This paper proposes a spatiotemporal fusion-based evapotranspiration inversion model (OL-SS) for grassland areas on the GEE platform. The model uses the OL processing strategy, with Landsat imagery being used as fine-resolution images and MCD43A4 imagery as coarse-resolution images, combined with GEE’s spatiotemporal fusion technology to generate 30 m resolution images. It then estimates the daily evapotranspiration of grasslands using the constant evaporation ratio method. The model was validated in the Xilin Gol League, Inner Mongolia, for grassland evapotranspiration inversion during the summer of 2015. The results show the following: 1. the OL-SS model can efficiently generate good spatiotemporal fusion results, but the fusion effect is poorer in some images due to cloud cover; 2. compared with the measured data from flux stations in grassland areas, the evapotranspiration inversion results show a good fit. The model demonstrates strong performance in grassland evapotranspiration monitoring and is suitable for the rapid estimation of daily evapotranspiration in certain grassland regions.