Assessment of pollutant sources of River Musa in Niger State using receptor model and principal component analysis

Abstract

River water plays an important role in dilution of various pollutants and thereby affecting water quality for various purposes. The objective of this study  was to assess Water Quality index (WQI), identify and quantify pollutants levels flowing into the River Musa in Bida. Water samples were collected at five different locations along the river during rainy season in 2018. Ten water quality parameters (Temperature, pH, EC, Mg, Na, Iron, Mn, Calcium, Potassium  and SAR) were determined in five stations. Experiment were set in 5 x 3x 2 factorial experiment in a Complete Randomized Design (CRD). To achieve the  objective, Cananadian Council of Ministers of Enviroment (CCME) index was used to determine WQI and Principal Component Analysis (PCA) to identify  pollutants. However, Receptor Model (RM) was used to predict the pollutant levels. Model evaluation results showed good fit between predicted and  observed values, with R, Adjusted R and RMSE values of 0.911, 0.643 and 0.074 respectively. The difference between Akaike‟s Information Criteria (AIC)  and Schwarz Bayesian Criteria (SBC) value is -1.56 indicating high accuracy of the model performance. Analysis of variance (ANOVA) showed the  significance difference between the predictors at 95% confidence interval. According to CCME WQI, the results for the five locations (Edokota station,  Musa bridge station, Bida/Minna station, Ciriko station and Army barrack station) were 74.47, 72.85, 64.69, 47.62, and 51.56 respectively. Three of the five stations investigated were ranked as marginal and the remaining two were fair in rank. PCA was used to identify three pollutants flowing to the river to  be industrial, municipal and erosion, and pollutants levels were determined to be 0.936, 0.457 and 0.104 using RM. The WQI of the river is marginal and  the implication is that it poised threat to the users. Erosion was predicted as one of the strongest polluttants contributor in the model, followed by  municipal and the least contributor is industrial waste. It is strongly recommended that periodic monitoring of the river water quality is carried out.