Early warning of harmful cyanobacteria blooms based on high frequency in situ monitoring and intelligible machine learning modelling: The case study of Lake Müggelsee (Germany)

Journal:

Water Research

Published:

2025-09-01

DOI:

10.1016/j.watres.2025.124514

Affiliations:

3

Authors:

4

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Institutions	Authors	Share
Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Germany	2.000000	0.50
The University of Adelaide (Adelaide Uni), Australia	1.000000	0.25
Chongqing Institute of Green and Intelligent Technology (CIGIT), CAS, China	1.000000	0.25

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