Predicting Imminent Cyanobacterial Blooms in Lakes Using Incomplete Timely Data

Predicting Imminent Cyanobacterial Blooms in Lakes Using Incomplete Timely Data

Abstract Toxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long‐range forecasts is overly challenging, predicting imminent CBs is possible from precise monitoring data of the underlying covariates. It is, however, infeasibly...

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Bibliographic Details
Main Authors: Christopher M. Heggerud, Jingjing Xu, Hao Wang, Mark A. Lewis, Ron W. Zurawell, Charlie J. G. Loewen, Rolf D. Vinebrooke, Pouria Ramazi
Format: Article
Language:English
Published: Wiley 2024-02-01
Series:Water Resources Research
Subjects:
cyanobacterial bloom
Bayesian network
predictive ecology
machine learning
environmental covariates
Online Access:https://doi.org/10.1029/2023WR035540
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https://doi.org/10.1029/2023WR035540

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