assessing the impact of anthropogenic activities on spatio-temporal variation of water quality in...

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

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 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

[email protected] 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 physico-chemical 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 co-relation 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.

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

Kashmir Himalayas

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

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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


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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


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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).


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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 inter-correlation 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


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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


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algal bloom (Sachidanandamurthy and Yajurvedi, 2004). Further, BOD showed negative co-relation 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.

Parameters Month Mean Range Min. Max. Std.

Error Std.

Deviation Variance

1 Water

Temperature (oC)

Feb 7.83 3.00 6.00 9.00 0.48 1.17 1.37

Mar 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

June 21.92 3.50 20.00 23.50 0.52 1.28 1.64

July 24.50 3.40 22.60 26.00 0.49 1.19 1.42

2 Depth (m)

Feb 1.00 0.57 0.74 1.31 0.08 0.20 0.04

Mar 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

May 1.67 0.79 1.28 2.07 0.12 0.28 0.08

June 1.11 0.24 0.98 1.22 0.05 0.12 0.01

July 0.93 0.11 0.89 1.00 0.01 0.04 0.00

3 Transparency

(m)

Feb 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

4 pH

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

5 Dissolved Oxygen

(DO) (mg/L)

Feb 8.98 1.00 8.50 9.50 0.15 0.36 0.13

Mar 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 11.67 5.00 9.00 14.00 0.84 2.07 4.27


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6 Free CO2

(mg/L) Apr 9.67 7.00 6.00 13.00 1.05 2.58 6.67

May 8.45 4.50 6.50 11.00 0.73 1.78 3.16

June 7.33 6.00 4.00 10.00 0.99 2.42 5.87

July 6.25 4.50 4.00 8.50 0.79 1.94 3.78

7

Conductivity

(µS/cm)

Feb 163.67 98.00 129.00 227.00 14.10 34.54 1193.07

Mar 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

June 322.50 50.00 300.00 350.00 8.04 19.71 388.30

July 296.00 93.00 227.00 320.00 14.47 35.43 1255.60

8 TDS(mg/L)

Feb 104.67 68.00 85.00 153.00 10.28 25.19 634.67

Mar 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

May 375.83 161.00 301.00 462.00 21.94 53.74 2888.17

June 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

9 Total

Alkalinity (mg/L)

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

10 Chloride (mg/L)

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

11 Total

hardness (mg/L)

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

12 Calcium hardness (mg/L)

Feb 123.33 87.00 95.00 182.00 12.48 30.56 933.87

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 33.21 10.21 30.62 40.82 1.58 3.87 15.01


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13 Magnesium hardness (mg/L)

Mar 24.34 8.51 19.68 28.19 1.48 3.62 13.07

Apr 19.72 9.96 14.34 24.30 1.51 3.71 13.73

May 11.30 8.75 8.26 17.01 1.24 3.03 9.16

June 8.83 3.40 7.29 10.69 0.66 1.63 2.64

July 7.97 3.79 6.32 10.11 0.69 1.69 2.85

14

Ammonical

nitrogen (mg/L)

Feb 0.16 0.16 0.10 0.26 0.03 0.06 0.00

Mar 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

June 0.06 0.07 0.03 0.10 0.01 0.02 0.00

July 0.05 0.06 0.03 0.09 0.01 0.02 0.00

15 Nitrate

nitrogen (mg/L)

Feb 0.54 0.15 0.50 0.65 0.02 0.06 0.00

Mar 0.45 0.07 0.41 0.48 0.01 0.03 0.00

Apr 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

June 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

16 Phosphate

(mg/L)

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

17 Iron (mg/L)

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

18 BOD (mg/L)

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

19 COD (mg/L)

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 58.00 22.00 46.00 68.00 3.34 8.17 66.80


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


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


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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

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%

01

23

45

6

0.8

8

0.8

96

0.9

12

0.9

28

0.9

44

0.9

6

0.9

76

0.9

92

Similarity

Site__VI

Site_III

Site_V

Site_IV

Site_II

Site_I


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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.

4. References

1. Agarkar, S.V. and Garode, A.M., (2000), Evaluation of physico-chemical and microbiological parameters of Vyazadi reservoir water, Indian Hydrobiology. 3, pp 3-5.

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