1. Title, Journal and Authors

Title: Probabilistic prediction of cyanobacteria abundance in a Korean reservoir using a Bayesian Poisson model.

Journal: Water Resources Research (2014)

Authors: Cha, Y., Park, S., Kim, K., Byeon, M. and Stow, C

 

2. Summary

 

Cha et al, researched the model of cyanobacteria abundance to improve the accuracy in the paper, “Probabilistic prediction of cyanobacteria abundance in a Korean reservoir using a Bayesian Poisson Model”. Because of the low occurrence of cyanobacteria bloom, there are small data sets in that subject. Cha suggests the Poisson Hurdle Model, which can include the zero information. Using monitored data from 2004 to 2014, the Poisson model is made and both the occurrence and non-occurrence of cyanobacterial bloom are predicted. Also relationships between cyanobacteria occurrence and water quality variables such as temperature, turbidity, SS, and residence time, are also captured by the model.

 

3. Application to research

 

 The Poisson Hurdle Model is the technique, which has not been used in the environmental field. Cha uses the Poisson model for modeling the river systems for the first, and successfully capture the characteristics of cyanobacterial bloom. This research shows us the possibilities of using Bayesian model such as Poisson Model, Hierarchical model in our field, river modeling.

 

4. Contact

Sung Ho Shin (Ph.D. program)

Environmental Systems Engineering Lab.

School of Earth Sciences and Environmental Engineering

Gwangju Institute of Science and Technology

1 Oryong-dong Buk-gu Gwangju, 500-712, Korea

 Phone : +82-10-6634-8614

E-mail : hogili89@gist.ac.kr