Modification of the SCE-UA to Include Constraints by Embedding an Adaptive Penalty Function and Application: Application Approach

Evolutionary algorithms that are commonly used for automatic calibration of watershed runoff simulation models are unconstrained optimization algorithms. The watershed runoff phenomenon, however, is quite complex, so there are some limitations to the calibration of such models with a single-objective function. The purposes of this study are to improve the shuffled complex evolution-University of Arizona (SCE-UA) to include constraints and to develop an automatic calibration module of the SWMM (storm water management model). An adaptive penalty function was used to impose constraints on the SCE-UA. Two constraints are imposed to diminish errors of peak flow and peak time on a watershed runoff event simulation. We applied the new automatic calibration module to a watershed runoff event simulation for the Milyang Dam Basin in Korea. The automatic calibration results that included the constraints showed improvement in reducing errors of peak flow and peak flow occurrence time. The overall shapes of flood hydrographs were also more similar to observed hydrographs than those of automatic calibration results without the constraints.