CTD, Meteo, nutrient chemistry and Aquascope camera data, used to predict Chl-a as part of Gabriel Vallat civil service project. There is a data set with daily averages and one with hourly measurements. In each dataset a single average value was calculated across the photic zone (0-8m) for each profile, and zooplankton and phytoplankton cluster abundances were estimated using machine learning classifier output of Aquascope camera data (more information about aquascope see https://doi.org/10.1016/j.watres.2021.117524 https://doi.org/10.25678/0004BW)