Assessment of Water Quality of Some Selected Sites ...

International Journal of Lakes and Rivers. ISSN 0973-4570 Volume 4, Number 2 (2011), pp. 177-198 © Research India Publications http://www.ripublication.com/ijlr.htm

Assessment of Water Quality of Some Selected Sites of Durgapur Industrial Belt, West Bengal, India through Distribution and Abundance of Larval Chironomidae in Relation with Physicochemical Characteristics of Water Debolina Kar1, Arnab Banerjee2 and Debnath Palit3* Research Scholar, 2Assistant Professor, 3 Assistant Professor in Botany and Head, PG Dept. of Conservation Biology, Durgapur Govt. College, Durgapur, West Bengal, India *Corresponding Author E-mail: [email protected] 1

Abstract The present investigation was conducted to assess the status of water quality of selected sites of Durgapur area in terms of density and abundance of chironomid population in correlation with physico-chemical parameters of water. Six physical and eleven chemical water quality parameters were measured in four selected sites along with density and abundance of Chironomid population. The investigation revealed that chironomid larvae were abundant in site IV throughout the study period. Water and air temperature, light intensity, humidity, Dissolved Oxygen content showed significant seasonal variation among the four studied sites. The TDS, conductivity, total alkalinity, hardness, chloride, phosphate, nitrate value of water samples significantly varied in the four studied sites at different seasons throughout the study period.From the distribution of chironomid population it can be concluded that water quality of site IV is deteriorating at fast rate than site I, II and III respectively. Keywords: Physico-chemical parameters; Water quality, pollution status, Chironomid population.

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Introduction Water is the universal solvent on earth. Of the total amount of global water only 2.4 per cent is distributed on terrestrial region. From this amount only a small portion can be utilized as fresh water. The available fresh water to man is hardly 0.3 to 5 per cent of the total supply and therefore its judicious use is imperative. Though ponds and lakes are the principle forms of inland standing surface water, important to men, fishes, aquatic-birds, growth in population, industries and advanced agricultural practices in our country. They are became a threat to those ecosystem which were continuously used. Population explosion, industrialization, urbanization and developmental thrust of man have created problems of water pollution. Direct effluent discharges, agricultural run off, domestic sewage an oligotrophic water body most often contain complex mixtures of contaminants which may produce new compounds due to breakdown and transformation processes and hence contribute to the complexity of the total toxic burden. By the employment of chemical and physical measurements only, the synergistic effect of pollution on its biotic community may not be fully and easily assessed. In general biological indicators provide a potential for direct observation of the overall effect of environmental contaminants by virtue of their role in aquatic ecosystems (Warwick, 1988). Benthic macro invertebrate communities of streams can provide a direct measure of water quality. Several indices of bio-diversity are used in the assessment of water quality (Johnson 1995).The abundance of benthic fauna greatly depends on physical and chemical properties of the substratum (Paul and Nandi, 2003). Benthic macroinvertebrates can be used as a barometer of overall bio-diversity in aquatic ecosystems. Many benthic macro and micro-fauna species have short lifecycles and sedentary habits, making them more sensitive to pollution and physical and chemical variations in the water (Wu et al., 2004). For this reason, these organisms have been used in studies to evaluate the degree of alteration of these environments. Amongst them, Chironomids were considered as one of the most useful groups in assessing the quality of running waters because of their abundance, diversity and colonizing ability (Saether, 1979, 1980; Ruse and Wilson 1984, Bazzanti and Seminara 1987, Kawai et al., 1989, Bisthoven et al., 1992, Gerhardt and Bisthovan 1995). In particular chironomid (Diptera, : Chironomidae) larvae have been used successfully as bioindicators of toxicants in aquatic ecosystems. The Chironomidae family, one of the main representatives of the benthic community, is very diversified and abundant, and widely distributed (Oliver, 1971; Coffman and Ferrington, 1996) and can subsist in a wide range of water qualities (Saether, 1979; Lindergaard, 1995; Real et al., 2000; Higuti et al., 2005). Several studies have revealed that physical and chemical factors strongly influence the composition and abundance of chironomids (Oliver, 1971; Botts, 1997; Callisto, 1997). These characteristics make them potential candidates in monitoring water for the presence of pollution and determining the lake trophic level. Chironomids are one of the most abundant macro-invertebrate group and they often account for the majority of aquatic insects in freshwater environments (Epler, 2001). The larval stage that belongs to the family Chironomidae in various inland water (from lentic to lotic environments) is the longest period of life cycles of these

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insects. These are sometimes called 'bloodworms' because of their bright red colour, but they are not worms at all. Polluted water apparently favors their multiplication and emergence but relatively clean water can also support their breeding. Most of them are detritus feeders. Due to adaptation capability and ecological ability of larvae to extreme environmental conditions of temperature, pH, salinity, depth, flow velocity and productivity, they can be found in many different aquatic environments (Armitage et al., 1995). Also, species composition of chironomid assemblages differs qualitatively and quantitatively among microhabitats, and larvae are highly selective in their choice of a site (Maasri et al., 2008). Larval chironomids are used as indicators in biological classification of inland water reservoirs by their abundance in unit area of bottom and species compositions (Kırgız, 1988). Chironomid populations are subject to changes in physicochemical conditions and input of nutrients (Lim, 1990) and their abundance patterns are also influenced by the available larval food, particularly the deposition of organic matter and detritus on the bottom (Galdean et al., 2000).Therefore, the objectives of this present investigation includes assessment of the differential response of chironomid population in relation to physico-chemical characteristics of water in and around Durgapur industrial belt.

Materials and methods Study Area Site-I represents a waste canal is located near housing complex, at Durgapur, (Latitude- 23o30’13.2’’N, Longitude-87o1729.0’’E). Locally it is known as “Moyla Canal”. The main sources of this canal are industrial effluents from Durgapur Projects Limited, Durgapur Chemicals Limited, Sponge Iron Factories and Alloy Steel Plant. This canal contains coal ash, acids, toxic chemicals and liquid byproducts. Predominant plants in this site include Calotropis gigantia, Colocasia esculanta, Ipomoea fistulosa, Nicotiana plumbaginifolia, Parthenium histerophorous, Solanum nigrum, Typha domingensis. and Amaranthus viridis. Site II represents a pond locally known as Padmapukur, resulting from rain water and ground water. It is located near Ashishnagar, Durgapur. [Latitude - 23o29’56.9’’ (N), Longitude -87o17’16.6’’E]. The total area of this site is about 1 acre. A fresh canal is connected with this pond. Aquaculture practice here. This is a natural waterbodies and remarkable feature is that this waterbody is oligotrophic or mesotrophic in state. Pistia stratiotes, Ipomoea fistulosa, Hydrilla verticillata, Eichhornia crassipes, Colocasia esculenta, Typha angustifolia are predominant macrophytes in this site. Site-III is represented by domestic sewage canal resulting from domestic sewage of Amarabati and adjoining areas. Zooplankton sample and water sample are collected from a part of the domestic sewage canal located near Amarabati, Durgapur. (Latitude -23°32’23” N and Longitude 87o19’45.1” E). Hydrilla verticillata, Eichhornia crassipes, Colocasia esculenta Eclipta alba, Commelina benghalensis, Ipomea fistulosa are present in this site. Site-IV is represented by run-off of fields and rain water. It is located near Kabiguru, Durgapur. (Latitude- 23o32’47.9” N, Longitude -87°18’40.1” E). Ipomea

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fistulosa, Calotropis procera, Datura repens are some of the noteworthy plants.

Sampling of water samples Water samples were collected from the four sites for a period of one year from December 2009 to November 2010. The water samples were collected with the help of samplers. Water samples were brought in one-liter plastic containers to the laboratory for analysis. Various physico-chemical parameters of water samples were measured following the standard methods of APHA (1998). Determination of physical parameters The temperature of the water was recorded using a thermo probe (Model TL1-A) on the spot. Air temperature is measured by using thermometer. pH was recorded on the spot using a portable pen pH meter (Hanna®, Mauritius). Light intensity is measured by Digital Lux Meter (LX-101). Humidity is measured by using hygrometer 3 times in a day. Specific conductance was measured by using conductivity meter (Autoranging conductivity TCM 15+/TDS meter). TDS (180°C for 1 h (APHA 5520B) were estimated by gravimetric analysis. Determination of chemical parameters Alkalinity (APHA 2320B) was measured using acid–base titrimetry. Calcium and magnesium hardness (APHA 2340C) were determined using complex metric titration. Chloride was determined by argentometric titration method. Phosphate was estimated using spectrophotometric method. Nitrite (APHA 4500 NO−2 B) and nitrate nitrogen were estimated by acid treatment followed by spectrophotometry. DO was determined using Winkler’s method on the site itself. Primary productivity (NPP, GPP and Community respiration) were measured using Aqua Merck Kit (DO 1.11107.0001), using light and dark bottle. All the reagents used for the analysis were analytical reagent grade. The quality assurance and quality procedure were also used as described in APHA 1998. Determination of Chironomid larval population density To determine chironomid larval population density, three 15×15×15 cm Ekman dredge samplers were used for sampling at each sampling site. These benthic samples were washed through a 0.35-mm pore screen and the retained material identified and counted using standard methods (Ali et al., 1977; Ali and Baggs, 1982). The larval identification was verified by determination of adults emerging from the sites.

Statistical analysis The data obtained on the physicochemical parameters were subjected to correlation analysis (Zar 1999). Correlation index was used to determine whether there were any correlation between the limnological parameters and number of individuals or not. Following the correlation values and linearity of the relationships between the

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variables, a principal component analysis (SPSS ver10., Kinnear and Gray 2000) was performed to reduce the variable redundancy and representing the data more economically with substitute indices or components. The major objective of the present work was to assess water quality by using Chironomid larval population or factors (Manly 1994).

Results The limnological parameters for assessment of water quality for 12 months period (from December 2009 to November 2010) of four different study sites were presented in Tables 1, 2, 3 and 4 respectively. Higher atmospheric temperature for all the four study sites were recorded during the summer months and lower atmospheric temperature were recorded in winter months with moderate level of air temperature were recorded in monsoonal period. Water temperature showed similar increasing trend followed by subsequent decrease during the monsoon and winter seasons under the present investigations. Among the four study sites site-III represented highest atmospheric temperature and water temperature range for all the three seasons under present investigation.. (Table-3) The water samples of the four studied sites were found to be alkaline in nature throughout the study period. Among the four studied sites maximum and minimum pH value were 9.78 and 7.13 in site I; 8.77 and 7.23 in site II; 8.81 and 7.19 in site III; 7.47 and 7.27.in site IV. In all four studied sites pH value gradually increased from winter to summer. Our findings corroborates with the earlier findings of Chandrasekhar (1996) on Saroornagar Lake of Hyderabad. (Table- 1-4) Table 1: Physico-chemical analysis of water ( site-1). PARAMETERS Atm. Temp.(˚C) W. temp.(°C) Water pH LI(×100 Lux) Humidity Conductivity(µΩ) TDS(mg/l) Alkalinity(mmol/l) Hardness(mmol/l) Chloride(mg/l) Phosphate(ppm) Nitrate(mg/l) DO(mg/l) NPP(mgC/m3/day) CR(mg C/m3/day) GPP(mgC/m3/day)

Dec 18.33±0.15 22.27±0.15 7.13±0.15 240.19±0.19 55.13±0.15 0.40±0.02 0.18±0.01 3.47±0.15 1.40±0.10 28.13±0.15 10.13±0.15 0.47±0.06 2.20±0.10 325.17±0.15 814.83±0.11 1139.86±0.15

Jan 19.12±0.16 21.30±0.20 7.23±0.16 310.14±0.17 38.30±0.30 0.42±0.01 0.15±0.01 3.20±0.10 1.37±0.15 32.23±0.25 10.10±0.10 0.33±0.15 2.23±0.15 298.90±0.10 798.83±0.12 1097.77±0.15

Feb 32.43±0.15 27.57±0.15 7.61±0.12 850.20±0.20 34.03±0.25 0.41±0.02 0.14±0.02 3.23±0.15 1.23±0.15 36.17±0.21 10.07±0.12 0.20±0.10 2.30±0.10 375.23±0.25 874.90±0.10 1249.81±0.18

March 29.63±0.15 27.63±0.15 8.63±0.20 722.15±0.21 39.23±0.21 0.41±0.01 0.14±0.01 0.77±0.15 1.33±0.15 28.07±0.21 10.23±0.12 0.53±0.06 2.27±0.15 249.86±0.15 624.86±0.15 874.91±0.12

Apr 34.27±0.15 37.23±0.15 8.64±0.12 759.04±0.17 69.17±0.15 0.45±0.02 0.18±0.01 1.30±0.20 1.27±0.12 41.27±0.25 10.13±0.06 0.40±0.10 2.23±0.15 375.10±0.10 249.83±0.20 624.82±0.22

May 33.50±0.20 30.37±0.15 9.78±0.11 560.12±0.13 70.37±0.35 0.45±0.01 0.18±0.01 0.50±0.10 1.33±0.15 42.10±0.17 10.13±0.15 0.43±0.06 1.80±0.10 375.27±0.25 249.89±0.10 624.87±0.12

Jun 32.23±0.15 28.40±0.20 9.44±0.14 564.27±0.24 77.17±0.15 0.46±0.01 0.17±0.02 0.63±0.15 1.27±0.15 45.27±0.25 10.17±0.15 0.53±0.06 1.60±0.10 355.30±0.26 329.73±0.15 658.60±0.20

Jul 31.60±0.20 27.70±0.20 8.79±0.10 523.11±0.20 80.13±0.15 0.46±0.02 0.18±0.01 0.77±0.15 1.57±0.15 43.17±0.21 10.10±0.10 0.57±0.21 1.63±0.15 287.10±0.17 330.77±0.15 701.80±0.10

Aug 28.10±0.10 27.47±0.15 8.45±0.14 483.10±0.18 67.23±0.25 0.43±0.03 0.17±0.02 1.37±0.15 1.43±0.15 33.17±0.15 10.2±0.10 0.53±0.06 2.33±0.15 286.80±0.26 543.91±0.13 903.70±0.20

Sept 25.37±0.15 25.30±0.10 7.50±0.30 367.16±0.15 64.13±0.15 0.43±0.02 0.16±0.02 2.27±0.15 1.43±0.15 31.20±0.35 10.07±0.12 0.40±0.10 2.27±0.21 312.23±0.21 578.88±0.17 1079.73±0.21

Oct 21.33±0.15 24.63±0.15 7.71±0.10 312.15±0.18 62.20±0.20 0.39±0.01 0.17±0.01 2.67±0.15 1.63±0.15 28.23±0.21 10.10±0.10 0.60±0.10 2.13±0.15 323.53±0.15 736.85±0.13 1087.73±0.21

Nov 18.60±0.20 21.47±0.15 7.34±0.14 229.01±0.13 59.07±0.21 0.39±0.01 0.17±0.01 2.77±0.15 1.67±0.21 28.17±0.21 10.07±0.06 0.47±0.06 2.27±0.15 322.10±0.10 810.70±0.20 1121.80±0.11

Note: All the values were reported in mean ±standard deviation. means of three replicates were taken.

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Debolina Kar et al Table 2: Physico-chemical analysis of water (site- 2).

PARAMETERS Dec Jan Feb March Apr May Jun Jul Aug Sept Oct Nov Atm. Temp.(˚C) 24.23±0.15 26.10±0.10 31.53±0.15 31.73±0.15 34.27±0.21 35.53±0.15 34.37±0.15 34.23±0.15 32.60±0.10 28.40±0.10 26.70±0.20 24.17±0.15 W. temp.(°C) 18.37±0.15 24.33±0.15 23.70±0.10 25.37±0.15 31.27±0.15 32.20±0.20 31.80±0.10 31.17±0.12 28.30±0.10 24.73±0.15 20.40±0.10 20.13±0.15 Water pH 7.07±0.21 7.23±0.15 7.70±0.10 7.60±0.10 7.53±0.15 8.77±0.15 8.40±0.10 8.50±0.10 8.27±0.15 7.70±0.10 7.70±0.10 7.50±0.10 LI(×100 Lux) 318.23±0.25 350.20±0.20 385.23±0.21 560.20±0.26 510.23±0.25 396.23±0.25 330.30±0.30 317.13±0.15 312.23±0.25 305.27±0.25 239.30±0.30 210.13±0.15 Humidity 50.23±0.25 33.13±0.15 42.20±0.20 50.17±0.15 54.23±0.25 65.17±0.21 77.27±0.25 69.17±0.15 60.10±0.10 56.30±0.26 51.17±0.21 49.17±0.15 Conductivity(µΩ) 0.36±0.02 0.38±0.02 0.41±0.02 0.41±0.03 0.44±0.01 0.44±0.02 0.42±0.02 0.37±0.01 0.35±0.01 0.36±0.02 0.34±0.01 0.32±0.01 TDS(mg/l) 0.15±0.02 0.16±0.01 0.16±0.01 0.17±0.02 0.18±0.02 0.17±0.03 0.16±0.01 0.18±0.02 0.15±0.01 0.16±0.02 0.15±0.01 0.15±0.01 Alkalinity(mmol/l) 2.50±0.10 2.27±0.15 2.30±0.20 2.20±0.10 2.60±0.10 2.63±0.15 2.60±0.10 2.27±0.15 1.77±0.15 1.47±0.15 1.50±0.10 1.20±0.10 Hardness(mmol/l) 1.40±0.10 1.20±0.10 1.23±0.15 0.77±0.15 1.20±0.10 1.30±0.20 1.30±0.10 1.23±0.15 1.20±0.10 1.40±0.10 1.20±0.10 1.30±0.10 Chloride(mg/l) 32.40±0.36 35.47±0.42 38.33±0.31 38.17±0.21 30.27±0.25 30.20±0.20 32.23±0.25 30.13±0.15 31.37±0.32 28.23±0.21 32.17±0.21 33.20±0.20 Phosphate(ppm) 5.20±0.20 5.27±0.25 5.17±0.15 5.33±0.31 5.17±0.15 5.23±0.15 5.10±0.17 5.23±0.21 5.13±0.15 5.23±0.25 1.27±0.25 1.10±0.10 Nitrate(mg/l) 0.13±0.02 0.13±0.01 0.13±0.02 0.13±0.01 0.16±0.02 0.14±0.01 0.13±0.01 0.13±0.02 0.12±0.01 0.13±0.02 0.12±0.02 0.13±0.02 DO(mg/l) 5.20±0.10 5.50±0.10 5.70±0.10 4.30±0.20 2.47±0.15 1.73±0.15 1.47±0.15 2.37±0.15 4.57±0.15 5.33±0.15 5.30±0.10 5.23±0.15 NPP(mgC/m3/day) 999.82±0.17 999.83±0.19 1125.12±0.12 1125.14±0.15 1375.18±0.16 749.90±0.15 728.83±0.20 812.88±0.11 837.81±0.16 910.80±0.16 902.89±0.10 985.89±0.11 CR(mg C/m3/day) 620.91±0.13 624.87±0.14 621.23±0.20 749.82±0.15 874.81±0.20 1125.13±0.4 945.76±0.16 776.19±0.20 582.15±0.19 769.88±0.10 723.86±0.11 669.16±0.20 GPP(mgC/m3/day) 1620.84±0.18 1624.91±0.14 1746.20±0.17 1874.89±0.16 2250.15±0.19 1874.75±0.20 1856.63±0.14 1735.73±0.21 1662.82±0.13 1616.13±0.15 1621.78±0.17 1628.20±0.21

Note: All the values were reported in mean ±standard deviation. means of three replicates were taken. Table 3: Physico-chemical analysis of water (site- 3). PARAMETERS Dec Jan Feb March Apr May Jun Jul Aug Sept Oct Nov Atm. Temp.(˚C) 24.33±0.15 26.33±0.15 34.20±0.20 37.23±0.25 36.27±0.15 45.40±0.36 42.47±0.42 38.17±0.15 33.33±0.31 26.20±0.20 25.57±0.25 24.13±0.15 W. temp.(°C) 21.50±0.10 24.23±0.25 25.67±0.15 26.17±0.15 29.27±0.15 30.30±0.10 30.13±0.15 29.17±0.15 28.40±0.20 25.27±0.15 25.13±0.15 24.57±0.15 Water pH 7.33±0.15 7.37±0.06 7.57±0.15 7.66±0.14 7.50±0.10 8.81±0.08 8.59±0.10 8.31±0.10 7.61±0.12 7.51±0.10 7.40±0.11 7.19±0.09 LI(×100 Lux) 575.13±0.15 634.23±0.25 789.33±0.31 810.20±0.20 852.17±0.21 963.17±0.15 778.23±0.25 764.33±0.35 690.63±0.55 648.33±0.31 644.23±0.25 621.23±0.32 Humidity 28.20±0.20 31.13±0.15 34.40±0.36 35.23±0.25 34.10±0.10 44.13±0.15 57.27±0.25 69.40±0.36 58.20±0.20 47.27±0.25 34.20±0.20 33.27±0.31 Conductivity(µΩ) 0.34±0.02 0.36±0.01 0.38±0.01 0.37±0.02 0.44±0.01 0.42±0.02 0.37±0.01 0.36±0.01 0.36±0.02 0.33±0.01 0.33±0.02 0.33±0.01 TDS(mg/l) 0.16±0.01 0.15±0.01 0.16±0.01 0.16±0.01 0.18±0.01 0.17±0.01 0.16±0.01 0.17±0.01 0.14±0.01 0.15±0.01 0.15±0.02 0.13±0.02 Alkalinity(mmol/l) 1.20±0.10 1.27±0.15 1.20±0.10 1.33±0.15 1.47±0.15 1.23±0.15 1.27±0.15 1.40±0.10 1.20±0.10 1.27±0.15 1.20±0.10 1.13±0.06 Hardness(mmol/l) 0.57±0.15 0.50±0.20 0.57±0.15 0.47±0.15 0.33±0.15 0.40±0.10 0.60±0.10 0.63±0.15 0.50±0.10 0.40±0.20 0.43±0.15 0.40±0.10 Chloride(mg/l) 20.33±0.15 29.17±0.15 38.20±0.20 38.13±0.15 30.23±0.25 28.23±0.21 27.37±0.32 29.50±0.46 28.27±0.25 26.30±0.30 27.23±0.21 26.23±0.25 Phosphate(ppm) 10.17±0.15 10.27±0.25 10.30±0.26 10.20±0.20 10.20±0.26 5.27±0.25 10.13±0.15 5.20±0.20 5.23±0.25 5.10±0.10 10.07±0.12 10.33±0.31 Nitrate(mg/l) 0.02±0.02 0.02±0.01 0.04±0.01 0.02±0.01 0.06±0.02 0.05±0.01 0.05±0.01 0.03±0.01 0.04±0.01 0.02±0.02 0.02±0.01 0.03±0.02 DO(mg/l) 5.30±0.10 5.30±0.10 5.50±0.10 6.57±0.15 2.20±0.10 4.47±0.15 3.33±0.15 4.77±0.15 5.57±0.15 5.43±0.15 5.37±0.21 5.23±0.15 NPP(mgC/m3/day) 874.92±0.11 749.85±0.19 875.07±0.23 962.89±0.10 1249.91±0.12 749.88±0.17 744.82±0.20 856.72±0.23 1010.88±0.11 980.82±0.15 999.84±0.17 987.77±0.23 CR(mg C/m3/day) 624.78±0.35 500.14±0.14 624.72±0.24 999.82±0.23 874.67±0.37 874.73±0.25 854.68±0.33 761.69±0.32 746.70±0.28 621.59±0.34 610.59±0.35 590.82±0.27 GPP(mgC/m3/day) 1500.86±0.12 1249.75±0.25 1499.83±0.24 1624.82±0.15 2124.82±0.18 1624.86±0.15 1660.78±0.21 1589.86±0.12 1527.84±0.14 1441.87±0.16 1212.76±0.21 1225.82±0.15

Note: All the values were reported in mean ±standard deviation. means of three replicates were taken. Table 4: Physico-chemical analysis of water (site- 4). PARAMETERS Atm. Temp.(˚C) W. temp.(°C) Water pH LI(×100 Lux) Humidity Conductivity(µΩ) TDS(mg/l) Alkalinity(mmol/l) Hardness(mmol/l) Chloride(mg/l) Phosphate(ppm) Nitrate(mg/l)

Dec 20.43±0.15 18.37±0.21 7.27±0.15 556.17±0.15 42.20±0.20 0.17±0.01 0.08±0.01 0.70±0.20 0.30±0.10 10.13±0.15 0.60±0.10 0.03±0.02

Jan 21.77±0.15 19.27±0.25 7.30±0.10 560.13±0.15 40.20±0.20 0.19±0.02 0.07±0.01 0.73±0.21 0.27±0.15 20.23±0.15 1.00±0.10 0.03±0.01

Feb 29.20±0.20 23.27±0.21 7.23±0.15 581.17±0.15 39.13±0.15 0.18±0.02 0.08±0.02 0.57±0.15 0.37±0.15 25.23±0.25 0.53±0.15 0.02±0.01

March 37.73±0.21 33.13±0.15 7.47±0.15 701.10±0.10 37.20±0.20 0.17±0.02 0.07±0.02 0.43±0.15 0.27±0.15 18.20±0.20 0.50±0.10 0.02±0.01

Apr 35.17±0.15 27.73±0.15 7.27±0.15 836.27±0.25 54.17±0.15 0.45±0.01 0.17±0.02 1.40±0.20 0.30±0.10 55.13±0.15 1.10±0.10 0.03±0.02

May 33.33±0.21 29.17±0.15 7.30±0.20 971.17±0.21 37.27±0.15 0.43±0.01 0.18±0.01 0.37±0.15 0.47±0.15 42.27±0.25 0.90±0.10 0.04±0.01

Jun 33.20±0.20 29.43±0.15 7.33±0.25 889.20±0.20 59.13±0.15 0.42±0.02 0.19±0.02 0.30±0.10 0.50±0.10 44.20±0.20 0.97±0.15 0.02±0.02

Jul 32.63±0.15 28.57±0.15 7.27±0.15 860.20±0.20 47.23±0.25 0.43±0.02 0.18±0.01 0.47±0.15 0.33±0.12 41.17±0.15 0.47±0.15 0.02±0.01

Aug 30.23±0.15 26.17±0.15 6.70±0.20 795.23±0.21 40.13±0.15 0.42±0.02 0.14±0.02 0.40±0.20 0.47±0.15 33.57±0.12 1.10±0.10 0.03±0.01

Sept 28.23±0.25 23.40±0.10 7.20±0.10 750.23±0.25 36.27±0.25 0.38±0.02 0.13±0.01 0.43±0.21 0.33±0.15 27.33±0.31 0.53±0.15 0.03±0.02

Oct 24.33±0.15 21.67±0.15 7.47±0.12 603.13±0.15 32.20±0.20 0.36±0.02 0.12±0.02 0.67±0.15 0.30±0.10 23.10±0.10 0.53±0.06 0.02±0.01

Nov 22.27±0.25 18.13±0.15 7.33±0.15 575.13±0.15 28.17±0.21 0.36±0.01 0.10±0.02 0.60±0.20 0.20±0.10 15.23±0.21 0.50±0.10 0.02±0.02


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DO(mg/l) 7.17±0.15 7.23±0.12 7.60±0.10 8.67±0.15 2.20±0.10 3.33±0.15 2.77±0.15 3.47±0.15 5.67±0.15 7.30±0.10 7.10±0.10 7.50±0.10 NPP(mgC/m3/day) 750.17±0.15 1000.09±0.18 1125.20±0.20 1125.27±0.25 1250.13±0.15 874.77±0.22 949.20±0.20 1029.13±0.15 984.73±0.15 876.82±0.19 753.86±0.14 747.81±0.20 3 CR(mg C/m /day) 250.20±0.20 250.13±0.15 500.20±0.20 749.86±0.12 749.85±0.13 625.27±0.25 620.17±0.15 639.84±0.15 398.28±0.28 281.85±0.12 277.80±0.16 250.82±0.17 GPP(mgC/m3/day) 1000.09±0.18 1250.13±0.15 1625.23±0.21 1874.80±0.20 2000.23±0.25 1500.23±0.21 1530.17±0.15 1525.23±0.25 1449.27±0.25 1427.17±0.21 1300.27±0.25 1288.30±0.26

Note: All the values were reported in mean ±standard deviation. means of three replicates were taken. In the present investigation, light intensity gradually increased from the month of December to May and then decreased during the winter months for all four study sites. The range of light intensity was found to be higher in site III and IV in comparison to site I and II. (Table – 1-4). Humidity values ranged between 34.03% to 80.13% in site 1, 33.13% to 77.27% in site 2, 28.20% to 69.40% in site 3 and 28.17% to 59.13% in site 4. Humidity was maximum in months of June-July and minimum in months December- February among the four studied sites. (Table-1-4) Higher level of conductivity value of water samples were recorded during the summer and pre -monsoon periods for all the four studied sites. (Table- 1-4) TDS value did not showed any significant level of variation among the four studied sites.TDS value were found to be higher in summer followed by winter and monsoon. Tripathi and Pandey (1990) similarly reported higher level of TDS during summer from two ponds of Uttar Pradesh. The levels of conductivity were found significantly higher for site-IV. (Table- 1-4) Total alkalinity showed a declining trend from winter to summer and then monsoon for site I. In site II, the level of total alkalinity was significantly higher during winter, summer and pre monsoon period and then declined from monsoonal period. For Site-III and Site-IV the level of total alkalinity showed considerable fluctuation among the different seasons throughout the investigation period. Site 1 reflected significantly higher measurements of total alkalinity in comparison to the other studied sites. (Table-1-4). In the present investigation, observations reveal that the values of hardness are in decreasing order from site1 > site2 > site3 > site4. Total hardness were highest in the month of March and lowest in the month of April and June for site 1, highest in the month of September and December and lowest in the month of March for site 2, highest in the month July and lowest in April in site 3 and highest in month June and lowest in November in site 4. (Table-1-4) During the present investigation, the values of chloride content of water samples of four studied sites were found to be higher in summer comparison to other seasons. (Table- 1-4) Phosphate content in water samples showed considerable variation among the four studied sites. Minimum level of phosphate content was found to be in case of site-IV through out the study period. There is no such variation in the level of phosphate content of water samples in site I. There is significant reduction in the phosphate content of water samples during pre winter months for site-II. Lower level of phosphate content was recorded during monsoonal period for site III. The phosphate level fluctuates throughout the whole study period for site-IV (Table- 1-4)

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The nitrate concentration of water of all the study sites showed significant fluctuation throughout the study period. Higher level of nitrates in water samples were recorded for site –I and minimum level were recorded for site-III and IV. (Table -1-4) There is a gradual decline in dissolved oxygen concentration from winter to summers in all the four sites. Jain et al., (1996) similarly reported a sharp decline in dissolved oxygen values from winters to summers in Halali reservoir at Vidisha. (Table-1-4) During the study period, the net primary productivity, community respiration and gross primary productivity ranged 249.86 to 1375.18, 249.83 to 1125.13, 624 to 2250.15 mgC/m3/day respectively. In site 1 productivity decreased gradually from the month December to April and then further increased and reverse observation were recorded for site 2. The productivity was high in the month April in both sites 3 and 4 and less in month of October in site 3 and December in site 4. (Table-1-4) The monthly fluctuation in relative abundance of total Chironomid larvae at four sampling sites is presented in Figure 1. In the present investigation, low abundance and distribution of larval chironomids were reported in site II and site III, highest values were recorded for site I and IV respectively. Number of chironomid population were found to higher during the winter and post winter season for first three study sites and site IV indicating the dense population of chironomid larva throughout the study period. From the correlation study, it was observed that, a negative correlation exists between atmospheric temperature and water temperature with distribution and abundance of population of Chironomid larvae (r=-0.31 and r=-0.37 respectively) for site I. In site II, atmospheric temperature is positively correlated with distribution and abundance of population of Chironomid larvae (r=0.05) but water temperature was found to be negatively correlated (r=-0.19). As far as site III is concerned, atmospheric temperature and water temperature are negatively correlated (r=-0.88 and r=-0.70 respectively) with distribution and abundance of population of Chironomid larvae. In site IV both parameters are positively correlated with larval population (r=0.13 and r=0.33 respectively). Similar results were indicated by Saha and Pandit (1986) In Site I and Site II, pH was positively correlated (r=0.05) and (r=0.02) and in Site III (r=-0.69) and Site IV, it is negatively correlated (r=-0.32) with chironomid larval population. Total hardness is positively correlated (r=0.94) with Chironomid larval population in site I. Chloride contents were positively correlated (r=0.88) with Chironomid population in site II and negatively correlated in site I. Net Primary Productivity (NPP) shows negative correlation with larval population (r= -0.93). The correlation matrix of the water quality parameters are presented in Table 5, 6, 7 and 8 for Site I, II, III and IV respectively. The correlation coefficient values were, in most cases, above 0.3 and significant at P < 0.05, thus justifying the use of multivariate statistics (PCA). Table 9-12 shows that factor analysis extracts three factors according to eigenvalues (>1) for the three studied sites. For site I the first, second and third factor accounts for 38.414%, 26.987% and 17.640 % of variability in the water quality. Parameters such as air temperature, water temperature, light intensity, conductivity and chloride were found to be significantly loaded in factor I, humidity, total dissolved solid, nitrate nitrogen were significantly loaded in factor 2, phosphate phosphorous in factor 3. For site II the first, second and third factor


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accounts for 43.284%, 18.997% and 16.859 % of variability in the water quality. Parameters such as air temperature, water temperature, conductivity, TDS, alkalinity, community respiration and GPP were found to be significantly loaded in factor I, NPP were significantly loaded in factor 2, light intensity, chloride in factor 3. For site III the first, second and third factor accounts for 41.526%, 17.194% and 16.606% of variability in the water quality. Parameters such as water temperature, conductivity, TDS, alkalinity, nitrate nitrogen, community respiration and GPP were found to be significantly loaded in factor I, Light intensity were significantly loaded in factor 2, and no such parameter were significantly loaded in factor 3. For site IV the first, second and third factor accounts for 31.076%, 28.684% and 17.913 % of variability in the water quality. Parameters such as air temperature, water temperature, NPP, community respiration and GPP were found to be significantly loaded in factor I, conductivity, TDS, chloride, phosphate were significantly loaded in factor 2, and light intensity in factor 3. Table 5: Correlation between different physico-chemical factors of water and chironomid larvae in site-I.

(*AT-Atmospheric temperature, WT-Water temperature, pH-Water pH, LI-Light intensity, HUMI-Humidity, CONDT -Conductivity, TDS-Total dissolved solids, ALK-Alkalinity, HRD-Total Hardness, CL-Chloride, PHOS-Phosphate, NI-Nitrate, DO-Dissolved oxygen, NPP-Net primary productivity, CR-Community Respiration, GPP-gross primary productivity, NOC- Number of chironomid larvae) Table 6: Correlation between different physico-chemical factors of water and chironomid larvae in site-II.

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Table 7: Correlation between different physico-chemical factors of water and chironomid larvae in site-III.

(*AT-Atmospheric temperature, WT-Water temperature, pH-Water pH, LI-Light intensity, HUMI-Humidity, CONDT -Conductivity, TDS-Total dissolved solids, ALK-Alkalinity, HRD-Total Hardness, CL-Chloride, PHOS-Phosphate, NI-Nitrate, DO-Dissolved oxygen, NPP-Net primary productivity, CR-Community Respiration, GPP-gross primary productivity, NOC- Number of chironomid larvae) Table 8: Correlation between different physico-chemical factors of water and chironomid larvae in site-IV.

(*AT-Atmospheric temperature, WT-Water temperature, pH-Water pH, LI-Light intensity, HUMI-Humidity, CONDT -Conductivity, TDS-Total dissolved solids, ALK-Alkalinity, HRD-Total Hardness, CL-Chloride, PHOS-Phosphate, NI-Nitrate, DO-Dissolved oxygen, NPP-Net primary productivity, CR-Community Respiration, GPP-gross primary productivity, NOC- Number of chironomid larvae) Table 9: Principal component analysis (3 components counted) with varimax rotation for physico-chemical parameters of water in site- I, II, III, IV. Site-I

ATM_TEMP W_TEMP

1 .981 .865

Component 2 3 4.435E-03 -2.069E-02 .120 -.108

Water Quality of Some Selected Sites of Durgapur Industrial Belt W_PH .696 .601 .294 LI .872 -.423 4.694E-02 HUM .135 .969 2.637E-02 CONDT .765 .463 -.178 TDS 1.389E-02 .867 -.285 ALK -.766 -.471 -.406 HRD -.131 -.143 .932 CL .798 .370 -.368 PHOS .358 .130 .700 NI -.128 .737 .587 DO -.444 -.632 6.817E-02 NPP .359 -1.754E-02 -.796 CR -.757 -.620 9.703E-03 GPP -.754 -.605 -.126 Eigenvalue 6.530 4.588 2.999 % of Variance 38.414 26.987 17.640 Cumulative % 38.414 65.401 83.040

Site-II Component 1 2 3 ATM_TEMP .868 -.316 .222 W_TEMP .890 -.332 6.485E-02 W_PH .561 -.697 -6.332E-02 LI .307 .438 .799 HUM 9.628E-02 -.831 -.262 CONDT .878 .186 .239 TDS .811 .123 .240 ALK .715 .160 .215 HRD -.114 3.482E-02 -.820 CL -.259 .191 .708 PHOS 9.848E-02 .151 .633 NI .732 .637 -.139 DO -.887 .307 .136 NPP 4.966E-02 .896 .361 CR .827 -.205 -.357 GPP .851 .386 .163 Eigenvalue 7.358 3.229 2.866 % of Variance 43.284 18.997 16.859 Cumulative % 43.284 62.281 79.140

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Site-IV

ATM_TEMP W_TEMP W_PH LI HUM CONDT TDS ALK HRD CL PHOS NI DO NPP CR

Component 1 2 3 .927 .152 .265 .874 .128 .395 .124 -.588 -.509 7.474E-02 .152 .960 .564 .489 -.120 .195 .718 .243 .369 .763 .330 .104 .259 -.932 .225 .531 .649 .614 .760 4.406E-02 .124 .756 -.132 -.275 .646 6.484E-02 -.424 -.843 -6.33E-02 .825 5.809E-02 -.316 .939 .178 9.094E-02

Water Quality of Some Selected Sites of Durgapur Industrial Belt GPP Eigen Values % of Variance Cumulative %

.928 5.283 31.076 31.076

6.471E-02 4.876 28.684 59.761

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-.155 3.045 17.913 77.674

(*AT-Atmospheric temperature, WT-Water temperature, pH-Water, LI-Light intensity, HMD-Humidity, CONDT -Conductivity, TDS-Total dissolved solids, ALKAlkalinity, HRD-Total Hardness, CL-Chloride, PHOS-Phosphate, NI-Nitrate, DODissolved oxygen, NPP-Net primary productivity, CR-community respiration, GPPgross primary productivity). With the help of hierarchical cluster analyses based on physicochemical conditions of site I (Fig.1), site II (Fig.2), site III (Fig.3) and site IV (Fig.4) the sampling months could be clustered and categorized into several small groups. The dendrogram shows that for site I, December – January formed a cluster which is closely related. This is distantly related with month of February. Month of April and May formed a cluster. This cluster is distantly related with the month of March. These two distantly related clusters are further joined by another distant cluster. For site II, December- January formed a closely related cluster adjoined by the month of February. Month of March again formed a cluster with previous one. Month of May again formed a cluster with previously related clusters. Month of April distantly formed a cluster with cluster of December, January, February, March and May. In site III, December- February and month March- May formed two separate clusters that are closely related. January form a cluster with month DecemberFebruary. These cluster again joined with the clusters of March- May. Again this newly formed cluster distantly related with the month April following another cluster. In site IV, month of December and January formed together a closely related cluster. Month of February and March formed a close cluster. This cluster again joined with month April by another cluster. This cluster joined with month May. This cluster was found to be distantly related with December- January forming another distant cluster.

Figure 1: Abundance of Chironomid larvae within four sites in monthly variation.

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Figure 2: Hierarchical cluster analysis for different months of water sampling in siteI.

Figure 3: Hierarchical cluster analysis for different months of water sampling in siteII.


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Figure 4: Hierarchical cluster analysis for different months of water sampling in siteIII.

Figure 5: Hierarchical cluster analysis for different months of water sampling in siteIV.

Discussion

In our present investigation measured temperature showed significant level of seasonal variation. According to Sharma and Jain (2000) the fluctuations in water

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temperature has relationships with the air temperature. The variation in water temperature found in the present investigation may be due to the normal climatic fluctuations and effect of seasons and different times of collection or may be due to the effect of atmospheric temperature as reported by Jayaraman et al., (2003); Tiwari et al., (2004); and Zingade (1981) respectively. The surface water temperature showed an increasing trend during summer months as influenced by the intensity of solar radiation, evaporation, freshwater influx and cooling and mix up with ebb and flow from adjoining neritic waters (Ajithkumar et al., 2006; Saravanakumar et al., 2008). The alkaline nature of the water samples of the four studied sites indicates towards the anthropogenic influence in terms of on-farm inputs as well as industrial and domestic discharges as well as due to the buffering capacity of water. (Datta et al., 2009) Hydrogen ion concentration (pH) in surface waters remained alkaline throughout the study period at four study sites with maximum value during the postmonsoon and summer seasons and the minimum during monsoon. Generally, its seasonal variations attributed to factors like removal of CO2 by photosynthesis through bicarbonate degradation, dilution of seawater by freshwater influx, low primary productivity, reduction of salinity and temperature, and decomposition of organic matter (Paramasivam and Kannan, 2005; Bragadeeswaran et al., 2007). The recorded high summer pH might be due to the influence of high biological activity (Govindasamy et al., 2000) and due to the occurrence of high photosynthetic activity (Sridhar et al., 2006; Saravanakumar et al., 2008). Light intensity value of the present investigation reflected the effect of different seasons on the four studied sites under the present investigation. Higher level of humidity were recorded during monsoonal period for all the four studied sites due to higher evaporation rate from the surface water bodies during the pre-monsoonal period and subsequent increase in the moisture content in the atmosphere during the monsoonal period. Lower level of humidity were observed during post monsoonal period reflecting lower evaporation rate from the water bodies and therefore lower level of moisture content in the atmosphere. Higher level of conductivity value during summer months may be attributed towards more concentration of organic matter and also due to human intervention (Claymo, 1983; Koshy and Nayar, 2000; Dakshini and Soni, 1979; Mahadavan and Krishnaswami, 1983; Datta et al., 1988; Mathew Vergis, 1995; Mathew Koshy, 2005). The TDS value were found to be higher during summer months which may attributed towards the higher evaporation rate under higher solar insulation and therefore increase in the soluble salt concentration as well as addition of sediments in the four studied sites in terms of agricultural run-off, industrial discharge as well as discharge of domestic sewage ( Datta et al., 2009). Higher alkalinity during summer months were recorded which may be attributed towards the increased photosynthesis in the algal blooms resulting into the precipitation of carbonates of calcium and magnesium from bicarbonates causing higher alkalinity. Similar observations were made by Kulshrestha et al., 1992. Higher level of hardness in water in site-I is due to the natural accumulation of salts from contact with the soil and geological formations or it may enter from the direct pollution by human activities. In short hardness is higher in the pre monsoon period in all sites, possibly due to the influx of water and lowered hardness in all the sites during monsoon rains (Joseph et al., 2010).


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Large content of chloride in fresh water are an indication of organic pollution (Thresh et al., 1944). Though chloride level as high as 250 mg/l (0.250g /l) is safe for human consumption, a level above this imparts salty taste to potable water. Chloride content of water is one of the important ecological factors, which influences the functional physiology and reproductive activity of organisms (Kinne, 1971) there by affecting distribution of planktons and animals.The higher level of chloride content during summer months may be attributed towards continuous evaporation of water especially during summer season (Nair et al., 1983; Harikantra and Parulekar, 1989; Sampathkumar and Kannan, 1998; Borase and Bhave, 2001) Higher level of phosphate content during summer months for site –II can be attributed due to agricultural activities and other domestic anthropogenic activities. (Tepe et al., 2005). The addition of super phosphates applied in the agricultural fields as fertilizers and alkyl phosphates used in households, as detergents can be other sources of inorganic phosphates during the season (Bragadeeswaran et al., 2007). The post-monsoonal low value could be attributed to the limited flow of freshwater, high salinity and utilization of phosphate by phytoplankton (Rajasegar, 2003). The variation may also be due to the processes like adsorption and desorption of phosphates and buffering action of sediment under varying environmental conditions (Rajasegar, 2003). The recorded highest monsoonal nitrate value could be through oxidation of ammonia form of nitrogen to nitrite formation (Rajasegar, 2003). The recorded low values during non-monsoon period may be due to its utilization by phytoplankton as evidenced by high photosynthetic activity (Rajaram et al., 2005; Bragadeeswaran et al., 2007). Dissolved oxygen content has inverse relationship with temperature. As the temperature was slightly lower during monsoon and winter months the dissolve oxygen content was found to be higher in water samples of the studied sites. (Datta et al., 2009). The higher water temperature may result in decline of dissolved oxygen concentration of water. The maximum value of gross production (GPP) was at site II and III, probably because of the higher phytoplankton biomass and low salinity as well as due to the presence of higher concentration of nitrogen and phosphorus leading to the growth of phytoplankton at site-II and III. Due to high intensity of sunlight at the surface water during summer, the net productivity (NPP) was higher as compared with monsoon and winter seasons for all four study sites. Higher rate of Community Respiration(CR) for site I in winter months and during summer months for site II, III and IV were due to higher growth rate of phytoplanktons, algal blooms as well as growth of aquatic macrophytes in the respective seasons (Prassanna et al., 2010). Seasonal differences in the density and abundance could be explained by the different amounts of allochthonous material entering these systems. Increased input of allochthonous matter produces a decrease in organism density. The higher values of chironomid larva during the winter and post winter period may be attributed towards increase in nutrient inputs and organic materials, primarily domestic sewage, agrochemicals which increased the amount of benthic surface area by increasing the three dimensional aspect of the four study sites and by providing an increase in food

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supply for the chironomids (Friemouth et al., , 1994). Also the lower level of air and water temperature, light intensity along with increased level of dissolved oxygen content during the winter and post winter period may have provided congenial environment for overgrowth and development of chirononid population among the four studied sites under the present investigation. As the population of chironomids were higher in site IV were significantly higher throughout the study period it therefore indicates towards higher nutrient enrichment and organic material concentration. Therefore the water quality of study site IV is deteriorating at fast rate due to anthropogenic inputs. Site I, II and III were less vulnerable with respect to deterioration of water quality due to anthropogenic influence. Our observations were further supported by negative correlations between pH and chironomid population and positive correlation between air and water temperature for study site-IV. The density of chironomid population in site I, II and III were least may be due to water pH, presence of toxic elements along with low nutrient inputs. From the overall observations it can be concluded that impairment of the water quality of the studied sites has contributed significantly towards distribution and abundance of chironomid population among different seasons. Among the four study sites the water quality of site IV is deteriorating at fast rate in compare to other study sites. Therefore, distribution and abundance of chironomid population shows considerable promise towards indicating the status of water quality of selected study sites in and around Durgapur Industrial belt, West Bengal India.

References [1] Ajithkumar, T.T., Thangaradjou, T. and Kannan, L. 2006. Physico-chemical and biological properties of the Muthupettai mangrove in Tamil Nadu. J. Mar. Biol. Ass. India, 48: 131-138. [2] Ali, A. & Baggs, R. D. 1982. Seasonal changes of chironomid populations in a shallow natural lake and in a man-made water cooling reservoir in central Florida. Mosq. News 42: 76–85. [3] Ali, A., Mulla, M. S., Federici, B. A. and Pelsue, F. W. 1977. Seasonal changes in chironomid fauna and rainfall reducing chironomids in urban flood control channels. Environ. Entomol. 6: 619–622. [4] American Public Health Association (APHA). 1998. Standard methods for the examination of water and wastewater (20th ed.) Washington, DC: American Public Health Association. [5] Armitage, P., Cranston, P.S. and Pinder, L.C.V. 1995. Chironomidae - Biology and ecology of non-biting midges. Chapman & Hall, London. 572. [6] Bazzanti M. and Seminara M. 1987. Environmental stress in a regulated Eutrophic lake indicated by the profounded benthic community. Bull. Zool., 54, 261-266. [7] Bisthoven I. G. J., Timmermans K. R. and Ollivier F. 1992. The concentration of cadmium, lead, copper and zinc I Chironomus thummi larvae (Diptera: Chironomidae) with deformed versus normal menta. Hydrobiol., 239: 141-149.


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[8] Borase, P.V. and Bhave, S.K. 2001. Seasonal variation in Temperature, Dissolved oxygen, pH, and Salinity and their influence on planktons Inaner River Water, Jalgaon, Maharashtra. Poll. Res., 20 (1): 79 - 82. [9] Botts, P.S. 1997. Spatial pattern, patch dynamics and successional change: chironomid assemblages in a Lake Erie coastal wetland. Freshw. Biol., vol.37, no. 2: 277-286. [10] Bragadeeswaran, S., Rajasegar, M., Srinivasan, M. and Kanagarajan, U. 2007. Sediment texture and nutrients of Arasalar estuary, Karaikkal, southeast coast of India. J. Environ. Biol., 28: 237-240. [11] Callisto, M. 1997. Larvas bentônicas de Chironomidae (Diptera: Insecta) em quatro ecossistemas lóticos amazônicos sob influência das atividades de uma mineração de bauxita. Anais do 8 Seminário Regional de Ecologia: 89-98. [12] Chandrasekhar, S. V. A. 1996. Ecological studies on Saroornagar Lake, Hyderabad. Ph. D. thesis, Osmania University, Hyderabad. [13] Clymo, R.S. 1983. Peat. In. Micro-swamps, Bog. Fen and Moor, Ecosystem of the world. (Ed.) A.J.P. Gore, Elsevier, Amsterdam. [14] Coffman, W.P. & Ferrington, L.C. jr. 1996. Chironomidae. In: R.W. Merritt & K.W. [15] Cummins (Eds.). An Introduction to the aquatic insects of North America, 3rd edn, Kendall/Hunt, Dubuque. 635-754. [16] Cranston P. S. 1995. Introduction. In The Chironomidae: Biology and Ecology of Non-biting midges (eds.:Armitage P. D., Cranston P.S. and Pinder L.C.V.).Chapman and Hall. London, United Kingdom: 1-10. [17] Dakshini, K.M.M. and Soni, J.K. 1979. Water quality of sewage drains entering Yamuna in Delhi. Indian J. Environ. Hlth. 21(4): 354-361. [18] Datta J.K., Layek S., Banerjee A., Mondal N.K. and Gupta, S. 2009. Physicochemical characterization of water quality of eutrophied surface water body and ground water around the field crop research station, Burdwan, West Bengal. Asian J. water Environ. and Poll., Vol 7(3): 69-75. [19] Datta, N.C., Bandyopadhya, B.K., Mujumdar, A. and Ahuja, D. 1988. Hydrological profile of Hooghly sector (Bally to Bandel) of river Ganga (in: R.K. Trivedi Ed.). Ecol. and Poll. India. rivers: 133-129. [20] Entrekin, S.A., Wallace, J.B. and Eggert, S.L. 2007. The response of Chironomidae (Diptera) to a long-term exclusion of terrestrial organic matter. Hydrobiologia, vol. 575: 401-413. [21] Epler, J.H. 2001. Identification manual for the larval Chironomidae (Diptera) of North and South Carolina. NC Dept. Environ. Nat. Res., Raleigh, NC: 526. [22] Freimuth, P. and Bass, D. 1994. Physicochemical Conditions and Larval Chironomidae (Diptera) of an Urban Pond. Proc. Okla. Acad. Sci., 74: 11-16. [23] Galdean N., Callisto M., Barbosa FAR.. 2000. Lotic ecosystems of Serra do Cipo, Southeast Brazil: water quality and a tentative classification based on the benthic macroinvertebrate community. Aquat. Ecosys. Hlth. and Manage., 66: 545-552.

196

Debolina Kar et al

[24] Gerhardt A. and Bisthovan J.de 1995. Behavioural developmentand morphological response of Chironomus thummi larvae (Diptera: Chironomidae) to aquatic pollution. J. Aquat. Eco. Hlth., 4: 205-214. [25] Govindasamy, C., Kannan, L. and Azariah, J. 2000. Seasonal variation in physico-chemical properties and primary production in the coastal water biotopes of Coromandel Coast, India. J. Environ. Biol., 21(1): 1-7. [26] Harikantra, S.N. and Parulekar, A.H. 1989. Population distribution of Meiofauna in relation to some environmental features in a sandy intertidal region of Goa, West cost of India. Indian J. Mar. Sci., 18: 259-264. [27] Helson, J.E., Williams, D.D. and Turner, D. 2006. Larval Chironomidae community organization in four tropical rivers: human impacts and longitudinal zonation. Hydrobiol., vol. 559: 413-431. [28] Higuti, J., Zviejkovski, I.P., Takahashi, M.A. and Dias, V.G. 2005.Chironomidae indicadora de estado trófico em reservatórios. In: Rodrigues, L., Thomaz, S.M., Agostinho, A.A. and Gomes, L.C. (eds). Biocenoses em reservatórios: Padrões espaciais e temporais. São Carlos: Rima: 137-145. [29] Jain, S.M., Sharma, M. and Thakur, R. 1996. Seasonal variations in physicochemical parameters of Halali reservoir of Vidisha district, India. J. Ecobiol., 8: 181-188. [30] Jayaraman, P.R., Ganga Devi, T.T. and Vasudevan N. 2003. Water quality studies on Karamana River, Thiruvananthapuram district, South Kerala, India. Poll. Res., 22 (1): 89-100. [31] Johnson R. K. 1995. The indicator concept in freshwater biomonitoring. In: Cranston P. S. (ed) Chironomids form Gene to Ecosystem, Csiro Canberra: 1127. [32] Joseph, P.V. and Jacob, C. 2010. Physicochemical Characteristics of Pennar River, A Fresh Water Wetland in Kerala, India. E-J. Chem., 7(4): 1266-1273. [33] Kawaii K., Yamaagishm T., Kuba Y., and Konishi K. 1989. Usafulness of Chironomid larvae as indicator of water quality. Jpn. J. Sanit. Zool. 40: 269283. [34] Kinne, O. 1971. In: Marine Ecology, Vol. I (Ed. O. Kinne), Wiley Interscience, London: 821. [35] Kinnear, P. R. and Gray, C. D. 2000. SPSS for Windowsmade simple.Release 10. Sussex, UK: Psychology Press. [36] Kırgız, T. 1988. A preliminary study on Chironomidae Larvae in Lake Gala (in Turkish). IX. National Biology Congress, Cumhuriyet Univ., Fen Edebiyat Faculty, Biology Department, Sivas: 11. [37] Koshy, M. and Nayar T.V. 2000. Water quality of river Pamba at Kozhencherry. Poll. Res., 19(4): 665-668. [38] Kulshrestha, S. K., George, M. P., Saxena, R., Johri, M. and Shrivastava, M. 1992. Seasonal variations in the limnochemical characteristics of Mansarovar reservoir of Bhopal. In Aquatic Ecology (Mishra S. R. and Saksena D. N. Eds.), Ashish Publishing House, New Delhi: 275-292.


197

[39] Lim R.P. 1990. Effects of pesticides on the aquatic invertebrate community in rice fields. In: Proceedings of the International Conference on Tropical Biodiversity. In Harmony with Nature, 12-16 June 1990, Kuala Lumpur, Malaysia: 336-352. [40] Lindergaard, C. 1995. Classification of water-bodies and pollution. In: Armitage, P., Cranston, P.S. and Pinder, LCV. (eds). The Chironomidae: biolgy and ecology of non-biting midges. London: Chapman and Hall: 385-404. [41] Maasri, A., Fayolle, S., Gandouin, E., Garnier, R. and Franquet, E. 2008. Epilithic chironomid larvae and water enrichment: is larval distribution explained by epilithon quantity or quality? J. N. Am. Benthol. Soc., 27(1): 38– 51. [42] Mahadavan and Krishnaswami 1983 Self purification capacity of river Vaigai (S. India). India. J. Environ. Hlth., 25 (A): 288-299. [43] Manly, B. F. J. 1994. Multivariate statistical methods: A primer II ed. London, UK: Chapman and Hall. [44] Mathew and Koshy 2005. A comparative study of the lotic and lentic systems of Mavelikara Taluk in Kerala. Poll. Res., 24 (4): 809-814. [45] Mathew and Vergis 1995. Hydrological study of river Narmada with special reference to phytoplankton and periphyton Ph.D. thesis. H.G.S. Sagar, University, Madhya Pradesh. [46] Nair, K. V. K. and Ganapati, S. 1983. Baseline ecology of Edaiyur Sadras estuarine system at Kakapakkam Part I General hydrographic and chemical feature. Mahasagar Bull. Nat. Inst. Oceangr, 16(2): 143-151. [47] Oliver, D.R. 1971. Life history of the Chironomidae. Ann. Rev. Ent., vol. 12: 211-230. [48] Paramasivam, S. and Kannan, L. 2005. Physico-chemical characteristics of Muthupettai mangrove environment, Southeast coast of India. Int. J. Ecol. Environ. Sci., 31: 273-278. [49] Paul, S. And Nandi S.C. 2003. Studies on intertidal macrozoobenthos of Hugli river in and around Calcutta in relation to water and soil conditions. Iii, , 18 figs, 20 tables, 2pls paperbound (Zool. Surv. India) HM 16076 € 12: 135. [50] Prasanna, M. B. and Ranjan, P.C. 2010. Physico chemical properties of water collected from Dhamra estuary. Int. J. Environ. Sci., Volume 1, No 3: 334-342. [51] Rajaram, R., Srinivasan M. and Rajasegar M. 2005. Seasonal distribution of physico-chemical parameters in effluent discharge area of Uppanar estuary, Cuddalore, South-east coast of India. J. Environ. Biol., 26: 291-297. [52] Rajasegar, M. 2003. Physico-chemical characteristics of the Vellar estuary in relation to shrimp farming. J. Environ. Biol., 24: 95-101. [53] Real, M., Rieradevall, M. and Prat, N. 2000. Chironomus species (Diptera: Chironomidae) in the profundal benthos of Spanish reservoirs and lakes: factors affecting distribution patterns. Freshw. Biol., vol. 43, no. 1: 1-18. [54] Ruse L. P. and Wilson R. S. 1984. The monitoring of river quality in the great Quse basin using Chironomid Exuvial analysis technique. Water Poll. Contrl. 83: 116-136.

198

Debolina Kar et al

[55] Saether O. A. 1979. Chironomid communities as water quality indicator. Holoarct. Ecol. 2: 66-74. [56] Saether O.A. 1980. The influence of eutrophication on deep lake benthic invertebrate communities. Prog. Wat. Tech. 12: 161-180. [57] Saha, L. C. and Pandit, B. 1986. Comparative limnology of Bhagalpurponds. Comp. Phyiol. Ecol., 1(14): 213-216. [58] Sampathkumar, P. and Kannan, L. 1998. Seasonal variations in physicochemical characteristics in the Tranquebar - Nagapattinam Region, Southeast coast of India. Poll. Res., 17 (4): 397 - 402. [59] Saravanakumar, A., Rajkumar, M., Serebiah J. S. and Thivakaran, G.A. 2008. Seasonal variations in physico-chemical characteristics of water, sediment and soil texture in arid zone mangroves of Kachchh-Gujarat. J. Environ. Biol., 29: 725-732. [60] Sharma, D. and Jain, R. 2000. Physic Chemical Analysis of Gopalpura Tank of Guna District (M. P.). Ecol. Env. And Cons., 6(4): 441-445. [61] Shrestha, S. and Kazama. F., 2007. Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin Japan. Environ. Model. Software, 22 (4): 464-475. [62] Sridhar, R., Thangaradjou, T., Kumar, S. S. and Kannan, L. 2006. Water quality and phytoplankton characteristics in the Palk Bay, southeast coast of India. J. Environ. Biol., 27, 561-566. [63] Tepe, Y., Türkmen, A., Mutlu, E. and Ate, A. 2005. Some Physicochemical Characteristics of Yarseli Lake, Hatay, Turkey. Tur. J. Fisheries and Aqua. Sci. 5: 35- 42. [64] Thresh, J. C., Suckling, E. V. and Beale J. P. 1944. The examination of water supplies. Ed. E. W. Taylor. [65] Tiwari, S., Dixit, S. and Gupta, S.K. 2004. An evaluation of various physicochemical parameters in surface waters of Shahpura Lake, Bhopal. Poll. Res., 23 (4): 829- 832. [66] Tripathi, A. K. and Pandey S. N. 1990. Water pollution. Ashish Publishing House, New Delhi. [67] Venkateswarju, V. 1969. An ecological study of the algae of river moosi, Hyderabad (India) with special reference to water pollution-1 physico-chemical complexes. Hydrobiol. 33: 117-143. [68] Warwick W.F. 1988. Morphological deformities in Chironomidae (Diptera) larvae as bioindicators of toxic stress. in: M.S. Evans (ed.). Toxic contaminants and ecosystem Health. A Great Lake focus. Wiley and Sons, New York: 281320. [69] Wu, J., Fu, C., Liang, Y. and Chen, J. 2004. Distribution of the meiofaunal community in a eutrophic lake of China. Arch. Hydrobiol., vol. 159, no. 4: 555575. [70] Zar J.H. 1999. Biostatistical analysis. The Edn. Prentice Hall, Englewood Cliffs, New Jersey, USA. [71] Zingade, M.D.1981.Base line water quality of river Narmada (Gujrat), India. J Mar. Sci., 1:161.