Modeling and Evaluation of Maize Under Full and Limited Irrigation.

Population growth in areas such as the Front Range of Colorado has led to increased pressure to transfer water from agriculture to municipalities.  In many cases, farmers may have an opportunity to remain agriculturally productive while practicing “limited irrigation,” where substantial yields may be obtained with reduced water applications during the non-water sensitive growth stages.  Savings in crop evapotranspiration (ET) can then be leased to municipalities or other entities as desired, providing supplemental income.  The objective of this study was to calibrate and evaluate the CERES-Maize crop growth model for full and limited irrigation conditions and determine the model's ability to differentiate irrigation treatments in terms of ET, crop growth, and yield. Field experiments of corn were performed near Fort Collins, Colorado between 2006 and 2008, where four replicates each of full and limited irrigation treatments were evaluated. Observations of soil profile water content, corn leaf area index, leaf number, and grain yield were used to calibrate and evaluate the model. Additionally, ET and water use efficiency (WUE) were calculated based on field water balance and compared to model estimates. Overall, the model agreed with observed trends in seasonal ET, corn growth, and yield for full and limited irrigation scenarios.  Phenological timing, growth measurements, and yields were in general agreement, although measures of late-season leaf area index in limited irrigation were underestimated, indicating model overestimation of water stress.  Simulated cumulative ET trended similar to observed values, although the model showed some tendency to underpredict for full irrigation and overpredict for limited irrigation.  Limited irrigation observations showed a significant increase in WUE over full irrigation in two of the three years; however, the model was unable to replicate these results due to underestimation of ET differences between treatments.  While CERES-Maize generally agreed with observed trends for full and limited irrigation scenarios, simulation results show that the model could benefit from a more robust water stress algorithm that can accurately reproduce plant responses such as those observed in this study.