山东农业大学学报（自然科学版）2026，Vol.57Issue(3)：517-527,11.DOI:10.3969/j.issn.1000-2324.2026.03.012
基于SWAT的流域闸坝联合生态优化调度
Joint Ecological Optimal Operation of Sluices and Dams in River Basin Based on SWAT
摘要
Abstract
The joint operation of basin sluice and dam systems considering river ecological flow is an important measure to alleviate water resource shortages and improve the water ecological environment.Taking the Si River Basin in Shandong Province as the study area,this study first establishes a SWAT model to simulate runoff and water quality in the reservoirs and sluice-dam sections.Then,it constructs a joint ecological optimal operation model for sluices and dams with the objective of maximizing their comprehensive storage capacity,which is solved by the Bitterling fish optimization algorithm(BFO).Furthermore,it compares the BFO-obtained operation schemes with schemes that do not consider joint operation and those solved using the particle swarm optimization algorithm(PSO).Finally,it inputs the optimized outflow of sluices and dams into the SWAT model for water quality simulation.The results indicate that the joint ecological optimal operation scheme is superior to the scheme that does not consider joint operation in terms of ensuring basin water supply,river ecological water demand,external water transfer and interception water resources.Moreover,the operation schemes solved by BFO outperform that obtained by PSO.Additionally,the four water quality indicators(total nitrogen,total phosphorus,ammonia nitrogen,and biochemical oxygen demand)have improved.The proposed joint ecological optimal operation model can fully exploit the potential of water resources and improve the water environment,offering a reference for integrated management of hydraulic infrastructure in river basins across northern China.关键词
SWAT模型/径流模拟/联合生态优化调度/鳑鲏鱼优化算法/泗河流域Key words
SWAT model/runoff simulation/joint ecological optimal operation/bitterling fish optimization algorithm/Si River Basin分类
建筑与水利引用本文复制引用
李淑贤,姚传辉,徐振翔,吴林静,刁艳芳..基于SWAT的流域闸坝联合生态优化调度[J].山东农业大学学报（自然科学版）,2026,57(3):517-527,11.基金项目
山东省自然科学基金面上项目(ZR2021ME058) （ZR2021ME058）
山东省重点研发计划项目(2019GSF111043) （2019GSF111043）
