REMOTE SENSING FOR CROP AND WATER MANAGEMENT IN IRRIGATED AGRICULTURE
Location: Water Management and Conservation Research
Title: Evaluation of the CSM-CROPSIM-CERES-Wheat Model as a Tool for Crop Water Management
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 25, 2009
Publication Date: March 15, 2010
Citation: Thorp, K.R., Hunsaker, D.J., French, A.N., White, J.W., Clarke, T.R., Pinter Jr, P.J. 2010. Evaluation of the CSM-CROPSIM-CERES-Wheat Model as a Tool for Crop Water Management. Transactions of the ASABE. 53(1):87-102.
Interpretive Summary: Efficient use of irrigation water is essential for sustainable agriculture in water scarce regions of the world. A cost effective way to manage and conserve water is to develop crop simulation models, which can forecast crop water needs and greatly improve outcomes from irrigation scheduling. In this study the CSM-CROPSIM-CERES-Wheat model was evaluated using two years of experimental data collected at Maricopa, Arizona. Results from the evaluation showed that soil water content could be accurately predicted usually better than 5.3 mm. Retrospective irrigation scheduling with the wheat model also showed that yields could be increased by 1.9% while reducing irrigation amounts by 31.4%. These results will be useful to crop modelers and water use managers.
Development and implementation of improved methodologies for irrigation scheduling will conserve valuable water resources in agricultural regions that depend on irrigation. To address this problem for conditions in central Arizona, we have evaluated the CSM-CROPSIM-CERES-Wheat model using measured wheat growth and soil water data from two plot-level irrigation scheduling experiments conducted during the winters of 2003-2004 and 2004-2005. Wheat plots were managed using two FAO-56-based irrigation scheduling approaches at three planting densities (~75, ~150, and ~300 plant m-2) and at two nitrogen application rates (~80 and ~215 kg ha-1 yr-1). For the 32 treatment plots, the model simulated wheat yield with relative root mean squared errors of 12.0% and 19.7% for the 2003-2004 model calibration season and the 2004-2005 model validation season, respectively. Time series plots of measured and simulated leaf, stem, and spike mass and green leaf area index demonstrated favorable wheat growth responses to experimental treatments and seasonal weather and management variability. Using simulated annealing optimization to adjust soil parameters to minimize error between measured and simulated soil water contents, the model was able to quantify soil water contents in eight soil layers with median root mean squared errors of 3.0 and 5.3 mm for calibration and validation seasons, respectively. Rescheduling the irrigations using hindcast simulations with the crop model reduced simulated effective irrigation amounts by median values of 20.2% and 31.4% and increased simulated wheat yields by median values of 2.4% and 1.9% for the 2003-2004 and 2004-2005 wheat seasons, respectively, as compared to the original irrigation schedules devised from FAO-56 methods. The results suggest that further development of the CSM-CROPSIM-CERES-Wheat model as a tool for irrigation scheduling may be an effective approach to improve irrigation water management for wheat crops in Arizona.