One of the key components of energy and hydrological processes is soil moisture, which is measured indirectly, because of exiting some problems in measuring directly. Some existing methods such as thermal inertia, vegetation indices, temperature and water indices (e.g. NDWI) has certain limitations such as difficulties in capturing images of day and night times, and differences in method of calculating of thermal inertia for different hours in a day. Therefore, finding a new method for calculating of soil moisture based soil temperature or water and soil spectral changes is very necessary. Although soil moisture is not calculated directly in the Surface Energy Balance Algorithm for Land (SEBAL), since all parameters that have effect on soil moisture changes, consider for calculating evapotranspiration in SEBAL, this model can be used to calculate soil moisture. Jarghoye-Sofla, as the study area, is located adjacent to the Gavkhoni playa, Isfahan province. The study area, has faced with declining in soil moisture, as a result of climatic fluctuations, and drying of the wetlands in recent years. The purpose of this research is assessing of the remote sensed based surface energy balance model, and evaluation of biophysical parameters derived from satellite imagery to estimate soil moisture. Data used in this research, consisted of MODIS satellite images and measurements of 33 soil samples taken at depth of 0-30 cm. By measuring point soil moisture, and calculating volumetric soil moisture, the rate of evapotranspiration was estimated using the SEBAL model. Then, correlation between the parameters used in the SEBAL and ground measurements of soil moisture was evaluated. Results show high correlation between parameters of the SEBAL and soil moisture. The highest correlation was determined between the SEBAL algorithm daily evapotranspiration and soil moisture for days of 16 and 17 November, 2014 with values of 0.51 and 0.68, respectively.