In urban watersheds, anthropogenic activities have major impacts on the ecological quality of water bodies. The degradation of water quality can result in toxic cyanobacteria blooms, which in turn may cause serious health risks to people in contact with water, e.g. when doing water sports. Due to the complexity of natural processes in water bodies, physically-based and spatially distributed models are valuable tools for better understanding the interactions between variables driving cyanobacteria blooms, as well as for helping stakeholders determine management strategies. However, traditional in situ measurements are limited by temporal and spatial resolution to make such numerical models reliable. Continuous in situ measurements provided by automated high-frequency monitoring can significantly improve adaptive decision-making. The main objectives of this work 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 physicallybased three-dimensional hydro-ecological model for predicting cyanobacteria blooms; (iii) implement a transfer platform for real-time data management; and (iv) develop a web platform for communicating information to lake managers, other stakeholders and the public. These steps were conducted in the framework of the OSS-cyano project, funded by the French Research Agency (ANR). The study site is Lake Champs-surMarne (0.12 km2 surface, 3.5 m maximum depth), located in Greater Paris. The field monitoring includes measurements of water temperature, dissolved oxygen, chlorophyll-a fluorescence and phycocyanin fluorescence at 10 min time steps, and regular vertical profiles of temperature and fluorescence of the main phytoplankton groups. The Delft3D hydrodynamic and ecological modules, Flow and Bloom respectively, were implemented. Using continuous measurements and short-term meteorological forecast, a predictive modelling of the cyanobacteria biomass evolution over four days was performed. Simulation results can then be communicated to the lake manager and the public through a web platform for health risk warning.