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Predicting methanogenesis from rice paddies using the DAYCENT ecosystem model

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  • Cheng, Kun
  • Ogle, Stephen M.
  • Parton, William J.
  • Pan, Genxing

Abstract

The prediction of methane (CH4) emissions from rice paddies could play a key role in greenhouse gas mitigation efforts associated with agriculture. We describe a methanogenesis sub-model that has been developed in the DAYCENT ecosystem model for estimating CH4 emissions and assessing mitigation potentials for rice paddies. Methanogenesis is modeled based on the simulation of soil hydrology and thermal regimes, rice plant growth, SOM decomposition, and CH4 transport from the soil to atmosphere. A total of 97 sites from China's rice paddies were used to develop and evaluate the model, in which 25 sites (91 observations) were used for parameterization and 72 sites (204 observations) were used for model evaluation. Comparison of modeled results with measurements demonstrated that CH4 emissions in rice paddies of China can be successfully simulated by the model with an overall R2 of 0.83, and included an evaluation of CH4 emissions for a range of climates and agricultural management practices. The model was most sensitive to parameters influencing the amount of labile C available for methanogenesis.

Suggested Citation

  • Cheng, Kun & Ogle, Stephen M. & Parton, William J. & Pan, Genxing, 2013. "Predicting methanogenesis from rice paddies using the DAYCENT ecosystem model," Ecological Modelling, Elsevier, vol. 261, pages 19-31.
    • Handle: RePEc:eee:ecomod:v:261-262:y:2013:i::p:19-31
    DOI: 10.1016/j.ecolmodel.2013.04.003
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    References listed on IDEAS

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    2. Huang, Jikun & Rozelle, Scott & Martin, William J. & Liu, Yu, 2007. "Distortions to Agricultural Incentives in China," Agricultural Distortions Working Paper Series 48478, World Bank.
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    Cited by:

    1. Rafique, Rashad & Kumar, Sandeep & Luo, Yiqi & Kiely, Gerard & Asrar, Ghassem, 2015. "An algorithmic calibration approach to identify globally optimal parameters for constraining the DayCent model," Ecological Modelling, Elsevier, vol. 297(C), pages 196-200.
    2. Khadiza Begum & Matthias Kuhnert & Jagadeesh Yeluripati & Stephen Ogle & William Parton & Md Abdul Kader & Pete Smith, 2018. "Model Based Regional Estimates of Soil Organic Carbon Sequestration and Greenhouse Gas Mitigation Potentials from Rice Croplands in Bangladesh," Land, MDPI, vol. 7(3), pages 1-18, July.

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