Estimation of Future Estimation of Future Earthquake Annualized Earthquake Annualized Losses in CaliforniaLosses in California

B. RowshandelB. Rowshandel, M. Reichle,, M. Reichle, C. Wills, C. Wills,

T. Cao, M. Petersen, and J. DavisT. Cao, M. Petersen, and J. Davis

California Geological Survey California Geological Survey

Sacramento, CA Sacramento, CA

Disaster Resistant CaliforniaDisaster Resistant California Conference, Conference,

May 3-5, 2004, Sacramento, CAMay 3-5, 2004, Sacramento, CA

Purpose:Purpose:

Estimate the expected long-term, average Estimate the expected long-term, average annual economic losses in California due annual economic losses in California due to future earthquakes in and around the to future earthquakes in and around the StateState

Prepare results useful for making policy Prepare results useful for making policy decisions regarding earthquake decisions regarding earthquake regulations and codes, mitigation, regulations and codes, mitigation, preparation, and response planning preparation, and response planning

Approach:Approach:

Analysis of Earth Science Data and Analysis of Earth Science Data and Estimation of Earthquake HazardsEstimation of Earthquake Hazards

Estimation of Losses Using HAZUS-SR2Estimation of Losses Using HAZUS-SR2

Analysis of Loss Estimation ResultsAnalysis of Loss Estimation Results

Input Data:Input Data: - Fault Data - Fault Data - Seismicity Data - Seismicity Data

Input Data:Input Data:

- - Liquefaction DataLiquefaction Data

San Francisco Bay Area Los Angeles AreaSan Francisco Bay Area Los Angeles Area

Input Data:Input Data: - Surface Geologic Materials - Surface Geologic Materials - Other Information and Assumptions - Other Information and Assumptions

Other Information Other Information and Assumptions:and Assumptions:

Model for Earthquake Model for Earthquake Occurrence in TimeOccurrence in Time

Model for Distribution of Model for Distribution of Earthquake MagnitudeEarthquake Magnitude

Model for Attenuation of Model for Attenuation of Traveling Seismic WavesTraveling Seismic Waves

Seismic Shaking Hazard Maps:Seismic Shaking Hazard Maps:

•

10% probability of being exceeded in 50 years.

Hazard Data for Annual Loss Computation Hazard Data for Annual Loss Computation Using HAZUS:Using HAZUS:

Use USGS/CGS PSHA Methodology to Calculate Use USGS/CGS PSHA Methodology to Calculate Ground Motions for Base Rock, with Return Ground Motions for Base Rock, with Return Periods of:Periods of:

100 Years100 Years (~40% chance of being exceeded in 50 years), (~40% chance of being exceeded in 50 years), 250 Years250 Years (~20%),(~20%), 500 Years500 Years (~10%),(~10%), 750 Years750 Years (~6.5%),(~6.5%), 1000 Years 1000 Years (~5%),(~5%), 1500 Years1500 Years (~3.3%),(~3.3%), 2000 Years2000 Years (~2.5%),(~2.5%), 2500 Years2500 Years (~2.0% chance of being exceeded in 50 years)(~2.0% chance of being exceeded in 50 years)

Prepare and Modify HAZUS Input Data for Prepare and Modify HAZUS Input Data for Ground Motion, Soil, Liquefaction and Other Ground Motion, Soil, Liquefaction and Other Data at the Census Tract LevelData at the Census Tract Level

Loss Estimation Methodology:Loss Estimation Methodology:

Used HAZUS-SR2 with Users’-Supplied Hazard Data Used HAZUS-SR2 with Users’-Supplied Hazard Data

and Default Data on the Built Environment and and Default Data on the Built Environment and DemographicsDemographics

Ground Motion and Liquefaction Hazards were Ground Motion and Liquefaction Hazards were ConsideredConsidered

Hazards Due to Ground Rupture, Landslide, and Hazards Due to Ground Rupture, Landslide, and Tsunami were not Considered due to Lack of DataTsunami were not Considered due to Lack of Data

Only the Building Inventory was Considered. Other Only the Building Inventory was Considered. Other Elements of the Built Environment in HAZUS were Elements of the Built Environment in HAZUS were not Considered Due to Lack of Adequate Datanot Considered Due to Lack of Adequate Data

Building Inventory: Building Inventory:

Building Count: Building Count: 7,971,0007,971,000 Residential: 76% Commercial: 17% Residential: 76% Commercial: 17%

Industrial: 4.5% Others: 2.5%Industrial: 4.5% Others: 2.5%

Building Types: Building Types: 3636

General Occupancy Classes: General Occupancy Classes: 77 (Residential, Commercial, Industrial, Agricultural, Religious, (Residential, Commercial, Industrial, Agricultural, Religious,

Government, Education)Government, Education)

Specific Occupancy Classes: Specific Occupancy Classes: 2828

Building Replacement Value: Building Replacement Value: $1,594,626 Billion$1,594,626 Billion (1994 (1994 Dollars) of Which 76% is ResidentialDollars) of Which 76% is Residential

Economic Losses:Economic Losses:

Direct Losses Direct Losses ((Considered) Considered) :: - Capital Stock Losses (Due to Structural Damage, - Capital Stock Losses (Due to Structural Damage, Non-Structural Damage, Contents, and Inventory)Non-Structural Damage, Contents, and Inventory) - Income Losses (Relocation, Capital Related, Wages, - Income Losses (Relocation, Capital Related, Wages, and Rental)and Rental)

Indirect Losses (Indirect Losses (Not Included) Not Included) :: - Losses due to Long-term economic effects : Capital - Losses due to Long-term economic effects : Capital

Related to Income, Employment, and Economic OutputRelated to Income, Employment, and Economic Output

Annual Building Damage Economic Loss:Annual Building Damage Economic Loss:- By County - By County - By Census Tract- By Census Tract

Per-Capita Annual Loss:Per-Capita Annual Loss:- By County - By County - By Census Tract- By Census Tract

Annual Loss As Percentage of Annual Loss As Percentage of Building Replacement Value:Building Replacement Value:- By County - By County - By Census Tract- By Census Tract

Summary Results:Summary Results:

Distribution of Annual LossesDistribution of Annual LossesBy Building Type:By Building Type:

Distribution of Annual LossesDistribution of Annual LossesBy Occupancy Type:By Occupancy Type:

Uncertainty in the Estimates: Uncertainty in the Estimates: The Level of Uncertainty in the Estimates Obtained using The Level of Uncertainty in the Estimates Obtained using HAZUS is Relatively High. This is Due to Inadequacies in HAZUS is Relatively High. This is Due to Inadequacies in the Methodology and Data.the Methodology and Data.

Hazard Characterization:Hazard Characterization: Magnitude and Distribution Magnitude and Distribution of Ground Motions Have Major Effect on the Estimated Loss of Ground Motions Have Major Effect on the Estimated Loss (~30-40% change in estimated annualized losses resulted from (~30-40% change in estimated annualized losses resulted from switching from one method of soil correction to another) switching from one method of soil correction to another)

Hazard to Damage:Hazard to Damage: Equations relating ground motion to Equations relating ground motion to damage (fragility functions) play a major role (~15% decrease damage (fragility functions) play a major role (~15% decrease in estimated annualized loss resulted from using HAZUS-SR2 in estimated annualized loss resulted from using HAZUS-SR2 compared to HAZUS-SR1; this change is most likely due to compared to HAZUS-SR1; this change is most likely due to fragility curves)fragility curves)

Damage to LossDamage to Loss Inventory DataInventory Data

Summary and Conclusions:Summary and Conclusions:

Estimate of the Direct Economic Loss Due to Building Damage Exceeds Estimate of the Direct Economic Loss Due to Building Damage Exceeds $2 Billion Annually, of which 61% is due to residential buildings. This $2 Billion Annually, of which 61% is due to residential buildings. This corresponds to an average per-capita loss of $100 and a loss in corresponds to an average per-capita loss of $100 and a loss in building replacement value of 0.2% each year.building replacement value of 0.2% each year.

The uncertainty associated with this estimate is relatively high, The uncertainty associated with this estimate is relatively high, implying that this estimate could be an order of magnitude larger.implying that this estimate could be an order of magnitude larger.

Indirect losses due to building damage, and losses due to secondary Indirect losses due to building damage, and losses due to secondary effects (landslide, tsunami, fire), which were not included in this study, effects (landslide, tsunami, fire), which were not included in this study, would add to the above estimate. would add to the above estimate.

Losses due to damage to other facilities, such as transportation, utility Losses due to damage to other facilities, such as transportation, utility lifelines, essential facilities and high potential loss facilities were not lifelines, essential facilities and high potential loss facilities were not included due to the incomplete data in HAZUS.included due to the incomplete data in HAZUS.

Estimates of losses were found to be particularly sensitive to soil Estimates of losses were found to be particularly sensitive to soil effects. Better characterization of soils and geologic units help reduce effects. Better characterization of soils and geologic units help reduce the uncertainty in the estimates.the uncertainty in the estimates.

HAZUS data inventory needs much improvement. Improvements in HAZUS data inventory needs much improvement. Improvements in data inventory would have major effects on estimated losses.data inventory would have major effects on estimated losses.

Other CGS Loss Estimation Studies:Other CGS Loss Estimation Studies:

http://www.consrv.ca.gov/CGS/rghm/loss/http://www.consrv.ca.gov/CGS/rghm/loss/

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Thank You!Thank You!