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ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Water Management and Conservation Research » Research » Publications at this Location » Publication #165501

Title: SCHEDULING COTTON IRRIGATIONS USING REMOTELY-SENSED BASAL CROP COEFFICIENTS AND FAO-56

Author
item Hunsaker, Douglas - Doug
item PINTER JR, PAUL
item CLARKE, THOMAS
item FITZGERALD, GLENN
item Kimball, Bruce
item BARNES, EDWARD - SOTTON INC, CARY ND
item SILVERTOOTH, JEFFREY - THE UNIV OF ARIZONA
item Hagler, James

Submitted to: Proceedings of American Society of Agricultural Engineers
Publication Type: Proceedings
Publication Acceptance Date: 5/31/2004
Publication Date: 8/1/2004
Citation: Hunsaker, D.J., Pinter Jr, P.J., Clarke, T.R., Fitzgerald, G.J., Kimball, B.A., Barnes, E.M., Silvertooth, J.C., Hagler, J.R. 2004. Scheduling cotton irrigations using remotely-sensed basal crop coefficients and fao-56. Proceedings of American Society of Agricultural Engineers. CD-Rom 42090.

Interpretive Summary: To improve crop water use efficiency, reliable techniques are needed to help farmers decide when to irrigate their crops and how much water to apply. To determine crop irrigation schedules, standard crop coefficient (Kc) curves are used with weather information to estimate how much of the water in the soil has been taken up by the crop in evapotranspiration (ET), which is the combined crop transpiration plus water evaporation from the soil. However, these standard Kc curves can often be in error, resulting in imprecise estimates of actual ET requirements, leading to poor irrigation scheduling and inefficient water use. This research tested a technique which corrects the Kc curve for cotton depending on how the cotton canopy develops during the season. Frequent remote sensing observations of cotton canopy reflectances were made during the season to continually correct the Kc curve for determining proper irrigation scheduling. Results indicate that the remote sensing technique produced more precise estimates of measured ET than the standard Kc curve over a wide range of cotton growth conditions. However, because irrigation scheduling determined from the remote sensing technique did not increase cotton yields over the standard method, future work is needed to further improve the method. Ultimately, this research is expected to provide a means to more accurately determine actual crop ET requirements, thus, helping growers with optimal water use management, which will be of interest to farmers, farm consultants, government agencies, and the irrigation industry.

Technical Abstract: Techniques to more accurately quantify crop evapotranspiration (ETc) are needed for determining crop water needs and appropriate irrigation scheduling. In this study, remotely sensed observations of the normalized difference vegetation index (NDVI) were used to estimate cotton basal crop coefficients (Kcb), which were then applied within the dual crop coefficient procedures of the Food and Agricultural Organization (FAO), Paper 56 (FAO-56) to calculate daily ETc. An experiment in central Arizona during 2003 compared irrigation scheduling using a remotely sensed Kcb technique (NDVI treatment) with the FAO-56 Kcb curve (FAO treatment). The FAO curve was locally developed for optimum crop conditions and standard cotton density. Final lint yield means were not significantly different between the two irrigation methods, which included sub-treatments of two levels of nitrogen and three plant densities. However, NDVI attained higher yields under low N input, whereas FAO generally had higher yields under high N. The ETc estimated using the NDVI-Kcb method was in closer agreement with measured cumulative ETc than the FAO Kcb. For high N treatments, the mean absolute differences between measured and estimated cumulative ETc during the growing season for typical, dense, and sparse populations (10, 20, and 5 plants m-2, respectively) were 4, 17, and 4 mm, respectively, for NDVI, whereas they were10, 32, and 13 mm, respectively, for FAO. Although additional research is needed for improving our remote sensing technique, it potentially offers an improvement over the FAO Kcb curve for quantifying actual ETc.