INTRODUCTION

There is no doubt that water is the basis of life, without it no living creature can exist. Water is very necessary to irrigate crops and provide food for people. Conservation of the water resource is very important to the continuation of living on the planet. Therefore, world governments are striving to focus on the good management of water resources. Moreover, reducing the degradation of water resources is a concern of all human beings (Adimalla et al., 2020). Recently, the problems of deteriorating water resources, which are pollution, salinization, depletion, and others, have increased. With the increasing climatic changes that negatively affect water resources, it has become necessary to move quickly towards finding innovative solutions to address the matter. Egypt suffers from a severe water problem, as the population increases and its needs in water consumption, and on the other hand, Egypt's share of the Nile water has decreased due to the construction of the Grand Ethiopian Renaissance Dam. However, the Egyptian government is focusing on finding quick solutions that are innovative and economical at the same time to save water consumption. More than 80% of Egypt's share of water falls under the category of agricultural consumption, and 20% is consumed in industry and other activities (Amer et al., 2017). There are two main sources of water in Egypt, the Nile River, and groundwater. The Egyptian government has resorted to establishing several agricultural reclamation projects in the new desert lands, east, and west, to meet the population's food needs. Therefore, water is provided for agricultural activities in those new areas from groundwater that is less in quantity and quality than from the waters of the Nile River (Ibrahim and Elhaddad 2021). Therefore, during this period, the focus should be on evaluating the quality and suitability of water, whether from the Nile River or groundwater for irrigating different crops (Bahadir et al., 2016). One of the methods used to assess the quality and suitability of water is chemical laboratory methods. Therefore, many water analyses are performed and the results are included in many water quality and suitability assessment models. These models used are intended to classify water samples according to their quality and suitability for irrigating crops. Many studies were carried out to assess water quality and suitability using water chemical parameters (Adimalla and Qian, 2019; Adimalla and Taloor, 2020; Aravinthasamy et al., 2020; Balamurugan et al., 2020; Haque et al., 2020; Karuppannan and Serre Kawo, 2020; Khan et al., 2020; Panneerselvam et al., 2020; Yetis et al., 2021). The suitability classification data can then be used to produce spatial maps using the Geographic Information System (GIS) that can be utilized as a guide for decision-makers to reach the best use of water and to better manage those resources. Based on what was previously mentioned, this study aims to assess the quality and suitability of water sources in Sohag area and also to produce spatial distribution maps of water suitability.

MATERIALS AND METHODS

Study area

The study area is a part of Sohag Governorate that extend from Tahta city in the North to El-Baliana city in the South which mainly includes Nile Valley’s old cultivated lands and some newly reclaimed areas. The study area lies between 26°10'21.28", 26°50'30.95"N latitudes and 31°20'51.45", 32° 9'49.11"E longitudes with elevation ranged between 61 and 73 m.a.s.l. The map of the study area was demonstrated in figure (1). The study area belongs to the arid region of North Africa which is generally characterized by hot summer and mild winter with low rainfall. Air temperature ranges between36.5°C (summer) and 15.5°C (winter), relative humidity ranges between 51% and 61% (winter), 33%, and 41% (spring), and 35% and 42% (summer). Old agricultural soils are mainly irrigated by the Nile River and some parts of the newly reclaimed soils are irrigated by the groundwater.

Figure (1) The study area and water sampling location map.

RESULTS

The physical and hydraulic properties of Soil samples: Analysis of the soil particle content presented in (Fig. 2) revealed that the sand content ranged between 12 and 95.38 %, with a mean of 51.103%, and the silt content ranged between 1.61 to 86% and with mean of 43.538%. The clay content ranged between 1 and 19 %, with a mean of 5.359 (Table 2). Samples ranged between sand, sandy loam, and silty loam. In Table2, the descriptive statistics of the studied soils were presented as ϕ and θ_s that range from 0.198 cm³ cm^-3 to 0.566 cm³ cm^-3, with the mean being 0.398 cm³

BC and VG parameters prediction:

Table 3 presents a statistical evaluation of CalcPTF's accuracy in predicting Brooks and Corey's (eq. 1) parameters. There was a strong correlation between the estimated and the measured porosity ϕ for all models, with R values

ranging from 0.863 to 0.896. At the same time, the other parameters (θr, ψb, and λ) did not show any significant correlation. On the other hand, the other statistical indicators (RMSE, NES, and RSR) for CalcPTFs models prediction for equation 1 parameters (ψb, θr, and λ) demonstrated an extremely high degree of uncertainty and deviation. They, therefore, were rated as unsatisfactory or invalid models.  As shown in Table 3, the CalcPTF models NES results for predicting equation 1 parameters were very low (< 0.5).

Water sampling

Water samples were collected from different locations in the study area whereas different water sources (Nile River and groundwater). A total number of 61 water samples were collected and shifted immediately to the water testing laboratory to be analyzed for their elemental content. The geo-coordinates of latitudes and longitudes of each water sampling location were recorded using GPS in the sampling sites. Table (1) showed the geo-coordinates of the water sampling locations.

Table (1) Water sampling locations.

Water analysis

Water samples were analyzed using the standard methods of analysis. Analyzed water parameters are such as water pH, water Electrical Conductivity (EC_w), water-soluble cations (sodium ‘Na⁺’, potassium ‘K⁺’, calcium ‘Ca²⁺’ and magnesium ‘Mg²⁺’), and soluble anions (chloride ‘Cl^-’, bi-carbonates ‘HCO₃^-’ and sulphates ‘SO₄^2-’). Data of EC_w was calculated in ds.m^-1, while soluble cations and anions were calculated in meq.l^-1. The methods used for water analysis are presented in table (2).

Table (2) Methods used for estimation of different chemical parameters of water samples in the study area

Criteria of water quality assessment

Different indices were used to assess the quality as well as the suitability of collected water samples. These indices are electrical conductivity (EC_w), total dissolved salts (TDS), residual sodium carbonates (RSC), sodium adsorption ratio (SAR), sodium percentage (SP), permeability index (PI), Kelly ratio (KR), and magnesium hazard (MH). The obtained data from analyzed samples were compared to the reference data of each index to categorize the suitability of each water sample. The calculation of the different water quality indices was expressed in equations (1 to 8). Tables (3 to 10) showed the suitability and quality assessment criteria using different indices.

Table (3) Electrical Conductivity (EC_w) Richards (1954)

EC_w (ds.m^-1) = EC_w (ms.m^-1) / 1000        equation (1)

Table (4) Total Dissolved Salts (TDS) Richards (1954)

TDS (mg.l^-1) = EC_w (ds.m^-1) x 640          equation (2)

Table (5) Sodium Adsorption Ratio (SAR) Ayers and Westcot (1976)

           equation (3)

Table (6) Residual Sodium Carbonates (RSC) Eaton (1950)

          equation (4)

Table (7) Sodium Percentage (SP) Wilcox (1955)

         equation (5)

Table (8) Permeability index (PI) Doneen (1964)

        equation (6)

Table (9) Kelly Ratio (KR) Kelly (1940)

              equation (7)

Table (10) Magnesium Hazard (MH) Szabolcs and Darab (1964)

         equation (8)

Descriptive statistical analysis

A correlation test was done between all water parameters. Mean, maximum, minimum, and other descriptive statistical parameters were done using Microsoft Excel software.

Mapping of spatial variability

Depending on laboratory data of water parameters and corresponding geographic information, Arc-GIS 10.4 was used for mapping the spatial variability of different water parameters as well as water quality and suitability indices.

RESULTS AND DISCUSSION

Water samples characterization

The data of water samples’ analysis were shown in table (11). The descriptive statistical parameters of the studied water samples were shown in table (12). The obtained results demonstrated that all water samples are alkaline (pH is more than 7.00). Water pH ranged between 7.10 and 8.90 with an average of 8.06. This alkaline pH is not preferable for agricultural purposes as using this water for irrigating the grown crops in the study area because it affects the availability of macro and micronutrients in the soil (Mohiuddin et al., 2022). However, the pH is not significantly affecting water quality because of the buffering capacity of the soil and also the majority of the crops are pH tolerant (Bresler et al. 1982). Regarding EC_w results, minimum and maximum values of total soluble salts were 0.21 ds.m^-1 and 5.62 ds.m^-1, respectively with the mean value of 1.05 ds.m^-1. According to Richards (1954), this water ranged between low saline (EC_w is between 0.25 and 0.75 dS.m^-1) and very high saline water (EC_w is more than 3.00 dS.m^-1). The low saline water is suitable for irrigating all plants except sensitive kinds, while very high saline water is not-suitable for irrigation Richards (1954). Soluble sodium data showed a wide range of water content of this cation whereas the minimum value was 0.91 meq.l^-1 while the maximum value was 42.82 meq.l^-1. The high concentrations of soluble sodium lead to increasing the sodium adsorption by the soil, and affects soil properties (Hailu and Mehari 2021). High sodium and chloride levels in water, affect the plant and the soil physically and chemically which lead to productivity decrease (Jang and Chen 2009). Furthermore, sodium hazard is resulted from the high concentration of water sodium, which can reduce the soil permeability as well as inhibit crop water absorption (Tahmasebi et al., 2018). Soluble potassium varied between 0.08 and 0.36 meq.l^-1 in all studied water samples. These concentrations are non-hazardous, while a problem of low infiltration of irrigation water may cause by the high levels of potassium in the applied water (Rengasamy and Marchuk, 2011). Regarding the soluble calcium, minimum and maximum values were 0.40 and 8.43 meq.l^-1, respectively. The soluble magnesium content in the water samples ranged between 0.10 and 6.11 meq.l^-1 with an average of 1.57 meq.l^-1. The magnesium hazard is caused when high concentration of magnesium in water, which lead to alkalinity of soil and also declining crop yields (Ravikumar et al., 2011). According to soluble bicarbonates were ranged between 0.50 and 7.66 meq.l^-1, soluble chloride varied between 0.38 and 22.92 meq.l^-1, while soluble sulphates ranged between 0.01 and 23.83 meq.l^-1. However, sulfate is not taken in a consideration when calculating water quality indices and currently not assigned in water quality assessment (Zaman et al., 2018).

Table (11) Water samples characterization.

Table (12) Descriptive Statistical Analysis.

The correlation test

Correlation coefficient values of all studied water parameters were shown in table (13). From the obtained data, a high correlation was observed between EC_w and all studied parameters except soluble potassium. The highest correlation was recorded between EC_w and soluble sodium (r=0.94) while the minimum correlation was for soluble potassium (r=-0.06). A very low correlation was observed between water pH and all other water parameters. Similar observation was for soluble potassium which performed poorly against all water parameters. Soluble calcium and magnesium showed reasonable correlation coefficient values for all other parameters. However, soluble chloride was highly correlated with EC_w and soluble sodium, and showed low correlation with other water parameters. Regarding soluble sulphates, it was highly correlated with all parameters except pH and soluble potassium.

Table (13) Correlation between water parameters.

Water quality assessment

Table (15) Descriptive statistical analysis of water quality indices.

Table (16) showed the classes of water quality and suitability based on applied indices. Starting with the data of EC_w, the majority of water samples were under low class whereas electrical conductivity values of those samples were below 0.25 ds.m^-1. This water is suitable for irrigating all crops except for sensitive plants. Some sites in the study area were found to be having mid water quality whereas EC_w values were between 0.25 ds.m^-1 and 0.75 ds.m^-1, which is moderately suitable for irrigation. Few sites such as El-Baliana, Sohag, Akhmim and El-Maragha were having very high EC_w values (more than 3.00 ds.m^-1). This water is not suitable for irrigating any kind of crop. Regarding the total dissolved salts (TDS) index, all studied water samples varied between very low and low classes of suitability whereas TDS values of these samples ranged from less than 500 to 1000 mg.L^-1. This water varied from excellent in all conditions to suitable for irrigating all crops except for sensitive plants. Mid water suitability was observed in some sites in the study area such as Markaz Tahta, Sahel Tahta, Gehiena Nazet Elheish, Akhmim Elsalamouna, Sohag, and Saqulta. The TDS values of these samples ranged between 1000 mg.L^-1 and 2000 mg.L^-1 whereas this water is moderately suitable for irrigation. El-baliana, akhmim and El-Maragha sites were high in TDS which values ranged between 2000 mg.L^-1 and 3000 mg.L^-1. This water is marginally suitable for irrigation. The obtained data of residual sodium carbonates (RSC) revealed that about a half of the total number of water samples were categorized to be low (RSC is lower than 1.25) whereas this water was excellent for irrigation. Other half of water samples ranged between mid to high for their RSC values (ranged from 1.25 to more than 2.5). According to sodium adsorption ratio (SAR) values, all water samples were classified as low SAR samples whereas their values were less than 10, while one site of Akhmim was under mid SAR class (SAR is between 10 and 18), other one site of El-Maragha was high (SAR is more than 18). All water samples were suitable for irrigation regarding their results of magnesium hazard index (MH), whereas values were less than 50%. Sites of Sahel Tahta, Elmonshah, Sohag, Akhmim, Saqulta, and El-Maragha were found to be under not suitable class where their MH values were more than 50%. Regarding Kelly ratio index (KR), approximately half of the studied water samples were suitable for irrigation (having KR values less than 1) while the other half of water samples are not suitable (having KR values more than 1). Low sodium percentage (SP) values were recorded for sites of El-Baliana, Elmonshah, Sohag, Akhmim, and Saqulta whereas SP values were between 20 and 40 %. This water was suitable for irrigating all crops except for sensitive plants. Moderate suitability was found in many water samples whereas SP values ranged between 40 and 60%, while the rest water samples were classified to be marginally suitable for irrigation and with high SP values (between 60 and 80%). Regarding permeability index (PI), all water samples were under mid class whereas PI values were lower than 35%, except a few sites of Sohag and El-Maragha were having PI values higher than 100%.  

From the previous discussion of water suitability indices’ results, it was clear that sites (26, 27. 29, 32, 34 and 35) of Elmonshah, Sohag, Sohag, Akhmim, El-Maraghah and El-Maraghah, respectively were not suitable for using in irrigating crops. Other water samples ranged from moderately suitable to highly suitable for irrigation.

Table (16) classification of water quality.

Mapping of spatial variability

Spatial variability distribution maps of water parameters and water suitability indices were generated and shown in figures (2 to 17). Each map was classified into different colors in five classes ranged ascending from blue color (lowest values) to red color (highest values) based on values of water parameters or suitability indices.

   Figure (2) Map of Water pH.                                                           Figure (3) Map of Water EC_w.

Figure (4) Map of soluble Na.                                             Figure (5) Map of Soluble K.

Figure (6) Map of soluble Ca.                                             Figure (7) Map of Soluble Mg.

Figure (8) Map of soluble HCO₃.                                     Figure (9) Map of Soluble Cl.

Figure (10) Map of soluble SO₄.                                         Figure (11) Map of TDS.

Figure (12) Map of RSC.                                              Figure (13) Map of SAR.

Figure (14) Map of SP.                                           Figure (15) Map of MH.

Figure (16) Map of PI.                                                     Figure (17) Map of KR.

CONCLUSION

Water quality and suitability of Sohag area were assessed using different indices (EC_w, TDS, SAR, RSC, PI, KR, SP and MH) based on water properties. The studied water samples of sites (Elmonshah, Sohag, Akhmim, and El-Maraghah) were not suitable for irrigating crops, while the rest water samples were suitable for irrigation. It should be recommended that these water sources shall not be used for agricultural purposes without treatment for enhancing their quality. These results as well as the generated maps can be used as a guide for decision-makers and help in better water management planning.