Ijciet 10 02_092

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 02, February 2019, pp. 940-950, Article ID: IJCIET_10_02_092
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=02
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication Scopus Indexed
APPLICATION OF WATER QUALITY INDEX
(WQI) FOR THE ASSESSMENT OF NATURAL
SOURCES OF WATER IN RURAL AREAS OF
LAKE ALEG IN MAURITANIA
Yahya Maham Ould Sidi*
GEOPAC Center (GEOPHYSICS, NATURAL PATRIMONY AND GREEN CHEMISTRY)
Laboratory Geo Biodiversity National Heritage (LGBPN), Scientific Institute, Mohammed V
University of Rabat. Av Ibn Batouta, PO 703, 10106 Rabat - Morocco,
Assriya University of Nouakchott, Sciences and technologies Faculty,
880 Nouakchott, Mauritanie
Mohamed Fakhaoui, Abdlekbir Bellaouchou
GEOPAC Center (GEOPHYSICS, NATURAL PATRIMONY AND GREEN CHEMISTRY)
Laboratory Geo Biodiversity National Heritage (LGBPN), Scientific Institute, Mohammed V
University of Rabat. Av Ibn Batouta, PO 703, 10106 Rabat
M.S. Kankou and Brahim Ahmed DICK
Assriya University of Nouakchott, Sciences and technologies Faculty,
880 Nouakchott, Mauritanie
ABSTRACT
In Aleg, Mauritania, especially in the rural areas where there is no supply of
treated water for drinking and other domestic uses, natural surface water is the only
source. The objective was to assess the water quality of natural sources of water in
the rural areas of the BRAKNA region (in the south-west of the country) using a water
quality index (WQI) for different seasons. A total of 40 samples, that is, 20 in winter
and 20 in summer were collected from different sources for physicochemical analysis,
and a WQI was calculated. Twenty-seven parameters were evaluated (Rrgaonkar and
V. Deshpande et al. 2007).
Follow-up and physicochemical analyzes made it possible to determine the WQI
index. The results obtained show that raw water from Lake Aleg is classified in the
category "Unsuitable" (undesirable).
The overall quality of the waters is strongly influenced by the alternation of
seasons of the year. Correlation analysis showed a perfect correlation between WQI
and water turbidity (r = 0.999). This made it possible to specify the turbidity as a
factor of deterioration in the quality of the lake water

Application of Water Quality Index (Wqi) for the Assessment of Natural Sources of Water in
Rural Areas of Lake Aleg in Mauritania
The water quality of the natural sources indicated that the water is poor-quality
and not totally safe for human consumption, and that it needs treatment before
consumption.
Keywords: Natural sources of water, physicochemical parameters, water quality
index, Lake Aleg Mauritania (WQI).
Cite this Article: Yahya Maham Ould Sidi, Mohamed Fakhaoui, Abdlekbir
Bellaouchou, M.S. Kankou and Brahim Ahmed DICK, Application of Water Quality
Index (Wqi) for the Assessment of Natural Sources of Water in Rural Areas of Lake
Aleg in Mauritania, International Journal of Civil Engineering and Technology,
10(2), 2019, pp. 940-950.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=02
1. INTRODUCTION
Water resources play an important role in the development of different sectors in different
countries. Indeed, surface water can be used for various needs: drinking water supply,
irrigation, etc. (E. OuldMohamedou et al. 2009). In Mauritania, Lake Aleg occupies an
important place in fresh surface water sources. However, the filling dynamics of Lake Aleg
depend directly on the intermittent flows of the KETCHI valley, which represents the largest
endorheic stream in the BRAKNA region, these flows occur only during the rainy season.
from July to October. The water ends in the lake, which is a shallow depression (Yi Li† and
Xianze Liu 2018). This source plays a key role in the water supply in several localities in the
BRAKNA region (in the south-west of the country) (Al-Nakshaband et al. 2007). It is an area
characterized by an arid and dry climate. For many years, this lake has been exposed to
constraints that threaten the physicochemical quality of its waters (Lado, M. and Ben-Hur, M.
2009).
The objective of this work is the Determination of the overall water quality index for the
assessment of the raw water quality of the lake for the spatiotemporal variation of the water
quality of Lake Aleg. Indeed, several samplings were organized during the year 2017.
The water quality index will be applied to assess the overall quality of the water. In
addition, a statistical analysis is used to investigate the origin of evolution and change and the
overall quality of water (Katarzyna Glińska-Lewczu, 2016).
2. MATERIALS AND METHODS
2.1. STUDY AREA
Lake Aleg is located in the Brakna region of southwest Mauritania (Fig1). This zone is
characterized by a hot Saharan-Sahelian climate with a dry season that lasts 8 months (from
November to June) (Fatimetou Salma et al 2017). The wintering or rainy season that follows
is generally four months, with a peak of rainfall in August (250-400 mm of rainfall /year)
(Kankou M.O.S.O. 2004).

Yahya Maham Ould Sidi, Mohamed Fakhaoui, Abdlekbir Bellaouchou, M.S. Kankou and Brahim
Ahmed DICK
Figure 1 Location of Lake Aleg in the regional context of southwestern Mauritania.
2.2. Water sampling and analytical procedures
This work focuses on the evaluation of 27 parameters. Sampling and analysis took place
according to the methods described by Rodier (Z. NOUACEUR 2009). Table1 summarizes
the sampling sites and their GPS (Garmin 78) coordinates. Fig2 shows the study area and
location of sampling sites along the perimeter of Lake Aleg. Samples took place in different
seasons of the year. Samples were collected using 1 liter bottles.
Figure 2 Location of sampling sites [11]

Table 1 sampling sites and their GPS coordinates of Lake Aleg in Mauritania
Local Name
Coordinate
Withadrawal code
X (N) Y (W0)
1 Mechraa 17088131398435 Alg 01
2 Akreraye 17091191398634 Alg 02
3 Mechraaveived 17104791398811 Alg 03
4 Dwalek 17119131399449 Alg 04
5 Mechraaelbel 17144391402297 Alg 05
6 Enegabe 17140331403505 Alg 06
7
Mechraa
Levreiwatt1
17134301404510 Alg 07
8
Mechraa
Levreiwatt2
17125451403948 Alg 08
9 MechraaLehjare 17110191401345 Alg 09
10 Avreiraye 17088441399225 Alg 10
The water temperature and pH were measured using a HANNA pH meter (HI 8314).
Electrical conductivity was determined using a HANNA type conductivity meter (HI 8733).
Turbidity was measured using a HANNA turbidimeter (HI 2100). Nitrates, nitrites,
ammonium, sulphates, iron, copper and aluminum are determined by a UV-Visible
Spectrophotometer (WEG 7100). The alkali metals (Na+
K +
) are determined by flame
photometer. Alkalinity (TA, TAC), total hardness (TH), calcium (Ca2+
), magnesium (Mg2+
),
chloride (Cl-
), oxidability, Bicarbonates (HCO3-) are determined by the volumetric method
(Andreu et al.).
2.3. Water Quality Index (WQI)
The method proposed by Tiwari and Mishra (Katarzyna Glińska-Lewczu, 2016) has been
applied for the assessment of the Water Quality Index (WQI). The standards (Si) are those
recommended by WHO (World Health Organization). The table summarizes the relative
weights (Wi) calculated by the equation.
Calculates the water quality index:
WQI =
1
100
[∑(qi
. 𝑤𝑖)
𝑛
𝑖=1
]
2
𝑛 - number of sub-indices aggregated,
qi
– quality rating, expressed as the 0 - 100 sub-index rating for each variable
𝑤𝑖 – weight of each individual parameter
According to the water quality index (WQI) values, the water quality is classified
according to Table 2.
Table 2 Water quality classification based on WQI value
WQI 0-25 26-50 51-75 76-100 >100
Water quality Excellent Good Poor Very poor Unsuitable

Ahmed DICK
2.4. General characterization
The results obtained are summarized in Table 3. In fact, the pH records average values of
7.42 and 7.46. The temperature of the water changes according to the climatic conditions of
the sampling site. The electrical conductivity shows average values of 452.2 μs / cm in the
dry season and 169.58 μs / cm in the rainy season. The effect of dilutions is noted on the
values obtained.
Table 3 Results obtained for physico-chemical analyzes of lake water for both seasons
pH
T CE
Turbidi
té
HCO
3-
Ca2
+
Mg2
+ TH Cl- SO4
2-
NO
3-
Oxydabil
ite
(°C)
µs/c
m
NTU mg/l mg/l mg/l °F mg/l mg/l mg/l mg/l
Saiso
n
sèche
Max
7.6
2
24.0
0
702.0
0
771.00
341.6
0
54.5
0
45.2
0
12.2
0
102.9
5
61.0
0
15.0
0
1.22
Min
7.0
2
20.0
0
339.0
0
141.00
189.1
0
16.0
3
19.4
4
5.20 17.75 9.00 3.80 0.19
Moy
7.4
2
23.2
8
452.2
0
466.60
240.6
5
35.7
5
29.1
6
7.50 41.54
28.3
0
9.54 0.51
Ecarty
pe
0.2
1
1.22
124.0
1
212.63 56.16
10.5
8
9.47 2.21 27.55
20.5
7
3.77 0.30
Saiso
n de
pluie
Min
7.1
5
30.1
0
67.00 331.00 36.60
10.4
2
5.83 2.20 7.10 1.00 0.20 8.76
Max
7.6
5
30.3
0
259.0
0
912.00
115.9
0
32.8
6
17.4
9
9.60 28.40
41.0
0
2.00 22.40
Moy
7.4
6
30.2
3
169.5
8
657.67 76.76
21.5
6
12.1
5
5.78 15.38
14.9
2
0.71 15.94
Ecarty
pe
0.1
9
0.07 69.90 202.75 29.21 7.71 3.93 2.11 5.99
14.8
9
0.50 4.91
NH4+
NO2-
TAC Al
Fe
Total
Cu Na+
K+
Pb Cd Mn
mg/l mg/l mg/l mg/l mg/l mg/l mg/l mg/l µg/l µg/l mg/l
Saison sèche
Max 0.40 1.60 27.50 0.13 2.20 0.62 51.00 35.00 1.52 0.17 0.01
Min - 0.05 10.50 0.02 0.60 0.14 25.00 20.00 0.32 0.04 0.01
Moy 0.14 0.48 18.78 0.05 1.32 0.30 32.00 24.40 0.91 0.08 0.01
Ecartype 0.16 0.48 5.24 0.03 0.53 0.15 9.06 5.10 0.33 0.05 0.00
Saison de
pluie
Min - 0.01 2.50 0.01 0.06 0.04 12.00 9.00 0.29 0.04 -
Max 0.22 0.18 9.00 0.40 0.70 1.15 26.00 18.00 1.43 0.14 0.01
Moy 0.04 0.07 5.79 0.09 0.24 0.35 16.83 12.50 0.85 0.07 0.00
Ecartype 0.07 0.05 2.39 0.12 0.21 0.38 5.30 3.13 0.32 0.03 0.00
The turbidity evolves according to seasonal variations; the maximum values are in the
order of 912 NTU. Bicarbonates have a maximum level of 341.6 mg / l during the dry season.
The hardness shows an acceptable level in the study period, the TH varies between 7.5 and
5.7 ° F. Alkalinity shows a maximum value during the dry season. The chloride, Sulphate,
sodium and potassium contents indicate acceptable values.
There are also low levels for nitrogen elements, nitrates, nitrites and ammonium
respectively record maximum values of 15, 1.6 and 0.4 mg / l. The oxidability registers

maximum values during the rainy season 22.4 mg / l of O2. Metal trace elements remain
below the limits required by WHO (Josué Esdras et al 2017).
2.5. Evaluation of the spatiotemporal variability of the WQI index
The application of equations (1) to the analytical data allowed the determination of
spatiotemporal trends of the water quality index (WQI) (Fig; 3)
Figure 3 Evolution of WQI (WQI 1: Dry season, WQI 1: Rain season)
3. RESULTS AND DISCUSSION
The results obtained show that for the dry season, the values of WQI are between 668-3541,
while for the rainy season, the values oscillate between 1584 -4272. In fact, it is noted that the
Alg10 site records maximum values during the rainy season. However, the Alg 6 site presents
the maximum values during the dry season. It can be noted that, in general, the values
obtained for the WQI are very high. This can be interpreted in the context of the study of
turbidity evolution. The two minimum values are obtained in sites Alg 6 (rainy season) and
Alg 7 (dry season). The values obtained for the WQI are very high (greater than 100). The
water quality of Lake Aleg is classified in the category Unsuitable (Table 4). The calculation
of the WQI index shows a significant change in overall water quality during the rainy season.
(Tahera Akter1 et al, 2016).
Table 4 Descriptive statistics for the Water Quality Index (WQI)
Saison Min Moy Max SD
Dry period 668.41 2151.86 3541.40 970.78
Wet period 1584.67 3123.36 4272.72 934.32
3.1. Statistical analysis
A statistical evaluation was carried out for the interpretation of the results obtained, and in
order to highlight the correlations between the different parameters. The tests are carried out
by the Origin 8.5 and SPSS 20 software.
3.2. Principal Component Analysis (PCA)
ACP is a widely used technique for interpreting the different parameters influencing the
quality of water resources. Based on the eigenvalue graph (fig 4), it is possible to extract the
first five components that represent 93.74% of the total variance (Table 5). The three-
dimensional projection of the first three components representing 81.5%

Ahmed DICK
Figure 4 eigenvalue graph and component diagram
Table 5 initial eigenvalues
Com Composante
Initial Eigenvalues
Total % de la variance % cumulés
1 5.516 39.399 39.399
2 3.660 26.141 65.540
3 2.243 16.025 81.565
4 .945 6.752 88.317
5 .760 5.427 93.743
6 .407 2.907 96.651
7 .299 2.139 98.789
8 .112 .801 99.590
9 .057 .410 100.000
10 4.618E-16 3.299E-15 100.000
11 1.479E-16 1.057E-15 100.000
12 4.598E-17 3.284E-16 100.000
13 -2.437E-16 -1.740E-15 100.000
14 -3.185E-16 -2.275E-15 100.000

Component 1 includes electrical conductivity, bicarbonates, calcium, magnesium,
hardness, chlorides and nitrites (Table 6). PH, temperature, sulphates and nitrates are
correlated with component 2. However, turbidity and oxidizable matter are included in
component 3.
Table 6 Correlation between the First Three
Component
1 2 3
pH .113 .930 .161
TE -.157 .747 .243
CE .961 .024 .011
TU .099 .154 .919
BIC .840 -.418 -.258
Ca .814 -.363 .074
Mg .908 .168 .063
TH .963 -.051 -.101
Cl .871 .318 .167
SO4 -.206 -.850 -.186
NO3 .250 -.663 .210
MO -.220 .077 .713
NO2 -.616 .383 -.575
WQI .097 .157 .919
3.3. Correlation Analysis
Table 7 summarizes the parameters that were considered. The Pearson correlation
coefficients show the consistency of the results obtained. The table shows good positive
correlations between WQI and turbidity (0.999). PH shows a negative correlation with sulfate
(-0.868). However, the temperature is negatively correlated with bicarbonates (-0.542) and
sulphates (-0.527). Electrical conductivity shows significant correlations with bicarbonates
(0.809), calcium (0.699), magnesium (0.852), chlorides (0.915) and nitrites (-0.566). Nitrates
and nitrites are negatively correlated (-0.604). These correlation analyzes, the WQI is
controlled by fluctuations in turbidity values ( Tahera Akter1 et al 2016).
Table 7 Correlation Matrix
pH TE CE TU BIC Ca Mg TH Cl SO4
NO
3
MO
NO
2
WQ
I
Corrélati
on
pH
1.00
0
TE .784
1.00
0
CO .097
-
.221
1.00
0
TU .287 .288 .170
1.00
0
BI
C
-
.331
-
.542
.809
-
.182
1.00
0

Ahmed DICK
pH TE CE TU BIC Ca Mg TH Cl SO4
NO
3
MO
NO
2
WQ
I
Ca
-
.212
-
.269
.699 .078 .804
1.00
0
Mg .284 .083 .852 .119 .595 .660
1.00
0
TH .059
-
.175
.881
-
.045
.855 .886 .836
1.00
0
Cl .344 .015 .915 .334 .595 .531 .784 .776
1.00
0
SO
4
-
.868
-
.527
-
.166
-
.236
.230 .145
-
.342
-
.150
-
.460
1.00
0
NO
3
-
.374
-
.275
.101 .033 .405 .494 .232 .264
-
.147
.371
1.00
0
MO .118 .158
-
.257
.470
-
.428
-
.086
-
.160
-
.181
-
.037
-
.296
-
.052
1.00
0
NO
2
.198 .203
-
.566
-
.438
-
.491
-
.594
-
.620
-
.530
-
.497
-
.042
-
.604
-
.306
1.00
0
W
QI
.290 .290 .168
1.00
0
-
.185
.076 .117
-
.047
.333
-
.239
.030 .470
-
.435
1.00
0
4. CONCLUSIONS
Here, we report that water of Lake Aleg in Mauritania was mainly alkaline with pH values
within acceptable limits. According to WHO standards, the results obtained as part of this
work made it possible to highlight the seasonal variation of the WQI index. The values
obtained are between 668 and 3541 for the dry season. However, these values vary from 1584
to 4272 the rainy season.
These results make it possible to classify water in the category (Unsuitable). The ACP
shows that it is possible to extract the first five components, which represent 93.74% of the
total variance. The three-dimensional projection of the first three components represents
81.5% of the total variance. Correlation analysis showed a perfect correlation between WQI
and water turbidity.
It is recommended that more surveys be conducted covering more areas, to develop water
treatment and purification plants in specific locations, and to propagate public health
education. The results of this study are expected to be a helpful tool for the public and for
water quality management.
ABBREVIATIONS
Aleg: areas of the BRAKNA region (in the south-west of the Mauritania) ,EPE:Pollution
and Environment Unit, GEOPAC: Center (geophysics, natural patrimony and green
chemistry) KETCHI:the largest river that feeds Lake Aleg, WHO :World Health
Organization, ACP: is a widely used technique for interpreting the different parameters , Fe:
iron; IQR: interquartile range; MDG: Millennium Development Goals; Mn: manganese;
NaCl: sodium chloride; WASH: Water, Sanitation andHygiene;; WQI: Water Quality Index.

ACKNOWLEDGEMENTS
We would like to thank the respondents who provided valuable information and time for this
study. We thank all the interviewers involved in the data collection and the field staff for their
assistance in conducting this study.
We acknowledge the Data Management EPE Unit for their support in data entry and
cleaning. Finally, we acknowledge the Government of the Mauritania for funding the study.
We thank the direction of scientific research at the level of our Ministry of Higher Education
and Scientific Research of Mauritania (www.mesrs.mr/fr/) for editorial assistance.
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