Biogeosciences www.biogeosciences.net 1726-4170 1726-4189 7 2 2010 10.5194/bg-7-763-2010 http://www.biogeosciences.net/7/763/2010/ http://www.biogeosciences.net/7/763/2010/bg-7-763-2010.html http://www.biogeosciences.net/7/763/2010/bg-7-763-2010.pdf 763 776 2010-02-25 Information content of incubation experiments for inverse estimation of pools in the Rothamsted carbon model: a Bayesian perspective B. Scharnagl b.scharnagl@fz-juelich.de J. A. Vrugt H. Vereecken M. Herbst Agrosphere Institute (ICG-4), Forschungszentrum Jülich, 52425 Jülich, Germany Center for Nonlinear Studies, Los Alamos National Lab., Los Alamos, NM 87545, USA Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, The Netherlands now at: Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA 92697, USA A major drawback of current soil organic carbon (SOC) models is that their conceptually defined pools do not necessarily correspond to measurable SOC fractions in real practice. This not only impairs our ability to rigorously evaluate SOC models but also makes it difficult to derive accurate initial states of the individual carbon pools. In this study, we tested the feasibility of inverse modelling for estimating pools in the Rothamsted carbon model (ROTHC) using mineralization rates observed during incubation experiments. This inverse approach may provide an alternative to existing SOC fractionation methods. To illustrate our approach, we used a time series of synthetically generated mineralization rates using the ROTHC model. We adopted a Bayesian approach using the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to infer probability density functions of the various carbon pools at the start of incubation. The Kullback-Leibler divergence was used to quantify the information content of the mineralization rate data. Our results indicate that measured mineralization rates generally provided sufficient information to reliably estimate all carbon pools in the ROTHC model. The incubation time necessary to appropriately constrain all pools was about 900 days. The use of prior information on microbial biomass carbon significantly reduced the uncertainty of the initial carbon pools, decreasing the required incubation time to about 600 days. 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