Exposure and Health

, Volume 11, Issue 2, pp 81–94 | Cite as

Solute Geochemistry and Multivariate Analysis of Water Quality in the Guohua Phosphorite Mine, Guizhou Province, China

  • Peiyue LiEmail author
  • Rui Tian
  • Rong Liu
S.I. : Drinking Water Quality and Public Health


Water plays a critical role in securing the mine production and domestic consumption in mining areas. This research was carried out to assess the water quality status and to identify the hydrochemical processes contributing to the dissolved constituents of the water in the Guohua phosphorite mine, Guizhou Province, China. Multivariate statistical techniques and correlation analysis were employed to gain a better understanding of the hydrogeochemical processes, and water quality for domestic and irrigation purposes was also assessed. The results indicate that groundwater and surface water quality in the phosphorite mine area is currently excellent with low concentrations of major ions, salinity, and trace metals. Whereas, E. coli is excessive in groundwater and surface water, and treatment is required before the water is used for drinking purpose. Groundwater and surface water are, however, suitable for agricultural purposes. The major ions are Ca2+, Mg2+, and HCO3, and all water samples are predominantly of the HCO3–Ca·Mg type. Hierarchical cluster analysis (HCA) indicates that the water chemistry in the mining area is regulated by natural processes that are controlled by the different geological formations and different hydrogeological settings. Carbonate dissolution/precipitation is the key factor controlling the concentrations of Ca2+, Mg2+, and HCO3. Pyrite oxidation is an important factor influencing the concentration of SO42–, whereas evaporation is a minor factor regulating the water chemistry in the mining area. The study results are beneficial for sustainable water quality management in the mining area, and they will also interest mine hydrogeologists and practitioners of the world as a reference for relevant studies in other regions.


Water quality Groundwater Hydrochemistry Phosphorite mine Water–rock interaction 


Water is essential in mining areas in terms of domestic use and mine production, and it is also an important natural resource for industrial and irrigation uses all over the world (Nair et al. 2017; Wu et al. 2017a). Mining activities, however, can have noticeable impacts on water quality and water regime. For instance, Arkoc et al. (2016) assessed the possible impact of coal mining on groundwater and surface water quality in the Tozaklı coal field, Turkey. They found that Enterococcus spp., E. coli, and total coliforms were present in the mine pond waters. Similar studies have also been carried out in China (Li et al. 2013a; Wu et al. 2014), Serbia (Atanacković et al. 2016), Nigeria (Utom et al. 2013), Brazil (Roisenberg et al. 2016), and India (Mahato et al. 2017). As indicated by these studies, mine production has a tremendous influence on groundwater quality and groundwater chemistry in mining areas. As such, gaining a full understanding of the solute geochemistry and water quality status of mining areas is important for the sustainable management and protection of water resources in mining areas (Li et al. 2017a).

During the past three decades, hydrogeochemical methods and isotopic signatures have become a useful and widely adopted tool for exploring groundwater quality evolution and water recharge sources (Wu et al. 2015). For example, Li et al. (2008) used hydrogeochemistry and environmental isotopes to analyze the origin, hydraulic connections, and renewability of groundwater in the Qingshuihe Basin, northwestern China. Similarly, Gomaah et al. (2016) adopted stable isotopes and hydrogeochemistry to identify the sources and geochemical evolution of groundwater in an area of Egypt. Redwan et al. (2016) applied the hydrochemical signatures and correlation relationships of various elements to understand the effects of water–rock interaction processes on groundwater quality. There are many similar studies (e.g., Li et al. 2016a, b, c; Oyarzún et al. 2015; Vetrimurugan et al. 2013; Vetrimurugan and Elango 2015; Wu and Sun 2016; Xiao et al. 2012) published in international journals. Particularly, some scholars (e.g., Abdrakhmanov and Akhmetov 2016; Bidone et al. 2016; Neogi et al. 2017) used these approaches in mine water studies to identify the effects of mining activities on water circulation and water quality, which enhanced our understanding of natural and anthropogenic processes governing groundwater geochemical evolution in mining areas.

In addition to hydrogeochemistry and stable isotopes, multivariate techniques such as principal component analysis (PCA) and cluster analysis (CA) have also been widely used in mine water studies (Chen et al. 2017; Ferati et al. 2015; Howladar and Mustafizur Rahman 2016; Qian et al. 2016). Some of the latest achievements in this research field, which may provide useful references for similar studies, are summarized as follows.
  • Rapantová et al. (2012) developed a software tool, KYBL-7, that integrated geochemical modeling and multivariate statistics to quantify the different sources of mine water. This model proposed by the authors can be applicable in mine water source identification with acceptable accuracy. The mixing proportions of the different sources, however, were calculated in steady state without accounting for chemical reactions.

  • Horák and Hejcman (2016) applied PCA and exploratory data analysis to explore the contamination of a very old (800 years) center of medieval mining in the region of Kutná Hora in the Czech Republic. Through PCA, they found that As and Cd in the sediments of the old mining region were associated with mining activities, whereas Be, Co, Cr, Hg, and V were not related to mining. The most significant and interesting contribution of this research is that multivariate techniques were used to study the environmental impacts of a very old mine.

  • Tiwari et al. (2017) employed PCA and CA to explore the impact of seepages from mine dumps and a tailing dam on surface waters in a local area of India. They identified the spatial and temporal patterns in river water quality, which may be helpful for establishing priorities for sustainable water management.

  • Extensive underground mining activities are usually responsible factors of ground surface subsidence in many mining areas. Sahu et al. (2017) used several multivariate approaches to study the contribution of each factor to the occurrence of subsidence in mining areas. They found that the depth of working and dip of seam were the main factors influencing the magnitude and extent of subsidence.

China is a big country with thousands of mines, especially in western China where natural gas, oil, and coal are abundant. In recent years, swift national economic development has improved the living conditions in many rural and remote mountainous regions of western China (Gao et al. 2007). However, it is not easy to guarantee the sustainability and harmony between humans and the environment (Li et al. 2017b), because many environmental problems have been seen in many regions of China (Li 2016; Li et al. 2018a). Like in many mining regions of the world, groundwater quality in the mining regions of China is facing substantial water quality deterioration. Especially after the implementation of the Chinese West Development Program and the recent Belt and Road Initiative (Li et al. 2015), the large mine industry has developed rapidly, potentially threatening the environment and human health. It is always important and necessary to gain a full understanding of the main factors influencing groundwater quality and to systematically monitor and assess water quality in the mining areas. Therefore, the main objectives of this study are (1) to assess the water quality status in the Guohua phosphorite mine, Guizhou Province of China, and (2) to identify the hydrochemical processes contributing to the dissolved constituents of the water in the phosphorite mine. Knowledge of the solute geochemistry and water quality in this area will be helpful for a better understanding of the hydrogeochemical system in the phosphorite mine, ensuring sustainable management and protection of water resources in this area.

Study Area

Location, Climate, and Hydrology

The Guohua phosphorite mine is situated in the middle of the Yunnan–Guizhou Plateau, and it belongs to the transition zone from the plateau area of northwest Guizhou to the basin area of southeast Guizhou. It is about 15 km east of Zhijin County, Guizhou Province of China (Fig. 1). The major landform is characterized mainly by small to moderate hills ranging from 1242.2 to 1754.8 m above mean sea level (Chen et al. 2011). Some small valleys where local villages are located are developed among the hills. Local agriculture in this area relies on food production such as rice, corn, wheat, and potato, and industry mainly includes hydropower, chemical engineering, coal, and phosphorite mines.
Fig. 1

Study area map showing the location, geology, hydrogeology, and sampling sites

The study area belongs to a subtropical monsoon climate zone that is significantly influenced by the Asian Summer Monsoon, with abundant rainfall in summer season (Zeng et al. 2015). According to the meteorological data of the local meteorological bureau, the average annual temperature in this area is 14.1 °C, with the hottest season in July and the coldest in January (Li et al. 2016d). The average annual rainfall is 1391.2 mm, with April to September being the rainy season. Precipitation in the rainy season accounts for 82.3% of the annual precipitation, and precipitation in the dry season (December and January) accounts for only 6% of the annual precipitation (Chen et al. 2011). Precipitation is the main groundwater recharge source in this area. Average annual evaporation in this area is 832.0 mm.

The surface water network in the study area belongs to the Wujiang River drainage system, and it is well developed. The Nagong River and the Niudong River are the main rivers in the study area, and both merge into the Liangcha River to the north of the phosphorite mine region. Other rivers in this area, however, are only seasonal streams. The river runoff for the Nagong River is approximately 17.43 × 104 m3/day, and that for the Niudong River is approximately 13.20 × 104 m3/day (Chen et al. 2011). The Nagong River is formed by the outcrop of underground rivers, and the Niudong River also receives a great amount of recharge from groundwater. Therefore, the quality and chemical characteristics of the two rivers are significantly governed by groundwater. The surface water in the area is one of the main sources of water for agriculture.

Geology and Hydrogeology

The main outcropped strata within the mining area are, from oldest to youngest, the Sinian, Cambrian, Carboniferous, and Quaternary formations (Chen et al. 2011). A Permian formation can be found in the southeast boundary of the phosphorite mine region. The Sinian Dengying unit (Z2dy) is formed by gray and gray-white medium-thick layered dolomite, algae clinker dolomite, and fine-grained dolomite. The Cambrian formation in the area can be subdivided into several units, and they are from oldest to youngest the Gezhongwu unit (∈1gz), the Niutitang unit (∈1n), and the Mingxinsi unit (∈1m). The Gezhongwu unit is generally composed of a dark gray medium-thick layer of fine-grained phosphorus-bearing dolomite, imbedded locally by dark gray thin dolomitic phosphorite. The overlying Niutitang unit consists of gray-black silicic silt biochip phosphorus and black carbonaceous siltstone. This unit is a low permeability layer, acting as an aquitard in the area. The Mingxinsi unit, which overlies the Niutitang unit, is a formation consisting of medium-thick fine sandstone imbedded with siltstone. The Carboniferous formation outcrops locally in the mining area, and it is classified into two units: the Jiujialu unit (C1jj) and the Dapu unit (C1d). The Jiujialu unit is a coastal lacustrine deposition in the continental margin region, and it is mainly composed of gray-white thin pyrite containing silty clay rock and hydromica clay rock (Chen et al. 2011). For the Dapu unit, the bottom part is formed by light gray thin to medium-thick muddy dolomite imbedded with gray-green thin hydromica clay rock, while the upper part is composed of gray and brown yellow medium-thick clay-containing dolomite and gray thick massive coarse dolomite. The Quaternary deposits are mainly distributed in the foothills and low-lying terrains or gentle slopes, and they consist of mainly gravel, sand, and clay.

Groundwater occurrence and distribution in the study area are regulated by the hydrogeological settings and a number of faults, especially the northeast (NE) direction faults. The main groundwater types in the area are karst water in carbonate rocks and pore–fissure water in bedrock. Pore water in loose Quaternary sediments is only available locally in this area. The main groundwater aquifers in the region include the Sinian Dengying (Z2dy), Gezhongwu (∈1gz), Mingxinsi (∈1m), Dapu (C1d), Liangshan (P1l), and Qixia (P2q) units, while the Niutitang (∈1n) and Jiujialu (C1jj) units form the aquitards.

Groundwater in the area is recharged mainly by atmospheric precipitation and leakage of surface water in some local areas. Karst is well developed in the region, which favors the infiltration of atmospheric precipitation directly through ground karst fissures and karst funnels. The karst serves as the main recharge source for groundwater. The surface rivers in the region are also very well developed, and they can have close hydraulic connection with groundwater in the course of runoff. Groundwater flows generally from southwest to northeast, and its flow patterns are influenced by karst fissures and faults. Fissures and faults are distributed in a crisscross pattern, which is in favor of the inter-aquifer correlation. They are also important routes of groundwater discharge. The groundwater in the region is mainly discharged in the form of springs, which vary substantially in flow rate with seasonal changes. In addition, the development of underground rivers in the region is also an important form of groundwater discharge.

Materials and Methods

Sample Collection and Analysis

For this study, nine groundwater samples (G1–G9) and one surface water sample (S1) were collected from the study area. The surface water sample was collected from the downstream of the Niudong River after the river flows through the mining area. Groundwater samples were collected randomly from the springs distributed over the mining area. Five of the groundwater samples were collected from different geological units of the Cambrian period (three from the Mingxinsi unit and two from the Niutitang unit). The others were sampled from the Sinian Dengying unit. The locations were recorded using a portable GPS device and are displayed in Fig. 1. Samples were collected using white plastic bottles. Before sampling, all containers were washed for 3–5 times using the water to be sampled. After collection, the bottles were sealed and transported to the laboratory for physicochemical analysis. All samples were analyzed and calculated for total dissolved solids (TDS), total hardness (TH), electric conductivity (EC), pH, and major ions (Na+ + K+, Ca2+, Mg2+, HCO3, SO42−, Cl). To assess the suitability of water for drinking purpose, two groundwater samples (G2 and G9) and the surface water sample (S1) were additionally analyzed for trace metals (Hg, Cd, Cr6+, As, Pb, Cu, and Mn), nitrate (NO3–N), fluoride (F), chemical oxygen demand (CODMn), and E. coli. pH was measured in situ using a portable pH meter. The traditional titrimetric methods were adopted in this study to determine the concentrations of Cl, SO42–, HCO3, and NH4–N, while Ca2+, Mg2+, and TH were analyzed by the EDTA titrimetric method. Na+ and K+ were measured by flame atomic absorption spectrometry. The concentration of K+ was quite low in this study, so it is recorded together with Na+ as Na+ + K+. TDS was determined by the drying and weighing approach. The ion-selective electrode method was used for the measurement of F, and ion chromatography was used for the determination of NO3–N and NO2–N. Potassium permanganate (KMnO4) was used as the oxidant for analyzing CODMn through the titrimetric method. The trace metals were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The accuracies of the analyses for all the water samples were checked by calculating the ionic balance error, for which 5% was considered the upper error limit. As a result, the ionic balance errors for all water samples were below the limit.

Multivariate Techniques

Hierarchical cluster analysis (HCA) is a useful tool for analyzing water quality parameters in terms of their origin and influencing factors (Wu et al. 2014). Typically, two HCA modes exist. One is called R mode HCA, which can classify water quality parameters into several clusters. The other is Q mode HCA, which can classify water samples into several groups according to their physicochemical parameters. R mode is usually used for the analysis of the origin or influencing factors of the physiochemical parameters, whereas Q mode HCA is usually applied in the analysis of the influencing factors for water samples (Li et al. 2013a). In this study, both Q mode and R mode HCA were adopted to give readers a full understanding of the factors influencing the water quality.

Irrigation Water Quality

The quality of irrigation water may have effects on plant growth, thus reducing agricultural production. There are numbers of indicators available for irrigation water quality assessment, such as sodium adsorption ratio (SAR), soluble sodium percentage (%Na), residual sodium carbonate (RSC), Kelly’s ratio (KR), and permeability index (PI), among many others (Santacruz et al. 2017). In this study, SAR, Na%, and RSC were employed for sodium hazard assessment, and EC was applied for salinity hazard assessment. SAR, Na%, and RSC can be computed as follows (Davraz and Özdemir 2014; Li et al. 2013b, 2016c; Santacruz et al. 2017), where all ions are expressed in milliequivalents per liter (meq/L).
$${\text{SAR}} = \frac{{{\text{Na}}^{ + } }}{{\sqrt {\frac{{{\text{Ca}}^{{ 2 { + }}} {\text{ + Mg}}^{{ 2 { + }}} }}{2}} }}$$
$${\text{Na}}\% = \frac{{{\text{Na}}^{ + } }}{{{\text{Ca}}^{{ 2 { + }}} {\text{ + Mg}}^{{ 2 { + }}} {\text{ + Na}}^{ + } {\text{ + K}}^{ + } \, }} \times 100\%$$
$${\text{RSC}} = \left( {{\text{CO}}_{ 3}^{2 - } {\text{ + HCO}}_{ 3}^{ - } } \right) - \left( {{\text{Ca}}^{{ 2 { + }}} {\text{ + Mg}}^{{ 2 { + }}} } \right)$$
The criteria of irrigation water quality classification based on SAR, Na%, RSC, and EC are shown in Table 1.
Table 1

Criteria of classifying irrigation water quality based on SAR, %Na, RSC, and EC



Irrigation water quality



Irrigation water quality

<  10


Excellent quality

< 30

< 1.25




Good quality



Marginally suitable



Acceptable quality

> 60

> 2.5


> 26

> 2250

Unacceptable quality


Results and Discussion

General Hydrochemistry

Water chemistry depends on various factors such as geological and hydrogeological settings, intensity and rate of rock weathering, climatic conditions, recharge water quality, types and intensity of human activities, and connections and interactions of different water bodies (Li et al. 2017c; Towfiqul Islam et al. 2017; Wu et al. 2017b). These factors vary in different environments, and their interactions can create complex water chemistry (Li et al. 2017d). To explore the general hydrochemistry of water in the study area, the statistical summary of groundwater and surface water is presented in Table 2.
Table 2

General statistics of groundwater samples and surface water. All indices are expressed in mg/L except pH, EC (μS/cm), and E. coli (/L)




K+ + Na+









E. coli























− 0.26





































Surface water

















− 0.01

The pH of groundwater ranges from 6.78 to 7.80 with a mean of 7.45 (Table 2), indicating that the groundwater is generally slightly acidic (6.78) to slightly alkaline (7.80). These pH values are slightly lower than those of groundwater in the Laoheba phosphorite mine in Sichuan of China (Wu et al. 2014). The pH of surface water is 8.00, which is slightly higher than those of groundwater in the study area, indicating a more alkaline environment of the surface water. The TDS of groundwater ranges between 116.98 and 344.73 mg/L with a mean of 208.84 mg/L. On the other hand, the EC of groundwater varies from 208.88 to 581.95 μS/cm with a mean value of 357.42 μS/cm. TDS and EC for surface water in this area are 286.58 mg/L and 501.11 μS/cm, respectively. Based on TDS classification of groundwater, all groundwater samples and the surface water sample are fresh water in this area (TDS < 1000 mg/L), which is suitable for domestic consumption and irrigation. The TH value of water measures the dissolved Ca2+ and Mg2+ content expressed as CaCO3 (Wu et al. 2013). Long-term dietary exposure to hard to very hard water may lead to increased incidences of health problems such as anencephaly, parental mortality, and cardiovascular disorders (Chabukdhara et al. 2017). The TH of groundwater in this area varies from 89.10 to 292.15 mg/L with a mean of 176.12, and the TH of the surface water is 267.29 mg/L, suggesting soft water (TH < 150 mg/L) to slightly hard water (TH within 150–300 mg/L) based on the classification of Chinese Standards for Drinking Water Quality (Li et al. 2010).

The predominant cations and anions in the groundwater and surface water samples are Ca2+, Mg2+, and HCO3. The orders of major ions of water samples are Ca2+ > Mg2+ > Na+ + K+ for cations and HCO3 > SO42− > Cl for anions. The dissolution of carbonates such as calcite [CaCO3] and dolomite [CaMg(CO3)2] may be responsible for high concentrations of HCO3, Ca2+, and Mg2+. The concentrations of Na+ + K+ and Cl are low in the water samples and they do not show a linear relationship, indicating that the water in the study area is of non-marine origin, and the dissolution of halite (NaCl) is not a major process of groundwater chemical formation. The SO42− concentration in the water samples is also very low compared with water samples from many other regions of the world, such as arid and semi-arid northwest China. This indicates that gypsum is not a dominant mineral in the lithology of the study area. Low concentrations of SO42− may also be attributed to less human activity in this study area. As indicated by the Piper diagram (Fig. 2), all water samples fall within zone IV, demonstrating that all water samples are predominantly of the HCO3–Ca·Mg type. The Piper diagram also indicates that weathering of carbonates is the main process governing groundwater chemistry in this study area, and groundwater and surface water in the study area have close connection, which results in their similar hydrochemical characteristics.
Fig. 2

Piper diagram of water samples showing the main water type in this area

Water Quality Assessment

Water in the Guohua phosphorite mine region is mainly used for domestic and agricultural purposes. Physiochemical indices were compared with the WHO (2017) and national (Ministry of Health of the P. R. China and Standardization Administration of the P. R. China 2006) guidelines for drinking water quality. The desirable limit of pH for drinking purpose is 6.5–8.5. All water samples fall within this limit, indicating suitability for drinking purpose. The guideline values of TH and TDS are 450 and 1000 mg/L, respectively, according to the national guidelines for drinking water quality. As shown in Table 2, the TH and TDS of groundwater and surface water are both within the permissible limits for drinking purposes. The concentrations of Cl and SO42− are very low in the study area, and they are both within their acceptable limits (250 mg/L for both Cl and SO42−) for drinking purposes (WHO 2017). The contents of trace metals analyzed in this study are all very low. Especially, the contents of Hg, Cd, Cr6+, As, and Pb are all below the detection limits, thus will not be discussed in detail. The concentrations of Cu and Mn in the surface water are 0.01 and 0.04 mg/L, respectively. Their concentrations in groundwater are < 0.01 and 0.01 mg/L, respectively. The concentrations of Cu and Mn in surface water and groundwater are well below the permissible limits for drinking purpose. Groundwater fluoride ranges from 0.155 to 0.308 mg/L and surface water fluoride is 0.186 mg/L, which are both well below the permissible limit for drinking purpose recommended by the WHO (2017). Nitrate concentration in groundwater varies from 0.683 to 0.899 mg/L and that in surface water is 0.327 mg/L. Nitrate concentration is also much lower than the guideline value, indicating suitability of the water for drinking purpose. CODMn represents the amount of oxygen required for the degradation of organic contaminants. High CODMn indicates high concentration of organic contaminants. In this study, CODMn is lower than the acceptable limit for drinking purpose in groundwater and the surface water. Surface water contains excessive E. coli. There are 16,000 E. coli per liter in surface water, which is much higher than the guideline value for drinking purpose (3 E. coli per liter). The number of E. coli in groundwater is lower than that in surface water, ranging from 20 to 3500 per liter, but is still higher than the guideline value. This indicates a serious contamination from excrement of livestock and local residents in this area, and poses the biggest threat to the suitability of groundwater and surface water for drinking purpose. E. coli levels in samples G2 and S1 are very high (3500 and 16,000 per liter, respectively), and G2 was sampled near the river, which suggests a close hydraulic connection between groundwater and surface water. In general, the water quality in the Guohua phosphorite mine region is excellent except the E. coli. If used for drinking, the E. coli must be treated.

The SAR value represents the capacity of soils to adsorb Na+ from irrigation water and the possibility of sodium hazard to soils posed by irrigation with water containing large amounts of sodium (Davraz and Özdemir 2014). In this study, the calculation results indicate that all water samples are of excellent or good quality (SAR < 1 for all water samples), which is suitable for irrigation (Table 2). Na% and RSC (Na% < 30% and RSC < 1.25 for all water samples) also show that water quality in this area is suitable for irrigation. In addition, the USSL and Wilcox diagrams (Fig. 3) show that all water samples fall within zones C1S1 and C2S1 in the USSL diagram and fall into the “Excellent to Good” quality zone in the Wilcox diagram, demonstrating the suitability of the water for irrigation (Li et al. 2017d). Long-term use of such water will not induce soil problems and will not affect agricultural production.
Fig. 3

USSL (a) and Wilcox (b) diagrams showing the irrigation water quality in terms of alkalinity and salinity

Overall, except the E. coli, the water in the study area is generally suitable for domestic and agricultural uses at present, which may be attributed to less human activity in this area. However, with the development of mines, human activities may become more intense and extensive, and water quality protection should always be considered carefully and seriously.

Multivariate Analysis of Water Quality

Correlations among water quality variables are a useful tool for understanding the major hydrogeochemical processes that control the chemical characteristics (Singh et al. 2017). Pearson correlation analysis was carried out to explore the correlation between each pair of physicochemical indices (Table 3). The results show that most of the physicochemical indices are correlated significantly with each other. TH is significantly correlated with Ca2+ and Mg2+ (correlation coefficients are 0.961 and 0.971, respectively), because Ca2+ and Mg2+ are the major contributors of TH. Additionally, Ca2+ and Mg2+ are also significantly correlated with HCO3 (correlation coefficients are 0.909 and 0.968, respectively), indicating the contribution of carbonate dissolution to water chemistry (Li et al. 2013a). This is evidenced by the fact that the study area is a karst area and carbonates such as calcite and dolomite are common in the geological formations. Similarly, Cl is also significantly correlated with Na+ and HCO3 (correlation coefficients are 0.633 and 0.648, respectively), suggesting that weathering of halite and silicates is an important process, though may not the sole process, regulating water chemistry in the area. In addition, the correlation between SO42– and Ca2+ is insignificant (correlation coefficient is 0.577), demonstrating that SO42– is not sourced from the dissolution of gypsum. The oxidation of pyrite is a possible source of SO42– in groundwater, as pyrite reserve has been reported in and around this area. TDS and EC are a measure of water salinity and are contributed by all soluble ions. As shown in Table 3, TDS and EC are significantly correlated with HCO3, Mg2+, Ca2+, K+ + Na+, and Cl, indicating the important role of carbonate dissolution and weathering of halite and silicates in forming the water chemistry.
Table 3

Pearson correlation matrix between physicochemical parameters of water samples




K+ + Na+






























K+ + Na+




















































*Correlation is significant at the 0.05 level (two tailed)

**Correlation is significant at the 0.01 level (two tailed)

Both Q mode HCA and R mode HCA were performed in this study. Ward's linkage method with squared Euclidean distance was used in both Q mode and R mode HCA for measurement of similarity between the water quality variables. Dendrograms of R mode and Q mode clusters are shown in Fig. 4. The R mode HCA indicates two major associations between the 10 water quality variables. Cluster 1 includes pH, SO42–, Cl, Na + K, Mg2+, and Ca2+, suggesting the processes of carbonate dissolution and rock weathering. Cluster 2 comprises TH, TDS, HCO3, and EC, indicating the relationship between carbonate dissolution and water salinity and hardness. Overall, R mode HCA shows that water quality in the study area is governed mainly by natural processes.
Fig. 4

Dendrograms of R mode cluster (a) and Q mode cluster (b) showing the cluster of physicochemical parameters using Ward’s linkage

Q mode HCA clusters all water samples into two groups. Cluster 1 consists of samples G2, G3, S1, G9, and G5, and the remaining water samples belong to cluster 2. Samples classified into different clusters have unique physicochemical characteristics. The average concentrations for physicochemical parameters in the two clusters follow a decreasing trend where Cluster 1 > Cluster 2. The concentrations of HCO3 for water samples in Cluster 1 are all higher than 300 mg/L, while those for water samples in Cluster 2 are all lower than 200 mg/L. Similarly, TH and TDS for water samples in Cluster 1 are all higher than 200 mg/L, and those for water samples in Cluster 2 are all lower than 150 mg/L. This may be due to the geological structures, hydrogeological settings, and the regions where different groups of water samples are located. As shown in Fig. 1, groundwater samples of Cluster 1 were all collected from the Sinian Dengying unit, and those of Cluster 2 belong to the Cambrian Gezhongwu unit and the Cambrian Niutitang unit. The different geological formations and different hydrogeological settings play a key role in regulating groundwater circulation and transformation.

Processes Influencing Solute Geochemistry

The above discussions have shown that water quality in the study area is largely controlled by natural processes such as rock weathering, mineral dissolution, and pyrite oxidation. In this section, these natural processes are discussed in detail.

Rock Weathering and Mineral Dissolution/Precipitation

The Gibbs diagram (Gibbs 1970) was originally used to explore the mechanisms regulating the evolution of world surface water, and it has more recently been widely used in groundwater studies (Li et al. 2016e). In this study, the Gibbs diagram (Fig. 5a) shows that rock weathering is the main mechanism controlling the major ion chemistry of river water and shallow groundwater in this area. The Gibbs diagram, however, is unable to indicate the impacts of human activities on water chemistry (Li et al. 2016b), and it is not effective in some situations where the Na/(Na + Ca) ratio will be increased by leaching of soil salts (Webster et al. 1994; Zhu et al. 2011). In the research by Zhu et al. (2011), they proposed to use the Mg2+/Ca2+ ratio instead of Mg2+/Na+ to determine the process of evaporation and soil salt leaching because Mg is a very minor component of soil salts and is not precipitated in the early stages of evaporation of low silica water (Hardie and Eugster 1970). The groundwater plots derived from Xiao et al. (2012) were governed by evaporation (filled triangle in Fig. 5b). In our study, the relatively low Mg2+/Ca2+ ratio and the relatively high Mg2+/Na+ ratio (Fig. 5b) show that rock interaction is the main force governing water chemistry.
Fig. 5

Gibbs diagram (a) and Mg/Na versus Mg/Na diagram (b) showing the mechanisms of groundwater evolution

Mineral dissolution is a process of rock weathering, and it is probably the dominating natural process responsible for major solutes in natural waters, even in mine water (Li et al. 2018b; Zhu et al. 2011). The dissolution/precipitation of minerals depends on the state of saturation. The saturation indices of major minerals were computed and graphed in Fig. 6. As shown in Fig. 6a, the calcite and dolomite are oversaturated with respect to surface water, which demonstrates that calcite and dolomite will not dissolve in the surface water. However, calcite and dolomite are oversaturated with respect to some groundwater samples and are unsaturated with respect to the remaining groundwater samples. This indicates that calcite and dolomite may continue to dissolve in groundwater in some locations, which is a significant process increasing the concentrations of Ca2+, Mg2+, and HCO3 in groundwater.
Fig. 6

Relationships of saturation indices for common minerals in the study area: (a) dolomite vs calcite, and (b) halite vs gypsum

Figure 6b illustrates that both gypsum and halite are unsaturated with respect to groundwater and surface water, indicating the possibility of gypsum and halite dissolution in groundwater and surface water if gypsum and halite are prevalent in the study area. However, as the correlation coefficient for Na+ and Cl is only 0.633, other factors such as cation exchange discussed in the next subsection may be an important process for the Na+ and Cl concentrations in groundwater and surface water. In addition, pyrite oxidation (which is a common process in the study area) is an important factor affecting the concentration of SO42–.

Cation Exchange

Cation exchange is also an important process controlling water chemistry (Wu and Sun 2016; Zhu et al. 2011). Typically, two chloro-alkaline indices (CAI-1 and CAI-2) proposed by Schoeller (1965) are used to explore the possibility of cation exchange, which can be expressed as follows (Li et al. 2014), where all ions are expressed in meq/L.
$${\text{CAI-1 = }}\frac{{{\text{Cl}}^{ - } - ({\text{Na}}^{ + } {\text{ + K}}^{ + } )}}{{{\text{Cl}}^{ - } }}$$
$${\text{CAI-2 = }}\frac{{{\text{Cl}}^{ - } - ({\text{Na}}^{ + } {\text{ + K}}^{ + } )}}{{{\text{HCO}}_{ 3}^{ - } + {\text{SO}}_{ 4}^{ 2- } + {\text{CO}}_{ 3}^{ 2- } + {\text{NO}}_{3}^{ - } }}$$
Positive values for the two indices indicate cation exchange expressed as Eq. (6), whereas negative values suggest reverse ion exchange expressed as Eq. (7) (Li et al. 2016b). In this study, all water samples are plotted in the lower left region of Fig. 7a, suggesting that reverse cation exchange expressed as Eq. (7) is an important process.
$$2 {\text{Na}}^{ + } {\text{ + CaX}}_{ 2} {\text{ = Ca}}^{{ 2 { + }}} {\text{ + 2NaX}}$$
$${\text{Ca}}^{{ 2 { + }}} {\text{ + 2NaX = 2Na}}^{ + } {\text{ + CaX}}_{ 2}$$
Fig. 7

Plots of CAI-1 against CAI-2 (a) and [(Ca + Mg) − (SO4 + HCO3)] versus (Na + K − Cl) (b)

To confirm the occurrence of cation exchange reactions, the relationship of (Na+ + K+ − Cl) with [(Ca2+ + Mg2+) − (HCO3 + SO42−)] was also applied in this study (Fig. 7b). In most cases, Na+ and Cl originate from the dissolution of halite, and (Na+ + K+ − Cl) indicates an increase or decrease in Na+ induced by processes excluding halite dissolution (Farid et al. 2013). Calcite, dolomite, and gypsum are the most likely additional sources from which Ca2+ and Mg2+ could enter the natural water apart from cation exchange (Zhu et al. 2011). [(Ca2+ + Mg2+) − (HCO3 + SO42−)] represents the increase or decrease in Ca2+ and Mg2+ by processes other than the dissolution/precipitation of gypsum, calcite, and dolomite (Li et al. 2016b). The results (Fig. 7b) show that the relationship of [(Ca2+ + Mg2+) − (HCO3 + SO42−)] with (Na+ + K+ − Cl) can be expressed as Y = − 1.034X + 0.172 with a correlation coefficient of 0.954. This suggests that [(Ca2+ + Mg2+) − (HCO3 + SO42−)] and (Na+ + K+ − Cl) are significantly linearly correlated and that cation exchange is an important process regulating water chemistry in the mining area.


The geochemistry of shallow groundwater and surface water is also potentially affected by evaporation. Evaporation is an important process governing water quality in arid and semi-arid regions (Li et al. 2016b). However, the study area lies in the subtropical monsoon climate zone, where annual evaporation is 832 mm. The Gibbs diagram (Fig. 5a) shows that the influence of evaporation on water quality is not obvious, but the Mg2+/Ca2+ ratios (Fig. 5b) for some water samples are similar to those from Xiao et al. (2012), which may indicate that evaporation is a minor factor affecting water chemistry in the mining area.


This study explores the hydrogeochemistry and water quality in the Guohua phosphorite mine, Guizhou Province of China using multivariate techniques and correlation analyses. The main hydrochemical processes contributing to the dissolved constituents of the water in the phosphorite mine were discussed in depth. The following conclusions can be summarized.
  • Groundwater in the phosphorite mine is slightly acidic to slightly alkaline, and surface water is slightly alkaline in nature. Groundwater and surface water are fresh water and are soft to slightly hard water in this area. The concentrations of major ions are ordered as Ca2+ > Mg2+ >Na+ + K+ for cations and HCO3 > SO42−> Cl for anions. All water samples are predominantly of the HCO3–Ca·Mg type.

  • The concentrations of trace metals and physiochemical indices in groundwater and surface water are lower than the permissible limits for drinking purpose. Groundwater and surface water quality in the phosphorite mine area is currently excellent except high E. coli and is suitable for agricultural purposes and domestic uses after treatment of E. coli. However, water quality monitoring should be implemented, because human activities will become more intense and extensive with the development of mines, which may have negative impacts on water quality in the mining area.

  • R mode HCA indicates that natural processes such as carbonate dissolution and rock weathering are the dominant processes regulating water chemistry in the mining area. Q mode HCA reveals that groundwater circulation and transformation are controlled by the different geological formations and different hydrogeological settings.

  • Multiple indicators and graphs demonstrate that natural processes such as rock weathering and mineral dissolution, as well as cation exchange, are the dominant processes regulating the water chemistry in the mining area. In particular, carbonate dissolution/precipitation is the key factor controlling the concentrations of Ca2+, Mg2+, and HCO3. In addition, pyrite oxidation is an important factor influencing the concentration of SO42−. Evaporation is a minor factor controlling the water chemistry in the area.



The research is supported jointly by the following projects: the National Natural Science Foundation of China (41502234, 41761144059, and 41602238), the Research Funds for Young Stars in Science and Technology of Shaanxi Province (2016KJXX-29), the Foundation of Outstanding Young Scholar of Chang’an University (310829153509 and 300102298301), the General Financial Grant from the China Postdoctoral Science Foundation (2015M580804), the Special Financial Grant from the China Postdoctoral Science Foundation (2016T090878), the Fok Ying Tong Education Foundation (161098), the Special Financial Grant from the Shaanxi Postdoctoral Science Foundation (2015BSHTDZZ09), and the Innovation Training Program for Undergraduate Students of Chang’an University (201610710073, 201710710099 and 201710710100). The anonymous reviewers and the editors are also sincerely acknowledged for their constructive suggestions which are helpful in improving the quality of the paper.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no competing interest.


  1. Abdrakhmanov RF, Akhmetov RM (2016) Hydrogeochemistry at mining districts. Geochem Int 54:795–806. CrossRefGoogle Scholar
  2. Arkoc O, Ucar S, Ozcan C (2016) Assessment of impact of coal mining on ground and surface waters in Tozaklı coal field, Kırklareli, northeast of Thrace, Turkey. Environ Earth Sci 75:514. CrossRefGoogle Scholar
  3. Atanacković N, Dragišić V, Živanović V, Gardijan S, Magazinović S (2016) Regional-scale screening of groundwater pollution risk induced by historical mining activities in Serbia. Environ Earth Sci 75:1152. CrossRefGoogle Scholar
  4. Bidone E, Castilhos Z, Cesar R, Santos MC, Sierpe R, Ferreira M (2016) Hydrogeochemistry of arsenic pollution in watersheds influenced by gold mining activities in Paracatu (Minas Gerais State, Brazil). Environ Sci Pollut Res 23(9):8546–8555. CrossRefGoogle Scholar
  5. Chabukdhara M, Gupta SK, Kotecha Y, Nema AK (2017) Groundwater quality in Ghaziabad district, Uttar Pradesh, India: multivariate and health risk assessment. Chemosphere 179:167–178. CrossRefGoogle Scholar
  6. Chen Y, Mo C, Gan Q, Li W, Liu C, Li X, Zhou D, Yang Z (2011) Exploration report on phosphorus and rare Earth ore in Guohua mine section of Xinhua phosphorus mining area, Zhijin County, Guizhou Province. Guizhou Bureau of Mineral Reserve Trading, p 159 (in Chinese)Google Scholar
  7. Chen M, Wu Y, Gao D, Chang M (2017) Identification of coal mine water-bursting source using multivariate statistical analysis and tracing test. Arab J Geosci 10:28. CrossRefGoogle Scholar
  8. Davraz A, Özdemir A (2014) Groundwater quality assessment and its suitability in Çeltikçi plain (Burdur/Turkey). Environ Earth Sci 72:1167–1190. CrossRefGoogle Scholar
  9. Farid I, Trabelsi R, Zouari K, Abid K, Ayachi M (2013) Hydrogeochemical processes affecting groundwater in an irrigated land in Central Tunisia. Environ Earth Sci 68:1215–1231. CrossRefGoogle Scholar
  10. Ferati F, Kerolli-Mustafa M, Kraja-Ylli A (2015) Assessment of heavy metal contamination in water and sediments of Trepça and Sitnica rivers, Kosovo, using pollution indicators and multivariate cluster analysis. Environ Monit Assess 187:338. CrossRefGoogle Scholar
  11. Gao Y, Che G, Shen M (2007) Scattered rural settlements and development of mountainous regions in western Sichuan, China. Wuhan Univ J Nat Sci 12(4):737–742. CrossRefGoogle Scholar
  12. Gibbs RJ (1970) Mechanisms controlling world water chemistry. Science 170:795–840CrossRefGoogle Scholar
  13. Gomaah M, Meixner T, Korany EA, Garamoon H, Gomaa MA (2016) Identifying the sources and geochemical evolution of groundwater using stable isotopes and hydrogeochemistry in the quaternary aquifer in the area between Ismailia and El Kassara canals, northeastern Egypt. Arab J Geosci 9:437. CrossRefGoogle Scholar
  14. Hardie LA, Eugster HP (1970) The evolution of closed-basin brines. Mineral Soc Am 3:273–290Google Scholar
  15. Horák J, Hejcman M (2016) 800 years of mining and smelting in Kutná Hora region (the Czech Republic)—spatial and multivariate meta-analysis of contamination studies. J Soils Sediments 16:1584–1598. CrossRefGoogle Scholar
  16. Howladar MF, Mustafizur Rahman M (2016) Characterization of underground tunnel water hydrochemical system and uses through multivariate statistical methods: a case study from Maddhapara Granite Mine, Dinajpur, Bangladesh. Environ Earth Sci 75:1501. CrossRefGoogle Scholar
  17. Li P (2016) Groundwater quality in western China: challenges and paths forward for groundwater quality research in western China. Expo Health 8(3):305–310. CrossRefGoogle Scholar
  18. Li X, Zhang L, Hou X (2008) Use of hydrogeochemistry and environmental isotopes for evaluation of groundwater in Qingshuihe Basin, northwestern China. Hydrogeol J 16(2):335–348. CrossRefGoogle Scholar
  19. Li P, Qian H, Wu J (2010) Groundwater quality assessment based on improved water quality index in Pengyang County, Ningxia, northwest China. J Chem 7(S1):S209–S216. CrossRefGoogle Scholar
  20. Li P, Qian H, Wu J, Zhang Y, Zhang H (2013a) Major ion chemistry of shallow groundwater in the Dongsheng Coalfield, Ordos Basin, China. Mine Water Environ 32(3):195–206. CrossRefGoogle Scholar
  21. Li P, Wu J, Qian H (2013b) Assessment of groundwater quality for irrigation purposes and identification of hydrogeochemical evolution mechanisms in Pengyang County, China. Environ Earth Sci 69(7):2211–2225. CrossRefGoogle Scholar
  22. Li P, Wu J, Qian H, Lyu X, Liu H (2014) Origin and assessment of groundwater pollution and associated health risk: a case study in an industrial park, northwest China. Environ Geochem Health 36(4):693–712. CrossRefGoogle Scholar
  23. Li P, Qian H, Howard KWF, Wu J (2015) Building a new and sustainable “Silk Road economic belt”. Environ Earth Sci 74(10):7267–7270. CrossRefGoogle Scholar
  24. Li P, Zhang Y, Yang N, Jing L, Yu P (2016a) Major ion chemistry and quality assessment of groundwater in and around a mountainous tourist town of China. Expo Health 8(2):239–252. CrossRefGoogle Scholar
  25. Li P, Wu J, Qian H, Zhang Y, Yang N, Jing L, Yu P (2016b) Hydrogeochemical characterization of groundwater in and around a wastewater irrigated forest in the southeastern edge of the Tengger Desert, northwest China. Expo Health 8(3):331–348. CrossRefGoogle Scholar
  26. Li P, Wu J, Qian H (2016c) Hydrochemical appraisal of groundwater quality for drinking and irrigation purposes and the major influencing factors: a case study in and around Hua County, China. Arab J Geosci 9(1):15. CrossRefGoogle Scholar
  27. Li X, Wu P, Han Z, Shi J (2016d) Sources, distributions of fluoride in waters and its influencing factors from an endemic fluorosis region in central Guizhou, China. Environ Earth Sci 75:981. CrossRefGoogle Scholar
  28. Li P, Li X, Meng X, Li M, Zhang Y (2016e) Appraising groundwater quality and health risks from contamination in a semiarid region of northwest China. Expo Health 8(3):361–379. CrossRefGoogle Scholar
  29. Li P, Tian R, Xue C, Wu J (2017a) Progress, opportunities and key fields for groundwater quality research under the impacts of human activities in China with a special focus on western China. Environ Sci Pollut Res 24(15):13224–13234. CrossRefGoogle Scholar
  30. Li P, Qian H, Zhou W (2017b) Finding harmony between the environment and humanity: an introduction to the thematic issue of the Silk Road. Environ Earth Sci 76(3):105. CrossRefGoogle Scholar
  31. Li P, Feng W, Xue C, Tian R, Wang S (2017c) Spatiotemporal variability of contaminants in lake water and their risks to human health: a case study of the Shahu Lake tourist area, northwest China. Expo Health 9(3):213–225. CrossRefGoogle Scholar
  32. Li P, He S, He X, Tian R (2017d) Seasonal hydrochemical characterization and groundwater quality delineation based on matter element extension analysis in a paper wastewater irrigation area, northwest China. Expo Health. CrossRefGoogle Scholar
  33. Li P, Qian H, Wu J (2018a) Conjunctive use of groundwater-surface water to reduce soil salinization in the Yinchuan Plain, northwest China. Int J Water Resour Dev. CrossRefGoogle Scholar
  34. Li P, Wu J, Tian R, He S, He X, Xue C, Zhang K (2018b) Geochemistry, hydraulic connectivity and quality appraisal of multilayered groundwater in the Hongdunzi coal mine, northwest China. Mine Water Environ. CrossRefGoogle Scholar
  35. Mahato MK, Singh G, Singh PK, Singh AK, Tiwari AK (2017) Assessment of mine water quality using heavy metal pollution index in a coal mining area of Damodar River Basin, India. Bull Environ Contam Toxicol. CrossRefGoogle Scholar
  36. Ministry of Health of the P. R. China, Standardization Administration of the P. R. China (2006) Standards for drinking water quality (GB 5749–2006). China Standard Press, Beijing (in Chinese) Google Scholar
  37. Nair HC, Padmalal D, Joseph A, Vinod PG (2017) Delineation of groundwater potential zones in river basins using geospatial tools-an example from southern Western Ghats, Kerala, India. J Geovis Spat Anal 1:5. CrossRefGoogle Scholar
  38. Neogi B, Singh AK, Pathak DD, Chaturvedi A (2017) Hydrogeochemistry of coal mine water of north Karanpura coalfields, India: implication for solute acquisition processes, dissolved fluxes and water quality assessment. Environ Earth Sci 76:489. CrossRefGoogle Scholar
  39. Oyarzún R, Jofré E, Morales P, Maturana H, Oyarzún J, Kretschmer N, Aguirre E, Gallardo P, Toro LE, Muñoz JF, Aravena R (2015) A hydrogeochemistry and isotopic approach for the assessment of surface water–groundwater dynamics in an arid basin: the Limarí watershed, north-central Chile. Environ Earth Sci 73(1):39–55. CrossRefGoogle Scholar
  40. Qian J, Wang L, Ma L, Lu YH, Zhao W, Zhang Y (2016) Multivariate statistical analysis of water chemistry in evaluating groundwater geochemical evolution and aquifer connectivity near a large coal mine, Anhui, China. Environ Earth Sci 75:747. CrossRefGoogle Scholar
  41. Rapantová N, Krzeszowski Ś, Grmela A, Wolkersdorfer C (2012) Quantitative assessment of mine water sources based on the general mixing equation and multivariate statistics. Mine Water Environ 31:252–265. CrossRefGoogle Scholar
  42. Redwan M, Abdel Moneim AA, Amra MA (2016) Effect of water–rock interaction processes on the hydrogeochemistry of groundwater west of Sohag area, Egypt. Arab J Geosci 9:111. CrossRefGoogle Scholar
  43. Roisenberg C, Loubet M, Formoso ML, Berger G, Munoz M, Dani N (2016) Tracing the origin and evolution of geochemical characteristics of waters from the Candiota coal mine area (southern Brazil): part I. Mine Water Environ 35:29–43. CrossRefGoogle Scholar
  44. Sahu SP, Yadav M, Das AJ, Prakash A, Kumar A (2017) A multivariate statistical approach for assessment of subsidence in Jharia coalfields, India. Arab J Geosci 10:191. CrossRefGoogle Scholar
  45. Santacruz G, Ramos JA, Moran J, Lopez B, Santacruz EE (2017) Quality indices of groundwater for agricultural use in the Soconusco, Chiapas, Mexico. Earth Sci Res J 21(3):117–127. CrossRefGoogle Scholar
  46. Schoeller H (1965) Qualitative evaluation of groundwater resources. In: Methods and techniques of groundwater investigation and development. Water Research, Series-33. UNESCO, Delft, pp 54–83Google Scholar
  47. Singh CK, Kumar A, Shashtri S, Kumar A, Kumar P, Mallick J (2017) Multivariate statistical analysis and geochemical modeling for geochemical assessment of groundwater of Delhi, India. J Geochem Explor 175:59–71. CrossRefGoogle Scholar
  48. Tiwari ON, Devadoss C, Pradhan M, Nandy T (2017) Pattern recognition techniques for evaluating the spatial impact of copper mining on surface waters. Int J Environ Sci Technol 14:49–60. CrossRefGoogle Scholar
  49. Towfiqul Islam ARM, Shen S, Bodrud-Doza MD, Safiur Rahman M (2017) Assessing irrigation water quality in Faridpur district of Bangladesh using several indices and statistical approaches. Arab J Geosci 10:418. CrossRefGoogle Scholar
  50. Utom AU, Odoh BI, Egboka BCE (2013) Assessment of hydrogeochemical characteristics of groundwater quality in the vicinity of Okpara coal and Obwetti fireclay mines, near Enugu town, Nigeria. Appl Water Sci 3:271–283. CrossRefGoogle Scholar
  51. Vetrimurugan E, Elango L (2015) Groundwater quality in an intensively cultivated river delta. Water Qual Expo Health 7(2):125–141. CrossRefGoogle Scholar
  52. Vetrimurugan E, Elango L, Rajmohan N (2013) Sources of contaminants and groundwater quality in the coastal part of a river delta. Int J Environ Sci Technol 10(3):473–486. CrossRefGoogle Scholar
  53. Webster JG, Brown KL, Vincent WF (1994) Geochemical processes affecting meltwater chemistry and the formation of saline ponds in the Victoria Valley and Bull Pass region, Antarctica. Hydrobiologia 281:171–186CrossRefGoogle Scholar
  54. WHO (2017) Guidelines for drinking-water quality: fourth edition incorporating the first addendum. World Health Organization, Geneva, p 631Google Scholar
  55. Wu J, Sun Z (2016) Evaluation of shallow groundwater contamination and associated human health risk in an alluvial plain impacted by agricultural and industrial activities, mid-west China. Expo Health 8(3):311–329. CrossRefGoogle Scholar
  56. Wu J, Li P, Qian H (2013) Environmental chemistry of groundwater near an industrial area, northwest China. Asian J Chem 25(17):9795–9799. CrossRefGoogle Scholar
  57. Wu J, Li P, Qian H, Duan Z, Zhang X (2014) Using correlation and multivariate statistical analysis to identify hydrogeochemical processes affecting the major ion chemistry of waters: case study in Laoheba phosphorite mine in Sichuan, China. Arab J Geosci 7(10):3973–3982. CrossRefGoogle Scholar
  58. Wu J, Li P, Qian H (2015) Hydrochemical characterization of drinking groundwater with special reference to fluoride in an arid area of China and the control of aquifer leakage on its concentrations. Environ Earth Sci 73(12):8575–8588. CrossRefGoogle Scholar
  59. Wu J, Wang L, Wang S, Tian R, Xue C, Feng W, Li Y (2017a) Spatiotemporal variation of groundwater quality in an arid area experiencing long-term paper wastewater irrigation, northwest China. Environ Earth Sci 76(13):460. CrossRefGoogle Scholar
  60. Wu J, Xue C, Tian R, Wang S (2017b) Lake water quality assessment: a case study of Shahu Lake in the semi-arid loess area of northwest China. Environ Earth Sci 76:232. CrossRefGoogle Scholar
  61. Xiao J, Jin ZD, Zhang F, Wang J (2012) Solute geochemistry and its sources of the groundwaters in the Qinghai Lake catchment, NW China. J Asian Earth Sci 52:21–30. CrossRefGoogle Scholar
  62. Zeng G, Luo W, Wang S, Du X (2015) Hydrogeochemical and climatic interpretations of isotopic signals from precipitation to drip waters in Liangfeng Cave, Guizhou Province, China. Environ Earth Sci 74(2):1509–1519. CrossRefGoogle Scholar
  63. Zhu BQ, Yang XP, Rioual P, Qin XG, Liu ZT, Xiong HG, Yu JJ (2011) Hydrogeochemistry of three watersheds (the Erlqis, Zhungarer and Yili) in northern Xinjiang, NW China. Appl Geochem 26:1535–1548. CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.School of Environmental Science and EngineeringChang’an UniversityXi’anChina
  2. 2.Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region of the Ministry of EducationChang’an UniversityXi’anChina

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