Study on multi-objective optimization of loading and solute concentration models for simulating stream flow and water quality with acceptable accuracy

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This study aims at establishment of a parameter calibration method to achieve a good balance of estimated accuracies of stream flow and water quality in the application of loading model and solute concentration model. Firstly, the applicability of compromise programming, one of the multi-objective optimization methods was investigated in the multi-objective optimization of Tank Model parameters. Secondly, sodium loading and sodium concentration of a small forest catchment in Gojo, Nara prefecture were estimated by the Long- and Short-Term Runoff Model (LSTRM) combined LQ or CQ equations applied to four runoff components. 14 parameters of LSTRM and 8 parameters of LQ or CQ equations were estimated by the compromise programming. The results show that the compromise programming is effective for calibrating model parameters which show good accuracies of both stream flow and sodium loading or both stream flow and sodium concentration.