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Bayesian Technique for the Selection of Probability Distributions for Frequency Analyses of Hydrometeorological Extremes

机译:贝叶斯技术选择水文气象极端频率分析的概率分布

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Frequency analysis of hydrometeorological extremes plays an important role in the design of hydraulic structures. A multitude of distributions have been employed for hydrological frequency analysis, and more than one distribution is often found to be adequate for frequency analysis. The current method for selecting the best fitted distributions are not so objective. Using different kinds of constraints, entropy theory was employed in this study to derive five generalized distributions for frequency analysis. These distributions are the generalized gamma (GG) distribution, generalized beta distribution of the second kind (GB2), Halphen type A distribution (Hal-A), Halphen type B distribution (Hal-B), and Halphen type inverse B (Hal-IB) distribution. The Bayesian technique was employed to objectively select the optimal distribution. The method of selection was tested using simulation as well as using extreme daily and hourly rainfall data from the Mississippi. The results showed that the Bayesian technique was able to select the best fitted distribution, thus providing a new way for model selection for frequency analysis of hydrometeorological extremes.
机译:水文气象极端事件的频率分析在水工结构设计中起着重要作用。水文频率分析已采用多种分布,通常发现一种以上的分布足以进行频率分析。当前选择最佳拟合分布的方法并不那么客观。利用不同的约束条件,在本研究中采用熵理论来导出五个广义分布用于频率分析。这些分布是广义伽玛(GG)分布,第二种广义β分布(GB2),哈尔芬A型分布(Hal-A),哈尔芬B型分布(Hal-B)和哈尔芬反B型(Hal- IB)分发。贝叶斯技术被用来客观地选择最佳分布。选择方法通过模拟以及密西西比州极端的每日和每小时降雨数据进行了测试。结果表明,贝叶斯技术能够选择最佳拟合分布,从而为水文气象极端频率分析的模型选择提供了新途径。

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