Arab J Geosci DOI 10.1007/s12517-013-0940-3
ORIGINAL PAPER
Assessment of hydrochemistry and groundwater quality in the coastal area of South Chennai, India P. J. Sajil Kumar & L. Elango & E. J. James
Received: 4 April 2012 / Accepted: 28 March 2013 # Saudi Society for Geosciences 2013
Abstract An attempt has been made to evaluate the water quality in the fast-growing coastal area of South Chennai. Groundwater samples were collected from selected locations and analyzed for major physico-chemical parameters. Experimental results show that the water has alkaline with pH varying from 7.2 to 8.2. Concentrations of Na and Cl were positively correlated with EC and elevated levels of these parameters near the coastal region, especially in the northern end of the study area, indicating the influence of seawater intrusion. Piper diagram identified Na–Cl as the dominant type of water in most of the samples. The presence of Ca–Cl facies in the groundwater suggests the possible ion exchange (Na with Ca) reaction in the aquifer. Molar ratios of Cl/HCO3 and Mg/Ca showed a higher value (>1) in many samples, which confirmed the influence of seawater intrusion on water quality. The Water Quality Index (WQI) of the study area ranged between 8 and 116, the highest recorded being at Thiruvanmiyur and the lowest at Muttukkadu. However, total hardness values show that 64% of the samples were hard or very hard in nature. The results of SAR, Na%, and PI show that majority of the samples are suitable for irrigation purposes. A comparison of spatial distribution maps of water quality parameters with those of WQI shows that groundwater quality has highly deteriorated in the Thiruvanmiyur region, located on the northeast part of theGood-quality water is found at the southeast part of the P. J. Sajil Kumar : E. J. James Water Institute, Karunya University, Coimbatore 641114, Tamil Nadu, India L. Elango Department of Geology, Anna University, Chennai 600025, Tamil Nadu, India Present Address: P. J. Sajil Kumar (*) Brandenburg Technical University (BTU), 03046 Cottbus, Germany e-mail:
[email protected]
study area, namely, Muttukkadu. This study indicates that urbanization and seawater intrusion have heavily affected the groundwater quality of South Chennai coastal area. Keywords Hydrochemistry . Groundwater quality . Water Quality Index (WQI) . Spatial distribution . South Chennai
Introduction Groundwater quantity and quality are equally important factors in the context of modern water management. Quality of water is mainly affected by pollution from different sources. Sectoral approaches divide the total available water, leading to scarcity. In the coastal area, the major cause for groundwater pollution is seawater intrusion. Over-exploitation is a severe problem that affects the potability of water. Hydrogeochemical processes are controlling factors of water chemistry. The present study was carried out in South Chennai area in order to analyze water quality. This area is sandwiched between Bay of Bengal and Buckingham canal. Seawater intrusion is reported from this area by various researchers (Gnanasundar and Elango 1999; Sathish et al. 2011). Chemical parameters such as major and minor ions are commonly used to identify the origin and related problems of water quality in areas affected by salinity in the coastal belt. Water quality of coastal aquifers is assessed using different methods. Some of the common methods used to study the water quality of aquifers include hydrogeochemical methods (Al-Taani 2012; Mustapha et al. 2012; Ravikumar and Somashekar 2011), geophysical investigations (Kashouty et al. 2012), and remote sensing with GIS (Ketata et al. 2012; Manap et al. 2012; Pradhan 2009; Pradhan and Pirasteh 2011). Among all these, geochemical method is one of the widely used. Fuzzy complex logic and geostatistics are relatively new techniques in the assessment of water quality (Adhikary et al. 2012; Lermontov et al. 2009; Sajil Kumar et al. 2011). Water Quality Index (WQI) is an effective tool to assess the state of an ecosystem, and this method is based on a group of
Arab J Geosci
physico-chemical and biological characteristics of water samples (Namibian 2007; Simoes et al. 2008). Water quality level can be directly represented by a single number, “index”, derived from a large number of variables (Sánchez et al. 2007; Bordalo et al. 2006). Elango et al. (1992) studied the groundwater quality in the coastal regions of Southern Madras and they have reported that Na and Cl are dominating the cation and anion chemistry. The major contaminant sources identified in this area were brine water in estuaries as well as liquid and solid wastes with Na and Cl as the dominant ions in the ground water. Alobaidy et al. (2010) applied WQI in Dokan Lake, Kurdistan region, Iraq, using ten water quality parameters. The study concluded that there is degradation in the quality of water from 1978 to 2009 and pointed out the need for effective monitoring. Ramakrishnaia et al. (2009) used water quality index to assess the groundwater quality of Tumkur taluk, Karnataka. WQI for these samples ranges from 89.21 to 660.56 and the analysis reveals that the groundwater of the area needs some degree of treatment before consumption. Vasanthavigar et al. (2010) assessed the water quality for human consumption using WQI method for the post- and pre-monsoon seasons in Thirumanimuttar river basin. They identified that the leaching of ions, over-exploitation of groundwater, direct discharge of effluents, and agrochemicals are responsible for the poor quality of water in the premonsoon season. Sisodia and Moundiotiya (2006) studied WQI for different seasons to evaluate the impact of industries, agriculture, and human activities on Kalakho Lake. This study reported that almost all of the stations exceeded the limit, which caused damage to lake ecology. Literature suggests that kriging and cokriging methods of geostatistics are useful for spatial distribution mapping. This tool is effectively used to predict the spatial distribution of chemical parameters of groundwater (Mehrjardi et al. 2008). Hydrochemical analysis can give the quality of the isolated patches only, but geostatistics can give the concentration of the unknown points as well. Heavy groundwater contamination was reported from South Chennai region after the tsunami incident in 2004 (Palanivelu et al. 2006). The present study was conducted with an objective to assess the current status of groundwater chemistry and water quality in the coastal area of South Chennai. Study area The present study was conducted along the South Chennai coastal aquifer (Fig. 1), which extends from Thiruvanmiyur in the north to Muttukkadu in the south. It covers an area of 20 km in length and 3 km in width. This area falls between 12°48′39.1″ and 12°59′25.9″ N latitude and 80°14′36.5″ and 80°15′398″ E longitude. This area is bounded by Bay of Bengal on the east, Buckingham canal on the west, and Aadyar River and Muttukkadu estuary on the north and south, respectively. In general, high salinity may be found
in all of these four water sources due to natural (seawater) and/or anthropogenic activities (Mondal et al. 2011).The elevation of this sandy aquifer ranges between 3 and 10 m from the MSL. The climate is tropical with a range in temperature of 24.3 to 41°C. The average annual rainfall of the area is 1,200 mm (1,978–2,008). The major rainy season is October–December, which occurs under the influence of north–east monsoon (CGWB 2008). The study area mainly constitutes alluvial deposits, interlayered clay, silt, sand, gravel, and pebble beds with thickness ranging from 10 to 24 m. This unconsolidated formation is underlined by charnockite of Proterozoic age. Above that alluvial soil, unconsolidated coarse-grained sand, gravels, pebbles, clay, and sandstone are found. The aquifer materials comprise of fine- to coarse-grained sand and small patches of clay lenses. Clay lenses were mostly deposited in fluvial or shallow marine environment. Aeolian dunes and beach sands of a few meters in depth are also found along the study area. The groundwater in the aquifer occurs in unconfined quaternary sediments with a shallow water table. Major water-bearing formations are the coastal sands. Water level fluctuation of 2.5 m in a year is recorded from the study area. Majority of the wells are tapping the recent quaternary aquifer, except a few wells that are slightly deeper and penetrated until the weathered charnockite. Aquifer gets replenished mainly by rainfall. Bay of Bengal forms a constant head at eastern boundary, whereas hydraulic conductivity (K) of South Chennai coastal aquifer ranges between 25 and 75 m/day and the specific yield ranges from 0.17 to 0.23.
Materials and methods A detailed field study was carried out in South Chennai coastal area during March 2008. Samples were collected from 25 wells situated at five sampling locations, namely, Thiruvanmiyur, Kottivakkam, Neelankarai, Injampakkam, and Muttukkadu. Five samples were collected from each location. The samples were collected during the pumping operation. Samples were collected in cleaned polythene bottles (500-ml capacity) and were properly labelled, indicating the source, date, and time of collection. Two samples were collected from each well for cation and anion analysis, in which samples for cations were acidified with concentrated HNO3. All of the samples were analyzed using standard procedures (APHA 1995). Electrical conductivity (EC) and pH were analyzed using a field kit. Major ions like chlorides, bicarbonates, calcium, and magnesium were analyzed using titration. Sodium and potassium were measured by a flame photometer. Sulfates were estimated by the UV–visible spectrophotometer. In general, ion balance error of the samples was observed below±5%. Water quality of the study area was analyzed by WQI, total hardness, SAR, and sodium percentage. The geostatistical analyst tool of ArcGIS 9.3 was used to create the spatial distribution map of different
Arab J Geosci Fig. 1 Location map of the study area
water quality parameters; statistical variations of the data are not considered in this operation, but in geostatistics, these statistical variations are effectively utilized to predict the unknown values from a limited number of known values. Spatial distribution maps of the groundwater quality parameters were created using geostatistics tool in ArcGIS. Geostatistics methods depend on both statistical and mathematical functions that include autocorrelation (Sajil Kumar et al. 2011). The basic assumption is that the sample points close to the unknown points will have more or less similar value. In this study, ordinary kriging was selected as the interpolation method. In kriging method, a semivariogram will be created and which will evaluate the average degree of dissimilarity between the unknown point and nearby known value. From the analysis of the experimental variogram, a suitable model (e.g., spherical, exponential) is fitted by weighted least squares,
and the parameters (e.g., range, nugget, and sill) are then used in the kriging procedure. Spherical model was showing best fit for the semivariogram for all the parameters. The ratio of nugget variance to sill was ranged between 0.14 and 0.29, indicating that strong to moderate spatial dependence.
Results and discussion Hyrogeochemistry The statistical summary of the analyzed parameters are presented in Table 1. Physical and chemical parameters of groundwater samples show a general saline enrichment along the direction of flow, with a marked increase in the concentration of TDS and major ions. These parameters are
Arab J Geosci Table 1 Statistical summary of the hydrochemical parameters All of the parameters are expressed in mg/l, except EC (which is in μs/cm); pH has no unit
Parameters
pH
EC
TDS
Ca2+
Mg+
Na+
K+
HCO3−
SO42−
Cl−
Min Max Mean
7.4 8.2 7.7
157 3,140 1,139
105 2,104 762.92
10 86 41.44
4.8 60 21.17
16 572 151.1
3.8 133 20.8
26 519 161.7
9.5 207 57.5
16 637 152
indicative of some of the hydrogeochemical processes such as dissolution, evaporation, reversible ion exchange process, precipitation, etc. The physical parameters measured in the present study are EC, TDS, and pH. These parameters are prone to change their concentrations with other environmental conditions. The EC of groundwater samples from South Chennai coastal aquifer varies between 157 and 3,140 μS/cm. It shows an increasing trend towards the coast and also towards the Buckingham canal. The higher EC towards coast than the central part of the aquifer may be due to the seawater intrusion. On the other hand, Buckingham canal is a small stream contaminated with urban and industrial wastes. This may be the reason for the increasing trend of EC towards both of these directions. The highest EC is recorded in Neelankarai, which is near to Buckingham canal. Almost 88% of the samples show EC values less than 2,000 μS/cm. TDS is one of the parameters used to understand the amount of contaminant present in the groundwater which is directly proportional to EC. TDS is calculated by multiplying the EC with 0.64. It ranged from 105 to 2,104 mg/l. High concentration of TDS in the Thiruvanmiyur coastal region suggests the probability of saline enrichment from seawater due to the overexploitation by urbanization. The quality and types of matter dissolved depend on the chemical composition and physical structure of rock as well as the hydrogen ion concentration, pH. The pH of the ground water samples ranged from 7.4 to 8.5, indicating an alkaline nature. Sodium is the major ion dominant in the cation chemistry. Its concentration generally increases from the south to the northeast. The maximum concentration (572 mg/l) is recorded at Neelankarai, the central part of the study area, and the minimum (16 mg/l) is at Injampakkam. Higher Na can be due to silicate weathering, dissolution of halites, and also over-exploitation of coastal regions (Hem 1985). The calcium content of the groundwater samples varies from 10 to 86 mg/l. The origin of calcium may be due to the dissolution of precipitates of CaCO3 and CaMg(CO3)2 during recharge (Lakshmanan et al. 2003). The maximum concentration of calcium is recorded from Kottivakkam area. In the case of magnesium, concentration varies from 4.8 to 60 mg/l. Water hardness mainly depends on the presence of cations such as calcium and magnesium. Generally, the sources of magnesium are dissolution of dolomites and silicate weathering. However, in the coastal areas, higher Mg content in the seawater might be a reason for elevated Mg concentration in groundwater due to saline intrusion. Potassium originated from the weathering of
the potash feldspar and the clay minerals from the aquifer matrix. The minimum and maximum concentrations vary between 3.8 and 133 mg/l. Eighty-four percent of the samples show the potassium concentration to be less than 20 mg/l. The order of dominance of cations in the groundwater was Na>Ca>Mg>K in majority of the samples, indicating the effect of seawater intrusion into the freshwater aquifer. The series shows that, in all types, Na is the dominant cation, followed by calcium and magnesium. This shows that overall contribution to the hydrochemistry would have come primarily from seawater intrusion and secondarily from geological formations. The carbonate and bicarbonate analyses show that the carbonate is totally absent in this area. The concentration of the bicarbonate varies from 26 to 519 mg/l. Chloride is the dominant anion present in the study area with a range from 16 to 691 mg/l. The maximum concentration is found along the coastal side of Thiruvanmiyur. The origins of chloride are soil, infiltrated seawater, wind-blown sea salt precipitation, and industrial and domestic wastes. As the mineral content increases, the chlorine content also increases. Sulfate content of the study area varies from 9.5 to 207 mg/l, and the maximum concentration is found from Thiruvanmiyur. It should be from action of leaching and anthropogenic activities. Cl> HCO3 >SO4 type represents the major anions for 68% of total water samples analyzed. HCO3 >Cl>SO4 and Cl>SO4 > HCO3 constitutes 20 and 12%, respectively. Anion analysis again proved the control of seawater intrusion and subsurface geology for the high percentages of chloride and bicarbonate. Dominant reactions and the geochemical process that controls the groundwater chemistry can be identified using molar ratios of ions. In general, HCO3 in groundwater systems represents freshwater, whereas Cl concentration is largely controlled by the seawater in the coastal regions. A positive correlation was observed for Cl and HCO3 with TDS in a few samples (Fig. 2a, b). This is showing the contribution of these ions to the total ions. Many samples showed a linear increment for Na and Cl; this is suggesting that several samples are affected by seawater intrusion (see Fig. 2c). Molar ratios of Cl/HCO3 showed that 13 samples out of 25 have a ratio higher than 1 (see Fig. 2d), suggesting an elevated Cl concentration over HCO3. Moreover, Mg/Ca ratio was also used to evaluate the groundwater chemistry. As the seawater has higher Mg concentration than Ca, those wells influenced by seawater will have Mg/Ca ratio higher than 1. In the study area, nine samples out of 25 showed
Arab J Geosci
a
b 20
10
HCO3 (meq/l)
Cl (meq/l)
15 10 5 0
8 6 4 2 0
0
500
1000
1500
2000
0
2500
1000
TDS (mg/l)
c
d
30
3000
100
Cl/HCO3
Ionic Ratio
25
Cl (meq/l)
2000
TDS (mg/l)
20 15 10
Mg/Ca
10
1
5 0
0.1 0
5
10
15
20
Na (meq/l)
1
3
5
7
9 11 13 15 17 19 21 23 25
Sample No
Fig. 2 a Relation between EC and Cl. b EC and HCO3. c Na and Cl. d Ionic ratios of Cl/HCO3 and Mg/Ca
Mg/Ca ratio more than 1 (see Fig. 2d), suggesting that seawater intrusion has taken place into the aquifer. Hydrogeochemical facies The chemical processes and the evolution of the groundwater in the aquifers due to the residence and the flow may be evaluated using the hydrochemical facies. This can be well interpreted by drawing the Hill Piper plot (Piper 1953). The results show that most of the samples belong to mixed Na–Cl type. Calcium and magnesium do not have much contribution to the overall water type. Thiruvanmiyur area falls well within the sodium and potassium type. Other representations come from mixed Ca–Mg–Cl, mixed Ca– Na–HCO3, Ca–Cl, and Ca–HCO3 types. The origin of Cl in groundwater may be attributed to the Na–Cl-rich seawater encroachment to the aquifer. However, the change from NaCl to Ca–Mg–Cl type groundwater may be due to the cation exchange reaction. This can be better explained by calculating chloro alkaline indices (CAI 1 and CAI 2) as suggested by Schoeller (1965). CAI I ¼ ½C1 ðNaþ þ K þ Þ=C1
When there is an exchange between Ca or Mg in the groundwater with Na and K in the aquifer material, both of these indices are negative, and if there is a reverse-ion exchange, then both of these indices will be positive (Schoeller 1965, 1967). In this study, majority of the samples showed a negative value for Chloro Alkaline Indices, showing that reverse-ion exchange is a prominent reaction that controls the hydrogeochemistry. In the reverse-
ð1Þ
CAI II ¼ ½C1 ðNaþ þ K þ Þ=ðSO4 þ HCO3 þCO3 þ NO3 Þð2Þ
Fig. 3 Piper diagram showing the hydrogeochemical facies of groundwater samples
Arab J Geosci 100000 Evaporation dominance
TDS (mg/L)
10000
1000
Rock dominance
100
10
1 0.00
Precipitation dominance
0.20
0.40
0.60
0.80
1.00
Na+K/ (Na+K+Ca) Fig. 4 Gibbs plot showing mechanisms controlling the groundwater chemistry of the study area
ion exchange processes, Na and Cl, which are exchanged to the aquifer during the seawater intrusion in the summer season, were taken into the solution by the Ca–Mgrich groundwater as a consequence of aquifer freshening by the monsoon rain. Piper diagram (Fig. 3) shows that alkalis (Na and K) exceed alkaline earths (Ca and Mg), and strong acids (Cl and SO 4 ) exceed weak acids (HCO3). A number of processes other than ion exchange may be encountered during the subsurface movement of groundwater. The most logical method to identify the common processes such as evaporation, rock dominance, and precipitation is Gibbs plot (Gibbs 1970). This plot of the study area shows that rock–water interaction is the dominant process that controls the groundwater chemistry (see Fig. 4). However, few samples fall
Fig. 5 a Spatial distribution of EC (a), HCO3 (b), Cl (c) in the groundwater samples. b Spatial distribution of SO4 (d), Ca (e), and Mg (f) in the groundwater samples. c Spatial distribution of Na (g) and K (h) in the groundwater samples
Arab J Geosci
Fig. 5 (continued)
near the evaporation and precipitation dominant zone in the same plot. Since the study area is located in the east coast of India, higher Na concentration in the precipitationdominant zones is clearly representing the coastal precipitation (rich in Na–Cl). Spatial variation of major ions The spatial distribution of concentration of selected cations and anions is given in Fig. 5a–c. Ions were selected according to the relative importance of their influence on the quality of water. Spherical semivariogram models were best fitted for all the water quality parameters. A detailed description of the semivariogram parameters and means square error (MSE) is presented in Table 2. All the ions increase towards the seaside and also Buckingham canal.
EC, Na, and Cl show higher concentrations in the northern and the central part of the aquifer. It clearly shows the seawater intrusion into that part of the aquifer. Northern and central parts of the aquifer constitute the urban areas of Chennai City. The population is denser in these parts of the study area than the southern part. This increases the demand of water and leads to overexploitation of groundwater. This over-exploitation result in seawater encroachment and this trend is clearly observed in the concentration of ions like sodium and chloride. Calcium shows a different trend and it has a relatively less concentration in the northern part of the aquifer. This can be explained by the fact that seawater has a relatively less concentration of calcium. Seawater samples from Bay of Bengal near the study area analyzed by Gurumoorthy et al. (2004) provided that the
Arab J Geosci
Fig. 5 (continued)
concentration of Ca is 238 mg/L against Na at 13,572 mg/L and Mg at 918 mg/L. Application of the WQI WQI is defined as a technique of rating that provides the composite influence of individual water quality parameters on the overall quality of water for human consumption (Mitra 1998). For this purpose, ten water quality parameters have been selected. Parameter consideration to develop a WQI depends on the purpose for which water is used. Parameters were selected according to the availability of data as well as their relative importance in defining water quality for human consumption. The standards set for this purpose is according to the WHO guidelines (WHO 1984). Calculation of WQI starts with assigning weights to the measured parameters based on their relative importance. The maximum weight of 5 was assigned to parameters like sodium, chloride, TDS, and sulfate because of their importance in water quality assessments. A less weight
of 1 is given to bicarbonate since it plays a comparatively less significant role in water quality assessment (Srinivasamoorthy et al. 2008; Vasanthavigar et al. 2010). In the second step, relative weights (Rwi) were calculated using the equation 1. Awi Rwi ¼ P n 1 Awi
ð1Þ
where Rwi is the relative weight, Awi is the assigned weight of each parameter, and n is the number of parameters. The calculated relative weights (Rwi) of each parameter and water quality standards are given in Table 2. Quality rating for each parameter was calculated by dividing their concentration with respective water quality standards (BIS Bureau of Indian Standards 10500 1991); this value is multiplied by 100 and given in Eq. 2: Qi ¼ ðCi =Si Þ 100
ð2Þ
where Qi is the quality rating, Ci is the concentration of specific chemical parameter in each water sample (mg/l), and Si is the
Arab J Geosci Table 2 Summary of semivariogram parameters and error statistics for water quality parameters Parameter
Number of samples
Best fit model
Nugget, C0
Sill, C0 +C
R2
RSS
MSE
EC HCO3 Cl SO4 Ca Mg Na K
25 25 25 25 25 25 25 25
Spherical Spherical Spherical Spherical Spherical Spherical Spherical Spherical
0.71 0.69 0.76 0.59 0.16 0.25 0.79 0.061
1.96 1.35 1.81 1.03 0.81 0.72 1.91 0.31
0.914 0.813 0.936 0.757 0.102 0.093 9.632 0.562
0.016 0.032 0.025 0.056 0.013 0.009 0.029 0.012
0.213 0.162 0.145 0.075 0.165 0.325 0.269 0.413
WQI
25
Spherical
0.73
1.63
0.896
0.0156
0.156
Indian drinking water standard for each chemical parameter (mg/l) (BIS Bureau of Indian Standards 10500 1991). The subindex for each parameter is determined and WQI is calculated from Eqs. 3 and 4: SIi ¼ Wi Qi WQI ¼
X
ð3Þ ð4Þ
SIi
where SIi is the sub-index of ith parameter, Qi is the rating based on the concentration of ith parameter, and n is the number of parameters. Classification of water based on the WQI values is given in Table 3. The water quality index of South Chennai coastal aquifer is ranged from 8 to 116. A spatial distribution map of WQI of the groundwater in the study area is presented in Fig. 6. Higher values are recorded at Thiruvanmiyur area and the values decrease towards the southern side of the aquifer, namely, Muttukkadu. This is exactly following the trend of EC and other dominant cations and anions. WQI model is taking into account of a group of water quality parameters and will be more accurate and representative of the groundwater quality in the study area. According to WQI classification, 68% of the samples represent excellent Table 3 Drinking water quality standards of WHO and BIS with assigned weights for quality parameters
Parameters used
water quality, 28% good water quality, and 4% poor water quality. Total hardness Hardness of water is defined as its content of metallic ion which reacts with sodium soaps to produce solid soaps or scummy residue and have been reacted with negative ion, when the water is evaporated in boilers, to produce solid boiler scale. Hard water is unsuitable for domestic purposes. Normally, hardness is expressed as the total concentration of Ca2+ and Mg2+ (mg/l) equivalent to CaCO3. Hardness can be temporary or permanent. Temporary hardness is mainly due to the presence of calcium carbonate and is removed by boiling the water. Presence of calcium, magnesium chlorides, and sulfates is responsible for permanent hardness and can be treated with ion exchange process. Total hardness is determined by substituting the concentration of Ca2+ and Mg2+ (mg/l) as expressed in Eq. 5: ð5Þ Total hardness ¼ 2:497 Ca2þ þ 4:115 Mg2þ Classification of water based on hardness (Sawyer and McCarthy 1967) is described in Table 4. Total hardness Relative weight P
Indian standard (BIS Bureau of Indian Standards 10500 1991) (permissible limit)
WHO standards (permissible limit)
Assigned weight (Awi)
ðRw Þ ¼ Awi
pH
6.5–8.5
7–8
1
0.0333
TDS
500
1,000
5
0.1667
Bicarbonate (mg/l)
–
–
1
0.0333
Chloride (mg/l)
250
250
5
0.1667
Sulfate (mg/l)
200
250
5
0.1667
Calcium (mg/l)
75
75
3
0.1000
Magnesium (mg/l)
30
30
3
0.1000
Sodium (mg/l)
–
200
5
0.1667
Potassium (mg/l)
2
P
0.0667 i Awi
¼ 30
P
i Rwi
¼1
n 1 Awi
Arab J Geosci
Sodium adsorption ratio Sodium adsorption ratio (SAR) is a measurement of the ratio of sodium (Na+) ions to calcium (Ca2+) and magnesium (Mg2+) ions, expressed in meq/1. This is calculated by Eq. 6: p SAR ¼ Naþ = 1=2 Ca2þ þ Mg2þ ð6Þ The values of SAR in excess of 9 indicate that there is a medium or high sodium or low calcium plus magnesium content in the groundwater. If this kind of water is used in irrigation, it can cause the dispersion of soil colloids, destroying soil texture and permeability. This produces conditions similar to droughts. Prolonged exposure of soil to high SAR groundwater can render large tracts of land not suitable for agriculture (Younger and Casey 2003). In the study area, 16% of the samples show SAR values more than 10 and other samples show low sodium hazard (Table 5). Wilcox diagram (Wilcox 1955) is a useful representation of sodium alkalinity hazards. Based on this plot (Fig. 7), most of the samples are falling under C3S1 category. The rest of the samples are falling under C3S4 and C3S3 categories. A relatively high salinity hazard is found at Thiruvanmiyur and Neelankarai areas. Samples from Muttukkadu area fall under permissible range with less salinity hazard. Higher sodicity hazard is well correlated with higher population in the urban part (Thiruvanmiyur and Neelankarai) of the aquifer. Higher demand for water in these regions results in over-exploitation and subsequent seawater intrusion, which may increase the Na content in groundwater. However, Muttukad region is a rural area located away from the city, so the water demand is less. Sodium percentage (Na %) and permeability index Fig. 6 Spatial distribution of WQI of groundwater samples
varied between 65 and 383 mg/l, with 64% of samples placed in the hard or very hard water category in the study area. The rest of them fall under moderate or soft water category. The origin of total hardness is mainly due to the dissolution of carbonate minerals such as calcium and magnesium. Table 4 Classification of groundwater based on WQI WQI range
Type of water
% of samples
Sample numbers Rest of the samples 2, 6, 13, 15, 16, 18, 20 – – –
300
Poor water Very poor water Water unsuitable for drinking
4 – –
The sodium in irrigation waters is usually denoted as per cent sodium and can be determined using the Eq. 7: Na% ¼ ðNaþ Þ 100= Ca2þ þ Mg2þ þ Naþ þ Kþ ð7Þ where the quantity of Ca 2+ , Mg 2+ , Na + , and K + are expressed in milliequivalent per liter (epm). In water having a high concentration of bicarbonate, there is a tendency for calcium and magnesium to precipitate as the water in the soil is more concentrated. As a result, the relative proportion Table 5 Classification of groundwater based on hardness Total hardness (mg/l)
Water class
% of samples
Sample numbers
0–75 75–150 150–300
Soft Moderate Hard
12 24 52
>300
Very hard
12
23, 24, 25 4, 5, 10, 16, 21, 22 1–3, 6–8, 9, 11–14, 17, 19 15, 18, 20
Arab J Geosci Fig. 7 Wilcox diagram for groundwater samples
of sodium in the water is increased in the form of sodium carbonate (Sadashivaiah et al. 2008). When the percentage of sodium exceeds the permissible limit, the permeability of water reduces and causes damage to the crops. The majority of samples (72%) from the study area fall under permissible category, 12% of the samples were doubtful, and 16% of the samples show sodium percentage above 80 and are classified as unsuitable (see Table 6). In addition to sodium percentage (Na %), Permeability Index (PI) was calculated for the groundwater. Ragunath (1987) defined a formula for the calculation of permeability index using Na, Ca, Mg, and HCO3 (see Eq. 8). p ð8Þ PI ¼ Naþ þ HCO3 100= Ca2þ þ Mg2þ þ Naþ The PI values in groundwater of the study area ranges from 7 to 35%. This result suggests that all of the samples were suitable for irrigation purposes. A slight deviation from the results of Na% was observed. This may be attributed to the incorporation of HCO3 to the equation for PI.
Conclusions This paper presents the groundwater quality assessment carried out for the coastal area of southern Chennai.
Results show that the composition of groundwater is largely affected by seawater intrusion, especially in the northeast part. Na and Cl were the dominating cations and anions in wells near the coast, which is also evident from the Na–Cl facies observed in majority of the samples. An increase in Na and Cl have been observed with EC; this trend was prominent in samples which are collected near the coast (east) as well as Buckingham canal (west), a small stream contaminated with urban and industrial wastes. Ionic ratios of Cl/HCO3 and Mg/Ca were more than 1, many samples of which were collected near the coast, indicating the influence of seawater on hydrochemistry. The bulk of the samples that was plotted in the rock–water interaction field in Gibbs plot shows that instead of direct groundwater–seawater mixing, cation exchange is the dominant process that controls the source of Na. Negative values for the chloro alkaline indices (reverse-ion exchange) and the presence of Ca–Cl facies support this argument and subsequently the occurrence of seawater intrusion. The results of WQI show that 96% of the groundwater samples were either excellent or good for drinking purposes. However, many samples remain hard throughout the study area. Spatial distribution maps of major ions and WQI show that groundwater quality is substantially deteriorated in the northern side of the aquifer Table 7 Classification of groundwater based on the sodium percentage
Table 6 Classification of groundwater based on SAR SAR
Sodium hazard class
Water class
% of samples
Sample numbers
26
S2 S3 S4
Good Doubtful Unsuitable
16 0 0
Rest of the samples 1, 13, 16, 23 – –
Sodium %
Water class
% of samples
Sample numbers
< 20 20–40 40–60
Excellent Good Permissible
4 8 60
60–80 >80
Doubtful Unsuitable
12 16
18 22, 25 2–5, 8–12, 14, 15, 19–21, 24 6, 7, 17 13, 16, 21, 23
Arab J Geosci
(Thiruvanmiyur), whereas good quality water is found in the southern part (Muttukad). This contrast in hydrochemistry is attributed to the heavy population due to urbanization in the northern side and subsequent over-exploitation of groundwater. However, irrigation indices (SAR, Na%, and PI) show that groundwater samples were generally suitable for agricultural purposes.
References Adhikary PP, Dash CJ, Chandrasekharan H, Rajput TBS, Dubey SK (2012) Evaluation of groundwater quality for irrigation and drinking using GIS and geostatistics in a peri-urban area of Delhi, India. Arab J Geosci 5:1423–1434 Alobaidy AHMJ, Abid HS, Maulood BK (2010) Application of Water Quality Index for assessment of Dokan Lake ecosystem, Kurdistan Region, Iraq. J Water Res Prot 2:792–798 Al-Taani AA (2012) Seasonal variations in water quality of Al-Wehda Dam north of Jordan and water suitability for irrigation in summer. Arab J Geosci. doi:10.1007/s12517-011-0428-y APHA (1995) Standard methods for the examination of water and waste water (APHA) BIS (Bureau of Indian Standards) 10500 (1991) Indian Standard drinking water-specification. 1st rev pp. 1–8 Bordalo AA, Teixeira R, Wiebe WJ (2006) A Water Quality Index applied to an international shared river basin: the case of Douro River. Environ Manag 38:910–920 CGWB (2008) District groundwater brochure, Chennai,Tamil Nadu. Technical report series Elango L, Ramachandran S, Choudary YSN (1992) Ground water quality in coastal region of South Madras. Indian J Environ Health 34:318–325 Gibbs RJ (1970) Mechanisms controlling world water chemistry. Sci J 170:795–840 Gnanasundar D, Elango L (1999) Groundwater quality assessment of a coastal aquifer using geoelectrical techniques. J Environ Hydrol 7:21–33 Gurumoorthy C, Sasidhar P, Arunugham V, Nathur RK (2004) Subsurface investigations on deep saline ground water of charnokite rock formation, Kalpakkam, India. Environ Monit Assess 91: 211–222 Hem JD (1985) Study and interpretation of chemical characteristics of natural water. US Geological Survey, Water Supply Paper No. 2254 Kashouty ME, Aziz AA, Soliman M, Mesbah H (2012) Hydrogeophysical investigation of groundwater potential in the El Bawiti, Northern Bahariya Oasis, Western Desert, Egypt. Arab J Geosci 5:953– 970 Ketata M, Gueddari M, Bouhlila R (2012) Use of geographical information system and water quality index to assess groundwater quality in El Khairat deep aquifer (Enfidha, Central East Tunisia). Arab J Geosci 5:1379–1390 Lakshmanan E, Kannan K, Senthil Kumar M (2003) Major ion chemistry and identification of hydrogeochemical process of groundwater in part of Kancheepuram district, Tamilnadu, India. J Environ Geosci 10:157–166 Lermontov A, Yokoyama L, Lermontov M, Machado MAS (2009) River quality analysis using fuzzy water quality index: Ribeira do Iguape river watershed, Brazil. Ecol Indic 9:1188–1197 Manap MA, Sulaiman WNA, Ramli MF, Pradhan B, Surip N (2012) A knowledge driven GIS modelling technique for prediction of
groundwater potential zones at the Upper Langat Basin, Malaysia. Arab J Geosci. doi:10.1007/s12517-011-0469-2 Mehrjardi TR, Jahromi ZM, Mahmodi SHA (2008) Spatial distribution of groundwater quality with geostatistics (case study: YazdArdakan Plain). World Appl Sci J 4:9–17 Mitra BK (1998) Spatial and temporal variation of ground water quality in sand dune area of Aomori prefecture in Japan. Paper number 062023, 2006 ASAE annual meeting Mondal NC, Singh VS, SaxenaVK SVP (2011) Assessment of seawater impact using major hydrochemical ions: a case study from Sadras, Tamilnadu, India. Environ Monit Assess 177:315– 335 Mustapha A, Aris AZ, Juahir H, Ramli MF (2012) Surface water quality contamination source apportionment and physicochemical characterization at the upper section of the Jakara Basin, Nigeria. Arab J Geosci. doi:10.1007/s12517-012-0731-2 Namibian M (2007) A new Water Quality Index for environmental contamination contributed by mineral processing: a case study of Amang (tin tailing) processing activity. J Appl Sci 7:2977– 2987 Palanivelu K, Priya MN, Selvan AM, Natesan U (2006) Water quality assessment in the tsunami-affected coastal areas of Chennai. Curr Sci 91:5 Piper AM (1953) A graphic procedure in the geo-chemical interpretation of water analysis. USGS Groundwater Note No. 12 Pradhan B (2009) Ground water potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Cent Eur J Geosci 1:120–129 Pradhan B, Pirasteh S (2011) Hydro-chemical analysis of the ground water of the Basaltic catchments: upper Bhatsai Region, Maharastra. Open Hydrol J 5:51–57 Ragunath HM (1987) Groundwater. WileyEastern Ltd, New Delhi, pp 563 Ramakrishnaiah CR, Sadashivaiah C, Ranganna G (2009) Assessment of Water Quality Index for the groundwater in Tumkur Taluk, Karnataka State, India. E-J Chem 6:523–530 Ravikumar P, Somashekar RK (2011) A geochemical assessment of coastal groundwater quality in the Varahi river basin, Udupi District, Karnataka State, India. Arab J Geosci. doi:10.1007/s12517-011-0470-9 Sadashivaiah C, Ramakrishnaiah CR, Ranganna G (2008) Hydrochemical analysis and evaluation of groundwater quality inTumkur Taluk, Karnataka State, India. Int J Environ Res Public Health 5:158– 164 Sajil Kumar PJ, Jegathambal P, James EJ (2011) Multivariate and geostatistical analysis of groundwater quality in Palar river basin. Int J Geol 5:108–119 Sánchez E, Colmenarejo MF, Vicente J, Rubio A, García MG, Travieso L, Borja R (2007) Use of the Water Quality Index and dissolved oxygen deficit as simple indicators of watershed pollution. Ecol Indic 7:315–328 Sathish S, Elango L, Rajesh R, Sarma VS (2011) Assessment of seawater mixing in a coastal aquifer by high resolution electrical resistivity tomography. Int J Environ Sci Tech 8:483–492 Sawyer GN, McCarthy DL (1967) Chemistry of sanitary Engineers, 2nd edn. McGraw Hill, New York, p 518 Schoeller H (1965) Qualitative evaluation of groundwater resources. In Methods and techniques of groundwater investigations and development (pp. 54–83). UNESCO Schoeller H (1967) Geochemistry of groundwater—an international guide for research and practice (Chap. 15, pp. 1–18). UNESCO Simoes FS, Moreira AB, Bisinoti MC, Gimenez SMN, Yabe MJS (2008) Water Quality Index as a simple indicator of aquaculture effects on aquatic bodies. Ecol Indic 8:476–484 Sisodia R, Moundiotiya C (2006) Assessment of the water quality index of wetland Kalakho lake, Rajasthan, India. J Environ Hydrol 14:1– 11
Arab J Geosci Srinivasamoorthy K, Chidambaram M, Prasanna MV, Vasanthavigar M, John Peter A, Anandhan P (2008) Identification of major sources controlling Groundwater Chemistry from a hard rock terrain—a case study from Mettur taluk, Salem district, Tamilnadu, India. J Earth Syst Sci 117:49–58 Vasanthavigar M, Srinivasamoorthy K, Vijayaragavan K, Rajiv Ganthi R, Chidambaram S, Anandhan P, Manivannan R, Vasudevan S (2010) Application of water quality index for groundwater quality
assessment: Thirumanimuttar sub-basin, Tamilnadu, India. Environ Monit Assess. doi:10.1007/s10661-009-1302-1 WHO (1984) Guidelines for drinking water quality V.1 Recommendations. Switzerland: Geneva pp. 130 Wilcox LV (1955) Classification and use of irrigation water. US Geol Dep Agri Arc 969:19 Younger P, Casey V (2003) A simple method for determining the suitability of brackish groundwaters for irrigation. Waterlines 22:11–13
