Wheat basal crop coefficients determined by normalized difference vegetation index

Crop coefficient methodologies are widely used to estimate actual crop evapotranspiration (ET_c) for determining irrigation scheduling. Generalized crop coefficient curves presented in the literature are limited to providing estimates of ET_c for “optimum” crop condition within a field, which often need to be modified for local conditions and cultural practices, as well as adjusted for the variations from normal crop and weather conditions that might occur during a given growing season. Consequently, the uncertainties associated with generalized crop coefficients can result in ET_c estimates that are significantly different from actual ET_c, which could ultimately contribute to poor irrigation water management. Some important crop properties such as percent cover and leaf area index have been modeled with various vegetation indices (VIs), providing a means to quantify real-time crop variations from remotely-sensed VI observations. Limited research has also shown that VIs can be used to estimate the basal crop coefficient (K _cb) for several crops, including corn and cotton. The objective of this research was to develop a model for estimating K _cb values from observations of the normalized difference vegetation index (NDVI) for spring wheat. The K _cb data were derived from back-calculations of the FAO-56 dual crop coefficient procedures using field data obtained during two wheat experiments conducted during 1993–1994 and 1995–1996 in Maricopa, Arizona. The performance of the K _cb model for estimating ET_c was evaluated using data from a third wheat experiment in 1996–1997, also in Maricopa, Arizona. The K _cb was modeled as a function of a normalized quantity for NDVI, using a third-order polynomial regression relationship (r ²=0.90, n=232). The estimated seasonal ET_c for the 1996–1997 season agreed to within −33 mm (−5%) to 18 mm (3%) of measured ET_c. However, the mean absolute percent difference between the estimated and measured daily ET_c varied from 9% to 10%, which was similar to the 10% variation for K _cb that was unexplained by NDVI. The preliminary evaluation suggests that remotely-sensed NDVI observations could provide real-time K _cb estimates for determining the actual wheat ET_c during the growing season.