A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems

Philomina Onyedikachi Peter , Edoardo Bertone , Rodney A. Stewart
{"title":"A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems","authors":"Philomina Onyedikachi Peter ,&nbsp;Edoardo Bertone ,&nbsp;Rodney A. Stewart","doi":"10.1016/j.clwat.2025.100063","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100257,"journal":{"name":"Cleaner Water","volume":"3 ","pages":"Article 100063"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cleaner Water","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950263225000018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

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.
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信