# Performance of Satellite-Based Evapotranspiration
## 5 Discussion and Conclusions  
Summer evapotranspiration is becoming a crucial indicator for irrigation plans and drought management in the Chilean temperate pastures. A suite of four remote sensing surface energy balance (SEB) models and two readily available global evapotranspiration products were validated using ground observations. Surface temperature (T\({}_{\mathrm{s}}\)) was validated in a single point in the study area and the results are satisfactory, with an RMSE of 2.66 [K] for 42 days with data availability between 2014-2017. However, this validation could be improved by new measurement campaigns and equipping additional stations to measure T\({}_{\mathrm{s}}\) and determine in-situ emissivity, considering the phenology of grasslands under moisture limitation. Variations in phenology affect the emissivity by up to 3% due to surface moisture [60; 61] and therefore impact the proportion of soil and vegetation cover. Our results provided the first validation of surface temperature in southern Chile at high spatial resolution to estimate accurately crop water demand at regional scale. The models SSEBop and SEBS do not solve the dT under the selection of anchors pixels and probably the assumption of H and R\({}_{\mathrm{n}}\) can be more adaptable for retrievals at smaller spatial scales. The models SEBAL and METRIC require the selection of an extreme condition to estimate H and \(\lambda\)E. This selection procedure affects the performance of those models over temperate pastures in the southern Chile. Previous studies have shown that the assumption of extreme conditions lead to uncertainties in ET\({}_{\mathrm{a}}\) due to the subjectivity of pixel selection and range of soil moisture conditions in the study domain [62; 63; 64]. However, if the application of these models in the study region is limited to smaller areas, their performance might improve substantially. SEBS evapotranspiration estimates are well correlated with the observations in Oromo (R\({}^{2}\) = 0.83) but the high sensitivity of the model to R\({}_{\mathrm{n}}\) results in an overestimation. The global evapotranspiration products showed marked differences in their performance. GLEAM does not represent well ET\({}_{\mathrm{a}}\) at the local scale (RMSE over 1.45 [mm day\({}^{-1}\)]) and overestimates it during autumn and winter, likely because of mixed land covers in the coarse pixel of 25 km. The PML_V2 model, which is based on moderate-resolution biophysical estimation of ET\({}_{\mathrm{a}}\) coupled with GPP, showed high accuracy over southern grasslands, with a correlation coefficient of 80% and RMSE lower than 1 mm day\({}^{-1}\). A spatial comparison between SSEBop and the global products resampled to the same resolution (Supplementary Materials Figure S3) showed that GLEAM does not have a good performance, reaching on average a R\({}^{2}\) of 0.4. In contrast, PML_V2 had an overall R\({}^{2}\) = 0.8 at exception of Chiloe Island, where the spatial correlation is lower (R = 0.3 to 0.5). This finding indicates that PML_V2 can be used as a high-quality reference for evapotranspiration at the scale of 500 m over the vast continental grasslands across Los Rios and Los Lagos regions. Annual precipitation is twice annual evapotranspiration in the region (Table 1), but summer evapotranspiration exceeded precipitation during recent droughts. For this reason, validating actual evapotranspiration at regional scale for grasslands of southern Chile using satellite and meteorological data is essential to accurately determine the actual water consumption of grasslands. Using this information, it is possible to promote efficient irrigation programs that can correct the water deficit during the critical spring-summer period. This can effectively reduce the water footprint of regional pastoral systems, avoiding the extra irrigation of grasslands and promoting better practices to reduce energy and water consumption.