Articles | Volume 14, issue 1
Biogeosciences, 14, 163–176, 2017
https://doi.org/10.5194/bg-14-163-2017
Biogeosciences, 14, 163–176, 2017
https://doi.org/10.5194/bg-14-163-2017
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 articles

Aulakh, M., Wassmann, R., and Rennenberg, H.: Pattern and amount of aerenchyma relate to variable methane transport capacity of different rice cultivars, Plant Biol., 2, 182–194, 2008.
Bachelet, D. and Neue, H.: Methane emissions from wetland rice areas of Asia, Chemosphere, 26, 219–237, 1993.
Bachelet, D., Kern, J., and Toelg, M.: Balancing the rice carbon budget in China using spatially-distributed data, Ecol. Model., 79, 167–177, 1995.
Banger, K., Tian, H., and Lu, C.: Do nitrogen fertilizers stimulate or inhibit methane emissions from rice fields?, Glob. Change Biol., 18, 3259–3267, 2012.
Bhatia, A., Ghosh, A., Kumar, V., Tomer, R., Singh, S., and Pathak, H.: Effect of elevated tropospheric ozone on methane and nitrous oxide emission from rice soil in north India, Agr. Ecosyst. Environ., 144, 21–28, 2011.
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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.
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