Present vs. Future Losses from a 100-year Flood: A Case Study of Grand Isle, Louisiana

Mostafiz, Rubayet Bin; Bushra, Nazla; Freidland, Carol; Rohli, Robert V.

doi:10.1002/essoar.10509333.1

Cited by 2 publications

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“…In the next 30 years, flood-related property damage may increase by 60% as a result of climate change (Sastry, 2021 ), and many communities and individuals underestimate the potential for flood damage (Burningham et al, 2008 ; Mol et al, 2020 ). Therefore, many researchers worldwide have focused on flood risk and loss assessments (e.g., Dutta et al, 2003 ; Scawthorn et al, 2006 ; Tam et al, 2014 ; Afifi et al, 2019 ; Mostafiz et al, 2021a , d ; Al Assi et al, 2022a , b ; Jin et al, 2022 ; Rahim et al, 2022a , b ) and the value of mitigating the flood risk (Taghinezhad et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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“…The properties inside the shaded X Zone are considered to have "moderate" flood risk whereas properties inside the unshaded X Zone are labeled as being subjected to "minimal" flood risk (Federal Emergency Management Agency (FEMA) 2005), even though the precise risk throughout the zone is currently unknown. The need for greater quantitative techniques is obvious, so that citizen constituents and government leaders are more aware of the risks that they and their communities face (Mostafiz et al 2022c(Mostafiz et al , 2021d.…”

Section: Introductionmentioning

confidence: 99%

A Data-driven Spatial Approach to Characterize Flood Hazard

Mostafiz

Rahim

Friedland

et al. 2022

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The United States Federal Emergency Management Agency (FEMA) provides model-output localized flood grids that are useful in characterizing flood hazards for properties located in the Special Flood Hazard Area (SFHA -areas expected to experience a 1% or greater annual chance of flooding). However, due to the unavailability of higher-return-period flood grids, the flood risk of properties located outside the SFHA cannot be quantified. Here, we present a method to estimate flood hazards for U.S. properties that are located both inside and outside the SFHA using existing annual exceedance probability (AEP) surfaces. Flood hazards are characterized by the Gumbel extreme value distribution to project extreme flood event elevations for which an entire area is assumed to be submerged. Spatial interpolation techniques impute flood elevation values and are used to estimate flood hazards for areas outside the SFHA. The proposed method has the potential to improve the assessment of flood risk for properties located both inside and outside the SFHA and therefore to improve the decision-making process regarding flood insurance purchases, mitigation strategies, and long-term planning for enhanced resilience to one of the world's most ubiquitous natural hazards.

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Present vs. Future Losses from a 100-year Flood: A Case Study of Grand Isle, Louisiana

Cited by 2 publications

References 0 publications

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

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

A Data-driven Spatial Approach to Characterize Flood Hazard

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