机构:
USDA ARS, Southwest Watershed Res Ctr, 2000 E Allen Rd, Tucson, AZ 85719 USAColorado Sch Mines, Hydrol Sci & Engn, Dept Civil & Environm Engn, Golden, CO 80401 USA
Scott, Russell
[2
]
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机构:
Franz, Kristie
[3
]
机构:
[1] Colorado Sch Mines, Hydrol Sci & Engn, Dept Civil & Environm Engn, Golden, CO 80401 USA
[2] USDA ARS, Southwest Watershed Res Ctr, 2000 E Allen Rd, Tucson, AZ 85719 USA
[3] Iowa State Univ, Dept Geol & Atmospher Sci, 253 Sci, Ames, IA 50011 USA
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/m(2). 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.
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[1]
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