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A Data-driven Spatial Approach to Characterize Flood Hazard
  • +3
  • Rubayet Bin Mostafiz,
  • Adilur Rahim,
  • Carol J Friedland,
  • Robert V Rohli,
  • Nazla Bushra,
  • Fatemeh Orooji
Rubayet Bin Mostafiz
Louisiana State University

Corresponding Author:[email protected]

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Adilur Rahim
Louisiana State University
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Carol J Friedland
Louisiana State University Agricultural Center
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Robert V Rohli
College of the Coast & Environment
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Nazla Bushra
College of the Coast & Environment
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Fatemeh Orooji
Western Kentucky University
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Abstract

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.