Investigating Geogenic Sources of Selenium in Shallow Groundwaters of Las Vegas Valley, USA

doi:10.21203/rs.3.rs-4367183/v1

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Investigating Geogenic Sources of Selenium in Shallow Groundwaters of Las Vegas Valley, USA

https://doi.org/10.21203/rs.3.rs-4367183/v1

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Selenium concentrations above Environmental Protection Agency safe levels are of potential concern in various parts of the Las Vegas Valley in both water and sediment media. Previous studies suggest that the source of elevated selenium in the Valley is possibly resurfacing groundwater. Shallow groundwater flows into Las Vegas Wash wetlands and therefore has important environmental implications for surface water quality and aquatic life. The objective of this study was to identify the source of selenium in the shallow groundwater of the Las Vegas Valley through a detailed geochemical analysis. A comparison of major anions and cations concentrations and the 4 trace oxyanions (Se, B, As, and Mo) in the Quaternary alluvium (Qa) zone versus Quaternary to Tertiary (QTs) zone wells show that Qa wells consistently exhibit higher concentrations of all the mentioned parameters than QTs wells. The mean Qa concentrations of the major ions and trace oxyanions ranged between 130–728% higher than the mean QTs concentrations. Study results suggest that selenium concentrations in the shallow groundwater in the Qa zone were highly correlated (p < 0.01) with the major ions: Na⁺ (r = 0.88), K⁺ (r = 0.87), SO₄²⁻ (r = 0.86), NO₃⁻-N (r = 0.74), and TDS (r = 0.84), and EC (r = 0.87) indicating a common source genesis. However, in the QTs zone, correlations among Se and the mentioned parameters were not significant. Principal component analysis performed on the major ions, EC, TDS, and Se of Qa and QTs showed that Se was one of the influencing parameters in the first principal component of Qa; however, in QTs, Se did not contribute to the variations of the first principal component. Pearson correlations further corroborated that salinity is associated with Se, B, and As in the Qa zone and only associated with B in the QTs zone. Overall, many more significant associations of Se with water quality parameters were determined in the Qa than in the older QTs formations, indicating that geological processes and formations’ mineralogy have influenced the mentioned associations.

Selenium

Shallow groundwater

Water quality

Geology formations

Las Vegas Valley

Principal Component Analysis

Geochemical Analysis

Heavy Metals

Groundwater Pollution

1.1 Selenium hazard profile and occurrence in the Las Vegas Valley

Selenium mobilization into the aqueous phase leads to potential bioaccumulation in the food chain in vegetation and animal tissues and may cause dietary selenium exposure to aquatic organisms and possible biomagnification in their predators (Devitt et al., 2014; Ehsani et al., 2021; Zhang er al., 2024). Elevated concentrations of selenium in soils and sediments in many areas of the USA, especially the western part of the USA, have been documented (Deveral and Milliard, 1988; Devitt et al., 2014; Naftz et al., 1993; Smith and Guitjens, 1998). Human activities such as landscape irrigation can accelerate the mobilization of selenium from soils and sediments with elevated concentrations (Devitt et al., 2014; Ehsani et al., 2021). According to a study by Seiler et al. (1999), about 10,620 square kilometers of land in the western USA is at risk of selenium contamination due to irrigation. Elevated selenium concentrations in the food chain in Kesterson Reservoir have been extensively studied (Lemly 2002; Rodriguez et al. 2005; Devitt et al., 2014). A high occurrence of deformity and mortality of waterfowl at Kesterson National Wildlife Refuge in the western San Joaquin Valley, CA has been documented due to elevated concentration of selenium in agricultural drain water (Deverel and Millard, 1988; U.S. Bureau of Reclamation. 1984). The Environmental Protection Agency (EPA) has defined a hazard profile for total selenium concentrations (USEPA, 2023). The hazard profile categorizes the hazard of selenium concentration regarding the potential of biomagnification of selenium in the food chain from water, thus causing potential toxicity hazards to fish and birds. The criteria for monthly average exposure of selenium concentration in the water column for lentic and lotic aquatic systems are 1.5 µg/L, and 3.1 µg/L, respectively (USEPA, 2023). The hazard profile for selenium in sediments is: high, > 4 µg/g; moderate, 3–4 µg/g; low, 2–3 µg/g; minimal, 1–2 µg/g; no hazard, < 1 µg/g (Lemly, 1996).

Some measured concentrations of selenium in the Las Vegas Wash (Wash) have exceeded the USEPA aquatic life hazard criteria for Se (Cizdziel and Zhou 2005). According to the (Cizdziel and Zhou 2005) study in 2002-3, the primary source of the high concentration of selenium in the Las Vegas Valley (Valley) is resurfacing groundwater. Selenium-laden groundwater is primarily transported in tributaries to the Wash, becoming diluted by the treated effluent discharges within the main Wash channel (Briggs and Abusaba 2008). Quarterly samples gathered from strategic locations along the Wash for the sediment and monthly for the water column suggested a direct correlation between the concentration of total selenium in the water column and Wash sediments (Cizdziel and Zhou 2005). As a result, a monitoring program was developed and conducted by the Las Vegas Wash Coordination Committee in 2006 to measure the concentration of contaminants of concern in different media along the Wash and its tributaries. (Papelis 2007). The acid-leachable selenium concentration in the sediments ranged from 1.7 ppm in the Wash to 4.3 ppm (highly toxic) in one of the tributaries that flow to the Vegas (the Duck Creek) (Papelis 2007).

1.2 The Las Vegas Valley hydrology

The Las Vegas Valley is a naturally formed northwest-southeast trending structural basin that encompasses about 1,600 mi² in southern Nevada (Speck, 1985; Southern Nevada Water Authority, 2016). Surface water drains mostly toward the southeast through the Wash into Lake Mead. The Valley floor has a precipitation of around 10 cm (4 in) a year (Donovan and Katzer, 2000), mean evapotranspiration of 218 cm a year (86 in/year), and maximum evapotranspiration higher than 240 cm a year (94 in/year) (Dano, 2010). Because of the vertically and laterally discontinuous layers of clay, silt, gravel and caliche, and petrocalcic horizons, the aquifer system in the Valley is complex (Plume, 1989; Bernholtz, 1993; Morgan and Dettinger, 1996; Thiros et al., 2010; and Southern Nevada Water Authority, 2016).Shallow groundwater flows within the top 30 feet of the land surface. Due to either evapotranspiration, upwelling groundwater from the underlying Principal Aquifer, the infiltration of rainfall, irrigation, or septic system effluent, the chemical constituents in the soils and sediments of the Valley might dissolve and contribute to the poor water quality detected in portions of the shallow groundwater system (Dano, 2010; Southern Nevada Water Authority, 2016). The dissolution is especially more likely when the materials are volcanic and evaporites (Southern Nevada Water Authority, 2016). Shallow groundwater is discharged to the tributaries of the Wash through many small springs and seeps (Southern Nevada Water Authority, 2016; Dano, 2010). The Wash is host to various types of plants and animals and is an important ecosystem in Southern Nevada. Therefore, the inflows to the Wash are of particular interest as they affect the water quality of the Wash (Las Vegas Valley Water District, 2017).

1.3 Formation of soil that is high in soluble minerals and its relevance to selenium accumulation

The formation of soluble salts takes place in several steps. First, chemical weathering leads to the release of water-soluble minerals to form salt solutions. Then, the salt solutions move through sediment, soil, groundwater, and surface water. Next, as water is lost to evaporation, secondary deposits precipitate from the salt solution. In the last step, accumulation occurs after repeated deposition events (Petrukhin, 1993; Karakouzian et al., 1996). Salt accumulation occurs more often in semi-arid and arid regions (Karakouzian et al., 1996). The salts that are found most commonly in soluble soils of arid regions are calcium (Ca^+ 2), magnesium (Mg^+ 2), and sodium (Na⁺) cations in combination with sulfate (SO₄ ^− 2), and chloride (Cl⁻) anions. The less common anions and cations that are present in minor amounts in soluble soils are carbonate (CO₃ ^− 2), bicarbonate (HCO₃ ^− 1), nitrate (NO₃ ^− 1), and phosphate (PO₄ ^− 3) anions, and potassium (K⁺) cation. In humid regions, rainfall causes the leaching of soluble salts and it transports them into groundwater or surface water; where they are ultimately transported to the ocean. However, in arid regions soluble salts usually are not transported far because of low precipitation and high evaporation. Upward movement the seasonal capillary flow of groundwater to the surface (Buck et al., 2006; Karakouzian et al., 1996). The soluble salts can also be formed in subsurface layers because of evaporation from relict water tables (Buck et al., 2006). In arid and semi-arid regions, horizontal petrocalcic horizons and clay sediments act as horizontal barriers and cause further accumulation when evaporation occurs. The above-mentioned factors result in the accumulation of salts in the soil matrix and surface water on a regional scale (Karakouzian et al., 1996).

1.4 Research objective

The objective of this study is to understand selenium concentration and distribution regarding the chemical constituents and geology of the shallow groundwater wells in the Las Vegas Valley. To date, there have not been any studies to determine the origins of selenium in Las Vegas Valley shallow groundwater.

2.1 Shallow groundwater water quality data

The wells in the study are part of a shallow groundwater monitoring network maintained by Southern Nevada Water Authority (SNWA). Data collected by SNWA from existing representative shallow monitoring wells included well location, wellhead elevation, well depth, depth to water, well diameter; water quality parameters such as field temperature, electrical conductivity (EC), dissolved oxygen (DO), pH, Alkalinity-total, and total dissolved solids (TDS). Other parameters included: Na⁺, Mg²⁺, K⁺, Ca²⁺, Cl⁻, SO₄²⁻, NO₃⁻-N, F⁻, Se, As, B and Mo.

A total of 42 monitoring wells and 24 physicochemical variables were studied in this research. The date of the sampling of the wells covered the period from 1/31/2006 to 10/12/2015 (Southern Nevada Water Authority, 2016).

2.2 Geological framework

The four quadrangles of Las Vegas Geology maps were obtained from the Nevada Bureau of Mines and Geology (NBMG) (Table 1). The geographic coordinate system of the four maps is 1927 North American datum, east zone 1000-meter Universal Transverse Mercator grid ticks, zone 11.

Table 1

– Map names and Latitude and longitude of the four quadrangles of the Las Vegas Valley geology maps
Map name	Northeast corner	Northwest corner	southeast corner	southwest corner	Map reference
Las Vegas NE quadrangle geologic map, map 3C	36° 15', and 115° 00'	36° 15’, and 115° 07' 30"	36° 07’ 30”, and 115° 00'	36° 07’ 30”, and 115° 07' 30"	(Matti et al., 1993)
Las Vegas NW quadrangle geologic map, map 3Dg	36° 15', and 115° 07' 30"	36° 15’, and 115° 15'	36° 07’ 30”, and 115° 07' 30"	36° 07’ 30”, and 115° 15'	(Matti et al., 1987)
Las Vegas SE Folio Geologic Map, Environmental series	36° 07’ 30”, and 115° 00'	36° 07’ 30”, and 115° 07' 30"	36° 00’, and 115° 00'	36° 00’, and 115° 07' 30"	(Bingler, 1977)
Las Vegas SW quadrangle geologic map, map 3Bg	36° 07’ 30”, and 115° 00'	36° 07’ 30”, and 115° 07' 30"	36° 00’, and 115° 00'	36° 00’, and 115° 07' 30"	(Matti and Bachhuber, 1985)

2.3 Methods

The following section discusses the methods used for interpreting and analyzing data necessary to examine the groundwater quality parameters from two distinct geological formations.

2.3.1 Regression analysis

Regression analysis was used to identify the linear correlations of water constituents in the shallow groundwater database for the Las Vegas Valley. The Pearson correlation coefficient is a common statistical assessment tool and it measures the strength of the linear relationship between paired data (Walpole et al., 2017). When Pearson correlation is 0 between two data, that indicates that the parameters have no linear correlation; however, it does not necessarily mean that there is no relationship between the variables (e.g. a quadratic relationship may exist between the variables) (Walpole et al., 2017). Therefore, subsequent analysis by scatter plots or PCA will provide more information about the association between variables.

The strength of the correlation using Evans, 1996 as a guide for the absolute value of r is as follows:

0.00-0.19: very weak
0.20–0.39: weak
0.40–0.59: moderate
0.60–0.79: strong
0.80–1.00: very strong

2.3.2 Significance test of the correlation coefficient

To examine the reliability of the linear model, the Student’s t-test of the “significance of the correlation coefficient” is performed. “The sample correlation coefficient, r, is an estimate of the unknown population correlation coefficient (Walpole et al., 2017). The hypothesis test determines whether the value of the population correlation coefficient, ρ, is "close to zero" or "significantly different from zero" and that is decided by using the r and the sample size, n. The null hypothesis (H0) is true when the population correlation coefficient is not significantly different from zero (ρ = 0), meaning that there is not a significant correlation between the x and y variables in the population. The alternate hypothesis (Ha) is true when the population correlation coefficient (ρ ≠ 0) is significantly different from zero, meaning that “there is a significant linear correlation between x and y in the population”. One of the methods of testing the hypothesis is using the p-value. This method was used in this study by IBM SPSS Statistics software version 25, 2019 (Walpole et al., 2017).

2.3.3 Principal components analysis (PCA)

IBM SPSS Statistics software version 25 (IBM, 2019) was used to perform PCA on the database. Patterns in data of high dimensions can be difficult to find, and PCA is especially useful for finding patterns in data with higher than three numbers of dimensions when the luxury of graphical representation of data is not available. Once patterns are identified among the data, the number of dimensions can be reduced to their most common variable components without losing much information (Smith, 2002; Dano, 2010; Everitt and Dunn, 1992).

PCA has diverse applications. It is commonly used when working with large and complex trace metals data sets (Kreamer et al., 1996; Stetzenbach et al., 2001; Dano, 2010). In this study, PCA was used to identify the associations of selenium and various chemical constituents of the shallow groundwater in the Las Vegas Valley shallow groundwater database in two geology formations.

2.3.4 Mapping

An ESRI commercial product called ArcMap™, version 10.5.1, was used for GIS visualization of different maps and parameters in this research.

The four quadrangles of Las Vegas Geology maps obtained from NBMG were georeferenced using the maps’ reference information. Shallow groundwater well locations were overlaid on the four quadrangle maps by making point shapefiles of the well coordinates using ArcMap™ 10.5.1 to find their corresponding geology information.

2.3.5 Hydrogeochemical Analysis

Piper diagram were used to depict the characteristics and chemical composition of groundwater, using Microsoft Excel, Microsoft Office 365. Piper (1994) introduced a graphical approach to make water chemistry and its processes clearer. The principle behind the Piper diagram is the balance of charges among dissolved salts, employing separate ternary diagrams for both cations and anions and creating a diamond-shaped diagram from these ternary diagrams' linear combination. The extremities of the ternary diagrams represent specific ions: Ca2+, Mg2+, and Na + + K + for cations; and HCO3- + CO32-, Cl-, and SO42- for anions. These diagrams are essential for identifying and understanding hydrochemical facies, which reveal the chemical status and geological activities (Sadashivaiah et al., 2008).

3.1 Pearson correlation and significance tests

Data from 42 of the SNWA monitoring wells were evaluated in this research. Se concentrations in 41 of the 42 well samples were higher than EPA threshold levels for lentic systems (1.5 µg/L). Of the 41 wells with Se concentrations above EPA threshold levels for lentic systems (1.5 µg/L), 24% (10) of the wells were located in the Quaternary consolidated sediments zone (QTs) and 42% (17) of the wells were in the Quaternary alluvium zone (Qa). Therefore, 66% of the high selenium concentration measurements were recorded in wells that were located in either Qa or QTs zones (Figs. 1 through 4). As Qa and QTs are the dominant geology formations in the Valley, the analyses in this study are performed on the water quality data obtained from the Qa and QTs zones.

The following descriptions apply to the Qa and QTs zones:

Quaternary geology is a term that refers to the most recent 2.6 million years of geology development, extending up to the present day (Zagwijn, 1974). Qa zone in the Valley: Quaternary active alluvium of the Valley is “pink to pale-brown fine sand to pebble to cobble gravel occurring in incised, active stream channels and on between-channel alluvial flats; unconsolidated to locally-cemented by petrocalcic carbonate. Volcanic rock fragments are present in the southern part. Detrital gypsum is locally an important component” (Bingler, 1977; Matti and Bachhuber, 1985; Matti et al., 1987; Matti et al., 1993).

Tertiary is a geologic term that refers to the geologic period from 66 million to 2.6 million years ago (Bohor et al., 1987). QTs zone in the Valley: Quaternary to Tertiary consolidated sediments of the Valley is “white and light-gray to light and pale-red fine sand interstratified with silt, pebbly sand, and pebble to small cobble gravel; moderately- to well-consolidated to strongly-cemented. Layers of petrocalcic carbonate are common and have variable textures and fabrics. Surface exposures at the QTs zone are locally capped by a resistant petrocalcic crust. Fibrous and encrusting gypsum are common” (Bingler, 1977; Matti and Bachhuber, 1985; Matti et al., 1987; Matti et al., 1993).

The Pearson correlation coefficients, significance test value of the major ions, field chemistry, and Se parameters in the shallow groundwater of the two geology zones of Qa and QTs are provided in Table 2. The Pearson correlation coefficients larger than r > 0.6 and significant at the p < 0.01 or p < 0.05 level (2-tailed) are colored gray in Table 2.

A comparison between the correlations in the two geologic zones shows differences that relate to the effect of the geologic zones. The following major differences were noticed in the Pearson correlation analysis between the two geologic zones:

The correlations between total depth and Na⁺(0.62), K⁺ (0.63), SO₄^2- (0.65), and Se (0.79) in the Qa zone were significant at the p = 0.01 level (2-tailed); however, in the QTs zone, the correlation between total depth was not significant with any of the ions. Deeper wells are generally less vulnerable to sewage or surface contamination sources than shallower wells. However, in deeper wells, groundwater is more likely to contain minerals from bedrock than is water in the shallower wells and deposits. Therefore, the differences in the correlation between total depth and ions in the two geology zones can be attributed to the fact that higher concentrations of minerals in the Qa zone are dissolved and released into groundwater as depth increases than in QTs zones (USGS, 2022)
The correlations between well diameter and Na⁺ (0.81), K⁺(0.81), Cl^- (0.71), SO₄^2- (0.83), NO₃^- -N (0.73), EC (0.83), TDS (0.79) and Se (0.95) in the Qa zone were significant at the 0.01 level (2-tailed); however, in the QTs zone, the correlation between diameter and the mentioned parameters was not significant with any of the ions. Wells with higher diameters are known to cause erosion of the soil in the vicinity of the casing of the well and soil erosion might affect the chemical composition of the groundwater. A significant Pearson correlation between well diameter and mentioned parameters in the Qa zone may suggest a higher concentration of minerals in the Qa zone is released into groundwater as the result of soil erosion as the diameter increases (Chapuis and Sabourin, 1989).
In the Qa zone, the correlation between Ca²⁺ and SO₄^2- (0.69) was significant at the 0.01 level (2-tailed); however, no significant correlation (r = 0.42) was found between the two parameters in the QTs zone. The NBMG maps of four quadrangles of the Valley show that detrital gypsum (CaSO₄.2H₂O) is a major component of the geology, locally, in the Qa zone, and in the QTs zone, encrusting gypsum is common. As gypsum (a mineral containing calcium and sulfate) is present in both geology zones, the lack of correlation between Ca²⁺ and SO₄^2- in the QTs combined with the lower concentrations of the mentioned ions in the QTs zone (Ca²⁺ in Qa is 130% of QTs, SO₄^2- in Qa is 206% of QT) may indicate that the dissolution of minerals containing both ions occurs less in the QTs zone than the Qa zone.
In the Qa zone, the correlation between NO₃^--N and Na, K, Cl^- was significant at the 0.01 level (2-tailed); however, no significant correlation (r = 0.07) was found between the two parameters in the QTs zone. No interpretation regarding geology influence can be made here with confidence as the source of nitrate contamination is commonly anthropogenic activities such as septic tanks, municipal or domestic sewage, nitrogenous waste, and irrigation (Yadav et al., 2018).
In the Qa zone, the correlation between Se and Na (r = 0.88), K (r = 0.87), SO₄^2-(r = 0.86), NO₃^—N (r = 0.74), EC (r = 0.87), and TDS (r = 0.84), was significant at the 0.01 level (2-tailed); however, no significant correlation was found between Se and the mentioned parameters in the QTs zone. The significant correlations found in this regression analysis between Se and Na⁺, K⁺, SO₄^2- indicate that soluble salt concentrations (consisting of the mentioned ions) are showing to be good proxies for selenium concentration in the Valley. Se may also be present as a substitution in the sulfate ion in the following soluble minerals found in Buck et al., 2006 study: Gypsum (CaSO₄•2H₂O), Mirabilite (Na₂SO₄•10H₂O), Thenardite (Na₂SO₄), Eugsterite (Na₄Ca(SO₄)₃•2H₂O), Kainite (KMgClSO₄ •3H₂O). The accumulation of sulfate minerals in arid and semi-arid regions is prevalent in all regions of the world (Buck et al., 2006). Selenium and sulfur are especially known to behave similarly and form similar compounds (Price, 2013; Floor, 2011). According to previously mentioned literature, selenium is mostly found within sulfide mineral deposits (Price, 2013). Selenium mobilization occurs due to weathering of seleniferous rocks or the leaching of seleniferous soils (Price, 2013).

From the above comparisons of correlations in the Qa zone versus QTs zone, it can be concluded that in the Qa zone Se concentration is significantly associated with major ions such as Na⁺, K⁺, SO₄²⁻, NO₃⁻-N, and overall salinity descriptors (EC and TDS). In contrast, in the QTs zone, Se is not significantly associated with the mentioned parameters. The differences in the correlations between the two zones may be due to the fact that the water-soluble minerals in the soil/sediments of the Qa zone are more prone to dissolution than the soil/sediments in the QTs zone. The QTs zone consists of materials that are moderately to well-consolidated to strongly cemented, whereas in Qa soils/sediments are unconsolidated to locally cemented (Bingler, 1977; Matti and Bachhuber, 1985; Matti et al., 1987; Matti et al., 1993). Another possibility is that the QTs zone may have already been leached of the most soluble salts and therefore the correlations that hold in the Qa zone do not hold up in the QTs. QTs belongs to older geology (Bohor et al., 1987), and more water over time has moved through the QTs sediments.

3.2 Pearson correlations and significance test among trace elements and salinity

Regressions of mobile trace elements (Se, As, B, and Mo) concentrations on groundwater salinity using EC in two geologic zones were studied to further analyze and explain the processes that affect or control the distribution and concentrations of mobile inorganic trace elements. Correlations of EC with B, Mo, Se, and As were evaluated by analysis of Pearson correlations (Table 3).

In the Qa alluvial geologic zone, correlations among EC and Se, B, and As (likely to be oxyanions) are significant at the p < 0.01 level (2-tailed). Pearson correlations of EC and Se, B, Mo, and As are r = 0.87, 0.92, 0.45 and 0.77 respectively. In the QTs geologic zone, only the Pearson correlation between electrical conductivity and B (r = 0.93) is significant at the 0.01 level (2-tailed). No significant correlations were found between EC and the other elements (Se, Mo, and As).

Table 3

Pearson correlations for EC and mobile trace elements
		Qa _ EC	QTs _ EC
Se (µg/L)	Pearson Correlation	.872^**	0.427
Se (µg/L)	Sig. (2-tailed)	0.000	0.167
B (µg/L)	Pearson Correlation	.920^**	.931^**
B (µg/L)	Sig. (2-tailed)	0.000	0.000
Mo (µg/L)	Pearson Correlation	0.448	0.387
Mo (µg/L)	Sig. (2-tailed)	0.062	0.214
As (µg/L)	Pearson Correlation	.766^**	-0.215
As (µg/L)	Sig. (2-tailed)	0.000	0.501

** Correlation is significant at the 0.01 level (2-tailed).

The differences among the Pearson correlations between these two zones can be explained by the geologic origin of Se, B, As, and Mo and the presence of soluble salts. As the focus of this study is Se, only Se and its geologic origins will be discussed. The likely correlation between Se and EC in the Qa zone is likely because Se is being held in the sodium, potassium, and sulfate minerals and they are controlling EC in the Qa zone. Such correlation does not exist in QTs.

3.3 Major anions and cations, chemical properties, and trace elements in Qa vs QTs

A comparison among major anions and cations and the 4 trace oxyanions in Qa versus QTs shows that the Qa zone wells consistently exhibit higher concentrations of the mentioned parameters than wells in QTs. In summary form, comparing the major ion averages:

Na⁺ in Qa is 357% of QTs,
Mg²⁺ in Qa is 157% of QTs,
K⁺ in Qa is 289% of QTs,
Ca²⁺ in Qa is 130% of QTs,
Cl^- in Qa is 237% of QTs,
SO₄^2- in Qa is 206% of QTs,
NO₃^--N is 214% of QTs, and
F^- is 198% of QTs.

Figure 5 and Fig. 6 visually represent the average concentrations of the major ions and 4 trace elements respectively, in Qa versus QTs. The average concentration of all major ions and the 4 trace elements are consistently higher in Qa than in QTs. Higher mean values of major ions and trace elements in Qa compared to QTs might be due to the fact that dissolution of ions in the Qa geologic zone occurs more than in the QTs zone and therefore, higher masses of ions and trace elements are carried into the shallow groundwater in the Qa zone than in the QTs zone; it could also mean that the QTs zone is more leached and no longer contains the highly soluble salt minerals and trace elements.

Figure 9 demonstrates the differences in the statistical measures of Se between the two Qa and QTs zone.

3.4 Principal Component Analysis

3.4.1 PCA on shallow groundwater of the Valley

For principal component analysis (PCA), non-detectable values of the analytes were assigned random values between zero and the detection limit per the method used in Deverel and Millard, 1988.

The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy (IBM, 2019) is a test that indicates whether or not a PCA (factor analysis) may be useful with the data set. If the KMO value is less than 0.50, the results of factor analysis or PCA will not be useful.

Bartlett’s test of sphericity (IBM, 2019) evaluates the hypothesis that the correlation matrix is an identity matrix that would indicate that the database parameters are not related and therefore are not a good fit for structure and pattern detection. Small values of Bartlett’s test, a significance level of less than 0.05, show that a factor analysis is useful for the data.

3.4.2 Comparing PCA in the Qa and QTs zone

PCA analysis was separately performed on the major anions and cations, TDS, EC, and Se in Quaternary alluvium (Qa) and Quaternary to Tertiary sediments zone (QTs).

Table 4 and Table 6 are the KMO and Bartlett’s test of sphericity performed on the parameters of the Qa and QTs to test whether or not the PCA is useful on the dataset; they show that KMO values are higher than 0.50 and significance values are less than 0.05, indicating that the PCA was useful for both the Qa and QTs zone data. The results of the loadings of the eigenvectors of the first two principal components in the Qa and QTs zones are shown in Table 5 and Table 7, respectively.

In Tables 5 and 7, gray shading shows positive associations > 0.50 and negative associations < -0.50.

In the first eigenvector of the PCA component 1 (PC1), in both the Qa and QTs zone, Na⁺, K⁺, Cl⁻, SO₄²⁻, TDS and EC have significant loadings.

In the Qa zone, Ca²⁺, NO₃⁻-N, and Se all significantly contribute to the PC1 eigenvector; however, in the QTs zone the mentioned ions and Se do not have significant loadings; Ca²⁺ has a moderate loading of 0.48 and Se has a moderate loading of 0.47, NO₃⁻-N loading is insignificant (-0.14). In the QTs zone, Mg²⁺, and F⁻, contribute significantly to loading PC. However, in the Qa zone, the same two ions do not have significant loadings. Mg²⁺ loading is moderate at 0.47 and F⁻ loading is insignificant.

PC1 differences between the two zones might indicate the association of minerals containing Ca²⁺, NO₃⁻-N, and Se in the Qa zone than in the QTs zone and the stronger association of minerals that contain Mg²⁺ and F⁻ in the QTs zone than in Qa zone.

In PC2 of the Qa zone, the significant loadings are Ca²⁺ (0.78) and NO₃⁻-N, (-0.66). This indicates that PC2 of the Qa zone is mainly influenced by the mentioned two ions. The same ions control PC2 of the QTs zone but with different loading values: Ca²⁺ (-0.58) and NO₃⁻-N, (-0.78).

Table 4

KMO and Bartlett's Test for SNWA well data in the Qa zone
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.	0.720
Bartlett's Test of Sphericity Sig.	0.000

Table 5

Principal Component Matrix for Qa zone
	Component
	1	2
Na+	0.934	-0.021
Mg²⁺	0.473	0.439
K⁺	0.897	-0.078
Ca²⁺	0.511	0.782
Cl⁻	0.975	-0.070
SO₄²⁻	0.955	0.180
NO₃⁻N	0.645	-0.662
F⁻	0.043	0.449
TDS	0.981	0.116
Se	0.873	-0.411
EC	0.983	0.033

Table 6

KMO and Bartlett's Test for SNWA well data in the QTs zone
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		0.644
Bartlett's Test of Sphericity	Approx. Chi-Square	200.444
	Df	55
	Sig.	0.000

Table 7

Principal Component Matrix for the QTs zone
	Component
	1	2
Na⁺	0.980	0.064
Mg²⁺	0.755	-0.247
K⁺	0.953	0.039
Ca²⁺	0.483	-0.581
Cl⁻	0.942	0.259
SO₄²⁻	0.972	0.160
NO₃⁻N	-0.142	0.775
F⁻	0.626	-0.459
TDS	0.978	0.150
Se	0.471	0.073
EC	0.967	0.190

Hydrochemical facies

Hydrochemical facies characterize the unique groundwater environment with the lithologic framework, chemical processes, and hydrodynamic conditions influencing the rock-water interaction. The general groundwater chemistry and variation in hydrochemical facies can be understood by plotting major cation and anion concentrations on Piper's plot (Piper 1944). The major ions were used to draw general hydrochemical facies of two different formations (Fig. 10). The plot indicates that the majority of samples fall in CaCl₂ facies. In addition to this, the Qa samples also show Na-Cl facies while none of the samples from QTs qualifies for this field. One QTs sample shows Ca-HCO₃ facies, suggesting recent rainfall recharge with minimal mineralization. A wide variation in the chemical character of Qa water is observed where samples fall in Ca-Cl₂, CaMgCl_2, and Na-Cl types of waters.

The concentrations of Na and Cl in few samples of Qa are far greater than that of in QTs inferring greater role of rock weathering mechanism including evaporitic dissolution environment. The unique hydrochemical facies in groundwaters of Qa and QTs are acquired through variable degree of rock-water interactions. The Na versus Cl bivariate plot showcase two different mechanism, whilst at lower concentration both groundwater types behave similarly, but with increasing Na and Cl concentrations in Qa the samples shift towards the Na:Cl equi-line, indicating a common origin from rocks like halite and evaporite as confirmed in the geology of the study area. The exceptionally high Na concentration may originate from sewage effluent especially brine disposals. The samples occurring in Na-Cl type facies, apart from clear excess of Na and Cl, showcase an excess of NO₃ and SO₄, pointing towards an anthropogenic source.

4.1 Conclusions

In this study, an evaluation and characterization of the chemical constituents of shallow groundwater in regard to the corresponding geology formation was carried out to identify the potential sources of selenium in the Las Vegas Valley. Identifying sources of selenium can help resource managers come up with plans to mitigate the elevated selenium concentration in the Valley. The geological information in which the wells are located combined with significant correlations with major ions and PCA interpretations indicate that the geochemical processes that affect selenium concentration in the shallow groundwater of the Valley are mainly associated with geology in the vicinity of the well locations. The associations of Se with major ions, and salinity were much more significant in the Qa than in the QTs formations, indicating that water-soluble minerals in the soils of the Qa are more prone to dissolution than in the QTs zone or that the QTs zone is already leached of most of its soluble salts due to being an older geology formation.

4.2 Recommendations

Future research could include an additional sampling of soils in the vicinity of the shallow groundwater wells in different geologic areas combined with elution tests to determine the rate of dissolution of selenium and major ions (such as water-soluble sulfate) from those soils. This would help determine which locations and what geologic formations are causing more selenium to be leached or mobilized from the potential sources and will help resource managers come up with management plans for controlling the release of selenium in areas with high potential for selenium dissolution.
As mentioned in the literature review, soluble salts can also be formed in subsurface layers because of evaporation from relict water tables. In arid and semi-arid regions, horizontal petrocalcic horizons and clay sediments act as horizontal barriers and cause further accumulation when evaporation occurs. Further sampling of selenium and major ions in subsurface layers of the soil/sediments will provide more information about the distribution of selenium and major ions in the deeper soil/sediment levels and, determine if deeper layers of soil/sediments contain a higher concentration of salts and selenium.

This study was partially funded by Southern Nevada Water Authority.

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

SE, DJ, BB, and XZ contributed to the conceptualization and method. SE, DJ, VH, XZ, MK, and IA were involved in the statistical analysis of the research. SE wrote the main manuscript text. All authors reviewed the manuscript.

Availability of data and materials

The datasets analyzed during the current study are available from the corresponding author upon reasonable request.

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Table 2 is available in the Supplementary Files section.

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Investigating Geogenic Sources of Selenium in Shallow Groundwaters of Las Vegas Valley, USA

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Abstract

Figures

1. Introduction

1.1 Selenium hazard profile and occurrence in the Las Vegas Valley

1.2 The Las Vegas Valley hydrology

1.3 Formation of soil that is high in soluble minerals and its relevance to selenium accumulation

1.4 Research objective

2. Materials and Methods

2.1 Shallow groundwater water quality data

2.2 Geological framework

2.3 Methods

2.3.1 Regression analysis

2.3.2 Significance test of the correlation coefficient

2.3.3 Principal components analysis (PCA)

2.3.4 Mapping

2.3.5 Hydrogeochemical Analysis

3. Results and Discussion

3.1 Pearson correlation and significance tests

3.2 Pearson correlations and significance test among trace elements and salinity

3.3 Major anions and cations, chemical properties, and trace elements in Qa vs QTs

3.4 Principal Component Analysis

3.4.1 PCA on shallow groundwater of the Valley

3.4.2 Comparing PCA in the Qa and QTs zone

4. Conclusions and Recommendations

4.1 Conclusions

4.2 Recommendations

Declarations

References

Tables

Additional Declarations

Supplementary Files

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