Flood hazard risk evaluation using fuzzy logic and weightage-based combination methods in geographic information system

Abstract

This study addresses the crucial variables contributing highly to the risk of flooding based on the flood characteristics of the Waverly region and develop a fuzzy logic and geographic information based urban flood map with flood zones in Waverly City, Iowa. The methodology emphasizes on weighting crucial variables using spatial analyst tools and fuzzy logic based GIS mapping. Local elevation, distance from Cedar River, land use and population density in Waverly city are recognized as effective variables to risk of flooding in Waverly city. Twenty three calibration tests for determination of weightages of these variables on the risk of flood were performed and compared to previously produced Waverly flood risk maps. Finally, weightages of these variables were assigned as 70 % for elevation, 20 % for distance from Cedar River, 5 % for Manning's coefficient, and 5 % for population density. In a fuzzy environment they were assigned different fuzzy membership functions, for elevation, fuzzification technique Small was used, for distance, fuzzification technique MS Small was used, for Manning's coefficient and population density, fuzzification technique Large was used. The flood hazard maps created were overlaid with 100 and 500-year flood maps of Waverly city for calibration and risk evaluation.