Remote sensing algorithms are well known to estimate surface energy fluxes in regional to global scales with low cost. Accurate measurements of evapotranspiration (ET) in regional scales for crops were demanding for better water management scenarios. However, point estimates of ET from eddy covariance and lysimeters studies are very expensive and limiting the spatial variability. The remote sensing approach has an advantage of estimating ET from spatiotemporal scales compares with traditional methods. The objective of this study was to compare two remote sensing algorithms namely Surface Energy Balance Algorithms for Land (SEBAL) and Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) to calculate ET of semi-arid citrus orchards in India as a residual of a surface energy balance. A total of 6 Landsat 7 images (2016-17) were processed using both models and tested with eddy covariance measurements in the filed location. Meteorological data collected from near weather station for giving input to the models. METRIC is needed all major climatic parameters while SEBAL is having capable of calculating ET with less or no climatic parameters. Results showed that SEBAL was estimated a high value of ET with a large error while METRIC showed a good agreement with ET flux tower data with the best fit of 0.86. By comparing these results, we can use METRIC model to estimate crop coefficient curves for citrus orchards or any other crops with proper validation of eddy flux data or lysimeters for better management of water use in crops of semi-arid regions.