Grady Miller, Michael Dukes, and Mark Mitchell. University of Florida, 1545 WM Fifield Hall, Po Box 110670, Gainesville, FL 32611-0670
Because of the number of golf courses in Florida, and their visibility, there is a public concern that the golf industry is wasteful of water resources. When issuing consumptive use permits (CUP), various water-use models are used by Florida's five Water Management Districts to estimate irrigation requires on golf courses. The St. Johns River Water Management District uses the Agricultural Field Scale Irrigation Requirement Simulation (AFSIRS) model with available default data to predict irrigation requirements for all golf courses in their jurisdiction. In this study, data was collected at five golf courses to use in the AFSIRS model for comparison to irrigation requirements made using default data. Irrigation system distribution uniformity, rooting depths, and weather data were collected from each golf course. Updated crop coefficients for turfgrass were used in place of the default values. Sensitivity analysis was used to determine which inputs had the greatest influence on the model outputs. When actual data was used, the irrigation requirements predicted increased between 15 and 46 cm per year for the golf courses. Distribution uniformity had the greatest impact on the predicted irrigation requirements. When only distribution uniformities were substituted for the default irrigation system efficiency, irrigation requirement increased between 13 and 76 cm per year. Sensitivity analysis further indicated that irrigation system efficiency inputs have the greatest influence on the predicted irrigation requirements made by the AFSIRS model. Changing a system efficacy from 40% to 80%, a 100% increase, results in a 65% decrease in irrigation requirement. Using actual data in place of default values in the AFSIRS model can result in site-specific estimates of irrigation requirements on golf courses. Because distribution uniformity and crop coefficient values have the greatest impact on irrigation requirements predicted using the AFSIRS model, these data need to be measured the highest accuracy.
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