BG Biogeosciences BG Biogeosciences 1726-4189 Copernicus Publications Göttingen, Germany 10.5194/bg-11-1519-2014 Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications Ringeval B. https://orcid.org/0000-0001-8405-1304 1 2 3 4 5 Houweling S. https://orcid.org/0000-0002-6189-1009 1 2 van Bodegom P. M. https://orcid.org/0000-0003-0771-4500 3 Spahni R. https://orcid.org/0000-0002-4239-5130 6 van Beek R. https://orcid.org/0000-0002-4758-108X 7 Joos F. https://orcid.org/0000-0002-9483-6030 6 Röckmann T. https://orcid.org/0000-0002-6688-8968 1 Institute of Marine and Atmospheric research Utrecht (IMAU), Utrecht University, Utrecht, the Netherlands SRON Netherlands Institute for Space Research, Utrecht, the Netherlands Department of Systems Ecology, Vrije Universiteit, Amsterdam, the Netherlands INRA, UMR1391 ISPA, 33140 Villenave d'Ornon, France Bordeaux Science Agro, UMR1391 ISPA, 33170 Gradignan, France Climate and Environmental Physics, Physics Institute, and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland Department of Physical Geography, Utrecht University, Utrecht, the Netherlands European Commission GEOCARBON - Operational Global Carbon Observing System (283080) 21 03 2014 11 6 1519 1558 Copyright: © 2014 B. Ringeval et al. 2014 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://bg.copernicus.org/articles/11/1519/2014/bg-11-1519-2014.html The full text article is available as a PDF file from https://bg.copernicus.org/articles/11/1519/2014/bg-11-1519-2014.pdf

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH<sub>4</sub>) emissions and explain a large fraction of the observed CH<sub>4</sub> variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH<sub>4</sub> emissions. This publication documents a first step in the development of a process-based model of CH<sub>4</sub> emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH<sub>4</sub> emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH<sub>4</sub> flux densities were evaluated against field observations and regional flux inventories. Simulated CH<sub>4</sub> emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH<sub>4</sub> flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH<sub>4</sub> emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH<sub>4</sub> emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr<sup>−1</sup>. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH<sub>4</sub> emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH<sub>4</sub> emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH<sub>4</sub> emissions, and they stress the need for more research to constrain floodplain CH<sub>4</sub> emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

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