Automatic calibration of a conceptual rainfall–runoff model using multiple objectives

Abstract

Formulation of an automatic calibration strategy for the MIKE 11/NAM rainfall–runoff model is outlined. The calibration scheme includes optimisation of multiple objectives that measure different aspects of the hydrograph: (1) overall water balance, (2) overall shape of the hydrograph, (3) peak flows, and (4) low flows. An automatic optimisation procedure based on the shuffled complex evolution algorithm is introduced for solving the multi-objective calibration problem. A test example is presented that illustrates the principles and implications of using multiple objectives in model calibration. Significant trade-offs between the different objectives are observed in this case and no single unique set of parameter values is able to optimise all objectives simultaneously. Instead, the solution to the calibration problem is given as a set of Pareto optimal solutions, which from a multi-objective viewpoint are equivalent. A large variability is observed in the Pareto optimal parameter sets, resulting in a large range of “equally good” simulated hydrographs. From the set of Pareto optimal solutions, one can draw a single solution according to priorities of the different objectives for the specific model application being considered. A balanced aggregated objective function is proposed, which provides a compromise solution that puts equal weights to the different objectives.