Hydrogeochemistry and Quality Assessment of Groundwater Under Some Central Nile Delta Villages, Egypt

Abstract

The target of this work is to assess the impact of the human activities on the hydrochemistry and quality of the groundwater under Nile Delta villages. Sixteen groundwater samples were collected during 2016. Hydrochemical analyses including major and trace elements were done. Spatial distribution of the element concentrations according to WHO guidelines, WQI (drinking water quality index), and statistical analysis was used for assessment. The sampled groundwater showed variable quality from one village to another and was classified into three clusters. Cluster A is characterized by higher concentrations of total dissolved solids (TDS), electrical conductivity (EC), potassium, magnesium, sodium, calcium, sulfate, chloride, bicarbonate, Mn, Zn, P, NH₄, Ba, and unfit WQI values. Low water quality of this sample is related to the effect of El-Gharbia main drain and seawater intrusion. Cluster B included samples 4, 8, 11, and 15 and had the moderately mean ion concentrations and higher concentrations of Fe, Sr, and Si compared to the other two clusters. The latter cluster major ion concentration arrangement is sodium > calcium and chloride > bicarbonate. WQI of this cluster varies from poor, very poor to unfit.

Samples 1, 2, 3, 5, 6, 7, 9, 10, 12, 13, and 14 belong to cluster C which had the lowest ion concentrations and dominated by Ca > Na > Mg and HCO₃ > Cl ion concentration arrangement. WQI of most of these samples is good. Undesirable concentrations of arsenic and ammonia are indications of direct infiltration from septic tanks and/or seepage from the drains. Finally, water treatment should be done before usage of groundwater from under the Nile Delta villages because of human-induced contamination.

1 Introduction

The guidelines for drinking water are attributed to two main criteria: (1) the absence of unacceptable taste, odor, and color and (2) the absence of substances that harm the physiological functions. In this way, water needs to get together with certain physical, chemical, and microbiological principles, that is, it must be free from illnesses delivering microorganisms and concoction substances, hazardous to well-being before it can be named consumable.

Most of the villages of the developing countries currently have a water supply, yet few of them have wastewater collection and treatment system [1–3]. There is a need to construct proper sewer frameworks in the small communities; otherwise, individuals will depend on on-site sanitation. In such septic tank, sewage water infiltrates to the underlying aquifer forming the biggest volumetric source of pathogenic organisms to the groundwater. Wastewater and sludge are also dumped in the closest water body or directly on agrarian fields.

Bishnoi and Arora [1] found that village’s wastewater effluent was the major source of fluoride in the potable groundwater in Haryana, India. Village’s environs in central India were the source of nitrate contamination in basaltic groundwater aquifer [2]. Gao et al. [4] monitored the groundwater quality in drinking water wells in a village belonging to Shanghai City (China). They found that the groundwater in the residential areas was highly contaminated by NH4-N without significant seasonal patterns and most water samples are unsuitable for human consumption. The work of Sajidu et al. [5] revealed high levels of fluorides (>1.5 mg/l) in some villages of Southern Malawi, and a positive correlation was observed between the pH of the water and fluoride concentrations. Geriesh and EL-Rayes [6] studied the municipal contamination of the shallow groundwater under south Ismailia City villages (Egypt). They concluded that the major source of the groundwater contamination was the seepage from the poorly constructed septic tanks; therefore, the human activity was the main source of higher nitrate and heavy metals concentrations and high bacterial count in the shallow groundwater. Emara et al. [7] deduced that the industrial activities, wastewater drains, and fertilizers are the main sources of groundwater pollution in the water-bearing formation of the Quaternary aquifer under some rural areas in Giza Governorate of Greater Cairo, Egypt. In the central part of the Nile Delta, most of the villages are unsewered; therefore, the consumed water for domestic purposes is stored in the septic tanks and artificially recharges the groundwater causing water logging and groundwater pollution. Salem [3] integrated the water level, sedimentological setting, stable isotopes, subsurface temperature, and hydrochemistry data to investigate and evaluate the problem.

The Nile Delta is facing great challenges, with extremely dense housing, high pressure on the cultivated land, high water requests, and rapid population growth. Groundwater is an essential source of drinking water in the countryside regions in Egypt. Each needs about 2 l of clean drinking water every day. Hence, it is necessary to evaluate the quality of water proposed to be utilized for drinking. Indeed, the chemical pollutants seriously affect the human health. Natural processes and anthropogenic activities affect the water quality. The quality of water is portrayed by water parameters (physical, chemical, and microbiological), and human well-being is at hazard if values surpass satisfactory limits [8].

Water quality index (WQI) is the best strategy for measuring water quality. Various water quality parameters are incorporated into a mathematical equation to rate water quality, estimating the suitability of water for drinking [9]. WQI was initially created by [10] to gauge water quality by utilizing ten most routinely used water parameters. Subsequently, this method was modified by various specialists. The utilized water quality parameters fluctuate by number and types. The weights in every parameter depend on its separate guidelines, and the assigned weight shows the parameter’s importance and effects on the index. WQI enables comparison between various samples. The index is simplifying a complex dataset into easily estimated, usable data and understandable even by lay people. Groundwater was sampled from 16 villages (Fig. 1a, b) in the central part of the Nile Delta to evaluate the effect of human activities in the some Nile Delta villages on groundwater hydrogeochemistry and quality. Many researchers have investigated the water quality in the Nile Delta among them [3, 11–26].

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig1_HTML.png — Fig. 1
Location map of the study area (a) and the locations of the collected groundwater samples (b)

2 Geology of the Study Area

The geology of the Nile Delta has been extensively discussed by some researchers over several decades [27–34]. Mit Ghamr Formation composed of sand and gravels with thin clay intercalations. It is assumed to be Pliocene to Quaternary age. The whole sequence of Mit Ghamr is capped by Bilqas formation of the Holocene age. The depositional environment of this formation is probably shallow marine to fluvial. On both sides of the present delta, these deposits form a series of gravel terraces at various heights [35]. Bilqas formation is the top cover of the Delta area and consists mostly of clay. Fine-grained sands, silts, plant remains, and peat deposits are frequent. According to Salem [3] “These sediments appear to have been deposited under continental, lagoonal, fluvatile and beach environments. They represent the advent of a third Holocene sea transgression phase advancing almost from the N and NE direction.”

In the study area, according to the shallow cross section given in Fig. 2, Bilqas formation consists mainly of fine detrital materials ranging from the two classical end members, clay, and silt including some sand tracks, particularly in the north central part. The clay thickness increases from south to north and from west to east. The lowest clay thickness appears at Kotamma location to the west of the study area.

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig2_HTML.png — Fig. 2
Geohydrologic sections through the groundwater aquifer in the study area [36]

3 Materials and Methods

Groundwater samples were collected from 16 villages in the study area during 2016 (Fig. 1b). Samples were obtained from wells range in depth from 9 to 46 m.

3.1 Hydrochemical Analysis

Samples were gathered in prewashed clean polyethylene bottles. Temperature, pH, DO (dissolved oxygen), ORP, TDS (total dissolved solids), and electrical conductivity (EC) of the water samples were measured in site. Samples were kept at 4 °C and chemically analyzed after a short time of sampling to reduce the physicochemical changes [37]. Alkalinity and chloride concentrations were measured by titration. Sulfate, nitrate, and ammonia were measured by a spectrophotometer. Concentrations of cations were measured utilizing the ICP-Perkin Elmer/Optima 7000DV (inductively coupled plasma) at the Central Lab of Tanta University, Egypt. Complete hydrochemical analysis of the collected water samples is listed in Table 1.

Table 1

Hydrochemical characteristics of the analyzed water samples

S. No		1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
Village name		Shubra El-Namla	Abiar	Nawag	Damatt	Shabsheer Elhessa	Shenta Ayaash	Bolqina	Pirma	Saa Elhagr	Kotama	Shubra Qaas	Nahttai	Mit Badr Halawa	Mit Habib	Damro	Dokhmees
Param.	Units
Depth	m	35	27	44	15	46	45	38	28	28	30	9	25	33	32	21	16
Temp.	°C	25.3	25.4	25.3	25.1	25	25.5	24	23.7	23.7	24.1	20.2	un	un	un	21.6	22.4
TDS	mg/l	430	440	690	1,550	520	770	330	2,580	680	350	1,500	350	330	500	2,500	7,420
EC	us/cm	880	880	1,400	3,320	1,060	1,055	580	5,180	1,370	740	3,075	717.5	676.5	1,025	5,020	14,870
ORP	mv	−69	−69	150	−0.6	135	28	57	−9.6	−25.5	−50.1	−29	−26.5	−75	−75	−48.9	−17.3
PH		7.64	7.42	7.77	7.29	7.64	7.74	8.45	7.01	7.3	7.72	7.34	7.3	8.1	7.96	7.83	7.26
DO	mg/l	0.5	0.5	0.7	0.7	0.7	0.6	0.7	un	un	un	un	un	un	un	2.3	un
TH	mg/l	241.6	279.6	350.8	724.18	311.2	425.8	168.4	1,376	405.9	161.28	328.9	222	178.72	259.2	557.84	3898.6
K	mg/l	4.725	3.81	5.71	20.037	12.57	3.126	5.96	95.18	3.52	2.696	1.79	2.288	2.6	3.13	33.34	118.5
Na	mg/l	36	42	56	200.79	41	71	34	216.66	64.27	39.8	435.5	45.2	33.9	74.2	698	1,087
Mg	mg/l	26	31	38	49.8	32	38	24	160	49	15.8	29	20	14.2	12	32.4	446
Ca	mg/l	54	61	78	208	72	108	28	288	82	38.6	84	56	48.2	84	170	828
Cl	mg/l	105.8	98	157.6	516	82	113.4	82.5	697.1	163	58.8	613.5	57	49.9	166.7	486	2,566
NO₃	mg/l	1.93	1.69	0.6	1.87	2.23	2.14	2.01	6.63	4.83	1.97	1.7	1.83	1.68	4.64	28	3.8
SO₄	mg/l	23.24	56.66	72.47	72.5	52.27	63.67	25.29	188.2	39	15.6	72.3	65.2	0.3	4	244.53	220.68
HCO₃	mg/l	205	215	236	81.646	266	386	146	817.8	321.4	206	386	201	242.5	210	860	2,563
CO₃	mg/l	0	0	12	13	12	12	11	17.2	3.6	8	10	14	12	2.1	62	40
Fe	mg/l	0.286	0.025	0	0.43	0	0	0	1.144	1.824	0.0056	0	0	1.231	0.527	0	0
Mn	mg/l	1.087	0.722	0.645	0.774	0.51	0.324	0.2	0.863	1.616	0.644	1.85	0.387	0.25	0.217	0.299	1.496
Zn	mg/l	0.007	0.088	0.0072	0.007	0.007	0.0071	0	0.008	0.067	0.005	0.01	1.025	1.45	0.174	0.048	2.9
N	mg/l	1.93	1.69	2.07	1.87	2.23	2.14	1.52	6.63	4.83	0.122	5.155	4.09	4.14	3.46	4.53	3.8
P	mg/l	0.598	0.401	0.398	0.38	0.373	0.376	0.365	0.13	0.64	0.11	0.48	0.44	0.53	0.64	0.53	0.57
AS	mg/l	0.15	0.184	0.182	0.182	0.177	0.227	0.01	0.24	0.008	0.186	0.01	0.008	0.006	0.012	0.011	0.11
NH₄	mg/l	0.57	0.42	0.6	0.47	0.61	0.52	0.6	12.45	1.49	1.02	2.82	0.79	2.03	5.83	6.97	9.78
Ba	mg/l	0.177	0.145	0.027	0.025	0.02	0.02	0.01	0.024	0.025	0.067	0.074	0.068	0.066	0.091	0.314	0.114
Sr	mg/l	0.748	0.579	1.187	1.34	0.71	0.631	0.42	0.794	0.919	0.569	1.246	0.505	0.452	0.36	1.039	0.76
Si	mg/l	42.55	28.22	31.56	35.75	35.59	29.96	14	50.66	26.58	42.16	14.38	12.69	10.99	14.04	17.35	13.31

Note: un means unmeasured

Values of desirable and maximum allowable limits for drinking of the measured parameters are listed in Table 2 according to WHO [8]. Each parameter is assigned a weight according to its relative importance for the quality of water for drinking purposes. Maximum weight of 5 is assigned to total dissolved solids (TDS), EC, (NO₃), (Pb), and As; weight of 4 is assigned to (SO₄), TH, (Mn), and (Cr); weight of 3 is assigned to pH, (Cl), (Na), and (Cd); and weight of 2 is assigned to (K), (Mg), (Ca), (CO₃), (HCO₃), (Fe), (Cu), and (Zn). The water quality parameters are selected based on the guidelines as shown in Table 2 [38]. WQI is calculated as follows:

$\mathrm{WQI}=\Sigma\ Qi\times Wi$

(1)

Table 2

Desirable limits of parameters and its assigned relative weight

Parameters	WHO desirable limits	Weight (wi)	Relative weight
TDS	500 mg/l	5	0.08621
PH	6.5–8.5	3	0.05172
EC	1,500 us/cm	5	0.08621
TH	300 mg/l	4	0.06897
Ca	200 mg/l	2	0.03448
Na	200 mg/l	3	0.05172
Mg	125 mg/l	2	0.03448
K	12 mg/l	2	0.03448
Cl	250 mg/l	3	0.05172
CO₃	350 mg/l	2	0.03448
SO₄	250 mg/l	2	0.03448
NH₄	0.5 mg/l	4	0.06897
HCO₃	350 mg/l	2	0.03448
NO₃	50 mg/l	5	0.08621
Fe	0.3 mg/l	3	0.05172
Mn	0.4 mg/l	4	0.06897
Zn	5 mg/l	2	0.03448
As	0.01 mg/l	5	0.08621
		∑W = 58	∑W = 1

Qi is the ith quality rating and is given by Eq. (2), and Wi is the ith relative weight of the parameter I and is given by Eq. (3).

$Qi=\left( Ci/ Si\right)\times 100$

(2)

where Ci is the ith concentration of water quality parameter and Si is the ith drinking water quality standard according to the guidelines of WHO [8] in mg/l.

(3)

where wi is the weight of ith parameter and n is the number of chemical parameters.

3.2 Statistical Analysis

Multivariate statistical techniques, such as CA and PCA, are often used as “unbiased methods” to summarize associations between samples and variables. Such associations based on similar magnitudes and variations in the chemical and physical composition may reveal the effects of climate or human activity on water quality. Agglomerative hierarchical clustering approach options include single linkage, complete linkage, weighted and unweighted pair group average linkage, and centroid linkage. Ward’s method was used for this analysis because it is commonly applied in the literature germane to this study [39, 40]. One of the reasons it is widely applied is that it tends to yield spherical clusters of the same size (i.e., classification variables over all classes essentially have the same variance).

PCA is an effective method for pattern estimation that used to clarify the difference of an extensive arrangement of intercorrelated variables. It demonstrates the relationship between variables by decreasing the dimensionality of the dataset [41]. The covariance matrix of the original variables is used to extract the eigenvalues and eigenvectors. PCA changes informational collection into an uncorrelated one [42]. The first PC is the projections of the given points onto the extreme fluctuations, the second PC has the change subject to being orthogonal to PC1; the third PC has the greatest difference subject to being orthogonal to the first and second PCs [43, 44]. The multivariate statistical analysis relates variables into PCs depending on their common relationship coefficients and these affiliations might be used to estimate the mineralization, lithology and ecological procedures [45].

4 Results

The physical and chemical properties of the groundwater samples from the study area were given in Table 1.

4.1 Description and Spatial Distribution

The pH values were acceptable in the range of 7.01–8.45. Electrical conductivity reached its minimum value (580 μs/cm) in sample 7 and its maximum (14,870 μs/cm) in sample 16. According to WHO [8], groundwater samples 1, 2, 7, 10, 12, and 13 are under the desirable limit; samples 3, 5, 6, 9, and 14 are of permissible values; and samples 4, 8, 11, 15, and 16 are unfit for drinking. As shown in Table 1 and Fig. 3a, TDS content is variable where samples 2, 7, 10, 12, and 13 have TDS < 500 mg/l and fall within the desirable range for drinking category; samples 3, 5, 6, 9, and 14 have TDS range from 500 to 1,000 mg/l exceeding the desirable limit and permissible for drinking; and samples 4, 8, 11, 15, and 16 have TDS > 1,000 mg/l and fall within the unfit category for drinking. The water salinity reaches its maximum value (TDS equal 7,420 mg/l) at Dokhmees (sample 16) in the northeastern part of the area.

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig3_HTML.png — Fig. 3
Spatial distribution maps of TDS (a), HCO₃ (b), TH (c), Cl (d), NO₃ (e), and SO₄ (f) concentrations according to WHO [8] drinking water guidelines

The values of alkalinity in all samples ranged from 157 mg/l (sample 7) to 2,603 mg/l (sample 16). Except samples 6, 8, 11, 15, and 16, other samples are of the desirable limit of HCO₃ (Fig. 3b). Total hardness concentrations range from 161.28 mg/l (sample 10) to 3898.6 mg/l (sample 16). According to Sawyer and McCarty [46] common hardness scale, the groundwater samples 1, 2, 7, 10, 12, 13, and 14 are under the hard category, but all other samples are very hard water (Fig. 3c). The lowest concentration of the chloride ion is 49.9 mg/l (sample 13), and the highest level is 2,566 mg/l was detected in sample 16. Chloride levels in most samples are below WHO permissible limits (Fig. 3d) except that of samples 4, 8, 11, 15, and 16. Nitrate concentrations were found to be in a range of 0.6 mg/l (samples 3) to 6.63 mg/l (sample 8). Therefore, all samples are under the desirable limits (Fig. 3e). Concentrations of sulfate are below the WHO permissible limits (Table 1 and Fig. 3f) and range from 0.3 mg/l (samples 13) to 244.53 mg/l at sample 16.

Concentrations of calcium and magnesium in the collected water samples, respectively, range from 28 and 12 mg/l (samples 7 and 14, respectively) to 828 and 446 mg/l (samples 16). Calcium concentrations (Fig. 4a) are compatible with the desirable range in most samples except samples 4, 8, and 16 which are of unfit values. Magnesium levels are of desirable range in most samples and unfit in samples 8 and 16 (Fig. 4b). Water with unfit sodium levels has a bad taste. Ranges of sodium and potassium levels in the collected samples are, respectively, 33.9 mg/l (samples 13) to 1,087 mg/l (samples 16) and from 1.79 mg/l (samples 11) to 118.5 mg/l (samples 11). Sodium concentrations are compatible with the desirable range in samples 1, 2, 3, 5, 6, 7, 9, 10, 12, and 13 and of unfit values in samples 4, 8, 11, 15, and 16 (Fig. 4c). Potassium concentrations are of desirable range in samples 1, 2, 3, 6, 7, 9, 10, 11, 12, 13, and 14 and of unfit value in samples 4, 5, 8, 15, and 16 (Fig. 4d).

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig4_HTML.png — Fig. 4
Concentrations spatial distribution maps of Ca (a), Mg (b), Na (c), and K (d) according to WHO [8] drinking water guidelines

Trace element concentrations are listed in Table 1. Iron concentrations range from 0 to 1.824 mg/l. Samples 4, 8, 9, 13, and14 are above the acceptance WHO [8] limit which is 0.3 mg/l (Fig. 5a). Concentrations of zinc in all the samples are under WHO desirable limit (5 mg/l) and range from 0.005 to 1.45 mg/l (Fig. 5b). The content of manganese is lower than the desirable limit which is 0.4 mg/l in samples 6, 7, 12, 13, 14, and 15 (Fig. 5c). The levels of silicon in the samples were in the range of 10.99 mg/l in sample 13 to 50.66 mg/l in sample 8. Strontium highest concentration (1.34 mg/l) was recorded in sample 4, and sample 14 has the lowest concentration (0.36 mg/l). Barium concentrations were ranging from 0.01 mg/l in sample 7 to 0.314 mg/l in sample 15 (Fig. 5d). Concentrations of barium in all the samples are under WHO desirable limit (0.7 mg/l). The levels of arsenic in the samples were in the range of 0.006 in sample 13 to 0.24 mg/l in sample 8 (Fig. 5e) and exceeded the WHO guideline (0.01 mg/l) in all samples except samples 9, 12, and 13. Phosphorus concentrations were ranging from 0.11 mg/l in sample 10 to 0.64 mg/l in sample 14. Calculated corrosive ratio (CR) values reveal that most of the samples fall within corrosive category (13 wells), and just 3 wells are of noncorrosive properties (Fig. 5f). Concentrations of ammonia in all samples are ranging from 0.42 mg/l in sample 2 to 12.45 mg/l in sample 8. Samples 2 and 4 are under the acceptance WHO limit which is 0.5 mg/l, and all other are above the WHO limit (Fig. 5g).

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig5_HTML.png — Fig. 5
Spatial distribution maps of Fe (a), Zn (b), Mn (c), Ba (d), As (e), CR (f), and NH₄ (g) concentrations according to WHO [8] drinking water guidelines

4.2 Statistical Analysis

Analysis of correlation between the measured physicochemical parameters (Table 3) reveals that strong relationships were recognized between TDS-K, TDS-Na, TDS-Mg, TDS-Ca, TDS-Cl, TDS-SO₄, TDS-HCO₃, K-Na, K-Mg, K-Ca, K-Cl, K-SO₄, K-HCO₃, K-NH₄, Na-Mg, Na-Ca, Na-Cl, Na-SO₄, Na-HCO₃, Mg-Ca, Mg-Cl, Mg-SO₄, Mg-HCO₃, Mg-Zn, Ca-Cl, Ca-HCO₃, Ca-Zn, Ca-SO₄, Cl-SO₄, Cl-HCO₃, NO₃-CO₃, NO₃-Ba, SO₄-HCO₃, SO₄-NH₄, HCO₃-Zn, and As-Si. The intermediate relationship is shown between TDS-Zn, TDS-NH₄, K-Zn, Na-Zn, Na-NH₄, Mg-NH₄, Ca-NH₄, Cl-Zn, Cl-NH₄, NO₃-SO₄, SO₄-CO₃, HCO₃-NH₄, CO₃-Ba, Fe-N, and Mn-Sr. These very strong to intermediate relationships suggest that the increase in TDS was accompanied by an increase in the concentrations of the all major ions as well as the increase in NH₄, NO₃, Zn, and As. This indicates that water under the villages receives water from the domestic wastes due to bad or absence of sewage networks.

Table 3

Correlation matrix for the chemical constitutions present in the collected groundwater samples

	TDS	K	Na	Mg	Ca	Cl	NO₃	SO₄	HCO₃	CO₃	Fe	Mn	Zn	N	P	AS	NH₄	Ba	Sr	Si
TDS	1
K	0.91	1.00
Na	0.93	0.77	1.00
Mg	0.95	0.90	0.78	1.00
Ca	0.98	0.91	0.85	0.98	1.00
Cl	0.99	0.88	0.90	0.96	0.98	1.00
NO₃	0.26	0.23	0.48	0.02	0.13	0.12	1.00
SO₄	0.93	0.88	0.91	0.83	0.87	0.86	0.52	1.00
HCO₃	0.99	0.89	0.91	0.96	0.98	0.98	0.25	0.91	1.00
CO₃	0.14	0.13	0.38	−0.11	0.01	0.01	0.90	0.44	0.12	1.00
Fe	−0.10	0.05	−0.22	−0.03	−0.06	−0.11	−0.02	−0.17	−0.09	−0.15	1.00
Mn	0.42	0.36	0.40	0.43	0.39	0.49	−0.18	0.28	0.38	−0.32	0.20	1.00
Zn	0.71	0.56	0.60	0.76	0.75	0.74	−0.08	0.54	0.75	−0.13	0.00	0.17	1.00
N	0.34	0.48	0.37	0.27	0.27	0.30	0.36	0.41	0.30	0.30	0.52	0.32	0.21	1.00
P	0.12	−0.13	0.24	0.07	0.11	0.15	0.16	0.03	0.15	−0.06	0.20	0.21	0.31	0.23	1.00
AS	−0.01	0.17	−0.22	0.12	0.07	−0.02	−0.32	0.01	−0.01	−0.21	−0.27	−0.14	−0.29	−0.49	−0.70	1.00
NH₄	0.72	0.86	0.65	0.66	0.68	0.66	0.46	0.75	0.69	0.30	0.21	0.17	0.37	0.67	−0.05	−0.07	1.00
Ba	0.22	0.09	0.46	0.03	0.10	0.14	0.76	0.39	0.23	0.57	−0.28	−0.08	0.07	0.06	0.36	−0.34	0.24	1.00
Sr	0.23	0.16	0.33	0.07	0.15	0.22	0.20	0.29	0.15	0.30	−0.04	0.51	−0.24	0.16	0.00	0.04	0.01	0.02	1.00
Si	−0.20	0.05	−0.38	−0.11	−0.16	−0.23	−0.17	−0.14	−0.22	−0.14	0.07	0.02	−0.55	−0.31	−0.65	0.81	−0.04	−0.26	0.15	1.00

Values listed in bold font are strong positive relationship. Values listed in italic font are intermediate positive relationship

Using HCA dendrogram, collected samples were classified according to the abundance of the elements into three groups A, B, and C (Fig. 6). The elements’ average concentrations are shown in Table 4. Cluster A includes sample 16 which is dominated by higher concentrations of TDS, EC, potassium, magnesium, sodium, calcium, sulfate, chloride, bicarbonate, Mn, Zn, P, NH_4, and Ba compared to the other two clusters. However, its pH values (7.26) were the lowest compared to cluster B (7.40) and cluster C (7.73). This sample was obtained from Dokhmees village which is located in the northeastern part of the study area and near to El-Gharbia main drain. Therefore, such concentrations could be related to the effect of the drain water and/or seawater intrusion.

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig6_HTML.png — Fig. 6
Dendrogram based on Ward’s method shows three groups of the collected water samples according to the abundance of the hydrochemical composition

Table 4

Hydrochemical compositions of clusters A, B, and C

	Unit	Cluster A (sample 16)	Cluster B (samples 4,11, 8, and 15)			Cluster C (samples 1, 2, 3, 5, 6, 7, 9, 10, 12, 13, and 14)
	Unit	Cluster A (sample 16)	Min	Max	Average	Min	Max	Average
TDS	mg/l	7,420	1,500	2,580	2032.5	330	770	490
EC	μS/cm	14,870	3,075	5,180	4148.75	580	1,400	944
PH		7.26	7.01	7.83	7.3675	7.300	8.450	7.731
K	meq/l	3.03	0.48	2.44	1.07	0.059	0.322	0.117
Na	meq/l	47.27	8.73	30.36	16.86	1.474	3.227	2.085
Mg	meq/l	36.71	2.39	13.17	5.58	0.988	4.033	2.245
Ca	meq/l	41.40	4.20	14.40	9.38	1.400	5.400	3.226
Cl	meq/l	72.41	14.55	32.44	20.99	1.407	4.701	2.909
NO₃	mg/l	3.80	1.70	28.00	9.55	0.600	4.830	2.323
SO₄	meq/l	7.29	0.58	3.91	1.88	0.006	1.507	0.790
HCO₃	meq/l	42.03	6.33	13.41	8.77	2.394	6.330	3.928
CO₃	meq/l	0.66	0.16	1.02	0.42	0.000	0.230	0.129
Fe	mg/l	0.01	0.01	1.14	0.40	0.002	1.824	0.365
Mn	mg/l	1.496	0.30	1.85	0.95	0.217	1.616	0.611
Zn	mg/l	2.9	0.01	0.05	0.02	0.005	1.450	0.259
N	mg/l	3.8	1.87	6.63	4.55	0.122	4.830	2.610
P	mg/l	0.57	0.13	0.53	0.38	0.110	0.640	0.444
AS	mg/l	0.11	0.01	0.24	0.11	0.006	0.227	0.120
NH₄	mg/l	9.78	0.47	12.45	5.68	0.420	5.830	1.316
Ba	mg/l	0.114	0.02	0.31	0.11	0.020	0.177	0.069
Sr	mg/l	0.76	0.79	1.34	1.10	0.360	1.187	0.653
Si	mg/l	13.31	14.38	50.66	29.54	10.990	42.550	27.545

Cluster B includes samples 4, 8, 11, and 15. As for chemical elements, this water type had the moderately mean concentrations among the three clusters (Table 4), and it had higher ion concentrations of Fe, Sr, and Si than the other two clusters and dominated major ion concentrations arranged as follows: sodium > calcium and chloride > bicarbonate. They also had relatively high concentrations of potassium, magnesium, and sulfate. Finally, the water samples of cluster C (samples 1, 2, 3, 5, 6, 7, 9, 10, 12, 13, and 14) were dominated by Ca > Na > Mg and HCO₃ > Cl ion concentration arrangement (Table 4). The average concentrations of the physicochemical parameters of this cluster are the lowest among the three groups.

PCA scatter diagram (Fig. 7) showed that K, Mg, Ca, Cl, HCO₃, SO₄, Mn, Sr, EC, and TDS were the most effective in samples 8 and 16. Na, NH₄, Zn, Fe, NO₃, CO₃, Ba, N, and P were the most effective in samples 11 and 15. pH was effective on samples 9, 12, 13, and 14. Si and As were the most effective elements in samples 1, 2, 3, 4, 5, 6, 7, and 10.

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig7_HTML.png — Fig. 7
PCA scatter diagram showing the relationships between samples and the water physicochemical characteristics

4.3 Drinking Water Quality

Drinking water quality index (WQI) of the collected samples (Fig. 8) shows that good water is represented in some localities in the eastern side of the area. Those samples include 5, 6, 7, 10, 12, 13, and 14 (villages Shabsheer Elhessa, Shenta Ayaash, Bolqina, Kotama, Nahttai, Mit Badr Halawa, and Mit Habib, respectively). On the other hand, samples 1, 2, 3, and 4 (villages Shubra El-Namla, Abiar, Nawag, and Damatt, respectively) are of poor groundwater quality and located in the central part of the study area. Water quality decreases toward northern villages where very poor water quality occurs in Saa Elhagr (sample 9), Damro (sample 15), as well as Shobra Qaas village (sample 11) in the southwest. In villages of Pirma and Dokhmees, groundwater samples (8 and 16, respectively) are of unfit character for drinking.

../images/437178_1_En_111_Chapter/437178_1_En_111_Fig8_HTML.png — Fig. 8
Spatial distribution map of drinking water quality index (WQI)

5 Discussion

Egyptians living in the villages directly use groundwater for various purposes. Nile Delta villages have no or badly constructed sewage networks. Therefore, groundwater under these villages might receive pollutants. Physicochemical parameters of 16 groundwater samples (one sample for one village) were measured to evaluate this problem. The quality of the sampled groundwater varied greatly from one village to another. Using cluster analysis, the collected samples were classified into three groups. Cluster A includes sample 16 which is dominated by higher concentrations of TDS, EC, potassium, magnesium, sodium, calcium, sulfate, chloride, bicarbonate, Mn, Zn, P, NH₄, Ba, and unfit WQI values. Bad water quality of this group might be related to the effect of El-Gharbia main drain and seawater intrusion.

Cluster B includes samples 4, 8, 11, and 15. This group had the moderately mean ion concentrations among the three clusters, and it had higher ion concentrations of Fe, Sr, and Si than the other two clusters and dominated major ion concentrations arranged as follows: sodium > calcium and chloride > bicarbonate. They also had relatively high concentrations of potassium, magnesium, and sulfate. WQI of this group varies from poor characters in Damatt (4), very poor in Shobra Qaas village (11) and Damro (15), to unfit in Pirma (8). Groundwater of this group might receive a seepage from the domestic wastes.

Samples of cluster C (1–3, 5–7, 9, 10, and 12–14) were dominated by Ca > Na > Mg and HCO₃ > Cl ion concentration arrangement (Table 4). The average concentrations of the physicochemical parameters of this cluster are the lowest among the three groups. WQI of these samples varies from good as in samples 5, 6, 7, 10, 12, 13, and 14, poor (1–3, and) to very poor (sample 9). A wide range of WQI in this group is assumed to be related to the slight seepage from domestic wastes which increase the values of minor elements like NH₄ but did not affect the major ion concentrations.

The presence of undesirable concentrations of arsenic and ammonia in most of the samples is related to the direct seepage from the domestic wastes such that of the drains and septic tanks. Higher concentrations of arsenic and ammonia sometimes accompanied with higher TDS and major element concentrations due to the higher leakage from septic tanks under the village like that of Pirma (sample 8) and both the effect of seepage from the main drains and seawater intrusion as in sample 16 (village of Dokhmees).

6 Conclusions

Groundwater was sampled from 16 villages during 2016. Spatial distribution of the elements’ concentrations according to WHO guidelines, WQI (drinking water quality index), and statistical analysis was used to evaluate the groundwater pollution under Central Nile Delta villages. The studied groundwater was affected by the seepage from the septic tanks and/or drains in most of the villages. The groundwater affected by drains showed high TDS, EC, potassium, magnesium, sodium, calcium, sulfate, chloride, bicarbonate, Mn, Zn, P, NH₄, Ba, and unfit WQI values. Samples directly affected by seepage from the septic tanks had moderately mean ion concentrations and higher concentrations of Fe, Sr, and Si. It also had WQI values range from poor, very poor to unfit. Other samples were affected by neither drains nor septic tanks and had the lowest TDS concentrations and good WQI. Arsenic and ammonia undesirable concentrations in most of the collected groundwater samples are indications of direct infiltration from septic tanks and/or seepage from the drains. These two chemicals are of severe hazardous effect on the human health.

7 Recommendations

Sewage networks should be constructed in the Egyptian villages to prevent the groundwater contamination due to the use of septic tanks. The state and civil society organizations should inform the residents of the villages of the need to analyze the groundwater of their wells and consult the concerned authorities to determine the validity of this water for different uses. Also, they should be aware of the health hazards resulting from the use of contaminated water. The state should also extend the villages with clean water networks so that the need for underground water is reduced. Detailed hydrochemical and the microbial survey should be done to evaluate the groundwater contamination under the Egyptian village.

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