Groundwater dependency has increased due to several factors like population increase, industrialization, and climate change impact. Analysis of groundwater is important to know the present status and also for better management of natural resources. Groundwater samples from 41 locations were collected along the study area during the pre and post-monsoon seasons, and samples were analysed for pH, EC, total dissolved solids (TDS), major cations, and anions like Ca2+, Mg2+, Na+, K+, Cl, HCO3 and SO42−. From the chemical analysis results, seawater intrusion is identified through qualitative approaches, i.e., Simson ratio (Cl/(HCO3 + CO3) and Na/Cl ratio. Simson ratio ranges between 0.316 to 2.119 during pre-monsoon and 0.124 to 3.947 during post-monsoon, and from Na/Cl ratio, 30 samples fell under seawater intrusion during pre-monsoon and 38 samples during post-monsoon. The Simpson ratio results also show that seawater intrusion is reducing during the post-monsoon due to increasing groundwater levels caused by rains. From the water quality index classification, 4.88% of the water samples fell under excellent in both seasons, and the rest of the samples were all in the remaining four classes. The spatial analysis was also done to understand the changes in groundwater quality and seawater intrusion over space.

  • Assessment and status of groundwater quality in the coastal area.

  • Factors controlling groundwater quality in the study area.

  • Analysis of seawater intrusion risk assessment.

  • Identification of water suitability for drinking purposes.

  • Spatial analysis for identification of areas under threat.

Groundwater has become an important source to meet all freshwater needs, including domestic and agricultural demands (Saha & Ray 2019). India ranks among the highest in terms of groundwater extraction compared to other countries (Al-Omran et al. 2018; Sircar et al. 2021). Over usage of groundwater has contributed to the depletion of groundwater resources worldwide, and India is one of the severe victims of that (Asante-Annor et al. 2018; Ersoy et al. 2021).

Visakhapatnam is a coastal city that has increased stress in groundwater due to an increase in industries and population. Assessment of groundwater quality in the Visakhapatnam coastal aquifer is necessary to know the present status of the aquifer. Groundwater quality analysis is the most effective for the development and sustainable management of water resources (Bear 1999; Hussien & Faiyad 2016). In this study, groundwater quality assessment is employed for Visakhapatnam groundwater aquifers.

Evaluation of the type of salts present in the study area and components controlling their ion formation are essential to know the source of abstracted water (Goyal et al. 2010; Wei et al. 2020). The origin of the groundwater in an aquifer can be identified by analysing the hydrochemical facies (Shelton et al. 2018; Aladejana et al. 2021). In this study, an attempt has been made to determine the presence of brackish water due to seawater intrusion.

The study area is Visakhapatnam, which is positioned along the east coast of Andhra Pradesh in India at latitude 17°45′ North and longitude 83°16′ East. The study area and locations of the wells are shown in Figure 1. The rapid growth of population, industry, and agricultural practice has increased the significant diversion of surface water. To meet the requirements, dependence on groundwater is increasing. The exploitation of groundwater leads to the scarcity of groundwater, causing deterioration of water quality. For this study, 41 groundwater wells were considered from three Mandals, i.e., Bheemunipatnam, Visakhapatnam rural, and Visakhapatnam urban areas in Visakhapatnam.
Figure 1

Study area map.

Groundwater samples were collected from 41 groundwater wells at different locations in the study area during the pre-monsoon (PRMS) and post-monsoon (POMS) in the year 2021 to evaluate the groundwater quality. Bore wells were continuously pumped for a minimum of 10 min before collecting the samples, and then the samples were collected using HDPE (high-density polyethylene) bottles. Sample bottles were rinsed and washed properly with deionised water before the sample collection. The samples were preserved as per the standard methods according to APHA (American Public Health Association). The methodology adopted for this study is shown in Figure 2. Standard procedures (Adimalla & Wu 2019; Gaikwad et al. 2020) have been applied to analyse the collected samples in the study area. Physicochemical parameters such as pH are measured by a pH meter (ELICO L1617) and electrical conductivity (EC) is measured by using an EC meter (ELICO CM180). and anions were determined by the titration method. Cations (Ca2+, Mg2+, Na+, and K+) and anions (Cl, , and ) were determined by 930 compact ion flex chromatograph as per 4100B of APHA.
Figure 2

Flow-chart of the methodology.

Figure 2

Flow-chart of the methodology.

Close modal

Identification of seawater intrusion

There are many indicators to identify seawater intrusion from other sources of salinity, like an elevated chloride concentration, Cl/Br ratio, Na/Cl ratio, Simpson ratio, base exchange indices, etc. From the results of chemical analysis, seawater intrusion is identified through qualitative approaches (Bear 1999). Na/Cl ratios are calculated in the study area, and a ratio of <0.86 indicates that the water is affected by seawater and a ratio of >1 indicates that the water is affected by anthropogenic activities (Brown et al. 1972; Zhi et al. 2021). The Simpson ratio (Todd 1959) is described as the ratio of Cl/(HCO3 + CO3). There are five classes to identify the level of groundwater contamination: a ratio of <0.5 indicates good quality water, a ratio of 0.5–1.3 indicates slightly contaminated water, a ratio of 1.3–2.8 indicates moderately contaminated water, a ratio of 2.8–6.6 indicates injuriously contaminated, and a ratio of 6.6–15.5 indicates highly contaminated water.

Water quality index

To analyse the water quality based on various parameters present in the collected samples, the water quality index mathematical model (Gupta et al. 2009; Hora et al. 2019) is the robust method. In this water quality index, the first step is to assign the weights to each parameter based on the relative importance of the water quality of drinking water. The weights of the parameters total dissolved solids (TDS), pH, EC, Ca2+, Na+, Mg2+, K+, Cl, , , and total hardness are assigned 1 to the maximum weight of 5. The relative weight Wi of each parameter is calculated by the following equations:
formula
(1)
where ‘wi is the assigned weight of each parameter and ‘n’ is the number of parameters.
After calculating relative weight, the next step is to calculate the quality classification. The quality rating scale of each element is calculated by dividing the analysed concentration of each parameter by the standard value and multiplying it by 100:
formula
(2)
where ‘Ci’ is analysed as the concentration of chemical parameters of each sample and ‘Si’ is the standard value of the parameter.
The final step of the water quality index is to calculate the sub-index of the ith parameter ‘Sli’ of each parameter. It is calculated by multiplying the relative weight and quality rating scale:
formula
(3)
The water quality index ‘Wqi’ is given by:
formula
(4)

The water quality index ‘Wqi’ has been classified into five classes: excellent, good, poor, very poor water, and unsuitable for drinking.

Spatial variation of groundwater quality

In the present study, the spatial analysis aims to understand the changes in groundwater quality over space. For proper management of natural water resources, spatial analysis is one of the vital techniques. The present work studied the spatial analysis of groundwater quality of 41 samples in the year 2021 of PRMS and POMS. A Geographical Information System has been used for spatial analysis. The Inverse Distance Weighted (IDW) method (Goyal et al. 2010; Kumar et al. 2018) is applied to develop the seasonal groundwater quality maps.

Hydrochemical analysis of groundwater

Groundwater samples collected from 41 wells in Visakhapatnam coastal area during PRMS and POMS, i.e., June 2021 and November 2021, were analysed for EC, pH, major anion, and cations. Table 1 shows chemical parameters that are analysed.

Table 1

Seasonal variation of chemical parameters in the study area

S. No.Chemical parameterPre-monsoon
Post-monsoon
BIS 2012
Minimum valueMaximum valueMeanStandard deviationMinimum valueMaximum valueMeanStandard deviation
pH 6.18 8.90 7.99 0.65 6.03 8.56 7.33 0.76 6.5–8.5 
Electrical conductivity (EC) 330.00 5,300.00 1,196.44 794.05 240.00 7,020.00 897.56 1,061.04 1,500 μS/cm 
Total dissolved solids (ppm) 211.20 3,392.00 765.67 508.17 153.60 4,492.80 574.44 679.07 500 mg/L 
Bicarbonate (ppm) 50.00 420.00 197.67 91.62 50.00 504.00 260.24 103.45 300 mg/L 
Chloride (ppm) 38.00 890.10 174.82 156.49 14.94 863.21 174.69 156.46 250 mg/L 
Fluoride (ppm) 0.04 200.00 34.26 51.94 0.12 919.93 45.75 143.40 1.5 mg/L 
Nitrate (ppm) 0.11 45.26 8.67 13.00 0.09 940.50 135.88 190.01 45 mg/L 
Sulphate(ppm) 0.33 215.00 59.66 59.87 1.95 292.56 82.14 59.60 200 mg/L 
Sodium (ppm) 23.10 621.40 111.37 101.63 14.01 585.68 71.62 86.86 200 mg/L 
10 Potassium (ppm) 0.26 104.40 14.72 20.33 0.85 53.98 7.49 10.72 12 mg/L 
11 Calcium (ppm) 8.00 144.00 48.15 29.40 1.46 31.67 13.81 8.18 75 mg/L 
12 Mg Magnesium (ppm) 19.40 102.10 47.22 24.12 0.27 84.69 29.50 17.01 48.15 
S. No.Chemical parameterPre-monsoon
Post-monsoon
BIS 2012
Minimum valueMaximum valueMeanStandard deviationMinimum valueMaximum valueMeanStandard deviation
pH 6.18 8.90 7.99 0.65 6.03 8.56 7.33 0.76 6.5–8.5 
Electrical conductivity (EC) 330.00 5,300.00 1,196.44 794.05 240.00 7,020.00 897.56 1,061.04 1,500 μS/cm 
Total dissolved solids (ppm) 211.20 3,392.00 765.67 508.17 153.60 4,492.80 574.44 679.07 500 mg/L 
Bicarbonate (ppm) 50.00 420.00 197.67 91.62 50.00 504.00 260.24 103.45 300 mg/L 
Chloride (ppm) 38.00 890.10 174.82 156.49 14.94 863.21 174.69 156.46 250 mg/L 
Fluoride (ppm) 0.04 200.00 34.26 51.94 0.12 919.93 45.75 143.40 1.5 mg/L 
Nitrate (ppm) 0.11 45.26 8.67 13.00 0.09 940.50 135.88 190.01 45 mg/L 
Sulphate(ppm) 0.33 215.00 59.66 59.87 1.95 292.56 82.14 59.60 200 mg/L 
Sodium (ppm) 23.10 621.40 111.37 101.63 14.01 585.68 71.62 86.86 200 mg/L 
10 Potassium (ppm) 0.26 104.40 14.72 20.33 0.85 53.98 7.49 10.72 12 mg/L 
11 Calcium (ppm) 8.00 144.00 48.15 29.40 1.46 31.67 13.81 8.18 75 mg/L 
12 Mg Magnesium (ppm) 19.40 102.10 47.22 24.12 0.27 84.69 29.50 17.01 48.15 

The pH values of the groundwater samples vary from 6.18 to 8.9 and 6.03 to 8.56 in PRMS and POMS, respectively. The pH found in the study area is from acidic to alkaline in nature. EC varies from 330 to 5,300 μS/cm in PRMS and 240 to 7,020 μS/cm in POMS. TDS concentration in the study area ranges from 211.20 to 3,392 mg/L and 153.60 to 4,492.80 mg/L during PRMS and POMS, respectively. High TDS values present in the samples along the coast may indicate seawater mixing. The sodium, potassium, and calcium parameters vary from 23.10 to 621.40, 0.26 to 104.40, and 8 to 144 mg/L during PRMS, 14.01 to 585.68, 0.85 to 53.98, and 1.46 to 31.68 mg/L during POMS, respectively. Bicarbonate, chloride, fluoride, nitrate, and sulphate vary from 50 to 420, 38 to 890, 0.04 to 200, and 0.11 to 45.26 during PRMS and 50 to 504, 14.94 to 863.21, 0.12 to 919.93 and 0.09 to 940.5 during POMS, respectively.

Seawater intrusion

The ratio of Na/Cl is calculated for the 41 samples and ranges from 0.207 to 1.833 during PRMS and 0.092 to 1.462 during POMS. The ratio of Na/Cl <0.86 is indicated as seawater intrusion. In the study area, 30 samples fell under seawater intrusion during PRMS and 38 samples during POMS.

The spatial distributions of the Na/Cl ratio during PRMS and POMS are shown in Figure 3. The Simpson ratio (Cl/(HCO3 + CO3) is calculated for all the samples and ranges between 0.316 and 2.119 during PRMS and 0.124 and 3.947 during POMS. Fourteen samples are of good quality, 22 are slightly contaminated, and five are moderately contaminated during PRMS. Twenty-two samples are of good quality, 11 are slightly contaminated, and eight are moderately contaminated during POMS. Spatial distributions of the Simpson ratio during PRMS and POMS are shown in Figure 4.
Figure 3

Spatial distribution of the Na/Cl ratio during PRMS and POMS.

Figure 3

Spatial distribution of the Na/Cl ratio during PRMS and POMS.

Close modal
Figure 4

Spatial distribution of the Simpson ratio during PRMS and POMS.

Figure 4

Spatial distribution of the Simpson ratio during PRMS and POMS.

Close modal

Groundwater quality for drinking purposes

The water quality index has been calculated, and the minimum index value is 42.47, with a maximum of 9,007.26, and an average of 958.53. As per the water quality index values, samples were categorised into five classes as shown in Table 2.

Table 2

Classification of water quality and suitability of drinking water

S.No.WQI valueWater quality classesPre-monsoon
Post-monsoon
Sample no.% of samplesSample no.% of samples
<50 Excellent 7, 8 4.88 4,8 4.88 
50–100 Good water 1,2,3,4,5,9,18,19,20, 27,32 26.83 2,13,21,22,23,24,25 17.08 
100–200 Poor water 6,10,11,12,13,14,15,16,17,21,22,23,29,33,34 36.58 1,3,5,6,7,9,10,12,15,17,18,20,27, 29,32,33,34 41.46 
200–300 Very poor water 24,25 4.88 11,14 4.88 
>300 Unsuitable for drinking 26,28,30,31,35,36,37,38,39,40,41 26.83 16,19,26,28,30,31,35,36,37,38,39,40,41 31.70 
S.No.WQI valueWater quality classesPre-monsoon
Post-monsoon
Sample no.% of samplesSample no.% of samples
<50 Excellent 7, 8 4.88 4,8 4.88 
50–100 Good water 1,2,3,4,5,9,18,19,20, 27,32 26.83 2,13,21,22,23,24,25 17.08 
100–200 Poor water 6,10,11,12,13,14,15,16,17,21,22,23,29,33,34 36.58 1,3,5,6,7,9,10,12,15,17,18,20,27, 29,32,33,34 41.46 
200–300 Very poor water 24,25 4.88 11,14 4.88 
>300 Unsuitable for drinking 26,28,30,31,35,36,37,38,39,40,41 26.83 16,19,26,28,30,31,35,36,37,38,39,40,41 31.70 

From the analysed values of the water quality index classification, 4.88% of the water samples fell under an excellent category in both seasons, 26.83% of the samples fell under a good water category, 36.58% under a poor water category, 4.88% under a very poor water category, and 26.83% are not suitable for drinking during PRMS; 17.08% of the samples fell under a good water category, 41.46% under a poor water category, 4.88% under a very poor water category, and 31.70% are not suitable for drinking during POMS. The IDW method in Arc GIS 10.3 was applied to create groundwater quality spatial maps for two seasons. The maps which are developed are shown in Figure 5 to help to understand the groundwater quality present in the study area.
Figure 5

Spatial distribution map of the Water Quality Index (WQI) during PRMS and POMS.

Figure 5

Spatial distribution map of the Water Quality Index (WQI) during PRMS and POMS.

Close modal

Chemical quality analysis of groundwater has been done in the Visakhapatnam coastal area, Andhra Pradesh. In total, 41 samples were collected during PRMS and POMS and analysed for chemical parameters such as pH, EC, TDS, major cations, and anions present in the groundwater. pH values of the groundwater samples vary from 6.18 to 8.9 and 6.03 to 8.56 in PRMS and POMS, respectively. The pH found in the study area is from acidic to alkaline in nature. TDS concentration in the study area ranges from 211.20 to 3,392 and 153.60 to 4,492.80 mg/L during PRMS and POMS, respectively. High TDS values present in the samples along the coast may indicate seawater mixing. The ratio of Na/Cl is calculated in the study area, and 30 samples fell under seawater intrusion during PRMS and 38 samples during POMS. The Simpson ratio (Cl/(HCO3 + CO3) is calculated for all the samples and ranges between 0.316 and 2.119 during PRMS and 0.124 and 3.947 during POMS. Fourteen samples are of good quality, 22 are slightly contaminated, and five are moderately contaminated during PRMS. Twenty-two samples are of good quality, 11 are slightly contaminated, and eight are moderately contaminated during POMS.

The Simpson ratio results also show that seawater intrusion is reducing during the POMS due to increasing groundwater levels caused by rains. Water quality index classification shows that 4.88% of the water samples fell under an excellent category in both seasons; 26.83 and 31.70% were not suitable for drinking during PRMS and POMS. Chukkavanipalem, Nagarampalem, Marikavalasa, Rushikonda, Yendada, Appugar, MVP, Sivajipalem, Pandurangapuram, and Arilova are the areas where water is not suitable to drink during both seasons. From this study, due to the increase in population, overexploitation of groundwater could lead to declining groundwater quality in the study area. However, groundwater monitoring over time is necessary to sustain groundwater quality in the study area.

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

The authors declare there is no conflict.

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