Title of article :
Using chemical and physical parameters to define the quality of karstic freshwaters (Timavo River, North-eastern Italy): a chemometric approach
Author/Authors :
E. Reisenhofer، نويسنده , , G. Adami، نويسنده , , P. Barbieri، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 1998
Pages :
11
From page :
1193
To page :
1203
Abstract :
The Timavo River, rising in Monte Nevoso (Slovenia), sinks into a limestone fissure and proceeds subterraneously toward the Adriatic Sea, feeding many springs and ponds in the Karst region near Trieste (Italy). In order to characterize and discriminate the freshwaters of this complex hydrological system, 84 samples were taken in 14 selected sites during the autumnal flood. Six chemical-physical parameters were determined: temperature, pH and conductivity in situ; chloride, nitrate and sulphate contents in the laboratory, by high-performance ion-exchange chromatography (HPIEC). Univariate analysis of dispersion and centrality estimates of the populations of the experimental data allow us to discriminate a group of typically-karstic springs situated near S.Giovanni di Duino, as well as a group—to the north—of “mixed waters” that receive run-off from the northern Isonzo and Vipacco river-beds, and also seem affected by seasonal conditions. The multivariate cluster analysis (CA) confirms the discriminating ability of the considered parameters, and allow us to observe occasional intrusions of waters belonging to a group within a different group. The principal component analysis (PCA) supports the results of CA and permits us to assert the existence of a common watershed for the examined karstic freshwaters, which are characterized by 2 PCʹs: the ionic solutes are associated with the first component, whereas temperature and pH are associated with the second one. Factor scores show seasonal and meteorological effects on the chemical composition of the freshwaters.
Keywords :
chemical-physical parameters , karstic hydrology , karstic springs , Ion-exchange chromatography , cluster analysis , Principal component analysis , multivariate patternrecognition , freshwater parameters
Journal title :
Water Research
Serial Year :
1998
Journal title :
Water Research
Record number :
766452
Link To Document :
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