Using Resilience Indicators in the Prediction of Earthquake Recovery

This paper presents a probabilistic methodology for the prediction of post-earthquake community recovery over time, based on a set of socioeconomic resilience parameters and a post-earthquake damage indicator. Pre-existing socioeconomic conditions are widely associated with the ability of a community to recover following an earthquake and, therefore, should be considered in a recovery prediction model. The city of Napa, California and the monitored recovery from the 2014 South Napa earthquake were used as a case study for the development and validation of the proposed methodology. The documentation of the recovery, which is herein associated with the recovery of the building stock, was accomplished via field surveys over a period of 18 months following the event. In addition to community-level recovery predictions in different areas over time, the methodology allows for the identification of the pre-existing socioeconomic parameters that most significantly affect the recovery trajectory. Thus, emergency managers can identify critical areas that take longer to recover, as well as identify strengths and weaknesses of their communities and respectively promote or address issues that facilitate recovery.