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<p>Understanding the dynamics of peatland methane (<span class="inline-formula">CH₄</span>) emissions and quantifying sources of uncertainty in estimating peatland <span class="inline-formula">CH₄</span> emissions are critical for mitigating climate change. The relative contributions of <span class="inline-formula">CH₄</span> emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of <span class="inline-formula">CH₄</span> to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled <span class="inline-formula">CH₄</span> emissions. To improve model simulations of <span class="inline-formula">CH₄</span> 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 <span class="inline-formula">CH₄</span> flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed <span class="inline-formula">CH₄</span> fluxes, the <span class="inline-formula">CH₄</span> emissions simulated by the EBG approach (RMSE <span class="inline-formula">=</span> 0.53) had a better agreement with observations than the ECT approach (RMSE <span class="inline-formula">=</span> 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 <span class="inline-formula">CH₄</span> concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both <span class="inline-formula">CH₄</span> flux and concentration data in model–data fusion, uncertainty of the modeled <span class="inline-formula">CH₄</span> concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on <span class="inline-formula">CH₄</span> flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the <span class="inline-formula">CH₄</span> production and emission pathways. Our results suggest that the EBG modeling approach better characterizes <span class="inline-formula">CH₄</span> emission and underlying mechanisms. Moreover, to achieve the best model results both <span class="inline-formula">CH₄</span> flux and concentration data are required to constrain model parameterization.</p>