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At-Site Flood Frequency Analysis of Annual Maximum Stream Flows in Pakistan Using Robust Estimation Methods

机译:基于稳健估计方法的巴基斯坦年度最大河流量实地洪水频率分析

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Our paper compares the L-moments (MLM), TL-moments (MTLM), and maximum likelihood estimation (MLE) methods in order to select the best-fit distribution of annual maximum stream flow (AMSF) data for at-site flood frequency analysis (FFA) in Pakistan. Initially this study considered different probability distributions. Best distribution for each site is identified using different goodness of fit tests such as mean absolute deviation index (MADI), Anderson darling (AD) test, probability plot correlation coefficient (PPCC), and L-moments ratio diagram. Results show that GPA distribution is the most suitable distribution for most of the sites, followed by GLO and GEV distributions, respectively. MLM is found to be the most suitable estimation method in finding the best-fit distribution for most of the sites in this study, followed by MTLM and MILE. For at-site FFA we also estimated different return periods associated with given flood magnitudes (quantiles of best fit distribution/maximum annual discharge values). It is found that estimated flows based on fitted distribution are in close agreement with observed flows.
机译:本文比较了L矩(MLM),TL矩(MTLM)和最大似然估计(MLE)方法,以便为现场洪水频率选择年度最大流量(AMSF)数据的最佳拟合分布分析(FFA)。最初,这项研究考虑了不同的概率分布。使用不同的拟合优度检验,例如平均绝对偏差指数(MADI),安德森亲爱的(AD)检验,概率图相关系数(PPCC)和L矩比图,可以确定每个站点的最佳分布。结果表明,GPA分布是大多数站点的最合适分布,其次分别是GLO和GEV分布。在本研究的大多数地点,发现传销是发现最合适分布的最合适的估算方法,其次是传销和传销。对于现场FFA,我们还估算了与给定洪水强度(最佳拟合分布的分位数/最大年排放量)相关的不同回报期。结果发现,基于拟合分布的估计流量与观察到的流量非常吻合。

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