350-3 Evaluating the Response of CSM-CERES-Maize to High Temperature and Drought Stress Under Field Conditions.

Poster Number 223

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agroclimatology and Agronomic Modeling: III
Wednesday, October 24, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
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Jakarat Anothai1, Cecilia Tojo Soler1, Alan Green2, Michael Ottman3, Bruce Kimball4 and Gerrit Hoogenboom1, (1)AgWeatherNet, Washington State University, Prosser, WA
(2)AgroFresh, Des Moines, IA
(3)1140 E. South Campus Drive, University of Arizona, Tucson, AZ
(4)U.S. Arid-Land Agricultural Research Center, USDA-ARS, Maricopa, AZ
High temperature, drought stress and their interactions can have a great detrimental effect on crop growth and productivity in many regions of the world. Crop simulation models could assist in determining the adverse effect from either of these abiotic stress factors on crops. However, the appropriate performance of crop models under such conditions should be confirmed using experimental data. The objective of this study was to evaluate the response of the Cropping System Model (CSM)–CERES–Maize model to simulate the impact of high temperature and drought stress under field conditions on maize (Zea mays L.) growth and development, soil water content and drought stress index. Data on plant growth and yield obtained from an experiment that was conducted at the University of Arizona Maricopa Agricultural Center from May to August 2011. The irrigation treatments included both adequate and deficit irrigations. For the deficit irrigation, irrigation water was withheld for 10 days starting at V10, while this treatment received sufficient water prior to and after this “stress period”. The ability of the CSM–CERES–Maize model in simulating growth and development as well as soil water content under these high temperature and drought conditions was analyzed. Also, the drought stress index calculated from the model was compared with Idso Crop Water Stress Index (CWSI). The results showed that the CSM–CERES–Maize model predicted phenology accurately for all irrigation treatments with two days differences for silking and identical values for physiological maturity. The model underestimated values of time series data for leaf area index, leaf weight, stem weight and total biomass, whereas overestimated grain yield at harvest, especially for the deficit irrigation. The normalized root mean square error ranged from 17.4 to 56.0% for the adequate irrigation and 26.9 to 76.7% for the deficit irrigation treatment. There was a reasonable agreement between the simulated and observed water content for all seven soil depths of the two irrigation treatments. In addition, the model accurately simulated the fluctuation and time span of the cyclic variation of soil water. The model also estimated the drought stress index in good agreement with the corresponding CWSI. However, the CWSI assessed the time of occurrence of water stress about three days earlier than the model for the deficit irrigation treatment. Overall, our results found that the CSM–CERES–Maize model does not perform well in simulating yield and yield components under extreme high temperature and drought stress such in an arid environment, suggesting that the optimum temperatures and maximum temperature for photosynthesis and grain filling rate use in the model need to be verified. The approach used in the CSM–CERES–Maize model for simulating the soil water balance and the drought stress index performed reasonably well.
See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agroclimatology and Agronomic Modeling: III