Estimations of evapotranspiration and surface soil moisture based on remote sensing data and influence factors

Evapotranspiration and surface soil moisture are important parameters in global hydrological circle studies. Based on Landsat TM remotely sensed data, the Surface Energy Balance Algorithm for Land (SEBAL) model was applied to estimate regional evapotranspiration, and the vegetation temperature condition index was used to estimate surface soil moisture (0～20 cm) in Wuwei city of Gansu Province in northwest China. Factors of influencing evapotranspiration and surface soil moisture were also discussed. The results show that the estimations of evapotranspiration and surface soil moisture are in good agreement with the ground measured ones. The spatial variations of evapotranspiration under dry condition are larger than those under wet condition. There are significant correlations between daily evapotranspiration, and net radiation, land surface temperature and vegetation coverage both under wet and dry conditions, and the correlation coefficient between daily evapotranspiration and surface soil moisture under wet condition is higher than that under dry condition. There are obvious correlation between surface soil moisture, and land surface temperature and vegetation coverage, and the correlation coefficient between soil surface moisture and land surface temperature is higher than that between soil surface moisture and vegetation coverage. The higher the surface soil moisture, the higher the correlation coefficients.