Assessment of Surface Water Quality Using Chemometric Tools: A Case Study of Jabi Lake, Abuja, Nigeria

Abstract

Abstract Water pollution has become a growing threat to human society and natural ecosystems in recent decades. It increases the need to understand surface water quality assessment better using chemometric tools within aquatic systems. This study sampled the water quality of 21 parameters at multiple sampling points in Jabi Lake during wet and dry seasons (August–December 2021) using various statistical methods including cluster analysis, principal component analysis/factorial analysis, discriminant analysis, and box plot analysis. These samples were examined for physicochemical parameters employing standard techniques. The study revealed significant seasonal variations in water quality. During the wet season, key measurements included total dissolved solids (100.40 mg/l), dissolved oxygen (13.72 mg/l), and electrical conductivity (97.14 µs/cm). The dry season showed higher levels of most parameters, with total dissolved solids at 137.91 mg/l and electrical conductivity at 230.93 µs/cm. Statistical analysis identified strong correlations between various parameters, notably between phosphate and total hardness in the wet season (r = 0.978, α = 0.05) and between pH and temperature in the dry season (r = 0.995, α = 0.05). The study identified four principal components explaining 98.5–100% of the variance, representing various pollution sources including organic waste, domestic sewage, and natural factors. The findings indicated that dry season water samples were more polluted, with some parameters exceeding World Health Organisation standards, suggesting potential health risks. The research demonstrated the effectiveness of multivariate statistical techniques in analysing complex water quality data and provided valuable insights for water resource management, particularly regarding seasonal variations' impact on water quality.