Variance-based sensitivity analysis of BIOME-BGC for gross and net primary production

R. Raj, N.A.S. Hamm, C. van der Tol and A. Stein

Ecological Modelling, 2014, vol. 292, issue C, 26-36

Abstract: Parameterization and calibration of a process-based simulator (PBS) is a major challenge when simulating gross and net primary production (GPP and NPP). The large number of parameters makes the calibration computationally expensive and is complicated by the dependence of several parameters on other parameters. Calibration can be simplified by first identifying those parameters for which GPP and NPP are most sensitive. For an appropriate application of a PBS, a sensitivity analysis is an essential step. Sensitivity analysis based on local derivatives (i.e., one-at-a-time analysis) does not examine the PBS behaviour over the whole parameter space. This study therefore implements a variance-based sensitivity analysis (VBSA) addressing the full range of PBS input. A VBSA is also independent of non-linearity in a PBS. This paper performs a VBSA of the process-based simulator BIOME-BGC for GPP and NPP output in a Douglas-fir stand at the Speulderbos forest site, The Netherlands. The results show that GPP and NPP are highly sensitive to the following parameters: fraction of leaf nitrogen in Rubisco, the ratio of fine root carbon to leaf carbon, the ratio of carbon to nitrogen in leaf and fine root, the leaf and fine root turnover, the water interception coefficient and soil depth. GPP and NPP are particularly sensitive to the ratio of fine root carbon to leaf carbon that is responsible for leaf area index development. The study concludes that a VBSA analysis provides a reliable and useful approach for a sensitivity analysis of process-based simulators with a complicated structure in the parameters.

Keywords: Process-based simulator; BIOME-BGC; Gross and net primary production; Sensitivity analysis (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380014003913
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:292:y:2014:i:c:p:26-36

DOI: 10.1016/j.ecolmodel.2014.08.012

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 ().