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Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height

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 re...

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Autores principales: Al Assi, Ayat, Mostafiz, Rubayet Bin, Friedland, Carol J., Rahim, Md Adilur, Rohli, Robert V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868865/
https://www.ncbi.nlm.nih.gov/pubmed/36700139
http://dx.doi.org/10.3389/fdata.2022.997447
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author Al Assi, Ayat
Mostafiz, Rubayet Bin
Friedland, Carol J.
Rahim, Md Adilur
Rohli, Robert V.
author_facet Al Assi, Ayat
Mostafiz, Rubayet Bin
Friedland, Carol J.
Rahim, Md Adilur
Rohli, Robert V.
author_sort Al Assi, Ayat
collection PubMed
description 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 (E(100)), 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 E(100) 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.
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spelling pubmed-98688652023-01-24 Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height Al Assi, Ayat Mostafiz, Rubayet Bin Friedland, Carol J. Rahim, Md Adilur Rohli, Robert V. Front Big Data Big Data 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 (E(100)), 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 E(100) 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. Frontiers Media S.A. 2023-01-09 /pmc/articles/PMC9868865/ /pubmed/36700139 http://dx.doi.org/10.3389/fdata.2022.997447 Text en Copyright © 2023 Al Assi, Mostafiz, Friedland, Rahim and Rohli. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Al Assi, Ayat
Mostafiz, Rubayet Bin
Friedland, Carol J.
Rahim, Md Adilur
Rohli, Robert V.
Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
title Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
title_full Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
title_fullStr Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
title_full_unstemmed Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
title_short Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
title_sort flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868865/
https://www.ncbi.nlm.nih.gov/pubmed/36700139
http://dx.doi.org/10.3389/fdata.2022.997447
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