Water Quality Index and Correlation Study of religious ponds in the temple. city, Bhubaneswar, Odisha.

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1 AMERICAN JOURNAL OF SCIENTIFIC AND INDUSTRIAL RESEARCH 2016,Science Huβ, ISSN: X, doi: /ajsir Water Quality Index and Correlation Study of religious ponds in the temple city, Bhubaneswar, Odisha. Amarendra Harichandan 1, Himansu Sekhar Patra 1*, Kabir Mohan Sethy 2, Saswat Kumar Mohanty 2* and Rabindra Panda 3 1 Researcher in Environmental science, Konark Institute of Science and Technology, BBSR, Odisha, (India) 1*Researcher in Environmental science, Odisha (India) 2 Professor in Geography, Department of Geography, Utkal University,Vanibihar, Bhubaneswar, Odisha, (India) 2* Scientist, State Pollution Control Board, BBSR, Odisha, (India) 3 Gandhi Institute for Technological Advancement, Bhubaneswar, Odisha, (India) harichandan.amarendra@gmail.com,himansupat@gmail.com. ABSTRACT: The present study is focused at assessing the water quality index (WQI) of seven temple ponds of BBSR which includes the 11 parameters: ph, electrical conductivity(ec), total suspended solid(tss), total dissolved solids(tds), chloride(cl - ), total alkalinity(ta), total hardness(th), sulphate(so 2-4 ), dissolve oxygen(do), biochemical oxygen demand(bod) and chemical oxygen demand(cod). This has been determined by collecting pond water samples and its comprehensive physicochemical analysis. The WQI of these samples ranges from to All pond WQI values are above the 200 mark which are specified for bad water quality. The high value of WQI has been found to be mainly from the higher values of EC, BOD and COD in the water. Correlation regression analysis shows a high value of Correlation coefficient (r) and regression coefficient (k) exist between BOD, WQI (r = 0.834, k = 11.18, positive) and between DO, WQI (r = -905, k = , negative). The analysis reveals that the water of this area needs some degree of treatment before consumption, and it also needs to be protected from the perils of contamination. Keywords: Water quality standards, Water quality index, Correlation, Regression study INTRODUCTION Bhubaneswar, the capital of the Indian state of Odisha, formerly known as Orissa. Bhubaneswar, derived its name from Tribhubaneswar, which literally means the Lord (Eeswar) of the Three World (Tribhuban), which refers to Shiva [1]. With many Hindu temples, Bhubaneswar is often referred to as a Temple City of India and together with Puri and Konark it forms the Swarna Tribhuja ("Golden Triangle"); one of eastern India's most visited destinations [2]. The city has more than 1000 remarkable ancient temples [3] those are frequently visited by millions of people throughout the year. The strong beliving nature on god and with a thought of gaining punya, holy dips are taken and poojas performed in temple ponds. But now these ponds have become the source for infectious diseases due to ample of anthropogenic behaviours like throwing of temple wastes by sevayats, 22

2 discharging of waste water through nalas, throwing of wastes from neighbouring people into these ponds. It has seen during the last three decades of the twentieth century that as the population of the world has grown, the concern for water quality has been exceedingly great so that fresh water quality has now acquired as much attention than water quantity [4]. According to the WHO [5], about 80% of all the diseases in human beings are caused by contaminated water. It is used in this apprehension that the WQI and correlation among different water quality parameters (WQP) of seven temple ponds of BBSR has been studied/monitored over a period of one year during 2014 to aware the general people regarding water pollution problem and to communicate the information to Government personnel, non-scientific water executives and the community. This will helpfully lead to efficient water quality improvement programmes. In this regard WQI is optional as a very helpful tool that enables the public and decision makers to evaluate water quality of these holy ponds. Karl Pearson correlation and regression analysis are useful tools for correlating different parameters with WQI which then provide mechanisms for prediction or forecasting of WQI. Study area: Bhubaneswar is located in the Khurda district of the Orissa state between N to N (Fig.1) latitude and E to E longitude on the western fringe of the coastal plain across the main axis of the Eastern Ghats Mountains [6]. The city has an average altitude of 45 m (148 ft) above sea level [6]. It lies southwest of the Mahanadi River that forms the northern boundary of Bhubaneswar metropolitan area, within its delta. The city is bounded by the Daya River to the south and the Kuakhai to the east [6]. Fig 1. Google map of BBSR city Methodology :- The water samples from seven major physico-chemical parameters. The tested 11 temple ponds (Fig.2) Papanasini Kunda(P), physico-chemical parameters are ph, EC, TSS, TDS, Kedargouri temple pond(k), Mausima (M), Cl -, TA, TH, SO 2-4, DO, BOD, COD. The samples Chintamaniswar Pond(C), Devipadahara pond(d), Brahmeswar pond (Br) and Bindusagar pond (Bi) were collected as per the norms of the American Public were collected in sterilized plastic containers during morning hours and are analyzed in the laboratory. The analytical method of these samples follows APHA Health Association (APHA) [7], during three different [7]. The parameters ph, electrical conductivity and seasons of the year 2014 i.e. in monsoon, in summer, dissolved water were monitored at the sampling site in winter and were analysed for 11 23

3 and other parameters were in laboratory as per the standard procedures of APHA(ref). Fig 2. Location of sampling points (seven temple ponds of BBSR) The obtained data from laboratory analysis of collected water samples are used for calculation of WQI (eq-1) and the Karl Pearson Correlation matrix (eq-2) [8] has used to find out the closeness of the relationship between above 11 tested parameters and also that of with calculated WQI. Subsequently regression analysis are also carried out between WQI and 11 physicochemical parameters with the Origin software (origin version 6.1). The obtained regression analysis from origin software is used as a useful information to project the index value of the studied area, if the strongly WQI dependent variables are measured. WQ. I n i 1 q w...( eq.1) i i n = number of parameters. q i = the quality rating of parameters. w i = unit weight of different parameters. q i w i = parameters sub-index. r n i 1 n i ( x ( xi x)( yi y) 1...( eq.2) i x) 2 n i 1 ( yi y) Where, n = number of data points, x = values of x- variable, y = values of y-variable, x = mean of all variables of x, y = mean of all variables of y, r = Pearson Correlation. RESULT AND DISCUSSION The WQI is a dimensionless, useful management tool 2 24

4 in water quality assessment [9],which is used to express various WQP and their dimensions into a single Score [10]. On the other hand the Karl Pearson correlation matrix is calculated for the WQP and also for WQP with WQI, is displayed in Table-1. This correlation provides a mechanism for prediction or forecasting of overall WQI dependent variable of temple ponds of BBSR with known values of independent water parameter of these ponds. A higher index value represents poor water quality (Table-2). The annual averages of the eleven physico-chemical parameters of temple ponds are presented in Table 3 and in Fig 4.a. The WQI of the seven temple ponds viz., P, K, M, C, D, Bi and Br has been established from eleven important physico-chemical parameters during the year 2014 and is shown in Fig-3. From the results (Table-3, Fig 3) it is observed that the WQI value of seven temples ranges from with an average WQI of 280 which is much higher than even the WQI score for poor quality water (Table-2). Result shows that, in temple ponds P (318),Bi (313), M(311) WQI are on higher side. From the present correlation analysis (Table-1) it is clear that the higher values of WQI score result mainly from higher values of the water quality parameters EC, COD, BOD as there exist slightly positive and strongly positive correlation between these WQP and WQI. The correlation between EC and WQI is slightly positive with correlations co-efficient, r = where as another slightly positive correlation is observed between COD and WQI with correlation co-efficient, r = But a strongly positive correlation is found between BOD and WQI with correlation co-efficient, r = The present study shows a highest WQI score of 318 in P temple pond which is obvious as the pond registered a highest BOD value of 15.5 mg/l. Next to it other higher WQI values are found in Bi and M temple ponds where the registered BOD values are 11.2 mg/l and 13.2 mg/l respectively. In the Bi temple pond, higher value of WQI also resulted from slightly positively correlated water quality parameters EC and COD with concentrations of 479 ms/m and 84.2 mg/l, respectively. Correlation Table-3 indicates a strongly negative correlation between WQI and DO water quality parameter with correlation-coefficient, r = This means lower WQI score would be result with higher the DO concentration which has seen in temple ponds K and Br. The lowest WQI score of 240 is observed in K temple pond with a highest DO value of 11.5mg/L. Next to K the temple pond, the lowest WQI score of is found in Br temple pond with a registered DO concentration of 11.3mg/L. Among other parameters the correlation of WQI towards TH and ph is poorly negative (r = ) and positive (r = 0.071), respectively. 25

5 Fig. 3. Water quality index temple ponds comparision to average WQI of BBSR temple ponds. Table-1: Correlation coefficient matrix of WQP and WQI. WQP PH EC TSS TDS CL - TA TH SO4 2- DO BOD COD WQI PH EC TSS TDS CL TA TH SO DO BOD COD WQI 1 Note:- Slightly strong +ve - -ve correlation, r >

6 Table-2. Classification of water quality based on WQI score [14]. WQI Score Water Quality <50 Excellent Good water Poor water Very poor water >300 Water unsuitable for drinking Table-3 WQP, WQI of water samples from BBSR temple ponds in [12] [13] Table-3 Drinking water standards as recommended by recommending agencies Location PH EC TSS TDS Cl - TA TH SO4 2- DO BOD COD WQI Description P Poor K Poor M Poor C Poor D Poor Bi poor Br poor Average Poor Standard Recommended agency ICMR/BIS ICMR WHO ICMR/BIS ICMR/BIS ICMR ICMR/BIS ICMR/BIS ICMR ICMR WHO Note - All values in Table-3 except ph and electrical conductivity are in mg/l, EC in ms/m. 27

7 Table-4. Regression equation of WQI with ph, EC, TSS, TDS, Cl -, TA, TH, SO 2-4, DO, BOD, COD. Regression equation Regression coefficient(k) R 2 Remark WQI = ph Positively correlated WQI = EC Positively correlated WQI = TSS Positively correlated WQI = TDS Positively correlated WQI = CL Positively correlated WQI = TA Negatively correlated WQI = TH Negatively correlated WQI = SO Negatively correlated WQI = DO Negatively correlated WQI = BOD Positively correlated WQI = COD Positively correlated 4. a. 4. b. Fig 4.Water quality parameter and WQI variation in temple pond of BBSR in

8 Fig. 5.a. k. Scatter diagrams showing correlation and regression between WQP and WQI during the year In this present study the linear regression analysis also has been carried out between WQP and WQI by using the Origin software, version-6.1. It was found to have a better level of significance in their correlation coefficient. The greater the value of regression coefficient, the better is the linear fit and the more useful the regression variables [11], which happens in case of the water quality parameter DO, BOD with WQI. The present regression (k = , k = 11.18) analysis tells us regarding the regressors DO and 29

9 BOD are good at predicting the values of WQI, a dependent variables. As these two parameter are strongly regressed with WQI. But the regressors like TSS and EC are not good at predicting the values of WQI, a dependent variables (k = , k = ). Next to BOD the other two regressors are ph and Cl - possess higher value of positive regression coefficients (k = , k = ). The regression equations obtained from the analysis are given in the Table 4. The linear regression models Fig.5.a-k have been obtained from positive and negatively correlated WQP with WQI. A known value of DO or BOD, the WQI can be obtained by substituting an average value for the entire study area. Regression analysis shows a positive linear regression model between WQI with BOD, COD, EC, ph, TSS, TDS, Cl - where as a negative linear regression model between WQI 2- with DO, TH, TA, SO 4 as is shown in Table-4. Conclusions From the present study the obtained WQI values (Fig 3,Table 3) of various temple ponds, it has been observed that the WQI value of different temple ponds are above the 250 score which indicated that an increase in pollution level and water quality is very very poor. This is due to effluent discharge, domestic waste water discharge from neighbouring area, discharges of nalas, urban runoff etc. Thus there by increase in TSS, algal growth, BOD level and decrease in DO level. Hence, application of water quality index technique is a useful tool for the overall assessment of the water quality of water bodies. In the correlation regression study, we can conclude that all the parameters are more or less correlated with WQI. But the influence of DO and BOD with WQI is very high. From the regression analysis, we concluded that the regressors DO and BOD are good at predicting the values of WQI, if values of independent variable DO and BOD are known. Thus correlation regression analysis is very useful to get fairly accurate idea of quality of water by determining a few parameters experimentally. Hence it can be concluded that the regression study of the water quality parameters have a great significance in the study of water resources. REFERENCE 1.Kalia, Ravi (1994). Bhubaneswar: From a Temple Town to a Capital City. SIU Press. p. 3. ISBN Ramesh Prasad Mohapatra, Archaeology in Orissa, Vol I, Page 47, B. R. Publishing Corporation, Delhi, 1986, ISBN Abbasi S. A, Water quality Indices state-of-the art, center for pollution control and energy technology, Pondichery University, World Health Organization, Guidelines for drinking water quality, 3rd Edn., WHO, Geneva, a b c d e f g h i j k l m n o "City Development Plan: Bhubaneswar". JNNURM, Government of India. Retrieved 14 December APHA, Standard methods for the Examination of water and waste water, 19 th Ed., American Public Health Association, Washington DC, U.S.A.. 8.Kreyszig Erwin, Advanced Engineering Mathematics, 8 th edition, 2004,pg.1151, John wiley & Sons (Asia) Pte. Ltd., Singapore. 9.Parmar K., Parmar V., Evaluation of water quality index for drinking purposes of river Subernarekha in Singhbhum District, International Journal of Environmental Sciences, Volume 1, No1,

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