International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 4, April 2018, pp. 372–381, Article ID: IJCIET_09_04_041 Available online at http://iaeme.com/Home/issue/IJCIET?Volume=9&Issue=4 ISSN Print: 0976-6308 and ISSN Online: 0976-6316

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STATISTICAL INVESTIGATION OF GROUND WATER QUALITY ACROSS COOVUM WATERSHED

Thanga Gurusamy.B, Ilango.T, Soundarya.M.K Assistant Professor, Department of Civil Engineering, VELS Institute of Science, Technology and Advanced Studies, (VISTAS)

Paul Abbinesh.L.S, Ram Kumar.R, Janagar.N Student, Department of Civil Engineering, VELS Institute of Science, Technology and Advanced Studies, (VISTAS) Chennai

ABSTRACT This paper investigate about the spatial variation of ground water quality across Chennai-Coovum watershed during the pre monsoon and pre 2015 flood season and compared with that of post monsoon and post 2015 flood season. Only chemical water quality parameters have been considered for this analysis. Basic statistical methods have been used to convert the observed data into useful information. This analysis is based on the data that has been made available to the public by Water Resources Department, Chennai . Both summary statistics analysis and Correlation based analysis has been carried out and the result have been presented in graphical and tabular form. SPSS software has been used to perform Correlation Coefficient analysis and other Measures of Dispersion and Measures of Central Tendency used to describe the water quality spatial distribution characteristics. Analysis of ratio of pre flood water quality to that of post flood water quality has been performed. Three locations such as Pudupet, , and Mugappair west have reported high flood sensitivity for most of the chemical water quality parameters. The ground water quality near and hostel location are consistently not suitable for drinking purposes without proper treatment. Total Dissolved Solids (TDS) and Electrical conductivity (EC) are proving very good correlation strength with others such as Ca, Mg, Na, k and Cl. But some of the parameters such as PH, NO3, SO4, CO3, F and HCO3 do not show correlation strength with other parameters. Negative skewness has been reported only by PH parameter and the distribution of HCO3 is having zero skewness and similar to that of Normal distribution. Many parameters including TDS, Hardness and Fluorides proved to have Positive skewness and leptokurtic distribution. Keywords: Ground water quality, spatial distribution Analysis, Statistical methods, Correlation coefficient.

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Cite this Article: Thanga Gurusamy.B, Ilango.T, Soundarya.M.K, Paul Abbinesh.L.S, Ram Kumar.R and Janagar.N, Statistical Investigation of Ground Water Quality Across Coovum Watershed, International Journal of Civil Engineering and Technology, 9(4), 2018, pp. 372–381. http://iaeme.com/Home/issue/IJCIET?Volume=9&Issue=4

1. INTRODUCTION The earth consists of atmosphere, lithosphere and hydrosphere. Life sustaining resources are available on all these three components of earth. The hydrosphere includes the oceans, streams, lakes and ground water resources that interflow with the surface water. The lithosphere covers the core of the earth. The atmosphere is containing a mixture of gases extending outward from the earth surface. The biosphere has received and assimilated the wastes generated by plants and animals. [1] Water quality in the intermediate stage between precipitation and evaporation will affect the Human use of water. The impurities present in the water may be in suspended, colloidal and dissolved form. Metcalf (1979)[2] has classified these impurities such that if the impurity particles size is above 1µm then it is called as Suspended impurities and if it is below 0.001 µm then it is dissolved impurities and in between 0.001 µm and 1µm is called as colloidal particles. Water pollution has been defined as the presence of impurities in such a quantity so as to impair the use of water for a stated purpose. The BUREAU OF INDIAN STANDARDS (BIS) has given water quality specifications for drinking use of water using the IS code 10500:2012. [3] These impurities have been classified as Physical, chemical and biological. Water resources management at all levels from upper stage National and State levels to lower stage local municipality level involves the task of monitoring the existing quantity and quality of water resources. This is because the objectives of this water resources department is to supply necessary amount of water with acceptable quality at the demanded point of time and space to satisfy the domestic, agricultural and industrial water requirements of the society. The monitoring involves the tasks of data collection and converting the data into useful information for decision making purposes such that the management process will get optimized. This research work involves the analysis of data collected by the water resources department to get useful information with the use of Statistical methods. The result presented in graphical and tabular form has been discussed.

2. LITERATURE REVIEW The importance of Ground water in both quantitative and qualitative perspectives has been discussed by Ayibatele (1992) [4] at world as well as local levels. The typical ground water quality of samples collected from tube wells and open wells has been discussed using basic methods by Mishra (2002) [5] and has been illustrated along with sources of pollutants. Garg (1990) [6] had presented the statistical based correlation analysis of ground water quality for the Roorkee city in the North Indian region. Shah (2007) [7] had reported the statistical based analysis for the ground water quality and other physiochemical parameters for area located in the Gujarat state. Sarkar (2006) [8] had presented the spatial variation of fluoride concentration in the ground water using statistical based correlation and regression methods. Shihab (1993) [9] had reported the application multivariate method for the analysis and interpretation of water quality data monitored for the Saddam reservoir. Pantelić (2012) [10] had used statistical based methods for the analysis of water quality parameters in the canal and the spatial distribution of water quality along the length of the canal had been discussed.

http://iaeme.com/Home/journal/IJCIET 373 [email protected] Thanga Gurusamy.B, Ilango.T, Soundarya.M.K, Paul Abbinesh.L.S, Ram Kumar.R and Janagar.N Pollution of ground water resources due to infiltration of polluted water from Cooum River is has been investigated and reported by CGWD annual report. [11] Application of Statistical based methods in the area of water resources had been discussed by Helsel (2002). [12] Evaluation of the ground water quality based on the statistical methods had been performed by Singh (2006) [13] in the area of Northern Indo-Gangetic Alluvium Region.

APHA, Washington (1998) [14] has reported the contamination of ground water quality from solid waste disposal system. Assessment of ground water quality had been carried out and reported by Hong (1999) [15] which involves the use of geographical information system to analyse the spatial variation of ground water quality.

3. STUDY AREA Coovum Watershed is geographically bounded between latitudes 12.9° N to 13.12° N and longitudes 79.6° E to 80.3° E. and having total catchment area is 400sq.km. Location of confluence with Bay of Bengal for this is Coovum mouth near Napier Bridge. The total length of this Coovum river is about is 72km and out of this, the length in the Chennai city limit is 18km, whereas the length in the Chennai Metropolitan Area (CMA) limit the length is 40 km.The origin of Coovum river is from the Coovum tank in the Thiruvallur district, which in turn receives water by the diversion from the Kesavaram anicut located across the near Thakkolam. The upper catchment of Coovum River is primarily rural and it is constrained by the channels when it passes through Chennai city.The Ground water quality along Coovum river is highly polluted by the drainage networks of the Chennai city. The Coovum watershed contains the area and typical bed width of Coovum River is in between 40m to 120m. The Figure 3.1 shows the location of Coovum watershed in the Chennai Sub basin in between the Kosasthalaiyar watershed in the north and Adayar watershed in the south.

Figure 3.1 Location map of Chennai Coovum watershed.

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4. RESEARCH METHODOLOGY A set of water quality monitoring wells is being maintained by the water resources department and a set of chemical water quality parameters is being observed by the department during every year pre monsoon and post monsoon season. These data is being made available for the analysis by students, research scholars and other departmental staffs. The list of the wells located in the Coovum watershed is shown in the table 4.1 and the corresponding location map of observation wells is shown in the Figure 4.1.

Table 4.1 Location of water quality monitoring well across Coovum watershed WELL NUMBER Village WELL NUMBER Village C01 Govindavadi C19 Parthipattu C02 Govinthavadiagaram C20 Ayabakkam C03 Purisai C21 Mugapper West C04 C22 C05 Maduramangalam C23 Koyambedu-temple C06 Kumaracheri C24 -school C07 Pudupet C25 Saligramam-kovil C08 C26 C09 Mappedu C27 Arumbakkam-green Tribunal C10 Melnallathur C28 Nugambakkam-park C11 Illuppur C29 Nugambakkam-school C12 C30 Purasavakkam-school C13 Nemam C31 -mandapam C14 Thirumazhisai C32 Purasavakkam-mandapam C15 Thandarai C33 Vepery C16 Kannamapalayam C34 Vepery-jain School C17 C35 Chepauk Hostel C18 C36 Chepauk

Figure 4.1 Location map of water quality monitoring well across Coovum watershed The well number is given in sequential order from west to east. The well C1 is located in the extreme west of the watershed near Coovum tank and the well C36 is at Chepauk near sea shore. The ground water Quality distribution graph is drawn such that the horizontal x axis refers from west to east. Temporal and spatial variation of ground water quality can be analyzed

http://iaeme.com/Home/journal/IJCIET 375 [email protected] Thanga Gurusamy.B, Ilango.T, Soundarya.M.K, Paul Abbinesh.L.S, Ram Kumar.R and Janagar.N by any appropriate methods and the information deducted can be used for the decision making purposes. Various set of graphs are used to detect information from the data. These graphs are Frequency distribution, Cumulative frequency distribution, Relative frequency distribution, etc. Graphs of frequency distribution and Relative frequency distribution are useful because they emphasis and clarify patterns that are not so readily discernible in tables. Frequency Distribution has been defined as an organized display of data that shows the number of observations from the data set that falls into each of the set of mutually exclusive and collectively exhaustive classes. Relative frequency Distribution has been defined as the display of a data set that shows the fraction or percentage of the total data set that falls into each of a set of mutually exclusive and collectively exhaustive classes. Skewness has been defined as the extent to which a distribution of data points is concentrated at one end or the other; the lack of symmetry. Range has been defined as the distance between the highest and lowest values in the data set. Kurtosis has been defined as peakedness of a distribution of data points. Coefficient of variation has been defined as a relative measure of dispersion, comparable across distribution that expresses the standard deviation as a percentage of the mean. Variance has been defined as a measure of the squared distance between the mean and each item in the population. The figure 4.2 shows the shape of the distribution having positive and negative skewness.

Figure 4.2 Positive and Negative skewness of the distribution The binomial distribution is mesokurtic. Examples of leptokurtic distributions include the Laplace distribution, and Poisson distribution. Uniform distribution is platykurtic. The expression for correlation coefficient r is given as below, where X and Y are the two variables selected and n is the number of observations. If the correlation coefficient is nearby to 1 then it represents the strong relationship between the two variables selected.

All the above statistical parameters have been calculated and tabulated in the form of Measures of central tendency and the measures of dispersion and the matrix of correlation coefficient. The information detected has been discussed. The frequency distribution graphs and cumulative distribution graph have been drawn to detect the information contained in data set.

5. RESULTS AND DISCUSSIONS Spatial distribution selected water quality and Flood sensitivity ratio of water quality are shown in Figure 5.1 Tables for the dispersion and central tendency measures have been prepared for both pre 2015 flood season and post 2015 flood season as shown in the Table 5.1 and

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5.2.Frequency distribution and Cumulative frequency distribution has been prepared for the selected water quality parameters and shown in the Figure 5.2. Matrix of the correlation coefficients has been prepared for all combinations of the water quality parameters for both pre 2015 flood season and post 2015 flood season and are shown in Table 5.3 and Table 5.4 respectively. The water quality at Vepery and Chepauk locations are consistently above permissible limit and hence not suitable for drinking purposes without proper treatment. Most of the water quality parameters including TDS, fluorides, total hardness, Electrical conductivity etc are exhibiting positive skewness in its frequency distribution. Negative skewness has been reported only by PH parameter and the distribution of HCO3 is having zero skewness having similar to that of Normal distribution. Very good correlation strength has been reported by both TDS and EC along with other parameters such as Calcium. Magnesium, Sodium, Potassium and chlorides. Nitrates do not have correlation with any other water quality parameters. But some of the parameters such as H P , NO3, SO4, CO3, F and HCO3 do not show correlation strength with other parameters. 6. CONCLUSIONS The water resources management system at any of the national, state, and local municipality level can be modeled as a closed loop control system. This system is having objectives to optimize the water resources utilization process in order to satisfy the domestic, agricultural and industrial water demand with specified water quality. The feedback mechanism involves the water quality monitoring system in order to design the separate water treatment system for domestic and industrial requirements. Design involves decision making. For such decision making process, the information received from the analysis of water quality is highly useful. Even though basic statistical methods have been used in this paper, some other analytical, simulation based and other advanced statistical methods are also available. Using time series water quality data the forecasting of future water quality can be done to plan for the design of system to satisfy the future requirements during the design period. Computer based automatic water quality analysis system on real time basis can also be implemented to work like a Management Information System (MIS) to assist the water resources management process.

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Figure 5.1 Spatial distribution selected water quality and Flood sensitivity ratio of water quality

Table 5.1 Measures of central tendency and measures of Dispersion for pre 2015 flood season

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Table 5.2 Measures of central tendency and measures of Dispersion for Post 2015 flood season

Table 5.3 Matrix of Correlation coefficients for pre 2015 flood season Ground water quality

Table 5.4 Matrix of Correlation coefficients for post 2015 flood season Ground water quality

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Figure 5.2 Frequency & Cumulative frequency distribution for selected water quality parameters

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ACKNOWLEDGEMENT The authors are grateful to the management of VELS Institute of Science, Technology and Advanced studies (VISTAS) for their consistent encouragement towards this research work and to the Executive Engineer, Tamil Nadu Water Resources Department Chennai, for their kind support to provide necessary ground water quality data for the study area considered. REFERENCES

[1] Bella. D. A. and W.S.Overton. “Environmental planning and Ecological possibilities,” presented at the annual national environmental engineering meeting of ASCE, 1971, p18- 22 [2] Metcalf & Eddy, “Waste water Engineering: Treatment, Disposal, Reuse, 2d ed. McGraw- Hill, New York, 1979. [3] BIS (Bureau of Indian Standards) 10500 -2012.Indian standard drinking water specification, Second version: 1-11. [4] Ayibatele. N.B First Season Environmental Baseline Survey in 1992. Proc. of international. Conf. on water and environ. 1: 4-26. [5] Mishra, K.R, Pradip and S.P. Tripathi. Groundwater Quality of Open Wells and Tubewells 2002 Acta Ciencia Indica, XXXIIIC no.2: 179. [6] Garg,D.K, Goyal R.N, and Agrawal,V.P Correlation among water quality parameters of ground water: Roorkee City 1990.Indian J. Envir. Prot. 10 no. 5: 355. [7] Shah M.C, Shilpkar P, and Sharma S, Correlation, Regression Study on Physico-chemical Patramters and water quality assessment of ground water of Mansa Taluka in Gujrat 2007.Asian J. Chem.19 no. 5: 3449. [8] Sarkar M, Banerjee A. Paramters P and. Chakraborty S, 2006. Appraisal of elevated fluoride concentration in ground water using statistical correlation and regression study. J. Indian Chem. Soc., 83: 1023. [9] Shihab,.A.S Application of Multivariate Method in the Interpretation of Water Quality Monitoring Data of Saddam Dam Reservoir, (1993). [10] [10] Pantelić M., Dolinaj D., Savić S., Stojanović V., Nađ I. Statistical Analysis of water quality parameters of Veliki Bački Canal (Vojvodina, Serbia) in period 2000- 2009. Carpathian Journal of Earth and Environmental Sciences 7, (2), 255, 2012. [11] CGWB Report “Ground water resources and development prospects in Madras District”, Tamil Nadu. Chennai: Central Ground Water Board, CGWB. 1993. [12] Helsel D.R, and Hirsch R.M, 2002. Statistical methods in water resources U.S. Department of the interiorgale chapter 3:218. [13] SinghV.K, Sinha. S., Singh,K.P. , Malik, A., Mohan, D., Evaluation of Groundwater Quality in Northern Indo-Gangetic Alluvium Region Environmental Monitoring and Assessment (2006) (112: 211–230 DOI: 10.1007/s10661-006-0357-5 _c 2006) [14] Standard Methods for Examination of Water and Wastewater, 20 ed, APHA, Washington D.C, USA (1998). [15] Dr. M. Venkateshwarlu, Dr. M. Narsi Reddy and Dr. A. Kiran Kumar, A Case Study on Assessment of Ground Water Quality Parameters In and Around Lambapur Area, Nalgonda District, Telangana State, International Journal of Civil Engineering and Technology, 8(7), 2017, pp. 563–566 [16] Hong, I. A., & Chon, H. T. (1999). Assessment of groundwater contamination using geographic information systems. Environmental Geochemistry and Health, 21(3), 273–289.

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