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Article

Spatial Variability and Health Implications of Heavy Metals in Wadi Al-Hamd’s Groundwater: A Multivariate and Risk-Based Approach

by
Talal Alharbi
,
Abdelbaset S. El-Sorogy
*,
Suhail S. Alhejji
and
Naji Rikan
Department of Geology and Geophysics, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
*
Author to whom correspondence should be addressed.
Water 2025, 17(17), 2549; https://doi.org/10.3390/w17172549
Submission received: 1 July 2025 / Revised: 22 August 2025 / Accepted: 25 August 2025 / Published: 28 August 2025
(This article belongs to the Special Issue Assessment of Groundwater Quality and Pollution Remediation)
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Abstract

This study comprehensively evaluates heavy metal (HM) contamination and associated health risks in 31 groundwater samples from Wadi Al-Hamd, northwest Saudi Arabia. Cd, Pb, Zn, As, Cr, Cu, Ba, and Ni showed variable concentrations, some elements approaching WHO guideline values in localized samples. The analyzed HMs showed variable concentrations, with As reaching 5.02 µg/L (50% of WHO guideline) in sample M27. The heavy metal pollution index (HPI) ranged from 0.15 (M29) to 10.07 (M27), with values below 15 indicating low pollution overall, while the metal index (MI) ranged from 0.022 (M29) to 0.621 (M27), all below the threshold of 1 for safe water, indicating geogenic enrichment, particularly in arsenic and nickel. Principal component analysis identified three PCs explaining 73.58% of total variance, with PC1 (35.50%) dominated by Zn-Cu-Ni (geogenic weathering) and PC2 (23.62%) by As-Cd (redox-driven dissolution). Health risk assessment via chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) models confirmed negligible non-carcinogenic risks (HI < 1) for both adults and children, though children exhibited 1.5–2 times higher exposure. The highest HQ values were observed for As (HQoral-child: 0.365 in M27), approaching but not exceeding safety thresholds. Dermal exposure contributed minimally (<1% of total risk). The average lifetime carcinogenic risk (LCR) due to exposure to arsenic through drinking water aligns with the US EPA’s acceptable risk range of 1 × 10−6 to 1 × 10−4 (average 1.18 × 10−5 for adults, 2.06 × 10−5 for children). These findings align with regional studies, but highlight localized As high values for few samples. The study underscores the dominance of natural weathering in HM release and provides a framework for targeted groundwater management in arid regions.

1. Introduction

Groundwater contamination by heavy metals (HMs) is a growing global concern due to its detrimental effects on human health and ecosystems [1,2]. In arid regions such as Saudi Arabia, groundwater serves as a critical resource for drinking and irrigation, making its quality paramount. HMs such as arsenic, lead, cadmium, and chromium can originate from both natural and anthropogenic sources. Geogenic processes, including weathering of basaltic and ultramafic rocks, are primary contributors to HM enrichment in groundwater, particularly in regions with complex hydrogeological settings [3]. Anthropogenic activities, such as agricultural runoff, industrial discharge, and improper waste disposal, may further exacerbate HM contamination [4,5]. Understanding the sources and distribution of HMs is essential for mitigating health risks and ensuring sustainable water management.
Exposure to HMs through contaminated groundwater poses significant health risks, particularly in vulnerable populations such as children [6]. Chronic ingestion of even low concentrations of arsenic and lead can lead to carcinogenic and non-carcinogenic effects, including neurological disorders, kidney damage, and cardiovascular diseases [7,8]. The non-carcinogenic risks are typically assessed using chronic daily intake (CDI), hazard quotients (HQ), and hazard indices (HI), while carcinogenic risks are evaluated through cancer risk (CR) and lifetime cancer risk (LCR) models [9]. To assess HM contamination, researchers employ a combination of contamination indices and multivariate statistical tools. Indices such as the heavy metal pollution index (HPI) and metal index (MI) provide aggregated measures of water quality [10,11,12], while multivariate techniques such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) help identify pollution sources and spatial patterns [13,14]. GIS facilitates the integration of spatial and temporal datasets to produce distribution maps of HM concentrations and associated risks, enabling more targeted mitigation and policy interventions. Remote sensing, through satellite-based land use and land cover mapping, supports the identification of pollution sources and their correlation with land management practices [15].
In Saudi Arabia, the last-mentioned methods have been applied to evaluate groundwater quality in regions such as Al-Kharj, Yanbu, and Jazan, revealing geogenic dominance in HM distribution [16,17,18,19]. Integrating these approaches can provide a holistic understanding of contamination dynamics and guide targeted mitigation strategies. The hydrogeological and hydrochemical characteristics of groundwater in the Wadi Al-Hamd Basin were examined for suitability in agricultural irrigation [20]. The groundwater exists in unconfined aquifers in alluvial deposits and moves from southeast and northwest to west and south, respectively. The study concluded that the water levels have been dropping and groundwater quality deteriorated due to the intensive exploitation of groundwater. Moreover, the study attributed the different water types and salinity behaviors to the rock-forming minerals in the Wadi Al-Hamd Basin and the groundwater–rock interaction and reverse ion-exchange processes. El-Sorogy et al. [21] defined the groundwater potential zones (GWPZ) in Wadi Al-Hamd Basin, utilizing remote sensing and geographic information system (GIS) techniques alongside meteorological data. Seven thematic maps were produced based on the regulatory characteristics of geology, drainage density, height, slope, precipitation, soil, and normalized difference vegetation index (NDVI). The groundwater potentials were classified into very poor, moderate, and good zones.
The objectives of this study are as follows: (i) evaluate the spatial distribution of HMs in Wadi Al-Hamd’s groundwater using contamination indices (HPI, MI); (ii) identify pollution sources and pathways through principal component analysis and the correlation matrix; (iii) assess non-carcinogenic and carcinogenic health risks for adults and children using CDI, HQ, HI, CR, and LCR models; and (iv) compare the results with regional and global benchmarks to inform water management policies. By addressing these objectives, this study aims to fill critical knowledge gaps and provide actionable insights for safeguarding groundwater resources in Wadi Al-Hamd and similar arid regions.

2. Materials and Methods

2.1. Study Area

The Wadi Al-Hamd Basin is recognized as one of the largest basins in the Kingdom of Saudi Arabia, with a total area of 104,679 square kilometers (Figure 1). It flows in a southeastern to northwestern direction, dividing into two primary valleys. One of these valleys, called Wadi Al-Hamd, continues to flow northwest towards the Red Sea. The other valley, known as Wadi Al Jazl, travels north towards the city of Al Ula [20]. The primary economic activity in this basin is agriculture, which heavily relies on unlicensed and uncontrolled groundwater wells, primarily drilled wells. The Wadi Al-Hamd Basin experiences an annual rainfall distribution ranging from 40 mm to 80 mm, with an increasing trend from the northwest to the southeast. The majority of precipitation occurs in November, December, and January, with intermittent rainstorms occurring in April [21]. The Wadi Al-Hamd Basin is distinguished by the existence of two formations that contain groundwater. The Quaternary aquifer is located in the ancient basins, while the volcanic aquifer covers the southern part of Al-Madinah Al-Munawarah city [20,21]. The groundwater level is comprised between 535 and 594 m, whereas the water table depth varies between 28 and 93 m [22,23].
Figure 2 presents a digital elevation model (DEM) and geological map of the Wadi Al-Hamd Basin, illustrating the area’s topographical variation and lithological heterogeneity, both of which are critical in influencing groundwater flow, recharge, and geochemical interactions. The DEM reveals that elevations range from approximately 487 to 1524 m, descending from mountainous highlands in the north and south areas toward lower elevations where the Wadi Al-Hamd flows, consistent with a downstream gradient from southeast to northwest that governs surface runoff and potential pollutant transport pathways. This gradient aligns with the general hydrological direction of the stream, supporting sediment mobilization from upstream sources. The geological map underscores this complexity by highlighting a diverse bedrock composition ranging from Quaternary deposits and volcanic rocks in the upper stream region (sites 1–14) to tertiary basalts and intrusive and sedimentary rocks in the downstream basin (sites 19–31).

2.2. Sampling and HM Analysis

In March 2024, thirty-one groundwater samples were collected from various locations characterized by intensive agricultural activities within the Wadi Al-Hamd Basin (Figure 1). Prior to sample collection, 500 mL polyethylene bottles were thoroughly cleaned with distilled water and subsequently rinsed three times with the local groundwater to prevent cross-contamination. The collected samples were then transported in insulated coolers that maintained a constant temperature of 4 °C. Concentrations of As, Cd, Cr, Cu, Ni, Pb, Ba, and Zn were measured using a ThermoFisher Scientific iCAP-RQ inductively coupled plasma mass spectrometer (ICP-MS) at the W.M. Keck Collaboratory for Plasma Spectrometry at Oregon State University (OSU), Corvallis, OR, USA. Groundwater samples were first filtered using 0.45 μm filter paper and then acidified with 0.5% nitric acid.
Prior to analysis, a calibration curve was established using a 22-element mixed standard solution prepared from certified single-element standards and high-purity reagents. The calibration included six points, ranging from a blank to a tenfold dilution, to ensure accurate quantification across a wide concentration range. All samples and standards were spiked with a 0.5 ppb mixed rhodium/iridium (Rh/Ir) internal standard to correct for matrix effects. Analytes were measured in both kinetic energy discrimination reaction (KEDR) and standard (STDR) modes to reduce spectral interferences. Samples were diluted tenfold prior to analysis to ensure analyte concentrations remained within the instrument’s optimal detection range.
To maintain analytical reliability, a rigorous quality assurance/quality control (QA/QC) protocol was followed. Certified reference materials (CRMs), field blanks, and method blanks were included in each analytical batch. The recovery rates for all target elements in the CRMs ranged between 90% and 110%, indicating satisfactory analytical accuracy. Duplicate samples were analyzed at a frequency of 10% and showed relative percent differences (RPDs) below 5%, confirming precision. Instrument performance was verified using ongoing calibration verification (OCV) standards analyzed every 10 samples, and calibration drift was corrected whenever necessary. Quality control samples (including blanks, spikes, and duplicates) were analyzed after every 20 unknown samples to ensure consistent performance.

2.3. Multivariate and Contamination Assessment

To evaluate the relationships among HMs and reduce the dataset, Pearson correlation coefficients and principal component analysis were employed. The spatial distribution of HMs, along with the digital elevation model (DEM), was mapped using geographic information system (GIS) tools and contouring techniques in ArcGIS 10.6. Descriptive statistics for each parameter were analyzed using IBM SPSS Statistics 25. To assess pollution levels and the impact of various HMs on groundwater quality, the heavy metal pollution index (HPI) and metal index (MI) were applied following methodologies [10,11,12]. Appraisal scores were calculated using a weighted arithmetic mean to evaluate groundwater contamination levels [24]. In this analysis, weights ranging from 0 to 1 were assigned based on each metal’s relative significance in drinking water quality. Table S1 outlines the standard permissible limits (Si) and ideal values (Ii) as defined by the World Health Organization [25]. HPI values were calculated according to Equations (1)–(3) as follows:
HPI = (Σ (Wi × Qi))/ΣWi
Wi = 1/Si
Qi = ((Mi − Ii)/(Si − Ii)) × 100
where “Qi” is the i-th parameter’s sub-index and “Wi” is the i-th parameter’s unit weight. “Si” is the WHO-established standard permissible value, “Mi” is the monitored value of the heavy metal, and “Ii” is the ideal value. However, Table 1 presents the classification of the indices applied in this study.
MI = Σ (Ci/MACi)
where “Ci” is the measured concentration of the i-th parameter, “MACi” is the maximum permitted value for each metal (Table S1), and “i” is the i-th sample.
The human health risk assessment for HMs in tap water was conducted using the US EPA model [26]. This assessment involves estimating the chronic daily intake of individuals to HMs per kilogram of body weight per day through direct ingestion (CDIi) and dermal absorption (CDId) for adults and children using Equations (5) and (6). Table 2 summarizes the parameter values and assumptions used for these calculations.
CDIi = (C × IR × EF × ED)/(BW × AT)
CDId = (C × SA × Kp × ET × EF × ED × CF)/(BW × AT)
The exposure frequency (EF) was adjusted to better reflect local water usage patterns. While the original model assumed 365 days/year, field observations suggest that residents may not exclusively rely on Wadi Al-Hamd for daily water needs. Thus, an EF of 182 days/year was adopted for ingestion exposure, assuming approximately six months of reliance per year, while dermal exposure EF was reduced to 104 days/year, accounting for biweekly ablution or recreational contact. Similarly, the exposed skin area (SA) was revised from full-body values to partial-body estimates, representing face, hands, and feet typically involved in contact during ablution or incidental use. Estimated SA was 5700 cm2 for adults and 1300 cm2 for children, in line with USEPA guidelines for partial-body contact scenarios.
Equations (7) and (8) present the hazard quotient through ingestion “HQi” and the hazard quotient through dermal absorption “HQd”. Using Equation (9), the total non-carcinogenic risk of a single HM is calculated and displayed as a hazard index (HI) for the two exposure routes.
HQi = CDIi/RfDi
HQd = CDId/RfDd
HI = HQi + HQd
where “RfDi” and “RfDd” are the ingestion and dermal reference doses (mg/kg/day), respectively (Table 3).
To estimate the probability of an individual developing cancer over a lifetime due to exposure to potential carcinogenic HMs, carcinogenic risks (CRs) were calculated using Equations (10) and (11). This assessment was based on established methods recommended by US EPA [26,29].
CRi = CDIi × CSF
CRd = CDId × CSF
where CSF is the carcinogenic slope factor, a toxicity value that describes the association between dose and response. CSF (mg/kg/day) values are as follows: As = 1.5; Cr = 41; and Cd = 6.1 [28]. The lifetime carcinogenic risk (LCR) was subsequently determined by summing the individual CR for each hazardous metal, as described in Equation (12):
LCR = Cri + CRd.

3. Results and Discussion

3.1. HM Concentration and Distribution

The analyzed groundwater samples present in Table S2 exhibit significant variability in HM concentrations. Table 4 indicates the statistical results of HMs in groundwater samples and their comparison with WHO guidelines [25], USEPA MCL [30], and Saudi standards [31]. Arsenic shows notable contamination, with concentrations ranging from 0.02 µg/L (M29) to 5.02 µg/L (M27), averaging 1.46 µg/L. The maximum As level remains below the WHO guideline (10 µg/L), USEPA MCL (10 µg/L), and arsenic levels from Pakistan’s Thar Desert (32–1900 μg/L) [32]. Cr levels range from 0.21 µg/L (M29) to 4.98 µg/L (M20), with an average of 2.11 µg/L, well below WHO (50 µg/L), USEPA (100 µg/L) limits, and Cr levels from the Oued Souf Valley in Algeria (0–23 µg/L) [33]. Cd concentrations (0.0035–0.0849 µg/L) and Pb (0.0019–0.4058 µg/L) generally comply with WHO (3 µg/L for Cd, 10 µg/L for Pb) and USEPA (5 µg/L for Cd, 15 µg/L for Pb) standards. Zn concentrations vary widely (0.10–14.17 µg/L), with M31 (14.17 µg/L) standing out, though still far below WHO (3000 µg/L), USEPA (5000 µg/L), Saudi standards (20 µg/L) thresholds, and the levels reported from Southern Italy and Morocco (0.85–786.2 and 64.5–104.5 μg/L) [34,35]. Ni ranges from 0.09 µg/L (M4) to 2.01 µg/L (M27, M30), averaging 0.58 µg/L, which is within WHO (70 µg/L), Saudi standards (20 µg/L) limits, and the groundwater from Oued Souf Valley in Algeria (0–24 µg/L) [33]. Cu levels vary from 0.04 µg/L in M6 to 3.47 µg/L in M29 and are well below all regulatory limits and the levels reported from Morocco (12.5–32.5 µg/L) [35].
Barium concentrations (3.02–59.98 µg/L) are significantly lower than WHO (700 µg/L), USEPA (2000 µg/L), and Saudi (1000 µg/L) standards, posing minimal health risks. However, the wide range and standard deviation (12.63) reflect geological variability, with higher values potentially linked to natural mineral dissolution [36]. Cd levels are uniformly low (avg. 0.0346 µg/L), but the maximum (0.0849 µg/L in M27) approaches 17% of the WHO limit, necessitating vigilance given Cd’s bioaccumulative toxicity [37]. However, the maximum Cd level remains below the levels reported from Southern Italy (0.53–6.2 μg/L) [34]. The near-normal distribution (skewness 0.954) suggests diffuse sources, such as fertilizers or atmospheric deposition, rather than point source pollution. Statistical analysis reveals right-skewed distributions for Pb (skewness 4.281), Ni (2.584), and Cu (2.467), indicating contamination hotspots, likely from agricultural activities.
The spatial distribution map of HMs (Figure 3) reveals significant variations in concentrations across different sites, with notable localized hotspots. Cd levels peak centrally (around sites 15–18), while Pb displays a marked increase in the northwestern corner (sites 30–31) and southeastern edge (sites 1–4), likely associated with surface water interactions. Zn exhibits a strong gradient, with the highest concentrations again in the northwestern area and a secondary hotspot in the southeast, following a west-to-east decreasing trend along the central transect. As and Cr show elevated values primarily around sites 25–28 and sites 1–5 in both upstream and downstream zones. Cu shows a similar dual-peak pattern, with hotspots near the northernmost and southernmost sample points. Ba, with its highest recorded value among the metals, shows spatial peaks in both the central-south (around site 12) and southeastern (sites 1–4) areas, suggesting multiple input sources. Ni concentrations are relatively low in the center of the region but increase near both extremities, particularly in the northwestern (sites 29–31) and southeastern corners.

3.2. Assessment of Groundwater Contamination

3.2.1. Heavy Metal Pollution Index (HPI)

The HPI was calculated to assess the cumulative contamination risk posed by HMs. The present HPI values (Table S2) ranged from 0.15 (M29) to 10.07 (M27), revealing spatial variability in HM contamination levels. These results are interpreted below within the context of established HPI classification schemes [10,38]. All samples in Wadi Al-Hamd fall within the “low pollution” category (HPI < 15), indicating that the groundwater is generally safe with respect to HM concentrations. However, the spatial variability in HPI values suggests localized influences that warrant further attention. Samples such as M6, M22, M29, and M31 exhibit minimal HM contamination, with HPI values close to 0. Such low indices are typical of pristine groundwater influenced primarily by natural weathering processes [17,39]. The low HPI correlates with samples having undetectable or trace levels of toxic metals such as Cd and Pb. The majority of samples fall into 2 ≤ HPI < 5, reflecting slight but non-hazardous HM enrichment. For instance, M13 and M23 show elevated As and Cr, likely from natural mineral dissolution [7]. Samples M10 and M16 have higher Zn and Cu, potentially linked to minor anthropogenic inputs, e.g., irrigation return flow [40]. Elevated Cd and As in M14 and M15 suggest proximity to natural mineralized zones or minor anthropogenic disturbances. Additionally, the highest HPI in M27 (HPI: 10.07) is driven by elevated As (5.02 µg/L), Cu (3.47 µg/L), and Ni (2.01 µg/L), possibly due to a combination of geogenic leaching and historical agricultural practices [2]. The HPI results align with groundwater studies in arid regions, where low to moderate HPI values dominate due to limited industrial activity and dilution effects [39]. Comparable results were reported in arid areas of Italy (HPI range: 0.002–14.3) [34] and Southwest China (HPI: 1.43–66.28) [41], indicating a consistent geogenic influence in HM signatures across desert aquifers. The spatial distribution map of HPI (Figure 4) reveals significant variations in concentrations across the study area, with higher values in M27, M15, and M14, while the lowest values were recorded in M6 in the southeastern corner and M29-M31 in the northwestern corner of the study area.

3.2.2. Metal Index (MI)

The MI was calculated to evaluate the cumulative impact of HM contamination in groundwater samples. The MI values (Table S2) ranged from 0.022 (M29) to 0.621 (M27), providing insights into the overall water quality and potential risks associated with HM exposure. All samples from Wadi Al-Hamd fall within the low contamination category (MI < 1), indicating that the groundwater is generally safe for drinking and irrigation [13,42]. However, the variability in MI values highlights spatial differences in HM distribution, with some samples approaching the upper limit of the low contamination range. Samples such as M6, M29, and M31 showed MI < 0.1, and these samples exhibit minimal HM contamination, with MI values as low as 0.022 (M29). Such low indices are characteristic of groundwater influenced primarily by natural weathering processes, with negligible anthropogenic input [16,20,39]. For instance, M29 and M31 show undetectable or trace levels of toxic metals such as As and Cd, aligning with pristine conditions [5].
The majority of samples fall into the range of 0.1 ≤ MI < 0.5, such as M1–M25, M28, and M30, reflecting slight but non-hazardous HM enrichment. Notable examples include M13 (MI: 0.293) and M23 (MI: 0.282): elevated contributions from As and Cr, likely due to natural dissolution of minerals such as sulfides or chromite [7]. M14 (MI: 0.378) and M15 (MI: 0.326): higher As and Cd levels, possibly linked to localized geogenic anomalies or minor agricultural runoff. M27 (MI: 0.621) stands out as the most contaminated sample, driven by significantly higher As (0.502) and Ni (0.029). This outlier suggests a geogenic hotspot where natural mineral dissolution (e.g., arsenic-rich sulfides) is pronounced [17]. However, it may also suggest potential historical anthropogenic activity, such as pesticide use, though the absence of nearby sources favors a natural origin [43]. These values remain below the findings from the northwestern desert of Egypt (MI: 6.5–462) [44] and Mnasra Region, Morocco (MI: 3.34–12.17) [27]. MI shows a distribution pattern similar to HPI with the lowest values in M6 in the southeastern corner and M29-M31 in the northwestern corner of the study area, while the higher values are in M27, M15, and M14 (Figure 5).

3.3. Multivariate Tools

The Pearson correlation matrix reveals significant relationships between HMs in the groundwater, providing insights into their potential sources and geochemical behavior. The strong positive correlation between Zn and Cu (r = 0.512, p < 0.01) likely reflects their co-occurrence (Table 5). This linkage is consistent with findings in urbanized aquifers, where Zn-Cu pairs often indicate anthropogenic contamination [45]. The strong positive correlation between Ba and Cr (r = 0.541, p < 0.01) may arise from natural processes, such as the dissolution of barite (BaSO4) and chromite (FeCr2O4) in aquifer rocks [46]. The absence of nearby industrial sources supports a geogenic explanation. This moderate positive correlation between As and Cd (r = 0.455, p < 0.05) suggests a possible common origin for As and Cd, such as weathering of sulfide minerals or anthropogenic activities such as agricultural runoff (e.g., phosphate fertilizers) [7]. Similar correlations have been reported in groundwater systems with mixed geogenic and anthropogenic influences [2].
The strong inverse relationship between Zn and Ba (r = −0.591, p < 0.01) suggests competitive adsorption or dilution effects, where high Zn concentrations coincide with low Ba levels, possibly due to differences in mobility or solubility [2]. Such patterns are documented in aquifers with redox-controlled HM partitioning [7]. Moreover, the negative correlation between Cr and Ni (r = −0.473, p < 0.01) could reflect divergent geochemical pathways, Cr often persists in oxidized forms (Cr6+), while Ni is more mobile under reducing conditions [47]. The inverse trend aligns with studies of ultramafic rock weathering [48]. Pb showed no significant correlations except a weak positive link with Cu (r = 0.364, p < 0.05), hinting at minor shared sources (e.g., pipe corrosion). Its isolation in the matrix suggests diffuse or historic contamination [48]. The lack of correlation between Cd and Ni (r = −0.014) implies independent origins, with Cd potentially linked to agricultural inputs and Ni to natural rock weathering [49].
Principal component analysis (PCA) was conducted to identify the underlying sources and processes influencing HM distribution in the investigated groundwater samples. The analysis extracted three PCs that together explain 73.58% of the total variance (Table 6). PC1 accounts for 35.50% of the variance and shows strong positive loadings for Zn (0.795) and Cu (0.791), and moderate loadings for Ni (0.627). In comparison with HM patterns observed in other arid regions, Zn-Cu-Ni associations are commonly associated with natural weathering of mafic rocks in basaltic aquifers [50,51]. Negative loadings for Cr (−0.734) and Ba (−0.636) suggest these elements behave inversely to Zn/Cu, which is likely due to differences in solubility (Cr6+ is mobile in oxidizing conditions, while Ba precipitates as barite) [7]. This dichotomy highlights the aquifer’s redox heterogeneity.
PC2 explains 23.62% of the variance and is heavily loaded with As (0.891) and moderately with Cd (0.571) and Ni (0.528). This suggests a geogenic origin from natural rock–water interactions linked to arsenic-rich minerals (e.g., sulfides or Fe-oxyhydroxides) dissolving under reducing conditions [52]. The weak negative loading for Zn (−0.413) implies that Zn is less associated with this As-rich phase, possibly due to its adsorption onto clay minerals [53]. PC3 (14.46% variance) is marked by high loadings for Pb (0.550) and Ba (0.495), with negative loadings for Cd (−0.544). This may reflect legacy contamination [54]. The inverse Cd-Pb relationship could indicate differing transport mechanisms (e.g., Cd mobility in acidic vs. Pb adsorption to colloids) [7].

3.4. Health Risk Assessment

3.4.1. Chronic Daily Intake (CDI)

Humans are more susceptible to both non-carcinogenic and cancer-causing illnesses when they drink water tainted with harmful metals [27,55]. The CDI values for HMs via oral ingestion in Wadi Al-Hamd’s groundwater were calculated for both adults and children, revealing minimal health risks across all samples (Table S3). The CDI values for individual metals were consistently below established reference doses (RfDs) [2,6], indicating negligible non-carcinogenic risk from long-term consumption. For example, the highest CDI for As (M27: 6.44 × 10−5 mg/kg/day for adults, 1.10 × 10−4 mg/kg/day for children) remained well below the U.S. EPA RfD of 3.00 × 10−4 mg/kg/day, suggesting no immediate health concern [56,57]. Similarly, Pb and Cd exposures were orders of magnitude lower than their respective thresholds [8], reinforcing the overall safety of the groundwater for drinking. However, children exhibited higher CDI values than adults (approximately 1.5–2 times greater), reflecting their lower body weight and higher water intake relative to mass (Table 7). This trend aligns with global studies on HM exposure in arid regions, where children are more vulnerable to metal bioaccumulation [58]. Notably, M27 showed the highest CDI for As and Ni, which is likely due to geogenic leaching from arsenic-rich minerals, as observed in similar basaltic aquifers [59]. Despite this outlier, all samples posed low chronic exposure risks, supporting the groundwater’s suitability for consumption under WHO standards [2].
The CDI values from the dermal pathway for HMs reveal negligible health risks across all samples (Table S4). The CDI values for Ni, Cu, Zn, As, Cd, Pb, Cr, and Ba were orders of magnitude lower than the U.S. EPA and WHO reference doses (RfDs) for dermal exposure, indicating minimal non-carcinogenic risk from skin contact. For instance, the highest dermal CDI for As (M27: 7.49 × 10−8 mg/kg/day for adults, 1.88 × 10−7 mg/kg/day for children) was significantly below the U.S. EPA RfD of 3 × 10−4 mg/kg/day for dermal arsenic exposure. Similarly, Pb and Cd exposures were extremely low (<10−10–10−12 mg/kg/day), reinforcing that dermal absorption of HMs from this groundwater poses no significant health threat [6]. Children exhibited slightly higher CDI dermal values than adults (1.5–2 times greater), consistent with their higher skin surface area-to-body weight ratio and greater susceptibility to contaminant absorption [60,61]. Notably, M27 again emerged as the sample with the highest dermal CDI for As and Cu, though still well below hazardous levels. This aligns with geogenic enrichment patterns observed in oral CDI results, suggesting that even the most contaminated sample in Wadi Al-Hamd does not pose a dermal exposure risk. The uniformly low dermal CDI values reflect the limited bioavailability of HMs in groundwater during transient skin contact, as documented in arid region studies [62].

3.4.2. Hazard Quotient (HQ) and Hazard Index (HI)

The HQ and HI values for HMs in Wadi Al-Hamd’s groundwater were calculated to assess non-carcinogenic risks for both adults and children via oral and dermal exposure pathways (Table S5 and Table 7). The results indicate that all HQ values for individual metals are significantly below 1, the threshold for potential health risks [6]. For example, the highest HQ values were observed for As in sample M27 (HQoral-adult: 0.215, HQoral-child: 0.365), and they still remain below the safety limit of 1. Similarly, Pb and Cd exhibited negligible HQs (<0.01), reinforcing the absence of acute toxicity risks [2]. Notably, children exhibited higher HQ and HI values than adults (1.5–2 times greater), reflecting their higher ingestion rates and lower body weight, a trend consistent with global risk assessments. The dominance of As and Ni in contributing to HI aligns with geogenic sources, such as weathering of arsenic-rich minerals in the region’s basaltic aquifers [44].
When compared to global benchmarks, Wadi Al-Hamd’s HI values are orders of magnitude lower than those reported in industrially contaminated areas [13]. For instance, the highest HI in M27 (0.367 for children) is far below the threshold of 1, whereas studies in Bangladesh and India report HI > 10 for As-endemic regions [7]. The dermal pathway contributed minimally to HI (<1% of oral risks), as HM absorption through skin is limited [6]. However, the elevated As in M27 suggests localized geogenic enrichment [2]. Overall, the groundwater complies with SASO and WHO standards [2,31].
The spatial distribution of HI values across groundwater sampling sites for Ni, Cu, Zn, and As in adults and children (Figure 6) reveal a clear spatial trend generally increasing from southeast to northwest across most metals. Among the metals, As exhibits the highest HI values, with significantly elevated levels particularly in the central and northwestern parts of the study area, and Ni also shows higher HI values in the northern region compared to the southern sites, with children again more affected than adults, suggesting localized sources of Ni likely influenced by geological inputs in that area. Cu and Zn show comparatively lower HI values, yet they follow a similar spatial trend with slightly higher values concentrated in the northwestern and southeastern corners, particularly near sites 2–5 and 29–31. The spatial distribution maps of (HI) for Cd, Pb, Cr, and Ba (Figure 7) reveal clear spatial patterns with notably higher HI values consistently recorded for children. Cd exhibits elevated HI values, particularly in the southeastern part of the region (around sites 1–5 and 11–13). Pb shows its highest HI values concentrated in the northwestern and southeastern extremities, especially near sites 2–5 and 29–31. This suggests that Pb contamination is likely influenced by upstream and downstream sources, with children’s HI surpassing adults. Cr presents a pronounced increase in HI values both in the far northwestern (sites 28–31) and southeastern (sites 1–5, 11–13) zones, forming two distinct clusters of elevated value, with children’s HI being high compared to adults. Finally, Ba also follows a similar trend, with three prominent zones: the northwestern cluster (around sites 28–31), central-eastern (sites 10–14), and southeastern (sites 1–5).

3.4.3. Carcinogenic Risk (CR) and Lifetime Carcinogenic Risk (LCR)

The results of the CR and LCR assessments for HMs in groundwater samples for both adults and children via oral and dermal exposure pathways are present in Table S6 and Table 8. As exhibits the highest carcinogenic values, with oral CR values for adults ranging from 1.28 × 10−5 (M1) to 9.66 × 10−5 (M27), while children face even higher risks (2.18 × 10−5 to 0.00016). These values exceed the USEPA’s acceptable risk threshold of 1 × 10−6. These findings are less than those that have been reported in India (CR: 10−4 to 10−3) [63]. Cd and Cr showed values lower than As, with adult oral CR values for Cd ranging from 1.48 × 10−6 (M2) to 5.45 × 10−6 (M15) and for Cr from 1.23 × 10−5 (M1) to 3.19 × 10−5 (M20). The dermal pathway, while less significant than oral exposure, still contributes to cumulative risk, particularly for Cr, where dermal CR values reach up to 6.09 × 10−6 (M20). These findings align with previous studies in groundwater, with children being more vulnerable due to higher ingestion rates and lower body weight [36,64].
The LCR values, which combine oral and dermal exposure, further emphasize the elevated risks, particularly for children (Table S6). For instance, As LCR in children peaks at 0.00016 (M27), nearly double the adult value (9.68 × 10−5), underscoring the heightened susceptibility of younger populations. Pb shows relatively lower CR values (oral CR: 1.23 × 10−8 to 2.60 × 10−6), but its neurotoxic effects at low doses remain a concern, especially for children [25,65]. The variability in CR across samples suggests localized contamination, possibly from agricultural sources [66,67,68].
The spatial distribution of LCR values across the study area (Figure 8) reveals distinct geographic trends in carcinogenic view. The highest LCR values for As (9.68 × 10−5 for adults, 1.60 × 10−4 for children) are clustered in the northwestern sector near the volcanic rock formations, gradually decreasing by 72–85% toward the southeastern alluvial plains. Cr exhibits a more localized distribution, with peak values (3.80 × 10−5 adults, 6.96 × 10−5 children) concentrated in central samples, decreasing radially by 60–68% toward peripheral areas. Cd demonstrates an inverse pattern to As, with slightly elevated values (6.65 × 10−6 adults, 1.13 × 10−5 children) appearing in southeastern agricultural zones before decreasing northwestward by 55–60%. Pb shows the most uniform distribution, with minimal variation (2.60 × 10−6 to 4.43 × 10−6) across all sites. Notably, the western flank displays a 40–50% higher LCR burden overall compared to eastern samples, correlating with the region’s hydrogeological divide. These spatial trends strongly reflect the area’s underlying geology, where northwest volcanic units contribute to As/Cr enrichment.

4. Conclusions

This study systematically assessed heavy metal (HM) contamination and associated health risks in Wadi Al-Hamd’s groundwater, revealing that while most concentrations were below WHO limits, localized elevations, such as As in M27 (5.02 µg/L) and Zn in M31 (14.17 µg/L) were attributed to geogenic processes such as sulfide mineral dissolution and ultramafic rock weathering. Risk indices (HPI and MI) and multivariate analyses confirmed natural dominance in HM sources, with limited anthropogenic input. Although non-carcinogenic risks were generally low (HI < 1), children exhibited higher exposure levels (HQoral-child up to 0.365 for As). The dermal exposure route was negligible. The spatial patterns of LCR are closely linked to the area’s geological characteristics, with arsenic and chromium enrichment likely originating from volcanic formations in the northwest. Based on these findings, several measures are recommended to improve water quality and minimize risks: regular monitoring of As and Ni, especially in high-HPI areas; community education on groundwater safety; and isotopic tracing to differentiate geogenic from potential anthropogenic inputs. Additionally, local groundwater management strategies should be developed in collaboration with regulatory bodies to safeguard water sources.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17172549/s1, Table S1: The WHO (2017) guidelines of HMs and weight scores; Table S2: Concentration of HMs (µg/L), results of MI and HPI, and the analytical limits; Table S3: The chronic daily intake values (CDI) for HMs in adults and children via oral ingestion in Wadi Al-Hamd’s groundwater; Table S4: The chronic daily intake values (CDI) for HMs in adults and children via dermal contact in Wadi Al-Hamd’s groundwater; Table S5: Results of HI for HMs in the investigated groundwater samples; Table S6: Results of LCR for As, Cr, Pb, and Cd per sample location in the study area.

Author Contributions

Conceptualization, T.A. and A.S.E.-S.; methodology, T.A., A.S.E.-S., S.S.A. and N.R.; software, N.R.; validation T.A. and A.S.E.-S.; writing—original draft preparation, T.A., A.S.E.-S., S.S.A. and N.R.; writing—review and editing, T.A., A.S.E.-S., S.S.A. and N.R.; supervision, T.A.; project administration, T.A.; funding acquisition, T.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Ongoing Research Funding program, (ORF-2025-791), King Saud University, Riyadh, Saudi Arabia.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors extend their appreciation to Ongoing Research Funding program, (ORF-2025-791), King Saud University, Riyadh, Saudi Arabia.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location map of the study area.
Figure 1. Location map of the study area.
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Figure 2. Digital elevation model and the geologic map of the study area.
Figure 2. Digital elevation model and the geologic map of the study area.
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Figure 3. Spatial distribution of HMs per sample locations in Wadi Al-Hamd groundwater.
Figure 3. Spatial distribution of HMs per sample locations in Wadi Al-Hamd groundwater.
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Figure 4. Spatial distribution of HPI per sampled location.
Figure 4. Spatial distribution of HPI per sampled location.
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Figure 5. Spatial distribution of MI per sampled location.
Figure 5. Spatial distribution of MI per sampled location.
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Figure 6. Spatial distribution of HI per sample locations for Ni, Cu, Zn, and As in Wadi Al-Hamd groundwater.
Figure 6. Spatial distribution of HI per sample locations for Ni, Cu, Zn, and As in Wadi Al-Hamd groundwater.
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Figure 7. Spatial distribution of HI per sample locations for Cd, Pb, Cr, and Ba in Wadi Al-Hamd groundwater.
Figure 7. Spatial distribution of HI per sample locations for Cd, Pb, Cr, and Ba in Wadi Al-Hamd groundwater.
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Figure 8. Spatial distribution of LCR per sample locations for Cd, As, Pb, and Cr in Wadi Al-Hamd groundwater.
Figure 8. Spatial distribution of LCR per sample locations for Cd, As, Pb, and Cr in Wadi Al-Hamd groundwater.
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Table 1. Classification of the indices applied in this study [10,11,12,26,27,28].
Table 1. Classification of the indices applied in this study [10,11,12,26,27,28].
Indices ValuesClassification
HPI<15Low water pollution
15 < HPI < 30Medium water pollution
>30High water pollution
MI<0.3Very pure
0.3 < MI < 1Pure
1 < MI < 2Slightly affected
2 < MI < 4Moderately affected
4 < MI < 6Strongly affected
>6Seriously affected
HIHI < 1Low detrimental impact on human health
HI > 1Greater chances of harmful health effects
LCR<10−6Negligible carcinogenic risk
between 10−6 and 10−4Acceptable or tolerable risk
>10−4Significant potential for adverse health effects
Table 2. Parameters and input assumptions for exposure assessment of metals through ingestion and dermal pathways [26,27,28].
Table 2. Parameters and input assumptions for exposure assessment of metals through ingestion and dermal pathways [26,27,28].
ParameterUnitValues
IngestionDermal Adsorption
Heavy metal concentration (C)mg/L--
Water ingestion rate (IR)L/Day1.8 for children and 0.7 for adults-
Exposure frequency (EF)Day/years182 (assumes partial-year consumption of Wadi water)104 (dermal contact due to ablution/bathing)
Exposure duration (ED)Year30 for adults and 6 for children 30 for adults and 6 for children
Average body weight (BW) Kg70 for adults and 16 for children 70 for adults and 16 for children
Average time (AT)DaysED × 365ED × 365
Exposed skin area (SA)cm2-5700 for adults and 1300 for children (face, hands, and feet)
Dermal permeability coefficient (Kp)cm/h-Pb 0.0001, As, Cd, Cu, Cr, 0.002, Zn 0.0006, Ni 0.0002, and Ba 0.00004
Exposure time (ET)h/event-1 h/day for children and 0.58 h/day for adult
Conversion factor (CF)L/cm3-0.001
Table 3. Reference dose (RfD) and cancer slope factor (CSF) for different metals [26,27,28].
Table 3. Reference dose (RfD) and cancer slope factor (CSF) for different metals [26,27,28].
Element RfDiRfDd
Pb 0.00140.3
Cr 0.0030.025
Zn 0.30.2
Cu 0.040.3
Ba 0.20.04
Ni 0.020.04
As0.00030.00012
Cd0.00050.000025
Table 4. Statistical results of HMs in groundwater samples.
Table 4. Statistical results of HMs in groundwater samples.
MetalMin (µg/L)Max (µg/L)Average (µg/L)St. Dev.SkewnessKurtosisWHO [25]USEPA [30]Saudi Arabia [31]
Cr0.214.982.111.4307970.360−1.0855010037
Cu0.043.470.680.7321252.4677.218200013001500
Zn0.1014.172.183.0897743.0629.6463000500020
Ni0.092.010.580.4326072.5847.35570-20
As0.025.021.460.9455731.7456.31510107.5
Ba3.0259.9829.2812.6256350.1061.15170020001000
Cd0.00350.08490.03460.0179810.9541.056353
Pb0.00190.40580.03860.07864114.28119.23310157.5
Table 5. The correlation matrix of the analyzed HMs.
Table 5. The correlation matrix of the analyzed HMs.
CdPbZnAsCrCuBaNi
Cd1
Pb−0.0431
Zn−0.389 *0.0551
As0.455 *0.122−0.3431
Cr0.048−0.134−0.458 **−0.1591
Cu−0.3170.364*0.512 **0.289−0.3521
Ba0.1350.019−0.591 **0.1680.541 **−0.3101
Ni−0.0140.2530.3140.376 *−0.473 **0.549 **−0.0321
Note: *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (two-tailed).
Table 6. Principal component loadings and the four extracted PCs with varimax normalized rotation.
Table 6. Principal component loadings and the four extracted PCs with varimax normalized rotation.
Component
PC1PC2PC3
Cd−0.3740.571−0.544
Pb0.3240.3460.550
Zn0.795−0.413−0.053
As0.0380.891−0.162
Cr−0.734−0.1300.430
Cu0.7910.2440.300
Ba−0.6360.3530.495
Ni0.6270.5280.095
% of variance35.5023.6214.46
Cumulative %35.5059.1273.58
Table 7. Average values of CDI (mg/kg/day), HQ, and HI for non-carcinogenic risk in adults and children from Wadi Al-Hamd.
Table 7. Average values of CDI (mg/kg/day), HQ, and HI for non-carcinogenic risk in adults and children from Wadi Al-Hamd.
HMsAdults
CDI IngCDI DermHQ IngHQ DemHI
As1.87 × 10−52.047 × 10−86.2 × 10−21.7 × 10−46.26 × 10−2
Pb4.95 × 10−74.17 × 10−113.5 × 10−41.39 × 10−10 3.50 × 10−4
Cd4.44 × 10−75.068 × 10−108.9 × 10−42.027 × 10−59.00 × 10−4
Cu7.44 × 10−69.075 × 10−91.9 × 10−43.025 × 10−81.90 × 10−4
Cr2.71 × 10−56.20 × 10−89.0 × 10−32.48 × 10−69.00 × 10−3
Ni7.44 × 10−61.64 × 10−93.7 × 10−44.099 × 10−83.70 × 10−4
Zn2.80 × 10−51.67 × 10−89.33 × 10−58.34 × 10−89.00 × 10−5
Ba3.8 × 10−41.74 × 10−81.9 × 10−34.34 × 10−71.90 × 10−3
HMsChildren
CDI IngCDI DermHQ IngHQ DemHi
As3.19 × 10−55.22 × 10−81.10 × 10−1 4.4 × 10−410.67 × 10−2
Pb8.43 × 10−71.05 × 10−106.00 × 10−4 3.50 × 10−106.0 × 10−4
Cd7.55 × 10−71.27 × 10−91.50 × 10−3 5.10 × 10−51.6 × 10−3
Cu1.48 × 10−52.28 × 10−83.70 × 10−4 7.61 × 10−83.7 × 10−4
Cr4.60 × 10−51.56 × 10−71.50 × 10−2 6.24 × 10−61.54 × 10−2
Ni1.26 × 10−54.12 × 10−96.30 × 10−4 1.03 × 10−76.3 × 10−4
Zn4.76 × 10−54.19 × 10−81.60 × 10−4 2.10 × 10−73.2 × 10−4
Ba1.3 × 10−34.36 × 10−86.30 × 10−3 1.09 × 10−66 3 × 10−3
Table 8. Average CRs and LCR values for As, Pb, Cd, and Cr from Wadi Al-Hamd.
Table 8. Average CRs and LCR values for As, Pb, Cd, and Cr from Wadi Al-Hamd.
HMsAdults
CR IngCR DermLCR
As2.68 × 10−5 7.49 × 10−8 2.82 × 10−5
Pb1.79 × 10−7 2.09 × 10−11 2.48 × 10−7
Cd2.66 × 10−6 3.09 × 10−9 2.71 × 10−6
Cr1.33 × 10−5 2.54 × 10−6 1.61 × 10−5
HMsChildren
CR IngCR DermLCR
As4.56 × 10−5 1.91 × 10−7 4.80 × 10−5
Pb3.05 × 10−7 5.24 × 10−11 4.21 × 10−7
Cd4.52 × 10−6 7.77 × 10−9 4.61 × 10−6
Cr2.27 × 10−5 6.39 × 10−6 2.95 × 10−5
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Alharbi, T.; El-Sorogy, A.S.; Alhejji, S.S.; Rikan, N. Spatial Variability and Health Implications of Heavy Metals in Wadi Al-Hamd’s Groundwater: A Multivariate and Risk-Based Approach. Water 2025, 17, 2549. https://doi.org/10.3390/w17172549

AMA Style

Alharbi T, El-Sorogy AS, Alhejji SS, Rikan N. Spatial Variability and Health Implications of Heavy Metals in Wadi Al-Hamd’s Groundwater: A Multivariate and Risk-Based Approach. Water. 2025; 17(17):2549. https://doi.org/10.3390/w17172549

Chicago/Turabian Style

Alharbi, Talal, Abdelbaset S. El-Sorogy, Suhail S. Alhejji, and Naji Rikan. 2025. "Spatial Variability and Health Implications of Heavy Metals in Wadi Al-Hamd’s Groundwater: A Multivariate and Risk-Based Approach" Water 17, no. 17: 2549. https://doi.org/10.3390/w17172549

APA Style

Alharbi, T., El-Sorogy, A. S., Alhejji, S. S., & Rikan, N. (2025). Spatial Variability and Health Implications of Heavy Metals in Wadi Al-Hamd’s Groundwater: A Multivariate and Risk-Based Approach. Water, 17(17), 2549. https://doi.org/10.3390/w17172549

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