Articles | Volume 26, issue 12
https://doi.org/10.5194/hess-26-3103-2022
https://doi.org/10.5194/hess-26-3103-2022
Research article
 | 
20 Jun 2022
Research article |  | 20 Jun 2022

Seasonal forecasting of lake water quality and algal bloom risk using a continuous Gaussian Bayesian network

Leah A. Jackson-Blake, François Clayer, Sigrid Haande, James E. Sample, and S. Jannicke Moe

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Latest update: 17 Jul 2024
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Short summary
We develop a Gaussian Bayesian network (GBN) for seasonal forecasting of lake water quality and algal bloom risk in a nutrient-impacted lake in southern Norway. Bayesian networks are powerful tools for environmental modelling but are almost exclusively discrete. We demonstrate that a continuous GBN is a promising alternative approach. Predictive performance of the GBN was similar or improved compared to a discrete network, and it was substantially less time-consuming and subjective to develop.