Application of geochemical modeling using NETPATH and water quality index for assessing the groundwater geochemistry in the south Wadi El-Farigh area, Egypt

1 Introduction

Water security for industry and society represents challenge being addressed by development plans in semi-arid and arid areas. Wadi El-Farigh area is one of the newest reclaimed regions in Egypt so, studying its hydrogeology and groundwater quality are very important for soil and crops. Hydrogeochemical models are useful for determining the different factors that control the evolution of groundwater through an aquifer. The Mass Balance Transfer Model NETPATH model (Plummer et al., 1994; El Osta et al., 2020; Gomaa et al., 2020) is mainly used for calculating the mass transfer reaction between groundwater and the aquifer rock matrix along the flow-path.

Groundwater along a flow-path can be assessed by comparing ion activity and solubility products in a state of saturation and groundwater mineralization. This study is oriented to evaluate water security in this area by determining the groundwater geochemistry, water quality index along the flow-path using NETPATH software. The study covers a newly reclaimed area westward of the Nile Delta between longitudes 30°38′ and 30°53‘ E and latitudes 30°05‘ and 30°22‘ N (Fig. 1a). The area comprises a grid of wells, as in 2016, a drilling company drilled many wells in a grid with spacing 100 feddan between each.

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Fig. 1

A) Location map of the study area, b) Groundwater aquifers in the western Nile Delta (modified after RIGW and IWACO, 1991).

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2 Geological setting

The sedimentary succession ranges from the Late Tertiary at 750 m depth to the Quaternary at 300 m in age. Faults with NE-SW and NW-SE trends form essential structural features. Fluvial and lacustrine sediments of Nilotic sands and gravels are the primary deposits of the Pleistocene strata. Shallow marine and brackish water deposits with a thickness of about 45 m that mainly consist of mild green sandstone with fossiliferous limestone underlain by darkish gray clay signify the Pliocene strata. Moreover, a huge area from the Northwestern desert is enclosed by Miocene sediments. These sediments extend from the neighborhood of Wadi El Natrun westward to the Libyan borders. El Moghra Formation represents the Miocene rocks, which essentially consist of gravel, sandstone, and sand with clay interbeds, silicified wood, and vertebrate remains (Said, 1962). The Oligocene strata is ∼390 m think. Lenses of sand in clay are created in the middle and lower parts while basalt form the upper part.

3 Groundwater hydrology

Wadi El-Farigh area is located westward of Nile Delta aquifer (Fig. 1b). The Miocene aquifer is placed in the depression of Wadi El-Farigh in the west and south of Wadi El Natrun, which is ∼100 m thick. The general trend of the groundwater movement is from all directions to the depressions. The recharge is from the Nile Delta’s southern part. Furthermore, faults play a significant role as connecting agent between the different aquifers.

4 Materials and methods

In December 2017, 25 groundwater samples were gathered from different boreholes for chemical investigation. During the sampling process, the temperatures of the samples were recorded at depth and electric conductivity using CLT equipment. Unacidified samples were gathered in 200 ml polyethylene bottles. Analysis of major cations (Na⁺, K⁺, Ca²⁺, and Mg²⁺), anions (Cl⁻, SO₄²⁻, HCO₃⁻), and minor ions, such as silica (SiO₂), nitrate (NO₃–) and phosphate (PO₄³⁻), were carried out. Geochemical results were plotted on Gibbs diagram (Gibbs, 1970) and Piper plot (Piper, 1944) to create the controlling mechanism for water chemistry as well as hydrogeochemical facies of the collected samples. The Gibbs diagram clarifies the mechanism through the groundwater chemical composition. It involves the connection among of the total dissolved solids (TDS) and Cl^-/ (Cl^- + HCO₃^–) or Na⁺/ (Na⁺ + Ca²⁺) where distinguished into three fundamental procedures, such as rock-weathering, precipitation, and evaporation can be inferred.

Such investigations can be conducted through different chloro-alkaline indices, CAI-1 and CAI-2, and at the end, these can be employed by many experts to outline the techniques of base ion exchange that manage the hydrochemical facies of groundwater (Toumi et al., 2015). The following formula is used to calculate chloro-alkaline indices (CAI) as in Eqs. (1) and (2):

Negative values indicate the exchange of Mg²⁺ and Ca²⁺ in water with Na⁺ and K⁺ ions from rocks that reflect subsidiary exchange, which known as a cation–anion exchange reaction. While positive values illustrate the variation of Na⁺ and K⁺ ions of water with Mg²⁺ and Ca²⁺ ions of rocks. The origin of the groundwater was defined based on different hydrochemical indices, such as Cl/HCO₃, Mg/Ca, and the cationic exchange value (CEV) = {Cl^– (Na + K)}/Cl. For calculating water quality index (WQI), firstly, the weight of each groundwater sample was assigned (wi), and then, a quality scheme (qi) and relative weight (Wi) were computed. Wi has been specified for TDS, EC, pH, Na⁺, K⁺, Mg²⁺, Ca²⁺, Cl⁻, HCO₃⁻, SO₄²⁻, PO₄³⁻, NO₃ ⁻ and F⁻, and Wi was estimated from Eq. (3) (Rabeiy, 2018).

The Wi values for different groundwater parameters were computed as;

The measured concentrations of the parameters (ci) were considered to estimate qi according to the WHO (2011) standard for drinking activities. The calculation of qi was built on Eq. (4) (Rabeiy, 2018).

Then, as illustrated in Eq. (3), WQI was computed using the estimated qi and Wi.

The calculated WQI was finally verified with the WQI range (Sahu and Sikdar, 2008) to categorize the water type in the studied area. Then, a WQI map was developed using ESRI ArcGIS version 10. The method used for interpolating data is the Inverse Distance Weight (IDW) method. The drinking groundwater was interpreted according to Davis and Dewiest (1966) and WHO (2011). Various concepts must consider, such as sodium percentage (%Na), sodium adsorption ratio (SAR), residual sodium carbonate (RSC), permeability index (PI), and United States Salinity Laboratory Diagram (USSL) classification during determining the groundwater quality and their appropriateness for agricultural activities. NETPATH software (Plummer et al., 1994) is a valuable tool in order to simulate the net geochemical mass-balance reactions along the hydrologic flow-path from upstream towards downstream. This software helps to calculate the mmol/kg H₂O of relevant minerals that enter (dissolution) or leave (precipitation) the solution. Five profiles were created along the flow-path (Fig. 2). Generally, the flow direction in the studied aquifer was from south to north. The constrains were calcium, carbon, sodium, magnesium, sulfur, chloride, potassium, and silica, while the phases were kaolinite, calcite, dolomite, sodium chloride, illite gypsum, SiO₂, and Na₂SO₄.

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Fig. 2

Water table map with the flow direction and model paths in the studied area.

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5 Results and discussion

5.3

5.3 Estimation of ionic relationships

The mechanism of salinity and saline intrusion in arid and semi-arid areas can be assessed through the Na-Cl relationship (Sami, 1992). A good matching was illustrated between Na⁺ and Cl⁻ (Fig. 3a). A relationship between Ca + Mg-(SO₄ + CO₃ + HCO₃) and Na-Cl was applied to illustrate the source of excess Na was plotted (Fig. 3b). Results indicate a good linear correlation (R² = 0.81) with a slope of −0.8. The relationship in (Fig. 3c) displays the weathering of silicate is a momentous agent in identifying the chemical composition of groundwater. A relationship was found between Na⁺ and Ca + Mg (Fig. 3d). A positive relationship between Na⁺ and SO²⁻ (Fig. 3e) revealed that the weathering of Glauber’s salt (Na₂SO₄.10 H₂O) is an alternative source of excess Na⁺. A positive correlation between Ca and SO₄ (Fig. 3f) reflects the prevalence of gypsum.

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Fig. 3

Different ions relation plots for the studied groundwater samples.

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5.4

5.4 Hydrogeochemical types

Plotting the analyzed samples though Piper diagram indicated that (Na + K) alkali metals exceeded the (Ca + Mg) earth elements and the supremacy of strong acid (Cl⁻ and SO₄²⁻) above the weak acid (HCO₃⁻ and CO₃²⁻) (Fig. 4). About 56% of the samples were of similar hydrochemical type of (Na + K) – (Cl + SO₄), about 20% were (Na-K- HCO₃) type while 16% were Ca²⁺–Mg²⁺–Cl⁻–SO₄²⁻ type and about 8% were the water type of Ca²⁺–Mg²⁺– HCO₃⁻. By plotting the chemical analysis in the Gibbs diagram (Fig. 5) it is indicating rock weathering controlling the groundwater chemistry.

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Fig. 4

Piper trilinear diagram showing the identified hydrogeochemical types.

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Fig. 5

Gibbs diagram for the groundwater samples. a Cationic. b Anionic.

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6 Water quality for drinking and irrigation utilities

6.1

6.1 Drinking water quality

The TDS groundwater classification (Davis and Dewiest, 1966) was carried out to assess the appropriateness of groundwater for household and agricultural usage. Depending on the values of TDS, it is concluded that only 32% of the samples were fit for drinking; 56% allowable for drinking activities, and 12% are considered appropriate for irrigation. Results of nitrate concentration indicate that all the samples did not exceed the WHO limit for nitrates in drinking water, which is ∼10 mg/l, which means that all the studied samples are appropriate for drinking.

The estimated water quality index is illustrated in Table 3. It illustrates that 80% of the studied samples were described as good quality water, 8% were classified as poor-quality water, and 12% were excellent (Table 3). The WQI map illustrated that most of the water samples had a WQI less than 100 mg/l and were appropriate for drinking (Fig. 6a).

Table 3 Calculated WQI for groundwater samples.

Sample	WQI	Type of water
1	67	Good water
2	85	Good water
3	107	Poor water
4	82	Good water
5	80	Good water
6	91	Good water
7	91	Good water
8	97	Good water
9	49	Excellent water
10	73	Good water
11	83	Good water
12	91	Good water
13	68	Good water
14	117	Poor water
15	63	Good water
16	59	Good water
17	53	Good water
18	46	Excellent water
19	51	Good water
20	50	Good water
21	41	Excellent water
22	82	Good water
23	87	Good water
24	52	Good water
25	50	Good water

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Fig. 6

a) Water Quality Index map in the study area, b) USSL classification of groundwater samples in the study area (after Richards, 1954).

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7 Conclusions

Hydrochemical analysis on 25 water samples specified that the groundwater is fresh to brackish, with weak alkalinity. Depending on the calculated CAI 1 and CAI 2, it was noticed that 84% of the analyzed samples reflect an indirect base-exchange reaction, which confirms the ion exchange is a vital agent that affect the groundwater chemistry, while 16% of the samples give positive values. The sequence of the major ions was arranged as Na⁺ ˃ Ca²⁺ ˃ Mg²⁺ ˃ K⁺ and Cl⁻ ˃ SO₄²⁻ ˃ HCO₃⁻ ˃ CO₃²⁻. The predominant hydrochemical properties of groundwater were the (Na⁺+K⁺) (Cl⁻ + SO₄^2-) type. Gibbs diagram illustrated that rock weathering and evaporation were the main agents controlling groundwater chemistry in Wadi El-Farigh area. Consistent with the calculated hydrochemical indices Mg/Ca and Cl/HCO₃ and the cationic exchange value (CEV), it was clarified that the groundwater samples are of inland origin.

Evaluation of groundwater samples according to WHO (2011), reveals that 88% of the samples are appropriate for drinking utilities and the concentration of nitrate not exceed 10 mg/l in all samples. From the results of calculating water quality index it can be inferred that 80% of the samples are of good water type for drinking utilities, 8% are in poor class and 12% are in the excellent class. None of the samples are located in the unsuitable water type class. The evaluation of the groundwater for irrigation purposes was determined from Na%, SAR, RSC, PI and USSL plot which illustrate that all the studied samples are appropriate for irrigation utilities but the high salinity values can have bad effect on growth of plant. Therefore, the preferable solution will be to grow crops that are highly resistant to salinity. Results of geochemical modeling for groundwater of the Miocene aquifer reveal that the water is under saturated with respect to gypsum, calcite and dolomite and overestimated with kaolinite, illite along the flow paths. Silicate weathering, ion exchange and dissolution of halite processes are the main geochemical processes that control the chemical composition along groundwater flow-paths.