Pathways of major ion chemistry and evaluation of contaminants in the River Ajay, India Open Access

Rivers are vital and valuable freshwater systems, which play an important role in life from molecules to humans. They also play an imperative role in the transportation of 0.0002% of freshwater out of 0.006% of the total freshwater resources (Mir et al. 2016). In India, twenty major rivers and several minor rivers fulfill the water demands for agriculture and domestic and industrial purposes, which is the greatest strength of Indian freshwater. As per the National Commission for Integrated Water Resource Management, there is about 1,953 km³ average annual flow of Indian Rivers, whereas the utilizable quantity of water is only about 690 km³, i.e. around 36% of the total flow of the rivers (Kumar et al. 2005). However, in the present scenario, pollution of the rivers is a global problem due to the increase in human population, industrialization, urbanization and changes in land-use patterns (Suratman et al. 2015; Dominguez et al. 2016; Xu et al. 2017). In China, land creation by cutting off hilltops for urbanization and industrial setups has increased the risk for air pollution, water contamination, groundwater and surface water loss, soil erosion and geological hazards due to massive sediment formation, changing geological and hydro-geological conditions, landslides, flooding and altered watercourses (Li et al. 2014). The rebirth of the new Silk Road (the economic belt of China) also has caused collateral damage to the natural environment since a major part of this route is located in semi-arid and arid regions of China, where water resources are already in vulnerable condition due to high density of human population and climate change (Li et al. 2015a, b). Similarly, the Three Gorges Reservoir (TGR) over the Yangtze River is suffering from water quality degradation due to eutrophication problems and significant inputs of non-point and point sources of pollutants in the river (Tang et al. 2015). These consequences lead to more water demand and subsequently increase polluted water with different contaminants (Suratman et al. 2015). Rivers are loaded with different types of contaminants through agricultural, industrial and domestic activities worldwide (Gurgel et al. 2016). In India, it has been reported that about 70% of the available water is polluted and the prime source of pollution is sewage which contributes approximately 84–92% of the waste in the river system (Joshi et al. 2009). Approximately 10% of urban and rural Indians access unsafe drinking water (Suthar 2011). Around 3 million people die every year because of poor drinking water and unsanitary conditions worldwide (WHO 2004). Similarly, the accumulation of contaminants in the river system creates a high ecological risk for aquatic organisms and is responsible for high mortality rate, alteration in growth, damage to reproduction and loss of aquatic diversity (Devanesan et al. 2017; Mahmoud et al. 2017). Consequently, the assessment of river geochemistry is very important to identify the factors (weathering, seasonal variation, hydrological and anthropogenic) which are influencing the quality of river water (Gholizadeh et al. 2016; MacDonald et al. 2016; Wang et al. 2017). The chemical composition of river water is reflected through weathering products, mineralized organic material, soil profile washed out during excess water discharge and industrial effluent, sewage and agricultural discharges (Pettersson et al. 2000). The geochemical composition of river water mainly depends on weathering and dissolution of rock minerals, which are responsible for dissolved ions present in the river. Climatic condition also influences the river water chemistry due to elevation, temperature, precipitation and geographical features (Bowser & Jones 2002). A detailed study of the geochemical properties of river systems can provide significant information about the composition of ions, types of minerals, water types and history of the elemental cycle (Zhang et al. 1995; Gupta & Banarjee 2012).

The Ajay River flows through one of the richest coal-mining belts (Andal and Raniganj coalfield) of Jharkhand and West Bengal provinces, India and drains through Deoghar, Jamtara, Chittranjan, Illam Bazar and Katwa towns before joining the Bhagirathi River at Katwa, West Bengal. It also encounters (Gondwana land) the mineral-rich area (Jamtara and Dumka) which includes black stones, fireclay, china clay, silica sand, quartz, feldspar and coal (Singh et al. 2012). Therefore, the Ajay River is more contamination-prone due to surface activities for mineral exploration while industries, mining machinery, power plants and vehicular emissions are also additional sources of pollution. These issues clearly indicate that the water chemistry of the Ajay River can be strongly reflected by weathering, mineral exploration, agricultural runoff, atmospheric deposition and anthropogenic activities in the catchment area. However, a comprehensive assessment of the Ajay River Basin has largely been unstudied and very little literature is available on the hydro-geochemistry of the Ajay River Basin. So, it is very pertinent to assess and monitor the comprehensive environmental condition of the Ajay River Basin. Keeping in view the above gap, this study may provide insights so that any policy decision can be implemented at a larger scale for this river basin in particular and overall river basins in general.

The major objectives of this study are divided into five phases: (a) to identify the major ion chemistry and evolution of the contaminants in the river water; (b) to study the spatial and temporal distribution pattern of the major ion, (c) to identify possible sources of the physicochemical and biochemical parameters with the help of compositional analysis, (d) to apply the Water Quality Index (WQI) to identify the present water quality status in the study area, and (e) to verify whether principal component analysis (PCA) and geochemical indices can provide better understanding of the process occurring within the studied catchment than the simple statistical techniques.

The lithology of the Ajay River Basin is mainly characterized by alluvial, major red and yellow loam sedimentary types. The younger alluvial is made up of clay, silt, sand, gravel, pebble and calcareous concretion, whereas the older alluvial is composed of laterite, sand, silt, ferruginous concretion, lithomargic clay and gravel. In the lower part of the basin at Illambazar, Birbhum district, the river has the tendency of laterisation which is commonly known as Illambazar formation and is mainly composed of ferruginous lateritic soil with sand, gravel and pebble. The lateritic soil is formed during the intense tropical weathering of minerals and has a composition dominated by iron oxide, aluminium-oxide, oxy-hydroxide, kaolinite and quartz (Tardy 1992). This part of the basin is characterized by chemical weathering (basalt) and crusting of aluminium (Al) and iron (Fe) minerals.

Nineteen replicate water samples were collected from each site in three consecutive seasons (pre-monsoon (PM) in May 2017), (monsoon (MON) in July 2017) and (post-monsoon (POM) in December 2017). The selection of sites was done considering the location of different project components, junction of stream courses, spots of high-water velocity and some of the stagnated pools along with the areas having human interference. Both sites were targeted based on the availability of human activities. The study includes the various baseline parameters of water quality. Integration of water quality parameters gives an overall perception of positive and negative impacts due to agriculture, industrial and some other human activities, if any. In the collection of samples for water samples, different methods and techniques were applied separately based on the international standards method by the American Public Health Association (APHA 2022). Selected physicochemical parameters have been analyzed at the site for projecting the status of existing water quality based on existing aquatic environmental conditions. Samples for chemical analysis were collected in 1 liter-sterilized polyethylene containers. Samples for bacteriological analysis were collected in sterilized dark brown glass bottles to avoid any oxidation process by bacteria.

Water samples were analyzed for twenty-three parameters to determine the overall quality with respect to physicochemical and biochemical parameters as per the standard procedure of APHA (2005). Electrical conductivity (EC), total dissolved solid (TDS) and pH were analyzed through a multi-parameters Orion Versa Star Pro bench-top meter with pH/ISE/mV module (A-214). All major ions such as calcium (Ca²⁺), magnesium (Mg²⁺), nitrate (⁠⁠), chloride (Cl⁻), sodium (Na⁺), alkalinity (⁠⁠), sulfate (⁠⁠), potassium (K⁺), fluoride (F⁻), boron (Br⁻), nitrite (⁠⁠), ammonia (⁠⁠), and phosphate (⁠⁠) were analyzed by ion chromatograph (IC-Plus, 5: Metrohom). The rest of the parameters such as dissolved oxygen (DO), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) were examined by the titrimetric method suggested by (APHA 2005) while bacterial counts such as total coliform (TC) and fecal coliform (FC) were analyzed through the most probable number (MPN) method.

The reproducibility of the analytical procedures was checked by carrying out duplicate analysis. The variations in results were less than 5% of the mean. The ability to replicate samples was determined by collecting two samples at every station. All the reagents were of analytical grade and purchased from Merck, India. For the preparation of all reagents and calibration standards, Millipore water of the Synergy Water Purification System (resistivity of 18.2 MΩ.cm at 25 °C with TOC ≤5 ppb) was used. Percentage recovery (P) and measurement of uncertainty (MOU) were calculated and followed by ISO, 17025 (1999) for better laboratorial practices, as listed in (Table 2). To calculate the accuracy of chemical analysis, the ion balance error method was applied according to Mandel & Shiftan (1981) and Lloyd & Heathcote (1985). The percentage error of major ions during chemical analysis was within the range (≈ of 10%).

Table 2

List of parameters and their analytical procedure

Parameters .	Units .	Analytical methods .	BIS .	WHO (2006)  .	Range .	MOU .	P. R. .
pH	–	Multi-parameter analyzer	6.5–8.5	6.5–9	0.1–13.9	± 0.84	100
Temperature	°C	Thermo meter	–	–	1–100	–
Turbidity	NTU	Turbidity meter	5	–	1–1,000		98.6
Alkalinity	mg/L	Ion chromatograph	200	–	1–5,000	±0.68	102.2
EC	μS/cm	Multi-parameter analyzer		1,400	1–4,000	±0.12	97.9
TDS	mg/L	Multi-parameter analyzer	500	1,500	1–10,000	±0.63	–
DO	mg/L	Winkler method	–	–	1–20	–	–
Ca2+	mg/L	Ion chromatograph	70	200	1–1,000	–	101.4
Mg2+	mg/L	Ion chromatograph	30	150
Cl−	mg/L	Ion chromatograph	250	500	1–5,000	± 0.55	99.2
	mg/L	Ion chromatograph	200	400	1–1,000	–	98.6
	mg/L	Ion chromatograph	45	40–70	1–100	–	104.4
	mg/L	Ion chromatograph	–	–	0.01–1	–	–
	mg/L	Ion chromatograph	–	–	1–100	–	–
	mg/L	Ion chromatograph	–	10	0.01–100	–	102.2
Na+	mg/L	Ion chromatograph	–	500	1–2,000		98.4
K+	mg/L	Ion chromatograph	–	50	1–1,000		100.8
F−	mg/L	Ion chromatograph	1.5	–	0.01–100	–	–
COD	mg/L	Open reflux method	<4	–	1–1,000	± 1.0	100.2
BOD	mg/L	Winkler method	<2	–	1–1,000	–	–
TC and FC	MPN/100mL	MPN method	Absent	10	–	–	–

Parameters .	Units .	Analytical methods .	BIS .	WHO (2006)  .	Range .	MOU .	P. R. .
pH	–	Multi-parameter analyzer	6.5–8.5	6.5–9	0.1–13.9	± 0.84	100
Temperature	°C	Thermo meter	–	–	1–100	–
Turbidity	NTU	Turbidity meter	5	–	1–1,000		98.6
Alkalinity	mg/L	Ion chromatograph	200	–	1–5,000	±0.68	102.2
EC	μS/cm	Multi-parameter analyzer		1,400	1–4,000	±0.12	97.9
TDS	mg/L	Multi-parameter analyzer	500	1,500	1–10,000	±0.63	–
DO	mg/L	Winkler method	–	–	1–20	–	–
Ca2+	mg/L	Ion chromatograph	70	200	1–1,000	–	101.4
Mg2+	mg/L	Ion chromatograph	30	150
Cl−	mg/L	Ion chromatograph	250	500	1–5,000	± 0.55	99.2
	mg/L	Ion chromatograph	200	400	1–1,000	–	98.6
	mg/L	Ion chromatograph	45	40–70	1–100	–	104.4
	mg/L	Ion chromatograph	–	–	0.01–1	–	–
	mg/L	Ion chromatograph	–	–	1–100	–	–
	mg/L	Ion chromatograph	–	10	0.01–100	–	102.2
Na+	mg/L	Ion chromatograph	–	500	1–2,000		98.4
K+	mg/L	Ion chromatograph	–	50	1–1,000		100.8
F−	mg/L	Ion chromatograph	1.5	–	0.01–100	–	–
COD	mg/L	Open reflux method	<4	–	1–1,000	± 1.0	100.2
BOD	mg/L	Winkler method	<2	–	1–1,000	–	–
TC and FC	MPN/100mL	MPN method	Absent	10	–	–	–

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In this study, the fluctuation of temperature is mainly due to seasonal changes, geographical location and sampling time. The range of pH varies from 7.02 to 8.10 with a mean of 7.49, which indicates that the river water is moderately alkaline throughout the year. The presence of limestone bedrock along the basin area can increase the level of ions during water-rock interaction and lead to higher pH in the river water. pH value of the river water samples was found to be within the safe limit prescribed by BIS (1991) and WHO (2006). EC of the Ajay River water increased 17-fold along the basin route from 214 to 4,572 μS/cm with a mean value of 907.0 μS/cm. The EC values at three sites (S2, S5 and S6) were above the critical water conductivity of 3,000 μS/cm according to salinity classification (Selvakumar et al. 2017). The higher EC was observed in the upper part of the river basin. It may be due to the presence of gneissic rock, which leads to higher EC value because of the dissolution of carbonate minerals in the river water. Other sources like wastewater, urban runoff, application of nitrogenous content fertilizer and atmospheric deposition are also responsible for higher levels of EC in the river system. Similarly, the value of TDS varies from 112 to 2,980 mg/L with a mean value of 582.1 mg/L. The higher value of TDS suggests that the water of S2, S5 and S6 sites are not under fresh water type. Because the TDS level higher than >1,000 mg/L in water bodies is considered as brackish water type (Ayed et al. 2017). A higher amount of TDS was observed in the upper domain of the basin. An extreme level of TDS in this area is owing to anthropogenic sources like mining waste and urban and industrial effluents which can amplify the TDS level in the river water. Consequently, the river might get a significant amount of waste accomplished with ionized substances, biodegradable compounds and nutrients in the upper basin from urban and industrial centers and are responsible for a higher amount of TDS in the river system. Similarly, higher values of EC and TDS were obtained in the PM and POM seasons which may be the evidence of high temperature which enhances the evaporation rate, loss of water, decomposition and mineralization of organic materials during these periods.

The DO value ranges from 2.6 to 5.2 mg/L with a mean value of 4.06 mg/L. The values of DO indicated that the river water is not well oxygenated because all values were less than the regulatory standard (≥6.0 mg/L) as per BIS (1991) at all sites. The inferior amount of DO level in the river system is mainly due to the high amount of organic load and the presence of a high microbial population (Sharma et al. 2014). DO level of the river may also be affected by many environmental and biochemical factors such as temperature, photosynthesis and chemical and biological oxygen demands (Zhang et al. 2007). It may harm the self-purification capacity of the river and could form hypoxic conditions in aquatic systems (Suthar et al. 2009). However, in the monsoon period, DO levels showed a little higher value but did not fulfill the regulatory criteria. Elevated levels of DO in this period may be due to the high dispersion of organic pollutants as a result of the flushing effect and breakdown of organic waste. The value of BOD and COD varies from 3.2 to 19.5 mg/L with a mean value of 8.07 and 8.2 to 56 mg/L with a mean value of 19.06 mg/L, respectively. The values of both parameters indicated that all values exceeded the regulatory standard (<3 and <10 mg/L, respectively), as suggested by BIS (1991). The elevated level of both parameters suggests that river water is contaminated through point sources of decomposable organic matter from domestic, agricultural and industrial discharge. This is because both parameters are indicators of domestic and industrial discharge into the river system (Erturk et al. 2010). It was also noted that S2, S3, S4, S5, S6 and S11 sites are major contributors of organic load into the river basin that is responsible for elevated values of COD and BOD (>20 and >8 mg/L, respectively). These sites belong to urban and industrial centers, which are associated with different types of organic and inorganic compounds. TC and FC values of river water range from 130 to 585 MPN/100 mL with a mean value of 234.6 MPN/100 mL and 23 to 108 MPN/100 mL with a mean value of 49.6 MPN/100 mL, respectively. The value of both bacterial parameters did not fulfill the drinking water quality criteria and exceeded the permissible limit WHO (2006). The river water is contaminated due to significant counts of fecal bacteria present in the whole basin route. However, a higher concentration of these parameters was observed in the POM followed by the PM period. During this period, freshwater levels in river catchments are believed to be very low compared with other seasons. Consequently, it is possible that the organic wastes increase the microbial activities in the river and lead high concentration of these parameters.

The value of in the study area varies from 11.6 to 133.2 mg/L with a mean value of 101.6 mg/L. The results revealed that the river water quality is under alkaline conditions. The values of were within desirable limits (200 mg/L), as suggested by BIS (1991). The higher value of was noted in the POM followed by PM and monsoon periods. Availability of in river water generally depends on the rate of carbonates and silicate weathering, oxidation of organic matter and dissolution of atmospheric CO₂ (Hartmann et al. 2013). The value of Ca²⁺ and Mg²⁺ in the study area varies from 15.21 to 39.56 mg/L and 6.51 to 19.2 mg/L with mean values of 27.9 and 13.57 mg/L, respectively. The values of Ca²⁺ and Mg²⁺ of all collected water samples were within the permissible limit prescribed by BIS (1991). The result suggested that the river water is not hard (<150–300 mg/L) according to hardness classification. However, enhancement of Ca²⁺ and Mg²⁺ values was observed in the upper domain of the basin, which may be due to the presence of a gneissic rock with an abundance of limestone, dolomite and calc-granulite. Chloride value in the study area varies from 4.33 to 145 mg/L with a mean value of 31.5 mg/L. Cl⁻ value of all collected water samples was less than the regulatory standard (200 mg/L) and under the safe limit. It is usually derived from rainfall sources, evaporites and atmospheric deposition (Mir et al. 2016). The temporal study indicated that the highest value of these parameters was obtained in the monsoon and POM period and sometime in the PM period.

Similarly, the Na⁺ and K⁺ value of the water samples in the study area varies from 13.19 to 48.5 mg/L and 2.75 to 12.5 mg/L with mean values of 28.2 and 5.8 mg/L, respectively. Na⁺ and K⁺ values of all collected water samples were within permissible limits according to WHO (2006). Both are very important to the human body for the proper functioning of the nervous and membrane system. The seasonal variations of both parameters were less but higher concentration was noted in the POM followed by PM, especially in the middle and lower part of the river basin. Na⁺ and K⁺ in the river water generally depend on the weathering of ferro-magnesium and feldspar minerals while anthropogenic inputs are additional sources (Breault et al. 2000). value of the collected water samples varies from 3.25 to 72.4 mg/L with a mean value of 27.9 mg/L. The results indicated that the value of all water samples was under the permissible limit prescribed by BIS (1991). The presence of in the river water generally depends on the geology of the area (gypsum containing rock) and land-use practices like application of fertilizer to agricultural land and input of domestic and industrial discharge. However, the higher concentration of in the monsoon period indicates that river water is slightly affected by agricultural runoff with sulfate-containing fertilizers from agricultural areas.

In the last few decades, the majority of river basins have been contaminated due to high concentrations of fluoride (F⁻), nitrate (⁠⁠), nitrite (⁠⁠), ammonia (⁠⁠) and phosphate (⁠⁠) which are the most omnipresent chemical contaminants of the river water. The observed value of F⁻ varied from 0.01 to 3.2 mg/L with a mean value of 1.08 mg/L. The higher value of F⁻ was observed in nine samples of sites S1, S6, S8, S10 and S14 in all seasons and exceeded the water quality standard (1.5 mg/L) suggested by BIS (1991). The availability of fluoride in the river usually depends on the weathering of fluoride-bearing rocks (natural) and proximity to human emission sources (anthropogenic) along the basin area (Singh et al. 2008). Higher levels of F⁻ in collected river water samples along these regions may be due to the mineralization of granitic or sandstone and fluoride-bearing rocks (muscovite, biotite, fluorite and fluoro-apatite). However, the mining of coal, processing of phosphate rock and manufacturing of glass and ceramic products lead to the concentration of F⁻ in the basin area. However, the presence of a high concentration of F⁻ in the Ajay River Basin makes water unsuitable for drinking purposes. As a result, high fluoride-containing water for a long time causes chronic adverse effects on local public health. Therefore, it can be believed that the risk that we assumed in the present study may increase in future through geogenic and anthropogenic sources.

value of the river water in the study area varies from 0.15 to 2,734 mg/L with a mean value of 368.04 mg/L. value of collected samples was higher than regulatory standard (<45 mg/L) as per BIS (1991) in 17 samples from sites S2, S3, S4, S5, S6, S7 and S11 in all seasons. The elevated level of at these sites may be due to the increasing rate of mineral exploration, mining, agricultural and industrial development, which caused nitrogen accumulation in water. In this area, the river receives large amounts of waste from fertilizer industries, biodegradable wastes from domestic discharge, ionized substances from food and beverage industries and nitrogenous waste from agricultural fields. level in the river system is also positively influenced by biological fixation, precipitation and application of nitrogenous (N) fertilizers (Rao 2014). In addition, atmospheric deposition, sanitary landfills, garbage dumps, soil-containing organic matter, animal waste and poorly functioning septic systems are potential sources of ⁠. A higher amount of in the river can cause water quality degradation by the eutrophication process and create hypoxic conditions in the water body (Daisuke et al. 2014). It is also harmful to the human body and could be responsible for stomach cancer (Zeng & Wu 2015).

value varies from 0.01 to 0.74 mg/L with a mean value of 0.16 mg/L. The result indicated that all water samples have low value as compared to the regulatory standard (<1.2 mg/L), prescribed by ISI: 2296 (1982). The elevated level of was observed in the lower basin of the Ajay River Basin in all seasons. The land use of the Ajay River in the lower basin is commonly used for paddy cultivation. However, elevated levels of in the lower basin may be due to agricultural activities with the application of N-content fertilizers. The value of varies from 0.01 to 0.24 mg/L with a mean value of 0.05 mg/L. A higher concentration of was obtained in the upper and lower parts of the river basin in all the seasons. This is because that area is generally used for domestic and agricultural purposes. However, the presence of in the river system indicates that the water is affected by municipal wastewater discharges and domestic uses (bathing and washing purposes) because detergents are an important source of (Gebre 2017). The overall study showed that ⁠, ⁠, Cl⁻, Na⁺ and are major dominant ions present in the river. The higher level of ions like ⁠, Cl⁻, Na⁺ and in the river system may be due to weathering of aged rock-forming minerals. Furthermore, extreme level in the river system reveals the contribution of anthropogenic inputs such as fertilizer and urban and industrial wastes.

PCAs for the water of the Ajay River include Scree plot, eigenvalue, percentage variance and cumulative percentage. Scree plot observed that the eigenvalues are associated with each component in descending order to identify important components or factors present in the dataset (Ledesma 2007). PCA develops a rotated component matrix in the expression of eigenvalues for each component with the percentage of variance and cumulative percentage to explain each component. Four components (PC) were obtained with a cumulative variance of 57.54% of the total variance in the dataset, in which PC1 accounts for 19.06%, PC2 accounts for 13.95%, PC3 accounts for 10.31% and PC4 accounts for 14.21% of the total variance. Eigenvalues of the eight principal components have been found more than one so they can be used to assess the dominant components present in the data set (Table 5). Eigenvalue of each factor has been characterized into four groups viz. >0.75 is considered as strong loading, 0.5–0.75 is considered as moderate loading and 0.3–0.5 is considered as weak loading (Liu et al. 2003).

Table 5

The rotated component matrix of water quality parameters of the Ajay River

Parameters .	D1 .	D2 .	D3 .	D4 .
pH	− 0.112	0.344	0.258	0.188
DO	− 0.355	0.007	− 0.176	− 0.548
Alk	0.112	− 0.147	0.432	0.185
EC	0.942	− 0.161	− 0.016	0.114
TDS	0.947	− 0.153	0.015	0.132
Ca2+	0.059	− 0.648	0.136	− 0.012
Mg2+	− 0.223	− 0.700	0.121	− 0.017
Cl−	0.428	0.060	− 0.177	0.449
	0.353	0.288	− 0.002	0.154
	0.941	− 0.166	− 0.076	0.096
	− 0.385	0.806	0.079	0.008
	0.034	− 0.707	− 0.076	− 0.048
	− 0.019	0.093	0.765	0.266
Na+	− 0.073	− 0.177	0.483	− 0.236
K+	0.047	0.312	0.611	0.042
F−	0.033	0.478	0.567	0.187
COD	0.415	0.139	0.353	0.585
BOD	0.544	0.167	0.236	− 0.254
TC	− 0.054	0.119	0.019	0.929
FC	− 0.026	0.050	0.043	0.879
Eigenvalue	4.319	3.245	2.184	1.763
% of Variance	19.061	13.958	10.315	14.214
Cumulative %	19.061	33.020	43.335	57.549

Parameters .	D1 .	D2 .	D3 .	D4 .
pH	− 0.112	0.344	0.258	0.188
DO	− 0.355	0.007	− 0.176	− 0.548
Alk	0.112	− 0.147	0.432	0.185
EC	0.942	− 0.161	− 0.016	0.114
TDS	0.947	− 0.153	0.015	0.132
Ca2+	0.059	− 0.648	0.136	− 0.012
Mg2+	− 0.223	− 0.700	0.121	− 0.017
Cl−	0.428	0.060	− 0.177	0.449
	0.353	0.288	− 0.002	0.154
	0.941	− 0.166	− 0.076	0.096
	− 0.385	0.806	0.079	0.008
	0.034	− 0.707	− 0.076	− 0.048
	− 0.019	0.093	0.765	0.266
Na+	− 0.073	− 0.177	0.483	− 0.236
K+	0.047	0.312	0.611	0.042
F−	0.033	0.478	0.567	0.187
COD	0.415	0.139	0.353	0.585
BOD	0.544	0.167	0.236	− 0.254
TC	− 0.054	0.119	0.019	0.929
FC	− 0.026	0.050	0.043	0.879
Eigenvalue	4.319	3.245	2.184	1.763
% of Variance	19.061	13.958	10.315	14.214
Cumulative %	19.061	33.020	43.335	57.549

Four principal components (PCs) accumulated 57.54% of the total variance in which PC1 represent 19.06%, PC2 represent 13.95%, PC3 represent 10.31% and PC4 represent 14.21%. Eigenvalues of these four PCs (D1-D4) with bold values considered as moderate to strong loading to demonstrate the compositional relationship and grouping pattern between variables.

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Understanding of hydrochemical analysis suggests that multifaceted hydrochemical processes and numerous sources of contaminants influence the study area. The results indicated that mineral dissolution, climatic factors, geological setting, oxidation of ammonium and organic matter and anthropogenic inputs influence the water quality of the region. The weathering of minerals is the most imperative process that has controlled the water chemistry of the study area. The river water is moderately alkaline with high TDS and EC. The water type of the river is Ca²⁺–Mg²⁺– followed by Na⁺–K⁺–Cl⁻– and Ca²⁺–Mg²⁺– Cl⁻– which suggest the major role of carbonate, gypsum and dolomite weathering in the chemical composition of water. The availability of and showed that the river water is highly influenced by agricultural runoff and industrial discharge, which mainly includes nitrogenous fertilizer and organic wastes. The higher value of COD, BOD, TC and FC indicates organic pollution in the river due to domestic and industrial discharge. PCA determined seven PCs, which concluded the dominancy of geogenic activities, atmospheric deposition and anthropogenic sources on the river water quality. WQI and CA classified the 19 sites into four groups based on rating scale and statistical relation respectively. River water is trending toward deterioration condition and is presently unsuitable for drinking and agriculture purposes. Therefore, water should be treated before application for agriculture and drinking purposes. Specific technology for defluoridation, desalination and bacterial disinfection by conventional treatment methods needs to be considered in contaminated areas. The Ajay River water needs proper management practices with some inclusive techniques so that it can be utilized for drinking and agriculture purposes. This study introduced some environmental procedures for the interpretation of voluminous data, the effect on water quality according to land-use pattern, hydro-climatic factors on surface water chemistry, characterization and identification of pollution sources and comprehensive assessment of spatial and temporal variation. These findings will help significantly in better understanding the hydro-geochemistry of surface water bodies and their pollution sources at the global level.

The authors would like to thank the University Grants Commission (UGC) Government of India (F. No. 42- 437/2013 (SR)), for the financial grant through the major research project. We wish to thank the editor and the anonymous reviewers for their suggestions and critical comments.

The authors declare that the submitted manuscript is original. They also acknowledge that the current research has been conducted ethically and all authors have agreed on the final shape of the study.

The authors consent to participate in this research study.

The authors consent to publish this research study.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.