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Groundwater Quality Research Active

Groundwater—our invisible, vital resource, what’s in our groundwater—current conditions and changes, learn about groundwater quality in principal aquifers across the nation and how it's changed over time, predicting groundwater quality in unmonitored areas, see where a contaminant is likely to occur and at what concentration, is groundwater quality getting better or worse, use the web-based tool to see how groundwater quality across the nation has changed over the decades.

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Every day, millions of gallons of groundwater are pumped to supply drinking water for about 140 million people, almost one-half of the Nation’s population. Learn about the quality and availability of groundwater for drinking, where and why groundwater quality is degraded, and where groundwater quality is changing.

Featured: 3-D Models of As and Mn in the Glacial Aquifer System

New 3-D models from the USGS National Water Quality Program predict where high concentrations of arsenic and manganese likely occur in the glacial aquifer system, groundwater supply for 30 million. Redox conditions and pH are controlling factors. 

Featured: Updated Information on Groundwater Quality

Three new USGS fact sheets update information on groundwater quality in the nation's most heavily used aquifers. Fact sheets are now available for the Edwards-Trinity aquifer system, the Stream Valley aquifers, and the Colorado Plateau aquifers. 

Groundwater is our invisible, vital resource. The USGS National Water Quality Program (NWQP) is focusing on studies of principal aquifers, regionally extensive aquifers that are critical sources of groundwater used for public supply. The studies have two main thrusts:

• Current conditions and changes through time . These assessments characterize groundwater quality in principal aquifers, comparing concentrations of inorganic constituents, such as arsenic and nitrate, and organic constituents, such as pesticides and volatile organic compounds, to benchmarks established for the protection of human health.  Tracking changes in groundwater quality through time and investigating the reasons for these changes is crucial for informing management decisions to protect and sustain our valuable groundwater resources.  See how concentrations of metals, nutrients, pesticides, and organic contaminants in groundwater are changing during decadal periods across the Nation, and view real-time fluctuations in groundwater quality.
• Predicting groundwater quality . Statistical models and 3-D characterizations predict where a contaminant is likely to occur in groundwater, at what depth, and at what concentration. These forecasts anticipate water quality in areas where groundwater has not been sampled.

From 1991 to 2010, about 6,600 wells were sampled by the NWQP to document where contaminants occur and to develop an understanding of the natural and human factors that affect the occurrence of contaminants in the Nation’s groundwater. Learn about groundwater quality in the Nation’s principal aquifers, 1991–2010 .

Explore USGS science on topics related to groundwater quality:

National Water Quality Assessment (NAWQA) Project

Contaminants in groundwater       Arsenic and Drinking Water       Chloride, Salinity, and Dissolved Solids       Emerging Contaminants       Metals and Other Trace Elements       Nutrients and Eutrophication       Pesticides and Water Quality       Radionuclides       Volatile organic compounds (VOCs)       Hydraulic Fracturing

Drinking and source-water quality       Corrosivity       Domestic (private) supply wells       Public-supply wells       Drinking-water taste and odor       Water-Quality Benchmarks for Contaminants      

Processes affecting groundwater quality       Groundwater Age       Oxidation/Reduction (Redox)

How do we do it?  Access USGS publications and manuals on National Water-Quality Project sampling methods .

Looking for information on surface-water quality as well?  Explore these links:       Surface-Water Quality and Ecology       Groundwater/Surface-Water Interaction  

National Water-Quality Assessment (NAWQA)

Nutrients and Eutrophication

Drinking Water and Source Water Research

Groundwater/Surface-Water Interaction

Hydraulic Fracturing

Chloride, Salinity, and Dissolved Solids

Arsenic and Drinking Water

Pesticides and Water Quality

Metals and Other Trace Elements

Corrosivity

Public Supply Wells

Domestic (Private) Supply Wells

Access our most recent groundwater-quality data.  

Data Release for Secondary Hydrogeologic Regions of the Conterminous United States (ver. 2.0, June 2022)

Input and results from a boosted regression tree (brt) model relating base flow nitrate concentrations in the chesapeake bay watershed to catchment characteristics (1970-2013), datasets from groundwater-quality and select quality-control data from the national water-quality assessment project, january through december 2016, and previously unpublished data from 2013 to 2015, data for fluoride occurrence in united states groundwater, generalized lithology of the conterminous united states, laboratory quality-control data associated with groundwater samples collected for hormones and pharmaceuticals by the national water-quality assessment project in 2013-15, third-party performance assessment data encompassing the time period of analysis of groundwater samples collected for hormones and pharmaceuticals by the national water-quality assessment project in 2013-15, environmental and quality-control data collected by the usgs national water-quality assessment project for hormones and pharmaceuticals in groundwater used as a source of drinking water across the united states, 2013-15, datasets and metadata for estimates of nitrate loads and yields from groundwater to streams in the chesapeake bay watershed based on land use and geology, data release for metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, wisconsin, usa, datasets from groundwater-quality data from the national water-quality assessment project, january through december 2014 and select quality-control data from may 2012 through december 2014, data from methane in aquifers used for public supply in the united states.

Below, you’ll find the latest in peer-reviewed journal articles and USGS reports on groundwater water-quality issues. 

Tritium as an indicator of modern, mixed, and premodern groundwater age

Groundwater quality in the colorado plateaus aquifers, western united states, groundwater quality in selected stream valley aquifers, western united states, groundwater quality in the edwards-trinity aquifer system, groundwater-quality and select quality-control data from the national water-quality assessment project, january 2017 through december 2019, three-dimensional distribution of residence time metrics in the glaciated united states using metamodels trained on general numerical models, the occurrence and distribution of strontium in u.s. groundwater, machine learning predictions of ph in the glacial aquifer system, northern usa, groundwater-quality and select quality-control data from the national water-quality assessment project, january through december 2016, and previously unpublished data from 2013 to 2015, fluoride occurrence in united states groundwater, the relation of geogenic contaminants to groundwater age, aquifer hydrologic position, water type, and redox conditions in atlantic and gulf coastal plain aquifers, eastern and south-central usa, groundwater quality in the ozark plateaus aquifer system, central united states, groundwater quality in the biscayne aquifer, florida, groundwater quality: decadal change.

Almost one-half of the U.S. population rely on groundwater for their water supply, and demand for groundwater for public supply, irrigation, and agriculture continues to increase. This mapper shows how concentrations of pesticides, nutrients, metals, and organic contaminants in groundwater are changing during decadal periods across the Nation.

Contaminants present in many parts of the Glacial aquifer system

Are you one of 30 million Americans whose drinking-water supply relies on groundwater from the glacial aquifer system?  A new USGS study assesses the quality of untreated groundwater from this critical water resource, which underlies parts of 25 northern U.S. states.

Updated Information on Locations of Domestic Well Use

A new USGS geonarrative illustrates where domestic (private) wells are located and how many people are using them, based on the results of a 2019 USGS...

Domestic groundwater wells in the eastern and southeastern U.S. at risk of lead contamination

About one-third of more than 8,300 wells tested across the U.S. had groundwater with chemical characteristics that could cause lead, if present in...

Groundwater Quality in the Southwest: The Rio Grande Aquifer System

A regional assessment of untreated groundwater in the Rio Grande aquifer system, which includes parts of Colorado, New Mexico and Texas, is now...

The Quality of the Nation’s Groundwater: Progress on a National Survey

The U.S. Geological Survey makes progress on a complex undertaking to survey the quality of the nation’s largest drinking-water sources.

New reports...

Groundwater Quality in the East: The Piedmont and Blue Ridge Crystalline-Rock Aquifers

A regional assessment of untreated groundwater in the Piedmont and Blue Ridge crystalline-rock aquifers, which includes parts of 11 states across the...

Groundwater Quality in the Midwest: The Cambrian-Ordovician Aquifer System

A regional assessment of untreated groundwater in the Cambrian-Ordovician aquifer system, which includes parts of Minnesota, Wisconsin, Michigan, Iowa...

Groundwater Quality in the North: The Glacial Aquifer System

A regional assessment of untreated groundwater in the Glacial aquifer system, which includes parts of 25 states across the northern contiguous United...

Scientists Home in on Causes of High Radium Levels in Key Midwestern Aquifer

Oxygen levels, dissolved minerals among factors responsible for high concentrations of radium in untreated water from aquifer that underlies six...

Study Estimates about 2.1 Million People using Wells High in Arsenic

Most Arsenic Presumed to be From Naturally Occurring Sources

Unconventional Oil and Gas Production Not Currently Affecting Drinking Water Quality

Decades or longer may be needed to fully assess the effects of unconventional oil and gas production on the quality of groundwater used for drinking...

Groundwater Quality in the Northern Atlantic Coastal Plain Aquifer System

A regional assessment of untreated groundwater in the Northern Atlantic Coastal Plain aquifer system in the eastern United States is now available...

Groundwater Quality in the Southeastern Coastal Plain Aquifer System

A regional assessment of untreated groundwater in the Southeastern Coastal Plain aquifer system is now available from the U.S. Geological Survey.

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• Published: 26 July 2023

Assessment of groundwater hydrochemistry, water quality, and health risk in Hainan Island, China

• Qingqin Hou 1 , 2   na1 ,
• Yujie Pan 3   na1 ,
• Min Zeng 4 ,
• Simiao Wang 5 ,
• Huanhuan Shi 6 ,
• Changsheng Huang 4 &
• Hongxia Peng 1 , 7 , 8  

Scientific Reports volume  13 , Article number:  12104 ( 2023 ) Cite this article

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• Environmental chemistry
• Environmental impact
• Environmental sciences

Groundwater is an important source of water for human sustenance. The determination of groundwater quality at island sites is an urgent priority in China, but there are lacking systematic reports relating to them. Here, 63 groups of groundwater samples were collected and analyzed of Hainan Island. The groundwater in the study area is weakly alkaline, mainly comprising hard and soft freshwater. The predominant anions and cations are HCO 3 − , and Ca 2+ and Na + , respectively, and the main water chemistry types are HCO 3 –Cl–Na and HCO 3 –Cl–Na–Ca. The chemical evolution of groundwater is mainly affected by water–rock interactions, cation exchange, and human activity. The groundwater is mostly of high quality and, in most areas, is suitable for drinking and irrigation. Contrastingly, the water quality in the west of the island is relatively poor. The spatial distribution of the risk coefficient (HQ) is consistent with the spatial variation in the NO 3 − concentrations in the groundwater. Notably, there are unacceptable health risks for different groups of people, with infants having the greatest level of impact, followed by children, teenagers, and adults. This study provides a valuable reference for the development and utilization of groundwater resources, as well as the improvement of aquatic ecological conditions on Hainan Island and other island areas worldwide.

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Introduction

Groundwater is an important source of water for consumption, irrigation, and industrial use 1 , 2 , 3 , 4 . However, the improvement in people’s living standards and the degree of industrialization has resulted in a perpetual increase in the demand for water resources 5 , 6 , 7 , consequently leading to the over-exploitation of global groundwater resources, deterioration in water quality, and worsening of water security problems 8 , 9 , 10 , 11 . In particularly, groundwater resources face severe challenges, especially in island areas with more fragile natural ecosystems 12 , 13 , 14 . Most of the island areas have low rainfall, large evaporation, serious water and soil loss, and relatively lack of surface water resources. Therefore, the exploitation and utilization of groundwater is extremely important for the production and life of residents. The island groundwater system is an independent circulating system with limited supply sources. If water quality pollution is caused by natural factors and human activities, it may cause irreversible losses.

The chemical composition of groundwater is the result of its long-term interactions with the surrounding environment 15 . During groundwater formation and migration, physical and chemical interactions occur with the surrounding media, which affect the chemical composition of the water 16 , 17 . Simultaneously, groundwater is increasingly being affected by human factors 18 , 19 . Harmful substances produced by humans may enter groundwater, and the resulting pollution, which is spread via groundwater flows, can penetrate deep into the ground. In particular, NO 3 − produced by industrial production, agricultural activities and domestic sewage will enter shallow or even deep groundwater with rainwater or surface water, affecting the water quality and hydrochemical evolution process 20 . At present, nitrate pollution has become one of the major pollutants in the global groundwater and has caused potential health risks to residents 21 , 22 . The water quality index (WQI) simplifies the complex water quality index into a single value, which can be used to evaluate the water quality more intuitively and effectively 23 . At present, it has been widely used in the evaluation of drinking and irrigation water, and even innovatively used by some scholars to evaluate the suitability for industrial use. Nsabimana et al. and Li et al. used a new industrial water quality index (Ind WQI) model to determine the overall industrial water quality 24 . According to the determination of the main influencing factors in water quality assessments, the health risk assessment model and the assessment standard provided by the U.S. Environmental Protection Agency (USEPA) can be used to further assess risks to human health 25 .

Hainan Island is China’s second largest island, with one of the largest special economic zones and free trade ports, serving as the country’s major development strategy. Due to its location advantages and policy support, Hainan Island has undergone rapid modernization and the establishment of numerous industrial and agricultural parks. This rapid economic development has also increased pressure on residential water supplies and caused a series of ecological and environmental issues, including pollution, soil salinization, and seawater intrusion 26 , 27 . However, current research on groundwater on Hainan Island remains focused on hydro-chemical exploration, with a lack of comprehensive research on water quality evaluation and human health risk.

To address this research gap, the main goals of this study were to (1) analyze the groundwater hydro-chemical characteristics and the main controlling factors on Hainan Island; (2) evaluate the suitability of groundwater for drinking and irrigation; and (3) assess the risk of the nitrates in groundwater to human health. Our findings will help to better understand the chemical characteristics and quality of groundwater in this area of China, and provide a reference for the development and utilization of groundwater resources and the improvement of the aquatic ecological environment.

Materials and methods

Hainan Island is located at the southernmost tip of China (18° 10′–20° 10′ N and 108° 37′–111° 03′ E; Fig.  1 ). Hainan is surrounded by the sea, located in the tropics and subtropics, and receives abundant precipitation; however, the problems of regional and seasonal precipitation are prominent. High temperatures throughout the year drive strong evaporation. The long-term annual average rainfall in Hainan is 1750 mm, but it is unevenly distributed. The central and northeastern parts of the island receive more rain than the southwest regions. Hainan Island is low and flat, with raised topography in the center of the island, which limits the options for surface water storage. As China’s largest provincial-level special economic zone, the island has a growing population density and is experiencing rapid industrial development, which has resulted in high water demand, leading to a scarcity of water resources. At the end of the 1970s, the amount of groundwater exploitation in Hainan Island was only 290 million m 3 /a. After the construction of Hainan Island as a province, the amount of groundwater exploitation gradually increased due to economic development and technological progress. In 2004, the amount of groundwater exploitation increased to 515 million m 3 /a. Since then, due to the introduction of the national underground water pipe control policy and the enhancement of the development and utilization capacity of surface water, the mining capacity has gradually decreased, and the water supply of underground water in 2015 is still 274 million m 3 /a.

Groundwater sampling points on Hainan Island, China. The map was created using ArcGIS 10.8 ( https://www.esri.com/software/ArcGIS ).

According to the type of water-bearing medium and occurrence conditions, the groundwater in Hainan Island can be divided into five types: bedrock fissure water, pore-confined water of loose and semi-consolidated rock, volcanic rock pore fissure water, carbonate rock fissure karst water, and loose rock pore phreatic water. The main aquifer strata are Quaternary, Neogene, Cretaceous and Triassic. The groundwater in the area is mainly supplied by atmospheric rainfall, and some sections are supplied by surface water. Its runoff generally follows a complete hydrogeological unit, its flow direction is perpendicular to the contour line, and flows from high to low. With Wuzhi Mountain, Limu Mountain, Diaoluo Mountain, etc. as the core, the groundwater runoff flows around and radiates, and discharges along the coast. Generally, it is discharged to rivers, lakes, or discharged to the ground in the form of springs and scattered wetlands. Artificial drainage of groundwater has also become an important form of discharge.

Sample collection and testing

A total of 63 groups of groundwater samples were collected from civilian wells, pump wells and springs, with the sampling well depth between 3.5 and 340 m. According to the sampling depth, it is divided into shallow groundwater (0–20-m deep), middle groundwater (20–50-m deep) and deep groundwater (> 50-m deep), which are respectively from phreatic water, middle confined water and deep confined water. The water temperature, pH, conductivity, dissolved oxygen, total dissolved solids, and redox potential were measured on-site using a portable water-quality analyzer (HQ-40d, HACH, America). The collected water samples were filtered using 0.45-μm microporous filter membranes and then packed in 500-mL polyethylene plastic sample bottles that had been rinsed with deionized water at least three times. The samples used for the determination of cations were acidified to pH < 2 with approximately 3 mL of 65% HNO 3 . The samples for anion detection, without any modification, were sealed and stored in a refrigerator at 4 °C. The processed samples were tested by the Changsha Mineral Resources Supervision and Testing Center, Ministry of Land and Resources. The contents of K + , Na + , Ca 2+ , and Mg 2+ were determined using a plasma-generation spectrometer (ICP-MS; 7700X, Agilent Technologies, Japan); the contents of SO 4 2− , Cl − , and NO 3 − were measured by ion chromatography (ICS-1100, Thermo Scientific, America); and the content of HCO 3 − was determined by titration. The detection limit of each ion was 0.01 mg/L and the measurement error was less than 0.1%. After all the analysis procedures were completed, the charge balance error (CBE) was calculated by the following formula:

In the study, the average value of CBE is less than 5%, indicating that the analysis result is reasonable.

Data processing

Water quality index (wqi).

The WQI is an effective tool for appraising the overall quality of groundwater 28 , and is calculated as:

where i represents the sample number; \({W}_{i}\) and \({w}_{i}\) are the relative weight and weight of each index, respectively (Table S1 ); \({C}_{i}\) and \({S}_{i}\) are the measured concentration and permissible value of each index, respectively; and EW i is the effective weight of each index. WQI values can be categorized as non-drinkable ( WQI  ≥ 300), very poor (200 ≤  WQI  < 300), poor (100 ≤  WQI  < 200), good (50 ≤  WQI  < 100), and excellent ( WQI  < 50).

Irrigation water quality

Understanding the properties of groundwater is essential in areas where it is used as a source of irrigation. For example, an excessive salt content can result in sodium and salinity hazards 29 , 30 . In this study, the irrigation water quality was assessed based on the sodium adsorption ratio (SAR), soluble sodium percentage (% Na), and residual sodium carbonate (RSC), as follows:

where all the ionic concentrations of the respective ions are expressed in milliequivalents per liter (meq/L).

Health risk assessment

The health risk assessment models and standards provided by the USEPA have been widely used to quantitatively assess potential hazards. Previous studies suggested that the oral ingestion of groundwater pollutants is more harmful to human health than inhalation and skin contact, and several factors that are human health risks induced by skin-contact pollutants are relatively uncertain. Therefore, we assessed the threat of nitrate pollution to human health through drinking using 28 , 29 :

where HQ is the non-carcinogenic risk coefficient; E and RfD are the exposure dose and reference dose, respectively; C is the measured nitrate concentration; IR is the daily water consumption; EF is the exposure frequency; ED is the exposure duration; BW is the average body weight; and AT is the average lifetime. Table S2 shows the parameters of the health risk assessment model used to assess the risk from groundwater nitrates on Hainan Island 31 , 32 , 33 , 34 .

Monte Carlo simulation is a random number based calculation method used to simulate probability distribution functions, suitable for simulating highly complex phenomena that traditional analytical methods are difficult to solve. Its basic idea is to simulate a set of random variables that conform to the probability distribution function through random sampling, and perform numerical calculations or statistical analysis based on these random variables to obtain statistical quantities or numerical results. This method can to some extent reduce the impact of exposure parameter uncertainty in health risk models. The concentration of nitrate (C), adult weight (BW), and ingestion rate (IR) were considered as variable parameters, and distribution functions were shown in Table S3 21 . Monte Carlo simulation was performed using Crystal Ball 11.1.2.4 and iterated 10,000 times to ensure the robustness of the study.

Results and discussion

Groundwater chemical characteristics, descriptive statistics.

The pH of groundwater on Hainan Island ranged from 5.11 to 9.37, with an average of 7.47, indicating weak alkalinity (Table 1 ). According to the TDS content, the underground water can be divided into fresh water (TDS < 1000 mg/L) and brackish water (TDS > 1000 mg/L). According to the TH content, the underground water can be divided into soft water (TH < 150 mg/L) and hard water (TH > 150 mg/L). The range and mean value of TDS were 30.95–1077.30 and 287.41 mg/L, respectively, with only one water sample exceeding 1000 mg/L. The range and mean TH were 5.31–495.72 and 121.91 mg/L, respectively, indicating that the island’s groundwater is a combination of both hard and soft freshwater.

The relative abundances of the major cations in the sampled groundwater were in the order of Ca 2+  > Na +  > Mg 2+  > K + , whereas those of the anions were in the order of HCO 3 −  > NO 3 −  > Cl −  > SO 4 2− . The dominant cation was HCO 3 − , which accounted for 42.42% of the total anion concentration, whereas the dominant cations were Ca 2+ and Na + , which accounted for 36.83% and 32.07% of the total cation concentration, respectively. The coefficient of variation of the main ions in the groundwater ranged from 0.14 to 1.61, with the values of Mg 2+ , K + , Cl − , SO 4 2− , and NO 3 − exceeding 1. This indicates that the spatial distribution of these ions was significantly different, with a high degree of local enrichment.

The nitrate concentration in the groundwater samples was 0–226.26 mg/L, with an average of 38.92 mg/L. Based on these results, 41.27% of the samples exceeded the class III value of 20 mg/L, as specified in China’s groundwater quality standard (2017), which was mainly attributable to the discharge of domestic sewage and industrial and agricultural activities.

Hydro-chemical classification of groundwater

Groundwater chemistry is closely correlated with water quality 35 . Piper diagrams are often used to examine the general chemical characteristics and types of groundwater. The Piper diagrams for Hainan Island showed that the predominant cations comprised Ca 2+ and Na +  + K + terminal members, and the predominant anions comprised HCO 3 − terminal members, which may be mainly related to the rich rainfall and the dissolution of carbonate minerals in the study area (Supplementary Fig. S1 ). According to the Schukalev classification, the hydro-chemical types of the regional groundwater were, therefore, HCO 3 –Cl–Na and HCO 3 –Cl–Na–Ca. In the Piper diagram, the groundwater sample points in the study area are relatively scattered and there are many types of hydrochemical types, indicating that the groundwater chemical characteristics vary greatly and may be affected by natural and human factors.

Factors controlling groundwater chemistry

Natural factors.

Gibbs diagrams, which divide formation mechanisms into natural factors, including precipitation, rock weathering processes, and evaporation, are widely employed to explore groundwater formation mechanisms. These diagrams have, indeed, been applied by many scholars to assess groundwater evolution 36 . The groundwater samples from Hainan Island were mainly distributed in the “rock dominance” area, with a few falling in the “precipitation dominance” area (Fig.  2 a,b). This suggests that rock weathering processes dominated the groundwater chemistry in the study area. Precipitation also had some influence on groundwater chemistry, whereas evaporation (and crystallization) appeared to have little influence. Some of the shallow groundwater sample points fell outside of the model block diagram, indicating a stronger influence of human activities.

Gibbs diagrams of groundwater hydro-chemistry for ( a ) total dissolved solids (TDS) versus Na + /(Ca 2+  + Na + ); ( b ) TDS versus Cl − /(Cl −  + HCO 3 − ); ( c ) Mg 2+ /Na + versus Ca 2+ /Na + ; and ( d ) HCO 3 − /Na + versus Ca 2+ /Na + .

The effect of rock weathering on the hydro-chemical evolution of groundwater can be further explored using endmember diagrams. Weathering sources can be divided into carbonate weathering 37 , silicate weathering, and evaporite dissolution based on the ratios of Mg 2+ /Na + , Ca 2+ /Na + , and HCO 3 − /Na + . The groundwater samples from the study area were mainly plotted between the silicate and carbonate weathering endmembers, with only a few samples plotted between the silicate weathering and evaporite dissolution endmembers (Fig.  2 c,d). In contrast to the shallow groundwater samples, the middle and deep groundwater samples tended toward the carbonate mineral endmembers. This implies that the weathering of silicate and carbonate minerals plays a major role in the evolution of groundwater on the island, with a weaker contribution from evaporite dissolution.

Figure  3 shows the Pearson correlation coefficient matrix between the measured groundwater chemical parameters. A strong significant, positive correlation can be observed between Na + and Cl − (r = 0.92), indicating that the two ions had similar sources. The ratio of Na + and Cl − can also indicate the sources of Na + and K + in groundwater 38 . Most of the Hainan samples were plotted to the left of the 1:1 equivalent line (Supplementary Fig. S2 a), indicating that the excess Na + and K + in the groundwater may have originated from the weathering of silicate rocks or cation exchange.

Correlation matrix between water chemistry variables. p < 0.10, **p < 0.05, ***p < 0.01.

Ca 2+ and Mg 2+ were significantly, positively correlated with HCO 3 − (r = 0.78 and r = 0.70, respectively), indicating a common source. The sources of Ca 2+ and Mg 2+ can be determined by (Ca 2+  + Mg 2+ )/HCO 3 − : > 1, indicating that the dissolution of carbonate rocks is likely dominant, and < 1, indicating that the dissolution of silicate and evaporite rocks are considered dominant 39 . For Hainan Island, most of the middle and deep groundwater samples were plotted to the lower right of the 1:1 line (Supplementary Fig. S2 b), indicating that the Ca 2+ and Mg 2+ in these waters were mainly derived from the dissolution of silicates and evaporites. In contrast, the ratios of 71.15% of the shallow groundwater samples were > 1, the dominance of the dissolution of carbonate rocks.

The ratio of Cl −  + SO 4 2− and HCO 3 − can also be used as an index to distinguish the relative contributions of the weathering of different types of rocks. Both the middle and deep groundwater samples were plotted to the upper left in Supplementary Fig. S2 c, indicating that the dissolved ions in these waters were mainly affected by evaporite rocks. In comparison, the shallow groundwater samples were distributed on both sides of the 1:1 line, indicating inputs from both evaporite and carbonate rocks.

Through their long-term interaction, the negative charges carried by rock surfaces can adsorb cations from and release cations to groundwater, i.e., alternate cation adsorption can occur. The possibility of alternate cation adsorption can be determined by the relationship (Mg 2+  + Ca 2+ –SO 4 2– HCO 3 − )/(Na +  + K + –Cl − ), whereby ratios closer to − 1 indicate cation exchange 32 . Most of the shallow, middle, and deep groundwater samples from Hainan Island were plotted around the − 1 ratio line (Supplementary Fig. S2 d), indicating alternate cation adsorption.

The direction and intensity of alternate cation adsorption can be further expressed using the Chloron–Alkaline Index (CAI). In this case, when the Ca 2+ and Mg 2+ in groundwater are exchanged with Na + and K + in the aquifer, both CAI-I and CAI-II are negative, and when reverse ion exchange occurs, CAI-I and CAI-II are positive 40 , 41 . For the Hainan Island samples, 88.89% of the CAI values were negative (Supplementary Fig. S2 e). This indicates that reverse cation exchange is dominant and likely acts to increase the Na + and K + and decrease the Ca 2+ and Mg 2+ concentrations in groundwater. These processes act as an important source of sodium.

Anthropogenic inputs

Nitrate has good solubility in water 42 . Therefore, NO 3 − in wastewater, waste gas, and waste produced through human activities can enter shallow and deep groundwater via rainwater or surface water, thereby affecting groundwater quality and water chemistry 43 . The relationship between Cl − /Na + and NO 3 − /Na + can reflect the influence of groundwater by human activities; the higher the ratio, the stronger the effect of human activities on groundwater chemistry 44 . The ratios of Cl − /Na + and NO 3 − /Na + were relatively high in the samples from Hainan Island (Supplementary Fig. S2 f). Indeed, most of the water samples showed bias towards agricultural activities, with only a few points plotting between carbonate rock and salt rock. This indicates some degree of agricultural pollution on the island. Simultaneously, NO 3 − and K + were strongly correlated (r = 0.71), indicating that agricultural fertilizers, such as potassium fertilizer, that are not fully absorbed by crops enter surface waters or penetrate the groundwater system with irrigation water, resulting in nitrate pollution. The amount of fertilizer applied in Hainan Province is 511,400 tons, including 152,700 tons of nitrogen fertilizer, 40,500 of phosphate fertilizer, 91,100 tons of potassium fertilizer and 227,100 tons of compound fertilizer (Fig. S3 ). The higher application rate of chemical fertilizer can also support our conjecture.

The groundwater samples with NO 3 − concentrations higher than the class III limit specified by China’s groundwater quality standard (20 mg/L) were mainly obtained from Dongfang City and Danzhou City in the west of the island; Sanya City, Ledong County, and Lingshui County in the south; and Wenchang City and Qionghai City in the northeast and coastal areas (Supplementary Fig. S4 a). The high hydrochloride content of the groundwater in these areas may present a certain health risk to the locals; therefore, it cannot be considered suitable as a direct source of drinking water. Given the ongoing development of “tropical agriculture” on Hainan Island, the use of chemical fertilizers needs to be carefully controlled to reduce the impact of agricultural pollution on groundwater quality and avoid damage to the ecological environment.

Water quality evaluation

Adaptability of groundwater for drinking.

Groundwater quality assessment is very important for determining regional drinking water safety 45 . In this study, the WQI was used to evaluate the drinking water quality in the study area. The WQI of the groundwater on Hainan Island ranged from 9.96 to 266.10, with an average of 61.37; and 60.32% of the samples were classified as “excellent”, 19.05% as “good”, 14.29% as “medium”, and 4.76% as “poor”. The overall water quality was “good”. The average Ew i for NO 3 − and pH were the highest, at 43.67% and 29.73%, respectively, indicating that these parameters had the greatest impact on the WQI (Table S1 ).

The groundwater in the study area showed strong spatial variability (Supplementary Fig. S4 b). The samples with “good” water quality were mainly distributed in the middle of the island, whereas the samples with “poor” water quality were mainly obtained from the coastal areas of Dongfang City and to the west of Danzhou City. This may partially reflect the west of the island being on the leeward slope of the southeast monsoon. The southeast monsoon is blocked by Wuzhi Mountain; thus, the air in the southwest is relatively dry, with low precipitation. In addition, the rich mineral resources and convenient transport links in the west of the island make its industry develop rapidly, but also affect the quality of groundwater. Thus, a combination of natural and human factors has a major impact on the groundwater quality of the island.

Adaptability of groundwater for irrigation

Groundwater is the main water source of water for agricultural irrigation; however, high salinity and sodium content in irrigation water lead to salinization, which reduces soil quality and crop yields 46 . The SAR and %Na values can be used to evaluate these potential effects, and RSC indicates the potential for removing Ca 2+ and Mg 2+ from soil solutions. For Hainan Island, the SAR and RSC values were 0.18–3.6 and − 4.16 to 0.99, respectively (Table 1 ). This indicates that all the groundwater sampling points were suitable for irrigation. However, the %Na values ranged from 10.28 to 82.36, with 14.29% of the samples exceeding the acceptable limit for irrigation by 60.

Wilcox and USSL plots can help to evaluate the quality of irrigation water 47 , 48 . Wilcox plots are divided into five areas—“excellent to good”, “good to permissible”, “permissible to doubtful”, “doubtful to unsuitable”, and “unsuitable” 49 . Most of the Hainan Island samples were distributed in the excellent to permissible categories, with one sample (from Changjiang County) falling into the “permissible to doubtful” category (Supplementary Fig. S4 c, Fig.  4 a). In the USSL diagram (Fig.  4 b), the samples fell into the S1 region, with most distributed in the S1C1 and S1C2 regions and 14.29% in the S1C3 region. All sampling points, except for two, were obtained from Danzhou City, Changjiang County, Dongfang City, and Baisha County in the west of the island (Supplementary Fig. S4 d). This may reflect serious seawater intrusion and the widespread distribution of salt fields in the western coastal area of Hainan Island.

Wilcox ( a ) and USSL ( b ) diagrams for irrigation water quality assessment.

Table 2 shows a comparison of irrigation suitability between Hainan Island and other coastal countries. Hainan Island, the Muda Basin in Malaysia 50 , and KwaZulu-Natal in southern Africa 51 have SAR values below 10, indicating good irrigation suitability. In comparison, 20.83% and 10.34% of northern Algeria 52 and Dar es Salaam 53 in Tanzania have SAR values above 10, indicating poor irrigation suitability. Based on %Na, the irrigation suitability of the groundwater on Hainan Island was slightly lower than that of Tamil Nadu in India, but higher than that of a few other regions. The average EC value for the Hainan Island samples was also higher than that of KwaZulu Natal in southern Africa and the Muda Basin in Malaysia, but far lower than those of Tamil Nadu in India, northern Algeria, and Dar es Salaam in Tanzania. Overall, Hainan Island exhibited good groundwater irrigation suitability compared with other regions, with lower salinity and good water quality.

When the nitrate content in groundwater exceeds the safe limit, it poses a potential threat to human health 54 . Previous studies have shown that NO 3 - is the main factor affecting water quality. While water quality assessment can indicate whether groundwater is suitable for drinking at the regional scale, it does not reflect the potential health risks caused by local pollution. Therefore, the model recommended by the U.S. Environmental Protection Agency was used to evaluate the impact of groundwater NO 3 − on human health on Hainan Island.

The HQ ranges for infants, children, adolescents, and adults were 0–10.68, 0–9.03, 0–4.16, and 0–3.66, respectively, with the greatest risk for infants and children. The average HQ of infants and children in all groundwater samples was 1.84 and 1.55, respectively, with 46.03% and 44.44% of the samples exceeding the acceptable value of 1. The average HQ for teenagers and adults was 0.72 and 0.63, respectively, with an over standard rate of 25.4%. The uncertainty analysis results of Monte Carlo simulation showed that the mean values of infants, children, adolescents, and adults were 1.85, 1.56, 0.74, and 0.64, respectively, and the probability of exceeding the threshold was 46%, 44%, 21%, and 17%, respectively (Fig.  5 ). These results are similar to the average value of traditional health risks and the proportion of exceeding acceptable risks, indicating that the results of the two methods are consistent and suitable for human health risk assessment. The NO 3 − health risks reflect the spatial distribution of the NO 3 − concentrations, which were notably high in the west of Danzhou City and Dongfang City, and central Weifang City (Fig.  6 ).

Cumulative probability distribution diagram.

Spatial distribution of the health risks (HQ, hazard quotient) associated with the use of nitrate-contaminated groundwater for drinking by infants ( a ), children ( b ), teenagers ( c ), and adults ( d ). The map was created using ArcGIS 10.8 ( https://www.esri.com/software/ArcGIS ).

Numerous studies have shown that groundwater nitrate pollution is mainly caused by human activities, such as the unqualified discharge of domestic sewage and industrial wastewater, agricultural fertilization, and runoff from livestock breeding 55 . With an increase in population and the development of industry and agriculture, nitrate pollution is becoming increasingly common worldwide. This study shows that nitrate pollution in Hainan Island is currently at a medium level, with a lower average value than that in the central and western regions of Jiaokou in northern China 56 , Songnen Plain in northeastern China 4 , and Shandong Peninsula in eastern China, but higher value than that in the North China Plain 57 and Nanchong in the southwest 58 (Supplementary Fig. S5 ). Hainan Island has a higher average concentration of nitrate in its groundwater than that in some regions of other countries, including Essaouira in Morocco 59 , Haryana in India 60 , South Africa, and Malaysia 61 , but lower than that in Tunisia 62 , and Nanganur and Mothkur in southern India 63 . Given the importance of nitrate groundwater pollution for the safety of regional drinking water, timely monitoring is essential for minimizing the risk to human health.

Conclusions

In conclusion, the groundwater on Hainan Island is mainly weakly alkaline freshwater, characterized as HCO 3 –Cl–Na and HCO 3 –Cl–Na–Ca. The chemical characteristics of groundwater are mainly affected by water–rock interactions, followed by cation alternating adsorption, and human activity. The WQI of 60.32% water sample points is less than 50, and the %Na of 85.71% is less than 60. The overall water quality is good, which is more suitable for drinking and irrigation, although the water quality is different in space. Compared with other areas, the water quality in the western part of the island is poor. Nevertheless, compared with other coastal areas, the average EC value of these samples is only 444.82, which is lower overall and more suitable for irrigation. The nitrate concentration range is 0–226.26 mg/L, and the nitrate pollution level is medium compared with areas of mainland China and other parts of the world. However, the non-carcinogenic risk of nitrate to infants is 36.51% higher than the acceptable value 1, which should be paid attention to. An appropriate level of development and management of water resources is essential, which must enable social development while maintaining use within the environmental carrying capacity. Simultaneously, the utilization efficiency of water resources needs to be improved by raising awareness of water quality and sustainability issues.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on request.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Number 41877297) and the China Geological Survey (12120114029601).

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These authors contributed equally: Qingqin Hou and Yujie Pan.

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School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430074, China

Qingqin Hou & Hongxia Peng

The second Institute of Resources and Environment Investigation of Henan Province, Henan, 471023, China

Qingqin Hou

College of Environmental Sciences and Engineering, Peking University, Beijing, 100000, China

Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430000, China

Min Zeng & Changsheng Huang

School of Mechanical Engineering and Automation, Northeastern University, Liaoning, 110819, China

Simiao Wang

School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China

Huanhuan Shi

School of Geography and Information Engineering, China University of Geosciences, No. 68, Jincheng Street, East Lake New Technology Development Zone, Wuhan, 430078, Hubei, China

Hongxia Peng

Hubei Key Laboratory of Regional Ecology and Environmental Change, China University of Geosciences, Wuhan, China

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Q.H.: Methodology, Formal analysis, Software, Methodology, Writing—original draft. Y.P.: Investigation, Data curation, Supervision, Writing—review and editing. H.P.: Conceptualization, Investigation, Resources, Funding acquisition. S.W.: Data curation, visualization, investigation. M.Z.: Methodology, Supervision, Formal analysis, Funding acquisition. C.H.: Investigation, Supervision. H.S.: Formal analysis. All authors reviewed the manuscript.

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Hou, Q., Pan, Y., Zeng, M. et al. Assessment of groundwater hydrochemistry, water quality, and health risk in Hainan Island, China. Sci Rep 13 , 12104 (2023). https://doi.org/10.1038/s41598-023-36621-3

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ORIGINAL RESEARCH article

Groundwater quality characterization for safe drinking water supply in sheikhpura district of bihar, india: a geospatial approach.

• School of Ecology and Environment Studies, Nalanda University, Rajgir, India

Groundwater quality due to geogenic factors, aggravated by anthropogenic activities, is a significant threat to human wellbeing and agricultural practices. This study aimed at mapping the spatial distribution of low and high groundwater-contaminated regions in the Sheikhpura district of Bihar for safe drinking and irrigation water availability. To account for spatial distribution, groundwater quality parameters, such as fluoride, iron, total dissolved solids, turbidity, and pH, were analyzed using integrated interpolation, geographical information systems, and regression analysis. A total of 206 dug wells and bore wells were analyzed for in-situ observations in the Sheikhpura district of Bihar, India. The analysis indicated that the periphery south of Chewara and Ariari blocks, i.e., about 9.16% of district area, is affected by fluoride content (1.55–2.32 mg/l) which is highly unsuitable for consumption, as recommended by the WHO and BIS standards. However, the remaining area (90.84%) is within the permissible limit of fluoride content (0.37–1.54 mg/l). In most areas, iron content is beyond WHO permissible limits (>0.1 mg/l), except 3.1% area in the eastern region with 0.06–0.12 mg/l iron, although iron concentrations in groundwater are under the acceptable limit (<0.3 mg/l) as per BIS standard across the district. However, pH and total dissolved solids were within permissible limits. Each of the modeled geospatial maps was validated using a set of 17 in-situ observations. The best-fit model between observed and predicted variables such as fluoride, iron, total dissolved solids, and pH produced a coefficient of determination ( R 2 ) of 0.96, 0.905, 0.91, and 0.906, respectively. The findings of this study provide insights and understanding on groundwater pollution regimes and minimize uncertain causes because of the high spatial distribution of geogenic fluoride and iron occurrence, and will also be helpful to policymakers for better planning, investments, and management to supply potable water in the area.

Introduction

Water, whether on the surface or underground, is the most essential and significant natural resource for sustaining life on Earth and for the sustainable growth of socioeconomic sectors such as irrigation and industrialization. Water, in each form, is an essential component of hydro-geo-ecological and various other metabolic, physiological, and ecological processes of living beings. The “resourcism” and unethical human activities in the Earth's biosphere–hydrosphere–geosphere have created a global water imbalance and crisis which threatens the life of the billion individuals and numerous natural ecosystems ( Mekonnen and Hoekstra, 2016 ; Falkenmark et al., 2019 ). At the global scale, in developed nations, per head water consumption is reported to be 382 l in the USA and 110 l in France ( Grafton et al., 2009 ), whereas, in developing countries like India, it is 150–200 l for drinking and domestic purposes ( CGWA, 2016 ). Even though nearly four billion people are facing severe water scarcity across the world ( Rijsberman, 2006 ; Mekonnen and Hoekstra, 2016 ; Adams et al., 2020 ; Tzanakakis et al., 2020 ), potable water scarcity is projected to affect nearly 10 billion people by 2050 ( Chouchane et al., 2018 ; Boretti and Rosa, 2019 ). Further, at the regional level, water quality deterioration, abstraction, drought, floods, erratic rainfall, etc., affect a large population due to which water scarcity has become a global issue ( Kumar et al., 2010 ; Jain, 2012 ; Jain et al., 2013 ; Boers et al., 2017 ; Ellison et al., 2017 ).

Groundwater aquifers are the primary source of water supply in rural and urban areas, mainly in the arid and semiarid regions worldwide ( Dash et al., 2010 ; Uyan and Cay, 2013 ; Rao et al., 2020 ). Groundwater scarcity in dry seasons draws global attention and perceived risk due to anthropogenic activities, like overexploitation of groundwater for irrigation, industrial, and drinking purposes ( Mekonnen et al., 2015 ; Adimalla et al., 2020b ). Therefore, the abuse of groundwater spawns hazardous impacts, mainly water quality, and quantity, in general ( Ray and Elango, 2019 ). Furthermore, groundwater resources are contaminated via anthropogenic activities and geogenic contaminants bearing rocks and soils ( Saha et al., 2018 ). Consequently, the groundwater crisis is driven by land-use changes, cropping patterns, high water demand, high-yielding crop races, and water availability ( Ellison et al., 2017 ). Inadequate management has further disturbed the global water cycle, likely accelerating groundwater pollution and climate change ( Abbott et al., 2019 ).

Groundwater systems have their unique chemistry and characteristics at each location and depend on various climatic changes, precipitation, surface water, and recharge parameters. Water quality depends mainly on underlying rock's geochemical and lithological composition and subsurface factors ( Magesh and Chandrasekar, 2013 ). Time-sensitive undulation in the source and the configuration of revived water and the hydrological and social variables may generate irregular changes in the parameters dealing with water quality ( Sahoo et al., 2019 ; Ijumulana et al., 2021 , 2022 ). Heavy metals, such as fluoride, arsenic, cadmium, iron, and mercury, and other toxic chemicals either geogenic or discharged from residential areas, industries, and agricultural land contaminate surface and subsurface systems and have been reported to have more than the permissible concentration in drinking water ( WHO, 2004 ; Bhagure and Mirgane, 2011 ; Sahoo et al., 2019 ; Adimalla et al., 2020a ; Ijumulana et al., 2021 , 2022 ). Groundwater quality has been measured using physicochemical properties, such as the concentration of arsenic, fluoride, pH, bicarbonates, chlorine, and total dissolved solids ( Kannel et al., 2007 ; Ijumulana et al., 2020 , 2021 ; Ligate et al., 2021 ). In India, including the present study area, arsenic, fluoride, iron, manganese, chromium, radon, uranium, etc., are geogenic contaminants from mineral deposits in the aquifer and have a significant health concern ( Banerjee et al., 2012 ; Thakur and Gupta, 2015 ; Saha and Sahu, 2016 ; Krishan et al., 2021 ; Sahoo et al., 2022 ). Bihar has severe problems of arsenic, fluoride, iron, nitrate, etc., contamination in groundwater. The majority of the Indo-Gangetic plain is formed by quaternary alluvium deposition (old and new). In the Southern Gangetic Plains of Bihar, groundwater from quaternary aquifers is the principal source for water supply in rural and urban areas through bore wells, dug wells, etc. ( Saha et al., 2007 ). The origin of contaminants is attributed to late quaternary stratigraphy and sedimentation in Middle Ganga Plains ( Shah, 2008 ). Fluoride contamination from underlying parent rocks and soil affects the water quality in the upper layer of alluvium and is a well-known menace ( Saha and Sahu, 2016 ). In the larger scenario, unsustainable and unplanned groundwater exploitation is constructing a negative influence on aquifer systems. It is complex ( Saha et al., 2019 ) and unfit for human consumption and irrigation purposes ( Earle, 2019 ).

India's dependency on groundwater for crop irrigation and drinking water is very high ( Shankar et al., 2011 ). The primary consumers of groundwater are utilizing about 70–90% of annual extrication for irrigation in global agriculture ( Llamas and Martínez-Santos, 2005 ; Kulkarni et al., 2015 ). It is assessed that the contribution of groundwater for irrigation is 62%, and the requirement of rural and urban water consumption is 85 and 50%, respectively, in India ( Saha and Ray, 2018 ; Saha et al., 2019 ). However, the dependency on groundwater utilization in rural Bihar is about 80%. In 2001, the per capita availability of groundwater was 1950 and 1816 cubic m for Bihar and India, respectively, and reported to decrease because of increased population, industrialization, irrigation, etc. Due to the ever-increasing population in India, the annual per capita water availability is projected to shift down from 5,177 cubic m in 1951 to 1,140 cubic m in 2051 ( MoWR, 2015 ). The total water gap across the Sheikhpura district was estimated to be 148.2 million cubic meters (MCM). For water budget, in 2020, it was estimated that groundwater and surface waters were 180.7 and 49.0 MCM, respectively ( TRUAGRICO, 2017 ). Water quantity and quality are inextricably related to water resource management and must be controlled using integrated ways to prevent water pollution.

Fluoride (F) contamination is a severe problem in groundwater across India and the world ( Changmai et al., 2018 ). It has a direct impact on the health of human beings, animals, and plants due to exceeded limits, and it varies in the air (0.1–0.6 μg/l), plant (0.01–42 mg/kg), soils (150–400 mg/kg), rocks (100–2,000 mg/kg), and water (1.0–38.5 mg/l) ( Singh et al., 2018 ). Fluoride concentration is acceptable with < 1.5 mg/l for drinking and irrigation purposes ( WHO, 1997 ). Millions of people are affected by diseases such as skeletal and dental fluorosis in many parts of India, caused by high fluoride contamination. Both lower concentrations of fluoride (0.6 mg/l) and upper concentrations of fluoride (1.2 mg/l) are harmful to health for prolonged consumption ( Singh et al., 2016 ). The fluoride concentration of 1.5–3.0 mg/l can cause dental fluorosis, and the concentration of 3.0–4.0 mg/l causes to stiffens brittle bones, and more than 4.0 mg/l of fluoride concentration can cause crippling fluorosis ( Saxena and Sewak, 2015 ). Besides, fluoride can also affect bruising of the liver, thyroid, and other organs, including deformation in bone and teeth spotting/flaking ( Jiménez-Reyes and Solache-Ríos, 2010 ). Total dissolved solids (TDS) are a useful parameter for deciding safe drinking water quality with a lower range of 500 mg/l to a higher permissible limit of 2,000 mg/l ( Jain et al., 2010 ); however, the World Health Organization (WHO) permits TDS for an extreme concentration of 1,700 mg/l ( WHO, 2008 ). The permissible limit of TDS with <300 mg/l is excellent, 300–600 mg/l good, 600–900 mg/l poor, and > 1,700 mg/l unacceptable ( WHO, 2008 ). However, the TDS concentration varies significantly due to diverse geological locations ( WHO, 2004 ; Magesh and Chandrasekar, 2013 ). The prevalence of high iron (Fe) in drinking water causes severe impacts on human health, such as diabetes, heart diseases, cirrhosis of the liver, liver cancer, and infertility ( Kumar et al., 2017 ). The permissible limit of iron content in drinking water is <0.1 mg/l ( Borah et al., 2010 ; WHO, 2011 ). pH, a crucial constraint in drinking water, varies greatly, and the permissible range is 6.5–9.5 ( Saxena and Ahmed, 2001 ; WHO, 2011 ).

In Bihar, among 38 districts, 13 districts are located beside the Gangetic river are partly impaired by pollution due to the high concentration of arsenic (As >0.05 mg/l), affecting 1,590 habitations ( Singh et al., 2014 ), whereas 11 districts are profoundly affected by fluoride pollution (F > 1.5 mg/l), having a detrimental impact over 4,157 habitations. The iron concentration (Fe > 1 mg/l) was found in 9 districts over 18,673 residences. Previous studies reported fluoride concentrations with respective concentrations of 0.00–1.34 mg/l in Bhagalpur ( Verma et al., 2017 ), 0.10–2.50 mg/l in Rohtas ( Ray et al., 2000 ), and 0.19–14.4 mg/l in Gaya ( Yasmin et al., 2011 ; Ranjan and Yasmin, 2012 ). The fluoride concentration in groundwater in the Sheikhpura district of Bihar is more than 1.5 mg/l, affecting 193 habitations ( PHED, 2009 ), and iron is < 1 mg/l; however, the WHO recommended 0.1 mg/l Fe as the permissible limit for drinking purposes.

Geostatistics has been globally applied as a decision-making tool for groundwater level ( Knotters and Bierkens, 2001 ), contamination analysis ( Gaus et al., 2003 ), groundwater quality analysis ( Yeh et al., 2006 ; Lee and Song, 2007 ; Sakram et al., 2019 ), and storage and reservoir capacity ( Rakhmatullaev et al., 2011 ). In the groundwater pollution modeling, the geostatistical interpolation techniques applied are kriging, inverse distance weighting (IDW), principal component analysis (PCA), etc. ( Chatterjee et al., 2010 ; Machiwal et al., 2011 ; Belkhiri and Narany, 2015 ; Bodrud-Doza et al., 2016 ; Verma et al., 2017 ; Kawo and Karuppannan, 2018 ). Investigating different groundwater quality parameters at every location would be time-consuming and economically inviable. The geospatial interpolation techniques are used significantly in unsampled areas. In this context, two different approaches, deterministic and geospatial methods, are adopted for groundwater pollution studies ( Sarangi et al., 2005 ; Dash et al., 2010 ), and geospatial interpolation techniques are reported and extensively applied in hydrology, hydrogeology, geography, geology, soil science, atmospheric science, etc. ( Diodato and Ceccarelli, 2005 ; Sarangi et al., 2006 ; Tweed et al., 2007 ; Dash et al., 2010 ; Pandian and Jeyachandran, 2014 ; Bodrud-Doza et al., 2016 ; Kawo and Karuppannan, 2018 ; Aher and Deshmukh, 2019 ).

This study aims for adequate information on spatial distribution of groundwater quality for long-term assessment and implementation of groundwater management strategies for irrigation and potable water supply. Therefore, this study proposed spatial mapping and distribution of groundwater quality parameters, such as fluoride, iron, pH, and TDS, using integrated interpolation techniques, geographical information systems, and regression analysis into low and high groundwater contaminated regions in the Sheikhpura district of Bihar for safe drinking and irrigation water supply. Geospatial pattern analysis of different quality parameters is essential for management and monitoring agencies such as Central and State Pollution Control Boards, farmers, agricultural research institutes, the Government of Bihar, and India to implement schemes and policy in different regions.

Materials and Methods

The study area was Sheikhpura, a district in South Bihar, India, which lies between 24 ° 45 ′ and 25 ° 45 ′ North and 85 ° 45 ′ and 86 ° 45 ′ East longitude. The district has six blocks and 360 villages, extending over 609.51 km 2 in size ( Figure 1 ). Groundwater-bearing geological formations in the area have unconsolidated sediments of alluvium plain having hard rock with fissured quartzite formation, as shown in Supplementary Figure 1 ( Rajmohan and Prathapar, 2013 ; IEED, 2019 ). IEED (2019) reported that the geology of the Sheikhpura district is composed of quartzites, phyllite, and schist rocks. Further, several studies documented that the geological formations of quartzites, phyllite, and schist rocks are primary sources of fluoride and iron in groundwater ( Rao and Devadas, 2003 ; Suthar et al., 2008 ; Okofo et al., 2021 ). The area is enriched with old alluvial soil. Most of the area is covered by sand, silt, and clay, with aquifer thickness in the range of 20–190 m because of uneven bed-rock topography across the district ( CGWB, 2013 ; TRUAGRICO, 2017 ). The hydrogeology features comprise unconsolidated formation, i.e., quaternary alluvium and consolidated formation due to hard rocks ( Supplementary Figure 1 ) ( CGWB, 2013 ). The major part is covered with old alluvium, which receives sediments from the Phalgu-Kiul sub-basin of River Ganga. Soils are coarse loamy with dominant subgroups of typic ustifluvents, fine aeric ochraqualfs, fine vertical ochraqualfs, and fine vertical ustochrepts. The major part in the south has fine vertic ochraqualfs and fine vertic ustochrepts in the middle region. In the northern side, soils are coarse loamy typic ustifluvents. The fine aeric ochraqualfs randomly occupy in the west, southeast, and northeast. The maps of soil types and dominant soil subgroups are shown in Figures 2A,B , respectively, and are used for water management strategy. The majority of the area is covered with greenish clay with caliche oxidized and pedocal soil, followed by silt and clay of variegated colors in the northeastern region and sand, silt, and clay unoxidized in the southeastern side. The greenish clay in the northern part occupies a significant area. The minimum area has silt and clay of variegated colors.

Figure 1 . Village map of Sheikhpura district indicates groundwater sample locations ( N = 206) (source: http://www.sheikhpura.bih.nic.in/ ).

Figure 2 . Soil maps (A) soil type, (B) dominant soil subgroups (source: NATMO, Kolkata, India).

Research Methods and Data Collection

With a sampling intensity of 10%, 36 villages encompassing all the blocks were randomly selected based on strata of location, population, block, and village size (big, medium, and small). Out of 2,000 bore wells in the area, 206 bore wells were sampled and analyzed. The data on F, Fe, TDS, turbidity, and pH collected by the Ministry of Drinking Water and Sanitation, Government of India, in 2017 under the National Rural Drinking Water Programme were used in this study. The geotagging of these wells was done using the Garmin eTrex Legend navigation system. We prepared a geospatial database of soil types and subgroups ( ICAR, 1998 ) in the geospatial information system (GIS) domain and land use/land cover using satellite data. Geo-coordinates of 206 well locations were imported in the GIS domain, and attributes on F, Fe, TDS, and pH were assigned to prepare geospatial maps using Arc GIS 10.9 software ( Figure 1 ).

Geospatial Modeling

The geospatial approaches such as Kriging and IDW interpolate the spatial variability of point attributes and predict for an unobserved location using nearby known attributes ( Rakhmatullaev et al., 2011 ; Sahoo et al., 2019 ; Ijumulana et al., 2020 , 2021 , 2022 ; Ligate et al., 2021 ). The Kriging interpolation technique is the optimal and widely applicable procedure for estimating unknown values (attributes) using normally distributed known data ( Jager, 1990 ; Dong et al., 2011 ; Wu et al., 2011 ; Ijumulana et al., 2022 ). A linear interpolation method predicts the value of unobserved location attributes based on probabilistic models ( Shyu et al., 2011 ; Ijumulana et al., 2021 , 2022 ) with minimum error ( Mendes and Ribeiro, 2010 ). In the present study, kriging was applied and validated the reliability of different groundwater quality parameters by incorporating geospatial statistical techniques. The water quality parameters, such as F, Fe, TDS, and pH, were characterized as good, moderate, and poor based on the ranges and permissible limits for groundwater quality characterization ( Table 1 ). Under the National Rural Drinking Water Programme, Ministry of Drinking Water and Sanitation, Government of India, in 2017, turbidity was reported almost negligible (<2 NTU) across the Sheikhpura district of Bihar. Therefore, the turbidity data were not considered for integrated interpolation, GIS, and regression analysis. Therefore, except turbidity, each parameter was assigned weights considering their negative impacts. The highest weight of four was assigned to fluoride, then iron (3), TDS (2), and the lowest (1) to pH. Fluoride is more than its permissible limit (> 1.5 mg/l); therefore, it was assigned high weight, and pH was set with the least weight due to its concentration being under the allowable limit (6.5–9.5). A simple overlay analysis considering the ranges and these weights were performed for suitability analysis. The groundwater suitability for irrigation and drinking water supply was characterized, assigned from very good (rank rating = 3), i.e., under the permissible limit, to very poor (rank rating = 1) for more than the allowable limit to each quality parameter ( Islam et al., 2018 ). With criteria for drinking and irrigation purposes, the water quality has been characterized based on each contaminant presented in Table 1 . The validation and adequacy of the model were tested by determining the coefficient of determination ( R 2 ) based on 17 randomly selected point data to establish the relationship between the actual and predicted ranges of pollution parameters.

Table 1 . Parameterization of groundwater quality assessment.

Results and Discussion

Geospatial mapping of groundwater pollutants.

In this study, groundwater quality parameter limits followed the standards outlined by WHO (1997) and BIS (2012) for drinking and irrigation purposes. Fluoride and iron concentrations exceed the permissible limit, whereas TDS and pH values are under permissible limits. Fluoride level was observed within the permissible limit except in the southeastern region ( Figure 3A ). The northern part is occupied by “Tal” (a low-lying area having soil of silt and clay of variegated colors), contaminated with fluoride ranging between 0.37 and 0.76 mg/l. The southeastern part has slightly higher concentrations of fluoride that range from 1.024 to 1.45 mg/l, which are also within the acceptable limit. The fluoride concentration is acceptable with < 1.5 mg/l for drinking and irrigation purposes, according to the WHO and BIS (Bureau of Indian Standards) standards ( WHO, 1997 ; BIS, 2012 ). Geospatial analyses indicated that the fluoride contamination with permissible limit is higher in most of the area; the moderately affected (1.16–1.54 mg/l) area in the Ariari block covers 6.54% of the total area. The majority of the area is within the fluoride concentration of 1.5 mg/l, which possesses coarse-loamy soils in the northeastern region and fine-loamy soil in the southern region of the Sheikhpura district. Besides this, the lowest range of fluoride from 0.37 to 0.76 mg/l was associated with greenish clay, characterized by caliche oxidized with pedocal soils, and covered almost 76.10% area of the entire district. 91.15% area comes under Sheikhpura, Ghat Kusumbha, Barbigha, and Sheikhpura Sarai, and major portions of Ariari blocks have groundwater with fluoride concentrations in the range of 0.37–1.54 mg/l, i.e., under the WHO-permissible limit of fluoride concentrations, and are suitable for drinking purposes. The maximum fluoride concentration was 1.54–2.32 mg/l in the southeastern region, where groundwater is unsuitable for domestic and drinking purposes. The analysis indicated that the southern peripheral area of Chewara is profoundly affected with fluoride concentrations of 1.55–2.32 mg/l, which covers 5.07% of the total district area. Pedocal soils have high concentrations of fluoride (1.94 mg/l < F <2.32 mg/l) in groundwater ( Figure 3A ) and are unsuitable for drinking purposes. This is the highest level of fluoride spread in ~24.71 km 2 (4.09%) of the total area.

Figure 3 . Geospatial maps of groundwater quality: (A) fluoride, (B) iron, (C) pH, and (D) TDS based on kriging interpolation of field observations.

Iron is a vital element and occurs naturally in water. The geogenic source of iron in groundwater is due to the underlying quartzite rocks of Sheikhpura. A similar geogenic source of iron in groundwater is reported in the literature ( Rao, 2008 ; Amanambu, 2015 ). In general, the desirable limit of iron is <0.1 mg/l ( WHO, 2011 ) and <0.3 mg/l ( BIS, 2012 ), according to the WHO and BIS standards for drinking purposes. The high concentration of iron in groundwater has a direct impact on health. The categorization of groundwater quality parameters for drinking and irrigation purposes based upon iron is presented in Table 1 . In this regard, the spatial distribution of iron concentration is shown in Figure 3B , indicating that 96.9% of the total area has a concentration of more than 0.1 mg/l. The analysis also revealed that the northern region has 0.23–0.29 mg/l of iron concentration, covering Barbigha, Sheikhpura, and Ghat Kusumbha blocks and a small portion in the Chewara block. Moreover, the west and south regions of the district exhibit a high iron level of 0.20–0.22 mg/l in Sheikhpura Sarai, Ariari, and Chewara blocks. Iron concentrations ranged from 0.13 to 0.18 mg/l in most northeastern blocks, like Sheikhpura, Chewara, and Ghat Kusumbha ( Figure 3B ). The permissible limit (0.00–0.12 mg/l) for drinking purposes was found in pockets of Sheikhpura and Chewara blocks in the northeastern region. Based on the BIS standard, iron concentrations are under the required acceptable limit (<0.3 mg/l).

The pH determines the acidity and alkalinity of groundwater as a significant water quality parameter. The permissible limit of pH ranged from 6.5 to 9.5 as per WHO recommendations ( WHO, 2011 ) and 6.5 to 8.5 according to BIS standards ( BIS, 2012 ) for drinking purposes. Figure 3C depicts the geospatial pattern of pH and is in the desirable limit. It varied from 7.04 to 7.51, under permissible limits recommended by the WHO and BIS standards in drinking water. In the northern area of the district, it ranged from 7.23 to 7.51.

TDS characterizes the total concentration of dissolved substances in groundwater, an important parameter to measure drinking water/groundwater quality. TDS indicate fully dissolved minerals, such as calcium, chlorides, carbonates, bicarbonates, magnesium, silica, and sodium, in groundwater ( Anbazhagan and Nair, 2004 ). The permissible limit <300 mg/l is excellent, and the unacceptable limit is > 1,700 mg/l ( WHO, 2008 ) and 2,000 mg/l according to BIS (2012) standards. In this regard, TDS varied between 271 and 713 mg/l. A slightly higher level of TDS (713 mg/l) was noted in small pockets of Sheikhpura and Ghat Kusumbha blocks ( Figure 3D ). Thus, it is not much of a concern for drinking and irrigation purposes ( Table 1 ). Therefore, this study recommends the development of a practical groundwater management support tool for fluoride-free water for drinking and irrigation purposes. Besides, implementing an efficient and reliable technique should be adopted to achieve groundwater quality under WHO and BIS standard permissible limits.

Model Accuracy

Seventeen observational data points were used to validate the results of Kriging interpolation. The actual observations were evaluated concerning the predicted values. The goodness of fit for an actual concentration of contaminants indicated that the coefficient of determination ( R 2 ) between observed/actual and predicted for F, Fe, TDS, and pH were 0.96, 0.905, 0.91, and 0.906, respectively ( Figures 4A–D ), which shows heterogeneity in the quality parameters ( Table 2 ).

Figure 4 . Model accuracy assessment between observed and predicted groundwater quality parameters: (A) fluoride, (B) iron, (C) pH, and (D) TDS.

Table 2 . Relationship between observed vis-à-vis predicted groundwater quality.

Geospatial Modeling for Suitability of Groundwater

Characterization for groundwater quality mapping based on class interval and weights to different layers of F, Fe, TDS, and pH per their significance is shown in a map ( Figure 5 ). Prioritization of groundwater quality was done for planning and conservation of groundwater resources for drinking and irrigation purposes. Only 5.08% area is falling under the “very good” category. Many villages are in Sheikhpura block, whereas four villages, viz., Angpur, Bahuwara, Chakandara, and Chewara villages, are of the Chewara block, and two villages, Kusumbha and Rajauli villages, are of the Ghat Kusumbha block. Significant areas are covered under suitable groundwater conditions in each block, i.e., 55.84% of the total district area has groundwater fit for drinking purposes. Therein, the medium/moderate quality of groundwater is falling under all blocks, which covered 33.95% area of the district, except the Ariari block. The poor, unsuitable groundwater quality covered only 5.13% of the total area. The poor water quality only extended in Arari, Chewara, and Sheikhpura blocks. Nabinagar, Husenabad, Diha, Belchhi, Karki, and Pandhar villages are the most affected in the Arari block. In contrast, Sheikhpura and Eksari villages are affected in the Sheikhpura block, and Mane, Barari, and Chewara are the most affected from the Chewara block. Villages have been categorized under different water quality parameters with corresponding percent area, including the uninhabited village of Sheikhpura district polluted under quality parameters ( Supplementary Table 1 ).

Figure 5 . Potential groundwater quality map for planning and management of groundwater harvesting and supply.

Relationship Between Soil Types and Groundwater Quality Parameters

Groundwater is vulnerable to contamination under different soil types ( Li et al., 2020 ). Geogenic fluoride contamination is globally observed in shallow aquifers ( Edmunds and Smedley, 2013 ). In the Indo-Gangetic plains, potential fluoride contamination was observed in alluvial aquifers of northwest India, but < 1.5 mg/l of fluoride concentration in groundwater ( Lapworth et al., 2017 ). Therefore, the principal source of contamination might be from underlying rocks and the flow rate in the aquifers ( Saha et al., 2007 ; Saha and Sahu, 2016 ). Overall, it was observed that the groundwater quality parameters exceed the desirable limits for domestic, drinking, and agriculture purposes at several locations in the Sheikhpura district. In Sheikhpura, the high fluoride concentration in the range of 1.55–2.32 mg/l was found in the southeastern region. In addition, the iron concentration is found in the range of 0.13–0.30 mg/l, which is above the permissible limit recommended by the WHO. The geological characteristics which constituted quartzites, phyllite, and schist rocks are responsible for the enrichment of fluoride and iron in groundwater in the Sheikhpura area of Bihar. Both fluoride and iron are likely to indicate geogenic contamination of aquifers in the area ( Saha et al., 2007 ; Saha and Sahu, 2016 ). The pH and TDS are well within the permissible limits, i.e., 7.04–7.51 and 271–713 mg/l, respectively, as per WHO recommendations. The causal relationship between soil types and groundwater contaminants across the district is tabulated ( Table 3 ).

Table 3 . Summarized relationship between soil types and groundwater quality.

Groundwater contaminant concentrations were randomly distributed among different soil types in the area. There is no noticeable, quantifiable, and significant relationship between soil types and groundwater contaminants. A similar study by Sheehan et al. (2003) highlighted no statistical correlation between groundwater chemistry and toxicity and soil. However, the lack of correlation between soil and groundwater contaminants must not ignore the potential risk assessment to quantify contaminated soils for determining underlying aquifers characteristics, land uses, and groundwater footprint.

Conclusions

Integrated interpolation techniques, geostatistical systems, and regression analysis have proved efficient decision-making tools for groundwater quality analysis, monitoring, and management. In this study, the spatial groundwater quality parameters, such as F, Fe, TDS, and pH, were analyzed across six blocks of the Sheikhpura district of Bihar. Groundwater in Sheikhpura, Arari, and Chewara blocks were contaminated with high fluoride concentrations up to 2.42 mg/l. In addition, iron has also spread with more than the WHO permissible limit (>0.1 mg/l) across all six blocks. Reasons behind the enrichment of fluoride and iron in the groundwater of the Sheikhpura district of Bihar are the underlying geological features composed of quartzites, phyllite, and schist rocks. Besides this, TDS and pH were found under the allowable limit across the district. The spatial analysis of different parameters is conducted based on the Kriging method by estimating unobserved locations relating to the known values. This study also attempted to establish the relationship between soil types and groundwater contaminants; however, no statistical correlation was found for each groundwater quality parameter considered for spatial mapping in the Sheikhpura district. The final groundwater quality map highlighted the area having groundwater quality from “poor” to “very good” across the district. In the interpolated map, the overall groundwater quality of the Arari, Chewara, and Sheikhpura blocks is not appropriate; thus, aquifer quality is relatively low and not acceptable for drinking and irrigation purposes. Thus, spatial mapping of groundwater quality will help policymakers to better operate and manage the groundwater resources through detecting pollutants, demand–supply gap, etc. Overall, proper utility and management of groundwater through canals, channels, and underground movement from safe to affected blocks/zones are recommended for drinking and agricultural purposes to avoid carcinogenic diseases among the population in the future.

Data Availability Statement

Publicly available datasets were analyzed in this study. This data can be found at: All the primary groundwater quality data were obtained from the website of Ministry of Drinking Water and Sanitation, Government of India, surveyed in 2017 under the National Rural Drinking Water Programme and has been duly acknowledged. Map of soil types and soil subgroups published by the National Bureau of Soil Survey and Land Use Planning (ICAR 1998), Nagpur, India. were used.

Author Contributions

RiK: conceptualization, sampling strategy, fieldwork, GIS database creation and analysis, and writing of the first draft of the manuscript. SS: conceptualization, sampling strategy, methodology, GIS analysis supervision, review of results, and editing of the manuscript. RaK: support in GIS analysis, writing, reviewing, and editing of the manuscript. PS: initial conceptualization, review, and editing of the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors would like to record their gratitude to SEES lab, Nalanda University for scientific facilities and also like to express their gratitude to the National Rural Drinking Water Programme, Ministry of Drinking Water and Sanitation, Government of India for allowing access to the data on their website. We want to thank Dr. Dharmendra Singh, Assistant Scientist (Environment/Ecology) Haryana Space Applications Centre, Hissar for his timely help during the analysis.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frwa.2022.848018/full#supplementary-material

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Keywords: groundwater pollution, geospatial modeling, fluoride, iron, Bihar

Citation: Kumar R, Singh S, Kumar R and Sharma P (2022) Groundwater Quality Characterization for Safe Drinking Water Supply in Sheikhpura District of Bihar, India: A Geospatial Approach. Front. Water 4:848018. doi: 10.3389/frwa.2022.848018

Received: 03 January 2022; Accepted: 11 February 2022; Published: 24 March 2022.

Reviewed by:

Copyright © 2022 Kumar, Singh, Kumar and Sharma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Rakesh Kumar, rakesh.kumar.PhD@nalandauniv.edu.in

† ORCID: Sarnam Singh orcid.org/0000-0003-1829-7941 Rakesh Kumar orcid.org/0000-0001-7264-5682 Prabhakar Sharma orcid.org/0000-0003-0894-0809

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• Open access
• Published: 09 September 2022

Water quality index for assessment of drinking groundwater purpose case study: area surrounding Ismailia Canal, Egypt

• Hend Samir Atta   ORCID: orcid.org/0000-0001-5529-0664 1 ,
• Maha Abdel-Salam Omar 1 &
• Ahmed Mohamed Tawfik 2  

Journal of Engineering and Applied Science volume  69 , Article number:  83 ( 2022 ) Cite this article

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The dramatic increase of different human activities around and along Ismailia Canal threats the groundwater system. The assessment of groundwater suitability for drinking purpose is needed for groundwater sustainability as a main second source for drinking. The Water Quality Index (WQI) is an approach to identify and assess the drinking groundwater quality suitability.

The analyses are based on Pearson correlation to build the relationship matrix between 20 variables (electrical conductivity (Ec), pH, total dissolved solids (TDS), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), chloride (Cl), carbonate (CO 3 ), sulphate (SO 4 ), bicarbonate (HCO 3 ), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), lead (Pb), cobalt (Co), chromium (Cr), cadmium (Cd), and aluminium (Al). Very strong correlation is found at [Ec with Na, SO 4 ] and [Mg with Cl]; strong correlation is found at [TDS with Na, Cl], [Na with Cl, SO 4 ], [K with SO 4 ], [Mg with SO 4 ] and [Cl with SO 4 ], [Fe with Al], [Pb with Al]. The water type is Na–Cl in the southern area due to salinity of the Miocene aquifer and Mg–HCO 3 water type in the northern area due to seepage from Ismailia Canal and excess of irrigation water.

The WQI classification for drinking water quality is assigned with excellent and good groundwater classes between km 10 to km 60, km 80 to km 95 and the adjacent areas around Ismailia Canal. While the rest of WQI classification for drinking water quality is assigned with poor, very poor, undesirable and unfit limits which are assigned between km 67 to km 73 and from km 95 to km 128 along Ismailia Canal.

Introduction

Nowadays, groundwater has become an important source of water in Egypt. Water crises and quality are serious concerns in a lot of countries, particularly in arid and semi-arid regions where water scarcity is widespread, and water quality assessment has received minimal attention [ 3 , 9 ]. So, it is important to assess the quality of water to be used, especially for drinking purposes.

Poor hydrogeological conditions have been encountered causing adverse impacts on threatening the adjacent groundwater aquifer under the Ismailia Canal. The groundwater quality degradation is due to rapid urban development, industrialization, and unwise water use of agricultural water, either groundwater or surface water.

As groundwater quality is affected by several factors, an appropriate study of groundwater aquifers characteristics is an essential step to state a supportable utilization of groundwater resources for future development and requirements [ 11 , 12 ]. It is important that hydrogeochemical information is obtained for the region to help improving the groundwater management practices (sustainability and protection from deterioration) [ 17 ].

Many researchers have paid great attention to groundwater studies. In the current study area, the hydrogeology and physio-hydrochemistry of groundwater in the current study area had been previously discussed by El Fayoumy [ 15 ] and classified the water to NaCl type; Khalil et al. [ 27 ] stated that water had high concentration of Na, Ca, Mg, and K. Geriesh et al. [ 21 ] detected and monitored a waterlogging problem at the Wadi El Tumilate basin, which increased salinity in the area. Singh [ 34 ] studied the problem of salinization on crop yield. Awad et al. [ 7 ] revealed that the groundwater salinity ranges between 303 ppm and 16,638 ppm, increasing northward in the area.

Various statistical concepts were used to understand the water quality parameters [ 24 , 28 , 35 ].

Armanuos et al. [ 4 ] studied the groundwater quality using WQI in the Western Nile Delta, Egypt. They had generated the spatial distribution map of different parameters of water quality. The results of the computed WQI showed that 45.37% and 66.66% of groundwater wells falls into good categories according to WHO and Egypt standards respectively.

Eltarabily et al. [ 19 ] investigate the hydrochemical characteristics of the groundwater at El-Khanka in the eastern Nile Delta to discuss the possibility of groundwater use for agricultural purposes. They used Pearson correlation to deduce the relationship between 13 chemical variables used in their analysis. They concluded that the groundwater is suitable for irrigation use in El-Qalubia Governorate.

The basic goal of WQI is to convert and integrate large numbers of complicated datasets of the physio-hydrochemistry elements with the hydrogeological parameters (which have sensitive effect on the groundwater system) into quantitative and qualitative water quality data, thus contributing to a better understanding and enhancing the evaluation of water quality [ 38 ]. The WQI is calculated by performing a series of computations to convert several values from physicochemical element data into a single value which reflects the water quality level's validity for drinking [ 16 ].

Based on the physicochemical properties of the groundwater, it should be appraised for various uses. One can determine whether groundwater is suitable for use or unsafe based on the maximum allowable concentration, which can be local or international. The type of the material surrounding the groundwater or dissolving from the aquifer matrix is usually reflected in the physicochemical parameters of the groundwater. These metrics are critical in determining groundwater quality and are regarded as a useful tool for determining groundwater chemistry and primary control mechanisms [ 18 ].

The objective of this research is to assess suitability of groundwater quality of the study area around Ismailia Canal for drinking purpose and generating WQI map to help decision-makers and local authorities to use the created WQI map for groundwater in order to avoid the contamination of groundwater and to facilitate in selection safely future development areas around Ismailia Canal.

Description of study area

The study area lies between latitudes 30° 00′ and 31° 00′ North and longitude 31° 00′ and 32° 30′ East. It is bounded by the Nile River in the west, in the east there is the Suez Canal, in the south, there is the Cairo-Ismailia Desert road, and in the north, there are Sharqia and Ismailia Governorates as shown in Fig. 1 . Ismailia Canal passes through the study area. It is considered as the main water resource for the whole Eastern Nile Delta and its fringes. Its intake is driven from the Nile River at Shoubra El Kheima, and its outlet at the Suez Canal. At the intake of the canal, there are large industrial areas, which include the activities of the north Cairo power plant, Amyeria drinking water plant, petroleum companies, Abu Zabaal fertilizer and chemical company, and Egyptian company of Alum. Ismailia Canal has many sources of pollution, which potentially affects and deteriorates the water quality of the canal [ 22 ].

Map of the study area and location of groundwater wells

The topography plays an important role in the direction of groundwater. The ground level in the study area is characterized by a small slope northern Ismailia Canal. It drops gently from around 18 m in the south close to El-Qanater El-Khairia to 2 amsl northward. While southern Ismailia Canal, it is characterized by moderate to high slope. The topography rises from 10 m to more than 200 m in the south direction.

Geology and hydrogeology

The sequence of deposits rocks of wells was investigated through the study of hydrogeological cross-section A-A′ and B-B′ located in Fig. 2 a, b [ 32 ]. Section B-B′ shows that the study area represents two main aquifers that can be distinguished into the Oligocene aquifer (southern portion of the study area) and the Quaternary aquifer (northern portion of the study area). The Oligocene aquifer dominates the area of Cairo-Suez aquifer foothills. The Quaternary occupies the majority of the Eastern Nile Delta. It consists of Pleistocene sand and gravel. It is overlain by Holocene clay. The aquifer is semi-confined (old flood plain) and is phreatic at fringes areas in the southern portion of eastern Nile Delta fringes. The Quaternary aquifer thickness varies from 300 m (northern of the study area) to 0 at the boundary of the Miocene aquifer (south of the study area). The hydraulic conductivity ranges from 60 m/day to 100 m/day [ 8 ]. The transmissivity varies between 10,000 and 20,000 m 2 /day.

a Geology map of the study area. b Hydrogeological cross-section of the aquifer system (A-A′) and geological cross-section for East of Delta (B-B′)

Groundwater recharge and discharge

The main source of recharge into the aquifer under the study area is the excess drainage surplus (0.5–1.1 mm/day) [ 29 ], in addition to the seepage from irrigation system including Damietta branch and Ismailia Canal.

Groundwater and its movements

In the current research, it was possible to attempt drawing sub-local contour maps for groundwater level with its movement as shown in Fig. 3 . Figure 3 shows the main direction of groundwater flow from south to north. The groundwater levels vary between 5 m and 13 m (above mean sea level). The sensitive areas are affected by (1) the excess drainage surplus from the surface water reclaimed areas which located at low lying areas; (2) the seepage from the Ismailia Canal bed due to the interaction between it and the adjacent groundwater system, and (3) misuse of the irrigation water of the new communities and other issues. Accordingly, a secondary movement was established in a radial direction that is encountered as a source point at the low-lying area (Mullak, Shabab, and Manaief). Groundwater movement acts as a sink at lower groundwater areas (the northern areas of Ismailia Canal located between km 80 to km 90) due to the excessive groundwater extraction. The groundwater level reaches 2 m (AMSL). The groundwater levels range between + 15 m (AMSL) (southern portion of Ismailia Canal and study area near the boundary between the quaternary and Miocene aquifers).

Groundwater flow direction map in the study area (2019)

The assessment of groundwater suitability for drinking purposes is needed and become imperative based on (1) the integration between the effective environmental hydrogeological factors (the selected 9 trace elements Fe, Mn, Zn, Cu, Pb, Co, Cr, Cd, Al) and 11 physio-chemical parameters (major elements of the anions and cations pH, EC, TDS, Na, K, Ca, Mg, Cl, CO 3 , SO 4 , HCO 3 ); (2) evaluation of WQI for drinking water according to WHO [ 36 ] and drinking Egyptian standards limit [ 14 ]; (3) GIS is used as a very helpful tool for mapping the thematic maps to allocate the spatial distribution for some of hydrochemical parameters with reference standards.

The groundwater quality for drinking water suitability is assessed by collecting 53 water samples from an observation well network covering the area of study, as seen in Fig. 1 . The samples were collected after 10 min of pumping and stored in properly washed 2 L of polyethylene bottles in iceboxes until the analyses were finished. The samples for trace elements were acidified with nitric acid to prevent the precipitation of trace elements. They were analyzed by the standard method in the Central Lab of Quality Monitoring according to American Public Health Association [ 2 ].

The water quality index is used as it provides a single number (a grade) that expresses overall water quality at a certain location based on several water quality parameters. It is calculated from different water parameters to evaluate the water quality in the area and its potential for drinking purposes [ 13 , 25 , 31 , 33 ]. Horton [ 23 ] has first used the concept of WQI, which was further developed by many scholars.

The first step of the factor analysis is applying the correlation matrix to measure the degree of the relationship and strength between linearly chemical parameters, using “Pearson correlation matrix” through an excel sheet. The analyses are mainly based on the data from 53 wells for physio-chemical parameters for the major elements and trace elements. Accordingly, it classified the index of correlation into three classes: 95 to 99.9% (very strong correlation); 85 to 94.9% (strong correlation), 70 to 84.9% (moderately), < 70% (weak or negative).

Equation ( 1 ) [ 4 ] is used to calculate WQI for the effective 20 selected parameters of groundwater quality.

In which Q i is the ith quality rating and is given by equation ( 2 ) [ 4 ], W i is the i th relative weight of the parameter i and is given by Eq. ( 3 ) [ 4 ].

Where C i is the i th concentration of water quality parameter and S i is the i th drinking water quality standard according to the guidelines of WHO [ 36 ] and Egypt drinking water standards [ 14 ] in milligram per liter.

Where W i is the relative weight, w i is the weight of i th parameter and n is the number of chemical parameters. The weight of each parameter was assigned ( w i ) according to their relative importance relevant to the water quality as shown in Table 2 , which were figured out from the matrix correlation (Pearson correlation, Table 1 ). Accordingly, it was possible assigning the index for weight ( w i ). Max weight 5 was assigned to very strong effective parameter for EC, K, Na, Mg, and Cl; weight 4 was assigned to a strong effective parameter as TDS, SO 4 ; 3 for a moderate effective parameter as Ca; and weight 2 was assigned to a weak effective parameter like pH, HCO 3, CO 3 , Fe, Cr, Cu, Co, Cd, Pb, Zn, Mn, and Al. Equation ( 2 ) was calculated based on the concertation of the collected samples from representative 53 wells and guidelines of WHO [ 36 ] and Egypt drinking water standards [ 14 ] in milligram per liter. This led to calculation of the relative weight for the weight ( W i ) by equation ( 3 ) of the selected 20 elements (see Table 2 ). Finally, Eq. ( 1 ) is the summation of WQI both the physio-chemical and environmental parameters for each well eventually.

The spatial analysis module GIS software was integrated to generate a map that includes information relating to water quality and its distribution over the study area.

Results and discussion

The basic statistics of groundwater chemistry and permissible limits WHO were presented in Table 3 . It summarized the minimum, maximum, average, med. for all selected 20 parameters and well percentage relevant to the permissible limits for each one; the pH values of groundwater samples ranged from 7.1 to 8.5 with an average value of 7.78 which indicated that the groundwater was alkaline. While TDS ranged from 263 to 5765 mg/l with an average value of 1276 mg/l. Sodium represented the dominant cation in the analyzed groundwater samples as it varied between 31 and 1242 mg/l, with an average value of 270 mg/l. Moreover, sulfate was the most dominant anion which had a broad range (between 12 and 1108 mg/l), with an average value of 184 mg/l. This high sulfate concentration was due to the seepage from excess irrigation water and the dissolution processes of sulfate minerals of soil composition which are rich in the aquifer. Magnesium ranged between 11 and 243 mg/l, with an average value of 43 mg/l. The presence of magnesium normally increased the alkalinity of the soil and groundwater [ 10 , 37 ]. Calcium ranged between 12 and 714 mg/l with a mean value of 119 mg/l. For all the collected groundwater samples, calcium concentration is higher than magnesium. This can be explained by the abundance of carbonate minerals that compose the water-bearing formations as well as ion exchange processes and the precipitation of calcite in the aquifer. Chloride content for groundwater samples varies between 18 and 2662 mg/l with an average value of 423 mg/l. Carbonate was not detected in groundwater, while bicarbonate ranged from 85 to 500 mg/l. Figures 5 , 6 , and 7 were drawn to show the extent of variation between the samples in each well.

Piper diagram [ 30 ] was used to identify the groundwater type in the study area as shown in Fig. 4 . According to the prevailing cations and anions in groundwater samples Na–Cl water type in the southern area due to salinity of the Miocene aquifer, Mg–HCO 3 water type in the northern area due to seepage from Ismailia Canal and excess of irrigation water and there is an interference zone which has a mixed water type between marine water from south and fresh water from north.

Piper trilinear diagram for the groundwater samples

Concentration of selected physio-chemical parameters

Concentration of major elements

Concentration of trace element

Concentration for 20 elements by percentage of wells (relevant to their limits of WHO for each element)

a , b WQI aerial distribution for drinking groundwater suitability for WHO ( a ) and Egyptian standards ( b )

Atta, et al. [ 5 ] revealed that the abundance of Fe, Mn, and Zn in the groundwater is due to geogenic aspects, not pollution sources. Khalil et al. [ 26 ] and Awad et al. [ 6 ] revealed that the source of groundwater in the area is greatly affected by freshwater seepage from canals and excess irrigation water which all agreed with the study.

Table 3 and Fig. 8 showed that 100% of wells for EC were assigned at desirable limits. 43.79% of wells for TDS were assigned at the desirable limit and 27.05% of them at the undesirable limits. While pH, 81.25% were assigned at the desirable limit. The percentage of wells for the aerial distribution of cations concentration assigned at desirable limits ranged between 64.6% for K, 85.45% for Mg, 68.73% for Na, and 70.8% for Ca. While the percentage of wells for the aerial distribution of cations concentration assigned at the undesirable limits ranged between 8.3% for Mg, 31.27% for Na, 14.6% for K, and 16.7% for Ca.

The percentage of wells for the aerial distribution of anions concentration assigned at desirable limits ranged between 72.9% for Cl, 66.7% for HCO 3 , and 79.2% for SO 4 . While the percentage of wells for the aerial distribution of anions concentration assigned at the undesirable limit ranged between 4.2% for Cl, 0% for HCO 3 , and 20.8% for SO 4 as shown in Table 3 and Fig. 8 .

Table 3 and Fig. 8 presented the aerial distribution concentration for 8 sensitive trace elements. The percentage of wells assigned at desirable limits ranged between 100% for (Zn, Cr, and Co), 86% for Fe, 27.3% for Mn, 77.4% for Cd, 27.2% for Pb, and 96% for Al, while the percentage of wells assigned at undesirable limits ranged between 0% for (Fe, Zn, Cr, and Co), 50% for Mn, 13.6% for Cd, 36.4% for Pb, and 4% for Al.

Figure 8 summarizes the results of the concentration for the selected 20 elements (11 physio-hydrochemical characteristics, and 9 sensitive environmental trace elements) by %wells relevant to the limits of WHO for each element.

The water quality index is one of the most important methods to observe groundwater pollution (Alam and Pathak, 2010) [ 1 ] which agreed with the results. It was calculated by using the compared different standard limits of drinking water quality recommended by WHO (2008) and Egyptian Standards (2007). Two values for WQI were calculated and drawn according to these two standards. It was classified into six classes relevant to the drinking groundwater quality classes: excelled water (WQI < 25 mg/l), good water (25–50 mg/l), poor water (50–75 mg/l), very poor water (75–100 mg/l), undesirable water (100–150 mg/l), and unfit water for drinking water (> 150 mg/l) as shown in Fig. 9 a, b. Figure 9 a (WHO classification) indicated that in the most parts of the study area, the good water class was dominant and reached to 35.8%, 28.8% was excellent water; 7.5% were poor water, 11.3% very poor water quality, and 13.3% were unfit water for drinking water. Similarly, for Egyptian Standard classification via WQI, the study area was divided into six classes: Fig. 9 b indicated that 35.8% of groundwater was categorized as excellent water quality, 34% as good water quality, 9.4% as poor water, 5.7% as very poor water, 1.9% as undesirable water and 13.3% as unfit water quality. This assessment was compared to Embaby et al. [ 20 ], who used WQI in the assessment of groundwater quality in El-Salhia Plain East Nile Delta. The study showed that 70% of the analyzed groundwater samples fall in the good class, and the remainder (30%), which were situated in the middle of the plain, was a poor class which mostly agreed with the study.

Conclusions and recommendation

This research studied the groundwater quality assessment for drinking using WQI and concluded that most of observation wells are located within desirable and max. allowable limits.

The groundwater in the study area is alkaline. TDS in groundwater ranged from 263 to 5765 mg/l, with a mean value of 1277 mg/l. Sodium and chloride are the main cation and anion constituents.

The water type is Na–Cl in the southern area due to salinity of the Miocene aquifer, Mg–HCO 3 water type in the northern area due to seepage from Ismailia Canal and excess of irrigation water and there is an interference zone which has a mixed water type between marine water from south and fresh water from north.

The WQI relevant to WHO limits indicated that 23% of wells were located in excellent water quality class that could be used for drinking, irrigation and industrial uses, 38% of wells were located in good water quality class that could be used for domestic, irrigation, and industrial uses, 11% of wells were located in poor water quality class that could be used for irrigation and industrial uses, 8% of wells were located in very poor water quality class that could be used for irrigation, 6% of wells were located in unsuitable water quality class which is restricted for irrigation use and 15% of wells were located in unfit water quality which will require proper treatment before use.

The WQI relevant to Egyptian standard limits indicated that 25% of wells were located in excellent water quality class that could be used for drinking, irrigation, and industrial uses, 43% of wells were located in good water quality class that could be used for domestic, irrigation, and industrial uses, 8% of wells were located in poor water quality class that could be used for irrigation and industrial uses, 6% of wells were located in very poor water quality class that could be used in irrigation, 6% of wells were located in unsuitable water quality class which is restricted for irrigation use and 13% of wells were located in unfit water quality which will require proper treatment before use.

The percentage of wells located at unfit water for drinking were assigned in the Miocene aquifer, and north of Ismailia Canal between km 67 to km 73 and from km 95 to km 128.

It is highly recommended to study the water quality of the Ismailia Canal which may affect the groundwater quality. It is recommended to study the water quality in detail between km 67 to 73 and from km 95 to km 128 as the WQI is unfit in this region and needs more investigations in this region. A full environmental impact assessment should be applied for any future development projects to maximize and sustain the groundwater as a second resource under the area of Ismailia Canal.

Availability of data and materials

The datasets generated and analyzed during the current study are not publicly available because they are part of a PhD thesis and not finished yet but are available from the corresponding author on reasonable request.

Abbreviations

World Health Organization

• Water Quality Index

Electrical conductivity

Total dissolved solids

Bicarbonate

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Atta, H.S., Omar, M.AS. & Tawfik, A.M. Water quality index for assessment of drinking groundwater purpose case study: area surrounding Ismailia Canal, Egypt. J. Eng. Appl. Sci. 69 , 83 (2022). https://doi.org/10.1186/s44147-022-00138-9

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Groundwater contamination is a global problem that has a significant impact on human health and ecological services. Studies reported in this special issue focus on contaminants in groundwater of geogenic and anthropogenic origin distributed over a wide geographic range, with contributions from researchers studying groundwater contamination in India, China, Pakistan, Turkey, Ethiopia, and Nigeria. Thus, this special issue reports on the latest research conducted in the eastern hemisphere on the sources and scale of groundwater contamination and the consequences for human health and the environment, as well as technologies for removing selected contaminants from groundwater. In this article, the state of the science on groundwater contamination is reviewed, and the papers published in this special issue are summarized in terms of their contributions to the literature. Finally, some key issues for advancing research on groundwater contamination are proposed.

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Groundwater is a major source of fresh water for the global population and is used for domestic, agricultural, and industrial uses. Approximately one third of the global population depends on groundwater for drinking water (International Association of Hydrogeologists 2020 ). Groundwater is a particularly important resource in arid and semi-arid regions where surface water and precipitation are limited (Li et al. 2017a ). Securing a safe and renewable supply of groundwater for drinking is one of the crucial drivers of sustainable development for a nation. However, urbanization, agricultural practices, industrial activities, and climate change all pose significant threats to groundwater quality. Contaminants, such as toxic metals, hydrocarbons, trace organic contaminants, pesticides, nanoparticles, microplastics, and other emerging contaminants, are a threat to human health, ecological services, and sustainable socioeconomic development (Li 2020 ; Li and Wu 2019 ).

Over the past three decades, chemical contamination is a common theme reported in groundwater studies. While groundwater contamination is a great challenge to human populations, this subject also presents a great opportunity for researchers to better understand how our subsurface aquifers have evolved and for decision makers to grasp how we can protect both the quality and quantity of these resources. Fresh water aquifers are one of the most important sections of the Critical Zone (CZ), which extends from the top of the vegetation canopy down to the bottom of the aquifer (Lin 2010 ). As part of the global effort to understand the functions, structures, and processes within the CZ, a range of investigations have been performed that contribute to our knowledge of the circulation and evolution of groundwater (Sawyer et al. 2016 ; Goldhaber et al. 2014 ).

Many of the contaminants in groundwater are of geogenic origin as a result of dissolution of the natural mineral deposits within the Earth’s crust (Basu et al. 2014 ; Pandey et al. 2016 ; Subba Rao et al. 2020 ; He et al. 2020a ). However, due to rapid expansion of the global population, urbanization, industrialization, agricultural production, and the economy, we now are faced with the challenge of the negative impacts of contaminants of anthropogenic origin. The countries most affected by these global changes are those that are going through rapid economic development, with many of them located in the eastern hemisphere (Clement and Meunie 2010 ; Hayashi et al. 2013 ; Lam et al. 2015 ). Thus, it is appropriate that this special issue entitled, “The fate and consequences of groundwater contamination” focuses on studies of the unique challenges related to contaminants of both anthropogenic and geogenic origin in groundwater in several countries in the eastern hemisphere, including China, India, Turkey, Bangladesh, Ethiopia, and Nigeria. Figure  1 illustrates the countries where the research was conducted and the classes of chemical contaminants reported in the articles in this special issue.

Eastern hemisphere, showing the countries where the groundwater research was conducted and the classes of contaminants studied in the articles published in this special issue

The range of topics included in articles in this special issue includes: (1) Latest methods for detecting and tracking the movement of groundwater contaminants; (2) Novel techniques for assessing risks to human populations consuming contaminated groundwater; (3) Effects of groundwater contamination on the abiotic environment, such as soil, sediments, and surface water; and (4) Case studies and remedial actions to control groundwater contamination from natural and anthropogenic sources. The co-editors of this special issue anticipate that these articles will facilitate an understanding of the origins and extent of groundwater contamination and its consequences and will provide examples of approaches that can be taken for remediation of groundwater contamination and protection of groundwater quality.

Major Contaminants

Groundwater contamination is defined as the addition of undesirable substances to groundwater caused by human activities (Government of Canada 2017 ). This can be caused by chemicals, road salt, bacteria, viruses, medications, fertilizers, and fuel. However, groundwater contamination differs from contamination of surface water in that it is invisible and recovery of the resource is difficult at the current level of technology (MacDonald and Kavanaugh 1994 ). Contaminants in groundwater are usually colorless and odorless. In addition, the negative impacts of contaminated groundwater on human health are chronic and are very difficult to detect (Chakraborti et al. 2015 ). Once contaminated, remediation is challenging and costly, because groundwater is located in subsurface geological strata and residence times are long (Wang et al. 2020 ; Su et al. 2020 ). The natural purification processes for contaminated groundwater can take decades or even hundreds of years, even if the source of contamination is cut off (Tatti et al. 2019 ).

The numbers of classes of contaminants detected in groundwater are increasing rapidly, but they can be broadly classified into three major types: chemical contaminants, biological contaminants, and radioactive contaminants. These contaminants can come from natural and anthropogenic sources (Elumalai et al. 2020 ). The natural sources of groundwater contamination include seawater, brackish water, surface waters with poor quality, and mineral deposits. These natural sources may become serious sources of contamination if human activities upset the natural environmental balance, such as depletion of aquifers leading to saltwater intrusion, acid mine drainage as a result of exploitation of mineral resources, and leaching of hazardous chemicals as a result of excessive irrigation (Su et al. 2020 ; Wu et al. 2015 ; Li et al. 2016 , 2018 ).

Nitrogen contaminants, such as nitrate, nitrite, and ammonia nitrogen, are prevalent inorganic contaminants. Nitrate is predominantly from anthropogenic sources, including agriculture (i.e., fertilizers, manure) and domestic wastewater (Hansen et al. 2017 ; He and Wu 2019 ; He et al. 2019 ; Karunanidhi et al. 2019 ; Li et al. 2019a ; Serio et al. 2018 ; Zhang et al. 2018 ). Groundwater nitrate contamination has been widely reported from regions all over the world. Other common inorganic contaminants found in groundwater include anions and oxyanions, such as F − , SO 4 2− , and Cl − , and major cations, such as Ca 2+ and Mg 2+ . Total dissolved solids (TDS), which refers to the total amount of inorganic and organic ligands in water, also may be elevated in groundwater. These contaminants are usually of natural origin, but human activities also can elevate levels in groundwater (Adimalla and Wu 2019 ).

Toxic metals and metalloids are a risk factor for the health of both human populations and for the natural environment. Chemical elements widely detected in groundwater include metals, such as zinc (Zn), lead (Pb), mercury (Hg), chromium (Cr), and cadmium (Cd), and metalloids, such as selenium (Se) and arsenic (As). Exposures at high concentrations can lead to severe poisoning, although some of these elements are essential micronutrients at lower doses (Hashim et al. 2011 ). For example, exposure to hexavalent chromium (Cr 6+ ) can increase the risk of cancer (He and Li 2020 ). Arsenic is ranked as a Group 1 human carcinogen by the US Environmental Protection Agency (EPA) and the International Agency for Research on Cancer (IARC), and As 3+ can react with sulfhydryl (–SH) groups of proteins and enzymes to upset cellular functions and eventually cause cell death (Abbas et al. 2018 ; Rebelo and Caldas 2016 ). Toxic metals in the environment are persistent and subject to moderate bioaccumulation when they enter the food chain (He and Li 2020 ; Hashim et al. 2011 ).

Organic contaminants have been widely detected in drinking water, and many of these compounds are regarded as human carcinogens or endocrine disrupting chemicals. In groundwater, more than 200 organic contaminants have been detected, and this number is still increasing (Lesser et al. 2018 ; Jurado et al. 2012 ; Lapworth et al. 2012 ; Sorensen et al. 2015 ). Some organic contaminants are biodegradable, while some are persistent. The biodegradable organic contaminants originate mainly from domestic sewage and industrial wastewater. Many of these organic substances are naturally produced from carbohydrates, proteins, fats, and oils and can be transformed into stable inorganic substances by microorganisms. They have no direct toxic effects on living beings but can reduce the dissolved oxygen levels in groundwater. Common organic contaminants include hydrocarbons, halogenated compounds, plasticizers, pesticides, pharmaceuticals, and personal care products and natural estrogens, among others (Lapworth et al. 2015 ; Meffe and Bustamante 2014 ). Many of the halogenated compounds (e.g., chlorinated, brominated, fluorinated) are stable in the environment and can be accumulated and enriched in organisms, causing harmful effects in organisms from higher trophic levels, including humans (Gwenzi and Chaukura 2018 ; Schulze et al. 2019 ). The persistent organic contaminants are mainly compounds used for agriculture, industrial processes, and protection of human health (Lapworth et al. 2015 ). Because these compounds degrade very slowly or even not at all, they may permanently threaten the quality of groundwater for drinking purposes (Schulze et al. 2019 ).

Radioactive contaminants in groundwater can originate from geological deposits of radionuclides but also can originate from anthropogenic sources, such as wastes from nuclear power plants, nuclear weapons testing, and improper disposal of medical radioisotopes (Dahlgaard et al. 2004 ; Lytle et al. 2014 ; Huang et al. 2012 ). Radioactive substances can enter the human body through a variety of routes, including drinking water. However, radioactive contaminants have been rarely detected in groundwater at levels that are a threat to human health.

Biological contaminants include algae and microbial organisms, such as bacteria, viruses, and protozoa. For microbial contaminants, more than 400 kinds of bacteria have been identified in human and animal feces, and more than 100 kinds of viruses have been recognized (Shen and Gao 1995 ). Some of these microbial organisms originate from natural sources, but some include microscopic organisms that co-exist with natural algal species and compete for available resources (Flemming and Wuertz 2019 ; Lam et al. 2018 ). Drinking water contaminated by microbial contaminants can result in many human diseases, including serious diarrheal diseases, such as typhoid and cholera. Currently, the COVID-19 virus has resulted in pandemic affecting every corner of the world. This coronavirus is primarily transmitted from person-to-person through respiratory droplets (Centers for Disease Control and Prevention 2020 ). However, water contaminated by this virus also can threaten human health (Bhowmick et al. 2020 ; Lokhandwala and Gautam 2020 ). Algal contamination is very common in surface waters, such as lakes and reservoirs due to eutrophication, but algae are rarely found at a high biomass in groundwater.

Consequences of Groundwater Contamination

Groundwater contamination can impact human health, environmental quality, and socioeconomic development. For example, many studies have shown that high levels of fluoride, nitrate, metals, and persistent organic pollutants are a health risk for human populations (Wu et al. 2020 ). This is especially critical for infants and children who are more susceptible to the effects of these contaminants than adults (He et al. 2020b ; Wu and Sun 2016 ; Karunanidhi et al. 2020 ; Mthembu et al. 2020 ; Ji et al. 2020 ; Subba Rao et al. 2020 ; Zhou et al. 2020 ). For example, “blue baby syndrome,” also known as infant methemoglobinemia, is caused by excessive nitrate concentrations in the drinking water used to make baby formulas. Human health also can be affected by the groundwater contamination through effects on the food production system. Irrigation with groundwater contaminated by heavy metals and wastewater containing persistent contaminants can result in the accumulation of toxic elements in cereals and vegetables, causing health risks to humans (Jenifer and Jha 2018 ; Yuan et al. 2019 ; Njuguna et al. 2019 ).

Groundwater contamination also can negatively affect the quality of lands and forests. Contaminated groundwater can lead to soil contamination and degradation of land quality. For example, in many agricultural areas in arid regions, high groundwater salinity is one of the major factors influencing soil salinization (Wu et al. 2014 ). The soluble salts and other contaminants, such as toxic metals, can accumulate in the root zone, affecting vegetation growth. Groundwater contaminants also can be transported by surface water-groundwater interactions, leading to deterioration of surface water quality (Teng et al. 2018 ).

Sustainable economic development requires a balance between the rate of renewal of natural resources and human demand (Li et al. 2017b ). Freshwater is probably the most valuable of the natural resources. However, chronic groundwater contamination may reduce the availability of freshwater, breaking the balance between water supply and demand and leading to socioeconomic crises and even wars. Water shortages induced by contamination may become a factor causing conflicts among citizens in the future (Schillinger et al. 2020 ), possibly delaying the socioeconomic development of a nation. Groundwater contamination is not only an environmental issue but also a social issue, demanding collaboration between both natural scientists and social scientists.

Articles in the Special Issue

Nineteen papers are included in this special issue. The topics of these papers cover a range of contamination issues, including the sources of geogenic and anthropogenic contamination, seasonal cycles in contamination, human health risks, and remediation technologies. Figure  2 illustrates a word cloud generated using the words in the titles and abstracts of the articles in this special issue, showing the most frequently used terms. The word cloud shows that the most frequently used technical terms in the articles are water, risk, metals, nitrate, fluoride, polycyclic aromatic hydrocarbons (PAHs), health, limits, and values. These terms reflect the main topics of the articles, which cover the assessment of the concentrations of trace metals, fluoride, nitrate, PAHs, and other organic contaminants in groundwater and the associated risks to the health of human populations. Some more minor terms, such as geogenic, source, removal, statistical, EWQI, and mobility, indicate that some articles focus on evaluating the sources of groundwater contamination, approaches to groundwater quality assessment, and contaminant remediation techniques. The main contributions of each article in this special issue are summarized below.

Word cloud generated using the words in the titles and abstracts of articles in this special issue

Toxic metals are persistent contaminants and can be bioaccumulated in human tissues via food chain (He and Li 2020 ). In this special issue, six articles focused on the assessing trace metal pollution in groundwater. Çiner et al. ( 2021 ) used multivariate statistical analysis to identify the sources of trace elements in groundwater, including Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, and Ba, and assessed the health risks from arsenic contamination in a region of south-central Turkey. Their research results indicate that the carcinogenic risks from exposure to arsenic to both adults and children were higher than the guideline limit, and the geogenic processes are the main cause of trace element contamination in groundwater in this region. Chandrasekar et al. ( 2021 ) also identified geogenic metal contamination in their article focused on the source, geochemical mobility, and health risks from trace metals in groundwater in a Cretaceous-Tertiary (K/T) contact region of India. However, Raja et al. ( 2021 ) concluded that industrial activities and leaching from municipal dumpsites were the main sources of the metal pollution in the groundwater in the industrialized township (Taluk) of Virudhunagar in India.

In addition to contamination of groundwater, trace elements can be transported via groundwater into surface waters and into oceans. In the article by Prakash et al. ( 2021 ), estimates were made of the submarine groundwater discharge and associated trace element fluxes from an urban estuary region to the marine environment in the Bay of Bengal in India. This study revealed that submarine groundwater discharge is an important factor contributing to the fluxes to the sea of dissolved trace elements.

Finding efficient and cost-effective technologies for removal of trace elements from groundwater is crucial for the sustainable management of water resources. Zhao et al. ( 2021 ) studied Cd removal from water using a novel low-temperature roasting technique associated with alkali to synthesize a high-performance adsorbent from coal fly ash. Dutta et al. ( 2021 ) proposed to use electrocoagulation with iron electrodes as a treatment technology for arsenic removal from groundwater, and a pilot scale filtration unit was used to remove ferric hydroxide flocs produced during the process.

Fluoride is of value in trace amounts for promoting dental health, but this anion is toxic when present in high concentrations in water and food (Adimalla and Li 2019 ; Li et al. 2014 , 2019b ; Marghade et al. 2020 ). In this special issue, two articles specifically address fluoride occurrence, distribution, and health risks. The article by Haji et al. ( 2021 ) describes a study of groundwater quality and human health risks from fluoride contamination in a region within the southern Main Ethiopian Rift. Keesari et al. ( 2021 ) used the empirical cumulative density function to estimate the health risks from consuming fluoride contaminated groundwater in northeastern parts of Rajasthan in India. These authors also produced a fluorosis risk map to aid decision makers in taking necessary remedial measures to improve the groundwater quality.

Organic pollutants, including polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), are common contaminants of anthropogenic origin in groundwater that could cause serious health problems. In this special issue, two articles focused on these organic pollutants. The article by Ololade et al. ( 2021 ) reported an investigation into PAHs and PCBs in groundwater near selected waste dumpsites located in two southwestern states in Nigeria. They found that the more water-soluble, low molecular weight-PAHs accounted for more than 61% of the total PAHs detected across all locations, but surprisingly the more highly chlorinated hexa-PCBs dominated the congener profiles. In another paper in this issue by Ambade et al. ( 2021 ), the occurrence, distribution, health risk, and composition of 16 priority PAHs were investigated in drinking water from southern Jharkhand in the eastern part of India. These authors found that lower and middle molecular weight PAHs were dominant in groundwater from the study area, but the levels are currently below concentrations that are a carcinogenic risk.

Studies of radioactive elements in groundwater often are neglected, but these radionuclides can be a hazard to human health. Adithya et al. ( 2021 ) conducted a study in Tamil Nadu state in southern India to measure the levels of radon (Rn) in groundwater and quantify the health risks. Their study showed that the Rn is released into groundwater from granitic and gneissic rocks within uranium-enriched lithological zones. However, the Rn levels determined in Bequerels per litre were lower than the guideline limit and the groundwater does not pose health risks to consumers.

In this special issue, Adimalla and Qian ( 2021 ) conducted a study on the spatial distribution and potential health risks from nitrate pollution in groundwater in southern India. The article revealed high nitrate levels in groundwater, at concentrations up to 130 mg/L. Both adults and children were judged to face health risks from consumption of nitrate in drinking water, but children were identified as more susceptible to the effects of groundwater nitrate pollution. The paper by Karunanidhi et al. ( 2021 ) describes the improvements in groundwater quality that occurred in an industrialized region of southeastern India between January and June of 2020. These improvements included reduced nitrate contamination, which may have been due to reduced transport of nitrate into groundwater before the monsoon period, but also could have been due to the decline in industrial and agricultural activity in the region during the lockdown in India that began in March 2020 in response to the first wave of the COVID-19 pandemic. In this study, fluoride concentrations of geogenic origin also were lower in groundwater before the monsoon.

Understanding the seasonal and spatial variations in groundwater quality is essential for the protection of human health and to maintain the crop yields. Subba Rao et al. ( 2021 ) used multiple approaches to identify the seasonal variations in groundwater quality and revealed that the groundwater quality for drinking and irrigation purposes was lower in the post-monsoon period relative to the pre-monsoon period. The deterioration of groundwater quality in the post-monsoon period was attributed to contaminant transport occurring through groundwater recharge but also was influenced by topographical factors and human activities.

Understanding the hydrogeochemical processes affecting groundwater chemistry is the basis for effective management of groundwater resources. Ren et al. ( 2021 ) adopted statistical approaches and multivariate statistical analysis techniques to understand the hydrogeochemical processes affecting groundwater in the central part of the Guanzhong Basin, China. The main contribution of this article is that it could help local decision makers to make water management decisions in the densely populated river basin by providing them with useful groundwater management options.

There are four articles in this special issue that focus specifically on methods to assess groundwater quality and humfluoride and associated arsenicosis and fluoan health risks. Shukla and Saxena ( 2021 ) assessed the groundwater quality and health risk in the rural parts of Raebareli district in northern India. Wang et al. ( 2021 ) identified the hydrochemical characteristics of groundwater and assessed health risk to consumers in a part of the Ordos basin in China. Adimalla ( 2021 ) applied two indices: the entropy weighted water quality index (EWQI), and the pollution index of groundwater (PIG) to assess the suitability of groundwater for drinking purpose in the Telangana state in southeastern India. Khan et al. ( 2021 ) assessed the drinking water quality and potential health impacts by considering physicochemical parameters, as well as bacteriological contamination of groundwater in Bajaur, Pakistan.

Collectively, these articles contribute to the literature on scientific developments in the field of groundwater contamination. The case studies presented in these articles are useful for policy makers and the public to understand the current water quality status in these regions. In particular, these articles provide a window into the groundwater contamination issues that are affecting low- and middle-income countries and countries with emerging economies in the eastern hemisphere. Researchers from Europe, North America, and other high-income countries often do not grasp the extent of groundwater contamination from geogenic and anthropogenic sources in these regions and do not realize that many human populations have no choice but to consume the contaminated drinking water.

The Way Ahead

Groundwater contamination is now a global problem and the resolution of these problems requires close collaboration among researchers in universities and government agencies, industries, and decision makers from all levels of government. To solve the groundwater contamination problems, international collaboration is needed. This is particularly true in countries with developing economies where financial resources and access to advanced technologies are not readily available. Special focus should be given to the following aspects of research and training:

Groundwater contamination issues in different countries should be addressed with a range of measures, techniques, and policies. Although groundwater contamination is a global problem, its nature and influencing factors are different between countries, climatic regions, and geological features. It may not be optimal to adopt remediation approaches that are successful in other countries or regions. For example, nitrate pollution is caused by fertilizer and manure applications in some agricultural regions (Zhang et al. 2018 ) but also may be caused by pollution by industrial and domestic wastewater in other areas, or even by explosives used in mineral exploration (Li et al. 2018 ). It may be necessary to use different approaches to mitigate different types of nitrate pollution. Even in instances where fertilizer application is the common cause of nitrate pollution in a tropical and a temperate region, the remediation approaches could be different, as climate factors and soil characteristics will have a great influence on the mechanisms and extent of contaminant transport.

With the rapid technological development, many novel techniques have been developed to study groundwater contamination, including geophysical and geoinformatics techniques. Geographical information systems (GIS) and remote sensing (Ahmed et al. 2020 ; Al-Abadi et al. 2020 ; Alshayef et al. 2019 ; Kannan et al. 2019 ) have accelerated the development of groundwater science. In the future, artificial intelligence, “big data” analysis, drone surveys, and molecular and stable isotope analysis technologies will be more widely available for applications in groundwater research. Groundwater scientists need to adopt and apply these new technologies for the study of groundwater contamination.

Governments, particularly in countries with developing economies need to invest in and encourage research and training in groundwater science. In many regions, human populations have no alternative but to consume groundwater that is contaminated with chemical or biological agents, potentially causing wide ranging health effects. Investment is needed to determine the extent of this contamination and how to remediate the impacts on human health, or to find alternate sources of drinking water.

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Acknowledgements

Editing a successful special issue is not easy. The Guest Editors must ensure that the topic is of importance and of broad interest so that there are an adequate number of contributors willing to submit their manuscripts. They must also make sure that the peer review process is efficient and effective, while maintaining the high quality of the papers. All of these cannot be fulfilled without the support of the Editor in Chief. So, we are extremely grateful for Prof. Chris Metcalfe’s guidance and support for this special issue. We are also sincerely thankful to the reviewers who provided constructive comments that are essential for maintaining the high quality of the special issue. Last but not the least, the authors whose manuscripts were included and those whose manuscripts were rejected are acknowledged for their interest in contributing to the special issue. The special issue was edited in a situation in which the COVID-19 struck in nearly every corner of the world. We are impressed by the dedication of doctors who fought and/or are fighting against the coronavirus. Prof. Peiyue Li is grateful for the financial support granted by the National Natural Science Foundation of China (41761144059 and 42072286), the Fundamental Research Funds for the Central Universities of CHD (300102299301), the Fok Ying Tong Education Foundation (161098), and the Ten Thousand Talents Program (W03070125), which allow him to carry out various investigations. The year 2021 is the 70th anniversary of Chang’an University. Congratulations!

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Li, P., Karunanidhi, D., Subramani, T. et al. Sources and Consequences of Groundwater Contamination. Arch Environ Contam Toxicol 80 , 1–10 (2021). https://doi.org/10.1007/s00244-020-00805-z

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A new look at Grand Canyon springs and possible threats from uranium mining

A new research paper published recently in Annual Review of Earth and Planetary Sciences , coordinated by scientists from The University of New Mexico and collaborating institutions, addresses the complex nature and societal importance of Grand Canyon's springs and groundwater.

The paper , "Hydrotectonics of Grand Canyon Groundwater," recommends sustainable groundwater management and uranium mining threats that require better monitoring and application of hydrotectonic concepts.

The data suggest an interconnectivity of the groundwater systems such that uranium mining and other contaminants pose risks to people, aquifers, and ecosystems. The conclusion based on multiple datasets is that groundwater systems involve significant mixing.

"This is unsurprising for anyone who has looked at the mixing of rivers, but similar processes are more hidden and incompletely understood in groundwater," said Department of Earth & Planetary Sciences Distinguished Professor Karl Karlstrom, one of the paper's authors. "Water flows down gradient, and fault pathways control where groundwater ponds in sub-basins. In the Grand Canyon region, these sub-basins are each vented by major springs on tribal or Park lands."

The highest-volume springs are Havasu Spring, on the Havasupai Reservation, which supplies water for the Village of Havasupai people inside the Grand Canyon, and Blue Spring, which is of cultural significance for Navajo and Hopi peoples. Other springs emerge in Park lands and provide water for Grand Canyon's more than 6 million annual visitors. This paper shows that "hydro-tectonic" concepts are needed to understand Grand Canyon springs and groundwater wells.

"Our research efforts have utilized geologic mapping and geochemical tracers in the groundwater systems, leading us to conclude that faults act as fluid superhighways, connecting upper and lower aquifers that were once thought of as separated by impermeable layers," said Laura Crossey, lead author of the review paper. "These concepts have wide applications and generally have been underappreciated in other global arid-land groundwater systems."

In the case of the Colorado Plateau system, the concepts have significant and timely societal importance. The Pinyon Plain (formerly known as the Canyon) uranium mine, very close to the Park's South Rim Village, began extracting ore in January 2024. The tribes and environmental groups are protesting, and it seems the new "Ancestral Footsteps" National Monument does not protect against this, as the mine is "grandfathered in" having received prior approval.

"State and Federal permitting agencies should consider all the available science," said Karlstrom. "Tribes claim the permitting is ignoring recent peer-reviewed science and risks to culturally significant features."

This Annual Review paper is a timely summary of the science in which the authors favor abundant caution and no mining in this sensitive region due to the considerable risk of contamination of portions of the regional aquifer system, including the very susceptible Havasupai springs that supply Havasupai Village.

More information: L.J. Crossey et al, Hydrotectonics of Grand Canyon Groundwater, Annual Review of Earth and Planetary Sciences (2024). DOI: 10.1146/annurev-earth-080723-083513

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One Thing Most Countries Have in Common: Unsafe Air

New research found that fewer than 10 percent of countries and territories met World Health Organization guidelines for particulate matter pollution last year.

By Delger Erdenesanaa

Only 10 countries and territories out of 134 achieved the World Health Organization’s standards for a pervasive form of air pollution last year, according to air quality data compiled by IQAir , a Swiss company.

The pollution studied is called fine particulate matter, or PM2.5, because it refers to solid particles less than 2.5 micrometers in size: small enough to enter the bloodstream. PM2.5 is the deadliest form of air pollution, leading to millions of premature deaths each year .

“Air pollution and climate change both have the same culprit, which is fossil fuels,” said Glory Dolphin Hammes, the CEO of IQAir’s North American division.

The World Health Organization sets a guideline that people shouldn’t breathe more than 5 micrograms of fine particulate matter per cubic meter of air, on average, throughout a year. The U.S. Environmental Protection Agency recently proposed tightening its standard from 12 to 9 micrograms per cubic meter.

The few oases of clean air that meet World Health Organization guidelines are mostly islands, as well as Australia and the northern European countries of Finland and Estonia. Of the non-achievers, where the vast majority of the human population lives, the countries with the worst air quality were mostly in Asia and Africa.

Where some of the dirtiest air is found

The four most polluted countries in IQAir’s ranking for 2023 — Bangladesh, Pakistan, India and Tajikistan — are in South and Central Asia.

Air quality sensors in almost a third of the region’s cities reported concentrations of fine particulate matter that were more than 10 times the WHO guideline. This was a proportion “vastly exceeding any other region,” the report’s authors wrote.

The researchers pointed to vehicle traffic, coal and industrial emissions, particularly from brick kilns, as major sources of the region’s pollution. Farmers seasonally burning their crop waste contribute to the problem, as do households burning wood and dung for heat and cooking.

China reversed recent gains

One notable change in 2023 was a 6.3 percent increase in China’s air pollution compared with 2022, after at least five years of improvement. Beijing experienced a 14 percent increase in PM2.5 pollution last year.

The national government announced a “war against pollution” in 2014 and had been making progress ever since. But the sharpest decline in China’s PM2.5 pollution happened in 2020, when the coronavirus pandemic forced much of the country’s economic activity to slow or shut down. Ms. Dolphin Hammes attributed last year’s uptick to a reopening economy.

And challenges remain: Eleven cities in China reported air pollution levels last year that exceeded the WHO guidelines by 10 times or more. The worst was Hotan, Xinjiang.

Significant gaps in the data

IQAir researchers analyze data from more than 30,000 air quality monitoring stations and sensors across 134 countries, territories and disputed regions. Some of these monitoring stations are run by government agencies, while others are overseen by nonprofit organizations, schools, private companies and citizen scientists.

There are large gaps in ground-level air quality monitoring in Africa and the Middle East, including in regions where satellite data show some of the highest levels of air pollution on Earth.

As IQAir works to add data from more cities and countries in future years, “the worst might be yet to come in terms of what we’re measuring,” Ms. Dolphin Hammes said.

Wildfire smoke: a growing problem

Although North America is one of the cleaner regions in the world, in 2023 wildfires burned 4 percent of Canada’s forests, an area about half the size of Germany, and significantly impaired air quality.

Usually, North America’s list of most polluted cities is dominated by the United States. But last year, the top 13 spots all went to Canadian cities, many of them in Alberta.

In the United States, cities in the Upper Midwest and the Mid-Atlantic states also got significant amounts of PM2.5 pollution from wildfire smoke that drifted across the border.

Risks of short-term exposure

It’s not just chronic exposure to air pollution that harms people’s health.

For vulnerable people like the very young and old, or those with underlying illnesses, breathing in large amounts of fine particulate pollution for just a few hours or days can sometimes be deadly. About 1 million premature deaths per year can be attributed to short-term PM2.5 exposure, according to a recent global study published in The Lancet Planetary Health.

The problem is worst in East and South Asia, as well as in West Africa.

Without accounting for short-term exposures, “we might be underestimating the mortality burden from air pollution,” said Yuming Guo, a professor at Monash University in Melbourne, Australia, and one of the study’s authors.

U.S. disparities widen

Within individual countries, air pollution and its health effects aren’t evenly distributed.

Air quality in the United States has generally been improving since the Clean Air Act of the 1970s. Last decade, premature deaths from PM2.5 exposure declined to about 49,400 in 2019, down from about 69,000 in 2010.

But progress has happened faster in some communities than in others. Racial and ethnic disparities in air pollution deaths have grown in recent years, according to a national study published this month .

The census tracts in the United States with the fewest white residents have about 32 percent higher rates of PM2.5-related deaths, compared with those with the most white residents. This disparity in deaths per capita has increased by 16 percent between 2010 and 2019.

The study examined race and ethnicity separately, and found the disparity between the census tracts with the most and least Hispanic residents grew even more, by 40 percent.

In IQAir’s rankings, the United States is doing much better than most other countries. But studies that dig deeper show air quality is still an issue, said Gaige Kerr, a research scientist at George Washington University and the lead author of the disparities paper published in the journal Environmental Health Perspectives. “There’s still a lot of work to do,” he said.

Dr. Kerr’s research showed that mortality rates were highest on the Gulf Coast and in the Ohio River Valley, in areas dominated by petrochemical and manufacturing industries. He also noted that researchers have seen a slight uptick in rates of PM2.5-related deaths starting around 2016, particularly in the Western states, likely because of increasing wildfires.

Delger Erdenesanaa is a reporter covering climate and the environment and a member of the 2023-24 Times Fellowship class, a program for journalists early in their careers. More about Delger Erdenesanaa

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Title: improving vietnamese-english medical machine translation.

Abstract: Machine translation for Vietnamese-English in the medical domain is still an under-explored research area. In this paper, we introduce MedEV -- a high-quality Vietnamese-English parallel dataset constructed specifically for the medical domain, comprising approximately 360K sentence pairs. We conduct extensive experiments comparing Google Translate, ChatGPT (gpt-3.5-turbo), state-of-the-art Vietnamese-English neural machine translation models and pre-trained bilingual/multilingual sequence-to-sequence models on our new MedEV dataset. Experimental results show that the best performance is achieved by fine-tuning "vinai-translate" for each translation direction. We publicly release our dataset to promote further research.

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AI generates high-quality images 30 times faster in a single step

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In our current age of artificial intelligence, computers can generate their own “art” by way of diffusion models , iteratively adding structure to a noisy initial state until a clear image or video emerges. Diffusion models have suddenly grabbed a seat at everyone’s table: Enter a few words and experience instantaneous, dopamine-spiking dreamscapes at the intersection of reality and fantasy. Behind the scenes, it involves a complex, time-intensive process requiring numerous iterations for the algorithm to perfect the image.

MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have introduced a new framework that simplifies the multi-step process of traditional diffusion models into a single step, addressing previous limitations. This is done through a type of teacher-student model: teaching a new computer model to mimic the behavior of more complicated, original models that generate images. The approach, known as distribution matching distillation (DMD), retains the quality of the generated images and allows for much faster generation. 

“Our work is a novel method that accelerates current diffusion models such as Stable Diffusion and DALLE-3 by 30 times,” says Tianwei Yin, an MIT PhD student in electrical engineering and computer science, CSAIL affiliate, and the lead researcher on the DMD framework. “This advancement not only significantly reduces computational time but also retains, if not surpasses, the quality of the generated visual content. Theoretically, the approach marries the principles of generative adversarial networks (GANs) with those of diffusion models, achieving visual content generation in a single step — a stark contrast to the hundred steps of iterative refinement required by current diffusion models. It could potentially be a new generative modeling method that excels in speed and quality.”

This single-step diffusion model could enhance design tools, enabling quicker content creation and potentially supporting advancements in drug discovery and 3D modeling, where promptness and efficacy are key.

Distribution dreams

DMD cleverly has two components. First, it uses a regression loss, which anchors the mapping to ensure a coarse organization of the space of images to make training more stable. Next, it uses a distribution matching loss, which ensures that the probability to generate a given image with the student model corresponds to its real-world occurrence frequency. To do this, it leverages two diffusion models that act as guides, helping the system understand the difference between real and generated images and making training the speedy one-step generator possible.

The system achieves faster generation by training a new network to minimize the distribution divergence between its generated images and those from the training dataset used by traditional diffusion models. “Our key insight is to approximate gradients that guide the improvement of the new model using two diffusion models,” says Yin. “In this way, we distill the knowledge of the original, more complex model into the simpler, faster one, while bypassing the notorious instability and mode collapse issues in GANs.” 

Yin and colleagues used pre-trained networks for the new student model, simplifying the process. By copying and fine-tuning parameters from the original models, the team achieved fast training convergence of the new model, which is capable of producing high-quality images with the same architectural foundation. “This enables combining with other system optimizations based on the original architecture to further accelerate the creation process,” adds Yin. 

When put to the test against the usual methods, using a wide range of benchmarks, DMD showed consistent performance. On the popular benchmark of generating images based on specific classes on ImageNet, DMD is the first one-step diffusion technique that churns out pictures pretty much on par with those from the original, more complex models, rocking a super-close Fréchet inception distance (FID) score of just 0.3, which is impressive, since FID is all about judging the quality and diversity of generated images. Furthermore, DMD excels in industrial-scale text-to-image generation and achieves state-of-the-art one-step generation performance. There's still a slight quality gap when tackling trickier text-to-image applications, suggesting there's a bit of room for improvement down the line. 

Additionally, the performance of the DMD-generated images is intrinsically linked to the capabilities of the teacher model used during the distillation process. In the current form, which uses Stable Diffusion v1.5 as the teacher model, the student inherits limitations such as rendering detailed depictions of text and small faces, suggesting that DMD-generated images could be further enhanced by more advanced teacher models. 

“Decreasing the number of iterations has been the Holy Grail in diffusion models since their inception,” says Fredo Durand, MIT professor of electrical engineering and computer science, CSAIL principal investigator, and a lead author on the paper. “We are very excited to finally enable single-step image generation, which will dramatically reduce compute costs and accelerate the process.” 

“Finally, a paper that successfully combines the versatility and high visual quality of diffusion models with the real-time performance of GANs,” says Alexei Efros, a professor of electrical engineering and computer science at the University of California at Berkeley who was not involved in this study. “I expect this work to open up fantastic possibilities for high-quality real-time visual editing.” 

Yin and Durand’s fellow authors are MIT electrical engineering and computer science professor and CSAIL principal investigator William T. Freeman, as well as Adobe research scientists Michaël Gharbi SM '15, PhD '18; Richard Zhang; Eli Shechtman; and Taesung Park. Their work was supported, in part, by U.S. National Science Foundation grants (including one for the Institute for Artificial Intelligence and Fundamental Interactions), the Singapore Defense Science and Technology Agency, and by funding from Gwangju Institute of Science and Technology and Amazon. Their work will be presented at the Conference on Computer Vision and Pattern Recognition in June.

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