Location: Water Management and Systems ResearchTitle: Evaluation of two evapotranspiration approaches simulated with the CSM-CERES-Maize model under different irrigation strategies and the impact on maize growth, development and soil moisture content for semi-arid conditions) Author
Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/16/2013
Publication Date: 4/16/2013
Publication URL: http://dx.doi.org/10.1016/j.agrformet.2013.03.001
Citation: Anothai, J., Soler, C., Green, A., Trout, T.J., Hoogenboom, G. 2013. Evaluation of two evapotranspiration approaches simulated with the CSM-CERES-Maize model under different irrigation strategies and the impact on maize growth, development and soil moisture content for semi-arid conditions. Agricultural and Forest Meteorology. 176: 64-76. Interpretive Summary: Crop models are used to predict growth and yields under a wide range of conditions. Accuracy depends on their ability to model physiological processes and responses to environmental factors. In this modeling study, the CSM-CERES-Maize model was used to predict water use and yields of corn grown in the high plains near Greeley, CO. The model, once calibrated with field data, was able to predict water use and yields reasonably well under both fully irrigated and deficit irrigated conditions. Accurate models will help predict impacts of limited water supplies and climate change on future crop yields.
Technical Abstract: Water deficit is the most common adverse environmental condition that can seriously reduce crop productivity. Crop simulation models could assist in determining alternate crop management scenarios to deal with water-limited conditions. However, prior to the application of crop models, the appropriate performance under different soil moisture levels should be confirmed. The objective of this study was to evaluate the capability of the CSM-CERES-Maize model to simulate the impact of different irrigation regimes on maize (Zea mays L.) growth and development, evapotranspiration and soil water content under semi-arid conditions. Data from irrigation trials that were conducted in 2008 and 2010 in northeast of Greeley, Colorado were used for this assessment. The irrigation treatments were 100, 85, 70, 55 and 40% of full crop water requirements. The daily evapotranspiration (ET) was measured using Bowen ratio-energy balance (BREB) instrumentation. The ability of the CSM-CERES-Maize model using two different ET approaches, i.e., Priestley-Taylor (PT) and FAO-56 Penman-Monteith (PM), in reproducing the experimental maize growth and development data as well as the daily and seasonal ET measured with the BREB method, and soil water content based on different water regimes was analyzed. The results showed that the model with both the PT and FAO-56 PM approach simulated phenology accurately for all irrigation treatments. The CSM-CERES-Maize model simulated both grain yield and final biomass fairly well for all irrigation levels for both ET approaches. The normalized root mean square error was less than 10.2% for grain yield and 36.8% for final biomass for the PT approach and 12.1% for grain yield and 26.0% for final biomass for the FAO-56 PM approach. The model using the FAO-56 PM approach provided daily and seasonal ET values that were slightly overestimated as compared to the measured ET by the BREB method, while the PT tended to underestimate ET during late growing seasons. However, the accuracy of both ET approaches was higher than 90% as compared to the measured ET. There was a reasonable agreement between the simulated and observed water content for all four soil depths of the six irrigation treatments which were derived from both approaches. In addition, the model accurately simulated the fluctuation and time span of the cyclic variation of soil water. Overall, it can be concluded that the CSM-CERES-Maize model using the two different ET approaches, i.e., PT and FAO-56 PM, was able to simulate crop development and yield as well as ET and soil water content in response to the different irrigation regimes under semi-arid conditions. These results also confirmed that the model has the potential for use as a tool for agricultural water management under water-limited conditions.