Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region
AbstractEvapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed observations. ET is calculated by scaling PET estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) products with downscaled soil moisture derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula. The MODis-Soil Moisture ET (MOD-SMET) estimates are validated using four flux tower sites in southern Arizona USA, a calibrated empirical ET model, and model output from Version 2 of the North American Land Data Assimilation System (NLDAS-2). Validation against daily eddy covariance ET indicates correlations between 0.63 and 0.83 and root mean square errors (RMSE) between 40 and 96 W/m2. MOD-SMET estimates compare well to the calibrated empirical ET model, with a −0.14 difference in correlation between sites, on average. By comparison, NLDAS-2 models underestimate daily ET compared to both flux towers and MOD-SMET estimates. Our analysis shows the MOD-SMET approach to be effective for estimating ET. Because it requires limited ancillary ground-based data and no site-specific calibration, the method is applicable to regions where ground-based measurements are not available. View Full-Text
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Knipper, K.; Hogue, T.; Scott, R.; Franz, K. Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region. Remote Sens. 2017, 9, 184.
Knipper K, Hogue T, Scott R, Franz K. Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region. Remote Sensing. 2017; 9(3):184.Chicago/Turabian Style
Knipper, Kyle; Hogue, Terri; Scott, Russell; Franz, Kristie. 2017. "Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region." Remote Sens. 9, no. 3: 184.