Estimating Evapotranspiration from Satellite Using Easily Obtainable Variables: A Case Study over the Southern Great Plains, U.S.A.

Evapotranspiration (ET) is a critical component of the Earth's water budget, a critical modulator of land-atmosphere (L-A) interactions, and also plays a crucial role in managing the Earth's energy balance. In this study, the feasibility of generating spatially-continuous daily evaporative fraction (EF) and ET from minimal remotely-sensed and meteorological inputs in a trapezoidal framework is demonstrated. A total of four variables, Normalized Difference Vegetation Index (NDVI), Land surface temperature (T(sub s)), gridded daily average temperature (T(sub a)) and elevation (z) are required to estimate EF. Then, ET can be estimated with the available soil heat flux (G) and net radiation (Rn) data. Firstly, the crucial model variable, T(sub s)-T(sub a), is examined how well it characterizes the variation in EF using in situ data recorded at two eddy correlation flux towers in Southern Great Plains, U.S.A. in 2011. Next, accuracy of satellite-based T(sub s) are compared to ground-based T(sub s). Finally, EF and ET estimates are validated. The results reveal that the model performed satisfactorily in modeling EF and ET variation at winter wheat and deciduous forest during the high evaporative months. Even though the model works best with the observed MODIS-T(sub s) as opposed to temporally interpolated T(sub s), results obtained from interpolated T(sub s) are able to close the gaps with reasonable accuracy. Due to the fact that T(sub s)-T(sub a), is not a good indicator of EF outside the growing season when deciduous forest is dormant, potential improvements to the model are proposed to improve accuracy in EF and ET estimates at the expense of adding more variables