Observational Verification of the Cumulative Resilience Screening Index (CRSI) Using Hurricanes, Inland Floods, and Wildfires From 2016 to 2019.

Abstract

Users can apply three processes to develop confidence in decision‐making tools like models and indices—validation, verification, and observation. The utility of the Cumulative Resilience Screening Index (CRSI) was demonstrated by combining the processes of verification and observation using real‐world natural hazard events (i.e., hurricanes, inland flooding, and wildfires). The ability of CRSI to determine the counties most vulnerable to hazards and least likely to recover quickly from natural hazards is demonstrated using these natural hazard events from outside the original index construction data set. Using Hurricane Harvey and Hurricane Michael, the counties in Texas and Florida/Georgia, respectively, experiencing the most damage and the most extended recovery intervals were determined accurately. Similarly, the most vulnerable and least recoverable counties were correctly identified as those associated with the Great Louisiana Flood of 2016. Finally, three different types of wildfires in California were examined to determine the likelihood of recovery and the strength of pre‐event planning. All models and indices developed for use by decision‐makers should consider undertaking this verification or a similar validation operation to enhance user confidence.