Integrating flood loss data into an empirical model for community estimates of risk.

With an increase and intensification of tropical storm events in the future, it becomes paramount for individual communities and homeowners to understand their potential risks of impacts from these events. This study describes an empirical modeling methodology using the City of Norfolk in southeastern Virginia to indicate areas of higher risk based on built infrastructure, property exposure, and temporal records of previous losses. Under this new empirical modeling methodology, a risk score is defined as the properties that may be at higher risk from future flooding events based on elevation differences, the number of flood insurance payouts a property has received, and whether a property has an active flood insurance policy. Results make evident how the methodology can be used to characterize a community's risk and highlight higher-risk hot spots that can in turn be used for future resilience planning and hazard mitigation. Future work to further refine the model can reduce the overall uncertainty levels as data become more publicly accessible.