A Study on Flood Hazard Zonation Mapping Based on GIS-driven Approach using Remote Sensing Data and Weighted Overlay Analysis (Woa) Model

Abstract

Flood hazard mapping is crucial for identifying flood-prone areas and developing effective mitigation strategies. This study utilized a Weighted Overlay Analysis, which is one of the subjective model derived from Multi-Criteria Decision Support System (MCDA), to assess flood hazards in the Auranga watershed, India. Six key flood-inducing factors were selected, including topographic data such as elevation, slope, river distance, and flow length derived from remote sensing data of Digital Elevation Model and classified Land use/Land cover data, along with hydro-meteorological data of precipitation. Each dataset was standardized to a common scale to facilitate comparison and integration. Weights were assigned to the layers like elevation, slope, river distance, flow length, Land use/Land cover, and precipitation according to their significance in contributing to flood risk. These weighted layers were then combined using GIS tools like ArcGIS, resulting in a composite map that delineates areas with varying flood hazard zones. The final flood hazard map identified that approximately 914 sq. km (60.0%) of the study area was at high to very high flood risk, particularly in regions close to rivers, while around 97 sq. km (6.4%) exhibited very low flood hazard. The GIS-Weighted Overlay Analysis method proved effective in flood hazard zone mapping, especially when incorporating a greater number of parameters. This approach is widely recognized in environmental planning and risk assessment, especially in areas vulnerable to natural disasters like floods.