Impact of Apex Parameterization and Soil Data on Runoff, Sediment & Nutrients Transport Assessment.

Hydrological models have become essential tools for environmental assessments. This study’s objective was to evaluate a best professional judgment (BPJ) parameterization of the Agricultural Policy and Environmental eXtender (APEX) model with soil-survey data against the calibrated model with either soil-survey or measured soil data.  The BPJ parameterization was derived from the CEAP parameterization, the User’s manual, discussions with model developers, and our own understanding of the parameters. Long-term monitored data from a watershed with claypan soils and a corn (Zea mays L)-soybean [Glycine max (L.) Merr.]  rotation in Northeast Missouri was used for the model performance assessment.  Overall, the coefficient of determination (r²), Nash-Sutcliffe Coefficient (NSC), and Percent bias (Pbias) were always better for the calibrated model and with site-specific soil data. The calibrated model with soil-survey data showed satisfactory predictions for runoff. The sediment simulation performance was very poor (NSC < 0) with the BPJ parameterization and best with measured soil data and a calibrated model (NSC 0.25 -0.53). Using soil survey or measured data has inconsistent effects on model performance.  Average annual runoff, TP, and TN with the BPJ parameterization were 12%, 19%, and 26% lower, respectively than with the calibrated model and site-specific soil data while sediment losses were 113% higher. This indicates the need for calibration before running scenario analyses of sediment or nutrient transport.