Probabilistic prediction of cyanobacteria abundance in a Korean reservoir using a Bayesian Poisson model-Reference-Cited by-同舟云学术

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

Published:2014-03 Issue:3 Volume:50 Page:2518-2532
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Cha YoonKyung¹,Park Seok Soon²,Kim Kyunghyun³,Byeon Myeongseop³,Stow Craig A.⁴

Affiliation:

1. Cooperative Institute for Limnology and Ecosystems Research; University of Michigan; Ann Arbor Michigan USA

2. Department of Environmental Science and Engineering; College of Engineering; Ewha Womans University; Seoul South Korea

3. National Institute of Environmental Research; Incheon South Korea

4. NOAA Great Lakes Environmental Research Laboratory; Ann Arbor Michigan USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Reference75 articles.

1. Rainfall, phycocyanin, and N:P ratios related to cyanobacterial blooms in a Korean large reservoir;Ahn;Hydrobiologia,2002

2. Evaluation of environmental factors on cyanobacteria bloom in eutrophic reservoir using artificial neural networks;Ahn;J. Phycol.,2011

3. Factors regulating bluegreen dominance in a reservoir directly influenced by the Asian monsoon;An;Hydrobiologia,2000a

4. Temporal and spatial patterns in salinity and suspended solids in a reservoir influenced by the Asian monsoon;An;Hydrobiologia,2000b

5. Nutrients and water temperature are significant predictors of cyanobacterial biomass in a 1147 lakes data set;Beaulieu;Limnol. Oceanogr.,2013

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