Application of Multivariate Statistical Analysis in the Assessment of Surface Water Quality in the Hydrographic Network of Mazafran Wadi, Algeria

To study the spatial variation of the water quality of the Wadi Mazafran river network and to identify the sources of pollution, multivariate statistical techniques, such as cluster analysis (CA) and principal component analysis (PCA), were applied. Seasonal sampling was conducted from May 2018 to May 2019. Twelve (12) sites were selected. The temperature of the water and air, hydrogen potential, dissolved oxygen, conductivity, water speed, chlorides, sulphates, calcium, magnesium, total hardness, bicarbonates, nitrates, nitrites, phosphates, and BOD5 are measured. The hierarchical CA has grouped 12 sampling sites into three groups. The PCA resulted in three factors explaining 81.04% of the total variance. The first factor obtained represents mineral and organic pollutions. Factor 2 represents the phosphate pollution. The third factor represents the effects of flow velocity.