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Li X, Cui P, Zhang X, Hao J, Li C, Du X. Recent decreasing precipitation and snowmelt reduce the floods around the Chinese Tianshan Mountains. Sci Total Environ 2023; 905:167324. [PMID: 37748598 DOI: 10.1016/j.scitotenv.2023.167324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 08/03/2023] [Accepted: 09/22/2023] [Indexed: 09/27/2023]
Abstract
Understanding and managing mountain floods has become increasingly urgent, with global climate change and human activities exacerbating flood risk. However, flood research in Tianshan Mountains, a typical flood-prone mountainous region in China, is still insufficient. Here, we customized a set of flood research methods based on rainstorms and extreme snowmelt events, including a new flood counting method that comprehensively considered the frequency and magnitude of floods and the methods of flood classification and change attribution. We found that floods around the Chinese Tianshan Mountains (CTM) increased from 2014 to 2016 but decreased rapidly from 2016 to 2021, with storm floods, snowmelt floods, and mixed floods accounting for 38.3 %, 26.5 %, and 34.6 % of total flood events, respectively. The variation of floods was most significantly correlated with the average and extreme precipitation, followed by the temperature-driven average snowmelt change. Furthermore, atmospheric circulation anomalies and water vapor input from the western boundary of CTM caused decreasing precipitation and storm floods. Meanwhile, the warming hiatus also greatly impacted declining flood frequency. Notably, flood frequency is projected to rebound soon because of the rising precipitation and temperature, infrastructure aging, and reservoir abandonment, implying the present flood decline unsustainable. Our research develops a strategy to investigate short-term flood anomalies under climate oscillations around the CTM, providing insights into flood research and prevention in global mountainous regions.
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Affiliation(s)
- Xiang Li
- Key Lab of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, 11A, Datun Road, Beijing 100101, China; University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China
| | - Peng Cui
- Key Lab of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, 11A, Datun Road, Beijing 100101, China; China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission, Islamabad 45320, Pakistan
| | - Xueqin Zhang
- Key Lab of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, 11A, Datun Road, Beijing 100101, China.
| | - Jiansheng Hao
- Key Lab of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, 11A, Datun Road, Beijing 100101, China
| | - Chaoyue Li
- Key Lab of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, 11A, Datun Road, Beijing 100101, China; University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China
| | - Xinguan Du
- School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
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