Hydrochemical assessment of pond and stream water near abandoned barite mine sites in parts of Oban...

ORIGINAL ARTICLE

Hydrochemical assessment of pond and stream waternear abandoned barite mine sites in parts of Oban massifand Mamfe Embayment, Southeastern Nigeria

Christopher Iorfa Adamu • Therese Nganje •

Aniekan Edet

Received: 31 March 2013 / Accepted: 21 August 2013 / Published online: 27 September 2013

� Springer-Verlag Berlin Heidelberg 2013

Abstract Hydrochemical studies were carried out in parts

of Oban Massif and Mamfe Embayment, Southeastern

Nigeria to examine the contributions of barite mining

activities on water quality. Pond and stream water samples

were collected from six abandoned barite mines and

adjoining streams areas during dry and wet seasons. These

samples were analysed for physicochemical parameters

using standard techniques. The results showed that the

quality of water samples in the vicinity of barite mine sites

was characterized by low pH, low mineralization, high

suspended solids and deep colour. Sodium (Na?) and cal-

cium (Ca2?) are the dominant cations and bicarbonate

(HCO3-) and sulphate (SO4

2-) the dominant anions. The

low concentration of dissolved silica, relatively high con-

centrations of Na?, HCO3- and SO4

2- suggest a combined

influence of silicate, carbonate and weathering of mine

spoils. The total dissolved solids, total suspended solids,

electrical conductivity and major ions (except Na? and K?)

are higher for water draining barite mines from Cretaceous

sediments, while Na?, K?, Ba2? are higher in basement

rock areas. Correlation and factor analyses suggest that the

main components of the water samples are related to

anthropogenic, geogenic, mineralization and environmen-

tal controls, while Gibbs diagram plots indicate weathering

as the main process controlling the chemistry of water.

Computed values of hardness and some irrigational

parameters showed that the pond and stream water samples

are generally soft and can be used for irrigation. Generally,

the water quality satisfied the WHO (2008) and NIS (2007)

standards for domestic, agriculture and industrial.

However, there is the need to assess the impact of the

pollution on the ecosystem and human health while

remediation measures are being considered.

Keywords Hydrochemistry � Assessment �Barite Mines � Surface water � Nigeria

Introduction

In the last few years, mining of barite mineral in Nigeria

has increased tremendously due to the fact that the Federal

Government has encouraged and emphasized the sourcing

and utilization of local raw materials, especially as related

to the oil and gas industry (NEST 1995; Adamu et al.

2009). This action of the government had resulted in the

indiscriminate mining of barite by the rural communities

without adequate consideration to the environmental deg-

radation, especially with the disposal of mine wastes and

restoration of the land areas. Today, abandoned mine pits

characterizes most of these barite mining areas including

the present study area. The exposed mine spoils, which are

composed of fragments of barite, sulphides and the host

rocks are associated with a myriad of environmental haz-

ards (Nganje et al. 2010, 2011; Moncur et al. 2006).

Generally mining affects water resources at various stages

of the life cycle of the mine and even after abandonment

(Jung 2001). For example, Younger et al. (2002) noted that

the mining process, mineral processing, mine dewatering,

seepage of contaminated leachate into the environment, the

flooding of mine and discharge of untreated water are some

of the environmental issues associated with mining. Water

contaminated with mine waste from perennial ponds and

streams are used by the local people for drinking and

agricultural purposes. In Southeastern Nigeria, most rural

C. I. Adamu � T. Nganje � A. Edet (&)

Department of Geology, University of Calabar, P.O. Box 3609,

UPO, Calabar 540001, Nigeria

e-mail: [email protected]

123

Environ Earth Sci (2014) 71:3793–3811

DOI 10.1007/s12665-013-2757-5

communities, including the project area do not have access

to potable water. These communities rely on water from

streams, rivers and ponds for their daily water needs. Since

the quality of water is affected by the characteristics of the

environment of circulation and occurrence, such sources

are invariably exposed to anthropogenic pollutants from

the activities of barite mining in the area.

In spite of the potential threat to human health and the

ecosystem, the geo environmental problems of barite

mining on water quality have not been well studied and

documented in the area. Previous studies on barite in the

area focused on the genesis and distribution of barites

(Oden 2001), quality of barites (Egeh et al. 2004) and on

water quality assessment near abandoned barite mines

(Adamu et al. 2009). Hence not much has been done on the

natural processes that govern the chemical composition of

the surface waters near these barite mines and environs.

Hence, the increased knowledge of the surface water

quality in these areas will enhance the understanding of

hydrochemical systems that will guide the sustainable

development of water resources and the effective planning

and management of surface water resources in barite

mining areas.

In the past, barite was not considered as a major source

of environmental contaminant because it is an insoluble

compound (Hem 1985). However, Dogan (1999) revealed

that the problem of mining barite is a function of lithology,

climate, hydrology and the local inventory of acid-gener-

ating sulphides and acid-neutralizing carbonates as typified

in the Magampata barite region of Andhra Pradesh in India

(Nagaraju et al. 2006) and Homer Lokve barite mine in

Croatia (Franciskovic-Bilinski 2006). Generally, environ-

mental pollution from mining activities has continued to

generate unpleasant implications for health and economic

development in Nigeria (Adiuku-Brown and Ogezi 1991;

Chukwuma 1995; Adamu 2000). Despite the public and

international agencies policy focused on this problem, the

situation in Nigeria seems to be degenerating and therefore

demands urgent attention. To date, there are no clear pol-

icies in Nigeria aimed at coordinating and monitoring the

relationship between sustainable development and envi-

ronmental management (NEST 1995; Bell and Rusell

2002). Presently, the environmental protection legislation

in Nigeria is poorly enforced. Hence the need to employ

geoenvironmental studies as analytical tool to understand

the relationship between land use activities and environ-

mental contamination. This is important in Nigeria and

other developing nations, where environmental consider-

ation usually takes a second place to economic growth.

Consequently, this study was borne-out of the need to

evaluate the quality of surface water resources within the

barite mines and its environs. The aim of the study there-

fore, was to assess the impact of barite mining activities on

the quality of surface water; examine the degree and extent

of any pollution; appraise the controls and consequence of

any established pollution as well as suggest ways to ame-

liorate their possible effects.

Study area description

Physical characteristics

The study area is situated between latitudes 05�300–06�100N and longitudes 08�000–08�500E and covers parts of

the Oban Massif and the Mamfe Embayment, southeastern

Nigeria (Fig. 1). The area is situated within the subequa-

torial climate of Nigeria with total annual rainfall varying

between 180 and 200 cm. The annual temperature varies

between 25 and 30 �C (Iloeje 1997). The area experiences

two seasons: the wet (April to October) and dry (November

to March) seasons. The mean humidity decreases from

80 % in the rainy season to as low as 60 % in the dry

season.

The relief of the study area varies from the low-lying

northern fringes in the sedimentary areas to high elevations

towards Oban Massif in the south. The elevation ranges

from 100 m in the Mamfe Embayment in the north to more

than 500 m above sea level in the Oban Massif in the south

(Iloeje 1997). The area is drained by the Cross River with

major tributaries being Udip, Udam, Ukong, Bogai, Lak-

poi, Okwo and Okpon rivers, and many perennial streams

which take their rise from Enugu escarpment and the

Cameroon highlands.

Geology and hydrogeology

The geology of the study area falls within parts of the

Cretaceous sediments of Mamfe Embayment and that of

the Precambrian Basement Complex of Oban Massif (Edet

1993), Fig. 1. Rocks of the Oban Massif are mainly phyl-

lites, schists, gneisses and amphibolites. These are intruded

by pegmatites, granites, granodiorites tonalities, monzo-

nites and dolerites. Associated with these intrusives are

charnockites which occur as enclaves in gneisses and

granodiorites (Rahman et al. 1981; Ekwueme 1995a, b).

Overlying the Oban Massif is the Albian Mamfe For-

mation of Asu River Group, the oldest formation within the

Mamfe Embayment. The rocks of the formation comprise

the continental arkosic sandstones, bluish grey/black to

olivine brown shale and sandy shale, fine-grained mica-

ceous calcareous sandstone and siltstone with limestone

lenses. The shales are often carbonaceous and pyritic which

indicates that the sediments were deposited under a poorly

oxygenated shallow water environment of restricted cir-

culation, an indication of low energy environment (Petters

3794 Environ Earth Sci (2014) 71:3793–3811

123

et al 1987). The Mamfe Formation is succeeded by the

middle Cenomanian–Turonian Eze-Aku Formation. This

geologic formation covers the northern flanks of the study

area and consists of greyish shale and siltstone with int-

erbedded sandstone and limestone intercalations. Rocks of

the Eze-Aku Formation are texturally similar to those of

Asu River Group and could have been deposited under

similar conditions (Petters et al. 1987).

The study area falls into the Hydrogeological Group II

(sandstone-siltstone-limestone unit) of Cross River State

(CRBDA 1992; Petters 1989; Okereke et al. 1998). This

group consists of shales of the Asu River Group, Eze Aku

Shales and Nkporo Shales as well as the Sandstones of the

Ajali Formation and the sandstone lenses of Eze Aku

Shales and Nkporo Shales (Petters 1989). Groundwater

occurrence in this group is dependent almost entirely on

joint pattern (CRBDA 1992). The depth to water table is

generally less than 25 m. For example, water levels for 8

UNICEF RUWATSAN boreholes drilled in Obubra zone

range from 2.14 to 9.15 m. This area also holds very low

prospects for groundwater except where boreholes are

located within the sandstones through careful geophysical

investigations (Petters 1989).

Barite mineralization

The schists and phyllites (Oban Massif) and the shales and

sandstones (Mamfe Embayment) play host for the barite

deposits of hydrothermal type mineralization in the

area (Adamu 2000, 2011; Egeh et al 2004; Akpeke 2008).

The mineralization in the Benue Trough where the study

area is situated is structurally controlled and restricted to

gentle dipping veins, fault zones and bedding planes (Olade

1976). These structures were controlled by later

Fig. 1 Geological sketch map of parts of southeastern Nigeria showing study area including the sampled locations

Environ Earth Sci (2014) 71:3793–3811 3795

123

compression related to geotectonic events in the Pre-Tu-

ronian and Santonian times (Nwabufo-Ene 1993). Most of

the shear zones containing the barite deposits are within the

Mamfe Embayment with only a few within the Oban

Massif. The shear zones within the Oban Massif trend in

the N-S direction and are associated with quartz, Fe-oxides

and sulphides. The barite at these sites varied from brown

(stained with Fe-oxides) to transparent with cleavage line

in 3D. The barite deposits in the Mamfe Embayment trends

in the N-S and NE-SW directions and are associated with

less quartz and Fe-oxides but with increased sulphide and

calcite minerals. The barite minerals vary from dark yel-

low, sulphide stained to transparent in colour and are of

high quality with specific gravity of 4.26 with more than

92 % BaSO4 at Agoi Ibami, Yala and Agoi Ibiami (Oden

2001). However, the quality is poor at some areas, where

these barite minerals occurred in association with sulphides

and Fe-oxides.

Materials and methods

Sampling was carried out from six abandoned barite mine

sites. Two of the mine sites at Akpet 1 and Ibogo are

located within the Precambrian Basement Complex of

Oban Massif, while four sites at Nde, Alese, Okumurutet

and Iyametet are situated within the Cretaceous Mamfe

Embayment (Table 1, Figs. 1, 2). Sixty water samples were

collected from mine ponds and adjoining streams during

two sampling campaign periods comprising the wet (July

2009) and dry (February, 2010) seasons.

The pond and stream water physical parameters

including temperature, electrical conductivity (EC), total

dissolved solids (TDS), pH, dissolved oxygen (DO) and

turbidity, were measured in the field using a multi-purpose

water quality meter model PHT-027. A HACH Spectro-

photometer (model DR 3007) was used for the determi-

nation of colour and total suspended solids (TSS). Dry

Table 1 Sample location and

description

See Fig. 1

Mine site Sample ID Source Stratigraphic unit Host rock Age

Nde W1 Sandstone/Shale

Alese W6 Sandstone/Shale

Okumurutet W11 Mamfe embayment Shale/Dolomite Cretaceous

Okumurutet W12 Mine pond Shale/Dolomite

Iyametet W16 Shale/Siltstone

Akpet I W21 Schists

Akpet I W22 Oban massif Schists Precambrian

Ibongo W26 Schists






Alese W8 Mamfe embayment Sandstone/Shale


Alese W10 Sandstone Cretaceous

Okumurutet W13 Shale/Limestone

Okumurutet W14 Shale/Dolomite

Okumurutet W15 Shale

Iyametet W17 Stream Shale/Siltstone




Akpet I W23 Phyillite

Akpet I W24 Schists

Akpet I W25 Schists

Ibongo W27 Oban massif Gneiss Precambrian

Ibongo W28 Gneiss

Ibongo W29 Schists

Ibongo W30 Schists


123

clean and sterilized 1-litre polyethylene bottles were used

for sampling. The sample bottles were thoroughly rinsed

with aliquots of the water, prior to sampling. The collected

samples were labelled, kept in a cooler and transported to

the laboratory where they were preserved in the refrigerator

prior to instrumental analysis.

In the laboratory, the water samples were filtered

through 0.45-mm Millipore membrane filters to remove the

suspended materials. The water samples were analysed for

Ba2?, Ca2?, Mg2?, Na?, K?, HCO3-, SO4

2-, Cl-, NO3-,

PO42-, NH4

?, and SiO2 (Table 2) The analytical precision

was maintained by running the known standards and

duplicates after every 15 samples. The overall precision,

expressed as percent relative standard cations (%RSC) was

within 10 % and overall data reproducibility for anions was

found within 5 %. Details on analytical methods are pre-

sented in Adamu (2011). The irrigational parameters were

calculated using equations in Table 3. The statistical

analyses including descriptive statistics, correlation and

linear regression were performed using STATISTICA�

software.

Results and analysis

Table 4 contains the descriptive statistics of the physical

and chemical parameters for the pond and stream water

samples from all the sampled locations for the dry and wet

seasons, and rain water sample. Table 5 includes a sum-

mary of physicochemical parameters for the different water

types, basins and seasons. The data from the present study

(Tables 4, 5) are also compared with existing water quality

guidelines (World Health Organization WHO 1993, 1996,

2004, 2008; Nigerian Industrial Standard, NIS 2007).

Pond water chemistry

The temperature of the pond water varies between 28.6 and

30.0 �C with a mean and median of 29.13 and 29 �C. The

low standard deviation value of 0.35 suggests low variation

of temperature between the wet and dry season. The colour

of the pond water samples at all locations varies from 15

(Mamfe Embayment, ME) in the dry season (DS) to 470 Pt/

Co (Oban Massif, OM) in the dry season. The mean values

of colour for the dry and wet seasons are 133 and 153.75

Pt/Co. The TSS range from 8 to 900 mg/l with mean of

Fig. 2 A typical a barite mine area and b pond water (After Adamu

et al. 2009)

Table 2 Sample Methods of

analysis used in the present

study

Parameter Method Remarks

Ba Induced couple plasma mass spectrophotometer ACME Laboratory Limited,

Vancouver, Canada

Na, K Flame atomic emission spectrophotometer

Ca, Mg EDTA

SiO2 Molybdosilicate titration (ALPHA 1995) Benue state rural water supply

and sanitation agency

NH4 Nesslerization (BERWASSA), Makurdi, Nigeria

Cl Mohr titration

HCO3 Hydrochloric acid titration

SO4 Turbidimetry

NO3, PO4 Spectrophotometric techniques


123

31.80 and 212.30 mg/l for the dry and wet seasons. pH of

the pond water varies from 4.70 (OM; DS) to 6.2 (ME; DS)

indicating acidic water. All the samples display pH values

below the (1993, 2004) standard of 6.5–8.5. EC of the pond

water varies from 52 (OM, DS) to 600 lS/cm (ME, DS).

The EC values of all the water samples is below the WHO

(2004) standard of 1,500 lS/cm. TDS values range from 30

to 430 mg/l, which is below the WHO (2004) standard of

1000 mg/l. TSS vary from 8 to 900 mg/l, while the dis-

solved oxygen (DO) varies between 2 and 4.6 mg/l. DO

concentration for all the pond water samples is not within

the standard value of 5 mg/l minimum for potable water.

The maximum concentrations of cations (mg/l) indicate

that Na (ME, DS) [ Mg (ME, DS) [ Ca (ME, DS) [ K

(ME, DS). The concentrations are below the WHO (2004)

standard.

Barium in the pond water varies between 0.01 (ME,

WS) and 2.00 mg/l (OM, DS). This range of values is

below the WHO standard of 0.7 mg/l. However, one

sample from Ibongo (OM, DS) representing 6.25 % of all

the samples has barium content above the WHO standard.

Chloride content varies from 0.00 (ME, WS) to 22.10 mg/l

(ME, WS). Sulphate content ranges between 8.0 (ME, WS)

and 31 mg/l (ME, DS). Bicarbonate content ranges from 3

(OM, DS) to 100 mg/l (ME, DS). Nitrate and phosphates

varies between 6 (ME, DS) to 32 mg/l (OM, DS) and 0.0

(ME/OM, DS) to 0.60 mg/l (OM/ME, DS/WS). The con-

tents of the anions were below the WHO standard.

The six mine sites were divided into two groups on the

basis of lithology and hydrochemical characteristics. The

first group comprised Akpet 1 and Ibogo Mines charac-

terized by low ionic concentrations (Table 5). These mines

were associated with the less reactive crystalline rocks of

the Oban Massif. The mines were, however enriched in Ba

relative to the mines in the sedimentary area. This was

attributed to the age of the mines and poor quality of the

barite which resulted from Fe-oxide impurities, tourmaline

inclusions and lateritic soils (Ekwueme 1995b). The second

group included the mines at Nde, Alese, Okumurutet and

Iyametet located in the Mamfe Embayment. This group

was characterized by high ionic concentrations. The high

concentrations of dissolved ions were attributed to intense

weathering of the sedimentary rocks and associated sulp-

hides, which alongside its gangue minerals were more

abundant in the sedimentary area relative to the crystalline

basement area (Ekwueme 1995b).

Stream water chemistry

The temperature of the stream water varies from 28 (ME,

WS) to 30 �C (ME, DS). The colour of the stream water

samples ranges from a low of 3.4 to a high of 600 Pt/Co in

the wet season. The mean values of colour for the dry and

wet seasons are 149.5 and 151.14 Pt/Co. The pH values of

stream water samples of the study area varies between 4.30

(OM, DS) and 7.00 (ME, WS) with mean value of 5.85.

More than 90 % of the samples had pH \ 7.00. EC is

directly related to the concentrations of ions in water. EC

of the stream water varies from 56 (OM, WS) to 520 lS/

cm (ME, DS). The EC for all the stream water samples are

below the permissible unit of 1,400 lS/cm. The TDS of the

water samples ranges from 40 (OM, WS) to 410 mg/l (ME,

DS). According to WHO (1993) specification, TDS up to

500 mg/l is desirable for drinking water. This study shows

that more than 90 % of the stream water samples are below

the desirable unit of TDS, which can be used for drinking

without any risk.

The DO value for the stream water samples varies from

1.20 mg/l (ME, DS) to 5 mg/l (ME, WS). More than 90 %

of the samples had DO \ 5.0 mg/l probably due to high

presence of materials of high organic content leading to

oxygen depletion (Alam et al. 2012). The total hardness

(TH) varies from 0.5 (ME, WS) to 113 (ME, DS) with an

average of 19.33 mg/l. Four samples representing 9 %

from the ME in the dry season, had TH [ 75 mg/l (Soft)

but \150 mg/l (Moderately hard), using the classification

of Sawyer and McCarthy (1967). The high TH in some

locations is attributed to the presence of carbonate rocks.

The chloride concentration varies from 0.6 (ME, WS) to

23 mg/l (ME, WS) with an average of 10.40 mg/l. The

concentration of chloride in the stream water is below the

desirable limit of 250 mg/l (WHO 1993, 2004). The

Table 3 Equations for calculating irrigational water parameters

No Irrigational water parameter Equation Reference

1 Sodium adsorption ratio SAR = Na/[(Ca2? ? Mg2?)/2]� Richards (1954)

2 Percent sodium % Na = [(Na2? ?K?)/(Ca2?? Mg2? ? Na? ? K?)] 9 100 Wilcox (1955)

3 Total hardness TH = 2.5 Ca2? ? 4.1 Mg2? Todd (1980)

4 Residual sodium carbonate RSC = (HCO3- ? CO3

2-) - (Ca2? ? Mg2?) Eaton (1950)

5 Permeability index PI = [Na? ? HHCO3-/ (Ca2? ? Mg2? ? Na?)]*100 Ragunath (1987)

6 Kelly’s index KI = Na?/(Ca2? ? Mg2?) Kelly (1940) and Paliwal (1967)

7 Magnesium ratio Mg2?/Ca2? Nagaraju et al. (2006)


123

Ta

ble

4S

um

mar

yst

atis

tics

of

wat

erp

hy

sico

chem

ical

dat

afr

om

the

stu

dy

area

for

the

dry

and

wet

seas

on

s

Sourc

eP

ond

(n=

16)

Str

eam

(n=

44)

Rai

n(n

=3)

Sta

ndar

d

Sta

tist

ics

Mea

nM

edia

nM

inim

um

Max

imum

Std

.Dev

.M

ean

Med

ian

Min

imum

Max

imum

Std

.Dev

.M

ean

Med

ian

Min

imum

Max

imum

Std

.Dev

.W

HO

NIS

(2007

)E

U(1

975

)

Tem

p�C

29.2

329.0

028.6

030.0

00.4

229.2

429.0

028.0

030.0

00.4

923.6

724.0

023.0

024.0

00.5

8

Colo

ur

pt/

Co

143.4

459.0

015.0

0470.0

0154.9

1167.1

0126.0

03.4

0600.0

0133.2

810.0

010.0

08.0

012.0

02.0

050

pH

5.5

25.5

54.7

06.2

00.4

85.8

56.0

04.8

07.0

00.5

05.3

35.0

05.0

06.0

00.5

86.5

–8.5

6.5

–8.5

10

TD

Sm

g/l

150.3

1131.0

030.0

0430.0

0101.4

3152.6

8140.5

040.0

0410.0

095.8

58.0

08.0

06.0

010.0

02.0

01000

500

1500

EC

lS

/cm

214.9

4195.0

052.0

0600.0

0143.4

8221.3

4196.0

056.0

0520.0

0125.3

512.6

713.0

010.0

015.0

02.5

21400

1000

1250

TS

Sm

g/l

121.7

531.0

08.0

0900.0

0252.3

3255.3

0122.0

06.0

0870.0

0253.9

9

DO

mg/l

3.2

32.8

02.0

04.6

00.9

43.0

62.8

01.2

05.0

00.9

53.9

73.8

03.5

04.6

00.5

75

55

TH

mg/l

14.2

412.5

02.3

057.0

013.1

619.3

38.1

00.5

0113.0

028.7

25.1

35.6

03.5

06.3

01.4

6100

Ba2

?m

g/l

0.3

90.2

00.0

12.0

00.4

90.2

70.1

20.0

01.2

00.3

10.7

0.7

0.1

Na?

mg/l

3.8

43.0

70.5

020.1

04.4

75.9

12.7

50.0

131.0

08.4

53.5

00.8

00.7

09.0

04.7

6200

200

100

K?

mg/l

2.4

52.1

00.3

45.2

01.4

12.0

41.6

00.1

05.1

01.4

112

12

Ca2

?m

g/l

2.3

82.1

20.0

35.8

51.7

23.4

42.1

00.0

216.4

04.3

31.9

72.2

01.3

02.4

00.5

975

100

Mg

2?

mg/l

2.0

21.1

00.2

014.0

03.2

92.6

71.0

50.0

517.5

04.6

00.0

60.0

60.0

40.0

80.0

2100

0.2

50

SiO

2m

g/l

0.4

00.1

10.0

21.4

00.4

70.3

80.3

00.0

11.5

00.3

6

NH

4?

mg/l

0.8

61.0

00.1

02.0

00.5

80.9

60.9

00.0

62.4

00.6

61.5

Cl-

mg/l

9.2

19.5

00.0

022.1

05.4

110.4

010.0

00.6

023.0

04.1

6250

200

SO

42-

mg/l

18.2

518.5

08.0

031.0

06.0

215.4

114.5

01.3

032.0

07.6

6400

100

250

HC

O3-

mg/l

46.4

444.0

03.0

0100.0

024.5

756.8

050.0

014.0

0150.0

033.9

97.0

07.0

06.0

08.0

01.0

030

NO

3-

mg/l

16.6

918.0

03.0

032.0

07.8

018.1

819.0

04.0

036.0

08.1

050

50

PO

4-

mg/l

0.1

20.0

20.0

00.6

00.2

10.0

40.0

10.0

00.3

00.0

7

WH

O(1

993

,1996

,2004

,2008)


123

occurrence of high levels of nitrate in water is a prominent

problem in many parts of the world. The concentration of

nitrate in the study area varies from 4 (ME, DS) to 36 (OM,

DS) with an average of 18.18 mg/l. It is found that all the

stream water samples did not exceed the desirable limit of

45 mg/l (WHO 1993, 2004). Sulphate concentration varies

between 1.3 (ME, WS) and 32.0 mg/l (OM, DS) with an

average of 15.41 mg/l. These values are within the WHO

(2004) desirable limit of 250 mg/l.

Rain water chemistry

The pH values of the rain water samples of the study area

vary from 5.00 to 6.00 with mean of 5.33. This shows that

the rain water is mainly of acidic nature, besides the values

are below the WHO (2004) standard of 6.5–8.5. The EC of

the rain water samples was\15.00 lS/cm (mean 12.67 lS/

cm). The average TDS is less than 10 mg/l. The EC and

TDS values of the rain water samples are below the NIS

(2007) and WHO (2004) limits of 1,500 lS/cm and

1,000 mg/l, respectively. The concentrations of ions in the

rain water samples were \10 mg/l.

Table 4 shows that although waters from the abandoned

mine ponds are more mineralized than stream and rain

waters due to high concentrations of TDS and ions (except

NO3, NH4 and PO4), the difference was not statistically

significant. The water samples were therefore adjudged to

have a common source. The depletion in concentration of

dissolved solids in the stream waters was attributed to

dilution by surface run-off. The washing of solids into the

streams by run-off also contributed to the high level of

suspended matter in stream waters. The elevated concen-

trations of nitrates, ammonium and phosphates in stream

waters are attributed to the use of manures and fertiliser in

crop production as well as indiscriminate dumping of

organic waste into or close to the streams in the area.

Seasonal and spatial variation

The highest values of physical parameters in both seasons

(Table 6) were below the maximum acceptable limits

(WHO; NIS 2007). However, colour, pH, TSS and tem-

perature exceeded these limits. Test of significance for the

relation of physical parameters between different seasons

by z test was significant (z calculated [ z critical of 1.96 at

P \ 0.05) for most physical parameters (TDS, EC, DO,

HT). However, the z test indicated that there was no sig-

nificant difference between values of the different physical

parameters from samples of the pond water and the stream

water samples with the exception of TSS in both seasons

Table 5 Mean values of pond water and stream water physicochemical data from the study area for the different geologic area and seasons

Source Pond water Stream water WHO NIS (2007) EU (1975)

Basin ME ME OM OM ME ME OM OM

Season D W D W D W D W

Temp 29.30 29.20 29.40 29.00 29.53 28.93 29.54 29.00

Colour 51.00 86.00 270.00 266.67 160.87 200.36 125.14 151.14 50

pH 5.70 5.80 5.27 5.00 5.99 5.80 5.66 5.86 6.5–8.5 6.5–8.5 10

TDS 237.60 134.00 115.67 66.67 212.00 144.40 122.86 73.14 1000 500 1500

EC 324.80 178.00 204.33 104.00 288.00 217.40 201.71 106.57 1400 1000 1250

TSS 31.00 147.40 32.00 320.00 112.13 350.13 48.71 565.43

DO 3.28 3.32 2.90 3.33 2.49 3.53 2.61 3.71 5 5 5

TH 25.00 10.00 10.43 7.17 37.83 9.47 12.90 7.21 100

Ba2? 0.27 0.11 1.01 0.43 0.32 0.14 0.57 0.18 0.7 0.7 0.1

Na? 6.43 3.21 3.01 1.40 11.48 3.79 2.23 2.19 200 200 100

K? 4.22 1.19 2.17 1.90 3.52 1.39 0.76 1.53 12 12

Ca2? 3.60 1.86 2.05 1.52 5.65 2.11 3.24 1.71 75 100

Mg2? 3.89 1.33 1.26 0.80 5.78 1.18 1.18 0.72 100 0.2 50

SiO2 0.05 0.43 0.27 1.07 0.11 0.46 0.43 0.79

NH4? 1.40 0.62 0.93 0.27 1.27 0.72 1.14 0.61 1.5

Cl- 8.00 11.26 9.33 7.67 10.53 9.95 11.29 10.20 250 200

SO42- 21.00 16.00 21.00 14.67 16.07 10.61 26.83 12.89 400 100 250

HCO3- 72.20 40.60 29.00 30.67 94.00 43.27 37.71 25.14 30

NO3- 11.20 17.00 18.67 23.33 15.87 19.20 22.00 17.14 50 50

PO43- 0.02 0.23 0.20 0.01 0.01 0.07 0.03 0.01

ME Mamfe Embayment, OM Oban massif, D dry season, W wet season


123

Table 6 Summary statistics of water geochemical data from the study area in (A) dry season and (B) wet season

Parameter Units Mean SD Median Minimum Maximum CV SK WHO NIS (2007) EU (1975)

A

Temp �C 29.43 0.17 29.6 28.5 30 0 -0.76

Colour Pt/Co 140.25 96.76 119 15 470 69 1.46 50

pH 5.71** 0.38 5.76 4.7 6.8 7 -0.02 6.5–8.5 6.5–8.5 10

TDS mg/l 202.88*,** 64.86 160 85 430 32 1.05 1,000 500 1,500

EC lS/cm 292.83*,** 81.56 242 130 600 28 0.81 1,400 1,000 1,250

TSS mg/l 84.67*,** 30.85 60 8 200 36 0.81

DO mg/l 2.84 0.3 2.4 2 4.6 11 1.04 5 5 5

Hardness mg/l 24.93* 20.87 16.8 2.6 112.75 80 1.74 100

Ba2? mg/l 0.46*,** 0.32 0.21 0 2 71 1.62 0.7 0.7 0.1

Na? mg/l 6.71* 6.72 3.065 0.01 30 75 1.64 200 200 100

K? mg/l 3.01* 1.41 2.6 0.5 5.2 47 -0.18 12 12

Ca2? mg/l 4.34* 3.17 3.17 0.03 16.4 69 1.76 75 100

Mg2? mg/l 3.44* 3.49 1.7 0.2 17.5 72 1.65 100 0.2 50

SiO2 mg/l 0.19* 0.15 0.1 0.02 0.6 79 1.11

NH4? mg/l 1.20* 0.42 1.2 0.08 2.4 35 -0.1 1.5

Cl- mg/l 10.32 1.77 10 4 16 17 -0.16 250 200

SO42- mg/l 21.20*,** 3.83 20 10 32 18 -0.13 400 100 250

HCO3- mg/l 67.58* 29.24 66 3 142 43 0.48 30

NO3- mg/l 16.33* 4.53 16.33 3 36 28 0.47 50 50

PO43- mg/l 0.04* 0.08 0.01 0 0.6 75 5.1

B

Temp �C 28.92 0.2 28.8 28 29.7 0 -1.17

Colour Pt/Co 184 105.73 120.36 3.4 400 87 1.39 50

pH 5.67** 0.33 5.73 4.6 6.6 6 -0.69 6.5–8.5 6.5–8.5 10

TDS mg/l 119.94* 64.73 67.36 30 390 54 1.39 1,000 500 1,500

EC lS/cm 173.89* 87.05 91 52 500 50 1.48 1,400 1,000 1,250

TSS mg/l 439.74* 184.8 469.87 6 900 42 1.62

DO mg/l 3.45 0.4 3 2.4 4.6 12 3.02 5 5 5

Hardness mg/l 8.53 7.19 7.7 1.2 29.05 82 0.83 100

Ba2? mg/l 0.19*,** 0.1 0.1 0.01 0.5 53 2.88 0.7 0.7 0.1

Na? mg/l 3.14* 1.79 2.53 0.5 16 57 0.98 200 200 100

K? mg/l 1.49* 0.3 1.49 0.2 3 20 0.94 12 12

Ca2? mg/l 1.89* 1.65 2 0.02 6.7 87 0.62 75 100

Mg2? mg/l 1.02* 0.88 1 0.14 3 86 1.07 100 0.2 50

SiO2 mg/l 0.57 0.3 0.6 0.05 1.4 53 -0.35

NH4? mg/l 0.58* 0.26 0.4 0.06 1.2 45 -0.25 1.5

Cl- mg/l 10.08 4.21 10 0 23 42 0.06 250 200

SO42- mg/l 13.57*,** 2.74 10.4 8 22 20 1.39 400 100 250

HCO3- mg/l 36.44* 8.8 33 14 70 24 -1.21 30

NO3- mg/l 19.73* 3.64 18.86 6 31 18 -0.23 50 50

PO43- mg/l 0.07 0.06 0.02 0 0.6 86 2.85

Standard = Maximum acceptable limit (NIS 2007; WHO 1993, 1996, 2004, 2008)

CV coefficient of variation, SK skewness

* Significant seasonal variation at p \ 0.05 using z test

** Significant spatial variation at p \ 0.05 using z test


123

and pH, TDS and EC in the dry season. Comparison of the

values of the physical parameters with those of the stream

water samples shows higher values for the pond water

except for pH and DO (Table 5). The pond water is more

saline than the stream water due to high concentrations of

TDS and commensurately high EC. Contrary, the stream

water was more coloured with commensurately high TSS

However, the z test indicates that there was no significant

difference between values of the different physical

parameters from the mine pond and stream waters with the

exception of TSS and colour. Ellis (1993) attributed the

colour of natural waters to organic matter, which may

occur in the dissolved state, in colloidal suspension, or as

coarse-suspended matter. The high levels of suspended

matter in the water samples were attributed to the disper-

sion of mine spoils. In addition, the presence of acidic

waters in the study area was due to decaying organic matter

in the soil and oxidation of sulphides from mine spoils.

Normally, the pH of mine water is B3.5 (Rose and Cravotta

1998). However, for the study area, the pH values on the

average were [3.5 due to buffering by carbonates and

crystalline rocks, which underline the area.

The major anions (HCO3-, SO4

2-, NO3-, Cl-) consti-

tuted more than 80 % of the TDS in both seasons. Bicar-

bonate is the dominant anion accounting for more than

50 % of the total anions in water. Bicarbonate ion was

followed by sulphate ion (SO42-) which accounted for

about 15 % of total anions. Nitrate (NO3-) constituted

about 12 % of total anions. The content of chloride ion

constituted only about 8 % of total anions. The major

cations (Na?, Ca2?, Mg2?, and K?) constituted less than

20 % of TDS. Sodium and calcium accounted for about

5 % (31 %) and 3 % (19 %) of the TDS (cations),

respectively. The contents of magnesium (Mg2?) and

potassium (K?) constituted less than 4 % (25 %) each of

the TDS (cations). The levels of minor dissolved solids

(NH4?, SiO2 and PO4

3-) were low (\3 mg/l) with little or

no contribution to the total ionic budget. The comparative

minor dissolved ionic composition of the hydrochemical

data showed that the order of concentration of minor dis-

solved solids was NH4? [ SiO2 [ PO4

3-.

The highest values of chemical parameters in both

seasons were within maximum acceptable limits of NIS

(2007) and WHO, except for barium (Ba). Test of signifi-

cance for the relation of chemical parameters between

different seasons by z test was significant (z calcu-

lated [ z critical of 1.96 at P \ 0.05) for most chemical

parameters. The z test indicates that there is no significant

difference between levels of chemical parameters from the

mine pond water and the stream water, except for Ba and

SO42- in both seasons. The mean concentrations of

chemical parameters (Na?, K?, Ca2?, Mg2?, Cl-, HCO3-,

SiO2, NH4?) were higher in the mine pond waters than the

stream waters except for NO3 and PO4. Test of significance

for the relation of chemical parameters between pond and

stream water samples by z test was not significant (z cal-

culated [ z critical of 1.96 at P \ 0.05). Hence less

emphasis was placed in the study on water types (sources).

Water type

Hydrochemical classification

Major ions were plotted on a trilinear Piper diagram (Piper

1944) to evaluate the hydrochemistry of the different

waters (Fig. 3). Majority of the water type falls in the field

Na?–HCO3- and Ca2?–HCO3

- (Table 7). These water

types made up 55 and 20 % of the different water types in

the area. This was followed by Mg2?–HCO3- (12 %);

Na?–SO42-, Mg2?–SO4

2-, Ca2?–SO42- (3 % each);

Na?–Cl- and Mg2?–Cl- (2 % each). The Na?–HCO3-

occurs in all scenarios, except for the pond water sample in

the wet season from Oban Massif. The Ca2?–HCO3- water

type was found in all the scenarios of sampling, except for

the stream water sample in the dry season from Oban

Massif. Abundance of this water type is probably the result

of dissolution of feldspar and carbonate minerals from the

rock matrix. The source (s) of other water types is due to

minor variations in the lithology of the bedrock.

Anthropogenic classification

The water samples were classified into four groups based

on pH and Ba which represent the influence of barite

mining activities. Following the method of Sinclair (1974),

the threshold values were 5.5 and 0.4 mg/l for pH and Ba,

respectively. These threshold values were then used to

divide the samples into four classes (Table 8). The samples

of group 1 (GP 1) are relatively high in pH ([5.5) and low

in Ba (\0.4 mg/l) and accounted for 41.67 and 58.33 % of

water samples in the dry and wet seasons, respectively.

This group (GP 1) also accounted for 11.11 and 88.89 %

for the pond and stream water samples, respectively. This

is the slightly acidic-low barium group. Group 2 (GP 2) is

the low pH (\5.5)—low barium (\0.4 mg/l) group and

accounted for 37.50 and 62.50 % of water samples,

respectively, for the dry and the wet seasons. The GP 2 also

accounted for 25 and 75 % of the pond and stream samples.

Group 3 (GP 3) is the high pH ([5.5) and high Ba

([0.4 mg/l) group. This group (GP 3) accounted for 100 %

of samples in the dry season with no sample in the wet

season and 25 and 75 %, respectively, for the pond and

stream waters. Group 4 (GP 4) comprised samples that are

relatively low in pH (\5.5) but high in Ba ([0.4 mg/l) and

accounted for 42.86 and 57.14 % of water samples in the


123

wet and the dry seasons, respectively. The same group (GP

4) had 42.86 and 57.14 % of the pond and river water

samples, respectively. This is the low acidic–high barium

group that is considered most hazardous. The implication

of the classification is that group 1 is controlled mainly by

natural and geogenic (weathering) processes, group 2 by

geogenic and environmental processes, group 3 by

environmental and anthropogenic activities and group 4 by

anthropogenic activities. It must, however, be noted that

the high percentage for stream water samples is due to the

fact that the stream water samples for the two seasons (44)

were higher than that of the pond water samples (16). High

percentage for wet dry season may be attributed to high

rate of dissolution relative to the dry season.

Fig. 3 Piper’s trilinear diagram

of hydrochemical data in the

study area a wet season, b dry

season


123

Sources of ions

Correlation analysis

Statistical analyses using the product coefficient of corre-

lation between physicochemical parameters were used to

determine the relationship between the dissolved ions and

the possible sources. The correlation coefficient (r) is a unit

less number, which ranges between ?1 and -1, where ?1

indicates a perfect direct relationship between two vari-

ables and a correlation of -1 indicates an inverse perfect

relationship. Between the two extremes is a spectrum of

less than perfect relationships, including zero, which indi-

cates lack of linear relationship. Linear correlation analysis

was done for elements with not less than 50 % of the

measurements falling below analytical detection limit

(ADL).The physical and chemical parameters were inclu-

ded in the correlation analysis to determine their interre-

lationship and controls on element concentrations.

Correlation analysis result, for the entire scenario cov-

ering the two seasons and geologic terrain, is presented in

Table 9. The highest correlation occurs between TDS and

EC with p value\0.05 (0.92). EC and TDS display positive

correlations with Na?, K?, Ca2?, Mg2? and HCO3-.

Table 7 Hydrochemical facies for the pond and stream waters in percentage

Source Season Geology N Na?–

HCO3-

Ca2?–

HCO3-

Mg2?–

HCO3-

Na?–

SO42-

Mg2?–

SO42-

Ca2?–

SO42-

Na?–

Cl-Mg2?–

Cl-

Pond Dry Mamfe Embayment 5 40 60

Dry Oban Massif 3 33 33 33

Wet Mamfe Embayment 5 40 20 20 20

Wet Oban Massif 3 67 33

Stream Dry Mamfe Embayment 15 60 7 33

Dry Oban Massif 7 29 14 29 29

Wet Mamfe Embayment 15 80 20

Wet Oban Massif 7 71 14 14

Total 55 20 12 3 3 3 2 2

Table 8 Anthropogenic classification of water

GP Class Dry no Wet no Dry % Wet % Pond no Stream no Pond % Stream %

1 pH [ 5.5, Ba \ 0.4 15 21 41.67 58.33 4 32 11.11 88.89

2 pH \ 5.5, Ba \ 0.4 3 5 37.50 62.50 2 6 25.00 75.00

3 pH [ 5.5, Ba [ 0.4 8 0 100.00 0.00 2 6 25.00 75.00

4 pH \ 5.5, Ba [ 0.4 3 4 42.86 57.14 3 4 42.86 57.14

Table 9 Correlation analysis between some physicochemical parameters in water of the study area (Bold numbers are significant at p \ 0.05)

pH TDS EC Ba2? Na? K? Ca2? Mg2? Cl- SO42- HCO3

- NO3-

pH 1.000

TDS -0.010 1.000

EC -0.078 0.920 1.000

Ba2? -0.316 -0.033 0.065 1.000

Na? 0.325 0.291 0.190 -0.217 1.000

K? 0.135 0.440 0.438 -0.074 0.643 1.000

Ca2? 0.250 0.390 0.388 -0.198 0.796 0.536 1.000

Mg2? 0.279 0.481 0.419 -0.074 0.846 0.614 0.741 1.000

Cl- 0.042 -0.200 -0.230 -0.104 0.084 0.024 -0.134 -0.065 1.000

SO42- -0.293 -0.029 0.020 0.326 -0.030 0.041 0.103 -0.092 0.147 1.000

HCO3- 0.385 0.351 0.322 -0.003 0.444 0.577 0.370 0.367 -0.031 -0.046 1.000

NO3- 0.136 -0.244 -0.282 0.150 -0.219 -0.385 -0.235 -0.180 0.219 0.069 -0.207 1.000


123

Barium and sulphate are positively correlated reflecting the

dissolution of barite mineral. The correlation between Ca2?

and HCO3- and Ca2? and Mg2? suggest the weathering of

calcite and dolomite minerals, especially from Mamfe

Embayment. The correlation between Na? and K?, Ca2?,

Mg2? may be attributed to cation exchange (Edet et al.

2012), while that between K? and NO3- is due to poor

waste management.

Poor correlations between the different parameters are

attributed to variability, and differences in geochemical

behaviour of parameters (Cox 1995; Edet et al. 2003;

Nganje et al. 2010). Within the study area, ions are released

into the drainage system from different sources including

weathering of different rocks types, oxidation of sulphides,

barite, silicates, carbonates and other minerals. Minor

contributions included atmospheric fall-out and agricul-

tural practices. The different sources of ions are responsible

for the variability in elemental content in the drainage

system. This is supported by the high coefficient of varia-

tions values (Table 6), and lack of strong correlation

between parameters (Table 9).

Factor analysis

Factor analysis is a multivariate statistical method which

yields the general relationship between measured chemical

variables by showing multivariate patterns that may help to

classify the original data. The geological interpretation of

factors gives an insight into the main processes, which may

govern the distribution of hydrochemical variables. Factor

analysis can identify several pollution factors reasonably

but the interpretation of these factors in terms of actual

controlling sources and processes is highly subjective

(Matalas and Reiher 1967; Bahar and Reza 2010). R-mode

factor analysis on the combined data sets provided four

factors with eigenvalue [1 that explained approximately

71.53 % of the variability of the data (Table 10). Factor 1

has an eigenvalue of 4.30 and explains 35.83 % of the total

variance and shows high loadings on Na?, K?, Ca2?, Mg2?

and HCO3-. The high loading for these ions EC, TDS, Na?

and Cl- indicates silicate and carbonate mineral

dissolution.

The Na?, K?, Ca2? and Mg2? may also reflect the

contributions of other hydrochemical processes (ion

exchange, soil CO2 or from bacterial degradation). Factor 2

has an eigenvalue of 1.87 and explains 15.56 % of the total

variance with high loading on EC, TDS and Cl-. This is

attributed to mineral dissolution and absence of halite in

the area. Factor 3 has an eigenvalue of 1.39 and explains

11.59 % of the total variance. It shows high loadings on

pH, Ba? and SO42-, which is attributed to dissolution of

barite mineral. Factor 4 has an eigenvalue of 1.03 and

explains 8.55 % of the total variance. It shows high

loadings on NO3-. This reveals atmospheric and pollution

sources (Jeong 2001) and poor waste management.

Processes controlling water chemistry

Water rock interaction plays a significant role in water

quality, which is useful for understanding the source of

ions in water (Prasanna et al. 2011). The Gibbs diagram

was therefore used to determine the source of ions in water.

Figure 4 illustrates that all the samples, with the exception

of the rain water, fall in the rock weathering field, sug-

gesting weathering of minerals such as silicates, carbonates

and barites. It is therefore obvious that mineral dissolution

is the major processes that regulate water chemistry in the

area. Hence, saturation index (SI) of the water samples

were calculated using the geochemical equilibrium model

MINTEQA2 (Parkhurst and Appelo 1999), Table 11.

Nearly all the samples are oversaturated with respect to

barite (SI [ 0). Therefore, the water chemistry seems to be

largely affected by the dissolution of barite and carbonate

minerals.

Irrigational water quality assessment

The quality of any water for irrigation use is determined by

the concentration and composition of dissolved

Table 10 Factor analysis between some physicochemical parameters

in water of the study area (Bold numbers are significant at p \ 0.05)

Source Parameter Factor

1 2 3 4

Pond and

Stream

pH 0.379 -0.070 0.614 0.498

TDS 0.288 0.859 0.006 -0.070

EC 0.225 0.892 -0.078 -0.108

Ba2? -0.234 0.262 -0.647 0.299

Na? 0.937 0.022 0.084 -0.045

K? 0.752 0.305 -0.064 -0.163

Ca2? 0.818 0.210 0.018 -0.120

Mg2? 0.815 0.302 0.076 0.010

Cl- 0.218 -0.517 -0.227 0.259

SO42- 0.113 -0.097 -0.836 0.030

HCO3- 0.547 0.361 0.135 0.236

NO3- -0.236 -0.200 -0.080 0.812

Eigenval 4.299 1.868 1.390 1.026

% total

variance

35.829 15.563 11.586 8.549

Cumul.

Eigenval

4.299 6.167 7.557 8.583

% Cumul.

variance

35.829 51.392 62.977 71.526


123

constituents in the water. A lot of chemical constituents

affect the suitability of water for irrigation based on the

total concentration of soluble salts and the relative pro-

portion of major cations. The suitability of water for irri-

gation depends on the effect of mineral constituent of water

for both plants and soil (Wilcox 1955).

Sodium adsorption ratio (SAR)

Excess Na? in water produces undesirable effects of

changing soil properties and reducing soil permeability

(Kelly 1940). Hence, assessment of Na is essential when

considering the suitability of water for irrigation. The

degree to which irrigation water enters into cation

exchange reactions in soil can be indicated by the SAR. Na

replacing adsorbs Ca2? and Mg2? causes damage to soil

structure. Table 12 shows that all the samples from the dry

and wet seasons and Mamfe Embayment and Oban Massif

are excellent for irrigation purposes.

Percent sodium (% Na)

Water for irrigation containing large amounts of sodium is

a special concern due to sodium’s hazard on soil. Excess

sodium in water produces undesirable effects of reducing

soil permeability (Subba Rao 2006). Hence the assessment

of percentage of sodium in irrigation water was performed.

The classification of water on the basis of %Na is given in

Table 12. The table shows that 20, 29, 14, 14 % of pond

water from Mamfe Embayment (dry season, DS), stream

water from Oban massif (DS), stream water from Mamfe

Embayment (wet season, WS) and stream water from Oban

Massif (WS) are excellent for irrigation while 28 % of all

the stream water samples from Mamfe Embayment with

[80 % Na are unsuitable for irrigation.

1

10

100

1000

10000

0.00 0.20 0.40 0.60 0.80 1.00

Na/(Na+Ca)

TD

S (m

g/l)

PDME

PDOM

SDME

SDOM

PWME

PWOM

SWME

SWOM

Rain

Evaporation Dominance

Rock weathering Dominance

Atomspheric Precipitation Dominance

Fig. 4 Gibbs (1970) diagram showing mechanism controlling water

chemistry in the study area (PDME pond water dry season, Mamfe

Embayment; PDOM pond water dry season, Oban Massif; SDME

stream water dry season, Mamfe Embayment; SDOM stream water,

dry season, Oban Massif; PWME pond water wet season, Mamfe

Embayment; PWOM pond water wet season, Oban Massif; SWME

stream water wet season, Mamfe Embayment; SWOM stream water,

wet season, Oban Massif)

Table 11 Saturation indices for mineral phases in the study area

Mineral Nde Alese Okumurutet Iyametet Akpet I Ibogo

Angliste (PbSO4) -1.6 (-2.1) -2.3 (-3.3) -3.2 ( -4.4) -4.0 (-6.00) -3.8 (-4.6) -3.7 (-4.4)

Barite (BaSO4) 0.2 (0.08) 0.6 (0.30) -0.16 (0.4) 0.5 (0.30) 0.7 (0.2) 1.1 (0.6)

Epsomite (MgSO4) -6.1 (6.4) -6.2 (6.7) -5.3 (-6.6) -5.3 (-7.2) -6.0 (-3.2) -5.9 (-7.6)

Gypsum (CaSO4) 2H20) -3.3 (-4.1) -3.7 ( -5.7) -2.9 (-5.0) -3.3 (-6.2) -3.4 (-6.6) -3.2 (-4.2)

Covellite (CuS) -26.2 (-27) -25.2 (-30.2) -26.7 (-4.6) -26.8 (-26.3) -23.5 (-39.6) -27.1 (-30.3)

Greemokite (CdS) -11.1 (-14) -10.8 (-16.11) -11.7 (-16.3) -16.5 (-20.4) -14.0 (-18) -11.2 (-14.5)

Galena (PbS) -9.5 (-11.1) -9.5 (-12.9) -10.2 (-13.0) -10.8 (-13.3) -9.0 (-11.7) -9.7 (-13)

Sphaletite (ZnS) -9.4 (-10.6) -9.4 ( 10.2) -10.1 (-11.0) -10.29 (-12.4) -9.4 (-11.2) -9.3 (-10.8)

Pyrite (FeS2) -6.3 (-6.8) -6.6 (-7.2) -726 (-7.7) -7.6 (-8.0) -6.4 (-6.8) -6.3 (-6.4)

Al (OH)3 -8.7 (-9.8) -9.0 (-10.0) -9.2 (-11.0) -8.8 (-9.6) -8.4 (-10.0) -8.2 (-9.2)

Fe (OH)3 -5.6 (-6.6) -5.4 ( -6.6) -6.0 (-7.2) -5.2 (-6.8) -4.8 (-0.8) -5.0 (-7.0)

Goethite (FeOOH) -7.2 (-9.0) -6.8 (-8.8) -7.0 (-9.2) -6.6 (-8.8) -6.4 (-8.2) -7.1 (-7.2)

Henatite (Fe2O3) -6.9 (-8.2) -6.8 (-9.0) -5.7 (-9.11) -5.3 (-80 -5.9 (-85) -6.6 (-9.2)

Magnetite (Fe3O4) -6.4 (-7.8) -6.49 (-7.8) -5.3 (-8.0) -5.0 (-7.1) -5.6 (-7.7) -6.2 (-8.0)

Cxalcite (CaCO3) -4.2 (-6.0) -4.4 (-6.2) -2.8 (-7.4) -2.7 (-7.2) -4.6 (-6.8) -5.1 (-6.9)

Siderite (FeCO3) -2.6 (-2.8) -2.6 (-3.0) -1.5 (-4.4) -1.2 (-1.8) -2.0 (-3.0.) -2.3 (-3.1)

Cerusite (PbCO3) -1.1 (-2.1) -1.6 (-1.8) -1.5 (-3.0) -2.0 (-2.6) -3.5 (-5.40) -4.2 (-6.0)

Witherite (ZnCO3) -6.0 (-8.4) -5.4 (-8.8) -5.2 (-9.0) -4.2 (-7.0) -5.7 (-7.80) -6.1 (-8.1)

Otavite (CdCO3) -4.3 (-6.3) -3.9 (-6.6) -3.7 (-7.1) -3.5 (-6.8) -3.8 (-6.90) -4.3 (-6.4)

Values in brackets are for wet season


123

Residual sodium carbonate (RSC)

When total carbonate concentration exceed the total

amount of Ca and Mg, the water quality may be impaired

for irrigational use. When the excess carbonate becomes

too high, it combines with Ca and Mg and precipitates.

Hence, the relative abundance of Na with respect alkaline

earths and the quantity of bicarbonates and carbonate in

excess of alkaline earths also influence the suitability of

water for irrigation use. In the pond and stream water, most

of the samples fall in the good category indicating water fit

for irrigation use (Table 12). However, 7 % of the stream

water samples from Mamfe Embayment (DS) were clas-

sified as doubtful for irrigation use.

Total dissolved solids (TDS) and electrical conductivity

(EC)

According to TDS classification, all the samples fall in the

fresh category indicating that the pond and stream water

are fit for irrigation (Table 12). The EC is usually con-

sidered important in classifying irrigation water. High EC

Table 12 Assessment of pond and stream waters for irrigation use

Parameter Range Class Pond Pond Pond Source Season Geology Stream Stream

Pond Stream Stream

Dry Dry Wet Wet Dry Dry Wet Wet

ME OM ME OM ME OM ME OM

Total no of samples (n) 5 3 5 3 15 7 15 7

Sodium adsorption ratio (SAR) \10.0 Excellent 100 100 100 100 100 100 100 100

10.0–18.0 Good

18.0–26.0 Doubtful

[26.0 Unsuitable

Percent sodium (% Na) \20 Excellent 20 29 14 14

20–40 Good 20 33 20 43 7

40–60 Permissible 60 67 40 67 60 14 21 86

60–80 Doubtful 20 33 40 13 14 33

[80 Unsuitable 7 28

Electrical conductivity (EC) lS/cm \250 Excellent 67 100 80 100 33 71 53 100

250–750 Good 33 20 67 29 47

750–2,000 Permissible

2,000–3,000 Doubtful

[3,000 Unsuitable

Residual sodium carbonate \1.25 Good 100 100 100 100 93 100 100 100

1.25–2.5 Doubtful 7

[2.5 Unsuitable

Kelly’s index (KI) [1 20 33 40 20 29 60

\1 80 67 60 100 80 71 40 100

Total dissolved solids (TDS) mg/l \1,000 Fresh 100 100 100 100 100 100 100 100

1,000–3,000 Slightly saline

3,000–10,000 Moderately saline

[10,000 High saline

Total hardness (TH) mg/l \75 Soft 100 100 100 100 73 100 100 100

75–150 Moderately hard 27

150–300 Hard

[300 Very hard

Permeability index (PI) % [75 Excellent 100 100 100 100 100 100 100 100

25–75 Good

\25 Unsuitable

Magnesium ratio (MH) % \50 % Suitable 80 67 20 67 13 71 20 14

[50 % Unsuitable 20 33 80 33 87 29 80 86

ME Mamfe Embayment, OM Oban Massif


123

leads to formation of saline soil (Nagarajan et al. 2010).

Most of the water samples from this study indicates good to

excellent water for irrigation with EC \ 250 lS/cm

(Table 12).

Permeability index (PI)

The permeability index indicates whether water is suitable

for irrigation. Doneen (1964) classified water as Class I

with permeability index [75 % (Excellent); Class II hav-

ing PI of between\75 to[25 % (Good) and Class III with

PI \ 25 % (Unsuitable). All the samples fall in the Class I

category, indicating excellent water for irrigation

(Table 12).

Total hardness (TH)

Water hardness refers to the soap neutralizing effect of

water. According to USGS hardness scale, majority of the

samples fall in the soft category. However, 27 % of stream

water from the Mamfe Embayment in the dry season fall in

the moderate category (Table 12).

Kelly index (KI)

.On the basis of Kelly’s index, the pond and stream water

samples are classified for irrigation use. A Kelly index [1

indicates excess of sodium in water (Kelly 1940; Paliwal

1967). Therefore water with KI \ 1 is suitable for irriga-

tion, whereas water with KI [ 1 is unsuitable. From

table 12, most of the water samples are suitable for irri-

gation use.

Magnesium hazard (MH)

Calcium and magnesium maintain a state of equilibrium in

most waters. In equilibrium, more magnesium will

adversely affect crop yields. It is observed that most of the

water contains more Ca and Mg. In this study, most of the

pond water samples from ME (DS), OM (DS & WS) and

stream water (OM, dry season) are suitable for irrigation

use (Table 12).

Discussions and environmental management

implications

The physical parameters (temperature, colour, pH, TDS,

EC, TSS and DO) showed significant variations. Temper-

ature (CV = 0.02 %) exhibited the least relative variabil-

ity, while colour (CV = 87 %) exhibited the highest

relative variability. Generally, the physical parameters

varied greatly amongst the different mine sites. High

variability was attributed to the changes in environmental,

geological or anthropogenic conditions (Lee et al. 2005).

The temperature values (28–30 �C) recorded for the water

samples were close to the atmospheric temperature

(23–32 �C) recorded during the sampling periods. The low

variability in temperature values was attributed to the high

heat capacity of water to act as a ‘‘thermal buffer’’ (Adamu

and Nyiatagher 2005).

There was no significant difference at p \ 0.05 between

values of colour observed from the pond water and stream

water samples. However, the mean value of colour in the

stream water was higher than the mean value of the pond

water (Table 5). High values of colour have been variously

attributed to iron content in water (Udom et al. 1998) and

suspended matter (Hem 1985). Thus the high values of

suspended particles recorded in this study and the observed

brownish/yellowish iron precipitates on river beds during

the field study may suggest these factors as impacting the

colour of water in the study area.

There was statistically significant difference (p \ 0.05)

in mean pH values between the pond water and stream

water samples. Besides, the mean values of pH obtained for

both dry and wet seasons (Table 5) were not within the

limits of 6.5–8.5 stipulated for drinking water by WHO and

NIS (2007), indicating the slightly to moderately acidic

nature of the water. According to Hem (1985), surface

water acidity is rare and can only occur in the presence of

strong mineral acids or carbonic acids. It is reasonable to

suggest that dissolution of CO2 from atmosphere, and

leaching of organic acid from decaying organic matter and

soils contribute to acidity of water in the study area

(Nganje et al. 2010). The relatively lower mean values of

pH in the mine area compared to the stream water samples

suggested the presence of strong mineral acids, most

probably from the weathering of sulphides, sulphates and

Fe-oxides in mine spoils.

The mean TDS values of the pond water samples for the

dry (202.88 mg/l) and wet seasons were significantly

(p \ 0.05) higher than the mean values for the stream

water samples. This indicated higher mineral dissolution in

the mine area compared to the streams. The mining of

barite, resulted in a marked increase in surface area of

mineralized rocks exposed to the atmosphere, which

induces chemical reactions leading to enhanced dissolu-

tion. The electrical conductivity followed the same trend as

the TDS.

The present study shows that Cl- and NO3- exhibited

low variability, while SiO2 and Ca exhibited high vari-

ability in the dry and wet seasons (Table 5). The cations

(Na?, K?, Mg2? and Ca2?) had concentrations generally

below \50 mg/l in waters from the pond and stream

waters. The enhanced level of Ba2? (*2 mg/l) in the mine

area relative to the stream waters was attributed to


123

weathering of barite (BaSO4). The relatively high contents

of Ba indicated that the waters from the area were con-

taminated from barite mining activities. This is also con-

sistent with elevated levels of Ba and SO4 in waters in

other areas affected by barite mining activities. The con-

tents of Ba were attributed to the oxidation and hydrolysis

of BaSO4 (Baldi et al. 1996).

Sodium and bicarbonate were the dominant cation and

anion, respectively. This reflected the excess of HCO3-

over alkaline earths (Ca2? ? Mg2?) concentrations.

According to Lee et al. (2005), the Na–HCO3 water type is

an indication of cation exchange processes. The probable

sources of carbonates were carbonate dissolution, dissoci-

ation of carbonic acid and silicate weathering (Nganje et al.

2010). According to Moncur et al. (2006), the dissolution

of carbonate and alumino-silicates released HCO3, which

neutralized the H? released by the oxidation of sulphide

minerals. Geochemical modelling using MINTEQA2�

indicated that the waters in the study area are undersatu-

rated with respect to calcite (Table 6), suggesting that

calcite dissolution is an important pH-buffering reaction in

the waters in this area. The mean values of SO4, in both

seasons, from the mine area were statistically significantly

different (p \ 0.05) from mean values in the stream water

samples. The source of SO4 was related to the oxidation of

the barite and pyrite, from the mine spoils (Akpeke 2008).

The study area is a rural agricultural set up, where more

than 90 % of the inhabitants are engaged in subsistence

agriculture. Land is intensively cultivated and domestic

animals are reared for food production. Some expanse of

land is, however, covered with thick vegetation and has

experienced minimal anthropogenic inputs. Manufacturing

industries are non-existence in the area. Some of the

inhabitants of the area are presently engaged in local

mining of barite.

In future, the uncontrolled disposal of the mine waste

materials will result in the contamination of water by

barium, suspended sediments and acidic mine drainage.

Streams draining the mine dump sites and ponds are used

for domestic, fishing and irrigation purposes. The common

diet of the wild and domestic animals and inhabitants is

locally grown crops. It is likely that animals and inhabit-

ants in the area might be accumulating barium through

ingesting tailings (Alloway 1990), through diet grown on

the contaminated soils (Cox 1995; Siegel 2002), and

drinking of contaminated water (Adiuku-Brown and Ogezi

1991; Adamu 2000) as well as feeding on fish from con-

taminated streams. The enhanced levels of Ba in the water

samples implied that it was accessible and may have had

some health implications on the animals and human beings

in the area through bioaccumulation and biomagnifications

of contaminants in animals and man (Alloway 1990; Siegel

2002). This is a health risk, especially for babies and

children in the study area (Adamu 2011). Besides, the pH

of the water is also low and may contribute in the further

dispersion of pollutants. Unfortunately, it was not possible

to sample crops, human and animal tissues in the area for

toxicological investigation.

High TSS and colour of the surface streams could lead

to poor penetration of light caused by absorbent or

reflecting pollutants (Hem 1985). This together with low

DO stream water diminished algal productivity and

decreased aquatic food.

Summary and conclusion

Water quality in the vicinity of barite mine sites shows that

the waters were characterized by low pH, low minerali-

zation, high suspended solids and high colour. Sodium

(Na?) and calcium (Ca2?) were the dominant cations and

bicarbonate (HCO3-) and sulphate (SO4

2-) the dominant

anions. The low concentration of dissolved silica, relatively

high concentrations of Na, HCO3 and SO4 suggest a

combined influence of silicate, carbonate and weathering of

mine spoils.

The TDS, TSS, EC and major ions (except Na? and K?)

are higher for water draining barite mines from Cretaceous

sediments, while Na?, K?, Ba2? are higher in basement

rock areas. Computed values of hardness and some irri-

gational parameters show that the pond and stream waters

are generally soft and can be used for irrigation. Correla-

tion and factor analyses indicate the association of physi-

cochemical parameters to be related to geogenic

environmental and anthropogenic controls. Generally, the

water quality satisfied the WHO (2008) and NIS (2007)

standards for domestic, agriculture and industrial.

Acknowledgments This study is part of the PhD dissertation of the

first author. The authors are grateful to the Benue State Government

for financial support. We appreciate the support and assistance we

received from the traditional rulers and youth leaders of Nde, Alese,

Okumurutet, Iyametet, Akpet 1 and Ibogo communities during the

field work. The support and encouragement from Prof. C. S. Okereke

of the Department of Geology University of Calabar is also

acknowledged.

References

Adamu CI (2000) Environmental geochemical studies of Arufu Pb–

Zn–Ag mining districts, Northeastern Nigeria. M.Sc. Thesis.

University of Calabar, Nigeria

Adamu CI (2011) Geoenvironmental studies of barite mines in parts

of Oban Massif and Mamfe embayment, Southeastern Nigeria.

PhD Dissertation. University of Calabar, Nigeria

Adamu CI, Nyiatagher T (2005) Physico-chemical and bacteriolog-

ical quality of surfacewater of River Benue, Nigeria. Glob J Geol

Sci 3(1):45–48


123

Adamu CI, Nganje TN, Edet A (2009) Hydrochemistry of waters near

some barite mining areas, Cross River State, Nigeria. DAAD

Alumni expert seminar on ‘‘Mining and Water’’ October 5th–

9th, Namibia

Adiuku-Brown ME, Ogezi AE (1991) Heavy metal pollution from

mining practices: a case study of Zurak. J Mining Geol

27(2):205–211

Akpeke GB (2008) Investigation of the origin, nature and occurrence

of barite mineralization in CRS, Southeastern Nigeria. PhD

Dissertation University of Calabar, Nigeria

Alam M, Sumbul R, Aslam M (2012) Hydrochemical investigation

and quality assessment of groundwater in rural areas of Delhi,

India. Environ Earth Sci 66:97–110

Alloway BJ (1990) Heavy metals in Soil. J Agric Scis 241:1511–1514

ALPHA (1995) Study methods for the examination of water and

waste, 2nd edn. DC Willey, Washington

Bahar MM, Reza MS (2010) Hydrochemical characteristics and

quality assessment of shallow groundwater in a coastal area of

southwest Bangladesh. Environ Earth Sci 61:1065–1073

Baldi F, Pepi M, Burini D, Kniewald G, Scali D, Lanciotti E (1996)

Dissolution of barium from barite in sewage sludges and cultures

of Desulforibrin desulfuricans. Appl Environ mineral

67(7):2398–2404

Bell RG, Rusell C (2002) Environmental policy for developing

countries. Issues in science and technology. Springer University

Press, New York

Chukwuma C (1995) Evaluating baseline data for Cu, Mn, Ni and Zn

in rice, yams, cassava and guinea grass from cultivated soils in

Nigeria. Agric Ecosyst Environ 53:47–61

Cox PA (1995) The elements on earth: Inorganic geochemistry in the

environment. Oxford University Press, New York

Cross River Basin Development Authority, CRBDA (1992) Inventory

of Natural Site Conditions-Soil, Slope, Hydrology, Landuse and

Vegetation throughtout the areas of operation of the Authority.

Surveys and Mapping Geodata Ltd (Nigeria) with Institute of

Applied Geosciences (Germany), pp 145

Dogan PA (1999) Characterization of mine waste for prediction of

acid mine drainage. In: Azcue JM (ed) Environmental impact of

mining activities. Springer, Heidelberg, pp 19–38

Doneen LD (1964) Notes on water quality in agriculture. Published in

Water Science and Engineering University of California, Davis

Eaton FM (1950) Significance of carbonates in irrigation waters. Soil

Sci 39:123–133

Edet AE (1993) Hydrogeology of parts of Cross River State, Nigeria:

Evidence from Aero-Geological and Surface Resistivity Studies.

PhD Dissertation, University of Calabar, Calabar, Nigeria

Edet AE, Markel BI, Offiong OE (2003) Trace element hydrochem-

ical assessment of the Calabar coastal plain aquifer, Southeastern

Nigeria: using statistical methods. Environ Geol 44:137–149

Edet AE, Worden RH, Mohammed EA, Preston MR (2012)

Hydrogeochemical processes in a populated shallow Coastal

Plain Sand Aquifer southeastern Nigeria. Environ Earth Sci

65:1933–1953

Egeh EU, Ekwueme BN, Akpeke B (2004) The appraisal of a

proposed barite quarry in Akpet area, Cross River State, from

resistivity investigation. Global J Geol Sci 2(2):171–175

Ekwueme BN (1995a) Geochemistry of the crystalline basement

rocks in SW Ugep, Nigeria. Dee-Ford J Pure Appl Sci 1:15–28

Ekwueme BN (1995b) Geological excursion guide book. Bachude

Print Press, Calabar

Ellis KU (1993) Surface water pollution and its control. Macmillan

Press, London

European Union, EU (1975) Council Directive 75/440/EEC of 16

June 1975 concerning the quality required of surface water

intended for the abstraction of drinking water in the Member

States as amended by Council Directive 79/869/EEC (further

amended by Council Directive 81/855/EEC and Council Regu-

lation 807/2003/EC) and both amended by Council Directive

91/692/EEC (further amended by Regulation 1882/2003/EC)

Franciskovic-Bilinski S (2006) Barium anomaly in Kupa River

Drainage Basin. J Geochem Explor 88:106–109

Gibbs RJ (1970) Mechanisms controlling water chemistry. Science

170:1088–1090

Hem JD (1985) Study and interpretation of the chemical character-

istics of natural waters. US Geol. Survey Water Supply Paper

1473, 3rd edn. Harvard University Press, Massachusetts

Iloeje NP (1997) A new geography of Nigeria. Longman Ltd, Benin

Jeong CH (2001) Effect of landuse and urbanization on hydrochem-

istry and contamination of groundwater from Taejon area,

Korea. J Hydrol 253:194–210

Jung MC (2001) Heavy metal contamination of soils and waters in

and around the Inacheon Au-Ag mine, Korea. Appl Geochem

16:1369–1375

Kelly WP (1940) Permissible composition and concentration of

irrigated waters. Proc AFCS 66:607

Lee JS, Chon HT, Jung MC (2005) Toxic risk assessment and

environmental contamination of heavy metals around abandoned

metal mine sites in Korea, Key Eng. Materials 277:542–547

Matalas CN, Reiher JB (1967) Some comments on the use of factor

analysis. Water Resour 3:213–223

Moncur MC, Ptacek CJ, Blowers DW, Jambor JL (2006) Release,

transport and attenuation of metals from an old tailings

impoundment. Appl Geochem 20:639–659

Nagarajan R, Rajmohan N, Mahendran U, Senthamilkumar S (2010)

Evaluation of groundwater quality and its suitability for drinking

and agricultural use in Thanjavur city, Tamil Nadu, India.

Environ Monit Assess 171(1–4):289–308. doi:10.1007/s1066-

009-1279-9

Nagaraju A, Suresh S, Killam K, Hudson-Edwards K (2006)

Hydrogeochemistry of waters of Mangompeta barite mining

area, Cuddapah Basin, Andhra Pradesh, India. Turkish J Environ

Sci 30:203–219

NEST (1995) The challenge of sustainable development in Nigeria.

In: Aina TA, Salan AT (eds) Nigerian Environmental study

Action Team Report. Nigeria pp 16–44

Nganje TN, Adamu CI, Ugbaja AN, Ebieme E, Sikakwe GU (2010)

Environemntal contamination of trace elements in the vicinity of

Okpara coal mine, Enugu Southeastern Nigeria. Arabian J

Geosci. doi:10.1007/-S12517-010-0673-7

Nganje TN, Adamu CI, Ugbaja AN, Ebieme E, Sikakwe GU (2011)

Environmental contamination of trace elements in the vicinity of

Okpara coal mine, Enugu Southeastern Nigeria. Arabian J

Geosci 4(1 & 2):195–200

Nigerian Industrial Standard, NIS (2007) Nigerian Standards for

drinking water quality. SON Wuse, Abuja

Nwabufo-Ene KE (1993) Non – oil mineral exploration in Nigeria.

J Sci Technol 1(1):15–30

Oden MI (2001) Mineral potentials of Cross River State; Strategies

for optimal utilization. Paper presented at the 1st NNDC

stakeholders forum and workshop, Calabar, 2001

Okereke CS, Esu EO, Edet AE (1998) Determination of potential

groundwater sites using geological and geophysical techniques

in the Cross River State, Southeasthern Nigeria. J Afr Earth Sci

27(1):149–163

Olade MA (1976) On the genesis of Pb–Zn deposits in Nigeria’s Benue

rift (aulacogen): a reinterpretation. J Mining Geol 13:20–27

Paliwal KV (1967) Effect of Gypsum application on the quality of

irrigated waters. Madras Agric J 59:646–647

Parkhurst DL, Appelo CAJ (1999) Users guide to PHREEQC (version

2)—a computer program for speciation, batch – reactions one-

dimensional transport, and inverse geochemical calculations. US

Geol. Survey Water Resour. Invest. Rept


123

http://dx.doi.org/10.1007/s1066-009-1279-9

http://dx.doi.org/10.1007/s1066-009-1279-9

http://dx.doi.org/10.1007/-S12517-010-0673-7

Petters SW (1989) A regional hydrogeological study of rural water

supply options for planning and implementations of phase II

rural water programme of Cross River State. DFRRI, Cross

River State, Unpublished report

Petters SW, Okereke CS, Nwajide CS (1987) Geology of the Mamfe

Rift Southeastern Nigeria. In: Matheis G, Schadelimeirer HS

(eds) Current research in African Earth Sciences. Balkema,

Rotterdam, pp 299–302

Piper AM (1944) A graphical procedure in geochemical interpretation

of water analysis. Trans Am Geophys Union 25:914–923

Prasanna MV, Chidambaram S, Gireesh TV, Jabir Ali TV (2011) A

study on hydrochemical characteristics of surface and subsurface

water in and around Perumal Lake, Cuddalore district, Tamil

Nadu, South India. Environ Earth Sci 63:31–47

Ragunath HM (1987) Groundwater. Wiley Eastern Ltd, New Delhi

Rahman AAMS, Ukpong EE, Azumatullah M (1981) Geology of

parts of the Oban Massif, Southeastern Nigeria. J Mining Geol

18(1):60–65

Richards LA (1954) Diagnosis and improvement of saline alkali soils.

US Department of Agriculture, Handbook 60, pp 160

Rose AW, Cravotta CA (1998) Geochemistry of coal mine drainage.

In: Brady KBC, Smith MW, Schueck J (eds) Coal mine drainage

prediction and pollution prevention in Pennsylvania. Dept. of

Enviro. Protection, Harrisburg, pp 53–82

Sawyer CN, McCarthy PL (1967) Chemistry for sanitary engineers,

2nd edn. McGraw Hill, New York

Siegel FR (2002) Environmental geochemistry of potential toxic

metals. Springer, Heidelberg

Sinclair AJ (1974) Selection of thresholds in geochemical data using

probability graphs. J Geochem Explor 3:129–149

Subba Rao N (2006) Seasonal variation of groundwater quality in a part

of Guhur district, Andhra Pradesh India. Environ Geol 49:413–429

Todd DK (1980) Groundwater hydrology, 2nd edn. Wiley, New York

Udom GJ, Esu EO, Ekwere SJ (1998) Status of groundwater in

Calabar Municipality, Southeastern Nigeria. Global J Pure Appl

Sci 4(2):163–169

WHO (2008) Guideline for drinking-water quality (3rd edn incorpo-

rating 1st and 2nd Agenda) vol 1, Recommandations Genva

Wilcox LV (1955) Classification and use of irrigation water. USDA

circular, Washington

World Health Organization, WHO (1993) Guideline for drinking

water quality, Geneva


water quality, vol 1. Geneva, pp 53–73


water quality, Geneva

Younger P, Banwart S, Hedin R (2002) Mine water hydrology,

pollution and remediation. Kluwer, Dordrecht


123

Date post:	25-Jan-2017
Category:	Documents
Upload:	aniekan
View:	212 times
Download:	0 times

Hydrochemical assessment of pond and stream water near abandoned barite mine sites in parts of Oban...

Documents