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Hydrogeochemical characterization of groundwater in alluvial plains of river Yamuna in northern India: An insight of controlling processes
⁎Corresponding author. madhuririshi@pu.ac.in (Madhuri S. Rishi)
-
Received: ,
Accepted: ,
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.
Peer review under responsibility of King Saud University.
Abstract
Groundwater chemistry of an aquifer is influenced by several physical and chemical factors as well as their inter-ionic relationship prevailing in any area. To assess the factors influencing the chemical composition of groundwater in Panipat district, Haryana, India, a semi-arid alluvial region, different parameters including potential hydrogeochemical weathering as well as their ionic indices and conventional graphical methods were employed. The groundwater analysis data did not explicitly show the dominance of a single rock mineral dissolution process. The inter-ionic relationship between Ca2++Mg2+ and SO42− + HCO3– also indicated that the carbonate and silicate weathering were invariably prevailing in the region. The chloro-alkali indices have shown that Ca2+ and Mg2+ were replaced by K+ and Na+ of surrounding aquifer rock material in 51.1% of groundwater samples. However, there were strong indications of the influence of reverse ion exchange in rest of the data. The piper diagram represented the Ca2+-Mg2+-Cl−-SO42− type water, indicating an excess of alkaline earths over alkalies (Ca2+ + Mg2+ >Na+ +K+) and excess of stronger acidic anions over the weaker acidic anions (Cl−+ SO42− > CO3–+HCO3–). The factor analysis indicated that the weathering of aquifer rock material and anthropogenic activities are the main controlling factors in the region.
Keywords
Groundwater
Hydrogeochemistry
Weathering
Ion exchange
Chloro alkali indices
Factor scores
1 Introduction
Groundwater is an essential source for human due to its widespread availability and good quality. Globally, groundwater is a prominent source for irrigation, domestic and industrial supply in semi-arid provinces. Previous studies revealed that 65% of the global domestic water supply comes from groundwater, for irrigation it accounts for 20% and for industrial purposes around 15% (Adimalla et al., 2018). The groundwater quality in a region depends upon the geochemical composition of underlying rock strata, quality of recharge water, soil and water interaction processes, soil and gaseous phase interaction, rocks present in the unsaturated zone and their interaction with recharge water, residence time in aquifer and processes taking place in the aquifer itself (Freeze and Cherry, 1979).
Worldwide, agriculture is one of the major groundwater consumer and nowadays higher groundwater draft significantly altering the landscape. Geomorphologically, alluvial plains are the most vital and fertile landscapes used for high agricultural productivity (Verhoeven and Setter, 2009). Groundwater levels and quality always tend to vary, some changes are due to natural phenomenon and some are induced because of mankind. During summer season extraction of large quantities of groundwater from these aquifers adversely affect its quantity, quality and recharge which further alters the surface and groundwater interactions in alluvial regions (Lepure et al., 2014). In unconfined alluvial aquifers, groundwater is externally vulnerable to contamination due to surface and groundwater interaction. The fate, as well as the impact of agricultural and industrial chemical residue discharge, is principally a function of hydrogeochemistry of the region (Paudel et al., 2015). Thus, hydrogeochemical characterization and geological information of the aquifer system is important for the management of the resource (Howarth, 2013). The assessment of the groundwater system and hydrogeochemical processes responsible for its quality provides an insight into the comparative influences of rock-water interaction and human-induced alterations. Excessive natural resource exploitation and high waste generation in modern society also threaten groundwater quality in many regions.
Traditionally, India is an agricultural dominant country and groundwater is one of the most important sources of irrigation. Nearly 50–80% of irrigation in India is under groundwater command and 90% of rural inhabitants and more than 50% of the urban population’s water demands are fulfilled by groundwater (CGWB, 2013a,b). Groundwater depletion due to over-extraction for irrigation, industrial and other activities and alteration in its quality due to contamination and pollution resulting from industrial expansion, urbanization, unsystematic use of chemical fertilizers and pesticides in agriculture, waste disposal, insufficient drainage etc. are the great concerns in India. Such hydrogeochemical, as well as anthropogenic contamination processes responsible for the groundwater quality of a region, can be statistically analyzed. The multivariate statistical techniques are proved beneficial because of their relative significance in assessing large chemical dataset (Prasanna et al., 2010; Bouderbala, 2017; Ravikumar and Somashekar, 2017; Herojeet et al., 2017; Aghazadeh et al., 2017; Wu et al., 2017; Srivastava and Ramanathan, 2018; Gopinath et al., 2018; Rajkumar et al., 2018).
Panipat is one of the main hubs of the textile industry in India. Panipat has numerous large, medium and small cloth/thread dye houses along with a thermal power station, petroleum refinery, sugar mills and fertilizer processing plant providing livelihood to many people but it cannot be denied that these industries generate huge amounts of toxic wastewater too. The dimensions of urbanization and industrialization are increasing rapidly in the region and most of the medium to small-scale industries dispose off their wastewater without proper treatment on nearby land or in unlined drains. Further, maximum geographical area is under agricultural command, the unregulated use of fertilizers and pesticides along with unscientific industrial wastewater disposal may contribute to the changing hydrogeochemistry of the region as alluvial aquifers are the most vulnerable to contamination. Thus it is important to study the hydrogeochemical processes controlling the aquifer geochemistry. The aim of the present investigation is to evaluate the major hydrogeochemical processes influencing the aquifer chemistry in Panipat district of Haryana, India where the majority of the population is dependent on the groundwater for various uses.
2 Description of the study area
Panipat is an agricultural cum industrial district of Eastern Haryana, India. Its geographical extent extends from 29°10′15″:29°30′25″ North to 76°38′30″:77°09′15″ East (Fig. 1). It occupies nearly 1263 km2 area. River Yamuna flow throughout its eastern edge and serve as a natural boundary between the state of Haryana and Utter Pradesh. The climate of the study area is the semi-arid type and receives maximum rainfall during the monsoon period i.e. July to September each year.
Location Map of Study Area, District Panipat, Haryana, India.
The surface water resources in the region are usually precarious as they do not receive water for irrigation in the non-monsoon season and the local population mostly employs groundwater obtained from privately owned wells for irrigation, domestic and industrial purposes (CGWB, 2013a,b). About 80% of the geographical area is under the influence of agricultural activities, and the majority of the remaining area is dominated by urban-rural built up inhabitation and industrial setup. According to Haryana Pollution Control Board classification (no. of industries per 10 km2), the area study area has six highly polluting, 413 red categories, 1145 orange and green categories and 10 grossly polluting industries.
2.1 Geological and hydrogeological setting
The study area has almost homogenous geological nature and is completely covered by old and new alluvium deposits of Quaternary to Recent age, consisting of clay and sand. The geology of the region is shown in Fig. 2 indicating maximum area under older alluvium whereas newer terrace alluvium of erosional and depositional origin is present towards the eastern edge. Geological formations present in the area are of Quaternary age which comprises of recent alluvial deposits of the vast Gangetic alluvial plains. The whole district comprises of 8–23 granular zones up to a maximum depth of 260 m below ground level (m bgl) (CGWB, 2013a,b). Sand and gravel of varied size constitute these granular zones. The first aquifer occurs between 50 and 150 m bgl, the second one extends from 130 to 250 m bgl and the third one lies between 286 and 366 m bgl. The discharge rate of aquifers in the area ranges from 605 to 3258 Litre Per Minute (LPM). The aquifer holds a transmissivity range between 350–1990 m2/day (CGWB, 2013a,b). The groundwater development in the whole district surpassed the available recharge and is categorized as over-exploited with a groundwater development stage of 167%. Total available net annual replenishable groundwater is 308.65 MCM (million cubic meters) and total draft for all uses in Panipat is 514.56 MCM, thus parting short-fall (overdraft) of 205.91 MCM indicating that the groundwater resource is under stress and the water level is declining (CGWB, 2013a,b). The groundwater level trend in Panipat is showing continuous decline and the area may suffer from water shortage in near future (Kaur and Rishi, 2018).
Geology of district Panipat Haryana, India (taken from CGWB).
3 Materials and methods
A total of 45 samples were collected during post-monsoon season in the year 2015 from the study area after pumping for 10 minutes and the collected samples were stored in pre-washed HDPE bottles. Hanna (HI 98194) multi-parameter potable water testing kit was used to measure onsite parameters namely electrical conductivity (EC), total dissolved solids (TDS) and pH. The water quality analyses were performed by following the standard method given by APHA (2005). The results of the above said parameters were analysed statistically as well as graphically by using Microsoft Excel 2007, Minitab 18 and Rockworks 2015 software. Various spatial distribution maps along with sampling location map were prepared by using software ArcMap 10.4.1.
For the present assessment cation–anion balance, inter-ionic relationships, Chloro-Alkaline Indices (CAI), Piper diagram and Chadha’s diagram were employed to evaluate the chemical composition of groundwater in the study area.
The results of groundwater quality parameters were further selected for factor analysis. Principal Component Analysis (PCA) was employed to obtain the correlation matrix of the original variables data (Wu et al., 2014; Rajkumar et al., 2018). The criteria adopted for the selection of a number of factors was on the basis of eigen value >1(Kaiser, 1958). Varimax method was selected for the orthogonal rotation of the original factors to terminal factors as it makes the best use of the variance of the loadings on the factors and adjusts them closer to −1 to +1 or near 0. This method maximizes the variance of squared loadings within factors (Prasanna et al., 2010). The factor score coefficients were obtained from the factor loadings. For each water sample, the factor scores were determined by multiplying a factor score coefficient matrix with standardised data. Every individual factor score value expresses the significance of a specific factor at the sampling location. Factor score value +1 or more signifies strong influence by the process whereas the negative factor score values of the water samples were characterized as samples with non-representative scores indicating areas nearly unaltered by the process and the nearer to 0 signifies areas with the moderate influence of the process.
4 Results and discussion
The cation–anion balance of the samples ranged within 0–5%, indicating the acceptability of the laboratory analysis results for the present study. The summary statistics of quality parameters for the groundwater samples is given in Table 1. The mean concentration of the anion followed HCO3– > Cl− > SO42− > NO3– trend whereas cations followed Na+>Ca2+>Mg2+>K+ trend. The pH of the groundwater ranged from 7.29 to 8.89 with mean value of 8.01 indicating majority of the samples representing alkaline nature (Table 1). The TDS value ranged between 260 and 2160 mg/L having mean value of 701.24 mg/L (Table 1) indicating majority of the samples as freshwater whereas the total hardness for the groundwater samples ranged from 64 to 750 mg/L with a mean value of 340.58 mg/L.
Parameter
Unit
Minimum
Maximum
Mean
Standard deviation
n = 45
pH
–
7.29
8.89
8.01
0.345
TDS
mg/L
260
2160
701.24
429.13
EC
µS/cm
433.3
3600
1168.73
715.21
Cl−
mg/L
18
380
171.20
107.89
SO42−
mg/L
30
390
129.69
98.68
NO3–
mg/L
1.19
112
22.37
18.59
HCO3–
mg/L
195
940
469.84
194.77
CO3−
mg/L
0
50
5.04
11.09
Ca2+
mg/L
13
157
68.29
32.97
Mg2+
mg/L
10
90
32.00
17.94
Na+
mg/L
15
613
151.87
174.28
K+
mg/L
0.9
45
9.46
7.81
TH
mg/L
64
750
340.58
155.89
4.1 Ionic interactions
Rock weathering process is one of the main processes to control the geochemical cycling in the aquifer system (Berg, 1932). The nature and rate of chemical weathering differ significantly depending on the interlinked variables together with bedrock type, the topography of the area, climatic system and biological activities taking place in the area. Inter-ionic relationships of various cations versus anions have been plotted to assess their sources (common or varied) to understand the present chemical composition of groundwater.
Na+ and Cl− are important naturally present ions and if sodium present in the groundwater is derived from halite weathering, the sodium and chloride concentrations should be very closely aligned with the 1:1 line of Na+ versus Cl− plot (Tiwari and Singh, 2014; Aghazadeh et al., 2017). In the present study, most of the groundwater samples do not fall along the 1:1 equiline. Hence, it is clear from the plot (Fig. 3(a)) that sodium and chloride chemistry in the region cannot be explained only on the basis of halite dissolution processes because halite dissolution releases almost equal quantities of sodium and chloride into the solution. Meybeck (1987) reported that if the Na+/Cl− ratio in water is greater than 1, the source of Na+ is silicate weathering whereas approximately 1 indicates halite dissolution. In the present investigation, the observed average Na/Cl ratio of 2.23 in groundwater samples was greater than the standard marine/seawater mean value of 0.85 suggesting that higher concentration of sodium may be added from weathering of rocks or anthropogenic activities as compared to atmospheric precipitation (Aghazadeh et al., 2017). 48.9% of the groundwater samples were derived from other clay minerals (Fig. 3(a)) such as sodium montmorillonite, sodium aluminium silicate or albite aluminium silicate as in Eqs. (1) and (2) respectively.
(a). Na+ versus Cl− plot (b). Relation between SO42− + HCO3– and Ca2+ + Mg2+, (c) Relation between HCO3– and Ca2+ + Mg2+, (d) Relation between Cl− + SO42− and HCO3–.
Further, 40% samples showed Na/Cl ratio more than 1, indicating silicate weathering or anthropogenic influences as a potential source of sodium in groundwater samples (Li et al., 2018), whereas 11.1% samples showed Na/Cl ratio very close to 1 representing halite weathering in the study area.
The plot of SO42−+HCO3– and Ca2++Mg2+ will be close to equiline (1:1) if the dissolution or weathering of calcite, dolomite and gypsum are dominant processes in an aquifer system. In the present study, it is apparent from Fig. 3(b) that 46.7% of groundwater samples fall above the 1:1 equiline revealing carbonate weathering and 40% samples fall below the equiline due to excess of bicarbonate indicating silicate weathering (Bouderbala, 2017). The groundwater sample points along the 1:1 equiline signify chemical composition of water, in this case, is an outcome of both carbonate as well as silicate dissolution (Tiwari and Singh, 2014); only six samples fall in this chemical composition type. In majority of the samples Ca2++Mg2+ concentrations were higher than the HCO3– (Fig. 3(c)) suggesting the excess of Ca2++Mg2+ over HCO3– indicating that the carbonate weathering is dominant, which contributes Ca2+ and Mg2+ to groundwater (Li et al., 2018) and that the surplus of Ca2++Mg2+ in the groundwater samples is balanced by SO42− and Cl− ions (Fig. 3(d)). Some of the samples indicated a deficit of Ca2++Mg2+ in relation to HCO3– requires that surplus negative charge of HCO3– alkalinity must be balanced by alkali metals (Na+ and K+) (Tiwari and Singh, 2014).
4.2 Chloro alkaline indices (CAI)
Study of ion exchange indices is the easiest way to understand the groundwater composition and its interaction with rocks (Schoeller, 1965). For the present study chloro alkaline indices proposed by Schoeller (1965) were evaluated according to Eqs. (3) and (4)
Where all the units are expressed in meq/L.
CAI with positive value indicates that Na+ and K+ present in water were exchanged with Ca2+ and Mg2+ during contact with the aquifer material, representing the reverse ion exchange process whereas negative CAI implies that Ca2+ and Mg2+ in groundwater were replaced by K+ and Na+ representing ion exchange with the surrounding. If CAI value is 0, it implies no exchange, i.e. state of equilibrium between the chemical constituents present in groundwater and aquifer material. In the present study CAI-I value ranges from −12.07 to 0.86, whereas CAI-II value varies from −0.80 to 0.99. CAI-I and CAI-II values calculated for groundwater revealed that 51.11% of samples showed negative CAI, indicating that Ca2+ and Mg2+ ions in groundwater were replaced by K+ and Na+ ions of surrounding aquifer material. Thus, cation exchange is one of the main processes that can also govern the chemical constituents of the groundwater, whereas 48.89% samples showed positive CAI-I as well as CAI-II values, indicating reverse ion exchange process in the area.
To further supplement the results of weathering processes, different indices approach has been carried out to know the dominant hydrochemical facies of groundwater.
4.3 Piper’s tri-linear diagram
Piper’s tri-linear diagram (Piper, 1944) has been most widely used to understand the hydrochemistry of the area. Piper’s diagram is a major key to the identification and classification of rock-water interaction, solution kinetics, geology and sources of contamination in groundwater.
As per Piper’s plot (Fig. 4) 71.1% of the samples fall under field I representing Ca2+-Mg2+-Cl−-SO42− type water indicating an excess of alkaline earths than alkalies (Ca++Mg2+>Na++K+) and excess of stronger acidic anions than weaker acidic anions (Cl−+SO42−>CO3–+HCO3–) thus indicating permanent hardness (Ravikumar and Somashekar, 2017). Presence of alkaline earth cation facies represents the prevalence of natural weathering over human interventions with few exceptions that may have anthropogenic sources such as leaching of industrial effluent and fertilizers from agricultural fields (Srivastava and Ramanathan, 2018). 15.6% samples belong to field II representing the excess of alkalies over alkaline earths indicating Na++K+-Cl−+SO42− type water indicating halite weathering. 11.1% samples fall under category IV indicating Ca2+-Mg2+-SO42− type water whereas only 2.2% samples belong to Na+-K+–HCO3– type water. The diamond plot in Piper’s diagram was further classified as per Langguth (1966) in seven fields (A-G). According to this classification, the groundwater samples were distinguished into six fields represented by B, C, D, E, F & G. Field B (17.8% samples) and C (31.1% samples) symbolizes alkaline earths (Ca2++Mg2+) with prevailing anions HCO3– or SO42− or Cl−. Field D (8.9% samples) and E (24.4% samples) represent alkaline earths with dominant SO42− or Cl− anions. Field F (2.2% samples) and G (15.5% samples) indicate alkaline water with prevailing HCO3– or SO42−or Cl− anions. The dominance of Ca2+-Mg2+-Cl−-SO42− in the majority of the samples suggest the dissolution of carbonate minerals as well as infiltration of surface salts into groundwater due to irrigational practices in the study area. Sodium dominance in several groundwater samples may be because of acidic silicate mineral dissolution present in alluvium and cation exchange processes on clay particles. The source of bicarbonate in groundwater may be due to agricultural return flow cycle that makes a way for leaching of the carbonate mineral precipitates until it achieves the supersaturation state with calcite and dolomite in the groundwater. It is also noticeable that 40% of groundwater samples fall under mixed water type, where groundwater cannot be considered either as cation or anion dominant type (Herojeet et al., 2017).
Piper tri-linear plot showing major hydrochemical facies in the groundwater samples (Langguth, 1966).
4.4 Chadha’s diagram
A diagram introduced by Chadha (1999) was also evaluated to determine the various hydro-geochemical processes in the region. The plot was prepared by converting data into percentage equivalents (meq%) and denoted as difference among milliequivalent percentages of alkaline earth metals (Ca2++Mg2+) and alkali metals (Na++K+) for cations on X-axis and difference among weaker acidic anions (CO32–+HCO3–) and stronger acidic anions (Cl−+SO42−) on Y axis as shown in Fig. 5. Each quadrant of the plot indicates a specific hydro-geochemical process which further broadly classified as recharge water (Ca2+-Mg2+–HCO3– type), reverse ion exchange (Ca2+-Mg2+-Cl− type), seawater (Na+-Cl− type) end member and base ion exchange water (Na+–HCO3–). Fig. 5 indicates that most of the groundwater samples exhibits permanent hardness or reverse ion exchange water, meaning that Ca2+ + Mg2+ are in abundance than Na+ + K+ ions which may be caused by the release of Ca2+ and Mg2+ ions from exposed aquifer rock weathering such as carbonate rocks or perhaps reverse base cation exchange processes of alkali earth’s metals into solution and consequent Na+ adsorption onto the exposed rock mineral surfaces (Bouderbala, 2017). 15.6% samples fall under field 7, indicating sea water end member type i.e. alkalies surpasses alkaline earths and stronger acidic anions surpass weaker acidic anions and usually causes problems of salinity thus making it unfit for domestic as well as irrigation purposes (Chadha, 1999). Some of the samples belong to field 8 indicating an excess of alkalies over alkaline earths and weaker acidic anions surpass stronger acid anions thus signifying this type of waters deposit residual sodium carbonate which creates foaming problems in irrigation. Very few samples fall under Field 5, representing recharge type of water, evolved when water infiltrates into the aquifer from the surface irrigation and carries dissolved HCO3– and geochemically transportable/mobile Ca2+.
Chadha’s plot showing hydrochemical processes involved in groundwater samples.
The results of Piper and Chadha’s plot both revealed that alkali earths and strong acidic anions were abundant in the groundwater samples than the alkalies and weak acidic anions respectively thus indicating permanent hardness and reverse ion exchange.
4.5 Factor analysis
The factor analysis for the groundwater quality of only selected parameters (Cl−, SO42−, NO3– Ca2+ Mg2+, HCO3– Na+, K+ and TH) was carried out using rotated varimax method in Minitab 18 software and the results are shown in Table 2, indicating complex chemical nature of the region. In rotated varimax method total 3 factors were extracted accounting 74.8% of entire data variability representing the good insight of data structure and affirming the results of major controlling processes in the present study. The values represented in bold indicates positive loadings of the corresponding variables in extracted factors.
Variable
Factor 1
Factor 2
Factor 3
Varimax rotated (n = 45)
Cl−
0.785
0.237
0.237
SO42−
0.129
0.870
0.125
NO3–
0.433
0.267
0.642
Ca2+
0.830
−0.094
0.043
Mg2+
0.689
0.143
−0.033
HCO3–
0.193
0.900
0.067
Na+
−0.166
0.941
0.201
K+
−0.133
0.110
0.886
TH
0.849
−0.047
−0.068
Eigen value
3.34
2.37
1.02
Variance (%)
37.10
26.32
11.38
Cumulative (%)
37.10
63.42
74.8
The rotated varimax factor 1 describes 37.10% of the overall variance and strong positive factor loadings of TH, Ca2+, Cl− and Mg2+ indicating leaching of salts along with rock-water interface in the aquifer. The prevailing cations in this factor were Ca2+, Mg2+ that may have originated due to weathering of carbonate and silicate or owing to reverse ion exchange processes (Subramani et al., 2010). The presence of Ca2+, Mg2+ and Cl− and their high positive factor loadings with TH indicates the contribution of these chemical species to the total hardness of the groundwater.
Rotated varimax factor 2 represents strong positive loadings of Na+, HCO3– and SO42− and explains 26.32% of total variance. The dominant ion in this factor is Na+ indicating the presence of Na+ in groundwater is due to weathering of sodium containing feldspar (Albite). Higher loading of HCO3– and SO42− in factor 2 indicates silicate weathering and also represents the recharge processes (Prasanna et al., 2010; Subramani et al., 2010).
Rotated varimax factor 3 describes 11.38% of total sum of variance and strong positive factor loadings for K+ and NO3–. The presence of both K+ and NO3– signifying the impact of anthropogenic activities from agricultural processes. The presence of nitrate in the groundwater indicates seepage of sewage or industrial effluent or intensive application of nitrate fertilizer in agricultural practices.
It can be concluded from the factor analysis that the dominant hydrogeochemical processes are weathering of aquifer material, ion exchange and anthropogenic impacts including agricultural and industrial processes.
4.5.1 Spatial variation of factor scores
For the present study, the factor scores were derived for the estimation of spatial variability of dominant factors in the area. The factor scores used in the study were extracted by multiplying a factor score coefficient matrix with standardized data for each water sample location. The positive factor score zones represent the predominance of that particular factor i.e. hydrogeochemical processes. Inverse Distance Weighting (IDW) technique was employed for the interpolation of factor scores of each sampling location to prepare spatial variability maps. The spatial distribution of factor 1 is shown in Fig. 6 representing dominance of factor 1 scores towards the North-Western region of the study area indicating the prevalence of rock material and water interaction or carbonate and silicate weathering or reverse ion exchange in this zone. The spatial distribution of factor 2 is given in Fig. 7, clearly representing dominance of factor 2 in the north to south stretch towards the eastern side of the study area indicating albite and silicate weathering along with recharge processes as river Yamuna flows throughout the eastern side in the district. A perusal of Fig. 8 clearly depicts that the dominance of factor 3 is towards the south-west region in the study area and that the anthropogenic impacts are not only restricted to the southwestern side of the district but are conspicuous in other parts of the study area in patches.
Map showing spatial distribution of factor 1 in groundwater system of Panipat.
Map showing spatial distribution of factor 2 in groundwater system of Panipat.
Map showing spatial distribution of factor 3 in groundwater system of Panipat.
5 Conclusions
The aquifer hydrogeochemistry in Panipat is remarkably influenced by weathering of the aquifer rock material mainly carbonate and silicate-containing minerals. The inter-ionic interaction graphs indicated carbonate and silicate weathering in most of the groundwater samples. The chloro alkaline indices revealed nearly equal dominance of ion exchange as well as reverse ion exchange processes in the region. Piper’s plot and Chadha’s plot revealed rock weathering (reverse ion exchange) in most of the groundwater samples indicating Ca2++Mg2+-Cl−+SO42− water type representing permanent hardness in the region. This was further supported by the factor analysis which also suggested that the dominant hydrogeochemical processes in the region were weathering, ion exchange and anthropogenic influences. The anthropogenic influx from agricultural and industrial sources may pose a great threat to groundwater resources in the region. The present investigation demonstrates the major hydrogeochemical and anthropogenic processes responsible for the aquifer chemistry in the region which in turn may help in the groundwater quality management, policy formulation and decision making in the study area.
Acknowledgements
The authors extend their thanks to University Grant Commission- Maulana Azad National fellowship (UGC-MANF), India for providing the financial assistance for the study. They are also grateful to the Department of Geology, Panjab University Chandigarh for providing necessary research facilities.
References
- Evaluation of groundwater quality, Peddavagu in Central Telangana (PCT), South India: an insight of controlling factors of fluoride enrichment. Model Earth Syst. Environ.. 2018;4(2):841-852.
- [Google Scholar]
- Hydrochemistry and quality assessment of groundwater in the Ardabil area. Iran. Appl. Water Sci.. 2017;7(7):3599-3616.
- [Google Scholar]
- Standard methods for the examination of water and wastewater (21st ed.). Washington DC, USASS: APHA; 2005.
- Das Vorkommen der chemischen Elemente auf der Erde. JA Barth; 1932.
- Assessment of groundwater quality and its suitability for domestic and agricultural uses in Low-Isser plain, Boumedres. Algeria Arab. J. Geosci.. 2017;10(15):333.
- [Google Scholar]
- Central Ground Water Board (CGWB), 2013. Ground Water Information Booklet Panipat District, Haryana. North Western Region, Chandigarh.
- Central Ground Water Board (CGWB), 2013. Master Plan for artificial recharge in India, Govt. of India, Unpublished report.
- A proposed new diagram for geochemical classification of natural waters and interpretation of chemical data. Hydrogeol. J.. 1999;7(5):431-439.
- [Google Scholar]
- Groundwater. New Jersey: Prentice-Hall, Inc. Englewood cliffs; 1979. pp. 604
- Hydrochemical characteristics and salinity of groundwater in parts of Nagapattinam district of Tamil Nadu and the Union Territory of Puducherry, India. Carbonate Evaporite. 2018;33(1):1-13.
- [Google Scholar]
- Quality characterization and pollution source identification of surface water using multivariate statistical techniques, Nalagarh Valley, Himachal Pradesh. India. Appl. Water Sci.. 2017;7(5):2137-2156.
- [Google Scholar]
- Statistics and Data Analysis in Geochemical Prospecting. New York: Elsevier; 2013.
- Haryana pollution Control Board, Action plan for the abatement of pollution in respect of Panipat town http://cpcb.nic.in/displaypdf.php?id=UGFuaXBhdC5wZGY= on 07/01/2018.
- The Varimax criterion for analytic rotation in factor analysis. Psychometrika. 1958;23b:187-200.
- [Google Scholar]
- Integrated geospatial, geostatistical, and remote-sensing approach to estimate groundwater level in North-western India. Environ. Earth Sci.. 2018;77(23):786.
- [CrossRef] [Google Scholar]
- Grundwasserverhältnisses im Bereich des Velberter Sattels (Rheinisches Schiefergebirge): Düsseldorf. Deutschland: Minister für Ernäherung und Gesundheit; 1966.
- Geochemical, geological and hydrological influence on ostracod assemblages distribution in the hyporheic zone of two Mediterranean rivers in central Spain. Int. Rev. Hydrobiol.. 2014;99(6):435-449.
- [Google Scholar]
- Geochemistry, Hydraulic Connectivity and Quality Appraisal of Multilayered Groundwater in the Hongdunzi Coal Mine, Northwest China. Mine Water Environ.. 2018;37(2):222-237.
- [CrossRef] [Google Scholar]
- Global chemical weathering of surficial rocks estimated from river dissolved loads. Am. J. Sci.. 1987;287(5):401-428.
- [Google Scholar]
- Soil characterization based on land cover heterogeneity over a tropical landscape: an integrated approach using earth observation datasets. Geo In.. 2015;30(2):218-241.
- [Google Scholar]
- A graphic procedure in the geochemica interpretation of water analyses. Eos. Trans. Am. Geophys. Union. 1944;25(6):914-928.
- [Google Scholar]
- Statistical analysis of the hydrogeochemical evolution of groundwater in hard and sedimentary aquifers system of Gadilam river basin, South India. J. King Saud Uni. Sci.. 2010;22(3):133-145.
- [Google Scholar]
- Evaluation of heavy metal contamination in soil using geochemical indexing approaches and chemometric techniques. Int. J. Environ. Sci. Technol.. 2018;1–20
- [CrossRef] [Google Scholar]
- Principal component analysis and hydrochemical facies characterization to evaluate groundwater quality in Varahi river basin, Karnataka state. India. Appl. Water Sci.. 2017;7(2):745-755.
- [Google Scholar]
- Qualitative evaluation of groundwater resources. Methods and techniques of groundwater investigations and development. UNESCO; 1965. 5483
- Geochemical assessment of fluoride enrichment and nitrate contamination in groundwater in hard-rock aquifer by using graphical and statistical methods. J. Earth Syst. Sci.. 2018;127(7):104.
- [Google Scholar]
- Groundwater geochemistry and identification of hydrogeochemical processes in a hard rock region, Southern India. Environ. Monit. Assess.. 2010;162(1–4):123-137.
- [Google Scholar]
- Hydrogeochemical investigation and groundwater quality assessment of Pratapgarh district, Uttar Pradesh. J. Geol. Soc. India. 2014;83(3):329-343.
- [Google Scholar]
- Agricultural use of wetlands: opportunities and limitations. Ann. Bot.. 2009;105:155-163.
- [Google Scholar]
- Using correlation and multivariate statistical analysis to identify hydrogeochemical processes affecting the major ion chemistry of waters: Case study in Laoheba phosphorite mine in Sichuan, China. Arab. J. Geosci.. 2014;7(10):3973-3982.
- [CrossRef] [Google Scholar]
- Spatiotemporal variation of groundwater quality in an arid area experiencing long-term paper wastewater irrigation, northwest China. Environ. Earth Sci.. 2017;76(13):460.
- [CrossRef] [Google Scholar]
