Estimating evapotranspiration (ET) is of the highest importance for understanding and eventually intervening in the water cycle of natural systems. ET is one of the major factors influencing climate change, at local, regional and global levels, and net primary productivity models, but it is difficult to measure and predict. Remote sensing cannot provide a direct measurement of Evapotranspiration (ET), but it can provide a reasonably good estimate of the Evaporative Fraction (EF), defined as the ratio of ET and available energy. In this study, a surface energy balance method, which combines meteorological observations with spectral data derived from remote sensing measurements, was used to estimate the ET. The modified (SEBAL) Surface Energy Balance Algorithm for Land has been applied to data from the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA-14 satellite and from the Landsat Thematic Mapper (TM) for the estimation of the surface albedo, surface temperature (T 0), normalized difference vegetation index (NDVI), net radiation, soil heat flux and sensible heat flux to estimate Evapotranspiration and surface conditions, on 1st June 1998 for the Sana'a Basin in Yemen, which is an arid and semi-arid region, with a mountainous terrain condition. The actual ET was computed from field data during the satellite overpass and integrated for 24-h on a pixel-by-pixel basis for daily ET distribution and compared to the value obtained from the AVHRR and TM data. Being a mountainous basin, an attempt has been made to consider terrain effects in estimating net radiation by adding DEM information. As a result, a daily ET map over the Basin was used to analyze some observation data, such as radiation and surface temperature, and was compared with estimated data. The results showed that AVHRR gives some reasonable values; however, the TM data gives better results since the spatial resolution of TM is better than that of AVHRR
