Articles | Volume 6, issue 12
Biogeosciences, 6, 3035–3051, 2009
https://doi.org/10.5194/bg-6-3035-2009
Biogeosciences, 6, 3035–3051, 2009
https://doi.org/10.5194/bg-6-3035-2009

  16 Dec 2009

16 Dec 2009

Sensitivity analysis of a wetland methane emission model based on temperate and arctic wetland sites

J. van Huissteden1, A. M. R. Petrescu1, D. M. D. Hendriks2, and K. T. Rebel3 J. van Huissteden et al.
  • 1Vrije Universiteit, Faculty of Earth and Life Sciences, Hydrology and Geo-environmental Sciences Group, De Boelelaan 1085, 1081HV Amsterdam, The Netherlands
  • 2Deltares, Department Groundwater Mangement, P.O. Box 85467, 3508AL Utrecht, The Netherlands
  • 3Copernicus Institute for Sustainable Development and Innovation, Research Group Environmental Sciences, Universiteit Utrecht, Faculteit Geowetenschappen Departement IMW Heidelberglaan 2, Office 1101, P.O. Box 80115, 3508 TC Utrecht, The Netherlands

Abstract. Modelling of wetland CH4 fluxes using wetland soil emission models is used to determine the size of this natural source of CH4 emission on local to global scale. Most process models of CH4 formation and soil-atmosphere CH4 transport processes operate on a plot scale. For large scale emission modelling (regional to global scale) upscaling of this type of model requires thorough analysis of the sensitivity of these models to parameter uncertainty. We applied the GLUE (Generalized Likelihood Uncertainty Analysis) methodology to a well-known CH4 emission model, the Walter-Heimann model, as implemented in the PEATLAND-VU model. The model is tested using data from two temperate wetland sites and one arctic site. The tests include experiments with different objective functions, which quantify the fit of the model results to the data.

The results indicate that the model 1) in most cases is capable of estimating CH4 fluxes better than an estimate based on the data avarage, but does not clearly outcompete a regression model based on local data; 2) is capable of reproducing larger scale (seasonal) temporal variability in the data, but not the small-scale (daily) temporal variability; 3) is not strongly sensitive to soil parameters, 4) is sensitive to parameters determining CH4 transport and oxidation in vegetation, and the temperature sensitivity of the microbial population. The GLUE method also allowed testing of several smaller modifications of the original model.

We conclude that upscaling of this plot-based wetland CH4 emission model is feasible, but considerable improvements of wetland CH4 modelling will result from improvement of wetland vegetation data.

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