Actual evapotranspiration is an important parameter and its accurate estimation is critical for the design, operation, and management of irrigation systems. However, the scarcity of metrological data required to estimate reference evapotranspiration (ETo) in poor countries and the lack of spatial variability of crop coefficient (Kc) are clear barriers to the proper management of irrigation water. The main objective of this study was to estimate crop evapotranspiration (ETc) using remotely sensed ETo and Kc derived from Normal Difference Vegetation index (NDVI). The study was carried out in the Koga Irrigation Project site for a wheat crop during growing seasons. For this purpose, FAO portal to monitor water productivity through open-access of remotely sensed derived data (WaPOR) ETo, Moderate-resolution imaging spectroradiometer (MODIS) potential evapotranspiration (PET), and Sentinel -2B images were acquired. The atmospheric corrections of sentinel-2B images were conducted and processed NDVI on a SeNtinel Application Platform (SNAP) and mapped on Arc GIS. The point values of WaPOR and MODIS PET were extracted for Bahir dar and Dangla stations and compared with FAO Penman-Monteith ETo. The result indicated that the WaPOR ETo value is most fitting for Dangla whereas MODIS PET is better for Bahir dar. However, MODIS PET was selected for ETc estimation due to its advantage of high spatial resolution. The maximum NDVI value for extracted wheat field plots was 0.8 at mid-stage in early March whereas a minimum was 0.23 at an initial stage. A simple linear regression model was developed to relate NDVI values and Kc FAO values, there was reported that a strong relation between NDVI-estimated Kc and FAO Kc with a correlation coefficient (R 2 ) of 0.95, root mean square error (RMSE) of 0.08, mean absolute error (MAE) of 0.07, and mean square error (MSE) of 0.01. Wheat crop evapotranspiration maps were created as an output of Kc derived from NDVI and ETo computed from MODIS PET values. These results showed that ETc values were low at initial, early development, and at an end of late-stage, whereas ETc value was high (5.51 mm/day) at mid-stage, additionally, the volume of crop water requirement was estimated and mapped. Based on the results can be concluded that ETc maps have generated from remotely sensed data are an appropriate technique for quantifying the spatial and temporal variability of crop water use in the field. Using that, farmers can enhance water use efficiency at the field level. The remote sensing data can be valuable for future irrigation water resource planning and to recover irrigation management in areas where the metrological station is scarce or unavailable.