Soil contamination with potentially toxic elements (PTEs) in the Malwa region belt of Punjab, India, can be a serious concern as a result of intensive agricultural practices and overuse of agrochemicals. The main objectives of the present study were to evaluate the spatial distribution, geochemical signature, and contamination level/health risk of PTEs in 76 soil samples (0–10 cm) collected from the three districts viz. Muktar, Faridkot, and Moga of Punjab, India. The result shows that PTEs concentrations vary widely in the region, with Fe and Mn distribution patterns being mostly coherent with each other. When compared to the Indian natural soil background values, the average concentration of Pb and Zn were higher than the limit, only Pb exceeded the average values of the world background and upper continental crust (UCC). Spatial autocorrelation plotted with a local indicator of spatial association (LISA) in GeoDa software version 1.18 was used to identify hotspots. A positive spatial autocorrelation (>0.2) was indicated with Moran’s I values for Pb, V, Mn, Cu, and Cr, being highest for Pb. A principal component analysis (PCA) identified the major geo-chemical patterns of Fe-Al-V-Cr and TOC-Mn-Zn-HCO₃⁻, which were positively loaded on PC1. This indicates that Fe/Al-oxyhydroxides and organic matter play a dominant role in controlling metal mobility in soils. This can be further substantiated with the Spearman’s rank correlation values. The contamination factor (CF) indicates that only Pb and Zn (15.7% and 3.9% samples, respectively) were under high risk. This could be due to the excessive application of chemical fertilizers. The large range of degree of contamination (C_deg) values suggests that there are variations in the degree of soil pollution due to PTEs. A little over 3.9% of samples had significant contamination, compared to 72.3% of samples with low contamination and 23.6% of samples with moderate contamination. Human non-carcinogenic and carcinogenic risk levels were investigated. The hazard index (HI) values for adult ranged from 0.00 to 0.2, and values for children ranged from 0.009 to 1.2. These findings suggest that both children and adults are not at potential risk, except in a few locations. Overall, the results of this study provide the current baseline status of toxic elements in agricultural soil. This would be helpful for developing strategies for sustainable management of the soil resources in the region, as well as for future monitoring programs of the soil quality in the Malwa region as a whole, to track any changes in the contamination levels over time.

To provide safe drinking water in contaminated hydrogeological environments, it is essential to have precise geochemical information on contamination hotspots. In this study, Geographic Information System (GIS) and multivariate statistics were utilized to analyze the spatial patterns, occurrence, and major factors controlling uranium (U) concentrations in groundwater. The global and local Moran’s I indices were utilized to detect hotspots and cool spots of U distribution. The substantial positive global Moran’s I index (at a p-value of 0.05) revealed a geographical pattern in U occurrences. The spatial clusters displayed patterns of drinking water source with U concentrations below and above the WHO limit, categorized as “regional U cool spots” and “regional U hotspots”, respectively. Spatial autocorrelation plots revealed that the high–high potential spatial patterns for U were situated in the northeastern region of the study area. As the order of queen’s contiguity increased, prospective low–high spatial patterns transitioned from the Faridkot district to the Muktsar district for U. Further, the multivariate statistical analysis methods such as correlation and principal component analysis (PCA) plots revealed substantial positive associations (p-value < 0.05) between U and total dissolved solids (TDS), salinity (SL), bicarbonate (HCO₃⁻), and sodium (Na) in groundwater from both shallow and deeper depth, indicating that these water quality parameters can significantly influence the occurrence of U in the groundwater. The output of the random forest model shows that among the groundwater parameters, TDS is the most influential variable for enrichment of U in groundwater, followed by HCO₃⁻, Na, F⁻, SO₄²⁻, Mg, Cl⁻, pH, NO₃⁻, and K concentrations. Additionally, the results of health risk assessment indicate that 47.86% and 41.3% of samples pose risks to children and adults, respectively, due to F⁻−contamination. About 93.49% and 89.14% of samples pose a risk to children and adults, respectively, due to U contamination, whereas 51.08% and 39.13% of samples pose a risk to children and adults, respectively, from NO₃⁻ contamination. The current data indicates an urgent need to create cost-effective and efficient remediation techniques for groundwater contamination in this region.