Abstract: Water depletion in irrigated agriculture is recognized as a major cause of water scarcity. For agricultural water resource management, the precise measurement of field evapotranspiration is critical because it plays a critical role in both energy and water cycles. As one of the major irrigation regions in the world, Pakistan’s agricultural areas necessitate the accurate calculation of actual evapotranspiration using remote sensing technology for more advanced agricultural water resource management. This study estimated the real evapotranspiration in the agricultural areas of Pakistan during 2019–2020 using MODIS, meteorological and digital elevation model (DEM) data and the METRIC model. This study analyzed the spatiotemporal distribution patterns of evapotranspiration throughout several crop growth stages to present empirical evidence supporting the prudent use of agricultural water resources in Pakistan. 1) Using lysimeters to compare the METRIC estimation results with the data from agricultural stations, the correlation coefficients were found to be 0.65 and 0.84 at daily and monthly scales, respectively, with root mean square errors of 1.2 mm∙d⁻¹ and 25 mm∙month⁻¹, respectively. Additionally, comparing METRIC estimation findings with ETMonitor products at the spatial scale showed that the former were more accurate. 2) In the agricultural areas of Pakistan, the planting structure was directly associated with the spatial distribution of evapotranspiration, which decreased progressively from north to south. For wheat, cotton, rice, and sugarcane, the evapotranspiration were 392, 652, 745, and 1224 mm, respectively, for the whole growth season. The rate of evapotranspiration in Punjab Province was higher than that in Sindh Province for the same crop during the growth season. 3) Throughout the growing season, wheat showed a pattern of monthly evapotranspiration that initially decreased, then increased, and finally decreased. The growth period observed for cotton showed a “bimodal” monthly evapotranspiration pattern in Sindh Province, and a “unimodal” monthly evapotranspiration pattern in Punjab Province. During the growth season, the monthly evapotranspiration patterns of rice and sugarcane were “unimodal”. In addition to providing a methodology for crop-scale or regional evapotranspiration estimation based on remote sensing, this study achieved the localization and applicability analysis of the METRIC model in Pakistan agricultural areas. This is significant because it reveals the spatial and temporal characteristics of evapotranspiration and water consumption of various crops and helps manage regional agricultural water resources.