Linking Biogeochemical and Hydrodynamic Processes to Model Methane Fluxes in Shallow, Tropical Floodplain Lakes

Floodplains lakes are abundant in the Amazon basin and are important methane sources to the atmosphere. Existing biogeochemical models require modifications and inclusion of hydrodynamic processes operative in shallow, warm waters to be applied to these aquatic ecosystems. We modified a 1-dimensional process-based, lake biogeochemical model and combined a 3-dimensional hydrodynamic model to suit Amazon floodplains. We evaluated the combined model's performance simulating methane concentrations and fluxes and several related processes in the open lake and an embayment of a well-studied Amazon lake. Parameters for calibration were selected through sensitivity tests using a machine learning-based algorithm, classification, and regression trees. Comparison between simulated and measured fluxes indicate generally good agreement in seasonal patterns and magnitudes. Comparisons of near-surface concentrations varied with no clear patterns. Simulations of methane concentrations at near-surface and near-bottom, and diffusive emissions are most sensitive to carbon mineralization rate, Q10 factors for methanogenesis and oxidation, and methane oxidation potential. Modeled rates of planktonic photosynthesis were generally lower than measurements, though simulated planktonic respiration was often similar to measurements. Simulated rates of methane oxidation were considerably lower, with a few exceptions, than measurements of methane oxidation in oxic water of the lake. Improvements of results of the linked hydrodynamic-biogeochemical model will result from inclusion of advective transport, use of parameter values appropriate for tropical waters, especially for methane oxidation and photosynthesis, and addition of changes in hydrostatic pressure to model of ebullition. Methane emissions from lakes are large, highly variable and without adequate measurements, especially in tropical regions. The combination of mechanistic models with results from intensive field data provides one way to improve understanding of the processes and sources of variability. Riverine floodplain lakes, as occur in the Amazon basin, constitute extensive aquatic ecosystems and are important methane sources to the atmosphere. Though tropical lakes typically experience muted seasonal variations in climate, strong diel changes occur, and floodplain lakes have additional biogeochemical and ecological variability caused by changes in water level, connectivity to rivers and optical properties. We modified a one-dimensional process-based, lake biogeochemical model and combined a 3-dimensional hydrodynamic model to be applicable to Amazon floodplains and similar shallow, warm waters. The combined model simulated well methane processes and fluxes based on evaluation using observations in a representative central Amazon floodplain lake with measurements of meteorological variables, water temperatures and ecological conditions, and methane emissions over the seasonal hydrological phases with large differences in water levels. Methane fluxes from Amazon floodplains lakes simulated with biogeochemical model combined with hydrodynamic modelSeasonal patterns and magnitudes of simulated and measured fluxes are generally in good agreementMethane concentrations and diffusive emissions are sensitive to carbon mineralization and methane production and oxidation