[Objective]A nonlinear multi-objective water resources optimization model has been developed to address issues such as missing information and neglecting the game process between targets in water demand forecasting.The interrelation and game characteristics between water resources and urban development in water demand forecasting are taken into consideration.[Meth-ods]The model aims to minimize total water consumption and minimize water consumption per 10,000 yuan of value-added,based on the principles of the"Basing Four Aspects on Water Resources".Joint optimization of water resource demand is con-ducted for different years and industries.In contrast to the traditional water quota forecasting method,which disregards the com-petition process between objective,the Pareto solution set of this nonlinear multi-objective model is determined using a genetic algorithm,[Results]ing in a series of water resource optimization schemes that fulfill the target requirements.[Results]The model has been applied to Wujiang District,Suzhou City,Jiangsu Province,yielding 100 non-inferior water resource optimization schemes.The findings indicate that the optimized solution on the Pareto solution set is 6％to 16％lower than the water quota method in terms of total regional water use,and the water use per 10,000 yuan of value-added is reduced by 19％～31％com-pared to the water quota method,demonstrating a significant optimization effect.[Conclusion]The result suggest that the com-petitive state between water use and urban development can be comprehensively illustrated by the Pareto solution set.It is revealed by the model that the relationship between water resources and population,land,cities,and industries is inherently complex and competitive.Richer decision-support information for practical applications is provided by taking into account these relationships.
关键词
帕累托解集/四水四定/多目标优化/定额法/水资源优化/水资源/影响因素/人口
Key words
Pareto solution set/Basing Four Aspects on Water Resources/multi-objective optimization/water quota method/water resources optimization/water resources/Influencing factors/population
维普
万方数据