Danube River water data modelling by multivariate data analysis

A data set (48 x 19) consisting of Danube river water analytical data colle cted at Galati site, Romania, during a four-year period has been treated by principal components analysis (PCA). The PCA indicated that seven latent f actors ("hardness", "biochemical", "waste inlets", "turbidity", "acidity", "soil extracts" and "organic wastes") are responsible for the data structur e and explain over 80 % of the total variance of the system. Its complexity is further proved by the application of multiple linear regression analysi s on the absolute principal components scores (APCS) where the contribution of each natural or anthropogenic sources in the factor formation is shown. The apportioning makes clear that each variable participates to a differen t extent to each source and, in this way, no pure natural or pure anthropog enic influence could be determined. No specific seasonality for the variabl es in consideration is found.