1. The "Seili-index" for the Prediction of Chlorophyll-α Levels in the Archipelago Sea of the northern Baltic Sea, southwest Finland.
- Author
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Hänninen, Jari, Mäkinen, Katja, Nordhausen, Klaus, Laaksonlaita, Jussi, Loisa, Olli, and Virta, Joni
- Subjects
NATURAL resources management ,SEA level ,POLLUTION management ,CYANOBACTERIAL blooms ,ENVIRONMENTAL monitoring ,ALGAL blooms - Abstract
To build a forecasting tool for the state of eutrophication in the Archipelago Sea, we fitted a Generalized Additive Mixed Model (GAMM) to marine environmental monitoring data, which were collected over the years 2011–2019 by an automated profiling buoy at the Seili ODAS-station. The resulting "Seili-index" can be used to predict the chlorophyll-α (chl-a) concentration in the seawater a number of days ahead by using the temperature forecast as a covariate. An array of test predictions with two separate models on the 2019 data set showed that the index is adept at predicting the amount of chl-a especially in the upper water layer. The visualization with 10 days of chl-a level predictions is presented online at https://saaristomeri.utu.fi/seili-index/. We also applied GAMMs to predict abrupt blooms of cyanobacteria on the basis of temperature and wind conditions and found the model to be feasible for short-term predictions. The use of automated monitoring data and the presented GAMM model in assessing the effects of natural resource management and pollution risks is discussed. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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