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Remote Sens. 2017, 9(3), 184; doi:10.3390/rs9030184

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
Received: 5 December 2016 / Revised: 31 January 2017 / Accepted: 16 February 2017 / Published: 23 February 2017
View Full-Text   |   Download PDF [4290 KB, uploaded 23 February 2017]   |  

Abstract

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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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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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.

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