Development of a Simple Remote Sensing EvapoTranspiration model (Sim-ReSET): Algorithm and model test

SummaryRemote sensing (RS) has been considered as the most promising tool for evapotranspiration (ET) estimations from local, regional to global scales. Many studies have been conducted to estimated ET using RS data, however, most of them are based partially on ground observations. In this study, we developed a new dual-source Simple Remote Sensing EvapoTranspiration model (Sim-ReSET) based only on RS data. One merit of this model is that the calculation of aerodynamic resistance can be avoided by means of a reference dry bare soil and an assumption that wind speed at the upper boundary of atmospheric surface layer is homogenous, but the aerodynamic characters are still considered by means of canopy height. The other merit is that all inputs (net radiation, soil heat flux, canopy height, variables related to land surface temperature) can be potentially obtained from remote sensing data, which allows obtaining regular RS-driven ET product. For the purposes of sensitivity analysis and performance evaluation of the Sim-ReSET model without the effect of potential uncertainties and errors from remote sensing data, the Sim-ReSET model was tested only using intensive ground observations at the Yucheng ecological station in the North China Plain from 2006 to 2008. Results show that the model has a good performance for instantaneous ET estimations with a mean absolute difference (MAD) of 34.27 W/m2 and a root mean square error (RMSE) of 41.84 W/m2 under neutral or near-neutral atmospheric conditions. On 12 cloudless days, the MAD of daily ET accumulated from instantaneous estimations is 0.26 mm/day, and the RMSE is 0.30 mm/day.