2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 6-12
Presentation Time: 11:20 AM

USING HISTORICAL INTENSITY DATA TO ASSESS LONG-TERM PERFORMANCE OF EARTHQUAKE HAZARD MAPS


BROOKS, Edward M., Earth & Planetary Sciences, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3130, STEIN, Seth, Earth & Planetary Sciences, Northwestern University, Evanston, IL 60208-3130 and SPENCER, Bruce D., Department of Statistics and Institute for Policy Research, Northwestern University, Evanston, IL 60208, ebrooks@earth.northwestern.edu

Although earthquake hazard maps are used worldwide in making costly policy decisions for shaking-resistant construction, how well they actually perform remains unknown. Testing the performance of these maps would require a long history of shaking after the map was made. An alternative is to compare historic intensity data to the maps. Although these data may have biases, hindcasts using them cover much longer time periods than will be practical for forecasts starting from the time a map is made. This should be possible using China’s long history of recorded seismicity. We illustrate this possibility by comparing how well a 510-year-long record of earthquake shaking is described by the Japanese national hazard (JNH) maps. Noting that all earthquakes that caused ten or more fatalities in Japan since 1979 occurred in places assigned a relatively low hazard, Geller (2011) argued that “all of Japan is at risk from earthquakes, and the present state of seismological science does not allow us to reliably differentiate the risk level in particular geographic areas.” In essence, a map showing uniform hazard would be preferable to existing maps. We explore this issue by comparing the 510-year-long record to uniform and randomized maps. Surprisingly, as measured by the metric implicit in the JNH maps, i.e. that during the chosen time interval the predicted ground motion should be exceeded only at a specific fraction of the sites, both uniform and randomized maps do better than the actual maps. However, using as a metric the squared misfit between maximum observed shaking and that predicted, the JNH maps do better than uniform or randomized maps. These results indicate that the JNH maps are not performing as well as expected, that what factors control map performance is complicated, and that learning more about how maps perform and why would be valuable in making more effective policy.