Modeling Deficit Irrigation of Maize Using the Daycent Model.

Recently, a new simple leaf area method was implemented in the DayCent ecosystem model and validated with field data of maize, soybean and winter wheat. In this study, we used measurement data from three limited irrigation experiments of maize in Colorado USA to evaluate the new DayCent model and compared the stress coefficient (K_s) of the DayCent model with the one in the FAO 56 paper. Overall, the new leaf area method provided fairly accurate estimation of green leaf area index (GLAI) for full and limited irrigation treatments. The method tends to over-predict the GLAI at late vegetative growth period of the limited irrigation treatments. The simulated actual transpiration rates by the two K_s methods are very similar and simulated soil water content is fairly accurate. As a result, GLAI, biomass, and grain yields by the two methods are close and these variables compared well with the measured values. The accuracy of the predictions was comparable to published simulation results of the same experiments from other models. In sum, the DayCent model could simulate the response of maize under water deficit conditions and could be used as a guide for application of limited irrigation strategies for water saving.