Integrated Assessment of Metal Contamination of Soils, Sediments, and Runoff Water in a Dry Riverbed from a Mining Area Under Torrential Rain Events

Abstract

Dry riverbeds can transport mining waste during torrential rain events, disseminating pollutants from mining areas to natural ecosystems. This study evaluates the impact of these mine wastes on soils, sediments, and runoff/pore water in the La Carrasquilla dry riverbed (southeastern Spain). An integrated approach utilizing geochemical and mineralogical techniques was employed, analyzing water, soil, and sediment samples from both the headwater and mouth of the riverbed. Soil profiles and pore water were collected at 30 cm, 60 cm, and 90 cm deep, alongside sediment and runoff water samples. The assessment of metal(loid) contamination focused on arsenic, cadmium, chromium, copper, iron, nickel, manganese, zinc, and lead, utilizing sequential extraction to evaluate metal partitioning across soil phases. Various pollution indices, including the contamination factor (Cf), pollution load index (PLI), potential ecological risk index (RI), and metal(loid) evaluation index (MEI), were employed to classify contamination levels. The highest level of contamination was reported in the headwater, which suggested anthropogenic activities linked to the presence of mining residues as the major source of metal(loid)s. However, an active deposition of As, Cd, Cu, Fe, Mn, and Zn was reported in the topsoil at the mouth. In the headwater, a quartz and muscovite-rich zone exhibited the highest Cf for Pb (1022), primarily bound to the soil residual fraction (62.8%). At the headwater and mouth, pore water showed higher concentrations of sulfate, Ca, Na, Cl, Mg, and Mn and higher salinity than acceptable limits for drinking water or irrigation established by the World Health Organization. Runoff-water metal concentrations surpassed established guidelines, with MEI values indicating significant contamination by cadmium (36.1) and manganese (19.0). These findings highlight the considerable ecological risk of Pb and underscore the need for targeted remediation strategies to mitigate environmental impacts in the Mar Menor coastal lagoon.

1. Introduction

Global climate and environmental changes cause erratic rainfall, increasing the incidence of floods and droughts, especially in semi-arid and arid regions [1]. In addition, climate change can affect metal deposition in water bodies by modifying their input from surface sources in the watershed, changing wet and dry deposition. As a result, this can impact mixing and stratification processes by changing water chemistry, resulting—in some cases—in the release of metals from bottom sediments [2]. Moreover, increases in the amount or intensity of rainfall can drive the dissolution of metal bound to carbonates and metal bound to sulfides in sediments, potentially increasing the release of those metals [3].

Mining activities involve the generation of waste occupying surfaces with the potential to have a substantial impact on the surrounding environment due to their associated pollutants [4]. Bi et al. [5] pointed out that every year rivers carry 18.3 Gt of suspended sediment rich in metal(loid)s, nutrients, and other compounds into the ocean. Among all of them, metal(loid)s are a major concern because of their persistent and bio-accumulative nature [6]. The toxicity, abundance, persistence, and incorrect disposal of waste containing metals constitute a potential environmental pollution source that affects soil, water, and the atmosphere. However, the fate and transport of these metals depend on several factors, including their geochemical and mineralogical characteristics and the physical transport process involved.

In drainage basins, the concentrations of metal(loid)s in the soil are highly influenced by the parent materials, the soil particle size, and the hydrologic regime [7]. The transport of waste from mining areas to surrounding areas (agricultural, urban, and recreational areas) is usually through water and wind erosion of the tailing dams [8]. This process occurs in two phases, during the first of which, most of the ions and metals are dissolved in fractions. While in the second phase, some of the metals are fully dissolved, being transported in solution, while others can remain adsorbed or precipitated, being transported by soil particles. As a result, the surrounding environment will be affected to a degree that depends on the phases in which the metal(loid)s are transported [9].

Macklin et al. [10] studied the transport of contaminated sediments by tracking the material downgradient in what they called “pulses”. They explained that pulses consist of material temporarily suspended in flood waters and ultimately deposited in localized spots beyond the source. Their findings showed that contaminated deposits decreased downstream in sediments of rivers and streams. Additionally, several incidents have been reported in the United Kingdom, one of which is related to a major flood occurred on lands once used for metal mining [11]. This study indicated that the contaminated material was derived from the waste from mined sources and historically contaminated floodplain deposits in the main river. On the other hand, in 2015, an exceptional hydrometeorological event struck the southern Atacama Desert in northern Chile, leading to a catastrophic flood in the city of Copiapó [12]. Upon evaluating the environmental impact of the sediments transported by the flood, one of the risk indicators, the geo-accumulation index, indicated moderate contamination of As, Cd, Cu, Fe, Mn, Ni, and Pb throughout the city. This study underscores the critical need to comprehend the relationship between extreme flood events and mining activities in arid, degraded regions, where such extraordinary occurrences can exacerbate damage through the deposition of polluted sediment transported by the floodwaters [12].

Extreme rainfall events that lead to the flooding of mine sediment generally alter soil’s physical and chemical properties and influence biological processes [13]. The consequences of mine sediment contamination are rarely observed immediately in soil; instead, they often result in delayed adverse ecological changes due to their persistence in the environment and non-biodegradability [14]. Additionally, mine sediment contamination can adversely affect plants and organisms by impacting their activities, growth rates, metabolisms, and reproductions, causing physiological stress symptoms and potentially leading to death [15].

Soil erosion leads to land degradation, increases sedimentation, and consequently can contaminate water bodies. Various solutions have been proposed to address this issue; research has shown that plant roots can reduce soil erodibility by improving soil properties, thus preventing soil detachment by raindrops and transport by runoff [16]. Another approach for erosion mitigation is the installation of check dams, which have both upstream and downstream impacts. Upstream, check dams alter water and sediment transport by impounding storm flows, reducing flow velocity and peak rates, decreasing channel slopes, and providing more time for infiltration and sediment deposition [17]. However, sediments accumulated behind check dams can be mobilized during large runoff events, potentially depleting the system and starting a new deposition cycle.

A detailed assessment of the sediment volumes transferred along a water course induced by a torrential rain event can explain the changes in the distributions of metal(loid) concentrations of the stream in arid areas potentially polluted by mining activities. In addition, knowing the characteristics of contaminated sediment transport, particularly during extreme flood events, is crucial for developing appropriate mitigation strategies. By thoroughly analyzing these processes, soil and water quality will be better managed, preventing further environmental degradation and protecting ecosystems from the adverse effects of mine sediment contamination. Understanding how physical, geochemical, and mineralogical processes control the mobility of metal(loid)s is important in minimizing environmental impacts on the ecosystems and human health risks. Unfortunately, little information is known about the mobility of metals in dry riverbeds impacted by mining activity in semi-arid regions under torrential rain events. Therefore, the objectives of this study are (1) to determine the physico-chemical characteristics of sediments, soils, runoff water, and soil pore water in a dry riverbed under a torrential rainfall event, (2) to evaluate the impact of a torrential rainfall event on metal(loid) pollution in soil, sediments, and water, and (3) to assess the metal mobility and their chemical partitioning in different soil phases.

2. Materials and Methods

2.1. Study Area

The study area is in the Cartagena-La Unión mining district in southeastern Spain, historically exploited for over 2500 years for silver (Ag), copper (Cu), iron (Fe), lead (Pb), and zinc (Zn) extraction. This prolonged activity has significantly altered the landscape, leaving residues with high concentrations of metal(loid)s even after mining ceased in 1991 [18,19]. Within this district, the La Carrasquilla dry riverbed occupies a sloped basin of 28.5 km² and a perimeter of 25.3 km, making it one of the primary surface watercourses in the area. Its flow channels storm water runoff from the mining region directly into the Mar Menor coastal lagoon, a key environmental site and one of the largest coastal lagoons in the Mediterranean. The Mar Menor is protected as a Ramsar wetland and designated as a priority habitat (Habitat 1150) by the Habitats Directive (92/43/CEE) [20,21].

The basin’s land use is diverse, comprising mainly crops (38%), scrubland (19%), unproductive land (20%), coniferous forests (15%), and urban areas (8%) [20]. The vegetation cover along the dry riverbed is sparse, and agricultural activities have encroached upon its banks, narrowing its cross-section and modifying its natural flow. These agricultural alterations, combined with the erodible silty-sandy substrate, enhance sediment transport during storm events, a process managed by the installation of small retention dikes along the riverbed [20].

This area experiences a semi-arid Mediterranean climate, with an annual average precipitation of approximately 300 mm, mostly during brief, intense rainfall events from October to May [22]. Due to this climate, La Carrasquilla exhibits an ephemeral hydrological regime, with water flows occurring only during significant storms (Figure 1) [23].

During and after intense rain events, the dry riverbed is filled with runoff water from the surrounding areas of the Cartagena-La Unión mining district [24,25]. In recent decades, the region has faced increasingly severe flooding events, partly due to climate anomalies such as the 2016 and 2019 DANAs (Isolated Depression at High Levels), which caused unprecedented rainfall and led to severe environmental impacts. Notably, the DANA of September 2019 brought record-breaking rainfall, with two days’ accumulation surpassing the annual average in parts of the area, including a peak of 146 mm in a single hour [26,27]. Such events underscore the vulnerability of La Carrasquilla and the surrounding mining district to extreme weather, further exacerbating erosion, sediment transport, and the mobilization of contaminants from mining residues [24,28].

2.2. Sampling and Analytical Methods

2.2.1. Soil, Sediment, and Runoff Water Sampling

The sampling campaign was carried out from October 2021 to March 2022, collecting soil samples before and after the rain event, sediments transported by the runoff, pore water, and runoff water samples during the rain event.

Soil profile samples were collected in October 2021 in the headwater (37°36′09″ N 0°49′49″ W) and mouth (37°38′50″ N 0°46′27″ W) of the dry riverbed. Samples were taken with an auger at 30 cm (L1), 60 cm (L2), and 90 cm (L3) and packed and sealed in polyethylene bags. Furthermore, to collect the suspended sediments and runoff water, plastic traps were placed at the headwaters and mouth of the riverbed from November 2021 to March 2022. The water samples were stored in 100 mL vials and preserved at −4 °C, while sediment samples were packed and sealed in polyethylene bags.

Three lysimeters (IRROMETER Moisture Indicator, Irrometer Company, Riverside, CA, USA) were installed in October 2021 at different depths (L1—30 cm, L2—60 cm, and L3—90 cm) for pore water sampling. The lysimeters consisted of PVC tubes with 100 kPa porous ceramic cups. The lysimeters were moistened with soil and water to help with the lysimeter–soil contact. Suction was applied on the lysimeters using a vacuum hand pump (IRROMETER Moisture Indicator, Info Agro) at 70 kPa to create a negative pressure inside the pore water sample.

Riverbeds in this region only experience water flow and sediment transport during significant rainfall. Rainfall data from the Roche meteorological station, located 11 km from the study area, recorded monthly precipitation as follows: 3 mm in November 2021, 3.2 mm in December 2021, 15 mm in January 2022, 2 mm in February 2022, and 138 mm in March 2022. In March 2022, rainfall magnitudes could generate the necessary runoff to mobilize sediments. Suspended sediment/water sample collection campaigns were conducted on 18th March (R1), 23rd March (R2), and 28th March (R3) of 2022 (Figure 2).

2.2.2. Laboratory Analytical Methods

Soil and Sediments Analysis

Before the physico-chemical analysis, the soil and sediment samples were dried in an oven at 50 °C for 72 h and passed through a 2 mm sieve. Particles larger than 2 mm were excluded, as the primary aim of this study is to assess fine-grained materials (sand, silt, and clay) that influence metal(loid) transport and retention. Most of the tailing ponds that have a coarse texture (sandy loam) generally show higher Pb and Zn contents than those having a more clayish texture. Additionally, the levels showing higher Fe, As, and Cu contents are associated with a sandy texture. The physico-chemical analysis based on dry weight was conducted under the following conditions: pH was measured in the ratio of 1:2.5 for soil and distilled water, and electrical conductivity (EC) was determined in the ratio of 1:5 for soil and distilled water, respectively; both cases used HANNA model equipment [29]. The particle size distribution was determined by a Malvern Hydro 2000 g laser particle size analyzer (MASTERSIZER, 2000LF, Malvern Instruments, Marvern, UK) [29]. Water soluble ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl⁻, and SO₄²⁻) were determined using the 861 METROHM ion chromatography system. Ground soil samples were used to determine the total carbon (TC) and total nitrogen (TN) by a CHN 628 LECO Instrumentos, Madrid, Spain). Inorganic carbon was determined by the volumetric method of Bernard’s calcimeter [30].

Total metal(loid) concentrations were determined by acid digestion. For each sample, 0.5 g of ground soil was weighed and placed in Teflon vessels, followed by the addition of 10 mL of nitric acid (HNO₃). The digestion process was carried out in a microwave system according to the USEPA Method 3051 [31,32]. The water-soluble metal(loid)s were extracted in the ratio of 1:5 for soil and water [31]. The concentrations of 9 metal(loid)s (As, Cd, Cr, Cu, Fe, Ni, Mn, Zn, and Pb) were determined by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS PerkinElmer optima 8300-DV, PerkinElmer, Shelton, CT, USA) [32]. During the analysis, quality control samples were utilized, including the use of certified reference material (BAM-U110) sourced from the Federal Institute for Materials Research and Testing [33].

Metal sequential extraction was used to evaluate the association of metals to different solid phases [34]. F1-(1st Fraction) exchangeable: metal(loid)s bound to the surface soil minerals and organic matter; F2-(2nd fraction) carbonate: metal(loid)s co-precipitated with carbonate minerals; F3-(3rd fraction) reducible: metal(loid)s bound within Fe- and Mn-(oxy) hydroxides; F4-(4th fraction) oxidizable: metal(loid)s bound within complex organic matter and sulfide mineral; and F5-(5th fraction) residual fraction. In the case of arsenic, there are 5 fractions in which it can be retained: F1-(1st Fraction) soluble, F2-(2nd Fraction) adsorbed on the surface, F3-(3rd Fraction) associated with Fe–Al, F4-(4th Fraction) bound to carbonates, and F5-(5th Fraction) residual.

Mineral phases were determined through X-Ray Diffraction (XRD) using a Bruker D8 Advance instrument in θ–θ mode (provided by Bruker Corporation, Billerica, MA, USA). The samples underwent stepwise scanning from 5 to 70 degrees in the 2θ direction, with intervals of 0.05 degrees between steps, each step taking 1 s to complete, and at a rotational speed of 30 rpm. Evaluation of the diffraction patterns was carried out using DIFFRAC.EVA version 3.0, a commercially available software package from Bruker AXS in 2012, along with the powder diffraction files database PDF4+ from ICDD in 2022. The method serves as a swift and potent tool for the identification of all crystalline compounds, proving particularly beneficial in instances involving polymorphs or quasi-isochemical compounds, where conventional chemical techniques may not be applicable [35].

A Crossbeam 350 Field Emission Scanning Microscope (FESEM-FIB DE ZEISS CROSSBEAM 350, ZEISS, Oberkochen, Germany) was used to acquire the image of the samples. It has been worked in High Vacuum Mode (HV), with an accelerating voltage of 2 KV and a working distance of 5.1 mm. The software used for the image acquisition was SmartSEM Version 6.07 with Service Pack 10 (16-Jun-20). For EDX analysis and acquisition of elemental maps, Aztec 5.0 software from Oxford Instruments Nanotechnology Tools Ltd. (Oxford, UK) was used.

Water Samples Analysis

The pH of the water samples was measured using HANNA HI 5221 (Gipuzkoa, Spain), and electrical conductivity with HANNA conductivity 5321 (Gipuzkoa, Spain). The water samples were then filtered using a 0.22 μm membrane filter, and metal(loid)s (As, Cd, Cr, Cu, Fe, Ni, Mn, Zn, and Pb) were analyzed by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS PerkinElmer optima 8300-DV, PerkinElmer, Shelton, CT, USA), while ions concentration (Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl⁻, and SO₄²⁻) were determined by an 861 METROHM ion chromatography system.

2.3. Quality Indicators for Assessing Pollution Levels

Quality indices were used to measure the level of contamination and classify the degree of pollution. This classification is based on the corresponding quality standards, as outlined by Rees et al. [36].

2.3.1. Contamination Factor

The contamination factor (Cf) (Equation (1)), introduced by Hakanson [37], is a measure of the level of contamination for a specific element, relative to its baseline concentration. The Cf is calculated as follows:

$$\mathrm{C}\mathrm{f}={\displaystyle \frac{C_{Sample }}{C_{Background}}}$$

(1)

where C_sample is the metal(loid) concentration in the sample and C_background is the background concentration in the area. The local background concentrations of metal(loid)s in the study area are as follows (mg kg⁻¹): As (7), Cd (0.32), Cr (40.4), Cu (12.6), Ni (21.7), Pb (9.30), Zn (41.4), and Mn (770) [38].

Values of Cf < 1 are considered low; 1 ≤ Cf < 3 moderate; 3 ≤ Cf < 6 considerable; and Cf ≥ 6 very high.

2.3.2. Pollution Load Index

The pollution load index (PLI) (Equation (2)), introduced by Tomlinson et al. [39], is an empirical index that can be used to assess the overall degree of contamination for all the analyzed metals (n). The PLI is calculated as follows:

$$\mathrm{P}\mathrm{L}\mathrm{I}=n\sqrt{{\mathrm{C}\mathrm{f}}_{\mathrm{i}1}\times {\mathrm{C}\mathrm{f}}_{\mathrm{i}2}\times {\mathrm{C}\mathrm{f}}_{\mathrm{i}3}\times \dots {\mathrm{C}\mathrm{f}}_{\mathrm{i}\mathrm{n}}}$$

(2)

where Cf_i is the contamination factor of each metal(loid) (Equation (1)).

The PLI is used to assess and compare the overall level of metal contamination in a specific area [40]. A PLI value exceeding 1 indicates that sample is contaminated, while values lower than 1 indicate no pollution load. The pollution load index (PLI) is divided into seven levels, ranging from no pollution to high pollution, to indicate the degree of contamination. These levels are defined as follows: unpolluted (0 < PLI ≤ 1), unpolluted to moderately polluted (1 < PLI ≤ 2), moderately polluted (2 < PLI ≤ 3), moderately to highly polluted (3 < PLI ≤ 4), highly polluted (4 < PLI ≤ 5), or very highly polluted (PLI > 5) [40].

2.3.3. Potential Ecological Risk Index

The potential ecological risk index (RI) (Equation (3)), formulated by Hakanson [37], is used to assess the potential ecological risk of trace metal contamination, considering the toxicity of each metal. The RI is calculated as follows:

$$RI={\sum }_{i=1}^n{\mathrm{E}}_{\mathrm{r}\mathrm{i}}$$

(3)

where E_ri is the potential ecological risk of an individual element (Equation (4)).

Hakanson [37] categorized the potential ecological risk of individual metals (E_ri) into five levels: low (E_ri < 40), moderate (40 ≤ E_ri < 80), considerable (80 ≤ E_ri < 160), high (160 ≤ E_ri < 320), and very high (E_ri ≥ 320); while values of RI < 150 are categorized as low; 150 ≤ RI < 300 moderate; 300 ≤ RI < 600 high; RI ≥ 600 significantly high.

$${\mathrm{E}}_{\mathrm{r}\mathrm{i}}={\mathrm{T}}_{\mathrm{r}\mathrm{i}}\times {\mathrm{C}\mathrm{f}}_{\mathrm{i}}$$

(4)

The RI is a measure of the potential for biological absorption of trace metals that could potentially impact organisms within the ecosystem, as pointed out by Birch [41]. The individual biological toxicity factor, T_ri, has predetermined values for elements such as Cd, Cr, Cu, Mn, Ni, Pb, Zn, and As, which are set at 30, 2, 5, 1, 5, 5, 1, and 10, respectively [42].

2.3.4. Metal(loid) Evaluation Index

The metal(loid) evaluation index (MEI) offers insights into the general water quality in relation to metal(loid)s [43]. This index was determined through the given formula:

$$\mathrm{M}\mathrm{E}\mathrm{I}={\sum }_{i=1}^n{\displaystyle \frac{\mathrm{M}\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{c}}{\mathrm{M}\mathrm{M}\mathrm{P}\mathrm{C}}}$$

(5)

In this context, M_Conc refers to the observed concentration of a specific metal(loid), while M_MPC represents the highest allowable concentration. A contamination benchmark of 1.0 was established, an MEI value less than 1.0 is deemed Suitable, and any value greater than 1.0 is labeled Not Suitable for drinking. The classifications of the MEI are as follows: low (<10), medium (10 ≤ MEI < 20), and high (>20) [43].

2.3.5. Statistical Analysis

One-way ANOVA was used to evaluate variations in metal(loid) concentrations across different sites or depths in the headwater and mouth of the riverbed. All parameters were assessed for normality, with the results indicating a normal distribution (p > 0.05). One-way ANOVA revealed significant differences between mean values at p < 0.05. Different letters (a, b) in Tables and Supplementary Materials indicate statistically significant differences (p < 0.05) within each parameter across depths and locations.

3. Results

3.1. Soil Profile Characterization

3.1.1. Physico-Chemical Characteristics

Table 1. Soil’s physico-chemical characteristics in the headwater and the mouth of the La Carrasquilla dry riverbed (n = 3). Mean (standard deviation).

	Headwater			Mouth
Layer	L1	L2	L3	L1	L2	L3
Depth (cm)	0–30	30–60	60–90	0–30	30–60	60–90
pH	6.99 (0.21)	7.18 (0.09)	7.49 (0.37)	7.83 (0.05)a	7.88 (0.04)a	8.18 (0.19)b
EC * (mS cm−1)	2.91 (0.74)	3.01 (0.27)	3.67 (0.57)	1.76 (0.65)	2.44 (1.01)	2.61 (0.48)
Sand (%)	80.3 (10.9)	80.8 (8.7)	58.7 (7.4)	36.9 (6.2)a	28.0 (13.2)ab	14.2 (3.6)b
Silt (%)	17.1 (8.6)	17.0 (7.9)	31.9 (6.1)	52.0 (5.9)	58.2 (10.7)	61.8 (5.4)
Clay (%)	2.63 (2.33)a	2.14 (1.12)a	9.38 (0.84)b	11.1 (0.4)a	13.8 (2.7)a	24.1 (3.4)b
TN (%)	0.04 (0.02)	0.04 (0.02)	0.03 (0.01)	0.12 (0.02)a	0.07 (0.01)ab	0.05 (0.03)b
OC (%)	2.17 (2.31)	0.90 (0.25)	1.60 (0.53)	1.79 (0.48)a	1.06 (0.36)ab	0.48 (0.17)b
IC (%)	0.25 (0.19)a	0.84 (0.10)b	0.62 (0.10)b	2.33 (0.05)	2.67 (0.25)	2.48 (0.29)
TS (%)	4.64 (3.09)	6.13 (2.74)	7.30 (1.81)	0.17 (0.08)	0.30 (0.26)	0.40 (0.10)
Cl− (mg kg−1)	678 (242)a	425 (41)a	1117 (56)b	1791 (1130)	1873 (793)	1406 (442)
SO42− (mg kg−1)	8679 (701)	8812 (759)	10,153 (866)	1198 (971)	4229 (4394)	4641 (1186)
Ca2+ (mg kg−1)	2449 (155)a	2929 (106)b	2902 (95)b	733 (169)	1459 (1114)	1036 (99)
K+ (mg kg−1)	7.11 (0.43)	16.2 (12.6)	7.34 (0.72)	121 (87)	69.0 (37.9)	65.4 (11.4)
Na+ (mg kg−1)	328 (170)	230 (214)	601 (171)	426 (304)	659 (408)	1023 (102)
Mg2+ (mg kg−1)	554 (118)	360 (204)	677 (96)	203 (106)	340 (184)	285 (79)

* EC: electrical conductivity, TN: total nitrogen, OC: organic carbon, IC: inorganic carbon, TS: total sulfur. Different letters (a, b) on each layer and sampling site indicate significant differences (p < 0.05).

summarizes the soil’s physico-chemical characteristics at the headwater and mouth of the La Carrasquilla dry riverbed, analyzed at three depths (0–30 cm, 30–60 cm, and 60–90 cm). The parameters measured include pH, electrical conductivity (EC), particle size distribution (sand, silt, and clay percentages), total nitrogen (TN), organic carbon (OC), inorganic carbon (IC), and total sulfur (TS), along with concentrations of major ions (Cl⁻, SO₄²⁻, Ca²⁺, K⁺, Na⁺, and Mg²⁺). Values in the table represent the mean, with standard deviations in parentheses, based on triplicate samples (n = 3) for each depth interval. This provides a measure of consistency and allows comparison across layers and sites, with different letters (a, b) indicating statistically significant differences (p < 0.05) within each parameter across depths and locations.

Soil profile samples collected in the headwater of the dry riverbed showed an increase in pH with depth, from 6.99 in L1 to 7.49 in L3 (Table 1). The same trend was found in electrical conductivity (EC), with values increasing by 3.63% between L1 and L2 and by 21.7% between L2 and L3. The principal ions along the profile were Ca²⁺ (2449–2929 mg kg⁻¹), and SO₄²⁻ (8679–10,153 mg kg⁻¹) showed the lowest values in L1, with a trend to increase with depth (Table 1). Additionally, the textural analysis presented similar particle sizes distribution for L1 and L2, with a mean value of 80.6% sand, 17.0% silt, and 2.4% clay, while L3 was silt enriched with 31.9% silt (Table 1). The content of organic/inorganic carbon (TC) and total nitrogen (TN) did not present significant changes along the profile, with mean values of 1.55%, 0.57%, and 0.04%, respectively (Table 1). In contrast, the content of total sulfur (TS) showed an increased trend with depth from L1 (4.6%) to L3 (7.3%) (Table 1).

At the mouth of the dry riverbed, the pHs were similar between L1 (7.83) and L2 (7.88), while it increased to 8.18 in L3. Meanwhile, EC increased along the profile, 1.76 mScm⁻¹ in L1, 2.44 mScm⁻¹ in L2, and 2.61 mScm⁻¹ in L3 (Table 1). These values were 29% lower than those found in the headwater. In general, the predominant anion was SO₄²⁻ (3356 mg kg⁻¹), except for L1, where the highest concentration was for Cl⁻ (1792 mg kg⁻¹) (Table 1). The mean concentration of SO₄²⁻ was 63.6% lower in the mouth than in the headwater, increasing with depth in both sampling sites; oppositely, Cl⁻ showed an overall value 2.28 times higher in the mouth. Conversely, the main cation was Ca²⁺ (1459 mg kg⁻¹), which presented the highest concentration in L2, although 50.2% lower than in the headwater. Silt was the dominant particle size in the 3 sampling depths, L1 (52.0%), L2 (58.2%), and L3 (61.8%) (Table 1). The presence of OC was 28.7% lower in the mouth than in the headwater, while the value of TN was 1.69 times higher than that from the headwater. In contrast, a high content of IC (2.48%) was found in the mouth, higher than the determine in the headwater (Table 1). In addition, the highest percentage of TN was found in L1 (0.12%), and for IC in L2 (2.67%). The TS content increased along the profile as it happened in the headwater; however, the mean value was 21 times lower than in the headwater.

3.1.2. Metal(loid) Concentrations and Pollution Indices

Table 2. Soil’s Cf values in the headwater and mouth of the La Carrasquilla dry riverbed. Mean value (standard deviation).

Layer	Depth (cm)	As	Cd	Cr	Cu	Mn	Ni	Pb	Zn
Cf from the headwater
L1	0–30	42.6 (6.25) a	120 (55)	0.26 (0.09)	6.64 (1.65)	10.5 (0.8)	0.64 (0.17) ab	689 (308)	274(86)
L2	30–60	35.4 (14.6) a	105 (66)	0.26 (0.09)	5.01 (0.51)	9.0 (2.1)	0.66 (0.07) a	926 (465)	268(139)
L3	60–90	72.2 (11.5) b	113 (25)	0.17 (0.05)	5.95 (0.89)	8.4 (1.51)	0.42 (0.09) b	1452 (443)	298(78)
Mean		50.1 (19.5)	113 (7)	0.23 (0.05)	5.87 (0.82)	9.29 (1.08)	0.57 (0.13)	1023 (391)	280 (280)
Cf from the mouth
L1	0–30	3.14 (1.12) a	6.14 (1.88) a	0.34 (0.02)	1.51 (0.05)	1.68 (0.38)	0.77 (0.03)	94.1 (40.3) a	16.5(5.6) a
L2	30–60	3.13 (1.70) ab	5.48 (3.05) ab	0.32 (0.03)	1.40 (0.28)	1.54 (0.42)	0.78 (0.09)	125 (86) ab	15.4(9.6) ab
L3	60–90	1.02 (0.52) b	1.81 (0.58) b	0.34 (0.02)	1.29 (0.15)	1.04 (0.17)	0.81 (0.11)	18.3 (2.3) b	4.9(1.9) b
Mean		2.43 (1.22)	4.48 (2.33)	0.33 (0.01)	1.40 (0.11)	1.42 (0.34)	0.79 (0.02)	79.2 (55.0)	12.3 (6.4)

Different letters (a, b) on each layer and sampling site indicate significant differences (p < 0.05). The contamination factor (Cf) introduced by Hakanson [37]: Values of Cd < 1 are considered low; 1 ≤ Cf < 3 moderate; 3 ≤ Cf < 6 considerable; and Cf ≥ 257 very high.

shows the contamination factor (Cf) values for various metal(loid)s (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn) at the headwater and mouth of the La Carrasquilla dry riverbed, measured at three depths (0–30 cm, 30–60 cm, and 60–90 cm). Mean Cf values, along with standard deviations in parentheses, are presented for each layer to provide insights into contamination levels across the study area. Different letters (a, b) indicate statistically significant differences (p < 0.05) within each metal(loid) across depths and sites.

Along the soil profile in the headwater, Pb > Zn > Cd > As > Mn > Cu showed values of Cf > 1 (Table 2), without differences with depth, except for As, which highest Cf value was reported in L3 (72.2). The highest Cf values were reported for Pb (1028) and Zn (280). Oppositely, the concentrations under the background values along the profile corresponded to Cr (Cf: 0.23) and Ni (Cf: 0.57). However, the PLI values were >1 for all depths: L1 (18.0), L2 (17.0), and L3 (18.3) (Figure 3a). Furthermore, along the profile, the potential ecological risk index (RI) increased with depth, with the highest value close to 12,000 in L3 (Figure 3b). The increase along the profile was promoted by the individual potential ecological risk (Eri) of Pb (Supplementary Material-Table S1). In general, along the profile, the highest individual contributions E_ri, in comparison to the general risk RI, were Zn (3.0%), As (5.4%), Cd (36.3%), and Pb (54.9%).

The metal(loid)s that showed similar concentrations in the mouth for L1–L2 were As (22–21.9 mg kg⁻¹), Cd (1.96–1.75 mg kg⁻¹), Cr (13.8–13.1 mg kg⁻¹), Cu (19.0–17.6 mg kg⁻¹), Fe (22,379–21,444 mg kg⁻¹), Mn (1295–1185 mg kg⁻¹), Ni (16.7–16.9 mg kg⁻¹), and Zn (683–637 mg kg⁻¹), while Pb increased by 33% (876–1164 mg kg⁻¹) (Supplementary Material-Table S2). In contrast, a decrease in the concentrations of As (67.3%), Cd (66.9%), Cu (7.71%), Fe (24.7%), Mn (32.3%), Pb (84.5%), and Zn (68.3%) was reported between L2 and L3. The metal(loid)s with mean CF > 1 were as follows: As (2.43), Cd (4.5), Cu (1.40), Mn (1.42), Pb (79.2), and Zn (12.3) (Table 2). The PLI exhibited similar values for L1 (3.45) and L2 (3.40), while L3 (1.67) showed a decrease of 50.8% compared to L2 (Figure 3a). At the mouth of the dry riverbed compared to the headwater, the PLI was lower, L1 (19.2% lower), L2 (20.0% lower), and L3 (9.13% lower). Similarly, the RI showed values of 716 for L1, 850 for L2, and 173 for L3 (Figure 3b). The highest E_ri values were for Cd (134) and Pb (396); corresponding values in the headwater were 96.0% and 92.3% lower, respectively (Supplementary Material-Table S1).

3.1.3. Sequential Extraction of Metal(loid)s

Table 3. Sequential extraction of metal(loid)s in soils from the headwater and mouth of the La Carrasquilla dry riverbed. Mean value (standard deviation).

Fraction	As	Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn
Headwater (mg kg−1)
F1	0.22 (0.14)	0.21 (0.12)	BDL	0.07 (0.02)	0.09 (0.03)	5.15 (3.18)	0.02 (0.01)	1.23 (0.60)	11.9 (8.16)
F2	1.55 (0.99)	10.6 (2.25)	0.05 (0.01)	1.57 (0.12)	11.5 (7.49)	439 (237)	0.64 (0.20)	1798 (928)	1678 (529)
F3	80.9 (33.0)	17.6 (1.93)	1.14 (0.06)	5.98 (4.81)	16,054 (7777)	5043 (737)	3.68 (0.71)	1248 (9.69)	4714 (719)
F4	14.5 (9.5)	3.12 (3.12)	0.65 (0.14)	20.9 (12.3)	5905 (311)	607 (209)	1.77 (0.12)	236 (96)	1041 (816)
F5	566 (388)	11.4 (13.7)	12.1 (2.3)	348 (505)	144,830 (29,146)	1738 (85)	9.87 (1.56)	5535 (3241)	6207 (4276)
Sum	664	42.8	14.0	377	166,800	7832	16.0	8819	13,651
Mouth (mg kg−1)
F1	0.04 (0.03)	BDL	BDL	0.10 (0.04)	0.02 (0.02)	0.47 (0.43)	0.03 (0.01)	0.10 (0.06)	0.19 (0.08)
F2	0.79 (0.54)	0.50 (0.22)	0.04 (0.01)	0.24 (0.05)	1.98 (0.41)	33.6 (28.6)	0.24 (0.10)	35.6 (27.6)	12.6 (10.1)
F3	5.78 (2.20)	0.72 (0.33)	0.96 (0.20)	2.77 (1.42)	1159 (272)	828 (59)	5.85 (1.72)	468 (302)	186 (109)
F4	1.76 (1.04)	0.05 (0.02)	1.10 (0.21)	1.08 (0.51)	436 (222)	40.5 (9.8)	1.26 (0.14)	54.4 (31.0)	26.1 (15.8)
F5	13.6 (5.2)	0.13 (0.09)	9.14 (0.77)	13.6 (3.4)	14,900 (3451)	135 (48)	7.46 (0.61)	115 (67)	235 (108)
Sum	21.9	1.40	11.3	17.8	16,496	1038	14.8	673	460

BDL: below detection limit.

presents the sequential extraction results of metal(loid)s (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in soils from the headwater and mouth of the La Carrasquilla dry riverbed. Each metal(loid) is shown in different fractions (F1 to F5) according to its bioavailability and binding strength to the soil matrix. Values in parentheses indicate the standard deviation, representing variability across three replicates (n = 3) for each measurement. The results provide insights into each metal(loid) distribution across fractions, highlighting the potential mobility and bioavailability of contaminants in this mining-impacted area.

The sequential extraction for metal(loid)s in the headwater can be observed in Table 3 and Supplementary Material-Table S3. Cadmium was mainly bound to F3 (41.0%, reducible fraction), F5 (26.5%, residual), and F2 (24.7%, carbonates) (Table 3). However, Pb was mostly bound to F5 (62.8%, residual), followed by F2 (20.4%, carbonates) and F3 (14.2%, reducible). Conversely, Zn mostly showed affinity to F5 (45.5%), followed by F3 (34.5%) and F2 (12.3%) (Table 3). On the other hand, As exhibited residual fraction (F5) as the dominant one, with 85.4% of this metalloid bound to this fraction.

At the mouth, the sequential extraction analysis indicated that only As and Zn exhibited the same pattern as the headwater, where the highest fractions corresponded to F5 and F3 (Table 3). In the case of Zn, the main fraction was F5, accounting for 51.1%, and F3, accounting for 40.5%. While As showed the highest concentration in the F5 (61.9%), Cd (51.3%) was mainly bound to F3 (reducible), followed by F2 (carbonates) 35.6% (Table 3). Finally, Pb showed the highest concentrations in the fractions F5 (61.9%) and F3 (69.6%), respectively.

3.1.4. Mineralogical Composition

In the headwater, the mineralogical analysis revealed the presence of several predominant minerals, including silicates (muscovite, clinochlore, and quartz), and oxides (goethite). Additionally, the samples in the headwater exhibited the presence of sulfates (gypsum and plumbojarosite), as well as carbonates (such as calcite) (Supplementary Material-Table S4). At the mouth, the soils showed the presence of silicates (quartz, muscovite, and montmorillonite), carbonates (calcite), sulfates (gypsum), and a small portion of oxide minerals (goethite). Main mineral compositions for L2 were quartz (SiO₂) (32%), muscovite (KAl₂(Si.Al)₄O10(OH)₂) (28%), montmorillonite (Na_0.3(Al.Mg)₂Si₄O₁₀(OH)₂·8H₂O) (15%) and calcite Ca(CO₃) (12%) (Supplementary Material-Table S4). Comparing the mineralogical data in the headwater and the mouth, the difference between both zones was the presence of montmorillonite at the mouth; also, the carbonate minerals in the mouth was remarkable, due to the high presence of calcite (12%), which corresponded to being four times higher than in the headwater.

3.2. Physico-Chemical Characteristics of Pore Water

Table 4. Physico-Chemical characteristics of pore water in the headwater and mouth of the La Carrasquilla dry riverbed.

Pore Water	Headwater				Mouth
Layer	L1	L2	L3	Mean	L1	L2	L3	Mean	WHO
Depth	0–30	30–60	60–90		0–30	30–60	60–90
pH	7.21 (0.34)	7.38 (0.23)	7.48 (0.36)	7.36 (0.1)	7.49 (0.15)	7.36 (0.10)	7.28 (0.11)	7.38 (0.11)	6.5–9.5
EC (mS cm−1)	17.7 (7.6)	20.7 (2.17)	21.5 (0.28)	20.0 (2.0)	8.74 (1.44)	9.82 (2.21)	7.18 (3.11)	8.58 (1.33)	2.5
Cl− (mg L−1)	2984 (2068)	2502 (1509)	3570 (1104)	3019 (535)	1598 (588)	1978 (1198)	1556 (1230)	1710 (233)	250
SO42− (mg L−1)	6777 (4132)	6183 (2283)	7474 (1438)	6811 (646)	580 (142) a	1152 (297) b	659 (194) a	797 (310)	(500)
Na+ (mg L−1)	1320 (899)	1359 (467)	1647 (272)	1442 (178)	357 (184)	447 (282)	529 (463)	444 (86)	(200)
K+ (mg L−1)	13.1 (5.8)	9.08 (6.09)	16.0 (6.5)	12.7 (3.5)	19.4 (9.1) a	21.1 (14.5) ab	7.21 (1.50) b	15.9 (7.6)	(150)
Ca2+ (mg L−1)	353 (64)	325 (78)	385 (87)	354 (30)	536 (143) a	613.5 (251) a	297 (60) b	482 (165)	(200)
Mg2+ (mg L−1)	1765 (1119)	1418 (958)	1829 (520)	1670 (221)	217 (77)	241 (139)	168 (124)	208 (37)	(50)
As (μg L−1)	3.27 (1.54)	7.13 (4.60)	4.50 (1.34)	4.97 (1.97)	4.72 (1.73) a	1.90 (0.95) b	1.14 (0.56) b	2.59 (1.88)	10
Cd (μg L−1)	0.21 (0.06)	0.35 (0.17)	0.44 (0.17)	0.33 (0.12)	0.16 (0.05)	0.08 (0.03)	0.07 (0.03)	0.10 (0.05)	3
Cr (μg L−1)	0.26 (0.24)	0.27 (0.30)	0.04 (0.02)	0.19 (0.13)	0.13 (0.07)	0.19 (0.18)	0.15 (0.11)	0.16 (0.03)	50
Cu (μg L−1)	3.19 (3.50)	2.78 (3.04)	0.64 (0.31)	2.21 (1.37)	2.26 (1.72)	2.12 (1.98)	1.31 (0.42)	1.90 (0.51)	2000
Fe (μg L−1)	BDL	BDL	BDL	BDL	BDL	BDL	BDL	BDL	(300)
Mn (μg L−1)	491 (185) a	1304 (576) a	31,840 (1460) b	11,211 (17,869)	270 (190) a	620 (317) a	1190 (302) b	693 (464)	(400)
Ni (μg L−1)	3.97 (1.04)	4.00 (1.04)	6.06 (1.98)	4.68 (1.20)	6.22 (3.78) a	3.72 (1.35) ab	1.45 (0.45) b	3.80 (2.39)	70
Pb (μg L−1)	1.59 (0.76)	2.58 (0.53)	0.09 (0.05)	1.42 (1.25)	0.49 (0.44)	0.04 (0.07)	BDL	0.18 (0.27)	10
Zn (μg L−1)	64.3 (39.4)	114 (46)	80.6 (40.0)	86.1 (25.0)	9.05 (3.21)	5.15 (4.69)	8.99 (4.49)	7.73 (2.24)	(3000)

The WHO recommendations for drinking water quality specify that values in parentheses are determined not by health considerations, but rather by limits deemed unacceptable due to factors such as the taste, aesthetics, or corrosion of facilities. Different letters (a, b) indicate significant differences (p < 0.05). BDL: below detection limit.

details the physico-chemical characteristics of pore water in both the headwater and mouth of the La Carrasquilla dry riverbed. The parameters measured include pH, electrical conductivity (CE), and concentrations of major ions (Cl⁻, SO₄²⁻, Na⁺, K⁺, Ca²⁺, and Mg²⁺), as well as metal(loid)s (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn). These data are provided across three depth intervals (0–30 cm, 30–60 cm, and 60–90 cm), with mean values for each depth and location. The mean concentrations are presented alongside the World Health Organization (WHO)-recommended limits for drinking water quality, where applicable, allowing for a comparison with health-based benchmarks. Values in parentheses represent the standard deviation for each measurement, providing a measure of variability across the three replicate samples (n = 3) taken for each depth at both the headwater and mouth locations. Different letters (a, b) next to values denote statistically significant differences (p < 0.05) between the two locations for each parameter.

In the headwater, soil pore water presented pH values with small increases through the soil layers from L1 (7.21) to L3 (7.48) (Table 4). A similar spatial variation pattern on the layers was also observed on EC values at L1 (17.7 mS cm⁻¹) and L3 (21.5 mS cm⁻¹). Along the profile, the ions with the highest mean concentration were SO₄²⁻ (6811 mg L⁻¹) and Mg²⁺ (1671 mg L⁻¹) (Table 4). Additionally, the spatial analysis along the profile showed that the highest values of these ions were in L3 (7473 mg SO₄²⁻ L⁻¹ and 1829 mg Mg²⁺ L⁻¹) (Table 4).

At the mouth of the dry riverbed, the pH showed small variations, decreasing with depth from L1 (7.49) to L3 (7.28), which was the opposite of what happened in the headwater (Table 4). In contrast, there was not a clear trend for EC, with a peak value at L2 (9.82 mS cm⁻¹). The ions that showed the highest mean concentrations along the profile were Cl⁻ (1710 mg L⁻¹) as the main anion and the main cation Na⁺ (444 mg L⁻¹) (Table 4). Moreover, the spatial variability of Cl⁻ exhibited the highest value at L2 (1872 mg L⁻¹) and for Na⁺ at L3 (529 mg L⁻¹).

Along the profile in the headwater, pore water metal(loid)s’ mean concentrations were, in descending order, Mn > Zn > As > Ni > Cu > Pb > Cd > Cr > Fe (Table 4). The spatial analysis exhibited that Cr, Cu, and Ni had similar concentrations between L1 and L2: Cr (0.16–0.10 μg L⁻¹), Cu (3.19–2.78 μg L⁻¹), and Ni (3.97–4.00 μg L⁻¹). While others presented the highest value in L2: As (7.13 μg L⁻¹), Pb (2.58 μg L⁻¹), and Zn (113 μg L⁻¹). The metals whose values constantly increased with depth were Cd and Mn, with the highest concentration at L3, 0.44 μg L⁻¹ and 31,840 μg L⁻¹, respectively. Additionally, Mn represented the highest MEI in all depths, ranging from L1 (1.23) to L3 (79.6) (Supplementary Material-Table S5). In general, along the profile in the mouth, pore water metal(loid)s’ concentrations were, in descending order, Mn > Zn > Ni > As > Cu > Pb > Cr > Cd > Fe. There were decreasing patterns from L1 to L3 on the concentrations of As (4.72–1.14 μg L⁻¹), Cd (0.16–0.07 μg L⁻¹), Cu (2.26–1.31 μg L⁻¹), Ni (6.22–1.45 μg L⁻¹), and Pb (0.49–0.00 μg L⁻¹). However, Zn presented a fluctuation with a decrease by 43.1% between L1 and L2 (9.05–5.15 μg L⁻¹), followed by an increase by 74.7% from L2 (5.15 μg L⁻¹) to L3 (8.99 μg L⁻¹). Along the profile, the Zn’s mean concentration represented a value 11.1 times lower than that in the headwater. However, the concentration of Mn at the mouth was 93.8% lower than that in the headwater, with the highest values at L3 (1189 μg L⁻¹).

3.3. Physico-Chemical Characterization of Sediments

Table 5. Physico-chemical characteristics of sediments in the headwater and mouth of the La Carrasquilla dry riverbed.

Sediments	Headwater	Mouth
pH	7.90 (0.10)	8.27 (0.26)
EC (mS cm−1)	2.48 (0.30)	1.04 (0.64)
Sand (%)	96.9 (1.5) a	80.4 (8.9) b
Silt (%)	2.20 (0.85)	11.7 (5.4)
Clay (%)	0.93 (0.62) a	7.86 (4.2) b
TN (%)	0.00 (0.00) a	0.07 (0.04) b
OC (%)	0.87 (0.13)	1.05 (0.41)
IC (%)	0.50 (0.08) a	2.36 (0.24) b
TS (%)	1.86 (1.50) a	0.09 (0.06) b
Cl− (mg kg−1)	183 (227)	648 (540)
SO42− (mg kg−1)	5643 (660) a	1291 (1076) b
Ca2+ (mg kg−1)	2180 (86) a	420 (349) b
K+ (mg kg−1)	5.28 (2.70) a	61.4 (28.7) b
Na+ (mg kg−1)	121 (117)	487 (307)
Mg2+ (mg kg−1)	225 (140)	107 (61)

Different letters (a, b) indicate significant differences (p < 0.05).

presents the physico-chemical characteristics of sediments collected from the headwater and mouth of the La Carrasquilla dry riverbed. The parameters analyzed include pH, electrical conductivity (EC), particle size distribution (sand, silt, and clay percentages), total nitrogen (TN), organic carbon (OC), inorganic carbon (IC), total sulfur (TS), and concentrations of major ions (Cl⁻, SO₄²⁻, Ca²⁺, K⁺, Na⁺, and Mg²⁺). Values in parentheses indicate the standard deviation for each parameter, representing the variability across replicate samples (n = 3) at each site. Different letters (a, b) next to values denote statistically significant differences (p < 0.05) between the two locations for each parameter.

The composition of the runoff sediments during the rain event of March 2022 were characterized in the headwater and mouth of the La Carrasquilla dry riverbed. In the headwater, sediment pH exhibited a mean value of 7.90 (Table 5), while EC was 2.48 mS cm⁻¹. Those properties showed similar results as those found along the profile in the headwater. In addition, the same main ions were found: Ca²⁺ (2180 mg kg⁻¹) and SO₄²⁻ (5652 mg kg⁻¹). In comparison to the mean values found along the soil profile, Ca²⁺ and SO₄²⁻ concentrations were 20.8% and 38.7% lower, respectively. The texture of the sediment was dominated by sand with 96.9%, followed by silt (2.19%) and clay (0.93%) (Table 5). On the other hand, the amount of TN (0.00%) and TS (1.89%) showed a significant decrease in comparison to the values along the soil profile (Table 1 and Table 5).

At the mouth of the dry riverbed, the sediments showed pH values between 8.08 and 8.61. However, the EC exhibited a mean value of 1.04 mS cm⁻¹, similar to the top layer L1 along the profile. The main ions for the sediments in the mouth were Na⁺ (487 mg kg⁻¹) and SO₄²⁻ (1291 mg kg⁻¹), with concentrations like those reported in the topsoil (Table 1 and Table 5). The sediment particle size was 80.4% sand, 11.7% silt, and 7.86% clay (Table 5). The content of TN in the sediment exhibited the same spatial pattern found in the soils with higher values in the mouth (Table 5). The content of OC showed a mean value of 1.04%, which represented a similar content found on L2 (Table 1 and Table 5). Likewise, the mean content of TN in the sediment was 0.07%. The content of TS in the sediment at the mouth showed a mean value of 0.09%, representing a value 21.0 times lower than that in the headwater (Table 5).

Table 6. Metal(loid) concentrations, Cfs, PLIs, and RIs of sediments in the headwater and mouth of the La Carrasquilla dry riverbed.

	Headwater			Mouth
	mg kg−1	Cf	mg kg−1	Cf
As	353 (50)	50.4 (4.4)	20.8 (7.4)	2.96 (1.17)
Cd	26.7 (3.2)	83.6 (2.7)	2.60 (1.38)	8.04 (5.00)
Cr	20.9 (1.50)	0.52 (0.01)	13.8 (1.2)	0.34 (0.03)
Cu	71.8 (12.0)	5.70 (1.02)	16.8 (1.2)	1.28 (0.10)
Fe	164,344 (23,550)	-	202,002 (6772)	-
Mn	8813 (843)	11.5 (0.2)	1401 (373)	1.80 (0.57)
Ni	19.1 (1.6)	0.88 (0.04)	15.1 (1.4)	0.69 (0.06)
Pb	3419 (409)	368 (21)	741 (249)	70.9 (32.8)
Zn	7698 (906)	186 (5)	881 (525)	21.5 (14.5)
PLI		17.4 (0.1)		3.35 (0.92)
RI		5081 (113)		659 (339)

Neeraj et al. [40] established the classification as follows: unpolluted (0 < PLI ≤ 1), unpolluted to moderately polluted (1 < PLI ≤ 2), moderately polluted (2 < PLI ≤ 3), moderately to highly polluted (3 < PLI ≤ 4), highly polluted (4 < PLI ≤ 5), or very highly polluted (PLI > 5). Hakanson [37] categorized RI < 150 as low potential ecological risk; 150 ≤ RI < 300 as moderate; 300 ≤ RI < 600 as high; and RI ≥ 600 as significantly high.

presents the concentrations of metal(loid)s (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in sediments from the headwater and mouth of the La Carrasquilla dry riverbed. Additionally, it includes the contamination factor (Cf), pollution load index (PLI), and the potential ecological risk index (RI) for each sampling site. These indices provide a comprehensive assessment of contamination levels and potential ecological risks associated with metal(loid) concentrations in the sediments. Values in parentheses represent the standard deviation, indicating variability across replicate measurements (n = 3) for each parameter.

The metal(loid)s that presented CF > 1 in the headwater were Pb > Zn > Cd > As > Mn > Cu, with the three highest values for Pb (368), Zn (186), Cd (83), and As (50) (Table 6). However, they were significantly lower in comparison to soils, with reductions for Pb, Zn, and Cd of 64%, 34%, and 26%, respectively. Nevertheless, the mean PLI exhibited a similar value to that reported for soils, with a mean value of 17.4 (Table 6). Moreover, the potential ecological risk index (RI) was 5081 (Table 6). The metal(loid)s that individually (Eri) contributed more to the potential ecological risk index (RI) in the sediment were As (504, 9.9%), Cd (2508, 49.4%), and Pb (1938, 36.2%) (Figure 4). The metal(loid) concentrations analyzed in the sediment from the mouth were lower than in the headwater (Table 6), and similar to those found in the soil (Supplementary Material-Table S2). In the mouth of the dry riverbed, the Cf showed the highest values for Pb (79.7) and Zn (21.3), which were 77.1% and 93.0% lower than those in the headwater, respectively (Table 6). The PLI was 3.35, while the potential ecological risk index (RI) was 659 (Table 6). The main individual potential risk (E_ri) was Pb (53.8%), Cd (36.6%), As (4.5%), and Zn (3.26%) (Figure 4).

As, Cd, Zn, and Pb showed different binding forms in the sequential extraction analysis in the headwater (Supplementary Material-Table S6). Cd was mainly bound to three fractions, 47.6% with F3 (reducible), 24.0% with F5 (residual), and 20.8% with F2 (carbonates). Pb was predominantly adhered to the F5 (residual, 41.8%) and F3 (reducible, 49.2%). Similarly, Zn was primarily associated with F5 at 52.8%, followed by F3 at 28.7% and F2 at 9.27%. Finally, As was mainly bound to the residual fraction (F5), constituting 84.7%. At the mouth, sequential extraction of metal(loid)s indicated that Cd was mainly bound to F3 (reducible, 41.0%), with F2 (carbonates, 26.5%), and F5 (residual, 24.5%.). Conversely, the predominant fraction for Pb was F3, representing 52.0%, followed by F5 (30.8%). As and Zn were predominantly bound to a residual fraction (F5) with 65.0% and 61.8%, respectively (Supplementary Material-Table S6).

The most abundant minerals in the sediments from the headwater were muscovite (33.0%), quartz (26.0%), and clinochlore (17.0%) (Supplementary Material-Table S7). There were also notable presences of sulfates as gypsum (8.0%) and carbonates as calcite (5.0%). In addition, there was a small presence of crystalline Zn as bianchite (1.0%) (Supplementary Material-Table S7). The mineralogical composition of the sediment at the mouth exhibited quartz (41%) and muscovite (23%) as the most representative minerals (Supplementary Material-Table S7). In addition, there were montmorillonite, 13%, calcite, 12%, dolomite, 0.80%, and goethite, 0.40%.

3.4. Physico-Chemical Characteristics of Runoff Water

Table 7. Physico-Chemical characteristics and the MEI of runoff water in the headwater and mouth of the La Carrasquilla dry riverbed.

Runoff Water	Headwater	Mouth	WHO
pH	6.70 (0.21) a	7.50 (0.22) b	6.5–9.5
CE * (ms cm−1)	5.39 (4.49)	3.44 (3.04)	2.5
Cl− (mg L−1)	436 (452)	555 (650)	250
SO42− (mg L−1)	1839 (853) a	320 (405) b	(500)
Na+ (mg L−1)	210 (215)	378 (301)	(200)
K+ (mg L−1)	2.83 (2.34)	10.5 (5.6)	(150)
Ca2+ (mg L−1)	343 (19) a	86.8 (71.5) b	(200)	MEI
Mg2+ (mg L−1)	257 (226)	71.5 (60.0)	(50)	Headwater	Mouth
As (μg L−1)	0.48 (0.17) a	1.79 (0.79) b	10	0.05 (0.02) a	0.18 (0.08) b
Cd (μg L−1)	108 (82) a	0.68 (0.44) b	3	36.1 (27.4)	0.23 (0.15)
Cr (μg L−1)	BDL	0.39 (0.28)	50	-	0.01 (0.01)
Cu (μg L−1)	0.40 (0.17) a	4.37 (5.69) b	2000	0.00 (0.00)	0.00 (0.00)
Fe (μg L−1)	BDL	BDL	(300)	-	-
Mn (μg L−1)	7524 (3689) a	234 (224) b	(400)	18.8 (9.2) a	0.58 (0.56) b
Ni (μg L−1)	13.7 (8.5) a	2.33 (1.16) b	70	0.20 (0.12)	0.03 (0.02)
Pb (μg L−1)	1.34 (0.91)	BDL	10	0.13 (0.09)	-
Zn (μg L−1)	18,515 (13,733) a	137 (70) b	(3000)	6.17 (4.58) a	0.05 (0.02) b

* Electrical conductivity. BDL: below detection limit. Different letters (a, b) indicate significant differences (p < 0.05). The WHO recommendations for the quality of drinking water specify that values in parentheses are determined not by health considerations, but rather by limits deemed unacceptable due to factors such as the taste, aesthetics, or corrosion of facilities. MEI < 1 is deemed suitable, and MEI > 1 is not suitable. The classifications of the MEI are as follows: low (<10), medium (10 ≤ MEI < 20), and high (>20) [43].

presents the physico-chemical characteristics and the Metal Evaluation Index (MEI) of runoff water collected from the headwater and mouth of the La Carrasquilla dry riverbed. Additionally, it includes comparisons with WHO guidelines for drinking water quality. Letters “a” and “b” denote statistically significant differences (p < 0.05) between sampling sites, with different letters indicating significant variation. Values in parentheses represent the standard deviation, highlighting variability across replicate measurements (n = 3) for each parameter.

In the headwater of the dry riverbed, runoff water showed a pH of 6.70 (Table 7), with values increasing from 6.51 in R1 to 6.92 in R3 (Supplementary Material-Table S8). In contrast, EC values decreased by 63% from R1 (10.45 mS cm⁻¹) to R2 (3.87 mS cm⁻¹) and by 51.9% from R2 to R3 (1.86 mS cm⁻¹), resulting in a mean value of 5.39 mS cm⁻¹ (Table 7). Sulphate exhibited the highest concentration among anions (1839 mg L⁻¹) (Table 7), with values decreasing from R1 (2723 mg L⁻¹) to R2 (1773 mg L⁻¹) and further to R3 (1021 mg L⁻¹). Additionally, Ca²⁺ was identified as the principal cation, ranging from 329 to 364 mg L⁻¹, with a mean concentration of 343 mg L⁻¹, reflecting no significant variations in runoff samples (Table 7). Metal(loid) concentrations followed the order Zn > Mn > Cd > Ni > Pb > As > Cu > Cr > Fe. The three highest mean concentrations of metal(loid)s in the runoff from the headwater were Cd 108 μg L⁻¹, Mn 7524 μg L⁻¹, and Zn 18,515 μg L⁻¹ (Table 7). In addition, the highest Metal Evaluation Indices (MEIs) were observed for Cd (36.1), Mn (19.0), and Zn (6.17) (Table 7). On the other hand, only Pb exhibited similar concentrations in the runoff (1.34 μg L⁻¹) and in the lysimeter pore water (1.42 μg L⁻¹).

At the mouth of the dry riverbed, the mean pH was 7.50, with values ranging from 7.27 in R1 to 7.72 in R2, and then decreasing to 7.52 in R3 (Supplementary Material-Table S8). In contrast, electrical conductivity (EC) averaged 3.44 mS cm⁻¹ (Table 7), with values of 3.45 mS cm⁻¹ in R1, 0.40 mS cm⁻¹ in R2, and 6.48 mS cm⁻¹ in R3. The dominant anion was Cl⁻, with a mean concentration of 555 mg L⁻¹, while Na⁺ was the primary cation at 377 mg L⁻¹. The concentrations of Cl⁻ presented values of 304 mg L⁻¹ in R1, 68.0 mg L⁻¹ in R2, and 1293 mg L⁻¹ in R3. The concentrations of Na⁺ in the runoff were 218 mg L⁻¹ in R1, 191 mg L⁻¹ in R2, and 724 mg L⁻¹ in R3. Metal(loid) concentrations followed the order Mn > Zn > Cu > Ni > As > Cd > Cr, with Fe and Pb below detection limits (Table 7). The metal(loid)s that presented a higher concentration in the mouth than in the headwater were As (1.79 μg L⁻¹), Cr (0.28 μg L⁻¹), and Cu (4.37 μg L⁻¹). Moreover, the rest of the mean concentrations in comparison to the headwater represented a fraction with percentages for Cd (0.63%), Mn (3.11%), Ni (17.0%), and Zn (0.74%). Among the nine metal(loid)s analyzed, all of them showed the mean value below the guidelines proposed by WHO (2011) with an MEI < 1 (Table 7).

4. Discussion

4.1. Soil’s Physico-Chemical Differences Between Headwater and Mouth of the Dry Riverbed

Soil characteristics, relief features, the positioning of sampling locations, and the proximity to pollution sources may contribute to the disparities observed in the vertical arrangement of metals [44]. Furthermore, soil pH and particle size distribution significantly influence the build-up and movement of metal(loid)s in soils [45]. The pH of soils from the headwater (Table 1) ranged from neutral (L1 and L2) to slightly alkaline (L3) (Soil Survey Division Staff, 1993), with L3 soil being very slightly saline (2–4 mS cm⁻¹) (Soil Survey Division Staff, 1993). The same pattern was found for anions and cations, since when the concentration of soluble salts in the soil rises, EC increases [46]. Navarro et al. [47] studied tailings and dry riverbeds from the Cartagena-La Unión mining district, where the elevated concentration of sulfate in all the samples was consistent with the EC values. The increasing trend observed with depth in the percentage of sulfur suggests that this element comes from mining waste (Table 1). Similarly, Gonzalez-Fernandez, [48] studied the El Beal dry riverbed in the mining district of Cartagena-La Unión and reported sulfur contents two to three times higher in the upper layers than those found in the deepest part of the profile.

At the mouth of the dry riverbed, soil pH was slightly alkaline in L1 and L2, increasing to moderate alkaline in L3 (Soil Survey Division Staff, 1993) (Table 1); this is likely due to the high content of inorganic carbon [49], which comes from calcareous rocks of the parent material [50]. The higher EC and ion concentrations found in the mouth of the dry riverbed compared to the headwater suggests the influence of proximity to the coast, due to the presence of dissolved salts, such as sodium chloride (NaCl) [51].

At the headwater, Pb > Zn > Cd > As > Mn > Cu exceed the reference concentrations proposed by Martínez-Sánchez et al. [38], indicating a very high soil contamination for all of them [37], with the highest Cf values reported in L3 (Table 2). The L3 layer was characterized by the highest content of clay, 9.38%; clay horizons with high organic matter deeper in the profile can bind and immobilize metals, preventing their further leaching and causing accumulation [52,53]. Gonzalez-Fernandez et al. [48] reported from the El Beal dry riverbed that the lowest concentration of Pb and Zn was detected between 18 and 22 cm deep, with an increase as depth progresses, with the highest Zn concentration observed at 125–130 cm depth. In contrast, Cf values for Cr and Ni were categorized as low (CF < 1) [37]. Cuevas et al. [19] studied the sediment along the dry riverbed of La Carrasquilla, identifying the concentration of Cr and Ni as of lithogenic origin. However, the PLI classified all the layers as contaminated with a PLI > 1 [54] (Figure 3a), also the potential ecological risk index (RI) classified all the sampling depths (Figure 3b) as significantly high ecological risk (R1 ≥ 600), increasing those values along the profile due to mainly to the high concentrations of Pb.

At the mouth, As, Cd, Cu, Fe, Mn, and Zn concentrations showed a decrease with depth, suggesting an active deposition of those elements in topsoil, which were likely washed away by runoff water from the headwater. Meanwhile, the metal(loid)s of lithogenic origin, Cr and Ni, pointed out by Cuevas et al. [19] maintained similar concentration levels. Along the soil profile, As, Cd, Cu, Mn, Pb, and Zn showed concentrations above reference levels [38] and therefore, classified as contaminated [37]; similar results were reported with the PLI values, where the highest values were reported in topsoils (Figure 3a), being lower in the mouth than in the headwater. The RI showed significantly high ecological risk (≥600) for L1 and L2, while L3 had moderate ecological risk (150 ≤ RI < 300) (Figure 3b).

At the headwater, the sequential extraction analysis indicated that soil organic matter (OM) and Fe/Mn oxides were the major sorbents of Cd in soil [55], since Cd was mainly bound to the reducible fraction (Table 3). Also, the results suggested that Pb comes from stable minerals, which are resistant to weathering and leaching due to the physico-chemical characteristics of the soil. These minerals include Pb-sulfides, Pb-carbonates, and Pb-oxides. Li and Thornton [56] in the Pb–Zn mining and smelting region of Derbyshire in central England found that the main fractions for Pb in soils were bound to carbonates (F2) and Fe/Mn oxide phases (F4). Also, the high presence of Zn–Pb carbonates in waste of the studied area can be attributed to their limited ability to float during ore processing [57]. Results indicated that arsenic was mainly bound to a residual fraction (Table 3), which agrees with the finding of Akhavan and Golchin [58], who studied the distribution of arsenic in Zn–Pb mine tailings and observed that most of the arsenic in mine tailings was residually hosted by aluminosilicates or sulfide minerals. Sahuquillo et al. [59] reported that soils, with distinct origins, had a range from 30% to 55% of the total As bound to the residual fraction (F5).

At the mouth of the dry riverbed, the sequential metal(loid) extraction shows that Cd distribution may be linked to the significant proportion of Fe oxides, clay minerals, and the relatively low concentration of organic matter found in these soils; also, pH can affect the behavior of Cd [60]. Numerous studies have provided evidence on how the soil pH substantially affects the mobility of metals being the fractions and sensitive to the change [61,62]. In fact, according to the findings of Mulligan et al. [63], Cd exhibits limited mobility when the pH exceeds 7.5. Also, Zn distribution can be affected by soil pH, since most of its concentration was bound to F5 (Table 3). McBride and Martínez [64] observed that at elevated pH levels, the solubility of zinc decreases due to chemisorption of oxides and aluminosilicates. Finally, As and Pb showed the highest concentration in the fractions F5 and F3, respectively. Arsenic exhibited a strong tendency to combine various metals, particularly in the presence of Fe/Al hydroxides and oxides, as exemplified by arsenopyrite, which is a prevalent mineral in the investigated region [65]. Conversely, Martínez-Carlos et al. [66] studied soil samples collected from the “El Avenque” dry riverbed in the Cartagena-La Unión mining district, close to five tailing ponds, and reported that Pb was mainly bound to the reducible fraction (50–70%) in all soil samples.

The mineralogical composition observed in this study was similar to that reported by Manteca [67] and Martínez-Martínez et al. [68], where the dominating phases were gypsum and muscovite, while quartz and clinochlore were also present (Supplementary Material-Table S4). Plumbojarosite, a mineral commonly found in this mining area, was observed at a concentration of 4.0%. This mineral is formed mainly due to the alteration processes that take place in the tailings [69]. Additionally, the presence of goethite (FeO(OH)) was at 1.0% and indicates that the oxidation of sulfides had taken place. The process of sulfide oxidation also results in the emergence of oxides, oxyhydroxides, and oxy-hydroxy sulfates (such as goethite), which subsequently undergo precipitation or flocculation, either as discrete particles or by forming coatings on other sedimentary particles [70]. This explains the abundant presence of calcite at the mouth, which could be related to the downstream pH being more alkaline (Table 1), promoting the precipitation of carbonates. In the case of Fe, it was observed that abundance of goethite (FeO(OH)) was lower at downstream (0.3%) than in the headwater, which was according to the total metal(loid) concentration with the highest value for L3 in the headwater of the dry riverbed. Goethite releases Fe ions in acidic soils, as Fe are more soluble in those conditions [71].

4.2. Physico-Chemical Differences Between Pore Water from the Headwater and Mouth of the Dry Riverbed

The physico-chemical properties of pore water along the profile were analyzed to evaluate the potential impact of runoff infiltrating along the surface of the La Carrasquilla dry riverbed (Table 4). The increases in pH and EC with depth indicated potential changes in soil chemistry as water moves through deeper layers. The results from the headwater indicate that pore water adhere to the drinking water quality pH standards (6.50–9.50) [72]. However, EC values were categorized as not suitable for drinking water or irrigation (EC < 2.50 mS cm⁻¹) [72]. The high sulfate concentration found could be influenced by the mining activity, which generated large quantities of waste materials, where the oxidized materials contain significant amounts of water-soluble secondary sulfate minerals [73]. In addition, the Cartagena-La Unión mining district hosts rocks of sulfide mineralization mainly limestone and dolomite (CaMg(CO₃)₂) [74]. According to WHO [72], Mg²⁺ and SO₄²⁻ exhibited values 13.6 and 33.4 times higher than the limits, suggesting an accumulation of these ions in the deeper layers of the profile.

At the mouth of the dry riverbed, L2 presented the highest EC, whose values were above the maximum established by WHO [72] (EC < 2.50 mS cm⁻¹). According to the reference values proposed by WHO [72], the mean Cl⁻ and Na⁺ concentrations were 6.84 and 2.22 times higher than the acceptable limits. In some coastal areas, the groundwater has a direct connection to the seawater, which can lead to an increase in NaCl content in the groundwater, and subsequently, along the soil profile [75]. Similarly, the distance from the tailing’s deposits could influence the concentration of sulfates, which was several times higher in the headwater than in the mouth.

In the headwater, only Mn mean concentration surpassed the guideline values by WHO [72] along the profile (Table 4). This could be related to the formation of stable compounds on the other metals, while Cd and Mn were more soluble during the oxidation process on the sulfide minerals. The mineral deposits parageneses in Sierra de Cartagena-La Unión are formed by carbonate minerals like siderite with Zn- and Mn-bearing varieties. Additionally, the riverbed outlets had a significant soluble fraction of Mn, Ni, Cu, Zn, As, Cd, and Pb [35]. The MEI was determined to assess the overall quality of pore water in the headwater concerning metal(loid) concentrations. Again, Mn was the only metal with MEI values above 1 in all the layers. Clémence et al. [75] studied pore water in mine tailing ponds from the mining district and reported that Mn was mainly a free ion and complex with sulfate.

Alcolea [35] studied various riverbeds in the Cartagena-La Unión mining district and found that runoff water exhibited strong spatial variability. Additionally, he pointed out that this variability increased with distance from the abandoned mine area, regardless of the drainage basin characteristics of the riverbeds. Similar to the headwater pore water, the only metal(loid)s that surpassed the guideline values by WHO [72] along the profile in the mouth was Mn, 1.73 times higher. Nevertheless, the Mn concentration at the mouth was lower than that at the headwater, with the highest values in L3, which also corresponded with the highest concentration in the headwater. In addition, L3 showed the highest clay content. Certainly, clay minerals can adsorb and desorb Mn depending on pH and other soil conditions [55]. Along the soil profile at the headwater and mouth, Mn was mainly bound to F3 (Mn-(oxy) hydroxides). The formation of oxyhydroxides, through the oxidation of sulfide minerals increases metal(loid)s’ solubility and facilitates their dispersion [47].

4.3. Effect of Torrential Rain Events on Physico-Chemical Characteristics of Sediments

During the rain event in March 2022, in the headwater, the sediments’ pH ranged from slightly alkaline to very slightly saline [29] (Table 5). Calcium and sulfates were the main ions, whose concentrations were lower than those reported in soils (Table 1), which could be due to that, over time, in the absence of active water flow, ions like Ca²⁺ and SO₄²⁻ may precipitate and accumulate in the soil matrix [76]. The lower amount of total nitrogen (TN) and total sulfur (TS) in the sediments compared to the soil could be associated with the decrease in the OC content, which is a major source of nitrogen in the soil, especially on the top layer (Table 1). In addition, Kour et al. [77] studied the correlation of soil sulfur forms with the physico-chemical properties and found increases in TS content in soils associated with greater clay fractions and OC contents. In contrast, at the mouth of the dry riverbed, the pH of the sediments ranged from moderately alkaline to strongly alkaline, being no saline [29]. Also, calcium and sulfates were the main ions at the mouth, whose concentrations were similar to those reported in the topsoil (Table 1), but compared to L2, they were 3.28 times lower. These results suggested that the higher presence of clay in subsurface layers enhanced the ion exchange capacity and provided more surfaces for ion adsorption and precipitation, leading to higher concentrations of these ions. The lower percentage of TS in the sediment at the mouth could be related to the absence of pyrite (FeS2), sphalerite (ZnS), and galena (PbS) in this part of the dry riverbed.

At the headwater, lower Pb, Cd, and Zn concentrations and RI values in sediments compared with soils were reported (Table 6 and Figure 3b), indicating that the runoff particles downstream (mainly sand) generate less ecological risk than the soils. Cuevas et al. [19] reported from the headwater of La Carrasquilla dry riverbed values with the highest individual ecological risk for Cd and Pb on topsoil samples. The concentrations of metals in the sediment from the mouth were lower than those from the headwater, with decreases of As (94.1%), Cd (90.3%), Zn (88.6%), Fe (87.7%), Mn (84.1%), Pb (78.3%), Cu (76.6%), Cr (34.0%), and Ni (20.9%), suggesting a diluting effect on the metal(loid) concentrations by the time the sediment reaches the mouth. Alcolea [35] indicated that the distribution of trace metals is influenced by the physico-chemical weathering of mining and metallurgical wastes, along with the oxidation of metallic sulfides connected to the Pb–Zn ores, which extends to processes of transport, dispersion, and deposition. PLIs and RIs were high [37,53] but significantly lower than those reported in the headwater.

At the headwater, an important reduction of the Pb bound to carbonates in sediments compared to soils was reported, from 24.4% to 4.14%, which could be associated with the difference in the finer grained silt and clay percentage, which can cement the secondary minerals such as carbonates [78]. Pb is often preferentially bound to Fe/Mn hydrous oxides, due to the pronounced adsorption and coprecipitation processes [79]. In contrast, As showed the same behavior in sediment and soils, which is, according to Gomez-Ros et al. [80], who studied topsoil from the Cartagena-La Unión mining area, because As mostly binds to mineral lattices or as part of the clays. At the mouth, Cd and Pb showed the same dominant fractions exhibited in the sediment from the headwater and the soil profile of the mouth, where the main fraction was F3 (reducible). The Fe–Mn oxyhydroxides are important in binding Cd, driven by electrostatic forces as well as by specific adsorption and co-precipitation processes [81]. In addition, at neutral to slightly alkaline pH, Pb tends to form less soluble species and can preferentially bind to Fe/Mn oxides. García et al. [82] studied soils and sediments collected from an old mining area in Cartagena-La Unión and found Pb mostly present in the reducible fraction (47.9%) of the soils.

Similar mineralogy was found in sediments than soils at the headwater, suggesting a similar source material from which the minerals derive (Supplementary Material-Table S7). Gonzalez-Fernandez et al. [48] examined the mineralogical composition of the sediment in the El Beal dry riverbed (Cartagena-La Unión mining area) and found that quartz, gypsum, calcite dolomite, chlorite, illite, kaolinite, and jarosite were the main minerals. The mineralogy composition of the sediment at the mouth was, according to Martín et al. [83], who indicated that the mineralogy of the Cartagena-La Unión mining district, characterized by quartz (46%), muscovite (21%) calcite (11%), dolomite (4.5%), gypsum (1%), chlorite (1.7%), goethite (0.6%), and jarosite (0.1%).

4.4. Effect of Torrential Rain Event on Physico-Chemical Characteristics of Runoff Water

The topography, drainage structure, and surface water flow patterns of each watercourse are unique [84]. The runoff water exhibited a 9.0% reduction in pH compared to pore water, while spatial analysis in the headwater showed that the mean pH remained within the range the World Health Organization guidelines for drinking water recommend (6.50–9.50) [72] (Table 7). However, electrical conductivity (EC) in the runoff water was significantly reduced, being 3.28 times lower than in pore water. Moreover, EC values in both runoff and pore water exceeded the WHO threshold for drinking water suitability (EC < 2.50 mS cm⁻¹), indicating an elevated ionic content. This pattern was also reflected in ion concentrations, particularly for SO₄²⁻, the dominant anion, 3.70 times lower in the runoff water than in the pore water. The reduced sulfate concentration in the runoff water can be explained by the rapid flow of water across the soil surface, especially during and following precipitation events, which limit the interaction time between the water and soil or mining wastes. Consequently, the dissolution and leaching of sulfates are less pronounced in runoff water compared to pore water. Despite the lower concentrations of SO₄²⁻ in the runoff water, the levels still exceeded the WHO guideline of 500 mg L⁻¹, highlighting potential environmental concerns. Similarly, the main cation, Ca²⁺, showed a concentration above the WHO recommendation, 200 mg L⁻¹. Alcolea [35] studied La Carrasquilla dry riverbed runoff activity, on tailing dams’ erosion, reporting concentrations for SO₄²⁻ and Ca²⁺, which comprehend those found in the headwater. The concentrations of metals that exceeded WHO guidelines several times were Cd, Mn, and Zn. Compared to the results by Alcolea [35], only Zn surpassed the reference values. The comparison of concentrations between the runoff water and pore water for Pb, which showed similar values in pore water, suggests that Pb may be relatively stable in the environment and not significantly affected by the hydrological processes occurring in the dry riverbed. Oppositely, Cd and Zn concentrations in the runoff water were 325 and 215 times higher, respectively, compared to the pore water (Table 4 and Table 7). This significant increase in Cd and Zn levels in the runoff water is likely attributed to the desorption of these metals from nearby contaminated sources, a process potentially facilitated by the lower pH of the runoff water.

At the mouth of the dry riverbed, compared to the pore water along the profile, the runoff water displayed a similar pH, which fell within the acceptable range proposed by WHO (6.50–9.50). However, the runoff water’s electrical conductivity (EC) was 2.49 times lower than the pore water. Despite this, EC still exceeded the threshold of the WHO guideline for drinking water, which has a maximum allowable value of 2.50 mS cm⁻¹. Additionally, the concentration of Cl⁻ in the runoff water was 3.08 times lower than that found in the pore water along the profile. However, both Cl⁻ and Na⁺ concentrations in the runoff water were significantly higher than the standards established by WHO [72]. The transition from the headwater to the mouth of the river highlights notable changes in metal(loid) concentrations. Higher concentrations of As, Cr, and Cu at the mouth compared to the headwater indicate possible accumulation as the water travels downstream. This could be due to sedimentation processes, where these metals are mobilized from the surrounding environment and concentrated at the mouth. Furthermore, Fe and Pb below detection limits suggest a complex interplay of factors influencing metal transport and deposition.

5. Conclusions

The mineralogical composition and contamination indices observed in this study indicate significant anthropogenic influence, likely from mining activities, as the primary source of metal(loid) pollution in the La Carrasquilla dry riverbed. In the headwater and the mouth along the soil profile the metal(loid)s with the highest mean pollution index were Cd, Pb, and Zn. In addition, for the metal(loid)s with Cf > 1, only As concentration showed a strong spatial variability while depth increased on both sites. However, in the headwater and the mouth, the three different layers sampled were categorized as contaminated by metal(loid) PLI > 1. The PLIs corresponding to the sediment presented similar values to those from L1 (30 cm) and L2 (60 cm) in the soil profile on both sites.

As, Cd, Pb, and Zn showed similar binding forms on the sequential extraction analysis in the sediment and along the soil profile. The main fraction for As, Pb, and Zn corresponded to the residual fraction, while Cd was mostly bound to the reducible fraction. In addition, on both sites, the sediment and soil profile shared the same main minerals quartz, muscovite, clinochlore, and montmorillonite.

At the headwater and mouth, pore water showed higher concentrations of sulfate, Ca, Na, Cl, Mg, and Mn and higher salinity than acceptable limits for drinking water or irrigation established by World Health Organization. Nevertheless, in the headwater, runoff water exhibited high levels of the metal(loid) evaluation index (MEI) for Cd and Zn. Those metal(loid)s with concentrations several times higher than the limits established by WHO could potentially represent an environmental threat.