New Software for Computing Time Dependent Seismic Hazard During Aftershock Sequences Using the Opensha Platform

Date: 4/24/2019

Time: 06:00 PM

Room: Grand Ballroom

The chaos caused by a major earthquake does not end when the shaking stops. Search and rescue, damage assessment, and lifeline repairs all need to be carried out under the constant threat of damaging aftershocks. In some cases, aftershocks can be even more destructive than the initial event, as was the case in Christchurch, New Zealand . While it may never be possible to predict the exact time, place, and magnitude of an impending earthquake, it is nonetheless possible to make probabilistic assessments of aftershock hazard based on past regional sequences and the specifics of an ongoing sequence. Forecasts, and in particular forecast maps, can provide situational awareness, increase public resilience, and help decision makers to prioritize response and recovery operations. The public has increasingly come to expect such information, and information vacuums are likely to be filled by non-authoritative sources.

The USGS, with support of USAID-Office of U.S. Foreign Disaster Assistance, is developing several lines of aftershock forecasting products with the goal of providing rapid quantitative aftershock information to emergency responders, lifeline operators, and the general public. Here we introduce a software application designed to streamline the process of analyzing and forecasting aftershock sequences within a modified Epidemic-Type Aftershock Sequence framework. Forecasts are a Bayesian combination of a regionalized generic model and a specific model tuned to the ongoing sequence. The software uses the OpenSHA architecture to translate spatio-temporal rate forecasts into time-dependent probabilistic hazard estimates using standard ground-motion prediction equations. The software automatically generates graphical forecast summaries and hazard maps that supplement standard magnitude-probability tables. This poster will describe modifications to the ETAS model that allow for efficient and stable generation of aftershock forecasts, and discuss expected applications of the software.

Presenting Author: Nicholas van der Elst

Authors