关键词: copula function drought risk meteorological drought run theory

Mesh : Droughts China Tibet Rivers

来  源:   DOI:10.3390/ijerph20054074   PDF(Pubmed)

Abstract:
Droughts are widespread in China and have brought considerable losses to the economy and society. Droughts are intricate, stochastic processes with multi-attributes (e.g., duration, severity, intensity, and return period). However, most drought assessments tend to focus on univariate drought characteristics, which are inadequate to describe the intrinsic characteristics of droughts due to the existence of correlations between drought attributes. In this study, we employed the standardized precipitation index to identify drought events using China\'s monthly gridded precipitation dataset from 1961 to 2020. Univariate and copula-based bivariate methods were then used to examine drought duration and severity on 3-, 6-, and 12-month time scales. Finally, we used the hierarchical cluster method to identify drought-prone regions in mainland China at various return periods. Results revealed that time scale played an essential role in the spatial heterogeneity of drought behaviors, such as average characteristics, joint probability, and risk regionalization. The main findings were as follows: (1) 3- and 6-month time scales yielded comparable regional drought features, but not 12-month time scales; (2) higher drought severity was associated with longer drought duration; (3) drought risk was higher in the northern Xinjiang, western Qinghai, southern Tibet, southwest China, and the middle and lower reaches of the Yangtze River, and lower in the southeastern coastal areas of China, the Changbai Mountains, and the Greater Khingan Mountains; (4) mainland China was divided into six subregions according to joint probabilities of drought duration and severity. Our study is expected to contribute to better drought risk assessment in mainland China.
摘要:
干旱在中国普遍存在,给经济和社会带来了相当大的损失。干旱错综复杂,具有多属性的随机过程(例如,持续时间,严重程度,强度,和返回期)。然而,大多数干旱评估倾向于关注单变量干旱特征,由于干旱属性之间存在相关性,因此不足以描述干旱的内在特征。在这项研究中,我们采用标准化降水指数,利用中国1961年至2020年的月度降水数据集识别干旱事件。然后使用单变量和基于copula的双变量方法来检查3-的干旱持续时间和严重程度,6-,和12个月的时间尺度。最后,我们使用层次聚类方法来识别中国大陆在不同重现期的干旱易发地区。结果表明,时间尺度在干旱行为的空间异质性中起着至关重要的作用。如平均特征,联合概率,和风险区域化。主要研究结果如下:(1)3个月和6个月时间尺度具有可比性的区域干旱特征,但不是12个月的时间尺度;(2)干旱严重程度越高,干旱持续时间越长;(3)新疆北部干旱风险越高,青海西部,西藏南部,中国西南,和长江中下游,在中国东南沿海地区较低,长白山,和大兴安岭;(4)根据干旱持续时间和严重程度的联合概率,中国大陆分为六个分区。我们的研究有望有助于更好地评估中国大陆的干旱风险。
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