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dc.contributor.authorMISSTEAR, BRUCEen
dc.date.accessioned2014-03-03T11:41:59Z
dc.date.available2014-03-03T11:41:59Z
dc.date.issued2014en
dc.date.submitted2014en
dc.identifier.citationHynds, Paul Misstear, Bruce D. Gill, Laurence W. Murphy, Heather M., Groundwater source contamination mechanisms: Physicochemical profile clustering, risk factor analysis and multivariate modelling, Journal of Contaminant Hydrology, 2014en
dc.identifier.otherYen
dc.descriptionPUBLISHEDen
dc.description.abstractAn integrated domestic well sampling and ?susceptibility assessment? programme was undertaken in the Republic of Ireland from April 2008 to November 2010. Overall, 211 domestic wells were sampled, assessed and collated with local climate data. Based upon groundwater physicochemical profile, three clusters have been identified and characterized by source type (borehole or hand-dug well) and local geological setting. Statistical analysis indicates that cluster membership is significantly associated with the prevalence of bacteria (p = 0.001), with mean E. coli presence within clusters ranging from 15.4% (Cluster-1) to 47.6% (Cluster-3). Bivariate risk factor analysis shows that on-site septic tank presence was the only risk factor significantly associated (p <0.05) with bacterial presence within all clusters. Point agriculture adjacency was significantly associated with both borehole-related clusters. Well design criteria were associated with hand-dug wells and boreholes in areas characterized by high permeability subsoils, while local geological setting was significant for hand-dug wells and boreholes in areas dominated by low/moderate permeability subsoils. Multivariate susceptibility models were developed for all clusters, with predictive accuracies of 84% (Cluster-1) to 91% (Cluster-2) achieved. Septic tank setback was a common variable within all multivariate models, while agricultural sources were also significant, albeit to a lesser degree. Furthermore, well liner clearance was a significant factor in all models, indicating that direct surface ingress is a significant well contamination mechanism. Identification and elucidation of cluster- specific contamination mechanisms may be used to develop improved overall risk management and wellhead protection strategies, while also informing future remediation and maintenance efforts.en
dc.language.isoenen
dc.relation.ispartofseriesJournal of Contaminant Hydrologyen
dc.rightsYen
dc.subjectCluster Analysis,en
dc.subjectE. colien
dc.titleGroundwater source contamination mechanisms: Physicochemical profile clustering, risk factor analysis and multivariate modellingen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/bmissteren
dc.identifier.rssinternalid92249en
dc.rights.ecaccessrightsOpenAccess
dc.identifier.urihttp://hdl.handle.net/2262/68185


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