Technical Abstract: Increasing population growth along the Front Range of Colorado has led to increased competition for water resources. In many cases cities have purchased land and water rights from agricultural producers to obtain the resources needed to sustain this growth. As an alternative to this scenario, farmers may have an opportunity to remain agriculturally productive while practicing “limited irrigation,” where substantial yields are obtained with reduced water applications. Field experiments of corn were performed near Fort Collins, CO between 2006 and 2008, where four replicates each of one full irrigation and two limited irrigation treatments were evaluated. Experimental field data obtained include soil moisture content and yield in all years, as well as biomass and leaf area index in 2008. While field data is invaluable in evaluating irrigation management scenarios such as this, properly calibrated and validated crop simulation models can provide opportunities to evaluate many potential agricultural practices in a much smaller time frame. The first objective of this study is to calibrate and validate the CERES-Maize crop growth model for corn using the experimental field data. Genetic crop growth parameters were systematically adjusted to minimize statistical error between observed and simulated soil water content, leaf area index, and yield. The second objective is to use this calibrated model to perform analyses of potential management criteria relating to limited irrigation. The overall goal of these simulations is to increase water use efficiency by maximizing the crop yield per amount of irrigation water required, through adjustments in irrigation timing, amount, or combination of both. Results from these simulations can provide focus for future field experiments by indicating management approaches with the greatest opportunity for success. In addition to guiding future research, general limited irrigation management concepts outlined in this study may be considered by agricultural producers as viable options.