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Using DNDC models with two assimilation algorithms to simulate N2O emissions from a farmland after biochar added

Author

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  • Chen, Can
  • Wang, Kexin
  • Zhu, Hongxia

Abstract

As a greenhouse gas in the atmosphere, N2O has been widely concerned by scientists because of its high warming potential. Using modeling methods to simulate N2O emissions from farmland is the main one of current research approaches. In this study, the coupled assimilation method is used to compare the Denitrification-Decomposition (DNDC) model simulation results with the measured data. The results were as follows: (1) The DNDC model without assimilation has poor effectiveness in simulating the daily N2O emission flux and total N2O emissions from farmland after biochar added. The simulation accuracy of N2O emissions is: r = 0.677, R2 = 0.458, RMSE = 0.892; (2) The DNDC model, assimilated by simulating annealing (SA) algorithm and Bayesian inference (BI) algorithm, has significantly improved the simulation accuracy of daily N2O emissions flux and total N2O emissions from farmland after biochar added. The SA algorithm simulation accuracy of N2O emission is: r = 0.964, R2 = 0.929, RMSE = 0.18. The BI algorithm simulation accuracy of N2O emission is: r = 0.917, R2 = 0.841, RMSE = 0.29. From the uncertainty analysis of this study, it could be inferred that 50 % of the calibration points could already meet the DNDC simulation accuracy requirements for the assimilation algorithm. The simulation accuracy of SA algorithm after assimilation is higher than BI algorithm. The results of this study provide scientific data for using the DNDC model to increase the accuracy of simulating N2O emissions after biochar added.

Suggested Citation

  • Chen, Can & Wang, Kexin & Zhu, Hongxia, 2025. "Using DNDC models with two assimilation algorithms to simulate N2O emissions from a farmland after biochar added," Ecological Modelling, Elsevier, vol. 510(C).
    • Handle: RePEc:eee:ecomod:v:510:y:2025:i:c:s0304380025002650
    DOI: 10.1016/j.ecolmodel.2025.111279
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