Physicochemical characteristics of Lake IRAD, an artificial lake in Wakwa region, Cameroon

Physicochemical characteristics of Lake IRAD, an

artificial lake in Wakwa region, CameroonW.M.L. Fezeu,1,2*M.B. Ngassoum,1 E. Montarges-Pelletier,3 G. Echevarria4 and

C.M.F. Mbofung1

1National School of Agro-Industrial Sciences, Ngaoundere University, Ngaoundere, Cameroon, 2Belisle Laboratory,

100 Fisher, Mont-St-Hilaire (Quebec), Canada, 3Laboratoire Environnement et Mineralurgie, CNRS-Nancy University,

15 avenue du Charmois, 54500 Vandoeuvre les Nancy, France, and 4Laboratory of Soil and Environmental Sciences

(LSE), E.N.S.A.I.A. – INPL, Vandoeuvre-les-Nancy, France

AbstractWakwa is a region in north Cameroon characterized by intensive cattle production. This study evaluated the physico-

chemical characteristics of the waters in Lake IRAD, located near Wakwa, which is the main water source for cattle graz-

ing in this area. Water samples were collected at four sampling sites during the rainy and dry seasons (April, July,

October and February). The chemical composition of the water samples was analysed for various constituents, including

nitrate (NO3–), chloride (Cl)), phosphate (PO4

3)), bicarbonate (HCO3)), calcium (Ca), magnesium (Mg), manganese

(Mn), aluminium (Al), zinc (Zn), copper (Cu), iron (Fe), nickel (Ni), cadmium (Cd), ammonia–nitrogen (NH4–N) and

organic matter (OM). The mineral composition varied significantly (P < 0.05) with the sampling period. High concentra-

tions of zinc (0.96 mg L)1) and dissolved iron (1.23 mg L)l) were observed during the dry season. Total iron

(3.25 mg L)1), OM (15.4 mg of O2 L)1), nitrate (28.82 mg L)1) and NH4–N (1.05 mg L)1) concentrations were highest

during the rainy season. The iron, OM and NH4–N concentrations were higher than the USEPA-recommended values

(0.2 mg L)1, 4 mg of O2 L)1 and 0.5 mg L)1, respectively). The phosphate, copper, nickel and cadmium concentrations,

considered as the polluting substances, were present in negligible concentrations, being below the detection limits of the

analytical techniques used to measure them. The high iron, OM and nitrogen concentrations were attributed to water-lea-

ched soil run-off, as well as the activity of animals in the lake. Sampling sites 1 and 2, which were used mostly by cattle,

were observed to have the highest concentrations of NH4–N, compared with sites 3 and S (exit point). It will be neces-

sary to delimit cattle access points to the lake to reduce this type of contamination of drinking water.

Key wordsagricultural activities, lake, livestock husbandry, minerals.

INTRODUCTIONAlthough an important physiological requirement for all

life, including humans, water is not uniformly distributed

on our planet. Grazing cattle in most tropical countries

generally use surface water sources (e.g. rivers, lakes

and springs) to satisfy their water needs. Being a tropical

country, Cameroon has readily substantial water during

its rainy season. In contrast, during the dry season, after

the rains have ended, and rivers have dried up, water

demands increase at the same time that water sources

become rare. In the Adamawa region, a major cattle-rais-

ing area of Cameroon, the dry season is generally

marked by nomadic behaviour, during which cattle farm-

ers bring their cattle to the few water points that have

resisted to drought (Boutrais 1974).

Cattle raising is generally artisanal in the Adamawa

region, with grazers using any accessible water source to

satisfy their water needs (e.g. rivers, lakes and springs).

Although animals can tolerate poor water quality better

than humans, cattle can nevertheless be affected if the

concentrations of some specific compounds (organic or

mineral) in the water they drink are sufficiently elevated.

Although the cattle might not exhibit clinical signs of ill-

ness, growth, lactation and reproduction might be

affected (Braul & Kirychuk 2001). Thus, the mineral

*Corresponding author. Email: [email protected]

Accepted for publication 15 May 2009.

� 2009 The AuthorsDoi: 10.1111/j.1440-1770.2009.00402.x Journal compilation � 2009 Blackwell Publishing Asia Pty Ltd

Lakes & Reservoirs: Research and Management 2009 14: 259–268

quality of water is a very important parameter for optimal

cattle raising and reproduction. Water deemed safe for

human consumption must meet specific criteria (NRC

(National Research Council) 2001), including organoleptic

properties (e.g. odour and taste), physicochemical prop-

erties (e.g. pH, total dissolved solids and hardness, total

dissolved oxygen and suspended solids) toxic compound

levels (e.g. heavy metals, organophosphates and hydro-

carbons), excess cations or anions levels (e.g. nitrates,

sodium, sulphates and iron) and bacterial levels.

To facilitate cattle grazing consistent with these crite-

ria, watering points for cattle are distributed and the

water quality is controlled. In recognition of this link

between the quality of water and its effects on cattle rear-

ing, researchers at the Wakwa Research Center, in the

Adamawa region of Cameroon, constructed an artificial

lake to satisfy cattle water needs.

For grazing lands for which the aforementioned crite-

ria are being met, the drinking points are well con-

structed and protected. Fewer precautions, however, are

taken to protect water quality in many tropical pastures.

As a result, these latter water sources are susceptible to

contamination by the cattle that drink it. This concern is

especially serious at Wakwa, in Cameroon, owing to the

interrelation of farming and cattle raising (Boutrais 1974).

As a result, the available water sources used by both

cattle breeders and farmers, as well as for human activi-

ties, could be significantly contaminated.

The artificial lake covered the water requirements of

cattle for the research centre at Wakwa 60 years ago dur-

ing the rainy season, and especially in the dry season.

With the contribution of rain water, the lake has usually

has an important surface area, becoming with time an

important drinking water source for animals in the lake

vicinity during both dry and rainy seasons. This lake is

not only a water source for cattle breeders, but also a

source of minerals for animals. At the same time, how-

ever, it also might represent a health and ⁄ or environmen-

tal danger, as it is possible to find dead fish in the lake

during the dry season, likely attributable to organic or

mineral pollution (Hubbard et al. 2004). Despite the

importance of this lake for watering livestock, no informa-

tion exists on the quality of its water, although of organic

matter (OM) contamination of these waters have been

previously demonstrated (Sangogin 1991; Mignolet et al.

1999; Smith et al. 1999).

Accordingly, the objective of this study was to deter-

mine the organic and mineral quality of the waters in the

artificial lake at the Wakwa Research Center.

METHODSThe study deals with is an artificial lake of the Institute of

Agricultural Research for Development (IRAD), Camer-

oon. Hereafter referred to as Lake IRAD, the lake is situ-

ated at Wakwa (located �10 km from Ngaoundere,

Cameroon), with a surface area of 36.6 ha (Fig. 1). Wakwa

is located in a soudano-Guinean climate area, with one dry

season (generally from November to March) and one rainy

season (from April to October) (Pamo & Yonkeu 1986).

Sampling was carried out at four sites in the lake

coded 1, 2, 3 and S (Fig. 1 and Table 1) in: (i) April (tran-

sition from dry to rainy seasons); (ii) July (rainy season);

(iii) October (end of rainy season); and (iv) February

(dry season). These sampling sites correspond to: (i)

zones where cattle drink (sites 1 and 2); (ii) zones that

are inaccessible to animals during the rainy season (site

3); and (iii) the site where water exits the lake during

Fig. 1. Geographic location of Lake

IARD (Institute of Agricultural

Research for Development) sampling

sites, Wakwa region, Cameroon.

� 2009 The AuthorsJournal compilation � 2009 Blackwell Publishing Asia Pty Ltd

260 W. M. L. Fezeu et al.

the rainy season (site S). Water samples were collected

in cleaned polypropylene bottles, and quickly transported

to the laboratory for chemical analyses.

The pH was measured with a portable pH meter (PIC-

COLO-ATC brand, Hanna, France), whereas the electrical

conductivity (EC; v) was measured with a TACUSSEL

CD-60 resistivimeter (Tacussel Electronique, France).

The bicarbonate, carbonate and chloride concentrations

were determined by titrimetric methods (AFNOR 1986).

The sulphate and nitrate concentrations were assayed on

the basis of the colorimetric methods described by

Rodier (1978). As also described by Rodier (1978), a

method that makes use of the oxidative properties of per-

manganate was utilized to determine the OM content in

the water samples.

The water samples were filtered through a 0.2 lm fil-

ter and analysed for dissolved iron and filtered trough

25 lm filter and digested with concentrated nitric acid

and analysed for total calcium, magnesium, sodium, iron,

aluminium, manganese and zinc concentrations, using

inductive coupled plasma atomic emission spectrometry

(ICP-AES). The copper content was assayed via atomic

absorption spectrophotometry (Varian SpectrAA-600, Var-

ian, Palo Alto, CA, USA).

All analyses were carried out in duplicate. The data

were then subjected to analysis of variance (ANOVA), as a

means of detecting the effects of period (month) and

sampling location on the physicochemical composition of

the lake water. The Duncan multiple range test (DMRT)

was used to compare individual means in the case of sig-

nificant variations. Pearson’s correlation was used to

determine the relationships between all the analysed

parameters. Statistical analyses were carried out with the

Statgraphics Plus 5.2 (ANOVA, Statpoint Technologie, Inc.,

USA) and Statistica (Pearson’s correlation, Statsft, Inc.,

USA) software. The statistical significance of the data

was defined at P < 0.05.

RESULTS AND DISCUSSIONThe physicochemical characteristics of the water samples

collected at the different sampling sites are summarized

in Table 2 and Figures 2–7. The pH values for the differ-

ent water samples varied between 6.13 and 7.78. The

measured pH values were within the acceptable range (6

and 8.5) for human or cattle consumption, respectively

(Rodier 1978; Harris & Van Horn 1992; EPA (Environ-

mental Protection Agency) 1997). There was a significant

variation (P < 0.05) of pH with different seasons, whereas

the sampling sites were not significantly different. The

highest pH value was measured for October, and the low-

est for February.

Rainwater, which has a slightly acidic pH, as well as a

dilution effect, could be responsible for the decreased pH

values during the rainy season, whereas the lake water

was generally stagnant during the dry season. This could

encourage biological productivity in the lake, thereby

causing the elevated pH values (Neal et al. 2000). The

elevated pH values in April also could be attributable to

the leaching of soils rich in organic elements, which

entered the lake in the run-off from the first precipitation

events. A positive, significant correlation was observed

between pH and OM (r = 0.6; P < 0.001), the latter being

apparently linked to soil leaching by rainwater (Table 3;

Viers et al. 1997). This observation was confirmed in

Figure 3, which illustrates the variation of OM with sea-

sons. The highest value for OM was observed in April

(14 ± 2 mg L)1), decreasing to 6 ± 1 mg L)1 of O2 L)1 in

February in the dry season.

The variation of ammonia–nitrogen (NH4–N) with sea-

son is illustrated in Figure 4. The NH4–N concentration

decreased in July, with the highest concentrations

observed in October. With a weak circulation of lake

waters during the dry season, development of a high

quantity of vegetation would cause a decrease in the dis-

solved oxygen concentration in the water and, therefore,

the NH4–N concentration (Satoh et al. 2001, 2002).

Although the contribution of the OM is higher with rain-

fall, the rain results in a dilution effect that prevents vege-

tative and microbial development, and maintains a low

NH4–N concentration (Satoh et al. 2001). Thus, the accu-

mulation of OM occurs during the rainy season, whereas

it deteriorates during the dry season. In this study, in

spite of the high quantity of OM observed in April (first

rains) and July (month of highest rainfall), the NH4–N

concentration was not higher than that observed in

October when rainfall has decreased, and the oxygen

contributed to OM decomposition, producing NH4–N.

Nevertheless, the higher NH4–N concentration in Octo-

ber (the rainy season) indicated that several other

parameters could have also enhanced the NH4–N concen-

tration in the lake waters. As illustrated in Figure 4,

regardless of the month, sampling sites 1 and 2 (most

Table 1. Geographic coordinates of Lake IRAD (Institute of

Agricultural Research for Development) sampling sites

Longitude Latitude Altitude

Site 1 7�26572N 13�53700E 1205M

Site 2 7�26491N 13�53388E 1201M

Site 3 7�25977N 13�53350E 1195M

Site S 7�26450N 13�53818E 1184M


Physicochemical characteristics of Lake IRAD 261

Tab

le2.

Phys

icoch

emic

alch

arac

terist

ics

of

Lake

IRA

D(In

stitute

of

Agricu

ltura

lRes

earc

hfo

rD

evel

opm

ent)

wat

ers

Period

Poin

ts

v

(ls

cm)

1)

HC

O3)

(mg

L)1)

CO

32)

(mg

L–1)

Cl)

(mg

L–1)

SO42)

(mg

L–1)

NO

3)

(mg

L–1)

PO43)

(mg

L–1)

Ca

(mg

L–1)

Mg

(mg

L–1)

Na

(mg

L–1)

K

(mg

L–1)

Al

(mg

L–1)

Mn

(mg

L–1)

Cd

(mg

L–1)

Ni

(mg

L–1)

Febru

ary

129.8

28.8

<1

3.7

0.5

<0.1

<0.1

2.2

1.4

1.4

1.8

0.6

<0.1

<0.0

1<

0.0

1

229.8

28.9

<1

4.0

0.8

<0.1

<0.1

2.9

2.8

1.8

1.2

0.3

<0.1

<0.0

1<

0.0

1

329.8

28.9

<1

3.6

1.3

<0.1

<0.1

2.5

4.2

2.5

1.5

1.6

<0.1

<0.0

1<

0.0

1

S30.5

29.1

<1

3.6

0.7

<0.1

<0.1

6.0

1.5

2.2

1.4

0.3

<0.1

<0.0

1<

0.0

1

Mea

n30.0

±0.4

c28.9

±01

b<

1a

3.7

±0.2

b0.8

±0.3

a<

0.1

a<

0.1

3.4

±1.8

a2.5

±1.3

ab

2.0

±0.5

b1.5

±0.3

c0.7

±0.6

ab

<0.1

<0.0

1<

0.0

1

April

17.8

31.3

4.7

11.9

1.0

<0.1

<0.1

10.4

1.4

1.7

0.7

0.4

<0.1

<0.0

1<

0.0

1

27.4

29.2

6.3

6.0

1.5

0.3

<0.1

24.6

1.7

2.3

0.8

0.8

<0.1

<0.0

1<

0.0

1

38.1

36.6

<1

7.1

0.6

1.1

<0.1

2.3

1.6

1.8

0.7

0.4

<0.1

<0.0

1<

0.0

1

S7.9

32.6

<1

6.1

1.0

1.0

<0.1

12.5

1.4

1.4

0.8

0.5

<0.1

<0.0

1<

0.0

1

Mea

n7.8

±0.3

a32.4

±3.1

b2.7

±3.2

b7.8

±2.8

c1.1

±0.4

a0.6

±0.5

a<

0.1

12.5

±9.2

b1.5

±0.1

a1.8

±0.4

b0.8

±0.1

ab

0.5

±0.2

ab

<0.1

<0.0

1<

0.0

1

July

111.1

25.5

<1

2.0

1.0

24.5

<0.1

1.9

5.7

1.6

1.2

0.7

<0.1

<0.0

1<

0.0

1

25.3

21.3

<1

2.1

0.2

26.6

<0.1

1.4

1.0

1.4

1.0

1.4

<0.1

<0.0

1<

0.0

1

35.4

13.3

<1

1.8

0.9

<0.1

<0.1

2.2

3.1

1.4

1.2

0.5

<0.1

<0.0

1<

0.0

1

S6.1

24.9

<1

1.8

1.0

27.4

<0.1

1.7

4.7

1.2

0.7

0.6

<0.1

<0.0

1<

0.0

1

Mea

n7.0

±2.8

a23.9

±1.9

a<

1a

1.9

±0.2

a0.8

±0.4

a19.6

±13.1

b<

0.1

1.8

±0.3

a3.6

±2.1

b1.4

±0.2

a1.1

±0.2

b0.8

±0.4

c<

0.1

<0.0

1<

0.0

1

Oct

ober

127.3

20.3

<1

2.3

0.7

<0.1

<0.1

2.2

4.7

1.3

0.6

0.3

<0.1

<0.0

1<

0.0

1

228.4

21.9

<1

5.0

0.5

<0.1

<0.1

1.6

1.2

1.5

0.7

0.4

<0.1

<0.0

1<

0.0

1

326.2

22.5

<1

4.4

1.2

<0.1

<0.1

13.2

1.2

1.2

0.7

0.3

<0.1

<0.0

1<

0.0

1

S27.3

23.9

<1

5.1

0.5

<0.1

<0.1

2.4

1.2

1.5

0.6

0.5

<0.1

<0.0

1<

0.0

1

Mea

n27.3

±0.9

ab

22.1

±1.5

a<

1a

4.2

±1.3

b0.7

±0.3

a<

0.1

a<

0.1

4.9

±5.6

a2.1

±1.8

a1.4

±0.2

a0.7

±0.1

a0.4

±0.1

a<

0.1

<0.0

1<

0.0

1

Mea

ns

with

the

sam

ele

tter

sar

enot

signifi

cantly

diffe

rent

atP

<0.0

5,

acco

rdin

gto

Dunca

nm

ultip

lera

nge

test

.



often visited sites) exhibited the highest NH4–N concen-

trations. These latter observations on sites 1 & 2 suggest

that while consuming waters, animals likely contamined

the lake with their faeces and urine, and thus contributed

to the increase of NH4-N level (Hooda et al. 2000).

It was interesting to note that the water pH was within

normal limits. However, the content of OM, which coin-

cided with oxygen values between 5.4 and 15.4 mg of

O2 L)1, and the NH4–N concentrations as 1.05 mg L)1,

were above the recommended minimal values (i.e. 4 mg

of O2 L)1 and 0.5 mg L)1, respectively; Rodier 1978; EPA

1997; Delisle et al. 1998). The low quality of these waters

used for cattle is substantiated by its appearance and the

0

0.2

0.4

0.6

0.8

1

1.2

1.4

February

Dis

solv

ed F

e m

g L–1

Point 1

Point 2

Point 3

Point S

*0.05 ± 0.05a

April July October

*0.46 ± 0.51b *0.69 ± 0.24c *0.35 ± 0.27b

Fig. 6. Variation of dissolved iron (dissolved Fe) concentrations

as a function of sampling period and site.

0

0.2

0.4

0.6

0.8

1

1.2

February

Zn

mg

L–1

Point 1

Point 2

Point 3

Point S

*0.29 ± 0.24a*0.36 ± 0.20ab *0.55 ± 0.31b *0.32 ± 0.28a

April July October

Fig. 7. Variation of zinc (Zn) concentrations as a function of

sampling period and site.

5

5.5

6

6.5

7

7.5

8

Febru

ary

April

July

Octobe

r

pHPoint 1

Point 2

Point 3

Point S

*6.86 ± 0.2b *6.39 ± 0.26a

* Mean per month

*6.36 ± 0.17a*7.67 ± 0.12c

Means with the same letters are notsignificantly different at P < 0.05

Fig. 2. Variation of pH as a function of sampling period and site.

0

0.5

1

1.5

2

2.5

3

3.5

February April July October

Tot

al F

e m

g L–1

Point 1

Point 2

Point 3

Point S

*1.16 ± 0.97ab *0.83 ± 0.36a *1.67 ± 0.96b *1.29 ± 0.29ab

Fig. 5. Variation of total iron (total Fe) concentrations as a func-

tion of sampling period and site.

0

2

4

6

8

10

12

14

16


Org

anic

mat

ter

mg

of O

2 L–1

Point 1

Point 2

Point 3

Point S

*6.36 ± 1.00a *13.62 ± 1.52d *7.73 ± 0.95b*10.61 ± 0.96c

Fig. 3. Variation of organic matter concentrations as a function

of sampling period and site.

0

0.2

0.4

0.6

0.8

1

1.2


N-N

H4

mg

L–1

Point 1

Point 2

Point 3

Point S

*0.48 ± 0.24b *0.53 ± 0.32bc *0.31 ± 0.12a *0.67 ± 0.35c

Fig. 4. Variation of ammonia–nitrogen (N–NH4) concentrations

as a function of sampling period and site.



Tab

le3.

Corr

elat

ions

bet

wee

ndiffe

rent

chem

ical

par

amet

ers

for

Lake

IRA

D(In

stitute

of

Agricu

ltura

lRes

earc

hfo

rD

evel

opm

ent)

pH

v

Bic

arbonat

e

(HC

O3))

Car

bonat

e

(CO

32))

Chlo

ride

(Cl)

)

Sulp

hat

e

(SO

42))

Org

anic

mat

ter

(OM

)

Am

monia

–

nitro

gen

(N–N

H4)

Nitra

te

(NO

3))

Cal

cium

(Ca)

Mag

nes

ium

(Mg)

Sodiu

m

(Na)

Pota

ssiu

m

(K)

Alu

min

ium

(Al)

Tota

l

iron

(Fe)

Dis

solv

ed

iron

(Fe

dis

.)

Man

gan

ese

(Mn)

pH v

)0.3

34

P=

0.0

62

HC

O3)

0.8

57

)0.2

10

P=

0.0

00

P=

0.2

49

CO

32)

0.6

39

)0.3

62

0.2

71

P=

0.0

00

P=

0.0

42

P=

0.1

33

Cl)

0.7

45

)0.1

54

0.5

90

0.6

13

P=

0.0

00

P=

0.4

01

P=

0.0

00

P=

0.0

00

SO42)

0.4

64

)0.1

67

0.2

61

0.5

34

0.2

00

P=

0.0

07

P=

0.3

61

P=

0.1

49

P=

0.0

02

P=

0.2

72

OM

0.5

69

)0.8

44

0.4

93

0.3

80

0.5

04

0.1

23

P=

0.0

01

P=

0.0

00

P=

0.0

04

P=

0.0

32

P=

0.0

03

P=

0.5

03

N–N

H4

)0.2

70

0.4

15

)0.3

71

)0.0

60

)0.2

34

)0.0

98

)0.3

96

P=

0.1

36

P=

0.0

18

P=

0.0

37

P=

0.7

45

P=

0.1

98

P=

0.5

93

P=

0.0

25

NO

3)

)0.3

09

)0.4

90

)0.2

97

)0.1

79

)0.4

59

)0.1

84

0.1

39

)0.2

22

P=

0.0

86

P=

0.0

04

P=

0.0

99

P=

0.3

27

P=

0.0

08

P=

0.3

14

P=

0.4

49

P=

0.2

21

Ca

0.6

19

)0.2

42

0.2

70

0.7

68

0.4

61

0.6

84

0.2

62

0.0

23

)0.3

00

P=

0.0

00

P=

0.1

82

P=

0.1

35

P=

0.0

00

P=

0.0

08

P=

0.0

00

P=

0.1

48

P=

0.9

02

P=

0.0

96

Mg

)0.2

86

)0.0

46

)0.2

16

)0.2

14

)0.5

27

0.3

09

)0.1

49

0.0

18

0.4

07

)0.3

51

P=

0.1

12

P=

0.8

05

P=

0.2

35

P=

0.2

39

P=

0.0

02

P=

0.0

85

P=

0.4

16

P=

0.9

21

P=

0.0

21

P=

0.0

49

Na

0.4

23

0.1

40

0.4

80

0.3

80

0.2

13

0.4

07

)0.1

37

)0.0

63

)0.2

67

0.2

84

0.0

25

P=

0.0

16

P=

0.4

44

P=

0.0

05

P=

0.0

32

P=

0.2

41

P=

0.0

21

P=

0.4

54

P=

0.7

34

P=

0.1

40

P=

0.1

16

P=

0.8

94

K)

0.0

72

0.2

92

0.1

88

)0.2

04

)0.3

09

)0.0

13

)0.3

67

)0.0

19

)0.0

49

)0.2

10

0.1

14

0.3

47

P=

0.6

96

P=

0.1

05

P=

0.3

03

P=

0.2

64

P=

0.0

85

P=

0.9

44

P=

0.0

39

P=

0.9

19

P=

0.7

91

P=

0.2

48

P=

0.5

34

P=

0.0

52

Al

)0.1

05

)0.1

21

)0.0

75

0.0

06

)0.2

58

0.0

32

)0.1

69

0.0

30

0.3

75

)0.1

17

0.1

67

0.4

21

0.3

05

P=

0.5

66

P=

0.5

10

P=

0.6

84

P=

0.9

73

P=

0.1

55

P=

0.8

64

P=

0.3

56

P=

0.8

71

P=

0.0

34

P=

0.5

23

P=

0.3

62

P=

0.0

16

P=

0.0

89

Fe)

0.4

29

)0.0

59

)0.4

77

)0.0

64

)0.3

31

)0.1

89

)0.2

75

0.2

26

0.4

31

)0.2

24

0.0

94

0.1

17

0.0

32

0.8

60

P=

0.0

14

P=

0.7

48

P=

0.0

06

P=

0.7

28

P=

0.0

64

P=

0.3

01

P=

0.1

28

P=

0.2

14

P=

0.0

14

P=

0.2

18

P=

0.6

08

P=

0.5

25

P=

0.8

63

P=

0.0

00

Fedis

.0.5

48

0.0

74

0.3

99

0.5

04

0.5

69

0.1

44

0.1

26

0.2

70

)0.4

18

0.4

02

)0.3

42

0.2

12

)0.1

94

)0.3

05

)0.3

02

P=

0.0

01

P=

0.6

86

P=

0.0

24

P=

0.0

03

P=

0.0

01

P=

0.4

32

P=

0.4

93

P=

0.1

35

P=

0.0

17

P=

0.0

23

P=

0.0

55

P=

0.2

43

P=

0.2

88

P=

0.0

89

P=

0.0

93

Mn

)0.0

63

0.2

18

)0.3

63

0.4

43

0.3

51

0.2

11

)0.1

55

0.3

15

)0.2

67

0.3

79

)0.2

71

0.0

60

)0.4

44

0.0

28

0.2

91

0.2

87

P=

0.7

30

P=

0.2

30

P=

0.0

41

P=

0.0

11

P=

0.0

49

P=

0.2

46

P=

0.3

97

P=

0.0

80

P=

0.1

39

P=

0.0

32

P=

0.1

33

P=

0.7

43

P=

0.0

11

P=

0.8

79

P=

0.1

06

P=

0.1

11

Zn0.4

18

)0.1

51

0.5

91

0.0

31

0.3

57

)0.0

85

0.4

79

)0.4

31

0.0

10

)0.0

98

0.0

22

0.1

28

0.0

07

)0.1

35

)0.4

01

0.0

05

)0.2

78

P=

0.0

17

P=

0.4

11

P=

0.0

00

P=

0.8

67

P=

0.0

45

P=

0.6

44

P=

0.0

06

P=

0.0

14

P=

0.9

57

P=

0.5

95

P=

0.9

05

P=

0.4

86

P=

0.9

71

P=

0.4

60

P=

0.0

23

P=

0.9

77

P=

0.1

23



development of germs, algae and fungi in the water

(Rodier 1978), with a consequent decrease in the dis-

solved oxygen concentration that could explain the pres-

ence of death fish in the lake during the dry season.

EC and elementsEC, an indicator of the overall water salinity, ranged

between 5.29 and 30.53 lS cm)1. The conductivity of the

different samples varied significantly (P < 0.05) with sea-

son. The sample from July had the lowest conductivity,

whereas the February sample had the highest values.

Thus, the rainy season exhibited low conductivities,

whereas the dry season exhibited higher conductivities.

This could be attributed to dilution of the lake water by

the rain-associated run-off (or by the rain itself, it rains

on the soil surrounding the lake and it rains on the lake

too). Nevertheless, whatever the season and sampling

site, the waters of the lake exhibited conductivity values

lower than 200 lS cm)1, thereby being categorized as

weakly mineralized waters (Rodier 1978; AFNOR, 1986).

Table 2 indicates that the highest values of carbonate

(CO32–) and nitrate (NO3

–) were 6.3 (April) and

27.4 mg L)1 (July), respectively. The presence of NO3– in

water is viewed as a sign of water pollution. The high

concentration (45 mg L)1) observed in some water sys-

tems in France has been associated with surrounding

farming activities related to the utilization of manures

(Mignolet et al. 1999). The water of Lake IRAD does not

exhibit high nitrate concentrations, all samples being

lower than 100 mg L)1, the maximum permissible level

for livestock watering (La Plante & Bachelier 1953; EPA

1997). The nitrate concentrations were very low in Octo-

ber, and although their presence could be related to the

nitrification of NH4–N, there was no significant correla-

tion (P > 0.05) between NH4–N and nitrate. The accumu-

lated nitrate in the soil during the dry season can be

washed away with the first rains, this phenomenon being

observed in April and July, when the nitrate levels

increased to 27 mg L)1. At the end of the rainy season

(October), the rain-washed soils contained less nitrate

than at the beginning of the rainy season (April). The

presence of nitrate in the lake waters, therefore, could be

related to the nitrification of NH4–N in soils and their

leaching soil by rain waters.

There were no significant correlations (P > 0.05) for

the other anions, bicarbonate (HCO3–), chloride (Cl–) and

sulphate (SO42–), with EC. The bicarbonate and chloride

concentrations in the lake varied between 4.5–37.2 and

1.8–11.9 mg L)1, respectively. These values are far below

1000 and 250 mg L)1, the maximum permissible levels for

drinking water, respectively (NRC 1980; Degremont 1989;

EPA 1997; Delisle et al. 1998). The anions concentration in

the lake increased with pH, with the lake exhibiting signifi-

cant positive correlations of pH with bicarbonate (r = 0.86;

P < 0.01), carbonate (r = 0.64; P < 0.01) and chloride

(r = 0.75; P < 0.01). As observed for the pH values, the

concentrations of these elements were higher in the dry

season, with highest values being observed during April.

There were also other major elements contributing to

the salinity of the lake water, including magnesium,

sodium and potassium. The water hardness varied

between 2.3 and 30.6 mg L)1, indicating that the IRAD

lake contained essentially soft water. The highest values

recorded for calcium and magnesium were 24.82 (April)

and 5.78 mg L)1 (July), respectively. Similar observations

were obtained for sodium and potassium which exhibited

maximum concentrations of only 2.7 and 2.1 mg L)1,

respectively.

IronThe total iron concentrations varied between 0.3 (Febru-

ary) and 3.3 mg L)1 (July), whereas the dissolved iron

concentrations between 0.01 (July) and 1.2 mg L)1 (Feb-

ruary). There was a high total iron concentration in the

lake during the rainy season, compared with dissolved

iron. A high total iron and low dissolved iron concentra-

tion was observed during July and October. Thus, rainfall

appears to decrease the dissolved iron concentration in

the lake (Fig. 6). These results indicate that the Lake

IRAD waters exhibited high dissolved concentrations

>0.2 mg L)1 of the maximum permissible level for human

or cattle consumption (Rodier 1978; Degremont 1989;

EPA 1997). This high iron concentration in the lake

waters could be harmful for animals because iron often

forms a complex compound with other trace minerals

(e.g. copper) that becomes unavailable, and can cause

copper deficiency (Thornton 2002). In addition to its

potential toxic impacts, the high iron concentration in the

water commonly consumed by grazing cattle can affect

the taste of the water, thereby decreasing the appetite of

the animals (WQM 1996). The high iron concentration

is attributed to the passage of water through the soil

(Rodier 1978). The region of Wakwa has ferralitic soils

(La Plante & Bachelier 1953), and the high iron concen-

tration could originate from features associated with cat-

tle moving soil and contaminating the water when

drinking. This phenomenon can be explained by the high

total iron concentration of these waters which, for exam-

ple, can reach 3.35 mg L)1 in July, a period when rainfall

often is intense. The high total iron concentration could

be attributed to particles of iron oxide, or OM–iron com-

plexes, generally observed in surface waters in tropical



regions (WQM 1996). High iron concentrations also have

been observed in Ethiopian lakes, which exhibit values

between 0.5 and 2.5 mg L)1 (Zinabu & Pearce 2003). Ani-

mals can ingest a high quantity of iron when drinking

water from Lake IRAD.

ManganeseThe manganese concentration varied between 0.04 (April)

and 0.15 mg L)1 (October), with 94% of the samples con-

taining concentrations greater than the maximum permis-

sible level of 0.05 mg L)1 for livestock drinking water

(EPA 1997). Manganese has the effect of reducing iron

absorption in the haemoglobin in blood (Gross et al.

1979), and the accumulation of zinc in an organism

(Abdelrahman & Kincaid 1993). In a similar way to iron,

manganese can contribute to an unpleasant taste in

water, thereby reducing its consumption by cattle (EPA

1997). For certain soils, it has been shown that a high

iron content is often associated with a high manganese

content (EPA 1997). This was not the case for the water

of Lake IRAD in this study, which exhibited no signifi-

cant correlation (P > 0.05) between iron and manganese.

As a result of leaching during the rainy season, most lake

water samples exhibited iron and manganese concentra-

tions above the maximum permissible limit for drinking

water for cattle. Similar observations were reported by

some researchers in the United States, who reported that

3600 water samples contained iron and manganese con-

centrations about the maximum permissible limit for

drinking water for cattle. These latter samples contrib-

uted 1.8 and 1.0% of the cattle daily intake of iron and

manganese, respectively (Socha et al. 2001).

AluminiumThe aluminium concentration of the lake waters varied

between 0.25 and 1.71 mg L)1. It decreased at the end of

the rainy season, varying between 0.25 and 0.52 mg L)1

in October, compared with 0.31–1.63 mg L)1 in February.

Aluminium toxicity has been observed for waters contain-

ing >0.5 mg L)1 (EPA 1997). The toxicity is characterized

by its link to transferin phosphatase, noting that this

effect would facilitate anaemia by decreasing iron absorp-

tion. An iron deficiency, in turn, can enhance aluminium

absorption (Linder 1991). About 44% of the water samples

from the lake contained high aluminium concentrations,

thereby representing toxicity risks.

ZincAnalysis of variance indicated that the zinc concentration

was significantly affected by the sampling site. Figure 7

illustrates the presence of zinc for all sampling sites and

in all seasons. This phenomenon could be attributable to

the geochemical characteristics of the soils in the lake

basin, or the wastes associated with animal excretions

(Xue et al. 2002). The lowest zinc concentration

(0.03 mg L)1) was observed in July, and the highest val-

ues (0.96 mg L)1) in February. All of the measured zinc

concentrations, however, were <5 mg L)1, which is the

maximum limit recommended for livestock drinking. Xue

et al. (2002) found that the surface waters drained from

soils that were extensively cultivated with animal manure

had maximum zinc concentrations of 0.02 mg L)1, these

being very low values compared with the results of this

study. However, the zinc concentration in the Lake IRAD

water could be influenced by cattle activities around the

lake, associated with a high animal population density

that would produce much manure. Some studies have

indicated that animal wastes represent a source of min-

eral elements (Nunez-Delgado et al. 2002). As an exam-

ple, wastes from dairy cattle in the United Kingdom

contained up to 50 mg kg)1 (dry matter) of zinc (Nichol-

son et al. 1999).

Other elementsThe lake waters also were analysed for other minerals,

including cadmium, nickel, copper and phosphate, with

the measured concentrations being below the detection

limits of the analytical methods used in this study. Phos-

phate pollution, for example, is generally attributable to

domestic activities involving phosphate-containing deter-

gents, or phosphate manures that can enter the lake

water from the leaching of cultivated soil (Dorioz et al.

1997). The very low phosphate concentrations in the lake

water indicate that phosphate manures were not utilized

in the Wakwa lowlands.

CONCLUSIONThe results of this study of the physicochemical composi-

tion of the artificial Lake IRAD in Wakwa indicated that

the concentrations of OM, NH4–N, iron, manganese and

aluminium exceeded the recommended values for drink-

ing water for grazing animal. The nitrate, NH4–N and

OM concentrations were highest during the rainy season,

whereas zinc and dissolved iron concentrations were

highest in the dry season. The lake water pH was related

to the high bicarbonate, carbonate, chloride, OM and cal-

cium. The presence of zinc in the lake water samples was

related to the presence of OM and bicarbonate. At the

conclusion of this study, it was also observed that leach-

ing of soils by rain water, as well as animal activities in

the water, contributed to the elevated concentrations of

iron and aluminium.



The water of Lake IRAD in the Wakwa region was

found to be contaminated by cattle. Sampling sites 1 and

2, the sites most frequented by these animals, exhibited

high concentrations of NH4–N, compared with sampling

sites 3 and S, the latter being less frequented by grazing

animals. To reduce the contamination of the lake waters

associated with cattle, it will be important to develop

access zones to water for these animals.

ACKNOWLEDGEMENTSThis research was funded by the Agence Universitaire de

la Francophonie (AUF). Acknowledgments are also due

to the IRAD, Wakwa (Cameroon), for collecting the sam-

ples utilized in this study.

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Physicochemical characteristics of Lake IRAD, an artificial lake in Wakwa region, Cameroon

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