The hydrodynamics and ecological status of water bodies have been affected during the last decades by anthropogenic stressors. While climate change threatens lakes globally, urbanization can enhance symptoms of eutrophication locally by increasing nutrient loads. These anthropogenic pressures need to be carefully assessed through relevant monitoring, and generalized via modelling approaches. The scarcity of available data limits the knowledge and the transfer of research outcomes to decision makers. During the last decade, the availability of a wide range of sensors allowed to collect high-frequency measurements of variables relevant to the functioning of the water bodies. Nevertheless, a limited number of monitoring systems has been developed for measuring the cyanobacteria specific photosynthetic pigment, phycocyanin, as well as for designing warning systems for preventing public health risks from cyanobacteria blooms. This paper will present outcomes obtained in the framework of the OSS-CYANO project (funded by ANR), regarding: (i) a full-scale experimental site for high-frequency monitoring of cyanobacteria biomass in an urban lake; (ii) a data transfer platform for real-time management of harmful blooms; (iii) the automatic design for data analysis and three dimensional model initialization, and (iv) how the short term predictions of the cyanobacteria biomass can be used for supporting decision-making.