Preprints
https://doi.org/10.5194/gmd-2023-114
https://doi.org/10.5194/gmd-2023-114
Submitted as: model description paper
 | 
10 Jul 2023
Submitted as: model description paper |  | 10 Jul 2023
Status: a revised version of this preprint was accepted for the journal GMD.

Modeling biochar effects on soil organic carbon on croplands in the MIMICS (MIcrobial-MIneral Carbon Stabilization) model

Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li

Abstract. Biochar application in croplands aims to sequester carbon and improve soil quality, but its impact on soil organic carbon (SOC) dynamics is not represented in most land models used for assessing land-based climate mitigation, therefore we are unable to quantify the effect of biochar applications under different climate conditions or land management. To fill this gap, here we implemented a submodel to represent biochar into a microbial decomposition model named MIMICS (MIcrobial-MIneral Carbon Stabilization). We first calibrate MIMICS with new representations of density-dependent microbial turnover rate, adsorption of available organic carbon on mineral soil particles, and soil moisture effects on decomposition using global field measured cropland SOC at 58 sites. The calibration of MIMICS leads to an increase in explained spatial variation of SOC from 38 % in the default version to 47 %–52 % in the updated model with new representations. We further integrate biochar in MIMICS resolving its effect on microbial decomposition and SOC sorption/desorption and optimize two biochar-related parameters in these processes using 134 paired SOC measurements with and without biochar addition. The MIMICS-biochar version can generally reproduce the short-term (≤ 6 yr) and long-term (8 yr) SOC changes after adding biochar (mean addition rate: 25.6 t ha-1) (R2 = 0.65 and 0.84) with a low root mean square error (RMSE = 3.61 and 3.31 g kg-1). Our study incorporates sorption and soil moisture processes into MIMICS and extends its capacity to simulate biochar decomposition, providing a useful tool to couple with dynamic land models to evaluate the effectiveness of biochar applications on removing CO2 from the atmosphere.

Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2023-114', Juan Antonio Añel, 03 Aug 2023
    • AC1: 'Reply on CEC1', Wei Li, 09 Aug 2023
      • EC1: 'Reply on AC1', Sam Rabin, 11 Aug 2023
  • RC1: 'Comment on gmd-2023-114', Anonymous Referee #1, 07 Sep 2023
  • RC2: 'Comment on gmd-2023-114', William Wieder, 29 Sep 2023
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li

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Short summary
Because the impact of biochar on SOC dynamics is not represented in most land carbon models used for assessing land-based climate mitigation, our study develops a biochar model that incorporates our current understanding of biochar effects on SOC based on a soil carbon model (MIMICS) for future predictions at the regional and global scale. The MIMICS model was improved with new processes considered and the developed biochar model can generally reproduce the SOC changes after adding biochar.