Remote Sensing Derived Crop Coefficient for Estimating Crop Water Requirements for Irrigated Sorghum in the Gezira Scheme, Sudan

Abstract

Improved management of crop water requires accurate scheduling of irrigation which, in turn, requires accurate calculation of actual daily evapotranspiration (ETa). This study was carried out to examine seasonal changes in crop coefficients and evapotranspiration values for sorghum irrigated in the Gezira scheme, with the use of remote sensing data and field measurements. Three methods, namely remote sensing-derived kc, Farbrother kc (experimental) and FAO kc, revealed that the crop coefficient for sorghum reached growing season peaks of approximately 1.15, 1.21, and 1.17, respectively, at the beginning of October. The crop coefficient, derived from remote sensing data, varied over the growing season from 0.62 in the initial growth stage, 1.15 in the mid-season stage to 0.58 at harvest. The total ETc over the growing season of irrigated sorghum estimated by remote sensing-derived kc, experimental kc and FAO kc was 674, 704, and 642 mm, respectively. The ETc by the three methods, combined with the Penman-Monteith reference ET0, was also compared with the actual ET measured by the water balance approach. Statistical analysis showed that the remote sensing-derived kc was superior to the others in all regression parameters. This study demonstrates that remote sensing data are a very useful tool for estimating water requirements for field crops, hence providing irrigation decision makers with information not available before.