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Selecting a probability distribution for extreme rainfall series in Malaysia

机译:选择马来西亚极端降雨序列的概率分布

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This paper discusses the comparative assessment of eight candidate distributions in providing accurate and reliable maximum rainfall estimates for Malaysia. The models considered were the Gamma, Generalised Normal, Generalised Pareto, Generalised Extreme Value, Gumbel, Log Pearson Type III, Pearson Type III and Wakeby. Annual maximum rainfall series for one-hour resolution from a network of seventeen automatic gauging stations located throughout Peninsular Malaysia were selected for this study. The length of rainfall records varies from twenty-three to twenty-eight years. Model parameters were estimated using the L-moment method, The quantitative assessment of the descriptive ability of each model was based on the Probability Plot Correlation Coefficient test combined with root mean squared error, relative root mean squared error and maximum absolute deviation. Bootstrap resampling was employed to investigate the extrapolative ability of each distribution. On the basis of these comparisons, it can be concluded that the GEV distribution is the most appropriate distribution for describing the annual maximum rainfall series in Malaysia. [References: 18]
机译:本文讨论了对八个候选分布的比较评估,以便为马来西亚提供准确和可靠的最大降雨量估计值。所考虑的模型是Gamma,广义范式,广义帕累托,广义极值,Gumbel,Log Pearson III型,Pearson III型和Wakeby。通过位于马来西亚半岛各地的17个自动测量站组成的网络,选择了一个小时分辨率的年度最大降雨量序列进行此项研究。降雨记录的长度从23年到28年不等。使用L矩法估计模型参数,基于概率图相关系数检验结合均方根误差,相对均方根误差和最大绝对偏差,对每个模型的描述能力进行定量评估。自举重采样用于研究每个分布的外推能力。根据这些比较,可以得出结论,GEV分布是描述马来西亚年度最大降雨量序列的最合适的分布。 [参考:18]

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