Geospatial modelling of flood susceptibility pattern in a subtropical area of West Bengal, India

Abstract

Flood hazards are the most destructive among all natural disasters and are a constant threat to human’s life and property. Effective disaster risk reduction strategies can be improved by geospatial approach in the way of producing information and knowledge that are useful to plan truly effective actions for the protection from floods. This research aims to develop a quantified predictive model of flood susceptibility in the Ghatal and Tamluk subdivision of Medinipur district of West Bengal, India, by means of empirically selected and weighted spatial predictors of flood. The weighted prediction model is used to quantify the spatial associations between individual geospatial factors within the flood inundated study area. Yule’s coefficient and distance distribution analysis are used to assign weights to individual geo-factors, and finally weighted spatial predictors are integrated to a multi-class index overlay analysis to derive the spatially explicit predictive model of flood susceptibility. The resultant susceptibility model reveals that approximately 32.35 and 52.99% of the total study areas (3261.45 km2) are under the category of high-to-moderate flood susceptible zone. Quantitative results of this study could be integrated into the policy process in the formulation of local and national government plans for the future flood mitigation management and also to develop appropriate infrastructure in order to protect the lives and properties of the common people of the Medinipur district.