A probabilistic multi-return-period framework for integrated flood risk assessment in the Teesta River Basin, northern Bangladesh

Flooding in the Teesta River Basin, northern Bangladesh, frequently threatens lives, agriculture, and infrastructure due to intense monsoonal rainfall, transboundary flows, and low-lying floodplains. This study presents an integrated probabilistic flood risk assessment by combining statistical flood frequency analysis, 1D–2D hydrodynamic modelling (HEC-RAS), and GIS-based socio-economic vulnerability assessment using the Analytic Hierarchy Process (AHP). Long-term discharge and water level records were analyzed using six probability distributions: Normal, Log-normal, Pearson Type-III, Log-Pearson Type-III, Gumbel, and Generalized Extreme Value. Based on the goodness-of-fit tests (Chi-square, Kolmogorov-Smirnov, and Anderson-Darling), the Generalized Extreme Value and Pearson Type-III distributions were selected for the upstream and downstream stations, respectively, to estimate design discharges and water levels for the 50-, 100-, 200-, and 500-year return periods, along with the 5th and 95th percentile confidence intervals. Calibration and validation of the 1D model were conducted at Kaunia station, yielding RMSE of 0.183–0.273 m, NSE of 0.917–0.967, and PBIAS of –0.46 to +0.22, indicating excellent predictive performance. The 2D model was validated using Receiver Operating Characteristic analysis, achieving an Area Under the Curve value of 0.864. Coupled 1D–2D simulations revealed 34–40% of the basin inundated across return periods, with maximum depths exceeding 7 m in main channels. AHP-based vulnerability mapping, integrating nine socio-economic and physical indicators, identified moderate to high vulnerability across most of the study area. Combined flood hazard and vulnerability analysis indicated that over 20% of the basin falls under high and very high flood risk, with the most affected upazilas (sub-districts) including Lalmonirhat Sadar, Kaunia, Gangachara, Dimla, and Aditmari. This integrated framework highlights the combined influence of hydrological extremes and socio-economic exposure on flood risk, offering a transferable approach for data-limited deltaic basins to support targeted mitigation, land-use planning, and resilience enhancement.