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Remote Sens. 2013, 5(10), 5369-5396;

Derivation of Daily Evaporative Fraction Based on Temporal Variations in Surface Temperature, Air Temperature, and Net Radiation

State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
ICube, UdS, CNRS, Bld Sebastien Brant, BP10413, Illkirch 67412, France
Author to whom correspondence should be addressed.
Received: 30 August 2013 / Revised: 25 September 2013 / Accepted: 9 October 2013 / Published: 22 October 2013
(This article belongs to the Special Issue Hydrological Remote Sensing)
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Based on surface energy balance and the assumption of fairly invariant evaporative fraction (EF) during daytime, this study proposes a new parameterization scheme of directly estimating daily EF. Daily EF is parameterized as a function of temporal variations in surface temperature, air temperature, and net radiation. The proposed EF parameterization scheme can well reproduce daily EF estimates from a soil-vegetation-atmosphere transfer (SVAT) model with a root mean square error (RMSE) of 0.13 and a coefficient of determination (R2) of 0.719. When input variables from in situ measurements at the Yucheng station in North China are used, daily EF estimated by the proposed method is in good agreement with measurements from the eddy covariance system corrected by the residual energy method with an R2 of 0.857 and an RMSE of 0.119. MODIS/Aqua remotely sensed data were also applied to estimate daily EF. Though there are some inconsistencies between the remotely sensed daily EF estimates and in situ measurements due to errors in input variables and measurements, the result from the proposed parameterization scheme shows a slight improvement to SEBS-estimated EF with remotely sensed instantaneous inputs. View Full-Text
Keywords: evaporative fraction; temporal variation; remote sensing; SVAT model evaporative fraction; temporal variation; remote sensing; SVAT model
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Lu, J.; Tang, R.; Tang, H.; Li, Z.-L. Derivation of Daily Evaporative Fraction Based on Temporal Variations in Surface Temperature, Air Temperature, and Net Radiation. Remote Sens. 2013, 5, 5369-5396.

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