The study area, known as the Greater Niaye of Dakar, covers a surface area of approximately 1.298 hectares [11]. It straddles the departments of Dakar, Pikine, and Guediawaye, encompassing ten (10) municipalities: Pikine Ouest, Pikine Nord, Pikine Est, Sam Notaire, Medina Gounass, Dalifort, Golf Sud, Patte d’Oie, Grand-Yoff, and Hann Bel-Air. The study area includes three main sites, the Grande Niaye of Pikine (Technopole site), the Niaye of Patte d’Oie, and the Niaye of Hann Maristes. Groundwater samples were collected from shallow wells located in the Niaye of Patte d’Oie. The Niaye of Patte d’Oie, an agricultural zone located in the Dakar Department, covers an area of approximately 100 hectares [12], representing about one-third of the total surface area of the municipality. Due to its proximity to the city center, it has been designated as a non-building zone (zone non aedificandi), primarily reserved for agricultural purposes or landscape development [13]. Groundwater samples were collected within the Patte d’Oie study area from two production boreholes and one well, all situated in the Niaye of Patte d’Oie. The chain of custody was strictly maintained throughout the sampling and analytical process, including sample coding, double data entry, quality control, and secure digital archiving. Analytical results were expressed in mg/L following standard procedures and compared to FAO guideline thresholds to assess the water stress level of the site.

The parameters pH, electrical conductivity (EC), and total dissolved solids (TDS) were measured in situ using a portable multiparameter meter (Thermo Scientific model). Water samples were collected in 1.5 L plastic bottles and transported to the Inorganic and Analytical Chemistry Laboratory (LACHIMIA) for analysis. The analyzed chemical parameters included: Na⁺, K⁺, Ca²⁺, Mg²⁺, NH 4 + , HCO 3 − , Cl − , SO 4 2 − , NO 3 − , PO 4 3 − , and F − .

Sulfate ( SO 4 2 − ), nitrate ( NO 3 − ), phosphate ( PO 4 3 − ), and fluoride ( F − ) ions were determined using a HACH DR39000 spectrophotometer.Calcium (Ca²⁺) and magnesium (Mg²⁺) concentrations were measured by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES).Sodium (Na⁺), potassium (K⁺), and ammonium ( NH 4 + ) were analyzed using a LAQUA ion meter.Bicarbonate ( HCO 3 − ) and chloride ( Cl − ) ions were determined by titrimetric methods [14].

2.2.1. Ionic Balance

The ionic balance (IB) was calculated using the following equation, with a tolerance limit of ±5%, to verify the analytical consistency of ionic concentrations expressed in meq/L [15][16]:

Analytical procedures were validated through a rigorous quality control process, including regular instrument calibration and verification of measurement accuracy for each analyzed sample.

2.2.2. Data Processing

The hydrochemical classification of water samples was performed using the Piper, Wilcox, and Riverside diagrams, generated with the DIAGAMMES 6.5 software. The water quality indices used to assess the suitability of groundwater for irrigation included the Sodium Adsorption Ratio (SAR), Soluble Sodium Percentage (SSP), Kelly’s Index (KI), Potential Salinity (PS), and Residual Sodium Carbonate (RSC).

2.2.3. Irrigation Water Quality Indices (IWQI)

The calculation of Irrigation Water Quality Indices (IWQI) was performed using the equations presented in Table 1. Since agricultural practices, soil types, and water quality all influence the most appropriate irrigation techniques [17][18], several indices were applied in this study to evaluate the suitability of water for agricultural use, particularly the irrigation-specific indices: SAR, KI, RSC, PS, and SSP. These parameters help to highlight the risk of soil salinization and the potential adverse effects of irrigation on soil and plant health. The data derived from the IWQI calculations were statistically analyzed to determine the overall suitability of the water for agricultural purposes.

Table 1.Equations used for the calculation of irrigation water quality indices.

Note: All indices were calculated in meq/L.

The classification of groundwater was based on physico-chemical parameters relevant for assessing their suitability for irrigation in the Niaye of Patte d’Oie. These parameters include pH, electrical conductivity (EC), total dissolved solids (TDS), as well as major cations (K⁺, Na⁺, Mg²⁺, Ca²⁺, and NH 4 + ) and anions ( Cl − , SO 4 2 − , HCO 3 − , NO 3 − , PO 4 3 − , and F − ). These elements directly influence soil quality and crop productivity. Table 2 presents the measured physico-chemical parameters from the three groundwater samples collected.

Table 2.Physico-chemical parameters of groundwater.

To assess the quality of groundwater, the measured parameter values were compared with the guideline values of the Food and Agriculture Organization of the United Nations (FAO) [26] for irrigation water (Table 2). The analysis results show that the pH values of the groundwater ranged from 6.10 to 8.46, falling within the intervals defined by the FAO. Electrical conductivity (EC) values varied between 1660 and 2340 µS/cm, indicating the presence of several mineralization processes. These results are consistent with the findings of [27], which report slightly mineralized groundwater. The maximum total dissolved solids (TDS) content reached 472.06 mg/L, which remains within FAO regulatory limits. The concentrations of calcium (Ca²⁺) and magnesium (Mg²⁺) in all samples comply with FAO irrigation standards. However, potassium (K⁺) concentrations exceeded the FAO guideline value of 2 mg/L. Pollution indicator parameters, such as nitrogen and phosphate compounds ( NO 3 − , NH 4 + , and PO 4 3 − ), showed values exceeding FAO guideline limits. These chemical parameters originate from the weathering of clay formations or from the dissolution of chemical fertilizers (NPK) applied by farmers. Nitrates present in the water can come from various natural and anthropogenic sources. In urban areas, such as the study zone, high nitrate levels are often linked to domestic and urban wastewater, local contamination of groundwater, latrine influence, and animal waste. Chlorides ( Cl − ) and sulfates ( SO 4 2 − ) were the dominant anions in groundwater, with average concentrations of 312.40 mg/L and 228 mg/L, respectively, generally compatible with irrigation standards. When present in irrigation water, these elements contribute to increasing the concentration of soluble salts. Excessive chloride concentrations can cause tip burn on the leaves of certain crops and may even lead to plant death. Concentrations ranging from 250 to 400 ppm, as observed in our study, are considered undesirable for the irrigation of salt-sensitive plants. Fortunately, chloride salts are highly soluble and can therefore be leached from well-drained soils. Bicarbonates ( HCO 3 − ) showed concentrations acceptable for irrigation, with a maximum value of 603.9 mg/L [26].

The correlation matrix between the different analyzed parameters (16 elements) shows that some variables (considered in pairs) are strongly correlated, with highly significant coefficients exceeding 0.95. This is particularly the case for the following element pairs: pH- HCO 3 − (r = 0.91); pH- NH 4 + (r = 0.99); EC-Na⁺ (r = 0.95); EC-Ca²⁺ (r = 0.98); EC- Cl − (r = 0.98); Na⁺-Ca²⁺ (r = 0.99); Na⁺- Cl − (r = 0.92); Mg²⁺- SO 4 2 − (r = 0.92); and PO 4 3 − - Cl − (r = 0.99). These highly significant correlations may provide insight into the possible origin of these elements (natural or anthropogenic), particularly those contributing to the mineralization of groundwater ( Cl − , HCO 3 − , Ca²⁺, Mg²⁺, Na⁺, SO 4 2 − , and K⁺). In the factorial plane (axes 1-2), axis F1 contains the largest amount of information, accounting for 70.5% of the total variance (Figure 1). This axis is defined by the chemical elements responsible for the mineralization of the water. The grouping of these variables along axis F1 indicates that this factor explains the predominant mechanisms governing the mineralization processes in the aquifer. The correlation observed among the variables defining factor F1 reflects a common origin for most of these ions. It is worth noting that pH, NH 4 + , Ca²⁺, Na⁺, K⁺, F − , PO 4 3 − , and HCO 3 − contribute to the mineralization pole and are mainly opposed to NO 3 − . This suggests that axis 1 highlights the key roles played in water chemistry by both the rock matrix (through element dissolution) and anthropogenic activities, particularly agriculture. Axis 2, which explains 29.5% of the total variance, is characterized by a group of water samples dominated by Mg²⁺, SO 4 2 − , Cl − , and NO 3 − ions. This opposition reveals the influence of anthropogenic contamination.

Figure 1. Principal component analysis (PCA) of the measured physicochemical parameters.

The results obtained from this study showed a significant variation in the general hydrochemistry among the different samples. A summary of the general hydrochemical characteristics of the irrigation waters is presented in Table 3.

Table 3.Water quality indices and agricultural classification [28].

In irrigation water, the SAR parameter reflects the soil matrix’s ability to release Ca²⁺ and Mg²⁺ ions and adsorb Na⁺ ions at exchange sites, which can disperse soil particles and reduce its infiltration capacity [29][30]. Highly saline water can sometimes improve soil structure by accelerating infiltration; however, it imposes increased water stress on plants, which must expend more energy to extract water from the soil. SAR is a key indicator of water quality for agricultural use [17]. A high SAR, indicating a high sodium content, corresponds to poor water quality for irrigation [31][32]. In this study, the maximum SAR value for all samples was below 10, indicating excellent water quality for irrigation.

The Riverside diagram (Figure 2) is used to assess the risk of soil salinization. It considers electrical conductivity and the sodium adsorption ratio (SAR), also referred to as the “alkalizing power.”

Figure 2. Riverside diagram of the analyzed waters.

According to the classification derived from the Riverside diagram [33]:

Samples 1 and 3 fall into the C3-S1 class, meaning low SAR and moderate to high salinity (Table 4).Sample 2 falls into the C4-S1 class, corresponding to very high salinity with a low SAR.

Table 4. Classes from the riverside diagram [33].

These results indicate that the irrigation waters are of medium to poor quality and should be used with caution. Proper drainage, along with leaching doses and/or gypsum application [34], is recommended to prevent soil sodification. In conclusion, all three samples are characterized by a high risk of salinization but low alkalinity, suggesting that these waters can be used for irrigation without risk of soil alkalinization.

The Kelly’s Index (KI) is used to assess the suitability of groundwater for agricultural irrigation. A Kelly’s Index greater than 1 indicates a high sodium concentration in the irrigation water [35], making it unsuitable for irrigation. Conversely, a value below 1 reflects a relative deficiency of sodium ions, and the water is considered suitable for irrigation [36]. In the study area, Kelly’s Index values ranged from 0.96, 1.13, to 1.27, as shown in Table 3. These results indicate that the water contains a moderately high sodium content, which can reduce water infiltration into the soil [37].

The Wilcox diagram is a graphical tool used in hydrochemistry to classify water quality, primarily for irrigation purposes. It classifies water based on electrical conductivity (EC) on the horizontal axis and sodium percentage on the vertical axis.

Figure 3. Wilcox diagram of the waters.

In our study, the three samples plotted on the Wilcox diagram (Figure 3) are divided into two groups:

Sample 2 is highly loaded with sodium, corresponding to a very high EC (2340 µS/cm), placing it in the class of poor-quality water unsuitable for irrigation.Samples 1 and 3 have EC values ranging from 1660 to 1797 µS/cm, which fall within the acceptable range for irrigation water (can be used if moderate leaching is applied).

The concentration of chloride ions and half the concentration of sulfates are important parameters for assessing the suitability of groundwater for irrigation through the potential salinity index (PS). PS values are generally classified as:

Unsuitable when PS > 3Suitable when PS < 3 [24]

In this study, PS values ranged from 8.94 to 13.18, with a mean of 10.95 (Table 3), indicating that the waters fall into the harmful to unsatisfactory class.

An excess of carbonate and bicarbonate relative to calcium and magnesium ions is commonly used to assess irrigation water quality. The RSC was calculated to predict the potential precipitation of Ca²⁺ and Mg²⁺ on soil particle surfaces, which removes them from the soil solution. Precipitation of Ca²⁺ and Mg²⁺ as carbonate minerals can increase Na⁺ concentrations and consequently SAR values [23]. High RSC can deteriorate soil physical properties, causing organic matter dissociation and the formation of black patches on the soil surface when dry [38][39]. Based on RSC values, groundwater is classified into three categories [40]:

RSC < 1.25: Acceptable irrigation waterRSC 1.25 - 2.5: TolerableRSC > 2.5: Unacceptable

In this study, all three water samples had RSC values below 1.25 (Table 3), indicating that the water is acceptable and of good quality for irrigation.

The Piper diagram highlights the hydrochemical facies of the three water samples.

Samples 2 and 3 mainly show a bicarbonate-chloride sodium-potassium facies.Sample 1 is characterized by a sulfate-sodium-potassium facies.

Overall, the samples show a predominance of chloride, sulfate, calcium, and magnesium ions in Sample 1. Sample 2 exhibits a chloride sodium-potassium facies with a tendency toward sulfate-sodium, while Sample 3 is characterized by a bicarbonate sodium-potassium facies (Figure 4).

The majority of the analyzed samples show that salinity (represented by SO 4 2 − + Cl − ) is generally higher than alkalinity ( HCO 3 − + CO 3 2 − ), and that alkali ions (Na⁺ + K⁺) predominate over alkaline-earth ions (Ca²⁺ + Mg²⁺). These ionic relationships are the main factors controlling the hydrochemistry of groundwater in the Niaye de Patte d’Oie region.

Figure 4.Piper diagram of the waters.