Control of Rivers with Flood Avoidance

Abstract

River control and decision support system can help improving water resource management. Rivers often have two modes of operations: normal operations, which include maintaining water levels and flows at their reference points, and flood avoidance. This work formulates the river control problem as a Stochastic Model Predictive Control (S-MPC), where a Multiple Chance-Constrained optimisation Problem (M-CCP) is solved at every time step. The M-CCP accommodates the constraints related to normal river operations and flood avoidance as two probabilistic constraints. We use the soft probabilistic constraints, because a hard constraint on the water level that depends on uncertain forecasts of the un..