Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

Ma, Shuang; Jiang, Lifen; Wilson, Rachel M.; Chanton, Jeff P.; Bridgham, Scott; Niu, Shuli; Iversen, Colleen M.; Malhotra, Avni; Jiang, Jiang; Lu, Xingjie; Huang, Yuanyuan; Keller, Jason; Xu, Xiaofeng; Ricciuto, Daniel M.; Hanson, Paul J.; Luo, Yiqi

doi:https://doi.org/10.5194/bg-19-2245-2022

Articles | Volume 19, issue 8

https://doi.org/10.5194/bg-19-2245-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-19-2245-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 8

Research article

|

27 Apr 2022

Research article |

| 27 Apr 2022

Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo

Supplement

https://doi.org/10.5194/bg-19-2245-2022-supplement

Data sets

Data sets for Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data-model fusion S. Ma, L. Jiang, R. M. Wilson, J. P. Chanton, S. Bridgham, S. Niu, C. M. Iversen, A. Malhotra, J. Jiang, X. Lu, Y. Huang, J. Keller, X. Xu, D. M. Ricciuto, P. J. Hanson, and Y. Luo https://doi.org/10.5281/zenodo.5722449

Model code and software

Model code for Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data-model fusion S. Ma, L. Jiang, R. M. Wilson, J. P. Chanton, S. Bridgham, S. Niu, C. M. Iversen, A. Malhotra, J. Jiang, X. Lu, Y. Huang, J. Keller, X. Xu, D. M. Ricciuto, P. J. Hanson, and Y. Luo https://doi.org/10.5281/zenodo.5722449

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Short summary

The relative ratio of wetland methane (CH₄) emission pathways determines how much CH₄ is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH₄ concentration. We suggest using this approach in land surface models to accurately represent CH₄ emission dynamics and response to climate change. Our results also highlight that both CH₄ flux and belowground concentration data are important to constrain model parameters.