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Estimation of biogeochemical rates from concentration profiles: A novel inverse method

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Riedinger,  N.
Department of Biogeochemistry, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Knab,  N.
Department of Biogeochemistry, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Boettcher,  M. E.
Department of Biogeochemistry, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Khalili,  A.
Department of Biogeochemistry, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Jørgensen,  B. B.
Department of Biogeochemistry, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Citation

Lettmann, K. A., Riedinger, N., Ramlau, R., Knab, N., Boettcher, M. E., Khalili, A., et al. (2012). Estimation of biogeochemical rates from concentration profiles: A novel inverse method. Estuarine, Coastal and Shelf Science, 100(Sp. Iss. SI), 26-37.


Cite as: http://hdl.handle.net/21.11116/0000-0001-C86B-6
Abstract
A numerical procedure is proposed to estimate net microbiological and chemical consumption and production rates from measured solute profiles in limnic and marine sediments, as well as pelagic aquatic systems. The estimation process builds on the one-dimensional steady state diagenetic transport-reaction equation for dissolved compounds (e.g. electron acceptors, nutrients, or metabolic products). This equation is inverted by a technique called Tikhonov regularization which is a common and robust technique for solving ill-conditioned inverse problems. The new procedure (REC model, Rate Estimation from Concentrations) is tested with both some artificial test cases and real measurements of sulfate and methane profiles in marine sediments. Furthermore, the technique is compared with results obtained from the models of Berg et al. (1998) and Wang et al. (2008). The REC model results demonstrate that the proposed numerical procedure is well suited to estimate robust and reasonable rate profiles for relative concentration measurement uncertainties not larger than ±5%. At larger uncertainties, the model provides an estimation of a nearly constant mean rate profile. Our new approach has a similar performance as the PROFILE model of Berg et al. (1998) and the model of Wang et al. (2008). However, the REC model has the advantage of providing smooth rate profiles and estimation of the position of discrete zones of enhanced biogeochemical activities, more accurately. Highlights ► A novel procedure is proposed to estimate net rates from measured solute profiles. ► The estimation process builds on the one-dim. steady state diagenetic equation. ► This equation is robustly inverted by a technique called Tikhonov regularization. ► In contrast to other models in the literature, smooth rate profiles are obtained. ► The model estimates robust rate profiles for measurement uncertainties below 5%.