An eco-environmental water demand based model for optimising water resources using hybrid genetic simulated annealing algorithms. Part II. Model application and results.
The present optimisation model described in Part I of this work is applied to optimise water resources in the Haihe river basin, an important basin in north China that covers 31.82 million km(2). Results show that this optimisation model with the HGSAA solution is feasible and effective in the long-term optimisation of water resource use. It is shown that the combined forecasting method can improve the forecast precision. The results obtained indicate that the mean relative errors of BP and polynomial models are 2.3% and 4.9%, respectively, while that of the combined forecasting method is 1.93% in a case study on the Tumahe River for 2010. The combined forecasting method performs better because it incorporates various forecasting methods. The optimisation results show that both domestic and eco-environmental water demands can satisfy the requirements of the forecasting procedure, and the harmonious indices all exceeded 0.7. The Luanhe River is the most water-scarce sub-basin in the Haihe river basin.
Wang
Xiaoling
X
School of Environment Science and Engineering, Tianjin University, Tianjin, China. wangxl@tju.edu.cn
Sun
Yuefeng
Y
Song
Lingguang
L
Mei
Chuanshu
C
D000465:Algorithms; D002681:China; D003247:Conservation of Natural Resources / Q000379:methods*; D004784:Environmental Monitoring / Q000379:methods*; D014872:Water Movements; D014881:Water Supply / Q000032:analysis*