Abstract
ABSTRACT A method for estimating the best set of parameters for multiobjective hydrologic models was developed. The method of Multiple Objective Programming (MOP) and a method based on Bayesian statistical theory were used to construct objective functions and to carry out the optimization procedures. A hydrological model called PRMS (Leavesley et al., 1983) was used. Three objectives and four parameters were considered. The results show that when a single objective function is used, the optimal parameters are good with respect to the optimized objective but may be poor in terms of other objectives. When a multiple objective function is used, the optimized parameters are relatively good with respect to all objectives
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