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Study on quantile estimates of extreme precipitation and their spatiotemporal consistency adjustment over the Huaihe River basin

机译:淮河流域极端降水分位数估计及其时空一致性调整研究。

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The quantile estimates and spatiotemporal consistency of extreme precipitation are studied by regional linear frequency analysis for Huaihe River basin in China. Firstly, the study area can be categorized into six homogeneous regions by using cluster analysis, heterogeneity measure, and discordancy measure. In the next step, we determine the optimum distribution for each homogeneous region by using two criteria of Monte Carlo simulations and the root-mean-square error (RMSE) of the sample L-moments. A diagram of L-moments ratio is used to further judge and validate the optimum distribution. The generalized extreme value (GEV), generalized normal (GNO), and generalized logistic (GLO) for 24-h duration are determined to be the more appropriate distribution based on the two criteria, L-moments ratio plot, and the tail thickness of curve in adjacent regions. A summary assessment can provide the more reasonable distribution, which avoids arbitrary results from single test. An important practical element of this study that was missing from previous works is the quantile spatiotemporal consistency analysis, which helps identify non-monotonicity among quantiles at different durations and reduces the gradient of estimates in the adjacent regions. Abnormality and spatial discontinuation can be removed by distributing the surplus of the ratio and twice different interpolation. A complete set of spatiotemporal consistent quantile estimates for various duration (24 h, 3 days, 5 days, and 7 days) and return periods (from 2 to 1000 years) can be obtained by using the abovementioned method in the study area, which are in the agreement with the observed precipitation extremes. It will provide important basis for hydrometeorological research, which is of significant scientific and practical merit.
机译:通过区域线性频率分析,研究了淮河流域极端降水的分位数估计和时空一致性。首先,可以通过聚类分析,异质性度量和不一致性度量将研究区域划分为六个同质区域。在下一步中,我们使用蒙特卡罗模拟的两个标准和样本L矩的均方根误差(RMSE)确定每个均匀区域的最佳分布。 L矩比图表用于进一步判断和验证最佳分布。根据两个标准(L矩比图和尾部厚度)确定24小时内的广义极值(GEV),广义正态(GNO)和广义对数(GLO)是更合适的分布。相邻区域的曲线。摘要评估可以提供更合理的分布,从而避免了单个测试的任意结果。分位数时空一致性分析是这项研究中缺少的重要实践元素,它有助于识别分位数在不同持续时间的分位数之间的非单调性,并减少相邻区域中估计值的梯度。可以通过分配比率的剩余部分和两次不同的插值来消除异常和空间中断。通过使用上述方法,可以在研究区域获得各种持续时间(24小时,3天,5天和7天)和返回期(2至1000年)的时空一致性分位数的完整估计值。与观测到的极端降水量一致。这将为水文气象研究提供重要依据,具有重要的科学和实践价值。

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