Influence of hydrological, biogeochemical and temperature transients on subsurface carbon fluxes in a flood plain environment
Published Web Locationhttps://doi.org/10.1007/s10533-016-0186-8
Flood plains play a potentially important role in the global carbon cycle. The accumulation of organic matter in flood plains often induces the formation of chemically reduced groundwater and sediments along riverbanks. In this study, our objective is to evaluate the cumulative impact of such reduced zones, water table fluctuations, and temperature gradients on subsurface carbon fluxes in a flood plain at Rifle, Colorado located along the Colorado River. 2-D coupled variably-saturated, non-isothermal flow and biogeochemical reactive transport modeling was applied to improve our understanding of the abiotic and microbially mediated reactions controlling carbon dynamics at the Rifle site. Model simulations considering only abiotic reactions (thus ignoring microbial reactions) underestimated CO₂ partial pressures observed in the unsaturated zone and severely underestimated inorganic (and overestimated organic) carbon fluxes to the river compared to simulations with biotic pathways. Both model simulations and field observations highlighted the need to include microbial contributions from chemolithoautotrophic processes (e.g., Fe⁺² and S⁻² oxidation) to match locally-observed high CO₂ concentrations above reduced zones. Observed seasonal variations in CO₂ concentrations in the unsaturated zone could not be reproduced without incorporating temperature gradients in the simulations. Incorporating temperature fluctuations resulted in an increase in the annual groundwater carbon fluxes to the river by 170 % to 3.3 g m⁻² d⁻¹, while including water table variations resulted in an overall decrease in the simulated fluxes. We conclude that spatial microbial and redox zonation as well as temporal fluctuations of temperature and water table depth contribute significantly to subsurface carbon fluxes in flood plains and need to be represented appropriately in model simulations.