2026-10-06T04:22:47Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34038990 2026-10-01T05:10:10Z category_26965 category_26560 category_26563 item_type_3 month_year_10_2026

Seasonal recharge forcing and hydrogeological controls on groundwater contaminant vulnerability: a process-informed spatial machine-learning framework in the Middle Benue Trough, Nigeria. Gabriel Ogbeh (24174177) Groundwater quality processes and contaminated land assessment Environmentally sustainable engineering Global and planetary environmental engineering groundwater vulnerability assessment Recharge estimation spatial cross-validation Conformal Prediction Multitask prediction explainable machine learning (XAI) <p dir="ltr">This dataset supports the study <b>“Seasonal recharge forcing and hydrogeological controls on groundwater contaminant vulnerability: a process-informed spatial machine-learning framework in the Middle Benue Trough, Nigeria.”</b> It comprises <b>600 groundwater observations from 100 monitoring locations</b> across five Local Government Areas—Awe, Doma, Keana, Lafia and Obi—sampled during six seasonal campaigns in 2024.</p><p dir="ltr">The dataset integrates groundwater hydrochemical measurements with temporally matched environmental predictors, including antecedent precipitation, soil moisture, runoff, hydrogeomorphological variables and land-cover indicators. The principal contaminants modelled are <b>Mn, Pb, Cd, Cr and As</b>. Associated modelling outputs include grouped and spatial cross-validation results, hierarchical H1–H4 predictor evaluations, explainability metrics, spatial prediction surfaces, and uncertainty-supported benchmark-exceedance products.</p><p dir="ltr">The dataset was developed to support reproducible analysis of seasonal recharge forcing, contaminant-specific groundwater vulnerability, spatial transferability and predictive uncertainty in the Middle Benue Trough.</p> 2026-10-01T05:10:10Z Dataset Dataset 10.6084/m9.figshare.34038990.v1 https://figshare.com/articles/dataset/Seasonal_recharge_forcing_and_hydrogeological_controls_on_groundwater_contaminant_vulnerability_a_process-informed_spatial_machine-learning_framework_in_the_Middle_Benue_Trough_Nigeria_/34038990 CC BY 4.0