Robust cluster analysis for detecting physico-chemical typologies of freshwater from wells of the plain of Friuli (northeastern Italy)

An approach for the characterisation of the groundwater system of the south ern plain of Friuli-Venezia Giulia Region (Italy) is proposed on the basis of its physico-chemical composition, in order to detect multivariate patter ns for unpolluted waters typical of specific areas in the plain, as well as for eventual polluted zones. The analytical data are relative to 38 wells (depth ranging from 20 to 200 m) sampled in three different periods along a year. Ten physico-chemical parameters were determined: conductivity, tempe rature, dissolved oxygen, calcium, magnesium, chlorides, nitrates, sulphate s, atrazine and desethylatrazine. Cluster analysis (CA) provides the methodological bases for detecting the c lasses of freshwater being typical for the considered plain: partitioning a round medoids (PAM) and fuzzy clustering are considered. The number of clas ses to be characterised and the clustering algorithm are selected by compar ing the average silhouette index for models counting from 2 to 10 clusters; six classes obtained by PAM partition the data set at best. Plotting the frequencies of cluster membership for each well on a map permi ts the association of the six classes of waters to five easily recognisable geographical areas and to one group of two wells that are highly polluted by nitrates and triazines. Averages and ranges of values for physico-chemical parameters of each class can be provided according to this methodology, defining a set of values be ing characteristic for the composition of waters belonging to the classes o f wells identified in the considered plain. (C) 2001 Elsevier Science B.V. All rights reserved.