The multivariate tools of Principal Components Analysis (PCA) and K-Means Cluster Analysis (CA) were applied analyze the evolution of groundwater chemistry in the El Paso, Texas region. The source data consisted of public domain chemical analyses from 7687 wells. The data was filtered and scanned to remove inconsistent analyses, remove statistical outliers, and determine analytes where data completeness was sufficiently great to allow for multivariate statistical analysis. The data was divided into five basins: (a) Mimbres Basin, (b) Tularosa Basin, (c) Hueco Basin, (d) Rio Grande Basin, (e) Diablo Plateau Aquifer and analyzed in its entirety. For each basin a different subset of analytes was chosen for multivariate analysis depending upon ...
The groundwater hydrochemical behaviour of the Langueyú creek basin (Argentina) has been evaluated t...
The present study focuses on hydrogeochemical data from a Hercynian granitic mass where a new underg...
ABSTRACT: Q-mode hierarchical cluster (HCA) and principal component analysis (PCA) were simultaneous...
Multivariate statistical methods (MSMs) applied to groundwater chemistry provide valuable insight in...
The development of high-speed computers has enlarged the scope of data processing and reduction. Man...
Multivariate techniques are useful in hydrogeological studies to reduce the complexity of large-scal...
Multivariate statistical techniques including correlation, principal component analysis (PCA), and c...
Multivariate statistical techniques such as principal component (PCA) and cluster analyses, were app...
Abstract: The study of hydrogeochemistry of the Mio-Pliocene sedimentary rock aquifer system in Veer...
The ground water quality of the Trinity Aquifer for wells sampled between 2000 and 2009 was examined...
The different factors (seasonal changes) and variables (physicochemical) controlling the groundwater...
Multivariate statistical techniques are efficient ways to display complex relationships among many o...
The objective of this work is to compare the chemical composition and the spatial and temporal varia...
Multivariate statistics are widely and routinely used in the field of hydrogeochemistry. Trace eleme...
This study is a contribution to the knowledge of hydrochemical properties of the groundwater in Fesd...
The groundwater hydrochemical behaviour of the Langueyú creek basin (Argentina) has been evaluated t...
The present study focuses on hydrogeochemical data from a Hercynian granitic mass where a new underg...
ABSTRACT: Q-mode hierarchical cluster (HCA) and principal component analysis (PCA) were simultaneous...
Multivariate statistical methods (MSMs) applied to groundwater chemistry provide valuable insight in...
The development of high-speed computers has enlarged the scope of data processing and reduction. Man...
Multivariate techniques are useful in hydrogeological studies to reduce the complexity of large-scal...
Multivariate statistical techniques including correlation, principal component analysis (PCA), and c...
Multivariate statistical techniques such as principal component (PCA) and cluster analyses, were app...
Abstract: The study of hydrogeochemistry of the Mio-Pliocene sedimentary rock aquifer system in Veer...
The ground water quality of the Trinity Aquifer for wells sampled between 2000 and 2009 was examined...
The different factors (seasonal changes) and variables (physicochemical) controlling the groundwater...
Multivariate statistical techniques are efficient ways to display complex relationships among many o...
The objective of this work is to compare the chemical composition and the spatial and temporal varia...
Multivariate statistics are widely and routinely used in the field of hydrogeochemistry. Trace eleme...
This study is a contribution to the knowledge of hydrochemical properties of the groundwater in Fesd...
The groundwater hydrochemical behaviour of the Langueyú creek basin (Argentina) has been evaluated t...
The present study focuses on hydrogeochemical data from a Hercynian granitic mass where a new underg...
ABSTRACT: Q-mode hierarchical cluster (HCA) and principal component analysis (PCA) were simultaneous...