Verifiable soil organic carbon modelling to facilitate regional reporting of cropland carbon change: a test case in the Czech Republic

Regional monitoring, reporting and verification of soil organic carbon change occurring in managed cropland are indispensable to support carbon-related policies. Rapidly evolving gridded agronomic models can facilitate the reporting and verification efforts throughout Europe. However, their performance in modelling soil carbon dynamics at regional scale is as of yet unexplored. Importantly, as such models are often driven by large-scale inputs, they need to be benchmarked against field experiments. In this study we elucidate the level of detail that needs to be incorporated in gridded models to robustly estimate regional soil carbon dynamics in managed cropland, testing the approach for regions in the Czech Republic. We first calibrated the biogeochemical Environmental Policy Integrated Climate (EPIC) model against long-term experiments. Subsequently, we examined EPIC within a top-down gridded modelling framework constructed for European agricultural soils from Europe-wide datasets and regional land-use statistics. We explored the top-down, as opposed to a bottom-up, modelling approach for reporting agronomically relevant and verifiable soil carbon dynamics. In comparison with a no-input baseline, the regional EPIC model suggested soil carbon changes (~0.1 to 0.5 Mg C ha–1 y–1) consistent with empirical-based studies for all studied agricultural practices. However, inaccurate soil information, crop management inputs, or inappropriate model calibration may undermine regional reporting since each of the three components imply uncertainty (~0.5 to 1.5 Mg C ha–1 y–1) that is substantially larger than the actual impact of high-input agricultural practices relative to the no-input baseline. Besides, inaccurate soil data obtained from the background datasets biased the simulated carbon trends compared to observations, thus hampering the model’s verifiability at the locations of field experiments. Encouragingly, the top-down agricultural management derived from regional land-use statistics proved suitable for the estimation of soil carbon dynamics consistently with actual field practices. Despite sensitivity to biophysical parameters, we found a robust scalability of the soil organic carbon routine for various climatic regions and soil types represented in the Czech experimental stations. The model performed better than the tier 1 methodology of the Intergovernmental Panel on Climate Change, which indicates a great potential for improved carbon change modelling over larger political regions.

BALKOVIC Juraj;  MADARAS Mikulas;  SKALSKY R;  FOLBERTH Chris;  SMATANOVA Michela;  SCHMID Erwin;  VAN DER VELDE Marijn;  KRAXNER Florian;  OBERSTEINER Michael; 

2021-07-02

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD

JRC121357

0301-4797 (online),   

https://www.sciencedirect.com/science/article/pii/S0301479720311312?via%3Dihub,    https://publications.jrc.ec.europa.eu/repository/handle/JRC121357,   

10.1016/j.jenvman.2020.111206 (online),