Carlos Eduardo Veras, John Tobiason, Amanda Carneiro Marques, Yuehlin Lee, Emily Kumpel
{"title":"饮用水库中季节性总大肠菌群动态","authors":"Carlos Eduardo Veras, John Tobiason, Amanda Carneiro Marques, Yuehlin Lee, Emily Kumpel","doi":"10.1016/j.watres.2025.123850","DOIUrl":null,"url":null,"abstract":"Maintaining high-quality drinking water supply reservoirs is important for protecting public health. Despite extensive watershed protection efforts, reservoirs can still experience seasonal, elevated total coliform bacteria concentrations, indicator bacteria commonly used for regulations. This study aimed to understand associations between concentrations of total coliform and an array of water quality, soil, and meteorological parameters over 10 years to identify potential causes and correlations of elevated total coliform bacteria concentrations in a protected watershed and clear, oligotrophic waters. Leveraging long-term data, we performed extensive data analysis and a data-driven model to investigate these relationships in the Quabbin Reservoir (Massachusetts, USA). Data analysis and data-driven modeling results indicated that proxies of algae, organic matter, and dry conditions, as well as water temperature and dissolved oxygen, were most associated with increased total coliforms in the reservoir. Although indicator bacteria such as total coliform are frequently used for routine monitoring, our findings highlight that it was unlikely that their proliferation is indicating a likely elevated risk in the reservoir. The studied reservoir has pristine water quality with low variability and low fecal bacteria indicator levels with no sign of external contamination; therefore, the high concentrations of total coliform bacteria in the summer is likely an autochthonous process. Additionally, applying machine learning methods to leverage long-term routine data collected by monitoring agencies highlights opportunities to better understand how to maintain high-quality surface water in drinking water supply reservoirs through a rapidly changing climate.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"10 1","pages":""},"PeriodicalIF":11.4000,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seasonal Total Coliform Dynamics in a Drinking Water Reservoir\",\"authors\":\"Carlos Eduardo Veras, John Tobiason, Amanda Carneiro Marques, Yuehlin Lee, Emily Kumpel\",\"doi\":\"10.1016/j.watres.2025.123850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Maintaining high-quality drinking water supply reservoirs is important for protecting public health. Despite extensive watershed protection efforts, reservoirs can still experience seasonal, elevated total coliform bacteria concentrations, indicator bacteria commonly used for regulations. This study aimed to understand associations between concentrations of total coliform and an array of water quality, soil, and meteorological parameters over 10 years to identify potential causes and correlations of elevated total coliform bacteria concentrations in a protected watershed and clear, oligotrophic waters. Leveraging long-term data, we performed extensive data analysis and a data-driven model to investigate these relationships in the Quabbin Reservoir (Massachusetts, USA). Data analysis and data-driven modeling results indicated that proxies of algae, organic matter, and dry conditions, as well as water temperature and dissolved oxygen, were most associated with increased total coliforms in the reservoir. Although indicator bacteria such as total coliform are frequently used for routine monitoring, our findings highlight that it was unlikely that their proliferation is indicating a likely elevated risk in the reservoir. The studied reservoir has pristine water quality with low variability and low fecal bacteria indicator levels with no sign of external contamination; therefore, the high concentrations of total coliform bacteria in the summer is likely an autochthonous process. Additionally, applying machine learning methods to leverage long-term routine data collected by monitoring agencies highlights opportunities to better understand how to maintain high-quality surface water in drinking water supply reservoirs through a rapidly changing climate.\",\"PeriodicalId\":443,\"journal\":{\"name\":\"Water Research\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":11.4000,\"publicationDate\":\"2025-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.watres.2025.123850\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.watres.2025.123850","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Seasonal Total Coliform Dynamics in a Drinking Water Reservoir
Maintaining high-quality drinking water supply reservoirs is important for protecting public health. Despite extensive watershed protection efforts, reservoirs can still experience seasonal, elevated total coliform bacteria concentrations, indicator bacteria commonly used for regulations. This study aimed to understand associations between concentrations of total coliform and an array of water quality, soil, and meteorological parameters over 10 years to identify potential causes and correlations of elevated total coliform bacteria concentrations in a protected watershed and clear, oligotrophic waters. Leveraging long-term data, we performed extensive data analysis and a data-driven model to investigate these relationships in the Quabbin Reservoir (Massachusetts, USA). Data analysis and data-driven modeling results indicated that proxies of algae, organic matter, and dry conditions, as well as water temperature and dissolved oxygen, were most associated with increased total coliforms in the reservoir. Although indicator bacteria such as total coliform are frequently used for routine monitoring, our findings highlight that it was unlikely that their proliferation is indicating a likely elevated risk in the reservoir. The studied reservoir has pristine water quality with low variability and low fecal bacteria indicator levels with no sign of external contamination; therefore, the high concentrations of total coliform bacteria in the summer is likely an autochthonous process. Additionally, applying machine learning methods to leverage long-term routine data collected by monitoring agencies highlights opportunities to better understand how to maintain high-quality surface water in drinking water supply reservoirs through a rapidly changing climate.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.