Groundwater quality is a major problem for humanity since it is closely related to human health. The flow of seawater into freshwater aquifers is known as saltwater intrusion, and it can lead to groundwater quality contamination, including drinking water. Due to the extremely severe hydraulic interface between groundwater and seawater, saltwater intrusion can happen naturally in coastal aquifers. The aim of the study is to examine the status of seawater intrusion within the study region of the South-West zone of Surat city, Gujarat. The present study evaluates Groundwater Quality Index using a weighted arithmetic method including various chemical ions. The South-West zone of Surat city is located along the coast; seawater infiltration has a significant impact on the groundwater in the state. The conceptual model will be developed and analyzed using MODFLOW to analyze the effects of seawater intrusion analysis. The model domain is characterized by three hydro-stratographic layers and covers an area of approximately 110 km2 in a 400 m × 400 m grid size. An analytical study with MODFLOW would be carried out for three-dimensional groundwater flows with species of solute transport. This study would help profile the study area regarding groundwater quality.

  • To examine the status of seawater intrusion within the study region.

  • To evaluate Groundwater Quality Index using a weighted arithmetic method including various chemical ions.

  • Study area is located along the coast; seawater infiltration has a significant impact on the groundwater in the state.

  • Conceptual model will be developed and analyzed using MODFLOW.

  • To analyze the water quality parameters of the groundwater

Water is becoming contaminated as a result of the growing population, industrialization, the use of compost in agricultural production, and man-made activities (Maghrebi et al. 2021). Surface water and groundwater are the prime water source for household and drinking uses in metropolitan areas (Dominic et al. 2016). According to the World Bank and the Union Jal Shakti Ministry, India is the world's greatest consumer of groundwater. According to the World Bank, the country's Annual Ground Water Resource is 447 billion cubic meters (BCM) and its Net Annual Groundwater Availability is 411 BCM (Hauff & Mistri 2012). The groundwater utilization for different purposes is 253 BCM per year. The state of Gujarat has conducted much comprehensive research and introduced a variety of protective measures along the coast regarding seawater intrusion. Surat city is likely to face severe water crises of a different kind. It may not face a shortage of water, but is likely to get poor quality of water; at least 50 percent of the area of Surat city faces the problem of salinity and reduction in groundwater level (Kumar 2018).

In the case of Surat city, Tapi river water is used for drinking purposes, treated water is provided to people by Surat Municipal Corporation (SMC) after treating the river water in a water treatment plant before consumption (India Water Portal, n.d.). However, due to rapid infrastructure development and an increase in population, many areas of Surat city are not able to get a good quality of drinking water, which is provided by SMC. In this case, groundwater is the best alternative. But due to industrial activities, agricultural activities, and improper waste disposal, groundwater in many areas is being polluted. Along these lines, the crumbling in the groundwater quality because of common and anthropogenic exercises has drawn incredible consideration as it is the significant substitute source of water to homegrown and drinking water supply. The water quality index (WQI) is one of the most effective and widely used tools to rate the quality of groundwater. The context of the above scenario in this present study was to analyze the water quality parameters of the groundwater in the area of Surat City, Gujarat, India.

Seawater intrusion

Saltwater intrusion is the development of saline water into freshwater springs, which can prompt groundwater quality corruption, including drinking water sources, and different outcomes (Central Water Commission 2017). Saltiness is a significant ecological misfortune influencing soil and water assets, horticulture, and making aggravations in the characteristic biological system. Expanded groundwater saltiness is additionally related to high groupings of some components like sodium, sulfate, boron, fluoride, selenium, arsenic, and high radioactivity (NIT Roorkee, India). The coastal redevelopment prevents seawater from intruding on fresh aquifers, as is mandatory. This interface among new and seawater is kept up near the coast or path beneath the land surface. The interface really might be a diffuse zone any place new and seawater join with each other. This zone is known as the zone of scattering or the zone of change (United States Geological Survey, n.d.). Groundwater siphoning can diminish freshwater streams toward waterfront regions and cause saltwater to be drawn toward the freshwater zones of the spring. Saltwater interruption diminishes freshwater storage inside the springs, and, in outrageous cases, can bring about the drain over of wells. Saltwater interruption happens in numerous kinds of ways, including parallel intrusion from beachfront waters and vertical development of saltwater close releasing wells. The interruption of saltwater brought about by withdrawals of freshwater from the groundwater framework will make the asset unacceptable for use. Subsequently, the executives’ plans should consider expected changes in water quality that may happen because of saline solution intrusion (United States Geological Survey, n.d.).

Groundwater Quality Index (GWQI)

The Ground Water Quality Index is probably the most reliable way to measure the quality of groundwater (Chaudhari et al. 2021). Groundwater demand has risen dramatically in India as a result of rapid population growth, rapid industrialization, and urbanization (Singh & Singh 2002). Owing to anthropogenic practices such as overexploitation and excessive waste management (industrial, residential, and agricultural) to groundwater reservoirs, the supply and quality of groundwater is deteriorating at an unprecedented pace (Ram et al. 2021). Many of the previous WQI experiments were mostly on surface water, with just a few studies concerned with groundwater. Chemical properties (temperature, turbidity, color, dissolved oxygen, pH, etc.) are essential parameters for determining groundwater quality, while hydro-chemical characteristics (major ions and anions) are critical factors of groundwater quality (Vadiati et al. 2019). The evaluation of groundwater quality involves several water-quality metrics, and data limitations often obstruct the creation of the Groundwater Quality Index (GWQI) (Mehta et al. 2018). Several studies dealing with GWQI growth in various parts of the world were carried out using their methodology (Saeedi et al. 2010). The Groundwater Quality Index (GWQI) is a simple method that uses the maximal values of various water quality variables to provide results that are easy to understand (Sharma & Patel 2010). However, one of the major problems with conventional WQIs (for both surface and groundwater) is that they don't account for the uncertainties and subjectivity that come with evaluating environmental concerns, primarily when characterizing water quality within the polynomial threshold (Pashaeifar et al. 2021). In general, the groundwater quality of urban areas in coastal areas is observed to be impaired due to the effects of seawater intrusion during tidal and non-tidal cycles in the study area district, which may significantly or partially impede the propagation of tidal currents and contribute to lateral pollution intrusion of urban aquifers. However, the cumulative depletion of groundwater quality throughout the coastal area is a result of aquifer characteristics, forms of aquifers, the effects of other contamination causes such as discharge of toxic or residential pollutants, the supply of groundwater in the aquifer, and the flow of recharge water to the aquifer across the year, and the hydro-geological factors of the aquifer during the year, hydro-geological characteristics of the aquifer, the extent of groundwater extraction, and so on (Langevin 2003).

Objectives of the study

  • To investigate the existing status of groundwater in the South-West zone of Surat city.

  • To identify the contaminant ratio of groundwater.

  • To prepare the planning proposal as per the result of the analysis.

Study area

Surat is Gujarat's second-biggest city and India's eighth-most populated city (regarding Populace in City Company region of the city) with a populace of 4.2 million. Surat positions fourth in a worldwide investigation of quickest creating urban areas led by The City Chairmen Establishment, a global research organization on metropolitan issues. Surat city is situated at latitude 21°12′N and longitude 72°52′E on the bank of Tapi waterway having a coastline of Arabian Sea to its West. It is 13 m above mean sea level. It is situated in very much growing south Gujarat district. It is found 306 km south of the state capital, Gandhinagar. By decentralizing various public services being provided by Surat Municipal Corporation, Zonal systems have been implemented. The whole of Surat city has been divided into 7 zones and different wards (Figure 1).

The study area zone (South-West zone) situated on the shoreline of the Dummas region of the Surat district, Arabian Sea, comprises a seaside plain with a profound, fine, salt-influenced soil surface. Concern to the investigation zone there are numerous little villages like Abhva, Panas, Khajod, Bhatpor, and some others. Individuals who live there have only the solitary resources of groundwater for drinking purposes and domestic uses, and because of that we selected this zone as our study area. The location is close to the Deccan promontory's southwestern coastlands. The Sahyadri scarp might be a little outside the region's eastward constraints, but it gives the region its course. Sedimentary fields and shorefront fields are two distinct areas.

The Tapi River runs through alluvial fields in the district's central areas (CGWB 2013). Tapi is a meandering canal that is moderately wide and has terraces carved into it. The topography is mostly flat, with a slight westward slope. The lowest elevation is 45 meters above mean sea level (m.amsl). The general elevations are below 60 meters above mean sea level (m.amsl) (above mean sea level). To the west, alluvial plains merge onto a dry dusty sandy coastal front plain, which is bordered by a moist shoreline. Near to the beach, there are creeks and spits. Alluvium covers the study area. Newer alluvium and older alluvium are the two regions that can be found in this aquifer. Although the sand is unconsolidated, it does display some consistency in some areas. In general, water levels are higher in newer alluvium.

The groundwater is largely unconfined, although semi-confined conditions have been found in some areas, most likely caused by the presence of clay objects.

Data collection

All data are provided by the various government departments, such as, Groundwater quality data collected from Gujarat Water Resources Development Corporation (GWRDC, n.d.), Central Groundwater Board (CGWB, n.d.), Gujarat, India, and (India-WRIS, n.d.). The annual and Seasonal fluctuation of groundwater data (Table 1) and annual rainfall data (Table 2) were downloaded from (India-WRIS, n.d.). Gujarat Water Resource Development Corporation, Gandhinagar, and Central Groundwater Board, Gujarat, provided 10 years of data about groundwater level and water quality data (Table 3) for Surat city, Chorasi, Taluka. Pre- and post-monsoon water level data (Table 4) was collected from Gujarat Water Resources Development Corporation (GWRDC, n. d.). The following data had collected for the study effect of seawater intrusion on groundwater. In India, there are 7525 Groundwater quality measurement stations, 668 stations in Gujarat state, 39 stations in Surat district (India-WRIS, n.d.), and only one station from all of them is relevant to this study, the Sultanabad station and a few wells as shown in Figure 2.

Table 1

Water level data: years 2009–2019

District Surat, Surat City
20092010201120122013201420152016201720182019
Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) 
7.14 6.18 6.82 7.87 6.56 11.62 6.97 6.8 7.06 7.4 3.15 
District Surat, Surat City
20092010201120122013201420152016201720182019
Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) Level (m) 
7.14 6.18 6.82 7.87 6.56 11.62 6.97 6.8 7.06 7.4 3.15 

Source: India-WRIS.

Table 2

Rainfall data: years 2015–2020

District: Surat, Surat City
Year201520162017201820192020
Rainfall (mm) 898.03 1,013.23 1,011.22 1,398.55 2,926.53 3,261.75 
District: Surat, Surat City
Year201520162017201820192020
Rainfall (mm) 898.03 1,013.23 1,011.22 1,398.55 2,926.53 3,261.75 

(Source: India-WRIS).

Table 3

Water quality data: years 2008–2018

District: Surat, Surat City
Sample site details: Latitude: 21°05°30, Longitude: 72°43°30, Geology: Alluvium, Site Id: 210530072433001
Parameters20082009201020112012201320142015201620172018
Ca (mg/L) 64 52 92 64 80 36 44 44 85 42 54 
Cl (mg/L) 284 206 178 163 135 152 128 135 263 115 114 
EC (μs/cm) 1,668 1,425 1,250 1,505 1,230 1,304 1,074 1,140 1,448 1,226 840 
F (mg/L) 0.12 0.14 0.17 0.15 0.35 0.3 0.2 0.35 0.38 0.25 0.3 
Mg (mg/L) 71 90 41 58 63 63 60.84 60.84 67 48.62 67 
NO3 (mg/L) 22 46 37 34 26 17 28 32 47 28 43 
SO4 (mg/L) 83 14 36 50 79 86 37 54 63 63 86 
Total hardness (mg/L) 450 400 400 400 410 350 360 360 365 290 240 
Total alkalinity (mg/L) 309.8 359.8 369.7 419.7 380.3 376.2 369.67 359.84 338.27 400 130 
Total dissolved solids (mg/L) 1,117.56 954.75 837.5 1,008.35 824.1 873.68 719.58 763.8 970.16 821.42 763 
pH 7.92 8.08 7.72 7.98 8.22 7.81 7.68 7.85 8.15 8.21 8.57 
District: Surat, Surat City
Sample site details: Latitude: 21°05°30, Longitude: 72°43°30, Geology: Alluvium, Site Id: 210530072433001
Parameters20082009201020112012201320142015201620172018
Ca (mg/L) 64 52 92 64 80 36 44 44 85 42 54 
Cl (mg/L) 284 206 178 163 135 152 128 135 263 115 114 
EC (μs/cm) 1,668 1,425 1,250 1,505 1,230 1,304 1,074 1,140 1,448 1,226 840 
F (mg/L) 0.12 0.14 0.17 0.15 0.35 0.3 0.2 0.35 0.38 0.25 0.3 
Mg (mg/L) 71 90 41 58 63 63 60.84 60.84 67 48.62 67 
NO3 (mg/L) 22 46 37 34 26 17 28 32 47 28 43 
SO4 (mg/L) 83 14 36 50 79 86 37 54 63 63 86 
Total hardness (mg/L) 450 400 400 400 410 350 360 360 365 290 240 
Total alkalinity (mg/L) 309.8 359.8 369.7 419.7 380.3 376.2 369.67 359.84 338.27 400 130 
Total dissolved solids (mg/L) 1,117.56 954.75 837.5 1,008.35 824.1 873.68 719.58 763.8 970.16 821.42 763 
pH 7.92 8.08 7.72 7.98 8.22 7.81 7.68 7.85 8.15 8.21 8.57 

(Source: India-WRIS).

Table 4

Village wise pre and post monsoon water level data

BlockVillageElevation of Ground LevelLat.Long.Water level data (m)
May-2009Oct-2009May-2013Oct-2013May-2017Oct-2017May-2019Oct-2019
Surat City Gabheni 11 21°05′16″ 72°49′45″   10.70 6.15 10.10 6.85 10.55 7.10 
Surat City 16.3 21°10′43″ 72°48′00″   15.93 11.45 16.10 14.75 16.90 14.30 
Chorasi Kansad 15 21°03′34″ 72°52′48″   6.43 0.85 6.15 2.60 6.85 1.95 
Dumas 5.69 21°06′38″ 72°42′54″ 6.55 5.05 6.80 3.65 6.75 5.85 6.90 5.10 
Hajira 7.84 21°07'35″ 72°38'58″ 3.50 1.10 3.60 0.25 3.50 1.95 3.10 0.95 
Kumbharia 24.81 21°11'16″ 72°53'42″ 11.25 5.20 11.60 7.40 15.00 14.10   
Sunvali 9.3 21°09'23″ 72°38'49″ 4.70 2.40 6.70 2.30 6.60 4.80 5.95 2.40 
Sachin 17.24 21°05'21″ 72°52'56″ 6.10 3.20 7.80 2.80 5.50 2.90 4.40 2.50 
BlockVillageElevation of Ground LevelLat.Long.Water level data (m)
May-2009Oct-2009May-2013Oct-2013May-2017Oct-2017May-2019Oct-2019
Surat City Gabheni 11 21°05′16″ 72°49′45″   10.70 6.15 10.10 6.85 10.55 7.10 
Surat City 16.3 21°10′43″ 72°48′00″   15.93 11.45 16.10 14.75 16.90 14.30 
Chorasi Kansad 15 21°03′34″ 72°52′48″   6.43 0.85 6.15 2.60 6.85 1.95 
Dumas 5.69 21°06′38″ 72°42′54″ 6.55 5.05 6.80 3.65 6.75 5.85 6.90 5.10 
Hajira 7.84 21°07'35″ 72°38'58″ 3.50 1.10 3.60 0.25 3.50 1.95 3.10 0.95 
Kumbharia 24.81 21°11'16″ 72°53'42″ 11.25 5.20 11.60 7.40 15.00 14.10   
Sunvali 9.3 21°09'23″ 72°38'49″ 4.70 2.40 6.70 2.30 6.60 4.80 5.95 2.40 
Sachin 17.24 21°05'21″ 72°52'56″ 6.10 3.20 7.80 2.80 5.50 2.90 4.40 2.50 

(Source: India-WRIS).

The next step of the evaluation is evaluating the Groundwater Quality Index for the problem and study area justification using arithmetic weightage method with several chemical parameters like Co3: Carbonate, Ca: Calcium, Cl: Chlorine, EC: Electrical Conductivity, F: Fluoride, Fe: Iron, HCo3: Bicarbonate, K: Potassium, Mg: Magnesium, No3: Nitrate, Na: Sodium, SAR: Sodium, adsorption ratio, So4: Nitrate, TDS: Total Dissolved solids, and so on, as shown in Table 3.

Calculation of groundwater quality index (GWQI)

  • A.

    The first step to develop the GWQI, is to assign a weight or weightage factor (Gwi) to each parameter with a relative importance of the overall quality of water. The value of 5 assigns to F, Cl, So4, and TDS, which is the maximum weightage; the value of 3 assigns to Ca, Mg, Total Hardness; the value of 1 and 2 assigns to NO3 and EC respectively, which reflect the importance of groundwater quality.

  • B.
    The second step is to determine Relative Weight (Gwr), calculate the ratio of Gwi and Total Gwi, and the result of that is called Relative Weight with the following Equation (1)
    formula
    (1)
  • C.
    In the third step, a quality rating scale for every parameter was allocated by isolating the parameter's focus in each water test by its separate norm (Si) as indicated by the rules set out by the Bureau of Indian Standards (Standards) and afterward multiplying the outcome by 100 (Environment, n.d.) as the following Equation (2)
    formula
    (2)
    where,
  • qi = Quality rating,

  • Ci = Concentration of every chemical parameter in each water in mg/L,

  • Si = Drinking water standard of India for each chemical parameter as indicated to the BIS 10500-2012.

  • D.

    Compute the GWQI

To compute the GWQI, the SIi is first determined for each chemical parameter as Equations (3) and (4)
formula
(3)
formula
(4)

where, SIi is the sub-index of the i parameter and qi is the quality rating dependent on the concentration of the i parameter. The computed GWQI estimates were then relegated to one of five levels of water quality ranging from ‘excellent’ to ‘unacceptable for drinking’

Overview of MODFLOW

MODFLOW has a graphical user interface (GUI) called Model Muse. The two- and three-dimensional finite-difference models defined by Trescott et al. (1982) were widely used by the Geological Survey and many others for stream flow computer simulation. MODFLOW 6 is the most recent variant of the MODFLOW model developed by the United States Geological Survey. MODFLOW–2006 is a three-dimensional finite-difference groundwater model. It replicates steady and non-steady flow in a randomly formed flow structure with enclosed, unconfined, or mixed confined and unconfined aquifer layers. This simulates steady and non-steady flow in a variably formed flow structure with enclosed, unconstrained, or mixed constrained and unconstrained aquifer layers. The impacts of wells, reservoirs, and other groundwater constraints on an aquifer environment are the subject of simulations. The MODFLOW's capabilities have developed over time to include surface-water flow simulations, contaminant transport simulations, and organizational enhancement. The remote sensing data for the model in ModelMuse is unaffected by the grid, and the temporal data is unaffected by the anxiety intervals. The ability to separately insert all such data helps the user to reframe the temporal and spatial convolutions as required.

The prime objective of the study is to investigate the present salinity status of groundwater in the study area. The present groundwater model evaluates the required development in the study area. A groundwater model is a simplified representation of the natural groundwater flow system (Inayathulla 2015). The use of a numerical and conceptual model to consider the baseline and potential modified parameters of oceans and coastal hydraulics, as well as water quality heterogeneity, is a reliable and validated method. Using a groundwater seawater infiltration model, researchers investigated the relationship of river/coastal water salinity with neighboring aquifer water and its spatial-temporal difference. Seawater accumulation onshore due to increased human activity reduced dry-season flow, and environmental issues have been assessed using a seawater transport model within the study area.

Following the pre-processing of the model, hydraulic properties are estimated and the model is set for simulations. The various components are taken into consideration for simulation, such as, the concentration of chemical parameters, rainfall (recharge), groundwater level, temperature as well as geomorphology of the study area. The present groundwater model simulates for existing conditions (years 2008–2018) and also simulates for the next 10 years (till the year 2028). The models would help in identifying and analyzing the salinity infiltration mechanism under current conditions, as well as analyzing improvements as a result of increased groundwater usage and rising sea levels.

Governing equation for groundwater flow and transport process

The partial differential equation (Equation (5)) can be used to define a general form of the equation that governs the three-dimensional non-equilibrium movement of constant density groundwater by porous, anisotropic, three-dimensional, and heterogeneous groundwater flow.
formula
(5)
(Source: Winston 2009)

where,

  • Kxx, Kyy, Kzz are elements of aquifer layer hydraulic conductivity on the x, y, and z axes,

  • h is the hydraulic head,

  • qs is water supplies and/or sinks per unit time as described by the volumetric flux per unit volume,

  • Ss is specific storage of the porous material,

  • t is modeling time.

Three-dimensional transient flow equation

formula
(6)

(Source: Winston 2009).

where,

  • Ck is the dissolved concentration of species k

  • is porosity of the subsurface medium

  • t is time

  • xi is the distance along the respective cartesian coordinator axis

  • Dij is the hydrodynamic dispersion coefficient tensor

  • vi is the seepage or linear water velocity

  • qs is the volumetric flow rate per unit volume of aquifer

  • Csk is the concentration of the source

  • ∑Rn is the chemical reaction term

The finite-difference approximation (Equation (6)) approach is used to solve the numerical groundwater flow equation (Salmasi & Azamathulla 2013). The thickness of model layers can change over time. Each cube, referred to as a cell, has its flow equation. In each phase of a MODFLOW stress cycle, the preconditioned conjugate gradient (PCG) solver with an Improved Nonlinear Control package is used to solve the finite difference equations. For each stress process, groundwater volume balances and flow rates from each form of inflow and outflow are calculated. The simulation result is given by the MODFLOW programmed according to this differential equation.

Boundary conditions

The basin's primary geologic formations are among the Quaternary alluvium, Tertiary limestone and sandstones, and Deccan Trap basalt. Mathematical boundary conditions must be used to describe hydrological characteristics that are adjacent to and within the model domain (Xu et al. 2011). The boundary state chosen is determined by the hydro-geological conditions of the study area's aquifer, as well as the modeling's intent. The following boundary conditions are used in this modeling method. Table 5 contains the information on the geology and hydraulic conductivity.

Table 5

Aquifer layer properties

Sr. No.LayerSoil typeHydraulic conductivity (m/day)
Layer 1 Quaternary alluvium 7.32 
Layer 2 Tertiary limestone 5.85 
Layer 3 Sandstones 4.35 
Layer 4 Deccan Trap basalt 0.001 
Sr. No.LayerSoil typeHydraulic conductivity (m/day)
Layer 1 Quaternary alluvium 7.32 
Layer 2 Tertiary limestone 5.85 
Layer 3 Sandstones 4.35 
Layer 4 Deccan Trap basalt 0.001 

The groundwater model on the seawater intrusion effect uses the MODFLOW, and the USGS developed the Seawater Intrusion Package 2 (SWI2) modeling programme, which is compatible with MODFLOW version 6 (Bakker et al. 2013). In coastal aquifer ecosystems, SWI2 encourages the three-dimensional variable-density groundwater flow and seawater intrusion. This study focuses on the application of SWI2 to a MODFLOW model created in Model Muse. It represents the whole model configuration, dataset operation, boundary condition conceptualization (Table 7), and assessment of outcome. We need to collect several hydrogeological surveys, development of datasets, and prove the efficiency of hydraulic testing to provide an entire set of parameters and input data for a valuable computational simulation. The boundary with known flux and boundary with head-based flux are the two forms of groundwater model boundary conditions. A boundary of known flux will appear when modeling water tables in unconfined aquifers with inflow/outflow by lateral contacts between different aquifers. To recreate known flux conditions, the following (Table 6) packages should be used.

Table 6

Applied MODFLOW packages in MODFLOW modeling

Sr. No.Hydro-GeologyPackagesDescriptions
Flow packages LPF Layer property flow package 
SWI2 Seawater intrusion package 
Specified head CHD Time variant specific package 
Specified flux RCH Recharge package 
WEL Well package 
Head dependent flux RIV River package 
EVT Evapotranspiration package 
GHB General head boundary package 
Sr. No.Hydro-GeologyPackagesDescriptions
Flow packages LPF Layer property flow package 
SWI2 Seawater intrusion package 
Specified head CHD Time variant specific package 
Specified flux RCH Recharge package 
WEL Well package 
Head dependent flux RIV River package 
EVT Evapotranspiration package 
GHB General head boundary package 
Table 7

Summary of the boundary conditions

Model componentDescription
Domain The model domain covers an area of approximately 110 km² 
Hydro-geological units Defined by three hydro-stratographic layers
  • Upper Aquifer

  • Middle Aquifer

  • Lower Aquifer

 
Model boundaries 
  • ○ The boundary for Upper Aquifer

  • • The observed groundwater level is used as hydraulic head boundary and used the fluid transfer boundary of surface water of the Arabian sea

  • ○ The boundary for Middle Aquifer

  • • The observed groundwater level is used as a hydraulic head boundary for the entire Layer.

  • ○ The boundary for the Lower Aquifer

  • • The observed groundwater level and hydraulic conductivity used a hydraulic head boundary for the entire outer boundary.

 
Groundwater recharge Recharge due to infiltration of rainfall and recharge well-considered to groundwater recharge 
Model componentDescription
Domain The model domain covers an area of approximately 110 km² 
Hydro-geological units Defined by three hydro-stratographic layers
  • Upper Aquifer

  • Middle Aquifer

  • Lower Aquifer

 
Model boundaries 
  • ○ The boundary for Upper Aquifer

  • • The observed groundwater level is used as hydraulic head boundary and used the fluid transfer boundary of surface water of the Arabian sea

  • ○ The boundary for Middle Aquifer

  • • The observed groundwater level is used as a hydraulic head boundary for the entire Layer.

  • ○ The boundary for the Lower Aquifer

  • • The observed groundwater level and hydraulic conductivity used a hydraulic head boundary for the entire outer boundary.

 
Groundwater recharge Recharge due to infiltration of rainfall and recharge well-considered to groundwater recharge 

MODFLOW simulation period

When running a transient model, the Time Steps selection is only open (i.e., when Transient Flow run type is selected) (Figure 3). MODFLOW consequently merges all of the distinctive time periods indicated for all of the individual pumping wells and boundary conditions into the uniform stress period format needed by MODFLOW for transient flow simulations. A stress period is described as a period of time during which all of the system's stresses (boundary conditions, pumping speeds, and so on) remain constant. Unfortunately, the data obtained for each modeling site in terms of stress periods are not aligned, so MODFLOW combines the time schedules for both pumping wells and boundary conditions to assess the duration of each stress period for a transient simulation.

Figure 1

Study area location.

Figure 1

Study area location.

Close modal
Figure 2

Location of well site.

Figure 2

Location of well site.

Close modal
Figure 3

MODFLOW time.

Model execution

Model Monitoring will start running MODFLOW after ModelMuse exports the MODFLOW input data. The percent discrepancy in the water budget is shown in Model Monitor's Results tab. This is a major concern if the percent discrepancy is greater than 1% at the end of the time phase. When Model Monitor is closed, the listing file will open in Notepad as shown in Figure 4. Simulation modeling calculation for ten years was done in the 100 steps and has been calculated in a single stress period as a steady-state simulation, and in the second step, period model would be a transient condition and count the next 100 steps for the next ten years to predict the salinity effect.

Figure 4

Model accuracy.

Groundwater quality index (GWQI)

The computed WQI values were divided into five categories, ranging from ‘excellent water’ to ‘water unfit for drinking.’ Table 8 indicates the proportion of water samples that fell into various content categories.

Table 8

Classification of water quality

GWQI ValueWater Quality
< 50 Excellent 
50–100 Good 
100–200 Poor 
200–300 Very poor 
> 300 Unfit for drinking purpose 
GWQI ValueWater Quality
< 50 Excellent 
50–100 Good 
100–200 Poor 
200–300 Very poor 
> 300 Unfit for drinking purpose 

The spreadsheet model was used to determine the change in groundwater quality from 2008 to 2018. The groundwater quality of the study area, including the southwest zone of the city, has been analyzed each year during the period of the ten years 2008–2018 and the results are outlined in the tables.

The overall result of the evaluation (each year 2008–2018) indicates the poor quality of water occurs in the study area as shown in Table 9, also shown in Figure 5 is the graphical representation of GWQI. The high value of WQI at this location has been found to be mainly from the higher values of nitrate, total dissolved solids, electrical conductivity, hardness, and magnesium in the groundwater.

Table 9

Result of GWQI for each year from 2008 to 2018

YearCaClECFMgNO3SO4Total HardnessTDSGWQI
2008 8.00 17.75 34.75 1.88 22.19 1.53 6.48 21.09 34.92 148.59 
2009 6.50 12.88 29.69 2.19 28.13 3.19 1.09 18.75 29.84 132.25 
2010 11.50 11.13 26.04 2.66 12.81 2.57 2.82 18.75 26.17 114.44 
2011 8.00 10.19 31.35 2.34 18.13 2.36 3.91 18.75 31.51 126.54 
2012 10.00 8.44 25.63 5.47 19.69 1.81 6.17 19.22 25.75 122.17 
2013 4.50 9.50 27.16 4.68 19.68 1.18 6.71 16.41 27.30 117.14 
2014 5.50 8.00 22.38 3.13 19.01 1.94 2.89 16.87 22.48 102.20 
2015 5.50 8.43 23.75 5.46 19.01 2.22 4.21 16.87 23.86 109.35 
2016 10.63 16.44 30.17 5.94 20.94 3.26 4.92 17.11 30.32 139.72 
2017 5.25 7.19 25.54 3.91 15.19 1.94 4.92 13.59 25.67 103.21 
2018 6.75 7.13 17.5 4.69 20.94 2.99 6.72 11.25 23.84 101.8 
YearCaClECFMgNO3SO4Total HardnessTDSGWQI
2008 8.00 17.75 34.75 1.88 22.19 1.53 6.48 21.09 34.92 148.59 
2009 6.50 12.88 29.69 2.19 28.13 3.19 1.09 18.75 29.84 132.25 
2010 11.50 11.13 26.04 2.66 12.81 2.57 2.82 18.75 26.17 114.44 
2011 8.00 10.19 31.35 2.34 18.13 2.36 3.91 18.75 31.51 126.54 
2012 10.00 8.44 25.63 5.47 19.69 1.81 6.17 19.22 25.75 122.17 
2013 4.50 9.50 27.16 4.68 19.68 1.18 6.71 16.41 27.30 117.14 
2014 5.50 8.00 22.38 3.13 19.01 1.94 2.89 16.87 22.48 102.20 
2015 5.50 8.43 23.75 5.46 19.01 2.22 4.21 16.87 23.86 109.35 
2016 10.63 16.44 30.17 5.94 20.94 3.26 4.92 17.11 30.32 139.72 
2017 5.25 7.19 25.54 3.91 15.19 1.94 4.92 13.59 25.67 103.21 
2018 6.75 7.13 17.5 4.69 20.94 2.99 6.72 11.25 23.84 101.8 
Figure 5

Graphical representation of GWQI.

Figure 5

Graphical representation of GWQI.

Close modal

The correlation matrix calculates the coefficients of correlation between groundwater quality components. These factors aim to reduce the intensity of the linear relationships among the variables. Both positive and negative connections have been estimated using it. Table 10 reveals a strong positive correlation that can be identified as Cl = 0.84 and EC = 0.93. Essential particle variables have also been shown to have poor connections (e.g., F and NO3). In the sample region, NO3 and important particles have negative and weak correlation coefficients.

Table 10

Correlation matrix of water quality parameters

CaClECFMgNO3SO4Total HardnessTDS
Ca 1.00         
Cl 0.46 1.00        
EC 0.28 0.80 1.00       
0.02 − 0.28 − 0.44 1.00      
Mg − 0.21 0.39 0.25 − 0.10 1.00     
NO3 0.38 0.18 − 0.13 0.06 0.29 1.00    
SO4 − 0.06 − 0.03 − 0.10 0.46 − 0.12 − 0.47 1.00   
Total Hardness 0.44 0.62 0.78 − 0.43 0.18 − 0.21 − 0.27 1.00  
TDS 0.30 0.84 0.93 − 0.45 0.37 0.01 0.07 0.61 1.00 
CaClECFMgNO3SO4Total HardnessTDS
Ca 1.00         
Cl 0.46 1.00        
EC 0.28 0.80 1.00       
0.02 − 0.28 − 0.44 1.00      
Mg − 0.21 0.39 0.25 − 0.10 1.00     
NO3 0.38 0.18 − 0.13 0.06 0.29 1.00    
SO4 − 0.06 − 0.03 − 0.10 0.46 − 0.12 − 0.47 1.00   
Total Hardness 0.44 0.62 0.78 − 0.43 0.18 − 0.21 − 0.27 1.00  
TDS 0.30 0.84 0.93 − 0.45 0.37 0.01 0.07 0.61 1.00 

Regional flow simulation in MODFLOW

The study region's simulated groundwater level contour for the rainy season 2018 is shown in Figure 6. It explains the recharge of groundwater during the monsoon season when the groundwater supply is recharged and the water level is in a protected zone due to high precipitation, and on the other hand, the water table has dropped significantly over the years, particularly during the dry season.

Figure 6

Regional flow simulation.

Figure 6

Regional flow simulation.

Close modal

The simulated contour and head of the study area are described in the color legend on the left (Figure 7). According to the DEM, the provincial head is higher due to the prevalence of low-lying regions on the red side. The blue region represents a drainage/river system where recharge has been detected. The appearance of a surface water body in the blue zone also indicates that the rate of evaporation in that study area is extremely high. The water table can be observed, which is available well at the depth of 30 m from the model top as shown in Figure 8.

Figure 7

Front cross section of the regional flow model.

Figure 7

Front cross section of the regional flow model.

Close modal
Figure 8

Top view result of the seawater intrusion model.

Figure 8

Top view result of the seawater intrusion model.

Close modal

Seawater intrusion modeling in MODFLOW

The results of the seawater intrusion modeling in Model Muse are presented in this section. The outcomes depict the action of the modeled aquifer of the study area. The piezometric levels as well as the salt water-fresh water interface shifts are presented in this section. Simultaneously modeling the aquifer was performed to ensure that the data represented the literature analysis and that it remained accurate in the modeling period.

The final results were then imported into Model Muse and adjusted using the trial-and-error method as well as a finer value for conductivity (transmissivity) and river conductance. As a result, the simulation has different effects on these input values depending on their yield. After that, the overall effect of these individual parameters on the salt water-fresh water interface was then determined. Combinations of factors are considered to be the most probable future scenarios.

The -10 (Figure 8) in this model denotes the seawater area where the value is negative, indicating that water with higher concentrations will flow out of the area, causing the groundwater to be affected by salinity effects. The cross-section in Figure 9 depicts the existing water level in the study area, where three wells were taken from the study area where the extraction rate was higher (150 l/m). In simulation modeling, 100 steps have been measured over ten years to see whether saltwater contamination has occurred in the existing groundwater, so at the 50th step if extraction continues at the same rate for the next five years, it will soon reach the water level (orange in color), and the modeling analysis for the next ten years will occupy the whole region due to higher extraction. The salt-producing method has been observed in the surrounding region during groundwater studies, which facilitates the accumulation of NA and K ions in the water level at shallow depth. Other reasons contribute to the accumulation of saltwater in groundwater, such as precipitation patterns, recharge, and climate change, which may also be responsible for an increase in seawater intrusion.

Figure 9

Cross section of the seawater intrusion model.

Figure 9

Cross section of the seawater intrusion model.

Close modal
Figure 10

Simulation of salinity effect: year 2008. The full colour versions of all figures are available in the online version of this paper, at http://dx.doi.org/10.2166/ws.2021.323.

Figure 10

Simulation of salinity effect: year 2008. The full colour versions of all figures are available in the online version of this paper, at http://dx.doi.org/10.2166/ws.2021.323.

Close modal

The simulation of salinity influence in the Upper, Middle, and Lower Aquifers in different years can be seen in Figure 10. The volume of salinity infiltrated in the different aquifers is shown by the color legend on the left side. Freshwater is often represented by blue, while salinity-affected regions are represented by red. The year 2008, depicts the freshwater area with a value of −1.4469 (l/m) and the salinity intruded areas with a value of 17.1141 (l/m). In the year 2013, Figure 11 depicts the freshwater area with a value of −1.94667 (l/m) and salinity intruded areas with a value of 15.3757 (l/m). In 2018, the freshwater area had a value of −2.33992 (l/m), while the salinity intruded zones had a value of 14.55137 (l/m). From 2008 to 2018 (Figure 12), the model was used to simulate all parameters in steady-state conditions, and from 2023 to 2028, the model was used to forecast salinity in transient conditions. In the year 2023, Figure 13 reveals the freshwater region's forecast of −0.3882 (l/m) and the salinity intruded areas’ prediction of 11.1544 (l/m). In the year 2028, Figure 14 reveals the freshwater area forecast of 0.00450785 (l/m) and the salinity intruded areas prediction of 10.4741 (l/m).

Figure 11

Simulation of salinity effect: year 2013.

Figure 11

Simulation of salinity effect: year 2013.

Close modal
Figure 12

Simulation of salinity effect: year 2018.

Figure 12

Simulation of salinity effect: year 2018.

Close modal
Figure 13

Prediction of salinity effect: year 2023.

Figure 13

Prediction of salinity effect: year 2023.

Close modal
Figure 14

Prediction of salinity effect: year 2028.

Figure 14

Prediction of salinity effect: year 2028.

Close modal

Planning proposal

To improve the resolution of groundwater quality problems in the study area, this study proposes two groundwater recharge wells along the Arabian Sea coast (Figure 15) near Sultanabad Village, where there are large communities that use groundwater for a variety of purposes, including drinking.

Figure 15

Recharge wells.

Figure 15

Recharge wells.

Close modal

Construction of the recharge wells would be easier than other artificial recharging methods, and while the recharge wells are on government property, there should be no political issues. These recharge wells infiltrate the freshwater into the aquifers and meet the freshwater chemical ions requirement, so these recharge wells must be supplied with fresh water. Boundary conditions, MODFLOW time; other wells' characteristics, all the parameters remain the same as the previous model, add another two recharge wells and both the recharge wells infiltrate the freshwater into the aquifers with the recharge rate of 6E-8. The recharge value is considered as (((((0.2 * 13000) - 700)/86400)/1000)/365), where 13000 is the elevation of Surat city (amsl), 700 is the level of sea-level rise each year, 86,400 is seconds of one day and 365 is number of days in one year. As per the simulation result with recharge salinity can be reduced at the desired level (Figure 16) by including two recharge wells near the low-lying area.

Figure 16

Simulation of salinity effect with recharge.

Figure 16

Simulation of salinity effect with recharge.

Close modal

The finding of the study indicates that the salinity contaminant spreads unevenly over the horizontal, resulting in finer concentration distributions. Additionally, more precise calculations of initial and final data values can be used to enhance the model. Multiple factors are affecting the quality of water in the South West Zone of Surat city are as follows:

  1. Salinity was observed to be very high in the study area as a result of less rainfall, precipitation patterns, recharge, and climate change, which includes an increase in sea level. Sea level rise could have drastic consequences, but it is manageable if sufficient measures are taken.

  2. The salt-producing process has been observed in the surrounding region during groundwater studies, which facilitates the accumulation of NA and K ions in the water level at shallow depth.

  3. It is necessary to establish an effective approach for scientifically monitoring salinity levels in groundwater, which will aid in the adoption of appropriate safety measures for the specific area and scenario.

  4. There is also a need to investigate unique and multi-component techniques for controlling seawater salinization, which should be re-aligned depending on the severity of the issue and the needs of various coastal regions.

  5. The best salinity control results require stakeholders and populations to be involved. For effective coastal salinity management, long-term routine monitoring, especially of groundwater level and salinity in coastal regions, is important.

  6. People living in coastal areas need to be aware of the hazards of excessive extraction and groundwater utilization. It aids in determining what types of prevention steps can be taken to avoid salinity intrusion.

  7. This would also help to ensure that departments are actively involved in environmental protection, river management, waterway prevention, and land management to salinity management improvements.

All relevant data are included in the paper or its Supplementary Information.

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