Physical Characteristics
A summary of the physical-geographical attributes of the seven water reservoirs is presented in Table 1. Notably, among the three ponds, the Dhanras pond exhibited the largest catchment area. During the post-monsoon period, the T, pH, DO, RP, EC, and TDS of water displayed were in the 20.8–22.2°C, 6.7–7.7, 5.8–8.1 mg·L− 1, 176–210 mV, 172–504 µS cm− 1, and 2865–8540 mg·L− 1 range, respectively. The corresponding mean values were 21.6 ± 0.4°C, 7.4 ± 0.2, 7.1 ± 0.7 mg·L− 1, 193 ± 10 mV, 318 ± 99 µS cm− 1, and 4122 ± 1475 mg·L− 1, respectively. The water from the pit lake revealed significantly elevated values for EC and TDS, a phenomenon likely stemming from continuous leaching processes associated with coal sediments. In contrast, the mobile water from the river displayed heightened pH and DO values, indicative of frequent occurrences of water (Gupta et al. 2017).
Table 1
Physical characteristics of surface reservoir.
S. No. | Location | Type | Area | Depth | T | pH | DO | RP | EC | TDS, |
m2 | m | oC | - | mg L− 1 | mV | µS cm L− 1 | mg L− 1 |
1 | Bhainskhatal | Po | 6540 | 5 | 22.0 | 6.7 | 7.8 | 182 | 220 | 3510 |
2 | Kohadiya | Ca | - | 3 | 21.6 | 7.4 | 6.7 | 202 | 331 | 3140 |
3 | Parsabhantha | Po | 5232 | 4 | 21.4 | 7.7 | 5.8 | 210 | 493 | 2865 |
4 | SNR | Ca | - | 2 | 22.2 | 7.3 | 5.9 | 208 | 172 | 3016 |
5 | CR | Ri | - | 4 | 21.7 | 7.6 | 8.1 | 176 | 210 | 4016 |
6 | SB | PL | 654 | 2 | 21.5 | 7.5 | 7.4 | 189 | 504 | 5540 |
7 | Dhanras | Po | 21800 | 10 | 20.8 | 7.3 | 7.8 | 182 | 300 | 3767 |
SNR = Satnam Nagar, Risdi; CR = Chhatghat Rampu,r SB = Surakachhar, Bharotal, Po = Pond, Ca = Canal, Ri = River, PL = PL |
Chemical Characteristics
During the post-monsoon period in December 2012, the concentration range and mean values of 25 chemical species (OC, CC, F−, Cl−, NO3−, SO42−, SiO44−, Li, Na, K, Rb, Mg, Ca, Ba, Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Sb, Pb, and U) in the surface water are summarized in Table 2. The total concentration of these species in the water varied from 2790 to 7969 mg·L− 1, with a mean value of 3960 ± 1340 mg·L− 1. A significant fraction was contributed by OC and CC, with concentrations ranging between 1110–3260 and 1010–4420 mg·L− 1, respectively. Both carbons exhibited a moderate correlation (r = 0.72), suggesting the origin of CC through the bacterial oxidation of OC.
The element abundance in the surface water was categorized into three groups: group I (HCO3−, Li, K, Rb, SiO44−, Sb, Pb and U), group II (F−, Cl−, NO3−, SO42−, Mg, Ca, and Ba), and group III (Na, Al, Fe, Mn, Zn, Cr, Co, Ni, Cu, OC, and CC), corresponding to where the maximum concentrations were detected, namely in pond, pit lake, and river water, respectively. The occurrence trend of the 24 elements in the water, based on mean values, followed a decreasing order: CC > OC > > NO3− > Ca > Na+ > Cl− > SO42− > K+ > Mg > F− > Al > Fe > Mn > Zn > Ba > > Li > Rb > Cu > Pb > Ni > Cr > Co > Sb > U. Comparable contamination patterns of ions and metals in the surface water were observed at other locations (Hossain et al., 2021; Kumar and Singh, 2016; Li et al., 2021; Varada et al., 2014; Verma, 2018; Xinyue and Guangzhou, 2022). However, the OC content in the studied area was found to be several folds higher than the reported global content of 3.88 mg·L− 1 (Toming et al., 2020).
Table 2
The concentration of chemical species in surface water.
Species | Unit | Min | Max | Mean | ±Std |
OC | mg L− 1 | 1110 | 3260 | 1737 | 707 |
CC | mg L− 1 | 1056 | 4420 | 1877 | 1216 |
F− | mg L− 1 | 1.8 | 4.4 | 2.6 | 0.9 |
SO42− | mg L− 1 | 10 | 70 | 28 | 21 |
Cl− | mg L− 1 | 7 | 37 | 17 | 11 |
NO3− | mg L− 1 | 7 | 50 | 20 | 16 |
HCOO3− | mg L− 1 | 81 | 113 | 94 | 10 |
SiO44− | mg L− 1 | 3.1 | 23 | 9.2 | 6.4 |
Na | mg L− 1 | 6 | 47 | 27 | 19 |
K | mg L− 1 | 4.9 | 14.6 | 9.7 | 4.5 |
Mg | mg L− 1 | 5 | 15 | 7.3 | 3.7 |
Ca | mg L− 1 | 16 | 42 | 22.3 | 9.7 |
Al | mg L− 1 | 0.96 | 2.14 | 1.33 | 0.41 |
Fe | mg L− 1 | 0.42 | 1.91 | 1.03 | 0.57 |
Mn | mg L− 1 | 0.29 | 1.22 | 0.70 | 0.38 |
Ba | mg L− 1 | 0.067 | 0.215 | 0.099 | 0.052 |
Zn | mg L− 1 | 0.045 | 0.423 | 0.181 | 0.130 |
Li | µg L− 1 | 5.8 | 23.6 | 15.9 | 6.9 |
Rb | µg L− 1 | 3.6 | 25.5 | 13.9 | 9.2 |
Cr | µg L− 1 | 3.0 | 8.0 | 3.9 | 1.9 |
Co | µg L− 1 | 2.5 | 5.9 | 3.6 | 1.2 |
Ni | µg L− 1 | 3.2 | 7.9 | 5.4 | 1.6 |
Cu | µg L− 1 | 5.4 | 14 | 8.6 | 2.8 |
Sb | µg L− 1 | 1.36 | 4.43 | 2.95 | 1.03 |
Pb | µg L− 1 | 2.8 | 6.3 | 5.2 | 1.3 |
U | µg L− 1 | 0.32 | 0.97 | 0.74 | 0.22 |
Cluster Analysis |
The hierarchical cluster software was utilized to group water samples, and the results are illustrated in Fig. 2. The seven surface water samples were effectively categorized into three distinct groups. Group I comprised pit lake water from the Surakachhar Bharotal site. Group II encompassed water from ash dump areas, specifically Dhanras and Chhatghat Rampur. On the other hand, Group III consisted of pond and canal water from Parsabhatha, Satnam Nagar Risdi, Kohadiya, and Bhainskhatal sites. A comparison of median values emphasized Group I as an outlier.
Seasonal and Temporal Variations
The Parsabhatha pond was chosen for seasonal and temporal variation studies due to its extensive use of water for domestic purposes. The water quality parameters of the Parsabhatha pond are outlined in Table 3. The pH value of the water reservoir decreased to 6.5 during the rainy season, likely attributed to the discharge of acidic runoff water. However, it slightly increased to 7.8 in the pre-monsoon period. The maximum values for most chemical species were observed during the rainy season, possibly due to the mixing of runoff water.
Temporal variations in the water quality of the Parsabhatha pond over the period 2012–17 during the summer season is also documented in Table 3. An increase in the concentration of chemical species such as OC, CC, F−, SO42−, Cl−, NO3−, SiO2, Na, K, Mg, Ca, Al, Ba, Fe, Mn, Zn, Li, Rb, Cr, Co, Ni, Cu, Sb, Pb, and U was observed, with an increment rate of approximately 8.2, 1.0, 4.0, 1.8, 8.1, 32, 33, 17, 14, 11, 22, 20, 16, 12, 9, 4.3, 13, 15, 19, 14, 21, 23, 22, 27, and 5%, respectively. Among these, lithium (Li) was the most significant element, and its concentration in the present surface water was higher than those reported in other areas (Ewuzie et al., 2020; Giotakos et al., 2013; Kostik et al., 2014).
Table 3
Seasonal variation of physicochemical parameters in Parsabhantha pond during 2012.
S. No. | Parameter | Monsoon, Aug. 12 | Post-monsoon, Feb. 12 | Pre-monsoon, May 12 |
1 | pH | 6.5 | 7.7 | 7.8 |
2 | Color | YI | CL | CL |
3 | T, oC | 25.2 | 21.4 | 35.6 |
4 | DO* | 7.1 | 6.2 | 5.6 |
5 | RP, mV | 170 | 210 | 215 |
6 | EC, µS cm− 1 | 678 | 493 | 517 |
7 | TDS* | 5310 | 3140 | 4198 |
8 | OC* | 1342 | 1347 | 1157 |
9 | CC* | 2467 | 1143 | 2216 |
10 | F−* | 4.8 | 2.4 | 3.2 |
11 | SO42−* | 67 | 16 | 21 |
12 | Cl−* | 38 | 14 | 23 |
13 | NO3−* | 116 | 13 | 37 |
14 | SiO2* | 14 | 3.1 | 5 |
15 | Na* | 63 | 47 | 51 |
16 | K* | 37 | 14 | 23 |
17 | Mg* | 30 | 6 | 9 |
18 | Ca* | 91 | 16 | 31 |
19 | Al* | 1.8 | 1.0 | 1.2 |
20 | Ba* | 1.11 | 0.08 | 0.26 |
21 | Fe* | 1.78 | 0.61 | 0.75 |
22 | Mn* | 0.62 | 0.35 | 0.41 |
23 | Zn* | 0.27 | 0.05 | 0.13 |
24 | Li≠ | 45 | 24 | 32 |
25 | Rb≠ | 31 | 19 | 22 |
26 | Cr≠ | 13.1 | 3.1 | 7.2 |
27 | Co≠ | 11.2 | 3.9 | 6.1 |
28 | Ni≠ | 8.1 | 4.8 | 4.1 |
29 | Cu≠ | 14.6 | 7.5 | 8.4 |
30 | Sb≠ | 9.6 | 3.5 | 4.6 |
31 | Pb≠ | 16 | 5.7 | 7.1 |
32 | U≠ | 2.3 | 0.9 | 0.81 |
CL = Colorless, YI = Yellowish, * = mg L− 1, ≠ = µg L− 1 |
Water Topology and Mechanism
Schoeller Diagram (Fig. 3) and Piper Diagram (Fig. 4) were constructed based on the analyzed water data, revealing the dominance of ions such as HCO3, Na, and Ca. The inferred water type is characterized as HCO3-Na/-Ca. It seems that Ca-Mg-HCO3 hydro-chemical facies is the predominant (mixed type). This indicates that hydrochemistry of the study area is influenced
by mineral dissolution, interaction of other ions present in the water as well as anthropogenic activities such as mining waste runoff. Among cations, most of the samples (sample 1, 2, 3,4 and 5) fall in no dominance zone, sample 6 showed Ca type of water. As per anion triangle, most of the surface water samples (sample 7) were bicarbonate type water followed by non-dominance zone. In a study, it was revealed that 94% and 92% of the samples were in no dominance type in cation and anion facies, respectively based on surface water analyzed from Singrauli coalfield, India. Only 6% and 5% of the samples fall in Ca type and bicarbonate type, respectively (Varshney et al. 2022).
Future investigation should include large number of surface water samples to obtain the clear scenario of hydrochemical facies of the study area. To comprehend the principal mechanisms governing water chemistry in the region, the Gibbs Diagram was also generated (Fig. 5). The primary process identified in the studied region is evaporation, evident from the high TDS values. Additionally, the water chemistry within the aquifer framework suggests saltwater intrusion.
Correlation and Sources
Species F−, Cl−, SO42−, SiO44−, Mg, Ca, and Ba exhibited significant correlation (r = 0.74 − 0.96) at p-value > 0.05, suggesting their presence as corresponding salts. Additional correlations were observed, including HCO3 − with Mg and Ca; NO3 − with Al; Na with K; and Fe and Mn with Zn (r = 0.84 − 0.85, 0.72, 0.98, and 0.93–0.99, respectively).
To further analyze the measured parameters in surface water reservoirs within the Korba basin, factor analysis (FA) was employed. Three factors with Eigenvalues > 1, contributing to a total variance of 89.01%, were identified (Table 4). The first factor (F1) exhibited strong positive loadings for TDS, Ba, Al, Ca2+, Mg2+, F−, Cl−, SO42−, NO3−, and SiO44−. The presence of Ca2+ and
Mg2+ minerals suggested weathering and dissolution of carbonate minerals through surface runoff (Ateş et al., 2020; Brindha et al., 2020). Additionally, Cl−, SO42−, and NO3− were attributed to agricultural runoff, irrigation water returns, and domestic sewage/wastewater discharges, indicating a mixed factor comprising 34.58% of the total variance from geogenic and anthropogenic sources.
The second factor (F2) was associated with natural bedrock weathering and geogenic processes, displaying high loadings of OC, CC, DO, Cd, Co, Cr, Cu, Ni, and Zn. In turn, Cd, Co, Cr, Cu, Ni, Pb, and Zn were primarily linked to industrial sources (Ateş et al., 2020). Hence, this factor that accounted for 31.05% of the total variance indicates contributions from domestic and industrial wastewater discharges.
The third factor (F3), representing 23.38% of the total variance, displayed strong positive loadings on Fe, Mn, and pH. Fe and Mn were attributed to geogenic processes involving weathering and redox reactions (Brindha et al., 2020).
Table 4
FA analysis results of the trace metals and ions detected in the surface water reservoirs located in Korba basin during post monsoon season.
Parameter | Component |
F1 | F2 | F3 |
pH | | | 0.876 |
DO, mg L− 1 | 0.251 | 0.743 | |
RP, mV | | | 0.434 |
EC, µS cm− 1 | 0.366 | | 0.366 |
TDS, mg L− 1 | 0.951 | | |
F− | 0.936 | | 0.295 |
SO42− | 0.88 | | 0.418 |
Cl− | 0.932 | | |
NO3− | 0.902 | 0.324 | 0.239 |
SiO44− | 0.901 | | |
OC | | 0.93 | |
CC | | 0.909 | 0.373 |
Na | | 0.255 | |
K | | 0.285 | |
Mg | 0.92 | 0.245 | |
Ca | 0.897 | 0.289 | 0.255 |
Fe | | 0.554 | 0.819 |
Mn | | 0.482 | 0.837 |
Al | 0.948 | | |
Ba | 0.954 | | |
Zn | | 0.747 | 0.642 |
Cr | | 0.94 | 0.285 |
Co | | 0.663 | 0.26 |
Ni | | 0.6 | |
Cu | | 0.852 | |
Sb | | | 0.376 |
Pb | | | 0.232 |
U | | | 0.309 |
Variance % | 34.58 | 31.05 | 23.38 |
Cumulative % | 34.58 | 65.63 | 89.01 |
Water Quality Assessment
Several chemical species, including OC, F−, Al, Mn, and Fe, were consistently found to exceed the permissible limits of 25, 1.5, 0.5, 0.05, and 0.300 mg·L− 1of BIS and WHO, respectively, throughout all seasons (BIS 2012; WHO, 2012) similar to other coal field areas (Sahoo et al. 2022; Zhou et al. 2020). Remarkable increases in the concentrations of carbons, ions, and metals were observed during the monsoon period, attributed to the discharge of runoff water. In the rainy season, concentrations of NO3− and Pb exceeded the tolerance limits of 45 and 0.01 mg·L− 1, respectively.
The ESP, SH, MH, SAR, and WQI values were assessed for domestic and irrigation purposes. The observed values ranged from 16.4–61.4%, 20.2–72.9%, 31.6–40.0%, 0.32 to 2.56, and 226 to 372, with mean values of 32.2 ± 20.0, 40.3 ± 22.2, 35.7 ± 3.0, 1.40 ± 1.09, and 296 ± 26, respectively. The water quality was thus deemed unsuitable for drinking purposes, as indicated by a very poor WQI, exceeding 200 (WHO, 2012).
However, the values of ESP (Na%), MH, and SAR were found to be less than 80%, 50%, and 6, respectively. The water quality fell within the C1 − S1 and C2 − S2 categories with low salinity (Fig. 6), making it suitable for direct use in irrigation (Bouwer, 1978; Paliwal, 1972; Richards, 1954; Wilcox, 1955).