The impact of objective function formulation on the optimal calibration of QUAL2E

Aksoy, Ayşegül
Successful calibration and verification of a model is important to confirm its usage for water quality predictions. Instead of trial-and-error approach, optimization techniques can be used to adjust the biological, chemical, and kinetic parameters in a more efficient way. In this study, a genetic algorithm (GA) is used to calibrate and verify QUAL2E for the reaeration coefficient (K2) and the sediment oxygen demand rate (K4) with reference to dissolved oxygen (DO) observation data. Three different objective functions were used to investigate the impact of formulation itself on the performance of the optimization models. The results show that for the river system considered in this study, objective function formulation may have an impact for a successful outcome.