Advancing parcel-level hurricane regional loss assessments using open data and the regional resilience determination tool

Abstract

Hurricanes are a major driver of losses in the United States and thus are the focus of risk assessment capacity building efforts in the public and private sectors, as well as in the scholarly community. Capabilities for loss modeling have been particularly advanced through the development of open-source scientific workflows that conduct site-specific, building-specific, and even component-level loss assessments across entire regions. Notable among these is the Natural Hazards Engineering Research Infrastructure's Computational Modeling and Simulation Center's (NHERI SimCenter) Regional Resilience Determination (R2D) tool. However, the modular architecture of R2D's computational scaffolding has only been described and illustrated through testbed applications thus far. This study presents the first replication and extension of the R2D tool to conduct parcel-level and component-level hurricane performance assessments outside of the SimCenter's testbed locations. The study first details how building inventories that capture time-evolving building characteristics and regional construction practices can be generated using updated heuristic rulesets that guide the integration of tax assessor data with other open data sources. These rulesets and supporting data are then utilized to generate building inventory information for a set of single family homes located in Florida's Bay County, the landfall site of Hurricane Michael in 2018. HAZUS-compatible, parcel-level damage and loss assessments are then conducted, considering Hurricane Michael's peak gust wind speeds. Finally, a set of custom fragilities, empirically-derived from multiple regional post-disaster datasets, are incorporated into R2D to conduct the first component-level damage assessment of buildings under hurricanes using the SimCenter's regional loss modeling workflows. In total, this represents an important first step in operationalizing replicable regional risk assessments down to the parcel level to provide more granular risk information to key stakeholders.