A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems
Ensuring the quality of recreational waters is critical for safeguarding public health and supporting tourism-driven economies. However, rising levels of Enterococci (ENT) present significant risks to aquatic ecosystems and human well-being. Predicting ENT concentrations and understanding their envi...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Cleaner Water |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950263225000018 |
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| author | Philomina Onyedikachi Peter Edoardo Bertone Rodney A. Stewart |
| author_facet | Philomina Onyedikachi Peter Edoardo Bertone Rodney A. Stewart |
| author_sort | Philomina Onyedikachi Peter |
| collection | DOAJ |
| description | Ensuring the quality of recreational waters is critical for safeguarding public health and supporting tourism-driven economies. However, rising levels of Enterococci (ENT) present significant risks to aquatic ecosystems and human well-being. Predicting ENT concentrations and understanding their environmental and anthropogenic drivers are essential for effective water resource management and the mitigation of health risks. This systematic review explores the existing body of research on water quality modeling by analyzing various model types, their applications, and their effectiveness. It identifies rainfall and storms as primary drivers of elevated ENT concentrations, emphasizing the critical role of environmental factors in shaping water quality. Additionally, human and animal waste, particularly from sewage intrusion, are highlighted as significant sources of ENT, underscoring the need to address anthropogenic impacts on water contamination. Process-based and data-driven models emerge as prominent tools for forecasting ENT levels in recreational waters. While both approaches are widely utilized, the review notes the difficulty in directly comparing their performance due to methodological variations. By synthesizing findings from diverse studies, the review provides insights into the complex relationships between predictors such as rainfall, ENT levels, and associated health risks from human exposure. The review also addresses the health implications of ENT contamination by identifying its primary sources and associated diseases, enhancing understanding of its broader impacts on public health. Furthermore, it offers evidence-based recommendations for selecting appropriate models to predict ENT levels, empowering researchers and water resource managers to design more effective water quality management strategies. These insights may contribute to reducing the prevalence of waterborne diseases associated with recreational water use, ultimately promoting safer and more sustainable aquatic environments. |
| format | Article |
| id | doaj-art-d8f2b61c50944cd5b9236d80c7713802 |
| institution | Kabale University |
| issn | 2950-2632 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cleaner Water |
| spelling | doaj-art-d8f2b61c50944cd5b9236d80c77138022025-01-19T06:27:06ZengElsevierCleaner Water2950-26322025-06-013100063A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystemsPhilomina Onyedikachi Peter0Edoardo Bertone1Rodney A. Stewart2Griffith School of Engineering and Built Environment, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia; Australian Rivers Institute, Griffith University, 170 Kessels Road, Nathan, Queensland 4111, AustraliaGriffith School of Engineering and Built Environment, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia; Australian Rivers Institute, Griffith University, 170 Kessels Road, Nathan, Queensland 4111, Australia; Cities Research Institute, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia; Corresponding author at: Griffith School of Engineering and Built Environment, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia.Griffith School of Engineering and Built Environment, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia; Cities Research Institute, Griffith University, Parklands Drive, Southport, Queensland 4222, AustraliaEnsuring the quality of recreational waters is critical for safeguarding public health and supporting tourism-driven economies. However, rising levels of Enterococci (ENT) present significant risks to aquatic ecosystems and human well-being. Predicting ENT concentrations and understanding their environmental and anthropogenic drivers are essential for effective water resource management and the mitigation of health risks. This systematic review explores the existing body of research on water quality modeling by analyzing various model types, their applications, and their effectiveness. It identifies rainfall and storms as primary drivers of elevated ENT concentrations, emphasizing the critical role of environmental factors in shaping water quality. Additionally, human and animal waste, particularly from sewage intrusion, are highlighted as significant sources of ENT, underscoring the need to address anthropogenic impacts on water contamination. Process-based and data-driven models emerge as prominent tools for forecasting ENT levels in recreational waters. While both approaches are widely utilized, the review notes the difficulty in directly comparing their performance due to methodological variations. By synthesizing findings from diverse studies, the review provides insights into the complex relationships between predictors such as rainfall, ENT levels, and associated health risks from human exposure. The review also addresses the health implications of ENT contamination by identifying its primary sources and associated diseases, enhancing understanding of its broader impacts on public health. Furthermore, it offers evidence-based recommendations for selecting appropriate models to predict ENT levels, empowering researchers and water resource managers to design more effective water quality management strategies. These insights may contribute to reducing the prevalence of waterborne diseases associated with recreational water use, ultimately promoting safer and more sustainable aquatic environments.http://www.sciencedirect.com/science/article/pii/S2950263225000018EnterococciModelingSedimentDiseasesSourcesRecreational water |
| spellingShingle | Philomina Onyedikachi Peter Edoardo Bertone Rodney A. Stewart A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems Cleaner Water Enterococci Modeling Sediment Diseases Sources Recreational water |
| title | A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems |
| title_full | A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems |
| title_fullStr | A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems |
| title_full_unstemmed | A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems |
| title_short | A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems |
| title_sort | systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems |
| topic | Enterococci Modeling Sediment Diseases Sources Recreational water |
| url | http://www.sciencedirect.com/science/article/pii/S2950263225000018 |
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