WATER QUALITY PARAMETERS FOR POLLUTION SOURCE IDENTIFICATION IN WARWADE DAM WATER, DUTSE, JIGAWA STATE, NIGERIA: STATISTICAL AND SPATIOTEMPORAL EVALUATION (FUDMA JOURNAL OF SCIENCES, 2022)
This study looked at the diminishing water quality of Warwade Dam, which is one of Dutse's largest dams. Statistical methodologies such as descriptive statistics, principal component analysis (PCA), regression analysis, correlation analysis, and cluster analysis were used to examine selected water quality characteristics. pH, conductivity, TDS, temperature, and DO captured the highest variability (98.94%) in the data set, according to the PCA scree plot. Ca and Mg were the most variable from the PCA scree plot among the metals studied (99.96 percent). The correlational analysis revealed that the characteristics differed in terms of spatio-temporal and/or limnological aspects. Variables within a cluster are relatively similar, whereas variables outside a cluster are very dissimilar, according to cluster analysis employing hierarchical dendrogram to establish linkages, relationships, and differences among parameters. The validation test was passed by 67 percent of the parameters in the general linear regression model (very strong fit at P value 0.05). The PCA scree plot of 99.39 percent variability revealed that the dam concentrations of nitrate, nitrite, and chloride were identical
Keywords: Principal component, Cluster, Correlation, Descriptive statistics, Regression analyses, Warwade Dam, Spatio-Temporal