The Value of Hydrologic Information in Reservoir Outflow Decision-Making

被引:7
作者
Chen, Kebing [1 ]
Guo, Shenglian [1 ]
He, Shaokun [1 ]
Xu, Tao [2 ]
Zhong, Yixuan [1 ]
Sun, Sirui [3 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China
[2] China Yangtze Power Co Ltd, Yichang 443133, Peoples R China
[3] Middle Changjiang River Bur Hydrol & Water Resour, Wuhan 430012, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
reservoir operations; hydrologic information; data mining; random forests; decision-making; three gorges reservoir; CASCADE HYDROPOWER STATIONS; OPTIMAL OPERATION; 3; GORGES; FLOOD; LAKE; PREDICTION; 3-GORGE; SYSTEM; RULES;
D O I
10.3390/w10101372
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The controlled outflows from a reservoir are highly dependent on the decisions made by the reservoir operators who mainly rely on available hydrologic information, such as past outflows, reservoir water level and forecasted inflows. In this study, Random Forests (RF) algorithm is used to build reservoir outflow simulation model to evaluate the value of hydrologic information. The Three Gorges Reservoir (TGR) in China is selected as a case study. As input variables of the model, the classic hydrologic information is divided into past, current and future information. Several different simulation models are established based on the combinations of these three groups of information. The influences and value of hydrologic information on reservoir outflow decision-making are evaluated from two different perspectives, the one is the simulation result of different models and the other is the importance ranking of the input variables in RF algorithm. Simulation results demonstrate that the proposed model is able to reasonably simulate outflow decisions of TGR. It is shown that past outflow is the most important information and the forecasted inflows are more important in the flood season than in the non-flood season for reservoir operation decision-making.
引用
收藏
页数:15
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