A multiscale attribution framework for separating the effects of cascade and individual reservoirs on runoff

Yongsheng Jie; Hui Qin; Benjun Jia; Mengqi Tian; Sijing Lou; Guanjun Liu; Yuanjian Huang

doi:10.1016/j.scitotenv.2024.172784

A multiscale attribution framework for separating the effects of cascade and individual reservoirs on runoff

Sci Total Environ. 2024 Apr 26:172784. doi: 10.1016/j.scitotenv.2024.172784. Online ahead of print.

Authors

Yongsheng Jie¹, Hui Qin², Benjun Jia³, Mengqi Tian⁴, Sijing Lou¹, Guanjun Liu¹, Yuanjian Huang¹

Affiliations

¹ School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Hubei Key Laboratory of Digital River Basin Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China; Institute of Water Resources and Hydropower, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
² School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Hubei Key Laboratory of Digital River Basin Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China; Institute of Water Resources and Hydropower, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China. Electronic address: hqin@hust.edu.cn.
³ Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co., Ltd., Yichang 443000, China.
⁴ Yellow River Conservancy Technical Institute, Kaifeng 475004, China; Henan Engineering Technology Center for Water Resources Conservation and Utilization in the Middle and Lower Reaches of Yellow River, Kaifeng 475004, China.

PMID: 38679101
DOI: 10.1016/j.scitotenv.2024.172784

Abstract

Climate change and human activities have great impacts on runoff. With the gradual development of cascade hydropower in the watershed, the reservoirs have increasingly impacted runoff. However, the current study mainly focuses on quantifying the impacts of human activities and climate change on runoff, lacking the exploration of the impacts of cascade reservoirs, and the attribution results are relatively rough. Therefore, this study utilized data-driven models to establish a runoff attribution framework with the basic steps of "interval runoff prediction and scheduling rule extraction", which achieved the spatial scale separation of the impacts of cascade and individual reservoirs on the runoff, and the analysis of the impacts of each factor at multiple time scales. Taking the upper reaches of the Yangtze River mainstem as an example, we verified the applicability and accuracy of the framework, explored the impacts of climate change, human activities (without reservoir scheduling), and reservoir scheduling on runoff during the period 1980-2018. The research found: (1) Compared to the base period 1980-2005, the average multi-year runoff changes at Pingshan Station (during 2013-2018), Yichang Station (during 2006-2012) and Yichang Station (during 2013-2018) were - 2.61 %, -4.33 % and - 0.89 %, respectively, with decreasing, increasing, and flattening trends over time. (2) Reservoir scheduling is the main factor leading to runoff change, showing negative impacts during flood season and positive impacts during non-flood season. (3) Under the control domain of single and cascade reservoirs, the annual scale impacts of climate change, human activities, and reservoir scheduling on runoff accounted for approximately 1:1:8 and 2:2:6, respectively, showing a complex nonlinear relationship between the impacts of single and cascade reservoirs on runoff. This study provides ideas for quantitatively assessing the impacts of cascade reservoirs on runoff and provide a basis for comprehensively assessing the ecosystem and socio-economic impacts of reservoirs on future runoff changes.

Keywords: Data-driven model; Reservoir impacts; Runoff attribution; Runoff changes.