C2. Develop and benchmark data-driven algorithms to forecast the short-term dynamics of phytoplankton in surface waters reservoirs (71)

C1. Assess the relevance of hydrometeorological variables in phytoplankton dynamics of surface waters using data-driven modeling (69)

A1. Imaging spectrometry (21)

C3. Quantile-based modeling of phytoplankton dynamics using Random Forests (19)

B1. Assimilation of Earth Observation products and in-situ data in seasonal hydrological forecasting services (18)

B4. Developing an error-correcting complementary modeling approach for surface water quality (12)

A2. Multiscale Optical Data (6)

B2. Assimilation of Earth Observation products in water quality modelling (3)