Optimal salinity and water level control of water courses using Model Predictive Control.

Abstract Worldwide, delta areas are under stress due to climate change. With rising sea levels and decreasing freshwater availability, surface water salinization due to groundwater exfiltration is expected to increase in these low-lying areas. To counteract surface water salinization, freshwater diverted from rivers is used to flush agricultural ditches. In this paper, we demonstrate a Model Predictive Control (MPC) scheme to control salinity and water levels in a water course while minimizing freshwater usage. A state space description of the discretized De Saint Venant and advection-dispersion equations for water and salt transport, respectively, is used as the internal model of the controller. The developed MPC scheme is tested using groundwater exfiltration data from two different representative Dutch polders. The tests demonstrate that water levels and salinity concentrations can successfully be controlled within set limits while minimizing the freshwater used. Highlights • A real time control method is proposed for optimal flushing of polder systems. • Low-order physical model is employed to formulate model predictive control problem. • Water level and salinity regulation is achieved by minimizing the freshwater use. • A quadratic program is formulated and solved to optimize regulation. • 35–45% savings in freshwater used is realized compared to traditional flushing. [ABSTRACT FROM AUTHOR]