Date of Publication : June 2026

Abstract: Flood events represent one of the most devastating natural hazards in India, with the Kolhapur district of Maharashtra being particularly vulnerable due to its complex topography, intense monsoonal rainfall, and rapidly expanding urban footprint. This study presents a comprehensive geospatial assessment of flood susceptibility and flood risk across Kolhapur district by integrating four key biophysical and socio-demographic parameters: mean annual rainfall, terrain slope, urban density, and population count. A multi-criteria weighted index approach was employed wherein flood susceptibility was computed as a normalised composite of rainfall erosivity and slope gradient, while flood risk was derived by coupling susceptibility with population exposure and urban density. Spatial data were processed and analysed using Python-based geospatial libraries (rasterio, numpy, matplotlib) operating on high-resolution raster datasets. Results reveal that flood susceptibility values across the district range predominantly between 0.3 and 0.7 (mean ≈ 0.45), with the highest susceptibility concentrated in the northwestern and central urban zones where low slopes intersect with high monsoonal rainfall. Flood risk, after incorporating population and urban density weights, is highly skewed towards near-zero values for the majority of the district, while a spatially concentrated nucleus of high risk (index > 0.4) is evident in and around the Kolhapur Municipal Corporation area. Quantile-based classification identifies approximately 30% of non-zero pixels as moderate-to-high risk. Scatter plot diagnostics confirm that flood risk exhibits a non-linear threshold response to flood susceptibility, activating sharply around a susceptibility value of 0.62–0.65, which corresponds to zones of peak population density and near-complete urban coverage. These findings have direct implications for urban flood management planning, early warning system design, and infrastructure investment prioritisation in Kolhapur.

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