The magnitude and drivers of harmful algal blooms in China’s lakes and reservoirs: A national-scale characterization

Huang, Jiacong; Zhang, Yinjun; Arhonditsis, George B.; Gao, Junfeng; Chen, Qiuwen; Peng, Jian

doi:10.1016/j.watres.2020.115902

Cited by 162 publications

(48 citation statements)

References 87 publications

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“…It is well accepted that phytoplankton will not flourish and form substantial blooms without a proper supply of nutrients. It is not surprising, therefore, that the leading premise/theme/dogma in the field is that eutrophication is a major driving force of the intensification of toxic cyanobacteria blooms, in addition to global warming [ 8 , 17 , 18 , 19 , 20 ]. Contrary to this widely accepted view, the analysis by Ho and co-workers [ 12 ] of near-surface phytoplankton blooms from 71 large lakes around the world, covering three decades using Landsat 5 data, showed that exacerbation of bloom conditions in the majority of the lakes did not consistently track with previously hypothesized drivers.…”

Section: Prevention Of Bloom Developmentmentioning

confidence: 99%

Cyanobacterial Harmful Algal Blooms in Aquatic Ecosystems: A Comprehensive Outlook on Current and Emerging Mitigation and Control Approaches

Sukenik

2021

Microorganisms

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An intensification of toxic cyanobacteria blooms has occurred over the last three decades, severely affecting coastal and lake water quality in many parts of the world. Extensive research is being conducted in an attempt to gain a better understanding of the driving forces that alter the ecological balance in water bodies and of the biological role of the secondary metabolites, toxins included, produced by the cyanobacteria. In the long-term, such knowledge may help to develop the needed procedures to restore the phytoplankton community to the pre-toxic blooms era. In the short-term, the mission of the scientific community is to develop novel approaches to mitigate the blooms and thereby restore the ability of affected communities to enjoy coastal and lake waters. Here, we critically review some of the recently proposed, currently leading, and potentially emerging mitigation approaches in-lake novel methodologies and applications relevant to drinking-water treatment.

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Section: Prevention Of Bloom Developmentmentioning

confidence: 99%

Cyanobacterial Harmful Algal Blooms in Aquatic Ecosystems: A Comprehensive Outlook on Current and Emerging Mitigation and Control Approaches

Sukenik

2021

Microorganisms

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“…In recent years, with the frequent occurrence of water pollution in lakes and reservoirs, eutrophication, and high incidence of algae, the safety of surface water quality has increasingly attracted great attention. Harmful algal abnormal proliferation presents the most severe threat to the quality of oligotrophic surface water around the world, [1][2][3][4][5] even in water sources such as China's South-to-North Water Diversion Project. 6 The middle route of the South-to-North Water Diversion Project (MRP) diverts 13 billion m 3 of water every year from the Dan-Jiang-Kou reservoir to many large cities and counties in the North of China since its start of operation in 2014 and realizes the regulation of unevenly distributed water resources and alleviation of water shortage in northern China.…”

Section: Introductionmentioning

confidence: 99%

Algae control in oligotrophic surface water under the joint effect of nutritional competition and microbial algae-lytic substances

Gao

Xie

Liu

2022

Environ. Sci.: Water Res. Technol.

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“…Common association analysis methods include similarity analysis [ 4 , 5 ], cluster analysis [ 6 , 7 ], regression model [ 8 – 10 ], time series model [ 11 – 13 ], and artificial neural network (ANN) [ 14 – 16 ]. Similarity analysis and clustering analysis methods can effectively classify a variety of data, and these methods have been widely used in many fields [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

The water supply association analysis method in Shenzhen based on kmeans clustering discretization and apriori algorithm

et al. 2021

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Since water supply association analysis plays an important role in attribution analysis of water supply fluctuation, how to carry out effective association analysis has become a critical problem. However, the current techniques and methods used for association analysis are not very effective because they are based on continuous data. In general, there is different degrees of monotone relationship between continuous data, which makes the analysis results easily affected by monotone relationship. The multicollinearity between continuous data distorts these analytical methods and may generate incorrect results. Meanwhile, we cannot know the association rules and value interval between features and water supply. Therefore, the lack of an effective analysis method hinders the water supply association analysis. Association rules and value interval of features obtained from association analysis are helpful to grasp cause of water supply fluctuation and know the fluctuation interval of water supply, so as to provide better support for water supply dispatching. But the association rules and value interval between features and water supply are not fully understood. In this study, a data mining method coupling kmeans clustering discretization and apriori algorithm was proposed. The kmeans was used for data discretization to obtain the one-hot encoding that can be recognized by apriori, and the discretization can also avoid the influence of monotone relationship and multicollinearity on analysis results. All the rules eventually need to be validated in order to filter out spurious rules. The results show that the method in this study is an effective association analysis method. The method can not only obtain the valid strong association rules between features and water supply, but also understand whether the association relationship between features and water supply is direct or indirect. Meanwhile, the method can also obtain value interval of features, the association degree between features and confidence probability of rules.

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The magnitude and drivers of harmful algal blooms in China’s lakes and reservoirs: A national-scale characterization

Cited by 162 publications

References 87 publications

Cyanobacterial Harmful Algal Blooms in Aquatic Ecosystems: A Comprehensive Outlook on Current and Emerging Mitigation and Control Approaches

Cyanobacterial Harmful Algal Blooms in Aquatic Ecosystems: A Comprehensive Outlook on Current and Emerging Mitigation and Control Approaches

Algae control in oligotrophic surface water under the joint effect of nutritional competition and microbial algae-lytic substances

The water supply association analysis method in Shenzhen based on kmeans clustering discretization and apriori algorithm

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