The Chenab River has always offered a cradle for civilizations in Punjab province of Pakistan; however, in recent times, the quality of this river has been gradually degraded due to several point and non-point pollution sources being introduced in its water. The riverine water quality was evaluated to check the suitability of water for drinking, livestock and irrigation purposes. Water samples (n = 54) were collected across the river, over a period of three years (2012–2014) and subjected to physicochemical analysis. Water quality index rating revealed that the water of River Chenab fell under the marginal category for drinking and livestock watering, due to the presence of heavy metals pollution above safe limits. Irrigation suitability parameters, such as the sodium absorption ratio (SAR), residual sodium carbonate (RSC), Na (%), Kelley's ratio (KR), magnesium hazard (MH) and the permeability index (PI) were measured, and most of the samples were within the safe limit. The piper classification of hydro-chemical parameters revealed that the alkaline-earth metals and strong acids exceed the alkali metals and weak acids, respectively. A Wilcox diagram indicated the alkali hazard was low while salinity hazard has an increasing trend. Spatiotemporal distribution of the pollutants highlighted minimal pollution until Qadirabad site (S4) which gradually keeps worsening at the downstream sites. Two factors of water quality deterioration were identified as pollution addition from the point and nonpoint sources, and diversion of the water through canals. It is inevitable to manage water quality of the Chenab River by reducing point sources pollution, through law enforcement.

  • Paper includes information regarding water toxicity for humans and animals.

  • At the same time, it is fit for irrigation.

Water is an essential component for the sustainment of life on earth. Humanity depends upon water for its survival, good health, and economic development (Malmqvist & Rundle 2002). Freshwater ecosystems have been the most exploited ecosystems by humans for thousands of years to the extent that only a few of them are now in natural state (Vaishali & Punita 2013). Rivers as a resource have never been an issue of concern until a recent population outburst that has triggered pressure on water resources (Qadir & Malik 2009). Population growth has reduced water availability and increased urbanization, industrialization, and intensified agriculture which leads to increased pressure on water resources (Engelman 1997). The agriculture sector consumes 80–90% of the freshwater supply (Morison et al. 2007). Pollution of rivers and their tributaries are more significant near urban stretches due to enormous amounts of wastewater containing hazardous elements are being discharged by urban activities (Ensink et al. 2010). Almost 90% of domestic and 75% of industrial effluents are normally discharged from urban areas (Briscoe et al. 2006). Especially Pakistan is struggling to develop its industrial sector and is not taking into account the problems associated with pollution (UNIDO 2000). The indiscriminate discharge of effluents into water bodies often contains toxic substances that render water unfit for different uses, including drinking, agriculture and aquatic life (Qadir et al. 2008; Mishra 2010; Gatica et al. 2012). The impacts of pollution on health, water resources productivity, and crop production are considerable and worsening (UNIDO 2000). The developed countries have been applying different techniques for the protection of water bodies. In contrast, surface water pollution is more evident in developing countries, which results in loss of productivity and becomes a health hazard (Bozzetti & Schulz 2004; Al-Shujairi 2013).

Pakistan is an agro-based economy and River Chenab is overexploited through water extraction for irrigation (Bhatti & Latif 2011). The Chenab River receives partial or untreated wastewater and agricultural runoff generated in its catchment (Qadir et al. 2008). The water quality assessment of Chenab River on the basis of its suitability for various consumption purposes needs to be closely monitored. Therefore, this study aims to evaluate the water quality of Chenab River spatially and seasonally on the basis of its different end uses including drinking, livestock watering, and irrigated agriculture.

Study area

The Chenab River originates from snowcapped peaks of Himalaya in Himachal Pradesh, India and enters into Pakistan in Sialkot district, upstream to Marala Barrage (74°–29′E and 32°–40′N). In Pakistan, it traverses from densely populated areas of the Punjab province. The catchment soil is fertile and the plain is formed by the deposition of the sediments from the Indus river and its tributaries. The soil is loamy and gradually becomes silty downstream. The sediments are characteristically calcareous. Climate of the catchment is extreme; it is sub-humid with foggy winters. In mid-February the temperature begins to rise and spring comes with pleasant weather which continues till mid-April. Summer is very hot especially in the river's lower reaches where desertic conditions prevail. The monsoon season starts in mid-July and August bringing lots of rains. The river delta is very fertile and most of the people are farmers, cotton and wheat are major cash crops. Other crops include sugarcane millet, rice, corn, oil-seeds, and pulses. Among vegetables, the potato is the most important crop, but ladyfinger, tomato, brinjal, onion, cabbage, among others, are also grown in the region. Fruits such as mango, guava, watermelon and orange are also grown. Livestock and poultry production are also important economic activities. The manufacturing industry in the catchment includes textiles, sports goods, heavy machinery, electrical appliances, surgical tools, vehicles, auto parts, sugar mills and fertilizer production.

Sample collection and analysis

The water samples were collected by strictly following the sampling guidelines established by the American Public Health Association (APHA 2005). Grab sampling technique was employed for sample collection and on-field water quality parameters, including temperature (T °C), total dissolved solids (TDS), electric conductance (EC) and pH were determined in the field using a pH and electrical conductivity (EC) meter (HANNA 9828, USA). After the field analysis, the samples were sealed, labeled, and preserved according to the concerned analytes. Water-quality analyses were carried out following the standard methods by the APHA (2005). TDS by method 2,540-C, Cl−1 by argentometry method (4500-B), by method 4500-D, K by method 3500-B, Ca by method 2340-C, Na by method 3500-B, Mg by 3500-Mg-B, sodium and potassium were determined by operating flame photometer (PFP 7 Jenway); hardness was tested by Complexometric (EDTA) Titration Method 2340-C. Heavy metals Cu, Cd, Cr, Fe, Pb were analyzed by Atomic Absorption Spectrometer (Perkin Elmer A Analyst 800). Carbonates and bicarbonates were determined by digital titration/USEPA 10244. The water samples were collected from nine sampling stations as shown in Figure 1. Sampling was done in two distinct phases, i.e. March–April representing pre-monsoon season and September monsoon season over the period of three years (2012–2014). The Canadian Water Quality Index values established by the Canadian Council of Ministers of the Environment (CCME 2001) were employed for the calculation of drinking water quality index using WHO and National Drinking Water Quality Standards Guidelines. The geochemical results are plotted using Aqua Chem 4.2 software and correlation analysis was carried out using Statistica 10.2 software.

Figure 1

Map of study area showing sampling points along Chenab River.

Figure 1

Map of study area showing sampling points along Chenab River.

Close modal

Water quality evaluation for drinking purposes

Experimental results obtained from water quality analyses and their corresponding descriptive statistics are presented in Table 1. River Chenab traverses from some areas where underground water is brackish and people use river water for drinking and livestock watering. The suitability of water of Chenab River for drinking purposes was evaluated using WHO Guidelines (2011) and National Drinking Water Quality Standards (NDWQS) as references in Table 1. The pH of the riverine water samples was ranged from 7.02 to 8.64. Previously, Bhatti & Latif (2011) and Khadse et al. (2016) reported the pH values of 8.1–8.3 and 8–8.5 from Chenab River in Pakistan and Jammu and Kashmir, respectively. In Pakistan, comparable pH values were reported by Qadir et al. (2008), Mahmood et al. (2014) and Eqani et al. (2015). Fluoride concentration range was 0.15–1.02 mg/L which complied with the limit. All the sampling sites had chlorides (10–220 mg/L) also within the limits. The maximum TDS contents determined from Chenab River was 550 mg/L with an average value of 210 mg/L, which was comparable with the study of Sharma et al. (2015) reporting 109–460 mg/L for river Manawar Tawi (a tributary of Chenab River).

Table 1

Descriptive statistics of water quality data from Chenab River, Pakistan

WHONDWQSMinimumMaximumStd. Dev.
pH 6.5–8.5 6.5–8.5 7.02 8.64 0.34 
TDS (mg/L) 1,000 1,000 110.00 550.00 95.00 
BOD (mg/L)  1.60 24.00 3.58 
Cl (mg/L) 250 250 10.00 220.00 55.00 
SO4 (mg/L) 500  18.00 240.00 43.90 
F (mg/L) 1.5 1.5 0.15 1.02 0.24 
Mg (mg/L) 50  0.00 32.00 7.09 
Na (mg/L) 200  2.50 145.00 38.24 
Ca (mg/L) 75  12.00 65.00 10.21 
K (mg/L) 10  1.50 8.00 4.27 
Cu (mg/L) 0.02 0.36 0.06 
Cr (mg/L) <0.05 0.05 0.001 0.38 0.07 
Cd (mg/L) 0.003 0.003 0.00 0.74 0.12 
Fe (mg/L) 0.30  0.08 4.12 0.97 
Pb (mg/L) 0.01 0.05 0.0022 0.98 0.15 
WHONDWQSMinimumMaximumStd. Dev.
pH 6.5–8.5 6.5–8.5 7.02 8.64 0.34 
TDS (mg/L) 1,000 1,000 110.00 550.00 95.00 
BOD (mg/L)  1.60 24.00 3.58 
Cl (mg/L) 250 250 10.00 220.00 55.00 
SO4 (mg/L) 500  18.00 240.00 43.90 
F (mg/L) 1.5 1.5 0.15 1.02 0.24 
Mg (mg/L) 50  0.00 32.00 7.09 
Na (mg/L) 200  2.50 145.00 38.24 
Ca (mg/L) 75  12.00 65.00 10.21 
K (mg/L) 10  1.50 8.00 4.27 
Cu (mg/L) 0.02 0.36 0.06 
Cr (mg/L) <0.05 0.05 0.001 0.38 0.07 
Cd (mg/L) 0.003 0.003 0.00 0.74 0.12 
Fe (mg/L) 0.30  0.08 4.12 0.97 
Pb (mg/L) 0.01 0.05 0.0022 0.98 0.15 

NDWQS, National Drinking Water Quality Standards.

The mean calcium concentration determined during the study was 30 mg/L (range: 12–65 mg/L) which was consistent to the findings of Sharma et al. (2015), i.e. 25.2–65.6 mg/L from, Manawar Tawi, a tributary of Chenab River in Jammu and Kashmir. In contrast Fotedar et al. (2010) reported calcium concentration ranging from 3.8 to 4.8 mg/L from the Chenab River and Kumar & Dua (2009) reported levels of 26–98 mg/L in the water of River Ravi (a tributary of Chenab) from India. Bhardwaj et al. (2010) from Chhoti Gandak river reported 6–36 mg/L. In present study, the magnesium mean concentration was found to be 8.4 mg/L (range 0–32 mg/L) which was higher than findings from Indian Chenab water (0.76–1 mg/L) and lower or to an extent comparable to those from Manawar Tawi (15.5–52.7 mg/L) while almost consistent 4.8–42 mg/L from Chhoti Gandak river with (Bhardwaj et al. 2010; Fotedar et al. 2010; Sharma et al. 2015) However, Sharma et al. (2015) recognized the anthropogenic activities along the River Manawar Tawi principally responsible for its pollution. The calcium and potassium concentrations across Chenab River varied from 1.5 to 8.0 mg/L, higher than the levels previously reported from upper reaches of Chenab River in India by Khadse et al. (2016) (i.e. 0.5–2.2). Sodium contents in the present study were found to be 2.5–145 mg/L, within the standard limit (200 mg/L) defined by WHO (2011). The Cd in the water of Chenab River was exceeding the limit value of 0.003 mg/L in 55% of the samples (WHO 2011). Cadmium is extremely toxic to human health and may lead to renal failure (Järup 2003). Similarly, chromium levels in 24% of water samples exceeded the WHO and NDWQS limit of 0.05 mg/L; maximum Cr concentration was found to be 0.38 mg/L at sampling station S5 (Chiniot), which was comparable with the findings of Saleem et al. (2015) from an adjacent river in Pakistan.

The maximum concentration of lead was 0.98 mg/L which is much higher than the standard limit of Pb is 0.01 mg/L (WHO 2004). In the upstream region, similarly, high levels of Pb concentration were reported in Tawi River, a major tributary to Chenab River from India. The atmospheric deposition of gasoline-associated Pb was identified as a principal source of Pb in riverine water (Sharma et al. 2015). The higher Pb concentrations were also previously reported from Indian segment of Chenab River (0.05–0.12 mg/L) (Fotedar et al. 2010) and Gobind Sagar Lake (0.850–3.680 mg/L), a lake in Himachal Pradesh, India (origin point of Chenab River) (Sharma & Walia 2015). The Pb concentrations were also observed relative higher during summer (wet period) as compared to the winter (dry period) which was similar to the trend reported by an Iraqi study (Al Obaidy et al. 2015). Pb in high concentration adversely affects the nervous system, damages gastrointestinal tract, kidneys, testes, and bones (Asonye et al. 2007). Pakistan Council of Research in Water Resources (2005) in its report of lead levels in major cities of Pakistan stated that the surface water has greater contamination as compared to the groundwater. Almost 15% of surface water and 1% of groundwater specimens had lead contamination above the permissible limits.

Iron is another important constituent that plays a vital role in the normal functioning of the human body. The mean iron concentration measured in the present study was 1.57 mg/L, while the standard limit value established by WHO (2004) is 0.3 mg/L. So, the high levels of heavy metals contamination in the River Chenab water makes it unfit for drinking purpose. Pakistan Council for Research in Water Resources reported that approximately 40% of the surface water samples collected during the year 2003–2004 were exceeded the standard iron limit (PCRWR 2005). Nonetheless, iron levels of the present study were much lower than those observed in the Gomati River, India (0.0–25.5 mg/L) and much higher than those reported for the Ebro River Spain (0.075–0.14 mg/L), River Beas, India (mean value. 0.41 mg/L) and west Bengal's water bodies (0.1–0.53 mg/L) (Singh et al. 2005; Bouza-Deaño et al. 2008; Samanta et al. 2013; Sharma & Walia 2016). The iron concentrations found in the present study were comparable to those reported for the Ganga River (0.013–5.49 mg/L) (Aktar et al. 2010). Iron is also contributed from natural sources as the Pir Panjal range in Jammu and Kashmir has ferro-magnesium mineral deposits adding Fe via weathering and erosion process (Jeelani et al. 2014). A summary with the comparison of selected variables from this work with other studies is presented in Table 2.

Table 2

Comparison of selected variables of the current study with previous studies

River name and locationpHCa (mg/L)Mg (mg/L)K (mg/L)Na (mg/L)Pb (mg/L)Fe (mg/L)Reference
Chenab, Pakistan 7.02–8.64 12–65.6 0–32 1.5–8 2.5–145 0.002–0.195 0.08–4.12 Present study 
Adyar, India 6.2–9.1 32–288 9.6–105.6 0–58.9 27–1,750 – – Venugopal et al. (2009)  
Gomti, India 6–8.9 5.1–80 0.16–41 2.2–12.1 7.9–85.5 0–0.146 0–25.5 Singh et al. (2005)  
Chocancharava, Argentina 8.07–8.43 36–40  3.4 22–30  – Gatica et al. (2012)  
Ebro, Spain. 7.8–8 56–121 8.4–26.3 1.5–3.9 6–123  0.075–0.14 Bouza-Deaño et al. (2008)  
Beas, India 0.736 13 4.62 1.5 13.22 0.01 0.41 Sharma & Walia (2016)  
Ganga, India 6.7–7.3 – – – – 0.05–0.53 0.013–5.49 Aktar et al. (2010)  
Water bodies of West Bengal, India 7.56–8.39 14–33 0.98–4.39 6.6–7.93 8.63–26.97  0.1–0.53 Samanta et al. (2013)  
Manawar Tawi, India 6.2–8.9 25.2–65.6 15.5–52.7 – – – – Sharma et al. (2015)  
Chenab, India  3.8–4.8 0.76–1 1.06–2.25 1.06–2.03 0.05–0.12 0.39–0.62 Fotedar et al. (2010)  
Chhoti Gandak, India 6.24–8.61 6–36 4.8–41 2.8–116 12–86 – – Bhardwaj et al. (2010)  
Jhelum, Pakistan 7.0–7.4 40–55 36–45 7.1–8.6 24–40 – 2.62–3.98 Iqbal et al. (2017)  
River name and locationpHCa (mg/L)Mg (mg/L)K (mg/L)Na (mg/L)Pb (mg/L)Fe (mg/L)Reference
Chenab, Pakistan 7.02–8.64 12–65.6 0–32 1.5–8 2.5–145 0.002–0.195 0.08–4.12 Present study 
Adyar, India 6.2–9.1 32–288 9.6–105.6 0–58.9 27–1,750 – – Venugopal et al. (2009)  
Gomti, India 6–8.9 5.1–80 0.16–41 2.2–12.1 7.9–85.5 0–0.146 0–25.5 Singh et al. (2005)  
Chocancharava, Argentina 8.07–8.43 36–40  3.4 22–30  – Gatica et al. (2012)  
Ebro, Spain. 7.8–8 56–121 8.4–26.3 1.5–3.9 6–123  0.075–0.14 Bouza-Deaño et al. (2008)  
Beas, India 0.736 13 4.62 1.5 13.22 0.01 0.41 Sharma & Walia (2016)  
Ganga, India 6.7–7.3 – – – – 0.05–0.53 0.013–5.49 Aktar et al. (2010)  
Water bodies of West Bengal, India 7.56–8.39 14–33 0.98–4.39 6.6–7.93 8.63–26.97  0.1–0.53 Samanta et al. (2013)  
Manawar Tawi, India 6.2–8.9 25.2–65.6 15.5–52.7 – – – – Sharma et al. (2015)  
Chenab, India  3.8–4.8 0.76–1 1.06–2.25 1.06–2.03 0.05–0.12 0.39–0.62 Fotedar et al. (2010)  
Chhoti Gandak, India 6.24–8.61 6–36 4.8–41 2.8–116 12–86 – – Bhardwaj et al. (2010)  
Jhelum, Pakistan 7.0–7.4 40–55 36–45 7.1–8.6 24–40 – 2.62–3.98 Iqbal et al. (2017)  

Water quality index for drinking water

A total of 15 water quality parameters (given in Table 1) were considered for the calculation of Water Quality Index (WQI) for Chenab River. On the temporal basis, the water quality of Chenab River followed the order as 2012 > 2014 > 2013. The mean WQI value for year 2012 was 82.2, while it was calculated to 62 and 65 for the year 2013 and 2014, respectively. During the 2014 monsoon, heavier rainfalls than the normal in the catchment caused excessive dilution, reducing pollution load. One of the reasons for pollution reduction was an electricity shortfall in 2012 (Dawn News 2012), the industrial and agriculture sectors faced 2,623 and 2,324 h per annum of load shedding respectively, resulting in low production and consequently truncated effluents reducing pollution load (USAID 2013). The WQI criteria is presented in Table 3 and the results are shown in Figure 2.

Table 3

Water quality ranking using CCME water quality index

WQI valueDegree of threatCondition of water
100–95 Non Excellent 
80–94 Minor Good 
65–79 Little Fair 
45–64 High Marginal 
0–44 Very High Poor 
WQI valueDegree of threatCondition of water
100–95 Non Excellent 
80–94 Minor Good 
65–79 Little Fair 
45–64 High Marginal 
0–44 Very High Poor 
Figure 2

Temporal variation in the water quality index of Chenab River during study period (i.e. 2012–14).

Figure 2

Temporal variation in the water quality index of Chenab River during study period (i.e. 2012–14).

Close modal

The seasonal variations indicated that the water quality was worse in the monsoon as compared to pre-monsoon. The deterioration in water quality might be attributed to the addition of contaminants through atmospheric deposition and surface runoff from the catchment (Bhardwaj et al. 2017), agriculture runoff, i.e. fertilizer and pesticides deposited on soil throughout the year find their way in the rainy season. Pakzadtoochaei & Einollahipeer (2013) from Iran reported the increase in Ni, Cu and Zn concentrations in the aquatic environment in monsoon and post-monsoon seasons. Similarly, high Pb concentration was noticed by Sharma & Walia (2015) from Gobind Sagar Lake who claimed it was coming from atmospheric deposition, as leaded petroleum products were used in the area. On the spatial basis, the overall water quality of Chenab River up to Qadirabad Barrage was good. The spatiotemporal water quality pattern across Chenab River revealed relatively poor water quality persists in wet seasons. However, the overall Water Quality Index for the year 2014 was comparatively better due to heavier rains than normal. The upstream most contamination source across the Chenab River in Pakistan includes the wastewater from Sialkot city, which comprises tanneries, surgical, textile, metallurgical and pharmaceutical industries (Ullah et al. 2009). Approximately 52 million L of wastewater is generated from Sialkot city each day, with ultimate disposal in Chenab River through various drains and streams (Qadir et al. 2008). In the midstream region, the Gujranwala city is inhibited with textile, dying, ceramic, electronics, metal utensils, kitchenware, and steel industry and Faisalabad city has substantial textile, fertilizer, sugar, and paper. Tanneries, Ni-Cr plating, ghee, and the textile sector have a significant amount of heavy metals industries (Hanif et al. 2005). Textile wastewater is usually alkaline and contains a substantial concentration of pollutants, including organic and inorganic matter, solids, oil, and grease content, while the paper industry contributes to organic matter and suspended solids. The bleaching of paper is a very environmentally degrading process as it produces complex chlorinated compounds UNIDO (2000). Whereas, in the downstream area, the Multan region contains a number of ghee, fertilizer and textile industries disposing untreated wastewater to the river's mainstream channel.

Assessment of water quality of Chenab River using different classification schemes

The water quality of Chenab River was also classified by considering various assessment criteria established by scientific reports (Table 4). The Sawyer & McCartly (1967) Classification involves distribution on the basis of total hardness levels in the water samples. The total hardness in the present study ranged from 67.2 to 225 mg/L. So, the water of Chenab River was classified as slightly hard water (75–150 mg/L) as 74% and 77% of the samples during pre-monsoon and monsoon seasons, respectively, fall under this class (Table 4). Following Davis & De-Wiest (1966), the TDS contents-based classification scheme of 100, 96% of the pre-monsoon and monsoon samples complied with TDS levels less than 500 mg/L.

Table 4

Classification of Chenab River water using different classification schemes

ParameterRangeWater classificationPre-monsoon (%age)Monsoon (%age)Reference
Hardness (mg/L) <75 Soft water 7.4 14 Sawyer & McCartly (1967)  
75–150 Slightly hard water 74 77 
150–300 Moderately hard water 18 
>300 Very hard water – – 
TDS (mg/L) <500 Appropriate for drinking 100 96 Davis & De-Wiest (1966)  
500–1,000 Acceptable for drinking – 3.7 
1,000–3,000 Appropriate for agriculture – – 
>3,000 Not appropriate for drinking/agriculture – – 
Cl (meq/L) <0.141 Extremely fresh – – Stuyfzand (1991)  
0.141–0.846 Very fresh 30 19 
0.846–4.231 Fresh 59 81 
4.231–8.462 Fresh to brackish 11 – 
8.462–28.206 Brackish – – 
28.206–282.064 Brackish salty – – 
CCME WQI for drinking 95–100 Excellent – – CCME (2001)  
80–94 Good 41 41 
65–79 Fair 26 26 
46–64 Marginal 33 33 
ParameterRangeWater classificationPre-monsoon (%age)Monsoon (%age)Reference
Hardness (mg/L) <75 Soft water 7.4 14 Sawyer & McCartly (1967)  
75–150 Slightly hard water 74 77 
150–300 Moderately hard water 18 
>300 Very hard water – – 
TDS (mg/L) <500 Appropriate for drinking 100 96 Davis & De-Wiest (1966)  
500–1,000 Acceptable for drinking – 3.7 
1,000–3,000 Appropriate for agriculture – – 
>3,000 Not appropriate for drinking/agriculture – – 
Cl (meq/L) <0.141 Extremely fresh – – Stuyfzand (1991)  
0.141–0.846 Very fresh 30 19 
0.846–4.231 Fresh 59 81 
4.231–8.462 Fresh to brackish 11 – 
8.462–28.206 Brackish – – 
28.206–282.064 Brackish salty – – 
CCME WQI for drinking 95–100 Excellent – – CCME (2001)  
80–94 Good 41 41 
65–79 Fair 26 26 
46–64 Marginal 33 33 

The Stuyfzand (1991) Classification, based upon chlorides contents in surface water, revealed that 59% of pre-monsoon and 81% of monsoon samples across Chenab River were under the freshwater category, and only 11% of samples of pre-monsoon samples from the study were classified as ‘fresh to brackish’ (4.231–8.462 mg/L). As far as CCME Water Quality Index is concerned, 41, 26 and 33% of water samples from Chenab in both seasons were found to be categorized as good, fair and marginal, respectively.

Water quality assessment for livestock

An adequate amount of good quality water is necessary for the good health of the livestock. Following the British Drinking Water Quality Guidelines for Cattle (Higgins et al. 2008). The pH of all the samples was well within safe limits (5–9). The total dissolved solids less than 1,000 mg/L were considered safe for livestock consumption. The standards for livestock consumption have established permissible limits of 0.05 mg/L for cadmium,1 mg/L for chromium, 0.5 mg/L for, copper, 2 mg/L for fluoride, and 0.1 mg/L for lead (Higgins et al. 2008). Therefore, Chenab's water was unfit for the livestock consumption as cadmium exceeds the limit of in 38% and most of the contamination was found in the lower reaches after Tarimmu barrage (S6) of the Chenab River. The concentration of cadmium increases where the agriculture activities and traffic density increased (Chen et al. 2000).

In contrast, the Pb contamination was found at the entry point of the river, meaning that the origin of the problem was on the other side of the border above the safe limits, which subsequently bioaccumulates in the food chain, so it is recommended not to use this water for livestock production. Pesticides, leaded gasoline, lead batteries production, and disposal units were primarily responsible for Pb addition to water bodies. Chiroma et al. (2007) reported increased heavy-metal concentrations after pesticide application with the maximum concentration in leaves. Akan et al. (2013) also reported heavy metals in vegetables. Chen et al. (2000) computed Pb concentration increases in intensively farmed areas.

Evaluation of Chenab River water for irrigation

The irrigation water quality is mainly dependent upon total dissolved solids and the types of salts dissolved in irrigation water (Khalaf & Hassan 2013). The salts present in irrigation water are mainly associated with the weathering of the rocks and composition of the soil in the catchment of any river. Nevertheless, the anthropogenic discharges, i.e. industrial and domestic effluents disposing off to the rivers have come up as a key source of high levels of dissolved salts in the irrigation water (Mohammed 2011; Singh et al. 2015). Therefore, the water suitability for irrigation was evaluated through i.e. sodium absorption ratio, sodium percentage, residual sodium carbonate, Kelley's ratio, permeability index, and magnesium hazard. The summary of the information is presented in Table 5.

Table 5

Surface water quality classification with respect to irrigation

ParameterLimitsClassificationMonsoon (%age)Pre-monsoon (%age)
EC Wilcox (1955)  100–250 Excellent 63 26 
250–750 Desirable 37 63 
750–2,250 Suspicious – 
>2,250 Poor – – 
SAR Wilcox (1955)  <10 Excellent 100 100 
18 Desirable – – 
18–26 Suspicious – – 
>26 Poor – – 
RSC <1.25 Safe 100 100 
1.25–2.5 Moderate – – 
>2.5 Unsafe – – 
% Na Wilcox (1955)  <20 Excellent 74 44 
20–40 Desirable 15 42 
40–60 Suspicious 10 
>80 Poor 3.7 3.7 
KR Kelley (1940)  <1 Desirable 89 85 
>1 Undesirable 11 15 
MH <50 Desirable 89 81 
>50 Unsuitable 11 19 
PI Doneen (1964>75% Excellent(C1)  5.5 3.7 
75–25% Desirable (C2) 78.5 92.6 
<25% Poor (C3) 16 3.7 
ParameterLimitsClassificationMonsoon (%age)Pre-monsoon (%age)
EC Wilcox (1955)  100–250 Excellent 63 26 
250–750 Desirable 37 63 
750–2,250 Suspicious – 
>2,250 Poor – – 
SAR Wilcox (1955)  <10 Excellent 100 100 
18 Desirable – – 
18–26 Suspicious – – 
>26 Poor – – 
RSC <1.25 Safe 100 100 
1.25–2.5 Moderate – – 
>2.5 Unsafe – – 
% Na Wilcox (1955)  <20 Excellent 74 44 
20–40 Desirable 15 42 
40–60 Suspicious 10 
>80 Poor 3.7 3.7 
KR Kelley (1940)  <1 Desirable 89 85 
>1 Undesirable 11 15 
MH <50 Desirable 89 81 
>50 Unsuitable 11 19 
PI Doneen (1964>75% Excellent(C1)  5.5 3.7 
75–25% Desirable (C2) 78.5 92.6 
<25% Poor (C3) 16 3.7 

Sodium absorption ratio (SAR)

The share of sodium in total dissolved solid needs to be assessed keenly as it decides the degree to which irrigation water tends to participate in cation-exchange reactions in soil (Raju 2007). Normally, if SAR is high then the rate of infiltration gets disturbed, water with high concentrations of Na+ and low concentration of Ca2+ has the problem that the ion-exchange complex becomes saturated with Na+ which deteriorates the soil structure (Fipps 2003; Raju 2007) and thus, in turn, reduces the growth of plants. Excessive salinity also disturbs the osmotic activity of plant and water and nutrient intake gets adversely affected (Ishaku et al. 2011). High levels of sodium make the soil hard that eventually becomes impermeable to the penetration of water (Dhembare 2012). Therefore, the SAR was measured using Richards (1954) formula as given in Equation (1):
formula
(1)

The SAR ranged from 0.125 to- 5.04 meq/L. The results were comparable with the values reported from Manka canal DG khan (0.39–2.04 meq/L), Damodar River, India (0.069–2.159 meq/L), Dynaneshwar Dam, India (0.17–3.87 meq/L) and Mahrut River, Iraq (0.18–3.61 meq/L) (Chughtai et al. 2011; Dhembare 2012; Gupta & Banerjee 2012; Al Obaidy et al. 2015). However, the SAR values from Ganaga River, West Bengal, India (0.397–1.49; 0.5–1.25 meq/L) were slightly lower than those reported in the present study (Joshi et al. 2009; Samanta et al. 2013). In contrast, Bhatti & Latif (2011) previously reported the SAR values 2.2–48 meq/L from Chenab's water which were much higher than the values observed in the present study.

Sodium percentage (% Na)

In addition to SAR, sodium percentage has been extensively used as a measure of water suitability for irrigation. The mathematical measurement of the parameter was proposed by Wilcox (1959) as given in Equation (2).
formula
(2)

Generally, Na percentage should not be greater than 60% in irrigation water (Nag & Lahiri 2012). Chenab River water was fit for irrigation only in 96.3% of samples in both seasons. The values observed in the present study ranges from 6.6% to 66.8% while Samanta et al. (2013) reported 33–45% from West Bengal, India.

Residual sodium carbonate (black alkali)

Residual sodium carbonate (RSC) is being calculated to check the adverse effects of both carbonates and bicarbonates ions (Aghazadeh & Mogaddam 2010). If the sum of carbonates and bicarbonates exceeds the collective concentration of calcium and magnesium, the water suitability for the irrigation becomes doubtful since low crop yield is prevalent in the areas with high RSC (Singh et al. 2015). Water with high contents of RSC has high alkalinity and long-term irrigation with such water makes the soil infertile. Moreover, excess of carbonates also reacts with sodium other than calcium and magnesium, producing sodium carbonate which forms black scales (Wadie & Abuljalil 2010; Dhembare 2012).
formula
(3)

The calculated values of RSC in the present study ranged from −4.324 to −0.462 meq/L. which was to an extent comparable with the values reported from Manka Canal (DG Khan) Pakistan (0–1.18 meq/L), Dynaneshwar Dam water (−0.3 to −8 meq/L, from Ghaggar River (−2.93–1.53 meq/L) and Mahrut River (−1.63 to −1.01 meq/L) (Chughtai et al. 2011; Dhembare 2012; Kundu 2012; Al Obaidy et al. 2015). The negative value of RSC shows the suitability of water for irrigation (Pawar et al. 1998). The water quality with respect to RSC was healthier in monsoon as compared to pre-monsoon.

Kelley's ratio (KR)

The relative amount of Na with respect to Ca and Mg is known as Kelley's ratio. The Kelley's ratio is calculated according to Equation (4).
formula
(4)

The value of Kelley's ratio less than <1 shows good quality water for irrigation and vice versa (Kelley 1940). The KR for the present study was ranged from 0.05 to 1.98 meq/L with 85% and 89% pre-monsoon and monsoon sample showed the KR value <1. Thus, the water quality of Chenab River was suitable for irrigation purposes as per Kelley's classification. Samanta et al. (2013) reported 0.08–0.36 meq/L from West Bengal, India.

Permeability index (PI)

The penetration of water in the soil is affected by the relative proportion of the ions, predominantly Na, Ca, Mg, and HCO3 ions (Singh et al. 2015). The Permeability Index (PI) assesses the water suitability for irrigation through Equation (5) established by Doneen (1964).
formula
(5)

The calculated values of PI in the current study were ranged from 13.5 to 82.5 meq/L (Table 5). Overall, 16% and 3.7% of the samples in monsoon and pre-monsoon, respectively, fell in the poor class (C3). A similar trend was observed by Joshi et al. (2009), where PI was higher in monsoon as compared to pre-monsoon.

Magnesium hazard (MH)

Magnesium is essential for plant growth. Its deficiency imparts yellow color in plant leaves between the veins (Gupta & Banerjee 2012) and its excess when absorbed by soils, affecting the physical structure of soil, and disrupting aggregation and friability of soil (Joshi et al. 2009; Rishi 2016). The magnesium hazard (MH) is calculated through (Equation (6)) as proposed by Szabolcs (1964).
formula
(6)

Irrigation water with MH values more than 50 is declared unfit for crop irrigation. The MH values observed in the present study ranges between 0.4 and −59 meq/L which show that the water of Chenab River in 89% and 81% samples of monsoon and pre-monsoon seasons respectively, was fit for irrigation. Similar results were reported from River Damodar (MH = 20.7–67.6 meq/L) by Gupta & Banerjee (2012). The detail findings regarding irrigation water quality parameters and their categorization criteria are presented in Table 5. A comparison of selected irrigation parameters from the current study with other studies of the region is presented in Table 6.

Table 6

Comparison of the irrigation parameters with other studies from the region

LocationSAR meq/LRSC meq/L%Na %agePI meq/LKR meq/LReferences
River Chenab, Pakistan 0.125–5.04 −4.324 to 0.462 6.6–66.8 13.5–82.5 0.05–1.98 Present study 
Mankan Canal D.G. Khan, Pakistan 0.39–2.04 0–1.18 – – – Chughtai et al. (2011)  
Mahrut River, Iraq 0.18–3.61 −1.63 to 1.01 – – – Al Obaidy et al. (2015)  
Burdwan District, Bangladesh 0.51–1.25 0.63–1.46 33.52–45.17 – 0.08–0.36 Samanta et al. (2013)  
Manawar Tawi, India 10.36–16.26 −1,935 to 763 11.25–17.96 10.88–17.59 – Zeeshan & Azeez (2016)  
Ganga River, India 0.397–1.49 <1.25 23.56–52.35 – – Joshi et al. (2009)  
Ghagger River system, India 0.693–10.3 −2.93 to 1.53 18.89–77.4 45.2–88.24 – Kundu (2012)  
Bogra District in Bangladesh 0.13–0.45 0.17–3.87 14.79–41.99 – 0.137–0.61 Islam & Shamsad (2009
Son River, India 0.17–1.96 −6.08 to 0.58 15.4–35.6 – – Maharana et al. (2015)  
Damodar River 0.06–2.15 −2.223 to 1.72 10.2–53.3 40–143 – Gupta & Banerjee (2012)  
LocationSAR meq/LRSC meq/L%Na %agePI meq/LKR meq/LReferences
River Chenab, Pakistan 0.125–5.04 −4.324 to 0.462 6.6–66.8 13.5–82.5 0.05–1.98 Present study 
Mankan Canal D.G. Khan, Pakistan 0.39–2.04 0–1.18 – – – Chughtai et al. (2011)  
Mahrut River, Iraq 0.18–3.61 −1.63 to 1.01 – – – Al Obaidy et al. (2015)  
Burdwan District, Bangladesh 0.51–1.25 0.63–1.46 33.52–45.17 – 0.08–0.36 Samanta et al. (2013)  
Manawar Tawi, India 10.36–16.26 −1,935 to 763 11.25–17.96 10.88–17.59 – Zeeshan & Azeez (2016)  
Ganga River, India 0.397–1.49 <1.25 23.56–52.35 – – Joshi et al. (2009)  
Ghagger River system, India 0.693–10.3 −2.93 to 1.53 18.89–77.4 45.2–88.24 – Kundu (2012)  
Bogra District in Bangladesh 0.13–0.45 0.17–3.87 14.79–41.99 – 0.137–0.61 Islam & Shamsad (2009
Son River, India 0.17–1.96 −6.08 to 0.58 15.4–35.6 – – Maharana et al. (2015)  
Damodar River 0.06–2.15 −2.223 to 1.72 10.2–53.3 40–143 – Gupta & Banerjee (2012)  

Wilcox classification for irrigation water quality assessment

A Wilcox (1955) diagram was employed in the present study through utilization of the sodium absorption ratio (SAR) and electrical conductivity (to assess the salinity hazard to crops) values to explain the suitability of irrigation water for agriculture. The Wilcox diagram shown in Figure 3 indicates that all the samples fall under the class 1 (i.e. S1) of the sodium hazard, depicting low levels of alkali-associated hazard to the soil. Similarly, the samples fall under the salinity hazard categories of low (C1) and medium (C2) hazard classes.

Figure 3

Sodium absorption ration and specific conductance in evaluating the suitability of water of River Chenab for irrigation. (Units for conductivity are micro ohms/cm). Wilcox diagram, Wilcox (1955).

Figure 3

Sodium absorption ration and specific conductance in evaluating the suitability of water of River Chenab for irrigation. (Units for conductivity are micro ohms/cm). Wilcox diagram, Wilcox (1955).

Close modal

Geochemical evaluation of Chenab River water using Piper diagram

A Piper diagram (diamond-shaped) is helpful in describing the relative contaminants concentration and their internal relationship with each other that helps in classifying water on the basis of different chemical properties. Back and Hanshaw's method of classification for a diamond of a Piper diagram was used for explanation Figure 4. The central diamond, cationic and anionic field of Piper diagram were explained on the basis of subdivisions (Figure 5).

Figure 4

Back and Hanshaw classification diamond of Piper diagram for explanation of water type on the basis of their position in the field (Back 1961; Hanshaw 1965).

Figure 4

Back and Hanshaw classification diamond of Piper diagram for explanation of water type on the basis of their position in the field (Back 1961; Hanshaw 1965).

Close modal
Figure 5

Piper diagram for chemical analyses major ion of Chenab River water (Piper 1944).

Figure 5

Piper diagram for chemical analyses major ion of Chenab River water (Piper 1944).

Close modal

The number of samples fall under each sub-division are as under the following:

  • 1.

    The subdivision 1 shows the percentage of samples in which alkaline earth metals (Ca2+, Mg2+) exceeds alkalies (Na+1, K+1) in 87% samples.

  • 2.

    The second subdivision depicts the percentage of samples in which alkali metals (Na+1, K+1) exceed alkaline earth (Ca2+, Mg2+) 13% samples.

  • 3.

    Weak acids ( + ) exceeds strong acids ( + Cl−1) 12%.

  • 4.

    Strong acids ( + Cl−1) exceeds weak acids ( + ) 88%.

  • 5.

    Only 9% of the samples fall in the field 5 showing the share of carbonate hardness.

  • 6.

    Field 6 depicts non-carbonate hardness, 40%.

  • 7.

    The 9% of samples were in the field 7 representing chloride type.

  • 8.

    No sample fall in sodium bicarbonate type.

  • 9.

    The no dominant field (9) has 17% of samples which specifies the transitional chemical character having none of dominant cationic or anionic pair.

Considering the cationic field of the Piper diagram it shows that 65% of water samples fall in Ca+2 dominant category and only 13% in Na+1+K+1 dominant category and 22% of water samples fall in no dominant class. On the other hand, in the anionic triangle, 60% of the samples come in Cl−1 dominant class, 7% each in + and dominant class. The remaining 26% of the samples show no dominant class.

Major ions chemistry

In the present study, the relative abundance of cation was Ca+2 > Na+1 > Mg+2 > K+1 constituting 50, 25, 22 and 2% of the total cations, respectively. Maharana et al. (2015) reported from Son River, India almost the same results where Ca+2 and Mg+2 accounted for 52% and 25% of the total cation concentrations. Whereas, anions were dominated by Cl−1 with 60% followed by (19.5%) and (16%). Fluoride contribution was very little towards the total anion. Whereas in Son River was the dominating contributor with 75% of total anions followed by Cl−1 (16.6%) and (5.7%).

Correlation matrix for surface water of Chenab River

The correlation analysis of 22 water quality parameters was performed and the results are presented in Table 7. The results expressed a moderate-negative correlation between DO and organic load, i.e. BOD5 (−0.57) and COD (−0.62), and a strong-positive correlation of BOD5 with COD (0.94) as expected. BOD5 has a strong correlation with TDS (0.78) and EC (0.78) and a moderate correlation with Cl−1(0.71) (0.68) and F−1 (0.59).

Table 7

Correlation data of water-quality parameters of the Chenab River

pHDOCODBODTHECTDSCaMgNaKCLHCO3SO4FCdCuCrFePbRSCSAR
pH 1.00                      
DO 0.09 1.00                     
COD 0.06 −0.62 1.00                    
BOD 0.02 −0.57 0.94 1.00                   
TH 0.07 −0.40 0.53 0.58 1.00                  
EC −0.19 −0.55 0.73 0.78 0.66 1.00                 
TDS −0.19 −0.55 0.73 0.78 0.66 1.00 1.00                
Ca 0.31 −0.17 0.43 0.52 0.59 0.50 0.50 1.00               
Mg −0.12 −0.39 0.37 0.37 0.84 0.48 0.48 0.06 1.00              
Na −0.25 −0.38 0.42 0.44 0.01 0.68 0.68 0.29 −0.18 1.00             
−0.02 −0.30 0.33 0.41 0.29 0.50 0.50 0.57 −0.03 0.64 1.00            
CL −0.14 −0.60 0.61 0.71 0.50 0.91 0.91 0.53 0.27 0.75 0.62 1.00           
HCO3 −0.03 0.27 −0.10 −0.20 0.26 −0.07 −0.07 −0.13 0.41 −0.33 −0.15 −0.27 1.00          
SO4 −0.30 −0.52 0.61 0.68 0.42 0.89 0.89 0.34 0.29 0.70 0.35 0.85 −0.32 1.00         
−0.25 −0.37 0.53 0.59 0.42 0.75 0.75 0.32 0.30 0.58 0.52 0.76 0.00 0.62 1.00        
Cd 0.27 −0.24 0.01 −0.03 0.08 −0.22 −0.22 −0.02 0.12 −0.36 −0.12 −0.13 −0.04 −0.37 −0.06 1.00       
Cu 0.30 −0.26 0.30 0.38 0.38 0.21 0.20 0.38 0.22 −0.03 0.27 0.30 −0.13 −0.01 0.20 0.38 1.00      
Cr 0.48 −0.18 0.33 0.35 0.19 −0.11 −0.11 0.10 0.16 −0.29 −0.04 −0.13 −0.11 −0.18 −0.15 0.15 0.42 1.00     
Fe 0.28 −0.36 0.25 0.27 0.25 0.05 0.05 0.21 0.18 −0.11 0.29 0.20 0.09 −0.16 0.32 0.56 0.55 0.30 1.00    
Pb 0.15 −0.31 0.08 0.15 0.01 0.03 0.03 0.14 −0.09 0.14 0.32 0.17 −0.23 0.05 −0.03 0.06 0.23 0.29 0.29 1.00   
RSC −0.05 0.52 −0.54 −0.65 −0.71 −0.64 −0.64 −0.60 −0.48 −0.23 −0.37 −0.65 0.45 −0.62 −0.38 −0.06 −0.44 −0.22 −0.13 −0.17 1.00  
SAR 0.31 0.14 −0.16 −0.22 0.05 −0.53 −0.53 −0.18 0.18 −0.69 −0.41 −0.61 0.30 −0.60 −0.50 0.34 0.14 0.54 0.11 0.09 0.18 1.00 
pHDOCODBODTHECTDSCaMgNaKCLHCO3SO4FCdCuCrFePbRSCSAR
pH 1.00                      
DO 0.09 1.00                     
COD 0.06 −0.62 1.00                    
BOD 0.02 −0.57 0.94 1.00                   
TH 0.07 −0.40 0.53 0.58 1.00                  
EC −0.19 −0.55 0.73 0.78 0.66 1.00                 
TDS −0.19 −0.55 0.73 0.78 0.66 1.00 1.00                
Ca 0.31 −0.17 0.43 0.52 0.59 0.50 0.50 1.00               
Mg −0.12 −0.39 0.37 0.37 0.84 0.48 0.48 0.06 1.00              
Na −0.25 −0.38 0.42 0.44 0.01 0.68 0.68 0.29 −0.18 1.00             
−0.02 −0.30 0.33 0.41 0.29 0.50 0.50 0.57 −0.03 0.64 1.00            
CL −0.14 −0.60 0.61 0.71 0.50 0.91 0.91 0.53 0.27 0.75 0.62 1.00           
HCO3 −0.03 0.27 −0.10 −0.20 0.26 −0.07 −0.07 −0.13 0.41 −0.33 −0.15 −0.27 1.00          
SO4 −0.30 −0.52 0.61 0.68 0.42 0.89 0.89 0.34 0.29 0.70 0.35 0.85 −0.32 1.00         
−0.25 −0.37 0.53 0.59 0.42 0.75 0.75 0.32 0.30 0.58 0.52 0.76 0.00 0.62 1.00        
Cd 0.27 −0.24 0.01 −0.03 0.08 −0.22 −0.22 −0.02 0.12 −0.36 −0.12 −0.13 −0.04 −0.37 −0.06 1.00       
Cu 0.30 −0.26 0.30 0.38 0.38 0.21 0.20 0.38 0.22 −0.03 0.27 0.30 −0.13 −0.01 0.20 0.38 1.00      
Cr 0.48 −0.18 0.33 0.35 0.19 −0.11 −0.11 0.10 0.16 −0.29 −0.04 −0.13 −0.11 −0.18 −0.15 0.15 0.42 1.00     
Fe 0.28 −0.36 0.25 0.27 0.25 0.05 0.05 0.21 0.18 −0.11 0.29 0.20 0.09 −0.16 0.32 0.56 0.55 0.30 1.00    
Pb 0.15 −0.31 0.08 0.15 0.01 0.03 0.03 0.14 −0.09 0.14 0.32 0.17 −0.23 0.05 −0.03 0.06 0.23 0.29 0.29 1.00   
RSC −0.05 0.52 −0.54 −0.65 −0.71 −0.64 −0.64 −0.60 −0.48 −0.23 −0.37 −0.65 0.45 −0.62 −0.38 −0.06 −0.44 −0.22 −0.13 −0.17 1.00  
SAR 0.31 0.14 −0.16 −0.22 0.05 −0.53 −0.53 −0.18 0.18 −0.69 −0.41 −0.61 0.30 −0.60 −0.50 0.34 0.14 0.54 0.11 0.09 0.18 1.00 

Total hardness (TH) has a strong correlation with Mg+2 (0.84), and a moderate correlation with Ca+2 (0.59), indicating that most of the hardness was due to salts of Mg+2 and Ca+2 was responsible to a lesser extent, while Mg+2 has shown a moderate correlation with (0.41), which indicates temporary hardness due to Mg+2. On the other side, Mg+2 has a weak correlation with Cl−1 (0.27) and (0.29) indicating that most of the hardness due to Mg+2 was temporary. However, very strong correlations of EC and TDS with Cl−1 (0.91) and (0.89) were observed, and moderate correlation with Na+1 (0.68) and F−1 (0.75). Strong correlations of Na+1 with Cl−1 (0.75), (0.7) and F−1 (0.58) have shown an anthropogenic contribution of sodium in its different forms. The most important source of chloride in the surface water is municipal sewerage; a high level of chloride acts as an indicator of sewage addition (Koli & Ranga 2011). Sodium chloride and sulfate are used in the textile sector to improve the affinity of the dyestuff to fibers and lowering of its solubility in the solution (Giwa & Ogunribido 2012). Moreover, NaCl is being used in tanneries as dehydrating and antiseptic agents in hide preservation (Dettmer et al. 2013). Whereas, the NaF has been used in metal processing, fertilizers, and glass-manufacturing industries (Shen et al. 2003).

Potassium has a moderately strong correlation with Cl−1 (0.62) showing the geochemical behavior of K and natural contribution; in the earth crust, potassium is mostly present in the form of chlorides and sulfate. The major ores of potassium are sylvite (KCl), the carnalite (KCl.MgCl2.6H2O), langbeinite (K2SO4.2MgSO4), and the polyhalite (K2SO4.MgSO4.2CaSO4.2H2O). Potassium has a relatively weak correlation with SO4 (0.35) representing the relatively poor contribution from nature. A low correlation of with Ca+2 (0.34) has shown that the gypsum has no significant contribution in ions added to the water of Chenab River (Islam & Shamsad 2009).

The overall assessment showed that tanneries and the textile industry were among the major pollutants along with fertilizer glass industry, while heavy metals were added from both point and nonpoint sources (atmospheric depositions, fertilizer, pesticides, along with industry). Most of the lead and iron are contributed from the other side of the border.

The water of Chenab River is neutral to alkaline, fresh and moderately hard. The order of abundance of major cation was Ca > Na > Mg > K while anions were in Cl > SO4 > HCO3 > F. The water of Chenab is dominated by alkaline earth metals; overall, water is Cl-Ca-HCO3 and SO4-Na-Cl. The results acquired during this study indicated the pollution propensities of Chenab River waters attributable to anthropogenic activities and the contribution of natural processes were negligible. The water of Chenab previously gave life to its users has become misfit for human consumption as well as livestock consumption, due to pollution addition from point and nonpoint sources of heavy metals. One-third of water samples fall in the marginal category with respect to WQI for drinking. The major source of heavy metals is the weathering of rock minerals, pesticides, industrial activities, and air pollution. Lead and iron are also contributed from Indian-occupied areas. Whereas water was fit for irrigation with a few exceptions, there was a minor salinity hazard to the crops. The water quality of Chenab is deteriorating gradually due to pollution. There is an alarming need to control domestic, industrial, and agriculture pollution.

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

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