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Journal of Applied Remote Sensing

Evapotranspiration estimation using moderate resolution imaging spectroradiometer products through a surface energy balance algorithm for land model in Songnen Plain, China
Author(s): Lihong Zeng; Kaishan Song; Bai Zhang; Lin Li; Zongming Wang
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Paper Abstract

The Songnen Plain is an important commodity grain product base in China for which a spatiotemporal pattern of actual evapotranspiration (ETa) would provide critical important information to evaluate crop growth status and water use efficiency. ETa over the Songnen Plain in the 2008 growing season (from May to September) was mapped using the moderate resolution imaging spectroradiometer time-series products based on the surface energy balance algorithm for land model and the Penman-Monteith equation. The estimated ETa was validated using eddy covariance surface data. The calculated and observed ETa values were highly consistent with a total difference of 18.26% in the whole growing season. Therefore, the ETa retrieval method based on remote sensing technology could satisfy the requirements for regional ETa estimation over the Songnen Plain. The total ETa over the Songnen Plain in the 2008 growing season ranged from 182.7 to 1002.4 mm, and the average value for the whole study area was 591.1 ± 122.2 mm (standard deviation). ETa exhibited obvious spatial variation, gradually increasing from low values in the southwest to higher values in the east and northeast. Monthly ETa varied with meteorological conditions, land covers, root-zone soil moisture, and vegetation phenology. Higher monthly ETa values appeared in June, July, and August with a maximum value of 139.5 mm observed in July. The average monthly ETa for water-body, woodland, and wetland was much higher than cropland and grassland during the growing season. Grassland obtained the lowest monthly ETa due to the scarcity of rainfall and lower groundwater level.

Paper Details

Date Published: 1 January 2011
PDF: 15 pages
J. Appl. Remote Sens. 5(1) 053535 doi: 10.1117/1.3609840
Published in: Journal of Applied Remote Sensing Volume 5, Issue 1
Show Author Affiliations
Lihong Zeng, Northeast Institute of Geography and Agroecology (China)
Kaishan Song, Northeast Institute of Geography and Agroecology (China)
Bai Zhang, Northeast Institute of Geography and Agroecology (China)
Lin Li, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Zongming Wang, Northeast Institute of Geography and Agroecology (China)


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