| Summary: | The role of lakes and reservoirs as significant emitters of the potent greenhouse gas methane (CH4) to the atmosphere is well established, but several uncertainties remain particularly due to knowledge gaps in the relationship between CH4 dynamics and sediment characteristics, which limit our capabilities to provide robust estimates of CH4 fluxes from lakes. In my thesis, I investigated CH4 formation and CH4 bubble emissions (ebullition) in lakes, with a particular focus on sediment characteristics that control these processes, using different approaches such as laboratory experiments, field surveys and process-based modelling. Sediment incubation experiments have revealed that CH4 formation rates can be predicted based on the age and total nitrogen content of the sediment. This relationship holds true across a wide range of sediment types found in various climates, ranging from alpine tundra to tropical regions, and can be effectively estimated by a common empirical model. Additionally, the supply and the quality of organic matter play a crucial role in determining the extent of CH4 formation in the sediment. Moreover, frequent additions of organic matter to surface sediment enhance the speed of CH4 formation rates. Importantly, the relationship between organic matter supply, its quality and frequency of addition with CH4 formation rates can be predicted with a logistic model. Field surveys conducted in a small eutrophic lake revealed that the spatial variability in CH4 ebullition is regulated by site-specific sediment characteristics: high CH4 ebullition rates were observed in areas characterized by elevated organic matter density in surface sediment and temporary sediment deposition, although no correlation was found with sediment accumulation rates. The use of a 1D model to simulate CH4 fluxes from a lake demonstrated its ability to simulate fairly well the whole-lake average CH4 ebullition fluxes observed in the field, despite experiencing some interannual variability in model performance. However, when ...
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