title: Combining natural background levels (NBLs) assessment with indicator kriging analysis to improve groundwater quality data interpretation and management.
abstract: The natural background level (NBL) concept is revisited and combined with indicator kriging method to analyze the spatial distribution of groundwater quality within a groundwater body (GWB). The aim is to provide a methodology to easily identify areas with the same probability of exceeding a given threshold (which may be a groundwater quality criteria, standards, or recommended limits for selected properties and constituents). Three case studies with different hydrogeological settings and located in two countries (Portugal and Italy) are used to derive NBL using the preselection method and validate the proposed methodology illustrating its main advantages over conventional statistical water quality analysis. Indicator kriging analysis was used to create probability maps of the three potential groundwater contaminants. The results clearly indicate the areas within a groundwater body that are potentially contaminated because the concentrations exceed the drinking water standards or even the local NBL, and cannot be justified by geogenic origin. The combined methodology developed facilitates the management of groundwater quality because it allows for the spatial interpretation of NBL values.
authors.affiliation: Department of Civil, Architectural and Environmental Engineering, University of Naples, Piazzale Tecchio 80, 80125 Naples, Italy; IRSA-CNR, Water Research Institute, National Research Council, Via Salaria Km 29,300, 00015, Monterotondo, Rome, Italy. Electronic address: daniela@unina.it.
authors.forename: Daniela
authors.initials: D
authors.lastname: Ducci
authors.affiliation: CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal.
authors.forename: M Teresa Condesso
authors.initials: MTC
authors.lastname: de Melo
authors.affiliation: IRSA-CNR, Water Research Institute, National Research Council, Via Salaria Km 29,300, 00015, Monterotondo, Rome, Italy.
authors.forename: Elisabetta
authors.initials: E
authors.lastname: Preziosi
authors.affiliation: Department of Civil, Architectural and Environmental Engineering, University of Naples, Piazzale Tecchio 80, 80125 Naples, Italy.
authors.forename: Mariangela
authors.initials: M
authors.lastname: Sellerino
authors.affiliation: IRSA-CNR, Water Research Institute, National Research Council, Via Salaria Km 29,300, 00015, Monterotondo, Rome, Italy; Department of Science, RomaTre University, Rome, Italy.
authors.forename: Daniele
authors.initials: D
authors.lastname: Parrone
authors.affiliation: CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal.
authors.forename: Luis
authors.initials: L
authors.lastname: Ribeiro
mesh_terms: D001151:Arsenic / Q000032:analysis; D004784:Environmental Monitoring / Q000379:methods*; D060587:Groundwater / Q000032:analysis*; D007501:Iron / Q000032:analysis; D007558:Italy; D008345:Manganese / Q000032:analysis; D011174:Portugal; D062206:Spatial Analysis; D014874:Water Pollutants, Chemical / Q000032:analysis*; D060753:Water Quality / Q000592:standards
chemical_list: D014874:Water Pollutants, Chemical; D008345:Manganese; D007501:Iron; D001151:Arsenic
keywords: Groundwater contamination; Indicator kriging; Natural background level; Probability maps