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SN Applied Sciences

, 1:1389 | Cite as

Assessment of groundwater quality in Bamenda–Cameroon for suitable applications

  • Akoanung A. AbendongEmail author
  • Endene Emmanuel
  • Enoh Jeanot Fongoh
  • Akoachere Richard Ayuk II
Research Article
  • 80 Downloads
Part of the following topical collections:
  1. 2. Earth and Environmental Sciences (general)

Abstract

Groundwater quality of the Bamenda metropolis (Northwest Region—Cameroon) was assessed for its suitability for possible uses. A total of 22 groundwater samples were collected from dug wells and boreholes within the Bamenda town during the wet and dry seasons. Hydrodynamics and physicochemical parameters were measured. Other parameters including, major ions, sodium percentage (Na %), sodium adsorption ratio (SAR), and water quality index (WQI) were deduced from chemical analysis, and their distributions were demonstrated using spatial distribution contour maps. Durov’s plot, Gibbs diagram, and chloro-alkaline indices were used to deduce the source and detect the groundwater samples for different applications. The findings indicate that groundwater flows in the study area from shallow to deep aquifers. Piper’s plot shows Ca–Mg–CO3–HCO3 and Ca–Mg–Cl–SO4 as the main water types. WQI and World Health Organization (WHO) guidelines show that all the groundwater samples have excellent water quality for drinking purpose. Electrical conductivity (EC), Na %, and SAR values indicate that all wet season water samples are of low-salinity class, whereas dry season samples are of low to medium salinity; hence, all the samples are suitable for irrigation. Though there is extensive use of agricultural fertilizers and intense urbanization in the metropolis, anthropogenic activities, for now, seem to have minimal impact on the quality of groundwater.

Keywords

Groundwater Bamenda–Cameroon Physicochemical analysis Water quality index Suitability 

1 Introduction

Groundwater is one of the natural resources available for humanities. Its exploitation and utilization have been noted in both developed and developing countries. It plays a vital role in sustainable and socioeconomic development as it is required for livelihood, industrial growth, public health, economic development, and food security [1]. Groundwater is historically considered the most reliable source of water regarding its quality [2]. However, increasing population, unplanned urbanization, industrialization, and agricultural intensification globally pose potential threats to groundwater reserves by altering the consumption pattern and degrading the quality [3].

In many developing countries with deplorable housing and infrastructures as well as inadequate waste disposal facilities and pipe-borne water supply; pushes the population to depend mainly on groundwater resources as their main water supply for domestic, irrigation, and industrial purpose. The literature indicates that approximately 80% of the population in developing countries utilizes groundwater as their main source for drinking and domestic needs [4, 5]. Likewise, Siebert et al. [6] cited that groundwater accounts for 43% of the irrigation water use and is more suitable for irrigation purpose relative to surface water. While Cameroon has generally made substantial progress in the provision of safe and potable water, the country still faces problems in addressing water supply in rural and informal settlements as well as densely populated areas. Like many other developing countries, Cameroon depends on groundwater as a source for domestic, agricultural, and industrial water supply, especially the population residing in fast-growing industrialized and densely populated towns like Bamenda. Unfortunately, degradation of the quality of groundwater is one of the major challenges encountered in such a metropolis.

Bamenda, being the capital of the North West Region of Cameroon, is inhabited by people of diverse cultures whose major activities are agriculture and animal husbandry. The daily activities of the inhabitants are highly aided by the use of groundwater, due to the inadequate piped water supply. With the problem of scarce pipe-borne water supply and limited surface water resources, the demands of the population are met only by the exploitation of groundwater from open dug wells and springs which is comparatively cleaner and free from pollution relative to surface water. Nevertheless, the ever-increasing population, poor sanitation, excessive use of fertilizers and pesticides in agriculture, poor sewerage system, and improper effluent disposal facilities within the metropolis pose potential threats to the groundwater reserves, resulting in health problems.

Even though the groundwater resources in the Bamenda metropolis are serving the population domestically, agriculturally, and industrially, there are still no water quality monitoring systems, no aquifer, and wellhead protection zones for groundwater quality protection. This, therefore, remains a threat both to the aquifer and to the population. Hence, proper monitoring and analysis of groundwater within the metropolis are of paramount importance to ensure a sustainable supply of the resource. Lack of data for groundwater quality in the study area makes investigating the aforementioned groundwater chemistry extremely important to determine its health impact on the population. Likewise, producing spatial variation maps of the major physicochemical parameters for groundwater in Bamenda is essential for sustainable development and managing of groundwater resources. In an attempt to address these voids, a baseline study was conducted in Bamenda–Cameroon to determine the physicochemical properties of groundwater for suitable uses. Piper’s plot, Gibbs diagram, spatial variation maps of major physicochemical parameters, water quality index (WQI), extended Durov plot, as well as seasonal groundwater contour maps and flow models, were employed to characterize the water based on their wide usage and general acceptability [2, 6]. Findings from this study will not only contribute in improving the understanding of the factors controlling groundwater quality in Bamenda but will also provide groundwater quality data in the study area with emphasis on parameters that have not been addressed before, thus contributing to sustainable development and management of groundwater resources within Bamenda metropolis. The findings will also provide safer information to the population on the quality of drinking and irrigation water from the wells and springs.

2 Description of the study area

2.1 Location and climate of the study area

The study area (Bamenda) is situated in Mezam Division in the North West Region of Cameroon, precisely at the central part of the Cameroon Volcanic Line (CVL) and is implanted below the high lava plateau, at an altitude of about 1100–1500 m above sea level [7]. The climate is mainly of the equatorial monsoonal type characterized by high rainfall and relative humidity with two main seasons: a long rainy (wet) season lasting for 7.5 months from mid-March to early November, with approximately > 45% chance of a given day being wet, while the dry season lasts for 4.5 months from early November to mid-March. The annual average precipitation ranges from 1700 to 2824 mm and exhibits fluctuations [8, 9].

2.2 Geology and hydrogeology of the study area

The geology of the study area has been described in detail by Morin [10]. The scholar indicated that Bamenda belongs to the West Cameroon Highlands, the most important geomorphologic system in the region. The study area constitutes part of the Bamenda Mountains which is made up of a basement rock comprised mainly of leucogranite of Precambrian age, with the basement rock overlain by volcanic materials composed of mafic and felsic lavas [11]. The mafic lavas comprise of basalts which outcrop as lava flows and pyroclastic deposits, while the felsic lavas include trachytes, phonolites, and rhyolites [12]. These felsic lavas originate through fractional crystallization from mafic magmas, with crustal contamination. Chemical weathering of the basement and the resulting volcanic rocks (from felsic and mafic lavas) produced thick unconsoliated sediments consisting mainly of clay to sand-sized particles [13] with the major clay minerals being montmorillonite (smectite), while cristobalite, feldspars, ilmenite, and heulandite constitute the accessory minerals [14]. The Online Resource shows the geological map of Bamenda with the major lithologies.

The study area is characterized by fractured phreatic aquiferous formations found within the hard rock system, and the aquifer types are defined as being superimposed or isolated [15]. The weathered basement (regolith) and alkali-rich fluvial sediments constitute the aquiferous materials in the area. Percolation of water through the unconsolidated sediments forms the groundwater aquifer system with depths < 30 m below the surface [16].

3 Field and experimental program

3.1 Fieldwork

3.1.1 Water sample collection

The fieldwork was conducted in two campaigns (wet and dry seasons), to have a better understanding of the variations of the groundwater quality during both seasons. A total of 22 sites (18 hand-dug wells and 4 boreholes) were sampled for both campaigns. Permission to conduct the study at the selected locations was sought from relevant authorities. The sampling technique employed was the stratified grid sampling method based on access and rate of utilization of the wells, boreholes, and springs. Water sample collection constituted water being drawn from the open dug wells using a bucket tied to a rope, while boreholes were pumped for 10–20 min before sampling to prevent non-representative samples and polluted water. Three (3) sets of water samples were obtained from each water source. The first set was untreated sample for the determination of the pH, electrical conductivity (EC), and temperature with the use of a pH and EC meters as well as a thermometer, respectively. The second set was filtered untreated for the determination of anionic concentrations, and the last set was acidified (1:1 dilute nitric acid) for cationic concentrations.

The sample containers (0.35-liter plastic bottles) were cleaned with hydrochloric acid and then washed with tap water to render it free of acid, and later washed with distilled water and finally rinsed with the sampled water. Field filtration was carried out through acetate cellulose filter papers with a pore size of 0.45 µm to remove any suspended solids before being transferred into the containers and tightly closed in order to avoid evaporation. The samples were then sealed, labeled, and transported to the laboratory of the Agronomical Institute of Research and Development (IRAD) Ekona–Cameroon for chemical analysis. Prior to analysis, the samples were kept in a refrigerator at an operating temperature range of 7–10 °C. This procedure was adopted to prevent or minimize any chemical and biochemical reactions. Figure 1 depicts the sample site within the study area.
Fig. 1

Map of Bamenda with sample sites indicated

3.1.2 Determination of physical parameters

The design of the dug wells varied from one site to another. They were characterized by varied collars, aprons, lids, and angles of inclination. The wells had been developed over 2–15 years. In all cases, the tested wells were characterized by radii ranging from 0.3 to 0.55 m and depths ranging from 1.51 to 9.76 m. At each well site, coordinates of the site were recorded with the aid of a GPS, and the in situ physical parameters (EC, pH, and temperature) of the well and borehole waters were measured.

3.2 Laboratory work

The laboratory work involved the determination of the major cations and anions present in the water samples. The analyses were done at the Agronomical Institute of Research and Development (IRAD) laboratory Ekona–Cameroon. Sodium ions (Na+), potassium ions (K+), calcium ions (Ca2+), magnesium ion (Mg2+), and ammonium ion (NH4+) were the major cations determined. Sodium ions (Na+) and potassium ions (K+) were determined using the flame photometry technique, according to standard procedures outlined in Chikhale and Pratibha [18]. Calcium ions (Ca2+) were determined by titration with a 0.02 M standardized solution of Ca – EDTA which combines with 1 ml of TEA and 1 ml of 5% KCN. Magnesium ions (Mg2+) and ammonium ions (NH4+) were analyzed using the calorimetric method. Major anions such as bicarbonate ion (HCO3) and chloride ion (Cl) were determined by titration. The nitrate ion (NO3) and phosphate ions (PO4) were determined by calorimetry, and the sulfate ion (SO42−) was analyzed by turbidimetry.

3.3 Data synthesis

Analysis of data was done with the use of geological and statistical software packages including AQUA-CHEM 2012.1, Surfer 12, Global mapper 15, and Microsoft Excel 2016. Detailed discussion on the process and math mechanisms of these software packages can be found on their user guides. AQUA-CHEM was employed to construct ternary diagrams (Piper, extended Durov, Gibbs diagrams, and USSL diagrams) to determine the water types. The sampling locations and spatial distribution maps were prepared using Surfer 12. Global mapper was employed for georeferencing the base map. Microsoft Excel 2016 was used to statistically analyze the data, including the means, ranges, and standard deviations of the water quality data.

3.3.1 Water quality for drinking

In order to assess the water samples for drinking, World Health Organization (WHO) 2004 [19] guidelines and water quality index (WQI) as described by Ravikumar [20] were used.

3.3.1.1 Water quality index
The WQI was determined using Eq. (1):
$${\text{WQI}} = {{\sum\nolimits_{i = 1}^{n} {W_{i} q_{i} } } \mathord{\left/ {\vphantom {{\sum\nolimits_{i = 1}^{n} {W_{i} q_{i} } } {\sum\nolimits_{i = 1}^{n} {W_{i} } }}} \right. \kern-0pt} {\sum\nolimits_{i = 1}^{n} {W_{i} } }}$$
(1)
where
$$W_{i} = {\raise0.7ex\hbox{$K$} \!\mathord{\left/ {\vphantom {K {S_{n} }}}\right.\kern-0pt} \!\lower0.7ex\hbox{${S_{n} }$}}$$
(2)
Wi = weightage factor of the ith parameter.
$$K = \left[ {\sum\limits_{i = 1}^{n} {S_{n}^{ - 1} } } \right]^{ - 1}$$
(3)
K = constant of proportionality, n = number of parameters, Sn = sum of the standard permissible value of the ith parameter.
$$q_{i} = \left[ {\left( {V_{\text{actual}} - V_{\text{ideal}} } \right)/\left( {V_{\text{standard}} - V_{\text{ideal}} } \right)} \right] \times 100$$
(4)
qi = quality rating based on the concentration of ith parameter, Vactual = estimated value of the ith parameter from laboratory analysis, Vstandard = WHO (2004), prescribed guideline permissible value of the ith parameter in mg/l except for conductivity (µS/cm) and pH.Videal = ideal value of the ith parameter in pure water (pH = 7 and for the other parameters it is equivalent to zero).

3.3.2 Water for irrigation purpose

To evaluate the suitability of groundwater for irrigation purpose, sodium adsorption ratio (SAR), sodium percentage (Na %), and EC measurements were obtained. The aforementioned parameters are defined by Eqs. (5) and (6).
$${\text{SAR}} \left( {{\text{meq}}/l} \right) = \frac{{{\text{Na}}^{ + } }}{{\left( {{\text{Ca}}^{2 + } {\text{Mg}}^{2 + } } \right)^{0.5} }}$$
(5)
$${\text{Na}}\% = \frac{{\left( {{\text{Na}}^{ + } + {\text{K}}^{ + } } \right)}}{{\left( {{\text{K}}^{ + } + {\text{Mg}}^{2 + } {\text{Ca}}^{2 + } {\text{Na}}^{ + } } \right)}}$$
(6)

4 Results and discussion

4.1 Groundwater level and aquifer flow paths

The measured depths to water level in the wells varied from 1.12 to 9.27 m with higher water levels in the center and northeastern parts of the study area. The measured well depths varied from 1.52 to 9.76 m with deeper wells observed in areas with higher water levels. From the measured depths to water levels and well depths, groundwater level contour and flow maps of the study area were incorporated to ascertain the flow direction. Locations with higher altitude showed high water elevation relative to the surrounding low-altitude locations.

The groundwater level and aquifer flow path maps for both wet and dry seasons in the study area are presented in Fig. 2a, b, respectively. Both maps indicate that the flow of groundwater in the study area is generally from shallow aquifers (northwestern part) toward the deeper aquifers (center and northeastern parts) with higher elevations relative to their surrounding areas. Groundwater flow is, therefore, a function of the groundwater table and elevation since water flows from higher to lower water levels above mean sea level. This flow direction agrees with the drainage pattern of the main river and streams in the study area, as depicted in Fig. 1. Based on this, it is evident that the centre and northeastern parts of the study area experience large exploitation of groundwater for drinking, domestic, and irrigation uses evidenced by the high density of dug wells in these areas which are characterized by high urbanization and industrial activities.
Fig. 2

Water level and flow direction maps within the study area a wet season; b dry season

According to Wirmvem et al. [21], areas with higher water levels are associated with higher elevations as a result of groundwater discharge at such high elevations through joints from some likely perched aquifer systems. Ako et al. [22] further cited that the use of altitudes and water levels from wells gives a better flow path and direction of groundwater flow. Ako et al. [22] showed that contaminant exposure pathways generally follow the groundwater route, and they also indicated that topography plays a major role in groundwater flow.

4.2 Physical properties

Water temperatures were slightly lower during the wet season relative to the dry season for almost all sampled points (see Tables 1, 2). The pH of the groundwater ranged between 4.8 and 7.6, with a mean value of 5.71 in the wet season (see Table 3). Similarly, in the dry season, the pH ranged between 5.20 and 9.50 with a mean value of 7.40 (see Table 3).
Table 1

Variations of physicochemical parameters and ions in the wet season for each sample location

Sample locations

Temp

pH

EC

Na+

K+

Ca2+

Mg2+

NH4+

HCO3

NO3

SO42−

Cl

HPO42−

TH

Nitob IV

22.4

5

90

0.28

2.28

10.88

4

0.43

10.98

0

0.32

18

0.02

43.60

Alamatson

23.2

5.6

10

0.18

1.56

4.36

0.51

0.65

19.52

2.43

0

6

0.02

12.99

Mile 7 Mankon

23.4

5.5

20

0.14

1.72

4.36

0.39

0.61

43.92

0

0.33

2

0

12.50

Mile 6 Mankon

22.6

5.7

60

0.14

1.17

4.36

0.51

0.42

15.86

0

0.31

2

0

12.99

Foncha Street 1

23.8

6.2

20

0.23

2.57

6.52

0.65

1.47

91.50

0

0.34

2

0.01

18.97

Foncha Street 2

25.6

5.6

40

0.18

1.17

6.52

0.61

0.65

18.30

0

1.20

0

0.01

18.80

Mile 4 Nkwen

24.2

5.7

100

0.51

5.46

17.40

2.06

0.2

32.94

0.23

0.63

6

0.01

51.95

Mile 6 Nkwen

22.9

6.1

160

0.28

2.89

13.04

5.64

0.34

36.60

0.21

0

1

0.02

55.72

Mile 3 Nkwen

22.5

6.3

110

0.18

1.72

6.52

2.71

0.39

62.22

0

0

4

0.01

27.41

Mile 2 Nkwen

23.8

6.1

240

0.37

4.06

13.04

4.21

0.1

100.04

4.11

2.12

14

0

49.86

Nitob III

24.3

5.1

180

0.64

8.19

21.76

7.95

0.53

17.08

1.23

0.68

16

0.02

87.00

Travelers

22.8

5

110

0.46

3.51

10.88

3.01

0

2.44

0

0

12

0

39.54

Mile 7 Nkwen

22.4

6.3

30

0.18

1.87

8.68

2.84

0.43

40.26

0

0

2

0.01

33.34

Church Center

23

6

60

0.23

1.56

8.68

4.48

0.41

14.64

0.10

0

8

0.01

40.07

Oldtown

23.1

5.6

6

0.23

2.73

10.88

6.21

0.41

12.20

0.10

0

1

0.03

52.66

Atuakom

23.2

5.1

190

0.46

4.45

17.40

7.32

0

0

0

1.45

12

0.02

73.51

Ntarinkon Br.

24.1

4.9

110

0.41

4.91

15.24

3.84

0.4

14.64

0

0

1

0

53.84

Ntarinkon KG

22.3

4.9

80

0.23

1.87

15.24

3.25

0

1.22

0

0

1

0

51.43

Alakuma

22.7

4.8

40

0.37

3.51

8.68

3.33

0.32

9.76

4.21

1.42

6

0

35.35

Mbinfebei

21.9

5.2

10

0.18

1.17

17.36

2.95

0.34

39.04

0.23

0.65

4

0.02

55.50

Upstation

26.1

7.4

10

0.30

3.2

14.80

4.10

0.24

42.90

0.90

0.70

5

0.01

53.81

Finance junction

25.8

7.6

40

0.25

2.86

13.26

2.74

0.2

40.05

0.55

0.71

6

0.01

44.38

All ions concentration and total hardness (TH) in mg/l

Table 2

Variations of physio-chemical parameters and ions in the dry season for each sample location

Sample locations

Temp

pH

EC

Na+

K+

Ca2+

Mg2+

NH4+

HCO3

NO3

SO42−

CL

HPO42−

TH

Nitob IV

23.9

8.3

100

0.35

3.71

14.36

6.15

0.81

8.54

0.31

0.14

16

0.02

61.12

Alamatson

24.9

7.2

10

0.18

2.05

10.76

4.53

0.3

18.3

0.4

1.69

2

0.02

45.47

Mile 7 Mankon

24.1

6.7

20

0.37

3.28

14.36

10.91

0.3

32.33

0

0.61

24

0

84.63

Mile 6 Mankon

23

6.8

40

0.16

1.64

10.77

9.81

0.2

16.47

0.01

0.55

2

0

67.15

Foncha Street 1

24

7.5

180

0.27

2.89

7.18

10.11

0.74

42.7

0.08

8.31

1

0.01

59.40

Foncha Street 2

26.2

7.4

9.8

0.16

1.25

10.78

3.73

2.02

14.64

0.59

10.17

1

0.02

42.24

Mile 4 Nkwen

25

9.5

170

0.32

3.28

17.94

5.43

4.21

18.3

0.81

7.17

4

0.05

67.11

Mile 6 Nkwen

23

8.1

70

0.46

2.89

14.36

4.06

0.84

6.1

0.92

0.24

22

0.03

52.55

Mile 3 Nkwen

26.8

8.3

110

0.14

1.64

3.68

5.21

0

53.64

0.21

5.88

9

0.03

30.56

Mile 2 Nkwen

23

8.4

200

0.25

1.64

10.78

5.04

0.66

26.23

0.63

0.11

17

0.04

47.61

Nitob III

24.7

6.4

140

0.51

6.98

14.36

4.06

0.84

7.93

0.92

0.24

1

0.03

52.55

Travelers

23.6

5.2

110

0.14

1.25

3.58

2.25

0.3

9.76

0.23

0.39

0

0.02

18.18

Mile 7 Nkwen

22.0

8

110

0.3

1.64

7.18

4.54

0.31

17.08

0.43

1.68

24

0.02

36.56

Church Center

23

6.9

490

0.76

6.55

28.72

4.87

0.21

0

0

0.21

64

0

91.77

Oldtown

24

8.3

30

0.12

1.64

7.18

1.33

0.31

1.22

0

0.11

4

0

23.40

Atuakom

23

7.4

370

0.51

6.16

14.36

2.81

2.7

0

0

0.2

30

0.01

47.42

Ntarinkon Br

25

6.5

110

0.74

8.62

25.12

2.7

0.41

0

0.31

1

20

0.01

73.87

Ntarinkon KG

23

5.8

60

0.14

1.64

7.18

4.35

0.45

0

0

0.23

8

0

35.79

Alakuma

22.5

7.5

70

0.25

3.38

14.36

2.68

0.35

0

0

0.23

4

0.01

46.89

Mbinfebei

22.4

7.3

10

0.16

2.07

10.78

4.21

0.65

53.68

2.87

0.63

6

0.02

44.21

Upstation

26.4

7.8

10

0.16

2.46

10.78

4.51

0.31

17.08

0.41

1.66

2

0.02

45.44

Finance junction

26.6

7.5

40

0.83

10.69

32.3

8.68

0

104.92

0

3.6

20

0.01

116.34

All ions concentration and total hardness (TH) in mg/l

Table 3

Summary of the physicochemical and water quality parameters for the sampled groundwater in both wet and dry seasons

 

Wet season

Dry season

Parameter

Max. value

Min. value

Mean value

Median. value

SD

Max. value

Min. value

Mean value

Median. value

SD

Temp

26.10

21.90

23.46

23.15

1.16

26.80

22.00

24.10

23.95

1.44

pH

7.60

4.80

5.71

5.60

0.76

9.50

5.20

7.40

7.45

0.96

EC

240.00

6.00

78.00

60.00

66.44

490.00

10.00

111.82

85.00

119.43

TDS

156.00

3.90

50.70

39.00

43.18

318.50

6.50

72.68

55.25

77.63

Na+

0.64

0.14

0.29

0.24

0.13

0.83

0.12

0.33

0.26

0.22

K+

8.19

1.17

2.93

2.65

1.71

10.69

1.25

3.52

2.68

2.61

Ca2+

21.76

4.36

11.36

10.88

4.92

32.30

3.58

13.22

10.78

7.37

Mg2+

7.95

0.39

3.33

3.13

2.14

10.91

1.33

5.09

4.52

2.59

NH4+

1.47

0.00

0.39

0.40

0.31

4.21

0.00

0.77

0.38

0.99

HCO3

100.04

0.00

30.28

18.91

26.80

104.92

0.00

20.41

15.56

25.04

NO3

4.21

0.00

0.65

0.05

1.27

2.87

0.00

0.42

0.27

0.63

SO42−

2.12

0.00

0.49

0.33

0.59

10.17

0.11

2.05

0.58

3.01

CL

18.00

0.00

5.86

4.50

5.31

64.00

0.00

12.77

7.00

18.02

HPO42−

0.03

0.00

0.01

0.01

0.01

0.05

0.00

0.02

0.02

0.01

TH

87.00

12.50

42.06

43.99

19.52

116.34

18.18

53.92

47.52

22.64

Na %

28.14

6.23

18.54

16.82

5.79

28.91

8.04

16.42

15.42

5.51

SAR

0.02

0.00

0.01

0.01

0.00

0.01

0.00

0.01

0.01

0.00

CAI 1

17.86

− 4.32

5.02

4.30

6.08

63.89

− 6.49

11.84

6.70

15.50

CAI 2

4.89

− 0.90

0.43

0.04

1.27

269.95

− 0.71

19.57

0.34

61.28

RSC

84.33

− 24.72

15.59

12.33

28.89

63.94

− 33.59

2.09

− 1.99

23.37

Na/Cl

0.41

0.02

0.10

0.06

0.10

0.51

0.01

0.08

0.03

0.12

WQI

15.06

0.41

3.40

1.58

3.75

13.26

0.36

4.44

4.37

2.91

Temperature in  °C; EC in µS/cm; ions concentration, TDS, RSC, and total hardness (TH) in mg/l

The electrical conductivity values were lower in the wet season with a maximum value of 240 µS/cm, minimum value of 6 µS/cm, and a mean value of 78 µS/cm and generally higher in the dry season with a maximum value of 490 µS/cm, minimum value of 9.8 µS/cm, and a mean value of 111.8 µS/cm.

4.2.1 pH of the groundwater

Figure 3a, b depicts the pH spatial variation map of groundwater in the wet and dry seasons of the study area, respectively. Various minerals and organic matter interact with each other, resulting in an increase or decrease in pH values [23]. The spatial variation map of the pH indicates that the groundwater of the study area is slightly acidic to basic in both wet and dry seasons, however, with higher alkalinity in the dry season. The highest pH values were recorded in the center and southeastern parts of the study area in the wet season; likewise, in the dry season the highest pH values were observed in the north and northeastern parts of the study area. The slightly acidic nature of the groundwater may be due to the formation and dissolution of minerals as well as the influenced of biochemical processes in solution [24]. On the other hand, the high pH values may be due to waste discharge and microbial decomposition of organic matter in the water body [25]. Ako et al. [22] obtained a similar range of pH values in groundwater sources along the Cameroon volcanic line, and they attributed the acidic nature of the waters to the presence of dissolved CO2 from root respiration, decay of organic matter in soils, or dissolution of carbonate minerals.
Fig. 3

Spatial variation map of pH for groundwater: a wet season; b dry season

Majority of the groundwater samples in the wet season failed to meet the permissible range (6.5–8.5) of pH for drinking water proposed by WHO [19], except for samples from Upstation and Finance junction. Conversely, the majority of the groundwater samples in the dry season are within the permissible range prescribed by WHO [19] for drinking water except for samples from Nitob III, Ntarinkon KG, and travelers.

4.2.2 Electrical conductivity of the groundwater

EC is a measure of the groundwater capacity to convey electric current. It indicates the amount of total dissolved salts in the groundwater, and it is a vital parameter for evaluating the purity of water. The spatial variation map of the groundwater EC for both wet and dry seasons in the study area is shown in Fig. 4a, b, respectively. It can be deduced that the conductance of the groundwater in both wet and dry seasons is a function of Ca2+ and Mg2+ cations as well as \({\text{HCO}}_{3}^{ - }\) and \({\text{Cl}}^{ - }\) anions concentrations. Thus, Ca2+, Mg2+, \({\text{HCO}}_{3}^{ - }\), and \({\text{Cl}}^{ - }\) are the ions dominating among salts constituting total dissolved salt amount. The EC values were lower in the wet season and generally higher in the dry season, thus indicating the presence of a high amount of dissolved inorganic substances in ionized form in the groundwater during the dry season relative to the wet season. The lowest EC was recorded at Oldtown in the wet season and Foncha Street 2 in the dry season, while the highest EC was recorded at Mile 2 Nkwen in the wet season and Church center in the dry season.
Fig. 4

Spatial variation map of EC for groundwater a wet season; b dry season

The spatial variation maps of the EC in both wet and dry seasons show that low elevations of the study area recorded high groundwater EC. High ECs were recorded in the center, north, and southern parts of the study area in the wet season. Similarly, in the dry season, high groundwater ECs were observed in the center and southern parts of the study area. The high ECs recorded in these areas may be due to the surface–groundwater interaction based on hydraulic conductance and groundwater level as well as the possible leaching of river water in the groundwater. Nonetheless, all the analyzed groundwater samples for both the wet and dry seasons in the study area are within the EC permissible limit (< 750 µS/cm) for drinking water prescribed by WHO [19].

4.2.3 Temperature of the groundwater

Temperature is one of the most vital properties of an aquatic system affecting the dissolved oxygen levels. Figure 5a, b depicts the interpolated spatial variation temperature map of the groundwater in both wet and dry seasons for the study area, respectively. Groundwater temperatures ranged between 21.90 and 26.10 °C in the wet season and 22.0–26.80 °C in the dry season. These low-temperature values suggest quick infiltration and shallow flow path [22]. Furthermore, it refutes any possibility of magmatic heating, as suggested in other volcanic areas [26]. Groundwater temperatures were generally higher during the dry season and lower in the wet season for all sampled locations with mean temperatures of 23.46 °C in the wet season and 24.10 °C in the dry season. The slightly high temperatures recorded in the dry season relative to the wet season might be due to overheating by the sun. Similar findings were reported by Magha et al. [27], when they investigated the physicochemical properties of some springs and well waters in Bamenda III–Cameroon.
Fig. 5

Spatial variation map of temperature for groundwater: a wet season; b dry season

The low mean groundwater temperatures relative to the air temperature (28.4 °C) suggest that the depth of circulation is short as in local systems and near recharge areas with quick infiltration [28]. Studies carried out by Gnazou et al. [29] in coastal aquifers in Togo (along the Gulf of Benin) indicated higher groundwater temperatures (29–34 °C) relative to lower air temperature (27 °C). The authors associated the behavior to the presence of confined aquifers with depths of 50 to ≥ 200 m. Following this, the lower mean groundwater temperatures relative to the mean air temperatures as observed can be associated with the unconfined nature of the aquiferous formation. This fact is supported by field observations where aquifers are typically shallow, unconfined, and characterized by depths of 1.52–9.76 m.

4.2.4 Total hardness (TH)

Hardness is a very significant property of water for domestic applications. Hardness of water is caused by the presence of alkaline earth metals, i.e., calcium and magnesium, and by a variety of other metals. It represents the total concentration of Ca2+ and Mg2+, indicated as calcium carbonate. That is, the amount of dissolved calcium and magnesium in water determines its hardness. The groundwater spatial variation maps of TH for both wet and dry seasons are presented in Fig. 6a, b, respectively. Likewise, the maximum, minimum, and mean concentrations of TH in groundwater from the study area are presented in Table 3.
Fig. 6

Spatial variation map of TH for groundwater: a wet season; b dry season

Although hardness of water is not considered a health risk, there is some suggestive evidence that long-term consumption of very hard water might lead to an increased incidence of urolithiasis, anencephaly, parental mortality, some types of cancer, and cardiovascular disorders [30]. Hardness of water is generally considered as total hardness (TH) and expressed by Eq. (7) after Todd [31].
$${\text{TH }} = \, 2.5{\text{Ca }} + \, 4.1{\text{Mg}}$$
(7)
where TH is the total hardness as CaCO3 in mg/l; Ca is the Ca2+ concentration in mg/l; and Mg is the Mg2+ concentration in mg/l.
Table 4 classifies the groundwater samples in the study area according to their hardness based on Dumfor and Becker [32] classification. The [19] guideline value for water for drinking purpose is 100 mg/l CaCO3, and all the groundwater samples of the study area in the wet season comply with this limit.
Table 4

Hardness of groundwaters in the study area

  

Wet season

Dry season

Hardness (mg/l CaCO3)

Water classification

Number of samples

%

Number of samples

%

0–75

Soft

21

95.45

19

86.36

75–150

Moderately hard

1

4.55

3

13.64

150–300

Hard

0

0

0

0

> 300

Very hard

0

0

0

0

Totals

 

22

 

22

 

4.3 Chemical properties

4.3.1 Cations

A summary of the chemical analysis of the 22 water samples indicating their highest, mean, and lowest cationic and anionic concentrations in both wet and dry seasons is presented in Table 3. Likewise, the individual concentrations of the cations and anions at each sampled location in both wet and dry seasons are presented in Tables 1 and 2, respectively. The dominant cation in the wet season in about 91% of the water samples is Ca2+, followed by Mg2+ and then by K+ and NH4+ (Table 3).

Likewise, in the dry season, the dominant cation was Ca2+ followed by Mg2+ and then by K+ and \({\text{NH}}_{4}^{ + }\). Na+ was the least abundant cation in the water samples during both wet and dry seasons (see Table 1, 2).

4.3.2 Anions

\({\text{HCO}}_{3}^{ - }\) is the most abundant anion present in about 86% of the groundwater samples in the wet season (see Table 1). The next abundant anion is \({\text{Cl}}^{ - }\) followed by \({\text{NO}}_{3}^{ - }\) and \({\text{HPO}}_{4}^{2 - }\) the least abundant anion in the water samples during the wet season.

\({\text{HPO}}_{4}^{2 - }\) and \({\text{NO}}_{3}^{ - }\) are barely detectable in the dry season (see Table 2). \({\text{HCO}}_{3}^{ - }\) and \({\text{Cl}}^{ - }\) are the most abundant anions detected in the dry season (see Table 2). The highest concentrations of \({\text{HCO}}_{3}^{ - }\) in the wet and dry seasons were recorded at Mile 2 Nkwen and Finance junction, respectively.

4.4 Hydrochemical facies

To understand the chemical facies of the groundwater in the study area, Piper’s plot (Fig. 7a, b) for the groundwater chemistry in both wet and dry seasons was generated. In both seasons, the major cations and anions in the groundwater samples presented similar facies of Ca–Mg–CO3–HCO3 and Ca–Mg–Cl–SO4. The similar facies indicate that there are no significant differences in the hydrochemical processes occurring within the aquifer during the dry and wet seasons, implying the mineralization processes occurring in both seasons are homogenous. Rock–water interactions, solution kinetics, geology, and contamination sources are the factors that determine hydrochemical facies [33]
Fig. 7

Piper’s plot for groundwater samples during: a wet season; b dry season. The major hydrogeochemical facies are Ca–Mg–CO3–HCO3 and Ca–Mg–Cl–SO4 (after Piper [34])

Gibbs diagrams were employed to reveal the main mechanism responsible for the chemistry of the groundwater. According to the Gibbs plot (Fig. 8a, b), the dominant mechanisms appear to be rock weathering followed by atmospheric precipitation with no dominance of evaporation and crystallization process. Moreover, it was found that mixed water types prevail in the study area as depicted in Durov diagram (Fig. 9a, b) in which 50% and 18% of the samples in the wet and dry seasons, respectively, plot along the dissolution or mixing line. Based on the classification of Lloyd and Heathcote [35], this trend can be attributed to recent fresh recharge water exhibiting simple dissolution or mixing. Also, a couple of samples (about 14% for the wet season and 36% for dry season) indicate that the groundwater is related to reverse ion exchange of Na–Cl waters. The remaining samples (about 36% for the wet season and 45% for dry season) are plotted in the ion-exchange field.
Fig. 8

Mechanisms controlling the chemistry of groundwater: a wet season and b for dry season (modified after Gibbs [38]). Red dots for cation ratio and green dots for anion ratio

Fig. 9

Extended Durov’s diagram with the various samples plotted at respective fields: a wet season and b dry season (after Durov [39])

[36] used Na/Cl molar ratios to study silicate weathering reactions and showed that Na/Cl molar ratio > 1 reflects Na+ released from silicate (feldspar) weathering in the process of exchange of magnesium and calcium in water with sodium and potassium in rock (cation–anion exchange reaction). The molar ratios of Na/Cl for groundwater sources ranged from 0.02 to 0.41 for the wet season and 0.01–0.55 for the dry season (Fig. 10a, b). The values being < 1 imply that another source is contributing the chloride to the groundwater other than silicate, most likely anthropogenic sources [37].
Fig. 10

Spatial variation map of Na/Cl for groundwater: a wet season; b dry season

4.4.1 Chloro-alkaline Indices

Two chloro-alkaline indices (CAI 1 and CAI 2) proposed by Schoeller [40] were computed to constrain the possible ion-exchange reactions between groundwater and the host aquifers. CAI 1 and CAI 2 were computed using Eqs. (8) and (9), respectively.
$${\text{CAI }}1 = {\text{Cl}} - \left( {{\text{Na}} + {\text{K}}} \right)/{\text{Cl}}$$
(8)
$${\text{CAI }}2 = {\text{Cl}} - \left( {{\text{Na}} + {\text{K}}} \right)/\left( {{\text{SO}}_{4} + {\text{HCO}}_{3} + {\text{CO}}_{3} + {\text{NO}}_{3} } \right)$$
(9)
18% and 32% of the samples in the wet season recorded negative values for CAI 1 and CAI 2 indices, respectively, whereas 82% and 68% showed positive indices for CAI 1 and CAI 2, respectively, in the wet season. About 14% and 27% of the samples in the dry season recorded negative values of CAI 1 and CAI 2 indices, respectively, while about 86% and 73% showed positive CAI 1 and CAI 2 values, respectively (Fig. 11a–d). The predominance of CAI 1 and CAI 2 values being positive suggests that Mg2+ and Ca2+ from water are exchanged with Na+ and K+ in rock favoring cation–anion exchange reactions [41]. The CAI ratio is negative when Na+ and K+ contents are high. This situation occurs when groundwater has strongly been in contact with minerals able to yield these interchangeable cations easily [42]. This exchange is common with alumino-silicated clays formed by layers whose cohesion is ensured by the existence of interlayer cations and water. The surface of the layers is negatively charged, thus promoting the possibility of cation exchange with those of groundwater.
Fig. 11

Spatial variation of CAI 1, CAI 2; a CAI 1 wet season; b CAI 1 dry season; c CAI 2 wet season; d CAI 2 dry season

On the other hand, if the exchange occurs between Ca2+ and Mg2+ in the groundwater with Na+ or K+ in the aquifer material, the index will result to a negative, indicating ion exchange [40, 43]. The values of CAI 1 and CAI 2 as mentioned earlier are positive in majority of the investigated water samples, thus suggesting an inverse reverse ion-exchange processes due to direct exchange of Ca2+ and Mg2+ from the aquifer matrix with Na+ and k+ from groundwater [43]. Hence, supports the fact that alkali earth elements are the most abundant.

4.5 Suitability for drinking purpose

The analytical results were evaluated to ascertain the suitability of groundwater in the study area for drinking purpose based on [19] recommendation as well as the calculated water quality index (WQI). Table 5 shows the range of parameters in the study in compliance with WHO guidelines. WQI is defined as a rating reflecting the composite influence of different water quality parameters on the overall quality of water. It indicates the quality of an index number, which represents the overall quality of water for any intended use [44]. Spatial distribution of WQI values plotted as an infinite element map (Fig. 12a, b) for both wet and dry seasons reveal values in the range of 0.41–15.06 for the wet season samples and 0.36–13.26 for the dry season samples. According to Ravikumar’s [20] classification, these values fall within the excellent quality class as the values are less than 25. Therefore, all water samples based on this criterion are considered excellent for human consumption. However, the pH and TH of the groundwater samples in some locations failed to meet the recommended limits prescribed by the WHO [19]. Notwithstanding, the authors are of the view that the high value of the TH in some locations should not be used as a basis to reject the groundwater in those locations for drinking purpose since hardness is not considered as a serious health risk.
Table 5

Groundwater quality parameters range within Bamenda in compliance with WHO [19] drinking water guidelines

Parameters

Range within Bamenda wet season

Range within Bamenda dry season

WHO limits

% Acceptability

pH

4.8–7.6

5.2–9.5*

6.5–8.5

90.9 and 13.6 unacceptable, respectively

EC

6–240

10–490

750

100% acceptable

TDS

3.9–156

6.5–319.5

500

100% acceptable

Na+

0.14–0.64

0.83

200

100% acceptable

K+

1.17–8.19

0.12–0.83

100

100% acceptable

Ca+

4.36–21.76

1.25–10.69

75

100% acceptable

Mg2+

0.39–7.95

3.58–32.3

30

100% acceptable

HCO3

0–100.04

1.33–10.91

200

100% acceptable

NO3

0–4.21

0–2.87

10

100% acceptable

SO42−

0–2.12

0.11–10.17

250

100% acceptable

CL

0–18

0–64

250

100% acceptable

TH

12.49–86.99

18.18–116.34*

100

4.5% unacceptable for wet season

*Parameters out of WHO-recommended limit

Fig. 12

Spatial variation map of WQI for groundwater a wet season; b dry season

4.6 Suitability for irrigation use

In the current study, groundwater suitability for irrigation purpose was assessed based on EC, SAR, Na %, and USSL.

4.6.1 EC and SAR

According to Richard’s [45] classification, SAR and EC values for irrigation water are classified into four groups: low (EC < 250 µS/cm, SAR < 10), medium (250–750 µS/cm, SAR, 10–18), high (750–2250 µS/cm, SAR, 18–26), and very high (2250–5000 µS/cm, SAR > 26). While a high salt concentration in water leads to the formation of saline soil, a high sodium concentration leads to the development of alkaline soil [22]. The sampled groundwater in the study area recorded EC values in the range 6–240 µS/cm and SAR values in the range 0.004–0.02 for the wet season; likewise for the dry season EC values were recorded in the range 10–490 µS/cm and SAR values in the range 0.03–0.01. Figures 4a, b and 13a, b depict the spatial variation maps for the EC and SAR, respectively. Thus, all wet season samples are of the low-salinity class, whereas dry season samples are of low to medium salinity according to Richard’s classification. As such, the groundwater is generally suitable for irrigation purpose based on their EC and SAR.
Fig. 13

Spatial variation map of SAR for groundwater: a wet season; b dry season

4.6.2 Na%

In all natural waters, Na % is a common parameter used to assess its suitability for agricultural purpose [46]. A high Na % causes deflocculation and impairment of the tilt and permeability of soils [22, 47]. For agriculture use, Na % of water should not exceed 60% [22]. Based on this criterion, all investigated groundwater samples for both wet and dry seasons in the study area are excellent for irrigation purpose as their Na % are less than 60%. Figure 14a, b, depicts the spatial variation map of Na % of the groundwater samples in both wet and dry seasons, respectively.
Fig. 14

Spatial variation map of Na % for groundwater: a wet season; b dry season

4.6.3 United States Salinity Laboratory (USSL) classification scheme

With respect to the United States Salinity Laboratory [48] classification. All the investigated samples plot in the C1S1 (low salinity and low sodium hazard) field for wet season (Fig. 15a). Likewise, for the dry season, 90.9% plots in the C1S1 field and 9.1% plots in the C2S1 (medium salinity and low alkalinity) field (Fig. 15b). Thus, all the investigated groundwater samples are suitable for irrigation application.
Fig. 15

Wilcox plot and USSL classification plot for irrigation suitability of groundwater within Bamenda: a wet season samples; b dry season (modified after Wilcox [46])

5 Summary and conclusions

Efforts have been made in the current study to evaluate the suitability of groundwater in the Bamenda metropolis for suitable applications. Twenty-two groundwater samples were collected from existing dug wells and boreholes, and their physicochemical properties were analyzed. Spatial variation maps of the physicochemical properties, as well as other water quality parameters, were generated. Assessment of the physicochemical properties of the groundwater samples led to an excellent understanding of groundwater quality within Bamenda for various applications. Based on the main findings, the following conclusions can be established:
  • Ca2+ and Mg2+ were the dominant cations in groundwater of the study area, while \({\text{HCO}}_{3}^{ - }\) and \({\text{Cl}}^{ - }\) were the dominant anions in the groundwater. Piper plot showed that Ca–Mg-CO3-HCO3 and Ca–Mg-Cl-SO4 are the main water types found in the study area. Gibb’s diagram indicates that rock weathering followed by atmospheric precipitation were the main water quality controlling factor.

  • The computed SAR, Na %, USSL, and EC values reveal that all the groundwater samples were suitable for irrigation purpose

  • The groundwater samples were generally suitable for drinking purpose according to WHO guidelines, though some few locations recorded pH and total hardness values out of boundary limits. The computed WQI showed that groundwater within the Bamenda metropolis is of excellent quality for drinking.

In general, although the effects of geogenic process, urban sewage, extensive use of agricultural fertilizers, and intense urbanization are not yet felt on the groundwater quality within the study area, their effects are inevitable in the nearest future. It is, however, recommended that other equally important water quality parameters of health concern such as arsenic (As), iodine (I), lead (Pb), mercury (Hg), as well as bacteriological parameters should be investigated in future studies.

Notes

Acknowledgements

The authors wish to thank the Government of Cameroon for “The Higher Education Research Modernization Grant to University Academic Staff” (PSMR) through which the apparatus utilized in the current study was attained. Immense gratitude also goes to the Abunde Sustainable Engineering Group and Community Health Promotion and Rehabilitation Initiative (CoHePaR) for their valuable advice.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

42452_2019_1351_MOESM1_ESM.pdf (180 kb)
Supplementary material 1 (PDF 180 kb)

References

  1. 1.
    Sojobi AO (2016) Evaluation of groundwater quality in a rural community in north central of Nigeria. Environ Monit Assess 188(3):192CrossRefGoogle Scholar
  2. 2.
    Pranab S, Prasanta S, Mishra AK (2010) Interpretation of groundwater and surface water quality using principal component analysis in gohpur sub-division of Sonitpur District, Assam,India. Int J Chem Sci 8(3):1523–1536Google Scholar
  3. 3.
    Kundzewicz ZW (1997) Water resources for sustainable development. Hydrol Sci J 42(4):467–480CrossRefGoogle Scholar
  4. 4.
    Cronin AA, Breslin N, Gibson J, Pedley S (2006) Monitoring source and domestic water quality in parallel with sanitary risk identification in northern Mozambique to prioritise protection interventions. J Water Health 4(3):333–345CrossRefGoogle Scholar
  5. 5.
    Tanawa E, Tchapnga HBD, Ngnikam E, Temgoua E, Siakeu J (2002) Habitat and protection of water resources in suburban areas in African cities. Build Environ 37(3):269–275CrossRefGoogle Scholar
  6. 6.
    Siebert S, Burke J, Faures J, Frenken K, Hoogeveen J, Döll P, Portmann F (2010) Groundwater use for irrigation: a global inventory. Hydrol Earth Syst Sci Dis 7(3):3977–4021CrossRefGoogle Scholar
  7. 7.
    Acho CC (1998) Human interphase and environmental instability: addressing the environmental problems of rapid urban growth. J Environ Urban 10(2):415Google Scholar
  8. 8.
    Ayonghe SN (2001) A quantitative evaluation of global warming and precipitation in Cameroon from 1930 to 1995 and projections to 2060: effects on environment and water resources. In: Lambi CM (ed) Environmental issues: problems and prospects. Unique Printers, Bamenda, pp 142–155Google Scholar
  9. 9.
    Neba A (1999) Modern geography of the Republic of Cameroon, 3rd edn. Neba Publishers, Bamenda, p 235Google Scholar
  10. 10.
    Morin S (1988) Les Dissymétries Fondamentales des Hautes Terres de l’Ouest-Cameroun et leurs Conséquences sur l’Occupation Humaine. Exemple des Monts Bamboutos. L’Homme et la Montagne Tropicale. Sépanrit Bordeaux, pp 49–51Google Scholar
  11. 11.
    Nzenti JP, Abaga B, Suh EC, Nzolang C (2010) Petrogenesis of peraluminous magmas from the Akum- Bamenda massifs, Pan-African Fold Belt. Int Geol Rev 53(10):1121–1149CrossRefGoogle Scholar
  12. 12.
    Gountie DM, Njonfang E, Nono A, Kamgang P, Zangmo TG, Kagou DA, Nkouathio DG (2012) Dynamic and evolution of the Mounts Bamboutos and Bamenda calderas by study of ignimbritic deposits (West Cameroon, Cameroon Line). Syllab Rev 3:11–23Google Scholar
  13. 13.
    Wirmvem MJ, Ohba T, Fantong WY, Ayonghe SN, Suila JY, Asaah A, Tanyileke G, Hell JV (2013) Hydrochemistry of Shallow Groundwater and Surface Water in the Ndop plain, North West Cameroon. Afr J Environ Sci Technol 7(6):518–530CrossRefGoogle Scholar
  14. 14.
    Mache JR, Signing P, Njoya A, Kunyukubundo F, Mbey JA, Njopwouo D, Fagel N (2013) Smectite clay from the sabga deposit (Cameroon); mineralogical and physicochemical properties. Clay Miner 48:499–512CrossRefGoogle Scholar
  15. 15.
    Keleko TD, Tadjou JM, Kamguia J, Tabod TC, Feumoe AN, Kenfack JV (2013) Groundwater investigation using geoelectrical method: a case study of the western region of Cameroon. J Water Res Prot 5(6):633–641CrossRefGoogle Scholar
  16. 16.
    Wirmvem MJ, Ohba T, Suila JY, Fantong WY, Bate NO, Seigo O, Wotany ER, Asaah A, Ayonghe SN, Tanyileke G, Hell JV (2014) Hydrochemical and isotopic characteristics of groundwater in the Ndop plain, North West Cameroon: resilience to seasonal climatic changes. Environ Earth Sci 72(9):3585–3598CrossRefGoogle Scholar
  17. 17.
    Kamgang P, Njonfang E, Nono A, Gountie DM, Tchoua F (2010) Petrogenesis of a silicic magma system: geochemical evidence from Bamenda Mountains, NW Cameroon, Cameroon volcanic line. J Afr Earth Sci 58(2):285–304CrossRefGoogle Scholar
  18. 18.
    Chikhale HU, Chikhale PU (2017) Flame photometric estimation of sodium and potassium ion present in water sample of Darna and Godavari River. Int J Sci Eng Res 8(1):131–136Google Scholar
  19. 19.
    WHO (2004) Guidelines for drinking-water quality: recommendations, vol 1. World Health Organization, GenevaGoogle Scholar
  20. 20.
    Ravikumar P (2015) A comparative study on usage of durov and piper diagrams to interpret hydrochemical processes in groundwater from SRLIS River Basin Karnalaka India. Elixir Earth Sci 80(2015):31073–31077Google Scholar
  21. 21.
    United States Salinity Laboratory (USSL) (1954) Diagnosis and Improvement of Saline and Alkaline Soils, US Department of Agriculture. Handbook, vol 60, pp 160Google Scholar
  22. 22.
    Ako AA, Shimada J, Hosono T, Ichiyanagi K, Nkeng GE, Fantong WY, Eyong GE, Roger NN (2011) Evaluation of Groundwater quality and its suitability for drinking, domestic, and agricultural uses in the Banana Plain (Mbanga, Njombe and Penja) of the Cameroon Volcanic Line. J Environ Geochem Health 33(6):559–575CrossRefGoogle Scholar
  23. 23.
    Tiwari K, Goyal R, Sarkar A (2017) GIS-based spatial distribution of groundwater quality and regional suitability evaluation for drinking water. EnvironProcess 4(3):645–662Google Scholar
  24. 24.
    Nduka JK, Orisakwe OE (2011) Water quality issues in the Niger Delta of Nigeria: a look at heavy metal levels and some physicochemical properties. J Environ Sci Pollut Res 18(2):237–246CrossRefGoogle Scholar
  25. 25.
    Patil SG, Chonde SG, Jadhav AS, Raut PD (2012) Impact of physico-chemical characteristics of Shivaji University Lakes on Phytoplankton Communities, Kolhapur,India. Res J Recent Sci 1(2):56–60Google Scholar
  26. 26.
    Rose TP, Davisson ML, Criss RE (1996) Isotope hydrology of voluminous cold springs in fractured rock from an active volcanic region, northeastern California. J Hydrol 179(1–4):207–236CrossRefGoogle Scholar
  27. 27.
    Magha A, Awah MT, Nono GDK, Wotchoko P, Tabot MA, Kabeyene VK (2015) Physico-chemical and bacteriological characterization of spring and well water in Bamenda III (NW Region, Cameroon). Am J Environ Prot 4(3):163–173CrossRefGoogle Scholar
  28. 28.
    Chapman DV (1996) Water quality assessments: a guide to the use of biota, sediments and water in environmental monitoring. Taylor and Francis, Routledge, pp 1–625CrossRefGoogle Scholar
  29. 29.
    Gnazou MDT, Bawa LM, Banton O, Djanéyé-boundjou G (2011) Hydrogeochemical characterization of the coastal paleocene aquifer of Togo (West Africa). Int J Water Res Environ Eng 3(1):10–29Google Scholar
  30. 30.
    Durvey VS, Sharma LL, Saini VP, Shama BK (1991) Handbook on the methodology of water quality assessment in India. Rajasthan Agriculture University, BikanerGoogle Scholar
  31. 31.
    Todd DK (1980) Groundwater hydrology. Wiley, New YorkGoogle Scholar
  32. 32.
    Durfor CN, Becker E (1964) Public Water Supply of the 100 Largest Cities in US. US Geological Survey Water Supply Paper 1812:364Google Scholar
  33. 33.
    Srinivasamoorthy K, Gopinath M, Chidambaram S, Vasanthavigar M, Sarma VS (2014) Hydrochemical characterization and quality appraisal of groundwater from Pungar Sub Basin, Tamilnadu, India. J King Saud Univ Sci 26(1):37–52CrossRefGoogle Scholar
  34. 34.
    Piper AM (1944) A graphic procedure in the geochemical interpretation of water analyses. Am Geophys Union Trans 25:914–923CrossRefGoogle Scholar
  35. 35.
    Lloyd JA, Heathcote JA (1985) Natural inorganic hydrochemistry in relation to groundwater: an introduction. Oxford University Press, New York, p 296Google Scholar
  36. 36.
    Meybeck M (1987) Global Chemical Weathering of Surficial Rocks Estimated from River Dissolved Loads. Am J Sci 287(5):401–428CrossRefGoogle Scholar
  37. 37.
    Edet A, Nganje TN, Ukpong AL, Ekwere AS (2011) Groundwater chemistry and quality of Nigeria; a status review. Afr J Environ Sci Technol 5(13):1152–1169Google Scholar
  38. 38.
    Gibbs RJ (1970) Mechanisms controlling world water chemistry. Science 170(3962):1088–1090CrossRefGoogle Scholar
  39. 39.
    Durov SA (1948) Natural waters and graphical representation of their composition. Dokl Akad Nauk SSSR 59:87–90Google Scholar
  40. 40.
    Schoeller H (1967) Geochemistry of Groundwater. Groundwater studies—an international guide for research and practice. UNESCO, Paris, pp 1–18Google Scholar
  41. 41.
    Gupta S, Dandele PS, Verma MB, Maithani PB (2009) Geochemical assessment of groundwater around Macherla-Karempudi area, Guntur district, Andhra Pradesh. J Geolog Soc 73(2):202–212Google Scholar
  42. 42.
    Abderamane H, Razack M, Vassolo S (2013) Hydrogeochemical and Isotopic characterization of groundwater in the Chari-Baguirmi depression, Republic of Chad. J Environ Earth Sci 69:2337–2350CrossRefGoogle Scholar
  43. 43.
    Kumar M, Kumari K, Ramanathan A, Saxena R (2007) A comparative evaluation of groundwater suitability for irrigation and drinking purposes in two intensively cultivated districts of Punjab, India. Environ Geol 53(3):553–574CrossRefGoogle Scholar
  44. 44.
    Sisodia R, Moundiotiya C (2006) Assessment of the water quality index of wetland Kalakho Lake, Rajasthan, India. J Environ Hydrol 14(23):1Google Scholar
  45. 45.
    Richard LA (1954) Diagnosis and improvement of saline and alkaline soils. US Department of Agriculture Handbook, p 60Google Scholar
  46. 46.
    Wilcox LV (1955) Classification and use of irrigation waters. U.S. Department of Agriculture Washington, D.C., USA, Circular, vol 969, p 40Google Scholar
  47. 47.
    Karanth KR (1987) Groundwater assessment: development and management. Tatamc Grawl Hill publishing company limited, New Delhi, p 488Google Scholar
  48. 48.
    Wirmvem MJ, Mimba ME, Kamtchueng BT, Wotany ER, Bafon TG, Asaah AN, Fatong WY, Ayonghe SN, Ohba T (2015) Shallow ground water recharge mechanism and apparent age in the Ndop Plain, north west region Cameroon. Appl Water Sci 7(1):489–502CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Science, Department of GeologyUniversity of BueaBueaCameroon
  2. 2.Civil Engineering Discipline, School of EngineeringMonash University MalaysiaBandar SunwayMalaysia
  3. 3.Ministry of Scientific ResearchYaoundéCameroon
  4. 4.Abunde Sustainable Engineering Group (AbundeSEG)KumasiGhana

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