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dc.contributor.authorGuadagnini, Laura
dc.contributor.authorMenafoglio, Alessandra
dc.contributor.authorSánchez Vila, Francisco Javier
dc.contributor.authorGuadagnini, Alberto
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2020-10-20T14:43:44Z
dc.date.issued2020-10
dc.identifier.citationGuadagnini, L. [et al.]. Probabilistic assessment of spatial heterogeneity of natural background concentrations in large-scale groundwater bodies through Functional Geostatistics. "Science of the total environment", Octubre 2020, vol. 740, p. 140139:1-140139:12.
dc.identifier.issn0048-9697
dc.identifier.urihttp://hdl.handle.net/2117/330514
dc.description.abstractWe propose and exemplify a framework to assess Natural Background Levels (NBLs) of target chemical species in large-scale groundwater bodies based on the context of Object Oriented Spatial Statistics. The approach enables one to fully exploit the richness of the information content embedded in the probability density function (PDF) of the variables of interest, as estimated from historical records of chemical observations. As such, the population of the entire distribution functions of NBL concentrations monitored across a network of monitoring boreholes across a given aquifer is considered as the object of the spatial analysis. Our approach starkly differs from previous studies which are mainly focused on the estimation of NBLs on the basis of the median or selected quantiles of chemical concentrations, thus resulting in information loss and limitations related to the need to invoke parametric assumptions to obtain further summary statistics in addition to those considered for the spatial analysis. Our work enables one to (i) assess spatial dependencies among observed PDFs of natural background concentrations, (ii) provide spatially distributed kriging predictions of NBLs, as well as (iii) yield a robust quantification of the ensuing uncertainty and probability of exceeding given threshold concentration values via stochastic simulation. We illustrate the approach by considering the (probabilistic) characterization of spatially variable NBLs of ammonium and arsenic detected at a monitoring network across a large scale confined groundwater body in Northern Italy.
dc.language.isoeng
dc.publisherElsevier
dc.rights© 2019. Elsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Geologia::Hidrologia subterrània
dc.subject.lcshGroundwater--Management
dc.subject.otherNatural background level
dc.subject.otherGroundwater quality
dc.subject.otherChemical status
dc.subject.otherKriging
dc.subject.otherProbability density function
dc.subject.otherUncertainty quantification
dc.titleProbabilistic assessment of spatial heterogeneity of natural background concentrations in large-scale groundwater bodies through Functional Geostatistics
dc.typeArticle
dc.subject.lemacAigües subterrànies -- Gestió
dc.contributor.groupUniversitat Politècnica de Catalunya. GHS - Grup d'Hidrologia Subterrània
dc.identifier.doi10.1016/j.scitotenv.2020.140139
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0048969720336603
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac29291590
dc.description.versionPostprint (author's final draft)
dc.date.lift2022-06-10
local.citation.authorGuadagnini, L.; Menafoglio, A.; Sanchez-Vila, X.; Guadagnini, A.
local.citation.publicationNameScience of the total environment
local.citation.volume740
local.citation.startingPage140139:1
local.citation.endingPage140139:12


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