Multivariate statistical analysis supporting the hydrochemical characterization of groundwater and surface water: a case study in northern Italy

Marco Rotiroti (1), Chiara Zanotti (1), Letizia Fumagalli (1), Sara Taviani (1), Gennaro A. Stefania (1), Martina Patelli (1), Veronica Nava (1), Valentina Soler (1), Elisa Sacchi (2) & Barbara Leoni (1)
(1) Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy. (2) Department of Earth and Environmental Sciences, University of Pavia, Pavia, Italy. Corresponding author e-mail: marco.rotiroti@unimib.it

Multivariate statistical analysis is a useful method for supporting the interpretation of experimental data, particularly in the case of large datasets. In the present study, cluster analysis and factor analysis are used to support the hydrochemical characterization of groundwater and surface water in an area located in the Oglio River basin (N Italy). During a field survey performed in Fall 2015, 58 groundwater, 20 river (Oglio River and its main tributaries), 1 Lake Iseo and 7 spring samples were collected for chemical analysis. Results of multivariate statistical analysis led to the identification of the following 5 main clusters which characterize the hydrological system: (1) higher plain groundwater and springs, characterized by an oxidized hydrofacies with higher NO₃, (2) lower plain groundwater, characterized by a reduced hydrofacies with higher As, Fe and Mn, (3) Oglio River, (4) Oglio River tributaries and (5) outliers. This characterization will bear the improvement of the hydrogeological conceptual model of the area, also oriented to groundwater/surface water interactions, that, in turn, will support the numerical flow modeling of the system.

Cluster Analysis, Factor Analysis, Nitrate, Arsenic, Oglio River.