AUTHOR=Al Assi Ayat , Mostafiz Rubayet Bin , Friedland Carol J. , Rahim Md Adilur , Rohli Robert V. TITLE=Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height JOURNAL=Frontiers in Big Data VOLUME=5 YEAR=2023 URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2022.997447 DOI=10.3389/fdata.2022.997447 ISSN=2624-909X ABSTRACT=

Evaluating flood risk is an essential component of understanding and increasing community resilience. A robust approach for quantifying flood risk in terms of average annual loss (AAL) in dollars across multiple homes is needed to provide valuable information for stakeholder decision-making. This research develops a computational framework to evaluate AAL at the neighborhood level by owner/occupant type (i.e., homeowner, landlord, and tenant) for increasing first-floor height (FFH). The AAL values were calculated here by numerically integrating loss-exceedance probability distributions to represent economic annual flood risk to the building, contents, and use. A simple case study for a census block in Jefferson Parish, Louisiana, revealed that homeowners bear a mean AAL of $4,390 at the 100-year flood elevation (E100), compared with $2,960, and $1,590 for landlords and tenants, respectively, because the homeowner incurs losses to building, contents, and use, rather than only two of the three, as for the landlord and tenant. The results of this case study showed that increasing FFH reduces AAL proportionately for each owner/occupant type, and that two feet of additional elevation above E100 may provide the most economically advantageous benefit. The modeled results suggested that Hazus Multi-Hazard (Hazus-MH) output underestimates the AAL by 11% for building and 15% for contents. Application of this technique while partitioning the owner/occupant types will improve planning for improved resilience and assessment of impacts attributable to the costly flood hazard.