Arab J Geosci (2017) 10:231 DOI 10.1007/s12517-017-2981-5

ORIGINAL PAPER

Groundwater chemical and fecal contamination assessment of the Jerba unconfined aquifer, southeast of Tunisia Faiza Souid 1 & Belgacem Agoubi 1 & Mohamed Hamdi 1 & Faten Telahigue 1 & Adel Kharroubi 1

Received: 1 October 2015 / Accepted: 3 April 2017 # Saudi Society for Geosciences 2017

Abstract Located in the southeast of Tunisia, on the Mediterranean Sea, Jerba Island has a semiarid climate condition. The surface water scarcity has made groundwater the main source to supply the domestic, touristic, and agricultural water demand. Unconfined aquifer is a vulnerable costal aquifer system that undergoes several phenomena. This work aims at assessing the geochemical and bacteriological groundwater quality, defining groundwater pollution sources and promoting sustainable development and effective management of groundwater resources in Jerba Island. Data were collected after the wet season in 2014 from 79 wells. Electric conductivity, pH, TDS, and major and fecal tracers (total coliforms, thermotolerant coliforms, Escherichia coli, and Salmonella) were analyzed. Geochemical modeling including the relationships between geochemical tracers Na+ vs. Cl−, Ca2+ vs. Cl−, K+ vs. Cl−, representative ionic ratios (Br−/Cl−, Na+/Cl−, Mg2+/ Ca2+), and statistical analysis were used to specify major process contributing to groundwater pollution and main factors controlling groundwater mineralization in the island. * Faiza Souid [email protected] Belgacem Agoubi [email protected] Mohamed Hamdi [email protected] Faten Telahigue [email protected] Adel Kharroubi [email protected] 1

RU: Applied Hydrosciences Research Unit, Higher Institute of Water Sciences and Techniques, University of Gabès, Campus Universitaire, 6072 Gabès, Tunisia

Groundwater varieties were hydrochemically classified into three types in terms of salinity values: group 1 (8.86%) to fresh water, group 2 (27.84%) to brackish water, and group 3 (63.29%) belongs to saline water. In addition, groundwater quality revealed high concentrations in chemical pollution tracers (Na +, Cl−, SO42−, and NO 3− ) and fecal tracers. Besides, most of the sampled wells were contaminated with nitrate (50.63%). Also, thermotolerant coliforms and E. coli were detected in all groundwater samples (96.2% of wells). Results indicated that the Jerba shallow aquifer was under serious threat from both natural and anthropogenic contamination. However, the wild discharge of domestic effluents, septic tanks, and sewage were the main origins of underground water contamination in Jerba Island. The reduction of fecal sources, through constructing normalized latrines is thus recommended. Keywords Unconfined aquifer . Chemical pollution . Bacteriological contamination . Seawater intrusion . Jerba Island . Tunisia

Introduction Groundwater can be polluted with viruses, bacteria, and other pollutants coming from several origins (Coleman et al. 2013). Identifying contamination refers to a combination of several approaches like geochemical, isotopic, bacteriological, and statistical methods (Marjoua et al. 1997; Fakir et al. 2001; El Moujabber et al. 2006; Ben Hamouda et al. 2009; Kouzana et al. 2009; Mondal et al. 2010; Malana and Khosa 2011; Belghiti et al. 2013; Yu et al. 2013; Kim et al. 2014; Kumar 2014). Groundwater quality deterioration and aquifer vulnerability due to anthropogenic activities can be studied using the DRASTIC model coupled to Geophysical Information System (Smida et al. 2010; Ben Brahim et al. 2012).

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Contamination of groundwater due to seawater intrusion and anthropogenic activities can be demonstrated using geochemical, isotopic, and statistical methods based on correlation between several elements (Zammouri et al. 2007; Ben Hamouda et al. 2009; Kouzana et al. 2009; Kharroubi et al. 2012). Chemical tracers as well as conservative elements (chloride and bromide) were used to specify the origin of groundwater degradation (Andreasen and Fleck 1997; Fedrigoni et al. 2001). Nitrate and bacteriological indicators such as fecal gems are a proxy of anthropogenic inputs to the aquifer (Tandia et al. 1999; Sall and Vanclooster 2009; Bonton et al. 2010; Degbey et al. 2011; Huang et al. 2013; Youmbi et al. 2013). Poor water resources management, anthropogenic activities, and the inexistence of a catchment protection policy lead to bacteriological contamination of groundwater. The main origin of bacteria is human sewage and animal dejection (Servais and Passerat 2009). Microbiological contamination, due to ingestion of polluted water, is considered the first cause of waterborne disease (Villanueva et al. 2014). The bacteriological groundwater contamination can be assessed through indicators such as Escherichia coli, enterococci, and aerobic bacteria. E. coli and enterococci are usually linked to fecal contamination (Schaffter and Parriaux 2002). Their presence in groundwater is assumed to be related to input of contaminants in the aquifer. The factors leading to groundwater contamination are frequently associated to pollution by on-site sanitation facilities, such as pit latrines and private septic systems, which represent an obvious origin of fecal contamination (Howard et al. 2003). In Jerba Island, located in southeastern Tunisia, on the Mediterranean Sea, the quaternary aquifer is the most important resource for the predominantly rural populations. Groundwater is used for drinking, domestic purpose, and mainly for irrigation. Population growth, agriculture development, and a semiarid climate result in overexploitation of the groundwater resources in this region. In 2005, more than 3000 wells were inventoried (Kharroubi et al. 2012). High pumping rate has led to a water table decline which favored seawater intrusion. In addition, the great number of undeveloped septic tanks is a potential source of groundwater contamination. Kharroubi et al. (2012) studied the geochemistry of this coastal aquifer using geochemical and statistical methods and reported that high mineralization was due to gypsum and carbonate dissolution coupled with the seawater intrusion in many areas of the island. This study aims to assess hydrogeochemical and bacteriological groundwater quality and understand the factors controlling groundwater contamination of Jerba unconfined aquifer, based on the geochemical modeling in conjunction with statistical data analyses.

Materials and methods Study area The study area is located in the southeast of Tunisia and covers about 510 km2. It is a semiarid island with annual precipitation of 220 mm and mean annual temperature of 20 °C (Yahyaoui 2012). The rainfall is torrential, causing, due to the soil quality, more streaming and very low infiltration (Kharroubi et al. 2012). Jerba is a flat zone with a maximum altitude of 54 m in the Southern part of the island. Geological and hydrogeological frameworks The geological settings of study area are shown in Fig. 1. The site belongs to the Mio-Pliocene and Quaternary sediments (Fig. 2). The upper layers consist of Quaternary dunes located principally in the northeast of the island and Holocene bioclastic sands covering the main northern coast and another area in the South. The middle layer is made of Holocene oolitic limestone found near the sea and covering a restricted area. The bedrock consists of red alluvium attributed to Pleistocene and Holocene. Faults system strike NW–SE affects the island (Jedoui 2000; Bouaziz et al. 2003). Jerba’s unconfined aquifer mainly consists of sandy levels of the Mio-Pliocene intercalated with clay lenses as well as in marine limestone of the Tyrrhenian formation (Jedoui 2000). It is a multi-layered aquifer system with several compartments (Yahyaoui 2012). The total thickness of this aquifer is around 50 m (Smaoui et al. 1997). The bedrock aquifer is consist of clay and marl of Mio-Pliocene and Miocene (100 to 150 m thickness), which constitute the roof of the confined aquifer (Yahyaoui 2012). The unconfined aquifer of the island has a static level between 2 and 40 m (Kharroubi et al. 2012). The specific capacity of the aquifer ranges between 0.32 and 3 l s−1 m−1, and the transmissivity is 10 −3 m 2 s −1 (Kharroubi et al. 2012). Groundwater is mainly recharged by vertical infiltration from precipitation and through fractures and agricultural irrigation flow. The piezometric fluctuations of Jerba aquifer are highly dependent on rainfall. The piezometric head of this aquifer varies on an average of 30 m (in the center and southeast of the island) to 10 m (near the cost). The heterogeneity of the aquifer lithology, excessive pumping, and the density of wells has resulted in a diffuse groundwater flow with no specific direction (Yahyaoui 2012). Groundwater samples Groundwater was sampled from 79 locations during the long rainy seasons of 2014 (25 Feb to 14 Apr 2014). Samples from traditional wells were collected with previously sterilized

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Fig. 1 Geological context of Jerba Island (Jedoui 2000) and geographical location of groundwater samples

buckets. As for wells equipped with pumps, samples were taken after pumping for 5 min. The tap and the bucket were cleaned before sampling, and caution was taken to avoid splashing. Prior to analysis, the samples were diluted to 1/ 10th and filtered with a cellulose filter with pores of 0.45 mm. Samples for bacteriological analysis were kept in 200 ml sterile glass bottles. For physical and chemical analyses, samples were stored in 500 ml polyethylene bottles. Once collected, all samples were stored on ice and immediately transported to the laboratory. The sampling points were selected based on the geographic location of wells and the use of the wells as sources of drinking water. Figure 1 shows the location of the selected wells. The depth of the sampled wells varied from 4 to 54 m.

Physicochemical analysis methods The pH, electrical conductivity (EC), salinity, and total dissolved solids (TDS) of water samples were measured in situ using the Consort 933 portable analyzer. Analyses for Na+, Fig. 2 Schematic stratigraphic cross-sections of Jerba Island (Khalili 1986)

Cl−, SO42−, Br−, K+, F−, NO3−, Mg2+, and Ca2+ were measured using ion chromatography method (Methrohm 850 Professional IC).

Bacteriological analysis methods The indicators of bacteriological contamination used in this study were total coliforms (TC), thermotolerant coliforms (Thc), E. coli, and Salmonella. TC and Thc were enumerated by the membrane filtration method (ISO 9308-1 2000), using sterile gridded cellulose filters of 0.45 mm nominal pore size. Incubation was carried out on Tergitol TTC Agar for 24 h at 37 °C for TC and at 44 °C for Thc. The total number of bacteria was determined as CFU 100 ml−1. E. coli was determined using transplanting TC colonies on tryptophan. Results were obtained after incubation at a temperature of 44 °C and observed after 24 h, with the addition of Kovac’s. Indole production was determined by adding a few drops of Kovac’s. A positive test referred to the development of a red color in the reagent layer.

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The identification of Salmonella was carried out over three stages: pre-enrichment, selective enrichment, and isolation.

Results and discussion Hydrochemical characteristics of groundwater The hydrochemical analyses (Table 1) indicated a wide range of water quality varying from fresh to saline water. In general, the salinity increased with respect to the groundwater flow direction. The salinity rates of wells water ranged between 0.3 and 7 g l−1 with the majority above 2.41 g l−1. Total dissolved solid (TDS) values were generally high to moderate (7.9–0.4 g l−1, with a mean of 2.91 g l−1). Among the physical parameters, pH ranged from 6.82 to 8.04 with an average of 7.46, indicating the alkaline nature. Electrical conductivity (EC) in the groundwater varied from 0.76 to 12.34 mS cm−1, with an average of 4.56 mS cm−1. According to the EC v a l u e s , g r o un d w at e r c a n b e c l a s s e d i n t o f r e s h (<1500 μS cm−1), brackish (1500–3000 μS cm−1) and saline (>3000 μS cm−1) (Park et al. 2012). Thus, the sampled wells were classified as follows: 7 wells supplied fresh water, 22 wells supplied brackish water, and all the rest saline water. The groundwater samples in Jerba Island are characterized by high concentration of Na/Cl. The concentration of sodium in the groundwater ranged from 3142.8 to 208.96 mg l−1 with an average of 1088.93 mg l−1. This result suggests that groundwater had an elevated level of sodium, concentration of Cl− also showed a wide range of 4748.72–125.37 mg l−1, with an average of 1715.81 mg l−1. Sulfate also showed an elevated concentration (49.29–1125.72 mg l−1, with a mean of 509.92 mg l−1). The Bromide values varied from 12.25 to 16.36 mg l−1. For Mg2+ and Ca2+, magnesium varied from 417.54 to 16.56 mg l−1 and calcium ranged from 796.29 to 61.16 mg l−1. Fluoride concentrations in the groundwater varied from 9.99 to 6.5 mg l−1 with an average of 9 mg l−1. The measured nitrate values of groundwater samples from the study area were relatively high (average = 68.26 mg l−1) in samples collected near the agriculture area, which indicated that the aquifers were generally contaminated by nitrate. The nitrate levels were extensively high (exceeding 50 mg l−1) for 40 samples. Bacteriological characteristics of groundwater According to the analytical data, 94.9% of wells presented TC densities higher than 10 CFU 100 ml−1. Thc and E. coli were detected in all groundwater sampled (96.2% of wells) except for three wells that were deeper than 50 m.

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Assessing the groundwater quality for drinking The chemical quality of groundwater samples in the study area goes beyond the WHO guideline and Tunisian Standard 09.14 (TS 09.14) (2013) values for parameters such as chloride, sodium, sulfate, nitrate, and fluoride. The fluoride content of all samples was within the maximum allowable limit as per the guideline prescribed by the WHO (2008) for drinking water. The WHO guideline prescribes that more than 1.7 mg l−1 of F− concentration water becomes unpalatable for drinking. Exposure to high concentrations of fluoride can lead to mottling of teeth and, in severe cases, crippling skeletal fluorosis (WHO 2008). However, because of the gastrointestinal effects resulting from ingestion of drinking water containing high sulfate levels (WHO 2008), it is recommended by TS 09.14 (2013) that sulfate concentrations should not exceed 600 mg l−1. Most samples (68.35%) were above the tolerance limit of SO 4 2− in drinking water specified by the TS 09.14 (2013). As regard to chloride parameters, the majority of samples presented high levels of chloride. In drinking water, the permissible limit stated by the TS 09.14 (2013) is equal to 600 mg l−1. The nitrate levels of 59.49% of samples exceeded the value set by TS 09.14 (2013) which is equal to 45 mg l−1. Extremely high concentration of nitrate was seen near the agricultural areas and wells located near septic tanks. In addition, nitrate may arise from the agricultural activities or from leaching of wastewater or other organic wastes into groundwater (WHO 2008). An excessive nitrate concentration in drinking water has been associated with methaemoglobinaemia (WHO 2008). The groundwater samples were characterized by high levels of alkaline earth element (calcium and magnesium), besides, 58.22% of wells had TH values exceeding the threshold values assigned by TS 09.14 (2013). Referring to the guideline prescribed by WHO (2008) for the assessment of bacteriological quality of drinking water, E. coli must not be detectable in any 100 ml sample. This germ provides conclusive evidence of recent fecal pollution (WHO 2008). Consequently, the presence of E. coli in the groundwater makes groundwater unfit for drinking. Geochemical modeling To better understand the groundwater mineralization process, bivariate diagrams of major ions were plotted. In coastal aquifer, the potential origin of Cl− and Na+ is the seawater intrusion, evaporites dissolution, and anthropogenic sources (Agoubi et al. 2012). Na+ vs. Cl− diagrams showed the variation of the concentrations of Cl− and Na+ of different water samples. In the diagram (Fig. 3a, b), almost all of the water wells were above the dilution line of seawater excluding some points that are beneath the dilution line of seawater. This finding is confirmed by the Br−/Cl− = f(Cl−) diagram (Fig. 3d) where almost all of the points were beyond the dilution line of the seawater. The important

Arab J Geosci (2017) 10:231 Table 1

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Geochemical analysis of 79 sampled wells

Wells Salinity TDS pH (g l−1) ID no. (g l−1)

EC Cl− −1 (mS cm ) (mg l−1)

Br− (mg l−1)

NO3− (mg l−1)

SO42− (mg l−1)

Na+ (mg l−1)

K+ Ca2+ −1 (mg l ) (mg l−1)

Mg2+ (mg l−1)

F− (mg l−1)

1 2 3 4

7 3.3 2.7 4.5

7.9 3.91 3.24 5.2

7.51 7.59 7.56 7.45

12.34 6.11 5.07 8.12

4748.72 2128.54 1920.69 3945.16

16.36 14.9 15.03 15.82

35.29 70.47 149.69 108.81

841.05 385.63 613.41 323.79

3142.8 1500.94 1237.9 2018.96

142.7 67.9 55.92 91.5

796.29 384.89 319 514.69

417.54 193.14 157.2 263.94

8.47 9.38 9.87 9.49

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

5 4.2 2.2 1.4 1.7 4.2 3.5 3.6 1.2 1.6 4 2.7 3.8 2.6 1.8 1.1 1.4 1.1

5.82 4.93 2.66 1.76 2.1 4.88 4.18 4.29 1.53 2.05 4.67 3.31 4.52 3.16 2.28 1.49 1.75 1.48

7.78 7.77 7.63 7.65 7.21 7.01 7.14 7.16 7.8 7.5 7.35 8.04 7.35 7.2 7.27 7.02 7.04 7.75

9.09 7.7 4.16 2.75 3.28 7.63 6.53 6.7 2.39 3.2 7.3 5.17 7.06 4.94 3.56 2.33 2.73 2.31

3824.48 2207.85 1796.12 1151.96 1249.58 3320.02 2066.85 2898.19 1010.83 1313.94 3102.13 1849.26 2455.82 1845.14 1483.24 842.35 837.73 867.09

15.57 15.67 14.11 13.47 14.09 15.47 15.23 15.04 13.58 13.46 14.87 13.85 15.85 14.25 13.61 14.16 13.36 13.02

92.16 35.51 37.47 47.28 82.97 82.31 183.35 36.04 48.23 52.46 111.99 49 54.28 83.02 69.54 34.32 35.54 39.87

736.96 279.96 415.23 233.84 435.58 620.29 820.77 684.41 309.31 588.27 984.38 654 1032.86 681.02 463.91 722.89 690.73 525.5

2273.58 1538.62 1011.45 668.15 795.9 1891.65 1608.05 1651.51 582.55 776.59 1806.04 1263 1744.14 1205.49 863.95 568.06 663.32 563.23

103.1 86.52 45.6 29.96 35.78 85.7 72.78 74.76 26.06 34.9 81.8 57.06 78.98 54.44 38.88 25.4 29.74 25.18

578.49 487.3 262.24 176.22 208.23 482.79 411.73 422.62 154.77 203.39 461.34 325.27 445.83 310.86 225.28 151.14 175.01 149.93

298.74 249 126.24 79.32 96.78 246.54 207.78 213.72 67.62 94.14 234.84 160.62 226.38 152.76 106.08 65.64 78.66 64.98

9.53 9.75 9.79 9.37 9.08 9.15 8.93 9.27 6.66 9.74 8.61 9.08 8.73 8.59 9.36 8.62 8.74 8.80

23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

2.2 1.2 2.1 3.4 2.9 1.4 1.3 2.2 0.6 2 0.8 2.8 5.7 2.8 0.9 1.6 1 1.1 1.3

2.67 1.5 2.54 4 3.47 1.83 1.61 2.73 0.851 3.47 1 3.34 6.49 3.36 1.23 2 1.31 1.47 1.65

7.71 7.61 7.6 7.42 7.52 7.31 7.53 7.2 7.68 7.1 7.88 7.31 7.15 7.88 7.71 7.33 7.19 7.94 7.77

4.18 2.34 3.97 6.25 5.43 2.86 2.52 4.27 1.333 5.42 1.577 5.22 10.14 5.25 1.934 3.12 2.05 2.3 2.58

1875.35 648.37 1354.28 3020.21 2128.05 1087.66 875.38 1771.39 422.67 2128.49 458.51 2242.41 4254.6 1726.51 510.93 1182.36 611.69 740.06 758.55

14.17 13.14 14.97 14.62 14.33 13.28 13.25 13.89 12.52 14.69 12.91 14.19 15.4 14.48 13.09 12.35 13.09 13.25 13.16

138.64 36.34 114.51 95.9 68.17 38.5 41.14 165.93 34.59 42.55 73.79 129.43 46.9 34.82 34.25 108.62 33.53 37.17 49.04

138.64 371.9 114.51 586.46 599.98 422.16 408.55 165.93 273.24 427.14 182.16 454.48 496.83 260.67 424.66 598.62 212.09 467.78 600.75

1236.95 570.7 964.48 1536.5 1328.41 694.49 613.28 1038.67 335.83 1325.78 392.02 1275.73 2551.46 1283.19 474.99 757.27 502.21 561.04 627.33

45.82 25.52 43.46 69.52 60.04 31.16 27.46 46.84 14.82 59.92 17.38 57.64 115.76 57.98 21.16 34.02 22.4 25.08 28.1

263.45 151.8 250.47 393.8 341.66 182.82 162.47 269.06 92.95 341 107.03 328.46 648.12 330.33 127.82 198.55 134.64 149.38 165.99

126.9 66 119.82 198 169.56 82.92 71.82 169.96 33.9 169.2 41.58 162.36 336.72 163.38 52.92 91.5 56.64 64.68 73.74

7.13 9.20 6.50 8.63 9.41 9.43 9.20 8.81 8.23 9.36 9.43 9.99 9.37 9.14 8.54 8.36 8.51 8.75 8.61

42 43 44 45 46 47 48

1.9 2 7 4.5 4.1 3 4.3

2.39 2.44 7.83 5.23 4.83 3.57 5.01

7.65 7.29 7.13 7.2 7.38 7.52 6.9

3.73 3.82 12.24 8.18 7.55 5.58 7.83

1217.84 1463.57 1885.38 3477.55 3390.74 2522.63 2284.97

13.45 14.03 14.4 15.1 15.2 14.52 15.55

112.89 43.89 55.74 100.17 133.53 90.18 118.31

112.89 424.36 1125.72 504.64 478.4 963.34 449.74

905.65 927.6 1257.62 2034.76 1871.01 1366.16 1943.45

40.78 41.78 41.76 92.22 84.76 61.76 88.06

235.73 241.23 441.12 518.65 477.62 351.12 495.77

111.78 114.78 114.72 266.1 243.72 174.72 253.62

9.25 9.69 9.00 9.42 9.43 8.30 9.46

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Table 1 (continued) Wells Salinity TDS pH (g l−1) ID no. (g l−1)

EC Cl− −1 (mS cm ) (mg l−1)

Br− (mg l−1)

NO3− (mg l−1)

SO42− (mg l−1)

Na+ (mg l−1)

K+ Ca2+ −1 (mg l ) (mg l−1)

Mg2+ (mg l−1)

F− (mg l−1)

49 50 51 52 53 54 55 56

3.1 1.3 0.9 1.3 0.8 1.5 1.5 2.6

3.77 1.61 1.16 1.63 1.07 1.87 1.89 3.14

7.13 7.37 7.37 7.58 7.41 7.44 7.51 7.68

5.89 2.51 1.824 2.54 1.682 2.92 2.95 4.91

2252.87 669.34 305.4 812.49 583.86 966.95 1023.83 2131.16

14.72 13.07 14.02 13.24 12.77 13.23 13.33 14.03

125.09 42.01 37.79 41.81 34.27 38.99 94.05 79.39

572.96 536.93 437.63 764.17 418.03 377.01 679.17 725.73

1444.74 611.08 249.58 618.11 416.17 708.98 716 1198.03

65.34 27.36 19.98 27.68 18.48 31.82 32.14 54.1

370.81 161.92 121.33 163.68 113.08 186.45 188.21 308.99

185.46 71.52 49.38 72.48 44.88 84.9 85.86 151.74

9.33 8.99 8.95 8.49 9.05 9.52 8.59 8.91

57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

2.8 1 4.9 2.3 2.2 1.7 1.8 3.7 3.5 3.2 3.4 2.9 0.7 0.5 1.1 0.4 0.7 0.3

3.4 1.34 5.65 2.78 2.69 2.11 2.23 4.39 4.16 3.85 4.06 3.5 0.928 0.749 1.43 0.55 0.92 0.48

7.51 7.66 7.54 7.58 7.84 7.57 7.38 7.4 7.19 7.39 6.82 7.35 7.63 7.6 7.75 7.77 7.12 7.67

5.32 2.09 8.83 4.34 4.21 3.3 3.48 6.86 6.5 6.02 6.35 5.47 1.452 1.172 2.23 0.867 1.451 0.769

1251.38 519.51 3706 1374.11 1403.32 1237.52 1211.26 3801.57 2520.22 2245.56 3075.77 1918.26 366.65 305.29 671.74 174.1 373.73 125.37

12.25 13.01 15.32 13.66 13.38 13.58 13.52 15.57 14.51 14.47 15.12 14.6 14.9 12.52 13.06 14.53 12.87 14.97

42.92 35.67 64.81 75.63 82.58 72.04 67.12 152.66 98.61 49.97 63.11 41.13 34.11 34.83 40.11 34.24 37.74 33.81

566.92 594.43 683.95 637.04 743.59 668.05 562.46 687.11 444.14 490.65 573.05 545.75 126.03 102.59 289.17 49.29 274.16 72.62

732.92 511.43 2205.09 1055.79 1023.74 800.73 844.63 1692.78 1600.15 1478.11 1561.96 1338.51 363.05 299.39 544.3 230.47 363.05 208.96

58.78 22.82 99.98 47.62 46.16 36 38 76.64 72.42 66.86 70.68 60.5 16.06 13.16 24.32 10.02 16.06 9.04

334.73 136.95 561.33 273.35 265.32 209.44 220.44 432.96 409.75 379.17 400.18 344.19 99.77 83.82 145.2 66.55 99.77 61.16

165.78 57.9 289.38 132.3 127.92 97.44 103.44 219.36 206.7 190.02 201.48 170.94 37.62 28.92 62.4 19.5 37.62 16.56

9.02 8.68 9.15 8.86 8.58 8.81 9.41 8.58 9.23 9.71 9.36 9.51 9.26 9.46 9.41 9.63 9.78 9.76

75 76 77 78 79

0.7 1.2 3.2 3.6 3

0.92 1.58 3.81 4.3 3.59

7.64 7.66 7.29 7.51 7.43

1.442 2.47 5.96 6.72 5.61

337.59 794.5 2362.01 2747.03 2117.84

13.77 13.25 14.2 14.66 14.08

46.59 42.45 64.36 71.2 73.42

284.14 522.06 644.36 889.65 1011.58

360.85 601.43 1462.74 1656.78 1374.07

15.96 26.92 66.16 75 62.12

99.22 159.5 375.32 423.94 353.1

37.32 70.2 187.92 214.44 175.8

8.30 8.52 9.01 8.64 8.76

Table 2 Correlation matrix of salinity and major ions of study area Salinity F− Cl− Br− NO3− SO42− Na+ K+ Ca2+ Mg2+

Salinity

F−

Cl−

Br−

NO3−

SO42−

Na+

K+

Ca2+

Mg2+

1 0.11 0.90 0.75 0.35 0.54 0.93 0.92 0.97 0.92

1 0.10 0.13 −0.11 −0.09 0.10 0.12 0.12 0.12

1 0.78 0.44 0.45 0.97 0.96 0.96 0.96

1 0.36 0.25 0.80 0.79 0.79 0.79

1 0.14 0.41 0.38 0.38 0.40

1 0.46 0.45 0.49 0.44

1 0.99 0.99 0.99

1 0.99 1.00

1 0.99

1

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Fig. 3 Bivariate plots of groundwater quality parameters to identify salinization origin of Jerba shallow aquifer: a Na+ vs. Cl−, b Na+/Cl− vs. Cl−, c Br− vs. Cl−, d Br−/Cl− vs. Cl−, e K+ vs. Cl−, and f Ca2+ vs. Cl−

coefficient of correlation between Cl− and Br− confirms the common source of these two parameters which may be attributed to marine intrusion. It is indicated by the relationship between Cl− and Br− (Fig. 3c) that the intensive pumping facilitates the migration of seawater to the aquifer, as a result, the chemical quality of groundwater is directly influenced by seawater. On the other hand, the diagram illustrating the relationship between K+ and Cl− (Fig. 3e) shows that the majority of the points are above the dilution line, which confirms the existence of an anthropogenic source of potassium, such as agricultural activities in the central parts of the island (Oualegh, Guecheine, Mahboubin) that provide potassium load due to the use of fertilizers. Further, the dissolution of evaporites included in the clayey layer of Mio-Pliocene can be considered another source of potassium. The bivariate plot of Cl− vs. Ca2+ (Fig. 3f) shows that the study area was relatively enriched in calcium. The high loading

in Ca2+ may be related to the dissolution of evaporites or by the rock-water interaction phenomenon that results in the adsorption of Na+ and the release of Ca2+ (Chemseddine et al. 2009). Figure 4 shows the values of different ratios (Br−/Cl−, Na+/ − Cl , and Mg2+/Ca2+) for the sampled water compared with the Br−/Cl−, Na+/Cl−, and Mg2+/Ca2+ ratios. The Br−/Cl− ratio is widely used as a proxy to specify the origin of bromides and chlorides in groundwater (Cartwright et al. 2006; Alcala and Custodio 2008; McArthur et al. 2012). From bivariate diagram (Fig. 4a), we conclude that the sampled wells have a Br−/Cl− value that exceeds the seawater ratio, which is equal to 1.36 × 10−3 (Klein et al. 1999). Referring to the graph, the presence of other possible sources of contamination like anthropogenic activities is noticeable. Rainwater is also a source of bromide and chloride input to the water table due to the influence of sea spray on rainwater (Ben Hamouda et al. 2009). The highest Br−/Cl− ratios, up to

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Table 3 Table of communalities

Table 5 Initial

Extraction

Salinity Cl− Br− NO3− SO42−

1.000 1.000 1.000 1.000 1.000

0.907 0.946 0.659 0.401 0.348

Na+ K+ Ca2+ Mg2+ F−

1.000 1.000 1.000 1.000 1.000

0.980 0.971 0.984 0.969 0.835

Salinity Cl− Br− NO3− SO42− Na+ K+ Ca2+ Mg2+ F−

Br−/Cl−seawater ratio, may be attributed to the important flow of Cl− emanating from domestic wastewater rejection in the sub-surface. The clearest indication of seawater intrusion is an increase in Cl− concentration as a proxy for salinity. The Na+/ Cl− ratio of 97.46% of groundwater points exceeds the seawater ratio (0.82) (Fig. 4b). This fact confirms that groundwater salinization was controlled by natural and anthropogenic processes. The high Na+/Cl− ratios were typical of anthropogenic sources like domestic wastewaters (Jones et al. 1999 in El Moujabber et al. 2006). The groundwater Mg2+/Ca2+ ratio (Fig. 4c) is lower than the seawater which is equal to 5.18 (klein et al. 1999). The Mg2+/Ca2+ ratio was used as a tracer of seawater intrusion in coastal aquifer. The value of this ratio increased with the proportion of seawater in groundwater (Pulido Leboeuf et al. 2003). In areas where seawater intrudes a fresh coastal aquifer, cation exchange reaction influenced groundwater chemistry. The low Mg 2+ /Ca 2+ ratio is interpreted as being due to the existence of inverse cation exchange, which withdraws Ca2+ and gives Na+ to the solution (Pulido Lebeouf 2003). In addition, gypsum dissolution releases Mg2+ and contributes to the increase of Mg2+/Ca2+ (Aoun Sebaiti 2010). Table 4

Component 1

Component 2

0.952 0.973 0.805 0.455 0.518 0.990 0.984 0.991 0.984 0.119

0.017 −0.001 0.104 −0.441 −0.282 0.014 0.047 0.039 0.041 0.906

Principal component analysis In this study, principal component analysis (PCA) was performed using 10 groundwater quality parameters (salinity, F−, Cl−, Br−, NO3−, SO42−, Na+, K+, Ca2+, Mg2+) for 79 individuals (the sampled wells). PCA gives a large set of principal components to explain the relationship among the chemical variables and to better interpret the contribution of each variable (chemical element) to the contamination of groundwater (Taiwo 2012; Machiwal and K Jha 2015). The correlation matrix (Table 2) indicates the strong correlation between salinity, calcium, magnesium, potassium, chloride, and bromide. Table 1 shows that correlation ranges between 0.75 and 0.97. These strong correlations confirm the contribution of these chemical elements in groundwater mineralization processes of the Mio-Pliocene-Quaternary aquifer of Jerba. The explained variance percentage in the extracted dimensions is shown in Table 3. The variables taken into account are the salinity, Cl−, Ca2+, Mg2+, Na+ and K+. In fact, more than 90% of the variance of each initial variable was taken into account by one of the selected factors.

Rotated component matrix of the chemical data

Component

1 2 3 4 5 6 7 8 9 10

Component matrix

Initial Eigenvalues

Extraction sums of squared loadings

Rotation sums of squared loadings

Total

% of variance

Cumulative %

Total

% of variance

Cumulative %

Total

% of variance

Cumulative %

6.889 1.112 0.887 0.637 0.305 0.107 0.049 0.011 0.001 0.001

68.890 11.116 8.868 6.375 3.054 1.073 0.493 0.112 0.015 0.005

68.890 80.005 88.873 95.248 98.302 99.375 99.868 99.980 99.995 100.000

6.88 1.112

68.890 11.116

68.890 80.005

6.819 1.181

68.192 11.814

68.192 80.005

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Fig. 4 Br−/Cl−, Na+/Cl−, and Mg2+/Ca2+ ratio variations to differentiate the natural contamination processes from the other anthropogenic influences in groundwater samples in the study area

Table 4 shows the calculated variability for studied variables. The components with variance values less than 10% were not taken in consideration (Agoubi 2012). The two first components took more than 80% of the variance. The first component explains 68.1% of the total inertia of the phenomenon; the second dimension explains 11.8%. The factorial plane F1 × F2 alone accounts for about 80% of the total inertia (total variance). According to the component matrix (Table 5), salinity, chlorides, sodium, potassium, magnesium, and calcium were

Fig. 5 Plot of principal component loadings showing inter-relationships among ten variables on planes F1 and F2

highly correlated with the first component that was not on the second axis. The second factor had significant positive loadings for fluoride. Figure 5 shows the eigenvectors of each variable that allowed us to interpret that Ca2+, Mg2+, Na+, K+, Cl−, and Br− were worn by the main component. The factorial diagram confirms the two processes of groundwater contamination. The first process was associated with the enrichment of groundwater by chloride, sodium, calcium, bromide magnesium, and potassium. The second reflects on the anthropogenic activities. The projection of individuals in the factorial plane (F1 × F2) (Fig. 6) defines a distribution of wells according to their chemical behavior. As a result, wells can be classified to (i) wells affected by anthropogenic activities where sulfate and nitrate ions were the most dominant (group 1), (ii) wells of high mineralization where natural and anthropogenic activities contribute to the salinization (group 2), and (iii) wells with low mineralization (group 3). The hierarchical cluster analysis (HCA) was performed by average linkage (between groups) using Euclidean distance as a similarity measure. Results of the HCA are shown on the dendrogram in Fig. 7. The dendrogram rendered 79 sampling wells into three statistically significant clusters; the sampled wells categorized into individual clusters had a similar chemical signature. As can be seen from this figure, the groundwater samples were classed to three clusters (groups). The samples of group I were typical in terms of their higher salinity (exceeding 4 g l −1) and major ion concentrations. The

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Fig. 6 Plot of principal component scores in factorial plane (F1 × F2), showing the variability of groundwater mineralization

mineralization of this groundwater group was governed by both natural and anthropogenic contamination processes, which is indicated by the high levels of chloride, sodium, sulfate, nitrate, and potassium. Group II contained moderate salt concentration; as for group III, the samples were characterized by low mineralization. Spatial distribution of pollution Figure 8a, b shows that spatial distribution of Cl− and Na+ in Jerba Island is similar. Cl− and Na+ showed high values in the north, the northwest, near the south, and the west of the study area. Cl− and Na+ concentrations gradually decreased towards the eastern and the central part of the island. Maximum salinity values (Fig. 8c, d) were found adjacent to the north, the northwest, and the south. They decreased gradually in the western parts of Jerba. The maps also reveal the salinization of the north costal part of the island due to the seawater intrusion deduced by Kharroubi et al. (2012). In Jerba Island, several factors have probably led to the seawater intrusion into the shallow aquifer system: (i) the topography of the island, (ii) the fault system, and (iii) increased pumping frequency. Thus, the shallow and the coastal regions (north and west), characterized by low topographic and piezometric levels, were the most contaminated areas. This fact promotes seawater intrusion by reversing the hydraulic gradients. Over exploitation of groundwater in these regions of the island has created several drawdown cones, lowered the water table, and generated depressions causing saltwater migration to the aquifer. The spatial distribution pattern of NO3− concentration (Fig. 8e, f), eminent variability, and NO3− elevated concentration were detected near agricultural areas (the center of Jerba) and in shallow wells (the north and the north west parts). The spatial distribution of K+ concentration (Fig. 8g) can clearly be attributed to the anthropogenic

Fig. 7 Dendorgram of the hierarchical cluster analysis using average linkage (between groups), showing three clusters of groundwater quality in the study area.

activities (wastewater discharge) near shallow water (northern part) and the ion exchange between groundwater and potassium clays (southern part). The sulfate map

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Fig. 8 Spatial distribution maps for the concentrations of major cations and anions in groundwater

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Fig. 8 (continued)

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Fig. 9 Spatial distribution of fecal tracers in Jerba unconfined aquifer: a Total coliforms, b thermotolerant coliforms, and c E. coli

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shows (Fig. 8h) that the highest sulfate concentrations occur in the central and the southern parts of the study area. It has been reported that high concentration of SO42− in the study area was associated with evaporites contained in geological layers. Referring to Fig. 9, spatial distribution of coliforms confirms that the wells were seriously affected by the fecal pollution problem. The abundance of coliforms, therefore, demonstrates that bacteria are widely distributed in the studied water wells confirming the existence of significant bacteriological pollution in groundwater. In this area, coliforms were uncountable in 78.48% of the visited wells (Fig. 9a). The presence of Thc and E. coli in most wells (96.2%) indicates that these sampling wells were contaminated (Fig. 9b, c). Contamination by both human and animal fecal sources was the most dominant type of pollution among all samples. Heavy rainfall promotes the movement of bacteria through soil. Therefore, a large number of germs which have survived in the vadose zone were rapidly transported into the aquifer by heavy rains, thus contaminating the groundwater (WHO 2008). Therefore, Salmonella was absent in all sampled wells. Origin of pollution In Jerba Island, open dug wells are the principal mean to exploit the quaternary aquifer. However, dug wells are generally the worst groundwater sources in terms of fecal contamination (World Health Organization 2007). This includes point sources of pollution (human and industrial waste discharge) as well as diffuse sources (those arising from agricultural and animal husbandry activities). Further, abandoned wells used as habitat by birds are somehow responsible for polluting the water aquifer. The irrigation water return and the intensive pumping have been identified as sources of salinization (Trabelsi et al. 2005); also, the short distance between wells and septic tanks also causes the increase of fecal pollution in their groundwater. The absence of sewage systems in suburban regions of the island generates sub-soil contaminants which are transported to the water table. Moreover, rainwater is considered a contamination vector through mobilization of superficial contaminant to aquifer. Abandoned dug wells and septic tanks were identified as direct contamination sources that contribute to increase chemical and bacteriological inputs in the study area for both shallow and deep wells. In addition, contaminants from seawater (especially Cl− and Na+) are carried from shallow coastal parts of the aquifer to the other parts under pumping effect. It seems that excessive groundwater pumping facilitates contaminant migration from seawater and punctual pollution sources to the different parts of the aquifer and contributes to homogenize groundwater geochemistry. Due to the different origins of groundwater geochemical

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elements and the complexity of mixing phenomena between fresh water and several pollutants, no relationship between hydrochemistry and depth appeared. Sulfate origin was due to gypsum dissolution. Gypsum clay layers intercalated within the Mio-Plio-quaternary sand were suspected to be the major natural source of sulfate excess in groundwater. Moreover, the interaction between groundwater and the bedrock (clay and marl gypsum of Mio-Pliocene and Miocene) leads to gypsum dissolution. This process is the main source of sulfate in groundwater. Nitrate (NO3−) in groundwater largely originates from diffuse sources relating agricultural (agrochemicals such as pesticides) and domestic practices, as well as from point sources such as sewage effluent (Kim et al. 2014), also, septic tanks are considered point sources of nitrogen (Ma et al. 2009). In addition, the spatial irregularity of nitrate concentrations confirms the existence of punctual sources of pollution (Tandia et al. 1999) such as septic tanks. Nitrate is a proxy of the aquifer vulnerability (Yao et al. 2012). The important concentration of NO3−, indicates the effect of anthropogenic sources like municipal sewages and agricultural fertilizers (Kumar 2014). However, the proximity of wells to latrines can contribute to high concentrations of nitrate (Tandia et al. 1999). Cl− is a conservative ion so its concentration is not affected by the interaction with aquifer matrix (Kumar 2014). The origin of chloride is attributed to the marine intrusion (Kharroubi et al. 2012). Also, this ion is attributed to industrial effluents, municipal and domestic sewages, fertilizers, and septic tanks, and also naturally from rainfall, the dissolution of fluid inclusions, and evaporites (Kumar 2014). Abandoned wells used as uncontrolled discharge are also an important source of pollution. In the present study, the leachates of the uncontrolled discharge are the primary sources of groundwater contamination in the island, especially during the wet season. The high fluoride concentrations may be attributed to the agrochemicals used in agriculture (Su et al. 2013). According to the guideline set by WHO (2008) for the evaluation of bacteriological quality of drinking water, E. coli must not be detectable in any 100 ml sample. The most serious source of pollution is the contamination by human and animal waste from latrine, septic tanks, and farm manure. However, the most hazardous gross fecal contamination was most commonly associated with latrine (underground pollution sources) sited too close to the well. Therefore, fecal pollution is only attributed to the anthropogenic inputs. E. coli is the most obvious indicator of fecal pollution. This germ is mobilized when water flow increases (WHO 2008). In fact, shallow wells tend to have higher levels of fecal pollution than deep wells. In general, the aquifer potential protection increases with depth to water (Ben Brahim et al. 2012), that is why deep wells are less affected by fecal pollution.

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Conclusion The results of this study showed that the reasons underlying the groundwater quality deterioration in Jerba Island were both anthropogenic and natural contamination processes. The results of our analysis indicated that the high concentrations of the chemical pollution and biological tracers in most water samples confirm the human impact on Jerba aquifer, which have several indicators: (i) fecal indicators, obvious from the fecal material of humans or other warm-blooded animals; (ii) nitrate from septic tanks, fertilizers, pesticides, and manure used as organic amendment for the soil; and (iii) potassium, magnesium, and calcium, which may appear in surplus amounts due to irrigation backflow and water infiltration with soil into the groundwater. Moreover, referring to relationships between conservative elements (chloride and bromide), it can be concluded that this area is directly influenced by the seawater intrusion. In addition, the results of statistical analysis of chemical data prove that groundwater deterioration in Jerba is governed by two major factors, which are anthropogenic and natural processes. Likewise, the geographical location of Jerba (an island) exposes the unconfined aquifer to seawater intrusion which is considered the major natural process that governs the groundwater mineralization by increasing the rates of sodium and chloride in Quaternary Jerba aquifer. It also appeared that the contamination of the prospected aquifer was due to the various sources of pollution around the wells. Infiltration of wastewater, discharge leachates, or human and animal activities near the studied wells seem to lead to the contamination of groundwater. Furthermore, the nature and texture of the soil contribute to facilitating the transfer of chemical and bacteriological pollutants from superficial layers to groundwater. Intensive pumping also contributes to facilitate pollutants migration into the aquifer. Acknowledgements The authors are grateful to Kamel Maaloul, interpreter and English professor for having proofread the manuscript.

References Agoubi B (2012) Caractérisation hydrogéologique et géochimique du système aquifère de la Jeffara maritime: Apport des approches géostatistiques. Thèse de doctorat en sciences géologiques, Université de Sfax, 175 p Agoubi B, Kharroubi A, Abida H (2012) Saltwater intrusion modelling in Jorf coastal aquifer, South-eastern Tunisia: geochemical, geoelectrical and geostatistical application. Hydrol Process journal. doi:10.1002/hyp.9207 Alcala FJ, Custodio F (2008) Using the cl/Br ratio as a tracer to identify the origin of salinity in aquifers in Spain and Portugal. J Hydro 359: 189–207 Andreasen DC, Fleck WB (1997) Use of bromide: chloride ratios to differentiate potential sources of chloride in a shallow, unconfined aquifer affected by brackish-water intrusion. Hydrology Journal 5(2):17–26

Page 15 of 16 231 Aoun Sebaiti B (2010) Gestion optimisée des ressources en eau d’une nappe côtière Application à la plaine d’Annaba (Nord-est Algérien). Thèse de doctorat en Génie Civil. Université Lille 1. 211 Belghiti ML, Chahlaoui A, Bengoumi D, El Moustaine R (2013) Etude de la qualité physico-chimique et bactériologique des eaux souterraines de la nappe Plio-quaternaire dans la région de Meknès (Maroc). Larhyss J ISSN 1112–3680, no. 14, 21–36 Ben Brahim F, Khanfir H, Bouri S (2012) Groundwater vulnerability and risk mapping of the Northern Sfax Aquifer, Tunisia. Arab J Sci Eng 1405–1421 Ben Hamouda MF, Leduc C, Trhouni J, Zouari K (2009) Origine de la minéralisation dans l’aquifère Plio-quaternaire de la côte orientale du cap Bon (Tunisie). Sécheresse 20(1):78–86 Bonton A, Rouleau A, Bouchard C, Rodriguez MJ (2010) Assessment of groundwater quality and its variations in the capture zone of a pumping well in an agricultural area. Agric Water Manag 97:824– 834 Bouaziz S, Jedoui Y, Barrier E, Angelier J (2003) Néotectonique affectant les dépôts marins tyrrhéniens du littoral sud-est tunisien: implication pour les variations du niveau marin. Compt Rendus Geosci 335: 247–254 Cartwright I, Weaver Tamie R, Fifield Keith L (2006) Cl/Br ratios and environmental isotopes as indicators of recharge variability and groundwater flow: an example from the southeast Murray Basin, Australia. Chem Geol 231:35–56 Chemseddine F, Boudoukha A, Rouabhia A, Salmeh E (2009) Caractérisation hydrochimique des eaux souterraines du complexe aquifère Morsott-Louinet (Région Nord de Tébessa, Sud-Est Algérien). J Afrique Science 14:217–231 Coleman BL, Louie M, Salvadori MI, McEwen SA, Neumann N, Sibley K, Irwin RJ, Jamieson FB, Daignault D, Majury A, Braithwaite S, Crago B, McGeer AJ (2013) Contamination of Canadian private drinking water sources with antimicrobial resistant Escherichia coli. Water Res 47:3026–3063 Degbey C, Makoutode M, Agueh V, Dramaix M, De Brouwer C (2011) Facteurs associés à la qualité de l’eau de puits et prévalence des maladies hydriques dans la commune d’Abomey-Calavi (Bénin). Santé 21. doi:10.1684/san.2011.0238, 47-55 El Moujabber M, BouSamra B, Darwish T, Atallah T (2006) Comparison of different indicators for groundwater contamination by seawater intrusion on the Lebanese coast. Water Resour Manag 20:161–180 Fakir Y, Zerouali A, Aboufirassi M, Bouabdelli M (2001) Potentiel exploitation and salinity of aquifers Chaouia coast. J Afr Earth Sci 32(4):791–801 Fedrigoni L, Krimissa M, Zouari K, Maliki A, Zuppi GM (2001) Origin of the salinisation and hydrogeochemicalbehaviour of a phreatic aquifer suffering severe natural and anthropic constraints: an example from the Djebeniana aquifer (Tunisia). C R Acad Sci Paris, Sciences de la Terre et des planètes/Earth and Planetary Sciences 332:665–671 Howard G, Pedley S, Barrett M, Nalubega M, Johal K (2003) Risk factors contributing to microbiological contamination of shallow groundwater in Kampala, Uganda. Water Res 37(14):3421–3429 Huang G, Sun J, Zhang Y, Chen Z, Liu F (2013) Impact of anthropogenic and natural processes on the evolution of groundwater chemistry in a rapidly urbanized coastal area, South China. Sci Total Environ 463– 464:209–221 International Organization for Standardization 9308-1 (2000) Qualité de l’eau-dénombrement des Escherichia coli et des bactéries coliformes-Partie 1: Méthode par filtration sur membrane, Edition 2 Jedoui Y (2000) Sédimentologie et géochimie des Dépôt littoraux quaternaires: reconstitution des variations des climats et du niveau marin dans le sud est tunisien. Thèse de doctorat en sciences géologiques, Université de Tunis II Khalili B (1986) Hydrogeological study of Jerba unconfined aquifer. Water Resources Direction, Ministry of Agriculture, Tunisia

231

Page 16 of 16

Kharroubi A, Tlahigue F, Agoubi B, Azri C, Bouri S (2012) Hydrochemical and statistical studies of the groundwater salinization in Mediterranean arid zones: case of the Jerba coastal aquifer in southeast Tunisia. Environ Earth Sci 67:2089–2100 Kim KH, Yun ST, Park SS, Joo Y, Kim TS (2014) Model-based clustering of hydrochemical data to demarcate natural versus human impacts on bedrock groundwater quality in rural areas, South Korea. J Hydrol 519:626–636 Klein B, Roether W, Macana BB, Bregant D, Beitzel V, Kovacevic V, Luchetta A (1999) The large deep water transient in the Eastern Mediterranean. Deep-Sea Res 46:371–414 Kouzana L, Ben Mammou A, Sfar Felfoul M (2009) Seawater intrusion and associated processes: case of the Korba aquifer (Cap-Bon, Tunisia). C R Geoscience 341:21–35 Kumar PJS (2014) Evolution of groundwater chemistry in and around Vaniyambadi industrial area: differentiating the natural and anthropogenic sources of contamination. Chem Erde Geochem 11 Ma J, Ding Z, Wei G, Zhao H, Huang T (2009) Sources of water pollution and evolution of water quality in the Wuwei basin of Shiyang river, Northwest China. J Environ Manag 90(2):1168–1177 Machiwal D, K Jha M (2015) Identifying sources of groundwater contamination in a hard-rock aquifer system using multivariate statistical analyses and GIS-based geostatistical modeling techniques. J Hydrol Reg Stud 31 p Malana MA, Khosa MA (2011) Groundwater pollution with special focus on arsenic, Dera Ghazi Khan-Pakistan. Journal of Saudi Chemical Society 15:39–47 Marjoua A, Olive PH, Jusserand C (1997) Apport des outils chimiques et isotopiques à l’identification des origines de la salinisation des eaux: cas de la nappe de la Chaouia côtière (Maroc). Revue des sciences de l’eau 4:489–505 McArthur JM, Sikdar PK, Hoque MA, Ghosal U (2012) Waste-water impacts on groundwater: Cl/Br ratios and implications for arsenic pollution of groundwater in the Bengal Basin and Red River Basin, Vietnam. Sci Total Environ 437:390–402 Mondal NC, Singh VP, Singh VS, Saxena VK (2010) Determining the interaction between groundwater and saline water through groundwater major ions chemistry. J Hydrol 388:100–111 Park Y, Lee JY, Kim JH, Song SH (2012) National scale evaluation of groundwater chemistry in Korea coastal aquifers: evidences of seawater intrusion. Environmental Earth Sciences 66(3):707–718 Pulido Leboeuf P, Pulido-Bosch A, Calvache ML, Vallejos A, Andreu JM (2003) Strontium, SO42−/cl− and Mg2+/Ca 2+ ratios as tracers for the evolution of sea water into coastal aquifers: the example of castell de Ferro-aquifer. CR Geoscience 335:1039–1048 Sall M, Vanclooster M (2009) Assessing the well water pollution problem by nitrates in the small scale farming systems of the Niayes region, Senegal. Agric Water Manag 96(2009):1360–1368 Schaffter N, Parriaux A (2002) Pathogenic-bacterial water contamination in mountainous catchments. Water Res 36:131–139 Servais P, Passerat J (2009) Antimicrobial resistance of fecal bacteria in waters of the seine river basin (France). Sci Total Environ 408:365–372

Arab J Geosci (2017) 10:231 Smaoui A, Malha C, Snoussi N, Zamouri M, Yahyaoui H, Chouchane R (1997) Etude agro-économique de l’île de Djerba « situation actuelle », Ministère de l’agriculture. CRDA de Medenine, Tunisie, p 47 Smida H, Abdellaoui C, Zairi M, Ben Dhia H (2010) Cartographie des zones vulnérables à la pollution agricole par la méthode DRASTIC couplé à un Système d’information géographique (SIG): cas de la nappe phréatique de Chaffar (sud de Sfax, Tunisie). Sécheresse 21(2):131–114 Su C, Wang Y, Xie X, Li J (2013) Aqueous geochemistry of high-fluoride groundwater in Datong Basin, Northern China. J Geochem Explor 135:79–92 Taiwo AM (2012) Source identification and apportionmentof pollution sources to groundwater qualityin major cities in Southwest, Nigeria. Geofizika 29:158–174 Tandia A, Diop ES, Gaye CB (1999) Nitrate groundwater pollution in sub-urban areas: example of groundwater from Yeumbeul, Senegal. J Afr Earth Sci 29(4):809–822 Trabelsi R, Zairi M, Smida H, Ben Dhia H (2005) Salinisation des nappes côtières: cas de la nappe nord du Sahel de Sfax, Tunisie. CR Géoscience 377:315–325 Tunisian Standard 09.14 (2013) Eaux destinées à la consommation humaine à l’exclusion des eaux conditionnées Villanueva CM, Kogevinas M, Cordier S, Templeton MR, Vermeulen R, Nuckols JR, Nieuwenhuijsen MJ, Levallois P (2014) Assessing exposure and health consequences of chemicals in drinking water: current state of knowledge and research needs. Environ Health Perspect 122(3):213–221 World Health Organization (2007) Nitrate and nitrite in drinking water background document for development of WHO guidelines for drinking-water quality. WHO Press, Geneva, p 29 World Health Organization (2008) Guidelines for drinking-water quality, volume 1 recommendations, third edition, 515 Yahyaoui H (2012) Nappe phréatique de l’île de Jerba: Aspects hydrogéologiques et mobilisation des ressources, Ministère de l’agriculture. Comissariat Régionale De l’Agriculture de Medenine, Tunisie, p 7 Yao TK, Oga MS, Fouché O, Baka D, Pernelle C, Biemi J (2012) Évaluation de la potabilité chimique des eaux souterraines dans un bassin versant tropical: cas du Sud-Ouest de la Côte d’Ivoire. Int J Biol Chem Sci (6)6:7069–7086 ISSN 1991–8631 Youmbi JGT, Feumba R, Njitat VT, De Marsily G, Ekodeck GE (2013) Water pollution and health risks at Yaoundé, Cameroon. Comptesrendus Biologies 336:310–316 Yu Y, Song X, Zhang Y, Zheng F, Liang J, Han D, Ma Y, Bu H (2013) Identification of key factors governing chemistry in groundwater near the water course recharged by reclaimed water at Miyun County, Northern China. Journal of of Environmental Sciences 25(9):1754–1763 Zammouri M, Siegfried T, El-Fahem T, Kriâa S, Kinzelbach W (2007) Salinization of groundwater in the Nefzawa oases region, Tunisia: results of a regional-scale hydrogeologic approach. Hydrogeol J 15: 1357–1375