Research on the coupled model of canal system optimization control and water distribution

Abstract

The process of water delivery and distribution in irrigation districts requires the coordinated operation of check gates and turn-out gates. The Integrator-Delay (ID) model is a widely used canal control model, assuming that offtakes are located at the downstream end of canal pools. However, previous studies have often analyzed water delivery and distribution separately, and the assumptions of the ID model fail to reflect the actual distribution of most open-canal offtakes. To address these issues, this paper establishes a coupled model for optimal control and water distribution in canal systems. Firstly, an Optimized Integrator-Delay (OID) model is proposed to more accurately represent the dynamic impact of offtake locations on water level variations. Model Predictive Controllers (MPCs) are then designed based on both the OID model and the ID model for performance comparison. Secondly, to evaluate the applicability and control performance of the two models when coupled with the canal system optimization water distribution model, three irrigation scenarios are defined: (1) prioritizing the backwater area, followed by the uniform flow area; (2) prioritizing the uniform flow area, followed by the backwater area; and (3) random irrigation. Control performance metrics are used to assess the stability of water levels, flow rates, and gate adjustments under the two controllers. Water delivery and distribution strategies are formulated for various scenarios and applied in the Bojili Irrigation District. The results show that， compared to the ID model, the OID model achieves maximum improvements in water level, flow rate, and gate opening control stability by 8.81 %, 16.47 %, and 7.06 %, respectively. The coupled model provides effective target water levels, water distribution schemes, and scheduling schemes for the three scenarios. It significantly reduces the frequency and magnitude of gate adjustments, minimizes water shortages and abandonment, and enhances system efficiency and resilience against complex demands and disturbances.