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International audience; The variability of the phytoplankton biomass derived from daily chlorophyll-a (Chl-a) satellite images was investigated over the period 1998-2017 in the surface waters of the English Channel and the northern Bay of Biscay. Merged satellite (SeaWiFS-MODIS/Aqua-MERIS-VIIRS) Chl-a was calculated using the OC5 Ifremer algorithm which is optimized for moderately-turbid waters. The seasonal cycle in satellite-derived Chl-a was compared with in situ measurements made at seven coastal stations located in the southern side of the English Channel and in the northern Bay of Biscay. The results firstly showed that the satellite Chl-a product, derived from a suite of space-borne marine reflectance data, is in agreement with the coastal observations. For compliance with the directives of the European Union on water quality, time-series of 6-year moving average of Chl-a were assessed over the region. A clear decline was observed in the mean and 90th percentile of Chl-a at stations located in the mixed waters of the English Channel. The time-series at the stations located in the Bay of Biscay showed yearly fluctuations which correlated well with river discharge, but no overall Chl-a trend was observed. In the English Channel, the shape of the seasonal cycle in Chl-a changed over time. Narrower peaks were observed in spring at the end of the studied period, indicating an earlier limitation by nutrients. Monthly averages of satellite Chl-a, over the periods 1998-2003 and 2012-2017, exhibited spatial and temporal patterns in the evolution of the phytoplankton biomass similar to these observed at the seven coastal stations. Both the in situ and satellite Chl-a times-series showed a decrease in Chl-a in the English Channel in May, June and July. This trend in phytoplankton biomass is correlated with lower river discharges at the end of the period and a constant reduction in the riverine input of phosphorus through improvements in the water quality of the surrounding river catchments.

The report describes the models that were used within the H2020 project EOMORES to forecast cyanobacteria. Two models, developed by Deltares, were used: EWACS and AlgaeRadar. EWACS was applied to lake Paterswoldsemeer in the Netherlands and is a 3D model used to forecast algal scums. The AlgaeRadar is a statistical model that predicts cyanobacteria concentrations and was applied in lakes Paterswoldsemeer, Twiske (both in the Netherlands) and Trasimeno (Italy). For both models the current status is described and what is needed for further improvements. In addition, the Deltares BLOOM model was applied to lake Twiske to model the factors that limit growth in the lake.

Cyanobacterial blooms can be toxic to humans swimming in affected waters. According to the European Bathing Water Directive bathing waters should be closed during cyanobacterial blooms. In the Netherlands, cyanobacteria monitoring in all official bathing water locations is usually performed every two weeks during the bathing season. In face of the large temporal and spatial variability of cyanobacterial bloom dynamics this monitoring frequency however is too low for adequate early warnings to the public. High frequency monitoring and forecasting models can provide information on cyanobacterial blooms in between the regular monitoring dates and for a few days into the future. In the H2020 project EOMORES, we have combined observational data from a spectral camera (Ecowatch) near a Dutch bathing site with fluorescence data from an underwater drone to analyse the variability of cyanobacterial blooms at short temporal and spatial scales. The results are used in a short term forecasting model of cyanobacterial blooms (AlgaeRadar) and a 3D scum forecasting model (EWACS). The AlgaeRadar is cross-validated with biweekly data from other bathing water sites and shows improved model performance compared to an earlier version that was built with only biweekly data. For the site with high-frequency chlorophyll observations the near-real time data are assimilated in the model to further enhance the model performance. Model performance of EWACS is verified using high frequency pictures from the Ecowatch station, showing scum layers on the water. This allowed us to validate and calibrate the EWACS model. Model validation abilities were in the past also limited by to the patchy nature and high temporal variability of the scum layers, which was not covered by sparse scum observations. With the resulting models, early warnings for cyanobacterial blooms are more reliable than those from the current practice that are merely based on biweekly monitoring data. For the protection of public health this provides better opportunities as well.

The report describes the models that were used within the H2020 projectEOMORES to forecast cyanobacteria. Two models, developed by Deltares,were used: EWACS and AlgaeRadar. EWACS was applied to lake Paterswoldsemeer in the Netherlands and is a 3D model used to forecast algal scums. The AlgaeRadar is a statistical model that predicts cyanobacteria concentrations and was applied in lakes Paterswoldsemeer, Twiske (both in the Netherlands) and Trasimeno (Italy). For both models the current status is described and what is needed for further improvements. In addition, the Deltares BLOOM model was applied to lake Twiske to model the factors that limit growth in the lake. &nbsp

The report describes the models that were used within the H2020 project EOMORES to forecast cyanobacteria. Two models, developed by Deltares, were used: EWACS and AlgaeRadar. EWACS was applied to lake Paterswoldsemeer in the Netherlands and is a 3D model used to forecast algal scums. The AlgaeRadar is a statistical model that predicts cyanobacteria concentrations and was applied in lakes Paterswoldsemeer, Twiske (both in the Netherlands) and Trasimeno (Italy). For both models the current status is described and what is needed for further improvements. In addition, the Deltares BLOOM model was applied to lake Twiske to model the factors that limit growth in the lake.

The report describes the models that were used within the H2020 projectEOMORES to forecast cyanobacteria. Two models, developed by Deltares,were used: EWACS and AlgaeRadar. EWACS was applied to lake Paterswoldsemeer in the Netherlands and is a 3D model used to forecast algal scums. The AlgaeRadar is a statistical model that predicts cyanobacteria concentrations and was applied in lakes Paterswoldsemeer, Twiske (both in the Netherlands) and Trasimeno (Italy). For both models the current status is described and what is needed for further improvements. In addition, the Deltares BLOOM model was applied to lake Twiske to model the factors that limit growth in the lake. &nbsp