On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

Abstract

Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data. However, these classical multivariate methods deal with two-way matrices, usually parameters× sites or parameters× time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters× sites× time. Three-way matrices, such as the one proposed here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach is the use of Partial Triadic Analysis (PTA). Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears to be a new promising statistical instrument for hydrogeologists, for characterization of temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for (1) identifying a common multivariate spatial structure, (2) untapping the different hydrochemical patterns and explaining their controlling factors and (3) analyzing the temporal variability of this structure and grasping hydrochemical changes. © 2013 Elsevier Ltd.