Hydrochemical characterization of groundwater under agricultural

Arab J Geosci86:9 )6102( DOI 10.1007/s12517-015-2136-5

ORIGINAL PAPER

Hydrochemical characterization of groundwater under agricultural land in arid environment: a case study of Al-Kharj, Saudi Arabia Abdulrasoul M. Al-Omran 1 & Anwar A. Aly 1,2 & Mohammad I. Al-Wabel 1 & Abdulazeam S. Sallam 1 & Mohammad S. Al-Shayaa 3

Received: 1 February 2015 / Accepted: 18 September 2015 # Saudi Society for Geosciences 2015

Abstract This study focuses on chemical analysis of 180 different groundwater samples in Al-Kharj governorate, Saudi Arabia. The distribution of chemical constituents (major, minor, and trace elements) is determined and compared with drinking and irrigation water standards. The water quality index (WQI) is applied to investigate groundwaters suitability for drinking. The obtained results indicated that the concentrations of dissolved salts, soluble cations and anions, and nitrate, were above permissible limits set by drinking water standards, WHO, for most wells. The WQI concluded that 65.2 % of studied wells are considered poor water Bclass (III)^, 24.9 % are very poor water Bclass (IV)^, 6.1 % are unsuitable water for drinking Bclass (V)^, and only 3.9 % are good water for drinking or Bclass (II). Most groundwater is contaminated with nitrate with an average concentration of 14.7 mg L−1. The water evaluation for irrigation poses that 69.4 % of studied wells are classified as moderately saline; however, the remaining are classified as severe saline water. The US Salinity Laboratory’s diagram reveals that majority of studied waters fall in class C4–S1, the area of very high salinity and low sodium hazards. Durov and Piper diagrams revealed that the majority of investigated waters

* Abdulrasoul M. Al-Omran [email protected] * Anwar A. Aly [email protected] 1

Soil Science Department, College of Food & Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia

2

Soil and Water Science Department, Faculty of Agriculture, Alexandria University, Alexandria, Egypt

3

Agricultural Extension and Rural Community Department, College of Food & Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia

are magnesium-calcium/sulfate–chloride water type. The Gibbs’s diagram revealed that the chemical weathering of rock-forming minerals and evaporation are influencing the groundwater quality. The hydrochemical modeling indicates that all water samples are undersaturated for halite and saturated for anhydrite and gypsum. The approach of this research could be applicable to similar situations worldwide. Keywords Al Kharj . Groundwater quality . Waters types . AquaChem software

Introduction The Kingdom of Saudi Arabia (KSA), like other countries located in arid regions, suffers from water scarcity and limited renewable water resources (Al-Omran et al. 2012). The KSA depends mainly on groundwater and seawater desalination to cover its need for drinking and irrigation as KSA does not have rivers or freshwater lakes. Al-Kharj governorate, lies in a broad low area (wadi) in the center of the KSA, depends on groundwater as a main source of drinking and irrigation. The Al Kharj is considered the most important agricultural area in KSA for historical, demographical, and economical reasons, and has the highest potential for agricultural development. The recent years have witnessed great focus directed towards expanding agricultural projects based on developing groundwater resources. This stress on groundwater is the main cause of its deterioration (Al-Omran et al. 2013). A good understanding of hydrochemical processes that govern groundwater quality is required for the sustainable management of the groundwater resources (Ledesma-Ruiz et al. 2014; El-Sayed et al. 2012). The chemical composition of groundwater is determined by cation exchanges with the surrounding geological layers, dissolution and precipitation of minerals, evaporation and oxidation-reduction reactions. Understanding these complicated

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hydrogeochemical processes will help to get an insight in the contribution of rock-water interactions that influence groundwater quality. Moreover, these geochemical processes are responsible for the spatial and temporal variations of the groundwater’s chemistry (Matthess 1982; Kumar et al. 2006). Varsányi et al. (2014) say that the analytical data and chemical considerations, together with geology, pressure conditions, and evolution history of the area, explain the evolution of the subsurface water. The spatiotemporal monitoring and assessment of groundwater used for drinking and irrigation is essential for sustainable safe use of water. The water quality index (WQI) is one of the most effective tools to assess the quality of water and can be used by policymakers and to reassure concerned citizens (Lateef 2011). The purpose of the WQI is to provide a simple and concise method for assessing the water quality for drinking usage. The WQI expresses the quality of water by integrating the water quality variables into one single number (Stambuck-Giljanovic 1999; Stigter et al. 2006; Saeedi et al. 2010). The traditional approaches for assessing water quality are based on the comparison of experimentally determined parameters with the local or international standards. Although, these approaches allow a proper identification of contamination sources and may be essential for checking legal compliance, they don’t readily give a global vision of the

Fig 1 Location of the study area

Arab J Geosci86:9 )6102(

spatial and temporal trends in the overall water quality (Debels et al. 2005). Numerous studies have proposed the use of a WQI (Horton 1965; Ott 1978; Miller et al. 1986; Bordalo et al. 2001; Cude 2001; Hallock 2002; Saeedi et al. 2010; Lateef 2011), and different methods for the calculation of the WQI have been developed, considering similar physical and chemical parameters but differing in the way the parameter values are statistically integrated and interpreted (Zagatto et al. 1998; Magesh and Chandrasekar 2013; Magesh et al. 2013). Backman et al. (1998) presented an index for evaluating the degree of groundwater contamination in southwestern Finland and central Slovakia. On the other hand, Soltan (1999) used the WQI to indicate the groundwater quality in Dakhla oasis, Egypt; furthermore, Saeedi et al. (2010) used the WQI of groundwater to identify places with the best quality of drinking water in central-west Iran. KetataRokbani et al. (2011) used the WQI and geographical information system to assess groundwater quality in the deep aquifer of El Khairat in Tunisia and Al-hadithi (2012) applied the WQI to assess suitability of groundwater for drinking water purposes in the Ratmao–Pathri Rao catchment in India. Meanwhile, in Saudi Arabia, Aly et al. (2014) used the WQI and hydro-chemical modeling to evaluate the groundwater quality of Hafer Abatein for drinking and irrigation purposes.


The main objectives of this study are to evaluate the groundwater resources of Al-Kharj for drinking and irrigation purposes and to classify the hydrochemical characterization of groundwater resources in the study area.

Material and methods Study area Al-Kharj is a productive agro-ecosystem set in a desert depression and is irrigated by waters from natural springs and dug

Fig 2 Geological map of Saudi Arabia showing study area

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wells. The region produces date palms, other fruits (e.g., grapes), and vegetables (e.g., lettuce, carrots, tomatoes, cucumbers, and melons) (Fig. 1). Al-Kharj is a fragile dryland agro-ecosystem that has a low degree of resilience to external stresses and a low carrying capacity, i.e., a limited potential for the expansion of economic activities and population. The AlKharj governorate, located at 24°8′54″N, 47°18′18″E, lies in a broad low area (wadi) in the center of the Kingdom of Saudi Arabia, 80 km from Riyadh, the capital of the kingdom. The term BAl-Kharj^ refers to a number of small towns. The two largest towns are Dilam and Asseeh, and the smaller towns in the region include Al-Hayathim, Yamamah, and Sulamiyya.

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In addition to these towns, the area has many smaller hamlets and villages. The climate of Al-Kharj is characterized by hot and dry summers with daytime temperatures range between 45 and 48 °C; on the other hand, the winter daytime temperatures range between 20 and 25 °C; in contrast, the winter nights are cold with average temperature of −2 and 5 °C. The average precipitation during winter is 51 mm; however, no rainfall in summer is recorded (CDSI 2011; Al-Omran et al. 2013).

Table 2 The WHO standard for drinking purpose (WHO 2011)

Table 1 Relative weight for parameters (Ramakrishnalah et al. 2009; Aly et al. 2014) Chemical parameters

Weights (wi)

Relative weight (Wi)

pH TDS (mg L−1) Calcium (mg L−1) Magnesium (mg L−1) Sodium (mg L−1) Potassium (mg L−1) Bicarbonate (mg L−1) Chloride (mg L−1) Sulfate (mg L−1) Nitrate (mg L−1) Boron (mg L−1) Total

3 4 2 2 2 2 2 3 3 5 3 31

0.097 0.129 0.065 0.065 0.065 0.065 0.065 0.097 0.097 0.161 0.097 1.00

WHO Standards

pH TDS (mg L−1) Calcium (mg L−1) Magnesium (mg L−1) Sodium (mg L−1)

6.5–8.5 600 753 503 200

Potassium (mg L−1)

12 120 250 250 10 0.5

−1

Bicarbonate (mg L ) Chloride (mg L−1) Sulfate (mg L−1) Nitrate (mg L−1) Boron (mg L−1)

Geology Al-Kharj is located on the sedimentary basin of Saudi Arabia (Fig. 2). The foundation for sedimentary deposition is the Arabian Shield, which is a vast Precambrian complex of igneous and metamorphic rocks. The sedimentary layers crop out in a great curved belt bordering the rigid shield part (Fig. 2). The Al-Kharj is located at the apex of the curved belt and covers about 1800 km 2. The Al-Kharj aquifers from the recent deposition age to older are Wasia, Biyadh, Sulaiy, and Arab. Yamama formation is not considered to be aquifer in Al-Kharj, since it has a relatively impermeable character. Likewise, the nature of the Buwaib formation provides the impermeable substratum to the Biyadh aquifer east of Al-Kharj. However, the Hith is unseen exposed except in the pits. The Wasia and Biyadh are clastic productive aquifers; on the other hand, the Sulaiy and Arab are non-clastic aquifers. The Sulaiy formation has undergone considerable underground solution to form a Karst topography over some parts of AlKharj area. Furthermore, Arab formation is characterized by joints, fractured, and solution openings up to 1 m in diameter (Said and Bazuhair 1989).

Parameters

3

WHO 2004

Hydrogeology The territory of eastern KSA contains aquifers of good water quality with wide variations in the geological setting (Vincent 2008). The main aquifers can be classified into two broad groups based on their primary and secondary origin. The Primary origin aquifers include the quaternary sands of the wadi systems which are quartzose sandstones and conglomerates with primary porosity, and calcarenites, coquinites, and oolitic limestone with secondary porosity (Alsharhan et al. 2001; Vincent 2008). In Al-Kharj, the floods of many wadis (valleys), such as Wadi Hanifa, discharge water into Wadi AlKharj. The Al-Kharj ecosystem contains several springs, called oyun or asiah, and is considered to be one of the richest locations in the kingdom with respect to water resources; since ancient times, the area has supported the kingdom with grain, dairy products, and other crops. Recently, the springs of AlKharj have dried up dramatically, like those in other places of the kingdom. The shortage and deterioration of the water and land resources is a serious impediment to the sustainable agricultural development of Al-Kharj, for without proper drainage, salt has been accumulating in the soil. The groundwater level in the aquifer has been declining in an alarming way as more deep wells are drilled into the aquifer, with the result of

Table 3 Water quality classification based on WQI value (Ramakrishnalah et al. 2009; Ketata-Rokbani 2011; Aly et al. 2014) Classification of Drinking Water quality WQI Range 300

Class I II III IV V

Type of water Excellent water Good water Poor water Very poor water Water unsuitable for drinking

Arab J Geosci86:9 )6102( Table 4

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Descriptive statistics of Al-Kharj groundwater chemical composition (n=180) PH

EC dS m−1

Mg2+ Ca2+ −1 meq L

Na+

K+

Cl−

HCO3−

CO3−2

SO4−2

SAR

KR

B NO3− −1 mg L

Max.

8.60

10.15

36.75

29.85

43.40

0.72

58.17

18.83

4.33

43.19

9.14

2.27

3.06

111.50

Mini. Mean

6.78 7.72

1.05 3.00

3.45 10.79

0.79 7.78

2.24 11.28

0.05 0.25

3.13 10.86

0.87 3.99

0.00 0.13

3.22 15.03

1.08 3.74

0.18 0.65

0.02 0.63

0.00 14.67

Stdev

0.44

1.29

5.09

3.93

5.96

0.10

7.32

1.49

0.37

7.05

1.47

0.30

0.43

21.22

Vari. St. error

0.66 0.18

1.13 0.23

2.26 0.33

1.98 0.31

2.44 0.34

0.31 0.12

2.71 0.36

1.22 0.24

0.61 0.17

2.66 0.36

1.21 0.24

0.55 0.16

0.66 0.18

4.61 0.47

Med.

7.72

2.64

9.60

6.69

10.21

0.23

9.50

3.83

0.00

12.83

3.51

0.58

0.60

2.05

Skew

−0.15

2.47

1.39

2.16

2.53

1.66

3.85

5.96

8.20

1.18

1.12

1.90

1.84

2.08

serious degradation and salinization of the adjacent agricultural lands (Alsharhan et al. 2001; Vincent 2008).

Chemical analysis In this study, groundwater samples were collected from 180 different locations in the Al-Kharj region of the KSA, in an attempt to capture the spatial variations in groundwater quality in the study area (Fig. 1). All samples were stored in the dark at room temperature. The samples were analyzed for EC, pH, Ca2+, Mg2+, Na+, K+, HCO3−, Cl−, SO42−, NO3−, and B. The EC was measured by using an EC meter in units of dS×m−1 at 25 °C (Test kit Model 1500_20 Cole and Parmer). The water reaction (pH) was determined using a pH meter (pH meter— CG 817). The soluble Ca2+ and Mg2+ were determined by versenate titration method (EDTA); however, the soluble Na+ and K+ concentrations were determined using flame photometer (Corning 400). The HCO3− concentration was determined by titration with sulfuric acid (H2SO4), whereas the Cl− concentration was determined by titration with silver nitrate (AgNO3). The sulfate (SO4−2) concentration was determined by the turbidity method (Tabatabai 1996), and the nitrate

Fig 3 Values of WQI of studied samples

(NO3−) concentration was determined by the phenoldisulfonic acid method (APHA 1998). The B was determined using azomethine-H method (Bingham 1982). Ion balance errors The correctness of the chemical analysis was verified by calculating ion balance errors; furthermore, standard solutions and blanks were commonly run to check for possible errors in the analytical procedures. The level of error in the data was calculated using the following formula (Appelo and Postma 1996): X X cations− anions Error of ion balance ¼ X *100 ð1Þ X cations þ anions An error of up to ±3 % is tolerable, while every water sample with a calculated error outside this range should be measured again. Approximately, 95 % of the measured water samples were within this range. This means that the resultant data quality is sufficient for chemical modeling and/or for drawing simple conclusions about water quality.

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Page 6 of 17 Fig 4 Schoeller diagram indicating ionic concentrations of groundwater in the study area



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WQI computing The WQI calculations include three successive steps (Horton 1965; Yidana and Yidana 2010; Ketata-Rokbani et al. 2011; Lateef 2011; Al-hadithi 2012). The first step is Bassigning weight^ Each of the 11 parameters has been assigned a weight (wi) according to its relative importance in the overall quality of drinking water as shown in Table 1. The most significant parameters have a weight of 5 and the least significant have a weight of 1. In this study, the maximum weight of 5 has been assigned to nitrate, due to its major importance in water quality assessment (Ramakrishnalah et al. 2009), the less harmful parameters i.e., calcium, magnesium, and sodium have been given a weight of 2. The second step is the Brelative weight calculation^ The relative weight (Wi) is computed from the following equation: wi Wi ¼ X n

ð2Þ

wi i¼1

where Wi is the relative weight, wi is the weight of each parameter, and n is the number of parameters. The calculated relative weight (Wi) values of each parameter are given in Table 1. Fig 5 Salinity classification of groundwater used irrigation

The third step is Bquality rating scale calculation^ The quality rating scale (qi) for each parameter is calculated by dividing the parameter concentration in each water sample by its respective standard (WHO 2011) (Table 2) multiplied by 100: qi ¼

Ci 100 Si

ð3Þ

where qi is the quality rating, Ci is the concentration of each chemical parameter in each water sample in mg L−1, except pH, and Si is the WHO (2011) standard for each chemical parameter. Finally, the Wi and qi are used to calculate the SIi for each chemical parameter, and then the WQI is calculated from the following equation: SIi ¼ W i qi Xn SIi W QI ¼ i¼1

ð4Þ ð5Þ

where SIi is the sub index of each parameter, qi is the rating based on concentration of each parameter, and n is the number of parameters. The computed WQI values are classified into five categories, as shown in Table 3. Hydrochemical characteristics The hydrochemical characterization of the groundwater samples was evaluated by means of major ions, Ca2+, Mg2+, Na+,

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K+, HCO3−, Cl−, and SO42. The chemical analysis data of the water samples were plotted on the Piper, Schoeller, and Durov diagrams using Geochemistry Software AquaChem 2014.2 for the identification of water types. The Gibbs (Gibbs 1970) and US salinity laboratory (Richards 1954) diagrams were also adopted in this study. In addition, salinity hazard, sodium adsorption ratio (SAR), and Kelly’s ratio (KR) were calculated to investigate the groundwater suitability for irrigation.

where IAP is the ion activity product of the dissociated chemical species in solution and kt is the equilibrium solubility product of the chemical involved (Alexakis 2011). The hydro-geochemical equilibrium model, Phreeqc model (Parkhurst and Appelo 1999), was used to calculate the SI of the groundwater with respect to the main mineral phases.

Geochemical modeling

GIS analysis

Interactions between water and the surrounding rocks and soil are considered to be the main processes controlling the observed chemical characteristics of the water. The deviation of water from equilibrium with respect to dissolved minerals is quantitatively described by the saturation index (SI). The SI of a mineral is obtained from the following formula:

Georeferenced location of the studied area

SI ¼ logIAP=k t

Fig 6 Piper—tri-linear diagram

ð6Þ

The coordinates of the studied observation wells were obtained using a real-time differential GPS, which uses a radio signal to correct the GPS signal in real time and provides an accuracy of approximately 5 m. The GPS was used to locate the observation wells, using either the geographic latitude or the UTM northing/easting coordinate system.


GIS data input The locations of the different attributes were formatted as a comma-delimited text file (in the form of well number, easting, and northing). Arc GIS 9.3 software (ESRI 2010) was used to overlay the point data on a satellite image.

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and maximum for most parameters in the groundwater exceeded the acceptable limits of the standard used; however, with exception of boron, the minima of the parameters were within the acceptable limits (Table 4) (Al-Omran et al. 2012; Aly et al. 2013). The main reason of high nitrate concentrations in all waters is the over application of fertilizer on surrounding agricultural land (Al-hadithi 2012; Aly et al. 2014).

Statistical analysis Statistical analysis was carried out using the statistical package for social sciences (IBM SPSS Statistics 21 Core System, IBM Corporation 2012). The statistical tests applied were basic statistics (maximum, minimum, mean, standard deviation, variance, standard error, median, skewness) and Spearman’s correlation matrix (assuming pMg2+ >Ca2+ and the anions order is Cl− >SO42− >HCO3− (Fig. 4). (iii) pH, the pH is a term used universally to express the intensity of the acid or alkaline condition of a water. Table 4 concluded that the pH values of the water samples ranged between 6.78 and 8.60 with a mean value of 7.72. The maximum permissible limit of pH in irrigation water is ranged between 6.5 and 8.4 (Ayers and Westcot 1985). These mean that 99.5 % of studied water samples were within safe limit with respect to pH since only one sample has pH=8.6 (Ayers and Westcot 1985). (iv) Salinity hazard, electrical conductivity (EC) is a measure of water capacity to convey electric current. It represents the amount of total dissolved salts (TDS). Therefore, in the present study, the salinity hazard was evaluated by EC which varies from 1.05 to 10.15 dSm−1 with an average value of 3.45 dSm−1. Based on

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the classification of EC suggested by Ayers and Westcot (1985), 69.4 % of studied wells are classified as slight to moderate water salinity whereas the remaining wells can be classified severe water salinity. (v) Sodium hazard, the excessive sodium content in water sample reduces the permeability, and hence, the available water for the plant is reduced. Sodium replacing adsorbed calcium and magnesium is a hazard, as it causes damage to the soil structure resulting in compact and impervious soil (Arveti et al. 2011). Excess absorption of sodium can cause sodium toxicity in sensitive plants, causing marginal leaf burn on older foliage and possibly defoliation and water containing excessive amount of sodium may immobilize other nutrient ions particularly calcium, magnesium, and potassium, which can result in deficiencies of these elements in plants (Sharifi and Safari Sinegani 2012). One of the most important criteria in determining sodium hazard is sodium adsorption ratio (SAR) (Todd and Mays 2005). The sodium adsorption ratio is computed as: Na SAR ¼ rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Ca þ Mg 2

Fig 11 Interpolation of groundwater EC using GIS

ð7Þ

where the ionic concentration is in meq L−1. The SAR values of the groundwater samples varied from 1.08 to 9.14 with an average value of 3.74 (Table 4). All SAR values of the water samples were less than 10 and are classified as excellent for irrigation (Richards 1954). Kelly (1940) has also determined the hazardous effect of sodium on water quality for irrigation usage in terms of Kelly’s ratio (KR). The Kelly’s ratio is computed as: KR ¼

Na Ca þ Mg

ð8Þ

where the ionic concentrations are in meql−1. A Kelly’s ratio of more than one indicates excessive sodium in water. Therefore, water with a Kelly’s ratio less than one is considered suitable for irrigation; on the other hand, the ratios more than one are unsuitable. The Kelly’s ratios in studied waters were ranged between 0.2 and 2.3 with an average value of 0.7 (Table 4). About 93.3 % of the studied waters were considered suitable for irrigation since Kelly’s ratio less than one. (vi) Boron toxicity, the boron concentrations were within permissible limits in 65.6 % of water samples, and the


remaining samples were considered to have slight to moderate boron toxicity (Ayers and Westcot 1985). Salinity and alkalinity hazard class In this study, the US Salinity Laboratory’s diagram (Richards 1954) is used for irrigation water quality evaluation (Fig. 5). The salinity and alkalinity hazard class of studied water samples were C3–S1, C4–S1, and C4–S2. The result shows that the groundwaters possess high to very high salinity hazards with low to medium sodium hazards (Fig. 5). The excessive amount of salts can be one of the major problems in water used for irrigation in the study area. The waters cannot be used for irrigation of most crops without special circumstances for salinity control such as leaching requirement or cropping of salt-tolerant plants (Laüchli and Epstein 1990). Hydrochemical aspects The chemical analysis data of the groundwater samples are plotted on a Piper trilinear (Piper 1944) and Schoeller (1955) diagrams (Figs. 6 and 4). The piper diagrams provide a convenient method to classify water types collected from different

Fig 12 Interpolation of groundwater B using GIS

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groundwater resources, based on the ionic composition of different water samples (Al-Omran et al. 2012; Semerjian 2011; Baba et al. 2008). The main water types have been identified on the basis of the major ion concentrations as in Aly and Benaabidate (2010), and Aly et al. (2013). The piper diagram reveals that the water types of Al-Kharj groundwater is rich in calcium- magnesium/sulfate–chloride. In the Schoeller diagram (Fig. 4), it may be seen that there is a predominance of sodium and magnesium/calcium which influences the tendencies towards the chloride/sulfate–sodium/magnesium and calcium facies. The major cation and anion concentrations of the samples collected from groundwater in the region are plotted on a Durov diagram (Fig. 7). Durov’s diagram helps the interpretation of the evolutionary trends and the hydrochemical processes occurring in the groundwater system and can indicate mixing of different water types, ion exchanges, and reverse ion exchange processes. The result shows that majority of the samples fall in fields 4 and 5, the zones of high-water salinity. The samples belonging to field 4 suggest presence of SO4−2 and Ca2+ as dominant type of water, and indicating gypsumbearing sedimentary aquifer and the groundwater affected by oxidation of pyrite and other sulfide minerals. However,

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samples located in field 5 of Durov’s diagram indicate mixing processes of two or more different facies might be occurring; this finding is similar to those found by Aly et al. (2014). Gibbs’s diagrams, representing the ratios of Na++ K+: (Na++ Ca2++ Mg2+) and Cl−: (Cl−)+HCO3−) as a function of TDS, are widely employed to assess the functional sources of dissolved chemical constituents, such as precipitation-dominance, rock-dominance, and evaporation-dominance (Gibbs 1970). The chemical analysis data of groundwater sample points of the studied area are plotted in Gibbs’s diagrams (Fig. 8). The distribution of sample points suggests that the chemical weathering of rock-forming minerals and evaporation are influencing the groundwater quality. Evaporation increases salinity by increasing Na+ and Cl− with relative enhancement of TDS. The rock domain suggests that rock–water interaction is the major source of dissolved ions over the control of groundwater chemistry. The rock–water interaction process includes the chemical weathering of rocks, dissolution–precipitation of secondary carbonates, and ion exchange between water and clay minerals. The evaporation greatly increases the concentrations of ions formed by chemical weathering, leading to higher salinity. The moving of

Fig 13 Interpolation of groundwater NO3 using GIS


groundwater sampling points in the Gibbs field towards the evaporation domain from the rock domain suggests an increase of Na+ and Cl− ions and consequent higher TDS due to water contamination, caused by the influences of poor sanitary conditions, agricultural fertilizers, and irrigation-return flows (Subba Rao 2006; Kumar et al. 2014). Geochemical modeling The saturation index (SI) is the parameter most commonly used for groundwater. Water is in equilibrium with a mineral when the SI of this mineral is equal to zero. It is under-saturated if this index is below zero and it is over-saturated when the SI is above zero. However, in order to allow for measurement inaccuracies and changes in the water composition as it makes its way towards the surface, it is recommended to consider a wider area for SI, such as −1