Uncertainties in modelling CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; emissions from northern wetlands in glacial climates: the role of vegetation parameters

Berrittella, C.; Huissteden, J. van

doi:10.5194/cp-7-1075-2011

Cited by 17 publications

(15 citation statements)

References 72 publications

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“…Some observations can, however, be made. In several studies, the parameters affecting the CH 4 production rate have been found important (Wania et al, 2010;Berrittella and van Huissteden, 2011), which corresponds to our result that the input anoxic respiration rate affects the output significantly. Wania et al (2010) tested the effect of tiller porosity on the CH 4 emissions and found that at four out of five of their sites, greater porosity increased the total CH 4 flux because of enhanced plant transport of CH 4 , despite the fact that also O 2 transport increased.…”

Section: Testsupporting

confidence: 50%

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

et al. 2017

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Abstract. Wetlands are one of the most significant natural sources of methane (CH 4 ) to the atmosphere. They emit CH 4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH 4 , in addition to carbon dioxide (CO 2 ). Production of CH 4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH 4 emissions are thus needed for upscaling observations to estimate present CH 4 emissions and for producing scenarios of future atmospheric CH 4 concentrations. Aiming at a CH 4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH 4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH 4 , CO 2 , and oxygen (O 2 ) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH 4 -related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH 4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH 4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of Published by Copernicus Publications on behalf of the European Geosciences Union. 4666M. Raivonen et al.: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands the total CH 4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O 2 concentrations that affect the CH 4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH 4 emissions in this model version.

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Section: Testsupporting

confidence: 50%

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

et al. 2017

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“…The rates of potential oxidation ranged from 0 to 80 μmol g dw −1 day − 1 (Kip et al, 2012;Larmola et al, 2010;Raghoebarsing et al, 2005). The above variations have been ascribed to differences in the CH 4 substrate, plant transport and oxidation of CH 4 and can be reproduced by plot-scale models if the vegetation parameters of the model are correctly specified (Berrittella and Huissteden, 2011;Huissteden et al, 2009;Parmentier et al, 2011). The present regional or global scale model simulations of CH 4 fluxes often lumped the effects of all vegetation together, which may induce large uncertainties in the estimates (Melton et al, 2013;Meng et al, 2015;Petrescu et al, 2010;Zhu et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland

Raivonen

Alekseychik

et al. 2016

Science of The Total Environment

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• CH 4 emission from Finnish wetlands was simulated by CH4MOD wetland .• We recalibrated the vegetation parameters of graminoids, shrubs and Sphagnum.• Simulated CH 4 variations agreed well with the eddy-covariance observations. • Annual CH 4 emissions were reasonably simulated in different years and sites.• Parameterization of different vegetation process was essential in long-term CH 4 estimates. Boreal/arctic wetlands are dominated by diverse plant species, which vary in their contribution to CH 4 production, oxidation and transport processes. Earlier studies have often lumped the processes all together, which may induce large uncertainties into the results. We present a novel model, which includes three vegetation classes and can be used to simulate CH 4 emissions from boreal and arctic treeless wetlands. The model is based on an earlier biogeophysical model, CH4MOD wetland . We grouped the vegetation as graminoids, shrubs and Sphagnum and recalibrated the vegetation parameters according to their different CH 4 production, oxidation and transport capacities. Then, we used eddy-covariance-based CH 4 flux observations from a boreal (Siikaneva) and a subarctic fen , which was consistent with the observations (7-22 g m −2 yr −1 G R A P H I C A L A B S T R A C T a b s t r a c t a r t i c l e i n f o). However, there are some discrepancies between the simulated and observed daily CH 4 fluxes for the Siikaneva site (RMSE = 50.0%) and the Lompolojänkkä site (RMSE = 47.9%). Model sensitivity analysis showed that increasing the proportion of the graminoids would significantly increase the CH 4 emission levels. Our study demonstrated that the parameterization of the different vegetation processes was important in estimating long-term wetland CH 4 emissions.

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“…Some of the scatter in model sensitivities to drivers may come from differences in the values of parameters related to methane production, methane oxidation, and plant-aided transport, which recent studies (Riley et al, 2011;Berrittella and van Huissteden, 2011) have found to be particularly influential over wetland CH 4 emissions. The investigation of these parameters over the WSL in a model intercomparison can be difficult due to the many large differences among model formulations.…”

Section: Temporal Variability Environmental Drivers and Model Featuresmentioning

confidence: 99%

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

et al. 2015

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Abstract. Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the perPublished by Copernicus Publications on behalf of the European Geosciences Union. T. J. Bohn et al.: Intercomparison of wetland methane emissions modelsformance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH 4 emissions, simulated wetland areas, and CH 4 fluxes per unit wetland area and compared these results to an intensive in situ CH 4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH 4 yr −1 ), inversions (6.06 ± 1.22 Tg CH 4 yr −1 ), and in situ observations (3.91 ± 1.29 Tg CH 4 yr −1 ) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH 4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

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Uncertainties in modelling CH<sub>4</sub> emissions from northern wetlands in glacial climates: the role of vegetation parameters

Cited by 17 publications

References 72 publications

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

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