Regional Flood Frequency Analysis in Northeastern Bangladesh Using L-Moments for Peak Discharge Estimation at Various Return Periods in Ungauged Catchments
Sujoy Dey, S. M. Tasin Zahid, Saptaporna Dey, Kh. M. Anik Rahaman, A. K. M. Saiful Islam
Abstract
The Sylhet Division of Bangladesh, highly susceptible to monsoon flooding, requires effective flood risk management to reduce socio-economic losses. Flood frequency analysis is an essential aspect of flood risk management and plays a crucial role in designing hydraulic structures. This study applies regional flood frequency analysis (RFFA) using L-moments to identify homogeneous hydrological regions and estimate extreme flood quantiles. Records from 26 streamflow gauging stations were used, including streamflow data along with corresponding physiographic and climatic characteristic data, obtained from GIS analysis and ERA5 respectively. Most stations showed no significant monotonic trends, temporal correlations, or spatial dependence, supporting the assumptions of stationarity and independence necessary for reliable frequency analysis, which allowed the use of cluster analysis, discordancy measures, heterogeneity tests for regionalization, and goodness-of-fit tests to evaluate candidate distributions. The Generalized Logistic (GLO) distribution performed best, offering robust quantile estimates with narrow confidence intervals. Multiple Non-Linear Regression models, based on catchment area, elevation, and other parameters, reasonably predicted ungauged basin peak discharges (R2 = 0.61–0.87; RMSE = 438–2726 m3/s; MAPE = 41–74%) at different return periods, although uncertainty was higher for extreme events. Four homogeneous regions were identified, showing significant differences in hydrological behavior, with two regions yielding stable estimates and two exhibiting greater extreme variability.