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Nonstationary Flood Frequency Analysis for Annual Flood Peak and Volume Series in Both Univariate and Bivariate Domain

机译：单变量和双变量域中年度洪水峰值和流量序列的非平稳洪水频率分析

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摘要

Flood frequency analysis for practical application is traditionally based on the assumption of stationarity, but this assumption has been open to doubt in recent years. A number of studies have focused on the nonstationary flood frequency analysis, and the associated causes of nonstationarity. In this study, the annual maximum flood peak and flood volume of Wangkuai reservoir watershed were used, and several univariate and bivariate models were established to investigate the nonstationary flood frequency, with the distribution parameters changing over the climate indices (NPO, Nino3) and the check dam indices (CDIp, CDIv). In the univariate models, the Weibull distribution performed best and exhibited an undulate behavior for both flood peak and volume, which tended to describe the nonstationarity reasonably well. The bivariate models were constructed using copulas, of which the optimal Weibull distribution in the univariate flood frequency analysis was considered as marginal distributions within the joint distribution. The results showed that the Gumbel-Hougaard copula offered the best joint distribution, and most of the probability isolines crossed each other, which demonstrated the possibility that the occurrence of combinations of the flood peak and volume may be the same under multiple effects of phase changes in the climate patterns and certain human activities (i.e. soil and water conservation). The most likely events were elaborated in diagrams, and the associated combinations of the flood peak and volume were smaller than that estimated by the fixed parameters (i.e. stationary condition) during most of the study period, while it was the opposite in 1956, 1959 and 1963. The result highlight the necessity of nonstationary flood frequency analysis under various conditions in both univariate and multivariate domains.
机译：实际应用中的洪水频率分析传统上是基于平稳性的假设，但是近年来这种假设一直令人怀疑。大量研究集中在非平稳洪水频率分析以及非平稳洪水的相关原因上。本研究利用旺快水库集水区的年最大洪峰和洪量，建立了几个单变量和双变量模型来研究非平稳洪水频率，其分布参数随气候指数（NPO，Nino3）和水位的变化而变化。检查水坝指数（CDIp，CDIv）。在单变量模型中，威布尔分布表现最佳，并且在洪峰和洪量方面都表现出起伏的行为，这往往可以很好地描述非平稳性。使用copulas建立双变量模型，其中单变量洪水频率分析中的最佳威布尔分布被视为联合分布内的边际分布。结果表明，Gumbel-Hougaard copula提供了最佳的联合分布，并且大多数等值线相互交叉，这表明在相变的多种影响下，洪峰和洪峰组合的发生可能相同气候模式和某些人类活动（即水土保持）。在图表中详细说明了最可能发生的事件，在大部分研究期间，洪水峰值和洪水量的相关组合均小于固定参数（即静止状态）所估计的组合，而在1956年，1959年和2007年则相反。 1963年。结果强调了在单变量和多变量域中各种条件下进行非平稳洪水频率分析的必要性。

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  • 来源
    《Water Resources Management》 |2018年第13期|4239-4252|共14页
  • 作者

    Li Jianzhu; Lei Yuming; Tan Senming; Bell Colin D.; Engel Bernard A.; Wang Yixuan;

  • 作者单位

    Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China;

    Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China;

    Minist Water Resources, Pearl River Comprehens Technol Ctr, Informat Ctr, Pearl River Water Resources Commiss, Guangzhou 510611, Guangdong, Peoples R China;

    Purdue Univ, Dept Agr & Biol Engn, 225 S Univ St, W Lafayette, IN 47907 USA;

    Purdue Univ, Dept Agr & Biol Engn, 225 S Univ St, W Lafayette, IN 47907 USA;

    Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Nonstationarity; Univariate model; GAMLSS; Bivariate model; Copulas;

    机译：非平稳性;单变量模型;GAMLSS;双变量模型;Copulas;

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