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ORIGINAL RESEARCH
Searching for the Most Suited Distribution
and Estimation Method for At-Site Flood Frequency
Analysis: A Case of the Chenab River
1
College of Statistical Sciences, University of the Punjab, Lahore, Pakistan
2
Department of Statistics, Government College University Faisalabad, Pakistan
3
Department of Mathematical Statistics and Actuarial Science, University of the Free State, Bloemfontein, South Africa
4
Institute of Environmental Medicine, Division of Biostatistics, Karolinska Institute, Stockholm, Sweden
Submission date: 2023-10-08
Final revision date: 2023-12-17
Acceptance date: 2024-03-11
Online publication date: 2024-04-03
Publication date: 2025-01-02
Corresponding author
Pol. J. Environ. Stud. 2025;34(1):29-42
KEYWORDS
generalized extreme valuegeneralized logisticgeneralized paretomaximum likelihoodreverse Gumbel distribution
TOPICS
ABSTRACT
The article deals with at-site flood frequency analysis for different gauging stations of the Chenab
River in Pakistan. The study aimed at recommending the most suitable probability distribution
and efficient method of parameter estimation for each gauging site. Generalized extreme value,
generalized logistic, Gumbel, generalized Pareto, and reverse Gumbel probability models are fitted
to the annual peak flow/discharge. For each gauging site, the parameters of these distributions are
estimated through L-moments, maximum likelihood, least squares, weighted least squares, and relative
least squares methods. For each site, the probability models with a particular estimation method
are ranked on the basis of goodness-of-tests and accuracy measures, and then the most suitable pair
of model and estimation method is identified through a total rank. The results indicate that
the generalized Pareto distribution is the best fit for Marala, Khanki, Qadirabad, and Punjnad, while
the generalized extreme value distribution is the most suited for the Trimmu gauging site. As far as
the estimation method is concerned, least squares and weighted least squares methods are more accurate
for most of the gauging sites. Finally, for each gauging site, the best-suited probability model is used to
estimate the annual peak flow and to construct associated confidence intervals for different return years.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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