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Regional risk analysis and derivation of copula-based drought for severity-duration curve in arid and semi-arid regions
Theoretical and Applied Climatology ( IF 2.8 ) Pub Date : 2020-05-17 , DOI: 10.1007/s00704-020-03217-0
Ommolbanin Bazrafshan , Hossein Zamani , Marzieh Shekari , Vijay P. Singh

This study investigated droughts in arid and semi-arid regions in Iran using long historical data from 25 stations. These stations were clustered into three homogeneous regions using a fuzzy clustering method. The severity and duration were extracted using the Standardized Precipitation Index-12, and the dependence structure between drought severity and duration was evaluated using Pearson’s, Spearman’s ranked, and Kendal’s tau correlation coefficients. The best marginal distributions of severity and duration were selected using graphical and theoretical goodness-of-fit criteria. Results showed that the generalized logistic (GLO) model satisfactorily fitted drought duration in regions I and III, while the Wakeby distribution fitted better in region II. For drought severity, the best fitted model was the GLO model in region I, the generalized extreme value (GEV) model in region III, and the Wakeby model in region II. Furthermore, the Gumbel copula in region I and the Gaussian copulas in regions II and III were able to model the dependence between drought variables well. Also, stochastic simulation of bivariate drought using selected copulas showed that the behavior of bivariate drought changed when the degree of correlation between variables was considered. The copula method was used to obtain bivariate and conditional return periods. The bivariate analysis of drought risk indicated that coastal and internal regions of Iran were more risky than semi-arid and arid regions. The results of this study would be useful for water resource management and risk analysis at the regional scale.



中文翻译:

干旱和半干旱地区严重度-持续时间曲线的基于copula的干旱区域风险分析和推导

这项研究使用来自25个气象站的长期历史数据调查了伊朗干旱和半干旱地区的干旱。使用模糊聚类方法将这些站点聚类为三个同质区域。使用标准降水指数12提取严重程度和持续时间,并使用Pearson,Spearman等级和Kendal的tau相关系数评估干旱严重程度和持续时间之间的依赖关系。使用图形和理论拟合优度标准选择严重程度和持续时间的最佳边际分布。结果表明,广义逻辑模型(GLO)令人满意地拟合了I区和III区的干旱持续时间,而Wakeby分布在II区更合适。对于干旱严重程度,最佳拟合模型是I区的GLO模型,区域III中的广义极值(GEV)模型和区域II中的Wakeby模型。此外,I区的Gumbel copula和II区和III区的Gaussian copula能够很好地模拟干旱变量之间的相关性。同样,使用选定的copulas对双变量干旱进行随机模拟显示,当考虑变量之间的相关程度时,双变量干旱的行为会发生变化。copula方法用于获得双变量和条件返回期。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。I区的Gumbel copula和II区和III区的Gaussian copula能够很好地模拟干旱变量之间的相关性。同样,使用选定的copulas对双变量干旱进行随机模拟显示,当考虑变量之间的相关程度时,双变量干旱的行为会发生变化。copula方法用于获得双变量和条件返回期。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。I区的Gumbel copula和II区和III区的Gaussian copula能够很好地模拟干旱变量之间的相关性。同样,使用选定的copulas对双变量干旱进行随机模拟显示,当考虑变量之间的相关程度时,双变量干旱的行为会发生变化。copula方法用于获得双变量和条件返回期。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。使用选择的copulas随机模拟双变量干旱表明,当考虑变量之间的相关程度时,双变量干旱的行为发生了变化。copula方法用于获得双变量和条件返回期。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。使用选择的copulas随机模拟双变量干旱表明,当考虑变量之间的相关程度时,双变量干旱的行为发生了变化。copula方法用于获得双变量和条件返回期。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。对干旱风险的二元分析表明,伊朗的沿海和内陆地区比半干旱和干旱地区的风险更高。这项研究的结果将对区域范围的水资源管理和风险分析有用。

更新日期:2020-05-17
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