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A general methodology is presented to integrate complex simulation models of hydrological systems into op- timization models, as an alternative to scenario-based ap- proaches. A gradient-based hill climbing algorithm is pro- posed to reach locally optimal solutions from distinct start- ing points. The gradient of the objective function is esti- mated numerically with the simulation model. A statistical procedure based on the Weibull distribution is used to build a confidence interval for the global optimum. The method- ology is illustrated by an application to a small watershed in Ohio, where the decision variables are related to land-use al- locations and the objective is to minimize peak runoff. The results suggest that this specific runoff function is convex in terms of the land-use variables, and that the global optimum has been reached. Modeling extensions and areas for further research are discussed.

Global spatial optimization with hydrological systems simulation: application to land-use allocation and peak runoff minimization