Comparing population exposure to multiple Washington earthquake scenarios for prioritizing loss estimation studies
Applied Geography
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Abstract
Scenario-based, loss-estimation studies are useful for gauging potential societal impacts from earthquakes but can be challenging to undertake in areas with multiple scenarios and jurisdictions. We present a geospatial approach using various population data for comparing earthquake scenarios and jurisdictions to help emergency managers prioritize where to focus limited resources on data development and loss-estimation studies. Using 20 earthquake scenarios developed for the State of Washington (USA), we demonstrate how a population-exposure analysis across multiple jurisdictions based on Modified Mercalli Intensity (MMI) classes helps emergency managers understand and communicate where potential loss of life may be concentrated and where impacts may be more related to quality of life. Results indicate that certain well-known scenarios may directly impact the greatest number of people, whereas other, potentially lesser-known, scenarios impact fewer people but consequences could be more severe. The use of economic data to profile each jurisdiction’s workforce in earthquake hazard zones also provides additional insight on at-risk populations. This approach can serve as a first step in understanding societal impacts of earthquakes and helping practitioners to efficiently use their limited risk-reduction resources.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Comparing population exposure to multiple Washington earthquake scenarios for prioritizing loss estimation studies |
| Series title | Applied Geography |
| DOI | 10.1016/j.apgeog.2014.05.013 |
| Volume | 52 |
| Year Published | 2014 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Western Geographic Science Center |
| Description | 13 p. |
| First page | 191 |
| Last page | 203 |
| Country | United States |
| State | Washington |
| Google Analytic Metrics | Metrics page |