ABSTRACT
The estuarine management problem can be formulated with different management objectives or even as a multiobjective problem. This chapter reformulates the mathematical programming model on estuarine management as an optimal control model. In the estuarine management model, the objective function is to maximize the summation of fishery harvest. In the estuarine management problem, salinity at the beginning of each month is chosen as the state variable, and monthly freshwater inflow is chosen as the control variable. The Dynamic programming (DDP) method loses its advantage for the estuarine management model, with hydrodynamic model (HYD)-salinity transport model (SAL) as the transition equation. A system with nonlinear dynamics can be addressed by linearizing the simulation dynamics in the optimization stage and then updating the control and the state vectors through simulation of the full nonlinear model. Successive approximation linear quadratic regulator (SALQR) differs from DDP only in that the nonlinear simulation equations are linearized in the optimization step.
