EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Power-law thermal stratification in lake Geneva and its seasonal evolution

Vinicius Beltram Tergolina1, Yueting Jiang2, François Schmitt3, Stefano Berti1, Enrico Calzavarini1, and Orlane Anneville4
Vinicius Beltram Tergolina et al.
  • 1ULR 7512 - Unité de Mécanique de Lille Joseph Boussinesq (UML), Université de Lille, Villeneuve D'Ascq, France
  • 2Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  • 3Laboratoire d’Océanologie et de Géosciences (LOG), Wimereux, France
  • 4Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Lake Geneva is one of the largest bodies of water in western Europe and the largest one in the Alps region. Besides its obvious touristic importance it supplies drinking water for a large portion of Switzerland and work for hundreds of commercial fishermen. It has been under constant monitoring since the 1970's, for the impact of human activities on its water quality and biodiversity. The lake is known to be a warm monomictic lake, thermally stratified through most of the year with the exception of winter, when small thermal vertical gradients permit mixing from top to bottom. In lake Geneva, thermal stratification is one of the main environmental drivers of phytoplankton communities which are widely used as bioindicators for freshwater ecosystems. Studies on thermal stratification are thus essential to better predict phytoplankton seasonality and the development of harmful species blooms. In this work we examine more than 20 years of surveillance data from the INRAE (National Research Institute for Agriculture, Food and Environment) regarding temperature vertical profiles and meteorological data. We review both the climatology and the temperature stratification history of the lake and refine the temperature depth profiles obtaining the yearly progressions of the mixed layer depths. We then discuss the fitting of the depth profiles through the use of power-law and exponential functions, finding that in 66% of the cases the power-law better describes the experimental data, and we report the probability density function of the related statistics throughout the seasons.  Finally, we discuss the implications of our results for the modelling of the lake turbulent regime and phytoplankton seasonality.

How to cite: Beltram Tergolina, V., Jiang, Y., Schmitt, F., Berti, S., Calzavarini, E., and Anneville, O.: Power-law thermal stratification in lake Geneva and its seasonal evolution, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8821,, 2021.

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