Optimal allocation of water quantity and waste load in the Northwest Pearl River Delta, China

被引:39
|
作者
Liu, Dedi [1 ,2 ]
Guo, Shenglian [1 ]
Shao, Quanxi [3 ]
Jiang, Yunzhong [4 ]
Chen, Xiaohong [5 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China
[2] Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Jiangsu, Peoples R China
[3] CSIRO Math & Informat Sci, Wembley, WA 6913, Australia
[4] China Inst Water Resources & Hydropower Res, Beijing 100038, Peoples R China
[5] Sun Yat Sen Univ, Ctr Water Resource & Environm, Guangzhou 510275, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Water allocation policy; Wasteload allocation; Optimization; MULTIOBJECTIVE GENETIC ALGORITHMS; MULTIRESERVOIR SYSTEMS; RESERVOIR OPERATION; DEFICIT IRRIGATION; QUALITY MANAGEMENT; MODEL; OPTIMIZATION; BASIN; RESOURCES; NETWORKS;
D O I
10.1007/s00477-013-0829-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Northwest Pearl River Delta is one of the most developed areas in China and has faced serious water problems because of its fast economic growth, urbanisation and other developments. It is widely believed that an integrated management of the socio-economic factors cross individual administrative cities is an effective way to solve the water problems. To serve this purpose, this paper aims to develop an integrated model for the optimal allocation of water quantity and waste load. In order to consider the interaction between water quantity and waste load allocation, the Saint-Venant equations were used to simulate dynamic water flow for the water quantity allocation, whereas the one dimensional advection-dispersion mass transport equation was used to simulate water quality for the waste load allocation. In addition to the maximisation of the economic benefits, which is often considered as an objective of optimal water resource allocation models, the minimisation of water shortages and maximisation of waste load were also introduced as objectives of the model. To solve the multi-objective allocation model, a second generation non-dominated sorting genetic algorithm was employed because of its computational efficiency and running time. The results indicate that it is a serious task to reduce the COD in the Northwest Pearl River Delta since the maximum waste load allocations under water quality targets is less than the present amount of waste discharged into rivers in the study area.
引用
收藏
页码:1525 / 1542
页数:18
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