Lakes emit substantial amounts of carbon dioxide (CO₂) into the atmosphere, but why they do remains debated. The long-standing vision of lakes as solely respirators of the organic matter leaking from the soils has been challenged by evidence that inorganic carbon produced by weathering of the catchment bedrock could also support lake CO₂ emissions. How inorganic carbon inputs ultimately generate lake CO₂ outgassing remains a blind spot. We develop and introduce a calcite module in a coupled one-dimensional physical-biogeochemical model that we use to simulate the carbon cycle of the large Lake Geneva over the past 40 years. We mechanistically demonstrate how the so-far neglected process of calcite precipitation boosts net CO₂ emissions at the annual scale. Far from being anecdotal, we show that calcite precipitation could explain CO₂ outgassing across various lakes globally, including some of the largest lakes in the world.

Lake Kivu is a 485 m deep, Central-East African rift lake with huge amounts of carbon dioxide and methane dissolved in its stably stratified deep waters. In view of future large-scale methane extraction, one-dimensional numerical modelling is an important and computationally inexpensive tool to analyze the evolution of stratification and the content of gases in Lake Kivu. For this purpose, we coupled the physical lake model Simstrat to the biogeochemical library AED2. Compared to an earlier modelling approach, this coupled approach offers several key improvements, most importantly the dynamic evaluation of mixing processes over the whole water column, including a parameterization for double-diffusive transport, and the density-dependent stratification of groundwater inflows. The coupled model successfully reproduces today's near steady-state of Lake Kivu, and we demonstrate that a complete mixing event ∼2000 years ago is compatible with today's physical and biogeochemical state.

Lake Kivu is a 485 m deep tropical rift lake in East-Africa and well-known for its very high concentrations of dissolved carbon dioxide and methane in the stratified deep waters. In view of future large-scale methane extraction for power production, there is a need for predicting the evolution of gas concentrations and lake stability using numerical modelling. However, knowledge about the geochemical origin and transport processes affecting dissolved gases in the lake is still partially missing. Due to their inert nature, the analysis of dissolved noble gases can help to shed light on such questions. To learn more about transport processes in Lake Kivu, we extended a well-established sampling method for dissolved noble gases to work in the lake's high gas pressure waters. The results of our analysis show a distinct non-atmospheric isotopic signal in the deep waters (below 250 m) with ³He/⁴He and ⁴⁰Ar/³⁶Ar ratios ~250% and ~20% higher than air saturated water (ASW). Moreover, the gas concentration profiles reveal a striking lack of atmospheric noble gases in the deep waters with respect to ASW. While Ne is depleted by ~45%, the more soluble ³⁶Ar and Kr even decrease by ~70%. In contrast, ⁴He concentrations increase with depth by a factor of up to ~600. We attribute this excess He and the increases in ³He/⁴He and ⁴⁰Ar/³⁶Ar to the inflow of magmatic gases into Lake Kivu, along with a significant contribution of radiogenic ⁴He. To explain the depletion of atmospheric noble gases, we present and discuss three different scenarios, namely continuous outgassing, the inflow of depleted groundwater and a large past outgassing event. Due to the best agreement with our observations, we conclude that the inflow of depleted groundwater is likely responsible for the observed atmospheric noble gas depletions.

Lake Kivu, East Africa, is well known for its huge reservoir of dissolved methane (CH₄) and carbon dioxide (CO₂) in the stratified deep waters (below 250 m). The methane concentrations of up to ~ 20 mmol/l are sufficiently high for commercial gas extraction and power production. In view of the projected extraction capacity of up to several hundred MW in the next decades, reliable and accurate gas measurement techniques are required to closely monitor the evolution of gas concentrations. For this purpose, an intercomparison campaign for dissolved gas measurements was planned and conducted in March 2018. The applied measurement techniques included on-site mass spectrometry of continuously pumped sample water, gas chromatography of in-situ filled gas bags, an in-situ membrane inlet laser spectrometer sensor and a prototype sensor for total dissolved gas pressure (TDGP). We present the results of three datasets for CH₄, two for CO₂ and one for TDGP. The resulting methane profiles show a good agreement within a range of around 5-10% in the deep water. We also observe that TDGP measurements in the deep waters are systematically around 5 to 10% lower than TDGP computed from gas concentrations. Part of this difference may be attributed to the non-trivial conversion of concentration to partial pressure in gas-rich Lake Kivu. When comparing our data to past measurements, we cannot verify the previously suggested increase in methane concentrations since 1974. We therefore conclude that the methane and carbon dioxide concentrations in Lake Kivu are currently close to a steady state.

One-dimensional hydrodynamic models are nowadays widely recognized as key tools for lake studies. They offer the possibility to analyze processes at high frequency, here referring to hourly timescales, to investigate scenarios and test hypotheses. Yet, simulation outputs are mainly used by the modellers themselves and often not easily reachable for the outside community. We have developed an open-access web-based platform for visualization and promotion of easy access to lake model output data updated in near-real time (http://simstrat.eawag.ch, last access: 29 August 2019). This platform was developed for 54 lakes in Switzerland with potential for adaptation to other regions or at global scale using appropriate forcing input data. The benefit of this data platform is practically illustrated with two examples. First, we show that the output data allows for assessing the long-term effects of past climate change on the thermal structure of a lake. The study confirms the need to not only evaluate changes in all atmospheric forcing but also changes in the watershed or throughflow heat energy and changes in light penetration to assess the lake thermal structure. Then, we show how the data platform can be used to study and compare the role of episodic strong wind events for different lakes on a regional scale and especially how their thermal structure is temporarily destabilized. With this open-access data platform, we demonstrate a new path forward for scientists and practitioners promoting a cross exchange of expertise through openly sharing in situ and model data.