Abstract
Design flood estimation is very important for hydraulic structure design, reservoir operation, and water resources management. During the last few decades, severe flash floods have caused substantial human, agricultural, and economic damages in Pakistan during the Monsoon seasons. However, despite phenomenal losses, the flood characteristics are rarely investigated. In this paper, flood frequency analysis (FFA) on four major rivers over Pakistan is performed to probe probability distributions (PDs)at the right-tail flood events. For this purpose, (i) we employed ten different probability distributions associating with an L-moments method for constructing FFA models across Pakistan; (ii) we evaluated the best-fit distribution by using goodness-of-fit test and statistical criteria; and finally; (iii) we devised a Monte Carlo simulation to systematically evaluate the robustness of a selected distribution’s fitting performance by using a synthetic data series of different sizes. Our results indicated that generalized Pareto and Weibull emerged as the most viable options for quantifying hydrological quantiles for most of the river basins in Pakistan. Our main findings would provide rich information as references for flood risk assessment and water resource management in Pakistan.
Highlights
Our results indicated that generalized Pareto and Weibull emerged as the most viable options for quantifying hydrological quantiles for most of the river basins in Pakistan
Flooding is among the most threatening natural disasters, and its mitigation and management are pivotal for the design of enormous hydraulic structures, according to regulations administered by flood frequency analysis (FFA) [1,2]
It is projected that flooding phenomena will continue to happen in the future; FFA is recommended to evaluate the frequency of occurrence of extreme flood events by using several probability distributions (PDs) [3,4,5,6]
Summary
Flooding is among the most threatening natural disasters, and its mitigation and management are pivotal for the design of enormous hydraulic structures, according to regulations administered by flood frequency analysis (FFA) [1,2]. It is projected that flooding phenomena will continue to happen in the future; FFA is recommended to evaluate the frequency of occurrence of extreme flood events by using several probability distributions (PDs) [3,4,5,6]. To achieve this purpose, one key issue is the selection of appropriate PD [6,7]. China uses P3 distribution [10,11], whereas the United
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