Abstract
Study region
Transboundary Komadugu-Yobe basin, located in the semi-arid to arid region of Nigeria and Niger Republic, is a vital water resource supporting domestic, agricultural, and industrial activities.
Study focus
This study investigates the pollution levels, potential sources, and human health risks associated with potentially toxic elements (PTEs) in groundwater using an integrated approach combining index-based models and chemometric analysis.
New hydrological insights for the region
The results indicate that Pb, Fe, Mn, and Cd are the key contaminants, with no significant seasonal variations. Pollution indices (Cdeg, HEI, HPI, and mHPI) classify groundwater as less polluted in upgradient areas and highly polluted in downgradient zones. Human health risk assessment (HHRA) reveals significant non-carcinogenic and carcinogenic risks (mean HI > 1 for both adults and children; mean CR > 1.0 × 10⁻³ for adults, and > 1.0 × 10⁻⁴ for children). As, Cd, Mn, and Pb are key the contributors to non-carcinogenic and carcinogenic health risks and potential risks of chronic kidney disease of unknown aetiology (CKDu). Correlation analysis suggests distinct geochemical behaviours of PTEs. Principal Component Analysis/Factor Analysis (PCA/FA) and R-mode Hierarchical Cluster Analysis (HCA) identify mixed sources, including industrial and domestic discharges as well as agricultural activities, as major contributors to groundwater contamination. These findings provide critical insights for policymakers, stakeholders and regulatory institutions to develop effective strategies for sustainable groundwater resource management in the region.
Transboundary Komadugu-Yobe basin, located in the semi-arid to arid region of Nigeria and Niger Republic, is a vital water resource supporting domestic, agricultural, and industrial activities.
Study focus
This study investigates the pollution levels, potential sources, and human health risks associated with potentially toxic elements (PTEs) in groundwater using an integrated approach combining index-based models and chemometric analysis.
New hydrological insights for the region
The results indicate that Pb, Fe, Mn, and Cd are the key contaminants, with no significant seasonal variations. Pollution indices (Cdeg, HEI, HPI, and mHPI) classify groundwater as less polluted in upgradient areas and highly polluted in downgradient zones. Human health risk assessment (HHRA) reveals significant non-carcinogenic and carcinogenic risks (mean HI > 1 for both adults and children; mean CR > 1.0 × 10⁻³ for adults, and > 1.0 × 10⁻⁴ for children). As, Cd, Mn, and Pb are key the contributors to non-carcinogenic and carcinogenic health risks and potential risks of chronic kidney disease of unknown aetiology (CKDu). Correlation analysis suggests distinct geochemical behaviours of PTEs. Principal Component Analysis/Factor Analysis (PCA/FA) and R-mode Hierarchical Cluster Analysis (HCA) identify mixed sources, including industrial and domestic discharges as well as agricultural activities, as major contributors to groundwater contamination. These findings provide critical insights for policymakers, stakeholders and regulatory institutions to develop effective strategies for sustainable groundwater resource management in the region.
| Original language | English |
|---|---|
| Article number | 102439 |
| Journal | Journal of Hydrology Regional Studies |
| Volume | 59 |
| Early online date | 8 May 2025 |
| DOIs | |
| Publication status | Published - 1 Jun 2025 |
Funding
The research study was supported through funding from the Petroleum Technology Development Fund (PTDF) and the Scottish Government under the Climate Justice Fund Water Futures Program (research grant HN-CJF-03), awarded to the University of Strathclyde (Prof. R.M. Kalin).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- potentially toxic elements (PTEs)
- human health risk assessment
- pourbaix diagrams
- irrigation water quality index
- groundwater quality index
- chemometric analysis
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