Optimization of freshwater inflow to estuaries

This paper presents a methodology that can be used for determining the optimal freshwater inflows into bays and estuaries for the purpose of balancing freshwater demands with the harvest of various types of estuarine resources (e.g., finfish and shrimp). The optimization problem is a nonlinear programming problem solved using a generalized reduced gradient technique. Salinity is expressed as a function of freshwater inflow in a nonlinear regression equation and used as a constraint. Additional nonlinear constraints are the harvest regression equations for the various species that express harvest as a function of the quantity of freshwater inflow. Because of the uncertainty associated with the regression equations for salinity and harvest, these constraints are expressed in a chance-constrained formulation. The methodology is applied to the Lavaca-Tres Palacios Estuary in Texas. The results of the numerical application indicate that the minimum freshwater inflow requirement increases as the required reliability of chance constraints increases. The uncertainty in the regression equations limits the maximum achievable reliability.