Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT‐JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM‐MOD), and Penman–Monteith Nagler model (PM‐VI). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (%). As for PM‐VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land‐use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.

Global climate predictions and possible environmental impacts have an increasing source of concern in recent years. Analyses of the impacts of climate change scenarios on regional hydrology are required to design effective adaptation strategies for specific river basins. This study focuses on assessment of future climate change impacts on water resources of the Mundaú River Basin (MRB), in Brazil, using the Soil Water Assessment Tool (SWAT) and Regional Climate Models (RCMs) Eta‐MIROC5 and Eta‐HadGEM2, for three time periods under two Representative Concentration Pathways (RCPs). In general, climate models predict that the MRB will experience significant annual precipitation decreases, between 0.4% (1,087.45 mm) and 25.3% (815.59 mm), in both scenarios (RCP 4.5 and RCP 8.5) respectively, when compared to the observed period (2003–2016). Maximum and minimum temperature increases up to 2.3°C and 0.65°C under the RCP 4.5 scenario, and up to 4.3°C and 2.2°C under the RCP 8.5 scenario. SWAT simulations predict substantial surface runoff decreases with a minimum average annual value of 21.3 mm for the RCP 8.5 in medium‐term. Additionally, actual evapotranspiration (ET) is predicted to decrease from 780.77 to a minimum of 648.1 mm, although increases in potential evapotranspiration (ET₀) are expected. In general, annual streamflow also is expected to decrease, more severely under RCP 8.5 conditions, reaching a drop of approximately 66.7% (15.2 m³·s⁻¹), compared to the observed period (45.5 m³·s⁻¹). Seasonal streamflow is predicted to decrease for both models, in both rainy and dry seasons, except for medium‐term of the Eta‐HadGEM2. Although there are still some uncertainties associated with climate models, the findings from this study can assist water resource managers in management decisions for appropriate water use, development of public policies that favour sustainability, and adoption of mitigation and prevention practices to ensure water security in the basin.