A Data-driven Spatial Approach to Characterize Flood Hazard

Abstract

United States Federal Emergency Management Agency 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). But these flood grids are often unavailable or fail to include return periods for particular applications, such as understanding flood risk of properties during the 70-year useful building life cycle. Furthermore, 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 the flood hazard for U.S. properties that are located both inside and outside the SFHA. The flood hazard is characterized by the Gumbel extreme value distribution to project flood elevations to extreme flood events for which an entire area is assumed to be submerged. Spatial interpolation techniques impute elevation values in the extreme flood elevation surfaces and therefore can estimate the flood hazard for areas outside the SFHA. The proposed method can improve the assessment of flood risk for properties located in both inside and outside the SFHA and therefore, 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.