Abstract
A set of quantitative descriptive and analytical data from the wastewater treatment plant (WWTP) of Sfax, located on the south-east of Tunisia, has been processed by multivariate statistical techniques in order to investigate the evolution of the wastewater quality over a period of 12 years (1984–1996) for six physico-chemical and biological parameters. The experimental 6×12 matrix was analysed by principal component analysis (PCA). The exploration of the correlation matrix allowed to uncover strong associations between some variables (BODi CODi, SSi BDOo, CODo SSo) as well as a lack of association between the others (Twater and SSo). PCA showed the existence of up to three significant PCs which account for 74% of the variance. The first one assigned to water with relatively low organic load, whereas the second and the third assigned to water with an average and high organic and mineral loads. This study presents necessity and usefulness of multivariate statistical techniques for evaluation and interpretation of large complex data sets with view to get better information about the water quality and design of monitoring network for effective management of water resources.
Published Version
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