Application of Water Quality Index (WQI) in Some Waterbodies in Enugu-Agidi, Njikoka LGA of Anambra State, Southeastern Nigeria
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Keywords:
Physicochemical; Water; Heavy Metal; Statistical Analysis; Principal ComponentAbstract
Water is a very important resource, especially for its usage in domestic and irrigation purposes. It is therefore pertinent to evaluate and determine the quality of water in our locality. In this study, five (5) freshwater bodies, namely Obibia River, Ogbunago Stream, Ovia Stream, Otukpuma River, and Diochiogba River, located at Enugu-Agidi, Njikoka LGA of Anambra State, were evaluated for their suitability for drinking and other domestic use. Three water samples were collected in-stitu from each stream, making it a total of fifteen water samples from the five sites, and analyzed in the laboratory for their physicochemical and heavy metal content. Thirteen (13) physicochemical parameters and four (4) heavy metals were used to determine the suitability of the water based on WHO 2022 addendum standards. The physicochemical parameters include: pH, TDS, EC, hardness, temperature, chloride, nitrate, BOD, DO, color, odor, appearance, and turbidity. The heavy metals include iron, arsenic, zinc, and lead. The heavy metals within the water body are spatially analyzed using a bar chart, which shows that iron has the highest concentration, followed by zinc, and the lowest is arsenic. The Pearson correlation analysis was also used to unravel the complex relationship of the 15 water quality parameters examined across five sampling points. In the Pearson correlation matrix, strong positive correlation was observed in conductivity, turbidity, nitrate, and iron, with values ranging from 0.84 to 0.98. Conductivity correlated 0.98 with iron, 0.89 with turbidity, and 0.84 with nitrate. Similarly, turbidity showed a correlation of 0.92 with nitrate. Temperature exhibits a strong negative relationship with pH (-0.73), hardness (-0.57), and lead (-0.91). Lead (Pb) has a strong negative correlation with temperature, which means lead solubility and mobility increase substantially with decreasing temperature. The principal component analysis (PCA) was also used to explain the variance, with PC1 explaining 33.15% of the total variance to represent conductivity, turbidity, nitrate, and biological oxygen demand. PC2 similarly explains 30.56% of the variance controlled by pH and temperature. PC3 represents 22% of the mineralization and salinity concentration, and PC4, 13.29%, explains the variation in the component that captures arsenic and lead. Whereas PC5 measures the noise and is less than 1%. Therefore, the physicochemical parameters and heavy metals were compared to the WHO standard, and the general water quality index was greater than 100 (WQI value > 100) for the five rivers; when compared with BIS-WQI (Bureau of Indian Standards Water Quality Index), the value was greater than 300 (WQI value > 300), which, when placed on their classification scheme, shows that the water was unsuitable for drinking and other uses. Therefore, from the results obtained in the statistical analysis, the rural community using this water should be cautious of infection and other diseases, as it is recommended that government and non-governmental agencies be involved in producing suitable and palatable drinking water for the community affected that solely relies on this stream and river for their daily survival.
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