Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data-model fusion
- 1Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, Arizona, USA
- 2Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA
- 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- 4Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, Florida, USA
- 5Institute of Ecology & Evolution, University of Oregon, Eugene, Oregon, USA
- 6Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- 7Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
- 8Department of Earth System Science, Stanford University, Stanford, California, USA
- 9Department of Soil and Water Conservation, Nanjing Forestry University, Nanjing, Jiangsu, China
- 10School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
- 11CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
- 12Schmid College of Science and Technology, Chapman University, Orange, USA
- 13Biology Department, San Diego State University, San Diego, California, USA
Abstract. Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion together with their different transport rates and vulnerability to oxidation determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways have not been well characterized by experiments or modeling approaches. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: 1) the Ebullition Bubble Growth volume threshold approach (EBG) and 2) the modified Ebullition Concentration Threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model-data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization.
Shuang Ma et al.
Shuang Ma et al.
Data sets for Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data-model fusion 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 https://doi.org/10.5281/zenodo.5722449
Shuang Ma et al.
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