干旱区生态环境知识资源中心(Arid): Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland

Arid

DOI	10.1016/j.agrformet.2020.108067
	Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland
	Li, Yuzhen; Li, Longhui; Dong, Jiaqi; Bai, Jie; Yuan, Xiuliang; Song, Shikai; Zhao, Hongfei; Chen, Xi; Li, Yali
通讯作者	Li, LH
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
ISSN	0168-1923
EISSN	1873-2240
出版年	2020
卷号	291
英文摘要	The Common Land Model (CoLM) has been widely used to estimate carbon and water fluxes at site or regional scales, but the model is still underperforming in dryland ecosystems. Our research focuses on the joint analysis of both modifying the model process and using parameter optimization techniques to improve the models performance in a semi-arid grassland ecosystem in Xinjiang, China. The study presents a comparison of the simulated carbon and water fluxes by replacing the root water uptake function (RWUF) of the CoLM and by using particle swarm optimization (PSO) algorithm to optimize the most sensitive parameters. Prior to PSO, the method of Morris one-factor-at-a-time (MOAT) is utilized to screen out parameters that have strong effects on gross primary production (GPP) and latent heat flux (LE) in CoLM. Either modifying the root water uptake process in the CoLM or optimizing model parameters can significantly reduce the biases of the simulated GPP, LE, and water use efficiency (WUE). The coefficient of determination (R-2) with the modified RWUF in the CoLM increases from 0.85 to 0.92 for GPP and from 0.76 to 0.81 for LE. Meanwhile, the root mean square error (RMSE) decreases from 3.57 mu mol m(-2) S-1 to 2.78 mu mol m(-2) S-1 for GPP and from 50.75 W m(-2) to 46.85 W m(-2) for LE. Using the PSO approach, the R-2 increases to 0.89 and RMSE decreases to 2.92 mu mol m(-2) S-1 for GPP, while, the R-2 increases to 0.79 and RMSE decreases to 46.16 W m(-2) for LE. Therefore, modifying the model process contributed more to improve the model simulations than using parameter estimation techniques. Our study recommends that a justified refinement in model structure plays vital role in quantifying the carbon and water fluxes in dryland ecosystems or other ecosystems.
英文关键词	Common Land Model Sensitivity analysis Particle swarm optimization Gross primary production Latent heat flux Water use efficiency
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000556177600029
WOS关键词	LAND-SURFACE MODEL ; NET ECOSYSTEM EXCHANGE ; HYDRAULIC REDISTRIBUTION ; USE EFFICIENCY ; UNCERTAINTY ANALYSIS ; SENSITIVITY-ANALYSIS ; TURBULENT FLUXES ; CLIMATE ; ASSIMILATION ; TEMPERATURE
WOS类目	Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS研究方向	Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
来源机构	中国科学院新疆生态与地理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325450
作者单位	[Li, Yuzhen; Li, Longhui; Dong, Jiaqi; Bai, Jie; Yuan, Xiuliang; Song, Shikai; Zhao, Hongfei; Chen, Xi] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China; [Li, Longhui] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China; [Li, Longhui] State Key Lab Cultivat Base Geog Environm Evolut, Nanjing 210023, Peoples R China; [Li, Yuzhen; Dong, Jiaqi; Zhao, Hongfei] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Yuan, Xiuliang] Univ Ghent, Dept Geog, B-9000 Ghent, Belgium; [Song, Shikai] Hebei Normal Univ, Coll Resources & Environm Sci, Shijiazhuang 050024, Hebei, Peoples R China; [Li, Yali] Chinese Acad Agr Sci, Inst Special Wild Econ Anim & Plants, Changchun 130112, Peoples R China
推荐引用方式 GB/T 7714	Li, Yuzhen,Li, Longhui,Dong, Jiaqi,et al. Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland[J]. 中国科学院新疆生态与地理研究所,2020,291.
APA	Li, Yuzhen.,Li, Longhui.,Dong, Jiaqi.,Bai, Jie.,Yuan, Xiuliang.,...&Li, Yali.(2020).Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland.AGRICULTURAL AND FOREST METEOROLOGY,291.
MLA	Li, Yuzhen,et al."Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland".AGRICULTURAL AND FOREST METEOROLOGY 291(2020).