Assessment of groundwater quality using statistical techniques in high Basin of Guir (Eastern High Atlas, Morocco)

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ScienceDirect Materials Today: Proceedings 13 (2019) 1084–1091

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ICMES 2018

Assessment of groundwater quality using statistical techniques in high Basin of Guir (Eastern High Atlas, Morocco) A. Nouaytia*, D. Khattacha, M. Hilalib, N. Nouaytia,c and M. Arabid a b

Laboratory of Applied Geosciences, Faculty of Sciences, University Mohamed First Oujda 60000, Morocco Laboratory of Geo-Engineering and Environment, Faculty of Sciences and Technologyiques of Errachidia. c Ecole Nationale des Sciences Appliques, University Abdelmalek Assaadi Tetouan, Morocco d Laboratory of Water Sciences, Environment and Ecology, Faculty of Sciences, Oujda 60000, Morocco.

Abstract This paper reports results of a physico-chimical study of groundwater in in high Basin of Guir (Eastern High Atlas, Morocco). The water quality data was monitored at ten different wells and springs using 12 water quality parameters (Biochemical oxygen demand (DBO5), chemical oxygen demand (DCO), Sulfate (SO42-), Ammonium (NH4+), Nitrate (NO3-), Nitrogen dioxide (NO2-), chloride (Cl-), Sodium (Na+), Electrical conductivity(EC), pH, Turbidity, suspended matter(MES)). The Principal Component Analysis (PCA) was used to examine the data with the objective of determining the spatial variability of groundwater and to identify the sources of pollution. Results show that two factors account for almost 59% of the variance: factor 1 is that of the nitrogenous salts (NH4+, NO3- and NO2-) while the factor 2 is related to mineral salts (Cl- and SO42-). The typological structure of the plan analysis F1 x F2 shows four areas depending on the nature of salt pollutants. The contamination observed for the majority of stations could be related to domestic, fertilizers and geological sources of pollution. © 2019 Elsevier Ltd. All rights reserved. Peer-review under responsibility of the scientific committee of the International Conference on Materials and Environmental Science, ICMES 2018. Keywords: Guir high Basin; Geostatistical; PCA; Groundwater; Physico-chemical; Morocco.

* Corresponding author. Tel.: +212670129569. E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Peer-review under responsibility of the scientific committee of the International Conference on Materials and Environmental Science, ICMES 2018.

A. Nouayti et al / Materials Today: Proceedings 13 (2019) 1084–1091

1.

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Introduction

In Morocco, groundwater constitutes an important part of the country's hydraulic heritage [1 & 2], due to its relatively easy exploitation. Groundwater is traditionally the preferred water resource for drinking water because it is more pollutant-free than surface water [3 & 4]. In southern the Guir basin suffers from the scarcity of water linked to the succession of periods of drought and the poor quality of the waters of some aquifers. [5-7]. In the high Guir basin, especially in rural and semi-rural areas, access to drinking water is a key factor in economic development, improving the standard of living of populations and their stabilization, the availability of groundwater in acceptable quality has become a difficult challenge due to the severity of the climate and the risks of pollution (domestic, industrial, agricultural) which weakens and makes these waters vulnerable to different factors. To assess the groundwater quality in the high Basin of Guir, a physico-chemical study was carried out on ten samples taken from the various boreholes and springs spread over the study area. The Principal Component Analysis (PCA) was used to examine the data with the objective of determining the spatial variability of groundwater and to identify the main factors responsible for the water quality of the surveyed environment. 2. Material and Methods 2.1. Study area The studied area is part of the Guir Basin, its situated in a box ranging from −2.4° and −5.52° in longitude and 32.2° to 32.5° in latitude, total area is 4005 km2 (Fig. 1).

Fig. 1. Geographical situation of the studied area.

2.2. Geological framework The geological formations in the area consist mainly of Jurassic deposits affected by faults and folding during the Hercynian cycle [8-11]. Fig. 2 shows the main geological formations of the Guir Basin. The Trias is constituted of detrital deposits, doleritic basalt with evaporite levels, in angular unconformably above the deformed Paleozoic basement and structured by several tectonic phases [12-14]. The Jurassic series rest conformably on the red formations Triassic-Lower Lias. Their lithology constituded essentially of dolomite, limestone, calcareous marl alternations, and silico-clastic detritus (Fig. 2) [11-14].

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Fig. 2. Geological map of the studied area.

2.3. Hydrological and Hydrogeological frame The Guir high Basin is located in a semi-desert bioclimatic stage. Temperatures have significant seasonal variations with a very hot summer and a very cold winter [8-9]. The annual rainfall regime is characterized by the existence of two rainy seasons: autumn and spring [15-16]; with an average annual rainfall reaching 250 mm in of the high Basin and 112 mm at downstream of the basin (Fig. 3). The aquifer systems in the Rheris watershed are : 1) Plio-Quaternary alluvium aquifers containing essentially, conglomerates, gravels and pebbles, located along the valleys ; 2) Cretaceous Aquifer generally containing limestone with a karst behavior, sand and sandstone ; 3) Lias-Domerian lower aquifer with limestone and dolomite, often fractured and sometimes karstified ; 4) Aalenian-Dogger aquifer with the limestonemarl with cracked and karst networks [6-17-19].

Fig. 3. Variation of inter-annual rainfall at the Tazougert station during 2009.

2.4. Sampling and analysis Water of ten wells and springs were sampled in the Guir high Basin (Fig. 4). Samples were collected manually in polyethylene bottles of 1.5 liters capacity. These bottles were washed with distilled water and three times with groundwater. The samples have been transported in coolers at 4°C to the laboratory.

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The water points (wells, boreholes, springs) sampled were chosen in such a way to cover the whole of our study area. Some parameters (pH, temperature, and Conductivity) were measured in situ. Other physico-chemical parameters (Turbidity, BOD5, COD, SO42-, NH4+, NO3-, NO2- and Cl-) were analysed in the laboratory of COSTE.

Fig. 4. Distribution of the sampling points of Groundwater in the Guir high Basin.

3. Results and discussion 3.1. Description of data matrix The Principal Component Analysis (PCA) was applied on a data consisting of ten water samples and twelve variables (Table 1) : Biochemical oxygen demand (DBO5), chemical oxygen demand (DCO), Sulfate (SO42-), Ammonium (NH4+), Nitrate (NO3-), Nitrogen dioxide (NO2-), chloride (Cl-), Sodium(Na+), Electrical conductivity(EC), PH, Turbidity, suspended matter(SM). Table 1. Atomic percentage of the elements present in the pyrolyzed structure.

Points

DBO5 (mg/l)

DCO (mg/l)

SO42(mg/l)

NH4+ (mg/l)

NO3(mg/l)

NO2(mg/l)

Cl(mg/l)

Na+ (mg/l)

EC (µS/cm)

pH

Turbidity (NTU)

SM (mg/l)

1

2.76

46.00

163.75

2.40

12.60

0.55

305.30

198.5

1123.00

7.16

55.41

VN

2

2.30

18.80

212.75

0.60

43.73

0.53

321.63

209.1

1321.00

8.00

86.00

0.01

3

2.70

19.70

112.00

0.08

43.10

0.42

315.60

205.13

1182.00

7.90

87.00

0.02

4

2.20

49.00

196.50

4.07

37.00

1.15

317.58

206.42

973.00

7.34

68.00

0.01

5

5.00

29.00

298.00

3.75

13.00

1.06

276.01

179.40

840.00

7.31

27.00

0.01

6

2.76

40.00

146.50

12.83

36.16

0.86

743.58

483.32

984.00

7.45

39.00

0.09

7

1.04

43.00

373.00

6.64

45.00

0.16

1092.65

710.22

1175.00

7.46

13.98

0.03

8

1.70

28.40

228.75

5.82

28.00

0.13

546.34

355.12

1024.00

7.72

98.64

0.03

9

2.76

10.90

237.25

1.61

42.38

0.58

15.62

10.15

1393.00

7.00

74.60

-

10

1.30

12.80

346.75

4.06

9.60

0.30

70.40

45.7

908.00

7.49

73.90

-

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3.2. Choice of Eigenvalues (selectable number of factors) The treatment of these physico-chemical data via this CPA method gives several results that are presented in Tables 2, 3 and 4. Table 2 depicts the values own, variability and the accumulation, the contributions of different parameters in the expression of the first two factorial axes F1 and F2 are respectively 33.15% and 25.80 % or 58.9 % of the information explained. The maximum of the total inertia is accumulated by the plan formed by the factorial axis F1 × F2 (Fig. 5). Eigenvalues of correlation matrix Active variables only 4,5 4,0

33.15%

3,5 25.73%

Eigenvalue

3,0 2,5 2,0

14.89%

1,5

10.23%

1,0

6.52% 4.55% 3.56%

0,5

.84%.53%

9

0,0 -0,5 -2

0

2

4

6

8

10

12

14

Y

Eigenvalue number

Fig. 5. Projection of the variables on the factorial plan F1 x F2 (58.9%). Table 2. Own values with an inertia of 58.9 %. Component

Eigenvalues Total

% Variance

% Cumulative

1

3.646

33.147

33.147

2

2.831

25.734

58.881

3

1.638

14.888

73.769

4

1.125

10.230

83.999

5

0.717

6.519

90.518

6

0.501

4.553

95.070

7

0.391

3.559

98.629

8

0.092

0.838

99.468

9

0.059

0.532

100.00

10

2.259E-16

2.054E-15

100.00

11

-4.502E-16

-4.092E-15

100.00

Table 3 shows the contribution of the different variables and principles factors. Results indicate that the F1 factor, defined by Cl- (r=0.955), Na+ (r=0.955), NH4+ (r=0.75) and DCO(r=0.71), is the more important factor.

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Table 3. Own values with an inertia of 58.9 %. Variables

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

Factor 6

Factor 7

Factor 8

Factor 9

DBO5 (mg/l)

-0.201

0.632

0.539

0.032

-0.371

-0.009

-0.340

-0.103

-0.035

DCO (mg/l)

0.710

0.333

0.159

0.174

0.374

0.408

0.132

-0.026

-0.054

2-

SO4 (mg/l)

0.171

0.111

-0.767

-0.121

-0.525

0.012

0.261

-0.057

-0.082

NH4+ (mg/l)

0.750

0.242

-0.101

-0.084

0.274

-0.523

-0.061

0.012

-0.076

NO3- (mg/l)

0.253

-0.687

0.375

0.454

-0.157

-0.189

0.212

-0.017

0.092

-

NO2 (mg/l)

0.007

0.692

0.612

0.143

-0.066

-0.086

0.309

0.117

-0.059

-

0.955

-0.242

-0.075

0.048

-0.016

0.050

-0.125

-0.027

-0.001

+

Na (mg/l)

0.955

-0.242

-0.075

0.048

-0.016

0.050

-0.125

-0.027

-0.001

EC (µS/cm)

-0.280

-0.659

0.050

0.661

-0.103

0.028

-0.116

0.028

-0.143

PH

0.076

-0.688

0.315

-0.593

-0.114

0.082

-0.058

0.208

-0.056

Turbidity (NTU)

-0.656

-0.511

0.195

-0.284

0.353

-0.059

0.120

-0.198

-0.075

SM (mg/l)

-0.619

0.233

-0.588

0.320

0.280

-0.022

-0.118

0.136

0.003

Cl (mg/l)

3.3. Analysis of the distribution of parameters in the plan F1xF2 The examination of the correlation matrix between variable shows an important correlation between NO2*DBO5(0.682); EC*NO3-(0.674); Na+*NH4+(0.638); Cl-*NH4+(0.638); Na+*DCO(0.593) and Cl-*DCO(0.593). There is also to a lesser degree of correlation between variables such as NH4+*DCO(0.468); NO2-*DCO (0.339); Cl*NO3-(0.370); Na+*NO3-(0.370) and PH*NO3-(0.322). These different correlations reflect the influence of each parameter on the mineralization of the waters of the Guir high Basin (Table 4). Table 4. Correlation Matrix.%. Variables

DBO5

DCO

SO42-

NH4+

NO3-

NO2-

Cl-

Na+

EC

pH

DBO5 (mg/l) DCO (mg/l) SO42- (mg/l) NH4+ (mg/l) NO3- (mg/l) NO2- (mg/l) Cl- (mg/l) Na+ (mg/l) EC (µS/cm) PH Turbidity (NTU) SM (mg/l)

1 -0.024 -0.267 -0.130 -0.282 0.682 -0.334 -0.334 -0.232 -0.257

1 -0.13 0.468 -0.02 0.339 0.593 0.593 -0.33 -0.24

1 0.081 -0.246 -0.295 0.166 0.166 -0.205 -0.194

1 -0.016 0.114 0.638 0.638 -0.456 -0.155

1 -0.09 0.370 0.370 0.674 0.322

1 -0.24 -0.245 -0.352 -0.357

1 1 -0.06 0.195

1 -0.06 0.195

1 0.090

1

-0.243

-0.52

-0.422

-0.488

0.107

-0.280

-0.55

-0.55

0.296

0.442

1

-0.112

-0.32

0.145

-0.278

-0.46

-0.194

-0.58

-0.58

0.189

-0.582

0.140

NTU

SM

1

Principal component analysis (PCA) was conducted to identify trends, correlations and phenomena that may influence the distribution of chemical elements in groundwater of the Guir high basin. At the level of the circle of correlation formed by the axis F1 and F2 (Fig. 6), there are a set of variables such as the Cl-, Na+, NO3-, EC, PH and Turbidity which are correlated positively on the F1 axis with a variability of 33.15%. Conversely there is a negative correlation between the variables NH4+, DCO, NO2- and DBO5. On the F2 axis with a variability of 25.73%, it was a positive correlation between the variability of SO42-, DCO, NH4+, NO3-, Cl- and Na+, has the opposite the variable pH, EC, DBO5 and Turbidity. The graph of Fig.7 illustrates the distribution of the various sampling points studied (10 points) in the region of Guir high Basin on the factorial plan F1 x F2, which will be stalled automatically with the one of the variables (chemical elements) to provide an idea on the groups according to their quality.

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Fig. 6. Graphical presentation of own the factorial plan F1 x F2 (58.9%).

Fig. 7. representation of water points of the factorial planF1 × F2.

The typological structure of the plan analysis F1 x F2 (Fig. 7) allows the identification of four areas (GI, GII, GIII, and GIV), depending on the nature of pollutants and their degree of contamination. Group I : This group occupies the negative part of the F1 axis. It is represented by water points 1 and 10. The groundwater in this area is characterized by anthropogenic pollution reflected by the high levels of NH4+ and NO2-. This heavy load in these chemical elements NH4+and NO2- seems to be mainly due to human activity (domestic and agricultural). Group II : This group occupies the positive part of the F2 axis and the negative part of the F1 axis. It is represented by the water points 2,3 and 9. The groundwaters of this zone, as well as their anthropogenic pollution, also experienced a geological contamination, because of the high levels of Cl-, NO2- and NO3-. These high values recorded could be attributed to the domestic salts (nitrogen salts such as NO2- and NO3-) and geological salts (salts of salts). Group III : This group occupies the positive parts of F1 and F2. It is represented by points 7 and 8. It is characterized by a high chemical element charge (NH4+, NO3-, SO4- and Cl-). The presence of these elements in this groundwater could be related to the concentration of human and geological activity.

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Group IV : This group the positive part of the F1 axis. It is represented by the water points 4, 5 and 6. The high concentrations can result from the decomposition of the nitrogenous salts (NH4+, NO2- and NO3-). These could be due to domestic human activities and agriculture, the existence of any kind of waste and uncontrolled landfills. Moreover, the stations of our study area experiencing heavy pollution in indicators of domestic contamination, are in agreement with those found by [19-20] for the Ziz high basin and of Rheris high basin. The groundwater is more vulnerable when the top of the water table is close to the ground surface and the rocks which demonstrated the aquifer permeability. 4. Conclusions The study has examined water quality of groundwater in Guir high Basin. The application of hydrochemical and statistical tools has shown significant links between the different chemical elements in the ten stations studied. The Principal Component Analysis (PCA) method allows identifying four classes in sampling stations. It also showed that two factors account for almost 59% of the variance. Factor 1 is that of the nitrogenous salts (NH4+, NO3- and NO2-) whereas the factor 2 is that of pollution by mineral salts (Cl- and SO42-). The degradation of water quality in the aquifer of the Guir high basin is associated to geological and anthropogenic origins. References [1] Ministry of Territorial Development. Water and Environment, National Observatory of the Environment of Morocco; 2001; 2: 296–297. [2] A. Singh, J. Jayaram, M. Madou, S. Akbar, Pyrolysis of Negative Photoresists to Fabricate Carbon Structures for Microelectromechanical Systems and Electrochemical Applications. J Electrochem Soc., 149 (2002) E78–E83. [3] Margat J. Plan Blue. L’Eau des Méditerranéens : situation et perspectives, Athènes, PAM; 2004; 158: 403. [4] Guergazi S, Achour S. 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