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Dataset: Greifensee Chlorophyll-a forecasting based on deep learning 2019-2021

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)

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Curator Merkli, Stefanie
Contact Pomati, Francesco <Francesco.Pomati@eawag.ch>