Abstract

This study is a real-time hydrogeological investigation to appraise the groundwater scenario and spatial variations of its major physicochemical parameters at the southernmost apical fringe of the Indian Sundarban Biosphere Reserve area in mesoscale during the recent post-monsoon season (PoM). The study was based on the acquisition and analysis of primary field data collected from the southernmost apex of the river Ganga-Brahmaputra-Meghna delta and restricted to the Namkhana Development Block of South 24 Parganas district, West Bengal, India. Twenty-two groundwater samples were collected from bore wells post-monsoon (October 2022). Measurements of major physical parameters were done in situ. Geospatial contour maps representing variations of influencing parameters were prepared. The drinking and irrigation suitability of the water was validated by existing standard equations and plots. Chemical analyses were done to evaluate its hydrochemistry and suitability for drinking and agriculture. Obtained results primarily revealed that TDS and pH are at marginal ranges with significantly alarming concentrations for some major contributing ions, chiefly bicarbonates, and sodium. The overall suitability of groundwater for agriculture, drinking, and domestic purposes differs from acceptable limits. Indiscriminate groundwater exploitation from deeper aquifers for agriculture seemed to be the prime factor responsible for this situation.

1 Introduction

Across the globe, the utilization of groundwater is surpassing its natural replenishment rate, with an estimated annual extraction of approximately 1500 km³ (Döll et al. 2012). The Ganges-Brahmaputra-Meghna River delta is known for its high population density and significant groundwater extraction from the aquifer. Researchers have extensively studied this region (Worland et al. 2015; Wada et al. 2010). The decline in groundwater level (GWL) can result in contamination from natural or human-caused sources (Mukherjee et al. 2007; Mukherjee and Fryar 2008; Michael et al. 2013; MacDonald et al. 2016). A significant majority of the Indian population relies on groundwater as their primary source of drinking water. However, this valuable resource is depleting due to the increasing population density. The decrease in GWL significantly affects the inland and coastal aquifers in the tropical ocean (Fendorf et al. 2010; MacDonald et al. 2016). The groundwater of coastal aquifers significantly impacts salinization and poses a potential threat to the surrounding community (Jones et al. 1999).

Since the last few decades, some specific locations in India and the state of West Bengal have faced a daunting freshwater crisis, specifically with its degraded quality in terms of its suitability for drinking, irrigation, and domestic use. The inadequacy of safe, fresh water gradually impedes socio-economic and environmental sustainability development. The massive need for irrigated farming and drinking water supply, coupled with the threat of prolific population growth and industrial development, imposed immense stress on the quality and quantity of freshwater resources. The situation will be more critically alarming for the groundwater scenario in coastal aquifers, which reside in a delicate balance with seawater, where a small imbalance can lead to a drastic degradation of the groundwater quality by seawater ingress (Jones et al. 1999). The tidal rivers of the Sundarbans are saline, and the groundwater from shallow aquifers is unsuitable for drinking and agriculture. Changing global weather patterns and the gradual rise in sea water temperature caused cyclonic surge storms to happen more often than usual at this point where the Indian subcontinent and the Bay of Bengal meet. These storms had big effects on the quality of the surface water and the way groundwater recharged.

The sharp rise in human encroachment on the islands of SBR posed a serious threat to shallow and deeper aquifers below the surface, which greatly reduced the quality of these water sources. Almost five million people in Sundarban depend only on deep groundwater to meet their potable water demand. According to the last report by the World Bank, almost two-thirds of the total population of SBR will eventually have limited and seasonal access to adequate and safe drinking water. Recurring devastative cyclonic events lead to the admixing of saline water with groundwater. The inadequacy of fresh surface water and saltwater intrusion because of the overexploitation of shallower aquifers has become a common phenomenon worldwide (Singh et al. 2009). The crux of the issue of saline water ingress can be governed by various factors like coastal hydraulics, groundwater scenarios, indiscriminate and overexploitation of groundwater, cyclonic events, sea level rise, tidal influence, and adverse effects on water resources in different coastal parts of India. (Kim et al. 2009; Umrikar and Devi 2011; Sahu et al. 2011).

The present investigation was conducted to delineate the groundwater appraisal to evaluate the spatial variations of its physicochemical parameters at the southernmost apical fringe of SBR in mesoscale during the post-monsoon season. The study was based on real-time primary field data collected within the Namkhana Development Block of South 24 Parganas District, West Bengal, India. Twenty-two groundwater samples from bore wells were collected during the post-monsoon season (October 2022). Measurements of major hydrogeological parameters, i.e., water table head, pH, TDS, and EC, were done in situ during (PoM) fieldwork. Geospatial contour maps representing concentration variations of chief influencing ions and hydrogeological parameters were prepared. The drinking and irrigation suitability of the groundwater were estimated following existing standard equations and relevant plots. Chemical analyses were done to evaluate hydrochemistry and its suitability for drinking and agriculture. 

The results mostly showed that TDS and pH are on the low side, with very high levels of some important contributing ions (mostly bicarbonates and sodium) in most of the places that were studied. The overall suitability of groundwater for agriculture, drinking, and domestic purposes is also considerably different from usual, acceptable limits. Excessive exploitation of deeper aquifers by submersible and hand pumps for domestic and agricultural purposes seemed to be the prime factor in this situation. Since the study area is meteorologically vulnerable with fragile riverine systems and dynamic geohydrology, an active equilibrium exists in between saline water and fresh water. The aquifers in this coastal region are more prone to contamination through various channels; climatically turbulent, erratic rainfall, and a decline in freshwater availability are all plaguing the Sundarbans region, impacting fishing and agricultural practices. This is the adversely affected area that endorsed saline water intrusion at the southern part, which is in contact with Bay of Bengal (Ghosh et al. 2021). At the same time, immense population growth has been encountered in the past few decades; so, for the sake of sustainable development of livelihood, a vivid hydrogeological assessment was required. There have not yet been any reports of a thorough geohydrological study focused only on the sole Namkhana block of the south 24 Parganas District. It is anticipated that the results may have positive effects on farmers, irrigation planners, small-scale industrialists and the general health of the people living in those blocks with proper implementation of mitigation policies for better and sustainable groundwater governance.

2 Study area

The Namkhana block in the Sundarbans has a difficult groundwater situation because of several issues. The region is very vulnerable to the effects of climate change and related calamities, such as how salinization affects the quality of groundwater. Furthermore, irregular monsoon rains, saline water intrusion, and a decline in freshwater availability due to a radical rise to meet agricultural needs are all plaguing the Sundarbans region and are having a negative impact. This region has been adversely affected, primarily due to saline water intrusion in the southern part, which is in contact with the Bay of Bengal (Ghosh et al. 2021). Since the Bengal basin tilts eastwards, this accelerated global sea level rise shows further acceleration in the Sundarban estuary; for example, in the Indian portion, it is 3.14 mm per year against the global average of 2 mm per year. Consequently, this phenomenon endorsed a rising trend of salinity in both the surface and groundwater over the years (Hazra et al. 2002; Park et al. 2005; Costall et al. 2020; Das et al. 2021).

The Namkhana block lies between the latitude of 21º04ʹ50ʹʹ to 21º40ʹ10 ̎ N, and longitude from 88˚13̕ 50 ̎ to 85˚16̕ 15 ̎ E, and is a part of West Bengal, under the Kakdwip sub-division of South 24 Parganas. It is in the Sundarban deltaic region, which points to the southern apical fringe of Ganga-Brahmaputra-Meghna deltaic plain of the Holocene period. It covers a 524 km² geographical area, surrounded by the Muriganga and Saptamukhi rivers. It consists of 7 Gram Panchayats and 32 villages, with a total population of 2.13 lakh (Ministry of Jal Shakti 2023) and a delicately acute cyclone-prone area facing BOB. Figure 1 represents the geospatial location of the block within the Indian subcontinent.

Figure 1 Geospatial location of the study area within the Indian subcontinent.

Existing reports (CGWB 2021) reveal that the subsurface hydrogeology of the area is primarily composed of three types of aquifer systems. The depth range of these aquifer zones is 12.2–30 mbgl (meters below ground level), 66–100 mbgl, and 219–374.9 mbgl, respectively. Aquifer I and Aquifer II are saline, whereas Aquifer III bears fresh groundwater (CGWB 2021). The CGWB has identified two granular sand zones in the Aquifer III system. The thickness of the first and second granular zones is 17.8 m and 34 m, respectively. All freshwater-bearing aquifers are confined between the clay layers. There are several creeks and rivulets that traverse the entire block.  

The present hydrogeological survey was carried out throughout the block during the post-monsoon (PoM) period. Twenty-two (22) water samples were collected from nearly equidistant deep tube wells (Mark II and hand pumps with cylinders). These samples were taken from aquifers located at a depth greater than 800 feet, namely in the Aquifer III zone, according to CGWB. Table 1 displays the geospatial coordinates of the sampling locations.

Figure 2 shows the positions of the sampling wells in the block.

Table 1 Sampling locations of the study area.

Location No.	Location Name	Latitude (N)	Longitude (E)	Altitude above MSL (m)	Water Table Depth (m)
L1	Fresarganj	21°33’36.36”	88°14’57.80”	5	10.25
L2	Laxmipur	21°33’44.36”	88°15’20.54”	4	WNO
L3	Purba Amravati	21°33’58.19”	88°16’15.05”	4	10.50
L4	Bijoybati	21°34’42.40”	88°16’24.63”	3	10.35
L5	Narayanitala	21°35’40.64”	88°15’46.54”	5	10.70
L6	Purba Bijoybati	21°35’26.91”	88°16’26.09”	5	WNO
L7	10-mile bus stand	21°37’40.00”	88°15’31.24”	5	WNO
L8	Haripur Bishalaxmi Temple	21°38’30.00”	88°17’12.12”	4	WNO
L9	Kalimata Temple	21°38’05.19”	88°15’21.04”	3	WNO
L10	Shibrampur	21°39’01.73”	88°15’26.62”	5	WNO
L11	Dakshin Chandanpidi	21°39’58.00”	88°17’58.06”	4	WNO
L12	Rajnagar	21°40’09.16”	88°15’02.34”	3	WNO
L13	Moynapada, Radhanagar	21°41’31.25”	88°14’04.36”	6	10.77
L14	South Durgapur Mosque	21°41’15.85”	88°12’43.46”	3	11.60
L15	Devnagar	21°43’13.00”	88°12’54.08”	5	11.15
L16	Namkhana Girls School	21°43’59.02”	88°14’35.11”	4.5	WNO
L17	Dwarikanagar	21°43’03.24”	88°15’54.65”	4	WNO
L18	Madanganj	21°44’29.76”	88°14’56.95”	5	WNO
L19	Shibani Mandal College	21°44’36.98”	88°14’22.74”	4	WNO
L20	Namkhana Bazar Area	21°45’30.91”	88°14’02.30”	3.5	10.90
L21	Patigunia Ferry Ghat	21°37’18.03”	88°13’24.21”	2	10.20
L22	Baghdanga Kusumtala	21°39’57.10”	88°11’30.34”	4	10.80

N.B: *WNO = Well cannot be opened

Figure 2 Sampling locations within the study area (Namkhana block).

3 Materials and methods

The methodology of the present study involved three main steps. First, we selected specific locations and determined their geospatial coordinates. Then, we conducted on-site in situ measurements of key physicochemical parameters. Finally, all the collected samples were analyzed in the laboratory to determine the concentrations of ions that have a significant impact. In the present survey, real-time hydrogeological data acquisition involves the collection of groundwater samples from 22 distinct locations which were euqi-spatially placed, and the upper portion of the tube wells (mark II) were partially dismantled from its main body to measure the depth of the groundwater by inserting a model acoustic water level indicator (model – Solinst 100m–101B). This provided the elevation head above the Mean Sea Level (MSL) of the groundwater table for each location. The geospatial coordinates of the sampling well were accurately taken by a standard GPS (model – Garmin eTrex-20x). Subsequently, groundwater samples were taken from each location after purging to avoid the contamination of stagnant water stored in the well casing, near the screen, and the freshwater samples were kept in HDPE double capped 500 ml bottles. Regarding the in-situ measurement of the physical parameters, the measurements were done using a portable multi-parameter water testing instrument (model – Hanna HI-98194). Sensors are automatically recognized by the probe and meter when connected. Figure 3 reveals the steps followed to acquire primary real time geohydrological data (PoM) from the sampling location (L10).

Figure 3 Collection of water samples and acquisition of the field data: (a) recording geospatial ordinates of the well; (b) unscrewing the well top; (c) measuring water depth by inserting acoustic tape; (c) collection of water samples, and acquisition of in-situ physicochemical data by testing probe.

The measurement of physical parameters was followed by laboratory chemical analysis of the groundwater samples (within 72 hours from collection) to obtain the concentration of major ions, following the standard laboratory procedure (APHA 1995). The methods recommended by APHA for the determination the concentrations of major ions in groundwater typically involve instrumental analysis techniques such as atomic absorption spectrophotometry (AAS) or inductively coupled plasma-optical emission spectrometry (ICP-OES). Recommended methods for the determination of sulfate and nitrate in groundwater typically involve colorimetric techniques or ion chromatography. Major ions concentration contour diagrams were developed using ARC GIS 10.5 software, using the spatial analysis module of Arc GIS 10.3.1. Major figures were developed by the software Grapher 21.

Following standard procedure, data obtained from the chemical analysis were used to assess the variation in concentration of major ions. This evaluation aimed to determine the overall suitability of groundwater for health, domestic, and irrigation purposes. Parameters such as Sodium Adsorption Ratio (SAR), Soluble Sodium Percentage (SSP), and Kelly's Ratio (KR), were used to assess the suitability of water for agricultural and drinking purposes. These values were plotted on standard reference diagrams like Wilcox, U.S. Salinity (US Salinity Lab 1954), Water Quality Index (WQI), and Piper diagrams (Piper 1944). Statistical connections were found between the controlling variables in Pearson's correlation matrix of affecting ions. The correlation matrix was evaluated in R Software (Version 4.3.2), using the “sjPlot” library. Maps showing the variation in key parameters were created by extracting the relevant area from TNT MIPS 2017, a software that uses GIS technology. These maps were then geo-referenced for accuracy.

4 Results and discussion

The ranges of results obtained from in-situ field tests, chemical analysis, and other estimated physicochemical parameters of all the collected PoM water samples in the studied area are summarized in Table 2, comparing the proposed standards prescribed by WHO (2017) and Indian standards (ISI 2012).

Table 2 Limiting ranges of physicochemical parameters of studied groundwater – PoM.

Sr. no	Parameter	Limiting Values	Mean	Median	Standard Deviation	WHO Standards (WHO 2017)	Indian Standards (ISI 2012)	US EPA Drinking water standards
1	pH	6.79 - 7.12	6.95	6.96	0.07	6.5-8.5	6.5-8.5	6.5-8.5
2	EC (µs/cm)	869 - 1233	992.65	972.58	87.83	-	-	-
3	TDS (mg/L)	435 – 844.5	516.56	501.83	87.24	500	500	500
4	TH (mg/L)	44.08-84.15	64.75	66.022	10.79	-	-	-
5	Na+ (mg/L)	170.60 -211.98	193.99	193.59	11.78	200	-	-
6	K+ (mg/L)	3.07 - 4.33	3.78	3.73	0.38	12	-	-
7	Ca+2 (mg/L)	8.40 – 21.00	16.37	16.80	3.17	75	75	-
8	Mg+2 (mg/L)	0.85 - 10.25	5.80	6.07	2.09	< 30	30	-
9	HCO3- (mg/L)	269.33 - 436	375.28	382.00	39.63	30-350	-	30-350
10	Cl- (mg/L)	64.97 - 34.95	96.75	95.80	18.32	200	250	250
11	SO4-2 (mg/L)	3.42 - 7.12	4.58	4.44	0.92	200	200	250
12	NO3- (mg/L)	1.50 - 4.00	2.74	2.82	0.64	< 0.1	-	1

4.1 Cation chemistry

Obtained results, as presented in Table 2, revealed that sodium (Na⁺) is the dominant cation in the study area, ranging from 170.60–211.98, with a mean value of 193.99. Following that, concentrations of the remaining cations (Na⁺>Ca⁺²>Mg⁺²>K⁺) had a contribution of 88%, 7%, 5%, respectively (Table 3). With the replacement of Ca⁺² and Mg⁺² ions by Na⁺ due to reverse cation exchange and dissolution of soil salts in groundwater, silicate weathering may be the possible reason for elevated Na⁺ concentration (Krishna Kumar et al. 2012, Krishna Kumar et al. 2014). During the PoM, as the level of groundwater rises, the sea water retreats and dissolved salts like Na⁺ become more concentrated in the remaining groundwater, which leads to a higher sodium content. Increased recharge during this period (PoM) seemed to be another key factor for enhanced admixing with the saline-infested aquifer. These mechanisms of interaction ultimately lead to the higher concentration of sodium (Na⁺), subsequently, the mixing or flushing phenomenon leads to the saltwater intrusion farther inland, and contribution of elevated sodium encounters. The potassium (K⁺) concentration was the lowest in the study area. The result depicts that spatially with sodium, concentrations of other major cations gradually decrease from the coastal areas, i.e., the southernmost zone, towards the northern zone or interior of the block. The possibility of a hydraulic connection between seawater and groundwater aggravates the solute exchange process in this deltaic complex. The seawater is involved in the solute exchange process locally with the shallow aquifer, while regionally with the deep groundwater, increasing groundwater salinity.

Table 3 Pearson correlation matrix with corresponding ‘p’ values for all 12 physicochemical variables of studied groundwater.

	pH	EC	TDS	TH	(Na+)	(K+)	(Ca+2)	(Mg+2)	(HCO3-)	(Cl-)	(SO4-2)	(NO3-)
pH		0.305 (.168)	0.584 (.004)	-0.394 (.069)	0.364 (.096)	-0.632 (.002)	-0.462 (.030)	-0.070 (.757)	0.229 (.306)	-0.025 (.912)	-0.044 (.846)	0.545 (.009)
EC	0.305 (.168)		0.639 (.001)	-0.633 (.002)	0.861 (<.001)	-0.731 (<.001)	-0.110 (.627)	-0.692 (<.001)	0.353 (.107)	0.590 (.004)	-0.584 (.004)	0.436 (.042)
TDS	0.584 (.004)	0.639 (.001)		-0.579 (.005)	0.642 (.001)	-0.675 (.001)	-0.174 (.440)	-0.566 (.006)	0.355 (.105)	0.249 (.264)	-0.496 (.019)	0.512 (.015)
TH	-0.394 (.069)	-0.633 (.002)	-0.579 (.005)		-0.804 (<.001)	0.853 (<.001)	0.615 (.002)	0.689 (<.001)	-0.690 (<.001)	0.023 (.918)	0.480 (.024)	-0.364 (.096)
(Na+)	0.364 (.096)	0.861 (<.001)	0.642 (.001)	-0.804 (<.001)		-0.853 (<.001)	-0.336 (.126)	-0.700 (<.001)	0.470 (.027)	0.466 (.029)	-0.740 (<.001)	0.574 (.005)
(K+)	-0.632 (.002)	-0.731 (<.001)	-0.675 (.001)	0.853 (<.001)	-0.853 (<.001)		0.524 (.012)	0.588 (.004)	-0.590 (.004)	-0.065 (.774)	0.536 (.010)	-0.645 (.001)
(Ca+2)	-0.462 (.030)	-0.110 (.627)	-0.174 (.440)	0.615 (.002)	-0.336 (.126)	0.524 (.012)		-0.148 (.511)	-0.414 (.055)	0.357 (.103)	-0.159 (.480)	-0.408 (.060)
(Mg+2)	-0.070 (.757)	-0.692 (<.001)	-0.566 (.006)	0.689 (<.001)	-0.700 (<.001)	0.588 (.004)	-0.148 (.511)		-0.485 (.022)	-0.299 (.177)	0.748 (<.001)	-0.081 (.719)
(HCO3-)	0.229 (.306)	0.353 (.107)	0.355 (.105)	-0.690 (<.001)	0.470 (.027)	-0.590 (.004)	-0.414 (.055)	-0.485 (.022)		-0.328 (.136)	-0.198 (.377)	0.088 (.697)
(Cl-)	-0.025 (.912)	0.590 (.004)	0.249 (.264)	0.023 (.918)	0.466 (.029)	-0.065 (.774)	0.357 (.103)	-0.299 (.177)	-0.328 (.136)		-0.493 (.020)	0.237 (.288)
(SO4-2)	-0.044 (.846)	-0.584 (.004)	-0.496 (.019)	0.480 (.024)	-0.740 (<.001)	0.536 (.010)	-0.159 (.480)	0.748 (<.001)	-0.198 (.377)	-0.493 (.020)		-0.424 (.049)
(NO3-)	0.545 (.009)	0.436 (.042)	0.512 (.015)	-0.364 (.096)	0.574 (.005)	-0.645 (.001)	-0.408 (.060)	-0.081 (.719)	0.088 (.697)	0.237 (.288)	-0.424 (.049)

4.2 Anion chemistry

The estimated concentration of anions and their correlation with other major variables (Table 2 and Table 3) shows that the order of concentration of anions HCO₃-> Cl^-> SO₄^-2>NO₃^- has a contribution of 78%, 20%, and 1%< for SO₄^-2 and NO₃^-. The preponderance of HCO₃^- seems to be a result of carbonate mineral breakdown by weathering of calcite, dolomite, and silicate minerals. The infusion of saline water, dissolution of salt deposits, and its possible cause could be attributed to the Cl^- concentration in groundwater (Jeong 2001; Jeevanandam et al. 2012; Krishna Kumar et al. 2014).

Isolines, i.e., contour plots for spatial concentration fluctuations of HCO₃^- and Na⁺ (Figures 4 a and b), ascertain that the concentration gradually declines from the southernmost coastal fringe northwards.

Figure 4 Fluctuation of spatial concentrations of (a) HCO₃^-, and (b) Na⁺ during PoM.

To establish a relationship between the physicochemical characteristics of water samples, which can reveal the origin of solutes, and the process that generated the observed chemical status of the PoM groundwater, Table 3 represents Pearson’s correlation matrix of the major controlling physicochemical parameters as estimated during the PoM season of the studied block. The sole purpose for the determination of Pearson’s correlation coefficient is to ascertain whether there is a significant relation or correlation between the two variables. The Pearson’s correlation coefficient is also termed as Pearson’s ‘r ’. In the context of groundwater studies, Pearson’s correlation can be employed to explore relationships between various groundwater parameters or between groundwater parameters and other environmental factors. The correlations between various water quality measures in groundwater, such as pH, dissolved oxygen, electrical conductivity, and concentrations of different ions (e.g., sodium (Na⁺), chloride (Cl^-), nitrate (NO₃^-), can be investigated using Pearson’s correlation analysis. The correlation coefficient between two continuous variables helps to decipher sources of contamination, the underlying process of mechanism that governs groundwater quality. If a correlation coefficient is 0 or zero, it infers there is no relationship. Pearson’s ‘r’ will always be in between +1 to -1. A correlation coefficient of +1 means there is perfect positive correlation between two variables, and if one variable increases, the second one also increases in the same magnitude or proportion. When Pearson's correlation was employed, the initial correlation coefficient was determined between all pairs of variables of the dataset. Pearson's correlation coefficient between two variables can be determined using the following formula (Obilor and Amadi 2018).

(1)

Where:

r	=	Pearson’s correlation coefficient;
N	=	Number of pairs of values;
Σxy	=	Sum of the products of x and y;
	=	Mean of x values;
	=	Mean of y values;
	=	Product of mean values of x and y;
Σx²	=	Sum of square of x values; and
Σy²	=	Sum of the square of y values.

With the above equation, a computational equation can be written as:

(2)

Where:

N	=	Number of pairs of values;
Σxy	=	Sum of the products of x and y;
Σx	=	Sum of the x values;
Σy	=	Sum of the y values;
Σx²	=	Sum of square of x values;
Σy²	=	Sum of square of y values;
(Σx)²	=	Square of sum of x values; and
(Σy)²	=	Square of sum of y values.

After getting the value of Pearson’s r, the next step would be determining the P value to ascertain whether the correlation is statistically significant. The level of significance between two variables can be expressed by levels of p. It can be noted that the larger the correlation value r the stronger the relationship, whereas a smaller p level indicates a more significant relationship. For the test of statistical significance of the correlation coefficient, t distribution may be employed by obtaining t value or t ratio. The t distribution formula for computing appropriate t value can be expressed by the following formula:

(3)

Where:

t	=	t value required for the test of significance of the correlation coefficient r;
N	=	sample size or no. of observations;
r	=	the computed correlation coefficient being tested for significance; and
N-2	=	the degree of freedom. After getting the computed t value, critical value table of t at a specified degree of freedom (two-tailed test) was consulted. If the computed value of t becomes higher than the critical t value of the table, then the null hypothesis that there is no significant relationship between two specified variables can be rejected.

In other words, a significant relationship may exist. To get the p value, a “TDIST” function can be used in Microsoft Excel. ”TDIST” (x, degrees freedom, tails) is the syntax, where x, the observed t value. To create the correlation matrix, here R software 4.3.2 was used, and to determine the correlation matrix along with p values, the “sjPlot” library function was used for the visually appealing matrix. The sjPlot package's ‘tab_corr () function’ creates correlation matrices with two-tailed tests and a default significance level of 0.05. The correlation matrix indicates the degree of linear relationship between independent and dependent variables (Nair et al. 2006). The estimated matrix showed that the study area's hard groundwater or Total Hardness (TH) with Ca⁺² and Mg⁺², shows a positive correlation of 0.615 and 0.689, respectively, which is mostly caused by the dissolution of Ca and Mg bearing minerals salts like MgCO₃ and CaCO₃, that may be carried by the dense river network of the area and deposited continuously with time in this apical zone of active deltaic plane. Dissolution of gypsum, anhydrite, and Ca-Mg bearing silicates within the aquifer may also be responsible for the contribution of Ca and Mg, which again may contribute to the total hardness of groundwater.

There is a strong link between electrical conductivity (EC) and Na⁺, and a moderate link between EC and HCO₃^-, Cl^-, and NO₃^-. This suggests that conductivity rises with the concentration of these ions. From the Pearson correlation matrix, as presented in Table 3, the upper row values for each physicochemical parameter represent the Pearson correlation coefficient, and the corresponding lower row values represent p values. Now, considering the two valid parameters Na⁺ and Ca₂⁺, the value of the coefficient is (-0.336), which denotes a negative correlation, i.e., the theory or hypothesis of freshening by ion exchange of similar types may be established, where calcium is taken up by releasing sodium ions. Therefore, the concentration of sodium increases with the depletion of calcium ions. The comparatively higher positive correlation between sodium (Na⁺) and bicarbonate (HCO₃^-) ions (0.470) and between sodium and chloride (0.465) imparts a clear impression of freshening activity. It establishes the Na-HCO₃ type facies. The spatial fluctuation trend of TDS, SSP, SAR, KR, and EC of the studied block (during PoM), as revealed by contour plots, gradually decreases towards the central locations of the block. Figure 5 (a–b) presents the spatial variations plots of EC and TDS, showing a similar trend of its radical declinations northward. This implies the connectivity of saline water-influenced local shallower aquifers with these deeper aquifers.

Figure 5 Fluctuation of spatial concentrations of (a) EC, and (b) TDS during PoM.

4.3 Appraisal of water quality for drinking, domestic, and irrigation

The quality of the water for drinking, domestic use, and irrigation depends on the minerals it contains. It is worth noting that salts can have a significant impact on plant growth. They can physically hinder the intake of water by altering osmotic processes, which can be detrimental (Todd 2004; Tiwari et al. 2016). The hydrogeochemical facies were determined using the Piper trilinear diagram (Piper 1944), and the water quality index (based on Ramakrishnaiah et al. 2009) was calculated for all the locations in the block. Various parameters were computed to assess the suitability of water for irrigation purposes. These parameters include the Sodium Absorption Ratio (SAR), Magnesium Absorption Ratio (MAR), Soluble Sodium Percentage (SSP), Permeability Index (PI), Residual Sodium Carbonate (RSC), and Kelly's Ratio (KI).

Hydro-geochemical facies

Determination of the hydro-geochemical facies and the evaluation of the PoM water of the area for drinking purposes was introspected through the Piper trilinear diagram (Piper 1944) by plotting the major cations and anions. This diagram divulges similarities and differences among water samples because those with similar qualities will tend to project together as groups (Todd 2004). The Piper trilinear diagram (Piper 1944) is useful to bring out chemical relationships among water in more definite terms (Apambire et al. 1997). It specifically defines chemical relationships among water in more definite terms. Major ions are plotted as cations and anions in percentages of milli-equivalents in two base triangles. Figure 6 shows the Piper diagram of the water during the PoM season.

Figure 6 Plots in Piper's trilinear diagram to assess the hydro-geochemical facies of the study area.

From the plot, it is revealed that the PoM water of the block is acutely constricted in the lowermost block of the diamond that represents the Na-HCO₃ type. The key reason is that Na and Cl are dominant ions near seawater, and calcium and bicarbonate are the two dominant ions of freshwater. Thus, as per the facies type, the significantly highest dominance of sodium ions may indicate the process of freshening, or when freshwater is flushed in with the saline water aquifer (Appelo and Postma 2005; Jiao and Post 2019). During the saltwater intrusion process, an ion exchange process takes place, and as a consequence, sodium ions are taken up by the sediment, and calcium ions are released. Consequently, water type changes from Na-Cl type to Ca-Cl², opposite to this incident, when freshwater flushes a saline water aquifer or during the freshening process, the reverse case happens, and calcium ions get taken up. In contrast, sodium ions get released, resulting in Na-HCO₃. Therefore, water composition or facies defines the incident freshening or flushing of saline water or solute exchange from shallow depth to deeper water (Taylor et al. 2013; Das and Mukherjee 2019).

Water quality index

The water quality index (WQI) is a reliable indicator for assessing water quality and its impact on public health. It is a valuable tool for concerned citizens and policymakers alike, providing insights into the state of water quality (Chatterjee and Raziuddin 2002; Ramakrishnaiah et al. 2009; Alobaidy et al. 2010; Lumb et al. 2011). The WQI is a method commonly employed to assess the overall water quality by considering various parameters. These parameters are combined to produce a single number, typically dimensionless, in a straightforward and replicable manner (Abbasi and Abbasi 2012). This study determined that WQI values per the weighted arithmetic water quality indexing method (after Ramakrishnaiah et al. 2009) for all 22 locations. The estimated ranges of reference values of PoM water quality (Table 4; Table 5) seem to be ‘Very Poor’ concerning public health. Figure 7 shows the presentation of the WQI of the block during PoM. 

Table 4 Water quality as per Weight Arithmetic Indexing Method (Chatterjee and Raziuddin 2002).

WQI Value	Rating of Water Quality	Grading
0-25	Excellent	A
26-50	Good	B
51-75	Poor	C
76-100	Very Poor	D
>100	Unsuitable for drinking	E

Table 5 Location-wise WQI values of study area.

Location	1	2	3	4	5	6	7	8	9	10	11
WQI Value	78.33	79.89	77.11	75.90	76.81	77.07	78.20	78.85	80.73	77.83	78.40
Location	12	13	14	15	16	17	18	19	20	21	22
WQI Value	76.33	77.76	78.26	77.44	76.69	75.04	78.08	78.11	79.62	78.64	78.07

Figure 7 Categorization of PoM groundwater according to WQI.

Suitability towards irrigation

Water quality degradation may have an adverse effect on the irrigation sector. Frequent salinization imposes a negative outcome on crop production. Since the entire block depends on the groundwater of comparatively deeper aquifers, as the shallower aquifers are intensely saline-infested, the collected water samples were assessed to estimate their irrigation suitability. This physicochemical appraisal was done by computing secondary water quality parameters and comparing those with standard hydro-chemical plots (Todd 2004; Ayers and Westcot 1985; Westcot and Ayers 1985; Doneen 1964; Kelly 1963). The parameters include the Sodium Adsorption Ratio (SAR), Soluble Sodium Percentage (SSP), Magnesium Adsorption Ratio (MAR), Permeability Index (PI), and Kelly’s Ratio (KI). Table 6 represents the location-wise values of estimated parameters (PoM) relevant to irrigation suitability. All these parameters are crucial in evaluating the appropriateness of water for irrigation applications. Increased levels of bicarbonate can exacerbate irrigation conditions by elevating the soluble sodium percentage (SSP) and sodium adsorption ratio (SAR) of the water, particularly in areas with sodic soils. Plant growth may be impeded, soil permeability may be reduced, and soil alkalinity may occur. Kelly's Ratio is crucial for evaluating the appropriateness of irrigation water, especially in areas where Na-HCO₃ type water is common. It aids in assessing the sodium threat, forecasting its influence on soil structure and crop growth, and directing efficient irrigation management techniques to maintain agricultural productivity in soils affected by sodium.

Table 6 Location-wise physicochemical parameters of groundwater on irrigation suitability.

Location	SAR	SSP	MAR	KR	PI
L1	13.54	91.14	52.41	10.20	163.52
L2	12.88	90.18	26.61	9.11	156.31
L3	12.33	89.27	6.28	8.25	149.42
L4	12.36	89.64	19.32	8.57	159.43
L5	12.44	89.61	25.81	8.54	157.12
L6	11.75	88.45	30.12	7.58	156.48
L7	11.01	87.43	42.68	6.88	149.71
L8	10.63	86.81	42.38	6.51	130.76
L9	10.32	86.35	53.81	6.26	142.63
L10	9.94	85.56	41.80	5.85	142.85
L11	9.51	84.84	39.80	5.53	142.46
L12	9.58	84.77	31.04	5.49	143.06
L13	8.93	83.68	32.81	5.06	142.14
L14	8.30	82.48	34.50	4.64	141.13
L15	9.63	85.12	34.95	5.66	149.51
L16	9.45	85.13	35.10	5.65	147.55
L17	11.66	89.11	39.56	8.09	159.06
L18	10.56	87.35	43.25	6.82	156.38
L19	9.65	85.55	46.09	5.85	153.65
L20	8.18	81.90	50.14	4.46	148.08
L21	11.16	88.11	36.74	7.33	154.05
L22	10.34	86.62	35.75	6.40	151.78

The Permeability Index is crucial because it is directly linked to the deterioration of soil structure and the ability of water to infiltrate and drain. Due to the predominance of Na-HCO₃ type water in the area, the use of this water for irrigation can result in the displacement of calcium and magnesium cations in the soil by sodium ions, causing soil sodicity. Sodic soils are susceptible to structural deterioration, such as soil crusting, compaction, and decreased water infiltration rates. The Permeability Index is a numerical metric that evaluates the likelihood of soil dispersion caused by water and helps determine the danger of soil structure degradation resulting from the sodium concentration in irrigation water. The Permeability Index measures the capacity of water to penetrate soil profiles. In regions where groundwater contains Na-HCO₃, elevated sodium concentrations can cause soil degradation, resulting in decreased water permeability and heightened surface runoff. This can worsen soil erosion and nutrient leaching, which has a detrimental influence on agricultural output. Through the assessment of the Permeability Index, farmers and land managers can determine the likelihood of waterlogging and drainage issues that may arise from the use of irrigation water with high sodium content. The Magnesium Adsorption Ratio (MAR) evaluates the abundance of magnesium compared to other positively charged ions in the soil, specifically calcium and sodium. Higher MAR values signify an increased presence of magnesium, which helps mitigate the adverse impacts of salt on soil composition. All these parameters are crucial in evaluating the appropriateness of water for irrigation applications. Increased levels of bicarbonate can exacerbate irrigation conditions by elevating the soluble sodium percentage (SSP) and sodium adsorption ratio (SAR) of the water, particularly in areas with sodic soils. Plant growth may be hindered, soil permeability may be reduced, and soil alkalinity may occur. Kelly's Ratio is crucial for evaluating the appropriateness of irrigation water, especially in areas where Na-HCO₃ type water is common. It aids in assessing the sodium threat, forecasting its influence on soil structure and crop growth, and directing efficient irrigation management techniques to maintain agricultural productivity in soils affected by sodium. The Permeability Index is crucial because it is directly linked to the deterioration of soil structure and the ability of water to infiltrate and drain. Due to the predominance of Na-HCO₃ type water in the area, the use of this water for irrigation can result in the displacement of calcium and magnesium cations in the soil by sodium ions, causing soil sodicity. Sodic soils are susceptible to structural deterioration, such as soil crusting, compaction, and decreased water infiltration rates. The Permeability Index is a numerical indicator that measures the likelihood of soil dispersion caused by water and helps evaluate the danger of soil structure deterioration caused by sodium in irrigation water. The Permeability Index measures the capacity of water to penetrate soil profiles. In regions where groundwater contains Na-HCO₃, elevated sodium levels can cause soil structure degradation, resulting in decreased rates of water penetration and heightened surface runoff. This can worsen soil erosion and nutrient leaching, which has a detrimental influence on agricultural output. Through the assessment of the Permeability Index, farmers and land managers can determine the likelihood of waterlogging and drainage issues that may arise from the use of irrigation water high in sodium content. The MAR evaluates the abundance of magnesium compared to other positively charged ions in the soil, specifically calcium and sodium. Higher MAR values suggest a larger quantity of magnesium, which helps mitigate the adverse impacts of salt on soil structure.

In conclusion, each of these variables offers vital information about the possible impacts of irrigation water on plant development and soil quality. Careful monitoring and management of these characteristics is necessary when working with Na-HCO₃ type water to minimize negative effects on crop productivity and soil structure.

Table 7 compares the prescribed standards of each parameter (WHO 2017) used for groundwater appraisal and the percentage contribution with respect to the total number of collected water samples from the studied block during PoM to infer a better conclusion.

Table 7 Classification of groundwater samples according to the standards of WHO (2017).

Parameter	Range	Class	No. of Samples	% of Samples
SAR	0-10	Excellent	9	41
	10-18	Good	13	59
	18-26	Permissible	0	0
	>26	Doubtful	0	0
SSP	<20	Excellent	0	0
	20-40	Good	0	0
	40-60	Permissible	0	0
	60-80	Doubtful	0	0
	>80	Unsuitable	22	100
MAR	<50	Suitable	20	90
	>50	Unsuitable	2	10
PI	<80	Good	0	0
	80-100	Moderate	0	0
	100-120	Poor	0	0
KR	≤ 1	Suitable	0	0
	>1	Unsuitable	22	100

Wilcox diagram and Doneen’s chart

Figure 8 (a-b) shows the plots of the Wilcox diagram and Doneen’s chart for the PI value of the analyzed water samples. In hydrogeology, a graphical tool called a Wilcox diagram is used to determine if groundwater is suitable for irrigation. It displays the sodium adsorption ratio (SAR) against the concentration of common ions present in groundwater. Water that fits into the "excellent" or "good" categories and has a low SAR, and low quantities of hazardous ions, such as salt and chloride, would be appropriate for irrigation. Water that falls into the "unsuitable" category and has a high SAR and large concentrations of hazardous ions, is not suitable for irrigation. Wilcox (1955) applied the sodium percentage against specific conductance to make a clear inference for the suitability of groundwater for irrigation purposes. It is pertinent to mention here that the soluble sodium percentage can be defined as the ratio of sodium to the total cations, viz. sodium, potassium, calcium, and magnesium. As per the diagram, it can be inferred that most of the groundwater samples in the study area fall under the “doubtful” to “unusable” categories (Figure 8a). If the SSP becomes higher, then it may have an adverse effect on the physical properties of soil; when sodium concentration becomes higher or becomes the most dominant cation, it tends to be absorbed by clay particles and replaces calcium and magnesium. Consequently, the soil reduces its permeability and develops a poor drainage quality.

Figure 8 Classification of PoM water by plots of (a) Wilcox diagram, and (b) Doneen’s chart.

The soil permeability can be governed by the sodium, calcium, and magnesium bi-carbonate content in the soil. The Doneen's chart classifies water quality into several classes based on the degrees of salinity and sodicity. As per Doneen (1964), Class I can be characterized by low salinity and low sodicity; this combination makes an ideal situation for irrigation without deteriorating the soil. It is usually recommended for direct irrigation without the need for extensive management practices. Class II is the combination of Medium Salinity (EC) or Medium Sodicity (SAR). Groundwater that falls in Class II may have elevated levels of SAR and EC, which infers a moderate risk of soil degradation. To lessen possible soil issues, management techniques like crop selection, leaching, and soil amendments may be needed. Class III can be categorized as unsuitable for irrigation (Figure 8b), and water in Class III poses a high risk of soil degradation, including salinization and sodification, if used for irrigation without proper management.

Gibbs diagram

The Gibbs diagram (Gibbs 1970) depicts the process that controls groundwater chemistry. It helps to decipher the evolution of the groundwater during the travel path. As we know, the evolutionary path of groundwater with respect to the facies change is from HCO₃ type to Cl^- type, with increasing salinity (Marandi and Shand 2018). Figure 9 portrays the evolution of groundwater chemistry or groundwater facies along a flow path. The evolution of groundwater chemistry can be triggered by water-rock interaction, mixing of different type of groundwater, redox controlled reactions, exchange with aquifer matrix, cross-formational flows or admixing of two aquifers or inputs from surface source. With the changes along a flow-path, the chemistry of groundwater also changes, and ultimately facies changes are encountered. In general, groundwater evolves from a Ca-HCO₃ type, to a Ca-Mg-HCO₃ type, to a Na-HCO₃ type, and ultimately to a Na-Cl type (Edmunds et al. 1987). This evolution causes a shift to fresh groundwater, in the upper right corner of the diagram. The same shift can also be favorable by the processes of dissolution of evaporates in the aquifer matrix, admixing of saline water in coastal areas, admixing with an upper saline infested aquifer, connection with an evaporite lake, and flushing of a salinized upper aquifer matrix (Marandi and Shand 2018).

Figure 9 Classification of PoM groundwater after Gibbs diagram (Gibbs 1970).

The Piper trilinear diagram and the plotted data in the Gibbs diagram convey that a shift of fresh groundwater, seen towards the upper right corner of the Gibbs diagram (Figure 9), is generally indicative of the existence of Na- HCO₃ type water, which may be the product of freshening activity due to flushing of a saline infested upper or shallow aquifer matrix (Banks and Frengstad 2006; Sarwade et al. 2007) via the cation exchange process (Howden and Mather 2012).

5 Conclusion

Finally, to summarize the obtained results of the present study, it is concluded that due to its location at the apex of the propagating delta front of the river Ganga-Brahmaputra-Meghna, the present study area is severely vulnerable to periodic cyclonic events.

Saline water ingress, scarcity of sustainable freshwater availability, and rampant tapping for groundwater to quench the thirst of local livelihoods, are radically depleting the hydrogeological scenario. The research depicts that chemically, the sequence of the cation concentrations by dominance is Na⁺, Ca⁺², Mg⁺², and K⁺, with contributions of 88%, 85%, 7%, and <5%%, respectively. Similarly, the sequence for the anions in the study area is as follows: HCO₃^->Cl^->SO₄^-2>NO₃^-, with contributions of 78%, 20%, and < 1% (for SO₄^-2 > NO₃^-). This is illustrated using the Piper trilinear diagram, Gibbs diagram, and Pearson’s correlation matrix, considering the correlation coefficient between Na⁺, Ca⁺², and HCO₃^-.

It reveals that the hydro-chemical facies of the area are entirely Na-HCO₃ type, which is possibly the result of admixing or incursion of sodium-rich brine water derived from the seawater into the zones of the freshwater-infested area. The process responsible for this is expected to be the cation exchange process between aquifers of different depths.

The estimated WQI of the area precisely points out that the overall water quality of the block is considerably ‘poor’. Isoline contour diagrams of bicarbonate, sodium, and conductivity show that greater values are encountered in the near-shore region, and they gradually decrease as they move inland. This is possible because solute exchange processes are much more dominant in the near-shore region than in the inland region, with increased inhabitation and profuse agriculture.

The study reveals poor suitability of groundwater for irrigation, with almost all 22 locations exceeding permissible limits. The Water Quality Index also indicates a significant issue, with 80% of samples falling in class IV, 'very poor'. Despite the favorable PoM season, the overall groundwater quality, suitability, and availability are significantly degraded. The pre-monsoon period may make the hydrogeological scenario more vulnerable, which will be addressed in future studies. Admixing of fresh water from deeper aquifers, while sea infested saline shallow aquifers can be inferred by the isotopic approach. By using a stable isotope system, the zone of admixing may be determined.

To enhance the study, it is recommended to install a small number of tube wells to extract water from the shallow saline aquifers for the purpose of evaluating the salinity level of the groundwater. Gaining insight into the movement of saltwater into freshwater aquifers can be achieved by monitoring the changes in the isotopic composition of groundwater over time. Fluctuations in oxygen isotopic variations measurements over time may indicate seasonal fluctuations in the replenishment of groundwater, alterations in the extent of intrusion, or the impacts of human activities on aquifer systems. Studying the transport of water between aquaculture ponds and aquifers could provide valuable insights into their dynamics.

To address the declining water situation, mandatory rainwater harvesting schemes, pond excavation for rainwater storage, and less water-intensive crop production are recommended. A pilot project can help identify potential aquifer contamination locations. Mass awareness programs can help prevent indiscriminate groundwater usage. Regular monitoring and policymaking for water conservation are needed. However, population growth, lack of public awareness, poor governance, and frequent storm surge-induced disasters with climatic change are major barriers to implementing these policies. Additionally, periodic storm surge-induced disasters and erratic climate change can also hinder sustainable water management plans.

Acknowledgments

All the laboratory-based chemical analysis was done at the Water Chemistry Laboratory of the Department of Environmental Sciences, University of Burdwan, West Bengal, India,

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