Abstract
This study details the hydrochemical characterization and human health risk assessment of groundwater in the Narmada River Basin. The study was performed based on data collected from 305 groundwater sample stations in the Narmada River Basin. Hydrochemical evaluation illustrated that cationic ions in the upper and middle Narmada Basin were dominated by Ca2+; however, in the lower basin it was dominated by Na+ ions. Similarly, anionic ions were dominated by HCO3− throughout the basin. A Chadha plot drawn from the collected data inferred that most groundwater belonged to the recharge water category (Ca-Mg-HCO3 type). Base-exchange indices of the collected data confirmed the presence of Na+-SO42− type of groundwater. Meteoric genesis indices indicated deep meteoric percolation groundwater. Further, Gibbs plots categorized groundwater samples in the rock dominated section, while chloro-alkaline indices confirmed direct as well as reverse ion-exchange reactions governing groundwater quality. Water Quality Index values showed that groundwater ranged from excellent to very poor. Human health risk of the Narmada River confirmed the non-carcinogenic risk for Nitrate (NO3−) and Fluoride (F−) ions. However, several indices justified that groundwater was ideal for irrigation. However, groundwater treatment is recommended before direct consumption such as drinking.
HIGHLIGHTS
Both reverse and direct ion exchange reactions and rock weathering govern the groundwater quality.
Dominance of Na+-SO42− type and deep meteoric percolation types of groundwater.
The Water Quality Index (WQI) ranges from excellent to very poor categories.
A non-carcinogenic risk due to nitrate and fluoride contamination was confirmed.
Graphical Abstract
INTRODUCTION
Groundwater is a clean, safe, and portable source of water in comparison to surface water (Şener et al. 2017). Surface water deficiency in arid and semi-arid areas can be complemented by groundwater to meet drinking and irrigation demands (Khosravi et al. 2016). Population growth, urbanization and industrialization during the past few decades have accelerated water demand in different sectors (Gupta et al. 2020a, 2020b). The constantly increasing pressure of waste discharges from households and industries, and runoff from agricultural lands to surface water have all imposed pressure on groundwater resources and has led to their depletion and degradation (Kaviarasan et al. 2016; Gnanachandrasamy et al. 2020). In the past few decades, an increasing trend in groundwater exploitation has resulted in poor recharge, and enhanced contamination through rock water interaction (McArthur et al. 2011). Groundwater quality alters with time and space, depending upon lithology, weathering of rocks, ion-exchange reactions, evaporation and dissolution (Narany et al. 2015; Gnanachandrasamy et al. 2020). Extreme weather events such as floods and droughts etc. triggered due to climate change have also impacted groundwater quality. Occurrence of a drought in an area can affect aquifer ‘recharge/discharge’ balance and further alter the water quality of aquifers (Barbieri et al. 2021). Groundwater quality also gets degraded by anthropogenic inputs such as discharge of untreated industrial and municipal wastewater, agriculture runoff and leaching (Mondal et al. 2010; Matta et al. 2017; Barbieri et al. 2019).
The hydrochemical characterization of groundwater is necessary because it helps in revealing the processes involved in governing its quality to meet the various standards for drinking and irrigation. Several techniques have been used for geochemical identification of groundwater, such as a Chadha plot, chloro-alkaline indices, and saturation indices (Kumar et al. 2022). Moreover, determination of overall water quality through different indices like the Arithmetic Water Quality Index (AWQI) (Gupta et al. 2020a, 2020b), Comprehensive Water Quality Indices (CPI) (Gupta et al. 2020a, 2020b), Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI) (Akkoyunlu & Akiner 2012), Entropy Water Quality Index (EWQI) (Rao et al. 2020) and Oregon Water Quality Index (OWQI) (Abbasi 2002) have also been applied to evaluate the quality of water. Water quality assessment for irrigation, using different indices, e.g. Sodium Percentage (Na%), Kelly Index (Ki), and Sodium Adsorption Ratio (SAR), has also been promising (Gupta et al. 2022) in assessing groundwater conditions.
Several diseases such as dental fluorosis and methemoglobinemia (blue baby syndrome) are caused by the consumption of water contaminated with fluoride and nitrate (Rao et al. 2018). Thus, methods of assessment of human health hazards concerning ingestion of groundwater with high levels of fluoride and nitrate need to be identified for the protection and safeguarding of human health (Shukla & Saxena 2021).
Groundwater quality in the Narmada basin has been evaluated by several researchers and found to be contaminated with many pollutants. Jha et al. (2021) studied the water quality in the Mandala region located in the Narmada basin finding that aquifers in the low lying region (below 500 m mean sea level) were contaminated by fluoride and are harmful to human health. Gawle et al. (2021) studied the groundwater of the Dindori region situated in the Narmada basin and concluded that the majority of groundwater samples were not fit for direct drinking. Thus, the groundwater resource of the Narmada basin might be of poor quality and may be hazardous to human health especially concerning fluoride and nitrate contamination. Considering the pressure on groundwater resources and importance of its quality assessment, we performed this study with the objectives (i) to assess and determine the important geochemical processes and factors impacting the groundwater chemistry in different sub-basins of the Narmada River, and (ii) to identify its suitability for consumption and irrigation.
METHODOLOGY AND MATERIALS
General characteristics of study area
Narmada River Basin map showing geological features as well as groundwater sampling stations.
Narmada River Basin map showing geological features as well as groundwater sampling stations.
Hydrogeology and topography of study area
The NRB is a part of a volcanic province i.e., the Deccan Trap, covered by heterogeneous geological features. The main lithology of the study area consist of Archaean, alluvial sedimentary formations of Gondwanas and Vindhyan groups, with the major portion covered by Deccan Trap basalt (Kumar et al. 2005). Topographically, UNB terrain is hilly consisting of flat Proterozoic sedimentary rock, whereas the terrains of the MNB and LNB are fertile plains dominated by limestone and sandstones and are suitable for cultivation. However, the western part of LNB lies in the coastal region of the Arabian Sea and is of an alluvial nature. The basin is dominated and covered by black soil.
Granite rock, medium to coarse grained sandstone and limestone bearing rocks, and basaltic rock are the dominant rocks found in this region. Granitic aquifers, mostly unconfined sandstone supporting phreatic aquifers, basaltic aquifers of a confined to semi-confined nature and alluvium aquifers are found in the basin (Jha et al. 2021). The developed porosity in Gondwana rocks, vascularity in the basalt rocks, and presence of joints and fractures in the rocks along with varying degrees of weathering and secondary porosity developed naturally due to joints and fractures play a crucial role in groundwater yield and its movement (CGWB 2017). The basin is mostly covered with basaltic aquifers and yields about 10–50 m3 day−1 (CGWB 2017), with low hydraulic conductivity and high inhomogeneity. The depth of water level in the study area varies from 5 to 20 m below ground level (CGWB 2018).
Data collection and preparation
The India Water Resources Information System (India WRIS) is a web-based database developed under the National Hydrology Project in 2016 with the prime goal of gathering information on the water resources of India. India-WRIS has groundwater quality monitoring stations throughout the nation. The groundwater quality data for 2018 for the NRB from 305 monitoring stations (132 samples from UNB; 122 samples from MNB; and 51 samples from LNB) were collected from India-WRIS. The locations of the above mentioned 305 sampling stations are shown in Figure 1. The data obtained represent 12 parameters i.e., pH, total dissolved solids, electrical conductivity, sodium, potassium, calcium, magnesium, chloride, bicarbonate, nitrate, sulphate, and fluoride.
The values of the normalized charge balance were in the range of ±15%, justifying the balance in ions (cations and anions), and confirmed the reliability of data for further geochemical studies.
Groundwater chemistry and geochemical modeling
Inverse geochemical modeling
Water quality index and irrigation water quality indices
The appropriateness of groundwater for irrigation purposes was computed and classified as per sodium percentage (Na %), Kelly's index (Ki), sodium adsorption ratio (SAR), Permeability index (Pi), Magnesium ratio (MAR), Residual Sodium Carbonate (RSC), Wilcox diagram (Wilcox 1955) and US Salinity Laboratory (USSL's) diagram (Table 8).
Human health risk assessment
Here, RfD = 0.04 and 1.6 mg/kg/day for fluoride and nitrate, respectively (USEPA 2014).
According to (USEPA 2014), THI > 1 indicates non-carcinogenic health risk to its consumers, whereas THI < 1 confirms no risk to its consumers (Haghnazar et al. 2022).
Statistical and spatial analysis
The detailed statistics (mean, standard deviation, minimum, maximum) of different physicochemical parameters were calculated using MS Excel 2013. Pearson's correlation coefficient was calculated in R-4.2.0 software. Spatial analysis using the interpolation technique (IDW)) was performed in Quantum gis (https://www.qgis.org).
RESULTS AND DISCUSSION
General physicochemical characteristics of groundwater
The physicochemical characteristics of the groundwater of UNB, MNB and LNB are summarized and compared with BIS (BIS 2012) and World Health Organization (WHO) (WHO 2017) standards in Table 1.
Descriptive statistics of hydrochemical parameters of groundwater in the Narmada River Basin
Parameter . | BIS (2012) AND WHO (2017) . | Upper Narmada Basin . | Middle Narmada Basin . | Lower Narmada Basin . | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Acceptable limit . | Permissible limit . | min . | max . | mean . | SD . | min . | max . | mean . | SD . | min . | max . | mean . | SD . | |
pH | 6.5–8.5 | – | 6.79 | 8.69 | 7.54 | 0.37 | 6.86 | 8.42 | 7.37 | 0.25 | 6.22 | 8.36 | 7.85 | 0.39 |
EC (μmhos/cm) | – | 500 | 210 | 1,742 | 800.64 | 332.3 | 365 | 2,320 | 1,067.25 | 428.41 | 363 | 5,530 | 1,248.9 | 957.65 |
TDS (mg/L) | 500 | 2,000 | 136.5 | 1,132.3 | 520.41 | 215.99 | 237.25 | 1,508 | 693.71 | 278.47 | 243.21 | 3,705 | 834.4 | 641.3 |
Ca2+ (mg/L) | 75 | 200 | 12 | 178 | 59.37 | 29.5 | 20 | 312 | 80.82 | 41.73 | 28 | 218 | 77.42 | 41.88 |
Mg2+ (mg/L) | 30 | 100 | 1.49 | 153.25 | 32.22 | 24.39 | 2.45 | 137.59 | 38.15 | 23.51 | 2 | 277 | 49.85 | 48.07 |
Na+ (mg/L) | – | 200 | 8 | 321 | 50.19 | 39.04 | 14 | 289 | 70.99 | 54.27 | 2 | 777 | 110.31 | 137.26 |
K+ (mg/L) | 12 | 300 | 0.1 | 7 | 1.46 | 1.39 | 0.1 | 86.1 | 7.19 | 14.02 | 0.1 | 38.4 | 4.47 | 7.79 |
HCO3− (mg/L) | 120 | 600 | 49 | 656 | 297.91 | 135.26 | 24 | 766 | 366.24 | 130.03 | 49 | 659 | 314.44 | 154.21 |
Cl− (mg/L) | 250 | 1,000 | 7 | 260 | 63.42 | 52.04 | 10 | 404 | 96.75 | 76.89 | 14 | 1,454 | 189.94 | 252.21 |
SO42− (mg/L) | 200 | 400 | 4 | 195 | 24.55 | 22.46 | 5 | 185 | 28.57 | 25.38 | 4 | 414.37 | 73.3 | 88.55 |
NO3− (mg/L) | 45 | 100 | 1 | 115 | 27.88 | 23.39 | 1 | 217 | 51.82 | 39.73 | 2 | 250 | 34.88 | 46.46 |
F− (mg/L) | 1 | 1.5 | 0.01 | 2.19 | 0.36 | 0.36 | 0.08 | 3.7 | 0.57 | 0.52 | 0.12 | 3 | 0.87 | 0.5 |
ICB% (±15%) | − 9.5 | 5.26 | − 2.06 | 2.23 | − 9.9 | 1.93 | − 1.61 | 2.3 | − 14.2 | 9.59 | − 4.1 | 4.69 | ||
Anhydrite | − 3.73 | − 2.01 | − 2.79 | 0.35 | − 3.48 | 3.03 | − 2.62 | 0.64 | − 3.50 | − 1.27 | − 2.44 | 0.52 | ||
Aragonite | − 15 | 1.06 | 0.00 | 1.39 | − 0.67 | 1.03 | 0.15 | 0.33 | − 1.38 | 1.39 | 0.52 | 0.45 | ||
Calcite | − 1.38 | 1.21 | 0.28 | 0.44 | − 0.53 | 1.17 | 0.30 | 0.32 | − 1.24 | 1.53 | 0.65 | 0.46 | ||
Dolomite | − 2.83 | 2.29 | 0.52 | 0.96 | − 1.99 | 2.50 | 0.49 | 0.82 | − 2.43 | 3.18 | 1.40 | 0.97 | ||
Fluorite | − 5.29 | 0.31 | − 2.43 | 0.92 | − 3.16 | 1.45 | − 1.74 | 0.74 | − 2.45 | − 0.23 | − 1.37 | 0.41 | ||
Gypsum | − 3.42 | − 1.71 | − 2.49 | 0.35 | − 22.77 | − 1.33 | − 2.52 | 1.89 | − 3.19 | − 0.97 | − 2.13 | 0.52 | ||
Halite | − 8.51 | 7.20 | − 7.20 | 1.37 | − 8.31 | − 5.61 | − 7.00 | 0.59 | − 8.23 | − 4.62 | − 6.76 | 0.84 | ||
Sylvite | − 10.1 | − 7.07 | − 8.45 | 0.57 | − 9.94 | − 5.64 | − 7.96 | 0.86 | − 9.27 | − 6.06 | − 7.85 | 0.83 |
Parameter . | BIS (2012) AND WHO (2017) . | Upper Narmada Basin . | Middle Narmada Basin . | Lower Narmada Basin . | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Acceptable limit . | Permissible limit . | min . | max . | mean . | SD . | min . | max . | mean . | SD . | min . | max . | mean . | SD . | |
pH | 6.5–8.5 | – | 6.79 | 8.69 | 7.54 | 0.37 | 6.86 | 8.42 | 7.37 | 0.25 | 6.22 | 8.36 | 7.85 | 0.39 |
EC (μmhos/cm) | – | 500 | 210 | 1,742 | 800.64 | 332.3 | 365 | 2,320 | 1,067.25 | 428.41 | 363 | 5,530 | 1,248.9 | 957.65 |
TDS (mg/L) | 500 | 2,000 | 136.5 | 1,132.3 | 520.41 | 215.99 | 237.25 | 1,508 | 693.71 | 278.47 | 243.21 | 3,705 | 834.4 | 641.3 |
Ca2+ (mg/L) | 75 | 200 | 12 | 178 | 59.37 | 29.5 | 20 | 312 | 80.82 | 41.73 | 28 | 218 | 77.42 | 41.88 |
Mg2+ (mg/L) | 30 | 100 | 1.49 | 153.25 | 32.22 | 24.39 | 2.45 | 137.59 | 38.15 | 23.51 | 2 | 277 | 49.85 | 48.07 |
Na+ (mg/L) | – | 200 | 8 | 321 | 50.19 | 39.04 | 14 | 289 | 70.99 | 54.27 | 2 | 777 | 110.31 | 137.26 |
K+ (mg/L) | 12 | 300 | 0.1 | 7 | 1.46 | 1.39 | 0.1 | 86.1 | 7.19 | 14.02 | 0.1 | 38.4 | 4.47 | 7.79 |
HCO3− (mg/L) | 120 | 600 | 49 | 656 | 297.91 | 135.26 | 24 | 766 | 366.24 | 130.03 | 49 | 659 | 314.44 | 154.21 |
Cl− (mg/L) | 250 | 1,000 | 7 | 260 | 63.42 | 52.04 | 10 | 404 | 96.75 | 76.89 | 14 | 1,454 | 189.94 | 252.21 |
SO42− (mg/L) | 200 | 400 | 4 | 195 | 24.55 | 22.46 | 5 | 185 | 28.57 | 25.38 | 4 | 414.37 | 73.3 | 88.55 |
NO3− (mg/L) | 45 | 100 | 1 | 115 | 27.88 | 23.39 | 1 | 217 | 51.82 | 39.73 | 2 | 250 | 34.88 | 46.46 |
F− (mg/L) | 1 | 1.5 | 0.01 | 2.19 | 0.36 | 0.36 | 0.08 | 3.7 | 0.57 | 0.52 | 0.12 | 3 | 0.87 | 0.5 |
ICB% (±15%) | − 9.5 | 5.26 | − 2.06 | 2.23 | − 9.9 | 1.93 | − 1.61 | 2.3 | − 14.2 | 9.59 | − 4.1 | 4.69 | ||
Anhydrite | − 3.73 | − 2.01 | − 2.79 | 0.35 | − 3.48 | 3.03 | − 2.62 | 0.64 | − 3.50 | − 1.27 | − 2.44 | 0.52 | ||
Aragonite | − 15 | 1.06 | 0.00 | 1.39 | − 0.67 | 1.03 | 0.15 | 0.33 | − 1.38 | 1.39 | 0.52 | 0.45 | ||
Calcite | − 1.38 | 1.21 | 0.28 | 0.44 | − 0.53 | 1.17 | 0.30 | 0.32 | − 1.24 | 1.53 | 0.65 | 0.46 | ||
Dolomite | − 2.83 | 2.29 | 0.52 | 0.96 | − 1.99 | 2.50 | 0.49 | 0.82 | − 2.43 | 3.18 | 1.40 | 0.97 | ||
Fluorite | − 5.29 | 0.31 | − 2.43 | 0.92 | − 3.16 | 1.45 | − 1.74 | 0.74 | − 2.45 | − 0.23 | − 1.37 | 0.41 | ||
Gypsum | − 3.42 | − 1.71 | − 2.49 | 0.35 | − 22.77 | − 1.33 | − 2.52 | 1.89 | − 3.19 | − 0.97 | − 2.13 | 0.52 | ||
Halite | − 8.51 | 7.20 | − 7.20 | 1.37 | − 8.31 | − 5.61 | − 7.00 | 0.59 | − 8.23 | − 4.62 | − 6.76 | 0.84 | ||
Sylvite | − 10.1 | − 7.07 | − 8.45 | 0.57 | − 9.94 | − 5.64 | − 7.96 | 0.86 | − 9.27 | − 6.06 | − 7.85 | 0.83 |
The pH values ranged from (6.79–8.69), (6.86–8.42), (6.22–8.36) for UNB, MNB and LNB respectively, with an average value of ∼7.58 for the NRB, showed a neutral to slight alkaline nature of groundwater. However, 1.5% of samples in UNB and 1.96% of samples in LNB exceeded the recommended pH value of 6.5–8.5 (BIS 2012). The electrical conductivity (EC) had a wide range of variation from (210–1,742), (365–2,320), (363–5,530) with a mean value of 800.64, 1,067.25, and 1,248 μmhos/cm for UNB, MNB and LNB, respectively. According to WHO standards, EC value should not exceed 1,500 μmhos/cm, but 3%, 13.9% and 29.4% of the groundwater samples were far beyond the permissible limit for UNB, MNB and LNB, respectively. The TDS values in groundwater of UNB, MNB, and LNB varied from 136.5–1,132.3 mg/L, 237.25–1,508 mg/L, and 243.21–3,705 mg/L with mean values of 520.41, 693.71, and 834.4 mg/L, respectively. About 52.3%, 72.1%, and 66.7% of groundwater samples of UNB, MNB, and LNB, respectively, surpassed the prescribed values of acceptable limits of TDS i.e., 500 mg/L (BIS 2012).
Ion concentration in groundwater
Spatial distribution of fluoride and nitrate concentration in groundwater.
Correlation analysis of groundwater samples
Hydrogeochemistry of groundwater
Representation of a Chadha plot showing different types of groundwater.
From the scatter plot (Figure 4) we can observe most groundwater samples of NRB falling in the recharge water (Ca-Mg-HCO3 type) section, meaning that during the groundwater recharge process, it might have carried and dissolved the carbonates in HCO3− form and Ca2+ ions in groundwater. Few groundwater samples of UNB and MNB were influenced by base ion-exchange reactions i.e., dissolution of Na+ ions in water and precipitation of Ca2+ ions. About four LNB groundwater samples were found to be of seawater type which indicates the mixing of seawater and groundwater, which is generally restricted to the coastal region (Ravikumar & Somashekar 2017). However, NRB groundwater samples were also controlled by reverse-ion exchange mechanisms where Ca + Mg ion concentration exceeds Na + K concentration owing to release of Ca and Mg dissolution and subsequently precipitation of Na+ ions on minerals.
The classification of groundwater via base-exchange indices (r1) using Equation (2) categorized 84.85% of water samples as Na+-SO42− type (r1 < 1) and 15.15% of samples as Na+-HCO3− type (r1 > 1) in UNB. In MNB about 86.04% and 13.93% of water samples were of Na+-SO42− type and Na+-HCO3− type respectively. However, in LNB 94.12% of water samples was categorized as Na+-SO42− type (r1 < 1) and only 5.88% of water samples belonged to Na+-HCO3− type (r1 > 1). A meteoric genesis index (r2) was calculated to classify groundwater samples of NRB using Equation (3). The obtained results showed that 82.58%, 78.69% and 96.08% of groundwater samples belonged to deep meteoric water percolation type (i.e., r2 < 1) for UNB, MNB, and LNB respectively, whilst the rest of the groundwater samples i.e., 17.42% (UNB), 21.31% (MNB) and 3.92% (LNB) were categorized as shallow meteoric water percolation type. Therefore, results from Equations (2) and (3) infer that the basin is dominated by Na+-SO42− type and deep meteoric percolation type of groundwater.
Identifying the source of ions in groundwater by Gibbs plot (a) TDS against Na/(Na + Ca) (b) TDS against Cl/(Cl + HCO3).
Identifying the source of ions in groundwater by Gibbs plot (a) TDS against Na/(Na + Ca) (b) TDS against Cl/(Cl + HCO3).
Identification of different types of weathering through an end-member diagram plot (a) HCO3−/Na+ against Ca2+/Na+ (b) Mg2+/Na+ against Ca2+/Na+.
Identification of different types of weathering through an end-member diagram plot (a) HCO3−/Na+ against Ca2+/Na+ (b) Mg2+/Na+ against Ca2+/Na+.
To examine the insights of lithology in weathering processes like silicate/carbonate/evaporate weathering were identified using different plots of HCO3−/Na+ v/s Ca2+/Na+ and Mg2+/Na+ v/s Ca2+/Na+ also known as end-member diagrams. The plot of HCO3−/Na+ v/s Ca2+/Na+ (Figure 6(a)) shows that silicate weathering was occurring in NRB, whereas, few sampling locations of LNB were governed by evaporate weathering. However, a plot of Mg2+/Na+ v/s Ca2+/Na+ reveals that the groundwater of NRB follows a silicate-evaporate mixing trend (Figure 6(b)), mainly governed by silicate weathering to attain thermodynamic equilibrium.
Bi-plot of (a) Ca against SO4 (b) Ca + Mg against SO4 + HCO3 (c) HCO3 against Ca + Mg and (d) Na+ against Cl−.
Bi-plot of (a) Ca against SO4 (b) Ca + Mg against SO4 + HCO3 (c) HCO3 against Ca + Mg and (d) Na+ against Cl−.
The SO42− + HCO3−v/s Ca2+ + Mg2+ scatter plot (Figure 7(b)) showed that the groundwater samples of UNB, MNB and LNB fall both above and below the equiline, thus indicating that weathering of carbonate and silicate minerals is contributing HCO3− ions to the groundwater.
The scatter diagram between Ca2+ + Mg2+ v/s HCO3− (Figure 7(c)) confirmed dolomite and calcite as main sources of Ca2+ and Mg2+ ions in groundwater. However, around 27% of groundwater samples of LNB were above the equiline. Therefore, the source of Ca2+ and Mg2+ ions in subsurface water might be due to dissolution of minerals like gypsum and cation-exchange between Ca2+ and Na+ during dissolution and precipitation processes (El Mountassir et al. 2021).
The obtained Na+ v/s Cl− scatter plot (Figure 7(d)) clearly depicts the origin of Na+ ions in groundwater samples from halite dissolution. According to Loni et al. (2015), where Na+ ions are in abundant against Cl− ion there is a possibility of silicate weathering being dominant during the weathering process. However, some proportion of samples were above the equiline which clearly showed the dominancy of Cl− over Na+. In LNB, Cl− dominance might be an indication of seawater intrusion ultimately influencing groundwater mineralization (El Mountassir et al. 2021).
Classification of groundwater samples as direct or reverse ion exchange through CAI-1 and CAI-2 values
Parameters . | Range . | % of samples . | ||
---|---|---|---|---|
UNB . | MNB . | LNB . | ||
CAI-1 (Schoeller, 1965)![]() | < 0 (Direct ion exchange) | 36.36% | 44.26% | 17.65% |
>0 (Reverse ion exchange) | 63.64% | 55.74% | 82.35% | |
CAI-2 (Schoeller, 1965)![]() | < 0 (Direct ion exchange) | 36.36% | 44.26% | 17.65% |
> 0 (Reverse ion exchange) | 63.64% | 55.74% | 82.35% |
Parameters . | Range . | % of samples . | ||
---|---|---|---|---|
UNB . | MNB . | LNB . | ||
CAI-1 (Schoeller, 1965)![]() | < 0 (Direct ion exchange) | 36.36% | 44.26% | 17.65% |
>0 (Reverse ion exchange) | 63.64% | 55.74% | 82.35% | |
CAI-2 (Schoeller, 1965)![]() | < 0 (Direct ion exchange) | 36.36% | 44.26% | 17.65% |
> 0 (Reverse ion exchange) | 63.64% | 55.74% | 82.35% |
UNB, Upper Narmada Basin; MNB, Middle Narmada Basin; LNB, Lower Narmada Basin.
Source identification and apportionment of minerals
Plots of SIcalcite, SIdolomite, SIaragonite, SIanahydrite and SIgypsum, SIsylvite SIhalite and SIflourite against TDS values.
Plots of SIcalcite, SIdolomite, SIaragonite, SIanahydrite and SIgypsum, SIsylvite SIhalite and SIflourite against TDS values.
The mean SI values for SO42− minerals i.e., SIanahydrite & SIgypsum were found to be −2.79 and −2.49, respectively, for UNB; −2.62 and −2.52 for MNB; −2.45 and −2.13 for LNB. The average SI values for potassium minerals, sodium mineral and flouride mineral such as SIsylvite, SIhalite and SIflourite were found to be −8.45, −7.2 and −2.43 for UNB, respectively; −7.96, −7 and −1.74 for MNB; and −7.85, −6.76 and −1.37 for LNB. Therefore, plots of SIanahydrite and SIgypsum against TDS values (Figure 10 and Table 3), showed that all groundwater samples was under saturated with sulphate minerals. Similarly, plots of SIsylvite SIhalite and SIflourite against TDS values (Figure 10 and Table 3), were found to be under saturated. Therefore, plots of SI of different minerals against TDS values point out minimal or absent soluble sulphate, potassium, and sodium or fluoride minerals. Carbonate minerals are said to be reactive minerals; therefore, oversaturation condition of carbonate minerals in the basin indicates regular dissolution of carbonate minerals with continuous contribution of Ca2+, Mg2+ and HCO3− ions in the groundwater (Batabyal 2018).
Classification of groundwater samples as precipitation, dissolution, and equilibrium through saturation indices
. | % of sample . | ||||||||
---|---|---|---|---|---|---|---|---|---|
Upper Narmada Basin . | Middle Narmada Basin . | Lower Narmada Basin . | |||||||
SI > 0 . | SI < 0 . | SI = 0 . | SI > 0 . | SI < 0 . | SI = 0 . | SI > 0 . | SI < 0 . | SI = 0 . | |
Calcite | 77.27% | 21.96% | 0.77% | 86.1% | 13.9% | – | 92.2% | 5.8% | 2% |
Dolomite | 77.28% | 22.72% | – | 79.5% | 20.5% | – | 94.2% | 5.8% | – |
Aragonite | 62.87% | 36.36% | 0.77% | 69.68% | 30.32% | – | 94.2% | 5.8% | – |
Anhydrite | – | 100% | – | 0.82% | 99.18% | – | – | 100% | – |
Gypsum | – | 100% | – | – | 100% | – | – | 100% | – |
Sylvite | – | 100% | – | – | 100% | – | – | 100% | – |
Halite | 0.77% | 99.23% | – | – | 100% | – | – | 100% | – |
Fluorite | 0.77% | 99.23% | – | 2.5% | 97.5% | – | – | 100% | – |
. | % of sample . | ||||||||
---|---|---|---|---|---|---|---|---|---|
Upper Narmada Basin . | Middle Narmada Basin . | Lower Narmada Basin . | |||||||
SI > 0 . | SI < 0 . | SI = 0 . | SI > 0 . | SI < 0 . | SI = 0 . | SI > 0 . | SI < 0 . | SI = 0 . | |
Calcite | 77.27% | 21.96% | 0.77% | 86.1% | 13.9% | – | 92.2% | 5.8% | 2% |
Dolomite | 77.28% | 22.72% | – | 79.5% | 20.5% | – | 94.2% | 5.8% | – |
Aragonite | 62.87% | 36.36% | 0.77% | 69.68% | 30.32% | – | 94.2% | 5.8% | – |
Anhydrite | – | 100% | – | 0.82% | 99.18% | – | – | 100% | – |
Gypsum | – | 100% | – | – | 100% | – | – | 100% | – |
Sylvite | – | 100% | – | – | 100% | – | – | 100% | – |
Halite | 0.77% | 99.23% | – | – | 100% | – | – | 100% | – |
Fluorite | 0.77% | 99.23% | – | 2.5% | 97.5% | – | – | 100% | – |
SI > 0 (precipitation); SI < 0 (dissolution); SI = 0 (equilibrium).
Appraisal of groundwater quality for drinking purposes using a water quality index (WQI)
Relative weights of major parameters
Chemical parameters . | Acceptable limits (BIS 2012; WHO 2017) . | Weight (wi) . | Relative weight (RWi) . |
---|---|---|---|
pH | 8.5 | 4 | 0.114285714 |
TDS (mg/L) | 500 | 3 | 0.085714286 |
Ca2+ (mg/L) | 75 | 2 | 0.057142857 |
Mg2+ (mg/L) | 30 | 2 | 0.057142857 |
Na+ (mg/L) | 200 | 2 | 0.057142857 |
K+ (mg/L) | 12 | 2 | 0.057142857 |
HCO3− (mg/L) | 120 | 3 | 0.085714286 |
Cl− (mg/L) | 250 | 4 | 0.114285714 |
SO42− (mg/L) | 200 | 3 | 0.085714286 |
NO3− (mg/L) | 45 | 5 | 0.142857143 |
F− (mg/L) | 1 | 5 | 0.142857143 |
∑wi = 35 | ∑RWi = 1 |
Chemical parameters . | Acceptable limits (BIS 2012; WHO 2017) . | Weight (wi) . | Relative weight (RWi) . |
---|---|---|---|
pH | 8.5 | 4 | 0.114285714 |
TDS (mg/L) | 500 | 3 | 0.085714286 |
Ca2+ (mg/L) | 75 | 2 | 0.057142857 |
Mg2+ (mg/L) | 30 | 2 | 0.057142857 |
Na+ (mg/L) | 200 | 2 | 0.057142857 |
K+ (mg/L) | 12 | 2 | 0.057142857 |
HCO3− (mg/L) | 120 | 3 | 0.085714286 |
Cl− (mg/L) | 250 | 4 | 0.114285714 |
SO42− (mg/L) | 200 | 3 | 0.085714286 |
NO3− (mg/L) | 45 | 5 | 0.142857143 |
F− (mg/L) | 1 | 5 | 0.142857143 |
∑wi = 35 | ∑RWi = 1 |
Classification of ground water quality based on WQI values
Water Quality Index (WQI) . | % of sample . | |||
---|---|---|---|---|
Range . | Water class . | UNB . | MNB . | LNB . |
(WQI < 50) | excellent | 23.5% | 4.1% | 9.85% |
(50 < WQI < 100) | good | 63.6% | 52.1% | 49.0% |
(100 < WQI < 200) | poor | 12.9% | 43.8% | 37.3% |
(200 < WQI < 300) | very poor | – | – | 3.9% |
Water Quality Index (WQI) . | % of sample . | |||
---|---|---|---|---|
Range . | Water class . | UNB . | MNB . | LNB . |
(WQI < 50) | excellent | 23.5% | 4.1% | 9.85% |
(50 < WQI < 100) | good | 63.6% | 52.1% | 49.0% |
(100 < WQI < 200) | poor | 12.9% | 43.8% | 37.3% |
(200 < WQI < 300) | very poor | – | – | 3.9% |
UNB, Upper Narmada Basin; MNB, Middle Narmada Basin; LNB, Lower Narmada Basin.
Human health risk assessment due to presence of NO3− and F−
The presence of NO3− and F− in groundwater at higher concentration poses a threat to the people of developing and under-developed nations because groundwater is their primary source for drinking. The consumption of groundwater contaminated with NO3− and F− leads to health risks (USEPA 2014). Since, the study area is contaminated with NO3− and F− as shown in Figure 2, we computed the non-carcinogenic human health risk for children (age < 12) and adults (age > 19) through a drinking water ingestion pathway. Further, we integrated a total hazard index (THI) (Figure 12) for these groups of children and adults.
Total Hazard Index (THI) indicting non-carcinogenic health risk (CR) and no risk (NR) among different population groups (adults and children)
. | Percentage of sample . | |||||
---|---|---|---|---|---|---|
Upper Narmada Basin . | Middle Narmada Basin . | Lower Narmada Basin . | ||||
< 1 (NR) . | > 1 (CR) . | < 1 (NR) . | > 1 (CR) . | < 1 (NR) . | > 1 (CR) . | |
THI: Adult (age > 19) | 50.8% | 49.2% | 17.2% | 82.8% | 23.5% | 76.5% |
THI: Children (age < 12) | 46.2% | 53.8% | 13.9% | 86.1% | 19.6% | 80.4% |
. | Percentage of sample . | |||||
---|---|---|---|---|---|---|
Upper Narmada Basin . | Middle Narmada Basin . | Lower Narmada Basin . | ||||
< 1 (NR) . | > 1 (CR) . | < 1 (NR) . | > 1 (CR) . | < 1 (NR) . | > 1 (CR) . | |
THI: Adult (age > 19) | 50.8% | 49.2% | 17.2% | 82.8% | 23.5% | 76.5% |
THI: Children (age < 12) | 46.2% | 53.8% | 13.9% | 86.1% | 19.6% | 80.4% |
USEPA (2014), THI > 1 indicates non-carcinogenic health risk (CR) to its consumers whereas THI < 1 confirms no risk (NR).
Descriptive statistics of CDI (chronic daily intake) and HQ (hazard quotient) for NO3− and F-, and THI (total hazard index)
. | Nitrate . | Fluoride . | THI . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
CDI . | HQ . | CDI . | HQ . | ||||||||
Adults . | Children . | Adults . | Children . | Adults . | Children . | Adults . | Children . | Adults . | Children . | ||
UNB | Min | 0.04 | 0.05 | 0.03 | 0.03 | 0.00 | 0.00 | 0.01 | 0.01 | 0.11 | 0.12 |
Max | 4.95 | 5.46 | 3.10 | 3.41 | 0.09 | 0.10 | 2.36 | 2.60 | 3.54 | 3.91 | |
Average | 1.20 | 1.32 | 0.75 | 0.83 | 0.02 | 0.02 | 0.39 | 0.43 | 1.14 | 1.26 | |
MNB | Min | 0.09 | 0.10 | 0.05 | 0.06 | 0.00 | 0.00 | 0.09 | 0.10 | 0.29 | 0.32 |
Max | 9.35 | 10.31 | 5.84 | 6.44 | 0.16 | 0.18 | 3.98 | 4.39 | 6.33 | 6.98 | |
Average | 2.25 | 2.48 | 1.40 | 1.55 | 0.02 | 0.03 | 0.61 | 0.68 | 2.02 | 2.22 | |
LNB | Min | 0.09 | 0.10 | 0.05 | 0.06 | 0.01 | 0.01 | 0.13 | 0.14 | 0.18 | 0.20 |
max | 10.77 | 11.88 | 6.73 | 7.42 | 0.13 | 0.14 | 3.23 | 3.56 | 7.48 | 8.25 | |
average | 1.50 | 1.66 | 0.94 | 1.04 | 0.04 | 0.04 | 0.94 | 1.03 | 1.88 | 2.07 |
. | Nitrate . | Fluoride . | THI . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
CDI . | HQ . | CDI . | HQ . | ||||||||
Adults . | Children . | Adults . | Children . | Adults . | Children . | Adults . | Children . | Adults . | Children . | ||
UNB | Min | 0.04 | 0.05 | 0.03 | 0.03 | 0.00 | 0.00 | 0.01 | 0.01 | 0.11 | 0.12 |
Max | 4.95 | 5.46 | 3.10 | 3.41 | 0.09 | 0.10 | 2.36 | 2.60 | 3.54 | 3.91 | |
Average | 1.20 | 1.32 | 0.75 | 0.83 | 0.02 | 0.02 | 0.39 | 0.43 | 1.14 | 1.26 | |
MNB | Min | 0.09 | 0.10 | 0.05 | 0.06 | 0.00 | 0.00 | 0.09 | 0.10 | 0.29 | 0.32 |
Max | 9.35 | 10.31 | 5.84 | 6.44 | 0.16 | 0.18 | 3.98 | 4.39 | 6.33 | 6.98 | |
Average | 2.25 | 2.48 | 1.40 | 1.55 | 0.02 | 0.03 | 0.61 | 0.68 | 2.02 | 2.22 | |
LNB | Min | 0.09 | 0.10 | 0.05 | 0.06 | 0.01 | 0.01 | 0.13 | 0.14 | 0.18 | 0.20 |
max | 10.77 | 11.88 | 6.73 | 7.42 | 0.13 | 0.14 | 3.23 | 3.56 | 7.48 | 8.25 | |
average | 1.50 | 1.66 | 0.94 | 1.04 | 0.04 | 0.04 | 0.94 | 1.03 | 1.88 | 2.07 |
USEPA (2014), THI > 1 indicates non-carcinogenic health risk whereas THI < 1 confirms no risk.
Note: Adults (age > 19); Children (age < 12).
UNB, Upper Narmada Basin; MNB, Middle Narmada Basin; LNB, Lower Narmada Basin.
Classification of groundwater quality through different indices for irrigation purposes
Parameters . | Range . | Water class . | % of sample . | ||
---|---|---|---|---|---|
UNB . | MNB . | LNB . | |||
Na% (Maharana et al. 2015)![]() | <20 | Excellent | 18.9% | 14.8% | 21.6% |
20-40 | Good | 44.7% | 45.1% | 35.3% | |
40-60 | Permissible | 30.3% | 27.9% | 25.5% | |
60-80 | Doubtful | 4.5% | 10.7% | 15.7% | |
80-100 | Bad | 1.5% | 1.6% | 2% | |
SAR (USSL 1954)![]() | <10 | Excellent | 76.5% | 64.8% | 54.9% |
10-18 | Good | 18.2% | 24.6% | 21.6% | |
18-26 | Doubtful | 3% | 5.7% | 11.8% | |
>26 | Unsuitable | 2.3% | 4.9% | 11.8% | |
Kelly's index (Ki) (Kelly 1963)![]() | Ki < 1 | Suitable | 84.1% | 83.6% | 70.6% |
Ki > 1 | Unsuitable | 15.9% | 16.4% | 29.4% | |
Permeability index (Pi) (Doneen 1964)![]() | Pi < 60% | Suitable | 52.27% | 67.21% | 62.75% |
Pi > 60% | Unsuitable | 47.72% | 32.79% | 37.25% | |
Magnesium ratio (MAR) (Paliwal 1972)![]() | MAR < 50 | Suitable | 82.6% | 89.3% | 76.5% |
MAR > 50 | Unsuitable | 17.4% | 10.7% | 23.5% | |
RSC (USSL 1954)![]() | <1.25 | Good | 90.9% | 89.3% | 96% |
1.25 < RSC > 2.5 | Marginally suitable | 6.1% | 9% | 2% | |
>2.5 | Unsuitable | 3% | 1.6% | 2% |
Parameters . | Range . | Water class . | % of sample . | ||
---|---|---|---|---|---|
UNB . | MNB . | LNB . | |||
Na% (Maharana et al. 2015)![]() | <20 | Excellent | 18.9% | 14.8% | 21.6% |
20-40 | Good | 44.7% | 45.1% | 35.3% | |
40-60 | Permissible | 30.3% | 27.9% | 25.5% | |
60-80 | Doubtful | 4.5% | 10.7% | 15.7% | |
80-100 | Bad | 1.5% | 1.6% | 2% | |
SAR (USSL 1954)![]() | <10 | Excellent | 76.5% | 64.8% | 54.9% |
10-18 | Good | 18.2% | 24.6% | 21.6% | |
18-26 | Doubtful | 3% | 5.7% | 11.8% | |
>26 | Unsuitable | 2.3% | 4.9% | 11.8% | |
Kelly's index (Ki) (Kelly 1963)![]() | Ki < 1 | Suitable | 84.1% | 83.6% | 70.6% |
Ki > 1 | Unsuitable | 15.9% | 16.4% | 29.4% | |
Permeability index (Pi) (Doneen 1964)![]() | Pi < 60% | Suitable | 52.27% | 67.21% | 62.75% |
Pi > 60% | Unsuitable | 47.72% | 32.79% | 37.25% | |
Magnesium ratio (MAR) (Paliwal 1972)![]() | MAR < 50 | Suitable | 82.6% | 89.3% | 76.5% |
MAR > 50 | Unsuitable | 17.4% | 10.7% | 23.5% | |
RSC (USSL 1954)![]() | <1.25 | Good | 90.9% | 89.3% | 96% |
1.25 < RSC > 2.5 | Marginally suitable | 6.1% | 9% | 2% | |
>2.5 | Unsuitable | 3% | 1.6% | 2% |
UNB, Upper Narmada Basin; MNB, Middle Narmada Basin; LNB, Lower Narmada Basin.
Spatial distribution of total hazard index (THI) for different age groups along the basin.
Spatial distribution of total hazard index (THI) for different age groups along the basin.
Over 53.8%, 86.1% and 80.4% of groundwater samples of UNB, MNB and LNB, respectively, were greater than the acceptable limit (>1) and found to cause non-carcinogenic risk for children, whilst for adults, about 49.2%, 82.8% and 76.5% of groundwater samples of UNB, MNB and LNB, respectively, were identified to cause non-carcinogenic risk due to ingestion of groundwater. Tables 6 and 7 reveal that the THI risk assessment reveals more adverse health effects on children compared with adults.
Appropriateness of groundwater for irrigation and agriculture needs
To discern the appropriateness of groundwater for irrigation, six indices were calculated: Na%, SAR, Ki, Pi, MAR and RSC. The results of these indices are given in Table 8.
(a) USSL's diagram, (b) Wilcox diagram, representing the suitability of the groundwater samples for irrigation use.
(a) USSL's diagram, (b) Wilcox diagram, representing the suitability of the groundwater samples for irrigation use.
In UNB, Na% values ranged from 10.58 to 92.12 with a mean value of 35.68; in MNB they ranged from 7 to 88.15 with an average value of 37.6; and in LNB, Na% values ranged from 1.46 to 87.47 with an average value of 38.33.
The groundwater samples are identified for agriculture purposes with Na% falling in excellent to bad categories (Table 8). The biplot of Na% against EC was plotted to generate a Wilcox plot (Wilcox 1955) (Figure 13(b)) to identify the water usage for irrigation needs. The Wilcox plot showed that mostly groundwater samples were in a excellent to good water quality category and only a few water samples of MNB and LNB were in a doubtful to unsuitable region.
Kelly (1963) classified groundwater into two categories: if Ki < 1 then water is suitable but when Ki > 1 then water is considered to be unsuitable for irrigation use due to it being an alkali hazard (Table 8). In UNB, Ki values ranged from 0.09 to 11.68 with an average value of 0.74; in MNB, Ki values ranged from 0.05 to 7.3 with a mean value of 0.74; and Ki values ranged from 0.01 to 6.9 with a mean value of 0.88 in LNB. As shown in Table 8, 84.1%, 83.6% and 70.6% of groundwater samples of UNB, MNB, and LNB, respectively, were found to be suitable for irrigation use.
Doneen (1964) developed a formula (Table 8) to produce a permeability index (Pi) to understand the mobility capacity of groundwater in soil. Pi was categorised into two classes i.e., Pi < 60% (suitable) and Pi > 60% (unsuitable). In UNB, Pi values ranged from 25 to 120 with an average value of 58, whereas in MNB Pi values ranged from 19.13 to 107.6 with an average value of 55.29, and in LNB, Pi values ranged from 22.35 to 100.67 with an average value of 53.29. As shown in Table 8, 52.27%, 67.21%, and 62.75% of groundwaterwater samples of UNB, MNB, and LNB, respectively, were found to be fit for irrigation.
The presence of Mg2+ ions in high concentration degrade the soil quality, which ultimately promotes low yield. Therefore, it is very important to determine magnesium hazards. MAR was calculated according to the formula given in Table 8: if the MAR value of water samples is less than 50 then it is said to be suitable and when it exceeds 50 then the water is considered to be unfit for irrigation purposes. In UNB, MAR values ranged from 5.05 to 69.9 with average value of 33.54, and 82.6% of groundwater samples fell in the suitable category. The MAR values of groundwater samples in MNB ranged from 2.01 to 64.9 with an average value of 31.9 and 89.3% of water samples being categorised suitable. In LNB, MAR values ranged from 4.76 to 85.23 with an average value of 36.38 and only 76.5% of groundwater samples were found to be suitable for agricultural purpose.
Residual Sodium Carbonate (RSC) refers to sodium carbonate and sodium bicarbonate present in water. Therefore, a high concentration of carbonate and bicarbonate in water leads to the precipitation of calcium and magnesium in the soil, thus altering soil structure. According to USSL (1954), RSC can be calculated using the formula given in Table 8, and it is classified into three categories i.e., RSC < 1.25 (good), 1.25 < RSC > 2.5 (marginally suitable) and RSC > 2.5 (unsuitable). In UNB, RSC values ranged from 0.3 to 6 with an average value of 1 and about 90.9% of groundwater was categorised in the good category. In MNB, the RSC values ranged from 0.06 to 4.9 with an average an value of 0.9 and around 89.3% of groundwater samples were categorised in the good category. However, in LNB, most groundwater samples (96%) ranged in the good category with RSC values ranging from 0.13 to 3.4 with an average value of 0.8.
CONCLUSIONS
This is the first research of its kind which covers the hydrochemical study, human health risk assessment, geochemical modelling, water quality index, and irrigation water suitability of groundwater in the Narmada River Basin. The hydrochemical composition of subsurface water in the NRB is driven by natural processes such as rock weathering, as well as some anthropogenic activities. The results show that most water quality parameters exceeded the permissible limits. An overall high WQI value was present in the study area indicating the water to be unsuitable for human consumption. Human health risk assessments concluded that there was a ‘non-carcinogenic’ risk due to consumption of groundwater. However, groundwater is suitable for irrigation uses. This study highlights the need for detailed proper planning and policy making for water resources management. Thus, the current study recommends the treatment of polluted water before its consumption. Additionally, the government and policymakers of Madhya Pradesh should create awareness, and set up and supply treated water for drinking purposes. In general, this study will assist in the prevention of health risks, and also safeguard human well being, environmental sustainability and prosperity.
ACKNOWLEDGEMENT
The authors wish to extend their gratitude towards India Water Resources Information System (India -WRIS) for providing the online data on their official website.
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 of interest.