Heavy metal source identification in Shafa Badran using geographic information system and three-dimensional modelling

This study investigates heavy metal contamination in water sources in Shafa Badran, Jordan, focusing on Pb, Cd, and bromate (BrO3−). Over a 12-month period, water samples were collected monthly from 22 sites representing industrial, agricultural, residential, and urban runoff zones. The concentrations of Pb (25 μg∙dm−3), Cd (5 μg∙dm−3), and BrO3− (1.48 μg∙dm−3) exceeded World Health Organization (WHO) guidelines, indicating significant contamination risks. To identify contamination sources, principal component analysis (PCA) and factor analysis (FA) were used to reduce data complexity and reveal patterns. These methods identified strong correlations between high levels of Pb and Cd with industrial zones, while BrO3− levels were linked to urban runoff and water treatment processes. Spatial contamination patterns were mapped using inverse distance weighting (IDW), which identified contamination hotspots in industrial and agricultural zones, reinforcing statistical findings. A random forest (RF) model was applied to predict contamination levels, with cross-validation (10-fold) showing moderate accuracy for Pb and promising results for Cd and BrO3−. The RF model highlighted key predictors of contamination, such as industrial discharge and agricultural runoff. The findings emphasise the critical role of industrial discharges and agricultural runoff in heavy metal contamination in Shafa Badran’s water sources. These insights are essential for directing targeted remediation efforts and improving water quality management strategies in urbanising regions.