Groundwater chemistry and groundwater quality index incorporating health risk weighting in Dingbian County, Ordos basin of northwest China

Journal Pre-proof Groundwater chemistry and groundwater quality index incorporating health risk weighting in Dingbian County, Ordos basin of northwest China Jianhua Wu, Yuxin Zhang, Hui Zhou

PII:

S0009-2819(19)30122-9

DOI:

https://doi.org/10.1016/j.chemer.2020.125607

Reference:

CHEMER 125607

To appear in:

Geochemistry

Received Date:

27 November 2019

Revised Date:

28 January 2020

Accepted Date:

31 January 2020

Please cite this article as: Wu J, Zhang Y, Zhou H, Groundwater chemistry and groundwater quality index incorporating health risk weighting in Dingbian County, Ordos basin of northwest China, Geochemistry (2020), doi: https://doi.org/10.1016/j.chemer.2020.125607

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Groundwater chemistry and groundwater quality index incorporating health risk weighting in Dingbian County, Ordos basin of northwest China

Jianhua Wu1, 2* [email protected]; [email protected], Yuxin Zhang1, 2, Hui Zhou1, 2

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School of Water and Environment, Chang’an University, No. 126 Yanta Road, Xi’an 710054,

Shaanxi, China 2

. Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region of the Ministry of

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Education, Chang’an University, No. 126 Yanta Road, Xi’an 710054, Shaanxi, China

*

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Fax: 86-29-82339281; Tel: 86-29-82339383

Abstract: Groundwater is essential to secure the safety of water supply in the Ordos basin, China. In

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this study, 35 groundwater samples were collected from part of the Dingbian County, a significant

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part of the Ordos energy base in China, and were analyzed for 17 physicochemical parameters. The health risk was quantified through the model recommended by the United States Environmental Protection Agency (USEPA). In addition, water quality index (WQI), which is incorporated with

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human health risk weighting, was adopted to evaluate the overall groundwater quality. The results show that groundwater in the study area is slightly alkaline water, and the hydrochemical types of groundwater is mainly HCO3-Na, HCO3-Na·Mg·Ca and mixed SO4·Cl-Na types. The non-carcinogenic health risks follow the order: NO3->F->Cr6+>As>NO2->Mn, and the carcinogenic risks is mainly contributed by Cr6+. Children face higher risks than adults, and most groundwater samples are associated with unacceptable health risks for both adults and children. WQI results show that poor quality water and very poor quality water account for 11.43% and 17.14% of all sampled

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groundwater, respectively, which are not suitable for drinking. In terms of sodium hazard nearly half of the groundwater samples are not suitable for irrigation. The results of this study will be helpful in groundwater management and protection in this area, and the health risk weighting method can be referenced by international scholars.

Keywords: Groundwater environment; Water quality index; Health risk assessment; Irrigation purpose; Ordos basin

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1. Introduction

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A large number of people from different countries depend on groundwater to meet their daily needs, because groundwater has generally good quality and can be used for multiple purposes

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(Adimalla et al. 2018; Chakraborti et al. 2016; Duraisamy et al. 2018; He and Wu 2019a; Li et al. 2016a; Wang et al. 2019; Wu et al. 2019a). Especially, groundwater is the dependable source of water

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supply in the arid and semi-arid regions (Li et al. 2018a; Masindi and Abiye 2018). However, as a result of global climate change and population growth, the rainfall in the arid and semi-arid regions is

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likely to decline and the demand of groundwater will undoubtedly increase accordingly. This will increase the water crisis in many regions. What’s worse, groundwater contamination induced by increasing human activities will reduce the groundwater availability, aggravating the water crisis in

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the arid and semi-arid regions (He et al. 2019a; Masindi and Abiye 2018). The Ordos basin is located in the arid and semi-arid region of northwest China, and hosts a large coal and oil reserve (Li et al.

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2013a; Qian et al. 2016). Because of the intensive exploitation of oil and coal resources, groundwater pollution in the basin is becoming more and more serious (Qian et al. 2016; An and Lu 2018a, b). Therefore, it is urgent to carry out comprehensive groundwater quality studies to understand the

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status and impacts of groundwater pollution in this basin. In arid and semiarid regions, many concerns have been raised about the quality and sustainability

of water supplies (Li and Qian 2018). Both natural factors and human activities have adverse impacts on the groundwater quality. As revealed by He et al. (2019b) and He and Wu (2019b), the land use/land cover changes will have significant impacts on groundwater quality and associated health risks. As a consequence, some groundwater may become saline and unsafe under intense human activities, which is unsuitable for direct consumption and may cause waterborne diseases to human 2

(Chidambaram et al. 2016; Li 2016; Su et al. 2016). High quality groundwater is essential for domestic, industrial and agricultural purposes, but contaminated groundwater may exert high health risks to humans and other lives (Li et al. 2016b; Su et al. 2016; Li et al. 2018a; Wang et al. 2018). Drinking water intake of the hazardous contaminants in groundwater is one of the main factors affecting human health and mortality (Li et al. 2014, 2019a; Su et al. 2016). As such, it is essential to evaluate the groundwater quality and assess the health risk of groundwater to determine the suitability of it for multiple purposes and to provide a scientific support for groundwater management and protection.

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In recent years, many studies on groundwater quality and health risks have been carried out (He

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et al. 2019a; Wu and Sun 2016; Li et al. 2016b, 2019a, b). For example, Yang et al. (2012) assessed

the health risks of groundwater in North China plain for drinking and dermal exposure pathways, and

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concluded that the health risk through drinking water intake is much higher than that via dermal contact. A study carried out by Liang et al. (2016) assessed the human health risk of As in drinking

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water in Pingtung Plain of Taiwan, which considered the factors such as gender, water consumption rate, As concentration, and body weight. Most of these health risk assessment studies were carried out

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following the USEPA models. However, there are also some Chinese scholars who adopted the assessment models recommended by the Ministry of Environmental Protection of China to quantify the health risks. For instance, He and Wu (2019a) assessed the health risks from Cr6+ and NO3−

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through drinking water intake, while Li et al. (2016b) considered the oral and dermal contact

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pathways in the health risk assessment following the Chinese models which adopted model parameters appropriate for Chinese people. In terms of overall groundwater quality evaluation, Su et al. (2016) used the entropy weighted water quality index (EWQI) to analyze the groundwater quality

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in Dingbian County. WQI is considered the easiest approach to quantify the suitability of water for multiple purposes. The EWQI was proposed by Li et al. (2010) and has now been widely used by international scholars (Amiri et al. 2014; Li et al. 2018b; Su et al. 2018; Wu et al. 2011). Fuzzy comprehensive method was adopted by He and Wu (2019a) in groundwater pollution assessment and the results can help local authorities to make scientific decisions for groundwater exploitation and protection. In addition, Li et al. (2018c) combined matter-element extension analysis and entropy weight theory to form an entropy matter-element extension analysis model for comprehensive

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groundwater quality assessment, and the method can avoid the uncertainties in water quality assessment. In many groundwater quality studies, however, researchers usually assign weight to each of the parameters according to the experts’ experience (Vasanthavigar et al. 2010; Tiwari et al. 2017; Adimalla et al. 2018; He et al. 2019a). Uncertainties may incur because of subjective judgment. To improve this, Yi et al. (2019) recommended the health risk weighting model (HRWM), which excludes the subjective factors in weighting process and assigns weights based on the health risk degrees of the pollutants. HRWM is recommended for drinking water quality parameter weighting, because the purpose of drinking water quality assessment is to secure the safety of water supply in

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terms of human health. HRWM which bases on the human health risk assessment results can better

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meet this purpose. In this study, WQI and HRWM were combined for the evaluation of groundwater quality.

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To completely understand the current status of groundwater quality in the study area, and to help local decision makers in groundwater quality protection and health risk reduction, the present study

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was carried out. The main objectives are to (1) conduct groundwater health risk assessment for facilitating groundwater quality protection and management (2) evaluate the groundwater quality

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using WQI and HRWM (3) determine the hydrochemical characteristics of groundwater and evaluate the groundwater quality for irrigation purpose. 2. Study area

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Dingbian County is situated in the northern part of Shaanxi Province, northwest of China. It is

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situated in the transition zone of the Chinese Loess Plateau and the Inner Mongolia Plateau. It is bounded by the Wushen County (Inner Mongolia Autonomous Region) in the north, Yanchi County (Ningxia Hui Autonomous Region) in the west, Huachi County and Huan County (Gansu Province)

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in the southeast, Wuqi County (Yanan City of Shaanxi Province) in the southeast, and Jingbian County (Yulin City of Shaanxi Province) in the east. The location of study area is presented in Figure 1.

Figure 1 should be placed here

The area is dominated by arid and semiarid climate, and belongs to the warm temperate

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continental monsoon climate zone with four distinct seasons. The average temperature of Dingbian County is 7.85℃, and the difference between the highest and lowest temperature in a year is 30.0℃. The annual average rainfall and evaporation rate is 360.55 mm and 2062.65 mm, respectively. Rainfall is the primary source of water for recharging the groundwater in this area. In this study area, groundwater can be classified into several types according to hydrodynamic characteristics, occurrence conditions and the types of aquifer. The pore water in loose Quaternary sediment exists mainly in the desert and plain area of the study area. The aquifer thickness is generally 10-50 m, and the groundwater level depth ranges from 2 to 8 m above the mean sea level.

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As for the Quaternary fissure water, which is mainly distributed in the loess gully and hilly regions,

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groundwater level depth is in the range of 30-90 m above the mean sea level. The specific yield of groundwater ranges from 67.65–156.79 m3/day. The Quaternary pore water and the fissure water

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mentioned above are the main exploited groundwater in the study area. The fissure water in the Cretaceous and Jurassic clastic rocks distributes mainly in the weathered bed rocks beneath the river

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valleys. As mentioned previously, groundwater here is recharged mainly by rainfall, and partially by condensation water and irrigation infiltration. Groundwater flow follows the geography and

3. Materials and Method

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3.1. Sample collection and analysis

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geomorphology, running from hills to the valleys.

In this study, 35 groundwater samples were collected. The locations of the sampling sites were

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recorded by portable GPS device, and were shown in the sketch map (Figure 1). Before the samples were collected, wells were pumped for at least 10 minutes until the chemical conditions of groundwater were in steady-state to ensure the reliability of sampled groundwater. All samples were

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collected in plastic polyethylene bottles which had been cleaned and rinsed for 3-4 times before sampling. For each sample, indices including common ions (Na+, K+, Ca2+, Mg2+, Cl-, SO42-, HCO3-), trace elements (Cr6+, NO3-, NO2-, F-, As, Fe, Mn), pH, total dissolved solids (TDS) and total hardness (TH) were analyzed. The samples for trace metal analysis were added HNO3 to ensure the stability of the elements. All physicochemical parameters were analyzed in the laboratory and the concentrations are expressed in mg/L, except pH which was measured in situ and was dimensionless. In terms of the methods of analysis, flame atomic absorption spectrometry was used to measure Na+ and K+; while 5

Ca2+, Mg2+ and TH was measured by EDTA titrimetric method; routine titrimetric methods was used for the measurement of Cl-, SO42- and HCO3-; traditional drying and weighing approach was taken to measure TDS; NO3- and NO2- were measured through ion chromatography method and Cr6+ was measured using plasma emission spectrometry. The sampling methods, procedures and treatment were conducted as per the national standard strictly. After analysis, the percentage of charge balance errors (%CBE) of all sampled groundwater was calculated to check the reliability of the analysis. The calculation of %CBE is as follows: %CBE =

(∑ cations−∑ anions) × (∑ cations−∑ anions)

100%

(1)

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The results of calculation in this study show that all sampled groundwater have a %CBE within ±5%, which means the physicochemical analyses of all samples are of high quality and the data are

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acceptable for further study. 3.2. Health Risk Assessment

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Because of the adverse health effects of exposure to contaminants in groundwater on human body, health risk assessment is necessary to be conducted to assure the safety of groundwater (Li et al.

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2014). The health risk assessment method consists of four steps, which was put forward by the National Academy of Sciences (NAS) (Li et al. 2014; Zhou et al. 2016; Zhu et al. 2019; Wang et al. 2018). They are hazard identification, dose–response assessment, exposure assessment and risk

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characterization (Liang et al. 2016; Su et al. 2016). In this study, Cr6+, As, NO3-, NO2-, F-, Mn were

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selected as the parameters in the health risk assessment and only drinking water intake was considered as the only exposure pathway because the risks from dermal contact is reported too low (Wu et al. 2019b).

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The formula of human health risk assessment is as follows (Zhou et al. 2016; Wu et al. 2019b; Zhang et al. 2018): CDI =

𝑐×IR×EF×ED BW×AT

(2)

Where, CDI means the daily average exposure dosage, mg/(kg·day); c denotes the concentration of the pollutant, mg/L; IR represents the drinking water intake rate, L/day; EF signifies the exposure frequency, day/year; and ED is the exposure duration, year; BW is the body weight, kg; AT is the average time, day; In the present study, the values of IR, EF, ED, BW and AT are assigned 1.5 L/d,

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365 days/year, 30 years, 60 kg and 10950 days for adults, respectively, and 0.7 L/d, 365 days/year, 6 years, 15 kg and 2190 days for children respectively. For the non-carcinogenic contaminants, the risk degree by hazard quotient (HQ): CDI

HQ = RfD

(3)

For the carcinogenic contaminants, the carcinogenic risk (CR) is computed as follows: CR = CDI × SF

(4)

Where, HQ and CR represent the hazard quotient and carcinogenic risks, respectively. RfD and SF denote reference dosage [(mg/(kg·day))−1] and the slope factor [mg/(kg·day)], respectively. For Cr6+,

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As, F-, NO3-, NO2- and Mn, the values of RfD are 0.003, 0.0003, 1.6, 0.06, 0.14 mg/(kg·day),

respectively (Arya et al. 2019; Karunanidhi et al. 2019). The values of SF for Cr6+ and As are 0.5 and 1.5 (mg/(kg·day))−1 (He et al. 2019a; Li et al. 2017). When HQ is greater than 1, and/or CR is higher

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than 1×106, the risk is considered unacceptable and measures must be taken to reduce the risk (He

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and Wu 2019a; He et al. 2019a; He and Li 2020). 3.3. Water quality index incorporating health risk weighting

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WQI is a common tool for the evaluation of the overall groundwater quality. It converts several key water quality parameters into a single index, and is widely adopted by scholars all over the world

follows: 𝑐𝑖𝑗 𝑠𝑗

) × 100

(5)

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WQI = ∑𝑛𝑗=1(𝑤𝑗 ×

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(Li et al. 2016a; He et al. 2019a; Yi et al. 2019). The WQI can be calculated by formula (5) as

Where wj is the weight for parameter j; sj denotes the standard value of the parameter j and cij denotes the observation data of the parameter j at the sampling site i. n signifies the total number of

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parameters considered in the assessment. Apparently, j ranges from 1 to n. The most important procedure for the assessment of groundwater quality using WQI is the

determination of the weight for each parameter (Yi et al. 2019). There are several methods or models being used for calculating the weight, such as the importance scale weighting model (ISWM) and the entropy weighting method (EWM) (Saleem 2016; Singh and Hussian 2016; Tiwari et al. 2017; Adimalla et al. 2018; Rabeiy 2018; Wu et al. 2015). The above mentioned weighting approaches are widely used, but both of them have some disadvantages. In terms of ISWM, it is difficult to generate

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a unique weight because the experts’ cognition is subjective. As for EWM, it is dependent solely on the objective calculation, but it often neglects importance of the indicator with a serious pollution condition. Therefore, Yi et al. (2019) proposed a new method, which assigns weights to parameters based on the health risk degree. Health risk weighting method (HRWM) is superior to other weighting methods because it incorporates the health risk degree obtained from the health risk assessment study. By doing this, the WQI can truly reflect the purpose of the water quality assessment studies: to understand the true effects of water quality on human health. In this study, 6 parameters are considered for the WQI

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calculation: Cr6+, As, NO3-, F-, NO2- and Mn. The formulae for calculating the weights for these

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parameters are as follows:

For a given sample, the total health risk can be calculated according to formula (6). R 𝑖 = ∑𝑛𝑗=1(HQ 𝑗 × 10−6 + CR𝑗 )

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(6)

The contributing percentage of parameter j to the total health risk is: HQ𝑗 ×10−6 +CR𝑗

(7)

R𝑖

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𝑝𝑖𝑗 =

Then the wj can be calculated by formula (7).

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𝑤𝑗 =

C+(∑𝑚 𝑖=1 𝑝𝑖𝑗 ) m C+(∑𝑚 𝑖=1 𝑝𝑖𝑗 ) 𝑛 ∑𝑗=1( ) 𝑚

(8)

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Where, m represents the total number of samples, i=1, 2,..., m. To ensure that the weight is rational, a constant C is added, and its value is 0.25 according to Yi et al. (2019). It should be noted that the

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HRWM is applicable to parameters that can induce health risks. For those parameters that will not cause health risks, using this approach to determine the weight is meaningless. Based on WQI obtained, groundwater quality can be classified into five levels: excellent quality

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water (WQI <25), good quality water (25< WQI <50), fair quality water (50 < WQI <100), poor quality water (100 < WQI <150), and very poor quality water (WQI>150) (Su et al. 2016; Yi et al. 2019).

3.4. Water quality for irrigation Water with high concentration of sodium could pose sodium hazard to soil and affects the growth of plants if it is used for irrigation. The sodium hazard can be expressed by SAR, which can also

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represents the capacity of soils to adsorb Na+ from irrigation water (Li et al. 2016a; Rabeiy 2018). Na% is another indicator indicating the sodium hazard of irrigation water (Li et al. 2016a). The soil permeability may be influenced by irrigation water with high contents of Na+, Ca2+, Mg2+ and HCO3− for a long time, so PI is a useful indicator for the assessment of irrigation water quality. The above mentioned three indices can be computed as follows (Li et al. 2016a; He et al. 2019a; Rabeiy 2018), where all ions are expressed in meq/L. Na+

(9)

2+ 2+ √(Ca +Mg ) 2

(Na+ +K+ )×100

Na% = (Ca2+ +Mg2++Na++K+) (Na+ +√HCO− 3 )×100%

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PI =

(10) (11)

(Ca2+ +Mg2+ +Na+ )

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SAR =

4. Results and Discussion

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4.1. Physicochemical parameters

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The physicochemical parameters of groundwater in this area were compared with the Chinese groundwater quality standards (General Administration of Quality Supervision, Inspection and

Table 1.

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Table 1 should be placed here

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Quarantine of China and Standardization Administration of China 2017). The results are given in

High salinity is a remarkable feature for groundwater in this study area, and the TDS value of

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groundwater varies considerably. It ranges from 91.13 to 8460 mg/L, with a mean of 2484.58 mg/L. There are only 14 fresh water samples (TDS<1000 mg/L). Among the rest samples, 8 samples belong to brackish water (1000
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(>3000 mg/L). TH values range from 31.24 to 3254 mg/L with a mean of 822.39 mg/L. Twenty samples are hard water with TH exceeding the permissible limit of 450 mg/L for drinking purpose. The TH value represents dissolved Ca2+ and Mg2+ contents in groundwater, and high TH groundwater may affect the taste of drinking water and reduce the effectiveness of the detergent. The pH represents the acidity or alkalinity of groundwater, and the permissible limit for drinking purpose is 6.5-8.5. In this study area, the pH of groundwater samples ranges from 7.37 to 8.41, with a mean of 7.89, which indicates that all sampled groundwater is suitable for drinking in terms of pH, and the 9

water is slightly alkaline in nature. As shown in Table 1, the relative abundance of the major cations in groundwater samples follows the order: Na+>Mg2+>Ca2+>K+. The mean of Na+ is 566.83 mg/L, and it’s much higher than the permissible limit (200 mg/L). There are 23 samples have a higher Na+ concentration than the limit. The means of Mg2+, Ca2+ and K+ are 148.90, 83.72 and 3.69 mg/L, respectively. High concentrations of Ca2+ and Mg2+ can affect the taste of drinking water and block the pipes of boilers, causing boiler explosion. K+ is an essential element for humans, and it seldom exceeds the permissible limit in drinking water (Singh et al. 2016). With respect to major anions in this study area, the relative

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abundance of major anions is as follows: SO42->Cl->HCO3-. The concentrations of SO42- and Cl- are

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relatively higher. Ninety and twenty one samples, respectively, show higher SO42- and Cl-

concentrations than the permissible limit for drinking purpose (250 mg/L for both indices) . A pie

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chart (Figure 2) was drawn based on the mean ion concentrations expressed in meq/L. It can be concluded from the chart that Na+ is the predominant cation followed by Mg2+ and Ca2+, and SO42-

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Figure 2 should be placed here

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and Cl- are the dominant anions followed by HCO3-.

In terms of other minor groundwater constituents, the levels of NO3-N and NO2-N in

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groundwater are a reflection of anthropogenic pollution due to the use of chemical fertilizer and/or

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the irrigation with wastewater (Li et al. 2013b). Nitrogen is found naturally in the environment and serves as an important plant nutrient. However, the presence of NO3-N in drinking water in high concentration is a potential health hazard (Singh et al. 2016). In the present study, the concentrations

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of NO3-N and NO2-N range from 0.1 to 169.81 mg/L and 0 to 2.74 mg/L, respectively. Seventeen samples have NO3-N values over the acceptable limit for drinking purpose (20mg/L). As the most active element, F- is commonly found in groundwater. It’s essential for human

health, which can influence the growth and skeletal metabolism (Aravinthasamy et al. 2019a, b; Su et al. 2016). The acceptable limit for F- in groundwater is 1.0 mg/L according to the Chinese drinking water quality standard (General Administration of Quality Supervision, Inspection and Quarantine of China and Standardization Administration of China 2017). In this study area, the concentration of F-

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in the sampled groundwater ranges from 0.12 to 7.40 mg/L, with a mean of 1.89 mg/L. There are 23 samples showing F- concentration exceeding the limit, accounting for approximately 66% of the total water samples. It means that the majority of groundwater in this area cannot be used for drinking purpose directly because of high fluoride in groundwater. For As, it has a low concentration, which ranges from 0 to 0.03 mg/L with a mean of 0.004 mg/L. Most samples are suitable for drinking with respect to As, and only 5 samples exceed the acceptable limit (0.01 mg/L). Metals usually have low concentrations in groundwater. Trace metals such as Cr6+, Fe and Mn are considered in this study. As shown in Table 1, the concentrations of Cr6+, Fe and Mn range from 0 to 0.30, 0-3.40 and 0-0.93

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that there are 9, 8 and 5 samples exceed the limits for Cr6+, Fe and Mn, respectively.

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mg/L, with the mean values of 0.05, 0.35 and 0.049 mg/L, respectively. The statistical results show

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4.2. Hydrochemical characteristics of Groundwater

Durov diagram, which illustrates the proportion of different ions in each groundwater sample,

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can reflect the hydrochemical characteristics and groundwater types as well as the correlation with pH and salinity (Li et al. 2016a; Li et al. 2014; Su et al. 2016). The hydrochemical types are

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determined by major ions in groundwater, and the Durov diagram of the collected samples is shown in Figure 3.

Figure 3 shows that all groundwater samples with TDS<1000 fall into zone C of the upper

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triangle except one sample. In zone C, HCO3- is the major anion, indicating that the hydrochemical constituent of fresh groundwater is dominated by HCO3-.. The left triangle represents the major

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cations regulating the groundwater hydrochemical type. It is obvious that these fresh groundwater samples are mainly HCO3-Na (zone G), HCO3-Ca (zone E) and HCO3-Na·Mg·Ca (zone D) types. Similarly, for the rest samples, which belong to brackish water (1000
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(TDS>3000), they mainly distribute in zone G in the left triangle, but are plotted in zones D, A and B. The main cation of zone G in the left triangle is Na+. Therefore, combined with the upper triangle, the groundwater types of these brackish water and saline water samples are SO4·Cl-Na, Cl·SO4-Na and SO4·Cl·HCO3-Na types. High salinity groundwater samples are usually associated with high concentrations of SO42- and Cl-.

Figure 3 should be placed here 11

Gibbs diagram was also used in this study to quantify the main mechanisms of the groundwater chemistry (Figure 4). In this diagram, three mechanisms can be identified: rock dominance, precipitation dominance and evaporation dominance (He and Li 2019). Figure 4 shows that rock dominance and evaporation dominance are two major mechanisms controlling the groundwater chemistry. It is apparent that groundwater chemistry is controlled by rock dominance, because groundwater flows through the pores of the aquifer media, and water-rock interactions occurring in the aquifer media will alter the characteristics of groundwater chemistry. Evaporation dominance is

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also identified in Figure 4, indicating that groundwater evaporation is significant in the study area.

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The annual evaporation rate in the area is 2062.65 mm and the water level depth for the Quaternary pore water ranges from 2 to 8 m above the mean sea level. The high evaporation rate and shallow

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water level depth favor the evaporation of groundwater, making it an important mechanism affecting

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the groundwater chemistry.

4.3. Health Risk Assessment

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Figure 4 should be placed here

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Human health risk was conducted based on the method introduced previously, and the results are presented in Table 2. It can be concluded from the table that children suffer much higher carcinogenic

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and non-carcinogenic health risks than adults both for. For non-carcinogenic, the acceptable limit is 1. HQ>1 suggests that the non-carcinogenic risks is unacceptable. As shown in Table 2, the non-carcinogenic risks in the study region range from 0.33 to

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6.59 for adults and from 0.61 to 12.31 for children. The assessment shows that people in the study area faces potential non-carcinogenic risk as most of the samples have HQ values exceeding the limit. That’s to say, most of the samples are unsuitable for direct drinking due to unacceptable non-carcinogenic risks. The maximum non-carcinogenic risk value is 6.59 for adults and 12.31 for children, respectively. Figure 5 represent the distribution of health risks in the study area. High non-carcinogenic risks are observed in the middle of the study area, while the southern and northern parts of the study area witness relatively low risks (Figures 5a and b). As shown in Figure 6a, the 12

non-carcinogenic risk is mainly caused by NO3-, and the contribution of the pollutants to the non-carcinogenic risk follows the following order: NO3->F->Cr6+>As>NO2->Mn. The adverse effects of NO2- and Mn are much lower than the others 4 pollutants.

Figure 5 should be placed here

Figure 6 should be placed here

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With respect to acceptable carcinogenic risk level, there are currently several standards in the

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world (Zhu et al. 2019). According to the USEPA, the acceptable maximum level is 1×10-4, and the

International Committee of Radiation Protection (ICRP) recommends 5 × 10-5 as the acceptable level.

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The Sweden Environmental Protection Bureau (SEPB) recommended 1×10−6. In this study, 1×10−6 is selected as the acceptable limit for it is the most stringent and benefits the long term human survival.

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CR>1×10−6 indicates that the carcinogenic risks are unacceptable. In this study Cr6+ and As are considered for the carcinogenic risk assessment. The values of CR range from 0 to 3.79E-3 with a

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mean of 7.89E-4 for adults, while the values for children range from 0 to 7.18E-3 with a mean of 1.47E-3. The maximum carcinogenic risk is observed in sample D18 followed by D10 and D17. These samples have higher Cr6+ and As concentrations than other samples. Thirty-three samples show

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a risk higher carcinogenic risk value than the limit, indicating serious carcinogenic risk in this area.

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Figures 5c and 4d show that high carcinogenic risk zone is mainly observed in the center of study area. As Figure 6b shows, Cr6+ accounts for the majority of carcinogenic health risk. The adverse effect of As can also not be neglected, though its adverse effects are lower than Cr6+.

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The results indicate that the majority of sampled groundwater samples are unsafe for drinking, as it will pose unacceptable health risks for both adults and children. It is also observed that children are facing higher risks than adults. The results are consistent with that reported by Su et al. (2017) in Dingbian County, He et al. (2019a) and He and Wu (2019a) in Wuqi County which are adjacent areas to our study area. As per the discussion above, it is necessary to take actions to reduce the levels of NO3-, Cr6+, F- and As in groundwater. For example, to reduce NO3- pollution, the use of fertilizers and pesticides should be controlled in agriculture. Besides, domestic and industrial wastes should be

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treated before discharged. With regard to Cr6+ pollution, effective method should be taken to constrain its migration and transform, such as the permeable reactive barrier technique (PRB). Most importantly, regular groundwater quality monitoring system should be established and protection measures should be implemented, and groundwater quality management research should be strengthened. Table 2 should be placed here 4.4. Assessment of groundwater quality based on WQI

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Water quality index (WQI) was calculated and analyzed based on health risk weighting, and Cr6+,

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As, NO3-, F-, NO2- and Mn were considered in this study. As shown in the health risk assessment, the pollutants have contributed with different degrees to the total risk, which means that they have

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different weights or importance in affecting the overall groundwater quality. After calculation, the weights for these parameters are 0.4262, 0.4789, 0.0297, 0.0502, 0.0079 and 0.0070, respectively.

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Cr6+ and As have the highest weights, indicating that they are the key factors affecting the overall groundwater quality, and they are most toxic to human health. NO3- and F- are also very important

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water quality parameters affecting the suitability of groundwater for drinking purpose. They have relatively high weights, while NO2- and Mn have the smallest weights because their concentrations are low in groundwater and their contribution to the overall water quality and health risks are small.

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The WQI results are shown in Table 3. In this study, the WQI values range from 2.25 to 269.17. 57.14% of the groundwater samples are classified into excellent quality category (WQI<25) and good

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quality category (25
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for 11.43% and 17.14% of all sampled groundwater, respectively. The calculation results also show that, Cr6+ and As are the major contributors of WQI. Therefore, Cr6+ and As pose the main threat to human in terms of health risk. The distribution of WQI values is presented in Figure 7, from which it can be clearly seen that high level of WQI is mainly distributed in the middle of study area. The water samples D9, D10, D17, D18, D23 and D28 are showing high WQI, and will pose great health risks on local residents. Therefore, these groundwater samples cannot be used for drinking or should be properly treated before drinking. 14

Table 3 should be placed here

Figure 7 should be placed here 4.5. Assessment of groundwater for Irrigation Irrigation water quality indicators including SAR, Na% and PI were calculated. The results are listed in Table 4. In this study, SAR ranges from 0.35 to 29.67, with a mean of 8.37. The results show that 97.14% of the water samples are considered suitable for irrigation and the rest (2.86%) are

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unsuitable. Based on Na%, 45.71% samples are permissible for irrigation purpose, and of the rest

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groundwater samples with Na% higher than the acceptable limit are of doubtful quality (48.57%) and unsuitable quality (5.71%) for irrigation purpose. The majority of groundwater exceeds the

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permissible limits of Na%, which indicates high sodium hazard. In terms of PI, all groundwater samples are acceptable for irrigation, and long term irrigation with such water will not produce

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permeability problems to soil. In summary, all groundwater samples are suitable for irrigation considering the soil permeability. However, in terms of sodium hazard, the groundwater in this study

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area should be used cautiously because over half of groundwater from this study area is unsuitable for irrigation due to high Na% percentage. Therefore, measures should be taken to reduce the content of

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Na+ in groundwater or cultivate sodium tolerant plants.

Table 4 should be placed here.

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5. Conclusions

In the present study, 35 groundwater samples were collected and analyzed to assess the health risk and evaluate the quality of groundwater for drinking and irrigation purposes in Dingbian County,

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Ordos Basin of northwest China. The following conclusions can be summarized. Groundwater in the study area is slightly alkaline in nature with slightly high TDS. The

abundance of major cations in groundwater samples follows the order: Na+>Mg2+>Ca2+>K+ and for anions the order is SO42->Cl->HCO3-. The hydrochemical types of groundwater are mainly HCO3-Na type, HCO3-Na·Mg·Ca type, SO4·Cl-Na type and SO4·Cl·HCO3-Na type. The non-carcinogenic health risk ranges from 0.33 to 6.59 for adults and 0.61 to 12.31 for children. The majority of the water samples are at unacceptable health risk level. The contribution 15

of pollutants to the non-carcinogenic risks follows the order: NO3->F->Cr6+>As>NO2->Mn, and the adverse effects of NO2- and Mn are low and can be neglected. The carcinogenic risks are mainly contributed by Cr6+ followed by As. Like non-carcinogenic risks, most of the samples are at unacceptable carcinogenic risk for drinking. Cr6+ and As possess the highest weights determined by the health risk weighting method. The WQI values vary from 5.25 to 269.17, with 11.43% and 17.14% of all sampled groundwater being classified as poor and very poor quality water, respectively, which is absolutely unsuitable for drinking. The groundwater will not affect the soil permeability in terms of PI, but some of the

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Conflict of interest: The authors declare no conflict of interest.

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samples may not be suitable for irrigation in terms of sodium hazard.

Acknowledgement

The research was supported by the National Natural Science Foundation of China (41761144059),

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the Fundamental Research Funds for the Central Universities of CHD (300102299301), the Fok Ying

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Tong Education Foundation (161098), the China Postdoctoral Science Foundation (2015M580804, 2016M590911, 2016T090878 and 2017T100719), the Shaanxi Postdoctoral Science Foundation (2015BSHTDZZ09 and 2016BSHTDZZ03), and the Ten Thousand Talents Program (W03070125).

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The reviewers and the editor are acknowledged for their useful and constructive comments which are helpful for us to improve the quality of the paper.

16

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Figure captions

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Figure 1: Sketch map showing the study area and sampling locations

Figure 2: Pie chart of major ions

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Figure 3: Durov diagram of groundwater samples

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Figure 4: Gibbs diagram indicating the mechanisms controlling the groundwater chemistry

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Figure 5: Distribution of non-carcinogenic and carcinogenic risks for adults and children

Figure 6: Histogram of non-carcinogenic and carcinogenic risks contributed by different pollutants.

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Figure 7: Spatial distribution of groundwater quality based on WQI

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Table 1 Statistical analysis results of physiochemical parameters Max

Na+

35

mg/L 566.83

1903.00 6.58

200

23

+

35

mg/L 3.69

18.90

0.10

/

/

K

Ca

2+

Min

Chinese standards NSES*

Parameters Samples Units Mean

35

mg/L 83.72

360.90

2.75

/

/

2+

35

mg/L 148.90

631.20

0.81

/

/

2-

35

mg/L 791.54

3763.00 17.49 250

19

35

mg/L 602.05

2363.00 1.75

21

35

mg/L 308.16

803.50

60.05 /

/

F

35

mg/L 1.89

7.40

0.12

1.0

23

NO3-N

35

mg/L 25.01

74.29

1.45

20

17

NO2-N

35

mg/L 0.033

0.49

0.00

/

As

35

mg/L 0.004

0.03

0.00

0.01

5

35

mg/L 0.05

0.30

0.00

0.05

9

Fe

35

mg/L 0.35

3.40

0.00

0.3

8

Mn

35

mg/L 0.049

0.93

0.00

0.1

5

pH

35

/

8.41

7.37

6.5-8.5

0

TH

35

mg/L 822.39

TDS

35

mg/L 2484.578 8460.00 91.13 1000

HCO3 -

Cr

6+

7.89

3254.00 31.24 450

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* NSES: Number of samples exceeding standards

250

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-

28

/

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Cl

-

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SO4

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Mg

20 21

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CR 1.40E-04 3.74E-04 9.34E-04 1.40E-04 7.01E-04 4.90E-04 4.20E-04 9.11E-04 4.88E-03 5.67E-03 5.84E-04 7.01E-05 1.40E-04 0 0 4.67E-04 5.44E-03 7.08E-03 1.56E-03 2.80E-04 7.01E-05 1.17E-03 2.45E-03 2.80E-04 2.10E-04 6.54E-04 2.90E-03 3.95E-03 2.73E-03 1.40E-04 1.03E-03 2.80E-04 3.18E-03 2.10E-04 2.03E-03 7.08E-03 0 1.47E-03 33

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Table 2 Assessment results of health risks through drinking water intake Adults Children Sample No. HQ CR HQ D1 2.11 7.50E-05 3.94 D2 6.02 2.00E-04 11.25 D3 2.12 5.00E-04 3.96 D4 0.76 7.50E-05 1.42 D5 3.93 3.75E-04 7.34 D6 3.17 2.63E-04 5.93 D7 1.04 2.25E-04 1.94 D8 4.14 4.88E-04 7.73 D9 3.99 2.61E-03 7.45 D10 6.59 3.04E-03 12.31 D11 3.07 3.13E-04 5.73 D12 2.54 3.75E-05 4.74 D13 6.06 7.50E-05 11.32 D14 1.05 0 1.95 D15 2.27 0 4.24 D16 3.64 2.50E-04 6.81 D17 5.27 2.91E-03 9.85 D18 4.16 3.79E-03 7.77 D19 4.56 8.38E-04 8.51 D20 0.54 1.50E-04 1.01 D21 5.17 3.75E-05 9.66 D22 2.34 6.25E-04 4.38 D23 3.44 1.31E-03 6.43 D24 2.18 1.50E-04 4.06 D25 1.14 1.13E-04 2.13 D26 5.34 3.50E-04 9.97 D27 4.27 1.55E-03 7.98 D28 4.06 2.11E-03 7.59 D29 4.55 1.46E-03 8.50 D30 0.33 7.50E-05 0.61 D31 3.38 5.50E-04 6.32 D32 5.08 1.50E-04 9.49 D33 4.45 1.70E-03 8.30 D34 0.44 1.13E-04 0.82 D35 3.56 1.09E-03 6.65 Max 6.59 3.79E-03 12.31 Min 0.33 0 0.61 Mean 3.34 7.89E-04 6.23 NSEAL* 31 33 33 29

* NSEAL: Number of samples exceeding acceptable levels

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Water quality Excellent quality Good quality Fair quality Very poor quality Good quality Excellent quality Good quality Poor quality Very poor quality Poor quality Excellent quality Fair quality Good quality Poor quality Excellent quality Fair quality Excellent quality Very poor quality Fair quality

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WQI 21.10 36.61 80.98 164.29 28.91 19.27 49.53 120.80 161.53 128.02 10.38 63.33 42.06 135.46 15.42 89.42 5.25 269.17 78.93

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Sample number D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32 D33 D34 D35 Min Max Mean

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Table 3 Water quality assessment using WQI Sample number WQI Water quality D1 21.69 Excellent quality D2 41.33 Good quality D3 64.67 Fair quality D4 12.61 Excellent quality D5 48.22 Good quality D6 37.74 Good quality D7 25.56 Good quality D8 76.29 Fair quality D9 195.64 Very poor quality D10 233.09 Very poor quality D11 42.89 Good quality D12 14.01 Excellent quality D13 32.57 Good quality D14 5.25 Excellent quality D15 11.61 Excellent quality D16 43.20 Good quality D17 215.49 Very poor quality D18 269.17 Very poor quality D19 108.70 Poor quality

Means 8.37

55.76%

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Table 4: Water quality assessment for irrigation purpose using SAR, Na% and PI Number of samples Indicator Classification Water quality Percentages belong to this grade SAR 0-10 Good 21 60.00% 10-18 Permissible 13 37.14% 18-26 Doubtful 0 0 >26 Unsuitable 1 2.86% Na% <20 Excellent 0 0 20-40 Good 9 25.71% 40-60 Permissible 7 20.00% 60-80 Doubtful 17 48.57% >80 Unsuitable 2 5.71% PI >75% Good 10 28.57% 25-75% Suitable 25 71.43% <25% Unsuitable 0 0.00%

30

71.15%

31

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e-

Pr