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This study investigated soil–water quality–linked environmental risks in Potiskum, a semi-arid ecosystem in Yobe State, Nigeria, by integrating geo-referenced sampling, laboratory analysis, geospatial modelling and probabilistic risk assessment. Twenty-five soil and water samples were collected across diverse land-use domains, including agricultural fields, residential areas, waste-disposal vicinities and irrigation corridors. Physico-chemical and heavy metal parameters were analysed following APHA protocols, while GIS-based spatial analysis was employed to map contaminant patterns and identify risk zones. Complementary multivariate techniques, PCA, Pearson correlation and HCA, were applied to determine pollutant sources and soil–water interaction dynamics. Additionally, Monte Carlo simulation (10,000 iterations) quantified uncertainty in non-carcinogenic and carcinogenic risk pathways. The results revealed clear spatial differentiation between unregulated dumpsites and strategically located water points. Dumping sites clustered along dense road networks and high-population zones, suggesting accessibility-driven disposal practices, whereas water points demonstrated a more deliberate infrastructural layout with overlapping 200-m service buffers in central neighbourhoods. Multivariate results showed strong correlations among salinity indicators (EC, TDS, major ions) and co-mobilisation patterns among heavy metals, indicating shared geogenic and anthropogenic influences. PCA identified a small number of dominant components driving most contamination variability, while HCA grouped sampling locations into distinct environmental regimes reflecting varying pollution intensities. The findings highlighted the intertwined nature of solid-waste management, water accessibility and soil–water contamination dynamics in the study area. The study provided evidence-based findings for adaptive environmental planning, improved waste regulation and integrated soil–water quality monitoring in vulnerable dryland ecosystems.
| Title | Soil–Water Quality-Led Environmental Risk Probabilistic Analysis in a Semi-Arid Ecosystem: Evidence from Geo-Referenced Sampling Points |
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