A Numerically-integrated Approach for Residential Flood Loss Estimation at the Community Level

Mostafiz, Rubayet Bin; Assi, Ayat Al; Friedland, Carol J.; Rohli, Robert V.; Rahim, Md Adilur

doi:10.5194/egusphere-egu22-10827

Cited by 14 publications

(13 citation statements)

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“…In addition to evaluate the flood risk across multiple homes, understanding the absolute and relative economic effectiveness of FFH by owner/occupant type supports hazard planning and mitigation to decrease flood risk. Application of the improved, refined numerical integration approach across multiple homes with varying attributes is useful in future work for assessing community-level flood risk (Mostafiz et al, 2022b ), thereby leading to more informed decision-making (Mostafiz et al, 2022c ) at the second-most-local scale in the spectrum.…”

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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“…Consequences of this gap in scientific analysis ripple into many facets of flood awareness, communication, modeling, planning, preparation, and recovery (Huang and Xiao, 2015 ). Thus, improved quantification of flood hazards, and therefore flood risk, is crucial not only for its own sake, but also for the benefit of other, related efforts to reduce flood-induced losses to life and property (Merz et al, 2014 ; Mostafiz et al, 2021b , 2022a ; Al Assi et al, 2022a ; Gnan et al, 2022a ; Rahim et al, 2022a ).…”

Section: Introductionmentioning

confidence: 99%

A data-driven spatial approach to characterize the flood hazard

et al. 2022

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Model output of localized flood grids 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 [i.e., recurrence interval, or the reciprocal of the annual exceedance probability (AEP)] flood grids, the flood risk of properties located outside the SFHA cannot be quantified. Here, we present a method to estimate flood hazards that are located both inside and outside the SFHA using existing 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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“…Consequences of this gap in scientific analysis ripple into many facets of flood awareness, communication, modeling, planning, preparation, and recovery (Huang & Xiao 2015). Thus, improved quantification of flood hazards, and therefore flood risk, is crucial not only for its own sake, but also for the benefit of other, related efforts to reduce flood-induced losses to life and property (Al Assi et al 2022;Gnan et al 2022a;Merz et al 2014;Mostafiz et al 2021bMostafiz et al , 2022bRahim et al 2022a).…”

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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A Numerically-integrated Approach for Residential Flood Loss Estimation at the Community Level

Cited by 14 publications

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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 the flood hazard

A Data-driven Spatial Approach to Characterize Flood Hazard

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