Abstract

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. FLOPIT uses water surface elevation inundation maps for at least two return periods and creates Annual Exceedance Probability (AEP) as well as inundation maps for new return levels. Potential advantages of FLOPIT include being open-source, relatively easy to implement, capable of creating inundation maps from agencies other than FEMA, and applicable to locations where FEMA published flood inundation maps but not flood probability. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates.

Highlights

  • Introduction published maps and institutional affilFlooding drives sizable risks around the globe [1,2]

  • We first analyze the Annual Exceedance Probability (AEP) maps generated by FLOod Probability Interpolation Tool (FLOPIT)

  • We introduce FLOPIT, a flood probability interpolation tool that uses flood surface elevation-probability relationships and a digital elevation model to interpolate flood probabilities and produce flood probability maps as well as water surface elevation maps for any new return period between input return periods

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Summary

Introduction

Flooding drives sizable risks around the globe [1,2]. Future flood risks are projected to increase driven by a complex interplay between changes in exposures, vulnerabilities, and hazards [3,4,5,6]. How one communicates flood probabilities can impact decision-making [8,9]. Flood probability maps are important sources of information about floods. The information communicated through these maps impacts decisions on where to build and whether to elevate structures to prevent flood damage and purchase flood insurance [9,10]. The outer edge of a zone is the maximum extent of a flood with a designated probability E. the 1 in 100-year flood), while the inner edge iations The outer edge of a zone is the maximum extent of a flood with a designated probability (i. e. the 1 in 100-year flood), while the inner edge iations

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