An Automatic Monitoring System for High-Frequency Measuring and Real-Time Management of Cyanobacterial Blooms in Urban Water Bodies

Abstract : Urban lakes mitigate the negative impacts on the hydrological cycle and improve the quality of life in cities. Worldwide, the concern increases for the protection and management of urban water bodies. Since the physical-chemical and biological conditions of a small aquatic ecosystem can vary rapidly over time, traditional low frequency measurement approaches (weekly or monthly sampling) limits the knowledge and the transfer of research outcomes to management decision-making. In this context, this paper presents an automatic monitoring system including a full-scale experimental site and a data transfer platform for high-frequency observations (every 5 min) in a small and shallow urban lake (Lake Champs-sur-Marne, Paris, France, 10.3 ha). Lake stratification and mixing periods can be clearly observed, these periods are compared with the dynamic patterns of chlorophyll-a, phycocyanin, dissolved oxygen and pH. The results indicate that the phytoplankton growth corresponds with dissolved oxygen cycles. However, thermal stratification cannot totally explain the entire dynamic patterns of different physical-chemical and ecological variables. Besides, the cyanobacteria is one of the dominating groups of phytoplankton blooms during the lake stratification periods (8 August–29 September 2016). During the cooling mixed period (29 September–19 October 2016), the high concentration of chlorophyll-a is mainly caused by the other phytoplankton species, such as diatoms. Perspectives are discussed in order to apply this observation system for real-time management of water bodies and lakes.
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Soumis le : vendredi 9 février 2018 - 18:11:17
Dernière modification le : jeudi 15 mars 2018 - 17:44:04

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Viet Tran Khac, Yi Hong, Denis Plec, Bruno Lemaire, Philippe Dubois, et al.. An Automatic Monitoring System for High-Frequency Measuring and Real-Time Management of Cyanobacterial Blooms in Urban Water Bodies. Processes, MDPI, 2018, 6 (2), pp.11. 〈10.3390/pr6020011〉. 〈hal-01705796〉

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