The thermal behaviour of French water bodies: From ponds to Lake Geneva - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue Journal of Great Lakes Research Année : 2020

The thermal behaviour of French water bodies: From ponds to Lake Geneva

Résumé

The management of French freshwater bodies (lakes, reservoirs, ponds, etc.) needs to face the challenges imposed by the effects of climate change and by legal requirements to develop standards for water temperature and other physicochemical indicators. While 1D hydrodynamical models could be helpful in improving the knowledge of the thermal and hydrodynamic behaviour of French water bodies, the scarcity of data for calibration and validation, in addition to the unavailability of some forcing data, makes their application difficult for most French water bodies. In this article we explore an alternative statistical approach that takes advantage of the available data in order to inform future modelling applications. We used official monitoring data and satellite measurements to study the thermal characteristics of more than 400 French water bodies (depth: 1–310 m, surface area: 0.1–577 km2, volume: 0.1–89,000 hm3). The objective was to identify the importance of size on their thermal behaviour. For this we analysed the annual temperature cycle, the summer temperature profiles and within-lake spatial variability. Together with size, geography and transparency determine the thermal behaviour of water bodies through complex interactions. As a result of the analysis we propose a classification of French water bodies as a function of depth and surface area that reflects the summer vertical temperature gradient and the processes influencing the deepening of the thermocline.
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Dates et versions

hal-03166974 , version 1 (11-03-2021)

Identifiants

Citer

Jordi Prats, Vincent Roubeix, Nathalie Reynaud, Thierry Tormos, Pierre-Alain Danis. The thermal behaviour of French water bodies: From ponds to Lake Geneva. Journal of Great Lakes Research, 2020, 46 (4), pp.718-731. ⟨10.1016/j.jglr.2020.04.001⟩. ⟨hal-03166974⟩
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