algal1 {bnRep} | R Documentation |
algal Bayesian Networks
Description
Seasonal forecasting of lake water quality and algal bloom risk using a continuous Gaussian Bayesian networks.
Format
A discrete Bayesian network to to forecast, in spring, mean total phosphorus and chlorophyll a concentration, mean water colour, and maximum cyanobacteria biovolume for the upcoming growing season (May–October) in Vansjø. Probabilities were given within the referenced paper. The vertices are:
- ChiA
Mean lake chl a concentration - Current (Low, High);
- ChiA_PS
Mean lake chl a concentration - Previous (Low, High);
- Colour
Mean lake colour (Low, Medium, High);
- Cyanobacteria
Mean lake cyanobacterial biovolume (Low, High);
- RainSum
Precipitation sum (Low, High);
- TP
Mean lake TP concentration - Current (Low, High);
- TP_PS
Mean lake TP concentration - Previous (Low, High);
- WindSpeed
Mean daily mean wind speed (Low, High);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Jackson-Blake, L. A., Clayer, F., Haande, S., Sample, J. E., & Moe, S. J. (2022). Seasonal forecasting of lake water quality and algal bloom risk using a continuous Gaussian Bayesian network. Hydrology and Earth System Sciences, 26(12), 3103-3124.