NH23C-1895
SAFRR Tsunami Scenarios and USGS-NTHMP Collaboration

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Stephanie Ross, USGS, Menlo Park, CA, United States
Abstract:
Hazard scenarios provide emergency managers and others with information to help them prepare for future disasters. The SAFRR Tsunami Scenario, published in 2013, modeled a hypothetical but plausible tsunami, created by an Mw9.1 earthquake occurring offshore from the Alaskan peninsula, and its impacts on the California coast. It presented the modeled inundation areas, current velocities in key ports and harbors, physical damage and repair costs, economic consequences, environmental impacts, social vulnerability, emergency management, and policy implications for California associated with the scenario tsunami. The intended users were those responsible for making mitigation decisions before and those who need to make rapid decisions during future tsunamis. It provided the basis for many exercises involving, among others, NOAA, the State of Washington, several counties in California, and the National Institutes of Health. The scenario led to improvements in the warning protocol for southern California and highlighted issues that led to ongoing work on harbor and marina safety.

Building on the lessons learned in the SAFRR Tsunami Scenario, another tsunami scenario is being developed with impacts to Hawaii and to the source region in Alaska, focusing on the evacuation issues of remote communities with primarily shore parallel roads, and also on the effects of port closures. Community exposure studies in Hawaii (Ratliff et al., USGS-SIR, 2015) provided background for selecting these foci.

One complicated and important aspect of any hazard scenario is defining the source event. The USGS is building collaborations with the National Tsunami Hazard Mitigation Program (NTHMP) to consider issues involved in developing a standardized set of tsunami sources to support hazard mitigation work. Other key USGS-NTHMP collaborations involve population vulnerability and evacuation modeling.