Cotton Irrigation Scheduling Using Remotely Sensed and Fao-56 Basal Crop Coefficients

Multispectral vegetation indices calculated from canopy reflectance measurements have been used to simulatereal-time basal crop coefficients (Kcb), which have been validated to improve evapotranspiration (ETc) estimation for severalcrops. In this article, an application of the approach was evaluated for cotton using remote sensing observations of thenormalized difference vegetation index (NDVI) to estimate Kcb as a function of NDVI. The dual crop coefficient proceduresof FAO Paper 56 (FAO-56) were used to calculate ETc and determine irrigation scheduling using Kcb estimates from remotesensing (NDVI treatment) as well as from time-based Kcb curves (FAO treatment), which were developed locally for standardcrop conditions using FAO-56 procedures. Two cotton experiments, conducted in 2002 and 2003 in central Arizona, includedsub-treatments of three levels of plant density and two levels of nitrogen management to impose a wide range of cropdevelopment and water use. The NDVI-Kcb relationships used for 2002, developed from previous data for a different cottoncultivar, row orientation, and soil type, substantially underestimated ETc, resulting in significantly less irrigation waterapplied and lower lint yields for NDVI compared to the FAO treatment. The 2002 data were used to recalibrate the NDVI-Kcbrelationships, which were then used for the NDVI treatments in 2003. The FAO Kcb curve used in 2002 described ETc andirrigation scheduling reasonably well for sparse plots, but consistently underestimated water use and soil water depletionfor the higher plant densities during the first half of the season. Consequently, an adjusted FAO Kcb curve, based on 2002results, was employed for the FAO treatment in 2003. For the 2003 experiment, estimated cotton ETc for the NDVI treatmentresulted in a mean absolute error of 9% compared to 10% for the FAO treatment, where the difference was not significantbetween treatments. However, the NDVI-Kcb relations used in 2003 greatly improved estimates for ETc compared to theprevious year, where the mean absolute error for the NDVI treatment in 2002 was 22%. Predicted ETc using the FAO Kcb curveof 2003 for typical planting density and high nitrogen conditions resulted in a mean absolute error of 10% compared to 15%in 2002. Final lint yields for 2003 were not significantly different between the two Kcb methods. Although additional researchis needed to validate remote sensing Kcb estimation for other conditions than those in these experiments, this study did notshow significant advantages for the NDVI approach over a carefully derived single FAO Kcb application. However, the NDVIapproach has the potential to further extend our present crop coefficient estimation capabilities when weather, plant density,or other factors cause cotton canopy development and water use patterns to depart from typical conditions.