One of the largest sources of methane are wetlands, contributing about 20 to 40 % to global sources. However, process-based methane emission modeling is afflicted with large uncertainty. We developed a new Methane model which was derived from simplifying complex global land surface models. Our main goal is to develop a readily applicable model using the software R, allowing scientists who are not primary modelers to adapt the model quickly and effortlessly to their needs. In a first step we aim to determine the sensitivity of the model to specific setups, parameter choices, and to boundary conditions in order to determine set-up needs and inform what critical auxiliary variables need to be measured in order to better predict field-scale methane emissions from wetland soils.
In a first step we tested the numerical setup including the number and size of soil layers and length time steps, both critical to model performance and thus to the ease of use. We then tested the sensitivity to fluctuating water table, and how plant affect methane emissions via rooting depth facilitating methane transport from deep layers and via possible emissions through aerenchyma transport.
Testing the model under fluctuating water tables, we found that the model is relatively insensitive to vertical spacing. More important, however, was the overall depth of the soil column. Deeper depths act as a long-term buffer of methane, which affects transient emissions of methane. The results thus suggest, that application of the model in the field requires information on overall potential pore space throughout the soil column.
When evaluated at steady state net primary productivity (NPP) balances heterotrophic soil CO2 production and net methane outflow. We found, that perennial inundated soils yielded 26% of primary production emitted as methane, if NPP is 50 mol C m-2 yr-1. This fraction drops to 7% in the case where the water table is above the surface only during half of the year. The influence of the role of plant conduits for gas transport (araenchyma), and rooting depth is negligible.
In a next step, we will perform a global sensitivity analysis, which will help determining specific measurements that better constrain the methane emissions model. This characterization and its relative simple structure will make the model an effective tool for process-oriented analysis of field and laboratory data.