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Remote Sens. 2017, 9(12), 1181; doi:10.3390/rs9121181

Combining Remote Sensing and Water-Balance Evapotranspiration Estimates for the Conterminous United States

1
Hydrologic Remote Sensing Branch, U.S. Geological Survey, Reston, VA 20192, USA
2
Earth Resources Observation and Science (EROS) Center, North Central Climate Science Center, U.S. Geological Survey, Fort Collins, CO 80523, USA
3
Earth Systems Modeling Branch, U.S. Geological Survey, Reston, VA 20192, USA
*
Author to whom correspondence should be addressed.
Received: 21 September 2017 / Revised: 9 October 2017 / Accepted: 2 November 2017 / Published: 29 November 2017
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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Abstract

Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints. View Full-Text
Keywords: evapotranspiration; water resources; remote sensing; water balance; evaporation; transpiration evapotranspiration; water resources; remote sensing; water balance; evaporation; transpiration
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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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Reitz, M.; Senay, G.B.; Sanford, W.E. Combining Remote Sensing and Water-Balance Evapotranspiration Estimates for the Conterminous United States. Remote Sens. 2017, 9, 1181.

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