Hydrodynamic simulation and multi-objective optimization coupling for efficient decision-making of water transport and distribution in irrigated areas

With rising demand for refined management in irrigation districts, distribution and regulation technologies have steadily advanced. However, conventional scheduling models still suffer from low resource efficiency and lagging responsiveness. To address these challenges, this study proposes a multi-objective optimization framework for open-channel flow distribution under varying hydrological conditions. The framework simulates dynamic hydraulic level evolution driven by flow and gate regulation, capturing the interactions among flow conveyance, flow fluctuations, and irrigation efficiency. A multi-objective regulation model is constructed, targeting resource conservation, flow stability, and operational efficiency. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) algorithm generates optimized scheduling schemes for diverse scenarios. Applied to the Chahayang Irrigation District, the model reduces average flow fluctuations by 35 % and enhances distribution efficiency by 22 % over traditional methods. It also decreases gate adjustments by 28 % and extends adjustment intervals by 3.5 h, improving efficiency while lowering energy use. This research offers practical strategies and methodological support for intelligent, efficient, and refined irrigation management. • A multi-objective coordinated scheduling model was developed for gate-channel systems. • Hydrodynamic simulation was integrated to resolve canal scheduling delays. • The dynamic integration of field water demands optimizes canal flow. • Operational optimization achieves a significant reduction in both gate adjustments and water loss.