This paper presents a new methodology for determining optimal operation of soil aquifer treatment (SAT) systems considering parameter uncertainty. The problem of optimal operation of SAT systems is formulated and solved in a discrete-time optimal control framework by interfacing the SALQR (Successive Approximation Linear Quadratic Regulator) optimizer with the MSTS (Multiphase Subsurface Transport Simulator) model. Both deterministic and stochastic programming formulations have been solved. Through the use of first-order analysis of uncertainties, the uncertainty of the water content due to the uncertainties of the simulation parameters are evaluated. A chance constrained formulation of the optimization is utilized to account for the uncertainties of water content in the SAT operation. This approach enables one to quantity the uncertainty of the parameter estimates, and automatically account for the parameter uncertainty in the decision-making process through the SAT management model.
ASJC Scopus subject areas
- Civil and Structural Engineering
- Water Science and Technology