A multi-scale multi-objective optimization model for water resources scheduling in complex inter-basin water transfer systems - Gao, Yuqin; Xia, Meijuan; Zhang, Jingwen; Tan, Xilan; Yuan, Chenyu (Journal of hydrology (Amsterdam), 2025)
[Display omitted] •A new multi-scale multi-objective model is developed for inter-basin water scheduling.•The MOPSO algorithm is improved to solve complex system optimization models efficiently.•The model shows good stability and strong resistance to disturbances. Inter-basin water transfer (IBWT) projects play a crucial role in alleviating regional water resource shortages, promoting economic development, and protecting ecosystems. However, as IBWT system structures and transfer demands become increasingly complex, the transfer system is facing issues such as incomplete objective systems, fragmented time scales, and narrow feasible domains, calling for integrated innovation in theory and methodology to improve the scientific quality of decision-making. This paper proposes a Water-Economy-Ecology-Satisfaction-Carbon (WEESC) system and constructs a multi-scale, multi-objective water resources optimization scheduling framework. It sets water satisfaction, ecological benefits, and emission reduction as fundamental objectives at the monthly scale, with economic benefits as a developmental objective at the annual scale to achieve rational water resource allocation. The model introduces the concepts of flexible demand and satisfaction, quantifying water demand through a range of required water intervals to enhance the robustness of the water resource scheduling system. Simultaneously, it fully accounts for ecosystem carbon sequestration dynamics and quantifies the carbon footprint of water diversion. The improved multi-objective particle swarm optimization (IMOPSO) algorithm is used to solve the optimization problem, incorporating an alternating projection correction algorithm to enhance the ability to find solution sets under complex constraints. The Jiangsu section of the South-to-North Water Diversion Project is selected as the study area, with empirical validation based on data from 2000 to 2022. The results indicate that the proposed WEESC multidimensional objective system effectively coordinates conflicts among objectives. The integrated optimization strategy can increase water use satisfaction by 10.08%, reduce carbon emissions by 10.93%, and simultaneously constrain economic benefit fluctuations within a 0.26% range, with the multi-objective coupling coordination degree reaching 0.97. Through the annual-monthly nested optimization model and the IMOPSO, the model-solving complexity is significantly reduced, and the efficiency of feasible solution generation is improved. Sensitivity and uncertainty analysis show that the model exhibits good stability against disturbances in key parameters. Under the disturbance of the water demand quota, the key indicator deviations were controlled within 1.35%, verifying the model’s practicality and robustness. The results of parameter sensitivity and uncertainty analyses show that the model exhibits stability under perturbations of key parameters and can effectively mitigate system fluctuations caused by demand uncertainty. This study provides theoretical support for multi-objective optimization scheduling in IBWT projects, promoting the sustainable utilization of water resources.