Analysis On Water Quality Of Damodar River Biology Essay

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Water is the most vital natural resource for the existence of all living organisms in this Globe. But, this valued resource is increasingly become vulnerable due to human population growth and its demand for more water of high quality and economic activities. As a whole water is being using for a wide variety of purposes starting from domestic, industrial, agricultural, asthetics etc. To find out its accurate quality has become too much important now a days. This paper assesses water quality of Damodar river by employing Canadian Council of Ministers of Environment water quality index (CCME WQI) which provides a convenient mean to summarize a large amount of complex water quality data into a single term for reporting to the management, planners. The CCME Index incorporates three elements: scope - the number of variables not meeting water quality objectives; frequency - the number of times these objectives are not met; and amplitude - the amount by which the objectives are not met. This index produces a value in between 0 (worst) to 100 (best) to reflect water quality. In this paper the concept of WQI is applied for eight selected locations of Damodar river designated with D1- D8. Twenty water quality parameters such as pH, TDS, TSS, Conductivity, Turbidity, Dissolved oxygen, COD, BOD, Chloride, Fluoride, Chromium, Alkalinity, Total Hardness, Ca Hardness, Mg Hardness, Oil & Grease, Total Coliform are determined for the season of Summer, Mon-soon and Winter. WQI for all of these eight locations are evaluated.

Key Words : CCME, WQI, Scope, Frequency, Amplitude, TDS, TSS, BOD, COD.

Introduction

Rivers are large, natural stream of water emptying its content ultimately into an another water body may be a stream, lake or ocean usually associated by some additional tributaries. Rivers are vital carriers of water and nutrients to areas all around the earth (Wetzel, 2001).The main sources of water in a river are precipitation, groundwater recharge, release of stored water from natural reservoirs such as glaciers. Anthropogenic activities and natural processes degrade surface water and impair their use for drinking, industrial, agricultural, recreational and other purposes (Carpenter et al 1998 & Jervie et al 1998). Riverine water has gained its importance over the years as it is being useful for human as well as plant, animal and other aquatic kingdom. Traditionally, river water quality has been assessed by comparing the values with the local norms. However, this technique does not provide any information on the spatial and temporal trends of the overall quality (Debels et al. 2005). Thus, modern techniques such as water quality indices (WQI) and water quality modelling were developed. A number of indices have been developed to summarize water quality data in an easily expressible and easily understood format . The WQI which was first developed by Horton in the early 1970s is basically a mathematical means of calculating a single value from multiple test results. The index result represents the level of water quality in a given water basin, such as lake, river or stream. After Horton a number of workers all over the world developed WQI based on rating of different water quality parameters. WQI is a mathematical tool which has the ability to provide a single number for the large quantities of water quality data in a comprehensive manner. Therefore, it is a simple tool for decision makers on the quality and possible uses of a given water body (Bordalo et al. 2001; Cude 2001; Kannel et al. 2007) [7-10].

In the present study Canadian Council of Ministers of Environment water quality index (CCME WQI) was incorporated which is a well-accepted and universally applicable computer model for evaluating the water quality index (Canadian Council of Ministers of the Environment (CCME) 2001; Cash et al. 2001; Husain 2001; Lumb et al.2002, 2006; Sharma 2002; Khan et al. 2003; Paterson et al. 2003). In this study water was collected from different locations of Damodar river mainly the downstream part of Durgapur city towards Panagarh region in West Bengal during three consecutive seasons namely summer, mon-soon and winter. Water from this river generally meets the basic need of local inhabitants living beside the river basin. The river originates from Chandwa village of the Chota Nagpur Plateau in Jharkhand state in eastern India and flows towards the states of Jharkhand and West Bengal (almost 592 km) to the estaury of the Hooghly River. The Damodar has a Number of tributaries and sub-tributaries such as Barakar, Konar, Haharo Khadia etc. This river is mainly used for agricultural, industrial and domestic purposes. Durgapur which is situated at the Damodar river basin is greatly influenced with several large and small scale industries mainly steel, chemical, cement etc. The wash out from these industries ultimately meets the Damodar river at majher-mana village. The concept of WQI is based on the comparison of the water quality parameter with respective regulatory standards. The number of variables with exceedances (failed test), frequency of exceedances, and magnitude of exceedances of regulatory standards for specific parameters (variables) are reflected in WQIs [5].

Materials and Methods

The objective of this study was an assessment of the water quality of Damodar river specially the downstream part of Durgapur city towards Panagarh which are of domestic and industrial importance. This was conducted for consecutive three seasons namely summer, Mon-soon and winter. Twenty different parameters were considered to compute WQI. Samples were collected from eight different locations along the river which were apart from each other at specified distances. Summer sampling was been done in the month of march, whereas Monsoon sampling was been done in the month of august and winter sampling was done in the month of December, 2012.

Figure 1 : River DAMODAR showing sampling stations

In the past several researchers had done a lot of work to find out a suitable WQI method. The innovation in the field of WQI was first proposed by Scientist Horton. Brown et al. made the first attempt to derive a suitable WQI. DELPHI process provides an unique method to assess quality of water at different conditions and different point of time and also detect the progress of water pollution.

Canadian Council of ministry of Environment also provides a methodology which facilitate to detect WQI of surface water by allowing a considerable number of parameters. The basic attempt is collection of samples from different locations during three consecutive seasons namely summer, mon-soon and winter followed by characterization of samples by means of observing selected parameters.

The parameters, water temperature, pH, total dissolved solids (TDS) and electrical conductivity (EC) were analysed immediately at the sampling site using standard equipment (Merck Water Analysis Kit). Determination of parameters like DO, BOD, COD, Sulphate, Phosphate, Nitrate, Chloride, Total Hardness, Ca Hardness, Chromium, Total coliform bacetria are done using standard procedures.[2-4].

After characterization of all parameters during three seasons the observations are compared to respective site specific objectives given by CPCB or Indian standards [11-12]. Consequently F1, F2 and F3 values are determined for each of sampling location by CCME WQI computational methodology.

Computational Method:

This was been directly adopted from CCME ( Canadian Council of Ministry of Environment Index).Components of WQI are as follows :

Factor 1: Scope ; How many are not meeting their objectives

F1 = (Number of Failed Variables) / (Total no. of Variables) *100

where variables indicate those water quality parameters with objectives which were tested during time period for the index calculation.

Factor 2 : Frequency; How many times are not meeting their objectives

F2 = (number of failed tests) / (total number of tests) *100

F2 (Frequency) represents the percentage of individual tests that do not meet the objectives ('failed tests').

Factor 3: Amplitude; How far it is deviated from objectives

F3 (Amplitude) represents the amount by which the failed test values do not meet their objectives, and is calculated in three steps ;

When the number of times by which individual concentration is greater than the objective, it is termed as 'excursion' and is expressed as follows,

Excursion= (Failed test value / Objective) - 1

The collective amount by which individual tests are out of compliance is calculated by summing the excursions of individual tests from their objectives and dividing by the total number of tests. This variable, referred as the normalized sum excursions, or nse, is calculated as:

n

Nse = ∑ Excursion / no. of Tests.

i=1

F3 =(nse) / (0.01nse+0.01)

WQI =100 - √ (F12+F22+F32) / 1.732 (http://www.ec.gc.ca)

Interpretation of WQI for each location, Values are compared with interpretation table

WQI Value

Interpretation

95-100

Excellent

80-94

Good

65-79

Fair

45-64

Marginal

0-44

Poor

Result and Discussion

The physico-chemical parameters have shown temporal and spatial variations over the year for the present study. The seasonal variations of the physico-chemical analysis for few selected parameters are represented in Table 1. The WQI was calculated using the data of samples collected during summer, monsoon and winter season in the year of 2012. The calculated values of WQI is presented in Table 3, after calculating F1,F2 and F3 for all of Eight locations.

Table:1 Seasonal variation of parameters for sampling stations

location

pH

TDS

Conductivity

Turbidity

DO

BOD

T.H

Chloride

Fluoride

Chromium

Coliform

D1

7.4-8.1

68.7-152

136.9-290

13.97-78.2

5.3-9.2

2.6-5.1

112-145

25.6-35.8

0.5-0.8

0-0.07

14-34

D2

7.6-8.3

98.6-161

197.3-320

1.48-7.84

5.3-7.7

2.0-2.2

115-136

23.0-30.2

0.4-0.7

0-0.01

8-17

D3

7.3-8.1

84.9-149

169.9-223.3

5.23-25.8

6.4-7.2

3.2-4.7

100-180

17.9-29.9

0.3-0.6

0-0.04

17-22

D4

7.5-8.7

80.8-161

177.1-330

1.34-17.76

6-10.8

0.67-5

130-148

28.2-32.3

0.2-0.5

0-0.02

2-18

D5

7.5-8.7

63.8-140

127.1-247

1.7-48.6

5.3-11.2

2.0-5.6

115-144

15.3-15.9

0.5-0.8

0.01-0.17

6-28

D6

7.5-8.5

48.9-135

99-259

2.05-74.9

4.6-12

.67-5.2

110-132

13.9-17.9

0.5-0.8

0.01-0.05

6-17

D7

8.2-10

70.2-215

157.2-244

1.05-42.1

7.3-14

.67-4.0

60-145

13.9-19.9

0.5-0.9

0-0.06

4-34

D8

7.7-9

98.3-277

213.3-554

374-475

2.0-4.8

2.0-4.0

155-180

48.7-101

1.8-1.1

0.03-0.53

50-70

The values for several parameters have shown that there is a definite fluctuation from one place to another as well as the variations for different parameters have been noticed from one season to another. pH is an important parameter in order to detect the quality of water in terms of acidic or alkaline. It was found that the pH value remained within neutral to alkaline or slightly alkaline range throughout the year. A special notice can be given to the spot located with D7 due to its highest pH value compare to other locations. Total dissolved solids denote mainly the various kinds of minerals present in water. In present study it was found that TDS was maximum for the last location which was a discriminate value for all of three seasons. The observation of Fritsch (1931) and Rao (1971) who consider that Alkaline water have more total solids than acidic water holds true for present study also as such TSS value for each location has found persistently below considerable limit. EC is actually a measure of the ionic activity of a solution in term of its capacity to transmit current. A change in conductivity denotes the change in composition of water, leads to the change in treatment if it is required. Seasonal and location wise variation was observed for conductivity with a maximum of 554 µs for the D8 location in the season of summer. Turbidity reflects the cloudy nature of water. In the season of summer Turbidity value for D1 and D8 location were observed as 14.23 and 374 NTU respectively, which exceeded the permissible limit. In the season of Mon-soon, it was found out that apart from D2 and D4, every location crossed permissible limit of Turbidity. In the season of winter turbidity has exceeded for D1, D4, D8 locations.DO is an important input to compute WQI. It is an important indicator to support aquatic life. High chloride level leads to decrease DO level. The decrease in DO level also indicated with the increase in BOD level. A huge amount of organic waste when added into the river augments the microbial activity of the aquatic system resulting in the escalation of BOD and depletion of DO. Throughout in the season of summer it was observed that DO level was within the comfort level to support aquatic life apart from the last location with DO value of 2 mg/l. The temperature of hot effluents from thermal plants entering the river must be controlled by spray, cascading, etc., as it reduces DO levels by increasing the microbial activity. In the Mon-soon it was found that DO level for most of the location remained below the permissible limit, this may be due to increase in sewage contamination at different stations. This statement is also true for winter season, apart from last location the DO value remains below permissible limit. Along with DO and Turbidity Chromium concentration also contributed greatly to find out WQI. For few locations concentration of chromium has diverted copiously from its permissible value of 0.05 mg/l. This observation was watched out for all three consecutive seasons. This clumsy finding of chromium is due to the activity of few surrounding tannery industry. The concentration of sulphate, phosphate, nitrate, Total Hardness, Alkalinity remained within their permissible limit consistently for all of the three seasons. Fluoride which is also an important one to detect in terms of its ability to cause dangerous human disease such as fluorosis was within its permissible value of 1.5 mg/l for all of sampling stations. Only a fluctuation was observed in the season of summer for last location with an alarming fluoride level of 1.82 mg/l. It was found in all of three seasons that, apart from the last point

Table 2: Concentration of Chromium in Damodar river in mon-soon

the load of total coliform bacteria for remaining locations were within its permissible value of 50 MPN/100 ml. Though seasonal wise there was a discrete change in the no. of coliform bacteria for each of particular location. In the season of summer and Mon-soon and winter the no of coliform bacteria for last location was observed 70 and 50 and 55 MPN/100 ml respectively. This is due to the mixing of industrial wash out and addition of sewage contamination with this location which ultimately create a healthy condition for the microorganism to live.

The WQI values are given in Table 3. The results showed that except D5 and D8, all the WQI values were Good to Excellent in CCME WQI method. The D8 location which is influenced with Tamla nallah carried more effluents into the river showed a poor WQI value of 25.14. The pollutants from local sources were also carried down more and as a result the WQI value for D5 was comes under a fair value of 79. As the pollutant parameters increased the WQI value decreased and vice-verca.

Table: 3 WQI for all Location of river Damodar

Location

F12

F22

F32

WQI

D1

225

100

141.37

87.53

D2

25

2.755

0.009

94.73

D3

25

2.755

6.421

94.15

D4

25

11.08

1.643

93.85

D5

225

69.38

138.53

79.19

D6

100

44.35

103.83

84.24

D7

100

44.35

30.91

86.76

D8

225

469.15

4909.80

25.14

Conclusion:

The present study conclude the importance of implementing a water quality index that reflects the total influence of several possible reasons responsible for water pollution of any river body and allows interpretation of data from monitoring. Monitoring showed that different effluent from industries and sewage from municipal discharge affect water quality. The WQI of most of the locations indicate an acceptable level of quality for domestic use by the inhabitants followed by a mild treatment. It was also found that water quality was influenced by climatic conditions. In winter season water quality was found better than that of summer and monsoon. Water quality analysis revealed that the extreme location of Damodar river water is getting polluted from various sources like domestic sewage (due to the high population) or industrial effluents and garbage disposal or by other anthropogenic activity. A continuous monitoring is under expectation and a matter of concern as well as.

Acknowledgement

I am thankful to Mr. Sagnik Chakraborty, Research scholar, NIT Durgapur for his valuable help and suggestions regarding water sampling.

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