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Predicting Crop Yields with the Agricultural Reference Index for Drought

Woli, P., Jones, J. W., Ingram, K. T., Hoogenboom, G.
Journal of agronomy and crop science 2014 v.200 no.3 pp. 163-171
Daily Values, corn, cotton, crop yield, crops, drought, growing season, meteorological data, models, peanuts, prediction, regression analysis, soybeans, water stress, United States
A generic agricultural drought index, called Agricultural Reference Index for Drought (ARID), was designed recently to quantify water stress for use in predicting crop yield loss from drought. This study evaluated ARID in terms of its ability to predict crop yields. Daily historical weather data and yields of cotton, maize, peanut and soybean were obtained for several locations and years in the south‐eastern USA. Daily values of ARID were computed for each location and converted to monthly average values. Using regression analyses of crop yields vs. monthly ARID values during the crop growing season, ARID‐yield relationships were developed for each crop. The ability of ARID to predict yield loss from drought was evaluated using the root mean square error (RMSE), the Willmott index and the modelling efficiency (ME). The ARID‐based yield models predicted relative yields with the RMSE values of 0.144, 0.087, 0.089 and 0.142 (kg ha⁻¹ yield per kg ha⁻¹potential yield); the Willmott index values of 0.70, 0.92, 0.86 and 0.79; and the ME values of 0.33, 0.73, 0.60 and 0.49 for cotton, maize, peanut and soybean, respectively. These values indicated that the ARID‐based yield models can predict the yield loss from drought for these crops with reasonable accuracy.