This study assesses present and future urban flood hazards in the Bagjola Canal basin, Kolkata Metropolitan Area, by integrating climate-adjusted Intensity–Duration–Frequency (IDF) curves with a coupled 1D–2D MIKE+ hydrodynamic model under SSP2–4.5 and SSP5–8.5 scenarios. Extreme rainfall data (1980–2023) from the IMD Alipur station were analyzed using Gumbel, Log Pearson Type III, and Generalized Extreme Value (GEV) distributions, with GEV identified as the most suitable based on Kolmogorov–Smirnov, Anderson–Darling, and chi-square tests. Future rainfall projections were derived from CMIP6 models, where a Random Forest–based multi-model ensemble (MME-RF) showed superior performance (Taylor Skill Score = 0.751) and was adopted for IDF formulation. The climate-adjusted IDF curves were used as inputs to the MIKE+ rainfall–runoff and hydrodynamic modules to simulate flood depth, velocity, and momentum. Model validation against Sentinel-1 SAR–derived flood extents using the spatial fit index yielded a fit score of 0.58, comparable to recent urban flood studies in data-scarce, tidally influenced settings. Results indicate a statistically significant increase in extreme rainfall and a substantial expansion of high-hazard flood zones, with short-duration rainfall intensities projected to rise by ~ 48% under SSP2–4.5 and ~ 60% under SSP5–8.5. Under the 10-year return period, hazardous areas increase to nearly 75% of the basin under high-emission conditions, particularly in densely urbanized zones. The above results reveal that the IMD 1/3rd rule-based MIKE+ model, driven by climate scenarios, helps to generate physically induced nonlinear outcomes in the Bagjola region, thereby supporting the development of a more prepared and resilient flood mitigation plan.
Kumar et al. (Sun,) studied this question.
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