paving-related work).

Tabucchi and others (2010) elicited opinions from 

personnel at the Los Angeles Department of Water and Power 

(LADWP) on water-pipe repair productivity. They propose 

a model with triangular probability distributions for each of 

several repair operations. Each distribution is characterized by 

a minimum value (the left end of the triangle), a modal value 

(the peak of the triangle, which is the most likely value), and a 

maximum value (the right end of the triangle). Table 4 repeats 

LADWP’s estimates. Distribution-system leak and break repairs 

are estimated to require no less than 3 hours and no more than 

12 hours with modes of 4 to 6 hours.

Hazus-MH (Federal Emergency Management Agency, 

2012) employs four restoration times for pipe repair—two 

each for large and small diameter pipes (20-inch diameter and 

above is large, 12-inch diameter or less is small) times two to 

distinguish between breaks and leaks (see table 5).

Table 3. Repair times for water-supply pipeline damage in the moment magnitude (Mw) 5.9 1987 Whittier Narrows Earthquake and Mw 5.2 

aftershock in southern California (modified from Schiff, 1988).

[CI, concrete insert, RC, reinforced concrete; --, no data]

No. Location Estimated repair time, 

in hours

Pipe diameter, 

in inches (and 

material)

Installation 

date Type failure and comments

Mainshock

1 La Cuarta St. and Whittier Blvd. 3–4 4 (CI) 1920 Blowout—3–4-foot section

2 Citrus Ave. at Beverly Dr. 16 (down 3–4 days) 6 1932 Circumference crack

3 11741 S. Circle Dr. 3–4 4 (CI) 1929 Circumference crack

4 Bronte Dr. at Bacon Rd. 4–5 6 (CI) 1956 Blowout—Pressure hole

5 Beverly Blvd. (Citris and Pick) 12 24 (RC) 1930 Beam crack

6 Painter Ave. at Broadway Ave. -- -- -- Leaked surface from Painter Ave. and Beverly Blvd. and again after the aftershock

7 Dorland St. at Magnolia Ave. 5 6 (CI) 1938 Circumference crack

8 Painter Ave. at Sunset 1 3/4 (steel) Old

9 Greenleaf Ave. at Orange Dr. 16 -- -- Leak surfaced likely from Orange Dr. and 

Friends Ave., (see no. 10)

10 Orange Dr. at Friends Ave. 16 16 (RC) 1930 Circumference crack—Leak entered 

abandoned, uncapped steel pipe

11 13502 Beverly Blvd. 4 6 (CI) 1927 Joint pullout—Likely a flair joint

12 8041 Michigan Ave. 3–4 4 (steel) Very old Blowout—Hole developed

13 12101 Rideout Way 2–3 2 (steel) Old Blowout—2–3-foot section service line

14 South Circle Dr. at North Circle Dr. 4–6 6 CI 1929 Circumference crack

15 Panorama Dr. above Orange Dr. 20 24 1967 Leaks at caulked collars

Aftershock

16 11630 Whittier Blvd. 8 6×8 (CI) -- Shear—T-sheared at flange

17 8053 Michigan Ave. 6 (with no. 18) 4 (steel) Very Old Blowout—Hole a few feet away

18 Near no.17 See no.17 4 (steel) Very Old Blowout—Same as no. 17

19 5630 Omelia Rd. 8 (CI) 1938 Cracked bell

20 Painter Ave. and Beverly Blvd. 8 6×8 (CI) 1935 T-sheared at flange

21 14245 Bronte 6–8 -- 1948 Service cork pulled from main

22 Greenleaf Booster Station 8 16 (CI) 1930 Lead caulk forced out of bell; leak

23 Near 14245 Bronte 5 6 (CI) 1948 Blowout

24 11630 Whittier Blvd. 6 6×8 (CI) See no. 16 This may be from soil settlement 

associated with no. 16

25 12906 Orange Dr. 1 1 (steel) -- Corroded—Service line split
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 205

Table 4. Los Angeles Department of Water and Power (LADWP) water-pipe repair productivity estimates (modified from Tabucchi and others, 2010).

[MWD, Metropolitan Water District; hr, hour; km, kilometer]

 Event Minimum Mode Maximum

Inspect a:

 Trunk or distribution damage location 0.5 hr 0.5 hr 1 hr

 Pump station 1 hr 1 hr 2 hr

 Regulator station 1 hr 1 hr 2 hr

 Tank 1 hr 1 hr 2 hr

 Small reservoir 2 hr 2 hr 3 hr

Rerouting operation on a trunk line by:

 Truck redundancy (major)1 3–6 hr 6–12 hr 8–24 hr

 Trunk redundancy (minor)1 3 hr 4 hr 8 hr

 Connecting to MWD1 3–4 hr 6 hr 8–12 hr

 Connecting to well1 4–6 hr 6–8 hr 8–12 hr

 Using a fire truck1 1–2 hr 2–3 days 3–4 days

 Isolate distribution damage at one demand node 1 hr 2 hr 4 hr

Repair a:

 Distribution leak 3 hr 4 hr 6 hr

 Distribution break 4 hr 6 hr 12 hr

 Trunk leak 4 days 4 days 6 days

 Trunk break 6 days 8 days 10 days

 Travel a distance D (km) D/25 hr D/40 hr D/80 hr

1

Major trunk lines are the pipelines that are the sources for each of the 13 LADWP subsystems; minor trunk lines are the remaining ones. Task duration for 

major trunk line rerouting operations vary by specific trunk line, as listed in Tabucchi and Davidson (2008).

Table 5. Hazus-MH estimates of repair time per pipe repair as a result of earthquake (modified from Federal Emergency Management Agency, 2012).

Diameter from, in inches Diameter to, in inches Number of fixed breaks 

per day per worker

Number of fixed leaks 

per day per worker

Number of 

available workers Priority

60 300 0.33 0.66 User specified 1 (highest)

36 60 0.33 0.66 User specified 2

20 36 0.33 0.66 User specified 3

12 20 0.50 1.0 User specified 4

8 12 0.50 1.0 User specified 5 (lowest)

Unknown diameter or for 

default data analysis

Unknown diameter or for 

default data analysis

0.50 1.0 User specified 6 (lowest)

Seligson and others (1991) offer an empirical relation for 

time required to restore water service as a function of number 

of pipeline repairs per square mile, based on evidence from two 

earthquakes in southern California, the Mw 6.7 1971 San Fernando 

and Mw 5.9 1987 Whittier earthquakes. In equation 11, B denotes 

repairs per square mile and d denotes number of days of watersupply outage:

 . (11)

Serviceability of Water Supply

As previously noted, some analytical models are capable of 

modeling the serviceability of a damaged water-supply system 

using hydraulic or connectivity analysis (see, for example, Khater 

and Grigoriu, 1989). As in the case of the closely related Life 

Line Earthquake Engineering (LLEQE) software, the Applied 

Technology Council (1991) noted that such systems can be data 

intensive and computationally demanding. What can be done to 

estimate water-supply serviceability without a hydraulic model?

Isoyama and Katayama (1982) proposed to measure a 

quantity they called serviceability as the probability that the 

demand at a system node (such as a customer-service connection) 

is fully satisfied, or in the aggregate, the average fraction of nodes 

in the entire system whose demand is fully satisfied. Demand 

seems to mean the pre-earthquake consumption plus postearthquake leakage.

Markov and others (1994) propose to measure 

serviceability using a serviceability index, SS, defined as the 

ratio of the total available flow to the total required flow, 

= + × >

=

d B B

B

2.18 2.51 ln 0.42

0 ≤ 0.42
206 The HayWired Earthquake Scenario—Engineering Implications

which is similar but not identical to Isoyama and Katayama’s 

serviceability. If demand at 10 nodes were fully satisfied and 

demand at 10 other nodes were partially satisfied, the two 

measures of serviceability would take on different values—0.5 

in the case of Isoyama and Katayama (1982) and somewhat 

higher in the case of Markov and others (1994).

The developers of the Hazus-MH water system use 

data from Isoyama and Katayama (1982) and Markov and 

others (1994) to propose to estimate the serviceability index, 

s(r), as a function of break rate (breaks, not leaks, per km 

of service main pipe) using equation 12. They seem to use 

the serviceability index to measure the fraction of customers 

receiving any water service, because the software expresses 

loss of serviceability in terms of “households without water”:

 . (12) 

In equation 12, ln denotes natural logarithm, r/L denotes 

the average break rate (r main breaks per L kilometer of pipe), 

q and b are model parameters, and Φ is the standard normal 

cumulative distribution function (the y-value of the S-shaped 

curve in x–y space that depicts the probability that an uncertain 

quantity with standard normal distribution will take on a value 

less than or equal to x). Hazus-MH employs values of q=0.1 

and b=0.85, respectively, fitting the curve to Isoyama and 

Katayama’s (1982) modeling of Tokyo’s water-supply system, 

Markov and others (1994), modeling of the San Francisco 

Auxiliary Water-Supply System (a dedicated firefighting 

system), and analyses of EBMUD’s water-supply system. 

Hazus-MH’s serviceability model is illustrated in figure 4, in 

the curve labeled “NIBS.”

Thus, the Hazus-MH serviceability index might measure:

• The fraction of service connections receiving preearthquake flows, regardless of the degree of postearthquake flow received at other service connections, 

which would seem to be consistent with Isoyama and 

Katayama’s (1982) serviceability;

• The fraction of pre-earthquake flow being delivered 

after the earthquake, consistent with Markov and others 

(1994); or 

• The fraction of service connections receiving any water, as 

the Hazus-MH reports indicate.

Lund and others (2005), citing Kobe, Japan, Municipal 

Waterworks Bureau’s M. Matsushita, present a restoration 

curve for the Kobe water system after the Mw 6.9 1995 

Kobe earthquake. Tabucchi and Davidson (2008) offer an 

analogous plot for the restoration of water service in the San 

Fernando Valley after the 1994 Northridge earthquake. The 

two restoration curves are shown in figure 5. Restoration after 

Northridge appears fairly linear; Kobe less so.

Figure 4. Graph showing Hazus-MH (Federal Emergency 

Management Agency, 2012) water-pipe serviceability model and 

other models of water-pipe serviceability. Hazus-MH uses the curve 

labeled “NIBS.” AWSS, San Francisco Auxiliary Water Supply System 

(Markov and others,1994); EBMUD, East Bay Municipal Utility District; 

G&E, G&E Engineering Systems, Inc.; NIBS, National Institute of 

Building Sciences (Federal Emergency Management Agency, 2012). 

AAXXXX_fig 01

Average break rate, in breaks per kilometer

Serviceability index, in percent

0

20

40

60

80

100

0.01 0.1 1

NIBS

EXPLANATION

AWSS (simulation results 

at Cornell)

AWSS (average)

EBMUD(G&E) (large pipes)

EBMUD (G&E) (small pipes)

Isoyama and Katayama (1982) 

(lower range)

Isoyama and Katayama (1982) 

(upper range)

Lifeline Interaction

Many authors have characterized lifeline interaction 

after natural disasters. A few but not all relevant works are 

summarized here.

For ease of reference, I recall here some evidence previously 

noted—City of Winnipeg (2014) and American Water Works 

Association (2008) suggest that prerequisites for the repair of 

buried pipeline include cellular communications and electricity 

to learn about and coordinate repairs, fuel and roadway access to 

travel to and perform the repairs, site safety (especially that no 

fires, gas leaks, or electrical hazards are present), and consumable 

repair materials including pipe, fittings, repair hardware, and 

disinfecting chemicals.

Φ ( ) ( ) ( ) s r = − r L q

b

1

ln
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 207

0

20

40

60

80

100

A B

0 1 2 3 4 5 6 7 8 9 10

Time following earthquake, in weeks

Time following earthquake, in days

Water-service recovery, in percent

0

0

20

40

60

80

100

1 2 3 4 5 6 7

Figure 5. Graphs showing (A) restoration of water service to 

customers experiencing outages after the moment magnitude 

(Mw) 6.7 1994 Northridge, California, earthquake and (B) after the 

Mw 6.9 1995 Kobe, Japan, earthquake. A, Modified from Tabucchi 

and Davidson (2008); B, modified from Lund and others (2005).

Nojima and Kameda (1991) compiled instances of 

lifeline interaction in the 1989 Loma Prieta earthquake, noting 

particularly the loss of wastewater treatment because of the 

loss of electricity, and the degradation of telecommunications 

resulting from the loss of electricity and difficulty acquiring 

fuel for central offices’ emergency generators as a result of 

highway problems. See table 6 for a matrix summarizing lifeline 

interaction in the Loma Prieta earthquake. It shows that water 

supply was impaired for 18 hours in Santa Cruz because of loss 

of electric power for pumping. It also shows that electricity 

failure impaired EBMUD’s Lafayette filtration plant and its 

Oakland control center. Repairs in Santa Cruz were also impaired 

by delays transporting repair equipment over the damaged 

Oakland-San Francisco Bay Bridge. In San Francisco and Santa 

Cruz, overloaded telecommunications impaired repair efforts.

Scawthorn (1993) reviews literature and then-recent disaster 

experience on lifeline interaction in several disasters (for example, 

1989 Loma Prieta Earthquake and 1991 Oakland Hills firestorm 

in the east bay) to construct a model and analytical methodology 

for lifeline interaction. He points out that water supply in the 

1991 Oakland Hills fire was impaired in part because of breakage 

of service connections in buildings that collapsed in the fire and 

the reliance of water supply on electric power to pumps stations 

that were required to resupply ridge-top tanks. He suggests 

characterizing lifeline interactions as (1) cross-impact (impact on 

one lifeline’s function due to impairment of service to that lifeline 

by a second lifeline), (2) collocation (direct damage or impact 

on one lifeline’s function due to failure of another lifeline in a 

very proximate location), or (3) cascade (increasing impacts on a 

lifeline due to initial inadequacies, such as water-supply damage as 

buildings collapse and sever service connections). In Scawthorn’s 

(1993) quantitative model, one characterizes initial damage to a set 

of lifelines through a vector, D, of n scalar quantities, each element 

representing a fraction of customers receiving service for one of 

n lifelines if there were no interaction, that is, if only damage to 

that lifeline mattered. Lifeline interaction is quantified by an n×n

matrix denoted by L, where element Li,j (row i, column j) denotes 

the fraction of service of lifeline i that is contributed by lifeline j. 

A higher value of Li,j indicates greater reliance of lifeline i service 

on lifeline j. A value Li,j=0 indicates no interaction. The final 

functional state of the n lifelines is represented by vector F, whose 

value is given by equation 13. Element i of vector F measures 

the fraction of customers receiving service from lifeline i, where 

any reduction below Fi=1.0 is a result of initial damage D to all 

the lifelines and interaction L between them. Equation 13 is as 

follows:

 . (13)

Scawthorn offers the model but does not propose particular 

values for matrix L. Note that, because 0≤Di ≤1.0, to ensure that 

0≤Fi≤1.0, L must be constrained per equation 14:

 . (14)

The San Francisco Lifelines Council (2014) adapted 

the panel process of Porter and Sherrill (2011) to involve 

San Francisco Bay region lifeline operators in qualitatively 

characterizing the potential effects of lifeline interaction on the 

post-earthquake functionality of their systems. The authors sought 

to identify key assets and restoration schemes to prioritize postdisaster restoration and reconstruction activities for San Francisco 

and ultimately the entire region. Through panel discussion with 11 

lifeline operators, the authors identified lifeline interaction effects 

in the context of a hypothetical M7.9 earthquake on the northern 

San Andreas Fault. They propose a qualitative interaction matrix 

(table 7) that describes modes of interaction similar to Nojima 

F L = × D

∑ = ∈ { } =

L i ij 1.0 1, 2,...n

j

n

1
208 The HayWired Earthquake Scenario—Engineering Implications

Table 6. Lifeline interaction matrix in the moment-magnitude-6.7 1989 Loma Prieta, California, earthquake (modified from Nojima and Kameda, 1991).

[SF, San Francisco; BART, Bay Area Rapid Transit; EBMUD, East Bay Municipal Utility District; PBX, private branch exchange; hrs, hours; *, general 

interaction, meaning among components of the same system]

Lifeline 

type Electricity Gas Water Sewer Road Rail Telephone

Electricity * Santa Cruz gas 

explosion due 

to electricity 

comeback 

(spark ignition). 

Recovery work 

arrangement with 

electric powersupply system.

Santa Cruz: pump 

stopped for 18 hrs 

(gravity flow area 

survived; no water 

in pump-based 

supply area)

SF: power failure 

due to gas leak 

inspection, no 

water in pumpbased supply area 

and Marina district. 

No power for 

repair work.

EBMUD: short-term 

loss of power at 

Lafayette filtration 

plant. Oakland 

Control Center 

power loss, no 

service.

SF and Santa 

Cruz: 

power 

failure 

at pump 

station.

SF and Santa 

Cruz: traffic 

jam due to 

malfunction of 

traffic signal.

SF: BART 

omitted stops 

at some 

stations 

to save 

electricity.

Capacity diminished 

by use of storage 

cells. PBX 

with no battery, 

malfunction.

Pacific Bell Bush/

Pine Street office 

(SF) coolant 

trouble; no 

service for 3 hrs.

Pacific Bell 

Hollister office 

generator failure 

no service for 

3 hrs.

GTE Corp.: Monte 

Bello office (Los 

Gatos) failure of 

generator fuel 

tank; malfunction 

(6–7 hrs).

Gas SF and Santa 

Cruz: gas leak 

inspection 

before 

recovering 

electricity.

* Santa Cruz: no 

home treatment. 

Recovery work 

arrangement with 

gas supply system.

SF: road closed 

due to propane 

fire (Route 80 

westbound 

at Central 

Avenue).

Water Santa Cruz: recovery 

work arrangement 

with water-supply 

system.

* Santa Cruz: 

damage 

detection 

by analogy.

SF Marina 

District: road 

failure due to 

water leakage.

Sewer Santa Cruz: 

suspicion of 

underground water 

contamination 

due to outflow or 

crude sewage from 

pipeline.

*

Road Santa Cruz: no 

transporting 

machinery due to 

bridge damage.

Santa Cruz: 

damage 

detection 

by analogy.

* BART riders 

increased 

(October 

23, +40 

percent) due 

to Bay Bridge 

closure.

Rail *

Telephone SF and Santa Cruz: 

overload.

*
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 209

Table 7. The San Francisco Lifelines Council’s lifeline-system interdependencies matrix (modified from San Francisco Lifelines Council, 2014).[Darker shading indicating greater interaction. For lifeline operator’s dependency on other lifeline systems, read across rows. For the overall interaction and dependency on a particular lifeline system read down columns]

Lifeline Regional roads City streets Electric power Natural gas Telecom Water Auxiliary water Waste-water Transit Port Airport Fuel

Regional roads General Restoration, 

substitute

Restoration Restoration Restoration Restoration Restoration Substitute Restoration Restoration

City streets Substitute, 

restoration

General Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation, 

substitute, restoration

Collocation, 

restoration

Restoration

Electric power Restoration Collocation, 

restoration

General Restoration Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation Restoration Restoration

Natural gas Restoration Functional, 

collocation, restoration

Substitute General Restoration Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation Restoration Restoration

Telecom Restoration Functional, 

restoration

Functional, 

restoration

Restoration General Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Restoration Restoration

Water Restoration Restoration Restoration Restoration General Collocation RestorationAuxiliary water Restoration Functional, 

restoration

Restoration Restoration Functional, 

restoration

General Collocation, 

restoration

Restoration

Waste-water Restoration Collocation, 

restoration 

Functional, 

restoration

Restoration Functional, 

restoration

General Collocation, 

restoration

Restoration

Transit Substitute, 

restoration

Functional, 

substitute, collocation, restoration

Functional, 

restoration

Restoration Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation, 

general

Collocation, 

restoration

Functional, 

restoration

Port Restoration Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation, 

restoration

Collocation Collocation Collocation General Restoration

Airport Restoration Restoration Restoration Restoration Restoration Collocation, 

restoration

General Functional, 

restoration

Fuel Restoration Restoration Functional, 

restoration

Restoration Restoration Restoration Restoration General
210 The HayWired Earthquake Scenario—Engineering Implications

and Kameda (1991) and shows a degree of interaction, with 

darker shading indicating greater interaction, like a higher value 

in Scawthorn’s (1993) matrix. The authors found that restoring 

water supply in San Francisco depends significantly on city streets, 

telecommunications, and fuel and to a lesser extent on regional 

roads, electric power, and the Port of San Francisco. The matrix 

characterizes the mode of each interaction, with five possible 

modes. The following quotations are taken from San Francisco 

Lifelines Council (2014) but the interpretations are mine:

• “Functional disaster propagation and cascading 

interactions from one system to another due to 

interdependence.” This means that a system relies on 

one or more other systems to operate, each of which 

can rely on still others. I refer to these other systems as 

“upstream,” in the sense that failure of an upstream system 

flows or cascades down to the system in question and 

causes its failure. For example, consider water service 

in a pressure zone that is supplied from tanks whose 

source is water pumped from lower elevation. Water 

service in that pressure zone is functionally dependent 

on electricity, which may be functionally dependent on 

natural gas. Failure of fuel supplies or electric generation, 

transmission, or distribution propagates or cascades to 

cause water-supply failure through interdependence.

• “Collocation interaction, meaning physical disaster 

propagation among lifeline systems.” This means that one 

or more elements of the system in question are located 

close to one or more elements of another system and that 

the other system can fail in such a way that an area around 

the failure can impair the system in question. For example, 

fiber optic cable that serves the telecommunications 

network may be installed in a conduit on a roadway bridge. 

Excessive displacement of the bridge, such as a result of 

settlement of an abutment, can sever the fiber conduit. 

• “Restoration interaction, meaning various hindrances in 

the restoration and recovery stages.” This means that one 

or more elements of the system in question are located 

close to one or more elements of another system, and 

that repairs to the other system can damage or hinder the 

repair of the system in question. For example, consider a 

water main (the system in question) that is located above a 

damaged sewer line. Repair to the sewer line could require 

the temporary removal of or inadvertently lead to damage 

to the water main.

• “Substitute interaction, meaning one system’s disruption 

influences dependencies on alternative systems.” This 

means that the system in question may have substitutes 

(alternative systems), and that disruption of one of the 

alternatives can affect the system in question. For example, 

damage to the San Francisco-Oakland Bay Bridge in the 

Mw 6.9 1989 Loma Prieta earthquake caused a 32-percent 

increase in Bay Area Rapid Transit (BART) ridership 

during October and November 1989 (Bay Area Rapid 

Transit District, 2015).

• “General interaction, meaning between components of the 

same system.” Nojima and Kameda (1991) use an asterisk 

(*) to mean the same thing. This means that impairment 

of elements of the system in question can affect other 

elements of the same system. For example, overturning of 

electrical switchgear in a pumping station can cause the 

pumps to fail.

Pipeline Damage in Afterslip

Several authors have considered lifeline damage due 

to afterslip, which is fault slip immediately following an 

earthquake rupture that involves creep much faster than the 

interseismic rate. According to Aagaard and others (2012), 

“Afterslip develops very quickly and can have similar impacts 

as coseismic slip, with the added complexity that the slip 

continues for months to years, albeit with a decreasing rate.” 

They discuss afterslip in various Hayward Fault earthquake 

scenarios, including the one adopted for use in HayWired—

“Afterslip makes a substantial contribution to the long-term 

geologic slip and may be responsible for up to 0.5–1.5 m 

[meters] (median plus one standard deviation) of additional slip 

following an earthquake rupture.” The authors offer a powerlaw expression for afterslip as a function of time t, denoted D(t), 

as follows in equations 15–19 (s, second):

 , (15)

 , (16)

 , (17)

 

 

 , (18)

 

 

 , (19)

where T is referred to as the afterslip time constant, taken here 

as 365 days per Aagaard and others (2012). For example, with 

Mw=7.0, equation 19 leads to Cmedian=0.0984. With T=365 days, 

equation 18 leads to a=5.47. With Dtotal=1.86 meters (m) and 

Dcoseismic=0.83 m, equations 15, 16, and 17 produce A=0.608 m, 

B=1.25 m, and the estimate of slip versus time shown in figure 6.

O’Rourke and Palmer (1996) point out that understanding 

observations of pipeline damage at fault crossings requires 

estimating fault slip from the time of pipeline installation to the 

time of its excavation for inspection after an earthquake, including 

preseismic slip, coseismic slip, and afterslip. Treiman and Ponti 

(2011) suggested that afterslip could realistically account for 40 

percent of the total surface slip in the Coachella Valley, California, 

resulting from a M7.8 earthquake on the southern San Andreas 

Fault. The afterslip could aggravate damage to the Coachella 

( ) ( )

= + × +D t A B

T t

1

1 C

= ( ) − A × − × aD a D 1

1 total coseismic

= ( ) −

− B × − a

a

D D

1 total coseismic

a = +

T 1

1s

C

C M median = − 0.881 0.111× w
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 211

Figure 6. Graph showing afterslip versus time after a 

moment-magnitude-7.0 mainshock as derived from equations 

15 through 19 (see text).

Canal, railroads, fiber optic cable, electrical lines, gas and oil 

pipelines, and highways.

Hudnut and others (2014) measured deformation in a 

temporarily decommissioned 26-inch diameter gas pipeline 

that crosses the fault rupture involved in the 2014 South Napa 

earthquake. They observed that the pipeline was “subtly warped 

more than 35 cm [centimeters] by fault offset, most of which 

accumulated as afterslip that is still continuing as of 3 months after 

the earthquake.” They argue that “Lifeline performance in future 

events, with both coseismic slip and afterslip, deserves additional 

consideration.”

Measuring Loss of Resilience

Bruneau and others (2003) propose to measure the loss 

of resilience as the area above the curve Q(t), where Q(t) is 

defined (somewhat vaguely) as the “quality of the infrastructure 

of a community” They denote a quantity they call “community 

earthquake loss of resilience” by R and calculate it as in 

equation 20:

 

 , (20)

where t=0 and t=t

1 denote the times of the initiating event and 

the time of full restoration, respectively. For brevity, I refer to 

R more simply as the loss of resilience. Bruneau and others 

(2003) do not define t=0 and t=t1 precisely. I define t=0 here 

as the time of the first earthquake in the earthquake sequence 

0.0

0.5

1.0

1.5

2.0

0.00001 0.001 0.1 10 1,000

Slip, in meters

Time after mainshock, in days

under consideration, and I define t

1 as the time when Q(t)=1 

after the last earthquake in the sequence under consideration. 

Let Q(t) measure the fraction of water customers receiving 

at least an adequate degree of service at time t, meaning 

sufficient water flow and pressure at the tap for drinking (even 

if it needs to be boiled first), bathing, and using toilets. R has 

units of time, and as applied here, can be seen here as the 

expected value of the time that an arbitrary customer receives 

less water than a useful degree of service.

To be clear, a reduction in the loss of resilience indicates a 

briefer average time that an arbitrary customer lacks adequate 

service, but I will not equate a reduction in the loss of resilience 

with an increase in resilience. In Bruneau and others’ (2003) 

terminology, resilience is not a quantity but rather a quality 

that means “the ability of the system to reduce the chances 

of a shock, to absorb a shock if it occurs (abrupt reduction of 

performance) and to recover quickly after a shock (reestablish 

normal performance).” Resilience is not the mathematical 

complement of the loss of resilience.

Methodology

Using the brief literature review described above as a 

basis, I now turn to the proposed methodology. The methodology used in this chapter to evaluate water-network resilience 

for the HayWired scenario is discussed below.

Overview of the Methodology

A lifeline earthquake performance and restoration model 

typically involves the following analytical elements:

1. Asset definition, in which the system is described in terms 

of nodes and links. Nodes have a location, flow capacity, 

sometime a value (for example, replacement cost), and 

an asset category that associates the component with one 

or more relations among environmental excitation (for 

example, severity of shaking) and loss (for example, in terms 

of dollars, deaths, downtime, or some combination). Links 

connect nodes. They have a path, sometime a direction, flow 

capacity, sometimes a value, and an asset category. The assets 

in question here are defined in the San Jose Water Company 

case study (described later in this chapter).

2. Hazard model, relating geographic location to 

environmental excitation. In the case of earthquake hazard, 

the hazard model typically includes a mathematical 

idealization of seismic sources in the region, their locations, 

the frequency with which they can produce earthquakes 

of various magnitudes, and one or more ground motion 

prediction equations to relate earthquake magnitude and 

location to shaking and other site effects. In the present 

study, the hazard model is presented elsewhere. Briefly, it 

is a physics-based model of the San Francisco Bay Area, 

depicted in Aagaard and others (2010a, b).

R Q = − ∫ ( ) 1 ( )t dt

t

0

1
212 The HayWired Earthquake Scenario—Engineering Implications

3. Hazard analysis, in which one evaluates the hazard model 

for one or more realizations of an earthquake. In the present 

analysis, I use the realization from Aagaard and others 

(2010a, b) depicting a Mw 7.0 rupture of the Hayward Fault 

north and south segments with an epicenter under Oakland. 

Accompanying the model of shaking from the mainshock 

are estimates of liquefaction probability, landslide 

probability, coseismic slip, and afterslip associated with the 

mainshock, along with shaking in each of a sequence of 16 

aftershocks of M5.0 and greater, as described in Wein and 

others (2017).

4. Vulnerability model (described later in this chapter), which 

relates environmental excitation at a particular location to 

the potentially uncertain loss in each of a set of asset classes. 

5. Damage analysis (described later in this chapter), in which 

one evaluates the vulnerability model for each lifeline 

component at the level of environmental excitation to which 

the component is subjected.

6. Restoration model (described later in this chapter), which 

characterizes the time to restore the damaged components 

to their pre-disaster condition, and calculates the degree 

of service at each of many points in time. (The restoration 

model developed for the HayWired scenario is new. It 

includes a new method for quantifying the effects of lifeline 

interaction. It includes an initial assessment period suggested 

by engineers of the East Bay Municipal Utility District, 

along with a period during which repair crews and other 

resources ramp up from an initial, in-house quantity to one 

that includes mutual aid.)

7. Aftershock analysis, in which one inserts one or more 

aftershocks into the restoration process, which in a sense 

restarts the hazard, damage, and restoration analyses with a 

still-damaged lifeline system.

Vulnerability Model

Here, “vulnerability model” means a mathematical 

formulation of the relation between loss (usually normalized by 

quantity; for example, pipeline breaks and leaks per 1,000 feet, 

ft, of pipe) and environmental excitation (for example, degree of 

PGV).

Basic Elements of a Vulnerability Model

These relations often apply to classes of components that 

share common engineering features (for example, pipe sharing 

common material, diameter range, or joint type). All specimens of 

the class are assumed to be interchangeable and indistinguishable 

for purposes of estimating loss. A vulnerability model can be 

deterministic, providing for example only a mean estimate of loss 

conditioned on excitation, or probabilistic, providing both a mean 

value and error term. Some terms need to be defined:

• yi(x), the expected value of the degree of loss experienced 

by a component of class i when subjected to excitation x. 

One can refer to yi(x) as the mean vulnerability function 

for class i. 

• εi(x), the error term for class i. The error term can be 

constant for class i or it can depend on degree of excitation 

x. The error term has unit mean and usually has some 

parametric distribution, such as lognormal with a specified 

standard deviation of the natural logarithm of the error 

term, referred to here as the logarithmic standard deviation. 

The vulnerability model can provide mean vulnerability 

functions and error terms for one or more modes of damage 

j, such as damage by wave passage and damage by ground 

failure due to liquefaction, landslide, or fault offset. 

• yi,j(xi,j)=the mean loss to a component i of a specified 

class in damage mode j when component i is subjected to 

mode-j excitation xi,j, such as the peak ground velocity to 

which a particular segment of pipe is subjected. 

• εi,j(xi,j)=the mode-j vulnerability error term for the class 

to which component i belongs, when the component is 

subjected to excitation xi,j. 

• Yi,j(xi,j)=the uncertain normalized loss is denoted by (for 

example, uncertain total pipeline breaks and leaks per 

1,000 linear feet of pipe), where the index i refers to the 

component class to which component i belongs, j refers 

to the damage mode under consideration (for example, 

pipeline breaks and leaks per 1,000 linear feet of pipe as a 

result of wave passage), and xi,j is as previously defined. 

The uncertain normalized loss is calculated as:

 . (21)

The vulnerability model comprises the set of functions y and 

ε, the component classes to which they refer, and the domain of 

excitations for which the functions are valid.

Selecting a Vulnerability Model for a Pipeline 

Network

Several authors have created and published pipeline 

vulnerability functions; a few are discussed above in the Literature 

Review. There are no commonly accepted rating systems for 

pipeline vulnerability functions, but it seems reasonable to choose 

among competing vulnerability functions based on at least the 

following criteria:

• Vulnerability functions reflect diverse conditions—pipe 

material, diameters, joint systems, age, and corrosivity 

similar to the conditions where the vulnerability functions 

will be applied.

• Vulnerability functions are drawn from numerous damage 

data.

Y x( ) = × y x( ) ε ( ) x i j , ,i j i j , ,i j i j , ,i j
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 213

• Vulnerability functions are drawn from ground-motion 

levels reaching as strong as those where they will be 

applied.

• The articles in which the vulnerability functions are 

presented are respected, highly cited, and frequently used 

for similar applications, which here means estimating 

and depicting realistic outcomes of a hypothetical U.S. 

earthquake (table 8).

O’Rourke and others (2014) have been more cited in 

far fewer years than Eidinger (2001), suggesting somewhat 

greater credibility. Maximum PGV values are greater in the 

O’Rourke work, suggesting greater applicability in strong 

shaking. However, Eidinger (2001) draws on a larger dataset 

and his vulnerability functions cover both wave passage and 

ground failure. For these reasons, it seems the Eidinger vulnerability functions are most suited to the present problem.

Thus, for wave passage, one can use equation 3 to 

calculate repair rate with probability p of nonexceedance, or 

alternatively equation 4 for the mean repair rate. However, 

there is a problem applying a liquefaction and landslide model 

that requires permanent ground displacement to HayWired, 

as in Eidinger’s (2001) model equations 5 or 6. The problem 

here is that PGDs are unavailable for the HayWired scenario. 

HayWired instead has liquefaction probability and landslide 

probability. How to apply Eidinger’s ground-failure model 

without an estimate of PGD?

The solution employed here takes advantage of the fact 

that equation 6 is not very sensitive to PGD. One can see the 

limited sensitivity in the small power to which PGD is raised, 

0.319. At the same time, the logarithmic standard deviation 

β=0.74 in equation 5, which gives the marginal distribution of 

repair rate, is very large, suggesting the 90th percentile bounds 

differ by more than an order of magnitude. In this case, the 

95th and 5th percentiles of repair rate conditioned on PGD 

differ by a factor of 11.4.

So Eidinger’s (2001) liquefaction equation tells us that an 

increase in PGD from 1 inch to 10 inches only increases mean 

repair rate by a factor of 2. See figure 7; for K2=1, the repair 

rate for PGD=1 inch and the repair rate for PGD=10 inches 

are 1.4 and 2.9 repairs per 1,000 linear feet, respectively. 

At either point, PGD=1 inch or 10 inches, the uncertainty 

in repair rate is much greater, that is, even if I knew PGD, I 

would still be very uncertain as to repair rate. The apparent 

improvement in accuracy gained by estimating liquefactioninduced or landslide-induced PGD would be illusory. That is 

Table 8. Comparison of criteria for selecting pipeline vulnerability functions.

[PGV, peak ground velocity; PGD, permanent ground displacement; cm/s, centimeter per second; NA, not applicable]

Source Diverse pipe Repairs Max PGV Max PGD Citations

O’Rourke and Ayala (1993) Yes Unknown 50 cm/s NA 87

Honneger and Eguchi (1992) Yes Unknown Unknown Unknown 21

Eidinger (2001) Yes 3,350 52 cm/s 110 in 18

O’Rourke and others (2014) Yes 2,051 80 cm/s NA 20

not to say that it would not be a little better to estimate PGD, it 

just would not be much better.

In light of the very high uncertainty in repair rate and the 

relatively modest sensitivity of the vulnerability function to PGD, 

I assume a reasonable moderate PGD associated with liquefaction, 

say 6 inches, and rewrite equations 5 and 6 using liquefaction 

probability, as shown in equations 22 and 23:

 , (22)

 , (23)

where PL denotes probability of ground failure, either through 

liquefaction, landslide, or fault offset. The equation estimates 

mean repair rate per 1,000 linear feet of pipe.

How does one sum repair rates from wave passage and 

ground failure if one uses Eidinger’s (2001) model? He says that 

“wave propagation effects are masked within the more destructive 

Figure 7. Graph showing Eidinger’s (2001) pipe liquefaction vulnerability 

(Rl) for K2=1.0, mean and 90-percent bounds (see equations 5 and 6). Factor 

K2 accounts for pipe material, joints, soil corrosivity, and pipe diameter.

0.0

2.5

5.0

7.5

10.0

0 5 10 15 20

Breaks per 1,000 linear feet of pipe

Permanent ground deformation, in inches

Rl

(0.95)

Rl

(0.05)

Rl

Φ

Φ

( )

( )

( ) ( )

( )

= × × ⋅× × ×

= × × × ⋅

−

−

R P p K P p

K P p

, 1.06 6 exp 0.74

1.88 exp 0.74

l L 2 L

0.319 1

2 L

1

( ) = × × 6 ×

= × ×

R P K P

K P

1.39

2.46

l L 2

0.319

L

2 L
214 The HayWired Earthquake Scenario—Engineering Implications

effects of [peak ground displacements].” If one knew where 

ground failure occurs, one would ignore the wave-passage model 

so as not to double-count it. The problem here is that Eidinger’s 

(2001) empirical model of damage due to liquefaction probably 

includes some damage that was caused by wave passage, but he 

does not know which breaks and leaks were caused by which 

peril. In zones of liquefaction, he treats all damage as caused by 

liquefaction. That is, his empirical relation for damage in zones of 

liquefaction include an unknown (but probably small) fraction of 

damage caused by wave passage.

As a result, one must not double-count wave passage damage 

by applying both the liquefaction and wave-passage models in 

zones of liquefaction. To eliminate double-counting, I modify 

the wave-passage model of equations 3 and 4 by multiplying the 

repair rate by a factor (1–PL), where PL denotes ground-failure 

probability. After eliminating double-counting, one can sum the 

wave-passage and ground-failure models as shown in equations 

24 and 25. In both equations, R denotes repair rate in repairs per 

1,000 ft of buried pipe, PGV is peak ground velocity in inches per 

second, and p denotes nonexceedance probability. In equation 24, 

R gives repair rate with nonexceedance probability p, whereas 

equation 25 gives mean (average) repair rate. The coefficients are 

smaller in equation 24 than they are in equation 25 because the 

median is smaller than the average for a lognormally distributed 

random variable, and the difference depends on the logarithmic 

standard deviation:

 

 , (24)

 

 . (25)

For damage resulting from fault offset, one could apply 

Eidinger’s (2001) proposed model. Given the absence of 

supporting data, the relatively small number of breaks that occur 

at the fault trace compared with breaks and leaks that occur as a 

result of wave passage and liquefaction, and the desire to model 

breaks as a function of offset at the location of the pipe rather than 

average offset over the entire trace; a simpler model is adopted 

here. I assume that any pipe segment that crosses a fault is broken 

if the fault offset exceeds 6 inches and use the same threshold 

regardless of pipe material, jointing, and angle subtended by 

the fault and pipeline alignment. The fault trace is treated as a 

collection of line segments rather than as a zone on the surface 

of the Earth with a finite width. The offset therefore is lumped 

at the line rather than distributed over the width of the zone. 

Mathematically, let Zi denote a binary variable to indicate that pipe 

segment i is damaged by fault offset (1 if true, 0 if false), d denotes 

the fault offset distance, df denotes the threshold of fault offset 

distance that produces damage, and I(⋅) is the indicator function 

(1.0 if the value in parentheses is positive, 0.0 if negative), then

 , (26)

where df=6 inches, consistent with the fault offset that Eidinger 

(2001) equates with a 50-percent failure probability for all 

segmental pipe. One could use a more refined model such as 

American Society of Civil Engineers (ASCE) (1984), which 

applies engineering first principles of stress and strain, the 

engineering characteristics of pipe and backfill, the geometry 

of how a pipe crosses a fault, and other factors. In the context 

of an earthquake-planning scenario in which we care about the 

total number of pipe breaks and leaks over an entire strongly 

shaken region, such an analysis seems like excessive effort for 

a relatively small contributor to overall damage. Furthermore, 

considering the necessary assumptions about unknown backfill 

characteristics and probably other model parameters, such an 

analysis would probably provide illusory precision.

Damage Analysis (Number of Repairs Required)

A damage analysis applies the vulnerability model and 

the hazard model to the assets under consideration to estimate 

degree of damage or loss. An example would be the total 

number of pipeline repairs required when a particular pipeline 

network is affected by a particular earthquake.

Basic Elements of a Damage Analysis

I employ a common general formulation for number of 

repairs required for a system of ni discrete components (for 

example, segments of pipe) that can each be uniquely identified 

with a class of components (for example, type of pipe).

Each component i has an associated quantity or value Vi (for 

example, length of pipeline segment), and is assumed to be subject 

to damage from up to nj modes of damage (for example, wave 

passage and liquefaction). Each combination of component class 

and mode of damage is assigned a vulnerability model yi,j(xi,j) and 

εi,j(xi,j) as previously defined. Let R denote the total uncertain loss 

(for example, total number of instances of pipeline damage). It is 

estimated as shown in equation 27:

 

 . (27)

Equation 27 assumes that damage to one component or in 

one model is independent of damage to other components or in 

other modes. That is, that the degree of damage to component 

i in mode j is unaffected by damage to a different component, 

and that if component i is damaged in one mode, it can also be 

damaged in another mode and that the losses resulting from 

the two modes of damage simply sum.

In the case of water-supply pipelines, one implication of 

this assumption of independence is that it assumes that repairs 

Z I i = − ( ) d df

R V = × ∑∑ y x( )×ε ( ) x i i j i j

j

n

i

n

, , i j , ,i j

j i

Φ

Φ

( )

( )

( ) ( ) ( ) ( )

( )

( )

( )

= − × +

= − × × × ×

⋅ + × ×

× ×

−

−

R PGV P p P R PGV p R P p

P K PGV

p K P

p

, , 1 , ,

1 0.00187

 exp 1.15 1.88

 exp 0.74

L L w L L

L 1

1

2 L

1

( ) ( ) ( ) ( )

( )

= − × +

= − × × ×

+ × ×

R PGV P P R PGV R P

P K PGV

K P

, 1

1 0.003623

 2.46

L L w l L

L 1

2 L
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 215

are spaced widely enough apart that it makes sense to repair 

individual breaks or leaks, at least initially, rather than to 

remove and replace pipe and thus repair two or more instances 

of damage with a single repair.

Applying the Damage Analysis to a Water-Supply 

System

Applying equation 27 to water-supply pipelines using 

Eidinger’s (2001) vulnerability model, and adding an additional 

term for fault crossings, one can estimate mean total number of 

repairs r as shown in equation 28:

 

 

 , (28)

where i is an index to pipe segments, n is the total number of 

segments in the network, K1,i and K2,i denote the values of K1 and 

K2 for pipe segment i, PGVi is the peak ground velocity to which 

segment i is subjected, PL,i denotes the ground-failure probability 

at pipe segment i, Li is the length of pipe segment i in thousands 

of linear feet, I(⋅) is an indicator function that takes on the value 

1.0 if the expression in parentheses is positive, 0.0 if negative, di

is the fault offset to which a segment of pipe i is subjected, and df

is the offset at which breakage occurs. Here, I propose to take df

as deterministically equal to 6 inches (15 cm). Note that as long 

as pipe segments i are relatively short, less than a few hundred 

meters, there should be little difference between shaking at the 

ends and thus little error introduced by discretizing a pipeline 

network in this way.

Because the present analysis does not require a probabilistic 

estimate of loss, I ignore the error term e and deal only with the 

expected value of loss. I use the lower-case r in equation 28 to 

indicate a deterministic value rather than the upper-case R of 

equation 27 that stands for an uncertain quantity.

To carry out equation 28, one uses a geographic information 

system (GIS) to create a table of system components; for 

example, a table of pipe segments. Components are listed in 

rows. For each component, assign an identifier, determine its 

quantity (for example, its length), assign it to a class that has 

one or more vulnerability or fragility functions (for example, 

Eidinger’s, 2001, classes that group water-supply pipe by 

material, joint, soil corrosivity, and diameter), and determine 

its location (for example, the latitude and longitude of a pipe 

segment midpoint). Then using the GIS, look up the groundmotion parameter values xi,j. Equation 28 can then be calculated 

for each component (each row) and the losses summed over all 

rows to calculate the expected value of loss r (for example, the 

number of instances of pipeline damage requiring repairs).

Breaks or Leaks?

Lund and Schiff (1991) define leaks and breaks for purposes 

of compiling damage data. Under their definition, a pipe with a 

leak continues to function with minimal loss of service, whereas a 

pipe with a break completely loses function. It seems as if another, 

equivalent definition is that a pipe break separates a pipe segment 

into two, and a leak only partially fractures a pipe. Hazus-MH 

assumes an 80 percent/20 percent break/leak ratio for liquefaction 

and 20 percent/80 percent breaks/leaks ratio for wave-passage 

damage. The authors of the technical manual do not cite a source 

for their choices.

Lund and Schiff (1991) found that, among all pipeline 

failures in the Mw 6.9 1989 Loma Prieta earthquake, where it 

was known whether the failure was a break or a leak, it was 

more common for the pipeline to break (336 repairs, 71 percent) 

than to leak (140 repairs, 29 percent). A study by Ballantyne and 

others (1990) of pipe damage in the Mw 6.7 1949 Olympia and 

Mw 6.7 1969 Seattle (Washington), Mw 5.6 and 5.7 1969 Santa 

Rosa (California), Mw 6.7 1971 San Fernando Valley, Mw 6.2 

1983 Coalinga (California), and Mw 5.9 1987 Whittier Narrows 

earthquakes, found that ground failure resulted in a 50 percent/50 

percent break/leak ratio, and absent ground failure, the ratio was 

15 percent/85 percent breaks versus leaks. Because the present 

model allows one to distinguish between repairs associated with 

ground failure versus wave passage, and because Ballantyne 

and others (1990) are highly regarded and offer their evidence, I 

employ their ratios.

Degraded Vulnerability?

The model presented here applies the same vulnerability 

functions to the same system map in the aftershocks that it 

applies to the mainshock. Is it correct to do so? Perhaps I 

should consider a system that has already been degraded by 

the mainshock or a large aftershock to be weaker. Perhaps the 

mainshock causes small undetected leaks or incipient breaks 

that become large leaks or breaks in an aftershock. However, 

there does not seem to be sufficient research available to 

support explicitly modeling system degradation—making 

the mathematical model of the system more vulnerable in 

aftershocks than before the mainshock. This is a topic deserving 

of future research.

Restoration Model

As used here, a restoration model relates the damage (the 

output of the damage model) to a system’s functionality over time. 

It usually depicts a system’s return to its predisaster condition.

Basic Elements of the Lifeline Restoration Model

Functionality can be measured a variety of ways, but in 

the case of a utility such as a pipeline network, it is common 

∑ ∑ ∑

∑

∑ ∑

( )

( )

( ) ( )

( )

= × + × + −

= − × × × ×

+ × × × + −

= = =

=

= =

r R PGV L R P L I d d

P K PGV L

K P L I d d

1 0.003623

 2.46

i i

i

n

i i

i

n

i

n

i i i

i

n

i

i i i

i

n

i

n

w

1

l L,

1 1

L, 1,

1

2, L,

1 1

f

f
216 The HayWired Earthquake Scenario—Engineering Implications

to measure functionality in terms of the number of service 

connections that receive the lifeline service as a function of time. 

I do not offer a general mathematical formulation of a lifelinerestoration model, but merely list its elements here, and then 

propose a particular solution for water-supply pipeline systems. A 

lifeline-restoration model includes the following elements:

• A model of the level of functionality immediately after the 

disaster

• A model of the repair resources—crews and supplies—

available over time.

• A model of the number of services restored by each repair

• A model of the elapsed time after each repair

• Ideally, a model of lifeline interaction (that is, accounting 

for how damage or restoration of other lifelines affects or 

delays damage or restoration of the lifeline in question).

Number of Services Lost Because of Earthquake

A hydraulic or connectivity analysis similar to those of 

Khater and Grigoriu (1989) or Applied Technology Council 

(1991) is too demanding for present purposes. I use the same 

simplification as Hazus-MH does. As noted above in the 

section on Serviceability of Water Supply, Hazus interprets the 

serviceability index, which measures the drop-in water pressure 

as a function of the average number of pipe breaks (not leaks) 

per kilometer of pipe, as a proxy for the fraction of customers 

receiving service. I employ the serviceability index the same 

way—immediately after an earthquake, when the number of 

repairs required is r, L is the kilometers of pipe in the system, and 

M is the total number of customers, then the number of services 

available immediately after the earthquake is given by M times the 

serviceability index of equation 12. Let V0 denote the number of 

services available after the earthquake and before repairs begin as 

shown in equation 29:

 , (29)

where M is the total number of services, r is the number of main 

breaks (not leaks), L is the length of pipe in the distribution system 

(kilometers), q=0.1, and b=0.85. The parameter q determines 

the number of breaks (not leaks) per kilometer (0.1) at which 

V0 reaches 0.5M. The parameter b determines the width of the 

S-shaped curve labeled NIBS in figure 4. How long does it take to 

complete n repairs?

Number of Services Restored by the nth Repair

Equation 29 suggests one approach to estimating service as 

repairs proceed—measure the remaining repairs r as a function of 

the damage caused by the earthquake sequence, reduced by the 

number of repairs, and evaluate services available after n repairs 

have been completed as shown in equation 30, which I will refer 

to as the serviceability-index approach:

 . (30)

Or one could model services as being restored in 

proportion to the number of repairs remaining, as shown in 

equation 31. I refer to equation 31 as the proportional approach.

 . (31)

A more general approach is suggested by conversations 

with engineers of EBMUD. They indicated that their repair 

strategy in an earthquake would be to focus most of EBMUD’s 

resources to repair water-transmission lines that serve large 

areas, then smaller diameter distribution lines that serve smaller 

numbers of customers, and so on. The strategy would depend 

on how parts of the system, which may have been impacted 

by damage in large diameter pipes, could first be isolated to 

continue to maintain services to as many customers as possible 

by rerouting water using a combination of temporary system 

such as portable pumps and flexible hoses. If one were to plot 

a restoration curve with the fraction of customers receiving 

service on the y-axis and time after the earthquake on the x-axis, 

then a plot for EBMUD’s strategy would maximize slope as 

soon as repairs begin. The slope might increase if the number 

of crews increases, but with constant resources, the slope will 

decrease as individual repairs restore fewer and fewer services. 

Equation 32 would have such a form for values of 0<a<1. The 

smaller the value of a, the more the restoration curve would rise 

quickly early. Setting a=1 in equation 32 yields the proportional 

repair-restoration approach of equation 31. I refer to equation 32 

as the power approach.

 . (32)

If I assume that repairs after the 1994 Northridge and 1995 

Kobe earthquakes were completed at a constant pace, then the 

power approach with a=0.67 resembles the observed restoration of 

water service in the San Fernando Valley after the 1994 Northridge 

earthquake (fig. 5A), whereas the power approach with a=0.33 

resembles restoration after the Kobe earthquake (fig. 5B). Figure 8 

shows the three approaches all on the same plot (with two curves 

for the power approach, with a=0.33 and a=0.67). The y-axis is 

normalized by pre-earthquake number of services, and the x-axis is 

normalized by number of pipeline repairs.

Of the three, the power approach matches the two 

earthquakes the best, proportional next best, and serviceabilityindex approach the worst. There may be many other reasonable 

approaches, but considering the three examined here, I will 

employ the power approach with the more conservative of the two 

a-parameter values considered here, that is, a=0.67.

V n( ) = + V M( ) − × V n

r

a

0 0

Φ

= × ( )

= × − ×

V M s r

M

r

L q

b

1

ln

0

Φ

β ( ) = × −

−

× V n M

r n

L q 1

ln

V n( ) = + V M( ) − × V n

r 0 0
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 217

Figure 8. Graph showing parametric water-supply 

restoration curves plotted using equation 32, annotated with 

curves from the moment magnitude (Mw) 6.7 1994 Northridge, 

California, the Mw 6.9 1995 Kobe, Japan, earthquakes. The 

y-axis is normalized by pre-earthquake number of services, 

and the x-axis is normalized by number of pipeline repairs. 

Variables are—a, power-approach exponent; n, repairs 

completed; r, remaining repairs. 

Figure 9. Graphs showing pipe repair times based on data from Schiff (1988). A, all pipe repairs; B, pipe repairs excluding repairs 

to large diameter pipe. Stair-step lines represent Shiff’s (1988) data; curved lines are best fits.

Repair progress, n/r

Proportional

a = 0.33

a = 0.67

Fraction of water service restored

0.00

0.00

0.25 0.50 0.75 1.00

0.25

0.50

0.75

1.00

Serviceability

Kobe

EXPLANATION

Northridge

0.00

0.25

A B

0.50

0.75

1.00

0 5 10

Repair time, in hours

Cumulative probability

0 5 10 15 20 15 20

Repair Resources and Repair Rate with Lifeline 

Interaction

Now that I can estimate the number of services available 

after completing n repairs, I consider how long it takes to perform 

n repairs.

The section above on Time to Repair Pipe Leaks and Breaks 

summarizes a few sources of pipe repair-time information—an 

empirical model of repair time per break or leak, an empirical 

model of regional repair time as a function of regional damage 

rate, and expert opinion of repair time that generally agrees with 

the empirical evidence, albeit slightly lower both in terms of 

lower mean repair time and narrower confidence bounds. Loss 

estimation practitioners generally prefer empirical models with 

explanatory power; for this reason, I employ Schiff’s (1988) 

pipeline repair data.

Schiff’s repair data show an average repair time of 7.6 hours 

and a standard deviation of 5.3 hours. Staff of the San Jose Water 

Company found that figure to be reasonable (J. Walsh, San Jose 

water Company, oral commun., October 14, 2015). A lognormal 

distribution with median repair time of 6.5 hours and logarithmic 

standard deviation of 0.70 fits the data sufficiently well to satisfy 

the Lilliefors (1967) goodness of fit test, as shown in figure 9A. 

Separating the data for the small-diameter pipe repairs from 

the data for two large-diameter pipe repairs (24-inch damage 

instances, requiring 12 and 20 hours, respectively), the smalldiameter pipe median and logarithmic standard deviation are 6.1 

hours and 0.58, respectively, as illustrated in figure 9B. Schiff 

(1988) offers too few samples of large-diameter pipe repair time to 

derive an empirical distribution, so I assume a median of 16 hours 

and a logarithmic standard deviation of 0.6.
218 The HayWired Earthquake Scenario—Engineering Implications

The LADWP estimates of repair duration for distribution 

pipelines (Tabuchhi and others, 2010) generally agree with actual 

earthquake experience reported by Schiff (1988). However, they 

seem to underestimate uncertainty, with lower and upper limits 

that include only 70 percent of the repairs reported by Schiff, 

omitting the lower and upper 15 percent of repair times of figure 

9A. They are also slightly optimistic, with modes at the 20th and 

40th percentiles of repair times in figure 9A.

It is difficult to compare the Hazus repair times with Schiff 

(1988) or Tabucchi and others (2010) because the former measures 

repair time per worker and the latter two measure repair time 

per repair. However, assuming a crew size of four, Hazus’ perworker repair times equate with 6 to 18 hours, or the 35th and 90h 

percentiles of figure 9A.

For a deterministic model, it seems reasonable to use the 

mean estimate (7.6 hours per repair per crew, or 0.32 days per 

repair per crew) for small-diameter pipe repairs (here, assuming 

crews work 12 hours on, 12 hours off, until repairs are completed.

When will crews become available? As discussed earlier, 

public and private water agencies plan to provide mutual 

assistance for emergencies. CalWARN (California Water/

Wastewater Agency Response Network, n.d.) and East Bay 

Municipal Utility District (2014) report how three San Francisco 

Bay region water agencies dispatched teams to assist in the 

repair of water-supply pipelines in the City of Napa after the 

2014 South Napa earthquake. The assistance took 24 hours to 

arrive, which suggests a delay in the arrival of mutual aid from 

across a metropolitan region. Mutual aid in a major metropolitan 

earthquake would likely come from hundreds, possibly thousands 

of miles away, and probably take longer to mobilize, arrive, 

house, and integrate into repair operations. Repair resources ramp 

up over time, and the larger the disaster, probably the longer the 

ramp-up time. It may take several days to first assess the extent 

of damage and locate leaks before actual repairs can be initiated. 

I parameterize this assessment time and time to ramp-up crews 

using a time-dependent model of the number of repair crews 

available to an agency:

• c(t)=number of repair crews operating on the day of time t.

• w(t)=crew workload, fraction of day that crews work, for 

example, 0.5 for 12 hours on and 12 hours off.

• d0=unconstrained repair duration, days per repair for one 

crew under ideal conditions, that is, without constraints on 

materials, coordination, and other prerequisites—0.32 days 

on average.

• i=an index of rate-limiting factors. In table 2, there are six 

such factors: communications, electricity, fuel, site safety 

(that is, no fire), roadway access, and repair supplies.

• t

0

=time at which the 1st repair is performed.

• t=time at which the nth repair is performed.

• g(t)=flow of a rate-limiting factor (I refer to it as a flow 

factor) at time t.

Flow factors are as follow—gi(t)=flow of rate-limiting 

factor i at time t, normalized so that gi(t)=1.0 indicates unlimited 

availability, gi(t)=0.5 indicates that the flow or supply rate of 

factor i is half of what is normally available, and gi(t)=0 indicates 

that factor i is unavailable at time t. If, for example, there is no 

limit on fuel, g of fuel is 1.0. If a utility could only fuel half its 

repair vehicles, its g-value would be 0.5. If completing a phone 

call to coordinate repairs took twice as long as normal because 

of communications network congestion, its g-value would be 

0.5. If one could not complete a phone call at all, the g-value for 

communications would be 0. In the case of a rate-limiting factor 

that is a lifeline with a number of service connections Mi and a 

number of service connections available at time t denoted by Vi(t), 

then equation 33 follows:

 . (33)

A rate-limiting factor, ui , is a constant to indicate the 

reduction in repair productivity in the absence of a resources 

required to perform a repair, also called a u-factor, and indexed by 

i. One assigns u-factors based on an estimate of the additional time 

required to carry out one repair if it is necessary to do so without 

the required resource. It is estimated as shown in equation 34:

 , (34)

where d0 is the average time required to perform a repair under 

normal conditions and dimpaired is the average time it takes to 

perform a repair when the required resource required is unavailable. For example, if a repair takes 8 hours (hr) normally, but 

it takes 9 hr in the absence of a required resource, one assigns 

u=1–8 hr/9 hr=0.11. That is, productivity drops by 11 percent 

in the absence of the required resource. Thus, ui=1.0 indicates 

that resource i is crucial to repairs—without it, repairs do not 

proceed. A u-value of 0.5 indicates that repairs proceed by half 

their normal rate when resource i is unavailable.

I denote by f(t) the repair rate (repairs per unit time) at 

time t of the nth repair and estimate it as:

 . (35)

And let τ(n,t) denote the amount of time required to perform 

the nth repair, given that it starts at time t:

 . (36)

I can now calculate F(t), the total number of repairs completed by time t+τ. It is given by equation 37: 

( ) ( ) g t = V t

M i

i

i

u = − d

d

1 0

impaired

∏( ) ( )

( )

( ) ( ) ( )

=

× × − × −

f t

w t c t u g t

d

1 1 i i

i

0

∏

τ

( ) ( )

( ) ( ) ( ) ( ) ( )

= =

× − × −

n t

f t

d

w t c t u g t

, 1

1 1 i i

i

0
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 219

 . (37)

Recall that c(t) denotes the number of crews working on the 

day of time t, ui denotes the importance of rate-limiting factor i

(such as another lifeline), gi(t) denotes the flow of rate-limit factor 

i at time t (such as the fraction of fuel required that is actually 

available at time t), d0 denotes the unconstrained repair duration, 

and r denotes the total number of repairs. 

Equation 35 treats the effect of multiple required resources as 

multiplicative rather than a simple sum, but conceivably the effect 

is greater. The loss of only one out of two redundant resources 

(for example, commercial power and emergency onsite power) 

might not hinder repairs at all, whereas the loss of both might 

entirely prevent repairs. I acknowledge that such a complication is 

possible, but for simplicity do not treat it here.

Note that for other lifelines, F(t) might be part of a ratelimiting factor. For example, communication might require water 

service for evaporative cooling to cool some central offices. 

Suppose for example that from the perspective of communication, 

water has a u-value of 0.5 (half of central offices have evaporative 

cooling) and a g-value equal to the fraction of water services 

available, that is;

 . (38)

Water might in turn rely on communications, so a time 

series of simultaneous equations would have to be solved to 

find the simultaneous serviceability of multiple lifelines and 

other resources such as consumable repair supplies over time. 

I refer to the time series of restoration curves that satisfy their 

mutual restoration rates at all points in time as the equilibrium 

restoration solution.

Ordering Lifelines to Avoid Circular Lifeline Interaction

It would be desirable to avoid having to solve simultaneous 

equations to find the equilibrium restoration solution. I introduce 

a simplification for practicality by constraining the model of 

lifeline interdependencies so that lifelines do not affect one another 

in a circle—that is, there are no pairs of lifelines i and j where j

depends on i and i depends on j, either directly or through some 

intermediate lifeline k. 

The lifeline interaction matrices presented above in the 

Lifeline Interaction section do not clearly order the lifelines; 

there is no sense that the third row is somehow more or less of 

anything than is the second row. However, to deal with circular 

interactions I introduce an order to the lifeline interaction matrix 

so that lifelines appear in it in an approximate one-way chain 

of dependence, from so-called upstream lifelines first (upper 

rows, left-hand columns) to downstream lifelines last (lower 

rows, right-hand columns). If lifeline j depends on lifeline i, 

either directly or through an intermediary, but not vice versa, 

then I refer to lifeline i as being upstream of lifeline j, and order 

i before j. In our one-way model, downstream lifelines depend 

only on upstream lifelines or on none at all, and not vice versa.

This simplification requires compromising the fidelity of 

the model, because circular interactions probably exist. It takes 

fuel to repair a road, but to deliver fuel, one must drive over 

roads. This complication is ignored here for computational 

simplicity. There may be no right way to perfectly order 

these resources, and different people may judge the proper 

order differently. I propose the following order of lifeline 

repair resources, from upstream to downstream, based on the 

following rationale:

1. Consumable repair supplies.—Without repair supplies, 

one cannot repair fuel supplies, roads, electricity, 

communications, water, or wastewater. They are 

commonly stored and do not spoil or otherwise depend 

on fuel, roads, electricity, mobile telecommunications, 

natural gas, water, or wastewater.

2. Fuel.—Without fuel for repair vehicles, one cannot 

repair roads, electricity, communications, gas, water, 

or wastewater. One cannot pump fuel until damaged 

equipment at fuel depots is repaired, which requires 

consumables, but repairs do not require roads, electricity, 

mobile telecommunications, natural gas, water, or 

wastewater to use. Admittedly without water, one cannot 

create fuel, but fuel can be transported from somewhere 

else that has water. One must also use roads to access and 

to deliver fuel; however, the road network is so redundant, 

and it is often easy enough to travel at least slowly over 

damaged roads that any dependence seems weak.

3. Roads.—To repair roads requires consumable repair 

supplies and fuel, but one can operate roads without 

electricity, natural gas, water, or wastewater. One can 

communicate with road repair crews through direct, faceto-face meeting.

4. Electricity.—To repair damaged electric generation, 

transmission, and distribution facilities requires consumable 

repair supplies, fuel, and access by roads. One can repair 

electrical systems without electricity, natural gas, water, and 

wastewater. One can communicate with electrical repair 

crews through direct, face-to-face meeting.

5. Communication, especially mobile telephones.—Damage to 

central office and cell-tower equipment requires consumable 

∫

∏

∫

( ) ( )

( )

( )

( ) ( ) ( )

=

=

= ≥

<

× × − × −

≥

≤

F t t t

f t dt t t

a t c t u g t

d

dt t t

r

0

1 1

t

t

i i

i

t

t

0

0

0

0

0

0

( ) ( ) g t = V n

M water
220 The HayWired Earthquake Scenario—Engineering Implications

repair supplies. Powering then requires electricity or fuel. 

As with fuel, the dependency of communication on roads 

is weak but the dependency of roads on communication 

seems weaker. Operating or repairing central offices and 

cell towers does not seem to require natural gas, water, or 

wastewater. An exception is that some central offices may 

employ evaporative cooling, which requires makeup water.

6. Natural gas.—The repair of damaged natural-gas 

pipelines and other components requires consumable 

repair supplies, fuel, and roads (to a modest extent). 

Repair of damaged natural-gas pipelines seems like a 

time-critical need that requires rapid communication 

and coordination, which seems to call for electricity and 

communication. To operate a natural-gas system does not 

seem to require water or wastewater. 

7. Water.—The repair of a damaged water system requires 

consumable repair supplies, fuel, and roads (to a modest 

extent). To supply water in a pressure zone that relies on 

pumping requires electricity. Repair of damaged water 

pipelines seems like a time-critical need that requires 

rapid communication and coordination, which seems to 

call for electricity and communication. To operate a water 

system does not seem to require natural gas, so the order 

of natural gas and water repairs is arbitrary. The operate 

a water system does not seem to require a functioning 

wastewater system.

8. Wastewater.—The repair of a damaged wastewater system 

requires consumable repair supplies, fuel, and roads (to 

a modest extent). To treat wastewater and to operate 

water-lift stations requires electricity. Coordinating the 

repair of damaged wastewater pipelines seems to depend 

to a limited extent on electricity and communication. To 

operate a wastewater system does not seem to require 

natural gas, so the relative order of natural gas and 

wastewater is arbitrary. To operate a wastewater system 

does not seem to require a functioning water system, so 

their relative order also seems arbitrary.

Rate-limiting Factors for Lifeline Repairs

In the present formulation, the effect of the loss of a 

repair resource is quantified by the rate-limiting factor u that 

measures the reduction in repair productivity (repairs per unit 

time) when the required resource is unavailable. In the case 

of water supply, the list of tasks required to repair a pipeline 

break or leak (table 2) indicates that the rate-limiting factors 

include communications, electricity, fuel, site safety (for 

example, no fire), roadway access, and consumable repair 

materials. How much does the loss of each resource slow 

repairs?:

• Consumables.—Without replacement pipe and fittings, 

clamps, and other components, repairs do not proceed. 

Let uconsum=1.0.

• Fuel.—Required for a repair crew to travel to the location 

of the damage, operate a backhoe to dig down to the 

water main, and to backfill the excavated area (tasks 

2, 6, and 9 in table 2). Repairs do not proceed at all 

without fuel. I therefore assign ufuel=1–8 hr/∞=1.0. That 

is, repair productivity drops by 100 percent while fuel is 

unavailable.

• Roads.—Damage to roads could delay the initial delivery 

of additional equipment and crews, but the roadway 

network is highly redundant. Let uroad=0.0.

• Electricity 1.—In the case of a water-supply system that 

relies entirely on gravity to supply water, electricity is 

required for receiving notices about damage (task 1), 

referring to GIS-based system maps (not shown in 

table 2), and powering stoplights that control traffic and 

facilitate crews traveling from repair to repair. I assume 

that the addition time required to refer to paper maps 

occurs at headquarters while repairs are ongoing and 

does not actually slow repair crews but that travel from 

repair to repair increases repair duration by 15 minutes: 

uelectr=1–8 hr/8.25 hr=0.03. That is, repair productivity 

drops by 3 percent while electricity is unavailable.

• Electricity 2.—In the case of a water-supply system with 

pumped pressure zones, repairs may require electricity to 

provide water in order to locate leaks. For a utility with 

pumped pressure zones that relies on the commercial 

electric utility to provide a fraction z of its services (that 

is, after accounting for the utility’s own emergency 

generators), I add the quantity z to uelectr as calculated 

above, that is, uelectr=0.03+z.

• Communications.—I treat this solely as cellular 

communications and assume that utilities possess or can 

quickly acquire portable radios to communicate between 

their headquarters, repair crews, and a county emergency 

operations center. Compared with cellular, using a radio 

to communicate might slow the effort of receiving notices 

about water-main damage (task 1) and contacting other 

utilities to coordinate safety (task 4). Using radios might 

reduce repair productivity slightly, but not enormously. 

I assume that radio communication would increase 

the time to perform one repair by say 30 minutes in an 

8-hour repair, suggesting ucommun=1–8 hr/8.5 hr=0.06 for 

communications. That is, repair productivity drops by 

6 percent while cellular service is unavailable.

Site safety is not discussed in the Lifeline Interaction section 

but seems worth addressing if only to dismiss it. I assume that 

fires do not alter the order in which repairs are performed but 

do prevent repairs and that gas leaks will be shut off in a matter 

of hours after the earthquake and will not substantially hinder 

pipeline repairs afterwards. Let usafety=0.0.

I tentatively assign the u-values shown in table 9. The table 

shows for example that consumables (such as pipe and clamps) 

have a u-value of 1.0 for water supply. By equation 35, u=1 means 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 221

that repairs depend so strongly on consumables that without them 

repairs halt. That is, if at some point in time t, the available supply 

runs out, g(t)=0 for consumables, and repair rate f(t) goes to 0 until 

supply is restored.

I have assigned the same u-values to other lifelines that 

I have proposed for water, with one exception. It seems as if 

restoring mobile telephone service (under the label of communication) is more dependent on electricity than are water-pipeline 

repairs. Presumably the repair of equipment in central offices 

and the repair of cell towers requires either on-site generators 

or commercial power to power the equipment. Cell towers are 

generally supplied with onsite power in the form of uninterruptible power supply (UPS) sufficient for 4 to 8 hr of service 

if commercial power is interrupted (S. Daneshkhah, Sprint, oral 

commun., November 4, 2014). In the case of Verizon Wireless, 

90 percent of cell sites in northern California are also equipped 

with generators in addition to UPS (T. Serio, Verizon Wireless, 

oral commun., January 14, 2014).

I guess that all central offices and 1 in 3 cell towers have 

a generator on site (as in the case of most Verizon towers) and 

that, telecommunication being a national security priority, 

carriers can supply fuel to those central offices and towers. 

I guess that repairing the cell towers is what dominates repair 

efforts for cellular communications. If 33 percent of cell towers 

have generators, then the loss of commercial electricity prevents 

67 percent of repairs entirely and does not hinder the other 33 

percent at all, hence productivity drops by 67 percent, implying 

u=–0.67=0.33. The u-values are qualitatively consistent with 

the San Francisco Lifeline Council’s (2014) lifeline system 

interdependency matrix, in that darker shading in table 7 

corresponds to higher numerical values in table 9.

Depicting Lifeline Interaction with an Influence 

Diagram

It can sometimes help to depict the relations among 

decisions, uncertain quantities, and value outcomes using an 

influence diagram. These diagrams, sometimes also called a 

relevance diagrams, decision diagrams, and decision networks, 

are graphical representations of a decision situation. They 

Table 9. Tentative interdependency u-values.

[u is a constant to indicate the reduction in repair productivity in the absence of a resources required to perform a repair, also called a u-factor. u-factors are 

assigned based on an estimate of the additional time required to carry out one repair if it is necessary to do so without the required resource. z denotes the 

fraction of services in pumped pressure zones]

Upstream→

Downstream ↓ Consumables Fuel Roads Electricity Communications Natural gas Water

Fuel 1.0 – – – – – –

Roads 1.0 1.0 – – – – –

Electricity 1.0 1.0 0.0 – – – –

Communication 1.0 1.0 0.0 0.33 – – –

Natural gas 1.0 1.0 0.0 0.03 0.06 – –

Water 1.0 1.0 0.0 0.03+z 0.06 0.0 –

Wastewater 1.0 1.0 0.0 0.03+z 0.06 0.0 0.0

can represent a mathematical model that relates the decisions, 

uncertain quantities, and uncertain value outcomes with 

functional relations. They are commonly used in decision 

analysis. They tend to be more compact than decision trees, 

able to show more information in less space. The interested 

reader is referred for more background on influence diagrams 

to Howard (1990). The interdependencies implied by table 9 

are depicted in an influence diagram in figure 10.

In figure 10, decisions are depicted in rectangles, 

uncertain quantities in ovals, and mathematical dependency 

by arrows. Time generally flows from left to right or from 

top to bottom in an influence diagram; here time flows from 

left to right. Each arrow starts at a quantity (a decision or an 

uncertainty) and points to another quantity. An arrow implies 

that the second quantity depends to some extent on the first. 

Where there is no arrow connecting one quantity to another, 

the implication is that neither quantity depends on the other. 

For example, there is no arrow from roadway restoration to 

any of the other lifeline restoration uncertainties. This is not 

strictly true, at least according to the San Francisco Lifelines 

Council (2014) and other lifeline interaction matrices, but for 

practical reasons any such dependency can be ignored because 

the roadway network is so redundant that it seems unlikely 

that realistic roadway damage could significantly impair 

restoration of other lifelines. There is an arrow corresponding 

to each nonzero quantity in the interdependency matrix of 

table 9. The arrow is omitted where the corresponding u-value 

in table 9 has a zero value.

Figure 10 omits the dependence of lifeline restoration after 

aftershock 1 on fuel supply and on consumable repair resources, 

but the omission is just for clarity. In practice, or at least in the 

calculations performed here, those dependencies exist.

Figure 11 distills the influence diagram to combine 

all upstream lifelines together and all downstream lifelines 

together. The figure also adds value outcomes—the quantities 

that in the end the analyst cares about, which in the present case 

is indirect business interruption loss. In this more canonical 

influence diagram, value outcomes are shown in hexagons at 

the right side of the diagram. Indirect business interruption will 

be quantified later in the HayWired project as a function of the 

restoration of the lifelines.
222 The HayWired Earthquake Scenario—Engineering Implications

Figure 10. Lifeline interaction influence diagram. Decisions are depicted in rectangles, uncertain quantities in ovals, and mathematical 

dependency by arrows. An arrow implies that the second quantity may depend to some extent on the first. Colors are only used to group 

generalized categories.

Figure 11. Alternate lifeline interaction influence diagram, with value outcomes. This diagram distills the influence diagram in figure 10 to 

combine all upstream lifelines together and all downstream lifelines together. Decisions are depicted in rectangles, uncertain quantities in ovals, 

and mathematical dependency by arrows. Value outcomes (business-interruption losses) are shown in hexagons. Colors are only used to group 

generalized categories.

Supply of roadway

repair consumables

Mainshock: magnitude,

location, ground motion,

liquefaction, landslide,

fault offset, afterslip Roadway 

 damage

Roadway

restoration versus time

(until aftershock 1)

Electricity

infrastructure

damage Electricity

restoration versus time

(until aftershock 1)

Communication

infrastructure

damage Communication

restoration versus time

(until aftershock 1)

Natural gas

infrastructure

damage

Natural gas

restoration versus time

(until aftershock 1)

Water

infrastructure

damage

Water restoration

versus time (until

aftershock 1)

Wastewater

infrastructure

damage

Wastewater

restoration versus time

(until aftershock 1)

Supply of

electricity repair

consumables

Fuel supply

Supply of

communication

repair

consumables

Supply of natural

gas repair

consumables

Supply of

water repair

consumables

Supply of

wastewater

repair

consumables

Aftershock 1: magnitude,

location, ground motion,

liquefaction, landslide,

coseismic slip, afterslip

Roadway damage

from aftershock 1

Roadway restoration

from aftershock 1 to

aftershock 2

Electricity

infrastructure

damage from

aftershock 1 Electricity restoration

from aftershock 1 to

aftershock 2

Communication

infrastructure

damage from

aftershock 1

Natural gas

infrastructure

damage from

aftershock 1

Water

infrastructure

damage from

aftershock 1

Wastewater

infrastructure

damage from

aftershock 1

Communication

restoration from

aftershock 1 to

aftershock 2

Natural gas restoration 

from aftershock 1

to aftershock 2

Water restoration from

aftershock 1 to

aftershock 2

Wasterwater restoration

from aftershock 1 to

aftershock 2

Supply of fuel and

other repair

consumables for

upstream lifelines

Mainshock: magnitude,

location, ground motion,

liquefaction, landslide,

coseismic slip, afterslip

Mainshock

damage to

upstream lifelines

Upstream lifeline

restoration versus time

until aftershock 1

Mainshock damage

to this lifeline

Restoration of

this lifeline versus

time until

aftershock 1

Mainshock

damage to

downstream

lifelines Restoration of

downstream

lifelines versus time

until aftershock 1

Supply of fuel and

other repair

consumables for this

lifeline

Supply of fuel and

other repair

consumables for

downstream lifelines

Aftershock 1:

magnitude, location,

ground motion,

liquefaction,

landslide, coseismic

slip, afterslip

Aftershock 1

upstream

lifeline damage

Upstream lifeline

restoration between

aftershocks 1 and 2

Aftershock 1

damage to this

lifeline

Restoration of this

lifeline between

aftershocks 1 and 2

Aftershock 1

damage to

downstream

lifelines

Downstream lifeline

restoration between

aftershocks 1 and 2

Business interruption loss

from this lifeline

Business interruption loss

from upstream lifelines

Business interruption loss

from downstream lifelines
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 223

Measuring Water-Supply Resilience

As proposed by Bruneau and others (2003), I view the 

area above the restoration curve R as a measure of the loss of 

resilience—less area means less impact, faster recovery, or 

both. Recall that Bruneau and others (2003) measured R as in 

equation 39:

 

, (39)

where Q(t) denotes the degree of service as a fraction of full 

service at time t and times t=0 and t=t

1

 denote the initiating event 

(the earthquake) and the time of full restoration, respectively. 

For present purposes, I measure Q(t) as the fraction of all service 

connections receiving water at time t, whether treated or not, 

whether at normal pressure or not (which one can call “wet 

water,” as opposed to treated water). Because the present analysis 

calculates V(t), the number of service connections receiving 

water at time t, one can normalize V(t) by the number of service 

connections, denoted here by M, and substitute:

 . (40)

R can be seen as the average number of days a service 

connection loses service. It will be useful to estimate the total 

economic impact of the loss of resilience, which relates more 

closely to the number of service-days lost, R×M:

 . (41)

I measure the benefit of a mitigation option in terms of 

the reduction in R×M relative to some baseline condition such 

as as-is conditions:

 , (42)

where “what-if” indicates the loss of resilience with the mitigation 

measure.

Suppose that in some cases, loss of water supply is the 

sole cause that a home or business loses function, and the home 

residents or business occupants experience a financial loss as 

a consequence. (Loss of water service caused 18 percent of 

business closures after the 1994 Northridge earthquake, according 

to Tierney’s, 1995, survey.) A household might have to move 

temporarily to a hotel until water is restored. A business might also 

relocate or suspend operations until water is restored. What would 

be the daily cost of lost service?

One can in principle perform a proper economic analysis, 

similar to the analysis described by Rose and others (2011) for 

a hypothetical Mw 7.8 earthquake on the San Andreas Fault in 

southern California. If an analyst finds it impractical to carry out 

an economic analysis such as with input-output or computable 

general equilibrium, one could estimate on a preliminary, orderof-magnitude basis, the economic losses to society that result from 

loss of water supply. To do so, one estimates societal economic 

losses by assigning a dollar value L1 to one lost service-day. One 

then estimates the economic value of the lost water service L as in 

equation 43, and the economic value of a mitigation option, ΔL, 

using equation 44. (The monetary loss quantities L and L1 should 

not be confused with pipe lengths Li from previous equations.) To 

avoid confusion with the results of detailed economic analyses 

presented in a later volume, equations 43 and 44 are not evaluated 

here, nor do I offer an estimate of L1:

 , (43)

 . (44)

Optional Stochastic Simulation Methodology

The present work was developed for use in the U.S. 

Geological Survey’s HayWired earthquake scenario, which 

requires only a single realistic outcome, not best, worst, or mean 

cases or any particular probabilistic outcome. However, to make 

the work more generally useful, it is convenient to add features 

that allow the analyst to treat earthquake damage to a water-supply 

system as stochastic, that is, uncertain, random.

Simulation of Earthquake Excitation

I will treat the simulation of the earthquake excitation 

only superficially; the interested reader is referred to Chen and 

Scawthorn (2003) for methods to generate a stochastic set of 

earthquakes that are consistent with the seismicity of regional 

faults and their possible earthquake magnitudes and rupture 

locations. In the United States, the U.S. Geological Survey 

(USGS) National Seismic Hazard Maps (for example, Petersen 

and others, 2014) can offer a model of seismicity.

For each mainshock rupture in the stochastic set, one 

generates an earthquake sequence of foreshocks, mainshock, 

and aftershocks. Ogata (1998) provides a general reference for 

modeling aftershocks using an epidemic-type aftershock sequence 

(ETAS). The version of the ETAS model used for the HayWired 

scenario also distributes the aftershocks in space (Felzer and 

others, 2003). More sophisticated models mesh aftershock models 

with traditional fault and stress-renewal based seismic-hazard 

models (for example, the Uniform California Earthquake Rupture 

Forecast, version 3, ETAS; Field and others, 2013). 

Median ground motion and logarithmic standard deviations 

of ground motion in each earthquake in a sequence can be 

calculated using convenient and regionally appropriate groundmotion prediction equations. In the case of the HayWired 

mainshock, the results of a physics-based model by Aagaard 

and others (2010a, b) were adopted, but one can also use lessexpensive methods. For example, for shallow crustal earthquakes 

in active tectonic regimes, one can use the NGA-West 2 groundmotion prediction equations (see Boore and others, 2014).

Ground motion is uncertain and spatially correlated. Here, 

uncertain means that ground motion can be higher or lower than 

the median predicted by the ground-motion prediction equations, 

potentially many times higher and lower. It is important to treat 

R Q = − ∫ ( ) 1 ( )t dt

t

0

1

R M× = ∫ ( ) M V− ( )t dt

t

0

1

∫ ( ) R = − V t

M

1 dt

t

0

1

( ) R M× = ( ) R M× −( ) R M× baseline what-if

L R = × ( ) M L × 1

ΔL R = × Δ( ) M L × 1
224 The HayWired Earthquake Scenario—Engineering Implications

that variability about the median—ignoring it will tend to bias 

damage and loss estimates low, as explained elsewhere in the 

HayWired study (Porter 2017b). One can simulate a properly 

varying and spatially correlated field of ground motion using the 

model of Jayaram and Baker (2009).

Simulation of Pipeline Vulnerability

Vulnerability of buried pipeline is uncertain. To simulate 

damage rate in buried pipe subjected to wave passage, landslide, 

and liquefaction, one can draw two samples, u1 and u2, from a 

U(0,1) uniform distribution (that is, equally likely to take on 

any value between 0 and 1) and simulate damage rates in buried 

pipeline by substituting u for the nonexceedance probability 

p. For example, in the present adaptation of Eidinger’s (2001) 

model, equation 24, one substitutes u for p as shown in 

equations 45 and 46:

 , (45)

 

 .(46)

The symbol ~ here means “is a sample taken from the 

distribution” or “is distributed like.” Equation 45 says, “draw a 

sample u1 and another sample u2 from a U(0,1) distribution.” Each 

assignment can be carried out in a spreadsheet using, for example 

Microsoft Excel’s rand() function, which produces a sample 

U(0,1) and changes it each time the spreadsheet is recalculated.

The simulation equations assume that vulnerability to wave 

passage varies independently from vulnerability to ground failure 

but that the intrasystem vulnerability for each peril and each type 

of pipe is completely correlated. That is, all wave-passage damage 

rates for small-diameter cast-iron pipe within a system will be 

uniformly higher or lower than average in a given system, and all 

ground-failure damage rates for large-diameter asbestos cement 

pipe within a system will be uniformly higher or lower than 

average in a given system.

Simulation of Damage to Buried Pipeline

Next, simulate the damage to the buried water-supply 

pipeline system. The simulation treats the damage rates as 

uncertain as shown in equation 46. I denote by ri the simulated 

damage rate in each segment of pipe. The simulation then treats 

the number of leaks or breaks in any given segment of buried 

pipe i as distributed with a Poisson distribution whose mean rate 

r is estimated from equation 28 for summand i. The Poisson 

distribution is a discrete probability distribution that expresses 

the probability of a given number of events occurring in a fixed 

interval of time or space if these events occur with a known 

average rate and independently of the time or distance between 

events. In this case, the events are breaks or leaks and the fixed 

interval of space is the length of the pipe segment.

So, conditioned on the mainshock shaking and ground 

failure values (here, PGV and PL) at each pipe segment’s 

midpoint, and on the vulnerability function assigned to each 

component (here, K1, K2, and length L values for each pipeline 

segment), the simulation assumes that the probability of exactly 

y breaks or leaks on segment i (y ∈ {0, 1, 2, ... }) is given by 

equation 47. The probability that y or fewer breaks or leaks occur 

is given by equation 48, which is the cumulative distribution 

function for the Poisson distribution with rate parameter ri:

 , (47)

 , (48)

 . (49)

To simulate a particular number of repairs in segment i, one 

draws a sample ui from a uniform distribution ui ~ U(0,1) and 

solves equation 49 for y. The equation inverts the cumulative 

distribution function of a Poisson distribution with rate ri at ui to 

produce the number of simulated breaks on segment i. I know of 

no closed-form expression for the value of Yi in equation 49, but 

simulation software such as @Risk (http://www.palisade.com/

decisiontools_suite/) can perform the simulation.

Equation 49 does not include breaks at where the pipeline 

crosses the fault. To deal with pipe breakage at fault offset, I take 

df from equation 28 as uncertain. It is common to take fragility 

functions as approximated by a lognormal cumulative-distribution 

function, so absent a better empirical or analytical model, I do 

so here, and assume a median value θ=4 inches and logarithmic 

standard deviation β=0.6. I propose this particular median value 

because it seems like a reasonable threshold in light of Eidinger’s 

liquefaction vulnerability function in figure 7. I propose this 

particular logarithmic standard deviation because it reflects a 

relatively large degree of uncertainty, compared with other fragility 

functions such as those in FEMA P-58-1 (Applied Technology 

Council, 2012).

To use these fragility parameters to model pipe breaks due 

to fault offset, for each segment i that crosses the fault, add 0 or 

1 pipe breaks per equation 50. In the equation Zi denotes either 0 

or 1 pipe breaks produced by fault offset at segment i, I(⋅) is the 

indicator function (1.0 if the term in parentheses is positive, 0.0 

if negative), Φ(⋅) is the standard normal cumulative distribution 

function evaluated at the term in parentheses, di is the fault offset 

distance where the fault intersects pipeline segment i, θ and 

β are as just defined, and ui is another sample from a uniform 

distribution ui~U(0,1). To explain the equation, the Φ term gives 

the probability that segment i is broken. If ui is less than that 

probability, then the simulation says that that segment is broken, 

that is, that that segment’s uncertain capacity to resist fault offset 

was less than di:

 . (50)

u u 1 2 ~ ~ U ( ) 0,1

R PGV P u u P K PGV

u K

P u

, , , 1 0.00187

exp 1.15 1.88

exp 0.74

L 1 2 L 1

1

1 2

L

1

2

Φ

Φ

( )

( )

( ) ( )

( )

( )

= − × × ×

× × + ×

× × ×

−

−

( ) [ ] = = − P Y y r r

y

exp

! i

i

y

i

∑ ( ) [ ] ≤ = −

=

P Y y r r

n

exp

! i

i

n

i

n

y

0

Y y i i = ≤ max : ( ) u P[ ] Y y i ≤

Φ

θ

β

( ) Z I = − d

u

ln i

i

i
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 225

Finally, one can sum over all pipeline segments to simulate 

the total simulated number of breaks W, as in equation 51:

 . (51)

Simulation of Restoration

As shown in figure 9, time to repair a break or leak is 

uncertain and approximately lognormally distributed. I use the 

parameters derived from Schiff’s (1988) data for small-diameter 

pipe and the assumed parameters for large-diameter pipe as 

recapped in table 10. Repair duration for a single break or leak 

can be estimated using equation 52. In the equation, ui is a 

random number drawn from a uniform distribution, ui~U(0,1), 

and is not the same ui value as used elsewhere in this section:

 . (52)

It is problematic to offer a stochastic model for number of 

services lost as a function of damage (the serviceability index), 

partly because the use of the serviceability index seems so 

tenuous to begin with. Treating it as uncertain with a specified 

model seems like illusory thoroughness—“cutting the baloney 

too thin.” However, until a better model comes along, I treat 

the initial level of service V0 (now an uncertain quantity rather 

than a deterministic value) as beta-distributed with bounds 0 

and 1, mean value given by equation 53, and coefficient of 

variation δ=0.5 (this last by eye from fig. 4). (For the reader 

who is unfamiliar with the beta distribution, it is a commonly 

used probability distribution for an uncertain quantity that can 

take on a value only between two bounds, such as between 0 

and 1, and has a specified mean and standard deviation.) The 

parameters of the beta distribution, denoted here by α and β, 

can be calculated as shown in equations 55 and 56. The inverse 

cumulative distribution function for the beta distribution is 

approximated by the inverse of the Kumaraswamy cumulative 

distribution function (Kumaraswamy, 1980; Jones, 2009), which 

is easier to calculate. One generates a sample of a uniform 

distribution ν~U(0,1) and evaluates the inverse cumulative 

distribution function of the Kumaraswamy distribution as 

shown in equation 57 to produce a sample of the initial level of 

service V0:

 , (53)

 , (54)

 , (55)

 , (56)

= + ∑( ) =W Yi i Z

i

n

1

Table 10. Parameters for uncertain pipe-repair duration (see 

equation 52).

Diameter Median, 

θ 

Logarithmic standard 

deviation, β Basis

Small 

(<20 inches)

6.1 hours 0.58 Schiff (1988)

Large 

(≥20 inches)

16 hours 0.6 Schiff (1988) and 

this chapter

= ⋅ θ β( ) ⋅Φ ( ) − d u 0,i i exp 1

 . (57)

The rate-limiting factors for lifeline repairs can similarly be 

treated as beta-distributed (which one can approximate using the 

Kumaraswamy distribution as before) bounded by 0 and 1, with 

means as proposed in table 9. Values that are assigned 0 or 1 in the 

table can be taken as certain, that is, with coefficient of variation 

equal to 0. Rate-limiting factors greater than 0.0 and less than 1.0 

are uncertain; I take their coefficient of variation as substantial, say 

1.0. That is, let:

• u=a sample of the (possibly uncertain) rate-limiting factor,

• m=expected value of the rate-limiting factor, from table 9,

• d=assumed coefficient of variation of the rare-limiting 

factor,

• d=1, m ∉ {0,1} (the symbol ∉ means “is not a member of 

the set listed here”),

d=0, m ∈ {0,1} (the symbol ∈ means “is a member of the 

set listed here”),

• v=a sample of a uniform distribution bounded by 0 and 

1, that is, v~U(0,1). (I use v here for the sample uniform 

variate because u is already in use in this step.)

Then, equations 58 through 60 follow as:

 d ≠ 0 , (58)

 d ≠ 0 , (59)

 . (60)

Accounting for Afterslip and Aftershocks

Aftershocks produce new damage to a system that may be 

only partially repaired. To estimate the number of required repairs 

after an aftershock, I estimate new damage as if it occurred to a 

pristine system. Add the number of repairs that have not yet been 

completed, and recommence the calculation of services restored 

by the nth repair and time required to perform the nth repair.

Φ

= × ( )

= × − ×

μ M s r

M

r

L q

b

1

ln

δ = 0.5

β α= × − 1

μ

1

α

δ

( ) = − μ − μ

1

2

= = ( ) ν ν ( ) − − ( ) β α − V F 1 1 0

1 1 1

( ) = − a − m

d

m

1

2

b a = × − m

1 1

( ) ( )

{ }

= − − ≠

= = ∈

u v d

m d m

1 1 0

0, that is, 0,1

b a 1 1
226 The HayWired Earthquake Scenario—Engineering Implications

Afterslip can increase the deformation on a pipeline segment 

at a fault crossing where a pipeline is already strained by coseismic 

(and possibly preseismic) slip. One way to model pipeline damage 

due to afterslip is to treat the pipe as having a fixed capacity to 

resist deformation.

When the coseismic slip plus afterslip at a point where a 

pipeline segment crosses a fault reaches that capacity, the pipe 

breaks. The capacity can be treated as having a deterministic 

value or a probabilistic value. As discussed above in the Literature 

Review section, the capacity in reality depends on the material, 

pipe diameter, jointing, and sense of deformation; that is, whether 

in tension, shear, or compression. For simplicity for present 

purposes, I propose to treat the capacity as having a single scalar 

quantity for all materials (for example, diameters) per equation 26 

for a deterministic model or equation 50 for a stochastic model.

Adjusting Hazus-MH’s Lifeline Restoration 

Model

As discussed in the Literature Review section, Hazus-MH 

(Federal Emergency Management Agency, 2012) is FEMAfunded software. It is used to perform risk analysis for 

earthquakes, hurricanes, and floods in the United States.

Why One Might Need to Adjust the Restoration 

Curves Offered by Hazus-MH

Hazus performs hazard analysis, damage analysis, loss 

analysis and recovery analysis, including repair costs, life-safety 

impacts, and the duration and economic losses resulting from 

loss of function. It includes built-in asset definitions for virtually 

the entire built environment of the United States, including 

lifelines, and encodes other restoration parameters such as the 

number of workers available to perform repairs. It is a very 

powerful tool.

In the author’s experience, loss-estimation software, no 

matter how advanced, becomes obsolete soon after its release. 

Users see that the software’s capability extends to X and soon 

conceive of a new need “DX” that that the software does not 

satisfy. Hazus-MH is like that. The new need identified here 

is the ability to treat lifeline interactions and aftershocks. 

Hazus-MH is currently closed source, so the analyst who wants 

to add the ability to treat lifeline interaction and aftershocks 

cannot do so by changing the source code, although many 

parameters can be changed. How can one modify the outputs, 

using principles presented here to do so?

Adjusting Hazus-MH’s Estimates of Lifeline 

Restoration to Account for Repair Crews

Before addressing lifeline interaction and aftershocks, 

I consider the situation where a Hazus-MH analysis has already 

been performed and the user realizes that an important adjustable parameter—the number of workers available to perform 

repairs—was wrong? The Hazus-MH default value for the number 

of water-supply pipeline repair workers available in each county 

appears to be 100 regardless of the size of a county, which may 

be far from accurate in many cases. If the analyst has a supposedly better estimate of the number of repair workers in a particular 

county, how can the analyst adjust Hazus’s restoration estimate 

to account for that better estimate of repair crews after the fact? 

I assume that repair progress increases linearly with number of 

repair crews. It seems uncontroversial to adjust Hazus’ estimated 

restoration curve to account for a different estimate of repair-crew 

resources as shown in equations 61 through 63:

 , (61)

where

 j∈{1,2,...5}

 . (62)

 j∈{2,3,4,5}

I also assume 

 , (63)

where 

• V(τ)=estimate of the number of service connections with 

water service at time τ, after adjusting for the number of 

workers in the grographic area of interest (for example, a 

county),

• =Hazus-MH’s estimate of the number of service 

connections with water service at time t

j

, assuming default 

values of the number of workers in the geographic area of 

interest,

• j=an index to points in time after the earthquake, 

j∈{1, 2, ... 6},

• t

j

=time after the earthquake, t

j

∈{1, 3, 7, 30, 90, 210} days, 

where t

6

, 210 days, is added to Hazus’ basic list of five 

points in time (1, 3, 7, 30, 90) days to account for the fact 

that Hazus-MH might report incomplete restoration at 90 

days and that the analyst may need to evaluate restoration 

after 90 days, assuming full restoration by 7 months (I use 

7 months because a later calculation shows that a rounder 

number like 6 months is not enough for one agency):

• q(t)=analyst’s estimate of the number of water pipeline 

repair workers available in a county at time t,

• q0=Hazus-MH default value used in the analysis (for 

example, 100),

• M=number of service connections in the geographic area 

of interest (a county).

( ) τ ∫ ( ) ( ) = ×

≤

τ

=

V q t

q

dV t

dt

dt

M

ˆ

t 0 0

V t( ) ˆ j

dVˆ t( j)

dt

Vˆ t( j+1 ) Vˆ t( j)

tj+1 tj

≥ dVˆ(tj−1 )

dt

Vˆ t( 6 ) = M
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 227

The inequality in equation 62 is necessary in case 

=M, that is, the unadjusted Hazus estimate of restoration is 

complete in the time between t

j

 and t

j

+1, which would produce 

an unrealistically low restoration slope.

I refer to q(t)/q0 as the repair-crew availability factor, and 

I refer to V(t) as the repair-crew-adjusted estimate of restoration 

before accounting for lifeline interaction. Equation 61 says that 

the pace of repairs at time τ is estimated as Hazus’ estimate (the 

derivate gives the rate of restoration; that is, services restored per 

unit time), increased by the repair-crew availability factor (that is, 

to account for the analyst’s estimate of the correct number of repair 

workers available at time τ, and integrated from time 0 to time t).

For the special case of constant q(t), I substitute the constant 

q for q(t). Given constant q and piecewise linear restoration V(t) to 

go with Hazus-MH’s limited set of values, one can evaluate equation 61 to evaluate the repair-crew-adjusted estimate of 

restoration before accounting for lifeline interaction as shown in 

equation 64:

 

 . (64)

Accounting for Lifeline Interaction in Hazus-MH

Hazus-MH’s restoration curves do not consider lifeline 

interaction. As of this writing, Hazus-MH evaluates restoration 

at five points in time after an earthquake: 1, 3, 7, 30, and 

90 days. I further modify the restoration rate from equation 61 

as shown in equation 65:

 , (65)

where

 , (66)

ui is as previously defined (see table 9), and gi(t) is as defined in 

equation 33 (that is, the flow of rate-limiting factor i divided by 

the pre-earthquake flow). In the case of a lifeline, g is the fraction 

of service connections in upstream lifeline i receiving service at 

time t, after accounting for lifeline interaction with their upstream 

lifelines. In the case of consumable repair supplies, g is the flow of 

repair supplies as a fraction of the amount needed.

The product in equation 65 is just another factor that 

modifies the restoration rate, like q/q0 in equation 64. I can 

include lifeline interaction by multiplying the restoration rate by 

this additional factor, as in equation 67:

 

 . (67)

Accounting for Aftershocks in Hazus-MH

To adjust Hazus-MH results to account for aftershock 

occurrence, I reduce V(t) by the amount of service estimated lost 

when the virgin system is damaged by aftershock j; that is:

 , (68)

where M denotes the number of services in the county and 

Vj(0) denotes the number of service connections receiving 

lifeline service immediately after the aftershock, as estimated 

by Hazus-MH for the virgin system (that is, as if the system 

were undamaged at the time of the aftershock).

Mitigation Options

I consider only two mitigation options—(1) to reduce a 

water utility’s reliance on commercial fuel and (2) to reduce the 

quantity of brittle pipe or pipe running through liquefiable soil. 

Other mitigation options certainly exist. Notable among these is 

the judicious replacement of selected segments of brittle pipe that 

are particularly important in some way, such as because they carry 

high flow or because they are necessary for service to an important 

facility.

Fuel Plan

A utility can reduce its reliance on commercial fuel supplies 

by installing above-ground fuel storage tanks in its service centers. 

An above-ground storage tank of 3,000 gallons, such as shown in 

figure 12, would be sufficient for 10 repair crews to operate for 

a week or more before needing to be refilled. The above-ground 

fuel tank in figure 12 has a fuel transfer pump (the red box) that 

can be powered by a small vehicle-mounted generator that a repair 

Vˆ t( j+1 )

Vˆ (t)

( ) ( ) ∑ ( ) = + × − ( ) ∈{ }

≤

=

−

V t V t +

q

q

dV t

dt

t t j

M

ˆ 1,2, 3, 4,5 j

k

j

k

1 k k

1 0

1

1

' ' ∏( ) ( ) ( ) ( ) = × − × − ( ) =

dV t

dt

dV t

dt

1 1 u g t i i

i

n

1

∫ τ

τ ( ) ( ) τ ( ) = +

τ =

V t V t

dV

d

d

t

0

0

'

'

∑

∏( )

( )

( )

( ) ( )

( ) ( )

= + × ×

− × − −

≤

=

−

=

+

V t V t q

q

dV t

dt

u g t t t

M

 j∈{1,2,3,4,5}

ˆ

 1 1

j

k

j

k

i i

i

n

k k

1

1 0

1

1

1

' '

Vʹʹ(t) =Vʹ(t)−(M −Vj(0))

Figure 12. Photograph of a 3,000 gallon above-ground petroleum 

storage tank. This tank has a fuel transfer pump (the red box) that 

can be powered by a small vehicle-mounted generator that a 

repair truck can easily carry. (Photograph by Keith Porter.)
228 The HayWired Earthquake Scenario—Engineering Implications

truck can easily carry. An electrical contractor can be dispatched 

to connect a secondary electrical generator to a fuel island in a few 

hours. If trucks are regularly refilled at the end of each day, the 

time required to connect a fuel pump to a generator need not affect 

repair operations. Alternatively, service centers can be equipped 

with an emergency generator and switchgear to power fuel pumps 

in the case of commercial electric failure. At least one large 

California utility carries such a generator on all its repair vehicles, 

maintains a fuel supply of as much as 3,000 gallons or more at its 

service centers, and has installed emergency generators at several 

of its service centers.

Pipe Replacement

With an aggressive pipe-replacement program, a water utility 

can realistically replace 1 percent of buried pipe per year, although 

lower replacement rates are more common. For example, San 

Francisco planned to replace 1.3 percent of its water distribution 

pipe (15.5 miles of its 1,230-mile distribution system) in fiscal 

year (FY) 2016 (San Francisco Public Utilities Commission, 

2015). With a sustained program that focuses on replacing brittle 

pipe (for example, cast iron and asbestos cement), or pipe installed 

in liquefiable soil, a utility could replace the majority of its brittle 

or vulnerable system within a few decades.

Summary of the Methodology

To summarize, the methodology proposed here models 

damage and restoration of buried pipelines subject to earthquake 

shaking (called wave passage) and ground failure (liquefaction, 

landslide, and surface rupture of a fault). Briefly, its steps are as 

follows:

1. One acquires maps of ground motion, especially PGV and 

ground failure (liquefaction, landslide, and fault offset), for 

each earthquake of interest. One uses equation 28 and then 

carries out the following steps.

2. Equation 28 estimates r, the number of repairs required 

because of earthquake damage, using basic loss-estimation 

principles.

3. Equation 29 estimates V0, the number of service connections 

that have service available immediately after the earthquake. 

It assumes that the serviceability index (a measure of 

water-supply pressure loss as a function of water-supply 

pipeline breaks per kilometer of pipe) can be used as a proxy 

to estimate the fraction of services available. It would be 

desirable to replace this assumption, but doing so seems to 

require hydraulic modeling that would make the present 

analysis prohibitively time consuming.

4. Equation 32 estimates V(n), the number of services available 

after n repairs have been completed. It employs a parametric 

form for service restoration, one that reflects EBMUD 

engineers’ strategy to perform the most effective repairs 

(the ones that restore the most services per repair) first and 

one that generally agrees with experience in the Kobe and 

Northridge earthquakes. 

5. Equation 37 estimates F(t), the number of services restored 

by time t. Lifeline interaction is quantified at this stage by a 

set of time-independent rate-limiting factors u that indicate 

loss of repair productivity resulting from the loss of each 

upstream lifeline or other required repair resource. The 

lifeline interaction model modulates the time-dependent 

effect of the loss of required resources with a set of timedependent factors g(t) that measure the flow of each resource 

at time t. One calculates F(t) for each of many points in 

time, t=0, Dt, 2Dt, and so on, where the datum t=0 refers to 

the time when the mainshock occurs.

6. To apply these equations to a mainshock, one estimates 

damage and immediate loss of service. Then estimate the 

service restoration and time required to perform the service 

restoration for each repair n∈{1, 2, ... r}. Finally, one relates 

time to number of services available.

7. To account for aftershocks, repeat tasks 2–6, adding the 

damage that remains unrepaired as if the remaining damage 

occurred with the aftershock.

8. To treat the entire model as stochastic (that is, random, 

uncertain), simulate pipeline vulnerability using equation 

46, damage using equation 49, initial loss of service 

using equation 57, and the rate limiting factors for each 

upstream resource using equation 60. Carry out tasks 2–7 

as before, many times. Each time represents one possible 

outcome. Compile the samples of whichever parameter 

values are of interest, and estimate any moments (such as 

mean and variance) of interest.

9. To account for lifeline interaction in Hazus-MH, apply 

equation 66, which adjusts the slope of the Hazus-calculated 

restoration curve to account for rate-limiting factors among 

upstream lifelines and then integrates the adjusted slope to 

produce a new restoration curve.

10. To account for aftershocks in Hazus-MH, apply equation 

68 after each aftershock, which reduces each lifeline’s 

functionality as estimated by Hazus-MH for the virgin 

system shaken by the aftershock. One then continues 

the integration over time using the adjusted mainshock 

restoration curve of the previous step.

Case Study 1—San Jose Water Company

I test the proposed methodology on a real water-supply 

system subjected to the hypothetical HayWired earthquake 

sequence. First consider summary features of the case study 

system—the San Jose Water Company’s (SJWC) water-supply 

system’s buried pipeline network.
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 229

San Jose

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, 

NSF, NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015. 0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

 Area 

of map CALIF

37.3°

37.2°

122° 121.8°

37.4°

Figure 13. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a 

map of the San Jose Water Company’s water-supply system. The 3,959 kilometers of pipe in the system are shown in red. 

San Jose Water Company Asset Definition

The following statistics are taken from Elvert (2015). 

SJWC is 150 years old, has 225,000 service connections, and 

employs 345 people. It serves 80 percent of San Jose, 50 percent 

of Cupertino, all of Saratoga, Los Gatos, Monte Sereno, and 

Campbell, and unincorporated parts of Santa Clara County. Daily 

demand for drinking water varies from 85 to 165 million gallons, 

with an average daily demand for drinking water of approximately 

120 million gallons. It has 2,400 miles (4,000 km) of water pipes 

(mains), 105 active wells, a 6,500-acre watershed in the Santa 

Cruz Mountains, 96 distribution reservoirs, two surface-water 

treatment plants, and performs approximately 370 water-quality 

tests each month.

SJWC provided an ArcGIS map of its water-supply 

system. The system map is shown in figure 13. The map shows 

3,959 km of pipe of various types and lengths. Quantities of 

pipe are summarized by material in table 11 and by diameter 

in figure14. In table 11, “Eidinger type” and “ID” refer to the 

assumed corresponding vulnerability functions by Eidinger 

(2001) and their associated vulnerability factors K1 and K2

from table 1. Some of SJWC’s pipe does not map well to an 

Eidinger type, especially SJWC’s steel pipe, which generally 

has lead or cement caulk rather than any of the joint types that 

Eidinger considers.

Some of the material codes do not appear in SJWC’s 

glossary of pipe types, and are probably data-entry errors. I have 

made a reasonable assumption about the intended meaning, but 

in any case the total quantities of these questionable materials are 

small—30.2 of 2,459 miles, or just more than 1 percent.

San Jose Water Company Hazard Analysis

The HayWired earthquake sequence is described by Wein 

and others (2017). It begins with an M7.0 mainshock on the 

Hayward Fault, with an epicenter near the City of Oakland, that 

ruptures the north and south segments of the fault from a point 
230 The HayWired Earthquake Scenario—Engineering Implications

Table 11. San Jose Water Company, California, pipe construction, associated with Eidinger (2001) vulnerability functions.

[Code, code for pipe material; count, number of segments of that material in San Jose Water Company buried water-pipeline system; miles and kilometers, total 

length of pipe material; material description, description of pipe material; Eidinger type and ID, assumed corresponding vulnerability functions of Eidinger 

(2001) and their associated vulnerability factors K1 and K2 from table 1; PVC, polyvinyl chloride]

Code Count Miles Kilometers Material description1 Eidinger type2 ID2

AC 7,144 398.5 641.3 Asbestos cement Asbestos cement, cement joint 14

BCL 14 0.3 0.4 Bare cement-lined steel Welded steel, rubber gasket 10

CCCL 1,110 63.0 101.4 Cement mortar coated and lined steel pipe Cement mortar coated and lined steel pipe 10

CI 3,913 210.7 339.0 Cast iron Cast iron, rubber gasket 4

CL 5 0.0 0.0 Cement-lined steel Welded steel, rubber gasket 10

CU 71 0.9 1.4 Copper Copper 10

DCCL 136 4.7 7.6 Dimet coated cement-lined steel Dimet coated cement-lined steel 10

DCIL 1 0.2 0.3 Ductile iron cement lined Ductile iron, rubber gasket 19

DFK 1 0.0 0.0 Dipped and fiberglass-kraft wrapped (asphalt coated) steelWelded steel, rubber gasket 10

DICL 16,962 789.4 1,270.4 Ductile iron cement lined Ductile iron, rubber gasket 19

DIMCL 7 0.3 0.5 Dimet coated cement-lined steel Welded steel, rubber gasket 10

DS 6 0.3 0.4 Dimet coated steel Dimet coated steel 10

FKCL 3,643 199.4 320.8 Fiberglass-kraft wrapped cement-lined steel Fiberglass-kraft wrapped cement-lined 

steel

10

GALV 72 0.6 0.9 Galvanized steel Galvanized steel 10

GG 9 0.0 0.1 Groove and grip steel Welded steel, screwed joint 11

HDPE 14 2.9 4.6 High-density polyethylene plastic PVC, rubber gasket 18

PB 2 0.1 0.1 Polybutylene plastic Polybutylene plastic 18

PE 5 0.3 0.5 Polyethylene plastic Polyethylene plastic 18

PP 1 0.0 0.0 Polypropylene plastic Polypropylene plastic 18

PVC 857 40.2 64.7 Polyvinyl chloride plastic Polyvinyl chloride plastic 18

RCP 3 0.0 0.0 Reinforced concrete Asbestos cement, cement joint 14

S 109 1.7 2.7 Steel Welded steel, rubber gasket 10

SB 232 3.9 6.3 Standard black steel Standard black steel 10

SG 1 0.0 0.0 Standard galvanized steel Standard galvanized steel 10

SI 114 5.6 9.0 Sheet iron Sheet iron 10

SOMCL 4,903 281.8 453.5 Somastic coated cement-lined steel Somastic coated cement lined steel 10

SS 256 8.1 13.0 Standard screw steel Welded steel, screwed joint 11

TBD 695 29.4 47.3 Steel Welded steel, rubber gasket 14

WI 12 0.3 0.5 Wrought iron Cast iron, cement joint 1

WS 598 32.0 51.5 Wrapped steel unlined Welded steel, rubber gasket 10

WSCL 6,353 384.5 618.8 Wrapped steel cement lined Wrapped steel cement lined 10

ZCCL 5 0.2 0.3 Zinc coated cement-lined welded steel Zinc coated cement-lined welded steel 10

Total 47,254 2,459 3,957

1

Descriptions in italics are assumptions.

2

Assumed corresponding vulnerability function from table 1.

under San Pablo Bay at the north end to a point near the City 

of Hayward at the south end. It is followed by a hundreds of 

aftershocks of M2.5 or greater. Of these aftershocks, 16 are of 

M5.0 or greater. Table 12 summarizes the day, location, label, 

and magnitude of each event. In the table, day 1 corresponds to 

April 18, 2018.

Figures 15, 16, and 17 show the SJWC system map 

overlain with HayWired mainshock peak ground velocity, 

liquefaction probability, and landslide probability, respectively 

(see Aagaard and others, 2017, Jones and others, 2017, McCrink 

and Perez, 2017, respectively). The mainshock surface rupture 

does not reach SJWC’s system, so it does not appear in the 

figures. Figure 18 shows peak ground velocity contours in a 

M6.4 aftershock that occurs on day 166, that is, 5 months after 

the HayWired mainshock.

San Jose Water Company Damage Analysis

Table 13 summarizes mean damage to SJWC buried 

pipeline in the HayWired scenario mainshock (1,054 repairs). 

Aftershocks continue to aggravate damage, contributing 903 

more repairs—29 more in large-diameter pipe and 873 more 

in small-diameter pipe. See table 14 for the expected value 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 231

Figure 14. Graph showing pipe length by diameter in the San 

Jose Water Company, California, water-supply system.

0

200

400

600

800

1000

1,200

0

250

500

750

0 12 24

Pipe diameter, in inches

Length of pipe, in kilometers

Length of pipe, in miles

6 18 30 36 42 48

Table 12. Hypothetical earthquake sequence for the HayWired 

earthquake scenario (Wein and others, 2017).

[Day 1 corresponds to April 18, 2018. Mw, moment magnitude]

Day Epicenter Name Mw

1 Oakland Mainshock 7.05

1 Union City uc523 5.23

1 San Pablo sp504 5.04

12 Fairfield ff558 5.58

15 Fremont fr51 5.10

32 Oakland ok542 5.42

40 Palo Alto pa62 6.21

40 Menlo Park mp552 5.52

41 Palo Alto pa569 5.69

41 Atherton at511 5.11

67 Palo Alto pa522 5.22

74 Palo Alto pa526 5.26

166 Cupertino cu64 6.40

166 Mountain View mv598 5.98

166 Sunnyvale sv535 5.35

166 Santa Clara sc509 5.09

492 Palo Alto pa501 5.01

Figure 15. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a map 

of the San Jose Water Company’s buried water-pipeline system (red). Image is overlaid with peak ground velocity (PGV) for 

the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

San Jose

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, 

NSF, NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015. 0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

 Area 

of map CALIF

37.3°

37.2°

122.2° 122° 121.8°

37.4°

PGV, in meters per second
232 The HayWired Earthquake Scenario—Engineering Implications

Figure 17. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a map 

of the San Jose Water Company’s buried water-pipeline system (red). Image is overlaid with landslide probability for the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

San Jose

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, 

NSF, NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2018. 0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

37.3°

37.2°

122.2° 122° 121.8°

37.4°

EXPLANATION

Liquefaction probability

0.05–0.1

Not assigned

0.1–0.2

0.2–0.3

0.3–0.4

0.4–0.5

>0.5

 Area 

of map CALIF

San Jose

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, 

NSF, NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015.

37.3°

37.2°

122.2° 122° 121.8°

37.4°

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

 Area 

of map CALIF

EXPLANATION

Landslide probability, in percent

0

0–2

2–15

15–32

>32

Figure 16. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated 

with a map of the San Jose Water Company’s buried water-pipeline system (red). Image is overlaid with liquefaction 

probability for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 233

0

0 2 4 6 8

2 4 6 8 10 MILES

10 KILOMETERS

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, NOAA; 

data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015.

 Area 

of map CALIF

37.3°

37.4°

37.2°

122.2° 122° 121.8° 121.6°

Figure 18. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a map 

of the San Jose Water Company’s buried water-pipeline system (red). Image is overlaid with peak ground velocity contours 

(white lines; in increments of 8 centimeters per second) for a moment-magnitude-5.98 aftershock that occurs beneath the 

City of Mountain View 5 months after the mainshock of the HayWired earthquake scenario.

Table 13. Damage estimates for San Jose Water Company, 

California, buried water pipeline in the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

[%, percent]

Description Number

Mean number of repairs 1,054

Repairs per kilometer of pipe 0.27

Repairs due to wave passage 665 (63%)

Repairs due to liquefaction 345 (33%)

Repairs due to landslide 44 (4%)

Damage to large diameter pipe (≥20 inch diameter) 30 (3%)

Damage to small diameter pipe (<20 inch diameter) 1,024 (97%)

Breaks 294 (28%)

Leaks 760 (72%)

of number of pipe repairs by event in the HayWired scenario 

earthquake sequence and table 15 for subtotals by day. In those 

tables, “large diameter” means at least 20 inches. Table 16 

summarizes the expected value of the number of repairs by 

material, summing damage over the entire HayWired earthquake 

sequence. The table shows that the plurality of repairs are in 

asbestos cement pipe (481 breaks or leaks), and although the 

next-largest contributor is ductile-iron pipe (470 breaks or leaks), 

repairs are disproportionately from damage to asbestos-cement 

pipe, with an expected value of 0.23 repairs per 1,000 linear feet 

of pipe (0.75 per km) versus 0.11 repairs per 1,000 linear feet 

(0.37 per km) for ductile-iron pipe. The unsurprising implication 

is that it is better to have ductile-iron water pipe than asbestoscement water pipe.
234 The HayWired Earthquake Scenario—Engineering Implications

Table 14. Estimated number of leaks and breaks in San Jose Water 

Company, California, buried water pipeline in the HayWired scenario 

earthquake sequence (see table 12).

[Day 1 corresponds to April 18, 2018. Mw, moment magnitude]

Day Epicenter Name Mw

Leaks + 

breaks

Large

diameter

pipe

Small

diameter

pipe

1 Oakland Mainshock 7.05 1,054 30 1,024

1 Union City uc523 5.23 34 1 33

1 San Pablo sp504 5.04 6 0 6

12 Fairfield ff558 5.58 2 0 2

15 Fremont fr51 5.10 47 1 46

32 Oakland ok542 5.42 30 1 29

40 Palo Alto pa62 6.21 102 3 99

40 Menlo Park mp552 5.52 30 1 29

41 Palo Alto pa569 5.69 58 2 56

41 Atherton at511 5.11 30 1 29

67 Palo Alto pa522 5.22 47 2 45

74 Palo Alto pa526 5.26 48 2 46

166 Mountain View mv598 5.98 93 3 90

166 Cupertino cu64 6.40 172 6 166

166 Sunnyvale sv535 5.35 73 2 71

166 Santa Clara sc509 5.09 102 3 98

492 Palo Alto pa501 5.01 29 1 28

Total 1,957 59 1,897

Table 15. Total leaks and breaks by day in San Jose 

Water Company, California, buried water pipeline in the 

HayWired scenario earthquake sequence (see table 12).

[Day 1 corresponds to April 18, 2018]

Day Total leaks + 

breaks

Large 

diameter 

pipe

Small 

diameter 

pipe

1 1,094 31 1,063

12 2 0 2

15 47 1 46

32 30 1 29

40 132 4 127

41 88 3 85

67 47 2 45

74 48 2 46

166 440 14 426

492 29 1 28

Total 1,957 59 1,897

Table 16. Repair rate by material for San Jose Water Company, California, buried water 

pipeline in the HayWired scenario earthquake sequence (see table 12).

Material

1

Repairs

per 

1,000 linear feet

Repairs

per 

kilometer

AC 0.23 0.75

BCL 0.13 0.42

CCCL 0.19 0.62

CI 0.19 0.62

CL 0.12 0.40

CU 0.31 1.00

DCCL 0.14 0.45

DCIL 0.09 0.29

DFK 0.23 0.74

DICL 0.11 0.37

DIMCL 0.25 0.81

DS 0.07 0.21

FKCL 0.13 0.41

GALV 0.08 0.26

GG 0.23 0.74

HDPE 0.05 0.16

PB 0.08 0.27 1

See table 11 for explanation of material codes.

Material

1

Repairs

per 

1,000 linear feet

Repairs

per 

kilometer

PE 0.06 0.20

PP 0.05 0.17

PVC 0.09 0.29

RCP 0.08 0.26

S 0.13 0.42

SB 0.15 0.50

SG 0.12 0.39

SI 0.14 0.45

SOMCL 0.16 0.53

SS 0.19 0.63

TBD 0.18 0.60

WI 0.22 0.71

WS 0.12 0.39

WSCL 0.13 0.43

ZCCL 0.07 0.24

Total 0.15 0.50
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 235

The estimates in tables 14 and 15 ignore the potential for 

liquefaction outside the area with estimated liquefaction probability (that is, in places where liquefaction could occur but HayWired 

has no maps). They also ignore damage from ground failure in 

aftershocks, for which liquefaction and landslide probability were 

not estimated. However, because liquefaction requires long duration as well as strong shaking, and because aftershocks would tend 

to have short duration because of their moderate and small magnitude, they would tend to produce relatively few pipeline repairs as 

a result of liquefaction. Note that after the mainshock, the Mw 6.4 

aftershock near the City of Cupertino (table 14) adds the largest 

number of aftershock-related breaks and leaks in buried pipelines, 

likely setting SJWC back in restoring service.

Figure 19 is a heatmap (warmer color indicates greater 

concentration of damage) of SJWC pipeline repair rate in the 

HayWired scenario mainshock. To be clear, if any additional 

emphasis is needed, this map shows estimated damage rates in 

one scenario earthquake—the HayWired mainshock—not all 

possible earthquakes, not even all possible M7.0 earthquakes 

on the Hayward Fault. Different earthquakes produce different 

damage patterns. However, the point of a scenario is to 

understand what might realistically happen, and a heatmap 

makes a possible outcome more tangible, more useful for 

planning purposes. By planning for one scenario, one becomes 

more prepared for what actually happens, which will invariably 

differ from a scenario.

Figure 19 unsurprisingly shows greater damage near 

the fault and on soil with high liquefaction probability, with 

maximum values approaching 12 breaks or leaks per square 

kilometer (km2). Figure 20 shows an analogous map for the Mw 

6.4 Cupertino aftershock. Damage rates just exceed 1 break or 

leak per square kilometer in the aftershock in the neighborhoods 

Figure 19. Map of buried water-pipeline damage in San Jose Water Company’s, California’s, service area for the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario. Colors indicate mean repairs (breaks and leaks) per square kilometer. A 

warmer color indicates greater concentration of damage. To be informative, the color scale is shifted from those used in figures 20 and 21.

Palo Alto

Mountain View

Los Altos

Sunnyvale Santa Clara

Cupertino

Saratoga

Campbell

San Jose

Milpitas

Los Gatos

122° 121°45'

37°15'

0 2 4 KILOMETERS

0 2 4 MILES Hillshade derived from U.S. Geological Survey National Elevation Dataset, 2013.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Area CALIF of map

EXPLANATION

Mean pipeline repairs per

 square kilometer

<2

2–4

10–12

8–10

6–8

4–6

Major roadways

City boundaries

Water

 Calero 

Reservoir

Lexington

Reservoir
236 The HayWired Earthquake Scenario—Engineering Implications

Figure 20. Map of buried water-pipeline damage in San Jose Water Company’s, California’s, service area for the hypothetical moment-magnitude-6.4 

Cupertino aftershock in the HayWired scenario earthquake sequence. Colors indicate mean repairs (breaks and leaks) per square kilometer. A 

warmer color indicates greater concentration of damage. To be informative, the color scale is shifted from those used in figures 19 and 21.

Palo Alto

Mountain View

Los Altos

Sunnyvale Santa Clara

Cupertino

Saratoga

Campbell

San Jose

Milpitas

Los Gatos

122° 121°45'

37°15'

0 2 4 KILOMETERS

0 2 4 MILES Hillshade derived from U.S. Geological Survey National Elevation Dataset, 2013.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Area CALIF of map

EXPLANATION

Mean pipeline repairs per

 square kilometer

0.2

0.2–0.4

1.0–1.1

0.8–1.0

0.6–0.8

0.4–0.6

Major roadways

City boundaries

Water

 Calero 

Reservoir

Lexington

Reservoir

along the northern edge of the SJWC service area. Figure 21 

shows the heatmap for the entire sequence, with damage rates 

of approximately 15 repairs/km2 in the northeastern part of the 

service area.

I simulated damage locations by applying equation 49 once 

for the mainshock and once for each aftershock. Figure 22 shows 

pipeline segments with at least one simulated repair resulting 

from the Mw 7.0 HayWired mainshock. Figure 23 shows pipeline 

segments with at least one simulated repair resulting from the Mw

6.4 Cupertino aftershock. Figure 24 shows pipeline locations with 

at least one simulated repair resulting from the entire HayWired 

earthquake sequence.

San Jose Water Company Restoration Analysis

I take the following g-value (flow factor as discussed earlier) 

time series for lifelines upstream of water, and iterate later if 

necessary:

Consumables.— SJWC has one of the best stock of repair 

materials in the Bay Area (J. Wollbrinck, SJWC, oral commun., 

October 14, 2015). I assume sufficient repair consumable materials 

(such as pipe and clamps) are on hand or can be acquired as they 

are needed, that is, g(t)=1.0 for all t.

Fuel.—As of this writing, SJWC is in the process of 

preparing its fuel plan (J. Wollbrinck, SJWC, oral commun., 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 237

Figure 21. Map of buried water-pipeline damage in San Jose Water Company’s, California’s, service area for the entire hypothetical HayWired 

scenario earthquake sequence (events larger than moment-magnitude 5). Colors indicate mean repairs (breaks and leaks) per square kilometer. 

A warmer color indicates greater concentration of damage. To be informative, the color scale is shifted from those used in figures 19 and 20.

Palo Alto

Mountain View

Los Altos

Sunnyvale Santa Clara

Cupertino

Saratoga

Campbell

San Jose

Milpitas

Los Gatos

122° 121°45'

37°15'

0 2 4 KILOMETERS

0 2 4 MILES Hillshade derived from U.S. Geological Survey National Elevation Dataset, 2013.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Area CALIF of map

EXPLANATION

Mean pipeline repairs per

square kilometer

<2

2–4

10–12

8–10

6–8

4–6

Major roadways

City boundaries

Water

 Calero 

Reservoir

Lexington

Reservoir

October 14, 2015). I treat two possible outcomes—(1) the 

earthquake (Mw 7.0 HayWired scenario mainshock) happens 

before the plan is implemented and (2) the earthquake happens 

afterwards. If afterwards, I assume that the fuel plan is 

sufficient to ensure adequate supplies throughout the repair and 

restoration process, in which case g(t)=1.0 for all t. 

Without the fuel plan, I assume that there is sufficient fuel 

initially, but that shortages would impair restoration for a few days 

until emergency supplies were secured. Quantitatively, I assume 

that before implementing fuel plan:

g(t)=1.0 for 0≤t<3 days,

g(t)=0.25 for 3≤t<7 days,

g(t)=1.0 for t>7 days.

After implementing a fuel plan, I assume g(t)=1.0.

Electricity.—Pacific Gas and Electric Company (PG&E) 

was unable to offer a public estimate of the time required to 

restore power throughout the San Francisco Bay area after 

the HayWired scenario mainshock. On the basis, in part, of a 

Hazus-MH analysis, the HayWired project team and SJWC’s 

emergency manager believe it is realistic that 99.9 percent of 

customers in Santa Clara County will have power restored within 
238 The HayWired Earthquake Scenario—Engineering Implications

Figure 22. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a map of 

San Jose Water Company’s buried water-pipeline system. Simulated repairs (red circles) resulting from the hypothetical momentmagnitude-7.0 Cupertino aftershock in the HayWired scenario earthquake sequence are shown as red circles.

Figure 23. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a map of 

San Jose Water Company’s buried water-pipeline system. Simulated repairs (red circles) resulting from the hypothetical momentmagnitude-6.4 mainshock of the HayWired earthquake scenario are shown as red circles.

0

0 2 4 6 8

2 4 6 8 10 MILES

10 KILOMETERS

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, NOAA; 

data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015.

 Area 

of map CALIF

37.3°

37.4°

37.2°

122.2° 122° 121.8°

s

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, NOAA; 

data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015.

 Area 

of map CALIF

37.3°

37.4°

37.2°

122.2° 122° 121.8°

0

0 2 4 6 8

2 4 6 8 10 MILES

10 KILOMETERS

San Jose
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 239

Figure 24. Satellite image of Santa Clara Valley, California, at the southern end of San Francisco Bay, annotated with a map of San 

Jose Water Company’s buried water-pipeline system. Simulated repairs (red circles) resulting from the entire hypothetical HayWired 

scenario earthquake sequence are shown as red circles.

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, NOAA; 

data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2015.

 Area 

of map CALIF

37.3°

37.4°

37.2°

122.2° 122° 121.8°

0

0 2 4 6 8

2 4 6 8 10 MILES

10 KILOMETERS

2 weeks of the mainshock or 2 days after a M6+ aftershock. 

Quantitatively, I therefore take:

g(t)=1–exp(-0.4934×t), t measured in days after the 

 mainshock,

g(t)=1–exp(-3.45×t), t in days after the aftershocks on days 

 40 and 166.

Communication.—SJWC has battery powered radios for 

its repair crews that reach almost its entire service area. I assume 

that communication to facilitate coordination between utilities 

will be such a high priority that coordination will not be a 

constraint. I therefore assume g(t)=1.0.

Crews.—SJWC personnel estimated that they could 

realistically field between 20 and 25 crews on a work basis of 12 

hours on and 12 hours off. I therefore take w(t)=0.5 and c(t)=22 for 

purposes of equation 35.

I consider one more remediation measure. Suppose all of 

the more vulnerable SJWC buried pipe (especially 609 miles 

of asbestos-cement and cast-iron pipe) could be replaced with 

less-vulnerable pipe (for example, ductile-iron or plastic pipe). 

What would be the benefit in terms of damage reduction and 

accelerated recovery? To explore this question, I assume that 

all asbestos cement and cast-iron pipe is replaced with ductileiron or plastic pipe before the HayWired earthquake sequence 

occurs. I refer to this as the “ideal world” assumption. An SJWC 

engineer (J. Walsh, SJWC, oral commun., October 2, 2015) 

informed the HayWired project team that SJWC replaces 1 

percent, or 24 miles, of existing water mains every year. He did 

not imagine this study being used to change that percentage of 

replacement, but they might change their mix of pipes. Their 

replacement program is based on both consequences of failure 

and probability of failure. They consider a multitude of factors 

and then apply genetic algorithm software to predict leaks. They 

will likely add additional weighting to asbestos-cement and 

cast-iron pipe in close proximity to earthquake fault lines based 

on the present work. If SJWC were to focus on asbestos-cement 

and cast-iron pipe and were to continue to replace 24 miles of 

pipe per year, all 609 miles of asbestos-cement and cast-iron 

pipe could be replaced within 25 years.

Figure 25 shows the repair timeline for SJWC water-supply 

pipelines before and after implementing the fuel-management plan 

and after replacing all cast-iron and asbestos-cement pipe with 

ductile-iron or plastic pipe (the “ideal world”). Figure 26 illustrates 

the simulated restoration curve. If the Hazus-MH serviceability 

index realistically measures the fraction of services receiving any 

water, as reports produced by the Hazus software suggest, then 

“services available” in figure 26 measures the fraction of service 

connections receiving even small flows. If it means the postearthquake flow as a fraction of pre-earthquake flow, then figure 

26 underestimates the number of service connections receiving at 

least some water.
240 The HayWired Earthquake Scenario—Engineering Implications

Figure 25. Graph showing simulated repair timeline of San 

Jose Water Company, California, water-supply pipelines 

under three conditions for the HayWired scenario earthquake 

sequence. Conditions are (1) ideal world (all asbestos cement 

and cast-iron pipe is replaced with ductile-iron or plastic pipe 

before the earthquake sequence occurs and with a fuelmanagement plan), (2) with a fuel-management plan but no 

pipe replacement, and (3) without fuel-management plan or 

pipe replacement.

Figure 26. Graph showing simulated service availability of 

San Jose Water Company, California, water-supply system 

under three conditions for the HayWired scenario earthquake 

sequence. Conditions are (1) ideal world (all asbestos cement 

and cast-iron pipe is replaced with ductile-iron or plastic pipe 

before the earthquake sequence occurs and with a fuelmanagement plan), (2) with a fuel-management plan but no 

pipe replacement, and (3) without fuel-management plan or 

pipe replacement.

0

500

1,000

1,500

1 10 100 1,000

Repairs remaining

Time after mainshock, in days

Fuel shortage

Aftershocks

EXPLANATION

Ideal world

With fuel plan

No plan

Table 17. San Jose Water Company, California, total and 

per-customer average lost service days following the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake 

scenario.

[Numbers rounded to reduce the impression of excessive precision. Ideal 

world—all asbestos cement and cast-iron pipe is replaced with ductile-iron or 

plastic pipe before the earthquake sequence occurs and with fuel-management 

plan. R, number of days that service connection is without potable water; M, 

number of water service connections]

Condition

Lost service 

days, 

R×M

Resilience 

benefit, 

D(R×M)

Average lost 

service days 

(R)

As-is 940,000 0 4

With fuelmanagement plan750,000 190,000 3

Ideal world 470,000 470,000 2

0

50,000

100,000

150,000

200,000

250,000

1 10 100 1,000

Time after mainshock, in days

Number of water-service connections available

Fuel shortage

Aftershocks

Ideal world

With fuel plan

EXPLANATION

No plan

As discussed earlier, I view the area above the curves in 

figure 26 as a measure of resilience—less area means less impact, 

faster recovery, or both. The areas above the three curves are 

measured in units of service-days. That is, each day of lost water 

supply to a service connection equates with one service day. The 

areas above the three curves are shown in table 17—lost service 

days under as-is conditions, with a fuel-management plan, and 

under ideal-world conditions, that is, assuming that all brittle 

pipe is replaced before the HayWired scenario mainshock. The 

table shows the lost service days as a multiple of number of 

water service connections, that is, the average number of days 

that each service connection is without potable water under as-is 

conditions, with a fuel-management plan, and under ideal-world 

conditions. The difference between lost service days under as-is 

and what-if conditions (fuel-management plan or ideal world) 

measures the resilience benefit of the what-if condition—with a 

fuel-management plan and if all brittle pipe were replaced before 

the HayWired scenario mainshock occurs. 

Validation of San Jose Water Company 

Restoration Analysis

It is possible to compare the foregoing results for SJWC with 

other analyses as an initial check of the results. This validation is 

discussed below.

Cross Validation with San Jose Water Company’s 

Internal Damage Estimate

By scaling up the number of water pipeline breaks and leaks 

in the Mw 6.0 2014 South Napa earthquake, SJWC personnel 

estimated that the Mw 7.0 HayWired scenario mainshock would 

cause 1,200 water main breaks or leaks to their company’s system 

(J. Wollbrinck written commun., SJWC, October 19, 2015). The 

estimate follows this logic—the City of Napa has 370 miles of 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 241

water main and experienced 120 pipeline leaks the first week and 

more than 170 pipeline leaks in the first 6 months following the 

2014 earthquake. Scaling up by system size, SJWC estimates that 

Napa’s 120 leaks would equate with 850 leaks for SJWC and the 

170 leaks would equate with 1,200 leaks for SJWC. The South 

Napa earthquake was weaker than the mainshock modeled in 

the HayWired scenario, so the number of leaks could be more. 

The similarity between SJWC’s estimates of 850 increasing to 

1,200 and the ones produced here (1,054 increasing to 1,956) 

suggests that either or both are reasonable or neither is. That 

the two set of figures used two different approaches to arrive at 

a basically similar set of numbers tends to support both being 

reasonable, rather than neither. In either case, SJWC engineers 

found the results presented here to be reasonable (J. Walsh, 

written commun., SJWC, October 19, 2015), with the exception 

that Wollbrinck (written commun., SJWC, December 4, 2015) 

expected more damage to wrapped steel pipe because of its age 

and corrosion susceptibility.

Validation Against Northridge, Kobe, and South 

Napa Earthquakes

Jeon and O’Rourke (2005) report that the 1994 Northridge 

earthquake caused 1,095 breaks or leaks to buried pipeline 

operated by the Los Angeles Department of Water and Power, 

most of the damage occurring in the San Fernando Valley. Lund 

and others (2005) report that repairs took about 1 week. The 

present calculation suggests that SJWC would take 23 days to 

repair 1,176 repairs (mainshock plus 4 aftershocks through day 

15)—that is, about 3 times as long for about the same number of 

repairs. Lund and others (2005) do not report the number of crews 

required to perform those repairs. Presumably LADWP fielded 

more crews than SJWC has at its disposal.

Lund and others (2005) report that, according to M. 

Matsushita of the Kobe Municipal Waterworks Bureau, 1,757 

breaks and leaks occurred in buried water-supply distribution pipe 

in Kobe after the Mw 6.9 1995 Kobe earthquake and that repairs 

took 10 weeks. The present estimate of 3 weeks to repair 1,176 

breaks and leaks suggests one-third the time to repair two-thirds 

of the breaks and leaks. Thus, in a sense, the water-pipeline repair 

estimates for the Northridge and Kobe earthquakes bracket the 

restoration estimates for SJWC presented here.

The City of Napa repaired approximately 120 leaks 

and breaks in 5 days with approximately 10 crews working 

12-hour shifts (SPA Risk LLC, 2014), for a repair productivity 

of approximately 2.4 repairs per crew-day. The present model 

suggests that, before its fuel plan is implemented, San Jose Water 

Company would repair 1,176 breaks and leaks in 26 days with 

22 crews working 12-hour shifts, or 2.1 repairs per crew day, 

suggesting fairly good agreement.

Cross Validation with Hazus-MH

Using Hazus-MH (Federal Emergency Management Agency, 

2012), the estimated restoration of water supply in Santa Clara 

Table 18. Hazus-MH estimate of Santa Clara County, California, 

loss of water supply following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario 

(Federal Emergency Management Agency, 2012).

[%, percent]

Total Households without potable water following mainshock

households Day 1 Day 3 Day 7 Day 30 Day 90

565,853 504,596

89.20%

502,302

88.80%

497,394

87.90%

458,220

81.00%

137,185

24.20%

Figure 27. Graph comparing the estimated restoration of 

water supply in Santa Clara County, California, between the 

HayWired scenario model with fuel management plan and 

the Hazus-MH model (Federal Emergency Management 

Agency, 2012) for the hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake scenario.

County following the HayWired scenario mainshock (table 18). 

The estimates are for the mainshock only and do not reflect lifeline 

interaction. Applying the percentages to the number of SJWC’s 

customers, one can compare the HayWired scenario model 

with fuel management plan discussed in this chapter with the 

Hazus-MH model (fig. 27).

The present model and Hazus-MH disagree wildly in 

terms of initial level of water service and restoration time, with 

the Hazus-MH model estimating a six-times increase in time to 

restore service compared with the present model. Considering the 

validation against the Napa repair timeline, the present restoration 

model seems more plausible than the Hazus-MH restoration 

model. Why would Hazus-MH’s restoration model differ so 

markedly from the present one? The difference can be partly 

explained by the user-specified number of repair crews.

0

50,000

100,000

150,000

200,000

250,000

Number of water-service connections available

1 10 100 1,000

Time after mainshock, in days

Hazus-MH model—without 

 aftershocks or lifeline interaction

HayWired model—with fuel plan
242 The HayWired Earthquake Scenario—Engineering Implications

Effect of Lifeline Interaction and Consumable 

Limits

Suppose one ignored limitations in fuel and other consumables, and ignored impairment of electricity, telecommunications, 

and so on. How much difference do lifeline interaction and consumable limits make? Without these effects, damage is unaffected, 

but repairs could potentially proceed faster. Recall that equation 

36 gives the time τ(n,t) required to perform the nth repair, which 

occurs at time t. It can be expressed as a baseline productivity 

increased by a factor S(t) that accounts for how lifeline interaction 

and consumable limits slow repairs, that is:

 , (69)

where

 . (70)

The first multiplicand in equation 69 is the baseline 

productivity, that is, the time required to perform the nth repair, 

without lifeline interaction and consumable limits. The factor 

S(t), which is always at least 1.0, increases the repair time to 

account for lifeline interaction and consumable limits. Repeating 

the calculations for SJWC under as-is conditions but with S(t)=1 

produces an estimated 740,000 lost service days, about 80 percent 

of the value estimated considering lifeline interaction. Viewed 

another way, lifeline interaction and consumable limits decrease 

the calculated water-supply resilience in the area served by San 

Jose Water Company by 25 percent in the HayWired scenario. The 

factor would vary in other earthquakes, generally being larger the 

more dependent the utility is on other lifelines and consumables 

and the more these lifelines and consumables are impaired.

Case Study 2—East Bay Municipal 

Utility District

A second water system subjected to the same hypothetical 

earthquake sequence can be examined to see whether the model 

can produce plausible results twice. This section considers the East 

Bay Municipal Utility District’s (EBMUD) water-supply buried 

pipeline network.

East Bay Municipal Utility District Asset 

Definition

The following description is largely quoted from Contra 

Costa Local Agency Formation Commission (2008) and from 

conversations with EBMUD. EBMUD provides water- and 

sewage- treatment services for an area of approximately 331 

square miles in the eastern side of the San Francisco Bay. 

EBMUD serves approximately 1.3 million people in portions 

of Alameda County and Contra Costa County in California. 

EBMUD currently has an average annual growth rate of 0.8 

percent and is projected to serve 1.6 million people by 2030. 

As of 2015 it provides water to approximately 390,000 service 

connections. Approximately 100,000 service connections are 

located east of the East Bay Hills, and the other 290,000 service 

connections are to the west between the hills and San Francisco 

Bay. EBMUD’s administrative offices are located in The City of 

Oakland. EBMUD owns and maintains:

• 2 water storage reservoirs on the Mokelumne River,

• 5 terminal reservoirs,

• 91 miles of three separate water-transmission 

aqueducts,

• 4,162 miles of water mains (the only part of the system 

modeled here),

• 6 water-treatment plants,

• 29 miles of wastewater interceptor sewer lines, and

• A wastewater treatment facility rated at a maximum 

treatment capacity of 320 million gallons a day.

EBMUD provided an ArcGIS map of its water 

mains. The system is shown in figure 28. The map shows 

6,698 km (4,162 miles) of pipe of various types and lengths. 

Approximately 2,091 km of pipe are located east of the East 

Bay Hills, and the other 4,607 km of pipe are to the west 

between the hills and San Francisco Bay. Total quantities of 

pipe are summarized by material in table 19 and by diameter 

in table 20. EBMUD’s system is discretized into segments 

with an average length of 64 m and a standard deviation of 

79 m—short enough that earthquake shaking should vary little 

between ends of segments. Some of EBMUD’s pipe does not 

map well to an Eidinger type. One of the material codes do not 

appear in EBMUD’s glossary of pipe types and is probably a 

data-entry error. I have made a reasonable assumption about 

the intended meaning, but in any case, the total quantity is 

small—0.1 miles.

Terentieff and others (2015) report that 176,000 of 

390,000 water services are in pumped pressure zones. These 

pressure zones rely on 130 pumping stations, of which 117 

(90 percent) have no emergency generators. Therefore, I set the 

parameter z used in the lifeline interaction matrix for EBMUD 

to be 0.9×176,000/390,000=0.41, and uelectr=0.41+0.03=0.44. 

The factor 0.9 reflects the 90 percent of pumping stations 

that have no generator. Conceivably EBMUD could install 

emergency generators with large fuel tanks at all its pumping 

stations, in which case I can take uelectr=0.03. I take the former 

as the “real-world” scenario and the latter as an “ideal-world” 

scenario. I also assume that fuel limitations affect EBMUD 

the same as SJWC, and like SJWC, EBMUD can optionally 

develop a fuel-management plan and storage to ensure that fuel 

does not limit its ability to perform pipeline repairs.

∏( ) ( )

( )

( )

=

− × −

S t

u g t

1

1 1 i i

i

τ ( ) ( ) ( ) = ( ) × n t × d

w t c t , S t 0
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 243

Figure 28. Satellite 

image of the San 

Francisco Bay region, 

California, annotated 

with a map of the 

East Bay Municipal 

Utility District’s buried 

water-pipeline system 

(red) with dividing line 

(yellow) to approximately 

separate pipe and 

services east and west 

of the East Bay Hills.

10 MILES

10 KILOMETERS

0 2 4 6 8

0 2 4 6 8

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, 

NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2016.

 Area 

of map CALIF

38°

122.50° 122°

37.75°

SAN FRANCISCO BAY

Table 19. East Bay Municipal Utility District, California, pipe construction, associated with Eidinger (2001) vulnerability functions.

[Code, code for pipe material; count, number of segments of that material in East Bay Municipal Utility District buried water-pipeline system; miles, total length 

of pipe material; material description, description of pipe material; Eidinger type and ID, assumed corresponding vulnerability functions of Eidinger (2001) and 

their associated vulnerability factors K1 and K2 from table 1; PVC, polyvinyl chloride]

Code Count Miles Material, joint description1 Eidinger (2001) type2 ID2

A 24,543 1,136.4 Asbestos cement, unrestrained Asbestos cement with cement joint 14

C 33,747 1,322.1 Cast iron, unrestrained Cast iron with cement gasket 1

D 43 2.1 Ductile iron, unrestrained Ductile iron with rubber gasket 19

F 30 1.2 Fusible PVC, welded Welded steel with lap-arc welded joint 6

H 167 8.8 High-density polyethylene, weld PVC with rubber gasket 18

K 50 0.7 Copper, restrained Welded steel lap-arc weld joint small diameter 6

L 197 14.3 Reinforced concrete cylinder, unrestrained Concrete with steel-cylinder cement joint 16

N 8,613 380.4 PVC, unrestrained PVC with rubber gasket 18

P3 1 0.1 Pretensioned concrete cylinder, restrained Concrete with steel-cylinder cement joint 16

R 2 0.0 Reinforced concrete noncylinder Concrete with steel-cylinder cement joint 16

S 37,101 1282.4 Steel, welded Welded steel with lap-arc welded joint 6, 94

T 127 10.4 Pretensioned concrete cylinder, restrained Concrete with steel-cylinder lap-arc welded joint 15

W 71 2.7 Wrought iron Cast iron with cement gasket 1

Total 104,692 4,162

1

East Bay Municipal Utility District pipe material and description of joint; descriptions in italics are assumptions.

2

Closest equivalent corresponding vulnerability function from table 1.

3

One length of 48-inch-diameter pipe from 1927; P is probably a typo for T.

4

ID 6=small diameter (<20 inches); ID 9=large diameter (≥20 inches).
244 The HayWired Earthquake Scenario—Engineering Implications

EBMUD Hazard Analysis

Ground motion, liquefaction, landslide, coseismic slip, and 

afterslip for the HayWired scenario are quantified in Detweiler 

and Wein (2017). Figure 29 shows EBMUD’s buried waterpipeline system and PGV for the Mw 7.0 HayWired scenario 

mainshock. Figure 30 shows EBMUD’s buried water-pipeline 

system with liquefaction probabilities for the HayWired scenario 

mainshock. Liquefaction probability was not calculated for Contra 

Costa County, but it is assumed that liquefaction damage occurs 

in Contra Costa County in approximately the same proportion 

to shaking-induced damage as in Alameda County. Landslide 

probability in the EBMUD service area is mapped in figure 31. 

See figure 32 for a map of EBMUD’s water-supply buried pipeline 

system with a fence diagram showing coseismic slip. Figure 33 

shows PGV in one of the more damaging HayWired scenario 

aftershocks, a Mw 5.4 earthquake with an epicenter near Oakland.

The HayWired scenario does not have a map of afterslip, 

which progresses with time and varies spatially along the Hayward 

Fault. For present purposes, I assume that for most of the fault 

length, total slip (coseismic slip plus afterslip) equals 1.9 m, except 

where coseismic slip exceeds that amount. Afterslip evolves 

Diameter,

in inches

Length,

in miles

0.00 0.4

0.75 0.2

1.00 1.0

2.00 18.6

3.00 0.7

4.00 294.6

6.00 1,728.2

8.00 1,105.7

10.00 38.0

12.00 475.8

14.00 1.4

16.00 157.6

18.00 1.4

20.00 78.1

24.00 74.4

Table 20. Quantities of pipe by diameter in the East Bay 

Municipal Utility District, California, buried water-pipeline system.

Diameter,

in inches

Length,

in miles

25.00 0.5

30.00 36.5

36.00 66.8

42.00 18.5

48.00 38.3

54.00 8.8

60.00 2.6

66.00 6.8

69.00 4.6

72.00 0.0

78.00 0.2

84.00 1.8

90.00 0.2

96.00 0.1

108.00 0.0

Total 4,161.7

Figure 29. Satellite image of the San Francisco Bay region, California, annotated with a map of the East Bay Municipal Utility 

District buried water-pipeline system (red). Image is overlaid with mainshock peak ground velocities (PGV) for the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

10 MILES

10 KILOMETERS

0 2 4 6 8

0 2 4 6 8

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, 

NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2016.

 Area 

of map CALIF

0.0 0.5 1.0

PGV, in meters per second

1.5 2.0

122.5° 122°

38°

37.75°
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 245

10 MILES

10 KILOMETERS

0 2 4 6 8

0 2 4 6 8

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, 

NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2018.

 Area 

of map CALIF

122.5° 122°

37.75°

38°

EXPLANATION

Liquefaction probability

Not assigned

< 0.05

0.05–0.1

0.1–0.2

0.2–0.3

0.3–0.4

0.4–0.5

>0.5

SAN FRANCISCO BAY

Figure 30. Satellite image of the San Francisco Bay region, California, annotated with a map of the East Bay Municipal 

Utility District buried water-pipeline system (red). Image is overlaid with liquefaction probability for the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

over time following equations 6–9 in Aagaard and others (2012), 

with coseismic slip=0.09845, calculated using their figure 11 and 

Mw=7.0.

EBMUD Damage Analysis

Table 21 summarizes the estimated damage to EBMUD 

buried water pipelines from the HayWired scenario mainshock 

and aftershocks. Damage in the mainshock includes ground 

shaking, liquefaction, landsliding, and surface rupture. 

Because the liquefaction map does not include Contra Costa 

County, liquefaction damage in Contra Costa County is 

assumed to be proportional to earthquake shaking damage in 

Contra Costa County, in the same proportions as in Alameda 

County. An analysis of fire following earthquake for the 

HayWired scenario mainshock (Scawthorn, this volume) 

requires that the assumed liquefaction damage in Contra Costa 

County be assigned to particular locations; the damage is 

assigned to the cities of Pinole, Hercules, and Rodeo, where 

PGV values are very high and time-averaged shear-wave 

velocity to a depth of 30 m (VS30) values are low. As table 21 

illustrates, aftershock damage ignores landslides, liquefaction, 

and surface rupture. Note that the mainshock damage estimate 

for afterslip assumes that pipes that are ruptured by fault slip 

are damaged a second time by afterslip, EBMUD may decide 

to either install earthquake-resistant pipe (for example, highdensity polyethylene-plastic pipe or steel pipe with flexible 

joints that can tolerate extension, compression, and lateral 

deformation) or to temporarily install flexible hose until the 

damaged water main can be repaired or earthquake-resistant 

pipe can be installed. The table shows that the mainshock 

produces the majority of the overall damage but that after the 

mainshock 36 percent more damage occurs in aftershocks. 

Half the mainshock damage is associated with wave passage, 

the other half to liquefaction, landsliding, and fault offset.
246 The HayWired Earthquake Scenario—Engineering Implications

Figure 32. Oblique satellite image of the east bay part of California’s San Francisco Bay area, California, annotated with a map of the 

East Bay Municipal Utility District (EBMUD) buried water-pipeline system (red). Image is overlaid with a red “fence” along the northern 

Hayward Fault. The height of the red fence represents the right-lateral surface slip occurring on the Hayward Fault at the time of the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario. The tallest point on the fence, near the location 

where Interstate 80 crosses the fault between Richmond and Pinole, represents 2.1 meters of offset. At California Route 24 near 

Berkeley, the offset is 0.84 m. At Interstate 238 near Castro Valley, the offset is approximately 1.68 m.

10 MILES

10 KILOMETERS

4 6 8

6 8

0 2

0 2 4

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, 

NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2016.

 Area 

of map CALIF

EXPLANATION

Landslide probability, 

 in percent

0

0–2

2–15

15–32

>32

122.5° 122° 121.5°

38°

37.75°

SAN FRANCISCO BAY

Figure 31. Satellite image of the San Francisco Bay region, California, annotated with a map of the East Bay Municipal 

Utility District (EBMUD) buried water-pipeline system (red). Image is overlaid with landslide probabilities near the EBMUD 

service area for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

0 2 4 6 MILES

0 2 4 6 8 KILOMETERS

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, 

NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2016.

 Area 

of map CALIF

SAN FRANCISCO BAY
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 247

Figure 33. Satellite image of the San Francisco Bay region, California, annotated with a map of the East Bay 

Municipal Utility District (EBMUD) buried water-pipeline system (red). Image is overlaid with peak ground velocity 

contours (white lines; in increments of 5 centimeters per second) for a moment-magnitude-5.42 aftershock that occurs 

beneath the City of Oakland 32 days after the mainshock of the HayWired earthquake scenario.

2 4 6 8 10 MILES

2 4 6 8

0

0 10 KILOMETERS

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, 

NOAA; data SIO, NOAA, U.S., Navy, NGA, GEBCO, 2016.

 Area 

of map CALIF

Oakland

122.5° 122°

37.75°

38°

SAN FRANCISCO BAY

Table 21. Mean damage estimate for East Bay Municipal Utility District, California, buried 

water pipeline in the moment-magnitude-7 mainshock and aftershocks HayWired scenario 

earthquake sequence (see table 12).

[%, percent]

Mainshock Aftershocks Total

Mean number of repairs 4,294 1,395 5,688 

Repairs per kilometers of pipe 0.64 0.21 0.85

Due to wave passage 2,037 (47%) 1,395 (100%) 3,432 (60%)

Due to liquefaction 1,642 (38%) Not calculated 1,642 (29%)

Due to landslide 185 (4%) Not calculated 185 (3%)

Due to coseismic slip 214 (5%) Not calculated 214 (4%)

Due to afterslip 214 (5%) Not calculated 214 (4%)

Large diameter (≥20 inches diameter) 218 (5%) 84 (6%) 302 (5%)

Small diameter (<20 inches diameter) 4,076 (95%) 1,311 (94%) 5,386 (95%)

Breaks 1,582 (37%) 209 (15%) 1,791 (31%)

Leaks 2,712 (63%) 1,185 (85%) 3,898 (69%)
248 The HayWired Earthquake Scenario—Engineering Implications

Table 22 presents the estimated number of leaks plus breaks 

in EBMUD buried pipeline in each earthquake of the HayWired 

sequence. After the mainshock, 6 of 16 aftershocks each produces 

at least 100 breaks or leaks, and one produces more than 300, with 

significant numbers of breaks and leaks occurring almost 6 months 

after the mainshock, a point that is made somewhat clearer by 

table 23, which summarizes damage by day after the mainshock. 

Table 22. Estimated number of leaks plus breaks in East Bay Municipal Utility District, 

California, buried water pipeline in the HayWired scenario earthquake sequence (see table 12).

[Day 1 corresponds to April 18, 2018. Mw, moment magnitude]

Day Epicenter Name Mw

Leaks + 

breaks

Diameter

≥20 inches

Diameter

<20 inches

1 Oakland Mainshock 7.0 4,294 218 4,076

1 San Pablo sp504 5.04 102 6 96

1 Union City uc523 5.23 101 6 95

12 Fairfield ff558 5.58 49 3 46

15 Fremont fr510 5.1 37 2 35

32 Oakland ok542 5.42 323 20 304

40 Menlo Park mp552 5.52 44 3 41

40 Palo Alto pa62_ 6.2 141 8 133

41 Atherton pa569 5.11 61 4 57

41 Palo Alto at511 5.69 44 3 42

67 Palo Alto pa522 5.22 54 3 51

74 Palo Alto pa526 5.26 59 4 55

166 Cupertino sc509 6.4 25 2 24

166 Mountain View cu640 5.98 173 10 162

166 Santa Clara sv535 5.09 52 3 49

166 Sunnyvale mv598 5.35 102 6 96

492 Palo Alto pa501 5.01 28 2 26

Total 5,688 302 5,386

Table 23. Total leaks plus breaks in East Bay Municipal Utility 

District, California, buried water pipeline by day in the HayWired 

scenario earthquake sequence (see table 12).

[Day 1 corresponds to April 18, 2018]

Day Leaks + breaks1 Diameter

≥20 inches

Diameter

<20 inches

1 4,496 230 4,266

12 49 3 46

15 37 2 35

32 323 20 304

40 185 11 174

41 105 6 98

67 54 3 51

74 59 4 55

166 352 21 330

492 28 2 26

Total 5,688 302 5,386

1

Slight differences from numbers in table 22 and summation differences are 

due to rounding.

Table 24 details repair rate over the entire HayWired sequence 

by pipe material. Unsurprisingly, it shows that most damage is 

in brittle cast-iron and asbestos-cement pipe, with damage rates 

approaching 0.3 per 1,000 linear feet. Table 25 presents repair 

rate over the entire sequence by pipe diameter, with most repairs 

required in 6-inch- and 8-inch- diameter pipe, which together 

represent the majority of pipe in the system.
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 249

Table 24. Repair rate for East Bay Municipal Utility District, California, buried water pipeline in the 

HayWired scenario earthquake sequence.

Material1 Description Length, in feet Repairs2

Repairs per 

1,000 linear 

feet

A Asbestos cement, unrestrained 6,000,452 1,874 0.312

C Cast iron, unrestrained 6,980,888 2,206 0.316

D Ductile iron, unrestrained 10,841 5 0.433

F Fusible PVC, welded 6,478 1 0.156

H High-density polyethylene, weld 46,472 10 0.218

K Copper, restrained 3,646 0 0.135

L Reinforced-concrete cylinder, unrestrained 75,622 22 0.285

N PVC, unrestrained 2,008,486 438 0.218

P Reinforced-concrete cylinder 372 0 0.081

R Reinforced-concrete noncylinder 174 0 0.147

S Steel, welded 6,771,086 1,119 0.165

T Pretensioned concrete cylinder, restrained 55,106 10 0.183

W Wrought iron 14,319 4 0.284

Total 21,973,942 5,688 0.259

1

See material codes and descriptions in table 19.

2

Excludes damage estimated to occur in zones of liquefaction in Contra Costa County.

Table 25. Repair rate for East Bay Municipal Utility District, California, buried water pipeline by diameter in the HayWired scenario 

earthquake sequence.

Diameter,

in inches

Length,

in feet Repairs1 Repairs per 1,000 linear feet1

0 2,201 0 0.000

0.75 834 0 0.000

1 5,342 3 0.562

2 98,006 28 0.286

3 3,665 1 0.273

4 1,555,655 466 0.300

6 9,124,837 2,583 0.283

8 5,838,048 1,554 0.266

10 200,527 69 0.344

12 2,512,027 501 0.199

14 7,502 2 0.267

16 831,998 178 0.214

18 7,394 1 0.135

20 412,261 83 0.201

24 393,015 68 0.173

1

Where expected number of repairs is less than 0.5, number of repairs 

and repair rate per 1,000 linear feet are rounded to 0; table excludes damage assumed to occur in zones of liquefaction in Contra Costa County.

Diameter,

in inches

Length,

in feet Repairs1 Repairs per 1,000 linear feet1

25 2,581 0 0.000

30 192,540 30 0.156

36 352,938 51 0.145

42 97,882 16 0.163

48 202,222 35 0.173

54 46,248 11 0.238

60 13,778 3 0.218

66 35,784 3 0.084

69 24,207 2 0.083

72 70 0 0.000

78 978 0 0.000

84 9,598 1 0.104

90 994 0 0.000

96 689 0 0.000

108 122 0 0.000

Total 21,973,942 5,688 0.259
250 The HayWired Earthquake Scenario—Engineering Implications

Figures 34, 35, and 36 are damage heatmaps for EBMUD’s 

system. They map mean repairs (estimated per the present 

methodology) per square kilometer in the HayWired scenario 

mainshock, most-damaging aftershock (a Mw 5.4 event with an 

Oakland epicenter), and the entire HayWired earthquake sequence. 

Damage rates reach 50 repairs/km2 along the Hayward Fault and 

in zones of high liquefaction probability. The heatmap for the 

mainshock shows 20–50 repairs/km2 in large areas west of the 

fault, and no levels so high east of the fault, consistent with older 

pipe and higher liquefaction probability west of the fault. As a 

check of validity of the mainshock heatmap (fig. 34), notice that 

Figure 34. Map of buried water-pipeline damage in East Bay Municipal Utility District’s, California’s, service area for the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake scenario. Colors indicate mean repairs per square kilometer. A warmer 

color indicates greater concentration of damage. To be informative, the color scale is shifted from those used in figures 35 and 36.

it shows on the order of 10 leaks or breaks per square kilometer 

over an area of about 500 km2, approximately the 5,200 leaks and 

breaks estimated here.

As with the SJWC case study, the heatmaps show estimated 

repairs in the HayWired sequence. Different earthquakes would 

produce different damage patterns. The EBMUD heatmaps depict 

a single realistic damage pattern to make the HayWired scenario 

more tangible. EBMUD and its customers, by planning for this 

scenario, could better prepare for what actually happens in a future 

earthquake, which will invariably differ in total damage quantities, 

spatial distribution of damage, and over time.

Pinole

Richmond

Berkeley

Oakland

Alameda

San Leandro

Lafayette

Concord

Danville

Antioch

Dublin

Hayward

Pleasanton

San Francisco

San Pablo

Bay

SAN FRANCISCO BAY

122°30' 122°15' 122°

38°

37°45'

0 3 6 KILOMETERS

0 3 6 MILES Hillshade derived from U.S. Geological Survey National Elevation Dataset, 2013.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Major roadways

City boundaries

EXPLANATION

Mean pipeline repairs

 per square kilometer

<5

5–10

10–20

20–30

30–40

40–50

50–53

 Area 

of map CALIF
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 251

Figure 35. Map of buried water-pipeline damage in East Bay Municipal Utility District’s, California’s, service area for the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake scenario. Colors indicate mean repairs per square kilometer. A warmer 

color indicates greater concentration of damage. To be informative, the color scale is shifted from those used in figures 34 and 36.

Pinole

Richmond

Berkeley

Oakland

Alameda

San Leandro

Lafayette

Concord

Danville

Antioch

Dublin

Hayward

Pleasanton

San Francisco

San Pablo

Bay

SAN FRANCISCO BAY

122°30' 122°15' 122°

38°

37°45'

0 3 6 KILOMETERS

0 3 6 MILES Hillshade derived from U.S. Geological Survey National Elevation Dataset, 2013.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Major roadways

City boundaries

EXPLANATION

Mean pipeline repairs

 per square mile

1

2

3

4

5

 Area 

of map CALIF

EBMUD Restoration Analysis

See the San Jose Water Company Restoration Analysis 

section for the HayWired scenario’s assumptions about 

electricity, fuel, and communication. I further assume that 

EBMUD can acquire consumables—for example, pipe, 

clamps, and replacement valves—as quickly as needed to 

make repairs after the Mw 7.0 HayWired scenario mainshock. 

Regarding the availability of repair crews, EBMUD agrees 

with the scenario assumption that it would take as long as a 

week to assess the extent of damage and locate leaks before 

repairs can be initiated on a larger scale and that repair efforts 

would likely need to initially focus on larger diameter water 

mains. EBMUD staff also estimated that they may be able 

to field 20 of their own repair crews plus 15 crews provided 

through mutual aid, for a total about 35 repair crews. Of 

these, one-quarter are deployed east of the East Bay Hills, 

the other three-quarters are deployed to the west of the hills. 

I assume that repairs begin 5 days after the mainshock (the 

mainshock occurs on day 1), and that c(t) ramps up from 20 

to 35 crews over the following 14 days, and that crews work 

8-hour days until repairs are completed. Figure 37 illustrates 
252 The HayWired Earthquake Scenario—Engineering Implications

Figure 36. Map of buried water-pipeline damage in East Bay Municipal Utility District’s, California’s, service area for the entire hypothetical 

HayWired scenario earthquake sequence (events larger than moment-magnitude 5). Colors indicate mean repairs per square kilometer. A 

warmer color indicates greater concentration of damage. To be informative, the color scale is shifted from those used in figures 34 and 35.

Pinole

Richmond

Berkeley

Oakland

Alameda

San Leandro

Lafayette

Concord

Danville

Antioch

Dublin

Hayward

Pleasanton

San Francisco

San Pablo

Bay

SAN FRANCISCO BAY

122°30' 122°15' 122°

38°

37°45'

0 3 6 KILOMETERS

0 3 6 MILES Hillshade derived from U.S. Geological Survey National Elevation Dataset, 2013.

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Major roadways

City boundaries

EXPLANATION

Mean pipeline repairs

 per square kilometer

<5

5–10

10–20

20–30

30–40

40–50

50–55

 Area 

of map CALIF

repair crew availability, which is expressed mathematically 

here:

a(t)=0.33

c(t)=2 t<6

 =[2t – 5] 6 ≤ t<20

 =35 20 ≤ t<41

 =20 41 ≤ t

The notation [x] means the integer part of the quantity x, used 

here because there are no such things as fractional crews.

Figure 38 illustrates the initial level of water service 

according to equation 29—the loss of system pressure results 

in approximately 87 percent of service connections east of the 

East Bay Hills receiving water shortly after the mainshock, 8 

percent of those west of the hills.

It seems reasonable to assume that PG&E will take 2 weeks 

to restore electricity to 99.9 percent of customers in Alameda and 

Contra Costa Counties. EBMUD personnel concur. I therefore use 

the following electricity restoration curve for these counties:

 

 . (71)

Figure 39 shows the estimated service restoration 

curve for EBMUD under three conditions—(1) as is, (2) 

assuming EBMUD develops a fuel-management plan to 

ensure that repair crews are never slowed or idled from lack 

of fuel, and (3) under ideal conditions. If the Hazus-MH 

serviceability index realistically measures the fraction of 

service connections receiving any water, as reports produced 

g t( ) = −1 exp ( ) −0.493t

.
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 253

Figure 37. Graph showing East Bay Municipal Utility District, 

California, repair-crew availability by day following the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake 

scenario. East, areas east of the East Bay Hills; west, areas west of 

the East Bay Hills between the hills and San Francisco Bay.

Figure 38. Graph showing initial East Bay Municipal Utility 

District, California, water service availability (equation 29) 

east and west of the East Bay Hills, in the east bay part of the 

San Francisco Bay area, following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

0

10

20

30

40

1 10 100 1,000

Crews available

Time after mainshock, in days

East

West

Total

EXPLANATION

Figure 39. Graphs showing East Bay Municipal Utility District, California, water-service restoration curves by day following the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario. A, water-service restoration curves under as-is 

conditions, including total for the system and service east and west of the East Bay Hills, in the east bay part of the San Francisco Bay 

area. B, Total-system water-service restoration curves under several conditions—(1) with a fuel-management plan in place and all 

brittle pipe replaced, (2) with a fuel-management plan only, and (3) as-is conditions. With a fuel-management plan in place and all brittle 

pipe replaced before the mainshock, about 8 million service days are lost (lost connections×days), with average lost service days per 

lost connection being 21 days. With only a fuel-management plan in place and brittle pipe not replaced before the mainshock, about 

18.9 million service days are lost, with average lost service days per lost connection being 48 days. Under as-is conditions following the 

mainshock, about 19.91 million service days are lost, with average lost service days per lost connection being 49 days.

0.00

0.25

0.50

0.75

1.00

0.01 0.1 1

Serviceability index

Average pipe break rate per kilometer

East

West

0

100,000

200,000

300,000

400,000

1 10 100 1,000

Water service connections available

Time after mainshock, in days

1 10 100 1,000

Fuel plan and brittle

 pipe replaced

Inspection

Loss

of resilience

East of hills

West of hills

Total as-is

EXPLANATION

A B

As-is conditions

Fuel plan only

EXPLANATION
254 The HayWired Earthquake Scenario—Engineering Implications

by the Hazus software suggest, then “services available” 

means the fraction of service connections receiving even 

small flows. If it means the post-earthquake flow as a fraction 

of pre-earthquake flow, then the charts underestimate the 

number of service connections receiving at least some water. 

Note that “ideal conditions” refers to the case in which the 

HayWired mainshock occurs after all of EBMUD’s brittle 

pipe is replaced and all pumping stations are supplied with 

emergency generators and fuel. The curves show that under 

as-is conditions, full restoration takes 28 weeks (just more 

than 6 months). Under ideal-world conditions, full service 

is restored in 14 weeks (just more than 3 months), roughly 3 

months earlier than under as-is conditions. 

Figure 40 shows the progress of EBMUD repairs in the 

HayWired earthquake sequence, again illustrating the possible 

effects of fuel limitations, an estimate of the benefit of an 

in-place fuel-management plan, and the potential benefit of 

replacing brittle pipe in advance.

One can view the area above the curves in figure 40 as a 

measure of resilience—less area means less negative impact, 

faster recovery, or both. The areas above the three curves (as-is 

conditions, with fuel plan, and ideal-world) are measured in units 

of service days. That is, each day of lost water supply to a service 

connection equates with one service day. The areas above the three 

curves are shown in table 26. The table shows lost service-days 

under as-is conditions, with a fuel plan, and under ideal-world 

conditions, that is, in which all cast iron and asbestos cement pipe 

is replaced before the earthquake. The difference between lost 

Figure 40. Graphs showing East Bay Municipal Utility District, California, water-service repair progress following the hypothetical momentmagnitude-7 mainshock and aftershocks HayWired scenario earthquake sequence (see table 12). A, Curves for remaining repairs under 

as-is conditions, including total for the system and service east and west of the East Bay Hills, in the east bay part of the San Francisco Bay 

area. B, Curves for remaining repairs in the total system with (1) a fuel-management plan in place only and (2) a fuel-management plan in 

place and all brittle pipe replaced (the “ideal world”).

1 10 100 1,000 1 10 100 1,000

Time after mainshock, in days

East of hills

West of hills

Total as-is

EXPLANATION

A B

Ideal world

With fuel plan

Total as-is

EXPLANATION

0

1,000

2,000

3,000

4,000

5,000

6,000

Repairs remaining

Aftershocks Aftershocks

service days under as-is and what-if conditions (fuel-management 

plan or ideal world) measures the resilience benefit of the what-if 

condition—with a fuel-management plan and if all brittle pipe 

were replaced before the hypothetical earthquake occurred. 

Although full restoration takes much longer, the table also shows 

average number of days that each service connection goes without 

potable water under as-is conditions, with the fuel-management 

plan, and under ideal-world conditions.

Validation of EBMUD Damage and Recovery 

Estimates

As with SJWC, it is possible to perform some initial 

checks of the foregoing results, to see at least whether they are 

reasonable. This validation is discussed below.

Cross Validation with EBMUD Internal Damage 

Estimates

EBMUD commissioned a private study that estimated, 

among other things, the potential for water-supply pipeline 

damage resulting from a M7.0 earthquake on the Hayward Fault. 

As described by Terentieff and others (2015), that 1997 study 

estimated 4,054 pipe breaks and leaks, most of which occur 

in cast-iron and asbestos-cement pipe. EBMUD performed an 

internal study in 1997 of large-diameter pipe (at least 16- to 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 255

Table 26. East Bay Municipal Utility District, California, average lost service days following the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

[Numbers rounded to reduce the impression of excessive precision. Ideal world—fuel-management plan in place and all asbestos 

cement and cast-iron pipe is replaced with ductile-iron or plastic pipe before the earthquake sequence occurs. R, number of days 

that service connection is without potable water; M, number of water service connections]

Condition Lost service-days R×M Resilience benefit, D(R×M) Average lost days R

Total as-is 19,100,000 49 

With fuel-management plan 18,900,000 200,000 48 

Ideal world 8,100,000 11,000,000 21 

24-inch diameter, depending on pipe material) and estimated 

334 breaks and leaks could result from a M7.0 earthquake on the 

Hayward Fault. Terentieff and others (2015) report that EBMUD 

has initiated an infrastructure renewal program with a goal of 

replacing approximately 1 percent of its pipe per year, focusing 

first on cast-iron and asbestos-cement pipe.

The 1997 estimate of 4,054 breaks and leaks is close to the 

4,300 breaks and leaks estimated here for the Mw 7.0 HayWired 

scenario mainshock and somewhat smaller than the present 

estimate of 5,688 breaks and leaks in the entire HayWired 

earthquake sequence. The 1997 estimate of 334 breaks and leaks 

in large diameter pipes is somewhat higher than the present 

estimate of 218 breaks and leaks in pipe of at least 20-inches 

diameter in the HayWired mainshock, although similar to the 

present estimate of 302 large-diameter breaks and leaks in the 

entire HayWired sequence.

It seems realistic that EBMUD will complete much of its 

replacement of the 61 percent of its pipes that are constructed 

of cast iron or asbestos cement before a large earthquake occurs 

on the Hayward Fault. The issue is more complicated than just 

whether a Mw 7.0 or larger earthquake occurs on the Hayward 

Fault. According to the Uniform California Earthquake Rupture 

Forecast, version 3 (UCERF3), fault section data (Field and others, 

2013), the chance that such an earthquake will occur in the next 61 

years is approximately 16 percent on the northern segment of the 

Hayward Fault, 12 percent on the southern segment of the fault, 

and 26 percent on either of these fault segments—significant, but 

nowhere near certain.

Comparison with EBMUD Judgment, Northridge, 

Kobe, and Napa Restoration

As previously noted, Jeon and O’Rourke (2005) report 

that the 1994 Northridge earthquake caused 1,095 breaks or 

leaks to buried pipeline operated by the LADWP, whereas Lund 

and others (2005) report that repairs took about 1 week. The 

calculation discussed here for the HayWired scenario suggests 

that EBMUD would take 28 weeks to repair 5,700 breaks and 

leaks from the entire HayWired earthquake sequence. Although 

the estimate of just more than 6 months to restore EBMUD 

buried water pipelines following the HayWired mainshock 

agrees with EBMUD’s judgment, it is about 28 times as long 

for about five times the number of repairs, or about one-fifth 

on average as fast as LADWP’s actual repair rate following the 

Northridge earthquake.

Also, as previously noted, the Kobe Municipal Waterworks 

Bureau experienced 1,757 breaks and leaks after the 1995 Kobe 

earthquake and that repairs took 10 weeks, that is, 176 repairs per 

week. The present estimate of 28 weeks to repair 5,700 breaks and 

leaks (200 repairs per week) is roughly on par with Kobe.

The City of Napa repaired approximately 120 leaks and 

breaks in 5 days (170 repairs per week) after the 2014 South Napa 

earthquake, approximately equal to the 200 repairs per week 

estimated here.

Cross Validation with Hazus-MH

Table 27 shows the Hazus-MH estimate of water-supply 

restoration in Contra Costa and Alameda Counties, where 

EBMUD operates. As before, the estimates are for the HayWired 

mainshock only and do not reflect lifeline interaction. Applying 

the percentages to the number of EBMUD’s customers, one can 

compare the two models, as shown in figure 41. The two models 

substantially disagree in terms of initial service availability and in 

terms of restoration time.

Effect of Lifeline Interaction and Consumable 

Limits on EBMUD

EBMUD does not expect to begin repairs until about 

day 7 following the HayWired scenario mainshock, after 

power and telecommunications have been largely (though not 

completely) restored. Therefore, lifeline interaction will have 

little effect on EBMUD in the HayWired scenario.

Performance of Other Water Utilities 

Based on Hazus-MH

It is time consuming to acquire the necessary data and 

to perform the analysis of a water-supply system. The San 

Francisco Bay region has on the order of 30 of them. To 

estimate the effects of the HayWired earthquake sequence on 

the metropolitan area, I apply the proposed modification of the 

Hazus-MH (Federal Emergency Management Agency, 2012) 

methodology to the analysis of the bay region’s water-supply 

system (see Seligson and others, this volume). First, I adjust 

estimates of water-supply restoration time to account for the 
256 The HayWired Earthquake Scenario—Engineering Implications

Table 27. Hazus-MH estimate of Contra Costa and Alameda County, California, loss of water supply following the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

[%, percent]

Analysis Households without water following mainshock

Day 1 Day 3 Day 7 Day 30 Day 90

Hazus-MH1 855,207

98.58%

854,738

98.53%

853,731

98.41%

845,534

97.47%

762,299

87.87%

This analysis2 71% 71% 70% 46% 24%

1

Hazus-MH figures as reported by the software (Doug Bausch, written commun., Federal Emergency Management Agency, 2014), with its estimate 

of 867,495 total households.

2

Estimates rounded to the nearest percent to reduce the appearance of excessive accuracy. Hazus-MH figures are as reported by the software.

Figure 41. Graph comparing the estimated restoration of water 

supply connections for East Bay Municipal Utility District between 

the HayWired scenario model in this analysis and the Hazus-MH 

model for the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario (Seligson and others, this volume).

0

100,000

200,000

300,000

400,000

1 10 100 1,000

Water-service connections available

Time after mainshock, in days

Hazus-MH

This analysis

EXPLANATION

differences between Hazus’ default assumptions of repair crew 

availability.

SJWC estimates it can field 22 repair crews to respond to 

damage in its service area of 225,000 service connections, or 

approximately 1 crew per 10,000 service connections. Hazus-MH 

seems to equate households with service connections. With the 

inventory that FEMA enhanced for the San Francisco Bay region 

before the HayWired project, Hazus-MH estimates that Santa Clara 

County has 565,863 households, which it seems to equate with the 

number of service connections. To adjust Hazus’ default number of 

pipeline repair crews for purposes of equation 61, I take:

 . (72)

EBMUD engineers agree with the HayWired scenario 

assumption that EBMUD can field 35 crews to respond to 

damage in its system that provides water to 390,000 service 

connections. Those figures indicate approximately 1 crew per 

11,000 service connections, versus SJWC’s estimate of as many 

as 1 crew per 9,000 service connections. I assume therefore that 

Alameda and Contra Costa Counties (EBMUD’s service area) 

have approximately 1 crew (4 workers) per 11,000 households, 

Santa Clara County (SJWC’s service area) has 1 crew per 9,000 

households, and other counties have 1 crew per 10,000 households 

(an approximate mean of EBMUD and SJWC, in round numbers). 

Table 28 shows corresponding restoration-rate adjustment factors 

for repair-crew availability. The household-weighted average 

value of the repair-crew factor q/q0 is 1.37, although it is higher in 

the strongly shaken counties of Alameda and Santa Clara.

To address lifeline interaction for the purposes of equation 

67—the product term inside the summation—I take rate-limiting 

factors u and the flow of rate-limiting factors g as those proposed 

for EBMUD. That is, I assume that approximately half of services 

are in pumped pressure districts that require electricity, that 

electricity is restored within 1 week, and that there is a temporary 

fuel shortage between days 3 and 7.

Hazus’ estimates of the number of service connections 

with water service at time t

j

 (normalized by the number of 

households) are recapped in table 29. The assumption of 

complete restoration at day 210 is mine. Hazus-MH does 

not report level of service beyond 90 days, but I suggest that 

full restoration would likely be completed within 7 months. 

The table reports values of in the sense of equation 61. 

Table 30 shows the restoration curves adjusted for repair-crew 

availability and lifeline interaction but using the restoration 

curves for Alameda, Contra Costa, and Santa Clara Counties 

as those calculated in the case studies under as-is conditions. 

Table 31 shows the restoration curves adjusted with a fuelmanagement plan in place in all counties. Alameda, Contra 

Costa, and Santa Clara Counties are as those calculated in the 

case studies with a fuel plan. Table 32 shows the restoration 

curves with emergency generators and fuel in all counties. 

Alameda, Contra Costa, and Santa Clara counties are as those 

calculated in the case studies under ideal-world conditions. The 

tables are illustrated in figure 42A through D. Note that, because 

Hazus-MH analyses were unavailable for lifelines subjected 

to aftershocks in the HayWired earthquake sequence, the 

restoration curves for counties other than Santa Clara, Alameda, 

and Contra Costa Counties do not reflect aftershock damage.

= × ×

=

q

q

1

100

565,863

10,000

4

2.26

0

Vˆ(t)
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 257

Table 28. Repair-crew adjustment factor, q/q0, for San Francisco 

Bay region, California, buried water-supply pipeline restoration.

County Households Crews Workers q/q0

Alameda 523,366 48 190 1.90

Contra Costa 344,129 31 125 1.25

Marin 100,650 10 40 0.40

Merced 63,815 6 26 0.26

Monterey 121,236 12 48 0.48

Napa 45,402 5 18 0.18

Sacramento 453,602 45 181 1.81

San Benito 15,885 2 6 0.06

San Francisco 329,700 33 132 1.32

San Joaquin 181,629 18 73 0.73

San Mateo 254,103 25 102 1.02

Santa Clara 565,863 63 251 2.51

Santa Cruz 91,139 9 36 0.36

Solano 130,403 13 52 0.52

Sonoma 172,403 17 69 0.69

Stanislaus 145,146 15 58 0.58

Yolo 59,375 6 24 0.24

Table 29. Hazus-MH unadjusted estimate of water-service 

restoration for San Francisco Bay region, California, counties 

following the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

[%, percent]

County Day

1 3 7 30 90 210

Alameda 1% 1% 1% 1% 2% 100%

Contra Costa 3% 3% 3% 5% 28% 100%

Marin 91% 98% 100% 100% 100% 100%

Merced 98% 99% 100% 100% 100% 100%

Monterey 100% 100% 100% 100% 100% 100%

Napa 100% 100% 100% 100% 100% 100%

Sacramento 100% 100% 100% 100% 100% 100%

San Benito 98% 100% 100% 100% 100% 100%

San Francisco 40% 52% 87% 100% 100% 100%

San Joaquin 100% 100% 100% 100% 100% 100%

San Mateo 30% 34% 41% 100% 100% 100%

Santa Clara 11% 11% 12% 19% 76% 100%

Santa Cruz 100% 100% 100% 100% 100% 100%

Solano 98% 100% 100% 100% 100% 100%

Sonoma 100% 100% 100% 100% 100% 100%

Stanislaus 100% 100% 100% 100% 100% 100%

Yolo 100% 100% 100% 100% 100% 100%

County Day

1 3 7 30 90 210

Alameda 29% 29% 30% 54% 76% 100%

Contra Costa 29% 29% 30% 54% 76% 100%

Marin 91% 94% 95% 100% 100% 100%

Merced 98% 98% 98% 100% 100% 100%

Monterey 100% 100% 100% 100% 100% 100%

Napa 100% 100% 100% 100% 100% 100%

Sacramento 100% 100% 100% 100% 100% 100%

San Benito 98% 98% 100% 100% 100% 100%

San Francisco 40% 55% 67% 100% 100% 100%

San Joaquin 100% 100% 100% 100% 100% 100%

San Mateo 30% 34% 35% 80% 100% 100%

Santa Clara 63% 70% 73% 100% 100% 100%

Santa Cruz 100% 100% 100% 100% 100% 100%

Solano 98% 99% 99% 100% 100% 100%

Sonoma 100% 100% 100% 100% 100% 100%

Stanislaus 100% 100% 100% 100% 100% 100%

Yolo 100% 100% 100% 100% 100% 100%

Table 30. Hazus-MH-based estimate of water-service 

restoration after adjusting for repair crew availability and lifeline 

interaction without a fuel-management plan for San Francisco Bay 

region, California, counties following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

[Santa Clara, Alameda, and Contra Costa Counties are as calculated in case 

studies. %, percent]

Table 31. Hazus-MH-based estimate of water-service 

restoration after adjusting for repair crew availability and lifeline 

interaction with a fuel-management plan for San Francisco Bay 

region, California, counties following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

[Santa Clara, Alameda, and Contra Costa Counties are as calculated in case 

studies. %, percent]

County Day

1 3 7 30 90 210

Alameda 32% 33% 35% 59% 81% 100%

Contra Costa 32% 33% 35% 59% 81% 100%

Marin 91% 94% 100% 100% 100% 100%

Merced 98% 98% 99% 100% 100% 100%

Monterey 100% 100% 100% 100% 100% 100%

Napa 100% 100% 100% 100% 100% 100%

Sacramento 100% 100% 100% 100% 100% 100%

San Benito 98% 98% 100% 100% 100% 100%

San Francisco 40% 55% 100% 100% 100% 100%

San Joaquin 100% 100% 100% 100% 100% 100%

San Mateo 30% 34% 41% 86% 100% 100%

Santa Clara 63% 70% 73% 100% 100% 100%

Santa Cruz 100% 100% 100% 100% 100% 100%

Solano 98% 99% 100% 100% 100% 100%

Sonoma 100% 100% 100% 100% 100% 100%

Stanislaus 100% 100% 100% 100% 100% 100%

Yolo 100% 100% 100% 100% 100% 100%
258 The HayWired Earthquake Scenario—Engineering Implications

Table 32. Hazus-MH-based estimate of water-service restoration 

after adjusting for repair crew availability and lifeline interaction with a 

fuel-management plan, emergency generators and fuel at all pumping 

stations, and brittle pipe replaced (ideal world) for San Francisco Bay 

region, California, counties following the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

[Santa Clara, Alameda, and Contra Costa Counties are as calculated in case 

studies. %, percent]

County Day

1 3 7 30 90 210

Alameda 44% 44% 47% 73% 97% 100%

Contra Costa 44% 44% 47% 73% 97% 100%

Marin 91% 94% 100% 100% 100% 100%

Merced 98% 98% 99% 100% 100% 100%

Monterey 100% 100% 100% 100% 100% 100%

Napa 100% 100% 100% 100% 100% 100%

Sacramento 100% 100% 100% 100% 100% 100%

San Benito 98% 98% 100% 100% 100% 100%

San Francisco 40% 55% 100% 100% 100% 100%

San Joaquin 100% 100% 100% 100% 100% 100%

San Mateo 30% 34% 41% 86% 100% 100%

Santa Clara 71% 78% 85% 100% 100% 100%

Santa Cruz 100% 100% 100% 100% 100% 100%

Solano 98% 99% 100% 100% 100% 100%

Sonoma 100% 100% 100% 100% 100% 100%

Stanislaus 100% 100% 100% 100% 100% 100%

Yolo 100% 100% 100% 100% 100% 100%

Conclusions

This chapter introduces an analytical model of watersupply damage and restoration that can be implemented solely 

with GIS and spreadsheet software—no black-box, proprietary 

tool required. (Note: the damage part of the new model is not 

novel; the restoration part is.)

Summary

The analytical model of water-supply damage and 

restoration introduced in this chapter suggests that a Mw 7.0 

Hayward Fault earthquake could damage buried pipeline 

networks that supply potable water to the East Bay part of the 

San Francisco Bay area to the extent that the average customer of the EBMUD would be without water for 6 weeks. 

Some EBMUD customers would be without water service for 

6 months. The total loss of resilience (measured as the area 

above graph curves of number of customers receiving service 

versus time) totals 19 million service-days lost. That loss can 

be reduced by half if current efforts to replace brittle pipe 

are completed before the next large earthquake occurs—the 

replacement taking six decades at a reasonably aggressive rate 

of 1 percent per year. The loss can be reduced on the order of 

200,000 service days by reducing or eliminating EBMUD’s 

dependence on commercial fuel supplies.

The model suggests that a HayWired-like earthquake 

could cost the average customer of SJWC 4 days of lost water 

service, with a total loss of resilience equal to 940,000 service 

days. Implementing a fuel-management plan could reduce both 

calculations by about a quarter. If SJWC completes replacement 

of all cast-iron and asbestos-cement pipe before a significant 

earthquake occurs (about 25 years at current replacement rates), 

the as-is losses (no fuel-management plan of replacement of brittle 

pipe) would be reduced by about half.

Both case-study utilities (EBMUD and SJWC) reviewed 

the study described in this chapter and find its results reasonable 

and in line with previous studies, their own judgment, and 

comparison with restoration of other water-supply systems in other 

earthquakes. Results of the present study are greatly at odds with 

restoration estimates produced by Hazus-MH, which estimates 

much-longer restoration times and much-greater loss of resilience.

Innovations Introduced Here

The methodology proposed here models damage and 

restoration of buried water-supply pipelines subject to earthquake 

shaking (called wave passage) and ground failure (liquefaction, 

landslide and surface rupture of a fault). The methodology 

assumes that the analyst already has maps of the earthquake 

excitation (especially PGV and ground-failure probability) and 

of the pipeline system in question. Many authors have proposed 

such models in the past. The present model may be unique in 

combining some unusual features:

1. It treats lifeline interaction and limited consumables by 

reducing the speed with which repairs are completed in 

relation to how important those upstream lifelines and 

other resources are to repair productivity. In the example of 

SJWC, it was estimated that lifeline interaction and limited 

consumables increase the loss of resilience (measured in 

terms of lost service days) by 25 percent.

2. The model considers aftershocks.

3. It can be evaluated either deterministically (with no 

uncertainty) or as stochastic model (accounting for major 

sources of uncertainty).

4. It can be carried out with a GIS system and a spreadsheet 

and does not require other special software such as 

Hazus-MH. Doing so provides the analyst more insight into 

the reasonableness of model results and underlying sources 

of damage and restoration delay.

5. It offers an approximate method to modify Hazus-MH 

lifeline damage and restoration-time estimates to account for 

lifeline interaction.

6. It does not require hydraulic analysis of the damaged 

system or the system as repairs proceed. That 

simplification necessarily involves a common but 
Chapter N. A New Model of Water-Network Resilience, with Application to the HayWired Scenario 259

Figure 42. Graphs showing restoration of water service connections for San Francisco Bay region, California, counties 

following the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario. A, Restoration curves 

according to initial Hazus-MH calculations. B, Restoration curves after adjusting for repair-crew availability and lifeline 

interaction. C, Restoration curves after all utilties have implemented a fuel-management plan. D, Restoration curves with fuelmanagement plan in place and all brittle pipe replaced (the ideal world). Curves in B, C, and D use the more-detailed case-study 

calculations for Contra Costa, Alameda, and Santa Clara counties instead of calculations from Hazus-MH.

Water-service connections available, in percent

Time after mainshock, in days

0

25

50

75

100

0

25

50

75

100

0 28 56 84 112 140

Alameda

EXPLANATION

Contra Costa

Santa Clara

San Mateo

San Francisco

Marin

San Benito and Solano

Other counties

A

168 0 28 56 84 112 140 168

B

C D

questionable assumption relating break rate to loss of 

service, and it prevents the analyst from gaining important 

insight into variation in pressure throughout the system.

7. It mostly avoids reliance on expert opinion and 

unpublished data. Expert opinion seems to be required to 

quantify the rate-limiting factors u and the service time 

series g(t) for damage to other lifelines that have not been 

modeled.

The methodology is applied here to examine the effect of a 

large hypothetical but not exceedingly rare earthquake in the San 

Francisco Bay region on the buried pipeline networks of SJWC 

and EBMUD. Results tend to agree with operator judgment, 
260 The HayWired Earthquake Scenario—Engineering Implications

various restoration measures observed in past earthquakes, and 

comparable aspects of other models.

Like all other aspects of the HayWired earthquake scenario, 

the outcomes presented here will invariably differ in quantity, 

spatial distribution, and over time from whatever actually happens when (not if) a large earthquake next strikes on the Hayward 

Fault or other San Francisco Bay region fault. By preparing for the 

water-supply impacts of this hypothetical earthquake sequence, 

the region can better prepare for whatever real earthquake actually 

occurs.

Research Needs

The methodology proposed here mostly avoids reliance 

on opinion and judgment, but it would be practical to eliminate 

reliance on much of the opinion and judgment that remains. 

Presumably the u factors based on expert opinion could be 

replaced by compiling sufficient earthquake experience from 

utilities, perhaps by some survey analogous to that of Lund and 

Schiff (1991). The time series g(t) could be replaced by explicit 

modeling. It would be interesting to know if there were some 

theoretical justification for water service restoration following 

a power law as in equation 32, and whether or why the power 

should be approximately 2/3. It would be also desirable:

• To examine more closely or replace the Hazus-MH 

formulation of the serviceability index. Can one relate 

water-pipeline break rate to the fraction of customers 

receiving various thresholds of flow, such as minimal flows 

for cooking and basic sanitary needs?; 

• To know whether and how a large mainshock degrades the 

seismic resistance of apparently undamaged pipe;

• To add treatment of earthquake damage to other elements 

in a water-supply system, including tanks, tunnels, canals, 

valves, and reservoirs;

• Regarding the Lund and Schiff (1991) database, it would be 

desirable for water utilities to adopt a standard database for 

recording leaks and breaks, especially in earthquakes, so as 

to inform future improvements in mathematical functions 

for pipe-fragility; and 

• To model the damage to water-supply systems subjected 

to the August 24, 2014, South Napa earthquake to see how 

well it agrees with experience.

Acknowledgments

The author thanks Jacob Walsh and James Wollbrinck of 

SJWC, along with Julia Halsne, Andrea Chen, Clifford Chan, 

Xavier Irias, Roberts McMullin, Mike Ambrose, Devina Ojascastro, 

and Serge Terentieff of EBMUD for their help constructing and 

testing the models presented here and reviewing the report.

References Cited

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and Graymer, R.W., 2010a, Ground-motion modeling of 

Hayward Fault scenario earthquakes, part I; Construction 

of the suite of scenarios: Bulletin of the Seismological 

Society of America, v.100, no. 6, p. 2927–2944, https://doi.

org/10.1785/0120090324.

Aagaard, B.T., Graves, R.W., Rodgers, A., Brocher, T.M., 

Simpson, R.W., Dreger, D., Petersson, N.A., Larsen, 

S.C., Ma, S., and Jachens, R.C., 2010b, Ground-motion 

modeling of Hayward Fault scenario earthquakes, part 

II; Simulation of long-period and broadband ground 

motions: Bulletin of the Seismological Society of 

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https://doi.org/10.3133/sir20175013v1.


Chapter O

Case Studies of Tall-Building Structural Analyses and 

Downtime and Loss Assessment for the HayWired 

Scenario Mainshock

By Ibrahim M. Almufti,1 Carlos Molina-Hutt,2 Michael W. Mieler,1 Nicole A. Paul,1 and Chad R. Fusco1

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013]

1

Arup, North America, Ltd.

2

University College, London.

Abstract

The HayWired scenario examines a hypothetical 

earthquake (mainshock) with a moment magnitude (Mw) of 

7.0 occurring on April 18, 2018, at 4:18 p.m. on the Hayward 

Fault in the east bay part of California’s San Francisco 

Bay area. The tall-building performance assessment for the 

scenario includes a structural analysis and downtime and loss 

estimates for three archetype buildings that generally represent 

typical tall-building construction in the San Francisco and 

Oakland downtown areas. Two of the archetype buildings are 

steel-frame office towers (20 story and 40 story) designed to 

1970s-era building code and professional practice, and one is a 

reinforced-concrete residential tower (42 story) designed using 

the current state-of-the-art performance-based design approach. 

An inventory of tall buildings in San Francisco is also 

provided. Time histories of ground motions from the simulated 

mainshock fault rupture were provided by the U.S. Geological 

Survey (USGS). The simulated records closest to the San 

Francisco and Oakland downtown locations were selected to 

assess the performance of the archetype buildings.

A nonlinear response-history analysis (NLRHA) of each 

building was done using LS-DYNA software to ascertain the 

expected building performance. From a structural-engineering 

perspective, new concrete residential buildings performed 

relatively well with minimal structural damage. However, older 

steel-frame buildings sustained structural damage, including 

widespread yielding and some fractures of the (pre-Northridge) 

moment-frame beam connections in the upper stories. This 

did not result in collapse nor significant residual drifts, which 

indicates that the steel-frame buildings may be repairable. The 

interstory drifts for all analyses were within the interstory drift 

limit (story height/50) allowed by current building codes under 

the design basis earthquake. Peak floor accelerations (as much as 

roughly the acceleration due to gravity at the Earth’s surface, g) 

were significant due to higher mode effects, particularly in the 

reinforced concrete tower. (The period, or mode of vibration, of a 

building is a dynamic property that typically refers to the time it 

takes for a building, if excited horizontally by ground shaking, to 

complete one cycle of sway back and forth.)

A loss assessment was performed using the probabilistic 

approach (that is, Monte Carlo simulation) outlined in the Federal 

Emergency Management Agency’s (FEMA) P-58 document. The 

likely costs to repair and (or) replace damaged components are 

calculated based solely on FEMA P-58, whereas repair time and 

downtime are estimated using the FEMA P-58 based methodology 

outlined in the 2013 REDiTM (Resilience-based Earthquake Design 

Initiative for the Next Generation of Buildings) rating system. 

The engineering-demand parameters from the NLRHA were used 

as input parameters to assess the likelihood that each building 

component (structural and nonstructural) would sustain a discrete 

state of damage (defined by fragility functions). The extent and 

severity of the expected damage is used to assess the likelihood 

that building reoccupancy and (or) functionality is hindered (by 

repair-class assignments defined in REDi) enabling the estimation 

of repair time and total downtime (to achieve reoccupancy and 

(or) functionality). It is noted that the estimation of downtime has 

considerable uncertainty due to a number of interdependent factors 

that are difficult to quantify. The downtime estimates include the 

potential for delays to the initiation of repairs (termed impeding 

factors), including contractor mobilization, financing repairs, and 

permitting. The estimates for the impeding factors are based on 

those quantified in REDi and our additional research. The time to 

achieve functionality is also dependent on utility disruption times 

estimated elsewhere for the HayWired mainshock, but these did 

not govern any of the scenarios considered.

All scenarios resulted in significant downtime to achieve 

functional recovery, primarily due to nonstructural component 

damage. Existing steel-frame office towers had a median repair 

cost of 7.4–17.5 percent of replacement value, a median time to 

achieve reoccupancy of 186–250 days, and median time to achieve 

functional recovery of 242–288 days. New reinforced-concrete 

residential towers had a median repair cost of 3.1–5.1 percent 

of replacement value, a median time to achieve reoccupancy of 
268 The HayWired Earthquake Scenario—Engineering Implications

121–139 days, and median time to achieve functional recovery of 

224–245 days. The time to mobilize contractors (accounting for 

the bidding process, scarcity of contractors, and time to mobilize 

labor, material and equipment) often governed the total downtime. 

In the scenario, buildings located in Oakland generally sustained 

higher losses (see upper end of ranges provided in the table) than 

those in San Francisco due to the closer proximity to the Hayward 

Fault. Although the nonlinear analysis indicated that steel-frame 

buildings sustain some fractured beam connections, it is unlikely 

that an inspector would observe them because there are so few 

instances of this behavior.

Although the older steel-frame buildings have welldocumented structural deficiencies, none of the analyses 

undertaken resulted in structural collapse. This is primarily 

due to the relatively low shaking intensity from the HayWired 

scenario mainshock as compared to the maximum considered 

earthquake (MCE) and even design level defined in modern 

building codes. A 55-percent probability of collapse at MCE 

for the same San Francisco archetype steel-frame buildings in 

this study (approximately five times the acceptable collapse 

limit in modern codes) was estimated in a previous work. It is 

important to note that this study is limited to one structurally 

regular archetype steel-frame building, whereas in reality, many 

older buildings exhibit structural irregularities such as setbacks 

(and some even lack corner columns) that may make them 

more collapse-prone. In addition, the assessment considers only 

one scenario ground-motion record and thus does not account 

for the variability of ground shaking important for assessing 

collapse risk. Therefore, the results should not necessarily be 

interpreted to mean that a large earthquake on the Hayward 

Fault would not cause any tall-building collapses. Even one tall 

building damaged to the point of near collapse in a downtown 

area could cause closure of a significant number of surrounding 

buildings, even if the surrounding buildings are undamaged.

Introduction

The HayWired scenario examines a hypothetical 

earthquake (mainshock) with a moment magnitude (Mw) of 7.0 

occurring on April 18, 2018, at 4:18 p.m. on the Hayward Fault 

in the east bay part of California’s San Francisco Bay area. 

The U.S. Geological Survey (USGS) is currently leading an 

effort to study the implications of the scenario mainshock and 

aftershock sequence for the greater San Francisco Bay region. 

As part of this work, the USGS identified the need to assess the 

performance of the existing tall-building stock in downtown San 

Francisco and Oakland. We undertook an analysis of archetype 

tall buildings representative of the building stock to estimate 

damage levels, downtime, and repair costs for the HayWired 

mainshock scenario in San Francisco and Oakland. A 55-percent 

probability of collapse at the maximum considered earthquake 

(MCE) for the same San Francisco archetype steel-frame 

building in this study (approximately five times the acceptable 

collapse limit in modern codes) was estimated in a previous 

work (Molina-Hutt and others, 2015). 

Objectives

This study describes the performance of three building 

types found to be representative of the tall-building stock in the 

respective cities’ downtown areas:

• 1970s 40-story steel moment-resisting frame office 

building in San Francisco only.

• 1970s 20-story steel moment-resisting frame office 

building in San Francisco and Oakland.

• New 42-story reinforced-concrete core-only building 

designed to current code and Pacific Earthquake 

Engineering Research Center (PEER) (TBI Guidelines 

Working Group, 2010) in San Francisco and Oakland. 

(Although no new concrete towers of this height currently 

exist in Oakland, future development plans are likely to 

include them.)

Structural analysis results include peak interstory drifts, 

residual drifts, racking drift (where applicable), floor accelerations, and coupling beam rotation (where applicable). Repair costs 

are expressed in terms of both absolute dollars and percentage 

of building replacement cost. A breakdown of repair costs by 

building components (both structural and nonstructural) is also 

provided for each building.

Downtime estimates include repair time and downtime (the 

time to achieve either reoccupancy, functionality, or full recovery) 

in days. Downtime accounts for repair time plus impeding factors 

(such as the time required to mobilize contractors and engineers) 

and utility disruption.

Report Structure

Including the Introduction, this report is organized into seven 

sections—(1) Introduction; (2) HayWired Ground Motions, which 

describes the ground motions used in the nonlinear dynamic 

analyses, and provides a comparison of the HayWired scenario 

and the code design spectrum for each location; (3) Description 

of Archetype Buildings, Design and Analysis Assumptions, 

which describes the structural design—including the structural 

configuration, structural properties, and typical details—of the 

three archetype buildings, and the numerical modeling of the 

buildings; (4) Loss-Assessment Methodology, which describes the 

loss-assessment methodology; (5) Summary of Loss-Assessment 

Results, which provides a summary comparison of the lossassessment results; (6) Conclusion; and (7) References Cited.

The report also has 12 appendixes. Appendix 1 provides 

lists of the structural and nonstructural building components 

in each archetype building, including component quantities, 

median engineering design parameters (EDPs) and dispersions 

for each damage state, and repair-class assignments defined in 

REDiTM (Resilience-based Earthquake Design Initiative for the 

Next Generation of Buildings). Appendixes 2 through 11 provide 

detailed structural analysis and loss assessment results for each 

building, as shown in table 1. Appendix 12 provides an inventory 

of tall building stock in San Francisco.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 269

Table 1. Contents of appendixes 2 through 12.

Appendix Building case study Abbreviation

2 40-story steel-frame building in San Francisco, baseline orientation S-SF-B-43

3 40-story steel-frame building in San Francisco, rotated orientation S-SF-R-43

4 20-story steel-frame building in San Francisco, baseline orientation S-SF-B-20

5 20-story steel-frame building in San Francisco, rotated orientation S-SF-R-20

6 20-story steel-frame building in Oakland, baseline orientation S-OK-B-20

7 20-story steel-frame building in Oakland, rotated orientation S-OK-R-20

8 42-story reinforced-concrete building in San Francisco, baseline orientation C-SF-B-46

9 42-story reinforced-concrete building in San Francisco, rotated orientation C-SF-R-46

10 42-story reinforced-concrete building in Oakland, baseline orientation C-OK-B-46

11 42-story reinforced-concrete building in Oakland, rotated orientation C-OK-R-46

HayWired Ground Motions

The performance of the archetype building is assessed 

at two locations for which ground-motion time histories have 

been provided for the HayWired mainshock—southwest 

of downtown San Francisco (37.775° N, 122.402° W) and 

downtown Oakland (37.804° N, 122.270° W). These record 

sets are USGS code number CT06075018000 and SF384, 

respectively (see Aagaard and others, 2010). Figure 1 

illustrates these locations within the San Francisco Bay area. 

Out of the five ground-motion sets that USGS provided for 

Oakland, the one in downtown Oakland was selected, because 

this is where most tall buildings in Oakland are located. Five 

ground-motion sets were also provided for San Francisco, 

but none were located in the Financial District, where most 

tall buildings are located. The ground-motion record located 

roughly 1.5 kilometers (km) southwest of the Financial 

District (see fig. 1) was selected because its time-averaged 

shear-wave velocity to a depth of 30 meters (VS30) value was 

most representative of the soil conditions (site class D of the 

International Building Code) in the Financial District.

Time histories for the Oakland and San Francisco ground 

motions in the Mw 7.0 HayWired scenario mainshock are shown 

in figures 2 and 3, respectively. These are surface motions 

generated by a three-dimensional (3D) physics-based simulation 

for the scenario mainshock (Aagaard and others, 2017).

SAN

FRANCISCO

BAY

PA

CIFIC

OCEAN

122.4°

Golden 

 Gate

122.5° 122.3°

37.8°

37.7°

5 KILOMETERS

3 MILES

1 2 3 4

1 2

0

0

Base map ©2018 Google, Data SIO, NOAA, U.S. Navy, 

NGA, GEBCO, Data CSUMB SFML, CA OPC.

CT06075018000

SF384

CALIF

Area

of map

Figure 1. Map 

of the central San 

Francisco Bay area, 

California, showing 

locations at which 

archetype buildings 

were assessed in 

San Francisco (code 

CT06075018000, 

see Aagaard and 

others, 2010) and 

downtown Oakland 

(code SF384, see 

Aagaard and others, 

2010) for performance 

in ground-motions 

for the hypothetical 

moment-magnitude-7.0 

mainshock of the 

HayWired earthquake 

scenario.
270 The HayWired Earthquake Scenario—Engineering Implications

Figure 2. Graphs showing acceleration, velocity, and displacement time histories of the east-west and north-south 

components of the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario for downtown San 

Francisco, California (code ct06075018000, see Aagaard and others, 2010). Acceleration, in meters per second squared Velocity, in meters per second

East component

Time, in seconds

North component

Displacement, in meters 
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 271

Figure 3. Graphs showing acceleration, velocity, and displacement time histories of the east-west and north-south 

components of the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario for downtown 

Oakland, California (code SF384, see Aagaard and others, 2010). Acceleration, in meters per second squared Velocity, in meters per second

East component

Time, in seconds

North component

Displacement, in meters 
272 The HayWired Earthquake Scenario—Engineering Implications

For comparison purposes, figures 4 and 5 show the ASCE 

7–10 (American Society of Civil Engineers, 2010) design 

acceleration-response spectrum for the design-basis earthquake 

(DBE) scenario and the HayWired scenario ground-motion 

spectra selected for the Oakland and San Francisco sites, 

respectively. It can be observed that the HayWired groundmotion spectra selected for assessment have relatively low 

spectral accelerations near the fundamental period of the tall 

buildings (and consequently, relatively low spectral-displacement demands), although significant structural demands could 

be induced from higher mode effects.3 Moreover, because the 

epicenter of the HayWired mainshock is located in Oakland, 

there is less forward directivity for the cities of Oakland and 

San Francisco than if the epicenter was at either end of the 

Hayward Fault rupture, particularly compared to an epicenter at the south end of the rupture. Therefore, the HayWired 

mainshock ground motions may represent a nonconservative 

scenario for the buildings in this study. Acceleration, in g

Period, in seconds

EXPLANATION

ASCE 7–10 (site class D)

HayWired mainshock E-W

HayWired mainshock N-S

1.2

1.0

0.8

0.6

0.4

0.2

0

0 1 2 3 4 5 6

Acceleration, in g

Period, in seconds

EXPLANATION

ASCE 7–10 (site class D)

HayWired mainshock E-W

HayWired mainshock N-S

1.0

0.8

0.6

0.4

0.2

0

0 1 2 3 4 5 6

Figure 4. Graph showing 

ASCE 7–10 (American Society 

of Civil Engineers, 2010) design 

acceleration-response spectrum 

for its design-basis earthquake 

(DBE) versus ground-motion 

spectra for hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario for 

the representative site in Oakland, 

California. g, acceleration due to 

gravity at the Earth’s surface; N-S, 

north-south; E-W, east-west.

Figure 5. Graph showing 

ASCE 7–10 (American Society 

of Civil Engineers, 2010) design 

acceleration-response spectrum for 

its design-basis earthquake (DBE) 

versus ground-motion spectra for 

hypothetical moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario for the 

representative site in San Francisco, 

California. g, acceleration due to 

gravity at the Earth’s surface; N-S, 

north-south; E-W, east-west.

Description of Archetype Buildings, 

Design, and Analysis Assumptions

This section describes the building archetypes developed for 

this study of tall-building performance in the HayWired scenario 

mainshock. This includes a discussion of design and analysis 

assumptions.

Steel Office Tower

Forty-story and 20-story steel moment-resisting frame 

(MRF) office buildings designed according to the 1973 Uniform 

Building Code (International Conference of Building Officials, 

1973) were selected as archetype buildings for this study. The 

archetype buildings are rectangular in plan and represent the state 

of design and construction practice from the mid-1970s to the 

mid-1980s.

3

The period (or mode of vibration) of a building is a dynamic property that typically refers to the time it takes for a building, if excited horizontally by ground 

shaking, to complete one cycle of sway back and forth.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 273

X

Y

MF MF MF MF

MF MF MF MF

MF MF MF MF

MF MF MF MF

MF MF MF

MF MF MF

MF MF MF

MF MF MF MF MF MF

MF MF MF MF MF MF

20’ 20’ 20’ 20’

20’ 20’ 20’ 20’ 20’ 20’

120’

80’

A B C D E

7

6

5

4

3

2

1

A B

Design

The design of the archetype steel-MRF buildings is in 

accordance with the provisions of the 1973 Uniform Building 

Code and 1973 Structural Engineers Association of California 

(SEAOC) Bluebook (Structural Engineers Association of 

California, 1973), which was commonly used to supplement 

minimum design requirements. The design criteria for the 1970s 

archetype buildings would have been equivalent, whether in 

Oakland or in San Francisco, according to the requirements of the 

Uniform Building Code (UBC) in 1973 (both locations fall within 

the same seismic and wind zones). The 40-story and 20-story 

archetype buildings represent the existing building stock in San 

Francisco, whereas the building stock in Oakland is generally 

limited in height to 20 stories.

Based on examination of existing building drawings, the 

40-story building layout consists of 38 levels of office space, 2 

levels for mechanical equipment—one at mid-height and one at 

the top of the building—and three basement levels for parking. 

The overall height of the structure is 507.5 feet (ft) (154.7 meters, 

m) above ground and 30 ft (9.1 m) below grade. The 20-story 

building consists of 19 levels of office space—one level for 

mechanical equipment at the top of the building and one basement 

level for parking. The overall height of the structure is 267.5 ft 

(81.5 m) above ground and 10 ft (3.0 m) below grade.

For both buildings, the enclosure is composed of precast 

concrete panels and glass windows. The floor system is composed 

of 3-inch (in.) (76 millimeters, mm) concrete slab over 2.5-in. 

Figure 6. Diagrams showing 

archetype 40-story steelmoment-frame office building 

(A) plan and (B) isometric (from 

Molina-Hutt and others, 2016). 

MF, moment frame; ’, feet.

(64 mm) metal deck supported by steel beams meeting ASTM 

standard A36 (see ASTM International, 2014) with a yield stress 

of 36 kilopounds per square inch (ksi) (248 megapascal, MPa). 

The steel columns are ASTM A572 (see ASTM International, 

2015) with a yield stress of 42 ksi (290 MPa). As shown in figure 

6, the archetype structural system consists of a space frame with 

20–40 ft (6.1–12.2 m) spans using wide flange beams, built-up 

box columns, and welded beam-column connections. Typical 

story heights are 10 ft (3.0 m) for basement levels, 20 ft (6.1 m) at 

ground level (lobby), and 12.5 ft (3.8 m) for typical office levels as 

stated in Molina-Hutt and others (2016).

Because the buildings are rectangular in plan, two analyses 

were performed in which the building was aligned in two different 

orientations (with grid lines aligned in the cardinal directions) 

in consideration that an earthquake produces different ground 

shaking intensity normal and parallel to a fault, respectively. These 

orientations are shown in figure 7.

For the archetype buildings, because wind drift limits 

governed the MRF section sizes, beams and columns have low 

strength-utilization ratios under the building code prescribed 

seismic forces of the 1970s. Typical member sizes and connection 

details were verified against available existing building drawings. 

Consistent with these records, built-up box columns and wide 

flange beams were selected for the archetype buildings. A 

summary of the design section sizes of the 40-story steel MRF and 

of the 20-story MRF are provided in tables 2 and 3, respectively. 

More information on the design and analysis of the steel-frame 

buildings can be found in Molina-Hutt and others (2016).
274 The HayWired Earthquake Scenario—Engineering Implications

Figure 7. Diagrams showing (A) baseline and (B) rotated orientations of the archetype 

40-story steel-moment-frame office building shown in figure 6 (from Molina-Hutt and 

others, 2016). MF, moment frame; N-S, north-south; E-W, east-west; ’, feet.

A B

Baseline orientation Rotated orientation

Table 2. Lateral resisting system section sizes for the 40-story archetype steel-moment-frame office building (modified from MolinaHutt and others, 2016). 

[t, flange thickness; W, wide-flange beam width, in inches; lb/ft, pound per foot]

Level

range, in feet

Wide flange beams Box columns

Exterior short 

span (W×lb/ft)

Interior short 

span (W×lb/ft)

Interior long

span (W×lb/ft)

Interior, in 

inches

Exterior short 

elevation (x), in 

inches

Exterior long 

elevation (y), in 

inches

Base to 10 W36×256 W36×282 W30×124 22×22, t=3 26×26, t=3 20×20, t=2.5

Base to 10 W33×169 W36×194 W27×84 20×20, t=2 26×26, t=2.5 20×20, t=2

11 to 20 W33×118 W33×169 W27×84 18×18, t=1 24×24, t=1.5 18×18, t=1

21 to 30 W24×62 W27×84 W24×76 18×18, t=0.75 24×24, t=1 18×18, t=0.75

30 to roof W36×256 W36×282 W30×124 22×22, t=3 26×26, t=3 20×20, t=2.5

Table 3. Lateral resisting system section sizes for the 20-story archetype steel-moment-frame building (modified from Molina-Hutt and 

others, 2016).

[t, flange thickness; W, wide-flange beam width, in inches; lb/ft, pound per foot]

Level

range, in feet

Wide flange beams Box columns

Exterior short 

span (W×lb/ft)

Interior short 

span (W×lb/ft)

Interior long 

span (W×lb/ft)

Interior, in 

inches

Exterior short 

elevation (x), in 

inches

Exterior long 

elevation (y), in 

inches

Base to 10 W30×148 W30×173 W30×211 22×22 t=2 22×22, t=2.5 22×22, t=1.5

11 to 20 W27×129 W27×146 W30×191 22×22 t=1.5 22×22, t=2.0 22×22, t=1
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 275

A B C

Typical Details

Figure 8 shows some of the typical details frequently 

observed in existing building drawings. Welds in beam-column 

connections before 1994 had very low toughness, as evidenced 

by fractures observed in the Mw 6.7 1994 Northridge, California, 

earthquake (Bonowitz and Maison, 2003). It is assumed that these 

fracture-prone pre-Northridge moment connections are common in 

1970s construction. Therefore, all beam-column connections were 

modeled as pre-Northridge moment connections. Column splices 

are typically located 4 ft above the floor level, approximately every 

three floors. Observed typical splice connection details consist 

of partial joint-penetration welds of roughly half the thickness 

of the smaller section being connected. When subject to tensile 

forces, these splices can only carry a fraction of the moment 

capacity and (or) axial-tension capacity of the smallest section size 

being connected. Furthermore, experimental tests on heavy steel 

section-welded splices have illustrated sudden failures with limited 

ductility (Bruneau and Mahin, 1990). Based on this evidence, 

column splice failures are considered in this assessment.

Building Dynamic Properties

The dynamic properties, including the fundamental and 

second mode period of vibration in each translational direction, 

from a modal analysis of the archetype steel-frame buildings 

Figure 8. Diagrams showing typical details observed in existing building drawings. A, Plan section of typical moment connection; B, elevation of 

typical moment connection; C, typical splice. t, flange thickness; ’, inch; ”, feet; Rad. Max., maximum radius. (From Molina-Hutt and others, 2016.)

Table 4. Dynamic properties in x and y directions of archetype 20- and 40-story steel-moment-frame buildings 

examined for response in the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

[--, no data]

Vibration 

mode

Steel-frame building (40 story) Steel-frame building (20 story)

Period, in seconds Effective/total mass, in 

percent Period, in seconds Effective/total mass, in percent

1 5.62 (x) 60.79 (x) 2.33 (x) 75.15 (x)

2 5.29 (y) 60.80 (y) 2.04 (y) 73.33 (y)

3 2.86 (torsional) -- (torsional) 1.47 (torsional) -- (torsional)

4 1.86 21.33 (x) 0.78 13.44 (x)

5 1.66 19.28 (y) 0.65 15.74 (y)

is presented in table 4. The table shows that 80 percent of the 

modal mass is mobilized in the first two translational modes 

for the 40-story tower (that is, mode 1 and 4 in the x direction 

and mode 2 and 5 in the y direction), whereas 90 percent of the 

modal mass is mobilized in the first two translational modes for 

the 20-story tower.

Finite Element Modeling

The steel-moment-frame office buildings were modeled 

using LS-DYNA, an advanced general-purpose multiphysics 

simulation software package developed by Livermore Software 

Technology Corporation (2009). The use of LS-DYNA 

for performance-based seismic analysis has become more 

common, and several recent building projects in California 

have undergone rigorous seismic peer review by experts. A 

nonlinear response-history analysis, using an explicit solver—

which accounts for secondary moment effects and nonlinear 

materials—was done using the ground motions discussed 

above in HayWired Ground Motions, which were applied at the 

base of the model.

The model was subjected to the ground motions in 

conjunction with expected gravity loads, which include 

self-weight, superimposed dead loads, and 25 percent of the 

unreduced live loads. Fixed supports were assumed at the base 

of the structure. Soil-structure interaction was not considered. 
276 The HayWired Earthquake Scenario—Engineering Implications

For tall buildings with embedded basements in soft soils, the 

kinematic effects are likely to slightly reduce the peak floor 

accelerations associated with higher modes. The embedment 

depth is important and we note that older steel-frame buildings 

typically have one or two basement levels. A 2.5-percent 

critical damping was assumed based on work by PEER (TBI 

Guidelines Working Group, 2010).

The steel-frame office buildings were modeled with the 

following element types:

• One-dimensional (1D) lumped plasticity elements for 

the beams with nonlinear behavior intended to represent 

pre-Northridge connections which may fracture 

prematurely. Each beam connection was assigned a 

unique backbone curve based on the probability it 

would fracture at a given rotation based on experimental 

evidence (Molina-Hutt and others, 2016).

• 1D lumped plasticity elements for the columns.

• Two-dimensional (2D) elastic shell elements for the floors 

using stiffness modifiers.

• Nonlinear rotational springs for the steel-panel zones.

• Nonlinear rotational springs for the steel-column splices, 

with nonlinear behavior intended to represent the typical 

weld details that may fracture at demands lower than the 

column axial and moment strength.

For full details on the steel-frame building modeling, see 

Molina-Hutt and others (2016).

Reinforced-Concrete Residential Tower

A 42-story reinforced-concrete core-only residential building 

was selected as one of the archetype buildings for this study, 

because it has become a prevalent construction type in San 

Francisco. The building design is intended to represent the current 

state of practice for tall buildings in San Francisco.

Design

The archetype reinforced-concrete building design is 

originally based on the PEER Task 12 study (Moehle and 

others, 2011) for an archetypical building in Los Angeles 

and was redesigned for San Francisco seismic demands by 

Tipler (2014) following the PEER Tall Building Initiative 

guidelines (TBI Guidelines Working Group, 2010). The general 

performances objectives for the structure are no different than 

modern code objectives—to provide “collapse-prevention” 

in the MCE, “life-safety” in a DBE, and minimal damage in 

serviceability-level earthquakes (SLE). The design guidelines 

set out in PEER (TBI Guidelines Working Group, 2010) require 

that the structure be evaluated through a NLRHA to explicitly 

verify that the building has a low probability of collapse 

under the MCE. An isometric view of the building is shown in 

figure 9. As above for the steel-frame buildings, two building 

Figure 9. Diagram showing an isometric view of the 

archetype 42-story reinforced-concrete residentialbuilding analytical model.

orientations were analyzed for the reinforced-concrete building. 

These orientations are shown in figure 10. The core-only lateral 

system (fig. 11) is designed such that energy is dissipated 

through two flexural yield mechanisms—(1) plastic hinges 

at the base of each wall pier and (2) the ends of the coupling 

beams up the height of the building.

The reinforced-concrete residential building has 42 

above-ground levels and 4 below-ground levels for parking. 

The building is 457 ft (139.3 m) tall above grade, including the roof bulkhead. The superstructure floor plate is 

107.9×107.0ft (32.9×32.6 m) in plan. Floor-to-floor heights 

are typically 9.7 ft (3.0 m). The substructure is 228.0×227.0 ft 

(69.5×69.2 m) in plan. The gravity system is 8 in (203 mm) 

thick prestressed concrete slab and reinforced concrete columns. Columns sizes typically range from 36 in. (914 mm) 

square at the ground to 18 in. (457 mm) square at the roof. 

Core wall thickness is 32 in. (813 mm) thick up to superstructure level 13 and 24 in. (610 mm) thick from superstructure 

level 13 to the roof. Coupling beam depth is 30 in. (762 mm) 

everywhere except the basement, where the beams are 34 in. 

(864 mm) deep. Core-wall design (nominal) strength is 8 ksi 

(55 MPa). Shear-wall steel-reinforcement nominal yield 

strength is 60 ksi (410 MPa). Coupling-beam steel-reinforcement nominal yield strength is 75 ksi (520 MPa). 

More information on the design of the reinforced-concrete 

residential building can be found in Tipler (2014). Note that 
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 277

Figure 10. Diagrams showing (A) baseline and (B) rotated orientations of the archetype 42-story 

reinforced-concrete residential-building analytical model (from Moehle and others, 2011). N-S, northsouth; E-W, east-west; ’, feet; ”, inches.

Figure 11. Diagrams showing (A) core-wall layout with dimensions and (B) pier labeling (right) for the 

archetype 42-story reinforced-concrete residential-building analytical model (from Tipler, 2014). m, meters.

A B Baseline orientation Rotated orientation

A B

Tipler’s design was based on a San Francisco location, but we 

used it for Oakland (even though there are currently no 40-story 

towers in Oakland) to obtain a general understanding of how 

this type of building would perform.

Building Dynamic Properties

The dynamic properties of the archetype 42-story reinforcedconcrete residential building, using effective stiffness properties 

that account for flexural cracking, are shown in table 5. For further 

details see Tipler (2014).

Table 5. Dynamic properties of the archetype 42-story reinforcedconcrete residential-building analytical model (modified from 

Tipler, 2014).

Period (DBE), in seconds

Strong direction (y-axis) Weak direction (x-axis)

T1=4.37 T1=5.27

T2=0.93 T2=1.10

[DBE, design-basis earthquake (American Society of Civil Engineers, 2010), 

T1, first mode period in specified direction, T2, second mode period in 

specified direction]
278 The HayWired Earthquake Scenario—Engineering Implications

Modeling

Tipler (2014) modeled a reinforced-concrete building using 

LS-DYNA (Livermore Software Technology Corporation, 2009). 

We made some modifications to the LS-DYNA model to reflect 

updated knowledge of concrete-material modeling. A nonlinear 

response history analysis, using an explicit solver, which accounts 

for secondary moment effects and nonlinear materials, was 

undertaken with the ground motions discussed above in HayWired 

Ground Motions applied at the base of the model.

The reinforced-concrete residential buildings were modeled 

with the following element types:

• 1D distributed plasticity fiber beam elements for the 

shear walls, with fiber representing steel reinforcement, 

confined/unconfined concrete, and corresponding 

nonlinear material behavior. The use of fiber beam 

elements to represent core walls is industry practice. It 

enforces “plane sections remain plane” behavior which 

may underestimate the localized damage at the ends or 

corners of walls and may therefore underpredict losses.

• 1D lumped plasticity elements for the coupling beams, 

which have been validated against testing at the University 

of California Los Angeles (UCLA) (Naish and others, 

2009) to reproduce the hysteretic behavior.

• 2D elastic shell elements for the floors using stiffness 

modifiers.

• 2D elastic shell elements for the basement walls.

• 1D elastic beam elements for the columns.

The reinforced-concrete model was subjected to the ground 

motions in conjunction with expected gravity loads, which 

includes self-weight, superimposed dead loads, and 25 percent 

of the unreduced live loads. Fixed supports were assumed at 

the base of the structure and soil-structure interaction was not 

considered. For tall buildings with deep embedded basements in 

soft soils, the kinematic effects are likely to reduce the peak floor 

accelerations associated with higher modes. The embedment depth 

is important, and we note that newer reinforced-concrete buildings 

typically have three to five basement levels. It can be inferred 

that the damage to some acceleration-sensitive nonstructural 

components may be overestimated. A 2.5-percent critical damping 

was assumed based on work by PEER (TBI Guidelines Working 

Group, 2010). For full details on the reinforced-concrete building 

modeling, see Tipler (2014).

Loss-Assessment Methodology

The FEMA P-58 methodology (Applied Technology 

Council, 2012) was followed in to determine the risk metrics 

of interest for the buildings in this study. The fragility curves in 

the September 2016 update of FEMA P-58 volume 3 were used 

(Applied Technology Council, 2016). Using those results, the 

REDiTM downtime methodology (with some enhancements) was 

employed to calculate building downtime until reoccupancy and 

functional recovery is achieved (Almufti and Willford, 2013). 

Note that components which suffer only cosmetic damage do 

not contribute to the time required to achieve reoccupancy or 

functionality (only full recovery, which is not reported herein). 

These calculations are implemented using in-house software 

at Arup (Arup, North America, Ltd.), which runs Monte Carlo 

simulations (that is, realizations) for each building.

The loss-assessment methodology in FEMA P-58 relates 

expected building movements to expected damage in individual 

components to expected consequences (for example, repair 

costs and repair times). The structural response from the ground 

motions for the HayWired mainshock was assumed to be ‘best 

estimate’ structural response. A modeling dispersion was applied 

to obtain variability in response, accounting for uncertainty in 

analysis model quality and construction quality. The modeling 

dispersion assumed was 0.35 for steel-frame buildings and 0.27 

reinforced-concrete buildings based on guidance in FEMA P-58 

(Applied Technology Council, 2012). A lognormal distribution 

was assumed for this purpose, where each floor, parameter type, 

and direction was assumed independent of one another. Using the 

“best estimate” structural response and modeling dispersion, each 

individual building underwent 1,000 Monte Carlo loss simulations 

to capture the uncertainty in building damage and consequences. 

This results in a distribution of repair-cost and repair-time 

estimates with corresponding probabilities of nonexceedance 

(often referred to as “confidence levels”) for the HayWired 

scenario mainshock and archetype buildings. As a result of this 

being a scenario study, the risk results have a much narrower 

range as compared with intensity-based studies. In those cases, 

the motion to motion variability adds a significant amount to the 

overall dispersion on structural response. 

REDi Downtime Methodology

The REDiTM downtime methodology builds on the FEMA 

P-58 methodology to calculate the time required to achieve 

discrete downtime recovery states such as reoccupancy, 

functionality, and full recovery (Almufti and Willford, 2013). 

This is dependent on the extent and severity of damage 

to individual building components and their criticality in 

supporting occupancy or functionality. The REDi methodology 

maps each of the damaged components into repair classes, 

which indicate whether the extent and severity of damage to 

that component would hinder reoccupancy (repair class 3), 

functionality (repair class 2), and full recovery (repair class 1). 

Figure 12 provides an overview of the methodology, whereas 

figure 13 illustrates the aspects of the REDi downtime method 

for functional recovery.

Probability of Observing Damage

The FEMA P-58 methodology allows the estimation of the 

extent and severity of damage to specific building components. 
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 279

Figure 12. Diagram showing overview of methodologies used for the loss assessment for tall buildings for 

the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario. Methodologies—

FEMA P-58 (Applied Technology Council, 2012); REDi (see Almufti and Willford, 2013). SA, spectral 

acceleration; T1, fundamental mode of vibration; g, acceleration due to gravity; PFA, peak floor acceleration; 

IDR, interstory drift ratio; P, probability; DS, damage state; EDP, engineering design parameter.

Figure 13. Illustration showing REDiTM (Almufti and Willford, 2013) downtime framework for assessing the functional 

recovery of tall buildings after the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Seismic hazard analysis

SA(T1) = 0.5 g

Structural analysis Damage assessment Consequence analysis

Repair cost

Repair time Downtime

Functional

recovery

Utilities

Impeding 

factors

Class 2 and 3 

building 

component repairs

Earthquake 

occurence

However, the impact of the damage on whether downtime is 

triggered depends to a great extent on whether the damage is 

observed or hidden (particularly true of structural components). 

The REDi methodology explicitly accounts for the probability 

that an inspector would observe a certain type of damage (and 

thus influence their decision how to tag a building) by assigning 

a 50-percent chance that an inspector would observe the damage 

when 10 percent of all components of that type are in the highest 

realized damage state.

In this study, this assumption is particularly important 

for the pre-Northridge moment-frame connections in existing 

steel-frame buildings. Jurisdictions such as San Francisco do 

not have specific policies for post-earthquake inspection of the 

moment-frame connections and are unlikely to require such 

an inspection unless the building exhibited a lean (Laurence 

Kornfield, Earthquake Engineering Research Institute, written 

commun., 2017). However, many owners of older buildings 

retain structural engineers through the Building Occupancy 

Resumption Program (BORP) (Structural Engineers Association 

of Northern California, 2003). It likely that structural engineers, 

having become acutely aware of the deficiencies in such steel 

moment-frame connections, would recommend inspection of 

some connections (but not all). Section 3.3.3 of FEMA 352 

(SAC Joint Venture, 2000) recommends that one connection in 

each framing line in each direction (east-west and north-south) 

is exposed for inspection under certain circumstances that would 

appear to be satisfied by the HayWired mainshock. For the 

archetype steel-frame building, with 6 bays (12 connections) in 

one direction and 4 in the other (8 connections), this is between 

8.3 percent and 12.5 percent of all connections, respectively. 

This is relatively consistent with the 10-percent inspectionexposure assumption by REDi. In addition, the connections 

may be fire-proofed, which according to FEMA 352, may 

“tend to obscure many types of damage, unless the damage is 

very severe.” FEMA 352 also indicates that even for bare steel 

connections, certain types of damage “may be impossible to 

detect by visual observation alone.” This supports the REDi 

assumption that the likelihood of observing a fracture, having 

exposed the connection, is not 100 percent guaranteed. Because 

the number of beam fractures from the steel-frame building 

analysis in this study (see appendixes) is less than a few percent 

of all beam components in the building, it is unlikely that an 

inspector would observe one, and thus beam fractures do not 

contribute to downtime in the majority of realizations.
280 The HayWired Earthquake Scenario—Engineering Implications

Impeding Factors

The time to make corresponding repairs to earthquakedamaged buildings is calculated based on FEMA P-58 but 

modified by REDi to consider likely construction repair 

sequences and labor allocation. Based on the type and 

extent of repairs, the total time to achieve reoccupancy or 

functionality must also consider impeding factors (that is, 

delays to the initiation of repairs). The following impeding 

factors are considered, the default values of which are 

generally taken from REDi but have been modified as 

indicated below:

• Postearthquake inspection.

• Financing (assumes that the buildings are insured, 

based on the authors’ knowledge of earthquakeinsurance coverage for tall buildings in San Francisco).

• Engineering mobilization and review.

• Contractor mobilization (modified based on extent, 

type, and severity of damage and height of building; 

estimates based on survey of contractors administered 

by Arup).

• Permitting.

Utility disruption is also considered in the downtime, as 

described above under Utility Disruption.

Input Parameters

The basic building information used in the assessment 

methodology for the archetype tall-buildings included 

number of stories and square footage per floor. Sources for 

the assumed component types and corresponding quantities 

are provided in the appendixes. Building contents—such as 

modular workstations, bookcases, art pieces, and casework—

were not included in the loss assessment. For the steel-frame 

buildings, heavy mechanical equipment (that is, cooling 

tower and chiller) capacities were modified based on input 

from mechanical engineering experts at Arup. The structural 

analysis results for given ground motions for the HayWired 

mainshock at a site were interpreted to be “best estimate” 

results about which a modelling dispersion was assumed 

to account for uncertainty in analytical model quality and 

assumed construction quality.

Demolition Fragility

The probability that a building might need to be 

demolished as a result of the HayWired mainshock was 

considered in our analysis. If a building has a peak residual 

interstory drift (RIDR) of 0.5 percent or less, there is a 

negligible chance the structure would need to be demolished. 

If a building has a peak RIDR of 1 percent, there is a 50-50 

chance that it would need to be demolished.

Component Fragilities

A full list of the archetype building-component quantities and 

fragility criteria can be found in appendix 1. Appendix 1 provides 

information on both structural components and information on 

nonstructural components. In addition to the default fragilities 

provided by FEMA P-58, we modified fragilities for elevators 

and precast facades. Two elevator components were modeled to 

capture two possible types of damage:

1. Acceleration-sensitive component which is correlated to the 

elevator cabin damage.—This is modelled at the ground 

floor of the building because the FEMA P-58 fragility is 

a function of peak ground acceleration (PGA). It is our 

opinion that these are likely conservative for taller buildings, 

as the default FEMA P-58 fragilities were developed from 

shorter buildings in which the floor accelerations increased 

up the height (with roof accelerations likely to be 2–3 times 

PGA). The fragility does not account for the location of the 

elevator in the building, but presumably, the elevators that 

were damaged in observation were those at the upper stories. 

In a tall building, where the fundamental mode of vibration 

and higher mode effects contribute to the acceleration 

response, it is not necessarily the case that the PGA is 

amplified significantly.

2. RIDR sensitive component which is correlated to the shaft 

rail damage.—This is modeled at the superstructure level 

where the peak RIDR occurs, which varies from building to 

building.

The fragility function for the precast facades used in the 

steel-frame buildings were developed based on the methodology 

in section 7.4 of FEMA P-58 (Applied Technology Council, 

2012). The median interstory drift to cause damage was backcalculated by the gaps between façade panels and floor heights 

(determined through examination of drawings). The dispersion of 

0.5 was adopted per section 7.4. Damage to façades is assumed to 

cause reoccupancy issues due to the risk of loose façade materials 

potentially falling and injuring passersby.

Replacement Value

The replacement value of steel-frame buildings is based 

on a class-5 rough cost estimate of the Association for the 

Advancement of Cost Engineering (AACE) and has an accuracy 

range of −5 to +30 percent as discussed in Molina-Hutt and others 

(2016). It includes all structure; exterior enclosure; mechanical, 

electrical, and plumbing (MEP) infrastructure; and partitions. It 

does not include demolition and site clearance.

The replacement value of reinforced-concrete buildings 

is based on those of Tipler (2014), which used cost estimates 

from Moehle and others (2011) for most components, including 

structural elements. The cost of interior partitions and doors 

were provided by an experienced Arup estimator. Cost estimates 

for elevators and façade were obtained from vendors. The 

replacement value also includes MEP infrastructure and partitions. 

It does not include demolition and site clearance.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 281

Utility Disruption

Utility disruption times are considered when determining 

the time required to achieve building functionality. These 

are from other parts of the HayWired project (for example, 

Porter, Water-Network Resilience, this volume), except for 

natural gas. For natural gas, the values for utility disruption 

are based off of a study of several moderate to large magnitude 

earthquakes which have affected regions with modern 

infrastructure, including California, Japan, Chile, and New 

Zealand, as well as studies estimating utility disruption times 

with consideration of future earthquakes in the Western United 

States (Almufti and Willford, 2013). The utilities of interest 

include:

• Water

• Natural gas

• Electricity

• Voice/data

Table 6. Estimated building-restoration delays due to utility disruption 

at the San Francisco, California, site following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

Utility 50-percent restoration Tail restoration

Water1 3 days 100 percent at 7 days

Natural gas2 ~9 days 90 percent at ~33 days

Electricity3 1 day 99.5 percent at 30 days

Voice/data4 5 days 100 percent at 7 days

1

Porter (Water-Network Resilience, this volume). 

2

Per REDi (Almufti and Willford, 2013) for peak ground velocities 

associated with the HayWired mainshock.

3

Preliminary Hazus-MH (Federal Emergency Management Agency, 2012) 

estimate run for the HayWired scenario (Doug Bausch, written commun., 

Federal Emergency Management Agency, 2014).

4

Preliminary estimate provided by John Erichsen (oral commun., 2016 

HayWired Telecommunications Workshop).

Table 7. Estimated building-restoration delays due to utility disruption 

at the Oakland, California, site following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

Utility 50-percent restoration Tail restoration

Water1 30 days 100 percent at 90 days

Natural gas2 ~10 days 90 percent at ~36 days

Electricity3 2 days 96 percent at 30 days

Voice/data4 7 days 100 percent at 30 days

1

Porter (Water-Network Resilience, this volume). 

2

Per REDi (Almufti and Willford, 2013) for peak ground velocities 

associated with the HayWired mainshock.

3

Preliminary Hazus-MH (Federal Emergency Management Agency, 2012) 

estimate run for the HayWired scenario (Doug Bausch, written commun., 

Federal Emergency Management Agency, 2014).

4

Preliminary estimate provided by John Erichsen (oral commun., 2016 

HayWired Telecommunications Workshop).

Figure 14. Graph showing median and 

90th-percentile building-repair costs 

following the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario for all 

case study buildings (see table 1) as a 

percentage of replacement value. 

400

350

300

250

200

150

100

50

0

S-SF-B-43

S-SF-R-43

S-SF-B-20

S-SF-R-20

S-OK-B-20

S-OK-R-20

C-SF-B-46

C-SF-R-46

C-OK-B-46

C-OK-R-46

Downtime, in days

EXPLANATION

Case-study building abbreviation

Median functional

Median reoccupancy

90th percentile functional

90th percentile reoccupancy

The estimated building-restoration delays for due to disruptions 

of each of those utilities is shown in tables 6 and 7 for San 

Francisco and Oakland, respectively.

Summary of Loss-Assessment Results

The results of the loss assessment (repair cost and downtime 

estimates) for all 10 case-study buildings are discussed below. 

Both the median (50-percent confidence level) and probable 

maximum (90-percent confidence level) are presented. 

Because the HayWired mainshock is a scenario event, the 

difference between the median and 90th-percentile losses is small 

in comparison to the results from an intensity-based assessment 

involving many ground motions, where the motion to motion 

variability adds significantly to the overall dispersion.

Figure 14 and table 8 show the results of the repair-cost 

assessment for the 10 buildings. Figure 15 and table 9 show the 

results of the downtime assessment for the 10 buildings. See the 

appendixes for detailed repair-cost and downtime results for each 

individual building.
282 The HayWired Earthquake Scenario—Engineering Implications

Table 8. Summary of total building-repair costs following the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario for each case-study 

building (see table 1).

Case-study building 

abbreviation

Median total 

repair cost, in 

dollars

Percentage of 

replacement 

value

90th-percentile 

total repair cost, in 

dollars

Percentage of 

replacement 

value

S-SF-B-43 15,057,000 10.8 17,132,000 12.3

S-SF-R-43 13,512,000 9.7 15,690,958 11.3

S-SF-B-20 5,138,200 7.4 6,592,184 9.5

S-SF-R-20 5,687,900 8.2 7,261,380 10.4

S-OK-B-20 12,172,000 17.5 14,395,814 20.7

S-OK-R-20 11,510,000 16.5 13,065,046 18.7

C-SF-B-46 5,517,497 3.1 6,470,705 3.7

C-SF-R-46 9,023,409 5.1 9,839,828 5.6

C-OK-B-46 8,604,872 4.9 9,393,212 5.3

C-OK-R-46 8,864,100 5.0 10,829,600 6.2

Figure 15. Graph showing building 

downtime results in days following the 

hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake 

scenario for all case-study buildings (see 

table 1).

400

350

300

250

200

150

100

50

0

S-SF-B-43

S-SF-R-43

S-SF-B-20

S-SF-R-20

S-OK-B-20

S-OK-R-20

C-SF-B-46

C-SF-R-46

C-OK-B-46

C-OK-R-46

Downtime, in days

EXPLANATION

Case-study building abbreviation

Median functional

Median reoccupancy

90th percentile functional

90th percentile reoccupancy

Table 9. Summary of building reoccupancy and functional-repair-time results following 

the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario 

for each case-study building (see table 1).

Case-study building 

abbreviation

Median repair time 90th-percentile repair time

Reoccupancy, 

in days

Functional, in 

days

Reoccupancy, in 

days

Functional, in 

days

S-SF-B-43 41 45 61 126

S-SF-R-43 37 39 54 102

S-SF-B-20 20 29 39 145

S-SF-R-20 22 33 47 189

S-OK-B-20 54 92 116 272

S-OK-R-20 54 82 97 237

C-SF-B-46 3 15 5 27

C-SF-R-46 6 16 11 26

C-OK-B-46 5 16 9 26

C-OK-R-46 6 16 11 26
Conclusion

This study used state of the art structural analysis and risk 

assessment to examine tall-building performance in the Mw 7.0 

mainshock of the HayWired earthquake scenario. It is important to 

recognize that existing (and new) tall buildings have largely been 

untested by real earthquakes of this magnitude; thus the analytical 

methods have not been confirmed. The building-downtime 

estimates in particular rely on multiple assumptions that have not 

yet been robustly validated, including:

• The fragility functions and underlying methodology in 

FEMA P-58 (Applied Technology Council, 2012) are 

suitable for the purposes of predicting repair time.

• The severity and extent of damage to specified building 

components are the basis for the type of downtime 

incurred (that is, reoccupancy, functionality, or full 

recovery).

• The length of time before repairs can be initiated (that 

is, impeding factors)

• The time it takes to make repairs (dependent on the 

availability of laborers and the specific repair sequence 

schedule).

In many respects, the loss results seem reasonable. The 

financial losses for the new reinforced-concrete buildings 

are significantly lower than for the existing steel-frame 

buildings; the reoccupancy time for the new reinforcedconcrete buildings are roughly half those of the steel-frame 

buildings; and the losses for buildings located in Oakland 

are higher than those in San Francisco, primarily due to the 

much larger ground accelerations for HayWired mainshock in 

Oakland. However, the time to achieve functional recovery is 

relatively similar between the new and old buildings, which 

on the face of it seems suspicious. In studying the results in 

Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 283

Table 10. Summary of building reoccupancy and functional downtime results following the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario for each 

case-study building (see table 1).

Case-study building 

abbreviation

Median repair time 90th-percentile repair time

Reoccupancy, in 

days

Functional, in 

days

Reoccupancy, in 

days

Functional, in 

days

S-SF-B-43 248 288 375 388

S-SF-R-43 250 288 364 390

S-SF-B-20 189 242 316 364

S-SF-R-20 186 251 304 361

S-OK-B-20 231 273 344 385

S-OK-R-20 224 269 333 371

C-SF-B-46 126 224 194 328

C-SF-R-46 121 239 213 545

C-OK-B-46 130 233 198 346

C-OK-R-46 139 245 223 359

more detail, this seems plausible as new reinforced-concrete 

buildings experience higher peak floor accelerations than the 

steel-frame buildings, causing more nonstructural damage 

to acceleration-sensitive components that support building 

functions. Contractor mobilization times, which are dependent 

on the height of the building and the type and severity of 

component damage (primarily nonstructural for both building 

types), are similarly large and govern the total downtime for 

each building type.

Of course, in the event that the few beam fractures in the 

steel-frame buildings are observed by an inspector, the estimated 

downtimes between new and old buildings would significantly 

widen. This would suggest that just a slightly larger earthquake 

scenario than that modeled in the HayWired scenario (perhaps at 

the design level or greater) would pose a greater risk to existing 

tall steel-frame buildings than new reinforced-concrete tall 

buildings. In other words, existing and new tall buildings may 

perform relatively similarly up to a certain seismic demand (that 

is, before widespread fractures in steel-frame buildings), but the 

performance would diverge considerably after that point, with 

the steel-frame buildings more prone to irreparable damage and 

collapse. This is supported by the high collapse-risk rates of 

existing tall steel-frame buildings (Molina-Hutt and others, 2016) 

relative to the code objectives for new tall buildings.

Acknowledgments

The report was enhanced in response to comprehensive 

review by Terry Paret (Wiss, Janey, and Eistner Associates, 

Inc.; WJE), Andrew Shuck (WJE), Tony Yang (University of 

British Columbia), and Erol Kalkan (USGS). The study was 

funded by USGS Land Change Science Program (reference 

number G16PS00702; USGS HayWired Scenario—Tall 

Building Performance).
284 The HayWired Earthquake Scenario—Engineering Implications

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Sacramento, Calif., Structural Engineers Association of 

California.

Structural Engineers Association of Northern California, 

2003, Building occupancy resumption program 

(BORP): Structural Engineers Association of Northern 

California, accessed February 28, 2018, at http://sfdbi.

org/borp-guidelines-engineers.

TBI Guidelines Working Group, 2010, Tall Buildings Initiative—

Guidelines for performance-based seismic design of tall buildings

(ver. 1.0): Berkeley, Calif., Pacific Earthquake Engineering Research

Center, University of California, no. 2010/05, 104 p., accessed 

January 31, 2018, at http://peer.berkeley.edu/publications/peer_

reports/reports_2010/web_PEER2010_05_GUIDELINES.pdf.

Tipler, J.F., 2014, Seismic resilience of tall buildings—benchmarking 

performance and quantifying improvements: Stanford University 

master’s thesis, 91 p., accessed January 30, 2018, at https://

stacks.stanford.edu/file/druid:xh842sm8488/Thesis%20Final%20

Jennisie%20Tipler-augmented.pdf.

Yang, T.Y., Moehle, J., Stojadinovic, B., and Der Kiureghian, A., 

2009, Performance evaluation of structural systems—Theory and 

implementation: Journal of Structural Engineering, v. 135, no. 10, 

p. 1146–1154.

Appendix 1. Building Structural and Nonstructural Components

The tables below list the following information for the three 

building archetypes in the baseline orientation (40-story steelframe building, 20-story steel-frame building, and reinforcedconcrete building):

• Component quantities.

• Component National Institute of Standards and

Technology Interagency Reports (NISTIR) fragility

classification number (shown as “NISTIR” in tables).

• Component units, as specified by the NISTIR fragility.

• The source of the component quantity; sources are:

• The building design (for example, counting explicitly

the number of base plates in the building design).

• National Institute of Standards and Technology

(NIST) Normative Quantity estimation tool

packaged with FEMA’s Performance Assessment

Calculation Tool (PACT; see Applied Technology 

Council, 2012) (marked as simply “Norm Qty” in 

the tables).

• Moehle and others (2011), which documents the

original structural design of reinforced concrete building

before the San Francisco redesign by Tipler (2014).

• Arup estimator.

• Component medians and dispersions for each damage

state.

Tables 11–13 show structural components for each 

archetype building (40-story steel-frame building, 20-story 

steel-frame building, and reinforced-concrete building, 

respectively). Tables 14–16 show nonstructural components 

for each building type. Components for buildings with rotated 

orientation are generally the same as listed below, but with the 

east-west and north-south quantities flipped.
286 The HayWired Earthquake Scenario—Engineering Implications Structural Components Table 11. Forty-story steel-frame building structural components. [NISTIR, National Institute of Standards and Technology Interagency Reports. E-W qty, east-west quantity per floor; N-S qty, north-south quantity per floor—note that components with only one quantity listed are nondirectional. DS, damage state. Other abbreviations: 

A, area; HVAC, heating, ventilation, and air conditioning; IGU, insulating glass unit; FT IGU, fully tempered insulating glass unit; Ip, component 

importance factor; NA, not applicable; Norm Qty, National Institute of Standards and Technology Normative Quantity estimation tool packaged with Federal Emergency Management Agency’s Performance Assessment Calculation Tool; OSHPD, California Office of Statewide Planning and Development; RC, REDiTM repair class (Almufti and Willford, 2013); SDC, ASCE 7–10 seismic design criteria (American Society of Civil Engineers, 2010); SSG, structural silicone glazing; VAV, variable air volume; 

Vg, velocity of gravity; VHBTM SGT, 3MTM VHBTM structural glazing tape; 

Vo, velocity of object; W, wide-flange 

beam; WUF-B, welded unreinforced flange-bolted web. Unit abbreviations: A, ampere; ft2, square foot; ft3/min, cubic foot per minute; g, acceleration due to gravity; in., inch; kVA, kilo-volt-ampere; lin ft, linear foot; mm, millimeter; plf, per linear foot]

Floor Component NISTIR E-W qty N-S qty Units Source

DS1 median

(dispersion)

[repair class]

DS2 median

(dispersion)

[repair class]

DS3 median

(dispersion)

[repair class]

B3 Steel column base plates, column 

W>300 plf

B1031.011c 13 13 Each Building design 0.04 (0.4) rad [RC3] 0.07 (0.4) rad [RC3] 0.1 (0.4) rad [RC3]

B2 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad [RC3] 0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam one side of column, beam depth≥W30

B1035.042 8 10 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≥W30

B1035.052 24 32 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

B1 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad [RC3] 0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Welded column splices, column W>300 

plf

B1031.021c 13 13 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA

Pre-Northridge WUF-B beam-column 

joint, beam one side of column, beam depth≥W30

B1035.042 8 10 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≥W30

B1035.052 24 32 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

L1–L9 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad [RC3] 0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Welded column splices, column W>300 

plf **

B1031.021c 13 13 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA

Pre-Northridge WUF-B beam-column 

joint, beam one side of column, beam depth≥W30

B1035.042 8 10 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≥W30

B1035.052 24 32 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

L10–L17 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad [RC3] 0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam one side of column, beam depth≤W27

B1035.041 0 6 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 287 Table 11.—Continued Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Pre-Northridge WUF-B beam-column joint, beam one side of column, beam depth≥W30 B1035.042 8 4 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Pre-Northridge WUF-B beam-column joint, beam both sides of column, beam depth≤W27 B1035.051 0 12 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Pre-Northridge WUF-B beam-column joint, beam both sides of column, beam depth≥W30 B1035.052 24 20 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Welded column splices1, column W>300 plf B1031.021c 13 13 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA L18–L29 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad [RC3] 0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3] Welded column splices1, column 150 plf<W<300 plf B1031.021b 8 8 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA Welded column splices1, column W>300 plf B1031.021c 5 5 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA Pre-Northridge WUF-B beam-column joint, beam one side of column, beam depth≤W27 B1035.041 0 6 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Pre-Northridge WUF-B beam-column joint, beam one side of column, beam depth≥W30 B1035.042 8 4 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Pre-Northridge WUF-B beam-column joint, beam both sides of column, beam depth≤W27 B1035.051 0 12 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Pre-Northridge WUF-B beam-column joint, beam both sides of column, beam depth≥W30 B1035.052 24 20 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] L30–Roof Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad [RC3] 0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3] Welded column splices1, column 150 plf<W<300 plf B1031.021b 8 8 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA Welded column splices1, column W>300 plf B1031.021c 5 5 Each Building design 0.02 (0.4) rad [RC3] 0.05 (0.4) rad [RC3] NA Pre-Northridge WUF-B beam-column joint, beam one side of column, beam depth≤W27 B1035.041 8 10 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3] Pre-Northridge WUF-B beam-column joint, beam both sides of column, beam depth≤W27 B1035.051 24 32 Each Building design 0.017 (0.4) rad [RC3] 0.025 (0.4) rad [RC3] 0.03 (0.4) rad [RC3]

1Column splices only located on the following floors: L3, L6, L9, L12, L15, L18, L21, L24, L27, L30, L33, and L36.
288 The HayWired Earthquake Scenario—Engineering Implications Table 12. Twenty-story steel-frame building structural components. [NISTIR, National Institute of Standards and Technology Interagency Reports. E-W qty, east-west quantity per floor; N-S qty, north-south quantity per floor—note that components with only one quantity listed are nondirec- tional. DS, damage state. Other abbreviations: 

A, area; HVAC, heating, ventilation, and air conditioning; IGU, insulating glass unit; FT IGU, fully tempered insulating glass unit; Ip, component importance factor; NA, not applicable; Norm Qty, National Institute of Standards and Technology Normative Quantity estimation tool packaged with Federal Emergency Management Agency’s Performance Assessment Calculation Tool; OSHPD, California 

Office of Statewide Planning and Development; RC, REDiTM repair class (Almufti and Willford, 2013)—1=reoccupancy, 2=functional recovery, and 3=full recovery; SDC, ASCE 7–10 seismic design criteria (American Society of Civil Engineers, 2010); SSG, structural silicone glazing; VAV, variable air volume; 

Vg, velocity of gravity; VHBTM SGT, 3MTM VHBTM structural glazing tape; 

Vo, velocity of object; W, wide-flange beam; WUF-B, welded 

unreinforced flange-bolted web. Unit abbreviations: A, ampere; ft2, square foot; ft3/min, cubic foot per minute; g, acceleration due to gravity; in., inch; kVA, kilo-volt-ampere; lin ft, linear foot; mm, millimeter; plf, per linear foot]

1Column splices only located on the following floors: L3, L6, L9, L12, L15, L18, and L21.

Floor Component NISTIR E-W qty N-S qty Units Source

DS1 median

(dispersion)

[repair class]

DS2 median

(dispersion)

[repair class]

DS3 median

(dispersion)

[repair class]

B1 Steel column base plates, column W>300 plf B1031.011c 13 13 Each Building design 0.04 (0.4) rad 

[RC3]

0.07 (0.4) rad [RC3] 0.1 (0.4) rad [RC3]

L1 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad 

[RC3]

0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column joint, 

beam one side of column, beam depth≥W30

B1035.042 8 10 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≥W30

B1035.052 24 32 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

L2–L10 Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad 

[RC3]

0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Welded column splices1, column W>300 plf B1031.021c 13 13 Each Building design 0.02 (0.4) rad 

[RC3]

0.05 (0.4) rad [RC3] NA

Pre-Northridge WUF-B beam-column joint, 

beam one side of column, beam depth≥W30

B1035.042 8 10 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≥W30

B1035.052 24 32 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

L11–Roof Bolted shear tab gravity connections B1031.001 72 0 Each Building design 0.04 (0.4) rad 

[RC3]

0.08 (0.4) rad [RC3] 0.11 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column joint, 

beam one side of column, beam depth≤W27

B1035.041 8 4 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column joint, 

beam one side of column, beam depth≥W30

B1035.042 0 6 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≤W27

B1035.051 24 20 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

Pre-Northridge WUF-B beam-column 

joint, beam both sides of column, beam depth≥W30

B1035.052 0 12 Each Building design 0.017 (0.4) rad 

[RC3]

0.025 (0.4) rad 

[RC3]

0.03 (0.4) rad [RC3]

Welded column splices1, column 150 

plf<W<300 plf

B1031.021b 5 5 Each Building design 0.02 (0.4) rad 

[RC3]

0.05 (0.4) rad [RC3] NA

Welded column splices1, column W>300 plf B1031.021c 8 8 Each Building design 0.02 (0.4) rad 

[RC3]

0.05 (0.4) rad [RC3] NA
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 289 Table 13. Reinforced-concrete building structural components. [NISTIR, National Institute of Standards and Technology Interagency Reports. E-W qty, east-west quantity per floor; N-S qty, north-south quantity per floor—note that components with only one quantity listed are nondirectional. DS, damage state. Other abbreviations: 

A, area; HVAC, heating, ventilation, and air conditioning; IGU, insulating glass unit; FT IGU, fully tempered insulating glass unit; Ip, component importance factor; 

NA, not applicable; Norm Qty, National Institute of Standards and Technology Normative Quantity estimation tool packaged with Federal Emergency Management Agency’s Performance Assessment Calculation Tool; OSHPD, California Office of Statewide Planning and Development; RC, REDiTM repair class (Almufti and Willford, 2013)—1=reoccupancy, 2=functional recovery, and 3=full recovery; SDC, ASCE 7–10 seismic design criteria (American Society of Civil Engineers, 2010); SSG, structural silicone glazing; VAV, variable air volume; 

Vg, velocity of gravity; VHBTM SGT, 3MTM VHBTM structural glazing tape; 

Vo, velocity of object; W, wideflange beam; WUF-B, welded unreinforced flange-bolted web. Unit abbreviations: A, ampere; ft2, square foot; ft3/min, cubic foot per minute; g, acceleration due to gravity; in., inch; kVA, kilo-volt-ampere; lin ft, linear foot; 

mm, millimeter; plf, per linear foot]

Floor Component NISTIR E-W qty N-S qty Units Source

DS1 median

(dispersion)

[repair class]

DS2 median

(dispersion)

[repair class]

DS3 median

(dispersion)

[repair class]

B4 Slender concrete wall, 30 in. thick, 12 ft 

high, 15 ft long

B1044.111 0.55 5.42 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Slender concrete wall, 30 in. thick, 12 ft 

high, 30 ft long

B1044.113 3.61 0 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

B3–B2 Slender concrete wall, 30 in. thick, 12 ft 

high, 15 ft long

B1044.111 0.55 5.42 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Slender concrete wall, 30 in. thick, 12 ft 

high, 30 ft long

B1044.113 3.61 0 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Post-tensioned concrete flat slabscolumns with shear reinforcing 

0<

Vg

/V<0.4 o

B1049.031 52 Each Building design 0.028 (0.5) rad 

[RC3]

0.04 (0.5) rad [RC3] NA

Concrete link beam, diagonally 

reinforced, aspect ratio between 1.0 and 2.0, beam>24 in. wide and depth<30 in.

B1042.021a 2 4 Each Building design 0.0179 (0.38) g 

[RC1]

0.0352 (0.44) g 

[RC3]

0.0543 (0.95) g 

[RC3]

B1 Slender concrete wall, 30 in. thick, 12 ft 

high, 15 ft long

B1044.111 0.55 5.42 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Slender concrete wall, 30 in. thick, 12 ft 

high, 30 ft long

B1044.113 3.61 0 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Post-tensioned concrete flat slabscolumns with shear reinforcing 

0<

Vg

/V<0.4 o

B1049.031 52 Each Building design 0.028 (0.5) rad 

[RC3]

0.04 (0.5) rad [RC3] NA

Concrete link beam, diagonally 

reinforced, aspect ratio between 1.0 and 2.0, beam>24 in. wide and depth<30 in.

B1042.021a 2 4 Each Building design 0.0179 (0.38) g 

[RC1]

0.0352 (0.44) g 

[RC3]

0.0543 (0.95) g 

[RC3]

L1 Slender concrete wall, 30 in. thick, 12 ft 

high, 15 ft long

B1044.111 0.69 6.77 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Slender concrete wall, 30 in. thick, 12 ft 

high, 30 ft long

B1044.113 4.51 0 144 ft2 Building design 0.0093 (0.5) rad 

[RC3]

0.0128 (0.35) rad 

[RC3]

0.0186 (0.45) rad 

[RC3]

Post-tensioned concrete flat slabscolumns with shear reinforcing 

0<

Vg

/V<0.4 o

B1049.031 52 Each Building design 0.028 (0.5) rad 

[RC3]

0.04 (0.5) rad [RC3] NA
290 The HayWired Earthquake Scenario—Engineering Implications Table 13.—Continued Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Concrete link beam, diagonally reinforced, aspect ratio between 1.0 and 2.0, beam>24 in. wide and depth<30 in. B1042.021a 2 4 Each Building design 0.0179 (0.38) g [RC1] 0.0352 (0.44) g [RC3] 0.0543 (0.95) g [RC3] L2–L12 Slender concrete wall, 30 in. thick, 12 ft high, 15 ft long B1044.111 0.53 5.23 144 ft2 Building design 0.0093 (0.5) rad [RC3] 0.0128 (0.35) rad [RC3] 0.0186 (0.45) rad [RC3] Slender concrete wall, 30 in. thick, 12 ft high, 30 ft long B1044.113 3.49 0 144 ft2 Building design 0.0093 (0.5) rad [RC3] 0.0128 (0.35) rad [RC3] 0.0186 (0.45) rad [RC3] Post-tensioned concrete flat slabs- columns with shear reinforcing 0<

Vg

/V<0.4 o

B1049.031 28 Each Building design 0.028 (0.5) rad 

[RC3]

0.04 (0.5) rad [RC3] NA

Concrete link beam, diagonally 

reinforced, aspect ratio between 1.0 and 2.0, beam>24 in. wide and depth<30 in.

B1042.021a 2 4 Each Building design 0.0179 (0.38) g 

[RC1]

0.0352 (0.44) g 

[RC3]

0.0543 (0.95) g 

[RC3]

L13–L42 Rectangular low aspect ratio concrete 

walls 18–24 in. thick with double curtain and heights up to 15 ft 

B1044.021 4.02 5.23 144 ft2 Building design 0.0055 (0.36) rad 

[RC1]

0.0109 (0.3) rad 

[RC3]

0.013 (0.36) rad 

[RC3]

Post-tensioned concrete flat slabscolumns with shear reinforcing 

0<

Vg

/V<0.4 o

B1049.031 28 Each Building design 0.028 (0.5) rad 

[RC3]

0.04 (0.5) rad [RC3] NA

Concrete link beam, diagonally 

reinforced, aspect ratio between 1.0 and 2.0, beam>24 in. wide and depth<30 in.

B1042.021a 2 4 Each Building design 0.0179 (0.38) g 

[RC1]

0.0352 (0.44) g 

[RC3]

0.0543 (0.95) g 

[RC3]

Roof Post-tensioned concrete flat slabscolumns with shear reinforcing 

0<

Vg

/V<0.4 o

B1049.031 28 Each Building design 0.028 (0.5) rad 

[RC3]

0.04 (0.5) rad [RC3] NA

Concrete link beam, diagonally 

reinforced, aspect ratio between 1.0 and 2.0, beam>24 in. wide and depth<30 in.

B1042.021a 2 4 Each Building design 0.0179 (0.38) g 

[RC1]

0.0352 (0.44) g 

[RC3]

0.0543 (0.95) g 

[RC3]
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 291 Table 14. Forty-story steel-frame building nonstructural components. [NISTIR, National Institute of Standards and Technology Interagency Reports. E-W qty, east-west quantity per floor; N-S qty, north-south quantity per floor—note that components with only one quantity listed are nondi- rectional. DS, damage state. Other abbreviations: 

A, area; HVAC, heating, ventilation, and air conditioning; IGU, insulating glass unit; FT IGU, fully tempered insulating glass unit; Ip, component importance factor; NA, not 

applicable; Norm Qty, National Institute of Standards and Technology Normative Quantity estimation tool packaged with Federal Emergency Management Agency’s Performance Assessment Calculation Tool; OSHPD, California Office of Statewide Planning and Development; RC, REDiTM repair class (Almufti and Willford, 2013)—1=reoccupancy, 2=functional recovery, and 3=full recovery; SDC, ASCE 7–10 seismic design criteria (American Society of Civil Engineers, 2010); SSG, structural silicone glazing; VAV, variable air volume; 

Vg, velocity of gravity; VHBTM SGT, 3MTM VHBTM structural glazing tape; 

Vo, velocity of object; W, wide-flange 

beam; WUF-B, welded unreinforced flange-bolted web. Unit abbreviations: A, ampere; ft2, square foot; ft3/min, cubic foot per minute; g, acceleration due to gravity; in., inch; kVA, kilo-volt-ampere; lin ft, linear foot; mm, millimeter; plf, per linear foot]

Nonstructural Components

Floor Component NISTIR E-W qty N-S qty Units Source

DS1 median

(dispersion)

[repair class

DS2 median

(dispersion)

[repair class]

DS3 median

(dispersion)

[repair class]

NA Traction elevator—applies to most California installations 

1976 or later, most Western States installations 1982 or later and most other U.S. installations 1998 or later

D1014.011 12 Each Norm qty 0.002 (0.3) 

rad [RC2]

0.005 (0.3) 

rad

[RC2] 

NA

Traction elevator —applies to most California installations 

1976 or later, most Western States installations 1982 or later and most other U.S. installations 1998 or later

D1014.011_ridr 12 Each Norm qty 0.002 (0.3) 

rad [RC2]

0.005 (0.3) 

rad [RC2]

NA

B3–B1 Prefabricated steel stair with steel treads and landings with 

no seismic joint

C2011.001b 0.8 1.2 Each Norm qty 0.005 (0.6) 

rad [RC1]

0.017 (0.6) 

rad [RC3]

0.028 (0.45) 

rad [RC3]

Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g 

[RC3]

NA NA

Cold or hot potable water piping (diameter>2.5 in.), SDC 

A or B, PIPING FRAGILITY

D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC1]

2.6 (0.4) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g 

[RC1]

1.1 (0.5) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY

D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

Hot-water piping—large diameter welded steel—

(diameter>2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g 

[RC1]

2.6 (0.5) g 

[RC3]

NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A,B, PIPING FRAGILITY

D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g 

[RC1]

NA NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A,B, BRACING FRAGILITY

D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting less than 6 ft2 in 

cross-sectional area, SDC A or B

D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC3]

2.25 (0.4) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting—6 ft2 crosssectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NAHVAC drops/diffusers in suspended ceilings—no 

independent safety wires, SDC A or B

D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g 

[RC3]

NA NA

VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g 

[RC2]

NA NA
292 The HayWired Earthquake Scenario—Engineering Implications Table 14.—Continued Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 100 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to <350 A— unanchored equipment that is not vibration isolated— equipment fragility only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L1 Precast concrete panels 4.5 inches thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 Norm qty 0.005 (0.5) rad [RC3] NA NA Prefabricated steel stair with steel treads and landings with no seismic joint. C2011.001b 0.8 1.2 Each Norm qty 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] Raised access floor, nonseismically rated C3027.001 72 Each Panel Norm qty 0.5 (0.5) g [RC2] NA NA Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3] Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA Cold or hot potable water piping (diameter>2.5 in.), SDC 

A or B, PIPING FRAGILITY

D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC1]

2.6 (0.4) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g 

[RC1]

1.1 (0.5) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY

D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

Hot-water piping—Large Diameter Welded Steel—

(diameter>2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g 

[RC1]

2.6 (0.5) g 

[RC3]

NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A,B, PIPING FRAGILITY

D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g 

[RC1]

NA NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A,B, BRACING FRAGILITY

D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting less than 6 ft2 in 

cross-sectional area, SDC A or B

D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC3]

2.25 (0.4) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting—6 ft2 crosssectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NAHVAC Drops/Diffusers in suspended ceilings—No 

independent safety wires, SDC A or B

D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g 

[RC3]

NA NA

VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g 

[RC2]

NA NA
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 293 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 100 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to<350 A— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L2–L19 Precast concrete panels 4.5 inches thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 Norm qty 0.005 (0.5) rad [RC3] NA NA Wall partition, type: gypsum with metal studs, full height, fixed below, fixed above C1011.001a 3.84 5.76 900 ft2 Norm qty 0.005 (0.4) rad [RC1] 0.01 (0.3) rad [RC1] 0.021 (0.2) rad [RC2] Prefabricated steel stair with steel treads and landings with no seismic joint C2011.001b 0.8 1.2 Each Norm qty 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] Wall partition, type: gypsum and wallpaper, full height, fixed below, fixed above C3011.001a 0.29 0.435 900 ft2 Norm qty 0.0021 (0.6) rad [RC1] NA NA Raised access floor, nonseismically rated C3027.001 72 Each Panel Norm qty 0.5 (0.5) g [RC2] NA NA Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3] Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA Cold or hot potable water piping (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g [RC1] 2.6 (0.4) g [RC3] NA Hot-water piping—small diameter threaded steel— (diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA Hot-water piping—small diameter threaded steel— (diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA Hot-water piping—large diameter welded steel— (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g [RC1] 2.6 (0.5) g [RC3] NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, PIPING FRAGILITY D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g [RC1] NA NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, BRACING FRAGILITY D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA HVAC galvanized sheet-metal ducting less than 6 ft2 in cross-sectional area, SDC A or B D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting—6 ft2 cross- sectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA Table 14.—Continued
294 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] HVAC drops/diffusers in suspended ceilings—No independent safety wires, SDC A or B D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 10 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to <350 A— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L20 Precast concrete panels 4.5 inches thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 Norm qty 0.005 (0.5) rad [RC3] NA NA Prefabricated steel stair with steel treads and landings with no seismic joint. C2011.001b 0.8 1.2 Each Norm qty 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3] Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA

Cold or hot potable water piping (diameter>2.5 in.), SDC 

A or B, PIPING FRAGILITY

D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC1]

2.6 (0.4) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g 

[RC1]

1.1 (0.5) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY

D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

Hot-water piping—large diameter welded steel—

(diameter>2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g 

[RC1]

2.6 (0.5) g 

[RC3]

NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A,B, PIPING FRAGILITY

D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g 

[RC1]

NA NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A, B, BRACING FRAGILITY

D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting less than 6 ft2 in 

cross-sectional area, SDC A or B

D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC3]

2.25 (0.4) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting—6 ft2 crosssectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NAHVAC drops/diffusers in suspended ceilings—No 

independent safety wires, SDC A or B

D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g 

[RC3]

NA NA

Table 14.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 295 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA Air handling unit—capacity: 25,000 to <40,000 ft3/min— unanchored equipment that is not vibration isolated— Equipment fragility only D3052.011d 13 30,000 ft3/min Norm qty 0.25 (0.4) g [RC3] NA NA Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 10 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Motor control center capacity: all—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only D5012.013a 8.5 Each Norm qty 0.73 (0.45) g [RC3] NA NA Low voltage switchgear—capacity: 100 to <350 A— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L21–L39 Precast concrete panels 4.5 inches thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 Norm qty 0.005 (0.5) rad [RC3] NA NA Wall partition, type: gypsum with metal studs, full height, fixed below, fixed above C1011.001a 3.84 5.76 1,300 ft2 Norm qty 0.005 (0.4) rad [RC1] 0.01 (0.3) rad [RC1] 0.021 (0.2) rad [RC2] Prefabricated steel stair with steel treads and landings with no seismic joint. C2011.001b 0.8 1.2 Each Norm qty 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] Wall partition, type: gypsum and wallpaper, full height, fixed below, fixed above C3011.001a 0.29 0.435 900 ft2 Norm qty 0.0021 (0.6) rad [RC1] NA NA Raised access floor, nonseismically rated C3027.001 72 Each Panel Norm qty 0.5 (0.5) g [RC2] NA NA Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3] Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA Cold or hot potable water piping (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g [RC1] 2.6 (0.4) g [RC3] NA Hot-water piping—small diameter threaded steel— (diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA Hot-water piping—small diameter threaded steel— (diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA Hot-water piping—large diameter welded steel— (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g [RC1] 2.6 (0.5) g [RC3] NA Table 14.—Continued
296 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, PIPING FRAGILITY D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g [RC1] NA NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, BRACING FRAGILITY D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA HVAC galvanized sheet-metal ducting less than 6 ft2 in cross-sectional area, SDC A or B D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting—6 ft2 cross- sectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC drops/diffusers in suspended ceilings—No independent safety wires, SDC A or B D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 10 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to <350 A— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA

L40 Precast concrete panels 4.5 inches thick—in plane 

deformation

B2011.201a 5.332 7.998 390 ft2 Norm qty 0.005 (0.5) 

rad [RC3]

NA NA

Prefabricated steel stair with steel treads and landings with 

no seismic joint.

C2011.001b 0.8 1.2 Each Norm qty 0.005 (0.6) 

rad [RC1]

0.017 (0.6) 

rad [RC3]

0.028 (0.45) 

rad [RC3]

Suspended ceiling, SDC A, B, area (A): 250<A<1,000, 

vertical support only

C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g 

[RC1]

1.45 (0.25) g 

[RC3]

1.69 (0.25) g 

[RC3]

Independent Pendant Lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g 

[RC3]

NA NA

Cold or hot potable water piping (diameter>2.5 in.), SDC 

A or B, PIPING FRAGILITY

D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g 

[RC1]

2.6 (0.4) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g 

[RC1]

1.1 (0.5) g 

[RC3]

NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY

D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g 

[RC3]

2.4 (0.5) g 

[RC3]

NA

Hot-water piping—large diameter welded steel—

(diameter>2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g 

[RC1]

2.6 (0.5) g 

[RC3]

NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A, B, PIPING FRAGILITY

D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g 

[RC1]

NA NA

Table 14.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 297 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, BRACING FRAGILITY D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA Chiller—capacity: 750 to <1,000 tons—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only D3031.011d 3 850 tons Arup estimator 0.2 (0.4) g [RC3] NA NA HVAC galvanized sheet-metal ducting less than 6 ft2 in cross-sectional area, SDC A or B D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting—6 ft2 cross- sectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC drops/diffusers in suspended ceilings—No independent safety wires, SDC A or B D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 10 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Motor control center—capacity: all —unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only D5012.013a 8.5 Each Norm qty 0.73 (0.45) g [RC3] NA NA Low voltage switchgear—capacity: 100 to <350 A— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA Roof Cooling tower—capacity: 750 to <1,000 tons— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D3031.021d 3 850 tons Arup estimator 0.5 (0.4) g [RC3] NA NA Low voltage switchgear—capacity: 100 to <350 A— unanchored equipment that is not vibration isolated— EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA Table 14.—Continued
298 The HayWired Earthquake Scenario—Engineering Implications Table 15. Twenty-story steel-frame building nonstructural components. [NISTIR, National Institute of Standards and Technology Interagency Reports. E-W qty, east-west quantity per floor; N-S qty, north-south quantity per floor—note that components with only one quantity listed are nondirectional. DS, damage state. Other abbreviations: 

A, area; HVAC, heating, ventilation, and air conditioning; IGU, insulating glass unit; FT IGU, fully tempered insulating glass unit; Ip, component importance factor; NA, not applicable; Norm 

Qty, National Institute of Standards and Technology Normative Quantity estimation tool packaged with Federal Emergency Management Agency’s Performance Assessment Calculation Tool; OSHPD, California Office of Statewide Planning and Development; RC, RediTM repair class (Almufti and Willford, 2013)—1=reoccupancy, 2=functional recovery, and 3=full recovery; SDC, ASCE 7–10 seismic design criteria (American Society of Civil Engineers, 2010); SSG, structural silicone glazing; VAV, variable air volume; 

Vg, velocity of gravity; VHBTM SGT, 3MTM VHBTM structural glazing tape; 

Vo, velocity of object; W, wide-flange beam; WUF-B, welded unreinforced flange-bolted 

web. Unit abbreviations: A, ampere; ft2, square foot; ft3/min, cubic foot per minute; g, acceleration due to gravity; in., inch; kVA, kilo-volt-ampere; lin ft, linear foot; mm, millimeter; plf, per linear foot]

Floor Component NISTIR E-W qty N-S qty Units Source

DS1 median

(dispersion)

[repair class]

DS2 median

(dispersion)

[repair class]

DS3 median

(dispersion)

[repair class]

NA Traction elevator—applies to most California 

installations 1976 or later, most Western States installations 1982 or later and most other U.S. installations 1998 or later

D1014.011 6 Each Norm qty 0.002 (0.3) rad 

[RC2]

0.005 (0.3) rad

[RC2] 

NA

Traction elevator—applies to most California 

installations 1976 or later, most Western States installations 1982 or later and most other U.S. installations 1998 or later

D1014.011_ridr 6 Each Norm qty 0.002 (0.3) rad 

[RC2]

0.005 (0.3) rad 

[RC2]

NA

B1 Prefabricated steel stair with steel treads and landings 

with no seismic joint

C2011.001b 0.8 1.2 Each 0.005 (0.6) 

rad [RC1]

0.017 (0.6) rad 

[RC3]

0.028 (0.45) rad 

[RC3]

NA

Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NACold or hot potable water piping (diameter>2.5 in.), 

SDC A or B, PIPING FRAGILITY

D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g [RC1] 2.6 (0.4) g [RC3] NA

Hot-water piping—small diameter threaded 

steel—(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g 

[RC1]

1.1 (0.5) g [RC3] NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY

D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA

Hot-water piping—large diameter welded steel—

(diameter>2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g [RC1] 2.6 (0.5) g [RC3] NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A, B, PIPING FRAGILITY

D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g 

[RC1]

NA NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A, B, BRACING FRAGILITY

D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA

HVAC galvanized sheet-metal ducting less than 6 ft2

in cross-sectional area, SDC A or B

D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting—6 ft2 crosssectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NAHVAC drops/diffusers in suspended ceilings—no 

independent safety wires, SDC A or B

D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA

VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 299 Table 15.—Continued Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 100 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to <350 A—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L1 Precast concrete panels 4.5 inches thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 0.005 (0.5) rad [RC3] NA NA NA Prefabricated steel stair with steel treads and landings with no seismic joint C2011.001b 0.8 1.2 Each 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] 0.028 (0.45) rad Raised access floor, nonseismically rated C3027.001 72 Each Panel Norm qty 0.5 (0.5) g [RC2] NA NA Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3] Independent Pendant Lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA Cold or hot potable water piping (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g [RC1] 2.6 (0.4) g [RC3] NA Hot-water piping—small diameter threaded steel—(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA Hot-water piping—small diameter threaded steel— (diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA Hot-water piping—large diameter welded steel— (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g [RC1] 2.6 (0.5) g [RC3] NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, PIPING FRAGILITY D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g [RC1] NA NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, BRACING FRAGILITY D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA HVAC galvanized sheet-metal ducting less than 6 ft2 in cross-sectional area, SDC A or B D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting—6 ft2 cross- sectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC drops/diffusers in suspended ceilings—no independent safety wires, SDC A or B D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA
300 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 100 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to <350 A—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L2–L19 Precast concrete panels 4.5 inches thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 0.005 (0.5) rad [RC3] NA NA NA Wall partition, type: gypsum with metal studs, full height, fixed below, fixed above C1011.001a 3.84 5.76 900 ft2 0.005 (0.4) rad [RC1] 0.01 (0.3) rad [RC1] 0.021 (0.2) rad [RC2] NA Prefabricated steel stair with steel treads and landings with no seismic joint. C2011.001b 0.8 1.2 Each 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] NA Wall partition, type: gypsum and wallpaper, full height, fixed below, fixed above C3011.001a 0.29 0.435 900 ft2 0.0021 (0.6) rad [RC1] NA NA NA Raised access floor, nonseismically rated. C3027.001 72 Each Panel Norm qty 0.5 (0.5) g [RC2] NA NA Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3]

Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA

Cold or hot potable water piping (diameter>2.5 in.), 

SDC A or B, PIPING FRAGILITY

D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g [RC1] 2.6 (0.4) g [RC3] NA

Hot-water piping—small diameter threaded 

steel—(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g 

[RC1]

1.1 (0.5) g [RC3] NA

Hot-water piping—small diameter threaded steel—

(diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY

D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA

Hot-water piping—large diameter welded steel—

(diameter>2.5 in.), SDC A or B, PIPING FRAGILITY

D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g [RC1] 2.6 (0.5) g [RC3] NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A, B, PIPING FRAGILITY

D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g 

[RC1]

NA NA

Sanitary-waste piping—cast iron with bell and spigot 

couplings, SDC A, B, BRACING FRAGILITY

D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA

HVAC galvanized sheet-metal ducting less than 6 ft2

in cross-sectional area, SDC A or B

D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g 

[RC3]

NA

HVAC galvanized sheet-metal ducting—6 ft2 crosssectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA

Table 15.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 301 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] HVAC drops/diffusers in suspended ceilings—No independent safety wires, SDC A or B D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA Fire sprinkler water piping—horizontal mains and branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA Fire sprinkler drop standard threaded steel—dropping into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B D4011.031a 0.864 10 Units Norm qty 0.75 (0.4) g [RC2] 0.95 (0.4) g [RC3] NA Low voltage switchgear—capacity: 100 to <350 A—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA L20 Precast concrete panels 4.5 in. thick—in plane deformation B2011.201a 5.332 7.998 390 ft2 0.005 (0.5) rad [RC3] NA NA NA Prefabricated steel stair with steel treads and landings with no seismic joint. C2011.001b 0.8 1.2 Each 0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3] 0.028 (0.45) rad Suspended ceiling, SDC A, B, area (A): 250<A<1,000, vertical support only C3032.001b 14.4 600 ft2 Norm qty 1.01 (0.25) g [RC1] 1.45 (0.25) g [RC3] 1.69 (0.25) g [RC3] Independent pendant lighting—nonseismic C3034.001 144 Each Norm qty 0.6 (0.4) g [RC3] NA NA Cold or hot potable water piping (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2021.021a 0.144 1,000 lin ft Norm qty 1.5 (0.4) g [RC1] 2.6 (0.4) g [RC3] NA Hot-water piping—small diameter threaded steel—(diameter≤2.5 in.), SDC A or B, PIPING FRAGILITY D2022.011a 0.854 1,000 lin ft Norm qty 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA Hot-water piping—small diameter threaded steel— (diameter≤2.5 in.), SDC A or B, BRACING FRAGILITY D2022.011b 0.854 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA Hot-water piping—large diameter welded steel— (diameter>2.5 in.), SDC A or B, PIPING FRAGILITY D2022.021a 0.336 1,000 lin ft Norm qty 1.5 (0.5) g [RC1] 2.6 (0.5) g [RC3] NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, PIPING FRAGILITY D2031.021a 0.547 1,000 lin ft Norm qty 2.25 (0.4) g [RC1] NA NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC A, B, BRACING FRAGILITY D2031.021b 0.547 1,000 lin ft Norm qty 1.2 (0.5) g [RC3] 2.4 (0.5) g [RC3] NA Chiller—capacity: 350 to <750 tons—unanchored equipment that is not vibration isolated—equipment fragility only D3031.011c 3 490 tons Arup estimator 0.2 (0.4) g [RC3] NA NA HVAC galvanized sheet-metal ducting less than 6 ft2 in cross-sectional area, SDC A or B D3041.011a 0.72 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA Table 15.—Continued
302 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] HVAC galvanized sheet-metal ducting—6 ft2 cross- sectional area or greater, SDC A or B D3041.012a 0.192 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC Drops/Diffusers in suspended ceilings—No independent safety wires, SDC A or B D3041.031a 8.64 10 Units Norm qty 1.3 (0.4) g [RC3] NA NA VAV box with in-line coil, SDC A or B D3041.041a 6.72 10 Units Norm qty 1.9 (0.4) g [RC2] NA NA Air handling unit—capacity: 25,000 to <40,000 ft3

/

min—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only

D3052.011d 6.5 30,000 ft3

/

min

Norm qty 0.25 (0.4) g 

[RC3]

NA NA

Fire sprinkler water piping—horizontal mains and 

branches—old style Victaulic—thin wall steel—no bracing, SDC A or B, PIPING FRAGILITY

D4011.021a 1.92 1,000 lin ft Norm qty 1.1 (0.4) g [RC2] 2.4 (0.5) g [RC3] NA

Fire sprinkler drop standard threaded steel—dropping 

into unbraced lay-in tile soft ceiling—6 ft long drop maximum, SDC A or B

D4011.031a 0.864 10 Units Norm qty 0.75 (0.4) g 

[RC2]

0.95 (0.4) g 

[RC3]

NA

Motor control center—capacity: all —unanchored 

equipment that is not vibration isolated—EQUIPMENT FRAGILITY only

D5012.013a 8.5 Each Norm qty 0.73 (0.45) g 

[RC3]

NA NA

Low voltage switchgear—capacity: 100 to <350 

A—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only

D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA

Roof Cooling tower—capacity: 750 to <1,000 tons—

unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only

D3031.021d 2 850 tons Arup 

estimator

0.5 (0.4) g [RC3] NA NA

Low voltage switchgear—capacity: 100 to <350 

A—unanchored equipment that is not vibration isolated—EQUIPMENT FRAGILITY only

D5012.021a 1 225 A Norm qty 2.4 (0.4) g [RC3] NA NA

Table 15.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 303 Table 16. Reinforced-concrete building nonstructural components. [NISTIR, National Institute of Standards and Technology Interagency Reports. E-W qty, east-west quantity per floor; N-S qty, north-south quantity per floor—note that components with only one quantity listed are nondirectional. DS, damage state. Other abbreviations: 

A, area; HVAC, heating, ventilation, and air conditioning; IGU, insulating glass unit; FT IGU, fully tempered insulating glass unit; Ip, component importance factor; NA, not applicable; 

Norm Qty, National Institute of Standards and Technology Normative Quantity estimation tool packaged with Federal Emergency Management Agency’s Performance Assessment Calculation Tool; OSHPD, California Office of Statewide Planning and Development; RC, REDiTM repair class (Almufti and Willford, 2013)—1=reoccupancy, 2=functional recovery, and 3=full recovery; SDC, ASCE 7–10 seismic design criteria (American Society of Civil Engineers, 2010); SSG, structural silicone glazing; VAV, variable air volume; 

Vg, velocity of gravity; VHBTM SGT, 3MTM VHBTM structural glazing tape; 

Vo, velocity of object; W, wide-flange beam; WUF-B, welded unreinforced 

flange-bolted web. Unit abbreviations: A, ampere; ft2, square foot; ft3/min, cubic foot per minute; g, acceleration due to gravity; in., inch; kVA, kilo-volt-ampere; lin ft, linear foot; mm, millimeter; plf, per linear foot]

Floor Component NISTIR E-W qty N-S qty Units Source

DS1 median

(dispersion)

[repair class]

DS2 median

(dispersion)

[repair class]

DS3 median

(dispersion)

[repair class]

NA Traction elevator —applies to 

most California installations 1976 or later, most Western States installations 1982 or later and most other U.S. installations 1998 or later

D1014.011 6 Each Norm qty 0.002 (0.3) rad [RC2] 0.005 (0.3) rad [RC2] NA

Traction elevator—applies to 

most California installations 1976 or later, most Western States installations 1982 or later and most other U.S. installations 1998 or later

D1014.011_ridr 6 Each Norm qty 0.002 (0.3) rad [RC2] 0.005 (0.3) rad [RC2] NA

B4 Fire sprinkler water piping—horizontal mains and 

branches—old style Victaulic—thin wall steel—with designed bracing, SDC D, E, or F (OSHPD or similar), PIPING FRAGILITY

D4011.024a 5.69 1,000 lin ft Norm qty 1.9 (0.4) g [RC2] 3.4 (0.4) g [RC3] NA

Fire sprinkler drop standard 

threaded steel—no ceiling—6 ft long drop maximum, SDC D, E, or F

D4011.073a 4.14 100 Each Norm qty 2.6 (0.4) g [RC2] 3 (0.4) g [RC3] NA

B3–B2 Fire sprinkler water piping—horizontal mains and 

branches—old style Victaulic—thin wall steel—with designed bracing, SDC D, E, or F (OSHPD or similar), PIPING FRAGILITY

D4011.024a 5.69 1,000 lin ft Norm qty 1.9 (0.4) g [RC2] 3.4 (0.4) g [RC3] NA

Fire sprinkler drop standard 

threaded steel—no ceiling—6 ft long drop maximum, SDC D, E, or F

D4011.073a 4.14 100 Each Norm qty 2.6 (0.4) g [RC2] 3 (0.4) g [RC3] NA
304 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] B1 Chiller—capacity: 100 to <350 tons—Equipment is hard anchored— EQUIPMENT FRAGILITY only D3031.013e 2 250 tons Arup estimator 0.72 (0.2) g [RC2] NA NA Chiller—capacity: 100 to <350 tons—vibration isolated equipment that is not snubbed or restrained—AN- CHORAGE FRAGILITY only D3031.012d 2 250 tons Arup estimator 0.4 (0.5) g [RC3] NA NA Air handling unit—capac- ity: 5,000 to <10,000 ft3

/

min—equipment is hard anchored— EQUIPMENT FRAGILITY only

D3052.013e 1 8,000 ft3/min Arup 

estimator

1.54 (0.6) g [RC2] NA NA

Air handling unit—capacity: 5,000 to <10,000 ft3

/

min—equipment is hard anchored—ANCHORAGE FRAGILITY only

D3052.013d 1 8,000 ft3/min Arup 

estimator

0.4 (0.5) g [RC3] NA NA

Air handling unit—capacity: 10,000 to <25,000 ft3

/

min—equipment is hard anchored— EQUIPMENT FRAGILITY only

D3052.013h 1 20,000 ft3/min Arup 

estimator

1.54 (0.6) g [RC2] NA NA

Air handling unit—capacity: 10,000 to <25,000 ft3

/

min—equipment is hard anchored— ANCHORAGE FRAGILITY only

D3052.013g 1 20,000 ft3/min Norm qty 0.4 (0.5) g [RC3] NA NA

Fire sprinkler water piping—horizontal mains and 

branches—old style Victaulic—thin wall steel—with designed bracing, SDC D, E, or F (OSHPD or similar), PIPING FRAGILITY

D4011.024a 5.69 1,000 lin ft Norm qty 1.9 (0.4) g [RC2] 3.4 (0.4) g [RC3] NA

Table 16.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 305 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Fire sprinkler drop standard threaded steel—no ceil- ing—6 ft long drop maxi- mum, SDC D, E, or F D4011.073a 4.14 100 Each Arup estimator 2.6 (0.4) g [RC2] 3 (0.4) g [RC3] NA Transformer/primary ser- vice—capacity: 750 to 1,500 kVA—equipment is hard anchored— EQUIPMENT FRAGILITY only D5011.013k 1 1,000 kVa Arup estimator 3.05 (0.5) g [RC2] NA NA Transformer/primary ser- vice—capacity: 750 to 1,500 kVA—equipment is hard anchored— ANCHORAGE FRAGILITY only D5011.013j 1 1,000 kVa Arup estimator 0.4 (0.5) g [RC3] NA NA Low voltage switchgear— capacity: 750 to <1,200 A—equipment is hard anchored—EQUIPMENT FRAGILITY only D5012.023h 1 800 A Arup estimator 2.4 (0.4) g [RC2] NA NA Low voltage switchgear— capacity: 750 to <1,200 A—equipment is hard anchored—ANCHORAGE FRAGILITY only D5012.023g 1 800 A Arup estimator 0.4 (0.5) g [RC3] NA NA Low voltage switchgear— capacity: 1,200 to 2,000 A—equipment is hard anchored—EQUIPMENT FRAGILITY only D5012.023k 2 1,600 A Arup estimator 2.4 (0.4) g [RC2] NA NA Low voltage switchgear— capacity: 1,200 to 2,000 A—equipment is hard anchored—ANCHORAGE FRAGILITY only D5012.023j 2 1,600 A Arup estimator 0.4 (0.5) g [RC3] NA NA Distribution panel—capacity: 1,200 to 2,000 A—equip- ment is hard anchored— EQUIPMENT FRAGILITY only D5012.033k 1 1,600 A Arup estimator 3.05 (0.4) g [RC2] NA NA Table 16.—Continued
306 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Distribution panel—capacity: 1,200 to 2,000 A—equip- ment is hard anchored—AN- CHORAGE FRAGILITY only D5012.033j 1 1,600 A Arup estima- tor 0.4 (0.5) g [RC3] NA NA L1 Suspended ceiling, SDC D, E (Ip=1.0), area (A) < 250, vertical and lateral support C3032.003a 42 250 ft2 Norm qty 1.6 (0.3) g [RC1] 1.95 (0.3) g [RC3] 2.07 (0.3) g [RC3] Independent pendant lighting— nonseismic C3034.001 174 Each Norm qty 0.6 (0.4) g [RC3] NA NA Cold-water piping (diam- eter>2.5 in.), SDC D, E, F, PIPING FRAGILITY D2021.023a 0.02 1,000 lin ft Moehle and others, 2011 2.25 (0.4) g [RC1] 4.1 (0.4) g [RC3] NA Cold-water piping (diam- eter>2.5 in.), SDC D,E,F, BRACING FRAGILITY D2021.023b 0.02 1,000 lin ft Moehle and others, 2011 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA Hot-water piping—small diam- eter threaded steel—(diam- eter≤2.5 in.), SDC D, E, or F, PIPING FRAGILITY D2022.013a 0.88 1,000 lin ft Moehle and others, 2011 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA

Hot-water piping—small diameter threaded steel—(diameter≤2.5 in.), SDC D, E, or F, 

BRACING FRAGILITY

D2022.013b 0.88 1,000 lin ft Moehle and 

others, 2011

2.25 (0.5) g [RC3] NA NA

Hot-water piping—large diameter welded steel—(diameter>2.5 in.), SDC D, E, or F, 

PIPING FRAGILITY

D2022.023a 0.06 1,000 lin ft Moehle and 

others, 2011

2.25 (0.5) g [RC1] 4.1 (0.5) g [RC3] NA

Hot-water piping—large diameter welded steel—(diameter>2.5 in.), SDC D, E, or F, 

BRACING FRAGILITY

D2022.023b 0.06 1,000 lin ft Moehle and 

others, 2011

1.5 (0.5) g [RC3] 2.25 (0.5) g [RC3] NA

Sanitary-waste piping—cast 

iron with bell and spigot couplings, SDC D, E, F, PIPING FRAGILITY

D2031.023a 0.54 1,000 lin ft Moehle and 

others, 2011

3 (0.5) g [RC1] NA NA

Sanitary-waste piping—cast 

iron with bell and spigot couplings, SDC D, E, F, BRACING FRAGILITY

D2031.023b 0.54 1,000 lin ft Moehle and 

others, 2011

2.25 (0.5) g [RC3] NA NA

Table 16.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 307 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Chilled water piping—small diameter threaded steel—(di- ameter≤2.5 in.), SDC D, E, or F, PIPING FRAGILITY D2051.013a 0.45 1,000 lin ft Moehle and others, 2011 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA Chilled water piping—small diameter threaded steel—(di- ameter≤2.5 in.), SDC D, E, or F, BRACING FRAGIL- ITY D2051.013b 0.45 1,000 lin ft Moehle and others, 2011 2.25 (0.5) g [RC3] NA NA Steam piping—large diameter welded steel—(diameter>2.5 in.), SDC D, E, or F, PIPING FRAGILITY D2061.023a 0.06 1,000 lin ft Norm qty 2.25 (0.4) g [RC1] 4.1 (0.4) g [RC3] NA Steam piping—large diameter welded steel—(diameter>2.5 in.), SDC D, E, or F, BRAC- ING FRAGILITY D2061.023b 0.06 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting—6 ft2 cross-section- al area or greater, SDC D, E, or F D3041.011c 0.06 1,000 lin ft Norm qty 3.75 (0.4) g [RC3] 4.5 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting—6 ft2 cross-section- al area or greater, SDC D, E, or F D3041.012c 0.58 1,000 lin ft Norm qty 3.75 (0.4) g [RC3] 4.5 (0.4) g [RC3] NA HVAC Drops/Diffusers in suspended ceilings—No independent safety wires, SDC C D3041.031b 8.2 100 Each Moehle and others, 2011 1.3 (0.4) g [RC3] NA NA Fire sprinkler water pip- ing—horizontal mains and branches—old style Victau- lic—thin wall steel—with designed bracing, SDC D, E, or F (OSHPD or similar), PIPING FRAGILITY D4011.024a 2.08 1,000 lin ft Norm qty 1.9 (0.4) g [RC2] 3.4 (0.4) g [RC3] NA Table 16.—Continued
308 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Fire sprinkler drop standard threaded steel—dropping into braced lay-in tile soft ceiling—6 ft long drop maximum, SDC D, E, or F D4011.053a 1.86 100 Each Norm qty 1.5 (0.4) g [RC2] 2.25 (0.4) g [RC3] NA Curtain walls—unitized curtain wall (also generic unitized curtain wall), configuration: symmetric insulating glass units (dual-pane, equal-thick- ness IGU), lamination: not laminated, glass type: full tempered, details: 1-1/4 in. (32 mm) FT IGU [1/4 in. (6 mm) inner and outer panes], 4-sided SSG, VHBTM SGT; glass-frame clearance=0.43 in. (11 mm); aspect ratio=varies; sealant=wet B2022.201 68.9 68.9 30 ft2 Moehle and others, 2011 0.01 (0.3) rad [RC2] 0.03 (0.3) rad [RC3] 0.04 (0.3) rad [RC3] Wall partition, type: gypsum with metal studs, full height, 

fixed below, fixed above

C1011.001a 2.62 2.62 100 lin ft Norm qty 0.005 (0.4) rad [RC1] 0.01 (0.3) rad [RC1] 0.021 (0.2) rad [RC2]

Prefabricated steel stair with 

steel treads and landings with no seismic joint

C2011.001b 2 Each Moehle and 

others, 2011

0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3]

Wall partition, type: gypsum 

and wallpaper, full height, fixed below, fixed above

C3011.001a 0.79 0.79 100 lin ft Norm qty 0.0021 (0.6) rad [RC1] NA NA

L2–L42 Cold-water piping (diameter>2.5 in.), SDC D, E, F, 

PIPING FRAGILITY

D2021.013a 0.02 1,000 lin ft Moehle and 

others, 2011

2.25 (0.4) g [RC1] 4.1 (0.4) g [RC3] NA

Cold-water piping (diameter>2.5 in.), SDC D, E, F, 

BRACING FRAGILITY

D2021.013b 0.02 1,000 lin ft Moehle and 

others, 2011

1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA

Hot-water piping—small diameter threaded steel—(diameter≤2.5 in.), SDC D, E, or F, 

PIPING FRAGILITY

D2022.013a 1.66 1,000 lin ft Moehle and 

others, 2011

0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA

Table 16.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 309 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Hot-water piping—small diam- eter threaded steel—(diam- eter≤2.5 in.), SDC D, E, or F, BRACING FRAGILITY D2022.013b 1.66 1,000 lin ft Moehle and others, 2011 2.25 (0.5) g [RC3] NA NA Hot-water piping—large diam- eter welded steel—(diam- eter>2.5 in.), SDC D, E, or F, PIPING FRAGILITY D2022.023a 0.06 1,000 lin ft Moehle and others, 2011 2.25 (0.5) g [RC1] 4.1 (0.5) g [RC3] NA Hot-water piping—large diam- eter welded steel—(diam- eter>2.5 in.), SDC D, E, or F, BRACING FRAGILITY D2022.023b 0.06 1,000 lin ft Moehle and others, 2011 1.5 (0.5) g [RC3] 2.25 (0.5) g [RC3] NA Sanitary-waste piping—cast iron with bell and spigot cou- plings, SDC D, E, F, PIPING FRAGILITY D2031.023a 1.43 1,000 lin ft Moehle and others, 2011 3 (0.5) g [RC1] NA NA Sanitary-waste piping—cast iron with bell and spigot couplings, SDC D, E, F, BRACING FRAGILITY D2031.023b 1.43 1,000 lin ft Moehle and others, 2011 2.25 (0.5) g [RC3] NA NA Chilled water piping—small diameter threaded steel—(di- ameter≤2.5 in.), SDC D, E, or F, PIPING FRAGILITY D2051.013a 1.47 1,000 lin ft Moehle and others, 2011 0.55 (0.5) g [RC1] 1.1 (0.5) g [RC3] NA Chilled water piping—small diameter threaded steel—(di- ameter≤2.5 in.), SDC D, E, or F, BRACING FRAGIL- ITY D2051.013b 1.47 1,000 lin ft Moehle and others, 2011 2.25 (0.5) g [RC3] NA NA HVAC in-line fan, fan indepen- dently supported and vibra- tion isolators, SDC D, E, F D3041.001c 0.6 10 Each Arup estimator 2.25 (0.4) g [RC2] 2.6 (0.4) g [RC3] NA HVAC galvanized sheet-metal ducting less than 6 ft2 in cross-sectional area, SDC D, E, or F D3041.011c 0.58 1,000 lin ft Norm qty 1.5 (0.4) g [RC3] 2.25 (0.4) g [RC3] NA HVAC drops/diffusers without ceilings—supported by duct- ing only—No independent safety wires, SDC D, E, or F D3041.032c 8.2 100 Each Moehle and others, 2011 1.5 (0.4) g [RC3] NA NA Table 16.—Continued
310 The HayWired Earthquake Scenario—Engineering Implications Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] VAV box with in-line coil, SDC C D3041.041b 0.6 10 Each Norm qty 1.9 (0.4) g [RC2] NA NA Fire sprinkler water pip- ing—horizontal mains and branches—old style Victau- lic—thin wall steel—with designed bracing, SDC D, E, or F (OSHPD or similar), PIPING FRAGILITY D4011.024a 2.55 1,000 lin ft Norm qty 1.9 (0.4) g [RC2] 3.4 (0.4) g [RC3] NA Fire sprinkler drop standard threaded steel—no ceil- ing—6 ft long drop maxi- mum, SDC D, E, or F D4011.073a 1.39 100 Each Norm qty 2.6 (0.4) g [RC2] 3 (0.4) g [RC3] NA Curtain walls—unitized curtain wall (also generic unitized curtain wall), configuration: symmetric insulating glass units (dual-pane, equal-thick- ness IGU), lamination: not laminated, glass type: full tempered, details: 1-1/4 in. 

(32 mm) FT IGU [1/4 in. (6 mm) inner and outer panes], 4-sided SSG, VHBTM SGT; glass-frame clearance=0.43 in. (11 mm); aspect ratio=varies; sealant=wet

B2022.201 68.9 68.9 30 ft2 Moehle and 

others, 2011

0.01 (0.3) rad [RC2] 0.03 (0.3) rad [RC3] 0.04 (0.3) rad [RC3]

Wall partition, type: gypsum 

with metal studs, full height, fixed below, fixed above

C1011.001a-racking 4.51 4.51 100 lin ft Norm qty 0.005 (0.4) rad [RC1] 0.01 (0.3) rad [RC1] 0.021 (0.2) rad [RC2]

Prefabricated steel stair with 

steel treads and landings with no seismic joint.

C2011.001b 2 Each Moehle and 

others, 2011

0.005 (0.6) rad [RC1] 0.017 (0.6) rad [RC3] 0.028 (0.45) rad [RC3]

Wall partition, type: gypsum 

and wallpaper, full height, fixed below, fixed above

C3011.001a-racking 2.38 2.38 100 lin ft Norm qty 0.0021 (0.6) rad [RC1] NA NA

Wall partition, type: gypsum 

and ceramic tile, full height, fixed below, fixed above

C3011.002a-racking 3.43 3.43 100 lin ft Moehle and 

others, 2011

0.0021 (0.6) rad [RC1] 0.0071 (0.45) rad 

[RC1]

NA

Table 16.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 311 Floor Component NISTIR E-W qty N-S qty Units Source DS1 median (dispersion) [repair class] DS2 median (dispersion) [repair class] DS3 median (dispersion) [repair class] Low voltage switchgear— capacity: 100 to <350 A—equipment is hard anchored—EQUIPMENT FRAGILITY only D5012.023b 1 225 A Norm qty 2.4 (0.4) g [RC2] NA NA Roof Cooling tower—capacity: 350 to <750 tons—equipment is hard anchored—EQUIP- MENT FRAGILITY only D3031.023h 3 500 tons Arup estimator 1.52 (0.4) g [RC2] NA NA Cooling tower—capacity: 350 to <750 tons—equipment is hard anchored—EQUIP- MENT FRAGILITY only D3031.023g 3 500 tons Arup estimator 1.2 (0.5) g [RC3] NA NA HVAC fan—capacity: all— equipment is hard an- chored—EQUIPMENT FRAGILITY only D3041.103b 4 Each Arup estimator 4.8 (0.6) g [RC2] NA NA HVAC fan—capacity: all— equipment is hard an- chored—ANCHORAGE FRAGILITY only D3041.103a 4 Each Arup estimator 1.2 (0.5) g [RC3] NA NA Air handling unit—capac- ity: 10,000 to <25,000 ft3

/

min—equipment is hard anchored— EQUIPMENT FRAGILITY only

D3052.013h 1 20,000 ft3/min Arup 

estimator

1.54 (0.6) g [RC2] NA NA

Air Handling Unit—Capacity: 10,000 to <25,000 ft3

/

min—Equipment is hard anchored—ANCHORAGE FRAGILITY only

D3052.013g 1 20,000 ft3/min Arup 

estimator

0.4 (0.5) g [RC3] NA NA

Table 16.—Continued
312 The HayWired Earthquake Scenario—Engineering Implications

S-SF-B-43 Description

This appendix summarizes the results of interest for the HayWired mainshock from the structural analysis and loss assessment 

of building S-SF-B-43—a 40-story steel-frame office building in 

San Francisco with the baseline orientation shown in figure 7.

Engineering-Demand Parameters

The “best estimate” EDPs were obtained from the NLRHA. 

To capture uncertainty associated with modeling and construction 

quality, the EDPs for each realization in the loss assessment 

follows the method recommended by FEMA P-58 (Applied 

Technology Council, 2012) for buildings with nonlinear response 

history analysis results available. This algorithm was developed by 

Yang and others (2009).

Building S-SF-B-43 sees low-moderate acceleration 

demands, with peak nondirectional median floor acceleration for 

the whole building at 0.63 g. Peak median interstory drift ratio for 

the whole building is 1 percent, and the peak residual interstory 

Appendix 2. S-SF-B-43—40-Story Steel-Frame Building in San Francisco 

(Baseline Orientation)

Figure 16. Graphs showing 

realized peak interstory 

drift ratio demands in 

building S-SF-B-43 (40-story 

steel-frame building in 

San Francisco, California; 

baseline orientation) 

for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 

50th percentile is taken 

directly from the nonlinear 

response-history analysis. 

Due to the explicit modeling 

of the substructure, level 4 is 

the ground floor. Direction 1 

is east-west and direction 2 

is north-south.

0 .005 .01 .015 .02 0 .005 .01 .015 .02 0 .005 .01 .015 .02

0

5

10

15

20

25

30

35

40

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90

drift ratio is 0.04 percent. As shown in figures 16 and 17, the peak 

drifts occur around level 34 (31st superstructure floor). This is 

because beam fracturing and yielding is concentrated in the top 

third of the building as shown in figure 18. This concentration of 

damage is due to 1970s design procedure that distributed seismic 

design forces up the building height according to solely the first 

mode translational response. In addition, wind forces were applied 

as uniform up the height rather than in an inverted triangle as 

done in practice today. It should be noted that beam yielding does 

not necessarily mean repair is required. Conversely, the column 

performance for this building is good, with nearly all columns 

remaining elastic. All column splices remain elastic. Realized peak 

floor-acceleration demands for the building are shown in figure 19.

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed 

using the probabilistic approach outlined in the Federal 

Emergency Management Agency’s (FEMA) P-58 document 
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 313

Figure 17. Graphs showing 

realized peak residual 

interstory drift ratio demands 

in building S-SF-B-43 (40-

story steel-frame building in 

San Francisco, California; 

baseline orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 4 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0.8 1×10-3 1×10-3 1×10-3 0 0.2 0.4 0.6 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8

0

5

10

15

20

25

30

35

40

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

Elastic

EXPLANATION

A B

Yielded

Fractured

Figure 18. Diagrams showing beam performance for sample 

(A) long and (B) short elevations of building S-SF-B-43 (40-story 

steel-frame building in San Francisco, California; baseline 

orientation) for the hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake scenario. The 50th 

percentile is taken directly from the nonlinear response-history 

analysis. Due to the explicit modeling of the substructure, level 

4 is the ground floor. 
314 The HayWired Earthquake Scenario—Engineering Implications

Figure 19. Graphs 

showing realized peak 

floor-acceleration demands 

(relative to acceleration due to 

gravity, g) in building S-SF-B-43 

(40-story steel-frame building 

in San Francisco, California; 

baseline orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 4 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

30

35

40

45

Floor Level

Direction 1

0 0.2 0.4 0.6 0.8 1

Acceleration [g]

0

5

10

15

20

25

30

35

40

45 Direction 2

0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

30

35

40

45 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

30

35

40

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90

(Applied Technology Council, 2012). The likely costs to repair 

and (or) replace damaged components are calculated based 

solely on FEMA P-58, whereas repair time and downtime are 

estimated using the FEMA P-58 based methodology outlined 

REDi (Almufti and Willford, 2013).

Damaged Components

The probability that a component type in building S-SFB-43 incurs damage that hinders either reoccupancy, functionality, or full recovery was examined in the realizations. The 

results are shown in figure 20.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median repair cost for building S-SF-B-43 is 10.8 

percent of the total building replacement value, or $15.1 million. The 90th-percentile total repair cost is 12.3 percent of 

the total building replacement value, or $17.1 million. For this 

study, the total building replacement value is defined as the 

hard costs only required to replace the building, based on a 

construction cost estimate, including at minimum all structural 

and nonstructural components plus the value of damageable 

building contents if they are known. Figure 21 shows the 

contribution of building component groups to realized median 

total repair cost. Table 17 shows realized median and 90thpercentile repair time and total downtime, and table 18 shows 

realized median and 90th-percentile delays due to impeding 

factors to functional recovery.

Table 17. Realized median and 90th-percentile repair time 

and total downtime for building S-SF-B-43 (40-story steel-frame 

building in San Francisco, California; baseline orientation) due 

to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

Repair time

REDi repair class

Reoccupancy,

in days

Functional 

recovery,

in days

Full 

recovery,

in days

Median repair 

time

41 45 52

Median total 

downtime

248 288 292

90th-percentile 

repair time

61 126 132

90th-percentile 

downtime

374 388 395
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 315 Building component

Low voltage switchgear (unanchored)

Motor control center (unanchored)

Air handling unit (unanchored)

Cooling tower (unanchored)

Chiller (unanchored)

HVAC drops/diffusers

HVAC ducting

HVAC ducting

Traction elevator

Pendant lighting

Suspended ceilings

Raised access floors

Wall coverings

Fire sprinkler drops

Fire sprinkler water piping (piping)

Heating hot water piping, large diameter (piping)

Potable water piping, large diameter (piping)

Pre-Northridge beam-column joints

Percentage of realizations in which a repair 

class is triggered

Pre-Northridge beam-column joints

Prefabricated steel stairs (no seismic joint)

Gypsum wall partitions

Precast concrete cladding

Heating hot water piping, small diameter (bracing)

Heating hot water piping, small diameter (piping)

Sanitary waste piping (bracing)

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 20. Graph showing the 

percentage of realizations in which a 

building component type in building 

S-SF-B-43 (40-story steel-frame 

building in San Francisco, California; 

baseline orientation) incurs damage 

from the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

Damaged components are assigned 

to a given REDi repair class (Almufti 

and Willford, 2013)—reoccupancy, 

functional recovery, or full recovery. 

HVAC, heating, ventilation, air 

conditioning.

Precast concrete cladding

Gypsum wall partitions Other

Pendant lighting

Air handling unit (unanchored)

Chiller (unanchored) Traction elevator

EXPLANATION

Building component group

6

53

3

4

6

23

5

Figure 21. Pie chart showing the percentage contribution of building component groups to realized median total repair cost for 

building S-SF-B-43 (40-story steel-frame building in San Francisco, California; baseline orientation) due to the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.
316 The HayWired Earthquake Scenario—Engineering Implications

Table 18. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building S-SF-B-43 (40-story 

steel-frame building in San Francisco, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 55 200 None.

Engineer mobilization 0 0 The median engineer mobilization time is zero even though 

some beam-joint joints are redamaged because REDi 

(Almufti and Willford, 2013) assumes the likelihood of 

an inspector seeing structural damage decreases as the 

percentage of structural components damaged decreases.

Contractor mobilization 253 354 None.

Permitting 0 0 The median permitting time is zero even though some beamjoint joints are redamaged because REDi (Almufti and 

Willford, 2013) assumes the likelihood of an inspector 

seeing structural damage decreases as the percentage of 

structural components damaged decreases.

S-SF-R-43 Description

This appendix summarizes the results of interest for the HayWired mainshock from the structural analysis and loss assessment 

of building S-SF-R-43—a 40-story steel-frame office building 

in San Francisco with the rotated orientation shown in figure 7. 

Results are shown in figures 22–24.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended 

by FEMA P-58 (Applied Technology Council, 2012) for buildings 

with nonlinear response history analysis results available. This 

algorithm was developed by Yang and others (2009). 

Building S-SF-R-43 sees low-moderate acceleration 

demands, with peak nondirectional median floor acceleration 

for the whole building at 0.56 g. Peak median interstory drift 

ratio for the whole building is 0.7 percent, and the peak residual 

interstory drift ratio is 0.025 percent. The peak interstory drift ratio 

is governed by the ground-floor frames. All beams and columns 

remain elastic. All column splices remain elastic.

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed using 

the probabilistic approach outlined in the Federal Emergency 

Management Agency’s (FEMA) P-58 document (Applied 

Technology Council, 2012). The likely costs to repair and (or) 

Appendix 3. S-SF-R-43—40-Story Steel-Frame Building in San Francisco 

(Rotated Orientation)

replace damaged components are calculated based solely on 

FEMA P-58, whereas repair time and downtime are estimated 

using the FEMA P-58 based methodology outlined REDi (Almufti 

and Willford, 2013).

Damaged Components

The probability that a component type in building S-SF-R-43 

incurs damage that hinders either reoccupancy, functionality, or 

full recovery was examined in the realizations. The results are 

shown in figure 25.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building S-SF-R-43 is 9.7 

percent of the total building replacement value, or $13.5 million. 

The 90th-percentile total repair cost is 11.3 percent of the total 

building replacement value, or $15.7 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based on a construction cost 

estimate including at minimum all structural and nonstructural 

components plus the value of damageable building contents if 

they are known. Figure 26 shows the contribution of building 

component groups to realized median total repair cost. Table 19 

shows realized median and 90th-percentile repair time and 

total downtime, and table 20 shows realized median and 

90th-percentile delays due to impeding factors to functional 

recovery.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 317

Figure 22. Graphs showing 

realized peak interstory drift ratio 

demands in building S-SF-R-43 

(40-story steel-frame building in 

San Francisco, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 4 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

0 0.005 0.01 0.015

0

5

10

15

20

25

30

35

40

45

Floor Level

Direction 1

0 0.005 0.01 0.015

Story Drift Ratio

0

5

10

15

20

25

30

35

40

45 Direction 2

0 0.005 0.01 0.015

0

5

10

15

20

25

30

35

40

45 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

15

20

25

30

35

40

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90

2 2.5×10-4 0 0.5 1 1.5 2 2.5×10-4 0 0.5 1 1.5 2 2.5×10-4 0 0.5 1 1.5

0

5

10

15

20

25

30

35

40

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

Figure 23. Graphs showing realized 

peak residual interstory drift ratio 

demands in building S-SF-R-43 

(40-story steel-frame building in 

San Francisco, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock of 

the HayWired earthquake scenario. 

The 50th percentile is taken directly 

from the nonlinear response-history 

analysis. Due to the explicit modeling 

of the substructure, level 4 is the 

ground floor. Direction 1 is east-west 

and direction 2 is north-south.
318 The HayWired Earthquake Scenario—Engineering Implications

0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

30

35

40

45

Floor Level

Direction 1

0 0.2 0.4 0.6 0.8 1

Acceleration [g]

0

5

10

15

20

25

30

35

40

45 Direction 2

0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

30

35

40

45 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

30

35

40

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90

Building component

Low voltage switchgear (unanchored)

Motor control center (unanchored)

Air handling unit (unanchored)

Cooling tower (unanchored)

Chiller (unanchored)

Traction elevator

Pendant lighting

Suspended ceilings

Raised access floors

Wall coverings

Fire sprinkler drops

Fire sprinkler water piping (piping)

Heating hot water piping, large diameter (piping)

Percentage of realizations in which a repair 

class is triggered

Prefabricated steel stairs (no seismic joint)

Gypsum wall partitions

Precast concrete cladding

Heating hot water piping, small diameter (bracing)

Heating hot water piping, small diameter (piping)

Sanitary waste piping (bracing)

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 24. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration 

due to gravity, g) in building 

S-SF-R-43 (40-story steel-frame 

building in San Francisco, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 4 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

Figure 25. Graph showing the 

percentage of realizations in which a 

building component type in building 

S-SF-R-43 (40-story steel-frame building 

in San Francisco, California; rotated 

orientation) incurs damage from the 

hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake 

scenario. Damaged components 

are assigned to a given REDi repair 

class (Almufti and Willford, 2013)—

reoccupancy, functional recovery, or full 

recovery. HVAC, heating, ventilation, air 

conditioning.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 319

Precast concrete cladding

Gypsum wall partitions

Other

Pendant lighting

Air handling unit (unanchored)

Chiller (unanchored)

Traction elevator

EXPLANATION

Building component group

7

55

2

4

5

21

6

Figure 26. Pie chart showing the percentage contribution of 

building component groups to realized median total repair cost for 

building S-SF-R-43 (40-story steel-frame building in San Francisco, 

California; rotated orientation) due to the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

Table 19. Realized median and 90th-percentile repair time and total downtime 

for building S-SF-R-43 (40-story steel-frame building in San Francisco, California; 

rotated orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 37 39 44

Median total downtime 250 288 292

90th-percentile repair time 54 102 110

90th-percentile downtime 364 390 398

Table 20. Realized median and 90th-percentile delays due to impeding factors to functional recovery for 

building S-SF-R-43 (40-story steel-frame building in San Francisco, California; rotated orientation) due to the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Impeding factor

Median 

disruption,

in days

90th-percentile 

disruption,

in days

Comment

Inspection 5 10 None.

Financing 80 222 None.

Engineer mobilization 0 0 The median engineer mobilization is zero because 

no structural components are damaged.

Contractor mobilization 255 366 None.

Permitting 0 0 No structural damage.
320 The HayWired Earthquake Scenario—Engineering Implications

S-SF-B-20 Description

This appendix summarizes the results for the HayWired 

mainshock of interest from the structural analysis and loss 

assessment of building S-SF-B-20—a 20-story steel-frame office 

building in San Francisco with the baseline orientation shown in 

figure 7. Results are shown in figures 27–29.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended by FEMA P-58 (Applied Technology Council, 2012) 

for buildings with nonlinear response history analysis results 

available. This algorithm was developed by Yang and others 

(2009).

Building S-SF-B-20 sees low-moderate acceleration 

demands, with peak nondirectional median floor acceleration 

for the whole building at 0.63 g, slightly higher than the 

40-story San Francisco building. Peak median interstory drift 

ratio for the whole building is 0.45 percent, and the peak 

residual interstory drift ratio is 0.006 percent. All columns 

Appendix 4. S-SF-B-20—20-Story Steel-Frame Building in San Francisco 

(Baseline Orientation)

Figure 27. Graphs showing 

realized peak interstory drift 

ratio demands in building 

S-SF-B-20 (20-story steel-frame 

office building in San Francisco, 

California; baseline orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 2 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

and beams remain elastic for this building. All column splices 

remain elastic.

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed using 

the probabilistic approach outlined in the Federal Emergency 

Management Agency’s (FEMA) P-58 document (Applied 

Technology Council, 2012). The likely costs to repair and (or) 

replace damaged components are calculated based solely on 

FEMA P-58, whereas repair time and downtime are estimated 

using the FEMA P-58 based methodology outlined REDi (Almufti 

and Willford, 2013).

Damaged Components

The probability that a component type in building S-SFB-20 incurs damage that hinders either reoccupancy, functionality, or full recovery was examined in the realizations. The 

results are shown in figure 30.

0 0.002 0.004 0.006 0.008 0.01

0

5

10

15

20

25

Floor Level

Direction 1

0 0.002 0.004 0.006 0.008 0.01

Story Drift Ratio

0

5

10

15

20

25 Direction 2

0 0.002 0.004 0.006 0.008 0.01

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 .002 .004 .006 .008 .01 0 .002 .004 .006 .008 .01 0 .002 .004 .006 .008 .01

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 321

Figure 28. Graphs showing 

realized peak residual interstory 

drift ratio demands in building 

S-SF-B-20 (20-story steel-frame 

office building in San Francisco, 

California; baseline orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 2 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

Figure 29. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration 

due to gravity, g) in building 

S-SF-B-20 (20-story steel-frame 

office building in San Francisco, 

California; baseline orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 2 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

1 1.5×10-4 0 0.5 1 1.5×10-4 0 0.5 1 1.5×10-4 0 0.5

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

Floor Level

Direction 1

0 0.2 0.4 0.6 0.8 1

Acceleration [g]

0

5

10

15

20

25 Direction 2

0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
322 The HayWired Earthquake Scenario—Engineering Implications Building component

Air handling unit

Cooling tower

Chiller

HVAC drops/diffusers

HVAC ducting

HVAC ducting

Traction elevator

Pendant lighting

Suspended ceilings

Raised access floors

Wall coverings

Fire sprinkler drops

Fire sprinkler water piping (piping)

Heating hot water piping, large diameter (piping)

Potable water piping, large diameter (piping)

Percentage of realizations in which a repair 

class is triggered

Prefabricated steel stairs (no seismic joint)

Gypsum wall partitions

Precast concrete cladding

Heating hot water piping, small diameter (bracing)

Heating hot water piping, small diameter (piping)

Sanitary waste piping (bracing)

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 30. Graph showing the 

percentage of realizations in which a 

building component type in building 

S-SF-B-20 (20-story steel-frame office 

building in San Francisco, California; 

baseline orientation) incurs damage from 

the hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake 

scenario. Damaged components 

are assigned to a given REDi repair 

class (Almufti and Willford, 2013)—

reoccupancy, functional recovery, or full 

recovery. HVAC, heating, ventilation, air 

conditioning.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building S-SF-B-20 is 9.7 

percent of the total building replacement value, or $5.1 million. 

The 90th-percentile total repair cost is 9.5 percent of the total 

building replacement value, or $6.6 million. For this study, the 

total building replacement value is defined as the hard costs only 

Table 21. Realized median and 90th-percentile repair time and total downtime for building S-SF-B-20 (20-story 

steel-frame office building in San Francisco, California; baseline orientation) due to the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 20 29 35

Median total downtime 189 242 243

90th-percentile repair time 39 145 159

90th-percentile downtime 316 364 364

required to replace the building, based on a construction cost 

estimate including at minimum all structural and nonstructural 

components plus the value of damageable building contents if 

they are known. Figure 31 shows the contribution of building 

component groups to realized median total repair cost. Table 21 

shows realized median and 90th-percentile repair time and total 

downtime, and table 22 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 323

Figure 31. Pie chart showing the percentage contribution of building component groups to realized median total repair 

cost for building S-SF-B-20 (20-story steel-frame office building in San Francisco, California; baseline orientation) due to the 

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Table 22. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building S-SF-B-20 (20-story steelframe office building in San Francisco, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 101 239 None.

Engineer mobilization 0 0 The median engineer mobilization is zero because 

no structural components are damaged.

Contractor mobilization 229 347 None.

Permitting 0 0 No structural damage.

Precast concrete cladding

Gypsum wall partitions

Other

Pendant lighting

Traction elevator

EXPLANATION

Building component group

73

3

3

10

11
324 The HayWired Earthquake Scenario—Engineering Implications

S-SF-R-20 Description

This appendix summarizes the results of interest for the 

HayWired mainshock from the structural analysis and loss 

assessment of building S-SF-R-20—a 20-story steel-frame office 

building in San Francisco with the rotated orientation shown in 

figure 7. Results are shown in figures 32–34.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended by FEMA P-58 (Applied Technology Council, 2012) 

for buildings with nonlinear response history analysis results 

available. This algorithm was developed by Yang and others 

(2009).

Building S-SF-R-20 sees low-moderate acceleration 

demands, with peak nondirectional median floor acceleration 

for the whole building at 0.68 g, slightly higher than the 

40-story San Francisco building. Peak median interstory 

drift ratio for the whole building is 0.60 percent and the peak 

residual interstory drift ratio is 0.0075 percent. All columns 

Appendix 5. S-SF-R-20—20-Story Steel-Frame Building in San Francisco 

(Rotated Orientation)

Figure 32. Graphs showing realized peak interstory 

drift ratio demands in building 

S-SF-R-20 (20-story steel-frame 

office building in San Francisco, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear response-history analysis. 

Due to the explicit modeling 

of the substructure, level 2 is 

the ground floor. Direction 1 

is east-west and direction 2 is 

north-south.

and beams remain elastic for this building. All column splices 

remain elastic.

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed using 

the probabilistic approach outlined in the Federal Emergency 

Management Agency’s (FEMA) P-58 document (Applied 

Technology Council, 2012). The likely costs to repair and (or) 

replace damaged components are calculated based solely on 

FEMA P-58, whereas repair time and downtime are estimated 

using the FEMA P-58 based methodology outlined REDi (Almufti 

and Willford, 2013).

Damaged Components

The probability that a component type in building S-SF-R-20 

incurs damage that hinders either reoccupancy, functionality, or 

full recovery was examined in the realizations. The results are 

shown in figure 35.

0 0.002 0.004 0.006 0.008 0.01

0

5

10

15

20

25

Floor Level

Direction 1

0 0.002 0.004 0.006 0.008 0.01

Story Drift Ratio

0

5

10

15

20

25 Direction 2

0 0.002 0.004 0.006 0.008 0.01

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 .002 .004 .006 .008 .01 0 .002 .004 .006 .008 .01 0 .002 .004 .006 .008 .01

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 325

Figure 33. Graphs showing 

realized peak residual interstory 

drift ratio demands in building 

S-SF-R-20 (20-story steel-frame 

office building in San Francisco, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. 

Due to the explicit modeling 

of the substructure, level 2 is 

the ground floor. Direction 1 

is east-west and direction 2 is 

north-south.

Figure 34. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration due to gravity, g) in building 

S-SF-R-20 (20-story steel-frame 

office building in San Francisco, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due to 

the explicit modeling of the substructure, level 2 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

1 1.5×10-4 0 0.5 1 1.5×10-4 0 0.5 1 1.5×10-4 0 0.5

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

0 0.5 1 1.5

0

5

10

15

20

25

Floor Level

Direction 1

0 0.5 1 1.5

Acceleration [g]

0

5

10

15

20

25 Direction 2

0 0.5 1 1.5

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 0.5 1 1.5 0 0.5 1 1.5 0 0.5 1 1.5

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
326 The HayWired Earthquake Scenario—Engineering Implications Building component

Air handling unit

Cooling tower

Chiller

HVAC drops/diffusers

HVAC ducting

HVAC ducting

Traction elevator

Pendant lighting

Suspended ceilings

Raised access floors

Wall coverings

Fire sprinkler drops

Motor control center

Fire sprinkler water piping (piping)

Heating hot water piping, large diameter (piping)

Potable water piping, large diameter (piping)

Percentage of realizations in which a repair 

class is triggered

Prefabricated steel stairs (no seismic joint)

Gypsum wall partitions

Precast concrete cladding

Heating hot water piping, small diameter (bracing)

Heating hot water piping, small diameter (piping)

Sanitary waste piping (piping)

Sanitary waste piping (bracing)

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost in building S-SF-R-20 is 8.2 

percent of the total building replacement value, or $5.7 million. 

The 90th-percentile total repair cost is 10.4 percent of the total 

building replacement value, or $7.3 million. For this study, the 

total building replacement value is defined as the hard costs only 

Figure 35. Graph showing the 

percentage of realizations in which a 

building component type in building 

S-SF-R-20 (20-story steel-frame 

office building in San Francisco, 

California; rotated orientation) 

incurs damage from the hypothetical 

moment-magnitude-7.0 mainshock of 

the HayWired earthquake scenario. 

Damaged components are assigned 

to a given REDi repair class (Almufti 

and Willford, 2013)—reoccupancy, 

functional recovery, or full recovery. 

HVAC, heating, ventilation, air 

conditioning.

Table 23. Realized median and 90th-percentile repair time and total downtime for building S-SF-R-20 (20-story 

steel-frame office building in San Francisco, California; rotated orientation) due to the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 23 33 41

Median total downtime 186 251 253

90th-percentile repair time 47 189 199

90th-percentile downtime 304 361 363

required to replace the building, based on a construction cost 

estimate including at minimum all structural and nonstructural 

components plus the value of damageable building contents if 

they are known. Figure 36 shows the contribution of building 

component groups to realized median total repair cost. Table 23 

shows realized median and 90th-percentile repair time and total 

downtime, and table 24 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 327

Figure 36. Pie chart showing the percentage contribution of building component groups to realized median 

total repair cost for building S-SF-R-20 (20-story steel-frame office building in San Francisco, California; rotated 

orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Table 24. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building S-SF-R-20 (20-story 

steel-frame office building in San Francisco, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 mainshock 

of the HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 93 229 None.

Engineer mobilization 0 0 The median engineer mobilization is zero because no 

structural components are damaged.

Contractor mobilization 237 344 None.

Permitting 0 0 No structural damage.

Precast concrete cladding

Gypsum wall partitions

Other

Pendant lighting

Traction elevator

EXPLANATION

Building component group

69

3

4

11

13
328 The HayWired Earthquake Scenario—Engineering Implications

S-OK-B-20 Description

This appendix summarizes the results of interest for the 

HayWired mainshock from the structural analysis and loss 

assessment of building S-OK-B-20—a 20-story steel-frame office 

building in Oakland with the baseline orientation shown in figure 7.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended 

by FEMA P-58 (Applied Technology Council, 2012) for buildings 

with nonlinear response history analysis results available. This 

algorithm was developed by Yang and others (2009).

Building S-OK-B-20 sees moderate acceleration 

demands, with peak nondirectional median floor acceleration 

for the whole building at 1.04 g, significantly higher than the 

San Francisco buildings. Peak median interstory drift ratio 

for the whole building is 1.5 percent and the peak residual 

interstory drift ratio is 0.1 percent. As shown in figure 37, 

the peak residual drift occurs in the building’s long direction 

(north-south) around level 10. This is because, as shown in 

figure 38, the beams in the long direction see yielding and 

fracturing around the mid-height of the building. It should be 

noted that beam yielding doesn’t necessarily mean repair is 

Appendix 6. S-OK-B-20—20-Story Steel-Frame Building in Oakland 

(Baseline Orientation)

required. Conversely, the columns all remain elastic during 

the analysis. All column splices remain elastic. Realized peak 

interstory drift ratio demands are shown in figure 39, and 

realized peak floor-acceleration demands for the building are 

shown in figure 40.

Loss Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed 

using the probabilistic approach outlined in the Federal 

Emergency Management Agency’s (FEMA) P-58 document 

(Applied Technology Council, 2012). The likely costs to repair 

and (or) replace damaged components are calculated based 

solely on FEMA P-58, whereas repair time and downtime are 

estimated using the FEMA P-58 based methodology outlined 

REDi (Almufti and Willford, 2013).

Damaged Components

The probability that a component type in building 

S-OK-B-20 incurs damage that hinders either reoccupancy, 

functionality, or full recovery was examined in the 

realizations. The results are shown in figure 41.

Figure 37. Graphs showing realized 

peak residual interstory drift ratio 

demands in building S-OK-B-20 

(20-story steel-frame office building 

in Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock of 

the HayWired earthquake scenario. 

The 50th percentile is taken directly 

from the nonlinear response-history 

analysis. Due to the explicit modeling 

of the substructure, level 2 is the 

ground floor. Direction 1 is east-west 

and direction 2 is north-south.

0 .005 .01 .015 .02 .025 .03 0 .005 .01 .015 .02 .025 .03 0 .005 .01 .015 .02 .025 .03

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 329

Figure 39. Graphs showing 

realized peak interstory drift ratio 

demands in building S-OK-B-20 (20-

story steel-frame office building 

in Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 2 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

Elastic

EXPLANATION

A B

Yielded

Fractured

1 2×10-3 0 0.5 1.5 1 2×10-3 0 0.5 1.5 1 2×10-3 0 0.5 1.5

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

Figure 38. Diagrams showing 

beam performance for sample 

(A) long and (B) short elevations 

of building S-OK-B-20 (20-story 

steel-frame office building in 

Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 2 is the ground floor. 
330 The HayWired Earthquake Scenario—Engineering Implications

Figure 40. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration 

due to gravity, g) in building 

S-OK-B-20 (20-story steel-frame 

office building in Oakland, 

California; baseline orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 2 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

0 0.5 1 1.5 2

0

5

10

15

20

25

Floor Level

Direction 1

0 0.5 1 1.5 2

Acceleration [g]

0

5

10

15

20

25 Direction 2

0 0.5 1 1.5 2

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 0.5 1 1.5 2 0 0.5 1 1.5 2 0 0.5 1 1.5 2

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90

Building component

Switchgear 100–350 A

Motor control center

Air handling unit Variable air volume boxes

Cooling tower Chiller

HVAC drops/diffusers

HVAC ducting

HVAC ducting

Traction elevator

Traction elevator

Pendant lighting Suspended ceilings

Raised access floors

Wall coverings

Fire sprinkler drops

Fire sprinkler water piping (piping)

Heating hot water piping, large diameter (piping)

Potable water piping, large diameter (piping)

Pre-Northridge beam-column joints

Percentage of realizations in which a repair 

class is triggered

Pre-Northridge beam-column joints

Prefabricated steel stairs (no seismic joint) Gypsum wall partitions

Welded column splices

Precast concrete cladding

Heating hot water piping, small diameter (bracing)

Heating hot water piping, small diameter (piping)

Sanitary waste piping (bracing)

Sanitary waste piping (piping)

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery Figure 41. Graph showing the 

percentage of realizations in 

which a building component type 

in building S-OK-B-20 (20-story 

steel-frame office building in 

Oakland, California; baseline 

orientation) incurs damage 

from the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

Damaged components are 

assigned to a given REDi repair 

class (Almufti and Willford, 

2013)—reoccupancy, functional 

recovery, or full recovery. 

HVAC, heating, ventilation, air 

conditioning; A, ampere.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 331

Precast concrete cladding

Gypsum wall partitions

Other

Chiller

Pendant lighting

Traction elevator

Suspended ceilings

EXPLANATION

Building component group

58

4

2

3

8

16

9

Figure 42. Pie chart showing the percentage contribution 

of building component groups to realized median total repair 

cost for building S-OK-B-20 (20-story steel-frame office 

building in Oakland, California; baseline orientation) due to 

the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building S-OK-B-20 is 17.5 

percent of the total building replacement value, or $12.2 million. 

The 90th-percentile total repair cost is 20.7 percent of the total 

building replacement value, or $14.4 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based on a construction cost 

estimate including at minimum all structural and nonstructural 

components plus the value of damageable building contents if 

they are known. Figure 42 shows the contribution of building 

component groups to realized median total repair cost. Table 25 

shows realized median and 90th-percentile repair time and total 

downtime, and table 26 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 54 92 100

Median total downtime 231 273 277

90th-percentile repair time 116 272 274

90th-percentile downtime 343 385 388

Table 26. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building S-OK-B-20 (20-story 

steel-frame office building in Oakland, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 45 189 None.

Engineer mobilization 46 123 Engineer mobilization is triggered by structural damage.

Contractor mobilization 254 363 None.

Permitting 33 74 Permitting is triggered by structural damage.

Table 25. Realized median and 90th-percentile repair time and total downtime for building S-OK-B-20 (20-story steel-frame office 

building in Oakland, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired 

earthquake scenario.

[REDi (Almufti and Willford, 2013)]
332 The HayWired Earthquake Scenario—Engineering Implications

0 0.005 0.01 0.015 0.02

0

5

10

15

20

25

Floor Level

Direction 1

0 0.005 0.01 0.015 0.02

Story Drift Ratio

0

5

10

15

20

25 Direction 2

0 0.005 0.01 0.015 0.02

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 .005 .01 .015 .02 0 .005 .01 .015 .02 0 .005 .01 .015 .02

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90

S-OK-R-20 Description

This appendix summarizes the results of interest for the 

HayWired mainshock from the structural analysis and loss 

assessment of building S-OK-R-20—a 20-story steel-frame 

office building in Oakland with the rotated orientation shown 

in figure 7. Results are shown in figures 43–45.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended 

by FEMA P-58 (Applied Technology Council, 2012) for buildings 

with nonlinear response history analysis results available. This 

algorithm was developed by Yang and others (2009).

Building S-OK-R-20 sees moderate acceleration 

demands, with peak nondirectional median floor acceleration 

for the whole building at 1.06 g, significantly higher than the 

San Francisco buildings. Peak median interstory drift ratio 

for the whole building is 1.0 percent, and the peak residual 

interstory drift ratio is 0.007 percent. Roughly a quarter of 

the beams either yield or fracture on average. Conversely, the 

Appendix 7. S-OK-R-20—20-Story Steel-Frame Building in Oakland 

(Rotated Orientation)

Figure 43. Graphs showing 

realized peak interstory 

drift ratio demands in 

building S-OK-R-20 (20-story 

steel-frame office building 

in Oakland, California; 

rotated orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 2 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

columns all remain elastic during the analysis. All column 

splices remain elastic.

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed 

using the probabilistic approach outlined in the Federal 

Emergency Management Agency’s (FEMA) P-58 document 

(Applied Technology Council, 2012). The likely costs to repair 

and (or) replace damaged components are calculated based 

solely on FEMA P-58, whereas repair time and downtime are 

estimated using the FEMA P-58 based methodology outlined 

REDi (Almufti and Willford, 2013).

Damaged Components

The probability that a component type in building 

S-OK-R-20 incurs damage that hinders either reoccupancy, 

functionality, or full recovery was examined in the realizations. 

The results are shown in figure 46.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 333

Figure 44. Graphs showing 

realized peak residual interstory 

drift ratio demands in building 

S-OK-R-20 (20-story steel-frame 

office building in Oakland, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. 

Due to the explicit modeling 

of the substructure, level 2 is 

the ground floor. Direction 1 

is east-west and direction 2 is 

north-south.

Figure 45. Graphs showing 

realized peak floor-acceleration 

demands (relative to 

acceleration due to gravity, g) 

in building S-OK-R-20 (20-story 

steel-frame office building in 

Oakland, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 2 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 0.5 1 1.5

10-4

0

5

10

15

20

25

Floor Level

Direction 1

0 0.5 1 1.5

Max Residual Drift 10-4

0

5

10

15

20

25 Direction 2

0 0.5 1 1.5

10-4

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

1 1.5×10-4 0 0.5 1 1.5×10-4 0 0.5 1 1.5×10-4 0 0.5

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

0 0.5 1 1.5 2

0

5

10

15

20

25

Floor Level

Direction 1

0 0.5 1 1.5 2

Acceleration [g]

0

5

10

15

20

25 Direction 2

0 0.5 1 1.5 2

0

5

10

15

20

25 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 0.5 1 1.5 2 0 0.5 1 1.5 2 0 0.5 1 1.5 2

0

5

10

15

20

25

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
334 The HayWired Earthquake Scenario—Engineering Implications Building component

Switchgear 100–350 A

Motor control center

Air handling unit Variable air volume boxes

Cooling tower

Chiller

HVAC drops/diffusers

HVAC ducting

HVAC ducting

Traction elevator

Pendant lighting

Suspended ceilings

Raised access floors

Wall coverings

Fire sprinkler drops Fire sprinkler water piping (piping)

Heating hot water piping, large diameter (piping)

Potable water piping, large diameter (piping)

Pre-Northridge beam-column joints

Percentage of realizations in which a repair 

class is triggered

Pre-Northridge beam-column joints

Prefabricated steel stairs (no seismic joint) Gypsum wall partitions

Welded column splices

Precast concrete cladding

Heating hot water piping, small diameter (bracing)

Heating hot water piping, small diameter (piping)

Sanitary waste piping (bracing)

Sanitary waste piping (piping)

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery Figure 46. Graph showing the 

percentage of realizations in which a 

building component type in building 

S-OK-R-20 (20-story steel-frame 

office building in Oakland, California; 

rotated orientation) incurs damage 

from the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

Damaged components are assigned 

to a given REDi repair class (Almufti 

and Willford, 2013)—reoccupancy, 

functional recovery, or full recovery. 

HVAC, heating, ventilation, air 

conditioning; A, ampere.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building S-OK-R-20 is 16.5 

percent of the total building replacement value, or $11.5 million. 

The 90th-percentile total repair cost is 18.7 percent of the total 

building replacement value, or $13.1 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based on a construction cost 

estimate including at minimum all structural and nonstructural 

components plus the value of damageable building contents if 

they are known. Figure 47 shows the contribution of building 

component groups to realized median total repair cost. Table 27 

shows realized median and 90th-percentile repair time and total 

downtime, and table 28 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.

Table 27. Realized median and 90th-percentile repair time and total downtime for building S-OK-R-20 (20-story steel-frame office 

building in Oakland, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired 

earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 54 82 91

Median total downtime 224 269 274

90th-percentile repair time 97 237 241

90th-percentile downtime 333 371 378
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 335

Figure 47. Pie chart showing the percentage contribution of building component groups to realized median total 

repair cost for building S-OK-R-20 (20-story steel-frame office building in Oakland, California; rotated orientation) 

due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Table 28. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building S-OK-R-20 (20-story 

steel-frame office building in Oakland, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 41 175 None.

Engineer mobilization 0 101 Engineer mobilization is triggered by structural damage.

Contractor mobilization 249 348 None.

Permitting 0 67 Permitting is triggered by structural damage.

54

4

6

3

8

15

10

Precast concrete cladding

Gypsum wall partitions

Other

Chiller

Suspended ceilings

Pendant lighting

Traction elevator

EXPLANATION

Building component group
336 The HayWired Earthquake Scenario—Engineering Implications

C-SF-B-46 Description

This appendix summarizes the results of interest for the HayWired mainshock from the structural analysis and loss assessment 

of building C-SF-B-46—a 42-story reinforced-concrete residential 

building in San Francisco with the baseline orientation shown in 

figure 10. Results are shown in figures 48–53.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended by FEMA P-58 (Applied Technology Council, 2012) 

for buildings with nonlinear response history analysis results 

available. This algorithm was developed by Yang and others 

(2009).

Building C-SF-B-46 sees low demands, with a peak 

interstory drift (IDR) for whole building of just 0.4 percent. Peak 

floor acceleration is 0.9 g. Peak coupling beam rotation is 0.006 

radian (rad), far below 0.05–0.06 rad, the point at which significant 

shear strength degradation occurs. The core walls see no crushing. 

The core-wall rebar experiences little yielding, all occurring at the 

base of the core walls. 

Appendix 8. C-SF-B-46—42-Story Reinforced-Concrete Building in San 

Francisco (Baseline Orientation)

The damage in partitions and slab-column joints is better 

correlated with racking drift than IDR. Therefore, racking drift was 

used as the EDP for these components. Racking drift is different 

from IDR in that it excludes rigid body rotation and includes 

vertical racking resulting from the relative vertical movement 

between the core walls and the perimeter columns.

There are a few interesting things to note about the demands. 

First, figure 51 clearly shows the plastic hinge zone in the core 

wall at the ground floor level, as evidenced by the large spike in 

the wall rotation. However, this spike is modest, in an absolute 

sense, at about 0.00115 rad median. This compares favorably 

with the acceptable plastic hinge rotation per ASCE 41–13 

(American Society of Civil Engineers, 2014) of 0.001–0.002 rad 

for unconfined walls. Second, figure 53 shows that the coupling 

beam rotations are fairly constant up the height of the building with 

the exception of a dip in rotations at level 24 (superstructure floor 

20), due to a reduction in the core wall reinforcement ratio at level 

26 by about half. This reduction in core wall reinforcement is also 

evidenced by the small spikes in core-wall rotation in figure 52.

Coupling beam rotation demands were enveloped for all beams 

on each floor and thus, beam directionality was not considered. 

Despite this conservatism, beam rotations were very low and had 

virtually no impact on the loss and downtime assessment.

Figure 48. Graphs showing 

realized peak interstory drift ratio 

demands in building C-SF-B-46 

(42-story reinforced-concrete 

residential building in San 

Francisco, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 2 4 6 8×10-3 0 2 4 6 8×10-3 0 2 4 6 8×10-3 0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 337

Figure 49. Graphs showing 

realized peak residual 

interstory drift ratio demands 

in building C-SF-B-46 (42-

story reinforced-concrete 

residential building in 

San Francisco, California; 

baseline orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from 

the nonlinear responsehistory analysis. Due to the 

explicit modeling of the 

substructure, level 5 is the 

ground floor. Direction 1 is 

east-west and direction 2 is 

north-south.

Figure 50. Graphs showing 

realized peak racking drift ratio 

demands in building C-SF-B-46 

(42-story reinforced-concrete 

residential building in San 

Francisco, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

1 2 2.5×10-4 0 0.5 1.5

0

1 2 2.5×10-4 0 0.5 1.5 1 2 2.5×10-4 0 0.5 1.5

5

10

20

15

30

25

40

35

50

45

EXPLANATION

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

Percentile

10

25

50

75

90

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Racking drift

Direction 1

Percentile

10

25

50

75

90
338 The HayWired Earthquake Scenario—Engineering Implications

Figure 52. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration 

due to gravity, g) in building 

C-SF-B-46 (42-story reinforcedconcrete residential building in 

San Francisco, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 5 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

0 2 4 6 8

10-4

0

5

10

15

20

25

30

35

40

45

50

Floor Level

Direction 1

0 2 4 6 8

Effective Drift 10-4

0

5

10

15

20

25

30

35

40

45

50 Direction 2

0 2 4 6 8

10-4

0

5

10

15

20

25

30

35

40

45

50 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 2 4 6 8×10-4 0 2 4 6 8×10-4 0 2 4 6 8×10-4 0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Effective drift

Direction 1

Percentile

10

25

50

75

90

Figure 51. Graphs showing 

realized peak wall-rotation 

demands (radians) in building 

C-SF-B-46 (42-story reinforcedconcrete residential building in 

San Francisco, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 5 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

0 0.5 1 1.5 0 0.5 1 1.5 0 0.5 1 1.5

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 339

0 0.005 0.01 0.015

0

5

10

15

20

25

30

35

40

45

50

Floor Level

Direction 1

0 0.005 0.01 0.015

Link Beam Chord Rotation

0

5

10

15

20

25

30

35

40

45

50 Direction 2

0 0.005 0.01 0.015

0

5

10

15

20

25

30

35

40

45

50 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Link beam chord rotation

Direction 1

Percentile

10

25

50

75

90

Figure 53. Graphs showing 

realized peak coupling-beam 

rotation demands (radians) in 

building C-SF-B-46 (42-story 

reinforced-concrete residential 

building in San Francisco, 

California; baseline orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 5 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed 

using the probabilistic approach outlined in the Federal 

Emergency Management Agency’s (FEMA) P-58 document 

(Applied Technology Council, 2012). The likely costs to repair 

and (or) replace damaged components are calculated based 

solely on FEMA P-58, whereas repair time and downtime are 

estimated using the FEMA P-58 based methodology outlined 

REDi (Almufti and Willford, 2013).

Damaged Components

The probability that a component type in building C-SF-B-46 

incurs damage that hinders either reoccupancy, functionality, or 

full recovery was examined in the realizations. The results are 

shown in figure 54.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building C-SF-B-46 is 3.1 

percent of the total building replacement value, or $5.5 million. 

The 90th-percentile total repair cost is 3.7 percent of the total 

building replacement value, or $6.5 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based off a construction cost 

estimate, including at minimum all structural and nonstructural 

components plus the value of damageable building contents 

if they are known. The total repair cost is dominated by wall 

partitions because there are a large number of partitions in a 

residential building. Figure 55 shows the contribution of building 

component groups to realized median total repair cost. Table 29 

shows realized median and 90th-percentile repair time and total 

downtime, and table 30 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.
340 The HayWired Earthquake Scenario—Engineering Implications

Table 29. Realized median and 90th-percentile repair time and total downtime for building C-SF-B-46 (42-story reinforced-concrete 

residential building in San Francisco, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 3 15 109

Median total downtime 126 224 323

90th-percentile repair time 5 27 155

90th-percentile downtime 194 328 434 Building component

AHU 10,000–25,000 CFM

AHU 5,000– <10,000 CFM

HVAC fan

HVAC drops without ceilings

HVAC Sm ducting

Chilled water piping

Cooling tower

Chiller

HVAC drops in suspended ceilings

Large diameter hot water piping bracing

Small diameter hot water piping

Cold water piping bracing

Pendant lighting

Wall partition with tile

Wall partition with wallpaper

Elevator

Variable air volume box

Percentage of realizations in which a repair 

class is triggered

Stair

Wall partition

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 54. Graph showing the 

percentage of realizations in 

which a building component type 

in building C-SF-B-46 (42-story 

reinforced-concrete residential 

building in San Francisco, California; 

baseline orientation) incurs damage 

from the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

Damaged components are 

assigned to a given REDi repair 

class (Almufti and Willford, 2013)—

reoccupancy, functional recovery, 

or full recovery. HVAC, heating, 

ventilation, air conditioning; AHU, 

air handling unit; CFM, cubic feet 

per minute.
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 341

Figure 55. Pie chart showing the percentage contribution of building component groups to realized median total 

repair cost for building C-SF-B-46 (42-story reinforced-concrete residential building in San Francisco, California; 

baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Table 30. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building C-SF-B-46 (42-

story reinforced-concrete residential building in San Francisco, California; baseline orientation) due to the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 0 0 Total repair cost projections are <5 percent of the total 

replacement cost for median and 90th percentile, so 

it is assumed that the owner readily has funds available for these repairs.

Engineer mobilization 0 0 No structural damage.

Contractor mobilization 210 316 None.

Permitting 0 0 No structural damage.

61

20

7

2

10

Wall partition with tile

Wall partition

Other

Elevator

Wall partition with wallpaper

EXPLANATION

Building component group
342 The HayWired Earthquake Scenario—Engineering Implications

C-SF-R-46 Description

This appendix summarizes the results of interest for the HayWired mainshock from the structural analysis and loss assessment 

of building C-SF-R-46—a 42-story reinforced-concrete residential 

building in San Francisco with the rotated orientation shown in 

figure 10. Results are shown in figures 56–61.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended 

by FEMA P-58 (Applied Technology Council, 2012) for buildings 

with nonlinear response history analysis results available. This 

algorithm was developed by Yang and others (2009).

Building C-SF-R-46 sees low demands, with a peak 

interstory drift (IDR) for whole building of just 0.7 percent. 

Peak floor acceleration is 1.09 g. Peak coupling beam rotation 

is 0.009 rad, far below 0.05–0.06 rad, the point at which 

significant shear strength degradation occurs. The core walls see 

no crushing. The core-wall rebar experiences little yielding, all 

occurring at the base of the core walls.

Appendix 9. C-SF-R-46—42-Story Reinforced-Concrete Building in San 

Francisco (Rotated Orientation)

The damage in partitions and slab-column joints is better 

correlated with racking drift than IDR. Therefore, racking drift was 

used as the EDP for these components. Racking drift is different 

from IDR in that it excludes rigid body rotation and includes 

vertical racking resulting from the relative vertical movement 

between the core walls and the perimeter columns.

There are a few interesting things to note about the demands. 

First, figure 59 clearly shows the plastic hinge zone in the core 

wall at the ground floor level, as evidenced by the large spike in 

the wall rotation. However, this spike is modest, in an absolute 

sense, at about 0.00115 rad median. This compares favorably with 

the acceptable plastic hinge rotation per ASCE 41–13 (American 

Society of Civil Engineers, 2014) of 0.001–0.002 rad for 

unconfined walls. Second, figure 61 shows that the coupling beam 

rotations are fairly constant up the height of the building with the 

exception of a dip in rotations at level 17 (superstructure floor 13), 

where the core wall and coupling beam width abruptly changes 

from 32 to 24 in.

Coupling beam rotation demands were enveloped for 

all beams on each floor and thus, beam directionality was not 

considered. Despite this conservatism, beam rotations were very 

low and had virtually no impact on the loss assessment.

Figure 56. Graphs showing 

realized peak interstory drift 

ratio demands in building 

C-SF-R-46 (42-story reinforcedconcrete residential building 

in San Francisco, California; 

rotated orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. 

Due to the explicit modeling 

of the substructure, level 5 is 

the ground floor. Direction 1 

is east-west and direction 2 is 

north-south.

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 343

Figure 57. Graphs showing 

realized peak residual interstory 

drift ratio demands in building 

C-SF-R-46 (42-story reinforcedconcrete residential building in 

San Francisco, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

Figure 58. Graphs showing 

realized peak racking drift ratio 

demands in building C-SF-R-46 

(42-story reinforced-concrete 

residential building in San 

Francisco, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

EXPLANATION

Percentile

10

25

50

75

90

1 2 3×10-4 0 1 2 3×10-4 0 1 2 3×10-4 0

5

10

20

15

30

25

40

35

50

45

Nondirectional

Floor level

Direction 2

Maximum residual drift

Direction 1

0 .005 .01 .015 .02 0 .005 .01 .015 .02 0 .005 .01 .015 .02

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Racking drift

Direction 1

Percentile

10

25

50

75

90
344 The HayWired Earthquake Scenario—Engineering Implications

Figure 59. Graphs showing 

realized peak wall-rotation 

demands (radians) in building 

C-SF-R-46 (42-story reinforcedconcrete residential building in 

San Francisco, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 5 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

Figure 60. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration 

due to gravity, g) in building 

C-SF-R-46 (42-story reinforcedconcrete residential building in 

San Francisco, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. The 50th percentile is 

taken directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 5 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

0 0.5 1 1.5 2×10-3 0 0.5 1 1.5 2×10-3 0 0.5 1 1.5 2×10-3 0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Effective drift

Direction 1

Percentile

10

25

50

75

90

0 0.5 1 1.5 2 0 0.5 1 1.5 2 0 0.5 1 1.5 2

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 345

Figure 61. Graphs showing 

realized peak coupling-beam 

rotation demands (radians) in 

building C-SF-R-46 (42-story 

reinforced-concrete residential 

building in San Francisco, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. Due 

to the explicit modeling of the 

substructure, level 5 is the ground 

floor. Direction 1 is east-west and 

direction 2 is north-south.

0 0.005 0.01 0.015

0

5

10

15

20

25

30

35

40

45

50

Floor Level

Direction 1

0 0.005 0.01 0.015

Link Beam Chord Rotation

0

5

10

15

20

25

30

35

40

45

50 Direction 2

0 0.005 0.01 0.015

0

5

10

15

20

25

30

35

40

45

50 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Link beam chord rotation

Direction 1

Percentile

10

25

50

75

90

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed using 

the probabilistic approach outlined in the Federal Emergency 

Management Agency’s (FEMA) P-58 document (Applied 

Technology Council, 2012). The likely costs to repair and (or) 

replace damaged components are calculated based solely on 

FEMA P-58, whereas repair time and downtime are estimated 

using the FEMA P-58 based methodology outlined REDi (Almufti 

and Willford, 2013).

Damaged Components

The probability that a component type in building C-SF-R-46 

incurs damage that hinders either reoccupancy, functionality, or 

full recovery was examined in the realizations. The results are 

shown in figure 62.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building C-SF-R-46 is 5.0 

percent of the total building replacement value, or $8.9 million. 

The 90th-percentile total repair cost is 6.1 percent of the total 

building replacement value, or $10.8 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based off a construction cost 

estimate, including at minimum all structural and nonstructural 

components plus the value of damageable building contents 

if they are known. The total repair cost is dominated by wall 

partitions because there are a large number of partitions in a 

residential building. Figure 63 shows the contribution of building 

component groups to realized median total repair cost. Table 31 

shows realized median and 90th-percentile repair time and total 

downtime, and table 32 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.
346 The HayWired Earthquake Scenario—Engineering Implications Building component

AHU 10,000–25,000 CFM

Fire sprinkler piping-OSPHD bracing

Fire sprinkler drop with ceiling

Switchgear 1,200–2,000 A

AHU 5,000– <10,000 CFM

HVAC fan

HVAC drops without ceilings

HVAC small ducting

HVAC in line fan

Chilled water piping bracing Steam piping

Steam piping bracing

Chilled water piping

Cooling tower

Chiller

HVAC drops in suspended ceilings

Large diameter hot water piping bracing Sanitary waste piping bracing

Large diameter hot water piping

Small diameter hot water piping Small diameter hot water piping bracing

Cold water piping bracing

Cold water piping

Pendant lighting

Suspended ceiling

Wall partition with tile Wall partition with wallpaper

Elevator

Variable air volume box

Percentage of realizations in which a repair 

class is triggered

Stair

Coupling beam

Wall partition

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 62. Graph showing the 

percentage of realizations in which a 

building component type in building 

C-SF-R-46 (42-story reinforcedconcrete residential building in 

San Francisco, California; rotated 

orientation) incurs damage from the 

hypothetical moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. Damaged 

components are assigned to a given 

REDi repair class (Almufti and Willford, 

2013)—reoccupancy, functional 

recovery, or full recovery. HVAC, 

heating, ventilation, air conditioning; 

AHU, air handling unit; CFM, cubic 

feet per minute; A, ampere; OSPHD; 

California Office of Statewide Health 

Planning and Development.

Table 31. Realized median and 90th-percentile repair time and total downtime for building C-SF-R-46 (42-story reinforced-concrete 

residential building in San Francisco, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 6 16 183

Median total downtime 136 239 414

90th-percentile repair time 11 26 251

90th-percentile downtime 213 350 539
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 347

Figure 63. Pie chart showing the percentage contribution of building component groups to realized median total 

repair cost for building C-SF-R-46 (42-story reinforced-concrete residential building in San Francisco, California; rotated 

orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

62

17

2

2

10

7

Wall partition with tile

Wall partition

Other

Elevator

Chiller

Wall partition with wallpaper

EXPLANATION

Building component group

Table 32. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building C-SF-R-46 (42-story 

reinforced-concrete residential building in San Francisco, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 59 198 None.

Engineer mobilization 0 0 No structural damage.

Contractor mobilization 223 335 None.

Permitting 0 0 No structural damage.
348 The HayWired Earthquake Scenario—Engineering Implications

C-OK-B-46 Description

This appendix summarizes the results of interest for the HayWired mainshock from the structural analysis and loss assessment 

of building C-OK-B-46—a 42-story reinforced-concrete residential building in Oakland with the baseline orientation shown in 

figure 10. Results are shown in figures 64–69.

Engineering-Demand Parameters

The simulation of EDPs follows the method recommended 

by FEMA P-58 (Applied Technology Council, 2012) for buildings 

with nonlinear response history analysis results available. This 

algorithm was developed by Yang and others (2009).

Building C-OK-B-46 sees low demands, with a peak 

interstory drift (IDR) for whole building of just 0.7 percent. 

Peak floor acceleration is 1.06 g. Peak coupling beam rotation 

is 0.009 rad, far below 0.05–0.06 rad, the point at which 

significant shear strength degradation occurs. The core walls 

see no crushing, with a peak compressive strain of 0.0017. The 

core-wall rebar experiences little yielding, with a maximum 

tensile strain at the base of the core walls of 0.003.

Appendix 10. C-OK-B-46—42-Story Reinforced-Concrete Building in Oakland 

(Baseline Orientation)

The damage in partitions and slab-column joints is better 

correlated with racking drift than IDR. Therefore, racking drift was 

used as the EDP for these components. Racking drift is different 

from IDR in that it excludes rigid body rotation and includes 

vertical racking resulting from the relative vertical movement 

between the core walls and the perimeter columns.

There are a few interesting things to note about the 

demands. First, figure 67 clearly shows the plastic hinge zone in 

the core wall at the ground floor level, as evidenced by the large 

spike in the wall rotation. However, this spike is modest, in an 

absolute sense, at about 0.00105 rad median. This compares 

favorably with the acceptable plastic hinge rotation per ASCE 

41–13 (American Society of Civil Engineers, 2014) of 0.001–

0.002 rad for unconfined walls. Second, figure 69 shows that 

the coupling beam rotations are fairly constant up the height of 

the building. This is expected as the coupling beam sizes are 

the same for almost the full height of the building, with only 

the width changing with the core wall width one-third up the 

building height.

Coupling beam rotation demands were enveloped for all 

beams on each floor and thus, beam directionality was not considered. Despite this conservatism, beam rotations were very low and 

had virtually no impact on the loss assessment.

Figure 64. Graphs showing 

realized peak interstory drift 

ratio demands in building 

C-OK-B-46 (42-story reinforcedconcrete residential building 

in Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 349

Figure 66. Graphs showing 

realized peak racking drift ratio 

demands in building C-OK-B-46 

(42-story reinforced-concrete 

residential building in Oakland, 

California; baseline orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

The 50th percentile is taken 

directly from the nonlinear 

response-history analysis. 

Due to the explicit modeling 

of the substructure, level 5 is 

the ground floor. Direction 1 

is east-west and direction 2 is 

north-south.

0 0.5 1 1.5 2 2.5

10-4

0

5

10

15

20

25

30

35

40

45

50

Floor Level

Direction 1

0 0.5 1 1.5 2 2.5

Max Residual Drift 10-4

0

5

10

15

20

25

30

35

40

45

50 Direction 2

0 0.5 1 1.5 2 2.5

10-4

0

5

10

15

20

25

30

35

40

45

50 Non-directional

10%ile

25%ile

50%ile

75%ile

90%ile

0.5 1 1.5 2 2.5×10-4 0 0.5 1 1.5 2 2.5×10-4 0 0.5 1 1.5 2 2.5×10-4 0

0

5

10

20

15

30

25

40

35

50

45

Floor level

Direction 2 Direction 3

Maximum residual drift

Direction 1

EXPLANATION

Percentile

10

25

75

50

90

Figure 65. Graphs showing 

realized peak residual interstory 

drift ratio demands in building 

C-OK-B-46 (42-story reinforcedconcrete residential building 

in Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Racking drift

Direction 1

Percentile

10

25

50

75

90
350 The HayWired Earthquake Scenario—Engineering Implications

Figure 67. Graphs showing 

realized peak wall-rotation 

demands (radians) in building 

C-OK-B-46 (42-story reinforcedconcrete residential building 

in Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

Figure 68. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration 

due to gravity, g) in building 

C-OK-B-46 (42-story reinforcedconcrete residential building 

in Oakland, California; baseline 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 0.5 1 1.5 2×10-3 0 0.5 1 1.5 2×10-3 0 0.5 1 1.5 2×10-3 0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Effective drift

Direction 1

Percentile

10

25

50

75

90

0 0.5 1 1.5 0 0.5 1 1.5 0 0.5 1 1.5

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 351

Figure 69. Graphs showing 

realized peak coupling-beam 

rotation demands (radians) 

in building C-OK-B-46 (42-

story reinforced concrete 

residential building in 

Oakland, California; 

baseline orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 .005 .01 .015 .02 0 .005 .01 .015 .02 0 .005 .01 .015 .02

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Link beam chord rotation

Direction 1

Percentile

10

25

50

75

90

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed using 

the probabilistic approach outlined in the Federal Emergency 

Management Agency’s (FEMA) P-58 document (Applied 

Technology Council, 2012). The likely costs to repair and (or) 

replace damaged components are calculated based solely on 

FEMA P-58, whereas repair time and downtime are estimated 

using the FEMA P-58 based methodology outlined REDi (Almufti 

and Willford, 2013).

Damaged Components

The probability that a component type in building C-OKB-46 incurs damage that hinders either reoccupancy, functionality, 

or full recovery was examined in the realizations. The results are 

shown in figure 70.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building C-OK-B-46 is 4.9 

percent of the total building replacement value, or $8.6 million. 

The 90th-percentile total repair cost is 5.3 percent of the total 

building replacement value, or $9.4 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based off a construction cost 

estimate, including at minimum all structural and nonstructural 

components plus the value of damageable building contents 

if they are known. The total repair cost is dominated by wall 

partitions because there are a large number of partitions in a 

residential building. Figure 71 shows the contribution of building 

component groups to realized median total repair cost. Table 33 

shows realized median and 90th-percentile repair time and total 

downtime, and table 34 shows realized median and 90th-percentile 

delays due to impeding factors to functional recovery.
352 The HayWired Earthquake Scenario—Engineering Implications Building component

AHU 10,000–25,000 CFM

Fire sprinkler drop with ceiling

Switchgear 1,200–2,000 A

AHU 5,000– <10,000 CFM

HVAC fan

HVAC drops without ceilings

HVAC small ducting

Chilled water piping bracing

Steam piping

Steam piping bracing

Chilled water piping

Cooling tower

Chiller

HVAC drops in suspended ceilings

Large diameter hot water piping bracing

Sanitary waste piping bracing

Large diameter hot water piping

Small diameter hot water piping

Small diameter hot water piping bracing

Cold water piping bracing

Pendant lighting

Suspended ceiling

Wall partition with tile

Wall partition with wallpaper

Elevator

Variable air volume box

Percentage of realizations in which a repair 

class is triggered

Stair

Coupling beam

Wall partition

0 20 40 60 80 100

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 70. Graph showing the 

percentage of realizations in 

which a building component type 

in building C-OK-B-46 (42-story 

reinforced-concrete residential 

building in Oakland, California; 

baseline orientation) incurs 

damage from the hypothetical 

moment-magnitude-7.0 mainshock 

of the HayWired earthquake 

scenario. Damaged components 

are assigned to a given REDi repair 

class (Almufti and Willford, 2013)—

reoccupancy, functional recovery, 

or full recovery. HVAC, heating, 

ventilation, air conditioning; AHU, 

air handling unit; CFM, cubic feet 

per minute; A, ampere.

Table 33. Realized median and 90th-percentile repair time and total downtime for building C-OK-B-46 (42-story reinforced-concrete 

residential building in Oakland, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 5 16 173

Median total downtime 130 233 396

90th-percentile repair time 9 26 242

90th-percentile downtime 198 346 527
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 353

Figure 71. Pie chart showing the percentage contribution of building component groups to realized median total 

repair cost for building C-OK-B-46 (42-story reinforced-concrete residential building in Oakland, California; baseline 

orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

62

17

3

2

10

7

Wall partition with tile

Wall partition

Other

Elevator

Chiller

Wall partition with wallpaper

EXPLANATION

Building component group

Table 34. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building C-OK-B-46 (42-story 

reinforced-concrete residential building in Oakland, California; baseline orientation) due to the hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 10 None.

Financing 0 162 Total repair cost projections are <5 percent of the total 

replacement cost for median, so it is assumed that the 

owner readily has funds available for these repairs.

Engineer mobilization 0 0 No structural damage.

Contractor mobilization 219 329 None.

Permitting 0 0 No structural damage.
354 The HayWired Earthquake Scenario—Engineering Implications

C-OK-R-46 Description

This appendix summarizes the results of interest for the 

HayWired mainshock from the structural analysis and loss assessment of building C-OK-R-46—a 42-story reinforced-concrete 

residential building in Oakland with the rotated orientation shown 

in figure 10. Results are shown in figures 72–77.

Engineering-Demand Parameters

The simulation of engineering-demand parameters follows 

the method recommended by FEMA P-58 (Applied Technology 

Council, 2012) for buildings with nonlinear response history 

analysis results available. This algorithm was developed by 

Yang and others (2009).

Building C-OK-R-46 sees low demands, with a peak 

interstory drift (IDR) for whole building of just 0.7 percent. 

Peak floor acceleration is 1.09 g. Peak coupling beam rotation 

is 0.009 rad, far below 0.05–0.06 rad, the point at which 

significant shear strength degradation occurs. The core walls see 

no crushing. The core-wall rebar experiences little yielding, all 

occurring at the base of the core walls.

Appendix 11. C-OK-R-46—42-Story Reinforced-Concrete Building in Oakland 

(Rotated Orientation)

The damage in partitions and slab-column joints is better 

correlated with racking drift than IDR. Therefore, racking drift was 

used as the EDP for these components. Racking drift is different 

from IDR in that it excludes rigid body rotation and includes 

vertical racking resulting from the relative vertical movement 

between the core walls and the perimeter columns.

There are a few interesting things to note about the 

demands. First, figure 75 clearly shows the plastic hinge zone 

in the core wall at the ground floor level, as evidenced by the 

large spike in the wall rotation. However, this spike is modest, 

in an absolute sense, at about 0.00115 rad median. This 

compares favorably with the acceptable plastic hinge rotation 

per ASCE 41–13 (American Society of Civil Engineers, 

2014) of 0.001–0.002 rad for unconfined walls. Second, 

figure 77 shows that the coupling beam rotations are fairly 

constant up the height of the building with the exception of a 

dip in rotations at level 17 (superstructure floor 13), where the 

core wall and coupling beam width abruptly changes from 32 

to 24 in.

Coupling beam rotation demands were enveloped for 

all beams on each floor and thus, beam directionality was not 

considered. Despite this conservatism, beam rotations were 

very low and had virtually no impact on the loss assessment.

Figure 72. Graphs showing 

realized peak interstory drift 

ratio demands in building 

C-OK-R-46 (42-story reinforcedconcrete residential building 

in Oakland, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Story drift ratio

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 355

Figure 73. Graphs showing 

realized peak residual 

interstory drift ratio demands 

in building C-OK-R-46 (42-

story reinforced-concrete 

residential building in Oakland, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

Figure 74. Graphs showing 

realized peak racking drift ratio 

demands in building C-OK-R-46 

(42-story reinforced-concrete 

residential building in Oakland, 

California; rotated orientation) 

for the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

1 2 3×10-4 0 1 2 3×10-4 0 1 2 3×10-4 0

0

5

10

20

15

30

25

40

35

50

45

Floor level

Direction 2 Direction 3

Maximum residual drift

Direction 1

EXPLANATION

Percentile

10

25

75

50

90

0 2 4 6

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Racking drift

8×10-4 0 2 4 6 8×10-4 0 2 4 6 8×10-4

Direction 1

Percentile

10

25

50

75

90
356 The HayWired Earthquake Scenario—Engineering Implications

Figure 76. Graphs showing 

realized peak floor-acceleration 

demands (relative to acceleration due to gravity, g) in building 

C-OK-R-46 (42-story reinforcedconcrete residential building 

in Oakland, California; rotated 

orientation) for the hypothetical moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

Figure 75. Graphs showing 

realized peak wall-rotation 

demands (radians) in building 

C-OK-R-46 (42-story reinforcedconcrete residential building 

in Oakland, California; rotated 

orientation) for the hypothetical 

moment-magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 50th 

percentile is taken directly from 

the nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 0.5 1 1.5 2×10-3 0 0.5 1 1.5 2×10-3 0 0.5 1 1.5 2×10-3 0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Effective drift

Direction 1

Percentile

10

25

50

75

90

0 0.5 1 1.5 2 0 0.5 1 1.5 2 0 0.5 1 1.5 2

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Acceleration, in g

Direction 1

Percentile

10

25

50

75

90
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 357

Figure 77. Graphs showing 

realized peak coupling-beam 

rotation demands (radians) 

in building C-OK-R-46 (42-

story reinforced-concrete 

residential building in 

Oakland, California; 

rotated orientation) for 

the hypothetical momentmagnitude-7.0 mainshock of 

the HayWired earthquake 

scenario. The 50th percentile 

is taken directly from the 

nonlinear response-history 

analysis. Due to the explicit 

modeling of the substructure, 

level 5 is the ground floor. 

Direction 1 is east-west and 

direction 2 is north-south.

0 .005 .01 .015 0 .005 .01 .015 0 .005 .01 .015

0

5

10

20

30

25

15

40

35

45

50

EXPLANATION

Nondirectional

Floor level

Direction 2

Link beam chord rotation

Direction 1

Percentile

10

25

50

75

90

Loss-Assessment Results

The loss assessment is based on a Monte Carlo simulation 

with 1,000 realizations. The loss assessment was performed using 

the probabilistic approach outlined in the Federal Emergency 

Management Agency’s (FEMA) P-58 document (Applied 

Technology Council, 2012). The likely costs to repair and (or) 

replace damaged components are calculated based solely on 

FEMA P-58, whereas repair time and downtime are estimated 

using the FEMA P-58 based methodology outlined REDi (Almufti 

and Willford, 2013).

Damaged Components

The probability that a component type in building C-OKR-46 incurs damage that hinders either reoccupancy, functionality, or full recovery was examined in the realizations. The 

results are shown in figure 78.

Repair Costs, Repair Time, Downtime, and 

Impending Factors

The median total repair cost for building C-OK-R-46 is 5.0 

percent of the total building replacement value, or $8.9 million. 

The 90th-percentile total repair cost is 6.2 percent of the total 

building replacement value, or $10.8 million. For this study, the 

total building replacement value is defined as the hard costs only 

required to replace the building, based off a construction cost 

estimate, including at minimum all structural and nonstructural 

components plus the value of damageable building contents if they 

are known.

The total repair cost is dominated by wall partitions because 

there are a large number of partitions in a residential building. 

Figure 79 shows the contribution of building component groups to 

realized median total repair cost. Table 35 shows realized median 

and 90th-percentile repair time and total downtime, and table 36 

shows realized median and 90th-percentile delays due to impeding 

factors to functional recovery.
358 The HayWired Earthquake Scenario—Engineering Implications

Percentage of realizations in which a repair 

class is triggered

0 20 40 60 80 100

Building component

AHU 10,000–25,000 CFM

Fire sprinkler drop with ceiling

Switchgear 1,200–2,000 A

AHU 5,000– <10,000 CFM

HVAC fan

HVAC drops without ceilings

HVAC small ducting

Chilled water piping bracing

Steam piping

Steam piping bracing

Chilled water piping

Cooling tower

Chiller

HVAC drops in suspended ceilings

Large diameter hot water piping bracing

Sanitary waste piping bracing

Large diameter hot water piping

Small diameter hot water piping

Small diameter hot water piping bracing

Cold water piping bracing

Pendant lighting

Suspended ceiling

Wall partition with tile

Wall partition with wallpaper

Elevator

Variable air volume box

Stair

Coupling beam

Wall partition

EXPLANATION

REDi repair class

Reoccupancy

Functional

Full recovery

Figure 78. Graph showing the 

percentage of realizations in 

which a building component type 

in building C-OK-R-46 (42-story 

reinforced-concrete residential 

building in Oakland, California; 

rotated orientation) incurs damage 

from the hypothetical momentmagnitude-7.0 mainshock of the 

HayWired earthquake scenario. 

Damaged components are 

assigned to a given REDi repair 

class (Almufti and Willford, 2013)—

reoccupancy, functional recovery, 

or full recovery. HVAC, heating, 

ventilation, air conditioning; AHU, 

air handling unit; CFM, cubic feet 

per minute; A, ampere.

Table 35. Realized median and 90th-percentile repair time and total downtime for building C-OK-R-46 (42-story reinforced-concrete 

residential building in Oakland, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the 

HayWired earthquake scenario.

[REDi (Almufti and Willford, 2013)]

REDi repair class

Repair time Reoccupancy,

in days

Functional recovery,

in days

Full recovery,

in days

Median repair time 6 16 184

Median total downtime 139 245 415

90th-percentile repair time 11 26 251

90th-percentile downtime 222 359 555
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 359

Figure 79. Pie chart showing the percentage contribution of building component groups to realized median total 

repair cost for building C-OK-R-46 (42-story reinforced-concrete residential building in Oakland, California; rotated 

orientation) due to the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

Table 36. Realized median and 90th-percentile delays due to impeding factors to functional recovery for building C-OK-R-46 (42-story 

reinforced-concrete residential building in Oakland, California; rotated orientation) due to the hypothetical moment-magnitude-7.0 

mainshock of the HayWired earthquake scenario.

Impeding factor Median disruption,

in days

90th-percentile disruption,

in days Comment

Inspection 5 11 None.

Financing 59 204 None.

Engineer mobilization 0 0 No structural damage.

Contractor mobilization 229 342 None.

Permitting 0 0 No structural damage.

62

17

2

2

10

7

Wall partition with tile

Wall partition

Other

Elevator

Chiller

Wall partition with wallpaper

EXPLANATION

Building component group
360 The HayWired Earthquake Scenario—Engineering Implications

1900–19101911–19201921–19311931–19401941–19501951–19601961–19701971–19801981–1990

1991–2000

2001–2009

Year range

Number of stories

<20 20–25 26–30 31–35 36–40 41–45 >45

Number of buildings constructed

Number of buildings

50

40

30

20

10

0

40

30

20

10

0

EXPLANATION

A

B Steel moment-resisting frame

Other system

Unknown system

A list of tall buildings (more than 50 m/~160 ft in height) 

in San Francisco was compiled by the Structural Engineers 

Association of Northern California (SEAONC) (see MolinaHutt, 2017, table 37). There are roughly 230 buildings that 

fit this criterion. The building list is ordered by the year of 

construction and the type of lateral load-resisting system. 

Appendix 12. Inventory of Existing Tall-Building Stock in San Francisco

Figure 80. Graphs showing (A) 

number of tall buildings built in San 

Francisco, California, per decade 

between 1900 and 2010 and (B) type 

of lateral load-resisting system for 

tall buildings built in the city between 

1960 and 1990 (Modified from MolinaHutt and others, 2016).

Table 37. List of tall buildings (more than 50 meters/~160 feet in height) in San Francisco, California, compiled by the Structural 

Engineers Association of Northern California (SEAONC) (see Molina-Hutt, 2017).

[MF, moment frame; CBF, concentrically braced frame; EBF, eccentrically braced frame; RC, reinforced concrete; NA, not applicable; --, no data]

List 

number Name Street number Street Height, in meters Stories Year completed

Lateral loadresisting system

1 Ritz-Carlton Club and Residences 690 Market 95 24 1889 --

2 Mills Building 220 Montgomery 52 10 1892 Steel MF

3 Ferry Building 1 Ferry 75 12 1898 --

4 Central Tower 703 Market 91 21 1898 --

5 One Kearny Street Building 1 Kearny 54 12 1902 --

6 The Merchants Exchange 465 California 69 15 1904 --

7 The Westin St. Francis [The Westin St. 

Francis]

335 Powell 60 13 1904 --

8 Whittel Building 166 Geary 60 16 1907 --

9 One Sixth Street 1 6th 57 15 1908 --

10 Maxwell Hotel 386 Geary 51 12 1908 --

11 Humboldt Bank Building 785 Market 85 19 1908 --

12 Adam Grant Building 114 Sansome 64 14 1908 --

13 209 Post Building 209 Post 55 13 1909 --

14 Campton Place Hotel 340 Stockton 53 16 1913 --

15 Hobart Building 582 Market 87 21 1914 --

Figure 80 summarizes this information (Molina-Hutt and 

others, 2017). This list should not be considered as definitive 

because it has not been verified by the San Francisco 

Department of Building Inspection and it was developed 

approximately 7 or 8 years ago. We are not aware of a similar 

database for tall buildings in Oakland. 
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 361

Table 37.—Continued

List 

number Name Street number Street Height, in meters Stories Year completed

Lateral loadresisting system

16 The Chancellor Hotel 433 Powell 59 15 1914 --

17 San Francisco City Hall 1 Carlton B Goodlett 94 4 1915 --

18 115 Sansome Street 115 Sansome 61 13 1915 --

19 Southern Pacific Building 1 Market 65 12 1916 --

20 300 Montgomery 300 Montgomery 65 12 1917 --

21 JH Dollar Building 351 California 73 16 1920 --

22 Commercial Union Assurance Building 315 Montgomery 94 16 1921 --

23 Alexander Building 155 Montgomery 60 15 1921 --

24 225 Bush Street 225 Bush 100 22 1922 Steel MF

25 605 Market Street 605 Market 61 15 1922 --

26 Huntington Hotel 1075 California 52 12 1924 --

27 Pacific Gas & Electric Headquarters 245 Market 78 18 1924 Steel MF

28 Kensington Park Hotel 450 Post 62 14 1924 --

29 Bank of the Orient Building 233 Sansome 53 13 1924 --

30 Pacific Bell Building 140 New Montgomery 133 26 1925 Steel MF

31 Serrano Hotel 405 Taylor 56 16 1925 --

32 The Mark Hopkins Hotel 999 California 93 20 1926 --

33 Omni San Francisco Hotel 500 California 66 15 1926 --

34 Clift Hotel 491 to 499 Geary 64 15 1926 --

35 Marines’ Memorial Club and Hotel 450 Post 66 12 1926 --

36 Crown Tower Apartments 666 Post 55 16 1926 --

37 220 Sansome Street 220 Sansome 66 16 1926 --

38 Hunter-Dulin Building 111 Sutter 94 22 1926 --

39 1090 Chestnut Co-op 1090 Chestnut 53 13 1927 --

40 945 Green Street 945 Green 53 14 1927 --

41 Clay-Jones Apartments 1250 Jones 70 21 1927 --

42 Russ Building 235 Montgomery 133 32 1927 --

43 Medico Dental Building 490 Post 64 16 1928 --

44 Sir Francis Drake Hotel 450 Powell 96 22 1928 --

45 Shell Building 100 Bush 115 29 1929 --

46 McAllister Tower Apartments 100 McAllister 94 28 1929 --

47 Hamilton Apartments 631 O’Farrell 64 18 1929 --

48 450 Sutter 450 Sutter 105 26 1929 --

49 Cathedral Apartments 1201 California 74 19 1930 --

50 Bellaire Tower 1101 Green 77 20 1930 --

51 Pacific National Bank 333 to 341 Montgomery 93 18 1930 --

52 Clarion Hotel Cosmo 761 Post 60 16 1930 --

53 Pacific Coast Stock Exchange Tower 155 Sansome 60 13 1930 --

54 Mills Tower [The Mills Building] 220 Bush 92 22 1931 --

55 Bureau of Citizenship and Immigration 

Building

444 Washington 67 16 1944 --

56 1000 Green Apartments 1000 Green 51 16 1950 --

57 UCSF Medical Center Parnassus 505 Parnassus 77 18 1954 --

58 Medical Sciences Building 513 Parnassus 70 17 1954 --

59 Equitable Life 120 Montgomery 108 25 1955 Steel MF

60 One Bush Plaza 1 Bush 94 20 1959 Dual-system steel 

CBF/EBF; steel MF

61 Industrial Indemnity Building 245 California 70 17 1959 --

62 Philip Burton Federal Building 450 Golden Gate 95 21 1959 --

63 Bethlehem Steel Company HQ 100 California 52 13 1960 --

64 International Building 601 California 107 22 1961 --

65 Green Hill Tower 1070 Green 65 21 1961 --
362 The HayWired Earthquake Scenario—Engineering Implications

List 

number Name Street number Street Height, in meters Stories Year completed

Lateral loadresisting system

66 The Comstock 1333 Jones 55 16 1961 --

67 Fairmont Hotel Tower [The Fairmont San 

Francisco]

950 Mason 99 29 1962 --

68 Grosvenor Suites 899 Pine 70 20 1962 --

69 66 Cleary Court 66 Cleary 61 18 1963 --

70 10 Miller 10 Miller 70 22 1963 --

71 Nob Hill Community Apartments 1170 Sacramento 61 19 1963 --

72 Hartford Building 650 California 142 34 1964 Steel MF

73 One Maritime Plaza 300 Clay 121 27 1964 Dual-system steel 

CBF/EBF; steel MF

74 Carillon Tower 1100 Gough 66 1964 --

75 555 Market Street [Market Center] 555 Market 95 22 1964 --

76 Pacific Heights Towers 2200 Sacramento 65 20 1964 --

77 Macondray House [Golden Gateway 

Center]

405 Davis 80 25 1965 Dual-system RC 

wall/steel MF

78 Golden Gateway Center [Golden Gateway 

Center]

440 Davis 67 22 1965 --

79 Cathedral Hill Tower 1200 Gough 91 27 1965 --

80 The Summit 999 Green 96 32 1965 --

81 Buckelew House [Golden Gateway 

Center]

155 Jackson 80 25 1965 --

82 111 Pine Street 111 Pine 76 19 1965 RC core walls, RC 

gravity system

83 Royal Towers 1750 Taylor 101 29 1965 --

84 Archstone Fox Plaza 1390 Market 108 29 1966 --

85 Beal Bank Building 180 Sansome 76 17 1966 Steel MF

86 Golden Gateway Center [Golden Gateway 

Center]

550 Battery 67 22 1967 --

87 Bechtel Building 50 Beale 100 23 1967 Steel MF

88 Bank of California Building 400 California 95 22 1967 --

89 44 Montgomery 44 Montgomery 172 43 1967 Steel MF

90 Fontana West 1050 North Point 80 18 1967 --

91 Fontana East 1050 North Point 80 18 1967 --

92 Pacific Bell—Pine Street Building 555 Pine 88 16 1967 RC core walls, steel 

gravity system

93 Insurance Center Building 450 Sansome 93 19 1967 --

94 425 California Street 425 California 109 26 1968 Steel MF

95 555 California Street 555 California 237 52 1969 Steel MF

96 One California 1 California 134 32 1969 --

97 The Sequoias 1400 Geary 80 25 1969 --

98 McKesson Plaza 1 Post 161 38 1969 Steel MF

99 Donatello Hotel 501 Post 54 15 1969 --

100 Pacific Gas & Electric Building 77 Beale 150 34 1971 Steel MF

101 One Embarcadero Center [Embarcadero 

Center]

355 Clay 173 45 1971 Steel MF

102 Hilton Financial District 750 Kearny 111 30 1971 --

103 Hilton Hotel San Francisco 333 O’Farrell 150 46 1971 --

104 475 Sansome Street 475 Sansome 86 21 1971 RC core walls, steel 

gravity

105 50 California Street 50 California 148 37 1972 --

106 Transamerica Pyramid [Transamerica 

Center]

600 Montgomery 260 48 1972 Steel MF

107 100 Pine Center 100 Pine 145 33 1972 Steel MF

Table 37.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 363

List 

number Name Street number Street Height, in meters Stories Year completed

Lateral loadresisting system

108 The Westin St. Francis Hotel 335 Powell 120 32 1972 --

109 Grand Hyatt San Francisco 345 Stockton 108 35 1972 --

110 San Francisco Marriott Union Square or 

Crowne Plaza

480 Sutter 95 29 1972 --

111 Holiday Inn 1500 Van Ness 88 26 1972 --

112 Hyatt Regency 5 Embarcadero 85 20 1973 --

113 211 Main Street 211 Main 67 17 1973 Steel MF

114 First Market Tower 525 Market 161 39 1973 Steel MF

115 425 Market Street 425 Market 160 38 1973 Steel MF

116 Twelve Hundred California 1200 California 88 27 1974 --

117 Two Embarcadero Center [Embarcadero 

Center]

255 Clay 126 30 1974 Steel MF

118 221 Main Street 221 Main 64 16 1974 Steel MF

119 California Automobile Association 

Building

100 Van Ness 122 29 1974 Steel MF

120 Chevron Tower [Market Center] 575 Market 175 40 1975 Steel MF

121 Hinode Tower 1615 Sutter 55 15 1975 --

122 Spear Tower [One Market Plaza] 1 Market 172 43 1976 Steel MF

123 Steuart Tower [One Market Plaza] 1 Market 111 27 1976 Steel MF

124 California Building 350 California 99 23 1977 --

125 Three Embarcadero Center[Embarcadero 

Center]

155 Clay 126 31 1977 Steel MF

126 Bank of America Computer Center 1455 Market 88 21 1977 --

127 1275 Market Street 1275 Market 81 17 1977 --

128 Gramercy Towers 1177 California 61 17 1978 --

129 Bechtel Building 45 Fremont 145 34 1978 MF

130 601 Montgomery Street 601 Montgomery 77 20 1978 --

131 Shaklee Terraces 444 Market 164 38 1979 Steel MF

132 333 Market Street 333 Market 144 33 1979 Steel MF

133 595 Market Street 595 Market 125 30 1979 Steel MF

134 Bank of the West 180 Montgomery 98 24 1979 --

135 22 4th Street 22 4th 67 17 1980 --

136 201 California 201 California 72 17 1980 Steel MF

137 Two Transamerica Center 505 Sansome 80 20 1980 Steel moment frame

138 Providian Financial Building 201 Mission 127 30 1981 Dual-system steel 

CBF/EBF; steel MF

139 101 California Street 101 California 183 48 1982 Steel MF

140 Four Embarcadero Center [Embarcadero 

Center]

55 Clay 174 45 1982 Dual-system steel 

CBF/EBF; steel MF

141 Telesis Tower 1 Montgomery 152 38 1982 Steel MF

142 353 Sacramento 353 Sacramento 95 23 1982 --

143 150 Spear 150 Spear 79 18 1982 --

144 1 Ecker Square 1 Ecker 85 18 1983 Steel MF

145 Montgomery Washington Tower 655 Montgomery 91 26 1983 --

146 100 Spear Street 100 Spear 83 22 1983 Steel MF

147 Westin San Francisco Hotel—Market 

Street

50 3rd 114 34 1984 --

148 Renaissance Parc 55 55 Cyril Magnin 107 32 1984 --

149 101 Montgomery [101 Montgomery] 101 Montgomery 123 28 1984 Steel MF

150 United Commercial Bank 555 Montgomery 86 18 1984 --

151 Citicorp Center 1 Sansome 168 43 1984 Steel MF

152 50 Fremont Center 50 Fremont 183 43 1985 Steel MF

153 456 Montgomery Plaza 456 Montgomery 115 26 1985 --

Table 37.—Continued
364 The HayWired Earthquake Scenario—Engineering Implications

List 

number Name Street number Street Height, in meters Stories Year completed

Lateral loadresisting system

154 160 Spear Building 160 Spear 78 19 1985 --

155 Spear Street Terrace 201 Spear 75 18 1985 --

156 333 Bush Street 333 Bush 151 43 1986 Steel MF

157 345 California Center 345 California 212 48 1986 Steel moment frame

158 301 Howard Street 301 Howard 92 23 1986 Steel MF

159 88 Kearny Street 88 Kearny 94 22 1986 --

160 135 Main Street 135 Main 90 23 1986 --

161 123 Mission Street 123 Mission 124 29 1986 --

162 Continental Center 250 Montgomery 69 17 1986 --

163 33 New Montgomery 33 New Montgomery 65 20 1986 Dual-system steel 

CBF/EBF; steel MF

164 90 New Montgomery 90 New Montgomery 65 15 1986 --

165 580 California 580 California 107 23 1987 Dual-system steel 

CBF/EBF; steel MF

166 Hawthorne Plaza 75 Hawthorne 85 20 1987 --

167 Central Plaza 455 Market 97 23 1987 --

168 388 Market 388 Market 94 24 1987 --

169 Hotel Nikko 222 Mason 90 28 1987 --

170 Hilton San Francisco Hotel 333 O’Farrell 106 22 1987 Steel MF

171 JW Marriott Hotel 500 Post 70 20 1987 --

172 Stevenson Place 71 Stevenson 103 28 1987 --

173 Park Hyatt 333 Battery 80 25 1988 --

174 100 First Plaza 100 First 136 27 1988 --

175 505 Montgomery 505 Montgomery 100 24 1988 --

176 49 Stevenson Street 49 Stevenson 61 15 1988 --

177 San Francisco Marriott 55 4th 133 39 1989 Steel MF

178 Embarcadero West [Embarcadero Center] 275 Battery 123 34 1989 Steel MF

179 One Daniel Burnham Court West 1 Daniel Burnham 62 18 1989 Dual-system RC 

wall/RC MF

180 88 Howard Street 88 Howard 95 24 1989 --

181 Fillmore Center I 1755 O’Farrell 64 20 1989 --

182 101 Spear Street 101 Spear 95 24 1989 --

183 Hills Plaza 345 Spear 75 19 1989 --

184 222 Second Street 222 2nd 69 1990 --

185 235 Pine Street 235 Pine 110 26 1990 --

186 634 Sansome Street 634 Sansome 63 16 1990 --

187 600 California Street 600 California 85 22 1992 --

188 Post International 1377 Post 60 14 1993 --

189 PacBell Center 611 Folsom 80 20 1995 Steel MF

190 San Francisco Towers 1661 Pine 53 13 1997 --

191 101 Second Street 101 2nd 108 26 1999 --

192 Second Street Towers 246 2nd 58 17 1999 Dual-system RC 

wall/RC MF

193 W Hotel 181 3rd 96 33 1999 --

194 Avalon Towers North [Avalon Towers by 

the B..]

388 Beale 76 20 1999 Dual-system RC 

wall/RC MF

195 Avalon Towers South [Avalon Towers by 

the Bay]

388 Beale 76 20 1999 Dual-system RC 

wall/RC MF

196 150 California 150 California 101 24 2000 Dual-system steel 

CBF/EBF; steel MF

Table 37.—Continued
Chapter O. Case Studies of Tall-Building Structural Analyses and Downtime and Loss Assessment for the HayWired Scenario Mainshock 365

List 

number Name Street number Street Height, in meters Stories Year completed

Lateral loadresisting system

197 199 Fremont Street 199 Fremont 111 27 2000 Dual-system steel 

CBF/EBF; steel MF

198 Hiram W Johnson State Building 455 Golden Gate 58 14 2000 --

199 Courtyard San Francisco Downtown 299 2nd 62 18 2001 RC core walls, RC 

gravity

200 The Brannan II 229 Brannan 65 18 2001 RC MF

201 The Brannan I 219 Brannan 65 18 2001 RC MF

202 Gap Building 2 Folsom 84 14 2001 Dual-system RC 

wall/RC MF

203 Four Seasons Hotel 757 or 735 Market 121 40 2001 Dual-system steel 

CBF/EBF; steel MF

204 55 Second Street 55 2nd 101 25 2002 Steel MF

205 Bridgeview 400 Beale 87 26 2002 Dual-system RC 

wall/RC MF

206 Brannan III 239 Brannan 66 18 2002 RC MF

207 JPMorgan Chase Building 560 Mission 128 31 2002 --

208 The Paramount 680 Mission 128 40 2002 Others

209 The Beacon West 250 to 266 King 57 16 2003 Dual-system RC 

wall/RC MF

210 Avalon at Mission Bay 255 King 58 17 2003 RC core walls, RC 

gravity

211 The Metropolitan I [The Metropolitan] 355 1st 81 26 2004 --

212 The Metropolitan II [The Metropolitan] 333 1st 66 21 2004 --

213 St. Regis San Francisco 125 3rd 148 42 2005 --

214 International Hotel and St. Mary Catholic 

Center

848 Kearny 59 15 2005 --

215 The Watermark 501 Beale 73 22 2006 --

216 Avalon at Mission Bay IIA 301 King 58 17 2006 RC core walls RC 

gravity

217 San Francisco Federal Building 1000 Mission 71 18 2007 --

218 SoMa Grand 1146 to 1160 Mission 71 23 2007 --

219 One Rincon Hill, South [One Rincon Hill] 425 1st 184 54 2008 RC core walls with 

outrigger

220 Arterra 320 Berry 55 16 2008 --

221 Radiance I 325 China Basin 65 16 2008 --

222 InterContinental San Francisco 868 Howard 104 32 2008 --

223 555 Mission Street 555 Mission 140 33 2008 Steel MF

224 Argenta 1 Polk 68 20 2008 RC core walls, RC 

gravity

225 The Infinity, Phase I [The Infinity] 300 Spear 107 37 2008 --

226 Millennium Tower [Millennium Tower] 301 Mission 197 58 2009 Dual-system RC 

wall/RC MF

227 The Infinity, Phase II [The Infinity] 300 Spear 137 41 2009 RC core walls, RC 

gravity

228 Health Sciences West 513 Parnassus 64 16 NA RC core walls, RC 

gravity

229 Health Sciences East 513 Parnassus 64 16 NA --

230 Fillmore Center II 1510 Eddy 55 18 NA --

231 680 Folsom 680 Folsom 52 13 NA Steel MF

232 350 Mission Street 350 Mission 168 NA --

Table 37.—Continued

Chapter P

Fire Following the HayWired Scenario Mainshock

By Charles Scawthorn1

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013]

1

SPA Risk LLC.

2

Usage of the term conflagration varies within the fire service (and 

interestingly, does not appear in the 1,449-page National Fire Protection 

Association’s Glossary of Terms, 2013 Edition; http://www.nfpa.org/~/media/

files/codes-and-standards/glossary-of-terms/glossary_of_terms_2013.pdf). It has 

previously been defined by the author (Scawthorn and others, 2005) as “. . . in 

the urban context, a conflagration usually denotes a large fire that spreads across 

one or more city streets.”

Abstract

Fire following earthquake is a significant problem in 

California. This chapter discusses potential losses arising from 

fires following the HayWired earthquake scenario, a hypothetical 

moment magnitude (Mw) 7.0 earthquake (mainshock) occurring 

on April 18, 2018, at 4:18 p.m., on the Hayward Fault in the east 

bay part of the San Francisco Bay area. The earthquake causes 

Modified Mercalli Intensities of VI–X in the greater San Francisco 

Bay region, with very strong shaking along the fault in the densely 

urbanized east bay. Weather conditions are typical for the season, 

with strong onshore winds in the afternoon, subsiding to calm in 

the evening.

Fire following earthquake is a highly nonlinear process, 

modeling of which does not have great precision and is such 

that, in many cases, the only clear result is differentiation 

between situations of a few small fires versus major conflagration. For the Mw 7.0 scenario mainshock, it is estimated that 

approximately 668 ignitions will occur requiring the response 

of a fire engine. The first responding engine will not be able to 

adequately contain approximately 450 of these fires, such that 

in Alameda, Contra Costa, and Santa Clara Counties, dozens 

to hundreds of large fires are likely to merge into numerous 

conflagrations destroying tens of city blocks, with several of 

these potentially merging into one or several super conflagrations destroying hundreds of city blocks.

Under the assumed scenario conditions, it is estimated that 

the about 450 large fires will result in an ultimate burned area of 

approximately 79 million square feet of residential and commercial building floor area, equivalent to more than 52,000 single 

family dwellings. The fires following the scenario mainshock 

would be directly responsible for the loss of hundreds of lives, 

a total building replacement value of almost $16 billion, and 

property losses approaching $30 billion (2014 dollars). This loss is 

virtually fully insured and would be one of the largest single-loss 

events in the history of the insurance industry. Other economic 

impacts include the loss of perhaps $1 billion in local tax revenues. 

A number of opportunities exist for mitigating this problem, 

including greatly enhancing the postearthquake supply of water 

for firefighting and the mandatory use of automated gas shut-off 

valves, or seismic shut-off meters, in densely built areas.

Introduction

The HayWired earthquake scenario examines a hypothetical moment magnitude (Mw) 7.0 earthquake (mainshock) 

occurring on April 18, 2018, at 4:18 p.m., on the Hayward 

Fault in the east bay part of the San Francisco Bay area. This 

chapter discusses the potential for fire in the bay region after 

the mainshock. “Fire following earthquake” refers to a series 

of events or a stochastic process initiated by a large earthquake. Fires occur following all earthquakes that significantly 

shake a human settlement but are generally only a significant 

problem in large metropolitan areas predominantly composed 

of densely spaced wood buildings. In such circumstances, 

multiple simultaneous ignitions can lead to catastrophic 

conflagrations2 that may be the dominant agent of damage. 

Example regions vulnerable to such conflagrations include 

Japan, New Zealand, parts of Southeast Asia, and western 

North America. A large earthquake, such as a Mw 7.0 event on 

the Hayward Fault in the San Francisco Bay area (or comparable events in southern California, Washington’s Puget 

Sound region, or the lower mainland of British Columbia), 

combines all of the requisite factors for major conflagrations 

that, depending on circumstances, can be uniquely catastrophic, such as the fire following the Mw 7.8 Great 1906 San 

Francisco, California, earthquake.
368 The HayWired Earthquake Scenario—Engineering Implications

Purpose

The purpose of this chapter is to quantitatively describe 

fires following a hypothetical Mw 7.0 earthquake on the Hayward Fault, with primary emphasis for assisting emergency 

planning. The HayWired scenario occurs on Wednesday, April 

18, 2018, at 4:18 p.m., with average April weather conditions. 

This analysis is intended to be realistic and not a “worst-case” 

scenario, and addresses the following questions:

• What is a realistic scenario of ignitions, fire growth, and 

spread? 

• How will ignitions be reported after an earthquake, how 

will fire departments respond, and what factors will 

influence the spread of fires? What mutual-aid agreements 

are in place and how will they be activated?

• How will damage to telecommunications, water supply, 

and roadways affect response?

• What, if any, effective mitigation actions have been 

undertaken elsewhere that might be practical in the San 

Francisco Bay region in addition to those already taken?

• What are the limitations of the fire-following-earthquake 

scenario and what research would provide a more realistic, 

perhaps more challenging or detailed, scenario?

Background

Large fires, measured in terms of square miles of burned 

area, have not been unique to fires following earthquakes—

indeed the great fires of London (1666) and Chicago (1871) are 

only the most noteworthy of a long succession of nonearthquake 

related urban conflagrations. Large urban conflagrations were 

common in 19th century America, which allowed the National 

Board of Fire Underwriters (1905) to state the following with 

some confidence:

In fact, San Francisco has violated all underwriting 

traditions and precedent by not burning up. That it has 

not done so is largely due to the vigilance of the fire 

department, which cannot be relied upon indefinitely to 

stave off the inevitable.

Although the 1906 San Francisco earthquake had major 

geological effects and damaged many buildings, it was the 

ensuing fire that resulted in 80 percent of the total damage—a 

fire foreseen and expected, irrespective of an earthquake. As 

the fire service was professionalized in the 20th century—

with improvements in equipment, communications, training, 

and organization—large urban conflagrations tended to 

become much less common (National Commission on Fire 

Prevention and Control, 1973). However, they were not 

entirely eliminated, as witnessed in the San Francisco Bay area 

in the 1991 East Bay Hills Fire, when 3,500 buildings were 

destroyed in a matter of hours.

The two largest peacetime, urban conflagrations in history 

have been fires following earthquakes—1906 San Francisco 

(Mw 7.9) and 1923 Tokyo (Mw 7.9) earthquakes. In Tokyo, the 

fires caused the great majority of the 140,000 fatalities.

Much larger wildland fires also occur and continue to be 

a major source of loss in places such as southern California 

almost every year. However, historical earthquakes have not 

caused major wildland fires.

Although the combination of professionalized fire 

services, improved water supply, and better building practices 

has largely eliminated nonearthquake-related large urban 

conflagrations in the United States, fire following earthquakes 

is still a concern. This is owing to the correlated effects of a 

large earthquake simultaneously causing numerous ignitions, 

degrading building fire-resistive features, dropping pressure 

in water-supply mains, and overwhelming communications 

and transportation routes, thus allowing some fires to quickly 

grow into conflagrations that outstrip local resources. It 

is not sufficiently appreciated that the key to modern fire 

protection is a well-drilled, rapid response by professional 

firefighters in the early stages of structural fires, arriving in 

time to suppress a fire while that is still relatively feasible. For 

example, a typical response goal for urban fire departments is 

4 minutes (from time of report to arrival) for a single ignition. 

If suppression is delayed, owing to either delayed response 

or lack of water, a single structural fire can quickly spread to 

neighboring buildings and grow to the point where an entire 

municipality’s fire resources are required, and perhaps even 

assistance from neighboring communities. This is for a single 

ignition. Most fire departments are not sized or equipped to 

cope with the fires following a major earthquake. A major 

earthquake and its associated fires is a low probability event 

for which, although having very high potential consequences, 

it may not be feasible to adequately prepare. There are 

exceptions to this; the Cities of San Francisco, Los Angeles, 

and Vallejo Fire Departments (California) and Vancouver 

(British Columbia) Fire and Rescue Services have all 

undertaken special measures, which are discussed below.

Scenario Earthquake and Prevailing 

Conditions

This section summarizes the seismological aspects 

and affected region for the HayWired scenario. The focus is 

primarily on the fire-related aspects of the scenario.
Chapter P. Fire Following the HayWired Scenario Mainshock 369

Figure 1. Satellite image of the San Francisco Bay region, California, overlaid with a U.S. Geological Survey ShakeMap for the hypothetical 

magnitude-7.0 mainshock of the HayWired earthquake scenario on the Hayward Fault (fault rupture shown by bright red line). (Mainshock data from 

Aagaard and others, 2017.)

I II–III IV V VI VII VIII IX X+

Not felt Weak Light Moderate Strong Very strong Severe Violent

Moderate Heavy Very heavy Moderate/

 Heavy None None None Very light Light

Extreme

30 KILOMETERS

15 MILES

0

0 5 10

10 20

EXPLANATION

PACIFIC OCEAN

N

Base map from Google Earth; image Landsat/Copernicus; data LDEO-Columbia, NSF, NOAA; data SIO, NOAA, 

U.S., Navy, NGA, GEBCO, 2015.

Oakland

SAN FRANCISCO BAY

Table 1. Counties and populations in the San Francisco Bay 

region, California, affected in the HayWired earthquake scenario.

1

From California Department of Finance (2014).

Rupture Segment, Magnitude, and Intensity

The HayWired scenario Mw 7.0 mainshock on the 

Hayward Fault affects the entire San Francisco Bay region 

(fig. 1). Seismological aspects of the scenario are discussed in 

Detweiler and Wein (2017). Peak ground acceleration (PGA) 

and Modified Mercalli Intensity (MMI) distributions were 

developed by Aagaard and others (2017) for this project and 

furnished for this report (fig. 2). Noteworthy are the high MMI 

(VIII–X) along the fault in the entire east bay.

Affected Region

Ten San Francisco Bay region counties affected by the 

scenario mainshock were analyzed for fire following earthquake. 

The region is densely urbanized (fig. 3), and the total affected 

population is approximately 7.7 million people (table 1; California 

Department of Finance, 2014), with population density as shown 

in figure 4.

Exposure

Building exposure data for the San Francisco Bay area 

was provided by the Federal Emergency Management Agency 

based on Hazus-MH (Federal Emergency Management 

Agency, 2012) building inventory. There is a total building 

floor area of 5.77 billion square feet, with an estimated value 

(structure only) of approximately $1.15 trillion, distributed as 

shown in figure 5.

County Estimated population (2014)1

Alameda 1,573,254

Contra Costa 1,087,008

Marin 255,846

Napa 139,255

San Francisco 836,620

San Mateo 745,193

Santa Clara 1,868,558

Santa Cruz 271,595

Solano 424,233

Sonoma 490,486

Total 7,692,048
370 The HayWired Earthquake Scenario—Engineering Implications

EXPLANATION

Instrumental 

intensity

I

II

III

IV

V

VI

VII

VIII

IX

X

0

0 10 20

10 20 30 40

30 MILES

50 KILOMETERS

123° 122° 121°

B

38°

37°

PACIFIC 

OCEAN

San 

Francisco 

Bay

San 

Mateo

SF

Santa 

Cruz

Solano

Sacramento

 Area 

of map

CALIF

Figure 2. Maps of 

the San Francisco 

Bay region, California, 

showing (A) peak ground 

acceleration (PGA) and 

(B) instrumental intensity 

(approximately Modified 

Mercalli Intensity) for the 

hypothetical magnitude-7.0 

mainshock of the 

HayWired earthquake 

scenario on the Hayward 

Fault. g, acceleration 

due to gravity. SF, San 

Francisco. (Mainshock 

data from Aagaard and 

others, 2017.)

San 

Mateo

Santa 

Cruz

Solano

SF

Sacramento

EXPLANATION

Peak ground 

acceleration (g)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0

0 10 20

10 20 30 40

30 MILES

50 KILOMETERS

123° 122° 121°

A

38°

37°

 Area 

of map

CALIF

PACIFIC 

OCEAN

San 

Francisco 

Bay
Chapter P. Fire Following the HayWired Scenario Mainshock 371

Figure 3. Satellite image of San Francisco Bay region, California. The region is densely urbanized, with a population 

approximately 7.7 million people (California Department of Finance, 2014).

PACIFIC OCEAN

30 KILOMETERS

15 MILES

0

0 5 10

10 20

N

Base map modified from Google Earth, 2015.

 San 

Francisco

Oakland

San Jose

SAN FRANCISCO BAY

Fire Protection

More than 500 fire stations were considered in the analysis 

of fire protection (fig. 6). In the most heavily impacted area there 

are a total of 229 fire engines potentially available immediately 

following the HayWired mainshock.

Although many jurisdictions have seismically retrofitted 

fire stations (and other critical infrastructure), the functionality of 

a significant number of fire stations is still questionable (fig. 7). 

According to Bello and others (2006), an Earthquake Engineering 

Research Institute survey of these fire stations in 2006:

. . . indicated that average peak ground acceleration 

are [sic] 0.5 g, and 52 percent of the stations are in 

areas mapped as moderate to very high liquefaction 

susceptibility with 102 stations being located within 

State designated Seismic Hazard Zone of Required 

Investigation for liquefaction or landsliding. More than 

60 volunteers conducted walk-through field surveys of 

about 100 stations. In terms of life safety considerations, 

based on construction type, age and assessment of 

vulnerability, 42 percent of fire stations are in moderate 

to high-risk categories. In terms of functionality of the 

fire stations, based on a subset (293 stations) for which 

information was available, 67 percent were of moderate 

to high risk of not functioning after an earthquake. 

Based on these results, it is recommended that those fire 

stations at higher risk be evaluated and retrofitted such 

that life safety and vulnerability are improved before the 

next large earthquake occurs.

Each fire station in the affected region was allocated an 

immediate area using a Voronoi diagram3 as an approximation 

of the station’s primary response area (fig. 8). The subsequent 

analysis is based on these primary response areas.

Time of Day

Time of day is relevant in that more human activity occurs 

during waking hours, typically resulting in higher ignition rates at 

those times. The HayWired mainshock is specified as occurring 

Wednesday, April 18, 2018, at 4:18 p.m. However, the specific 

time of occurrence is not considered in this analysis. 

Wind and Humidity

Weather can affect fire growth and spread, as well as 

the direction and distance at which communities are affected 

by hazardous material release. Important meteorological 

parameters include windspeed, wind direction, temperature, 

rain, and humidity. For purposes of estimating fire effects in the 

HayWired scenario, average April conditions were assumed to 

apply, based on data for the period 1974–2012 (WeatherSpark, 

2014). Average conditions for the three San Francisco Bay 

area international airports are shown in table 2 and figure 9. 

In the case of precipitation, the most common condition is 

reported (for example, no rain), along with the probability of 

precipitation at some point in the day and the most common 

form of precipitation when it does rain. In the case of wind 

direction, the most common direction is tabulated. Humidity is 

reported as average daily low and high.

In April, wind conditions are typically created by a trough of 

low pressure east of the bay area, which draws in strong, westerly, 

cooler and more humid air from the ocean in the afternoon, 

subsiding to more calm conditions in evening. An example of this 

is shown in figure 10 for April 18, 2012, in which major streaklines 

are shown at 4 p.m. and 5 p.m., with much shorter streaklines at 9 

p.m. Cumulative distribution functions for windspeeds for 4 p.m., 

3

For this analysis, the Voronoi diagram was a partition of the region into 

polygons, each side of which was a line equidistant from the nearest two fire 

stations. (For an explanation of Voronoi diagrams see https://en.wikipedia.org/

wiki/Voronoi_diagram.)
372 The HayWired Earthquake Scenario—Engineering Implications

0 10 20 KILOMETERS

0 5 10 MILES

PACIFIC

OCEAN

SAN

FRANCISCO

BAY

122.75° 122.5°

38°

37.5°

122.25° 121°

B

Area

of map

CALIF

EXPLANATION

Population density

(persons/km2

)

HayWired 

 rupture

0–1

1–10

10–1,000

1,000–10,000

>10,000

San Francisco

Oakland

Figure 4. Maps of the 

San Francisco Bay region, 

California, showing population 

density for (A) the 10-county 

region and (B) the area 

adjacent to the fault rupture for 

the hypothetical magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. The 

length of the Hayward Fault 

ruptured in the scenario is 

shown on the maps. persons/

km2, persons per square 

kilometer.

SAN FRANCISCO BAY

PACIFIC

OCEAN

122° 123°

38°

37°

EXPLANATION

San Francisco Oakland

San Jose

A

Population density

(persons/km2

)

HayWired 

 rupture

0–1

1–10

10–1,000

1,000–10,000

>10,000

Area

of map

CALIF

40 KILOMETERS

0 10 20 MILES

0 10 20 30
Chapter P. Fire Following the HayWired Scenario Mainshock 373

SAN

FRANCISCO

BAY

PACIFIC

OCEAN

37°

38°

122.5° 122°

EXPLANATION

Total floor area ratio

San Francisco Oakland

San Jose

HayWired 

 rupture

<0.5

0.5–1

1–2

2–7

7–20

20–50

>50

Area

of map

CALIF 20 KILOMETERS

0 5 10 MILES

0 10

Figure 5. Map showing 

building density of San 

Francisco Bay region, 

California. The length of the 

Hayward Fault ruptured in the 

hypothetical magnitude-7.0 

mainshock of the HayWired 

earthquake scenario is shown 

on the map. Total floor area 

ratio, total building floor area 

in a census block divided by 

the area of the census block.

Figure 6. Map of San Francisco Bay area, California, fire stations overlaid on peak ground acceleration (PGA) for the 

hypothetical magnitude-7.0 mainshock of the HayWired earthquake scenario. The length of the Hayward Fault ruptured 

in scenario is shown on the map. g, acceleration due to gravity. (Mainshock data from Aagaard and others, 2017.)

20 KILOMETERS

0 5 10 MILES

0 10

EXPLANATION

PGA (g)

HayWired 

 rupture

Fire station

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

38°

122.5° 122°

37.5°

Area

of map

CALIF

SAN

FRANCISCO BAY

PACIFIC

 OCEAN
374 The HayWired Earthquake Scenario—Engineering Implications

Solano (13)

Santa Clara (64)

San Mateo (32)

San Francisco (38)

Napa (7)

Marin (18)

Contra Costa (48)

Alameda (66)

High Moderate

Low

0

5

10

15

20

25

30

35

40

Figure 8. Map of San Francisco Bay area, California, fire stations with associated Voronoi areas. The primary 

response area for each fire station was approximated by a Voronoi diagram. The length of the Hayward Fault 

ruptured in the hypothetical magnitude-7.0 mainshock of the HayWired earthquake scenario is shown on the map.

SAN

FRANCISCO

BAY

PACIFIC

OCEAN

20 KILOMETERS

0 5 10 MILES

0 10

HayWired 

 rupture

Fire stations

EXPLANATION

38°

122.5° 122°

37.5°

Area

of map

CALIF

Figure 7. Three-dimensional 

graph showing the number of fire 

stations in San Francisco Bay 

area, California, counties that 

are at low, moderate, and high 

risk of earthquake damage in 

the hypothetical magnitude-7.0 

mainshock of the HayWired 

earthquake scenario (data from 

Bello and others, 2006).
Chapter P. Fire Following the HayWired Scenario Mainshock 375

Figure 9. Maps and charts of average temperatures on April 18 at (A) San Francisco International Airport 

and (B) Hayward Executive Airport in the San Francisco Bay area, California. Average windspeeds are 

noted. (Images from WeatherSpark, 2014; http://www.weatherspark.com, used with permission.) 

A

B

EXPLANATION

Windspeed, in 

nautical miles per hour

0–4.9

5–9.9

10–14.9

15–19.9

20–24.9

+25

Area

of map

CALIF

50 KILOMETERS

30 MILES

0 10 20 30 40

0 10 20

N N N

Figure 10. Maps showing wind streaklines (arrows) for April 18, 2012 (4/18/2012), at 4 p.m. (left), 5 p.m. (center), 

and 9 p.m. (right), typical of April wind conditions in the San Francisco Bay region, California. Strong westerly winds 

in late afternoon subside in evening. Windspeed was measured 10 meters above surface elevation. PST, Pacific 

Standard Time. (Images from San Jose State University, 2014.)
376 The HayWired Earthquake Scenario—Engineering Implications

Figure 11. Graph showing cumulative distribution function of 

windspeeds in the central San Francisco Bay region, California, for 

4 p.m., 5 p.m., and 9 p.m. for the years 2000–2012. (Data from San 

Jose State University, 2014.)

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

0 10 20 30 40 50

4 p.m.

5 p.m.

9 p.m.

60

Windspeed cumulative distribution function

Windspeed, in miles per hour

EXPLANATION

5 p.m., and 9 p.m. for the years 2000–2012 are shown in figure 11, 

and indicate significant variability of the stronger afternoon winds, 

with consistently calmer conditions later in the evening.

However, a reverse of the typical summertime weather 

pattern can occur, consisting of occasional intense katabatic 

winds, locally sometimes termed “Diablo winds.” These are hot, 

dry, offshore winds from the northeast that sometimes occur in 

the San Francisco Bay region during the spring and fall. These 

winds differ from the more familiar Southern California Santa 

Ana winds, and are created by the combination of strong inland 

high pressure at the surface, strongly sinking air aloft, and lower 

pressure off the California coast. The air descending from aloft, 

as well as from the Coast Ranges, compresses at sea level, where 

it warms as much as 20 degrees Fahrenheit (°F) (11 degrees 

Celsius, °C), and loses humidity. If the pressure gradient is large 

enough, the dry offshore wind can become quite strong with gusts 

reaching speeds of 40 miles per hour (64 kilometers per hour) or 

higher, particularly along and in the lee of the ridges of the Coast 

Ranges, where warm, dry surface air from the windward eastern 

side is drawn up and over the ridgelines (fig. 12). Such winds 

were major factors in the 1923 Berkeley and 1991 East Bay 

Hills Fires (discussed below). This effect is especially significant 

as it can enhance the updraft generated by large wildland or 

urban fires. The pattern of windspeeds and direction used for the 

scenario was the more typical westerly wind subsiding in the 

evening, rather than the more dangerous Diablo-wind scenario.

Figure 12. Map showing wind streaklines (arrows) for 

September 13, 2003 (9/13/2003), at 10 a.m., typical of Diablo wind 

conditions in the San Francisco Bay region, California. Windspeed 

was measured at 10 meters above surface elevation. PST, Pacific 

Standard Time. (Images from San Jose State University, 2014.)

EXPLANATION

Windspeed, in 

nautical miles per hour

0–4.9

5–9.9

10–14.9

15–19.9

20–24.9

+25

Area

of map CALIF

50 KILOMETERS

30 MILES

0 10 20 30 40

0 10 20

N

Experience with Large Fires in the San Francisco 

Bay Region

The Great 1906 San Francisco earthquake and fire is the 

archetypical fire following earthquake event. It is so familiar and 

well documented that we will not spend much time on it here. 

Simply put, it was the largest peacetime urban fire in history at the 

time, only exceeded since by the 1923 Tokyo earthquake and fire. 

The 1906 earthquake and resulting fires caused an estimated 3,000 

Table 2. Average wind conditions in April at San Francisco Bay area, California, major airports.

[Weather data from WeatherSpark (2014); mi/hr, miles per hour; °F, degrees Fahrenheit; NW, northwest; W, west]

Airport (city/identifier) Windspeed 

(mi/hr) Direction Temperature(°F)

Light rain

(percent 

chance)

Percent 

humidity

San Jose (SJC) 7 NW 50–65 19 42–93

San Francisco (SFO) 12 W 50–65 28 52–88

Oakland (OAK) 10 W 50–65 22 56–92
Chapter P. Fire Following the HayWired Scenario Mainshock 377

Figure 13. Map of fires (orange 

and yellow diamonds) caused 

by the moment-magnitude-7.8 

1906 San Francisco, California, 

earthquake and area burned 

in the great conflagration that 

followed (orange). Ignition data 

from Scawthorn and O’Rourke 

(1989) and Scawthorn and others 

(2005).

1 2 KILOMETERS

0 0.5 1 MILE

0

Area

of map CALIF

N

deaths and $524 million (1906 dollars) in property loss. Fires that 

ignited in San Francisco soon after the onset of the earthquake 

burned for 3 days because of the lack of water to control them. The 

damage in San Francisco was devastating and 28,000 buildings 

were destroyed, although 80 percent of the damage was caused 

by the fire rather than the shaking (fig. 13). Fires also intensified 

the losses in 1906 at Fort Bragg and Santa Rosa (see Scawthorn 

and O’Rourke, 1989; Scawthorn and others, 2005; Scawthorn and 

others, 2006).

Beyond the 1906 San Francisco earthquake and fire, the 

San Francisco Bay region has a long history of conflagrations 

(fig. 14), owing in large part to the Diablo winds discussed 

above. According to the Hills Emergency Forum (2005), over 

the period from 1923 to 1991 the east bay has averaged a 

585-acre fire every 5 years, destroying on average 266 homes 

(2005). However, most of these building losses occurred in only 

two of these fires—the 1923 and 1991 events (fig. 15, table 3). 

It should also be noted that almost all of these fires occurred 

in autumn (which is typically the region’s greatest fire-risk 

season), in contrast to the scenario being considered here.

Three recent fires in the San Francisco Bay region are worthy 

of mention:

• On September 9, 2010, a buried, high-pressure, 30-inch 

steel natural-gas pipeline exploded in a residential 

neighborhood in San Bruno, California, near San 

Francisco. The explosion and ensuing fire killed 8 people 

and injured 58. It destroyed 38 homes and damaged an 

additional 70. During the first 50 hours following the 

incident, more than 500 firefighters and 90 firefighting 

apparatus responded, involving 42 fire agencies. The total 

cost of the disaster was estimated to be approximately 

$1.6 billion (Davidson and others, 2012).

• The Mission Bay fire was a five-alarm fire that occurred 

shortly before 5 p.m. on March 11, 2014, in the Mission 

Bay neighborhood of San Francisco, California. The 

conflagration appeared to completely destroy block 5, 

a 172-unit building, part of Mega Blocks 360, a $227 

million apartment complex being developed by San 

Francisco-based BRE Properties, Inc., at China Basin 

Street and Fourth Street (San Francisco Chronicle, 

2014).The San Francisco Fire Department needed a 

large amount of resources to combat the fire, including 

the city’s auxiliary water-supply system.

• On the night of October 8, 2017, Diablo winds started and 

drove widespread wildfires in the northern San Francisco 

Bay region counties of Napa, Sonoma, and Solano. The 

fires killed at least 43 people, destroyed 8,900 homes and 

other structures, and burned 164,000 acres. More than 

10,000 firefighters responded to the fires (Wikipedia, 

2017). (Note that because of its recency, this fire was not 

considered further in this chapter.)
378 The HayWired Earthquake Scenario—Engineering Implications

1961

1923 1970

1980 1905

1946

1937

1955

1961

1991

24

13

24

880

580

880

80

1968

1960

1931

1933

1940

1929

1991

SAN FRANCISCO 

BAY

San Leandro

Reservoir

Lake

Chabot

San Pablo

Reservoir

Lafayette

Reservoir

Briones

Reservoir

MACARTHUR

BLVD.

REDWOOD RD.

SAN PABLO DAM RD.

UNIVERSITY

BROADWAY

ASHBY

GRIZZLY PEAK

 BLVD.

SKYLINE BLVD.

N

Area

of map

CALIF

0 1 2 3 4

0 1 2 3 MILES

5 KILOMETERS

Figure 14. Map of fires in the east bay part of the San Francisco Bay area, 

California, from 1923 to 1991. Note that colors are only used to differentiate among 

areas burned by fires. (Modified from Hills Emergency Forum, 2005.)

Table 3. List of some large, historical fires driven by Diablo winds in the east bay part of the San Francisco Bay area, California (data from Hills 

Emergency Forum, 2005; California Governor’s Office of Emergency Services, 2013; Routley, [n.d.]; National Board of Fire Underwriters, 1923.

[--, no data]

Month/year Fire name/location Deaths Structures destroyed Acres 

burned

Estimated 

damage, in 

billions of 

U.S. dollars

Ignition cause

September 1923 City of Berkeley 0 584 130 -- Smoker

November 1933 Joaquin Miller (Redwood Road) 1 20 homes 1,000 -- Smoker

September 1946 Buckingham Boulevard/Norfolk 

Road

0 0 1,000 -- Arson and 

rekindle

October 1960 Leona Hillside 0 2 homes 1,200 -- Unknown

September 1970 Oakland Hills 0 37 homes and 21 damaged 204 -- Arson

October 1991 East Bay Hills 25 3,354 homes and 456 apartments 1,600 1.5 Rekindle
Chapter P. Fire Following the HayWired Scenario Mainshock 379

Figure 15. Map of final burned areas (dark orange) for 1923 Berkeley and 1991 East Bay Hills Fires in the 

east bay part of the San Francisco Bay area, California.

1991 East Bay 

Hills Fire

1923 

Berkeley

 Fire

37.85°

37.87°

37.83°

37.89°

122.3° 122.25°

 Area of map

CALIF

ALAMEDA 

COUNTY

2 KILOMETERS

0 0.5 1 MILE

0 1

Fire Following Earthquake Aspects of 

the Scenario

This section presents the analysis underlying the estimation 

of fires and losses likely to result from the HayWired scenario 

mainshock. The section discusses modeling of fire following 

earthquake, ignitions, initial response, fire spread, and performance 

of lifelines (for example, utilities and transportation).

Modeling of Fire Following Earthquake

A full probabilistic methodology for analysis of fire 

following earthquake was developed in the late 1970s (Scawthorn 

and others, 1981) and has been applied to major cities in western 

North America (Scawthorn and Khater, 1992). Scawthorn and 

others (2005) summarizes modeling for fire following earthquake, 

so only a brief review is presented here. In summary, the steps in 

the process of fire following earthquake are shown in figure 16:

• Occurrence of the earthquake—causing damage to 

buildings and contents, even if the damage is as simple as 

objects (such as candles or lamps) falling over.

• Ignition—whether a structure has been damaged or not, 

ignitions can occur as a result of earthquakes. The sources 

of ignitions are numerous, including overturned heat 

sources, abraded and shorted electrical wiring, spilled 

chemicals having exothermic reactions, and friction from 

objects rubbing together.

• Discovery—at some point, the fire resulting from the 

ignition will be discovered, if it has not self-extinguished 

(this aspect is discussed in more detail below). In the 

confusion following an earthquake, the discovery may 

take longer than it might otherwise.

• Report—if it is not possible for people discovering 

a fire to immediately extinguish it, fire department 

response will be required. For a fire department to 

respond, a report has to be made to the fire department. 

Communications-system malfunction and congestion 

may delay many reports.

• Response—a fire department then has to respond but 

may be delayed by responding to nonfire emergencies 

(for example, building collapse) and by transportation 

disruptions.

• Suppression—a fire department then has to suppress 

the fire. If the fire department is successful, they move 

on to the next incident. If not successful, they continue 

to attempt to control the fire, but it can spread and 

become a conflagration. Success or failure hinges 

on numerous factors, including the functionality of 

the water-supply system, building construction and 

density, and weather conditions such as wind and 
380 The HayWired Earthquake Scenario—Engineering Implications

humidity. If the fire department is unable to contain 

the fire, the process ends when the fuel is exhausted or 

when the fire reaches a firebreak.

This fire-following-earthquake process is also shown 

in figure 17, which is a fire department operations time 

line. A rapid response is essential to reduce losses from fire 

following earthquake. Fire following earthquake is not a 

linear process, and modeling it is not very precise—in many 

cases, only a few small fires versus a major conflagration can 

be distinguished.

Ignitions

Postearthquake ignition rates in the United States have 

been studied by a number of investigators (Lee and others, 

2008) with the most recent and relevant algorithms for 

estimating postearthquake ignition rates being developed by 

Davidson (2009a,b) and SPA Risk LLC (2009), both of which 

are considered here. 

Davidson (2009b) conducted an exhaustive selection to 

evaluate 48 potential covariates, of which model A.NB2 is:

 (1)

where 

 μ is ignitions per census tract, 

II is the instrumental intensity of the 

earthquake,4

Yes

No

Earthquake

Structural/nonstructural

 damage

Communication 

infrastructure 

damage/saturation

Building construction 

and density, wind, 

humidity, vegetation...

Water supply

damage/malfunction

Transportation 

 impediments

Ignition

Discovery

Report

Suppression

Spread/conflagration

Firebreak/fuel exhaustion

Fire department 

 response

Stop

Stop

Figure 16. Flow chart of the fire-following-earthquake process 

(from Scawthorn and others, 2005).

EXPLANATION

Ignition

Fire discovery

7

D

Fire report

Fire response

R

Suppression

Fire growth—Each stacked 

 line indicates one additional 

 engine needed 

Figure 17. Chart of fire department (FD) operations timeline when responding to fires following an earthquake. Horizontal axis is time, 

beginning at time of earthquake. Horizontal bars depict development of fires, from ignition through growth or increasing size (size is 

indicated by width or number of horizontal bars). (From Scawthorn and others, 2005.)

ln(μ) = β0 + βiiII + βtbldg ln(tbldg)+ β%CITx%CIT + βdensxdens,

4

Modified Mercalli Intensity (MMI) and Instrumental Intensity (II) are used 

synonymously here.
Chapter P. Fire Following the HayWired Scenario Mainshock 381

x%CIT is the percent of land area that is commercial, 

industrial, or transportation, 

 tbldg is the total building area in thousands of 

square meters, 

x%URM is the percent of building area that is 

unreinforced masonry (URM), 

 xdens is the population density (persons per square 

kilometer), and

parameter (β) estimates are β0=–15.42, βii=1.13, β%CIT=–32.48, 

βtbldg=0.85, β%URM=27.72, and βdens=0.0000453.

The SPA Risk LLC (2009) relation used the Davidson 

(2009b) dataset restricted to census tracts that (1) fell within 

jurisdictions for which ignition data was available, (2) experienced 

MMI≥VI, and (3) had population densities greater than 3,000 

per square kilometer. Using this approach, relatively simple 

regressions to model postearthquake ignitions were developed:

 Ignitions per million square feet of building floor 

 area= –0.029444PGA+0.581895PGA2, (2)

Ignitions per million square feet of building floor 

 area=1.0449–0.338MMI+0.0277MMI 2, (3)

where PGA is the peak ground acceleration of the earthquake, 

relative to the acceleration due to gravity at the Earth’s surface (g).

Of the two ignition regressions, the one in equation 1 requires 

more data, some of which may not be readily available (for 

example, percentage of URM building).5 A comparison of the two 

ignition models is shown in figure 18A, where equation 1 is plotted 

using median values (standard deviations in parentheses) for 

tbldg=244.7 (164), x%CIT=0.027 (0.016), x%URM = 0.013 (0.01), and 

xdens=3,445 (4,048) as provided in Davidson (2009b), and equation 

3 (SPA Risk LLC, 2009) is plotted in black using 2.6 million 

square feet of building floor area per census tract. Dotted lines in 

the figure are equation 1 plus and minus one standard deviation 

(determined by way of numerical simulation).

Figure 18B and C are similar, except that the variable 

x%CIT in Davidson’s (2009b) equation, representing the 

percentage of land area employed for commercial, industrial, 

and transportation (CIT) purposes, is varied by plus and minus 

one sigma (sigma of x%CIT), with equation 3 remaining the same 

in all plots. In figure 18A, it can be seen that the median SPA 

Risk LLC (2009) model is higher than the Davidson (2009b) 

model, by a factor of 2.8 at MMI VI and 2.3 at MMI VIII, 

while actually being lower (0.93) at MMI X. In figure 18B, 

corresponding to lower CIT land use (more representative of 

residential areas), the two models are in closer agreement, 

whereas C (representative of higher CIT uses) shows a 

somewhat greater difference of the two models.

Equation 2 was used to estimate the total number of 

ignitions for the HayWired mainshock, resulting in a mean 

estimate of 668 ignitions, as shown in figure 19 and table 4. 

Ninety percent of the ignitions are confined to three counties—

Alameda, Contra Costa and Santa Clara—with Alameda 

County alone having 53 percent of all ignitions. These are 

only ignitions that require fire department response; there 

may be other, typically minor, ignitions that are suppressed 

immediately by citizens, which are often not reported. Of 

the approximately 668 total ignitions, it is estimated 453 of 

these will grow to be large fires (defined as fires exceeding the 

capacity of the first arriving engine).

The cause of these ignitions will likely be similar to 

causes following the 1994 Mw 6.7 Northridge, California, 

earthquake, which is the best U.S. dataset for fire following 

a recent earthquake; about half of all ignitions would be 

electrical, a quarter gas related, and the remainder owing to a 

variety of causes, including chemical reactions (table 5). Also, 

on the basis of the Northridge experience, nearly half of all 

ignitions would typically occur in single-family residential 

dwellings, with another 26 percent in multifamily residential 

dwellings—that is, about 70 percent of all ignitions occur in 

residential dwellings (Scawthorn and others, 1998). Ignitions 

in educational facilities would be a small percentage of the 

total (3 percent in Northridge), and most of these would be 

a result of the exothermic reactions of spilled chemicals in 

chemistry laboratories.

A particular concern is the large number of oil refineries, 

tank farms, and related facilities in the northern bay area. These 

facilities refine one-third of the gasoline used west of the Rocky 

Mountains. When strongly shaken, oil refineries and tank farms 

have typically had large fires, which have burned for days. 

Examples include the Showa Refinery fire following the Mw

7.6 1964 Niigata, Japan, earthquake (Kawasumi, 1968), the 

Tüpraçs Refinery fire following the Mw 7.6 1999 İzmit, Turkey, 

earthquake (Scawthorn, 2000), and the Idemitsukosan Hokkaido 

Refinery fire following the Mw 8.3 2003 Tokachi-Oki, Japan, 

earthquake (Scawthorn and others, 2005).

Initial Response

This section discusses the initial response to ignitions 

following an earthquake. Reporting of fires is particularly 

crucial, yet problematic, following an earthquake.

Citizen Response

Initially, citizens will respond to the approximately 668 

ignitions requiring fire-department response in the HayWired 

scenario. When they realize suppressing the fires is beyond 

their capabilities, they will attempt to contact emergency 

5

Davidson (2009b) used default data from Hazus-MH MR2 (Federal 

Emergency Management Agency, 2003) for building floor area and 

unreinforced masonry (URM) estimates. An issue exists with the use of 

“URM” default data since most URM buildings in California have been 

retrofitted, so whether such buildings are now unreinforced is unclear. Ding 

and others (2008) have examined the Hazus-MH MR2 building inventory 

data (in general, in the context of flood) and found it to have significant 

inaccuracies. That being said, at the regional level the database can be useful, 

and Davidson’s use of it was innovative.
382 The HayWired Earthquake Scenario—Engineering Implications

Table 4. Estimated ignitions and damage from the hypothetical magnitude-7.0 mainshock of the HayWired earthquake scenario on 

April 18, 2018, at 4:18 p.m. (breezy conditions and moderate humidity). 

[--, no data; TFA, total floor area]

County Exposed 

building TFA Ignitions Large fires

Conflagrations 

(multiblock fires)

Final burned 

TFA, in millions 

of square feet

Final burned loss, 

in millions of 2014 

U.S. dollars ($)

Percent 

burned

Percent of 

total losses

Alameda 1,853 352 279 198 49 $9,710 4 53

Contra Costa 1,480 123 60 43 10 $2,103 1 18

Marin 342 23 14 10 2 $500 1.1 4

Napa 90 27 19 13 3 $651 5.3 4

San Francisco 817 21 5 4 1 $177 0 3

San Mateo 576 19 15 11 3 $519 1 3

Santa Clara 1,610 83 56 40 10 $1,940 1 12

Santa Cruz 96 1 -- -- -- -- 0.01 0

Solano 338 12 4 3 1 $142 0.4 2

Sonoma 38 7 0 0 0 $13 0.3 1

Total 7,241 668 453 321 79 $15,755 2 100

A

B

C

V

0

0.01

0.10

1.00

10.00

0

0.01

0.10

1.00

10.00

0

0.01

0.10

1.00

10.00

VI VII VIII

Modified Mercalli Intensity

EXPLANATION

Equation 1 median value

Equation 1 median plus

 standard deviation

Equation 1 median minus

 standard deviation

Equation 3

medianX%CIT = 0.027

X%CIT−1X%CITsigma = 0.014

X%CIT−1X%CITsigma = 0.0395

Ignition rate per census tract

IX X

Figure 18. Graphs comparing two regressions (equations 1 and 

3, see text) used to model postearthquake ignitions per census 

tract. A, Graph of equation 1 (Davidson 2009b, A.NB2) plotted in 

red using median values (standard deviations in parentheses) 

for tbldg=244.7 (164), x%CIT=0.027 (0.016), x%URM=0.013 (0.01), and 

xdens=3445 (4048) as provided in Davidson (2009b), and equation 3 

(SPA Risk LLC, 2009) is plotted in black using 2.6 million square feet 

of building floor area per census tract. Dashed lines in the graphs 

are equation 1 plus and minus one standard deviation (determined 

by way of numerical simulation). Equation 3 (SPA Risk LLC, 2009) is 

plotted in black. B and C are similar, except that the variable x%CIT

in Davidson’s (2009b) equation, representing the percentage of 

land area used for commercial, industrial and transportation (CIT) 

purposes, is varied by plus and minus one sigma (sigma of x%CIT), 

with equation 3 remaining the same in all plots. It can be seen that 

the median SPA Risk LLC (2009) model is higher than the Davidson 

(2009b) model by a factor of 2.8 at Modified Mercalli Intensity 

(MMI) VI and 2.3 at MMI VIII, while actually being lower (0.93) 

at MMI X. In B, corresponding to lower land use for commercial, 

industrial, or transportation purposes (CIT) (more representative 

of residential areas), the two models are in closer agreement, 

whereas C (representative of higher CIT uses) shows a somewhat 

greater difference in the two models.
Chapter P. Fire Following the HayWired Scenario Mainshock 383

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Ignitions

HayWired 

 rupture

<0.1

0.1–0.5

0.5–1.0

1.0–2.0

2.0–5.0

>5.0

Area

of map

CALIF

San

Francisco

Bay

PACIFIC

OCEAN

San 

Pablo

Bay

123° 122°

38°

37.5°

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

Figure 19. Map of San Francisco Bay region, California, showing estimated number of ignitions within 

fire station primary response areas (see fig. 8) following the hypothetical magnitude-7.0 mainshock of the 

HayWired earthquake scenario. Green indicates a small likelihood of ignition and dark red indicates five or 

more ignitions per area. The length of the Hayward Fault ruptured in the scenario is shown on the map.

Table 5. General sources of ignition after the momentmagnitude-6.7 1994 Northridge, California, earthquake. (ignition 

data from Scawthorn and others, 1998).

Source of ignition Percentage of ignitions

Electrical 56

Gas-related 26

Other 18

services by telephone, because street fire-alarm pull boxes 

have largely disappeared from the U.S. urban landscape. 

Attempts to report fires by calling 9-1-1 will likely be unsuccessful, owing to congestion of the system and overwhelmed 

9-1-1 dispatch centers. Citizens may then go in person to 

the nearest fire station, but such “still alarms” will largely be 

futile because the fire companies will have already responded 

(self-dispatched) to the nearest fire, if not dispatched by 9-1-1. 

Experience shows that citizens on scene will respond rationally (Van Anne and Scawthorn, 1994), rescuing as many 

people as possible and protecting neighboring buildings (exposures). Water supply from mains (discussed below) will often 

be unavailable.
384 The HayWired Earthquake Scenario—Engineering Implications

Reporting

As noted above, 9-1-1 dispatch centers will be overwhelmed and doing as much as possible to triage events and 

dispatch resources after the HayWired mainshock. Reports 

of fires during the initial period will be haphazard. Most fire 

departments do not have their own helicopters, and reporting 

by television news helicopters will be a valuable resource for a 

few major incidents, but not most. The first knowledge the San 

Francisco Emergency Operations Center had of the Marina fire 

following the 1989 Mw 6.9 Loma Prieta earthquake was from 

television news reports (despite several fire companies having 

responded). Quickly gaining an accurate and complete awareness of fires following an earthquake remains a challenge.

Fire Department Initial Response

The initial response of fire companies and personnel in the 

region of the HayWired scenario will be to protect themselves 

during violent shaking, and as soon as possible, open fire-station 

doors and remove firefighting apparatus (such as pumpers and 

ladder trucks). Different fire departments have somewhat varying earthquake procedures, but in general companies will remove 

firefighting apparatus to a predesignated location (often simply in 

front of the fire station), check the station for damage, and perform 

a radio check. By this time, typically within 5 minutes, they 

will either have self-dispatched to an observed smoke column, 

responded to a citizen still alarm, or been instructed to mobilize 

with other fire companies into a strike team.

Local fire department resources will be completely committed, and in need of assistance from outside of the San Francisco 

Bay region. The primary needs will be personnel, additional hose, 

hard suction hose (that is, hose that does not collapse when used to 

draft water from a source that is not already under pressure), firefighting foam, light equipment (gloves, hand tools, self-contained 

breathing apparatus [SCBA]), and heavy equipment (cranes, bulldozers, backhoes). Additional fire apparatus (pumpers and ladder 

trucks) will not be the primary need, but will still prove useful as 

extraregional strike teams arrive.

In the initial stage, personnel needs may be significantly 

supplemented by the Community Emergency Response Team 

(CERT) program, but will be more significantly strengthened by 

the recall of off-duty, trained firefighters. Off-duty personnel can 

be expected to have doubled staffing within 3–6 hours after the 

HayWired mainshock, and tripled it within 12–24 hours. How 

these personnel join their fire companies will be an issue, and 

there will be some inefficiencies as personnel join first available 

companies. Nevertheless, arrival of off-duty personnel will be very 

important to relieve on-duty personnel nearing physical limits.

Fire Spread

This analysis assumes that after the HayWired mainshock 

all fire-service resources will initially focus on firefighting, leaving search and rescue, hazmat response, and other 

emergencies until fires are brought under control. The initial 

668 ignitions will not all develop into large fires. Nevertheless, the normal 4-minute structural-fire response time will 

most likely be delayed. This delayed response, owing primarily to delayed reporting and dispatch, will result in many fires 

having grown such that a multiengine capacity is needed on 

arrival. Especially in low humidity conditions, an ignition that 

has not been suppressed can become a room-sized fire within 

several minutes and grow into a fully involved, single-family 

structural fire within several more minutes. To protect neighboring buildings, typically two or more companies are needed. 

If only one fire company is available, it is possible but unlikely 

that it might be able to protect two exposures using a monitor 

(water cannon) and hand line (fire hose) with civilian assistance. In fire following earthquake modeling, fires that have 

grown to exceed one engine company’s capabilities are termed 

large fires. The number of large fires for the HayWired mainshock is estimated based on several rules, including (1) availability of water for firefighting within each fire-response area 

and (2) ratio of ignitions to fire engines within each county 

(the latter to account for limited mutual aid), resulting in an 

estimate of 453 large fires (table 3). The large number of ignitions developing into large fires is a result of the high earthquake shaking intensities in the east bay combined with fuel 

provided by the high-density of wood construction between 

San Francisco Bay and hills to the east (East Bay Hills).

Lifelines

The performance of lifelines, such as water supply, gas, 

electric power, communications, and transportation, is integral 

to the firefighting process during fire following earthquake. A 

detailed discussion of lifeline performance for this scenario is 

beyond the scope of this report, which only briefly discusses 

selected lifelines with regard to fire following earthquake.

Water Supply

Water supply would be severely impacted by an 

earthquake like the HayWired scenario mainshock (see Porter, 

Water Supply, this volume). A significant part of the San 

Francisco Bay area’s water derives from the Sierra Nevada and 

is conveyed by several major canals and aqueducts, particularly 

the Mokelumne and Hetch Hetchy Aqueducts (fig. 20). In 

the last few decades, earthquake hazards mitigation has been 

largely focused on assuring delivery of water from these distant 

sources to the bay area. Major seismic retrofit programs have 

been completed by the East Bay Municipal Utilities District 

(EBMUD), Contra Costa Water District, and Marin Municipal 

Water District and are ongoing for the Santa Clara Valley Water 

District and the Hetch Hetchy system, which is owned by the 

City of San Francisco and serves that city as well as much of 

the west and south bay area (fig. 21).

These retrofit programs have focused on the dams, 

tanks, and major transmission lines; however, most of these 
Chapter P. Fire Following the HayWired Scenario Mainshock 385

water operators have found that significant upgrading of their 

extensive water distribution systems is beyond available 

resources. As a result, extensive portions of the water 

distribution systems are very vulnerable and likely to sustain 

a number of breaks in a large earthquake. The following 

was noted in a recent study by the Association of Bay Area 

Governments (2010):

. . . 68.1% of critical water system facilities . . . are 

exposed to extremely high shaking levels (peak 

ground accelerations, PGA, of greater than 60% g

with a 10% chance of being exceeded in the next 

50 years) . . . 95.2% of pipelines are estimated to 

be exposed to high shaking levels (PGA >40% g), 

and 62.8% are exposed to extremely high shaking 

levels (PGA >60% g) . . . [the Association of Bay 

Area Governments] has estimated that there could be, 

Figure 20. East Bay Municipal Utility District (EBMUD) map showing major water-supply systems of the San Francisco Bay 

area, California. A significant part of the bay area’s water comes from reservoirs in the Sierra Nevada. The Mokelumne Aqueduct 

supplies much of the water to the EBMUD service area, and the San Francisco Public Utilities Commission’s (SFPUC) Hetch Hetchy 

system primarily conveys water to San Francisco and the west and south bay. (From East Bay Municipal Utility District, 2017).

Area

of map

CALIF

60 KILOMETERS

30 MILES

0

0

20 40

10 20

for example, 6,000–10,000 water pipeline breaks or 

major leaks in an earthquake on the Hayward fault 

(compared to 507 in the Loma Prieta earthquake) . . . 

Pipe breaks in the 1989 Loma Prieta earthquake are 

shown in figure 22. Owing to their proximity to the Hayward 

Fault, east bay water distributions are particularly vulnerable 

(East Bay Municipal Utility District, 2011):

. . . earthquake hazard information . . . with more 

detailed information on materials and design of these 

facilities, and pipeline materials and connections 

associated with EBMUD, were used to estimate the 

problems associated with District facilities in a 1994 

study. At that time, EBMUD estimated that, should 

an earthquake occur on the Hayward fault EBMUD 

customers could have expected:
386 The HayWired Earthquake Scenario—Engineering Implications

Figure 21. Map of major water districts and water-supply reservoirs in the San 

Francisco Bay region, California. The length of the Hayward Fault ruptured in the 

hypothetical magnitude-7.0 mainshock of the HayWired earthquake scenario is shown 

on the map. (Water district and reservoir data from Bay Area Water Supply and 

Conservation Agency, [n.d.]; California Department of Water Resources, [n.d.]; and 

Datahub, [n.d.])

PACIFIC 

OCEAN

EXPLANATION

Major water districts

Water supply reservoirs (acre-feet)

Alameda County Water District (ACWD)

<10,000

>100,000

10,000–50,000

50,000–100,000

Contra Costa Water District (CCWD)

East Bay Municipal Utility District (EBMUD)

Marin Municipal Water District MMWD)

Napa Water Division (NWD)

San Francisco/Bay Area Water Supply 

 and Conservation District (SF/BAWSCA)

San Jose Water Company (SJWC)

Zone 7 (Z7)

HayWired rupture

Santa Clara Valley Water District (SCVWD)

0 10 20 30 40 KILOMETERS

0 5 10 15 20 MILES

Area

of map CALIF

122°

38°

37°

122.5° 121.5°

Z7
Chapter P. Fire Following the HayWired Scenario Mainshock 387

CONTRA COSTA

SAN FRANCISCO

ALAMEDA

MARIN

SANTA CLARA

SAN MATEO

SANTA 

 CRUZ

PACIFIC

OCEAN

SAN

FRANCISCO BAY

Area

of map CALIF

0

0

20 40 KILOMETERS

10 20 MILES

EXPLANATION

PGA (g)

Water-pipe

 breaks

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

123° 122°

38°

37°

Figure 22. Map of the San Francisco Bay region, California, showing breaks in 

water-distribution pipes from the moment-magnitude-6.9 1989 Loma Prieta earthquake 

overlaid on peak ground acceleration (PGA) for the event. g, acceleration due to 

gravity. (Data from Lund and Schiff, 1992.)

• Water cut off immediately to 63 percent of 

customers, including hospitals and disaster 

centers;

• Loss of water for fire hydrants and increased 

fire risk;

• More than 5,500 pipelines serving homes and 

businesses to break;

• A likelihood of untreated drinking water resulting 

from damage to four of six treatment plants;

• EBMUD’s most critical water conduit, the 

Claremont Tunnel, to be cut off west of 

the Oakland/Berkeley hills—affecting 70 

percent of EBMUD customers;

• Major damage to 65 water reservoirs and 

about 87 pumping plants that would require 

months, or even years, to repair;

• An estimated impact of $1.2 billion (in 1994 

dollars) to the regional economy owing to 

fire damage and lack of water; and

• Lack of water weeks after an earthquake, with 

some customers lacking service for as long 

as six months afterwards.

. . . As a result of the 1994 water system study, 

EBMUD developed a $189 million Capital 

Improvement program that, between 1995 and 2007, 

resulted in a system-wide mitigation of these impacts 

with the goal of providing an improved post-earthquake 
388 The HayWired Earthquake Scenario—Engineering Implications

A B

Area of B

San Francisco

Oakland

Alameda

Berkeley

Emeryville

37.5°

38°

122.5° 122°

N

20 KILOMETERS

0 5 10 MILES

Area 0 10

of map

CALIF

0 1 2 3 4 5 KILOMETERS

0 1 2 3 MILES

Figure 23. Maps of the San Francisco Bay region, California, showing water mains in areas of high liquefaction susceptibility in an 

earthquake (water mains were presumed to be under each road). A, Overview map of the San Francisco Bay region; B, detail map of 

parts of the Cities of, Berkeley, Emeryville, Oakland, and Alameda. Water-main susceptibility to liquefaction—red, very high; light red, 

high; yellow, moderate; pink, low. (Roads from U.S. Census Bureau, 2015; liquefaction data for most of the region from Witter and others, 

2006, which omits San Francsico County.)

functional water system with no redundancies. . . . In 

addition, portable equipment, such as pumps, hoses and 

generators, required to maintain operations following a 

disaster, has been procured. A number of other facilities 

still require seismic upgrades. . . Finally, roadway and 

building damage in EBMUD’s service area may result 

in delays in recovery that may necessitate on-going 

communication with service vehicles to ensure that 

repairs to pipelines and critical facilities are completed 

in a timely manner.

Although dating from 2011, these estimates (for 

distribution piping damage) actually rely on analyses 

developed in 1994. However, although key facilities such as 

the Claremont Water Tunnel, which crosses the Hayward Fault 

in Alameda County, have been improved, little has changed 

since 1994 regarding distribution piping, and the situation 

remains largely the same today (EBMUD, oral commun., 

October 30, 2014).

To examine the impacts of this situation following the 

HayWired mainshock, two sources of information were used to 

estimate the number and pattern of distribution pipe breaks and 

leaks. Data on pipe breaks and leaks from Porter (Water Supply, 

this volume) was used for one of the main water-distribution 

service areas affected by this earthquake, that of EBMUD. 

Outside of the EBMUD service area, a more approximate 

method was used to estimate water-main breaks and leaks, 

which consisted of assuming an “average” water main was 

under each street, and basing damage to water-distribution 

networks on that assumption. Sections of pipe in zones of high 

liquefaction susceptibility are shown in figure 23.

Based on this data, the HayWired mainshock devastates the 

water-supply infrastructure in the affected region, causing a total 

of about 9,400 buried water mains to require repairs,6 owing to 

a combination of fault rupture, shaking, and permanent ground 

displacement. The result is a lack of water supply to most hydrants 

in the east bay (fig. 24).

Without water infrastructure, firefighters will have to 

resort to alternative water sources, which in many cases 

require hard suction hose. Hard suction hose is a specific 

type of fire hose that allows a fire engine to create a vacuum 

in order to draft water from a source that is not pressurized 

(such as a swimming pool, river, or bay; fig. 25). The hose is 

reinforced with embedded metal rings to be circumferentially 

rigid so as to withstand an external pressure (such as internal 

vacuum). In the United States, the National Fire Protection 

Association specifies hard suction hose as standard equipment 

for class-A fire engines. However, in recent years some fire 

departments have adopted a practice of keeping hard suction 

hose in fire stations rather than carried on their engines. A 

limited survey of San Francisco Bay region fire departments 

conducted as part of this study found only about one-third of 

the departments could be confirmed as carrying hard suction 

hose on their engines.

6

The estimate of 9,400 buried water mains requiring repairs is the total from 

Porter (Water Supply, this volume) combined with the estimate in this paper 

based on street lengths.
Chapter P. Fire Following the HayWired Scenario Mainshock 389

PACIFIC

OCEAN

38°

123° 122°

37°

EXPLANATION

Water supply factor

HayWired rupture

<0.10

>0.90

0.10–0.20

0.20–0.30

0.30–0.40

0.40–0.50

0.50–0.60

0.60–0.70

0.70–0.80

0.80–0.90

Area

of map

CALIF

0

0

20 40 KILOMETERS

10 20 MILES

Figure 24. Map of the San Francisco 

Bay region, California, showing likelihood 

of the availability of water service within 

fire station Voronoi areas (a proxy for a 

fire station’s response area, see fig. 8) 

following the hypothetical magnitude-7.0 

mainshock of the HayWired earthquake 

scenario. Red areas approach zero 

likelihood of water service. The length 

of the Hayward Fault ruptured in the 

scenario is shown on the map.

Figure 25. Photograph of a San Francisco Fire Department, 

California, engine and firefighters using a hard-suction hose to 

draft water from a cistern (photograph by Charles Scawthorn).

Gas and Liquid Fuels

Gas and liquid fuel are used throughout many modern 

cities; there are buried major transmission lines (fig. 26) with 

associated terminals, refineries, and tank farms. A rupture of 

one large gas or liquid-fuel transmission line can be catastrophic 

and require the resources of a major fire department to respond. 

Similarly, a major petroleum refinery fire requires a major 

response, which may not be possible in the immediate aftermath 

of an earthquake. The San Francisco Bay area has five major 

petroleum refineries, which constitute 40 percent of California’s 

refining capacity. These refineries are concentrated at the north 

end of the HayWired scenario fault rupture. In the Mw 7.0 

scenario mainshock, these crucial refineries will experience 

severe shaking such that at least one (and possibly several) 

refineries will have major fires that may burn for several days, 

as has occurred in the past few decades in large earthquakes 

near refineries, such as the Mw 8.3 2003 Tokachi-Oki, Japan, and 

Mw 7.6 1999 İzmit, Turkey, earthquakes. In the bay area, and 

very significantly, gas distribution pipes underlie nearly every 

street, with connections to nearly every building. Ignitions from 

these sources typically account for about 25 percent of the total 

number of fire-following-earthquake ignitions.
390 The HayWired Earthquake Scenario—Engineering Implications

Figure 26. Maps showing gas and liquid-fuel transmission pipelines in the San Francisco Bay region, California. A, Pipelines 

overlaid on scenario peak ground acceleration distribution for the hypothetical magnitude-7.0 mainshock of the HayWired 

earthquake scenario on the Hayward Fault. B, Pipelines overlaid on zones of high liquefaction susceptibility. Length of fault 

rupture in the HayWired scenario shown by black lines. g, acceleration due to gravity. (Pipeline data from U.S. Department of 

Transportation, 2015; mainshock data from Aagaard and others, 2017; liquefaction data for most of the region from Witter and 

others, 2006, which omits San Francisco County.) 

San

Francisco

Oakland

SAN FRANCISCO BAY

122°30' 122°

38°

37°30'

San

Francisco

Oakland

SAN FRANCISCO BAY

122°30' 122°

0 20 MILES

Area 0 20 KILOMETERS

of map

CALIF

Peak ground acceleration (g)

0.4

0.1

0.2

0.3

EXPLANATION EXPLANATION

0.8

0.5

0.6

0.7

1.0

0.9

Liquefaction susceptibility

Low

Very high

High

Moderate

Pipelines

Gas pipeline

Liquid-fuel pipeline

HayWired rupture

Pipelines

Gas pipeline

Liquid-fuel pipeline

A B

HayWired rupture

Communications

Communications systems, particularly telephone networks, 

will sustain some damage but perhaps not enough to reduce 

functionality following the HayWired mainshock. However, 

congestion will reduce functionality to a great degree, for several 

hours or more. This lack of telephone service will result in delayed 

reporting of fires, with consequences as discussed above.

Transportation

The transportation system most relevant to fire following 

earthquake is the road network, which is most vulnerable at 

bridge crossings. The California Department of Transportation 

(Caltrans) has nearly completed a major seismic review and 

retrofit of all bridges under its purview (California Department 

of Transportation, 2014). Although the local road and highway 

networks are sufficiently dense in most places that redundant 

pathways exist within the San Francisco Bay region, heavy 

traffic following a major earthquake could significantly 

impede emergency responders. Emergency strike teams 

arriving from outside of the bay region may also be delayed 

owing to traffic disruptions at several chokepoints at the 

boundaries of the region, including U.S. Route 101 north of 

the Golden Gate Bridge and south of San Jose and westbound 

Interstates 80 and 580.
Chapter P. Fire Following the HayWired Scenario Mainshock 391

Regional and State Response

The HayWired scenario mainshock primarily affects 

California Governor’s Office of Emergency Services (Cal 

OES) region II (fig. 27). The most likely sources of regional 

resources will be a number of strike teams assembled by 

Cal OES from the Central Valley, arriving in the affected 

region within 6–24 hours. Some of these will be brush 

rigs (wildland fire engines specifically designed to assist 

in fighting wildfires), which are more suited to wildland 

than urban-structural fires. By the time of their arrival in 

the region affected by the HayWired mainshock, the issue 

will be large fires that have grown into conflagrations, 

constituting a much larger challenge.

Outside of region II, Cal OES is likely to stage a 

number of strike teams, drawn generally from southern 

California and the Central Valley. Assembling 100 strike 

teams, consisting of approximately 500 pumpers and other 

firefighting apparatus, as well as firefighters, is easily 

within Cal OES capability, and several times this number of 

people and equipment can be managed if necessary. Within 

about 12 hours of notification, 100 strike teams can arrive 

at staging areas, with probably another 100 teams arriving 

during the next week. In our analysis, however, mutual 

aid will be largely ineffective in the immediate period 

following the HayWired mainshock, owing to the following 

factors:

• Delayed response time to fire scene:

• Fire departments in the San Francisco Bay area 

(for example, peninsular and Walnut Creek-Concord area) will conserve resources and not be able 

to respond quickly to the east bay.

• Mutual aid will have to come from farther afield 

(northern California, southern California, and the 

Central Valley), requiring at least several hours, 

and will be arriving at night in blackout conditions (owing to wide-scale failure of electric 

power).

• Water shortages:

• Water-tanker truck refills will be at some distance 

from fires, resulting in delays. Although a few fire 

departments (Berkeley, Oakland, Vallejo, and San 

Francisco) have portable water-supply systems 

(PWSS), these are currently inadequate for the 

demands that will be placed on them.

• Aerial firefighting effectiveness in urban areas is 

currently unknown.

• Firefighting foam is a “force-multiplier,” greatly 

increasing the effectiveness of a hose stream. 

However, current local fire-department supplies 

of foam are limited.

Figure 27. Map showing California Governor’s Office of Emergency 

Services mutual-aid regions (from California Governor’s Office of Emergency 

Services, 2017).

• Access:

• The east bay hills are quite steep, with relatively narrow and winding roads that hinder access.

• The hills are also heavily vegetated which, combined 

with prevailing winds and topography, will greatly 

enhance fire spread and impede firefighting.

• Supplying water to higher elevations in the hills will 

be very difficult.

• Limited access to the San Francisco Bay area.

Final Burned Area

The 453 large fires estimated to follow the HayWired 

scenario mainshock will be spread over a large area of varying 

building density and availability of water for firefighting. The 

number of large fires that will grow into conflagrations, and 

the ultimate extent of the final burned area, will depend on the 

building density, weather conditions, initial unfought size of the 

fire before fire department response, number of responding fire 
392 The HayWired Earthquake Scenario—Engineering Implications

engines and water supply available for firefighting associated 

with each large fire. Under the assumed scenario conditions, 

it is estimated that of the 453 large fires, about 321 will grow 

to a size such that they will spread beyond the city block of 

origin (in other words, become a conflagration), with the final 

burned area then largely dependent on fires crossing streets 

and other firebreaks. Based on the probability of fire crossings, 

the estimated final burnt area is approximately 79 million 

square feet of residential and commercial building floor area 

equivalent to more than 52,000 single-family dwellings.7 This 

loss is equivalent to a total building replacement value of almost 

$16 billion8 (2014 dollars), representing about 2 percent of the 

entire exposed value (fig. 28, table 4), with most of the loss 

concentrated in Alameda County.

Under the assumed wind and humidity conditions during 

the HayWired mainshock, the areas of most concern for fire 

following earthquake are parts of Alameda and Santa Clara 

Counties, where large areas of relatively uniform, dense, 

low-rise buildings provide a fuel bed such that dozens to 

hundreds of large fires are likely to merge into many dozens of 

conflagrations, destroying tens of city blocks. Two particular 

concerns exist in this regard—(1) if Diablo winds are present 

(which is not assumed in this scenario), losses could be much 

larger; and (2) if extremely calm conditions exist (which is 

also not assumed in this scenario), a symmetric wind pattern 

could develop where uprising air from conflagrations draws 

air inward (an example of the stack effect) to create a selfsustaining feedback situation (commonly termed a firestorm), 

which can be very destructive. Although relatively unlikely, 

this potential should not be ignored. The first concern is a 

larger mass conflagration, fed by higher winds; the second is 

potentially much worse. Both would be catastrophic.

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Fire losses, in 

millions of dollars

HayWired 

 rupture

0

1–10

10–50

50–100

100–500

500+

Area

of map

CALIF

San

Francisco

Bay

PACIFIC

OCEAN

San 

Pablo

Bay

123° 122°

38°

37.5°

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

7

An average single-family equivalent dwelling is 1,500 square feet of residential 

or commercial occupancy floor area, and this measure is used to normalize and 

communicate overall building losses in a readily comprehensible way. A loss 

of 1.5 million square feet of residential and commercial building for example is 

equivalent to 1,000 single-family dwellings. Most people can more readily interpret 

the loss of 1,000 houses than 1.5 million square feet of floor area. 8

Based on a replacement cost of $200 per square foot. Note this is a conservative 

estimate of replacement cost. Hogan (2014) estimates that construction in San 

Francisco can cost $300 per square foot, not counting subsidies, permits, and 

selling expenses.

Figure 28. Map of the 

San Francisco Bay region, 

California, showing final 

burned-area losses (in millions 

of 2014 U.S. dollars) from fire 

following earthquake after the 

hypothetical magnitude-7.0 

mainshock of the HayWired 

earthquake scenario. Areas 

shown are fire station 

Voronoi areas (a proxy for a 

fire station’s response area, 

see fig. 8). The length of the 

Hayward Fault ruptured in the 

scenario is shown on the map.
Chapter P. Fire Following the HayWired Scenario Mainshock 393

Another major concern is the very large concentration of 

high-rise buildings in the financial district of San Francisco. 

Firefighting under postearthquake conditions in more than one 

of these buildings could be beyond the resources of the San 

Francisco Fire Department, so the loss of several high-rises is 

quite possible.

Uncertainty, Verification, and Validation

There is considerable uncertainty in the estimates of 

ignitions and final burned area presented above. The United 

States has been very fortunate in having few large earthquakes 

within urban areas in the past 50 or more years, so the 

experience database for ignitions following earthquakes is 

relatively sparse and has significant uncertainty, as can be 

seen in the confidence bands shown in figure 18, which span 

an order of magnitude. Moreover, the majority of data for 

ignitions (178 of 244 or 73 percent) are drawn from very 

early morning earthquakes, a time of day associated with 

low normal fire occurrence (U.S. Fire Administration, 2008). 

A full exploration of uncertainty is beyond the scope of the 

present study, but the number of ignitions estimated to follow 

the HayWired mainshock (668) could vary by hundreds, 

depending on many factors.

Regarding verification (accuracy of the estimate) and 

validation (meeting the intended need) of estimates of ignitions 

and final burned area in the HayWired scenario, a large earthquake 

like the Mw 7.0 mainshock is a rare event, and the postearthquake 

fire situation even rarer, so that verification and validation is very 

challenging.

Verification is particularly difficult, owing to the sparsity of 

data and experience. Qualitatively, the following experiences tend 

to support the scenario losses presented above:

• Precedent—several events support the potential for large 

postearthquake losses, including in the HayWired study 

region:

• Catastrophic fires following the 1906 San Francisco 

(Mw 7.8) and 1923 Tokyo (Mw 7.9) earthquakes. 

• More than 100 ignitions (each) following the 1971 

San Fernando, California (Mw 6.6); 1994 Northridge, 

California (Mw 6.7); and 1995 Kobe, Japan (Mw 6.9), 

earthquakes.

• At least 348 ignitions, more than any other earthquake in history, occurring in the 2011 Tohoku, 

Japan (Mw 9.0), earthquake and tsunami (Anderson 

and others, 2016)

• The 1991 East Bay Hills Fire (East Bay Hills 

Fire Operations Review Group, 1992), a massive 

conflagration centered in the study region that 

overwhelmed fire and water agencies.

• Quantitatively, the methods in this study were used to 

hindcast (estimate):

• Ignitions in previous California earthquakes (tables 6–8 

and fig. 29) with reasonable agreement. The base data is 

dataset A in Davidson (2009a).

• Large fires for the 1989 Loma Prieta (Mw 6.9) and 

2014 South Napa (Mw 6.0), California, earthquakes, the 

only events for which sufficient data on all aspects (fire 

resources, firefighting water availability, and so forth) 

was available.

Although this quantitative verification is quite limited, it 

tends to confirm the reasonableness of the estimates and also 

illustrate the uncertainty. Both the SPA Risk LLC (2009) and 

Davidson (2009b) ignition models produce enough fires following the HayWired mainshock to overwhelm currently available 

firefighting resources in the San Francisco Bay region, so the 

conclusions of this chapter would be the same regardless of 

which model was used.

Validation (meeting the intended need) for fire following 

earthquake in the HayWired scenario is also a challenge 

but toward this end the above methodology and findings 

were presented to a workshop on fire following earthquake, 

held at the University of California, Berkeley, Richmond 

Field Station on October 29, 2014. The workshop was 

attended by 76 personnel, representing 31 fire departments 

Table 6. Summary count of ignition data from California earthquakes since 1971 (SPA Risk LLC, 2009, 2014).

Earthquake Number of ignitions Date source1

1971 San Fernando 91 Unpublished data

1983 Coalinga 3 Scawthorn (1984)

1984 Morgan Hill 6 Scawthorn (1985)

1986 North Palm Springs 1 Earthquake Engineering Research Institute (1986)

1987 Whittier Narrows 20 Wiggins (1988)

1989 Loma Prieta 36 Mohammadi and others (1992); Scawthorn (1991)

1994 Northridge 81 Scawthorn and others (1997)

2014 Napa 6 SPA Risk LLC (2014)

Total number of ignitions 244

1

See SPA Risk LLC (2009, 2014) for detailed references.
394 The HayWired Earthquake Scenario—Engineering Implications

Table 7. Hindcast (estimated) ignitions for selected California earthquakes (1984–2014), using equations from Davidson (2009b) and 

SPA Risk LLC (2009) (see discussion in text and equations 1 and 3, respectively).

[NA, not applicable]

Earthquake Observed 

ignitions

Davidson (2009b; model A.NB2) 

estimated ignitions

SPA Risk LLC (2009) estimated 

ignitions

1984 Morgan Hill 41 1.2 4.0

1986 North Palm Springs 1 2.1 4.1

1987 Whittier 13 22.2 72.1

1989 Loma Prieta 36 29.5 15.9

1994 Northridge 81 99.0 166.4

2014 Napa 6 NA 6.24

1

There were four structural ignitions in Morgan Hill and two in San Jose in the 1984 earthquake. The total of six is indicated in table 6. For validation, only 

Morgan Hill was modeled, so table 7 shows only four observed ignitions.

Table 8. Observed and hindcast (estimated) large fires for 

selected northern California earthquakes.

Fire type Observed Estimated

1989 Loma Prieta earthquake1

Total ignitions 31 24

Large Fires 12 Negligible

Conflagrations 1? Negligible

2014 Napa earthquake

Total ignitions 6 6.24

Large Fires 1 Negligible

Conflagrations ? Negligible

1

Based on 1990 census population (dataset A in Davidson, 2009a).

Figure 29. Observed and hindcast (estimated) ignitions for selected California earthquakes (1984–2014), using equations from Davidson 

(2009b) and SPA Risk LLC (2009) (see discussion in text and equations 1 and 3, respectively; see table 7 for data). A, Number of ignitions plotted 

on arithmetic axes. B, Number of ignitions plotted on log-log axes.

and emergency response agencies. The workshop was 

subsequently independently evaluated by Allison Madera 

and others (Natural Hazards Center, University of Colorado 

Boulder, written commun., 2016), who found “almost all 

of the survey respondents (95.8 percent) indicated that they 

believed the HayWired scenario accurately represented what 

a fire following earthquake incident might look like in the San 

Francisco Bay Area.”

Impacts of Fire Following Earthquake

This section discusses the human and economic impacts 

of fire following earthquake. Not well understood, but 

discussed here, is the major impact such events can have on 

the insurance industry.

line of perfect agreement

line of perfect agreement

A B

200

180

160

140

120

100

100

10

1

80

60

40

20

0 20 40 60 80 100 1 10 100

Estimated number of ignitions

Observed number of ignitions

EXPLANATION

Davidson (2009b)

SPA Risk LLC (2009b)
Chapter P. Fire Following the HayWired Scenario Mainshock 395

Human Impacts

Estimating the fatalities associated with the fires following 

the HayWired mainshock is very problematic. A very simple 

approach is taken here; in the 1991 East Bay Hills Fire, which 

destroyed approximately 3,500 dwellings, 25 people perished. 

The building losses projected here are approximately 20 times 

larger. In proportion, there would be hundreds of deaths caused 

by fire following the scenario mainshock. Such an approach is 

admittedly very simplistic and does not account for the potential 

overwhelming of the regional emergency medical capacity in a 

large earthquake, as opposed to the isolated nature of the 1991 fire. 

Injuries would probably be an order of magnitude greater. For the 

HayWired scenario, an estimated 500,000 to 1 million people will 

need shelter as a result of fire following earthquake.

Economic and Insurance Impacts

Regarding the estimated $16 billion value of the structures 

burned by fire following earthquake in the HayWired scenario, 

the value of contents and other improvements (for example, 

landscaping) will add to this loss. For example, the contents of 

residences are commonly insured to 70 percent of the replacement 

cost of the building, so content loss could realistically amount to 

an additional $11 billion. An additional loss is loss of use; that 

is, the people normally living in these destroyed buildings (or 

conducting business in them) must find other accommodations, 

which most likely would not be available in the San Francisco 

Bay region given the impact of the scenario mainshock. This loss, 

termed “additional living expenses” by the insurance industry, can 

be consequential, equivalent to many tens of billions of dollars. 

Accounting for this can be difficult; if people who have lost their 

dwellings are housed in hotels at insurance company expense, the 

loss is simply the hotel bill. If people are forced to live in tents 

following the mainshock, at public expense, there may be no bill.9

In such a situation, people have not paid for their tents, and cannot 

therefore claim against the insurance company for a financial 

loss. However, they have lost value in services (of their house) 

approximately equivalent to the rental value of their house (minus 

the rental value of the tent) but would not be compensated for 

those losses. Nevertheless, this is a loss that should be accounted 

for, overall. One approximation is to estimate the additional 

living expenses in proportion to the typical limit of liability for 

homeowner’s insurance—20 percent of the replacement cost of 

the buildings, which for the HayWired scenario is about $3 billion.

Because virtually all buildings and contents in the United 

States are insured for fire, and U.S. insurance contracts include 

losses from fire following earthquake under the fire policy, 

the direct fire-following-earthquake losses for the HayWired 

mainshock are likely to result in a loss approaching $30 billion 

of insurance claims. Because $30 billion amounts to nearly 

6 percent of the gross domestic product of the San Francisco 

Bay region—and shaking, liquefaction, and landslide-related 

9

Note that public authorities may attempt to recoup their expenses, if the 

sheltered people are insured.

damage adds to the demands for construction services—it is 

likely that demand surge will occur (the temporary increase 

in construction costs following major natural disasters). 

Losses of this magnitude are probably sustainable by the 

U.S. insurance industry (the $60 billion in insured claims 

arising from the September 11, 2001, attacks were handled 

without great strain). The 1991 East Bay Hills Fire, in which 

3,500 homes were lost, at the time resulted in about $1 billion 

in insured losses—the event projected here is 23 years of 

inflation later and about 60 times as large. In summary, losses 

from fire following earthquake are likely to be the largest part 

of the insured losses in the scenario event, and would be one 

of the largest single-loss events in the history of the insurance 

industry.

Another aspect of the economic impacts is the loss of 

real-estate tax revenues. A loss of tens of billions of dollars 

in the value of property improvements is likely to result in 

perhaps a decrease of a billion dollars in regional real-estate 

tax revenues for several years, directly attributable to fire 

following earthquake.

Mitigation of Fire Following Earthquake

Mitigation of fire following earthquake has been extensively 

discussed elsewhere (Scawthorn and others, 2005). Only some 

limited observations specific to the HayWired scenario are 

provided here.

Fire-Service Opportunities

The fire service in California is perhaps the most experienced 

in the world in dealing with large conflagrations, owing to the 

wildland fires recurring annually in the region. Fire departments 

have also been relatively diligent in preparing for a large earthquake—the CERT program is a model in that regard. However, 

the following opportunities for improvement are noted:

• Improvements are needed in the ability to more quickly 

assess the event and facilitate fire incident reporting. 

Reconnaissance using unmanned aerial vehicles, 

as well as cellular text-messaging incident reports 

directly to a 9-1-1 portal, could be developed and 

operationalized.

• Alternative water sources need to be better identified 

and access and water movement capabilities enhanced. 

Hard suction hoses could be carried on all engines. 

Large diameter hose (LDH) systems, comparable to San 

Francisco Fire Department’s PWSS (Scawthorn and 

others, 2006), could be developed on a regional basis. In 

this regard and as part of the HayWired scenario project, 

the earlier mentioned October 29, 2014, workshop was 

held at the University of California’s Richmond Field 

Station. The four existing PWSSs, belonging to Berkeley, 

Oakland, San Francisco, and Vallejo Fire Departments 
396 The HayWired Earthquake Scenario—Engineering Implications

(fig. 30) were brought together and used in a joint exercise 

for the first time.

• A regional multidisciplinary task force could be formed 

within the fire service, to examine urban conflagration 

potential in more detail.

Water-Service Opportunities

Water-service providers in California have worked to prepare 

for a major earthquake, but more can still be done (Scawthorn, 

2011a,b). One overriding issue with regard to fire following 

earthquake is that water agencies typically are not institutionally 

responsible for fire protection. That is, although they provide 

hydrants, if the hydrants fail to supply water, the water agency is 

not responsible. Therefore, water-system upgrades are typically 

more oriented to maintenance of customer service and minimizing 

direct damage to the system than to maximizing water-supply 

reliability. A mandate could be developed to make water agencies 

more responsive to this need. Given the realities of the limited 

water supply in California, this may be unlikely to occur, but 

should at least be raised for discussion. A real way in which 

water agencies could be more responsive to the problem of fire 

following earthquake is if each agency were to configure and 

upgrade their system so as to provide a “backbone” system of 

water mains of high seismic reliability, which would both help 

ensure the reliability of water services to communities and provide 

fire departments with sources to draw water from to suppress a 

conflagration using an LDH system. This entire aspect is discussed 

in more detail in Scawthorn (2011a,b).

Building-Standards Opportunities

Since the 1906 San Francisco earthquake, significant 

progress has been made in making buildings more earthquake 

and fire resistant, yet there are still opportunities for improvement. For example, residential fire sprinklers are now required 

by many communities for new construction (at a cost less than 

the carpeting), but generally there are no requirements for 

existing homes (where the cost is significantly higher). Similarly, seismic retrofitting of existing buildings is increasingly 

being considered for older commercial buildings, but very 

few communities have requirements for existing single-family 

homes. Seismic retrofitting would reduce the number of postearthquake ignitions. Both seismic retrofitting and installation 

of fire sprinklers could be more widely mandated for existing 

buildings.

Energy-Industry Opportunities

The gas industry could contribute significantly to reducing the fire following earthquake by developing a program 

to either install automated gas shut-off valves (fig. 31) or 

redesign gas meters to have seismic shutoffs, particularly in 

densely built up areas. If the number of ignitions could be 

reduced by 25 percent, the number of large fires would be 

decreased in greater proportion and the total losses further 

reduced. For example, the City of Los Angeles Fire Department has shown leadership in seeking legislation to require 

gas shut-off valves. Note that the gas industry in Japan moved 

to do this proactively following the 1995 Kobe earthquake.

Figure 30. Photograph of four portable water-supply systems, belonging to the Berkeley, 

Oakland, San Francisco, and Vallejo Fire Departments, at the edge of San Francisco Bay 

in Berkeley, California, on October 29, 2014. This was the first time the four systems were 

brought together and used in a joint exercise. (Photograph by Charles Scawthorn.)
Chapter P. Fire Following the HayWired Scenario Mainshock 397

In regard to electricity, opportunities to reduce fire 

following earthquake are problematic. Electric power often 

fails in large earthquakes, owing to automatic system trips, 

as well as damage to the system. However, the power failure 

usually takes several seconds, during which power is a source 

of many ignitions. Certain electric appliances (such as those 

with heating elements) can still cause fires even after power 

is cut. Large-scale intentional curtailment of electric power 

would be problematic, because some communications systems 

and other essential equipment would not be useable.

Petroleum refineries and related facilities in the San 

Francisco Bay area are likely to sustain major fires in the 

HayWired scenario. The degree of earthquake preparedness 

of these facilities is generally unclear and may need to be 

reviewed.

Conclusion

That fire following earthquake is a significant problem in 

California is confirmed historically, by recent events, and by 

analysis. The Mw 7.0 mainshock of the HayWired earthquake 

scenario is estimated to result in approximately 668 ignitions, 

such that in Alameda, Contra Costa, and Santa Clara Counties 

dozens to hundreds of large fires are likely to merge into 

numerous conflagrations destroying tens of city blocks, with 

several of these potentially merging into one or more super 

conflagrations, destroying hundreds of city blocks. The ultimate 

burned area is estimated to total 79 million square feet of 

residential and commercial building floor area, equivalent to 

more than 52,000 single-family dwellings, with property losses 

approaching $30 billion. This loss is virtually fully insured and 

would be one of the largest single-loss events in the history of 

the insurance industry. Other economic impacts include the 

loss of perhaps $1 billion in local tax revenues. A number of 

opportunities exist for mitigating fire following earthquake, 

including greatly enhancing the potential postearthquake supply 

of water for firefighting and the use of automated gas shut-off 

valves, or seismic shut-off meters, in densely built areas.

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Chapter Q

How Many Injuries Can Be Avoided in the HayWired 

Scenario Through Earthquake Early Warning and Drop, 

Cover, and Hold On?

By Keith A. Porter1 and Jamie L. Jones2

1

University of Colorado Boulder.

2

U.S. Geological Survey.

occurring on April 18, 2018, at 4:18 p.m. on the Hayward 

Fault in the east bay part of California’s San Francisco Bay 

area. The hypothetical earthquake has its epicenter in Oakland, 

and strong ground shaking from the scenario causes a wide 

range of severe impacts throughout the greater bay region.

Background

Earthquake early warning (EEW) can provide several 

seconds advanced warning before the arrival of earthquake 

waves that cause strong ground motion. In that time, a person 

who receives the warning can take self-protective action. As 

of this writing, the American Red Cross, Earthquake Country Alliance, and others recommend a sequence of actions to 

protect oneself called “drop, cover, and hold on” (DCHO). To 

DCHO, a person drops to hands and knees on the floor, covers their head and neck with their arms, and if there is sturdy 

furniture such as a table nearby under which to take shelter, 

crawls there and holds on to the table legs to ensure that the 

cover does not slide away from the person. DCHO is also used 

as shorthand to cover a variety of additional advice for what to 

do during earthquake shaking in a variety of situations, such 

as outdoors, in a vehicle, and in a stadium. The Earthquake 

Country Alliance advises people to DCHO as a means to 

reduce the risk of injury, especially from falling objects (see, 

for example, https://earthquakecountry.org/step5/).

If DCHO reduces the risk of injury, then using EEW to 

get to cover sooner, before earthquake shaking arrives and 

causes items to fall, should further reduce injuries in earthquakes. To our knowledge no one has quantified the efficacy 

of DCHO; we do not know by how much DCHO reduces 

earthquake injury risk. We can establish an upper-bound 

estimate of its efficacy by assuming that DCHO prevents all 

earthquake injuries associated with falling, building contents, 

building nonstructural components, and actions such as jumping out of windows or attempting to catch falling objects.

Abstract

One of many potential benefits of earthquake early warning (EEW) is the reduction in injuries because people have 

more time to perform the self-protective series of actions 

called “drop, cover, and hold on” (DCHO). We offer an initial 

estimate of the potential benefit of EEW and DCHO in the 

HayWired earthquake scenario, both in terms of avoided 

injuries and the acceptable cost to avoid those injuries from 

the perspective of the U.S. Government. The HayWired 

scenario examines a hypothetical earthquake (mainshock) 

with a moment magnitude (Mw) of 7.0 occurring on April 18, 

2018, at 4:18 p.m. on the Hayward Fault in the east bay part of 

California’s San Francisco Bay area. Using estimates of EEW 

warning time in the HayWired scenario, new observations of 

the time required to DCHO, and Hazus-MH (Federal Emergency Management Agency, 2012) estimates of the number of 

nonfatal injuries in the scenario, we estimate that out of 18,000 

estimated nonfatal injuries in the HayWired scenario, as many 

as 1,500 people who would otherwise be injured could complete the DCHO actions before the arrival of strong motion 

and avoid injury. The estimated value of these prevented 

injuries is approximately $300 million. This is not the same 

as the probabilistic benefit of EEW and DCHO, because it is 

conditioned on the occurrence of a single earthquake among 

many whose occurrence is uncertain. However, it is a useful 

index of the potential benefit of EEW. The figures—1,500 

avoided injuries and $300 million value of statistical injuries 

avoided—represent upper bounds because we do not know 

how many people could realistically receive EEW and how 

effectively DCHO prevents injuries.

Introduction

The HayWired scenario examines a hypothetical earthquake (mainshock) with a moment magnitude (Mw) of 7.0 

The HayWired Earthquake Scenario—Engineering Implications

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–I–Q

[Also see https://doi.org/10.3133/sir20175013 ]
402 The HayWired Earthquake Scenario—Engineering Implications

Objectives

Our objectives in this study are twofold. First, estimate 

the benefit of earthquake early warning in terms of the number 

of human injuries that could be avoided if the HayWired 

mainshock were to occur after the population of the San Francisco Bay region were all trained and drilled on DCHO and 

equipped with EEW. Second, estimate the economic value of 

the avoided injuries. We do not examine other applications of 

EEW such as stopping trains.

Literature Review

EEW has been in development since at least 1995, among 

its many goals is reducing deaths and injuries (see Anderson 

and others, 1995; Lee and others, 1996; or Gasparini and 

others, 2007). EEW has been implemented in Japan and is 

available there as a free app for Android and iOS devices, 

called Yurekuru Call (Sung, 2011). The U.S. Geological Survey (USGS), along with a coalition of university partners, is 

developing and testing an EEW system called ShakeAlert for 

the West Coast of the United States (Burkett and others, 2014). 

If EEW can aid people in avoiding injuries, it is possible 

to assign an economic value to the avoided injuries. Since 

1993, the U.S. Government has been required to demonstrate 

the cost effectiveness of new regulations, including those 

intended to enhance public safety (Clinton, 1993). To meet 

this requirement an acceptable cost to avoid statistical deaths 

and nonfatal injuries had to be established. “Statistical deaths 

and injuries” means deaths and injuries to unknown persons 

at some uncertain future date, as opposed to the value of a 

particular person’s life or present or past injuries.

Different agencies of the U.S. Government assign these 

values differently but produce generally similar values. The 

U.S. Department of Transportation recently assigned a value 

of $9.1 million per statistical fatality avoided in 2013 U.S. 

dollars (USD), lesser values for nonfatal injuries, and an inflation factor of 1.18 percent per year for years after 2013 (U.S. 

Department of Transportation, 2014). The degree of the nonfatal injuries is measured using the Abbreviated Injury Scale 

(AIS) of the Association for the Advancement of Automotive 

Medicine (Gennarelli and Wodzin, 2005).

In Natural Hazard Mitigation Saves—An Independent 

Study to Assess the Future Savings From Mitigation Activities 

(Multihazard Mitigation Council, 2005), Porter and colleagues 

employed Hazus-MH’s (Federal Emergency Management 

Agency, 2012) estimates of deaths and injuries to estimate 

the cost effectiveness of natural-hazard mitigation, producing a value of $4 saved for every $1 invested by the Federal 

Emergency Management Agency (FEMA) on natural-hazard 

mitigation. To produce this value, the Hazus-MH 4-level 

injury severity scale was related to the 6-level scale of the AIS, 

using the definitions for each scale (Multihazard Mitigation 

Council, 2005).

The potential benefits of avoiding earthquake injuries are 

great. Porter and others (2006) show that the injuries experienced in the Mw 6.7 January 17, 1994, Northridge earthquake 

in southern California had an economic value of $2–3 billion 

in 2005 USD—that is, if all of the injuries in the 1994 Northridge earthquake could have been prevented, an expense of 

$2–3 billion by the U.S. Government would have been justifiable. That work drew on Shoaf and others (1998), who offer 

statistics on the number, severity, and causes of injuries in several earthquakes, including the 1994 Northridge earthquake. 

They show that 55 percent of injuries in that earthquake were 

caused by nonstructural damage, 22 percent by the “physical force of the earthquake,” 12 percent by behavior such as 

jumping out a window, 1 percent by “structural objects,” and 

the 10 percent by other causes. These statistics can provide 

insight into the fraction of injuries that might realistically be 

prevented or avoided by DCHO. Johnston and others (2014) 

provide analogous statistics for the Mw 7.1 September 4, 2010, 

Darfield and Mw 6.3 February 22, 2011, Christchurch, New 

Zealand, earthquakes.

Practicing DCHO is a key component of earthquake drills 

during annual ShakeOut exercises, which are held around the 

world. Practicing DCHO is the first item covered at ShakeOut.

org (https://www.shakeout.org), which coordinates global 

ShakeOut registration and provides instructions and other 

resources. McBride and others (2014) evaluated the 2012 New 

Zealand ShakeOut and reported on the degree to which participants performed DCHO: 

Over 60 percent of people seen by observers actively 

participated in drop, cover, and hold on. Of those 

who did not participate, disability and age (too 

young and too old) were reported to have been factors preventing participation. 

McBride and others (2014) also reported that embarrassment played a role in some people not participating. Becker 

and others (2017) reported higher participation in DCHO in 

the 2015 New Zealand ShakeOut, with 65 percent of respondents indicating that everyone they saw was performing 

DCHO and approximately 35 percent of people responding 

“not everybody” or “no-one.” The authors reported a 10-percent drop in people’s reluctance to practice DCHO because of 

disability and suggest that messaging from the New Zealand 

Ministry of Civil Defence and Emergency Management may 

have helped in addressing concerns about how to perform 

DCHO with impaired mobility. It is also possible that experiencing the 2012 New Zealand ShakeOut may have helped 

people be less embarrassed about performing DCHO during 

the 2015 ShakeOut. 

Lindell and others (2016) offer insight into what people 

do in actual earthquakes, having surveyed 257 people who 

experienced the 2011 Christchurch, New Zealand, earthquake 

and 332 people who experienced the 2011 Tohoku, Japan, 

earthquake. A considerable part of both groups of respondents 

reported their initial response to shaking was to freeze in place 

(38 percent of Christchurch respondents) rather than taking 
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 403

self-protective actions such as DCHO (only 17 percent of 

Christchurch respondents). However, it is noteworthy that as 

of 2011, New Zealand had not yet participated in a ShakeOut 

drill (which tends to promote training and practice of DCHO), 

so it is perhaps to be expected that few people completed 

DCHO. Lambie and others (2017) used closed-circuit television recordings to observe the reactions of 213 people during 

the 2011 Christchurch earthquake; none performed DCHO. 

Methodology

The New Zealand and Tohoku experiences suggest that 

before ShakeOut drills became common, few people actually completed DCHO in an earthquake and that even during 

ShakeOut drills some people do not attempt to DCHO. An 

EEW system that recommends DCHO might increase DCHO 

participation in two ways—(1) by giving warning time so that 

people can complete DCHO before strong shaking begins (and 

while they still can do it) and (2) by reminding people what 

to do as part of the warning message. Suppose that training, 

EEW messaging, and other preparations were able to encourage action in an earthquake, such that nearly everyone would 

at least attempt DCHO. What might be the upper bound of 

benefit from combining DCHO and EEW, in terms of reduced 

injuries in an actual earthquake? 

To estimate the number of avoided injuries, one can estimate the number of people who can complete DCHO actions 

after they receive an EEW message and before strong ground 

motion arrives at their location. That estimate requires an 

estimate of the time it takes people to complete DCHO, which 

we calculated from a survey of more than 400 people who 

took online training and then timed themselves performing the 

actions. The estimate also requires one to estimate the number 

of people who would have been injured without EEW and 

DCHO. We estimated those quantities on a geographic basis 

using Hazus-MH. Finally, the estimate of avoided injuries 

requires an estimate of what fraction of injuries can be avoided 

by successfully completing DCHO. Estimating that quantity 

is problematic. It seems prudent to assume that DCHO cannot 

help much in the event of building collapse but that DCHO 

can prevent some large fraction of nonfatal injuries in the 

absence of collapse; we make a reasonable guess. Details of 

the methodology follow.

Estimating Avoided Injuries

Our goal is to produce an upper-bound estimate of 

how many fewer people would be nonfatally injured in the 

HayWired scenario if everyone in the San Francisco Bay 

region received EEW and had been well trained and drilled 

on DCHO. We refer to the reduction as the injury-prevention benefit from the combination of EEW and DCHO, or 

EEW+DCHO. We denote the benefit by B. We associate earthquake deaths entirely with structural collapse and assume that 

DCHO would prevent few if any of them, so the EEW+DCHO 

benefit would be considered to accrue only from the reduction 

in nonfatal injuries from causes other than structural collapse. 

We estimate B in any particular location i as the product of 

three quantities:

•	 I=number of nonfatal injuries under as-is conditions 

(without EEW),

•	 F(t)=fraction of occupants who could in principle 

DCHO after receiving EEW and before arrival of 

strong motion t seconds later, and

•	 f=fraction of nonfatal injuries that could be avoided by 

DCHO. 

Then the upper bound of avoided injuries in a particular 

earthquake can be estimated as:

 , (1)

where Ii denotes the number of nonfatal injuries estimated in 

geographic location i (for example, a census tract or ZIP code) 

and F(t

i

) denotes the fraction of people in location i who could 

take effective self-protective action within the available warning time t

i

. The multiplicands can be estimated as follows—Ii

is estimated using Hazus-MH (Federal Emergency Management Agency, 2012), and t

i

 is the warning time at location i

(the time between the EEW alert and arrival of S waves). The 

warning time calculations during a fault rupture are explained 

in appendix 2. Equation 2 estimates the warning time at location i:

, (2)

where Ri is hypocentral distance to location i in kilometers, 

considering the 8-kilometer (km) focal depth of the HayWired 

mainshock; V is the shear-wave velocity in rock (3.4 kilometers per second, km/s); and t

L is latency time (from earthquake 

nucleation to transmission of the warning—5 seconds, s). F(t

i

) 

can be estimated as the cumulative distribution function of 

DCHO reaction time from a population survey evaluated at t

i

, 

the warning time for location i.

The fraction of nonfatal injuries that could be avoided by 

DCHO, f, can be estimated using data compiled from injuries 

suffered in the Northridge and possibly other earthquakes. 

Shoaf and others (1998) provide the necessary data—55 

percent of injuries result from nonstructural objects, 22 percent from earthquake force, and 12 percent from behavior. It 

seems reasonable that effective DCHO could prevent injuries 

from nonstructural objects such as a bookcase or television, 

by shielding the person from falling or sliding nonstructural 

objects. It also seems reasonable that DCHO could prevent 

injuries associated with earthquake force by having the person 

drop to the floor on hands and knees and therefore avoid being 

thrown by the force of the earthquake. Finally, DCHO is a 

behavior that substitutes for injurious ones such as jumping out of windows or trying to catch falling objects—two 

B = Ii

i=1

N

∑ × F t( i)× f

ti = Ri

V −tL
404 The HayWired Earthquake Scenario—Engineering Implications

examples of behavior-related injuries in the Northridge 

earthquake. Summing these injuries, it seems DCHO could 

conceivably prevent 0.55+0.22+0.12=89 percent of injuries, 

suggesting f=0.89. The remaining 11 percent of injuries in the 

Northridge earthquake were associated with structural objects 

(1 percent) and other causes (10 percent). Although some furnishings have supported structural objects in past earthquakes 

(for example, steel desks in a school building), it seems conservative to assume that this is not a general case, so we omit 

the 1 percent of injuries associated with structural objects from 

potential benefits of DCHO. Shoaf and others, (1998) provide 

no additional detail regarding the remaining 10 percent of 

injuries associated with other causes; we assume that DCHO 

would not prevent these either. We are aware of no research on 

the effectiveness of DCHO, so f=0.89 should be thought of as 

an upper bound on the number of nonfatal injuries that would 

in practice be avoided by DCHO. The figure f=0.89 with its 

two significant figures may give a false impression of precision. It is probably only meaningful to one significant figure, 

such as, f=0.9, but common engineering practice calls for carrying an extra significant figure to reduce cumulative rounding 

errors.

Note that Johnston and others (2014) categorize causes 

of injuries differently from Shoaf and others (1998) and lump 

together injuries that occurred during an earthquake and in its 

aftermath, such as helping others or injuries caused by glass. 

As a result, it is problematic to estimate f using Johnston 

and others (2014) data. Depending on what one includes and 

excludes, one can estimate f from these data to be between 

69 percent and 99 percent. The range overlaps and therefore 

does not contradict the value derived using Shoaf and others, 

(1998). 

Estimating the Acceptable Cost to Avoid Injuries

One can calculate the acceptable cost to avoid statistical 

injuries, B2, as suggested in Multihazard Mitigation Council 

(2005) as follows:

 , (3)

where Bj denotes the number of avoided injuries of severity j

and Vj denotes the U.S. Government’s acceptable cost to avoid 

a statistical injury of severity j. We take values of statistical injuries avoided from U.S. Department of Transportation 

(2014), inflate them to 2015 USD as instructed there, and map 

them to Hazus-MH injury severity levels using Multihazard 

Mitigation Council’s (2005) table F-5 mapping 2. Table 1 

presents those figures, rounded to two significant figures to 

avoid the appearance of excessive precision.

Survey Design

The University of Colorado Boulder developed a datacollection protocol to collect statistics about DCHO reaction time through a web-based survey instrument copied to 

appendix 1. The protocol was approved by the university’s 

Institutional Review Board (IRB) on November 17, 2015. The 

survey instrument has six parts:

1. An introduction that explains the purpose of the survey, 

its procedures, risks, benefits, confidentiality, and consent to participate.

2. Training materials, text and brief YouTube videos, on 

how to DCHO.

3. Instructions on where and how to time oneself performing DCHO.

4. A question to determine the setting where the volunteer 

performed the exercise, in terms of Hazus-MH occupancy classification.

5. A series of questions to examine how well the training 

material worked.

6. Demographic questions.

In an initial trial study, volunteers were recruited through 

Twitter feeds and social media accounts. The initial study 

yielded only 65 responses, so the earlier sample was ignored 

and more than 500 participants were recruited through 

Qualtrics Panels, a paid service provided to the University of 

Colorado Boulder. Subsequent findings refer only to responses 

from Qualtrics Panels.

Findings

Because physical dexterity and proximity to protective 

furniture differs from person to person and by time of day, one 

should expect that people will take different amounts of time 

to complete DCHO. Survey results bear out that expectation.

Distribution of DCHO Reaction Time

Data on DCHO reaction times were collected using the 

web-based survey instrument shown in appendix 1 between 

December 18 and 23, 2015. As of this writing, we collected 

B2 = Bi

j=1

3

∑ ×Vj

Hazus injury severity1 Acceptable cost per avoided injury, in 

2015 U.S. Dollars2

1. Basic medical aid by 

paraprofessionals 28,000

2. More than 1 but not life 

threatening 660,000

3. Life threatening but not 

immediately fatal 3,700,000

4. Fatal 9,400,000

1

Federal Emergency Management Agency (2012).

2

U.S. Department of Transportation (2014).

Table 1. Acceptable cost to avoid a statistical injury, calculated 

using Multihazard Mitigation Council (2005).
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 405

data from a large sample—525 people completed the survey 

out of 638 to whom the survey was sent, a response rate of 

82 percent. We refer to these data as round-1 surveyed reaction times, in case future surveys are performed. Many of the 

data appear to reflect an incorrect understanding of when to 

stop counting or data-entry typographic errors—38 respondents reported times in excess of 20 s, some as long as 200 s. 

Omitting these 38 responses, the remaining 487 responses are 

shown in figure 1 along with a lognormal distribution fit to the 

data.

The nontechnical reader can interpret figure 1 as follows. 

The dashed, stairstep line represents the survey respondents’ 

reaction time. For example, 10 percent of them were able to 

DCHO in 5 s or less (see how the dashed line passes through 

x=5 s, y=0.10), 50 percent in 9 s or less (x=9 s, y=0.50), and 90 

percent in 15 s or less (x=15 s, y=0.90). The smooth S-shaped 

curve is a parametric distribution called the lognormal cumulative distribution function. It approximates the stairstep line 

with a more convenient mathematical equation. It is closely 

related to the familiar bell-shaped curve called the normal or 

Gaussian distribution. The lognormal cumulative distribution 

function has two variables that determine its shape. One of 

the variables, called the median, adjusts the x-value associated 

with the midpoint of the curve (the x-value associated with 

y=0.50). The other variable, called the standard deviation of 

the natural logarithm of the variable (or logarithmic standard 

deviation), adjusts the width of the S-shaped curve.

The reader should understand that lognormal may be the 

parametric probability distribution more commonly used than 

any other in earthquake engineering. Engineers use it for any 

of several reasons: 

1. It often reasonably agrees with observations of realworld variables, as it does here. 

2. Like many real-world variables, it can only take on a 

positive value and has a specifiable median and logarithmic standard deviation. 

3. It assumes the least knowledge about the variable in 

question, conditioned on the value of the median and 

logarithmic standard deviation. 

4. Tradition—engineers have used the lognormal at least 

since the 1980s to characterize earthquake damage to 

building components.

With the survey we can estimate that reaction time is 

approximately lognormally distributed with median 8.8 s and 

standard deviation of the natural logarithm equal to 0.40, as 

shown in figure 1. The lognormal appears to be a reasonable 

approximation of the sample data provided by the study participants according to a Lilliefors (1967) goodness-of-fit test.

Respondents were aged between 18 and 95, with a mean 

age of 35. The majority of respondents (57 percent) were 

female, versus 50.8 percent in the general U.S. population 

in 2014 (U.S. Census, 2015). Most (69 percent) described 

their race or ethnicity as white/Caucasian (73.6 percent of the 

U.S. population), 13 percent described their race or ethnicity 

as African American (14 percent of the U.S. population), 10 

percent described their race or ethnicity as Hispanic (17 percent of the U.S. population), 8 percent described their race or 

ethnicity as Asian (6 percent of the U.S. population), 3 percent 

described their race or ethnicity as Native American (2 percent 

of the U.S. population), 1 percent described their race or 

ethnicity as Pacific Islander (same as the U.S. population), and 

4 percent described their race or ethnicity as other (respondents were allowed to select all that applied). The majority (56 

percent) have at most some college education (U.S. population is 61 percent), 33 percent have a 2- or 4-year college 

degree (U.S. population is 28 percent), and 11 percent had a 

masters, professional, or doctoral degree (U.S. population is 

10 percent) (U.S. population education attainment percentages 

from U.S. Census Bureau, 2015a). Respondents were slightly 

poorer than the U.S. population in general—53 percent report 

a combined household income less than $40,000 per year 

(U.S. median household income is $53,657) and 91 percent 

report a combined household income less than $110,000 per 

year (90th percentile among the U.S. population is $155,000) 

(U.S. general population household income data from U.S. 

Census Bureau, 2015b).

0.00

0.25

0.50

0.75

1.00

0 5 10 15 20

Cumulative probability

Drop, cover, and hold on reaction time, in seconds

EXPLANATION

Reported reaction times

LN(θ=8.8 seconds, β=0.4)

Figure 1. Graph of cumulative probability for “drop, cover, 

and hold on” (DCHO) reaction times. DCHO reaction times were 

collected from volunteers using the web-based survey instrument 

shown in appendix 1. Red dotted line shows the distribution of 

reported reaction times for 487 respondents (38 respondents who 

reported DCHO times in excess of 20 seconds were omitted). 

Black curved line shows the lognormal distribution—LN, 

lognormal; θ, median, β, standard deviation.
406 The HayWired Earthquake Scenario—Engineering Implications

Calculation of Benefits

We now apply the foregoing procedures to evaluate 

the benefits of the combination of EEW and DCHO in the 

HayWired scenario mainshock. Warning time t

i

 of equation 2 

is shown for the mainshock in figure 2. See appendix 2 of this 

chapter for the derivation of figure 2. 

We can now apply equations 1 and 3. We compiled Ii by 

census tract from the Hazus-MH (Federal Emergency Management Agency, 2012) analysis of the HayWired mainshock. We 

calculated Ri at each census tract centroid, took V=3.4 km/s 

and t

L

 as 5 s, (as discussed in appendix 2), and idealized F(t) 

as lognormally distributed with median reaction time equal to 

8.8 s and logarithmic standard deviation equal to 0.40, so that 

equation 4 now follows:

 . (4)

The total number of nonfatal injuries from the HayWired 

scenario mainshock is estimated to be 18,1303; EEW could 

avoid as many as 1,468 of these, or 8 percent (table 2). Dollar 

values in table 2 are rounded to two significant figures. The 

data in table 2 suggests that if EEW were fully implemented 

and everyone in the San Francisco Bay region had been 

trained and drilled on DCHO before the HayWired mainshock 

occurred, as many as ~1,500 people who would otherwise be 

injured would have time to complete DCHO before the arrival 

of strong motion and avoid nonfatal injury. (Table 2 shows a 

calculated figure of 1,468 avoided injuries, but we use “about 

1,500” to avoid the appearance of excessive accuracy.) The 

acceptable cost to avoid those injuries is about $300 million. Recall that the results in table 2 assume that completing 

DCHO effectively avoids 89 percent of injuries, which was 

acknowledged as an upper bound. The actual benefit would 

be lower in proportion to the ratio of actual nonfatal injuries 

avoided to the upper bound. Note also that some of the injuries 

shown in the first column would also be avoided by DCHO 

without EEW, because the Hazus injury model predates 

widespread training in DCHO. Perhaps DCHO would be less 

effective in the absence of EEW because people would be trying to take action during strong motion and would be injured 

before successfully completing the DCHO actions. We do not 

speculate on injuries avoided by DCHO without EEW.

EEW provides more advanced warning the farther the 

recipient is from the earthquake focus (fig. 3A), but injuries 

tend to be concentrated close to the focus. It is in the middle 

ground (where EEW provides at least some warning time but 

shaking is still strong enough to threaten life safety) that EEW 

combined with “drop, cover, and hold on” actions has the 

greatest potential to reduce injuries, as shown in figure 3B.

Conclusions

We do not know how effective DCHO is in preventing 

earthquake injuries, nor do we know how much time decisionmaking adds to DCHO reaction time. However, to begin to 

estimate the benefit of EEW and DCHO, we assume that 

training and drilling can reduce decision time to near zero relative to reaction time. We further neglect the benefit of DCHO 

without EEW and assume that DCHO before the arrival of 

strong motion can prevent almost all (f=89 percent) of nonfatal 

earthquake injuries. With all of these simplifying assumptions, 

we can estimate an upper bound to the benefit of the combination of EEW and DCHO. If everyone in the San Francisco Bay 

region were trained and drilled in DCHO and received EEW 

before the arrival of the HayWired scenario mainshock, the 

additional warning time provided by EEW would be sufficient 

for about 1,500 of 18,000 people who would otherwise be 

injured to take DCHO actions that successfully prevent their 

F(t) =Φ

ln(t / 8.8sec)

0.40

⎛

⎝

⎜ ⎞

⎠

⎟

Hazus injury severity1 Number of people injured Maximum number of 

avoided injuries

Acceptable cost per 

avoided injury, in 

2015 U.S. Dollars2

Acceptable cost to avoid, 

in millions of 2015 U.S. 

Dollars

1. Basic medical aid by 

paraprofessionals 14,081 1,216 28,000 34

2. More than 1 but not life 

threatening 3,491 218 660,000 144

3. Life threatening but not 

immediately fatal 558 34 3,700,000 127

4. Fatal 971 0 9,400,000 0

Total 19,101 1,468 Not applicable 305

1

Federal Emergency Management Agency (2012).

2

U.S. Department of Transportation (2014).

Table 2. Upper-bound number and value of avoided injuries from earthquake early warning combined with “drop, cover, and hold on” 

actions in the San Francisco Bay region, California, in the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake 

scenario.

3

The Hazus-MH analysis estimated damages for shaking from the HayWired mainshock, as well as liquefaction, and these numbers were combined. The 

number differs from the 16,000 injuries reported in Seligson and others (this volume) for the mainshock in the context of the HayWired earthquake sequence, 

because only the shaking hazard data was consistently available across all earthquakes in the sequence.
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 407

P a c i f i c O c e a n

San

Mateo

Sonoma

Napa

San

Joaquin

Stanislaus

Merced

San

Benito

Santa

Cruz

Monterey

San

Mateo

Sonoma

Napa

San

Joaquin

Stanislaus

Merced

San

Benito

Santa

Cruz

Monterey

Sacramento

Stockton

San Jose

Fremont

Livermore

Hayward

San Francisco Oakland

Alameda

Modesto

PA C I F I C O C E A N

0 seconds

20 seconds

123° 122° 121°

38°

37°

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016.

Boundary and population data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N. 0 10 20 KILOMETERS

0 10 20 MILES

County boundary

City

Warning Time, in seconds

0

25

100,102–203,949

EXPLANATION

Block group density—

residents per square kilometer

49,532–100,101

24,905–49,531

12,913–24,904

7,073–12,912

4,230–7,072

< 2,845

2,845–4,229

5 seconds

10 seconds

25 seconds

Area

of map

CALIFORNIA

0 seconds

20 seconds

5 seconds

10 seconds

25 seconds

Figure 2. Map of the San Francisco Bay region, California, with contours of warning time (t

i

; see equation 2) for the hypothetical 

moment-magnitude-7.0 mainshock of the HayWired earthquake scenario and block group density (residents per square kilometer). 
408 The HayWired Earthquake Scenario—Engineering Implications

PACIFIC OCEAN

SAN FRANCISCO BAY

San Francisco

Alameda

Oakland

Hayward

Fremont

San Jose

Livermore

Stockton

123° 122°

38°

37°

0 10 20 KILOMETERS

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016. 0 10 20 MILES

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W, latitude of origin, 0.0° N.

A

Area

of map

CALIFORNIA

EXPLANATION

Percent avoided injuries per 

census tract as a result of 

using earthquake early warning

City

No avoided injuries

No warning zone

80–90%

60–80%

40–60%

20–40%

< 20%

Figure 3. Maps of San Francisco Bay region, California, showing injuries potentially avoided because of earthquake early warning 

combined with “drop, cover, and hold on” actions in the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake 

scenario. A, Fraction of injuries potentially avoided as a result of using earthquake early warning; B, upper bound number of injuries 

avoided by census tract as a result of using earthquake early warning. %, percent.
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 409

San Francisco

Alameda

Oakland

Hayward

Fremont

San Jose

Livermore

Stockton

123° 122°

38°

37°

0 10 20 KILOMETERS

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016. 0 10 20 MILES

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W, latitude of origin, 0.0° N.

B

CALIFORNIA

Area

of map

No warning zone

EXPLANATION

Number of avoided injuries 

per census tract as a result of 

using earthquake early warning

City

No avoided injuries

1–10

10–20

20–40

40–80

80–160

160–212

PA C I F I C O C E A N

SAN FRANCISCO BAY

Figure 3.—Continued
410 The HayWired Earthquake Scenario—Engineering Implications

injury before the arrival of strong motion. The U.S. Government would value mitigation measures to avoid that number of 

nonfatal injuries at approximately $300 million (2015 USD). 

Limitations and Research Needs

The intent of this report is not to say that the probabilistic benefit of EEW and DCHO is $300 million, for several 

reasons. That figure is an upper bound, not an expected value, 

and it is conditioned on the occurrence of a single earthquake, 

when in fact the future date of such an earthquake is uncertain, 

and there are many other possible earthquakes where EEW 

and DCHO would contribute to probabilistic benefit. However, 

the figures of 1,500 injuries and $300 million are useful to 

understand the potential magnitude of the benefits of EEW and 

DCHO.

There does not appear to be any published research or 

other evidence on the effectiveness of DCHO to prevent injuries. For example, we do not know how many injuries related 

to nonstructural objects, earthquake force, or human behavior 

would actually be avoided by DCHO. 

Other important, unanswered questions include the following—What fraction of fatal injuries could be avoided by 

DCHO? How much would reaction times differ in the real 

event as opposed to the calm setting of the survey? What fraction of injuries can be avoided without EEW, that is, if people 

DCHO when they begin to feel strong motion? How long after 

the initiation of strong motion do injuries occur? (Presumably 

the answer to this last question depends on the severity of 

motion.)

One can imagine laboratory experiments using human 

simulacra (crash-test dummies), finite-element analysis, and 

other means to explore these questions, but such experiments do not appear to have been carried out. According to a 

National Science Foundation (NSF) program officer, NSF does 

not appear to have a program to address earthquake-induced 

injuries (David Mendonca, NSF, written commun., December 

8, 2015), nor can we find record of a relevant program within 

the National Institutes of Health.

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gov/sites/dot.gov/files/docs/VSL_Guidance_2014.pdf.
412 The HayWired Earthquake Scenario—Engineering Implications

Appendix 1. Survey of DCHO Reaction Times

The following survey instrument was successfully administered by the University of Colorado Boulder to study participants 

using the Qualtrics Panels service in December, 2015. The protocol was approved by the university’s Institutional Review Board 

on November 17, 2015.
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 413
414 The HayWired Earthquake Scenario—Engineering Implications

[Image used in original survey instrument not shown]
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 415

[Image used in original survey instrument not shown]
416 The HayWired Earthquake Scenario—Engineering Implications
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 417
418 The HayWired Earthquake Scenario—Engineering Implications
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420 The HayWired Earthquake Scenario—Engineering Implications
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422 The HayWired Earthquake Scenario—Engineering Implications
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424 The HayWired Earthquake Scenario—Engineering Implications
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426 The HayWired Earthquake Scenario—Engineering Implications
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 427

We estimate the earthquake early warning (EEW) capabilities for the magnitude (M) 7.0 HayWired scenario mainshock based on the performance of the ShakeAlert (https://

www.shakealert.org) demonstration system during the M 4.0 

Piedmont, California, earthquake on August 17, 2015. The 

Piedmont earthquake epicenter lies only 6 kilometers (km) 

from the epicenter of the HayWired scenario mainshock. 

Therefore, it is a reasonable proxy for our purposes here, 

because the initial alert latency (the delay between earthquake 

origin time and the time at which the first alert is issued) is 

primarily dependent on the local station density. The latency 

between the earthquake initiation and the initial ShakeAlert 

alert time was 4.8 seconds (s) for the 2015 Piedmont earthquake. The alert latency includes (1) the time for the P-wave 

to reach the surface and travel to at least four seismic stations, (2) waveform data to be transmitted to the processing 

centers (generally 1 s or less for California Integrated Seismic 

Network, CISN, stations close to the Piedmont earthquake), 

and (3) computation of the magnitude and location of the 

earthquake. The 3 km difference in hypocentral depth between 

the Piedmont earthquake (4.9 km) and the HayWired scenario earthquake (8 km) would add approximately 0.5 s to the 

P-wave travel time to the Earth’s surface—using an average

speed of P-waves in California of 6 kilometers per second

(km/s). Thus, we estimate that the initial alert time for the

HayWired scenario mainshock would be approximately 5.3

s after the earthquake origin time—that is, after the rupture

begins on the Hayward Fault.

For the purposes of this scenario, we make a series 

of simplifying assumptions. We assume the length of the 

waveform segments that were used for the estimation of the 

Piedmont earthquake magnitude are similar to those used for 

characterization of the HayWired scenario mainshock. For the 

Piedmont earthquake, the closest station is at a hypocentral 

distance of 6.2 km, with a source-to-station P-wave travel time 

of about 1 s. Assuming a network transmission latency of 1 s, 

there was about 3 s of waveform available to analyze at this 

station before an alert was issued. In ShakeAlert, magnitude 

estimates can be made using waveform data from a single 

station. A source duration of about 3 s (as captured in the first 

3 s of the P wave) would provide an initial magnitude estimate 

of at least M5.5 (for example, Meier and others, 2016). So, for 

the HayWired scenario mainshock, we estimate that an initial 

alert would be issued for a M5.5 earthquake at 5.3 s after the 

earthquake origin and that the magnitude estimate would 

subsequently be updated as the rupture continued to grow into 

a M7.0 earthquake. 

ShakeAlert plans to distribute alerts to the public when the 

observed ground motions are consistent with an earthquake that is 

above a minimum magnitude (for example, M>4.5), and alerts will 

be sent to regions expected to experience ground shaking above 

a minimum predicted Modified Mercalli Intensity (MMI) (for 

example, MMI≥II). For the HayWired scenario, we assume that 

when the first alert is sent the initial estimated magnitude would be 

M5.5, and alerts would be issued to regions expected to experience 

MMI greater than or equal to II. This corresponds to a region inside 

of which users are expected to feel ground shaking, with or without 

resulting damage. Using a standard intensity relation (Atkinson and 

others, 2014) to calculate the initial alerting region, we find that 

for a M5.5 earthquake, the area that encompasses MMI II or larger 

ground shaking extends to approximately 250 km.

We estimate the range of warning times for this initial 

alerting region from the time it takes for S-waves traveling at a 

velocity of 3.4 km/s to travel distances between 0 and 250 km, 

minus the alert latency time (5.3 s). At the time of the initial alert, 

issued 5.3 s after the earthquake origin time, S-waves would have 

traveled a hypocentral distance of 17 km (or 15 km epicentral 

distance). This circular region defined by a 15-km radius around 

the epicenter defines a region of no warning for S-wave shaking. 

Note that we neglect the time it takes to distribute an alert to 

users. At epicentral distances greater than 15 km, a user of the 

ShakeAlert system would receive an alert before the arrival of 

S-waves.

In the initial alert region, warning times range from no warning to more than 60 s of warning, assuming a constant S-wave 

velocity and no alert distribution latencies. This initial alert region 

encompasses the area that will eventually experience MMI III 

or greater shaking when the final magnitude (M7.0) is reached. 

Given that damage is unlikely to occur at shaking levels less than 

this, we do not extend this scenario through the entire rupture 

evolution. However, we expect that as the earthquake magnitude 

grows the alerting region will be also expanded in the seconds 

after the initial alert until the final scenario magnitude is reached. 

Assuming ShakeAlert algorithms correctly estimate the final 

earthquake magnitude of M7.0, then the alerting region will extend 

to epicentral distances of about 575 km. Here, we assume a point 

source that reflects the current capability of the ShakeAlert system, 

but a more realistic line source (finite rupture) EEW algorithm is 

currently under development for ShakeAlert and would result in a 

noncircular alert region.

Appendix 2. HayWired Mainshock Earthquake Early Warning Time Calculation

By Elizabeth S. Cochran,1 Anne M. Wein,1 Erin R. Burkett,1 Douglas D. Given,1 and Keith Porter2

1

U.S. Geological Survey.

2

University of Colorado Boulder.
428 The HayWired Earthquake Scenario—Engineering Implications

We note that earthquake-generated P-waves tend to 

shake the ground vertically, whereas S-waves tend to shake 

the ground side-to-side, horizontally. P-waves tend to have 

smaller amplitudes than S-waves. Buildings, bridges, and 

other infrastructure tend to be stronger in resisting vertical 

motion than horizontal motion. For these reasons, the slower, 

later-arriving, horizontally shaking, and stronger S-waves 

tend to cause more damage to buildings, bridges, and other 

infrastructure than do the faster but weaker, vertically shaking 

P-waves. That is why, for EEW purposes, the warning time 

is typically measured between the alert time and the arrival 

of S-waves at a site. However, it is important to note that, 

particularly for sites close to the rupture, shaking from the 

P-wave can also be strong, and thus the time available to 

take action may be shorter (Meier, 2017; Minson and others, 

2018). Also, warning times may be longer for cases where the 

shaking threshold is exceeded after S-wave arrival (Meier, 

2017; Minson and others, 2018). The available warning time at 

a given location depends on a variety of factors, including (1) 

the time it takes for the rupture to grow (the final magnitudes 

of large earthquakes that rupture over a period of several 

to tens of seconds cannot be predicted in advance), (2) the 

magnitude and (or) shaking-intensity threshold for which an 

alert is generated, (3) the frequency at which alerts are updated 

(as the rupture evolves), (4) the time required to distribute 

alerts, and (5) how far the recipient of the warning is from the 

hypocenter (Minson and others, 2018).

Table 3 catalogs the shaking intensities and warning 

times that an EEW alert could provide until S-wave arrival 

for major cities affected by the hypothetical M7.0 HayWired 

rupture. Figure 4 shows the HayWired instrumental intensity 

map and contours of the warning time until S-wave arrival.

References Cited

Atkinson, G.M., Worden, B., and Wald, D.J., 2014, Intensity 

prediction equations for North America: Bulletin of the 

Seismological Society of America, v. 104, no. 6, p. 3084–

3093, doi: 10.1785/0120140178.

Meier, M.-A., Heaton, T., and Clinton, J., 2016, Evidence for 

universal earthquake rupture initiation behavior: Geophysical Research Letters, v. 43, no. 15, p. 7991–7996, doi: 

10.1002/2016GL070081.

Meier, M.-A., 2017, How “good” are real-time ground motion 

predictions from earthquake early warning systems: Journal 

of Geophysical Research—Solid Earth, v. 122, no. 7, p. 

5561–5577, doi: 10.1002/2017JB014025.

Minson, S.E., Meier, M.-A., Baltay, A.S., Hanks, T.C., and 

Cochran, E.S., 2018, The limits of earthquake early warning—Timeliness of ground motion estimates: Science 

Advances, v. 4, no. 3, doi: 10.1126/sciadv.aaq0504.

City Latitude Longitude Epicentral distance, in miles

Epicentral 

distance, in 

kilometers

Warning time, in 

seconds Shaking intensity1

Oakland 37.80 122.27 5 8 0.0 VIII

Berkeley 37.87 122.27 7 11 0.0 IX

Hayward 37.67 122.08 11 17 0.7 IX

San Francisco 37.78 122.42 13 21 1.8 VII

San Mateo 37.55 122.31 19 30 4.3 VII

Fremont 37.55 122.99 21 33 5.2 IX

Vallejo 38.11 122.24 21 35 5.8 VII

Redwood City 37.48 122.24 23 36 6.0 VII

San Rafael 37.97 122.53 23 36 6.0 VII

Livermore 37.68 122.77 24 39 6.9 VIII

San Jose 37.34 121.89 36 58 12.4 VIII

1

Modified Mercalli Intensity.

Table 3. Estimated earthquake early warning times and shaking intensity at select locations in the San Francisco Bay region, 

California, for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.
Chapter Q. How Many Injuries Can Be Avoided Through Earthquake Early Warning and Drop, Cover, and Hold On? 429

Sonoma

Napa

San

Joaquin

San

Mateo

Santa

Cruz

Santa

Clara

Stanislaus

Merced

San

Benito

Monterey

P a c i f i c O c e a n

Sonoma

Napa

San

Joaquin

San

Mateo

Santa

Cruz

Santa

Clara

Stanislaus

Merced

San

Benito

Monterey

Oakland

Sacramento

Alameda

Hayward

Livermore

San Francisco

Stockton

Fremont

San Jose

Modesto

PA C I F I C O C E A N

0 seconds

5 seconds

10 seconds

20 seconds

25 seconds

0 seconds

5 seconds

10 seconds

20 seconds

25 seconds

123° 122° 121°

38°

37°

0 10 20 KILOMETERS

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016. 0 10 20 MILES

Boundary data from U.S. Census Bureau TIGER data, 2016.

North American Datum of 1983 UTM 10N projection.

Central meridian, 123° W., latitude of origin, 0.0° N.

County boundary

City

Warning time, in seconds

0

25

EXPLANATION

Modified Mercalli Intensity

X+ (extreme)

IX (violent)

VIII (severe)

VII (very strong)

VI (strong)

V (moderate)

IV (light)

III (weak)

Area

of map

CALIFORNIA

Figure 4. Map of the San Francisco Bay region, California, showing contours of estimated earthquake early warning times on a 

shaking intensity map (Modified Mercalli Intensity) for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake 

scenario on the Hayward Fault. For the scenario, the initial alerting region extends 250 kilometers from the earthquake epicenter, which 

is outside of the boundaries of the figure. Note that strong shaking can also occur at the time of the P-wave arrival, particularly close to 

the fault rupture, which would reduce available time for taking protective and risk-reduction actions.

Menlo Park Publishing Service Center, California

Manuscript approval date February 28, 2018

Edited by James W. Hendley II, Regan Austin, Scott Darling, 

Monica Erdman, Katherine Jacques, and Jessica Dyke

Design and layout by Cory Hurd and Vivian Nguyen
Detweiler and Wein, editors—The HayWired Earthquake Scenario—Engineering Implications—Scientific Investigations Report 2017–5013–I–Q

ISSN 2328-0328 (online)

https://doi.org/10.3133/sir20175013v2