Simulation of Spatially Variable Precision Irrigation and Its Effects On Corn Growth Using CERES-Maize
Few studies have been done considering the possibility of irrigation systems in Iowa or other humid regions. Recent technological progress in precision agriculture may allow irrigation in these areas to become more economically feasible. Crop models have emerged as a method to evaluate different crop management practices such as irrigation without costly and time-consuming onsite experiments. In this study, the CERES-Maize crop model was used in conjunction with APOLLO, a shell program developed at Iowa State University, to evaluate potential improved yield in a central Iowa cornfield on a spatially and temporally variable basis. Five years of historical yield and weather data were used to calibrate the model over 100 spatially variable grids for nonirrigated conditions in the 20.25 ha field. This calibrated model then used 28 years of historical weather data to simulate three irrigation scenarios: no irrigation, scheduled uniform irrigation, and precision irrigation. 30 mm irrigations were applied when the percent of available soil water fell below 50 percent. Irrigation improved yield by at least 1000 kg ha-1 in half of the years simulated, and also showed to have less variability both spatially and temporally. Precision irrigation showed slightly higher yields than scheduled uniform irrigation. Spatial variability of yield was most influence by topography, with the largest improvements occurring on steep sideslopes and hilltops. Assuming use of a center pivot irrigation system, irrigation showed economic returns in only three of the 28 years included in the study. High capital costs were the leading restrictor of economic feasibility.
This is an ASABE Meeting Presentation, Paper No. 062119.