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On-Farm Evaluation of the Model EPIC for Simulating Irrigation Demand

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  033039,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.13846) @2003
Authors:   Larry C. Guerra, Gerrit Hoogenboom, James E. Hook, Daniel L. Thomas, Vijendra K. Boken, Kerry A. Harrison
Keywords:   Cotton, Maize, Peanut, Irrigation, Decision Making, Crop Simulation

Crop simulation models can be valuable tools for irrigation management. However, these models must be evaluated with field data over a wide range of environmental conditions and crop management scenarios to provide credibility for applications and decision making. The objective of the present study was to evaluate the performance of the crop simulation model Environmental Policy Integrated Climate (EPIC) in simulating irrigation requirements for three major crops grown in farmers' fields in Georgia. We assumed that weather conditions and soil or plant water status were the most dominant factors influencing farmers' decisions on when to irrigate and how much water to apply. We then compared the simulated irrigation requirements with the amount of water that the farmers actually applied. For cotton, farmers applied less water than was needed. In contrast, farmers applied more water than was needed for maize and peanut. Statistical tests showed that the model EPIC performed better for cotton than for maize and peanut. The RMSD for total amount of irrigation was 114 mm for cotton, 128 mm for peanut, and 138 mm for maize. The major component of the mean squared deviation (MSD = RMSD2) for total amount of irrigation was the lack of correlation weighted by the standard deviations (LCS). This indicated that the irrigation strategy as described in the model implementation was not as sensitive to the factors responsible for the variability in total irrigation water use in farmers' fields. Since rainfall variability, crop rotations, water availability, scheduling approaches, and economic viability all contribute to the farmers' decisions about irrigation, the need for an effective understanding of the farmers' decision making process is very important.

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