Optimal allocation of water resources based on genetic algorithms: a case study in the Colorado Basin, USA

Lei Liu; Shuyu Zhang; Jianhui Qiu

doi:10.1117/12.2642712

28 July 2022 Optimal allocation of water resources based on genetic algorithms: a case study in the Colorado Basin, USA

Lei Liu, Shuyu Zhang, Jianhui Qiu

Proceedings Volume 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022); 123030W (2022) https://doi.org/10.1117/12.2642712
Event: International Conference on Cloud Computing, Internet of Things, and Computer Applications, 2022, Luoyang, China

Abstract

Water scarcity is the most serious problem facing a large part of the world's population, especially in the United States. Guided by goal programming and dynamic programming, this study uses MATLAB to carry out the concrete practice of genetic algorithm based on the conflict between water use and power generation water use (agriculture, industry, residential). This method can also be used to study the water use conflict in the optimization process of water resources optimal allocation in other areas. It is calculated that the ratio of pumping of domestic, industrial and agricultural water is 0.98:0.01:0.01, the pumping volume of Lake Powell and Lake Mead is 68,320,154,372.388 m³ and 5,283,944,815.489 m³ respectively, and the water supply quota of domestic, industrial and agricultural water in five big states is analyzed. Firstly, household water consumption accounts for the majority of the total water consumption, so the government should strongly advocate people to save water. Second, industrial water is much more economical than agricultural water, so the second type should meet industrial water needs. Finally, as rainfall declines in the Southwestern United States, the government should consider developing water-saving agriculture.

Citation Download Citation

Lei Liu, Shuyu Zhang, and Jianhui Qiu "Optimal allocation of water resources based on genetic algorithms: a case study in the Colorado Basin, USA", Proc. SPIE 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022), 123030W (28 July 2022); https://doi.org/10.1117/12.2642712

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