Irrigation performance can be improved if more precise estimations of spatially distributed crop water use are available. A common method of estimating crop evapotranspiration for irrigated areas is multiplying a reference evapotranspiration by a crop coefficient. This coefficient could be derived from multispectral vegetation indices obtained by remote sensing means. This study combined field radiometry, satellite measurements of canopy reflectance and direct crop monitoring during the growth cycle of sugarbeet and cotton crops. Detailed field radiometry along 2.5‐m transects was performed perpendicularly to the crop rows to obtain canopy reflectance. Ancillary measurements of green ground cover, plant height, leaf area index and biomass were conducted in the cropped strip covered by the radiometer field‐of‐view. Measurements were also made at the time of each Landsat‐5 overpass on two commercial fields, one grown with sugarbeet and the other with cotton. Crop height and ground cover were determined weekly in these two fields as well as in three additional sugarbeet fields and one cotton field. Field and satellite observations of canopy reflectance yielded similar results. Two vegetation indices derived from the canopy reflectance, the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI) were evaluated for this application. Although both indices described the crop growth well, the SAVI was linearly related to relevant crop growth variables and independent of the soil characteristics. Moreover, it was found that SAVI could be related to ground cover using a simple model with the maximum and minimum SAVI as parameters. A simple equation was formulated to calculate basal crop coefficients from SAVI through the estimation of ground cover. Based on these findings, crop water use variability was analysed in one large sample of sugarbeet and cotton fields, both within an irrigated area of Andalucia, Southern Spain, where reference evapotranspiration is provided through the web site of the regional network of meteorological stations. The pairs of data yield‐evapotranspiration were highly variable in the sugarbeet fields and below a linear yield function published in the literature. The pairs of data yield‐evapotranspiration for the cotton field were close to a curvilinear yield function obtained previously in a similar environment.

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