Wheat basal crop coefficients determined by normalized difference vegetation index

Crop coefficient methodologies are widely used to estimate actual crop evapotranspiration (ETc) for determining irrigation scheduling. Generalized crop coefficient curves presented in the literature are limited to providing estimates of ETc 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 ETc estimates that are significantly different from actual ETc, 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 (Kcb) for several crops, including corn and cotton. The objective of this research was to develop a model for estimating Kcb values from observations of the normalized difference vegetation index (NDVI) for spring wheat. The Kcb 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 Kcb model for estimating ETc was evaluated using data from a third wheat experiment in 1996-1997, also in Maricopa, Arizona. The Kcb was modeled as a function of a normalized quantity for NDVI, using a third-order polynomial regression relationship (r2=0.90, n=232). The estimated seasonal ETc for the 1996-1997 season agreed to within -33 mm ( -5%) to 18 mm (3%) of measured ETc. However, the mean absolute percent difference between the estimated and measured daily ETc 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 Kcb estimates for determining the actual wheat ETc during the growing season.