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Vol.:(0123456789)
Environmental Science and Pollution Research
https://doi.org/10.1007/s11356-024-33852-3
RESEARCH ARTICLE
Evaluating trends ingroundwater quality ofcoastal alluvial aquifers
ofEastern India forsustainable groundwater management
SubhankarGhosh1 · MadanKumarJha1
Received: 17 August 2023 / Accepted: 27 May 2024
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024
Abstract
Groundwater is a precious natural element which ensures global water, food, and environmental security in the twenty-first
century. Systematic monitoring, sustainable utilization, preservation and remediation are critical aspects of efficient ground-
water resource management. This study deals with the analysis of spatial variability and trend in groundwater chemistry
as well as identification of possible contamination sources in a coastal alluvial basin of eastern India. Pre-monsoon season
data of 14 groundwater-quality variables measured in ‘leaky confined’ and ‘confined’ aquifers were analyzed for ten years
(2012–2021). Mann–Kendall (M–K) test with the Sen’s Slope Estimator, Spearman Rank Order Correlation (SROC) and
Innovative Trend Analysis (ITA) tests were employed to assess decadal (2012–2021) trends. The analysis of the results indi-
cated that the ‘critical’ water-quality parameters exceeding the acceptable limits for drinking are TDS, EC, TH, pH, Mg2+,
Na+, K+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ. Weak negative correlations between rainfall and groundwater elevation for both the
aquifers reveal poor rainfall recharge into the aquifers. Therefore, a reduction in groundwater abstraction and augmentation of
groundwater recharge is recommended. Trend analysis results indicated that the concentrations of TH, Mg2+ and Fe2+ exhibit
significant increasing trends in the ‘leaky confined aquifer’. In contrast, significant rising trends in TH, Mg2+, Na+, Fe2+,
HCO3ˉ and NO3ˉ concentrations are identified in the ‘confined aquifer’. Further, the SROC test could not detect the trends in
groundwater quality in most blocks and for many parameters. On the other hand, the ITA test revealed significant trends in
most of the parameters of the two aquifers in almost all the blocks. Trend magnitudes of the groundwater-quality parameters
based on the Sen’s Slope Estimator and the ITA test vary from –63.7 to 58.65mg/L/year for TDS, –14 to 39.07mg/L/year
for TH, –1.49 to 4.83mg/L/year for Mg2+, –7.14 to 22.96mg/L/year for Na+, –0.32 to 0.44mg/L/year for Fe2+, –8.33 to
20.75mg/L/year for HCO3ˉ, –26.52 to 31.01mg/L/year for Clˉ and 1.29 to 3.76mg/L/year for NO3ˉ over the study area. The
results of M–K and ITA tests were found in agreement in all the blocks for both the aquifers. Groundwater contamination in
both the aquifers can be attributed to weathering, geogenic processes, mineral dissolution, seawater intrusion, poor recharge
pattern and injudicious anthropogenic activities. It is strongly recommended that concerned authorities urgently formulate
efficient strategies for managing groundwater quality in the ‘leaky confined’ and ‘confined’ aquifers which serve as vital
sources of drinking and irrigationwater suppliesin the study area.
Keywords Groundwater quality· Coastal aquifers· Trend analysis· Mann–Kendall· Spearman rank order correlation·
Innovative trend analysis· Groundwater contamination· Trend reversal
Introduction
Groundwater makes up more than 97% of the world’s
total freshwater reserve, keeping glaciers and ice caps out
of the equation (EC 2008). It is a vital freshwater source
for meeting the water requirements of the ever-increasing
population in various sectors of the economy around the
globe. Groundwater serves as a drinking water source for
roughly 50% of the global population and contributes to 43%
of worldwide irrigation (FAO 2010). Around 65% of total
Responsible Editor: Xianliang Yi
* Madan Kumar Jha
madan@agfe.iitkgp.ac.in
Subhankar Ghosh
subhankarghosh1994@yahoo.in
1 AgFE Department, Indian Institute ofTechnology
Kharagpur, Kharagpur721302, India
Environmental Science and Pollution Research
extracted groundwater worldwide is used for drinking, 20%
for irrigation and livestock, and the rest 15% for industrial
uses (Salehi etal. 2018; Adimalla etal. 2020). In India (as
of March 2017), around 89% (221.33 km3) of total ground-
water withdrawn (248.69 km3) is utilized for agricultural
production, 9% (22.38 km3) in the domestic sector, and the
remaining 2% (4.98 km3) in the industries (Margat and van
der Gun 2013; CGWB 2019). Groundwater supplies 85%
of India's drinking water and 60% of its agricultural water
needs, hence establishing it as the leading worldwide con-
sumer of groundwater (World Bank 2012; Jain etal. 2018).
The concentration of a water-quality parameter at a specific
location depends on several factors, including land-use/
cover characteristics, surface water-groundwater interac-
tion, depth-to-groundwater level, groundwater abstraction
regimes, saline water intrusion, seasonal and climatological
effects, as well as other natural and anthropogenic activities
(Craig and Daly 2010; Oliva etal. 2016). Because ground-
water travels slowly through the sub-surface, the conse-
quences of improper human actions may persist for decades,
and contamination events from past years will most likely
continue to endanger humanity for several generations. The
quantitative and qualitative deterioration of freshwater has
been reported in the past few decades due to several factors,
such as increasing population, urbanization and industriali-
zation, coupled with the rampant mismanagement of land
and water resources under changing climatic and socio-
economic conditions worldwide (e.g., Roscoe Moss Co.
1990; Vörösmarty etal. 2000; van der Gun 2012; Santucci
etal. 2018; Ouhamdouch etal. 2020), including India (e.g.,
Kumar and Singh 2015; Singh etal. 2020; Sahu etal. 2021;
Sutradhar and Mondal 2021).
Groundwater monitoring networks record temporal data
of pollutant concentrations at each sample location. The
European Union (EU) has implemented updated water regu-
lations that incorporate both the Water Framework Directive
(WFD) (EU 2000) and the Groundwater Daughter Directive
(GWD) (EU 2006). The WFD is a monitoring guideline for
conserving all natural waters that specifies environmental
goals to be met within 2015 and considers extending that
to 2021 or 2027. Both WFD and GWD aim to investigate
sustained rising contamination trends and their reversal.
Assessing these trends is of utmost importance to determine
and understand whether natural and anthropogenic activi-
ties, urban and peri-urban settlements, fertilizer applica-
tion, changes in land-use/ cover characteristics, saline water
intrusion, groundwater abstraction or climate change affect
groundwater chemistry. Groundwater chemistry is signifi-
cantly influenced by various point sources (e.g., contami-
nated land, landfill, mining, sewage etc.) and non-point/dif-
fused sources (e.g., agricultural chemicals through irrigation
return flow, urban waste etc.) of pollution. The European
Commission (EC 2011) recommends using water-quality
guidelines and threshold (acceptable) limits to assess its
chemical nature. Seawater intrusion assessment in coastal
aquifers involves the use of threshold limits along with
trend tests. It is due to the fact that if the Exploitation Index
(ratio of ‘water abstraction’ to ‘available resource/recharge’)
becomes more than 80%, saline water intrusion takes place.
The GWD further suggested suitable measures to control
and prevent the mixing of contaminants into groundwater.
Both WFD and GWD additionally demand that trends be
determined for contaminants that classify groundwater as
‘at risk’ of not fulfilling WFD’s environmental goals. Article
2 of the GWD states that these trends should have ‘statisti-
cal’ and ‘environmental’ significance. The environmental
significance points toward the probable future effect of a
detected rising trend in pollution. When groundwater-quality
concentrations exceed 75% of the threshold limits, the rising
trends need to be reverted to safe limits (EU 2000, 2006). It
requires implementing the ‘Program of Measures’ to gradu-
ally lower contamination and restrict further qualitative deg-
radation of groundwater (EU 2006).
Investigation of trends aims to identify and analyze
whether time-series data increases, decreases, or is station-
ary for a particular time duration. Furthermore, groundwater
monitoring involves elements that make it challenging to
precisely investigate trends, i.e., frequency of water sample
collection, presence of missing data and outliers, length of
the monitoring time, seasonal and auto-correlation effects
etc. In several instances, the attributes of groundwater data
may fail to meet the requisite requirements for conventional
statistical tests employed in evaluating trends (Kisi and Ay
2014). In relation to the temporal extent of annual time-
series data, Grath etal. (2001) suggested a minimum of
8 data records for identifying a trend and 15 data records
to determine the presence of a significant inflection point
(breakpoint) for reversing a trend. In data-scarce conditions,
the results should be analyzed and interpreted carefully. The
trend analysis techniques are broadly categorized into two
types, viz., ‘parametric’ techniques (distribution dependent)
and ‘non-parametric’ techniques (distribution free). Ground-
water trend evaluation is unquestionably a fascinating area of
study. Thus far, substantial conception has been developed
pertaining to the efficacy of various techniques, although not
sufficient to suggest which single method is best for analyz-
ing unknown time-series data. While investigating a dataset,
inflection points (breakpoints) must be identified properly
and effectively. This process is a critical step in analyzing
groundwater trends. Statistical methods for detecting linear
or monotonic patterns may be highly influenced by the pres-
ence of multiple trends (increasing and decreasing in suc-
cession); therefore, identifying a breakpoint is essential to
highlight a trend reversal. This complex task necessitates the
diligent exploration and aggregation of local data, primarily
pertaining to human-induced pressures, natural phenomena
Environmental Science and Pollution Research
and climatic change, including a comprehensive technical
knowledge of regional hydrogeology and hydrodynamics
(Oliva etal. 2016). When assessing the efficacy of reme-
dial measures for groundwater-quality restoration, a falling
trend is required to be achieved. In contrast, the presence
of increasing trends is the rationale behind trend reversal.
Several researchers in the past have reviewed different
statistical methods for studying water quality trends (e.g.,
Harris etal. 1987; Hirsch etal. 1991; Esterby 1996; Grath
etal. 2001; Mozejko 2012). They demonstrated specific
techniques for detecting monotonic, linear or cyclical (sea-
sonal) and step-wise trends in a dataset. Various statistical
approaches are employed for the identification of trends in
groundwater data, viz., Linear Regression (LR), Piece-wise
Linear Regression (PLR), Robust Linear Regression (RLR),
Mann–Kendall (M–K) with Sen’s slope test, Robust Rank
Correlation Coefficient and a Corresponding (RoCoCo)
test etc. Machiwal and Jha (2012) evaluated 28 statistical
approaches for identifying homogeneity, trends, periodicity
and seasonality in hydrological data. The LR method was
found to be highly sensitive to outliers and over-dispersion,
whereas RLR is good against outliers. However, both LR
and RLR have certain limitations, viz., (a) they can only
capture a linear trend, (b) they do not identify multiple (step-
wise) trends, and (c) they do not consider the possibility of
auto-correlation. The non-parametric M–K test, when used
with the non-parametric Sen Slope Estimator, becomes
very robust, even for a non-normal dataset with outliers
(Hirsch etal. 1982; Gilbert 1987; Rong 2000; Visser etal.
2009; Niazi etal. 2014; Machiwal and Jha 2015). Detecting
trends by employing the M–K test presents the challenge
of selecting the exact timeframe to apply it. Loftis (1996)
demonstrated why it is risky to use the technique over the
whole period of observation, more so if it is relatively long
(> 10years). In that scenario, it may not capture the presence
of any breakpoint causing trend reversal. No such technique
offers optimal performance under unknown circumstances,
and limited comparative studies of some proposed meth-
ods have been reported to date (Oliva etal. 2016). There
are different statistical methods to identify breakpoints in
a time-series dataset for performing trend reversal, such as
Quadratic Regression (QR), Piece-Wise Linear Regression
(PLR),Two/Three-SectionLinear Regression (2SLR/3SLR),
Two/Three-SectionMann–Kendall (2SM-K/3SM-K), Pet-
titt’s test etc. However, the PLR, 2SLR and 2SM-K tests
are strongly recommended to identify breakpoints in a data-
set (Oliva etal. 2016; Frollini etal. 2021). In addition, the
application of 3SLR and 3SM–K should be considered for
a longer (≥ 20years) time-series dataset (Oliva etal. 2016).
Several researchers in the past have used different statistical
techniques for identifying and analyzing trends in surface
water quality worldwide (e.g., Yu etal. 1993; Antonopou-
los etal. 2001; Bouza-Deaño etal. 2008; Lee etal. 2010;
Kisi and Ay 2014; Shammi etal. 2017; Ha etal. 2022), and
as well as in India (e.g., Ravichandran 2003). Several past
studies have considered different statistical techniques for
identifying and analyzing groundwater quality trends world-
wide (e.g., Batlle-Aguilar etal. 2007; Wahlin and Grimvall
2010; Mendizabal etal. 2012; Vousoughi etal. 2013; Lopez
etal. 2015; Niu etal. 2017; Ducci etal. 2019; Jeon etal.
2020; Frollini etal. 2021), as well as in India (Machiwal
and Jha 2015).
The review of literature presented above reveals that a
majority of the past researchers have investigated spatio-
temporal variation and trends in surface water quality. In
contrast, limited studies in the past have been conducted in
the field of groundwater quality, especially in developing
nations like India. More or less, all of the past studies
focused only on a single aquifer system for assessing
groundwater quality, though more than one aquifer usually
exist in most hydrogeological settings. Studies on the
comprehensive assessment of spatial variation and temporal
pattern in groundwater quality, groundwater pollution
source identification and trend reversal analysis are lacking
in the coastal aquifers of developing countries, including
India. Eastern India has a history of poor management
of groundwater resources, especially in the West Bengal
province. To date, no such scientific study has been
reported in the Indian sub-continent, particularly in the
coastal regions. Taking into account these research gaps
and the necessity for investigation in the coastal regions
of India, the present study has been undertaken in a river
basin located along the West Bengal coast of eastern India.
The objectives of this research are: (i) to assess the spatial
variation of groundwater quality in ‘leaky confined’ and
‘confined’ aquifer systems, (ii) to investigate decadal trends
in groundwater quality and identify possible sources of
groundwater contamination, and (iii) to analyze the trend
reversal of groundwater-quality parameters. In a world
where freshwater is diminishing at a faster rate, these kinds
of scientific investigations for sustainable groundwater
management are more important than ever.
Materials andmethods
Study area
The present study was conducted in a river basin on the
southern coast of West Bengal province, eastern India. The
geographical area has a size of around 6358.60 km2 con-
sisting of 32 Administrative Units (known as ‘block’), and
it is situated within the latitudes 21º32΄44˝N − 22º29΄32˝N
and longitudes 87º00΄57˝E − 88º02΄54˝E. Figure1 shows the
area's geographical boundaries: to the north, the Kansabati
River; to the northeast, the Haldi River; to the west, the
Environmental Science and Pollution Research
Subarnarekha River; and to the south, the 99.40km long Bay
of Bengal coastline. The study region receives about 73%
of the mean annual precipitation of 1758mm as a result of
the ‘southwest monsoon’ spanning between mid-June and
September (known as the ‘monsoon season’). There are four
major meteorological seasons, viz., ‘pre-monsoon’ (March
to May), ‘monsoon’ (June to September), ‘post-monsoon’
(October to November) and ‘winter’ (December to
February).
The study region is categorized by lateritic terrain under-
lain by older alluvium in the northwest, and younger allu-
vium in the northeast, east, south and central portions. Semi-
consolidated tertiary sediments underlie the entire alluvial
and coastal plains. Furthermore, Fig.S1 shows the major
Fig. 1 Map of the study area
showing the administrative
units (blocks), river network,
and location of observation
wells in ‘Leaky Confined’ and
‘Confined’ aquifers
Environmental Science and Pollution Research
land use/land cover types in the study region are ‘Agricul-
ture’ (covers 66.5% of the area), ‘Built-up Area’ (17.2%),
‘Forest and Bare Land’ (10.5%) and ‘Waterbodies’ (5.8%).
Groundwater is the primary source of freshwater supply for
agriculture and domestic sectors in the study region. The
main cropping seasons are Kharif (June–September), Rabi
(October–February) and Zaid (March–May) seasons. The
dominant crop, paddy, is cultivated over 70% of the gross
cultivated area during both Kharif and Rabi seasons. Under
a changing climate, water shortage threatens West Bengal's
coastal districts with seawater intrusion. Geogenic phenom-
ena, natural disasters like cyclones and floods, as well as
human-induced stresses such as salt farming, brackish water
fisheries and excessive fertilizer usage are causing ground-
water contamination (Kumar etal. 2020).
Data used
For the purpose of conducting groundwater quality trend
analysis, pre-monsoon season (April) data of 14 parameters
were acquired from 132 observation wells tapping the ‘leaky
confined aquifer’ (20–120m bgl depth) and 138 observation
wells tapping the ‘confined aquifer’ (121–287m bgl depth)
for ten years (2012–2021). The collected data consisted
of Total Dissolved Solids (TDS), Electrical Conductivity
(EC), Total Hardness (TH) as CaCO3, pH, five major cations
[Calcium (Ca2+), Magnesium (Mg2+), Sodium (Na+), Potas-
sium (K+), and Iron (Fe2+)], and five major anions [Bicar-
bonate (HCO3ˉ), Chloride (Clˉ), Sulphate (SO42ˉ), Nitrate
(NO3ˉ), and Fluoride (Fˉ)]. On the other hand, pre-monsoon
groundwater-level (elevation) data of the ‘leaky confined’
and ‘confined’ aquifers were also acquired. These data were
procured from (i) Central Ground Water Board, Kolkata, (ii)
Ground Water Survey and Investigation, Bhubaneswar, and
(iii) Water Resources Investigation & Development Depart-
ment, Kolkata. In addition, daily rainfall data were acquired
from (i) India Meteorological Department, Pune, and (ii)
Special Relief Commissioner, Bhubaneswar.
Analysis ofspatial variation ingroundwater
chemistry
Information about the spatial variability and temporal pattern
of groundwater quality is imperative for efficiently planning
and managing the groundwater resource (Freeze and Cherry
1979; Todd 1980; Fetter 1994). General characteristics of
groundwater chemistry in the study region were analyzed
by estimating ‘minimum’, ‘mean’, ‘median’, ‘maximum’,
‘standard deviation’ and ‘coefficient of variation’ for both
‘leaky confined’ and ‘confined’ aquifers. The concentration
levels of all 14 water-quality parameters were compared to
the acceptable (threshold) limits of drinking water-quality
standards (given in TableS1) recommended by the Bureau
of Indian Standards (BIS 2012) for the years 2019 and 2021.
The acceptable and permissible limits of water-quality
parameters for drinking are illustrated in TableS1, includ-
ing the possible health hazards associated with their high
intake during consumption. The water-quality parameters
exceeding the acceptable (threshold) limits for drinking were
identified as ‘critical’ parameters, and those were selected
for preparing spatial variation maps and other subsequent
analyses. Hence, the spatial variation maps of these ‘criti-
cal’ pre-monsoon groundwater-quality parameters of 2012
and 2021 were prepared in ArcGIS (v10.5) environment for
both aquifers using the Inverse Distance Weighted (IDW)
interpolation technique. In addition, the Pearson Correlation
Matrices (Pearson 1896) were prepared by employing MS
Excel (v2016) software to investigate the degree of linear
relationship between rainfall, groundwater elevation and the
water-quality parameters in the pre-monsoon season of 2021.
Investigation oftrends ingroundwater quality
In the present study, an assessment of the decadal
(2012–2021) trends in eight ‘critical’ pre-monsoon ground-
water-quality parameters (i.e., TDS, TH, Mg2+, Na+, Fe2+,
HCO3ˉ, Clˉ and NO3ˉ) was carried out for ‘leaky confined’
and ‘confined’ aquifers of the study area. Trends identified
by one single method are often not reliable. Applying mul-
tiple statistical tests to accomplish the same objective in a
time-series study enhances the likelihood of declining a cor-
rect null hypothesis (Machiwal and Jha 2008; 2012). Hence,
three non-parametric statistical tests, viz., Mann–Kendall
(M–K) test with Sen’s Slope Estimator, Spearman Rank
Order Correlation (SROC) and Innovative Trend Analy-
sis (ITA) tests have been in this study used for the critical
assessment of trends. If at least two trend tests indicate a
significant trend (increasing or decreasing) in a water-quality
parameter within a block, that significant trend is accepted.
Block-wise averages of observation well data for the two
aquifer systems were used in assessing the trends. All these
analyses have been performed using R-program (v3.5.2) and
MS Excel (v2016). A concise overview of these trend detec-
tion tests is given below.
Mann–Kendall test
The non-parametric Mann–Kendall (M–K) test is a rank-
based technique that evaluates all probable deviations among
the relative quantities of one particular value to the succes-
sive values in a dataset (Mann 1945; Kendall 1962). The
assumptions considered in the M–K test are that the data
are independent, identically distributed and in random order.
Four different metrics were computed to conduct the M–K
test, viz., (i) ‘S’ statistic, (ii) mean [E(S)], (iii) variance
Environmental Science and Pollution Research
[var(S)], and (iii) ‘Z’ statistic. The M–K test statistic ‘S’
was estimated using Eq.(1) (Kendall 1962):
The ‘S’ statistic is approximately normally distributed
when a dataset contains more than eight values (Mann 1945;
Kendall 1962). The mean [E(S)] and variance [var(S)] were
computed as:
where, xi and xj = sequential values in a dataset for ith and jth
years, respectively; N = dataset length; g = number of tied
groups; and tp = number of data values in pth group. The
M–K test statistic ‘Z’ was estimated using Eq.(5):
Positive values of the ‘Z’ statistic indicate increas-
ing trends, whereas negative estimates reveal decreasing
trends. For |Z|> Zcrit, i.e., Z > Zcrit, (1-α/2) (in case of increas-
ing trend) or Z < –Zcrit, α/2 (in case of decreasing trend), the
null hypothesis (H0) of ‘no trend exists’ can be rejected and
the alternate hypothesis (H1) of ‘significant trend exists’ is
established. On the other hand, if |Z|< Zcrit, the null hypoth-
esis (H0) of ‘no trend exists’ cannot be rejected. In this study
(N = 10), the M–K test was used at significance levels of
α = 5% (Zcrit = ± 1.960) and α = 1% (Zcrit = ± 2.576). The
‘Zcrit’ statistic is the critical test-statistic value defined as
the area under the Standard Normal curve for a 2-tailed test.
In order to quantify the trend magnitude, the non-par-
ametric Sen’s Slope Estimation test (Sen 1968) was used.
The positive values of trend magnitudes indicate increasing
trends and vice-versa. The Sen’s slope estimate (trend mag-
nitude) ‘β’ was computed as follows (Sen 1968):
(1)
S=
N−1
∑
i=1
N
∑
j=i+1
sgn
(
xj−x
i
)
(2)
sgn
xj−x
i
=
−1, if
xj−x
i
<
0
0, if
xj−x
i
=0
+1, if
xj−x
i
>
0
(3)
E(S)=0
(4)
var
(S)=1
18
[
N(N−1)(2N+5)−
g
∑
p=
1
tp(tp−1)(2tp+5)
]
(5)
Z=⎧
⎪
⎨
⎪
⎩
S−1
√var(S) if S >
0
0if S = 0
S+1
√
var(S) if S >
0
(6)
β = median[
xi−xj
i−j
]
∀i>
j
Spearman rank order correlation test
To examine the presence of long-term non-linear trends
in time-series data, the non-parametric Spearman Rank
Order Correlation (SROC) test was used (McGhee 1985).
The coefficient of trend (rs) was calculated using Eq.(7):
where, Rxt = rank allotted to a dataset (xt) measured in time
‘t’ such that the highest ‘xt’ has Rxt = 1, whereas the low-
est ‘xt’ has Rxt = n; and n = dataset length. Under the null
hypothesis (H0), the SROC test-statistic ‘ts’ has a 2-tailed
Student’s t-distribution with (n–2) degrees of freedom, and
the ‘ts’ was calculated as follows:
Positive values of the ‘ts’ statistic suggest increas-
ing trends, whereas negative estimates reveal decreas-
ing trends. The computed value of ‘ts’ was compared to
the critical test-statistic value (tcrit) of the 2-tailed stu-
dent’s t-distribution [tcrit (α, n–2)] at significance levels of
α = 5% and α = 1%, and for (n–2) degrees of freedom. For
|ts|> tcr it, i.e., ts > tcrit, (α, n–2) (in case of increasing trend)
or ts < –tcrit, (α, n–2) (in case of decreasing trend), the null
hypothesis (H0) of ‘no trend exists’ can be rejected, and
the alternate hypothesis (H1) of ‘significant trend exists’ is
established. On the other hand, if |ts|< tcrit, the null hypoth-
esis (H0) of ‘no trend exists’ cannot be rejected. In this
study (n = 10), the SROC test was used at significance
levels α = 5% (tcrit = ± 2.306) and α = 1% (tcrit = ± 3.355).
Innovative trend analysis test
The non-parametric Innovative Trend Analysis (ITA)
test was initially introduced by Şen (2012), which can be
applied to any dataset irrespective of any assumption. In
this analysis, the observed time-series dataset was divided
into two equal segments and sorted in ascending order.
The first segment of the dataset (Xi: i = 1, 2, 3, ….., n/2)
was plotted on the horizontal X-axis, and the remaining
part of the dataset (Xj: j = n/2 + 1, n/2 + 2, ……, n) was
plotted on the vertical Y-axis. A 1:1 (45˚) line was drawn
on the graph. When the plotted data values fall precisely
on this 1:1 line, it indicates that there is no trend in the
dataset. On the other hand, if the data points lie above the
(7)
r
s=
1−
6
n
t=1dt
2
n
n2−1
(8)
dt= (Rxt − t)
(9)
t
s=r
s×
√
n−2
1−r
s
2
Environmental Science and Pollution Research
1:1 line, it suggests a monotonic increasing trend in the
dataset and vice-versa (Şen 2012, 2014). However, when
the data points lie above and below the 1:1 line, it reveals
the existence of a non-monotonic trend. The trend slope
(S) was computed using Eq.(10) (Şen 2017):
The slope standard deviation (σs) was estimated as:
Finally, the confidence limit (CL) of the trend slope was
calculated as follows:
where, μ1 and μ2 = means of the first and the second half
of the time-series dataset, respectively; n = dataset length;
σ = standard deviation of the overall dataset; ρ = correla-
tion value between the two segments of the data; α = sig-
nificance level; and Scrit = critical slope value from 2-sided
Normal distribution table at α = 5% (Scrit = 1.645) and
α = 1% (Scrit = 2.326). Positive ITA trend slope ‘S’ values
indicate increasing trends, whereas negative estimates sug-
gest decreasing trends (Şen 2017). For |S|> CL(1–α), i.e.,
S > CL(1–α) (in case of increasing trend) or S < –CL(1–α) (in
case of decreasing trend), the null hypothesis (H0) of ‘no
trend exists’ can be rejected, and the alternate hypothesis
(H1) of ‘significant trend exists’ is established. On the other
hand, if |S|< CL(1–α), the null hypothesis (H0) of ‘no trend
exists’ cannot be rejected.
Assessment oftrend reversal ofgroundwater
quality
For this analysis, groundwater-quality parameters showing
increasing trends were identified, and their trend magni-
tudes (increasing or decreasing parameter concentration/
per year) estimated by Sen’s Slope Estimator and Inno-
vative Trend Analysis test were used to predict the time
period (with reference to the baseline year 2021) when
the concentrations of groundwater-quality parameters
will exceed 75% of the permissible limits for drinking as
recommended by WFD (EU 2000) and GWD (EU 2006).
The outcome of this analysis is of utmost importance for
the concerned regulatory bodies, policymakers and water
managers to urgently formulate sustainable groundwa-
ter management plans for reverting the increasing trend
and maintaining desirable/acceptable level of parameter
concentration.
(10)
S=
2× (μ
2
−μ
1
)
n
(11)
σ
s=
2
√
2×σ×
√
1
−ρ
n
√
n
(12)
CL(1−
𝛼
)=0±S
crit
×σ
s
Results anddiscussion
Identification ofcritical groundwater‑quality
parameters
The ‘critical’ groundwater-quality parameters based on the
BIS (2012) guidelines were identified, and the results are
presented in TablesS2(a,b). Results indicate the number
of sites in different Administrative Units (blocks) where
water-quality parameters exceed the acceptable (threshold)
limits for the drinking purpose during 2019 and 2021 in
both ‘leaky confined’ and ‘confined’ aquifers. TableS2(a)
reveals that among the 14 groundwater-quality parameters
analyzed in this study, ten parameters [TDS (7 blocks),
EC (7 blocks), TH (6 blocks), Mg2+ (1 block), Na+ (5
blocks), K+ (2 blocks), Fe2+ (8 blocks), HCO3ˉ (7 blocks),
Clˉ (2 blocks), and NO3ˉ (5 blocks)] exceed their respec-
tive acceptable limits for drinking during 2019 in the
‘leaky confined aquifer’. In addition, the same ten param-
eters [TDS (15 blocks), EC (6 blocks), TH (11 blocks),
Mg2+ (7 blocks), Na+ (8 blocks), K+ (4 blocks), Fe2+ (19
blocks), HCO3ˉ (9 blocks), Clˉ (1 block), and NO3ˉ (3
blocks)] exceed the acceptable limits in 2021. TableS2(b)
shows that among the 14 groundwater-quality parameters
analyzed in this study, nine parameters [TDS (14 blocks),
EC (15 blocks), TH (13 blocks), Mg2+ (4 blocks), Na+
(5 blocks), Fe2+ (9 blocks), HCO3ˉ (14 blocks), Clˉ (4
blocks), and NO3ˉ (3 blocks)] exceed their respective
acceptable limits for drinking during 2019 in the ‘confined
aquifer’ of the study area. In contrast, eleven parameters
[TDS (17 blocks), EC (14 blocks), TH (14 blocks), pH (2
blocks), Mg2+ (8 blocks), Na+ (12 blocks), K+ (2 blocks),
Fe2+ (16 blocks), HCO3ˉ (15 blocks), Clˉ (3 blocks), and
NO3ˉ (9 blocks)] exceed the acceptable limits in 2021.
Spatial variation ofgroundwater‑quality
parameters
General characteristics of pre-monsoon (April) ground-
water quality in ‘leaky confined’ and ‘confined’ aquifers
during 2021 are presented in Table1. The Total Dissolved
Solids (TDS) levels during 2021 varied between 40 to
1714mg/L with mean value 271.30mg/L in the ‘leaky
confined aquifer’, and 170 to 2110mg/L with mean value
453.72mg/L in the ‘confined aquifer’. TablesS2(a,b) show
that TDS levels in 2021 exceeded the BIS (2012) accept-
able (threshold) limit of 500mg/L in 26 observation wells
(in 15 blocks) tapping the ‘leaky confined aquifer’ and in
55 observation wells (in 17 blocks) tapping the ‘confined
aquifer’. Additionally, Figs.2 (a,b) reveal that the area in
which TDS levels in the ‘leaky confined aquifer’ exceeded
Environmental Science and Pollution Research
500mg/L decreased from 1645.54 km2 (25.9% of the total)
in 2012 to 744.76 km2 (11.7% of the total) in 2021. Fig-
ures2 (c,d) show that the area in which TDS levels in the
‘confined aquifer’ exceeded 500mg/L reduced from 1629
km2 (25.6% of the total) in 2012 to 1414.87 km2 (22.3% of
the total) in 2021. On the other hand, the Electrical Con-
ductivity (EC) values were in the range of 63 to 2670 μS/
cm (mean: 424.90 μS/cm) in the ‘leaky confined aquifer’,
and 248 to 3300 μS/cm (mean: 710.90 μS/cm) in the ‘con-
fined aquifer’. As BIS (2012) has not specified any limits
for EC, the World Health Organization (WHO) standards
were chosen to classify it. EC values < 750 μS/cm are con-
sidered as ‘acceptable’, 750–3000 μS/cm as ‘permissible’
and > 3000 μS/cm as ‘hazardous’ for drinking (WHO
2017). EC values in 2021 exceeded the acceptable limit
of 750 μS/cm in 13 observation wells (in 6 blocks) tap-
ping the ‘leaky confined aquifer’ and in 50 observation
wells (in 14 blocks) tapping the ‘confined aquifer’. Fur-
thermore, Figs.S2(a,b) indicate that the area in which EC
levels in the ‘leaky confined aquifer’ exceeded 750 μS/cm
decreased from 1834.77 km2 (28.9% of the total) in 2012
to 858.84 km2 (13.5% of the total) in 2021. Figs.S2(c,d)
depict that the area in which EC levels in the ‘confined
aquifer’ exceeded 750 μS/cm reduced from 1738.29 km2
(27.3% of the total) in 2012 to 1615.39 km2 (25.4% of the
total) in 2021. EC and TDS values of groundwater in both
aquifers have shown similar trends and are proportional
to each other.
Moreover, the Total Hardness (TH) values in 2021 ranged
20 to 480mg/L with mean 147.16mg/L in the ‘leaky con-
fined aquifer’, and 40 to 850mg/L with mean 169.33mg/L
in the ‘confined aquifer’. The TH levels exceeded the BIS
(2012) acceptable limit of 200mg/L in 18 observation wells
(in 11 blocks) tapping the ‘leaky confined aquifer’ and in 24
observation wells (in 14 blocks) tapping the ‘confined aqui-
fer’. In addition, Figs.S3(a,b) reveal that the area in which
TH levels in the ‘leaky confined aquifer’ exceeded 200mg/L
decreased from 1615.57 km2 (25.4% of the total) in 2012 to
391.12 km2 (6.2% of the total) in 2021. Figs.S3(c,d) show
that the area in which TH levels in the ‘confined aquifer’
exceeded 200mg/L reduced from 1523.39 km2 (24% of the
total) in 2012 to 573.88 km2 (9% of the total) in 2021. The
pH values varied between 6.60 to 8.46 with mean value 8.06
in the ‘leaky confined aquifer’, and 7.40 to 8.64 with mean
value 8.14 in the ‘confined aquifer’. As per the BIS (2012)
guidelines, pH values 6.5 to 8.5 are acceptable and in our
study, pH levels in 2 observation wells (in 2 blocks) tapping
the ‘confined aquifer’ exceeded the acceptable limit during
2021. Furthermore, concentrations of Calcium (Ca2+) during
2021 were in the range of 6 to 48mg/L (mean: 28.82mg/L)
in the ‘leaky confined aquifer’, and 12 to 60mg/L (mean:
28.95mg/L) in the ‘confined aquifer’. The Calcium values
in both aquifers did not exceed the BIS (2012) acceptable
limit of 75mg/L. On the other hand, concentrations of Mag-
nesium (Mg2+) ranged 0 to 56mg/L (mean: 20.47mg/L) in
the ‘leaky confined aquifer’, and 7.29 to 86mg/L (mean:
31.77mg/L) in the ‘confined aquifer’. Magnesium values in
11 observation wells (in 7 blocks) tapping the ‘leaky con-
fined aquifer’ and 14 observation wells (in 8 blocks) tapping
the ‘confined aquifer’ exceeded the BIS (2012) acceptable
limit of 30mg/L during 2021. Additionally, Figs.S4(a,b)
indicate that the area in which Magnesium levels in the
Table 1 Basic statistics of groundwater quality for drinking in 2021
Note: Min. = Minimum value; Max. = Maximum value; Med. = Median; Mean = Average; S.D. = Sample standard deviation; C.V. = Coefficient
of variation (%)
Groundwater-Qual-
ity Parameter
Leaky Confined Aquifer Confined Aquifer
Min Max Mean ± S.D Med C.V. (%) Min Max Mean ± S.D Med C.V. (%)
1. TDS (mg/L) 40.00 1714.00 271.30 ± 202.14 212.00 74.51 170.00 2110.00 453.72 ± 260.13 415.00 57.33
2. EC (μS/cm) 63.00 2670.00 424.90 ± 303.96 340.00 71.54 248.00 3300.00 710.90 ± 403.22 640.00 56.72
3. TH (mg/L) 20.00 480.00 147.16 ± 60.16 125.00 40.88 40.00 850.00 169.33 ± 94.91 150.00 56.05
4. pH 6.60 8.46 8.06 ± 0.30 8.17 3.73 7.40 8.64 8.14 ± 0.23 8.20 2.79
5. Ca2+ (mg/L) 6.00 48.00 28.82 ± 10.12 28.00 35.11 12.00 60.00 28.95 ± 12.47 25.00 43.06
6. Mg2+ (mg/L) 0.00 56.00 20.47 ± 12.87 15.90 62.86 7.29 86.00 31.77 ± 15.88 27.00 49.97
7. Na+ (mg/L) 4.00 101.00 31.12 ± 24.16 21.90 77.64 1.10 208.00 70.15 ± 46.70 57.00 66.57
8. K+ (mg/L) 0.70 41.00 5.04 ± 8.03 2.00 159.32 0.05 32.80 4.17 ± 6.49 2.94 155.65
9. Fe2+ (mg/L) 0.00 9.96 1.14 ± 2.14 0.32 187.22 0.00 9.79 0.69 ± 1.62 0.13 234.51
10. HCO3ˉ (mg/L) 12.00 390.00 199.41 ± 82.20 195.00 41.22 42.60 455.00 284.18 ± 90.95 295.00 32.00
11. Clˉ (mg/L) 14.18 770.00 54.56 ± 74.29 32.00 136.16 3.55 785.00 89.01 ± 96.60 65.00 108.53
12. SO42ˉ (mg/L) 0.00 35.00 12.18 ± 11.98 8.00 98.39 0.00 34.00 7.70 ± 10.02 4.00 130.15
13. NO3ˉ (mg/L) 0.00 21.00 2.89 ± 4.71 1.00 163.14 0.00 22.00 6.64 ± 6.37 3.00 95.97
14. Fˉ (mg/L) 0.00 0.95 0.27 ± 0.26 0.19 98.12 0.00 0.97 0.28 ± 0.26 0.30 91.17
Environmental Science and Pollution Research
‘leaky confined aquifer’ exceeded 30mg/L decreased from
944.39 km2 (14.9% of the total) in 2012 to 277.91 km2 (4.4%
of the total) in 2021. Figs.S4(c,d) depict that the area in
which Magnesium levels in the ‘confined aquifer’ exceeded
30mg/L increased from 1084.54 km2 (17.1% of the total) in
2012 to 3907.33 km2 (61.5% of the total) in 2021.
Furthermore, the Sodium (Na+) values during 2021 were
found between 4 to 101mg/L with mean 31.12mg/L in the
‘leaky confined aquifer’, and 1.10 to 208mg/L with mean
70.15mg/L in the ‘confined aquifer’. Sodium levels in 10
observation wells (in 8 blocks) tapping the ‘leaky confined
aquifer’ and in 18 observation wells (in 12 blocks) tapping
the ‘confined aquifer’ exceeded the BIS (2012) acceptable
limit of 50mg/L. In addition, Figs.3 (a,b) reveal that the
area in which Sodium levels in the ‘leaky confined aquifer’
exceeded 50mg/L decreased from 1663.95 km2 (26.2%
of the total) in 2012 to 931.75 km2 (14.7% of the total) in
2021. Figures3 (c,d) show that the area in which Sodium
levels in the ‘confined aquifer’ exceeded 50mg/L reduced
from 4165.12 km2 (65.5% of the total) in 2012 to 3580.34
km2 (56.3% of the total) in 2021. On the other hand,
the Potassium (K+) concentrations ranged from 0.70 to
41mg/L (mean: 5.04mg/L) in the ‘leaky confined aquifer’,
and 0.05 to 32.80mg/L (mean: 4.17mg/L) in the ‘confined
Fig. 2 (a–d) Spatial variation of pre-monsoon TDS Concentration in the ‘Leaky Confined Aquifer’ (a,b), and ‘Confined Aquifer’ (c,d)
Environmental Science and Pollution Research
aquifer’. Potassium values exceeded 12mg/L limit in 5
observation wells (in 4 blocks) tapping the ‘leaky confined
aquifer’ and in 2 observation wells (in 2 blocks) tapping the
‘confined aquifer’. Furthermore, Figs.S5(a,b) reveal that
the area in which Potassium levels in the ‘leaky confined
aquifer’ exceeded 12mg/L increased from 0 km2 in 2012
to 250.56 km2 (3.9% of the total) in 2021. The Iron (Fe2+)
values during 2021 varied between 0 to 9.96mg/L with
mean 1.14mg/L in the ‘leaky confined aquifer’, and 0 to
9.79mg/L with mean 0.69mg/L in the ‘confined aquifer’.
Iron values exceeded the BIS (2012) acceptable limit of
0.30mg/L in 68 observation wells (in 19 blocks) tapping
the ‘leaky confined aquifer’ and in 43 observation wells
(in 16 blocks) tapping the ‘confined aquifer’. Additionally,
Figs.4 (a,b) indicate that the area in which Iron levels in
the ‘leaky confined aquifer’ exceeded 0.30mg/L increased
from 2160.11 km2 (34% of the total) in 2012 to 5559.03
km2 (87.5% of the total) in 2021. Figures4 (c,d) depict
that the area in which Iron levels in the ‘confined aquifer’
exceeded 0.30mg/L increased from 3033.35 km2 (47.7%
of the total) in 2012 to 5324.07 km2 (83.8% of the total)
in 2021.
Fig. 3 (a–d) Spatial variation of pre-monsoon Sodium Concentration (Na+) in the ‘Leaky Confined Aquifer’ (a,b), and ‘Confined Aquifer’
(c,d)
Environmental Science and Pollution Research
Moreover, the Bicarbonate (HCO3ˉ) concentrations
during 2021 were found between 12 to 390mg/L (mean:
199.41mg/L) in the ‘leaky confined aquifer’, and 42.60 to
455mg/L (mean: 284.18mg/L) in the ‘confined aquifer’.
Bicarbonate levels exceeded the BIS (2012) acceptable limit
of 300mg/L in 16 observation wells (in 9 blocks) tapping
the ‘leaky confined aquifer’ and in 60 observation wells
(in 15 blocks) tapping the ‘confined aquifer’. In addition,
Figs.S6(a,b) reveal that the area in which Bicarbonate levels
in the ‘leaky confined aquifer’ exceeded 300mg/L decreased
from 1144.84 km2 (18% of the total) in 2012 to 401.37 km2
(6.3% of the total) in 2021. Figs.S6(c,d) show that the area in
which Bicarbonate levels in the ‘confined aquifer’ exceeded
300mg/L increased from 1085.03 km2 (17.1% of the total)
in 2012 to 1845.28 km2 (29% of the total) in 2021. On the
other hand, the Chloride (Clˉ) values ranged between 14.18
to 770mg/L (mean: 54.56mg/L) in the ‘leaky confined
aquifer’, and 3.55 to 785mg/L (mean: 89.01mg/L) in the
‘confined aquifer’. Chloride values in only 1 observation
well (in Contai-III block) tapping the ‘leaky confined
aquifer’ and in 4 observation wells (in 3 blocks) tapping the
‘confined aquifer’ exceeded the BIS (2012) acceptable limit
of 250mg/L during 2021. Additionally, Figs.S7(a,b) indicate
that the area in which Chloride levels in the ‘leaky confined
Fig. 4 (a–d) Spatial variation of pre-monsoon Iron Concentration (Fe2+) in the ‘Leaky Confined Aquifer’ (a,b), and ‘Confined Aquifer’ (c,d)
Environmental Science and Pollution Research
aquifer’ exceeded 250mg/L is found to be almost the same
as 140.25 km2 (2.2% of the total) both in 2012 and 2021.
Figs.S7(c,d) depict that the area in which Chloride levels in
the ‘confined aquifer’ exceeded 250mg/L decreased from
245.29 km2 (3.9% of the total) in 2012 to 92.35 km2 (1.5%
of the total) in 2021.
Furthermore, concentrations of Sulphate (SO42ˉ) were
found between 0 to 35mg/L with mean 12.18 mg/L in
the ‘leaky confined aquifer’, and 0 to 34mg/L with mean
7.70mg/L in the ‘confined aquifer’. The Sulphate values
in both aquifers did not exceed the BIS (2012) acceptable
limit of 200mg/L. On the other hand, the Nitrate (NO3ˉ)
concentrations ranged 0 to 21mg/L (mean: 2.89 mg/L)
in the ‘leaky confined aquifer’, and 0 to 22mg/L (mean:
6.64mg/L) in the ‘confined aquifer’. The Nitrate values
exceeded 10mg/L limit in 4 observation wells (in 3 blocks)
tapping the ‘leaky confined aquifer’ and in 12 observation
wells (in 9 blocks) tapping the ‘confined aquifer’. In addition,
Figs.S8(a,b) reveal that the area in which Nitrate levels in
the ‘leaky confined aquifer’ exceeded 10mg/L increased
from 67.52 km2 (1.1% of the total) in 2012 to 88.27 km2
(1.4% of the total) in 2021. Figs.S8(c,d) show that the area
in which Nitrate levels in the ‘confined aquifer’ exceeded
10mg/L increased from 0 km2 in 2012 to 452.76 km2 (7.1%
of the total) in 2021. The Fluoride (Fˉ) concentrations during
2021 varied between 0 to 0.95mg/L with mean 0.27mg/L in
the ‘leaky confined aquifer’, and 0 to 0.97mg/L with mean
0.28mg/L in the ‘confined aquifer’. The Fluoride values in
both aquifers did not exceed the BIS (2012) acceptable limit
of 1mg/L.
Table 2 Correlation Matrix of groundwater quality, GWE and rainfall for the Leaky Confined Aquifer during 2021
Note:Fractional numbers in bold indicate significant correlation (r > 0.50)
TDS EC TH Mg2+ Na+K+Fe2+ HCO3ˉ Clˉ NO3ˉGWE Rainfall
TDS 1
EC 0.997 1
TH 0.568 0.577 1
Mg2+ 0.637 0.573 0.936 1
Na+0.728 0.769 0.270 0.202 1
K+0.167 0.245 0.131 0.065 0.039 1
Fe2+ –0.114 –0.114 0.014 0.039 0.052 0.031 1
HCO3ˉ0.535 0.524 0.300 0.630 0.500 0.125 –0.076 1
Clˉ 0.903 0.894 0.558 0.329 0.635 0.133 –0.063 0.158 1
NO3ˉ 0.068 0.150 –0.043 –0.076 0.112 0.253 0.157 –0.055 0.136 1
GWE –0.109 –0.092 –0.076 –0.280 –0.057 0.324 0.029 –0.374 0.046 0.037 1
Rainfall 0.202 0.161 0.190 0.039 –0.102 –0.003 0.041 –0.167 0.269 0.011 –0.046 1
Table 3 Correlation Matrix of groundwater quality, GWE and rainfall for the Confined Aquifer during 2021
Note:Fractional numbers in bold indicate significant correlation (r > 0.50)
TDS EC TH pH Mg2+ Na+K+Fe2+ HCO3ˉ Clˉ NO3ˉGWE Rainfall
TDS 1
EC 0.998 1
TH 0.708 0.686 1
pH 0.027 –0.001 –0.207 1
Mg2+ 0.154 0.179 0.884 –0.189 1
Na+0.919 0.810 0.096 –0.143 0.170 1
K+0.368 0.634 0.193 0.066 0.252 0.535 1
Fe2+ –0.159 –0.166 0.048 –0.022 0.117 –0.044 –0.059 1
HCO3ˉ 0.465 0.438 0.064 –0.125 0.562 0.438 0.089 –0.174 1
Clˉ 0.931 0.928 0.763 –0.062 0.261 0.633 0.578 –0.120 0.230 1
NO3ˉ 0.310 0.404 –0.432 0.309 –0.433 0.209 0.031 –0.162 –0.539 0.324 1
GWE 0.019 0.001 –0.251 –0.093 0.099 –0.014 –0.289 0.004 0.340 –0.080 –0.138 1
Rainfall 0.505 0.501 0.212 –0.018 –0.053 0.496 0.080 –0.116 0.423 0.444 0.313 –0.179 1
Environmental Science and Pollution Research
Results ofcorrelation analysis
The correlation matrices between rainfall, groundwater
elevation (GWE) and groundwater chemistry for ‘leaky
confined’ and ‘confined’ aquifers are illustrated in Table2
and Table3, respectively. In this analysis, only those
groundwater-quality variables which exceed the acceptable
(threshold) limits for drinking were considered. Table2
and Table3 reveal significant correlations between the
pairs EC–Clˉ (r = 0.894), EC–Na+ (r = 0.769) and Na+–Clˉ
(r = 0.635) in the ‘leaky confined aquifer’ as well as in the
‘confined aquifer’ [EC–Clˉ (r = 0.928), EC–Na+ (r = 0.810)
and Na+–Clˉ (r = 0.633)]. These results suggest groundwater
mineralization in both aquifers is primarily due to strong
acidic anions such as Chlorides (Clˉ) and other minerals.
As far as weak acidic anions are concerned, the correlations
between the pairs HCO3ˉ–EC (r = 0.524), HCO3ˉ–Mg2+
(r = 0.630), and HCO3ˉ–Na+ (r = 0.500) are significant in the
‘leaky confined aquifer’ as well as in the ‘confined aquifer’
[HCO3ˉ–Mg2+ (r = 0.562)]. These findings indicate that
these cations (Mg2+ and Na+) may have originated in the
aquifers from sedimentary rocks such as limestone, dolomite
etc. On the other hand, strong correlations between the pairs
EC–Clˉ, Na+–Clˉ and Na+–HCO3ˉ indicate the presence of
halite/sylvite substances (evaporative compounds) or rock
salt (Ghosh and Jha 2023). Furthermore, weak correlations
(positive and negative) were found between GWE and the
water-quality parameters for both ‘leaky confined’ and
‘confined’ aquifers in 2021. Negative correlations indicate
dilution of groundwater-quality parameter concentrations
with an increase in GWE, whereas positive correlations
suggest a complex non-linear relationship between them. On
the other hand, weak negative correlations between rainfall
and GWE for both the aquifers reveal poor rainfall recharge
into the aquifers. These findings indicate an urgent need to
minimize groundwater pumping from both ‘leaky confined’
and ‘confined’ aquifers, and augment groundwater recharge
using suitable rainwater harvesting and artificial recharge
techniques.
Results oftrend analysis
Decadal (2012–2021) trend analysis results of eight ‘critical’
groundwater-quality parameters (i.e., TDS, TH, Mg2+, Na+,
Fe2+, HCO3ˉ, Clˉ, and NO3ˉ) for the ‘leaky confined’ and
‘confined’ aquifers are summarized in TablesS3(a–h) and
TablesS4(a–h), and discussed in subsequent sub-sections.
The results contain calculated test-statistic values of ‘Z’ and
‘ts’, confidence limits (at both α = 5% and α = 1%), and trend
magnitudes estimated by Sen’s Slope Estimation and Innova-
tive Trend Analysis (ITA) tests.
Leaky confined aquifer
The results of three trend tests (M–K, SROC and ITA)
for analyzing trends in Fe2+, TDS and Na+ in the ‘Leaky
Confined Aquifer’ are graphically shown in Figs.5 (a,b),
Figs.S9(a,b) and Figs.S10(a,b), respectively. It is evident
from TableS3(a) that the results of both M–K and SROC
tests show significantly decreasing TDS trends in Kharag-
pur-I and Pingla blocks at α = 5%, and the M–K test found
declining trend in Mohanpur (α = 5%) block also. The ITA
test reveals significantly increasing trends in Contai-III,
Egra-I and Panskura-I blocks at α = 1%, whereas decreas-
ing trends at α = 1% are observed in Keshiary, Kharagpur-
I, Khejuri-I, Khejuri-II, Mohanpur, Moyna, Nandigram-I,
Patashpur-I, Patashpur-II, Pingla and Sabang blocks. In addi-
tion, both M–K and ITA tests indicate significantly declining
TDS trends in Kharagpur-I, Mohanpur and Pingla blocks.
TableS3(b) shows that both M–K and SROC tests found
significantly rising TH trend in Dantan-I (α = 5%) block.
On the other hand, the ITA test reveals significantly declin-
ing trends of TH in Dantan-II, Keshiary, Patashpur-II and
Pingla blocks at α = 1%, and increasing trends in Contai-III,
Dantan-I, Mohanpur, Sabang and Sankrail blocks at α = 1%.
Both M–K and ITA tests indicate significantly increasing TH
trend in only Dantan-I block. It is apparent from TableS3(c)
that both M–K and SROC tests reveal significantly rising
Mg2+ trends in Kharagpur-I and Sabang blocks at α = 5%,
and the M–K test found increasing trend in Debra (α = 5%)
block also. Furthermore, the ITA test shows significantly
increasing trends of Mg2+ in Dantan-I, Dantan-II, Debra,
Kharagpur-I, Narayangarh, Pingla and Sabang blocks at
α = 1%. Additionally, both M–K and ITA tests indicate
significantly rising Mg2+ trends in Debra, Kharagpur-
I and Sabang blocks. TableS3(d) reveals that both M–K
and SROC tests found significantly declining Na+ trends in
Contai-III and Patashpur-II blocks at α = 5%. On the other
hand, the ITA test shows significantly decreasing trends of
Na+ in Contai-III, Keshiary, Kharagpur-I, Patashpur-II and
Sankrail blocks at α = 1%, and rising trends in Debra, Pingla
and Sabang blocks at α = 1%. Both M–K and ITA tests indi-
cate significantly decreasing Na+ trends in Contai-III and
Patashpur-II blocks. The graphical plots of the ITA test for
TH, Mg2+ and Fe2+ trends in the ‘Leaky Confined Aquifer’
are presented in Figs.6 (a–e), and similar plots for TDS and
Na+ parameters are shown in Figs.S11(a–e).
Furthermore, it is evident from TableS3(e) that both
M–K and ITA tests reveal significantly increasing Fe2+ trend
in only Ramnagar-I block at α = 5%. However, the SROC
test did not show any trend in Fe2+ levels in any block. The
ITA test shows significantly increasing trends of Fe2+ in
Dantan-II (α = 5%), Keshiary (α = 1%), Khejuri-II (α = 1%),
Narayangarh (α = 1%) and Ramnagar-I (α = 5%) blocks,
and declining trends in Bhagabanpur-I, Dantan-I, Debra,
Environmental Science and Pollution Research
Panskura-I, Patashpur-I, Pingla, Sabang and Sankrail blocks
also at α = 1%. Both M–K and SROC tests did not find sig-
nificant trends in HCO3ˉ, Clˉ and NO3ˉ concentrations in
any block. Additionally, TableS3(f) indicates that the ITA
test identified significantly rising trends of HCO3ˉ in Debra
(α = 5%), Egra-I (α = 1%), Egra-II (α = 1%), Kharagpur-I
(α = 1%), Moyna (α = 1%), Panskura-I (α = 1%), Patash-
pur-I (α = 1%) and Patashpur-II (α = 1%) blocks, whereas
decreasing trends are observed in Pingla and Sabang blocks
at α = 1%. It is apparent from TableS3(g) that the ITA test
found significantly increasing Clˉ trend in only Contai-III
block at α = 1%. On the other hand, TableS3(h) shows that
the ITA test identified significantly rising NO3ˉ trends Dan-
tan-I, Debra, Keshiary, Kharagpur-I, Sabang and Sankrail
blocks at α = 1%.
Moreover, the results obtained from the Sen’s Slope
Estimation test indicate that the trend magnitude values
(increasing or decreasing parameter concentration/year) of
TDS, TH, Mg2+, Na+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ param-
eters in the ‘leaky confined aquifer’ of different blocks var-
ied between –59.46 (Khejuri-II) to 1.30 (Sankrail) mg/L/
year, –5.50 (Patashpur-II) to 6.00 (Dantan-I) mg/L/year,
Fig. 5 (a,b) Results of trend
tests for Iron Concentration
(Fe2+) in the ‘Leaky Confined
Aquifer’: (a) M–K and SROC,
and (b) ITA
Environmental Science and Pollution Research
–0.50 (Dantan-I) to 2.46 (Narayangarh) mg/L/year, –3.00
(Keshiary) to 1.68 (Sabang) mg/L/year, –0.26 (Patashpur-
I) to 0.16 (Narayangarh) mg/L/year, –3.33 (Khejuri-I) to
6.25 (Egra-I) mg/L/year, –0.33 (Patashpur-II) to 16.67
(Contai-III) mg/L/year, and 0.14 (Debra and Kharagpur-
I) to 0.57 (Keshiary) mg/L/year, respectively. On the other
hand, the results obtained from the ITA test reveal that
the trend magnitudes (increasing or decreasing param-
eter concentration/year) of TDS, TH, Mg2+, Na+, Fe2+,
HCO3ˉ, Clˉ and NO3ˉ parameters in the ‘leaky confined
aquifer’ of different blocks ranged between –63.70 (Khe-
juri-II) to 58.65 (Contai-III) mg/L/year, –4.48 (Pingla) to
20.60 (Contai-III) mg/L/year, 0.74 (Narayangarh) to 2.09
(Sabang) mg/L/year, –5.69 (Keshiary) to 4.39 (Sabang)
mg/L/year, –0.32 (Patashpur-I) to 0.44 (Narayangarh)
mg/L/year, –4.45 (Pingla) to 12.25 (Egra-II) mg/L/year,
–2.88 (Patashpur-II) to 31.01 (Contai-III) mg/L/year, and
0.71 (Sabang) to 2.58 (Kharagpur-I) mg/L/year, respec-
tively. Based on the results of Sen’s Slope Estimation and
ITA tests, the highest average increasing trend magnitude
(per year) of 23.84mg/L was found for Clˉ, followed by
TDS (9.43mg/L), HCO3ˉ (5.47mg/L), TH (4.57mg/L),
Na+ (2.30mg/L), Mg2+ (1.33mg/L), NO3ˉ (0.88mg/L)
and Fe2+ (0.07 mg/L). In addition, good correlations
(r ≥ 0.80) between the trend magnitude values quantified
by Sen’s Slope Estimation and ITA tests are observed for
TDS (r = 0.79), Na+ (r = 0.92), Fe2+ (r = 0.81), and HCO3ˉ
(r = 0.83) parameters.
If at least two trend tests showed a significant trend
(increasing or decreasing) in a water-quality parameter
Fig. 6 (a–e) ITA graphical plots for significantly increasing trends of TH, Mg2+ and Fe2+ Concentrations in the ‘Leaky Confined Aquifer’
Environmental Science and Pollution Research
within a block, that significant trend has been accepted.
Therefore, among the eight ‘critical’ groundwater-
quality parameters assessed in the present research, the
concentrations of TDS (Kharagpur-I, Mohanpur and Pingla)
and Na+ (Contai-III and Patashpur-II) show significant
decreasing trends, whereas TH (Dantan-I), Mg2+ (Debra,
Kharagpur-I and Sabang) and Fe2+ (Ramnagar-I) levels
exhibit significant increasing trends in the ‘leaky confined
aquifer’. In a similar study, Batlle-Aguilar etal. (2007)
showed increasing NO3ˉ concentrations in an unconfined
chalk aquifer of Belgium, whereas NO3ˉ influence was
absent in the deeper leaky confined aquifer. Similarly, Jeon
etal. (2020) demonstrated the presence of significantly
increasing trends in EC, Ca2+, Mg2+, CO3ˉ and HCO3ˉ
concentrations, and decreasing trends in pH, Na+, K+, Clˉ,
NO3ˉ and SO42ˉ levels in the groundwater of South Korea.
The SROC test could not detect the trends in groundwater
quality of the ‘leaky confined aquifer’ in most blocks and
for many parameters. These results indicate that the SROC
test is less sensitive in detecting trends of water-quality
parameters than the other two methods. The ITA test
revealed significant trends for most parameters and in almost
all the blocks. Therefore, ITA method proved relatively
over-sensitive in identifying temporal patterns in a dataset.
However, M–K and ITA tests collectively yielded similar
results in all the blocks.
Fig. 7 (a,b) Results of trend
tests for Sodium Concentra-
tion (Na+) in the ‘Confined
Aquifer’: (a) M–K and SROC,
and (b) ITA
Environmental Science and Pollution Research
Confined aquifer
The results of three trend tests (M–K, SROC and ITA)
for investigating trends in Na+, NO3ˉ, TDS and Fe2+ in
the ‘Confined Aquifer’ are illustrated in Figs.7 (a,b),
Figs.8(a,b), Figs.S12(a,b) and Figs.S13(a,b), respectively.
It is evident from TableS4(a) that both M–K and SROC
tests show significantly decreasing TDS trend in Bhagaban-
pur-II block at α = 5%, and the M–K test found declining
trend in Contai-I (α = 5%) block also. The ITA test reveals
significantly increasing trends in Contai-III (α = 5%) and
Jaleswar (α = 1%) blocks, while decreasing trends at α = 1%
are observed in Bhagabanpur-I, Bhagabanpur-II, Contai-I,
Deshopran, Egra-II, Khejuri-I, Khejuri-II, Nandigram-I,
Nandigram-II, Panskura-I, Patashpur-I and Ramnagar-II
blocks. In addition, both M–K and ITA tests indicate sig-
nificantly decreasing TDS trends in Bhagabanpur-II and
Contai-I blocks. TableS4(b) shows that both M–K and
SROC tests found significantly rising TH trend in Jaleswar
(α = 5%) block, and the M–K test identified decreasing
trend in Nandigram-II (α = 5%) block also. On the other
hand, the ITA test reveals significantly declining trends of
TH in Bhagabanpur-I (α = 1%), Deshopran (α = 5%), Khe-
juri-I (α = 1%), Moyna (α = 1%), Nandigram-II (α = 1%)
and Patashpur-I (α = 1%) blocks, and increasing trends in
Contai-III (α = 1%), Jaleswar (α = 1%), Kamarda (α = 1%),
Fig. 8 (a,b) Results of trend
tests for Nitrate Concentra-
tion (NO3ˉ) in the ‘Confined
Aquifer’: (a) M–K and SROC,
and (b) ITA
Environmental Science and Pollution Research
Khejuri-II (α = 1%), Ramnagar-I (α = 1%) and Ramnagar-
II (α = 5%) blocks. Both M–K and ITA tests indicate sig-
nificantly increasing TH trend in only Jaleswar block, and
decreasing trend in only Nandigram-II block. Furthermore, it
is apparent from TableS4(c) that both M–K and SROC tests
reveal significantly rising Mg2+ trends in Egra-II and Moyna
blocks at α = 5%. On the other hand, the ITA test shows
significantly increasing trends of Mg2+ in Bhagabanpur-I,
Egra-II, Moyna, Patashpur-I, Patashpur-II, Ramnagar-I and
Ramnagar-II blocks at α = 1%, and declining trend in only
Khejuri-II (α = 1%) block. Additionally, both M–K and
ITA tests indicate significantly rising Mg2+ trends in Egra-
II and Moyna blocks. TableS4(d) reveals that both M–K
and SROC tests found significantly increasing Na+ trends
in Khejuri-II, Nandigram-I, Nandigram-II and Ramnagar-I
blocks at α = 5%, and the M–K test identified rising trend
in Deshopran (α = 5%) block also. Additionally, the ITA
test shows significantly decreasing trends of Na+ in Egra-II,
Moyna, Patashpur-I, Patashpur-II and Ramnagar-II blocks
at α = 1%, and increasing trends in Bhagabanpur-I, Deshop-
ran, Khejuri-II, Nandigram-I, Nandigram-II and Ramnagar-
I blocks at α = 1%. Both M–K and ITA tests indicate sig-
nificantly increasing Na+ trends in Deshopran, Khejuri-II,
Nandigram-I, Nandigram-II and Ramnagar-I blocks.
Furthermore, it is evident from TableS4(e) that both
M–K and SROC tests show significantly increasing Fe2+
trend in only Panskura-I block at α = 5%. The ITA test
reveals significantly increasing trends of Fe2+ in Contai-III
(α = 1%), Deshopran (α = 1%), Khejuri-I (α = 5%), Moyna
(α = 5%), Nandigram-II (α = 1%), Panskura-I (α = 1%),
Patashpur-I (α = 1%) and Ramnagar-II (α = 1%) blocks, and
decreasing trends in Bhagabanpur-I (α = 1%), Bhagabanpur-
II (α = 1%), Contai-I (α = 1%), Eg ra-I (α = 5%), Khejuri-II
(α = 1%) and Patashpur-II (α = 1%) blocks. In addition, both
M–K and ITA tests indicate significantly increasing Fe2+
trend in Panskura-I block. TableS4(f) shows that both M–K
and SROC tests found significantly rising HCO3ˉ trends in
Contai-I and Deshopran blocks at α = 5%, and the M–K
test identified increasing trend in Khejuri-I (α = 5%) block
also. On the other hand, the ITA test reveals significantly
rising trends of HCO3ˉ in Bhagabanpur-I, Bhagabanpur-II,
Chandipur, Contai-I, Deshopran, Egra-I, Egra-II, Khejuri-I,
Khejuri-II, Moyna, Nandigram-II, Patashpur-II, Ramnagar-I
and Ramnagar-II blocks at α = 1%, and declining trend in
Patashpur-I (α = 1%) block. Additionally, both M–K and
ITA tests indicate significantly increasing HCO3ˉ trends
in Contai-I, Deshopran and Khejuri-I blocks. It is appar-
ent from TableS4(g) that both M–K and SROC tests did
not find significant trend in Clˉ level in any block. On the
other hand, the ITA test shows significantly increasing trend
of Clˉ in Contai-III (α = 1%) block, and declining trends in
Chandipur, Deshopran and Nandigram-II blocks at α = 1%.
TableS4(h) reveals that both M–K and SROC tests found
significantly rising NO3ˉ trends in Contai-III, Deshopran,
Egra-I, Egra-II, Nandigram-I and Ramnagar-I blocks at
α = 5%, and the M–K test identified rising trend in Patash-
pur-I (α = 5%) block also. Additionally, the ITA test shows
significantly increasing trends of NO3ˉ in Bhagabanpur-I,
Contai-III, Deshopran, Egra-I, Egra-II, Khejuri-II, Nandi-
gram-I, Patashpur-I and Ramnagar-I blocks at α = 1%. Both
M–K and ITA tests indicate significantly rising NO3ˉ trends
in Contai-III, Deshopran, Egra-I, Egra-II, Nandigram-I,
Patashpur-I and Ramnagar-I blocks. The graphical plots of
the ITA test for TH, Mg2+ and Na+ trends as well as for NO3ˉ
trends in the ‘Confined Aquifer’ are depicted in Figs.9(a–h)
and Figs.10(a–g), respectively. The similar plots for TDS
and TH as well as for Fe2+ and HCO3ˉ parameters are shown
in Figs.S14(a–c) and Figs.S15(a–d), respectively.
Moreover, the results obtained from Sen’s Slope Estima-
tion test show that the trend magnitude values of TDS, TH,
Mg2+, Na+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ parameters in the
‘confined aquifer’ of different blocks ranged between –34.50
(Bhagabanpur-II) to 13.21 (Contai-III) mg/L/year, –14.00
(Nandigram-II) to 31.75 (Contai-III) mg/L/year, –1.00
(Khejuri-II) to 4.05 (Egra-II) mg/L/year, –2.63 (Ramnagar-
II) to 18.71 (Nandigram-II) mg/L/year, –0.23 (Patashpur-II)
to 0.15 (Panskura-I) mg/L/year, –8.33 (Contai-III) to 18.14
(Deshopran) mg/L/year, –16.22 (Nandigram-II) to 23.33
(Contai-III) mg/L/year, and 0.78 (Khejuri-II) to 3.14 (Nandi-
gram-I) mg/L/year, respectively. Furthermore, the results
obtained from the ITA test indicate that the trend magni-
tudes of TDS, TH, Mg2+, Na+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ
parameters in the ‘confined aquifer’ of different blocks var-
ied between –63.27 (Contai-I) to 28.95 (Contai-III) mg/L/
year, –11.89 (Nandigram-II) to 39.07 (Contai-III) mg/L/year,
–1.49 (Khejuri-II) to 4.83 (Egra-II) mg/L/year, –7.14 (Ram-
nagar-II) to 22.96 (Nandigram-II) mg/L/year, –0.16 (Patash-
pur-II) to 0.15 (Panskura-I) mg/L/year, –1.28 (Contai-III) to
20.75 (Deshopran) mg/L/year, –26.52 (Deshopran) to 20.23
(Contai-III) mg/L/year, and 1.29 (Bhagabanpur-I) to 3.76
(Nandigram-I) mg/L/year, respectively. Based on the results
of Sen’s Slope Estimation and ITA tests, the highest mean
rising trend magnitude (per year) of 13.79mg/L was found
for Clˉ concentrations, followed by TDS (12.12mg/L), TH
(9.05mg/L), Na+ (8.65mg/L), HCO3ˉ (8.43mg/L), Mg2+
(2.73mg/L), NO3ˉ (1.87mg/L) and Fe2+ (0.06mg/L). Addi-
tionally, strong correlations (r ≥ 0.80) between the trend
magnitude values estimated by Sen’s Slope Estimation and
ITA tests are observed for TDS (r = 0.83), TH (r = 0.91),
Mg2+ (r = 0.96), Na+ (r = 0.98), Fe2+ (r = 0.94), HCO3ˉ
(r = 0.91), and Clˉ (r = 0.93) parameters.
If at least two trend tests indicated a statistically
significant trend in a water-quality parameter within
a block, that significant trend was accepted. Hence,
out of eight ‘critical’ groundwater-quality parameters
analyzed in the present study, the concentrations of TDS
Environmental Science and Pollution Research
(Bhagabanpur-II and Contai-I) and TH (Nandigram-II)
show significant decreasing trends, whereas TH
(Jaleswar), Mg2+ (Egra-II and Moyna), Na+ (Deshopran,
Khejuri-II, Nandigram-I, Nandigram-II and Ramnagar-I),
Fe2+ (Panskura-I), HCO3ˉ (Contai-I, Deshopran and
Khejuri-I) and NO3ˉ (Contai-III, Deshopran, Egra-I,
Egra-II, Nandigram-I, Patashpur-I and Ramnagar-I)
levels exhibit significant increasing trends in the ‘confined
aquifer’. In a similar study, Mendizabal etal. (2012)
revealed significantly increasing trends in TH, HCO3ˉ,
Fig. 9 (a–h) ITA graphical plots for significantly increasing trends of TH, Mg2+ and Na+ Concentrations in the ‘Confined Aquifer’
Environmental Science and Pollution Research
Clˉ, SO42ˉ and NO3ˉ levels in the Netherlands. Similarly,
Lopez etal. (2015) found M–K test performs reasonably
well while detecting trends in Nitrate levels in the Seine-
Normandy basin, France, with only 11% of the dataset
showing significant trends. Machiwal and Jha (2015)
found significantly increasing (α = 5%) trends in TDS, EC,
Na+ and Fˉ levels in Udaipur district of Rajasthan, India
by applying the M–K test with Sen’s Slope Estimator.
In addition, Niu etal. (2017) demonstrated significant
Fig. 10 (a–g) ITA graphical plots for significantly increasing trends of NO3ˉ Concentrations in the ‘Confined Aquifer’
Environmental Science and Pollution Research
increasing trends in pH, NO3ˉ–N and Clˉ concentrations,
whereas decreasing trends were found in HCO3ˉ levels in
the groundwater of Jianghan plain, China. The SROC test
was conservative and the ITA test was highly sensitive in
detecting trends, whereas the results of M–K and ITA tests
are in agreement in all the blocks.
Sources ofgroundwater contamination
Higher TDS concentrations than the acceptable limit in both
‘leaky confined’ and ‘confined’ aquifers can be attributed to
saline water intrusion from the Bay of Bengal through the
backwater flow in Haldi, Kaliaghai, Kapaleswari, Rasulpur
and Champa Rivers, especially during high tides. Further,
the increased level of TDS in groundwater could be due to
the leaching of fertilizers from agricultural fields and sewage
into the groundwater through the percolation process (Todd
1980; Roscoe Moss Co. 1990). On the other hand, rising
trends of TH levels in both the aquifers is the consequences
of dissolution of limestone, gypsum, and weathering of other
Calcium and Magnesium-bearing formations (Roscoe Moss
Co. 1990; Diggs and Parker 2009). In addition, increasing
trends of Magnesium values in both the aquifers are due to
the existence of laterites, and decomposition of dolomite
and ferromagnesian minerals like amphiboles, pyroxene, oli-
vine and dark-coloured mica (Saha etal. 2019). Increasing
Sodium levels in some blocks have resulted from atmos-
pheric deposition, saline water intrusion, improper sew-
age disposal, salt farming, brackish water fish farming and
weathering of silicate and halite substances (Saha etal.
2019; Kumar etal. 2020). Furthermore, increasing trends
of Iron in both the aquifers can be attributed to geogenic pro-
cess, anthropogenic activities such as excessive groundwater
abstraction from deeper aquifers and presence of laterites
(Ityel 2011; Kumar etal. 2017, 2020). On the other hand,
significant rising trends of Bicarbonate levels in some blocks
could be due to the dissolution of calcite and dolomite, as
well as weathering of silicate minerals (Roscoe Moss Co.
1990; Gastmans etal. 2010). In addition, increasing trend
of Chloride level in the Contai-III block is due to seawater
intrusion, excessive groundwater withdrawal, salt farm-
ing, saltwater fish farming, and presence of halite/sylvite
substances and rock salts (Karanth 1987; Roscoe Moss Co.
1990; Saha etal. 2019).
Moreover, rise in Nitrate levels in some blocks can be
attributed to geogenic development, leaching of fertilizers,
burning of fossil fuel, improper sewage disposal and landfill
(Roscoe Moss Co. 1990; Rahman etal. 2021). On the other
hand, higher Potassium levels than the permissible limits
(12mg/L) for drinking are found in the ‘confined aquifer’
of some blocks possibly due to the chemical breakdown
of sylvite and silicates, clay minerals, as well as excessive
fertilizer/manure application and decomposition of animal
or other wastes (Roscoe Moss Co. 1990; Saha etal. 2019;
Kumar etal. 2020). In a similar study, Vousoughi etal.
(2013) showed anthropogenic activities are responsible for
significantly decreasing groundwater levels and rising con-
centrations of various cations and anions in Ardabil plain,
Iran. Machiwal and Jha (2015) found that injudicious anthro-
pogenic activities significantly increasing TDS and EC lev-
els, whereas geogenic processes are controlling the rise of
Na+ and Fˉ levels in the groundwater of Udaipur district in
Rajasthan, India. Similarly, Niu etal. (2017) demonstrated
that high concentrations of Fe2+, Clˉ and SO42ˉ in ground-
water have resulted from mineral weathering and industrial
effluents, whereas large spatial variability of Clˉ, SO42ˉ and
NO3ˉ–N point towards human-induced pressures in South
Korea. Ducci etal. (2019) demonstrated that agricultural
activities and urban settlements are the primary reasons for
increasing Nitrate trends in Campania, Italy.
Table 4 Results of trend reversal analysis for the Leaky Confined Aquifer
* : Groundwater-quality parameter concentration has already exceeded the permissible limit for drinking. Trend reversal is urgently needed
Groundwater-
Quality Param-
eter
Block (Time to Trend Reversal from 2021)
1. TDS (mg/L) Contai-III (8years); Egra-I (> 15years); Panskura-I (> 15years)
2. TH (mg/L) Contai-III (8years); Dantan-I (> 15years); Mohanpur (> 15years); Sabang (> 15years); Sankrail (> 15years)
3. Mg2+ (mg/L) Dantan-I (> 15years); Dantan-II (> 15years); Debra (> 15years); Kharagpur-I (> 15years); Narayangarh (> 15years);
Pingla (> 15years); Sabang (> 15years)
4. Na+ (mg/L) Debra (> 15years); Pingla (> 15years); Sabang (> 15years)
5. Fe2+ (mg/L) Dantan-II *; Keshiary *; Khejuri-II (8years); Narayangarh *; Ramnagar-I (3years)
6. HCO3ˉ (mg/L) Debra (> 15years); Egra-I (> 15years); Egra-II (> 15years); Kharagpur-I (> 15years); Moyna (14years); Panskura-I
(8years); Patashpur-I (> 15years); Patashpur-II (> 15years)
7. Clˉ (mg/L) Contai-III (10years)
8. NO3ˉ (mg/L) Dantan-I (> 15years); Debra (> 15years); Keshiary (> 15years); Kharagpur-I (13years); Sabang (> 15years); Sankrail
(13years)
Environmental Science and Pollution Research
Results oftrend reversal analysis
The trend reversal analysis results for the groundwater-qual-
ity parameters in ‘leaky confined’ and ‘confined’ aquifers are
illustrated in Table4 and Table5, respectively.
Leaky confined aquifer
It is evident from Table4 that TDS concentration will sur-
pass 75% of the permissible limit (i.e., 1500mg/L) in the
‘leaky confined aquifer’ of the Contai-III block in 8years
from 2021, whereas it will take > 15 years to exceed the
same in Egra-I and Panskura-I blocks. On the other hand,
TH level in the ‘leaky confined aquifer’ of the Contai-III
block will surpass 75% of the permissible limit (450mg/L)
within 8years from 2021, whereas it will take > 15years to
exceed the same for other four blocks. Results indicate that
both Magnesium (7 blocks) and Sodium concentrations (3
blocks) in different blocks will need > 15years from 2021
to exceed 75% of permissible limits (i.e., 75mg/L and
150mg/L, respectively). Furthermore, it was found that Iron
concentrations in the ‘leaky confined aquifer’ of Dantan-II,
Keshiary and Narayangarh have already exceeded 75% of
the permissible limit (i.e., 0.75mg/L). Therefore, sustain-
able groundwater restoration and management actions are
urgently needed in these three blocks to reduce Iron concen-
trations to safer drinking levels (acceptable limits). However,
the Iron levels are likely to surpass 0.75mg/L in Khejuri-
II and Ramnagar-I within 8years and 3years from 2021,
respectively. Except for Moyna (14years) and Panskura-I
(8years), Bicarbonate concentrations in the ‘leaky confined
aquifer’ of the other six blocks will take > 15years to exceed
75% of the permissible limit (i.e., 450mg/L) from 2021.
Results indicate that the Chloride level will surpass 75% of
the permissible limit (750mg/L) within 10years from 2021
in the Contai-III block. Results further show that except
for Kharagpur-I (13years) and Sankrail (13years), Nitrate
concentrations in the other four blocks will take > 15years
to exceed 75% of the permissible limit (i.e., 33.75mg/L).
In a more or less similar study, Mendizabal etal. (2012)
found that TH, HCO3ˉ, Clˉ and SO42ˉ concentrations show
the trend reversal phenomena (increasing to decreasing) in
the Netherlands.
Confined aquifer
It is apparent from Table5 that TDS concentration will sur-
pass 75% of the permissible limit (i.e., 1500mg/L) in the
‘confined aquifer’ of Contai-III block in 9years from 2021,
whereas it will take > 15years to exceed the same in Jaleswar
block. On the other hand, TH level in the ‘confined aquifer’
of the Contai-III block has already exceeded 75% of the per-
missible limit (450mg/L), whereas it will take > 15years to
surpass the same in the other five blocks. Therefore, a trend
reversal is urgently needed in the Contai-III block to reduce
TH levels with efficient groundwater restoration and man-
agement plans. Results show that except for Bhagabanpur-I
(15years), Egra-II (8years), Moyna (13years), Patashpur-
I (15years) and Ramnagar-II (1year), Magnesium con-
centrations in Patashpur-II and Ramnagar-I blocks will
take > 15 years from 2021 to exceed 75% of permissible
limit (i.e., 75mg/L). It was found that the Sodium level in
the ‘confined aquifer’ of the Nandigram-II block has already
exceeded 75% of the permissible limit (i.e., 150mg/L). In
Table 5 Results of trend reversal analysis for the Confined Aquifer
* : Groundwater-quality parameter concentration has already exceeded the permissible limit for drinking. Trend reversal is urgently needed
Groundwater-
Quality Param-
eter
Block (Time to Trend Reversal from 2021)
1. TDS (mg/L) Contai-III (9years); Jaleswar (> 15years)
2. TH (mg/L) Contai-III *; Jaleswar (> 15years); Kamarda (> 15years); Khejuri-II (> 15years); Ramnagar-I (> 15years); Ramna-
gar-II (> 15years)
3. Mg2+ (mg/L) Bhagabanpur-I (15years); Egra-II (8years); Moyna (13years); Patashpur-I (15years); Patashpur-II (> 15years);
Ramnagar-I (> 15years); Ramnagar-II (1year)
4. Na+ (mg/L) Bhagabanpur-I (14years); Deshopran (11years); Khejuri-II (4years); Nandigram-I (4years); Nandigram-II *;
Ramnagar-I (5years)
5. Fe2+ (mg/L) Contai-III (2years); Deshopran (4years); Khejuri-I (5years); Moyna *; Nandigram-II (2years); Panskura-I *; Patash-
pur-I *; Ramnagar-II (3.5months)
6. HCO3ˉ (mg/L) Bhagabanpur-I (15years); Bhagabanpur-II (> 15years); Chandipur (3.5months); Contai-I (15years); Deshopran
(6years); Egra-I (> 15years); Egra-II (> 15years); Khejuri-I (8years); Khejuri-II (10years); Moyna (> 15years);
Nandigram-II (4years); Patashpur-II (> 15years); Ramnagar-I (> 15years); Ramnagar-II (> 15years)
7. Clˉ (mg/L) Contai-III (> 15years)
8. NO3ˉ (mg/L) Bhagabanpur-I (14years); Contai-III (11years); Deshopran (11years); Egra-I (15years); Egra-II (15years); Khejuri-II
(8years); Nandigram-I (3years); Patashpur-I (15years); Ramnagar-I (12years)
Environmental Science and Pollution Research
contrast, it will take 14years, 11years, 4years, 4years and
5years to surpass the same in Bhagabanpur-I, Deshopran,
Khejuri-II, Nandigram-I and Ramnagar-I, respectively. Fur-
thermore, results indicate that Iron concentrations in Moyna,
Panskura-I and Patashpur-I blocks have already exceeded
75% of the permissible limit (i.e., 0.75mg/L). Therefore,
sustainable groundwater restoration and management plans
are urgently needed to be implemented in these three blocks
to lower the Iron levels to safer limits for human consump-
tion. However, the Iron levels are likely to exceed 0.75mg/L
in Contai-III, Deshopran, Khejuri-I, Nandigram-II and
Ramnagar-II within 2years, 4years, 5years, 2years and
3.5months from 2021, respectively. It was found that except
Bhagabanpur-I (15years), Chandipur (3.5months), Con-
tai-I (15years), Deshopran (6years), Khejuri-I (8years),
Khejuri-II (10years) and Nandigram-II (4years), Bicarbo-
nate concentrations in the ‘confined aquifer’ of other seven
blocks will take > 15years to surpass 75% of permissible
limit (i.e., 450mg/L) from 2021. Results indicate that it
will take > 15years from 2021 for the Chloride level in the
Contai-III block to exceed 75% of the permissible limit
(750mg/L). In addition, results show that Nitrate concentra-
tions in the ‘confined aquifer’ of 9 blocks will surpass 75%
of the permissible limit (i.e., 33.75mg/L) within 3–15years
from 2021. In a recent study, Frollini etal. (2021) showed
that theTwo-SectionMann–Kendall (2SM-K) test performs
better than the Pettitt test for trend reversal analysis in Pia-
cenza, Italy.
Based on the above results, it is suggested that there is an
urgent need to seriously consider the groundwater contami-
nation problem in the study region and other coastal zones
of the country. To avoid the further deterioration of ground-
water quality in the study region, the concerned regulatory
agencies must take necessary actions to urgently revert the
trends of TDS, TH, Mg2+, Na+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ
parameters of the ‘leaky confined’ and ‘confined’ aquifer
systems to safer levels (within acceptable limits) for drink-
ing. Any delay in the action may lead to a grave situation
where it will be next to impossible to bring the groundwater
contamination problem to normalcy.
Conclusions andrecommendations
The present study was carried out in the coastal aquifers
of West Bengal, eastern India, with a focus on the spatial
variability of groundwater quality, assessment of the
decadal (2012–2021) trends in critical groundwater-
quality parameters along with the identification of possible
contamination sources. Pre-monsoon groundwater-quality
data of ten years (2012–2021) for the ‘leaky confined’
and ‘confined’ aquifers were used in this study. The
characteristics and spatial variability of groundwater-quality
parameters were analyzed using MS Excel and ArcGIS
softwares. Trend analysis was performed by using three
non-parametric statistical trend tests, viz., Mann–Kendall
(M–K) test with Sen’s Slope Estimator, Spearman Rank
Order Correlation (SROC) and Innovative Trend Analysis
(ITA) tests using R-program and MS Excel. Additionally, the
trend reversal assessment was carried out to predict the time
period (with reference to 2021) when the concentrations
of groundwater-quality parameters will exceed 75%
of the permissible limits for drinking (EU 2006). The
novelty of this study lies in the fact that it demonstrates a
comprehensive investigation of groundwater quality in the
multi-aquifer systems of a coastal basin of eastern India.
This study is the first of its kind in the coastal regions of
India in general and eastern India in particular.
Based on the findings of this present study, the following
conclusions are drawn:
• Among the fourteen groundwater-quality parameters
analyzed in this study, ten parameters (TDS, EC, TH,
Mg2+, Na+, K+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ) exceed their
acceptable limits for drinking in the ‘leaky confined’
aquifer, whereas eleven parameters (TDS, EC, TH, pH,
Mg2+, Na+, K+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ) exceed their
acceptable limits for drinking in the ‘confined aquifer’ of
the study area.
• The groundwater mineralization of both ‘leaky confined’
and ‘confined’ aquifer systems was found primarily due
to Chlorides and/or halite/sylvite, and the cations (Mg2+
and Na+) originated from sedimentary rocks (limestone
or dolomite). In addition, weak negative correlations
between rainfall and groundwater elevation for both the
aquifers indicate poor rainfall recharge into the aquifers.
Therefore, the reduction in pumping and the augmen-
tation of groundwater resource using suitable artificial
recharge methods are recommended.
• The concentrations of TDS (slope = –63.70 to
58.65mg/L/year) and Na+ (slope = –5.69 to 4.39mg/L/
year) show significant decreasing trends in some
blocks, whereas TH (slope = –5.50 to 20.60 mg/L/
year), Mg2+ (slope = –0.50 to 2.46 mg/L/year), and
Fe2+ (slope = –0.32 to 0.44 mg/L/year) concentra-
tions exhibit significant increasing trends in the ‘leaky
confined aquifer’ system. In contrast, concentrations
of TDS (slope = –63.27 to 28.95mg/L/year) and TH
(slope = –11.89 to 39.07mg/L/year) have significant
decreasing trends in some blocks, and the concentra-
tions of TH, Mg2+ (slope = –1.49 to 4.83mg/L/year), Na+
(slope = –7.14 to 22.96mg/L/year), Fe2+ (slope = –0.23
to 0.15mg/L/year), HCO3ˉ (slope = –8.33 to 20.75mg/L/
year) and NO3ˉ (slope = 0.78 to 3.76mg/L/year) have
significant increasing trends in the ‘confined aquifer’
system.
Environmental Science and Pollution Research
• Out of the three tests used in this study, the results of
M–K and ITA tests were found in agreement in all the
blocks for both the aquifers, while the SROC test identi-
fied trends only in a few blocks. In contrast, the ITA test
was found more sensitive in detecting trends than the
remaining two techniques for both the aquifers.
• The major factors responsible for groundwater dete-
rioration in both the aquifer systems of the study area
are rock-water interaction (weathering), geogenic
processes, mineral dissolution, poor recharge pattern,
imprudent anthropogenic activities, improper sewage
disposal, brackish water fish farming, salt farming and
seawater intrusion.
• The results of trend reversal analysis indicated that
there is an urgent need to initiate suitable remedial
measures for maintaining the desirable levels of TDS,
TH and Clˉ concentrations in the ‘leaky confined aqui-
fer’ of Contai-III block; Fe2+ concentration in Dantan-
II, Keshiary, Khejuri-II, Narayangarh and Ramnagar-I
blocks as well as NO3ˉ concentration in Kharagpur-I
and Sankrail blocks. In addition, it is indispensable to
lower the TDS and TH concentrations in the ‘confined
aquifer’ of Contai-III block, Na+ in 6 blocks, Fe2+ in 8
blocks, and NO3ˉ in 9 blocks to ensure acceptable con-
centrations of these groundwater-quality parameters.
Overall, the outcomes of this research are of utmost
importance for the concerned policymakers, water manag-
ers and other stakeholders. The methodology demonstrated
in this research can be replicated in other coastal areas of
the Indian subcontinent as well as other regions of the globe.
There is also a need for comprehensive assessment of seawa-
ter-intrusion vulnerability/risk under changing climate and
socio-economic conditions in the study area. Furthermore, it
is recommended that a proper network of monitoring wells
for monitoring groundwater condition in three aquifer sys-
tems should be developed in the study area. Groundwater
monitoring should be done regularly (preferably monthly)
in the aquifers using modern monitoring tools/techniques.
These recommendations are of utmost significance for sus-
tainable planning and management of declining groundwater
resources and deteriorating groundwater quality in coastal
regions of India in general and West Bengal in particular.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s11356- 024- 33852-3.
Acknowledgements The first author is highly grateful to the Ministry
of Education (MOE), New Delhi, Government of India, for provid-
ing student fellowship to pursue Ph.D. study. The authors are also
thankful to the Central Ground Water Board (CGWB), Kolkata; the
Groundwater Survey and Investigation (GWS&I), Bhubaneswar; the
India Meteorological Department (IMD), Pune; the Special Relief
Commissioner (SRC), Bhubaneswar; and the Water Resources Inves-
tigation & Development Department (WRIDD), Kolkata for providing
rainfall, groundwater-level, groundwater-quality and other associated
information.
Authors contribution Subhankar Ghosh: Conceptualization, Data
curation, Software, Formal analysis, Writing – Original draft; Madan
Kumar Jha: Conceptualization, Supervision, Project administration,
Writing – Review and Technical Editing.
Funding No funding was provided to carry out this research work.
Data availability The datasets used will be made available by the cor-
responding author upon reasonable request.
Declarations
Ethics approval Not applicable.
Consent to participate Not applicable.
Consent for publication Not applicable.
Competing interest The authors declare no competing interests.
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