Articles | Volume 18, issue 13
https://doi.org/10.5194/bg-18-4211-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-4211-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2021
Research article |
| 14 Jul 2021
| 14 Jul 2021
An improved process-oriented hydro-biogeochemical model for simulating dynamic fluxes of methane and nitrous oxide in alpine ecosystems with seasonally frozen soils
Wei Zhang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Zhisheng Yao
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Siqi Li
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Xunhua Zheng
CORRESPONDING AUTHOR
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
College of Earth and Planetary Sciences, University of the Chinese Academy
of Sciences, Beijing 100049, P. R. China
Han Zhang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
School of Geographic and Environmental Sciences, Tianjin Normal
University, Tianjin 300387, P. R. China
Lei Ma
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Institute of Meteorology and Climate Research, Atmospheric
Environmental Research (IMK-IFU), Karlsruhe Institute of Technology,
Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, Germany
Kai Wang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Rui Wang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Chunyan Liu
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Shenghui Han
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Jia Deng
Complex Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, 39 College Road, Durham, NH
03824, USA
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
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Cited
7 citations as recorded by crossref.
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. 10.1080/20964471.2024.2325019
- Shifting soil N regimes over a 70-year chronosequence of wetland reclamation and restoration K. Li et al. 10.1016/j.catena.2025.108727
- Modelling forest-atmosphere exchanges of carbon and water using an improved hydro-biogeochemical model in subtropical and temperate monsoon climates W. Zhang et al. 10.1016/j.ecolmodel.2025.111174
- Rodent-induced grassland degradation increases annual non-CO2 greenhouse gas fluxes and NO losses despite CH4 uptake enhancement Z. Yao et al. 10.1016/j.agrformet.2025.110534
- Enhancing forest ecosystem simulation in the TASC model through the integration of the DAYCENT forest model S. Dangol et al. 10.1016/j.envsoft.2025.106565
- On the potential of biogeochemical models to predict hot moments of N2O following dry-wet cycles L. Hey et al. 10.1016/j.aeaoa.2025.100347
- Research advancements on agricultural non-point source pollution in major lake and reservoir watersheds of China: Status, sources, monitoring, and prospects Y. Tian et al. 10.1016/j.ecolind.2025.113981
7 citations as recorded by crossref.
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. 10.1080/20964471.2024.2325019
- Shifting soil N regimes over a 70-year chronosequence of wetland reclamation and restoration K. Li et al. 10.1016/j.catena.2025.108727
- Modelling forest-atmosphere exchanges of carbon and water using an improved hydro-biogeochemical model in subtropical and temperate monsoon climates W. Zhang et al. 10.1016/j.ecolmodel.2025.111174
- Rodent-induced grassland degradation increases annual non-CO2 greenhouse gas fluxes and NO losses despite CH4 uptake enhancement Z. Yao et al. 10.1016/j.agrformet.2025.110534
- Enhancing forest ecosystem simulation in the TASC model through the integration of the DAYCENT forest model S. Dangol et al. 10.1016/j.envsoft.2025.106565
- On the potential of biogeochemical models to predict hot moments of N2O following dry-wet cycles L. Hey et al. 10.1016/j.aeaoa.2025.100347
- Research advancements on agricultural non-point source pollution in major lake and reservoir watersheds of China: Status, sources, monitoring, and prospects Y. Tian et al. 10.1016/j.ecolind.2025.113981
Latest update: 29 Aug 2025
Short summary
The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) is improved by incorporating a soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model is validated at a seasonally frozen catchment with typical alpine ecosystems (wetland, meadow and forest). The simulated aggregate emissions of methane and nitrous oxide are highest for the wetland, which is dominated by the methane emissions.
The hydro-biogeochemical model Catchment Nutrient Management Model –...
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