Appraisal of Flood Susceptibility of Hooghly basin, India using Shannon Entropy (SE) and Fuzzy Analytical Hierarchy Process (FAHP)

Abstract Hooghly basin is one of the flood-affected areas of West Bengal in India. The basin's dense river system, topography, and geographic location make it more susceptible to flooding. Effective flood management necessitates the understating of the spatial distribution of flood susceptible areas. In this context, the present work has examined the flood susceptibility of the Hooghly basin using two significant methods of multicriteria decision making models (MCDM) i.e., Shannon Entropy (SE) and Fuzzy Analytical Hierarchy Process (FAHP) models. These two models were applied to twelve flood conditioning factors such as drainage density, elevation, LULC, normalized difference built up index (NDBI), normalized difference vegetation index (NDVI), normalized difference water index (NDWI), population density, rainfall, distance to rivers, slope, stream power index (SPI) and topographic wetness index (TWI). Binary logistic regression was also performed to identify the confounders of susceptibility in the basin. Drainage density, elevation, rainfall, and distance to rivers were identified as the major determinants of flood susceptibility. Validation of the models through the area under ROC curve (AUC) showed good predictability for SE (0.70) and FAHP (0.71) based flood susceptibility prediction. Therefore, this study may provide a base for stakeholders and planners in managing and minimizing flood susceptibility in the basin.