Performance Evaluation Of The CSM-CERES-Maize and CSM-Ixim-Maize Models For Simulating Maize Response To High Temperature and Drought Stress Under Field Conditions.

High temperature, drought stress and their interactions can seriously reduce both crop growth and productivity. Crop simulation models could assist in determining the adverse effect from either of these abiotic stress factors on crops. However, the appropriate performance of the models under such conditions should be confirmed using experimental data. The objective of this study was to evaluate the capability of the CSM–CERES–Maize and CSM–IXIM–Maize models to simulate the impact of high temperature and drought stress on maize grown under field conditions. The experiments were conducted at University of Arizona Maricopa Agricultural Center during the 2011 and 2012 growing seasons. The irrigation treatments were adequate and deficit irrigations. For the deficit irrigation, irrigation water was withheld for 12 days in 2011 and for 7 days in 2012, while this treatment received adequate water during the other parts of the growing season. The management and environmental conditions for these two experiments were used to define the inputs for the CSM–CERES–Maize and CSM–IXIM–Maize and the simulation outputs of plant growth and development, soil water content and drought stress index were analyzed. The results showed that the CSM–CERES–Maize simulated phenology accurately for both irrigation regimes and years, while the CSM–IXIM–Maize shortened the duration to physiological maturity for approximately 18 days in 2011 and 10 days in 2012. For the 2011 growing season, the CSM–CERES–Maize simulated leaf area index (LAI), stem weight and total biomass closer to the observed than the CSM–IXIM–Maize. However, both models underestimated the values for these traits. In contrast, seed yield was substantial overestimated by the CSM–CERES–Maize model compared to the CSM–IXIM–Maize model, especially for the deficit irrigation treatment. For 2012, the stress period was shorter than 2011. As a result, both the CSM–CERES–Maize and the CSM–IXIM–Maize simulated all traits, including LAI, leaf weight, stem weight, seed yield and total biomass, in good agreement with the observed data. The simulations of soil water content were slightly better for the CSM–CERES–Maize than for the CSM–IXIM–Maize model for both years. The estimation of the drought stress index by both models was comparable to the Idso Crop Water Stress Index (CWSI). However, the CWSI assessed the time of occurrence of water stress about three days earlier than the models for the deficit irrigation treatment. Overall, our results found that both models do not perform well in simulating yield and yield components under extreme conditions, especially under a severe and long period of drought stress as occurred in 2011, suggesting that the optimum and maximum temperature that are currently used in the models need to be verified. However, the approach used in the models for simulating the soil water balance and the drought stress index performed reasonably well.