Environ Geol (2009) 57:873–884 DOI 10.1007/s00254-008-1367-0
ORIGINAL ARTICLE
Hydrogeochemical processes in the groundwater environment of Muktsar, Punjab: conventional graphical and multivariate statistical approach Manish Kumar Æ Kalpana Kumari Æ Umesh Kumar Singh Æ AL. Ramanathan
Received: 30 August 2007 / Accepted: 3 May 2008 / Published online: 21 May 2008 Ó Springer-Verlag 2008
Abstract Understanding the hydrogeochemical processes that govern groundwater quality is important for sustainable management of the water resource. A study with the objective of identifying the hydro-geochemical processes and their relation with existing quality of groundwater was carried out in an intensively cultivated district of Punjab, India. The study approach includes conventional graphical plots and multivariate analysis of the hydrochemical data to define the geochemical evaluation of aquifer system based on the ionic constituents, water types, hydrochemical facies and factors controlling groundwater quality. The results suggest that different natural hydrogeochemical processes like simple dissolution, mixing, weathering of carbonate minerals locally known as ‘‘kankar’’ silicate weathering and ion exchange are the key factors in the pre-monsoon, which was superseded by leaching processes loaded with anthropogenic inputs in the post-monsoon. Limited reverse ion exchange has been noticed at few locations of the study area especially in pre-monsoon periods. There was a significant effect of monsoon observed in terms of hardness and the significant amount of area with temporary hardness (Ca2+–Mg2+–HCO-3 type) in the pre-monsoon switched to permanent hardness domain, i.e. (Ca2+–Mg2+–Cl- type) by the post-monsoon. At most, factor analyses substantiate the findings of conventional graphical plots and provide
M. Kumar K. Kumari U. K. Singh AL. Ramanathan School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110067, India M. Kumar (&) Department of Urban Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku 113-8656, Japan e-mail:
[email protected]
greater confidence in data-interpretation. Thus, the study highlights the descriptive capabilities of conventional and multivariate techniques as effective tools in groundwater evaluation. Keywords Groundwater quality Ion-exchange Factor analysis Weathering Punjab
Introduction The hydrogeochemical processes help to get an insight into the contributions of rock-water interaction and anthropogenic influences on groundwater quality. These geochemical processes are responsible for the seasonal and spatial variations in groundwater chemistry (Matthess 1982; Kumar et al. 2006). Groundwater chemically evolves by interacting with aquifer minerals or internal mixing among different groundwater along flow-paths in the subsurface (Domenico 1972; Wallick and Toth 1976; Toth 1984). Schuh et al. (1997) indicated that increase in solute concentrations in the groundwater were caused by spatially variable recharge, governed by microtopographic controls. Further, the weathering of primary and secondary minerals is also contributing cations and silica in the system (Freeze and Cherry 1979; Jacks 1973; Bartarya 1993). Multivariate analysis, such as factor analysis is used simply as a numerical method of discovering variables that are more important than other data for representing parameter variation or demonstrating hydrochemical processes. This technique helps to simplify and organize data set in order to make useful generalizations and insight. It relies on a set of assumptions about the nature of the present population from which samples are drawn. These assumptions provide the rationale for the operations that
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are performed, and the manner in which the results are interpreted (Klovan 1975; Ashley and Llyod 1978; Singh et al. 2007). In many parts of India, especially in the arid- and semi-arid regions, due to vagaries of monsoon and scarcity of surface water, dependence on groundwater resource has increased tremendously in recent years. India supports more than 16% of the world’s population with only 4% of the world’s fresh water resources (Singh 2003). The total area cultivated in India using groundwater has increased from 6.5 million hectare in 1951 to 35.38 million hectare in 1993 (GWREC 1997; Kumar et al. 2007). About 94% of the total sown area in Punjab is irrigated, out of which 61.6% is irrigated by tube wells and 38.3% by canals (Singh 1983; Kumar et al. 2007). There are very few studies reported on the groundwater quality scenario in most cultivated state of India, i.e. Punjab. In our previous study, we have compared the two districts of Punjab on the basis of their groundwater quality and its suitability for irrigation and drinking purposes, which revealed that the present status of groundwater in Muktsar is in deteriorating stage (Kumar et al. 2007). Henceforth, the identifications of hydrogeochemical processes is the next step towards the sustainable management and development of water resources in the area, which lack surface water as no river flowing through the district. In the present study, a detailed investigation was carried out with the objectives to define hydrogeochemical processes controlling groundwater quality based on major ion chemistry, conventional graphical plots, multivariate statistical analysis and the seasonal variations of groundwater quality in the study area.
Study area Muktsar district is located in the south-western part of Punjab and lies between north 29°540 2000 and 30°40 2000 lattitude and east 74°1500 and 74°1900 longitude. Geomorphologically, the area is a vast stretch of old and recent alluvium of Quaternary age as modified by orogenic processes associated with fluviatile action. The area has been divided into two major geomorphic units viz. Alluvial plain and Palaeo channels/Sand dune complexes (Fig. 1). Alluvial plain constitute the major part of study area. This unit is formed by the alluvial deposits brought by Satluj River (Wadia 1981). These deposits consist of sand, silt, clay, and kankar. This unit is further subdivided into three sub-units: (a) Upper alluvial plain composed of massive beds of clay and fine to coarse grained sand. The yellowish impervious clay/sticky clay locally known as pandoo occur below the intermediate horizon of soil and
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Fig. 1 Sampling location and geomorphology of Muktsar District
kankar. (b) Alluvial Plain with good moisture or water logged and (c) alluvial plain with salt encrustations consisting clay, sticky clay (pandoo) and fine grained sand. Pandoo helps in confining the water under artesian conditions, obstructing the drainage of the soil. This leads to the accumulation of sodium and magnesium salts and thus giving rise to salt encrustations at the surface and rendering the soil infertile. In these soils the basic cations are Ca2+ and Mg2+ and the distribution of calcium carbonate suggest different degree of carbonate leaching (Sharma et al. 1998; Kumar et al. 2007). The most striking calcite accumulations occur as nodules. On the basis of their morphology, two kinds of such nodules could be recognized in the field, viz. (a) whitish, soft, diffuse, rather small in size and (b) dark grayish, compact, hard, rather large in size, usually called ‘‘Kankar’’ (Sehgal and Stoops 1972). The Western Himalayas in the north and the Thar Desert in the south and southwest, mainly determines the climatic conditions of Muktsar. The soils in the district were largely developed on alluvium. The district has two types of soils, sierozen and desert soils. The net area sown is 84% of the total geographical area. This district is irrigated by two types of irrigation, surface irrigation by canals and groundwater irrigation by tube wells.
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Hydrogeology The area is underlain by the Indus alluvium of the Quaternary age. The exploratory drilling in Indus basin also shows the presence of thick sandy aquifer zones with the intervening thin clay layers identifying it as one unified multi-aquifer system (Fig. 2). The pumping tests on different test wells have shown high permeability (15–25 m/day) indicating high potential aquifer systems. Below the thick alluvial sediments, different types of basement rocks have been encountered. The area has both confined and unconfined aquifers, (CGWB Report 2001; Kumar et al. 2007). Out of total area of 2,608 km2, only 30% of the area in the district faced 0–3 m of decline while rest of the part has registered upto 10 m of water level rise from June 1984 to June 2002 (Takshi and Chopra 2004). The mean annual rainfall in the district is 349.7 mm (2000–2004). Most of the rainfall occurs in four months of south-west monsoon period from June to September (about 71%). Figure 3 provides details of average monthly rainfall distribution over the area (Department of soil and water conservation (DSWC) Punjab).
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groundwater sampling. Sampled wells were selected to represent different geological formations as well as landuse pattern and different depth of the aquifer. Fifteen groundwater samples were collected in March 2003 (premonsoon) and same locations were again sampled in September 2003 (post-monsoon) to evaluate seasonal variations. These water samples were collected in clean polyethylene bottles. At the time of sampling, bottles were thoroughly rinsed 2–3 times with groundwater to be sampled. In the case of bore wells and hand pumps, the water samples were collected after pumping for 10 min. This was done to remove groundwater stored in the well. In-situ measurements included EC, pH, DO, temperature and bicarbonate which were measured using a portable field kit and titration respectively as per WHO (1996) recommendations as these parameters change with storage time. Samples collected were brought to the laboratory and were filtered using 0.45 lm Millipore filter paper and acidified with nitric acid (Ultrapure Merck) for cation analyses and HBO3 acid was used as preservative for nitrate analysis (Kumar 2004). The samples were brought to the laboratory and stored in a cold room at 4°C.
Materials and methods
Laboratory analysis
Initially, in order to understand the general variation in groundwater chemistry of the study area, a well inventory was carried out during February 2003 and electrical conductivity (EC) and pH were measured. A Garmin III global positioning system (GPS) was used to mark the location by noting down the latitude and longitude. The data was used to select the representative tubewell and hand pumps for
Major cations like Ca2+, Mg2+, Na+ and K+ were analyzed on a AIMIL Flame Photometer (PE I). The chemical analysis was carried out as per the standard procedure given in American Public Health Association (APHA 1995). Nitrate analysis was performed using Brucine Method using UV Spectrophotometer (Cecil, model no. 594). Fluoride was determined with a Thermo-Orion
Fig. 2 Laterally extensive multiple aquifer system in Punjab area of Indus basin (Source: Kumar et al. 2007)
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Average rainfall (mm)
Pre-monsoon
South-west monsoon
100
Post-monsoon
period
80 60 40 20 0 Jan.
Feb.
Mar.
April
May
June
July
Aug.
Sept
Oct.
Nov.
Dec.
Fig. 3 Avearge monthly rainfall distribution of Muktsar district
Benchtop Ion Selective Electrode. Heavy metals were determined using Shimadzu AAS. Apart from the collection and analysis of water samples, additional information related with geology, climate, soil type, and land use of the area were collected from the Central Ground Water Board (CGWB), Indian Meteorology Department (IMD) and TIFAC, New Delhi. Factor analysis The obtained matrix of hydrogeochemical data was subjected to multivariate analytical technique. Factor analysis also known as principle component analysis (PCA), is an efficient ways of displaying complex relationships among many variables and their roles (Dalton and Upchurch 1978; Fovell and Fovell 1993; Guler et al. 2002). These analyses were performed using Statistical Package for Social Sciences (SPSS) software package (Version 10.0). The data have been standardized and presented using standard statistical procedures (Usunoff and Guzman-Guzman 1989). With the help of linear combinations, an originally large number of variables are reduced to a few factors. These factors can be interpreted in terms of new variables. Factor analysis aims to explain observed relation between numerous variables in term of simpler relations. It is also a way to classifying manifestation of variables (Cattel 1965). The factor model used is expressed as: Xp Xj ¼ a f ej r¼1 jr r where fr is the rth common factor, p is the specified number of factors, ‘‘j’’ is the random variation unique to the original variable Xj, aji is the loading of the Jth variate on the rth factor. It corresponds to the loading or weights on principal components. The principal component approach was started by extracting eigenvalues and eigenvectors of the correlation matrix and then discarding the less important of these (Davis 1986; Kumar et al. 2006).
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Results and discussion General expressions of hydro-geochemical data The analytical results of groundwater samples of Muktsar and their computed values have been summarized along with their standard deviation in Table 1. In general groundwater was found alkaline in nature with an average value of 7.56 and 7.77 in the pre and post-monsoon respectively. A slight increase was observed in the postmonsoon in comparison to pre-monsoon. Increase of pH in the post-monsoon suggests that dissolution has been enhanced due to high interaction between soil and rainwater as well as due to dilution from the influx of rainwater of lower alkalinity (Subramanian and Saxena 1983). TDS and EC found higher in the post-monsoon in terms of range but lower in their mean values. This pattern of data clearly shows that there are some areas affected with salt patch where additional leaching is taking place. On the other hand the higher average value of EC in the pre-monsoon suggests the enrichment of salt due to enhanced evaporation in the pre-monsoon followed by subsequent dilution through rainwater. Very high standard deviation in EC for the post-monsoon also suggests the spatial variability of leaching and dilution with recharging rainfall water, which can be further linked with the local variation in point sources, soil type, multiple aquifer system and other agriculture related activities in the area. In Muktsar, dominant cations are in the order of 2+ Ca [ Mg2+ [ Na+ [ K+. Although, clear seasonal variations were observed both in minimum and maximum concentrations of these cations, but the difference in mean value is not significant except for K+. This is due to the dynamic change among the different hydro-geochemical processes operating in the area. Despite the greater resistance of potassium silicate to weathering, ions are released during weathering but they seem to be used up in the
Environ Geol (2009) 57:873–884 Table 1 The statistical summary of hydro-geochemical parameters of groundwater of Muktsar
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Parameter
Mean ± SD
Post-monsoon Range
Mean ± SD
Range
pH
7.56 ± 0.33
7.12–8.21
7.77 ± 0.41
7.23–8.74
TDS
1032 ± 1030
302–3643
2226 ± 1919
324–6970
EC
1645 ± 1552
530–5520
2774 ± 2174
500–7580
Na+
355 ± 1269
42–4025
479 ± 1544
24–6060
+
K
7.9–120
21.3 ± 24
3.8–99
Ca2+
108 ± 91
23–327
71 ± 29
25–122
Mg2+
111 ± 57.3
59.2–228
59 ± 3.34
52.9–63.7
HCO3-
482 ± 177
218–773
502 ± 210
217–963
Cl-
178 ± 202
16.8–625
1271 ± 1498
58–4466
SO24
333 ± 305
22–903
394 ± 757
42–3050
H4SiO4 PO43-
39 ± 18.6 0.03 ± 0.03
16–82 BD–0.09
33 ± 7.26 0.01 ± 0.02
22.02–45 0.002–0.06
NO3
All values are in mg/l except pH, EC(lS/cm)
Pre-monsoon
26 ± 34.63
62 ± 38
7.5–120
65 ± 31
15.02–120
F-
0.89 ± 0.43
0.04–1.6
0.2 ± 0.18
0.02–0.75
Fe
0.5 ± 0.3
0.2–0.9
0.76 ± 1.09
0.11–47.4
CAI–1
–4.82 ± 16.5
-52–0.63
0.35 ± 0.83
-1.86–0.98
CAI–2
–0.71 ± 3.9
-11.8–1.51
1.18 ± 2.6
-7.39–10.4
formation of secondary minerals. The abnormal concentration of potassium at few places is due to urban pollution and fertilizer leaching. Alkalinity of water is the measure of its capacity for neutralization. Bicarbonate represents the major sources of alkalinity. Bicarbonate is slightly higher in post-monsoon period indicating the contribution from carbonate weathering process. There was a slight variation observed in seasonal and spatial distribution of HCO3- but very significant at certain locations, may be due to contributions from carbonate lithology. The significant increased of Clin the post-monsoon substantiate the high leaching of salt with percolating rain water. In general, the most of the natural waters contain SO42- in smaller concentrations than the Cl- . In Muktsar, it ranged from 22–903 mg/l in pre-monsoon and 42–3,050 mg/l in post-monsoon. This indicates addition of sulfate by the breakdown of organic substances of weathered soils, sulfate leaching, from fertilizers and other human influences (Miller 1979; Craig and Anderson 1979; Singh 1994; Kumar et al. 2007). Nutrients in the groundwater were found in the order of NO3- [ H4SiO4 [ PO43-. The concentration of silica in groundwater samples did show some seasonal fluctuations. The possible explanation may be viewed in the perspective of the existence of alkaline environment, which enhances the solubility of silica and reveals secondary impact of silicate weathering. The average value of nitrate found higher in the post-monsoon, may be due to leaching of NO3- from fertilizers and biocides during irrigation of agriculture land. The PO43- in the study area was very low, may be because of phosphate adsorption by soils as well as
its limiting factor nature due to which whatever PO43- is applied to the agricultural field is used up by the plants. Since the plantation is mostly wheat in the area which consumes more PO43- is also a supporting fact for the finding (Kumar et al. 2007). Bedrock containing fluoride minerals is generally responsible for high concentration of fluoride in groundwater (Handa 1988; Wenzel and Blum 1992). Characterization of hydro-geochemical data An overall characterization of hydro-geochemical data can be possible by knowing the hydrochemical facies of water, generally known as water type, using various plots like Durov diagram (1948), Piper (1944) tri-linear diagram, Schoeller diagram 1965, Stiff diagram and Radial plot. We have used the recently proposed diagram after Chadha (1999) for geochemical classification. The rectangular field of the plot describes the primary character of the water including the permanent and temporary hardness domain for that the rectangular field is divided into eight sub-fields, each of which represents a water type and hardness domain (Fig. 4) is as follows: (1) Alkaline earths exceed alkali metals. (2) Alkali metals exceed alkaline earths. (3) Weak acidic anions exceed strong acidic anions. (4) Strong acidic anions exceed weak acidic anions. (5) Alkaline earths and weak acidic anions exceed both alkali metals and strong acidic anions, respectively. Such water has temporary hardness. The positions of data points in this domain represent Ca2+–Mg2+–HCO3- water type. (6) Alkaline earths exceed alkali metals and strong
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Fig. 4 Diagram demonstrating geochemical classifications of groundwater
acidic anions exceed weak acidic anions. Such water has permanent hardness and does not deposit residual sodium carbonate in irrigation use. The positions of data points in this domain represent Ca2+–Mg2+–Cl- type of waters. (7) Alkali metals exceed alkaline earths and strong acidic anions exceed weak acidic anions. Such water generally creates salinity problems both in irrigation and drinking uses. The positions of data points in this domain represent Na+–Cl--type and Na+–SO42--type of waters. (8) Alkali metals exceed alkaline earths and weak acidic anions exceed strong acidic anions. Such waters deposit residual sodium carbonate in irrigation use and cause foaming problems. The positions of data points in this region represent Na+–HCO3--type waters. Overall distribution of dataset on the plot suggests that most of the sampling point exhibits permanent hardness (Ca2+–Mg2+–Cl- type) i.e. domain 6 in the post-monsoon, though few sampling point fall under domain 5, i.e. Ca2+– Mg2+–HCO3- water type (Fig. 4). This observation is just opposite to that of in the pre-monsoon where only few sample represents domain 6. Such observation suggests that there is a significant effect of monsoon in terms of hardness and the significant amount of area with temporary hardness (Ca2+–Mg2+–HCO3- type) in the pre-monsoon switched to permanent hardness domain, i.e. (Ca2+–Mg2+– Cl- type) by the post-monsoon. Identification of hydro-geochemical process The hydro-geochemical data subjected to various conventional graphical plots in order to identify the hydrogeochemical processes and mechanisms in the aquifer region of study area. All the possible identified processes are explained below in detail.
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Ion exchange Ion exchange is one of the important processes responsible for the concentration of ions in groundwater. Chloroalkaline indices 1 and 2 (CAI 1 and CAI 2) that was calculated using Eq. 1 and 2, plotted in Fig. 5. CAI 1 ¼ Cl ðNaþ þ Kþ Þ=Cl
ð1Þ
2 CAI 2 ¼ Cl ðNaþ þ Kþ Þ SO2 4 þ HCO3 þ CO3 þ NO3
ð2Þ
(All values are expressed in meq/l). When there is an exchange between Na+ or K+ with Mg2+ or Ca2+ in the groundwater, both the above indices will be positive and if there is a reverse ion exchange prevalent then both these indices will be negative (Schoeller 1965). Figure 5 for the groundwater samples of Muktsar suggests a significant switch over between the processes of ion and reverse ion exchange on seasonal basis. It is clearly visible that in pre-monsoon there is reverse ion-exchange dominant except at few locations while ion-exchange became dominant in post-monsoon with the exceptions of few samples like M1–M4. However, some locations only show ion-exchange in both the seasons, but not a single sampling location exhibits reverse-ion exchange in both the seasons (Fig. 5). The plot of Ca2+ + Mg2+ versus SO42- + HCO3- will be close to the 1:1 line if the dissolutions of calcite, dolomite and gypsum are the dominant reactions in a system. Ion exchange tends to shift the points to right due to an excess of SO42-+HCO3- (Cerling et al. 1989; Fisher and Mulican 1997). If reverse ion exchange is the process, it will shift the points to the left due to a large excess of Ca2+ + Mg2+ over SO42- + HCO3-. The plot of Ca2+ + Mg2+ versus SO42- + HCO3- (Fig. 6) shows that
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879
10
-20
15 M
14 M
13 M
12 M
11 M
9
10 M
M
M
-10
CAI (meq/l)
8
7 M
M
6
5 M
4 M
M
3
2 M
M
1
0
CAI 1(Pre) CAI 2(Pre)
-30
CAI 1(Post)
-40 CAI 2(Post)
-50
Fig. 5 Bar diagram of Chloro Alkaline Indices (CAI) 1 and 2 for the pre and post-monsoon season 30 1:1
Ca+Mg (meq/I)
25 20 15 10 5 0 0
20
40
60
80
SO4+HCO3 (meq/l) Pre-monsoon
Post-monsoon
Fig. 6 Relation between Ca2+ + Mg2+ and SO42- + HCO3-
most of the groundwater samples of the post-monsoon found below the 1:1 line except few samples which do indicate reverse-ion exchange but extent is very less. While in pre-monsoon it is evenly distributed on both sides but reverse ion tends to dominant over ion-exchange. The plot of m(Ca2+ + Mg2+) versus m(Cl-) (Fig. 7) indicates that Ca2+ and Mg2+ do not increase with increasing salinity which could be the indication of reverse ion exchange in the clay/weathered layer except few samples of post-monsoon. Carbonate weathering and dissolution Ca2+ and Mg2+ are the dominant cations with their average contributions of 65 and 73% to the total cations in the pre and post-monsoon respectively. While among anions HCO3- is the most dominant with more than 60% of contribution to the total anion in both seasons. The
crystalline limestone, dolomitic limestone and kankar (the lime rich weathered mantle overlies carbonate rocks) are the major sources for carbonate in the area. The carbonates from these sources might have been dissolved and added to the groundwater system with recharging water during irrigation, rainfall or leaching and mixing processes. In Ca2+ + Mg2+ versus SO42- + HCO3- scatter diagram (Fig. 6), the points falling along the equiline (Ca2+ + Mg2+ = SO42- + HCO3-) suggests that these ions have been resulted from weathering of carbonates and silicates (Datta et al. 1996; Rajmohan and Elango 2004; Kumar et al. 2006). Most of the points, which are placed in the Ca2+ + Mg2+ over SO42- + HCO3- side, indicate that carbonate weathering is the dominant hydro-geochemical process, while those placed below the 1:1 line are indicative of silicate weathering. The plot of Ca/Mg ratio of the groundwater suggests the dominance of the dissolution of calcite and dolomite that present in the alluvium of the Muktsar (Fig. 8). That is, if the ratio Ca/Mg = 1, dissolution of dolomite should occur, whereas a higher ratio is indicative of greater calcite contribution (Maya and Loucks 1995). Higher Ca/Mg molar ratio ([2) indicates the dissolution of silicate minerals, which contribute calcium and magnesium to groundwater. The points closer to the line (Ca/Mg = 1) indicate the dissolution of dolomite. Most of the samples found below 1, indicates the calcite weathering, the post-monsoon samples though having a ratio near to line 1 indicate the dominance of dolomite dissolutions. Only one pre-monsoon sample that lies above the ratio line 2 indicate the effect of silicate minerals. By and large the chemical composition of the groundwater in the study area has resulted from the dolomite weathering by carbonic acid.
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HCO3 (meq/l)
1:1
15 10 1:2
5 0 0
5
10
15
20
25
Ca (meq/l) Pre-monsoon
Post-monsoon
Fig. 9 The scatter diagram of Ca2+ versus HCO320
Fig. 7 Relation between Ca2+ + Mg2+ and Cl-
1:1
SO4 (meq/l)
15 1:2
10
5
0 0
5
10
15
20
Ca (meq/l) Pre-monsoon
Post-monsoon
Fig. 10 The scatter diagram of Ca2+ versus SO42Fig. 8 The scatter diagram of Ca2+/Mg2+ molar ratio
Presence of ‘‘kankar’’ carbonates in the alluvial sediments and occurrence of metamorphosed dolomite limestones could favour the weathering process. However, a possibility of calcite weathering by sulfuric acid is also there as indicated by Ca2+ and SO42- ratio. Sulfuric acid may be produced by SOx emission dissolved in rain from automobile and industrial sources. The presence of carbonic acid and sulfuric acid enhances weathering reactions. If the weathering of carbonates is by carbonic acid, the equivalent ratio of dissolved Ca2+ and HCO3- in the groundwater resulting from calcite weathering is 1:2, whereas for dolomite weathering it is 1:4 (Garrels and Mackenzie 1971). If sulfuric acid is the weathering agent, then the Ca2+:SO42- ratio is almost 1:1 (Das and Kaur 2001). In Ca2+ versus HCO3- scatter diagram (Fig. 9), only few groundwater samples fall along the 1:2 line and most of them lie above the 1:1 equiline. Furthermore, in Ca2+ versus SO42- scatter diagram (Fig. 10), more number of samples fall below the 1:2 line, and some samples also trend along and above the 1:1 equiline (Ca2+ = SO42-). This clearly indicates the dominance of calcite weathering in the presence of sulfuric acid rather than dolomite (Garrels and Mackenzie 1971). Moreover,
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it indicates the presence of dissolution of gypsum (CaSO42H2O) in the area. The sources of Ca and Mg in groundwater can be deduced from the m(Mg2+ + Ca2+)/mHCO3- ratio. As this ratio also does not increase with salinity (Fig. 11), Mg and Ca are added to solution at a lesser rate than HCO3 ratio which is evident from the majority of the samples of post-monsoon which are below one. If Ca2+ and Mg2+ originate solely from the dissolution of carbonates in the aquifer materials and from the weathering of accessory pyroxenes and amphibole minerals, this ratio would be about 0.5 (Sami 1992). Therefore, the abundance of Ca2+ + Mg2+ in groundwater in Muktsar can be attributed to mainly from gypsum and carbonate weathering (Sharma et al. 1998). The carbonate alkalinity in the few samples can be balanced by alkalis like Na+ + K+ through either by silicate weathering or dissolution of alkaline soil salts. Silicate weathering Silicate weathering is one of the key geochemical processes controlling the major ions chemistry of the groundwater, especially in hard rock aquifers (Mackenzie and Garrells 1965; Rajmohan and Elango 2004; Kumar et al. 2006). Silicate weathering can be understood by estimating the
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881
TZ (Total cations) meq/I
100 Ca+Mg= 0.5 TZ+ 80 60
1:1
40 20 0 0
10
20
30
40
50
Ca + Mg (meq/l) Pre-monsoon
Post-monsoon
Fig. 11 Relation between (Ca2+ + Mg2+)/HCO3- and Cl- (mmol/l)
Fig. 13 Scatter diagram of (Ca2+ + Mg2+) versus total cation (TZ+)
ratio between Na+ + K+ and total cations (TZ+). The relationship between Na+ + K+ and total cations (TZ+) of the area indicate that the majority of the samples are plotted near the Na+ + K+ = 0.5TZ+ line (Fig. 12) indicating the involvement of silicate weathering in the geochemical processes, which contributes mainly sodium and potassium ions to the groundwater (Stallard and Edmond 1983). Furthermore, weathering of soda feldspar (albite) and potash feldspars (orthoclase and microcline) may contribute Na+ and K+ ions to groundwater. Feldspars are more susceptible for weathering and alteration than quartz in silicate rocks. The (Ca2+ + Mg2+)/HCO-3 ratio of more than 3 (Fig. 11) of few samples in the pre-monsoon suggest that silicate weathering occurs in this region in addition to the carbonate dissolution. Further, Ca2+ + Mg2+ vs total cations (TZ+) plot of groundwater samples (Fig. 13) have a linear spread between 1:0.5 (Ca2+ + Mg2+ = 0.5TZ+) line and 1:1 equiline indicates that some of these ions (Ca2+ + Mg2+) are resulted from the weathering of silicate minerals. In the groundwater of the Muktsar K+ is however, not as abundant as that of Na+, due to its fixation in the formation of clay minerals.
Evaporation In general, it is expected that the evaporation process would cause an increase in concentrations of all species in water. If the evaporation process is dominant, assuming that no mineral species are precipitated, the Na+/Cl- ratio would be unchanged (Jankowski and Acworth 1997). Hence, the plot of Na+/Cl- versus EC would give a horizontal line, which would then be an effective indicator of concentration by evaporation and evapotranspiration. If halite dissolution is responsible for sodium, the Na+/Cl- molar ratio should be approximately equal to one, whereas a ratio greater than one is typically interpreted as Na released from a silicate weathering reaction (Mayback 1987). The molar ratio of Na+/Cl- for groundwater samples of the study area generally ranges from 0.03 to 3.92 (Fig. 14). As most of the samples having Na+/Cl- molar ratio is below one found in the post-monsoon indicates that halite dissolution is the major process in the post-monsoon, which is replaced by silicate weathering in the pre-monsoon at few locations where ratio found above one. The trend of EC versus Na+/Cl-
TZ+ (Total cation in meq/I)
50 40 Na + K = 0.5 TZ+ 30 20 10 0 0
5
10
15
20
Na+K(meq/l) Pre-monsoon
Post-monsoon
Fig. 12 Scatter diagram of (Na+ + K+) versus total cation (TZ+)
Fig. 14 Plot of Na+/Cl- ratio versus electrical conductivity (EC)
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factors were identified which controls groundwater quality. In both the seasons there were very slight difference observed in terms of total variance, loading matrix and eigen value exhibited by the same factor, i.e. by factor 1 in pre and post-monsoon as well as in the percentage of variance explained by particular factors in corresponding seasons. In the pre-monsoon, Factor 1 accounts 23.15% variance in the data. The variable present in this factor are Na+, K+, Mg2+ and HCO3- which indicates ion-exchange and carbonate weathering. Factor 2 accounts for 19.81% of total variance, with the high loading for Cl-, Ca2+, SO42and silica, attributed from the silicate weathering processes and reverse ion exchange. Factor 3 accounts 17.67% variance in the data with the variables like EC, F-, and NO3-. This factor seems to be attributed to the leaching from irrigation of agricultural field. Factor 4 accounts for the 11.47% of variance in the data. This factor shows high positive loadings only for PO43-, which may be attributed from anthropogenic activities such as domestic and industrial waste discharge, runoff from agriculture field. The factor 5 explains only 8.78% of variance with high loading for SO42- and EC. In the post-monsoon season the five factors i.e Factor 1, 2, 3, 4 and 5 which were found to be responsible for the variations in groundwater quality explains 28.86, 16.91, 13.77, 12.59 and 11.54% of variance respectively in the data. Here again factor 1 show high loading for Na+, K+ but there are three more variables showing high loading that is NO3-, Cl-, pH and HCO3-. This is a remarkable change in factor loading which not only signifies the high recharge and leaching in the area but also highlights the descriptive capabilities of multivariate techniques as effective tools in groundwater evaluation. Furthermore, high loading of NO3- in factor 1, provides hint of the huge amount of
30
Na (m eq/I)
25
1:1
20 15 10 5 0 0
50
100
150
Cl (meq/l) Pre-monsoon
Post-monsoon
Fig. 15 Scatter diagram of sodium versus chloride (meq/l)
scatter diagram of the groundwater samples shows that the trend line is inclined, which indicates that evaporation may not be the major geochemical process controlling the chemistry of groundwater. The sodium versus chloride (Fig. 15) plot indicates that most of the pre-monsoon samples lie slightly above the equiline. The excess of Na+ is attributed from silicate weathering (Stallard and Edmond 1983) while the post-monsoon samples are lying below of it, indicates that the addition of Cl- in the postmonsoon may be due to water level rise which causes more salt dissolution from the soil. Na concentration is also being reduced by ion-exchange. Hence Na+ and Cldoes not increases simultaneously. Factor analysis The results of the factor analysis for the pre and postmonsoon season hydro-geochemical data are summarized in Tables 2 and 3, respectively. For both the seasons five Table 2 Multivariate factor analysis score for pre-monsoon in Muktsar
Component
Factor 1
Factor 2
pH
-0.56
-0.46
0.30
EC
-0.26
0.37
0.62
0.86
0.18
-0.01
-0.08
Na+ + K+ Ca
2+
Mg2+ Cl-
Factor 4
Factor 5
Communalities
0.28
-0.11
0.713
-0.25
0.44
0.841
-0.27
0.860
-0.12
0.75
0.36
-0.07
0.36
0.833
0.87
-0.13
0.13
-0.22
-0.03
0.840 0.738
-0.19
0.68
-0.24
0.39
-0.19
SO42-
0.06
-0.60
-0.16
0.42
0.61
0.940
HCO3-
0.64
-0.15
0.45
-0.08
0.21
0.683
NO3-
-0.12
-0.01
-0.83
-0.09
0.16
0.734
PO43H4SiO4
-0.51 0.19
0.12 0.72
-0.23 -0.08
0.58 0.48
-0.03 0.04
0.903 0.799
F-
-0.37
-0.17
0.69
0.14
-0.39
0.822
2.78
2.38
2.12
1.38
1.05
Percentage of variance
23.15
19.81
17.67
11.47
8.78
Cumulative % of variance
23.15
42.96
60.63
72.10
80.88
Initial eigen value
123
Factor 3
Environ Geol (2009) 57:873–884 Table 3 Multivariate factor analysis score for post-monsoon in Muktsar
883
Component
Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
Communalities 0.850
pH
0.75
0.37
-0.33
-0.09
-0.20
EC
0.07
-0.03
0.63
0.61
-0.03
0.775
Na+ + K+
0.86
-0.44
0.04
0.01
-0.23
0.798
Ca2+
0.27
0.68
0.27
-0.34
-0.18
0.836
Mg2+
0.40
0.31
0.05
0.75
0.06
0.763
-
0.76
-0.44
0.03
0.17
0.22
0.850
SO42-
0.24
-0.64
-0.06
-0.04
0.61
0.842
HCO3-
0.71
0.36
0.16
-0.13
0.43
0.867
NO3-
0.75
-0.32
0.31
-0.07
-0.36
0.890
PO43-
-0.21
0.13
-0.58
0.62
-0.29
0.871
H4SiO4
-0.38
-0.03
0.76
0.03
-0.22
0.776
F-
-0.20
0.69
0.07
0.11
0.62
0.923
3.46
2.03
1.65
1.51
1.39
Percentage of variance
28.86
16.91
13.77
12.59
11.54
Cumulative % of variance
28.86
45.77
59.54
72.13
83.67
Cl
Initial eigen value
fertilizers being used in the area. Factor 2 includes variable like Ca2+, F- and SO42- showing enhancement of carbonate weathering with rainfall and water level rise. But in Factor 3 the variables are EC and SiO2 signifies silicate weathering which is less prevalent than the carbonate one as observed in previous section through graphical plots, which is evident here by factor 2 and 3. Factor 4 shows high loading for Mg2+, PO43- and EC while factor 5 shows it for F-. In summary, it seems that different hydro-geochemical processes like weathering, ion-exchange, and reverse ionexchange are the key factors in the pre-monsoon which was overshadowed by leaching processes loaded with anthropogenic input. At most, factor analyses substantiate the findings of previous sections and provide greater confidence in data-interpretation.
Conclusions The results suggests that different natural hydrogeochemical processes like simple dissolution, mixing, weathering of carbonate minerals locally known as ‘‘kankar’’ and of silicate weathering and ion exchange are the key factors in the pre-monsoon, which was overcast by leaching processes loaded with anthropogenic input in the postmonsoon. Limited reverse ion exchange has been noticed at few locations of the study area especially in pre-monsoon periods. There was a significant effect of monsoon observed in terms of hardness and the significant amount of area with temporary hardness in the pre-monsoon switched to permanent hardness domain by the post-monsoon. Although it is difficult to pinpoint that what will be the condition in the next pre-monsoon. Is there cyclic
freshening/salinization phenomenon operating in the groundwater system of the study area? Will the area with permanent hardness regain their previous domain of temporary hardness? If not then what is the conversion rate of this transformation? To answer, many of such possible questions a long term monitoring is required. A systematic change in saturation indices (SI) of various minerals is also bound to occur with water table fluctuations due to increase of the partial pressure of CO2 (pCO2), the supply of oxygen–rich soil water to the water table. Thus determining the equilibrium state and its change with time and space using geochemical modeling software like PhreeqC may be the topic of further studies. Acknowledgments The authors would like to thank anonymous reviewers for their constructive and useful suggestions. Author (MK) thanks Council of Scientific and Industrial Research (CSIR) India for financial grant through research fellowship. The authors also acknowledge the Department of Science and Technology (DST) and TIFAC-ITSAP, Government of India for partial funding. Authors also like to thank Rita Chauhan and Gurmeet Singh for their able contributions at different stages of manuscript writing. At last we would like to thank Dr. Roger Herbert Jr. for his useful comments on first draft of manuscript.
References APHA (1995) Standard methods for the examinations of water and waste water, 17th edn edn. Washington DC, USA Ashley RP, Lloyd JW (1978) An example of the use of factor analysis and cluster analysis in groundwater chemistry interpretation. J Hydrol 39:355–364 Bartarya SK (1993) Hydrochemistry and rock weathering in a subtropical lesser Himalayan river basin in Kumaun, India. J Hydrol 146:149–174 Cattel RB (1965) Factor analysis: introduction to essentials. Biometrics 21:405–435
123
884 Cerling TE, Pederson BL, Damm KLV (1989) Sodium-Calcium ion exchange in the weathering of shales: implications for global weathering budgets. Geology 17:552–554 Chadha DK (1999) A proposed new diagram for geochemical classification of natural waters and interpretation of chemical data. Hydrogeol J 7:431–439 Craig E, Anderson MP (1979) The effects of urbanization of ground water quality. A case study of ground water ecosystems. Environ Conserv 30(2):104–130 Dalton MG, Upchurch SB (1978) Interpretation of hydrochemical facies by factor analysis. Groundwater 16:228–233 Das BK, Kaur P (2001) Major ion chemistry of Renuka lake and weathering processes, Sirmaur district, Himachal Pradesh, India. J Envion Geol 40:908–917 Datta PS, Bhattacharya SK, Tyagi SK (1996) 18O studies on recharge of phreatic aquifers and groundwater flow-paths of mixing in the Delhi area. J Hydrol 176:25–36 Davis JC (1986) Statistics and data analysis in geology. Wiley, New York Domenico PA (1972) Concepts and Models in Groundwater Hydrology. McGraw-Hill, New York Durov SA (1948) Natural waters and graphical representation of their composition. Dokl Akad Nauk SSSR 59:87–90 Fisher RS, Mulican WF III (1997) Hydrochemical evolution of sodium-sulfate and sodium-chloride groundwater beneath the Northern Chihuahuan desert, Trans-Pecos, Rexas, USA. Hydrogeol J 10(4):455–474 Fovell R, Fovell MY (1993) Climate zones of the conterminous United States defined using cluster analysis. J Climate 6:2103– 2135 Freeze RA, Cherry JA (1979) Groundwater. Prentice-Hall, Englewood Cliffs, p 604 Garrels RM, Mackenzie FT (1971) Evolution of sedimentary rocks. WW Norton, New York Guler C, Thyne GD, McCray JE, Turner AK (2002) Evaluation of graphical and multivariate statistical method for classification of water chemistry data. Hydrogeol J 10(4):455–474 GWREC (1997) Report of ground water resource estimation committee, Ministry of water resoursces, Government of India, New Delhi Handa BK (1988) Content of potassium in groundwater in India. Fertil News 33(11):15–27 Jacks G (1973) Chemistry of groundwater in a district in Southern India. J Hydrol 18:185–200 Jankowski J, Acworth RI (1997) 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 5(4):71–88 Klovan JE (1975) R-mode and Q-mode factor analysis. In: McCammon RB (ed) Concepts in geostatistics. Springer, Berlin Heildelberg , p 168 Kumar M (2004) An integrated hydrogeochemical and isotopic study of NCR-Delhi, India. Mphil dissertation, Jawaharlal Nehru University, India (Unpublished) Kumar M, Ramanathan AL, Rao MS, Kumar B (2006) Identification and evaluation of hydrogeochemical processes in the groundwater environment of Delhi, India. J Environ Geol 50:1025–1039 Kumar M, Kumari K, Ramanathan AL, Saxena R (2007) A comparative evaluation of groundwater suitability for irrigation and drinking purposes in two agriculture dominated districts of Punjab, India. J Environ Geol 53:553–574 Mackenzie FJ, Garrells RH (1965) Silicates: reactivity with water. Sci J 1505:57–58 Matthess G (1982) The properties of groundwater. Wiley, New York, p 498 Maya AL, Loucks MD (1995) Solute and isotopic geochemistry and groundwater flow in the Central Wasatch Range, Utah. J Hydrol 172:31–59
123
Environ Geol (2009) 57:873–884 Mayback M (1987) Global chemical weathering of surficial rocks estimated from river dissolved loads. Am J Sci 287:401–428 Miller GT (1979) Living in the environment. Wordsworth Publishing company , Belmonol California, p 470 Rajmohan N, Elango L (2004) Identification and evolution of hydrogeochemical processes in the groundwater environment in an area of the Palar and Cheyyar River Basins, Southern India. Environ Geol 46:47–61 CGWB Report (2001) Unpublished report on ground water resources and development potentials of Muktsar district, Punjab Sami K (1992) Recharge mechanisms and geochemical processes in a semi-arid sedimentary basin, Eastern Cape, South Africa. J Hydrol 139:27–48 Schoeller (1965) Hydrodynamique lans lekarst (ecoulemented emmagusinement). Actes Colloques Doubronik, I, AIHS et UNESCO, pp 3–20 Schuh WM, Klinekebiel DL, Gardner JC, Meyar RF (1997) Tracer and nitrate movements to groundwater in the Norruem Great Plains. J Environ Qual 26:1335–1347 Sehgal JL, Stoops G (1972) Pedogenic calcite accumulation in arid and semi-arid regions of the Indo-Gangetic alluvial plain of erstwhile Punjab (India)—their morphology and origin. Geoderma 8:59–72 Sharma BD, Mukopadhyay SS, Sidhu PS (1998) Microtpographic controls on soil formation in the Punjab region, India. Geoderma 81:357–368 Singh H (1983) Crop production in India. Agric Situation India 38:635–639 Singh KP (1994) Temporal changes in the chemical quality of ground water in Ludhiana area. Curr Sci 66:375–378 Singh AK (2003) Water resources and their availability. In: Souvenir, National Symposium on Emerging Trends in Agricultural Physics, Indian Society of Agrophysics, New Delhi, 22–24 April 2003, pp 18–29 Singh UK, Kumar M, Chauhan R, Jha PK, Ramanathan AL, Subramanian V (2007) Assessment of the impact of landfill on groundwater quality: A case study of the Pirana site in western India. Environ Monit Assess. doi 10.1007/s10661–007–9897–6 Stallard RF, Edmond JM (1983) Geochemistry of Amazon, the influence of geology and weathering environment on the dissolved load. J Geophys Res 88:9671–9688 Subramanian V, Saxena K (1983), Hydrogeology of ground water in Delhi region of India, Relation of water quality and quantity (Proceedings of the Hamberg symposium IAHS publication no. 146 Takshi KS, Chopra RPS, (2004) Monitoring and Assessment of Groundwater Resources in Punjab State Abrol, I.P. Sharma BR, Sekhon GS (ed). Groundwater use in North-West India— workshop papers. Centre for advancement of sustainable agriculture, New Delhi, pp 8–14 Toth J (1984) The role of regional gravity flow in the chemical and thermal evolution of groundwater. Proceedings of the first Canadian/ American conference on hydrogeology, Banff, Alta, June, 1984 Usunoff EJ, Guzman-Guzman A (1989) Multivariate analysis in hydrogeochemistry: an example of the use factor and correspondence analyses. Groundwater 27:27–34 Wadia DN (1981) Geology of India. Tata McGraw-Hill, New Delhi, p 508 Wallick EI, Toth J (1976) Methods of regional groundwater flow analysis with suggestions for the use of environmental isotope and hydrochemical data in groundwater hydrology, IAEA, Vienna, 37–64 Wenzel WW, Blum WEH (1992) Fluoride speciation and mobility in fluoride contaminated soil and minerals. J Soil Sci 153:357–364 WHO (1996) water quality monitoring: a practical guide to the design and implementation of freshwater quality studies and monitoring programmes. E&FN Spon, London, United Kingdom.
