Copula based analysis of meteorological drought and catchment resilience across Indian river basins,International Journal of Climatology

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Copula based analysis of meteorological drought and catchment resilience across Indian river basins
International Journal of Climatology ( IF 3.5 ) Pub Date : 2020-07-20 , DOI: 10.1002/joc.6758
Vibhuti Bhushan Jha ₁ , Ashwin Gujrati ₁ , R P Singh ₁

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Drought analysis is an important part of risk management plan. Drought is usually characterized by variables such as severity and duration. Using standardized precipitation index (SPI) at an aggregated scale of 12 months, we construct different copula models for different river basins of India. Based on goodness of fit tests, suitable distributions are selected for duration and severity. These marginal distributions are then used to construct copula models from amongst‐Frank, Gumbel, Clayton and Student's t copula. It is found that for some river basins Frank copula can capture the dependence structure between duration and severity whereas for others Gumbel copula is effective. Exceedance probability, conditional probability and joint return period of different drought events are calculated which allude to differing drought resilience and persistence conditions in river basins. The river basins in the western India have a longer joint return period and smaller exceedance probability compared to the river basins in south India. We explore the conjunctive use for joint return period and exceedance probability to qualitatively assess the resilience of river basins to meteorological drought. The results suggest that the drought events in the south Indian river basins are less severe and more frequent whereas the ones in Central and Western India are severe and longer. The results of this study can provide useful information for drought mitigation strategies at a national scale.

中文翻译：

基于Copula的印度河流域气象干旱和集水能力分析

干旱分析是风险管理计划的重要组成部分。干旱通常以严重程度和持续时间等变量为特征。使用总计12个月的标准降水指数（SPI），我们为印度不同的流域构建了不同的copula模型。基于拟合优度的检验，为持续时间和严重程度选择合适的分布。这些边际分布然后被用来从弗兰克，古姆贝尔，克莱顿和学生的t中建立copula模型。系词。结果发现，对于某些流域，弗兰克·科珀拉（Frank copula）可以捕获持续时间和严重性之间的依存关系，而对于其他流域，古姆贝尔·科珀拉（Gumbel copula）是有效的。计算了不同干旱事件的超额概率，条件概率和联合回归期，这暗示了流域不同的干旱复原力和持续条件。与印度南部的流域相比，印度西部的流域具有更长的联合返还期，并且超出概率较小。我们探索联合返回期和超出概率的联合使用，以定性评估流域对气象干旱的适应力。结果表明，印度南部河流域的干旱事件较轻且更为频繁，而印度中部和西部的干旱事件则更为严重且持续时间较长。这项研究的结果可以为全国范围内的干旱缓解策略提供有用的信息。

更新日期：2020-07-20

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