Simulating Within-Field Spatial and Temporal Corn Yield Response to Nitrogen with APSIM Model

Process-based crop growth models can explain soil and crop dynamics that influence the optimal N rate for crop production. Currently, there is a lack of understanding regarding the accuracy of process-based models for site-specific zones within fields, as well as the key factors that need to be considered when calibrating these models for zone-specific economic optimum N rate (EONR). We calibrated the Agricultural Production Systems sIMulator (APSIM) model in contrasting zones within fields, quantified the model performance, and used the calibrated model to develop long-term corn yield response to N to assess the temporal variability between zones and sites to assist decision making. We conducted four N rate experiments (2 fields × 2 zones within a field) over two years in southeast Nebraska. Experimental data were used to calibrate and test the APSIM model. APSIM simulated corn yield response to N for each zone and site was obtained by running numerous iterations of the calibrated model at different N rates. Observed and simulated corn yield response to N rate were analyzed with statistical models to estimate the EONR. The APSIM model predicted corn yield over 11 historical years with a relative root mean square error (RRMSE) of 12