Search USGS⌕ Search

USGS · ofr20061020

Sensitivity of Earthquake Loss Estimates to Source Modeling Assumptions and Uncertainty

Abstract

Introduction: This report explores how uncertainty in an earthquake source model may affect estimates of earthquake economic loss. Specifically, it focuses on the earthquake source model for the San Francisco Bay region (SFBR) created by the Working Group on California Earthquake Probabilities. The loss calculations are made using HAZUS-MH, a publicly available computer program developed by the Federal Emergency Management Agency (FEMA) for calculating future losses from earthquakes, floods and hurricanes within the United States. The database built into HAZUS-MH includes a detailed building inventory, population data, data on transportation corridors, bridges, utility lifelines, etc. Earthquake hazard in the loss calculations is based upon expected (median value) ground motion maps called ShakeMaps calculated for the scenario earthquake sources defined in WGCEP. The study considers the effect of relaxing certain assumptions in the WG02 model, and explores the effect of hypothetical reductions in epistemic uncertainty in parts of the model. For example, it addresses questions such as what would happen to the calculated loss distribution if the uncertainty in slip rate in the WG02 model were reduced (say, by obtaining additional geologic data)? What would happen if the geometry or amount of aseismic slip (creep) on the region's faults were better known? And what would be the effect on the calculated loss distribution if the time-dependent earthquake probability were better constrained, either by eliminating certain probability models or by better constraining the inherent randomness in earthquake recurrence? The study does not consider the effect of reducing uncertainty in the hazard introduced through models of attenuation and local site characteristics, although these may have a comparable or greater effect than does source-related uncertainty. Nor does it consider sources of uncertainty in the building inventory, building fragility curves, and other assumptions adopted in the loss calculations. This is a sensitivity study aimed at future regional earthquake source modelers, so that they may be informed of the effects on loss introduced by modeling assumptions and epistemic uncertainty in the WG02 earthquake source model.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Paul A. Reasenberg, Nan Shostak, Sharon Terwilliger. 2006. Sensitivity of Earthquake Loss Estimates to Source Modeling Assumptions and Uncertainty. https://doi.org/10.3133/ofr20061020

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

ECCOE Landsat quarterly calibration and validation report—Quarter 2, 2026

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 2 (April–June), 2026. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.

Open-File Report↗

ECCOE Landsat quarterly calibration and validation report—Quarter 1, 2026

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 1 (January–March) of 2026. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov . One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 Thermal Infrared Sensor encoder alerts anomaly. On March 18, 2026, the Thermal Infrared Sensor instrument’s mechanism control electronics board reset, driving several parameters to default power-on values. Subsequent telemetry and analysis determined that no persistent hardware misconfiguration was present and no radiometric or geometric degradation was observed.

Open-File Report↗

Floods of June 20–July 6, 2024, in the Big Sioux River, Rock River, Little Sioux River, Ocheyedan River, and Floyd River Basins, northwestern Iowa

Major flooding occurred on June 20–July 6, 2024, in northwestern Iowa affecting the Big Sioux, Rock, Little Sioux, Ocheyedan, and Floyd River Basins. Heavy rain fell in northwestern Iowa, southwestern Minnesota, and southeastern South Dakota on June 20–22, 2024. Parts of northwestern Iowa recorded 2–6 inches of rainfall and localized amounts exceeding 12 inches. A maximum peak-of-record streamflow of 175,000 cubic feet per second at the U.S. Geological Survey streamgage Big Sioux River at Akron, Iowa (06485500), was recorded on June 22, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at four locations along the Big Sioux River between U.S. Interstate 29 at Sioux City, Iowa, upstream to Iowa Highway 10 north of Hawarden, Iowa, a distance of 75.7 river miles. A maximum peak-of-record streamflow of 157,000 cubic feet per second at the U.S. Geological Survey streamgage Rock River near Rock Valley, Iowa (06483500), was recorded on June 22, 2024, and had an annual exceedance probability of less than 0.2 percent. High-water marks were measured at eight locations along the Rock River between County Road B30 east of Hudson, South Dakota, upstream to Iowa Highway 9 at Rock Rapids, Iowa, a distance of 39.3 river miles. A maximum peak-of-record streamflow of 63,000 cubic feet per second at the U.S. Geological Survey streamgage Little Sioux River at Correctionville, Iowa (06606600), was recorded on June 24, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at 11 locations along the Little Sioux River between Iowa Highway 31 west of Correctionville, Iowa, upstream to U.S. Highway 18 north of Spencer, Iowa, a distance of 134.8 river miles. A maximum streamflow of 24,500 cubic feet per second at the U.S. Geological Survey streamgage Ocheyedan River near Spencer, Iowa (06605000), was recorded on June 22, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at three locations along the Ocheyedan River between County Road M38 west of Spencer, Iowa, upstream to U.S. Highway 18 west of Everly, Iowa, a distance of 12.8 river miles. A maximum streamflow of 41,000 cubic feet per second at the U.S. Geological Survey streamgage Floyd River at Alton, Iowa (06600100), was recorded on June 22, 2024, and had an annual exceedance probability range of 1–1.99 percent. High-water marks were measured at six locations along the Floyd River between Iowa Highway 3 at Le Mars, Iowa, upstream to Iowa Highway 10 at Alton, Iowa, a distance of 27.5 river miles. The high-water marks were used to develop flood profiles for the Big Sioux, Rock, Little Sioux, Ocheyedan, and Floyd Rivers.

Iowa, Minnesota, South Dakota↗