Indian Journal of Geo Marine Sciences Vol. 49 (4), April 2020, pp. 686-694

GIS based seasonal variation of groundwater quality and its suitability for drinking in Paravanar river basin, district, ,

S Sangeetha*,a, M Krishnavenia & S Mahalingamb aCentre for Water Resources, Anna University, Chennai, Tamil Nadu – 600 025, India bInstitute for Water Studies, Tharamani, Chennai, Tamil Nadu – 600 113, India *[E-mail: [email protected]]

Received 03 October 2018; revised 04 December 2018

Groundwater quality in Paravanar river basin has significant characteristics and its consideration is unavoidable, since it’s a major source of water for drinking, industries and irrigation usage. The present study was carried out to assess the groundwater quality suitability for drinking in Paravanar river basin, , Tamil Nadu, India. The rainfall frequency analysis was carried out in the basin area from 1971 to 2015 to delineate rainfall prominence years as drought, average rainfall, 75 % dependable rainfall and recent rainy years. In this study, nine parameters i.e., Electrical Conductivity (EC), pH, Total Dissolved Solids (TDS), Total Hardness (TH), Calcium (Ca2+), Magnesium (Mg2+), Chloride (Cl-), Sulphate 2- - (SO4 ) and Nitrate (NO3 ) were considered for computing the Water Quality Index (WQI) for the rainfall dependability years (1974, 1991, 2009 and 2015) by using weighted arithmetic index method for drinking purpose. Weighted overlay maps were prepared from the spatial distribution layers pertaining to WQI for the post and pre-monsoon seasons for the rainfall dependability years using ArcGIS 10.3. The results showed that the quality of water in Paravanar river basin was highly affected during post-monsoon than pre-monsoon period. More than 50 % of the basin area water samples weren’t really good enough for drinking without taking up water quality managing activities during post monsoon. Further, the water quality was highly degraded due to industrialization and agriculture activities compared to urbanization. The pollution control measures to improve the hazardous environment of industrial and agricultural practices, may develop the suitability area for drinking water in the basin.

[Keywords: Drinking water, Geographical Information System, Suitability area, Water Quality Index, Weighted overlay analysis] Introduction Water contamination influences its quality and Water is considered to be the most basic, valuable, affects human well-being, financial improvement rare and viable common assets. Over the most recent and social prosperity. Water waste and chemical couple of decades, there has been an enormous waste produced from several sources are a threat to increment in the interest of new water projects because groundwater aquifers. Accordingly, it is important of fast development of human race and quick pace of to control water contamination and screen its industrialization. It prompts over abuse of groundwater quality on a regular basis3. There are numerous and seawater interruption towards beachfront zones, illustrations used to analyze groundwater data where urbanization is occurring at a quickened pace, enabling a deeper understanding of the parameters consequently seawater intrusion causes the water of water quality. To determine water quality for progressively worse for usage1. different purposes, groundwater chemistry has been India is considered the fastest growing metropolitan utilized as a tool4-7. Finding out the appropriate nation; metropolisation has influenced overuse of ground water for drinking purpose, and testing the water water without any permissible restriction, leading to quality is essential which is determined as Water overexploitation of ground water resources. According to Quality Index (WQI)8-10. World Health organization report, polluted water is the In this study, Geographical Information System (GIS) major reason behind 80 % of human epidemic. Renewing based detailed physico-chemical characteristics were used the quality of ground water to its natural state will become to evaluate the suitability of groundwater for drinking challenging, if we continue to pollute. Routine inspection purpose in Paravanar river basin. Statistics result on WQI or a monitoring solution for inspecting the ground water is suggests an ameliorative benchmark to revise and maintain required to observe water getting polluted2. good groundwater quality for future usage. SANGEETHA et al.: SEASONAL VARIATION OF GROUNDWATER QUALITY AND ITS POTABILITY 687

Materials and Methods Thiessen polygon method Study area The spatial distribution of average rainfall is The Paravanar river basin is situated between identified by using Thiessen polygon method. The Pennaiyar river basin (north) and Vellar river basin raingauge station has an influence on the area of the (south) in Cuddalore district, Tamil Nadu, India within polygon surrounded by it. The area of influence the geographical coordinates of Latitude: 11º27'00" to laying both inside and outside the basin area of the 11º43'00" N and Longitude: 79º23'00 to 79º47'00" E rain gauge stations are considered for measurement. with the basin area of 879.462 sq. km. It consists of two The Thiessen polygon map using Arc GIS 10.3 is major tanks namely Wallajah tank and , and shown in Figure 3. several rainfed tanks and small streams are also Raingauge stations located in and around Paravanar available. The river basin area encloses , river basin are Chidambaram, Cuddalore, Cuddalore, and taluks. This Kothuvancheri, Panruti, Parangipettai, Sethiathoppu, region is known to be Naturally Cyclonic and and Virudhachalam. The monthly and annual rainfall precipitation depends substantially on the North East data for 45 years (1971 to 2015) were collected from Monsoon and receives rainfall due to low pressure in the the Institute for Water Studies, Chennai. The annual Bay of Bengal11. The quantity of annual rainfall received rainfall and influenced area measured by the is 1197 mm. The Paravanar river basin map is shown in raingauge stations were considered for calculating Figure 1. average rainfall of the basin. The Paravanar river originates from the highlands Average precipitation, in northwest of lignite corporation area i.e. 푛 푃 퐴 reserved forest near Semmakottai and Ammeri village 푃 = 푖=1 푖 푖 퐴 at an altitude of 100 m above Mean Sea Level. Most of the basin area is covered with agricultural lands. Where, The geological materials in the basin are sedimentary ‘Pi’ is the annual precipitation at various raingauge formation with 70 % of Cuddalore sandstone as stations. tertiary formation, consisting of laterite, sandstone, ‘Ai’ is the area of the polygon surrounding the clay, lignite, etc. and 30 % of river alluvium like sand, raingauge stations. silt, gravel and clay and coastal alluvium like sand in ‘A’ is the total area of the watershed. the form of stabilized sand dunes. The predominant soil types found in Paravanar river basin are Alfisols, Rainfall frequency analysis Entisols, Inceptisols, and Vertisols as result of It is used to understand the rainfall pattern and different stage of weathering of parent material12. computation of probability. The dependability of rainfall for Paravanar river basin is calculated by Methodology Weibull’s formula13,14. This study consist of three types of process i.e., rainfall frequency analysis, WQI and analysis using GIS as depicted in Figure 2.

Fig. 1 — Study area map Fig. 2 — Methodology of the study 688 INDIAN J GEO-MAR SCI, VOL 49, NO 04, APRIL 2020

Fig. 3 — Thiessen polygon map Percent probability, P = (1/T)*100%; depicted in Table 3 by following the standards16. Nine Where, water quality parameters such as EC, pH, Ca2+, Mg2+, 2- - - Recurrence interval, T = (n+1)/m; SO4 , TH, TDS, Cl and NO3 were considered for Where, computing WQI17,18. The WQI of the basin for ‘m’ is the rank drinking was calculated by weighted arithmetic index ‘n’ is the number of data. method. A quality rating (qn) was derived by the below equation19. The average precipitation data for 45 years from 1971 to 2015 were arranged in descending order, q n = 100[V n -V io] / [S n -V io] ranked from 1 to 45 and calculated recurrence interval Where, and probability using above mentioned formula th ‘qn’ is the quality rating for the n water quality (Table 1) and identified the recent rainy year as 2015, parameter. 75 % dependable rainfall as 1991, average rainfall th ‘Vn’ is the estimated value of the n parameter at a year as 2009 and drought year as 1974. given sampling station. ‘Sn’ is the standard permissible value of the nth Water Quality Index (WQI): parameter. The WQI is an approach where water quality th parameters with definite data are gathered, logged ‘Vio’ is the ideal value of n parameter in pure systematically and attained a distinctive value. This water. approach provides all the required parameters of (i.e., 0 for all parameters except pH = 7 and water quality in the precise area that are monitored. Dissolved oxygen = 14.6 mg/L) Unit weight of the parameter was calculated by Water quality concerns are addressed using WQI by gathering extensive data and analysis that will Wn = K /Sn generate a data table indicting the status of the water Where, quality and related changes. ‘Sn’ is the standard value for nth parameters. Several organizations like Indian Council for ‘K’ is the constant for proportionality. Medical Research (ICMR), Bureau of Indian The overall WQI was calculated by aggregating the Standards (BIS) and World Health Organization quality rating with the linear unit weight. (WHO) set the protocols to calculate standards for drinking water quality using WQI and results are WQI = ∑ q nWn/ ∑Wn SANGEETHA et al.: SEASONAL VARIATION OF GROUNDWATER QUALITY AND ITS POTABILITY 689

Table 1 — Rainfall frequency analysis Table 2 — Water Quality Index (WQI) and status of water quality Year Avg. RF Rank (m) T = (n+1)/m P = (1/T)*100 Water quality Water quality status 1985 1800.48 1 46 2.173913043 Index Level 1983 1763.67 2 23 4.347826087 0-25 Excellent water quality 2015 1723.43 3 15.33333333 6.52173913 26-50 Good water quality 2005 1688.13 4 11.5 8.695652174 51-75 Poor water quality 1996 1622.20 5 9.2 10.86956522 76-100 Very Poor water quality 2007 1544.95 6 7.666666667 13.04347826 >100 Unsuitable for drinking 1993 1503.81 7 6.571428571 15.2173913 Table 3 — Quality standards for drinking water with 1998 1430.67 8 5.75 17.39130435 recommending Agencies and unit weights. (All values except pH 1979 1409.96 9 5.111111111 19.56521739 and EC are in mg/L and EC in µS/cm) 1989 1376.09 10 4.6 21.73913043 S. Parameters Standard Recommended Unit 2004 1371.99 11 4.181818182 23.91304348 No. s agency Weight 1978 1371.47 12 3.833333333 26.08695652 1. pH 6.5-8.5 ICMR/BIS 0.2190 1997 1370.32 13 3.538461538 28.26086957 2. Electrical 300 ICMR 0.371 1977 1350.97 14 3.285714286 30.43478261 Conductivity 2003 1349.58 15 3.066666667 32.60869565 3. Total Dissolved 500 ICMR/BIS 0.0037 2011 1330.53 16 2.875 34.7826087 Solids 1971 1330.17 17 2.705882353 36.95652174 4. Total hardness 300 ICMR/BIS 0.0062 2010 1320.38 18 2.555555556 39.13043478 5. Calcium 75 ICMR/BIS 0.025 2006 1301.58 19 2.421052632 41.30434783 6. Magnesium 30 ICMR/BIS 0.061 2014 1294.26 20 2.3 43.47826087 7. Chlorides 250 ICMR 0.0074 2008 1265.47 21 2.19047619 45.65217391 8. Nitrate 45 ICMR/BIS 0.0412 1972 1261.27 22 2.090909091 47.82608696 9. Sulphate 150 ICMR/BIS 0.01236 2009 1243.64 23 2 50 Spatial analysis 2013 1191.68 24 1.916666667 52.17391304 Geographical Information System (GIS) is an 1973 1155.33 25 1.84 54.34782609 effective spatial data handling tool to provide better 1999 1130.12 26 1.769230769 56.52173913 solution for complex geographical problems. The 1984 1097.62 27 1.703703704 58.69565217 groundwater quality data for corresponding rainfall 2000 1090.65 28 1.642857143 60.86956522 dependability years were collected from the Institute 2001 1085.87 29 1.586206897 63.04347826 for Water Studies (IWS), Chennai. The interpolation 2012 1067.17 30 1.533333333 65.2173913 of water quality data by Inverse Distance Weighting 1976 1062.82 31 1.483870968 67.39130435 (IDW) in the ArcGIS 10.3 was made and delineated 1981 1044.45 32 1.4375 69.56521739 spatial distribution of water quality index of 1994 1036.99 33 1.393939394 71.73913043 Paravanar river basin for post and pre monsoon 1986 982.88 34 1.352941176 73.91304348 seasons of 2015, 2009, 1991 and 1974 as shown in 1991 969.87 35 1.314285714 76.08695652 Figure 4. The water quality index was classified into 1990 963.50 36 1.277777778 78.26086957 different classes which is important for the evaluation 1987 916.17 37 1.243243243 80.43478261 of the groundwater quality suitability for 1992 908.18 38 1.210526316 82.60869565 drinking purposes20. 1975 876.94 39 1.179487179 84.7826087 1988 848.95 40 1.15 86.95652174 Result and Discussion 1980 762.13 41 1.12195122 89.13043478 Weighted overlay analysis 2002 761.09 42 1.095238095 91.30434783 In weighted overlay analysis, all thematic layers of 1982 713.91 43 1.069767442 93.47826087 the WQI map were rehabilitated into raster format and 1995 656.26 44 1.045454545 95.65217391 overlay was done by weighted overlay method in 1974 546.56 45 1.022222222 97.82608696 ArcGIS 10.3. In this technique, each class of the The water quality index of groundwater was thematic layers was categorized into (i) excellent, classified into different status and level is (ii) good, (iii) poor, (iv) very poor, and (v) unsuitable. depicted in Table 2(ref. 15). During weighted overlay analysis, the rank was 690 INDIAN J GEO-MAR SCI, VOL 49, NO 04, APRIL 2020

Fig. 4 — Water quality index map SANGEETHA et al.: SEASONAL VARIATION OF GROUNDWATER QUALITY AND ITS POTABILITY 691

Table 4 — Weightage and rank for various quality category of drinking water S. No. Year Period Classes Category Rank Weightage (%)

1 1974 Post- monsoon 0-25 Excellent 1 35 26-50 Good 2 51-75 Poor 3 76-100 Very poor 4 Pre- monsoon 0-25 Excellent 1 26-50 Good 2 51-75 Poor 3 76-100 Very poor 4 2 1991 Post- monsoon 26-50 Good 2 30 51-75 Poor 3 76-100 Very poor 4 >100 Unsuitable 5 Pre- monsoon 0-25 Excellent 1 26-50 Good 2 51-75 Poor 3 76-100 Very poor 4 3 2009 Post- monsoon 0-25 Excellent 1 20 26-50 Good 2 51-75 Poor 3 76-100 Very poor 4 Pre- monsoon 0-25 Excellent 1 26-50 Good 2 51-75 Poor 3 76-100 Very poor 4 4 2015 Post- monsoon 0-25 Excellent 1 15 26-50 Good 2 51-75 Poor 3 Pre- monsoon 0-25 Excellent 1 26-50 Good 2 51-75 Poor 3 76-100 Very poor 4 assigned from 1 to 5 for each thematic map and assigned monsoon) of the total area had good groundwater weightage based water quality index and rainfall quality. Further, it also indicated that 54.86 % dependability year to assess suitability area for drinking (post-monsoon) and 32.29 % (pre-monsoon) of the purpose (Table 4). In the ranking method, a larger total basin area was poor for drinking purposes. number (5) was assigned to the feature with unsuitable The water under each block and villages had poor water quality for drinking purpose and a small number groundwater quality for the post and pre-monsoon (1) was assigned to the excellent water quality. seasons were depicted in Table 5 and imply that

WQI for drinking water the quality of groundwater in the basin was highly The spatial distribution of WQI (Fig. 5) showed influenced by the post-monsoon season than pre- that 44.79 % (post-monsoon) and 67.59 % (pre monsoon.

692 INDIAN J GEO-MAR SCI, VOL 49, NO 04, APRIL 2020

Fig. 5 — Drinking water suitability area: a) Post-monsoon b) Pre-monsoon SANGEETHA et al.: SEASONAL VARIATION OF GROUNDWATER QUALITY AND ITS POTABILITY 693

Table 5 — Block wise water quality status during Post and Pre-monsoon season S. Block Villages NO. Good Poor Very Poor 1. Bhuvanagiri (Highly influenced by Post monsoon) Post Monsoon NA Erumbur, Maruthur Pinnalur, Odaiyur Pre Monsoon NA Erumbur, Maruthur, Pinnalur, Odaiyur NA 2. Chidambaram (Similar water quality during Post and Pre monsoon) Post Monsoon NA Thurinjikollai NA Pre Monsoon NA Thurinjikollai 3. Cuddalore (Highly influenced by Post monsoon) Post Monsoon NA Thondamanatham, NA Vazhisothanaipalayam, Ramapuram, Sathankuppam Pre Monsoon Thondamanatham, Vazhisothanaipalayam, Ramapuram, NA NA Sathankuppam 4. Kammapuram (Similar water quality during Post and Pre monsoon) Post Monsoon Mudanai, Melakuppam, Edaikuppam NA NA Pre Monsoon Mudanai, Melakuppam, Edaikuppam NA NA 5. Kurinjipadi (Highly influenced by Post monsoon) Post Monsoon Madanagopalapuram, Co-Chatram, Krishnapuram, AdoorAgaram, Kothavachery, Thanur, NA Kullanchavadi, Pacharapalayam, Vadakkumelur, Kundiyamallur Meenakshipettai, Abatharanapuram, Pre Monsoon Madanagopalapuram, Co-Chatram, Krishnapuram, Thanur, Kundiyamallur NA Kullanchavadi, Pacharapalayam, Vadakkumelur, Meenakshipettai, Abatharanapuram, Vadalur, AdoorAgaram, Kothavachery 6. Panruti (Highly influenced by Post monsoon) Post Monsoon Annadanapettai Kattugudalur, Chithankuppam, Muthandikkuppam Alagappasamudram Pre Monsoon Annadanapettai, Kattugudalur, Chithankuppam, NA NA Alagappasamudram, Muthandikkuppam 7. Parangipettai (Highly influenced by Post monsoon) Post Monsoon NA NA Thatchankadu Pre Monsoon NA Thatchankadu NA 8. Virudachalam (Highly influenced by Pre monsoon) Post Monsoon Manakollai NA NA Pre Monsoon NA Manakollai NA

Conclusion which played a most important role in the The WQI was an essential tool to identify the area groundwater quality degradation than urbanization. for drinking water suitability of all water resources. The disposal, flooding, soil erosion and fertilizer The classification of Paravanar river basin holds good usage were considered as important drivers for physico-chemical characteristics of groundwater. The groundwater quality degradation. Therefore, the result concluded that Paravanar river basin was highly corrective methods like wastewater treatment in the affected by post-monsoon than pre-monsoon seasons. industries and sewage water from the urbanized area Almost 54.86 % of total basin area had poor before disposing into the watercourses was considered groundwater quality for drinking purposes, especially as important pollution control measure3. Further, in the post-monsoon season. The area under the pumping out of a large quantity of groundwater by the revenue blocks of Cuddalore, Bhuvanagiri, industries should be avoided. The Cuddalore district Kurinjipadi, and Parangipettai were severely affected was mainly affected by flooding and flood during post monsoon. The pollution was intensified management techniques such as control/reduce runoff by the industrialization and agricultural activities (artificial recharge, affore station, permeable 694 INDIAN J GEO-MAR SCI, VOL 49, NO 04, APRIL 2020

pavements), runoff storage (retarding basin, dam, 8 Basavaraddi S B, Kousar H & Puttaiah E T, Seasonal variation lake, wetlands), improvement of river’s capacity of groundwater quality and its suitability for drinking in and around Tipur town, Tumkur district, Karnataka, India: a WQI (reducing bends, increase the depth and width of the Approach, Int J Comp Eng Res, 2 (2012) 562-567. channel), dissociation of river and people (control the 9 Upadhyay A & Chandrakala M, Pre-Monsoon Study of usage of land, zoning, house rising, watercourses) and Physico-Chemical Parameters of Hemavathi River, managing the emergency during floods (better Turuvekere, Karnataka, India, Int J Innov Res Sci Engg and warning system, emergency works to improvement of Tech, 3 (2014) 15986-15990. 10 Joshi D M, Kumar A & Agrawal N, Studies on watercourses, migration) may prevent polluting of physicochemical parameters to assess the water quality of drinking water. The correct actions must be taken river Ganga for drinking purpose in Haridwar district, promptly to save the groundwater quality. Rasayan, J Chem, 2 (2009) 195-203. 11 Aravindan S & Shankar K, Groundwater quality maps of Author Contributions Paravana River sub basin, Cuddalore district, Tamil Nadu, SS contributed to the design and implementation of India, Indian Soc Remote Sen, 39 (2011) 565–581. the research, to the analysis of the results and to the 12 Shankar K, Aravindan S & Rajendran S, Assessment of Ground Water Quality in Paravanar River Sub-Basin, writing of the manuscript. MK was involved in Cuddalore district, Tamil Nadu, India, Adv Appl Sci Res, 2 planning and supervised the work. SM and SS (2011) 92-103. analyzed the data and worked in GIS environment. 13 Muruganantham M, Krishnaveni M & Sandeep Kumar All authors discussed the results and commented on Patakamuri, Performance evaluation of Uthiramerur tank the manuscript. irrigation system using spatial technologies and participatory approach, J Appl Hydr, 1 (2015) 79-86.

14 Rajendran V, Venkatasu bramani R & Vijaya kumar G, References Rainfall variation and frequency analysis study in 1 Srikanthan L, Jayaseelan J, Narendran D, Manikandan I & Dharmapuri district, India, Indian J Geo-Mar Sci, 45 (2016) Sing S H, Determination of ground water quality using water 1560-1565. quality index in part of Chennai city, Tamil Nadu, Indian 15 Chatterjee C & Raziuddin M, Determination of water quality J Sci, 3 (2013) 81-84. index (WQI) of a degraded river in Asanol industrial area, 2 Rama Krishnaiah C R, Sadashivaiah C & Ranganna G, Raniganj, Burdwan, West Bengal, Nat Environ and Poll Assessment of Water Quality Index for the Groundwater in Tech, 1 (2002) 181-189. Tumkur Taluk, Karnataka State, Indian J Chem, 6 (2009) 16 Bairu A, Tadesse N & Amare S, Use of geographic 523-530. information system and water quality index to assess 3 Arivarasi R & Ganesan M, Seasonal variation in ground suitability of groundwater quality for drinking purposes in water quality and its suitability for drinking and agriculture – Hewane areas, Tigray, Northern Ethiopia, Ethiopian J A case study in Kancheepuram region, Tamil Nadu, India, Environ Studies Manag, 6 (2013) 110 – 123. Global NEST J, 19 (2017) 131-139. 17 Manju E K, George A V & Rekha V B, A comparative study 4 Kalra N, Kumar R, Yadav S S & Singh R T, Water quality of Water Quality Index (WQI) of Vagamon and Peermade index assessment of groundwater in Koilwar block of sub-watersheds of Meenachil and Pamba river basins of Bhojpur (Bihar), J Chem Pharm Res, 4 (2012) 1782-1786. Western Ghats, Kerala, South Indian, J Environ Sci Toxicol 5 Gopal Krishan, Surjeet Singh, Suman Gurjar, Kumar C P & Food Tech, 8 (2014) 53-58. Ghosh N C, Water Quality Assessment in Terms of Water 18 Singh P & Khan I A, Ground water quality assessment of Quality Index (WQI) Using GIS in Ballia District, Uttar Dhankawadi ward of Pune by using GIS, Int J Geomatics Pradesh, India, J Environ Anal Toxicol, DOI: 10.4172/2161- Geo Sci, 2 (2011) 689-703. 0525.1000366. 19 Yogendra K & Puttaiah E T, Determination of Water Quality 6 Kankal N C, Indurkar M M, Gudadhe S K & Wate S R, Index and Suitability of an Urban Water body in Shimoga Water Quality Index of Surface Water Bodies of Gujarat, Town, Karnataka, Proc Taal: The 12th World Lake India, Asian J Exp Sci, 26 (2012) 39-48. Conference, 2008, pp. 342-346. 7 Rupal M, Tanushree B & Sukalyan C, Quality 20 Tiwari A K, Singh P K & Mahato M K, GIS-Based characterization of Groundwater using Water Quality Index Evaluation of Water Quality Index of Groundwater in Surat city, Gujarat, India, Int Res J Environ Sci, 1 (2012) Resources in West Bokaro coalfield, India, Curr World 14-23. Environ, http://dx.doi.org/10.12944/CWE.9.3.35.