Evaluation of Evapotranspiration Estimates From Multi-Platform Satellites in the Western U.S

In the current study, we develop an actual evapotranspiration (AET) product derived solely from remotely sensed observations by scaling potential evapotranspiration (PET) estimates with downscaled soil moisture observations. Downscaled soil moisture (1km) is derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula that parameterizes soil moisture based on land surface temperature and vegetation index. PET is estimated by the Priestly-Taylor formula and inputs derived from Moderate Resolution Imaging Spectroradiometer (MODIS) products. Derived AET estimates are validated using four ground-based flux tower sites in southern Arizona, while also being compared to a calibrated empirical ET model created specifically for the region and Version 2 of the North American Land Data Assimilation System (NLDAS-2) (i.e., Mosaic and Noah model simulations). Validation using eddy covariance measured ET indicate strong correlations (0.52 – 0.79), relatively low root mean square error (RMSE) (9 to 39 W/m²), and slight positive bias at all sites (+1.4 to +35.0 W/m²). Estimates also compare well to the calibrated empirical ET model, with only a -0.09 difference in correlation between sites, on average, and a +7.8 W/m² difference in RMSE between sites, on average. NLDAS-2 model output revealed severe underestimation by both LSMs. Following validation, the proposed methodology is applied over regions that have experienced wildfire, bark beetle infestation, and/or prolonged drought in order to decipher temporal and spatial changes and recovery in land cover. Application in these systems indicates an improved understanding of the water cycle and energy budget, providing an improved water management strategy. This study suggests that a simple ET model based on scaling PET with a soil moisture function may prove to be an effective alternative to more complex surface-atmosphere models for estimating actual ET. Moreover, the proposed methodology requires no ancillary ground-based data, site specific calibration, or subjective specifications, allowing it to be transferable to ungauged basins located in water-limited regions.