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Article

Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

1
Hydrologic Science and Engineering, Department of Civil and Environmental Engineering, Colorado School of Mines, 1500 Illinois Street, Golden, CO 80401, USA
2
Southwest Watershed Research Center, USDA-Agricultural Research Services, 2000 E. Allen Road, Tucson, AZ 85719, USA
3
Department of Geological and Atmospheric Sciences, Iowa State University, 253 Science, Ames, IA 50011, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Magaly Koch and Prasad S. Thenkabail
Remote Sens. 2017, 9(3), 184; https://doi.org/10.3390/rs9030184
Received: 5 December 2016 / Revised: 31 January 2017 / Accepted: 16 February 2017 / Published: 23 February 2017
Evapotranspiration (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
Keywords: evapotranspiration; remote sensing; soil moisture; Arizona; semiarid regions evapotranspiration; remote sensing; soil moisture; Arizona; semiarid regions
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MDPI and ACS Style

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. https://doi.org/10.3390/rs9030184

AMA Style

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. https://doi.org/10.3390/rs9030184

Chicago/Turabian Style

Knipper, Kyle, Terri Hogue, Russell Scott, and Kristie Franz. 2017. "Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region" Remote Sensing 9, no. 3: 184. https://doi.org/10.3390/rs9030184

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