Model Predictive Control in Irrigation Systems

Model predictive control (MPC) has emerged as a powerful methodology for optimising water distribution in irrigation networks by anticipating future hydraulic states and systematically adjusting inflows, gate positions and pump speeds. By using a dynamic model of the canal or conveyance system, MPC can account for physical constraints, time delays and external disturbances such as variable demand or unexpected inflows. Its receding-horizon framework enables continuous re-evaluation of control moves, promoting efficient water use and maintaining desired water levels across multiple pools or compartments. Practical implementations span open-channel canals, polder systems and pipe–canal combinations, addressing objectives such as minimising energy consumption, ensuring flood safety and meeting agricultural requirements. Advances in numerical solvers, mixed-integer formulations and integration with real-time telemetry have accelerated deployment in large-scale water transfer projects, underscoring the global significance of MPC for sustainable irrigation management and climate-resilient agriculture.

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Model Predictive Control in Irrigation Systems publication trend

The graph below shows the total number of articles in model predictive control in irrigation systems across all publications each year (not limited to Nature Index journals).

Technical terms

Model predictive control (MPC): A control strategy that uses a dynamic model to forecast future system behaviour and optimise control inputs over a finite horizon subject to constraints.

Prediction horizon: The future time window over which MPC computes system state predictions and control actions.

Polder: A tract of low-lying land reclaimed from water bodies and protected by embankments, reliant on pumps and gates for water management.

Inverted siphon: A hydraulic structure allowing a watercourse to pass beneath an obstacle through pressurised conduits.

References

1. Predictive control of irrigation canals – robust design and real-time implementation. Water Resources Management (2016).
2. On Modeling and Constrained Model Predictive Control of Open Irrigation Canals. Journal of Control Science and Engineering (2017).
3. Potential of model predictive control of a polder water system including pumps, weirs and gates. Journal of Process Control (2022).
4. Automatic Control of the Middle Route Project for South-to-North Water Transfer Based on Linear Model Predictive Control Algorithm. Water (2019).
5. Application of Model Predictive Control for Large-Scale Inverted Siphon in Water Distribution System in the Case of Emergency Operation. Water (2020).