Assessing the impact of anthropogenic activities on spatio-temporal variation of water quality in Anchar lake, Kashmir Himalayas

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES Volume 3, No 5, 2013
© Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0
Research article

ISSN 0976 – 4402

Assessing the impact of anthropogenic activities on spatio-temporal
variation of water quality in Anchar lake, Kashmir Himalayas
Salim Aijaz Bhat1, Gowhar Meraj2, Sayar Yaseen1, Ab. Rashid Bhat1,
Ashok K. Pandit1
1- Aquatic Ecology Laboratory, Centre of Research for Development (CORD),
University of Kashmir 190006, J&K India
2- GIS Laboratory, Department of Earth Sciences, University of Kashmir 190006, J&K, India
gowharmeraj@gmail.com
doi:10.6088/ijes.2013030500032
ABSTRACT
In the present study, various physico-chemical parameters of water were assessed over a
period of six months (from February, 2012 to July, 2012) on monthly basis at six study sites
in Anchar lake of Kashmir valley. The correlation matrix and dendrogram of physicochemical factors have been computed and analyzed. The positive co-relation coefficient was
observed between, free carbon dioxide and calcium, alkalinity and nitrate, alkalinity and
phosphate, total hardness and calcium, total hardness and magnesium, nitrate and phosphate,
conductivity and chloride and total dissolved solids and chloride, while as negative corelation coefficient was found between dissolved oxygen and biological oxygen demand and
pH and dissolved carbon dioxide. The Bray Curtis similarity analysis showed that there is a
similarity of 96 % between sites III and V, 94% between sites I and II, and < 92 % for other
sites. The physico-chemical analysis of Anchar revealed it is heavily polluted as a result of
anthropogenic pressures.
Keywords: Correlation, Bray Curtis similarity analysis, water quality, Anchar lake.
1. Introduction
Water is one of the most common, yet the most precious, resource on Earth. Water
pollution is a serious problem of 70% of India's surface water resources and a
growing number of its groundwater reserves have been contaminated by biological,
organic and inorganic pollutants. Due to tremendous development of industry and agriculture,
the aquatic ecosystems have become perceptibly altered in the recent years and as such
they are exposed to all local disturbances regardless of where they occur (Venkatesan,
2007). The health of lake ecosystems and their biological diversity are directly related to
health of almost every component of the ecosystem (Ramesh et al., 2007). Thus, estimation
of water quality is extremely important for proper assessment of the associated hazards
(Warhate et al., 2006). Multivariate statistical techniques, such as cluster analysis (CA), and
inter-correlation matrix have been used extensively to evaluate the effects of human activities
on the quality of surface waters. The valley of Kashmir is well known for its water resources.
However they are facing grave pollution problems and as a result number of indigenous and
high quality biological species inhabiting these water bodies are diminishing. To formulate
holistic mechanism to stop and avert these problems there is a need of application oriented
limnological research. The current study is a well thought of approach in this direction.

Received on January 2013 Published on April 2013

1625

Assessing the impact of anthropogenic activities on Spatio-Temporal variation of water quality in Anchar lake,
Kashmir Himalayas

The present study on physico-chemical characteristics of water was carried out on Anchar
Lake in Kashmir Himalaya. The Anchar lake is situated 14 km to the North West of Srinagar
city at an altitude of 1584 A.S.L within the geographical coordinates of 34˚20´ - 34˚26´ N lat.
and 74˚.82´- 74˚.85´ E long. Its area is about 5.8 km2. The lake is connected with Khusalsar
Lake which in turn is connected with the famous Dal Lake through small inflow channel,
Nalla Amir Khan. River Sind enters the lake on its western side and forms a network of
distributaries. The lake is also fed by a number of springs present in the basin itself and along
its periphery. Towards the north east of this water basin is situated the complex of SKIMS
(Sheri Kashmir Institute of medical Science), draining its toxic influents into the lake. The
runoff from the surrounding paddy fields including floating gardens and sewage from the
surrounding human habitation is also drained into the lake, there by further enhancing the
nutrient levels of the lake. Six different sites were selected for the present study on the basis
of water depth, vegetation, inlet and outlet and anthropogenic pressures. Six sampling sites
were chosen for the evaluation of various physico-chemical parameters of water within
the lake (Table 1. Figure 1)
Site I: This site is located near the Holy Shrine Jenab Sahib Soura. At this site the lake is fed
by a number of springs, which are present in its basin.
Site II: This site is situated on the western Shore of the lake, where the Sind Nalla enters into
the lake.
Site III: This site is located near about the centre of the lake. At this site lake has a maximum
depth.
Site IV: This site is situated near the place which is locally known as Kather Sahib dam. At
this site the lake is heavily infested with thick macrophytes.
Site V: This site is situated near the Sangam village. At this site the water exits from the lake
which finally enters into the River Jhelum.
Site VI: This site is located towards the north east region of the lake. At this site, the lake
receives the toxic effluents and sewage wastes from the drainage system of SKIMS.
Table 1: Sampling locations and their coordinates
Sampling Site

Longitude E (dd*)

Latitude N (dd)

Elevation form sea
level (m)

Site I

74.794

34.152

1581

Site II

74.788

34.152

1581

Site III

74.785

34.147

1581

Site IV

74.799

34.132

1581

Site V

74.774

34.136

1581

Site VI

74.793

34.142

1581

* dd Decimal degrees
Salim Aijaz Bhat et al
International Journal of Environmental Sciences Volume 3 No.5, 2013

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Kashmir Himalayas

2. Material and methods
The physico–chemical characteristics of water were monitored on monthly basis from
February, 2012 to July, 2012. The surface water samples were collected between 10.00 and
12.00 hours from each of the sampling sites in one liter plastic bottles for the laboratory
investigations. The parameters including depth, transparency, temperature, pH and
conductivity were determined on spot while the rest of the parameters were determined in the
laboratory within 24 hours of sampling. The analysis was done by adopting standard methods
of Mackereth (1963), Goltermann and Clymo (1969) and APHA (1989). The data collected
were subjected to Pearson’s correlation matrix to study the significant level at 0.05 and 0.01
(2 tailed) to note the positive and negative correlation among the physico-chemical factors.
Similarly, Bray-Curtis cluster analysis was applied to construct a dendrogram of percentage
of similarity in study sites on the basis of physico-chemical factors to identify relative
homogenous clusters of sites and to measure the distance or similarity in relation to aquatic
condition. The SPSS ver. 16.0 and PAST statistical programs were used for all statistical
analysis throughout this research.
3. Result, discussion and conclusion
The mean, range, minimum, maximum, standard deviation and variance of water quality
parameters at six study sites in Anchar lake are presented in Table 2. Mean water temperature
shows clear monthly variations and ranged from a minimum of 7.83oC in February to a
maximum of 24.5o C in July. There were signiﬁcant difference in temperature (SD = 1-1.9)
between sampling sites. Similar findings were also recorded by Shastri and Pendse (2001)
and Eshwaralal and Angadi (2002). Further, water temperature was found negatively
correlated with DO (Das, 2000) and transparency (Reid and Wood, 1976) (Table 3, Fig.2 a,
b). The mean depth of water ranged from 0.9m in February to 1.6m in May. Depth of water is
determined by the volume of water column in an aquatic system, which is in turn is
dependent on the discharge rate of inflows. The lowest mean depth is an indication of an
evolutionary process coinciding with higher trophic status of the lake as also opined by
Pandit (2002).
Throughout the study period, mean transparency ranged from 0.072 to 0.93 m. The value of
mean and coefficient of variation (6.48-26.32%) (Table 3) virtually shows that transparency
of water fluctuated spatially as well as temporally. The sites near inflow channel and urban
residential areas showed lower water transparency than those near agricultural area and
outflow channel. This could be due to the heavy load of organic matter carried into the river
by surface run-off and sewage and also by silt generated by the disturbance of the river
bottom (sediment) by the greater turbulence of flood water which comes after heavy
rains(Akpan, 2004). Seasonally, the highest value of water transparency occurred in winter at
all sampling sites and may be attributed to low suspended organic matter with poor
planktonic growth (Sinha et al., 2002). Values of inter-correlation matrix showed positive
correlation of transparency with total hardness and dissolved oxygen (Sharma et al., 2010)
(Figure 2 c).
The lowest pH value was found during the winter season (7.1) being attributed to lower rates
of photosynthesis, a fact also revealed by Agarkar and Garode (2001). The increased pH in
the month of July (pH=8) may be associated with increase in DO, produced as a result of
photosynthesis (Wetzel, 1975). Further, pH showed significant negative correlation with CO2
and positive correlation with DO, thereby confirming that pH is inversely dependent on the

1627

Kashmir Himalayas

amount of the CO2 present (Colin et al., 1997) and indirectly proportional to the
photosynthetic activity (Pandit et al., 2001) (Figure 2 d) (Table 3).

Figure 1: Geographic location of the study area with respect to India and J & K state and
sampling location sites.
Dissolved oxygen is one of the most important parameter in assessing the quality of
water, which is essential to maintain biotic forms in water. Oxygen content of water varies
with temperature, salinity, turbulence, photosynthetic activity of algae and higher
plants atmospheric pressure etc. The present investigation revealed that the average DO
content in lake ranged from 6.06 mg/L in July to 8.98 mg/L in February, denoting the inverse
relationship with the temperature (Agarwal et al., 1976). The lowest value of DO at Sites-IV
and VI may be due to the increased amount of organic matter due to agricultural runoff
and sewage which needs oxygen for decomposition, as also opined by Yousuf and Shah
(1988),(Figure 3.5).

1628

Kashmir Himalayas

Carbon dioxide is the chief source needed for photosynthesis process in plants. In
aquatic ecosystems carbon dioxide reacts with water and forms carbonic acid which soon
dissociates into carbonates and bicarbonates, thus altering pH of water. In the present study
the concentration of carbon dioxide in lake ranged between 6.25 mg/L in July at site I and
13.16 mg/L in February at site VI. Spatio-temporal variations in free CO2 are delineated by
the values of mean and coefficient of variation (16.23-33.03%, (Fig.3.7).The behavior of
carbon dioxide with pH is that an increase in carbon dioxide concentration in water results in
decrease of its pH due to the formation of carbonic acid (Chandler, 1970).
Conductivity measures the capacity of a substance or solution to conduct electrical
current. The electrical conductivity was found to fluctuate between 163.6 µS/cm
(February, 2012) and 362.8 µS/cm (April, 2012) and that falls within the range observed
for Indian waters. Olsen (1950) classified water bodies having conductivity values greater
than 500 µS/cm as eutrophic. According to this criteria, Anchar Lake falls under the category
of mesotrophic water body. Range and standard deviation values suggest that there is strong
spatial variation in conductivity and may be attributed to varying degree of anthropogenic
pressure. Furthermore, inter-correlation matrix showed positive correlation coefficient
between conductivity and chloride (Figure 2 e) (Table 3).
In natural waters, dissolved solids are composed mainly of carbonates, bicarbonates,
chlorides, sulphates, phosphates, nitrates, calcium, magnesium, sodium, potassium, iron,
manganese etc. (Ismailia and Jamal, 2005). The lowest total dissolved solids content (104
mg/l) was obtained during February due to low input from catchment while the highest
concentration (375 mg/l) was recorded in May as a result of runoff from catchment. Similar
findings have been reported by Kirubavathy et al., (2005) and Garg et al., (2006b) with
regard to seasonal variations of TDS. Alkalinity of water is the capacity to neutralize
strong acids and is primarily a function of carbonate, bicarbonate and hydroxide
content being formed due to the dissolution of carbon dioxide in water. In the present
investigation the total alkalinity values fluctuated from 19.4mg/L at Site I to 234 mg/L at
Site VI (Figure 3.9). . Total alkalinity in the lake followed a trend of decrease from winter to
summer months. Agarwal and Thapliyal (2005) also obtained maximum alkalinity
during winter months in Bhilangana. Further, the values of alkalinity above 90mg/L
can be categorized as hard water type of Moyle (1945). On the basis of intercorrelation matrix alkalinity showed positive correlations with nitrate and phosphate (Figure
2 f and g) (Table 3). This may be attributed to the enhancement of the decomposition of
organic matter by alkalinity which in turn increases concentrations of nitrate and phosphate.
Large contents of chloride in fresh-water is an indicator of organic pollution
(Venkatasubramani and Meenambal, 2007). In the present study, chloride concentration
varied from 5.9 (February at Site II) to 23.7 mg/L (April at Site IV). Jana (1973) and
Govindan and Sundaresan (1979) observed that higher concentration of chloride in the
summer period could be also due to sewage mixing, increased temperature and higher runoff
from catchment. Chloride showed significant positive co-relation coefficient with total
dissolved solids as they form one of the constituents of dissolved solids (Figure 2 h) (Table 3).
The abundance of Ca and Mg ions are responsible for an increase in hardness (Das, 2002)
while its negative correlation with pH is also evident.
Calcium, magnesium, carbonates, bicarbonates, sulphates, chlorides, nitrates, organic matter
together associate and form hardness of water. According to hardness scale of Water Quality
Association (Lehr et al., 1980), hardness values ranged from 0 to 17 mg/L is soft
water, 17 to 60 mg/L is slightly hard, 60 to 120 mg/L is moderately hard, 120 to 180

1629

Kashmir Himalayas

mg/L hard water and more than 180 mg/L is very hard. In the present investigation low
hardness value (84 mg/L) was recorded at Site V as against the high hardness value (362
mg/L) being recorded at Site II, (Fig. 3.11-13). In general, low hardness values were
regestered during the spring season which is due to the utilization of carbonates, as a source
of carbon, by phytoplankton a fact also revealed by Swarnalatha and Rao (1998) while
working on Banjara Lake, Hyderabad. Further, Patil et al. (1986) reported higher hardness
during monsoon season, being attributed it to the inflow of rainwater from agricultural
fields carrying good amount of suspended salts, which is also collaborated by the present
study.
In aquatic environment, calcium serves as one of the macronutrients for most of the
organisms. The calcium contents in Anchar lake varied from 45 (July, 2012) to 182
mg/L (February, 2012), being minimum in summer and maximum in winter which is in
consonance with the findings of Das (2002) on his studies while working on the reservoirs of
Andra Pradesh. A similar trend was also depicted for Mg with the minimum concentration of
the ion (6.3 mg/L) being noticed in July and the highest (40.82 mg/L) in February.
Furthermore, hardness was found positively correlated with calcium and magnesium (Das,
2002) (Fig.2 d I and j) (Table 3).
Ammonia in higher concentration is harmful to fishes and other aquatic life. The toxicity of
ammonia increases with pH because at higher pH most of the ammonia remains in
the gaseous form. At low pH toxicity of ammonia decreases which is attributed to the
conversion of ammonia into ammonium ions. In the present study, ammonia content
varied from 0.028 in July to 0.257 mg/L in February, 2012 with higher values in winter
season and lower value in summer season, a finding also revealed by Ingemar Ahlgren (1967).
The presence of nitrate in fresh water bodies depends mostly upon the activity of
nitrifying bacteria on nitrogen source of domestic and agricultural origin. In the present
study, nitrate content fluctuated from 0.141 mg/L in July to 0.649 mg/L in February. The
rapid decrease of nitrate concentrations in July could be explained as due to a combination of
a rapid assimilation by phytoplankton and a decreased intensity of nitrification caused by
high water temperature (Ingemar Ahlgren, 1967). Trisal (1977) also opined that the
increase in nitrate-nitrogen content during winter is the cumulative effect of nitrification
in the water column and the mud water interface.
The major sources of phosphorous in water are domestic sewage, agricultural runoff
containing fertilizers and industrial effluents. Phosphorus, a nutrient that limits primary
productivity of an aquatic ecosystem, is essential for the growth of organisms. In the
present study phosphate-phosphorus ranged from a minimum of 0.013 mg/L in July to a
maximum of 0.321 mg/L in February. The low content of phosphate-phosphorus in
summer season may be due to utilization of the nutrient by phytoplankton (Kaul et al. (1980).
Further, significant positive correlation coefficient was obtained between phosphate and
nitrate (Katiyar and Belsare, 1997) (Figure 2 k) (Table 3). The mean concentration of iron
measured in lake ranged from 0.02 mg/L in February to 0.17 mg/L in July. The significant
seasonal variation may be attributed to (i) the little role of iron in phytoplankton growth and
(ii) the chemical process in water especially the exchange of substances between sediments
and water (Mortimer, 1941-42). Biochemical oxygen demand (BOD ) is the amount of
oxygen utilized by microorganisms in stabilizing the organic matter. BOD in water
ranged from 19 mg/L in January to 46 mg/L in July. The minimum BOD, as noticed during
winter, was due to the decrease in temperature leading to decrease in microbial activity and

1630

Kashmir Himalayas

algal bloom (Sachidanandamurthy and Yajurvedi, 2004). Further, BOD showed negative corelation coefficient with DO as the latter is consumed in stabilization of organic matter (Fig.2
l). The COD of water increases with increasing concentration of organic matter (Boyd, 1981).
In the present study, COD ranged from 19 mg/L in May to 46 mg/L in July. The
monthly variations were also noticed by other workers (Fokmare and Musaddiq, 2002).
Table 2: Physico-chemical characteritics of water of Anchar lake
(February 2012 to July 2012)
S
No.

6.00

9.00

0.48

1.17

1.37

8.50

3.00

7.00

10.00

0.43

1.05

1.10

Apr

12.17

5.00

10.00

15.00

0.79

1.94

3.77

May

19.00

5.00

16.00

21.00

0.68

1.67

2.80

21.92

3.50

20.00

23.50

0.52

1.28

1.64

24.50

3.40

22.60

26.00

0.49

1.19

1.42

1.00

0.57

0.74

1.31

0.08

0.20

0.04

1.10

0.64

0.80

1.44

0.10

0.24

0.06

Apr

1.33

0.53

1.08

1.61

0.09

0.22

0.05

1.67

0.79

1.28

2.07

0.12

0.28

0.08

1.11

0.24

0.98

1.22

0.05

0.12

0.01

0.93

0.11

0.89

1.00

0.01

0.04

0.00

0.21

0.15

0.14

0.29

0.02

0.05

0.00

Mar

0.18

0.08

0.15

0.23

0.01

0.03

0.00

Apr

0.16

0.11

0.12

0.23

0.02

0.04

0.00

May

0.11

0.04

0.09

0.13

0.01

0.02

0.00

June

0.09

0.03

0.08

0.11

0.00

0.01

0.00

July

0.08

0.01

0.07

0.09

0.00

0.01

0.00

Feb

7.18

0.40

7.00

7.40

0.06

0.15

0.02

Mar

7.17

0.20

7.10

7.30

0.03

0.08

0.01

Apr

7.20

0.30

7.00

7.30

0.04

0.11

0.01

May

7.40

0.30

7.20

7.50

0.05

0.13

0.02

June

7.52

0.70

7.00

7.70

0.11

0.26

0.07

July

8.02

0.30

7.90

8.20

0.05

0.12

0.01

Feb

8.98

1.00

8.50

9.50

0.15

0.36

0.13

Mar
5

3.00

Feb

8.62

0.80

8.20

9.00

0.12

0.31

0.09

Apr

8.07

1.20

7.40

8.60

0.16

0.40

0.16

May

7.45

0.80

7.10

7.90

0.12

0.29

0.08

June

6.95

0.80

6.50

7.30

0.12

0.29

0.08

July

6.07

0.60

5.80

6.40

0.10

0.24

0.06

Feb

13.17

6.00

10.00

16.00

0.87

2.14

4.57

Mar

Dissolved
Oxygen
(DO) (mg/L)

7.83

July

pH

Variance

June

4

Std.
Deviation

May

Transparency
(m)

Std.
Error

Mar

3

Max.

Feb

Depth (m)

Min.

July

2

Range

June

1

Mean

Mar
Water
Temperature
(oC)

Month
Feb

Parameters

11.67

5.00

9.00

14.00

0.84

2.07

4.27


1631

Kashmir Himalayas
6

Free CO2
(mg/L)

0.73

1.78

3.16

7.33

6.00

4.00

10.00

0.99

2.42

5.87

6.25

4.50

4.00

8.50

0.79

1.94

3.78

163.67

98.00

129.00

227.00

14.10

34.54

1193.07

320.83

200.00

250.00

450.00

27.55

67.48

4554.17

Apr

362.83

93.00

335.00

428.00

14.60

35.75

1278.17

May

368.00

114.00

326.00

440.00

15.88

38.90

1513.20

322.50

50.00

300.00

350.00

8.04

19.71

388.30

296.00

93.00

227.00

320.00

14.47

35.43

1255.60

104.67

68.00

85.00

153.00

10.28

25.19

634.67

242.17

70.00

195.00

265.00

10.41

25.50

650.17

Apr

323.83

152.00

245.00

397.00

21.33

52.25

2729.77

375.83

161.00

301.00

462.00

21.94

53.74

2888.17

280.50

97.00

215.00

312.00

18.46

45.22

2044.70

July

212.50

43.00

195.00

238.00

7.08

17.35

301.10

Feb

128.67

185.00

49.00

234.00

31.33

76.74

5889.47

Mar

100.83

159.00

29.00

188.00

30.25

74.08

5488.57

Apr

91.00

150.00

26.00

176.00

28.31

69.34

4808.00

May

62.00

86.00

22.00

108.00

16.25

39.80

1584.40

June

54.98

77.50

21.50

99.00

14.87

36.42

1326.36

July

50.28

73.00

19.40

92.40

13.58

33.26

1106.21

Feb

8.13

5.00

5.90

10.90

0.83

2.02

4.09

Mar

12.95

7.10

9.80

16.90

2.20

5.38

28.99

Apr

18.07

12.80

10.90

23.70

1.83

4.48

20.10

May

15.57

7.20

12.50

19.70

1.05

2.58

6.66

June

13.08

5.00

11.00

16.00

0.86

2.11

4.44

July

10.87

3.80

9.70

13.50

0.57

1.40

1.97

Feb

299.33

120.00

242.00

362.00

19.08

46.74

2185.07

Mar

241.33

88.00

192.00

280.00

13.22

32.38

1048.67

Apr

212.00

108.00

156.00

264.00

15.21

37.25

1387.20

May

138.33

56.00

118.00

174.00

8.63

21.14

447.07

June

118.83

37.00

106.00

143.00

5.60

13.72

188.17

July

106.00

50.00

84.00

134.00

6.95

17.03

290.00

Feb

123.33

87.00

95.00

182.00

12.48

30.56

933.87

Mar
12

11.00

June

Calcium
hardness
(mg/L)

6.50

May

11

4.50

Mar

Total
hardness
(mg/L)

8.45

Feb

Chloride
(mg/L)

6.67

July

10

2.58

June

9

1.05

Mar

109.83

55.00

92.00

147.00

7.84

19.20

368.57

Apr

104.17

51.00

88.00

139.00

7.39

18.10

327.77

May

90.33

57.00

67.00

124.00

8.27

20.25

409.87

June

75.25

47.00

51.00

98.00

7.31

17.92

320.98

July

64.23

33.00

45.00

78.00

5.64

13.82

190.97

Feb

Total
Alkalinity
(mg/L)

13.00

Feb

TDS(mg/L)

6.00

July

8

7.00

June

Conductivity
(µS/cm)

9.67

May

7

Apr

33.21

10.21

30.62

40.82

1.58

3.87

15.01


1632

Kashmir Himalayas
13

Magnesium
hardness
(mg/L)

24.30

1.51

3.71

13.73

11.30

8.75

8.26

17.01

1.24

3.03

9.16

8.83

3.40

7.29

10.69

0.66

1.63

2.64

7.97

3.79

6.32

10.11

0.69

1.69

2.85

0.16

0.16

0.10

0.26

0.03

0.06

0.00

0.12

0.09

0.08

0.17

0.02

0.04

0.00

Apr

0.09

0.09

0.06

0.15

0.01

0.03

0.00

May

0.07

0.09

0.05

0.14

0.01

0.03

0.00

0.06

0.07

0.03

0.10

0.01

0.02

0.00

0.05

0.06

0.03

0.09

0.01

0.02

0.00

0.54

0.15

0.50

0.65

0.02

0.06

0.00

0.45

0.07

0.41

0.48

0.01

0.03

0.00

0.38

0.05

0.36

0.41

0.01

0.02

0.00

May

0.27

0.30

0.05

0.35

0.05

0.11

0.01

0.30

0.07

0.26

0.33

0.01

0.03

0.00

July

0.20

0.15

0.14

0.29

0.02

0.06

0.00

Feb

0.25

0.25

0.12

0.36

0.04

0.10

0.01

Mar

0.21

0.22

0.10

0.32

0.04

0.09

0.01

Apr

0.13

0.19

0.03

0.23

0.03

0.07

0.01

May

0.08

0.10

0.02

0.12

0.01

0.04

0.00

June

0.07

0.08

0.02

0.10

0.01

0.03

0.00

July

0.05

0.08

0.01

0.09

0.01

0.03

0.00

Feb

0.03

0.05

0.01

0.06

0.01

0.02

0.00

Mar

0.05

0.06

0.02

0.08

0.01

0.02

0.00

Apr

0.09

0.07

0.05

0.13

0.01

0.03

0.00

May

0.11

0.07

0.09

0.16

0.01

0.02

0.00

June

0.14

0.10

0.10

0.19

0.01

0.03

0.00

July

0.18

0.12

0.12

0.24

0.02

0.04

0.00

Feb

3.67

3.00

2.00

5.00

0.49

1.21

1.47

Mar

4.33

3.00

3.00

6.00

0.49

1.21

1.47

Apr

4.83

2.00

4.00

6.00

0.31

0.75

0.57

May

6.00

2.00

5.00

7.00

0.26

0.63

0.40

June

6.43

1.50

5.50

7.00

0.24

0.59

0.35

July

6.92

1.40

6.00

7.40

0.23

0.56

0.31

Feb

34.67

24.00

24.00

48.00

3.71

9.09

82.67

Mar

37.83

22.00

26.00

48.00

3.17

7.76

60.17

Apr

45.16

22.00

32.00

54.00

3.47

8.50

72.17

May

48.83

19.00

38.00

57.00

2.99

7.33

53.77

June

53.00

20.00

40.00

60.00

3.18

7.80

60.80

July

COD (mg/L)

14.34

June

19

9.96

Apr

BOD (mg/L)

19.72

Mar

18

Apr

Feb

Iron (mg/L)

13.07

July

17

3.62

June

Phosphate
(mg/L)

1.48

Mar

16

28.19

Feb

15

19.68

July

Nitrate
nitrogen
(mg/L)

8.51

June

Ammonical
nitrogen
(mg/L)

24.34

May

14

Mar

58.00

22.00

46.00

68.00

3.34

8.17

66.80


1633

Kashmir Himalayas

Figure 2: Scatter diagram showing positive and negative correlation between monthly
average values of physico-chemical parameters of water

1634

Kashmir Himalayas

Figure 3: Line plots (1-18) showing spatial variation of physico-chemical parameters of
water.

1635

Kashmir Himalayas

Table 3: Pearson’s correlation coefficients of physico-chemical characteristics of Anchar
Lake

**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
1 = Water temperature, 2 = Depth, 3 = Transparency, 4 = pH, 5 = Dissolved Oxygen, 6 =
Free Co2, 7 = Conductivity, 8 = TDS, 9= Total Alkalinity, 10 = Chloride, 11 = Total
Hardness, 12 = Calcium hardness, 13 = Magnesium hardness, 14 = Ammonical-N, 15 =
Nitrate-N, 16 = Phosphate, 17 = Iron, 18= BOD, 19 = COD
0.992

0.976

0.96

0.944

0.928

0.912

0.88

0.896

Similarity

0
1

Site__VI

2

Site_III

3

Site_V

4

Site_IV

5

Site_II

6

Site_I

Figure 4: Bray-Curtis cluster analysis of five study sites
The dendrogram of percentage similarity of five study sites on the basis of physico-chemical
factors is presented in Figure 4. The analysis of similarity of study sites from 0.88% to 1%

1636

Kashmir Himalayas

was carried out to indicate intensity of relations between sites as cluster. The Bray-Curtis
similarity analysis confirms that there is a similarity of 0.96% between sites III and V, 0.94%
between sites I and II, and < 0.928% for other sites. Contrary to these sites, sites IV and VI
showed maximum dissimilarity during the entire study period because the site IV represents
the outlet of the lake and site VI falls in immediate entry of waste water from SKIMS, Soura.
The overall nature of the physico-chemical characteristics depicts that the lake waters are
eutrophic in nature and the water quality has deteriorated as a result of input of nutrients
through various sources caused largely by anthropogenic pressures like urbanization,
agricultural expansion and changing land use land cover patterns in whole catchment area of
the lake. The trophic status of lake warrants a proper conservation and management strategy.
If proper measures are taken for the treatment of sewage before discharge and restrictions are
put on various anthropogenic activities in upstream, the lake would remain healthy and
ecologically sound in the long run.
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Kashmir Himalayas

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