This study aimed to evaluate the accuracy and performance of the SEBAL and WaPOR algorithms for estimating actual evapotranspiration (ETa) and actual evapotranspiration-based water productivity (WPET) in the Tashk–Bakhtegan sub-basin in Fars Province and the Maroon–Jarahi sub-basin in Khuzestan Province, Iran. Field data, including irrigation water volume, crop yield, and biomass, were collected from 22 farms and orchards during the 2022–2023 growing season, and ETa and WPET were calculated based on these data. To estimate ETa, WaPOR Version 3 products and Landsat 8 satellite imagery required for implementing the SEBAL algorithm were processed in the Google Earth Engine environment. The performance of the two algorithms was evaluated using the coefficient of determination (R²) and root mean square error (RMSE). The results showed that the performance of both algorithms in estimating ETa depended on the study area and crop type, and that their agreement with the reference data varied among different areas. Overall, the SEBAL algorithm showed better agreement with field data, although WaPOR provided estimates closer to the reference values for some crops and under certain spatial conditions. Although SEBAL showed better performance in terms of accuracy, WaPOR, owing to its easy accessibility, extensive spatial coverage, and continuous monitoring capability, is a suitable option for monitoring and managing agricultural water resources. The findings demonstrated that the selection of an appropriate algorithm for estimating ETa and WPET depends on climatic conditions, crop type, and the scale of the study, and that each approach can be used for agricultural water resources monitoring and management according to the specific objectives of the study.