Evaluation of probability distribution methods for flood frequency analysis in the Jhelum Basin of North-Western Himalayas, India

Asif Iqbal Shah , Nibedita Das Pan
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Abstract

The Kashmir Valley has frequently endured devastating floods, presenting significant challenges for flood management due to unpredictable flood magnitudes and limited pre-disaster preparedness. A major difficulty in addressing these challenges is the lack of reliable flood frequency analysis (FFA) for effective planning and mitigation. This study seeks to overcome these issues by employing a rigorous quantitative analysis of annual peak discharge data over a 51-year period (1971–2021). One key challenge was the presence of low outliers, which could compromise the integrity of the data. To address this, the Multiple Grubbs-Beck test was applied to remove these outliers before conducting FFA. The study's original achievement lies in its application of multiple distribution models which include Gumbel (EV1), Generalized Extreme Variations (GEV), Log-Normal, Log Pearson III (LP III), Gamma and Normal distribution. Goodness-of-fit tests, including Kolmogorov-Smirnov (KS), Anderson-Darling (AD), and Chi-square at the 5 % significance level, along with visualization techniques such as Probability plots (PP), Quantile plots (QQ), and Probabilistic distribution (PD) graphs, were used to identify the most suitable distribution methods. The Log Pearson Type III (LP-III) was identified as the best fit for the Sangam gauge site (Upper Jhelum), the gamma distribution for Ram Munshibagh (Middle Jhelum), and the Generalized Extreme Value (GEV) and LP-III for Asham (Lower Jhelum). For Sangam, the estimated discharges for 2, 5, 10, 50, 100, 150, 200, and 250-year return periods were 549.63, 1028.43, 1471.34, 2907.64, 3758.92, 4338.61, 4790.99, and 5167.23 cumecs, respectively, using LP-III. For Ram Munshibagh, the discharges were 602.13, 911.03, 1107.04, 1512.12, 1674.35, 1767.0, 1831.87, and 1881.74 cumecs using the gamma distribution. For Asham, the discharges were 685.8, 998.0, 1193.3, 1593.2, 1750.6, 1839.4, 1901.0, and 1948.0 cumecs using the GEV distribution. The findings indicate that the Jhelum River cannot accommodate excess discharge for return periods of 5 years or more, underscoring the need for enhanced flood management strategies.
印度西北喜马拉雅山杰赫勒姆盆地洪水频率分析概率分布方法评估
克什米尔山谷经常遭受毁灭性洪水的袭击,由于洪水规模难以预测以及灾前准备有限,给洪水管理带来了巨大挑战。应对这些挑战的一个主要困难是缺乏可靠的洪水频率分析 (FFA),无法进行有效的规划和减灾。本研究试图通过对 51 年间(1971-2021 年)的年峰值排水数据进行严格的定量分析来克服这些问题。一个主要挑战是存在低离群值,这可能会影响数据的完整性。为了解决这个问题,在进行 FFA 之前,采用了多重格拉布斯-贝克检验法来去除这些离群值。这项研究的原创性成就在于它应用了多种分布模型,包括 Gumbel (EV1)、广义极差 (GEV)、对数正态分布、对数皮尔逊 III (LPIII)、伽马分布和正态分布。拟合优度测试包括 Kolmogorov-Smirnov (KS)、Anderson-Darling (AD)、5% 显著性水平的 Chi-square,以及可视化技术,如概率图 (PP)、定量图 (QQ) 和概率分布图 (PD),用于确定最合适的分布方法。对数皮尔逊 III 型分布(LP-III)被认为是最适合桑加姆测量点(上杰赫勒姆)的分布,伽马分布被认为是最适合拉姆-蒙希巴格测量点(中杰赫勒姆)的分布,广义极值分布(GEV)和 LP-III 分布被认为是最适合阿沙姆测量点(下杰赫勒姆)的分布。对于 Sangam,使用 LP-III,2、5、10、50、100、150、200 和 250 年重现期的估计排水量分别为 549.63、1028.43、1471.34、2907.64、3758.92、4338.61、4790.99 和 5167.23 cumecs。在 Ram Munshibagh,采用伽马分布的排水量分别为 602.13、911.03、1107.04、1512.12、1674.35、1767.0、1831.87 和 1881.74 立方厘米。在阿沙姆河,采用 GEV 分布的排水量分别为 685.8、998.0、1193.3、1593.2、1750.6、1839.4、1901.0 和 1948.0 立方厘米。研究结果表明,杰赫勒姆河无法容纳 5 年或 5 年以上重现期的过量排水,这突出表明需要加强洪水管理战略。
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