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Understanding the spatio-temporal variation of actual evapotranspiration (ETa) over irrigated agricultural areas helps to manage water. Many remote sensing (RS) methods have been developed recently to estimate ETa. Nevertheless, selecting the suitable method is still a challenge. The objective of this research is to evaluate four RS methods for estimating ETa over the large-scale Gezira Scheme of Sudan. Three methods, namely Surface Energy Balance Algorithm for Land (SEBAL), Mapping EvapoTranspiration at High Resolution with Internalized Calibration (METRIC) and Simplified Surface Energy Balance (SSEB), were applied using Landsat images. Another RS dataset, i.e. ETa product from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite (MOD16A2), was also used in the comparison. The ETa methods were validated using field-scale water balance (WB) estimates during the 2004 crop season. Furthermore, the present study suggested the use of Normalized Difference Vegetation Index (NDVI) and integrated NDVI (iNDVI) as an approach to assessing the performance of the ETa estimates from RS on daily and seasonal scales, respectively. Several performance measures were evaluated, and a score was given for each method in order to extract the most valuable information for water management out of four different methods. Based on ranking criteria, SSEB gave the best performance followed by SEBAL. METRIC is not suitable for estimating ETa where ground-data are limited. MOD16A2 was less sensitive to detection of ETa at field level because of pixel resolution, but it had high score at the scheme level. All methods showed similar spatial patterns of seasonal ETa, with a decreasing ETa gradient from southeast to northeast of the scheme. In conclusion, SSEB and MOD16A2 are seen as suitable operational ETa methods on the regional scale as both methods require less application time compared to the other complex models. SSEB has the advantage of estimating ETa on field scale and on daily basis. The results of this study contribute to improving the understanding of performance of such methods in large irrigation schemes in arid climate zones. (C) 2016 Elsevier B.V. All rights reserved.