On the use of pareto optimization for multi-criteria calibration of hydrological models

The calibration of distributed and integrated hydrological model is formulated as a general multi-objective optimization problem that utilizes multiple sources of information in a consistent way. This formulation allows a comprehensive evaluation of the trade-off between different calibration objectives and an elaborate comparison of different model structures. It is a natural solution and extension to the weighted nonlinear least squares regression problem, and it allows the modeller or decision-maker to choose (or weight) solutions at a later stage according to the specific model application being considered. The proposed framework is illustrated for calibration of two MIKE SHE models of different complexity for the same catchment.