Application of Multivariate Methods for Assessment of Variations in Rivers/Streams Water Quality in Niger State, Nigeria

Abstract

Multivariate statistical methods, Cluster Analysis (CA) and Canonical Discriminant Analysis (CDA) were applied to assess the temporal and spatial variations, and identify pollution sources in some rivers/streams of Niger State in Nigeria. Sixteen towns were sampled as medium-sized towns in which data were gathered on four physical, eleven chemical and two microbial parameters of water. Hierarchical CA grouped the sixteen sampled sites into four main seasonal clusters and three main groups of similar water quality. Stepwise selection for the temporal Discriminant Analysis (DA) identified the most significant parameters for discriminating between the four seasons as magnesium, Escherichia coli, total coliform, total dissolved solid (TDS) and total hardness with 83.3% apparent correct classification. The stepwise selection for the spatial Discriminant Analysis (DA) show that, Escherichia coli and magnesium is more prevalent in winter; while Escherichia coli and total dissolved solid (TDS) is higher in spring; and Escherichia coli and total coliform were more in summer and autumn with 94% total success rate of classification. The outcome of this study also show that the sources of water in groups one and two were more polluted than group three during summer and autumn than in the winter and spring. Based on these findings, it is recommended that the frequency of monitoring sites could be reduced to only sites in groups one and two while the seasons could be based on summer and autumn.