This paper aims to understand the general background of groundwater quality that must be considered for the 'smart city' planning of Surat city. Twenty-Six water samples collected from bore wells of the city were analyzed. The results showed that water is alkaline, as pH varies from 7.6 to 9.2. The concentration of Cl and Na+ are correlated with EC. The highest levels of Cl and Na+ are found near the coastal region (predominantly northwestern); Piper trilinear diagram shows 52% of samples are Na-HCO3 type and 48% NaCl type. WQI shows that most samples are potable for drinking, but a few samples from the western part are not suitable for drinking. SAR, Na%, and PI results show that most samples are suitable for irrigation. The corrosivity index indicates that 50% of samples have a CR > 1(unsafe zone), and the rest are within the safe limit. The relationship of WQI with different water quality parameters revealed that groundwater quality has deteriorated in the city's western part, which may be due to seawater intrusion in the aquifer. This work gives a basic idea of groundwater quality, which will help make Surat a smart city.

  • Assessment of Groundwater quality for ‘smarty city’ planning.

  • Determination of Seawater intrusion in a coastal aquifer (Surat city).

  • Hydrogeochemical investigation and groundwater quality assessment for drinking and agriculture purposes.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Groundwater is an essential water source worldwide and is much cleaner and free from pollutants compared to surface water. It plays a significant role in agricultural production, environmental sustenance, and sustainable economic development. But the release of industrial waste material, domestic sewage, and solid waste dumping decreases its quality. Water quality and its suitability for agriculture, drinking, and household purposes are mainly determined by its chemical, physical, and bacteriological parameters. (Mohammed-Aslam & Rizvi 2020; Warsi et al. 2022). The overall goal of any water quality assessment is to give a comprehensive picture of the spatial distribution of groundwater quality. (Machiwal et al. 2018). Once groundwater is polluted, this remains the same for decades or even hundreds of years. The world's developmental activities are growing faster for economic development and prosperity, but all this is happening at the expense of water resources (Arora & Mishra 2022; Garai et al. 2022). Through development, it is necessary to manage aquifers which are the source of fresh groundwater. It should not be stressed in terms of quantity and quality for a city.

Surat city, the ninth-largest city in India, is located on the left bank of the Tapi River (Tapti) in Peninsular India along the coast of South Gujarat. This city has diamond processing, engineering, oil and port-based business, textiles, and the petrochemical industries. Because of the over-drafting of groundwater, seawater intrudes into the city's aquifers and makes the freshwater salty (Desai & Desai 2012; Chaudhari et al. 2022). This salty water highly affects areas closest to the sea. Apart from this, water availability from the Tapi River is also not vast. Currently, available water is ∼700 ML/d, decreasing daily. Paneria & Bhatt (2017) have shown that by 2050, Surat city needs 900 ML/d, and water demand will overtake more or less 200 ML/d. Considering the above situations, the present study is carried out in Surat city, which is on the way to becoming the country's first ‘smart city’ under the ‘Smart City Mission by the Govt. of India. It aims to understand the aquifer system's spatial variations in quality by analyzing the major ion chemistry of groundwater and water level measurements in and around Surat. This quantitative and qualitative assessment of water resources will provide the general background of the aquifer system to urban planners that need to be considered for ‘smart city’ planning and water management in Surat.

The motivation for the work

Water is the primary element of ‘smart city’ planning. ‘Smart city’ planning is a visionary approach by Govt of India to integrate sustainable urban planning. The supply of safe and clean water to the city's people is a significant part of the ‘smart city’ approach. Because the city is located on the bank of the Arabian Sea, it is facing saltwater intrusion into the freshwater aquifer.

Structure of the paper

Section 1 is the general introduction describing the degrading quality and depletion of water, and the introductory part of Surat city Section 2 describes the study area and its geological and hydrogeological setup. Section 3 introduces the methodologies used in carrying out physic-chemical analyses. Then finally, Section 4 is the Results and Discussion part. Section 5 concludes the entire work and provides suggestions for improvement.

The study area, Surat city of state Gujarat, lies between 72.570159° E to 73.342910° E longitudes and 21.034461° north to 21.407916° north latitudes (Figure 1). It encompasses an area of about 3,218 km2. Tapi river flows through it and merges with the Arabian Sea. The district is one of the emerging urban centres in Gujarat near Magdalla and Hazira ports that support the industrial expansion with foreign countries. The city is mainly known for its diamond cutting, processing, and textile industries. Geographically, the district belongs to the western coastlands of the Deccan peninsula, mainly divided into hilly areas, alluvial plains, and coastal plains. The western and central part is dominated by alluvial plains formed by flood plains of river Tapi, Kim, and Purna. The alluvial plains merge into a dry, barren sandy coastal plain fringed by a marshy shoreline towards the west.
Figure 1

Base map with geology and well locations of the study area (number of wells is randomly given).

Figure 1

Base map with geology and well locations of the study area (number of wells is randomly given).

Close modal

Geological setup

Geographically, Gujarat state comprises three distinct zones, which are: (i) Mainland Gujarat, (ii) Saurashtra, and (iii) Kachchh. Surat district, where the present study has been conducted, lies in the south and forms a part of Mainland Gujarat.

Deccan traps surround the eastern part of the study region. In contrast, the central part is occupied by Quaternary deposits known as Gujarat alluvial plains, forming the coastal plains at the western boundary. The area consists of Quaternary alluvium, Tertiary limestone, sandstone, and Deccan Trap basalts. Deccan traps form the basement, where the formation consists of Bentonitic shale, friable sandstone, and. This is called Vagad khol Formation. Above Vagadkhol Formation is overlain by a Nummulitic limestone formation comprising Nummulitic limestone, clays with sandstone lenses. This formation is overlain by the Tadkeshwar Formation, consisting of lenses of carbonaceous clays, bentonite clay with lignite bed, sandstone, and lignite. Lignite occurs on the northern side of the area. Overlying these beds is the Babaguru Formation comprising ferruginous sandstone agate-bearing conglomerate (Chopra & Choudhury 2011).

Hydrogeological framework

The aquifer system is mainly formed by the alluvium in the central and western parts and by Deccan Trap basalts in the eastern region. Groundwater occurs in basaltic rock in semi-confined to unconfined conditions. Water movement in this type of aquifer is controlled by the weathered zones, fractures, and joints. Groundwater in the alluvium formation occurs in confined and semi-confined conditions, probably due to clay lenses. The data collected during the fieldwork shows that the depth of the water table ranges from 0.71 meters (m) below the ground level (bgl) to 28.14 m bgl. The deep water table (>20 m bgl) occurs at two locations, Galteshwar (22.82 m bgl) and Kadodra (28.14 m bgl), while the shallowest (<1 m bgl) is recorded at Vihan (0.71 m bgl). However, shallower levels between 1 to 4 m bgl occur as isolated patches scattered in the northeastern area and along the coastal plains in the western part (Figure 2). Generally, the groundwater flow is from the eastern side to the western side (Figure 3). The elevation of the water table varies from 0 m to 60 m AMSL.
Figure 2

Depth to water level map.

Figure 2

Depth to water level map.

Close modal
Figure 3

Water level contour map (m amsl).

Figure 3

Water level contour map (m amsl).

Close modal
The information on the stratification of different layers below the ground surface was obtained from the borehole data from which a cross-section was prepared (Figure 4) along line AB (Figure 1). Figure 4 shows that the topsoil is composed of black silty sand with sticky soil and is 3 m to 6 m bgl thick. The second layer is made up of clay varying in thickness from 3 m to 9 m. Below this, a thick sand layer forming the aquifer occurs from 33 m to 37 m, with a thickness of approximately 22 m. It consists of medium to coarse-grained sand mixed with yellow sticky clay and silt. There are several lenses of clay, clay mixed with sand kankers, and sand with boulder cutting.
Figure 4

Hydrogeological cross-section of the area long AB line.

Figure 4

Hydrogeological cross-section of the area long AB line.

Close modal
The present work involves water level monitoring and hydrogeochemical analysis of groundwater samples in October 2017, corresponding to the post-monsoon period. A total of 40 bore wells were selected for water level measurements. Of these, 40 and 26 used for drinking and irrigation were chosen for sampling and physico-chemical analysis (Figure 5). The samples were taken in 500 ml polythene, pre-labelled bottles. Before sampling, all bottles were washed 2–3 times with the same water to be sampled. Physico-chemical parameters such as pH, temperature, and EC were measured using portable Hanna water quality meters. The samples were filtered with 0.45 μm pore size filter paper. After filtration, concentrations of major cations such as Na+, Mg2+, Ca2+, and K+, and anions such as Cl, , , , and F in the samples were determined in the laboratory by Ion Chromatograph. and concentrations were determined by titration using HCl. Data obtained after the physico-chemical analysis of water samples were used to prepare spatial distribution maps of cations and anions using Surfer 11, piper trilinear, and Wilcox diagrams using AquaChem.
Figure 5

Monitoring and sampling points map (numbers are given randomly).

Figure 5

Monitoring and sampling points map (numbers are given randomly).

Close modal

The results of the hydrogeochemical analysis are shown in (Table 1).

Table 1

Statistical summary of the chemical composition of groundwater samples collected from the study area (Min minimum, Max maximum, σ standard deviation, CV coefficient of variation)

Chemical Constituents (mg/lMinMaxMeanσCV
pH (units) 7.6 9.2 8.25 0.343 0.042 
EC (μS/cm) 614 5,220 1,832 1,345.4 0.688 
TDS 399 3,393 1,191 874.5 0.688 
Ca2+ 0.002 26.08 10.89 5.73 0.526 
Mg2+ 5.14 50.83 24.09 12.56 0.521 
Na+ 33.10 300.2 185.9 56.47 0.303 
K+ 0.448 90.62 20.94 25.87 1.235 
 0.000 90 37.6 25.6 0.680 
 97.6 866.2 364.36 157.33 0.431 
Cl 22.7 2,240.3 467.82 574.2 1.227 
 0.201 2.73 0.524 0.506 0.965 
NO3 0.19 260.5 43.88 66.92 1.525 
0.134 2.769 0.647 0.595 0.919 
Chemical Constituents (mg/lMinMaxMeanσCV
pH (units) 7.6 9.2 8.25 0.343 0.042 
EC (μS/cm) 614 5,220 1,832 1,345.4 0.688 
TDS 399 3,393 1,191 874.5 0.688 
Ca2+ 0.002 26.08 10.89 5.73 0.526 
Mg2+ 5.14 50.83 24.09 12.56 0.521 
Na+ 33.10 300.2 185.9 56.47 0.303 
K+ 0.448 90.62 20.94 25.87 1.235 
 0.000 90 37.6 25.6 0.680 
 97.6 866.2 364.36 157.33 0.431 
Cl 22.7 2,240.3 467.82 574.2 1.227 
 0.201 2.73 0.524 0.506 0.965 
NO3 0.19 260.5 43.88 66.92 1.525 
0.134 2.769 0.647 0.595 0.919 

The pH of groundwater in the study area ranges from 7.6 to 9.2 (average 8.25), indicating that groundwater is alkaline. Values above 9 indicate the non-potability of water. Spatial distribution (Figure 6(a)) shows that t values below 8 occur on the western side; the rest of the area is characterized by values between 8 and 9. Only at one location pH above nine is recorded. It confirms that towards the west, pH is slightly reduced due to salinity, while there is a decrease in salinity moving towards the eastern part (Tetteh et al. 2020).
Figure 6

(a) Spatial distribution of pH. (b) Spatial distribution of EC. (c) Spatial distribution of TDS.

Figure 6

(a) Spatial distribution of pH. (b) Spatial distribution of EC. (c) Spatial distribution of TDS.

Close modal

EC is a reciprocal of resistivity and is expressed as μS/cm or mS/cm. In the study area, EC values range from 614 to 5,220 μS/cm, averaging 1,832 μS/cm. Through the area, EC > 1,500 μS/cm is found above the right bank of river Tapi but values greater than 4,000 μS/cm are found at locations 9 and 15 (Figure 6(b)). Higher EC values show that there may be an intrusion of seawater in the aquifer and also because several industries are located which contribute to the contamination of groundwater through their effluents.

TDS of the area ranges from 399 to 3,393 mg/l in this area (average 1,199 mg/l). All samples have TDS >500 mg/l except three (nos. 4, 16, and 22). The distribution map of TDS shows a similar pattern to EC, i.e., high TDS values in the western part of the area (Figure 6(c)).

Ionic distribution in the area

The concentration of major ions in the area is as follows: The order of abundance of major ions is Na > Mg > K > Ca; Cl > HCO3 > NO2 > CO3 > F > SO4.

As Ca and Mg are essential ions contributing to human health, concentration within recommended limits is necessary for dietary intake for excellent health, mainly bones, and teeth (Srivastava & Flora 2020). Ca and Mg concentrations vary from 0 to 26 mg/l and 5 to 51 mg/l, respectively. These two ions should have been derived from the dissolution of calc-concretions in the clay beds. The spatial distribution of Ca and Mg (Figure 7(a) and 7(b)) shows that a higher value (26 mg/l) occurs at location no. 8. As far as magnesium is concerned, higher concentrations (>30 mg/l) happen in the western, central, and southeastern parts at locations 2, 3, 12, 13, and 23. Agricultural activities in the eastern part are dominant in the study area; therefore, in terms of anthropogenic sources, fertilizers (magnesium sulphate, MgSO4) which are returned to the groundwater through irrigation return flow, may be the reason for high values in this part.
Figure 7

(a) Spatial distribution of calcium (Ca). (b) Spatial distribution of magnesium (Mg). (c) Spatial distribution of sodium (Na). (d) Spatial distribution of potassium (K). (e) Spatial distribution of chloride (Cl). (f) Spatial distribution of bicarbonate (HCO3). (g) Spatial distribution of carbonate (CO3). (h) Spatial distribution of nitrate (NO3).

Figure 7

(a) Spatial distribution of calcium (Ca). (b) Spatial distribution of magnesium (Mg). (c) Spatial distribution of sodium (Na). (d) Spatial distribution of potassium (K). (e) Spatial distribution of chloride (Cl). (f) Spatial distribution of bicarbonate (HCO3). (g) Spatial distribution of carbonate (CO3). (h) Spatial distribution of nitrate (NO3).

Close modal

Sodium is a constituent of clay minerals. The breakdown of clay minerals increases sodium concentration in groundwater (Fakhreddine & Fendorf 2021). The concentration of Na ranges between 33 to 300 mg/l. The higher concentration is found in the northern, central, and western areas (Figure 7(c)). The high concentration is close to the sea in the western region, resulting in seawater ingress and a high concentration of Na. Secondly, the increased Na in groundwater is likely due to the leaching of the effluents released from industries and fertilizer-irrigated water (Vushe 2019).

Potassium is found to be in a lower concentration in groundwater because of the high resistance of potash feldspar (K2O.Al2O3.6SiO2) to chemical weathering (Buvaneshwari et al. 2020). The K concentration in the area's groundwater samples ranges between 0.448 to 90.6 mg/l. The potassium concentration is increased in the western area but shows lesser values. Industrial activities and the cation-exchange process can contribute to high potassium content (Leal et al. 2013) (Figure 7(d)).

Chloride is crucial in tracing natural flow patterns because of its conservative nature. It does not readily react with minerals/chemicals and remains unaltered throughout the underground flow. The main reason for the chloride concentration in coastal areas is the ingress of seawater. Secondly, rainfall near the seacoast is enriched in chloride ions (Behera et al. 2019). Infiltrating water entering the sub-surface system increases the chloride concentration in groundwater. The concentration of Cl varies between 22.7 to 2,240 mg/l. Although chloride concentration throughout the area is high, the spatial distribution map shows that the southern and eastern part is characterized by low values below the left bank of river Tapi. In contrast, the north and western part is characterized by higher values (Figure 7(e)). The highest concentration is found in samples 9 and 15, i.e., 1,825 and 2,240 mg/l. It can be due to the ingress of saline water.

Carbonate and bicarbonate concentrations constitute alkalinity. The concentration of Carbonates and bicarbonates is dependent upon CO2 and is also a function of pH. The source of these ions includes carbonate rocks; the other is CO2 released from decaying organic matter combined with water, which also constitutes bicarbonates in groundwater. In the study area, the concentration of carbonates is generally low (Ranges between 0 to 90 mg/l), even within those areas where the lithology is limestone. It may be because of low solubility and a minor degree of mineralization. In the central and at one location in the northern part, concentration reaches up to 90 mg/l. Otherwise, low concentration is observed in other regions (Figure 7(f) and 7). Carbonate concentration in the western part is low because of high salinity.

The sulphate concentration ranges between 0.201 to 2.73 mg/l, which is low throughout the area, and fluoride ranges between 0.13 to 2.769 mg/l, which is also within limits except at one location, within boundary limits.

Nitrates in groundwater usually come from agricultural activities utilizing fertilizers, seepage of the liquids due to sewage and septic tanks, and industrial effluents (Ducci 2018). Figure 7 shows the spatial distribution of nitrate where the concentration of nitrate is high at six places (9, 12, 13, 14, 18, and 23).

From the results of the physic-chemical analysis of groundwater samples of the study area, it has been observed that the concentration of most of the ions, mainly Ca2+, Mg2+, Na+, Cl, are high, mainly in the western part of the area. High concentration is found in the samples collected from locations very close to the sea, suggesting that the ingress of saline water makes the ions' concentration high in groundwater. Secondly, several industries are located in this region, and the leaching of the effluents released from industries also contributes ions to the groundwater.

Classification of groundwater

Piper's trilinear diagram

Based on Piper's trilinear diagram, groundwater can be classified by plotting the concentration of cations and anions in mEq/l. This diagram helps organize the hydrochemical data into facies based on the similarity in chemical composition. The fields categorize water into different types such as CaSO4 type (Gypsum groundwater and mine drainages), CaHCO3 type (shallow fresh groundwater), NaHCO3 type (Deeper groundwater influenced by ion exchange), and NaCl type (Marine and deep ancient groundwater) (Piper 1944). Our collected samples are only confined to the two fields, 52% in sodium bicarbonate and 48% in sodium chloride. It indicates the movement of saline water to the deeper aquifers (Alaya et al. 2014). The intrusion of saline water comes from the Arabian Sea and the presence of creeks (Tena creek, Hazira Creek, Mindhola creek). It represents a constant interaction between the sea and the aquifers.

Suitability of groundwater for drinking

The water for drinking should be clean, safe, and free from microorganisms, turbidity, and colour. To know the suitability of water for a particular purpose, especially drinking and irrigation, it is essential to compare the concentration of its constituents with the limits recommended by WHO (2017) and BIS (2022). In the present study, chemical parameters obtained from the analysis are compared with the limits prescribed by WHO (2017) and BIS (2022) (Table 2), indicating that pH, Ca, Mg, and SO4 present in samples are within the range of limits. However, EC, TDS, Cl, HCO3, NO3, and PO4 exceed the standards given by WHO (2017). EC values >1,000 μS/cm have been found in 17 samples, viz. 2, 5, 6, 7, 8, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 23, and 25. EC >4,000 has been found at 2 locations, i.e., Tena (9) and Malgama (15). Considering the classification for TDS, three samples (4, 16, and 22) are desirable, and 12 samples (1, 2, 3, 6, 7, 12, 17, 21, 23, 24, 25, and 26) are permissible for drinking purposes, two samples (9 and 15) are unsuitable for drinking purposes (Figure 8). Based on the classification of chloride given by Stuyfzand (1989), none of the samples seems to fall into the ‘Fresh Water’ category. All the samples belong to the brackish (3 samples), salty (15 samples), and hypersaline (8 samples) categories (Table 3).
Table 2

Range of physico-chemical parameters of groundwater and their comparison with drinking water standards

S. no.Water quality parametersRange in the study area
Most desirable limitMaximum permissible limits
pH 6.5–8.5 6.5–9.5 7.6–9.2 
EC 1,500  614–5,220 
TDS 500 600 399–3,393 
Ca 75 200 0.002–26.0 
Mg 50 100 5–50.8 
Na 200 200 33–300 
55  0.448–90.6 
CO3 –  0–90 
HCO3 1,000  97–866 
10 Cl 200 1,000 22.7–2,240 
11 SO4 200 400 0.201–2.7 
12 NO3 45  0.19–260.4 
S. no.Water quality parametersRange in the study area
Most desirable limitMaximum permissible limits
pH 6.5–8.5 6.5–9.5 7.6–9.2 
EC 1,500  614–5,220 
TDS 500 600 399–3,393 
Ca 75 200 0.002–26.0 
Mg 50 100 5–50.8 
Na 200 200 33–300 
55  0.448–90.6 
CO3 –  0–90 
HCO3 1,000  97–866 
10 Cl 200 1,000 22.7–2,240 
11 SO4 200 400 0.201–2.7 
12 NO3 45  0.19–260.4 
Table 3

Classification of groundwater based on TDS and chloride

ParametersRangeClassificationSamples
TDS <500 Desirable for drinking 4, 16, 22 
500–1,000 Permissible for drinking 1, 2, 3, 6, 7, 12, 17, 21, 23, 24, 25, 26 
1,000–3,000 Useful for agriculture 5, 8, 10, 11, 13, 14, 18, 19,20 
>3,000 Unfit for both drinking and irrigation 9, 15 
Chloride (Stuyfzand 1989<0.141 Extremely fresh  
0.141–0.846 Very fresh  
0.846–4.231 Fresh  
4.231–8.462 Fresh brackish  
8.462–28.064 Brackish 1, 3, 4 
28.064–564.127 Salt 2, 5, 6, 7, 11, 12, 16, 17, 18, 21, 22, 23, 24, 25, 26 
>564.127 Hyperhaline 8, 9, 10, 13, 14, 15, 19, 20 
ParametersRangeClassificationSamples
TDS <500 Desirable for drinking 4, 16, 22 
500–1,000 Permissible for drinking 1, 2, 3, 6, 7, 12, 17, 21, 23, 24, 25, 26 
1,000–3,000 Useful for agriculture 5, 8, 10, 11, 13, 14, 18, 19,20 
>3,000 Unfit for both drinking and irrigation 9, 15 
Chloride (Stuyfzand 1989<0.141 Extremely fresh  
0.141–0.846 Very fresh  
0.846–4.231 Fresh  
4.231–8.462 Fresh brackish  
8.462–28.064 Brackish 1, 3, 4 
28.064–564.127 Salt 2, 5, 6, 7, 11, 12, 16, 17, 18, 21, 22, 23, 24, 25, 26 
>564.127 Hyperhaline 8, 9, 10, 13, 14, 15, 19, 20 
Figure 8

Piper's trilinear diagram.

Figure 8

Piper's trilinear diagram.

Close modal

Water quality index (WQI)

WQI is calculated to assess groundwater's suitability for drinking. This method helps classify the samples from ‘excellent’ to ‘water unsuitable for drinking.’ (Vasanthavigar et al. 2010). In this method, the parameters of concern for drinking purposes are given a weight according to their relative importance using this equation given below:
Wi indicates ‘relative weight,’ wi means ‘weight of each parameter,’ and n is the number of parameters. A ‘quality rating’ scale (qi) for each parameter is assigned by dividing its concentration in each water sample by the respective standard, multiplied by 100.
Ci indicates ‘concentration of chemical parameter’; Si is standard drinking water (BIS prescribes). ‘SI’ is calculated for each parameter. Finally, WQI is computed
According to the WQI classification given in Table 4, collected samples belong to the ‘excellent’ to ‘very poor water’ category. The spatial distribution map (Figure 9) shows higher values in the western part, while low values are observed in the central and northern regions. Along the coast of the Arabian Sea, the presence of several industries in the western part makes it more vulnerable to contamination. It is why getting higher values of WQI are observed in this part.
Table 4

Water quality index range

RangeType of groundwaterSamples
<50 Excellent 1, 2, 3, 4, 16, 21, 22, 24, 26 
50–100 Good water 5, 6, 7, 12, 13, 17, 18, 23, 25 
100–200 Poor water 8, 10, 11, 14, 19, 20 
200–300 Very poor water 9 and 15 
>300 Unsuitable  
RangeType of groundwaterSamples
<50 Excellent 1, 2, 3, 4, 16, 21, 22, 24, 26 
50–100 Good water 5, 6, 7, 12, 13, 17, 18, 23, 25 
100–200 Poor water 8, 10, 11, 14, 19, 20 
200–300 Very poor water 9 and 15 
>300 Unsuitable  
Figure 9

Spatial distribution of water quality index.

Figure 9

Spatial distribution of water quality index.

Close modal

Suitability of groundwater for irrigation purposes

The quality of groundwater is equally essential for irrigation, but the presence of salts in groundwater makes it undesirable. Salts in higher concentrations lead to changes in soil composition and structure, decreasing soil permeability and affecting plant growth. Salts in the soil increase the osmotic pressure and decrease water uptake to the plants. Some important parameters to judge the suitability of groundwater for irrigation purposes are sodium percentage (%Na), SAR, and permeability index (PI).

Sodium percentage (%Na)

The concentration of Na+ affects the soil as it reduces the soil permeability (Okur & Örçen 2020). Na in groundwater is a significant parameter for judging the suitability of water for agriculture/irrigation (Wilcox 1948). The %Na is calculated concerning relative proportions of cations (in mEq/l) and is represented by
The amount of %Na concentration in groundwater ranges from 55.5 to 91.4. %Na is not suitable if exceeding >60%. Table 5 shows that a minimal number of the samples fall into the excellent, reasonable, or permissible category. Most of the samples either belong in the ‘Doubtful’ or ‘Unsuitable’ category. EC and Na% are plotted together, which shows that except for three samples (nos. 3, 17, and 22), samples fall in the ‘Permissible to Doubtful,’ ‘Doubtful to Unsuitable,’ and ‘Unsuitable’ category (Figure 10).
Table 5

Classification of groundwater based on different parameters

ParameterClassCategorySamples
% Na Class I Excellent to good 17, 22 
Class II Good to permissible 
Class III Permissible to doubtful 1, 2, 4, 7, 13, 16, 21, 23, 24, 26 
Class IV Doubtful to unsuitable 5, 6, 8, 12, 14, 18, 20, 25 
Class V Unsuitable 10,19 
SAR Class I Good water 1, 2, 3, 7, 22, 23, 26 
Class II Moderate water 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 24, 25 
Class III Bad water 9, 15 
PI Class I Maximum permeability 23 
Class II 75% of Max. permeability 2, 3, 5, 6, 8, 12, 13,15, 16, 20, 24 
Class III 25% of Max. permeability 1, 4, 7, 9, 10, 11, 14, 17, 18, 19, 21, 22, 25, 26 
ParameterClassCategorySamples
% Na Class I Excellent to good 17, 22 
Class II Good to permissible 
Class III Permissible to doubtful 1, 2, 4, 7, 13, 16, 21, 23, 24, 26 
Class IV Doubtful to unsuitable 5, 6, 8, 12, 14, 18, 20, 25 
Class V Unsuitable 10,19 
SAR Class I Good water 1, 2, 3, 7, 22, 23, 26 
Class II Moderate water 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 24, 25 
Class III Bad water 9, 15 
PI Class I Maximum permeability 23 
Class II 75% of Max. permeability 2, 3, 5, 6, 8, 12, 13,15, 16, 20, 24 
Class III 25% of Max. permeability 1, 4, 7, 9, 10, 11, 14, 17, 18, 19, 21, 22, 25, 26 
Figure 10

Suitability of irrigation water, based on EC and sodium percent (after Wilcox 1948).

Figure 10

Suitability of irrigation water, based on EC and sodium percent (after Wilcox 1948).

Close modal

Sodium adsorption ratio (SAR)

SAR is the Na concentration ratio to the square root concentration of the average (Ca + Mg) concentration in either irrigation water or the soil solution (Rizvi & Mohammed-Aslam 2019). SAR leads to a change in soil structure. The soil becomes very hard and impervious when cation exchange occurs in soil concerning Na, Ca, and Mg. Concerning the limits given in Table 5, collected samples are suitable for irrigation uses as most of the samples fall in the ‘Good’ and ‘Moderate’ categories (Figure 11). Since sample no. 15 has EC greater than 5,000 μS/cm, and this figure does not show.
Figure 11

Classification of irrigation waters.

Figure 11

Classification of irrigation waters.

Close modal

Permeability index (PI)

In 1964, Doneen gave the criteria to assess the permeability of the soil. He states that water with high salt content directly affects the permeability of soil in the long term(Doneen 1964). The following equation provides it:
Here, three main classes have been given; class I (>75%) corresponds to good permeability; class II (25–75%) suggests moderate permeability. Class III (<25%) indicates low permeability. Values under class I indicate ‘excellent quality of groundwater for agriculture. Class II indicates ‘good quality of groundwater for agriculture, and class III indicates ‘unsuitability’ of water for irrigation. Figure 12 shows the distribution of the samples falling into the different classes. According to the classification given in Table 5, values are divisible into excellent (23), good (2, 3, 5, 6, 8, 12, 13,15, 16, 20, 24), and unsuitable (1, 4, 7, 9, 10, 11, 14, 17, 18, 19, 21, 22, 25, 26) for irrigation.
Figure 12

Classification of irrigation water based on permeability index (PI).

Figure 12

Classification of irrigation water based on permeability index (PI).

Close modal

Corrosivity ratio (CR.)

‘Smart city’ needs fast and safe water, oil, and gas supply, achieved by connecting pipes throughout the city. The corrosivity ratio assesses the pipes' feasibility and safety and the groundwater's susceptibility to corrosion. It is usually expressed below the equation.
The corrosion effects are loss in pipes' hydraulic capacity. Lazur et al. (2020) have worked on the corrosive tendency of groundwater on metallic pipes. The corrosivity index shows if CR > 1 is highly corrosive and unsafe for metallic pipes and if CR <1 lies in the safe zone for supplying water through ant pipes. In the area where groundwater has CR > 1, only polyvinyl chloride (PVC) pipes should supply water or any other pipelines beneath the earth. Figure 13 shows that 50% of the area, primarily the northwest part, is highly corrosive, where the CR > 12 may be caused by saltwater intrusion. This area wants special care for water supply through the pipe by the ‘smart city’ planners.
Figure 13

Spatial distribution of corrosivity ratio.

Figure 13

Spatial distribution of corrosivity ratio.

Close modal

Management of water resources in ‘smart city’ planning

WHO (2004) reported that nearly 80% of water infections are caused by polluted water consumption, and almost 35% of the deaths in developing countries are caused due to polluted consumption of water. Water pollution severely damages the ecosystem, reducing agricultural production (Karanth 1987). The study results show that aquifers in the western part of Surat city are under the influence of saltwater intrusion. Many industries are located in this area, which is the main reason for groundwater exploitation and results in seawater intrusion. It affects groundwater quality and renders them unfit for drinking or irrigation uses.

To improve groundwater quality and quantity, the following management plans are suggested that will be helpful in ‘smart city’ planning and water resource management.

Managed aquifer recharge (MAR) techniques can increase groundwater quality. It can also reduce saltwater intrusion and protects soils. MAR increases crop yields, especially in the western part of Surat city and the coastal area. Geophysical methods (ERT, VES, TEM) can be used for aquifer mapping for suitable MAR sites and safe drinking water zone. Different treatment methods for groundwater (defluoridation, demineralization of water, ion exchange, and water softening) should be used to reduce concentrations of those ions that currently exceed the permissible limit for drinking water and irrigation purposes. It is suggested to avoid the excessive use of fertilizers in the agricultural field for higher crop yields. The corrosivity index should be followed in transporting groundwater or any other pipeline beneath the earth's surface throughout the city. The selection of crop type should be based on quality, availability, and water needs. An awareness program on ‘Environmental changes and their impact on human life’ should be started to reduce human activity on pollution because we never get sustainable development without local community support.

Groundwater is mainly alkaline as pH varies from 7.6 to 9.2 (average 8.3). The groundwater quality in the northwestern part is primarily influenced by saltwater intrusion and anthropogenic activities. About 85% of samples have TDS levels above the drinking water standards. About 23% of water samples contain a more significant amount of NO3, showing the occurrence of sewage, septic tanks, and industrial effluents. The concentration of chloride (Cl) and sodium (Na) was positively correlated with electrical conductivity (EC). The highest concentration of Cl and Na were found near the coastal region, especially in the northwestern part showing the influence of the saltwater intrusion. The Piper trilinear diagram identified 52% sodium bicarbonate (Na-HCO3) type and 48% sodium chloride (NaCl) type of water in the study area, indicating the movement of saline water to the deeper aquifers. The WQI shows that for drinking, 31%, 38, 23, and 8% of the water samples are ‘excellent,’ ‘good,’ ‘poor,’ and ‘very poor.’ The results of SAR (43% ‘good, 52% moderate, and 5% unsuitable), Na% (43% good, 44% moderate, and 13% unsuitable), and PI (5% excellent, 43% good, and 52% unsuitable) show that most of the samples are suitable for irrigation. 50% of the area, especially in the northwest, has a high corrosive value of CR > 1, showing the ingress of saline water. The rest of the area, mainly the left bank of the river, offers a safe zone value of CR. The WQI with the spatial distribution of different water quality parameters revealed that groundwater quality has deteriorated on the western side of Surat city. This paper provides a general background to urban planners that need to be considered for ‘smart city’ planning and water management in Surat.

The authors gratefully acknowledge Director, CSIR-NGRI, India, for permitting them to publish this paper. The authors would like to acknowledge Dr K Ram Mohan, hydro geochemistry group, NGRI, for sample analysis and his valuable suggestions. The authors also thank Dr Subhas Chandra, Veema Raju, and Dr Sahebrao Sonkamble for their help and support. This is part of the project work funded by Surat Municipality Corporation for ‘smart city’ planning.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.

Arora
N. K.
&
Mishra
I.
2022
Sustainable development goal 6: global water security
.
Environmental Sustainability
5
,
271
275
.
Buvaneshwari
S.
,
Riotte
J.
,
Sekhar
M.
,
Sharma
A. K.
,
Helliwell
R.
,
Kumar
M. S.
,
Braun
J. J.
&
Ruiz
L.
2020
Potash fertilizer promotes incipient salinization in groundwater irrigated semi-arid agriculture
.
Scientific Reports
10
(
1
),
1
14
.
Chopra
S.
&
Choudhury
P.
2011
A study of response spectra for different geological conditions in Gujarat, India
.
Soil Dynamics and Earthquake Engineering
31
(
11
),
1551
1564
.
Desai
B.
&
Desai
H.
2012
Assessment of water quality index for the groundwater with respect to saltwater intrusion at coastal region of Surat city, Gujarat, India
.
Journal of Environmental Research And Development
7
(
2
),
607
621
.
Doneen
L. D.
1964
Notes on Water Quality in Agriculture
.
Department of Water Science and Engineering, University of California
,
Davis
.
Fakhreddine
S.
&
Fendorf
S.
2021
The effect of porewater ionic composition on arsenate adsorption to clay minerals
.
Science of The Total Environment
785
,
147096
.
Garai
T.
,
Biswas
G.
&
Santra
U.
2022
A Novel MCDM Method Based on Possibility Mean and Its Application to Water Resource Management Problem Under Bipolar Fuzzy Environment
. In:
International Conference on Intelligent and Fuzzy Systems
.
Springer
,
Cham
, pp.
405
412
.
IS10500, B. I. S.
2022
Indian Standard Drinking Water–Specification (Second Revision)
.
Bureau of Indian Standards (BIS)
,
New Delhi
.
Karanth
K. R.
1987
Groundwater Assessment: Development and Management
.
Tata McGraw-Hill Education, Publishing Company Limited
,
New Delhi
.
Leal
R. M. P.
,
Alleoni
L. R. F.
,
Tornisielo
V. L.
&
Regitano
J. B.
2013
Sorption of fluoroquinolones and sulfonamides in 13 Brazilian soils
.
Chemosphere
92
(
8
),
979
985
.
Machiwal
D.
,
Cloutier
V.
,
Güler
C.
&
Kazakis
N.
2018
A review of GIS-integrated statistical techniques for groundwater quality evaluation and protection
.
Environmental Earth Sciences
77
(
19
),
1
30
.
Okur
B.
&
Örçen
N.
2020
Soil salinization and climate change
. In:
Climate Change and Soil Interactions
(M. N. V. Prasad and Marcin Pietrzykowski, eds).
Elsevier
, pp.
331
350
.
Paneria
D. B.
&
Bhatt
B. V.
2017
Analyzing the existing water distribution system of Surat using Bentley Water GEMS
.
Journal of Emerging Technologies and Innovative Research
4
(
05
),
19
23
.
Piper
A. M.
1944
A graphic procedure in the geochemical interpretation of water-analyses
.
Eos, Transactions American Geophysical Union
25
(
6
),
914
928
.
Srivastava
S.
&
Flora
S. J. S.
2020
Fluoride in drinking water and skeletal fluorosis: a review of the global impact
.
Current Environmental Health Reports
7
(
2
),
140
146
.
Stuyfzand
P. J.
1989
A new hydrochemical classification of water types
.
IAHS Publications
182
,
89
98
.
Tetteh
J. T.
,
Alimoradi
S.
,
Brady
P. V.
&
Ghahfarokhi
R. B.
2020
Electrokinetics at calcite-rich limestone surface: understanding the role of ions in modified salinity waterflooding
.
Journal of Molecular Liquids
297
,
111868
.
Vasanthavigar
M.
,
Srinivasamoorthy
K.
,
Vijayaragavan
K.
,
Rajiv Ganthi
R.
,
Chidambaram
S.
,
Anandhan
P.
,
Manivannan
R.
&
Vasudevan
S.
2010
Application of water quality index for groundwater quality assessment: thirumanimuttar sub-basin, Tamilnadu, India
.
Environmental Monitoring and Assessment
171
(
1
),
595
609
.
Vushe
A.
2019
Nitrate-nitrogen pollution and attenuation upstream of the Okavango delta in Angola and Namibia
.
Agriculture and Ecosystem Resilience in Sub Saharan Africa
,
Springer,
pp.
99
128
.
Warsi
T.
,
Mukherjee
S.
,
Biswas
G.
,
Mitran
T.
&
Rizvi
S. S.
2022
Urban water resources and its sustainable management
. In:
Current Directions in Water Scarcity Research
, Vol.
6
(A. K. Singh, A. L. Srivastav, E. Valsami-Jones & S. Madhav, eds).
Elsevier
, pp.
489
509
.
Wilcox
L. V.
1948
The Quality of Water for Irrigation use (No. 1488-2016-124600)
.
World Health Organization
2004
World Health Organisation Staff Guidelines for Drinking-Water Quality (Vol. 1)
.
World Health Organization
,
Geneva, Switzerland
.
World Health Organization 2017 Guidelines for Drinking-Water Quality: First Addendum to the Fourth Edition. World Health Organization, Geneva, Switzerland.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/).