Determination of optimal sampling strategy and water quality characterization of Ikere reservoir, Iseyin, south-west Nigeria
Keywords:
Principal Component Analysis, Cluster Analysis, World Health Organization, Ikere reservoir, Nigeria's Food and Drug Administrative ControlAbstract
Water resources are essential for sustaining human life and socioeconomic activities, with reservoirs serving as critical water bodies. However, limited data on the Ikere reservoir’s current water quality hinders effective management. This research aims to assess the quality of water variation to develop an optimal sampling strategy for the Ikere Gorge Dam, Iseyin, Oyo State. Nigeria. Laboratory analysis was conducted on six (6) water samples from both the rainy and dry seasons at the study area, adhering to APHA (2017) Standard Methods for the Examination of Water and Wastewater, and encompassing physicochemical and biological parameters as well as heavy metals. The results were compared to Nigeria's Food and Drug Administrative Control (NAFDAC, 2020) and World Health Organization (WHO, 2017) standards. Principal Component Analysis (PCA) and Cluster Analysis (CA) were employed for the statistical analysis of the water quality parameter data to determine the optimal sampling strategy within the study area. The physicochemical, heavy metals, and biological parameters for the rainy and dry seasons, including pH, electrical conductivity, temperature, turbidity, total dissolved solids, E. coli e.t.c showed values ranging from 6.41 to 6.77, 72.23 to 91.37 µS, 24.10 to 29.23°C, 1.30 to 10.23 NTU, 0.01 to 0.10 mg/L, and 12.33 to 47.67 MPN/100mL. Parameters such as turbidity, phosphates, DO, and E. coli exceeded WHO and NAFDAC standards. This indicates potential health risks and environmental pollution. PCA results indicate the variance distribution across five principal components, with significant clustering patterns. In conclusion, integrating CA and PCA is essential for effective water quality assessment at Ikere Gorge Dam. CA identified distinct clusters, while PCA revealed key factors like COD and hardness reflecting natural influences and turbidity and copper indicating pollution.