An inter-basin water transfer project is one of the effective ways to resolve the problem of an uneven distribution of water resources. Temporal and spatial variations in rainfall in different basins greatly affect water supply and demand in inter-basin water transfer projects, leading to risks to the operation of the water transfer projects. This paper applies a Bayesian network model to analyze this risk and studies the rich–poor rainfall encounter risk between a water source area and water receiving areas in the middle route of the South-to-North Water Transfer Project in China. Real time scenario simulations with the input of new observations were also studied. The results show that the rich–poor rainfall encounter risk is high for the Tangbai River receiving area in the fourth quarter, for the Huai River and South of Hai River receiving area in the second quarter, and for the North of the Hai River receiving area in the fourth and first quarters. The scenario simulations reflect risk change in the operation of water transfer projects, providing scientific decision support for the management of the water resource distribution in the inter-basin water transfer projects.
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Research Article|
September 01 2011
Risk analysis of rich–poor rainfall encounter in inter-basin water transfer projects based on Bayesian networks
Kang Ling;
1Department of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
E-mail: kling_hust@163.com
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He Xiaocong
He Xiaocong
1Department of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Water Supply (2011) 11 (4): 451–459.
Article history
Received:
January 26 2011
Accepted:
June 20 2011
Citation
Kang Ling, He Xiaocong; Risk analysis of rich–poor rainfall encounter in inter-basin water transfer projects based on Bayesian networks. Water Supply 1 September 2011; 11 (4): 451–459. doi: https://doi.org/10.2166/ws.2011.067
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Kang Ling, He Xiaocong; Risk analysis of rich–poor rainfall encounter in inter-basin water transfer projects based on Bayesian networks. Water Supply 1 September 2011; 11 (4): 451–459. doi: https://doi.org/10.2166/ws.2011.067
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