Technical Abstract: Simulating soil nutrient cycling under a range of agricultural management scenarios is essential for agricultural practice, as well as environmental protection. The objective of this study is to test the capability of GPFARM software to simulate corn yield, biomass, and soil nutrient cycling under different agricultural management. The treatments include high/low plant density, full/no fertilization, and medium/no irrigation. Comparisons are presented for model predictions versus field observations for 3 years of data from the South Farm research plots in Fort Collins. The results show that GPFARM gives reasonable predictions for yield and biomass of corn and associated residual NO3-N under different fertilization, irrigation, and plant density treatments. The model was able to estimate soil residual NO3- N levels for both non-fertilized and fertilized cases where crop N uptake early in the growing season played a key role. Corn biomass and yield under both irrigated and non-irrigated conditions were simulated reasonably well using a common model parameter set for the corn variety thus demonstrating the ability of the model stress function to handle dryland and irrigated conditions.