Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Xiaoyan Zhai
China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Jun Xia
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Wei Wang
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Jian Wu
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Xiaoyu Niu
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Bing Han
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
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Total article views: 2,223 (including HTML, PDF, and XML)
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Total article views: 814 (including HTML, PDF, and XML)
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It is challenging to investigate flood variabilities and their formation mechanisms from massive event samples. This study explores spatiotemporal variabilities of 1446 flood events using hierarchical and partitional clustering methods. Control mechanisms of meteorological and physio-geographical factors are explored for individual flood event classes using constrained rank analysis. This gives insights into comprehensive changes in flood events and aids in flood prediction and control.
It is challenging to investigate flood variabilities and their formation mechanisms from massive...