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Abstract：
This study delves into analyzing drought patterns in Baluchistan by applying copula-based bivariate probabilistic models complemented by Severity Duration Frequency (SDF) curves. The calculation of the Standardized Precipitation Index (SPI) hinges on monthly aggregate precipitation data from ten distinct sites compiled over six-month periods. After evaluating various parametric distributions, the Log-Normal distribution emerges as suitable for modeling drought severity and duration. A range of bivariate copulas is employed to simulate the characteristics of drought severity and duration, which are then compared against observed data. Remarkably, the Gumbel copula classified as an extreme value copula-outperforms its counterparts according to diverse statistical benchmarks. By utilizing the dependence function, we derive the conditional distribution of drought variables: severity and duration. These conditional distributions subsequently inform the calculation of return periods, forming the basis for constructing SDF diagrams at fixed recurrence levels across the study region. The study\'s finding indicates that a severe drought could occur over the region with higher return periods for a specific duration. The implications of this research are significant, showcasing the potential of copula-based joint modeling techniques to generate frequency curves for drought severity and duration. This development holds promise for effective water resource management and the formulation of strategies to mitigate the impact of drought in vulnerable regions.
摘要：
本研究通过应用基于copula的双变量概率模型以及严重程度持续时间频率（SDF）曲线来分析Bal路支斯坦的干旱模式。标准化降水指数（SPI）的计算取决于六个月内从十个不同地点收集的每月总降水数据。在评估各种参数分布之后，对数正态分布适用于模拟干旱严重程度和持续时间。采用一系列双变量copulas来模拟干旱严重程度和持续时间的特征，然后将其与观察到的数据进行比较。值得注意的是,根据不同的统计基准，将Gumbelcopula分类为极值copula的表现优于其对应物。通过利用依赖函数，我们得出干旱变量的条件分布：严重程度和持续时间。这些条件分布随后为计算返回期提供信息，形成在整个研究区域以固定复发水平构建SDF图的基础。该研究的发现表明，在特定持续时间内，该地区可能会发生严重干旱，重现期较高。这项研究的意义重大，展示了基于copula的联合建模技术在生成干旱严重程度和持续时间的频率曲线方面的潜力。这一发展为有效的水资源管理和制定战略以减轻干旱对脆弱地区的影响提供了希望。
