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. The gas transfer velocity (k) is a major source of uncertainty when assessing the magnitude of lake gas exchange with the atmosphere. For thediversity of existing empirical and process-based k models, the transfer velocity increases with the level of turbulence near the air–waterinterface. However, predictions for k can vary by a factor of 2 among different models. Near-surface turbulence results from the action of windshear, surface waves, and buoyancy-driven convection. Wind shear has long been identified as a key driver, but recent lake studies have shifted thefocus towards the role of convection, particularly in small lakes. In large lakes, wind fetch can, however, be long enough to generate surface wavesand contribute to enhance gas transfer, as widely recognised in oceanographic studies. Here, field values for gas transfer velocity were computed ina large hard-water lake, Lake Geneva, from CO2 fluxes measured with an automated (forced diffusion) flux chamber and CO2 partialpressure measured with high-frequency sensors. k estimates were compared to a set of reference limnological and oceanic k models. Our analysisreveals that accounting for surface waves generated during windy events significantly improves the accuracy of k estimates in this large lake. Theimproved k model is then used to compute k over a 1-year time period. Results show that episodic extreme events with surface waves (6 %occurrence, significant wave height &gt; 0.4 m) can generate more than 20 % of annual cumulative k and more than 25 % of annualnet CO2 fluxes in Lake Geneva. We conclude that for lakes whose fetch can exceed 15 km, k models need to integrate the effect ofsurface waves.

Accounting for surface waves improves gas flux estimation at high wind speed in a large lake