干旱区生态环境知识资源中心(Arid): Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration

Arid

DOI	10.1016/j.jhydrol.2021.126029
	Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration
	Chen, Han; Huang, Jinhui Jeanne; McBean, Edward; Singh, Vijay P.
通讯作者	Huang, JHJ (corresponding author), Nankai Univ, Coll Environm Sci & Engn, Sino Canada R&D Ctr Water & Environm Safety, Tianjin 300071, Peoples R China.
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2021
卷号	597
英文摘要	Remote sensing (RS)-based two-source models have been widely used to separate soil evaporation (E) and vegetation transpiration (T) in ecosystems. Alternative model assumptions and physical mechanisms employed in different two-source models cause the difference in model performance. Understanding of the characteristics and limitations of alternative two-source models is critical to ensure the most effective applications in various climatic zones and underlying surfaces. This study investigated two types of land surface temperature (LST) decomposition based two-source models, namely Two-Source Energy Balance Model (TSEB) and Modified Pixel Component Arranging and Comparing Algorithm (M-PCACA); as well as a meteorological factors-based Penman-Monteith type model (PM-MU) in the partitioning of E and T. The three models were compared at 21 flux stations across China, which included seven types of underlying surfaces and one isotope station. The study demonstrated that all three models were applicable in a large scale study for latent heat flux (LE) estimation. Overall, M-PCACA performed the best with average root-mean-square errors (RMSE) of 38.7 W/m(2), while PM-MU performs the worst with average RMSE of 61.4 W/m(2). For ET partitioning, the two models based on LST decomposition (TSEB and M-PCACA) gave more reliable estimates compared with stable water isotope observations. In addition, verification results for the seven types of underlying surfaces showed that the TSEB gave the best accuracy in the areas with high leaf area index (LAI) and vegetation height (e.g. forest), while the PM-MU had an advantage in the areas without vegetation (e.g. deserts and water bodies). Due to the characteristics of the land surface temperature-vegetation coverage (LST-fc) trapezoidal framework, the M-PCACA model had the most stable model performance for various underlying surfaces and gave the best estimates in grassland, wetland, and farmland areas. Using a thorough discussion, this study identified the sources of discrepancies induced by different physical mechanisms of three remote sensing-based two-source models. This investigation provided insights to better understand the alternative two-source models and provides guidance for model application.
英文关键词	ET partition Two-source model TSEB M-PCACA PM-MU Remote sensing
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000652835600031
WOS关键词	APERTURE SCINTILLOMETER MEASUREMENTS ; ENERGY BALANCE ALGORITHM ; LATENT-HEAT FLUX ; GAS-EXCHANGE ; ARID REGION ; MODIS ; EVAPORATION ; SOIL ; TRANSPIRATION ; VEGETATION
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/350896
作者单位	[Chen, Han; Huang, Jinhui Jeanne; McBean, Edward] Nankai Univ, Coll Environm Sci & Engn, Sino Canada Joint R&D Ctr Water & Environm Safety, Tianjin 300071, Peoples R China; [McBean, Edward] Univ Guelph, Sch Engn, Guelph, ON N1G 2W1, Canada; [Singh, Vijay P.] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA
推荐引用方式 GB/T 7714	Chen, Han,Huang, Jinhui Jeanne,McBean, Edward,et al. Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration[J],2021,597.
APA	Chen, Han,Huang, Jinhui Jeanne,McBean, Edward,&Singh, Vijay P..(2021).Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration.JOURNAL OF HYDROLOGY,597.
MLA	Chen, Han,et al."Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration".JOURNAL OF HYDROLOGY 597(2021).