06 Jun 2023
 | 06 Jun 2023
Status: this preprint is open for discussion.

Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)

Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and Rene Dechow

Abstract. Simulation models are tools commonly used to predict changes in soil carbon stocks. Prior validation is essential, however, for determining the reliability and applicability of model results. In this study, the process-based biogeochemical model MONICA (Model of Nitrogen and Carbon dynamics on Agro-ecosystems) was evaluated with respect to soil organic carbon (SOC) using long-term monitoring data from 46 German agricultural sites. A revision and parameterisation of equations, encompassing crop and fertiliser-specific C contents and the abiotic factors of soil temperature, soil water and clay content, were undertaken and included in the model. The modified version was also used for a Morris elementary effects screening method, which confirmed the importance of environmental and management factors to the model’s performance. The model was then calibrated by means of Bayesian inference using the Metropolis-Hastings algorithm. The performance of the MONICA model was compared with that of five established carbon turnover models (CCB, CENTURY, C-TOOL, ICBM and RothC). The original MONICA model systematically overestimated SOC decomposition rates and produced on average a ~17 % greater mean absolute error (MAE) than the other models. The modification and calibration significantly improved its performance, reducing the MAE by ~30 %. Consequently, MONICA outperformed CENTURY, CCB and C-TOOL, and produced results comparable with ICBM and RothC. Use of the modified model allowed mostly adequate reproduction of site-specific SOC stocks, while the availability of a nitrogen, plant growth and water submodel enhanced its applicability compared with models that only describe carbon dynamics.

Konstantin Aiteew et al.

Status: open (until 20 Oct 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on egusphere-2023-760', Juan Antonio Añel, 31 Jul 2023 reply
    • AC1: 'Reply on CEC1', Konstantin Aiteew, 03 Aug 2023 reply
      • CEC2: 'Reply on AC1', Juan Antonio Añel, 03 Aug 2023 reply
        • AC3: 'Reply on CEC2', Konstantin Aiteew, 04 Aug 2023 reply
  • RC1: 'Comment on egusphere-2023-760', Lorenzo Menichetti, 01 Aug 2023 reply
    • AC2: 'Reply on RC1', Konstantin Aiteew, 04 Aug 2023 reply
      • RC2: 'Reply on AC2', Lorenzo Menichetti, 07 Aug 2023 reply
        • AC4: 'Reply on RC2', Konstantin Aiteew, 18 Aug 2023 reply

Konstantin Aiteew et al.

Konstantin Aiteew et al.


Total article views: 346 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
231 93 22 346 4 6
  • HTML: 231
  • PDF: 93
  • XML: 22
  • Total: 346
  • BibTeX: 4
  • EndNote: 6
Views and downloads (calculated since 06 Jun 2023)
Cumulative views and downloads (calculated since 06 Jun 2023)

Viewed (geographical distribution)

Total article views: 341 (including HTML, PDF, and XML) Thereof 341 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 22 Sep 2023
Short summary
This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of SOC stock change rates was achieved. The MONICA model was capable of performing similarly or even better than the other models.