Statistical Approach in Determining the Spatial Changes of Surface Water Quality at the Upper Course of Kano River, Nigeria

Examining the dynamics of the relationship between water pH and other water quality parameters in ground and surface water systems

This study evaluated the relationship between water pH and the physicochemical properties of water while controlling for the influence of heavy metals and bacteriological factors using a nested logistic regression model. The study further sought to assess how these relationships are compared across confined water systems (ground water) and open water systems (surface water). Samples were collected from 100 groundwater and 132 surface water locations in the Tarkwa mining area. For the zero-order relationship in groundwater, EC, TDS, TSS, Ca, SO42-, total alkalinity, Zn, Mn, Cu, faecal and total coliform were more likely to predict optimal water pH. For surface water however, only TSS, turbidity, total alkalinity and Ca were significant predictors of optimal pH levels. At the multivariate level for groundwater, TDS, turbidity, total alkalinity and TSS were more likely to predict optimal water pH while EC, Mg, Mn and Zn were associated with non-optimal water pH. For the surface water system, turbidity, Ca, TSS, NO3, Mn and total coliform were associated with optimal water pH while SO42-, EC, Zn, Cu, and faecal coliform were associated with non-optimal water pH. The non-robustness of predictors in the surface water models were conspicuous. The results indicate that the relationship between water pH and other water quality parameters are different in different water systems and can be influenced by the presence of other parameters. Associations between parameters are steadier in groundwater systems due to its confined nature. Extraneous inputs and physical variations subject surface water to constant variations which reflected in the non-robustness of the predictors. However, the carbonate system was influential in how water quality parameters associate with one another in both ground and surface water systems. This study affirms that chemical constituents in natural water bodies react in the environment in far more complicated ways than if they were isolated and that the interaction between various parameters could predict the quality of water in a particular system.

Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir

Paldang Reservoir, located in the Han River basin in South Korea, is used for drinking water, fishing, irrigation, recreation, and hydroelectric power. Therefore, the water quality of the reservoir is of great importance. The main objectives of this study were to evaluate spatial and seasonal variations of surface water quality in the reservoir using multivariate statistical techniques (MSTs) along with the Trophic State Index (TSI) and Trophic State Index deviation (TSID). The empirical relationships among nutrients (total phosphorus, TP; total nitrogen, TN), chlorophyll-a (CHL-a), and annual variations of water quality parameters were also determined. To this end, 12 water quality parameters were monitored monthly at five sites along the reservoir from 1996 to 2019. Most of the parameters (all except pH, dissolved oxygen (DO), and total coliform bacteria (TCB)) showed significant spatial variations, indicating an influence of anthropogenic activities. Principal component analysis combined with factor analysis (PCA/FA) suggested that the parameters responsible for water quality variations were primarily correlated with nutrients and organic matter (anthropogenic), suspended solids (both natural and anthropogenic), and ionic concentrations (both natural and anthropogenic). Stepwise spatial discriminant analysis (DA) identified water temperature (WT), DO, electrical conductivity (EC), chemical oxygen demand (COD), the ratio of biological oxygen demand (BOD) to COD (BOD/COD), TN, TN:TP, and TCB as the parameters responsible for variations among sites, and seasonal stepwise DA identified WT, BOD, and total suspended solids (TSS) as the parameters responsible for variations among seasons. COD has increased (R2 = 0.63, p < 0.01) in the reservoir since 1996, suggesting that nonbiodegradable organic loading to the water body is rising. The empirical regression models of CHL-a-TP (R2 = 0.45) and CHL-a-TN (R2 = 0.27) indicated that TP better explained algal growth than TN. The mean TSI values for TP, CHL-a, and Secchi depth (SD) indicated a eutrophic state of the reservoir for all seasons and sites. Analysis of TSID suggested that blue-green algae dominated the algal community in the reservoir. The present results show that a significant increase in algal chlorophyll occurs during spring in the reservoir. Our findings may facilitate the management of Paldang Reservoir.

A comprehensive review of water quality monitoring and assessment in Nigeria

Nigeria is the most populated black nation in the world with about 199 million people. About 66.3 million Nigerians do not have access to safe drinking water. In this study, research findings on water quality monitoring and assessment in Nigeria over the past two decades were systematically reviewed. There are still grave enforcement issues in Nigeria as quality guidelines are still being contravened at no cost to the infringer due to the corrupt socio-political circumstances of the country. The quality of surface water, groundwater, rainwater and commercially available water was discussed in line with their pollution sources. The quality of surface water was generally poor. Groundwater pollution has come due to landfill leachate, oil and gas exploration and production, sewage and hydrogeological interactions of the groundwater with the base rock. The hydrogeological effect has led to the observation of lead and barium in groundwater in many locations across the country. The main issue with rainwater in Nigeria is the low pH but it was observed to be fairly clean. Commercially available water (bottled or sachet) is currently the best source of drinking water for the Nigerian populace. Bottled water quality is higher than for sachet water and the latter largely influenced by microbe contamination. Future perspectives in water quality monitoring and assessment are suggested in the evaluation of emerging contaminants and micro-pollutants and the utilisation of internet-enabled technologies.