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

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. • Analyzed annual peak discharge values from a 51-year period (1971–2021) for the Jhelum River, ensuring robust and reliable flood frequency estimates. • Applied the Multiple Grubbs-Beck test to detect and address low outliers before conducting Flood Frequency Analysis (FFA), ensuring the accuracy and integrity of the findings. • Employed Goodness of fit tests and Distribution visualization techniques were used to identify the most suitable flood prediction models. • Log Pearson III as the most suitable model for the Sangam gauge site, Gamma distribution for the Ram Munshibagh site, and both Generalized Extreme Value and LP III distributions for the Asham gauge site. • Jhelum River cannot contain the excess discharge for return periods ≥ 5 years.

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Publication Details

Journal
Cleaner Water
Published
2024-09-26
DOI
https://doi.org/10.1016/j.clwat.2024.100044
Citations
16
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
4.52
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article

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

Nibedita Das Pan, Asif Iqbal Shah
16 citations
Cleaner Water
Hydrology and Drought Analysis
4.52
article

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

Nibedita Das Pan, Asif Iqbal Shah
article en
16 citations

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. • Analyzed annual peak discharge values from a 51-year period (1971–2021) for the Jhelum River, ensuring robust and reliable flood frequency estimates. • Applied the Multiple Grubbs-Beck test to detect and address low outliers before conducting Flood Frequency Analysis (FFA), ensuring the accuracy and integrity of the findings. • Employed Goodness of fit tests and Distribution visualization techniques were used to identify the most suitable flood prediction models. • Log Pearson III as the most suitable model for the Sangam gauge site, Gamma distribution for the Ram Munshibagh site, and both Generalized Extreme Value and LP III distributions for the Asham gauge site. • Jhelum River cannot contain the excess discharge for return periods ≥ 5 years.

Cleaner WaterVol. 2
Tripura University (IN)
Climate action
Openalex Percentile: Top 5%
Hydrology and Drought Analysis
4.52
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