Uncertainty Analysis of RZWQM2 Calibration Using the Parameter Estimation Algorithm (PEST).

It is a challenge for modelers to obtain reliable model parameters that are transferrable to other experimental conditions and locations. In this study, we evaluated the PEST algorithm in the root zone water quality model (RZWQM2) for parameter optimization. Four years of corn data under six irrigation treatments were used for model calibration. We found that optimized model parameters depended on the subsets of data used in calibration as well as interactions between crop and soil parameters. The uncertainty of model parameters can be transferred to a confidence interval of simulated results, such as yield and biomass. This study will provide model users guidance on model parameterization.