Estimation of daily actual evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in North China

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Abstract:

Daily actual evapotranspiration over the upper Chao river basin in North China on 23 June 2005 was estimated based on the Surface Energy Balance Algorithm for Land (SEBAL), in which the parameterization schemes for calculating the instantaneous solar radiation and daily integrated radiation were improved by accounting for the variations in slope and azimuth of land surface and terrain shadow in mountainous areas. The evapotranspiration (ET) estimated from satellite data in this study for the whole watershed ranges from 0 mm to 7.3 mm day-1 with a mean of 3.4 mm day-1, which was validated by Penman-Monteith approaches for water body and paddy land. The comparison of ET estimates for a wide range of land cover types reflected distinct mechanisms of energy partition and water removal of various land cover types, showing differences in the spatial distribution pattern of ET, which could be not only the reflection but also the driving force of advection and local circulation that may violate the surface energy balance equation in the vertical direction. The spatial variation in daily solar radiation and ET estimates under the complex terrain of forest land were elaborated and evaluated by exploring the relationship between ET estimates and elevations for wood land and grass land. In addition, the utility and limitations of SEBAL's applicability to watersheds with various land cover types and complex terrain were analysed.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160701469073

Affiliations: 1: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,Graduate School of the Chinese Academy of Sciences, Beijing 100039, China 3: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,TRIO/LSIIT/ENSPS, Parc d'Innovation, Bld Sebastien Brant, 67412 Illkirch, France

Publication date: June 1, 2008

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