Attribution Analysis of Hydrological Drought Risk Under Climate Change and Human Activities: A Case Study on Kuye River Basin in China

被引:4
|
作者
Zhang, Ming [1 ]
Wang, Jinpeng [1 ]
Zhou, Runjuan [1 ]
机构
[1] Anhui Polytech Univ, Sch Civil Engn, Wuhu 241000, Peoples R China
基金
中国国家自然科学基金;
关键词
drought risk; climate change; human activities; quantitative attribution; artificial neural network; VIRTUAL WATER-FLOW; NEURAL-NETWORKS; GRAIN TRADE; PRECIPITATION; VARIABLES; PREDICTION; STREAMFLOW; SYSTEMS; RUNOFF; IMPACT;
D O I
10.3390/w11101958
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study conducted quantitative diagnosis on the impact of climate change and human activities on drought risk. Taking the Kuye river basin (KRB) in China as the research area, we used variation point diagnosis, simulation of precipitation and runoff, drought risk assessment, and attribution quantification. The results show that: (1) the annual runoff sequence of KRB changed significantly after 1979, which was consistent with the introduction of large-scale coal mining; (2) under the same drought recurrence period, the drought duration and severity in the human activity stage were significantly worse than in the natural and simulation stages, indicating that human activities changed the drought risk in this area; and (3) human activities had little impact on drought severity in the short duration and low recurrence period, but had a greater impact in the long duration and high recurrence period. These results provide scientific guidance for the management, prevention, and resistance of drought; and guarantee sustainable economic and social development in the KRB.
引用
收藏
页数:14
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