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Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index
Authors:Douglas?J.?Hunsaker  author-information"  >  author-information__contact u-icon-before"  >  mailto:dhunsaker@uswcl.ars.ag.gov"   title="  dhunsaker@uswcl.ars.ag.gov"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Paul?J.?Pinter  Suffix"  >Jr.,Edward?M.?Barnes,Bruce?A.?Kimball
Affiliation:(1) US Water Conservation Laboratory, USDA-ARS, 4331 East Broadway Road, Phoenix, AZ 85040, USA;(2) Cotton Incorporated, 6399 Weston Parkway, Cary, NC 27513, USA
Abstract:Crop coefficients are a widely used and universally accepted method for estimating the crop evapotranspiration (ETc) component in irrigation scheduling programs. However, uncertainties of generalized basal crop coefficient (Kcb) curves can contribute to ETc estimates that are substantially different from actual ETc. Limited research with corn has shown improvements to irrigation scheduling due to better water-use estimation and more appropriate timing of irrigations when Kcb estimates derived from remotely sensed multispectral vegetation indices (VIs) were incorporated into irrigation-scheduling algorithms. The purpose of this article was to develop and evaluate a Kcb estimation model based on observations of the normalized difference vegetation index (NDVI) for a full-season cotton grown in the desert southwestern USA. The Kcb data used in developing the relationship with NDVI were derived from back-calculations of the FAO-56 dual crop coefficient procedures using field data obtained during two cotton experiments conducted during 1990 and 1991 at a site in central Arizona. The estimation model consisted of two regression relations: a linear function of Kcb versus NDVI (r2=0.97, n=68) used to estimate Kcb from early vegetative growth to effective full cover, and a multiple regression of Kcb as a function of NDVI and cumulative growing-degree-days (GDD) (r2=0.82, n=64) used to estimate Kcb after effective full cover was attained. The NDVI for cotton at effective full cover was ~0.80; this value was used to mark the point at which the model transferred from the linear to the multiple regression function. An initial evaluation of the performance of the model was made by incorporating Kcb estimates, based on NDVI measurements and the developed regression functions, within the FAO-56 dual procedures and comparing the estimated ETc with field observations from two cotton plots collected during an experiment in central Arizona in 1998. Preliminary results indicate that the ETc based on the NDVI-Kcb model provided close estimates of actual ETc.Communicated by R. Evans
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