Comparison of Remotely Sensed Evapotranspiration Models Over Two Typical Sites in an Arid Riparian Ecosystem of Northwestern China

doi:10.3390/rs12091434

	Comparison of Remotely Sensed Evapotranspiration Models Over Two Typical Sites in an Arid Riparian Ecosystem of Northwestern China
	Du, Tao 1,2; Yuan, Guofu 1,2; Wang, Li 3; Sun, Xiaomin 1,2; Sun, Rui 2,4
刊名	REMOTE SENSING
	2020-05-01
卷号	12 期号:9 页码:21
关键词	evapotranspiration remote sensing eddy covariance arid riparian ecosystem vegetation indices Tamarix ramosissima Populus euphratica
DOI	10.3390/rs12091434
通讯作者	Yuan, Guofu(yuangf@igsnrr.ac.cn)
英文摘要	Accurate estimates of evapotranspiration (ET) are essential for the conservation of ecosystems and sustainable management of water resources in arid and semiarid regions. Over the last two decades, several empirical remotely sensed ET models (ERSETMs) had been developed and extensively used for regional-scale ET estimation in arid and semiarid ecosystems. These ERSETMs were constructed by combining datasets from different sites and relating measured daily ET to corresponding meteorological data and vegetation indices at the site scale. Then, regional-scale ET on a pixel basis can be estimated, using the established ERSETMs. The estimation accuracy of these ERSETMs at the site scale plays a fundamental and crucial role in regional-scale ET estimation. Recent studies have revealed that ET estimates from some of these models have significant uncertainties at different spatiotemporal scales. However, little information is available on the performance of these ERSETMs at the site scale. In this study, we compared eight ERSETMs, using ET measurements from 2013 to 2018 for two typical eddy covariance sites (Tamarix site and Populus site) in an arid riparian ecosystem of Northwestern China, intending to provide a guide for the selection of these models. Results showed that the Nagler-2013 model and the Yuan-2016 model outperformed the other models. There were substantial differences in the ET estimation of the eight ERSETMs at daily, monthly, and seasonal scales. The mean ET of the growing season from 2013 to 2018 ranged from 465.93 to 519.65 mm for the Tamarix site and from 386.22 to 437.05 mm for the Populus site, respectively. The differences in model structures and characterization of both meteorological conditions and vegetation factors were the primary sources of different model performance. Our findings provide useful information for choosing models and obtaining accurate ET estimation in arid regions.
资助项目	Strategic Priority Research Program of Chinese Academy of Sciences[XDA20060301]
WOS关键词	LEAF-AREA INDEX ; ENHANCED VEGETATION INDEX ; LOWER TARIM RIVER ; SENSING-BASED MODELS ; NDVI TIME-SERIES ; LAND-USE DATA ; EDDY-COVARIANCE ; SPATIAL EVAPOTRANSPIRATION ; DIORHABDA-CARINULATA ; EMPIRICAL ALGORITHM
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000543394000081
资助机构	Strategic Priority Research Program of Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/162458]
专题	中国科学院地理科学与资源研究所
通讯作者	Yuan, Guofu
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China 3.China Univ Geosci Beijing, Beijing Key Lab Water Resources & Environm Engn, Beijing 100083, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Du, Tao,Yuan, Guofu,Wang, Li,et al. Comparison of Remotely Sensed Evapotranspiration Models Over Two Typical Sites in an Arid Riparian Ecosystem of Northwestern China[J]. REMOTE SENSING,2020,12(9):21.
APA	Du, Tao,Yuan, Guofu,Wang, Li,Sun, Xiaomin,&Sun, Rui.(2020).Comparison of Remotely Sensed Evapotranspiration Models Over Two Typical Sites in an Arid Riparian Ecosystem of Northwestern China.REMOTE SENSING,12(9),21.
MLA	Du, Tao,et al."Comparison of Remotely Sensed Evapotranspiration Models Over Two Typical Sites in an Arid Riparian Ecosystem of Northwestern China".REMOTE SENSING 12.9(2020):21.