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A Probabilistic Methodology to Assess the Risk of Groundwater Quality Degradation

dc.contributor.authorPassarella, G.en_US
dc.contributor.authorVurro, M.en_US
dc.contributor.authorD'Agostino, V.en_US
dc.contributor.authorGiuliano, G.en_US
dc.contributor.authorBarcelona, Michael J.en_US
dc.date.accessioned2006-09-08T20:37:19Z
dc.date.available2006-09-08T20:37:19Z
dc.date.issued2002-10en_US
dc.identifier.citationPassarella, G.; Vurro, M.; D'Agostino, V.; Giuliano, G.; Barcelona, M. J.; (2002). "A Probabilistic Methodology to Assess the Risk of Groundwater Quality Degradation." Environmental Monitoring and Assessment 79(1): 57-74. <http://hdl.handle.net/2027.42/42696>en_US
dc.identifier.issn0167-6369en_US
dc.identifier.issn1573-2959en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/42696
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=12381023&dopt=citationen_US
dc.description.abstractAn approach to assess the risk of groundwater quality degradation with regard to fixed standards, based on DisjunctiveKriging ( DK ) is presented. The DK allows one to evaluate the Conditional Probability (CP) of overriding a given threshold of concentration of a pollutant at a given time, and at a generic point in a consideredgroundwater system. The result of such investigation over the considered area can be plotted in form of maps of spatial risk . By repeating this analysis at different times, several spatial risk maps will be produced, one for each consideredtime. By means of non-parametric statistics, the temporal trendof the CPs can be evaluated at every point of the considered area. The trend index , assessed by means of a sort of classification of the trend values obtained as described above,can be superimposed on the most recent values of the spatialrisk (i.e.: the most recent values of probability). Consequentlya classification of the risk of groundwater quality degradationresults with which to weigh both the spatial distribution and thetemporal behaviour of the probability to exceed a given standardthreshold. The methodology has been applied to values of nitrateconcentration sampled in the monitoring well network of theModena plain, northern Italy. This area is characterised by intensive agricultural exploitation and hog breeding along withindustrial and civil developments. The influence of agriculture on groundwater results in a high nitrate pollution that limitsits use for potable purposes.en_US
dc.format.extent1363070 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherEnvironmenten_US
dc.subject.otherEcologyen_US
dc.subject.otherAtmospheric Protection/Air Quality Control/Air Pollutionen_US
dc.subject.otherEnvironmental Managementen_US
dc.subject.otherMonitoring/Environmental Analysis/Environmental Ecotoxicologyen_US
dc.subject.otherConditional Probabilityen_US
dc.subject.otherDisjunctive Krigingen_US
dc.subject.otherGroundwater Managementen_US
dc.subject.otherGroundwater Qualityen_US
dc.subject.otherRisken_US
dc.titleA Probabilistic Methodology to Assess the Risk of Groundwater Quality Degradationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, U.S.Aen_US
dc.contributor.affiliationotherWater Research Institute, CNR, V. le De Blasio, Bari, Italyen_US
dc.contributor.affiliationotherWater Research Institute, CNR, V. le De Blasio, Bari, Italyen_US
dc.contributor.affiliationotherTecnopolis, NOVUS ORTUS, s.s. Casamassima, Valenzano, Bari, Italyen_US
dc.contributor.affiliationotherCNR, Via Reno, Rome, Italyen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.identifier.pmid12381023en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/42696/1/10661_2004_Article_392680.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1023/A:1020033808025en_US
dc.identifier.sourceEnvironmental Monitoring and Assessmenten_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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