report calema hazus 09 final

7/29/2019 Report CalEMA HAZUS 09 Final

1/47

1

CGS Project Report

Prepared for California Emergency Management Agency

HAZUS Loss Estimation forCalifornia Scenario Earthquakes

California Geological SurveyDepartment of Conservation

June 2009


2/47

2

Contents

ABSTRACT.................................................................................................................................................. 3

1. INTRODUCTION.................................................................................................................................... 7

2. SELECTION OF SCENARIO EARTHQUAKES.................................................................................

10

2.1 USGS Scenarios................................................................................................................................ 10

2.2 UCERF 2 Based Scenarios............................................................................................................ 14

3. HAZUS INVENTORY AND ANALYSES.......................................................................................... 16

4. RESULTS............................................................................................................................................... 18

4.1 USGS Scenarios................................................................................................................................ 18

4.2 UCERF 2 Based Scenarios............................................................................................................ 33

5. COMPARISON OF LOSS ESTIMATES............................................................................................... 35

5.1 Comparison of Building-Related Losses from HAZUS MH-MR3 (CGS 2009 Results) and HAZUS-

SR2 (CGS 2005 Results)........................................................................................................................ 35

5.2 Comparison of Building-Related Losses for UCERF 2-Based Scenarios (NGA GMPEs) and USGS

Scenarios................................................................................................................................................. 36

5.3 Comparison with Other Published Results....................................................................................... 40

6.CONCLUSION........................................................................................................................................... 42

7.REFERENCES............................................................................................................................................ 43

8.APPENDICES............................................................................................................................................ 46

8.1 Appendix A Electronic Attachment............................................................................................... 46

8.2 Appendix B Tables and Summary Reports for the Selected Scenario........................................... 47


3/47

3

ABSTRACT

Comprehensive estimation of the scale and extent of damage, social disruption, and

economic losses due to potential earthquakes is useful information inpreparing emergency

response plans, in developing earthquake hazard mitigation strategies, and in evaluating thenature and scope of response and recovery efforts prior to the earthquakes. California

Emergency Management Agency (CalEMA) requested that the California Geological Survey

(CGS) at the Department of Conservation estimate economic losses, social impact, and structural

damage due to potential earthquakes in California using HAZUS, a loss estimation software

package developed by the Federal Emergency Management Agency (FEMA). CalEMA

requested loss estimation for at least 50 scenario earthquakes developed by the United States

Geological Survey (USGS) using ShakeMap ground motion parameters, including peak ground

acceleration (PGA), peak ground velocity (PGV), spectral acceleration at 0.3 second (SA03), and

spectral acceleration at 1.0 second (SA10) published on the USGS ShakeMap Archive website.

CGS collected ShakeMap ground motions of 56 scenario earthquakes developed by

USGS for California (referred to as USGS scenarios) and conducted loss estimates using the

default information on built environment and demographics embedded in HAZUSMH MR3

with service patch 2 (the latest version of HAZUS as of May, 2009). These USGS scenarios

were developed using ground motion prediction equations (GMPEs) from Boore et al. 1997 for

PGA, SA03, and SA10, and from Joyner and Boore 1988 for PGV. Source parameters,

including magnitude and fault geometry, for these scenarios were based on the 2002 statewide

probabilistic seismic hazard assessments for California. Significant research developments have

occurred in the past few years in both ground motion prediction and rupture source

characterization. To estimate how these latest developments affect HAZUS loss estimates, CGSdeveloped and analyzed 10 additional scenarios. These scenarios were developed based on

source parameters and probability results of the Uniform California Earthquake Rupture Forecast

Version 2 (UCERF 2) completed in 2008 by the Working Group on California Earthquake

Probabilities. They are referred to as UCERF 2-based scenarios. Three of the five Next

Generation Attenuation (NGA) models were used to calculate PGA, PGV, SA03, and SA10 for

UCERF 2-based scenarios, namely models from Boore and Atkinson 2008, Campbell and

Bozorgnia 2008, and Chiou and Youngs 2008 models. Using these three NGA models is

justified because they were used in the USGS 2008 Update of the National Seismic Hazard Maps

which are used in the development of building codes. The NGA models are founded on a

significantly improved common database of ground motion recordings and to a large extent they

have replaced earlier GMPEs for shallow crustal earthquakes in western United States. Using

these NGA models resulted in notable changes in predicted ground motions, particularly for long

periods. One can expect that using NGA models could lead to substantial differences in

estimated losses and related effects than those derived from earlier GMPEs.


4/47

4

CalEMA requested that HAZUS output include HAZUS Global Summary Reports and

Quick Assessment Reports. The output also includes: shaking intensity; casualties at 2 A.M. (at

home time), 2 P.M. (at work time), and 5 P.M. (commute time); economic loss, displaced

households, and short term shelter needs by census tract; damage to highway bridges, airports,

schools, and hospitals; dam inventories with shaking intensity at the dam locations; and debris

generated. These HAZUS output maps, tables, and summary reports were compiled for eachscenario and included as an appendix to this report. In addition, pertinent results for all scenarios

were summarized and tabulated in this report. A complete set of results is presented for one

selected scenario to illustrate the contents of the electronic attachment. We also computed

building loss ratio, calculated as the ratio of economic loss due to building damage to building

replacement value, for each census tract. Because it is normalized by the building replacement

value, loss ratio is a better indicator of relative damage in different geographic areas than

building-related loss.

Based on the analyses of the USGS scenarios in northern California, the predicted three

most damaging scenario earthquakes involve co-seismic rupture of different combinations of atleast three Northern San Andreas Fault segments, resulting in an estimated economic loss

ranging from nearly $70 billion to over $80 billion. The most damaging scenario earthquake is a

repeat of the 1906 San Francisco magnitude 7.9 earthquake. It would rupture all four segments

of the Northern San Andreas Fault and cause nearly $84 billion of total economic loss, mostly

building-related. It would kill 1000 to 4000 people, displace nearly 64 thousand households, and

generate 23 million tons of debris. It would cause at least moderate damage on nearly 700

locations of highway bridges, 7 locations of airports, 6 schools, and over 343 thousand buildings.

Other earthquakes with over $30 billion estimated losses in northern California include: a

magnitude 7.26 earthquake rupturing the entire Hayward-Rodgers Creek Fault causing $39

billion in losses and a magnitude 7.42 earthquake rupturing the Santa Cruz Mountain and

Peninsula segments of the Northern San Andreas fault causing $36 billion in losses. HAZUS

estimates that no hospitals would experience moderate or greater damage in any of the northern

California scenarios analyzed in this study. The estimated loss ratio is less than 10 percent in

most areas affected by scenario earthquake ground motions. However, in some cases, loss ratio

exceeds 10 percent in the vicinity of the rupturing fault. For the three most damaging

earthquakes on the Northern San Andreas fault segments, loss ratio as high as 50 percent was

estimated for some census tracts in northeast San Mateo County.

In southern California, the most damaging scenario, by far, is the magnitude 7.1

earthquake on the Puente Hills fault. With building loss ratios up to 30% in some census tracts,

total predicted building loss is up at $79 billion ($82.8 billion in total economic loss). It would

kill 500 to 2000 people and displace 58,000 households. It would cause at least moderate

damage to 569 highway bridges, 2 airports and over 470,000 buildings. These numbers are in

the lower range of an earlier estimate by Field and others for the same fault. Other notable high

loss scenarios for southern California are: the Newport-Inglewood fault with over $34 billion in

total building loss, the Palos-Verde Fault with just over $20 billion in total building loss and a


5/47

5

magnitude 7.8 rupture along the Southern San Andreas Fault with just over $20 billion in total

building loss. When the same scenario was studied in great detail in the 2008 ShakeOut

Scenario, the total building loss was higher at $35 billion. This is likely due to a higher detailed

building inventory and ground failure effects (liquefaction, landslides, and surface rupture). A

less likely scenario, a magnitude 6.7 on the Verdugo Fault, would result in over $23 billion in

total building loss.

In a study conducted in 2005, CGS quantified building-related losses in ten counties in

the San Francisco Bay Area (SFBA) and in ten counties in southern California. That study used

scenario ground motions (or ShakeMaps) of 50 potential earthquakes published by the USGS

and default information on the built environment and demographics embedded in HAZUS

Service Release 2 (HAZUS-SR2). Most of the scenario ShakeMaps used in the CGS 2005 study

are identical to the ones used in this study for CalEMA. Therefore, for a given common

ShakeMap scenario, comparison of loss estimates from the current study and from the CGS 2005

study reflects differences in the HAZUS default inventory information on built environment and

demographics and in HAZUS analytical models. Comparison is made for building-related lossesonly because the CGS 2005 study only reported building-related losses. In northern California,

20 of the 33 comparable scenarios show building related losses from the current study that are

within 10 percent of CGS 2005 estimates. For most of the scenarios on the Northern San

Andreas Fault, the current estimates are up to 40% higher than the 2005 estimates. In contrast,

the current estimates are up to 36 percent lower than the 2005 estimates for most other scenarios.

In southern California, 75% of the common scenarios result in lower building related loss when

estimated using SR3 compared with SR2. Half of the differences are between 30% and 71%.

There are significant and consistent differences in the estimated building related losses

for the UCERF 2-based scenarios and for USGS scenarios. Among the 10 UCERF 2-basedscenarios, 6 can be compared directly to the corresponding USGS scenarios (similar earthquake

magnitude and fault model). Comparison shows that the estimated building-related loss for a

UCERF 2-based scenario is 30 to 60 percent lower than that for the comparable USGS scenario.

This difference is mainly due to different GMPEs used in the UCERF 2-based scenarios and in

USGS scenarios.

CGS was unable to collect and use enhanced data on the built environment and

demographics. Instead, we utilized available resources and augmented the original scope of loss

estimation for published USGS scenario ShakeMap earthquakes to include losses of UCERF 2-

based scenarios. The development of UCERF 2-based scenarios incorporated some of the mostsignificant research developments in ground motion characterization and rupture forecast in

California. Comparisons of estimated losses show that the differences in the estimated building-

related losses between the UCERF 2-based scenarios and the USGS scenarios are much more

significant and consistent than differences between the current and earlier versions of HAZUS.

Uncertainties are inherent in HAZUS loss estimates, just as they are inherent in all other

hazard, risk, and loss estimate methodologies. Uncertainties arise from incomplete scientific


6/47

6

knowledge concerning earthquake occurrence and ground motion characteristics and their effects

on buildings and other facilities. They also result from incomplete or inaccurate inventories of

the built environment, demographics, and economic parameters. A third source of uncertainties

comes from the approximations and simplifications that are necessary for model analyses. It is

estimated that these factors can result in total uncertainties in loss estimates produced by the

HAZUS-MH Earthquake Model of up to a factor of two or more (FEMA, 2009).


7/47

7

1. INTRODUCTION

California Emergency Management Agency (CalEMA) requested the California

Geological Survey (CGS) at the Department of Conservation to estimate economic losses, social

impact, and structural damage due to potential earthquakes using HAZUS (abbreviation forHAZards United States). HAZUS is a geographic information system (GIS)-based natural

hazard loss estimation software package developed by the Federal Emergency Management

Agency (FEMA). The objectives of the HAZUS exercise for CalEMA are: (i) to collect at least

50 of the scenario ShakeMaps developed by the United States Geological Survey (USGS) for

California to represent potential earthquakes; (ii) to estimate losses and related effects for each of

the selected earthquake scenarios using the USGS ShakeMap ground motions; and (iii) to

compile a suite of HAZUS output maps, tables, and summary reports for each scenario. The

output includes HAZUS Global Summary Reports and Quick Assessment Reports. The output

also includes: shaking intensity; casualties at 2 A.M. (at home time), 2 P.M. (at work time), and

5 P.M. (commute time); economic loss, displaced households, and short term shelter needs bycensus tract; damage to highway bridges, schools, and airports; dam inventories with shaking

intensity at the dam location; and debris generated.

In 1997 FEMA released its first edition of a commercial, off-the-shelf loss and risk

assessment software package built on GIS technology. This product was termed HAZUS97

[National Institute of Building Sciences (NIBS), 1997]. The development of HAZUS software

and its inventory is a work in progress. The current version is HAZUS-MH MR3, where MH

stands for Multi-Hazards. HAZUS-MH MR3 with its service patch 2 (SP2) is the most up-to-

date version of HAZUS as of May, 2009 (FEMA, 2009). This latest version is used to fulfill the

objectives of this project. All analyses utilize user-specified scenario ShakeMap ground motionsto represent potential earthquakes and HAZUS-MH MR3 default information for the built

environment and demographics. In HAZUS-MH MR3, the default information is derived from

the Bureau of Census 2000 census of population and housing data, the Dun & Bradstreet 2006

business population data, and other 2002 or newer data (FEMA, 2009).

In a previous study, CGS quantified building-related losses in ten counties in the San

Francisco Bay Area (SFBA) and in ten counties in southern California (Rowshandel et al., 2005).

That study used scenario ground motions (or ShakeMaps) of 50 potential earthquakes published

by the USGS and HAZUS Service Release 2 (HAZUS-SR2) (NIBS, 1997). It used HAZUS-SR2

default information on the built environment and demographics derived mostly from the 1990national census data.

The current project uses scenario ShakeMap ground motions of 56 potential earthquakes

published by the USGS for California. Most of these scenario ShakeMaps are identical to the

ones used in the CGS 2005 study (Rowshandel et al., 2005). Therefore, for a given common

ShakeMap scenario, comparison of loss estimates from the current study and from the CGS 2005

study (Rowshandel et al., 2005) reflects differences in the HAZUS default inventory information


8/47

8

on built environment and demographics. For a given scenario, estimated losses from the current

study are expected to increase compared to the earlier study due to increases in population and

structures over the more than 10 year period.

The existing ShakeMaps of potential earthquakes published by the USGS for California

were developed based on ground motion parameters calculated using ground motion prediction

equations (GMPEs) of Boore et al. (1997) for peak ground acceleration (PGA), peak spectral

acceleration at 0.3 second (SA03), and peak spectral acceleration at 1.0 second (SA10); and of

Joyner and Boore (1988) for peak ground velocity (PGV). Using a single GMPE is not the

standard practice in engineering seismology due to large uncertainty in ground motion

characterization. In addition, for shallow crustal earthquakes in western United States, earlier

GMPEs have been replaced to a large extent by the Next Generation Attenuation (NGA)

relations since the completion of the NGA project in 2008 (Steward et al., 2008). The NGA

project developed five sets of GMPEs for shallow crustal earthquakes in the western United

States and similar active tectonic regions. These new GMPEs were founded on a significantly

improved database of ground motion recordings. Three of the NGA models (Boore andAtkinson, 2008; Campbell and Bozorgnia, 2008; and Chiou and Youngs, 2008) were used in the

USGS 2008 Update of the National Seismic Hazard Maps (Petersen et al., 2008). Using these

NGA models resulted in notable changes in predicted ground motions, particularly for long

periods. For example, use of NGA models contributed significantly to the 5-30 percent decrease

in the 2008 National Seismic Hazard Map ground motion amplitudes compared to the 2002

hazard maps at long periods for some areas in the western United States (see comparison maps

on USGS website:

http://earthquake.usgs.gov/research/hazmaps/products_data/2008/maps/ratio.php). Consequently,

one can expect that using NGA models could lead to substantial differences in estimated losses

and related effects than those derived from earlier GMPEs.

To obtain a quantitative evaluation of the effect of NGA models on estimated losses and

to estimate losses based on state-of-the-art ground motion calculations, ten preliminary scenario

earthquakes were selected based on the results of the Uniform California Earthquake Rupture

Forecast, Version 2 (UCERF 2) by the 2007 Working Group on California Earthquake

Probabilities (WGCEP, 2008). These scenarios are referred to as UCERF 2-based scenarios.

The UCERF 2-based scenarios include 7 Type-A fault scenarios and 3 Type-B fault scenarios.

Type-A faults have known slip rates and paleoseismic estimates of recurrence interval and Type-

B faults have observed slip rates (WGCEP, 2008). Four of these scenarios are in northern

California and six are in southern California. To the extent practical, loss estimates for UCERF

2-based scenarios are compared to those for USGS scenarios.

Section 2 of this report provides details of scenario selection and ground motion

calculations. Section 3 explains HAZUS inventories used, types of loss analyses conducted,

intended use of HAZUS results, and limitations. Section 4 and Appendix B summarize HAZUS

results for all scenarios and presents a complete set of results for a selected scenario. Section 5


9/47

9

compares building-related losses obtained using HAZUS MH-MR3 (this study) versus losses

calculated using HAZUS-SR2 (CGS 2005 study). It discusses changes in estimated building-

related losses using NGA models compared to Boore et al. (1997) and Boore and Joyner (1988)

GMPEs. Comparison with other existing loss estimate results is also attempted. Section 6

discusses remaining issues and summarizes major findings. Detailed results for all scenarios are

compiled in Appendix A.


10/47

10

2. SELECTION OF SCENARIO EARTHQUAKES

Two groups of scenario earthquakes were selected and analyzed, namely the USGS

scenarios and UCERF 2-based scenarios. USGS scenarios for California are published on the

USGS website. UCERF 2-based scenarios are newly developed for this project.

2.1 USGS Scenarios

The USGS scenarios analyzed in this study for CalEMA include almost all of the scenarios

for California published on the USGS ShakeMap Archive website

(http://earthquake.usgs.gov/eqcenter/shakemap/list.php?x=1&n=nc&s=1 for northern California

and http://earthquake.usgs.gov/eqcenter/shakemap/list.php?x=1&n=sc&s=1 for southern

California). In northern California, 35 of the 36 published scenarios were analyzed. The

scenario with USGS Event ID SanAndreas_1a_se is excluded because it is redundant with

SanAndreas_1_se. Table 2-1 lists general information of these scenarios. ID numbers (column

1in table 2-1) are assigned mainly for bookkeeping purposes. Event names and USGS Event IDs

(columns 2 and 5 in table 2-1) are the same as those listed on the USGS website for easy

comparison and verification. The table also lists the assumed event magnitude and the date the

scenario was generated. For each scenario, the event name constitutes the abbreviated fault

name and an underscore followed by the abbreviated name of fault section that is assumed to

rupture to produce the earthquake. In southern California, 21 published scenarios were analyzed

(Table 2-2). Table 2-3 lists abbreviated section names and corresponding full names used in this

study and other information taking from the UCERF 2 report (WGCEP and NSHMP, 2008, table

4).

The existing ShakeMaps of potential earthquakes published by the USGS for California were

developed based on ground motion parameters calculated using the GMPEs of Boore et al.

(1997) for PGA, SA03, and SA10 and Joyner and Boore (1988) for PGV. The GMPEs allow

estimation of ground motion parameters for an assumed magnitude and fault rupture model. For

generating ShakeMaps and for HAZUS loss estimates, ground motions are calculated on a grid

centered along the causative fault. USGS scenario ShakeMaps for California used fault source

parameters of the 2002 statewide probabilistic seismic hazard assessments (Cao et al., 2003).

Ground motion parameters at rock sites were estimated using the above mentioned GMPEs and

then corrected for site soil conditions. The site conditions were determined from the Statewide

Site Conditions Map for California (Wills et al., 2000). Correction for site amplification was

made with the amplitude and frequency-dependent factors determined by Borcherdt (1994).


11/47

11

Table21.ScenarioEarthquakesinNorthernCalifornia

ID EventName Magnitude Date USGSEventIDSanAndreasFault

N1 SAF_SAS+SAP+SAN+SAO

(Repeatof1906earthquake)

7.90 3/6/03 SanAndreas_10_se

N2

SAF_SAS+SAP+SAN

7.76

3/6/03

SanAndreas_8_se

N3 SAF_SAP+SAN+SAO 7.83 3/6/03 SanAndreas_9_se

N4 SAF_SAS+SAP 7.42 3/6/03 SanAndreas_5_se

N5 SAF_SAS 7.03 3/6/03 SanAndreas_1_se

N6 SAF_SAP

(Repeatof1838earthquake)

7.15 3/6/03 SanAndreas_2_se

N7 SAF_SAN+SAO 7.70 3/6/03 SanAndreas_7_se

N8 SAF_SAN 7.45 3/6/03 SanAndreas_3_se

N9 SAF_SAO 7.29 3/6/03 SanAndreas_4_se

HaywardRodgersCreekFault

N10 HRC_HS

(Repeat

of

1868

earthquake)

6.67 3/6/03 HaywardRC_1_se

N11 HRC_HN 6.49 3/6/03 HaywardRC_2_se

N12 HRC_HS+HN 6.91 3/6/03 HaywardRC_4_se

N13 HRC_RC 6.98 3/6/03 HaywardRC_5_se

N14 HRC_HN+RC 7.11 3/6/03 HaywardRC_3_se

N15 HRC_HS+HN+RC 7.26 3/6/03 HaywardRC_6_se

CalaverasFault

N16 CLV_CS 5.78 3/6/03 Calaveras_1_se

N17 CLV_CC 6.23 3/6/03 Calaveras_2_se

N18 CLV_CS+CC 6.36 3/6/03 Calaveras_3_se

N19 CLV_CN 6.78 3/6/03 Calaveras_4_se

N20 CLV_CC+CN 6.90 3/6/03 Calaveras_5_se

N21

CLV_CS+CC+CN

6.93

3/6/03

Calaveras_6_se

ConcordGreenValleyFault

N22 CGV_CON 6.25 3/6/03 ConcordGV_1_se

N23 CGV_GVS 6.24 3/6/03 ConcordGV_2_se

N24 CGV_CON+GVS 6.58 3/6/03 ConcordGV_3_se

N25 CGV_GVN 6.02 3/6/03 ConcordGV_4_se

N26 CGV_GVS+GVN 6.48 3/6/03 ConcordGV_5_se

N27 CGV_CON+GVS+GVN 6.71 3/6/03 ConcordGV_6_se

SanGregorioFault

N28 SGF_SGS 7.0 3/6/03 SanGregorio_1_se

N29 SGF_SGN 7.2 3/6/03 SanGregorio_2_se

N30

SGF_SGS+SGN

7.4

3/6/03

SanGregorio_3_seGreenvilleFault

N31 GNV_GS 6.6 3/6/03 GreenVille_1_se

N32 GNV_GN 6.7 3/6/03 GreenVille_2_se

N33 GNV_GS+GN 6.9 3/6/03 GreenVille_3_se

Mt.DiabloFault

N34 MTD 6.65 3/6/03 MtDiablo_se

GreatValleyFault

N35 GV ? 3/6/03 GreatValley_6_se


12/47

12

Table22.ScenarioEarthquakesinSouthernCalifornia

ID EventName Magnitude Date USGSEventIDS1 VerdugoFault 6.7 4/21/09 Verdugo6.7_se

S2 SanAndreasFaultSouthern 7.8 8/3/06 SAF_south7.8_se

S3 ChinoHillsFault 6.7 5/30/05 Chino_Hills6.7_se

S4

SanJoce

Carro

Prieto

7.0

5/25/04

SJCP_se

S5 HosgriFault 7.5 3/8/04 Hosgri75_se

S6 ElsinoreJulianFault 7.1 8/12/03 Elsinore_Julian7.1_se

S7 NorthChannelSlope 7.4 3/24/03 North_Channel_se

S8 PuenteHills 7.1 1/11/03 Puente_Hills_se

S9 SanJoaquinHills 6.6 1/11/03 San_Joaquin_Hills_se

S10 ElsinoreFault 6.8 4/10/02 Elsinore6.8_se

S11 RaymondFault 6.5 4/4/02 Raymond6.5_se

S12 Whittier 6.8 3/11/02 Whittier6.8_se

S13 ImperialValley 7.0 1/26/02 Imperial_se

S14 CoachellaValley 7.1 11/14/01 Coachella7.1_se

S15

San

Andreas

Fault

Southern

7.4

11/14/01

SAF_south7.4_se

S16 SanJacintoFault 6.7 9/14/01 SanJacinto6.7_se

S17 NewportInglewoodFault 6.9 8/3/01 Newport_Inglewood6.9_se

S18 PalosVerdes 7.1 8/3/01 Palos_Verdes7.1_se

S19 SantaMonicaFault 6.6 7/16/01 StaMonica6.6_se

S20 RoseCanyon 6.9 7/3/01 Rose_Canyon6.9_se

S21 SanAndreasFault1857 7.8 2/15/02 1857_se


13/47

13

Table 2-3 Section Abbreviation, Full Name, and Other Available Information in California1

Abbreviation FullName Length(km) SlipRate(mm/yr) LastEvent(year)

NorthernSanAndreasFault(SAF)

SAO Offshore 136.1 24.0 1906

SAN

NorthCoast

189.4

24.0

1906

SAP Peninsula 84.5 17.0 1906

SAS SantaCruzMountain 472.1 17.0 1906

HaywardRodgersCreekFault (HRC)

RC RodgersCreek 62.4 9.0 1758

HN HaywardNorth 34.8 9.0 1715

HS HaywardSouth 52.5 9.0 1868

CalaverasFault(CF)

CN CalaverasNorth 45.2 6.0 1775

CC CalaverasCentral 58.9 15.0 1982

CS CalaverasSouth 19.3 15.0 1899

Concord

Green

Valley

Fault

(CGV)

CON Concord

NotCompiledGVS GreenValleySouth

GVN GreenValleyNorth

SanGregorioFault(SGF)

SGS SanGregorioSouth NotCompiled

SGN SanGregorioNorth

GreenvilleFault(GNV)

GS GreenvilleSouth NotCompiled

GN GreenvilleNorth

Mt.DiabloFault(MTD) NotCompiled

GreatValleyFault(GV) NotCompiled

SouthernSan

Andreas

Fault

(SAF)

CO Coachella 69.4 20.0 1680

SanJacintoFault(SJ)

SBV SanBernardino 45.1 6.0 1769

SJV SJValley 42.7 12.9 1918

A Anza 71.1 14.8 1795

C Clark 46.8 14.0 17951afterWGCEP(2008),table4


14/47

14

2.2 UCERF 2 Based Scenarios

UCERF 2-based scenarios were developed with the objective of assessing the effects of

NGA models on HAZUS loss estimates. The selection for UCERF 2-based scenarios is based on

the probability results of UCERF 2 (WGCEP, 2008). Due to limited time and resources, only 10

scenarios were analyzed, 7 scenarios for potential earthquakes on four Type-A faults and 3scenarios for potential earthquakes on Type-B faults.

We selected scenario earthquakes from four Type-A faults, the Southern San Andreas

Fault, San Jacinto Fault, Hayward-Rodgers Creek Fault, and Northern San Andreas Fault. These

four Type-A faults have the highest 30 year fault probability for M 6.7 ruptures among all

faults in California (WGCEP, 2008, Supplementary Excel Spreadsheet, Sheet 11). Table 2-4

lists essential information for UCERF 2-based scenarios, including event ID, event name, fault

name, assumed magnitude, date the scenario was generated, and comparable USGS scenarios.

Similar to the USGS scenarios, event names constitute abbreviations of faults and fault sections

that are assumed to rupture to produce the earthquakes. For each fault, the general rule is toselect one scenario with the largest magnitude and one with the highest 30 year rupture

probability for M 6.7 (from UCERF 2 full logic tree rupture scenarios, WGCEP, 2008,

Supplementary Excel Spreadsheet, Sheet 4). The exceptions are the Southern San Andreas Fault

and the San Jacinto Fault. Only the scenario with the highest probability was chosen for the

Southern San Andreas Fault. The scenario with the largest magnitude on this fault is similar to

the ShakeOut Scenario (Jones et al., 2008). The potential economic losses and other

implications of such an earthquake have been studied and documented in great detail. For the

San Jacinto Fault, the scenario with the largest magnitude involves co-seismic rupture of two

groups of fault segments with distinctively different orientations, and this scenario was

considered unlikely by WGCEP (2008) and assigned a very low probability. Therefore, weselected an event with slightly smaller magnitude that is more likely to occur.

The rationale for Type-B fault scenario selection was different from that for Type-A

faults. One scenario for each of the three selected Type-B faults was developed and analyzed

mainly because of great potential impact and disruption to society due to proximity of these

faults to large metropolitan areas. The three selected Type-B faults are the Imperial Fault, the

Palos Verdes Fault, and the Newport-Inglewood Fault (Table 2-4). All three are in southern

California.

For each UCERF-2 based scenario, the earthquake magnitude is determined as the meanof Ellsworth B and Hanks & Bakun magnitudes, as listed in the UCERF 2 Supplementary Excel

Spreadsheet (Sheet 4, WGCEP, 2008). Fault geometric parameters were taken directly from the

2008 National Seismic Hazard Maps and UCERF 2 (Wills et al., 2007). PGA, PGV, SA03, and

SA10 were calculated on a grid by CGS using a Fortran program developed by Art Frankel of

USGS (Frankel, 2009) and three NGA models with equal weight. These NGA models are from

Boore and Atkinson (2008), Campbell and Bozorgnia (2008), and Chiou and Youngs (2008).

These same three models are used in the 2008 National Seismic Hazard Maps (Petersen et al.,


15/47

15

2008). Ground motion parameter data files calculated by CGS were provided to the USGS to

generate ShakeMap files (HAZUS.zip) that can be used to define ground motion hazards in

HAZUS. ShakeMap files were generated using the USGS ShakeMap software in the way that is

consistent with published ShakeMaps on the USGS ShakeMap Archive website (courtesy of

Vincent Quitoriano of USGS).

A significant difference between the NGA models and the previous GMPEs is the use of

the average shear-wave velocity in the upper 30 meters of sediments, V s30, as the parameter for

characterizing site effects on ground motions. The use of Vs30 is considered to result in a much

improved characterization of site amplification effects as compared to site classifications and

amplification factors in the pre-existing relations. The latest Vs30 map for California (Wills and

Clahan, 2006) is used in calculating ground motions for the UCERF 2-based scenarios.

Seven of the UCERF-2 based scenarios are comparable to the USGS published scenarios.

These are indicated in Table 2-4. HAZUS results for these comparable scenarios are discussed

in Section 5 of this report to evaluate the effects of NGA models on loss estimates.

Table 2-4 UCERF 2-Based Scenarios

ID EventName FaultName Magnitude Date ComparableUSGSScenario

AFaults

U1 SAF_CO SouthernSan

Andreas

6.95 5/29/09 S14Coachela7.1_se

U2 SJ_SBV+SJV+A+C SanJacinto 7.76 6/09/09 None

U3 SJ_A+C SanJacinto 7.49 5/29/09 None

U4

HRC_RC+HN+HS

HaywardRodgers

Creek7.29

5/29/09

N15

HaywardRC_6_se

U5 HRC_RC HaywardRodgers

Creek

6.98 5/29/09 N13HaywardRC_4_se

U6 SAF_SAO+SAN+SAP+SAS NorthernSan

Andreas

7.99 5/29/09 N1SanAndreas_10_se

U7 SAF_SAP+SAS NorthernSan

Andreas

7.47 5/29/09 N4SanAndreas_5_se

BFaults

U8 Imperial Imperial 6.9 5/29/09 S13Imperial_se

U9 PalosVerdes PalosVerdes 7.2 5/29/09 S18

Palos_Verdes7.1_seU10 NewportInglewood Newport

Inglewood

7.2 5/29/09 S17Newport_Inglewood

6.9_se


16/47

16

3. HAZUS INVENTORY AND ANALYSES

HAZUS-MH MR3 runs on the ArcGIS 9.3 platform. The current project uses HAZUS-

MH MR3 default data for built environment and demographics and user-supplied scenario

ShakeMap ground motions for earthquake hazard. Estimated losses for this project only include

those due to ground shaking. Other potential earthquake effects such as liquefaction, landslides,

and surface faulting are not considered, although these earthquake features can cause permanent

ground displacements and have adverse effects on transportation and lifeline structures as well as

building structures.

The default information on built environment and demographics in HAZUS-MH MR3 is

based on year 2000 or newer site specific inventory data. These include: the 2002-aggregated

data for square footage, building count, building exposure, content exposure and demographics;

the Bureau of Census 2000 census of population and housing data; the Dun & Bradstreet 2006

business population data; and the 2006 R.S. Means building valuation data. HAZUS-MH MR3

SP2 incorporates the 2007 National Earthquake Information Center data. More details can be

found in a document titled Summary of Databases in HAZUS-MH. It can be found on the

FEMA website at http://www.fema.gov/plan/prevent/hazus/hz_database.shtm.

Uncertainties are inherent in HAZUS loss estimates, just as they are inherent in other

hazard, risk, and loss estimate methodologies. Uncertainties arise in part from incomplete

scientific knowledge concerning earthquake occurrence and ground motion characteristics and

their effects on buildings and other facilities. They also result from incomplete or inaccurate

inventories of the built environment, demographics, and economic parameters. A third source of

uncertainties comes from the approximations and simplifications that are necessary for model

analyses. It is estimated that these factors can result in total uncertainties in loss estimates

produced by the HAZUS-MH Earthquake Model of up to a factor of two or more (FEMA, 2009).

The HAZUS-MH Earthquake Model provides a credible estimate of aggregated losses

such as the total cost of damage and numbers of casualties when used with embedded inventories

and parameters (FEMA, 2009). HAZUS has done less well in estimating more detailed results,

such as the number of buildings or bridges experiencing different degrees of damage (FEMA,

2009).

Some specific limitations associated with HAZUS-MH Earthquake Model have been

noted by FEMA (2009). These limitations should be recognized when interpreting HAZUS loss

results. In particular: (1) building losses must be considered as averages for groups of similar

buildings; (2) accuracy of losses associated with lifelines may be less than for losses from the

general building stock when using embedded inventories due to simplifications and necessary

assumptions used to characterize the lifeline systems; and (3) losses from small magnitude

earthquakes (M < 6.0) in extensive urban regions may be overestimated.


17/47

17

The estimated scale and extent of potential damage and disruption by the HAZUS

Earthquake Model are useful information in preparing emergency response plans. HAZUS

results can be applied in developing earthquake hazard mitigation strategies and in evaluating the

nature and scope of response and recovery efforts prior to the earthquake. HAZUS results may

also have post-earthquake applications, including projection of immediate economic impact and

resource allocation, activation of immediate emergency recovery efforts, and planning for long-term reconstruction.


18/47

18

4. RESULTS

Results from HAZUS analyses are presented in the following two sections for USGS

scenarios and for UCERF 2-based scenarios, respectively. Pertinent results from all scenarios

are summarized and presented in tables. A compilation of results for all scenarios is provided in

Appendix A. A full set of results is also presented in this chapter for a selected USGS scenario

and a UCERF 2-based scenario as examples to illustrate the content of the electronic attachment.

4.1 USGS Scenarios

Tables 4-1 through 4-3 present selected HAZUS results for northern California scenario

earthquakes and tables 4-4 through 4-6 present similar results for southern California scenario

earthquakes. The results are categorized as economic losses (tables 4-1 and 4-4), social impact

and induced damages (tables 4-2 and 4-5), and facility damage (tables 4-3 and 4-6). Economic

losses include building-related losses and losses of transportation and utility systems. Social

impact includes number of mortalities (level 4 casualties) if the earthquake were to occur at 2

A.M. (at home time), 2 P.M. (at work time), and 5 P.M. (commute time), respectively. Social

impact also includes displaced households and short-term shelter needs. Induced damage

includes debris generated. The facility damage table lists facilities with at least moderate

damage, i.e., damage state greater than or equal to 50%. The listed facilities include highway

bridges, airports, hospitals, schools, and buildings. Again, these are selected results only. Other

summary results can be found in the electronic attachment, in particular, in the Global Summary

Report.

In northern California, the predicted three most damaging earthquakes are due to three

different rupture scenarios of the Northern San Andreas Fault (N1 through N3). The most

damaging earthquake is scenario N1, a repeat of the 1906 San Francisco M 7.9 earthquake. This

scenario involves rupturing all four segments of the Northern San Andreas Fault, namely the

Offshore, North Coast, Peninsula, and Santa Cruz Mountain segments. The total rupture length

is near 900 kilometers. This earthquake would cause nearly $84 billion of economic loss, mostly

building-related. It would kill 1000 to 4000 people, displace nearly 64 thousand households, and

generate 23 million tons of debris. It would cause at least moderate damage on nearly 700

locations of highway bridges, 7 locations of airports, 6 schools, and over 343 thousand buildings.

Should all three segments of the Hayward-Rodgers Creek Fault rupture (co-seismic rupturing

of Southern Hayward, Northern Hayward, and Rodgers Creek segments, total length of

approximately 150 kilometers), it would produce a magnitude 7.3 earthquake causing nearly $40

billion of economic loss, 100 to over 500 deaths, and at least moderate damage of over 100

highway locations and 200 thousand buildings.


19/47

19

Table 4-1. Northern California Scenario Earthquakes and Associated Economic Losses

Scenario Earthquakes MEconomic Losses ($M)

Buildings Related TransportationSystem

UtilitySystem

N1 SAF_SAS+SAP+SAN+SAO 7.90 79,834 1,436 2,583

N2

SAF_SAS+SAP+SAN

7.76

70,628 1,172 2,026

N3 SAF_SAP+SAN+SAO 7.83 66,216 1,162 1,856

N4 SAF_SAS+SAP 7.42 34,299 721 1,212

N5 SAF_SAS 7.03 6,789 118 353

N6 SAF_SAP 7.15 24,788 472 845

N7 SAF_SAN+SAO 7.70 17,814 426 910

N8 SAF_SAN 7.45 11,474 344 798

N9 SAF_SAO 7.29 161 32 100

N10 HRC_HS 6.67 14,469 221 613

N11 HRC_HN 6.49 7,655 180 518

N12 HRC_HS+HN 6.91 22,660 426 983

N13 HRC_RC 6.98 6,582 153 572

N14 HRC_HN+RC 7.11 19,244 508 1,163

N15 HRC_HS+HN+RC 7.26 36,883 826 1,695

N16 CLV_CS 5.78 168 12 23

N17 CLV_CC 6.23 2,666 45 135

N18 CLV_CS+CC 6.36 3,422 52 153

N19 CLV_CN 6.78 10,176 137 433

N20 CLV_CC+CN 6.90 13,534 182 528

N21

CLV_CS+CC+CN

6.93

14,217 196 540N22 CGV_CON 6.25 2,644 76 288

N23 CGV_GVS 6.24 1,872 78 280

N24 CGV_CON+GVS 6.58 5,326 122 455

N25 CGV_GVN 6.02 528 48 115

N26 CGV_GVS+GVN 6.48 2,267 96 351

N27 CGV_CON+GVS+GVN 6.71 6,631 144 513

N28 SGF_SGS 7.0 963 19 80

N29 SGF_SGN 7.2 12,111 274 567

N30 SGF_SGS+SGN 7.4 15,005 361 742

N31

GNV_GS

6.6

1,752 59 191N32 GNV_GN 6.7 3,198 79 319

N33 GNV_GS+GN 6.9 5,175 109 439

N34 MTD 6.65 7,296 118 472

N35 GV ? 3,503 111 513


20/47

20

Table 4-2. Northern California Scenarios and Associated Social Impact and Induced Damage

Scenario Earthquakes MSocial Impact (number of people)

DebrisGenerated(thousand

tons)

Level 4 Casualties(Deaths)

Shelter Requirement

2 A.M. 2 P.M. 5 P.M.

Displaced

Households

Short-

TermShelterNeeds

N1 SAF_SAS+SAP+SAN+SAO 7.90 927 4,616 3,641 63,762 37,776 23,445

N2 SAF_SAS+SAP+SAN 7.76 721 3,655 2,874 56,786 33,585 20,711

N3 SAF_SAP+SAN+SAO 7.83 746 3,762 2,944 56,168 32,471 19,374

N4 SAF_SAS+SAP 7.42 95 517 561 18,744 11,035 7,867

N5 SAF_SAS 7.03 1 6 14 638 478 970

N6 SAF_SAP 7.15 36 203 245 11,228 6,464 5,017

N7 SAF_SAN+SAO 7.70 132 565 421 16,069 9,000 5,082

N8 SAF_SAN 7.45 10 43 62 4,762 2,598 2,118

N9

SAF_SAO

7.29

0 0 1 17 12 29N10 HRC_HS 6.67 5 26 43 2,821 2,040 2,407

N11 HRC_HN 6.49 1 5 8 1,382 953 1,081

N12 HRC_HS+HN 6.91 22 104 137 7,837 5,600 4,527

N13 HRC_RC 6.98 4 19 28 1,067 696 1,103

N14 HRC_HN+RC 7.11 26 109 127 7,955 5,450 3,993

N15 HRC_HS+HN+RC 7.26 107 467 522 19,190 13,440 8,808

N16 CLV_CS 5.78 0 0 0 2 2 13

N17 CLV_CC 6.23 0 0 1 40 35 235

N18 CLV_CS+CC 6.36 0 0 2 90 78 344

N19 CLV_CN 6.78 2 13 31 879 542 1,406

N20

CLV_CC+CN

6.90

3 25 53 1,574 1,069 2,067N21 CLV_CS+CC+CN 6.93 4 32 62 1,800 1,231 2,237

N22 CGV_CON 6.25 0 1 2 126 80 237

N23 CGV_GVS 6.24 0 0 1 27 19 152

N24 CGV_CON+GVS 6.58 1 6 12 451 282 646

N25 CGV_GVN 6.02 0 0 0 2 1 31

N26 CGV_GVS+GVN 6.48 0 1 3 77 53

N27 CGV_CON+GVS+GVN 6.71 1 12 20 700 433 879

N28 SGF_SGS 7.0 0 0 1 75 46 127

N29 SGF_SGN 7.2 5 29 50 3,129 1,830 1,978

N30 SGF_SGS+SGN 7.4 12 69 103 5,125 2,944 2,690

N31

GNV_GS

6.6

0 0 2 20 12 145

N32 GNV_GN 6.7 0 1 4 74 44 289

N33 GNV_GS+GN 6.9 0 7 15 203 126 582

N34 MTD 6.65 1 7 15 679 374 904

N35 GV ? 1 7 20 382 289 0


21/47

21

Table 4-3. Northern California Scenarios and Facilities with at Least Moderate Damage

Scenario Earthquakes MTransportation Systems

(number of locations)Essential Facilities

(number of facilities)Buildings

(number ofbuildings)Highway

BridgesAirports Hospitals Schools

N1

SAF_SAS+SAP+SAN+SAO

7.90

697 7 0 6 343,485N2 SAF_SAS+SAP+SAN 7.76 505 6 0 3 321,126

N3 SAF_SAP+SAN+SAO 7.83 472 6 0 1 277,645

N4 SAF_SAS+SAP 7.42 164 0 0 0 185,843

N5 SAF_SAS 7.03 7 0 0 0 34,125

N6 SAF_SAP 7.15 48 0 0 0 127,263

N7 SAF_SAN+SAO 7.70 69 4 0 1 64,406

N8 SAF_SAN 7.45 27 3 0 0 40,851

N9 SAF_SAO 7.29 0 1 0 0 1,522

N10 HRC_HS 6.67 9 0 0 0 67,400

N11 HRC_HN 6.49 0 0 0 0 27,642

N12 HRC_HS+HN 6.91 26 0 0 0 121,534

N13 HRC_RC 6.98 19 0 0 0 37,254

N14 HRC_HN+RC 7.11 45 0 0 0 106,174

N15 HRC_HS+HN+RC 7.26 108 0 0 0 224,066

N16 CLV_CS 5.78 0 0 0 0 512

N17 CLV_CC 6.23 0 0 0 0 6,938

N18 CLV_CS+CC 6.36 1 0 0 0 10,597

N19 CLV_CN 6.78 1 0 0 0 37,737

N20 CLV_CC+CN 6.90 7 0 0 0 62,750

N21 CLV_CS+CC+CN 6.93 10 0 0 0 68,217

N22

CGV_CON

6.25

0 0 0 0 6,172

N23 CGV_GVS 6.24 0 0 0 0 3,630

N24 CGV_CON+GVS 6.58 0 0 0 0 20,131

N25 CGV_GVN 6.02 0 0 0 0 702

N26 CGV_GVS+GVN 6.48 0 9 0 0 8,087

N27 CGV_CON+GVS+GVN 6.71 3 0 0 0 27,317

N28 SGF_SGS 7.0 0 0 0 0 4,401

N29 SGF_SGN 7.2 4 2 0 0 43,853

N30 SGF_SGS+SGN 7.4 10 2 0 0 58,663

N31 GNV_GS 6.6 0 0 0 0 3,102

N32

GNV_GN

6.7

0 0 0 0 7,921N33 GNV_GS+GN 6.9 0 0 0 0 16,684

N34 MTD 6.65 1 0 0 0 29,338

N35 GV ? 11 0 0 0 22,666


22/47

22

Table 4-4. Southern California Scenario Earthquakes and Associated Economic Losses

Scenario Earthquakes M

Economic Losses ($M)

Buildings

Related

Transportation

System

Utility

System

S1 VerdugoFault 6.7 23,751 270 826

S2 SanAndreasFaultSouthernM7.8 7.8 20,515 503 1,489

S3 ChinoHillsFault 6.7 11,390 104 554

S4 SanJoce CarroPrietoFault 7.0 267 17 213

S5 HosgriFault 7.5 1,020 47 232

S6 ElsinoreFault(Julian) 7.1 1,184 51 129

S7 NorthChannelSlope 7.4 5,814 140 553

S8 PuenteHillsFault 7.1 79,662 1178 1,966

S9 SanJoaquinHillsFault 6.6 16,557 165 482

S10 ElsinoreFault 6.8 2,481 64 190

S11 RaymondFault 6.5 16,495 158 587

S12 WhittierFault 6.8 15,965 155 649

S13 ImperialValleyFault 7.0 421 37 341

S14 SanAndreasFaultCoachellaValley 7.1 5,138 152 287

S15 SanAndreasFaultSouthernM7.4 7.4 9,138 279 897

S16 SanJacintoFault 6.7 4,366 89 328

S17 NewportInglewoodFault 6.9 34,319 482 958

S18 PalosVerdesFault 7.1 20,084 367 796

S19 SantaMonicaFault 6.6 16,308 99 490

S20 RoseCanyonFault 6.9 9,771 183 456

S21 SanAndreasFault 1857 7.8 12,586 367 1,257


23/47

23

Table 4-5. Southern California Scenarios and Associated Social Impact and Induced Damage


Social Impact (number of people)

Debris1

Generated

(M tons)

Level 4 Casualties Shelter Requirement

2 am 2 pm 5 pm

Displaced

Households

Short-Term

Shelter Needs

S1 VerdugoFault 6.7 26 93 103 9,009 7,485 -

S2 SanAndreasFault

SouthernM7.8

7.8 176 632 536 8,517 8,098 -

S3 ChinoHillsFault 6.7 3 18 29 854 771 -

S4 SanJoce CarroPrietoFault 7.0 1 2 2 129 162 -

S5 HosgriFault 7.5 3 12 12 235 177 0

S6 ElsinoreFault(Julian) 7.1 0 0 1 13 10 -

S7 NorthChannelSlope 7.4 65 268 227 4,537 3,539 -

S8 PuenteHillsFault 7.1 489 1,997 1710 58,100 57,690 -

S9 SanJoaquinHillsFault 6.6 14 86 94 4,656 3,125 -

S10 ElsinoreFault 6.8 0 2 6 132 103 -

S11 RaymondFault 6.5 7 25 26 3,949 3,227 -

S12 WhittierFault 6.8 4 22 41 1,952 1,728 -

S13 ImperialValleyFault 7.0 1 3 3 144 160 -

S14 SanAndreasFault

CoachellaValley

7.1 6 16 27 1,110 1,041 -

S15 SanAndreasFault

SouthernM7.4

7.4 26 76 103 2,765 2,644 -

S16 SanJacintoFault 6.7 3 13 17 853 836 -

S17 NewportInglewoodFault 6.9 65 206 230 19,705 17,251 -

S18 PalosVerdesFault 7.1 29 129 133 8,265 6,026 4

S19 SantaMonicaFault 6.6 7 27 30 5,386 3,220 -

S20 RoseCanyonFault 6.9 12 51 57 5,117 3,253 -

S21 SanAndeasFault1857 7.8 65 302 258 2,896 2,629 3

1Debris generated were not successfully calculated for some scenarios


24/47

24

Table 4-6. Southern California Scenarios and Facilities with at Least Moderate Damage


Transportation Systems

(number of locations)

Essential Facilities

(number of facilities) Buildings

(number of

buildings)

Highway Bridges Airports Hospitals Schools

S1 VerdugoFault 6.7 30 0 0 0 125,890

S2 SanAndreasFault

SouthernM7.8

7.8 239 3 0 0 117,701

S3 ChinoHillsFault 6.7 4 0 0 0 57,617

S4 SanJoce CarroPrieto

Fault

7.0 1 0 0 0 2,960

S5 HosgriFault 7.5 8 0 0 0 9,895

S6 ElsinoreFault(Julian) 7.1 1 0 0 0 6,657

S7 NorthChannelSlope 7.4 214 4 0 0 33,639

S8 PuenteHillsFault 7.1 569 2 0 0 470,746

S9 SanJoaquinHillsFault 6.6 8 0 0 0 89,409

S10 ElsinoreFault 6.8 0 0 0 0 14,006

S11 RaymondFault 6.5 3 0 0 0 69,484

S12

WhittierFault

6.8

4 0 0 0 67,911

S13 ImperialValleyFault 7.0 1 0 0 0 4,234

S14 SanAndreasFault

CoachellaValley

7.1 7 0 0 5 47,845

S15 SanAndreasFault

SouthernM7.4

7.4 74 0 0 0 74,938

S16 SanJacintoFault 6.7 18 0 0 0 29,594

S17

Newport

Inglewood

Fault

6.9

83 0 0 0 172,560

S18 PalosVerdesFault 7.1 21 1 0 0 85,378

S19 SantaMonicaFault 6.6 0 0 0 0 51,905

S20 RoseCanyonFault 6.9 15 0 0 0 55,396

S21 SanAndreasFault1857 7.8 123 3 0 0 62,804


25/47

25

In the northern California scenarios, the estimated loss ratio is a few percent in most

areas. However, in some cases, loss ratio exceeds 10 percent in the immediate vicinity of the

rupturing fault. For the three most damaging earthquakes on the Northern San Andreas Faults,

loss ratio as high as 50 percent was estimated for some census tracts in northeast San Mateo

County.

HAZUS estimates none of the scenarios would cause moderate or greater damage to any

hospitals. A few scenarios would cause 1 to 6 schools to suffer at least moderate damage. The

highest number of fatalities is predicted if an earthquake would occur during working hours.

Predicted working hour fatalities are generally about 5 times higher than the numbers predicted

when most people are in their wood frame homes. Twelve scenarios would cause more than 20

highway bridge locations to suffer at least moderate damage. Nine scenarios would cause more

than 1 location of airports to have at least moderate damage.

In southern California, the predicted most damaging earthquakes are those which occur in

the Los Angeles basin. Outside of the Los Angeles basin, the most damaging event is the

magnitude 7.8 along the southern part of the San Andreas Fault.

A complete set of detailed results is presented for a northern California scenario (N1

SAF_SAS+SAP+SAN+SAO, co-seismic rupturing of all four segments of the Northern San

Andreas Fault) as an example. The detailed results reported here include 6 maps, 4 tables, and 2

summary reports. The first map shows the USGS shaking intensity map (ShakeMap, see figure

4-1). This map shows that most intensive shaking occurs in the immediate vicinity of the fault

section that is assumed to rupture to produce the earthquake. In general, shaking intensity

decreases as distance from the fault increases. Other ground motion parameters (PGA, PGV,

SA03, and SA10) have similar distributions. Maps 2 through 6 show the distribution of peak

ground acceleration, total building loss, building loss ratio, displaced households, and debris by

census tract (figures 4-2 through 4-6). These are standard HAZUS maps except building loss

ratio map (figure 4-4). Building loss ratio is calculated as the ratio of economic loss due to

building damage to building replacement value for each census tract. The economic loss due to

building damage includes losses due to structural damage and non-structural damage and

excludes losses related to contents damage, inventory loss, relocation cost, income loss, rental

income loss, and wage loss. Building replacement value is dollar exposure of buildings

(excluding contents). The first table (table B-1 in Appendix B) presents important dam

inventory data (including name, county, owner, dam height, and maximum storage) along with

ground motion amplitudes (PGA, PGV, SA03, and SA10) at the dam location. The data is sortedby SA10 in a descending order. The 2

ndand 3

rdtables are standard HAZUS tables listing direct

economic loss for buildings and short term shelter needs, respectively, for each county (tables B-

2 and B-3, in Appendix B). Direct economic loss includes building-related losses due to

building damage (structural damage and non-structural damage), contents damage, inventory

loss, relocation cost, income loss, rental income loss, and wage loss. Earthquakes may produce

dislocations in economic sectors not sustaining direct damage. All businesses are forward-linked


26/47

26

(rely on regional customers to purchase their output) or backward-linked (rely on regional

suppliers to provide their inputs) and are thus potentially vulnerable to interruptions in their

operation. Such interruptions are called indirect economic losses (FEMA, 2009). Indirect losses

are not report for this project. The 4th table (table B-4) summarizes casualties by county. Two

HAZUS standard summary reports are also included. These are Global Summary Report, and

Quick assessment reports (Reports B-1 and B-2a through B-2c in Appendix B). Again, acomplete set of these maps, tables, and summary reports is compiled in Appendix A.


27/47

27

Figure 4-1 Shaking Intensity Map (USGS ShakeMap)


28/47

28

Fi ure 4-2 Peak Ground Acceleration b Census Tract HAZUS Ma


29/47

29

Figure 4-3 Total Building Loss by Census Tract (HAZUS Map)


30/47

30

Figure 4-4 Loss Ratio by Census Tract


31/47

31

Figure 4-5 Displaced Household by Census Tract (HAZUS Map)


32/47

32

Figure 4-6 Debris Generated by Census Tract (HAZUS Map)


33/47

33

4.2 UCERF 2 Based Scenarios

Tables 4-7 through 4-9 present selected HAZUS results for UCERF 2-based scenarioearthquakes. Similar to USGS scenario results in the previous section, results are categorized aseconomic losses (tables 4-7), social impact and induced damages (tables 4-8), and facilitydamage (tables 4-9). A complete compilation of results can be found in Appendix A. Among

the UCERF 2-based, selected earthquake scenarios, the most damaging event is the magnitude7.2 earthquake on the Newport-Inglewood fault. It would cause over $45 billion total economicloss, kill 65 to 276 people, displace 23 thousand households, and cause at least moderate damageat 91 highway bridge locations and 4 airport locations. Other earthquakes with over $20 billionestimated losses among the UCERF 2-based scenarios include a magnitude 7.99 earthquakerupturing the entire Northern San Andreas Fault causing nearly $32 billion in losses and amagnitude 7.29 earthquake rupturing the entire Hayward-Rodgers Creek Fault leading to over$23 billion in losses.

Table 4-7. UCERF 2-Based Scenario Earthquakes and Associated Economic Losses

Scenario Earthquakes MEconomic Losses ($M)

BuildingsRelated

TransportationSystem

Utility System

U1 SAF_CO 6.95 684 3 163

U2 SJ_SBV+SJV+A+C 7.76 10,983 224 798

U3 SJ_A+C 7.49 2,654 69 302

U4 HRC_RC+HN+HS 7.29 21,966 404 1,136

U5 HRC_RC 6.98 3,963 93 424

U6 SAF_SAO+SAN+SAP+SAS 7.99 29,412 503 1,857

U7 SAF_SAP+SAS 7.47 17,031 303 738

U8

Imperial

6.9

236 18 274U9 PalosVerdes 7.2 14,513 324 782

U10 NewportInglewood 7.2 42,980 671 1,679


34/47

34

Table 4-8. UCERF 2-Based Scenarios and Associated Social Impact and Induced Damage

Scenario Earthquakes MSocial Impact (number of people)

DebrisGenerated(thousan

tons)

Level 4 Casualties Shelter Requirement

2 A.M. 2 P.M. 5 P.M. DisplacedHouseholds

Short-TermShelter

NeedsU1 SAF_CO 6.95 1 2 5 142 147 -

U2 SJ_SBV+SJV+A+C 7.76 60 238 176 4,388 4,234 -

U3 SJ_A+C 7.49 4 9 9 433 367 -

U4 HRC_RC+HN+HS 7.29 25 89 121 8,266 5,942 4,055

U5 HRC_RC 6.98 2 7 12 583 383 594

U6 SAF_SAO+SAN+SAP+SAS 7.99 102 528 431 16,565 9,888 7,199

U7 SAF_SAP+SAS 7.47 10 50 78 4,510 2,696 2,678

U8 Imperial 6.9 0 1 1 58 64 -

U9 PalosVerdes 7.2 7 31 39 3,663 2,578 -

U10

NewportInglewood

7.2

65 238 276 22,906 17,741 -

1Debris generated was not successfully calculated for some scenarios

Table 4-9. UCERF 2-Based Scenarios and Facilities with at Least Moderate Damage

Scenario Earthquakes MTransportation Systems

(number of locations)Essential Facilities

(number of facilities) Buildings(number ofbuildings)

Highway Bridges Airports Hospitals Schools

U1

SAF_CO

6.95

2 1 0 0 9,703U2 SJ_SBV+SJV+A+C 7.76 45 0 0 0 83,354

U3 SJ_A+C 7.49 1 0 0 0 29,193

U4 HRC_RC+HN+HS 7.29 27 0 0 0 128,522

U5 HRC_RC 6.98 2 0 0 0 22,809

U6 SAF_SAO+SAN+SAP+SAS 7.99 33 4 0 0 143,322

U7 SAF_SAP+SAS 7.47 11 0 0 0 77,239

U8 Imperial 6.9 0 0 0 0 2,487

U9 PalosVerdes 7.2 3 1 0 0 52,911

U10 NewportInglewood 7.2 91 4 0 0 203,886


35/47

35

5. COMPARISON OF LOSS ESTIMATES

This chapter compares building-related losses estimated using different versions of HAZUS

(section 5.1) and building-related losses due to ground motions calculated from different

generations of GMPEs (section 5.2). An attempt is also made to compare CGS loss estimates to

other published studies (section 5.3).

5.1 Comparison of Building-Related Losses from HAZUS MH-MR3 (CGS 2009 Results) and

HAZUS-SR2 (CGS 2005 Results)

The CGS 2005 study quantified building-related losses for scenario earthquakes in ten

counties in the San Francisco Bay Area (SFBA) and in ten counties in southern California

(Rowshandel et al., 2005). That study used scenario ground motions (or ShakeMaps) of 50

potential earthquakes published by the USGS, including 34 in northern California and 16 in

southern California. It used HAZUS, Service Release 2 (HAZUS-SR2) (NIBS, 1997). Like the

current study, that study used the HAZUS default inventory data on the built environment and

demographics. The default inventory information in HAZUS-SR2 is derived mostly from the

1990 national census data. It is, therefore, at least 10 years older than the inventory data

embedded in HAZUS MH-MR3 used in the current study.

Comparable scenario earthquakes are identified and listed in table 5-1 for northern

California. A difference between the current study and the CGS 2005 study (Rowshandel et al.,

2005) is the extent of HAZUS study regions. In the current study, the extent of HAZUS study

regions is determined by the extent of the corresponding ShakeMaps. It includes all countiesaffected by the USGS ShakeMap ground motions. In the CGS 2005 study, only counties in the

San Francisco Bay Area (SFBA) were included. These are Alameda, Contra Costa, Marin,

Napa, San Francisco, San Mateo, Santa Clara, Santa Cruz, Solano, and Sonoma counties. For

the current study, table 5-1 lists total building-related loss for both the region (all affected

counties, column 4) and for the ten SFBA counties (column 5) for the purpose of comparing with

the CGS 2005 study. Comparison is made on building-related losses in ten SFBA counties, and

percent difference (last column in table 5-1) is calculated as:

100%

whereLHAZUS MH-MR3 is loss from HAZUS MH-MR3 (results from the current study) andLHAZUS-

SR2 is loss from HAZUS-SR2 (results from CGS 2005 study). Both are the total building-related

loss for the ten SFBA counties. Comparison is made for building-related losses only because the

CGS 2005 study only reported building-related losses. In northern California, 20 of the 33

comparable scenarios show building related losses from the current study that are within 10

percent of CGS 2005 estimates. For most of the scenarios on the Northern San Andreas Fault,


36/47

36

the current estimates are up to 40% higher than the 2005 estimates. In contrast, the current

estimates are up to 36 percent lower than the 2005 estimates for other scenarios. In southern

California, 75% of the common scenarios result in lower building related loss when estimated

using SR3 compared with SR2. Half of the differences are between 30% and 71%. This

comparison can be seen in table 5-2.

For Southern California, the ten counties used were: Los Angeles, Orange, Ventura, San

Diego, San Bernardino, Riverside, Santa Barbara, Kern, San Luis Obispo and Imperial. As seen

in Table 5-2, the percentage of difference for the Southern California scenarios varies greatly

between MR3 and SR2 versions of HAZUS. Differences range from MR3 Coachella Valley

scenario being 71% higher than the SR2 results, to the MR3 Whittier scenario being 45% lower

than the SR2 results. The Imperial Valley fault scenario is shown as having a 71% difference but

this is likely due to the relatively low total building loss being rounded to the nearest million for

the SR2 results.

5.2 Comparison of Building-Related Losses for UCERF 2-Based Scenarios (NGA GMPEs)

and USGS Scenarios

Table 5-3 lists UCERF 2-based scenarios and comparable USGS scenarios analyzed in this

study. For given comparable scenarios, the extent of HAZUS regions for UCERF 2-based and

USGS scenarios are identical. However, ShakeMap extent, assumed magnitude, and fault

rupture geometry may be slightly different because, for UCERF 2-based scenarios, we use the

updated fault models and magnitude assignment based on the 2008 Update of the United States

National Seismic Hazard Maps (Petersen et al., 2008) and UCERF 2 (WGCEP, 2008) (compare

columns 3 and 6 in Table 5-3 for magnitude). These differences and their possible effects onHAZUS loss estimate are discussed case-by-case in the following paragraphs. Again,

comparison is made on building-related economic losses, and the percent difference (column 8)

is calculated as:

100%

whereLUCERF 2-basedis the total building-related economic loss for UCERF 2-based scenarios and

LUSGSis building-related economic loss for USGS scenarios.

For northern California scenarios (U4 through U7), there is little to no change in fault

geometry and magnitude between USGS scenarios and the comparable UCERF 2-based

scenarios. Therefore, the differences in estimated building-related losses are due to the use of

different sets of GMPEs in calculating ground motions. For the four scenarios calculated and

compared, NGA models lead to 40% to 60% reduction in building-related losses compared to

USGS scenarios using Boore et al. (1997) and Joyner and Boore (1988) GMPEs.


37/47

37

For Southern California, three Type-A fault and three Type-B fault scenarios were

reviewed. Two of the Type-A fault scenarios were ruptures along the San Jacinto fault zone.

These did not have any comparable USGS scenarios. The third Type-A fault scenario was a

Coachella Valley M6.95 event. When compared to the USGS S14 Coachella Valley M7.1 event

an 87% difference is seen. Most of this difference is likely due to the UCERF 2-based scenario

GMPEs (NGA) lowering of ground motions. Also, the magnitude in UCERF 2 is slightly lowerthan the USGS scenario (see table 2-4). The three Type-B fault scenarios were an M6.9 on the

Imperial Valley fault, an M7.2 on the Palos-Verdes fault and an M7.2 on the Newport-Inglewood

fault. The lower ground motions from UCERF 2-based scenario resulted in lower total building

loss (44% less) for the Imperial Valley scenario and for the Palos-Verdes fault scenario (28%

less). The UCERF 2 Newport-Inglewood fault scenario had a 25% increase in total building loss

due to the fact that the scenario was changed from a M6.9 to a M7.2 and rupture along the Rose

Canyon fault was included.


38/47

38

Table 5-1 Comparison of Estimated Total Building-Related Losses using Different Versions of HAZUS

for Northern California

Scenario Earthquakes MLoss from HAZUS MH-

MR3 ($M)Loss from HAZUS-

SR2 ($M) Difference(%)All Affected

Counties

Ten SFBA

Counties

Ten SFBA Counties

N1 SAF_SAS+SAP+SAN+SAO 7.90 79,834 77,113 54,000 43

N2 SAF_SAS+SAP+SAN 7.76 70,628 68,728 50,000 37

N3 SAF_SAP+SAN+SAO 7.83 66,216 65,622 47,000 40

N4 SAF_SAS+SAP 7.42 34,299 33,221 30,000 11

N5 SAF_SAS 7.03 6,789 6,040 5,900 2

N6 SAF_SAP 7.15 24,788 24,649 24,000 3

N7 SAF_SAN+SAO 7.70 17,814 17,376 16,000 9

N8 SAF_SAN 7.45 11,474 11,232 15,000 -25

N9 SAF_SAO 7.29 161 3 - -

N10

HRC_HS

6.67

14,469 14,410 15,000 -4N11 HRC_HN 6.49 7,655 7,620 9,000 -15

N12 HRC_HS+HN 6.91 22,660 22,556 23,000 -2

N13 HRC_RC 6.98 6,582 6,514 8,000 -19

N14 HRC_HN+RC 7.11 19,244 19,072 20,000 -5

N15 HRC_HS+HN+RC 7.26 36,883 36,591 34,000 8

N16 CLV_CS 5.78 168 64 100 -36

N17 CLV_CC 6.23 2,666 2,577 2,700 -5

N18 CLV_CS+CC 6.36 3,422 3,182 3,200 -1

N19 CLV_CN 6.78 10,176 10,069 10,000 1

N20

CLV_CC+CN

6.90

13,534 13,232 12,600 5N21 CLV_CS+CC+CN 6.93 14,217 13,661 13,000 5

N22 CGV_CON 6.25 2,644 2,596 2,800 -7

N23 CGV_GVS 6.24 1,872 1,820 2,100 -13

N24 CGV_CON+GVS 6.58 5,326 5,206 7,000 -26

N25 CGV_GVN 6.02 528 493 600 -18

N26 CGV_GVS+GVN 6.48 2,267 2,181 3,200 -32

N27 CGV_CON+GVS+GVN 6.71 6,631 6,456 6,800 -5

N28 SGF_SGS 7.0 963 309 300 3

N29 SGF_SGN 7.2 12,111 11,879 13,000 -9

N30

SGF_SGS+SGN

7.4

15,005 13,923 15,000 -7

N31 GNV_GS 6.6 1,752 1,516 1,800 -16

N32 GNV_GN 6.7 3,198 2,958 3,200 -8

N33 GNV_GS+GN 6.9 5,175 4,749 5,000 -5

N34 MTD 6.65 7,296 7,107 7,000 2

N35 GV ? 3,503 2,970 - -


39/47

39

Table 5-2 Comparison of Estimated Total Building-Related Losses using Different Versions of HAZUS

for Southern California.

Scenario Earthquakes MLoss from HAZUS MH-

MR3 ($M)Loss from HAZUS-

SR2 ($M) Difference(%)Ten Southern CA

Counties

Ten Southern CA

CountiesS1 VerdugoFault 6.7 23,751 24,000 -1

S7 NorthChannelSlope 7.4 5,814 4,000 45

S8 PuenteHillsFault 7.1 79,662 69,000 15

S9 SanJoaquinHillsFault 6.6 16,557 15,000 10

S10 ElsinoreFault 6.8 2,481 4,000 -38

S11 RaymondFault 6.5 16,495 17,000 -3

S12 WhittierFault 6.8 15,965 29,000 -45

S13 ImperialValleyFault 7.0 421 1,000 -58

S14 SAFCoachellaValley 7.1 5,138 3,000 71

S15

SAF

Southern

7.4

9,138 18,000 -49

S16 SanJacintoFault 6.7 4,366 7,000 -38

S17 NewportInglewood 6.9 34,319 49,000 -30

S18 PalosVerdesFault 7.1 20,084 30,000 -33

S19 SantaMonicaFault 6.6 16,308 17,000 -4

S20 RoseCanyonFault 6.9 9,771 14,000 -30

S21 SAF1857 7.8 12,035 17,000 -29

Table 5-3 Comparison of Estimated Losses for UCERF 2-Based Scenarios and for USGS Scenarios

Scenario EarthquakesUCERF 2-Based Scenario Comparable USGS Scenario

Difference(%)

ID M Building RelatedLoss ($M)

ID M Building-RelatedLoss ($M)

SAF_CO U1 6.95 684 S14 7.1 5,138 -87

SJ_SBV+SJV+A+C U2 7.76 10,983No comparable scenarioSJ_A+C U3 7.49 2,654

HRC_RC+HN+HS U4 7.29 21,966 N15 7.26 36,883 -40

HRC_RC U5 6.98 3,963 N13 6.98 6,582 -40

SAF_SAO+SAN+SAP+SAS

U6

7.99

29,412 N1 7.90 79,834 -63

SAF_SAP+SAS U7 7.47 17,031 N4 7.42 34,299 -50

Imperial U8 6.9 236 S13 7.0 421 -44

PalosVerdes U9 7.2 14,513 S18 7.1 20,084 -28

NewportInglewood U10 7.2 42,980 S17 6.9 34.319 25


40/47

40

5.3 Comparison with Other Published Results

The 1994 M6.7 Northridge earthquake resulted in an estimated $46 billion in total losses

and the 1989 M6.9 Loma Prieta in $10 billion. The Loma Prieta earthquake is similar in location

and magnitude with N5 SAF_SAS. Our HAZUS estimated loss for that scenario is more than $7

billion. The estimated loss is only due to ground motion, so would be expected to be less thanthe total loss, which included losses from liquefaction and landslides. We have not yet

calculated losses from the ShakeMap for the Northridge earthquake.

Field et al. (2005) estimated the loss for an earthquake rupturing the full length of the PuenteHills blind-thrust fault to be between $82 and $252 billion using a range of possible magnitudesand ground motion models. They estimated 3,000 18,000 fatalities, 142,000 735,000displaced households, 42,000 211,000 in need of short-term public shelter, and 30,000 99,000 tons of debris generated. Our estimates are in the lower end of these ranges. Field et al.(2005) demonstrated that the choice of ground motion model can be more influential than theearthquake magnitude. Although we did not isolate the effect of earthquake magnitude, our

results show that the choice of ground motion model is much more influential than the differentversion of HAZUS inventory data.

The 2002 Working Group on California Earthquake probabilities (WGCEP, 2002) conducteda loss estimation of ten SFBA counties due to the ten most likely earthquakes in the area. Eightof the ten scenario earthquakes analyzed by the 2002 WGCEP can be compared directly with thecorresponding scenarios in the current study. Major findings of the 2002 WGCEP aresummarized on the USGS website (http://earthquake.usgs.gov/regional/nca/wg02/losses.php),including: (1) all studied scenario earthquakes would cause at least $6 billion in damage tobuildings and infrastructures; (2) a repeat of the 1906 magnitude 7.9 earthquake is the worst casescenario for the SFBA and would kill about 5800 people if it strikes during working hours.

These predicted numbers are consistent with our results from the USGS scenarios.

FEMA simulated the repeat of the 1906 San Francisco earthquake, estimated its losses as partof the exercise term Golden Guardian 06 (GG06), and published some of the estimated resultson its website: http://www.fema.gov/plan/prevent/hazus/dl_sfeqlosses.shtm. This exerciseestimated over $120 billion building losses, 1,800 deaths at night time, 3,400 deaths at day time,200,000 300,000 displaced households, and 25 40 million tons of debris generated. Thesenumbers are generally higher than our estimates from the USGS scenario. The causes of thesedifferences are hard to evaluate because of lack of information. There could be a number offactors, including ground motion equations, earthquake source parameters, inventory data, andlosses due to secondary disasters following the earthquake, such as subsequent fires.

Risk Management Solutions (RMS) evaluated the potential impact of a repeat of the 1906San Francisco earthquake for the 100th anniversary of the earthquake (Risk ManagementSolutions, 2006). They estimated a total economic loss of $260 billion due to damage toresidential and commercial properties. A similar study by RMS in 1995 for a repeat of the 1906San Francisco earthquake yielded a total economic loss ranging from $150 and $200 billion(Risk Management Solutions, 1995). In addition, RMS estimated that an M 7.0 earthquakerupturing the Southern and Northern Hayward fault would cause $210 to $235 billion totaldamage and an M 6.8 earthquake rupturing the Southern Hayward fault (a repeat of the 1868


41/47

41

earthquake) would lead to $112 to $122 billion total damage (Risk Management Solutions,2008). These numbers are much higher than our estimates using HAZUS. However, RMSestimated losses included losses due to fire following the earthquake, and additional damage dueto liquefaction and landslides. Moreover, RMS calculation of losses also assumes some level ofloss amplification.


42/47

42

6.CONCLUSIONWe analyzed potential economic impact of 58 scenario earthquakes in California using the

published USGS ShakeMap ground motions and HAZUS default exposure data. Our results

show that the most damaging earthquake in northern California is a repeat of the 1906 SanFrancisco magnitude 7.9 earthquake, causing $84 billion economic losses (including building

and lifeline related losses) and 1000 to 4000 deaths. Eight potential earthquakes would lead to at

least $20 billion economic losses in northern California. Of the 22 scenarios analyzed in

southern California (including the M 7.8 earthquake on the Southern San Andreas Fault known

as the ShakeOut scenario), the most damaging earthquake is the M 7.1 earthquake on the Puente

Hills Fault, causing nearly $80 billion economic losses and 500 to 1700 deaths. Five potential

earthquakes would lead to at least $20 billion economic losses in southern California.

Comparison of estimated losses from this study and the CGS 2005 study does not show a

systematic and consistent trend. For majority of the scenarios, building related losses from thecurrent study is within 10 percent of the CGS 2005 estimates. Current estimates are up to 40

percent higher than the CGS 2005 estimates for some northern San Andreas scenarios, whereas

they are up to 36 percent lower for some scenarios on Calaveras Fault and Concord-Green

Valley Fault. Because the comparison is made between comparable earthquake scenarios with

identical ShakeMap ground motions, the differences should be considered as a reflection of the

difference in default data on built environment and/or modeling methodologies in different

versions of HAZUS.

Estimated losses for the UCERF 2-based scenarios are consistently lower than for the

comparable USGS scenarios (30 to 60 percent lower) due to the use of NGA models in groundmotion calculations. Lower losses based on the NGA ground motion equations may have

significant practical impact on the California earthquake insurance industry. We suggest that

additional scenarios should be analyzed to refine our understanding of the impact of NGA

models on loss estimates. Analyzing annualized losses based on the 2008 updated version of the

probabilistic seismic hazard map for California may also result in better understanding of the

effect of NGA models.


43/47

43

7.REFERENCESBoore, D.M. and Atkinson, G.M., 2008, Ground-Motion Prediction Equations for the Average

Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Period between 0.01 and

10.0 s, Earthquake Spectra, v 24, n 1, p 99-138.

Boore, D.M., Joyner, W.B., and Fumal, T.E., 1997, Equations for Estimating HorizontalResponse Spectra and Peak Acceleration from Western North American Earthquakes: ASummary of Recent Work,Seismological Research Letters, v 68, n 1, p 128-153.

Borcherdt, R.D., 1994, Estimates of Site-Dependent Response Spectra for Design (Methodologyand Justification), Earthquake Spectra, 10, 617-654.

Cao, T., Bryant, W.A., Rowshandel, B., Branum, D., and Wills, C.J., 2003, The Revised 2002

California Probabilistic Seismic Hazard Maps, June 2003, California Geological Survey Web

Page:http://www.conservation.ca.gov/cgs/rghm/psha/fault_parameters/pdf/2002_CA_Hazard_Maps.p

df

Campbell K.W. and Bozorgnia, Y., 2008, NGA Ground Motion Model for the Geometric Mean

Horizontal Component of PGA, PGV, PGD and 5% Damped Linear Elastic Response Spectra

for Periods Ranging from 0.01 to 10 s, Earthquake Spectra, v 24, n 1, p 139-172.

Chiou, B. S.-J. and Youngs, R.R., 2008, An NGA Model for the Average Horizontal Component

of Peak Ground Motion and Response Spectra, Earthquake Spectra, v24, n1, p173-216.

Field, E.H., Seligson, H.A., Gupta, N., Gupta, V., Jordan, T.H., and Campbell, K.W., 2005, LossEstimates for a Puente Hills Blind-Thrust Earthquake in Los Angeles, California, Earthquake

Spectra, v 21, n 2, p 329-338.

Federal Emergency Management Agency (FEMA), 2009, Multi-hazard Loss Estimation

Methodology, Earthquake Model, HAZUS-MH MR3, User Manual and Technical Manual,

developed by Department of Homeland Security, Emergency Preparedness and Response

Directorate, Federal Emergency Management Agency (FEMA), Mitigation Division,

Washington, D.C., under a contract with National Institute of building Sciences, Washington,

D.C. (Available online: http://www.fema.gov/plan/prevent/hazus/hz_resources.shtm,

downloaded in May 2009).

Frankel A., 2009, personnel communication.

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 (Available online at http://pubs.usgs.gov/of/2008/1150/)


44/47

44

Joyner, W. B. and Boore, D. M., 1988, Measurement, characterization, and prediction of strong

ground motion, Proc. Earthquake Engineering & Soil Dynamics II, Park City, Utah,

Geotechnical, Div., American Soc. Civil Engineers, 43-102.

National Institute of Building Science (NIBS), 1997, Earthquake Loss Estimation Methodology,

HAZUS (SR1): Technical Manual, Report prepared for the Federal Emergency Management

Agency, NIBS, Washington, D.C.

Peterson, M.D., Bryant, W.A., Cramer, C.H., Cao, T., Reichle, M.S., Frankel, A.D.,Lienkaemper, J.J., McCrory, P.A., and Schwartz, D.P., 1996, Probabilistic Seismic HazardAssessment for the State of California, California Division of Mines and Geology Open-FileReport 96-08, USGS Open File Report 96-706.

Petersen, M.D., Frankel, A.D., Harmsen, S.C., Mueller, C.S., Haller, K.M., Wheeler, R.L.,Wesson, R.L., Zeng, Y., Boyd, O.S., Perkins, D.M., Luco, N., Field, E.H., Wills, C.J., andRukstales, K.S., 2008, Documentation for the 2008 Update of the United States National SeismicHazard Maps, U.S. Geological Survey, Open-File Report 2008-1128 (Available online:http://pubs.usgs.gov/of/2008/1128/).

Risk Management Solutions, 2008, 1868 Hayward Earthquake: 140-Year Retrospective, RMSSpecial Report, online publication available at:http://www.rms.com/publications/1868_Hayward_Earthquake_Retrospective.pdf

Risk Management Solutions, 2006, The 1906 San Francisco Earthquake and Fire: Perspectiveson a Modern Super Cat. Online publication available at:http://www.rms.com/publications/1906_SF_EQ.pdf

Rowshandel, B., Reichle, M., Wills, C., Cao, T., Petersen, M., Branum, D., and Davis, J., 2005,Estimation of Future Earthquake Losses in California, web information paper,http://www.conservation.ca.gov/cgs/rghm/loss/Pages/index.aspx

Steward, J.P., Archuleta, R.J., and Power, M.S., 2008, Special Issue on the Next GenerationAttenuation project, Earthquake Spectra, v 24, n 1.

Wills, C.J., Weldon R.J. II, and Bryant, W.A., 2007, California Fault Parameter for the National

Seismic Hzard Maps and Working Group on California Earthquake Probabilities, Appendix A,

The Uniform California Earthquake Rupture Forecast Version 2 (UCERF 2) by Working Group

on California Earthquake Probabilities (WGCEP) and the USGS National Seismic Hazard

Mapping Program (NSHMP), California Geological Survey Special Report 203, U.S.Geological Survey Open File Report 2007-1437, and southern California Earthquake Center

Contribution 1138.

Wills, C.J., and Clahan, K.B., 2006, Developing a Map of Geologically Defined Site-ConditionCategories for California, Bulletin of the Seismological Society of America, v 96, n 4A, p 14831501.


45/47

45

Wills, C.J., Petersen, M.D., Bryant, W.A., Reichle, M.S., Saucedo, G.J., Tan, S.S., Taylor, G.C.and Treiman, J.A., 2000, A Site-Conditions Map For California Based On Geology and ShearWave Velocity, Bull. Seism. Soc. Am. 90, S187-S208.

Working Group on California Earthquake Probabilities (WGCEP) and the USGS National

Seismic Hazard Mapping Program (NSHMP), 2008, The Uniform California Earthquake

Rupture Forecast Version 2 (UCERF 2), California Geological Survey Special Report 203, U.S.

Geological Survey Open File Report 2007-1437, and Southern California Earthquake Center

Contribution 1138.

Working Group on California Earthquake Probabilities (WGCEP), 2003, Earthquake

Probabilities in the San Francisco Bay Region: 2002-2031, U.S. Geological Survey Open-File

Report 03-214.


46/47

46

8.APPENDICES8.1 Appendix A Electronic Attachment

This appendix consists of an electronic attachment. The attachment contains a PDF file

containing a complete set of results for all scenarios analyzed in this project for CalEMA. Each

PDF file contains maps, tables, and summary reports for each scenario. The files are named by

the event ID number and event name as given in Tables 2-1, 2-2, and 2-4. Each file contains the

following entries:

A. Maps1. Shaking intensity map (USGS ShakeMap)2. Peak ground acceleration by census tract (HAZUS map)3. Total building loss by census tract (HAZUS map)4. Loss ratio by census tract [ratio of building damage (includes structural damage and

non-structural damage) to replacement value (exposed value of buildings)]5. Displaced households by census tract (HAZUS map)6. Debris generated by census tract (HAZUS map)

B. Tables1. Dam inventory and ground motions at dam locations2. Direct economic loss for buildings by county3. Short term shelter needs by county4. Casualties summary report by county

C. Other Summary Reports1. Global Summary Report2. Quick assessment reports

a. 2 A.M. (at home time)b. 2 P.M. (at work time)c. 5 P.M. (commute time)


47/47

8.2 Appendix B Tables and Summary Reports for the Selected Scenario

This appendix is in the form of a PDF file named Appendix B. It contains a complete set of

tabulated results and summary reports for the selected scenario (N1

SAF_SAS+SAP+SAN+SAO, a repeat of the 1906 earthquake) for demonstration purposes.

Again, a complete suite of maps, tables, and summary reports for all of the scenarios analyzed in

this project is contained in an electronic attachment as explained in Appendix A.

Contents of Appendix B:

Table B-1 Dam inventory and ground motions at dam locations

Table B-2 Direct economic loss for buildings by county

Table B-3 Short term shelter needs by county

Table B-4 Casualties summary report by county

Report B-1 Global Summary Report

Report B-2 Quick assessment reports

report calema hazus 09 final

Documents