Assessment and interpretation of river water quality in Little Akaki River using multivariate statistical techniques

Abstract

Indiscriminant waste disposal is limiting the usability of the Little Akaki River in Addis Ababa, Ethiopia. Besides, there are inadequate comprehensive studies on the river principally due to insufficient research fund. Therefore, in this study, water quality investigation that is both regular and economical is sought. In October and November 2015, twenty-seven locations were sampled from the river and tributaries. Multivariate statistical tools were engaged to investigate data from measurements and laboratory analysis. Consequently, cluster analysis divided sampled sites into three according to level of their pollution. This indicates that water quality variation was caused because of the difference in land-use conditions. In addition, for the spatial analysis of the three pollution groups, backward stepwise approach of discriminant analysis was identified to provide data reduction (87.5%) to two parameters resulting in 85.2% correct assignment. The principal component analysis/factor analysis identified ten parameters accounting for 81.9% of total variation. However, data reduction was not significant. The factors that were latent and identified from the principal components’ varimax rotation suggest that variation in water quality was caused mainly by domestic sewage. The outcomes show that the methods can be applied to evaluate the river water quality variation using three monitoring sites and ten parameters: total nitrogen, total suspended solids, total ammonia, chemical oxygen demand, nitrite, total phosphorus, phosphate, nitrate, biological oxygen demand and electrical conductivity. This, in consequence, requires lesser cost and effort and hence paves way for more affordable, regular water quality evaluation of Little Akaki River.