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A copula‐based index for drought analysis in arid and semi‐arid regions of Iran
Natural Resource Modeling ( IF 1.6 ) Pub Date : 2019-08-08 , DOI: 10.1111/nrm.12237
Ommolbanin Bazrafshan 1 , Hossein Zamani 2 , Marzieh Shekari 2
Affiliation  

The copula functions are frequently used by researchers for modeling dependence structure among the correlated attributes in many areas. The copulas are widely used for the analysis of drought frequency, drought characteristics, drought coincidence risk, uncertainty, and drought forecasting. In this research, we have compared two indices of drought assessment, including SPI‐12 and copula‐based joint deficit index (JDI). In this regard, the drought characteristics, including the severity, duration, and drought frequency have been studied in 25 synoptic stations of Iran during the 1968–2014. The results showed that, unlike JDI, the SPI‐12 is not able to estimate the drought peak during the critical and extreme condition. Although JDI has identified a severe and extreme drought during the pervasive drought, the SPI‐12 estimated a normal condition. The results show that JDI accurately estimates the drought frequency, but the SPI‐12 provided an unexpected estimation is some stations. In addition, the MannKendal trend test for drought characteristics represents that JDI accurately estimates the expected trend (an increasing trend) whereas the SPI‐12 exhibits no significant trend in most stations. Finally, JDI provides a comprehensive assessment of drought for decision‐makers and natural managers.

中文翻译:

基于copula的伊朗干旱和半干旱地区的干旱分析指数

研究人员经常使用copula函数来建模许多领域中相关属性之间的依赖结构。copulas被广泛用于分析干旱频率,干旱特征,干旱重合风险,不确定性和干旱预报。在这项研究中,我们比较了两个干旱评估指数,包括SPI-12和基于copula的联合赤字指数(JDI)。在这方面,在1968-2014年期间,对伊朗的25个天气站进行了干旱特征研究,包括严重程度,持续时间和干旱频率。结果表明,与JDI不同,SPI-12无法估计关键和极端条件下的干旱峰值。尽管JDI在普遍干旱期间确定了严重和极端干旱,但SPI-12估计情况正常。结果表明,JDI可以准确估算干旱频率,但是SPI-12提供了一些站点意外的估算值。此外,MannKendal干旱特征趋势测试表明,JDI可以准确估算出预期趋势(呈上升趋势),而SPI-12在大多数站点中都没有显着趋势。最后,JDI为决策者和自然管理者提供了全面的干旱评估。
更新日期:2019-08-08
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