Assessing Electrical Conductivity and Sodium Adsorption Ratio as Soil Salinity Indicators in Reclaimed Well Sites

Abstract

Electrical conductivity (EC) and sodium adsorption ratio (SAR) are the two most widely used indicators of soil salinity worldwide. However, concerns regarding the use of EC and SAR for assessing soil salinity have been raised by industry, scientists, and regulators. This study examines 22 well sites across two ecoregions, sampling soils from 0 to 1.5 m depths, and hypothesized that EC and SAR may be insufficient indicators of soil salinity during reclamation. Both ecoregions had distinct soil salinity profiles, with greater variability in the upper 0.3 m. Across ecoregions, EC was 1.0–8.4 dSm⁻¹ and SAR was 0.7–9.1. In the dry mixed-grass ecoregion, EC was moderately correlated with SAR from 0 to 0.45 m depths and significantly correlated with all ions above 0.6 m. EC explained 44–56% of chloride variation and up to 51% of sulfate in topsoil. In central parkland, EC correlated with chloride and magnesium at all depths and with calcium at most depths. SAR was strongly correlated with sodium at all depths in both ecoregions, explaining 6–82% of variation, and poorly predicted chloride and sulfate. SAR and EC did not always represent potentially toxic sodium, chloride, and sulfate ions; thus, these ions could be included as indicators, and current reclamation criteria should be modified or interpreted differently based on ecoregions and soil depths.

1. Introduction

Excessive salt concentrations (EC: 4–8 dSm⁻¹ moderate; 8–16 dSm⁻¹ strong; >16 dSm⁻¹ extreme; SAR: 13–18 medium; 18–26 high; >26 very high salinity) in soil are one of the major causes of decline in agricultural productivity around the world [1,2]. Over 1030 million hectares of land worldwide and approximately 20 million hectares (30%) of agricultural land in Canada are considered salt-affected or at risk of salinization [3]. Soil salinization is rising globally, and has extended to over 100 countries [4]. Soil salinization is characterized by elevated salt concentrations, elevated pH, and high sodium concentrations [2], and can occur through natural and anthropogenic activities. Although soil salinization varies greatly across locations due to parent material, changes in soil physical and biochemical properties can be prompted by landscape position, climatic conditions, and human activities [5,6]. Therefore, elevated salinity can result in a loss of available soil resources (e.g., water quality), agricultural production (e.g., seed germination), and ecological well being [7]. This could negatively affect socioeconomic conditions if left unmanaged [8].

Western Canada, specifically Alberta, is well known for large quantities of oil and natural gas deposits, with over 473,280 wells sites and over 446,000 km of pipelines [9]. Many of these production sites are located in natural salt-affected soils, and further soil contamination with saline wastewater is frequent during oil and gas production. During oil and gas production, produced water or brine generally contains chloride salts such as sodium chloride (NaCl), calcium chloride (CaCl₂), or potassium chloride (KCl). Changes in salt composition are affected by geomorphology. The most common salt found in saline wastewater in western Canada is sodium chloride [10]. Chloride ions do not bind to soil particles, allowing for them to leach easily through the soil and increasing the likelihood of reaching ground water. Sodium ions bind to soil particles, causing clay dispersion and breakdown of soil structure. Excess sodium can raise soil pH and deteriorate soil quality through aggregate slaking, swelling, and clay dispersion, which hinders root penetration and creates unfavorable conditions for plant growth [11]. Salinity encourages soil flocculation, and sodicity leads to soil dispersion.

Government regulations require remediation of salt-affected soils before further reclamation can occur, and soil must satisfy provincial Tier 1 and Tier 2 Soil and Groundwater Remediation guidelines for salinity and sodicity, which are measured using electrical conductivity (EC) and the sodium adsorption ratio (SAR) [12,13]. According to Alberta government regulations, the threshold values for EC and SAR for salt-affected soils are ≥4 dS m⁻¹ and ≥12, respectively [12,13], although these values change with land use and soil depth. Many salt-affected sites may never meet current guidelines for EC and SAR with current remediation techniques. Thus, soil is excavated and transported to landfills for long-term storage at great monetary and environmental expense, as significant resources are directed towards the remediation and reclamation of salt-contaminated sites and may hamper reclamation outcomes. Provinces such as Saskatchewan in Canada use EC and SAR ranges that vary for different climatic zones, soil properties, crop varieties, and salt compositional properties [14].

Although using EC and SAR to determine reclamation success for salt-affected soil has been a longstanding practice in Alberta, there is concern among industry professionals, scientists, and regulators that these metrics may not be the most appropriate metrics for assessing salt-contaminated soils. In a recent report on salt-affected soils in Alberta, Naeth et al. [15] concluded that values for EC and SAR are largely arbitrary, primarily based on agricultural soils, and have been established in remediation guidelines without a strong science-based foundation to support them. Upper-limit-specific ions, soil structural properties (e.g., bulk density), and/or plant community species composition and productivity may be more effective indicators of detrimental salt conditions or of the ability of the ecosystem to recover from oil and gas extraction and production activities [15,16,17], although this has not been proven scientifically. Understanding the scientific basis for current guidelines, including the relationship between diverse measures of salinity and impacts on soil and vegetation, may lead to the development of scientifically based approaches for reclamation. An alternative to EC and SAR could be determined based on acceptable ion concentration ranges and incorporating ion types for achieving reclamation success.

This research was designed to increase our knowledge of the risk pathways regarding salinity issues in land reclamation, and thus reduce environmental risk for potentially salt-affected sites. The research objectives were to assess whether EC and SAR are the most appropriate indicators of salt-affected sites, their potential use from contaminant-remediation and land-reclamation criteria perspectives, and whether total salt and specific ion concentrations could better serve as alternatives or complementary measures to salinity and sodicity in land reclamation assessments. Our specific objectives were to assess the salinity and sodicity of sites based on EC, SAR, and individual salt and ion concentrations, and determine the relationships among these measures to better address what is needed in land reclamation criteria. We hypothesized that EC and SAR, as soil salinity and sodicity indicators, would be insufficient to determine acceptable reclamation outcomes.

2. Materials and Methods

2.1. Research Sites

A list of potential oil and gas well sites in Alberta with salinity issues was obtained from oil and gas companies and municipalities. Phase I and II environmental site assessment reports for each research site were used to locate saline areas in order to provide detailed site diagrams with historic work areas that could be sources of salinity, such as well heads, above-ground storage tanks, flare pits, and drilling waste disposal areas, and to provide information on whether any spill occurred, what contaminants were released on site, and the contaminant remediation techniques and timelines used. The well sites selected for this study required a salinity issue that had been addressed in some way: revegetation at least a year old; a reclamation certificate applied for, received, or not yet applied for; and accessibility by four wheel drive truck or by walking a short distance.

In total, 22 sites were selected for study based on the above requirements: 16 were located in the dry mixed-grass ecoregion, and 6 were located in the central parkland ecoregions. Sites had one of four different land uses: grazed native forage (13 sites), grazed non-native forage (4 sites), ungrazed cultivated (4 sites), and ungrazed non-native forage (1 site) (

Table 1. Well sites information summary table. DMG = dry mixed-grass; CP = central parkland.

Well Site	Ecoregion	Land Use	Drilling Year	Reclaim Year	Soil Texture
1	DMG	Grazed, native forage	1978	2016–2018	Fine
2	DMG	Grazed, native forage	1978	2012–2018	Fine
3	DMG	Grazed, native forage	1978	2012–2016	Fine
4	DMG	Grazed, native forage	1975	2016	Fine
5	DMG	Grazed, native forage	1979	2014–2018	Coarse
6	DMG	Grazed, native forage	1983	2013	Fine
7	DMG	Grazed, native forage	1975	2013	Fine
8	DMG	Grazed, native forage	1978	2014–2018	Fine
9	DMG	Grazed, native forage	2003	2014–2016	Fine
10	DMG	Grazed, native forage	2002	2014	Coarse
11	DMG	Grazed, native forage	1973/2002	2009	Fine
12	DMG	Grazed, native forage	1981/2002	1997	Fine
13	DMG	Grazed, native forage	1978/2002	1999–2014	Fine
14	DMG	Grazed, non-native forage	1977	2014–2015	Fine
15	DMG	Grazed, non-native forage	1970	2016–2018	Fine
16	CP	Grazed, non-native forage	1980	2018	Fine
17	CP	Grazed, non-native forage	1975	2003	Fine
18	CP	Ungrazed, non-native forage	1951	1983–1993	Fine
19	DMG	Cultivated	1980/2002	2014–2015	Fine
20	CP	Cultivated	1969	2018	Coarse
21	CP	Cultivated	1976	1998–2000	Mixed
22	CP	Cultivated	1993	2006–2007	Coarse

). Sites were drilled between 1951 and 2003, with most being drilled in the 1970s. Most of the wells were productive for 1–36 years (median 23 years), but one never produced. Wells were abandoned between 1970 and 2014. Most salt-affected soils resulted from regular production activities near the well centers, flare pits, drilling-waste disposal areas, and storage tanks. Limited documentation exists on the reclamation efforts undertaken; however, most sites underwent some soil remediation, primarily through the removal of contaminated soil and replacement with clean topsoil in highly contaminated areas. Cultivated and non-native forage sites were seeded. Soil texture at the well sites varied, comprising fine, coarse, and mixed textures (Table 1). While the time since reclamation activities began was of interest, particularly for soil remediation and revegetation, there was sparse documentation on what reclamation occurred, if any. Available information was anecdotal and was only available for some sites, and therefore is not presented in this paper.

2.2. Soil Sampling and Analyses

The four corners of each site were marked with pegs every 10 m, and an ground conductivity meter (model: EM38-MK2, Geonics Ltd., Mississauga, ON, Canada; https://www.geonics.com/html/em38.html, accessed on 14 October 2025) was used to survey the sites. This meter measures salinity at depths that correspond to the shallow and deep rooting zones (≤1.5 m) of most plant species [18,19]. The readings were taken in areas previously identified as having high EC and/or SAR, usually in production areas (well center, drilling-waste disposal area, above-ground storage tank, flare pit), and in areas with evidence of poor revegetation, such as bare ground and visibly stressed vegetation. Areas where EC was >2 dS m⁻¹ with poor vegetation were selected for soil sampling. Soil was sampled in high EM38 reading areas, then at two points 1–2 m from the first, for three subsamples per location. Each hole was marked with a pin flag, and GPS location was recorded. Sampling was performed using a percussion auger with a Cobra TT hammer (Atlas Copco, St Laurent, QC, Cananda) or a 5 cm Dutch hand auger, depending on soil conditions. After each hole, the auger was cleaned by removing excess soil with a knife and wiping it with isopropyl alcohol. Augering was performed up to 1.5 m with 15 cm increments at two points 1–2 m from the first for three subsamples per location.

Soil from each interval was deposited into a Ziploc bag and labeled with the well site, sampling location, subsample number, and depth interval. Soil samples were analyzed at a commercial laboratory in Edmonton, Alberta, for saturation % and EC using saturated paste, pH by calcium chloride, and soluble ions (sodium, sulfate, calcium, magnesium, potassium); using an inductively coupled plasma optical emission spectrometer and chloride by colorimetry, SAR was calculated [20].

2.3. Data Analyses

Statistical analyses were conducted in R statistics environment version 4.0.3 [21], and all significant results were reported for p ≤ 0.05. All data were tested for normality and homogeneity using density and residual plots prior to further analyses. Spearman correlation analysis was used to determine if soil variables were correlated using PerformanceAnalytics package [22], and R and p-values < 0.05 were obtained. PerformanceAnalytics helped us to understand how soil variables or factors might influence each other or be related to other soil properties [22]. Salinity parameters that were moderately (r² = 0.50–0.69) or strongly (r² > 0.70) significantly correlated were considered from a land management perspective [23]. A non-parametric multiple-response permutational procedure (MRPP) was conducted to determine the significant differences in soil chemistry between depths, as well as whether depth intervals could be combined for analyses. The MRPP analysis was conducted using Adonis from the ecodist package, where the Bray–Curtis distance matrix and 999 permutations were used. Following a significant overall MRPP, pairwise comparisons were conducted. MRPP was used to determine the differences among categorical groups, such as ecoregion and land use.

Nonmetric multidimensional scaling (NMDS) was used to visually assess the dissimilarities between sample locations based on soil salinity chemistry. This method does not assume normality, dimensionality, or linearity, and uses a system of ranking for dissimilarity. NMDS has a stress parameter (<0.05 excellent, <0.1 fair, <0.2 good, <0.3 poor) that assesses inadequate fit between object distances and measures dissimilarities among objects in the ordination space. Since soil variables had different units, log transformations were performed to equate variable weights and reduce skew. To obtain a stable configuration, metaMDS from the Vegan package [24] was used to perform several runs to achieve the lowest dissimilarity between ordinations. The Bray–Curtis distance matrix was used. Two regression models were used to determine which salt ions predicted the best response variable; a generalized mixed model and hierarchical partitioning we also used, since they complement each other [25]. The generalized linear regression model was used to obtain a subset of models that explained the best response variable using the best glm package [26]. Hierarchical partitioning is a multivariate regression model that joins all possible regression combinations to identify the best causal factors [27]. It does not account for multicollinearity, since it assumes that all measures are independent and estimates predictor variables; it is, therefore, a good analysis method for ecology. Hierarchical partitioning predictor significance was calculated from randomization testing with negative log likelihood (n = 1000) using the hier.part package [28]. Together, these two regressions showed the percent of variability explained by a variable and the frequency of the best model.

3. Results

3.1. Soil Properties

EC and SAR generally increased with depth in both ecoregions, and all other ions had higher concentrations in dry mixed-grass than central parkland (

Table 2. Mean (±SE) of soil chemical parameters at different depths by ecoregion.

Depth (m)	EC (dS m−1)	SAR	PH	Sodium (mg kg−1)	Chloride (mg kg−1)	Sulfate (mg kg−1)	Calcium (mg kg−1)	Magnesium (mg kg−1)	Potassium (mg kg−1)
Dry Mixed Grass
0.0–0.15	3.5(1.9)	3.4(0.8)	7.5(0.05)	94.2(24.9)	90.0(28.7)	294.4(73.8)	84.0(14.9)	22.5(3.9)	45.0(11.8)
0.16–0.30	3.6(0.5)	5.7(1.0)	7.8(0.06)	258.3(64.1)	243.7(67.6)	828.6(205.9)	38.1(19.0)	74.7(15.6)	67.5(17.9)
0.31–0.45	5.7(0.7)	7.3(1.0)	8.0(0.08)	403.8(74.8)	444.2(108.3)	1273.1(232)	206.3(30.0)	132.7(21.4)	85.8(21.3)
0.46–0.60	7.4(0.8)	8.5(1.0)	8.0(0.04)	505.8(83.8)	654.4(137.1)	1516.3(277.5)	250.9(37.0)	176.7(29.5)	105.7(28.2)
0.61–1.5	8.4(0.6)	9.1(1.1)	8.1(0.02)	590.7(85.4)	739.8(130.0)	1804.3(287.9)	261.3(22.1)	208.5(17.3)	147.0(50.4)
Central Parkland
0.0–0.15	1.0(0.2)	0.7(0.2)	7.0(0.20)	14.2(5.3)	23.1(7.5)	133.8(71.0)	74.1(17.0)	23.3(6.8)	12.5(2.5)
0.16–0.30	0.9(0.2)	0.7(0.1)	7.3(0.09)	16.3(5.3)	26.1(11.0)	106.1(60.1)	54.8(14.4)	19.4(5.9)	6.7(1.4)
0.31–0.45	0.8(0.2)	1.2(0.3)	7.5(0.04)	20.6(4.7)	34.1(14.2)	58.0(27.0)	36.6(7.7)	14.8(3.6)	6.8(2.7)
0.46–0.60	1.0(0.2)	2.1(0.7)	8.1(0.04)	31.2(8.0)	58.9(16.9)	44.4(147.0)	35.7(5.6)	14.6(2.5)	6.9(3.1)
0.61–1.5	2.3(0.5)	1.1(2.1)	8.1(0.03)	95.2(40.4)	343.4(125.7)	95.8(33.7)	120.7(45.1)	43.2(12.0)	9.8(2.7)

). Concentrations of calcium, magnesium, and potassium increased with depth in dry mixed-grass, but decreased with depth from 0 to 0.6 m in central parkland. The mean sulfate concentration was 294–1804 mg kg⁻¹ and 44–133 mg kg⁻¹ in dry mixed-grass and central parkland, respectively. Variability in pH was low throughout the depths and ecoregions. Soil parameters differed with land use, but, due to the highly uneven numbers of sites in each land use, that difference was not the focus of the analyses.

3.2. Site Factors and Soil Salinity

Soil salinity differed statistically (p < 0.001) among depths. The pairwise comparison showed that the two upper depths differed significantly from all of the others (from p = 0.002 to p = 0.037). Depths of 0.31–0.45 m differed significantly (from p = 0.002 to p = 0.004) from those below 0.60 m, and 0.46–0.60 m (from p = 0.002 to p = 0.003) differed from those below 1.0 m. There were no significant differences among soil depths below 0.60 m. Soil properties differed with ecoregion, where dry mixed-grass and central parkland showed dissimilarities in soil salinity relationships, as shown by a few point clusters in the NMDS plots (Figure 1). In the dry mixed-grass prairie, there was a similarity in soil chemistry between land uses (Figure 2). Regardless of land use, with depth, the similarity in soil chemistry between dry mixed-grass prairie samples increased. In central parkland, similarity was low among grazed non-native forage and ungrazed cultivated samples (Figure 3). Ungrazed non-native forage sample locations were the most similar to each other, and were dissimilar from other locations. Soil pH had the shortest gradient at all depths in both ecoregions (Figure 2 and Figure 3). Overall, other gradients were similar in length, indicating few differences in their influence on sample locations.

3.3. Relationship Between EC, SAR and Other Salt Ions

Across ecoregions, mean EC was 1.0–8.4 dS m⁻¹ and mean SAR was 0.7–9.1 (Table 2). When both ecoregions were combined, EC was strongly correlated with SAR at 0.15–0.45 m depths and all other salt ions—sodium, chloride, sulfate, calcium, magnesium, and potassium—at every depth; SAR was significantly correlated with most ions, strongly with sodium at all depths, and sulfate under 0.15 m (

Table A1. Correlation between soil variables across dry mixed-grass and central parkland (R).

Depth (m)		SAR	PH	Sodium (mg kg−1)	Chloride (mg kg−1)	Sulfate (mg kg−1)	Calcium (mg kg−1)	Magnesium (mg kg−1)	Potassium (mg kg−1)
0–0.15	EC	0.62 ***	0.61 ***	0.73 ***	0.63 ***	0.78 ***	0.65 ***	0.72 ***	0.38 **
	SAR		0.36 ***	0.77 ***	0.47 ***	0.53 ***		0.28 *
	PH			0.44 ***	0.26 *	0.46 ***	0.44 **	0.42 **	0.34 *
	Sodium				0.66 ***	0.78 ***		0.51 ***
	Chloride					0.47 ***	0.27 *	0.45 ***	0.32 *
	Sulfate						0.54 ***	0.69 ***
	Calcium							0.80 ***	0.34 *
	Magnesium								0.24 *
0.16–0.30	EC	0.72 ***	0.67 ***	0.86 ***	0.82 ***	0.89 ***	0.77 ***	0.84 ***	0.67 ***
	SAR		0.63 ***	0.94 ***	0.69 ***	0.71 ***		0.39 **	0.24 *
	PH			0.68 ***	0.51 ***	0.69 ***	0.44 ***	0.57 ***	0.41 **
	Sodium				0.77 ***	0.84 ***	0.47 ***	0.63 ***	0.35 *
	Chloride					0.64 ***	0.49 ***	0.60 ***	0.62 ***
	Sulfate						0.69 ***	0.81 ***	0.46 ***
	Calcium							0.88 ***	0.63 ***
	Magnesium								0.57 ***
0.31–0.45	EC	0.78 ***	0.70 ***	0.91 ***	0.80 ***	0.89 ***	0.85 ***	0.87 ***	0.79 ***
	SAR		0.68 ***	0.93 ***	0.55 ***	0.75 ***	0.47 ***	0.54 ***	0.41 **
	PH			0.73 ***	0.49 ***	0.77 ***	0.54 ***	0.64 ***	0.50 ***
	Sodium				0.62 ***	0.91 ***	0.74 ***	0.80 ***	0.55 ***
	Chloride					0.57 ***	0.65 ***	0.64 ***	0.80 ***
	Sulfate						0.83 ***	0.88 ***	0.63 ***
	Calcium							0.94 ***	0.72 ***
	Magnesium								0.67 ***
0.46–0.60	EC	0.65 ***	0.65 ***	0.87 ***	0.80 ***	0.86 ***	0.87 ***	0.89 ***	0.81 ***
	SAR		0.76 ***	0.88 ***	0.38 **	0.71 ***	0.37 **	0.42 **	0.35 *
	PH			0.75 ***	0.46 ***	0.71 ***	0.40 **	0.52 ***	0.41 **
	Sodium				0.50 ***	0.93 ***	0.73 ***	0.78 ***	0.59 ***
	Chloride					0.46 **	0.62 ***	0.64 ***	0.74 ***
	Sulfate						0.82 ***	0.86 ***	0.63 ***
	Calcium							0.93 ***	0.76 ***
	Magnesium								0.74 ***
0.61–1.50	EC	0.54 ***	0.55 ***	0.83 ***	0.68 ***	0.70 ***	0.84 ***	0.92 ***	0.70 ***
	SAR		0.65 ***	0.88 ***		0.71 ***	0.20 *	0.36 ***	0.18 *
	PH			0.66 ***	0.27 **	0.53 ***	0.18 *	0.48 ***	0.29 ***
	Sodium				0.36 ***	0.84 ***	0.60 ***	0.71 ***	0.45 ***
	Chloride						0.66 ***	0.61 ***	0.68 ***
	Sulfate						0.53 ***	0.69 ***	0.44 ***
	Calcium							0.86 ***	0.68 ***
	Magnesium								0.68 ***

EC = electrical conductivity; SAR = sodium adsorption ratio; * = 0.05; ** = 0.01; *** = 0.001.

). EC was moderately correlated with SAR from 0 to 0.45 m depths and significantly correlated with all ions above 0.6 m in dry mixed-grass (

Table A2. Correlations (R) between soil variables in dry mixed-grass.

Depth (m)		SAR	PH	Sodium (mg kg−1)	Chloride (mg kg−1)	Sulfate (mg kg−1)	Calcium (mg kg−1)	Magnesium (mg kg−1)	Potassium (mg kg−1)
0–0.15	EC	0.68 ***	0.44 *	0.75 ***	0.58 ***	0.83 ***	0.66 ***	0.78 ***	0.32 *
	SAR			0.88 ***	0.59 ***	0.52 **		0.43 *
	PH					0.33 *	0.51 **	0.46 **
	Sodium				0.66 ***	0.76 ***		0.59 ***
	Chloride					0.37 *		0.47 **	0.41 *
	Sulfate						0.65 ***	0.77 ***
	Calcium							0.80 ***	0.44 *
	Magnesium	0.56 ***	0.39 *	0.78 ***	0.70 ***	0.79 ***	0.78 ***	0.85 ***	0.47 **
0.16–0.30	EC		0.44 *	0.90 ***	0.53 **	0.52 **
	SAR			0.50 **		0.49 **	0.30 *	0.48 **
	PH				0.60 ***	0.72 ***	0.39 *	0.60 ***
	Sodium					0.29 *	0.35 *	0.46 **	0.56 ***
	Chloride						0.68 ***	0.81 ***
	Sulfate							0.88 ***	0.47 **
	Calcium								0.35 *
	Magnesium	0.52 **	0.40 *	0.78 ***	0.64 ***	0.71 ***	0.76 ***	0.85 ***	0.54 **
0.31–0.45	EC		0.51 **	0.84 ***		0.52 **
	SAR			0.59 ***		0.63 ***		0.45 **
	PH					0.85 ***	0.53 **	0.67 ***
	Sodium						0.46 **	0.46 **	0.67 ***
	Chloride						0.67 ***	0.79 ***
	Sulfate							0.90 ***	0.50 **
	Calcium								0.43 *
	Magnesium	0.36 *		0.70 ***	0.69 ***	0.62 ***	0.74 ***	0.86 ***	0.68 ***
0.46–0.60	EC		0.65 ***	0.76 ***		0.53 **
	SAR			0.46 **		0.39 *
	PH					0.88 ***	0.55 **	0.66 ***
	Sodium						0.42 *	0.50 **	0.74 ***
	Chloride						0.63 ***	0.72 ***
	Sulfate							0.83 ***	0.58 ***
	Calcium								0.56 **
	Magnesium			0.38 *	0.61 ***		0.75 ***	0.78 ***	0.53 **
0.61–1.50	EC		0.56 ***	0.88 ***	−0.33 *	0.70 ***			−0.45 **
	SAR			0.42*			−0.38 *
	PH					0.88 ***
	Sodium						0.50 **	0.54 **	0.73 ***
	Chloride							0.73 ***	0.61 ***
	Sulfate								0.44 *
	Calcium	0.68 ***	0.44 *	0.75 ***	0.58 ***	0.83 ***	0.66 ***	0.78 ***	0.32 *
	Magnesium			0.88 ***	0.59 ***	0.52 **		0.43*

EC = electrical conductivity; SAR = sodium adsorption ratio; * = 0.05; ** = 0.01; *** = 0.001.

). In central parkland, EC was significantly correlated with chloride and magnesium at all depths and calcium at most depths, with weak to no correlations with SAR (

Table A3. Correlations (R) between soil variables in central parkland.

Depth (m)		SAR	PH	Sodium (mg kg−1)	Chloride (mg kg−1)	Sulfate (mg kg−1)	Calcium (mg kg−1)	Magnesium (mg kg−1)	Potassium (mg kg−1)
0–0.15	EC		0.64 **		0.45 *		0.94 ***	0.77 ***
	SAR		0.49 *
	PH			0.52 *		0.45 *	0.50 *
	Sodium				0.47 *	0.59 *
	Chloride						0.59 *	0.47 *
	Sulfate							0.54 *
	Calcium							0.82 ***
	Magnesium								0.47 *
0.16–0.30	EC	0.44 *	0.59 *	0.70 **	0.54 *	0.77 ***	0.67 **	0.72 **	0.75 ***
	SAR		0.65 **	0.85 ***	0.45 *	0.57 *
	PH			0.68 **		0.60 *			0.50 *
	Sodium				0.71 **	0.76 **		0.51 *
	Chloride					0.58 *	0.56 *	0.56 *
	Sulfate							0.71 **	0.48 *
	Calcium							0.69 **	0.63 **
	Magnesium								0.70 **
0.31–0.45	EC	0.66 **		0.84 ***	0.60 *	0.82 ***		0.53 *	0.68 **
	SAR			0.86 ***
	Sodium					0.64 **			0.57 *
	Chloride					0.48 *
	Sulfate						0.54 *	0.79 ***	0.55 *
	Calcium							0.85 ***	0.46 *
	Magnesium								0.60 *
0.46–0.60	EC				0.90 ***		0.69 **	0.62 *	0.47 *
	SAR			0.89 ***			−0.53 *	−0.49 *
	Chloride						0.67 **	0.56 *
	Sulfate						0.54 *	0.63 *	0.60 *
	Calcium							0.95 ***
	Magnesium								0.45 *
0.61–1.50	EC			0.71 **	0.94 ***		0.80 ***	0.77 ***	0.77 ***
	SAR			0.44 *
	Sodium				0.54 *		0.54 *	0.46 *	0.51 *
	Chloride						0.70 **	0.69 **	0.67 **
	Calcium							0.88 ***	0.68 **
	Magnesium								0.59 *

EC = electrical conductivity; SAR = sodium adsorption ratio; * = 0.05; ** = 0.01; *** = 0.001.

). Sodium and sulfate correlated with SAR in dry mixed-grass at all depths and with chloride above 0.3 m. In central parkland, SAR correlated with pH above 0.3 m and sodium at all depths below 0.15 m. When other salt ions were considered, sodium was correlated with sulfate, chloride, and magnesium throughout all depths across ecoregions. Similar results were observed in dry mixed-grass, with the exception that chloride did not show a significant correlation with sodium below 0.3 m and magnesium with potassium above 0.15 m (Table A2). In central parkland, the strongest correlation was between calcium and magnesium, which were moderate with chloride to 0.3 m and with sulfate to 0.45 m (Table A3).

When all properties were assessed together in the NMDS, EC was most strongly correlated with sulfate above 0.3 m and with magnesium below that depth; SAR was most strongly correlated with sodium at all depths (Figure 1). The ordination of individual ecoregions showed that EC was strongly associated with sulfate in the upper 0.30 m and calcium and magnesium at lower depths in dry mixed-grass (Figure 2). In central parkland, ion associations with EC were variable with depth (Figure 3). Associations were strong with calcium and magnesium in the upper 0.30 m and below 0.60 m, with sodium and sulfate from 0.16 to 0.45 and chloride from 0.46 to 1.50. SAR and sodium were strongly associated, as expected, in both ecoregions at all depths (Figure 2 and Figure 3). Sulfate was strongly associated with sodium and moderately associated with SAR at all depths in dry mixed-grass prairie only, reflecting the naturally high sodium sulfate (Figure 2). SAR and sodium were moderately associated with chloride in the upper 0.30 m. In the dry mixed-grass prairie, below 0.15 m, chloride was moderately associated with calcium and magnesium (Figure 2b), and below 0.30 m, it was strongly associated with potassium (strongest) (Figure 2c–e). In central parkland, chloride was associated with sodium and sulfate in the upper 0.30 m, with potassium and sulfate at 0.31–0.45 m depth, and with potassium below 0.60 m (Figure 3e). Calcium and magnesium were strongly associated in both ecoregions at all depths (Figure 2 and Figure 3).

In the dry mixed-grass prairie, hierarchical partitioning showed that SAR significantly contributed to 13–16% of the variation in EC in the upper 0.45 m of depth; from 0 to 0.3 m, EC significantly contributed to 16–26% of the variation in SAR (

Table 3. Hierarchical partitioning showing percent contribution of soil parameters in dy mixed-grass.

Depth (m)	Variables	EC	SAR	PH	Sodium	Chloride	Sulfate
0–0.15	EC		16.4 *	7.2	22.4 *	19.0 *	35.0 *
	SAR	26.1 *		2.3	44.6 *	12.2	14.7
	PH	55.5*	10.8		7.6	8.0	18.1
	Sodium	27.4 *	34.9 *	2.2		13.4	22.1 *
	Chloride	43.8 *	13.8	3.6	21.5 *		17.3 *
	Sulfate	50.6 *	12.4 *	5.1	24.3 *	7.7
0.15–0.30	EC		15.4 *	5.2	31.3 *	25.0 *	23.1 *
	SAR	16.4 *		2.8	59.0 *	10.2	11.5 *
	PH	19.4	13.9		28.2	5.2	33.4
	Sodium	30.0 *	27.7 *	8.4		9.2	24.7 *
	Chloride	52.2 *	8.6	1.6	17.6 *		20
	Sulfate	31.1 *	15.1	9.5	33.7 *	10.5
0.30–0.45	EC		12.7 *	3.9	30.3 *	34.6 *	18.4 *
	SAR	13.5 *		2.9	65.9 *	3.6	14.1 *
	PH	15.2	11.1		24.5	3.3	45.9 *
	Sodium	22.5 *	31.6 *	17.4 *		3.4	24.5 *
	Chloride	56.4 *	9.5	1.6	16.4*		16.1 *
	Sulfate	23.2 *	14.5 *	20.9 *	32.2 *	9.2
0.45–0.60	EC		10.3	1.2	32.8 *	35.4 *	20.2 *
	SAR	8.0		18.3 *	55.1 *	2.0	16.7 *
	PH	10.0	47.8 *		23.8 *	5.0	13.5
	Sodium	22.8 *	30.1 *	10.3		4.0	32.6 *
	Chloride	49.0 *	14.8 *	4.2	16.2 *		15.7 *
	Sulfate	22.1 *	15.2 *	8.8	40.5 *	13.5 *
0.60–1.50	EC		11.8	2.4	28.5 *	47.9 *	9.4
	SAR	6.4		22.4*	50.4 *	4.0	16.8 *
	PH	4.1	57.2 *		24.7 *	4.5	9.5
	Sodium	12.5	43.8 *	4.6		4.1	35.0 *
	Chloride	47.6 *	16.6 *	3.5	13.6		18.8 *
	Sulfate	11.4	27.0 *	2.5	41.5 *	17.5 *

EC = electrical conductivity; SAR = sodium adsorption ratio; * = significant(p < 0.05) contribution from randomization.

). In central parkland, EC and SAR did not contribute to each other (Table 3). When EC was compared with other ions in dry mixed-grass, EC significantly explained most variations in soil chloride, being from 44 to 56% throughout the soil profile; sulfate’s variation was 51% in the upper 0.15 m, but this variation declined from 31 to 11% with increasing depth; and sodium had 23–30% variation, with the greatest variation at 0.15–0.30 m depth increments. The variation in sulfate explained by sodium increased with depth (24–41%) (Table 3). Similarly, in central parkland, EC significantly explained 34–65% of the variation in chloride and 15–46% of sulfate across depths. EC explained the greatest portion of sulfate variation above 0.60 m and sodium did below this depth (

Table 4. Hierarchical partitioning showing percent contribution of soil parameters in central parkland.

Depth (m)	Variables	EC	SAR	PH	Sodium	Chloride	Sulfate
0–0.15	EC		4.4	7.1	21.3	25.4 *	41.8 *
	SAR	12.4		21.0	18.9	21.6	26
	PH	37.9 *	13.6		14.3	19.7	14.3
	Sodium	31.7 *	5.9	6.1		19.9	36.4 *
	Chloride	34.2 *	2.5	3.9	21.6		37.9 *
	Sulfate	42.7 *	5.5	5.9	23.5 *	22.2 *
0.15–0.30	EC		12.9	4.5	26.4	25.6	30.6*
	SAR	10.3		15.6	53.0 *	9.0	12.0
	PH	14.4	35.6 *		25.7	10.8	13.4
	Sodium	30.9 *	20.5 *	7.0		18.8	22.8
	Chloride	34.7 *	9.6	4.8	21.0 *		29.9 *
	Sulfate	36.4 *	11.0	4.6	24.1	24.0
0.30–0.45	EC		7.4	1.3	21.5	35.6 *	34.1 *
	SAR	9.3		7.7	64.5*	4.0	14.5
	PH	9.7	36.1		23.1	23.5	7.6
	Sodium	25.2	47.5 *	2.2		13.9	11.2
	Chloride	49.0 *	5.5	1.1	16.1		28.8 *
	Sulfate	45.1 *	7.8	1.5	19.2	26.4 *
0.45–0.60	EC		5.2	7.9	9.6	51.0 *	26.4 *
	SAR	3.9		5.3	80.2 *	2.6	8.0
	PH	14.8	20.4		22.7	30.3 *	11.7
	Sodium	8.0	82.4 *	0.9		7.1	1.7
	Chloride	64.9 *	4.4	14.2	7.2		9.3
	Sulfate	45.8 *	10.3	4.8	18.8	20.3
0.60–1.50	EC		11.7	1.9	32.8 *	47.2 *	6.3
	SAR	7.6		4.1	74.6 *	5.1	8.5
	PH	11.6	30.1		14.8	20.9	22.7
	Sodium	13.1	71.8 *	3.0		9.3	2.9
	Chloride	51.0 *	8.2	2.6	25.5 *		12.7
	Sulfate	15.0	22.2	2.7	44.7 *	15.3

EC = electrical conductivity; SAR = sodium adsorption ratio; * = significant (p < 0.05) contribution from randomization.

). SAR was a poor predictor of chloride or sulfate in both ecoregions, as, in most cases, their contribution were insignificant (Table 3 and Table 4). In the dry mixed-grass prairie, most variation in sodium was jointly explained by EC and SAR, followed by sulfate; above 0.15 m, SAR was the dominant predictor, and EC was below 0.60 m (Table 3). In central parkland, the majority of the variation in sodium below 0.30 m was significantly explained by SAR, with 80% predicted by SAR in the 0.46–0.60 m depth interval (Table 4). In topsoil, EC and sulfate were the dominant predictors (approximately 30% and 20–38%, respectively). In both ecoregions, pH explained few of the variations in any salt ion (Table 3 and Table 4), confirming observations from the NMDS (Figure 2). When a comparison of generalized linear regression and hierarchical partitioning was conducted for EC and SAR with the most toxic sodium, chloride, and sulfate ions, the results showed that, in dry mixed-grass, sodium appeared to be most dependent on EC, SAR, and sulfate, chloride was dependent on EC and sodium, and sulfate was dependent on sodium. In central parkland, sodium was the most dependent on SAR, and chloride and sulfate was the most dependent on EC.

4. Discussion

4.1. Ecoregion and Soil Type Variation

Differences observed between ecoregions in the studied soil properties were as expected. Dry mixed-grass and central parkland ecoregions have distinct climate differences, influencing soils and vegetation. Dry mixed-grass consists of undulating semi-arid prairies, coulees, and valleys, dominated by brown chernozem and solonetz soils, and drought-tolerant vegetation [29]. Central parkland consists of agricultural lands, northern forests, and dry prairies, with black and dark gray chernozem and solonetz soils dominating. Soil properties change with depth, and manifest as specific horizons for the different types of soils. A main difference between black, dark brown, and brown chernozems is the climate they developed under. Chernozemic soils are characterized by an A horizon (Ah/Ahe/Ap) of at least 10 cm, with a C:N ratio less than 17, and with calcium as the dominant exchange cation [30,31]. Solonetzic soils form on saline parent material [30]. Southern Alberta soils are known to have high sulfate and calcium concentrations [32]. Therefore, reclamation criteria could be adapted for those soils to best determine reclamation success. For example, criteria at those locations could be based on background measures rather than specific criteria. Therefore, ecoregions and soil types should be taken into consideration for reclamation criteria.

4.2. EC, SAR, and Other Salt Ions as Reclamation Criteria

Soil salinity chemistry varied across soil depth intervals at a fine scale (15 cm). The upper 0.16–0.30 m was most often different from other soil depths. This layer of soil is biologically important, as it contains significant plant biomass, soil nutrients, and microbial activity, and is also the layer most immediately impacted by land disturbances that may compact the soil and remove organic matter and/or vegetation. The 0.31–0.60 m depth intervals often act as a transition zone, resembling either the upper soil layers or the subsoil below 0.60 m, depending on the soil type and land use.

Although EC is a measure of conductivity resulting from the amounts of soluble salts present in the soil, it does not indicate which specific ions are found in the highest concentrations. Since ions have different properties and interactions in the soil, EC might not always reflect detrimental effects on vegetation. Therefore, EC may be used to determine whether soluble salts are present in soil, but perhaps should not be used to accurately assess a site at the level of detail needed to determine if a reclamation certificate may be given. For example, EC may be used under acceptable criteria; however, one salt might be present in higher concentrations than another, and thereby have detrimental effects on soil and vegetation. In our study, some well sites with an EC of 1.74 dS m⁻¹ met reclamation criteria, although they had higher concentrations of sodium (380 mg kg⁻¹), chloride (152 mg kg⁻¹), and sulfate (293 mg kg⁻¹) than the same value of EC (1.74 dS m⁻¹) that had considerably lower concentrations of sodium (94 mg kg⁻¹), chloride (28.2 mg kg⁻¹), and sulfate (224 mg kg⁻¹). An EC of 2.5 dS m⁻¹ did not meet reclamation criteria, but had a small concentration of sodium (17.9 mg kg⁻¹) and a high concentration of sulfate (1070 mg kg⁻¹).

Research has shown that sodium becomes toxic for most plants after concentrations of 230 mg L⁻¹ in soil, and chloride becomes toxic for most plants at concentrations of 4–7 mg g⁻¹ [33,34]. Several investigations discuss the negative effects of chloride and sulfate on vegetation; however, no specific threshold has been identified, since plant species respond differently [35]. While the measurement of individual salt ions would be ideal, this is not always feasible at field-scale in many industries, so EC measurement is easier and is purportedly reliable [36,37]. Although our results demonstrate that EC effectively represents a range of salt ions and may be sufficient for diagnosing soil quality issues, its accuracy varies depending on ion type, ecoregion, and soil depth. Therefore, elevated EC may warrant further assessment and testing to evaluate the type and magnitude of issues, and researchers should consider other potentially toxic salt ions such as sodium, sulfate, and chloride.

SAR is the ratio of sodium, calcium, and magnesium concentrations, and it shows high sodium values when elevated. High sodium concentrations indicate potential detrimental impacts on soil, including dispersion, which causes swelling and surface crusting [38]. Swelling results in decreased large pores, reducing water infiltration and air movement. Reduced infiltration leads to a decreased amount of water available for plants and increased runoff and erosion [38]. Sodium is well represented by SAR, as it shows when sodium is high or low relative to calcium and magnesium. However, if calcium and magnesium were also high, SAR does not accurately represent sodium’s impacts on soil and plants; as our study suggests, SAR could be low, but ion concentrations could still be high enough to have detrimental impacts on soil and vegetation. The opposite may also occur, where the SAR could be high, but the sodium concentration would not be high enough to have adverse impacts on soil and vegetation. In some well sites, our data showed that SAR values of 3.49 had higher sodium (507 mg kg⁻¹), calcium (1460 mg kg⁻¹), and magnesium (925 mg kg⁻¹) content than SAR values of 7, which had lower sodium (1.3 mg kg⁻¹), calcium (34.8 mg kg⁻¹), and magnesium (10.1 mg kg⁻¹) content. Therefore, SAR alone may not be an adequate measure to assess sodicity when determining reclamation success.

Calcium and magnesium are major exchangeable cations in soils. Even though they have been grouped in classifications, magnesium can be more detrimental than calcium, and their ratio can dictate how soils will react [39]. For example, in most magnesium systems, magnesium adsorbs more sodium than in calcium systems, resulting in adverse impacts on soil structure [39,40]. Thus, it might be useful to include these ions in reclamation criteria. Other salts, particularly those that detrimentally affect vegetation and/or soil structure, could also be included. For example, when soil cations with monovalent and divalent cations charges are in the same space, both the dispersion and flocculation of clay particles induce soil pore stability and enhance air and water movement [41]. When soils are mainly charged with monovalent cations, such as sodium and potassium, dispersion leads to reductions in pore size, slaking, and macro-pore reduction, and reduced water infiltration can also occur. When soil is mainly charged with divalent cations, such as calcium and magnesium, flocculation may result. Therefore, soil containing high sodium and potassium would have a greater impact on soil and water relationships and potential negative impacts on vegetation [41,42,43]. For this reason, knowing which cations are present in the soil results in the better prediction of outcomes, and may affect how reclamation success is assessed.

5. Conclusions

The mixed-grass prairie and central parkland exhibited distinct soil salinity profiles. In both ecoregions, salinity chemistry was variable in the upper 0.30 m of soil, with particularly inconsistent patterns in the top 0.15 m, then became more uniform with depth across sample locations. Across ecoregions, EC was 1.0–8.4 dSm⁻¹ and SAR was 0.7–9.1. In dry mixed-grass, EC was moderately correlated with SAR from 0 to 0.45 m depths and was significantly correlated with all ions above 0.6 m. EC explained 44–56% of chloride variation and up to 51% of sulfate in topsoil. In central parkland, EC correlated with chloride and magnesium at all depths and with calcium at most depths. SAR was strongly correlated with sodium at all depths in both ecoregions, but explained 6–82% variation and poorly predicted chloride and sulfate. EC and SAR were positively associated with each other, with the strength of the relationship decreasing with depth. While associated, they do not duplicate each other as measures of soil salinity. SAR and EC indicated overall salt ion concentrations, although their accuracy for specific ions varied depending on the ion, ecoregion, and soil depth. Sodium, chloride, and sulfate, the more potentially toxic ions for plants, were not always represented by EC and SAR. As a result, including these three ions as additional indicators may be crucial when evaluating reclamation success. Reclamation criteria should be modified or interpreted differently based on specific ecoregions, soil depths, and historical salinity values to best reflect the optimal land reclamation target.