https://doi.org/10.25678/00066D
Dataset: Greifensee Chlorophyll-a forecasting based on deep learning 2019-2021
Dataset extent
Data and Resources
Citation
Merkli, S., Reyes, M., Ebi, C., Merz, E., Bulas, T., Dennis, S. R., & Pomati, F. (2022). Dataset: Greifensee Chlorophyll-a forecasting based on deep learning 2019-2021 (Version 1.0) [Data set]. Eawag: Swiss Federal Institute of Aquatic Science and Technology. https://doi.org/10.25678/00066D
Metadata
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Keywords | CTD,Meteo,Aquascope,AUA,ammonium,nitrate,nitrite,chlorophyll,dissolved oxygen,conductivity,PAR,pH,phycocyanin,precipitation,atmospheric pressure,relative humidity,solar radiation,air temperature,water temperature,TOC,TN,wind speed,turbidity,mixed layer depth,wind direction,mixed layer irradiance,schmidt stability,phycoerythrin,thermocline depth,oxycline depth,epilimnetic temperature,sunshine duration,cloud cover,oP,TP |
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Review Level | none |
Curator | Merkli, Stefanie |
Contact | Pomati, Francesco <Francesco.Pomati@eawag.ch> |
DOI | 10.25678/00066D |