An Optimization Scheme of Water Resources Allocation Based on the Particle Swarm Algorithm

Climate change will exacerbate water scarcity, as warmer temperatures will increase evaporation from soil and water surfaces, raising crop water requirements, and consumers’ demand for energy will increase at higher temperatures, with a concomitant increase in demand for cooling water. Therefore, water scarcity has evolved into a global issue, most notably in the Colorado Basin. As the climate changes, the future of the Colorado River becomes even more tragic. The river’s water levels are dropping year after year, while the water needs of the surrounding urban development are increasing, in what seems to be an endless cycle. At the same time, the entire southwestern United States may be in an unprecedented resource crisis as a result. Therefore, we have modeled water supply, demand, and allocation scenarios and constructed a water allocation model using the Colorado Basin water allocation as an example, combining Lake Mead, Lake Powell, and the agricultural, industrial, and residential demand for water and electricity in five states. To better achieve the optimal balance between the economy and the environment, we set three objectives: economic efficiency, regional surplus water, and total regional electricity generation, and solved the problem using a particle swarm algorithm. By solving the Colorado Basin water allocation problem, we explore a feasible solution with high generalization capability that can be applied in the future to scenarios of rational water allocation in multiple regions around the world.