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Evaluation of on-farm irrigation applications using the simulation model EPIC
Authors:L C Guerra  G Hoogenboom  J E Hook  D L Thomas  V K Boken  K A Harrison
Institution:(1) Department of Biological and Agricultural Engineering, The University of Georgia, 1109 Experiment Street, Griffin, GA 30223-1797, USA;(2) National Environmentally Sound Production Agriculture Laboratory, The University of Georgia, Tifton, GA 31793-0748, USA;(3) Department of Biological and Agricultural Engineering, Louisiana State University and the LSU AgCenter, Baton Rouge, LA 70803, USA;(4) Department of Biological and Agricultural Engineering, The University of Georgia, Tifton, GA 31793-0748, USA
Abstract:An understanding of water needs in agriculture is a critical input in resolving the water resource issues that confront many southeastern and other US states. The objective of this study was to evaluate on-farm irrigation applications for three major crops grown in Georgia, USA using the Environmental Policy Integrated Climate (EPIC) model. For cotton, 16, 58, and 75 farmersrsquo fields in 2000, 2001, and 2002, respectively, were selected from among the Agricultural Water Pumping (AWP) program sites across the state of Georgia. For maize, 9, 20, and 28 fields were selected in 2000, 2001, and 2002, respectively, and for peanut, 18, 51, and 54 fields were selected in 2000, 2001, and 2002, respectively. The majority of these fields were located in the southwest region of Georgia, where traditional row-crop agriculture is most dominant. We compared the simulated irrigation requirements with the amount of water that the farmers actually applied during the 2000, 2001, and 2002 growing seasons. For cotton and peanut, the means of farmer-applied irrigation amounts and simulated irrigation requirements agreed very well, with similar values for root mean squared deviation (RMSD) of the two crops. For maize, good agreement between simulated and farmer-applied irrigation amounts were found only in 2001. Farmers applied more water to their maize crop when compared to simulated irrigation requirements, especially when rainfall was very low and potential evapotranspiration was high during the 2000 and 2002 growing seasons. The component of the mean squared deviation (MSD = RMSD2) related to the pattern of variability in seasonal irrigation applications contributed most to MSD. Accurate estimates of the mean and the magnitude of variability in seasonal irrigation applications could be very useful for the estimation of overall water use by agriculture in Georgia and other southeastern states. This study showed that the EPIC model would be an adequate tool for this purpose; potential users could include policy makers, planners and regulators, including the Georgia Department of Natural Resources (DNR).
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