1. Introduction

2. Materials & Methods

2.1. Study area

The study area located in middle Egypt within longitude of 30°40'00"E - 30°47'00"E and latitudes of 28°45'00"N - 29°05'00"N and covers an area about 300 km², Figure (1). The location is dominated by sub orders calcids and gypsids (Embabi, 2004)  and slightly slope level ranged from 0.5 % to 2.0 %. In recent decade, the study area witnessed remarkable agricultural development, especially in the south corner, cultivated by strategic crops such as wheat, tomatoes, and onions.

Figure 1. Location of the study area, overlaid with Sentinel-2 imagery (false colour composition: NIR, Red, Green).

Figure 1. Location of the study area, overlaid with Sentinel-2 imagery (false colour composition: NIR, Red, Green).

The region climate has a Mediterranean pattern (Beck et al., 2018). The annual rainfall rates are very scarce, with an average of 2 mm/day. The groundwater is the main source of water supplies needed for various uses as agricultural, industrial, and drinking purposes. The drilling of more wells with high water use negatively withdraw the groundwater level. Recently, the high consumption of groundwater quantities led to an imbalance of the aquifer level, and increased the salinity of the water extracted from arid areas (Elsharkawy et al., 2022a). The geological structure in the study site indicate that the unrestricted groundwater-bearing layers follow the Quaternary Aquifer, which is composed of intrusions of sand, gravel, sandstone, and limestone (Said, 1962).

2.3. General description of the IWQI model

The IWQI model (Meireles et al., 2010) was designed to determine the quality of irrigation water by multivariate analysis technique. In order to calculate the relative weights of the various factors in this method, the values of those characteristics derived from the irrigation water quality data as suggested by (Ayers and Westcot, 1999). These factors include EC (dS/m), dissolved sodium, chlorides and dissolved bicarbonates, expressed in meq/l. In addition the SAR proposed by (Suarez, 1981), which was calculated according to (Lesch and Suarez, 2009) as shown in Eq (2).

$${SAR}^O=\frac{{Na}^{+}}{\sqrt{\frac{{Ca}_{eq}^{+2}+{Mg}^{+2}}{2}}}$$

Eq. 2

Where Na⁺ (meq/l) represents the concentration of dissolved sodium in irrigation water, Ca⁺² (meq/l) is the concentration of modified calcium dissolved in irrigation water, and Mg⁺² (meq/l) is the concentration of magnesium dissolved in irrigation water. The contribution of each parameter is determined separately when calculating the irrigation water quality index, so that this contribution includes both the estimated irrigation water quality values (q_i) and the relative weight (w_i). Equation (3) is also used to calculate the (q_i) values, as follows: the next:

$$q_i=q_{max}-\left(\frac{q_{iamp}*\left(x_{ij-}{x}_{inf}\right)}{x_{amp}}\right)$$

Eq. 3

Where q_i represents the estimated water quality values for each single parameter (Table 1); q_max represents the maximum value for each class. X_i is the measured value of each parameter, X_inf is the minimum value of the measured factor, q_iamp is the capacity of the class, and X_amp is the corresponding capacity value of the class that the parameter estimate.

The w_i values reflect the standard weight of the properties which related to its importance in explaining the total change in water quality, which is shown in Table 2.

The IWQI values (Meireles et al., 2010) f for irrigation purposes are determined from Equation (4) as follows:

$$\mathrm{I}\mathrm{W}\mathrm{Q}\mathrm{I}={\sum }_{i=1}^n{\mathrm{q}}_i{\mathrm{w}}_i$$

Eq. 4

According to the above equation, the IWQI is a unitless index, and its value ranges from 0 to 100. The different divisions of irrigation water shown in Table (3). It was classified based on the limitations of irrigation water use (Holanda and Amorim, 1997) such as salinity problems, the decrease in soil water infiltration rates, and the toxic effects on the plant.

Table 3. Weight importance (Wi) for different characteristics.

Table 3. Weight importance (Wi) for different characteristics.

IQWI value	Limitations	Recommendations
100 to 85	--	Suitable for all soil types and crops
85 to 70	Low	Not recommended in heavy soils and salinity sensitive crops
70 to 50	Normal	Recommended in moderate soils with continues leaching
50 to 40	High	Recommended in sandy soils with no compacted layers and crops that are not sensitive to salinity
< 40	Very high	Not recommended in for regular irrigation conditions

2.4. Spatial distribution maps of chemical properties:

The spatial distribution maps of groundwater characteristics were obtained using the Inverse Distance Weighted (IDW) technique in the geographic information systems (GIS) environment by ArcGIS 10.8 software, developed by the Environmental Systems Research Institute (ESRI) (ArcGIS, 2012). The IDW method is a quick deterministic interpolator that produce better estimated surfaces when the number of points is limited and their distribution is regular, as it was described by (Azpurua and Dos Ramos, 2010).

where: z(x₀) is the predicted value of the property under study at location x₀, n is the total number of available data (50 points in this study), and x_i is the value of the property at location I; h represents the distance between the point at the predicted element and β denotes the exponent of the distance. In this study a value of the exponent = 2 was chosen as recommended by (Babak and Deutsch, 2009). They indicated that this value is the most widely used when applying the IDW method in spatial estimations.

3. Results & Discussion

3.1. The chemical properties of groundwater

Figure (2) shows the numbers of wells, their locations, and the spatial distribution of the analysis of the chemical properties of groundwater. It shows that the pattern of spatial distribution of dissolved ions is very similar to the pattern of spatial distribution of the degree of electrical conductivity, where the group of wells from 25 to 31 constitutes a focus in which the concentrations of dissolved ions rise. Figure (2 b) shows that there is a relative increase in pH values at the northern border of the study area compared to the rest of the regions. Moreover, the spatial distribution demonstrated in Figure (2, f &h) also showed that the northern region has low concentrations of dissolved chloride and bicarbonate. Figure (2, a) shows that the salinity is concentrated in the south of the study area, and its effect extends towards the northwest. It is also clear that the pattern of spatial distribution of each of the Potassium and sulfates is very similar (Figure 2 g &i).

Figure 2. The spatial distribution of some chemical properties of the well water of the study area.

Figure 2. The spatial distribution of some chemical properties of the well water of the study area.

Table (4) shows some statistical characteristics of the chemical properties of groundwater in the study area. The results showed that the values of the pH ranged between 7.7 and 8.3, with a relatively low coefficient of variation (0.04%), and it falls within the suitable range for irrigation water (6.5 to 8.4) recommended by (Ayers and Westcot, 1999). Also, the results showed that the average depth of the still water level below ground level (WSL) in the study area was 83 meters, and that the lowest depth was recorded at 45 meters in well (10) located in the north middle of the study area. while recording the maximum depth 117 meters at well (49) located in the southwest of the study area. These results agree with what was concluded by (Ramesh and Srinithi, 2014) that the pH values decrease with the increase in the concentration of bicarbonate in the groundwater.

Table 4. Descriptive Statistics of some groundwater chemical properties.

Table 4. Descriptive Statistics of some groundwater chemical properties.

Parameters	Ca++	Mg++	Na+	K+	HCO3-	SO4--	Cl-	SARo	pH	EC	TDS	WSL
	meq/l									dS/m	ppm	m
AVG	236.4	102.0	77.5	106.2	309.6	148.1	113.0	5.9	7.9	3.24	1328.5	82.9
Min	155.4	2.2	25.8	5.6	197.8	58.0	11.7	2.0	7.7	1.63	668.7	45
Max	355.5	256.9	156.7	197.4	426.9	238.2	206.4	9.8	8.3	5.16	2112.6	117
S.E.	8.5	9.8	4.6	8.1	8.1	8.7	8.1	0.3	0.0	0.15	63.0	13.1
SD	60.0	69.2	32.3	57.2	57.1	61.8	57.4	2.2	0.2	1.09	445.4	1.8
CV	17.6	19.7	9.2	16.3	16.2	17.1	16.3	0.6	0.04	0.31	126.6	3.7

Where: Avg is the Mean value; Min is the Minimum value; Max is the Maximum value; SE is the Standard Error value; SD is the Standard Deviation value; CV is coefficient of variation; WSL is the still water level below ground level, EC is the Electrical Conductivity, Na⁺ is the concentration of dissolved Sodium, Cl^- is the concentration of dissolved Chloride, HCO3^- is the concentration of dissolved Bicarbonate and SAR is the Sodium Absorbed Ratio.

The coefficient of difference values in the concentration of the dissolved main ions show the clear differences between the groundwater wells in their content of those ions, as shown in Table (4). The results showed a significant variation in the degree of electrical conductivity (EC) in the collected samples. It ranged between 1.63 to 5.16 dS/m, with a standard deviation about 1.09 dS/m and coefficient of variation 0.31%. The high values of EC degree in the wells were those located in the south of the study area, wells (38 to 49), as shown in Figure (2, a). The concentrations of Magnesium and Calcium were the most different by 19.7% and 17.6%, respectively. While the Sodium ions were the least different (9.2%). Moreover, Bicarbonate ions and Sulfate represent the largest percentage of the total dissolved salts components, at 27% and 16%, respectively. The contribution of the rest of the ions in the components of the total dissolved salts was 14, 11, 2, 7, and 10% for Calcium, Magnesium, Potassium, Sodium, and Chloride, respectively.

Table (4) shows that the SAR^o values ranged from 2 to 9.8, with an average value of 5.9, and a coefficient of difference of 0.6%. According to (Bouaroudj et al., 2019), most of the groundwater of north Africa have less than 3 values of the modified sodium absorption rate, and therefore it does not document when using the emergence of problems related to the sodium absorption rate. While the values of the modified sodium absorption rate ranged in the water is between 1 and 7. The wells at middle area (11, 12 and 18 to 27) have water characterized with average SAR^o 7, which expected to cause permeability problems in the soil when it used for irrigation.

Regarding to permeability, Figure (2, e) shows the spatial distribution of the modified SAR^o values, where the SAR^o values are higher in the middle of the study area compared to the north and south borders. This distribution pattern is attributed to the high values of sodium in the water of the wells of that region, which may also indicate the existence of a direct hydraulic connection between the wells of that region. The expected harmful effect when using high SAR^o water is represented in the adsorption of sodium on the colloidal surfaces of the soil and its replacement with magnesium, and the rest of the cations, causing a decrease in the rate of soil permeability (Elsayed et al., 2020) and hardening of the soil at the surface, and damage to the germination processes (Bazza et al., 2018).

3.3. The relative quality dominance of dissolved ions in well water:

The average relative abundance of dissolved ions in the well water of the study area was 65.8, 20.4, 13.8 for chlorides, sulfates, and bicarbonate. As shown in Figure (3), the specific dominance of the anions was bicarbonate, according to their relative distribution on the triangle of the anions, where their ratios ranged from 40 to 58, for wells (25 - 34).

Figure 3. Piper diagram to determine the specific dominance of cations and anions.

Figure 3. Piper diagram to determine the specific dominance of cations and anions.

The specific predominance of sulphate was high in wells (28, 34, 46), with a predominance of 33, 32, and 33, respectively. Although the specific predominance of chloride ion for well 46 was the highest, the water of the rest of the wells was characterized by relatively low levels of chloride with average 113 meq/l. As for the dissolved cations, the mean relative abundances, expressed in meq/l, were 35.3, 22.4, 11.2, 0.9 for sodium, magnesium, calcium, and potassium, respectively. The relative distribution of these ions on the triangle of cations shows that the predominance of sodium and potassium ions exceeded in wells (10, 11, 34, 35, 39, 46). Regarding potassium ions, generally it has low percentage, as shown in Table (4).

3.4. Irrigation water quality index

The values of electrical conductivity, sodium, chloride, bicarbonate, and sodium adsorption ratio were used to estimate the irrigation water quality index, as suggested by (Meireles et al., 2010). Figure (4) show the spatial distribution of the contribution of electrical conductivity, sodium, chloride, bicarbonate, and sodium adsorption percentage to the irrigation water quality index values, respectively. As indicated by (Meireles et al., 2010), the higher the contribution values, the better the irrigation water quality. It can be seen from Figure (4) the great similarity in the spatial distribution pattern of the contribution of electrical conductivity, bicarbonate and chloride. This similarity can be attributed to the fact that the degree of electrical conductivity is related to the total dissolved salts, of which bicarbonate and chloride constitute most of its components, especially in arid areas far from freshwater sources (Li et al., 2018). The values of relative importance for each of the degree of electrical conductivity, bicarbonate, and sodium are close, as shown in Table (2), which may also explain some similarities in the spatial distribution pattern of these ions. Figure (4, b) shows a slightly increase in the values of the contribution of bicarbonate in the southeast of the study area, and its increase in the direction of the middle, and then its decrease again in the north borders. The dissolution processes that take place in aquifers containing limestone have an impact on the rise in the dissolved calcium and magnesium values, especially in the south of the study area, where in turn the values of the modified adsorbent sodium contribution decrease (Appelo, 1994) compared to the rest of the study area, as shown in Figure (4, e).

Figure 4. The spatial distribution of EC, HCO₃^-, Na⁺, Cl^- and SAR contribution to IWQI values.

Figure 4. The spatial distribution of EC, HCO₃^-, Na⁺, Cl^- and SAR contribution to IWQI values.

The irrigation water quality index was calculated using equation (3), taking into account the various factors, and their relative weight. Depending on usage restrictions shown in Table (3), the water of 14 wells with high use restrictions namely (wells no 25, 27, 28, 29, 32 to 38, 40, 48 and 50) as shown in Figure (5). These wells have water quality index values ranging from 38 to 51, which can be used for irrigating highly salt tolerant crops cultivated in highly permeable soils, that do not contain compacted layers and the irrigation process must be carried out with a high frequency. Furthermore, the water of seven wells was classified as having moderate usage restrictions namely (wells no 2, 10, 12, 13, 18, 26 and 30). Their IWQI values ranged between 50 and 70. This type of water is suitable for irrigating crops that are medium tolerant to salinity and grown in highly permeable soils, with medium leaching of salts to prevent soil degradation.

Figure 5. The spatial distribution of the irrigation water quality index values.

Figure 5. The spatial distribution of the irrigation water quality index values.

The results also showed that there were three wells (1, 3 and 5) had low use restriction characteristics for irrigation purposes, as the value of the water quality index ranged between 70 and 85. This type of water is suitable for irrigating salinity-sensitive crops. As shown in Figure (5), the irrigation water quality index decreases at the south of the study area and increase forward the north borders. Moreover, the results obtained from the spatial distribution of the irrigation water quality index show that 62.5% of the study area is classified as having water with moderate use restrictions for irrigation purposes, and 27% of it is classified as having a high degree of restriction of irrigation use, 10% of the area has very high limitations, while 0.5% of the area has low-restriction water for irrigation purposes.

4. Conclusions

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