Application of Water Quality Index for Drinking and Irrigation Suitability in Arid Zones: A Case Study of the Shallow Aquifer in Oued Souf, Southeastern Algeria

ABSTRACT

In southeastern Algeria, the Oued Souf's shallow aquifer is increasingly affected by environmental dynamics and human‐driven impacts, altering its hydrochemistry, elevating contamination levels, and diminishing water availability amid worldwide climate change. This study examines the sources and drivers of hydrochemical variability and of groundwater quality deterioration, accounting for land‐use changes and human impacts. The quality of groundwater was evaluated using the WQI method to determine its overall condition and its suitability for human consumption. Principal component analysis (PCA) and Pearson correlation were used to interpret the relationships between irrigation indices and hydrochemical variables. At the same time, a Durov diagram was employed to characterize the geochemical evolution of groundwater. The results revealed extremely high salinity (EC = 18,680 μS/cm) and high alkalinity, with Na–Cl facies dominating 80% of the samples, mainly due to reverse ion‐exchange processes and possibly cement‐related contamination. WQI, TDS, and TH values confirmed that the groundwater is unsuitable for drinking. Regarding irrigation, suitability ranged from suitable to conditionally suitable based on SAR, RSC, MH, and PI, whereas KR indicated that most samples are unsuitable. However, when salinity (EC) was considered through the Wilcox and USSL diagrams, together with the PS index, the overall suitability for agricultural use was found to be severely restricted. These results indicate that elevated salinity, rather than sodium hazard alone, represents the principal limiting factor for the use of groundwater in irrigation within the study area. Overall, the findings highlight the progressive deterioration of groundwater hydrochemistry in arid regions, underscoring the need for mitigation strategies, such as cultivating salt‐tolerant crops and pretreating groundwater before use. The findings reveal a decline in the quality of the aquifer, indicating that its appropriateness for both potable and irrigation purposes is substantially restricted under current conditions.

Summary

• Hydrochemistry of the Oued Souf shallow aquifer is dominated by Na–Cl facies.

• Reverse ion exchange and evaporation are the main controls on groundwater salinity.

• WQI, TDS, and TH indicate that groundwater is unsuitable for drinking.

• High salinity, rather than sodium hazard alone, severely limits irrigation suitability.

• Anthropogenic activities accelerate groundwater quality deterioration in the study area.

Groundwater in the shallow aquifer of Oued Souf, Algeria, is highly saline and mineralized, making it unsuitable for drinking and challenging for irrigation. Treatment strategies are essential to improve water quality for sustainable use in arid environments.

Abbreviations

DEM

digital elevation model

EC

electrical conductivity

FA

factor analysis

GIS

Geographical Information Systems

GPS

Global Positioning System

HCA

hierarchical cluster analysis

JORADP

Official Journal of the People's Democratic Republic of Algeria

KI

Kelley's index

LULC

land use and land cover

Max

maximum

meq/L

milliequivalents per liter

Min

minimum

MR

magnesium ratio

MSI

multi‐spectral instrument

Na%

sodium percentage

OK

ordinary kriging

OLI

Operational Land Imager

PCA

principal component analysis

PI

permeability index

PS

potential salinity

RS

remote sensing

RSC

residual sodium carbonate

SAR

sodium adsorption ratio

TDS

total dissolved solids

TH

total hardness

UK

universal kriging

WHO

World Health Organization

WQI

water quality index

μS/cm

micro‐Siemens per centimeter

1. Introduction

Water is an essential resource for human survival; however, its safety is frequently compromised by chemical and microbial contamination (Jat Baloch, Zhang, Zhang, et al. ²⁰²²). Among freshwater sources, groundwater is one of the most dependable, supporting domestic water supply, agriculture, and industrial activities in many regions of the world (Chen et al. 2023). Groundwater provides nearly half of the world's drinking water and more than 40% of irrigation water, highlighting its critical role in water and food security, particularly in arid and semi‐arid regions (Ghoto et al. 2025). This vital resource is becoming increasingly threatened by global environmental changes and intensive human activities (Sajib et al. 2025). The combined impacts of urbanization, population growth, and climate change further exacerbate the stress on aquifer systems, resulting in significant alterations in both water quality and availability (Chowdhury et al. 2025). Groundwater quality is closely associated with human health, crop production, and socio‐economic development. Nevertheless, environmental changes and anthropogenic activities, including urbanization, industrial development, and agricultural practices, have accelerated groundwater degradation and contributed to environmental issues such as soil salinization (Tian et al. 2025). Assessing groundwater quality is essential for environmental sustainability and for ensuring the sustainable management of local water resources (Jat Baloch, Zhang, Shoumik, et al. ²⁰²²). In arid regions, where precipitation and surface water availability are limited, groundwater constitutes the most reliable source of freshwater. However, the combination of restricted recharge, unsustainable agricultural practices, industrial discharges, and accelerated urban growth has intensified groundwater quality degradation (Aloui et al. 2025). In addition, certain practices such as the application of waste materials, including sewage sludge, to soils, may improve crop productivity but can also contribute to groundwater contamination (Hussein et al. 2023). Among various pollutants, pathogenic viruses pose a major environmental hazard worldwide. They can enter aquifers through multiple pathways, including irrigation practices, leaking sewer pipelines, faulty septic tanks, landfills, and urban runoff, potentially bypassing natural filtration and conventional disinfection barriers (Baloch, Baidya, et al. ²⁰²⁵). A wide range of studies has examined the environmental impacts of irrigation, particularly its influence on groundwater systems, the intensification of contamination risks, and possible remediation strategies (Ali et al. 2025). Furthermore, in arid and semi‐arid regions, the use of saline irrigation water together with limited rainfall and high evapotranspiration rates can accelerate soil salinization and land degradation (Baloch et al. 2023). This challenge is particularly significant in the Algerian Desert, where groundwater remains the sole source of water fulfilling domestic, agricultural, and industrial needs (Idder et al. 2014). Over the last two decades, cultivated areas in the Oued Souf region have increased remarkably, from approximately 200 ha in 1993 to more than 50 km². This rapid economic and agricultural growth, although improving livelihoods, has placed increasing pressure on aquifer systems and the surrounding natural environment (Boukhallat et al. 2025). The Oued Souf region of Algeria exemplifies this issue, as groundwater is the principal source of water supply. Rapid population growth, urban expansion, and agricultural intensification have collectively increased stress on local aquifers, leading to concerns about both water quantity and quality (Agharabi et al. 2025). Land use and land cover changes can substantially influence hydrological processes, thereby affecting groundwater resources and their sustainability (Nigar et al. 2024). The integration of remote sensing (RS) and Geographic Information Systems (GIS) enhances the spatial analysis and visualization of hydrochemical data, facilitating the detection of contamination patterns and their distribution over extensive areas (Oyda et al. 2026). Numerous researchers have studied the impact of land‐use and land‐cover (LULC) changes on groundwater quality in such environments. Excessive use of fertilizers, pesticides, and herbicides can contribute to groundwater contamination while land‐use changes driven by urbanization, agricultural expansion, and deforestation may degrade water quality through increased runoff, flooding, sewage discharge, and industrial pollution. Previous studies have confirmed that LULC changes significantly influence groundwater chemistry, whereas geogenic processes also play an important role in determining groundwater quality (Iqbal et al. 2024). Groundwater composition is controlled by both natural geochemical processes and human activities (Baloch, Zhang, et al. ²⁰²⁵). Groundwater quality has significantly deteriorated in many regions due to industrial and urban activities, leading to serious environmental and health impacts. Therefore, groundwater quality assessment is essential for understanding the effects of human and environmental pressures on water resources. Water quality is commonly described using physical, chemical, and biological parameters to evaluate its suitability for different uses, including drinking and irrigation. In this context, the water quality index (WQI) is widely used as an effective tool for integrating multiple parameters into a single value that represents the overall water quality status (Hussein et al. 2023). Complementary approaches, including principal component (PC) analysis (PCA), Pearson correlation analysis, and WQIs, are widely used to assess groundwater quality, identify potential contamination sources, and investigate the relationships among hydrochemical parameters (Rana et al. 2026). Water suitability for irrigation is primarily determined by the concentrations and composition of dissolved ions, as poor‐quality water can harm soil structure and reduce crop yields (Mansouri et al. 2025). Irrigation water quality is primarily controlled by salinity and sodicity levels, which are commonly assessed using parameters such as EC and SAR. The combined assessment of EC and SAR provides essential insights into groundwater suitability for irrigation (Almeida et al. 2025). Additionally, several index‐based approaches, such as RSC, KI, Na%, MR, PS, and PI, are commonly employed to evaluate irrigation water quality (Eid et al. 2023). Evaluating the quality of irrigation water requires continuous monitoring and expert judgment to confirm its suitability for agricultural applications. The chemical characteristics of irrigation water directly affect soil health and crop development. High‐quality irrigation water enhances productivity when combined with appropriate soil and water management practices (Agrawal and Dohare 2024). Despite the growing use of multivariate statistical approaches in hydrochemical research, such as correlation matrix analysis and box plot interpretation, their application in groundwater quality assessment remains relatively limited (Dheeraj et al. 2025). The main aim of this study is to assess the hydrochemical characteristics and overall quality of groundwater in the Oued Souf region of southeastern Algeria, with a focus on both drinking and irrigation purposes. This assessment includes analyzing chemical composition, dissolved constituents, and pollutants; evaluating drinking water quality using the WQI; and assessing irrigation suitability using specialized irrigation indices. The study also focuses on determining the main geochemical processes governing groundwater composition using the Durov diagram and applying multivariate statistical techniques to understand spatial variations and the underlying mechanisms affecting groundwater quality.

2. Methodology

2.1. Study Area

The investigated region lies within the Valley of El Oued (Oued Souf) in southeastern Algeria, covering approximately 682 km². It extends across latitudes 33°20′ to 33°40′ N and longitudes 06°40′ to 06°50′ E. Figure 1 shows the geographical context of the study area, including the positions of the groundwater sample wells. The Oued Souf region has a very arid environment, with high temperatures on the one hand and light, erratic precipitation on the other. Both significant evaporation and a lack of rainfall contribute to this aridity. Between 1991 and 2021, the temperature ranged from 5.18°C in January to 40.77°C in July. The average annual precipitation was 74.68 mm per the ONM 2022.

FIGURE 1.

Georeferenced map of the study area showing groundwater sampling locations, with GPS coordinates, DEM‐based elevation, and scale bar (1:60,000).

Located along the northern margin of the Grand Erg Oriental, the Oued Souf Valley is dominantly covered by extensive continental dune fields developed during the Quaternary period. As shown in the geological map (Figure 2), these formations consist mainly of compact, uniform, fine sands that blanket large portions of the region, particularly toward the south, where dune ridges may locally exceed 100 m in height. Between these dune systems, elongated depressions referred to locally as Sahans occur; these are broad, occasionally rocky corridors locally coated are associated with Quaternary gypsum formations. In addition, saline depressions (Sebkhas) occupy the uppermost northern section of the study area, corresponding to the lowest‐lying areas of the Saharan Basin. El Oued lies on the northeastern edge of the Saharan Platform, within the Mesozoic (Triassic) basin, where sedimentary units ranging from the Quaternary to the Lower Cretaceous form the bedrock (Karima et al. 2024).

FIGURE 2.

Geological map of the study area (1:60,000), showing major lithologies and structural features, with a detailed legend for units and cover types.

The shallow phreatic aquifer is the most exploited groundwater reservoir in the region. It reaches a thickness of 100 m, with groundwater levels varying between 1 and 40 m below the ground surface. The lithology is heterogeneous, consisting of fine sands and sandy clays, with local intercalations of gypsum lenses. An impermeable clay layer underlies the bottom of the aquifer. The measured hydraulic characteristics show fairly high horizontal permeability, varying between 1.1 × 10⁻⁴ and 2.6 × 10⁻⁴ m/s (Barkat et al. 2022). Natural recharge is likely controlled by deep infiltration of rainfall and runoff along the southern margin of the Grand Erg Oriental. This aquifer provides the principal water supply for irrigation in the region, where more than 30,000 boreholes are currently in use (Chebbah and Allia 2015).

3. Materials and Methods

3.1. Water Sampling and Laboratory Analysis

In August 2023, water samples were collected from 30 groundwater wells across the study area, representing domestic, drinking, agricultural, and industrial uses. The southern and western sectors are mainly influenced by intensive agricultural activities, whereas the eastern sector is more affected by anthropogenic pressures with relatively limited farming practices. A total of 30 groundwater samples were collected across the study area (682 km²), providing moderate spatial representativeness given the hydrogeological heterogeneity. Specifically, the sampling distribution includes 11 wells in the eastern Guemar agricultural zone, 8 wells in the northern Reguiba area influenced by sabkha environments, 10 wells distributed across the central and western agricultural sectors (Taghzout and Kouinine), and 1 well in the southern dune‐dominated area (Ouarmes). Despite this distribution, the sampling network remains more concentrated in the eastern sector, whereas the western agricultural zone and the northern sabkha‐influenced areas are relatively under‐represented. This uneven spatial coverage may limit the ability of the dataset to fully capture the hydrochemical variability across the entire study area. The sampling campaign followed internationally recognized methods to characterize the physical and chemical properties of groundwater. Before sampling, each 0.5‐L polyethylene bottle was thoroughly rinsed with the respective groundwater, and samples were taken only after approximately 10 min of pumping to ensure removal of stagnant water. Each bottle was labeled correctly (site code, date, and location) and subsequently stored in ice‐cooled, insulated boxes at 4°C, away from light to prevent post‐sampling chemical alteration, in line with (APHA [American Public Health Association] et al. ²⁰¹⁷). A handheld GPS device was used to accurately record the geographic coordinates of all sampling locations (Figure 1). Field measurements of pH, temperature, EC, and TDS were carried out using a Pro‐DSS multiparameter probe (YSI, USA) following APHA (2017) QA/QC procedures (APHA [American Public Health Association] et al. ²⁰¹⁷). Concentrations of major cations, including Na⁺, K⁺, Ca²⁺, and Mg²⁺, were determined by atomic absorption spectrophotometry (Analyst 400, PerkinElmer, USA), and major anions (SO₄ ²⁻, Cl⁻, and NO₃ ⁻) by ion chromatography (ICS‐1100, Thermo Fisher Scientific, USA). HCO₃ ⁻ was determined by titration following APHA (2017) methods. The same dataset was previously used by (Boukhallat et al. 2025).

Groundwater sampling was conducted during the dry period, which is considered representative of the dominant hydrogeochemical conditions in the Oued Souf region. Due to the arid climate and limited seasonal rainfall, groundwater quality exhibits relatively low temporal variability compared with spatial variability. Under these conditions, evaporation processes and reduced recharge contribute to increased concentrations of dissolved ions, particularly salinity‐related parameters. Therefore, sampling during this period provides a reliable representation of groundwater quality under prevailing environmental stress conditions, which is critical for evaluating water suitability for drinking and irrigation purposes. Although seasonal variations were not assessed, their impact is expected to be limited in comparison with spatial heterogeneity across the study area. The detailed research design and analytical framework adopted in this study are illustrated in the methodological workflow diagram (Figure 3).

FIGURE 3.

Methodological workflow of the study.

3.2. Assessment of Drinking Water Quality

3.2.1. Traditional Indicators (TDS and TH)

Drinking water quality assessment is frequently based on two principal parameters: TDS and TH. TDS indicates the overall concentration of dissolved inorganic salts and minerals (Jodhani et al. 2025). In this study, TDS was measured on‐site. TH results from the combined concentrations of calcium and magnesium ions and was calculated according to the following equation (Sultana et al. 2025):

$$\begin{array}{c}\mathrm{TH}\left(\mathrm{mg}/\mathrm{L}\text{asCaCO}3\right)\mathbf{=}\left[{\mathrm{Ca}}^{2+}\left(\mathrm{mg}/\mathrm{L}\right)\mathtt{\times }2.49\right]\hfill \\ +\left[{\mathrm{Mg}}^{2+}\left(\mathrm{mg}/\mathrm{L}\right)\mathtt{\times }4.118\right].\hfill \end{array}$$ (1)

Groundwater suitability for drinking was categorized according to standard thresholds of TDS and TH (Table 1).

TABLE 1.

Categorization of water for potable use based on TDS and TH.

Parameter	Range (mg/L)	Category
TDS (Kumari et al. 2025)	< 500	Desirable for drinking
	500–1000	Permissible for drinking
	1000–3000	Useful for irrigation
	> 3000	Unfit for drinking and irrigation
TH (Jodhani et al. 2025)	< 75	Soft
	75–150	Moderately hard
	150–300	Hard
	> 300	Very hard

3.3. WQI

WQI is a single value indicator widely employed to represent the general water quality (Siriwardhana et al. 2023). It functions as an essential tool for determining the suitability of water for human consumption. It is considered one of the most comprehensive approaches for evaluating groundwater quality (Jat Baloch et al. 2021). WQI was determined according to Algerian standards (JORADP, 2011). Eleven key water quality parameters, considered essential for evaluating drinking water safety, were selected and assigned a weight (w i) varying from 1 to 5, as presented in Table  2 . These weights reflect the importance of each parameter in assessing overall water quality and its potential effects on human health. The WQI was computed following a sequence of four consecutive steps, following the procedure described (El Mountassir et al. 2022), detailed in Equations ((1), (4)):

$$W_i=\frac{w_i}{{\sum }_{i=1}^n{w}_i}.$$ (1)

TABLE 2.

Physicochemical parameters' weights, relative weights, and JORADP (2011).

Parameter	Weight (w i )	JORADP (2011)	Relative weight (wi)
pH	4	6.5–8.5	0.114
EC	4	1500–2800	0.114
TDS	5	500–1500	0.143
Ca2+	2	100–200	0.057
Mg2+	1	50–150	0.028
Na+	2	200	0.057
K+	2	12	0.057
Cl−	3	250–500	0.086
HCO3 −	3	120*	0.086
SO4 2−	4	250–400	0.114
NO3 −	5	50	0.143
	∑w i  = 35	*WHO 2011	∑W i  = 1

Note: All parameters in mg/L, except EC in μS/cm. 120*mg/L for HCO₃‐ is according to WHO; other values are according to JORADP.

The proportional weight is denoted by W _i , while n indicates the total number of considered parameters. The quality rating (q _i ), which reflects the concentration level of each parameter in relation to standards, was computed using the corresponding Equation (2):

$$q_i=\frac{c_i}{s_i}\times 100,$$ (2)

c _i is the concentration (mg/L) for every parameter while s _i refers to Algerian Standard (JORADP 2011).

SI _i as the sub‐index for parameter i, calculated by multiplying the relative weight (W _i ) by the quality rating scale (q _i ). This relationship is defined by Equation (3):

$${\mathit{SI}}_i=W_i\times q_i.$$ (3)

WQI is computed as the sum of all individual sub‐indices (∑SI i), as shown in Equation (4):

$$\mathrm{WQI}=\sum {\mathit{SI}}_i.$$ (4)

The classification scheme is summarized in Table 3.

TABLE 3.

WQI classification and its suitability for drinking purposes (Manu et al. 2023).

WQI range	Water quality status	Suitability for drinking
0–50	Excellent	Suitable
50–100	Good	Suitable
100–200	Poor	Marginally suitable
200–300	Very poor	Unsuitable without treatment
> 300	Unsuitable for drinking	Not suitable

3.4. Water Quality for Agricultural Purposes

Groundwater quality assessment is essential for evaluating the suitability of water resources for irrigation, as each crop requires irrigation water with specific physicochemical characteristics. To ensure that irrigation water supports crop productivity and avoids negative impacts, such as reduced growth or yield quality, several hydrochemical indices are widely used, either independently or in combination, by different organizations and researchers (Dhaoui et al. 2023). The proportion of Na⁺ relative to total cations is a key factor in groundwater suitability for irrigation, as it strongly influences soil permeability and water infiltration (Mansouri et al. 2025). EC is widely used as a key indicator for assessing the salinity hazard of irrigation water because high EC values are directly linked to soil salinization, especially in poorly drained soils (Dendup et al. 2022). In this study, eight widely used indices include EC, SAR, Na%, MAR, RSC, PI, KR, and PS. Ionic concentrations were expressed in meq/L, except for EC, which was measured in μS/cm. All indices were determined using their respective standard equations.

• 1Electrical conductivity (EC)

  EC is a direct indicator of salinity levels in soil solution and irrigation water; higher EC values reflect higher concentrations of dissolved salts. EC is also directly measured in the field for rapid in situ evaluation of salinity conditions. Elevated EC in irrigation water can compromise plant osmotic regulation, consequently reducing the efficiency of water and nutrient uptake (Ranabhat et al. 2025).

• 2Sodium adsorption ratio (SAR)

  SAR indicates the potential sodium hazard of irrigation water (Mukonazwothe et al. 2022). Elevated SAR values reflect an increased risk of sodium accumulation in soils, which may lead to structural degradation (Zhao et al. 2025). The SAR is calculated using Equation (5):

$$\mathit{SAR}=\frac{{\mathrm{Na}}^{+}}{\sqrt{\frac{{\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}}{2}}}.$$ (5)

• 3Sodium percentage (Na%)

  Na% is one of the most frequently applied indices for evaluating the suitability of water for irrigation (Wilcox 1955). Excessive sodium levels in irrigation water can significantly reduce soil permeability, leading to poor internal drainage. This occurs because sodium ions in water may replace calcium and magnesium ions on the soil exchange complex, thereby deteriorating soil structure. Under such conditions, soils often restrict both air and water movement when moist and tend to harden upon drying (Dheeraj et al. 2025). Na% values were computed according to Equation (6):

$$\mathrm{Na}\%=\frac{{\mathrm{Na}}^{+}+{\mathrm{K}}^{+}}{{\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}+{\mathrm{Na}}^{+}+{\mathrm{K}}^{+}}\times 100.$$ (6)

• 4Magnesium hazard (MH)

  MH considers the balance between Mg²⁺ and Ca²⁺, as excessive magnesium can negatively affect soil structure and reduce crop productivity (Vranešević et al. 2024). The index is calculated using Equation (7):

$$\mathrm{MH}=\left(\frac{{\mathrm{Mg}}^{2+}}{{\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}}\right)\times 100.$$ (7)

• 5Residual sodium carbonate (RSC)

  RSC is widely applied to assess the suitability of groundwater for irrigation. When carbonate (CO₃ ²⁻) and bicarbonate (HCO₃ ⁻) concentrations exceed those of Ca²⁺ and Mg²⁺, precipitation of Ca²⁺ and Mg²⁺ may occur, leading to an increase in sodium hazard within the soil solution. This imbalance reduces soil permeability, alters its structure, and negatively affects crop productivity (Mukonazwothe et al. 2022). The RSC value is calculated using Equation (8):

$$\mathrm{RSC}=\left({{\mathrm{HCO}}_3}^{-}+{{\mathrm{CO}}_3}^{-}\right)-\left({\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}\right).$$ (8)

• 6Permeability index (PI)

  PI reflects the potential long‐term impact of irrigation water on soil permeability (Snousy et al. 2022), which is mainly controlled by the concentrations of Ca²⁺, Mg²⁺, Na⁺, and HCO₃ ⁻ (Ghosh and Bera 2023). The calculation of PI was performed using Equation (9):

$$\mathrm{PI}=\frac{\left({\mathrm{Na}}^{+}+\sqrt{{{\mathrm{HCO}}_3}^{-}}\right)}{\left({\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}+{\mathrm{Na}}^{+}\right)}\times 100.$$ (9)

• 7Kelly's ratio (KR)

  KR is employed for evaluating the potential salinity hazard of groundwater by comparing the concentration of sodium with those of calcium and magnesium. A high sodium‐to‐calcium and magnesium ratio can lead to the formation of harmful compounds, reducing water quality and hindering plant growth (Amwele et al. 2021). The KR values were calculated using Equation (10):

$$\mathrm{KR}=\frac{{\mathrm{Na}}^{2+}}{{\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}}.$$ (10)

• 8Potential salinity (PS)

  PS is a parameter used to estimate the salinity hazard of agricultural water supplies. It is calculated by adding the sum of chloride and half the sulfate levels, both expressed in meq/L. This parameter provides insight into the long‐term effect of dissolved salts on soil and crop productivity (Omeka 2024). The PS values were determined using Equation (11):

$$\mathrm{PS}={\mathrm{Cl}}^{-}+\frac{{{\mathrm{SO}}_4}^{2-}}{2}.$$ (11)

The classification criteria adopted for each index are presented in Table 4.

TABLE 4.

Categorization of groundwater quality indices for irrigation purposes.

Indicator	Range	Class
EC (Poonia et al. 2023)	100–250	Excellent
	250–750	Good
	750–2000	Permissible
	2000–3000	Doubtful
	> 3000	Unsuitable
SAR (Akintunde et al. 2022)	0–10	Excellent
	10–18	Good
	18–26	Doubtful
	> 26	Unsuitable
Na% (Monika et al. 2024)	< 20	Excellent
	20–40	Good
	40–60	Permissible
	60–80	Doubtful
	> 80	Unsuitable
MH (Hussein et al. 2024)	≤ 50	Suitable
	> 50	Unsuitable
RSC (Makki et al. 2021)	< 1.25	Good
	1.25–2.5	Doubtful
	> 2.5	Unsuitable
PI (Aşik and Özsoy 2023)	> 75	Excellent
	25–75	Good
	< 25	Unsuitable
KR (Olurin et al. 2022)	< 1	Good
	> 1	Unsuitable
PS (Bouselsal et al. 2025)	< 5	Excellent to good
	5–10	Good to injurious
	> 10	Injurious to unsatisfactory

3.5. Statistical and Graphical Analyses

Groundwater appropriateness for both drinking and irrigation purposes was assessed through statistical and graphical techniques in OriginPro 2025. Hydrogeochemical facies were interpreted with a Durov diagram, while boxplots illustrated the distribution and variability of irrigation indices. Salinity and sodium hazards were classified using Wilcox (Na% vs. EC) (Aher et al. 2022). Moreover, USSL (EC vs. SAR) diagrams (Demircioğlu et al. 2023) highlight potential risks of soil salinization, sodification, and alkalinity (Wang et al. 2020). The correlation matrix was also employed to examine relationships among irrigation water quality indices and their associations. To further investigate underlying patterns in the dataset, PCA was applied, as it reduces data dimensionality and converts correlated variables into independent PCs. Each PC represents a linear combination of the original indices weighted by their eigenvectors (loadings) (Dheeraj et al. 2025). Eigenvalues indicate the variance explained by each component while loadings reveal the relative contribution of individual irrigation indices. This approach facilitates the identification of dominant patterns controlling irrigation water quality. In addition, cluster analysis was employed to group groundwater samples with similar irrigation characteristics, thereby facilitating the interpretation of statistical relationships.

3.6. GIS and Mapping

Geostatistical techniques were applied to capture the spatial variability of groundwater quality. Kriging was selected as the primary interpolation method because it models spatial dependence through variogram analysis and enables estimation at unsampled points. Both ordinary kriging (OK) and universal kriging (UK) were found to better reflect the dataset's variability (Benam‐Beltoungou et al. ²⁰²⁵). In particular, OK proved effective for describing spatial dependence and autocorrelation among sampling sites, providing a reliable basis for accurate spatial prediction (Mansouri et al. 2025). GIS techniques were further employed to map the spatial and temporal distribution of groundwater quality. ArcGIS 10.8 and Google Earth were used to generate the study area map, georeferenced the sampling locations, and produce thematic maps. These included georeferenced layers of irrigation‐related indices and WQI, offering spatial insights into groundwater suitability for irrigation (Wang et al. 2024).

The LU/LC map of the study area for 2022 was produced from multispectral satellite imagery. Data were retrieved from Esri's Living Atlas of the World (https://livingatlas.arcgis.com/landcoverexplorer/Esri; Redlands, CA, USA), which provides curated, analysis‐ready datasets derived from sensors such as the Sentinel‐2 MSI and the Landsat‐8 OLI. These datasets are preprocessed to reduce computational demands and enhance usability. Additional preprocessing steps were performed in ArcGIS 10.8 (Esri, Redlands, CA, USA) to refine data quality before further classification.

4. Results

4.1. Assessment of Groundwater for Safe Drinking and Household Use

The TDS content in the groundwater ranges from 3652 to 13,835 mg/L, with a mean value of 7074.33 mg/L. All samples considerably exceed the recommended limit of 1000 mg/L. According to the applied classification system (Table 5), groundwater is not suitable for drinking or irrigation and is generally within the brackish‐to‐saline domain. TH ranges from 1588.68 to 3943.22 mg/L, with an average of 2177.33 mg/L. Based on standard classification criteria (Table 1); all analyzed samples qualify as “very hard” water. As illustrated in the TDS–TH relationship diagram (Figure 4), 83.33% of the 30 shallow groundwater samples fall within the brackish category, whereas 16.67% fall within the saline category. All samples (100%) are categorized as very hard.

TABLE 5.

Statistical summary (min, max, and mean) of drinking water and irrigation indices.

Indices	WQI	TDS	TH	EC	SAR	Na%	MH	RSC	PI	KR	PS
Min	346.51	3652	1588.68	4586	3.26	28.87	18.60	−59.50	30.95	0.38	33.68
Max	1154.63	13,835	3943.22	18,680	29.62	71.63	69.78	−31.51	72.41	2.50	178.13
Average	612.83	7074.33	2177.33	9605.67	13.15	55.86	41.90	−40.18	57.35	1.37	83.30

FIGURE 4.

Scatter plot of TDS versus TH in shallow groundwater samples.

WQI results derived from 30 groundwater samples, ranged between 346.51 and 1154.63, having a mean of 612.83 (Table 5). Based on the classification guidelines, where WQI values above 300 indicate unsuitability for drinking, all samples (100%) were categorized as unfit for human consumption (Table 3). The lowest WQI value was observed at well W28 (346.51), whereas the highest was recorded at well W07 (1154.63), showing marked variability in groundwater quality across the study area (Figure 5a). Correlation analysis showed a perfect positive relationship between WQI and TDS (R ² = 1) (Figure 5b).

FIGURE 5.

(a) Changes in WQI values among subsurface water samples in the investigated region; (b) relationship between WQI and TDS.

4.2. Suitability of Groundwater for Irrigation of Agricultural Lands

For the present research, the suitability of water for agricultural use was evaluated through selected key indicators most relevant to water quality. These indicators were categorized into classes ranging from excellent to poor, providing a clearer representation of water quality levels. EC of groundwater in the investigated region varied from 4586 to 18,680 μS/cm (Table 5; Figure 6a). According to the established classification system (Table 4), all samples (100%) fell into the fifth category (> 3000 μS/cm), which designates groundwater as unsuitable for irrigation. Not a single examined sample fell into the excellent, good, permissible, or doubtful categories. SAR values, derived from Table 5 and illustrated in Figure 6b, varied between 4.8 and 10.3 meq/L, with a mean value of 6.3 meq/L. Based on the classification criteria (Table 4), 30% of the samples were categorized as excellent (0–10), 50% as good (10–18), 16.67% as doubtful (18–26), and 3.33% as unsuitable for irrigation purposes (> 26). Na% values ranged from 28.87 to 71.63, with an average of 55.86 (Table 5; Figure 6c). The classification results (Table 4) showed that 16.67% of the samples were categorized as suitable (20–40), 40% as permissible (40–60), and 43.33% as doubtful (60–80). None of the examined samples qualified for the excellent and unsuitable. MH values ranged from 18.60 to 69.78, with a mean of 41.90 (Figure 6d). Based on the classification criteria, nearly 66.67% of the samples exhibited MH values ≤ 50%, indicating that the water is suitable for irrigation, whereas the remaining 33.33% exceeded this threshold (> 50), making the water unsuitable for agricultural use. RSC values (Figure 6e) ranged from −59.50 to −31.51 meq/L, with an average of—40.18 meq/L. Based on the classification criteria (Table 4), all groundwater samples (100%) were classified as good for irrigation (< 1.25), demonstrating their suitability for agricultural use. Not a single sample met the criteria for classification as doubtful and unsuitable classes.

FIGURE 6.

Boxplots of irrigation‐related indices: (a) EC (μS/cm), (b) SAR, (c) Na%, (d) MH, (e) RSC, (f) PI, (g) KR, and (h) PS.

The PI values ranged from 31.43% to 72.41%, averaging 57.35% (Table 5; Figure 6f). According to the classification (Table 4), all samples (100%) were categorized as good (25–75), indicating suitability for irrigation. No sample was found to fit within the excellent or unsuitable categories. The KR varied between 0.38 and 2.50 meq/L, averaging 1.37 meq/L (Table 5; Figure 6g). Based on the classification (Table 4), 80% of the samples were unsuitable for irrigation (KR > 1), while only 20% were considered suitable (KR < 1). In contrast, the PS values varied between 33.68 and 178.13 meq/L, averaging 83.30 meq/L (Table 5; Figure 6h). The classification results (Table 4) show that all samples (100%) fall within the harmful to unsuitable salinity range (> 10). All investigated samples fell outside the excellent, good, and injurious classes.

4.3. Spatial Distribution and Uncertainty Analysis (Kriging Variance)

The kriging variance map (Figure 7) was generated to evaluate the spatial uncertainty associated with the interpolation of groundwater quality and irrigation indices. Areas characterized by low variance values correspond to locations with higher sampling density and therefore greater prediction reliability. In contrast, higher variance values are mainly observed in sparsely sampled areas, indicating increased interpolation uncertainty. Overall, the map provides an assessment of the confidence associated with the spatial prediction results.

FIGURE 7.

Kriging standard error map showing spatial prediction uncertainty.

4.4. Classification Based on Wilcox and USSL Diagrams

According to the Wilcox classification (Tables 6 and 7), which considers the association between %Na and EC (Figure 8a), most groundwater samples were found to fall into very high‐risk categories. Thirteen samples (43.33%) were classified as C4–S4, indicating very high salinity and sodium hazard. Twelve samples (40%) fell into the C4–S3 class, reflecting very high salinity with high sodium hazard. The remaining five samples (16.67%) were placed in the C4–S2 class, corresponding to very high salinity and moderate sodium hazard.

TABLE 6.

Irrigation water classes based on salinity and sodium hazards (Ranabhat et al. 2025).

Classification	Salinity/sodium hazard	Water class	Classification	Water class
C1	Low	Appropriate	S1	Suitable
C2	Medium	Permissible	S2	Appreciable
C3	High	Poor	S3	Harmful
C4	Very high	Unsafe	S4	Unsafe

TABLE 7.

Wilcox diagram classification of irrigation water (Ranabhat et al. 2025).

Group/class	Water quality for agriculture
C1S1	Fresh—completely suitable for agriculture
C1S2, C2S2, C2S1	Brackish—approximately suitable for agriculture
C1S3, C2S3, C3S1, C3S2, C3S3	Marginal—usable with restrictions for agriculture
C4S4, C4S1, C1S4, C2S4, C3S4	Unsuitable—harmful for agriculture

FIGURE 8.

(a) Wilcox and (b) USSL diagrams showing groundwater suitability for irrigation.

Based on the USSL classification (Tables 8 and 9) relating SAR to EC (Figure 8b), most groundwater samples fall into very high salinity categories. About 15 of the samples (50%) are in the C4–S2 class, representing very high salinity with medium sodium hazard. A further seven samples (23.33%) belong to the C4–S4 class, reflecting very high salinity with very high sodium hazard. Irrigation is not recommended without prior treatment as it may result in serious soil deterioration and decreased water penetration. The remaining five samples (16.67%) fall within the C4–S1 and C4–S3 classes, also indicating unsuitability for irrigation. Overall, all samples are unsuitable for irrigation.

TABLE 8.

Sodium adsorption ratio (SAR) classification for irrigation water (Gevorgyan et al. 2025).

Class	Sodium hazard level	Description
S1	Low	Generally suitable for agriculture; has little impact on soil properties
S2	Medium	May cause moderate sodium accumulation, especially in clay‐rich soils
S3	High	Causes clay dispersion, reduces permeability, and restricts aeration
S4	Very high	Unsuitable without treatment; leads to severe soil degradation and poor infiltration

TABLE 9.

Salinity hazard classification based on electrical conductivity (EC) (Gevorgyan et al. 2025).

Class	Salinity risk level	Description
C1	Low	Fit for most crop types and soils, with negligible risk to plant growth
C2	Medium	Generally appropriate for soils with moderate drainage capacity
C3	High	May cause salt buildup in poorly drained soils, reducing crop yields
C4	Very high	Overall, not suitable for irrigation under standard conditions

4.5. Land Use and Land Cover (LULC)

Figure 9a illustrates the spatial distribution of land use and land cover categories across an area of approximately 682 km² while Figure 9b presents the proportional distribution of these categories. According to the classification results, the categories by area (km²) are as follows:

• Bare land: 71.7%

• Agricultural land (crops): 22.8%

• Built‐up areas: 3.6%

• Natural pastures: 1.9%

• Water bodies and wetlands: less than 0.01%

FIGURE 9.

(a,b) Land use/land cover (LULC) map of the study area showing the spatial distribution of WQI.

The results show that bare and arid lands dominate the study area (71.7%), followed by agricultural lands (22.8%). Built‐up areas account for only 3.6% of the total area. This distribution indicates that the impact of agricultural and urban activities remains limited and does not lead to substantial changes in land use patterns within this extremely arid environmental context.

4.6. Correlation Analysis of Irrigation Water Quality Parameters

To evaluate the relationships among key parameters affecting irrigation water quality, a Pearson correlation analysis was performed (Table 10) including EC, SAR, Na%, MH, PI, RSC, KR, and PS. The results revealed that EC exhibited strong positive correlations with all other parameters, reflecting the dominant influence of salinity on groundwater chemistry. Similarly, SAR, MH, and PS showed strong correlations with most indices, indicating their close association with ionic composition. In contrast, RSC showed strong negative correlations with most parameters, except for KR and PI, where moderate relationships were observed. Notably, very high correlations were identified between EC and PS (r = 0.988), KR with SAR (r = 0.965) and Na% (r = 0.960), and especially between Na% and PI (r = 0.999). The near‐perfect correlation between Na% and PI (r = 0.999), together with the very strong correlations between KR and both SAR (r = 0.965) and Na% (r = 0.960), suggest that these indices provide largely overlapping information and are influenced by similar hydrochemical processes. Therefore, although all indices were retained to allow comparison with previous irrigation water quality studies, greater emphasis was placed on the most representative and widely used indicators, particularly EC, SAR, and Na%. The PCA results further support this interpretation by grouping these highly correlated variables within the same component, suggesting a degree of statistical redundancy among them.

TABLE 10.

Correlation matrix of irrigation water quality parameters.

	EC	SAR	Na%	MH	RSC	PI	KR	PS
EC	1
SAR	0.943	1
Na%	0.785	0.897	1
MH	0.927	0.894	0.807	1
RSC	−0.923	−0.783	−0.532	−0.848	1
PI	0.771	0.889	0.999	0.795	−0.512	1
KR	0.845	0.965	0.960	0.816	−0.607	0.957	1
PS	0.988	0.911	0.774	0.927	−0.922	0.760	0.814	1

Note: Bold values represent strong positive or negative correlations that are statistically significant.

The PCA (Table 11) shows that PC1 explains 86.36% in the overall dataset variance, highlighting the dominant influence of salinity–sodicity parameters on groundwater quality. Strong positive loadings of EC, SAR, Na%, MH, PI, KR and PS, contrasted with the negative contribution of RSC, indicate that this component mainly reflects the combined effect of salinity and sodium hazard. PC2 explains 10.98% of the variance and is characterized by positive loadings on RSC, PI, Na%, and KR, and negative loadings on EC, PS, and MH. This suggests that PC2 primarily captures the balance between residual carbonate effects and overall salinity stress. Together, the first two components explain over 97.34% of the total variance, providing a robust representation of the key factors governing groundwater suitability for irrigation in the study area.

TABLE 11.

Principal component loadings for irrigation indices.

Parameter	PC1	PC2
EC	0.367	−0.248
SAR	0.373	0.053
Na	0.346	0.423
MH	0.359	−0.16299
RSC	−0.313	0.59391
PI	0.343	0.44678
KR	0.357	0.3204
PS	0.363	−0.27234
Eigenvalue	6.69	0.88
% Variance	86.36%	10.98%
Cumulative	86.36%	97.34%

Note: Bold values indicate statistically significant loadings, either positive or negative, reflecting strong correlations.

The scree plot (Figure 10) shows a sharp decline after the first PC, indicating that PC1 explains the majority of the variance in the dataset. A second, much smaller eigenvalue is observed for PC2, whereas the remaining components have negligible contributions. This pattern confirms that two PCs are sufficient to describe the hydrochemical variability of the groundwater system.

FIGURE 10.

Scree plot showing eigenvalues of principal components (PCA).

4.7. Geochemical Properties of Water

Table 12 presents the classification of groundwater samples into nine hydrochemical facies based on the Durov diagram. Figure 11 illustrates that most of the samples, representing 80% of the total, are located in Field 7, indicating a predominance of Na–Cl‐type waters. About 16.67% of the samples fall within Field 5, representing mixed facies without a dominant cation or anion. The remaining 3.33% are positioned in Field 2, corresponding to waters dominated by bicarbonate (HCO₃ ⁻).

TABLE 12.

Groundwater types from Durov diagram (Lloyd and Heathcote 1985).

Field	Water type
1	HCO3–Ca dominance → recharge in limestone/sandstone aquifers
2	Ca–HCO3 waters; Mg → dolomite interaction; Na → ion exchange
3	HCO3–Na dominance → ion exchange or CO2‐driven bicarbonate
4	SO4–Ca dominance → volcanic/gypsum recharge or mineral dissolution
5	Mixed waters without clear dominant ion
6	Rare type: SO4 (anion selective) + Na dominance → mixing/dissolution
7	Cl–Na waters; may result from cement contamination or reverse ion exchange
8	Strong Cl–Na dominance → reverse ion exchange, typical Na‐Cl waters
9	Na–Cl dominance → downgradient waters via dissolution (end‐member type)

Note: HCO₃ ⁻ refers to bicarbonate, Ca²⁺ to calcium, Mg²⁺ to magnesium, CO₂ to carbon dioxide, SO₄ ²⁻ to sulfate, Na⁺ to sodium, and Cl− to chloride.

FIGURE 11.

Durov plot of groundwater hydrochemistry in the study area.

5. Discussion

The high TDS values in the Oued Souf aquifer result from the combined effects of geochemical and climatic factors. Dissolution of evaporitic minerals such as halite and gypsum enriches groundwater with Na⁺, Ca²⁺, Cl⁻, and SO₄ ²⁻, while cation exchange further increases sodium at the expense of calcium and magnesium, elevating the sodicity hazard. Arid conditions promote evaporation, concentrating dissolved salts, which explains why the water is generally brackish to saline and unsuitable for drinking or irrigation, consistent with previous reports in Algeria (Djebassi et al. 2021; Ghodbane et al. ²⁰²²). The high total hardness is mainly due to calcium and magnesium from carbonate and sulfate mineral dissolution (e.g., dolomite and gypsum), limiting irrigation suitability and posing domestic challenges such as scaling, reduced soap efficiency, and decreased soil permeability. These findings align with earlier studies in arid and semi‐arid regions, which demonstrated that excessive salinity and hardness are linked to evaporite dissolution, ion exchange, and limited recharge under high‐evaporation conditions. Acquah et al. (2025), for instance, reported that groundwater with elevated TDS levels above permissible limits can deteriorate taste, stain clothes, and cause scaling in household appliances. TDS and TH serve as key parameters for evaluating water suitability for drinking. Elevated TDS levels reflect increased dissolved salts, which may result from natural rock weathering or human activities. Consumption of water with elevated TDS may cause health issues such as laxative effects or constipation (WHO, 2011). Water with low TDS values generally indicates clean and safe drinking water, whereas water with higher TDS levels may only be suitable for irrigation or should be used as an alternative source in the absence of cleaner water. TH is another key parameter affecting water potability. The hardness mainly results from the presence of calcium and magnesium ions. Prolonged consumption of hard water may contribute to health problems such as arterial calcification and renal disorders. In addition to health effects, hard and very hard water can cause practical issues such as the formation of soap scum, scaling of pipes, corrosion of appliances, and dryness of skin and hair. Compared with surface waters, groundwater generally exhibits higher hardness and salinity due to extended rock–water interaction and mineral dissolution processes (Kumari et al. 2025). The WQI values obtained in this study (346.51–1154.63; mean 612.83) indicate that all groundwater samples exceeded the permissible drinking water limit (WQI > 300), rendering them unsuitable for human consumption. The elevated WQI values are primarily due to high concentrations of major ions, including sodium, nitrate, chloride, and sulfate. These ions originate from both geogenic processes, including gypsum and halite dissolution, and anthropogenic activities. In particular, wastewater infiltration contributes to contamination in urban areas, while fertilizer application and irrigation return flow intensify nitrate and salinity levels in agricultural zones. Similar findings have been reported in other arid and semi‐arid regions. For example, Marzouki et al. (2025) documented WQI values exceeding 500 in eastern Morocco, mainly due to salinity and nitrate contamination. Likewise, Hidouri et al. (2025) reported comparable results from southwestern Tunisia, where WQI values exceeded 300 due to gypsum, halite, and anhydrite dissolution, coupled with direct and reverse ion‐exchange processes. These regional comparisons highlight the high vulnerability of groundwater quality in such environments to both geogenic salinization and human‐induced pollution, as also emphasized by (Boukhallat et al. 2025). The implications of these findings are significant. The unsuitability of the studied groundwater for drinking underscores the urgent need for sustainable water resource management strategies. Potential measures include regulating agricultural fertilizer use, enhancing wastewater‐treatment infrastructure, and exploring desalination or blending techniques to ensure a safe and dependable source of drinking water.

5.1. Geospatial Analysis of WQI and Irrigation Suitability Through GIS

The WQI map (Figure 12a) shows high values mainly in the northern and northeastern areas, which coincide with elevated nitrate concentrations. This pattern likely reflects anthropogenic influences associated with both urban wastewater infiltration from residential areas and, to a lesser extent, agricultural activities. The contribution from domestic sewage is considered more significant due to the dominance of residential land use in the area, while smaller values occurred in the southern part of the study area. The EC map (Figure 12b) indicates lower values were recorded in the south, while higher values occurred in the north, consistent with groundwater movement patterns. The SAR and Na% maps (Figure 12c,d) indicated that groundwater in the southern part of the study area ranged from suitable to conditionally suitable with respect to sodium hazard. However, when salinity (EC) was also considered through the Wilcox and USSL classifications, the overall irrigation suitability decreased substantially, and most samples were classified as unsuitable due to their high salinity levels. The MH map (Figure 12e) showed suitable conditions across most of the area, except in the northern part. PI and RSC (Figure 12f,g) reflected good quality in the entire region. The KR map (Figure 12h) revealed suitable water in the south but unsuitable conditions in the north, a pattern also observed in the PS map (Figure 12i), where all areas were unsatisfactory. The kriging variance map revealed spatial variations in interpolation uncertainty across the study area. Lower uncertainty values were observed in the western part of the study area, whereas higher values occurred in the remaining areas. Despite these spatial differences, the interpolated maps showed consistent spatial patterns, indicating that the observed uncertainty did not significantly influence the interpretation of groundwater quality or irrigation suitability. Therefore, the interpolation results can be considered sufficiently reliable to support the main conclusions of this study.

FIGURE 12.

(a–i) Geographical variation of WQI values and irrigation indices in the investigated region.

5.2. Irrigation Suitability Assessment

EC is considered a fundamental parameter because it directly reflects the levels of ions in solution and their impact on soil health and crop development. According to EC values, all samples (30) were classified in the fifth category, indicating very high salinity levels that render the water unsuitable for irrigation. Such elevated salinity restricts water movement in soils, reduces nutrient availability, and imposes osmotic stress on plants, ultimately affecting crop growth and productivity (Fadl et al. 2024). The high salinity observed in the Oued Souf region is primarily linked to the dissolution of gypsum‐ and halite‐bearing formations, in addition to the effect of intense evaporation under arid climatic conditions. These processes increase the concentration of dissolved salts and contribute significantly to groundwater salinization, particularly in shallow aquifers compared with deeper ones (Boukhallat et al. 2025). In addition to hydrogeological factors, soil characteristics also play a crucial role in amplifying salinity impacts. The study area is largely dominated by fine sandy deposits from Quaternary dune formations, with sandy loam patches, gypsum‐rich corridors (Sahans), and saline depressions (Sebkhas). These sandy‐to‐sandy loam textures, while favoring drainage, may enhance the accumulation of salts in the plant root zone, thereby intensifying the adverse effects of salinity on crop productivity.

Elevated EC values, indicating high salinity, create drought‐like conditions where plants are unable to absorb enough water because of competition with excess ions in the soil. Irrigation with saline water negatively affects soil structure and restricts crop growth. The buildup of salts in the root zone increases osmotic stress, disrupting biochemical and metabolic activities. Consequently, utilizing brackish groundwater for irrigation accelerates chlorophyll degradation, reduces protein synthesis, inhibits enzyme activity, and lowers photosynthetic efficiency, ultimately decreasing agricultural productivity (Al‐Rashidi et al. ²⁰²³). SAR, Na%, RSC, and are all closely associated with the amount of Na⁺ present in irrigation water. Elevated Na⁺ levels can displace Ca²⁺ and Mg²⁺ in the soil while interacting with HCO₃ ⁻ and CO₃ ²⁻, leading to base exchange reactions that cause soil compaction and reduced permeability. This ultimately limits water movement and root penetration, negatively affecting plant growth and crop productivity (Kumari et al. 2025). Additionally, high sodium levels may result in soil salinization (through combination with chloride ions) or alkalinization (through combination with bicarbonate ions), particularly when calcium and magnesium concentrations are low, further intensifying the reduction in soil fertility. According to the SAR assessment, nine samples were classified as exhibiting an excellent level, indicating a very low risk of sodicity when used for irrigation. Around half of the samples—fifteen—were placed in the good class, reflecting moderate sodium and salinity levels that may impose some limitations on crop development, yet remain broadly acceptable. In contrast, five samples were classified within the doubtful category, where irrigation use could lead to soil compaction and reduced fertility due to sodication; however, such water may still be utilized after treatment or dilution with freshwater. Only one of the samples was classified as unsuitable, with SAR values above 10. Such high levels pose serious concerns, as they diminish soil permeability and hydraulic conductivity, particularly in gypsum‐rich soils, thereby restricting plant development (Mohammed et al. 2023). The Na% results revealed that five groundwater samples were determined to be suitable for agricultural irrigation, while 12 were within the permissible range. However, 13 of the samples were categorized as doubtful, reflecting a potential risk of soil sodicity and reduced permeability if such water is used continuously for irrigation. Unlike the SAR classification, which emphasizes the balance between sodium and divalent cations, the Na% index highlights the overall dominance of sodium in the water. Long‐term irrigation with water falling into the doubtful category may gradually deteriorate soil structure and fertility, necessitating management practices such as blending with freshwater or periodic leaching to minimize adverse impacts on crops. In the study area, the main sources of sodium in groundwater are linked to cation exchange processes within Mio‐Pliocene clay formations, particularly smectite‐ and illite‐rich layers. Additional contributions may also arise from anthropogenic activities, including agricultural return flow and wastewater infiltration, which further elevate Na⁺ concentrations (Boukhallat et al. 2025). In regions where groundwater contains elevated sodium levels, soil infiltration capacity tends to decline due to reduced hydraulic conductivity. This effect is particularly pronounced in soils dominated by montmorillonitic clays, which are more vulnerable to sodium‐induced structural degradation than kaolinitic soils. The attachment of Na⁺ ions to soil cation exchange sites disrupts aggregate stability, leading to uneven soil structure and a consequent decrease in permeability, ultimately restricting water availability for crops (Al‐Rashidi et al. ²⁰²³).

Among 30 groundwater samples analyzed, 10 were unsuitable for irrigation due to MH values exceeding the recommended threshold of 50%. This indicates a relative dominance of magnesium over calcium in parts of the aquifer, which can negatively impact soil structure and crop productivity. The high magnesium concentrations are primarily caused by dolomite dissolution (CaMg (CO₃)₂) present in the Mio‐Pliocene formations, which increases Mg²⁺ concentrations in the water and creates an imbalance between calcium and magnesium. These natural geochemical processes explain the high MH values observed in the study area. All samples meet the requirements for irrigation use on both RSC and PI criteria, indicating that the water poses no significant risk of alkalinity or sodium‐related soil hazards. Out of 30 groundwater samples, 24 were considered unsuitable according to the KR, while all samples (30) fell into the injurious to unsatisfactory category according to the PS, indicating potential risks to soil structure and crop productivity if used for irrigation without proper management. The findings of this study are in harmony with those reported from comparable arid regions of southern Tunisia, particularly in the Jérid geothermal field within the SASS basin. Previous hydrochemical and isotopic investigations conducted in that area indicated that groundwater is highly mineralized and dominated by an SO₄–Cl–Na–Ca water type, mainly due to the dissolution of evaporitic formations and pyrite‐bearing rocks. These studies also showed that most groundwater samples were unsuitable for drinking and generally inappropriate for irrigation water using SAR, Na%, and PI and MH, which aligns with the patterns observed in the Oued Souf aquifer. Stable isotope evidence (δ¹⁸O and δ²H) further suggested recharge under colder and wetter paleoclimatic conditions, with limited mixing between geothermal and shallow cold groundwater hydrogeological mechanisms that may likewise be relevant in the study area (Tarki et al. 2024).

According to the Wilcox diagram, all 30 groundwater samples were classified within categories indicating very high salinity with low to very high sodium content, suggesting potential limitations for irrigation. It should be noted that the SAR and Na% indices primarily evaluate sodium hazard, whereas the Wilcox diagram incorporates both sodium content and salinity (EC). Therefore, groundwater samples that appear suitable or permissible based on sodium‐related indices may still exhibit irrigation limitations because of their elevated salinity levels. These findings highlight the importance of adopting effective management strategies to mitigate the effects of salinity and sodicity on soil and crops. Practical approaches include leaching treatments and the use of soil amendments, and selecting salt‐ or sodicity‐tolerant crops (e.g., date palms and barley) can help alleviate the challenges associated with these water quality conditions. The elevated sodium levels observed in the samples are likely linked to the occurrence of carbonate and bicarbonate ions, which can cause the precipitation of calcium and magnesium, leading to a relative increase in sodium concentration in the soil. This process may reduce soil permeability and compromise soil structure, further emphasizing the importance of proper management practices to safeguard agricultural productivity (Sutradhar and Mondal 2021). Similarly, the USSL diagram classified all 30 samples as very high salinity with moderate to very high sodium content, confirming that the combined effects of elevated salinity and sodium hazard represent the main constraints on groundwater use for irrigation in the study area. The agreement between the Wilcox and USSL classifications indicates that groundwater suitability for irrigation is primarily limited by the combined effects of high salinity and sodium hazard. Although the SAR and Na% indices suggest that some samples are suitable or permissible with respect to sodium hazard, the inclusion of salinity (EC) in the Wilcox and USSL assessments results in a more restrictive classification for irrigation use. Therefore, the apparent differences among these indices reflect the distinct hydrochemical parameters considered by each method rather than any inconsistency in the groundwater quality assessment. Overall, the elevated salinity levels represent the principal factor restricting the use of these groundwater resources for irrigation without appropriate management practices. These findings underscore the need for targeted management strategies to support sustainable irrigation practices in the study area.

This observation is consistent with previous studies in Tunisia (such as Panagiotou et al. ²⁰²⁵), which reported that about 50% of groundwater samples from the Grombalia phreatic aquifer were classified unfit for irrigation owing to excessive salinity, aligning well with the findings of the present study regarding elevated salinity and sodium levels. The findings of our study regarding the high salinity of groundwater in the Oued Souf region are consistent with previous research on saline soils and waters, such as (Arjumend and Turan 2020), which showed that applying biochar can improve soil physicochemical characteristics and reduce the adverse impacts of salinity on plant growth and crop productivity. Biochar works by adsorbing excess sodium ions (Na⁺) in the soil, thereby reducing osmotic stress on plants. It also improves cation exchange capacity and soil permeability, and supports beneficial soil microorganisms, enhancing soil stability and increasing organic matter and nutrient content. Although our study did not apply these materials, the comparison suggests that integrating solutions such as biochar or salt‐tolerant plants could be an effective strategy for addressing salinity in both water and soil. Implementing these amendments in future studies may help reduce salinity issues, improve soil permeability, and protect crops from the harmful effects of salinity, thereby promoting sustainable agriculture in the region. To mitigate the impacts of elevated salinity on irrigation, practical strategies such as drip irrigation, solar‐powered desalination, and ceramic membrane technologies can be adopted. These approaches reduce water losses, improve water quality, and minimize salt accumulation in soils, particularly under the arid conditions of the study area. The PCA results reveal that PC1, which explains more than 86% of the total variance, represents a salinity–sodium factor. This component is strongly defined by EC, SAR, Na%, MH, KR, PS, and PI, whereas RSC contributes negatively. Such a pattern reflects the dominant role of salinity and sodium hazards in controlling groundwater quality for irrigation, with carbonate equilibrium exerting an opposing influence. PC2, accounting for about 11% of the variance, is mainly associated with positive loadings of RSC, PI, Na%, and KR, contrasted by negative contributions from EC, PS, and MH. This indicates a balance between residual carbonate processes and sodium enrichment versus overall salinity and hardness effects. Together, these two components highlight that groundwater suitability for irrigation is governed by the interplay of salinity, sodium hazard, and the carbonate dynamics within the research area.

The correlation analysis highlights the strong interdependence among the irrigation water quality indices, particularly those related to salinity and sodium hazards. The strong correlation between EC and PS (r = 0.988) reflects that the salt load is the main driver of conductivity in groundwater, consistent with the dominance of dissolved solids observed in the study area. Likewise, the very high correlations of SAR with KR (r = 0.965) and Na% (r = 0.960) confirm that sodium enrichment plays a central role in controlling soil sodicity and permeability risks. The nearly perfect correlation between Na% and PI (r = 0.999) indicates that both indices provide almost identical information, pointing to sodium as the key determinant of irrigation water quality. In contrast, the negative correlation of RSC with most indices suggests that carbonate equilibrium acts in opposition to salinity–sodicity effects, potentially mitigating or masking sodium‐related risks under certain conditions. These patterns emphasize that in the Oued Souf region, salinity and sodium hazards are the dominant factors affecting irrigation water suitability, with carbonate chemistry playing a secondary, sometimes compensatory role.

5.3. Geochemical Properties

The Durov diagram, a modified version of the Piper diagram, provides a clearer representation of hydrochemical facies and the underlying geochemical processes, including ion exchange, dissolution, and mixing (Hounsinou 2023). Within the Quaternary groundwater system of the Oued Souf region, the majority of samples plot in Field 7, corresponding to Na–Cl‐type waters. This facies reflects the dominant influence of halite dissolution and intensive evaporation processes, both typical of arid environments. Additionally, reverse ion exchange promotes sodium enrichment at the expense of calcium and magnesium, thereby increasing sodicity hazards. Such hydrochemical conditions are characteristic of aquifers undergoing prolonged water–rock interaction and may also be influenced by anthropogenic sources, such as cement‐related contamination. Furthermore, the contribution of sabkha‐derived brines may enhance the Na–Cl signature, as these evaporative salt flats represent important natural sources of highly saline groundwater in arid regions. In addition, the dissolution of evaporite minerals within old marine deposits, particularly halite‐bearing formations, can further intensify groundwater salinization. Vertical mixing with deeper saline groundwater systems may also play a role in maintaining the observed Na–Cl dominance in the aquifer.

Approximately 16.67% of the samples fall within Field 5, representing mixed facies with no dominant cation or anion. These waters are generally associated with transitional hydrochemical conditions that arise from mixing between different water types or simple dissolution processes. Anthropogenic impacts, particularly from agricultural return flow, may further contribute to the chemical variability observed in these facies. A smaller proportion of samples (≈3.33%) plot in Field 2, corresponding to Ca–HCO₃‐type waters. This facies is indicative of localized recharge areas within the Quaternary aquifer, where carbonate weathering plays a significant role. The presence of magnesium (Mg²⁺) in this group suggests possible contributions from dolomite dissolution, while elevated sodium (Na⁺) levels point to cation exchange reactions (Asmoay 2024). Similar hydrochemical patterns, including high Na, SO₄, and Cl concentrations due to gypsum and halite dissolution, were reported in the Gafsa mining basin (Tunisia), highlighting the combined effects of geogenic and anthropogenic processes on groundwater quality (Nasri et al. 2024). Overall, the distribution of hydrochemical facies demonstrates that groundwater in Oued Souf is predominantly controlled by halite dissolution, evaporation, and ion exchange, with carbonate weathering contributing only to a limited extent. These processes explain the elevated electrical conductivity values observed and account for the widespread unsuitability of groundwater quality to determine its appropriateness for both domestic consumption and agricultural irrigation in the region.

6. Conclusion

The comprehensive hydrochemical assessment conducted in this study clearly demonstrates that the shallow aquifer of Oued Souf is undergoing progressive geochemical degradation driven by both natural and anthropogenic mechanisms. The dominance of halite‐ and gypsum‐bearing lithologies, combined with intense evaporation under hyper‐arid climatic conditions, promotes the continuous concentration of dissolved ions in groundwater. Reverse ion‐exchange further enhances sodium enrichment at the expense of calcium and magnesium, reinforcing the prevalence of Na–Cl facies (≈80% of samples). These intrinsic processes are additionally amplified by external pressures such as agricultural return flow, fertilizer residues, and wastewater infiltration in urbanized zones, thereby accelerating ionic loading and amplifying salinity–sodicity signatures across the aquifer.

The resulting hydrochemical patterns reveal extremely high salinity (EC up to 18,680 μS/cm), elevated TDS (3652–13,835 mg/L), excessive total hardness, and widespread brackish‐to‐saline conditions, with spatial GIS mapping showing a deterioration gradient from south toward the northern and eastern sectors. Statistical analysis reinforces this behavior: PCA indicates that salinity and sodium hazard account for the majority of the variance (> 86%). At the same time, correlation matrices highlight strong interdependence between salinity indices (EC and PS) and sodicity indicators (SAR, Na%, and KR). This confirms that groundwater evolution is not random but is systematically governed by salinity–sodicity co‐dominance rather than by carbonate equilibrium dynamics. From a water‐use perspective, classification schemes provide a consistent picture: WQI values well exceed potability thresholds, and Wilcox/USSL diagrams confirm that excessive salinity and sodium hazard impose severe limitations on agricultural use, regardless of local variations in SAR or MH classes. Therefore, based on integrated chemical, statistical, spatial, and classification evidence, it can be conclusively stated that groundwater in the Quaternary aquifer of Oued Souf in its current state is not suitable for drinking nor for irrigation without prior treatment or management intervention.

7. Recommendations

In light of the alarming deterioration of groundwater quality observed in Oued Souf, immediate and long‐term interventions are essential to prevent further degradation and maintain agricultural viability in this arid context. A crucial priority is the implementation of stricter groundwater abstraction policies, particularly in zones where GIS mapping shows accelerated salinity build‐up. Pumping from shallow wells should be quantitatively regulated, and the development of deeper alternative sources should be considered only under hydrogeologically controlled conditions to avoid downward migration of saline water and vertical mixing.

On the agricultural side, irrigation practices must be re‐engineered to reduce salt deposition in the soil around plant roots. This includes shifting toward improved irrigation systems (e.g., drip and localized irrigation) that minimize evaporation losses, as well as applying periodic leaching of soils during wet seasons to prevent salt crystallization and maintain hydraulic conductivity. The integration of soil amendments, especially gypsum and biochar, is strongly recommended: gypsum can replenish Ca²⁺ and counter sodium dispersion effects, whereas biochar can increase soil cation exchange capacity, improve microbial activity, and attenuate Na⁺ toxicity. These solutions should be paired with crop selection strategies that prioritize salt‐tolerant and moderately salt‐tolerant species (e.g., date palm, barley, sorghum, and certain halophytes) to sustain agricultural revenues under constrained water quality scenarios.

Based on the water quality classification, specific agricultural and irrigation management strategies can be recommended. In the southern part of the study area, where water quality is generally classified as good to excellent, high‐value crops such as date palm, olive, and quinoa may be cultivated using conventional drip irrigation systems. In the central part, where water quality is moderate, salt‐tolerant crops such as barley, sorghum, and forage species are more suitable, together with improved drip irrigation and periodic soil leaching to minimize salt accumulation. In the northern, northeastern, and eastern parts of the study area, where water quality is relatively poor, agricultural activities should be restricted to highly salt‐tolerant crops, including halophytic plants, while adopting highly efficient drip irrigation systems and strict soil salinity management practices. Surface irrigation is generally not recommended because of high evaporation rates and the associated risk of salt accumulation. Although drip irrigation systems require a higher initial investment, they provide substantial long‐term benefits by improving water‐use efficiency, reducing soil degradation, and enhancing agricultural sustainability in arid environments.

At the governance scale, improved regulation of fertilizer application and the upgrading of wastewater treatment infrastructure are essential to reduce anthropogenic ionic loading. In the medium term, the feasibility of pretreatment options such as desalination, partial blending with higher‐quality water, or low‐energy membrane systems should be evaluated, especially for drinking purposes and in densely populated areas. Regional monitoring networks should also be strengthened by integrating hydrochemical, remote sensing, and piezometric datasets into a unified early‐warning decision‐support system capable of detecting shifts in salinity–sodicity dynamics in near real time. Collectively, these measures will not eliminate salinity problems entirely, but they can significantly slow the rate of environmental degradation, preserve soil functionality, and sustain agricultural livelihoods, thereby aligning water management in the Oued Souf region with the long‐term sustainability requirements of hyper‐arid aquifer systems.

Author Contributions

Karima Boukhallat: writing – original draft, writing – review and editing, data curation, formal analysis, resources. Samia Halimi: writing – review and editing, investigation, validation, supervision. Khaldia Si Tayeb: conceptualization, data curation. Maurizio Barbieri: investigation, validation, writing – review and editing. Djemoui Mamour: data curation. Fatma Slimani: conceptualization. Miyada Ouanes: methodology. Tarek Daifallah: conceptualization. Horiya Bouali: data curation.

Funding

The authors declare no specific funding received for this study.

Ethics Statement

The authors have nothing to report.

Consent

The authors hereby grant all rights of publication of the manuscript to the publisher.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.