Calibration of Soil Moisture Correction Coefficient used in Surface Energy Balance Algorithm for Land

Surface energy balance algorithm for land (SEBAL) is one of the actual evapotranspiration predictor algorithms which are based on remote sensing. To determine outgoing long wave radiation from land surface in this algorithm, an index named soil adjusted vegetation index (SAVI) is used. In calculating SAVI, an equation consists an empirical coefficient (L) calibrated based on Idaho satellite images, USA, is used. In this study using MODIS satellite images of neyshabour watershed during 2009 to 2013, the mentioned coefficient was calibrated. The results showed the proposed value nearly L=0.5 for all areas may not evaluate adequately and it is better to calibrate this coefficient before using in SEBAL algorithm in each area. The results showed the trend of SAVI changes and thus determine the optimum value of L coefficient is sensitive to the time of satellite images and it is better to use the months with appropriate vegetation cover on the land surface. The results also showed the values of SAVI index are more sensitive to lower values of L coefficient. Results’ analysis showed the proposed value of 0.2 for L coefficient application in studies related to SEBAL algorithm in this area is properly assessed.