DOI: 10.1002/2013MS000298
Scopus记录号: 2-s2.0-84904907410
论文题名: Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States
作者: Wu Y ; , Liu S ; , Huang Z ; , Yan W
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2014
卷: 6, 期: 2 起始页码: 405
结束页码: 419
语种: 英语
英文关键词: Biogeochemistry
; Carbon
; Ecosystems
; Forestry
; Parameter estimation
; Biogeochemical modeling
; Carbon dynamics
; EDCM
; Flux towers
; Model inversion
; sensitivity and uncertainty
; Uncertainty analysis
; Carbon
; Ecosystems
; Forestry
英文摘要: Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package - Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling. Key Points FME was fully wrapped into EDCM to support sensitivity/uncertainty analysis FME functions can help identify the relationship between parameter and output Parameter uncertainty has distinct effects for variables in different seasons © 2014. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/76100
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: ASRC Research and Technology Solutions, U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls SD, United States; U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls SD, United States; Geographic Information Science Center of Excellence, South Dakota State University, Brookings SD, United States; National Engineering Laboratory for Applied Technology of Forestry and Ecology in Southern China, Central South University of Forestry and Technology, Changsha, China
Recommended Citation:
Wu Y,, Liu S,, Huang Z,et al. Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States[J]. Journal of Advances in Modeling Earth Systems,2014-01-01,6(2)