Identifying Reservoir-Induced Hydrological Alterations in the Upper Yangtze River Basin through Statistical and Modeling Approaches
Hanqi Liu,
Tingting Wang,
Yao Feng,
Fa Liu,
Ning Wang,
Hong Wang,
Wenbin Liu,
Fubao Sun
Affiliations
Hanqi Liu
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
Tingting 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
Yao Feng
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
Fa Liu
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
Ning Wang
National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Hong 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
Wenbin Liu
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
Fubao Sun
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
Elucidating the impact of reservoir operation on hydrological signatures is crucial for the effective management of large rivers under the changing climate. This study first revised the reservoir operation scheme in the Soil and Water Assessment Tool (SWAT) model to improve its description of actual operation laws of reservoirs in the upper Yangtze River basin (UYRB). Then, we identified the reservoir-induced hydrological alteration through a hydrological index method driven by observed and simulated daily streamflow from 1960 to 2017. The results revealed the superiority of the revised reservoir algorithm in the SWAT model in simulating streamflow and floods at Cuntan and Yichang stations with the Nash-Sutcliffe efficiency (NSE) coefficient and the Kling-Gupta efficiency (KGE) coefficient improved from 0.01 to 0.08 and 0.01 to 0.05, respectively. Relative to the baseline period (1960–2002), the hydrological signatures in the impact period (2003–2017) changed substantially after 2003. Reservoirs induced a remarkable increase of 27.76% and 55.97% in streamflow from January to March, accompanied by a notable decrease of 6.95% and 20.92% in streamflow from September to October after 2003 at Cuntan and Yichang stations, respectively. Meanwhile, the annual streamflow range contracted, and the flow became more stable with a reduced variation in daily streamflow, extremely low flow spell duration, and extremely high flow spell duration. Consequently, our results improved the quantitative understanding of reservoir-induced alteration and informed the management and planning of reservoir construction in the UYRB under climate change.