Real evapotranspiration (ETR) is a key variable in socio-ecological systems since it is related to the food supply, climate regulation, among others. Additionally, ETR plays a significant role in determining water yield (WY) at the catchment level, which directly impacts water availability for consumption and irrigation. Therefore, it is essential to quantify ETR and WY fluctuations in response to various human pressures to enable comprehensive water planning. In recent decades, remote sensing has become increasingly employed worldwide for hydrological monitoring and estimating ETR. In Uruguay, several approaches have been attempted to quantify ETR. However, there is still a lack of assessments concerning the performance of different products, particularly those using remote sensing. The main objectives of this article were twofold:a) to evaluate the performance of various spatial explicit approaches for estimating real ETR and b) to estimate and analyse the variability in WY derived from the different ETR products for three climatically contrasting years. To achieve these objectives, we utilized four remote sensing ETR products:the Penman?Monteith?Leuning model (PMLv2), the MODIS product, the Simplified Jackson Model based on Landsat images and INTA-SEPA model based on NOAA-AVHRR images. We also employed two water balance models at two scales:national (derived from the National Institute for Agricultural Research of Uruguay, INIA) and micro-watershed level. Our results indicate that MODIS and PMLv2 remote sensing products exhibited better performances compared to the other approaches. These products provided the highest spatial (500 m) and temporal (8 days) resolution, effectively capturing seasonal differences between land-covers. Moreover, they showed positive and strong correlations with annual precipitation and productivity. The discrepancies observed between products have direct implications on the estimation of WY, not only in terms of quantity but also in terms of spatial patterns. Future studies should explore the application of MODIS and PMLv2 ETR estimations for understanding hydrological and ecological processes, conducting climate change research, detecting and mitigating agricultural drought, and managing water resources effectively. © 2023 Elsevier B.V. All rights reserved.