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  The recent trends of runoff in China attributable to climate change

Sun, H., Krysanova, V., Gong, Y., Gao, M., Treu, S., Chen, Z., Jiang, T. (2024): The recent trends of runoff in China attributable to climate change. - Climatic Change, 177, 159.
https://doi.org/10.1007/s10584-024-03803-5

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 Creators:
Sun, Hemin1, Author
Krysanova, Valentina2, Author              
Gong, Yu1, Author
Gao, Miaoni1, Author
Treu, Simon2, Author              
Chen, Ziyan1, Author
Jiang, Tong1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Against the background of global warming, the losses caused by hydrological extreme events are becoming more serious. Understanding how to quantitatively attribute the trends of river discharge and extreme events will play an important role in climate change adaptation. The main objective of this study is to analyze recent trends in river discharge and annual maximum daily runoff in Chinese catchments and attribute them to the ongoing climate change, where possible. For that, 20 catchments in China, which are not influenced or influenced only slightly by water management, are chosen as study areas. Then, we use the long-term observational climate dataset GSWP3-W5E5 from ISIMIP3a as factual climate and a detrended climate dataset based on it as counterfactual climate to drive the hydrological model for quantification of climate change contribution to trends in mean and extreme runoff. Our analysis shows that the trends in annual discharge over the period 1961–2019 in eight catchments (all located in western China) represented by five stations in the Upper Yellow and Upper Yangtze, Kaqun station in the Tarim-Yeerqiang, Changdu station in the Lancangjiang and Xindi station in the Heihe can be attributed to climate change. As well, it is shown that climate change enhanced annual maximum daily runoff in the Upper Yellow and Upper Yangtze River basins. The results provide a new understanding of the degree to which observed changes in mean and extreme runoff were induced by the observed changes in climate, which may improve adaptation to climate change in China.

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Language(s): eng - English
 Dates: 2023-01-162024-08-282024-10-172024-10-17
 Publication Status: Finally published
 Pages: 19
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s10584-024-03803-5
Organisational keyword: RD3 - Transformation Pathways
PIKDOMAIN: RD3 - Transformation Pathways
Working Group: Data-Centric Modeling of Cross-Sectoral Impacts
MDB-ID: No data to archive
Model / method: Quantitative Methods
Regional keyword: Asia
Research topic keyword: Extremes
Research topic keyword: Ecosystems
Research topic keyword: Climate impacts
 Degree: -

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Title: Climatic Change
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 177 Sequence Number: 159 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals80
Publisher: Springer