Estimation of Evapotranspiration using Landsat 8 Satellite Images and SEBAL Method

Today remote sensing is used in various sciences such as geography, biology, meteorology, agriculture, water resources management, etc. Therefore, using the algorithms available in the remote sensing of evapotranspiration, one can take a major step in the management of water resource swhich is included SEBAL algorithm.In this study, using this algorithm, multi-spectral satellite data and meteorological data such as temperature, duration of sunshine, wind, saturation vapor pressure, soil moisture and so on were used to calculate surface albedo, surface temperature and vegetation status index. Seasonal monitoring of evapotranspiration changes over the past two years has shown that the process of evapotranspiration changes during a year is periodic that start at the beginning of the year (as in the picture of January 2018 and February 2017) with a relatively low amount, then it has an uptrend to reach its highest levels in the summer (July 2016 and 2017), and then it has downward trend and at the end of the year (October 2016 and 2017) reaches its minimum value. The highest amount of evapotranspiration dates to the 7th month of every year, which is the summer season. Due to the fact that the temperature of evapotranspiration in the heat season is higher because of high air temperature and atmospheric conditions, the results confirm the accuracy of this subject that highest amount of evapotranspiration is in the 7th month of every year.