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Agricultural Science Digest, volume 43 issue 3 (june 2023) : 327-333

Studies on Seasonal Variation of Water Quality Parameters of River Mara Bharali in Sonitpur District of Assam

A. Das1,*, S.P. Biswas2
1Darrang College, Tezpur-784 001, Assam, India.
2Department of Life Sciences, Dibrugarh University, Dibrugarh-786 004, Assam, India.
Cite article:- Das A., Biswas S.P. (2023). Studies on Seasonal Variation of Water Quality Parameters of River Mara Bharali in Sonitpur District of Assam . Agricultural Science Digest. 43(3): 327-333. doi: 10.18805/ag.D-5706.

ABSTRACT

Background: Freshwater is not only a finite resource but also essential for agriculture, industry and even human existence. The present investigation on seasonal water quality parameters was conducted in the remnants of old channel of river Jia Bharali called as Mara Bharali at Tezpur in the Sonitpur district of Assam from December, 2017 to November, 2020.
 
Methods: Five sampling stations were selected that covers a stretch of 16.5 km. Physico-chemical parameters were determined seasonally by following the standard methods of APHA (1998) and Trivedy et al., 1987. The statistical analyses of the data were done by one way ANOVA using Statistical Package for Social Scientists.

Result: TDS in monsoon in all the locations remained lowest (171.33a±3.059 mg/L at MB2) and highest in winter (320.11c±2.441 mg/L at MB3). The pH value is within the permissible limit except for site MB4 during the winter and post monsoon when the values were 6.38±0.146 and 6.44±0.039 respectively. Maximum DO of 7.878d±0.074 mg/L was observed at site MB1 during the winter season and minimum DO of 5.444a±0.047 mg/L was observed at site MB4 during the monsoon season. BOD was recorded below the tolerance limit of 3 mg/L in all sampling stations.

INTRODUCTION

Rivers are considered as the pillars of human civilization all over the world. The presence of irrigated agriculture, towns, cities and industrial sites along the river bank shows the inextricable dependence of human races on riverine ecosystem. Tropical floodplains play a significant role in providing highly productive ecosystem services (Pettit et al., 2011), vital to a range of ecosystem processes (Hamilton 2002). The deteriorating water quality affects man, animals and plant life with far-reaching consequences. In India, due to tremendous urbanization and industrialization, the problem of water pollution has assumed an alarming situation and about 70% of rivers in India are polluted. In the last few decades, there has been increasingly greater emphasis on the deterioration of water quality of Indian rivers (Jindal and Sharma, 2011; Matta et al., 2020). The destruction of natural habitats and the presence of environmental pollutants may affect the ecological balance of every ecosystem (Begon et al., 2009). Dwivedi and Pandey (2002) reported that industrial waste water, sewage and municipal wastes are being continuously added to water which affect the physicochemical quality of water and also making them unfit for even use of livestock and other organisms. All these impurities result in degradation of water quality, like bad taste, colour, odour, turbidity, hardness, corrosiveness, staining and frothing (Saha et al., 2017).
 

MATERIALS AND METHODS

Description of study area
 
The present investigation was conducted in the remnants of old channel of Jia Bharali called as Mara Bharali at Tezpur in the Sonitpur district of Assam during the period from December, 2017 to November, 2020. The 05 sampling stations were demarcated as MB1 (Pumpani village, N-26°45'10.52"and E-92°50'07.93"), MB2 (Amlopam village, N-26°41'16.84" and E-92°48'58.88"), MB3 (Dolabari village, N-26°40'00.65" and E-92°49'43.64"), MB4 (Porowa Bridge, N-26°39'10.05" and E-92°47'49.28") and MB5 (Maithan, N-26°37'05.69" and E-92°49'34.34") that covers a stretch of about 16.5 km (Fig 1).

Fig 1: Present courses of river Jia Bharali and the Mara Bharali.


 
Collection of water samples for analysis of  physicochemical  parameters
 
The samples were collected in plastic container from a depth of 5-10 cm below the surface water at each sampling sites. The physicochemical characteristics of water like temperature, pH, transparency, conductivity, dissolved oxygen (DO), biochemical oxygen demand (BOD), total dissolved solids (TDS), total alkalinity, total hardness and calcium were determined seasonally by following the standard methods of APHA, (1998) and Trivedy et al., 1987. Temperature, pH, transparency, conductivity, DO of the water were measured at their collection sites. Temperature was recorded with the help of mercury thermometer, pH was recorded by hand pH meter, water transparency was measured by using black and white disc (Secchi disc), conductivity was measured by using hand conductivity meter (EC TESTER) and DO was measured by following Winkler’s iodometric method. For the measurement of other physicochemical parameters, water samples were collected in plastic sampling bottles and transported to the laboratory. All the water samples were collected on a monthly basis and analyzed.

The data obtained for four different seasons in a year were calculated as mean values of the whole three years of the study period. Comparison was done between the values obtained in different seasons. The significance were recorded at 1% (p<0.01) and 5% (P<0.05) level. The statistical analyses of the data were done by one way ANOVA using Statistical Package for Social Scientists (SPSS) Windows version 20.0.

RESULTS AND DISCUSSION

Seasonal fluctuations in the values of various physicochemical parameters at different stations are given in Table 1 and 2.

Table 1: Seasonally evaluated physical parameters of river Mara Bharali.



Table 2: Seasonally evaluated chemical parameters of river Mara Bharali.



Air temperature at five different locations of Mara Bharali river were recorded in four different seasons of the year. At location MB1, the air temperature was significantly higher (p<0.01) in monsoon (31.08c±0.432) followed by post monsoon (28.44b±1.022) and pre monsoon (27.00b±0.589) and lowest in winter season (20.23a±0.934). Similar pattern of temperature variations were observed in other locations that is, MB2, MB3, MB4 and MB5 (Table 1).

The water temperature of any river does not remain the same due to environmental conditions (Kumari et al., 2013). During the entire study period, water temperature remained lowest in winter (14.23a±0.745°C at MB3) and highest in monsoon (27.11c±0.613°C at MB5). Similar seasonal fluctuation of temperature was also recorded in all the other sampling sites. No significant differences were observed between pre monsoon and post monsoon temperatures in all the locations. The differences are statistically highly significant (p<0.01).

Dokulil et al., (2006) reported that water transparency is not only a crucial parameter of river optics but also one of the important indexes of eutrophication evaluation of a river system. The transparency of water was highest in post monsoon season (40.44c±1.629 cm at MB2) in all the locations and the differences are statistically highly significant (p<0.01). The post monsoon value was followed by pre monsoon values in all the cases. Differences between monsoon and winter transparency values remained non significant in all the cases except in location MB3.

Conductivity is a measure of the ability of an aqueous solution to carry an electric current. Electrical conductivity is found to be good indicator of water quality (Gaikwad et al., 2008). Electrical conductivity in monsoon was recorded lowest (94.00a±2.906 µs/cm at MB2) and in winter it was highest in all the locations of the river (191.56c±4.553 µs/cm at MB4). Electrical conductivity was recorded below the WHO standards of 1400 µs/cm during all seasons (Fig 2). The differences were statistically highly significant (p<0.01).

Fig 2: Seasonal fluctuation of conductivity (µs/cm) at the sampling sites of R. Mara Bharali.



Total dissolved solids (TDS) is an important parameter in determining the water quality standards (Jayakumar et al., 2009). TDS was maximum during summer and minimum during monsoon (Narayan et al., 2007; Jacklin Jemi and Regini Balasingh, 2011). In the present investigation also, TDS in monsoon in all the locations remained lowest (171.33a±3.059 mg/L at MB2) and highest in winter (320.11c±2.441 mg/L at MB3) and pre monsoon seasons followed by post monsoon season. TDS was found below the ISI standard of 500 mg/L in all seasons (Fig 3). The differences are statistically highly significant (p<0.01).

Fig 3: Seasonal fluctuation of TDS at the sampling sites of R. Mara Bharali.



Water turbidity remained highest in monsoon (49.65b±0.294 NTU at MB5) at all locations except in MB5 where a non significant higher mean value is recorded in comparison to the monsoon value. The differences in all other cases were highly significant (p<0.01). Water turbidity was recorded lowest in the winter season (22.32a±0.439 NTU at MB3) at all sampling sites. Matta et al., 2020 working on the Ganga river system has obtained similar results.

pH is an important parameter which helps to determine the acid-base balance of river water (Bhalla and Waykar 2012). Moreover, pH is also positively correlated with electrical conductance and total alkalinity (Gupta et al., 2009). In the present investigation, pH value at all the locations in post-monsoon season was recorded lowest except in MB4. Significant differences in seasonal values were recorded in all locations except in MB4. At location MB1, pre-monsoon value was recorded highest (7.22c±0.054), followed by monsoon (7.06b±0.038), winter and post monsoon (p<0.01). At location MB2, pH was recorded highest in winter (7.31c±0.039) followed by pre monsoon, monsoon and post monsoon (p<0.01). In MB3, it was highest in pre monsoon (7.11b±0.073) and all other seasons have almost similar mean values (p<0.05). In MB5, the mean value in pre monsoon and winter was high followed by monsoon and post monsoon (Table 2; Fig 4). The differences were statistically highly significant (p<0.01). The pH value was within the permissible limit except for site MB4 during the winter and post monsoon when the values were 6.38±0.146 and 6.44±0.039 respectively (ISI permissible limit being 6.5-8.5).

Fig 4: Seasonal fluctuation of pH at the sampling sites of R. Mara Bharali.



Dissolved oxygen (DO) is an indicating parameter of water quality. Dissolved oxygen varies or changes with many factors including water flow rate, depth, temperature and time of the day (Tyagi et al., 2013). In natural water, the maximum DO concentration is highest at 0°Cand decreases with an increase in temperature (Mia et al., 2017). During the study, maximum DO of 7.878d±0.074 mg/L was observed at site MB1 during the winter season and minimum DO of 5.444a±0.047 mg/L was observed at site MB4 during the monsoon season. The differences were statistically highly significant (p<0.01). DO was found to be above the tolerance limit of 4 mg/L at all sampling stations during all seasons of the study period (Fig 5).

Fig 5: Seasonal fluctuation of DO (mg/L) at the sampling sites of R. Mara Bharali.



Relatively higher values of free CO2 were observed during pre-monsoon season (28.61c±0.597 mg/L at MB4). The results of the present findings are in conformity with the finding of Nath and Srivastava (2001) and Gurumayum et al., (2002) who also have reported higher values of free CO2 during pre monsoon season (28.61c±0.597 mg/L). Moreover, low values of free CO2 was recorded in monsoon season (11.86a±0.267 mg/L at MB5) which complies with the findings of Das et al., (2003) who reported low values of free CO2 during monsoon in river Brahmaputra. CO2 concentration significantly varied (p<0.01) among all the seasons at all the locations, where pre monsoon CO2 concentration was recorded highest and monsoon was the lowest in all the cases (Fig 6).

Fig 6: Seasonal fluctuation of free CO2 (mg/L) at the sampling sites of R. Mara Bharali.



Biochemical oxygen demand (BOD) is an essential parameter, which shows the quantity of consumed oxygen in biochemical decomposition of organic matter present in water. DO and BOD are inversely proportional to each other. This is because bacteria will consume oxygen while decomposing the available BOD (Sawyer et al., 2003). In the present investigation, BOD in winter remained significantly low (p<0.01) in all the locations (0.766a±0.024 mg/L at MB2) and recorded highest at MB3 during the monsoon season (2.838b±0.022). However, in all the sampling stations BOD was recorded below the tolerance limit of 3 mg/L during all seasons of the study period (Fig 7). No significant differences were recorded between pre monsoon, monsoon and post monsoon seasons at all the locations except MB5 where monsoon and post monsoon values remained significantly (p<0.01) higher than pre monsoon value. The differences were statistically highly significant (p<0.01).

Fig 7: Seasonal fluctuation of BOD (mg/L) at the sampling sites of R. Mara Bharali.



The alkalinity was found to be maximum in the pre-monsoon (146.33c±1.616 mg/L at MB1) and post monsoon season (132.44b±3.096 at MB1) whereas total alkalinity in monsoon and winter remained significantly low at 99.44a±2.328 mg/L (site MB4) and 99.89a±2.452 mg/L (site MB4) respectively (p<0.01). The major constituents of alkalinity in water are carbonates, bicarbonates and hydroxides which come from salts or sediments and dissolved rocks (Trivedy and Goel, 1986).

Hardness is an important parameter for detecting water pollution. According to Baruah et al., (1993) and Rao (2001), total hardness of water indicates the water quality in terms of calcium and magnesium only. In the present investigation, variation in total hardness was observed among different seasons. The hardness was highest (p<0.01) in winter and post monsoon at MB1 (43.62b±1.759 mg/L in winter), in winter at 48.13b±2.355 mg/L at MB2 (p<0.01) and non significant in MB3. Hardness was highest in winter (69.12b±1.094 mg/L) and post monsoon (69.34b±0.583 mg/L) and lowest in pre monsoon at MB4 (66.47a±0.459 mg/L) (p<0.05) and highly significant (p<0.01) at MB5 where the post monsoon value is the highest followed by winter, monsoon and pre monsoon. Hardness was obtained much below the permissible limit of 200 mg/L in all sampling stations during the study period.

Calcium level does not vary significantly except in location MB4 where it is found highest in winter (18.56b±0.435) and lowest in monsoon (16.82a±0.466).

CONCLUSION

The study evaluated the water quality of R. Mara Bharali with the assessment of seasonal fluctuation of certain important physicochemical parameters. The study revealed that the water quality of river Mara Bharali exhibited significant seasonal variability throughout the study period. The pH was slightly acidic, TDS was on a higher side during winter, a moderate concentration of dissolved oxygen, fairly high amount of alkalinity and BOD level within the permissible limit. The study showed that the physicochemical parameters of the R. Mara Bharali were within the permissible limit and productive for fisheries.

Conflict of interest

None

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