A Multivariate Statistical Analysis of Water Quality and Health Risk Assessment in Estie Denisa Spring and Wanka River, Ethiopia

Abstract

Abstract This study presents a comprehensive assessment of water quality in Estie Densa Spring and Wanka River in Ethiopia through the application of multivariate statistical methods. Water quality is a critical environmental parameter, and understanding its variations is essential for sustainable resource management. The research involves the collection of water samples from Estie Densa Spring and Wanka River, followed by the analysis of various physicochemical, nutrients and heavy metals parameters. Multivariate statistical methods, including principal component analysis (PCA) and cluster analyses, are employed to discern patterns and relationships within the dataset. Physicochemical parameters were measured using a multimeter and nutrients were measured using a portable photometer 7100 whereas heavy metals were determined by FAAS, after wet acid digestion. From the result, the range of physicochemical parameters and nutrients found in water samples were pH (6.4-8.1), EC (9.9-90 μS/cm), TDS (4.8-44.8 mg/L), Turbidity (4-315 NTU), Total alkalinity (1600 - 6800 mg/L), Temperature (21.3-28.6 ℃), Chlorine (35.6-213 mg/L), Phosphate (0.14-0.7 mg/L), Sulphate (1-4.25 mg/L), Ammonia (0.23-0.595 mg/L), Nitrate (1.2-11.8 mg/L) and Nitrite (0.015-0.139 mg/L). Among these parameters, only the level of turbidity was above the permissible limit. The levels of heavy metals (mg/L) in water samples were Cr (0.005-0.010), Mn (0.007-0.020), Ni (0.030-0.073), Fe (0.5- 0.71), Pb (0.005-0.006) and Cd (0.004-0.011). The levels of Fe and Cd, were higher than the permissible limit of WHO for drinking water which might have a risk for the consumers. The cumulative carcinogenicity risks of trace elements in the spring and river drinking water for adults and children were in the range of (9.2 ×10-3 - 2.52×10-2). which were above the acceptable monitored and controlled levels (1 × 10-4 – 1 × 10-6). Findings from this research contribute to the existing knowledge of water quality in the region, offering valuable information for decision-makers and environmental stakeholders. The application of multivariate statistical methods enhances the understanding of the interplay between various water quality parameters, facilitating more informed and targeted management strategies. Ultimately, this study serves as a basis for promoting sustainable water resource management practices in the context of Estie Densa Spring and Wanka River in Ethiopia.