Abstract

China’s inter-basin water transfer projects have gained increasing attention in recent years. This study proposes an intelligent water allocation methodology for establishing optimal inter-basin water allocation schemes and assessing the impacts of water transfer projects on water-demanding sectors in the Hanjiang River Basin of China. We first analyze water demands for water allocation purpose, and then search optimal water allocation strategies for maximizing the water supply to water-demanding sectors and mitigating the negative impacts by using the Standard Genetic Algorithm (SGA) and Adaptive Genetic Algorithm (AGA), respectively. Lastly, the performance indexes of the water supply system are evaluated under different scenarios of inter-basin water transfer projects. The results indicate that: the AGA with adaptive crossover and mutation operators could increase the average annual water transfer from the Hanjiang River by 0.79billionm3 (8.8%), the average annual water transfer from the Changjiang River by 0.18billionm3 (6.5%), and the average annual hydropower generation by 0.49billionkWh (5.4%) as well as reduce the average annual unmet water demand by 0.40billionm3 (9.7%), as compared with the those of the SGA. We demonstrate that the proposed intelligent water allocation schemes can significantly mitigate the negative impacts of inter-basin water transfer projects on the reliability, vulnerability and resilience of water supply to the demanding sectors in water-supplying basins. This study has a direct bearing on more intelligent and effectual water allocation management under various scenarios of inter-basin water transfer projects.

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