River Hydrological Regime Changes and Their Attribution: A Case Study in the Upper Reaches of the Yangtze River Using a Multi‐Model Approach

ABSTRACT A comprehensive quantitative evaluation framework was used to analyze the driving factors affecting the hydrological conditions and runoff changes in the upper Yangtze River basin across multiple time scales (annual, seasonal, and monthly). This study focuses on utilizing the LSTM model and the WEP‐L model for the quantitative assessment of factors influencing runoff changes. Additionally, we calculated the IHA indicators for actual runoff and the LSTM model‐simulated runoff and conducted a comparative analysis using the range of variability approach (RVA) to study changes in the overall hydrological regime of the river. Following an abrupt change, the runoff in the upper reaches of the Yangtze River decreased by 6.6%, and the ecological response of the basin showed a negative trend, as reflected in the changes of five sets of hydrological‐ecological indicators. The contributions of various driving forces exhibited significant differences across different time scales. On an annual scale, the LSTM model indicated that runoff was predominantly influenced by human activities with a contribution rate of 55%, whereas the WEP‐L model indicated that climate factors were the dominant influence, with a contribution rate of 75%. On a seasonal scale, the WEP‐L model showed that runoff was more influenced by climate in summer and autumn, with relative contribution rates of 68% and 73%, respectively. Conversely, the LSTM model showed that runoff was more influenced by human activities in summer and winter, with relative contribution rates of 98% and 91%, respectively. On a monthly scale, the situation was more complex. The LSTM model results indicated significant contributions from human activities in May, July, October, and November (76%, 68%, 69%, and 87%, respectively) and slightly higher contributions than climate factors in February and September (51% and 57%, respectively). In the remaining months (13%–95%), climate factors were the primary driving force. The WEP‐L model results indicated significant contributions from land‐use changes in January, February, and May (79%, 74%, and 80%, respectively) and slightly higher contributions than climate factors in December (57%), with climate factors being the primary driving force in the remaining months (20%–92%). The findings of this study provide valuable insights for the ecological protection and restoration of the upper Yangtze River basin.

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Publication Details

Journal
River Research and Applications
Published
2024-10-02
DOI
https://doi.org/10.1002/rra.4377
Citations
3
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
0.60

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article

River Hydrological Regime Changes and Their Attribution: A Case Study in the Upper Reaches of the Yangtze River Using a Multi‐Model Approach

Gaozhen Wang, Xuyang Jiao, Ning He, Hongxiang Wang et al.
3 citations
River Research and Applications
Hydrology and Watershed Management Studies
0.60
article

River Hydrological Regime Changes and Their Attribution: A Case Study in the Upper Reaches of the Yangtze River Using a Multi‐Model Approach

Gaozhen Wang, Xuyang Jiao, Ning He, Hongxiang Wang, Chaohui Sun, Wenxian Guo, Handong Ye, Jiaqi Lan
article en
3 citations

Abstract

ABSTRACT A comprehensive quantitative evaluation framework was used to analyze the driving factors affecting the hydrological conditions and runoff changes in the upper Yangtze River basin across multiple time scales (annual, seasonal, and monthly). This study focuses on utilizing the LSTM model and the WEP‐L model for the quantitative assessment of factors influencing runoff changes. Additionally, we calculated the IHA indicators for actual runoff and the LSTM model‐simulated runoff and conducted a comparative analysis using the range of variability approach (RVA) to study changes in the overall hydrological regime of the river. Following an abrupt change, the runoff in the upper reaches of the Yangtze River decreased by 6.6%, and the ecological response of the basin showed a negative trend, as reflected in the changes of five sets of hydrological‐ecological indicators. The contributions of various driving forces exhibited significant differences across different time scales. On an annual scale, the LSTM model indicated that runoff was predominantly influenced by human activities with a contribution rate of 55%, whereas the WEP‐L model indicated that climate factors were the dominant influence, with a contribution rate of 75%. On a seasonal scale, the WEP‐L model showed that runoff was more influenced by climate in summer and autumn, with relative contribution rates of 68% and 73%, respectively. Conversely, the LSTM model showed that runoff was more influenced by human activities in summer and winter, with relative contribution rates of 98% and 91%, respectively. On a monthly scale, the situation was more complex. The LSTM model results indicated significant contributions from human activities in May, July, October, and November (76%, 68%, 69%, and 87%, respectively) and slightly higher contributions than climate factors in February and September (51% and 57%, respectively). In the remaining months (13%–95%), climate factors were the primary driving force. The WEP‐L model results indicated significant contributions from land‐use changes in January, February, and May (79%, 74%, and 80%, respectively) and slightly higher contributions than climate factors in December (57%), with climate factors being the primary driving force in the remaining months (20%–92%). The findings of this study provide valuable insights for the ecological protection and restoration of the upper Yangtze River basin.

River Research and ApplicationsVol. 41(2)
North China University of Water Resources and Electric Power (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 33%
Hydrology and Watershed Management Studies
0.60
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