Water quality of the Loopspruit, North- West Province: a geospatial, physicochemical and microbiological analysis
In the North West Province, surface water is polluted from sources such as surface runoff from agricultural settings, storm-water runoff as well as sewage from urban locations, and mining. This study aimed to evaluate the water quality of the Loopspruit River by analysing the physico-chemical and microbiological aspects of the Loopspruit River. Six objectives were set to achieve this. The first objective focussed to identify sampling sites using Geographic Information Systems (GIS) and aerial photographs to ensure. The second and third objectives set out to determine the water quality of two wet seasons and two dry seasons (2018 to 2019) and to analyse the historic data. The fourth was the isolation and identification of possible faecal associated micro-organisms, including Clostridium, presumptive E. coli and Enterococci species. Objectives five and six were to create predictive physico-chemical and microbiological point source contamination visual representation with historic data and data obtained from this study and to compare the outcomes. These isolated bacterial species (objective 4) were used to create a faecal point source pollution visual representation with their associated land-use contributions that were deposited within the Loopspruit River. Historic data were used to develop a predictive geospatial visual representation of the physico-chemical parameters to illustrate the land-use contributions to possible pollution in the Loopspruit River. The historic and current water quality data were visually represented using GIS software for water quantity. The results visually indicated that high magnesium (±41.30 mg/L) levels are prominent in mining and urban areas and pH levels (±9.49) are high in the dam area - all above normal levels. Antibiotic profiles indicated an increase in Multiple Antibiotic Resistances (MAR) with increased urban activities. Genes associated with antibiotic resistance were also detected. These included the intI1 integrase gene and the FOX AmpC β-lactamase gene. The LC/MS analyses revealed an excess amount of Ampicillin in the Loopspruit River with a risk value of 637.95 where the predicted no-effect concentration is 75. The bacterial diversity showed the highest diversity at less polluted areas whereas, in contrast, more pollution-prone areas showed less bacterial diversity. Dominating at all the sites were Proteobacteria, followed by Bacteroidetes, Cyanobacteria, Actinobacteria and Verrucomicrobia, having a broad variation to the total contribution from sample to sample. Finally, the predicted metagenome analysis revealed a correlation between the physico-chemical parameters and the observed taxonomic units (OTU). The temperature had negative correlations with Patescibacteria, Nanoarchaeaeota and Firmicutes (p<0.05). The negative correlation was strongest with Patescibacteria. SO4 showed the best correlation with Fusobacteria (p<0.05). The metabolic activity of the species diversity showed that 24.6% of the total OTUs used the ammonia oxidizer metabolic pathway, followed by dehalogenation with 20.2%. The sulphate-reducing bacteria, sulphide oxidizers, nitrite reducers and nitrogen fixation were also abundant in the predicted metabolic pathways that were used. Analysing and visually representing the water quality of the Loopspruit River demonstrated the value of combining geospatial and microbiological components for a holistic understanding of environmental health risks and management strategies.