干旱区生态环境知识资源中心(Arid): Improving ecological indicators of arid zone deserts through simulation

Arid

DOI	10.1016/j.ecolmodel.2023.110506
	Improving ecological indicators of arid zone deserts through simulation
	Wang, Jing; Xue, Lianqing; Xiang, Chenguang; Li, Xinghan; Xie, Lei
通讯作者	Xue, LQ
来源期刊	ECOLOGICAL MODELLING
ISSN	0304-3800
EISSN	1872-7026
出版年	2023
卷号	485
英文摘要	Ecological indicators, such as soil moisture content and gross primary production (GPP), play important roles in the management of ecosystems and water resources and within climate change research. However, studies on monitoring and simulation of ecological indicators of arid zones remain limited. This study simulated soil moisture (SM), latent heat (LH), and gross primary productivity (GPP) for the arid Yarkant River Basin in China using the High-Resolution Land Data Assimilation System and Deep learning. Simulation of hydrology over a large spatial scale is difficult due to a lack of observed data and the difficulty in parameterizing models to represent complicated ecological mechanisms. A comparison of Noah Multi-Parameterization (Noah-MP) simulations to multiple datasets at an annual scale obtained correlation coefficients exceeding 0.8. The model was able to replicate the broad temporal dynamics of GPP and LH over the Yarkant River Basin. Point-and regionalscale assessments across the Yarkant River Basin obtained the optimal model performance. The temporal trends in simulated SM anomalies were consistent with observations across the different sub-basins. The simulations of the Noah-MP model driven by Global Land Data Assimilation System (GLDAS) and ERA5 data provided accurate representations of most hydrological variables, except for in the upper reaches of Yarkant River Basin, likely due to the extensive freeze-thaw activity in this transitional region. The results of this study can fill hydrological data gaps in arid zones areas.
英文关键词	Data reconstruction Yarkant river basins Arid zones Data assimilation GLDAS
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001081388500001
WOS关键词	LAND-SURFACE TEMPERATURE ; INDUCED CHLOROPHYLL FLUORESCENCE ; TURBULENT HEAT FLUXES ; SENSED SOIL-MOISTURE ; LEAF-AREA INDEX ; DATA ASSIMILATION ; SENSITIVITY-ANALYSIS ; ENVIRONMENTAL-MODELS ; KALMAN FILTER ; VEGETATION
WOS类目	Ecology
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396004
推荐引用方式 GB/T 7714	Wang, Jing,Xue, Lianqing,Xiang, Chenguang,et al. Improving ecological indicators of arid zone deserts through simulation[J],2023,485.
APA	Wang, Jing,Xue, Lianqing,Xiang, Chenguang,Li, Xinghan,&Xie, Lei.(2023).Improving ecological indicators of arid zone deserts through simulation.ECOLOGICAL MODELLING,485.
MLA	Wang, Jing,et al."Improving ecological indicators of arid zone deserts through simulation".ECOLOGICAL MODELLING 485(2023).