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Estimation of flood quantiles at gauged and ungauged sites of the four major rivers of Punjab, Pakistan

机译:巴基斯坦旁遮普省四条主要河流的测量和未测量地点的洪水分位数估计

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摘要

The paper illustrates the results of regional flood frequency analysis of eleven sites of the four major rivers of Punjab, Pakistan. The discordancy measure (D (i) ) shows that none of the site, in the cluster of eleven sites, is discordant. Timing of the flood occurrences has been used, initially, for the formation of homogeneous region, but the heterogeneity measure (H) has shown a small amount of heterogeneity. To reduce the amount of heterogeneity, a subjective adjustment has been made considering the fact that a couple of site is located at the confluence of rivers. As a result, two homogeneous regions have been identified, i.e., Region 1 having nine sites and Region 2 containing couple of site located at the confluence of the rivers. In order to find out suitable candidate(s) for regional distribution L-moment ration diagram, average weighted distance and Z (DIST) statistics have been used. To obtain the flood quantiles at ungauged sites, multiple linear regression relationship has been developed, between mean of annual maximum peak flows (AMPF) at gauged sites (l (1)) and best subset of site characteristics, i.e., average rainfall during monsoon and catchment area of the rivers to which the sites belong. A cross-validation with the observed AMPF from 2010 to 2014 and historical data (the highest of the AMPF attained so far at various sites of Region 1) showed that the estimates based on this model/procedure are accurate and useful, especially for the longer return periods.
机译:本文阐述了巴基斯坦旁遮普省四条主要河流的11个地点的区域洪水频率分析结果。不和谐度量(D(i))表明,在11个站点的集群中,没有一个站点是不和谐的。洪水发生的时间最初被用于形成同质区域,但异质性度量(H)显示出少量的异质性。为了减少异质性,考虑到几个地点位于河流交汇处这一事实,进行了主观调整。因此,已经确定了两个同质区域,即区域 1 有 9 个地点,区域 2 包含位于河流交汇处的几个地点。为了找到适合区域分布的 L 矩比图的候选者,使用了平均加权距离和 Z (DIST) 统计量。为了获得未测量地点的洪水分位数,建立了测量地点的年最大峰值流量(AMPF)平均值(l(1))与场地特征的最佳子集(即季风期间的平均降雨量和场地所属河流的集水区)之间的多元线性回归关系。与 2010 年至 2014 年观测到 的 AMPF 和历史数据(迄今为止在 1 区不同地点达到的最高 AMPF)的交叉验证表明,基于该模型/程序的估计是准确和有用的,特别是对于较长的回报期。

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