Abstract

Flood damage estimates for two subwatersheds of the Red River Valley were found to be deficient in terms of availability, accuracy, and geographic detail. Data manipulation strategies were used to improve the quality of flood damage estimates in the two watersheds between 1989 and 1998. Extrapolating previous agricultural flood damage estimates for specific years based on hydrologic data increased such estimates by 340% in the Maple Watershed, North Dakota and by 200% in the Wild Rice Watershed, Minnesota. Conversely, identifying the township location of nonagricultural flood damage payments by FEMA along with a simple population based adjustment of other county level nonagricultural damage in each watershed, reduced nonagricultural flood damage estimates by 80% in the Maple Watershed and by 27% in the Wild Rice Watershed. It is recommended that disaster relief agencies increase the geographical specificity of their damage payment data. Until then, the data manipulation procedures of this present study have the potential to improve the temporal and spatial accuracy of watershed level flood damage estimates.

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