Abstract
A total of 138, samples have been collected in both pre and post monsoon season to understand the seasonal variability in groundwater quality and its suitability for drinking and domestic water supply. The samples were analysed for physical parameters, major ions along with fluoride and uranium. The results were integrated with GIS to represent both seasonal and spatial variations of groundwater quality parameters, drinking groundwater quality index (DGQI) and irrigation groundwater quality index (IGQI). Results show that groundwater is alkaline in nature and largely controlled by the silicate weathering, ion exchange and reverse ion exchange processes. However high nitrate concentration exceeding the WHO guideline suggests the influence of anthropogenic activities on groundwater quality. The average values of the major ions concentrations was found higher in pre monsoon season due to change in the recharge. The DGQI values of 6 samples in pre monsoon and 2 samples in post monsoon season falls under poor water quality. However, individual irrigation indices along with the combine IGQI indicate groundwater is suitable for irrigation in both the seasons. These results along with the seasonal and spatial variability map may help the decision makers in planning for better domestic and irrigation water supply.
HIGHLIGHTS
Silicate weathering and ion exchange controls ionic species in groundwater.
High concentration of nitrate in pre-monsoon season suggests influence of anthropogenic activities on groundwater.
Relatively high ion concentrations are found in pre-monsoon season.
Groundwater is safe in terms of fluoride and uranium.
Both DGQI and IGQI suggests that groundwater is safe for drinking and domestic water supply.
INTRODUCTION
Groundwater resources play a significant role in economic development and improvement of human health. It is considered as safer in terms of microbial contamination compare to surface water sources but presence of geogenic contaminants has increased the concern over past few decades (Singh et al. 2017). The quality of groundwater is often controlled by the regional geology and the aquifer minerals, however, it is vulnerable to the anthropogenic activities. Along with the geogenic contaminants, anthropogenic activities, i.e. rapid urbanisation, unplanned development, improper waste management and other demographic change has also affected groundwater both in terms of its quality and in terms of quantity (Bhatt et al. 2021). The quality of groundwater is the most important factor in determining its suitability for drinking, domestic and industrial use. The presence of inorganic contaminants exceeding the World Health Organization (WHO) guidelines has become a major concern for human consumption and other water use (Singh et al. 2017; Kumar & Singh 2020). When groundwater moves through its flow path, it interacts with the aquifer minerals through various hydro geochemical processes including weathering, dissolution, precipitation, oxidation-reduction, and ion exchange. These processes majorly determine the ionic concentration in groundwater, however, other than these major processes, natural factors such as recharge-discharge zone, residence time, interaction of water with aquifer minerals, surface topography, intermixing of water along with climate plays an important role in determining the ions concentration. Anthropogenic activities, i.e. groundwater exploitation, change in land use/land cover, leaching of fertilizers, agricultural runoff, herbicides, insecticides, pesticides or industrial discharge significantly affects the groundwater quality (Wongsasuluk et al. 2014; Badeenezhad et al. 2020).
In general, compared to surface water resources, groundwater is not easily contaminated and, at the same time, if contaminated it is difficult to remediate due to inaccessibility and huge volume (Wang et al. 2020). As complex hydro-geochemical processes along with the anthropogenic activities may alter the chemical composition of groundwater, it is important to investigate the hydro-geochemical processes and water quality for sustainable economic growth and human health of the region (Kadam et al. 2020; Kumar et al. 2020; Rao et al. 2020).
The quality of groundwater plays a vital role in determining its suitability for human consumption and irrigation water supply. Several methods, i.e. mineral phase equilibrium, stable isotope, chemometric analysis, redox indicator, hydrogeochemical modelling along with conventional graphical methods are extensively used across the globe to understand the groundwater quality and major hydrogeochemical processes responsible for ionic evolution of groundwater (Singh et al. 2017; Kumar et al. 2020). However, to understand the suitability of groundwater for human and irrigation use national and international guidelines are followed for each of the ions, which may have negative implications on human health or crop productivity. Apart from the individual ions, water quality indices are also used to summarize the overall water quality, which is a numeric integration of large-scale groundwater quality data into a single dimensionless number (Horton 1965). It represents overall water quality at that particular location. Later the indices values are integrated with the GIS to represent the spatial distribution of water quality in the study area. The water quality indices have been compressively used across the globe; however, to make it more inclusive, it has been modified as irrigation water quality index (IWQI), drinking water quality index (DWQI), aquatic life water index (ALWI) and others (Bora & Goswami 2017; Mukate et al. 2019; Rao et al. 2020). Addition to WQI Kelly ratio (KR), sodium absorption ratio (SAR), sodium percentage (Na%), permeability index (PI), residual sodium bicarbonates (RSB), etc., are also used to determine the suitability of water for irrigation purpose (Abtahi et al. 2015; Kumar et al. 2020; Bhatt et al. 2021).
The study area is the part of the middle Gangetic floodplain under extensive agriculture and the rural population in the study region rely largely on groundwater for their drinking and irrigation use. Quality of shallow groundwater in this region is major concern as arsenic (As) exceeding the WHO guidelines is extensively explored by the several researchers (Acharyya 2005; Donselaar et al. 2017; Chakraborti et al. 2018; Maity et al. 2020; Kumar et al. 2021). However, apart from As, very limited studies have been conducted to explore the suitability of groundwater for irrigation and seasonal change in water quality in the study area. With this background, this study is intended to explore the groundwater quality and its suitability for drinking and irrigation purpose. This study excludes As, as a number of studies has been carried out to understand the As geochemistry in the study region. However, this study also explores the baseline uranium and fluoride concentration in the area. Along with the ionic ratio to understand the hydro geochemistry, the indices, i.e. drinking groundwater quality index (DGQI) and irrigation groundwater quality index (IGQI) are used to evaluate the overall water quality. Later, the outcomes are represented with GIS map for better planning and prioritizing efficient management strategies.
MATERIAL AND METHODS
Study area
The climate of the Bhojpur district is warm and humid. The climate represents a transition between the dry and extreme climates of northern India. In the summer season, the diurnal temperature rises to 44 °C, while in the winter season it drops to as low as 4 °C. The monsoon starts mostly from the middle of June and continues up to the end of September (CGWB 2013).
Samples collection and field analysis
Grid (6×6 km) sampling method was adopted and a sample from each grid was collected in both pre-monsoon (PRM; March to May 2018) and post-monsoon (POM; October to December 2018) seasons. A total of 138 samples (69 in each season) were collected and analyzed for major ions including calcium (Ca++), magnesium (Mg++), sodium (Na+), potassium (K+), chloride (Cl−), sulfate (SO4−), nitrate (NO3−), bicarbonate (HCO3−), fluoride (F−) and uranium (U). Before the collection of groundwater samples, hand pumps were purged for 5–6 min to eliminate the influence of iron cast pipe on groundwater quality. The samples were collected from both private and public wells and the location were recorded using the global positioning system (GPS- Model Garmin Etrex 30x). Field parameters, i.e. pH, total dissolved solids (TDS), electrical conductivity (EC), temperature (T), salinity and oxidation-reduction potential (ORP) were carried out on-site, using a portable digital multi-meter (Thermo Scientific: Orion Star A329). The multi-meter was calibrated for each field parameter using standard calibration solution every day before the use.
Two sets of groundwater samples were collected in prewashed and dried high-density polyethylene (HDPE). Samples for cation analysis was preserved with 6N HNO3 (Ultrapure Merck), however, the samples collected for anions analysis was kept un-acidified. Both sets of the samples were filled up to the top without any headspace before it was kept in the dry ice packed Styrofoam boxes and transported to a laboratory. In the laboratory, samples were stored at 4 °C and analysed within 10 days of the collection.
Laboratory analysis
Un-acidified groundwater samples were tested for major anions including F−, Cl−, NO3− using ions selective electrodes (ISE; Thermo Scientific: Orion Star A329). However, the concentration of SO4– and phosphate (PO4–) were analysed using UV-VIS Spectrophotometer (Perkin Elmer, λ25) by turbidity method and stannous chloride method, respectively, using a standard procedure (APHA 2012). Titrimetric method was used for determination of HCO3− using the measurement of total alkalinity and hardness as per the standard protocol prescribed in APHA (2012).
The major cations such Ca++, Mg++, Na+, K+ were determined using titrimetric and flame photometry using a standard procedure (APHA 2012). Replicates for both anion and cations were analysed after every five samples and found within 5%. The total hardness was estimated using the ethylenediaminetetra acetic acid (EDTA) method by titration procedure (APHA 2012). The chemicals, stocks and buffer solutions were analytical grade from Merck India. The progressive standards were made by diluting stock solutions as per the standard protocol (Lachica & Barahona 1993). Additional information such as depth of water, climate and rainfall, soil type and geology were collected from Central Ground Water Board (CGWB) Patna and Indian Meteorology Department (IMD), New Delhi, India.
Determination of uranium
Uranium concentration was analysed over LED Fluorimeter (LF 2 Quantalase Enterprises Pvt. Ltd, Indore, India), using Fluren buffer solution followed the BRNS standard protocol (Sahoo et al. 2010; Ajay et al. 2016; Kumar et al. 2018; Sahu et al. 2020). It is an efficient, precise, and well-established method for detecting uranium levels in aqueous samples, with upper and lower measurement limits of 1,000–0.1 μg/L. The diluted working concentrations were prepared for the regular calibration and testing of the instrument's functioning using a standard stock solution of 100 μg/mL U (Merck India). To minimize matrix distortion as well as other interference by ionic species, water samples were analysed using the standard addition procedure. The double-distilled water was used to prepare the Fluren buffer solution using 5% sodium pyrophosphate reagent and ortho phosphoric acid was used to keep the pH of the buffer solution at 7.0. The prepared reagent solution was then added to the sample water in a 1:10 ratio to transform all of the uranium species together into a single form, resulting in an equal fluorescence yield. The calibration data is provided in the supplementary file.
Suitability of groundwater for drinking and irrigation use
Drinking water quality index (DWQI)
Irrigation water quality index (IWQI)
To assess the suitability of groundwater for irrigation, indicators such as electrical conductivity, sulfate (SO42−), and pH were considered. Apart from that, sodium percentage (Na %), sodium absorption ratio (SAR), residual carbonate (RSC), permeability index (PI), magnesium ratio (MR), and Kelly's ratio (KR) are calculated using the formula provided in Table 1. The IWQI was calculated using the similar equation used for DWQI calculation. The values for Uw and Rw were calculated using Equations (1) and (3).
Irrigation water quality parameters and formula used for their computation
Parameters . | Formula . |
---|---|
Sodium adsorption ratio (SAR) | ![]() |
Residual sodium carbonate index (RSC) | (CO3+HCO3)-(Ca+Mg) |
Permeability index (PI) | ![]() |
Magnesium ratio (MR) | ![]() |
Kelly's ratio | ![]() |
Sodium % | ![]() |
Parameters . | Formula . |
---|---|
Sodium adsorption ratio (SAR) | ![]() |
Residual sodium carbonate index (RSC) | (CO3+HCO3)-(Ca+Mg) |
Permeability index (PI) | ![]() |
Magnesium ratio (MR) | ![]() |
Kelly's ratio | ![]() |
Sodium % | ![]() |
Spatial distribution and hydro chemical diagram
Spatial distribution (contour) maps were prepared for the spatial association of the chemical properties of data among the sampling locations. These maps were prepared using inverse distance weighted (IDW) raster interpolation and spatial analysis techniques built within ArcGIS 10.1 software. Golden Software Grapher 15 was used to plot Piper trilinear diagram and Chidem (developed by Water Research Centre, Kuwait Institute for Scientific Research) software was used to prepare the Gibbs & USSL diagram and Doneen's plot.
RESULTS AND DISCUSSION
Ground water chemistry
Descriptive statistics of groundwater in the study area in both seasons (PRM & POM)
Parameters . | Mean . | Median . | Mode . | Std. Devi. . | Range . | N > WHO limit . | BIS/WHO limits . | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
PRM . | POM . | PRM . | POM . | PRM . | POM . | PRM . | POM . | PRM . | POM . | |||
pH | 7.47 | 7.3 | 7.5 | 7.3 | 7.5 | 7.2 | 0.18 | 0.3 | 7.1–7.9 | 6.9–8.8 | 0 | 6.5–8.5 |
TDS | 240.2 | 395.8 | 372 | 360 | 378 | 354 | 135 | 144.8 | 138–888 | 66–912 | 0 | 1,000 |
EC | 670.3 | 659.7 | 620 | 600 | 630 | 590 | 225 | 241.4 | 230–1,480 | 110–1,520 | 0 | 1,400 |
ORP | 112.3 | 165.3 | 125 | 210.7 | 211 | – | 89.3 | 97.9 | –56.3–256.9 | –51.7–291.2 | 0 | – |
Salinity | 388 | 324.8 | 363 | 297.3 | 364 | – | 142 | 125.9 | 180.3–786.2 | 70.3–768.4 | 0 | – |
DO | 2.71 | 2.7 | 2.66 | 2.3 | 2.1 | 1.9 | 0.7 | 1.4 | 1.35–4.77 | 1.11–10.18 | 0 | – |
F– | 0.46 | 0.3 | 0.38 | 0.3 | 0.25 | 0.2 | 0.2 | 0.2 | 0.12–1.15 | 0.09–1 | 0 | 1.5 |
Cl– | 18.98 | 26.2 | 6.8 | 8 | 13.2 | 10 | 23 | 23.9 | 0.3–104 | 3.0–100 | 0 | 250 |
NO3– | 59.22 | 9.2 | 59.2 | 5.2 | 60.1 | 2.7 | 12.4 | 9 | 26.7–91.3 | 0.87–50.7 | 53 | 45 |
SO42– | 12.91 | 16.6 | 5.87 | 9.08 | 1.4 | 3 | 14.2 | 17.9 | 0.42–65.18 | 1.86–84.26 | 0 | 200 |
PO43– | 0.3 | 0.1 | 0.24 | 0.08 | 0.3 | 0.06 | 0.1 | 0.2 | 0.00–0.68 | 0.00–1.35 | 0 | – |
U– | 2.44 | 2.3 | 2.11 | 2.1 | 2.1 | 0.1 | 1.4 | 2 | 0.09–8.61 | 0.1–7.49 | 0 | 60 (AERB) |
TH | 289 | 269 | 280 | 252 | 260 | 236 | 77.3 | 88.7 | 100–544 | 144–668 | 0 | 200 |
HCO3– | 89.17 | 83 | 91 | 80 | 90 | 80 | 19.5 | 23.5 | 38–142 | 40–170 | 0 | 300 |
Ca++ | 72.1 | 73.35 | 67 | 67.7 | 58.9 | 61.8 | 21.7 | 23.4 | 23.5–140.5 | 41.9–171.5 | 0 | – |
Mg++ | 26.5 | 20.9 | 25.7 | 18.8 | 17.2 | 15.1 | 10.9 | 10 | 1.3–56.38 | 5.6–58.3 | 0 | – |
Na+ | 217.5 | 272.1 | 187 | 239.1 | 290 | – | 116 | 101.8 | 59.39–582.7 | 94.5–590.6 | 32 | 200 |
K+ | 31.2 | 12.5 | 19 | 12 | 10.4 | 7.5 | 27.8 | 7.5 | 1.89–131.92 | 1.04–39.6 | 32 | 20 |
Parameters . | Mean . | Median . | Mode . | Std. Devi. . | Range . | N > WHO limit . | BIS/WHO limits . | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
PRM . | POM . | PRM . | POM . | PRM . | POM . | PRM . | POM . | PRM . | POM . | |||
pH | 7.47 | 7.3 | 7.5 | 7.3 | 7.5 | 7.2 | 0.18 | 0.3 | 7.1–7.9 | 6.9–8.8 | 0 | 6.5–8.5 |
TDS | 240.2 | 395.8 | 372 | 360 | 378 | 354 | 135 | 144.8 | 138–888 | 66–912 | 0 | 1,000 |
EC | 670.3 | 659.7 | 620 | 600 | 630 | 590 | 225 | 241.4 | 230–1,480 | 110–1,520 | 0 | 1,400 |
ORP | 112.3 | 165.3 | 125 | 210.7 | 211 | – | 89.3 | 97.9 | –56.3–256.9 | –51.7–291.2 | 0 | – |
Salinity | 388 | 324.8 | 363 | 297.3 | 364 | – | 142 | 125.9 | 180.3–786.2 | 70.3–768.4 | 0 | – |
DO | 2.71 | 2.7 | 2.66 | 2.3 | 2.1 | 1.9 | 0.7 | 1.4 | 1.35–4.77 | 1.11–10.18 | 0 | – |
F– | 0.46 | 0.3 | 0.38 | 0.3 | 0.25 | 0.2 | 0.2 | 0.2 | 0.12–1.15 | 0.09–1 | 0 | 1.5 |
Cl– | 18.98 | 26.2 | 6.8 | 8 | 13.2 | 10 | 23 | 23.9 | 0.3–104 | 3.0–100 | 0 | 250 |
NO3– | 59.22 | 9.2 | 59.2 | 5.2 | 60.1 | 2.7 | 12.4 | 9 | 26.7–91.3 | 0.87–50.7 | 53 | 45 |
SO42– | 12.91 | 16.6 | 5.87 | 9.08 | 1.4 | 3 | 14.2 | 17.9 | 0.42–65.18 | 1.86–84.26 | 0 | 200 |
PO43– | 0.3 | 0.1 | 0.24 | 0.08 | 0.3 | 0.06 | 0.1 | 0.2 | 0.00–0.68 | 0.00–1.35 | 0 | – |
U– | 2.44 | 2.3 | 2.11 | 2.1 | 2.1 | 0.1 | 1.4 | 2 | 0.09–8.61 | 0.1–7.49 | 0 | 60 (AERB) |
TH | 289 | 269 | 280 | 252 | 260 | 236 | 77.3 | 88.7 | 100–544 | 144–668 | 0 | 200 |
HCO3– | 89.17 | 83 | 91 | 80 | 90 | 80 | 19.5 | 23.5 | 38–142 | 40–170 | 0 | 300 |
Ca++ | 72.1 | 73.35 | 67 | 67.7 | 58.9 | 61.8 | 21.7 | 23.4 | 23.5–140.5 | 41.9–171.5 | 0 | – |
Mg++ | 26.5 | 20.9 | 25.7 | 18.8 | 17.2 | 15.1 | 10.9 | 10 | 1.3–56.38 | 5.6–58.3 | 0 | – |
Na+ | 217.5 | 272.1 | 187 | 239.1 | 290 | – | 116 | 101.8 | 59.39–582.7 | 94.5–590.6 | 32 | 200 |
K+ | 31.2 | 12.5 | 19 | 12 | 10.4 | 7.5 | 27.8 | 7.5 | 1.89–131.92 | 1.04–39.6 | 32 | 20 |
All the values are in mg/L except pH, EC (μS/cm) and U (μg/L).
(a) Spatial and seasonal variation of pH, EC, Ca, U in the study area. (b) Spatial and seasonal distribution of major anions in the study area.
(a) Spatial and seasonal variation of pH, EC, Ca, U in the study area. (b) Spatial and seasonal distribution of major anions in the study area.
Based on the average concentration, Na+ is found as the most dominant cation followed by Ca++>Mg++>K+ in both the season. In the groundwater system, cations are mostly contributed due to the interaction between groundwater and aquifer minerals through geochemical process such as weathering, ion exchange, dissolution and precipitation (Singh et al. 2017; Bhatt et al. 2021). The concentration of Na+ varies from 59.39 to 582.7 mg/L with an average of 217.5 mg/L in PRM, however; in POM it is found 94.5–590.6 mg/L with an average of 272.1 mg/L, respectively. A total of 33 samples in PRM has high concentration of Na+, exceeding the WHO guidelines, however, 54 samples exceeds the WHO guidelines during POM season. A high concentration of Na+ in groundwater exceeding WHO guidelines may cause hypertension in humans (WHO 2011), while if used for irrigation, it may reduce the soil fertility (Bauder et al. 2011). Na+ is conservative in nature and it binds with the clay minerals owing to ion exchange (Subramanian & Saxena 1983), however, poor drainage condition are also an additional source of Na+ ion in groundwater (Subba Rao et al. 2017, 2021). Calcium (Ca++) in groundwater is contributed through the weathering of calcium bearing minerals such as calcite, fluorite, calcium feldspar, amphibole, apatite, etc. The Ca++ concentration in groundwater ranges from 23.5 to 140.5 with an average of 72.1 mg/L in PRM, however, 41.9–171.5 in POM, respectively (Figure 2(a)). Ca++ along with Mg++ and HCO3− ions determines the hardness of groundwater (Singh et al. 2017). Mg++ concentration in groundwater varies from 1.3 to 56.38 mg/L and 5.6 to 58.3 mg/L in both PRM and POM, respectively. Ca++ and Mg++ ions precipitate in the soil zone resulting in temporary hardness in the groundwater. As the deposited salts gets, washed away from the soil by rainwater which contributes to an increase of these ions in the groundwater during POM season. High concentration of Mg++ in irrigation water may reduce the fertility of the crop by reducing the uptake of Ca++ and K+ ions. High concentration of K+ ion in groundwater is observed during the PRM, as 43.6% of collected groundwater samples have high K+ exceeding the WHO guideline, however, in POM 17.3% of the samples exceed the WHO guidelines. Orthoclase feldspar are the natural source of K+ ion in groundwater, however, it is mostly contributed through the agricultural runoff containing the excess of potassium fertilizers used in agriculture.
Among the major anions, Cl− is found as the most dominant one followed by HCO3−, NO3− and SO4–. Concentration of Cl− ions ranges from 0.3 to 104 mg/L with an average of 18.98 mg/L in PRM however it varies from 3.0 to 100 mg/L in POM with an average of 26.2 mg/L (Table 2). High concentration of Cl− in groundwater is mostly attributed due to the climatic factor such as high evaporation; however, additionally domestic wastes, seepage from septic tank, and irrigation return flow might also contribute Cl− in groundwater (Kumar & Singh 2015). The HCO3− in groundwater ranges from 38–142 mg/L with an average of 89.3 mg/L in PRM; however, in POM it ranges from 40–170 mg/L with an average of 83 mg/L (Figure 2(b)). HCO3− along with Ca++ and Mg++ in groundwater determines the hardness of groundwater. The concentration of HCO3− in groundwater is mostly attributed due to the soil water interaction during the recharge process; however, other processes such as root respiration along with the degradation of organic matter might also attribute HCO3− in groundwater. The study area is a part of organic rich fertile alluvial floodplain with extensive agriculture; the decomposition of organic waste from agriculture might be the major reason for HCO3− enrichment (Singh et al. 2017; Kumar & Singh 2020).
The concentration of NO3− has ranged from 26.7 to 91.3 mg/L with an average of 59.2 mg/L in PRM; however, it varies from 0.87 to 50.7 mg/L with an average of 9.2 mg/L in POM. Anthropogenic activities such as leaching of fertilizers and agricultural runoff along with the leakages from septic tank and municipal waste are considered as the major source for NO3−. High concentration of NO3− is observed in PRM season, which might be due to the standing crop and fertilizers application during PRM season.
Fluoride (F−) concentration in groundwater of the study area varies from 0.12 to 1.15 mg/L in PRM with the mean of 0.46 mg/L; however, in the POM it ranges from 0.12 to 1.15 mg/L with an average of 0.3 mg/L. Groundwater in the study area is found safe with respect to the fluoride contamination, but in the majority of the samples F− is found to be below the recommended limit, which may pose a significant health risk.
Hydro-geochemical processes
The dominance of cations, i.e. Mg++ and Na+, suggests the weathering of aquifer minerals and ion exchange; however, dominance of bicarbonates is due to root respiration and decomposition of high organic matter (Kumar & Singh 2020).
(a) Scatter plot between HCO3/Na and Ca/Na. (b) Scatter plot between Mg/Na and Ca/Na. (c) Scatter plot between Ca+Mg and SO4+HCO3. (d) Scatter plot between Cl and Na ions. (e) Scatter plot between Ca and Na ions. (f) Scatter plot between Chlro Alkalinity indices I and II.
(a) Scatter plot between HCO3/Na and Ca/Na. (b) Scatter plot between Mg/Na and Ca/Na. (c) Scatter plot between Ca+Mg and SO4+HCO3. (d) Scatter plot between Cl and Na ions. (e) Scatter plot between Ca and Na ions. (f) Scatter plot between Chlro Alkalinity indices I and II.
In the case of negative values of CAI I and CAI II, it suggests that the Na ions absorbed on the surface of aquifer minerals will be replaced by Ca++ or Mg++ ions which will contribute Na+ in groundwater. However, the positive values of CAI indicate the exchange of Na+ from groundwater by the Ca++ or Mg++ ions from the aquifer mineral. As represented in Figure 5(f), all the groundwater samples fall on the lower right panel, indicating influence of both ion exchange and reverse ions exchange in processes in the study area (Figure 5(f)).
Suitability of water for human use
The suitability of groundwater is assessed using the DWQI, a dimensionless value which classifies groundwater into five major groups: 1) excellent with DWQI <50, 2) good with DWQI 50–100, (c) poor with DWQI values 100–200, (d) very poor with DWQI 200–300 and (e) not suitable for human use with DWQI>300. In the current study, the DWQI values vary from 43 to 135 with an average of 73 in PRM season. In total, five out of 69 samples belong to the excellent water quality, 58 out of 69 belong to good water quality, and six out of 69 samples are categorized under poor water quality. However, in POM season, the DWQI value ranges from 30 to 112 with an average of 53. In total, 37 out of 69 samples fall under excellent water quality, 30 out of 69 under good water quality and two samples fall under poor water quality. None of the groundwater samples collected from the study area were very poor or not suitable for human consumption.
As agriculture is the most dominant human activity in the study area, the groundwater quality for irrigation is evaluated using indices such as sodium absorption ratio, residual sodium carbonate, permeability index, magnesium ratio and Kelly index (Table 1). The values of these indices suggest suitable groundwater quality for irrigation. However, these individual indices were used to assess the overall groundwater for irrigation (IWQI) (Subba Rao 2020). The values of IWQI can also be classified into five major classes: (1) IWQI <50: excellent; (2) IWQI 50–100: good; (3) IWQI 100–200: poor; (4) IWQI 200–300: very poor and (5) IWQI >300: not suitable for irrigation. The groundwater quality in the study area is found suitable for irrigation as all the samples except one in both POM (101) and PRM (110) have IWQI values <100.
To obtain a more comprehensive assessment of irrigation waters quality, a USSL classification diagram can be used. Water is classified into 16 classes using the USSL diagram, which shows sodium risks (SAR) on the y-axis vs. salinity hazards (EC) on the x-axis (log scale). While classifying irrigation water, the USSL diagram best explains the combined effect of sodium and salinity hazards. As a result of the combined effect of sodium and salinity hazards, the curves may be interpreted.
CONCLUSION
The present study investigates the groundwater quality and its suitability in middle Gangetic floodplain. The majority study area is under agriculture and groundwater is extensively used for domestic and irrigation water supply. The results of this study infers that the groundwater quality is controlled by both natural and anthropogenic activities. Hydrogeochemical processes such as silicate weathering along with ion exchange and reverse ion exchange have major control over ionic species in both the seasons, however, anthropogenic activity such as agricultural runoff also influences the groundwater quality especially in post-monsoon season. Na-HCO3 is found as the dominant water types in both pre- and post-monsoon seasons. Based on the WHO guidelines, the excess of NO3− concentration at 53 sampling location along with K+ and Na+ ions exceeding at 35 locations, makes it unfit for drinking. However, groundwater of the study region is found safe in terms of uranium and fluoride ions investigated in this study. Based on both irrigation and drinking water quality indices, groundwater of the study region is found suitable for human consumption and irrigation water supply. The USSL diagram infers most groundwater has low salinity–low sodium danger or medium salinity–low sodium hazard. There is a need of continuous monitoring of wells in this region before use. The findings of this study along with the spatial-temporal map may help in effective management and supply of groundwater for drinking and irrigation purpose.
ACKNOWLEDGEMENTS
The authors would like to thank the Department of Environmental Science, Central University of South Bihar, Gaya for providing laboratory facilities. The authors would also like to thank Mr Rohit Bhardwaj (technical assistant) for assisting in sampling. The authors would also like to thank two anonymous reviewers for their critical comments which have greatly improved the manuscript. The study is funded by Board of Research in Nuclear sciences (BRNS), Department of Atomic Energy, Government of India (Grant no: (36(4)/14/36/2015-BRNS).
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.