Modeling Fecal Indicator Bacteria Concentrations in Natural Surface Waters: A Review

Brauwere, Anouk de; Ouattara, Nouho Koffi; Servais, Pierre

doi:10.1080/10643389.2013.829978

Cited by 117 publications

(90 citation statements)

References 201 publications

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“…Without the decay process FIB concentrations were found to be one or two orders of magnitude higher. This is in agreement with the studies by Brauwere et al (2014) and Ouattara et al (2013).…”

Section: Impact Of Different Processes On Fib Concentrationssupporting

confidence: 83%

“…This is also consistent with the values used by Liu et al (2006). The salinity coefficient (θS) was set to 1.006 for both the bacteria based on the values reported in the literature (Canteras et al, 1995, McCorquodale et al, 2004, Brauwere et al, 2014. A constant light intensity of 0.14 kW/m 2 was assigned in the model, which was based on the study area's daily average light intensity and daily sunshine hours data, collected from NASA's satellite derived data centre and the Bangladesh Meteorological Department respectively.…”

Section: Microbial Water Quality Modelmentioning

confidence: 53%

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Assessing the impact of socio-economic development and climate change on faecal indicator bacteria in the Betna River, Bangladesh

Islam¹

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Section: Impact Of Different Processes On Fib Concentrationssupporting

confidence: 83%

Section: Microbial Water Quality Modelmentioning

confidence: 53%

Assessing the impact of socio-economic development and climate change on faecal indicator bacteria in the Betna River, Bangladesh

Islam¹

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“…They can also help specify where future monitoring efforts are most needed and the results based on a particular site can be used to guide field investigations in other areas with similar hydrogeology and land use (Mair and El-Kadi 2013). Regressionbased models are particularly useful in operational contexts (de Brauwere et al 2014). Their use is common in the literature in studies on risk factors for microbial groundwater contamination, which have focused on: coliform bacteria in rural wells in Iowa, USA (Glanville et al 1997), the link between Cryptosporidium and onsite wastewater systems and private (Tollestrup et al 2014), Escherichia coli (E. coli) in 211 wells in the Republic of Ireland (Hynds et al 2014), E. coli in groundwater sources in northern, rural Malawi (Kanyerere et al 2012), coliform bacteria in shallow wells in Ibadan, Nigeria (Oguntoke et al 2013), TTCs and faecal streptococci in shallow groundwater in Kampala, Uganda (Howard et al 2003), enterococci and TTCs in shallow groundwater sources in Lichinga, Mozambique (Godfrey et al 2006), and faecal coliform and faecal streptococci in rural areas in Burkina Faso (Guillemin et al 1991).…”

Section: Introductionmentioning

confidence: 99%

Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan

2016

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This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation Médecins Sans Frontières in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model (p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

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“…The pathogenic E. coli, however, is not the only danger present in domestic sewage. In fact, in the present study, we regarded it principally as an indicator of overall pollution risk (de Brauwere et al 2014b). The management of that risk starts long before the outfall step, because the construction of a waste management technique requires hydrodynamic modeling that can assess the environmental impacts on the surrounding ecosystems (Fernández, 2011, Yang et al, 2000.…”

Section: Introductionmentioning

confidence: 99%

Critical evaluation of the factors affecting Escherichia coli environmental decay for outfall plume models

Carneiro¹,

Côrtes²,

Wasserman³

2018

Rev. ambiente água

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The Escherichia coli T90 parameter is widely employed in outfall plume hydrodynamic models. Although there is a great deal of academic literature estimating T90, no standard methodology has been validated so far. Estimation of die-off rates should consider many other biological, chemical and physical processes. Over the last three decades, while a great deal of new knowledge about microbial biology and ecology has become available, it has not been fully incorporated into the overall research. Consequently, hydrodynamic models of sewage plumes lack consistency with environmental dynamics and frequently do not fully reproduce processes. This article scrutinized the relevant works that could improve T90 assessment using the most robust and realistic approaches. The most important related literature since the 1990s was considered, together with earlier relevant works. The research focused on techniques and methodologies, especially their ecologic and cellular biology aspects. A brief discussion of the methods applied to evaluate the T90 of bacteria examined aspects like representativeness of incubation, incubation scale, measurement procedures and models' representations of bacterial decay. The factors affecting population decay, such as solar radiation, salinity and interaction with solids, were considered in the light of the very large literature registry. Finally, biological aspects affecting decay, like predation and genetic resistance, were also analyzed. The resulting updated understanding of T90 may contribute to better managerial procedures that could improve water quality in freshwater and coastal systems, and consequently improve human health outcomes.Keywords: bacteria, environmental decay, water quality. modelos hidrodinâmicos, não existe uma padronização metodológica para sua avaliação que seja validada até hoje. Além das taxas de decaimento, muitos outros processos biológicos, químicos e físicos deveriam ser considerados nas modelagens hidrodinâmicas. Nas últimas três décadas, embora um extenso conhecimento sobre biologia e ecologia microbiana tenha sido desenvolvido, pouco deste conhecimento foi incorporado às aplicações. Consequentemente, os modelos de plumas de esgotos não lograram reproduzir de maneira fiel os processos ambientais. No presente artigo, os trabalhos relevantes que poderiam melhorar a determinação do T90, sob abordagens mais robustas e realistas foram revisados. A literatura mais relevante desde os anos 1990 foi considerada, juntamente com alguns trabalhos relevantes mais antigos. A pesquisa focou em técnicas e metodologias de avaliação de aspectos ecológicos e de biologia celular. Uma breve discussão dos métodos aplicados à avaliação do T90 examinou aspectos como a representatividade das incubações, escala dos experimentos de incubação e procedimentos de medição, com ênfase em modelos de decaimento bacteriano. Os fatores que afetam o decaimento bacteriano como radiação solar, salinidade e interação com sólidos foram considerados à luz do extenso registro da literatura. Finalm...

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Modeling Fecal Indicator Bacteria Concentrations in Natural Surface Waters: A Review

Cited by 117 publications

References 201 publications

Assessing the impact of socio-economic development and climate change on faecal indicator bacteria in the Betna River, Bangladesh

Assessing the impact of socio-economic development and climate change on faecal indicator bacteria in the Betna River, Bangladesh

Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan

Critical evaluation of the factors affecting Escherichia coli environmental decay for outfall plume models

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