Enhancing Flood Risk Management: A Comparative Study of Regional Frequency Models in the Upper Meghna River, Bangladesh
Md. Touhidul Islam *
Department of Irrigation and Water Management, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
Nusrat Jahan
Department of Environmental Science, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
Nilima Das
Department of Irrigation and Water Management, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
Md. Asibur Rahman Abir
Haor and Char Development Institute, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
Abdullah Al Ferdaus
Haor and Char Development Institute, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
M. Shafiul Islam
Department of Irrigation and Water Management, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
Mohammed Mizanur Rahman
Department of Irrigation and Water Management, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
A.K.M. Adham
Department of Irrigation and Water Management, Bangladesh Agricultural University, Mymensingh -2202, Bangladesh.
*Author to whom correspondence should be addressed.
Abstract
Flood risk management is essential in Bangladesh, frequently affected by severe flooding due to its location at the confluence of the Ganges, Brahmaputra, and Meghna rivers. This study assesses the effectiveness of Gumbel and Log-Pearson Type III (LP3) probability distributions for flood frequency analysis at the Bhairab Bazar station in the Upper Meghna River. Using 32 years (1990-2021) of annual peak discharge data from the Bangladesh Water Development Board, flood magnitudes were predicted for various return periods. The Gumbel distribution predicted discharges from 10,709.71 m³/s for a 2-year return period to 24,519.62 m³/s for a 200-year return period, while LP3 estimates ranged from 10,701.51 m³/s to 22,911.84 m³/s for the same periods. The peak over threshold (POT) approach yielded higher discharge estimates, showing its sensitivity to extreme events. For a 200-year return period, the Gumbel-POT and LP3-POT estimates were 22,117.40 m³/s and 21,964.07 m³/s, respectively. Goodness-of-fit tests, including Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared, favored the LP3 distribution for both extreme value series (EVS) and POT data, especially in critical tail regions. A rating curve was also developed using the generalized reduced gradient algorithm to better understand the river's hydraulic behavior. These findings are crucial for local flood management strategies. Discharges exceeding critical thresholds, like the 5.8-m danger level and 6.8-m severe flood level, highlight the need for robust measures. This analysis offers essential insights for designing hydraulic structures, planning flood mitigation, and improving prediction models to enhance flood risk assessments in the Upper Meghna River basin.
Keywords: Flood frequency analysis, rating curve, extreme value series, peak over threshold, flood risk management