Statistical analysis and physicochemical characteristics of groundwater quality parameters: a case study

The assessment of groundwater quality was carried out by taking the shallow wells samples near the bank of River Indus at the downstream Kotri barrage; the study area covers the arid region of Hyderabad, Sindh. The space occupied by the wells was about 1- 2 km used for the quantification of geochemical characteristics of the shallow aquifer that lies on the left side of the river. A total of 13 groundwater samples were collected during pre-monsoon and post-monsoon seasons. All the groundwater samples were examined for the characterisation of physicochemical parameters such as Total Dissolved Solids ranged from 320 mg/l to 4011 mg/l, Total Hardness ranged from 120 mg/l to 1320 mg/l, Chloride ranged from 160 mg/l to 2260 mg/l, Sulphate ranged from 61 mg/l to 777 mg/l, pH ranged from 6.9 to 8.1. The findings of the study demonstrate the presence of high quantity physicochemical parameters at a shallow aquifer in contrast to guidelines values by the World Health Organization (WHO) for drinking water. Besides, the T-value was applied to check the variation in pre- and post-monsoon results between parameters, which found significant for chloride 2.701 with p-value 0.031, for fluoride 3.039 with p-value 0.019 and for iron 2.957 with p-value 0.021


Introduction
Water is a mandatory segment of our life. Pakistan is sanctifying with enough surface water and groundwater resources. The water shortage and the safe water crisis are all around the Globe as well as in developing countries of the World like Pakistan. The growing population and industrialisation in developing countries have an adverse effect on the available natural resources due to the mismanagement of natural resources such as water. The freshwater resources of the country are being depleted due to the drainage of untreated domestic and industrial wastewater into the freshwater bodies. Ultimately polluted water is being utilised by the domestic and industrial needs, which require prior treatment before its use. The proper treatment of polluted water sources for domestic and industrial purposes is very much expensive for developing countries. Due to the economic conditions of the country, there is a need for an economical and readily available source for domestic and industrial purposes.
Groundwater and its sustainability depend upon its quality that is used for drinking, irrigation, as well as industrial purposes [1]. Groundwater contamination and pollution are followed by four significant origins, such as agricultural, industrial, domestic, and overexploitation of groundwater, which causes hazardous health concern issues [2]. Because of the far-reaching pollution on the water surface, the quality of groundwater becomes depreciates. Along with this, the debris of wastewater through leachate and bores that are the products of unscientific disposal of solid wastes are usually contaminating and polluting the groundwater [3]. Nearly all the developed cities of the country are facing safe wastewater management. Up to now, there is no suitable platform developed where the waste debris could be handled smoothly and safely disposed of carefully. The Hyderabad city is the second-largest city of Sindh province, which is also facing the same issue, where the wastewater debris is being disposed of employing sewerage through the pumping system into the areas of Pinyari or Phuleli canals without any safety concern [4]. Several newspapers also reported the toxic wastewater effects on the health of plants, humans, animals, respectively. The Daily Dawn newspaper has highlighted the highly toxic wastes that come from slaughterhouses, plastic factories, as well as illegal cattle pens, were being disposed-off into the Phuleli canal, and the families lived in Tando Muhammad Khan, and Badin districts are duty-bound to use this polluted water for drinking purpose. Therefore, millions of people's health are affected by the usage of contaminated Phuleli canal water. There are various sources of groundwater contamination, such as sewage and industrial wastewater, and the seepage of agrochemicals. The industrial wastewater sewerage and seepage from unlined sewage are highly useful to contaminate the groundwater quality. Naturally, groundwater is richly filled by surface water from rivers, streams, and precipitation. Groundwater pollution is nearly negligible as compared to surface water, but once it gets, polluted it becomes problematic for a longer time [5]. In Sindh and Punjab province, groundwater salinity is interrelated to the morphology of the river [6].
Comparatively, groundwater sources are considered safe from the open drainage but depend on the geological setting of the area, where alluvium keeps the fresh water, and the geochemical deposits produce saline water. The groundwater in the study area is being used for domestic purposes without further treatment.
The drinking water shortage versus the water demand and water quality issues are discussed and reported in Pakistan by various authors through scientific studies. With the growing demand for water for the domestic, industrial, and agricultural sectors, it would be necessary to consider each watershed as a water management unit for the present and future. Water quality and health-related issues reported by the (WWF 2007) that the water table in Sindh and Baluchistan is decreased due to the over exploration of groundwater for drinking. A study from Pakistan reported that groundwater utilisation had increased 75% in Sindh and 17% in Punjab due to the population and industrial growth, including agricultural activities; both provinces are suffering from saline groundwater. In many cases, during the post-monsoon season's groundwater quality is improved as compared to the pre-monsoon seasons of the year [7,8].
This study was conducted on the water quality variations during the summer and winter seasons of the year, where perennial canal water and the bank filtered water quality was examined through the installation of the model well (abstraction well) at variable distances and depth from the canal (Phullali, Pinyari, and Lined Channel) banks at Hyderabad city. The results revealed that during the summer due to the high flow of the river water in the canals has a positive effect on groundwater dilution and has shown the lower concentrations of the geochemical in the abstracted water from the model wells [9]. Moreover, the results were compared and have shown an increase in chemical concentrations as the depth and distance was increased. Moreover, J. Nouri conducted a study in the southern part of Iran to check the water quality by analysing the heavy metals concentration in the groundwater. Because, in the rural and urban southern part of Iran, the groundwater is the only appropriate as well as a widely used source of drinking water [10].
Various water-borne diseases are associated with contaminated drinking water use [11]. World Health Organization (WHO) reports that due to water-borne diseases such as diarrhoea, cholera, dysentery, hepatitis, cancer, and other chronic diseases, mostly children under age five are more affected in developing countries due to the polluted drinking water. They were keeping the consideration of water quality characteristics for drinking in the study area where almost groundwater is saline as compared to the WHO guideline values [9].
The study area keeps almost warmer prolong in the months of the year, low or no rainfall, low or no flow at the downstream Kotri barrage a shown in Figure 1. The river bed looks dry except for a few months from July to October. The recharge of adjacent aquifer depends on the flow of surface water and its continuity, in arid regions low rainfall keeps the surface soil dry, which sick water rapidly, the rainwater and pond water are only the sources of recharging the aquifer, and the rate of recharging also depends on the aquifer overlying material (soil characteristics). On the other hand, the low water volume at the downstream Kotri barrage enhances the biological activities and the concentrations of the physiochemical characteristics of river water. The river water in the study area is being used for domestic animals such as cattle forms (buffalos), goats, dogs, and other animals. No river water management, protection measures are applied to protect the natural resource of water from pollution, which has been used for the life survival of the downstream users. Due to low dilution and the increasing pollution load, river water does not keep its fitness as compared to the upstream of the Kotri barrage. The overall objective of this study was to assess the physicochemical characteristics of groundwater and possible changes during pre-and post-monsoon seasons of the year.
The overall objective of this study was to assess the physicochemical characteristics of groundwater and possible changes during pre-and post-monsoon seasons of the year as well as to make a statistical analysis of the river of selected area viz; Mean, Minimum, Maximum, and Standard Deviation of the polluted parameters, and more importantly finding the Correlation and Regression equations between the parameters. [Highly significantly correlated water quality parameters (0.1 <r <0.8)].

Study area and description
The left side of the riverbank at downstream Kotri barrage was selected for the examination of the groundwater quality, the sampling was started from the railway bridges connecting Hyderabad and Kotri city. The covered area of study was approximately 5 kilometres from the starting point of the sampling well. The study area covered and the location and distance of the sampling point along the Indus River at the downstream Kotri barrage is shown in Figures 1 and 2.

Samples collections
The groundwater samples were collected from the selected well points, the frequency of sampling and analysis were made after each month for three months in pre-and post-monsoon seasons of the year. The nine locations of the groundwater wells were sampled and analysed for a period of a one-year study. The hand pumps and electric pumps were run for one minute to flush the stagnant water in the pipes. The grab water samples were collected in prewashed plastic and sterilised glass bottles from the wells and three grab samples were collected from different points of the river to make a composite sample of the river at downstream Kotri barrage Hyderabad. The glass bottles were used for the total coliform analysis of the collected samples. The temperature, turbidity, and dissolved oxygen parameters were monitored on the site, then samples were transferred within one hour after collection for further analysis to the Institute of Environmental Engineering & Management, MUET, Jamshoro. The distances, water sources, and locations are given in Table 1.

Experimental work
All the water samples were analysed by following the standard methods of water and wastewater examination (AWWA) and the Environmental Protection Agency of the United States (US-EPA). Whereas TDS was determined by using a Conductivity/  TDS metre (44,600-00), pH was tested by digital pH metre (WSTL007), Turbidity was analysed by Turbidity metre (WSTL002), Total Hardness by EDTA Titrimetric method, Chloride by APHA 4500B (Argentometric Method), Nitrate by using the cadmium reduction method, Fluoride by using SPADNS red zirconium dye and Sulphate by using barium and stabilising agent the turbidity method through UV/Visible Spectrophotometer. Total Coliforms were analysed by using Membrane Filtration Count (MFC) and Colony Forming Units (CFU/100 ml) were counted, whereas EMB agar was used for the colonies' development and the colonies were counted by using the magnifying glass.

Results and discussion
The average value of three months is discussed here for the water quality characteristics of the groundwater during pre-and post-monsoon seasons of the year of study. The water quality parameters and their concentrations for water source fitness are most important for drinking purposes. In this study drinking, water quality parameters were selected such as Total Dissolved Solids, Total Hardness, Chloride, Sulphate, pH, Turbidity, Fluoride, Nitrate, Iron, Manganese, Lead, and Total Coliforms were observed and shown in the tables below. The findings show the presence of high quantity physicochemical parameters at a shallow aquifer in contrast to guidelines values by the World Health Organization (WHO) for drinking water. The variation in parameters of groundwater quality could be due to ecological variation. However, the variation in the concentration of heavy metals was due to the use of different raw materials and variation of production level.

Total dissolved solids (TDS)
The TDS values of the well's water quality are quite variable and varying from 373 mg/l to 4913 mg/l during pre-monsoon and 320 mg/l to 4011 mg/l during post-monsoon. The TDS concentrations of the well water samples were found relatively lower during postmonsoon compared to pre-monsoon season, except for two wells at 170 m and 320 m from the riverbank. The Comparisons of pre-and post-monsoon and river water samples are shown in Figures 3 and 4. Moreover, well water samples at a distance of 150 m and 320 m from riverbanks were found fit for drinking according to WHO guidelines (i.e. TDS lower than 1000 mg/l). During post-monsoon, the sample at a distance of 320 m and 170 m have shown an increase in TDS concentration. The pollution sources such as agricultural, domestic waste, dumping of solid waste, and interaction of rock water may increase the TDS value of water [12]. The decrease in TDS values during the post-monsoon season maybe because of the low recharging and dilution of groundwater, two samples have shown higher TDS values during post-monsoon as compared to pre-monsoon season. The variation in TDS may be due to different soil characteristics and recharging water quality. TDS concentration was high due to the presence of bicarbonates, carbonates, sulphates, and chlorides of calcium [13,14] and TDS value of 500 mg/L is the desirable limit and water containing more than 500 mg/TDS causes gastrointestinal irritation [15]. The high value of TDS influences the taste, hardness, and corrosive property of the water [16][17][18]

Total hardness
The hardness values of groundwater varying from 120 mg/l to 1320 mg/l during premonsoon and 110 mg/l to 1476 mg/l in the post-monsoon season. The Hardness concentration of water samples was found relatively lower during post-monsoon compared to pre-monsoon expect two samples at a distance of 170 m and 320 m this maybe because of the increase of bicarbonate and carbonate salts in the post-monsoon, the results are compared to the study by [19]. The comparisons of pre-and post-monsoon and river water samples are shown in Figures 5 and 6.
Further, it was also observed that the water at a distance of 150 m, 250 m, and 320 m from the river bank was fit for drinking in pre-monsoon and post-monsoon seasons in the view of WHO guidelines for Pakistan i.e. hardness lower than 500 mg/l. Groundwater exceeding the limit of 300 mg/L is considered to be very hard [20].

Chloride
The concentration of chloride in the groundwater sample is ranging from 180 mg/l to 263 mg/l in pre-monsoon; however, 160 mg/l to 2260 mg/l was analysed in the postmonsoon season. However, it was also showed that the concentration of chloride in river and groundwater samples is optimally low in post-monsoon in contrast to pre-monsoon season except for the sample that lies at the distance of 320 m. The difference between pre-and post-monsoon and river water samples can be shown in Figures 7 and 8. Moreover, it was also found that the river water in pre-monsoon and groundwater samples in both pre-monsoon and post-monsoon measured high chloride value than the observed WHO values, i.e. 250 mg/l except for the samples visualised at the distances of 150 m and 320 m with the observed outcomes showed the desired limits. The concentration of chlorides can lead to sea intrusion [18].

Sulphate
The sulphate values for maximum and minimum water samples in pre-monsoon were determined 61 mg. l to 777 mg/l while 33 mg/l to 656 mg/l in post-monsoon season, respectively. After analysis, it was monitored that sulphate values observed in premonsoon were shown to be relatively high in comparison to the presence of Sulphate in water samples that were analysed in the post-monsoon. The variation in the analysed value was obtained in river water and the groundwater samples observed at the difference in the distance from the river except for the obtained samples at 170 m, 180 m, and 320 m, respectively. After the comprehensive analysis, it was found that dilution and infiltration can alter the presence of Sulphate in the groundwater sample. The difference in pre-and post-monsoon, as well as river water samples, are demonstrated in Figures 9  and 10. Due to the evaporation and evapotranspiration, the sulphate value exceeds the surface zone in the pre-monsoon season, while in the post-monsoon season in the rainwater salts are mixed and leached into the groundwater [21].
Moreover, it was also evaluated that samples were taken from groundwater at the respective distance of 150 m, 210 m, 250 m, and 350 m, and samples obtained from river water in pre-and post-monsoon season, likely to be suitable for drinking purpose according to the guidelines of WHO, i.e. 400 mg/l. The concentration of Sulphate can initiate respiratory problems for the people with the counteraction of cathartic [22].

pH
In this study, pH values of groundwater were analysed that were measured about 6.9 to 8.1 for pre-monsoon and 7.11 to 8.1 for post-monsoon, respectively. The outcomes for the difference in measured values revealed that pH value in the post-monsoon was lower, in contrast to pre-monsoon except for samples that were measured at a distance of 170, 180, and 250 mm, respectively. The comparison between the pre-and post-monsoon, as well as river water samples, is presented in Figures S1 and S2. Moreover, it was also detected that for all the groundwater samples, the pH values were alkaline and varies within the limits of (6.5 to 8.5 pH) as per the limits of the guidelines of WHO.

Turbidity
Turbidity is one of the factors that affect groundwater quality. Turbidity of groundwater samples measured in the post-monsoon season that was ranging from 0.66 to 43.4 NTU, respectively. Furthermore, it was also evaluated that the Turbidity of groundwater and river water samples for post-monsoon season measured higher as compared to the premonsoon season except for the samples that lie at a distance ranging from 250 m and 320 m respectively. It was also comprehensively figuring out that the increasing effect of Turbidity in post-monsoon is due to the presence of clay particles, and dissolved and suspended mud in groundwater samples [23]. Comparison between the pre-and postmonsoon seasons, as well as river water samples, are summarised in Figures S3 and S4.
Furthermore, it was also monitored that well water samples that were present at the distance of 40, 150, 180, 200, and 320 m respectively were suitable for drinking purpose according to the guidelines of WHO limits that accounted as (Turbidity lower than 5 NTU) in the pre-monsoon season, however, for the post-monsoon season the analysed samples lie at a respective distance of 40 and 320 m were acceptable for drinking purpose as per the guidelines given by WHO, and the remaining measured samples were not suitable for drinking purpose.

Fluoride
The Fluoride values of wells water quality are quite variable and varying from 0.12 mg/l to 1.17 mg/l during pre-monsoon and 0.12 mg/l to 0.74 mg/l during post-monsoon. The fluoride concentrations of the well water samples were found relatively lower during postmonsoon compared to the pre-monsoon season. The concentration of fluoride in groundwater is due to leachate, irrigation for the long term, semiarid climate [12]. Another study   [24]. Moreover, Jafar Nouri investigated the fluoride concentrations ranged from 0.12 to 2.17 mg/l in shush aquifer of Iran. This study has shown a positive and significant correlation between fluoride and alkalinity and a negative correlation between fluoride and pH of the groundwater [25].
The Comparisons of pre-and post-monsoon and river water samples are shown in Figures S5 and S6. Moreover, it was also observed in the experimental work that all samples of water were within desired WHO limits (i.e. 0.7 to 1.2 mg/l) in pre-and postmonsoon.

Nitrate
The nitrate values of wells water quality varying from 0.9 mg/l to 17 mg/l during premonsoon and 0.8 mg/l to 11 mg/l during post-monsoon. The nitrate concentrations of the well water samples were found relatively lower during post-monsoon compared to premonsoon season, except for two wells at 150 m, 180 m, and 320 m from the riverbank. Internally, the sewage infiltration under the ground surface and agricultural drainage consisting of fertiliser might be the actual reason for mixing nitrogen in groundwater [7]. The comparison between the pre-and post-monsoon and river eater samples is presented in Figures S7 and S8.
Additionally, it was evaluated that all the measured values of the analysed samples were lower than the adequate limit, i.e. 45 mg/l, and thus suitable and fit for drinking purposes.

Iron (Fe)
The iron of groundwater samples was ranging from 0.402 mg/L to 0.738 mg/L in premonsoon and 0.308 mg/l to 0.596 mg/l in post-monsoon. The values are shown in Figures  S9 and S10. The iron values of river water are higher than the groundwater obtained from wells at different locations in both pre-and post-monsoon seasons. However, it was also observed that the values of iron in the post-monsoon relatively lower as compared to the post-monsoon. It was found that the Fe content in groundwater of the study area is natural (i.e. Rocks and soils) as well as human-made sources such as sewage, solid waste disposal sites. The high iron in groundwater is related to the degree of susceptibility of weathering of rocks and lateralisation of overburden. Concentrations of iron in all collected samples are exceeding the desired limits of WHO guidelines, i.e. 0.3 mg/l.

Manganese (Mn)
The presence of Mn ions in groundwater samples was found in pre-monsoon within the range from 0.402 mg/l to 0.738 mg/l whereas, for post-monsoon these samples showed the observed values within the range of 0.308 mg/l to 0.596 mg/l as presented in Figures S11 and S12. The presence of Mn ions in the pre-monsoon season was shown to be higher in contrast to groundwater samples. At the same time, the measured values for Mn ions in post-monsoon were shown to be lower than the analysed groundwater samples.
Furthermore, the higher concentration of Mn ions was observed in pre-monsoon as compared to post-monsoon by the exception of water sample L4 that was found at the distance of 180 m. Comprehensively all the desired samples were fit for the acceptable limits, i.e. 0.5 mg/l in comparison to the river water samples and the samples L1 and L8 that were found at the respective distance of 40 and 320 m in pre-monsoon while the sample L1 in post-monsoon lies at a distance of 40 m does not fit for permissible limit. The presence of Mn ions in groundwater can varies seasonally with the change in position and depth of aquifer of the well and geological area, respectively. Naturally occurring metals in groundwater that consist of a little oxygen Metals naturally occur in groundwater, which has a little bit of oxygen, where the flow of groundwater is slow, where the flow of groundwater through soils rich in organic matter and deeper wells.

Lead (Pb)
In groundwater samples, the concentration of Pb varies in pre-monsoon season within the range of 0.4 µg/L to 13.5 µg/L whereas 0.2 µg/L to 9.1 µg/l in the post-monsoon season as shown in Figures S13 and S14. During pre-monsoon and post-monsoon season, the river water samples govern a lower concentration of Pb in contrast to the groundwater samples except for water samples L2 and L4 lie at the distance of 150 and 180 m, respectively.
Furthermore, it was also analysed that the concentration of Pb was higher in premonsoon and post-monsoon for all the observed water samples except for the R1 sample that lies at the distance of 40 m. Hence, for all the analysed samples, the concentration of Pb was found to be lower as compared to the guideline limit of WHO, except for sample L3 that lies at the distance of 170 m in the pre-monsoon and post-monsoon seasons from the riverbank side. In the groundwater, the presence of Pb metal chiefly occurred due to the wastewater leaching from the industries, rusting of buried metals, and percolation of irrigation water, respectively reported by [26].

Total coliform
Total coliform (TC) of the analysed groundwater sample was analysed, and the result showed the observed pre-monsoon and post-monsoon values ranging from OCFU/100 to 300CFU/100, respectively. However, it was also observed that the concentration of total coliform was efficiently higher in the post-monsoon season in contrast to the premonsoon season. Figures S15 and S16 represent the comparison between the pre-and post-monsoon season as well as river water samples.
It was also showed that the measured TC values were found to be higher in postmonsoon as compared to the pre-monsoon for all the analysed samples from the left side of the riverbank. In the pre-monsoon season, the decreasing value of TC affects the activity of microorganisms and thus caused to slow down the biological activities at the inappropriate condition and low humidity for bacterial growth such as temperature, nutrient, pH, DO, and other biological factors respectively. Furthermore, the mixture of different hazardous biological contaminants in drinking water may cause different infectious diseases such as cholera, typhoid, dysentery, etc. Consequently, it was also visualised that only one sample lies at a distance of 250 m and 350 m found in both seasons was acceptable to follow the permissible limit governed by WHO guidelines and all the other remaining samples present in both seasons were not acceptable to fit for the desirable guidelines by WHO such as OCFU/100. The presence of infectious pathogens in water may be due to the increasing content of TC in groundwater reported by [27].
The minimum and maximum concentration of different physicochemical parameters of water quality constituents such as Total Dissolved Solids (TDS), Total Hardness (TH), Chloride (Cl-), Sulphate (SO4), pH, Turbidity, Fluoride (F-), Nitrate (NO 3 -), Iron (Fe), Manganese (Mn), Lead (Pb) and Total Coliform (TC) for groundwater are given in Table 2 along with mean and standard deviations and t-test for each parameter. It is seen from the results that the Mean and Standard deviation of TDS, Chloride, Sulphate, Fluoride, Nitrate, and Iron were high in the pre-monsoon season as compared to the post-monsoon season. Whereas, only Total Hardness shows a high mean and Standard deviation in the post-monsoon season as opposed to the pre-monsoon season. However, pH and Turbidity show approximately the same values of mean and standard deviation in both seasons.
Abbas Abbasnia presented a study of Sistan city, Iran reported that the maximum value of TDS was found 2400 and the minimum value was 502.4 with a standard deviation of 529.34 and a mean of 1282.69. However, the maximum pH was noted 8.31 and the minimum pH was 7.15 with a standard deviation of 0.32 and mean of 7.77, respectively. Moreover, the maximum value of total hardness was found 1230.80 and the minimum value was 157.24 with a standard deviation of 299.65 and a mean of 519.22. However, the maximum chloride was noted 751, and the minimum value of 78 with a standard deviation of 163.96 and mean of 304.6, respectively. Sulphate shows a maximum value of 825 with a minimum value of 50 and the standard deviation was noted 244.12 with a mean of 381.13. Also, the maximum value of Nitrate was found at 87.5 and the minimum value was found 2 with a standard deviation of 12.88 and mean of 12.39. However, Fluoride shows a maximum value of 1.53 with a minimum value of 0.12, and the standard deviation was noted 0.29 with a mean of 0.56, respectively [28].
The data of groundwater quality of Sunamganj District Bangladesh presenting the minimum-maximum concentration, mean, and standard deviation of the same parameters [29]. Gajendran reported that the mean value of the TDS of all water samples was 927.58 mg/l which shows that the TDS of the basin water quality is high compared with the WHO standard value [30].
Also, T-value and P-value were not significant for TDS, Total Hardness, Sulphate, pH, Turbidity, Nitrate, Lead, and Total Coliform. However, for Chloride, Fluoride, Iron, and Manganese it was significant. The t-value for Chloride was 2.701 with a p-value of 0.031. For Fluoride, the t-value was 3.039 with a p-value of 0.019. Moreover, the t-value for Iron was 2.957 with a p-value of 0.021. And for Manganese, the t-value for Iron was 2.775 with a p-value of 0.027.

Correlation coefficient and linear regression
The correlation coefficient [PEARSON] (r) has been calculated between each pair of water quality parameters by using SPSS software for the experimental data. Let X and Y be the two variables, then the correlation 'r' between the variable X and Y is given by: ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi P If the values of the correlation coefficient 'r' between two variables X and Y are fairly large, it implies that these two variables are highly correlated. In such cases, it is fissile to try linear relation in the form: Y = Axe + B.

Correlation analysis
Correlation and regression analysis are useful for interpreting groundwater quality data and relating them to specific hydrogeological processes. These tools are quite useful in characterising and obtaining first-hand information on the groundwater system than actually going through complex methods and procedures. The degree of linear association between any two of the water quality parameters is measured by the simple correlation coefficient (r). The correlation matrix for different water quality parameters along with the significance level (2 tailed) is shown in Tables 3 and 4.
The results of the statistical analysis which are shown in Table 3 (Pre-Monsoon season) indicated that Total dissolved Solids has a strong positive and highly significant correlation with TH, Cl-, SO 4 2-, weak correlation with Turbidity, F-, NO 3  On an overall basis, it was observed that as the correlations between parameters become weaker it also becomes insignificant and vice versa. K. Ambiga and his teammates represented a study in which they articulating that in the pre-monsoon season, the obtained result of TDS has positively and significantly correlated with the respective EC, Ca, Mg, TH, and Cl − while, Potassium has a weak correlation whereas Nitrate, Chromium, and Iron has negatively correlation co-efficient. The obtained result of total hardness has a significant and positive correlation with Magnesium, Chloride, and Calcium; however, Sulphate has a weak correlation, and Fluoride, Chromium, Iron, Nitrate and Potassium have a negative correlation, respectively. Furthermore, it is comprehensively elaborated that Calcium has a significant positive correlation with Chloride and Mg ions, Sulphate has a weak correlation and Iron, Potassium, Nitrate, Iron, and Chromium have a negative correlation. Consequently, Chloride has positively and significantly correlated with Sodium, Fluoride has a weak correlation, while Chromium and Iron have negatively correlation coefficient values, respectively [31].
Another study by Abbas Abbasnia presented the correlation between ion concentration and physicochemical characteristics of groundwater. The results suggested that water quality could be affected by evaporation as well as seasonal effects. A high positive correlation of above 0.8 was found among different groundwater quality parameters such as calcium and hardness; sulphate and TDS; sulphate and TDS; sulphate and sodium; and chloride and TDS, respectively. Moreover, a high and significant correlation was noticed between sulphate and chloride owing to the anthropological activities as well as soil, natural, and rock materials [32]. The results of the statistical analysis which are shown in Table S1 (Post-Monsoon season) indicated that Total Dissolved Solids has a positive and significant correlation with TH, Cl − , SO 4-, weakly correlated with Turbidity, F − , Mn, Lead, TC, and negatively correlated with pH, NO 3 and Iron. Total Hardness has a positive and significant correlation with Cl − , SO 4 , Lead, weakly correlated with Turbidity, F − , Mn, TC, and negatively correlated with pH, NO3, Iron. Chloride has a positive and significant correlation with SO 4-, weakly correlated with Turbidity, F − , Iron, Mn, Lead, and negatively correlated with pH, NO 3 , and TC. However, Sulphate has weakly correlated with Turbidity, F − , Mn, Lead, TC, and negatively correlated with pH, NO 3 , and Iron. On contrary, pH, Turbidity, Fluoride, Nitrate, Iron, Manganese, and Lead are weakly and negatively correlated with most of the water quality parameters. On an overall basis, it was observed that as the correlations between parameters become weaker it also becomes insignificant and vice versa.
K. Ambiga and his correspondence collectively examined the study regarding postmonsoon, that TDS has a positive and significant correlation coefficient with TH, Mg, Ca, EC, and Cl − whereas iron showed weak correlation and Sulphate, Sodium and Potassium showed negative correlation coefficient values. It is also observed that EC has a significant and positive correlation with Mg, Cl − , Ca, and TH, respectively whereas iron has a weak correlation and Sulphate, Sodium and Potassium have negative correlation values. Moreover, it is also presented that the total hardness has a significant and positive correlation with Fluoride, Calcium, and Magnesium, Sodium has a weak correlation, and Sulphate and Potassium have a negative correlation coefficient, respectively. Furthermore, it also seemed that Calcium has positively and significantly correlated with Fluoride and Mg ions, weakly correlated with Sodium as well as negatively correlated with Sulphate and Potassium, respectively. It is also assumed that nitrate has a positive and significant correlation impact with Iron, Chloride has a weak correlation coefficient whereas Potassium and Sulphate have negative correlation coefficient values, respectively [31].
Sina Dobaradaran and his correspondence collectively presented a study suggesting that sulphate has a positive and significant correlation with fluoride. However, a negative correlation of sulphate was found with pH and Nitrate [33].

Regression analysis
Simple linear regression analysis was performed by using SPSS software by taking TDS as dependent variables and the other parameters as independent variables. The LR model gave a coefficient of determination of R2, for predicting TDS depending on the selected water parameters and the equations for predicting TDS. The results for both Pre and Post Monsoon cases were presented in Tables S2 and S3, respectively. Among all the parameters under consideration, the effects of TH, Cl − , SO 4 , and pH were found significant using a conventional level of significance (0.05). The proportion of explained variation as reported by the adjusted R2 was found to be very high which is ultimately an indication that the fitted regression model was found adequate in explaining the variation in the dependent variable.
On the other hand, the effects of Turbidity, F − , NO 3 , Fe, Mn, Pb, and TC were found insignificant as shown by the t-value and the corresponding p-value (as p-value is greater than 0.05 the level of significance). Also, the values of adjusted R2 were found to be very low (less than 50%) showing that these parameters failed to explain the variation in the dependent variable (TDS). It is interesting to note that the same results were reported in the case of post Monsoon with the exception that pH was also found significant at 0.01 level of significance. Otherwise, the proportion of explained variation was also found in the case of pre-monsoon. In pre-monsoon, the regression model of total hardness presented a maximum value of 0.928% of the observed variability. However, for chloride and sulphate regression model can predict up to 0.972 and 0.986% variability, respectively. On contrary, in post-monsoon, the regression model of total hardness presented a maximum value of 0.952% of the observed variability. Moreover, for chloride and sulphate regression model can predict up to 0.901 and 0.748% variability, respectively. By following the comprehensive study, it was assumed that all the observed independent variables have a significant effect ('t' test was applied for the partial regression co-efficient at the probability level of 5%) concerning the coefficient of the dependent variable. The regression model of nitrate showed that a maximum value of 70.93% obtained variability of nitrate is reported by the same model. Likewise, Na + , Mg 2+ , K + , Ca 2+ have a regression model that can be envisioned up to the variability values of 94.2%, and 97.7%, respectively [34].

Conclusion
The experimental study of groundwater utilising 12 physiochemical parameters of the study area was identified to check water quality for drinking purposes. The finding of this study has shown higher concentrations of geochemical parameters at a shallow aquifer in the selected area as compared to NEQS, and WHO guideline values for drinking water. It is found during the study that pre-and post-monsoon has a different impact on the groundwater quality parameters. For instance, some heavy metals in the water samples collected in pre-monsoon were found lower, while in post-monsoon the ratio of heavy metals in water samples was found higher.
The minimum & maximum values, the mean, and standard deviation of the groundwater quality parameters were calculated. The t-test was applied to check the variation in pre-and post-monsoon results between parameters of groundwater quality, which showed significant results in chloride, fluoride, iron, and manganese. Moreover, results of correlation analysis showed a positively strong, and significant correlation among many of the tested water quality parameters in both pre-and post-monsoon seasons. However, in some parameters, it was observed that as the correlations between parameters become weaker it also becomes insignificant and vice versa The Linear regression models were developed for predicting the concentration of groundwater quality parameters with a 1% and 5% level of significance. It was found that the same results were reported in the case of Post Monsoon (as pre-monsoon) with the exception that pH was found significant at 0.01 level of significance. It is suggested to treat groundwater before drinking and potable uses. Suitable strategies to groundwater recharge, controlled groundwater usage, measures to reduce groundwater pollution, and awareness of the importance of water quality for private bore well users are recommended.