Research Journal of Chemical Sciences ______________________________________________ ISSN 2231-606X Vol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 1 Hydrogeochemical Evaluation of Groundwater of the steel city Durgapur, West Bengal, IndiaBhattacharyya R., Manoj K. and Padhy P.K.* Department of Environmental Studies, Institute of Science, Visva-Bharati, Santiniketan, 731235, Birbhum, West Bengal, INDIA Available online at: www.isca.in, www.isca.me Received 17th April 2014, revised 29th May 2014, accepted 10th June 2014Abstract Quality assessment of groundwater of the steel city Durgapur, West Bengal, India, was carried out to investigate what roles anthropogenic activities and various hydrogeochemical processes play on it, employing combinations of hydrogeochemical analyses and two multivariate statistical techniques, namely, cluster analysis and principal component analysis. Values of analyzed parameters, namely, Na, K, Ca2+, pH, electrical conductivity, total dissolved solids, hardness, Mg2+, HCO, NO, PO3-, SO2- and Cl reported wide variations which ranged from 49.50-248.50 mg/l, 1.70-225.00 mg/l, 29.70-217.40 mg/l, 4.90-6.83, 257-2501 µS/cm, 170-1273 mg/l, 16-568 mg/l, 1.90-48.60 mg/l, 40-520 mg/l, 0.99-15.42 mg/l, 0.02-1.00 mg/l, 6.51-182.46 mg/l and 19-314 mg/l respectively. Analyzed results demonstrated roles of natural hydrogeochemical processes like weathering of silicates and carbonates and exchange of ions as well as human-made developmental activities responsible for affecting the groundwater quality. Anthropogenic control on groundwater chemistry emerged as a basic concern especially in the industrial areas, where some assessed parameters recorded much elevated levels. Keywords: Cluster analysis, geochemistry, piper diagram, principal component analysis. Introduction Twenty four regions in the country (India) can be designated as ‘problem areas’ where extensive industrial and other developmental activities dominate. In the state of West Bengal two such problem areas are Durgapur and Howrah. The Central Pollution Control Board (CPCB) examined groundwater quality of five selected locations in Durgapur industrial area and found physicochemical parameters exceeding the regulatory benchmark at some of the sites. With this background information, a thorough investigation and geochemical characterization of groundwater quality of Durgapur, the emerging and future megacity of the Eastern India, by increasing the sample size is required to arrive at some discrete conclusions with respect to the occurrence of chemical components from natural sources, artificial means or from both. In addition to hydrogeochemical processes, developmental activities in the form of industrialization, urbanization, intensive agriculture and change in land use also control groundwater quality of a region and, therefore, their understanding is important for sustainable management, designing conservation plans and development of these freshwater resources. In India, several groundwater investigations have been taken up across the country; a few names include Gwalior city (Madhya Pradesh), Muktsar district (Punjab), Deoria district (Uttar Pradesh), Akot city (Maharashtra)5 and Vaijapur, district Aurangabad (Maharashtra). This study is the first attempt to demonstrate and characterize groundwater chemistry of some selected industrial-commercial as well as residential zones of Durgapur employing combinations of hydrogeochemical analyses and some advanced multivariate data analyses techniques. Material and Methods Study area: The study area, located between latitudes 23°35 \n  \r  \n \rand 87°2138.93E, was a section of the Durgapur subdivision, Bardhaman district, West Bengal, India, figure-1. Many big and small industrial units are located here, notably, Durgapur Steel Plant, Durgapur Thermal Power Station, Alloy Steel Plant, Durgapur Cement and Durgapur Projects Limited. The industrial units and their townships have made Durgapur a flourishing urban-industrial region. Geologically the region is characterized by a thin occurrence of alluvial cover and presence of the Gondwana sedimentary rocks having continental sedimentary framework. Recent geo-environmental appraisal of the region distinguishes presence of four geomorphic units, namely, older alluvial surface, younger alluvial surface, present day surface and lateritic uplands. Sampling and analyses: Groundwater representative samples collected from twenty two strategically selected locations, figure-1, during March, 2013 were analyzed for the presence of major ions, namely, Na, K, Ca2+, Mg2+, Cl, SO2-, NO, PO3-and HCO following standard procedures described by APHA. Additionally, data of pH (measured at the sampling sites), electrical conductivity (EC), total dissolved solids (TDS) and hardness (HARD) were also obtained. Only double glass distilled and deionized waters and analytical grade reagents were used for the experiments. Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 2 Figure-1 Study area (a section of the Durgapur subdivision) and sampling locations Statistical analyses: Recorded physicochemical data were subjected to systematic statistical analyses, where, in addition to basic descriptive statistical tools and correlation analysis (Pearson), multivariate statistical techniques were applied on the dataset for intelligent interpretation of the hydrogeochemical data. Agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA) multivariate tools were employed in the present investigation. Dataset was checked for its normal distribution character following statistical protocols like P-P plots, Q-Q plots, mean-median comparison, skewness and kurtosis. Accordingly, data were log transformed to approach normal distribution and also removing the influence of outliers. Water chemistry being a multivariate data comprising many variables, some sophisticated statistical methodologies is required for its comprehensive appraisal. Many hidden phenomena and inherent multifaceted hydrochemical behaviours can be expressed through multivariate modeling methods without much loss of original information. Multivariate data analyses systems provide concurrent examination of several variables both in space and time. Research Journal of Chemical Sciences ____ _ Vol. 4(6), 1-12, June (2014) International Science Congress Association AHCA is done for classifying an ungrouped data into homogeneous sets of related observations based on their similarities and the result is presented as a dendrogram. This study used Ward’s method and squared Euclidean distance, as a measure of proximity, for the classification of sampling sites. The Euclidean distance is expressed as given below  \n  \n\n\rWhere, ij = Euclidean distance for two individuals = squared Euclidean distance) , each measured on jl, l = 1… q. PCA is an intelligent dimension reduction technique which reduces a large dataset into a new set of linear combination of variables designated as principal components (PC). words, each orthogon al PC is a linear combination of the original variables and denotes a different variation source These PCs disclose information about the most significant variables explaining the complete dataset by rendering exclusion of the variables considered less significant, while still retaining original information with minimum loss generated through PCA can be expressed as14 :  = \r\r   Where = component score, = component loading, measured value of the variable, = component number, sample number, and = total number of variables. In the present study, Kaiser Normalization along with VARIMAX rotation was employed for the generation of PCs. Box and whisker plots showing distribution of analyzed _ _____________________________________________ _ International Science Congress Association AHCA is done for classifying an ungrouped data into homogeneous sets of related observations based on their similarities and the result is presented as a dendrogram. This study used Ward’s method and squared Euclidean distance, as a proximity, for the classification of sampling sites. The Euclidean distance is expressed as given below 10. Euclidean distance for two individuals i and (ij , each measured on q variables, il, PCA is an intelligent dimension reduction technique which reduces a large dataset into a new set of linear combination of variables designated as principal components (PC). In other al PC is a linear combination of the original variables and denotes a different variation source 11. These PCs disclose information about the most significant variables explaining the complete dataset by rendering significant, while still retaining original information with minimum loss 12,13. The PCs :   = component loading, x = = component number, = = total number of variables. In the present study, Kaiser Normalization along with VARIMAX rotation was employed for the generation of PCs. Results and Discussion Groundwater physicochemical profile: hydrochemical parameters is essential to evaluate groundwater quality and assign contaminated or uncontaminated nature. Moreover, generated data is employed in investigating various hydrogeochemical mechan isms responsible for controlling geochemistry of groundwater. Study of water quality is indispensable to understand aquatic ecosystem parameters reported wide variation and range values, figure and table- 1, suggesting role of different facto chemistry of the aquifer systems. Parameters like Na Cl, Mg2+, HCO , TDS and EC crossed the desirable regulatory standards of the World Health Organization Indian Standards17 for drinking water at some of mostly industrial areas, indicating occurrence of influence of human- made developmental activities on the groundwater quality. As TDS is directly dependent on the concentration of ions, its distribution in groundwater of the area is demonstrate in figure- 3. In Pearson’s correlation analysis, table the parameters displayed strong association indicating possible interactions between them. Significantly high correlation ( 0.05) was noted for Na—K, Na + Cl, K—Cl, Ca2+—HCO, Ca2+ — HCO, Mg2+—SO2-, HCO—SO 2 demonstrating high correlation may suggest similar origin and associated controlling processes. EC exhibited strong correlation (P 0.05) with Na (0.92), Ca Cl (0.75) and relatively good relation with K (0.62) implying involvement of most of the ions in controlling groundwater physicochemical processes such as oxidation reduction and exchange of ions . Hig observed with Cl (0.89, 0.05) suggesting contribution of artificial (anthropogenic) sources to the groundwater chemistry Figure-2 Box and whisker plots showing distribution of analyzed physicochemical parameters in groundwater samples _ ________ ISSN 2231-606X Res. J. Chem. Sci. 3 Groundwater physicochemical profile: Assessment of hydrochemical parameters is essential to evaluate groundwater quality and assign contaminated or uncontaminated nature. Moreover, generated data is employed in investigating various isms responsible for controlling geochemistry of groundwater. Study of water quality is indispensable to understand aquatic ecosystem 15. Analyzed parameters reported wide variation and range values, figure -2 1, suggesting role of different facto rs in controlling chemistry of the aquifer systems. Parameters like Na , K, Ca2+, , TDS and EC crossed the desirable regulatory standards of the World Health Organization 16 and the Bureau of for drinking water at some of the sites, mostly industrial areas, indicating occurrence of influence of made developmental activities on the groundwater quality. As TDS is directly dependent on the concentration of ions, its distribution in groundwater of the area is demonstrate d 3. In Pearson’s correlation analysis, table -2, most of the parameters displayed strong association indicating possible interactions between them. Significantly high correlation ( + —Ca2+, Na—SO2-, Na— — SO2-, Ca2+—Cl, Mg2+ 2 and SO2-—Cl. Parameters demonstrating high correlation may suggest similar origin and associated controlling processes. EC exhibited strong (0.92), Ca 2+ (0.99), SO2- (0.94), (0.75) and relatively good relation with K (0.52) and HCO (0.62) implying involvement of most of the ions in controlling groundwater physicochemical processes such as oxidation - . Hig hest correlation of Na was 0.05) suggesting contribution of artificial (anthropogenic) sources to the groundwater chemistry . physicochemical parameters in groundwater samples Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 4 Table-1 Descriptive geo-statistics of the analyzed groundwater samples and some guideline values AP Min Max Mean SD Med Skewness Kurtosis BIS (2004) Desirable limit # WHO (1997) Desirable limit Na + 49.5 248.5 122.7 60.94 98.5 1.2 0.185 - 50 K + 1.7 225 46.9 60.95 28.95 2.35 5.25 - 100 Ca 2+ 29.7 217.4 103.9 50.95 86.05 0.982 0.262 75 75 pH 4.9 6.83 6.2 0.59 6.32 -0.67 -0.461 6.5-8.5 7.0-8.5 EC 257 2501 998.8 635.06 682 1.29 0.95 - 750 TDS 170 1273 619.1 323.01 491 0.72 -0.61 500 500 HARD 16 568 255.4 187.74 156 0.46 -1.459 300 100 Mg 2+ 1.9 48.6 18.3 14.78 12.65 0.969 -0.338 30 30 HCO 3 - 40 520 205.9 161.68 133 0.775 -0.992 200 * 200 NO 3 - 0.99 15.42 9.8 5.72 12.73 -0.33 -1.78 45 - PO 4 3 - 0.02 1.0 0.47 0.33 0.38 0.36 -1.44 - - SO 4 2 - 6.51 182.5 71.4 58.09 42.99 0.9 -0.51 200 200 Cl - 19 314 122.1 87.01 133 0.855 -0.012 250 250 Cations, anions, TDS and HARD in mg/l; EC in µS/cm; and adopted from other source23; AP = analyzed parameters, min = minimum, max = maximum, SD = standard deviation, med = medianTable-2 Correlation analysis of the groundwater quality dataset Na + K + Ca 2+ pH EC TDS HARD Mg 2+ HCO 3 - NO 3 - PO 4 3 - SO 4 2 - Cl - Na + 1.0 0.66 0.88 0.31 0.92 0.89 0.68 0.25 0.34 0.45 0.15 0.77 0.89 K + 1.0 0.43 -0.26 0.52 0.56 0.18 -0.05 -0.28 0.73 0.14 0.45 0.81 Ca 2+ 1.0 0.65 0.99 0.98 0.92 0.49 0.69 0.04 0.43 0.95 0.69 pH 1.0 0.58 0.56 0.79 0.65 0.92 -0.57 0.49 0.69 0.09 EC 1.0 0.99 0.86 0.40 0.62 0.14 0.35 0.94 0.75 TDS 1.0 0.85 0.43 0.61 0.12 0.43 0.96 0.77 TH 1.0 0.76 0.79 -0.27 0.49 0.90 0.42 Mg 2+ 1.0 0.52 -0.44 0.45 0.54 0.06 HCO 3 - 1.0 -0.62 0.42 0.72 0.07 NO 3 - 1.0 -0.29 -0.07 0.68 PO 4 3 - 1.0 0.45 0.21 SO 4 2 - 1.0 0.61 Cl - 1.0 Figure-3 Spatial distribution of analyzed TDS in groundwater samples Research Journal of Chemical Sciences ____ _ Vol. 4(6), 1-12, June (2014) International Science Congress Association Hydrogeochemical evaluation: Piper trilinear plot, developed for investigating evolution of hydrogeochemical classified collected groundwater samples into four distinct types, namely, Ca2+—HCO, Mixed Ca2+ — Ca2+—Na—HCO and Na—Cl . Accordingly, 40.91%, 18.18%, 27.27% and 13.64% samples belonged to four identified water types respec tively. The evaluation further revealed 68.18% water samples represented temporary hardness of water. Since, the study area lies adjacent to the Damodar river basin rich in coal deposits, this classification was also supported by the work of Jayaprakash et al. hydrochemical facies of Mixed Ca2+—NaCa2+—Mg2+—Cl, Na—Cl and Ca2+ HCO Neyveli groundwater basin (India). Piper plot illustrating water types are displayed in figure-4. Piper trilinear plot illustrating hydrochemical regime of the groundwater samples _ _____________________________________________ _ International Science Congress Association Piper trilinear plot, developed for investigating evolution of hydrogeochemical parameters, classified collected groundwater samples into four distinct — Mg2+—Cl, Mixed . Accordingly, 40.91%, 18.18%, 27.27% and 13.64% samples belonged to four tively. The evaluation further revealed 68.18% water samples represented temporary hardness of water. Since, the study area lies adjacent to the Damodar river basin rich in coal deposits, this classification was also al. 18 who reported Na —HCO, Mixed HCO types from the Neyveli groundwater basin (India). Piper plot illustrating water Identifying hydrogeochemical groundwater chemistry is essential to discover key sources affecting its quality. The ion exchange chemistry between sub surface waters and the surrounding environment is a major phenomenon that controls distribution and occurrence o the former19 . This hydrogeochemical process can be evaluated employing chloro- alkaline indices (CAI by Schoeller20 and also described in literature of other authors 21, 22 . The CAIs can be computed from the formulae given (ions expressed in meq/l).  " %' ( ) "  +" %'() ! ,-  \r Figure-4 Piper trilinear plot illustrating hydrochemical regime of the groundwater samples _ ________ ISSN 2231-606X Res. J. Chem. Sci. 5 processes controlling groundwater chemistry is essential to discover key sources affecting its quality. The ion exchange chemistry between sub - surface waters and the surrounding environment is a major phenomenon that controls distribution and occurrence o f ions in . This hydrogeochemical process can be evaluated alkaline indices (CAI -1 and CAI-2) suggested and also described in literature of other authors 3, . The CAIs can be computed from the formulae given below ( ) " # !  \r .--\r#%- Piper trilinear plot illustrating hydrochemical regime of the groundwater samples Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 6 When Na and K ions present in the groundwater are exchanged with Ca2+ and Mg2+ present in the surrounding rock, the CAIs are positive and the exchange is known as direct. This reaction is also called base-exchange reaction and the resulting condition chloro-alkaline equilibrium. Whereas, in reverse process the CAIs are negative and the exchange is known as indirect. This reaction is also called cation-anion exchange reaction and the resulting condition chloro-alkaline disequilibrium21,23. CAIs calculated for the groundwater samples showed negative values (result not shown) which illustrated prevalence and existence of cation-anion exchange process and chloro-alkaline disequilibrium respectively. Another method to determine underlying mechanism controlling groundwater quality is the Gibbs plot. In TDS versus [Na/(Na+ + Ca2+)] plot most of the chemical data, except a few, plotted in the rock weathering dominance zone, figure-5. Similar plot was noted for TDS versus [Cl/(Cl- + HCO)], figure-6, indicating control of rock-water interaction in hydrogeochemistry of the region. Two plots, namely, Na versus Cl and Na/Cl versus EC also demonstrate whether evaporation is a major controlling factor of the groundwater chemistry. If evaporation is the dominant process for increasing concentration of chemical species then the ratio of Na/Cl would remain unchanged presuming that no mineral species have undergone precipitation, and consequently Na/Cl versus EC would produce a horizontal plot3,24. A molar ratio of Na/Cl approximating one indicates halite dissolution whereas ratio greater than one points to weathering of silicates3,25. The recorded molar Na/Cl ratios typically disclosed silicate weathering as one of the factors, except at two stations where halite dissolution was noted, figure-7. The plot of Na/Cl versus EC, figure-8, illustrated slightly inclined trend suggesting weathering and exchange of ions, and not evaporation, were the prevalent hydrogeochemical processes which affected groundwater chemistry of the area. In the plot of (Ca2+ + Mg2+versus (SO2- + HCO) chemical data points featuring along the equiline indicate presence of ions in groundwater from weathering of both carbonates and silicates while points falling above or below the equiline suggest carbonate weathering or silicate weathering as dominant process respectively. Data points in figure-9 clearly indicated coupled weathering involving both carbonates and silicates. Existence of coupled weathering was also demonstrated by (Ca2+ + Mg2+versus HCO, figure-10; (Ca2+ + Mg2+ versus total cations, figure-11; and (Na + Kversus total cations, figure-12, plots. The ratio of (Ca2+ + Mg2+)/HCO is used for source identification of Ca2+ and Mg2+ as the mole ratio around one indicates weathering of minerals. The graphical representation, figure-13, evidently pointed that weathering was not the only source of alkaline earths in groundwater. In addition to reverse ion exchange, anthropogenic contribution could also be attributed26. With the increase of (SO2- + Cl) the alkalis also reported increasing trend, figure-14, which suggested a common source for these ions and the occurrence of NaSO and KSOin soils of the Durgapur area. Figure-5 Gibbs plot showing TDS versus Na:(Na + Ca2+) hydrogeochemistry Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 7 Figure-6 Gibbs plot showing TDS versus Cl:(Cl + HCO) hydrogeochemistry Figure-7 Scatter plot of Na versus Cl obtained from the hydrogeochemical data Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 8 Figure-8 Scatter plot of Na/Cl versus EC obtained from the hydrogeochemical data Figure-9 Scatter plot of (Ca2+ + Mg2+) versus (SO2- + HCO) obtained from the analyzed groundwater samples Figure-10 Scatter plot of (Ca2+ + Mg2+) versus HCO obtained from the analyzed groundwater samples Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 9 Figure-11 Scatter plot of (Ca2+ + Mg2+) versus total cations obtained from the analyzed groundwater samples Figure-12 Scatter plot of (Na + K) versus total cations obtained from the analyzed groundwater samples Figure-13 Scatter plot of (Ca2+ + Mg2+)/HCO versus Cl obtained from the analyzed groundwater samples Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 10 Multivariate statistical analyses: AHCA performed on standardized dataset, to organize groundwater sampling sites into groups based on their spatial resemblance, generated four statistically significant clusters, figure-15. Accordingly, the resultant model effectively classified four groups based on developmental activities as industrial zone (group 1), organized residential zone (group 2), organized residential-cum-market zone (group 3) and unorganized residential zone (group 4) suggesting control of human-actions on groundwater quality. This investigation successfully established AHCA as a potent exploratory data analysis model which can be employed extensively for spatial classification and categorization of water resources and their management. As environmental management of freshwater resources requires constant monitoring and assessment, cluster analysis effectively reduces number of sampling sites recognizing some representative samples which could be suggestive enough to predict water quality of the whole area. Figure-14 Scatter plot of (SO2- + Cl) versus (Na + K) obtained from the analyzed groundwater samples Figure-15 AHCA as dendrogram displaying four spatially homogeneous groups of the groundwater sampling sites Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 11 PCA with VARIMAX rotation generated three principal components (PCs) together accounting for 90.63% of the variance in the hydrogeochemical dataset, table-3. PC1 loaded with Ca2+, Mg2+, HCO and SO2-, accounted 41.34% variance and represented silicate weathering. PC2, dominated with factor loadings of Na, K and Cl, accounted 40.20% of the variance and specified events of carbonate weathering along with cation-anion exchange reactions. Thus, PCA established occurrence of mixed weathering in aquifer systems of the area (also suggested by re-emergence of PC1 dominant ions in PC2). Exhibition of almost similar variance by PC1 and PC2 demonstrated that the groundwater chemistry of the area was overwhelmingly controlled by the behaviour of ions. However, Na, Cl and HCO along with Ca2+ were predominantly involved in controlling the ionic properties. Water classification evaluated through modeling Piper plot also confirmed this noted observation. Presence of TDS and its surrogate partner EC with relatively close and high factor loadings in both PC1 and PC2 suggested that in addition to underlying geology, some artificial factors also influenced groundwater chemistry of the Durgapur area. For examples, domestic water use causes elevation of the TDS concentration with the addition of salts, detergents and other household by-products; dissolution of minerals in the subsurface and a corresponding increase in the TDS level of the water can also occur from aerobic oxidation of domestic-waste effluent (which causes acidity)27. Contaminated artificial recharge water from large industrial complexes, such as downward migration of liquids discharged (from spills and inadequate control of wastes) onto the ground surface and leaching of unsheltered stockpiles of solid materials can also increase TDS concentration of the groundwater. Residential developments can also influence the water quality that recharges aquifers28. PC3 accounted 9.09% of the variance and displayed dominance of PO3-. As NO showed high loading in PC2 independent of PC3, and, since, PO3- and NO represent both inorganic and organic pollution load, mixing of polluted water with the sub-surface water from various sources, industrial, agricultural (application of chemical fertilizers) and domestic wastes (for example, domestic sewage), was likely to happen. PC3 having high loading of PO3- suggested its predominant presence in water from industrial and domestic outcomes. Conclusion The present investigation markedly demonstrated hydrogeochemical processes like weathering of rocks and exchange of ions between aquifer materials and the sub-surface water as well as human-made developmental activities influenced groundwater quality of the steel city Durgapur. Anthropogenic influence on groundwater chemistry, which emerged as a basic concern in this research work needs more detailed study by further increasing the sample size, including seasonal studies, and chemical parameters. The baseline information reported in this study is the first step in this direction. Moreover, studies on occurrence of trace elements in groundwater of the Durgapur subdivision should immediately be taken up. This communication also illustrated that hydrogeochemical analyses and multivariate statistical techniques together provide valuable insights into comprehensive characterization of the groundwater quality. Table-3 Rotated component matrix of PCA of the groundwater quality dataset Rotated Component 1 2 3 Na + 0.360 0.900 -0.039 K + -0.232 0.897 0.159 Ca 2+ 0.715 0.677 0.099 pH 0.906 -0.015 0.059 EC 0.641 0.755 0.010 TDS 0.626 0.759 0.102 HARD 0.817 0.420 0.281 Mg 2+ 0.692 0.000 0.376 HCO 3 2 - 0.962 -0.015 -0.032 NO 3 - -0.620 0.731 -0.128 PO 4 3 - 0.155 0.064 0.942 SO 4 2 - 0.755 0.604 0.066 Cl - 0.074 0.962 0.045 Eigenvalue 5.375 5.226 1.182 % of variance 41.34 40.20 9.09 Cumulative % 41.34 81.54 90.63 References 1.Central Pollution Control Board (CPCB)., Findings: Problem Areas, Chapter IV, Ministry of Environment and Forests, Government of India, http://www.cpcb.nic.in..... Chapter4. pdf, Accessed on 20.03.2013 (2013)2.Parihar S.S., Kumar A., Kumar A., Gupta R.N., Pathak M., Shrivastav A. and Pandey A.C., Physico-Chemical and Microbiological Analysis of Underground Water in and Around Gwalior City, MP, India, Res. J. Recent Sci.,1 (6), 62-65 (2012) 3.Kumar M., Kumari K., Singh U.K. and Ramanathan A.L., Hydrogeochemical Processes in the Groundwater Environment of Muktsar, Punjab: Conventional Graphical and Multivariate Statistical Approach, Environ. Geol., 57, 873-884 (2009)4.Bhardwaj V., Singh D.S. and Singh A.K., Hydrogeochemistry of Groundwater and Anthropogenic Control over Dolomitization Reactions in Alluvial Sediments of the Deoria district: Ganga plain, India, Environ. Earth Sci.,59, 1099-1109 (2010)5.Murhekar G.H., Assessment of Physico-Chemical Status of Ground Water Samples in Akot city, Res. J. Chem. Sci.,1 (4), 117-124 (2011)6.Deshpande S.M. and Aher K.R., Evaluation of Groundwater Quality and its Suitability for Drinking and Research Journal of Chemical Sciences ___________________________________________________________ ISSN 2231-606XVol. 4(6), 1-12, June (2014) Res. J. Chem. Sci. International Science Congress Association 12 Agriculture use in Parts of Vaijapur, District Aurangabad, MS, India, Res. J. Chem. Sci.,2 (1), 25-31 (2012)7.Wadhawan S.K., Base Document on Geosciences for Sustainable Development, Central Geological Programming Board, Geological Survey of India, Ministry of Mines, Government of India (2011)8.American Public Health Association (APHA)., Standard Methods for the Examination of Water and Wastewater, 21st Centennial Edition, APHA, AWWA, WEF, Washington DC, USA (2005)9.Manoj K., Ghosh S. and Padhy P.K., Characterization and Classification of Hydrochemistry using Multivariate Graphical and Hydrostatistical Techniques, Res. J. Chem. Sci., , 32-42 (2013)10.Landau S. and Everitt B.S., A Handbook of Statistical Analyses using SPSS, Chapman & Hall/CRC Press LLC, USA (2004)11.Praus P., Urban Water Quality Evaluation using Multivariate Analysis, Acta Montanistica Slovaca, 12 (2), 150-158 (2007) 12.Singh K.P., Malik A. and Sinha S., Water Quality Assessment and Apportionment of Pollution Sources of Gomti River (India) using Multivariate Statistical Techniques-A Case Study, Anal. Chim. Acta,538, 355-374 (2005) 13.Juahir H., Zain S.M., Yusoff M.K., Hanidza T.I.T., Armi A.S.M., Toriman M.E. and Mokhtar M., Spatial Water Quality Assessment of Langat River Basin (Malaysia) using Environmetric Techniques. Environ. Monit. Assess.,173, 625-641 (2011) 14.Bhattacharyya R., Manoj K. and Padhy P. K., Index Analysis, Graphical and Multivariate Statistical Approaches for Hydrochemical Characterization of Damodar River and its Canal System, Durgapur, West Bengal, India. Int. Res. J. Environment Sci., 2 (2), 53-62 (2013)15.Barai S.R. and Kumar S., Evaluation of the Physico-chemical Characteristics of River Varuna at Varanasi, India, J. Environ. Biol.,34, 259-265 (2013)16.World Health Organization (WHO)., Guidelines for Drinking-Water Quality, Vol 1, Recommendations, Geneva (1997)17.Bureau of Indian Standards (BIS)., Indian Standard Drinking Water Specification (second revision of IS: 10500), Manak Bhawan, New Delhi, India (2004) 18.Jayaprakash M., Nagarajan R., Muthusamy S., Gopal V., Viswam A. and Kalaivanan P., Groundwater Geochemistry of Neyveli Lignite Mine-Industrial Complex, Tamil Nadu, India and its Suitability for Irrigation, Int. J. Adv. Earth Sci. Eng.,, 27-42 (2012) 19.Senthilkumar M. and Elango L., Geochemical Processes Controlling the Groundwater Quality in Lower Palar River Basin, Southern India, J. Earth Syst. Sci., 122, 419-432 (2013)20.Schoeller H., Qualitative Evaluation of Groundwater Resources, In: Methods and Techniques of Groundwater Investigations and Development, UNESCO, 54–83 (1965)21.Aghazadeh N. and Mogaddam A.A., Investigation of Hydrochemical Characteristics of Groundwater in the Harzandat aquifer, Northwest of Iran, Environ. Monit. Assess.,176, 183-195 (2011)22.Kumar P.J.S. and James E.J., Physicochemical Parameters and their Sources in Groundwater in the Thirupathur Region, Tamil Nadu, South India, Appl. Water Sci.,, 219-228 (2013)23.Bhardwaj V. and Singh D.S., Surface and Groundwater Quality Characterization of Deoria District, Ganga plain, India, Environ. Earth Sci.,63, 383-395 (2011)24.Jankowski J. and Acworth R.I., Impact of Debris-flow Deposits on Hydrogeochemical Process and the Development of Dry Land Salinity in the Yass River Catchment, New South Wales, Australia, Hydrogeol J.,, 71-88 (1997)25.Meyback M., Global Chemical Weathering of Surficial Rocks Estimated from River Dissolved Loads, Am. J. Sci.,287, 401-428 (1987)26.Prasath B.B., Nandakumar R., Dinesh K.S., Ananth S., Shenbaga D.A., Jayalakshmi T., Raju P., Thiyagarajan M. and Santhanam P., Seasonal Variations in Physico-chemical Characteristics of Pond and Groundwater of Tiruchirapalli, India, J. Environ. Biol.,34, 529-537 (2013)27.Kresic N., Hydrogeology and Groundwater Modeling, 2ndEdition, CRC Press, Taylor and Francis group, Boca Raton, USA (2007) 28.Todd D.K. and Mays L.W., Groundwater Hydrology, 3rdEdition, Wiley India Pvt. Ltd., New Delhi, India (2012)