AbstractThe World Food Studies (WOFOST) model’s performance in simulating different field maize (Zea mays L.) growth and productivity variables was evaluated using 6 years of field experimental data that were measured from the 2005–2010 maize growing seasons in south central Nebraska. Irrigation levels were rainfed (no irrigation), limited irrigation [50% full irrigation (FIT), 60% FIT, and 75% FIT] and full irrigation conditions. Different maize growth and developmental periods and the entire growing seasons were evaluated by comparing simulated leaf area index (LAI), aboveground biomass, grain yield, and soil water content (SWC). When the data for all growing seasons were pooled, the values of RMS error (RMSE) and normalized RMSE (NRMSE) between simulated and observed days to flowering were 3.7 and 4 days, respectively, which were considered very accurate. When all growing seasons’ data were combined, the values of RMSE and NRMSE between simulated and observed days to maturity were 7.5 and 5 days, respectively. There was acceptable agreement between predicted and observed LAI (RMSEn=13%–24%, and R2=0.80–0.95) and aboveground biomass (RMSEn=9%–25%, and R2=0.91–0.99). During the validation, there was no significant difference between the simulated and observed LAI values (P>0.05). The model simulated the rainfed and irrigated aboveground biomass reasonably well. There were no significant differences between model-estimated and measured grain yield. The Pe of grain yields across the 2005–2010 growing seasons ranged from −18% to 31%. The RMSE between the observed and simulated grain yield ranged between 1.02 and 2.05 ton ha−1 and NRMSE ranged from 7% to 17%. The largest difference between yield potential and measured grain yield (yield gap) was observed in the rainfed treatment (9.97 ton ha−1) and the least gap was in the FIT (3.75 ton ha−1). The model’s performance in simulating SWC was considered to be poor to moderate, with a wide range R2 values between the treatments, from 0.10 to 0.82. The mean difference between observed and simulated SWC ranged from 0.2 to 0.4 m3 m−3. Although overall, the WOFOST model’s performance was considered to be good for some of the variables (i.e., plant phenology, LAI, and grain yield), its performance in simulating other variables (i.e., SWC) was marginal under these experimental conditions. Its performance declined substantially under water-limiting and rainfed conditions. Further research that identifies potential reasons for the poor performance and determining potential solutions to improve the model’s prediction accuracy is needed.