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Modelling of Extreme Rainfall Events in Peninsular Malaysia based on Annual Maximum and Partial Duration Series

机译:基于年度最大和部分持续时间系列的半岛马来西亚极端降雨事件的建模

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In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.
机译:在这项研究中,基于年度最大和部分持续时间方法产生了两种用于极端降雨事件的数据,从1982 - 2012年从半岛的102个雨量站得出。为了确定每个站的最佳阈值,必须满足几种要求,并且为此目的采用适应的Hill估计器。然后使用半参数自举引导程序来估计每个阈值处的估计器的平均误差(MSE),并且基于最小的MSE选择最佳阈值。还检查了平均年度频率,以确保它位于一到五个范围内,并且所产生的数据也被解聚以确保独立性。然后,两种数据序列分别适用于广义极值和广义Pareto分布,分别为年度最大和部分持续时间系列。使用的参数估计方法是最大可能性和L-矩方法。然后使用两种拟合测试的良好评估最佳分布。结果表明,具有广义帕累托分布和最大似然参数估计的部分持续时间序列为学习的大多数车站提供了半岛马来西亚的极端降雨事件的最佳表示。基于这些发现,还导出了几个返回值,构建了空间映射,以确定半岛马来西亚的极端降雨的分布特征。

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