Statistical Modeling for Flood Frequency in Upper Chaophraya River Basin

Areerat Anuchon, Kamon Budsaba, Andrei Volodin
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Abstract

The research deals with the probabilistic estimates of annual maximum flood peaks in the upper Chaophraya basin (Thailand) used the extreme value theory, the Block Maxima. The Generalized Extreme Value (GEV) distribution model, the Frèchet distribution (EV2), the extension of the Frèchet distribution such as the Kumaraswamy Frèchet distribution and the new distribution as called the Exponentiated Kumaraswamy Frèchet distribution satisfied the Goodness of fit test (Kolmokorov-smirnov test). The return levels are estimated for 3, 5, 10, 30, 50, 100, 500 and 1000 years which are consistently increasing for designs of flood protection in future. The return period of flood for each stations are estimated. The investigation of the new distribution and appropriated estimation technique for the flood frequency in upper Chaophraya river basin as we called the Exponentiated Kumaraswamy Frèchet distribution and the differential evolution maximum likelihood estimation were done. We derived the properties of the Frèchet family; such as the Frèchet distribution (EV2), the Kumaraswamy Frèchet distribution (KF) and the Exponentiated Kumaraswamy Frèchet distribution (EKF). We also compared Bias, Variance, Mean Square Error and Mean Absolute Percentage Error for all parameters in each distribution by generating the Frèchet family random number. For the effectiveness of analytical solutions of the parameters we provided the numerical solutions (differential evolution method) to obtain estimates for all parameters by using Scilab program. Accuracy of flood assessment of extreme event is of fundamental importance for many safety, engineering and financial application. In part of application we provided the probabilistic estimates of annual maximum flood peaks or momentary peak data in the upper Chaophraya river basin (Thailand). The Generalized Extreme Value (GEV) distribution model were used to be gain to compare with as the Frèchet distribution (EV2), the Kumaraswamy Frèchet distribution (KF) and the Exponentiated Kumaraswamy Frèchet distribution (EKF). The Goodness of fit test, the return level and return period were done. The return periods of flood were classified by hazard class using GEV found that in upper Chaophraya river basin flood occurred highly. The result from the Frèchet family also occurred highly, but the return period and return level from the Kumaraswamy Frèchet distribution (KF) quite closed to GEV more than another distribution.
Chaophraya河上游流域洪水频率的统计模拟
该研究使用极值理论,即块极值,对泰国Chaophraya流域上游的年最大洪峰进行了概率估计。广义极值(GEV)分布模型、fr 分布(EV2)、fr 分布的扩展如Kumaraswamy fr分布和新的指数Kumaraswamy fr分布满足拟合优度检验(Kolmokorov-smirnov检验)。预计未来3年、5年、10年、30年、50年、100年、500年和1000年的水位将持续上升,以供未来防洪设计之用。估算了各站汛期。研究了Chaophraya河上游洪水频率的新分布和适宜的估计技术——指数Kumaraswamy fr分布和差分演化极大似然估计。我们推导出fr契特族的性质;如fr 分布(EV2)、Kumaraswamy fr分布(KF)和指数Kumaraswamy fr分布(EKF)。通过生成fr切特族随机数,我们还比较了每个分布中所有参数的偏差、方差、均方误差和平均绝对百分比误差。为了保证参数解析解的有效性,我们利用Scilab程序提供了数值解(差分进化法)来获得所有参数的估计。极端事件洪水评估的准确性对许多安全、工程和金融应用具有重要意义。在部分应用中,我们提供了泰国Chaophraya河上游流域年最大洪峰或瞬时洪峰数据的概率估计。采用广义极值(GEV)分布模型与fr 的)分布(EV2)、Kumaraswamy fr的分布(KF)和指数Kumaraswamy fr的分布(EKF)进行比较。进行拟合优度检验、回归水平检验和回归期检验。利用GEV对洪水的重现期进行灾害等级划分,发现Chaophraya河上游流域发生洪水较多。fr切特家族的结果也很高,但Kumaraswamy fr切特分布(KF)的返回周期和返回水平比其他分布更接近GEV。
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