Parametrization consequences of constraining soil organic matter models by total carbon and radiocarbon using long-term field data

Summary

This study addresses equifinality and parameter uncertainty in soil organic carbon models by comparing five model structures applied to long-term field data from the Zürich Organic Fertilization Experiment. By incorporating radiocarbon measurements alongside total carbon data as dual constraints during Bayesian calibration, the authors demonstrate that the relative weighting of these two data streams significantly influences estimated kinetic parameters. The findings suggest that combining radiocarbon chronology with conventional total-carbon measurements provides a critical approach to reducing model uncertainty in SOC dynamics studies.

UK applicability

The methodological approach is directly applicable to UK arable and mixed farming systems, particularly given the UK's climatic similarity to Switzerland and extensive soil monitoring infrastructure. The findings would inform more robust parameterisation of SOC models used in UK agricultural policy and soil carbon sequestration assessments.

Key measures

Soil organic carbon (SOC) pool sizes and turnover rates; radiocarbon (¹⁴C) concentrations; kinetic decomposition parameters; model parameter uncertainty (Bayesian calibration); model structural uncertainty across five SOC model variants

Outcomes reported

The study evaluated how radiocarbon (¹⁴C) measurements constrain soil organic carbon (SOC) model parameters when combined with total carbon data, using five different model structures applied to a 60+ year cropland experiment. The research quantified how the relative weighting of total SOC versus ¹⁴C data streams affects estimated kinetic parameters and model outcomes.

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