Acoustic Mapping of Gas Stored in Sediments of Shallow Aquatic Systems Linked to Methane Production and Ebullition Patterns - Marcon, Lediane; Sotiri, Klajdi; Bleninger, Tobias; Lorke, Andreas; Männich, Michael; Hilgert, Stephan (Frontiers in Environmental Science, 2022)
Bubble-mediated transport is the predominant pathway of methane emissions from inland waters, which are a globally significant sources of the potent greenhouse gas to the atmosphere. High uncertainties exist in emission estimates due to high spatial and temporal variability. Acoustic methods have been applied for the spatial mapping of ebullition rates by quantification of rising gas bubbles in the water column. However, the high temporal variability of ebullition fluxes can influence estimates of mean emission rates if they are based on reduced surveys. On the other hand, echo sounding has been successfully applied to detect free gas stored in the sediment, which provide insights into the spatial variability of methane production and release. In this study, a subtropical, midsize, mesotrophic drinking water reservoir in Brazil was investigated to address the spatial and temporal variability of free gas stored in the sediment matrix. High spatial resolution maps of gas content in the sediment were estimated from echo-sounding surveys. The gas content was analyzed in relation to water depth, sediment deposition, and organic matter content (OMC) available from previous studies, to investigate its spatial variability. The analysis was further supported by measurements of potential methane production rates, porewater methane concentration, and ebullition flux. The largest gas content (above average) was found at locations with high sediment deposition, and its magnitude depended on the water depth. At shallow water depth (< 10 m), high methane production rates support gas-rich sediment, and ebullition is observed to occur rather continuously. At larger water depth (> 12 m), the gas stored in the sediment is released episodically during short events. An artificial neural network model was successfully trained to predict the gas content in the sediment as a function of water depth, OMC, and sediment thickness (R² = 0.89). Largest discrepancies were observed in the regions with steep slopes and for low areal gas content (< 4 L m−2). Although further improvements are proposed, we demonstrate the potential of echo-sounding for gas detection in the sediment, which combined with sediment and water body characteristics provides insights into the process that regulate methane emissions from inland waters.