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Components of a satellite-based system for estimating the crop water requirements of irrigated vegetation have been combined, applied, and tested against field data in the Yaqui Valley, northwest Mexico. Frequent satellite observations have the potential to provide snap shots of cloud variability at the high spatial and temporal resolutions that are needed for making simple, near real-time estimates of incoming solar radiation and, thus, daytime evaporation required for irrigation scheduling. Less frequent polar orbiting satellites offer the capacity of following the vegetation development at higher spatial resolution. The operational framework for obtaining cloud cover has been developed and applied using hourly sampled, 1 km resolution, GOES-10 data received in real-time. The high-resolution, cloud-screening algorithm has proved to be efficient and reliable and has been used to provide high-resolution (4 km) estimates of solar radiation. Relationships between vegetation indices (NDVI and SAVI) and crop coefficients (the ratio of measured to reference evapotranspiration) have been derived with four different models (Shuttleworth, Penman, Priestley–Taylor and Makkink), using ground-based surface reflectance measured over the crop. Continuous measurements of surface fluxes and other meteorological variables were made following almost the entire vegetative cycle of the plant using a station equipped with standard meteorological instruments and an eddy-correlation system. Actual evapotranspiration was computed as the product of the estimated crop coefficients, derived from field radiometer measurements, and reference evapotranspiration. In comparison with ground data, RMSE values are on the order of 1 mm per day. Finally the opportunity to use high-resolution satellite data to make near real-time estimates of crop evaporation is discussed. [ABSTRACT FROM AUTHOR]