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Communication dans un congrès

Coupling high-frequency measurements and predictive modelling in a monitoring and early warning system of cyanobacteria blooms

Abstract : Anthropogenic activities have major impacts on the ecological quality of downstream water bodies. The degradation of the water quality can lead to toxic cyanobacteria blooms, which in turn may cause serious health risks to people doing water sports. Due to the complexity of natural processes in water bodies, physically-based and spatially distributed models are valuable tools for a better understanding of the interactions between variables driving cyanobacteria blooms, as well as for helping stakeholders determine their management strategies. However, traditional in situ measurements have too limited temporal and spatial resolution to make such a numerical model reliable. Efforts must be made to use innovative monitoring to overcome these limitations. Continuous in situ measurements provided by automated high-frequency monitoring can decisively improve model performances. Therefore, the main objectives of the study were to (i) set up a full-scale experimental site for high-frequency monitoring of cyanobacteria biomass in an urban lake; (ii) couple the high-frequency measurements and a physically-based three-dimensional hydro-ecological model for predicting cyanobacteria blooms; (iii) establish a transfer platform for real-time data management; and (iv) develop a web platform for communicating information with lake managers, other stakeholders and the public. In the framework of the OSS-cyano project, the study site is Lake Champs-sur-Marne (0.12 km2 surface, 3.5 m maximum depth), located in Greater Paris. The field monitoring includes measurements of water temperature, dissolved oxygen, chlorophyll fluorescence and phycocyanin fluorescence every fifth minute, and fortnightly vertical profiles of temperature and of the fluorescence of the main phytoplankton groups. The Delft3D hydrodynamic and ecological models, respectively Flow and Bloom, were implemented. Using continuous measurements and short-term meteorological forecast, a predictive modelling of the cyanobacteria biomass evolution over a week was performed. Simulation results were then communicated to the lake manager and the public through a web platform for sanitary risk warning.
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Communication dans un congrès
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https://hal-enpc.archives-ouvertes.fr/hal-01961019
Contributeur : Bruno J. Lemaire <>
Soumis le : mercredi 19 décembre 2018 - 16:26:51
Dernière modification le : mardi 22 septembre 2020 - 03:47:40

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  • HAL Id : hal-01961019, version 1

Citation

Brigitte Vinçon-Leite, Yi Hong, Viet Tran Khac, Denis Plec, Chenlu Li, et al.. Coupling high-frequency measurements and predictive modelling in a monitoring and early warning system of cyanobacteria blooms. 18th International Conference on Harmful Algae (ICHA 2018), Oct 2018, Nantes, France. ⟨hal-01961019⟩

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