Joint interpretation of the hydrochemistry of two neighbouring basins by N-way multivariate methods
详细信息   
摘要
The objective of this work is to compare the chemical composition and the spatial and temporal variabilities of groundwater in two basins, the Langueyú and Del Azul creeks basins, located in the Pampean plain, Buenos Aires province (Argentina). The Pampean plain is the most productive region in Argentina, agriculture and livestock being the main economic activities. Groundwater is the principal water resource in the region, with a strong and growing demand for human supply and for agriculture and industrial activities. Several sampling campaigns were carried out on shallow wells of the two studied basins along a period of 3 years (2010–2013) to identify seasonal variations. Electrical conductivity, pH, bicarbonate, chloride, sulphate, nitrate, calcium, magnesium, sodium and potassium were determined following standard methods. For hydrochemical interpretation, descriptive statistical analyses, matrix augmentation principal component analysis, MA-PCA, and multidimensional principal component analysis, N-PCA (Parafac and Tucker3 models), were applied to the hydrochemical datasets from both basins. Three main hydrochemical processes have been identified in both basins: saline enrichment in the groundwater flow direction caused by dissolution of carbonates; exchange of calcium and magnesium by sodium in the same direction, and located areas of nitrate pollution. The paper shows that N-PCA is a good tool to deepen in the understanding of the hydrochemical features of groundwater from two neighbour basins, simplifying the analysis of large amounts of data, as well as establishing relations between the compared basins. Therefore the work is considered an interesting contribution to the study of groundwater resources with a regional scope. This knowledge is essential in basins with high socio-economic interests it causes a direct impact on resources management. Keywords Groundwater Pampean plain N-way principal component analysis Multivariate statistics Hydrochemistry Spatial and temporal variabilities Regional scope