Variance-based sensitivity analysis of a forest growth model
Xiaodong Song,
Brett A. Bryan,
Keryn I. Paul and
Gang Zhao
Ecological Modelling, 2012, vol. 247, issue C, 135-143
Abstract:
Computer models are increasingly used to simulate and predict the behaviour of forest systems. Uncertainties in both parameter calibration and outputs co-exist in these models due to both the incomplete understanding of the system under simulation, and biased model structure. We used sensitivity analysis, including both screening and global variance-based methods, to explore these uncertainties. We applied these techniques to the widely used forest growth model Physiological Principles for Predicting Growth (3-PG2) using field data from 141 plots of Corymbia maculata and Eucalyptus cladocalyx in Australia. The screening method was used to select influential input parameters for the subsequent variance-based analysis and thereby reduce its computational cost. We assessed model outputs including biomass partitioning and water balance, and the sensitivities of the soil texture group, which includes 7 parameters. We also compared the screening and variance-based methods, and assessed the convergence of the variance-based method, and the change in sensitivities over time. Using these techniques, we quantified the relative sensitivities of each model output to each input parameter. The variance-based method exhibited good convergence and stable sensitivity rankings. The results indicated changes in input parameter sensitivities over longer simulation periods. The variance-based global sensitivity analysis can be very effective in calibration and identification of important processes within forest models.
Keywords: 3-PG2; Sensitivity analysis; Variance-based; Elementary effects; Group effect (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380012004024
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:247:y:2012:i:c:p:135-143
DOI: 10.1016/j.ecolmodel.2012.08.005
Access Statistics for this article
Ecological Modelling is currently edited by Brian D. Fath
More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().