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Identifying key parameters to differentiate groundwater flow systems using multifactorial analysis

Multivariate techniques are useful in hydrogeological studies to reduce the complexity of large-scale data sets, and provide more understandable insight into the system hydrology.In this study, principal component analysis (PCA) has been used as an exploratory method to identify the key parameters that define distinct flow systems in the Selva basin (NE Spain). In this statistical analysis, all the information obtained in hydrogeological studies (that is, hydrochemical and isotopic data, but also potentiometric data) is used. Additionally, cluster analysis, based on PCA results, allows the associations between samples to be identified, and thus, corroborates the occurrence of different groundwater fluxes.PCA and cluster analysis reveal that two main groundwater flow systems exist in the Selva basin, each with distinct hydrochemical, isotopic, and potentiometric features. Regional groundwater fluxes are associated with high F- contents, and confined aquifer layers; while local fluxes are linked to nitrate polluted unconfined aquifers with a different recharge rates.In agreement with previous hydrogeological studies, these statistical methods stand as valid screening tools to highlight the fingerprint variables that can be used as indicators to facilitate further, more arduous, analytical approaches and a feasible interpretation of the whole data set

This study started as part of the research Project CICYT CGL-2008-06373-C03-03/BTE, and continued under Project CGL-2011-29975-C04-04, both of them funded by the Spanish Government

漏 Journal of Hydrology, 2012, vol. 472-473, p. 301-313

Elsevier

Author: Menci贸 i Domingo, Anna
Folch i Sancho, Albert
Mas-Pla, Josep
Date: 2012 November 23
Abstract: Multivariate techniques are useful in hydrogeological studies to reduce the complexity of large-scale data sets, and provide more understandable insight into the system hydrology.In this study, principal component analysis (PCA) has been used as an exploratory method to identify the key parameters that define distinct flow systems in the Selva basin (NE Spain). In this statistical analysis, all the information obtained in hydrogeological studies (that is, hydrochemical and isotopic data, but also potentiometric data) is used. Additionally, cluster analysis, based on PCA results, allows the associations between samples to be identified, and thus, corroborates the occurrence of different groundwater fluxes.PCA and cluster analysis reveal that two main groundwater flow systems exist in the Selva basin, each with distinct hydrochemical, isotopic, and potentiometric features. Regional groundwater fluxes are associated with high F- contents, and confined aquifer layers; while local fluxes are linked to nitrate polluted unconfined aquifers with a different recharge rates.In agreement with previous hydrogeological studies, these statistical methods stand as valid screening tools to highlight the fingerprint variables that can be used as indicators to facilitate further, more arduous, analytical approaches and a feasible interpretation of the whole data set
This study started as part of the research Project CICYT CGL-2008-06373-C03-03/BTE, and continued under Project CGL-2011-29975-C04-04, both of them funded by the Spanish Government
Format: application/pdf
ISSN: 0022-1694
Document access: http://hdl.handle.net/10256/12926
Language: eng
Publisher: Elsevier
Collection: MEC/PN 2009-2011/CGL2008-06373-C03-03
MICINN/PN 2012-2015/CGL2011-29975-C04-04
Reproducci贸 digital del document publicat a: http://dx.doi.org/10.1016/j.jhydrol.2012.09.030
Articles publicats (D-CCAA)
Is part of: 漏 Journal of Hydrology, 2012, vol. 472-473, p. 301-313
Rights: Tots els drets reservats
Subject: Aigua -- Fluoraci贸
Water -- Fluoridation
Hidrogeologia
Hydrogeology
An脿lisi multivariable
Multivariate analysis
Nitrats -- Contaminaci贸
Nitrates -- Pollution
Title: Identifying key parameters to differentiate groundwater flow systems using multifactorial analysis
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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