Articles | Volume 9, issue 12
Geosci. Model Dev., 9, 4313–4338, 2016
Geosci. Model Dev., 9, 4313–4338, 2016

Model evaluation paper 05 Dec 2016

Model evaluation paper | 05 Dec 2016

Parameter interactions and sensitivity analysis for modelling carbon heat and water fluxes in a natural peatland, using CoupModel v5

Christine Metzger1,a, Mats B. Nilsson2, Matthias Peichl2, and Per-Erik Jansson1 Christine Metzger et al.
  • 1Department of Land and Water Resources Engineering, Royal Institute of Technology, Stockholm, 100 44, Sweden
  • 2Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, 901 83, Sweden
  • anow at: Institute for Meteorology and Climate Research/Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute for Technology, 82467 Garmisch-Partenkirchen, Germany

Abstract. In contrast to previous peatland carbon dioxide (CO2) model sensitivity analyses, which usually focussed on only one or a few processes, this study investigates interactions between various biotic and abiotic processes and their parameters by comparing CoupModel v5 results with multiple observation variables.

Many interactions were found not only within but also between various process categories simulating plant growth, decomposition, radiation interception, soil temperature, aerodynamic resistance, transpiration, soil hydrology and snow. Each measurement variable was sensitive to up to 10 (out of 54) parameters, from up to 7 different process categories. The constrained parameter ranges varied, depending on the variable and performance index chosen as criteria, and on other calibrated parameters (equifinalities).

Therefore, transferring parameter ranges between models needs to be done with caution, especially if such ranges were achieved by only considering a few processes. The identified interactions and constrained parameters will be of great interest to use for comparisons with model results and data from similar ecosystems. All of the available measurement variables (net ecosystem exchange, leaf area index, sensible and latent heat fluxes, net radiation, soil temperatures, water table depth and snow depth) improved the model constraint. If hydraulic properties or water content were measured, further parameters could be constrained, resolving several equifinalities and reducing model uncertainty. The presented results highlight the importance of considering biotic and abiotic processes together and can help modellers and experimentalists to design and calibrate models as well as to direct experimental set-ups in peatland ecosystems towards modelling needs.

Short summary
Many interactions between various abiotic and biotic processes and their parameters were identified by global sensitivity analysis, revealing strong dependence of a certain model output (e.g. CO2 or heat fluxes, leaf area index, radiation, water table, soil temperature or snow depth) to model set-up and parameterization in many different processes, a limited transferability of parameter values between models, and the importance of ancillary measurements for improving models and thus predictions.