Environ Monit Assess (2015) 187:295 DOI 10.1007/s10661-015-4522-6

Modelling of lindane transport in groundwater of metropolitan city Vadodara, Gujarat, India M. K. Sharma & C. K. Jain & G. Tamma Rao & V. V. S. Gurunadha Rao

Received: 16 June 2014 / Accepted: 9 April 2015 # Springer International Publishing Switzerland 2015

Abstract Migration pattern of organochloro pesticide lindane has been studied in groundwater of metropolitan city Vadodara. Groundwater flow was simulated using the groundwater flow model constructed up to a depth of 60 m considering a three-layer structure with grid size of 40×40×40 m3. The general groundwater flow direction is from northeast to south and southwest. The river Vishwamitri and river Jambua form natural hydrologic boundary. The constant head in the north and south end of the study area is taken as another boundary condition in the model. The hydraulic head distribution in the multilayer aquifer has been computed from the visual MODFLOW groundwater flow model. TDS has been computed though MT3D mass transport model starting with a background concentration of 500 mg/l and using a porosity value of 0.3. Simulated TDS values from the model matches well with the observed data. Model MT3D was run for lindane pesticide with a background concentration of 0.5μg/l. The predictions of the mass transport model for next 50 years indicate that advancement of containment of plume size in the aquifer system both spatially and depth wise as a result of increasing level of pesticide in river Vishwamitri. The restoration of the aquifer system may take a very long time as seen from slow improvement in the groundwater quality M. K. Sharma (*) : C. K. Jain National Institute of Hydrology, Roorkee 24766, India e-mail: [email protected] G. T. Rao : V. V. S. G. Rao National Geophysical Research Institute, Hyderabad 500 007, India

from the predicted scenarios, thereby, indicating alarming situation of groundwater quality deterioration in different layers. It is recommended that all the industries operating in the region should install efficient effluent treatment plants to abate the pollution problem. Keywords Groundwater . Vadodara . Lindane . River Vishwamitri . River Jambua

Introduction In the twelfth Stockholm Convention, nine organochlorine pesticides (OCPs), including aldrine, toxaphene, DDTs, chlordane, dieldrine, endrin, heptachlor, mirex, and hexachlorobenzene, were proposed to be controlled as persistent organic pollutants (POPs), a variety of organic chemicals which have lasting harms to environment and ecosystem. Due to their intensive utilization in agricultural and industrial activities, residues of the OCPs have been widely identified in almost all the inter-compartments viz: water, sediments, atmospheric air, biotic environment, etc., coming either through direct dumping into rivers, etc., or from agricultural area and reported across the world, even in Antarctica and the Arctic Zone (Fu et al. 2001; Chiuchiolo et al. 2004). These organochlorine pesticides are most commonly found as they break down slowly and remain in environment for long after its application. DDT, which is the most notorious organochlorine pesticide, was banned in the 1970s, but still it is present in traces as its half-life is 75 years. Unused pesticides and their degradation

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products and metabolites in various compartments (air, water, soil, aquatic biota, etc.) can affect human as well as aquatic biota and other domestic life both directly or indirectly. So pollution by these organochlorine pesticides leading to food chain accumulation cannot be ignored (Chopra et al. 2011) Organic pollutant ‘Lindane’ (γ-hexachlorocyclohexane) is an organochlorinated insecticide and fumigant and is commonly used on a wide variety of crops, in warehouses, and in public health to control insect-borne diseases (with fungicides) as a seed treatment. It may be mobile in soils with especially low organic matter content or subject to high rainfall. It may pose a risk of groundwater contamination. It is very stable in both fresh and salt–water environments and is resistant to photodegradation (Kidd and James 1991). Jayashree and Vasudev (2007) studied the organochlorine pesticide residues in ground water of Thiruvallur district, India and reported that the samples were highly contaminated with DDT, hexachlorocyclohexane (HCH), endosulphan, and their derivatives. γ-HCH residues were found maximum of 9.8 μg/l in Arumbakkam open wells and concentrations of pp-DDT and o, p-DDT were 14.3 and 0.8 μg/l. Endosulphan concentration is 15.9 μg/l in Kandigai village bore well. Nalini et al. (2005) reported the presence of high concentration of γHCH and malathion in surface water collected from the River Ganges in Kanpur, India and in ground water samples collected from various hand pumps located in agricultural and industrial areas posing a high risk to the common people. Shukla et al. (2006) analysed water samples collected from domestic well supplies of Hyderabad city, India for organochlorine pesticides using solid-phase extraction technique and found the presence of DDT, βendosulphan, α-endosulphan, and lindane more than their respective acceptable daily intake values for humans. Gurunadha Rao et al. (2004) analysed pesticide residues in groundwater samples of Ludhiana and Muktsar districts of Punjab state, India and reported the presence of organochlorine pesticide residues of BHC, endrin, heptachlor, heptachlor epoxide, DDT, and endosulphan. It has been found that the presence of organochlorine pesticide residues in groundwater of Muktsar district was about 6–8 times higher than that of Ludhiana district which may be attributed to cotton crop grown over large part of Muktsar district and shallow groundwater table condition through which pesticides leach fast.

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Groundwater modelling has become an important tool for planning and decision-making process involved in groundwater management. For managers of water resources, models may provide essential support for regulations and engineering designs affecting groundwater. This is particularly evident with respect to groundwater protection and aquifer restoration. Assessment of the validity of model-based projections is difficult and often controversial. The success or failure of a model depends on the availability of field information and the type and quality of the mathematical tools. The mass transport processes determine the extent of plume spread and the geometry of the concentration distribution. Advection is by far the most dominant mass transport process in shaping the plume. Hydrodynamic dispersion is usually a second order process. The advective transport is controlled by the configuration of water table or piezometric surface, presence of sources or sinks, permeability distribution within the flow field, and shape of flow domain. These parameters are important in controlling the groundwater velocity, which drives advective transport. Adding dispersion to advective transport can cause important changes in the shape of a plume. Other important process is sorption, and irrespective of the model describing sorption, the process is of paramount importance in controlling contaminant transport (Gurunadha Rao and Dhar 2000). A number of studies on contaminant transport modelling have been carried out by different workers across the world (Halfon 1986; Padilla et al. 1988; Van Jaarsveld et al. 1997; Ares et al. 1999; Gurunadha Rao and Dhar 2000; Warren et al. 2002; Gurunadha Rao 2003; Holman et al. 2004; Federico et al. 2005; Hoffmann et al. 2006; Tao et al. 2006; Connell 2007; Villanneau et al. 2009; Kumar et al. 2010; Gurunadha Rao and Surinaidu 2010; Kong et al. 2014). Gurunadha Rao and Dhar (2000) demonstrated the utility of groundwater flow and mass transport modelling for assessment and management of groundwater contamination. The geophysical and geohydrological investigations and water quality monitoring have been carried out to generate database for development of groundwater flow and mass transport model for a 2year period for the assessment of groundwater contamination around Gujarat Refinary, Vadodara, Gujarat, India. The finding reveals that the present groundwater contamination is limited to small area as the wastewater treatment facilities and the associated lagoons are

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located on low permeability formations in the refinery area (Gurunadha Rao 2003). Kumar et al. (2010) developed a groundwater model using Visual MODFLOW software to understand the reasons for declining water table in Central Punjab, India. The groundwater flow model for the study area was formulated by using input hydrogeological data and appropriate boundary conditions. The outcome of modelling shows that this model can be used for prediction purpose in the future by updating input boundary conditions and hydrologic stresses during the preceding years. Padilla et al. (1988) used a mathematical model solved by finite elements method namely MELEF-3v model, to simulate the 1D water flow as well as the heat and the mass transport through the unsaturated-saturated zones of the soil. Holman et al. (2004) presented a spatially distributed modelling system for predicting pesticide losses to groundwater through micro- and macropore flow paths. The system combines a metaversion of the mechanistics, dual porosity, preferential flow pesticide leaching model MACRO, which describes pesticide transport and attenuation in the soil zone to an attenuation factor leaching model for the unsaturated zone. The methodology provides a firststep assessment of the potential for pesticide leaching to groundwater in England and Wales. Federico et al. (2005) evaluated the new version of PELMO 3.31 model in predicting the pesticide volatilization under field conditions. Comparing simulation results obtained with PELMO 3.31, after calibration, with the previous version PELMO 3.20 shows that the estimated volatilization results seems improved for malathion, similar or slightly overestimating in the warmer season for ethoprophos, and similar or slightly underestimating in the colder season for procymidone. The new release of PELMO allows a more accurate estimation of pesticides volatilization from soil as a function of meteorological factors, especially for medium or low volatile pesticides. Persistence of a typical organochlorine pesticide has been illustrated through PESTAN model for the prevailing groundwater conditions in Muktsar and Ludhiana districts. Suggested regular monitoring of pesticide residues provide secured potable water supply to the people in these districts (Gurunadha Rao and Surinaidu 2010). Halfon (1986) used a seasonally averaged (June– November) fate model (TOXFATE) of organic contaminants to assess the relative importance of transport, degradation, and volatization processes in the Niagara

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River and in Lake Ontario near the river mouth. The model predicts concentrations in several compartments, including suspended sediments, water, plankton, and fish. Two contaminants were modelled, mirex and lindane. Simulations show that the largest amount of contaminants is usually in the water fraction. About 70 % of mirex is in the water at the mouth of the Niagara River, compared with 99 % for lindane. Van Jaarsveld et al. (1997) investigated the transport and deposition of POP in Europe using calculations with the TREND model based on high-resolution 1990 emission estimates. Lindane (γ-HCH) and benzo(a)pyrene were chosen to represent components found predominantly in the gas and particle phases, respectively. Model calculations indicate that γ-HCH has the potential for dispersion throughout the hemisphere, with most of it ending up in large water bodies. Ares et al. (1999) studied the pattern of lindane breakthrough to groundwater and its mobilization in a semiarid irrigated agricultural basin in southern Argentina and estimated pesticide half-life in the unsaturated vadose zone. K[oc] were estimated through parameter optimization techniques on the basis of an adhoc developed fugacity model, and two existing models of the transport of pesticides in soils (RITZ and PRZM2) and reported that the estimated half-life values are in agreement with values reported in the literature and K[oc] was lower than usually reported, indicating that the adsorption of the pesticide is controlled by the kinetics of soil water infiltration. The relevance of considering the kinetics constraints imposed by the hydraulic conductivity of soil profile and the partition with the soil organic matter are highlighted in relation to the prediction of pesticide environmental fate. Villanneau et al. (2009) investigated the concentrations of lindane in topsoil in Northern France and used robust geostatistics to map the geographical distribution of lindane. Results suggested that some of the lindane observed in the high concentration area may have come from volatilization of old lindane applied to intensively cultivated areas, which was then transported by prevailing winds coming from the south-west and deposited in a densely inhabited depression. Tao et al. (2006) used a level IV fugacity model to simulate the dynamic changes of γ-HCH concentrations in environmental media in Tianjin, China. Application of the level IV fugacity model has been validated using independently observed γ-HCH concentrations in various media during the early 1980s and during 2001. It

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was found that concentrations of γ-HCH reached within 95 % of their steady-state levels in all media after less than 15 years. Kong et al. (2014) simulated seasonal variations of both α- and γ-hexachlorocyclohexane in various environmental media in Lake Chaohu, China with a fugacity-based level IV Quantitative Water Air Sediment Interaction model. Warren et al. (2002) applied the fugacity-based quantitative water–air–sediment interaction (QWASI) model to the Rihand Reservoir in India for lindane and benzo(a)pyrene. The roles were discussed by which such models can contribute to improved management of chemicals that may adversely affect aquatic systems, especially in developing regions.

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spills from loading of the oil tankers also contributes to the groundwater contamination. Lindane is highly persistent in groundwater of metropolitan city of Vadodara as it is being used as a raw material in producing medicines for curing vector control diseases in the surrounding of the metropolitan city. In view of intensive utilization of lindane in agricultural and industrial activities, surface and groundwater quality in and around Vadodara City has been assessed and lindane migration pattern has been studied for future projections.

Materials and methods Sampling and analysis

Study area The metropolitan city Vadodara is the graceful city of Gujarat State bounded between 22°18′ N latitude and 73°16′ E longitude with an area of about 140 km2. The climate of the city is moderate tropical type. The temperature of the city varies from 8 to 46 °C. The average annual rainfall is 900 mm. The rivers Jambua, Vishwamitri, and Dhadhar flow through the study area (Fig. 1). The earliest geological evolution of the basement rocks, exposed in northern and eastern parts, had been controlled by the Precambrian orogenies (Arvalli and Delhi cycles), and the older crystalline rocks ideally shows folds, faults, and magmatism related to the two orogenies. After Precambrian orogenies, major geological events of Vadodara district were confined to Mesozoic and Cenozoic Eras which can be related with the breaking up of the Gondwana land and the subsequent northward drift of the Indian sub-continent, involving formation of sediments and Deccan Trap Volcanism with uplifts and subsidence along the two major lineaments—Narmada and Cambay rift system. There is no yield of water up to 50 ft, sandy aquifer was found from 50 to 70 ft. Metropolitan city of Vadodara is the industrial nucleus of the Gujarat State. A number of industries related to engineering goods, petrochemicals, plastics, pharmaceutical, fabrication, electronics, electrical, heavy machine, and light machine engineering are functioning in the city. In addition, sludge ponds, lagoons, and holding ponds also exist since last more than 40 years, and leakage from these structures infiltrates into groundwater system. Surface runoff caused by the rainfall and

Six wastewater drains viz: Nandesari Drain (ND), Nandesari; Gujarat Alkalies and Chemicals Limited (GACL) Drain, Ranauli; Gujarat Refinery (GR) Drain (Jaspura canal), Koyali; Indian Petrochemicals Corporation Limited (IPCL) Drain, Dhanora; Kamati Bagh (KB) Drain, Kala Ghoda Circle, Vadodara; and Gujarat Industrial Development Corporation (GIDC) Drain, Wadsar, and two rivers, namely, river Jambua and river Vishwamitri, were identified in and around metropolitan city of Vadodara, through which the mixture of different kind of untreated/partially treated/treated waste is being discharged. The water and wastewater samples from these drains, river Jambua and Vishwamitri and 35 groundwater samples from open wells (OW), tubewells (TW), piezometric wells (PzW), bore wells (BW), and hand pumps (HP) in and around Vadodara city (Table 1 and Fig. 2) were collected for physico-chemical analysis in polypropylene bottles and for pesticides analysis in glass bottles in pre- and post-monsoon seasons during 2008 and 2009. All the samples were stored in sampling kits maintained at 4 °C and brought to the laboratory for detailed chemical analysis. All general chemicals used in the study were of analytical reagent grade (Merck/BDH). De-ionized water was used throughout the study. The physico-chemical analysis was performed following standard methods (APHA 1995). Chloride was estimated by argentometric method in the form of silver chloride. Total hardness and calcium hardness were determined by EDTA titrimetric method while magnesium hardness was calculated by deducting calcium hardness from total hardness. Nitrogen in the form of nitrate was determined in the ultra-voilet range using

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Fig. 1 Map showing location of study area

UV–VIS spectrophotometer. Sodium and potassium were determined by flame emission method using flame photometer. Sulphate was determined by turbidimetric method in the form of barium sulphate crystals. Fluoride

was determined by SPADNS method using UV–VIS spectrophotometer. Dissolved oxygen (DO) was estimated using Winkler titration method. Biochemical oxygen demand (BOD) was determined based on 5 days

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Table 1 Details of surface and ground water sampling

Surface water sampling Sample ID Name of the drain/river D1 Nandesari Drain (ND) D2 Gujarat Alkalies and Chemicals Limited (GACL) Drain D3 Gujarat Refinery (GR) Drain (Jaspura canal) D4 Indian Petrochemicals Corporation Limited (IPCL) Drain D5 Kamati Bagh (KB) Drain, Kala Ghoda Circle D6 Gujarat Industrial Development Corporation (GIDC) Drain RJ River Jambua RV River Vishwamitri

Site location Nandesari Ranauli Koyali Dhanora Vadodara Wadsar Jambua Talshat

Groundwater sampling Sample ID Site location 1 Dashrath 2 Shokhda 3 Bapod 4 Shankarpura 5 Alamgir 6 Varnama 7 Itola 8 Pipliya 9 Limda 10 Kandha 11 Wagodiya 12 Goraj 13 Rushtampura 14 Rameshwarpura 15 Bhaniyara 16 Bhaniyara 17 Jarod 18 Panchdevla 19 Sarnej 20 Harni 21 Wadsar 22 Kalali 23 Ankhodiya 24 Bazwa 25 Ranoli 26 Rayaka 27 Nandesari 28 Sherkhi 29 Manjhalpur 30 Manjhalpur 31 Sharad Nagar 32 Makarpura 33 Jambua Jakat Naka 34 Makarpura 35 Pratap Nagar

Source OW OW OW PzW PzW OW PzW PzW PzW OW OW OW OW PzW PzW OW OW PzW PzW PzW HP PzW PzW PzW PzW PzW TW TW BW TW HP HP HP HP HP

Type of locality Village Village Village Village Village Village Village Village Village Village Taluka Head Quarter Village Village Village Village Village Village Village Village Village Vadodara City Village Village Village Village Village Village Village Vadodara City Vadodara City Vadodara City Vadodara City Vadodara City Vadodara City Vadodara City

Depth (m) 13.25 20.40 5.30 6.88 9.85 9.70 21.35 14.28 9.90 4.80 9.30 7.65 2.00 4.95 9.08 7.30 4.65 6.10 8.90 20.05 21.00 6.45 18.70 8.08 29.62 36.25 38.75 37.50 21.00 21.00 15.00 23.30 20.00 15.00 16.60

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Fig. 2 Map showing location of sampling sites

incubation at 20 °C followed by titration. Chemical oxygen demand (COD) was analysed based on digestion followed by titration. Ionic balance was determined; the error in the ionic balance for all samples was less than 10 %. The river water, wastewater, and groundwater samples were extracted for organochloro pesticide analysis with n-hexane, and the combined extract was concentrated using Kuderna Danish assembly under reduced vacuum. The moisture from the extracts was removed by using anhydrous sodium sulphate. The analysis of the pesticides was carried using Aimil Nucon Gas Chromatograph with the 63Ni selective electron capture detector. This detector allows the detection of contaminants at trace level concentrations in lower ppb range in the presence of multiple of compounds extracted from the matrix to which the detector does not respond. The column used was EQUITY-5, 30 m with internal diameter of 0.25 mm. Nitrogen gas was used as carrier gas at 2.0 ml/min with 28 ml/min as makeup gas. The temperatures of the oven was kept at 150 °C with a hold time of 1 min, then from 150 to 200 °C at a rate of 10 °C/min with a hold time of 1 min and then from 200 to 250 °C at a rate of 1 °C/min with a hold time of 1 min, and finally, to 280 °C at a rate of 10 °C/min with a hold time of 4 min. The detector was maintained at 285 °C. The qualitative and quantitative determination of the

organochloro pesticides were carried out by comparing the retention time and peak area of the pesticides. The confirmation of the pesticides in the water samples was achieved by using standard internal addition method. Recovery experiment was performed and recovery was about 75–103 % for organochloro pesticides. The reproducibility of the results for all pesticides was 95 % and above for all samples. Further, the mean average reading of an individual sample analysed in triplicate has been taken for reporting the results. Visual MODFLOW MT3D Visual MODFLOW Premium Version 2009.1 (MODular 3D finite difference groundwater FLOW model) MT3D developed by McDonald and Harbaugh of USGS, USA was used to simulate three dimensions groundwater flow. Modular structure consists of main program and independent modules; the modules are grouped into packages. Groundwater flow was simulated using a block centered finite difference approach. The finite-difference equations are solved using the strongly implicit procedure or using the slicesuccessive over relaxation methods. After flow simulation, MT3D module was run to study the contaminant (pesticide) migration pattern in the groundwater in space and time for prediction purposes. Boundary condition of

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dissolved oxygen. TDS values in wastewater vary from 768 to 8,063 mg/l. Maximum value of TDS was observed in the wastewater of IPCL drain which contains a mixture of different kind of wastes from different operations of petrochemicals industries. Maximum value of BOD (55 mg/l) was observed in IPCL drain, followed by Kamati Bagh drain. High values of BOD and COD observed in these drains indicate high degree of organic pollution load. The pH value of the river Jambua varies from 6.3 to 7.1 and of river Vishwamitri varies from 6.4 to 7.4. TDS values in both rivers were observed within the maximum permissible limit of 2,000 mg/l. It may be stated that the maximum permissible value of BOD for potable water is 2 mg/l, and that for bathing, it is 3 mg/l (website: http://cpcb.nic.in/Water_Quality_Criteria). High values of BOD and COD observed in these rivers rendering the water of these rivers unsuitable even for bathing purpose.

constant concentration of lindane was considered in the model domain. Data used Groundwater level data of observation wells, tube wells, piezometeric wells, aquifer parameter data, pumping test data, and lithologs data of the study area collected f r o m G r o un d w a t e r R e s o ur c e s D e ve l op m en t Corporation (GWRDC), Gandhinagar (Gujarat) were used for modelling. Pumping test in a large diameter open well at Asoj, Vadodara Taluka and in a bore well at village Dena, Harni, Vadodara Taluka (Fig. 1) was carried out and calculated the aquifer parameters using observed field data.

Results and discussions Physico-chemical characteristics of pollution sources

Physico-chemical characteristics of groundwater The physico-chemical characteristics of six identified drains viz: ND (D1), Nandesari; GACL drain (D2), Ranauli; GR drain (D3; Jaspura canal), Koyali; IPCL drain (D4), Dhanora; KB drain (D5), Kala Ghoda Circle, Vadodara; and GIDC drain (D6), Wadsar, and two rivers namely Jambua and Vishwamitri are given in Table 2 and Fig. 3. The determination of pH serves as a valuable index which shows whether the waste is acidic or alkaline in nature. The pH of the drain wastewater varies from 5.2 to 7.9. Total dissolved solids (TDS) create an imbalance due to increased turbidity and cause suffocation to the fish life even in the presence of high

The hydro-chemical data of groundwater samples of premonsoon, 2008, is presented in Table 3. The pH values in the groundwater of metropolitan city of Vadodara mostly fall within the range 7.6 to 8.6. The pH values for most of the samples are well within the limits prescribed by BIS (2012) for various uses of water including drinking and other domestic supplies. The electrical conductivity and dissolved salt concentrations are directly related to the concentration of ionized substance in water and may also be related to problems of excessive hardness and/or other mineral contamination. The

Table 2 Physico-chemical characteristics of the identified drains/rivers Drain/river

pH

EC (μs/cm)

TDS (mg/L)

DO (mg/L)

BOD (mg/L)

COD (mg/L)

7.5–7.9

1,940–5,650

1,242–3,616

4.0–7.8

2.2–16

48–187

Drain Nandesari (D1) GACL (D2)

7.3–7.9

4,320–5,812

2,765–3,720

4.5–5.8

2.4–8.0

48–137

Gujarat Refinery (D3)

5.8–7.4

2,750–3,592

1,760–2,385

0.0–4.4

0.9–12

72–180

IPCL (D4)

6.2–7.3

9,045–12,598

5,789–8,063

0.0–8.8

1.1–55

230–448

Kamati Bagh (D5)

5.2–7.8

1,400–6,115

896–3,914

0.0–3.0

2.7–25

72–187

GIDC (D6)

7.6–7.8

1,200–3,312

768–2,120

0.0–0.7

2.7–16

32–56

River R. Jambua

6.3–7.1

1,190–2,352

762–1,506

0.0–4.0

1.6–52

48–200

R. Vishwamitri

6.4–7.4

1,010–2,600

646–1,664

0.0–5.2

1.15–32

48–230

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Fig. 3 Physico-chemical characteristics of drains/rivers

conductivity values in the groundwater samples of the metropolitan city vary widely from 760 to 5,480 μS/cm with almost 80 % of the samples having conductivity value above 1,000 μS/cm. The maximum conductivity value of 5,480 μS/cm was observed in the sample of Harni. In the metropolitan city of Vadodara, the values of TDS in the groundwater varies from 486 to 3,507 mg/l. Almost all the samples were found above the acceptable limit but within the maximum permissible limit of 2,000 mg/l, and only 14 % of the samples exceed the maximum permissible limit of 2,000 mg/l. Water containing more than 500 mg/l of TDS is not considered desirable for drinking water supplies, though more highly mineralized water is also used where better water is

not available. For this reason, 500 mg/l as the acceptable limit and 2,000 mg/l as the maximum permissible limit has been suggested for drinking water (BIS 2012). Water containing TDS more than 500 mg/l causes gastrointestinal irritation (BIS 2012). The presence of calcium and magnesium along with their carbonates, sulphates, and chlorides are the main cause of hardness in the water. A limit of 200 mg/l as acceptable limit and 600 mg/l as permissible limit has been recommended for drinking water (BIS 2012). The total hardness values in the study area range from 79 to 1,143 mg/l. About 20 % of the samples fall within acceptable limit of 200 mg/l and 29 % sample cross the permissible limit of 600 mg/l. In groundwater of the

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Table 3 Hydro-chemical characteristics of the groundwater during pre-monsoon 2008

Parameters

Minimum

Maximum

Average

BIS (2012) Limit Acceptable

Permissible

pH

7.6

8.6

8.0

6.5

8.5

Conductivity, μS/cm

760

5,480

2,013

–

–

TDS, mg/L

486

3,507

1,288

500

2,000

Hardness, mg/L

79

1,143

435

200

400

Chloride, mg/L

20

1,464

320

250

1,000

Sulphate, mg/L

6.0

600

112

200

400

Nitrate, mg/L

0.0

252

36

45

–

Fluoride, mg/L

0.0

1.3

0.6

1.0

1.5 –

Sodium, mg/L

54

1,110

250

–

Potassium, mg/L

1.0

77

11.7

–

–

Calcium, mg/L

12

313

103

75

200

Magnesium, mg/L

12

127

43

30

100

study area, the values of calcium range from 12 to 313 mg/l. The values of magnesium vary from 12 to 127 mg/l. The acceptable limit for calcium and magnesium for drinking water are 75 and 30 mg/l, respectively (BIS 2012). Further, only few samples exceed maximum permissible limit of calcium as 200 mg/l and magnesium as 100 mg/l. The concentration of sodium in the study area varies from 54 to 1,110 mg/l. High sodium values in the city may be attributed to baseexchange phenomena causing sodium hazards. Such groundwater with high value of sodium is not suitable for irrigation purpose. The concentration of potassium in groundwater of the study area varies from 1.0 to 77 mg/l. As per EEC criteria, ten samples exceed the guideline level of 10 mg/l. The concentration of chloride varies from 20 to 1,464 mg/l. More than 60 % samples of the metropolitan city falls within the desirable limit of 250 mg/l, and only three samples of the city exceeds the maximum permissible limit of 1,000 mg/l. The concentration of sulphate in the metropolitan city varies from 6 to 600 mg/l. Bureau of Indian standard has prescribed 200 mg/l as the desirable limit and 400 mg/l as the permissible limit for sulphate in drinking water. In the study area, 89 % of the samples analysed fall within the desirable limit of 200 mg/l, and only two samples exceed the maximum permissible limit of 400 mg/l. The nitrate content in the metropolitan city of Vadodara varies from 0.0 to 252 mg/l. About 84 % of the samples of the metropolitan city of Vadodara fall within the acceptable limit of 45 mg/l and six samples even cross the permissible limit

of 45 mg/l. In higher concentrations, nitrate may produce a disease known as methaemoglobinaemia (blue babies) which generally affects bottle-fed infants. The higher nitrate concentration in the metropolitan city at few locations may be attributed due to combined effect of contamination from domestic sewage, livestockrearing landfills, and runoff from fertilized fields. The fluoride content in the groundwater of the study area varies from 0.00 to 1.26 mg/l. Almost all the samples of the metropolitan city fall within the acceptable limit of 1.0 mg/l, and none of the samples exceeded the maximum permissible limit of 1.5 mg/l. From the above discussion, it is clearly indicated that in the groundwater of metropolitan city of Vadodara, the concentration of total dissolved solids exceeds the acceptable limit of 500 mg/l in almost all the samples but within the maximum permissible limit of 2,000 mg/l. From the hardness point of view, about 20 % of the samples fall within acceptable limit of 200 mg/l and 29 % sample cross the permissible limit of 600 mg/l. The chloride content exceeds the desirable limit in more than 40 % of the pre-monsoon samples. Sulphate contents are within the desirable limits in about 89 % samples. The nitrate content in more than 84 % samples is well within the permissible limit. The concentration of fluoride in almost all the samples is well within the desirable limit. The violation of BIS limit could not be ascertained for sodium and potassium as no permissible limit for these constituents has been prescribed in BIS drinking water specifications.

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Sherkhi, Shokhda, Navi Khadki, Manjhalpur, Sharadnagar, Jambua Jatak Naka, Harni, and Goraj.

Pesticides in pollution sources The collected wastewater samples from different drains and water samples from rivers of the study area were analysed for organochlorinated pesticides (Aldrin, αBHC, β-BHC, γ-BHC, δ-BHC, DDD, DDE, αendosulphan, and methoxychlor). The results of pesticides analysis are presented in Table 4. Lindane (γBHC) was detected in the waste of GACL drain, IPCL drain, Kamati Bagh drain, GIDC drain, and river Vishwamitri. Aldrin was detected in GIDC drain, river Jambua and river Vishwamitri. α-endosulphan was also detected in GACL drain, GIDC drain, river Jambua and river Vishwamitri. Highest concentration of α-BHC (49.864 μg/l) and δ-BHC (36.849 μg/l) were observed in river Jambua and river Vishwamitri followed by GIDC drain (δ-BHC 34.507 μg/l) and Kamati Bagh drain (δ-BHC 22.599 μg/l). The presence of the pesticides in the wastewater of these drains/rivers may be attributed to the fact that few pesticides are being used as a raw material by the Pharmaceutical industries in the production of medicines being used for curing of vector control diseases.

Pesticides in groundwater The collected groundwater samples of the study area were analysed for organochlorinated pesticides (Aldrin, α-BHC, β-BHC, γ-BHC, δ-BHC, DDD, DDE, αendosulphan, and methoxychlor). The results of pesticides analysis are presented in Table 5. Presence of lindane (γ-BHC) was detected in groundwater of

Groundwater modelling and contaminant transport modelling Vadodara city is the industrial nucleus of the Gujarat State. Many large-scale industries are operating continuously. The treated/untreated effluents discharged from some of these industries in the north-eastern part of the study area flow through drains, which join the Effluent Channel, which ultimately meets river Mahi, while treated/untreated effluents discharged from some of these industries in the southern part of the study area flow through drains, which join either river Vishwamitri or river Jambua. Both of these rivers, Vishwamitri and Jambua, meet further downstream in the south end of Vadodara city. The water quality monitoring carried out in the drains, river Jambua and Vishwamitri and 35 groundwater samples from open wells, tube wells, piezometric wells, bore wells, and hand pumps in and around Vadodara city during pre- and post-monsoon seasons of the years 2008 and 2009, indicated high level of groundwater contamination from anthropogenic sources. The presence of organochloro pesticides was detected in wastewater of drains, river’s water, and groundwater. In the present investigation, an attempt has been made to simulate groundwater flow using MODFLOW and to study contaminant transport in space and time using MT3D in the groundwater of Vadodara city.

Table 4 Maximum concentration (μg/L) of pesticide observed in the drains/rivers during 2008–2009 Drain/river

α-BHC

β-BHC

γ-BHC

δ-BHC

Aldrin

α-Endosulphan

DDE

DDD

Methoxychlor

Drain Nandesari

BDL

BDL

BDL

BDL

BDL

BDL

BDL

1.769

BDL

GACL

BDL

BDL

0.909

BDL

BDL

1.133

BDL

BDL

BDL

Gujarat Refinery

BDL

0.257

BDL

BDL

BDL

BDL

BDL

BDL

BDL

IPCL

17.460

1.201

2.375

BDL

BDL

BDL

BDL

BDL

BDL

Kamati Bagh

BDL

0.367

0.998

22.599

BDL

BDL

BDL

BDL

BDL

GIDC

0.700

BDL

1.417

34.507

0.348

4.736

BDL

BDL

BDL

R. Jambua

49.864

BDL

BDL

BDL

9.200

1.127

BDL

BDL

BDL

R. Vishwamitri

BDL

BDL

3.650

36.849

0.632

2.059

0.259

BDL

0.572

River

BDL below detection limit

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Table 5 Maximum concentration (μg/L) of pesticide observed in the groundwater during 2008–2009 Location

α-BHC

β-BHC

γ-BHC

δ-BHC

Aldrin

α-Endosulphan

DDE μg/L

DDD μg/L

Methoxychlor

Bapod OW

5.230

BDL

BDL

BDL

BDL

BDL

BDL

BDL

BDL

Bhaniyara OW

BDL

BDL

BDL

22.552

BDL

BDL

BDL

0.315

BDL

Sherkhi TW

0.305

BDL

0.080

BDL

0.325

BDL

BDL

BDL

BDL

Navi Khadki BW

BDL

1.929

0.089

0.478

0.039

BDL

BDL

BDL

BDL

Manjhalpur TW

1.074

BDL

0.951

BDL

0.775

BDL

BDL

BDL

BDL

Goraj OW

BDL

0.472

0.089

BDL

BDL

0.318

BDL

0.023

1.596

Harni PzW

BDL

BDL

0.158

BDL

BDL

BDL

BDL

BDL

BDL

Rayaka PzW

BDL

0.184

BDL

BDL

BDL

0.073

BDL

0.768

BDL

Sharadnagar HP

BDL

BDL

0.163

BDL

BDL

BDL

BDL

0.129

BDL

Makarpura HP

BDL

1.624

BDL

BDL

1.407

0.619

BDL

BDL

BDL

Shokhda OW

BDL

BDL

0.572

BDL

BDL

BDL

BDL

BDL

BDL

Kandha OW

BDL

BDL

BDL

BDL

BDL

BDL

BDL

BDL

4.471

Sarnej PzW

BDL

0.961

BDL

BDL

BDL

BDL

BDL

BDL

BDL

Kalali PzW

BDL

0.787

BDL

BDL

0.209

1.059

BDL

BDL

BDL

Bazwa PzW

BDL

BDL

BDL

BDL

BDL

3.464

BDL

BDL

BDL

Ranoli PzW

0.746

0.586

BDL

0.217

BDL

BDL

0.128

BDL

5.853

Nandesari TW

BDL

BDL

BDL

BDL

BDL

BDL

BDL

BDL

3.089

JambuajatakNaka HP

BDL

1.732

1.209

BDL

BDL

BDL

BDL

BDL

BDL

Pratap Nagar HP

BDL

BDL

BDL

0.106

BDL

BDL

BDL

BDL

BDL

BIS (2012) Limit

0.01

0.04

2.0

0.04

0.03

0.4

1.0

1.0

–

BDL below detection limit

No flow

Kx=Ky=15m/d

Kx=Ky=18m/d

Kx=Ky=12m/d

and Kz=1.5 m/d

and Kz=1.8 m/d

and Kz=0.6 m/d No flow

Unconfined aquifer 30 m thick

Kx=Ky=15m/d and Kz=1.5 m/d

Semi-Confined aquifer 18 m thick

Kx=Ky=2m/d and Kz=0.2 m/d Confined aquifer

10 m thick

Kx=Ky=0.5m/d and Kz=0.05 m/d

Fig. 4 Conceptual model and hydraulic conductivity distribution in the model domain

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Detailed hydrogeological investigations have been carried out over an area of 15 km2 in Vadodara City to prepare a groundwater flow and mass transport model for the aquifer system. The area is covered by alluvial deposits comprising of clay, silt, and sand underlain by traps. Sandy horizons of considerable thickness have been delineated in the upper layers in central part and around the river Vishwamitri and river Jambua in the study area. The deeper layers invariably comprise of clay. Based on the geology and hydrogeological conditions, a conceptual hydrogeological model was developed for the study area. The conceptual model is the assignment or distribution of material property values within the model area. The development of a conceptual Fig. 5 Grid map and observation wells in the model domain

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model prior to the development of numerical model and definition of a numerical grid or mesh has always been the first step in model development. Model parameters such as boundary conditions and material properties are then selected for each node or cell with in the model domain. The distribution of model parameters and boundary condition are presented in the conceptual model (Fig. 4). Setting up of flow model Groundwater flow and mass transport modelling has been used as a predictive tool to prognose the impact of contaminant on groundwater. The hydrogeologic

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framework inferred from the geophysical investigations carried out by different workers and the hydrogeologic information collected from GWRDC, Gandhinagar has been used for conceptualizing the aquifer system. The groundwater flow model has been constructed upto a depth of 60 m considering a three layer structure: first layer 0–30 m, second layer 30–48 m, third layer 48– 60 m, and grid size 40×40×40 m3. The model grids are further divided into 10 m×10 m to simulate comprehensively at desired areas (Fig. 5). Lithologically, the top unconfined aquifer is mainly consists of sandy, sandy with mixed gravel, and clay layer; the middle one is medium to fine-grained sandy and silty clay layer; and third aquifer is fine sandy, clay, and silty clay formation. The general groundwater flow direction is from northeast to south and southwest. Hydraulic conductivity values for different regions of the study area and for the river bed are assigned based on field observations. The river Vishwamitri and river Jambua form natural hydrologic boundaries such as RIVER and DRAIN boundary conditions (Fig. 6). The constant head in the north of the study area is taken as another boundary condition in the model. The natural groundwater

Fig. 6 Boundary conditions in the model domain

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recharge is from 45 to 60 mm/year, but it could be less in the mid-portion of the study area (Fig. 6). The shallow aquifer thickness is about 10 m underlain by thick clay formation. All the three layers are occupied by highly permeable sands near the rivers. Calibration process and flow modelling results Calibration was done with eleven measured groundwater level values (Targets) for model calibration process during the study period. The calibration of the model was accomplished by manual trial and error adjustment of model parameters (Anderson and Woessner 1992). Model fit was considered to be adequate if it was consistent with the observed data. Values of hydraulic conductivity and recharge values were adjusted during the calibration process. The simulated groundwater levels mainly flow from northwest to southeast in the northern part, northeast in the eastern part and south in the southern part of the model domain (Fig. 7). The average groundwater velocity has been estimated as 0.26 m/day. The recharge components include groundwater inflow into the

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Fig. 7 Simulated groundwater elevation contours in the model domain

modelling domain form the up gradient areas and surface recharge. The surface recharge within the model area includes infiltration of rainfall water from the northern and eastern part of the model and from the unpaved areas. The calculated and observed heads of the calibrated model are shown in the scatter diagram Fig. 8. Formulating mass transport modelling The calibrated steady state model was used to set up mass transport model using MT3D code. For mass transport modelling, TDS has been computed through MT3D mass transport model starting with a background concentration of 500 mg/l and using a porosity value of

0.3. The mass transport model also accounts for dispersion phenomena of mixing of fluids within the groundwater regime. The longitudinal dispersivity of 80 m and transverse dispersivity of 8 m and about 1/100 in the horizontal traverse direction has been used. Even though TDS has been selected for simulation of contaminant migration, the migration of any other species, conservative in nature, will follow a similar pattern as mass transport is primarily driven by advection. In the absence of historical data on groundwater quality, calibration of the mass transport model has been carried out for the year 2008. Simulated TDS values from the model matches well with the observed data. Now the model MT3D was run for lindane pesticide with a background

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Fig. 8 Calculated vs. observed heads steady state condition in the model domain

concentration of 0.5 μg/l (Fig. 9). Sorption is simulated using a linear isotherm, as concentrations are low and degradation is represented by a first order irreversible decay process. The main source distribution to be

simulated covers the source area. This is meant to represent a highly diffuse source resulting from widespread agriculture, as much of this area has been some level of intensive agriculture in the past and soil contamination

Fig. 9 Source loading constant lindane concentration (μg/L) in the MT3D model

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has been observed throughout the source area. Lindane was assigned as constant (specified) concentration boundary in the model domain in row 45, 44 and column 58, 59 and row 69, 70 and column 53, 52 at source areas. MT3D model was based on the grids and results of MODFLOW and samples of lindane concentration were input for the mass transport model. The boundary conditions for the transport simulations are dependent on the flow boundary and assigned constant concentration boundary conditions. The predictions of the mass transport model for next 50 years indicate containment of plume size both spatially and depth wise as a result of increasing level of pesticide in river Vishwamitri. The reduction of concentration in the first layer and also containment of the size of the plume has been predicted. However a lower

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concentration of the contaminants may infiltrate to a maximum depth of 55 m (Fig. 10). The simulated lindane concentration plume is spreading out to be in northeast to southwest direction. The shape of the plume mainly depends on the longitudinal and transverse dispersion values assigned in the model and simulation were made without changing the concentration values. It was observed that advection, not dispersion is the predominant source mode of solute migration in the groundwater. Given these prediction, it was concluded that it is likely that a small number of point sources in soils could possibly lead to the widespread distribution of groundwater contamination observed in the area. Based on the range of possible source magnitude, it was determined that the observed groundwater contamination distribution could not have resulted solely from a

Fig. 10 Lindane plume (μg/L) around river Vishwamitri-Mass transport model

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small number of point sources in soils but the presence of a possible diffuse source is seen. The widespread nature of soil contamination in the area and transport from the soil to groundwater may occur from a diffuse source though preferential flow, soley at wells through shortcutting or wind-blown transport. The restoration of the aquifer system may take a very long time as seen from slow improvement in the groundwater quality from the predicted scenarios for different years. This may be due to very low groundwater velocities prevailing in the area because of clay predominant formations.

Conclusion It is evident from the study that the drains and rivers passing through the heart of the Vadodara City are highly polluted and contaminating the groundwater. The contaminant transport modelling revealed advancement of containment plume as a result of increasing level of pesticide in river Vishwamitri. The restoration of the aquifer system may take a very long time as seen from slow improvement in the groundwater quality from the predicted scenarios for different years, thereby indicating alarming situation of groundwater quality deterioration in different layers. It is recommended that all the industries operating in the region should install efficient effluent treatment plants to abate the pollution problem.

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