Articles | Volume 14, issue 1
Biogeosciences, 14, 163–176, 2017
https://doi.org/10.5194/bg-14-163-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Biogeosciences, 14, 163–176, 2017
https://doi.org/10.5194/bg-14-163-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
12 Jan 2017
Research article
| 12 Jan 2017
Uncertainties in the national inventory of methane emissions from rice cultivation: field measurements and modeling approaches
Wen Zhang et al.
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Cited
9 citations as recorded by crossref.
- Estimation of methane emissions based on crop yield and remote sensing data in a paddy field Y. Shi et al. 10.1002/ghg.1946
- Environmental Indicator Principium with Case References to Agricultural Soil, Water, and Air Quality and Model-Derived Indicators T. Zhang et al. 10.2134/jeq2017.10.0398
- Methane budget of East Asia, 1990–2015: A bottom-up evaluation A. Ito et al. 10.1016/j.scitotenv.2019.04.263
- The relationship between phosphine, methane, and ozone over paddy field in Guangzhou, China J. Ma et al. 10.1016/j.gecco.2019.e00581
- Decrease in the annual emissions of CH4 and N2O following the initial land management change from rice to vegetable production L. Wu et al. 10.1007/s11356-018-1559-4
- A comparative study of anthropogenic CH<sub>4</sub> emissions over China based on the ensembles of bottom-up inventories X. Lin et al. 10.5194/essd-13-1073-2021
- Quantitative analysis of the methane gas emissions from municipal solid waste in India C. Singh et al. 10.1038/s41598-018-21326-9
- Effects of irrigation regime and rice variety on greenhouse gas emissions and grain yields from paddy fields in central China Z. Feng et al. 10.1016/j.agwat.2021.106830
- Accuracy and uncertainty analysis of staple food crop modelling by the process-based Agro-C model Q. Zhang et al. 10.1007/s00484-020-02053-1
9 citations as recorded by crossref.
- Estimation of methane emissions based on crop yield and remote sensing data in a paddy field Y. Shi et al. 10.1002/ghg.1946
- Environmental Indicator Principium with Case References to Agricultural Soil, Water, and Air Quality and Model-Derived Indicators T. Zhang et al. 10.2134/jeq2017.10.0398
- Methane budget of East Asia, 1990–2015: A bottom-up evaluation A. Ito et al. 10.1016/j.scitotenv.2019.04.263
- The relationship between phosphine, methane, and ozone over paddy field in Guangzhou, China J. Ma et al. 10.1016/j.gecco.2019.e00581
- Decrease in the annual emissions of CH4 and N2O following the initial land management change from rice to vegetable production L. Wu et al. 10.1007/s11356-018-1559-4
- A comparative study of anthropogenic CH<sub>4</sub> emissions over China based on the ensembles of bottom-up inventories X. Lin et al. 10.5194/essd-13-1073-2021
- Quantitative analysis of the methane gas emissions from municipal solid waste in India C. Singh et al. 10.1038/s41598-018-21326-9
- Effects of irrigation regime and rice variety on greenhouse gas emissions and grain yields from paddy fields in central China Z. Feng et al. 10.1016/j.agwat.2021.106830
- Accuracy and uncertainty analysis of staple food crop modelling by the process-based Agro-C model Q. Zhang et al. 10.1007/s00484-020-02053-1
Latest update: 08 Aug 2022
Short summary
Regional estimated uncertainties originate from methodological failures, errors, and supporting data insufficiency. A case study showed that the fallacy of the CH4MOD contributed 56.6 % to the uncertainty of a national inventory, with the remaining 43.4 % attributed to the scarcity of model inputs. We also revealed a dilemma between model performance and data availability: a model with better performance may reduce uncertainty from model fallacy but increases the uncertainty from data scarcity.
Regional estimated uncertainties originate from methodological failures, errors, and supporting...
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