Mapping Lead Contamination Hotspots in Topsoil’s of the Sokoto Basin Using Regression Kriging

Usman U; Dauran N. S.; Ahijo Y. M.; Abubakar; M.

doi:10.56201/ijasmt.vol.11.no9.2025.pg88.98

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Mapping Lead Contamination Hotspots in Topsoil’s of the Sokoto Basin Using Regression Kriging

Usman U, Dauran N. S., Ahijo Y. M. and , Abubakar, M.

Abstract

Soil contamination by heavy metals poses a significant and persistent threat to ecosystem integrity, agricultural sustainability, and public health, necessitating accurate spatial assessment for effective mitigation. To address this need, this study implemented a regression kriging (RK) methodology to generate a high-resolution predictive map of lead (Pb) concentrations across the Sokoto Basin in northwestern Nigeria. A geochemical dataset comprising 103 surface soil samples, analyzed for Pb and associated elements (Al, Zn, Mn, Ti, Fe, As), served as the foundation for the model. The analytical framework involved a two-stage hybrid approach: first, stepwise multiple regression and principal component analysis were employed to identify and model the latent geochemical relationships and environmental covariates controlling the global trend of Pb distribution. Subsequently, the spatially autocorrelated residuals from this regression model were analyzed using a spherical variogram and interpolated across the study area via ordinary kriging. The integrated RK model demonstrated robust predictive capability, capturing 84.2% of the observed spatial variability in Pb concentrations (R2 = 0.842), thereby substantially outperforming standalone global regression techniques. The final contamination map delineates pronounced hotspots of elevated Pb accumulation, primarily localized within the central and northeastern sectors of the Sokoto Basin. The spatial patterning of these hotspots suggests a complex etiology, implicating both natural lithogenic weathering processes and potential anthropogenic inputs. This research underscores the practical efficacy of the regression kriging framework, which successfully synthesizes deterministic geochemical trends with stochastic local spatial variation. The resulting reliable, spatially continuous output provides a critical tool for evidence-based environmental monitoring, risk zonation, and the prioritization of targeted remediation strat

Keywords

Regression KrigingGeostatisticsVariogramHeavy MetalsSokoto BasinSoil Contamination

References

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Mapping Lead Contamination Hotspots in Topsoil’s of the Sokoto Basin Using Regression Kriging

Abstract

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