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Copula-based Drought Severity-Area-Frequency Analysis in Western Rajasthan, India

机译:基于Copula的干旱严重程度区频率分析在印度拉贾斯坦邦

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Extreme hydrological events such as droughts can cause substantial damage to society and ecosystem. Droughts can be characterized by severity, duration, spatial extent and frequency of occurrences. In this study gridded (0.5° latitude * 0.5° longitude) daily precipitation data for the year 1971-2005 from Western Rajasthan meteorological subdivision of India are used to develop monthly time series of Standardized Precipitation Index (SPI). The drought conditions are identified based on SPI percentile value of 20% or below for each grid point in the study domain. The spatial identification of drought is based on spatial contiguity of SPI values aggregated at a time scale of six months (SPI 6) at each pixel. Drought severity is assessed from spatialmean SPI value of drought cluster identified at successive monthly time scale. It is found that drought severity and spatial extent is negatively correlated with each other. The drought severity is best described by generalized extreme value distributionand spatial extent using log normal distribution. The joint distribution of drought severity and spatial extent are modeled using bivariate Plackett and Archimedean class of Frank copulas. Standard goodness-of-fit test suggests that Plackett copula as amore suitable model. The copula based joint distribution of drought severity and spatial extent is employed to derive conditional return period, which in turn is used to derive drought severity-area-frequency (SAF) curves. The results of the study can be useful in water resources planning in drought affected areas and for deciding drought management policies.
机译:诸如干旱等极端水文事件可能对社会和生态系统造成重大损害。干旱可以以严重性,持续时间,空间范围和出现频率为特征。在本研究中,来自印度的西拉贾斯坦国气象细分的1971 - 2005年的每日降水数据用于开发标准化降水指数(SPI)的月度时间序列。基于研究领域的每个网格点的SPI百分位值鉴定干旱条件。干旱的空间识别基于每个像素在六个月(SPI 6)的时间等级聚合的SPI值的空间邻接。从连续每月时间尺度识别的干旱群集的SpatialMean SPI值评估干旱严重程度。发现干旱严重程度和空间程度彼此负相关。通过使用日志正态分布,通过概括的极值分布和空间范围最佳地描述了干旱严重性。干旱严重程度和空间范围的联合分布是使用一体的普氏素和Archimedean类的弗兰克共克拉斯建模的。标准的健康测试表明,Plackett Copula作为Amore合适的模型。采用干旱严重程度和空间范围的基于拷贝的联合分布,以导出条件返回期,这反过来用于导出干旱严重程度区频率(SAF)曲线。该研究的结果可用于干旱受影响地区的水资源规划,并决定干旱管理政策。

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