This study investigates the performance of Optical-microwave scintillometers (OMS) in quantifying latent heat flux (LE) and assess its effectiveness in validating the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) model, driven by LANDSAT satellite data. The study was conducted over a drip-irrigated olive orchard within the Agdal olive yard in central Morocco, covering a full annual cycle from May 2022 to May 2023. In the first phase, OMS-derived LE was compared against eddy-covariance (EC) measurements over the entire study period. The comparison showed reasonable agreement, with a correlation of determination (R2) of 0.77, and a root mean square error (RMSE) of 26.31 W m-2. Discrepancies were mainly attributed to differences in the spatial footprints, as OMS integrates fluxes over a much larger area than EC. In the second phase, LE estimates from the SPARSE model - driven by LANDSAT-8/9 data and spatially weighted according to OMS and EC footprints - were evaluated against observations. The model showed good agreement, with R2 values of 0.83(EC) and 0.71(OMS), and RMSEs of 28.5 and 23.65 W m-2, respectively. However, when inputs were aggregated over the entire Agdal unit without footprint weighting, performance declined significantly for EC( R2=0.53, RMSE=40.16 W m-2), while OMS-based validation remained consistent, indicating its superior ability to capture area-averaged fluxes at larger scales. These findings highlight OMS as a robust tool for measuring large-scale LE fluxes, and support the use of OMS as a more reliable benchmark for large-scale model evaluations.