Literature DB >> 28734958

The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers.

YoonKyung Cha1, Kyung Hwa Cho2, Hyuk Lee3, Taegu Kang4, Joon Ha Kim5.   

Abstract

Despite a growing awareness of the problems associated with cyanobacterial blooms in rivers, and particularly in regulated rivers, the drivers of bloom formation and abundance in rivers are not well understood. We developed a Bayesian hierarchical model to assess the relative importance of predictors of summer cyanobacteria abundance, and to test whether the relative importance of each predictor varies by site, using monitoring data from 16 sites in the four major rivers of South Korea. The results suggested that temperature and residence time, but not nutrient levels, are important predictors of summer cyanobacteria abundance in rivers. Although the two predictors were of similar significance across the sites, the residence time was marginally better in accounting for the variation in cyanobacteria abundance. The model with spatial hierarchy demonstrated that temperature played a consistently significant role at all sites, and showed no effect from site-specific factors. In contrast, the importance of residence time varied significantly from site to site. This variation was shown to depend on the trophic state, indicated by the chlorophyll-a and total phosphorus levels. Our results also suggested that the magnitude of weir inflow is a key factor determining the cyanobacteria abundance under baseline conditions.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian hierarchical model; Cyanobacteria; Overdispersed Poisson regression; Residence time; Rivers and streams; Temperature

Mesh:

Substances:

Year:  2017        PMID: 28734958     DOI: 10.1016/j.watres.2017.07.040

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  5 in total

1.  Development of a Risk Characterization Tool for Harmful Cyanobacteria Blooms on the Ohio River.

Authors:  Christopher T Nietch; Leslie Gains-Germain; James Lazorchak; Scott P Keely; Gregory Youngstrom; Emilee M Urichich; Brian Astifan; Abram DaSilva; Heather Mayfield
Journal:  Water (Basel)       Date:  2022-02-18       Impact factor: 3.530

2.  Probing the Cyanobacterial Microcystis Gas Vesicles after Static Pressure Treatment: A Potential In Situ Rapid Method.

Authors:  Jiajin Li; Ran Liao; Yi Tao; Zepeng Zhuo; Zhidi Liu; Hanbo Deng; Hui Ma
Journal:  Sensors (Basel)       Date:  2020-07-27       Impact factor: 3.576

3.  Spatio-Temporal Modeling for Forecasting High-Risk Freshwater Cyanobacterial Harmful Algal Blooms in Florida.

Authors:  Mark H Myer; Erin Urquhart; Blake A Schaeffer; John M Johnston
Journal:  Front Environ Sci       Date:  2020-11-02

4.  Climate change induced habitat expansion of nutria (Myocastor coypus) in South Korea.

Authors:  Pradeep Adhikari; Baek-Jun Kim; Sun-Hee Hong; Do-Hun Lee
Journal:  Sci Rep       Date:  2022-02-28       Impact factor: 4.379

5.  Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea.

Authors:  Hye-Suk Yi; Sangyoung Park; Kwang-Guk An; Keun-Chang Kwak
Journal:  Int J Environ Res Public Health       Date:  2018-09-21       Impact factor: 3.390

  5 in total

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