作者:Li, ZS (Li, Zhansheng)[ 1,2 ] ; Jia, L (Jia, Li)[ 1,3 ] ; Hu, GC (Hu, Guangcheng)[ 1 ] ; Lu, J (Lu, Jing)[ 1 ] ; Zhang, JX (Zhang, Jingxiao)[ 1,2 ] ; Chen, QT (Chen, Qiting)[ 1,2 ] ; Wang, K (Wang, Kun)[ 1 ]

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS

卷: 12  期: 5  页: 948-952

DOI: 10.1109/LGRS.2014.2368694

出版年: MAY 2015

摘要

Spatial mapping of evapotranspiration (ET) is specifically critical for the semi-arid inland river basin with great heterogeneity in land-cover types. This letter estimates the spatial distribution of daily ET over the middle stream and downstream areas of the Heihe River Basin during the growing season of 2012 by using the Surface Energy Balance System algorithm with land surface temperature at high spatial resolution (300 m) derived from observations by the Chinese satellite HJ-1. The results demonstrate that ET estimates are consistent with ground-based measurements collected during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) with acceptable accuracy. The magnitude of daily ET in the downstream area is obviously lower than that in the middle stream area. Further analysis based on classification maps shows that there is significant temporal-spatial heterogeneity of daily ET over different land-cover surfaces and also within the same vegetation type. The temporal variation of ET in the middle stream area has clear seasonality with an obvious peak in July, whereas it is flat in the downstream area due to the dominating arid-region vegetation species and low soil water content in growing season. In addition, because of the abundant irrigation in the maize and irrigated orchard fields, the daily ET values of them are higher than that of wetland and even comparable with that of water surface in the middle stream area of the Heihe River Basin.

通讯作者地址: Jia, L (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[ 3 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China