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

Abstract

This study addresses the crucial variables that contribute highly to the risk of flood based on the flood characteristics of the Waverly region and develops a fuzzy logic and geographic information-based urban flood map with flood zones in Waverly City, Iowa. The methodology emphasizes weighting crucial variables using spatial analyst tools and fuzzy logic-based Geographic Information System (GIS) mapping. Local elevation, distance from Cedar River, land use, and population density in Waverly City are recognized as effective variables involved in the risk of flood in Waverly City. Twenty-three calibration tests for determining the weights of these variables on the risk of flood were performed and compared to previously produced Waverly flood risk maps. Finally, the weights 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 to 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. (C) 2020 Sharif University of Technology. All rights reserved.