10 citations as recorded by crossref.

1. Coupling process-based models with machine learning for the prediction of soil carbon and nitrogen cycling X. Zhang et al. https://doi.org/10.1016/j.envsoft.2026.107089
2. Sediment pore-network architecture may shape spatial patterns of denitrification in freshwater littoral zones X. Zhao et al. https://doi.org/10.1016/j.watres.2026.126517
3. Modeling of dual-permeability gas and solute reactive transport in macroporous agricultural soils with a focus on GHG cycling and emissions M. Jia et al. https://doi.org/10.1016/j.jhydrol.2023.129408
4. Informing APSIM using 15N recovery data to establish fertiliser N budgets in grain systems N. Takeda et al. https://doi.org/10.1007/s10705-025-10403-x
5. Modeling coupled nitrification–denitrification in soil with an organic hotspot J. Zhang et al. https://doi.org/10.5194/bg-20-3895-2023
6. In-situ N2O and N2 data improved N budget simulation with APSIM and LandscapeDNDC in tropical sugarcane systems N. Takeda et al. https://doi.org/10.1016/j.agee.2024.109193
7. Modeling Denitrification: Can We Report What We Don't Know? B. Grosz et al. https://doi.org/10.1029/2023AV000990
8. Determining N2O and N2 fluxes in relation to winter wheat and sugar beet growth and development using the improved 15N gas flux method on the field scale J. Eckei et al. https://doi.org/10.1007/s00374-024-01806-z
9. The anaerobic soil volume as a controlling factor of denitrification: a review S. Schlüter et al. https://doi.org/10.1007/s00374-024-01819-8
10. Modeling nitrous oxide emissions from agricultural soil incubation experiments using CoupModel J. Zhang et al. https://doi.org/10.5194/bg-19-4811-2022