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Understanding flood probabilities is essential to making sound decisionsabout flood-risk management. Many people rely on flood probability maps toinform decisions about purchasing flood insurance, buying or sellingreal-estate, flood-proofing a house, or managing floodplain development.Current flood probability maps typically use flood zones (for example the 1 in100 or 1 in 500-year flood zones) to communicate flooding probabilities.However, this choice of communication format can miss important details andlead to biased risk assessments. Here we develop, test, and demonstrate theFLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates floodprobabilities between water surface elevation to produce continuousflood-probability maps. We show that FLOPIT can be relatively easily applied toexisting datasets used to create flood zones. Using publicly available datafrom the Federal Emergency Management Agency (FEMA) flood risk databases aswell as state and national datasets, we produce continuous flood-probabilitymaps at three example locations in the United States: Houston (TX), Muncy (PA),and Selinsgrove (PA). We find that the discrete flood zones generallycommunicate substantially lower flood probabilities than the continuousestimates.

The FLOod Probability Interpolation Tool (FLOPIT): Improving Spatial  Flood Probability Quantification and Communication Through Higher Resolution  Mapping